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| author | MridulS <mail@mriduls.com> | 2023-01-02 13:08:27 +0000 |
|---|---|---|
| committer | MridulS <mail@mriduls.com> | 2023-01-02 13:08:27 +0000 |
| commit | 0b9a02d6b3796e8ce4fed6cbce282fced15e486a (patch) | |
| tree | 8b48b18926291619367d4f9537892bd228bf7987 | |
| parent | 6ae99ab58d8b8ba50f66768c0f3aa4bb82b22196 (diff) | |
| download | networkx-0b9a02d6b3796e8ce4fed6cbce282fced15e486a.tar.gz | |
Deploying to gh-pages from @ networkx/networkx@71ad516a90c89c7294e32bf28e1f05c63c5f17e4 🚀
1708 files changed, 3812 insertions, 3811 deletions
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b/_images/tutorial-35.png diff --git a/_modules/index.html b/_modules/index.html index 515a25a6..abb4eb61 100644 --- a/_modules/index.html +++ b/_modules/index.html @@ -752,7 +752,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/approximation/clique.html b/_modules/networkx/algorithms/approximation/clique.html index 3efa43f5..2ecec5e1 100644 --- a/_modules/networkx/algorithms/approximation/clique.html +++ b/_modules/networkx/algorithms/approximation/clique.html @@ -477,7 +477,7 @@ <div class="viewcode-block" id="maximum_independent_set"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.clique.maximum_independent_set.html#networkx.algorithms.approximation.clique.maximum_independent_set">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">maximum_independent_set</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns an approximate maximum independent set.</span> +<span class="w"> </span><span class="sd">"""Returns an approximate maximum independent set.</span> <span class="sd"> Independent set or stable set is a set of vertices in a graph, no two of</span> <span class="sd"> which are adjacent. That is, it is a set I of vertices such that for every</span> @@ -527,7 +527,7 @@ <div class="viewcode-block" id="max_clique"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.clique.max_clique.html#networkx.algorithms.approximation.clique.max_clique">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">max_clique</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Find the Maximum Clique</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Find the Maximum Clique</span> <span class="sd"> Finds the $O(|V|/(log|V|)^2)$ apx of maximum clique/independent set</span> <span class="sd"> in the worst case.</span> @@ -582,7 +582,7 @@ <div class="viewcode-block" id="clique_removal"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.clique.clique_removal.html#networkx.algorithms.approximation.clique.clique_removal">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">clique_removal</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Repeatedly remove cliques from the graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Repeatedly remove cliques from the graph.</span> <span class="sd"> Results in a $O(|V|/(\log |V|)^2)$ approximation of maximum clique</span> <span class="sd"> and independent set. Returns the largest independent set found, along</span> @@ -628,7 +628,7 @@ <div class="viewcode-block" id="large_clique_size"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.clique.large_clique_size.html#networkx.algorithms.approximation.clique.large_clique_size">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">large_clique_size</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Find the size of a large clique in a graph.</span> +<span class="w"> </span><span class="sd">"""Find the size of a large clique in a graph.</span> <span class="sd"> A *clique* is a subset of nodes in which each pair of nodes is</span> <span class="sd"> adjacent. This function is a heuristic for finding the size of a</span> @@ -745,7 +745,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/approximation/clustering_coefficient.html b/_modules/networkx/algorithms/approximation/clustering_coefficient.html index 4f5e25a3..c494aa3f 100644 --- a/_modules/networkx/algorithms/approximation/clustering_coefficient.html +++ b/_modules/networkx/algorithms/approximation/clustering_coefficient.html @@ -469,7 +469,7 @@ <div class="viewcode-block" id="average_clustering"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.clustering_coefficient.average_clustering.html#networkx.algorithms.approximation.clustering_coefficient.average_clustering">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">average_clustering</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">trials</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Estimates the average clustering coefficient of G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Estimates the average clustering coefficient of G.</span> <span class="sd"> The local clustering of each node in `G` is the fraction of triangles</span> <span class="sd"> that actually exist over all possible triangles in its neighborhood.</span> @@ -576,7 +576,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/approximation/connectivity.html b/_modules/networkx/algorithms/approximation/connectivity.html index d43dc9b3..218de1e1 100644 --- a/_modules/networkx/algorithms/approximation/connectivity.html +++ b/_modules/networkx/algorithms/approximation/connectivity.html @@ -476,7 +476,7 @@ <div class="viewcode-block" id="local_node_connectivity"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.connectivity.local_node_connectivity.html#networkx.algorithms.approximation.connectivity.local_node_connectivity">[docs]</a><span class="k">def</span> <span class="nf">local_node_connectivity</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute node connectivity between source and target.</span> +<span class="w"> </span><span class="sd">"""Compute node connectivity between source and target.</span> <span class="sd"> Pairwise or local node connectivity between two distinct and nonadjacent</span> <span class="sd"> nodes is the minimum number of nodes that must be removed (minimum</span> @@ -571,7 +571,7 @@ <div class="viewcode-block" id="node_connectivity"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.connectivity.node_connectivity.html#networkx.algorithms.approximation.connectivity.node_connectivity">[docs]</a><span class="k">def</span> <span class="nf">node_connectivity</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">t</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns an approximation for node connectivity for a graph or digraph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns an approximation for node connectivity for a graph or digraph G.</span> <span class="sd"> Node connectivity is equal to the minimum number of nodes that</span> <span class="sd"> must be removed to disconnect G or render it trivial. By Menger's theorem,</span> @@ -676,7 +676,7 @@ <div class="viewcode-block" id="all_pairs_node_connectivity"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.connectivity.all_pairs_node_connectivity.html#networkx.algorithms.approximation.connectivity.all_pairs_node_connectivity">[docs]</a><span class="k">def</span> <span class="nf">all_pairs_node_connectivity</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nbunch</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute node connectivity between all pairs of nodes.</span> +<span class="w"> </span><span class="sd">"""Compute node connectivity between all pairs of nodes.</span> <span class="sd"> Pairwise or local node connectivity between two distinct and nonadjacent</span> <span class="sd"> nodes is the minimum number of nodes that must be removed (minimum</span> @@ -755,7 +755,7 @@ <span class="k">def</span> <span class="nf">_bidirectional_shortest_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">exclude</span><span class="p">):</span> - <span class="sd">"""Returns shortest path between source and target ignoring nodes in the</span> +<span class="w"> </span><span class="sd">"""Returns shortest path between source and target ignoring nodes in the</span> <span class="sd"> container 'exclude'.</span> <span class="sd"> Parameters</span> @@ -927,7 +927,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/approximation/distance_measures.html b/_modules/networkx/algorithms/approximation/distance_measures.html index 93f4e1b8..550b00be 100644 --- a/_modules/networkx/algorithms/approximation/distance_measures.html +++ b/_modules/networkx/algorithms/approximation/distance_measures.html @@ -471,7 +471,7 @@ <div class="viewcode-block" id="diameter"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.distance_measures.diameter.html#networkx.algorithms.approximation.distance_measures.diameter">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="k">def</span> <span class="nf">diameter</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a lower bound on the diameter of the graph G.</span> +<span class="w"> </span><span class="sd">"""Returns a lower bound on the diameter of the graph G.</span> <span class="sd"> The function computes a lower bound on the diameter (i.e., the maximum eccentricity)</span> <span class="sd"> of a directed or undirected graph G. The procedure used varies depending on the graph</span> @@ -538,7 +538,7 @@ <span class="k">def</span> <span class="nf">_two_sweep_undirected</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">seed</span><span class="p">):</span> - <span class="sd">"""Helper function for finding a lower bound on the diameter</span> +<span class="w"> </span><span class="sd">"""Helper function for finding a lower bound on the diameter</span> <span class="sd"> for undirected Graphs.</span> <span class="sd"> The idea is to pick the farthest node from a random node</span> @@ -564,7 +564,7 @@ <span class="k">def</span> <span class="nf">_two_sweep_directed</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">seed</span><span class="p">):</span> - <span class="sd">"""Helper function for finding a lower bound on the diameter</span> +<span class="w"> </span><span class="sd">"""Helper function for finding a lower bound on the diameter</span> <span class="sd"> for directed Graphs.</span> <span class="sd"> It implements 2-dSweep, the directed version of the 2-sweep algorithm.</span> @@ -652,7 +652,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/approximation/dominating_set.html b/_modules/networkx/algorithms/approximation/dominating_set.html index 6aeb086c..2a533abd 100644 --- a/_modules/networkx/algorithms/approximation/dominating_set.html +++ b/_modules/networkx/algorithms/approximation/dominating_set.html @@ -483,7 +483,7 @@ <span class="c1"># TODO Why doesn't this algorithm work for directed graphs?</span> <div class="viewcode-block" id="min_weighted_dominating_set"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.dominating_set.min_weighted_dominating_set.html#networkx.algorithms.approximation.dominating_set.min_weighted_dominating_set">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">min_weighted_dominating_set</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a dominating set that approximates the minimum weight node</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a dominating set that approximates the minimum weight node</span> <span class="sd"> dominating set.</span> <span class="sd"> Parameters</span> @@ -530,7 +530,7 @@ <span class="n">dom_set</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span> <span class="k">def</span> <span class="nf">_cost</span><span class="p">(</span><span class="n">node_and_neighborhood</span><span class="p">):</span> - <span class="sd">"""Returns the cost-effectiveness of greedily choosing the given</span> +<span class="w"> </span><span class="sd">"""Returns the cost-effectiveness of greedily choosing the given</span> <span class="sd"> node.</span> <span class="sd"> `node_and_neighborhood` is a two-tuple comprising a node and its</span> @@ -563,7 +563,7 @@ <div class="viewcode-block" id="min_edge_dominating_set"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.dominating_set.min_edge_dominating_set.html#networkx.algorithms.approximation.dominating_set.min_edge_dominating_set">[docs]</a><span class="k">def</span> <span class="nf">min_edge_dominating_set</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns minimum cardinality edge dominating set.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns minimum cardinality edge dominating set.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -635,7 +635,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/approximation/kcomponents.html b/_modules/networkx/algorithms/approximation/kcomponents.html index e0accb66..045c2762 100644 --- a/_modules/networkx/algorithms/approximation/kcomponents.html +++ b/_modules/networkx/algorithms/approximation/kcomponents.html @@ -478,7 +478,7 @@ <div class="viewcode-block" id="k_components"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.kcomponents.k_components.html#networkx.algorithms.approximation.kcomponents.k_components">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">k_components</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">min_density</span><span class="o">=</span><span class="mf">0.95</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the approximate k-component structure of a graph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the approximate k-component structure of a graph G.</span> <span class="sd"> A `k`-component is a maximal subgraph of a graph G that has, at least,</span> <span class="sd"> node connectivity `k`: we need to remove at least `k` nodes to break it</span> @@ -657,7 +657,7 @@ <span class="k">class</span> <span class="nc">_AntiGraph</span><span class="p">(</span><span class="n">nx</span><span class="o">.</span><span class="n">Graph</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Class for complement graphs.</span> <span class="sd"> The main goal is to be able to work with big and dense graphs with</span> @@ -678,7 +678,7 @@ <span class="n">edge_attr_dict_factory</span> <span class="o">=</span> <span class="n">single_edge_dict</span> <span class="c1"># type: ignore</span> <span class="k">def</span> <span class="fm">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span> - <span class="sd">"""Returns a dict of neighbors of node n in the dense graph.</span> +<span class="w"> </span><span class="sd">"""Returns a dict of neighbors of node n in the dense graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -697,7 +697,7 @@ <span class="p">}</span> <span class="k">def</span> <span class="nf">neighbors</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span> - <span class="sd">"""Returns an iterator over all neighbors of node n in the</span> +<span class="w"> </span><span class="sd">"""Returns an iterator over all neighbors of node n in the</span> <span class="sd"> dense graph.</span> <span class="sd"> """</span> <span class="k">try</span><span class="p">:</span> @@ -706,7 +706,7 @@ <span class="k">raise</span> <span class="n">NetworkXError</span><span class="p">(</span><span class="sa">f</span><span class="s2">"The node </span><span class="si">{</span><span class="n">n</span><span class="si">}</span><span class="s2"> is not in the graph."</span><span class="p">)</span> <span class="kn">from</span> <span class="nn">err</span> <span class="k">class</span> <span class="nc">AntiAtlasView</span><span class="p">(</span><span class="n">Mapping</span><span class="p">):</span> - <span class="sd">"""An adjacency inner dict for AntiGraph"""</span> +<span class="w"> </span><span class="sd">"""An adjacency inner dict for AntiGraph"""</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">graph</span><span class="p">,</span> <span class="n">node</span><span class="p">):</span> <span class="bp">self</span><span class="o">.</span><span class="n">_graph</span> <span class="o">=</span> <span class="n">graph</span> @@ -726,7 +726,7 @@ <span class="k">raise</span> <span class="ne">KeyError</span><span class="p">(</span><span class="n">nbr</span><span class="p">)</span> <span class="k">class</span> <span class="nc">AntiAdjacencyView</span><span class="p">(</span><span class="n">AntiAtlasView</span><span class="p">):</span> - <span class="sd">"""An adjacency outer dict for AntiGraph"""</span> +<span class="w"> </span><span class="sd">"""An adjacency outer dict for AntiGraph"""</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">graph</span><span class="p">):</span> <span class="bp">self</span><span class="o">.</span><span class="n">_graph</span> <span class="o">=</span> <span class="n">graph</span> @@ -748,7 +748,7 @@ <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">AntiAdjacencyView</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="k">def</span> <span class="nf">subgraph</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">nodes</span><span class="p">):</span> - <span class="sd">"""This subgraph method returns a full AntiGraph. Not a View"""</span> +<span class="w"> </span><span class="sd">"""This subgraph method returns a full AntiGraph. Not a View"""</span> <span class="n">nodes</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">nodes</span><span class="p">)</span> <span class="n">G</span> <span class="o">=</span> <span class="n">_AntiGraph</span><span class="p">()</span> <span class="n">G</span><span class="o">.</span><span class="n">add_nodes_from</span><span class="p">(</span><span class="n">nodes</span><span class="p">)</span> @@ -776,7 +776,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">degree</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns an iterator for (node, degree) and degree for single node.</span> +<span class="w"> </span><span class="sd">"""Returns an iterator for (node, degree) and degree for single node.</span> <span class="sd"> The node degree is the number of edges adjacent to the node.</span> @@ -814,7 +814,7 @@ <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">AntiDegreeView</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="k">def</span> <span class="nf">adjacency</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns an iterator of (node, adjacency set) tuples for all nodes</span> +<span class="w"> </span><span class="sd">"""Returns an iterator of (node, adjacency set) tuples for all nodes</span> <span class="sd"> in the dense graph.</span> <span class="sd"> This is the fastest way to look at every edge.</span> @@ -880,7 +880,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/approximation/matching.html b/_modules/networkx/algorithms/approximation/matching.html index df5e1d03..48d5f4de 100644 --- a/_modules/networkx/algorithms/approximation/matching.html +++ b/_modules/networkx/algorithms/approximation/matching.html @@ -477,7 +477,7 @@ <div class="viewcode-block" id="min_maximal_matching"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.matching.min_maximal_matching.html#networkx.algorithms.approximation.matching.min_maximal_matching">[docs]</a><span class="k">def</span> <span class="nf">min_maximal_matching</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the minimum maximal matching of G. That is, out of all maximal</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the minimum maximal matching of G. That is, out of all maximal</span> <span class="sd"> matchings of the graph G, the smallest is returned.</span> <span class="sd"> Parameters</span> @@ -554,7 +554,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/approximation/maxcut.html b/_modules/networkx/algorithms/approximation/maxcut.html index bf2a5a18..e7d40048 100644 --- a/_modules/networkx/algorithms/approximation/maxcut.html +++ b/_modules/networkx/algorithms/approximation/maxcut.html @@ -470,7 +470,7 @@ <div class="viewcode-block" id="randomized_partitioning"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.maxcut.randomized_partitioning.html#networkx.algorithms.approximation.maxcut.randomized_partitioning">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">,</span> <span class="s2">"multigraph"</span><span class="p">)</span> <span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="k">def</span> <span class="nf">randomized_partitioning</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute a random partitioning of the graph nodes and its cut value.</span> +<span class="w"> </span><span class="sd">"""Compute a random partitioning of the graph nodes and its cut value.</span> <span class="sd"> A partitioning is calculated by observing each node</span> <span class="sd"> and deciding to add it to the partition with probability `p`,</span> @@ -514,7 +514,7 @@ <div class="viewcode-block" id="one_exchange"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.maxcut.one_exchange.html#networkx.algorithms.approximation.maxcut.one_exchange">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">,</span> <span class="s2">"multigraph"</span><span class="p">)</span> <span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">one_exchange</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">initial_cut</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute a partitioning of the graphs nodes and the corresponding cut value.</span> +<span class="w"> </span><span class="sd">"""Compute a partitioning of the graphs nodes and the corresponding cut value.</span> <span class="sd"> Use a greedy one exchange strategy to find a locally maximal cut</span> <span class="sd"> and its value, it works by finding the best node (one that gives</span> @@ -623,7 +623,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/approximation/ramsey.html b/_modules/networkx/algorithms/approximation/ramsey.html index 58560989..bd83ea28 100644 --- a/_modules/networkx/algorithms/approximation/ramsey.html +++ b/_modules/networkx/algorithms/approximation/ramsey.html @@ -475,7 +475,7 @@ <div class="viewcode-block" id="ramsey_R2"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.ramsey.ramsey_R2.html#networkx.algorithms.approximation.ramsey.ramsey_R2">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">ramsey_R2</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the largest clique and largest independent set in `G`.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the largest clique and largest independent set in `G`.</span> <span class="sd"> This can be used to estimate bounds for the 2-color</span> <span class="sd"> Ramsey number `R(2;s,t)` for `G`.</span> @@ -563,7 +563,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/approximation/steinertree.html b/_modules/networkx/algorithms/approximation/steinertree.html index 4c7e01a8..270ca630 100644 --- a/_modules/networkx/algorithms/approximation/steinertree.html +++ b/_modules/networkx/algorithms/approximation/steinertree.html @@ -471,7 +471,7 @@ <div class="viewcode-block" id="metric_closure"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.steinertree.metric_closure.html#networkx.algorithms.approximation.steinertree.metric_closure">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">metric_closure</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Return the metric closure of a graph.</span> +<span class="w"> </span><span class="sd">"""Return the metric closure of a graph.</span> <span class="sd"> The metric closure of a graph *G* is the complete graph in which each edge</span> <span class="sd"> is weighted by the shortest path distance between the nodes in *G* .</span> @@ -589,7 +589,7 @@ <div class="viewcode-block" id="steiner_tree"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.steinertree.steiner_tree.html#networkx.algorithms.approximation.steinertree.steiner_tree">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">steiner_tree</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">terminal_nodes</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Return an approximation to the minimum Steiner tree of a graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Return an approximation to the minimum Steiner tree of a graph.</span> <span class="sd"> The minimum Steiner tree of `G` w.r.t a set of `terminal_nodes` (also *S*)</span> <span class="sd"> is a tree within `G` that spans those nodes and has minimum size (sum of</span> @@ -729,7 +729,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/approximation/traveling_salesman.html b/_modules/networkx/algorithms/approximation/traveling_salesman.html index 85de471c..e3c284cf 100644 --- a/_modules/networkx/algorithms/approximation/traveling_salesman.html +++ b/_modules/networkx/algorithms/approximation/traveling_salesman.html @@ -513,7 +513,7 @@ <span class="k">def</span> <span class="nf">swap_two_nodes</span><span class="p">(</span><span class="n">soln</span><span class="p">,</span> <span class="n">seed</span><span class="p">):</span> - <span class="sd">"""Swap two nodes in `soln` to give a neighbor solution.</span> +<span class="w"> </span><span class="sd">"""Swap two nodes in `soln` to give a neighbor solution.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -548,7 +548,7 @@ <span class="k">def</span> <span class="nf">move_one_node</span><span class="p">(</span><span class="n">soln</span><span class="p">,</span> <span class="n">seed</span><span class="p">):</span> - <span class="sd">"""Move one node to another position to give a neighbor solution.</span> +<span class="w"> </span><span class="sd">"""Move one node to another position to give a neighbor solution.</span> <span class="sd"> The node to move and the position to move to are chosen randomly.</span> <span class="sd"> The first and last nodes are left untouched as soln must be a cycle</span> @@ -588,7 +588,7 @@ <div class="viewcode-block" id="christofides"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.christofides.html#networkx.algorithms.approximation.traveling_salesman.christofides">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">christofides</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">tree</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Approximate a solution of the traveling salesman problem</span> +<span class="w"> </span><span class="sd">"""Approximate a solution of the traveling salesman problem</span> <span class="sd"> Compute a 3/2-approximation of the traveling salesman problem</span> <span class="sd"> in a complete undirected graph using Christofides [1]_ algorithm.</span> @@ -647,7 +647,7 @@ <span class="k">def</span> <span class="nf">_shortcutting</span><span class="p">(</span><span class="n">circuit</span><span class="p">):</span> - <span class="sd">"""Remove duplicate nodes in the path"""</span> +<span class="w"> </span><span class="sd">"""Remove duplicate nodes in the path"""</span> <span class="n">nodes</span> <span class="o">=</span> <span class="p">[]</span> <span class="k">for</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">circuit</span><span class="p">:</span> <span class="k">if</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">nodes</span><span class="p">:</span> @@ -660,7 +660,7 @@ <div class="viewcode-block" id="traveling_salesman_problem"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.traveling_salesman_problem.html#networkx.algorithms.approximation.traveling_salesman.traveling_salesman_problem">[docs]</a><span class="k">def</span> <span class="nf">traveling_salesman_problem</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cycle</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Find the shortest path in `G` connecting specified nodes</span> +<span class="w"> </span><span class="sd">"""Find the shortest path in `G` connecting specified nodes</span> <span class="sd"> This function allows approximate solution to the traveling salesman</span> <span class="sd"> problem on networks that are not complete graphs and/or where the</span> @@ -799,7 +799,7 @@ <div class="viewcode-block" id="asadpour_atsp"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.asadpour_atsp.html#networkx.algorithms.approximation.traveling_salesman.asadpour_atsp">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">asadpour_atsp</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns an approximate solution to the traveling salesman problem.</span> <span class="sd"> This approximate solution is one of the best known approximations for the</span> @@ -948,7 +948,7 @@ <span class="k">def</span> <span class="nf">held_karp_ascent</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Minimizes the Held-Karp relaxation of the TSP for `G`</span> <span class="sd"> Solves the Held-Karp relaxation of the input complete digraph and scales</span> @@ -996,7 +996,7 @@ <span class="kn">import</span> <span class="nn">scipy.optimize</span> <span class="k">as</span> <span class="nn">optimize</span> <span class="k">def</span> <span class="nf">k_pi</span><span class="p">():</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Find the set of minimum 1-Arborescences for G at point pi.</span> <span class="sd"> Returns</span> @@ -1080,7 +1080,7 @@ <span class="k">return</span> <span class="n">minimum_1_arborescences</span> <span class="k">def</span> <span class="nf">direction_of_ascent</span><span class="p">():</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Find the direction of ascent at point pi.</span> <span class="sd"> See [1]_ for more information.</span> @@ -1146,7 +1146,7 @@ <span class="c1"># 5. GO TO 2</span> <span class="k">def</span> <span class="nf">find_epsilon</span><span class="p">(</span><span class="n">k</span><span class="p">,</span> <span class="n">d</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Given the direction of ascent at pi, find the maximum distance we can go</span> <span class="sd"> in that direction.</span> @@ -1258,7 +1258,7 @@ <span class="k">def</span> <span class="nf">spanning_tree_distribution</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">z</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Find the asadpour exponential distribution of spanning trees.</span> <span class="sd"> Solves the Maximum Entropy Convex Program in the Asadpour algorithm [1]_</span> @@ -1289,7 +1289,7 @@ <span class="kn">from</span> <span class="nn">math</span> <span class="kn">import</span> <span class="n">log</span> <span class="k">as</span> <span class="n">ln</span> <span class="k">def</span> <span class="nf">q</span><span class="p">(</span><span class="n">e</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> The value of q(e) is described in the Asadpour paper is "the</span> <span class="sd"> probability that edge e will be included in a spanning tree T that is</span> <span class="sd"> chosen with probability proportional to exp(gamma(T))" which</span> @@ -1368,7 +1368,7 @@ <div class="viewcode-block" id="greedy_tsp"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.greedy_tsp.html#networkx.algorithms.approximation.traveling_salesman.greedy_tsp">[docs]</a><span class="k">def</span> <span class="nf">greedy_tsp</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Return a low cost cycle starting at `source` and its cost.</span> +<span class="w"> </span><span class="sd">"""Return a low cost cycle starting at `source` and its cost.</span> <span class="sd"> This approximates a solution to the traveling salesman problem.</span> <span class="sd"> It finds a cycle of all the nodes that a salesman can visit in order</span> @@ -1471,7 +1471,7 @@ <span class="n">alpha</span><span class="o">=</span><span class="mf">0.01</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns an approximate solution to the traveling salesman problem.</span> +<span class="w"> </span><span class="sd">"""Returns an approximate solution to the traveling salesman problem.</span> <span class="sd"> This function uses simulated annealing to approximate the minimal cost</span> <span class="sd"> cycle through the nodes. Starting from a suboptimal solution, simulated</span> @@ -1689,7 +1689,7 @@ <span class="n">alpha</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns an approximate solution to the traveling salesman problem.</span> +<span class="w"> </span><span class="sd">"""Returns an approximate solution to the traveling salesman problem.</span> <span class="sd"> This function uses threshold accepting methods to approximate the minimal cost</span> <span class="sd"> cycle through the nodes. Starting from a suboptimal solution, threshold</span> @@ -1946,7 +1946,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/approximation/treewidth.html b/_modules/networkx/algorithms/approximation/treewidth.html index 3d6a5a1a..025036ae 100644 --- a/_modules/networkx/algorithms/approximation/treewidth.html +++ b/_modules/networkx/algorithms/approximation/treewidth.html @@ -505,7 +505,7 @@ <div class="viewcode-block" id="treewidth_min_degree"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.treewidth.treewidth_min_degree.html#networkx.algorithms.approximation.treewidth.treewidth_min_degree">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">treewidth_min_degree</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns a treewidth decomposition using the Minimum Degree heuristic.</span> +<span class="w"> </span><span class="sd">"""Returns a treewidth decomposition using the Minimum Degree heuristic.</span> <span class="sd"> The heuristic chooses the nodes according to their degree, i.e., first</span> <span class="sd"> the node with the lowest degree is chosen, then the graph is updated</span> @@ -528,7 +528,7 @@ <div class="viewcode-block" id="treewidth_min_fill_in"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.treewidth.treewidth_min_fill_in.html#networkx.algorithms.approximation.treewidth.treewidth_min_fill_in">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">treewidth_min_fill_in</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns a treewidth decomposition using the Minimum Fill-in heuristic.</span> +<span class="w"> </span><span class="sd">"""Returns a treewidth decomposition using the Minimum Fill-in heuristic.</span> <span class="sd"> The heuristic chooses a node from the graph, where the number of edges</span> <span class="sd"> added turning the neighbourhood of the chosen node into clique is as</span> @@ -547,7 +547,7 @@ <span class="k">class</span> <span class="nc">MinDegreeHeuristic</span><span class="p">:</span> - <span class="sd">"""Implements the Minimum Degree heuristic.</span> +<span class="w"> </span><span class="sd">"""Implements the Minimum Degree heuristic.</span> <span class="sd"> The heuristic chooses the nodes according to their degree</span> <span class="sd"> (number of neighbours), i.e., first the node with the lowest degree is</span> @@ -594,7 +594,7 @@ <span class="k">def</span> <span class="nf">min_fill_in_heuristic</span><span class="p">(</span><span class="n">graph</span><span class="p">):</span> - <span class="sd">"""Implements the Minimum Degree heuristic.</span> +<span class="w"> </span><span class="sd">"""Implements the Minimum Degree heuristic.</span> <span class="sd"> Returns the node from the graph, where the number of edges added when</span> <span class="sd"> turning the neighbourhood of the chosen node into clique is as small as</span> @@ -639,7 +639,7 @@ <span class="k">def</span> <span class="nf">treewidth_decomp</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">heuristic</span><span class="o">=</span><span class="n">min_fill_in_heuristic</span><span class="p">):</span> - <span class="sd">"""Returns a treewidth decomposition using the passed heuristic.</span> +<span class="w"> </span><span class="sd">"""Returns a treewidth decomposition using the passed heuristic.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -761,7 +761,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/approximation/vertex_cover.html b/_modules/networkx/algorithms/approximation/vertex_cover.html index 6df1616f..fb5b7d8f 100644 --- a/_modules/networkx/algorithms/approximation/vertex_cover.html +++ b/_modules/networkx/algorithms/approximation/vertex_cover.html @@ -475,7 +475,7 @@ <div class="viewcode-block" id="min_weighted_vertex_cover"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.approximation.vertex_cover.min_weighted_vertex_cover.html#networkx.algorithms.approximation.vertex_cover.min_weighted_vertex_cover">[docs]</a><span class="k">def</span> <span class="nf">min_weighted_vertex_cover</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns an approximate minimum weighted vertex cover.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns an approximate minimum weighted vertex cover.</span> <span class="sd"> The set of nodes returned by this function is guaranteed to be a</span> <span class="sd"> vertex cover, and the total weight of the set is guaranteed to be at</span> @@ -592,7 +592,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/assortativity/connectivity.html b/_modules/networkx/algorithms/assortativity/connectivity.html index 01469c67..a9bab070 100644 --- a/_modules/networkx/algorithms/assortativity/connectivity.html +++ b/_modules/networkx/algorithms/assortativity/connectivity.html @@ -471,7 +471,7 @@ <div class="viewcode-block" id="average_degree_connectivity"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.assortativity.average_degree_connectivity.html#networkx.algorithms.assortativity.average_degree_connectivity">[docs]</a><span class="k">def</span> <span class="nf">average_degree_connectivity</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="s2">"in+out"</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="s2">"in+out"</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the average degree connectivity of graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the average degree connectivity of graph.</span> <span class="sd"> The average degree connectivity is the average nearest neighbor degree of</span> <span class="sd"> nodes with degree k. For weighted graphs, an analogous measure can</span> @@ -633,7 +633,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/assortativity/correlation.html b/_modules/networkx/algorithms/assortativity/correlation.html index 7082fdc9..b0b215ac 100644 --- a/_modules/networkx/algorithms/assortativity/correlation.html +++ b/_modules/networkx/algorithms/assortativity/correlation.html @@ -478,7 +478,7 @@ <div class="viewcode-block" id="degree_assortativity_coefficient"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.assortativity.degree_assortativity_coefficient.html#networkx.algorithms.assortativity.degree_assortativity_coefficient">[docs]</a><span class="k">def</span> <span class="nf">degree_assortativity_coefficient</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="s2">"out"</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="s2">"in"</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute degree assortativity of graph.</span> +<span class="w"> </span><span class="sd">"""Compute degree assortativity of graph.</span> <span class="sd"> Assortativity measures the similarity of connections</span> <span class="sd"> in the graph with respect to the node degree.</span> @@ -562,7 +562,7 @@ <div class="viewcode-block" id="degree_pearson_correlation_coefficient"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.assortativity.degree_pearson_correlation_coefficient.html#networkx.algorithms.assortativity.degree_pearson_correlation_coefficient">[docs]</a><span class="k">def</span> <span class="nf">degree_pearson_correlation_coefficient</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="s2">"out"</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="s2">"in"</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute degree assortativity of graph.</span> +<span class="w"> </span><span class="sd">"""Compute degree assortativity of graph.</span> <span class="sd"> Assortativity measures the similarity of connections</span> <span class="sd"> in the graph with respect to the node degree.</span> @@ -621,7 +621,7 @@ <div class="viewcode-block" id="attribute_assortativity_coefficient"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.assortativity.attribute_assortativity_coefficient.html#networkx.algorithms.assortativity.attribute_assortativity_coefficient">[docs]</a><span class="k">def</span> <span class="nf">attribute_assortativity_coefficient</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">attribute</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute assortativity for node attributes.</span> +<span class="w"> </span><span class="sd">"""Compute assortativity for node attributes.</span> <span class="sd"> Assortativity measures the similarity of connections</span> <span class="sd"> in the graph with respect to the given attribute.</span> @@ -667,7 +667,7 @@ <div class="viewcode-block" id="numeric_assortativity_coefficient"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.assortativity.numeric_assortativity_coefficient.html#networkx.algorithms.assortativity.numeric_assortativity_coefficient">[docs]</a><span class="k">def</span> <span class="nf">numeric_assortativity_coefficient</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">attribute</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute assortativity for numerical node attributes.</span> +<span class="w"> </span><span class="sd">"""Compute assortativity for numerical node attributes.</span> <span class="sd"> Assortativity measures the similarity of connections</span> <span class="sd"> in the graph with respect to the given numeric attribute.</span> @@ -716,7 +716,7 @@ <span class="k">def</span> <span class="nf">attribute_ac</span><span class="p">(</span><span class="n">M</span><span class="p">):</span> - <span class="sd">"""Compute assortativity for attribute matrix M.</span> +<span class="w"> </span><span class="sd">"""Compute assortativity for attribute matrix M.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -810,7 +810,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/assortativity/mixing.html b/_modules/networkx/algorithms/assortativity/mixing.html index 3a674dd1..181cf0f3 100644 --- a/_modules/networkx/algorithms/assortativity/mixing.html +++ b/_modules/networkx/algorithms/assortativity/mixing.html @@ -477,7 +477,7 @@ <div class="viewcode-block" id="attribute_mixing_dict"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.assortativity.attribute_mixing_dict.html#networkx.algorithms.assortativity.attribute_mixing_dict">[docs]</a><span class="k">def</span> <span class="nf">attribute_mixing_dict</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">attribute</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns dictionary representation of mixing matrix for attribute.</span> +<span class="w"> </span><span class="sd">"""Returns dictionary representation of mixing matrix for attribute.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -515,7 +515,7 @@ <div class="viewcode-block" id="attribute_mixing_matrix"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.assortativity.attribute_mixing_matrix.html#networkx.algorithms.assortativity.attribute_mixing_matrix">[docs]</a><span class="k">def</span> <span class="nf">attribute_mixing_matrix</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">attribute</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">mapping</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Returns mixing matrix for attribute.</span> +<span class="w"> </span><span class="sd">"""Returns mixing matrix for attribute.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -574,7 +574,7 @@ <div class="viewcode-block" id="degree_mixing_dict"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.assortativity.degree_mixing_dict.html#networkx.algorithms.assortativity.degree_mixing_dict">[docs]</a><span class="k">def</span> <span class="nf">degree_mixing_dict</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="s2">"out"</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="s2">"in"</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns dictionary representation of mixing matrix for degree.</span> +<span class="w"> </span><span class="sd">"""Returns dictionary representation of mixing matrix for degree.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -607,7 +607,7 @@ <div class="viewcode-block" id="degree_mixing_matrix"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.assortativity.degree_mixing_matrix.html#networkx.algorithms.assortativity.degree_mixing_matrix">[docs]</a><span class="k">def</span> <span class="nf">degree_mixing_matrix</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="s2">"out"</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="s2">"in"</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">mapping</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Returns mixing matrix for attribute.</span> +<span class="w"> </span><span class="sd">"""Returns mixing matrix for attribute.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -672,7 +672,7 @@ <div class="viewcode-block" id="mixing_dict"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.assortativity.mixing_dict.html#networkx.algorithms.assortativity.mixing_dict">[docs]</a><span class="k">def</span> <span class="nf">mixing_dict</span><span class="p">(</span><span class="n">xy</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns a dictionary representation of mixing matrix.</span> +<span class="w"> </span><span class="sd">"""Returns a dictionary representation of mixing matrix.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -757,7 +757,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/assortativity/neighbor_degree.html b/_modules/networkx/algorithms/assortativity/neighbor_degree.html index b4bf73d1..08f5bafa 100644 --- a/_modules/networkx/algorithms/assortativity/neighbor_degree.html +++ b/_modules/networkx/algorithms/assortativity/neighbor_degree.html @@ -467,7 +467,7 @@ <div class="viewcode-block" id="average_neighbor_degree"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.assortativity.average_neighbor_degree.html#networkx.algorithms.assortativity.average_neighbor_degree">[docs]</a><span class="k">def</span> <span class="nf">average_neighbor_degree</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="s2">"out"</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="s2">"out"</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the average degree of the neighborhood of each node.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the average degree of the neighborhood of each node.</span> <span class="sd"> In an undirected graph, the neighborhood `N(i)` of node `i` contains the</span> <span class="sd"> nodes that are connected to `i` by an edge.</span> @@ -671,7 +671,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/assortativity/pairs.html b/_modules/networkx/algorithms/assortativity/pairs.html index 808d1ccd..7690d519 100644 --- a/_modules/networkx/algorithms/assortativity/pairs.html +++ b/_modules/networkx/algorithms/assortativity/pairs.html @@ -466,7 +466,7 @@ <div class="viewcode-block" id="node_attribute_xy"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.assortativity.node_attribute_xy.html#networkx.algorithms.assortativity.node_attribute_xy">[docs]</a><span class="k">def</span> <span class="nf">node_attribute_xy</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">attribute</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns iterator of node-attribute pairs for all edges in G.</span> +<span class="w"> </span><span class="sd">"""Returns iterator of node-attribute pairs for all edges in G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -520,7 +520,7 @@ <div class="viewcode-block" id="node_degree_xy"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.assortativity.node_degree_xy.html#networkx.algorithms.assortativity.node_degree_xy">[docs]</a><span class="k">def</span> <span class="nf">node_degree_xy</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="s2">"out"</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="s2">"in"</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Generate node degree-degree pairs for edges in G.</span> +<span class="w"> </span><span class="sd">"""Generate node degree-degree pairs for edges in G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -626,7 +626,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/asteroidal.html b/_modules/networkx/algorithms/asteroidal.html index ef63c572..4bbc0066 100644 --- a/_modules/networkx/algorithms/asteroidal.html +++ b/_modules/networkx/algorithms/asteroidal.html @@ -482,7 +482,7 @@ <div class="viewcode-block" id="find_asteroidal_triple"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.asteroidal.find_asteroidal_triple.html#networkx.algorithms.asteroidal.find_asteroidal_triple">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">find_asteroidal_triple</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Find an asteroidal triple in the given graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Find an asteroidal triple in the given graph.</span> <span class="sd"> An asteroidal triple is a triple of non-adjacent vertices such that</span> <span class="sd"> there exists a path between any two of them which avoids the closed</span> @@ -554,7 +554,7 @@ <div class="viewcode-block" id="is_at_free"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.asteroidal.is_at_free.html#networkx.algorithms.asteroidal.is_at_free">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_at_free</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Check if a graph is AT-free.</span> +<span class="w"> </span><span class="sd">"""Check if a graph is AT-free.</span> <span class="sd"> The method uses the `find_asteroidal_triple` method to recognize</span> <span class="sd"> an AT-free graph. If no asteroidal triple is found the graph is</span> @@ -587,7 +587,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">create_component_structure</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Create component structure for G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Create component structure for G.</span> <span class="sd"> A *component structure* is an `nxn` array, denoted `c`, where `n` is</span> <span class="sd"> the number of vertices, where each row and column corresponds to a vertex.</span> @@ -679,7 +679,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/bipartite/basic.html b/_modules/networkx/algorithms/bipartite/basic.html index 2ea45d83..fa01367b 100644 --- a/_modules/networkx/algorithms/bipartite/basic.html +++ b/_modules/networkx/algorithms/bipartite/basic.html @@ -481,7 +481,7 @@ <div class="viewcode-block" id="color"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.basic.color.html#networkx.algorithms.bipartite.basic.color">[docs]</a><span class="k">def</span> <span class="nf">color</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns a two-coloring of the graph.</span> +<span class="w"> </span><span class="sd">"""Returns a two-coloring of the graph.</span> <span class="sd"> Raises an exception if the graph is not bipartite.</span> @@ -547,7 +547,7 @@ <div class="viewcode-block" id="is_bipartite"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.basic.is_bipartite.html#networkx.algorithms.bipartite.basic.is_bipartite">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">is_bipartite</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns True if graph G is bipartite, False if not.</span> +<span class="w"> </span><span class="sd">"""Returns True if graph G is bipartite, False if not.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -572,7 +572,7 @@ <div class="viewcode-block" id="is_bipartite_node_set"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.basic.is_bipartite_node_set.html#networkx.algorithms.bipartite.basic.is_bipartite_node_set">[docs]</a><span class="k">def</span> <span class="nf">is_bipartite_node_set</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="p">):</span> - <span class="sd">"""Returns True if nodes and G/nodes are a bipartition of G.</span> +<span class="w"> </span><span class="sd">"""Returns True if nodes and G/nodes are a bipartition of G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -616,7 +616,7 @@ <div class="viewcode-block" id="sets"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.basic.sets.html#networkx.algorithms.bipartite.basic.sets">[docs]</a><span class="k">def</span> <span class="nf">sets</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">top_nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns bipartite node sets of graph G.</span> +<span class="w"> </span><span class="sd">"""Returns bipartite node sets of graph G.</span> <span class="sd"> Raises an exception if the graph is not bipartite or if the input</span> <span class="sd"> graph is disconnected and thus more than one valid solution exists.</span> @@ -682,7 +682,7 @@ <div class="viewcode-block" id="density"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.basic.density.html#networkx.algorithms.bipartite.basic.density">[docs]</a><span class="k">def</span> <span class="nf">density</span><span class="p">(</span><span class="n">B</span><span class="p">,</span> <span class="n">nodes</span><span class="p">):</span> - <span class="sd">"""Returns density of bipartite graph B.</span> +<span class="w"> </span><span class="sd">"""Returns density of bipartite graph B.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -734,7 +734,7 @@ <div class="viewcode-block" id="degrees"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.basic.degrees.html#networkx.algorithms.bipartite.basic.degrees">[docs]</a><span class="k">def</span> <span class="nf">degrees</span><span class="p">(</span><span class="n">B</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the degrees of the two node sets in the bipartite graph B.</span> +<span class="w"> </span><span class="sd">"""Returns the degrees of the two node sets in the bipartite graph B.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -828,7 +828,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/bipartite/centrality.html b/_modules/networkx/algorithms/bipartite/centrality.html index 55aedd62..dc8ca164 100644 --- a/_modules/networkx/algorithms/bipartite/centrality.html +++ b/_modules/networkx/algorithms/bipartite/centrality.html @@ -467,7 +467,7 @@ <div class="viewcode-block" id="degree_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.centrality.degree_centrality.html#networkx.algorithms.bipartite.centrality.degree_centrality">[docs]</a><span class="k">def</span> <span class="nf">degree_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the degree centrality for nodes in a bipartite network.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the degree centrality for nodes in a bipartite network.</span> <span class="sd"> The degree centrality for a node `v` is the fraction of nodes</span> <span class="sd"> connected to it.</span> @@ -534,7 +534,7 @@ <div class="viewcode-block" id="betweenness_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.centrality.betweenness_centrality.html#networkx.algorithms.bipartite.centrality.betweenness_centrality">[docs]</a><span class="k">def</span> <span class="nf">betweenness_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute betweenness centrality for nodes in a bipartite network.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute betweenness centrality for nodes in a bipartite network.</span> <span class="sd"> Betweenness centrality of a node `v` is the sum of the</span> <span class="sd"> fraction of all-pairs shortest paths that pass through `v`.</span> @@ -630,7 +630,7 @@ <div class="viewcode-block" id="closeness_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.centrality.closeness_centrality.html#networkx.algorithms.bipartite.centrality.closeness_centrality">[docs]</a><span class="k">def</span> <span class="nf">closeness_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the closeness centrality for nodes in a bipartite network.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the closeness centrality for nodes in a bipartite network.</span> <span class="sd"> The closeness of a node is the distance to all other nodes in the</span> <span class="sd"> graph or in the case that the graph is not connected to all other nodes</span> @@ -778,7 +778,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/bipartite/cluster.html b/_modules/networkx/algorithms/bipartite/cluster.html index bb3a43b5..8c9687f5 100644 --- a/_modules/networkx/algorithms/bipartite/cluster.html +++ b/_modules/networkx/algorithms/bipartite/cluster.html @@ -493,7 +493,7 @@ <div class="viewcode-block" id="latapy_clustering"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.cluster.latapy_clustering.html#networkx.algorithms.bipartite.cluster.latapy_clustering">[docs]</a><span class="k">def</span> <span class="nf">latapy_clustering</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"dot"</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute a bipartite clustering coefficient for nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute a bipartite clustering coefficient for nodes.</span> <span class="sd"> The bipartie clustering coefficient is a measure of local density</span> <span class="sd"> of connections defined as [1]_:</span> @@ -597,7 +597,7 @@ <div class="viewcode-block" id="average_clustering"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.cluster.average_clustering.html#networkx.algorithms.bipartite.cluster.average_clustering">[docs]</a><span class="k">def</span> <span class="nf">average_clustering</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"dot"</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the average bipartite clustering coefficient.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the average bipartite clustering coefficient.</span> <span class="sd"> A clustering coefficient for the whole graph is the average,</span> @@ -673,7 +673,7 @@ <div class="viewcode-block" id="robins_alexander_clustering"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.cluster.robins_alexander_clustering.html#networkx.algorithms.bipartite.cluster.robins_alexander_clustering">[docs]</a><span class="k">def</span> <span class="nf">robins_alexander_clustering</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the bipartite clustering of G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the bipartite clustering of G.</span> <span class="sd"> Robins and Alexander [1]_ defined bipartite clustering coefficient as</span> <span class="sd"> four times the number of four cycles `C_4` divided by the number of</span> @@ -789,7 +789,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/bipartite/covering.html b/_modules/networkx/algorithms/bipartite/covering.html index ced1c691..5c11d584 100644 --- a/_modules/networkx/algorithms/bipartite/covering.html +++ b/_modules/networkx/algorithms/bipartite/covering.html @@ -473,7 +473,7 @@ <div class="viewcode-block" id="min_edge_cover"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.covering.min_edge_cover.html#networkx.algorithms.bipartite.covering.min_edge_cover">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">min_edge_cover</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">matching_algorithm</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a set of edges which constitutes</span> +<span class="w"> </span><span class="sd">"""Returns a set of edges which constitutes</span> <span class="sd"> the minimum edge cover of the graph.</span> <span class="sd"> The smallest edge cover can be found in polynomial time by finding</span> @@ -567,7 +567,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/bipartite/edgelist.html b/_modules/networkx/algorithms/bipartite/edgelist.html index bc5a4261..012ee0a2 100644 --- a/_modules/networkx/algorithms/bipartite/edgelist.html +++ b/_modules/networkx/algorithms/bipartite/edgelist.html @@ -493,7 +493,7 @@ <div class="viewcode-block" id="write_edgelist"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.write_edgelist.html#networkx.algorithms.bipartite.edgelist.write_edgelist">[docs]</a><span class="nd">@open_file</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"wb"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">write_edgelist</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">path</span><span class="p">,</span> <span class="n">comments</span><span class="o">=</span><span class="s2">"#"</span><span class="p">,</span> <span class="n">delimiter</span><span class="o">=</span><span class="s2">" "</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">):</span> - <span class="sd">"""Write a bipartite graph as a list of edges.</span> +<span class="w"> </span><span class="sd">"""Write a bipartite graph as a list of edges.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -543,7 +543,7 @@ <div class="viewcode-block" id="generate_edgelist"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.generate_edgelist.html#networkx.algorithms.bipartite.edgelist.generate_edgelist">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">generate_edgelist</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">delimiter</span><span class="o">=</span><span class="s2">" "</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Generate a single line of the bipartite graph G in edge list format.</span> +<span class="w"> </span><span class="sd">"""Generate a single line of the bipartite graph G in edge list format.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -612,7 +612,7 @@ <div class="viewcode-block" id="parse_edgelist"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.parse_edgelist.html#networkx.algorithms.bipartite.edgelist.parse_edgelist">[docs]</a><span class="k">def</span> <span class="nf">parse_edgelist</span><span class="p">(</span> <span class="n">lines</span><span class="p">,</span> <span class="n">comments</span><span class="o">=</span><span class="s2">"#"</span><span class="p">,</span> <span class="n">delimiter</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">nodetype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="kc">True</span> <span class="p">):</span> - <span class="sd">"""Parse lines of an edge list representation of a bipartite graph.</span> +<span class="w"> </span><span class="sd">"""Parse lines of an edge list representation of a bipartite graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -740,7 +740,7 @@ <span class="n">edgetype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Read a bipartite graph from a list of edges.</span> +<span class="w"> </span><span class="sd">"""Read a bipartite graph from a list of edges.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -869,7 +869,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/bipartite/generators.html b/_modules/networkx/algorithms/bipartite/generators.html index 7451cb06..b3cdb41c 100644 --- a/_modules/networkx/algorithms/bipartite/generators.html +++ b/_modules/networkx/algorithms/bipartite/generators.html @@ -485,7 +485,7 @@ <div class="viewcode-block" id="complete_bipartite_graph"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.generators.complete_bipartite_graph.html#networkx.algorithms.bipartite.generators.complete_bipartite_graph">[docs]</a><span class="nd">@nodes_or_number</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span> <span class="k">def</span> <span class="nf">complete_bipartite_graph</span><span class="p">(</span><span class="n">n1</span><span class="p">,</span> <span class="n">n2</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the complete bipartite graph `K_{n_1,n_2}`.</span> +<span class="w"> </span><span class="sd">"""Returns the complete bipartite graph `K_{n_1,n_2}`.</span> <span class="sd"> The graph is composed of two partitions with nodes 0 to (n1 - 1)</span> <span class="sd"> in the first and nodes n1 to (n1 + n2 - 1) in the second.</span> @@ -530,7 +530,7 @@ <div class="viewcode-block" id="configuration_model"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.generators.configuration_model.html#networkx.algorithms.bipartite.generators.configuration_model">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">configuration_model</span><span class="p">(</span><span class="n">aseq</span><span class="p">,</span> <span class="n">bseq</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a random bipartite graph from two given degree sequences.</span> +<span class="w"> </span><span class="sd">"""Returns a random bipartite graph from two given degree sequences.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -600,7 +600,7 @@ <div class="viewcode-block" id="havel_hakimi_graph"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.generators.havel_hakimi_graph.html#networkx.algorithms.bipartite.generators.havel_hakimi_graph">[docs]</a><span class="k">def</span> <span class="nf">havel_hakimi_graph</span><span class="p">(</span><span class="n">aseq</span><span class="p">,</span> <span class="n">bseq</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a bipartite graph from two given degree sequences using a</span> +<span class="w"> </span><span class="sd">"""Returns a bipartite graph from two given degree sequences using a</span> <span class="sd"> Havel-Hakimi style construction.</span> <span class="sd"> The graph is composed of two partitions. Set A has nodes 0 to</span> @@ -674,7 +674,7 @@ <div class="viewcode-block" id="reverse_havel_hakimi_graph"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.generators.reverse_havel_hakimi_graph.html#networkx.algorithms.bipartite.generators.reverse_havel_hakimi_graph">[docs]</a><span class="k">def</span> <span class="nf">reverse_havel_hakimi_graph</span><span class="p">(</span><span class="n">aseq</span><span class="p">,</span> <span class="n">bseq</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a bipartite graph from two given degree sequences using a</span> +<span class="w"> </span><span class="sd">"""Returns a bipartite graph from two given degree sequences using a</span> <span class="sd"> Havel-Hakimi style construction.</span> <span class="sd"> The graph is composed of two partitions. Set A has nodes 0 to</span> @@ -747,7 +747,7 @@ <div class="viewcode-block" id="alternating_havel_hakimi_graph"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.generators.alternating_havel_hakimi_graph.html#networkx.algorithms.bipartite.generators.alternating_havel_hakimi_graph">[docs]</a><span class="k">def</span> <span class="nf">alternating_havel_hakimi_graph</span><span class="p">(</span><span class="n">aseq</span><span class="p">,</span> <span class="n">bseq</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a bipartite graph from two given degree sequences using</span> +<span class="w"> </span><span class="sd">"""Returns a bipartite graph from two given degree sequences using</span> <span class="sd"> an alternating Havel-Hakimi style construction.</span> <span class="sd"> The graph is composed of two partitions. Set A has nodes 0 to</span> @@ -825,7 +825,7 @@ <div class="viewcode-block" id="preferential_attachment_graph"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.generators.preferential_attachment_graph.html#networkx.algorithms.bipartite.generators.preferential_attachment_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">preferential_attachment_graph</span><span class="p">(</span><span class="n">aseq</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Create a bipartite graph with a preferential attachment model from</span> +<span class="w"> </span><span class="sd">"""Create a bipartite graph with a preferential attachment model from</span> <span class="sd"> a given single degree sequence.</span> <span class="sd"> The graph is composed of two partitions. Set A has nodes 0 to</span> @@ -896,7 +896,7 @@ <div class="viewcode-block" id="random_graph"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.generators.random_graph.html#networkx.algorithms.bipartite.generators.random_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">directed</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns a bipartite random graph.</span> +<span class="w"> </span><span class="sd">"""Returns a bipartite random graph.</span> <span class="sd"> This is a bipartite version of the binomial (Erdős-Rényi) graph.</span> <span class="sd"> The graph is composed of two partitions. Set A has nodes 0 to</span> @@ -982,7 +982,7 @@ <div class="viewcode-block" id="gnmk_random_graph"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.generators.gnmk_random_graph.html#networkx.algorithms.bipartite.generators.gnmk_random_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">gnmk_random_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">directed</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns a random bipartite graph G_{n,m,k}.</span> +<span class="w"> </span><span class="sd">"""Returns a random bipartite graph G_{n,m,k}.</span> <span class="sd"> Produces a bipartite graph chosen randomly out of the set of all graphs</span> <span class="sd"> with n top nodes, m bottom nodes, and k edges.</span> @@ -1107,7 +1107,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/bipartite/matching.html b/_modules/networkx/algorithms/bipartite/matching.html index c389c45d..f3e29806 100644 --- a/_modules/networkx/algorithms/bipartite/matching.html +++ b/_modules/networkx/algorithms/bipartite/matching.html @@ -518,7 +518,7 @@ <div class="viewcode-block" id="hopcroft_karp_matching"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.matching.hopcroft_karp_matching.html#networkx.algorithms.bipartite.matching.hopcroft_karp_matching">[docs]</a><span class="k">def</span> <span class="nf">hopcroft_karp_matching</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">top_nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the maximum cardinality matching of the bipartite graph `G`.</span> +<span class="w"> </span><span class="sd">"""Returns the maximum cardinality matching of the bipartite graph `G`.</span> <span class="sd"> A matching is a set of edges that do not share any nodes. A maximum</span> <span class="sd"> cardinality matching is a matching with the most edges possible. It</span> @@ -643,7 +643,7 @@ <div class="viewcode-block" id="eppstein_matching"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.matching.eppstein_matching.html#networkx.algorithms.bipartite.matching.eppstein_matching">[docs]</a><span class="k">def</span> <span class="nf">eppstein_matching</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">top_nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the maximum cardinality matching of the bipartite graph `G`.</span> +<span class="w"> </span><span class="sd">"""Returns the maximum cardinality matching of the bipartite graph `G`.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -776,7 +776,7 @@ <span class="k">def</span> <span class="nf">_is_connected_by_alternating_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">matched_edges</span><span class="p">,</span> <span class="n">unmatched_edges</span><span class="p">,</span> <span class="n">targets</span><span class="p">):</span> - <span class="sd">"""Returns True if and only if the vertex `v` is connected to one of</span> +<span class="w"> </span><span class="sd">"""Returns True if and only if the vertex `v` is connected to one of</span> <span class="sd"> the target vertices by an alternating path in `G`.</span> <span class="sd"> An *alternating path* is a path in which every other edge is in the</span> @@ -799,7 +799,7 @@ <span class="sd"> """</span> <span class="k">def</span> <span class="nf">_alternating_dfs</span><span class="p">(</span><span class="n">u</span><span class="p">,</span> <span class="n">along_matched</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Returns True if and only if `u` is connected to one of the</span> +<span class="w"> </span><span class="sd">"""Returns True if and only if `u` is connected to one of the</span> <span class="sd"> targets by an alternating path.</span> <span class="sd"> `u` is a vertex in the graph `G`.</span> @@ -838,7 +838,7 @@ <span class="k">def</span> <span class="nf">_connected_by_alternating_paths</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">matching</span><span class="p">,</span> <span class="n">targets</span><span class="p">):</span> - <span class="sd">"""Returns the set of vertices that are connected to one of the target</span> +<span class="w"> </span><span class="sd">"""Returns the set of vertices that are connected to one of the target</span> <span class="sd"> vertices by an alternating path in `G` or are themselves a target.</span> <span class="sd"> An *alternating path* is a path in which every other edge is in the</span> @@ -876,7 +876,7 @@ <div class="viewcode-block" id="to_vertex_cover"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.matching.to_vertex_cover.html#networkx.algorithms.bipartite.matching.to_vertex_cover">[docs]</a><span class="k">def</span> <span class="nf">to_vertex_cover</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">matching</span><span class="p">,</span> <span class="n">top_nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the minimum vertex cover corresponding to the given maximum</span> +<span class="w"> </span><span class="sd">"""Returns the minimum vertex cover corresponding to the given maximum</span> <span class="sd"> matching of the bipartite graph `G`.</span> <span class="sd"> Parameters</span> @@ -956,7 +956,7 @@ <div class="viewcode-block" id="minimum_weight_full_matching"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.matching.minimum_weight_full_matching.html#networkx.algorithms.bipartite.matching.minimum_weight_full_matching">[docs]</a><span class="k">def</span> <span class="nf">minimum_weight_full_matching</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">top_nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a minimum weight full matching of the bipartite graph `G`.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a minimum weight full matching of the bipartite graph `G`.</span> <span class="sd"> Let :math:`G = ((U, V), E)` be a weighted bipartite graph with real weights</span> <span class="sd"> :math:`w : E \to \mathbb{R}`. This function then produces a matching</span> @@ -1091,7 +1091,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/bipartite/matrix.html b/_modules/networkx/algorithms/bipartite/matrix.html index 769bf14d..0c132da5 100644 --- a/_modules/networkx/algorithms/bipartite/matrix.html +++ b/_modules/networkx/algorithms/bipartite/matrix.html @@ -477,7 +477,7 @@ <div class="viewcode-block" id="biadjacency_matrix"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.matrix.biadjacency_matrix.html#networkx.algorithms.bipartite.matrix.biadjacency_matrix">[docs]</a><span class="k">def</span> <span class="nf">biadjacency_matrix</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">row_order</span><span class="p">,</span> <span class="n">column_order</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="nb">format</span><span class="o">=</span><span class="s2">"csr"</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the biadjacency matrix of the bipartite graph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the biadjacency matrix of the bipartite graph G.</span> <span class="sd"> Let `G = (U, V, E)` be a bipartite graph with node sets</span> <span class="sd"> `U = u_{1},...,u_{r}` and `V = v_{1},...,v_{s}`. The biadjacency</span> @@ -574,7 +574,7 @@ <div class="viewcode-block" id="from_biadjacency_matrix"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.matrix.from_biadjacency_matrix.html#networkx.algorithms.bipartite.matrix.from_biadjacency_matrix">[docs]</a><span class="k">def</span> <span class="nf">from_biadjacency_matrix</span><span class="p">(</span><span class="n">A</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">edge_attribute</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Creates a new bipartite graph from a biadjacency matrix given as a</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Creates a new bipartite graph from a biadjacency matrix given as a</span> <span class="sd"> SciPy sparse array.</span> <span class="sd"> Parameters</span> @@ -678,7 +678,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/bipartite/projection.html b/_modules/networkx/algorithms/bipartite/projection.html index 0e7a1d1c..657548a1 100644 --- a/_modules/networkx/algorithms/bipartite/projection.html +++ b/_modules/networkx/algorithms/bipartite/projection.html @@ -476,7 +476,7 @@ <div class="viewcode-block" id="projected_graph"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.projection.projected_graph.html#networkx.algorithms.bipartite.projection.projected_graph">[docs]</a><span class="k">def</span> <span class="nf">projected_graph</span><span class="p">(</span><span class="n">B</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">multigraph</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the projection of B onto one of its node sets.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the projection of B onto one of its node sets.</span> <span class="sd"> Returns the graph G that is the projection of the bipartite graph B</span> <span class="sd"> onto the specified nodes. They retain their attributes and are connected</span> @@ -580,7 +580,7 @@ <div class="viewcode-block" id="weighted_projected_graph"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.projection.weighted_projected_graph.html#networkx.algorithms.bipartite.projection.weighted_projected_graph">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">weighted_projected_graph</span><span class="p">(</span><span class="n">B</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">ratio</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a weighted projection of B onto one of its node sets.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a weighted projection of B onto one of its node sets.</span> <span class="sd"> The weighted projected graph is the projection of the bipartite</span> <span class="sd"> network B onto the specified nodes with weights representing the</span> @@ -680,7 +680,7 @@ <div class="viewcode-block" id="collaboration_weighted_projected_graph"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.projection.collaboration_weighted_projected_graph.html#networkx.algorithms.bipartite.projection.collaboration_weighted_projected_graph">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">collaboration_weighted_projected_graph</span><span class="p">(</span><span class="n">B</span><span class="p">,</span> <span class="n">nodes</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Newman's weighted projection of B onto one of its node sets.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Newman's weighted projection of B onto one of its node sets.</span> <span class="sd"> The collaboration weighted projection is the projection of the</span> <span class="sd"> bipartite network B onto the specified nodes with weights assigned</span> @@ -774,7 +774,7 @@ <div class="viewcode-block" id="overlap_weighted_projected_graph"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.projection.overlap_weighted_projected_graph.html#networkx.algorithms.bipartite.projection.overlap_weighted_projected_graph">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">overlap_weighted_projected_graph</span><span class="p">(</span><span class="n">B</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">jaccard</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Overlap weighted projection of B onto one of its node sets.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Overlap weighted projection of B onto one of its node sets.</span> <span class="sd"> The overlap weighted projection is the projection of the bipartite</span> <span class="sd"> network B onto the specified nodes with weights representing</span> @@ -873,7 +873,7 @@ <div class="viewcode-block" id="generic_weighted_projected_graph"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.projection.generic_weighted_projected_graph.html#networkx.algorithms.bipartite.projection.generic_weighted_projected_graph">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">generic_weighted_projected_graph</span><span class="p">(</span><span class="n">B</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">weight_function</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Weighted projection of B with a user-specified weight function.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Weighted projection of B with a user-specified weight function.</span> <span class="sd"> The bipartite network B is projected on to the specified nodes</span> <span class="sd"> with weights computed by a user-specified function. This function</span> @@ -1035,7 +1035,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/bipartite/redundancy.html b/_modules/networkx/algorithms/bipartite/redundancy.html index e2ac8668..325e602a 100644 --- a/_modules/networkx/algorithms/bipartite/redundancy.html +++ b/_modules/networkx/algorithms/bipartite/redundancy.html @@ -470,7 +470,7 @@ <div class="viewcode-block" id="node_redundancy"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.redundancy.node_redundancy.html#networkx.algorithms.bipartite.redundancy.node_redundancy">[docs]</a><span class="k">def</span> <span class="nf">node_redundancy</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Computes the node redundancy coefficients for the nodes in the bipartite</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Computes the node redundancy coefficients for the nodes in the bipartite</span> <span class="sd"> graph `G`.</span> <span class="sd"> The redundancy coefficient of a node `v` is the fraction of pairs of</span> @@ -555,7 +555,7 @@ <span class="k">def</span> <span class="nf">_node_redundancy</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Returns the redundancy of the node `v` in the bipartite graph `G`.</span> +<span class="w"> </span><span class="sd">"""Returns the redundancy of the node `v` in the bipartite graph `G`.</span> <span class="sd"> If `G` is a graph with `n` nodes, the redundancy of a node is the ratio</span> <span class="sd"> of the "overlap" of `v` to the maximum possible overlap of `v`</span> @@ -621,7 +621,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/bipartite/spectral.html b/_modules/networkx/algorithms/bipartite/spectral.html index 4a6bea15..d3693f38 100644 --- a/_modules/networkx/algorithms/bipartite/spectral.html +++ b/_modules/networkx/algorithms/bipartite/spectral.html @@ -470,7 +470,7 @@ <div class="viewcode-block" id="spectral_bipartivity"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.bipartite.spectral.spectral_bipartivity.html#networkx.algorithms.bipartite.spectral.spectral_bipartivity">[docs]</a><span class="k">def</span> <span class="nf">spectral_bipartivity</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns the spectral bipartivity.</span> +<span class="w"> </span><span class="sd">"""Returns the spectral bipartivity.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -580,7 +580,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/boundary.html b/_modules/networkx/algorithms/boundary.html index 73147d46..20e3d891 100644 --- a/_modules/networkx/algorithms/boundary.html +++ b/_modules/networkx/algorithms/boundary.html @@ -480,7 +480,7 @@ <div class="viewcode-block" id="edge_boundary"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.boundary.edge_boundary.html#networkx.algorithms.boundary.edge_boundary">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">edge_boundary</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nbunch1</span><span class="p">,</span> <span class="n">nbunch2</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">keys</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the edge boundary of `nbunch1`.</span> +<span class="w"> </span><span class="sd">"""Returns the edge boundary of `nbunch1`.</span> <span class="sd"> The *edge boundary* of a set *S* with respect to a set *T* is the</span> <span class="sd"> set of edges (*u*, *v*) such that *u* is in *S* and *v* is in *T*.</span> @@ -557,7 +557,7 @@ <div class="viewcode-block" id="node_boundary"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.boundary.node_boundary.html#networkx.algorithms.boundary.node_boundary">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span><span class="p">()</span> <span class="k">def</span> <span class="nf">node_boundary</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nbunch1</span><span class="p">,</span> <span class="n">nbunch2</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the node boundary of `nbunch1`.</span> +<span class="w"> </span><span class="sd">"""Returns the node boundary of `nbunch1`.</span> <span class="sd"> The *node boundary* of a set *S* with respect to a set *T* is the</span> <span class="sd"> set of nodes *v* in *T* such that for some *u* in *S*, there is an</span> @@ -651,7 +651,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/bridges.html b/_modules/networkx/algorithms/bridges.html index 8eb952a4..9daee3f1 100644 --- a/_modules/networkx/algorithms/bridges.html +++ b/_modules/networkx/algorithms/bridges.html @@ -472,7 +472,7 @@ <div class="viewcode-block" id="bridges"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.bridges.bridges.html#networkx.algorithms.bridges.bridges">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">bridges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">root</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Generate all bridges in a graph.</span> +<span class="w"> </span><span class="sd">"""Generate all bridges in a graph.</span> <span class="sd"> A *bridge* in a graph is an edge whose removal causes the number of</span> <span class="sd"> connected components of the graph to increase. Equivalently, a bridge is an</span> @@ -544,7 +544,7 @@ <div class="viewcode-block" id="has_bridges"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.bridges.has_bridges.html#networkx.algorithms.bridges.has_bridges">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">has_bridges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">root</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Decide whether a graph has any bridges.</span> +<span class="w"> </span><span class="sd">"""Decide whether a graph has any bridges.</span> <span class="sd"> A *bridge* in a graph is an edge whose removal causes the number of</span> <span class="sd"> connected components of the graph to increase.</span> @@ -604,7 +604,7 @@ <div class="viewcode-block" id="local_bridges"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.bridges.local_bridges.html#networkx.algorithms.bridges.local_bridges">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">local_bridges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">with_span</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Iterate over local bridges of `G` optionally computing the span</span> +<span class="w"> </span><span class="sd">"""Iterate over local bridges of `G` optionally computing the span</span> <span class="sd"> A *local bridge* is an edge whose endpoints have no common neighbors.</span> <span class="sd"> That is, the edge is not part of a triangle in the graph.</span> @@ -714,7 +714,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/betweenness.html b/_modules/networkx/algorithms/centrality/betweenness.html index 03beade9..a9474c72 100644 --- a/_modules/networkx/algorithms/centrality/betweenness.html +++ b/_modules/networkx/algorithms/centrality/betweenness.html @@ -479,7 +479,7 @@ <span class="k">def</span> <span class="nf">betweenness_centrality</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">endpoints</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the shortest-path betweenness centrality for nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the shortest-path betweenness centrality for nodes.</span> <span class="sd"> Betweenness centrality of a node $v$ is the sum of the</span> <span class="sd"> fraction of all-pairs shortest paths that pass through $v$</span> @@ -614,7 +614,7 @@ <div class="viewcode-block" id="edge_betweenness_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.edge_betweenness_centrality.html#networkx.algorithms.centrality.edge_betweenness_centrality">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="k">def</span> <span class="nf">edge_betweenness_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute betweenness centrality for edges.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute betweenness centrality for edges.</span> <span class="sd"> Betweenness centrality of an edge $e$ is the sum of the</span> <span class="sd"> fraction of all-pairs shortest paths that pass through $e$</span> @@ -859,7 +859,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"graph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">_add_edge_keys</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">betweenness</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Adds the corrected betweenness centrality (BC) values for multigraphs.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Adds the corrected betweenness centrality (BC) values for multigraphs.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -942,7 +942,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/betweenness_subset.html b/_modules/networkx/algorithms/centrality/betweenness_subset.html index faa70b64..60b79a6d 100644 --- a/_modules/networkx/algorithms/centrality/betweenness_subset.html +++ b/_modules/networkx/algorithms/centrality/betweenness_subset.html @@ -477,7 +477,7 @@ <div class="viewcode-block" id="betweenness_centrality_subset"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.betweenness_centrality_subset.html#networkx.algorithms.centrality.betweenness_centrality_subset">[docs]</a><span class="k">def</span> <span class="nf">betweenness_centrality_subset</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">sources</span><span class="p">,</span> <span class="n">targets</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute betweenness centrality for a subset of nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute betweenness centrality for a subset of nodes.</span> <span class="sd"> .. math::</span> @@ -576,7 +576,7 @@ <div class="viewcode-block" id="edge_betweenness_centrality_subset"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.edge_betweenness_centrality_subset.html#networkx.algorithms.centrality.edge_betweenness_centrality_subset">[docs]</a><span class="k">def</span> <span class="nf">edge_betweenness_centrality_subset</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">sources</span><span class="p">,</span> <span class="n">targets</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute betweenness centrality for edges for a subset of nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute betweenness centrality for edges for a subset of nodes.</span> <span class="sd"> .. math::</span> @@ -676,7 +676,7 @@ <span class="k">def</span> <span class="nf">_accumulate_edges_subset</span><span class="p">(</span><span class="n">betweenness</span><span class="p">,</span> <span class="n">S</span><span class="p">,</span> <span class="n">P</span><span class="p">,</span> <span class="n">sigma</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">targets</span><span class="p">):</span> - <span class="sd">"""edge_betweenness_centrality_subset helper."""</span> +<span class="w"> </span><span class="sd">"""edge_betweenness_centrality_subset helper."""</span> <span class="n">delta</span> <span class="o">=</span> <span class="nb">dict</span><span class="o">.</span><span class="n">fromkeys</span><span class="p">(</span><span class="n">S</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span> <span class="n">target_set</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">targets</span><span class="p">)</span> <span class="k">while</span> <span class="n">S</span><span class="p">:</span> @@ -697,7 +697,7 @@ <span class="k">def</span> <span class="nf">_rescale</span><span class="p">(</span><span class="n">betweenness</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">normalized</span><span class="p">,</span> <span class="n">directed</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""betweenness_centrality_subset helper."""</span> +<span class="w"> </span><span class="sd">"""betweenness_centrality_subset helper."""</span> <span class="k">if</span> <span class="n">normalized</span><span class="p">:</span> <span class="k">if</span> <span class="n">n</span> <span class="o"><=</span> <span class="mi">2</span><span class="p">:</span> <span class="n">scale</span> <span class="o">=</span> <span class="kc">None</span> <span class="c1"># no normalization b=0 for all nodes</span> @@ -715,7 +715,7 @@ <span class="k">def</span> <span class="nf">_rescale_e</span><span class="p">(</span><span class="n">betweenness</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">normalized</span><span class="p">,</span> <span class="n">directed</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""edge_betweenness_centrality_subset helper."""</span> +<span class="w"> </span><span class="sd">"""edge_betweenness_centrality_subset helper."""</span> <span class="k">if</span> <span class="n">normalized</span><span class="p">:</span> <span class="k">if</span> <span class="n">n</span> <span class="o"><=</span> <span class="mi">1</span><span class="p">:</span> <span class="n">scale</span> <span class="o">=</span> <span class="kc">None</span> <span class="c1"># no normalization b=0 for all nodes</span> @@ -781,7 +781,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/closeness.html b/_modules/networkx/algorithms/centrality/closeness.html index 5d2b9511..6dec3eaa 100644 --- a/_modules/networkx/algorithms/centrality/closeness.html +++ b/_modules/networkx/algorithms/centrality/closeness.html @@ -474,7 +474,7 @@ <div class="viewcode-block" id="closeness_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.closeness_centrality.html#networkx.algorithms.centrality.closeness_centrality">[docs]</a><span class="k">def</span> <span class="nf">closeness_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">u</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">distance</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">wf_improved</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute closeness centrality for nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute closeness centrality for nodes.</span> <span class="sd"> Closeness centrality [1]_ of a node `u` is the reciprocal of the</span> <span class="sd"> average shortest path distance to `u` over all `n-1` reachable nodes.</span> @@ -602,7 +602,7 @@ <span class="k">def</span> <span class="nf">incremental_closeness_centrality</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">edge</span><span class="p">,</span> <span class="n">prev_cc</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">insertion</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">wf_improved</span><span class="o">=</span><span class="kc">True</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Incremental closeness centrality for nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Incremental closeness centrality for nodes.</span> <span class="sd"> Compute closeness centrality for nodes using level-based work filtering</span> <span class="sd"> as described in Incremental Algorithms for Closeness Centrality by Sariyuce et al.</span> @@ -791,7 +791,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/current_flow_betweenness.html b/_modules/networkx/algorithms/centrality/current_flow_betweenness.html index 9f829d5c..03b9bad5 100644 --- a/_modules/networkx/algorithms/centrality/current_flow_betweenness.html +++ b/_modules/networkx/algorithms/centrality/current_flow_betweenness.html @@ -494,7 +494,7 @@ <span class="n">kmax</span><span class="o">=</span><span class="mi">10000</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the approximate current-flow betweenness centrality for nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the approximate current-flow betweenness centrality for nodes.</span> <span class="sd"> Approximates the current-flow betweenness centrality within absolute</span> <span class="sd"> error of epsilon with high probability [1]_.</span> @@ -609,7 +609,7 @@ <span class="k">def</span> <span class="nf">current_flow_betweenness_centrality</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">float</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s2">"full"</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute current-flow betweenness centrality for nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute current-flow betweenness centrality for nodes.</span> <span class="sd"> Current-flow betweenness centrality uses an electrical current</span> <span class="sd"> model for information spreading in contrast to betweenness</span> @@ -705,7 +705,7 @@ <span class="k">def</span> <span class="nf">edge_current_flow_betweenness_centrality</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">float</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s2">"full"</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute current-flow betweenness centrality for edges.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute current-flow betweenness centrality for edges.</span> <span class="sd"> Current-flow betweenness centrality uses an electrical current</span> <span class="sd"> model for information spreading in contrast to betweenness</span> @@ -852,7 +852,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/current_flow_betweenness_subset.html b/_modules/networkx/algorithms/centrality/current_flow_betweenness_subset.html index 683fbf63..61eb3e7a 100644 --- a/_modules/networkx/algorithms/centrality/current_flow_betweenness_subset.html +++ b/_modules/networkx/algorithms/centrality/current_flow_betweenness_subset.html @@ -476,7 +476,7 @@ <span class="k">def</span> <span class="nf">current_flow_betweenness_centrality_subset</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">sources</span><span class="p">,</span> <span class="n">targets</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">float</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s2">"lu"</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute current-flow betweenness centrality for subsets of nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute current-flow betweenness centrality for subsets of nodes.</span> <span class="sd"> Current-flow betweenness centrality uses an electrical current</span> <span class="sd"> model for information spreading in contrast to betweenness</span> @@ -585,7 +585,7 @@ <span class="k">def</span> <span class="nf">edge_current_flow_betweenness_centrality_subset</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">sources</span><span class="p">,</span> <span class="n">targets</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">float</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s2">"lu"</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute current-flow betweenness centrality for edges using subsets</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute current-flow betweenness centrality for edges using subsets</span> <span class="sd"> of nodes.</span> <span class="sd"> Current-flow betweenness centrality uses an electrical current</span> @@ -736,7 +736,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/current_flow_closeness.html b/_modules/networkx/algorithms/centrality/current_flow_closeness.html index 73fd1859..abcee6a3 100644 --- a/_modules/networkx/algorithms/centrality/current_flow_closeness.html +++ b/_modules/networkx/algorithms/centrality/current_flow_closeness.html @@ -475,7 +475,7 @@ <div class="viewcode-block" id="current_flow_closeness_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.current_flow_closeness_centrality.html#networkx.algorithms.centrality.current_flow_closeness_centrality">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">current_flow_closeness_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">float</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s2">"lu"</span><span class="p">):</span> - <span class="sd">"""Compute current-flow closeness centrality for nodes.</span> +<span class="w"> </span><span class="sd">"""Compute current-flow closeness centrality for nodes.</span> <span class="sd"> Current-flow closeness centrality is variant of closeness</span> <span class="sd"> centrality based on effective resistance between nodes in</span> @@ -608,7 +608,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/degree_alg.html b/_modules/networkx/algorithms/centrality/degree_alg.html index d8de0bba..b6b2850a 100644 --- a/_modules/networkx/algorithms/centrality/degree_alg.html +++ b/_modules/networkx/algorithms/centrality/degree_alg.html @@ -470,7 +470,7 @@ <div class="viewcode-block" id="degree_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.degree_centrality.html#networkx.algorithms.centrality.degree_centrality">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">degree_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Compute the degree centrality for nodes.</span> +<span class="w"> </span><span class="sd">"""Compute the degree centrality for nodes.</span> <span class="sd"> The degree centrality for a node v is the fraction of nodes it</span> <span class="sd"> is connected to.</span> @@ -515,7 +515,7 @@ <div class="viewcode-block" id="in_degree_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.in_degree_centrality.html#networkx.algorithms.centrality.in_degree_centrality">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">in_degree_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Compute the in-degree centrality for nodes.</span> +<span class="w"> </span><span class="sd">"""Compute the in-degree centrality for nodes.</span> <span class="sd"> The in-degree centrality for a node v is the fraction of nodes its</span> <span class="sd"> incoming edges are connected to.</span> @@ -565,7 +565,7 @@ <div class="viewcode-block" id="out_degree_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.out_degree_centrality.html#networkx.algorithms.centrality.out_degree_centrality">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">out_degree_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Compute the out-degree centrality for nodes.</span> +<span class="w"> </span><span class="sd">"""Compute the out-degree centrality for nodes.</span> <span class="sd"> The out-degree centrality for a node v is the fraction of nodes its</span> <span class="sd"> outgoing edges are connected to.</span> @@ -661,7 +661,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/dispersion.html b/_modules/networkx/algorithms/centrality/dispersion.html index 86bd35b4..9149c300 100644 --- a/_modules/networkx/algorithms/centrality/dispersion.html +++ b/_modules/networkx/algorithms/centrality/dispersion.html @@ -467,7 +467,7 @@ <div class="viewcode-block" id="dispersion"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.dispersion.html#networkx.algorithms.centrality.dispersion">[docs]</a><span class="k">def</span> <span class="nf">dispersion</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">u</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">v</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">b</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">c</span><span class="o">=</span><span class="mf">0.0</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Calculate dispersion between `u` and `v` in `G`.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Calculate dispersion between `u` and `v` in `G`.</span> <span class="sd"> A link between two actors (`u` and `v`) has a high dispersion when their</span> <span class="sd"> mutual ties (`s` and `t`) are not well connected with each other.</span> @@ -515,7 +515,7 @@ <span class="sd"> """</span> <span class="k">def</span> <span class="nf">_dispersion</span><span class="p">(</span><span class="n">G_u</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""dispersion for all nodes 'v' in a ego network G_u of node 'u'"""</span> +<span class="w"> </span><span class="sd">"""dispersion for all nodes 'v' in a ego network G_u of node 'u'"""</span> <span class="n">u_nbrs</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">G_u</span><span class="p">[</span><span class="n">u</span><span class="p">])</span> <span class="n">ST</span> <span class="o">=</span> <span class="p">{</span><span class="n">n</span> <span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="n">G_u</span><span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="k">if</span> <span class="n">n</span> <span class="ow">in</span> <span class="n">u_nbrs</span><span class="p">}</span> <span class="n">set_uv</span> <span class="o">=</span> <span class="p">{</span><span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">}</span> @@ -616,7 +616,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/eigenvector.html b/_modules/networkx/algorithms/centrality/eigenvector.html index fd04012e..2aebe6e1 100644 --- a/_modules/networkx/algorithms/centrality/eigenvector.html +++ b/_modules/networkx/algorithms/centrality/eigenvector.html @@ -473,7 +473,7 @@ <div class="viewcode-block" id="eigenvector_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.eigenvector_centrality.html#networkx.algorithms.centrality.eigenvector_centrality">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">eigenvector_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mf">1.0e-6</span><span class="p">,</span> <span class="n">nstart</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the eigenvector centrality for the graph `G`.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the eigenvector centrality for the graph `G`.</span> <span class="sd"> Eigenvector centrality computes the centrality for a node based on the</span> <span class="sd"> centrality of its neighbors. The eigenvector centrality for node $i$ is</span> @@ -602,7 +602,7 @@ <div class="viewcode-block" id="eigenvector_centrality_numpy"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.eigenvector_centrality_numpy.html#networkx.algorithms.centrality.eigenvector_centrality_numpy">[docs]</a><span class="k">def</span> <span class="nf">eigenvector_centrality_numpy</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">50</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the eigenvector centrality for the graph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the eigenvector centrality for the graph G.</span> <span class="sd"> Eigenvector centrality computes the centrality for a node based on the</span> <span class="sd"> centrality of its neighbors. The eigenvector centrality for node $i$ is</span> @@ -742,7 +742,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/group.html b/_modules/networkx/algorithms/centrality/group.html index e3b08959..97e6518b 100644 --- a/_modules/networkx/algorithms/centrality/group.html +++ b/_modules/networkx/algorithms/centrality/group.html @@ -483,7 +483,7 @@ <div class="viewcode-block" id="group_betweenness_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.group_betweenness_centrality.html#networkx.algorithms.centrality.group_betweenness_centrality">[docs]</a><span class="k">def</span> <span class="nf">group_betweenness_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">C</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">endpoints</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the group betweenness centrality for a group of nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the group betweenness centrality for a group of nodes.</span> <span class="sd"> Group betweenness centrality of a group of nodes $C$ is the sum of the</span> <span class="sd"> fraction of all-pairs shortest paths that pass through any vertex in $C$</span> @@ -583,7 +583,7 @@ <span class="n">list_of_groups</span> <span class="o">=</span> <span class="kc">False</span> <span class="n">set_v</span> <span class="o">=</span> <span class="p">{</span><span class="n">node</span> <span class="k">for</span> <span class="n">group</span> <span class="ow">in</span> <span class="n">C</span> <span class="k">for</span> <span class="n">node</span> <span class="ow">in</span> <span class="n">group</span><span class="p">}</span> <span class="k">if</span> <span class="n">set_v</span> <span class="o">-</span> <span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">:</span> <span class="c1"># element(s) of C not in G</span> - <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NodeNotFound</span><span class="p">(</span><span class="sa">f</span><span class="s2">"The node(s) </span><span class="si">{</span><span class="n">set_v</span> <span class="o">-</span> <span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="si">}</span><span class="s2"> are in C but not in G."</span><span class="p">)</span> + <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NodeNotFound</span><span class="p">(</span><span class="sa">f</span><span class="s2">"The node(s) </span><span class="si">{</span><span class="n">set_v</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="si">}</span><span class="s2"> are in C but not in G."</span><span class="p">)</span> <span class="c1"># pre-processing</span> <span class="n">PB</span><span class="p">,</span> <span class="n">sigma</span><span class="p">,</span> <span class="n">D</span> <span class="o">=</span> <span class="n">_group_preprocessing</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">set_v</span><span class="p">,</span> <span class="n">weight</span><span class="p">)</span> @@ -701,7 +701,7 @@ <div class="viewcode-block" id="prominent_group"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.prominent_group.html#networkx.algorithms.centrality.prominent_group">[docs]</a><span class="k">def</span> <span class="nf">prominent_group</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">endpoints</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">greedy</span><span class="o">=</span><span class="kc">False</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Find the prominent group of size $k$ in graph $G$. The prominence of the</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Find the prominent group of size $k$ in graph $G$. The prominence of the</span> <span class="sd"> group is evaluated by the group betweenness centrality.</span> <span class="sd"> Group betweenness centrality of a group of nodes $C$ is the sum of the</span> @@ -806,7 +806,7 @@ <span class="k">if</span> <span class="n">C</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> <span class="n">C</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">C</span><span class="p">)</span> <span class="k">if</span> <span class="n">C</span> <span class="o">-</span> <span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">:</span> <span class="c1"># element(s) of C not in G</span> - <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NodeNotFound</span><span class="p">(</span><span class="sa">f</span><span class="s2">"The node(s) </span><span class="si">{</span><span class="n">C</span> <span class="o">-</span> <span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="si">}</span><span class="s2"> are in C but not in G."</span><span class="p">)</span> + <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NodeNotFound</span><span class="p">(</span><span class="sa">f</span><span class="s2">"The node(s) </span><span class="si">{</span><span class="n">C</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="si">}</span><span class="s2"> are in C but not in G."</span><span class="p">)</span> <span class="n">nodes</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span> <span class="o">-</span> <span class="n">C</span><span class="p">)</span> <span class="k">else</span><span class="p">:</span> <span class="n">nodes</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">)</span> @@ -1005,7 +1005,7 @@ <div class="viewcode-block" id="group_closeness_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.group_closeness_centrality.html#networkx.algorithms.centrality.group_closeness_centrality">[docs]</a><span class="k">def</span> <span class="nf">group_closeness_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">S</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the group closeness centrality for a group of nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the group closeness centrality for a group of nodes.</span> <span class="sd"> Group closeness centrality of a group of nodes $S$ is a measure</span> <span class="sd"> of how close the group is to the other nodes in the graph.</span> @@ -1101,7 +1101,7 @@ <div class="viewcode-block" id="group_degree_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.group_degree_centrality.html#networkx.algorithms.centrality.group_degree_centrality">[docs]</a><span class="k">def</span> <span class="nf">group_degree_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">S</span><span class="p">):</span> - <span class="sd">"""Compute the group degree centrality for a group of nodes.</span> +<span class="w"> </span><span class="sd">"""Compute the group degree centrality for a group of nodes.</span> <span class="sd"> Group degree centrality of a group of nodes $S$ is the fraction</span> <span class="sd"> of non-group members connected to group members.</span> @@ -1152,7 +1152,7 @@ <div class="viewcode-block" id="group_in_degree_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.group_in_degree_centrality.html#networkx.algorithms.centrality.group_in_degree_centrality">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">group_in_degree_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">S</span><span class="p">):</span> - <span class="sd">"""Compute the group in-degree centrality for a group of nodes.</span> +<span class="w"> </span><span class="sd">"""Compute the group in-degree centrality for a group of nodes.</span> <span class="sd"> Group in-degree centrality of a group of nodes $S$ is the fraction</span> <span class="sd"> of non-group members connected to group members by incoming edges.</span> @@ -1198,7 +1198,7 @@ <div class="viewcode-block" id="group_out_degree_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.group_out_degree_centrality.html#networkx.algorithms.centrality.group_out_degree_centrality">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">group_out_degree_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">S</span><span class="p">):</span> - <span class="sd">"""Compute the group out-degree centrality for a group of nodes.</span> +<span class="w"> </span><span class="sd">"""Compute the group out-degree centrality for a group of nodes.</span> <span class="sd"> Group out-degree centrality of a group of nodes $S$ is the fraction</span> <span class="sd"> of non-group members connected to group members by outgoing edges.</span> @@ -1291,7 +1291,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/harmonic.html b/_modules/networkx/algorithms/centrality/harmonic.html index c4506f36..6abdf215 100644 --- a/_modules/networkx/algorithms/centrality/harmonic.html +++ b/_modules/networkx/algorithms/centrality/harmonic.html @@ -470,7 +470,7 @@ <div class="viewcode-block" id="harmonic_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.harmonic_centrality.html#networkx.algorithms.centrality.harmonic_centrality">[docs]</a><span class="k">def</span> <span class="nf">harmonic_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nbunch</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">distance</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">sources</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute harmonic centrality for nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute harmonic centrality for nodes.</span> <span class="sd"> Harmonic centrality [1]_ of a node `u` is the sum of the reciprocal</span> <span class="sd"> of the shortest path distances from all other nodes to `u`</span> @@ -591,7 +591,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/katz.html b/_modules/networkx/algorithms/centrality/katz.html index b0067c94..135b5be8 100644 --- a/_modules/networkx/algorithms/centrality/katz.html +++ b/_modules/networkx/algorithms/centrality/katz.html @@ -482,7 +482,7 @@ <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the Katz centrality for the nodes of the graph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the Katz centrality for the nodes of the graph G.</span> <span class="sd"> Katz centrality computes the centrality for a node based on the centrality</span> <span class="sd"> of its neighbors. It is a generalization of the eigenvector centrality. The</span> @@ -659,7 +659,7 @@ <div class="viewcode-block" id="katz_centrality_numpy"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.katz_centrality_numpy.html#networkx.algorithms.centrality.katz_centrality_numpy">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">katz_centrality_numpy</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">beta</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the Katz centrality for the graph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the Katz centrality for the graph G.</span> <span class="sd"> Katz centrality computes the centrality for a node based on the centrality</span> <span class="sd"> of its neighbors. It is a generalization of the eigenvector centrality. The</span> @@ -846,7 +846,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/load.html b/_modules/networkx/algorithms/centrality/load.html index 7505e60b..50ba5326 100644 --- a/_modules/networkx/algorithms/centrality/load.html +++ b/_modules/networkx/algorithms/centrality/load.html @@ -470,7 +470,7 @@ <span class="k">def</span> <span class="nf">newman_betweenness_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">v</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute load centrality for nodes.</span> +<span class="w"> </span><span class="sd">"""Compute load centrality for nodes.</span> <span class="sd"> The load centrality of a node is the fraction of all shortest</span> <span class="sd"> paths that pass through that node.</span> @@ -545,7 +545,7 @@ <span class="k">def</span> <span class="nf">_node_betweenness</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Node betweenness_centrality helper:</span> +<span class="w"> </span><span class="sd">"""Node betweenness_centrality helper:</span> <span class="sd"> See betweenness_centrality for what you probably want.</span> <span class="sd"> This actually computes "load" and not betweenness.</span> @@ -599,7 +599,7 @@ <div class="viewcode-block" id="edge_load_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.edge_load_centrality.html#networkx.algorithms.centrality.edge_load_centrality">[docs]</a><span class="k">def</span> <span class="nf">edge_load_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Compute edge load.</span> +<span class="w"> </span><span class="sd">"""Compute edge load.</span> <span class="sd"> WARNING: This concept of edge load has not been analysed</span> <span class="sd"> or discussed outside of NetworkX that we know of.</span> @@ -634,7 +634,7 @@ <span class="k">def</span> <span class="nf">_edge_betweenness</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Edge betweenness helper."""</span> +<span class="w"> </span><span class="sd">"""Edge betweenness helper."""</span> <span class="c1"># get the predecessor data</span> <span class="p">(</span><span class="n">pred</span><span class="p">,</span> <span class="n">length</span><span class="p">)</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">predecessor</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="n">cutoff</span><span class="p">,</span> <span class="n">return_seen</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="c1"># order the nodes by path length</span> @@ -709,7 +709,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/percolation.html b/_modules/networkx/algorithms/centrality/percolation.html index 992c84c5..6f084a9b 100644 --- a/_modules/networkx/algorithms/centrality/percolation.html +++ b/_modules/networkx/algorithms/centrality/percolation.html @@ -475,7 +475,7 @@ <div class="viewcode-block" id="percolation_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.percolation_centrality.html#networkx.algorithms.centrality.percolation_centrality">[docs]</a><span class="k">def</span> <span class="nf">percolation_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">attribute</span><span class="o">=</span><span class="s2">"percolation"</span><span class="p">,</span> <span class="n">states</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the percolation centrality for nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the percolation centrality for nodes.</span> <span class="sd"> Percolation centrality of a node $v$, at a given time, is defined</span> <span class="sd"> as the proportion of ‘percolated paths’ that go through that node.</span> @@ -636,7 +636,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/reaching.html b/_modules/networkx/algorithms/centrality/reaching.html index 63685af8..382c159a 100644 --- a/_modules/networkx/algorithms/centrality/reaching.html +++ b/_modules/networkx/algorithms/centrality/reaching.html @@ -470,7 +470,7 @@ <span class="k">def</span> <span class="nf">_average_weight</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">path</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the average weight of an edge in a weighted path.</span> +<span class="w"> </span><span class="sd">"""Returns the average weight of an edge in a weighted path.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -495,7 +495,7 @@ <div class="viewcode-block" id="global_reaching_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.global_reaching_centrality.html#networkx.algorithms.centrality.global_reaching_centrality">[docs]</a><span class="k">def</span> <span class="nf">global_reaching_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Returns the global reaching centrality of a directed graph.</span> +<span class="w"> </span><span class="sd">"""Returns the global reaching centrality of a directed graph.</span> <span class="sd"> The *global reaching centrality* of a weighted directed graph is the</span> <span class="sd"> average over all nodes of the difference between the local reaching</span> @@ -582,7 +582,7 @@ <div class="viewcode-block" id="local_reaching_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.local_reaching_centrality.html#networkx.algorithms.centrality.local_reaching_centrality">[docs]</a><span class="k">def</span> <span class="nf">local_reaching_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">paths</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Returns the local reaching centrality of a node in a directed</span> +<span class="w"> </span><span class="sd">"""Returns the local reaching centrality of a node in a directed</span> <span class="sd"> graph.</span> <span class="sd"> The *local reaching centrality* of a node in a directed graph is the</span> @@ -716,7 +716,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/second_order.html b/_modules/networkx/algorithms/centrality/second_order.html index 51f21551..175c0eed 100644 --- a/_modules/networkx/algorithms/centrality/second_order.html +++ b/_modules/networkx/algorithms/centrality/second_order.html @@ -503,7 +503,7 @@ <div class="viewcode-block" id="second_order_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.second_order_centrality.html#networkx.algorithms.centrality.second_order_centrality">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">second_order_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Compute the second order centrality for nodes of G.</span> +<span class="w"> </span><span class="sd">"""Compute the second order centrality for nodes of G.</span> <span class="sd"> The second order centrality of a given node is the standard deviation of</span> <span class="sd"> the return times to that node of a perpetual random walk on G:</span> @@ -645,7 +645,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/subgraph_alg.html b/_modules/networkx/algorithms/centrality/subgraph_alg.html index f19298fe..dbf1aed1 100644 --- a/_modules/networkx/algorithms/centrality/subgraph_alg.html +++ b/_modules/networkx/algorithms/centrality/subgraph_alg.html @@ -478,7 +478,7 @@ <div class="viewcode-block" id="subgraph_centrality_exp"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.subgraph_centrality_exp.html#networkx.algorithms.centrality.subgraph_centrality_exp">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">subgraph_centrality_exp</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the subgraph centrality for each node of G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the subgraph centrality for each node of G.</span> <span class="sd"> Subgraph centrality of a node `n` is the sum of weighted closed</span> <span class="sd"> walks of all lengths starting and ending at node `n`. The weights</span> @@ -562,7 +562,7 @@ <div class="viewcode-block" id="subgraph_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.subgraph_centrality.html#networkx.algorithms.centrality.subgraph_centrality">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">subgraph_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns subgraph centrality for each node in G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns subgraph centrality for each node in G.</span> <span class="sd"> Subgraph centrality of a node `n` is the sum of weighted closed</span> <span class="sd"> walks of all lengths starting and ending at node `n`. The weights</span> @@ -652,7 +652,7 @@ <div class="viewcode-block" id="communicability_betweenness_centrality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.communicability_betweenness_centrality.html#networkx.algorithms.centrality.communicability_betweenness_centrality">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">communicability_betweenness_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns subgraph communicability for all pairs of nodes in G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns subgraph communicability for all pairs of nodes in G.</span> <span class="sd"> Communicability betweenness measure makes use of the number of walks</span> <span class="sd"> connecting every pair of nodes as the basis of a betweenness centrality</span> @@ -754,7 +754,7 @@ <div class="viewcode-block" id="estrada_index"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.estrada_index.html#networkx.algorithms.centrality.estrada_index">[docs]</a><span class="k">def</span> <span class="nf">estrada_index</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the Estrada index of a the graph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the Estrada index of a the graph G.</span> <span class="sd"> The Estrada Index is a topological index of folding or 3D "compactness" ([1]_).</span> @@ -850,7 +850,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/trophic.html b/_modules/networkx/algorithms/centrality/trophic.html index f28c54e0..257a3141 100644 --- a/_modules/networkx/algorithms/centrality/trophic.html +++ b/_modules/networkx/algorithms/centrality/trophic.html @@ -470,7 +470,7 @@ <div class="viewcode-block" id="trophic_levels"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.trophic_levels.html#networkx.algorithms.centrality.trophic_levels">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">trophic_levels</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the trophic levels of nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the trophic levels of nodes.</span> <span class="sd"> The trophic level of a node $i$ is</span> @@ -545,7 +545,7 @@ <div class="viewcode-block" id="trophic_differences"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.trophic_differences.html#networkx.algorithms.centrality.trophic_differences">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">trophic_differences</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the trophic differences of the edges of a directed graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the trophic differences of the edges of a directed graph.</span> <span class="sd"> The trophic difference $x_ij$ for each edge is defined in Johnson et al.</span> <span class="sd"> [1]_ as:</span> @@ -579,7 +579,7 @@ <div class="viewcode-block" id="trophic_incoherence_parameter"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.trophic_incoherence_parameter.html#networkx.algorithms.centrality.trophic_incoherence_parameter">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">trophic_incoherence_parameter</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">cannibalism</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the trophic incoherence parameter of a graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the trophic incoherence parameter of a graph.</span> <span class="sd"> Trophic coherence is defined as the homogeneity of the distribution of</span> <span class="sd"> trophic distances: the more similar, the more coherent. This is measured by</span> @@ -671,7 +671,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/centrality/voterank_alg.html b/_modules/networkx/algorithms/centrality/voterank_alg.html index 0539dd35..dd8f0c2f 100644 --- a/_modules/networkx/algorithms/centrality/voterank_alg.html +++ b/_modules/networkx/algorithms/centrality/voterank_alg.html @@ -467,7 +467,7 @@ <div class="viewcode-block" id="voterank"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.centrality.voterank.html#networkx.algorithms.centrality.voterank">[docs]</a><span class="k">def</span> <span class="nf">voterank</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">number_of_nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Select a list of influential nodes in a graph using VoteRank algorithm</span> +<span class="w"> </span><span class="sd">"""Select a list of influential nodes in a graph using VoteRank algorithm</span> <span class="sd"> VoteRank [1]_ computes a ranking of the nodes in a graph G based on a</span> <span class="sd"> voting scheme. With VoteRank, all nodes vote for each of its in-neighbours</span> @@ -604,7 +604,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/chains.html b/_modules/networkx/algorithms/chains.html index 0cc9c910..29396974 100644 --- a/_modules/networkx/algorithms/chains.html +++ b/_modules/networkx/algorithms/chains.html @@ -472,7 +472,7 @@ <div class="viewcode-block" id="chain_decomposition"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.chains.chain_decomposition.html#networkx.algorithms.chains.chain_decomposition">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">chain_decomposition</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">root</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the chain decomposition of a graph.</span> +<span class="w"> </span><span class="sd">"""Returns the chain decomposition of a graph.</span> <span class="sd"> The *chain decomposition* of a graph with respect a depth-first</span> <span class="sd"> search tree is a set of cycles or paths derived from the set of</span> @@ -527,7 +527,7 @@ <span class="sd"> """</span> <span class="k">def</span> <span class="nf">_dfs_cycle_forest</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">root</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Builds a directed graph composed of cycles from the given graph.</span> +<span class="w"> </span><span class="sd">"""Builds a directed graph composed of cycles from the given graph.</span> <span class="sd"> `G` is an undirected simple graph. `root` is a node in the graph</span> <span class="sd"> from which the depth-first search is started.</span> @@ -583,7 +583,7 @@ <span class="k">return</span> <span class="n">H</span><span class="p">,</span> <span class="n">nodes</span> <span class="k">def</span> <span class="nf">_build_chain</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">visited</span><span class="p">):</span> - <span class="sd">"""Generate the chain starting from the given nontree edge.</span> +<span class="w"> </span><span class="sd">"""Generate the chain starting from the given nontree edge.</span> <span class="sd"> `G` is a DFS cycle graph as constructed by</span> <span class="sd"> :func:`_dfs_cycle_graph`. The edge (`u`, `v`) is a nontree edge</span> @@ -683,7 +683,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/chordal.html b/_modules/networkx/algorithms/chordal.html index 25da1ab0..f8f39247 100644 --- a/_modules/networkx/algorithms/chordal.html +++ b/_modules/networkx/algorithms/chordal.html @@ -485,14 +485,14 @@ <span class="k">class</span> <span class="nc">NetworkXTreewidthBoundExceeded</span><span class="p">(</span><span class="n">nx</span><span class="o">.</span><span class="n">NetworkXException</span><span class="p">):</span> - <span class="sd">"""Exception raised when a treewidth bound has been provided and it has</span> +<span class="w"> </span><span class="sd">"""Exception raised when a treewidth bound has been provided and it has</span> <span class="sd"> been exceeded"""</span> <div class="viewcode-block" id="is_chordal"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.chordal.is_chordal.html#networkx.algorithms.chordal.is_chordal">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_chordal</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Checks whether G is a chordal graph.</span> +<span class="w"> </span><span class="sd">"""Checks whether G is a chordal graph.</span> <span class="sd"> A graph is chordal if every cycle of length at least 4 has a chord</span> <span class="sd"> (an edge joining two nodes not adjacent in the cycle).</span> @@ -547,7 +547,7 @@ <div class="viewcode-block" id="find_induced_nodes"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.chordal.find_induced_nodes.html#networkx.algorithms.chordal.find_induced_nodes">[docs]</a><span class="k">def</span> <span class="nf">find_induced_nodes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">treewidth_bound</span><span class="o">=</span><span class="n">sys</span><span class="o">.</span><span class="n">maxsize</span><span class="p">):</span> - <span class="sd">"""Returns the set of induced nodes in the path from s to t.</span> +<span class="w"> </span><span class="sd">"""Returns the set of induced nodes in the path from s to t.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -624,7 +624,7 @@ <div class="viewcode-block" id="chordal_graph_cliques"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.chordal.chordal_graph_cliques.html#networkx.algorithms.chordal.chordal_graph_cliques">[docs]</a><span class="k">def</span> <span class="nf">chordal_graph_cliques</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns all maximal cliques of a chordal graph.</span> +<span class="w"> </span><span class="sd">"""Returns all maximal cliques of a chordal graph.</span> <span class="sd"> The algorithm breaks the graph in connected components and performs a</span> <span class="sd"> maximum cardinality search in each component to get the cliques.</span> @@ -696,7 +696,7 @@ <div class="viewcode-block" id="chordal_graph_treewidth"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.chordal.chordal_graph_treewidth.html#networkx.algorithms.chordal.chordal_graph_treewidth">[docs]</a><span class="k">def</span> <span class="nf">chordal_graph_treewidth</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the treewidth of the chordal graph G.</span> +<span class="w"> </span><span class="sd">"""Returns the treewidth of the chordal graph G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -749,7 +749,7 @@ <span class="k">def</span> <span class="nf">_is_complete_graph</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns True if G is a complete graph."""</span> +<span class="w"> </span><span class="sd">"""Returns True if G is a complete graph."""</span> <span class="k">if</span> <span class="n">nx</span><span class="o">.</span><span class="n">number_of_selfloops</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="s2">"Self loop found in _is_complete_graph()"</span><span class="p">)</span> <span class="n">n</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">number_of_nodes</span><span class="p">()</span> @@ -761,7 +761,7 @@ <span class="k">def</span> <span class="nf">_find_missing_edge</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Given a non-complete graph G, returns a missing edge."""</span> +<span class="w"> </span><span class="sd">"""Given a non-complete graph G, returns a missing edge."""</span> <span class="n">nodes</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> <span class="k">for</span> <span class="n">u</span> <span class="ow">in</span> <span class="n">G</span><span class="p">:</span> <span class="n">missing</span> <span class="o">=</span> <span class="n">nodes</span> <span class="o">-</span> <span class="nb">set</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">G</span><span class="p">[</span><span class="n">u</span><span class="p">]</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span> <span class="o">+</span> <span class="p">[</span><span class="n">u</span><span class="p">])</span> @@ -770,7 +770,7 @@ <span class="k">def</span> <span class="nf">_max_cardinality_node</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">choices</span><span class="p">,</span> <span class="n">wanna_connect</span><span class="p">):</span> - <span class="sd">"""Returns a the node in choices that has more connections in G</span> +<span class="w"> </span><span class="sd">"""Returns a the node in choices that has more connections in G</span> <span class="sd"> to nodes in wanna_connect.</span> <span class="sd"> """</span> <span class="n">max_number</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1</span> @@ -783,7 +783,7 @@ <span class="k">def</span> <span class="nf">_find_chordality_breaker</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">treewidth_bound</span><span class="o">=</span><span class="n">sys</span><span class="o">.</span><span class="n">maxsize</span><span class="p">):</span> - <span class="sd">"""Given a graph G, starts a max cardinality search</span> +<span class="w"> </span><span class="sd">"""Given a graph G, starts a max cardinality search</span> <span class="sd"> (starting from s if s is given and from an arbitrary node otherwise)</span> <span class="sd"> trying to find a non-chordal cycle.</span> @@ -821,7 +821,7 @@ <div class="viewcode-block" id="complete_to_chordal_graph"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.chordal.complete_to_chordal_graph.html#networkx.algorithms.chordal.complete_to_chordal_graph">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">complete_to_chordal_graph</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Return a copy of G completed to a chordal graph</span> +<span class="w"> </span><span class="sd">"""Return a copy of G completed to a chordal graph</span> <span class="sd"> Adds edges to a copy of G to create a chordal graph. A graph G=(V,E) is</span> <span class="sd"> called chordal if for each cycle with length bigger than 3, there exist</span> @@ -941,7 +941,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/clique.html b/_modules/networkx/algorithms/clique.html index aea7ae67..5e97ead2 100644 --- a/_modules/networkx/algorithms/clique.html +++ b/_modules/networkx/algorithms/clique.html @@ -493,7 +493,7 @@ <div class="viewcode-block" id="enumerate_all_cliques"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.clique.enumerate_all_cliques.html#networkx.algorithms.clique.enumerate_all_cliques">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">enumerate_all_cliques</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns all cliques in an undirected graph.</span> +<span class="w"> </span><span class="sd">"""Returns all cliques in an undirected graph.</span> <span class="sd"> This function returns an iterator over cliques, each of which is a</span> <span class="sd"> list of nodes. The iteration is ordered by cardinality of the</span> @@ -564,7 +564,7 @@ <div class="viewcode-block" id="find_cliques"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.clique.find_cliques.html#networkx.algorithms.clique.find_cliques">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">find_cliques</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns all maximal cliques in an undirected graph.</span> +<span class="w"> </span><span class="sd">"""Returns all maximal cliques in an undirected graph.</span> <span class="sd"> For each node *n*, a *maximal clique for n* is a largest complete</span> <span class="sd"> subgraph containing *n*. The largest maximal clique is sometimes</span> @@ -698,7 +698,7 @@ <span class="c1"># TODO Should this also be not implemented for directed graphs?</span> <div class="viewcode-block" id="find_cliques_recursive"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.clique.find_cliques_recursive.html#networkx.algorithms.clique.find_cliques_recursive">[docs]</a><span class="k">def</span> <span class="nf">find_cliques_recursive</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns all maximal cliques in a graph.</span> +<span class="w"> </span><span class="sd">"""Returns all maximal cliques in a graph.</span> <span class="sd"> For each node *v*, a *maximal clique for v* is a largest complete</span> <span class="sd"> subgraph containing *v*. The largest maximal clique is sometimes</span> @@ -815,7 +815,7 @@ <div class="viewcode-block" id="make_max_clique_graph"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.clique.make_max_clique_graph.html#networkx.algorithms.clique.make_max_clique_graph">[docs]</a><span class="k">def</span> <span class="nf">make_max_clique_graph</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the maximal clique graph of the given graph.</span> +<span class="w"> </span><span class="sd">"""Returns the maximal clique graph of the given graph.</span> <span class="sd"> The nodes of the maximal clique graph of `G` are the cliques of</span> <span class="sd"> `G` and an edge joins two cliques if the cliques are not disjoint.</span> @@ -861,7 +861,7 @@ <div class="viewcode-block" id="make_clique_bipartite"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.clique.make_clique_bipartite.html#networkx.algorithms.clique.make_clique_bipartite">[docs]</a><span class="k">def</span> <span class="nf">make_clique_bipartite</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">fpos</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the bipartite clique graph corresponding to `G`.</span> +<span class="w"> </span><span class="sd">"""Returns the bipartite clique graph corresponding to `G`.</span> <span class="sd"> In the returned bipartite graph, the "bottom" nodes are the nodes of</span> <span class="sd"> `G` and the "top" nodes represent the maximal cliques of `G`.</span> @@ -909,7 +909,7 @@ <div class="viewcode-block" id="graph_clique_number"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.clique.graph_clique_number.html#networkx.algorithms.clique.graph_clique_number">[docs]</a><span class="k">def</span> <span class="nf">graph_clique_number</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">cliques</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the clique number of the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the clique number of the graph.</span> <span class="sd"> The *clique number* of a graph is the size of the largest clique in</span> <span class="sd"> the graph.</span> @@ -944,7 +944,7 @@ <div class="viewcode-block" id="graph_number_of_cliques"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.clique.graph_number_of_cliques.html#networkx.algorithms.clique.graph_number_of_cliques">[docs]</a><span class="k">def</span> <span class="nf">graph_number_of_cliques</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">cliques</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the number of maximal cliques in the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the number of maximal cliques in the graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -974,7 +974,7 @@ <div class="viewcode-block" id="node_clique_number"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.clique.node_clique_number.html#networkx.algorithms.clique.node_clique_number">[docs]</a><span class="k">def</span> <span class="nf">node_clique_number</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cliques</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">separate_nodes</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns the size of the largest maximal clique containing each given node.</span> +<span class="w"> </span><span class="sd">"""Returns the size of the largest maximal clique containing each given node.</span> <span class="sd"> Returns a single or list depending on input nodes.</span> <span class="sd"> An optional list of cliques can be input if already computed.</span> @@ -1037,7 +1037,7 @@ <div class="viewcode-block" id="number_of_cliques"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.clique.number_of_cliques.html#networkx.algorithms.clique.number_of_cliques">[docs]</a><span class="k">def</span> <span class="nf">number_of_cliques</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cliques</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the number of maximal cliques for each node.</span> +<span class="w"> </span><span class="sd">"""Returns the number of maximal cliques for each node.</span> <span class="sd"> Returns a single or list depending on input nodes.</span> <span class="sd"> Optional list of cliques can be input if already computed.</span> @@ -1060,7 +1060,7 @@ <div class="viewcode-block" id="cliques_containing_node"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.clique.cliques_containing_node.html#networkx.algorithms.clique.cliques_containing_node">[docs]</a><span class="k">def</span> <span class="nf">cliques_containing_node</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cliques</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a list of cliques containing the given node.</span> +<span class="w"> </span><span class="sd">"""Returns a list of cliques containing the given node.</span> <span class="sd"> Returns a single list or list of lists depending on input nodes.</span> <span class="sd"> Optional list of cliques can be input if already computed.</span> @@ -1083,7 +1083,7 @@ <span class="k">class</span> <span class="nc">MaxWeightClique</span><span class="p">:</span> - <span class="sd">"""A class for the maximum weight clique algorithm.</span> +<span class="w"> </span><span class="sd">"""A class for the maximum weight clique algorithm.</span> <span class="sd"> This class is a helper for the `max_weight_clique` function. The class</span> <span class="sd"> should not normally be used directly.</span> @@ -1126,7 +1126,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">node_weights</span> <span class="o">=</span> <span class="p">{</span><span class="n">v</span><span class="p">:</span> <span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="n">v</span><span class="p">][</span><span class="n">weight</span><span class="p">]</span> <span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">()}</span> <span class="k">def</span> <span class="nf">update_incumbent_if_improved</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">C</span><span class="p">,</span> <span class="n">C_weight</span><span class="p">):</span> - <span class="sd">"""Update the incumbent if the node set C has greater weight.</span> +<span class="w"> </span><span class="sd">"""Update the incumbent if the node set C has greater weight.</span> <span class="sd"> C is assumed to be a clique.</span> <span class="sd"> """</span> @@ -1135,7 +1135,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">incumbent_weight</span> <span class="o">=</span> <span class="n">C_weight</span> <span class="k">def</span> <span class="nf">greedily_find_independent_set</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">P</span><span class="p">):</span> - <span class="sd">"""Greedily find an independent set of nodes from a set of</span> +<span class="w"> </span><span class="sd">"""Greedily find an independent set of nodes from a set of</span> <span class="sd"> nodes P."""</span> <span class="n">independent_set</span> <span class="o">=</span> <span class="p">[]</span> <span class="n">P</span> <span class="o">=</span> <span class="n">P</span><span class="p">[:]</span> @@ -1146,7 +1146,7 @@ <span class="k">return</span> <span class="n">independent_set</span> <span class="k">def</span> <span class="nf">find_branching_nodes</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">P</span><span class="p">,</span> <span class="n">target</span><span class="p">):</span> - <span class="sd">"""Find a set of nodes to branch on."""</span> +<span class="w"> </span><span class="sd">"""Find a set of nodes to branch on."""</span> <span class="n">residual_wt</span> <span class="o">=</span> <span class="p">{</span><span class="n">v</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">node_weights</span><span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">P</span><span class="p">}</span> <span class="n">total_wt</span> <span class="o">=</span> <span class="mi">0</span> <span class="n">P</span> <span class="o">=</span> <span class="n">P</span><span class="p">[:]</span> @@ -1162,7 +1162,7 @@ <span class="k">return</span> <span class="n">P</span> <span class="k">def</span> <span class="nf">expand</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">C</span><span class="p">,</span> <span class="n">C_weight</span><span class="p">,</span> <span class="n">P</span><span class="p">):</span> - <span class="sd">"""Look for the best clique that contains all the nodes in C and zero or</span> +<span class="w"> </span><span class="sd">"""Look for the best clique that contains all the nodes in C and zero or</span> <span class="sd"> more of the nodes in P, backtracking if it can be shown that no such</span> <span class="sd"> clique has greater weight than the incumbent.</span> <span class="sd"> """</span> @@ -1177,7 +1177,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">expand</span><span class="p">(</span><span class="n">new_C</span><span class="p">,</span> <span class="n">new_C_weight</span><span class="p">,</span> <span class="n">new_P</span><span class="p">)</span> <span class="k">def</span> <span class="nf">find_max_weight_clique</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Find a maximum weight clique."""</span> +<span class="w"> </span><span class="sd">"""Find a maximum weight clique."""</span> <span class="c1"># Sort nodes in reverse order of degree for speed</span> <span class="n">nodes</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(),</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">v</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">G</span><span class="o">.</span><span class="n">degree</span><span class="p">(</span><span class="n">v</span><span class="p">),</span> <span class="n">reverse</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="n">nodes</span> <span class="o">=</span> <span class="p">[</span><span class="n">v</span> <span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">nodes</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">node_weights</span><span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="o">></span> <span class="mi">0</span><span class="p">]</span> @@ -1186,7 +1186,7 @@ <div class="viewcode-block" id="max_weight_clique"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.clique.max_weight_clique.html#networkx.algorithms.clique.max_weight_clique">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">max_weight_clique</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Find a maximum weight clique in G.</span> +<span class="w"> </span><span class="sd">"""Find a maximum weight clique in G.</span> <span class="sd"> A *clique* in a graph is a set of nodes such that every two distinct nodes</span> <span class="sd"> are adjacent. The *weight* of a clique is the sum of the weights of its</span> @@ -1288,7 +1288,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/cluster.html b/_modules/networkx/algorithms/cluster.html index dc215547..cf2fed2b 100644 --- a/_modules/networkx/algorithms/cluster.html +++ b/_modules/networkx/algorithms/cluster.html @@ -482,7 +482,7 @@ <div class="viewcode-block" id="triangles"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cluster.triangles.html#networkx.algorithms.cluster.triangles">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span><span class="p">(</span><span class="s2">"triangles"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">triangles</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute the number of triangles.</span> +<span class="w"> </span><span class="sd">"""Compute the number of triangles.</span> <span class="sd"> Finds the number of triangles that include a node as one vertex.</span> @@ -525,7 +525,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">_triangles_and_degree_iter</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Return an iterator of (node, degree, triangles, generalized degree).</span> +<span class="w"> </span><span class="sd">"""Return an iterator of (node, degree, triangles, generalized degree).</span> <span class="sd"> This double counts triangles so you may want to divide by 2.</span> <span class="sd"> See degree(), triangles() and generalized_degree() for definitions</span> @@ -546,7 +546,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">_weighted_triangles_and_degree_iter</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Return an iterator of (node, degree, weighted_triangles).</span> +<span class="w"> </span><span class="sd">"""Return an iterator of (node, degree, weighted_triangles).</span> <span class="sd"> Used for weighted clustering.</span> <span class="sd"> Note: this returns the geometric average weight of edges in the triangle.</span> @@ -587,7 +587,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">_directed_triangles_and_degree_iter</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Return an iterator of</span> +<span class="w"> </span><span class="sd">"""Return an iterator of</span> <span class="sd"> (node, total_degree, reciprocal_degree, directed_triangles).</span> <span class="sd"> Used for directed clustering.</span> @@ -621,7 +621,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">_directed_weighted_triangles_and_degree_iter</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Return an iterator of</span> +<span class="w"> </span><span class="sd">"""Return an iterator of</span> <span class="sd"> (node, total_degree, reciprocal_degree, directed_weighted_triangles).</span> <span class="sd"> Used for directed weighted clustering.</span> @@ -685,7 +685,7 @@ <div class="viewcode-block" id="average_clustering"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cluster.average_clustering.html#networkx.algorithms.cluster.average_clustering">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"average_clustering"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">average_clustering</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">count_zeros</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the average clustering coefficient for the graph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the average clustering coefficient for the graph G.</span> <span class="sd"> The clustering coefficient for the graph is the average,</span> @@ -745,7 +745,7 @@ <div class="viewcode-block" id="clustering"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cluster.clustering.html#networkx.algorithms.cluster.clustering">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"clustering"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">clustering</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the clustering coefficient for nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the clustering coefficient for nodes.</span> <span class="sd"> For unweighted graphs, the clustering of a node :math:`u`</span> <span class="sd"> is the fraction of possible triangles through that node that exist,</span> @@ -859,7 +859,7 @@ <div class="viewcode-block" id="transitivity"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cluster.transitivity.html#networkx.algorithms.cluster.transitivity">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span><span class="p">(</span><span class="s2">"transitivity"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">transitivity</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute graph transitivity, the fraction of all possible triangles</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute graph transitivity, the fraction of all possible triangles</span> <span class="sd"> present in G.</span> <span class="sd"> Possible triangles are identified by the number of "triads"</span> @@ -898,7 +898,7 @@ <div class="viewcode-block" id="square_clustering"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cluster.square_clustering.html#networkx.algorithms.cluster.square_clustering">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"square_clustering"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">square_clustering</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the squares clustering coefficient for nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the squares clustering coefficient for nodes.</span> <span class="sd"> For each node return the fraction of possible squares that exist at</span> <span class="sd"> the node [1]_</span> @@ -977,7 +977,7 @@ <div class="viewcode-block" id="generalized_degree"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cluster.generalized_degree.html#networkx.algorithms.cluster.generalized_degree">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span><span class="p">(</span><span class="s2">"generalized_degree"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">generalized_degree</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the generalized degree for nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the generalized degree for nodes.</span> <span class="sd"> For each node, the generalized degree shows how many edges of given</span> <span class="sd"> triangle multiplicity the node is connected to. The triangle multiplicity</span> @@ -1087,7 +1087,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/coloring/equitable_coloring.html b/_modules/networkx/algorithms/coloring/equitable_coloring.html index 921c1e82..a5c4df25 100644 --- a/_modules/networkx/algorithms/coloring/equitable_coloring.html +++ b/_modules/networkx/algorithms/coloring/equitable_coloring.html @@ -473,7 +473,7 @@ <span class="k">def</span> <span class="nf">is_coloring</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">coloring</span><span class="p">):</span> - <span class="sd">"""Determine if the coloring is a valid coloring for the graph G."""</span> +<span class="w"> </span><span class="sd">"""Determine if the coloring is a valid coloring for the graph G."""</span> <span class="c1"># Verify that the coloring is valid.</span> <span class="k">for</span> <span class="p">(</span><span class="n">s</span><span class="p">,</span> <span class="n">d</span><span class="p">)</span> <span class="ow">in</span> <span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">:</span> <span class="k">if</span> <span class="n">coloring</span><span class="p">[</span><span class="n">s</span><span class="p">]</span> <span class="o">==</span> <span class="n">coloring</span><span class="p">[</span><span class="n">d</span><span class="p">]:</span> @@ -482,7 +482,7 @@ <span class="k">def</span> <span class="nf">is_equitable</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">coloring</span><span class="p">,</span> <span class="n">num_colors</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Determines if the coloring is valid and equitable for the graph G."""</span> +<span class="w"> </span><span class="sd">"""Determines if the coloring is valid and equitable for the graph G."""</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">is_coloring</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">coloring</span><span class="p">):</span> <span class="k">return</span> <span class="kc">False</span> @@ -538,7 +538,7 @@ <span class="k">def</span> <span class="nf">change_color</span><span class="p">(</span><span class="n">u</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">Y</span><span class="p">,</span> <span class="n">N</span><span class="p">,</span> <span class="n">H</span><span class="p">,</span> <span class="n">F</span><span class="p">,</span> <span class="n">C</span><span class="p">,</span> <span class="n">L</span><span class="p">):</span> - <span class="sd">"""Change the color of 'u' from X to Y and update N, H, F, C."""</span> +<span class="w"> </span><span class="sd">"""Change the color of 'u' from X to Y and update N, H, F, C."""</span> <span class="k">assert</span> <span class="n">F</span><span class="p">[</span><span class="n">u</span><span class="p">]</span> <span class="o">==</span> <span class="n">X</span> <span class="ow">and</span> <span class="n">X</span> <span class="o">!=</span> <span class="n">Y</span> <span class="c1"># Change the class of 'u' from X to Y</span> @@ -568,7 +568,7 @@ <span class="k">def</span> <span class="nf">move_witnesses</span><span class="p">(</span><span class="n">src_color</span><span class="p">,</span> <span class="n">dst_color</span><span class="p">,</span> <span class="n">N</span><span class="p">,</span> <span class="n">H</span><span class="p">,</span> <span class="n">F</span><span class="p">,</span> <span class="n">C</span><span class="p">,</span> <span class="n">T_cal</span><span class="p">,</span> <span class="n">L</span><span class="p">):</span> - <span class="sd">"""Move witness along a path from src_color to dst_color."""</span> +<span class="w"> </span><span class="sd">"""Move witness along a path from src_color to dst_color."""</span> <span class="n">X</span> <span class="o">=</span> <span class="n">src_color</span> <span class="k">while</span> <span class="n">X</span> <span class="o">!=</span> <span class="n">dst_color</span><span class="p">:</span> <span class="n">Y</span> <span class="o">=</span> <span class="n">T_cal</span><span class="p">[</span><span class="n">X</span><span class="p">]</span> @@ -579,7 +579,7 @@ <span class="k">def</span> <span class="nf">pad_graph</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">num_colors</span><span class="p">):</span> - <span class="sd">"""Add a disconnected complete clique K_p such that the number of nodes in</span> +<span class="w"> </span><span class="sd">"""Add a disconnected complete clique K_p such that the number of nodes in</span> <span class="sd"> the graph becomes a multiple of `num_colors`.</span> <span class="sd"> Assumes that the graph's nodes are labelled using integers.</span> @@ -604,7 +604,7 @@ <span class="k">def</span> <span class="nf">procedure_P</span><span class="p">(</span><span class="n">V_minus</span><span class="p">,</span> <span class="n">V_plus</span><span class="p">,</span> <span class="n">N</span><span class="p">,</span> <span class="n">H</span><span class="p">,</span> <span class="n">F</span><span class="p">,</span> <span class="n">C</span><span class="p">,</span> <span class="n">L</span><span class="p">,</span> <span class="n">excluded_colors</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Procedure P as described in the paper."""</span> +<span class="w"> </span><span class="sd">"""Procedure P as described in the paper."""</span> <span class="k">if</span> <span class="n">excluded_colors</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> <span class="n">excluded_colors</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span> @@ -859,7 +859,7 @@ <div class="viewcode-block" id="equitable_color"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.coloring.equitable_color.html#networkx.algorithms.coloring.equitable_color">[docs]</a><span class="k">def</span> <span class="nf">equitable_color</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">num_colors</span><span class="p">):</span> - <span class="sd">"""Provides equitable (r + 1)-coloring for nodes of G in O(r * n^2) time</span> +<span class="w"> </span><span class="sd">"""Provides equitable (r + 1)-coloring for nodes of G in O(r * n^2) time</span> <span class="sd"> if deg(G) <= r. The algorithm is described in [1]_.</span> <span class="sd"> Attempts to color a graph using r colors, where no neighbors of a node</span> @@ -919,7 +919,7 @@ <span class="k">if</span> <span class="n">r_</span> <span class="o">>=</span> <span class="n">num_colors</span><span class="p">:</span> <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXAlgorithmError</span><span class="p">(</span> <span class="sa">f</span><span class="s2">"Graph has maximum degree </span><span class="si">{</span><span class="n">r_</span><span class="si">}</span><span class="s2">, needs "</span> - <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">r_</span> <span class="o">+</span> <span class="mi">1</span><span class="si">}</span><span class="s2"> (> </span><span class="si">{</span><span class="n">num_colors</span><span class="si">}</span><span class="s2">) colors for guaranteed coloring."</span> + <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">r_</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">1</span><span class="si">}</span><span class="s2"> (> </span><span class="si">{</span><span class="n">num_colors</span><span class="si">}</span><span class="s2">) colors for guaranteed coloring."</span> <span class="p">)</span> <span class="c1"># Ensure that the number of nodes in G is a multiple of (r + 1)</span> @@ -1027,7 +1027,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/coloring/greedy_coloring.html b/_modules/networkx/algorithms/coloring/greedy_coloring.html index 56243af4..56f93c01 100644 --- a/_modules/networkx/algorithms/coloring/greedy_coloring.html +++ b/_modules/networkx/algorithms/coloring/greedy_coloring.html @@ -484,7 +484,7 @@ <div class="viewcode-block" id="strategy_largest_first"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.coloring.strategy_largest_first.html#networkx.algorithms.coloring.strategy_largest_first">[docs]</a><span class="k">def</span> <span class="nf">strategy_largest_first</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">colors</span><span class="p">):</span> - <span class="sd">"""Returns a list of the nodes of ``G`` in decreasing order by</span> +<span class="w"> </span><span class="sd">"""Returns a list of the nodes of ``G`` in decreasing order by</span> <span class="sd"> degree.</span> <span class="sd"> ``G`` is a NetworkX graph. ``colors`` is ignored.</span> @@ -495,7 +495,7 @@ <div class="viewcode-block" id="strategy_random_sequential"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.coloring.strategy_random_sequential.html#networkx.algorithms.coloring.strategy_random_sequential">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">strategy_random_sequential</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">colors</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a random permutation of the nodes of ``G`` as a list.</span> +<span class="w"> </span><span class="sd">"""Returns a random permutation of the nodes of ``G`` as a list.</span> <span class="sd"> ``G`` is a NetworkX graph. ``colors`` is ignored.</span> @@ -509,7 +509,7 @@ <div class="viewcode-block" id="strategy_smallest_last"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.coloring.strategy_smallest_last.html#networkx.algorithms.coloring.strategy_smallest_last">[docs]</a><span class="k">def</span> <span class="nf">strategy_smallest_last</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">colors</span><span class="p">):</span> - <span class="sd">"""Returns a deque of the nodes of ``G``, "smallest" last.</span> +<span class="w"> </span><span class="sd">"""Returns a deque of the nodes of ``G``, "smallest" last.</span> <span class="sd"> Specifically, the degrees of each node are tracked in a bucket queue.</span> <span class="sd"> From this, the node of minimum degree is repeatedly popped from the</span> @@ -566,7 +566,7 @@ <span class="k">def</span> <span class="nf">_maximal_independent_set</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns a maximal independent set of nodes in ``G`` by repeatedly</span> +<span class="w"> </span><span class="sd">"""Returns a maximal independent set of nodes in ``G`` by repeatedly</span> <span class="sd"> choosing an independent node of minimum degree (with respect to the</span> <span class="sd"> subgraph of unchosen nodes).</span> @@ -582,7 +582,7 @@ <div class="viewcode-block" id="strategy_independent_set"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.coloring.strategy_independent_set.html#networkx.algorithms.coloring.strategy_independent_set">[docs]</a><span class="k">def</span> <span class="nf">strategy_independent_set</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">colors</span><span class="p">):</span> - <span class="sd">"""Uses a greedy independent set removal strategy to determine the</span> +<span class="w"> </span><span class="sd">"""Uses a greedy independent set removal strategy to determine the</span> <span class="sd"> colors.</span> <span class="sd"> This function updates ``colors`` **in-place** and return ``None``,</span> @@ -606,7 +606,7 @@ <div class="viewcode-block" id="strategy_connected_sequential_bfs"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.coloring.strategy_connected_sequential_bfs.html#networkx.algorithms.coloring.strategy_connected_sequential_bfs">[docs]</a><span class="k">def</span> <span class="nf">strategy_connected_sequential_bfs</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">colors</span><span class="p">):</span> - <span class="sd">"""Returns an iterable over nodes in ``G`` in the order given by a</span> +<span class="w"> </span><span class="sd">"""Returns an iterable over nodes in ``G`` in the order given by a</span> <span class="sd"> breadth-first traversal.</span> <span class="sd"> The generated sequence has the property that for each node except</span> @@ -619,7 +619,7 @@ <div class="viewcode-block" id="strategy_connected_sequential_dfs"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.coloring.strategy_connected_sequential_dfs.html#networkx.algorithms.coloring.strategy_connected_sequential_dfs">[docs]</a><span class="k">def</span> <span class="nf">strategy_connected_sequential_dfs</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">colors</span><span class="p">):</span> - <span class="sd">"""Returns an iterable over nodes in ``G`` in the order given by a</span> +<span class="w"> </span><span class="sd">"""Returns an iterable over nodes in ``G`` in the order given by a</span> <span class="sd"> depth-first traversal.</span> <span class="sd"> The generated sequence has the property that for each node except</span> @@ -632,7 +632,7 @@ <div class="viewcode-block" id="strategy_connected_sequential"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.coloring.strategy_connected_sequential.html#networkx.algorithms.coloring.strategy_connected_sequential">[docs]</a><span class="k">def</span> <span class="nf">strategy_connected_sequential</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">colors</span><span class="p">,</span> <span class="n">traversal</span><span class="o">=</span><span class="s2">"bfs"</span><span class="p">):</span> - <span class="sd">"""Returns an iterable over nodes in ``G`` in the order given by a</span> +<span class="w"> </span><span class="sd">"""Returns an iterable over nodes in ``G`` in the order given by a</span> <span class="sd"> breadth-first or depth-first traversal.</span> <span class="sd"> ``traversal`` must be one of the strings ``'dfs'`` or ``'bfs'``,</span> @@ -664,7 +664,7 @@ <div class="viewcode-block" id="strategy_saturation_largest_first"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.coloring.strategy_saturation_largest_first.html#networkx.algorithms.coloring.strategy_saturation_largest_first">[docs]</a><span class="k">def</span> <span class="nf">strategy_saturation_largest_first</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">colors</span><span class="p">):</span> - <span class="sd">"""Iterates over all the nodes of ``G`` in "saturation order" (also</span> +<span class="w"> </span><span class="sd">"""Iterates over all the nodes of ``G`` in "saturation order" (also</span> <span class="sd"> known as "DSATUR").</span> <span class="sd"> ``G`` is a NetworkX graph. ``colors`` is a dictionary mapping nodes of</span> @@ -725,7 +725,7 @@ <div class="viewcode-block" id="greedy_color"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.coloring.greedy_color.html#networkx.algorithms.coloring.greedy_color">[docs]</a><span class="k">def</span> <span class="nf">greedy_color</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">strategy</span><span class="o">=</span><span class="s2">"largest_first"</span><span class="p">,</span> <span class="n">interchange</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Color a graph using various strategies of greedy graph coloring.</span> +<span class="w"> </span><span class="sd">"""Color a graph using various strategies of greedy graph coloring.</span> <span class="sd"> Attempts to color a graph using as few colors as possible, where no</span> <span class="sd"> neighbours of a node can have same color as the node itself. The</span> @@ -901,7 +901,7 @@ <span class="k">def</span> <span class="nf">_greedy_coloring_with_interchange</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="p">):</span> - <span class="sd">"""Return a coloring for `orginal_graph` using interchange approach</span> +<span class="w"> </span><span class="sd">"""Return a coloring for `orginal_graph` using interchange approach</span> <span class="sd"> This procedure is an adaption of the algorithm described by [1]_,</span> <span class="sd"> and is an implementation of coloring with interchange. Please be</span> @@ -1075,7 +1075,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/communicability_alg.html b/_modules/networkx/algorithms/communicability_alg.html index 55c28089..1dfc1f31 100644 --- a/_modules/networkx/algorithms/communicability_alg.html +++ b/_modules/networkx/algorithms/communicability_alg.html @@ -473,7 +473,7 @@ <div class="viewcode-block" id="communicability"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.communicability_alg.communicability.html#networkx.algorithms.communicability_alg.communicability">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">communicability</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns communicability between all pairs of nodes in G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns communicability between all pairs of nodes in G.</span> <span class="sd"> The communicability between pairs of nodes in G is the sum of</span> <span class="sd"> walks of different lengths starting at node u and ending at node v.</span> @@ -554,7 +554,7 @@ <div class="viewcode-block" id="communicability_exp"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.communicability_alg.communicability_exp.html#networkx.algorithms.communicability_alg.communicability_exp">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">communicability_exp</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns communicability between all pairs of nodes in G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns communicability between all pairs of nodes in G.</span> <span class="sd"> Communicability between pair of node (u,v) of node in G is the sum of</span> <span class="sd"> walks of different lengths starting at node u and ending at node v.</span> @@ -673,7 +673,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/community/asyn_fluid.html b/_modules/networkx/algorithms/community/asyn_fluid.html index b5211f16..20e96907 100644 --- a/_modules/networkx/algorithms/community/asyn_fluid.html +++ b/_modules/networkx/algorithms/community/asyn_fluid.html @@ -475,7 +475,7 @@ <div class="viewcode-block" id="asyn_fluidc"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.community.asyn_fluid.asyn_fluidc.html#networkx.algorithms.community.asyn_fluid.asyn_fluidc">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">,</span> <span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">asyn_fluidc</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns communities in `G` as detected by Fluid Communities algorithm.</span> +<span class="w"> </span><span class="sd">"""Returns communities in `G` as detected by Fluid Communities algorithm.</span> <span class="sd"> The asynchronous fluid communities algorithm is described in</span> <span class="sd"> [1]_. The algorithm is based on the simple idea of fluids interacting</span> @@ -659,7 +659,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/community/centrality.html b/_modules/networkx/algorithms/community/centrality.html index 45de9736..9b254f8f 100644 --- a/_modules/networkx/algorithms/community/centrality.html +++ b/_modules/networkx/algorithms/community/centrality.html @@ -469,7 +469,7 @@ <div class="viewcode-block" id="girvan_newman"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.community.centrality.girvan_newman.html#networkx.algorithms.community.centrality.girvan_newman">[docs]</a><span class="k">def</span> <span class="nf">girvan_newman</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">most_valuable_edge</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Finds communities in a graph using the Girvan–Newman method.</span> +<span class="w"> </span><span class="sd">"""Finds communities in a graph using the Girvan–Newman method.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -592,7 +592,7 @@ <span class="k">if</span> <span class="n">most_valuable_edge</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> <span class="k">def</span> <span class="nf">most_valuable_edge</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the edge with the highest betweenness centrality</span> +<span class="w"> </span><span class="sd">"""Returns the edge with the highest betweenness centrality</span> <span class="sd"> in the graph `G`.</span> <span class="sd"> """</span> @@ -611,7 +611,7 @@ <span class="k">def</span> <span class="nf">_without_most_central_edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">most_valuable_edge</span><span class="p">):</span> - <span class="sd">"""Returns the connected components of the graph that results from</span> +<span class="w"> </span><span class="sd">"""Returns the connected components of the graph that results from</span> <span class="sd"> repeatedly removing the most "valuable" edge in the graph.</span> <span class="sd"> `G` must be a non-empty graph. This function modifies the graph `G`</span> @@ -682,7 +682,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/community/community_utils.html b/_modules/networkx/algorithms/community/community_utils.html index 45ed92e2..6fd1f51c 100644 --- a/_modules/networkx/algorithms/community/community_utils.html +++ b/_modules/networkx/algorithms/community/community_utils.html @@ -467,7 +467,7 @@ <div class="viewcode-block" id="is_partition"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.community.community_utils.is_partition.html#networkx.algorithms.community.community_utils.is_partition">[docs]</a><span class="k">def</span> <span class="nf">is_partition</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">communities</span><span class="p">):</span> - <span class="sd">"""Returns *True* if `communities` is a partition of the nodes of `G`.</span> +<span class="w"> </span><span class="sd">"""Returns *True* if `communities` is a partition of the nodes of `G`.</span> <span class="sd"> A partition of a universe set is a family of pairwise disjoint sets</span> <span class="sd"> whose union is the entire universe set.</span> @@ -539,7 +539,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/community/kclique.html b/_modules/networkx/algorithms/community/kclique.html index d7fec04a..22546db6 100644 --- a/_modules/networkx/algorithms/community/kclique.html +++ b/_modules/networkx/algorithms/community/kclique.html @@ -469,7 +469,7 @@ <div class="viewcode-block" id="k_clique_communities"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.community.kclique.k_clique_communities.html#networkx.algorithms.community.kclique.k_clique_communities">[docs]</a><span class="k">def</span> <span class="nf">k_clique_communities</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">cliques</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Find k-clique communities in graph using the percolation method.</span> +<span class="w"> </span><span class="sd">"""Find k-clique communities in graph using the percolation method.</span> <span class="sd"> A k-clique community is the union of all cliques of size k that</span> <span class="sd"> can be reached through adjacent (sharing k-1 nodes) k-cliques.</span> @@ -591,7 +591,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/community/kernighan_lin.html b/_modules/networkx/algorithms/community/kernighan_lin.html index f7bc53cc..19f3c947 100644 --- a/_modules/networkx/algorithms/community/kernighan_lin.html +++ b/_modules/networkx/algorithms/community/kernighan_lin.html @@ -473,7 +473,7 @@ <span class="k">def</span> <span class="nf">_kernighan_lin_sweep</span><span class="p">(</span><span class="n">edges</span><span class="p">,</span> <span class="n">side</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> This is a modified form of Kernighan-Lin, which moves single nodes at a</span> <span class="sd"> time, alternating between sides to keep the bisection balanced. We keep</span> <span class="sd"> two min-heaps of swap costs to make optimal-next-move selection fast.</span> @@ -506,7 +506,7 @@ <div class="viewcode-block" id="kernighan_lin_bisection"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.community.kernighan_lin.kernighan_lin_bisection.html#networkx.algorithms.community.kernighan_lin.kernighan_lin_bisection">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">kernighan_lin_bisection</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">partition</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Partition a graph into two blocks using the Kernighan–Lin</span> +<span class="w"> </span><span class="sd">"""Partition a graph into two blocks using the Kernighan–Lin</span> <span class="sd"> algorithm.</span> <span class="sd"> This algorithm partitions a network into two sets by iteratively</span> @@ -649,7 +649,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/community/label_propagation.html b/_modules/networkx/algorithms/community/label_propagation.html index eabd86e8..31376342 100644 --- a/_modules/networkx/algorithms/community/label_propagation.html +++ b/_modules/networkx/algorithms/community/label_propagation.html @@ -474,7 +474,7 @@ <div class="viewcode-block" id="asyn_lpa_communities"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.community.label_propagation.asyn_lpa_communities.html#networkx.algorithms.community.label_propagation.asyn_lpa_communities">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">asyn_lpa_communities</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns communities in `G` as detected by asynchronous label</span> +<span class="w"> </span><span class="sd">"""Returns communities in `G` as detected by asynchronous label</span> <span class="sd"> propagation.</span> <span class="sd"> The asynchronous label propagation algorithm is described in</span> @@ -570,7 +570,7 @@ <div class="viewcode-block" id="label_propagation_communities"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.community.label_propagation.label_propagation_communities.html#networkx.algorithms.community.label_propagation.label_propagation_communities">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">label_propagation_communities</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Generates community sets determined by label propagation</span> +<span class="w"> </span><span class="sd">"""Generates community sets determined by label propagation</span> <span class="sd"> Finds communities in `G` using a semi-synchronous label propagation</span> <span class="sd"> method [1]_. This method combines the advantages of both the synchronous</span> @@ -614,7 +614,7 @@ <span class="k">def</span> <span class="nf">_color_network</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Colors the network so that neighboring nodes all have distinct colors.</span> +<span class="w"> </span><span class="sd">"""Colors the network so that neighboring nodes all have distinct colors.</span> <span class="sd"> Returns a dict keyed by color to a set of nodes with that color.</span> <span class="sd"> """</span> @@ -629,7 +629,7 @@ <span class="k">def</span> <span class="nf">_labeling_complete</span><span class="p">(</span><span class="n">labeling</span><span class="p">,</span> <span class="n">G</span><span class="p">):</span> - <span class="sd">"""Determines whether or not LPA is done.</span> +<span class="w"> </span><span class="sd">"""Determines whether or not LPA is done.</span> <span class="sd"> Label propagation is complete when all nodes have a label that is</span> <span class="sd"> in the set of highest frequency labels amongst its neighbors.</span> @@ -642,7 +642,7 @@ <span class="k">def</span> <span class="nf">_most_frequent_labels</span><span class="p">(</span><span class="n">node</span><span class="p">,</span> <span class="n">labeling</span><span class="p">,</span> <span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns a set of all labels with maximum frequency in `labeling`.</span> +<span class="w"> </span><span class="sd">"""Returns a set of all labels with maximum frequency in `labeling`.</span> <span class="sd"> Input `labeling` should be a dict keyed by node to labels.</span> <span class="sd"> """</span> @@ -658,7 +658,7 @@ <span class="k">def</span> <span class="nf">_update_label</span><span class="p">(</span><span class="n">node</span><span class="p">,</span> <span class="n">labeling</span><span class="p">,</span> <span class="n">G</span><span class="p">):</span> - <span class="sd">"""Updates the label of a node using the Prec-Max tie breaking algorithm</span> +<span class="w"> </span><span class="sd">"""Updates the label of a node using the Prec-Max tie breaking algorithm</span> <span class="sd"> The algorithm is explained in: 'Community Detection via Semi-Synchronous</span> <span class="sd"> Label Propagation Algorithms' Cordasco and Gargano, 2011</span> @@ -721,7 +721,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/community/louvain.html b/_modules/networkx/algorithms/community/louvain.html index f8bd0603..89674161 100644 --- a/_modules/networkx/algorithms/community/louvain.html +++ b/_modules/networkx/algorithms/community/louvain.html @@ -477,7 +477,7 @@ <span class="k">def</span> <span class="nf">louvain_communities</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">resolution</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">threshold</span><span class="o">=</span><span class="mf">0.0000001</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Find the best partition of a graph using the Louvain Community Detection</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Find the best partition of a graph using the Louvain Community Detection</span> <span class="sd"> Algorithm.</span> <span class="sd"> Louvain Community Detection Algorithm is a simple method to extract the community</span> @@ -579,7 +579,7 @@ <span class="k">def</span> <span class="nf">louvain_partitions</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">resolution</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">threshold</span><span class="o">=</span><span class="mf">0.0000001</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Yields partitions for each level of the Louvain Community Detection Algorithm</span> +<span class="w"> </span><span class="sd">"""Yields partitions for each level of the Louvain Community Detection Algorithm</span> <span class="sd"> Louvain Community Detection Algorithm is a simple method to extract the community</span> <span class="sd"> structure of a network. This is a heuristic method based on modularity optimization. [1]_</span> @@ -657,7 +657,7 @@ <span class="k">def</span> <span class="nf">_one_level</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">partition</span><span class="p">,</span> <span class="n">resolution</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">is_directed</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Calculate one level of the Louvain partitions tree</span> +<span class="w"> </span><span class="sd">"""Calculate one level of the Louvain partitions tree</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -763,7 +763,7 @@ <span class="k">def</span> <span class="nf">_neighbor_weights</span><span class="p">(</span><span class="n">nbrs</span><span class="p">,</span> <span class="n">node2com</span><span class="p">):</span> - <span class="sd">"""Calculate weights between node and its neighbor communities.</span> +<span class="w"> </span><span class="sd">"""Calculate weights between node and its neighbor communities.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -780,7 +780,7 @@ <span class="k">def</span> <span class="nf">_gen_graph</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">partition</span><span class="p">):</span> - <span class="sd">"""Generate a new graph based on the partitions of a given graph"""</span> +<span class="w"> </span><span class="sd">"""Generate a new graph based on the partitions of a given graph"""</span> <span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="vm">__class__</span><span class="p">()</span> <span class="n">node2com</span> <span class="o">=</span> <span class="p">{}</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">part</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">partition</span><span class="p">):</span> @@ -800,7 +800,7 @@ <span class="k">def</span> <span class="nf">_convert_multigraph</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">is_directed</span><span class="p">):</span> - <span class="sd">"""Convert a Multigraph to normal Graph"""</span> +<span class="w"> </span><span class="sd">"""Convert a Multigraph to normal Graph"""</span> <span class="k">if</span> <span class="n">is_directed</span><span class="p">:</span> <span class="n">H</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">DiGraph</span><span class="p">()</span> <span class="k">else</span><span class="p">:</span> @@ -863,7 +863,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/community/lukes.html b/_modules/networkx/algorithms/community/lukes.html index ed442b61..a5912a24 100644 --- a/_modules/networkx/algorithms/community/lukes.html +++ b/_modules/networkx/algorithms/community/lukes.html @@ -490,7 +490,7 @@ <div class="viewcode-block" id="lukes_partitioning"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.community.lukes.lukes_partitioning.html#networkx.algorithms.community.lukes.lukes_partitioning">[docs]</a><span class="k">def</span> <span class="nf">lukes_partitioning</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">max_size</span><span class="p">,</span> <span class="n">node_weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">edge_weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Optimal partitioning of a weighted tree using the Lukes algorithm.</span> +<span class="w"> </span><span class="sd">"""Optimal partitioning of a weighted tree using the Lukes algorithm.</span> <span class="sd"> This algorithm partitions a connected, acyclic graph featuring integer</span> <span class="sd"> node weights and float edge weights. The resulting clusters are such</span> @@ -739,7 +739,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/community/modularity_max.html b/_modules/networkx/algorithms/community/modularity_max.html index 686585de..5d49fa9a 100644 --- a/_modules/networkx/algorithms/community/modularity_max.html +++ b/_modules/networkx/algorithms/community/modularity_max.html @@ -477,7 +477,7 @@ <span class="k">def</span> <span class="nf">_greedy_modularity_communities_generator</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">resolution</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Yield community partitions of G and the modularity change at each step.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Yield community partitions of G and the modularity change at each step.</span> <span class="sd"> This function performs Clauset-Newman-Moore greedy modularity maximization [2]_</span> <span class="sd"> At each step of the process it yields the change in modularity that will occur in</span> @@ -693,7 +693,7 @@ <span class="n">cutoff</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">best_n</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Find communities in G using greedy modularity maximization.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Find communities in G using greedy modularity maximization.</span> <span class="sd"> This function uses Clauset-Newman-Moore greedy modularity maximization [2]_</span> <span class="sd"> to find the community partition with the largest modularity.</span> @@ -817,7 +817,7 @@ <div class="viewcode-block" id="naive_greedy_modularity_communities"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.community.modularity_max.naive_greedy_modularity_communities.html#networkx.algorithms.community.modularity_max.naive_greedy_modularity_communities">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">naive_greedy_modularity_communities</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">resolution</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Find communities in G using greedy modularity maximization.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Find communities in G using greedy modularity maximization.</span> <span class="sd"> This implementation is O(n^4), much slower than alternatives, but it is</span> <span class="sd"> provided as an easy-to-understand reference implementation.</span> @@ -960,7 +960,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/community/quality.html b/_modules/networkx/algorithms/community/quality.html index 9f1862e1..42b8008b 100644 --- a/_modules/networkx/algorithms/community/quality.html +++ b/_modules/networkx/algorithms/community/quality.html @@ -478,7 +478,7 @@ <span class="k">class</span> <span class="nc">NotAPartition</span><span class="p">(</span><span class="n">NetworkXError</span><span class="p">):</span> - <span class="sd">"""Raised if a given collection is not a partition."""</span> +<span class="w"> </span><span class="sd">"""Raised if a given collection is not a partition."""</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G</span><span class="p">,</span> <span class="n">collection</span><span class="p">):</span> <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">collection</span><span class="si">}</span><span class="s2"> is not a valid partition of the graph </span><span class="si">{</span><span class="n">G</span><span class="si">}</span><span class="s2">"</span> @@ -486,7 +486,7 @@ <span class="k">def</span> <span class="nf">_require_partition</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">partition</span><span class="p">):</span> - <span class="sd">"""Decorator to check that a valid partition is input to a function</span> +<span class="w"> </span><span class="sd">"""Decorator to check that a valid partition is input to a function</span> <span class="sd"> Raises :exc:`networkx.NetworkXError` if the partition is not valid.</span> @@ -524,7 +524,7 @@ <span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">intra_community_edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">partition</span><span class="p">):</span> - <span class="sd">"""Returns the number of intra-community edges for a partition of `G`.</span> +<span class="w"> </span><span class="sd">"""Returns the number of intra-community edges for a partition of `G`.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -542,7 +542,7 @@ <span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">inter_community_edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">partition</span><span class="p">):</span> - <span class="sd">"""Returns the number of inter-community edges for a partition of `G`.</span> +<span class="w"> </span><span class="sd">"""Returns the number of inter-community edges for a partition of `G`.</span> <span class="sd"> according to the given</span> <span class="sd"> partition of the nodes of `G`.</span> @@ -573,7 +573,7 @@ <span class="k">def</span> <span class="nf">inter_community_non_edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">partition</span><span class="p">):</span> - <span class="sd">"""Returns the number of inter-community non-edges according to the</span> +<span class="w"> </span><span class="sd">"""Returns the number of inter-community non-edges according to the</span> <span class="sd"> given partition of the nodes of `G`.</span> <span class="sd"> Parameters</span> @@ -605,7 +605,7 @@ <div class="viewcode-block" id="modularity"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.community.quality.modularity.html#networkx.algorithms.community.quality.modularity">[docs]</a><span class="k">def</span> <span class="nf">modularity</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">communities</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">resolution</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the modularity of the given partition of the graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the modularity of the given partition of the graph.</span> <span class="sd"> Modularity is defined in [1]_ as</span> @@ -717,7 +717,7 @@ <div class="viewcode-block" id="partition_quality"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.community.quality.partition_quality.html#networkx.algorithms.community.quality.partition_quality">[docs]</a><span class="nd">@require_partition</span> <span class="k">def</span> <span class="nf">partition_quality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">partition</span><span class="p">):</span> - <span class="sd">"""Returns the coverage and performance of a partition of G.</span> +<span class="w"> </span><span class="sd">"""Returns the coverage and performance of a partition of G.</span> <span class="sd"> The *coverage* of a partition is the ratio of the number of</span> <span class="sd"> intra-community edges to the total number of edges in the graph.</span> @@ -854,7 +854,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/components/attracting.html b/_modules/networkx/algorithms/components/attracting.html index db3593fe..d994b60b 100644 --- a/_modules/networkx/algorithms/components/attracting.html +++ b/_modules/networkx/algorithms/components/attracting.html @@ -474,7 +474,7 @@ <div class="viewcode-block" id="attracting_components"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.attracting_components.html#networkx.algorithms.components.attracting_components">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">attracting_components</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Generates the attracting components in `G`.</span> +<span class="w"> </span><span class="sd">"""Generates the attracting components in `G`.</span> <span class="sd"> An attracting component in a directed graph `G` is a strongly connected</span> <span class="sd"> component with the property that a random walker on the graph will never</span> @@ -517,7 +517,7 @@ <div class="viewcode-block" id="number_attracting_components"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.number_attracting_components.html#networkx.algorithms.components.number_attracting_components">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">number_attracting_components</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the number of attracting components in `G`.</span> +<span class="w"> </span><span class="sd">"""Returns the number of attracting components in `G`.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -545,7 +545,7 @@ <div class="viewcode-block" id="is_attracting_component"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.is_attracting_component.html#networkx.algorithms.components.is_attracting_component">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_attracting_component</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns True if `G` consists of a single attracting component.</span> +<span class="w"> </span><span class="sd">"""Returns True if `G` consists of a single attracting component.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -623,7 +623,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/components/biconnected.html b/_modules/networkx/algorithms/components/biconnected.html index 73cb04ef..61be38ad 100644 --- a/_modules/networkx/algorithms/components/biconnected.html +++ b/_modules/networkx/algorithms/components/biconnected.html @@ -476,7 +476,7 @@ <div class="viewcode-block" id="is_biconnected"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.is_biconnected.html#networkx.algorithms.components.is_biconnected">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_biconnected</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns True if the graph is biconnected, False otherwise.</span> +<span class="w"> </span><span class="sd">"""Returns True if the graph is biconnected, False otherwise.</span> <span class="sd"> A graph is biconnected if, and only if, it cannot be disconnected by</span> <span class="sd"> removing only one node (and all edges incident on that node). If</span> @@ -556,7 +556,7 @@ <div class="viewcode-block" id="biconnected_component_edges"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.biconnected_component_edges.html#networkx.algorithms.components.biconnected_component_edges">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">biconnected_component_edges</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns a generator of lists of edges, one list for each biconnected</span> +<span class="w"> </span><span class="sd">"""Returns a generator of lists of edges, one list for each biconnected</span> <span class="sd"> component of the input graph.</span> <span class="sd"> Biconnected components are maximal subgraphs such that the removal of a</span> @@ -628,7 +628,7 @@ <div class="viewcode-block" id="biconnected_components"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.biconnected_components.html#networkx.algorithms.components.biconnected_components">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">biconnected_components</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns a generator of sets of nodes, one set for each biconnected</span> +<span class="w"> </span><span class="sd">"""Returns a generator of sets of nodes, one set for each biconnected</span> <span class="sd"> component of the graph</span> <span class="sd"> Biconnected components are maximal subgraphs such that the removal of a</span> @@ -720,7 +720,7 @@ <div class="viewcode-block" id="articulation_points"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.articulation_points.html#networkx.algorithms.components.articulation_points">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">articulation_points</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Yield the articulation points, or cut vertices, of a graph.</span> +<span class="w"> </span><span class="sd">"""Yield the articulation points, or cut vertices, of a graph.</span> <span class="sd"> An articulation point or cut vertex is any node whose removal (along with</span> <span class="sd"> all its incident edges) increases the number of connected components of</span> @@ -900,7 +900,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/components/connected.html b/_modules/networkx/algorithms/components/connected.html index e875fdbd..59ae2a4d 100644 --- a/_modules/networkx/algorithms/components/connected.html +++ b/_modules/networkx/algorithms/components/connected.html @@ -478,7 +478,7 @@ <div class="viewcode-block" id="connected_components"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.connected_components.html#networkx.algorithms.components.connected_components">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">connected_components</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Generate connected components.</span> +<span class="w"> </span><span class="sd">"""Generate connected components.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -532,7 +532,7 @@ <div class="viewcode-block" id="number_connected_components"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.number_connected_components.html#networkx.algorithms.components.number_connected_components">[docs]</a><span class="k">def</span> <span class="nf">number_connected_components</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the number of connected components.</span> +<span class="w"> </span><span class="sd">"""Returns the number of connected components.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -566,7 +566,7 @@ <div class="viewcode-block" id="is_connected"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.is_connected.html#networkx.algorithms.components.is_connected">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_connected</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns True if the graph is connected, False otherwise.</span> +<span class="w"> </span><span class="sd">"""Returns True if the graph is connected, False otherwise.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -611,7 +611,7 @@ <div class="viewcode-block" id="node_connected_component"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.node_connected_component.html#networkx.algorithms.components.node_connected_component">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">node_connected_component</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span> - <span class="sd">"""Returns the set of nodes in the component of graph containing node n.</span> +<span class="w"> </span><span class="sd">"""Returns the set of nodes in the component of graph containing node n.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -650,7 +650,7 @@ <span class="k">def</span> <span class="nf">_plain_bfs</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">):</span> - <span class="sd">"""A fast BFS node generator"""</span> +<span class="w"> </span><span class="sd">"""A fast BFS node generator"""</span> <span class="n">G_adj</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">adj</span> <span class="n">seen</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span> <span class="n">nextlevel</span> <span class="o">=</span> <span class="p">{</span><span class="n">source</span><span class="p">}</span> @@ -713,7 +713,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/components/semiconnected.html b/_modules/networkx/algorithms/components/semiconnected.html index 72b0e3bb..8ceab779 100644 --- a/_modules/networkx/algorithms/components/semiconnected.html +++ b/_modules/networkx/algorithms/components/semiconnected.html @@ -470,7 +470,7 @@ <div class="viewcode-block" id="is_semiconnected"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.is_semiconnected.html#networkx.algorithms.components.is_semiconnected">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_semiconnected</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">topo_order</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns True if the graph is semiconnected, False otherwise.</span> +<span class="w"> </span><span class="sd">"""Returns True if the graph is semiconnected, False otherwise.</span> <span class="sd"> A graph is semiconnected if, and only if, for any pair of nodes, either one</span> <span class="sd"> is reachable from the other, or they are mutually reachable.</span> @@ -576,7 +576,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/components/strongly_connected.html b/_modules/networkx/algorithms/components/strongly_connected.html index cc351e59..1232f536 100644 --- a/_modules/networkx/algorithms/components/strongly_connected.html +++ b/_modules/networkx/algorithms/components/strongly_connected.html @@ -478,7 +478,7 @@ <div class="viewcode-block" id="strongly_connected_components"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.strongly_connected_components.html#networkx.algorithms.components.strongly_connected_components">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">strongly_connected_components</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Generate nodes in strongly connected components of graph.</span> +<span class="w"> </span><span class="sd">"""Generate nodes in strongly connected components of graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -576,7 +576,7 @@ <div class="viewcode-block" id="kosaraju_strongly_connected_components"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.kosaraju_strongly_connected_components.html#networkx.algorithms.components.kosaraju_strongly_connected_components">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">kosaraju_strongly_connected_components</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Generate nodes in strongly connected components of graph.</span> +<span class="w"> </span><span class="sd">"""Generate nodes in strongly connected components of graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -637,7 +637,7 @@ <div class="viewcode-block" id="strongly_connected_components_recursive"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.strongly_connected_components_recursive.html#networkx.algorithms.components.strongly_connected_components_recursive">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">strongly_connected_components_recursive</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Generate nodes in strongly connected components of graph.</span> +<span class="w"> </span><span class="sd">"""Generate nodes in strongly connected components of graph.</span> <span class="sd"> Recursive version of algorithm.</span> @@ -730,7 +730,7 @@ <div class="viewcode-block" id="number_strongly_connected_components"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.number_strongly_connected_components.html#networkx.algorithms.components.number_strongly_connected_components">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">number_strongly_connected_components</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns number of strongly connected components in graph.</span> +<span class="w"> </span><span class="sd">"""Returns number of strongly connected components in graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -768,7 +768,7 @@ <div class="viewcode-block" id="is_strongly_connected"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.is_strongly_connected.html#networkx.algorithms.components.is_strongly_connected">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_strongly_connected</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Test directed graph for strong connectivity.</span> +<span class="w"> </span><span class="sd">"""Test directed graph for strong connectivity.</span> <span class="sd"> A directed graph is strongly connected if and only if every vertex in</span> <span class="sd"> the graph is reachable from every other vertex.</span> @@ -811,7 +811,7 @@ <span class="sd"> """</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXPointlessConcept</span><span class="p">(</span> - <span class="sd">"""Connectivity is undefined for the null graph."""</span> +<span class="w"> </span><span class="sd">"""Connectivity is undefined for the null graph."""</span> <span class="p">)</span> <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="nb">next</span><span class="p">(</span><span class="n">strongly_connected_components</span><span class="p">(</span><span class="n">G</span><span class="p">)))</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">G</span><span class="p">)</span></div> @@ -819,7 +819,7 @@ <div class="viewcode-block" id="condensation"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.condensation.html#networkx.algorithms.components.condensation">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">condensation</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">scc</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the condensation of G.</span> +<span class="w"> </span><span class="sd">"""Returns the condensation of G.</span> <span class="sd"> The condensation of G is the graph with each of the strongly connected</span> <span class="sd"> components contracted into a single node.</span> @@ -950,7 +950,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/components/weakly_connected.html b/_modules/networkx/algorithms/components/weakly_connected.html index d00efaf7..3e1b4d94 100644 --- a/_modules/networkx/algorithms/components/weakly_connected.html +++ b/_modules/networkx/algorithms/components/weakly_connected.html @@ -475,7 +475,7 @@ <div class="viewcode-block" id="weakly_connected_components"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.weakly_connected_components.html#networkx.algorithms.components.weakly_connected_components">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">weakly_connected_components</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Generate weakly connected components of G.</span> +<span class="w"> </span><span class="sd">"""Generate weakly connected components of G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -530,7 +530,7 @@ <div class="viewcode-block" id="number_weakly_connected_components"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.number_weakly_connected_components.html#networkx.algorithms.components.number_weakly_connected_components">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">number_weakly_connected_components</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the number of weakly connected components in G.</span> +<span class="w"> </span><span class="sd">"""Returns the number of weakly connected components in G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -569,7 +569,7 @@ <div class="viewcode-block" id="is_weakly_connected"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.components.is_weakly_connected.html#networkx.algorithms.components.is_weakly_connected">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_weakly_connected</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Test directed graph for weak connectivity.</span> +<span class="w"> </span><span class="sd">"""Test directed graph for weak connectivity.</span> <span class="sd"> A directed graph is weakly connected if and only if the graph</span> <span class="sd"> is connected when the direction of the edge between nodes is ignored.</span> @@ -618,14 +618,14 @@ <span class="sd"> """</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXPointlessConcept</span><span class="p">(</span> - <span class="sd">"""Connectivity is undefined for the null graph."""</span> +<span class="w"> </span><span class="sd">"""Connectivity is undefined for the null graph."""</span> <span class="p">)</span> <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="nb">next</span><span class="p">(</span><span class="n">weakly_connected_components</span><span class="p">(</span><span class="n">G</span><span class="p">)))</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">G</span><span class="p">)</span></div> <span class="k">def</span> <span class="nf">_plain_bfs</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">):</span> - <span class="sd">"""A fast BFS node generator</span> +<span class="w"> </span><span class="sd">"""A fast BFS node generator</span> <span class="sd"> The direction of the edge between nodes is ignored.</span> @@ -697,7 +697,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/connectivity/connectivity.html b/_modules/networkx/algorithms/connectivity/connectivity.html index 23d5b4f7..0d39d855 100644 --- a/_modules/networkx/algorithms/connectivity/connectivity.html +++ b/_modules/networkx/algorithms/connectivity/connectivity.html @@ -497,7 +497,7 @@ <div class="viewcode-block" id="local_node_connectivity"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.local_node_connectivity.html#networkx.algorithms.connectivity.connectivity.local_node_connectivity">[docs]</a><span class="k">def</span> <span class="nf">local_node_connectivity</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">auxiliary</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">residual</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Computes local node connectivity for nodes s and t.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Computes local node connectivity for nodes s and t.</span> <span class="sd"> Local node connectivity for two non adjacent nodes s and t is the</span> <span class="sd"> minimum number of nodes that must be removed (along with their incident</span> @@ -673,7 +673,7 @@ <div class="viewcode-block" id="node_connectivity"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.node_connectivity.html#networkx.algorithms.connectivity.connectivity.node_connectivity">[docs]</a><span class="k">def</span> <span class="nf">node_connectivity</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">t</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns node connectivity for a graph or digraph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns node connectivity for a graph or digraph G.</span> <span class="sd"> Node connectivity is equal to the minimum number of nodes that</span> <span class="sd"> must be removed to disconnect G or render it trivial. If source</span> @@ -813,7 +813,7 @@ <div class="viewcode-block" id="average_node_connectivity"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.average_node_connectivity.html#networkx.algorithms.connectivity.connectivity.average_node_connectivity">[docs]</a><span class="k">def</span> <span class="nf">average_node_connectivity</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the average connectivity of a graph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the average connectivity of a graph G.</span> <span class="sd"> The average connectivity `\bar{\kappa}` of a graph G is the average</span> <span class="sd"> of local node connectivity over all pairs of nodes of G [1]_ .</span> @@ -881,7 +881,7 @@ <div class="viewcode-block" id="all_pairs_node_connectivity"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.all_pairs_node_connectivity.html#networkx.algorithms.connectivity.connectivity.all_pairs_node_connectivity">[docs]</a><span class="k">def</span> <span class="nf">all_pairs_node_connectivity</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nbunch</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute node connectivity between all pairs of nodes of G.</span> +<span class="w"> </span><span class="sd">"""Compute node connectivity between all pairs of nodes of G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -950,7 +950,7 @@ <div class="viewcode-block" id="local_edge_connectivity"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.local_edge_connectivity.html#networkx.algorithms.connectivity.connectivity.local_edge_connectivity">[docs]</a><span class="k">def</span> <span class="nf">local_edge_connectivity</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">auxiliary</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">residual</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns local edge connectivity for nodes s and t in G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns local edge connectivity for nodes s and t in G.</span> <span class="sd"> Local edge connectivity for two nodes s and t is the minimum number</span> <span class="sd"> of edges that must be removed to disconnect them.</span> @@ -1109,7 +1109,7 @@ <div class="viewcode-block" id="edge_connectivity"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.edge_connectivity.html#networkx.algorithms.connectivity.connectivity.edge_connectivity">[docs]</a><span class="k">def</span> <span class="nf">edge_connectivity</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">t</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the edge connectivity of the graph or digraph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the edge connectivity of the graph or digraph G.</span> <span class="sd"> The edge connectivity is equal to the minimum number of edges that</span> <span class="sd"> must be removed to disconnect G or render it trivial. If source</span> @@ -1324,7 +1324,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/connectivity/cuts.html b/_modules/networkx/algorithms/connectivity/cuts.html index 543c02eb..56616899 100644 --- a/_modules/networkx/algorithms/connectivity/cuts.html +++ b/_modules/networkx/algorithms/connectivity/cuts.html @@ -485,7 +485,7 @@ <div class="viewcode-block" id="minimum_st_edge_cut"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_st_edge_cut.html#networkx.algorithms.connectivity.cuts.minimum_st_edge_cut">[docs]</a><span class="k">def</span> <span class="nf">minimum_st_edge_cut</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">auxiliary</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">residual</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the edges of the cut-set of a minimum (s, t)-cut.</span> +<span class="w"> </span><span class="sd">"""Returns the edges of the cut-set of a minimum (s, t)-cut.</span> <span class="sd"> This function returns the set of edges of minimum cardinality that,</span> <span class="sd"> if removed, would destroy all paths among source and target in G.</span> @@ -617,7 +617,7 @@ <div class="viewcode-block" id="minimum_st_node_cut"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_st_node_cut.html#networkx.algorithms.connectivity.cuts.minimum_st_node_cut">[docs]</a><span class="k">def</span> <span class="nf">minimum_st_node_cut</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">auxiliary</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">residual</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a set of nodes of minimum cardinality that disconnect source</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a set of nodes of minimum cardinality that disconnect source</span> <span class="sd"> from target in G.</span> <span class="sd"> This function returns the set of nodes of minimum cardinality that,</span> @@ -755,7 +755,7 @@ <div class="viewcode-block" id="minimum_node_cut"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_node_cut.html#networkx.algorithms.connectivity.cuts.minimum_node_cut">[docs]</a><span class="k">def</span> <span class="nf">minimum_node_cut</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">t</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a set of nodes of minimum cardinality that disconnects G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a set of nodes of minimum cardinality that disconnects G.</span> <span class="sd"> If source and target nodes are provided, this function returns the</span> <span class="sd"> set of nodes of minimum cardinality that, if removed, would destroy</span> @@ -900,7 +900,7 @@ <div class="viewcode-block" id="minimum_edge_cut"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_edge_cut.html#networkx.algorithms.connectivity.cuts.minimum_edge_cut">[docs]</a><span class="k">def</span> <span class="nf">minimum_edge_cut</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">t</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a set of edges of minimum cardinality that disconnects G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a set of edges of minimum cardinality that disconnects G.</span> <span class="sd"> If source and target nodes are provided, this function returns the</span> <span class="sd"> set of edges of minimum cardinality that, if removed, would break</span> @@ -1111,7 +1111,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/connectivity/disjoint_paths.html b/_modules/networkx/algorithms/connectivity/disjoint_paths.html index 2aa39364..9c0471c4 100644 --- a/_modules/networkx/algorithms/connectivity/disjoint_paths.html +++ b/_modules/networkx/algorithms/connectivity/disjoint_paths.html @@ -485,7 +485,7 @@ <div class="viewcode-block" id="edge_disjoint_paths"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.disjoint_paths.edge_disjoint_paths.html#networkx.algorithms.connectivity.disjoint_paths.edge_disjoint_paths">[docs]</a><span class="k">def</span> <span class="nf">edge_disjoint_paths</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">auxiliary</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">residual</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Returns the edges disjoint paths between source and target.</span> +<span class="w"> </span><span class="sd">"""Returns the edges disjoint paths between source and target.</span> <span class="sd"> Edge disjoint paths are paths that do not share any edge. The</span> <span class="sd"> number of edge disjoint paths between source and target is equal</span> @@ -689,7 +689,7 @@ <div class="viewcode-block" id="node_disjoint_paths"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.disjoint_paths.node_disjoint_paths.html#networkx.algorithms.connectivity.disjoint_paths.node_disjoint_paths">[docs]</a><span class="k">def</span> <span class="nf">node_disjoint_paths</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">auxiliary</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">residual</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Computes node disjoint paths between source and target.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Computes node disjoint paths between source and target.</span> <span class="sd"> Node disjoint paths are paths that only share their first and last</span> <span class="sd"> nodes. The number of node independent paths between two nodes is</span> @@ -902,7 +902,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/connectivity/edge_augmentation.html b/_modules/networkx/algorithms/connectivity/edge_augmentation.html index 61f238bf..84d8553c 100644 --- a/_modules/networkx/algorithms/connectivity/edge_augmentation.html +++ b/_modules/networkx/algorithms/connectivity/edge_augmentation.html @@ -488,7 +488,7 @@ <div class="viewcode-block" id="is_k_edge_connected"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.is_k_edge_connected.html#networkx.algorithms.connectivity.edge_augmentation.is_k_edge_connected">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_k_edge_connected</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> - <span class="sd">"""Tests to see if a graph is k-edge-connected.</span> +<span class="w"> </span><span class="sd">"""Tests to see if a graph is k-edge-connected.</span> <span class="sd"> Is it impossible to disconnect the graph by removing fewer than k edges?</span> <span class="sd"> If so, then G is k-edge-connected.</span> @@ -538,7 +538,7 @@ <div class="viewcode-block" id="is_locally_k_edge_connected"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.is_locally_k_edge_connected.html#networkx.algorithms.connectivity.edge_augmentation.is_locally_k_edge_connected">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_locally_k_edge_connected</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> - <span class="sd">"""Tests to see if an edge in a graph is locally k-edge-connected.</span> +<span class="w"> </span><span class="sd">"""Tests to see if an edge in a graph is locally k-edge-connected.</span> <span class="sd"> Is it impossible to disconnect s and t by removing fewer than k edges?</span> <span class="sd"> If so, then s and t are locally k-edge-connected in G.</span> @@ -595,7 +595,7 @@ <div class="viewcode-block" id="k_edge_augmentation"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation.html#networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">k_edge_augmentation</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">avail</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">partial</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Finds set of edges to k-edge-connect G.</span> +<span class="w"> </span><span class="sd">"""Finds set of edges to k-edge-connect G.</span> <span class="sd"> Adding edges from the augmentation to G make it impossible to disconnect G</span> <span class="sd"> unless k or more edges are removed. This function uses the most efficient</span> @@ -708,7 +708,7 @@ <span class="k">if</span> <span class="n">k</span> <span class="o"><=</span> <span class="mi">0</span><span class="p">:</span> <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s2">"k must be a positive integer, not </span><span class="si">{</span><span class="n">k</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> <span class="k">elif</span> <span class="n">G</span><span class="o">.</span><span class="n">number_of_nodes</span><span class="p">()</span> <span class="o"><</span> <span class="n">k</span> <span class="o">+</span> <span class="mi">1</span><span class="p">:</span> - <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"impossible to </span><span class="si">{</span><span class="n">k</span><span class="si">}</span><span class="s2"> connect in graph with less than </span><span class="si">{</span><span class="n">k</span> <span class="o">+</span> <span class="mi">1</span><span class="si">}</span><span class="s2"> nodes"</span> + <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"impossible to </span><span class="si">{</span><span class="n">k</span><span class="si">}</span><span class="s2"> connect in graph with less than </span><span class="si">{</span><span class="n">k</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">1</span><span class="si">}</span><span class="s2"> nodes"</span> <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXUnfeasible</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span> <span class="k">elif</span> <span class="n">avail</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="n">avail</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">nx</span><span class="o">.</span><span class="n">is_k_edge_connected</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> @@ -745,7 +745,7 @@ <span class="k">def</span> <span class="nf">partial_k_edge_augmentation</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">avail</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Finds augmentation that k-edge-connects as much of the graph as possible.</span> +<span class="w"> </span><span class="sd">"""Finds augmentation that k-edge-connects as much of the graph as possible.</span> <span class="sd"> When a k-edge-augmentation is not possible, we can still try to find a</span> <span class="sd"> small set of edges that partially k-edge-connects as much of the graph as</span> @@ -798,7 +798,7 @@ <span class="sd"> """</span> <span class="k">def</span> <span class="nf">_edges_between_disjoint</span><span class="p">(</span><span class="n">H</span><span class="p">,</span> <span class="n">only1</span><span class="p">,</span> <span class="n">only2</span><span class="p">):</span> - <span class="sd">"""finds edges between disjoint nodes"""</span> +<span class="w"> </span><span class="sd">"""finds edges between disjoint nodes"""</span> <span class="n">only1_adj</span> <span class="o">=</span> <span class="p">{</span><span class="n">u</span><span class="p">:</span> <span class="nb">set</span><span class="p">(</span><span class="n">H</span><span class="o">.</span><span class="n">adj</span><span class="p">[</span><span class="n">u</span><span class="p">])</span> <span class="k">for</span> <span class="n">u</span> <span class="ow">in</span> <span class="n">only1</span><span class="p">}</span> <span class="k">for</span> <span class="n">u</span><span class="p">,</span> <span class="n">neighbs</span> <span class="ow">in</span> <span class="n">only1_adj</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> <span class="c1"># Find the neighbors of u in only1 that are also in only2</span> @@ -847,7 +847,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">one_edge_augmentation</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">avail</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">partial</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Finds minimum weight set of edges to connect G.</span> +<span class="w"> </span><span class="sd">"""Finds minimum weight set of edges to connect G.</span> <span class="sd"> Equivalent to :func:`k_edge_augmentation` when k=1. Adding the resulting</span> <span class="sd"> edges to G will make it 1-edge-connected. The solution is optimal for both</span> @@ -901,7 +901,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">bridge_augmentation</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">avail</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Finds the a set of edges that bridge connects G.</span> +<span class="w"> </span><span class="sd">"""Finds the a set of edges that bridge connects G.</span> <span class="sd"> Equivalent to :func:`k_edge_augmentation` when k=2, and partial=False.</span> <span class="sd"> Adding the resulting edges to G will make it 2-edge-connected. If no</span> @@ -953,12 +953,12 @@ <span class="k">def</span> <span class="nf">_ordered</span><span class="p">(</span><span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Returns the nodes in an undirected edge in lower-triangular order"""</span> +<span class="w"> </span><span class="sd">"""Returns the nodes in an undirected edge in lower-triangular order"""</span> <span class="k">return</span> <span class="p">(</span><span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">)</span> <span class="k">if</span> <span class="n">u</span> <span class="o"><</span> <span class="n">v</span> <span class="k">else</span> <span class="p">(</span><span class="n">v</span><span class="p">,</span> <span class="n">u</span><span class="p">)</span> <span class="k">def</span> <span class="nf">_unpack_available_edges</span><span class="p">(</span><span class="n">avail</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">G</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Helper to separate avail into edges and corresponding weights"""</span> +<span class="w"> </span><span class="sd">"""Helper to separate avail into edges and corresponding weights"""</span> <span class="k">if</span> <span class="n">weight</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> <span class="n">weight</span> <span class="o">=</span> <span class="s2">"weight"</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">avail</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span> @@ -987,7 +987,7 @@ <span class="k">def</span> <span class="nf">_lightest_meta_edges</span><span class="p">(</span><span class="n">mapping</span><span class="p">,</span> <span class="n">avail_uv</span><span class="p">,</span> <span class="n">avail_w</span><span class="p">):</span> - <span class="sd">"""Maps available edges in the original graph to edges in the metagraph.</span> +<span class="w"> </span><span class="sd">"""Maps available edges in the original graph to edges in the metagraph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1036,7 +1036,7 @@ <span class="k">def</span> <span class="nf">unconstrained_one_edge_augmentation</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Finds the smallest set of edges to connect G.</span> +<span class="w"> </span><span class="sd">"""Finds the smallest set of edges to connect G.</span> <span class="sd"> This is a variant of the unweighted MST problem.</span> <span class="sd"> If G is not empty, a feasible solution always exists.</span> @@ -1078,7 +1078,7 @@ <span class="k">def</span> <span class="nf">weighted_one_edge_augmentation</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">avail</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">partial</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Finds the minimum weight set of edges to connect G if one exists.</span> +<span class="w"> </span><span class="sd">"""Finds the minimum weight set of edges to connect G if one exists.</span> <span class="sd"> This is a variant of the weighted MST problem.</span> @@ -1146,7 +1146,7 @@ <span class="k">def</span> <span class="nf">unconstrained_bridge_augmentation</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Finds an optimal 2-edge-augmentation of G using the fewest edges.</span> +<span class="w"> </span><span class="sd">"""Finds an optimal 2-edge-augmentation of G using the fewest edges.</span> <span class="sd"> This is an implementation of the algorithm detailed in [1]_.</span> <span class="sd"> The basic idea is to construct a meta-graph of bridge-ccs, connect leaf</span> @@ -1300,7 +1300,7 @@ <span class="k">def</span> <span class="nf">weighted_bridge_augmentation</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">avail</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Finds an approximate min-weight 2-edge-augmentation of G.</span> +<span class="w"> </span><span class="sd">"""Finds an approximate min-weight 2-edge-augmentation of G.</span> <span class="sd"> This is an implementation of the approximation algorithm detailed in [1]_.</span> <span class="sd"> It chooses a set of edges from avail to add to G that renders it</span> @@ -1470,7 +1470,7 @@ <span class="k">def</span> <span class="nf">_minimum_rooted_branching</span><span class="p">(</span><span class="n">D</span><span class="p">,</span> <span class="n">root</span><span class="p">):</span> - <span class="sd">"""Helper function to compute a minimum rooted branching (aka rooted</span> +<span class="w"> </span><span class="sd">"""Helper function to compute a minimum rooted branching (aka rooted</span> <span class="sd"> arborescence)</span> <span class="sd"> Before the branching can be computed, the directed graph must be rooted by</span> @@ -1494,7 +1494,7 @@ <span class="k">def</span> <span class="nf">collapse</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">grouped_nodes</span><span class="p">):</span> - <span class="sd">"""Collapses each group of nodes into a single node.</span> +<span class="w"> </span><span class="sd">"""Collapses each group of nodes into a single node.</span> <span class="sd"> This is similar to condensation, but works on undirected graphs.</span> @@ -1565,7 +1565,7 @@ <span class="k">def</span> <span class="nf">complement_edges</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns only the edges in the complement of G</span> +<span class="w"> </span><span class="sd">"""Returns only the edges in the complement of G</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1602,7 +1602,7 @@ <span class="k">def</span> <span class="nf">_compat_shuffle</span><span class="p">(</span><span class="n">rng</span><span class="p">,</span> <span class="nb">input</span><span class="p">):</span> - <span class="sd">"""wrapper around rng.shuffle for python 2 compatibility reasons"""</span> +<span class="w"> </span><span class="sd">"""wrapper around rng.shuffle for python 2 compatibility reasons"""</span> <span class="n">rng</span><span class="o">.</span><span class="n">shuffle</span><span class="p">(</span><span class="nb">input</span><span class="p">)</span> @@ -1610,7 +1610,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">greedy_k_edge_augmentation</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">avail</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Greedy algorithm for finding a k-edge-augmentation</span> +<span class="w"> </span><span class="sd">"""Greedy algorithm for finding a k-edge-augmentation</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1768,7 +1768,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/connectivity/edge_kcomponents.html b/_modules/networkx/algorithms/connectivity/edge_kcomponents.html index 8623023f..e8794442 100644 --- a/_modules/networkx/algorithms/connectivity/edge_kcomponents.html +++ b/_modules/networkx/algorithms/connectivity/edge_kcomponents.html @@ -488,7 +488,7 @@ <div class="viewcode-block" id="k_edge_components"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.k_edge_components.html#networkx.algorithms.connectivity.edge_kcomponents.k_edge_components">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">k_edge_components</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> - <span class="sd">"""Generates nodes in each maximal k-edge-connected component in G.</span> +<span class="w"> </span><span class="sd">"""Generates nodes in each maximal k-edge-connected component in G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -571,7 +571,7 @@ <div class="viewcode-block" id="k_edge_subgraphs"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.k_edge_subgraphs.html#networkx.algorithms.connectivity.edge_kcomponents.k_edge_subgraphs">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">k_edge_subgraphs</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> - <span class="sd">"""Generates nodes in each maximal k-edge-connected subgraph in G.</span> +<span class="w"> </span><span class="sd">"""Generates nodes in each maximal k-edge-connected subgraph in G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -648,7 +648,7 @@ <span class="k">def</span> <span class="nf">_k_edge_subgraphs_nodes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> - <span class="sd">"""Helper to get the nodes from the subgraphs.</span> +<span class="w"> </span><span class="sd">"""Helper to get the nodes from the subgraphs.</span> <span class="sd"> This allows k_edge_subgraphs to return a generator.</span> <span class="sd"> """</span> @@ -659,7 +659,7 @@ <div class="viewcode-block" id="bridge_components"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.bridge_components.html#networkx.algorithms.connectivity.edge_kcomponents.bridge_components">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">bridge_components</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Finds all bridge-connected components G.</span> +<span class="w"> </span><span class="sd">"""Finds all bridge-connected components G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -700,7 +700,7 @@ <div class="viewcode-block" id="EdgeComponentAuxGraph"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.html#networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph">[docs]</a><span class="k">class</span> <span class="nc">EdgeComponentAuxGraph</span><span class="p">:</span> - <span class="sa">r</span><span class="sd">"""A simple algorithm to find all k-edge-connected components in a graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""A simple algorithm to find all k-edge-connected components in a graph.</span> <span class="sd"> Constructing the AuxillaryGraph (which may take some time) allows for the</span> <span class="sd"> k-edge-ccs to be found in linear time for arbitrary k.</span> @@ -774,7 +774,7 @@ <span class="c1"># @not_implemented_for('multigraph') # TODO: fix decor for classmethods</span> <div class="viewcode-block" id="EdgeComponentAuxGraph.construct"><a class="viewcode-back" href="../../../../reference/algorithms/generated/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.construct.html#networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.construct">[docs]</a> <span class="nd">@classmethod</span> <span class="k">def</span> <span class="nf">construct</span><span class="p">(</span><span class="n">EdgeComponentAuxGraph</span><span class="p">,</span> <span class="n">G</span><span class="p">):</span> - <span class="sd">"""Builds an auxiliary graph encoding edge-connectivity between nodes.</span> +<span class="w"> </span><span class="sd">"""Builds an auxiliary graph encoding edge-connectivity between nodes.</span> <span class="sd"> Notes</span> <span class="sd"> -----</span> @@ -841,7 +841,7 @@ <span class="k">return</span> <span class="bp">self</span></div> <div class="viewcode-block" id="EdgeComponentAuxGraph.k_edge_components"><a class="viewcode-back" href="../../../../reference/algorithms/generated/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.k_edge_components.html#networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.k_edge_components">[docs]</a> <span class="k">def</span> <span class="nf">k_edge_components</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> - <span class="sd">"""Queries the auxiliary graph for k-edge-connected components.</span> +<span class="w"> </span><span class="sd">"""Queries the auxiliary graph for k-edge-connected components.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -874,7 +874,7 @@ <span class="k">yield from</span> <span class="n">nx</span><span class="o">.</span><span class="n">connected_components</span><span class="p">(</span><span class="n">R</span><span class="p">)</span></div> <div class="viewcode-block" id="EdgeComponentAuxGraph.k_edge_subgraphs"><a class="viewcode-back" href="../../../../reference/algorithms/generated/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.k_edge_subgraphs.html#networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.k_edge_subgraphs">[docs]</a> <span class="k">def</span> <span class="nf">k_edge_subgraphs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> - <span class="sd">"""Queries the auxiliary graph for k-edge-connected subgraphs.</span> +<span class="w"> </span><span class="sd">"""Queries the auxiliary graph for k-edge-connected subgraphs.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -919,7 +919,7 @@ <span class="k">def</span> <span class="nf">_low_degree_nodes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">nbunch</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Helper for finding nodes with degree less than k."""</span> +<span class="w"> </span><span class="sd">"""Helper for finding nodes with degree less than k."""</span> <span class="c1"># Nodes with degree less than k cannot be k-edge-connected.</span> <span class="k">if</span> <span class="n">G</span><span class="o">.</span><span class="n">is_directed</span><span class="p">():</span> <span class="c1"># Consider both in and out degree in the directed case</span> @@ -940,7 +940,7 @@ <span class="k">def</span> <span class="nf">_high_degree_components</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> - <span class="sd">"""Helper for filtering components that can't be k-edge-connected.</span> +<span class="w"> </span><span class="sd">"""Helper for filtering components that can't be k-edge-connected.</span> <span class="sd"> Removes and generates each node with degree less than k. Then generates</span> <span class="sd"> remaining components where all nodes have degree at least k.</span> @@ -965,7 +965,7 @@ <span class="k">def</span> <span class="nf">general_k_edge_subgraphs</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> - <span class="sd">"""General algorithm to find all maximal k-edge-connected subgraphs in G.</span> +<span class="w"> </span><span class="sd">"""General algorithm to find all maximal k-edge-connected subgraphs in G.</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> @@ -1093,7 +1093,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/connectivity/kcomponents.html b/_modules/networkx/algorithms/connectivity/kcomponents.html index 693dcc41..193495fe 100644 --- a/_modules/networkx/algorithms/connectivity/kcomponents.html +++ b/_modules/networkx/algorithms/connectivity/kcomponents.html @@ -481,7 +481,7 @@ <div class="viewcode-block" id="k_components"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.kcomponents.k_components.html#networkx.algorithms.connectivity.kcomponents.k_components">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">k_components</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the k-component structure of a graph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the k-component structure of a graph G.</span> <span class="sd"> A `k`-component is a maximal subgraph of a graph G that has, at least,</span> <span class="sd"> node connectivity `k`: we need to remove at least `k` nodes to break it</span> @@ -618,7 +618,7 @@ <span class="k">def</span> <span class="nf">_consolidate</span><span class="p">(</span><span class="n">sets</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> - <span class="sd">"""Merge sets that share k or more elements.</span> +<span class="w"> </span><span class="sd">"""Merge sets that share k or more elements.</span> <span class="sd"> See: http://rosettacode.org/wiki/Set_consolidation</span> @@ -736,7 +736,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/connectivity/kcutsets.html b/_modules/networkx/algorithms/connectivity/kcutsets.html index 986e1abe..c9190cb6 100644 --- a/_modules/networkx/algorithms/connectivity/kcutsets.html +++ b/_modules/networkx/algorithms/connectivity/kcutsets.html @@ -485,7 +485,7 @@ <div class="viewcode-block" id="all_node_cuts"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.kcutsets.all_node_cuts.html#networkx.algorithms.connectivity.kcutsets.all_node_cuts">[docs]</a><span class="k">def</span> <span class="nf">all_node_cuts</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns all minimum k cutsets of an undirected graph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns all minimum k cutsets of an undirected graph G.</span> <span class="sd"> This implementation is based on Kanevsky's algorithm [1]_ for finding all</span> <span class="sd"> minimum-size node cut-sets of an undirected graph G; ie the set (or sets)</span> @@ -685,7 +685,7 @@ <span class="k">def</span> <span class="nf">_is_separating_set</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">cut</span><span class="p">):</span> - <span class="sd">"""Assumes that the input graph is connected"""</span> +<span class="w"> </span><span class="sd">"""Assumes that the input graph is connected"""</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">cut</span><span class="p">)</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">:</span> <span class="k">return</span> <span class="kc">True</span> @@ -744,7 +744,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/connectivity/stoerwagner.html b/_modules/networkx/algorithms/connectivity/stoerwagner.html index d13be75d..f46c1ec0 100644 --- a/_modules/networkx/algorithms/connectivity/stoerwagner.html +++ b/_modules/networkx/algorithms/connectivity/stoerwagner.html @@ -476,7 +476,7 @@ <div class="viewcode-block" id="stoer_wagner"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.stoerwagner.stoer_wagner.html#networkx.algorithms.connectivity.stoerwagner.stoer_wagner">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">stoer_wagner</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">heap</span><span class="o">=</span><span class="n">BinaryHeap</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the weighted minimum edge cut using the Stoer-Wagner algorithm.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the weighted minimum edge cut using the Stoer-Wagner algorithm.</span> <span class="sd"> Determine the minimum edge cut of a connected graph using the</span> <span class="sd"> Stoer-Wagner algorithm. In weighted cases, all weights must be</span> @@ -661,7 +661,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/connectivity/utils.html b/_modules/networkx/algorithms/connectivity/utils.html index 975084fc..a1a59b07 100644 --- a/_modules/networkx/algorithms/connectivity/utils.html +++ b/_modules/networkx/algorithms/connectivity/utils.html @@ -470,7 +470,7 @@ <div class="viewcode-block" id="build_auxiliary_node_connectivity"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.utils.build_auxiliary_node_connectivity.html#networkx.algorithms.connectivity.utils.build_auxiliary_node_connectivity">[docs]</a><span class="k">def</span> <span class="nf">build_auxiliary_node_connectivity</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Creates a directed graph D from an undirected graph G to compute flow</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Creates a directed graph D from an undirected graph G to compute flow</span> <span class="sd"> based node connectivity.</span> <span class="sd"> For an undirected graph G having `n` nodes and `m` edges we derive a</span> @@ -522,7 +522,7 @@ <div class="viewcode-block" id="build_auxiliary_edge_connectivity"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.connectivity.utils.build_auxiliary_edge_connectivity.html#networkx.algorithms.connectivity.utils.build_auxiliary_edge_connectivity">[docs]</a><span class="k">def</span> <span class="nf">build_auxiliary_edge_connectivity</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Auxiliary digraph for computing flow based edge connectivity</span> +<span class="w"> </span><span class="sd">"""Auxiliary digraph for computing flow based edge connectivity</span> <span class="sd"> If the input graph is undirected, we replace each edge (`u`,`v`) with</span> <span class="sd"> two reciprocal arcs (`u`, `v`) and (`v`, `u`) and then we set the attribute</span> @@ -597,7 +597,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/core.html b/_modules/networkx/algorithms/core.html index 8a1c3119..68607fce 100644 --- a/_modules/networkx/algorithms/core.html +++ b/_modules/networkx/algorithms/core.html @@ -509,7 +509,7 @@ <div class="viewcode-block" id="core_number"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.core.core_number.html#networkx.algorithms.core.core_number">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">core_number</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the core number for each vertex.</span> +<span class="w"> </span><span class="sd">"""Returns the core number for each vertex.</span> <span class="sd"> A k-core is a maximal subgraph that contains nodes of degree k or more.</span> @@ -579,7 +579,7 @@ <span class="k">def</span> <span class="nf">_core_subgraph</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k_filter</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">core</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the subgraph induced by nodes passing filter `k_filter`.</span> +<span class="w"> </span><span class="sd">"""Returns the subgraph induced by nodes passing filter `k_filter`.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -607,7 +607,7 @@ <div class="viewcode-block" id="k_core"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.core.k_core.html#networkx.algorithms.core.k_core">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">k_core</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">core_number</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the k-core of G.</span> +<span class="w"> </span><span class="sd">"""Returns the k-core of G.</span> <span class="sd"> A k-core is a maximal subgraph that contains nodes of degree k or more.</span> @@ -659,7 +659,7 @@ <div class="viewcode-block" id="k_shell"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.core.k_shell.html#networkx.algorithms.core.k_shell">[docs]</a><span class="k">def</span> <span class="nf">k_shell</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">core_number</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the k-shell of G.</span> +<span class="w"> </span><span class="sd">"""Returns the k-shell of G.</span> <span class="sd"> The k-shell is the subgraph induced by nodes with core number k.</span> <span class="sd"> That is, nodes in the k-core that are not in the (k+1)-core.</span> @@ -718,7 +718,7 @@ <div class="viewcode-block" id="k_crust"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.core.k_crust.html#networkx.algorithms.core.k_crust">[docs]</a><span class="k">def</span> <span class="nf">k_crust</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">core_number</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the k-crust of G.</span> +<span class="w"> </span><span class="sd">"""Returns the k-crust of G.</span> <span class="sd"> The k-crust is the graph G with the edges of the k-core removed</span> <span class="sd"> and isolated nodes found after the removal of edges are also removed.</span> @@ -777,7 +777,7 @@ <div class="viewcode-block" id="k_corona"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.core.k_corona.html#networkx.algorithms.core.k_corona">[docs]</a><span class="k">def</span> <span class="nf">k_corona</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">core_number</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the k-corona of G.</span> +<span class="w"> </span><span class="sd">"""Returns the k-corona of G.</span> <span class="sd"> The k-corona is the subgraph of nodes in the k-core which have</span> <span class="sd"> exactly k neighbours in the k-core.</span> @@ -834,7 +834,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">k_truss</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> - <span class="sd">"""Returns the k-truss of `G`.</span> +<span class="w"> </span><span class="sd">"""Returns the k-truss of `G`.</span> <span class="sd"> The k-truss is the maximal induced subgraph of `G` which contains at least</span> <span class="sd"> three vertices where every edge is incident to at least `k-2` triangles.</span> @@ -903,7 +903,7 @@ <div class="viewcode-block" id="onion_layers"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.core.onion_layers.html#networkx.algorithms.core.onion_layers">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">onion_layers</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the layer of each vertex in an onion decomposition of the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the layer of each vertex in an onion decomposition of the graph.</span> <span class="sd"> The onion decomposition refines the k-core decomposition by providing</span> <span class="sd"> information on the internal organization of each k-shell. It is usually</span> @@ -1046,7 +1046,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/covering.html b/_modules/networkx/algorithms/covering.html index b3927816..e8efd5fe 100644 --- a/_modules/networkx/algorithms/covering.html +++ b/_modules/networkx/algorithms/covering.html @@ -475,7 +475,7 @@ <div class="viewcode-block" id="min_edge_cover"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.covering.min_edge_cover.html#networkx.algorithms.covering.min_edge_cover">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">min_edge_cover</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">matching_algorithm</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the min cardinality edge cover of the graph as a set of edges.</span> +<span class="w"> </span><span class="sd">"""Returns the min cardinality edge cover of the graph as a set of edges.</span> <span class="sd"> A smallest edge cover can be found in polynomial time by finding</span> <span class="sd"> a maximum matching and extending it greedily so that all nodes</span> @@ -569,7 +569,7 @@ <div class="viewcode-block" id="is_edge_cover"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.covering.is_edge_cover.html#networkx.algorithms.covering.is_edge_cover">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_edge_cover</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">cover</span><span class="p">):</span> - <span class="sd">"""Decides whether a set of edges is a valid edge cover of the graph.</span> +<span class="w"> </span><span class="sd">"""Decides whether a set of edges is a valid edge cover of the graph.</span> <span class="sd"> Given a set of edges, whether it is an edge covering can</span> <span class="sd"> be decided if we just check whether all nodes of the graph</span> @@ -652,7 +652,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/cuts.html b/_modules/networkx/algorithms/cuts.html index 14508e1c..1dfbeef8 100644 --- a/_modules/networkx/algorithms/cuts.html +++ b/_modules/networkx/algorithms/cuts.html @@ -486,7 +486,7 @@ <div class="viewcode-block" id="cut_size"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cuts.cut_size.html#networkx.algorithms.cuts.cut_size">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">cut_size</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">S</span><span class="p">,</span> <span class="n">T</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the size of the cut between two sets of nodes.</span> +<span class="w"> </span><span class="sd">"""Returns the size of the cut between two sets of nodes.</span> <span class="sd"> A *cut* is a partition of the nodes of a graph into two sets. The</span> <span class="sd"> *cut size* is the sum of the weights of the edges "between" the two</span> @@ -549,7 +549,7 @@ <div class="viewcode-block" id="volume"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cuts.volume.html#networkx.algorithms.cuts.volume">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">volume</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">S</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the volume of a set of nodes.</span> +<span class="w"> </span><span class="sd">"""Returns the volume of a set of nodes.</span> <span class="sd"> The *volume* of a set *S* is the sum of the (out-)degrees of nodes</span> <span class="sd"> in *S* (taking into account parallel edges in multigraphs). [1]</span> @@ -592,7 +592,7 @@ <div class="viewcode-block" id="normalized_cut_size"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cuts.normalized_cut_size.html#networkx.algorithms.cuts.normalized_cut_size">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">normalized_cut_size</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">S</span><span class="p">,</span> <span class="n">T</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the normalized size of the cut between two sets of nodes.</span> +<span class="w"> </span><span class="sd">"""Returns the normalized size of the cut between two sets of nodes.</span> <span class="sd"> The *normalized cut size* is the cut size times the sum of the</span> <span class="sd"> reciprocal sizes of the volumes of the two sets. [1]</span> @@ -645,7 +645,7 @@ <div class="viewcode-block" id="conductance"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cuts.conductance.html#networkx.algorithms.cuts.conductance">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">conductance</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">S</span><span class="p">,</span> <span class="n">T</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the conductance of two sets of nodes.</span> +<span class="w"> </span><span class="sd">"""Returns the conductance of two sets of nodes.</span> <span class="sd"> The *conductance* is the quotient of the cut size and the smaller of</span> <span class="sd"> the volumes of the two sets. [1]</span> @@ -693,7 +693,7 @@ <div class="viewcode-block" id="edge_expansion"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cuts.edge_expansion.html#networkx.algorithms.cuts.edge_expansion">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">edge_expansion</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">S</span><span class="p">,</span> <span class="n">T</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the edge expansion between two node sets.</span> +<span class="w"> </span><span class="sd">"""Returns the edge expansion between two node sets.</span> <span class="sd"> The *edge expansion* is the quotient of the cut size and the smaller</span> <span class="sd"> of the cardinalities of the two sets. [1]</span> @@ -740,7 +740,7 @@ <div class="viewcode-block" id="mixing_expansion"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cuts.mixing_expansion.html#networkx.algorithms.cuts.mixing_expansion">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">mixing_expansion</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">S</span><span class="p">,</span> <span class="n">T</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the mixing expansion between two node sets.</span> +<span class="w"> </span><span class="sd">"""Returns the mixing expansion between two node sets.</span> <span class="sd"> The *mixing expansion* is the quotient of the cut size and twice the</span> <span class="sd"> number of edges in the graph. [1]</span> @@ -788,7 +788,7 @@ <span class="c1"># denominator become `min(len(S), len(T))`?</span> <div class="viewcode-block" id="node_expansion"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cuts.node_expansion.html#networkx.algorithms.cuts.node_expansion">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">node_expansion</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">S</span><span class="p">):</span> - <span class="sd">"""Returns the node expansion of the set `S`.</span> +<span class="w"> </span><span class="sd">"""Returns the node expansion of the set `S`.</span> <span class="sd"> The *node expansion* is the quotient of the size of the node</span> <span class="sd"> boundary of *S* and the cardinality of *S*. [1]</span> @@ -828,7 +828,7 @@ <span class="c1"># denominator become `min(len(S), len(T))`?</span> <div class="viewcode-block" id="boundary_expansion"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cuts.boundary_expansion.html#networkx.algorithms.cuts.boundary_expansion">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">boundary_expansion</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">S</span><span class="p">):</span> - <span class="sd">"""Returns the boundary expansion of the set `S`.</span> +<span class="w"> </span><span class="sd">"""Returns the boundary expansion of the set `S`.</span> <span class="sd"> The *boundary expansion* is the quotient of the size</span> <span class="sd"> of the node boundary and the cardinality of *S*. [1]</span> @@ -912,7 +912,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/cycles.html b/_modules/networkx/algorithms/cycles.html index 6ee41fd0..591aa56e 100644 --- a/_modules/networkx/algorithms/cycles.html +++ b/_modules/networkx/algorithms/cycles.html @@ -484,7 +484,7 @@ <div class="viewcode-block" id="cycle_basis"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cycles.cycle_basis.html#networkx.algorithms.cycles.cycle_basis">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">cycle_basis</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">root</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a list of cycles which form a basis for cycles of G.</span> +<span class="w"> </span><span class="sd">"""Returns a list of cycles which form a basis for cycles of G.</span> <span class="sd"> A basis for cycles of a network is a minimal collection of</span> <span class="sd"> cycles such that any cycle in the network can be written</span> @@ -560,7 +560,7 @@ <div class="viewcode-block" id="simple_cycles"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cycles.simple_cycles.html#networkx.algorithms.cycles.simple_cycles">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">simple_cycles</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Find simple cycles (elementary circuits) of a directed graph.</span> +<span class="w"> </span><span class="sd">"""Find simple cycles (elementary circuits) of a directed graph.</span> <span class="sd"> A `simple cycle`, or `elementary circuit`, is a closed path where</span> <span class="sd"> no node appears twice. Two elementary circuits are distinct if they</span> @@ -687,7 +687,7 @@ <div class="viewcode-block" id="recursive_simple_cycles"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cycles.recursive_simple_cycles.html#networkx.algorithms.cycles.recursive_simple_cycles">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">recursive_simple_cycles</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Find simple cycles (elementary circuits) of a directed graph.</span> +<span class="w"> </span><span class="sd">"""Find simple cycles (elementary circuits) of a directed graph.</span> <span class="sd"> A `simple cycle`, or `elementary circuit`, is a closed path where</span> <span class="sd"> no node appears twice. Two elementary circuits are distinct if they</span> @@ -734,7 +734,7 @@ <span class="sd"> """</span> <span class="c1"># Jon Olav Vik, 2010-08-09</span> <span class="k">def</span> <span class="nf">_unblock</span><span class="p">(</span><span class="n">thisnode</span><span class="p">):</span> - <span class="sd">"""Recursively unblock and remove nodes from B[thisnode]."""</span> +<span class="w"> </span><span class="sd">"""Recursively unblock and remove nodes from B[thisnode]."""</span> <span class="k">if</span> <span class="n">blocked</span><span class="p">[</span><span class="n">thisnode</span><span class="p">]:</span> <span class="n">blocked</span><span class="p">[</span><span class="n">thisnode</span><span class="p">]</span> <span class="o">=</span> <span class="kc">False</span> <span class="k">while</span> <span class="n">B</span><span class="p">[</span><span class="n">thisnode</span><span class="p">]:</span> @@ -795,7 +795,7 @@ <div class="viewcode-block" id="find_cycle"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cycles.find_cycle.html#networkx.algorithms.cycles.find_cycle">[docs]</a><span class="k">def</span> <span class="nf">find_cycle</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">orientation</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a cycle found via depth-first traversal.</span> +<span class="w"> </span><span class="sd">"""Returns a cycle found via depth-first traversal.</span> <span class="sd"> The cycle is a list of edges indicating the cyclic path.</span> <span class="sd"> Orientation of directed edges is controlled by `orientation`.</span> @@ -956,7 +956,7 @@ <div class="viewcode-block" id="minimum_cycle_basis"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.cycles.minimum_cycle_basis.html#networkx.algorithms.cycles.minimum_cycle_basis">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">minimum_cycle_basis</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a minimum weight cycle basis for G</span> +<span class="w"> </span><span class="sd">"""Returns a minimum weight cycle basis for G</span> <span class="sd"> Minimum weight means a cycle basis for which the total weight</span> <span class="sd"> (length for unweighted graphs) of all the cycles is minimum.</span> @@ -1025,7 +1025,7 @@ <span class="k">def</span> <span class="nf">_min_cycle</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">orth</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Computes the minimum weight cycle in G,</span> <span class="sd"> orthogonal to the vector orth as per [p. 338, 1]</span> <span class="sd"> """</span> @@ -1069,7 +1069,7 @@ <span class="k">def</span> <span class="nf">_path_to_cycle</span><span class="p">(</span><span class="n">path</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Removes the edges from path that occur even number of times.</span> <span class="sd"> Returns a set of edges</span> <span class="sd"> """</span> @@ -1129,7 +1129,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/d_separation.html b/_modules/networkx/algorithms/d_separation.html index c437ec20..f95c23cb 100644 --- a/_modules/networkx/algorithms/d_separation.html +++ b/_modules/networkx/algorithms/d_separation.html @@ -591,7 +591,7 @@ <div class="viewcode-block" id="d_separated"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.d_separation.d_separated.html#networkx.algorithms.d_separation.d_separated">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">d_separated</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">z</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Return whether node sets ``x`` and ``y`` are d-separated by ``z``.</span> <span class="sd"> Parameters</span> @@ -677,7 +677,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">minimal_d_separator</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Compute a minimal d-separating set between 'u' and 'v'.</span> +<span class="w"> </span><span class="sd">"""Compute a minimal d-separating set between 'u' and 'v'.</span> <span class="sd"> A d-separating set in a DAG is a set of nodes that blocks all paths</span> <span class="sd"> between the two nodes, 'u' and 'v'. This function</span> @@ -759,7 +759,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_minimal_d_separator</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">z</span><span class="p">):</span> - <span class="sd">"""Determine if a d-separating set is minimal.</span> +<span class="w"> </span><span class="sd">"""Determine if a d-separating set is minimal.</span> <span class="sd"> A d-separating set, `z`, in a DAG is a set of nodes that blocks</span> <span class="sd"> all paths between the two nodes, `u` and `v`. This function</span> @@ -861,7 +861,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">_bfs_with_marks</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">start_node</span><span class="p">,</span> <span class="n">check_set</span><span class="p">):</span> - <span class="sd">"""Breadth-first-search with markings.</span> +<span class="w"> </span><span class="sd">"""Breadth-first-search with markings.</span> <span class="sd"> Performs BFS starting from ``start_node`` and whenever a node</span> <span class="sd"> inside ``check_set`` is met, it is "marked". Once a node is marked,</span> @@ -953,7 +953,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/dag.html b/_modules/networkx/algorithms/dag.html index 6ba9c1b3..6cf6ed34 100644 --- a/_modules/networkx/algorithms/dag.html +++ b/_modules/networkx/algorithms/dag.html @@ -501,7 +501,7 @@ <div class="viewcode-block" id="descendants"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dag.descendants.html#networkx.algorithms.dag.descendants">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">descendants</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">):</span> - <span class="sd">"""Returns all nodes reachable from `source` in `G`.</span> +<span class="w"> </span><span class="sd">"""Returns all nodes reachable from `source` in `G`.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -538,7 +538,7 @@ <div class="viewcode-block" id="ancestors"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dag.ancestors.html#networkx.algorithms.dag.ancestors">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">ancestors</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">):</span> - <span class="sd">"""Returns all nodes having a path to `source` in `G`.</span> +<span class="w"> </span><span class="sd">"""Returns all nodes having a path to `source` in `G`.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -574,7 +574,7 @@ <span class="k">def</span> <span class="nf">has_cycle</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Decides whether the directed graph has a cycle."""</span> +<span class="w"> </span><span class="sd">"""Decides whether the directed graph has a cycle."""</span> <span class="k">try</span><span class="p">:</span> <span class="c1"># Feed the entire iterator into a zero-length deque.</span> <span class="n">deque</span><span class="p">(</span><span class="n">topological_sort</span><span class="p">(</span><span class="n">G</span><span class="p">),</span> <span class="n">maxlen</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span> @@ -585,7 +585,7 @@ <div class="viewcode-block" id="is_directed_acyclic_graph"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dag.is_directed_acyclic_graph.html#networkx.algorithms.dag.is_directed_acyclic_graph">[docs]</a><span class="k">def</span> <span class="nf">is_directed_acyclic_graph</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns True if the graph `G` is a directed acyclic graph (DAG) or</span> +<span class="w"> </span><span class="sd">"""Returns True if the graph `G` is a directed acyclic graph (DAG) or</span> <span class="sd"> False if not.</span> <span class="sd"> Parameters</span> @@ -625,7 +625,7 @@ <div class="viewcode-block" id="topological_generations"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dag.topological_generations.html#networkx.algorithms.dag.topological_generations">[docs]</a><span class="k">def</span> <span class="nf">topological_generations</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Stratifies a DAG into generations.</span> +<span class="w"> </span><span class="sd">"""Stratifies a DAG into generations.</span> <span class="sd"> A topological generation is node collection in which ancestors of a node in each</span> <span class="sd"> generation are guaranteed to be in a previous generation, and any descendants of</span> @@ -702,7 +702,7 @@ <div class="viewcode-block" id="topological_sort"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dag.topological_sort.html#networkx.algorithms.dag.topological_sort">[docs]</a><span class="k">def</span> <span class="nf">topological_sort</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns a generator of nodes in topologically sorted order.</span> +<span class="w"> </span><span class="sd">"""Returns a generator of nodes in topologically sorted order.</span> <span class="sd"> A topological sort is a nonunique permutation of the nodes of a</span> <span class="sd"> directed graph such that an edge from u to v implies that u</span> @@ -770,7 +770,7 @@ <div class="viewcode-block" id="lexicographical_topological_sort"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dag.lexicographical_topological_sort.html#networkx.algorithms.dag.lexicographical_topological_sort">[docs]</a><span class="k">def</span> <span class="nf">lexicographical_topological_sort</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Generate the nodes in the unique lexicographical topological sort order.</span> +<span class="w"> </span><span class="sd">"""Generate the nodes in the unique lexicographical topological sort order.</span> <span class="sd"> Generates a unique ordering of nodes by first sorting topologically (for which there are often</span> <span class="sd"> multiple valid orderings) and then additionally by sorting lexicographically.</span> @@ -912,7 +912,7 @@ <div class="viewcode-block" id="all_topological_sorts"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dag.all_topological_sorts.html#networkx.algorithms.dag.all_topological_sorts">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">all_topological_sorts</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns a generator of _all_ topological sorts of the directed graph G.</span> +<span class="w"> </span><span class="sd">"""Returns a generator of _all_ topological sorts of the directed graph G.</span> <span class="sd"> A topological sort is a nonunique permutation of the nodes such that an</span> <span class="sd"> edge from u to v implies that u appears before v in the topological sort</span> @@ -1030,7 +1030,7 @@ <div class="viewcode-block" id="is_aperiodic"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dag.is_aperiodic.html#networkx.algorithms.dag.is_aperiodic">[docs]</a><span class="k">def</span> <span class="nf">is_aperiodic</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns True if `G` is aperiodic.</span> +<span class="w"> </span><span class="sd">"""Returns True if `G` is aperiodic.</span> <span class="sd"> A directed graph is aperiodic if there is no integer k > 1 that</span> <span class="sd"> divides the length of every cycle in the graph.</span> @@ -1121,7 +1121,7 @@ <div class="viewcode-block" id="transitive_closure"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dag.transitive_closure.html#networkx.algorithms.dag.transitive_closure">[docs]</a><span class="k">def</span> <span class="nf">transitive_closure</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">reflexive</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns transitive closure of a graph</span> +<span class="w"> </span><span class="sd">"""Returns transitive closure of a graph</span> <span class="sd"> The transitive closure of G = (V,E) is a graph G+ = (V,E+) such that</span> <span class="sd"> for all v, w in V there is an edge (v, w) in E+ if and only if there</span> @@ -1213,7 +1213,7 @@ <div class="viewcode-block" id="transitive_closure_dag"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dag.transitive_closure_dag.html#networkx.algorithms.dag.transitive_closure_dag">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">transitive_closure_dag</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">topo_order</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the transitive closure of a directed acyclic graph.</span> +<span class="w"> </span><span class="sd">"""Returns the transitive closure of a directed acyclic graph.</span> <span class="sd"> This function is faster than the function `transitive_closure`, but fails</span> <span class="sd"> if the graph has a cycle.</span> @@ -1269,7 +1269,7 @@ <div class="viewcode-block" id="transitive_reduction"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dag.transitive_reduction.html#networkx.algorithms.dag.transitive_reduction">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">transitive_reduction</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns transitive reduction of a directed graph</span> +<span class="w"> </span><span class="sd">"""Returns transitive reduction of a directed graph</span> <span class="sd"> The transitive reduction of G = (V,E) is a graph G- = (V,E-) such that</span> <span class="sd"> for all v,w in V there is an edge (v,w) in E- if and only if (v,w) is</span> @@ -1341,7 +1341,7 @@ <div class="viewcode-block" id="antichains"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dag.antichains.html#networkx.algorithms.dag.antichains">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">antichains</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">topo_order</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Generates antichains from a directed acyclic graph (DAG).</span> +<span class="w"> </span><span class="sd">"""Generates antichains from a directed acyclic graph (DAG).</span> <span class="sd"> An antichain is a subset of a partially ordered set such that any</span> <span class="sd"> two elements in the subset are incomparable.</span> @@ -1407,7 +1407,7 @@ <div class="viewcode-block" id="dag_longest_path"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dag.dag_longest_path.html#networkx.algorithms.dag.dag_longest_path">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">dag_longest_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">default_weight</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">topo_order</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the longest path in a directed acyclic graph (DAG).</span> +<span class="w"> </span><span class="sd">"""Returns the longest path in a directed acyclic graph (DAG).</span> <span class="sd"> If `G` has edges with `weight` attribute the edge data are used as</span> <span class="sd"> weight values.</span> @@ -1502,7 +1502,7 @@ <div class="viewcode-block" id="dag_longest_path_length"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dag.dag_longest_path_length.html#networkx.algorithms.dag.dag_longest_path_length">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">dag_longest_path_length</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">default_weight</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span> - <span class="sd">"""Returns the longest path length in a DAG</span> +<span class="w"> </span><span class="sd">"""Returns the longest path length in a DAG</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1553,7 +1553,7 @@ <span class="k">def</span> <span class="nf">root_to_leaf_paths</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Yields root-to-leaf paths in a directed acyclic graph.</span> +<span class="w"> </span><span class="sd">"""Yields root-to-leaf paths in a directed acyclic graph.</span> <span class="sd"> `G` must be a directed acyclic graph. If not, the behavior of this</span> <span class="sd"> function is undefined. A "root" in this graph is a node of in-degree</span> @@ -1573,7 +1573,7 @@ <div class="viewcode-block" id="dag_to_branching"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dag.dag_to_branching.html#networkx.algorithms.dag.dag_to_branching">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">dag_to_branching</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns a branching representing all (overlapping) paths from</span> +<span class="w"> </span><span class="sd">"""Returns a branching representing all (overlapping) paths from</span> <span class="sd"> root nodes to leaf nodes in the given directed acyclic graph.</span> <span class="sd"> As described in :mod:`networkx.algorithms.tree.recognition`, a</span> @@ -1670,7 +1670,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">compute_v_structures</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Iterate through the graph to compute all v-structures.</span> +<span class="w"> </span><span class="sd">"""Iterate through the graph to compute all v-structures.</span> <span class="sd"> V-structures are triples in the directed graph where</span> <span class="sd"> two parent nodes point to the same child and the two parent nodes</span> @@ -1747,7 +1747,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/distance_measures.html b/_modules/networkx/algorithms/distance_measures.html index b6582a26..b67c0356 100644 --- a/_modules/networkx/algorithms/distance_measures.html +++ b/_modules/networkx/algorithms/distance_measures.html @@ -478,7 +478,7 @@ <span class="k">def</span> <span class="nf">_extrema_bounding</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">compute</span><span class="o">=</span><span class="s2">"diameter"</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute requested extreme distance metric of undirected graph G</span> +<span class="w"> </span><span class="sd">"""Compute requested extreme distance metric of undirected graph G</span> <span class="sd"> Computation is based on smart lower and upper bounds, and in practice</span> <span class="sd"> linear in the number of nodes, rather than quadratic (except for some</span> @@ -699,7 +699,7 @@ <div class="viewcode-block" id="eccentricity"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.distance_measures.eccentricity.html#networkx.algorithms.distance_measures.eccentricity">[docs]</a><span class="k">def</span> <span class="nf">eccentricity</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">v</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">sp</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the eccentricity of nodes in G.</span> +<span class="w"> </span><span class="sd">"""Returns the eccentricity of nodes in G.</span> <span class="sd"> The eccentricity of a node v is the maximum distance from v to</span> <span class="sd"> all other nodes in G.</span> @@ -787,7 +787,7 @@ <div class="viewcode-block" id="diameter"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.distance_measures.diameter.html#networkx.algorithms.distance_measures.diameter">[docs]</a><span class="k">def</span> <span class="nf">diameter</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">e</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">usebounds</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the diameter of the graph G.</span> +<span class="w"> </span><span class="sd">"""Returns the diameter of the graph G.</span> <span class="sd"> The diameter is the maximum eccentricity.</span> @@ -842,7 +842,7 @@ <div class="viewcode-block" id="periphery"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.distance_measures.periphery.html#networkx.algorithms.distance_measures.periphery">[docs]</a><span class="k">def</span> <span class="nf">periphery</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">e</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">usebounds</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the periphery of the graph G.</span> +<span class="w"> </span><span class="sd">"""Returns the periphery of the graph G.</span> <span class="sd"> The periphery is the set of nodes with eccentricity equal to the diameter.</span> @@ -900,7 +900,7 @@ <div class="viewcode-block" id="radius"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.distance_measures.radius.html#networkx.algorithms.distance_measures.radius">[docs]</a><span class="k">def</span> <span class="nf">radius</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">e</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">usebounds</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the radius of the graph G.</span> +<span class="w"> </span><span class="sd">"""Returns the radius of the graph G.</span> <span class="sd"> The radius is the minimum eccentricity.</span> @@ -952,7 +952,7 @@ <div class="viewcode-block" id="center"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.distance_measures.center.html#networkx.algorithms.distance_measures.center">[docs]</a><span class="k">def</span> <span class="nf">center</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">e</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">usebounds</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the center of the graph G.</span> +<span class="w"> </span><span class="sd">"""Returns the center of the graph G.</span> <span class="sd"> The center is the set of nodes with eccentricity equal to radius.</span> @@ -1010,7 +1010,7 @@ <div class="viewcode-block" id="barycenter"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.distance_measures.barycenter.html#networkx.algorithms.distance_measures.barycenter">[docs]</a><span class="k">def</span> <span class="nf">barycenter</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">attr</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">sp</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Calculate barycenter of a connected graph, optionally with edge weights.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Calculate barycenter of a connected graph, optionally with edge weights.</span> <span class="sd"> The :dfn:`barycenter` a</span> <span class="sd"> :func:`connected <networkx.algorithms.components.is_connected>` graph</span> @@ -1088,7 +1088,7 @@ <span class="k">def</span> <span class="nf">_count_lu_permutations</span><span class="p">(</span><span class="n">perm_array</span><span class="p">):</span> - <span class="sd">"""Counts the number of permutations in SuperLU perm_c or perm_r"""</span> +<span class="w"> </span><span class="sd">"""Counts the number of permutations in SuperLU perm_c or perm_r"""</span> <span class="n">perm_cnt</span> <span class="o">=</span> <span class="mi">0</span> <span class="n">arr</span> <span class="o">=</span> <span class="n">perm_array</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">arr</span><span class="p">)):</span> @@ -1103,7 +1103,7 @@ <div class="viewcode-block" id="resistance_distance"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.distance_measures.resistance_distance.html#networkx.algorithms.distance_measures.resistance_distance">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">resistance_distance</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodeA</span><span class="p">,</span> <span class="n">nodeB</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">invert_weight</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Returns the resistance distance between node A and node B on graph G.</span> +<span class="w"> </span><span class="sd">"""Returns the resistance distance between node A and node B on graph G.</span> <span class="sd"> The resistance distance between two nodes of a graph is akin to treating</span> <span class="sd"> the graph as a grid of resistorses with a resistance equal to the provided</span> @@ -1277,7 +1277,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/distance_regular.html b/_modules/networkx/algorithms/distance_regular.html index b326bfe8..d4909128 100644 --- a/_modules/networkx/algorithms/distance_regular.html +++ b/_modules/networkx/algorithms/distance_regular.html @@ -481,7 +481,7 @@ <div class="viewcode-block" id="is_distance_regular"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.distance_regular.is_distance_regular.html#networkx.algorithms.distance_regular.is_distance_regular">[docs]</a><span class="k">def</span> <span class="nf">is_distance_regular</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns True if the graph is distance regular, False otherwise.</span> +<span class="w"> </span><span class="sd">"""Returns True if the graph is distance regular, False otherwise.</span> <span class="sd"> A connected graph G is distance-regular if for any nodes x,y</span> <span class="sd"> and any integers i,j=0,1,...,d (where d is the graph</span> @@ -528,7 +528,7 @@ <div class="viewcode-block" id="global_parameters"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.distance_regular.global_parameters.html#networkx.algorithms.distance_regular.global_parameters">[docs]</a><span class="k">def</span> <span class="nf">global_parameters</span><span class="p">(</span><span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">):</span> - <span class="sd">"""Returns global parameters for a given intersection array.</span> +<span class="w"> </span><span class="sd">"""Returns global parameters for a given intersection array.</span> <span class="sd"> Given a distance-regular graph G with integers b_i, c_i,i = 0,....,d</span> <span class="sd"> such that for any 2 vertices x,y in G at a distance i=d(x,y), there</span> @@ -573,7 +573,7 @@ <div class="viewcode-block" id="intersection_array"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.distance_regular.intersection_array.html#networkx.algorithms.distance_regular.intersection_array">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">,</span> <span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">intersection_array</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the intersection array of a distance-regular graph.</span> +<span class="w"> </span><span class="sd">"""Returns the intersection array of a distance-regular graph.</span> <span class="sd"> Given a distance-regular graph G with integers b_i, c_i,i = 0,....,d</span> <span class="sd"> such that for any 2 vertices x,y in G at a distance i=d(x,y), there</span> @@ -642,7 +642,7 @@ <span class="c1"># TODO There is a definition for directed strongly regular graphs.</span> <div class="viewcode-block" id="is_strongly_regular"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.distance_regular.is_strongly_regular.html#networkx.algorithms.distance_regular.is_strongly_regular">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">,</span> <span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_strongly_regular</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns True if and only if the given graph is strongly</span> +<span class="w"> </span><span class="sd">"""Returns True if and only if the given graph is strongly</span> <span class="sd"> regular.</span> <span class="sd"> An undirected graph is *strongly regular* if</span> @@ -743,7 +743,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/dominance.html b/_modules/networkx/algorithms/dominance.html index 5c95b752..9085730b 100644 --- a/_modules/networkx/algorithms/dominance.html +++ b/_modules/networkx/algorithms/dominance.html @@ -475,7 +475,7 @@ <div class="viewcode-block" id="immediate_dominators"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dominance.immediate_dominators.html#networkx.algorithms.dominance.immediate_dominators">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">immediate_dominators</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">start</span><span class="p">):</span> - <span class="sd">"""Returns the immediate dominators of all nodes of a directed graph.</span> +<span class="w"> </span><span class="sd">"""Returns the immediate dominators of all nodes of a directed graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -547,7 +547,7 @@ <div class="viewcode-block" id="dominance_frontiers"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dominance.dominance_frontiers.html#networkx.algorithms.dominance.dominance_frontiers">[docs]</a><span class="k">def</span> <span class="nf">dominance_frontiers</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">start</span><span class="p">):</span> - <span class="sd">"""Returns the dominance frontiers of all nodes of a directed graph.</span> +<span class="w"> </span><span class="sd">"""Returns the dominance frontiers of all nodes of a directed graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -645,7 +645,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/dominating.html b/_modules/networkx/algorithms/dominating.html index 205087b2..123655a1 100644 --- a/_modules/networkx/algorithms/dominating.html +++ b/_modules/networkx/algorithms/dominating.html @@ -471,7 +471,7 @@ <div class="viewcode-block" id="dominating_set"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dominating.dominating_set.html#networkx.algorithms.dominating.dominating_set">[docs]</a><span class="k">def</span> <span class="nf">dominating_set</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">start_with</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Finds a dominating set for the graph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Finds a dominating set for the graph G.</span> <span class="sd"> A *dominating set* for a graph with node set *V* is a subset *D* of</span> <span class="sd"> *V* such that every node not in *D* is adjacent to at least one</span> @@ -529,7 +529,7 @@ <div class="viewcode-block" id="is_dominating_set"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.dominating.is_dominating_set.html#networkx.algorithms.dominating.is_dominating_set">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">is_dominating_set</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nbunch</span><span class="p">):</span> - <span class="sd">"""Checks if `nbunch` is a dominating set for `G`.</span> +<span class="w"> </span><span class="sd">"""Checks if `nbunch` is a dominating set for `G`.</span> <span class="sd"> A *dominating set* for a graph with node set *V* is a subset *D* of</span> <span class="sd"> *V* such that every node not in *D* is adjacent to at least one</span> @@ -605,7 +605,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/efficiency_measures.html b/_modules/networkx/algorithms/efficiency_measures.html index 88b4f8ae..652ce0b2 100644 --- a/_modules/networkx/algorithms/efficiency_measures.html +++ b/_modules/networkx/algorithms/efficiency_measures.html @@ -473,7 +473,7 @@ <div class="viewcode-block" id="efficiency"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.efficiency_measures.efficiency.html#networkx.algorithms.efficiency_measures.efficiency">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">efficiency</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Returns the efficiency of a pair of nodes in a graph.</span> +<span class="w"> </span><span class="sd">"""Returns the efficiency of a pair of nodes in a graph.</span> <span class="sd"> The *efficiency* of a pair of nodes is the multiplicative inverse of the</span> <span class="sd"> shortest path distance between the nodes [1]_. Returns 0 if no path</span> @@ -523,7 +523,7 @@ <div class="viewcode-block" id="global_efficiency"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.efficiency_measures.global_efficiency.html#networkx.algorithms.efficiency_measures.global_efficiency">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">global_efficiency</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the average global efficiency of the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the average global efficiency of the graph.</span> <span class="sd"> The *efficiency* of a pair of nodes in a graph is the multiplicative</span> <span class="sd"> inverse of the shortest path distance between the nodes. The *average</span> @@ -583,7 +583,7 @@ <div class="viewcode-block" id="local_efficiency"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.efficiency_measures.local_efficiency.html#networkx.algorithms.efficiency_measures.local_efficiency">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">local_efficiency</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the average local efficiency of the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the average local efficiency of the graph.</span> <span class="sd"> The *efficiency* of a pair of nodes in a graph is the multiplicative</span> <span class="sd"> inverse of the shortest path distance between the nodes. The *local</span> @@ -677,7 +677,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/euler.html b/_modules/networkx/algorithms/euler.html index 7f0a4cbb..0afa0b74 100644 --- a/_modules/networkx/algorithms/euler.html +++ b/_modules/networkx/algorithms/euler.html @@ -481,7 +481,7 @@ <div class="viewcode-block" id="is_eulerian"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.euler.is_eulerian.html#networkx.algorithms.euler.is_eulerian">[docs]</a><span class="k">def</span> <span class="nf">is_eulerian</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns True if and only if `G` is Eulerian.</span> +<span class="w"> </span><span class="sd">"""Returns True if and only if `G` is Eulerian.</span> <span class="sd"> A graph is *Eulerian* if it has an Eulerian circuit. An *Eulerian</span> <span class="sd"> circuit* is a closed walk that includes each edge of a graph exactly</span> @@ -532,7 +532,7 @@ <div class="viewcode-block" id="is_semieulerian"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.euler.is_semieulerian.html#networkx.algorithms.euler.is_semieulerian">[docs]</a><span class="k">def</span> <span class="nf">is_semieulerian</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Return True iff `G` is semi-Eulerian.</span> +<span class="w"> </span><span class="sd">"""Return True iff `G` is semi-Eulerian.</span> <span class="sd"> G is semi-Eulerian if it has an Eulerian path but no Eulerian circuit.</span> @@ -545,7 +545,7 @@ <span class="k">def</span> <span class="nf">_find_path_start</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Return a suitable starting vertex for an Eulerian path.</span> +<span class="w"> </span><span class="sd">"""Return a suitable starting vertex for an Eulerian path.</span> <span class="sd"> If no path exists, return None.</span> <span class="sd"> """</span> @@ -616,7 +616,7 @@ <div class="viewcode-block" id="eulerian_circuit"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.euler.eulerian_circuit.html#networkx.algorithms.euler.eulerian_circuit">[docs]</a><span class="k">def</span> <span class="nf">eulerian_circuit</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">keys</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns an iterator over the edges of an Eulerian circuit in `G`.</span> +<span class="w"> </span><span class="sd">"""Returns an iterator over the edges of an Eulerian circuit in `G`.</span> <span class="sd"> An *Eulerian circuit* is a closed walk that includes each edge of a</span> <span class="sd"> graph exactly once.</span> @@ -696,7 +696,7 @@ <div class="viewcode-block" id="has_eulerian_path"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.euler.has_eulerian_path.html#networkx.algorithms.euler.has_eulerian_path">[docs]</a><span class="k">def</span> <span class="nf">has_eulerian_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Return True iff `G` has an Eulerian path.</span> +<span class="w"> </span><span class="sd">"""Return True iff `G` has an Eulerian path.</span> <span class="sd"> An Eulerian path is a path in a graph which uses each edge of a graph</span> <span class="sd"> exactly once. If `source` is specified, then this function checks</span> @@ -790,7 +790,7 @@ <div class="viewcode-block" id="eulerian_path"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.euler.eulerian_path.html#networkx.algorithms.euler.eulerian_path">[docs]</a><span class="k">def</span> <span class="nf">eulerian_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">keys</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Return an iterator over the edges of an Eulerian path in `G`.</span> +<span class="w"> </span><span class="sd">"""Return an iterator over the edges of an Eulerian path in `G`.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -845,7 +845,7 @@ <div class="viewcode-block" id="eulerize"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.euler.eulerize.html#networkx.algorithms.euler.eulerize">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">eulerize</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Transforms a graph into an Eulerian graph.</span> +<span class="w"> </span><span class="sd">"""Transforms a graph into an Eulerian graph.</span> <span class="sd"> If `G` is Eulerian the result is `G` as a MultiGraph, otherwise the result is a smallest</span> <span class="sd"> (in terms of the number of edges) multigraph whose underlying simple graph is `G`.</span> @@ -975,7 +975,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/flow/boykovkolmogorov.html b/_modules/networkx/algorithms/flow/boykovkolmogorov.html index eea1cf92..f456aad0 100644 --- a/_modules/networkx/algorithms/flow/boykovkolmogorov.html +++ b/_modules/networkx/algorithms/flow/boykovkolmogorov.html @@ -476,7 +476,7 @@ <div class="viewcode-block" id="boykov_kolmogorov"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.flow.boykov_kolmogorov.html#networkx.algorithms.flow.boykov_kolmogorov">[docs]</a><span class="k">def</span> <span class="nf">boykov_kolmogorov</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">capacity</span><span class="o">=</span><span class="s2">"capacity"</span><span class="p">,</span> <span class="n">residual</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">value_only</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Find a maximum single-commodity flow using Boykov-Kolmogorov algorithm.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Find a maximum single-commodity flow using Boykov-Kolmogorov algorithm.</span> <span class="sd"> This function returns the residual network resulting after computing</span> <span class="sd"> the maximum flow. See below for details about the conventions</span> @@ -652,7 +652,7 @@ <span class="n">R_pred</span> <span class="o">=</span> <span class="n">R</span><span class="o">.</span><span class="n">pred</span> <span class="k">def</span> <span class="nf">grow</span><span class="p">():</span> - <span class="sd">"""Bidirectional breadth-first search for the growth stage.</span> +<span class="w"> </span><span class="sd">"""Bidirectional breadth-first search for the growth stage.</span> <span class="sd"> Returns a connecting edge, that is and edge that connects</span> <span class="sd"> a node from the source search tree with a node from the</span> @@ -687,7 +687,7 @@ <span class="k">return</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span> <span class="k">def</span> <span class="nf">augment</span><span class="p">(</span><span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Augmentation stage.</span> +<span class="w"> </span><span class="sd">"""Augmentation stage.</span> <span class="sd"> Reconstruct path and determine its residual capacity.</span> <span class="sd"> We start from a connecting edge, which links a node</span> @@ -735,7 +735,7 @@ <span class="k">return</span> <span class="n">flow</span> <span class="k">def</span> <span class="nf">adopt</span><span class="p">():</span> - <span class="sd">"""Adoption stage.</span> +<span class="w"> </span><span class="sd">"""Adoption stage.</span> <span class="sd"> Reconstruct search trees by adopting or discarding orphans.</span> <span class="sd"> During augmentation stage some edges got saturated and thus</span> @@ -879,7 +879,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/flow/capacityscaling.html b/_modules/networkx/algorithms/flow/capacityscaling.html index edaf0b98..dbf60083 100644 --- a/_modules/networkx/algorithms/flow/capacityscaling.html +++ b/_modules/networkx/algorithms/flow/capacityscaling.html @@ -476,7 +476,7 @@ <span class="k">def</span> <span class="nf">_detect_unboundedness</span><span class="p">(</span><span class="n">R</span><span class="p">):</span> - <span class="sd">"""Detect infinite-capacity negative cycles."""</span> +<span class="w"> </span><span class="sd">"""Detect infinite-capacity negative cycles."""</span> <span class="n">G</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">DiGraph</span><span class="p">()</span> <span class="n">G</span><span class="o">.</span><span class="n">add_nodes_from</span><span class="p">(</span><span class="n">R</span><span class="p">)</span> @@ -503,7 +503,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">_build_residual_network</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">demand</span><span class="p">,</span> <span class="n">capacity</span><span class="p">,</span> <span class="n">weight</span><span class="p">):</span> - <span class="sd">"""Build a residual network and initialize a zero flow."""</span> +<span class="w"> </span><span class="sd">"""Build a residual network and initialize a zero flow."""</span> <span class="k">if</span> <span class="nb">sum</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="n">u</span><span class="p">]</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">demand</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span> <span class="k">for</span> <span class="n">u</span> <span class="ow">in</span> <span class="n">G</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span> <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXUnfeasible</span><span class="p">(</span><span class="s2">"Sum of the demands should be 0."</span><span class="p">)</span> @@ -569,7 +569,7 @@ <span class="k">def</span> <span class="nf">_build_flow_dict</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">R</span><span class="p">,</span> <span class="n">capacity</span><span class="p">,</span> <span class="n">weight</span><span class="p">):</span> - <span class="sd">"""Build a flow dictionary from a residual network."""</span> +<span class="w"> </span><span class="sd">"""Build a flow dictionary from a residual network."""</span> <span class="n">inf</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="s2">"inf"</span><span class="p">)</span> <span class="n">flow_dict</span> <span class="o">=</span> <span class="p">{}</span> <span class="k">if</span> <span class="n">G</span><span class="o">.</span><span class="n">is_multigraph</span><span class="p">():</span> @@ -615,7 +615,7 @@ <div class="viewcode-block" id="capacity_scaling"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.flow.capacity_scaling.html#networkx.algorithms.flow.capacity_scaling">[docs]</a><span class="k">def</span> <span class="nf">capacity_scaling</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">demand</span><span class="o">=</span><span class="s2">"demand"</span><span class="p">,</span> <span class="n">capacity</span><span class="o">=</span><span class="s2">"capacity"</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">heap</span><span class="o">=</span><span class="n">BinaryHeap</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Find a minimum cost flow satisfying all demands in digraph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Find a minimum cost flow satisfying all demands in digraph G.</span> <span class="sd"> This is a capacity scaling successive shortest augmenting path algorithm.</span> @@ -916,7 +916,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/flow/dinitz_alg.html b/_modules/networkx/algorithms/flow/dinitz_alg.html index f26fc3c1..28f39557 100644 --- a/_modules/networkx/algorithms/flow/dinitz_alg.html +++ b/_modules/networkx/algorithms/flow/dinitz_alg.html @@ -474,7 +474,7 @@ <div class="viewcode-block" id="dinitz"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.flow.dinitz.html#networkx.algorithms.flow.dinitz">[docs]</a><span class="k">def</span> <span class="nf">dinitz</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">capacity</span><span class="o">=</span><span class="s2">"capacity"</span><span class="p">,</span> <span class="n">residual</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">value_only</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Find a maximum single-commodity flow using Dinitz' algorithm.</span> +<span class="w"> </span><span class="sd">"""Find a maximum single-commodity flow using Dinitz' algorithm.</span> <span class="sd"> This function returns the residual network resulting after computing</span> <span class="sd"> the maximum flow. See below for details about the conventions</span> @@ -643,7 +643,7 @@ <span class="k">return</span> <span class="n">parents</span> <span class="k">def</span> <span class="nf">depth_first_search</span><span class="p">(</span><span class="n">parents</span><span class="p">):</span> - <span class="sd">"""Build a path using DFS starting from the sink"""</span> +<span class="w"> </span><span class="sd">"""Build a path using DFS starting from the sink"""</span> <span class="n">path</span> <span class="o">=</span> <span class="p">[]</span> <span class="n">u</span> <span class="o">=</span> <span class="n">t</span> <span class="n">flow</span> <span class="o">=</span> <span class="n">INF</span> @@ -723,7 +723,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/flow/edmondskarp.html b/_modules/networkx/algorithms/flow/edmondskarp.html index abef7969..8c2ee927 100644 --- a/_modules/networkx/algorithms/flow/edmondskarp.html +++ b/_modules/networkx/algorithms/flow/edmondskarp.html @@ -472,7 +472,7 @@ <span class="k">def</span> <span class="nf">edmonds_karp_core</span><span class="p">(</span><span class="n">R</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">cutoff</span><span class="p">):</span> - <span class="sd">"""Implementation of the Edmonds-Karp algorithm."""</span> +<span class="w"> </span><span class="sd">"""Implementation of the Edmonds-Karp algorithm."""</span> <span class="n">R_nodes</span> <span class="o">=</span> <span class="n">R</span><span class="o">.</span><span class="n">nodes</span> <span class="n">R_pred</span> <span class="o">=</span> <span class="n">R</span><span class="o">.</span><span class="n">pred</span> <span class="n">R_succ</span> <span class="o">=</span> <span class="n">R</span><span class="o">.</span><span class="n">succ</span> @@ -480,7 +480,7 @@ <span class="n">inf</span> <span class="o">=</span> <span class="n">R</span><span class="o">.</span><span class="n">graph</span><span class="p">[</span><span class="s2">"inf"</span><span class="p">]</span> <span class="k">def</span> <span class="nf">augment</span><span class="p">(</span><span class="n">path</span><span class="p">):</span> - <span class="sd">"""Augment flow along a path from s to t."""</span> +<span class="w"> </span><span class="sd">"""Augment flow along a path from s to t."""</span> <span class="c1"># Determine the path residual capacity.</span> <span class="n">flow</span> <span class="o">=</span> <span class="n">inf</span> <span class="n">it</span> <span class="o">=</span> <span class="nb">iter</span><span class="p">(</span><span class="n">path</span><span class="p">)</span> @@ -501,7 +501,7 @@ <span class="k">return</span> <span class="n">flow</span> <span class="k">def</span> <span class="nf">bidirectional_bfs</span><span class="p">():</span> - <span class="sd">"""Bidirectional breadth-first search for an augmenting path."""</span> +<span class="w"> </span><span class="sd">"""Bidirectional breadth-first search for an augmenting path."""</span> <span class="n">pred</span> <span class="o">=</span> <span class="p">{</span><span class="n">s</span><span class="p">:</span> <span class="kc">None</span><span class="p">}</span> <span class="n">q_s</span> <span class="o">=</span> <span class="p">[</span><span class="n">s</span><span class="p">]</span> <span class="n">succ</span> <span class="o">=</span> <span class="p">{</span><span class="n">t</span><span class="p">:</span> <span class="kc">None</span><span class="p">}</span> @@ -555,7 +555,7 @@ <span class="k">def</span> <span class="nf">edmonds_karp_impl</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">capacity</span><span class="p">,</span> <span class="n">residual</span><span class="p">,</span> <span class="n">cutoff</span><span class="p">):</span> - <span class="sd">"""Implementation of the Edmonds-Karp algorithm."""</span> +<span class="w"> </span><span class="sd">"""Implementation of the Edmonds-Karp algorithm."""</span> <span class="k">if</span> <span class="n">s</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">G</span><span class="p">:</span> <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="sa">f</span><span class="s2">"node </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="n">s</span><span class="p">)</span><span class="si">}</span><span class="s2"> not in graph"</span><span class="p">)</span> <span class="k">if</span> <span class="n">t</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">G</span><span class="p">:</span> @@ -583,7 +583,7 @@ <div class="viewcode-block" id="edmonds_karp"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.flow.edmonds_karp.html#networkx.algorithms.flow.edmonds_karp">[docs]</a><span class="k">def</span> <span class="nf">edmonds_karp</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">capacity</span><span class="o">=</span><span class="s2">"capacity"</span><span class="p">,</span> <span class="n">residual</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">value_only</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Find a maximum single-commodity flow using the Edmonds-Karp algorithm.</span> +<span class="w"> </span><span class="sd">"""Find a maximum single-commodity flow using the Edmonds-Karp algorithm.</span> <span class="sd"> This function returns the residual network resulting after computing</span> <span class="sd"> the maximum flow. See below for details about the conventions</span> @@ -751,7 +751,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/flow/gomory_hu.html b/_modules/networkx/algorithms/flow/gomory_hu.html index 24afe5b4..03d2775a 100644 --- a/_modules/networkx/algorithms/flow/gomory_hu.html +++ b/_modules/networkx/algorithms/flow/gomory_hu.html @@ -477,7 +477,7 @@ <div class="viewcode-block" id="gomory_hu_tree"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.flow.gomory_hu_tree.html#networkx.algorithms.flow.gomory_hu_tree">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">gomory_hu_tree</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">capacity</span><span class="o">=</span><span class="s2">"capacity"</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the Gomory-Hu tree of an undirected graph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the Gomory-Hu tree of an undirected graph G.</span> <span class="sd"> A Gomory-Hu tree of an undirected graph with capacities is a</span> <span class="sd"> weighted tree that represents the minimum s-t cuts for all s-t</span> @@ -688,7 +688,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/flow/maxflow.html b/_modules/networkx/algorithms/flow/maxflow.html index 8553181d..7c1a0fdc 100644 --- a/_modules/networkx/algorithms/flow/maxflow.html +++ b/_modules/networkx/algorithms/flow/maxflow.html @@ -480,7 +480,7 @@ <div class="viewcode-block" id="maximum_flow"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.flow.maximum_flow.html#networkx.algorithms.flow.maximum_flow">[docs]</a><span class="k">def</span> <span class="nf">maximum_flow</span><span class="p">(</span><span class="n">flowG</span><span class="p">,</span> <span class="n">_s</span><span class="p">,</span> <span class="n">_t</span><span class="p">,</span> <span class="n">capacity</span><span class="o">=</span><span class="s2">"capacity"</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> - <span class="sd">"""Find a maximum single-commodity flow.</span> +<span class="w"> </span><span class="sd">"""Find a maximum single-commodity flow.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -626,7 +626,7 @@ <div class="viewcode-block" id="maximum_flow_value"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.flow.maximum_flow_value.html#networkx.algorithms.flow.maximum_flow_value">[docs]</a><span class="k">def</span> <span class="nf">maximum_flow_value</span><span class="p">(</span><span class="n">flowG</span><span class="p">,</span> <span class="n">_s</span><span class="p">,</span> <span class="n">_t</span><span class="p">,</span> <span class="n">capacity</span><span class="o">=</span><span class="s2">"capacity"</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> - <span class="sd">"""Find the value of maximum single-commodity flow.</span> +<span class="w"> </span><span class="sd">"""Find the value of maximum single-commodity flow.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -765,7 +765,7 @@ <div class="viewcode-block" id="minimum_cut"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.flow.minimum_cut.html#networkx.algorithms.flow.minimum_cut">[docs]</a><span class="k">def</span> <span class="nf">minimum_cut</span><span class="p">(</span><span class="n">flowG</span><span class="p">,</span> <span class="n">_s</span><span class="p">,</span> <span class="n">_t</span><span class="p">,</span> <span class="n">capacity</span><span class="o">=</span><span class="s2">"capacity"</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> - <span class="sd">"""Compute the value and the node partition of a minimum (s, t)-cut.</span> +<span class="w"> </span><span class="sd">"""Compute the value and the node partition of a minimum (s, t)-cut.</span> <span class="sd"> Use the max-flow min-cut theorem, i.e., the capacity of a minimum</span> <span class="sd"> capacity cut is equal to the flow value of a maximum flow.</span> @@ -928,7 +928,7 @@ <div class="viewcode-block" id="minimum_cut_value"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.flow.minimum_cut_value.html#networkx.algorithms.flow.minimum_cut_value">[docs]</a><span class="k">def</span> <span class="nf">minimum_cut_value</span><span class="p">(</span><span class="n">flowG</span><span class="p">,</span> <span class="n">_s</span><span class="p">,</span> <span class="n">_t</span><span class="p">,</span> <span class="n">capacity</span><span class="o">=</span><span class="s2">"capacity"</span><span class="p">,</span> <span class="n">flow_func</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> - <span class="sd">"""Compute the value of a minimum (s, t)-cut.</span> +<span class="w"> </span><span class="sd">"""Compute the value of a minimum (s, t)-cut.</span> <span class="sd"> Use the max-flow min-cut theorem, i.e., the capacity of a minimum</span> <span class="sd"> capacity cut is equal to the flow value of a maximum flow.</span> @@ -1115,7 +1115,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/flow/mincost.html b/_modules/networkx/algorithms/flow/mincost.html index ab2bfb03..8bfc9daf 100644 --- a/_modules/networkx/algorithms/flow/mincost.html +++ b/_modules/networkx/algorithms/flow/mincost.html @@ -471,7 +471,7 @@ <div class="viewcode-block" id="min_cost_flow_cost"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.flow.min_cost_flow_cost.html#networkx.algorithms.flow.min_cost_flow_cost">[docs]</a><span class="k">def</span> <span class="nf">min_cost_flow_cost</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">demand</span><span class="o">=</span><span class="s2">"demand"</span><span class="p">,</span> <span class="n">capacity</span><span class="o">=</span><span class="s2">"capacity"</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Find the cost of a minimum cost flow satisfying all demands in digraph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Find the cost of a minimum cost flow satisfying all demands in digraph G.</span> <span class="sd"> G is a digraph with edge costs and capacities and in which nodes</span> <span class="sd"> have demand, i.e., they want to send or receive some amount of</span> @@ -560,7 +560,7 @@ <div class="viewcode-block" id="min_cost_flow"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.flow.min_cost_flow.html#networkx.algorithms.flow.min_cost_flow">[docs]</a><span class="k">def</span> <span class="nf">min_cost_flow</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">demand</span><span class="o">=</span><span class="s2">"demand"</span><span class="p">,</span> <span class="n">capacity</span><span class="o">=</span><span class="s2">"capacity"</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a minimum cost flow satisfying all demands in digraph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a minimum cost flow satisfying all demands in digraph G.</span> <span class="sd"> G is a digraph with edge costs and capacities and in which nodes</span> <span class="sd"> have demand, i.e., they want to send or receive some amount of</span> @@ -648,7 +648,7 @@ <div class="viewcode-block" id="cost_of_flow"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.flow.cost_of_flow.html#networkx.algorithms.flow.cost_of_flow">[docs]</a><span class="k">def</span> <span class="nf">cost_of_flow</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">flowDict</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Compute the cost of the flow given by flowDict on graph G.</span> +<span class="w"> </span><span class="sd">"""Compute the cost of the flow given by flowDict on graph G.</span> <span class="sd"> Note that this function does not check for the validity of the</span> <span class="sd"> flow flowDict. This function will fail if the graph G and the</span> @@ -692,7 +692,7 @@ <div class="viewcode-block" id="max_flow_min_cost"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.flow.max_flow_min_cost.html#networkx.algorithms.flow.max_flow_min_cost">[docs]</a><span class="k">def</span> <span class="nf">max_flow_min_cost</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">capacity</span><span class="o">=</span><span class="s2">"capacity"</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns a maximum (s, t)-flow of minimum cost.</span> +<span class="w"> </span><span class="sd">"""Returns a maximum (s, t)-flow of minimum cost.</span> <span class="sd"> G is a digraph with edge costs and capacities. There is a source</span> <span class="sd"> node s and a sink node t. This function finds a maximum flow from</span> @@ -843,7 +843,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/flow/networksimplex.html b/_modules/networkx/algorithms/flow/networksimplex.html index 50c056f4..e125a490 100644 --- a/_modules/networkx/algorithms/flow/networksimplex.html +++ b/_modules/networkx/algorithms/flow/networksimplex.html @@ -548,7 +548,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">_spanning_tree_initialized</span> <span class="o">=</span> <span class="kc">True</span> <span class="c1"># True only if all the assignments pass</span> <span class="k">def</span> <span class="nf">find_apex</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">q</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Find the lowest common ancestor of nodes p and q in the spanning tree.</span> <span class="sd"> """</span> <span class="n">size_p</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">subtree_size</span><span class="p">[</span><span class="n">p</span><span class="p">]</span> @@ -570,7 +570,7 @@ <span class="k">return</span> <span class="n">p</span> <span class="k">def</span> <span class="nf">trace_path</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">w</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the nodes and edges on the path from node p to its ancestor w.</span> <span class="sd"> """</span> <span class="n">Wn</span> <span class="o">=</span> <span class="p">[</span><span class="n">p</span><span class="p">]</span> @@ -582,7 +582,7 @@ <span class="k">return</span> <span class="n">Wn</span><span class="p">,</span> <span class="n">We</span> <span class="k">def</span> <span class="nf">find_cycle</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">q</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the nodes and edges on the cycle containing edge i == (p, q)</span> <span class="sd"> when the latter is added to the spanning tree.</span> @@ -601,7 +601,7 @@ <span class="k">return</span> <span class="n">Wn</span><span class="p">,</span> <span class="n">We</span> <span class="k">def</span> <span class="nf">augment_flow</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">Wn</span><span class="p">,</span> <span class="n">We</span><span class="p">,</span> <span class="n">f</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Augment f units of flow along a cycle represented by Wn and We.</span> <span class="sd"> """</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">p</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">We</span><span class="p">,</span> <span class="n">Wn</span><span class="p">):</span> @@ -611,7 +611,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">edge_flow</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">-=</span> <span class="n">f</span> <span class="k">def</span> <span class="nf">trace_subtree</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">p</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Yield the nodes in the subtree rooted at a node p.</span> <span class="sd"> """</span> <span class="k">yield</span> <span class="n">p</span> @@ -621,7 +621,7 @@ <span class="k">yield</span> <span class="n">p</span> <span class="k">def</span> <span class="nf">remove_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Remove an edge (s, t) where parent[t] == s from the spanning tree.</span> <span class="sd"> """</span> <span class="n">size_t</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">subtree_size</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> @@ -645,7 +645,7 @@ <span class="n">s</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">parent</span><span class="p">[</span><span class="n">s</span><span class="p">]</span> <span class="k">def</span> <span class="nf">make_root</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">q</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Make a node q the root of its containing subtree.</span> <span class="sd"> """</span> <span class="n">ancestors</span> <span class="o">=</span> <span class="p">[]</span> @@ -683,7 +683,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">last_descendent_dft</span><span class="p">[</span><span class="n">q</span><span class="p">]</span> <span class="o">=</span> <span class="n">last_p</span> <span class="k">def</span> <span class="nf">add_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">q</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Add an edge (p, q) to the spanning tree where q is the root of a subtree.</span> <span class="sd"> """</span> <span class="n">last_p</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">last_descendent_dft</span><span class="p">[</span><span class="n">p</span><span class="p">]</span> @@ -707,7 +707,7 @@ <span class="n">p</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">parent</span><span class="p">[</span><span class="n">p</span><span class="p">]</span> <span class="k">def</span> <span class="nf">update_potentials</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">q</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Update the potentials of the nodes in the subtree rooted at a node</span> <span class="sd"> q connected to its parent p by an edge i.</span> <span class="sd"> """</span> @@ -719,7 +719,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">node_potentials</span><span class="p">[</span><span class="n">q</span><span class="p">]</span> <span class="o">+=</span> <span class="n">d</span> <span class="k">def</span> <span class="nf">reduced_cost</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">i</span><span class="p">):</span> - <span class="sd">"""Returns the reduced cost of an edge i."""</span> +<span class="w"> </span><span class="sd">"""Returns the reduced cost of an edge i."""</span> <span class="n">c</span> <span class="o">=</span> <span class="p">(</span> <span class="bp">self</span><span class="o">.</span><span class="n">edge_weights</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">node_potentials</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">edge_sources</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span> @@ -728,7 +728,7 @@ <span class="k">return</span> <span class="n">c</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">edge_flow</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span> <span class="k">else</span> <span class="o">-</span><span class="n">c</span> <span class="k">def</span> <span class="nf">find_entering_edges</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Yield entering edges until none can be found."""</span> +<span class="w"> </span><span class="sd">"""Yield entering edges until none can be found."""</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">edge_count</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> <span class="k">return</span> @@ -770,7 +770,7 @@ <span class="c1"># optimal.</span> <span class="k">def</span> <span class="nf">residual_capacity</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="n">p</span><span class="p">):</span> - <span class="sd">"""Returns the residual capacity of an edge i in the direction away</span> +<span class="w"> </span><span class="sd">"""Returns the residual capacity of an edge i in the direction away</span> <span class="sd"> from its endpoint p.</span> <span class="sd"> """</span> <span class="k">return</span> <span class="p">(</span> @@ -780,7 +780,7 @@ <span class="p">)</span> <span class="k">def</span> <span class="nf">find_leaving_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">Wn</span><span class="p">,</span> <span class="n">We</span><span class="p">):</span> - <span class="sd">"""Returns the leaving edge in a cycle represented by Wn and We."""</span> +<span class="w"> </span><span class="sd">"""Returns the leaving edge in a cycle represented by Wn and We."""</span> <span class="n">j</span><span class="p">,</span> <span class="n">s</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span> <span class="nb">zip</span><span class="p">(</span><span class="nb">reversed</span><span class="p">(</span><span class="n">We</span><span class="p">),</span> <span class="nb">reversed</span><span class="p">(</span><span class="n">Wn</span><span class="p">)),</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">i_p</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">residual_capacity</span><span class="p">(</span><span class="o">*</span><span class="n">i_p</span><span class="p">),</span> @@ -791,7 +791,7 @@ <div class="viewcode-block" id="network_simplex"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.flow.network_simplex.html#networkx.algorithms.flow.network_simplex">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">network_simplex</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">demand</span><span class="o">=</span><span class="s2">"demand"</span><span class="p">,</span> <span class="n">capacity</span><span class="o">=</span><span class="s2">"capacity"</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Find a minimum cost flow satisfying all demands in digraph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Find a minimum cost flow satisfying all demands in digraph G.</span> <span class="sd"> This is a primal network simplex algorithm that uses the leaving</span> <span class="sd"> arc rule to prevent cycling.</span> @@ -1084,7 +1084,7 @@ <span class="n">flow_dict</span> <span class="o">=</span> <span class="p">{</span><span class="n">n</span><span class="p">:</span> <span class="p">{}</span> <span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="n">DEAF</span><span class="o">.</span><span class="n">node_list</span><span class="p">}</span> <span class="k">def</span> <span class="nf">add_entry</span><span class="p">(</span><span class="n">e</span><span class="p">):</span> - <span class="sd">"""Add a flow dict entry."""</span> +<span class="w"> </span><span class="sd">"""Add a flow dict entry."""</span> <span class="n">d</span> <span class="o">=</span> <span class="n">flow_dict</span><span class="p">[</span><span class="n">e</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">e</span><span class="p">[</span><span class="mi">1</span><span class="p">:</span><span class="o">-</span><span class="mi">2</span><span class="p">]:</span> <span class="k">try</span><span class="p">:</span> @@ -1176,7 +1176,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/flow/preflowpush.html b/_modules/networkx/algorithms/flow/preflowpush.html index 04e5cd8f..eac762cc 100644 --- a/_modules/networkx/algorithms/flow/preflowpush.html +++ b/_modules/networkx/algorithms/flow/preflowpush.html @@ -483,7 +483,7 @@ <span class="k">def</span> <span class="nf">preflow_push_impl</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">capacity</span><span class="p">,</span> <span class="n">residual</span><span class="p">,</span> <span class="n">global_relabel_freq</span><span class="p">,</span> <span class="n">value_only</span><span class="p">):</span> - <span class="sd">"""Implementation of the highest-label preflow-push algorithm."""</span> +<span class="w"> </span><span class="sd">"""Implementation of the highest-label preflow-push algorithm."""</span> <span class="k">if</span> <span class="n">s</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">G</span><span class="p">:</span> <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="sa">f</span><span class="s2">"node </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="n">s</span><span class="p">)</span><span class="si">}</span><span class="s2"> not in graph"</span><span class="p">)</span> <span class="k">if</span> <span class="n">t</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">G</span><span class="p">:</span> @@ -514,7 +514,7 @@ <span class="n">e</span><span class="p">[</span><span class="s2">"flow"</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span> <span class="k">def</span> <span class="nf">reverse_bfs</span><span class="p">(</span><span class="n">src</span><span class="p">):</span> - <span class="sd">"""Perform a reverse breadth-first search from src in the residual</span> +<span class="w"> </span><span class="sd">"""Perform a reverse breadth-first search from src in the residual</span> <span class="sd"> network.</span> <span class="sd"> """</span> <span class="n">heights</span> <span class="o">=</span> <span class="p">{</span><span class="n">src</span><span class="p">:</span> <span class="mi">0</span><span class="p">}</span> @@ -551,7 +551,7 @@ <span class="n">R_nodes</span><span class="p">[</span><span class="n">u</span><span class="p">][</span><span class="s2">"curr_edge"</span><span class="p">]</span> <span class="o">=</span> <span class="n">CurrentEdge</span><span class="p">(</span><span class="n">R_succ</span><span class="p">[</span><span class="n">u</span><span class="p">])</span> <span class="k">def</span> <span class="nf">push</span><span class="p">(</span><span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">flow</span><span class="p">):</span> - <span class="sd">"""Push flow units of flow from u to v."""</span> +<span class="w"> </span><span class="sd">"""Push flow units of flow from u to v."""</span> <span class="n">R_succ</span><span class="p">[</span><span class="n">u</span><span class="p">][</span><span class="n">v</span><span class="p">][</span><span class="s2">"flow"</span><span class="p">]</span> <span class="o">+=</span> <span class="n">flow</span> <span class="n">R_succ</span><span class="p">[</span><span class="n">v</span><span class="p">][</span><span class="n">u</span><span class="p">][</span><span class="s2">"flow"</span><span class="p">]</span> <span class="o">-=</span> <span class="n">flow</span> <span class="n">R_nodes</span><span class="p">[</span><span class="n">u</span><span class="p">][</span><span class="s2">"excess"</span><span class="p">]</span> <span class="o">-=</span> <span class="n">flow</span> @@ -575,7 +575,7 @@ <span class="n">level</span><span class="o">.</span><span class="n">inactive</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">u</span><span class="p">)</span> <span class="k">def</span> <span class="nf">activate</span><span class="p">(</span><span class="n">v</span><span class="p">):</span> - <span class="sd">"""Move a node from the inactive set to the active set of its level."""</span> +<span class="w"> </span><span class="sd">"""Move a node from the inactive set to the active set of its level."""</span> <span class="k">if</span> <span class="n">v</span> <span class="o">!=</span> <span class="n">s</span> <span class="ow">and</span> <span class="n">v</span> <span class="o">!=</span> <span class="n">t</span><span class="p">:</span> <span class="n">level</span> <span class="o">=</span> <span class="n">levels</span><span class="p">[</span><span class="n">R_nodes</span><span class="p">[</span><span class="n">v</span><span class="p">][</span><span class="s2">"height"</span><span class="p">]]</span> <span class="k">if</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">level</span><span class="o">.</span><span class="n">inactive</span><span class="p">:</span> @@ -583,7 +583,7 @@ <span class="n">level</span><span class="o">.</span><span class="n">active</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">v</span><span class="p">)</span> <span class="k">def</span> <span class="nf">relabel</span><span class="p">(</span><span class="n">u</span><span class="p">):</span> - <span class="sd">"""Relabel a node to create an admissible edge."""</span> +<span class="w"> </span><span class="sd">"""Relabel a node to create an admissible edge."""</span> <span class="n">grt</span><span class="o">.</span><span class="n">add_work</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">R_succ</span><span class="p">[</span><span class="n">u</span><span class="p">]))</span> <span class="k">return</span> <span class="p">(</span> <span class="nb">min</span><span class="p">(</span> @@ -595,7 +595,7 @@ <span class="p">)</span> <span class="k">def</span> <span class="nf">discharge</span><span class="p">(</span><span class="n">u</span><span class="p">,</span> <span class="n">is_phase1</span><span class="p">):</span> - <span class="sd">"""Discharge a node until it becomes inactive or, during phase 1 (see</span> +<span class="w"> </span><span class="sd">"""Discharge a node until it becomes inactive or, during phase 1 (see</span> <span class="sd"> below), its height reaches at least n. The node is known to have the</span> <span class="sd"> largest height among active nodes.</span> <span class="sd"> """</span> @@ -636,7 +636,7 @@ <span class="k">return</span> <span class="n">next_height</span> <span class="k">def</span> <span class="nf">gap_heuristic</span><span class="p">(</span><span class="n">height</span><span class="p">):</span> - <span class="sd">"""Apply the gap heuristic."""</span> +<span class="w"> </span><span class="sd">"""Apply the gap heuristic."""</span> <span class="c1"># Move all nodes at levels (height + 1) to max_height to level n + 1.</span> <span class="k">for</span> <span class="n">level</span> <span class="ow">in</span> <span class="n">islice</span><span class="p">(</span><span class="n">levels</span><span class="p">,</span> <span class="n">height</span> <span class="o">+</span> <span class="mi">1</span><span class="p">,</span> <span class="n">max_height</span> <span class="o">+</span> <span class="mi">1</span><span class="p">):</span> <span class="k">for</span> <span class="n">u</span> <span class="ow">in</span> <span class="n">level</span><span class="o">.</span><span class="n">active</span><span class="p">:</span> @@ -649,7 +649,7 @@ <span class="n">level</span><span class="o">.</span><span class="n">inactive</span><span class="o">.</span><span class="n">clear</span><span class="p">()</span> <span class="k">def</span> <span class="nf">global_relabel</span><span class="p">(</span><span class="n">from_sink</span><span class="p">):</span> - <span class="sd">"""Apply the global relabeling heuristic."""</span> +<span class="w"> </span><span class="sd">"""Apply the global relabeling heuristic."""</span> <span class="n">src</span> <span class="o">=</span> <span class="n">t</span> <span class="k">if</span> <span class="n">from_sink</span> <span class="k">else</span> <span class="n">s</span> <span class="n">heights</span> <span class="o">=</span> <span class="n">reverse_bfs</span><span class="p">(</span><span class="n">src</span><span class="p">)</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">from_sink</span><span class="p">:</span> @@ -754,7 +754,7 @@ <div class="viewcode-block" id="preflow_push"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.flow.preflow_push.html#networkx.algorithms.flow.preflow_push">[docs]</a><span class="k">def</span> <span class="nf">preflow_push</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">capacity</span><span class="o">=</span><span class="s2">"capacity"</span><span class="p">,</span> <span class="n">residual</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">global_relabel_freq</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">value_only</span><span class="o">=</span><span class="kc">False</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Find a maximum single-commodity flow using the highest-label</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Find a maximum single-commodity flow using the highest-label</span> <span class="sd"> preflow-push algorithm.</span> <span class="sd"> This function returns the residual network resulting after computing</span> @@ -935,7 +935,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/flow/shortestaugmentingpath.html b/_modules/networkx/algorithms/flow/shortestaugmentingpath.html index 27ebd430..d66305e1 100644 --- a/_modules/networkx/algorithms/flow/shortestaugmentingpath.html +++ b/_modules/networkx/algorithms/flow/shortestaugmentingpath.html @@ -476,7 +476,7 @@ <span class="k">def</span> <span class="nf">shortest_augmenting_path_impl</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">capacity</span><span class="p">,</span> <span class="n">residual</span><span class="p">,</span> <span class="n">two_phase</span><span class="p">,</span> <span class="n">cutoff</span><span class="p">):</span> - <span class="sd">"""Implementation of the shortest augmenting path algorithm."""</span> +<span class="w"> </span><span class="sd">"""Implementation of the shortest augmenting path algorithm."""</span> <span class="k">if</span> <span class="n">s</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">G</span><span class="p">:</span> <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="sa">f</span><span class="s2">"node </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="n">s</span><span class="p">)</span><span class="si">}</span><span class="s2"> not in graph"</span><span class="p">)</span> <span class="k">if</span> <span class="n">t</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">G</span><span class="p">:</span> @@ -531,7 +531,7 @@ <span class="n">inf</span> <span class="o">=</span> <span class="n">R</span><span class="o">.</span><span class="n">graph</span><span class="p">[</span><span class="s2">"inf"</span><span class="p">]</span> <span class="k">def</span> <span class="nf">augment</span><span class="p">(</span><span class="n">path</span><span class="p">):</span> - <span class="sd">"""Augment flow along a path from s to t."""</span> +<span class="w"> </span><span class="sd">"""Augment flow along a path from s to t."""</span> <span class="c1"># Determine the path residual capacity.</span> <span class="n">flow</span> <span class="o">=</span> <span class="n">inf</span> <span class="n">it</span> <span class="o">=</span> <span class="nb">iter</span><span class="p">(</span><span class="n">path</span><span class="p">)</span> @@ -552,7 +552,7 @@ <span class="k">return</span> <span class="n">flow</span> <span class="k">def</span> <span class="nf">relabel</span><span class="p">(</span><span class="n">u</span><span class="p">):</span> - <span class="sd">"""Relabel a node to create an admissible edge."""</span> +<span class="w"> </span><span class="sd">"""Relabel a node to create an admissible edge."""</span> <span class="n">height</span> <span class="o">=</span> <span class="n">n</span> <span class="o">-</span> <span class="mi">1</span> <span class="k">for</span> <span class="n">v</span><span class="p">,</span> <span class="n">attr</span> <span class="ow">in</span> <span class="n">R_succ</span><span class="p">[</span><span class="n">u</span><span class="p">]</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> <span class="k">if</span> <span class="n">attr</span><span class="p">[</span><span class="s2">"flow"</span><span class="p">]</span> <span class="o"><</span> <span class="n">attr</span><span class="p">[</span><span class="s2">"capacity"</span><span class="p">]:</span> @@ -636,7 +636,7 @@ <span class="n">two_phase</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Find a maximum single-commodity flow using the shortest augmenting path</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Find a maximum single-commodity flow using the shortest augmenting path</span> <span class="sd"> algorithm.</span> <span class="sd"> This function returns the residual network resulting after computing</span> @@ -810,7 +810,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/flow/utils.html b/_modules/networkx/algorithms/flow/utils.html index 3a345604..5d37c97e 100644 --- a/_modules/networkx/algorithms/flow/utils.html +++ b/_modules/networkx/algorithms/flow/utils.html @@ -480,7 +480,7 @@ <span class="k">class</span> <span class="nc">CurrentEdge</span><span class="p">:</span> - <span class="sd">"""Mechanism for iterating over out-edges incident to a node in a circular</span> +<span class="w"> </span><span class="sd">"""Mechanism for iterating over out-edges incident to a node in a circular</span> <span class="sd"> manner. StopIteration exception is raised when wraparound occurs.</span> <span class="sd"> """</span> @@ -507,7 +507,7 @@ <span class="k">class</span> <span class="nc">Level</span><span class="p">:</span> - <span class="sd">"""Active and inactive nodes in a level."""</span> +<span class="w"> </span><span class="sd">"""Active and inactive nodes in a level."""</span> <span class="vm">__slots__</span> <span class="o">=</span> <span class="p">(</span><span class="s2">"active"</span><span class="p">,</span> <span class="s2">"inactive"</span><span class="p">)</span> @@ -517,7 +517,7 @@ <span class="k">class</span> <span class="nc">GlobalRelabelThreshold</span><span class="p">:</span> - <span class="sd">"""Measurement of work before the global relabeling heuristic should be</span> +<span class="w"> </span><span class="sd">"""Measurement of work before the global relabeling heuristic should be</span> <span class="sd"> applied.</span> <span class="sd"> """</span> @@ -536,7 +536,7 @@ <div class="viewcode-block" id="build_residual_network"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.flow.build_residual_network.html#networkx.algorithms.flow.build_residual_network">[docs]</a><span class="k">def</span> <span class="nf">build_residual_network</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">capacity</span><span class="p">):</span> - <span class="sd">"""Build a residual network and initialize a zero flow.</span> +<span class="w"> </span><span class="sd">"""Build a residual network and initialize a zero flow.</span> <span class="sd"> The residual network :samp:`R` from an input graph :samp:`G` has the</span> <span class="sd"> same nodes as :samp:`G`. :samp:`R` is a DiGraph that contains a pair</span> @@ -617,7 +617,7 @@ <span class="k">def</span> <span class="nf">detect_unboundedness</span><span class="p">(</span><span class="n">R</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">):</span> - <span class="sd">"""Detect an infinite-capacity s-t path in R."""</span> +<span class="w"> </span><span class="sd">"""Detect an infinite-capacity s-t path in R."""</span> <span class="n">q</span> <span class="o">=</span> <span class="n">deque</span><span class="p">([</span><span class="n">s</span><span class="p">])</span> <span class="n">seen</span> <span class="o">=</span> <span class="p">{</span><span class="n">s</span><span class="p">}</span> <span class="n">inf</span> <span class="o">=</span> <span class="n">R</span><span class="o">.</span><span class="n">graph</span><span class="p">[</span><span class="s2">"inf"</span><span class="p">]</span> @@ -634,7 +634,7 @@ <span class="k">def</span> <span class="nf">build_flow_dict</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">R</span><span class="p">):</span> - <span class="sd">"""Build a flow dictionary from a residual network."""</span> +<span class="w"> </span><span class="sd">"""Build a flow dictionary from a residual network."""</span> <span class="n">flow_dict</span> <span class="o">=</span> <span class="p">{}</span> <span class="k">for</span> <span class="n">u</span> <span class="ow">in</span> <span class="n">G</span><span class="p">:</span> <span class="n">flow_dict</span><span class="p">[</span><span class="n">u</span><span class="p">]</span> <span class="o">=</span> <span class="p">{</span><span class="n">v</span><span class="p">:</span> <span class="mi">0</span> <span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">G</span><span class="p">[</span><span class="n">u</span><span class="p">]}</span> @@ -693,7 +693,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/graph_hashing.html b/_modules/networkx/algorithms/graph_hashing.html index 21e26642..b94e024d 100644 --- a/_modules/networkx/algorithms/graph_hashing.html +++ b/_modules/networkx/algorithms/graph_hashing.html @@ -487,7 +487,7 @@ <span class="k">def</span> <span class="nf">_neighborhood_aggregate</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">node</span><span class="p">,</span> <span class="n">node_labels</span><span class="p">,</span> <span class="n">edge_attr</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Compute new labels for given node by aggregating</span> <span class="sd"> the labels of each node's neighbors.</span> <span class="sd"> """</span> @@ -501,7 +501,7 @@ <div class="viewcode-block" id="weisfeiler_lehman_graph_hash"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.graph_hashing.weisfeiler_lehman_graph_hash.html#networkx.algorithms.graph_hashing.weisfeiler_lehman_graph_hash">[docs]</a><span class="k">def</span> <span class="nf">weisfeiler_lehman_graph_hash</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">edge_attr</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">node_attr</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">digest_size</span><span class="o">=</span><span class="mi">16</span> <span class="p">):</span> - <span class="sd">"""Return Weisfeiler Lehman (WL) graph hash.</span> +<span class="w"> </span><span class="sd">"""Return Weisfeiler Lehman (WL) graph hash.</span> <span class="sd"> The function iteratively aggregates and hashes neighbourhoods of each node.</span> <span class="sd"> After each node's neighbors are hashed to obtain updated node labels,</span> @@ -595,7 +595,7 @@ <span class="sd"> """</span> <span class="k">def</span> <span class="nf">weisfeiler_lehman_step</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="n">edge_attr</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Apply neighborhood aggregation to each node</span> <span class="sd"> in the graph.</span> <span class="sd"> Computes a dictionary with labels for each node.</span> @@ -623,7 +623,7 @@ <div class="viewcode-block" id="weisfeiler_lehman_subgraph_hashes"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.graph_hashing.weisfeiler_lehman_subgraph_hashes.html#networkx.algorithms.graph_hashing.weisfeiler_lehman_subgraph_hashes">[docs]</a><span class="k">def</span> <span class="nf">weisfeiler_lehman_subgraph_hashes</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">edge_attr</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">node_attr</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">digest_size</span><span class="o">=</span><span class="mi">16</span> <span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Return a dictionary of subgraph hashes by node.</span> <span class="sd"> The dictionary is keyed by node to a list of hashes in increasingly</span> @@ -741,7 +741,7 @@ <span class="sd"> """</span> <span class="k">def</span> <span class="nf">weisfeiler_lehman_step</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="n">node_subgraph_hashes</span><span class="p">,</span> <span class="n">edge_attr</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Apply neighborhood aggregation to each node</span> <span class="sd"> in the graph.</span> <span class="sd"> Computes a dictionary with labels for each node.</span> @@ -816,7 +816,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/graphical.html b/_modules/networkx/algorithms/graphical.html index 0553a3fb..b7fce3d7 100644 --- a/_modules/networkx/algorithms/graphical.html +++ b/_modules/networkx/algorithms/graphical.html @@ -478,7 +478,7 @@ <div class="viewcode-block" id="is_graphical"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.graphical.is_graphical.html#networkx.algorithms.graphical.is_graphical">[docs]</a><span class="k">def</span> <span class="nf">is_graphical</span><span class="p">(</span><span class="n">sequence</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s2">"eg"</span><span class="p">):</span> - <span class="sd">"""Returns True if sequence is a valid degree sequence.</span> +<span class="w"> </span><span class="sd">"""Returns True if sequence is a valid degree sequence.</span> <span class="sd"> A degree sequence is valid if some graph can realize it.</span> @@ -550,7 +550,7 @@ <div class="viewcode-block" id="is_valid_degree_sequence_havel_hakimi"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.graphical.is_valid_degree_sequence_havel_hakimi.html#networkx.algorithms.graphical.is_valid_degree_sequence_havel_hakimi">[docs]</a><span class="k">def</span> <span class="nf">is_valid_degree_sequence_havel_hakimi</span><span class="p">(</span><span class="n">deg_sequence</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns True if deg_sequence can be realized by a simple graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns True if deg_sequence can be realized by a simple graph.</span> <span class="sd"> The validation proceeds using the Havel-Hakimi theorem</span> <span class="sd"> [havel1955]_, [hakimi1962]_, [CL1996]_.</span> @@ -626,7 +626,7 @@ <div class="viewcode-block" id="is_valid_degree_sequence_erdos_gallai"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.graphical.is_valid_degree_sequence_erdos_gallai.html#networkx.algorithms.graphical.is_valid_degree_sequence_erdos_gallai">[docs]</a><span class="k">def</span> <span class="nf">is_valid_degree_sequence_erdos_gallai</span><span class="p">(</span><span class="n">deg_sequence</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns True if deg_sequence can be realized by a simple graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns True if deg_sequence can be realized by a simple graph.</span> <span class="sd"> The validation is done using the Erdős-Gallai theorem [EG1960]_.</span> @@ -703,7 +703,7 @@ <div class="viewcode-block" id="is_multigraphical"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.graphical.is_multigraphical.html#networkx.algorithms.graphical.is_multigraphical">[docs]</a><span class="k">def</span> <span class="nf">is_multigraphical</span><span class="p">(</span><span class="n">sequence</span><span class="p">):</span> - <span class="sd">"""Returns True if some multigraph can realize the sequence.</span> +<span class="w"> </span><span class="sd">"""Returns True if some multigraph can realize the sequence.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -740,7 +740,7 @@ <div class="viewcode-block" id="is_pseudographical"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.graphical.is_pseudographical.html#networkx.algorithms.graphical.is_pseudographical">[docs]</a><span class="k">def</span> <span class="nf">is_pseudographical</span><span class="p">(</span><span class="n">sequence</span><span class="p">):</span> - <span class="sd">"""Returns True if some pseudograph can realize the sequence.</span> +<span class="w"> </span><span class="sd">"""Returns True if some pseudograph can realize the sequence.</span> <span class="sd"> Every nonnegative integer sequence with an even sum is pseudographical</span> <span class="sd"> (see [1]_).</span> @@ -773,7 +773,7 @@ <div class="viewcode-block" id="is_digraphical"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.graphical.is_digraphical.html#networkx.algorithms.graphical.is_digraphical">[docs]</a><span class="k">def</span> <span class="nf">is_digraphical</span><span class="p">(</span><span class="n">in_sequence</span><span class="p">,</span> <span class="n">out_sequence</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns True if some directed graph can realize the in- and out-degree</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns True if some directed graph can realize the in- and out-degree</span> <span class="sd"> sequences.</span> <span class="sd"> Parameters</span> @@ -917,7 +917,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/hierarchy.html b/_modules/networkx/algorithms/hierarchy.html index ff7a61f8..48a0787f 100644 --- a/_modules/networkx/algorithms/hierarchy.html +++ b/_modules/networkx/algorithms/hierarchy.html @@ -470,7 +470,7 @@ <div class="viewcode-block" id="flow_hierarchy"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.hierarchy.flow_hierarchy.html#networkx.algorithms.hierarchy.flow_hierarchy">[docs]</a><span class="k">def</span> <span class="nf">flow_hierarchy</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the flow hierarchy of a directed network.</span> +<span class="w"> </span><span class="sd">"""Returns the flow hierarchy of a directed network.</span> <span class="sd"> Flow hierarchy is defined as the fraction of edges not participating</span> <span class="sd"> in cycles in a directed graph [1]_.</span> @@ -559,7 +559,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/hybrid.html b/_modules/networkx/algorithms/hybrid.html index 2da1c5cd..71d62f62 100644 --- a/_modules/networkx/algorithms/hybrid.html +++ b/_modules/networkx/algorithms/hybrid.html @@ -474,7 +474,7 @@ <div class="viewcode-block" id="kl_connected_subgraph"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.hybrid.kl_connected_subgraph.html#networkx.algorithms.hybrid.kl_connected_subgraph">[docs]</a><span class="k">def</span> <span class="nf">kl_connected_subgraph</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">l</span><span class="p">,</span> <span class="n">low_memory</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">same_as_graph</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns the maximum locally `(k, l)`-connected subgraph of `G`.</span> +<span class="w"> </span><span class="sd">"""Returns the maximum locally `(k, l)`-connected subgraph of `G`.</span> <span class="sd"> A graph is locally `(k, l)`-connected if for each edge `(u, v)` in the</span> <span class="sd"> graph there are at least `l` edge-disjoint paths of length at most `k`</span> @@ -578,7 +578,7 @@ <div class="viewcode-block" id="is_kl_connected"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.hybrid.is_kl_connected.html#networkx.algorithms.hybrid.is_kl_connected">[docs]</a><span class="k">def</span> <span class="nf">is_kl_connected</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">l</span><span class="p">,</span> <span class="n">low_memory</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns True if and only if `G` is locally `(k, l)`-connected.</span> +<span class="w"> </span><span class="sd">"""Returns True if and only if `G` is locally `(k, l)`-connected.</span> <span class="sd"> A graph is locally `(k, l)`-connected if for each edge `(u, v)` in the</span> <span class="sd"> graph there are at least `l` edge-disjoint paths of length at most `k`</span> @@ -705,7 +705,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/isolate.html b/_modules/networkx/algorithms/isolate.html index 7a1d5c6d..6df3744c 100644 --- a/_modules/networkx/algorithms/isolate.html +++ b/_modules/networkx/algorithms/isolate.html @@ -471,7 +471,7 @@ <div class="viewcode-block" id="is_isolate"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.isolate.is_isolate.html#networkx.algorithms.isolate.is_isolate">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">is_isolate</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span> - <span class="sd">"""Determines whether a node is an isolate.</span> +<span class="w"> </span><span class="sd">"""Determines whether a node is an isolate.</span> <span class="sd"> An *isolate* is a node with no neighbors (that is, with degree</span> <span class="sd"> zero). For directed graphs, this means no in-neighbors and no</span> @@ -504,7 +504,7 @@ <div class="viewcode-block" id="isolates"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.isolate.isolates.html#networkx.algorithms.isolate.isolates">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">isolates</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Iterator over isolates in the graph.</span> +<span class="w"> </span><span class="sd">"""Iterator over isolates in the graph.</span> <span class="sd"> An *isolate* is a node with no neighbors (that is, with degree</span> <span class="sd"> zero). For directed graphs, this means no in-neighbors and no</span> @@ -550,7 +550,7 @@ <div class="viewcode-block" id="number_of_isolates"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.isolate.number_of_isolates.html#networkx.algorithms.isolate.number_of_isolates">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">number_of_isolates</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the number of isolates in the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the number of isolates in the graph.</span> <span class="sd"> An *isolate* is a node with no neighbors (that is, with degree</span> <span class="sd"> zero). For directed graphs, this means no in-neighbors and no</span> @@ -619,7 +619,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/isomorphism/ismags.html b/_modules/networkx/algorithms/isomorphism/ismags.html index d10ca9d7..475e53d7 100644 --- a/_modules/networkx/algorithms/isomorphism/ismags.html +++ b/_modules/networkx/algorithms/isomorphism/ismags.html @@ -578,7 +578,7 @@ <span class="k">def</span> <span class="nf">are_all_equal</span><span class="p">(</span><span class="n">iterable</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns ``True`` if and only if all elements in `iterable` are equal; and</span> <span class="sd"> ``False`` otherwise.</span> @@ -608,7 +608,7 @@ <span class="k">def</span> <span class="nf">make_partitions</span><span class="p">(</span><span class="n">items</span><span class="p">,</span> <span class="n">test</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Partitions items into sets based on the outcome of ``test(item1, item2)``.</span> <span class="sd"> Pairs of items for which `test` returns `True` end up in the same set.</span> @@ -646,7 +646,7 @@ <span class="k">def</span> <span class="nf">partition_to_color</span><span class="p">(</span><span class="n">partitions</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Creates a dictionary with for every item in partition for every partition</span> <span class="sd"> in partitions the index of partition in partitions.</span> @@ -667,7 +667,7 @@ <span class="k">def</span> <span class="nf">intersect</span><span class="p">(</span><span class="n">collection_of_sets</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Given an collection of sets, returns the intersection of those sets.</span> <span class="sd"> Parameters</span> @@ -688,7 +688,7 @@ <div class="viewcode-block" id="ISMAGS"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.ISMAGS.html#networkx.algorithms.isomorphism.ISMAGS">[docs]</a><span class="k">class</span> <span class="nc">ISMAGS</span><span class="p">:</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Implements the ISMAGS subgraph matching algorith. [1]_ ISMAGS stands for</span> <span class="sd"> "Index-based Subgraph Matching Algorithm with General Symmetries". As the</span> <span class="sd"> name implies, it is symmetry aware and will only generate non-symmetric</span> @@ -731,7 +731,7 @@ <span class="sd"> """</span> <div class="viewcode-block" id="ISMAGS.__init__"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.ISMAGS.html#networkx.algorithms.isomorphism.ISMAGS.__init__">[docs]</a> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">graph</span><span class="p">,</span> <span class="n">subgraph</span><span class="p">,</span> <span class="n">node_match</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">edge_match</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cache</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> <span class="sd"> graph: networkx.Graph</span> @@ -904,7 +904,7 @@ <span class="k">return</span> <span class="n">comparer</span> <div class="viewcode-block" id="ISMAGS.find_isomorphisms"><a class="viewcode-back" href="../../../../reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.find_isomorphisms.html#networkx.algorithms.isomorphism.ISMAGS.find_isomorphisms">[docs]</a> <span class="k">def</span> <span class="nf">find_isomorphisms</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">symmetry</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Find all subgraph isomorphisms between subgraph and graph</span> +<span class="w"> </span><span class="sd">"""Find all subgraph isomorphisms between subgraph and graph</span> <span class="sd"> Finds isomorphisms where :attr:`subgraph` <= :attr:`graph`.</span> @@ -953,7 +953,7 @@ <span class="nd">@staticmethod</span> <span class="k">def</span> <span class="nf">_find_neighbor_color_count</span><span class="p">(</span><span class="n">graph</span><span class="p">,</span> <span class="n">node</span><span class="p">,</span> <span class="n">node_color</span><span class="p">,</span> <span class="n">edge_color</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> For `node` in `graph`, count the number of edges of a specific color</span> <span class="sd"> it has to nodes of a specific color.</span> <span class="sd"> """</span> @@ -969,7 +969,7 @@ <span class="k">return</span> <span class="n">counts</span> <span class="k">def</span> <span class="nf">_get_lookahead_candidates</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns a mapping of {subgraph node: collection of graph nodes} for</span> <span class="sd"> which the graph nodes are feasible candidates for the subgraph node, as</span> <span class="sd"> determined by looking ahead one edge.</span> @@ -1001,7 +1001,7 @@ <span class="k">return</span> <span class="n">candidates</span> <div class="viewcode-block" id="ISMAGS.largest_common_subgraph"><a class="viewcode-back" href="../../../../reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.largest_common_subgraph.html#networkx.algorithms.isomorphism.ISMAGS.largest_common_subgraph">[docs]</a> <span class="k">def</span> <span class="nf">largest_common_subgraph</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">symmetry</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Find the largest common induced subgraphs between :attr:`subgraph` and</span> <span class="sd"> :attr:`graph`.</span> @@ -1040,7 +1040,7 @@ <span class="k">return</span></div> <div class="viewcode-block" id="ISMAGS.analyze_symmetry"><a class="viewcode-back" href="../../../../reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.analyze_symmetry.html#networkx.algorithms.isomorphism.ISMAGS.analyze_symmetry">[docs]</a> <span class="k">def</span> <span class="nf">analyze_symmetry</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">graph</span><span class="p">,</span> <span class="n">node_partitions</span><span class="p">,</span> <span class="n">edge_colors</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Find a minimal set of permutations and corresponding co-sets that</span> <span class="sd"> describe the symmetry of `graph`, given the node and edge equalities</span> <span class="sd"> given by `node_partitions` and `edge_colors`, respectively.</span> @@ -1095,7 +1095,7 @@ <span class="k">return</span> <span class="n">permutations</span><span class="p">,</span> <span class="n">cosets</span></div> <div class="viewcode-block" id="ISMAGS.is_isomorphic"><a class="viewcode-back" href="../../../../reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.is_isomorphic.html#networkx.algorithms.isomorphism.ISMAGS.is_isomorphic">[docs]</a> <span class="k">def</span> <span class="nf">is_isomorphic</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">symmetry</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns True if :attr:`graph` is isomorphic to :attr:`subgraph` and</span> <span class="sd"> False otherwise.</span> @@ -1108,7 +1108,7 @@ <span class="p">)</span></div> <div class="viewcode-block" id="ISMAGS.subgraph_is_isomorphic"><a class="viewcode-back" href="../../../../reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.subgraph_is_isomorphic.html#networkx.algorithms.isomorphism.ISMAGS.subgraph_is_isomorphic">[docs]</a> <span class="k">def</span> <span class="nf">subgraph_is_isomorphic</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">symmetry</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns True if a subgraph of :attr:`graph` is isomorphic to</span> <span class="sd"> :attr:`subgraph` and False otherwise.</span> @@ -1123,7 +1123,7 @@ <span class="k">return</span> <span class="n">isom</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span></div> <div class="viewcode-block" id="ISMAGS.isomorphisms_iter"><a class="viewcode-back" href="../../../../reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.isomorphisms_iter.html#networkx.algorithms.isomorphism.ISMAGS.isomorphisms_iter">[docs]</a> <span class="k">def</span> <span class="nf">isomorphisms_iter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">symmetry</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Does the same as :meth:`find_isomorphisms` if :attr:`graph` and</span> <span class="sd"> :attr:`subgraph` have the same number of nodes.</span> <span class="sd"> """</span> @@ -1131,11 +1131,11 @@ <span class="k">yield from</span> <span class="bp">self</span><span class="o">.</span><span class="n">subgraph_isomorphisms_iter</span><span class="p">(</span><span class="n">symmetry</span><span class="o">=</span><span class="n">symmetry</span><span class="p">)</span></div> <div class="viewcode-block" id="ISMAGS.subgraph_isomorphisms_iter"><a class="viewcode-back" href="../../../../reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.subgraph_isomorphisms_iter.html#networkx.algorithms.isomorphism.ISMAGS.subgraph_isomorphisms_iter">[docs]</a> <span class="k">def</span> <span class="nf">subgraph_isomorphisms_iter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">symmetry</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Alternative name for :meth:`find_isomorphisms`."""</span> +<span class="w"> </span><span class="sd">"""Alternative name for :meth:`find_isomorphisms`."""</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">find_isomorphisms</span><span class="p">(</span><span class="n">symmetry</span><span class="p">)</span></div> <span class="k">def</span> <span class="nf">_find_nodecolor_candidates</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Per node in subgraph find all nodes in graph that have the same color.</span> <span class="sd"> """</span> <span class="n">candidates</span> <span class="o">=</span> <span class="n">defaultdict</span><span class="p">(</span><span class="nb">set</span><span class="p">)</span> @@ -1153,7 +1153,7 @@ <span class="nd">@staticmethod</span> <span class="k">def</span> <span class="nf">_make_constraints</span><span class="p">(</span><span class="n">cosets</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Turn cosets into constraints.</span> <span class="sd"> """</span> <span class="n">constraints</span> <span class="o">=</span> <span class="p">[]</span> @@ -1166,7 +1166,7 @@ <span class="nd">@staticmethod</span> <span class="k">def</span> <span class="nf">_find_node_edge_color</span><span class="p">(</span><span class="n">graph</span><span class="p">,</span> <span class="n">node_colors</span><span class="p">,</span> <span class="n">edge_colors</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> For every node in graph, come up with a color that combines 1) the</span> <span class="sd"> color of the node, and 2) the number of edges of a color to each type</span> <span class="sd"> of node.</span> @@ -1191,7 +1191,7 @@ <span class="nd">@staticmethod</span> <span class="k">def</span> <span class="nf">_get_permutations_by_length</span><span class="p">(</span><span class="n">items</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Get all permutations of items, but only permute items with the same</span> <span class="sd"> length.</span> @@ -1215,7 +1215,7 @@ <span class="nd">@classmethod</span> <span class="k">def</span> <span class="nf">_refine_node_partitions</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">graph</span><span class="p">,</span> <span class="n">node_partitions</span><span class="p">,</span> <span class="n">edge_colors</span><span class="p">,</span> <span class="n">branch</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Given a partition of nodes in graph, make the partitions smaller such</span> <span class="sd"> that all nodes in a partition have 1) the same color, and 2) the same</span> <span class="sd"> number of edges to specific other partitions.</span> @@ -1265,7 +1265,7 @@ <span class="k">yield from</span> <span class="bp">cls</span><span class="o">.</span><span class="n">_refine_node_partitions</span><span class="p">(</span><span class="n">graph</span><span class="p">,</span> <span class="n">n_p</span><span class="p">,</span> <span class="n">edge_colors</span><span class="p">,</span> <span class="n">branch</span><span class="p">)</span> <span class="k">def</span> <span class="nf">_edges_of_same_color</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sgn1</span><span class="p">,</span> <span class="n">sgn2</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns all edges in :attr:`graph` that have the same colour as the</span> <span class="sd"> edge between sgn1 and sgn2 in :attr:`subgraph`.</span> <span class="sd"> """</span> @@ -1282,7 +1282,7 @@ <span class="k">return</span> <span class="n">g_edges</span> <span class="k">def</span> <span class="nf">_map_nodes</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sgn</span><span class="p">,</span> <span class="n">candidates</span><span class="p">,</span> <span class="n">constraints</span><span class="p">,</span> <span class="n">mapping</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">to_be_mapped</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Find all subgraph isomorphisms honoring constraints.</span> <span class="sd"> """</span> <span class="k">if</span> <span class="n">mapping</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> @@ -1362,7 +1362,7 @@ <span class="c1"># del mapping[sgn]</span> <span class="k">def</span> <span class="nf">_largest_common_subgraph</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">candidates</span><span class="p">,</span> <span class="n">constraints</span><span class="p">,</span> <span class="n">to_be_mapped</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Find all largest common subgraphs honoring constraints.</span> <span class="sd"> """</span> <span class="k">if</span> <span class="n">to_be_mapped</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> @@ -1433,7 +1433,7 @@ <span class="nd">@staticmethod</span> <span class="k">def</span> <span class="nf">_remove_node</span><span class="p">(</span><span class="n">node</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">constraints</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns a new set where node has been removed from nodes, subject to</span> <span class="sd"> symmetry constraints. We know, that for every constraint we have</span> <span class="sd"> those subgraph nodes are equal. So whenever we would remove the</span> @@ -1450,7 +1450,7 @@ <span class="nd">@staticmethod</span> <span class="k">def</span> <span class="nf">_find_permutations</span><span class="p">(</span><span class="n">top_partitions</span><span class="p">,</span> <span class="n">bottom_partitions</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Return the pairs of top/bottom partitions where the partitions are</span> <span class="sd"> different. Ensures that all partitions in both top and bottom</span> <span class="sd"> partitions have size 1.</span> @@ -1470,7 +1470,7 @@ <span class="nd">@staticmethod</span> <span class="k">def</span> <span class="nf">_update_orbits</span><span class="p">(</span><span class="n">orbits</span><span class="p">,</span> <span class="n">permutations</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Update orbits based on permutations. Orbits is modified in place.</span> <span class="sd"> For every pair of items in permutations their respective orbits are</span> <span class="sd"> merged.</span> @@ -1501,7 +1501,7 @@ <span class="n">graph</span><span class="p">,</span> <span class="n">edge_colors</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Generate new partitions from top and bottom_partitions where t_node is</span> <span class="sd"> coupled to b_node. pair_idx is the index of the partitions where t_ and</span> <span class="sd"> b_node can be found.</span> @@ -1541,7 +1541,7 @@ <span class="n">orbits</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cosets</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Processes ordered pair partitions as per the reference paper. Finds and</span> <span class="sd"> returns all permutations and cosets that leave the graph unchanged.</span> <span class="sd"> """</span> @@ -1682,7 +1682,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/isomorphism/isomorph.html b/_modules/networkx/algorithms/isomorphism/isomorph.html index d663ba40..640975ae 100644 --- a/_modules/networkx/algorithms/isomorphism/isomorph.html +++ b/_modules/networkx/algorithms/isomorphism/isomorph.html @@ -476,7 +476,7 @@ <div class="viewcode-block" id="could_be_isomorphic"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.could_be_isomorphic.html#networkx.algorithms.isomorphism.could_be_isomorphic">[docs]</a><span class="k">def</span> <span class="nf">could_be_isomorphic</span><span class="p">(</span><span class="n">G1</span><span class="p">,</span> <span class="n">G2</span><span class="p">):</span> - <span class="sd">"""Returns False if graphs are definitely not isomorphic.</span> +<span class="w"> </span><span class="sd">"""Returns False if graphs are definitely not isomorphic.</span> <span class="sd"> True does NOT guarantee isomorphism.</span> <span class="sd"> Parameters</span> @@ -521,7 +521,7 @@ <div class="viewcode-block" id="fast_could_be_isomorphic"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.fast_could_be_isomorphic.html#networkx.algorithms.isomorphism.fast_could_be_isomorphic">[docs]</a><span class="k">def</span> <span class="nf">fast_could_be_isomorphic</span><span class="p">(</span><span class="n">G1</span><span class="p">,</span> <span class="n">G2</span><span class="p">):</span> - <span class="sd">"""Returns False if graphs are definitely not isomorphic.</span> +<span class="w"> </span><span class="sd">"""Returns False if graphs are definitely not isomorphic.</span> <span class="sd"> True does NOT guarantee isomorphism.</span> @@ -561,7 +561,7 @@ <div class="viewcode-block" id="faster_could_be_isomorphic"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.faster_could_be_isomorphic.html#networkx.algorithms.isomorphism.faster_could_be_isomorphic">[docs]</a><span class="k">def</span> <span class="nf">faster_could_be_isomorphic</span><span class="p">(</span><span class="n">G1</span><span class="p">,</span> <span class="n">G2</span><span class="p">):</span> - <span class="sd">"""Returns False if graphs are definitely not isomorphic.</span> +<span class="w"> </span><span class="sd">"""Returns False if graphs are definitely not isomorphic.</span> <span class="sd"> True does NOT guarantee isomorphism.</span> @@ -593,7 +593,7 @@ <div class="viewcode-block" id="is_isomorphic"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.is_isomorphic.html#networkx.algorithms.isomorphism.is_isomorphic">[docs]</a><span class="k">def</span> <span class="nf">is_isomorphic</span><span class="p">(</span><span class="n">G1</span><span class="p">,</span> <span class="n">G2</span><span class="p">,</span> <span class="n">node_match</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">edge_match</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns True if the graphs G1 and G2 are isomorphic and False otherwise.</span> +<span class="w"> </span><span class="sd">"""Returns True if the graphs G1 and G2 are isomorphic and False otherwise.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -750,7 +750,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/isomorphism/isomorphvf2.html b/_modules/networkx/algorithms/isomorphism/isomorphvf2.html index a537cca9..0166cdd5 100644 --- a/_modules/networkx/algorithms/isomorphism/isomorphvf2.html +++ b/_modules/networkx/algorithms/isomorphism/isomorphvf2.html @@ -608,13 +608,13 @@ <span class="k">class</span> <span class="nc">GraphMatcher</span><span class="p">:</span> - <span class="sd">"""Implementation of VF2 algorithm for matching undirected graphs.</span> +<span class="w"> </span><span class="sd">"""Implementation of VF2 algorithm for matching undirected graphs.</span> <span class="sd"> Suitable for Graph and MultiGraph instances.</span> <span class="sd"> """</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G1</span><span class="p">,</span> <span class="n">G2</span><span class="p">):</span> - <span class="sd">"""Initialize GraphMatcher.</span> +<span class="w"> </span><span class="sd">"""Initialize GraphMatcher.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -650,7 +650,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">initialize</span><span class="p">()</span> <span class="k">def</span> <span class="nf">reset_recursion_limit</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Restores the recursion limit."""</span> +<span class="w"> </span><span class="sd">"""Restores the recursion limit."""</span> <span class="c1"># TODO:</span> <span class="c1"># Currently, we use recursion and set the recursion level higher.</span> <span class="c1"># It would be nice to restore the level, but because the</span> @@ -663,7 +663,7 @@ <span class="n">sys</span><span class="o">.</span><span class="n">setrecursionlimit</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">old_recursion_limit</span><span class="p">)</span> <div class="viewcode-block" id="GraphMatcher.candidate_pairs_iter"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.candidate_pairs_iter.html#networkx.algorithms.isomorphism.GraphMatcher.candidate_pairs_iter">[docs]</a> <span class="k">def</span> <span class="nf">candidate_pairs_iter</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Iterator over candidate pairs of nodes in G1 and G2."""</span> +<span class="w"> </span><span class="sd">"""Iterator over candidate pairs of nodes in G1 and G2."""</span> <span class="c1"># All computations are done using the current state!</span> @@ -696,7 +696,7 @@ <span class="c1"># For all other cases, we don't have any candidate pairs.</span> <div class="viewcode-block" id="GraphMatcher.initialize"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.initialize.html#networkx.algorithms.isomorphism.GraphMatcher.initialize">[docs]</a> <span class="k">def</span> <span class="nf">initialize</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Reinitializes the state of the algorithm.</span> +<span class="w"> </span><span class="sd">"""Reinitializes the state of the algorithm.</span> <span class="sd"> This method should be redefined if using something other than GMState.</span> <span class="sd"> If only subclassing GraphMatcher, a redefinition is not necessary.</span> @@ -727,7 +727,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">mapping</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">core_1</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span></div> <div class="viewcode-block" id="GraphMatcher.is_isomorphic"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.is_isomorphic.html#networkx.algorithms.isomorphism.GraphMatcher.is_isomorphic">[docs]</a> <span class="k">def</span> <span class="nf">is_isomorphic</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns True if G1 and G2 are isomorphic graphs."""</span> +<span class="w"> </span><span class="sd">"""Returns True if G1 and G2 are isomorphic graphs."""</span> <span class="c1"># Let's do two very quick checks!</span> <span class="c1"># QUESTION: Should we call faster_graph_could_be_isomorphic(G1,G2)?</span> @@ -750,14 +750,14 @@ <span class="k">return</span> <span class="kc">False</span></div> <div class="viewcode-block" id="GraphMatcher.isomorphisms_iter"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.isomorphisms_iter.html#networkx.algorithms.isomorphism.GraphMatcher.isomorphisms_iter">[docs]</a> <span class="k">def</span> <span class="nf">isomorphisms_iter</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Generator over isomorphisms between G1 and G2."""</span> +<span class="w"> </span><span class="sd">"""Generator over isomorphisms between G1 and G2."""</span> <span class="c1"># Declare that we are looking for a graph-graph isomorphism.</span> <span class="bp">self</span><span class="o">.</span><span class="n">test</span> <span class="o">=</span> <span class="s2">"graph"</span> <span class="bp">self</span><span class="o">.</span><span class="n">initialize</span><span class="p">()</span> <span class="k">yield from</span> <span class="bp">self</span><span class="o">.</span><span class="n">match</span><span class="p">()</span></div> <div class="viewcode-block" id="GraphMatcher.match"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.match.html#networkx.algorithms.isomorphism.GraphMatcher.match">[docs]</a> <span class="k">def</span> <span class="nf">match</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Extends the isomorphism mapping.</span> +<span class="w"> </span><span class="sd">"""Extends the isomorphism mapping.</span> <span class="sd"> This function is called recursively to determine if a complete</span> <span class="sd"> isomorphism can be found between G1 and G2. It cleans up the class</span> @@ -782,7 +782,7 @@ <span class="n">newstate</span><span class="o">.</span><span class="n">restore</span><span class="p">()</span></div> <span class="k">def</span> <span class="nf">semantic_feasibility</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G1_node</span><span class="p">,</span> <span class="n">G2_node</span><span class="p">):</span> - <span class="sd">"""Returns True if adding (G1_node, G2_node) is symantically feasible.</span> +<span class="w"> </span><span class="sd">"""Returns True if adding (G1_node, G2_node) is symantically feasible.</span> <span class="sd"> The semantic feasibility function should return True if it is</span> <span class="sd"> acceptable to add the candidate pair (G1_node, G2_node) to the current</span> @@ -822,7 +822,7 @@ <span class="k">return</span> <span class="kc">True</span> <div class="viewcode-block" id="GraphMatcher.subgraph_is_isomorphic"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.subgraph_is_isomorphic.html#networkx.algorithms.isomorphism.GraphMatcher.subgraph_is_isomorphic">[docs]</a> <span class="k">def</span> <span class="nf">subgraph_is_isomorphic</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns True if a subgraph of G1 is isomorphic to G2."""</span> +<span class="w"> </span><span class="sd">"""Returns True if a subgraph of G1 is isomorphic to G2."""</span> <span class="k">try</span><span class="p">:</span> <span class="n">x</span> <span class="o">=</span> <span class="nb">next</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">subgraph_isomorphisms_iter</span><span class="p">())</span> <span class="k">return</span> <span class="kc">True</span> @@ -830,7 +830,7 @@ <span class="k">return</span> <span class="kc">False</span></div> <span class="k">def</span> <span class="nf">subgraph_is_monomorphic</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns True if a subgraph of G1 is monomorphic to G2."""</span> +<span class="w"> </span><span class="sd">"""Returns True if a subgraph of G1 is monomorphic to G2."""</span> <span class="k">try</span><span class="p">:</span> <span class="n">x</span> <span class="o">=</span> <span class="nb">next</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">subgraph_monomorphisms_iter</span><span class="p">())</span> <span class="k">return</span> <span class="kc">True</span> @@ -840,14 +840,14 @@ <span class="c1"># subgraph_is_isomorphic.__doc__ += "\n" + subgraph.replace('\n','\n'+indent)</span> <div class="viewcode-block" id="GraphMatcher.subgraph_isomorphisms_iter"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.subgraph_isomorphisms_iter.html#networkx.algorithms.isomorphism.GraphMatcher.subgraph_isomorphisms_iter">[docs]</a> <span class="k">def</span> <span class="nf">subgraph_isomorphisms_iter</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Generator over isomorphisms between a subgraph of G1 and G2."""</span> +<span class="w"> </span><span class="sd">"""Generator over isomorphisms between a subgraph of G1 and G2."""</span> <span class="c1"># Declare that we are looking for graph-subgraph isomorphism.</span> <span class="bp">self</span><span class="o">.</span><span class="n">test</span> <span class="o">=</span> <span class="s2">"subgraph"</span> <span class="bp">self</span><span class="o">.</span><span class="n">initialize</span><span class="p">()</span> <span class="k">yield from</span> <span class="bp">self</span><span class="o">.</span><span class="n">match</span><span class="p">()</span></div> <span class="k">def</span> <span class="nf">subgraph_monomorphisms_iter</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Generator over monomorphisms between a subgraph of G1 and G2."""</span> +<span class="w"> </span><span class="sd">"""Generator over monomorphisms between a subgraph of G1 and G2."""</span> <span class="c1"># Declare that we are looking for graph-subgraph monomorphism.</span> <span class="bp">self</span><span class="o">.</span><span class="n">test</span> <span class="o">=</span> <span class="s2">"mono"</span> <span class="bp">self</span><span class="o">.</span><span class="n">initialize</span><span class="p">()</span> @@ -856,7 +856,7 @@ <span class="c1"># subgraph_isomorphisms_iter.__doc__ += "\n" + subgraph.replace('\n','\n'+indent)</span> <div class="viewcode-block" id="GraphMatcher.syntactic_feasibility"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.syntactic_feasibility.html#networkx.algorithms.isomorphism.GraphMatcher.syntactic_feasibility">[docs]</a> <span class="k">def</span> <span class="nf">syntactic_feasibility</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G1_node</span><span class="p">,</span> <span class="n">G2_node</span><span class="p">):</span> - <span class="sd">"""Returns True if adding (G1_node, G2_node) is syntactically feasible.</span> +<span class="w"> </span><span class="sd">"""Returns True if adding (G1_node, G2_node) is syntactically feasible.</span> <span class="sd"> This function returns True if it is adding the candidate pair</span> <span class="sd"> to the current partial isomorphism/monomorphism mapping is allowable.</span> @@ -980,13 +980,13 @@ <span class="k">class</span> <span class="nc">DiGraphMatcher</span><span class="p">(</span><span class="n">GraphMatcher</span><span class="p">):</span> - <span class="sd">"""Implementation of VF2 algorithm for matching directed graphs.</span> +<span class="w"> </span><span class="sd">"""Implementation of VF2 algorithm for matching directed graphs.</span> <span class="sd"> Suitable for DiGraph and MultiDiGraph instances.</span> <span class="sd"> """</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G1</span><span class="p">,</span> <span class="n">G2</span><span class="p">):</span> - <span class="sd">"""Initialize DiGraphMatcher.</span> +<span class="w"> </span><span class="sd">"""Initialize DiGraphMatcher.</span> <span class="sd"> G1 and G2 should be nx.Graph or nx.MultiGraph instances.</span> @@ -1002,7 +1002,7 @@ <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">G1</span><span class="p">,</span> <span class="n">G2</span><span class="p">)</span> <div class="viewcode-block" id="DiGraphMatcher.candidate_pairs_iter"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.candidate_pairs_iter.html#networkx.algorithms.isomorphism.DiGraphMatcher.candidate_pairs_iter">[docs]</a> <span class="k">def</span> <span class="nf">candidate_pairs_iter</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Iterator over candidate pairs of nodes in G1 and G2."""</span> +<span class="w"> </span><span class="sd">"""Iterator over candidate pairs of nodes in G1 and G2."""</span> <span class="c1"># All computations are done using the current state!</span> @@ -1049,7 +1049,7 @@ <span class="c1"># For all other cases, we don't have any candidate pairs.</span> <div class="viewcode-block" id="DiGraphMatcher.initialize"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.initialize.html#networkx.algorithms.isomorphism.DiGraphMatcher.initialize">[docs]</a> <span class="k">def</span> <span class="nf">initialize</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Reinitializes the state of the algorithm.</span> +<span class="w"> </span><span class="sd">"""Reinitializes the state of the algorithm.</span> <span class="sd"> This method should be redefined if using something other than DiGMState.</span> <span class="sd"> If only subclassing GraphMatcher, a redefinition is not necessary.</span> @@ -1083,7 +1083,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">mapping</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">core_1</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span></div> <div class="viewcode-block" id="DiGraphMatcher.syntactic_feasibility"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.syntactic_feasibility.html#networkx.algorithms.isomorphism.DiGraphMatcher.syntactic_feasibility">[docs]</a> <span class="k">def</span> <span class="nf">syntactic_feasibility</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G1_node</span><span class="p">,</span> <span class="n">G2_node</span><span class="p">):</span> - <span class="sd">"""Returns True if adding (G1_node, G2_node) is syntactically feasible.</span> +<span class="w"> </span><span class="sd">"""Returns True if adding (G1_node, G2_node) is syntactically feasible.</span> <span class="sd"> This function returns True if it is adding the candidate pair</span> <span class="sd"> to the current partial isomorphism/monomorphism mapping is allowable.</span> @@ -1307,7 +1307,7 @@ <span class="k">class</span> <span class="nc">GMState</span><span class="p">:</span> - <span class="sd">"""Internal representation of state for the GraphMatcher class.</span> +<span class="w"> </span><span class="sd">"""Internal representation of state for the GraphMatcher class.</span> <span class="sd"> This class is used internally by the GraphMatcher class. It is used</span> <span class="sd"> only to store state specific data. There will be at most G2.order() of</span> @@ -1316,7 +1316,7 @@ <span class="sd"> """</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">GM</span><span class="p">,</span> <span class="n">G1_node</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">G2_node</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Initializes GMState object.</span> +<span class="w"> </span><span class="sd">"""Initializes GMState object.</span> <span class="sd"> Pass in the GraphMatcher to which this GMState belongs and the</span> <span class="sd"> new node pair that will be added to the GraphMatcher's current</span> @@ -1379,7 +1379,7 @@ <span class="n">GM</span><span class="o">.</span><span class="n">inout_2</span><span class="p">[</span><span class="n">node</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">depth</span> <span class="k">def</span> <span class="nf">restore</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Deletes the GMState object and restores the class variables."""</span> +<span class="w"> </span><span class="sd">"""Deletes the GMState object and restores the class variables."""</span> <span class="c1"># First we remove the node that was added from the core vectors.</span> <span class="c1"># Watch out! G1_node == 0 should evaluate to True.</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">G1_node</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">G2_node</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> @@ -1395,7 +1395,7 @@ <span class="k">class</span> <span class="nc">DiGMState</span><span class="p">:</span> - <span class="sd">"""Internal representation of state for the DiGraphMatcher class.</span> +<span class="w"> </span><span class="sd">"""Internal representation of state for the DiGraphMatcher class.</span> <span class="sd"> This class is used internally by the DiGraphMatcher class. It is used</span> <span class="sd"> only to store state specific data. There will be at most G2.order() of</span> @@ -1405,7 +1405,7 @@ <span class="sd"> """</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">GM</span><span class="p">,</span> <span class="n">G1_node</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">G2_node</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Initializes DiGMState object.</span> +<span class="w"> </span><span class="sd">"""Initializes DiGMState object.</span> <span class="sd"> Pass in the DiGraphMatcher to which this DiGMState belongs and the</span> <span class="sd"> new node pair that will be added to the GraphMatcher's current</span> @@ -1508,7 +1508,7 @@ <span class="n">GM</span><span class="o">.</span><span class="n">out_2</span><span class="p">[</span><span class="n">node</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">depth</span> <span class="k">def</span> <span class="nf">restore</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Deletes the DiGMState object and restores the class variables."""</span> +<span class="w"> </span><span class="sd">"""Deletes the DiGMState object and restores the class variables."""</span> <span class="c1"># First we remove the node that was added from the core vectors.</span> <span class="c1"># Watch out! G1_node == 0 should evaluate to True.</span> @@ -1573,7 +1573,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/isomorphism/matchhelpers.html b/_modules/networkx/algorithms/isomorphism/matchhelpers.html index 8818825c..dca838b0 100644 --- a/_modules/networkx/algorithms/isomorphism/matchhelpers.html +++ b/_modules/networkx/algorithms/isomorphism/matchhelpers.html @@ -482,14 +482,14 @@ <span class="k">def</span> <span class="nf">copyfunc</span><span class="p">(</span><span class="n">f</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a deepcopy of a function."""</span> +<span class="w"> </span><span class="sd">"""Returns a deepcopy of a function."""</span> <span class="k">return</span> <span class="n">types</span><span class="o">.</span><span class="n">FunctionType</span><span class="p">(</span> <span class="n">f</span><span class="o">.</span><span class="vm">__code__</span><span class="p">,</span> <span class="n">f</span><span class="o">.</span><span class="vm">__globals__</span><span class="p">,</span> <span class="n">name</span> <span class="ow">or</span> <span class="n">f</span><span class="o">.</span><span class="vm">__name__</span><span class="p">,</span> <span class="n">f</span><span class="o">.</span><span class="vm">__defaults__</span><span class="p">,</span> <span class="n">f</span><span class="o">.</span><span class="vm">__closure__</span> <span class="p">)</span> <span class="k">def</span> <span class="nf">allclose</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">rtol</span><span class="o">=</span><span class="mf">1.0000000000000001e-05</span><span class="p">,</span> <span class="n">atol</span><span class="o">=</span><span class="mf">1e-08</span><span class="p">):</span> - <span class="sd">"""Returns True if x and y are sufficiently close, elementwise.</span> +<span class="w"> </span><span class="sd">"""Returns True if x and y are sufficiently close, elementwise.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -744,7 +744,7 @@ <div class="viewcode-block" id="generic_multiedge_match"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.generic_multiedge_match.html#networkx.algorithms.isomorphism.generic_multiedge_match">[docs]</a><span class="k">def</span> <span class="nf">generic_multiedge_match</span><span class="p">(</span><span class="n">attr</span><span class="p">,</span> <span class="n">default</span><span class="p">,</span> <span class="n">op</span><span class="p">):</span> - <span class="sd">"""Returns a comparison function for a generic attribute.</span> +<span class="w"> </span><span class="sd">"""Returns a comparison function for a generic attribute.</span> <span class="sd"> The value(s) of the attr(s) are compared using the specified</span> <span class="sd"> operators. If all the attributes are equal, then the constructed</span> @@ -867,7 +867,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/isomorphism/tree_isomorphism.html b/_modules/networkx/algorithms/isomorphism/tree_isomorphism.html index fb9d05ea..bddf86ea 100644 --- a/_modules/networkx/algorithms/isomorphism/tree_isomorphism.html +++ b/_modules/networkx/algorithms/isomorphism/tree_isomorphism.html @@ -488,7 +488,7 @@ <span class="k">def</span> <span class="nf">root_trees</span><span class="p">(</span><span class="n">t1</span><span class="p">,</span> <span class="n">root1</span><span class="p">,</span> <span class="n">t2</span><span class="p">,</span> <span class="n">root2</span><span class="p">):</span> - <span class="sd">"""Create a single digraph dT of free trees t1 and t2</span> +<span class="w"> </span><span class="sd">"""Create a single digraph dT of free trees t1 and t2</span> <span class="sd"> # with roots root1 and root2 respectively</span> <span class="sd"> # rename the nodes with consecutive integers</span> <span class="sd"> # so that all nodes get a unique name between both trees</span> @@ -564,7 +564,7 @@ <div class="viewcode-block" id="rooted_tree_isomorphism"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.tree_isomorphism.rooted_tree_isomorphism.html#networkx.algorithms.isomorphism.tree_isomorphism.rooted_tree_isomorphism">[docs]</a><span class="k">def</span> <span class="nf">rooted_tree_isomorphism</span><span class="p">(</span><span class="n">t1</span><span class="p">,</span> <span class="n">root1</span><span class="p">,</span> <span class="n">t2</span><span class="p">,</span> <span class="n">root2</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Given two rooted trees `t1` and `t2`,</span> <span class="sd"> with roots `root1` and `root2` respectivly</span> <span class="sd"> this routine will determine if they are isomorphic.</span> @@ -671,7 +671,7 @@ <div class="viewcode-block" id="tree_isomorphism"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.tree_isomorphism.tree_isomorphism.html#networkx.algorithms.isomorphism.tree_isomorphism.tree_isomorphism">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">,</span> <span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">tree_isomorphism</span><span class="p">(</span><span class="n">t1</span><span class="p">,</span> <span class="n">t2</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Given two undirected (or free) trees `t1` and `t2`,</span> <span class="sd"> this routine will determine if they are isomorphic.</span> <span class="sd"> It returns the isomorphism, a mapping of the nodes of `t1` onto the nodes</span> @@ -791,7 +791,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/isomorphism/vf2pp.html b/_modules/networkx/algorithms/isomorphism/vf2pp.html index 47fca9ea..8379e377 100644 --- a/_modules/networkx/algorithms/isomorphism/vf2pp.html +++ b/_modules/networkx/algorithms/isomorphism/vf2pp.html @@ -560,7 +560,7 @@ <div class="viewcode-block" id="vf2pp_isomorphism"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.vf2pp.vf2pp_isomorphism.html#networkx.algorithms.isomorphism.vf2pp.vf2pp_isomorphism">[docs]</a><span class="k">def</span> <span class="nf">vf2pp_isomorphism</span><span class="p">(</span><span class="n">G1</span><span class="p">,</span> <span class="n">G2</span><span class="p">,</span> <span class="n">node_label</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">default_label</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Return an isomorphic mapping between `G1` and `G2` if it exists.</span> +<span class="w"> </span><span class="sd">"""Return an isomorphic mapping between `G1` and `G2` if it exists.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -590,7 +590,7 @@ <div class="viewcode-block" id="vf2pp_is_isomorphic"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.vf2pp.vf2pp_is_isomorphic.html#networkx.algorithms.isomorphism.vf2pp.vf2pp_is_isomorphic">[docs]</a><span class="k">def</span> <span class="nf">vf2pp_is_isomorphic</span><span class="p">(</span><span class="n">G1</span><span class="p">,</span> <span class="n">G2</span><span class="p">,</span> <span class="n">node_label</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">default_label</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Examines whether G1 and G2 are isomorphic.</span> +<span class="w"> </span><span class="sd">"""Examines whether G1 and G2 are isomorphic.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -618,7 +618,7 @@ <div class="viewcode-block" id="vf2pp_all_isomorphisms"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.vf2pp.vf2pp_all_isomorphisms.html#networkx.algorithms.isomorphism.vf2pp.vf2pp_all_isomorphisms">[docs]</a><span class="k">def</span> <span class="nf">vf2pp_all_isomorphisms</span><span class="p">(</span><span class="n">G1</span><span class="p">,</span> <span class="n">G2</span><span class="p">,</span> <span class="n">node_label</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">default_label</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Yields all the possible mappings between G1 and G2.</span> +<span class="w"> </span><span class="sd">"""Yields all the possible mappings between G1 and G2.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -746,7 +746,7 @@ <span class="k">def</span> <span class="nf">_initialize_parameters</span><span class="p">(</span><span class="n">G1</span><span class="p">,</span> <span class="n">G2</span><span class="p">,</span> <span class="n">G2_degree</span><span class="p">,</span> <span class="n">node_label</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">default_label</span><span class="o">=-</span><span class="mi">1</span><span class="p">):</span> - <span class="sd">"""Initializes all the necessary parameters for VF2++</span> +<span class="w"> </span><span class="sd">"""Initializes all the necessary parameters for VF2++</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -870,7 +870,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/isomorphism/vf2userfunc.html b/_modules/networkx/algorithms/isomorphism/vf2userfunc.html index 800ca5f4..310610e2 100644 --- a/_modules/networkx/algorithms/isomorphism/vf2userfunc.html +++ b/_modules/networkx/algorithms/isomorphism/vf2userfunc.html @@ -500,7 +500,7 @@ <span class="k">def</span> <span class="nf">_semantic_feasibility</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G1_node</span><span class="p">,</span> <span class="n">G2_node</span><span class="p">):</span> - <span class="sd">"""Returns True if mapping G1_node to G2_node is semantically feasible."""</span> +<span class="w"> </span><span class="sd">"""Returns True if mapping G1_node to G2_node is semantically feasible."""</span> <span class="c1"># Make sure the nodes match</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">node_match</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> <span class="n">nm</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">node_match</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">G1</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="n">G1_node</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">G2</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="n">G2_node</span><span class="p">])</span> @@ -535,10 +535,10 @@ <span class="k">class</span> <span class="nc">GraphMatcher</span><span class="p">(</span><span class="n">vf2</span><span class="o">.</span><span class="n">GraphMatcher</span><span class="p">):</span> - <span class="sd">"""VF2 isomorphism checker for undirected graphs."""</span> +<span class="w"> </span><span class="sd">"""VF2 isomorphism checker for undirected graphs."""</span> <div class="viewcode-block" id="GraphMatcher.__init__"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.__init__.html#networkx.algorithms.isomorphism.GraphMatcher.__init__">[docs]</a> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G1</span><span class="p">,</span> <span class="n">G2</span><span class="p">,</span> <span class="n">node_match</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">edge_match</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Initialize graph matcher.</span> +<span class="w"> </span><span class="sd">"""Initialize graph matcher.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -582,10 +582,10 @@ <span class="k">class</span> <span class="nc">DiGraphMatcher</span><span class="p">(</span><span class="n">vf2</span><span class="o">.</span><span class="n">DiGraphMatcher</span><span class="p">):</span> - <span class="sd">"""VF2 isomorphism checker for directed graphs."""</span> +<span class="w"> </span><span class="sd">"""VF2 isomorphism checker for directed graphs."""</span> <div class="viewcode-block" id="DiGraphMatcher.__init__"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.__init__.html#networkx.algorithms.isomorphism.DiGraphMatcher.__init__">[docs]</a> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G1</span><span class="p">,</span> <span class="n">G2</span><span class="p">,</span> <span class="n">node_match</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">edge_match</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Initialize graph matcher.</span> +<span class="w"> </span><span class="sd">"""Initialize graph matcher.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -626,7 +626,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">G2_adj</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">G2</span><span class="o">.</span><span class="n">adj</span></div> <div class="viewcode-block" id="DiGraphMatcher.semantic_feasibility"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.semantic_feasibility.html#networkx.algorithms.isomorphism.DiGraphMatcher.semantic_feasibility">[docs]</a> <span class="k">def</span> <span class="nf">semantic_feasibility</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G1_node</span><span class="p">,</span> <span class="n">G2_node</span><span class="p">):</span> - <span class="sd">"""Returns True if mapping G1_node to G2_node is semantically feasible."""</span> +<span class="w"> </span><span class="sd">"""Returns True if mapping G1_node to G2_node is semantically feasible."""</span> <span class="c1"># Test node_match and also test edge_match on successors</span> <span class="n">feasible</span> <span class="o">=</span> <span class="n">_semantic_feasibility</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G1_node</span><span class="p">,</span> <span class="n">G2_node</span><span class="p">)</span> @@ -649,13 +649,13 @@ <span class="k">class</span> <span class="nc">MultiGraphMatcher</span><span class="p">(</span><span class="n">GraphMatcher</span><span class="p">):</span> - <span class="sd">"""VF2 isomorphism checker for undirected multigraphs."""</span> +<span class="w"> </span><span class="sd">"""VF2 isomorphism checker for undirected multigraphs."""</span> <span class="k">pass</span> <span class="k">class</span> <span class="nc">MultiDiGraphMatcher</span><span class="p">(</span><span class="n">DiGraphMatcher</span><span class="p">):</span> - <span class="sd">"""VF2 isomorphism checker for directed multigraphs."""</span> +<span class="w"> </span><span class="sd">"""VF2 isomorphism checker for directed multigraphs."""</span> <span class="k">pass</span> </pre></div> @@ -709,7 +709,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/link_analysis/hits_alg.html b/_modules/networkx/algorithms/link_analysis/hits_alg.html index ee6c543a..ddb890c9 100644 --- a/_modules/networkx/algorithms/link_analysis/hits_alg.html +++ b/_modules/networkx/algorithms/link_analysis/hits_alg.html @@ -470,7 +470,7 @@ <div class="viewcode-block" id="hits"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.link_analysis.hits_alg.hits.html#networkx.algorithms.link_analysis.hits_alg.hits">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">hits</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mf">1.0e-8</span><span class="p">,</span> <span class="n">nstart</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Returns HITS hubs and authorities values for nodes.</span> +<span class="w"> </span><span class="sd">"""Returns HITS hubs and authorities values for nodes.</span> <span class="sd"> The HITS algorithm computes two numbers for a node.</span> <span class="sd"> Authorities estimates the node value based on the incoming links.</span> @@ -609,7 +609,7 @@ <span class="k">def</span> <span class="nf">_hits_numpy</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Returns HITS hubs and authorities values for nodes.</span> +<span class="w"> </span><span class="sd">"""Returns HITS hubs and authorities values for nodes.</span> <span class="sd"> The HITS algorithm computes two numbers for a node.</span> <span class="sd"> Authorities estimates the node value based on the incoming links.</span> @@ -693,7 +693,7 @@ <span class="k">def</span> <span class="nf">_hits_scipy</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mf">1.0e-6</span><span class="p">,</span> <span class="n">nstart</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Returns HITS hubs and authorities values for nodes.</span> +<span class="w"> </span><span class="sd">"""Returns HITS hubs and authorities values for nodes.</span> <span class="sd"> The HITS algorithm computes two numbers for a node.</span> @@ -847,7 +847,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/link_analysis/pagerank_alg.html b/_modules/networkx/algorithms/link_analysis/pagerank_alg.html index 179c6930..cba43835 100644 --- a/_modules/networkx/algorithms/link_analysis/pagerank_alg.html +++ b/_modules/networkx/algorithms/link_analysis/pagerank_alg.html @@ -480,7 +480,7 @@ <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">dangling</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns the PageRank of the nodes in the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the PageRank of the nodes in the graph.</span> <span class="sd"> PageRank computes a ranking of the nodes in the graph G based on</span> <span class="sd"> the structure of the incoming links. It was originally designed as</span> @@ -638,7 +638,7 @@ <span class="k">def</span> <span class="nf">google_matrix</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.85</span><span class="p">,</span> <span class="n">personalization</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">dangling</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Returns the Google matrix of the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the Google matrix of the graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -733,7 +733,7 @@ <span class="k">def</span> <span class="nf">_pagerank_numpy</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.85</span><span class="p">,</span> <span class="n">personalization</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">dangling</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Returns the PageRank of the nodes in the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the PageRank of the nodes in the graph.</span> <span class="sd"> PageRank computes a ranking of the nodes in the graph G based on</span> <span class="sd"> the structure of the incoming links. It was originally designed as</span> @@ -827,7 +827,7 @@ <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">dangling</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns the PageRank of the nodes in the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the PageRank of the nodes in the graph.</span> <span class="sd"> PageRank computes a ranking of the nodes in the graph G based on</span> <span class="sd"> the structure of the incoming links. It was originally designed as</span> @@ -1010,7 +1010,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/link_prediction.html b/_modules/networkx/algorithms/link_prediction.html index d1c1c472..e7df6b9b 100644 --- a/_modules/networkx/algorithms/link_prediction.html +++ b/_modules/networkx/algorithms/link_prediction.html @@ -484,7 +484,7 @@ <span class="k">def</span> <span class="nf">_apply_prediction</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">func</span><span class="p">,</span> <span class="n">ebunch</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Applies the given function to each edge in the specified iterable</span> +<span class="w"> </span><span class="sd">"""Applies the given function to each edge in the specified iterable</span> <span class="sd"> of edges.</span> <span class="sd"> `G` is an instance of :class:`networkx.Graph`.</span> @@ -506,7 +506,7 @@ <div class="viewcode-block" id="resource_allocation_index"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.link_prediction.resource_allocation_index.html#networkx.algorithms.link_prediction.resource_allocation_index">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">resource_allocation_index</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">ebunch</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the resource allocation index of all node pairs in ebunch.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the resource allocation index of all node pairs in ebunch.</span> <span class="sd"> Resource allocation index of `u` and `v` is defined as</span> @@ -561,7 +561,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">jaccard_coefficient</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">ebunch</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the Jaccard coefficient of all node pairs in ebunch.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the Jaccard coefficient of all node pairs in ebunch.</span> <span class="sd"> Jaccard coefficient of nodes `u` and `v` is defined as</span> @@ -617,7 +617,7 @@ <div class="viewcode-block" id="adamic_adar_index"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.link_prediction.adamic_adar_index.html#networkx.algorithms.link_prediction.adamic_adar_index">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">adamic_adar_index</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">ebunch</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the Adamic-Adar index of all node pairs in ebunch.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the Adamic-Adar index of all node pairs in ebunch.</span> <span class="sd"> Adamic-Adar index of `u` and `v` is defined as</span> @@ -672,7 +672,7 @@ <div class="viewcode-block" id="common_neighbor_centrality"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.link_prediction.common_neighbor_centrality.html#networkx.algorithms.link_prediction.common_neighbor_centrality">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">common_neighbor_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">ebunch</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.8</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Return the CCPA score for each pair of nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Return the CCPA score for each pair of nodes.</span> <span class="sd"> Compute the Common Neighbor and Centrality based Parameterized Algorithm(CCPA)</span> <span class="sd"> score of all node pairs in ebunch.</span> @@ -769,7 +769,7 @@ <div class="viewcode-block" id="preferential_attachment"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.link_prediction.preferential_attachment.html#networkx.algorithms.link_prediction.preferential_attachment">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">preferential_attachment</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">ebunch</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the preferential attachment score of all node pairs in ebunch.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the preferential attachment score of all node pairs in ebunch.</span> <span class="sd"> Preferential attachment score of `u` and `v` is defined as</span> @@ -822,7 +822,7 @@ <div class="viewcode-block" id="cn_soundarajan_hopcroft"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.link_prediction.cn_soundarajan_hopcroft.html#networkx.algorithms.link_prediction.cn_soundarajan_hopcroft">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">cn_soundarajan_hopcroft</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">ebunch</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">community</span><span class="o">=</span><span class="s2">"community"</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Count the number of common neighbors of all node pairs in ebunch</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Count the number of common neighbors of all node pairs in ebunch</span> <span class="sd"> using community information.</span> <span class="sd"> For two nodes $u$ and $v$, this function computes the number of</span> @@ -896,7 +896,7 @@ <div class="viewcode-block" id="ra_index_soundarajan_hopcroft"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.link_prediction.ra_index_soundarajan_hopcroft.html#networkx.algorithms.link_prediction.ra_index_soundarajan_hopcroft">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">ra_index_soundarajan_hopcroft</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">ebunch</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">community</span><span class="o">=</span><span class="s2">"community"</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the resource allocation index of all node pairs in</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the resource allocation index of all node pairs in</span> <span class="sd"> ebunch using community information.</span> <span class="sd"> For two nodes $u$ and $v$, this function computes the resource</span> @@ -971,7 +971,7 @@ <div class="viewcode-block" id="within_inter_cluster"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.link_prediction.within_inter_cluster.html#networkx.algorithms.link_prediction.within_inter_cluster">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">within_inter_cluster</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">ebunch</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">delta</span><span class="o">=</span><span class="mf">0.001</span><span class="p">,</span> <span class="n">community</span><span class="o">=</span><span class="s2">"community"</span><span class="p">):</span> - <span class="sd">"""Compute the ratio of within- and inter-cluster common neighbors</span> +<span class="w"> </span><span class="sd">"""Compute the ratio of within- and inter-cluster common neighbors</span> <span class="sd"> of all node pairs in ebunch.</span> <span class="sd"> For two nodes `u` and `v`, if a common neighbor `w` belongs to the</span> @@ -1052,7 +1052,7 @@ <span class="k">def</span> <span class="nf">_community</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">community</span><span class="p">):</span> - <span class="sd">"""Get the community of the given node."""</span> +<span class="w"> </span><span class="sd">"""Get the community of the given node."""</span> <span class="n">node_u</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="n">u</span><span class="p">]</span> <span class="k">try</span><span class="p">:</span> <span class="k">return</span> <span class="n">node_u</span><span class="p">[</span><span class="n">community</span><span class="p">]</span> @@ -1109,7 +1109,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/lowest_common_ancestors.html b/_modules/networkx/algorithms/lowest_common_ancestors.html index 401c7bb8..a6f48279 100644 --- a/_modules/networkx/algorithms/lowest_common_ancestors.html +++ b/_modules/networkx/algorithms/lowest_common_ancestors.html @@ -478,7 +478,7 @@ <div class="viewcode-block" id="all_pairs_lowest_common_ancestor"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.lowest_common_ancestors.all_pairs_lowest_common_ancestor.html#networkx.algorithms.lowest_common_ancestors.all_pairs_lowest_common_ancestor">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">all_pairs_lowest_common_ancestor</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">pairs</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Return the lowest common ancestor of all pairs or the provided pairs</span> +<span class="w"> </span><span class="sd">"""Return the lowest common ancestor of all pairs or the provided pairs</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -540,7 +540,7 @@ <span class="k">for</span> <span class="n">pair</span> <span class="ow">in</span> <span class="n">pairs</span><span class="p">:</span> <span class="k">if</span> <span class="nb">set</span><span class="p">(</span><span class="n">pair</span><span class="p">)</span> <span class="o">-</span> <span class="n">nodeset</span><span class="p">:</span> <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NodeNotFound</span><span class="p">(</span> - <span class="sa">f</span><span class="s2">"Node(s) </span><span class="si">{</span><span class="nb">set</span><span class="p">(</span><span class="n">pair</span><span class="p">)</span> <span class="o">-</span> <span class="n">nodeset</span><span class="si">}</span><span class="s2"> from pair </span><span class="si">{</span><span class="n">pair</span><span class="si">}</span><span class="s2"> not in G."</span> + <span class="sa">f</span><span class="s2">"Node(s) </span><span class="si">{</span><span class="nb">set</span><span class="p">(</span><span class="n">pair</span><span class="p">)</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="n">nodeset</span><span class="si">}</span><span class="s2"> from pair </span><span class="si">{</span><span class="n">pair</span><span class="si">}</span><span class="s2"> not in G."</span> <span class="p">)</span> <span class="c1"># Once input validation is done, construct the generator</span> @@ -575,7 +575,7 @@ <div class="viewcode-block" id="lowest_common_ancestor"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.lowest_common_ancestors.lowest_common_ancestor.html#networkx.algorithms.lowest_common_ancestors.lowest_common_ancestor">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">lowest_common_ancestor</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">node1</span><span class="p">,</span> <span class="n">node2</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute the lowest common ancestor of the given pair of nodes.</span> +<span class="w"> </span><span class="sd">"""Compute the lowest common ancestor of the given pair of nodes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -612,7 +612,7 @@ <div class="viewcode-block" id="tree_all_pairs_lowest_common_ancestor"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.lowest_common_ancestors.tree_all_pairs_lowest_common_ancestor.html#networkx.algorithms.lowest_common_ancestors.tree_all_pairs_lowest_common_ancestor">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">tree_all_pairs_lowest_common_ancestor</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">root</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">pairs</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Yield the lowest common ancestor for sets of pairs in a tree.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Yield the lowest common ancestor for sets of pairs in a tree.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -777,7 +777,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/matching.html b/_modules/networkx/algorithms/matching.html index 0acd3ebc..c413ddd7 100644 --- a/_modules/networkx/algorithms/matching.html +++ b/_modules/networkx/algorithms/matching.html @@ -481,7 +481,7 @@ <div class="viewcode-block" id="maximal_matching"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.matching.maximal_matching.html#networkx.algorithms.matching.maximal_matching">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">maximal_matching</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Find a maximal matching in the graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Find a maximal matching in the graph.</span> <span class="sd"> A matching is a subset of edges in which no node occurs more than once.</span> <span class="sd"> A maximal matching cannot add more edges and still be a matching.</span> @@ -520,7 +520,7 @@ <span class="k">def</span> <span class="nf">matching_dict_to_set</span><span class="p">(</span><span class="n">matching</span><span class="p">):</span> - <span class="sd">"""Converts matching dict format to matching set format</span> +<span class="w"> </span><span class="sd">"""Converts matching dict format to matching set format</span> <span class="sd"> Converts a dictionary representing a matching (as returned by</span> <span class="sd"> :func:`max_weight_matching`) to a set representing a matching (as</span> @@ -545,7 +545,7 @@ <div class="viewcode-block" id="is_matching"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.matching.is_matching.html#networkx.algorithms.matching.is_matching">[docs]</a><span class="k">def</span> <span class="nf">is_matching</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">matching</span><span class="p">):</span> - <span class="sd">"""Return True if ``matching`` is a valid matching of ``G``</span> +<span class="w"> </span><span class="sd">"""Return True if ``matching`` is a valid matching of ``G``</span> <span class="sd"> A *matching* in a graph is a set of edges in which no two distinct</span> <span class="sd"> edges share a common endpoint. Each node is incident to at most one</span> @@ -605,7 +605,7 @@ <div class="viewcode-block" id="is_maximal_matching"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.matching.is_maximal_matching.html#networkx.algorithms.matching.is_maximal_matching">[docs]</a><span class="k">def</span> <span class="nf">is_maximal_matching</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">matching</span><span class="p">):</span> - <span class="sd">"""Return True if ``matching`` is a maximal matching of ``G``</span> +<span class="w"> </span><span class="sd">"""Return True if ``matching`` is a maximal matching of ``G``</span> <span class="sd"> A *maximal matching* in a graph is a matching in which adding any</span> <span class="sd"> edge would cause the set to no longer be a valid matching.</span> @@ -666,7 +666,7 @@ <div class="viewcode-block" id="is_perfect_matching"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.matching.is_perfect_matching.html#networkx.algorithms.matching.is_perfect_matching">[docs]</a><span class="k">def</span> <span class="nf">is_perfect_matching</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">matching</span><span class="p">):</span> - <span class="sd">"""Return True if ``matching`` is a perfect matching for ``G``</span> +<span class="w"> </span><span class="sd">"""Return True if ``matching`` is a perfect matching for ``G``</span> <span class="sd"> A *perfect matching* in a graph is a matching in which exactly one edge</span> <span class="sd"> is incident upon each vertex.</span> @@ -719,7 +719,7 @@ <div class="viewcode-block" id="min_weight_matching"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.matching.min_weight_matching.html#networkx.algorithms.matching.min_weight_matching">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">min_weight_matching</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Computing a minimum-weight maximal matching of G.</span> +<span class="w"> </span><span class="sd">"""Computing a minimum-weight maximal matching of G.</span> <span class="sd"> Use the maximum-weight algorithm with edge weights subtracted</span> <span class="sd"> from the maximum weight of all edges.</span> @@ -779,7 +779,7 @@ <div class="viewcode-block" id="max_weight_matching"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.matching.max_weight_matching.html#networkx.algorithms.matching.max_weight_matching">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">max_weight_matching</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">maxcardinality</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Compute a maximum-weighted matching of G.</span> +<span class="w"> </span><span class="sd">"""Compute a maximum-weighted matching of G.</span> <span class="sd"> A matching is a subset of edges in which no node occurs more than once.</span> <span class="sd"> The weight of a matching is the sum of the weights of its edges.</span> @@ -852,12 +852,12 @@ <span class="c1">#</span> <span class="k">class</span> <span class="nc">NoNode</span><span class="p">:</span> - <span class="sd">"""Dummy value which is different from any node."""</span> +<span class="w"> </span><span class="sd">"""Dummy value which is different from any node."""</span> <span class="k">pass</span> <span class="k">class</span> <span class="nc">Blossom</span><span class="p">:</span> - <span class="sd">"""Representation of a non-trivial blossom or sub-blossom."""</span> +<span class="w"> </span><span class="sd">"""Representation of a non-trivial blossom or sub-blossom."""</span> <span class="vm">__slots__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"childs"</span><span class="p">,</span> <span class="s2">"edges"</span><span class="p">,</span> <span class="s2">"mybestedges"</span><span class="p">]</span> @@ -1620,7 +1620,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/minors/contraction.html b/_modules/networkx/algorithms/minors/contraction.html index 8f6025f2..90cd96a0 100644 --- a/_modules/networkx/algorithms/minors/contraction.html +++ b/_modules/networkx/algorithms/minors/contraction.html @@ -481,7 +481,7 @@ <div class="viewcode-block" id="equivalence_classes"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.minors.equivalence_classes.html#networkx.algorithms.minors.equivalence_classes">[docs]</a><span class="k">def</span> <span class="nf">equivalence_classes</span><span class="p">(</span><span class="n">iterable</span><span class="p">,</span> <span class="n">relation</span><span class="p">):</span> - <span class="sd">"""Returns equivalence classes of `relation` when applied to `iterable`.</span> +<span class="w"> </span><span class="sd">"""Returns equivalence classes of `relation` when applied to `iterable`.</span> <span class="sd"> The equivalence classes, or blocks, consist of objects from `iterable`</span> <span class="sd"> which are all equivalent. They are defined to be equivalent if the</span> @@ -566,7 +566,7 @@ <span class="n">relabel</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns the quotient graph of `G` under the specified equivalence</span> +<span class="w"> </span><span class="sd">"""Returns the quotient graph of `G` under the specified equivalence</span> <span class="sd"> relation on nodes.</span> <span class="sd"> Parameters</span> @@ -796,7 +796,7 @@ <span class="n">relabel</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Construct the quotient graph assuming input has been checked"""</span> +<span class="w"> </span><span class="sd">"""Construct the quotient graph assuming input has been checked"""</span> <span class="k">if</span> <span class="n">create_using</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> <span class="n">H</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="vm">__class__</span><span class="p">()</span> <span class="k">else</span><span class="p">:</span> @@ -872,7 +872,7 @@ <div class="viewcode-block" id="contracted_nodes"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.minors.contracted_nodes.html#networkx.algorithms.minors.contracted_nodes">[docs]</a><span class="k">def</span> <span class="nf">contracted_nodes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">self_loops</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Returns the graph that results from contracting `u` and `v`.</span> +<span class="w"> </span><span class="sd">"""Returns the graph that results from contracting `u` and `v`.</span> <span class="sd"> Node contraction identifies the two nodes as a single node incident to any</span> <span class="sd"> edge that was incident to the original two nodes.</span> @@ -994,7 +994,7 @@ <div class="viewcode-block" id="contracted_edge"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.minors.contracted_edge.html#networkx.algorithms.minors.contracted_edge">[docs]</a><span class="k">def</span> <span class="nf">contracted_edge</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">edge</span><span class="p">,</span> <span class="n">self_loops</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Returns the graph that results from contracting the specified edge.</span> +<span class="w"> </span><span class="sd">"""Returns the graph that results from contracting the specified edge.</span> <span class="sd"> Edge contraction identifies the two endpoints of the edge as a single node</span> <span class="sd"> incident to any edge that was incident to the original two nodes. A graph</span> @@ -1111,7 +1111,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/mis.html b/_modules/networkx/algorithms/mis.html index dfca32a0..d9143cb7 100644 --- a/_modules/networkx/algorithms/mis.html +++ b/_modules/networkx/algorithms/mis.html @@ -474,7 +474,7 @@ <div class="viewcode-block" id="maximal_independent_set"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.mis.maximal_independent_set.html#networkx.algorithms.mis.maximal_independent_set">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">maximal_independent_set</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a random maximal independent set guaranteed to contain</span> +<span class="w"> </span><span class="sd">"""Returns a random maximal independent set guaranteed to contain</span> <span class="sd"> a given set of nodes.</span> <span class="sd"> An independent set is a set of nodes such that the subgraph</span> @@ -588,7 +588,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/moral.html b/_modules/networkx/algorithms/moral.html index ca6a6ceb..ff45b514 100644 --- a/_modules/networkx/algorithms/moral.html +++ b/_modules/networkx/algorithms/moral.html @@ -472,7 +472,7 @@ <div class="viewcode-block" id="moral_graph"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.moral.moral_graph.html#networkx.algorithms.moral.moral_graph">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">moral_graph</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Return the Moral Graph</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Return the Moral Graph</span> <span class="sd"> Returns the moralized graph of a given directed graph.</span> @@ -569,7 +569,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/node_classification.html b/_modules/networkx/algorithms/node_classification.html index 5c270d5a..43d7b891 100644 --- a/_modules/networkx/algorithms/node_classification.html +++ b/_modules/networkx/algorithms/node_classification.html @@ -492,7 +492,7 @@ <div class="viewcode-block" id="harmonic_function"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.node_classification.harmonic_function.html#networkx.algorithms.node_classification.harmonic_function">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">harmonic_function</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">30</span><span class="p">,</span> <span class="n">label_name</span><span class="o">=</span><span class="s2">"label"</span><span class="p">):</span> - <span class="sd">"""Node classification by Harmonic function</span> +<span class="w"> </span><span class="sd">"""Node classification by Harmonic function</span> <span class="sd"> Function for computing Harmonic function algorithm by Zhu et al.</span> @@ -569,7 +569,7 @@ <div class="viewcode-block" id="local_and_global_consistency"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.node_classification.local_and_global_consistency.html#networkx.algorithms.node_classification.local_and_global_consistency">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">local_and_global_consistency</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.99</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">30</span><span class="p">,</span> <span class="n">label_name</span><span class="o">=</span><span class="s2">"label"</span><span class="p">):</span> - <span class="sd">"""Node classification by Local and Global Consistency</span> +<span class="w"> </span><span class="sd">"""Node classification by Local and Global Consistency</span> <span class="sd"> Function for computing Local and global consistency algorithm by Zhou et al.</span> @@ -646,7 +646,7 @@ <span class="k">def</span> <span class="nf">_get_label_info</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">label_name</span><span class="p">):</span> - <span class="sd">"""Get and return information of labels from the input graph</span> +<span class="w"> </span><span class="sd">"""Get and return information of labels from the input graph</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -730,7 +730,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/non_randomness.html b/_modules/networkx/algorithms/non_randomness.html index 45abfb74..4e97da33 100644 --- a/_modules/networkx/algorithms/non_randomness.html +++ b/_modules/networkx/algorithms/non_randomness.html @@ -475,7 +475,7 @@ <div class="viewcode-block" id="non_randomness"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.non_randomness.non_randomness.html#networkx.algorithms.non_randomness.non_randomness">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">non_randomness</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Compute the non-randomness of graph G.</span> +<span class="w"> </span><span class="sd">"""Compute the non-randomness of graph G.</span> <span class="sd"> The first returned value nr is the sum of non-randomness values of all</span> <span class="sd"> edges within the graph (where the non-randomness of an edge tends to be</span> @@ -607,7 +607,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/operators/all.html b/_modules/networkx/algorithms/operators/all.html index 2f311782..f3a6855a 100644 --- a/_modules/networkx/algorithms/operators/all.html +++ b/_modules/networkx/algorithms/operators/all.html @@ -471,7 +471,7 @@ <div class="viewcode-block" id="union_all"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.all.union_all.html#networkx.algorithms.operators.all.union_all">[docs]</a><span class="k">def</span> <span class="nf">union_all</span><span class="p">(</span><span class="n">graphs</span><span class="p">,</span> <span class="n">rename</span><span class="o">=</span><span class="p">()):</span> - <span class="sd">"""Returns the union of all graphs.</span> +<span class="w"> </span><span class="sd">"""Returns the union of all graphs.</span> <span class="sd"> The graphs must be disjoint, otherwise an exception is raised.</span> @@ -554,7 +554,7 @@ <div class="viewcode-block" id="disjoint_union_all"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.all.disjoint_union_all.html#networkx.algorithms.operators.all.disjoint_union_all">[docs]</a><span class="k">def</span> <span class="nf">disjoint_union_all</span><span class="p">(</span><span class="n">graphs</span><span class="p">):</span> - <span class="sd">"""Returns the disjoint union of all graphs.</span> +<span class="w"> </span><span class="sd">"""Returns the disjoint union of all graphs.</span> <span class="sd"> This operation forces distinct integer node labels starting with 0</span> <span class="sd"> for the first graph in the list and numbering consecutively.</span> @@ -594,7 +594,7 @@ <div class="viewcode-block" id="compose_all"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.all.compose_all.html#networkx.algorithms.operators.all.compose_all">[docs]</a><span class="k">def</span> <span class="nf">compose_all</span><span class="p">(</span><span class="n">graphs</span><span class="p">):</span> - <span class="sd">"""Returns the composition of all graphs.</span> +<span class="w"> </span><span class="sd">"""Returns the composition of all graphs.</span> <span class="sd"> Composition is the simple union of the node sets and edge sets.</span> <span class="sd"> The node sets of the supplied graphs need not be disjoint.</span> @@ -645,7 +645,7 @@ <div class="viewcode-block" id="intersection_all"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.all.intersection_all.html#networkx.algorithms.operators.all.intersection_all">[docs]</a><span class="k">def</span> <span class="nf">intersection_all</span><span class="p">(</span><span class="n">graphs</span><span class="p">):</span> - <span class="sd">"""Returns a new graph that contains only the nodes and the edges that exist in</span> +<span class="w"> </span><span class="sd">"""Returns a new graph that contains only the nodes and the edges that exist in</span> <span class="sd"> all graphs.</span> <span class="sd"> Parameters</span> @@ -743,7 +743,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/operators/binary.html b/_modules/networkx/algorithms/operators/binary.html index 1bb3cd6e..d766ce23 100644 --- a/_modules/networkx/algorithms/operators/binary.html +++ b/_modules/networkx/algorithms/operators/binary.html @@ -478,7 +478,7 @@ <div class="viewcode-block" id="union"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.binary.union.html#networkx.algorithms.operators.binary.union">[docs]</a><span class="k">def</span> <span class="nf">union</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">H</span><span class="p">,</span> <span class="n">rename</span><span class="o">=</span><span class="p">()):</span> - <span class="sd">"""Combine graphs G and H. The names of nodes must be unique.</span> +<span class="w"> </span><span class="sd">"""Combine graphs G and H. The names of nodes must be unique.</span> <span class="sd"> A name collision between the graphs will raise an exception.</span> @@ -533,7 +533,7 @@ <div class="viewcode-block" id="disjoint_union"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.binary.disjoint_union.html#networkx.algorithms.operators.binary.disjoint_union">[docs]</a><span class="k">def</span> <span class="nf">disjoint_union</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">H</span><span class="p">):</span> - <span class="sd">"""Combine graphs G and H. The nodes are assumed to be unique (disjoint).</span> +<span class="w"> </span><span class="sd">"""Combine graphs G and H. The nodes are assumed to be unique (disjoint).</span> <span class="sd"> This algorithm automatically relabels nodes to avoid name collisions.</span> @@ -586,7 +586,7 @@ <div class="viewcode-block" id="intersection"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.binary.intersection.html#networkx.algorithms.operators.binary.intersection">[docs]</a><span class="k">def</span> <span class="nf">intersection</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">H</span><span class="p">):</span> - <span class="sd">"""Returns a new graph that contains only the nodes and the edges that exist in</span> +<span class="w"> </span><span class="sd">"""Returns a new graph that contains only the nodes and the edges that exist in</span> <span class="sd"> both G and H.</span> <span class="sd"> Parameters</span> @@ -630,7 +630,7 @@ <div class="viewcode-block" id="difference"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.binary.difference.html#networkx.algorithms.operators.binary.difference">[docs]</a><span class="k">def</span> <span class="nf">difference</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">H</span><span class="p">):</span> - <span class="sd">"""Returns a new graph that contains the edges that exist in G but not in H.</span> +<span class="w"> </span><span class="sd">"""Returns a new graph that contains the edges that exist in G but not in H.</span> <span class="sd"> The node sets of H and G must be the same.</span> @@ -684,7 +684,7 @@ <div class="viewcode-block" id="symmetric_difference"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.binary.symmetric_difference.html#networkx.algorithms.operators.binary.symmetric_difference">[docs]</a><span class="k">def</span> <span class="nf">symmetric_difference</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">H</span><span class="p">):</span> - <span class="sd">"""Returns new graph with edges that exist in either G or H but not both.</span> +<span class="w"> </span><span class="sd">"""Returns new graph with edges that exist in either G or H but not both.</span> <span class="sd"> The node sets of H and G must be the same.</span> @@ -746,7 +746,7 @@ <div class="viewcode-block" id="compose"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.binary.compose.html#networkx.algorithms.operators.binary.compose">[docs]</a><span class="k">def</span> <span class="nf">compose</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">H</span><span class="p">):</span> - <span class="sd">"""Compose graph G with H by combining nodes and edges into a single graph.</span> +<span class="w"> </span><span class="sd">"""Compose graph G with H by combining nodes and edges into a single graph.</span> <span class="sd"> The node sets and edges sets do not need to be disjoint.</span> @@ -822,7 +822,7 @@ <div class="viewcode-block" id="full_join"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.binary.full_join.html#networkx.algorithms.operators.binary.full_join">[docs]</a><span class="k">def</span> <span class="nf">full_join</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">H</span><span class="p">,</span> <span class="n">rename</span><span class="o">=</span><span class="p">(</span><span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">)):</span> - <span class="sd">"""Returns the full join of graphs G and H.</span> +<span class="w"> </span><span class="sd">"""Returns the full join of graphs G and H.</span> <span class="sd"> Full join is the union of G and H in which all edges between</span> <span class="sd"> G and H are added.</span> @@ -948,7 +948,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/operators/product.html b/_modules/networkx/algorithms/operators/product.html index c97eb533..310beb8e 100644 --- a/_modules/networkx/algorithms/operators/product.html +++ b/_modules/networkx/algorithms/operators/product.html @@ -586,7 +586,7 @@ <div class="viewcode-block" id="tensor_product"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.product.tensor_product.html#networkx.algorithms.operators.product.tensor_product">[docs]</a><span class="k">def</span> <span class="nf">tensor_product</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">H</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the tensor product of G and H.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the tensor product of G and H.</span> <span class="sd"> The tensor product $P$ of the graphs $G$ and $H$ has a node set that</span> <span class="sd"> is the tensor product of the node sets, $V(P)=V(G) \times V(H)$.</span> @@ -641,7 +641,7 @@ <div class="viewcode-block" id="cartesian_product"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.product.cartesian_product.html#networkx.algorithms.operators.product.cartesian_product">[docs]</a><span class="k">def</span> <span class="nf">cartesian_product</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">H</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the Cartesian product of G and H.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the Cartesian product of G and H.</span> <span class="sd"> The Cartesian product $P$ of the graphs $G$ and $H$ has a node set that</span> <span class="sd"> is the Cartesian product of the node sets, $V(P)=V(G) \times V(H)$.</span> @@ -692,7 +692,7 @@ <div class="viewcode-block" id="lexicographic_product"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.product.lexicographic_product.html#networkx.algorithms.operators.product.lexicographic_product">[docs]</a><span class="k">def</span> <span class="nf">lexicographic_product</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">H</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the lexicographic product of G and H.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the lexicographic product of G and H.</span> <span class="sd"> The lexicographical product $P$ of the graphs $G$ and $H$ has a node set</span> <span class="sd"> that is the Cartesian product of the node sets, $V(P)=V(G) \times V(H)$.</span> @@ -744,7 +744,7 @@ <div class="viewcode-block" id="strong_product"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.product.strong_product.html#networkx.algorithms.operators.product.strong_product">[docs]</a><span class="k">def</span> <span class="nf">strong_product</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">H</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the strong product of G and H.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the strong product of G and H.</span> <span class="sd"> The strong product $P$ of the graphs $G$ and $H$ has a node set that</span> <span class="sd"> is the Cartesian product of the node sets, $V(P)=V(G) \times V(H)$.</span> @@ -801,7 +801,7 @@ <div class="viewcode-block" id="power"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.product.power.html#networkx.algorithms.operators.product.power">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">power</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> - <span class="sd">"""Returns the specified power of a graph.</span> +<span class="w"> </span><span class="sd">"""Returns the specified power of a graph.</span> <span class="sd"> The $k$th power of a simple graph $G$, denoted $G^k$, is a</span> <span class="sd"> graph on the same set of nodes in which two distinct nodes $u$ and</span> @@ -889,7 +889,7 @@ <div class="viewcode-block" id="rooted_product"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.product.rooted_product.html#networkx.algorithms.operators.product.rooted_product">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">rooted_product</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">H</span><span class="p">,</span> <span class="n">root</span><span class="p">):</span> - <span class="sd">"""Return the rooted product of graphs G and H rooted at root in H.</span> +<span class="w"> </span><span class="sd">"""Return the rooted product of graphs G and H rooted at root in H.</span> <span class="sd"> A new graph is constructed representing the rooted product of</span> <span class="sd"> the inputted graphs, G and H, with a root in H.</span> @@ -928,7 +928,7 @@ <div class="viewcode-block" id="corona_product"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.product.corona_product.html#networkx.algorithms.operators.product.corona_product">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">corona_product</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">H</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the Corona product of G and H.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the Corona product of G and H.</span> <span class="sd"> The corona product of $G$ and $H$ is the graph $C = G \circ H$ obtained by</span> <span class="sd"> taking one copy of $G$, called the center graph, $|V(G)|$ copies of $H$,</span> @@ -1039,7 +1039,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/operators/unary.html b/_modules/networkx/algorithms/operators/unary.html index 59814f96..15408756 100644 --- a/_modules/networkx/algorithms/operators/unary.html +++ b/_modules/networkx/algorithms/operators/unary.html @@ -468,7 +468,7 @@ <div class="viewcode-block" id="complement"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.unary.complement.html#networkx.algorithms.operators.unary.complement">[docs]</a><span class="k">def</span> <span class="nf">complement</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the graph complement of G.</span> +<span class="w"> </span><span class="sd">"""Returns the graph complement of G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -503,7 +503,7 @@ <div class="viewcode-block" id="reverse"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.operators.unary.reverse.html#networkx.algorithms.operators.unary.reverse">[docs]</a><span class="k">def</span> <span class="nf">reverse</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Returns the reverse directed graph of G.</span> +<span class="w"> </span><span class="sd">"""Returns the reverse directed graph of G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -586,7 +586,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/planar_drawing.html b/_modules/networkx/algorithms/planar_drawing.html index 09cdd9a4..fb6c5154 100644 --- a/_modules/networkx/algorithms/planar_drawing.html +++ b/_modules/networkx/algorithms/planar_drawing.html @@ -469,7 +469,7 @@ <div class="viewcode-block" id="combinatorial_embedding_to_pos"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.planar_drawing.combinatorial_embedding_to_pos.html#networkx.algorithms.planar_drawing.combinatorial_embedding_to_pos">[docs]</a><span class="k">def</span> <span class="nf">combinatorial_embedding_to_pos</span><span class="p">(</span><span class="n">embedding</span><span class="p">,</span> <span class="n">fully_triangulate</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Assigns every node a (x, y) position based on the given embedding</span> +<span class="w"> </span><span class="sd">"""Assigns every node a (x, y) position based on the given embedding</span> <span class="sd"> The algorithm iteratively inserts nodes of the input graph in a certain</span> <span class="sd"> order and rearranges previously inserted nodes so that the planar drawing</span> @@ -589,7 +589,7 @@ <span class="k">def</span> <span class="nf">set_position</span><span class="p">(</span><span class="n">parent</span><span class="p">,</span> <span class="n">tree</span><span class="p">,</span> <span class="n">remaining_nodes</span><span class="p">,</span> <span class="n">delta_x</span><span class="p">,</span> <span class="n">y_coordinate</span><span class="p">,</span> <span class="n">pos</span><span class="p">):</span> - <span class="sd">"""Helper method to calculate the absolute position of nodes."""</span> +<span class="w"> </span><span class="sd">"""Helper method to calculate the absolute position of nodes."""</span> <span class="n">child</span> <span class="o">=</span> <span class="n">tree</span><span class="p">[</span><span class="n">parent</span><span class="p">]</span> <span class="n">parent_node_x</span> <span class="o">=</span> <span class="n">pos</span><span class="p">[</span><span class="n">parent</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="k">if</span> <span class="n">child</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> @@ -601,7 +601,7 @@ <span class="k">def</span> <span class="nf">get_canonical_ordering</span><span class="p">(</span><span class="n">embedding</span><span class="p">,</span> <span class="n">outer_face</span><span class="p">):</span> - <span class="sd">"""Returns a canonical ordering of the nodes</span> +<span class="w"> </span><span class="sd">"""Returns a canonical ordering of the nodes</span> <span class="sd"> The canonical ordering of nodes (v1, ..., vn) must fulfill the following</span> <span class="sd"> conditions:</span> @@ -768,7 +768,7 @@ <span class="k">def</span> <span class="nf">triangulate_face</span><span class="p">(</span><span class="n">embedding</span><span class="p">,</span> <span class="n">v1</span><span class="p">,</span> <span class="n">v2</span><span class="p">):</span> - <span class="sd">"""Triangulates the face given by half edge (v, w)</span> +<span class="w"> </span><span class="sd">"""Triangulates the face given by half edge (v, w)</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -797,7 +797,7 @@ <span class="k">def</span> <span class="nf">triangulate_embedding</span><span class="p">(</span><span class="n">embedding</span><span class="p">,</span> <span class="n">fully_triangulate</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Triangulates the embedding.</span> +<span class="w"> </span><span class="sd">"""Triangulates the embedding.</span> <span class="sd"> Traverses faces of the embedding and adds edges to a copy of the</span> <span class="sd"> embedding to triangulate it.</span> @@ -866,7 +866,7 @@ <span class="k">def</span> <span class="nf">make_bi_connected</span><span class="p">(</span><span class="n">embedding</span><span class="p">,</span> <span class="n">starting_node</span><span class="p">,</span> <span class="n">outgoing_node</span><span class="p">,</span> <span class="n">edges_counted</span><span class="p">):</span> - <span class="sd">"""Triangulate a face and make it 2-connected</span> +<span class="w"> </span><span class="sd">"""Triangulate a face and make it 2-connected</span> <span class="sd"> This method also adds all edges on the face to `edges_counted`.</span> @@ -976,7 +976,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/planarity.html b/_modules/networkx/algorithms/planarity.html index 13145296..b8853a46 100644 --- a/_modules/networkx/algorithms/planarity.html +++ b/_modules/networkx/algorithms/planarity.html @@ -469,7 +469,7 @@ <div class="viewcode-block" id="is_planar"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.planarity.is_planar.html#networkx.algorithms.planarity.is_planar">[docs]</a><span class="k">def</span> <span class="nf">is_planar</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns True if and only if `G` is planar.</span> +<span class="w"> </span><span class="sd">"""Returns True if and only if `G` is planar.</span> <span class="sd"> A graph is *planar* iff it can be drawn in a plane without</span> <span class="sd"> any edge intersections.</span> @@ -501,7 +501,7 @@ <div class="viewcode-block" id="check_planarity"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.planarity.check_planarity.html#networkx.algorithms.planarity.check_planarity">[docs]</a><span class="k">def</span> <span class="nf">check_planarity</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">counterexample</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Check if a graph is planar and return a counterexample or an embedding.</span> +<span class="w"> </span><span class="sd">"""Check if a graph is planar and return a counterexample or an embedding.</span> <span class="sd"> A graph is planar iff it can be drawn in a plane without</span> <span class="sd"> any edge intersections.</span> @@ -576,7 +576,7 @@ <span class="k">def</span> <span class="nf">check_planarity_recursive</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">counterexample</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Recursive version of :meth:`check_planarity`."""</span> +<span class="w"> </span><span class="sd">"""Recursive version of :meth:`check_planarity`."""</span> <span class="n">planarity_state</span> <span class="o">=</span> <span class="n">LRPlanarity</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> <span class="n">embedding</span> <span class="o">=</span> <span class="n">planarity_state</span><span class="o">.</span><span class="n">lr_planarity_recursive</span><span class="p">()</span> <span class="k">if</span> <span class="n">embedding</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> @@ -591,7 +591,7 @@ <span class="k">def</span> <span class="nf">get_counterexample</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Obtains a Kuratowski subgraph.</span> +<span class="w"> </span><span class="sd">"""Obtains a Kuratowski subgraph.</span> <span class="sd"> Raises nx.NetworkXException if G is planar.</span> @@ -629,7 +629,7 @@ <span class="k">def</span> <span class="nf">get_counterexample_recursive</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Recursive version of :meth:`get_counterexample`."""</span> +<span class="w"> </span><span class="sd">"""Recursive version of :meth:`get_counterexample`."""</span> <span class="c1"># copy graph</span> <span class="n">G</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">Graph</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> @@ -651,7 +651,7 @@ <span class="k">class</span> <span class="nc">Interval</span><span class="p">:</span> - <span class="sd">"""Represents a set of return edges.</span> +<span class="w"> </span><span class="sd">"""Represents a set of return edges.</span> <span class="sd"> All return edges in an interval induce a same constraint on the contained</span> <span class="sd"> edges, which means that all edges must either have a left orientation or</span> @@ -663,15 +663,15 @@ <span class="bp">self</span><span class="o">.</span><span class="n">high</span> <span class="o">=</span> <span class="n">high</span> <span class="k">def</span> <span class="nf">empty</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Check if the interval is empty"""</span> +<span class="w"> </span><span class="sd">"""Check if the interval is empty"""</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">low</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">high</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">def</span> <span class="nf">copy</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns a copy of this interval"""</span> +<span class="w"> </span><span class="sd">"""Returns a copy of this interval"""</span> <span class="k">return</span> <span class="n">Interval</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">low</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">high</span><span class="p">)</span> <span class="k">def</span> <span class="nf">conflicting</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">planarity_state</span><span class="p">):</span> - <span class="sd">"""Returns True if interval I conflicts with edge b"""</span> +<span class="w"> </span><span class="sd">"""Returns True if interval I conflicts with edge b"""</span> <span class="k">return</span> <span class="p">(</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">empty</span><span class="p">()</span> <span class="ow">and</span> <span class="n">planarity_state</span><span class="o">.</span><span class="n">lowpt</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">high</span><span class="p">]</span> <span class="o">></span> <span class="n">planarity_state</span><span class="o">.</span><span class="n">lowpt</span><span class="p">[</span><span class="n">b</span><span class="p">]</span> @@ -679,7 +679,7 @@ <span class="k">class</span> <span class="nc">ConflictPair</span><span class="p">:</span> - <span class="sd">"""Represents a different constraint between two intervals.</span> +<span class="w"> </span><span class="sd">"""Represents a different constraint between two intervals.</span> <span class="sd"> The edges in the left interval must have a different orientation than</span> <span class="sd"> the one in the right interval.</span> @@ -690,13 +690,13 @@ <span class="bp">self</span><span class="o">.</span><span class="n">right</span> <span class="o">=</span> <span class="n">right</span> <span class="k">def</span> <span class="nf">swap</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Swap left and right intervals"""</span> +<span class="w"> </span><span class="sd">"""Swap left and right intervals"""</span> <span class="n">temp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">left</span> <span class="bp">self</span><span class="o">.</span><span class="n">left</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">right</span> <span class="bp">self</span><span class="o">.</span><span class="n">right</span> <span class="o">=</span> <span class="n">temp</span> <span class="k">def</span> <span class="nf">lowest</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">planarity_state</span><span class="p">):</span> - <span class="sd">"""Returns the lowest lowpoint of a conflict pair"""</span> +<span class="w"> </span><span class="sd">"""Returns the lowest lowpoint of a conflict pair"""</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">left</span><span class="o">.</span><span class="n">empty</span><span class="p">():</span> <span class="k">return</span> <span class="n">planarity_state</span><span class="o">.</span><span class="n">lowpt</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">right</span><span class="o">.</span><span class="n">low</span><span class="p">]</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">right</span><span class="o">.</span><span class="n">empty</span><span class="p">():</span> @@ -707,14 +707,14 @@ <span class="k">def</span> <span class="nf">top_of_stack</span><span class="p">(</span><span class="n">l</span><span class="p">):</span> - <span class="sd">"""Returns the element on top of the stack."""</span> +<span class="w"> </span><span class="sd">"""Returns the element on top of the stack."""</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">l</span><span class="p">:</span> <span class="k">return</span> <span class="kc">None</span> <span class="k">return</span> <span class="n">l</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="k">class</span> <span class="nc">LRPlanarity</span><span class="p">:</span> - <span class="sd">"""A class to maintain the state during planarity check."""</span> +<span class="w"> </span><span class="sd">"""A class to maintain the state during planarity check."""</span> <span class="vm">__slots__</span> <span class="o">=</span> <span class="p">[</span> <span class="s2">"G"</span><span class="p">,</span> @@ -778,7 +778,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">embedding</span> <span class="o">=</span> <span class="n">PlanarEmbedding</span><span class="p">()</span> <span class="k">def</span> <span class="nf">lr_planarity</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Execute the LR planarity test.</span> +<span class="w"> </span><span class="sd">"""Execute the LR planarity test.</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> @@ -857,7 +857,7 @@ <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">embedding</span> <span class="k">def</span> <span class="nf">lr_planarity_recursive</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Recursive version of :meth:`lr_planarity`."""</span> +<span class="w"> </span><span class="sd">"""Recursive version of :meth:`lr_planarity`."""</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">G</span><span class="o">.</span><span class="n">order</span><span class="p">()</span> <span class="o">></span> <span class="mi">2</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">G</span><span class="o">.</span><span class="n">size</span><span class="p">()</span> <span class="o">></span> <span class="mi">3</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">G</span><span class="o">.</span><span class="n">order</span><span class="p">()</span> <span class="o">-</span> <span class="mi">6</span><span class="p">:</span> <span class="c1"># graph is not planar</span> <span class="k">return</span> <span class="kc">None</span> @@ -904,7 +904,7 @@ <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">embedding</span> <span class="k">def</span> <span class="nf">dfs_orientation</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Orient the graph by DFS, compute lowpoints and nesting order."""</span> +<span class="w"> </span><span class="sd">"""Orient the graph by DFS, compute lowpoints and nesting order."""</span> <span class="c1"># the recursion stack</span> <span class="n">dfs_stack</span> <span class="o">=</span> <span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="c1"># index of next edge to handle in adjacency list of each node</span> @@ -957,7 +957,7 @@ <span class="n">ind</span><span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="o">+=</span> <span class="mi">1</span> <span class="k">def</span> <span class="nf">dfs_orientation_recursive</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Recursive version of :meth:`dfs_orientation`."""</span> +<span class="w"> </span><span class="sd">"""Recursive version of :meth:`dfs_orientation`."""</span> <span class="n">e</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">parent_edge</span><span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="k">for</span> <span class="n">w</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">G</span><span class="p">[</span><span class="n">v</span><span class="p">]:</span> <span class="k">if</span> <span class="p">(</span><span class="n">v</span><span class="p">,</span> <span class="n">w</span><span class="p">)</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">DG</span><span class="o">.</span><span class="n">edges</span> <span class="ow">or</span> <span class="p">(</span><span class="n">w</span><span class="p">,</span> <span class="n">v</span><span class="p">)</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">DG</span><span class="o">.</span><span class="n">edges</span><span class="p">:</span> @@ -990,7 +990,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">lowpt2</span><span class="p">[</span><span class="n">e</span><span class="p">]</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">lowpt2</span><span class="p">[</span><span class="n">e</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">lowpt2</span><span class="p">[</span><span class="n">vw</span><span class="p">])</span> <span class="k">def</span> <span class="nf">dfs_testing</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Test for LR partition."""</span> +<span class="w"> </span><span class="sd">"""Test for LR partition."""</span> <span class="c1"># the recursion stack</span> <span class="n">dfs_stack</span> <span class="o">=</span> <span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="c1"># index of next edge to handle in adjacency list of each node</span> @@ -1039,7 +1039,7 @@ <span class="k">return</span> <span class="kc">True</span> <span class="k">def</span> <span class="nf">dfs_testing_recursive</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Recursive version of :meth:`dfs_testing`."""</span> +<span class="w"> </span><span class="sd">"""Recursive version of :meth:`dfs_testing`."""</span> <span class="n">e</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">parent_edge</span><span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="k">for</span> <span class="n">w</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">ordered_adjs</span><span class="p">[</span><span class="n">v</span><span class="p">]:</span> <span class="n">ei</span> <span class="o">=</span> <span class="p">(</span><span class="n">v</span><span class="p">,</span> <span class="n">w</span><span class="p">)</span> @@ -1149,7 +1149,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">ref</span><span class="p">[</span><span class="n">e</span><span class="p">]</span> <span class="o">=</span> <span class="n">hr</span> <span class="k">def</span> <span class="nf">dfs_embedding</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Completes the embedding."""</span> +<span class="w"> </span><span class="sd">"""Completes the embedding."""</span> <span class="c1"># the recursion stack</span> <span class="n">dfs_stack</span> <span class="o">=</span> <span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="c1"># index of next edge to handle in adjacency list of each node</span> @@ -1178,7 +1178,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">left_ref</span><span class="p">[</span><span class="n">w</span><span class="p">]</span> <span class="o">=</span> <span class="n">v</span> <span class="k">def</span> <span class="nf">dfs_embedding_recursive</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Recursive version of :meth:`dfs_embedding`."""</span> +<span class="w"> </span><span class="sd">"""Recursive version of :meth:`dfs_embedding`."""</span> <span class="k">for</span> <span class="n">w</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">ordered_adjs</span><span class="p">[</span><span class="n">v</span><span class="p">]:</span> <span class="n">ei</span> <span class="o">=</span> <span class="p">(</span><span class="n">v</span><span class="p">,</span> <span class="n">w</span><span class="p">)</span> <span class="k">if</span> <span class="n">ei</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">parent_edge</span><span class="p">[</span><span class="n">w</span><span class="p">]:</span> <span class="c1"># tree edge</span> @@ -1196,7 +1196,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">left_ref</span><span class="p">[</span><span class="n">w</span><span class="p">]</span> <span class="o">=</span> <span class="n">v</span> <span class="k">def</span> <span class="nf">sign</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">e</span><span class="p">):</span> - <span class="sd">"""Resolve the relative side of an edge to the absolute side."""</span> +<span class="w"> </span><span class="sd">"""Resolve the relative side of an edge to the absolute side."""</span> <span class="c1"># the recursion stack</span> <span class="n">dfs_stack</span> <span class="o">=</span> <span class="p">[</span><span class="n">e</span><span class="p">]</span> <span class="c1"># dict to remember reference edges</span> @@ -1216,7 +1216,7 @@ <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">side</span><span class="p">[</span><span class="n">e</span><span class="p">]</span> <span class="k">def</span> <span class="nf">sign_recursive</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">e</span><span class="p">):</span> - <span class="sd">"""Recursive version of :meth:`sign`."""</span> +<span class="w"> </span><span class="sd">"""Recursive version of :meth:`sign`."""</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">ref</span><span class="p">[</span><span class="n">e</span><span class="p">]</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">side</span><span class="p">[</span><span class="n">e</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">side</span><span class="p">[</span><span class="n">e</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">sign_recursive</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">ref</span><span class="p">[</span><span class="n">e</span><span class="p">])</span> <span class="bp">self</span><span class="o">.</span><span class="n">ref</span><span class="p">[</span><span class="n">e</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span> @@ -1224,7 +1224,7 @@ <div class="viewcode-block" id="PlanarEmbedding"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.planarity.PlanarEmbedding.html#networkx.algorithms.planarity.PlanarEmbedding">[docs]</a><span class="k">class</span> <span class="nc">PlanarEmbedding</span><span class="p">(</span><span class="n">nx</span><span class="o">.</span><span class="n">DiGraph</span><span class="p">):</span> - <span class="sd">"""Represents a planar graph with its planar embedding.</span> +<span class="w"> </span><span class="sd">"""Represents a planar graph with its planar embedding.</span> <span class="sd"> The planar embedding is given by a `combinatorial embedding</span> <span class="sd"> <https://en.wikipedia.org/wiki/Graph_embedding#Combinatorial_embedding>`_.</span> @@ -1317,7 +1317,7 @@ <span class="sd"> """</span> <div class="viewcode-block" id="PlanarEmbedding.get_data"><a class="viewcode-back" href="../../../reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.get_data.html#networkx.algorithms.planarity.PlanarEmbedding.get_data">[docs]</a> <span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Converts the adjacency structure into a better readable structure.</span> +<span class="w"> </span><span class="sd">"""Converts the adjacency structure into a better readable structure.</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> @@ -1336,7 +1336,7 @@ <span class="k">return</span> <span class="n">embedding</span></div> <div class="viewcode-block" id="PlanarEmbedding.set_data"><a class="viewcode-back" href="../../../reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.set_data.html#networkx.algorithms.planarity.PlanarEmbedding.set_data">[docs]</a> <span class="k">def</span> <span class="nf">set_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span> - <span class="sd">"""Inserts edges according to given sorted neighbor list.</span> +<span class="w"> </span><span class="sd">"""Inserts edges according to given sorted neighbor list.</span> <span class="sd"> The input format is the same as the output format of get_data().</span> @@ -1356,7 +1356,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">add_half_edge_first</span><span class="p">(</span><span class="n">v</span><span class="p">,</span> <span class="n">w</span><span class="p">)</span></div> <div class="viewcode-block" id="PlanarEmbedding.neighbors_cw_order"><a class="viewcode-back" href="../../../reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.neighbors_cw_order.html#networkx.algorithms.planarity.PlanarEmbedding.neighbors_cw_order">[docs]</a> <span class="k">def</span> <span class="nf">neighbors_cw_order</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Generator for the neighbors of v in clockwise order.</span> +<span class="w"> </span><span class="sd">"""Generator for the neighbors of v in clockwise order.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1378,7 +1378,7 @@ <span class="n">current_node</span> <span class="o">=</span> <span class="bp">self</span><span class="p">[</span><span class="n">v</span><span class="p">][</span><span class="n">current_node</span><span class="p">][</span><span class="s2">"cw"</span><span class="p">]</span></div> <div class="viewcode-block" id="PlanarEmbedding.check_structure"><a class="viewcode-back" href="../../../reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.check_structure.html#networkx.algorithms.planarity.PlanarEmbedding.check_structure">[docs]</a> <span class="k">def</span> <span class="nf">check_structure</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Runs without exceptions if this object is valid.</span> +<span class="w"> </span><span class="sd">"""Runs without exceptions if this object is valid.</span> <span class="sd"> Checks that the following properties are fulfilled:</span> @@ -1437,7 +1437,7 @@ <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXException</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span></div> <div class="viewcode-block" id="PlanarEmbedding.add_half_edge_ccw"><a class="viewcode-back" href="../../../reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_ccw.html#networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_ccw">[docs]</a> <span class="k">def</span> <span class="nf">add_half_edge_ccw</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">start_node</span><span class="p">,</span> <span class="n">end_node</span><span class="p">,</span> <span class="n">reference_neighbor</span><span class="p">):</span> - <span class="sd">"""Adds a half-edge from start_node to end_node.</span> +<span class="w"> </span><span class="sd">"""Adds a half-edge from start_node to end_node.</span> <span class="sd"> The half-edge is added counter clockwise next to the existing half-edge</span> <span class="sd"> (start_node, reference_neighbor).</span> @@ -1478,7 +1478,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">nodes</span><span class="p">[</span><span class="n">start_node</span><span class="p">][</span><span class="s2">"first_nbr"</span><span class="p">]</span> <span class="o">=</span> <span class="n">end_node</span></div> <div class="viewcode-block" id="PlanarEmbedding.add_half_edge_cw"><a class="viewcode-back" href="../../../reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_cw.html#networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_cw">[docs]</a> <span class="k">def</span> <span class="nf">add_half_edge_cw</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">start_node</span><span class="p">,</span> <span class="n">end_node</span><span class="p">,</span> <span class="n">reference_neighbor</span><span class="p">):</span> - <span class="sd">"""Adds a half-edge from start_node to end_node.</span> +<span class="w"> </span><span class="sd">"""Adds a half-edge from start_node to end_node.</span> <span class="sd"> The half-edge is added clockwise next to the existing half-edge</span> <span class="sd"> (start_node, reference_neighbor).</span> @@ -1526,7 +1526,7 @@ <span class="bp">self</span><span class="p">[</span><span class="n">start_node</span><span class="p">][</span><span class="n">end_node</span><span class="p">][</span><span class="s2">"ccw"</span><span class="p">]</span> <span class="o">=</span> <span class="n">reference_neighbor</span></div> <div class="viewcode-block" id="PlanarEmbedding.connect_components"><a class="viewcode-back" href="../../../reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.connect_components.html#networkx.algorithms.planarity.PlanarEmbedding.connect_components">[docs]</a> <span class="k">def</span> <span class="nf">connect_components</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">w</span><span class="p">):</span> - <span class="sd">"""Adds half-edges for (v, w) and (w, v) at some position.</span> +<span class="w"> </span><span class="sd">"""Adds half-edges for (v, w) and (w, v) at some position.</span> <span class="sd"> This method should only be called if v and w are in different</span> <span class="sd"> components, or it might break the embedding.</span> @@ -1550,7 +1550,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">add_half_edge_first</span><span class="p">(</span><span class="n">w</span><span class="p">,</span> <span class="n">v</span><span class="p">)</span></div> <div class="viewcode-block" id="PlanarEmbedding.add_half_edge_first"><a class="viewcode-back" href="../../../reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_first.html#networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_first">[docs]</a> <span class="k">def</span> <span class="nf">add_half_edge_first</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">start_node</span><span class="p">,</span> <span class="n">end_node</span><span class="p">):</span> - <span class="sd">"""The added half-edge is inserted at the first position in the order.</span> +<span class="w"> </span><span class="sd">"""The added half-edge is inserted at the first position in the order.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1570,7 +1570,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">add_half_edge_ccw</span><span class="p">(</span><span class="n">start_node</span><span class="p">,</span> <span class="n">end_node</span><span class="p">,</span> <span class="n">reference</span><span class="p">)</span></div> <div class="viewcode-block" id="PlanarEmbedding.next_face_half_edge"><a class="viewcode-back" href="../../../reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.next_face_half_edge.html#networkx.algorithms.planarity.PlanarEmbedding.next_face_half_edge">[docs]</a> <span class="k">def</span> <span class="nf">next_face_half_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">w</span><span class="p">):</span> - <span class="sd">"""Returns the following half-edge left of a face.</span> +<span class="w"> </span><span class="sd">"""Returns the following half-edge left of a face.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1585,7 +1585,7 @@ <span class="k">return</span> <span class="n">w</span><span class="p">,</span> <span class="n">new_node</span></div> <div class="viewcode-block" id="PlanarEmbedding.traverse_face"><a class="viewcode-back" href="../../../reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.traverse_face.html#networkx.algorithms.planarity.PlanarEmbedding.traverse_face">[docs]</a> <span class="k">def</span> <span class="nf">traverse_face</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">w</span><span class="p">,</span> <span class="n">mark_half_edges</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns nodes on the face that belong to the half-edge (v, w).</span> +<span class="w"> </span><span class="sd">"""Returns nodes on the face that belong to the half-edge (v, w).</span> <span class="sd"> The face that is traversed lies to the right of the half-edge (in an</span> <span class="sd"> orientation where v is below w).</span> @@ -1628,7 +1628,7 @@ <span class="k">return</span> <span class="n">face_nodes</span></div> <div class="viewcode-block" id="PlanarEmbedding.is_directed"><a class="viewcode-back" href="../../../reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.is_directed.html#networkx.algorithms.planarity.PlanarEmbedding.is_directed">[docs]</a> <span class="k">def</span> <span class="nf">is_directed</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""A valid PlanarEmbedding is undirected.</span> +<span class="w"> </span><span class="sd">"""A valid PlanarEmbedding is undirected.</span> <span class="sd"> All reverse edges are contained, i.e. for every existing</span> <span class="sd"> half-edge (v, w) the half-edge in the opposite direction (w, v) is also</span> @@ -1686,7 +1686,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/polynomials.html b/_modules/networkx/algorithms/polynomials.html index f42dd64c..09211792 100644 --- a/_modules/networkx/algorithms/polynomials.html +++ b/_modules/networkx/algorithms/polynomials.html @@ -494,7 +494,7 @@ <div class="viewcode-block" id="tutte_polynomial"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.polynomials.tutte_polynomial.html#networkx.algorithms.polynomials.tutte_polynomial">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">tutte_polynomial</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the Tutte polynomial of `G`</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the Tutte polynomial of `G`</span> <span class="sd"> This function computes the Tutte polynomial via an iterative version of</span> <span class="sd"> the deletion-contraction algorithm.</span> @@ -643,7 +643,7 @@ <div class="viewcode-block" id="chromatic_polynomial"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.polynomials.chromatic_polynomial.html#networkx.algorithms.polynomials.chromatic_polynomial">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">chromatic_polynomial</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the chromatic polynomial of `G`</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the chromatic polynomial of `G`</span> <span class="sd"> This function computes the chromatic polynomial via an iterative version of</span> <span class="sd"> the deletion-contraction algorithm.</span> @@ -815,7 +815,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/reciprocity.html b/_modules/networkx/algorithms/reciprocity.html index caa04463..12e28869 100644 --- a/_modules/networkx/algorithms/reciprocity.html +++ b/_modules/networkx/algorithms/reciprocity.html @@ -473,7 +473,7 @@ <div class="viewcode-block" id="reciprocity"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.reciprocity.reciprocity.html#networkx.algorithms.reciprocity.reciprocity">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">,</span> <span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">reciprocity</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Compute the reciprocity in a directed graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Compute the reciprocity in a directed graph.</span> <span class="sd"> The reciprocity of a directed graph is defined as the ratio</span> <span class="sd"> of the number of edges pointing in both directions to the total</span> @@ -521,7 +521,7 @@ <span class="k">def</span> <span class="nf">_reciprocity_iter</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="p">):</span> - <span class="sd">"""Return an iterator of (node, reciprocity)."""</span> +<span class="w"> </span><span class="sd">"""Return an iterator of (node, reciprocity)."""</span> <span class="n">n</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">nbunch_iter</span><span class="p">(</span><span class="n">nodes</span><span class="p">)</span> <span class="k">for</span> <span class="n">node</span> <span class="ow">in</span> <span class="n">n</span><span class="p">:</span> <span class="n">pred</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">predecessors</span><span class="p">(</span><span class="n">node</span><span class="p">))</span> @@ -541,7 +541,7 @@ <div class="viewcode-block" id="overall_reciprocity"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.reciprocity.overall_reciprocity.html#networkx.algorithms.reciprocity.overall_reciprocity">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">,</span> <span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">overall_reciprocity</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Compute the reciprocity for the whole graph.</span> +<span class="w"> </span><span class="sd">"""Compute the reciprocity for the whole graph.</span> <span class="sd"> See the doc of reciprocity for the definition.</span> @@ -609,7 +609,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/regular.html b/_modules/networkx/algorithms/regular.html index 63e54ebb..20f36e84 100644 --- a/_modules/networkx/algorithms/regular.html +++ b/_modules/networkx/algorithms/regular.html @@ -470,7 +470,7 @@ <div class="viewcode-block" id="is_regular"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.regular.is_regular.html#networkx.algorithms.regular.is_regular">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">is_regular</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Determines whether the graph ``G`` is a regular graph.</span> +<span class="w"> </span><span class="sd">"""Determines whether the graph ``G`` is a regular graph.</span> <span class="sd"> A regular graph is a graph where each vertex has the same degree. A</span> <span class="sd"> regular digraph is a graph where the indegree and outdegree of each</span> @@ -507,7 +507,7 @@ <div class="viewcode-block" id="is_k_regular"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.regular.is_k_regular.html#networkx.algorithms.regular.is_k_regular">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_k_regular</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> - <span class="sd">"""Determines whether the graph ``G`` is a k-regular graph.</span> +<span class="w"> </span><span class="sd">"""Determines whether the graph ``G`` is a k-regular graph.</span> <span class="sd"> A k-regular graph is a graph where each vertex has degree k.</span> @@ -533,7 +533,7 @@ <div class="viewcode-block" id="k_factor"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.regular.k_factor.html#networkx.algorithms.regular.k_factor">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">k_factor</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">matching_weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Compute a k-factor of G</span> +<span class="w"> </span><span class="sd">"""Compute a k-factor of G</span> <span class="sd"> A k-factor of a graph is a spanning k-regular subgraph.</span> <span class="sd"> A spanning k-regular subgraph of G is a subgraph that contains</span> @@ -723,7 +723,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/richclub.html b/_modules/networkx/algorithms/richclub.html index 0c024ba7..80626a6f 100644 --- a/_modules/networkx/algorithms/richclub.html +++ b/_modules/networkx/algorithms/richclub.html @@ -474,7 +474,7 @@ <div class="viewcode-block" id="rich_club_coefficient"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.richclub.rich_club_coefficient.html#networkx.algorithms.richclub.rich_club_coefficient">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">rich_club_coefficient</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">Q</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the rich-club coefficient of the graph `G`.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the rich-club coefficient of the graph `G`.</span> <span class="sd"> For each degree *k*, the *rich-club coefficient* is the ratio of the</span> <span class="sd"> number of actual to the number of potential edges for nodes with</span> @@ -549,7 +549,7 @@ <span class="k">def</span> <span class="nf">_compute_rc</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the rich-club coefficient for each degree in the graph</span> +<span class="w"> </span><span class="sd">"""Returns the rich-club coefficient for each degree in the graph</span> <span class="sd"> `G`.</span> <span class="sd"> `G` is an undirected graph without multiedges.</span> @@ -632,7 +632,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/shortest_paths/astar.html b/_modules/networkx/algorithms/shortest_paths/astar.html index 7179d006..3bf7bd4d 100644 --- a/_modules/networkx/algorithms/shortest_paths/astar.html +++ b/_modules/networkx/algorithms/shortest_paths/astar.html @@ -473,7 +473,7 @@ <div class="viewcode-block" id="astar_path"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.astar.astar_path.html#networkx.algorithms.shortest_paths.astar.astar_path">[docs]</a><span class="k">def</span> <span class="nf">astar_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">heuristic</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns a list of nodes in a shortest path between source and target</span> +<span class="w"> </span><span class="sd">"""Returns a list of nodes in a shortest path between source and target</span> <span class="sd"> using the A* ("A-star") algorithm.</span> <span class="sd"> There may be more than one shortest path. This returns only one.</span> @@ -619,7 +619,7 @@ <div class="viewcode-block" id="astar_path_length"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.astar.astar_path_length.html#networkx.algorithms.shortest_paths.astar.astar_path_length">[docs]</a><span class="k">def</span> <span class="nf">astar_path_length</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">heuristic</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns the length of the shortest path between source and target using</span> +<span class="w"> </span><span class="sd">"""Returns the length of the shortest path between source and target using</span> <span class="sd"> the A* ("A-star") algorithm.</span> <span class="sd"> Parameters</span> @@ -722,7 +722,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/shortest_paths/dense.html b/_modules/networkx/algorithms/shortest_paths/dense.html index 4b084769..b7b67c15 100644 --- a/_modules/networkx/algorithms/shortest_paths/dense.html +++ b/_modules/networkx/algorithms/shortest_paths/dense.html @@ -474,7 +474,7 @@ <div class="viewcode-block" id="floyd_warshall_numpy"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.floyd_warshall_numpy.html#networkx.algorithms.shortest_paths.dense.floyd_warshall_numpy">[docs]</a><span class="k">def</span> <span class="nf">floyd_warshall_numpy</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Find all-pairs shortest path lengths using Floyd's algorithm.</span> +<span class="w"> </span><span class="sd">"""Find all-pairs shortest path lengths using Floyd's algorithm.</span> <span class="sd"> This algorithm for finding shortest paths takes advantage of</span> <span class="sd"> matrix representations of a graph and works well for dense</span> @@ -537,7 +537,7 @@ <div class="viewcode-block" id="floyd_warshall_predecessor_and_distance"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.floyd_warshall_predecessor_and_distance.html#networkx.algorithms.shortest_paths.dense.floyd_warshall_predecessor_and_distance">[docs]</a><span class="k">def</span> <span class="nf">floyd_warshall_predecessor_and_distance</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Find all-pairs shortest path lengths using Floyd's algorithm.</span> +<span class="w"> </span><span class="sd">"""Find all-pairs shortest path lengths using Floyd's algorithm.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -619,7 +619,7 @@ <div class="viewcode-block" id="reconstruct_path"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.reconstruct_path.html#networkx.algorithms.shortest_paths.dense.reconstruct_path">[docs]</a><span class="k">def</span> <span class="nf">reconstruct_path</span><span class="p">(</span><span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">predecessors</span><span class="p">):</span> - <span class="sd">"""Reconstruct a path from source to target using the predecessors</span> +<span class="w"> </span><span class="sd">"""Reconstruct a path from source to target using the predecessors</span> <span class="sd"> dict as returned by floyd_warshall_predecessor_and_distance</span> <span class="sd"> Parameters</span> @@ -662,7 +662,7 @@ <div class="viewcode-block" id="floyd_warshall"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.floyd_warshall.html#networkx.algorithms.shortest_paths.dense.floyd_warshall">[docs]</a><span class="k">def</span> <span class="nf">floyd_warshall</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Find all-pairs shortest path lengths using Floyd's algorithm.</span> +<span class="w"> </span><span class="sd">"""Find all-pairs shortest path lengths using Floyd's algorithm.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -745,7 +745,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/shortest_paths/generic.html b/_modules/networkx/algorithms/shortest_paths/generic.html index 0f058311..5fdf61f3 100644 --- a/_modules/networkx/algorithms/shortest_paths/generic.html +++ b/_modules/networkx/algorithms/shortest_paths/generic.html @@ -481,7 +481,7 @@ <div class="viewcode-block" id="has_path"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.has_path.html#networkx.algorithms.shortest_paths.generic.has_path">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">has_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">):</span> - <span class="sd">"""Returns *True* if *G* has a path from *source* to *target*.</span> +<span class="w"> </span><span class="sd">"""Returns *True* if *G* has a path from *source* to *target*.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -502,7 +502,7 @@ <div class="viewcode-block" id="shortest_path"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.shortest_path.html#networkx.algorithms.shortest_paths.generic.shortest_path">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">shortest_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s2">"dijkstra"</span><span class="p">):</span> - <span class="sd">"""Compute shortest paths in the graph.</span> +<span class="w"> </span><span class="sd">"""Compute shortest paths in the graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -637,7 +637,7 @@ <div class="viewcode-block" id="shortest_path_length"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.shortest_path_length.html#networkx.algorithms.shortest_paths.generic.shortest_path_length">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">shortest_path_length</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s2">"dijkstra"</span><span class="p">):</span> - <span class="sd">"""Compute shortest path lengths in the graph.</span> +<span class="w"> </span><span class="sd">"""Compute shortest path lengths in the graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -780,7 +780,7 @@ <div class="viewcode-block" id="average_shortest_path_length"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.average_shortest_path_length.html#networkx.algorithms.shortest_paths.generic.average_shortest_path_length">[docs]</a><span class="k">def</span> <span class="nf">average_shortest_path_length</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the average shortest path length.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the average shortest path length.</span> <span class="sd"> The average shortest path length is</span> @@ -896,7 +896,7 @@ <div class="viewcode-block" id="all_shortest_paths"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.all_shortest_paths.html#networkx.algorithms.shortest_paths.generic.all_shortest_paths">[docs]</a><span class="k">def</span> <span class="nf">all_shortest_paths</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s2">"dijkstra"</span><span class="p">):</span> - <span class="sd">"""Compute all shortest simple paths in the graph.</span> +<span class="w"> </span><span class="sd">"""Compute all shortest simple paths in the graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -973,7 +973,7 @@ <span class="k">def</span> <span class="nf">_build_paths_from_predecessors</span><span class="p">(</span><span class="n">sources</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">pred</span><span class="p">):</span> - <span class="sd">"""Compute all simple paths to target, given the predecessors found in</span> +<span class="w"> </span><span class="sd">"""Compute all simple paths to target, given the predecessors found in</span> <span class="sd"> pred, terminating when any source in sources is found.</span> <span class="sd"> Parameters</span> @@ -1088,7 +1088,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/shortest_paths/unweighted.html b/_modules/networkx/algorithms/shortest_paths/unweighted.html index 3cbeecde..f8565ac0 100644 --- a/_modules/networkx/algorithms/shortest_paths/unweighted.html +++ b/_modules/networkx/algorithms/shortest_paths/unweighted.html @@ -479,7 +479,7 @@ <div class="viewcode-block" id="single_source_shortest_path_length"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path_length.html#networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path_length">[docs]</a><span class="k">def</span> <span class="nf">single_source_shortest_path_length</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute the shortest path lengths from source to all reachable nodes.</span> +<span class="w"> </span><span class="sd">"""Compute the shortest path lengths from source to all reachable nodes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -523,7 +523,7 @@ <span class="k">def</span> <span class="nf">_single_shortest_path_length</span><span class="p">(</span><span class="n">adj</span><span class="p">,</span> <span class="n">firstlevel</span><span class="p">,</span> <span class="n">cutoff</span><span class="p">):</span> - <span class="sd">"""Yields (node, level) in a breadth first search</span> +<span class="w"> </span><span class="sd">"""Yields (node, level) in a breadth first search</span> <span class="sd"> Shortest Path Length helper function</span> <span class="sd"> Parameters</span> @@ -557,7 +557,7 @@ <div class="viewcode-block" id="single_target_shortest_path_length"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path_length.html#networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path_length">[docs]</a><span class="k">def</span> <span class="nf">single_target_shortest_path_length</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute the shortest path lengths to target from all reachable nodes.</span> +<span class="w"> </span><span class="sd">"""Compute the shortest path lengths to target from all reachable nodes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -604,7 +604,7 @@ <div class="viewcode-block" id="all_pairs_shortest_path_length"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path_length.html#networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path_length">[docs]</a><span class="k">def</span> <span class="nf">all_pairs_shortest_path_length</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Computes the shortest path lengths between all nodes in `G`.</span> +<span class="w"> </span><span class="sd">"""Computes the shortest path lengths between all nodes in `G`.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -648,7 +648,7 @@ <div class="viewcode-block" id="bidirectional_shortest_path"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.bidirectional_shortest_path.html#networkx.algorithms.shortest_paths.unweighted.bidirectional_shortest_path">[docs]</a><span class="k">def</span> <span class="nf">bidirectional_shortest_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">):</span> - <span class="sd">"""Returns a list of nodes in a shortest path between source and target.</span> +<span class="w"> </span><span class="sd">"""Returns a list of nodes in a shortest path between source and target.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -704,7 +704,7 @@ <span class="k">def</span> <span class="nf">_bidirectional_pred_succ</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">):</span> - <span class="sd">"""Bidirectional shortest path helper.</span> +<span class="w"> </span><span class="sd">"""Bidirectional shortest path helper.</span> <span class="sd"> Returns (pred, succ, w) where</span> <span class="sd"> pred is a dictionary of predecessors from w to the source, and</span> @@ -756,7 +756,7 @@ <div class="viewcode-block" id="single_source_shortest_path"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path.html#networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path">[docs]</a><span class="k">def</span> <span class="nf">single_source_shortest_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute shortest path between source</span> +<span class="w"> </span><span class="sd">"""Compute shortest path between source</span> <span class="sd"> and all other nodes reachable from source.</span> <span class="sd"> Parameters</span> @@ -806,7 +806,7 @@ <span class="k">def</span> <span class="nf">_single_shortest_path</span><span class="p">(</span><span class="n">adj</span><span class="p">,</span> <span class="n">firstlevel</span><span class="p">,</span> <span class="n">paths</span><span class="p">,</span> <span class="n">cutoff</span><span class="p">,</span> <span class="n">join</span><span class="p">):</span> - <span class="sd">"""Returns shortest paths</span> +<span class="w"> </span><span class="sd">"""Returns shortest paths</span> <span class="sd"> Shortest Path helper function</span> <span class="sd"> Parameters</span> @@ -839,7 +839,7 @@ <div class="viewcode-block" id="single_target_shortest_path"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path.html#networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path">[docs]</a><span class="k">def</span> <span class="nf">single_target_shortest_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute shortest path to target from all nodes that reach target.</span> +<span class="w"> </span><span class="sd">"""Compute shortest path to target from all nodes that reach target.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -890,7 +890,7 @@ <div class="viewcode-block" id="all_pairs_shortest_path"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path.html#networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path">[docs]</a><span class="k">def</span> <span class="nf">all_pairs_shortest_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute shortest paths between all nodes.</span> +<span class="w"> </span><span class="sd">"""Compute shortest paths between all nodes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -923,7 +923,7 @@ <div class="viewcode-block" id="predecessor"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.predecessor.html#networkx.algorithms.shortest_paths.unweighted.predecessor">[docs]</a><span class="k">def</span> <span class="nf">predecessor</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">return_seen</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns dict of predecessors for the path from source to all nodes in G.</span> +<span class="w"> </span><span class="sd">"""Returns dict of predecessors for the path from source to all nodes in G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1055,7 +1055,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/shortest_paths/weighted.html b/_modules/networkx/algorithms/shortest_paths/weighted.html index a2e23f33..61c9e9e5 100644 --- a/_modules/networkx/algorithms/shortest_paths/weighted.html +++ b/_modules/networkx/algorithms/shortest_paths/weighted.html @@ -502,7 +502,7 @@ <span class="k">def</span> <span class="nf">_weight_function</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="p">):</span> - <span class="sd">"""Returns a function that returns the weight of an edge.</span> +<span class="w"> </span><span class="sd">"""Returns a function that returns the weight of an edge.</span> <span class="sd"> The returned function is specifically suitable for input to</span> <span class="sd"> functions :func:`_dijkstra` and :func:`_bellman_ford_relaxation`.</span> @@ -542,7 +542,7 @@ <div class="viewcode-block" id="dijkstra_path"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.dijkstra_path.html#networkx.algorithms.shortest_paths.weighted.dijkstra_path">[docs]</a><span class="k">def</span> <span class="nf">dijkstra_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns the shortest weighted path from source to target in G.</span> +<span class="w"> </span><span class="sd">"""Returns the shortest weighted path from source to target in G.</span> <span class="sd"> Uses Dijkstra's Method to compute the shortest weighted path</span> <span class="sd"> between two nodes in a graph.</span> @@ -623,7 +623,7 @@ <div class="viewcode-block" id="dijkstra_path_length"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.dijkstra_path_length.html#networkx.algorithms.shortest_paths.weighted.dijkstra_path_length">[docs]</a><span class="k">def</span> <span class="nf">dijkstra_path_length</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns the shortest weighted path length in G from source to target.</span> +<span class="w"> </span><span class="sd">"""Returns the shortest weighted path length in G from source to target.</span> <span class="sd"> Uses Dijkstra's Method to compute the shortest weighted path length</span> <span class="sd"> between two nodes in a graph.</span> @@ -702,7 +702,7 @@ <div class="viewcode-block" id="single_source_dijkstra_path"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path.html#networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path">[docs]</a><span class="k">def</span> <span class="nf">single_source_dijkstra_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Find shortest weighted paths in G from a source node.</span> +<span class="w"> </span><span class="sd">"""Find shortest weighted paths in G from a source node.</span> <span class="sd"> Compute shortest path between source and all other reachable</span> <span class="sd"> nodes for a weighted graph.</span> @@ -766,7 +766,7 @@ <div class="viewcode-block" id="single_source_dijkstra_path_length"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path_length.html#networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path_length">[docs]</a><span class="k">def</span> <span class="nf">single_source_dijkstra_path_length</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Find shortest weighted path lengths in G from a source node.</span> +<span class="w"> </span><span class="sd">"""Find shortest weighted path lengths in G from a source node.</span> <span class="sd"> Compute the shortest path length between source and all other</span> <span class="sd"> reachable nodes for a weighted graph.</span> @@ -837,7 +837,7 @@ <div class="viewcode-block" id="single_source_dijkstra"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_dijkstra.html#networkx.algorithms.shortest_paths.weighted.single_source_dijkstra">[docs]</a><span class="k">def</span> <span class="nf">single_source_dijkstra</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Find shortest weighted paths and lengths from a source node.</span> +<span class="w"> </span><span class="sd">"""Find shortest weighted paths and lengths from a source node.</span> <span class="sd"> Compute the shortest path length between source and all other</span> <span class="sd"> reachable nodes for a weighted graph.</span> @@ -938,7 +938,7 @@ <div class="viewcode-block" id="multi_source_dijkstra_path"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra_path.html#networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra_path">[docs]</a><span class="k">def</span> <span class="nf">multi_source_dijkstra_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">sources</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Find shortest weighted paths in G from a given set of source</span> +<span class="w"> </span><span class="sd">"""Find shortest weighted paths in G from a given set of source</span> <span class="sd"> nodes.</span> <span class="sd"> Compute shortest path between any of the source nodes and all other</span> @@ -1011,7 +1011,7 @@ <div class="viewcode-block" id="multi_source_dijkstra_path_length"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra_path_length.html#networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra_path_length">[docs]</a><span class="k">def</span> <span class="nf">multi_source_dijkstra_path_length</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">sources</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Find shortest weighted path lengths in G from a given set of</span> +<span class="w"> </span><span class="sd">"""Find shortest weighted path lengths in G from a given set of</span> <span class="sd"> source nodes.</span> <span class="sd"> Compute the shortest path length between any of the source nodes and</span> @@ -1092,7 +1092,7 @@ <div class="viewcode-block" id="multi_source_dijkstra"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra.html#networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra">[docs]</a><span class="k">def</span> <span class="nf">multi_source_dijkstra</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">sources</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Find shortest weighted paths and lengths from a given set of</span> +<span class="w"> </span><span class="sd">"""Find shortest weighted paths and lengths from a given set of</span> <span class="sd"> source nodes.</span> <span class="sd"> Uses Dijkstra's algorithm to compute the shortest paths and lengths</span> @@ -1211,7 +1211,7 @@ <span class="k">def</span> <span class="nf">_dijkstra</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">pred</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">paths</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Uses Dijkstra's algorithm to find shortest weighted paths from a</span> +<span class="w"> </span><span class="sd">"""Uses Dijkstra's algorithm to find shortest weighted paths from a</span> <span class="sd"> single source.</span> <span class="sd"> This is a convenience function for :func:`_dijkstra_multisource`</span> @@ -1227,7 +1227,7 @@ <span class="k">def</span> <span class="nf">_dijkstra_multisource</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">sources</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">pred</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">paths</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Uses Dijkstra's algorithm to find shortest weighted paths</span> +<span class="w"> </span><span class="sd">"""Uses Dijkstra's algorithm to find shortest weighted paths</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1328,7 +1328,7 @@ <div class="viewcode-block" id="dijkstra_predecessor_and_distance"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.dijkstra_predecessor_and_distance.html#networkx.algorithms.shortest_paths.weighted.dijkstra_predecessor_and_distance">[docs]</a><span class="k">def</span> <span class="nf">dijkstra_predecessor_and_distance</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Compute weighted shortest path length and predecessors.</span> +<span class="w"> </span><span class="sd">"""Compute weighted shortest path length and predecessors.</span> <span class="sd"> Uses Dijkstra's Method to obtain the shortest weighted paths</span> <span class="sd"> and return dictionaries of predecessors for each node and</span> @@ -1400,7 +1400,7 @@ <div class="viewcode-block" id="all_pairs_dijkstra"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra.html#networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra">[docs]</a><span class="k">def</span> <span class="nf">all_pairs_dijkstra</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Find shortest weighted paths and lengths between all nodes.</span> +<span class="w"> </span><span class="sd">"""Find shortest weighted paths and lengths between all nodes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1468,7 +1468,7 @@ <div class="viewcode-block" id="all_pairs_dijkstra_path_length"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra_path_length.html#networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra_path_length">[docs]</a><span class="k">def</span> <span class="nf">all_pairs_dijkstra_path_length</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Compute shortest path lengths between all nodes in a weighted graph.</span> +<span class="w"> </span><span class="sd">"""Compute shortest path lengths between all nodes in a weighted graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1526,7 +1526,7 @@ <div class="viewcode-block" id="all_pairs_dijkstra_path"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra_path.html#networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra_path">[docs]</a><span class="k">def</span> <span class="nf">all_pairs_dijkstra_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Compute shortest paths between all nodes in a weighted graph.</span> +<span class="w"> </span><span class="sd">"""Compute shortest paths between all nodes in a weighted graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1580,7 +1580,7 @@ <div class="viewcode-block" id="bellman_ford_predecessor_and_distance"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bellman_ford_predecessor_and_distance.html#networkx.algorithms.shortest_paths.weighted.bellman_ford_predecessor_and_distance">[docs]</a><span class="k">def</span> <span class="nf">bellman_ford_predecessor_and_distance</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">heuristic</span><span class="o">=</span><span class="kc">False</span> <span class="p">):</span> - <span class="sd">"""Compute shortest path lengths and predecessors on shortest paths</span> +<span class="w"> </span><span class="sd">"""Compute shortest path lengths and predecessors on shortest paths</span> <span class="sd"> in weighted graphs.</span> <span class="sd"> The algorithm has a running time of $O(mn)$ where $n$ is the number of</span> @@ -1709,7 +1709,7 @@ <span class="n">target</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">heuristic</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Calls relaxation loop for Bellman–Ford algorithm and builds paths</span> +<span class="w"> </span><span class="sd">"""Calls relaxation loop for Bellman–Ford algorithm and builds paths</span> <span class="sd"> This is an implementation of the SPFA variant.</span> <span class="sd"> See https://en.wikipedia.org/wiki/Shortest_Path_Faster_Algorithm</span> @@ -1801,7 +1801,7 @@ <span class="n">dist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">heuristic</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Inner Relaxation loop for Bellman–Ford algorithm.</span> +<span class="w"> </span><span class="sd">"""Inner Relaxation loop for Bellman–Ford algorithm.</span> <span class="sd"> This is an implementation of the SPFA variant.</span> <span class="sd"> See https://en.wikipedia.org/wiki/Shortest_Path_Faster_Algorithm</span> @@ -1918,7 +1918,7 @@ <div class="viewcode-block" id="bellman_ford_path"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bellman_ford_path.html#networkx.algorithms.shortest_paths.weighted.bellman_ford_path">[docs]</a><span class="k">def</span> <span class="nf">bellman_ford_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns the shortest path from source to target in a weighted graph G.</span> +<span class="w"> </span><span class="sd">"""Returns the shortest path from source to target in a weighted graph G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1976,7 +1976,7 @@ <div class="viewcode-block" id="bellman_ford_path_length"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bellman_ford_path_length.html#networkx.algorithms.shortest_paths.weighted.bellman_ford_path_length">[docs]</a><span class="k">def</span> <span class="nf">bellman_ford_path_length</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns the shortest path length from source to target</span> +<span class="w"> </span><span class="sd">"""Returns the shortest path length from source to target</span> <span class="sd"> in a weighted graph.</span> <span class="sd"> Parameters</span> @@ -2046,7 +2046,7 @@ <div class="viewcode-block" id="single_source_bellman_ford_path"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path.html#networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path">[docs]</a><span class="k">def</span> <span class="nf">single_source_bellman_ford_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Compute shortest path between source and all other reachable</span> +<span class="w"> </span><span class="sd">"""Compute shortest path between source and all other reachable</span> <span class="sd"> nodes for a weighted graph.</span> <span class="sd"> Parameters</span> @@ -2101,7 +2101,7 @@ <div class="viewcode-block" id="single_source_bellman_ford_path_length"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path_length.html#networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path_length">[docs]</a><span class="k">def</span> <span class="nf">single_source_bellman_ford_path_length</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Compute the shortest path length between source and all other</span> +<span class="w"> </span><span class="sd">"""Compute the shortest path length between source and all other</span> <span class="sd"> reachable nodes for a weighted graph.</span> <span class="sd"> Parameters</span> @@ -2163,7 +2163,7 @@ <div class="viewcode-block" id="single_source_bellman_ford"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford.html#networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford">[docs]</a><span class="k">def</span> <span class="nf">single_source_bellman_ford</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Compute shortest paths and lengths in a weighted graph G.</span> +<span class="w"> </span><span class="sd">"""Compute shortest paths and lengths in a weighted graph G.</span> <span class="sd"> Uses Bellman-Ford algorithm for shortest paths.</span> @@ -2256,7 +2256,7 @@ <div class="viewcode-block" id="all_pairs_bellman_ford_path_length"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_bellman_ford_path_length.html#networkx.algorithms.shortest_paths.weighted.all_pairs_bellman_ford_path_length">[docs]</a><span class="k">def</span> <span class="nf">all_pairs_bellman_ford_path_length</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Compute shortest path lengths between all nodes in a weighted graph.</span> +<span class="w"> </span><span class="sd">"""Compute shortest path lengths between all nodes in a weighted graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -2310,7 +2310,7 @@ <div class="viewcode-block" id="all_pairs_bellman_ford_path"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_bellman_ford_path.html#networkx.algorithms.shortest_paths.weighted.all_pairs_bellman_ford_path">[docs]</a><span class="k">def</span> <span class="nf">all_pairs_bellman_ford_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Compute shortest paths between all nodes in a weighted graph.</span> +<span class="w"> </span><span class="sd">"""Compute shortest paths between all nodes in a weighted graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -2358,7 +2358,7 @@ <div class="viewcode-block" id="goldberg_radzik"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.goldberg_radzik.html#networkx.algorithms.shortest_paths.weighted.goldberg_radzik">[docs]</a><span class="k">def</span> <span class="nf">goldberg_radzik</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Compute shortest path lengths and predecessors on shortest paths</span> +<span class="w"> </span><span class="sd">"""Compute shortest path lengths and predecessors on shortest paths</span> <span class="sd"> in weighted graphs.</span> <span class="sd"> The algorithm has a running time of $O(mn)$ where $n$ is the number of</span> @@ -2450,7 +2450,7 @@ <span class="n">pred</span> <span class="o">=</span> <span class="p">{</span><span class="n">source</span><span class="p">:</span> <span class="kc">None</span><span class="p">}</span> <span class="k">def</span> <span class="nf">topo_sort</span><span class="p">(</span><span class="n">relabeled</span><span class="p">):</span> - <span class="sd">"""Topologically sort nodes relabeled in the previous round and detect</span> +<span class="w"> </span><span class="sd">"""Topologically sort nodes relabeled in the previous round and detect</span> <span class="sd"> negative cycles.</span> <span class="sd"> """</span> <span class="c1"># List of nodes to scan in this round. Denoted by A in Goldberg and</span> @@ -2506,7 +2506,7 @@ <span class="k">return</span> <span class="n">to_scan</span> <span class="k">def</span> <span class="nf">relax</span><span class="p">(</span><span class="n">to_scan</span><span class="p">):</span> - <span class="sd">"""Relax out-edges of relabeled nodes."""</span> +<span class="w"> </span><span class="sd">"""Relax out-edges of relabeled nodes."""</span> <span class="n">relabeled</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span> <span class="c1"># Scan nodes in to_scan in topological order and relax incident</span> <span class="c1"># out-edges. Add the relabled nodes to labeled.</span> @@ -2533,7 +2533,7 @@ <div class="viewcode-block" id="negative_edge_cycle"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.negative_edge_cycle.html#networkx.algorithms.shortest_paths.weighted.negative_edge_cycle">[docs]</a><span class="k">def</span> <span class="nf">negative_edge_cycle</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">heuristic</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Returns True if there exists a negative edge cycle anywhere in G.</span> +<span class="w"> </span><span class="sd">"""Returns True if there exists a negative edge cycle anywhere in G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -2600,7 +2600,7 @@ <div class="viewcode-block" id="find_negative_cycle"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.find_negative_cycle.html#networkx.algorithms.shortest_paths.weighted.find_negative_cycle">[docs]</a><span class="k">def</span> <span class="nf">find_negative_cycle</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns a cycle with negative total weight if it exists.</span> +<span class="w"> </span><span class="sd">"""Returns a cycle with negative total weight if it exists.</span> <span class="sd"> Bellman-Ford is used to find shortest_paths. That algorithm</span> <span class="sd"> stops if there exists a negative cycle. This algorithm</span> @@ -2692,7 +2692,7 @@ <div class="viewcode-block" id="bidirectional_dijkstra"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bidirectional_dijkstra.html#networkx.algorithms.shortest_paths.weighted.bidirectional_dijkstra">[docs]</a><span class="k">def</span> <span class="nf">bidirectional_dijkstra</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Dijkstra's algorithm for shortest paths using bidirectional search.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Dijkstra's algorithm for shortest paths using bidirectional search.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -2839,7 +2839,7 @@ <div class="viewcode-block" id="johnson"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.johnson.html#networkx.algorithms.shortest_paths.weighted.johnson">[docs]</a><span class="k">def</span> <span class="nf">johnson</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Uses Johnson's Algorithm to compute shortest paths.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Uses Johnson's Algorithm to compute shortest paths.</span> <span class="sd"> Johnson's Algorithm finds a shortest path between each pair of</span> <span class="sd"> nodes in a weighted graph even if negative weights are present.</span> @@ -2977,7 +2977,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/similarity.html b/_modules/networkx/algorithms/similarity.html index 12ea90f1..61cc66f9 100644 --- a/_modules/networkx/algorithms/similarity.html +++ b/_modules/networkx/algorithms/similarity.html @@ -515,7 +515,7 @@ <span class="n">upper_bound</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">timeout</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns GED (graph edit distance) between graphs G1 and G2.</span> +<span class="w"> </span><span class="sd">"""Returns GED (graph edit distance) between graphs G1 and G2.</span> <span class="sd"> Graph edit distance is a graph similarity measure analogous to</span> <span class="sd"> Levenshtein distance for strings. It is defined as minimum cost</span> @@ -684,7 +684,7 @@ <span class="n">edge_ins_cost</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">upper_bound</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns all minimum-cost edit paths transforming G1 to G2.</span> +<span class="w"> </span><span class="sd">"""Returns all minimum-cost edit paths transforming G1 to G2.</span> <span class="sd"> Graph edit path is a sequence of node and edge edit operations</span> <span class="sd"> transforming graph G1 to graph isomorphic to G2. Edit operations</span> @@ -846,7 +846,7 @@ <span class="n">edge_ins_cost</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">upper_bound</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns consecutive approximations of GED (graph edit distance)</span> +<span class="w"> </span><span class="sd">"""Returns consecutive approximations of GED (graph edit distance)</span> <span class="sd"> between graphs G1 and G2.</span> <span class="sd"> Graph edit distance is a graph similarity measure analogous to</span> @@ -999,7 +999,7 @@ <span class="n">roots</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">timeout</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""GED (graph edit distance) calculation: advanced interface.</span> +<span class="w"> </span><span class="sd">"""GED (graph edit distance) calculation: advanced interface.</span> <span class="sd"> Graph edit path is a sequence of node and edge edit operations</span> <span class="sd"> transforming graph G1 to graph isomorphic to G2. Edit operations</span> @@ -1188,7 +1188,7 @@ <span class="k">return</span> <span class="n">rind</span> <span class="k">def</span> <span class="nf">match_edges</span><span class="p">(</span><span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">pending_g</span><span class="p">,</span> <span class="n">pending_h</span><span class="p">,</span> <span class="n">Ce</span><span class="p">,</span> <span class="n">matched_uv</span><span class="o">=</span><span class="p">[]):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Parameters:</span> <span class="sd"> u, v: matched vertices, u=None or v=None for</span> <span class="sd"> deletion/insertion</span> @@ -1291,7 +1291,7 @@ <span class="k">def</span> <span class="nf">get_edit_ops</span><span class="p">(</span> <span class="n">matched_uv</span><span class="p">,</span> <span class="n">pending_u</span><span class="p">,</span> <span class="n">pending_v</span><span class="p">,</span> <span class="n">Cv</span><span class="p">,</span> <span class="n">pending_g</span><span class="p">,</span> <span class="n">pending_h</span><span class="p">,</span> <span class="n">Ce</span><span class="p">,</span> <span class="n">matched_cost</span> <span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Parameters:</span> <span class="sd"> matched_uv: partial vertex edit path</span> <span class="sd"> list of tuples (u, v) of vertex mappings u<->v,</span> @@ -1398,7 +1398,7 @@ <span class="n">Ce</span><span class="p">,</span> <span class="n">matched_cost</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Parameters:</span> <span class="sd"> matched_uv: partial vertex edit path</span> <span class="sd"> list of tuples (u, v) of vertex mappings u<->v,</span> @@ -1679,7 +1679,7 @@ <span class="n">max_iterations</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> <span class="n">tolerance</span><span class="o">=</span><span class="mf">1e-4</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns the SimRank similarity of nodes in the graph ``G``.</span> +<span class="w"> </span><span class="sd">"""Returns the SimRank similarity of nodes in the graph ``G``.</span> <span class="sd"> SimRank is a similarity metric that says "two objects are considered</span> <span class="sd"> to be similar if they are referenced by similar objects." [1]_.</span> @@ -1801,7 +1801,7 @@ <span class="n">max_iterations</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> <span class="n">tolerance</span><span class="o">=</span><span class="mf">1e-4</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns the SimRank similarity of nodes in the graph ``G``.</span> +<span class="w"> </span><span class="sd">"""Returns the SimRank similarity of nodes in the graph ``G``.</span> <span class="sd"> This pure Python version is provided for pedagogical purposes.</span> @@ -1861,7 +1861,7 @@ <span class="n">max_iterations</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> <span class="n">tolerance</span><span class="o">=</span><span class="mf">1e-4</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Calculate SimRank of nodes in ``G`` using matrices with ``numpy``.</span> +<span class="w"> </span><span class="sd">"""Calculate SimRank of nodes in ``G`` using matrices with ``numpy``.</span> <span class="sd"> The SimRank algorithm for determining node similarity is defined in</span> <span class="sd"> [1]_.</span> @@ -1963,7 +1963,7 @@ <div class="viewcode-block" id="panther_similarity"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.similarity.panther_similarity.html#networkx.algorithms.similarity.panther_similarity">[docs]</a><span class="k">def</span> <span class="nf">panther_similarity</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">path_length</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">c</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">delta</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the Panther similarity of nodes in the graph `G` to node ``v``.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the Panther similarity of nodes in the graph `G` to node ``v``.</span> <span class="sd"> Panther is a similarity metric that says "two objects are considered</span> <span class="sd"> to be similar if they frequently appear on the same paths." [1]_.</span> @@ -2068,7 +2068,7 @@ <div class="viewcode-block" id="generate_random_paths"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.similarity.generate_random_paths.html#networkx.algorithms.similarity.generate_random_paths">[docs]</a><span class="k">def</span> <span class="nf">generate_random_paths</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">sample_size</span><span class="p">,</span> <span class="n">path_length</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">index_map</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Randomly generate `sample_size` paths of length `path_length`.</span> +<span class="w"> </span><span class="sd">"""Randomly generate `sample_size` paths of length `path_length`.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -2214,7 +2214,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/simple_paths.html b/_modules/networkx/algorithms/simple_paths.html index 5645d675..77138848 100644 --- a/_modules/networkx/algorithms/simple_paths.html +++ b/_modules/networkx/algorithms/simple_paths.html @@ -478,7 +478,7 @@ <div class="viewcode-block" id="is_simple_path"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.simple_paths.is_simple_path.html#networkx.algorithms.simple_paths.is_simple_path">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">is_simple_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="p">):</span> - <span class="sd">"""Returns True if and only if `nodes` form a simple path in `G`.</span> +<span class="w"> </span><span class="sd">"""Returns True if and only if `nodes` form a simple path in `G`.</span> <span class="sd"> A *simple path* in a graph is a nonempty sequence of nodes in which</span> <span class="sd"> no node appears more than once in the sequence, and each adjacent</span> @@ -555,7 +555,7 @@ <div class="viewcode-block" id="all_simple_paths"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.simple_paths.all_simple_paths.html#networkx.algorithms.simple_paths.all_simple_paths">[docs]</a><span class="k">def</span> <span class="nf">all_simple_paths</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Generate all simple paths in the graph G from source to target.</span> +<span class="w"> </span><span class="sd">"""Generate all simple paths in the graph G from source to target.</span> <span class="sd"> A simple path is a path with no repeated nodes.</span> @@ -784,7 +784,7 @@ <div class="viewcode-block" id="all_simple_edge_paths"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.simple_paths.all_simple_edge_paths.html#networkx.algorithms.simple_paths.all_simple_edge_paths">[docs]</a><span class="k">def</span> <span class="nf">all_simple_edge_paths</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Generate lists of edges for all simple paths in G from source to target.</span> +<span class="w"> </span><span class="sd">"""Generate lists of edges for all simple paths in G from source to target.</span> <span class="sd"> A simple path is a path with no repeated nodes.</span> @@ -905,7 +905,7 @@ <div class="viewcode-block" id="shortest_simple_paths"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.simple_paths.shortest_simple_paths.html#networkx.algorithms.simple_paths.shortest_simple_paths">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">shortest_simple_paths</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Generate all simple paths in the graph G from source to target,</span> +<span class="w"> </span><span class="sd">"""Generate all simple paths in the graph G from source to target,</span> <span class="sd"> starting from shortest ones.</span> <span class="sd"> A simple path is a path with no repeated nodes.</span> @@ -1075,7 +1075,7 @@ <span class="k">def</span> <span class="nf">_bidirectional_shortest_path</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">ignore_nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">ignore_edges</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Returns the shortest path between source and target ignoring</span> +<span class="w"> </span><span class="sd">"""Returns the shortest path between source and target ignoring</span> <span class="sd"> nodes and edges in the containers ignore_nodes and ignore_edges.</span> <span class="sd"> This is a custom modification of the standard bidirectional shortest</span> @@ -1136,7 +1136,7 @@ <span class="k">def</span> <span class="nf">_bidirectional_pred_succ</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">ignore_nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">ignore_edges</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Bidirectional shortest path helper.</span> +<span class="w"> </span><span class="sd">"""Bidirectional shortest path helper.</span> <span class="sd"> Returns (pred,succ,w) where</span> <span class="sd"> pred is a dictionary of predecessors from w to the source, and</span> <span class="sd"> succ is a dictionary of successors from w to the target.</span> @@ -1243,7 +1243,7 @@ <span class="k">def</span> <span class="nf">_bidirectional_dijkstra</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">ignore_nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">ignore_edges</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Dijkstra's algorithm for shortest paths using bidirectional search.</span> +<span class="w"> </span><span class="sd">"""Dijkstra's algorithm for shortest paths using bidirectional search.</span> <span class="sd"> This function returns the shortest path between source and target</span> <span class="sd"> ignoring nodes and edges in the containers ignore_nodes and</span> @@ -1487,7 +1487,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/smallworld.html b/_modules/networkx/algorithms/smallworld.html index a7215f9d..4800d028 100644 --- a/_modules/networkx/algorithms/smallworld.html +++ b/_modules/networkx/algorithms/smallworld.html @@ -487,7 +487,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_reference</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">connectivity</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Compute a random graph by swapping edges of a given graph.</span> +<span class="w"> </span><span class="sd">"""Compute a random graph by swapping edges of a given graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -584,7 +584,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">lattice_reference</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">D</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">connectivity</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Latticize the given graph by swapping edges.</span> +<span class="w"> </span><span class="sd">"""Latticize the given graph by swapping edges.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -707,7 +707,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">sigma</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">nrand</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the small-world coefficient (sigma) of the given graph.</span> +<span class="w"> </span><span class="sd">"""Returns the small-world coefficient (sigma) of the given graph.</span> <span class="sd"> The small-world coefficient is defined as:</span> <span class="sd"> sigma = C/Cr / L/Lr</span> @@ -775,7 +775,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">omega</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">nrand</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the small-world coefficient (omega) of a graph</span> +<span class="w"> </span><span class="sd">"""Returns the small-world coefficient (omega) of a graph</span> <span class="sd"> The small-world coefficient of a graph G is:</span> @@ -911,7 +911,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/smetric.html b/_modules/networkx/algorithms/smetric.html index ad527382..00cd4176 100644 --- a/_modules/networkx/algorithms/smetric.html +++ b/_modules/networkx/algorithms/smetric.html @@ -468,7 +468,7 @@ <div class="viewcode-block" id="s_metric"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.smetric.s_metric.html#networkx.algorithms.smetric.s_metric">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">s_metric</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Returns the s-metric of graph.</span> +<span class="w"> </span><span class="sd">"""Returns the s-metric of graph.</span> <span class="sd"> The s-metric is defined as the sum of the products deg(u)*deg(v)</span> <span class="sd"> for every edge (u,v) in G. If norm is provided construct the</span> @@ -551,7 +551,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/sparsifiers.html b/_modules/networkx/algorithms/sparsifiers.html index 4b0da1a7..e889a918 100644 --- a/_modules/networkx/algorithms/sparsifiers.html +++ b/_modules/networkx/algorithms/sparsifiers.html @@ -474,7 +474,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">spanner</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">stretch</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a spanner of the given graph with the given stretch.</span> +<span class="w"> </span><span class="sd">"""Returns a spanner of the given graph with the given stretch.</span> <span class="sd"> A spanner of a graph G = (V, E) with stretch t is a subgraph</span> <span class="sd"> H = (V, E_S) such that E_S is a subset of E and the distance between</span> @@ -649,7 +649,7 @@ <span class="k">def</span> <span class="nf">_setup_residual_graph</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="p">):</span> - <span class="sd">"""Setup residual graph as a copy of G with unique edges weights.</span> +<span class="w"> </span><span class="sd">"""Setup residual graph as a copy of G with unique edges weights.</span> <span class="sd"> The node set of the residual graph corresponds to the set V' from</span> <span class="sd"> the Baswana-Sen paper and the edge set corresponds to the set E'</span> @@ -685,7 +685,7 @@ <span class="k">def</span> <span class="nf">_lightest_edge_dicts</span><span class="p">(</span><span class="n">residual_graph</span><span class="p">,</span> <span class="n">clustering</span><span class="p">,</span> <span class="n">node</span><span class="p">):</span> - <span class="sd">"""Find the lightest edge to each cluster.</span> +<span class="w"> </span><span class="sd">"""Find the lightest edge to each cluster.</span> <span class="sd"> Searches for the minimum-weight edge to each cluster adjacent to</span> <span class="sd"> the given node.</span> @@ -731,7 +731,7 @@ <span class="k">def</span> <span class="nf">_add_edge_to_spanner</span><span class="p">(</span><span class="n">H</span><span class="p">,</span> <span class="n">residual_graph</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">weight</span><span class="p">):</span> - <span class="sd">"""Add the edge {u, v} to the spanner H and take weight from</span> +<span class="w"> </span><span class="sd">"""Add the edge {u, v} to the spanner H and take weight from</span> <span class="sd"> the residual graph.</span> <span class="sd"> Parameters</span> @@ -806,7 +806,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/structuralholes.html b/_modules/networkx/algorithms/structuralholes.html index 8e70f7df..a1f3c86c 100644 --- a/_modules/networkx/algorithms/structuralholes.html +++ b/_modules/networkx/algorithms/structuralholes.html @@ -470,7 +470,7 @@ <span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">mutual_weight</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the sum of the weights of the edge from `u` to `v` and</span> +<span class="w"> </span><span class="sd">"""Returns the sum of the weights of the edge from `u` to `v` and</span> <span class="sd"> the edge from `v` to `u` in `G`.</span> <span class="sd"> `weight` is the edge data key that represents the edge weight. If</span> @@ -492,7 +492,7 @@ <span class="k">def</span> <span class="nf">normalized_mutual_weight</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="nb">sum</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns normalized mutual weight of the edges from `u` to `v`</span> +<span class="w"> </span><span class="sd">"""Returns normalized mutual weight of the edges from `u` to `v`</span> <span class="sd"> with respect to the mutual weights of the neighbors of `u` in `G`.</span> <span class="sd"> `norm` specifies how the normalization factor is computed. It must</span> @@ -512,7 +512,7 @@ <div class="viewcode-block" id="effective_size"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.structuralholes.effective_size.html#networkx.algorithms.structuralholes.effective_size">[docs]</a><span class="k">def</span> <span class="nf">effective_size</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the effective size of all nodes in the graph ``G``.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the effective size of all nodes in the graph ``G``.</span> <span class="sd"> The *effective size* of a node's ego network is based on the concept</span> <span class="sd"> of redundancy. A person's ego network has redundancy to the extent</span> @@ -624,7 +624,7 @@ <div class="viewcode-block" id="constraint"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.structuralholes.constraint.html#networkx.algorithms.structuralholes.constraint">[docs]</a><span class="k">def</span> <span class="nf">constraint</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the constraint on all nodes in the graph ``G``.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the constraint on all nodes in the graph ``G``.</span> <span class="sd"> The *constraint* is a measure of the extent to which a node *v* is</span> <span class="sd"> invested in those nodes that are themselves invested in the</span> @@ -684,7 +684,7 @@ <div class="viewcode-block" id="local_constraint"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.structuralholes.local_constraint.html#networkx.algorithms.structuralholes.local_constraint">[docs]</a><span class="k">def</span> <span class="nf">local_constraint</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the local constraint on the node ``u`` with respect to</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the local constraint on the node ``u`` with respect to</span> <span class="sd"> the node ``v`` in the graph ``G``.</span> <span class="sd"> Formally, the *local constraint on u with respect to v*, denoted</span> @@ -791,7 +791,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/summarization.html b/_modules/networkx/algorithms/summarization.html index b733d299..7bd44172 100644 --- a/_modules/networkx/algorithms/summarization.html +++ b/_modules/networkx/algorithms/summarization.html @@ -529,7 +529,7 @@ <div class="viewcode-block" id="dedensify"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.summarization.dedensify.html#networkx.algorithms.summarization.dedensify">[docs]</a><span class="k">def</span> <span class="nf">dedensify</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">threshold</span><span class="p">,</span> <span class="n">prefix</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Compresses neighborhoods around high-degree nodes</span> +<span class="w"> </span><span class="sd">"""Compresses neighborhoods around high-degree nodes</span> <span class="sd"> Reduces the number of edges to high-degree nodes by adding compressor nodes</span> <span class="sd"> that summarize multiple edges of the same type to high-degree nodes (nodes</span> @@ -686,7 +686,7 @@ <span class="n">supernode_attribute</span><span class="p">,</span> <span class="n">superedge_attribute</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Build the summary graph from the data structures produced in the SNAP aggregation algorithm</span> <span class="sd"> Used in the SNAP aggregation algorithm to build the output summary graph and supernode</span> @@ -766,7 +766,7 @@ <span class="k">def</span> <span class="nf">_snap_eligible_group</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">groups</span><span class="p">,</span> <span class="n">group_lookup</span><span class="p">,</span> <span class="n">edge_types</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Determines if a group is eligible to be split.</span> <span class="sd"> A group is eligible to be split if all nodes in the group have edges of the same type(s)</span> @@ -818,7 +818,7 @@ <span class="k">def</span> <span class="nf">_snap_split</span><span class="p">(</span><span class="n">groups</span><span class="p">,</span> <span class="n">neighbor_info</span><span class="p">,</span> <span class="n">group_lookup</span><span class="p">,</span> <span class="n">group_id</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Splits a group based on edge types and updates the groups accordingly</span> <span class="sd"> Splits the group with the given group_id based on the edge types</span> @@ -874,7 +874,7 @@ <span class="n">supernode_attribute</span><span class="o">=</span><span class="s2">"group"</span><span class="p">,</span> <span class="n">superedge_attribute</span><span class="o">=</span><span class="s2">"types"</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Creates a summary graph based on attributes and connectivity.</span> +<span class="w"> </span><span class="sd">"""Creates a summary graph based on attributes and connectivity.</span> <span class="sd"> This function uses the Summarization by Grouping Nodes on Attributes</span> <span class="sd"> and Pairwise edges (SNAP) algorithm for summarizing a given</span> @@ -1068,7 +1068,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/swap.html b/_modules/networkx/algorithms/swap.html index 25308ce5..27e7bbe0 100644 --- a/_modules/networkx/algorithms/swap.html +++ b/_modules/networkx/algorithms/swap.html @@ -475,7 +475,7 @@ <div class="viewcode-block" id="directed_edge_swap"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.swap.directed_edge_swap.html#networkx.algorithms.swap.directed_edge_swap">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="nd">@nx</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">directed_edge_swap</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">nswap</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">max_tries</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Swap three edges in a directed graph while keeping the node degrees fixed.</span> +<span class="w"> </span><span class="sd">"""Swap three edges in a directed graph while keeping the node degrees fixed.</span> <span class="sd"> A directed edge swap swaps three edges such that a -> b -> c -> d becomes</span> <span class="sd"> a -> c -> b -> d. This pattern of swapping allows all possible states with the</span> @@ -594,7 +594,7 @@ <div class="viewcode-block" id="double_edge_swap"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.swap.double_edge_swap.html#networkx.algorithms.swap.double_edge_swap">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">double_edge_swap</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nswap</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">max_tries</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Swap two edges in the graph while keeping the node degrees fixed.</span> +<span class="w"> </span><span class="sd">"""Swap two edges in the graph while keeping the node degrees fixed.</span> <span class="sd"> A double-edge swap removes two randomly chosen edges u-v and x-y</span> <span class="sd"> and creates the new edges u-x and v-y::</span> @@ -691,7 +691,7 @@ <div class="viewcode-block" id="connected_double_edge_swap"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.swap.connected_double_edge_swap.html#networkx.algorithms.swap.connected_double_edge_swap">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">connected_double_edge_swap</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nswap</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">_window_threshold</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Attempts the specified number of double-edge swaps in the graph `G`.</span> +<span class="w"> </span><span class="sd">"""Attempts the specified number of double-edge swaps in the graph `G`.</span> <span class="sd"> A double-edge swap removes two randomly chosen edges `(u, v)` and `(x,</span> <span class="sd"> y)` and creates the new edges `(u, x)` and `(v, y)`::</span> @@ -914,7 +914,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/threshold.html b/_modules/networkx/algorithms/threshold.html index afb3444d..45c6128d 100644 --- a/_modules/networkx/algorithms/threshold.html +++ b/_modules/networkx/algorithms/threshold.html @@ -473,7 +473,7 @@ <div class="viewcode-block" id="is_threshold_graph"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.threshold.is_threshold_graph.html#networkx.algorithms.threshold.is_threshold_graph">[docs]</a><span class="k">def</span> <span class="nf">is_threshold_graph</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns `True` if `G` is a threshold graph.</span> <span class="sd"> Parameters</span> @@ -504,7 +504,7 @@ <span class="k">def</span> <span class="nf">is_threshold_sequence</span><span class="p">(</span><span class="n">degree_sequence</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns True if the sequence is a threshold degree seqeunce.</span> <span class="sd"> Uses the property that a threshold graph must be constructed by</span> @@ -527,7 +527,7 @@ <span class="k">def</span> <span class="nf">creation_sequence</span><span class="p">(</span><span class="n">degree_sequence</span><span class="p">,</span> <span class="n">with_labels</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">compact</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Determines the creation sequence for the given threshold degree sequence.</span> <span class="sd"> The creation sequence is a list of single characters 'd'</span> @@ -586,7 +586,7 @@ <span class="k">def</span> <span class="nf">make_compact</span><span class="p">(</span><span class="n">creation_sequence</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the creation sequence in a compact form</span> <span class="sd"> that is the number of 'i's and 'd's alternating.</span> @@ -630,7 +630,7 @@ <span class="k">def</span> <span class="nf">uncompact</span><span class="p">(</span><span class="n">creation_sequence</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Converts a compact creation sequence for a threshold</span> <span class="sd"> graph to a standard creation sequence (unlabeled).</span> <span class="sd"> If the creation_sequence is already standard, return it.</span> @@ -654,7 +654,7 @@ <span class="k">def</span> <span class="nf">creation_sequence_to_weights</span><span class="p">(</span><span class="n">creation_sequence</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns a list of node weights which create the threshold</span> <span class="sd"> graph designated by the creation sequence. The weights</span> <span class="sd"> are scaled so that the threshold is 1.0. The order of the</span> @@ -703,7 +703,7 @@ <span class="k">def</span> <span class="nf">weights_to_creation_sequence</span><span class="p">(</span> <span class="n">weights</span><span class="p">,</span> <span class="n">threshold</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">with_labels</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">compact</span><span class="o">=</span><span class="kc">False</span> <span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns a creation sequence for a threshold graph</span> <span class="sd"> determined by the weights and threshold given as input.</span> <span class="sd"> If the sum of two node weights is greater than the</span> @@ -764,7 +764,7 @@ <span class="c1"># Manipulating NetworkX.Graphs in context of threshold graphs</span> <span class="k">def</span> <span class="nf">threshold_graph</span><span class="p">(</span><span class="n">creation_sequence</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Create a threshold graph from the creation sequence or compact</span> <span class="sd"> creation_sequence.</span> @@ -815,7 +815,7 @@ <span class="k">def</span> <span class="nf">find_alternating_4_cycle</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns False if there aren't any alternating 4 cycles.</span> <span class="sd"> Otherwise returns the cycle as [a,b,c,d] where (a,b)</span> <span class="sd"> and (c,d) are edges and (a,c) and (b,d) are not.</span> @@ -830,7 +830,7 @@ <div class="viewcode-block" id="find_threshold_graph"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.threshold.find_threshold_graph.html#networkx.algorithms.threshold.find_threshold_graph">[docs]</a><span class="k">def</span> <span class="nf">find_threshold_graph</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns a threshold subgraph that is close to largest in `G`.</span> <span class="sd"> The threshold graph will contain the largest degree node in G.</span> @@ -864,7 +864,7 @@ <span class="k">def</span> <span class="nf">find_creation_sequence</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Find a threshold subgraph that is close to largest in G.</span> <span class="sd"> Returns the labeled creation sequence of that threshold graph.</span> <span class="sd"> """</span> @@ -896,7 +896,7 @@ <span class="c1"># Properties of Threshold Graphs</span> <span class="k">def</span> <span class="nf">triangles</span><span class="p">(</span><span class="n">creation_sequence</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Compute number of triangles in the threshold graph with the</span> <span class="sd"> given creation sequence.</span> <span class="sd"> """</span> @@ -916,7 +916,7 @@ <span class="k">def</span> <span class="nf">triangle_sequence</span><span class="p">(</span><span class="n">creation_sequence</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Return triangle sequence for the given threshold graph creation sequence.</span> <span class="sd"> """</span> @@ -944,7 +944,7 @@ <span class="k">def</span> <span class="nf">cluster_sequence</span><span class="p">(</span><span class="n">creation_sequence</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Return cluster sequence for the given threshold graph creation sequence.</span> <span class="sd"> """</span> <span class="n">triseq</span> <span class="o">=</span> <span class="n">triangle_sequence</span><span class="p">(</span><span class="n">creation_sequence</span><span class="p">)</span> @@ -961,7 +961,7 @@ <span class="k">def</span> <span class="nf">degree_sequence</span><span class="p">(</span><span class="n">creation_sequence</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Return degree sequence for the threshold graph with the given</span> <span class="sd"> creation sequence</span> <span class="sd"> """</span> @@ -978,7 +978,7 @@ <span class="k">def</span> <span class="nf">density</span><span class="p">(</span><span class="n">creation_sequence</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Return the density of the graph with this creation_sequence.</span> <span class="sd"> The density is the fraction of possible edges present.</span> <span class="sd"> """</span> @@ -990,7 +990,7 @@ <span class="k">def</span> <span class="nf">degree_correlation</span><span class="p">(</span><span class="n">creation_sequence</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Return the degree-degree correlation over all edges.</span> <span class="sd"> """</span> <span class="n">cs</span> <span class="o">=</span> <span class="n">creation_sequence</span> @@ -1024,7 +1024,7 @@ <span class="k">def</span> <span class="nf">shortest_path</span><span class="p">(</span><span class="n">creation_sequence</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Find the shortest path between u and v in a</span> <span class="sd"> threshold graph G with the given creation_sequence.</span> @@ -1077,7 +1077,7 @@ <span class="k">def</span> <span class="nf">shortest_path_length</span><span class="p">(</span><span class="n">creation_sequence</span><span class="p">,</span> <span class="n">i</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Return the shortest path length from indicated node to</span> <span class="sd"> every other node for the threshold graph with the given</span> <span class="sd"> creation sequence.</span> @@ -1123,7 +1123,7 @@ <span class="k">def</span> <span class="nf">betweenness_sequence</span><span class="p">(</span><span class="n">creation_sequence</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Return betweenness for the threshold graph with the given creation</span> <span class="sd"> sequence. The result is unscaled. To scale the values</span> <span class="sd"> to the iterval [0,1] divide by (n-1)*(n-2).</span> @@ -1163,7 +1163,7 @@ <span class="k">def</span> <span class="nf">eigenvectors</span><span class="p">(</span><span class="n">creation_sequence</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Return a 2-tuple of Laplacian eigenvalues and eigenvectors</span> <span class="sd"> for the threshold network with creation_sequence.</span> <span class="sd"> The first value is a list of eigenvalues.</span> @@ -1221,7 +1221,7 @@ <span class="k">def</span> <span class="nf">spectral_projection</span><span class="p">(</span><span class="n">u</span><span class="p">,</span> <span class="n">eigenpairs</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the coefficients of each eigenvector</span> <span class="sd"> in a projection of the vector u onto the normalized</span> <span class="sd"> eigenvectors which are contained in eigenpairs.</span> @@ -1242,7 +1242,7 @@ <span class="k">def</span> <span class="nf">eigenvalues</span><span class="p">(</span><span class="n">creation_sequence</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Return sequence of eigenvalues of the Laplacian of the threshold</span> <span class="sd"> graph for the given creation_sequence.</span> @@ -1285,7 +1285,7 @@ <span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_threshold_sequence</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Create a random threshold sequence of size n.</span> <span class="sd"> A creation sequence is built by randomly choosing d's with</span> <span class="sd"> probabiliy p and i's with probability 1-p.</span> @@ -1319,7 +1319,7 @@ <span class="c1"># be (or be called from) a single routine with a more descriptive name</span> <span class="c1"># and a keyword parameter?</span> <span class="k">def</span> <span class="nf">right_d_threshold_sequence</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Create a skewed threshold graph with a given number</span> <span class="sd"> of vertices (n) and a given number of edges (m).</span> @@ -1353,7 +1353,7 @@ <span class="k">def</span> <span class="nf">left_d_threshold_sequence</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Create a skewed threshold graph with a given number</span> <span class="sd"> of vertices (n) and a given number of edges (m).</span> @@ -1389,7 +1389,7 @@ <span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">swap_d</span><span class="p">(</span><span class="n">cs</span><span class="p">,</span> <span class="n">p_split</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">p_combine</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Perform a "swap" operation on a threshold sequence.</span> <span class="sd"> The swap preserves the number of nodes and edges</span> @@ -1486,7 +1486,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/tournament.html b/_modules/networkx/algorithms/tournament.html index 8515dc62..101e895c 100644 --- a/_modules/networkx/algorithms/tournament.html +++ b/_modules/networkx/algorithms/tournament.html @@ -498,7 +498,7 @@ <span class="k">def</span> <span class="nf">index_satisfying</span><span class="p">(</span><span class="n">iterable</span><span class="p">,</span> <span class="n">condition</span><span class="p">):</span> - <span class="sd">"""Returns the index of the first element in `iterable` that</span> +<span class="w"> </span><span class="sd">"""Returns the index of the first element in `iterable` that</span> <span class="sd"> satisfies the given condition.</span> <span class="sd"> If no such element is found (that is, when the iterable is</span> @@ -528,7 +528,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_tournament</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns True if and only if `G` is a tournament.</span> +<span class="w"> </span><span class="sd">"""Returns True if and only if `G` is a tournament.</span> <span class="sd"> A tournament is a directed graph, with neither self-loops nor</span> <span class="sd"> multi-edges, in which there is exactly one directed edge joining</span> @@ -567,7 +567,7 @@ <div class="viewcode-block" id="hamiltonian_path"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.tournament.hamiltonian_path.html#networkx.algorithms.tournament.hamiltonian_path">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">hamiltonian_path</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns a Hamiltonian path in the given tournament graph.</span> +<span class="w"> </span><span class="sd">"""Returns a Hamiltonian path in the given tournament graph.</span> <span class="sd"> Each tournament has a Hamiltonian path. If furthermore, the</span> <span class="sd"> tournament is strongly connected, then the returned Hamiltonian path</span> @@ -612,7 +612,7 @@ <div class="viewcode-block" id="random_tournament"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.tournament.random_tournament.html#networkx.algorithms.tournament.random_tournament">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_tournament</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a random tournament graph on `n` nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a random tournament graph on `n` nodes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -647,7 +647,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">score_sequence</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the score sequence for the given tournament graph.</span> +<span class="w"> </span><span class="sd">"""Returns the score sequence for the given tournament graph.</span> <span class="sd"> The score sequence is the sorted list of the out-degrees of the</span> <span class="sd"> nodes of the graph.</span> @@ -677,7 +677,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">tournament_matrix</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the tournament matrix for the given tournament graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the tournament matrix for the given tournament graph.</span> <span class="sd"> This function requires SciPy.</span> @@ -719,7 +719,7 @@ <div class="viewcode-block" id="is_reachable"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.tournament.is_reachable.html#networkx.algorithms.tournament.is_reachable">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_reachable</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">t</span><span class="p">):</span> - <span class="sd">"""Decides whether there is a path from `s` to `t` in the</span> +<span class="w"> </span><span class="sd">"""Decides whether there is a path from `s` to `t` in the</span> <span class="sd"> tournament.</span> <span class="sd"> This function is more theoretically efficient than the reachability</span> @@ -773,7 +773,7 @@ <span class="sd"> """</span> <span class="k">def</span> <span class="nf">two_neighborhood</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Returns the set of nodes at distance at most two from `v`.</span> +<span class="w"> </span><span class="sd">"""Returns the set of nodes at distance at most two from `v`.</span> <span class="sd"> `G` must be a graph and `v` a node in that graph.</span> @@ -788,7 +788,7 @@ <span class="p">}</span> <span class="k">def</span> <span class="nf">is_closed</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="p">):</span> - <span class="sd">"""Decides whether the given set of nodes is closed.</span> +<span class="w"> </span><span class="sd">"""Decides whether the given set of nodes is closed.</span> <span class="sd"> A set *S* of nodes is *closed* if for each node *u* in the graph</span> <span class="sd"> not in *S* and for each node *v* in *S*, there is an edge from</span> @@ -806,7 +806,7 @@ <div class="viewcode-block" id="is_strongly_connected"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.tournament.is_strongly_connected.html#networkx.algorithms.tournament.is_strongly_connected">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_strongly_connected</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Decides whether the given tournament is strongly connected.</span> +<span class="w"> </span><span class="sd">"""Decides whether the given tournament is strongly connected.</span> <span class="sd"> This function is more theoretically efficient than the</span> <span class="sd"> :func:`~networkx.algorithms.components.is_strongly_connected`</span> @@ -906,7 +906,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/traversal/beamsearch.html b/_modules/networkx/algorithms/traversal/beamsearch.html index 63c1ef6f..e8c9dd3d 100644 --- a/_modules/networkx/algorithms/traversal/beamsearch.html +++ b/_modules/networkx/algorithms/traversal/beamsearch.html @@ -469,7 +469,7 @@ <div class="viewcode-block" id="bfs_beam_edges"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.traversal.beamsearch.bfs_beam_edges.html#networkx.algorithms.traversal.beamsearch.bfs_beam_edges">[docs]</a><span class="k">def</span> <span class="nf">bfs_beam_edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">value</span><span class="p">,</span> <span class="n">width</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Iterates over edges in a beam search.</span> +<span class="w"> </span><span class="sd">"""Iterates over edges in a beam search.</span> <span class="sd"> The beam search is a generalized breadth-first search in which only</span> <span class="sd"> the "best" *w* neighbors of the current node are enqueued, where *w*</span> @@ -539,7 +539,7 @@ <span class="n">width</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> <span class="k">def</span> <span class="nf">successors</span><span class="p">(</span><span class="n">v</span><span class="p">):</span> - <span class="sd">"""Returns a list of the best neighbors of a node.</span> +<span class="w"> </span><span class="sd">"""Returns a list of the best neighbors of a node.</span> <span class="sd"> `v` is a node in the graph `G`.</span> @@ -616,7 +616,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/traversal/breadth_first_search.html b/_modules/networkx/algorithms/traversal/breadth_first_search.html index 1d2283da..a89dc704 100644 --- a/_modules/networkx/algorithms/traversal/breadth_first_search.html +++ b/_modules/networkx/algorithms/traversal/breadth_first_search.html @@ -477,7 +477,7 @@ <span class="k">def</span> <span class="nf">generic_bfs_edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">neighbors</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">depth_limit</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">sort_neighbors</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Iterate over edges in a breadth-first search.</span> +<span class="w"> </span><span class="sd">"""Iterate over edges in a breadth-first search.</span> <span class="sd"> The breadth-first search begins at `source` and enqueues the</span> <span class="sd"> neighbors of newly visited nodes specified by the `neighbors`</span> @@ -553,7 +553,7 @@ <div class="viewcode-block" id="bfs_edges"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_edges.html#networkx.algorithms.traversal.breadth_first_search.bfs_edges">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">bfs_edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">reverse</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">depth_limit</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">sort_neighbors</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Iterate over edges in a breadth-first-search starting at source.</span> +<span class="w"> </span><span class="sd">"""Iterate over edges in a breadth-first-search starting at source.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -634,7 +634,7 @@ <div class="viewcode-block" id="bfs_tree"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_tree.html#networkx.algorithms.traversal.breadth_first_search.bfs_tree">[docs]</a><span class="k">def</span> <span class="nf">bfs_tree</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">reverse</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">depth_limit</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">sort_neighbors</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns an oriented tree constructed from of a breadth-first-search</span> +<span class="w"> </span><span class="sd">"""Returns an oriented tree constructed from of a breadth-first-search</span> <span class="sd"> starting at source.</span> <span class="sd"> Parameters</span> @@ -700,7 +700,7 @@ <div class="viewcode-block" id="bfs_predecessors"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_predecessors.html#networkx.algorithms.traversal.breadth_first_search.bfs_predecessors">[docs]</a><span class="k">def</span> <span class="nf">bfs_predecessors</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">depth_limit</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">sort_neighbors</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns an iterator of predecessors in breadth-first-search from source.</span> +<span class="w"> </span><span class="sd">"""Returns an iterator of predecessors in breadth-first-search from source.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -764,7 +764,7 @@ <div class="viewcode-block" id="bfs_successors"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_successors.html#networkx.algorithms.traversal.breadth_first_search.bfs_successors">[docs]</a><span class="k">def</span> <span class="nf">bfs_successors</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">depth_limit</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">sort_neighbors</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns an iterator of successors in breadth-first-search from source.</span> +<span class="w"> </span><span class="sd">"""Returns an iterator of successors in breadth-first-search from source.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -836,7 +836,7 @@ <div class="viewcode-block" id="bfs_layers"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_layers.html#networkx.algorithms.traversal.breadth_first_search.bfs_layers">[docs]</a><span class="k">def</span> <span class="nf">bfs_layers</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">sources</span><span class="p">):</span> - <span class="sd">"""Returns an iterator of all the layers in breadth-first search traversal.</span> +<span class="w"> </span><span class="sd">"""Returns an iterator of all the layers in breadth-first search traversal.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -887,7 +887,7 @@ <div class="viewcode-block" id="descendants_at_distance"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.descendants_at_distance.html#networkx.algorithms.traversal.breadth_first_search.descendants_at_distance">[docs]</a><span class="k">def</span> <span class="nf">descendants_at_distance</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="p">,</span> <span class="n">distance</span><span class="p">):</span> - <span class="sd">"""Returns all nodes at a fixed `distance` from `source` in `G`.</span> +<span class="w"> </span><span class="sd">"""Returns all nodes at a fixed `distance` from `source` in `G`.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -974,7 +974,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/traversal/depth_first_search.html b/_modules/networkx/algorithms/traversal/depth_first_search.html index ba8878df..ef9b18e7 100644 --- a/_modules/networkx/algorithms/traversal/depth_first_search.html +++ b/_modules/networkx/algorithms/traversal/depth_first_search.html @@ -478,7 +478,7 @@ <div class="viewcode-block" id="dfs_edges"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_edges.html#networkx.algorithms.traversal.depth_first_search.dfs_edges">[docs]</a><span class="k">def</span> <span class="nf">dfs_edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">depth_limit</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Iterate over edges in a depth-first-search (DFS).</span> +<span class="w"> </span><span class="sd">"""Iterate over edges in a depth-first-search (DFS).</span> <span class="sd"> Perform a depth-first-search over the nodes of `G` and yield</span> <span class="sd"> the edges in order. This may not generate all edges in `G`</span> @@ -559,7 +559,7 @@ <div class="viewcode-block" id="dfs_tree"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_tree.html#networkx.algorithms.traversal.depth_first_search.dfs_tree">[docs]</a><span class="k">def</span> <span class="nf">dfs_tree</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">depth_limit</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns oriented tree constructed from a depth-first-search from source.</span> +<span class="w"> </span><span class="sd">"""Returns oriented tree constructed from a depth-first-search from source.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -604,7 +604,7 @@ <div class="viewcode-block" id="dfs_predecessors"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_predecessors.html#networkx.algorithms.traversal.depth_first_search.dfs_predecessors">[docs]</a><span class="k">def</span> <span class="nf">dfs_predecessors</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">depth_limit</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns dictionary of predecessors in depth-first-search from source.</span> +<span class="w"> </span><span class="sd">"""Returns dictionary of predecessors in depth-first-search from source.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -654,7 +654,7 @@ <div class="viewcode-block" id="dfs_successors"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_successors.html#networkx.algorithms.traversal.depth_first_search.dfs_successors">[docs]</a><span class="k">def</span> <span class="nf">dfs_successors</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">depth_limit</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns dictionary of successors in depth-first-search from source.</span> +<span class="w"> </span><span class="sd">"""Returns dictionary of successors in depth-first-search from source.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -707,7 +707,7 @@ <div class="viewcode-block" id="dfs_postorder_nodes"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_postorder_nodes.html#networkx.algorithms.traversal.depth_first_search.dfs_postorder_nodes">[docs]</a><span class="k">def</span> <span class="nf">dfs_postorder_nodes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">depth_limit</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Generate nodes in a depth-first-search post-ordering starting at source.</span> +<span class="w"> </span><span class="sd">"""Generate nodes in a depth-first-search post-ordering starting at source.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -758,7 +758,7 @@ <div class="viewcode-block" id="dfs_preorder_nodes"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_preorder_nodes.html#networkx.algorithms.traversal.depth_first_search.dfs_preorder_nodes">[docs]</a><span class="k">def</span> <span class="nf">dfs_preorder_nodes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">depth_limit</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Generate nodes in a depth-first-search pre-ordering starting at source.</span> +<span class="w"> </span><span class="sd">"""Generate nodes in a depth-first-search pre-ordering starting at source.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -809,7 +809,7 @@ <div class="viewcode-block" id="dfs_labeled_edges"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_labeled_edges.html#networkx.algorithms.traversal.depth_first_search.dfs_labeled_edges">[docs]</a><span class="k">def</span> <span class="nf">dfs_labeled_edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">depth_limit</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Iterate over edges in a depth-first-search (DFS) labeled by type.</span> +<span class="w"> </span><span class="sd">"""Iterate over edges in a depth-first-search (DFS) labeled by type.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -960,7 +960,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/traversal/edgebfs.html b/_modules/networkx/algorithms/traversal/edgebfs.html index 3d50a559..5fdf851f 100644 --- a/_modules/networkx/algorithms/traversal/edgebfs.html +++ b/_modules/networkx/algorithms/traversal/edgebfs.html @@ -480,7 +480,7 @@ <div class="viewcode-block" id="edge_bfs"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.traversal.edgebfs.edge_bfs.html#networkx.algorithms.traversal.edgebfs.edge_bfs">[docs]</a><span class="k">def</span> <span class="nf">edge_bfs</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">orientation</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""A directed, breadth-first-search of edges in `G`, beginning at `source`.</span> +<span class="w"> </span><span class="sd">"""A directed, breadth-first-search of edges in `G`, beginning at `source`.</span> <span class="sd"> Yield the edges of G in a breadth-first-search order continuing until</span> <span class="sd"> all edges are generated.</span> @@ -688,7 +688,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/traversal/edgedfs.html b/_modules/networkx/algorithms/traversal/edgedfs.html index ccb9b575..a23c1ce6 100644 --- a/_modules/networkx/algorithms/traversal/edgedfs.html +++ b/_modules/networkx/algorithms/traversal/edgedfs.html @@ -478,7 +478,7 @@ <div class="viewcode-block" id="edge_dfs"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.traversal.edgedfs.edge_dfs.html#networkx.algorithms.traversal.edgedfs.edge_dfs">[docs]</a><span class="k">def</span> <span class="nf">edge_dfs</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">orientation</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""A directed, depth-first-search of edges in `G`, beginning at `source`.</span> +<span class="w"> </span><span class="sd">"""A directed, depth-first-search of edges in `G`, beginning at `source`.</span> <span class="sd"> Yield the edges of G in a depth-first-search order continuing until</span> <span class="sd"> all edges are generated.</span> @@ -686,7 +686,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/tree/branchings.html b/_modules/networkx/algorithms/tree/branchings.html index f7eb644d..4f521d08 100644 --- a/_modules/networkx/algorithms/tree/branchings.html +++ b/_modules/networkx/algorithms/tree/branchings.html @@ -536,7 +536,7 @@ <div class="viewcode-block" id="branching_weight"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.branchings.branching_weight.html#networkx.algorithms.tree.branchings.branching_weight">[docs]</a><span class="k">def</span> <span class="nf">branching_weight</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">attr</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the total weight of a branching.</span> <span class="sd"> You must access this function through the networkx.algorithms.tree module.</span> @@ -570,7 +570,7 @@ <div class="viewcode-block" id="greedy_branching"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.branchings.greedy_branching.html#networkx.algorithms.tree.branchings.greedy_branching">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="k">def</span> <span class="nf">greedy_branching</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">attr</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">kind</span><span class="o">=</span><span class="s2">"max"</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns a branching obtained through a greedy algorithm.</span> <span class="sd"> This algorithm is wrong, and cannot give a proper optimal branching.</span> @@ -649,7 +649,7 @@ <span class="k">class</span> <span class="nc">MultiDiGraph_EdgeKey</span><span class="p">(</span><span class="n">nx</span><span class="o">.</span><span class="n">MultiDiGraph</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> MultiDiGraph which assigns unique keys to every edge.</span> <span class="sd"> Adds a dictionary edge_index which maps edge keys to (u, v, data) tuples.</span> @@ -689,7 +689,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">remove_node</span><span class="p">(</span><span class="n">n</span><span class="p">)</span> <span class="k">def</span> <span class="nf">add_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u_for_edge</span><span class="p">,</span> <span class="n">v_for_edge</span><span class="p">,</span> <span class="n">key_for_edge</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Key is now required.</span> <span class="sd"> """</span> @@ -720,7 +720,7 @@ <span class="k">def</span> <span class="nf">get_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the edge keys of the unique path between u and v.</span> <span class="sd"> This is not a generic function. G must be a branching and an instance of</span> @@ -744,7 +744,7 @@ <div class="viewcode-block" id="Edmonds"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.branchings.Edmonds.html#networkx.algorithms.tree.branchings.Edmonds">[docs]</a><span class="k">class</span> <span class="nc">Edmonds</span><span class="p">:</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Edmonds algorithm [1]_ for finding optimal branchings and spanning</span> <span class="sd"> arborescences.</span> @@ -857,7 +857,7 @@ <span class="n">partition</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns a branching from G.</span> <span class="sd"> Parameters</span> @@ -903,7 +903,7 @@ <span class="n">G_pred</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">pred</span> <span class="k">def</span> <span class="nf">desired_edge</span><span class="p">(</span><span class="n">v</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Find the edge directed toward v with maximal weight.</span> <span class="sd"> If an edge partition exists in this graph, return the included edge</span> @@ -1081,7 +1081,7 @@ <span class="n">H</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">G_original</span><span class="o">.</span><span class="vm">__class__</span><span class="p">()</span> <span class="k">def</span> <span class="nf">is_root</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">edgekeys</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns True if `u` is a root node in G.</span> <span class="sd"> Node `u` will be a root node if its in-degree, restricted to the</span> @@ -1292,7 +1292,7 @@ <div class="viewcode-block" id="ArborescenceIterator"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.branchings.ArborescenceIterator.html#networkx.algorithms.tree.branchings.ArborescenceIterator">[docs]</a><span class="k">class</span> <span class="nc">ArborescenceIterator</span><span class="p">:</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Iterate over all spanning arborescences of a graph in either increasing or</span> <span class="sd"> decreasing cost.</span> @@ -1314,7 +1314,7 @@ <span class="nd">@dataclass</span><span class="p">(</span><span class="n">order</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="k">class</span> <span class="nc">Partition</span><span class="p">:</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> This dataclass represents a partition and stores a dict with the edge</span> <span class="sd"> data and the weight of the minimum spanning arborescence of the</span> <span class="sd"> partition dict.</span> @@ -1329,7 +1329,7 @@ <span class="p">)</span> <div class="viewcode-block" id="ArborescenceIterator.__init__"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.branchings.ArborescenceIterator.html#networkx.algorithms.tree.branchings.ArborescenceIterator.__init__">[docs]</a> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">minimum</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">init_partition</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Initialize the iterator</span> <span class="sd"> Parameters</span> @@ -1372,7 +1372,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">init_partition</span> <span class="o">=</span> <span class="kc">None</span></div> <span class="k">def</span> <span class="fm">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> <span class="sd"> ArborescenceIterator</span> @@ -1404,7 +1404,7 @@ <span class="k">return</span> <span class="bp">self</span> <span class="k">def</span> <span class="fm">__next__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> <span class="sd"> (multi)Graph</span> @@ -1429,7 +1429,7 @@ <span class="k">return</span> <span class="n">next_arborescence</span> <span class="k">def</span> <span class="nf">_partition</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">partition</span><span class="p">,</span> <span class="n">partition_arborescence</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Create new partitions based of the minimum spanning tree of the</span> <span class="sd"> current minimum partition.</span> @@ -1469,7 +1469,7 @@ <span class="n">p1</span><span class="o">.</span><span class="n">partition_dict</span> <span class="o">=</span> <span class="n">p2</span><span class="o">.</span><span class="n">partition_dict</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span> <span class="k">def</span> <span class="nf">_write_partition</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">partition</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Writes the desired partition into the graph to calculate the minimum</span> <span class="sd"> spanning tree. Also, if one incoming edge is included, mark all others</span> <span class="sd"> as excluded so that if that vertex is merged during Edmonds' algorithm</span> @@ -1503,7 +1503,7 @@ <span class="n">d</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">partition_key</span><span class="p">]</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">EdgePartition</span><span class="o">.</span><span class="n">EXCLUDED</span> <span class="k">def</span> <span class="nf">_clear_partition</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Removes partition data from the graph</span> <span class="sd"> """</span> <span class="k">for</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> @@ -1560,7 +1560,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/tree/coding.html b/_modules/networkx/algorithms/tree/coding.html index 2592c833..7201bd2b 100644 --- a/_modules/networkx/algorithms/tree/coding.html +++ b/_modules/networkx/algorithms/tree/coding.html @@ -487,7 +487,7 @@ <div class="viewcode-block" id="NotATree"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.coding.NotATree.html#networkx.algorithms.tree.coding.NotATree">[docs]</a><span class="k">class</span> <span class="nc">NotATree</span><span class="p">(</span><span class="n">nx</span><span class="o">.</span><span class="n">NetworkXException</span><span class="p">):</span> - <span class="sd">"""Raised when a function expects a tree (that is, a connected</span> +<span class="w"> </span><span class="sd">"""Raised when a function expects a tree (that is, a connected</span> <span class="sd"> undirected graph with no cycles) but gets a non-tree graph as input</span> <span class="sd"> instead.</span> @@ -496,7 +496,7 @@ <div class="viewcode-block" id="to_nested_tuple"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.coding.to_nested_tuple.html#networkx.algorithms.tree.coding.to_nested_tuple">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">to_nested_tuple</span><span class="p">(</span><span class="n">T</span><span class="p">,</span> <span class="n">root</span><span class="p">,</span> <span class="n">canonical_form</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns a nested tuple representation of the given tree.</span> +<span class="w"> </span><span class="sd">"""Returns a nested tuple representation of the given tree.</span> <span class="sd"> The nested tuple representation of a tree is defined</span> <span class="sd"> recursively. The tree with one node and no edges is represented by</span> @@ -562,7 +562,7 @@ <span class="sd"> """</span> <span class="k">def</span> <span class="nf">_make_tuple</span><span class="p">(</span><span class="n">T</span><span class="p">,</span> <span class="n">root</span><span class="p">,</span> <span class="n">_parent</span><span class="p">):</span> - <span class="sd">"""Recursively compute the nested tuple representation of the</span> +<span class="w"> </span><span class="sd">"""Recursively compute the nested tuple representation of the</span> <span class="sd"> given rooted tree.</span> <span class="sd"> ``_parent`` is the parent node of ``root`` in the supertree in</span> @@ -591,7 +591,7 @@ <div class="viewcode-block" id="from_nested_tuple"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.coding.from_nested_tuple.html#networkx.algorithms.tree.coding.from_nested_tuple">[docs]</a><span class="k">def</span> <span class="nf">from_nested_tuple</span><span class="p">(</span><span class="n">sequence</span><span class="p">,</span> <span class="n">sensible_relabeling</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns the rooted tree corresponding to the given nested tuple.</span> +<span class="w"> </span><span class="sd">"""Returns the rooted tree corresponding to the given nested tuple.</span> <span class="sd"> The nested tuple representation of a tree is defined</span> <span class="sd"> recursively. The tree with one node and no edges is represented by</span> @@ -641,7 +641,7 @@ <span class="sd"> """</span> <span class="k">def</span> <span class="nf">_make_tree</span><span class="p">(</span><span class="n">sequence</span><span class="p">):</span> - <span class="sd">"""Recursively creates a tree from the given sequence of nested</span> +<span class="w"> </span><span class="sd">"""Recursively creates a tree from the given sequence of nested</span> <span class="sd"> tuples.</span> <span class="sd"> This function employs the :func:`~networkx.tree.join` function</span> @@ -675,7 +675,7 @@ <div class="viewcode-block" id="to_prufer_sequence"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.coding.to_prufer_sequence.html#networkx.algorithms.tree.coding.to_prufer_sequence">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">to_prufer_sequence</span><span class="p">(</span><span class="n">T</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the Prüfer sequence of the given tree.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the Prüfer sequence of the given tree.</span> <span class="sd"> A *Prüfer sequence* is a list of *n* - 2 numbers between 0 and</span> <span class="sd"> *n* - 1, inclusive. The tree corresponding to a given Prüfer</span> @@ -775,7 +775,7 @@ <div class="viewcode-block" id="from_prufer_sequence"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.coding.from_prufer_sequence.html#networkx.algorithms.tree.coding.from_prufer_sequence">[docs]</a><span class="k">def</span> <span class="nf">from_prufer_sequence</span><span class="p">(</span><span class="n">sequence</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the tree corresponding to the given Prüfer sequence.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the tree corresponding to the given Prüfer sequence.</span> <span class="sd"> A *Prüfer sequence* is a list of *n* - 2 numbers between 0 and</span> <span class="sd"> *n* - 1, inclusive. The tree corresponding to a given Prüfer</span> @@ -910,7 +910,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/tree/decomposition.html b/_modules/networkx/algorithms/tree/decomposition.html index 9b894257..3015dd5e 100644 --- a/_modules/networkx/algorithms/tree/decomposition.html +++ b/_modules/networkx/algorithms/tree/decomposition.html @@ -474,7 +474,7 @@ <div class="viewcode-block" id="junction_tree"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.decomposition.junction_tree.html#networkx.algorithms.tree.decomposition.junction_tree">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">junction_tree</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a junction tree of a given graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a junction tree of a given graph.</span> <span class="sd"> A junction tree (or clique tree) is constructed from a (un)directed graph G.</span> <span class="sd"> The tree is constructed based on a moralized and triangulated version of G.</span> @@ -599,7 +599,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/tree/mst.html b/_modules/networkx/algorithms/tree/mst.html index 12764cf6..2ac894cf 100644 --- a/_modules/networkx/algorithms/tree/mst.html +++ b/_modules/networkx/algorithms/tree/mst.html @@ -489,7 +489,7 @@ <span class="k">class</span> <span class="nc">EdgePartition</span><span class="p">(</span><span class="n">Enum</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> An enum to store the state of an edge partition. The enum is written to the</span> <span class="sd"> edges of a graph before being pasted to `kruskal_mst_edges`. Options are:</span> @@ -507,7 +507,7 @@ <span class="k">def</span> <span class="nf">boruvka_mst_edges</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">minimum</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">keys</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">ignore_nan</span><span class="o">=</span><span class="kc">False</span> <span class="p">):</span> - <span class="sd">"""Iterate over edges of a Borůvka's algorithm min/max spanning tree.</span> +<span class="w"> </span><span class="sd">"""Iterate over edges of a Borůvka's algorithm min/max spanning tree.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -541,7 +541,7 @@ <span class="n">forest</span> <span class="o">=</span> <span class="n">UnionFind</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> <span class="k">def</span> <span class="nf">best_edge</span><span class="p">(</span><span class="n">component</span><span class="p">):</span> - <span class="sd">"""Returns the optimum (minimum or maximum) edge on the edge</span> +<span class="w"> </span><span class="sd">"""Returns the optimum (minimum or maximum) edge on the edge</span> <span class="sd"> boundary of the given set of nodes.</span> <span class="sd"> A return value of ``None`` indicates an empty boundary.</span> @@ -603,7 +603,7 @@ <span class="k">def</span> <span class="nf">kruskal_mst_edges</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">minimum</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">keys</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">ignore_nan</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">partition</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Iterate over edge of a Kruskal's algorithm min/max spanning tree.</span> <span class="sd"> Parameters</span> @@ -649,7 +649,7 @@ <span class="k">else</span><span class="p">:</span> <span class="n">edges</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Sort the edges of the graph with respect to the partition data. </span> <span class="sd"> Edges are returned in the following order:</span> @@ -711,7 +711,7 @@ <span class="k">def</span> <span class="nf">prim_mst_edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">minimum</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">keys</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">ignore_nan</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Iterate over edges of Prim's algorithm min/max spanning tree.</span> +<span class="w"> </span><span class="sd">"""Iterate over edges of Prim's algorithm min/max spanning tree.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -758,7 +758,7 @@ <span class="k">if</span> <span class="n">isnan</span><span class="p">(</span><span class="n">wt</span><span class="p">):</span> <span class="k">if</span> <span class="n">ignore_nan</span><span class="p">:</span> <span class="k">continue</span> - <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"NaN found as an edge weight. Edge </span><span class="si">{</span><span class="p">(</span><span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">d</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span> + <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"NaN found as an edge weight. Edge </span><span class="si">{</span><span class="p">(</span><span class="n">u</span><span class="p">,</span><span class="w"> </span><span class="n">v</span><span class="p">,</span><span class="w"> </span><span class="n">k</span><span class="p">,</span><span class="w"> </span><span class="n">d</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span> <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span> <span class="n">push</span><span class="p">(</span><span class="n">frontier</span><span class="p">,</span> <span class="p">(</span><span class="n">wt</span><span class="p">,</span> <span class="nb">next</span><span class="p">(</span><span class="n">c</span><span class="p">),</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">d</span><span class="p">))</span> <span class="k">else</span><span class="p">:</span> @@ -767,7 +767,7 @@ <span class="k">if</span> <span class="n">isnan</span><span class="p">(</span><span class="n">wt</span><span class="p">):</span> <span class="k">if</span> <span class="n">ignore_nan</span><span class="p">:</span> <span class="k">continue</span> - <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"NaN found as an edge weight. Edge </span><span class="si">{</span><span class="p">(</span><span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">d</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span> + <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"NaN found as an edge weight. Edge </span><span class="si">{</span><span class="p">(</span><span class="n">u</span><span class="p">,</span><span class="w"> </span><span class="n">v</span><span class="p">,</span><span class="w"> </span><span class="n">d</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span> <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span> <span class="n">push</span><span class="p">(</span><span class="n">frontier</span><span class="p">,</span> <span class="p">(</span><span class="n">wt</span><span class="p">,</span> <span class="nb">next</span><span class="p">(</span><span class="n">c</span><span class="p">),</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">d</span><span class="p">))</span> <span class="k">while</span> <span class="n">nodes</span> <span class="ow">and</span> <span class="n">frontier</span><span class="p">:</span> @@ -818,7 +818,7 @@ <span class="k">def</span> <span class="nf">minimum_spanning_edges</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">algorithm</span><span class="o">=</span><span class="s2">"kruskal"</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">keys</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">ignore_nan</span><span class="o">=</span><span class="kc">False</span> <span class="p">):</span> - <span class="sd">"""Generate edges in a minimum spanning forest of an undirected</span> +<span class="w"> </span><span class="sd">"""Generate edges in a minimum spanning forest of an undirected</span> <span class="sd"> weighted graph.</span> <span class="sd"> A minimum spanning tree is a subgraph of the graph (a tree)</span> @@ -912,7 +912,7 @@ <span class="k">def</span> <span class="nf">maximum_spanning_edges</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">algorithm</span><span class="o">=</span><span class="s2">"kruskal"</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">keys</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">ignore_nan</span><span class="o">=</span><span class="kc">False</span> <span class="p">):</span> - <span class="sd">"""Generate edges in a maximum spanning forest of an undirected</span> +<span class="w"> </span><span class="sd">"""Generate edges in a maximum spanning forest of an undirected</span> <span class="sd"> weighted graph.</span> <span class="sd"> A maximum spanning tree is a subgraph of the graph (a tree)</span> @@ -1002,7 +1002,7 @@ <div class="viewcode-block" id="minimum_spanning_tree"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.mst.minimum_spanning_tree.html#networkx.algorithms.tree.mst.minimum_spanning_tree">[docs]</a><span class="k">def</span> <span class="nf">minimum_spanning_tree</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">algorithm</span><span class="o">=</span><span class="s2">"kruskal"</span><span class="p">,</span> <span class="n">ignore_nan</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns a minimum spanning tree or forest on an undirected graph `G`.</span> +<span class="w"> </span><span class="sd">"""Returns a minimum spanning tree or forest on an undirected graph `G`.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1063,7 +1063,7 @@ <span class="k">def</span> <span class="nf">partition_spanning_tree</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">minimum</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">partition</span><span class="o">=</span><span class="s2">"partition"</span><span class="p">,</span> <span class="n">ignore_nan</span><span class="o">=</span><span class="kc">False</span> <span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Find a spanning tree while respecting a partition of edges.</span> <span class="sd"> Edges can be flagged as either `INLCUDED` which are required to be in the</span> @@ -1124,7 +1124,7 @@ <div class="viewcode-block" id="maximum_spanning_tree"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.mst.maximum_spanning_tree.html#networkx.algorithms.tree.mst.maximum_spanning_tree">[docs]</a><span class="k">def</span> <span class="nf">maximum_spanning_tree</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">algorithm</span><span class="o">=</span><span class="s2">"kruskal"</span><span class="p">,</span> <span class="n">ignore_nan</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns a maximum spanning tree or forest on an undirected graph `G`.</span> +<span class="w"> </span><span class="sd">"""Returns a maximum spanning tree or forest on an undirected graph `G`.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1187,7 +1187,7 @@ <div class="viewcode-block" id="random_spanning_tree"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.mst.random_spanning_tree.html#networkx.algorithms.tree.mst.random_spanning_tree">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_spanning_tree</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">multiplicative</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Sample a random spanning tree using the edges weights of `G`.</span> <span class="sd"> This function supports two different methods for determining the</span> @@ -1231,7 +1231,7 @@ <span class="sd"> """</span> <span class="k">def</span> <span class="nf">find_node</span><span class="p">(</span><span class="n">merged_nodes</span><span class="p">,</span> <span class="n">node</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> We can think of clusters of contracted nodes as having one</span> <span class="sd"> representative in the graph. Each node which is not in merged_nodes</span> <span class="sd"> is still its own representative. Since a representative can be later</span> @@ -1263,7 +1263,7 @@ <span class="k">return</span> <span class="n">rep</span> <span class="k">def</span> <span class="nf">prepare_graph</span><span class="p">():</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> For the graph `G`, remove all edges not in the set `V` and then</span> <span class="sd"> contract all edges in the set `U`.</span> @@ -1306,7 +1306,7 @@ <span class="k">return</span> <span class="n">merged_nodes</span><span class="p">,</span> <span class="n">result</span> <span class="k">def</span> <span class="nf">spanning_tree_total_weight</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Find the sum of weights of the spanning trees of `G` using the</span> <span class="sd"> approioate `method`.</span> @@ -1408,7 +1408,7 @@ <div class="viewcode-block" id="SpanningTreeIterator"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.mst.SpanningTreeIterator.html#networkx.algorithms.tree.mst.SpanningTreeIterator">[docs]</a><span class="k">class</span> <span class="nc">SpanningTreeIterator</span><span class="p">:</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Iterate over all spanning trees of a graph in either increasing or</span> <span class="sd"> decreasing cost.</span> @@ -1429,7 +1429,7 @@ <span class="nd">@dataclass</span><span class="p">(</span><span class="n">order</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="k">class</span> <span class="nc">Partition</span><span class="p">:</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> This dataclass represents a partition and stores a dict with the edge</span> <span class="sd"> data and the weight of the minimum spanning tree of the partition dict.</span> <span class="sd"> """</span> @@ -1443,7 +1443,7 @@ <span class="p">)</span> <div class="viewcode-block" id="SpanningTreeIterator.__init__"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.mst.SpanningTreeIterator.html#networkx.algorithms.tree.mst.SpanningTreeIterator.__init__">[docs]</a> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">minimum</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">ignore_nan</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Initialize the iterator</span> <span class="sd"> Parameters</span> @@ -1472,7 +1472,7 @@ <span class="p">)</span></div> <span class="k">def</span> <span class="fm">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> <span class="sd"> SpanningTreeIterator</span> @@ -1491,7 +1491,7 @@ <span class="k">return</span> <span class="bp">self</span> <span class="k">def</span> <span class="fm">__next__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> <span class="sd"> (multi)Graph</span> @@ -1513,7 +1513,7 @@ <span class="k">return</span> <span class="n">next_tree</span> <span class="k">def</span> <span class="nf">_partition</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">partition</span><span class="p">,</span> <span class="n">partition_tree</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Create new partitions based of the minimum spanning tree of the</span> <span class="sd"> current minimum partition.</span> @@ -1550,7 +1550,7 @@ <span class="n">p1</span><span class="o">.</span><span class="n">partition_dict</span> <span class="o">=</span> <span class="n">p2</span><span class="o">.</span><span class="n">partition_dict</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span> <span class="k">def</span> <span class="nf">_write_partition</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">partition</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Writes the desired partition into the graph to calculate the minimum</span> <span class="sd"> spanning tree.</span> @@ -1567,7 +1567,7 @@ <span class="n">d</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">partition_key</span><span class="p">]</span> <span class="o">=</span> <span class="n">EdgePartition</span><span class="o">.</span><span class="n">OPEN</span> <span class="k">def</span> <span class="nf">_clear_partition</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Removes partition data from the graph</span> <span class="sd"> """</span> <span class="k">for</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> @@ -1624,7 +1624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/tree/operations.html b/_modules/networkx/algorithms/tree/operations.html index 7caf82cc..90520311 100644 --- a/_modules/networkx/algorithms/tree/operations.html +++ b/_modules/networkx/algorithms/tree/operations.html @@ -471,7 +471,7 @@ <div class="viewcode-block" id="join"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.operations.join.html#networkx.algorithms.tree.operations.join">[docs]</a><span class="k">def</span> <span class="nf">join</span><span class="p">(</span><span class="n">rooted_trees</span><span class="p">,</span> <span class="n">label_attribute</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a new rooted tree with a root node joined with the roots</span> +<span class="w"> </span><span class="sd">"""Returns a new rooted tree with a root node joined with the roots</span> <span class="sd"> of each of the given rooted trees.</span> <span class="sd"> Parameters</span> @@ -618,7 +618,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/tree/recognition.html b/_modules/networkx/algorithms/tree/recognition.html index 5a6885bc..9c10710b 100644 --- a/_modules/networkx/algorithms/tree/recognition.html +++ b/_modules/networkx/algorithms/tree/recognition.html @@ -543,7 +543,7 @@ <div class="viewcode-block" id="is_arborescence"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.recognition.is_arborescence.html#networkx.algorithms.tree.recognition.is_arborescence">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_arborescence</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns True if `G` is an arborescence.</span> <span class="sd"> An arborescence is a directed tree with maximum in-degree equal to 1.</span> @@ -582,7 +582,7 @@ <div class="viewcode-block" id="is_branching"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.recognition.is_branching.html#networkx.algorithms.tree.recognition.is_branching">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_branching</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns True if `G` is a branching.</span> <span class="sd"> A branching is a directed forest with maximum in-degree equal to 1.</span> @@ -620,7 +620,7 @@ <div class="viewcode-block" id="is_forest"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.recognition.is_forest.html#networkx.algorithms.tree.recognition.is_forest">[docs]</a><span class="k">def</span> <span class="nf">is_forest</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns True if `G` is a forest.</span> <span class="sd"> A forest is a graph with no undirected cycles.</span> @@ -676,7 +676,7 @@ <div class="viewcode-block" id="is_tree"><a class="viewcode-back" href="../../../../reference/algorithms/generated/networkx.algorithms.tree.recognition.is_tree.html#networkx.algorithms.tree.recognition.is_tree">[docs]</a><span class="k">def</span> <span class="nf">is_tree</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns True if `G` is a tree.</span> <span class="sd"> A tree is a connected graph with no undirected cycles.</span> @@ -781,7 +781,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/triads.html b/_modules/networkx/algorithms/triads.html index e9c9cef3..394588ed 100644 --- a/_modules/networkx/algorithms/triads.html +++ b/_modules/networkx/algorithms/triads.html @@ -580,7 +580,7 @@ <span class="k">def</span> <span class="nf">_tricode</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">w</span><span class="p">):</span> - <span class="sd">"""Returns the integer code of the given triad.</span> +<span class="w"> </span><span class="sd">"""Returns the integer code of the given triad.</span> <span class="sd"> This is some fancy magic that comes from Batagelj and Mrvar's paper. It</span> <span class="sd"> treats each edge joining a pair of `v`, `u`, and `w` as a bit in</span> @@ -593,7 +593,7 @@ <div class="viewcode-block" id="triadic_census"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.triads.triadic_census.html#networkx.algorithms.triads.triadic_census">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">triadic_census</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Determines the triadic census of a directed graph.</span> +<span class="w"> </span><span class="sd">"""Determines the triadic census of a directed graph.</span> <span class="sd"> The triadic census is a count of how many of the 16 possible types of</span> <span class="sd"> triads are present in a directed graph. If a list of nodes is passed, then</span> @@ -740,7 +740,7 @@ <div class="viewcode-block" id="is_triad"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.triads.is_triad.html#networkx.algorithms.triads.is_triad">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span><span class="p">()</span> <span class="k">def</span> <span class="nf">is_triad</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns True if the graph G is a triad, else False.</span> +<span class="w"> </span><span class="sd">"""Returns True if the graph G is a triad, else False.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -770,7 +770,7 @@ <div class="viewcode-block" id="all_triplets"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.triads.all_triplets.html#networkx.algorithms.triads.all_triplets">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">all_triplets</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns a generator of all possible sets of 3 nodes in a DiGraph.</span> +<span class="w"> </span><span class="sd">"""Returns a generator of all possible sets of 3 nodes in a DiGraph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -795,7 +795,7 @@ <div class="viewcode-block" id="all_triads"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.triads.all_triads.html#networkx.algorithms.triads.all_triads">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">all_triads</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""A generator of all possible triads in G.</span> +<span class="w"> </span><span class="sd">"""A generator of all possible triads in G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -825,7 +825,7 @@ <div class="viewcode-block" id="triads_by_type"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.triads.triads_by_type.html#networkx.algorithms.triads.triads_by_type">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">triads_by_type</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns a list of all triads for each triad type in a directed graph.</span> +<span class="w"> </span><span class="sd">"""Returns a list of all triads for each triad type in a directed graph.</span> <span class="sd"> There are exactly 16 different types of triads possible. Suppose 1, 2, 3 are three</span> <span class="sd"> nodes, they will be classified as a particular triad type if their connections</span> <span class="sd"> are as follows:</span> @@ -887,7 +887,7 @@ <div class="viewcode-block" id="triad_type"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.triads.triad_type.html#networkx.algorithms.triads.triad_type">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">triad_type</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the sociological triad type for a triad.</span> +<span class="w"> </span><span class="sd">"""Returns the sociological triad type for a triad.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -985,7 +985,7 @@ <div class="viewcode-block" id="random_triad"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.triads.random_triad.html#networkx.algorithms.triads.random_triad">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_triad</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a random triad from a directed graph.</span> +<span class="w"> </span><span class="sd">"""Returns a random triad from a directed graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1120,7 +1120,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/vitality.html b/_modules/networkx/algorithms/vitality.html index c0a1036e..789c9102 100644 --- a/_modules/networkx/algorithms/vitality.html +++ b/_modules/networkx/algorithms/vitality.html @@ -472,7 +472,7 @@ <div class="viewcode-block" id="closeness_vitality"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.vitality.closeness_vitality.html#networkx.algorithms.vitality.closeness_vitality">[docs]</a><span class="k">def</span> <span class="nf">closeness_vitality</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">node</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">wiener_index</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the closeness vitality for nodes in the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the closeness vitality for nodes in the graph.</span> <span class="sd"> The *closeness vitality* of a node, defined in Section 3.6.2 of [1],</span> <span class="sd"> is the change in the sum of distances between all node pairs when</span> @@ -587,7 +587,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/voronoi.html b/_modules/networkx/algorithms/voronoi.html index 1fcad711..d8cc0aa0 100644 --- a/_modules/networkx/algorithms/voronoi.html +++ b/_modules/networkx/algorithms/voronoi.html @@ -469,7 +469,7 @@ <div class="viewcode-block" id="voronoi_cells"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.voronoi.voronoi_cells.html#networkx.algorithms.voronoi.voronoi_cells">[docs]</a><span class="k">def</span> <span class="nf">voronoi_cells</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">center_nodes</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns the Voronoi cells centered at `center_nodes` with respect</span> +<span class="w"> </span><span class="sd">"""Returns the Voronoi cells centered at `center_nodes` with respect</span> <span class="sd"> to the shortest-path distance metric.</span> <span class="sd"> If *C* is a set of nodes in the graph and *c* is an element of *C*,</span> @@ -597,7 +597,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/algorithms/wiener.html b/_modules/networkx/algorithms/wiener.html index adc0a32f..ba5e24d3 100644 --- a/_modules/networkx/algorithms/wiener.html +++ b/_modules/networkx/algorithms/wiener.html @@ -476,7 +476,7 @@ <div class="viewcode-block" id="wiener_index"><a class="viewcode-back" href="../../../reference/algorithms/generated/networkx.algorithms.wiener.wiener_index.html#networkx.algorithms.wiener.wiener_index">[docs]</a><span class="k">def</span> <span class="nf">wiener_index</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the Wiener index of the given graph.</span> +<span class="w"> </span><span class="sd">"""Returns the Wiener index of the given graph.</span> <span class="sd"> The *Wiener index* of a graph is the sum of the shortest-path</span> <span class="sd"> distances between each pair of reachable nodes. For pairs of nodes</span> @@ -588,7 +588,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/classes/backends.html b/_modules/networkx/classes/backends.html index 49c8337b..1a00bf6f 100644 --- a/_modules/networkx/classes/backends.html +++ b/_modules/networkx/classes/backends.html @@ -532,7 +532,7 @@ <span class="k">class</span> <span class="nc">PluginInfo</span><span class="p">:</span> - <span class="sd">"""Lazily loaded entry_points plugin information"""</span> +<span class="w"> </span><span class="sd">"""Lazily loaded entry_points plugin information"""</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span> <span class="o">=</span> <span class="kc">None</span> @@ -572,7 +572,7 @@ <div class="viewcode-block" id="_dispatch"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.classes.backends._dispatch.html#networkx.classes.backends._dispatch">[docs]</a><span class="k">def</span> <span class="nf">_dispatch</span><span class="p">(</span><span class="n">func</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Dispatches to a backend algorithm</span> +<span class="w"> </span><span class="sd">"""Dispatches to a backend algorithm</span> <span class="sd"> when the first argument is a backend graph-like object.</span> <span class="sd"> """</span> <span class="c1"># Allow any of the following decorator forms:</span> @@ -610,7 +610,7 @@ <span class="k">def</span> <span class="nf">test_override_dispatch</span><span class="p">(</span><span class="n">func</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Auto-converts the first argument into the backend equivalent,</span> +<span class="w"> </span><span class="sd">"""Auto-converts the first argument into the backend equivalent,</span> <span class="sd"> causing the dispatching mechanism to trigger for every</span> <span class="sd"> decorated algorithm."""</span> <span class="k">if</span> <span class="n">func</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> @@ -678,7 +678,7 @@ <span class="k">def</span> <span class="nf">_mark_tests</span><span class="p">(</span><span class="n">items</span><span class="p">):</span> - <span class="sd">"""Allow backend to mark tests (skip or xfail) if they aren't able to correctly handle them"""</span> +<span class="w"> </span><span class="sd">"""Allow backend to mark tests (skip or xfail) if they aren't able to correctly handle them"""</span> <span class="k">if</span> <span class="n">os</span><span class="o">.</span><span class="n">environ</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"NETWORKX_GRAPH_CONVERT"</span><span class="p">):</span> <span class="n">plugin_name</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">environ</span><span class="p">[</span><span class="s2">"NETWORKX_GRAPH_CONVERT"</span><span class="p">]</span> <span class="n">backend</span> <span class="o">=</span> <span class="n">plugins</span><span class="p">[</span><span class="n">plugin_name</span><span class="p">]</span><span class="o">.</span><span class="n">load</span><span class="p">()</span> @@ -735,7 +735,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/classes/coreviews.html b/_modules/networkx/classes/coreviews.html index 99cf611f..35dd22d2 100644 --- a/_modules/networkx/classes/coreviews.html +++ b/_modules/networkx/classes/coreviews.html @@ -483,7 +483,7 @@ <div class="viewcode-block" id="AtlasView"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.classes.coreviews.AtlasView.html#networkx.classes.coreviews.AtlasView">[docs]</a><span class="k">class</span> <span class="nc">AtlasView</span><span class="p">(</span><span class="n">Mapping</span><span class="p">):</span> - <span class="sd">"""An AtlasView is a Read-only Mapping of Mappings.</span> +<span class="w"> </span><span class="sd">"""An AtlasView is a Read-only Mapping of Mappings.</span> <span class="sd"> It is a View into a dict-of-dict data structure.</span> <span class="sd"> The inner level of dict is read-write. But the</span> @@ -526,7 +526,7 @@ <div class="viewcode-block" id="AdjacencyView"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.classes.coreviews.AdjacencyView.html#networkx.classes.coreviews.AdjacencyView">[docs]</a><span class="k">class</span> <span class="nc">AdjacencyView</span><span class="p">(</span><span class="n">AtlasView</span><span class="p">):</span> - <span class="sd">"""An AdjacencyView is a Read-only Map of Maps of Maps.</span> +<span class="w"> </span><span class="sd">"""An AdjacencyView is a Read-only Map of Maps of Maps.</span> <span class="sd"> It is a View into a dict-of-dict-of-dict data structure.</span> <span class="sd"> The inner level of dict is read-write. But the</span> @@ -548,7 +548,7 @@ <div class="viewcode-block" id="MultiAdjacencyView"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.classes.coreviews.MultiAdjacencyView.html#networkx.classes.coreviews.MultiAdjacencyView">[docs]</a><span class="k">class</span> <span class="nc">MultiAdjacencyView</span><span class="p">(</span><span class="n">AdjacencyView</span><span class="p">):</span> - <span class="sd">"""An MultiAdjacencyView is a Read-only Map of Maps of Maps of Maps.</span> +<span class="w"> </span><span class="sd">"""An MultiAdjacencyView is a Read-only Map of Maps of Maps of Maps.</span> <span class="sd"> It is a View into a dict-of-dict-of-dict-of-dict data structure.</span> <span class="sd"> The inner level of dict is read-write. But the</span> @@ -570,7 +570,7 @@ <div class="viewcode-block" id="UnionAtlas"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.classes.coreviews.UnionAtlas.html#networkx.classes.coreviews.UnionAtlas">[docs]</a><span class="k">class</span> <span class="nc">UnionAtlas</span><span class="p">(</span><span class="n">Mapping</span><span class="p">):</span> - <span class="sd">"""A read-only union of two atlases (dict-of-dict).</span> +<span class="w"> </span><span class="sd">"""A read-only union of two atlases (dict-of-dict).</span> <span class="sd"> The two dict-of-dicts represent the inner dict of</span> <span class="sd"> an Adjacency: `G.succ[node]` and `G.pred[node]`.</span> @@ -625,7 +625,7 @@ <div class="viewcode-block" id="UnionAdjacency"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.classes.coreviews.UnionAdjacency.html#networkx.classes.coreviews.UnionAdjacency">[docs]</a><span class="k">class</span> <span class="nc">UnionAdjacency</span><span class="p">(</span><span class="n">Mapping</span><span class="p">):</span> - <span class="sd">"""A read-only union of dict Adjacencies as a Map of Maps of Maps.</span> +<span class="w"> </span><span class="sd">"""A read-only union of dict Adjacencies as a Map of Maps of Maps.</span> <span class="sd"> The two input dict-of-dict-of-dicts represent the union of</span> <span class="sd"> `G.succ` and `G.pred`. Return values are UnionAtlas</span> @@ -677,7 +677,7 @@ <div class="viewcode-block" id="UnionMultiInner"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.classes.coreviews.UnionMultiInner.html#networkx.classes.coreviews.UnionMultiInner">[docs]</a><span class="k">class</span> <span class="nc">UnionMultiInner</span><span class="p">(</span><span class="n">UnionAtlas</span><span class="p">):</span> - <span class="sd">"""A read-only union of two inner dicts of MultiAdjacencies.</span> +<span class="w"> </span><span class="sd">"""A read-only union of two inner dicts of MultiAdjacencies.</span> <span class="sd"> The two input dict-of-dict-of-dicts represent the union of</span> <span class="sd"> `G.succ[node]` and `G.pred[node]` for MultiDiGraphs.</span> @@ -708,7 +708,7 @@ <div class="viewcode-block" id="UnionMultiAdjacency"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.classes.coreviews.UnionMultiAdjacency.html#networkx.classes.coreviews.UnionMultiAdjacency">[docs]</a><span class="k">class</span> <span class="nc">UnionMultiAdjacency</span><span class="p">(</span><span class="n">UnionAdjacency</span><span class="p">):</span> - <span class="sd">"""A read-only union of two dict MultiAdjacencies.</span> +<span class="w"> </span><span class="sd">"""A read-only union of two dict MultiAdjacencies.</span> <span class="sd"> The two input dict-of-dict-of-dict-of-dicts represent the union of</span> <span class="sd"> `G.succ` and `G.pred` for MultiDiGraphs. Return values are UnionAdjacency.</span> @@ -879,7 +879,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/classes/digraph.html b/_modules/networkx/classes/digraph.html index 932102bc..58b34f4e 100644 --- a/_modules/networkx/classes/digraph.html +++ b/_modules/networkx/classes/digraph.html @@ -482,7 +482,7 @@ <span class="k">class</span> <span class="nc">_CachedPropertyResetterAdjAndSucc</span><span class="p">:</span> - <span class="sd">"""Data Descriptor class that syncs and resets cached properties adj and succ</span> +<span class="w"> </span><span class="sd">"""Data Descriptor class that syncs and resets cached properties adj and succ</span> <span class="sd"> The cached properties `adj` and `succ` are reset whenever `_adj` or `_succ`</span> <span class="sd"> are set to new objects. In addition, the attributes `_succ` and `_adj`</span> @@ -509,7 +509,7 @@ <span class="k">class</span> <span class="nc">_CachedPropertyResetterPred</span><span class="p">:</span> - <span class="sd">"""Data Descriptor class for _pred that resets ``pred`` cached_property when needed</span> +<span class="w"> </span><span class="sd">"""Data Descriptor class for _pred that resets ``pred`` cached_property when needed</span> <span class="sd"> This assumes that the ``cached_property`` ``G.pred`` should be reset whenever</span> <span class="sd"> ``G._pred`` is set to a new value.</span> @@ -531,7 +531,7 @@ <div class="viewcode-block" id="DiGraph"><a class="viewcode-back" href="../../../reference/classes/digraph.html#networkx.DiGraph">[docs]</a><span class="k">class</span> <span class="nc">DiGraph</span><span class="p">(</span><span class="n">Graph</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Base class for directed graphs.</span> <span class="sd"> A DiGraph stores nodes and edges with optional data, or attributes.</span> @@ -777,7 +777,7 @@ <span class="n">_pred</span> <span class="o">=</span> <span class="n">_CachedPropertyResetterPred</span><span class="p">()</span> <div class="viewcode-block" id="DiGraph.__init__"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.DiGraph.__init__.html#networkx.DiGraph.__init__">[docs]</a> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">incoming_graph_data</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Initialize a graph with edges, name, or graph attributes.</span> +<span class="w"> </span><span class="sd">"""Initialize a graph with edges, name, or graph attributes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -826,7 +826,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">adj</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Graph adjacency object holding the neighbors of each node.</span> +<span class="w"> </span><span class="sd">"""Graph adjacency object holding the neighbors of each node.</span> <span class="sd"> This object is a read-only dict-like structure with node keys</span> <span class="sd"> and neighbor-dict values. The neighbor-dict is keyed by neighbor</span> @@ -845,7 +845,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">succ</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Graph adjacency object holding the successors of each node.</span> +<span class="w"> </span><span class="sd">"""Graph adjacency object holding the successors of each node.</span> <span class="sd"> This object is a read-only dict-like structure with node keys</span> <span class="sd"> and neighbor-dict values. The neighbor-dict is keyed by neighbor</span> @@ -866,7 +866,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">pred</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Graph adjacency object holding the predecessors of each node.</span> +<span class="w"> </span><span class="sd">"""Graph adjacency object holding the predecessors of each node.</span> <span class="sd"> This object is a read-only dict-like structure with node keys</span> <span class="sd"> and neighbor-dict values. The neighbor-dict is keyed by neighbor</span> @@ -881,7 +881,7 @@ <span class="k">return</span> <span class="n">AdjacencyView</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_pred</span><span class="p">)</span> <div class="viewcode-block" id="DiGraph.add_node"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.DiGraph.add_node.html#networkx.DiGraph.add_node">[docs]</a> <span class="k">def</span> <span class="nf">add_node</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">node_for_adding</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Add a single node `node_for_adding` and update node attributes.</span> +<span class="w"> </span><span class="sd">"""Add a single node `node_for_adding` and update node attributes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -930,7 +930,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">_node</span><span class="p">[</span><span class="n">node_for_adding</span><span class="p">]</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">attr</span><span class="p">)</span></div> <div class="viewcode-block" id="DiGraph.add_nodes_from"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.DiGraph.add_nodes_from.html#networkx.DiGraph.add_nodes_from">[docs]</a> <span class="k">def</span> <span class="nf">add_nodes_from</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">nodes_for_adding</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Add multiple nodes.</span> +<span class="w"> </span><span class="sd">"""Add multiple nodes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1008,7 +1008,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">_node</span><span class="p">[</span><span class="n">n</span><span class="p">]</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">newdict</span><span class="p">)</span></div> <div class="viewcode-block" id="DiGraph.remove_node"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.DiGraph.remove_node.html#networkx.DiGraph.remove_node">[docs]</a> <span class="k">def</span> <span class="nf">remove_node</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span> - <span class="sd">"""Remove node n.</span> +<span class="w"> </span><span class="sd">"""Remove node n.</span> <span class="sd"> Removes the node n and all adjacent edges.</span> <span class="sd"> Attempting to remove a non-existent node will raise an exception.</span> @@ -1050,7 +1050,7 @@ <span class="k">del</span> <span class="bp">self</span><span class="o">.</span><span class="n">_pred</span><span class="p">[</span><span class="n">n</span><span class="p">]</span> <span class="c1"># remove node from pred</span></div> <div class="viewcode-block" id="DiGraph.remove_nodes_from"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.DiGraph.remove_nodes_from.html#networkx.DiGraph.remove_nodes_from">[docs]</a> <span class="k">def</span> <span class="nf">remove_nodes_from</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">nodes</span><span class="p">):</span> - <span class="sd">"""Remove multiple nodes.</span> +<span class="w"> </span><span class="sd">"""Remove multiple nodes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1104,7 +1104,7 @@ <span class="k">pass</span> <span class="c1"># silent failure on remove</span></div> <div class="viewcode-block" id="DiGraph.add_edge"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.DiGraph.add_edge.html#networkx.DiGraph.add_edge">[docs]</a> <span class="k">def</span> <span class="nf">add_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u_of_edge</span><span class="p">,</span> <span class="n">v_of_edge</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Add an edge between u and v.</span> +<span class="w"> </span><span class="sd">"""Add an edge between u and v.</span> <span class="sd"> The nodes u and v will be automatically added if they are</span> <span class="sd"> not already in the graph.</span> @@ -1174,7 +1174,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">_pred</span><span class="p">[</span><span class="n">v</span><span class="p">][</span><span class="n">u</span><span class="p">]</span> <span class="o">=</span> <span class="n">datadict</span></div> <div class="viewcode-block" id="DiGraph.add_edges_from"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.DiGraph.add_edges_from.html#networkx.DiGraph.add_edges_from">[docs]</a> <span class="k">def</span> <span class="nf">add_edges_from</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ebunch_to_add</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Add all the edges in ebunch_to_add.</span> +<span class="w"> </span><span class="sd">"""Add all the edges in ebunch_to_add.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1256,7 +1256,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">_pred</span><span class="p">[</span><span class="n">v</span><span class="p">][</span><span class="n">u</span><span class="p">]</span> <span class="o">=</span> <span class="n">datadict</span></div> <div class="viewcode-block" id="DiGraph.remove_edge"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.DiGraph.remove_edge.html#networkx.DiGraph.remove_edge">[docs]</a> <span class="k">def</span> <span class="nf">remove_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Remove the edge between u and v.</span> +<span class="w"> </span><span class="sd">"""Remove the edge between u and v.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1289,7 +1289,7 @@ <span class="k">raise</span> <span class="n">NetworkXError</span><span class="p">(</span><span class="sa">f</span><span class="s2">"The edge </span><span class="si">{</span><span class="n">u</span><span class="si">}</span><span class="s2">-</span><span class="si">{</span><span class="n">v</span><span class="si">}</span><span class="s2"> not in graph."</span><span class="p">)</span> <span class="kn">from</span> <span class="nn">err</span></div> <div class="viewcode-block" id="DiGraph.remove_edges_from"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.DiGraph.remove_edges_from.html#networkx.DiGraph.remove_edges_from">[docs]</a> <span class="k">def</span> <span class="nf">remove_edges_from</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ebunch</span><span class="p">):</span> - <span class="sd">"""Remove all edges specified in ebunch.</span> +<span class="w"> </span><span class="sd">"""Remove all edges specified in ebunch.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1321,21 +1321,21 @@ <span class="k">del</span> <span class="bp">self</span><span class="o">.</span><span class="n">_pred</span><span class="p">[</span><span class="n">v</span><span class="p">][</span><span class="n">u</span><span class="p">]</span></div> <span class="k">def</span> <span class="nf">has_successor</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Returns True if node u has successor v.</span> +<span class="w"> </span><span class="sd">"""Returns True if node u has successor v.</span> <span class="sd"> This is true if graph has the edge u->v.</span> <span class="sd"> """</span> <span class="k">return</span> <span class="n">u</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_succ</span> <span class="ow">and</span> <span class="n">v</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_succ</span><span class="p">[</span><span class="n">u</span><span class="p">]</span> <span class="k">def</span> <span class="nf">has_predecessor</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Returns True if node u has predecessor v.</span> +<span class="w"> </span><span class="sd">"""Returns True if node u has predecessor v.</span> <span class="sd"> This is true if graph has the edge u<-v.</span> <span class="sd"> """</span> <span class="k">return</span> <span class="n">u</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_pred</span> <span class="ow">and</span> <span class="n">v</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_pred</span><span class="p">[</span><span class="n">u</span><span class="p">]</span> <div class="viewcode-block" id="DiGraph.successors"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.DiGraph.successors.html#networkx.DiGraph.successors">[docs]</a> <span class="k">def</span> <span class="nf">successors</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span> - <span class="sd">"""Returns an iterator over successor nodes of n.</span> +<span class="w"> </span><span class="sd">"""Returns an iterator over successor nodes of n.</span> <span class="sd"> A successor of n is a node m such that there exists a directed</span> <span class="sd"> edge from n to m.</span> @@ -1367,7 +1367,7 @@ <span class="n">neighbors</span> <span class="o">=</span> <span class="n">successors</span> <div class="viewcode-block" id="DiGraph.predecessors"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.DiGraph.predecessors.html#networkx.DiGraph.predecessors">[docs]</a> <span class="k">def</span> <span class="nf">predecessors</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span> - <span class="sd">"""Returns an iterator over predecessor nodes of n.</span> +<span class="w"> </span><span class="sd">"""Returns an iterator over predecessor nodes of n.</span> <span class="sd"> A predecessor of n is a node m such that there exists a directed</span> <span class="sd"> edge from m to n.</span> @@ -1393,7 +1393,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">edges</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""An OutEdgeView of the DiGraph as G.edges or G.edges().</span> +<span class="w"> </span><span class="sd">"""An OutEdgeView of the DiGraph as G.edges or G.edges().</span> <span class="sd"> edges(self, nbunch=None, data=False, default=None)</span> @@ -1463,7 +1463,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">in_edges</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""A view of the in edges of the graph as G.in_edges or G.in_edges().</span> +<span class="w"> </span><span class="sd">"""A view of the in edges of the graph as G.in_edges or G.in_edges().</span> <span class="sd"> in_edges(self, nbunch=None, data=False, default=None):</span> @@ -1503,7 +1503,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">degree</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""A DegreeView for the Graph as G.degree or G.degree().</span> +<span class="w"> </span><span class="sd">"""A DegreeView for the Graph as G.degree or G.degree().</span> <span class="sd"> The node degree is the number of edges adjacent to the node.</span> <span class="sd"> The weighted node degree is the sum of the edge weights for</span> @@ -1547,7 +1547,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">in_degree</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""An InDegreeView for (node, in_degree) or in_degree for single node.</span> +<span class="w"> </span><span class="sd">"""An InDegreeView for (node, in_degree) or in_degree for single node.</span> <span class="sd"> The node in_degree is the number of edges pointing to the node.</span> <span class="sd"> The weighted node degree is the sum of the edge weights for</span> @@ -1594,7 +1594,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">out_degree</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""An OutDegreeView for (node, out_degree)</span> +<span class="w"> </span><span class="sd">"""An OutDegreeView for (node, out_degree)</span> <span class="sd"> The node out_degree is the number of edges pointing out of the node.</span> <span class="sd"> The weighted node degree is the sum of the edge weights for</span> @@ -1640,7 +1640,7 @@ <span class="k">return</span> <span class="n">OutDegreeView</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <div class="viewcode-block" id="DiGraph.clear"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.DiGraph.clear.html#networkx.DiGraph.clear">[docs]</a> <span class="k">def</span> <span class="nf">clear</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Remove all nodes and edges from the graph.</span> +<span class="w"> </span><span class="sd">"""Remove all nodes and edges from the graph.</span> <span class="sd"> This also removes the name, and all graph, node, and edge attributes.</span> @@ -1660,7 +1660,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">graph</span><span class="o">.</span><span class="n">clear</span><span class="p">()</span></div> <div class="viewcode-block" id="DiGraph.clear_edges"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.DiGraph.clear_edges.html#networkx.DiGraph.clear_edges">[docs]</a> <span class="k">def</span> <span class="nf">clear_edges</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Remove all edges from the graph without altering nodes.</span> +<span class="w"> </span><span class="sd">"""Remove all edges from the graph without altering nodes.</span> <span class="sd"> Examples</span> <span class="sd"> --------</span> @@ -1678,15 +1678,15 @@ <span class="n">successor_dict</span><span class="o">.</span><span class="n">clear</span><span class="p">()</span></div> <span class="k">def</span> <span class="nf">is_multigraph</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns True if graph is a multigraph, False otherwise."""</span> +<span class="w"> </span><span class="sd">"""Returns True if graph is a multigraph, False otherwise."""</span> <span class="k">return</span> <span class="kc">False</span> <span class="k">def</span> <span class="nf">is_directed</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns True if graph is directed, False otherwise."""</span> +<span class="w"> </span><span class="sd">"""Returns True if graph is directed, False otherwise."""</span> <span class="k">return</span> <span class="kc">True</span> <div class="viewcode-block" id="DiGraph.to_undirected"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.DiGraph.to_undirected.html#networkx.DiGraph.to_undirected">[docs]</a> <span class="k">def</span> <span class="nf">to_undirected</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">reciprocal</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">as_view</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns an undirected representation of the digraph.</span> +<span class="w"> </span><span class="sd">"""Returns an undirected representation of the digraph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1765,7 +1765,7 @@ <span class="k">return</span> <span class="n">G</span></div> <div class="viewcode-block" id="DiGraph.reverse"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.DiGraph.reverse.html#networkx.DiGraph.reverse">[docs]</a> <span class="k">def</span> <span class="nf">reverse</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Returns the reverse of the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the reverse of the graph.</span> <span class="sd"> The reverse is a graph with the same nodes and edges</span> <span class="sd"> but with the directions of the edges reversed.</span> @@ -1835,7 +1835,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/classes/filters.html b/_modules/networkx/classes/filters.html index 49431334..8c4bfc87 100644 --- a/_modules/networkx/classes/filters.html +++ b/_modules/networkx/classes/filters.html @@ -587,7 +587,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/classes/function.html b/_modules/networkx/classes/function.html index a61c946a..bec045a0 100644 --- a/_modules/networkx/classes/function.html +++ b/_modules/networkx/classes/function.html @@ -515,12 +515,12 @@ <div class="viewcode-block" id="nodes"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.nodes.html#networkx.classes.function.nodes">[docs]</a><span class="k">def</span> <span class="nf">nodes</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns an iterator over the graph nodes."""</span> +<span class="w"> </span><span class="sd">"""Returns an iterator over the graph nodes."""</span> <span class="k">return</span> <span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">()</span></div> <div class="viewcode-block" id="edges"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.edges.html#networkx.classes.function.edges">[docs]</a><span class="k">def</span> <span class="nf">edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nbunch</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns an edge view of edges incident to nodes in nbunch.</span> +<span class="w"> </span><span class="sd">"""Returns an edge view of edges incident to nodes in nbunch.</span> <span class="sd"> Return all edges if nbunch is unspecified or nbunch=None.</span> @@ -530,29 +530,29 @@ <div class="viewcode-block" id="degree"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.degree.html#networkx.classes.function.degree">[docs]</a><span class="k">def</span> <span class="nf">degree</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nbunch</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a degree view of single node or of nbunch of nodes.</span> +<span class="w"> </span><span class="sd">"""Returns a degree view of single node or of nbunch of nodes.</span> <span class="sd"> If nbunch is omitted, then return degrees of *all* nodes.</span> <span class="sd"> """</span> <span class="k">return</span> <span class="n">G</span><span class="o">.</span><span class="n">degree</span><span class="p">(</span><span class="n">nbunch</span><span class="p">,</span> <span class="n">weight</span><span class="p">)</span></div> <div class="viewcode-block" id="neighbors"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.neighbors.html#networkx.classes.function.neighbors">[docs]</a><span class="k">def</span> <span class="nf">neighbors</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span> - <span class="sd">"""Returns a list of nodes connected to node n."""</span> +<span class="w"> </span><span class="sd">"""Returns a list of nodes connected to node n."""</span> <span class="k">return</span> <span class="n">G</span><span class="o">.</span><span class="n">neighbors</span><span class="p">(</span><span class="n">n</span><span class="p">)</span></div> <div class="viewcode-block" id="number_of_nodes"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.number_of_nodes.html#networkx.classes.function.number_of_nodes">[docs]</a><span class="k">def</span> <span class="nf">number_of_nodes</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the number of nodes in the graph."""</span> +<span class="w"> </span><span class="sd">"""Returns the number of nodes in the graph."""</span> <span class="k">return</span> <span class="n">G</span><span class="o">.</span><span class="n">number_of_nodes</span><span class="p">()</span></div> <div class="viewcode-block" id="number_of_edges"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.number_of_edges.html#networkx.classes.function.number_of_edges">[docs]</a><span class="k">def</span> <span class="nf">number_of_edges</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the number of edges in the graph."""</span> +<span class="w"> </span><span class="sd">"""Returns the number of edges in the graph."""</span> <span class="k">return</span> <span class="n">G</span><span class="o">.</span><span class="n">number_of_edges</span><span class="p">()</span></div> <div class="viewcode-block" id="density"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.density.html#networkx.classes.function.density">[docs]</a><span class="k">def</span> <span class="nf">density</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the density of a graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the density of a graph.</span> <span class="sd"> The density for undirected graphs is</span> @@ -587,7 +587,7 @@ <div class="viewcode-block" id="degree_histogram"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.degree_histogram.html#networkx.classes.function.degree_histogram">[docs]</a><span class="k">def</span> <span class="nf">degree_histogram</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns a list of the frequency of each degree value.</span> +<span class="w"> </span><span class="sd">"""Returns a list of the frequency of each degree value.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -610,17 +610,17 @@ <div class="viewcode-block" id="is_directed"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.is_directed.html#networkx.classes.function.is_directed">[docs]</a><span class="k">def</span> <span class="nf">is_directed</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Return True if graph is directed."""</span> +<span class="w"> </span><span class="sd">"""Return True if graph is directed."""</span> <span class="k">return</span> <span class="n">G</span><span class="o">.</span><span class="n">is_directed</span><span class="p">()</span></div> <span class="k">def</span> <span class="nf">frozen</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> - <span class="sd">"""Dummy method for raising errors when trying to modify frozen graphs"""</span> +<span class="w"> </span><span class="sd">"""Dummy method for raising errors when trying to modify frozen graphs"""</span> <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="s2">"Frozen graph can't be modified"</span><span class="p">)</span> <div class="viewcode-block" id="freeze"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.freeze.html#networkx.classes.function.freeze">[docs]</a><span class="k">def</span> <span class="nf">freeze</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Modify graph to prevent further change by adding or removing</span> +<span class="w"> </span><span class="sd">"""Modify graph to prevent further change by adding or removing</span> <span class="sd"> nodes or edges.</span> <span class="sd"> Node and edge data can still be modified.</span> @@ -670,7 +670,7 @@ <div class="viewcode-block" id="is_frozen"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.is_frozen.html#networkx.classes.function.is_frozen">[docs]</a><span class="k">def</span> <span class="nf">is_frozen</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns True if graph is frozen.</span> +<span class="w"> </span><span class="sd">"""Returns True if graph is frozen.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -688,7 +688,7 @@ <div class="viewcode-block" id="add_star"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.add_star.html#networkx.classes.function.add_star">[docs]</a><span class="k">def</span> <span class="nf">add_star</span><span class="p">(</span><span class="n">G_to_add_to</span><span class="p">,</span> <span class="n">nodes_for_star</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Add a star to Graph G_to_add_to.</span> +<span class="w"> </span><span class="sd">"""Add a star to Graph G_to_add_to.</span> <span class="sd"> The first node in `nodes_for_star` is the middle of the star.</span> <span class="sd"> It is connected to all other nodes.</span> @@ -723,7 +723,7 @@ <div class="viewcode-block" id="add_path"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.add_path.html#networkx.classes.function.add_path">[docs]</a><span class="k">def</span> <span class="nf">add_path</span><span class="p">(</span><span class="n">G_to_add_to</span><span class="p">,</span> <span class="n">nodes_for_path</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Add a path to the Graph G_to_add_to.</span> +<span class="w"> </span><span class="sd">"""Add a path to the Graph G_to_add_to.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -755,7 +755,7 @@ <div class="viewcode-block" id="add_cycle"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.add_cycle.html#networkx.classes.function.add_cycle">[docs]</a><span class="k">def</span> <span class="nf">add_cycle</span><span class="p">(</span><span class="n">G_to_add_to</span><span class="p">,</span> <span class="n">nodes_for_cycle</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Add a cycle to the Graph G_to_add_to.</span> +<span class="w"> </span><span class="sd">"""Add a cycle to the Graph G_to_add_to.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -789,7 +789,7 @@ <div class="viewcode-block" id="subgraph"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.subgraph.html#networkx.classes.function.subgraph">[docs]</a><span class="k">def</span> <span class="nf">subgraph</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nbunch</span><span class="p">):</span> - <span class="sd">"""Returns the subgraph induced on nodes in nbunch.</span> +<span class="w"> </span><span class="sd">"""Returns the subgraph induced on nodes in nbunch.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -812,7 +812,7 @@ <div class="viewcode-block" id="induced_subgraph"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.induced_subgraph.html#networkx.classes.function.induced_subgraph">[docs]</a><span class="k">def</span> <span class="nf">induced_subgraph</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nbunch</span><span class="p">):</span> - <span class="sd">"""Returns a SubGraph view of `G` showing only nodes in nbunch.</span> +<span class="w"> </span><span class="sd">"""Returns a SubGraph view of `G` showing only nodes in nbunch.</span> <span class="sd"> The induced subgraph of a graph on a set of nodes N is the</span> <span class="sd"> graph with nodes N and edges from G which have both ends in N.</span> @@ -858,7 +858,7 @@ <div class="viewcode-block" id="edge_subgraph"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.edge_subgraph.html#networkx.classes.function.edge_subgraph">[docs]</a><span class="k">def</span> <span class="nf">edge_subgraph</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">edges</span><span class="p">):</span> - <span class="sd">"""Returns a view of the subgraph induced by the specified edges.</span> +<span class="w"> </span><span class="sd">"""Returns a view of the subgraph induced by the specified edges.</span> <span class="sd"> The induced subgraph contains each edge in `edges` and each</span> <span class="sd"> node incident to any of those edges.</span> @@ -917,7 +917,7 @@ <div class="viewcode-block" id="restricted_view"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.restricted_view.html#networkx.classes.function.restricted_view">[docs]</a><span class="k">def</span> <span class="nf">restricted_view</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">edges</span><span class="p">):</span> - <span class="sd">"""Returns a view of `G` with hidden nodes and edges.</span> +<span class="w"> </span><span class="sd">"""Returns a view of `G` with hidden nodes and edges.</span> <span class="sd"> The resulting subgraph filters out node `nodes` and edges `edges`.</span> <span class="sd"> Filtered out nodes also filter out any of their edges.</span> @@ -973,7 +973,7 @@ <div class="viewcode-block" id="to_directed"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.to_directed.html#networkx.classes.function.to_directed">[docs]</a><span class="k">def</span> <span class="nf">to_directed</span><span class="p">(</span><span class="n">graph</span><span class="p">):</span> - <span class="sd">"""Returns a directed view of the graph `graph`.</span> +<span class="w"> </span><span class="sd">"""Returns a directed view of the graph `graph`.</span> <span class="sd"> Identical to graph.to_directed(as_view=True)</span> <span class="sd"> Note that graph.to_directed defaults to `as_view=False`</span> @@ -983,7 +983,7 @@ <div class="viewcode-block" id="to_undirected"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.to_undirected.html#networkx.classes.function.to_undirected">[docs]</a><span class="k">def</span> <span class="nf">to_undirected</span><span class="p">(</span><span class="n">graph</span><span class="p">):</span> - <span class="sd">"""Returns an undirected view of the graph `graph`.</span> +<span class="w"> </span><span class="sd">"""Returns an undirected view of the graph `graph`.</span> <span class="sd"> Identical to graph.to_undirected(as_view=True)</span> <span class="sd"> Note that graph.to_undirected defaults to `as_view=False`</span> @@ -993,7 +993,7 @@ <div class="viewcode-block" id="create_empty_copy"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.create_empty_copy.html#networkx.classes.function.create_empty_copy">[docs]</a><span class="k">def</span> <span class="nf">create_empty_copy</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">with_data</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Returns a copy of the graph G with all of the edges removed.</span> +<span class="w"> </span><span class="sd">"""Returns a copy of the graph G with all of the edges removed.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1016,7 +1016,7 @@ <div class="viewcode-block" id="set_node_attributes"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.set_node_attributes.html#networkx.classes.function.set_node_attributes">[docs]</a><span class="k">def</span> <span class="nf">set_node_attributes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Sets node attributes from a given value or dictionary of values.</span> +<span class="w"> </span><span class="sd">"""Sets node attributes from a given value or dictionary of values.</span> <span class="sd"> .. Warning:: The call order of arguments `values` and `name`</span> <span class="sd"> switched between v1.x & v2.x.</span> @@ -1116,7 +1116,7 @@ <div class="viewcode-block" id="get_node_attributes"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.get_node_attributes.html#networkx.classes.function.get_node_attributes">[docs]</a><span class="k">def</span> <span class="nf">get_node_attributes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">name</span><span class="p">):</span> - <span class="sd">"""Get node attributes from graph</span> +<span class="w"> </span><span class="sd">"""Get node attributes from graph</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1141,7 +1141,7 @@ <div class="viewcode-block" id="set_edge_attributes"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.set_edge_attributes.html#networkx.classes.function.set_edge_attributes">[docs]</a><span class="k">def</span> <span class="nf">set_edge_attributes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Sets edge attributes from a given value or dictionary of values.</span> +<span class="w"> </span><span class="sd">"""Sets edge attributes from a given value or dictionary of values.</span> <span class="sd"> .. Warning:: The call order of arguments `values` and `name`</span> <span class="sd"> switched between v1.x & v2.x.</span> @@ -1278,7 +1278,7 @@ <div class="viewcode-block" id="get_edge_attributes"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.get_edge_attributes.html#networkx.classes.function.get_edge_attributes">[docs]</a><span class="k">def</span> <span class="nf">get_edge_attributes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">name</span><span class="p">):</span> - <span class="sd">"""Get edge attributes from graph</span> +<span class="w"> </span><span class="sd">"""Get edge attributes from graph</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1309,7 +1309,7 @@ <div class="viewcode-block" id="all_neighbors"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.all_neighbors.html#networkx.classes.function.all_neighbors">[docs]</a><span class="k">def</span> <span class="nf">all_neighbors</span><span class="p">(</span><span class="n">graph</span><span class="p">,</span> <span class="n">node</span><span class="p">):</span> - <span class="sd">"""Returns all of the neighbors of a node in the graph.</span> +<span class="w"> </span><span class="sd">"""Returns all of the neighbors of a node in the graph.</span> <span class="sd"> If the graph is directed returns predecessors as well as successors.</span> @@ -1334,7 +1334,7 @@ <div class="viewcode-block" id="non_neighbors"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.non_neighbors.html#networkx.classes.function.non_neighbors">[docs]</a><span class="k">def</span> <span class="nf">non_neighbors</span><span class="p">(</span><span class="n">graph</span><span class="p">,</span> <span class="n">node</span><span class="p">):</span> - <span class="sd">"""Returns the non-neighbors of the node in the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the non-neighbors of the node in the graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1354,7 +1354,7 @@ <div class="viewcode-block" id="non_edges"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.non_edges.html#networkx.classes.function.non_edges">[docs]</a><span class="k">def</span> <span class="nf">non_edges</span><span class="p">(</span><span class="n">graph</span><span class="p">):</span> - <span class="sd">"""Returns the non-existent edges in the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the non-existent edges in the graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1380,7 +1380,7 @@ <div class="viewcode-block" id="common_neighbors"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.common_neighbors.html#networkx.classes.function.common_neighbors">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">common_neighbors</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Returns the common neighbors of two nodes in a graph.</span> +<span class="w"> </span><span class="sd">"""Returns the common neighbors of two nodes in a graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1417,7 +1417,7 @@ <div class="viewcode-block" id="is_weighted"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.is_weighted.html#networkx.classes.function.is_weighted">[docs]</a><span class="k">def</span> <span class="nf">is_weighted</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">edge</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns True if `G` has weighted edges.</span> +<span class="w"> </span><span class="sd">"""Returns True if `G` has weighted edges.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1470,7 +1470,7 @@ <div class="viewcode-block" id="is_negatively_weighted"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.is_negatively_weighted.html#networkx.classes.function.is_negatively_weighted">[docs]</a><span class="k">def</span> <span class="nf">is_negatively_weighted</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">edge</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns True if `G` has negatively weighted edges.</span> +<span class="w"> </span><span class="sd">"""Returns True if `G` has negatively weighted edges.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1523,7 +1523,7 @@ <div class="viewcode-block" id="is_empty"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.is_empty.html#networkx.classes.function.is_empty">[docs]</a><span class="k">def</span> <span class="nf">is_empty</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns True if `G` has no edges.</span> +<span class="w"> </span><span class="sd">"""Returns True if `G` has no edges.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1546,7 +1546,7 @@ <div class="viewcode-block" id="nodes_with_selfloops"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.nodes_with_selfloops.html#networkx.classes.function.nodes_with_selfloops">[docs]</a><span class="k">def</span> <span class="nf">nodes_with_selfloops</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns an iterator over nodes with self loops.</span> +<span class="w"> </span><span class="sd">"""Returns an iterator over nodes with self loops.</span> <span class="sd"> A node with a self loop has an edge with both ends adjacent</span> <span class="sd"> to that node.</span> @@ -1573,7 +1573,7 @@ <div class="viewcode-block" id="selfloop_edges"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.selfloop_edges.html#networkx.classes.function.selfloop_edges">[docs]</a><span class="k">def</span> <span class="nf">selfloop_edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">keys</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns an iterator over selfloop edges.</span> +<span class="w"> </span><span class="sd">"""Returns an iterator over selfloop edges.</span> <span class="sd"> A selfloop edge has the same node at both ends.</span> @@ -1672,7 +1672,7 @@ <div class="viewcode-block" id="number_of_selfloops"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.number_of_selfloops.html#networkx.classes.function.number_of_selfloops">[docs]</a><span class="k">def</span> <span class="nf">number_of_selfloops</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the number of selfloop edges.</span> +<span class="w"> </span><span class="sd">"""Returns the number of selfloop edges.</span> <span class="sd"> A selfloop edge has the same node at both ends.</span> @@ -1697,7 +1697,7 @@ <div class="viewcode-block" id="is_path"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.is_path.html#networkx.classes.function.is_path">[docs]</a><span class="k">def</span> <span class="nf">is_path</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">path</span><span class="p">):</span> - <span class="sd">"""Returns whether or not the specified path exists.</span> +<span class="w"> </span><span class="sd">"""Returns whether or not the specified path exists.</span> <span class="sd"> For it to return True, every node on the path must exist and</span> <span class="sd"> each consecutive pair must be connected via one or more edges.</span> @@ -1723,7 +1723,7 @@ <div class="viewcode-block" id="path_weight"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.path_weight.html#networkx.classes.function.path_weight">[docs]</a><span class="k">def</span> <span class="nf">path_weight</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">path</span><span class="p">,</span> <span class="n">weight</span><span class="p">):</span> - <span class="sd">"""Returns total cost associated with specified path and weight</span> +<span class="w"> </span><span class="sd">"""Returns total cost associated with specified path and weight</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1809,7 +1809,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/classes/graph.html b/_modules/networkx/classes/graph.html index e58ec4ea..84a65957 100644 --- a/_modules/networkx/classes/graph.html +++ b/_modules/networkx/classes/graph.html @@ -483,7 +483,7 @@ <span class="k">class</span> <span class="nc">_CachedPropertyResetterAdj</span><span class="p">:</span> - <span class="sd">"""Data Descriptor class for _adj that resets ``adj`` cached_property when needed</span> +<span class="w"> </span><span class="sd">"""Data Descriptor class for _adj that resets ``adj`` cached_property when needed</span> <span class="sd"> This assumes that the ``cached_property`` ``G.adj`` should be reset whenever</span> <span class="sd"> ``G._adj`` is set to a new value.</span> @@ -505,7 +505,7 @@ <span class="k">class</span> <span class="nc">_CachedPropertyResetterNode</span><span class="p">:</span> - <span class="sd">"""Data Descriptor class for _node that resets ``nodes`` cached_property when needed</span> +<span class="w"> </span><span class="sd">"""Data Descriptor class for _node that resets ``nodes`` cached_property when needed</span> <span class="sd"> This assumes that the ``cached_property`` ``G.node`` should be reset whenever</span> <span class="sd"> ``G._node`` is set to a new value.</span> @@ -527,7 +527,7 @@ <div class="viewcode-block" id="Graph"><a class="viewcode-back" href="../../../reference/classes/graph.html#networkx.Graph">[docs]</a><span class="k">class</span> <span class="nc">Graph</span><span class="p">:</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Base class for undirected graphs.</span> <span class="sd"> A Graph stores nodes and edges with optional data, or attributes.</span> @@ -777,7 +777,7 @@ <span class="n">graph_attr_dict_factory</span> <span class="o">=</span> <span class="nb">dict</span> <span class="k">def</span> <span class="nf">to_directed_class</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns the class to use for empty directed copies.</span> +<span class="w"> </span><span class="sd">"""Returns the class to use for empty directed copies.</span> <span class="sd"> If you subclass the base classes, use this to designate</span> <span class="sd"> what directed class to use for `to_directed()` copies.</span> @@ -785,7 +785,7 @@ <span class="k">return</span> <span class="n">nx</span><span class="o">.</span><span class="n">DiGraph</span> <span class="k">def</span> <span class="nf">to_undirected_class</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns the class to use for empty undirected copies.</span> +<span class="w"> </span><span class="sd">"""Returns the class to use for empty undirected copies.</span> <span class="sd"> If you subclass the base classes, use this to designate</span> <span class="sd"> what directed class to use for `to_directed()` copies.</span> @@ -793,7 +793,7 @@ <span class="k">return</span> <span class="n">Graph</span> <div class="viewcode-block" id="Graph.__init__"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.__init__.html#networkx.Graph.__init__">[docs]</a> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">incoming_graph_data</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Initialize a graph with edges, name, or graph attributes.</span> +<span class="w"> </span><span class="sd">"""Initialize a graph with edges, name, or graph attributes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -836,7 +836,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">adj</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Graph adjacency object holding the neighbors of each node.</span> +<span class="w"> </span><span class="sd">"""Graph adjacency object holding the neighbors of each node.</span> <span class="sd"> This object is a read-only dict-like structure with node keys</span> <span class="sd"> and neighbor-dict values. The neighbor-dict is keyed by neighbor</span> @@ -855,7 +855,7 @@ <span class="nd">@property</span> <span class="k">def</span> <span class="nf">name</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""String identifier of the graph.</span> +<span class="w"> </span><span class="sd">"""String identifier of the graph.</span> <span class="sd"> This graph attribute appears in the attribute dict G.graph</span> <span class="sd"> keyed by the string `"name"`. as well as an attribute (technically</span> @@ -868,7 +868,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">graph</span><span class="p">[</span><span class="s2">"name"</span><span class="p">]</span> <span class="o">=</span> <span class="n">s</span> <span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns a short summary of the graph.</span> +<span class="w"> </span><span class="sd">"""Returns a short summary of the graph.</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> @@ -896,7 +896,7 @@ <span class="p">)</span> <div class="viewcode-block" id="Graph.__iter__"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.__iter__.html#networkx.Graph.__iter__">[docs]</a> <span class="k">def</span> <span class="fm">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Iterate over the nodes. Use: 'for n in G'.</span> +<span class="w"> </span><span class="sd">"""Iterate over the nodes. Use: 'for n in G'.</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> @@ -914,7 +914,7 @@ <span class="k">return</span> <span class="nb">iter</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_node</span><span class="p">)</span></div> <div class="viewcode-block" id="Graph.__contains__"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.__contains__.html#networkx.Graph.__contains__">[docs]</a> <span class="k">def</span> <span class="fm">__contains__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span> - <span class="sd">"""Returns True if n is a node, False otherwise. Use: 'n in G'.</span> +<span class="w"> </span><span class="sd">"""Returns True if n is a node, False otherwise. Use: 'n in G'.</span> <span class="sd"> Examples</span> <span class="sd"> --------</span> @@ -928,7 +928,7 @@ <span class="k">return</span> <span class="kc">False</span></div> <div class="viewcode-block" id="Graph.__len__"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.__len__.html#networkx.Graph.__len__">[docs]</a> <span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns the number of nodes in the graph. Use: 'len(G)'.</span> +<span class="w"> </span><span class="sd">"""Returns the number of nodes in the graph. Use: 'len(G)'.</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> @@ -950,7 +950,7 @@ <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_node</span><span class="p">)</span></div> <div class="viewcode-block" id="Graph.__getitem__"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.__getitem__.html#networkx.Graph.__getitem__">[docs]</a> <span class="k">def</span> <span class="fm">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span> - <span class="sd">"""Returns a dict of neighbors of node n. Use: 'G[n]'.</span> +<span class="w"> </span><span class="sd">"""Returns a dict of neighbors of node n. Use: 'G[n]'.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -976,7 +976,7 @@ <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">adj</span><span class="p">[</span><span class="n">n</span><span class="p">]</span></div> <div class="viewcode-block" id="Graph.add_node"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.add_node.html#networkx.Graph.add_node">[docs]</a> <span class="k">def</span> <span class="nf">add_node</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">node_for_adding</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Add a single node `node_for_adding` and update node attributes.</span> +<span class="w"> </span><span class="sd">"""Add a single node `node_for_adding` and update node attributes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1024,7 +1024,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">_node</span><span class="p">[</span><span class="n">node_for_adding</span><span class="p">]</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">attr</span><span class="p">)</span></div> <div class="viewcode-block" id="Graph.add_nodes_from"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.add_nodes_from.html#networkx.Graph.add_nodes_from">[docs]</a> <span class="k">def</span> <span class="nf">add_nodes_from</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">nodes_for_adding</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Add multiple nodes.</span> +<span class="w"> </span><span class="sd">"""Add multiple nodes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1101,7 +1101,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">_node</span><span class="p">[</span><span class="n">n</span><span class="p">]</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">newdict</span><span class="p">)</span></div> <div class="viewcode-block" id="Graph.remove_node"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.remove_node.html#networkx.Graph.remove_node">[docs]</a> <span class="k">def</span> <span class="nf">remove_node</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span> - <span class="sd">"""Remove node n.</span> +<span class="w"> </span><span class="sd">"""Remove node n.</span> <span class="sd"> Removes the node n and all adjacent edges.</span> <span class="sd"> Attempting to remove a non-existent node will raise an exception.</span> @@ -1141,7 +1141,7 @@ <span class="k">del</span> <span class="n">adj</span><span class="p">[</span><span class="n">n</span><span class="p">]</span> <span class="c1"># now remove node</span></div> <div class="viewcode-block" id="Graph.remove_nodes_from"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.remove_nodes_from.html#networkx.Graph.remove_nodes_from">[docs]</a> <span class="k">def</span> <span class="nf">remove_nodes_from</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">nodes</span><span class="p">):</span> - <span class="sd">"""Remove multiple nodes.</span> +<span class="w"> </span><span class="sd">"""Remove multiple nodes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1194,7 +1194,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">nodes</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""A NodeView of the Graph as G.nodes or G.nodes().</span> +<span class="w"> </span><span class="sd">"""A NodeView of the Graph as G.nodes or G.nodes().</span> <span class="sd"> Can be used as `G.nodes` for data lookup and for set-like operations.</span> <span class="sd"> Can also be used as `G.nodes(data='color', default=None)` to return a</span> @@ -1286,7 +1286,7 @@ <span class="k">return</span> <span class="n">NodeView</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <div class="viewcode-block" id="Graph.number_of_nodes"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.number_of_nodes.html#networkx.Graph.number_of_nodes">[docs]</a> <span class="k">def</span> <span class="nf">number_of_nodes</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns the number of nodes in the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the number of nodes in the graph.</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> @@ -1307,7 +1307,7 @@ <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_node</span><span class="p">)</span></div> <div class="viewcode-block" id="Graph.order"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.order.html#networkx.Graph.order">[docs]</a> <span class="k">def</span> <span class="nf">order</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns the number of nodes in the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the number of nodes in the graph.</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> @@ -1328,7 +1328,7 @@ <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_node</span><span class="p">)</span></div> <div class="viewcode-block" id="Graph.has_node"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.has_node.html#networkx.Graph.has_node">[docs]</a> <span class="k">def</span> <span class="nf">has_node</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span> - <span class="sd">"""Returns True if the graph contains the node n.</span> +<span class="w"> </span><span class="sd">"""Returns True if the graph contains the node n.</span> <span class="sd"> Identical to `n in G`</span> @@ -1354,7 +1354,7 @@ <span class="k">return</span> <span class="kc">False</span></div> <div class="viewcode-block" id="Graph.add_edge"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.add_edge.html#networkx.Graph.add_edge">[docs]</a> <span class="k">def</span> <span class="nf">add_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u_of_edge</span><span class="p">,</span> <span class="n">v_of_edge</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Add an edge between u and v.</span> +<span class="w"> </span><span class="sd">"""Add an edge between u and v.</span> <span class="sd"> The nodes u and v will be automatically added if they are</span> <span class="sd"> not already in the graph.</span> @@ -1422,7 +1422,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">_adj</span><span class="p">[</span><span class="n">v</span><span class="p">][</span><span class="n">u</span><span class="p">]</span> <span class="o">=</span> <span class="n">datadict</span></div> <div class="viewcode-block" id="Graph.add_edges_from"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.add_edges_from.html#networkx.Graph.add_edges_from">[docs]</a> <span class="k">def</span> <span class="nf">add_edges_from</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ebunch_to_add</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Add all the edges in ebunch_to_add.</span> +<span class="w"> </span><span class="sd">"""Add all the edges in ebunch_to_add.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1502,7 +1502,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">_adj</span><span class="p">[</span><span class="n">v</span><span class="p">][</span><span class="n">u</span><span class="p">]</span> <span class="o">=</span> <span class="n">datadict</span></div> <div class="viewcode-block" id="Graph.add_weighted_edges_from"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.add_weighted_edges_from.html#networkx.Graph.add_weighted_edges_from">[docs]</a> <span class="k">def</span> <span class="nf">add_weighted_edges_from</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ebunch_to_add</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Add weighted edges in `ebunch_to_add` with specified weight attr</span> +<span class="w"> </span><span class="sd">"""Add weighted edges in `ebunch_to_add` with specified weight attr</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1552,7 +1552,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">add_edges_from</span><span class="p">(((</span><span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="p">{</span><span class="n">weight</span><span class="p">:</span> <span class="n">d</span><span class="p">})</span> <span class="k">for</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">ebunch_to_add</span><span class="p">),</span> <span class="o">**</span><span class="n">attr</span><span class="p">)</span></div> <div class="viewcode-block" id="Graph.remove_edge"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.remove_edge.html#networkx.Graph.remove_edge">[docs]</a> <span class="k">def</span> <span class="nf">remove_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Remove the edge between u and v.</span> +<span class="w"> </span><span class="sd">"""Remove the edge between u and v.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1585,7 +1585,7 @@ <span class="k">raise</span> <span class="n">NetworkXError</span><span class="p">(</span><span class="sa">f</span><span class="s2">"The edge </span><span class="si">{</span><span class="n">u</span><span class="si">}</span><span class="s2">-</span><span class="si">{</span><span class="n">v</span><span class="si">}</span><span class="s2"> is not in the graph"</span><span class="p">)</span> <span class="kn">from</span> <span class="nn">err</span></div> <div class="viewcode-block" id="Graph.remove_edges_from"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.remove_edges_from.html#networkx.Graph.remove_edges_from">[docs]</a> <span class="k">def</span> <span class="nf">remove_edges_from</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ebunch</span><span class="p">):</span> - <span class="sd">"""Remove all edges specified in ebunch.</span> +<span class="w"> </span><span class="sd">"""Remove all edges specified in ebunch.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1619,7 +1619,7 @@ <span class="k">del</span> <span class="n">adj</span><span class="p">[</span><span class="n">v</span><span class="p">][</span><span class="n">u</span><span class="p">]</span></div> <div class="viewcode-block" id="Graph.update"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.update.html#networkx.Graph.update">[docs]</a> <span class="k">def</span> <span class="nf">update</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">edges</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Update the graph using nodes/edges/graphs as input.</span> +<span class="w"> </span><span class="sd">"""Update the graph using nodes/edges/graphs as input.</span> <span class="sd"> Like dict.update, this method takes a graph as input, adding the</span> <span class="sd"> graph's nodes and edges to this graph. It can also take two inputs:</span> @@ -1735,7 +1735,7 @@ <span class="k">raise</span> <span class="n">NetworkXError</span><span class="p">(</span><span class="s2">"update needs nodes or edges input"</span><span class="p">)</span></div> <div class="viewcode-block" id="Graph.has_edge"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.has_edge.html#networkx.Graph.has_edge">[docs]</a> <span class="k">def</span> <span class="nf">has_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Returns True if the edge (u, v) is in the graph.</span> +<span class="w"> </span><span class="sd">"""Returns True if the edge (u, v) is in the graph.</span> <span class="sd"> This is the same as `v in G[u]` without KeyError exceptions.</span> @@ -1776,7 +1776,7 @@ <span class="k">return</span> <span class="kc">False</span></div> <div class="viewcode-block" id="Graph.neighbors"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.neighbors.html#networkx.Graph.neighbors">[docs]</a> <span class="k">def</span> <span class="nf">neighbors</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span> - <span class="sd">"""Returns an iterator over all neighbors of node n.</span> +<span class="w"> </span><span class="sd">"""Returns an iterator over all neighbors of node n.</span> <span class="sd"> This is identical to `iter(G[n])`</span> @@ -1820,7 +1820,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">edges</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""An EdgeView of the Graph as G.edges or G.edges().</span> +<span class="w"> </span><span class="sd">"""An EdgeView of the Graph as G.edges or G.edges().</span> <span class="sd"> edges(self, nbunch=None, data=False, default=None)</span> @@ -1876,7 +1876,7 @@ <span class="k">return</span> <span class="n">EdgeView</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <div class="viewcode-block" id="Graph.get_edge_data"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.get_edge_data.html#networkx.Graph.get_edge_data">[docs]</a> <span class="k">def</span> <span class="nf">get_edge_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the attribute dictionary associated with edge (u, v).</span> +<span class="w"> </span><span class="sd">"""Returns the attribute dictionary associated with edge (u, v).</span> <span class="sd"> This is identical to `G[u][v]` except the default is returned</span> <span class="sd"> instead of an exception if the edge doesn't exist.</span> @@ -1922,7 +1922,7 @@ <span class="k">return</span> <span class="n">default</span></div> <div class="viewcode-block" id="Graph.adjacency"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.adjacency.html#networkx.Graph.adjacency">[docs]</a> <span class="k">def</span> <span class="nf">adjacency</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns an iterator over (node, adjacency dict) tuples for all nodes.</span> +<span class="w"> </span><span class="sd">"""Returns an iterator over (node, adjacency dict) tuples for all nodes.</span> <span class="sd"> For directed graphs, only outgoing neighbors/adjacencies are included.</span> @@ -1943,7 +1943,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">degree</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""A DegreeView for the Graph as G.degree or G.degree().</span> +<span class="w"> </span><span class="sd">"""A DegreeView for the Graph as G.degree or G.degree().</span> <span class="sd"> The node degree is the number of edges adjacent to the node.</span> <span class="sd"> The weighted node degree is the sum of the edge weights for</span> @@ -1980,7 +1980,7 @@ <span class="k">return</span> <span class="n">DegreeView</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <div class="viewcode-block" id="Graph.clear"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.clear.html#networkx.Graph.clear">[docs]</a> <span class="k">def</span> <span class="nf">clear</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Remove all nodes and edges from the graph.</span> +<span class="w"> </span><span class="sd">"""Remove all nodes and edges from the graph.</span> <span class="sd"> This also removes the name, and all graph, node, and edge attributes.</span> @@ -1999,7 +1999,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">graph</span><span class="o">.</span><span class="n">clear</span><span class="p">()</span></div> <div class="viewcode-block" id="Graph.clear_edges"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.clear_edges.html#networkx.Graph.clear_edges">[docs]</a> <span class="k">def</span> <span class="nf">clear_edges</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Remove all edges from the graph without altering nodes.</span> +<span class="w"> </span><span class="sd">"""Remove all edges from the graph without altering nodes.</span> <span class="sd"> Examples</span> <span class="sd"> --------</span> @@ -2014,15 +2014,15 @@ <span class="n">neighbours_dict</span><span class="o">.</span><span class="n">clear</span><span class="p">()</span></div> <span class="k">def</span> <span class="nf">is_multigraph</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns True if graph is a multigraph, False otherwise."""</span> +<span class="w"> </span><span class="sd">"""Returns True if graph is a multigraph, False otherwise."""</span> <span class="k">return</span> <span class="kc">False</span> <span class="k">def</span> <span class="nf">is_directed</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns True if graph is directed, False otherwise."""</span> +<span class="w"> </span><span class="sd">"""Returns True if graph is directed, False otherwise."""</span> <span class="k">return</span> <span class="kc">False</span> <div class="viewcode-block" id="Graph.copy"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.copy.html#networkx.Graph.copy">[docs]</a> <span class="k">def</span> <span class="nf">copy</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">as_view</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns a copy of the graph.</span> +<span class="w"> </span><span class="sd">"""Returns a copy of the graph.</span> <span class="sd"> The copy method by default returns an independent shallow copy</span> <span class="sd"> of the graph and attributes. That is, if an attribute is a</span> @@ -2111,7 +2111,7 @@ <span class="k">return</span> <span class="n">G</span></div> <div class="viewcode-block" id="Graph.to_directed"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.to_directed.html#networkx.Graph.to_directed">[docs]</a> <span class="k">def</span> <span class="nf">to_directed</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">as_view</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns a directed representation of the graph.</span> +<span class="w"> </span><span class="sd">"""Returns a directed representation of the graph.</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> @@ -2167,7 +2167,7 @@ <span class="k">return</span> <span class="n">G</span></div> <div class="viewcode-block" id="Graph.to_undirected"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.to_undirected.html#networkx.Graph.to_undirected">[docs]</a> <span class="k">def</span> <span class="nf">to_undirected</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">as_view</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns an undirected copy of the graph.</span> +<span class="w"> </span><span class="sd">"""Returns an undirected copy of the graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -2224,7 +2224,7 @@ <span class="k">return</span> <span class="n">G</span></div> <div class="viewcode-block" id="Graph.subgraph"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.subgraph.html#networkx.Graph.subgraph">[docs]</a> <span class="k">def</span> <span class="nf">subgraph</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">nodes</span><span class="p">):</span> - <span class="sd">"""Returns a SubGraph view of the subgraph induced on `nodes`.</span> +<span class="w"> </span><span class="sd">"""Returns a SubGraph view of the subgraph induced on `nodes`.</span> <span class="sd"> The induced subgraph of the graph contains the nodes in `nodes`</span> <span class="sd"> and the edges between those nodes.</span> @@ -2288,7 +2288,7 @@ <span class="k">return</span> <span class="n">subgraph</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">induced_nodes</span><span class="p">)</span></div> <div class="viewcode-block" id="Graph.edge_subgraph"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.edge_subgraph.html#networkx.Graph.edge_subgraph">[docs]</a> <span class="k">def</span> <span class="nf">edge_subgraph</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">edges</span><span class="p">):</span> - <span class="sd">"""Returns the subgraph induced by the specified edges.</span> +<span class="w"> </span><span class="sd">"""Returns the subgraph induced by the specified edges.</span> <span class="sd"> The induced subgraph contains each edge in `edges` and each</span> <span class="sd"> node incident to any one of those edges.</span> @@ -2328,7 +2328,7 @@ <span class="k">return</span> <span class="n">nx</span><span class="o">.</span><span class="n">edge_subgraph</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">edges</span><span class="p">)</span></div> <div class="viewcode-block" id="Graph.size"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.size.html#networkx.Graph.size">[docs]</a> <span class="k">def</span> <span class="nf">size</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the number of edges or total of all edge weights.</span> +<span class="w"> </span><span class="sd">"""Returns the number of edges or total of all edge weights.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -2371,7 +2371,7 @@ <span class="k">return</span> <span class="n">s</span> <span class="o">//</span> <span class="mi">2</span> <span class="k">if</span> <span class="n">weight</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">else</span> <span class="n">s</span> <span class="o">/</span> <span class="mi">2</span></div> <div class="viewcode-block" id="Graph.number_of_edges"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.number_of_edges.html#networkx.Graph.number_of_edges">[docs]</a> <span class="k">def</span> <span class="nf">number_of_edges</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">v</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the number of edges between two nodes.</span> +<span class="w"> </span><span class="sd">"""Returns the number of edges between two nodes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -2423,7 +2423,7 @@ <span class="k">return</span> <span class="mi">0</span></div> <div class="viewcode-block" id="Graph.nbunch_iter"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.Graph.nbunch_iter.html#networkx.Graph.nbunch_iter">[docs]</a> <span class="k">def</span> <span class="nf">nbunch_iter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">nbunch</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns an iterator over nodes contained in nbunch that are</span> +<span class="w"> </span><span class="sd">"""Returns an iterator over nodes contained in nbunch that are</span> <span class="sd"> also in the graph.</span> <span class="sd"> The nodes in nbunch are checked for membership in the graph</span> @@ -2540,7 +2540,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/classes/graphviews.html b/_modules/networkx/classes/graphviews.html index f572123e..1ad32f53 100644 --- a/_modules/networkx/classes/graphviews.html +++ b/_modules/networkx/classes/graphviews.html @@ -535,7 +535,7 @@ <div class="viewcode-block" id="subgraph_view"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.subgraph_view.html#networkx.classes.graphviews.subgraph_view">[docs]</a><span class="k">def</span> <span class="nf">subgraph_view</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">filter_node</span><span class="o">=</span><span class="n">no_filter</span><span class="p">,</span> <span class="n">filter_edge</span><span class="o">=</span><span class="n">no_filter</span><span class="p">):</span> - <span class="sd">"""View of `G` applying a filter on nodes and edges.</span> +<span class="w"> </span><span class="sd">"""View of `G` applying a filter on nodes and edges.</span> <span class="sd"> `subgraph_view` provides a read-only view of the input graph that excludes</span> <span class="sd"> nodes and edges based on the outcome of two filter functions `filter_node`</span> @@ -635,7 +635,7 @@ <div class="viewcode-block" id="reverse_view"><a class="viewcode-back" href="../../../reference/generated/networkx.classes.function.reverse_view.html#networkx.classes.graphviews.reverse_view">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">reverse_view</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""View of `G` with edge directions reversed</span> +<span class="w"> </span><span class="sd">"""View of `G` with edge directions reversed</span> <span class="sd"> `reverse_view` returns a read-only view of the input graph where</span> <span class="sd"> edge directions are reversed.</span> @@ -717,7 +717,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/classes/multidigraph.html b/_modules/networkx/classes/multidigraph.html index 4ec51584..0c34a199 100644 --- a/_modules/networkx/classes/multidigraph.html +++ b/_modules/networkx/classes/multidigraph.html @@ -483,7 +483,7 @@ <div class="viewcode-block" id="MultiDiGraph"><a class="viewcode-back" href="../../../reference/classes/multidigraph.html#networkx.MultiDiGraph">[docs]</a><span class="k">class</span> <span class="nc">MultiDiGraph</span><span class="p">(</span><span class="n">MultiGraph</span><span class="p">,</span> <span class="n">DiGraph</span><span class="p">):</span> - <span class="sd">"""A directed graph class that can store multiedges.</span> +<span class="w"> </span><span class="sd">"""A directed graph class that can store multiedges.</span> <span class="sd"> Multiedges are multiple edges between two nodes. Each edge</span> <span class="sd"> can hold optional data or attributes.</span> @@ -762,7 +762,7 @@ <span class="c1"># edge_attr_dict_factory = dict</span> <div class="viewcode-block" id="MultiDiGraph.__init__"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiDiGraph.__init__.html#networkx.MultiDiGraph.__init__">[docs]</a> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">incoming_graph_data</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">multigraph_input</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Initialize a graph with edges, name, or graph attributes.</span> +<span class="w"> </span><span class="sd">"""Initialize a graph with edges, name, or graph attributes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -826,7 +826,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">adj</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Graph adjacency object holding the neighbors of each node.</span> +<span class="w"> </span><span class="sd">"""Graph adjacency object holding the neighbors of each node.</span> <span class="sd"> This object is a read-only dict-like structure with node keys</span> <span class="sd"> and neighbor-dict values. The neighbor-dict is keyed by neighbor</span> @@ -845,7 +845,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">succ</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Graph adjacency object holding the successors of each node.</span> +<span class="w"> </span><span class="sd">"""Graph adjacency object holding the successors of each node.</span> <span class="sd"> This object is a read-only dict-like structure with node keys</span> <span class="sd"> and neighbor-dict values. The neighbor-dict is keyed by neighbor</span> @@ -864,7 +864,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">pred</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Graph adjacency object holding the predecessors of each node.</span> +<span class="w"> </span><span class="sd">"""Graph adjacency object holding the predecessors of each node.</span> <span class="sd"> This object is a read-only dict-like structure with node keys</span> <span class="sd"> and neighbor-dict values. The neighbor-dict is keyed by neighbor</span> @@ -877,7 +877,7 @@ <span class="k">return</span> <span class="n">MultiAdjacencyView</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_pred</span><span class="p">)</span> <div class="viewcode-block" id="MultiDiGraph.add_edge"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiDiGraph.add_edge.html#networkx.MultiDiGraph.add_edge">[docs]</a> <span class="k">def</span> <span class="nf">add_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u_for_edge</span><span class="p">,</span> <span class="n">v_for_edge</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Add an edge between u and v.</span> +<span class="w"> </span><span class="sd">"""Add an edge between u and v.</span> <span class="sd"> The nodes u and v will be automatically added if they are</span> <span class="sd"> not already in the graph.</span> @@ -974,7 +974,7 @@ <span class="k">return</span> <span class="n">key</span></div> <div class="viewcode-block" id="MultiDiGraph.remove_edge"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiDiGraph.remove_edge.html#networkx.MultiDiGraph.remove_edge">[docs]</a> <span class="k">def</span> <span class="nf">remove_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Remove an edge between u and v.</span> +<span class="w"> </span><span class="sd">"""Remove an edge between u and v.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1049,7 +1049,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">edges</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""An OutMultiEdgeView of the Graph as G.edges or G.edges().</span> +<span class="w"> </span><span class="sd">"""An OutMultiEdgeView of the Graph as G.edges or G.edges().</span> <span class="sd"> edges(self, nbunch=None, data=False, keys=False, default=None)</span> @@ -1137,7 +1137,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">in_edges</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""A view of the in edges of the graph as G.in_edges or G.in_edges().</span> +<span class="w"> </span><span class="sd">"""A view of the in edges of the graph as G.in_edges or G.in_edges().</span> <span class="sd"> in_edges(self, nbunch=None, data=False, keys=False, default=None)</span> @@ -1171,7 +1171,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">degree</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""A DegreeView for the Graph as G.degree or G.degree().</span> +<span class="w"> </span><span class="sd">"""A DegreeView for the Graph as G.degree or G.degree().</span> <span class="sd"> The node degree is the number of edges adjacent to the node.</span> <span class="sd"> The weighted node degree is the sum of the edge weights for</span> @@ -1219,7 +1219,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">in_degree</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""A DegreeView for (node, in_degree) or in_degree for single node.</span> +<span class="w"> </span><span class="sd">"""A DegreeView for (node, in_degree) or in_degree for single node.</span> <span class="sd"> The node in-degree is the number of edges pointing in to the node.</span> <span class="sd"> The weighted node degree is the sum of the edge weights for</span> @@ -1270,7 +1270,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">out_degree</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns an iterator for (node, out-degree) or out-degree for single node.</span> +<span class="w"> </span><span class="sd">"""Returns an iterator for (node, out-degree) or out-degree for single node.</span> <span class="sd"> out_degree(self, nbunch=None, weight=None)</span> @@ -1319,15 +1319,15 @@ <span class="k">return</span> <span class="n">OutMultiDegreeView</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_multigraph</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns True if graph is a multigraph, False otherwise."""</span> +<span class="w"> </span><span class="sd">"""Returns True if graph is a multigraph, False otherwise."""</span> <span class="k">return</span> <span class="kc">True</span> <span class="k">def</span> <span class="nf">is_directed</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns True if graph is directed, False otherwise."""</span> +<span class="w"> </span><span class="sd">"""Returns True if graph is directed, False otherwise."""</span> <span class="k">return</span> <span class="kc">True</span> <div class="viewcode-block" id="MultiDiGraph.to_undirected"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiDiGraph.to_undirected.html#networkx.MultiDiGraph.to_undirected">[docs]</a> <span class="k">def</span> <span class="nf">to_undirected</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">reciprocal</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">as_view</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns an undirected representation of the digraph.</span> +<span class="w"> </span><span class="sd">"""Returns an undirected representation of the digraph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1402,7 +1402,7 @@ <span class="k">return</span> <span class="n">G</span></div> <div class="viewcode-block" id="MultiDiGraph.reverse"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiDiGraph.reverse.html#networkx.MultiDiGraph.reverse">[docs]</a> <span class="k">def</span> <span class="nf">reverse</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Returns the reverse of the graph.</span> +<span class="w"> </span><span class="sd">"""Returns the reverse of the graph.</span> <span class="sd"> The reverse is a graph with the same nodes and edges</span> <span class="sd"> but with the directions of the edges reversed.</span> @@ -1475,7 +1475,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/classes/multigraph.html b/_modules/networkx/classes/multigraph.html index a8db1308..12e61e50 100644 --- a/_modules/networkx/classes/multigraph.html +++ b/_modules/networkx/classes/multigraph.html @@ -476,7 +476,7 @@ <div class="viewcode-block" id="MultiGraph"><a class="viewcode-back" href="../../../reference/classes/multigraph.html#networkx.MultiGraph">[docs]</a><span class="k">class</span> <span class="nc">MultiGraph</span><span class="p">(</span><span class="n">Graph</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> An undirected graph class that can store multiedges.</span> <span class="sd"> Multiedges are multiple edges between two nodes. Each edge</span> @@ -755,7 +755,7 @@ <span class="c1"># edge_attr_dict_factory = dict</span> <span class="k">def</span> <span class="nf">to_directed_class</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns the class to use for empty directed copies.</span> +<span class="w"> </span><span class="sd">"""Returns the class to use for empty directed copies.</span> <span class="sd"> If you subclass the base classes, use this to designate</span> <span class="sd"> what directed class to use for `to_directed()` copies.</span> @@ -763,7 +763,7 @@ <span class="k">return</span> <span class="n">nx</span><span class="o">.</span><span class="n">MultiDiGraph</span> <span class="k">def</span> <span class="nf">to_undirected_class</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns the class to use for empty undirected copies.</span> +<span class="w"> </span><span class="sd">"""Returns the class to use for empty undirected copies.</span> <span class="sd"> If you subclass the base classes, use this to designate</span> <span class="sd"> what directed class to use for `to_directed()` copies.</span> @@ -771,7 +771,7 @@ <span class="k">return</span> <span class="n">MultiGraph</span> <div class="viewcode-block" id="MultiGraph.__init__"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiGraph.__init__.html#networkx.MultiGraph.__init__">[docs]</a> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">incoming_graph_data</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">multigraph_input</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Initialize a graph with edges, name, or graph attributes.</span> +<span class="w"> </span><span class="sd">"""Initialize a graph with edges, name, or graph attributes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -835,7 +835,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">adj</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Graph adjacency object holding the neighbors of each node.</span> +<span class="w"> </span><span class="sd">"""Graph adjacency object holding the neighbors of each node.</span> <span class="sd"> This object is a read-only dict-like structure with node keys</span> <span class="sd"> and neighbor-dict values. The neighbor-dict is keyed by neighbor</span> @@ -863,7 +863,7 @@ <span class="k">return</span> <span class="n">MultiAdjacencyView</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_adj</span><span class="p">)</span> <div class="viewcode-block" id="MultiGraph.new_edge_key"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiGraph.new_edge_key.html#networkx.MultiGraph.new_edge_key">[docs]</a> <span class="k">def</span> <span class="nf">new_edge_key</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span> - <span class="sd">"""Returns an unused key for edges between nodes `u` and `v`.</span> +<span class="w"> </span><span class="sd">"""Returns an unused key for edges between nodes `u` and `v`.</span> <span class="sd"> The nodes `u` and `v` do not need to be already in the graph.</span> @@ -892,7 +892,7 @@ <span class="k">return</span> <span class="n">key</span></div> <div class="viewcode-block" id="MultiGraph.add_edge"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiGraph.add_edge.html#networkx.MultiGraph.add_edge">[docs]</a> <span class="k">def</span> <span class="nf">add_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u_for_edge</span><span class="p">,</span> <span class="n">v_for_edge</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Add an edge between u and v.</span> +<span class="w"> </span><span class="sd">"""Add an edge between u and v.</span> <span class="sd"> The nodes u and v will be automatically added if they are</span> <span class="sd"> not already in the graph.</span> @@ -987,7 +987,7 @@ <span class="k">return</span> <span class="n">key</span></div> <div class="viewcode-block" id="MultiGraph.add_edges_from"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiGraph.add_edges_from.html#networkx.MultiGraph.add_edges_from">[docs]</a> <span class="k">def</span> <span class="nf">add_edges_from</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ebunch_to_add</span><span class="p">,</span> <span class="o">**</span><span class="n">attr</span><span class="p">):</span> - <span class="sd">"""Add all the edges in ebunch_to_add.</span> +<span class="w"> </span><span class="sd">"""Add all the edges in ebunch_to_add.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1083,7 +1083,7 @@ <span class="k">return</span> <span class="n">keylist</span></div> <div class="viewcode-block" id="MultiGraph.remove_edge"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiGraph.remove_edge.html#networkx.MultiGraph.remove_edge">[docs]</a> <span class="k">def</span> <span class="nf">remove_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Remove an edge between u and v.</span> +<span class="w"> </span><span class="sd">"""Remove an edge between u and v.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1161,7 +1161,7 @@ <span class="k">del</span> <span class="bp">self</span><span class="o">.</span><span class="n">_adj</span><span class="p">[</span><span class="n">v</span><span class="p">][</span><span class="n">u</span><span class="p">]</span></div> <div class="viewcode-block" id="MultiGraph.remove_edges_from"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiGraph.remove_edges_from.html#networkx.MultiGraph.remove_edges_from">[docs]</a> <span class="k">def</span> <span class="nf">remove_edges_from</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ebunch</span><span class="p">):</span> - <span class="sd">"""Remove all edges specified in ebunch.</span> +<span class="w"> </span><span class="sd">"""Remove all edges specified in ebunch.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1219,7 +1219,7 @@ <span class="k">pass</span></div> <div class="viewcode-block" id="MultiGraph.has_edge"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiGraph.has_edge.html#networkx.MultiGraph.has_edge">[docs]</a> <span class="k">def</span> <span class="nf">has_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns True if the graph has an edge between nodes u and v.</span> +<span class="w"> </span><span class="sd">"""Returns True if the graph has an edge between nodes u and v.</span> <span class="sd"> This is the same as `v in G[u] or key in G[u][v]`</span> <span class="sd"> without KeyError exceptions.</span> @@ -1280,7 +1280,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">edges</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns an iterator over the edges.</span> +<span class="w"> </span><span class="sd">"""Returns an iterator over the edges.</span> <span class="sd"> edges(self, nbunch=None, data=False, keys=False, default=None)</span> @@ -1355,7 +1355,7 @@ <span class="k">return</span> <span class="n">MultiEdgeView</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <div class="viewcode-block" id="MultiGraph.get_edge_data"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiGraph.get_edge_data.html#networkx.MultiGraph.get_edge_data">[docs]</a> <span class="k">def</span> <span class="nf">get_edge_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the attribute dictionary associated with edge (u, v,</span> +<span class="w"> </span><span class="sd">"""Returns the attribute dictionary associated with edge (u, v,</span> <span class="sd"> key).</span> <span class="sd"> If a key is not provided, returns a dictionary mapping edge keys</span> @@ -1433,7 +1433,7 @@ <span class="nd">@cached_property</span> <span class="k">def</span> <span class="nf">degree</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""A DegreeView for the Graph as G.degree or G.degree().</span> +<span class="w"> </span><span class="sd">"""A DegreeView for the Graph as G.degree or G.degree().</span> <span class="sd"> The node degree is the number of edges adjacent to the node.</span> <span class="sd"> The weighted node degree is the sum of the edge weights for</span> @@ -1472,15 +1472,15 @@ <span class="k">return</span> <span class="n">MultiDegreeView</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="k">def</span> <span class="nf">is_multigraph</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns True if graph is a multigraph, False otherwise."""</span> +<span class="w"> </span><span class="sd">"""Returns True if graph is a multigraph, False otherwise."""</span> <span class="k">return</span> <span class="kc">True</span> <span class="k">def</span> <span class="nf">is_directed</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns True if graph is directed, False otherwise."""</span> +<span class="w"> </span><span class="sd">"""Returns True if graph is directed, False otherwise."""</span> <span class="k">return</span> <span class="kc">False</span> <div class="viewcode-block" id="MultiGraph.copy"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiGraph.copy.html#networkx.MultiGraph.copy">[docs]</a> <span class="k">def</span> <span class="nf">copy</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">as_view</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns a copy of the graph.</span> +<span class="w"> </span><span class="sd">"""Returns a copy of the graph.</span> <span class="sd"> The copy method by default returns an independent shallow copy</span> <span class="sd"> of the graph and attributes. That is, if an attribute is a</span> @@ -1570,7 +1570,7 @@ <span class="k">return</span> <span class="n">G</span></div> <div class="viewcode-block" id="MultiGraph.to_directed"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiGraph.to_directed.html#networkx.MultiGraph.to_directed">[docs]</a> <span class="k">def</span> <span class="nf">to_directed</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">as_view</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns a directed representation of the graph.</span> +<span class="w"> </span><span class="sd">"""Returns a directed representation of the graph.</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> @@ -1631,7 +1631,7 @@ <span class="k">return</span> <span class="n">G</span></div> <div class="viewcode-block" id="MultiGraph.to_undirected"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiGraph.to_undirected.html#networkx.MultiGraph.to_undirected">[docs]</a> <span class="k">def</span> <span class="nf">to_undirected</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">as_view</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns an undirected copy of the graph.</span> +<span class="w"> </span><span class="sd">"""Returns an undirected copy of the graph.</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> @@ -1684,7 +1684,7 @@ <span class="k">return</span> <span class="n">G</span></div> <div class="viewcode-block" id="MultiGraph.number_of_edges"><a class="viewcode-back" href="../../../reference/classes/generated/networkx.MultiGraph.number_of_edges.html#networkx.MultiGraph.number_of_edges">[docs]</a> <span class="k">def</span> <span class="nf">number_of_edges</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">v</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the number of edges between two nodes.</span> +<span class="w"> </span><span class="sd">"""Returns the number of edges between two nodes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1791,7 +1791,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/convert.html b/_modules/networkx/convert.html index 1197f25f..a78ff4ae 100644 --- a/_modules/networkx/convert.html +++ b/_modules/networkx/convert.html @@ -495,7 +495,7 @@ <div class="viewcode-block" id="to_networkx_graph"><a class="viewcode-back" href="../../reference/generated/networkx.convert.to_networkx_graph.html#networkx.convert.to_networkx_graph">[docs]</a><span class="k">def</span> <span class="nf">to_networkx_graph</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">multigraph_input</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Make a NetworkX graph from a known data structure.</span> +<span class="w"> </span><span class="sd">"""Make a NetworkX graph from a known data structure.</span> <span class="sd"> The preferred way to call this is automatically</span> <span class="sd"> from the class constructor</span> @@ -640,7 +640,7 @@ <div class="viewcode-block" id="to_dict_of_lists"><a class="viewcode-back" href="../../reference/generated/networkx.convert.to_dict_of_lists.html#networkx.convert.to_dict_of_lists">[docs]</a><span class="k">def</span> <span class="nf">to_dict_of_lists</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns adjacency representation of graph as a dictionary of lists.</span> +<span class="w"> </span><span class="sd">"""Returns adjacency representation of graph as a dictionary of lists.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -665,7 +665,7 @@ <div class="viewcode-block" id="from_dict_of_lists"><a class="viewcode-back" href="../../reference/generated/networkx.convert.from_dict_of_lists.html#networkx.convert.from_dict_of_lists">[docs]</a><span class="k">def</span> <span class="nf">from_dict_of_lists</span><span class="p">(</span><span class="n">d</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a graph from a dictionary of lists.</span> +<span class="w"> </span><span class="sd">"""Returns a graph from a dictionary of lists.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -705,7 +705,7 @@ <div class="viewcode-block" id="to_dict_of_dicts"><a class="viewcode-back" href="../../reference/generated/networkx.convert.to_dict_of_dicts.html#networkx.convert.to_dict_of_dicts">[docs]</a><span class="k">def</span> <span class="nf">to_dict_of_dicts</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">edge_data</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns adjacency representation of graph as a dictionary of dictionaries.</span> +<span class="w"> </span><span class="sd">"""Returns adjacency representation of graph as a dictionary of dictionaries.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -826,7 +826,7 @@ <div class="viewcode-block" id="from_dict_of_dicts"><a class="viewcode-back" href="../../reference/generated/networkx.convert.from_dict_of_dicts.html#networkx.convert.from_dict_of_dicts">[docs]</a><span class="k">def</span> <span class="nf">from_dict_of_dicts</span><span class="p">(</span><span class="n">d</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">multigraph_input</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns a graph from a dictionary of dictionaries.</span> +<span class="w"> </span><span class="sd">"""Returns a graph from a dictionary of dictionaries.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -912,7 +912,7 @@ <div class="viewcode-block" id="to_edgelist"><a class="viewcode-back" href="../../reference/generated/networkx.convert.to_edgelist.html#networkx.convert.to_edgelist">[docs]</a><span class="k">def</span> <span class="nf">to_edgelist</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a list of edges in the graph.</span> +<span class="w"> </span><span class="sd">"""Returns a list of edges in the graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -929,7 +929,7 @@ <div class="viewcode-block" id="from_edgelist"><a class="viewcode-back" href="../../reference/generated/networkx.convert.from_edgelist.html#networkx.convert.from_edgelist">[docs]</a><span class="k">def</span> <span class="nf">from_edgelist</span><span class="p">(</span><span class="n">edgelist</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a graph from a list of edges.</span> +<span class="w"> </span><span class="sd">"""Returns a graph from a list of edges.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1003,7 +1003,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/convert_matrix.html b/_modules/networkx/convert_matrix.html index ea3650f5..7bf92f2e 100644 --- a/_modules/networkx/convert_matrix.html +++ b/_modules/networkx/convert_matrix.html @@ -515,7 +515,7 @@ <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">nonedge</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns the graph adjacency matrix as a Pandas DataFrame.</span> +<span class="w"> </span><span class="sd">"""Returns the graph adjacency matrix as a Pandas DataFrame.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -613,7 +613,7 @@ <div class="viewcode-block" id="from_pandas_adjacency"><a class="viewcode-back" href="../../reference/generated/networkx.convert_matrix.from_pandas_adjacency.html#networkx.convert_matrix.from_pandas_adjacency">[docs]</a><span class="k">def</span> <span class="nf">from_pandas_adjacency</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a graph from Pandas DataFrame.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a graph from Pandas DataFrame.</span> <span class="sd"> The Pandas DataFrame is interpreted as an adjacency matrix for the graph.</span> @@ -680,7 +680,7 @@ <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">edge_key</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns the graph edge list as a Pandas DataFrame.</span> +<span class="w"> </span><span class="sd">"""Returns the graph edge list as a Pandas DataFrame.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -771,7 +771,7 @@ <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">edge_key</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns a graph from Pandas DataFrame containing an edge list.</span> +<span class="w"> </span><span class="sd">"""Returns a graph from Pandas DataFrame containing an edge list.</span> <span class="sd"> The Pandas DataFrame should contain at least two columns of node names and</span> <span class="sd"> zero or more columns of edge attributes. Each row will be processed as one</span> @@ -927,7 +927,7 @@ <div class="viewcode-block" id="to_scipy_sparse_array"><a class="viewcode-back" href="../../reference/generated/networkx.convert_matrix.to_scipy_sparse_array.html#networkx.convert_matrix.to_scipy_sparse_array">[docs]</a><span class="k">def</span> <span class="nf">to_scipy_sparse_array</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="nb">format</span><span class="o">=</span><span class="s2">"csr"</span><span class="p">):</span> - <span class="sd">"""Returns the graph adjacency matrix as a SciPy sparse array.</span> +<span class="w"> </span><span class="sd">"""Returns the graph adjacency matrix as a SciPy sparse array.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1061,7 +1061,7 @@ <span class="k">def</span> <span class="nf">_csr_gen_triples</span><span class="p">(</span><span class="n">A</span><span class="p">):</span> - <span class="sd">"""Converts a SciPy sparse array in **Compressed Sparse Row** format to</span> +<span class="w"> </span><span class="sd">"""Converts a SciPy sparse array in **Compressed Sparse Row** format to</span> <span class="sd"> an iterable of weighted edge triples.</span> <span class="sd"> """</span> @@ -1073,7 +1073,7 @@ <span class="k">def</span> <span class="nf">_csc_gen_triples</span><span class="p">(</span><span class="n">A</span><span class="p">):</span> - <span class="sd">"""Converts a SciPy sparse array in **Compressed Sparse Column** format to</span> +<span class="w"> </span><span class="sd">"""Converts a SciPy sparse array in **Compressed Sparse Column** format to</span> <span class="sd"> an iterable of weighted edge triples.</span> <span class="sd"> """</span> @@ -1085,7 +1085,7 @@ <span class="k">def</span> <span class="nf">_coo_gen_triples</span><span class="p">(</span><span class="n">A</span><span class="p">):</span> - <span class="sd">"""Converts a SciPy sparse array in **Coordinate** format to an iterable</span> +<span class="w"> </span><span class="sd">"""Converts a SciPy sparse array in **Coordinate** format to an iterable</span> <span class="sd"> of weighted edge triples.</span> <span class="sd"> """</span> @@ -1094,7 +1094,7 @@ <span class="k">def</span> <span class="nf">_dok_gen_triples</span><span class="p">(</span><span class="n">A</span><span class="p">):</span> - <span class="sd">"""Converts a SciPy sparse array in **Dictionary of Keys** format to an</span> +<span class="w"> </span><span class="sd">"""Converts a SciPy sparse array in **Dictionary of Keys** format to an</span> <span class="sd"> iterable of weighted edge triples.</span> <span class="sd"> """</span> @@ -1103,7 +1103,7 @@ <span class="k">def</span> <span class="nf">_generate_weighted_edges</span><span class="p">(</span><span class="n">A</span><span class="p">):</span> - <span class="sd">"""Returns an iterable over (u, v, w) triples, where u and v are adjacent</span> +<span class="w"> </span><span class="sd">"""Returns an iterable over (u, v, w) triples, where u and v are adjacent</span> <span class="sd"> vertices and w is the weight of the edge joining u and v.</span> <span class="sd"> `A` is a SciPy sparse array (in any format).</span> @@ -1122,7 +1122,7 @@ <div class="viewcode-block" id="from_scipy_sparse_array"><a class="viewcode-back" href="../../reference/generated/networkx.convert_matrix.from_scipy_sparse_array.html#networkx.convert_matrix.from_scipy_sparse_array">[docs]</a><span class="k">def</span> <span class="nf">from_scipy_sparse_array</span><span class="p">(</span> <span class="n">A</span><span class="p">,</span> <span class="n">parallel_edges</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">edge_attribute</span><span class="o">=</span><span class="s2">"weight"</span> <span class="p">):</span> - <span class="sd">"""Creates a new graph from an adjacency matrix given as a SciPy sparse</span> +<span class="w"> </span><span class="sd">"""Creates a new graph from an adjacency matrix given as a SciPy sparse</span> <span class="sd"> array.</span> <span class="sd"> Parameters</span> @@ -1233,7 +1233,7 @@ <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">nonedge</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns the graph adjacency matrix as a NumPy array.</span> +<span class="w"> </span><span class="sd">"""Returns the graph adjacency matrix as a NumPy array.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1392,7 +1392,7 @@ <span class="c1"># Input validation</span> <span class="n">nodeset</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">nodelist</span><span class="p">)</span> <span class="k">if</span> <span class="n">nodeset</span> <span class="o">-</span> <span class="nb">set</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Nodes </span><span class="si">{</span><span class="n">nodeset</span> <span class="o">-</span> <span class="nb">set</span><span class="p">(</span><span class="n">G</span><span class="p">)</span><span class="si">}</span><span class="s2"> in nodelist is not in G"</span><span class="p">)</span> + <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Nodes </span><span class="si">{</span><span class="n">nodeset</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="nb">set</span><span class="p">(</span><span class="n">G</span><span class="p">)</span><span class="si">}</span><span class="s2"> in nodelist is not in G"</span><span class="p">)</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">nodeset</span><span class="p">)</span> <span class="o"><</span> <span class="n">nlen</span><span class="p">:</span> <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="s2">"nodelist contains duplicates."</span><span class="p">)</span> @@ -1463,7 +1463,7 @@ <div class="viewcode-block" id="from_numpy_array"><a class="viewcode-back" href="../../reference/generated/networkx.convert_matrix.from_numpy_array.html#networkx.convert_matrix.from_numpy_array">[docs]</a><span class="k">def</span> <span class="nf">from_numpy_array</span><span class="p">(</span><span class="n">A</span><span class="p">,</span> <span class="n">parallel_edges</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a graph from a 2D NumPy array.</span> +<span class="w"> </span><span class="sd">"""Returns a graph from a 2D NumPy array.</span> <span class="sd"> The 2D NumPy array is interpreted as an adjacency matrix for the graph.</span> @@ -1674,7 +1674,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/drawing/layout.html b/_modules/networkx/drawing/layout.html index 5e2a18b8..0afdd047 100644 --- a/_modules/networkx/drawing/layout.html +++ b/_modules/networkx/drawing/layout.html @@ -522,7 +522,7 @@ <div class="viewcode-block" id="random_layout"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.layout.random_layout.html#networkx.drawing.layout.random_layout">[docs]</a><span class="nd">@np_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_layout</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">center</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Position nodes uniformly at random in the unit square.</span> +<span class="w"> </span><span class="sd">"""Position nodes uniformly at random in the unit square.</span> <span class="sd"> For every node, a position is generated by choosing each of dim</span> <span class="sd"> coordinates uniformly at random on the interval [0.0, 1.0).</span> @@ -571,7 +571,7 @@ <div class="viewcode-block" id="circular_layout"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.layout.circular_layout.html#networkx.drawing.layout.circular_layout">[docs]</a><span class="k">def</span> <span class="nf">circular_layout</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">center</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">2</span><span class="p">):</span> <span class="c1"># dim=2 only</span> - <span class="sd">"""Position nodes on a circle.</span> +<span class="w"> </span><span class="sd">"""Position nodes on a circle.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -638,7 +638,7 @@ <div class="viewcode-block" id="shell_layout"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.layout.shell_layout.html#networkx.drawing.layout.shell_layout">[docs]</a><span class="k">def</span> <span class="nf">shell_layout</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nlist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">rotate</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">center</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">2</span><span class="p">):</span> - <span class="sd">"""Position nodes in concentric circles.</span> +<span class="w"> </span><span class="sd">"""Position nodes in concentric circles.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -731,7 +731,7 @@ <div class="viewcode-block" id="bipartite_layout"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.layout.bipartite_layout.html#networkx.drawing.layout.bipartite_layout">[docs]</a><span class="k">def</span> <span class="nf">bipartite_layout</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">align</span><span class="o">=</span><span class="s2">"vertical"</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">center</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">aspect_ratio</span><span class="o">=</span><span class="mi">4</span> <span class="o">/</span> <span class="mi">3</span> <span class="p">):</span> - <span class="sd">"""Position nodes in two straight lines.</span> +<span class="w"> </span><span class="sd">"""Position nodes in two straight lines.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -820,7 +820,7 @@ <span class="n">dim</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Position nodes using Fruchterman-Reingold force-directed algorithm.</span> +<span class="w"> </span><span class="sd">"""Position nodes using Fruchterman-Reingold force-directed algorithm.</span> <span class="sd"> The algorithm simulates a force-directed representation of the network</span> <span class="sd"> treating edges as springs holding nodes close, while treating nodes</span> @@ -1102,7 +1102,7 @@ <div class="viewcode-block" id="kamada_kawai_layout"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.layout.kamada_kawai_layout.html#networkx.drawing.layout.kamada_kawai_layout">[docs]</a><span class="k">def</span> <span class="nf">kamada_kawai_layout</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">dist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">pos</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">center</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">2</span> <span class="p">):</span> - <span class="sd">"""Position nodes using Kamada-Kawai path-length cost-function.</span> +<span class="w"> </span><span class="sd">"""Position nodes using Kamada-Kawai path-length cost-function.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1225,7 +1225,7 @@ <div class="viewcode-block" id="spectral_layout"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.layout.spectral_layout.html#networkx.drawing.layout.spectral_layout">[docs]</a><span class="k">def</span> <span class="nf">spectral_layout</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">center</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">2</span><span class="p">):</span> - <span class="sd">"""Position nodes using the eigenvectors of the graph Laplacian.</span> +<span class="w"> </span><span class="sd">"""Position nodes using the eigenvectors of the graph Laplacian.</span> <span class="sd"> Using the unnormalized Laplacian, the layout shows possible clusters of</span> <span class="sd"> nodes which are an approximation of the ratio cut. If dim is the number of</span> @@ -1354,7 +1354,7 @@ <div class="viewcode-block" id="planar_layout"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.layout.planar_layout.html#networkx.drawing.layout.planar_layout">[docs]</a><span class="k">def</span> <span class="nf">planar_layout</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">center</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">2</span><span class="p">):</span> - <span class="sd">"""Position nodes without edge intersections.</span> +<span class="w"> </span><span class="sd">"""Position nodes without edge intersections.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1411,7 +1411,7 @@ <div class="viewcode-block" id="spiral_layout"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.layout.spiral_layout.html#networkx.drawing.layout.spiral_layout">[docs]</a><span class="k">def</span> <span class="nf">spiral_layout</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">center</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">resolution</span><span class="o">=</span><span class="mf">0.35</span><span class="p">,</span> <span class="n">equidistant</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Position nodes in a spiral layout.</span> +<span class="w"> </span><span class="sd">"""Position nodes in a spiral layout.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1490,7 +1490,7 @@ <div class="viewcode-block" id="multipartite_layout"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.layout.multipartite_layout.html#networkx.drawing.layout.multipartite_layout">[docs]</a><span class="k">def</span> <span class="nf">multipartite_layout</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">subset_key</span><span class="o">=</span><span class="s2">"subset"</span><span class="p">,</span> <span class="n">align</span><span class="o">=</span><span class="s2">"vertical"</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">center</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Position nodes in layers of straight lines.</span> +<span class="w"> </span><span class="sd">"""Position nodes in layers of straight lines.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1583,7 +1583,7 @@ <span class="n">dt</span><span class="o">=</span><span class="mf">1e-3</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Arf layout for networkx</span> +<span class="w"> </span><span class="sd">"""Arf layout for networkx</span> <span class="sd"> The attractive and repulsive forces (arf) layout [1]</span> <span class="sd"> improves the spring layout in three ways. First, it</span> @@ -1687,7 +1687,7 @@ <div class="viewcode-block" id="rescale_layout"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.layout.rescale_layout.html#networkx.drawing.layout.rescale_layout">[docs]</a><span class="k">def</span> <span class="nf">rescale_layout</span><span class="p">(</span><span class="n">pos</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span> - <span class="sd">"""Returns scaled position array to (-scale, scale) in all axes.</span> +<span class="w"> </span><span class="sd">"""Returns scaled position array to (-scale, scale) in all axes.</span> <span class="sd"> The function acts on NumPy arrays which hold position information.</span> <span class="sd"> Each position is one row of the array. The dimension of the space</span> @@ -1728,7 +1728,7 @@ <div class="viewcode-block" id="rescale_layout_dict"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.layout.rescale_layout_dict.html#networkx.drawing.layout.rescale_layout_dict">[docs]</a><span class="k">def</span> <span class="nf">rescale_layout_dict</span><span class="p">(</span><span class="n">pos</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span> - <span class="sd">"""Return a dictionary of scaled positions keyed by node</span> +<span class="w"> </span><span class="sd">"""Return a dictionary of scaled positions keyed by node</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1814,7 +1814,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/drawing/nx_agraph.html b/_modules/networkx/drawing/nx_agraph.html index 7f187a6d..a18c0e02 100644 --- a/_modules/networkx/drawing/nx_agraph.html +++ b/_modules/networkx/drawing/nx_agraph.html @@ -497,7 +497,7 @@ <div class="viewcode-block" id="from_agraph"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_agraph.from_agraph.html#networkx.drawing.nx_agraph.from_agraph">[docs]</a><span class="k">def</span> <span class="nf">from_agraph</span><span class="p">(</span><span class="n">A</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a NetworkX Graph or DiGraph from a PyGraphviz graph.</span> +<span class="w"> </span><span class="sd">"""Returns a NetworkX Graph or DiGraph from a PyGraphviz graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -573,7 +573,7 @@ <div class="viewcode-block" id="to_agraph"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_agraph.to_agraph.html#networkx.drawing.nx_agraph.to_agraph">[docs]</a><span class="k">def</span> <span class="nf">to_agraph</span><span class="p">(</span><span class="n">N</span><span class="p">):</span> - <span class="sd">"""Returns a pygraphviz graph from a NetworkX graph N.</span> +<span class="w"> </span><span class="sd">"""Returns a pygraphviz graph from a NetworkX graph N.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -639,7 +639,7 @@ <div class="viewcode-block" id="write_dot"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_agraph.write_dot.html#networkx.drawing.nx_agraph.write_dot">[docs]</a><span class="k">def</span> <span class="nf">write_dot</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">path</span><span class="p">):</span> - <span class="sd">"""Write NetworkX graph G to Graphviz dot format on path.</span> +<span class="w"> </span><span class="sd">"""Write NetworkX graph G to Graphviz dot format on path.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -661,7 +661,7 @@ <div class="viewcode-block" id="read_dot"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_agraph.read_dot.html#networkx.drawing.nx_agraph.read_dot">[docs]</a><span class="k">def</span> <span class="nf">read_dot</span><span class="p">(</span><span class="n">path</span><span class="p">):</span> - <span class="sd">"""Returns a NetworkX graph from a dot file on path.</span> +<span class="w"> </span><span class="sd">"""Returns a NetworkX graph from a dot file on path.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -681,7 +681,7 @@ <div class="viewcode-block" id="graphviz_layout"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_agraph.graphviz_layout.html#networkx.drawing.nx_agraph.graphviz_layout">[docs]</a><span class="k">def</span> <span class="nf">graphviz_layout</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">prog</span><span class="o">=</span><span class="s2">"neato"</span><span class="p">,</span> <span class="n">root</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">args</span><span class="o">=</span><span class="s2">""</span><span class="p">):</span> - <span class="sd">"""Create node positions for G using Graphviz.</span> +<span class="w"> </span><span class="sd">"""Create node positions for G using Graphviz.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -715,7 +715,7 @@ <div class="viewcode-block" id="pygraphviz_layout"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_agraph.pygraphviz_layout.html#networkx.drawing.nx_agraph.pygraphviz_layout">[docs]</a><span class="k">def</span> <span class="nf">pygraphviz_layout</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">prog</span><span class="o">=</span><span class="s2">"neato"</span><span class="p">,</span> <span class="n">root</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">args</span><span class="o">=</span><span class="s2">""</span><span class="p">):</span> - <span class="sd">"""Create node positions for G using Graphviz.</span> +<span class="w"> </span><span class="sd">"""Create node positions for G using Graphviz.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -780,7 +780,7 @@ <span class="k">def</span> <span class="nf">view_pygraphviz</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">edgelabel</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">prog</span><span class="o">=</span><span class="s2">"dot"</span><span class="p">,</span> <span class="n">args</span><span class="o">=</span><span class="s2">""</span><span class="p">,</span> <span class="n">suffix</span><span class="o">=</span><span class="s2">""</span><span class="p">,</span> <span class="n">path</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">show</span><span class="o">=</span><span class="kc">True</span> <span class="p">):</span> - <span class="sd">"""Views the graph G using the specified layout algorithm.</span> +<span class="w"> </span><span class="sd">"""Views the graph G using the specified layout algorithm.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -972,7 +972,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/drawing/nx_pydot.html b/_modules/networkx/drawing/nx_pydot.html index 9ea4f296..750562a6 100644 --- a/_modules/networkx/drawing/nx_pydot.html +++ b/_modules/networkx/drawing/nx_pydot.html @@ -500,7 +500,7 @@ <div class="viewcode-block" id="write_dot"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pydot.write_dot.html#networkx.drawing.nx_pydot.write_dot">[docs]</a><span class="nd">@open_file</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"w"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">write_dot</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">path</span><span class="p">):</span> - <span class="sd">"""Write NetworkX graph G to Graphviz dot format on path.</span> +<span class="w"> </span><span class="sd">"""Write NetworkX graph G to Graphviz dot format on path.</span> <span class="sd"> Path can be a string or a file handle.</span> <span class="sd"> """</span> @@ -518,7 +518,7 @@ <div class="viewcode-block" id="read_dot"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pydot.read_dot.html#networkx.drawing.nx_pydot.read_dot">[docs]</a><span class="nd">@open_file</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"r"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">read_dot</span><span class="p">(</span><span class="n">path</span><span class="p">):</span> - <span class="sd">"""Returns a NetworkX :class:`MultiGraph` or :class:`MultiDiGraph` from the</span> +<span class="w"> </span><span class="sd">"""Returns a NetworkX :class:`MultiGraph` or :class:`MultiDiGraph` from the</span> <span class="sd"> dot file with the passed path.</span> <span class="sd"> If this file contains multiple graphs, only the first such graph is</span> @@ -559,7 +559,7 @@ <div class="viewcode-block" id="from_pydot"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pydot.from_pydot.html#networkx.drawing.nx_pydot.from_pydot">[docs]</a><span class="k">def</span> <span class="nf">from_pydot</span><span class="p">(</span><span class="n">P</span><span class="p">):</span> - <span class="sd">"""Returns a NetworkX graph from a Pydot graph.</span> +<span class="w"> </span><span class="sd">"""Returns a NetworkX graph from a Pydot graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -663,7 +663,7 @@ <div class="viewcode-block" id="to_pydot"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pydot.to_pydot.html#networkx.drawing.nx_pydot.to_pydot">[docs]</a><span class="k">def</span> <span class="nf">to_pydot</span><span class="p">(</span><span class="n">N</span><span class="p">):</span> - <span class="sd">"""Returns a pydot graph from a NetworkX graph N.</span> +<span class="w"> </span><span class="sd">"""Returns a pydot graph from a NetworkX graph N.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -780,7 +780,7 @@ <div class="viewcode-block" id="graphviz_layout"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pydot.graphviz_layout.html#networkx.drawing.nx_pydot.graphviz_layout">[docs]</a><span class="k">def</span> <span class="nf">graphviz_layout</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">prog</span><span class="o">=</span><span class="s2">"neato"</span><span class="p">,</span> <span class="n">root</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Create node positions using Pydot and Graphviz.</span> +<span class="w"> </span><span class="sd">"""Create node positions using Pydot and Graphviz.</span> <span class="sd"> Returns a dictionary of positions keyed by node.</span> @@ -821,7 +821,7 @@ <div class="viewcode-block" id="pydot_layout"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pydot.pydot_layout.html#networkx.drawing.nx_pydot.pydot_layout">[docs]</a><span class="k">def</span> <span class="nf">pydot_layout</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">prog</span><span class="o">=</span><span class="s2">"neato"</span><span class="p">,</span> <span class="n">root</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Create node positions using :mod:`pydot` and Graphviz.</span> +<span class="w"> </span><span class="sd">"""Create node positions using :mod:`pydot` and Graphviz.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -964,7 +964,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/drawing/nx_pylab.html b/_modules/networkx/drawing/nx_pylab.html index 5f119c1b..c7ced280 100644 --- a/_modules/networkx/drawing/nx_pylab.html +++ b/_modules/networkx/drawing/nx_pylab.html @@ -510,7 +510,7 @@ <div class="viewcode-block" id="draw"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw.html#networkx.drawing.nx_pylab.draw">[docs]</a><span class="k">def</span> <span class="nf">draw</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">pos</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwds</span><span class="p">):</span> - <span class="sd">"""Draw the graph G with Matplotlib.</span> +<span class="w"> </span><span class="sd">"""Draw the graph G with Matplotlib.</span> <span class="sd"> Draw the graph as a simple representation with no node</span> <span class="sd"> labels or edge labels and using the full Matplotlib figure area</span> @@ -588,7 +588,7 @@ <div class="viewcode-block" id="draw_networkx"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_networkx.html#networkx.drawing.nx_pylab.draw_networkx">[docs]</a><span class="k">def</span> <span class="nf">draw_networkx</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">pos</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">arrows</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">with_labels</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="o">**</span><span class="n">kwds</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Draw the graph G using Matplotlib.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Draw the graph G using Matplotlib.</span> <span class="sd"> Draw the graph with Matplotlib with options for node positions,</span> <span class="sd"> labeling, titles, and many other drawing features.</span> @@ -787,7 +787,7 @@ <span class="n">label</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">margins</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Draw the nodes of the graph G.</span> +<span class="w"> </span><span class="sd">"""Draw the nodes of the graph G.</span> <span class="sd"> This draws only the nodes of the graph G.</span> @@ -949,7 +949,7 @@ <span class="n">min_source_margin</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">min_target_margin</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Draw the edges of the graph G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Draw the edges of the graph G.</span> <span class="sd"> This draws only the edges of the graph G.</span> @@ -1403,7 +1403,7 @@ <span class="n">ax</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">clip_on</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Draw node labels on the graph G.</span> +<span class="w"> </span><span class="sd">"""Draw node labels on the graph G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1529,7 +1529,7 @@ <span class="n">rotate</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">clip_on</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Draw edge labels.</span> +<span class="w"> </span><span class="sd">"""Draw edge labels.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1683,7 +1683,7 @@ <div class="viewcode-block" id="draw_circular"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_circular.html#networkx.drawing.nx_pylab.draw_circular">[docs]</a><span class="k">def</span> <span class="nf">draw_circular</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> - <span class="sd">"""Draw the graph `G` with a circular layout.</span> +<span class="w"> </span><span class="sd">"""Draw the graph `G` with a circular layout.</span> <span class="sd"> This is a convenience function equivalent to::</span> @@ -1717,7 +1717,7 @@ <div class="viewcode-block" id="draw_kamada_kawai"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_kamada_kawai.html#networkx.drawing.nx_pylab.draw_kamada_kawai">[docs]</a><span class="k">def</span> <span class="nf">draw_kamada_kawai</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> - <span class="sd">"""Draw the graph `G` with a Kamada-Kawai force-directed layout.</span> +<span class="w"> </span><span class="sd">"""Draw the graph `G` with a Kamada-Kawai force-directed layout.</span> <span class="sd"> This is a convenience function equivalent to::</span> @@ -1752,7 +1752,7 @@ <div class="viewcode-block" id="draw_random"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_random.html#networkx.drawing.nx_pylab.draw_random">[docs]</a><span class="k">def</span> <span class="nf">draw_random</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> - <span class="sd">"""Draw the graph `G` with a random layout.</span> +<span class="w"> </span><span class="sd">"""Draw the graph `G` with a random layout.</span> <span class="sd"> This is a convenience function equivalent to::</span> @@ -1786,7 +1786,7 @@ <div class="viewcode-block" id="draw_spectral"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_spectral.html#networkx.drawing.nx_pylab.draw_spectral">[docs]</a><span class="k">def</span> <span class="nf">draw_spectral</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> - <span class="sd">"""Draw the graph `G` with a spectral 2D layout.</span> +<span class="w"> </span><span class="sd">"""Draw the graph `G` with a spectral 2D layout.</span> <span class="sd"> This is a convenience function equivalent to::</span> @@ -1823,7 +1823,7 @@ <div class="viewcode-block" id="draw_spring"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_spring.html#networkx.drawing.nx_pylab.draw_spring">[docs]</a><span class="k">def</span> <span class="nf">draw_spring</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> - <span class="sd">"""Draw the graph `G` with a spring layout.</span> +<span class="w"> </span><span class="sd">"""Draw the graph `G` with a spring layout.</span> <span class="sd"> This is a convenience function equivalent to::</span> @@ -1861,7 +1861,7 @@ <div class="viewcode-block" id="draw_shell"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_shell.html#networkx.drawing.nx_pylab.draw_shell">[docs]</a><span class="k">def</span> <span class="nf">draw_shell</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nlist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> - <span class="sd">"""Draw networkx graph `G` with shell layout.</span> +<span class="w"> </span><span class="sd">"""Draw networkx graph `G` with shell layout.</span> <span class="sd"> This is a convenience function equivalent to::</span> @@ -1900,7 +1900,7 @@ <div class="viewcode-block" id="draw_planar"><a class="viewcode-back" href="../../../reference/generated/networkx.drawing.nx_pylab.draw_planar.html#networkx.drawing.nx_pylab.draw_planar">[docs]</a><span class="k">def</span> <span class="nf">draw_planar</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span> - <span class="sd">"""Draw a planar networkx graph `G` with planar layout.</span> +<span class="w"> </span><span class="sd">"""Draw a planar networkx graph `G` with planar layout.</span> <span class="sd"> This is a convenience function equivalent to::</span> @@ -1939,7 +1939,7 @@ <span class="k">def</span> <span class="nf">apply_alpha</span><span class="p">(</span><span class="n">colors</span><span class="p">,</span> <span class="n">alpha</span><span class="p">,</span> <span class="n">elem_list</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">vmin</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">vmax</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Apply an alpha (or list of alphas) to the colors provided.</span> +<span class="w"> </span><span class="sd">"""Apply an alpha (or list of alphas) to the colors provided.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -2064,7 +2064,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/exception.html b/_modules/networkx/exception.html index 9e1855a4..c665dcb7 100644 --- a/_modules/networkx/exception.html +++ b/_modules/networkx/exception.html @@ -488,15 +488,15 @@ <div class="viewcode-block" id="NetworkXException"><a class="viewcode-back" href="../../reference/exceptions.html#networkx.NetworkXException">[docs]</a><span class="k">class</span> <span class="nc">NetworkXException</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span> - <span class="sd">"""Base class for exceptions in NetworkX."""</span></div> +<span class="w"> </span><span class="sd">"""Base class for exceptions in NetworkX."""</span></div> <div class="viewcode-block" id="NetworkXError"><a class="viewcode-back" href="../../reference/exceptions.html#networkx.NetworkXError">[docs]</a><span class="k">class</span> <span class="nc">NetworkXError</span><span class="p">(</span><span class="n">NetworkXException</span><span class="p">):</span> - <span class="sd">"""Exception for a serious error in NetworkX"""</span></div> +<span class="w"> </span><span class="sd">"""Exception for a serious error in NetworkX"""</span></div> <div class="viewcode-block" id="NetworkXPointlessConcept"><a class="viewcode-back" href="../../reference/exceptions.html#networkx.NetworkXPointlessConcept">[docs]</a><span class="k">class</span> <span class="nc">NetworkXPointlessConcept</span><span class="p">(</span><span class="n">NetworkXException</span><span class="p">):</span> - <span class="sd">"""Raised when a null graph is provided as input to an algorithm</span> +<span class="w"> </span><span class="sd">"""Raised when a null graph is provided as input to an algorithm</span> <span class="sd"> that cannot use it.</span> <span class="sd"> The null graph is sometimes considered a pointless concept [1]_,</span> @@ -512,46 +512,46 @@ <div class="viewcode-block" id="NetworkXAlgorithmError"><a class="viewcode-back" href="../../reference/exceptions.html#networkx.NetworkXAlgorithmError">[docs]</a><span class="k">class</span> <span class="nc">NetworkXAlgorithmError</span><span class="p">(</span><span class="n">NetworkXException</span><span class="p">):</span> - <span class="sd">"""Exception for unexpected termination of algorithms."""</span></div> +<span class="w"> </span><span class="sd">"""Exception for unexpected termination of algorithms."""</span></div> <div class="viewcode-block" id="NetworkXUnfeasible"><a class="viewcode-back" href="../../reference/exceptions.html#networkx.NetworkXUnfeasible">[docs]</a><span class="k">class</span> <span class="nc">NetworkXUnfeasible</span><span class="p">(</span><span class="n">NetworkXAlgorithmError</span><span class="p">):</span> - <span class="sd">"""Exception raised by algorithms trying to solve a problem</span> +<span class="w"> </span><span class="sd">"""Exception raised by algorithms trying to solve a problem</span> <span class="sd"> instance that has no feasible solution."""</span></div> <div class="viewcode-block" id="NetworkXNoPath"><a class="viewcode-back" href="../../reference/exceptions.html#networkx.NetworkXNoPath">[docs]</a><span class="k">class</span> <span class="nc">NetworkXNoPath</span><span class="p">(</span><span class="n">NetworkXUnfeasible</span><span class="p">):</span> - <span class="sd">"""Exception for algorithms that should return a path when running</span> +<span class="w"> </span><span class="sd">"""Exception for algorithms that should return a path when running</span> <span class="sd"> on graphs where such a path does not exist."""</span></div> <div class="viewcode-block" id="NetworkXNoCycle"><a class="viewcode-back" href="../../reference/exceptions.html#networkx.NetworkXNoCycle">[docs]</a><span class="k">class</span> <span class="nc">NetworkXNoCycle</span><span class="p">(</span><span class="n">NetworkXUnfeasible</span><span class="p">):</span> - <span class="sd">"""Exception for algorithms that should return a cycle when running</span> +<span class="w"> </span><span class="sd">"""Exception for algorithms that should return a cycle when running</span> <span class="sd"> on graphs where such a cycle does not exist."""</span></div> <div class="viewcode-block" id="HasACycle"><a class="viewcode-back" href="../../reference/exceptions.html#networkx.HasACycle">[docs]</a><span class="k">class</span> <span class="nc">HasACycle</span><span class="p">(</span><span class="n">NetworkXException</span><span class="p">):</span> - <span class="sd">"""Raised if a graph has a cycle when an algorithm expects that it</span> +<span class="w"> </span><span class="sd">"""Raised if a graph has a cycle when an algorithm expects that it</span> <span class="sd"> will have no cycles.</span> <span class="sd"> """</span></div> <div class="viewcode-block" id="NetworkXUnbounded"><a class="viewcode-back" href="../../reference/exceptions.html#networkx.NetworkXUnbounded">[docs]</a><span class="k">class</span> <span class="nc">NetworkXUnbounded</span><span class="p">(</span><span class="n">NetworkXAlgorithmError</span><span class="p">):</span> - <span class="sd">"""Exception raised by algorithms trying to solve a maximization</span> +<span class="w"> </span><span class="sd">"""Exception raised by algorithms trying to solve a maximization</span> <span class="sd"> or a minimization problem instance that is unbounded."""</span></div> <div class="viewcode-block" id="NetworkXNotImplemented"><a class="viewcode-back" href="../../reference/exceptions.html#networkx.NetworkXNotImplemented">[docs]</a><span class="k">class</span> <span class="nc">NetworkXNotImplemented</span><span class="p">(</span><span class="n">NetworkXException</span><span class="p">):</span> - <span class="sd">"""Exception raised by algorithms not implemented for a type of graph."""</span></div> +<span class="w"> </span><span class="sd">"""Exception raised by algorithms not implemented for a type of graph."""</span></div> <div class="viewcode-block" id="NodeNotFound"><a class="viewcode-back" href="../../reference/exceptions.html#networkx.NodeNotFound">[docs]</a><span class="k">class</span> <span class="nc">NodeNotFound</span><span class="p">(</span><span class="n">NetworkXException</span><span class="p">):</span> - <span class="sd">"""Exception raised if requested node is not present in the graph"""</span></div> +<span class="w"> </span><span class="sd">"""Exception raised if requested node is not present in the graph"""</span></div> <div class="viewcode-block" id="AmbiguousSolution"><a class="viewcode-back" href="../../reference/exceptions.html#networkx.AmbiguousSolution">[docs]</a><span class="k">class</span> <span class="nc">AmbiguousSolution</span><span class="p">(</span><span class="n">NetworkXException</span><span class="p">):</span> - <span class="sd">"""Raised if more than one valid solution exists for an intermediary step</span> +<span class="w"> </span><span class="sd">"""Raised if more than one valid solution exists for an intermediary step</span> <span class="sd"> of an algorithm.</span> <span class="sd"> In the face of ambiguity, refuse the temptation to guess.</span> @@ -563,7 +563,7 @@ <div class="viewcode-block" id="ExceededMaxIterations"><a class="viewcode-back" href="../../reference/exceptions.html#networkx.ExceededMaxIterations">[docs]</a><span class="k">class</span> <span class="nc">ExceededMaxIterations</span><span class="p">(</span><span class="n">NetworkXException</span><span class="p">):</span> - <span class="sd">"""Raised if a loop iterates too many times without breaking.</span> +<span class="w"> </span><span class="sd">"""Raised if a loop iterates too many times without breaking.</span> <span class="sd"> This may occur, for example, in an algorithm that computes</span> <span class="sd"> progressively better approximations to a value but exceeds an</span> @@ -573,7 +573,7 @@ <div class="viewcode-block" id="PowerIterationFailedConvergence"><a class="viewcode-back" href="../../reference/exceptions.html#networkx.PowerIterationFailedConvergence">[docs]</a><span class="k">class</span> <span class="nc">PowerIterationFailedConvergence</span><span class="p">(</span><span class="n">ExceededMaxIterations</span><span class="p">):</span> - <span class="sd">"""Raised when the power iteration method fails to converge within a</span> +<span class="w"> </span><span class="sd">"""Raised when the power iteration method fails to converge within a</span> <span class="sd"> specified iteration limit.</span> <span class="sd"> `num_iterations` is the number of iterations that have been</span> @@ -637,7 +637,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/atlas.html b/_modules/networkx/generators/atlas.html index 3edd4853..400416be 100644 --- a/_modules/networkx/generators/atlas.html +++ b/_modules/networkx/generators/atlas.html @@ -518,7 +518,7 @@ <span class="k">def</span> <span class="nf">_generate_graphs</span><span class="p">():</span> - <span class="sd">"""Sequentially read the file containing the edge list data for the</span> +<span class="w"> </span><span class="sd">"""Sequentially read the file containing the edge list data for the</span> <span class="sd"> graphs in the atlas and generate the graphs one at a time.</span> <span class="sd"> This function reads the file given in :data:`.ATLAS_FILE`.</span> @@ -552,7 +552,7 @@ <div class="viewcode-block" id="graph_atlas"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.atlas.graph_atlas.html#networkx.generators.atlas.graph_atlas">[docs]</a><span class="k">def</span> <span class="nf">graph_atlas</span><span class="p">(</span><span class="n">i</span><span class="p">):</span> - <span class="sd">"""Returns graph number `i` from the Graph Atlas.</span> +<span class="w"> </span><span class="sd">"""Returns graph number `i` from the Graph Atlas.</span> <span class="sd"> For more information, see :func:`.graph_atlas_g`.</span> @@ -590,7 +590,7 @@ <div class="viewcode-block" id="graph_atlas_g"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.atlas.graph_atlas_g.html#networkx.generators.atlas.graph_atlas_g">[docs]</a><span class="k">def</span> <span class="nf">graph_atlas_g</span><span class="p">():</span> - <span class="sd">"""Returns the list of all graphs with up to seven nodes named in the</span> +<span class="w"> </span><span class="sd">"""Returns the list of all graphs with up to seven nodes named in the</span> <span class="sd"> Graph Atlas.</span> <span class="sd"> The graphs are listed in increasing order by</span> @@ -689,7 +689,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/classic.html b/_modules/networkx/generators/classic.html index bd5d97aa..f95736b0 100644 --- a/_modules/networkx/generators/classic.html +++ b/_modules/networkx/generators/classic.html @@ -528,7 +528,7 @@ <div class="viewcode-block" id="full_rary_tree"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.full_rary_tree.html#networkx.generators.classic.full_rary_tree">[docs]</a><span class="k">def</span> <span class="nf">full_rary_tree</span><span class="p">(</span><span class="n">r</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Creates a full r-ary tree of `n` nodes.</span> +<span class="w"> </span><span class="sd">"""Creates a full r-ary tree of `n` nodes.</span> <span class="sd"> Sometimes called a k-ary, n-ary, or m-ary tree.</span> <span class="sd"> "... all non-leaf nodes have exactly r children and all levels</span> @@ -561,7 +561,7 @@ <div class="viewcode-block" id="balanced_tree"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.balanced_tree.html#networkx.generators.classic.balanced_tree">[docs]</a><span class="k">def</span> <span class="nf">balanced_tree</span><span class="p">(</span><span class="n">r</span><span class="p">,</span> <span class="n">h</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the perfectly balanced `r`-ary tree of height `h`.</span> +<span class="w"> </span><span class="sd">"""Returns the perfectly balanced `r`-ary tree of height `h`.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -606,7 +606,7 @@ <div class="viewcode-block" id="barbell_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.barbell_graph.html#networkx.generators.classic.barbell_graph">[docs]</a><span class="k">def</span> <span class="nf">barbell_graph</span><span class="p">(</span><span class="n">m1</span><span class="p">,</span> <span class="n">m2</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the Barbell Graph: two complete graphs connected by a path.</span> +<span class="w"> </span><span class="sd">"""Returns the Barbell Graph: two complete graphs connected by a path.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -674,7 +674,7 @@ <div class="viewcode-block" id="binomial_tree"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.binomial_tree.html#networkx.generators.classic.binomial_tree">[docs]</a><span class="k">def</span> <span class="nf">binomial_tree</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the Binomial Tree of order n.</span> +<span class="w"> </span><span class="sd">"""Returns the Binomial Tree of order n.</span> <span class="sd"> The binomial tree of order 0 consists of a single node. A binomial tree of order k</span> <span class="sd"> is defined recursively by linking two binomial trees of order k-1: the root of one is</span> @@ -708,7 +708,7 @@ <div class="viewcode-block" id="complete_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.complete_graph.html#networkx.generators.classic.complete_graph">[docs]</a><span class="nd">@nodes_or_number</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="k">def</span> <span class="nf">complete_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Return the complete graph `K_n` with n nodes.</span> +<span class="w"> </span><span class="sd">"""Return the complete graph `K_n` with n nodes.</span> <span class="sd"> A complete graph on `n` nodes means that all pairs</span> <span class="sd"> of distinct nodes have an edge connecting them.</span> @@ -750,7 +750,7 @@ <div class="viewcode-block" id="circular_ladder_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.circular_ladder_graph.html#networkx.generators.classic.circular_ladder_graph">[docs]</a><span class="k">def</span> <span class="nf">circular_ladder_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the circular ladder graph $CL_n$ of length n.</span> +<span class="w"> </span><span class="sd">"""Returns the circular ladder graph $CL_n$ of length n.</span> <span class="sd"> $CL_n$ consists of two concentric n-cycles in which</span> <span class="sd"> each of the n pairs of concentric nodes are joined by an edge.</span> @@ -765,7 +765,7 @@ <div class="viewcode-block" id="circulant_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.circulant_graph.html#networkx.generators.classic.circulant_graph">[docs]</a><span class="k">def</span> <span class="nf">circulant_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">offsets</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the circulant graph $Ci_n(x_1, x_2, ..., x_m)$ with $n$ nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the circulant graph $Ci_n(x_1, x_2, ..., x_m)$ with $n$ nodes.</span> <span class="sd"> The circulant graph $Ci_n(x_1, ..., x_m)$ consists of $n$ nodes $0, ..., n-1$</span> <span class="sd"> such that node $i$ is connected to nodes $(i + x) \mod n$ and $(i - x) \mod n$</span> @@ -838,7 +838,7 @@ <div class="viewcode-block" id="cycle_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.cycle_graph.html#networkx.generators.classic.cycle_graph">[docs]</a><span class="nd">@nodes_or_number</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="k">def</span> <span class="nf">cycle_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the cycle graph $C_n$ of cyclically connected nodes.</span> +<span class="w"> </span><span class="sd">"""Returns the cycle graph $C_n$ of cyclically connected nodes.</span> <span class="sd"> $C_n$ is a path with its two end-nodes connected.</span> @@ -864,7 +864,7 @@ <div class="viewcode-block" id="dorogovtsev_goltsev_mendes_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.dorogovtsev_goltsev_mendes_graph.html#networkx.generators.classic.dorogovtsev_goltsev_mendes_graph">[docs]</a><span class="k">def</span> <span class="nf">dorogovtsev_goltsev_mendes_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the hierarchically constructed Dorogovtsev-Goltsev-Mendes graph.</span> +<span class="w"> </span><span class="sd">"""Returns the hierarchically constructed Dorogovtsev-Goltsev-Mendes graph.</span> <span class="sd"> n is the generation.</span> <span class="sd"> See: arXiv:/cond-mat/0112143 by Dorogovtsev, Goltsev and Mendes.</span> @@ -892,7 +892,7 @@ <div class="viewcode-block" id="empty_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.empty_graph.html#networkx.generators.classic.empty_graph">[docs]</a><span class="nd">@nodes_or_number</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="k">def</span> <span class="nf">empty_graph</span><span class="p">(</span><span class="n">n</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="n">Graph</span><span class="p">):</span> - <span class="sd">"""Returns the empty graph with n nodes and zero edges.</span> +<span class="w"> </span><span class="sd">"""Returns the empty graph with n nodes and zero edges.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -985,7 +985,7 @@ <div class="viewcode-block" id="ladder_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.ladder_graph.html#networkx.generators.classic.ladder_graph">[docs]</a><span class="k">def</span> <span class="nf">ladder_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the Ladder graph of length n.</span> +<span class="w"> </span><span class="sd">"""Returns the Ladder graph of length n.</span> <span class="sd"> This is two paths of n nodes, with</span> <span class="sd"> each pair connected by a single edge.</span> @@ -1004,7 +1004,7 @@ <div class="viewcode-block" id="lollipop_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.lollipop_graph.html#networkx.generators.classic.lollipop_graph">[docs]</a><span class="nd">@nodes_or_number</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span> <span class="k">def</span> <span class="nf">lollipop_graph</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the Lollipop Graph; `K_m` connected to `P_n`.</span> +<span class="w"> </span><span class="sd">"""Returns the Lollipop Graph; `K_m` connected to `P_n`.</span> <span class="sd"> This is the Barbell Graph without the right barbell.</span> @@ -1060,7 +1060,7 @@ <div class="viewcode-block" id="null_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.null_graph.html#networkx.generators.classic.null_graph">[docs]</a><span class="k">def</span> <span class="nf">null_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the Null graph with no nodes or edges.</span> +<span class="w"> </span><span class="sd">"""Returns the Null graph with no nodes or edges.</span> <span class="sd"> See empty_graph for the use of create_using.</span> @@ -1071,7 +1071,7 @@ <div class="viewcode-block" id="path_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.path_graph.html#networkx.generators.classic.path_graph">[docs]</a><span class="nd">@nodes_or_number</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="k">def</span> <span class="nf">path_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the Path graph `P_n` of linearly connected nodes.</span> +<span class="w"> </span><span class="sd">"""Returns the Path graph `P_n` of linearly connected nodes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1092,7 +1092,7 @@ <div class="viewcode-block" id="star_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.star_graph.html#networkx.generators.classic.star_graph">[docs]</a><span class="nd">@nodes_or_number</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="k">def</span> <span class="nf">star_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Return the star graph</span> +<span class="w"> </span><span class="sd">"""Return the star graph</span> <span class="sd"> The star graph consists of one center node connected to n outer nodes.</span> @@ -1125,13 +1125,13 @@ <div class="viewcode-block" id="trivial_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.trivial_graph.html#networkx.generators.classic.trivial_graph">[docs]</a><span class="k">def</span> <span class="nf">trivial_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Return the Trivial graph with one node (with label 0) and no edges."""</span> +<span class="w"> </span><span class="sd">"""Return the Trivial graph with one node (with label 0) and no edges."""</span> <span class="n">G</span> <span class="o">=</span> <span class="n">empty_graph</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">create_using</span><span class="p">)</span> <span class="k">return</span> <span class="n">G</span></div> <div class="viewcode-block" id="turan_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.turan_graph.html#networkx.generators.classic.turan_graph">[docs]</a><span class="k">def</span> <span class="nf">turan_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">r</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Return the Turan Graph</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Return the Turan Graph</span> <span class="sd"> The Turan Graph is a complete multipartite graph on $n$ nodes</span> <span class="sd"> with $r$ disjoint subsets. That is, edges connect each node to</span> @@ -1165,7 +1165,7 @@ <div class="viewcode-block" id="wheel_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.wheel_graph.html#networkx.generators.classic.wheel_graph">[docs]</a><span class="nd">@nodes_or_number</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="k">def</span> <span class="nf">wheel_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Return the wheel graph</span> +<span class="w"> </span><span class="sd">"""Return the wheel graph</span> <span class="sd"> The wheel graph consists of a hub node connected to a cycle of (n-1) nodes.</span> @@ -1195,7 +1195,7 @@ <div class="viewcode-block" id="complete_multipartite_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.classic.complete_multipartite_graph.html#networkx.generators.classic.complete_multipartite_graph">[docs]</a><span class="k">def</span> <span class="nf">complete_multipartite_graph</span><span class="p">(</span><span class="o">*</span><span class="n">subset_sizes</span><span class="p">):</span> - <span class="sd">"""Returns the complete multipartite graph with the specified subset sizes.</span> +<span class="w"> </span><span class="sd">"""Returns the complete multipartite graph with the specified subset sizes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1326,7 +1326,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/cographs.html b/_modules/networkx/generators/cographs.html index a3586e90..0eec65f1 100644 --- a/_modules/networkx/generators/cographs.html +++ b/_modules/networkx/generators/cographs.html @@ -482,7 +482,7 @@ <div class="viewcode-block" id="random_cograph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.cographs.random_cograph.html#networkx.generators.cographs.random_cograph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_cograph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a random cograph with $2 ^ n$ nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a random cograph with $2 ^ n$ nodes.</span> <span class="sd"> A cograph is a graph containing no path on four vertices.</span> <span class="sd"> Cographs or $P_4$-free graphs can be obtained from a single vertex</span> @@ -578,7 +578,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/community.html b/_modules/networkx/generators/community.html index 275fe412..f85e1e9c 100644 --- a/_modules/networkx/generators/community.html +++ b/_modules/networkx/generators/community.html @@ -483,7 +483,7 @@ <div class="viewcode-block" id="caveman_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.community.caveman_graph.html#networkx.generators.community.caveman_graph">[docs]</a><span class="k">def</span> <span class="nf">caveman_graph</span><span class="p">(</span><span class="n">l</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> - <span class="sd">"""Returns a caveman graph of `l` cliques of size `k`.</span> +<span class="w"> </span><span class="sd">"""Returns a caveman graph of `l` cliques of size `k`.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -529,7 +529,7 @@ <div class="viewcode-block" id="connected_caveman_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.community.connected_caveman_graph.html#networkx.generators.community.connected_caveman_graph">[docs]</a><span class="k">def</span> <span class="nf">connected_caveman_graph</span><span class="p">(</span><span class="n">l</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> - <span class="sd">"""Returns a connected caveman graph of `l` cliques of size `k`.</span> +<span class="w"> </span><span class="sd">"""Returns a connected caveman graph of `l` cliques of size `k`.</span> <span class="sd"> The connected caveman graph is formed by creating `n` cliques of size</span> <span class="sd"> `k`, then a single edge in each clique is rewired to a node in an</span> @@ -583,7 +583,7 @@ <div class="viewcode-block" id="relaxed_caveman_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.community.relaxed_caveman_graph.html#networkx.generators.community.relaxed_caveman_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">relaxed_caveman_graph</span><span class="p">(</span><span class="n">l</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a relaxed caveman graph.</span> +<span class="w"> </span><span class="sd">"""Returns a relaxed caveman graph.</span> <span class="sd"> A relaxed caveman graph starts with `l` cliques of size `k`. Edges are</span> <span class="sd"> then randomly rewired with probability `p` to link different cliques.</span> @@ -634,7 +634,7 @@ <div class="viewcode-block" id="random_partition_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.community.random_partition_graph.html#networkx.generators.community.random_partition_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_partition_graph</span><span class="p">(</span><span class="n">sizes</span><span class="p">,</span> <span class="n">p_in</span><span class="p">,</span> <span class="n">p_out</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">directed</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns the random partition graph with a partition of sizes.</span> +<span class="w"> </span><span class="sd">"""Returns the random partition graph with a partition of sizes.</span> <span class="sd"> A partition graph is a graph of communities with sizes defined by</span> <span class="sd"> s in sizes. Nodes in the same group are connected with probability</span> @@ -712,7 +712,7 @@ <div class="viewcode-block" id="planted_partition_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.community.planted_partition_graph.html#networkx.generators.community.planted_partition_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="k">def</span> <span class="nf">planted_partition_graph</span><span class="p">(</span><span class="n">l</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">p_in</span><span class="p">,</span> <span class="n">p_out</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">directed</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns the planted l-partition graph.</span> +<span class="w"> </span><span class="sd">"""Returns the planted l-partition graph.</span> <span class="sd"> This model partitions a graph with n=l*k vertices in</span> <span class="sd"> l groups with k vertices each. Vertices of the same</span> @@ -767,7 +767,7 @@ <div class="viewcode-block" id="gaussian_random_partition_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.community.gaussian_random_partition_graph.html#networkx.generators.community.gaussian_random_partition_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">6</span><span class="p">)</span> <span class="k">def</span> <span class="nf">gaussian_random_partition_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">p_in</span><span class="p">,</span> <span class="n">p_out</span><span class="p">,</span> <span class="n">directed</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Generate a Gaussian random partition graph.</span> +<span class="w"> </span><span class="sd">"""Generate a Gaussian random partition graph.</span> <span class="sd"> A Gaussian random partition graph is created by creating k partitions</span> <span class="sd"> each with a size drawn from a normal distribution with mean s and variance</span> @@ -842,7 +842,7 @@ <div class="viewcode-block" id="ring_of_cliques"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.community.ring_of_cliques.html#networkx.generators.community.ring_of_cliques">[docs]</a><span class="k">def</span> <span class="nf">ring_of_cliques</span><span class="p">(</span><span class="n">num_cliques</span><span class="p">,</span> <span class="n">clique_size</span><span class="p">):</span> - <span class="sd">"""Defines a "ring of cliques" graph.</span> +<span class="w"> </span><span class="sd">"""Defines a "ring of cliques" graph.</span> <span class="sd"> A ring of cliques graph is consisting of cliques, connected through single</span> <span class="sd"> links. Each clique is a complete graph.</span> @@ -897,7 +897,7 @@ <div class="viewcode-block" id="windmill_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.community.windmill_graph.html#networkx.generators.community.windmill_graph">[docs]</a><span class="k">def</span> <span class="nf">windmill_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span> - <span class="sd">"""Generate a windmill graph.</span> +<span class="w"> </span><span class="sd">"""Generate a windmill graph.</span> <span class="sd"> A windmill graph is a graph of `n` cliques each of size `k` that are all</span> <span class="sd"> joined at one node.</span> <span class="sd"> It can be thought of as taking a disjoint union of `n` cliques of size `k`,</span> @@ -952,7 +952,7 @@ <span class="k">def</span> <span class="nf">stochastic_block_model</span><span class="p">(</span> <span class="n">sizes</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">directed</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">selfloops</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">sparse</span><span class="o">=</span><span class="kc">True</span> <span class="p">):</span> - <span class="sd">"""Returns a stochastic block model graph.</span> +<span class="w"> </span><span class="sd">"""Returns a stochastic block model graph.</span> <span class="sd"> This model partitions the nodes in blocks of arbitrary sizes, and places</span> <span class="sd"> edges between pairs of nodes independently, with a probability that depends</span> @@ -1118,7 +1118,7 @@ <span class="k">def</span> <span class="nf">_zipf_rv_below</span><span class="p">(</span><span class="n">gamma</span><span class="p">,</span> <span class="n">xmin</span><span class="p">,</span> <span class="n">threshold</span><span class="p">,</span> <span class="n">seed</span><span class="p">):</span> - <span class="sd">"""Returns a random value chosen from the bounded Zipf distribution.</span> +<span class="w"> </span><span class="sd">"""Returns a random value chosen from the bounded Zipf distribution.</span> <span class="sd"> Repeatedly draws values from the Zipf distribution until the</span> <span class="sd"> threshold is met, then returns that value.</span> @@ -1130,7 +1130,7 @@ <span class="k">def</span> <span class="nf">_powerlaw_sequence</span><span class="p">(</span><span class="n">gamma</span><span class="p">,</span> <span class="n">low</span><span class="p">,</span> <span class="n">high</span><span class="p">,</span> <span class="n">condition</span><span class="p">,</span> <span class="n">length</span><span class="p">,</span> <span class="n">max_iters</span><span class="p">,</span> <span class="n">seed</span><span class="p">):</span> - <span class="sd">"""Returns a list of numbers obeying a constrained power law distribution.</span> +<span class="w"> </span><span class="sd">"""Returns a list of numbers obeying a constrained power law distribution.</span> <span class="sd"> ``gamma`` and ``low`` are the parameters for the Zipf distribution.</span> @@ -1161,7 +1161,7 @@ <span class="k">def</span> <span class="nf">_hurwitz_zeta</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">q</span><span class="p">,</span> <span class="n">tolerance</span><span class="p">):</span> - <span class="sd">"""The Hurwitz zeta function, or the Riemann zeta function of two arguments.</span> +<span class="w"> </span><span class="sd">"""The Hurwitz zeta function, or the Riemann zeta function of two arguments.</span> <span class="sd"> ``x`` must be greater than one and ``q`` must be positive.</span> @@ -1179,7 +1179,7 @@ <span class="k">def</span> <span class="nf">_generate_min_degree</span><span class="p">(</span><span class="n">gamma</span><span class="p">,</span> <span class="n">average_degree</span><span class="p">,</span> <span class="n">max_degree</span><span class="p">,</span> <span class="n">tolerance</span><span class="p">,</span> <span class="n">max_iters</span><span class="p">):</span> - <span class="sd">"""Returns a minimum degree from the given average degree."""</span> +<span class="w"> </span><span class="sd">"""Returns a minimum degree from the given average degree."""</span> <span class="c1"># Defines zeta function whether or not Scipy is available</span> <span class="k">try</span><span class="p">:</span> <span class="kn">from</span> <span class="nn">scipy.special</span> <span class="kn">import</span> <span class="n">zeta</span> @@ -1211,7 +1211,7 @@ <span class="k">def</span> <span class="nf">_generate_communities</span><span class="p">(</span><span class="n">degree_seq</span><span class="p">,</span> <span class="n">community_sizes</span><span class="p">,</span> <span class="n">mu</span><span class="p">,</span> <span class="n">max_iters</span><span class="p">,</span> <span class="n">seed</span><span class="p">):</span> - <span class="sd">"""Returns a list of sets, each of which represents a community.</span> +<span class="w"> </span><span class="sd">"""Returns a list of sets, each of which represents a community.</span> <span class="sd"> ``degree_seq`` is the degree sequence that must be met by the</span> <span class="sd"> graph.</span> @@ -1276,7 +1276,7 @@ <span class="n">max_iters</span><span class="o">=</span><span class="mi">500</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the LFR benchmark graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the LFR benchmark graph.</span> <span class="sd"> This algorithm proceeds as follows:</span> @@ -1573,7 +1573,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/degree_seq.html b/_modules/networkx/generators/degree_seq.html index 71c51514..7ab8faa5 100644 --- a/_modules/networkx/generators/degree_seq.html +++ b/_modules/networkx/generators/degree_seq.html @@ -486,7 +486,7 @@ <span class="k">def</span> <span class="nf">_to_stublist</span><span class="p">(</span><span class="n">degree_sequence</span><span class="p">):</span> - <span class="sd">"""Returns a list of degree-repeated node numbers.</span> +<span class="w"> </span><span class="sd">"""Returns a list of degree-repeated node numbers.</span> <span class="sd"> ``degree_sequence`` is a list of nonnegative integers representing</span> <span class="sd"> the degrees of nodes in a graph.</span> @@ -520,7 +520,7 @@ <span class="k">def</span> <span class="nf">_configuration_model</span><span class="p">(</span> <span class="n">deg_sequence</span><span class="p">,</span> <span class="n">create_using</span><span class="p">,</span> <span class="n">directed</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">in_deg_sequence</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Helper function for generating either undirected or directed</span> +<span class="w"> </span><span class="sd">"""Helper function for generating either undirected or directed</span> <span class="sd"> configuration model graphs.</span> <span class="sd"> ``deg_sequence`` is a list of nonnegative integers representing the</span> @@ -588,7 +588,7 @@ <div class="viewcode-block" id="configuration_model"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.degree_seq.configuration_model.html#networkx.generators.degree_seq.configuration_model">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">configuration_model</span><span class="p">(</span><span class="n">deg_sequence</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a random graph with the given degree sequence.</span> +<span class="w"> </span><span class="sd">"""Returns a random graph with the given degree sequence.</span> <span class="sd"> The configuration model generates a random pseudograph (graph with</span> <span class="sd"> parallel edges and self loops) by randomly assigning edges to</span> @@ -692,7 +692,7 @@ <span class="k">def</span> <span class="nf">directed_configuration_model</span><span class="p">(</span> <span class="n">in_degree_sequence</span><span class="p">,</span> <span class="n">out_degree_sequence</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Returns a directed_random graph with the given degree sequences.</span> +<span class="w"> </span><span class="sd">"""Returns a directed_random graph with the given degree sequences.</span> <span class="sd"> The configuration model generates a random directed pseudograph</span> <span class="sd"> (graph with parallel edges and self loops) by randomly assigning</span> @@ -792,7 +792,7 @@ <div class="viewcode-block" id="expected_degree_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.degree_seq.expected_degree_graph.html#networkx.generators.degree_seq.expected_degree_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="k">def</span> <span class="nf">expected_degree_graph</span><span class="p">(</span><span class="n">w</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">selfloops</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a random graph with given expected degrees.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a random graph with given expected degrees.</span> <span class="sd"> Given a sequence of expected degrees $W=(w_0,w_1,\ldots,w_{n-1})$</span> <span class="sd"> of length $n$ this algorithm assigns an edge between node $u$ and</span> @@ -900,7 +900,7 @@ <div class="viewcode-block" id="havel_hakimi_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.degree_seq.havel_hakimi_graph.html#networkx.generators.degree_seq.havel_hakimi_graph">[docs]</a><span class="k">def</span> <span class="nf">havel_hakimi_graph</span><span class="p">(</span><span class="n">deg_sequence</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a simple graph with given degree sequence constructed</span> +<span class="w"> </span><span class="sd">"""Returns a simple graph with given degree sequence constructed</span> <span class="sd"> using the Havel-Hakimi algorithm.</span> <span class="sd"> Parameters</span> @@ -992,7 +992,7 @@ <div class="viewcode-block" id="directed_havel_hakimi_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.degree_seq.directed_havel_hakimi_graph.html#networkx.generators.degree_seq.directed_havel_hakimi_graph">[docs]</a><span class="k">def</span> <span class="nf">directed_havel_hakimi_graph</span><span class="p">(</span><span class="n">in_deg_sequence</span><span class="p">,</span> <span class="n">out_deg_sequence</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a directed graph with the given degree sequences.</span> +<span class="w"> </span><span class="sd">"""Returns a directed graph with the given degree sequences.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1103,7 +1103,7 @@ <div class="viewcode-block" id="degree_sequence_tree"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.degree_seq.degree_sequence_tree.html#networkx.generators.degree_seq.degree_sequence_tree">[docs]</a><span class="k">def</span> <span class="nf">degree_sequence_tree</span><span class="p">(</span><span class="n">deg_sequence</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Make a tree for the given degree sequence.</span> +<span class="w"> </span><span class="sd">"""Make a tree for the given degree sequence.</span> <span class="sd"> A tree has #nodes-#edges=1 so</span> <span class="sd"> the degree sequence must have</span> @@ -1149,7 +1149,7 @@ <div class="viewcode-block" id="random_degree_sequence_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.degree_seq.random_degree_sequence_graph.html#networkx.generators.degree_seq.random_degree_sequence_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_degree_sequence_graph</span><span class="p">(</span><span class="n">sequence</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">tries</span><span class="o">=</span><span class="mi">10</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a simple random graph with the given degree sequence.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a simple random graph with the given degree sequence.</span> <span class="sd"> If the maximum degree $d_m$ in the sequence is $O(m^{1/4})$ then the</span> <span class="sd"> algorithm produces almost uniform random graphs in $O(m d_m)$ time</span> @@ -1270,7 +1270,7 @@ <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">remaining_degree</span><span class="p">[</span><span class="n">u</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">remaining_degree</span><span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="o">/</span> <span class="n">norm</span> <span class="k">def</span> <span class="nf">suitable_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Returns True if and only if an arbitrary remaining node can</span> +<span class="w"> </span><span class="sd">"""Returns True if and only if an arbitrary remaining node can</span> <span class="sd"> potentially be joined with some other remaining node.</span> <span class="sd"> """</span> @@ -1373,7 +1373,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/directed.html b/_modules/networkx/generators/directed.html index ee55d446..eeb82d95 100644 --- a/_modules/networkx/generators/directed.html +++ b/_modules/networkx/generators/directed.html @@ -485,7 +485,7 @@ <div class="viewcode-block" id="gn_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.directed.gn_graph.html#networkx.generators.directed.gn_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">gn_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">kernel</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the growing network (GN) digraph with `n` nodes.</span> +<span class="w"> </span><span class="sd">"""Returns the growing network (GN) digraph with `n` nodes.</span> <span class="sd"> The GN graph is built by adding nodes one at a time with a link to one</span> <span class="sd"> previously added node. The target node for the link is chosen with</span> @@ -552,7 +552,7 @@ <div class="viewcode-block" id="gnr_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.directed.gnr_graph.html#networkx.generators.directed.gnr_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">gnr_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the growing network with redirection (GNR) digraph with `n`</span> +<span class="w"> </span><span class="sd">"""Returns the growing network with redirection (GNR) digraph with `n`</span> <span class="sd"> nodes and redirection probability `p`.</span> <span class="sd"> The GNR graph is built by adding nodes one at a time with a link to one</span> @@ -605,7 +605,7 @@ <div class="viewcode-block" id="gnc_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.directed.gnc_graph.html#networkx.generators.directed.gnc_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">gnc_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the growing network with copying (GNC) digraph with `n` nodes.</span> +<span class="w"> </span><span class="sd">"""Returns the growing network with copying (GNC) digraph with `n` nodes.</span> <span class="sd"> The GNC graph is built by adding nodes one at a time with a link to one</span> <span class="sd"> previously added node (chosen uniformly at random) and to all of that</span> @@ -654,7 +654,7 @@ <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">initial_graph</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns a scale-free directed graph.</span> +<span class="w"> </span><span class="sd">"""Returns a scale-free directed graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -829,7 +829,7 @@ <span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_uniform_k_out_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">self_loops</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">with_replacement</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a random `k`-out graph with uniform attachment.</span> +<span class="w"> </span><span class="sd">"""Returns a random `k`-out graph with uniform attachment.</span> <span class="sd"> A random `k`-out graph with uniform attachment is a multidigraph</span> <span class="sd"> generated by the following algorithm. For each node *u*, choose</span> @@ -909,7 +909,7 @@ <div class="viewcode-block" id="random_k_out_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.directed.random_k_out_graph.html#networkx.generators.directed.random_k_out_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_k_out_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">alpha</span><span class="p">,</span> <span class="n">self_loops</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a random `k`-out graph with preferential attachment.</span> +<span class="w"> </span><span class="sd">"""Returns a random `k`-out graph with preferential attachment.</span> <span class="sd"> A random `k`-out graph with preferential attachment is a</span> <span class="sd"> multidigraph generated by the following algorithm.</span> @@ -1042,7 +1042,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/duplication.html b/_modules/networkx/generators/duplication.html index 8bdbe166..870a9578 100644 --- a/_modules/networkx/generators/duplication.html +++ b/_modules/networkx/generators/duplication.html @@ -477,7 +477,7 @@ <div class="viewcode-block" id="partial_duplication_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.duplication.partial_duplication_graph.html#networkx.generators.duplication.partial_duplication_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="k">def</span> <span class="nf">partial_duplication_graph</span><span class="p">(</span><span class="n">N</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">q</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a random graph using the partial duplication model.</span> +<span class="w"> </span><span class="sd">"""Returns a random graph using the partial duplication model.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -551,7 +551,7 @@ <div class="viewcode-block" id="duplication_divergence_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.duplication.duplication_divergence_graph.html#networkx.generators.duplication.duplication_divergence_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">duplication_divergence_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns an undirected graph using the duplication-divergence model.</span> +<span class="w"> </span><span class="sd">"""Returns an undirected graph using the duplication-divergence model.</span> <span class="sd"> A graph of `n` nodes is created by duplicating the initial nodes</span> <span class="sd"> and retaining edges incident to the original nodes with a retention</span> @@ -673,7 +673,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/ego.html b/_modules/networkx/generators/ego.html index 3f67ebae..df2b7df6 100644 --- a/_modules/networkx/generators/ego.html +++ b/_modules/networkx/generators/ego.html @@ -471,7 +471,7 @@ <div class="viewcode-block" id="ego_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.ego.ego_graph.html#networkx.generators.ego.ego_graph">[docs]</a><span class="nd">@nx</span><span class="o">.</span><span class="n">_dispatch</span> <span class="k">def</span> <span class="nf">ego_graph</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">radius</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">center</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">undirected</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">distance</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns induced subgraph of neighbors centered at node n within</span> +<span class="w"> </span><span class="sd">"""Returns induced subgraph of neighbors centered at node n within</span> <span class="sd"> a given radius.</span> <span class="sd"> Parameters</span> @@ -577,7 +577,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/expanders.html b/_modules/networkx/generators/expanders.html index caf923b2..8b49e567 100644 --- a/_modules/networkx/generators/expanders.html +++ b/_modules/networkx/generators/expanders.html @@ -504,7 +504,7 @@ <span class="c1"># (x, (y + (2*x + 2)) % n),</span> <span class="c1">#</span> <div class="viewcode-block" id="margulis_gabber_galil_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.expanders.margulis_gabber_galil_graph.html#networkx.generators.expanders.margulis_gabber_galil_graph">[docs]</a><span class="k">def</span> <span class="nf">margulis_gabber_galil_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the Margulis-Gabber-Galil undirected MultiGraph on `n^2` nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the Margulis-Gabber-Galil undirected MultiGraph on `n^2` nodes.</span> <span class="sd"> The undirected MultiGraph is regular with degree `8`. Nodes are integer</span> <span class="sd"> pairs. The second-largest eigenvalue of the adjacency matrix of the graph</span> @@ -546,7 +546,7 @@ <div class="viewcode-block" id="chordal_cycle_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.expanders.chordal_cycle_graph.html#networkx.generators.expanders.chordal_cycle_graph">[docs]</a><span class="k">def</span> <span class="nf">chordal_cycle_graph</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the chordal cycle graph on `p` nodes.</span> +<span class="w"> </span><span class="sd">"""Returns the chordal cycle graph on `p` nodes.</span> <span class="sd"> The returned graph is a cycle graph on `p` nodes with chords joining each</span> <span class="sd"> vertex `x` to its inverse modulo `p`. This graph is a (mildly explicit)</span> @@ -609,7 +609,7 @@ <div class="viewcode-block" id="paley_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.expanders.paley_graph.html#networkx.generators.expanders.paley_graph">[docs]</a><span class="k">def</span> <span class="nf">paley_graph</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the Paley (p-1)/2-regular graph on p nodes.</span> +<span class="w"> </span><span class="sd">"""Returns the Paley (p-1)/2-regular graph on p nodes.</span> <span class="sd"> The returned graph is a graph on Z/pZ with edges between x and y</span> <span class="sd"> if and only if x-y is a nonzero square in Z/pZ.</span> @@ -715,7 +715,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/geometric.html b/_modules/networkx/generators/geometric.html index 77cfb9e2..69c901d6 100644 --- a/_modules/networkx/generators/geometric.html +++ b/_modules/networkx/generators/geometric.html @@ -483,7 +483,7 @@ <div class="viewcode-block" id="geometric_edges"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.geometric.geometric_edges.html#networkx.generators.geometric.geometric_edges">[docs]</a><span class="k">def</span> <span class="nf">geometric_edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">radius</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mi">2</span><span class="p">):</span> - <span class="sd">"""Returns edge list of node pairs within `radius` of each other.</span> +<span class="w"> </span><span class="sd">"""Returns edge list of node pairs within `radius` of each other.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -544,7 +544,7 @@ <span class="k">def</span> <span class="nf">_geometric_edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">radius</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mi">2</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Implements `geometric_edges` without input validation. See `geometric_edges`</span> <span class="sd"> for complete docstring.</span> <span class="sd"> """</span> @@ -571,7 +571,7 @@ <div class="viewcode-block" id="random_geometric_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.geometric.random_geometric_graph.html#networkx.generators.geometric.random_geometric_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_geometric_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">radius</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">pos</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a random geometric graph in the unit cube of dimensions `dim`.</span> +<span class="w"> </span><span class="sd">"""Returns a random geometric graph in the unit cube of dimensions `dim`.</span> <span class="sd"> The random geometric graph model places `n` nodes uniformly at</span> <span class="sd"> random in the unit cube. Two nodes are joined by an edge if the</span> @@ -661,7 +661,7 @@ <span class="k">def</span> <span class="nf">soft_random_geometric_graph</span><span class="p">(</span> <span class="n">n</span><span class="p">,</span> <span class="n">radius</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">pos</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">p_dist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a soft random geometric graph in the unit cube.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a soft random geometric graph in the unit cube.</span> <span class="sd"> The soft random geometric graph [1] model places `n` nodes uniformly at</span> <span class="sd"> random in the unit cube in dimension `dim`. Two nodes of distance, `dist`,</span> @@ -787,7 +787,7 @@ <span class="k">def</span> <span class="nf">geographical_threshold_graph</span><span class="p">(</span> <span class="n">n</span><span class="p">,</span> <span class="n">theta</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">pos</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">metric</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">p_dist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a geographical threshold graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a geographical threshold graph.</span> <span class="sd"> The geographical threshold graph model places $n$ nodes uniformly at</span> <span class="sd"> random in a rectangular domain. Each node $u$ is assigned a weight</span> @@ -937,7 +937,7 @@ <span class="k">def</span> <span class="nf">waxman_graph</span><span class="p">(</span> <span class="n">n</span><span class="p">,</span> <span class="n">beta</span><span class="o">=</span><span class="mf">0.4</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">L</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">domain</span><span class="o">=</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">metric</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a Waxman random graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a Waxman random graph.</span> <span class="sd"> The Waxman random graph model places `n` nodes uniformly at random</span> <span class="sd"> in a rectangular domain. Each pair of nodes at distance `d` is</span> @@ -1056,7 +1056,7 @@ <div class="viewcode-block" id="navigable_small_world_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.geometric.navigable_small_world_graph.html#networkx.generators.geometric.navigable_small_world_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span> <span class="k">def</span> <span class="nf">navigable_small_world_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">q</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">r</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a navigable small-world graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a navigable small-world graph.</span> <span class="sd"> A navigable small-world graph is a directed grid with additional long-range</span> <span class="sd"> connections that are chosen randomly.</span> @@ -1130,7 +1130,7 @@ <span class="k">def</span> <span class="nf">thresholded_random_geometric_graph</span><span class="p">(</span> <span class="n">n</span><span class="p">,</span> <span class="n">radius</span><span class="p">,</span> <span class="n">theta</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">pos</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a thresholded random geometric graph in the unit cube.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a thresholded random geometric graph in the unit cube.</span> <span class="sd"> The thresholded random geometric graph [1] model places `n` nodes</span> <span class="sd"> uniformly at random in the unit cube of dimensions `dim`. Each node</span> @@ -1298,7 +1298,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/harary_graph.html b/_modules/networkx/generators/harary_graph.html index 33e71290..d91f2b54 100644 --- a/_modules/networkx/generators/harary_graph.html +++ b/_modules/networkx/generators/harary_graph.html @@ -485,7 +485,7 @@ <div class="viewcode-block" id="hnm_harary_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.harary_graph.hnm_harary_graph.html#networkx.generators.harary_graph.hnm_harary_graph">[docs]</a><span class="k">def</span> <span class="nf">hnm_harary_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the Harary graph with given numbers of nodes and edges.</span> +<span class="w"> </span><span class="sd">"""Returns the Harary graph with given numbers of nodes and edges.</span> <span class="sd"> The Harary graph $H_{n,m}$ is the graph that maximizes node connectivity</span> <span class="sd"> with $n$ nodes and $m$ edges.</span> @@ -576,7 +576,7 @@ <div class="viewcode-block" id="hkn_harary_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.harary_graph.hkn_harary_graph.html#networkx.generators.harary_graph.hkn_harary_graph">[docs]</a><span class="k">def</span> <span class="nf">hkn_harary_graph</span><span class="p">(</span><span class="n">k</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the Harary graph with given node connectivity and node number.</span> +<span class="w"> </span><span class="sd">"""Returns the Harary graph with given node connectivity and node number.</span> <span class="sd"> The Harary graph $H_{k,n}$ is the graph that minimizes the number of</span> <span class="sd"> edges needed with given node connectivity $k$ and node number $n$.</span> @@ -709,7 +709,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/internet_as_graphs.html b/_modules/networkx/generators/internet_as_graphs.html index dc135f7b..2e48a8e1 100644 --- a/_modules/networkx/generators/internet_as_graphs.html +++ b/_modules/networkx/generators/internet_as_graphs.html @@ -470,7 +470,7 @@ <span class="k">def</span> <span class="nf">uniform_int_from_avg</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">seed</span><span class="p">):</span> - <span class="sd">"""Pick a random integer with uniform probability.</span> +<span class="w"> </span><span class="sd">"""Pick a random integer with uniform probability.</span> <span class="sd"> Returns a random integer uniformly taken from a distribution with</span> <span class="sd"> minimum value 'a' and average value 'm', X~U(a,b), E[X]=m, X in N where</span> @@ -497,7 +497,7 @@ <span class="k">def</span> <span class="nf">choose_pref_attach</span><span class="p">(</span><span class="n">degs</span><span class="p">,</span> <span class="n">seed</span><span class="p">):</span> - <span class="sd">"""Pick a random value, with a probability given by its weight.</span> +<span class="w"> </span><span class="sd">"""Pick a random value, with a probability given by its weight.</span> <span class="sd"> Returns a random choice among degs keys, each of which has a</span> <span class="sd"> probability proportional to the corresponding dictionary value.</span> @@ -532,10 +532,10 @@ <span class="k">class</span> <span class="nc">AS_graph_generator</span><span class="p">:</span> - <span class="sd">"""Generates random internet AS graphs."""</span> +<span class="w"> </span><span class="sd">"""Generates random internet AS graphs."""</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">seed</span><span class="p">):</span> - <span class="sd">"""Initializes variables. Immediate numbers are taken from [1].</span> +<span class="w"> </span><span class="sd">"""Initializes variables. Immediate numbers are taken from [1].</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -575,7 +575,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">t_c</span> <span class="o">=</span> <span class="mf">0.125</span> <span class="c1"># probability C's provider is T</span> <span class="k">def</span> <span class="nf">t_graph</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Generates the core mesh network of tier one nodes of a AS graph.</span> +<span class="w"> </span><span class="sd">"""Generates the core mesh network of tier one nodes of a AS graph.</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> @@ -603,7 +603,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">G</span><span class="o">.</span><span class="n">add_edge</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">j</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="n">kind</span><span class="p">,</span> <span class="n">customer</span><span class="o">=</span><span class="n">customer</span><span class="p">)</span> <span class="k">def</span> <span class="nf">choose_peer_pref_attach</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">node_list</span><span class="p">):</span> - <span class="sd">"""Pick a node with a probability weighted by its peer degree.</span> +<span class="w"> </span><span class="sd">"""Pick a node with a probability weighted by its peer degree.</span> <span class="sd"> Pick a node from node_list with preferential attachment</span> <span class="sd"> computed only on their peer degree</span> @@ -615,7 +615,7 @@ <span class="k">return</span> <span class="n">choose_pref_attach</span><span class="p">(</span><span class="n">d</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">seed</span><span class="p">)</span> <span class="k">def</span> <span class="nf">choose_node_pref_attach</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">node_list</span><span class="p">):</span> - <span class="sd">"""Pick a node with a probability weighted by its degree.</span> +<span class="w"> </span><span class="sd">"""Pick a node with a probability weighted by its degree.</span> <span class="sd"> Pick a node from node_list with preferential attachment</span> <span class="sd"> computed on their degree</span> @@ -625,7 +625,7 @@ <span class="k">return</span> <span class="n">choose_pref_attach</span><span class="p">(</span><span class="n">degs</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">seed</span><span class="p">)</span> <span class="k">def</span> <span class="nf">add_customer</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="n">j</span><span class="p">):</span> - <span class="sd">"""Keep the dictionaries 'customers' and 'providers' consistent."""</span> +<span class="w"> </span><span class="sd">"""Keep the dictionaries 'customers' and 'providers' consistent."""</span> <span class="bp">self</span><span class="o">.</span><span class="n">customers</span><span class="p">[</span><span class="n">j</span><span class="p">]</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="bp">self</span><span class="o">.</span><span class="n">providers</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">j</span><span class="p">)</span> @@ -634,7 +634,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">providers</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">z</span><span class="p">)</span> <span class="k">def</span> <span class="nf">add_node</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="n">kind</span><span class="p">,</span> <span class="n">reg2prob</span><span class="p">,</span> <span class="n">avg_deg</span><span class="p">,</span> <span class="n">t_edge_prob</span><span class="p">):</span> - <span class="sd">"""Add a node and its customer transit edges to the graph.</span> +<span class="w"> </span><span class="sd">"""Add a node and its customer transit edges to the graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -693,7 +693,7 @@ <span class="k">return</span> <span class="n">i</span> <span class="k">def</span> <span class="nf">add_m_peering_link</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">to_kind</span><span class="p">):</span> - <span class="sd">"""Add a peering link between two middle tier (M) nodes.</span> +<span class="w"> </span><span class="sd">"""Add a peering link between two middle tier (M) nodes.</span> <span class="sd"> Target node j is drawn considering a preferential attachment based on</span> <span class="sd"> other M node peering degree.</span> @@ -733,7 +733,7 @@ <span class="k">return</span> <span class="kc">False</span> <span class="k">def</span> <span class="nf">add_cp_peering_link</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">cp</span><span class="p">,</span> <span class="n">to_kind</span><span class="p">):</span> - <span class="sd">"""Add a peering link to a content provider (CP) node.</span> +<span class="w"> </span><span class="sd">"""Add a peering link to a content provider (CP) node.</span> <span class="sd"> Target node j can be CP or M and it is drawn uniformely among the nodes</span> <span class="sd"> belonging to the same region as cp.</span> @@ -780,7 +780,7 @@ <span class="k">return</span> <span class="kc">False</span> <span class="k">def</span> <span class="nf">graph_regions</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">rn</span><span class="p">):</span> - <span class="sd">"""Initializes AS network regions.</span> +<span class="w"> </span><span class="sd">"""Initializes AS network regions.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -793,7 +793,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">regions</span><span class="p">[</span><span class="s2">"REG"</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span> <span class="k">def</span> <span class="nf">add_peering_links</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">from_kind</span><span class="p">,</span> <span class="n">to_kind</span><span class="p">):</span> - <span class="sd">"""Utility function to add peering links among node groups."""</span> +<span class="w"> </span><span class="sd">"""Utility function to add peering links among node groups."""</span> <span class="n">peer_link_method</span> <span class="o">=</span> <span class="kc">None</span> <span class="k">if</span> <span class="n">from_kind</span> <span class="o">==</span> <span class="s2">"M"</span><span class="p">:</span> <span class="n">peer_link_method</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">add_m_peering_link</span> @@ -811,7 +811,7 @@ <span class="n">peer_link_method</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">to_kind</span><span class="p">)</span> <span class="k">def</span> <span class="nf">generate</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Generates a random AS network graph as described in [1].</span> +<span class="w"> </span><span class="sd">"""Generates a random AS network graph as described in [1].</span> <span class="sd"> Returns</span> <span class="sd"> -------</span> @@ -861,7 +861,7 @@ <div class="viewcode-block" id="random_internet_as_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.internet_as_graphs.random_internet_as_graph.html#networkx.generators.internet_as_graphs.random_internet_as_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_internet_as_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Generates a random undirected graph resembling the Internet AS network</span> +<span class="w"> </span><span class="sd">"""Generates a random undirected graph resembling the Internet AS network</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -952,7 +952,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/intersection.html b/_modules/networkx/generators/intersection.html index 36f200ef..620aaa6f 100644 --- a/_modules/networkx/generators/intersection.html +++ b/_modules/networkx/generators/intersection.html @@ -476,7 +476,7 @@ <div class="viewcode-block" id="uniform_random_intersection_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.intersection.uniform_random_intersection_graph.html#networkx.generators.intersection.uniform_random_intersection_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">uniform_random_intersection_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a uniform random intersection graph.</span> +<span class="w"> </span><span class="sd">"""Returns a uniform random intersection graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -511,7 +511,7 @@ <div class="viewcode-block" id="k_random_intersection_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.intersection.k_random_intersection_graph.html#networkx.generators.intersection.k_random_intersection_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">k_random_intersection_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a intersection graph with randomly chosen attribute sets for</span> +<span class="w"> </span><span class="sd">"""Returns a intersection graph with randomly chosen attribute sets for</span> <span class="sd"> each node that are of equal size (k).</span> <span class="sd"> Parameters</span> @@ -546,7 +546,7 @@ <div class="viewcode-block" id="general_random_intersection_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.intersection.general_random_intersection_graph.html#networkx.generators.intersection.general_random_intersection_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">general_random_intersection_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a random intersection graph with independent probabilities</span> +<span class="w"> </span><span class="sd">"""Returns a random intersection graph with independent probabilities</span> <span class="sd"> for connections between node and attribute sets.</span> <span class="sd"> Parameters</span> @@ -633,7 +633,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/interval_graph.html b/_modules/networkx/generators/interval_graph.html index 97f6eb6a..62b7c24f 100644 --- a/_modules/networkx/generators/interval_graph.html +++ b/_modules/networkx/generators/interval_graph.html @@ -472,7 +472,7 @@ <div class="viewcode-block" id="interval_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.interval_graph.interval_graph.html#networkx.generators.interval_graph.interval_graph">[docs]</a><span class="k">def</span> <span class="nf">interval_graph</span><span class="p">(</span><span class="n">intervals</span><span class="p">):</span> - <span class="sd">"""Generates an interval graph for a list of intervals given.</span> +<span class="w"> </span><span class="sd">"""Generates an interval graph for a list of intervals given.</span> <span class="sd"> In graph theory, an interval graph is an undirected graph formed from a set</span> <span class="sd"> of closed intervals on the real line, with a vertex for each interval</span> @@ -582,7 +582,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/joint_degree_seq.html b/_modules/networkx/generators/joint_degree_seq.html index 635746e9..d86e6d4a 100644 --- a/_modules/networkx/generators/joint_degree_seq.html +++ b/_modules/networkx/generators/joint_degree_seq.html @@ -475,7 +475,7 @@ <div class="viewcode-block" id="is_valid_joint_degree"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.joint_degree_seq.is_valid_joint_degree.html#networkx.generators.joint_degree_seq.is_valid_joint_degree">[docs]</a><span class="k">def</span> <span class="nf">is_valid_joint_degree</span><span class="p">(</span><span class="n">joint_degrees</span><span class="p">):</span> - <span class="sd">"""Checks whether the given joint degree dictionary is realizable.</span> +<span class="w"> </span><span class="sd">"""Checks whether the given joint degree dictionary is realizable.</span> <span class="sd"> A *joint degree dictionary* is a dictionary of dictionaries, in</span> <span class="sd"> which entry ``joint_degrees[k][l]`` is an integer representing the</span> @@ -541,7 +541,7 @@ <span class="k">def</span> <span class="nf">_neighbor_switch</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">w</span><span class="p">,</span> <span class="n">unsat</span><span class="p">,</span> <span class="n">h_node_residual</span><span class="p">,</span> <span class="n">avoid_node_id</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Releases one free stub for ``w``, while preserving joint degree in G.</span> +<span class="w"> </span><span class="sd">"""Releases one free stub for ``w``, while preserving joint degree in G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -605,7 +605,7 @@ <div class="viewcode-block" id="joint_degree_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.joint_degree_seq.joint_degree_graph.html#networkx.generators.joint_degree_seq.joint_degree_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="k">def</span> <span class="nf">joint_degree_graph</span><span class="p">(</span><span class="n">joint_degrees</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Generates a random simple graph with the given joint degree dictionary.</span> +<span class="w"> </span><span class="sd">"""Generates a random simple graph with the given joint degree dictionary.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -751,7 +751,7 @@ <div class="viewcode-block" id="is_valid_directed_joint_degree"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.joint_degree_seq.is_valid_directed_joint_degree.html#networkx.generators.joint_degree_seq.is_valid_directed_joint_degree">[docs]</a><span class="k">def</span> <span class="nf">is_valid_directed_joint_degree</span><span class="p">(</span><span class="n">in_degrees</span><span class="p">,</span> <span class="n">out_degrees</span><span class="p">,</span> <span class="n">nkk</span><span class="p">):</span> - <span class="sd">"""Checks whether the given directed joint degree input is realizable</span> +<span class="w"> </span><span class="sd">"""Checks whether the given directed joint degree input is realizable</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -826,7 +826,7 @@ <span class="k">def</span> <span class="nf">_directed_neighbor_switch</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">w</span><span class="p">,</span> <span class="n">unsat</span><span class="p">,</span> <span class="n">h_node_residual_out</span><span class="p">,</span> <span class="n">chords</span><span class="p">,</span> <span class="n">h_partition_in</span><span class="p">,</span> <span class="n">partition</span> <span class="p">):</span> - <span class="sd">"""Releases one free stub for node w, while preserving joint degree in G.</span> +<span class="w"> </span><span class="sd">"""Releases one free stub for node w, while preserving joint degree in G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -889,7 +889,7 @@ <span class="k">def</span> <span class="nf">_directed_neighbor_switch_rev</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">w</span><span class="p">,</span> <span class="n">unsat</span><span class="p">,</span> <span class="n">h_node_residual_in</span><span class="p">,</span> <span class="n">chords</span><span class="p">,</span> <span class="n">h_partition_out</span><span class="p">,</span> <span class="n">partition</span> <span class="p">):</span> - <span class="sd">"""The reverse of directed_neighbor_switch.</span> +<span class="w"> </span><span class="sd">"""The reverse of directed_neighbor_switch.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -940,7 +940,7 @@ <div class="viewcode-block" id="directed_joint_degree_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.joint_degree_seq.directed_joint_degree_graph.html#networkx.generators.joint_degree_seq.directed_joint_degree_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">directed_joint_degree_graph</span><span class="p">(</span><span class="n">in_degrees</span><span class="p">,</span> <span class="n">out_degrees</span><span class="p">,</span> <span class="n">nkk</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Generates a random simple directed graph with the joint degree.</span> +<span class="w"> </span><span class="sd">"""Generates a random simple directed graph with the joint degree.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1182,7 +1182,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/lattice.html b/_modules/networkx/generators/lattice.html index 014f63b7..574b0f9d 100644 --- a/_modules/networkx/generators/lattice.html +++ b/_modules/networkx/generators/lattice.html @@ -496,7 +496,7 @@ <div class="viewcode-block" id="grid_2d_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.lattice.grid_2d_graph.html#networkx.generators.lattice.grid_2d_graph">[docs]</a><span class="nd">@nodes_or_number</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span> <span class="k">def</span> <span class="nf">grid_2d_graph</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">periodic</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the two-dimensional grid graph.</span> +<span class="w"> </span><span class="sd">"""Returns the two-dimensional grid graph.</span> <span class="sd"> The grid graph has each node connected to its four nearest neighbors.</span> @@ -548,7 +548,7 @@ <div class="viewcode-block" id="grid_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.lattice.grid_graph.html#networkx.generators.lattice.grid_graph">[docs]</a><span class="k">def</span> <span class="nf">grid_graph</span><span class="p">(</span><span class="n">dim</span><span class="p">,</span> <span class="n">periodic</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns the *n*-dimensional grid graph.</span> +<span class="w"> </span><span class="sd">"""Returns the *n*-dimensional grid graph.</span> <span class="sd"> The dimension *n* is the length of the list `dim` and the size in</span> <span class="sd"> each dimension is the value of the corresponding list element.</span> @@ -604,7 +604,7 @@ <div class="viewcode-block" id="hypercube_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.lattice.hypercube_graph.html#networkx.generators.lattice.hypercube_graph">[docs]</a><span class="k">def</span> <span class="nf">hypercube_graph</span><span class="p">(</span><span class="n">n</span><span class="p">):</span> - <span class="sd">"""Returns the *n*-dimensional hypercube graph.</span> +<span class="w"> </span><span class="sd">"""Returns the *n*-dimensional hypercube graph.</span> <span class="sd"> The nodes are the integers between 0 and ``2 ** n - 1``, inclusive.</span> @@ -632,7 +632,7 @@ <div class="viewcode-block" id="triangular_lattice_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.lattice.triangular_lattice_graph.html#networkx.generators.lattice.triangular_lattice_graph">[docs]</a><span class="k">def</span> <span class="nf">triangular_lattice_graph</span><span class="p">(</span> <span class="n">m</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">periodic</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">with_positions</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the $m$ by $n$ triangular lattice graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the $m$ by $n$ triangular lattice graph.</span> <span class="sd"> The `triangular lattice graph`_ is a two-dimensional `grid graph`_ in</span> <span class="sd"> which each square unit has a diagonal edge (each grid unit has a chord).</span> @@ -732,7 +732,7 @@ <div class="viewcode-block" id="hexagonal_lattice_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.lattice.hexagonal_lattice_graph.html#networkx.generators.lattice.hexagonal_lattice_graph">[docs]</a><span class="k">def</span> <span class="nf">hexagonal_lattice_graph</span><span class="p">(</span> <span class="n">m</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">periodic</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">with_positions</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Returns an `m` by `n` hexagonal lattice graph.</span> +<span class="w"> </span><span class="sd">"""Returns an `m` by `n` hexagonal lattice graph.</span> <span class="sd"> The *hexagonal lattice graph* is a graph whose nodes and edges are</span> <span class="sd"> the `hexagonal tiling`_ of the plane.</span> @@ -873,7 +873,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/line.html b/_modules/networkx/generators/line.html index 66215f95..7d5f4fee 100644 --- a/_modules/networkx/generators/line.html +++ b/_modules/networkx/generators/line.html @@ -474,7 +474,7 @@ <div class="viewcode-block" id="line_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.line.line_graph.html#networkx.generators.line.line_graph">[docs]</a><span class="k">def</span> <span class="nf">line_graph</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the line graph of the graph or digraph `G`.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the line graph of the graph or digraph `G`.</span> <span class="sd"> The line graph of a graph `G` has a node for each edge in `G` and an</span> <span class="sd"> edge joining those nodes if the two edges in `G` share a common node. For</span> @@ -582,7 +582,7 @@ <span class="k">def</span> <span class="nf">_lg_directed</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the line graph L of the (multi)digraph G.</span> +<span class="w"> </span><span class="sd">"""Returns the line graph L of the (multi)digraph G.</span> <span class="sd"> Edges in G appear as nodes in L, represented as tuples of the form (u,v)</span> <span class="sd"> or (u,v,key) if G is a multidigraph. A node in L corresponding to the edge</span> @@ -612,7 +612,7 @@ <span class="k">def</span> <span class="nf">_lg_undirected</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">selfloops</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the line graph L of the (multi)graph G.</span> +<span class="w"> </span><span class="sd">"""Returns the line graph L of the (multi)graph G.</span> <span class="sd"> Edges in G appear as nodes in L, represented as sorted tuples of the form</span> <span class="sd"> (u,v), or (u,v,key) if G is a multigraph. A node in L corresponding to</span> @@ -678,7 +678,7 @@ <div class="viewcode-block" id="inverse_line_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.line.inverse_line_graph.html#networkx.generators.line.inverse_line_graph">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">inverse_line_graph</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns the inverse line graph of graph G.</span> +<span class="w"> </span><span class="sd">"""Returns the inverse line graph of graph G.</span> <span class="sd"> If H is a graph, and G is the line graph of H, such that G = L(H).</span> <span class="sd"> Then H is the inverse line graph of G.</span> @@ -741,6 +741,13 @@ <span class="p">)</span> <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span> + <span class="k">if</span> <span class="n">nx</span><span class="o">.</span><span class="n">number_of_selfloops</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span> + <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span> + <span class="s2">"A line graph as generated by NetworkX has no selfloops, so G has no "</span> + <span class="s2">"inverse line graph. Please remove the selfloops from G and try again."</span> + <span class="p">)</span> + <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span> + <span class="n">starting_cell</span> <span class="o">=</span> <span class="n">_select_starting_cell</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> <span class="n">P</span> <span class="o">=</span> <span class="n">_find_partition</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">starting_cell</span><span class="p">)</span> <span class="c1"># count how many times each vertex appears in the partition set</span> @@ -763,7 +770,7 @@ <span class="k">def</span> <span class="nf">_triangles</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">e</span><span class="p">):</span> - <span class="sd">"""Return list of all triangles containing edge e"""</span> +<span class="w"> </span><span class="sd">"""Return list of all triangles containing edge e"""</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span> <span class="o">=</span> <span class="n">e</span> <span class="k">if</span> <span class="n">u</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">G</span><span class="p">:</span> <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Vertex </span><span class="si">{</span><span class="n">u</span><span class="si">}</span><span class="s2"> not in graph"</span><span class="p">)</span> @@ -777,7 +784,7 @@ <span class="k">def</span> <span class="nf">_odd_triangle</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">T</span><span class="p">):</span> - <span class="sd">"""Test whether T is an odd triangle in G</span> +<span class="w"> </span><span class="sd">"""Test whether T is an odd triangle in G</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -820,7 +827,7 @@ <span class="k">def</span> <span class="nf">_find_partition</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">starting_cell</span><span class="p">):</span> - <span class="sd">"""Find a partition of the vertices of G into cells of complete graphs</span> +<span class="w"> </span><span class="sd">"""Find a partition of the vertices of G into cells of complete graphs</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -843,13 +850,9 @@ <span class="n">partitioned_vertices</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">starting_cell</span><span class="p">)</span> <span class="k">while</span> <span class="n">G_partition</span><span class="o">.</span><span class="n">number_of_edges</span><span class="p">()</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> <span class="c1"># there are still edges left and so more cells to be made</span> - <span class="n">u</span> <span class="o">=</span> <span class="n">partitioned_vertices</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> + <span class="n">u</span> <span class="o">=</span> <span class="n">partitioned_vertices</span><span class="o">.</span><span class="n">pop</span><span class="p">()</span> <span class="n">deg_u</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">G_partition</span><span class="p">[</span><span class="n">u</span><span class="p">])</span> - <span class="k">if</span> <span class="n">deg_u</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> - <span class="c1"># if u has no edges left in G_partition then we have found</span> - <span class="c1"># all of its cells so we do not need to keep looking</span> - <span class="n">partitioned_vertices</span><span class="o">.</span><span class="n">pop</span><span class="p">()</span> - <span class="k">else</span><span class="p">:</span> + <span class="k">if</span> <span class="n">deg_u</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span> <span class="c1"># if u still has edges then we need to find its other cell</span> <span class="c1"># this other cell must be a complete subgraph or else G is</span> <span class="c1"># not a line graph</span> @@ -869,7 +872,7 @@ <span class="k">def</span> <span class="nf">_select_starting_cell</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">starting_edge</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Select a cell to initiate _find_partition</span> +<span class="w"> </span><span class="sd">"""Select a cell to initiate _find_partition</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -896,6 +899,8 @@ <span class="n">e</span> <span class="o">=</span> <span class="n">arbitrary_element</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">())</span> <span class="k">else</span><span class="p">:</span> <span class="n">e</span> <span class="o">=</span> <span class="n">starting_edge</span> + <span class="k">if</span> <span class="n">e</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">():</span> + <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Vertex </span><span class="si">{</span><span class="n">e</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s2"> not in graph"</span><span class="p">)</span> <span class="k">if</span> <span class="n">e</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">G</span><span class="p">[</span><span class="n">e</span><span class="p">[</span><span class="mi">0</span><span class="p">]]:</span> <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"starting_edge (</span><span class="si">{</span><span class="n">e</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s2">, </span><span class="si">{</span><span class="n">e</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s2">) is not in the Graph"</span> <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span> @@ -910,10 +915,10 @@ <span class="n">T</span> <span class="o">=</span> <span class="n">e_triangles</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span> <span class="o">=</span> <span class="n">T</span> <span class="c1"># ab was original edge so check the other 2 edges</span> - <span class="n">ac_edges</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">_triangles</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">c</span><span class="p">))]</span> - <span class="n">bc_edges</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">_triangles</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="p">(</span><span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">))]</span> - <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">ac_edges</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span> - <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">bc_edges</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span> + <span class="n">ac_edges</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">_triangles</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">c</span><span class="p">)))</span> + <span class="n">bc_edges</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">_triangles</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="p">(</span><span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">)))</span> + <span class="k">if</span> <span class="n">ac_edges</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span> + <span class="k">if</span> <span class="n">bc_edges</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span> <span class="n">starting_cell</span> <span class="o">=</span> <span class="n">T</span> <span class="k">else</span><span class="p">:</span> <span class="k">return</span> <span class="n">_select_starting_cell</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">starting_edge</span><span class="o">=</span><span class="p">(</span><span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">))</span> @@ -932,29 +937,22 @@ <span class="n">starting_cell</span> <span class="o">=</span> <span class="n">T</span> <span class="k">elif</span> <span class="n">r</span> <span class="o">-</span> <span class="mi">1</span> <span class="o"><=</span> <span class="n">s</span> <span class="o"><=</span> <span class="n">r</span><span class="p">:</span> <span class="c1"># check if odd triangles containing e form complete subgraph</span> - <span class="c1"># there must be exactly s+2 of them</span> - <span class="c1"># and they must all be connected</span> <span class="n">triangle_nodes</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span> <span class="k">for</span> <span class="n">T</span> <span class="ow">in</span> <span class="n">odd_triangles</span><span class="p">:</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">T</span><span class="p">:</span> <span class="n">triangle_nodes</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> - <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">triangle_nodes</span><span class="p">)</span> <span class="o">==</span> <span class="n">s</span> <span class="o">+</span> <span class="mi">2</span><span class="p">:</span> - <span class="k">for</span> <span class="n">u</span> <span class="ow">in</span> <span class="n">triangle_nodes</span><span class="p">:</span> - <span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">triangle_nodes</span><span class="p">:</span> - <span class="k">if</span> <span class="n">u</span> <span class="o">!=</span> <span class="n">v</span> <span class="ow">and</span> <span class="p">(</span><span class="n">v</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">G</span><span class="p">[</span><span class="n">u</span><span class="p">]):</span> - <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span> - <span class="s2">"G is not a line graph (odd triangles "</span> - <span class="s2">"do not form complete subgraph)"</span> - <span class="p">)</span> - <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span> - <span class="c1"># otherwise then we can use this as the starting cell</span> - <span class="n">starting_cell</span> <span class="o">=</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">triangle_nodes</span><span class="p">)</span> - <span class="k">else</span><span class="p">:</span> - <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span> - <span class="s2">"G is not a line graph (odd triangles "</span> - <span class="s2">"do not form complete subgraph)"</span> - <span class="p">)</span> - <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span> + + <span class="k">for</span> <span class="n">u</span> <span class="ow">in</span> <span class="n">triangle_nodes</span><span class="p">:</span> + <span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">triangle_nodes</span><span class="p">:</span> + <span class="k">if</span> <span class="n">u</span> <span class="o">!=</span> <span class="n">v</span> <span class="ow">and</span> <span class="p">(</span><span class="n">v</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">G</span><span class="p">[</span><span class="n">u</span><span class="p">]):</span> + <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span> + <span class="s2">"G is not a line graph (odd triangles "</span> + <span class="s2">"do not form complete subgraph)"</span> + <span class="p">)</span> + <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span> + <span class="c1"># otherwise then we can use this as the starting cell</span> + <span class="n">starting_cell</span> <span class="o">=</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">triangle_nodes</span><span class="p">)</span> + <span class="k">else</span><span class="p">:</span> <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span> <span class="s2">"G is not a line graph (incorrect number of "</span> @@ -1013,7 +1011,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/mycielski.html b/_modules/networkx/generators/mycielski.html index 3965a0cb..2adba60d 100644 --- a/_modules/networkx/generators/mycielski.html +++ b/_modules/networkx/generators/mycielski.html @@ -475,7 +475,7 @@ <div class="viewcode-block" id="mycielskian"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.mycielski.mycielskian.html#networkx.generators.mycielski.mycielskian">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">mycielskian</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the Mycielskian of a simple, undirected graph G</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the Mycielskian of a simple, undirected graph G</span> <span class="sd"> The Mycielskian of graph preserves a graph's triangle free</span> <span class="sd"> property while increasing the chromatic number by 1.</span> @@ -531,7 +531,7 @@ <div class="viewcode-block" id="mycielski_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.mycielski.mycielski_graph.html#networkx.generators.mycielski.mycielski_graph">[docs]</a><span class="k">def</span> <span class="nf">mycielski_graph</span><span class="p">(</span><span class="n">n</span><span class="p">):</span> - <span class="sd">"""Generator for the n_th Mycielski Graph.</span> +<span class="w"> </span><span class="sd">"""Generator for the n_th Mycielski Graph.</span> <span class="sd"> The Mycielski family of graphs is an infinite set of graphs.</span> <span class="sd"> :math:`M_1` is the singleton graph, :math:`M_2` is two vertices with an</span> @@ -620,7 +620,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/nonisomorphic_trees.html b/_modules/networkx/generators/nonisomorphic_trees.html index 9a7ec02a..ad9c6df0 100644 --- a/_modules/networkx/generators/nonisomorphic_trees.html +++ b/_modules/networkx/generators/nonisomorphic_trees.html @@ -476,7 +476,7 @@ <div class="viewcode-block" id="nonisomorphic_trees"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.nonisomorphic_trees.nonisomorphic_trees.html#networkx.generators.nonisomorphic_trees.nonisomorphic_trees">[docs]</a><span class="k">def</span> <span class="nf">nonisomorphic_trees</span><span class="p">(</span><span class="n">order</span><span class="p">,</span> <span class="n">create</span><span class="o">=</span><span class="s2">"graph"</span><span class="p">):</span> - <span class="sd">"""Returns a list of nonisomporphic trees</span> +<span class="w"> </span><span class="sd">"""Returns a list of nonisomporphic trees</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -515,7 +515,7 @@ <div class="viewcode-block" id="number_of_nonisomorphic_trees"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.nonisomorphic_trees.number_of_nonisomorphic_trees.html#networkx.generators.nonisomorphic_trees.number_of_nonisomorphic_trees">[docs]</a><span class="k">def</span> <span class="nf">number_of_nonisomorphic_trees</span><span class="p">(</span><span class="n">order</span><span class="p">):</span> - <span class="sd">"""Returns the number of nonisomorphic trees</span> +<span class="w"> </span><span class="sd">"""Returns the number of nonisomorphic trees</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -534,7 +534,7 @@ <span class="k">def</span> <span class="nf">_next_rooted_tree</span><span class="p">(</span><span class="n">predecessor</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""One iteration of the Beyer-Hedetniemi algorithm."""</span> +<span class="w"> </span><span class="sd">"""One iteration of the Beyer-Hedetniemi algorithm."""</span> <span class="k">if</span> <span class="n">p</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> <span class="n">p</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">predecessor</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span> @@ -553,7 +553,7 @@ <span class="k">def</span> <span class="nf">_next_tree</span><span class="p">(</span><span class="n">candidate</span><span class="p">):</span> - <span class="sd">"""One iteration of the Wright, Richmond, Odlyzko and McKay</span> +<span class="w"> </span><span class="sd">"""One iteration of the Wright, Richmond, Odlyzko and McKay</span> <span class="sd"> algorithm."""</span> <span class="c1"># valid representation of a free tree if:</span> @@ -592,7 +592,7 @@ <span class="k">def</span> <span class="nf">_split_tree</span><span class="p">(</span><span class="n">layout</span><span class="p">):</span> - <span class="sd">"""Returns a tuple of two layouts, one containing the left</span> +<span class="w"> </span><span class="sd">"""Returns a tuple of two layouts, one containing the left</span> <span class="sd"> subtree of the root vertex, and one containing the original tree</span> <span class="sd"> with the left subtree removed."""</span> @@ -615,7 +615,7 @@ <span class="k">def</span> <span class="nf">_layout_to_matrix</span><span class="p">(</span><span class="n">layout</span><span class="p">):</span> - <span class="sd">"""Create the adjacency matrix for the tree specified by the</span> +<span class="w"> </span><span class="sd">"""Create the adjacency matrix for the tree specified by the</span> <span class="sd"> given layout (level sequence)."""</span> <span class="n">result</span> <span class="o">=</span> <span class="p">[[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">layout</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">layout</span><span class="p">))]</span> @@ -635,7 +635,7 @@ <span class="k">def</span> <span class="nf">_layout_to_graph</span><span class="p">(</span><span class="n">layout</span><span class="p">):</span> - <span class="sd">"""Create a NetworkX Graph for the tree specified by the</span> +<span class="w"> </span><span class="sd">"""Create a NetworkX Graph for the tree specified by the</span> <span class="sd"> given layout(level sequence)"""</span> <span class="n">G</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">Graph</span><span class="p">()</span> <span class="n">stack</span> <span class="o">=</span> <span class="p">[]</span> @@ -702,7 +702,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/random_clustered.html b/_modules/networkx/generators/random_clustered.html index d9e2bdf8..c711813d 100644 --- a/_modules/networkx/generators/random_clustered.html +++ b/_modules/networkx/generators/random_clustered.html @@ -471,7 +471,7 @@ <div class="viewcode-block" id="random_clustered_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_clustered.random_clustered_graph.html#networkx.generators.random_clustered.random_clustered_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_clustered_graph</span><span class="p">(</span><span class="n">joint_degree_sequence</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Generate a random graph with the given joint independent edge degree and</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Generate a random graph with the given joint independent edge degree and</span> <span class="sd"> triangle degree sequence.</span> <span class="sd"> This uses a configuration model-like approach to generate a random graph</span> @@ -628,7 +628,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/random_graphs.html b/_modules/networkx/generators/random_graphs.html index c1fda8c6..ca1ddb16 100644 --- a/_modules/networkx/generators/random_graphs.html +++ b/_modules/networkx/generators/random_graphs.html @@ -501,7 +501,7 @@ <div class="viewcode-block" id="fast_gnp_random_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.fast_gnp_random_graph.html#networkx.generators.random_graphs.fast_gnp_random_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">fast_gnp_random_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">directed</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns a $G_{n,p}$ random graph, also known as an Erdős-Rényi graph or</span> +<span class="w"> </span><span class="sd">"""Returns a $G_{n,p}$ random graph, also known as an Erdős-Rényi graph or</span> <span class="sd"> a binomial graph.</span> <span class="sd"> Parameters</span> @@ -572,7 +572,7 @@ <div class="viewcode-block" id="gnp_random_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.gnp_random_graph.html#networkx.generators.random_graphs.gnp_random_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">gnp_random_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">directed</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns a $G_{n,p}$ random graph, also known as an Erdős-Rényi graph</span> +<span class="w"> </span><span class="sd">"""Returns a $G_{n,p}$ random graph, also known as an Erdős-Rényi graph</span> <span class="sd"> or a binomial graph.</span> <span class="sd"> The $G_{n,p}$ model chooses each of the possible edges with probability $p$.</span> @@ -636,7 +636,7 @@ <div class="viewcode-block" id="dense_gnm_random_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.dense_gnm_random_graph.html#networkx.generators.random_graphs.dense_gnm_random_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">dense_gnm_random_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a $G_{n,m}$ random graph.</span> +<span class="w"> </span><span class="sd">"""Returns a $G_{n,m}$ random graph.</span> <span class="sd"> In the $G_{n,m}$ model, a graph is chosen uniformly at random from the set</span> <span class="sd"> of all graphs with $n$ nodes and $m$ edges.</span> @@ -697,7 +697,7 @@ <div class="viewcode-block" id="gnm_random_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.gnm_random_graph.html#networkx.generators.random_graphs.gnm_random_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">gnm_random_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">directed</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Returns a $G_{n,m}$ random graph.</span> +<span class="w"> </span><span class="sd">"""Returns a $G_{n,m}$ random graph.</span> <span class="sd"> In the $G_{n,m}$ model, a graph is chosen uniformly at random from the set</span> <span class="sd"> of all graphs with $n$ nodes and $m$ edges.</span> @@ -752,7 +752,7 @@ <div class="viewcode-block" id="newman_watts_strogatz_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.newman_watts_strogatz_graph.html#networkx.generators.random_graphs.newman_watts_strogatz_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">newman_watts_strogatz_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a Newman–Watts–Strogatz small-world graph.</span> +<span class="w"> </span><span class="sd">"""Returns a Newman–Watts–Strogatz small-world graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -822,7 +822,7 @@ <div class="viewcode-block" id="watts_strogatz_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.watts_strogatz_graph.html#networkx.generators.random_graphs.watts_strogatz_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">watts_strogatz_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a Watts–Strogatz small-world graph.</span> +<span class="w"> </span><span class="sd">"""Returns a Watts–Strogatz small-world graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -896,7 +896,7 @@ <div class="viewcode-block" id="connected_watts_strogatz_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.connected_watts_strogatz_graph.html#networkx.generators.random_graphs.connected_watts_strogatz_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="k">def</span> <span class="nf">connected_watts_strogatz_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">tries</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a connected Watts–Strogatz small-world graph.</span> +<span class="w"> </span><span class="sd">"""Returns a connected Watts–Strogatz small-world graph.</span> <span class="sd"> Attempts to generate a connected graph by repeated generation of</span> <span class="sd"> Watts–Strogatz small-world graphs. An exception is raised if the maximum</span> @@ -948,7 +948,7 @@ <div class="viewcode-block" id="random_regular_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.random_regular_graph.html#networkx.generators.random_graphs.random_regular_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_regular_graph</span><span class="p">(</span><span class="n">d</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a random $d$-regular graph on $n$ nodes.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a random $d$-regular graph on $n$ nodes.</span> <span class="sd"> The resulting graph has no self-loops or parallel edges.</span> @@ -1060,7 +1060,7 @@ <span class="k">def</span> <span class="nf">_random_subset</span><span class="p">(</span><span class="n">seq</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">rng</span><span class="p">):</span> - <span class="sd">"""Return m unique elements from seq.</span> +<span class="w"> </span><span class="sd">"""Return m unique elements from seq.</span> <span class="sd"> This differs from random.sample which can return repeated</span> <span class="sd"> elements if seq holds repeated elements.</span> @@ -1076,7 +1076,7 @@ <div class="viewcode-block" id="barabasi_albert_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.barabasi_albert_graph.html#networkx.generators.random_graphs.barabasi_albert_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">barabasi_albert_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">initial_graph</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a random graph using Barabási–Albert preferential attachment</span> +<span class="w"> </span><span class="sd">"""Returns a random graph using Barabási–Albert preferential attachment</span> <span class="sd"> A graph of $n$ nodes is grown by attaching new nodes each with $m$</span> <span class="sd"> edges that are preferentially attached to existing nodes with high degree.</span> @@ -1148,7 +1148,7 @@ <div class="viewcode-block" id="dual_barabasi_albert_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.dual_barabasi_albert_graph.html#networkx.generators.random_graphs.dual_barabasi_albert_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="k">def</span> <span class="nf">dual_barabasi_albert_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">m1</span><span class="p">,</span> <span class="n">m2</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">initial_graph</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a random graph using dual Barabási–Albert preferential attachment</span> +<span class="w"> </span><span class="sd">"""Returns a random graph using dual Barabási–Albert preferential attachment</span> <span class="sd"> A graph of $n$ nodes is grown by attaching new nodes each with either $m_1$</span> <span class="sd"> edges (with probability $p$) or $m_2$ edges (with probability $1-p$) that</span> @@ -1215,7 +1215,7 @@ <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">initial_graph</span><span class="p">)</span> <span class="o"><</span> <span class="nb">max</span><span class="p">(</span><span class="n">m1</span><span class="p">,</span> <span class="n">m2</span><span class="p">)</span> <span class="ow">or</span> <span class="nb">len</span><span class="p">(</span><span class="n">initial_graph</span><span class="p">)</span> <span class="o">></span> <span class="n">n</span><span class="p">:</span> <span class="k">raise</span> <span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span><span class="p">(</span> <span class="sa">f</span><span class="s2">"Barabási–Albert initial graph must have between "</span> - <span class="sa">f</span><span class="s2">"max(m1, m2) = </span><span class="si">{</span><span class="nb">max</span><span class="p">(</span><span class="n">m1</span><span class="p">,</span> <span class="n">m2</span><span class="p">)</span><span class="si">}</span><span class="s2"> and n = </span><span class="si">{</span><span class="n">n</span><span class="si">}</span><span class="s2"> nodes"</span> + <span class="sa">f</span><span class="s2">"max(m1, m2) = </span><span class="si">{</span><span class="nb">max</span><span class="p">(</span><span class="n">m1</span><span class="p">,</span><span class="w"> </span><span class="n">m2</span><span class="p">)</span><span class="si">}</span><span class="s2"> and n = </span><span class="si">{</span><span class="n">n</span><span class="si">}</span><span class="s2"> nodes"</span> <span class="p">)</span> <span class="n">G</span> <span class="o">=</span> <span class="n">initial_graph</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span> @@ -1247,7 +1247,7 @@ <div class="viewcode-block" id="extended_barabasi_albert_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.extended_barabasi_albert_graph.html#networkx.generators.random_graphs.extended_barabasi_albert_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="k">def</span> <span class="nf">extended_barabasi_albert_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">q</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns an extended Barabási–Albert model graph.</span> +<span class="w"> </span><span class="sd">"""Returns an extended Barabási–Albert model graph.</span> <span class="sd"> An extended Barabási–Albert model graph is a random graph constructed</span> <span class="sd"> using preferential attachment. The extended model allows new edges,</span> @@ -1410,7 +1410,7 @@ <div class="viewcode-block" id="powerlaw_cluster_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.powerlaw_cluster_graph.html#networkx.generators.random_graphs.powerlaw_cluster_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">powerlaw_cluster_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Holme and Kim algorithm for growing graphs with powerlaw</span> +<span class="w"> </span><span class="sd">"""Holme and Kim algorithm for growing graphs with powerlaw</span> <span class="sd"> degree distribution and approximate average clustering.</span> <span class="sd"> Parameters</span> @@ -1499,7 +1499,7 @@ <div class="viewcode-block" id="random_lobster"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.random_lobster.html#networkx.generators.random_graphs.random_lobster">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_lobster</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">p1</span><span class="p">,</span> <span class="n">p2</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a random lobster graph.</span> +<span class="w"> </span><span class="sd">"""Returns a random lobster graph.</span> <span class="sd"> A lobster is a tree that reduces to a caterpillar when pruning all</span> <span class="sd"> leaf nodes. A caterpillar is a tree that reduces to a path graph</span> @@ -1549,7 +1549,7 @@ <div class="viewcode-block" id="random_shell_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.random_shell_graph.html#networkx.generators.random_graphs.random_shell_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_shell_graph</span><span class="p">(</span><span class="n">constructor</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a random shell graph for the constructor given.</span> +<span class="w"> </span><span class="sd">"""Returns a random shell graph for the constructor given.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1606,7 +1606,7 @@ <div class="viewcode-block" id="random_powerlaw_tree"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.random_powerlaw_tree.html#networkx.generators.random_graphs.random_powerlaw_tree">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_powerlaw_tree</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">gamma</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">tries</span><span class="o">=</span><span class="mi">100</span><span class="p">):</span> - <span class="sd">"""Returns a tree with a power law degree distribution.</span> +<span class="w"> </span><span class="sd">"""Returns a tree with a power law degree distribution.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1642,7 +1642,7 @@ <div class="viewcode-block" id="random_powerlaw_tree_sequence"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.random_powerlaw_tree_sequence.html#networkx.generators.random_graphs.random_powerlaw_tree_sequence">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_powerlaw_tree_sequence</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">gamma</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">tries</span><span class="o">=</span><span class="mi">100</span><span class="p">):</span> - <span class="sd">"""Returns a degree sequence for a tree with a power law distribution.</span> +<span class="w"> </span><span class="sd">"""Returns a degree sequence for a tree with a power law distribution.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1698,7 +1698,7 @@ <div class="viewcode-block" id="random_kernel_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.random_graphs.random_kernel_graph.html#networkx.generators.random_graphs.random_kernel_graph">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_kernel_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">kernel_integral</span><span class="p">,</span> <span class="n">kernel_root</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns an random graph based on the specified kernel.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns an random graph based on the specified kernel.</span> <span class="sd"> The algorithm chooses each of the $[n(n-1)]/2$ possible edges with</span> <span class="sd"> probability specified by a kernel $\kappa(x,y)$ [1]_. The kernel</span> @@ -1828,7 +1828,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/small.html b/_modules/networkx/generators/small.html index 763acdfd..b26088ee 100644 --- a/_modules/networkx/generators/small.html +++ b/_modules/networkx/generators/small.html @@ -505,7 +505,7 @@ <span class="k">def</span> <span class="nf">_raise_on_directed</span><span class="p">(</span><span class="n">func</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> A decorator which inspects the `create_using` argument and raises a</span> <span class="sd"> NetworkX exception when `create_using` is a DiGraph (class or instance) for</span> <span class="sd"> graph generators that do not support directed outputs.</span> @@ -523,7 +523,7 @@ <div class="viewcode-block" id="LCF_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.LCF_graph.html#networkx.generators.small.LCF_graph">[docs]</a><span class="k">def</span> <span class="nf">LCF_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">shift_list</span><span class="p">,</span> <span class="n">repeats</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Return the cubic graph specified in LCF notation.</span> <span class="sd"> LCF notation (LCF=Lederberg-Coxeter-Fruchte) is a compressed</span> @@ -589,7 +589,7 @@ <div class="viewcode-block" id="bull_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.bull_graph.html#networkx.generators.small.bull_graph">[docs]</a><span class="nd">@_raise_on_directed</span> <span class="k">def</span> <span class="nf">bull_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the Bull Graph</span> <span class="sd"> The Bull Graph has 5 nodes and 5 edges. It is a planar undirected</span> @@ -622,7 +622,7 @@ <div class="viewcode-block" id="chvatal_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.chvatal_graph.html#networkx.generators.small.chvatal_graph">[docs]</a><span class="nd">@_raise_on_directed</span> <span class="k">def</span> <span class="nf">chvatal_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the Chvátal Graph</span> <span class="sd"> The Chvátal Graph is an undirected graph with 12 nodes and 24 edges [1]_.</span> @@ -666,7 +666,7 @@ <div class="viewcode-block" id="cubical_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.cubical_graph.html#networkx.generators.small.cubical_graph">[docs]</a><span class="nd">@_raise_on_directed</span> <span class="k">def</span> <span class="nf">cubical_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the 3-regular Platonic Cubical Graph</span> <span class="sd"> The skeleton of the cube (the nodes and edges) form a graph, with 8</span> @@ -708,7 +708,7 @@ <div class="viewcode-block" id="desargues_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.desargues_graph.html#networkx.generators.small.desargues_graph">[docs]</a><span class="k">def</span> <span class="nf">desargues_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the Desargues Graph</span> <span class="sd"> The Desargues Graph is a non-planar, distance-transitive cubic graph</span> @@ -738,7 +738,7 @@ <div class="viewcode-block" id="diamond_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.diamond_graph.html#networkx.generators.small.diamond_graph">[docs]</a><span class="nd">@_raise_on_directed</span> <span class="k">def</span> <span class="nf">diamond_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the Diamond graph</span> <span class="sd"> The Diamond Graph is planar undirected graph with 4 nodes and 5 edges.</span> @@ -766,7 +766,7 @@ <div class="viewcode-block" id="dodecahedral_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.dodecahedral_graph.html#networkx.generators.small.dodecahedral_graph">[docs]</a><span class="k">def</span> <span class="nf">dodecahedral_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the Platonic Dodecahedral graph.</span> <span class="sd"> The dodecahedral graph has 20 nodes and 30 edges. The skeleton of the</span> @@ -796,7 +796,7 @@ <div class="viewcode-block" id="frucht_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.frucht_graph.html#networkx.generators.small.frucht_graph">[docs]</a><span class="k">def</span> <span class="nf">frucht_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the Frucht Graph.</span> <span class="sd"> The Frucht Graph is the smallest cubical graph whose</span> @@ -842,7 +842,7 @@ <div class="viewcode-block" id="heawood_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.heawood_graph.html#networkx.generators.small.heawood_graph">[docs]</a><span class="k">def</span> <span class="nf">heawood_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the Heawood Graph, a (3,6) cage.</span> <span class="sd"> The Heawood Graph is an undirected graph with 14 nodes and 21 edges,</span> @@ -875,7 +875,7 @@ <div class="viewcode-block" id="hoffman_singleton_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.hoffman_singleton_graph.html#networkx.generators.small.hoffman_singleton_graph">[docs]</a><span class="k">def</span> <span class="nf">hoffman_singleton_graph</span><span class="p">():</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the Hoffman-Singleton Graph.</span> <span class="sd"> The Hoffman–Singleton graph is a symmetrical undirected graph</span> @@ -918,7 +918,7 @@ <div class="viewcode-block" id="house_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.house_graph.html#networkx.generators.small.house_graph">[docs]</a><span class="nd">@_raise_on_directed</span> <span class="k">def</span> <span class="nf">house_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the House graph (square with triangle on top)</span> <span class="sd"> The house graph is a simple undirected graph with</span> @@ -948,7 +948,7 @@ <div class="viewcode-block" id="house_x_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.house_x_graph.html#networkx.generators.small.house_x_graph">[docs]</a><span class="nd">@_raise_on_directed</span> <span class="k">def</span> <span class="nf">house_x_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the House graph with a cross inside the house square.</span> <span class="sd"> The House X-graph is the House graph plus the two edges connecting diagonally</span> @@ -977,7 +977,7 @@ <div class="viewcode-block" id="icosahedral_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.icosahedral_graph.html#networkx.generators.small.icosahedral_graph">[docs]</a><span class="nd">@_raise_on_directed</span> <span class="k">def</span> <span class="nf">icosahedral_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the Platonic Icosahedral graph.</span> <span class="sd"> The icosahedral graph has 12 nodes and 30 edges. It is a Platonic graph</span> @@ -1019,7 +1019,7 @@ <div class="viewcode-block" id="krackhardt_kite_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.krackhardt_kite_graph.html#networkx.generators.small.krackhardt_kite_graph">[docs]</a><span class="nd">@_raise_on_directed</span> <span class="k">def</span> <span class="nf">krackhardt_kite_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the Krackhardt Kite Social Network.</span> <span class="sd"> A 10 actor social network introduced by David Krackhardt</span> @@ -1068,7 +1068,7 @@ <div class="viewcode-block" id="moebius_kantor_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.moebius_kantor_graph.html#networkx.generators.small.moebius_kantor_graph">[docs]</a><span class="k">def</span> <span class="nf">moebius_kantor_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the Moebius-Kantor graph.</span> <span class="sd"> The Möbius-Kantor graph is the cubic symmetric graph on 16 nodes.</span> @@ -1097,7 +1097,7 @@ <div class="viewcode-block" id="octahedral_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.octahedral_graph.html#networkx.generators.small.octahedral_graph">[docs]</a><span class="nd">@_raise_on_directed</span> <span class="k">def</span> <span class="nf">octahedral_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the Platonic Octahedral graph.</span> <span class="sd"> The octahedral graph is the 6-node 12-edge Platonic graph having the</span> @@ -1131,7 +1131,7 @@ <div class="viewcode-block" id="pappus_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.pappus_graph.html#networkx.generators.small.pappus_graph">[docs]</a><span class="k">def</span> <span class="nf">pappus_graph</span><span class="p">():</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the Pappus graph.</span> <span class="sd"> The Pappus graph is a cubic symmetric distance-regular graph with 18 nodes</span> @@ -1154,7 +1154,7 @@ <div class="viewcode-block" id="petersen_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.petersen_graph.html#networkx.generators.small.petersen_graph">[docs]</a><span class="nd">@_raise_on_directed</span> <span class="k">def</span> <span class="nf">petersen_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the Petersen graph.</span> <span class="sd"> The Peterson graph is a cubic, undirected graph with 10 nodes and 15 edges [1]_.</span> @@ -1197,7 +1197,7 @@ <div class="viewcode-block" id="sedgewick_maze_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.sedgewick_maze_graph.html#networkx.generators.small.sedgewick_maze_graph">[docs]</a><span class="k">def</span> <span class="nf">sedgewick_maze_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Return a small maze with a cycle.</span> <span class="sd"> This is the maze used in Sedgewick, 3rd Edition, Part 5, Graph</span> @@ -1229,7 +1229,7 @@ <div class="viewcode-block" id="tetrahedral_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.tetrahedral_graph.html#networkx.generators.small.tetrahedral_graph">[docs]</a><span class="k">def</span> <span class="nf">tetrahedral_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the 3-regular Platonic Tetrahedral graph.</span> <span class="sd"> Tetrahedral graph has 4 nodes and 6 edges. It is a</span> @@ -1258,7 +1258,7 @@ <div class="viewcode-block" id="truncated_cube_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.truncated_cube_graph.html#networkx.generators.small.truncated_cube_graph">[docs]</a><span class="nd">@_raise_on_directed</span> <span class="k">def</span> <span class="nf">truncated_cube_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the skeleton of the truncated cube.</span> <span class="sd"> The truncated cube is an Archimedean solid with 14 regular</span> @@ -1315,7 +1315,7 @@ <div class="viewcode-block" id="truncated_tetrahedron_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.truncated_tetrahedron_graph.html#networkx.generators.small.truncated_tetrahedron_graph">[docs]</a><span class="k">def</span> <span class="nf">truncated_tetrahedron_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the skeleton of the truncated Platonic tetrahedron.</span> <span class="sd"> The truncated tetrahedron is an Archimedean solid with 4 regular hexagonal faces,</span> @@ -1345,7 +1345,7 @@ <div class="viewcode-block" id="tutte_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.small.tutte_graph.html#networkx.generators.small.tutte_graph">[docs]</a><span class="nd">@_raise_on_directed</span> <span class="k">def</span> <span class="nf">tutte_graph</span><span class="p">(</span><span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the Tutte graph.</span> <span class="sd"> The Tutte graph is a cubic polyhedral, non-Hamiltonian graph. It has</span> @@ -1467,7 +1467,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/social.html b/_modules/networkx/generators/social.html index 651fcbca..6238bdba 100644 --- a/_modules/networkx/generators/social.html +++ b/_modules/networkx/generators/social.html @@ -475,7 +475,7 @@ <div class="viewcode-block" id="karate_club_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.social.karate_club_graph.html#networkx.generators.social.karate_club_graph">[docs]</a><span class="k">def</span> <span class="nf">karate_club_graph</span><span class="p">():</span> - <span class="sd">"""Returns Zachary's Karate Club graph.</span> +<span class="w"> </span><span class="sd">"""Returns Zachary's Karate Club graph.</span> <span class="sd"> Each node in the returned graph has a node attribute 'club' that</span> <span class="sd"> indicates the name of the club to which the member represented by that node</span> @@ -556,7 +556,7 @@ <div class="viewcode-block" id="davis_southern_women_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.social.davis_southern_women_graph.html#networkx.generators.social.davis_southern_women_graph">[docs]</a><span class="k">def</span> <span class="nf">davis_southern_women_graph</span><span class="p">():</span> - <span class="sd">"""Returns Davis Southern women social network.</span> +<span class="w"> </span><span class="sd">"""Returns Davis Southern women social network.</span> <span class="sd"> This is a bipartite graph.</span> @@ -706,7 +706,7 @@ <div class="viewcode-block" id="florentine_families_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.social.florentine_families_graph.html#networkx.generators.social.florentine_families_graph">[docs]</a><span class="k">def</span> <span class="nf">florentine_families_graph</span><span class="p">():</span> - <span class="sd">"""Returns Florentine families graph.</span> +<span class="w"> </span><span class="sd">"""Returns Florentine families graph.</span> <span class="sd"> References</span> <span class="sd"> ----------</span> @@ -739,7 +739,7 @@ <div class="viewcode-block" id="les_miserables_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.social.les_miserables_graph.html#networkx.generators.social.les_miserables_graph">[docs]</a><span class="k">def</span> <span class="nf">les_miserables_graph</span><span class="p">():</span> - <span class="sd">"""Returns coappearance network of characters in the novel Les Miserables.</span> +<span class="w"> </span><span class="sd">"""Returns coappearance network of characters in the novel Les Miserables.</span> <span class="sd"> References</span> <span class="sd"> ----------</span> @@ -1054,7 +1054,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/spectral_graph_forge.html b/_modules/networkx/generators/spectral_graph_forge.html index 333cfd96..554b3749 100644 --- a/_modules/networkx/generators/spectral_graph_forge.html +++ b/_modules/networkx/generators/spectral_graph_forge.html @@ -472,7 +472,7 @@ <div class="viewcode-block" id="spectral_graph_forge"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.spectral_graph_forge.spectral_graph_forge.html#networkx.generators.spectral_graph_forge.spectral_graph_forge">[docs]</a><span class="nd">@np_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">spectral_graph_forge</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">alpha</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="s2">"identity"</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a random simple graph with spectrum resembling that of `G`</span> +<span class="w"> </span><span class="sd">"""Returns a random simple graph with spectrum resembling that of `G`</span> <span class="sd"> This algorithm, called Spectral Graph Forge (SGF), computes the</span> <span class="sd"> eigenvectors of a given graph adjacency matrix, filters them and</span> @@ -633,7 +633,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/stochastic.html b/_modules/networkx/generators/stochastic.html index d4fb321e..8b3649d6 100644 --- a/_modules/networkx/generators/stochastic.html +++ b/_modules/networkx/generators/stochastic.html @@ -474,7 +474,7 @@ <div class="viewcode-block" id="stochastic_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.stochastic.stochastic_graph.html#networkx.generators.stochastic.stochastic_graph">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">stochastic_graph</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns a right-stochastic representation of directed graph `G`.</span> +<span class="w"> </span><span class="sd">"""Returns a right-stochastic representation of directed graph `G`.</span> <span class="sd"> A right-stochastic graph is a weighted digraph in which for each</span> <span class="sd"> node, the sum of the weights of all the out-edges of that node is</span> @@ -561,7 +561,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/sudoku.html b/_modules/networkx/generators/sudoku.html index 397c8a51..53574921 100644 --- a/_modules/networkx/generators/sudoku.html +++ b/_modules/networkx/generators/sudoku.html @@ -511,7 +511,7 @@ <div class="viewcode-block" id="sudoku_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.sudoku.sudoku_graph.html#networkx.generators.sudoku.sudoku_graph">[docs]</a><span class="k">def</span> <span class="nf">sudoku_graph</span><span class="p">(</span><span class="n">n</span><span class="o">=</span><span class="mi">3</span><span class="p">):</span> - <span class="sd">"""Returns the n-Sudoku graph. The default value of n is 3.</span> +<span class="w"> </span><span class="sd">"""Returns the n-Sudoku graph. The default value of n is 3.</span> <span class="sd"> The n-Sudoku graph is a graph with n^4 vertices, corresponding to the</span> <span class="sd"> cells of an n^2 by n^2 grid. Two distinct vertices are adjacent if and</span> @@ -642,7 +642,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/trees.html b/_modules/networkx/generators/trees.html index d12fe040..295a7333 100644 --- a/_modules/networkx/generators/trees.html +++ b/_modules/networkx/generators/trees.html @@ -471,7 +471,7 @@ <div class="viewcode-block" id="prefix_tree"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.trees.prefix_tree.html#networkx.generators.trees.prefix_tree">[docs]</a><span class="k">def</span> <span class="nf">prefix_tree</span><span class="p">(</span><span class="n">paths</span><span class="p">):</span> - <span class="sd">"""Creates a directed prefix tree from a list of paths.</span> +<span class="w"> </span><span class="sd">"""Creates a directed prefix tree from a list of paths.</span> <span class="sd"> Usually the paths are described as strings or lists of integers.</span> @@ -603,7 +603,7 @@ <span class="k">def</span> <span class="nf">prefix_tree_recursive</span><span class="p">(</span><span class="n">paths</span><span class="p">):</span> - <span class="sd">"""Recursively creates a directed prefix tree from a list of paths.</span> +<span class="w"> </span><span class="sd">"""Recursively creates a directed prefix tree from a list of paths.</span> <span class="sd"> The original recursive version of prefix_tree for comparison. It is</span> <span class="sd"> the same algorithm but the recursion is unrolled onto a stack.</span> @@ -697,7 +697,7 @@ <span class="sd"> """</span> <span class="k">def</span> <span class="nf">_helper</span><span class="p">(</span><span class="n">paths</span><span class="p">,</span> <span class="n">root</span><span class="p">,</span> <span class="n">tree</span><span class="p">):</span> - <span class="sd">"""Recursively create a trie from the given list of paths.</span> +<span class="w"> </span><span class="sd">"""Recursively create a trie from the given list of paths.</span> <span class="sd"> `paths` is a list of paths, each of which is itself a list of</span> <span class="sd"> nodes, relative to the given `root` (but not including it). This</span> @@ -751,7 +751,7 @@ <span class="c1">#</span> <div class="viewcode-block" id="random_tree"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.trees.random_tree.html#networkx.generators.trees.random_tree">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_tree</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a uniformly random tree on `n` nodes.</span> +<span class="w"> </span><span class="sd">"""Returns a uniformly random tree on `n` nodes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -886,7 +886,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/generators/triads.html b/_modules/networkx/generators/triads.html index 00376007..3e461b77 100644 --- a/_modules/networkx/generators/triads.html +++ b/_modules/networkx/generators/triads.html @@ -496,7 +496,7 @@ <div class="viewcode-block" id="triad_graph"><a class="viewcode-back" href="../../../reference/generated/networkx.generators.triads.triad_graph.html#networkx.generators.triads.triad_graph">[docs]</a><span class="k">def</span> <span class="nf">triad_graph</span><span class="p">(</span><span class="n">triad_name</span><span class="p">):</span> - <span class="sd">"""Returns the triad graph with the given name.</span> +<span class="w"> </span><span class="sd">"""Returns the triad graph with the given name.</span> <span class="sd"> Each string in the following tuple is a valid triad name::</span> @@ -587,7 +587,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/linalg/algebraicconnectivity.html b/_modules/networkx/linalg/algebraicconnectivity.html index c125b7b5..e377b40f 100644 --- a/_modules/networkx/linalg/algebraicconnectivity.html +++ b/_modules/networkx/linalg/algebraicconnectivity.html @@ -477,7 +477,7 @@ <span class="k">class</span> <span class="nc">_PCGSolver</span><span class="p">:</span> - <span class="sd">"""Preconditioned conjugate gradient method.</span> +<span class="w"> </span><span class="sd">"""Preconditioned conjugate gradient method.</span> <span class="sd"> To solve Ax = b:</span> <span class="sd"> M = A.diagonal() # or some other preconditioner</span> @@ -535,7 +535,7 @@ <span class="k">class</span> <span class="nc">_LUSolver</span><span class="p">:</span> - <span class="sd">"""LU factorization.</span> +<span class="w"> </span><span class="sd">"""LU factorization.</span> <span class="sd"> To solve Ax = b:</span> <span class="sd"> solver = _LUSolver(A)</span> @@ -567,7 +567,7 @@ <span class="k">def</span> <span class="nf">_preprocess_graph</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="p">):</span> - <span class="sd">"""Compute edge weights and eliminate zero-weight edges."""</span> +<span class="w"> </span><span class="sd">"""Compute edge weights and eliminate zero-weight edges."""</span> <span class="k">if</span> <span class="n">G</span><span class="o">.</span><span class="n">is_directed</span><span class="p">():</span> <span class="n">H</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">MultiGraph</span><span class="p">()</span> <span class="n">H</span><span class="o">.</span><span class="n">add_nodes_from</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> @@ -593,7 +593,7 @@ <span class="k">def</span> <span class="nf">_rcm_estimate</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="p">):</span> - <span class="sd">"""Estimate the Fiedler vector using the reverse Cuthill-McKee ordering."""</span> +<span class="w"> </span><span class="sd">"""Estimate the Fiedler vector using the reverse Cuthill-McKee ordering."""</span> <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span> <span class="n">G</span> <span class="o">=</span> <span class="n">G</span><span class="o">.</span><span class="n">subgraph</span><span class="p">(</span><span class="n">nodelist</span><span class="p">)</span> @@ -608,7 +608,7 @@ <span class="k">def</span> <span class="nf">_tracemin_fiedler</span><span class="p">(</span><span class="n">L</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">normalized</span><span class="p">,</span> <span class="n">tol</span><span class="p">,</span> <span class="n">method</span><span class="p">):</span> - <span class="sd">"""Compute the Fiedler vector of L using the TraceMIN-Fiedler algorithm.</span> +<span class="w"> </span><span class="sd">"""Compute the Fiedler vector of L using the TraceMIN-Fiedler algorithm.</span> <span class="sd"> The Fiedler vector of a connected undirected graph is the eigenvector</span> <span class="sd"> corresponding to the second smallest eigenvalue of the Laplacian matrix</span> @@ -661,7 +661,7 @@ <span class="k">if</span> <span class="n">normalized</span><span class="p">:</span> <span class="k">def</span> <span class="nf">project</span><span class="p">(</span><span class="n">X</span><span class="p">):</span> - <span class="sd">"""Make X orthogonal to the nullspace of L."""</span> +<span class="w"> </span><span class="sd">"""Make X orthogonal to the nullspace of L."""</span> <span class="n">X</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">X</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">X</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]):</span> <span class="n">X</span><span class="p">[:,</span> <span class="n">j</span><span class="p">]</span> <span class="o">-=</span> <span class="p">(</span><span class="n">X</span><span class="p">[:,</span> <span class="n">j</span><span class="p">]</span> <span class="o">@</span> <span class="n">e</span><span class="p">)</span> <span class="o">*</span> <span class="n">e</span> @@ -669,7 +669,7 @@ <span class="k">else</span><span class="p">:</span> <span class="k">def</span> <span class="nf">project</span><span class="p">(</span><span class="n">X</span><span class="p">):</span> - <span class="sd">"""Make X orthogonal to the nullspace of L."""</span> +<span class="w"> </span><span class="sd">"""Make X orthogonal to the nullspace of L."""</span> <span class="n">X</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">X</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">X</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]):</span> <span class="n">X</span><span class="p">[:,</span> <span class="n">j</span><span class="p">]</span> <span class="o">-=</span> <span class="n">X</span><span class="p">[:,</span> <span class="n">j</span><span class="p">]</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span> <span class="o">/</span> <span class="n">n</span> @@ -719,7 +719,7 @@ <span class="k">def</span> <span class="nf">_get_fiedler_func</span><span class="p">(</span><span class="n">method</span><span class="p">):</span> - <span class="sd">"""Returns a function that solves the Fiedler eigenvalue problem."""</span> +<span class="w"> </span><span class="sd">"""Returns a function that solves the Fiedler eigenvalue problem."""</span> <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span> <span class="k">if</span> <span class="n">method</span> <span class="o">==</span> <span class="s2">"tracemin"</span><span class="p">:</span> <span class="c1"># old style keyword <v2.1</span> @@ -780,7 +780,7 @@ <span class="k">def</span> <span class="nf">algebraic_connectivity</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mf">1e-8</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s2">"tracemin_pcg"</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the algebraic connectivity of an undirected graph.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the algebraic connectivity of an undirected graph.</span> <span class="sd"> The algebraic connectivity of a connected undirected graph is the second</span> <span class="sd"> smallest eigenvalue of its Laplacian matrix.</span> @@ -875,7 +875,7 @@ <span class="k">def</span> <span class="nf">fiedler_vector</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mf">1e-8</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s2">"tracemin_pcg"</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Returns the Fiedler vector of a connected undirected graph.</span> +<span class="w"> </span><span class="sd">"""Returns the Fiedler vector of a connected undirected graph.</span> <span class="sd"> The Fiedler vector of a connected undirected graph is the eigenvector</span> <span class="sd"> corresponding to the second smallest eigenvalue of the Laplacian matrix</span> @@ -971,7 +971,7 @@ <span class="k">def</span> <span class="nf">spectral_ordering</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mf">1e-8</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s2">"tracemin_pcg"</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Compute the spectral_ordering of a graph.</span> +<span class="w"> </span><span class="sd">"""Compute the spectral_ordering of a graph.</span> <span class="sd"> The spectral ordering of a graph is an ordering of its nodes where nodes</span> <span class="sd"> in the same weakly connected components appear contiguous and ordered by</span> @@ -1099,7 +1099,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/linalg/attrmatrix.html b/_modules/networkx/linalg/attrmatrix.html index 122721bd..83f6faa6 100644 --- a/_modules/networkx/linalg/attrmatrix.html +++ b/_modules/networkx/linalg/attrmatrix.html @@ -469,7 +469,7 @@ <span class="k">def</span> <span class="nf">_node_value</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">node_attr</span><span class="p">):</span> - <span class="sd">"""Returns a function that returns a value from G.nodes[u].</span> +<span class="w"> </span><span class="sd">"""Returns a function that returns a value from G.nodes[u].</span> <span class="sd"> We return a function expecting a node as its sole argument. Then, in the</span> <span class="sd"> simplest scenario, the returned function will return G.nodes[u][node_attr].</span> @@ -514,7 +514,7 @@ <span class="k">def</span> <span class="nf">_edge_value</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">edge_attr</span><span class="p">):</span> - <span class="sd">"""Returns a function that returns a value from G[u][v].</span> +<span class="w"> </span><span class="sd">"""Returns a function that returns a value from G[u][v].</span> <span class="sd"> Suppose there exists an edge between u and v. Then we return a function</span> <span class="sd"> expecting u and v as arguments. For Graph and DiGraph, G[u][v] is</span> @@ -613,7 +613,7 @@ <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns the attribute matrix using attributes from `G` as a numpy array.</span> +<span class="w"> </span><span class="sd">"""Returns the attribute matrix using attributes from `G` as a numpy array.</span> <span class="sd"> If only `G` is passed in, then the adjacency matrix is constructed.</span> @@ -770,7 +770,7 @@ <div class="viewcode-block" id="attr_sparse_matrix"><a class="viewcode-back" href="../../../reference/generated/networkx.linalg.attrmatrix.attr_sparse_matrix.html#networkx.linalg.attrmatrix.attr_sparse_matrix">[docs]</a><span class="k">def</span> <span class="nf">attr_sparse_matrix</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">edge_attr</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">node_attr</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">normalized</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">rc_order</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Returns a SciPy sparse array using attributes from G.</span> +<span class="w"> </span><span class="sd">"""Returns a SciPy sparse array using attributes from G.</span> <span class="sd"> If only `G` is passed in, then the adjacency matrix is constructed.</span> @@ -974,7 +974,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/linalg/bethehessianmatrix.html b/_modules/networkx/linalg/bethehessianmatrix.html index 82d35e80..8403f92d 100644 --- a/_modules/networkx/linalg/bethehessianmatrix.html +++ b/_modules/networkx/linalg/bethehessianmatrix.html @@ -471,7 +471,7 @@ <div class="viewcode-block" id="bethe_hessian_matrix"><a class="viewcode-back" href="../../../reference/generated/networkx.linalg.bethehessianmatrix.bethe_hessian_matrix.html#networkx.linalg.bethehessianmatrix.bethe_hessian_matrix">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">bethe_hessian_matrix</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">r</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the Bethe Hessian matrix of G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the Bethe Hessian matrix of G.</span> <span class="sd"> The Bethe Hessian is a family of matrices parametrized by r, defined as</span> <span class="sd"> H(r) = (r^2 - 1) I - r A + D where A is the adjacency matrix, D is the</span> @@ -590,7 +590,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/linalg/graphmatrix.html b/_modules/networkx/linalg/graphmatrix.html index b5db4379..52a089d7 100644 --- a/_modules/networkx/linalg/graphmatrix.html +++ b/_modules/networkx/linalg/graphmatrix.html @@ -470,7 +470,7 @@ <div class="viewcode-block" id="incidence_matrix"><a class="viewcode-back" href="../../../reference/generated/networkx.linalg.graphmatrix.incidence_matrix.html#networkx.linalg.graphmatrix.incidence_matrix">[docs]</a><span class="k">def</span> <span class="nf">incidence_matrix</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">edgelist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">oriented</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns incidence matrix of G.</span> +<span class="w"> </span><span class="sd">"""Returns incidence matrix of G.</span> <span class="sd"> The incidence matrix assigns each row to a node and each column to an edge.</span> <span class="sd"> For a standard incidence matrix a 1 appears wherever a row's node is</span> @@ -560,7 +560,7 @@ <div class="viewcode-block" id="adjacency_matrix"><a class="viewcode-back" href="../../../reference/generated/networkx.linalg.graphmatrix.adjacency_matrix.html#networkx.linalg.graphmatrix.adjacency_matrix">[docs]</a><span class="k">def</span> <span class="nf">adjacency_matrix</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns adjacency matrix of G.</span> +<span class="w"> </span><span class="sd">"""Returns adjacency matrix of G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -669,7 +669,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/linalg/laplacianmatrix.html b/_modules/networkx/linalg/laplacianmatrix.html index 7300abf2..e2051e81 100644 --- a/_modules/networkx/linalg/laplacianmatrix.html +++ b/_modules/networkx/linalg/laplacianmatrix.html @@ -477,7 +477,7 @@ <div class="viewcode-block" id="laplacian_matrix"><a class="viewcode-back" href="../../../reference/generated/networkx.linalg.laplacianmatrix.laplacian_matrix.html#networkx.linalg.laplacianmatrix.laplacian_matrix">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">laplacian_matrix</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns the Laplacian matrix of G.</span> +<span class="w"> </span><span class="sd">"""Returns the Laplacian matrix of G.</span> <span class="sd"> The graph Laplacian is the matrix L = D - A, where</span> <span class="sd"> A is the adjacency matrix and D is the diagonal matrix of node degrees.</span> @@ -539,7 +539,7 @@ <div class="viewcode-block" id="normalized_laplacian_matrix"><a class="viewcode-back" href="../../../reference/generated/networkx.linalg.laplacianmatrix.normalized_laplacian_matrix.html#networkx.linalg.laplacianmatrix.normalized_laplacian_matrix">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">normalized_laplacian_matrix</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the normalized Laplacian matrix of G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the normalized Laplacian matrix of G.</span> <span class="sd"> The normalized graph Laplacian is the matrix</span> @@ -610,7 +610,7 @@ <span class="k">def</span> <span class="nf">total_spanning_tree_weight</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Returns the total weight of all spanning trees of `G`.</span> <span class="sd"> Kirchoff's Tree Matrix Theorem states that the determinant of any cofactor of the</span> @@ -650,7 +650,7 @@ <span class="k">def</span> <span class="nf">directed_laplacian_matrix</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">walk_type</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.95</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the directed Laplacian matrix of G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the directed Laplacian matrix of G.</span> <span class="sd"> The graph directed Laplacian is the matrix</span> @@ -739,7 +739,7 @@ <span class="k">def</span> <span class="nf">directed_combinatorial_laplacian_matrix</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">walk_type</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.95</span> <span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Return the directed combinatorial Laplacian matrix of G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Return the directed combinatorial Laplacian matrix of G.</span> <span class="sd"> The graph directed combinatorial Laplacian is the matrix</span> @@ -814,7 +814,7 @@ <span class="k">def</span> <span class="nf">_transition_matrix</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">,</span> <span class="n">walk_type</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.95</span><span class="p">):</span> - <span class="sd">"""Returns the transition matrix of G.</span> +<span class="w"> </span><span class="sd">"""Returns the transition matrix of G.</span> <span class="sd"> This is a row stochastic giving the transition probabilities while</span> <span class="sd"> performing a random walk on the graph. Depending on the value of walk_type,</span> @@ -941,7 +941,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/linalg/modularitymatrix.html b/_modules/networkx/linalg/modularitymatrix.html index a2aea089..e4ecc2e5 100644 --- a/_modules/networkx/linalg/modularitymatrix.html +++ b/_modules/networkx/linalg/modularitymatrix.html @@ -472,7 +472,7 @@ <div class="viewcode-block" id="modularity_matrix"><a class="viewcode-back" href="../../../reference/generated/networkx.linalg.modularitymatrix.modularity_matrix.html#networkx.linalg.modularitymatrix.modularity_matrix">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">modularity_matrix</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns the modularity matrix of G.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns the modularity matrix of G.</span> <span class="sd"> The modularity matrix is the matrix B = A - <A>, where A is the adjacency</span> <span class="sd"> matrix and <A> is the average adjacency matrix, assuming that the graph</span> @@ -540,7 +540,7 @@ <div class="viewcode-block" id="directed_modularity_matrix"><a class="viewcode-back" href="../../../reference/generated/networkx.linalg.modularitymatrix.directed_modularity_matrix.html#networkx.linalg.modularitymatrix.directed_modularity_matrix">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"undirected"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">directed_modularity_matrix</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns the directed modularity matrix of G.</span> +<span class="w"> </span><span class="sd">"""Returns the directed modularity matrix of G.</span> <span class="sd"> The modularity matrix is the matrix B = A - <A>, where A is the adjacency</span> <span class="sd"> matrix and <A> is the expected adjacency matrix, assuming that the graph</span> @@ -676,7 +676,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/linalg/spectrum.html b/_modules/networkx/linalg/spectrum.html index bbde9bc1..049aaaf9 100644 --- a/_modules/networkx/linalg/spectrum.html +++ b/_modules/networkx/linalg/spectrum.html @@ -476,7 +476,7 @@ <div class="viewcode-block" id="laplacian_spectrum"><a class="viewcode-back" href="../../../reference/generated/networkx.linalg.spectrum.laplacian_spectrum.html#networkx.linalg.spectrum.laplacian_spectrum">[docs]</a><span class="k">def</span> <span class="nf">laplacian_spectrum</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns eigenvalues of the Laplacian of G</span> +<span class="w"> </span><span class="sd">"""Returns eigenvalues of the Laplacian of G</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -520,7 +520,7 @@ <div class="viewcode-block" id="normalized_laplacian_spectrum"><a class="viewcode-back" href="../../../reference/generated/networkx.linalg.spectrum.normalized_laplacian_spectrum.html#networkx.linalg.spectrum.normalized_laplacian_spectrum">[docs]</a><span class="k">def</span> <span class="nf">normalized_laplacian_spectrum</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Return eigenvalues of the normalized Laplacian of G</span> +<span class="w"> </span><span class="sd">"""Return eigenvalues of the normalized Laplacian of G</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -554,7 +554,7 @@ <div class="viewcode-block" id="adjacency_spectrum"><a class="viewcode-back" href="../../../reference/generated/networkx.linalg.spectrum.adjacency_spectrum.html#networkx.linalg.spectrum.adjacency_spectrum">[docs]</a><span class="k">def</span> <span class="nf">adjacency_spectrum</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s2">"weight"</span><span class="p">):</span> - <span class="sd">"""Returns eigenvalues of the adjacency matrix of G.</span> +<span class="w"> </span><span class="sd">"""Returns eigenvalues of the adjacency matrix of G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -586,7 +586,7 @@ <div class="viewcode-block" id="modularity_spectrum"><a class="viewcode-back" href="../../../reference/generated/networkx.linalg.spectrum.modularity_spectrum.html#networkx.linalg.spectrum.modularity_spectrum">[docs]</a><span class="k">def</span> <span class="nf">modularity_spectrum</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Returns eigenvalues of the modularity matrix of G.</span> +<span class="w"> </span><span class="sd">"""Returns eigenvalues of the modularity matrix of G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -617,7 +617,7 @@ <div class="viewcode-block" id="bethe_hessian_spectrum"><a class="viewcode-back" href="../../../reference/generated/networkx.linalg.spectrum.bethe_hessian_spectrum.html#networkx.linalg.spectrum.bethe_hessian_spectrum">[docs]</a><span class="k">def</span> <span class="nf">bethe_hessian_spectrum</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">r</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns eigenvalues of the Bethe Hessian matrix of G.</span> +<span class="w"> </span><span class="sd">"""Returns eigenvalues of the Bethe Hessian matrix of G.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -697,7 +697,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/readwrite/adjlist.html b/_modules/networkx/readwrite/adjlist.html index 0ba8f3c3..3b97ea74 100644 --- a/_modules/networkx/readwrite/adjlist.html +++ b/_modules/networkx/readwrite/adjlist.html @@ -492,7 +492,7 @@ <div class="viewcode-block" id="generate_adjlist"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.adjlist.generate_adjlist.html#networkx.readwrite.adjlist.generate_adjlist">[docs]</a><span class="k">def</span> <span class="nf">generate_adjlist</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">delimiter</span><span class="o">=</span><span class="s2">" "</span><span class="p">):</span> - <span class="sd">"""Generate a single line of the graph G in adjacency list format.</span> +<span class="w"> </span><span class="sd">"""Generate a single line of the graph G in adjacency list format.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -551,7 +551,7 @@ <div class="viewcode-block" id="write_adjlist"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.adjlist.write_adjlist.html#networkx.readwrite.adjlist.write_adjlist">[docs]</a><span class="nd">@open_file</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"wb"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">write_adjlist</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">path</span><span class="p">,</span> <span class="n">comments</span><span class="o">=</span><span class="s2">"#"</span><span class="p">,</span> <span class="n">delimiter</span><span class="o">=</span><span class="s2">" "</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">):</span> - <span class="sd">"""Write graph G in single-line adjacency-list format to path.</span> +<span class="w"> </span><span class="sd">"""Write graph G in single-line adjacency-list format to path.</span> <span class="sd"> Parameters</span> @@ -616,7 +616,7 @@ <div class="viewcode-block" id="parse_adjlist"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.adjlist.parse_adjlist.html#networkx.readwrite.adjlist.parse_adjlist">[docs]</a><span class="k">def</span> <span class="nf">parse_adjlist</span><span class="p">(</span> <span class="n">lines</span><span class="p">,</span> <span class="n">comments</span><span class="o">=</span><span class="s2">"#"</span><span class="p">,</span> <span class="n">delimiter</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">nodetype</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Parse lines of a graph adjacency list representation.</span> +<span class="w"> </span><span class="sd">"""Parse lines of a graph adjacency list representation.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -694,7 +694,7 @@ <span class="n">nodetype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Read graph in adjacency list format from path.</span> +<span class="w"> </span><span class="sd">"""Read graph in adjacency list format from path.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -820,7 +820,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/readwrite/edgelist.html b/_modules/networkx/readwrite/edgelist.html index 2deb1ebe..eaa43342 100644 --- a/_modules/networkx/readwrite/edgelist.html +++ b/_modules/networkx/readwrite/edgelist.html @@ -504,7 +504,7 @@ <div class="viewcode-block" id="generate_edgelist"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.edgelist.generate_edgelist.html#networkx.readwrite.edgelist.generate_edgelist">[docs]</a><span class="k">def</span> <span class="nf">generate_edgelist</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">delimiter</span><span class="o">=</span><span class="s2">" "</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Generate a single line of the graph G in edge list format.</span> +<span class="w"> </span><span class="sd">"""Generate a single line of the graph G in edge list format.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -588,7 +588,7 @@ <div class="viewcode-block" id="write_edgelist"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.edgelist.write_edgelist.html#networkx.readwrite.edgelist.write_edgelist">[docs]</a><span class="nd">@open_file</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"wb"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">write_edgelist</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">path</span><span class="p">,</span> <span class="n">comments</span><span class="o">=</span><span class="s2">"#"</span><span class="p">,</span> <span class="n">delimiter</span><span class="o">=</span><span class="s2">" "</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">):</span> - <span class="sd">"""Write graph as a list of edges.</span> +<span class="w"> </span><span class="sd">"""Write graph as a list of edges.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -639,7 +639,7 @@ <div class="viewcode-block" id="parse_edgelist"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.edgelist.parse_edgelist.html#networkx.readwrite.edgelist.parse_edgelist">[docs]</a><span class="k">def</span> <span class="nf">parse_edgelist</span><span class="p">(</span> <span class="n">lines</span><span class="p">,</span> <span class="n">comments</span><span class="o">=</span><span class="s2">"#"</span><span class="p">,</span> <span class="n">delimiter</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">nodetype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="kc">True</span> <span class="p">):</span> - <span class="sd">"""Parse lines of an edge list representation of a graph.</span> +<span class="w"> </span><span class="sd">"""Parse lines of an edge list representation of a graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -770,7 +770,7 @@ <span class="n">edgetype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Read a graph from a list of edges.</span> +<span class="w"> </span><span class="sd">"""Read a graph from a list of edges.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -847,7 +847,7 @@ <div class="viewcode-block" id="write_weighted_edgelist"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.edgelist.write_weighted_edgelist.html#networkx.readwrite.edgelist.write_weighted_edgelist">[docs]</a><span class="k">def</span> <span class="nf">write_weighted_edgelist</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">path</span><span class="p">,</span> <span class="n">comments</span><span class="o">=</span><span class="s2">"#"</span><span class="p">,</span> <span class="n">delimiter</span><span class="o">=</span><span class="s2">" "</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">):</span> - <span class="sd">"""Write graph G as a list of edges with numeric weights.</span> +<span class="w"> </span><span class="sd">"""Write graph G as a list of edges with numeric weights.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -894,7 +894,7 @@ <span class="n">nodetype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Read a graph as list of edges with numeric weights.</span> +<span class="w"> </span><span class="sd">"""Read a graph as list of edges with numeric weights.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -998,7 +998,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/readwrite/gexf.html b/_modules/networkx/readwrite/gexf.html index 931347ac..5b64cc5a 100644 --- a/_modules/networkx/readwrite/gexf.html +++ b/_modules/networkx/readwrite/gexf.html @@ -497,7 +497,7 @@ <div class="viewcode-block" id="write_gexf"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.gexf.write_gexf.html#networkx.readwrite.gexf.write_gexf">[docs]</a><span class="nd">@open_file</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"wb"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">write_gexf</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">path</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">,</span> <span class="n">prettyprint</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">version</span><span class="o">=</span><span class="s2">"1.2draft"</span><span class="p">):</span> - <span class="sd">"""Write G in GEXF format to path.</span> +<span class="w"> </span><span class="sd">"""Write G in GEXF format to path.</span> <span class="sd"> "GEXF (Graph Exchange XML Format) is a language for describing</span> <span class="sd"> complex networks structures, their associated data and dynamics" [1]_.</span> @@ -551,7 +551,7 @@ <div class="viewcode-block" id="generate_gexf"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.gexf.generate_gexf.html#networkx.readwrite.gexf.generate_gexf">[docs]</a><span class="k">def</span> <span class="nf">generate_gexf</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">,</span> <span class="n">prettyprint</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">version</span><span class="o">=</span><span class="s2">"1.2draft"</span><span class="p">):</span> - <span class="sd">"""Generate lines of GEXF format representation of G.</span> +<span class="w"> </span><span class="sd">"""Generate lines of GEXF format representation of G.</span> <span class="sd"> "GEXF (Graph Exchange XML Format) is a language for describing</span> <span class="sd"> complex networks structures, their associated data and dynamics" [1]_.</span> @@ -597,7 +597,7 @@ <div class="viewcode-block" id="read_gexf"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.gexf.read_gexf.html#networkx.readwrite.gexf.read_gexf">[docs]</a><span class="nd">@open_file</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"rb"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">read_gexf</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">node_type</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">relabel</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">version</span><span class="o">=</span><span class="s2">"1.2draft"</span><span class="p">):</span> - <span class="sd">"""Read graph in GEXF format from path.</span> +<span class="w"> </span><span class="sd">"""Read graph in GEXF format from path.</span> <span class="sd"> "GEXF (Graph Exchange XML Format) is a language for describing</span> <span class="sd"> complex networks structures, their associated data and dynamics" [1]_.</span> @@ -1472,7 +1472,7 @@ <div class="viewcode-block" id="relabel_gexf_graph"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.gexf.relabel_gexf_graph.html#networkx.readwrite.gexf.relabel_gexf_graph">[docs]</a><span class="k">def</span> <span class="nf">relabel_gexf_graph</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Relabel graph using "label" node keyword for node label.</span> +<span class="w"> </span><span class="sd">"""Relabel graph using "label" node keyword for node label.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1572,7 +1572,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/readwrite/gml.html b/_modules/networkx/readwrite/gml.html index 2859e368..673c9714 100644 --- a/_modules/networkx/readwrite/gml.html +++ b/_modules/networkx/readwrite/gml.html @@ -507,7 +507,7 @@ <span class="k">def</span> <span class="nf">escape</span><span class="p">(</span><span class="n">text</span><span class="p">):</span> - <span class="sd">"""Use XML character references to escape characters.</span> +<span class="w"> </span><span class="sd">"""Use XML character references to escape characters.</span> <span class="sd"> Use XML character references for unprintable or non-ASCII</span> <span class="sd"> characters, double quotes and ampersands in a string</span> @@ -522,7 +522,7 @@ <span class="k">def</span> <span class="nf">unescape</span><span class="p">(</span><span class="n">text</span><span class="p">):</span> - <span class="sd">"""Replace XML character references with the referenced characters"""</span> +<span class="w"> </span><span class="sd">"""Replace XML character references with the referenced characters"""</span> <span class="k">def</span> <span class="nf">fixup</span><span class="p">(</span><span class="n">m</span><span class="p">):</span> <span class="n">text</span> <span class="o">=</span> <span class="n">m</span><span class="o">.</span><span class="n">group</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> @@ -547,7 +547,7 @@ <div class="viewcode-block" id="literal_destringizer"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.gml.literal_destringizer.html#networkx.readwrite.gml.literal_destringizer">[docs]</a><span class="k">def</span> <span class="nf">literal_destringizer</span><span class="p">(</span><span class="n">rep</span><span class="p">):</span> - <span class="sd">"""Convert a Python literal to the value it represents.</span> +<span class="w"> </span><span class="sd">"""Convert a Python literal to the value it represents.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -578,7 +578,7 @@ <div class="viewcode-block" id="read_gml"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.gml.read_gml.html#networkx.readwrite.gml.read_gml">[docs]</a><span class="nd">@open_file</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"rb"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">read_gml</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">"label"</span><span class="p">,</span> <span class="n">destringizer</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Read graph in GML format from `path`.</span> +<span class="w"> </span><span class="sd">"""Read graph in GML format from `path`.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -660,7 +660,7 @@ <div class="viewcode-block" id="parse_gml"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.gml.parse_gml.html#networkx.readwrite.gml.parse_gml">[docs]</a><span class="k">def</span> <span class="nf">parse_gml</span><span class="p">(</span><span class="n">lines</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">"label"</span><span class="p">,</span> <span class="n">destringizer</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Parse GML graph from a string or iterable.</span> +<span class="w"> </span><span class="sd">"""Parse GML graph from a string or iterable.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -737,7 +737,7 @@ <span class="k">class</span> <span class="nc">Pattern</span><span class="p">(</span><span class="n">Enum</span><span class="p">):</span> - <span class="sd">"""encodes the index of each token-matching pattern in `tokenize`."""</span> +<span class="w"> </span><span class="sd">"""encodes the index of each token-matching pattern in `tokenize`."""</span> <span class="n">KEYS</span> <span class="o">=</span> <span class="mi">0</span> <span class="n">REALS</span> <span class="o">=</span> <span class="mi">1</span> @@ -759,7 +759,7 @@ <span class="k">def</span> <span class="nf">parse_gml_lines</span><span class="p">(</span><span class="n">lines</span><span class="p">,</span> <span class="n">label</span><span class="p">,</span> <span class="n">destringizer</span><span class="p">):</span> - <span class="sd">"""Parse GML `lines` into a graph."""</span> +<span class="w"> </span><span class="sd">"""Parse GML `lines` into a graph."""</span> <span class="k">def</span> <span class="nf">tokenize</span><span class="p">():</span> <span class="n">patterns</span> <span class="o">=</span> <span class="p">[</span> @@ -780,7 +780,7 @@ <span class="k">while</span> <span class="n">pos</span> <span class="o"><</span> <span class="n">length</span><span class="p">:</span> <span class="n">match</span> <span class="o">=</span> <span class="n">tokens</span><span class="o">.</span><span class="n">match</span><span class="p">(</span><span class="n">line</span><span class="p">,</span> <span class="n">pos</span><span class="p">)</span> <span class="k">if</span> <span class="n">match</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> - <span class="n">m</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"cannot tokenize </span><span class="si">{</span><span class="n">line</span><span class="p">[</span><span class="n">pos</span><span class="p">:]</span><span class="si">}</span><span class="s2"> at (</span><span class="si">{</span><span class="n">lineno</span> <span class="o">+</span> <span class="mi">1</span><span class="si">}</span><span class="s2">, </span><span class="si">{</span><span class="n">pos</span> <span class="o">+</span> <span class="mi">1</span><span class="si">}</span><span class="s2">)"</span> + <span class="n">m</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"cannot tokenize </span><span class="si">{</span><span class="n">line</span><span class="p">[</span><span class="n">pos</span><span class="p">:]</span><span class="si">}</span><span class="s2"> at (</span><span class="si">{</span><span class="n">lineno</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">1</span><span class="si">}</span><span class="s2">, </span><span class="si">{</span><span class="n">pos</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">1</span><span class="si">}</span><span class="s2">)"</span> <span class="k">raise</span> <span class="n">NetworkXError</span><span class="p">(</span><span class="n">m</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">patterns</span><span class="p">)):</span> <span class="n">group</span> <span class="o">=</span> <span class="n">match</span><span class="o">.</span><span class="n">group</span><span class="p">(</span><span class="n">i</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> @@ -960,7 +960,7 @@ <div class="viewcode-block" id="literal_stringizer"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.gml.literal_stringizer.html#networkx.readwrite.gml.literal_stringizer">[docs]</a><span class="k">def</span> <span class="nf">literal_stringizer</span><span class="p">(</span><span class="n">value</span><span class="p">):</span> - <span class="sd">"""Convert a `value` to a Python literal in GML representation.</span> +<span class="w"> </span><span class="sd">"""Convert a `value` to a Python literal in GML representation.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1068,7 +1068,7 @@ <div class="viewcode-block" id="generate_gml"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.gml.generate_gml.html#networkx.readwrite.gml.generate_gml">[docs]</a><span class="k">def</span> <span class="nf">generate_gml</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">stringizer</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Generate a single entry of the graph `G` in GML format.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Generate a single entry of the graph `G` in GML format.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1258,7 +1258,7 @@ <div class="viewcode-block" id="write_gml"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.gml.write_gml.html#networkx.readwrite.gml.write_gml">[docs]</a><span class="nd">@open_file</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"wb"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">write_gml</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">path</span><span class="p">,</span> <span class="n">stringizer</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Write a graph `G` in GML format to the file or file handle `path`.</span> +<span class="w"> </span><span class="sd">"""Write a graph `G` in GML format to the file or file handle `path`.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1370,7 +1370,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/readwrite/graph6.html b/_modules/networkx/readwrite/graph6.html index e3d2727a..8c22affc 100644 --- a/_modules/networkx/readwrite/graph6.html +++ b/_modules/networkx/readwrite/graph6.html @@ -483,7 +483,7 @@ <span class="k">def</span> <span class="nf">_generate_graph6_bytes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">header</span><span class="p">):</span> - <span class="sd">"""Yield bytes in the graph6 encoding of a graph.</span> +<span class="w"> </span><span class="sd">"""Yield bytes in the graph6 encoding of a graph.</span> <span class="sd"> `G` is an undirected simple graph. `nodes` is the list of nodes for</span> <span class="sd"> which the node-induced subgraph will be encoded; if `nodes` is the</span> @@ -524,7 +524,7 @@ <div class="viewcode-block" id="from_graph6_bytes"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.graph6.from_graph6_bytes.html#networkx.readwrite.graph6.from_graph6_bytes">[docs]</a><span class="k">def</span> <span class="nf">from_graph6_bytes</span><span class="p">(</span><span class="n">bytes_in</span><span class="p">):</span> - <span class="sd">"""Read a simple undirected graph in graph6 format from bytes.</span> +<span class="w"> </span><span class="sd">"""Read a simple undirected graph in graph6 format from bytes.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -562,7 +562,7 @@ <span class="sd"> """</span> <span class="k">def</span> <span class="nf">bits</span><span class="p">():</span> - <span class="sd">"""Returns sequence of individual bits from 6-bit-per-value</span> +<span class="w"> </span><span class="sd">"""Returns sequence of individual bits from 6-bit-per-value</span> <span class="sd"> list of data values."""</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">data</span><span class="p">:</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">5</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]:</span> @@ -579,7 +579,7 @@ <span class="n">nd</span> <span class="o">=</span> <span class="p">(</span><span class="n">n</span> <span class="o">*</span> <span class="p">(</span><span class="n">n</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">//</span> <span class="mi">2</span> <span class="o">+</span> <span class="mi">5</span><span class="p">)</span> <span class="o">//</span> <span class="mi">6</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> <span class="o">!=</span> <span class="n">nd</span><span class="p">:</span> <span class="k">raise</span> <span class="n">NetworkXError</span><span class="p">(</span> - <span class="sa">f</span><span class="s2">"Expected </span><span class="si">{</span><span class="n">n</span> <span class="o">*</span> <span class="p">(</span><span class="n">n</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">//</span> <span class="mi">2</span><span class="si">}</span><span class="s2"> bits but got </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> <span class="o">*</span> <span class="mi">6</span><span class="si">}</span><span class="s2"> in graph6"</span> + <span class="sa">f</span><span class="s2">"Expected </span><span class="si">{</span><span class="n">n</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="p">(</span><span class="n">n</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="mi">1</span><span class="p">)</span><span class="w"> </span><span class="o">//</span><span class="w"> </span><span class="mi">2</span><span class="si">}</span><span class="s2"> bits but got </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="mi">6</span><span class="si">}</span><span class="s2"> in graph6"</span> <span class="p">)</span> <span class="n">G</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">Graph</span><span class="p">()</span> @@ -594,7 +594,7 @@ <div class="viewcode-block" id="to_graph6_bytes"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.graph6.to_graph6_bytes.html#networkx.readwrite.graph6.to_graph6_bytes">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">to_graph6_bytes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">header</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Convert a simple undirected graph to bytes in graph6 format.</span> +<span class="w"> </span><span class="sd">"""Convert a simple undirected graph to bytes in graph6 format.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -647,7 +647,7 @@ <div class="viewcode-block" id="read_graph6"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.graph6.read_graph6.html#networkx.readwrite.graph6.read_graph6">[docs]</a><span class="nd">@open_file</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"rb"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">read_graph6</span><span class="p">(</span><span class="n">path</span><span class="p">):</span> - <span class="sd">"""Read simple undirected graphs in graph6 format from path.</span> +<span class="w"> </span><span class="sd">"""Read simple undirected graphs in graph6 format from path.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -712,7 +712,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="nd">@open_file</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"wb"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">write_graph6</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">path</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">header</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Write a simple undirected graph to a path in graph6 format.</span> +<span class="w"> </span><span class="sd">"""Write a simple undirected graph to a path in graph6 format.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -772,7 +772,7 @@ <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"multigraph"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">write_graph6_file</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">f</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">header</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Write a simple undirected graph to a file-like object in graph6 format.</span> +<span class="w"> </span><span class="sd">"""Write a simple undirected graph to a file-like object in graph6 format.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -835,7 +835,7 @@ <span class="k">def</span> <span class="nf">data_to_n</span><span class="p">(</span><span class="n">data</span><span class="p">):</span> - <span class="sd">"""Read initial one-, four- or eight-unit value from graph6</span> +<span class="w"> </span><span class="sd">"""Read initial one-, four- or eight-unit value from graph6</span> <span class="sd"> integer sequence.</span> <span class="sd"> Return (value, rest of seq.)"""</span> @@ -855,7 +855,7 @@ <span class="k">def</span> <span class="nf">n_to_data</span><span class="p">(</span><span class="n">n</span><span class="p">):</span> - <span class="sd">"""Convert an integer to one-, four- or eight-unit graph6 sequence.</span> +<span class="w"> </span><span class="sd">"""Convert an integer to one-, four- or eight-unit graph6 sequence.</span> <span class="sd"> This function is undefined if `n` is not in ``range(2 ** 36)``.</span> @@ -926,7 +926,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/readwrite/graphml.html b/_modules/networkx/readwrite/graphml.html index c19cfda7..2d4de0ce 100644 --- a/_modules/networkx/readwrite/graphml.html +++ b/_modules/networkx/readwrite/graphml.html @@ -531,7 +531,7 @@ <span class="n">named_key_ids</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">edge_id_from_attribute</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Write G in GraphML XML format to path</span> +<span class="w"> </span><span class="sd">"""Write G in GraphML XML format to path</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -586,7 +586,7 @@ <span class="n">named_key_ids</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">edge_id_from_attribute</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Write G in GraphML XML format to path</span> +<span class="w"> </span><span class="sd">"""Write G in GraphML XML format to path</span> <span class="sd"> This function uses the LXML framework and should be faster than</span> <span class="sd"> the version using the xml library.</span> @@ -655,7 +655,7 @@ <span class="n">named_key_ids</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">edge_id_from_attribute</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Generate GraphML lines for G</span> +<span class="w"> </span><span class="sd">"""Generate GraphML lines for G</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -697,7 +697,7 @@ <div class="viewcode-block" id="read_graphml"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.graphml.read_graphml.html#networkx.readwrite.graphml.read_graphml">[docs]</a><span class="nd">@open_file</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"rb"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">read_graphml</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">node_type</span><span class="o">=</span><span class="nb">str</span><span class="p">,</span> <span class="n">edge_key_type</span><span class="o">=</span><span class="nb">int</span><span class="p">,</span> <span class="n">force_multigraph</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> - <span class="sd">"""Read graph in GraphML format from path.</span> +<span class="w"> </span><span class="sd">"""Read graph in GraphML format from path.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -771,7 +771,7 @@ <div class="viewcode-block" id="parse_graphml"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.graphml.parse_graphml.html#networkx.readwrite.graphml.parse_graphml">[docs]</a><span class="k">def</span> <span class="nf">parse_graphml</span><span class="p">(</span> <span class="n">graphml_string</span><span class="p">,</span> <span class="n">node_type</span><span class="o">=</span><span class="nb">str</span><span class="p">,</span> <span class="n">edge_key_type</span><span class="o">=</span><span class="nb">int</span><span class="p">,</span> <span class="n">force_multigraph</span><span class="o">=</span><span class="kc">False</span> <span class="p">):</span> - <span class="sd">"""Read graph in GraphML format from string.</span> +<span class="w"> </span><span class="sd">"""Read graph in GraphML format from string.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -910,7 +910,7 @@ <span class="p">}</span> <span class="k">def</span> <span class="nf">get_xml_type</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">key</span><span class="p">):</span> - <span class="sd">"""Wrapper around the xml_type dict that raises a more informative</span> +<span class="w"> </span><span class="sd">"""Wrapper around the xml_type dict that raises a more informative</span> <span class="sd"> exception message when a user attempts to use data of a type not</span> <span class="sd"> supported by GraphML."""</span> <span class="k">try</span><span class="p">:</span> @@ -965,7 +965,7 @@ <span class="k">return</span> <span class="n">s</span> <span class="k">def</span> <span class="nf">attr_type</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">scope</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> - <span class="sd">"""Infer the attribute type of data named name. Currently this only</span> +<span class="w"> </span><span class="sd">"""Infer the attribute type of data named name. Currently this only</span> <span class="sd"> supports inference of numeric types.</span> <span class="sd"> If self.infer_numeric_types is false, type is used. Otherwise, pick the</span> @@ -1016,7 +1016,7 @@ <span class="k">return</span> <span class="n">new_id</span> <span class="k">def</span> <span class="nf">add_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">element_type</span><span class="p">,</span> <span class="n">value</span><span class="p">,</span> <span class="n">scope</span><span class="o">=</span><span class="s2">"all"</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Make a data element for an edge or a node. Keep a log of the</span> <span class="sd"> type in the keys table.</span> <span class="sd"> """</span> @@ -1030,7 +1030,7 @@ <span class="k">return</span> <span class="n">data_element</span> <span class="k">def</span> <span class="nf">add_attributes</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scope</span><span class="p">,</span> <span class="n">xml_obj</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">default</span><span class="p">):</span> - <span class="sd">"""Appends attribute data to edges or nodes, and stores type information</span> +<span class="w"> </span><span class="sd">"""Appends attribute data to edges or nodes, and stores type information</span> <span class="sd"> to be added later. See add_graph_element.</span> <span class="sd"> """</span> <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">data</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> @@ -1077,7 +1077,7 @@ <span class="n">graph_element</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">edge_element</span><span class="p">)</span> <span class="k">def</span> <span class="nf">add_graph_element</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Serialize graph G in GraphML to the stream.</span> <span class="sd"> """</span> <span class="k">if</span> <span class="n">G</span><span class="o">.</span><span class="n">is_directed</span><span class="p">():</span> @@ -1116,7 +1116,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">xml</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">graph_element</span><span class="p">)</span> <span class="k">def</span> <span class="nf">add_graphs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">graph_list</span><span class="p">):</span> - <span class="sd">"""Add many graphs to this GraphML document."""</span> +<span class="w"> </span><span class="sd">"""Add many graphs to this GraphML document."""</span> <span class="k">for</span> <span class="n">G</span> <span class="ow">in</span> <span class="n">graph_list</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">add_graph_element</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> @@ -1146,7 +1146,7 @@ <span class="k">class</span> <span class="nc">IncrementalElement</span><span class="p">:</span> - <span class="sd">"""Wrapper for _IncrementalWriter providing an Element like interface.</span> +<span class="w"> </span><span class="sd">"""Wrapper for _IncrementalWriter providing an Element like interface.</span> <span class="sd"> This wrapper does not intend to be a complete implementation but rather to</span> <span class="sd"> deal with those calls used in GraphMLWriter.</span> @@ -1208,7 +1208,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">add_graph_element</span><span class="p">(</span><span class="n">graph</span><span class="p">)</span> <span class="k">def</span> <span class="nf">add_graph_element</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Serialize graph G in GraphML to the stream.</span> <span class="sd"> """</span> <span class="k">if</span> <span class="n">G</span><span class="o">.</span><span class="n">is_directed</span><span class="p">():</span> @@ -1278,7 +1278,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">add_edges</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">incremental_writer</span><span class="p">)</span> <span class="c1"># adds attributes too</span> <span class="k">def</span> <span class="nf">add_attributes</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scope</span><span class="p">,</span> <span class="n">xml_obj</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">default</span><span class="p">):</span> - <span class="sd">"""Appends attribute data."""</span> +<span class="w"> </span><span class="sd">"""Appends attribute data."""</span> <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">data</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> <span class="n">data_element</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">add_data</span><span class="p">(</span> <span class="nb">str</span><span class="p">(</span><span class="n">k</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">attr_type</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">k</span><span class="p">),</span> <span class="n">scope</span><span class="p">,</span> <span class="n">v</span><span class="p">),</span> <span class="nb">str</span><span class="p">(</span><span class="n">v</span><span class="p">),</span> <span class="n">scope</span><span class="p">,</span> <span class="n">default</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">k</span><span class="p">)</span> @@ -1298,7 +1298,7 @@ <span class="k">class</span> <span class="nc">GraphMLReader</span><span class="p">(</span><span class="n">GraphML</span><span class="p">):</span> - <span class="sd">"""Read a GraphML document. Produces NetworkX graph objects."""</span> +<span class="w"> </span><span class="sd">"""Read a GraphML document. Produces NetworkX graph objects."""</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">node_type</span><span class="o">=</span><span class="nb">str</span><span class="p">,</span> <span class="n">edge_key_type</span><span class="o">=</span><span class="nb">int</span><span class="p">,</span> <span class="n">force_multigraph</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span> <span class="bp">self</span><span class="o">.</span><span class="n">construct_types</span><span class="p">()</span> @@ -1363,7 +1363,7 @@ <span class="k">return</span> <span class="n">G</span> <span class="k">def</span> <span class="nf">add_node</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G</span><span class="p">,</span> <span class="n">node_xml</span><span class="p">,</span> <span class="n">graphml_keys</span><span class="p">,</span> <span class="n">defaults</span><span class="p">):</span> - <span class="sd">"""Add a node to the graph."""</span> +<span class="w"> </span><span class="sd">"""Add a node to the graph."""</span> <span class="c1"># warn on finding unsupported ports tag</span> <span class="n">ports</span> <span class="o">=</span> <span class="n">node_xml</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">{{</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">NS_GRAPHML</span><span class="si">}</span><span class="se">}}</span><span class="s2">port"</span><span class="p">)</span> <span class="k">if</span> <span class="n">ports</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> @@ -1379,7 +1379,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">make_graph</span><span class="p">(</span><span class="n">graph_xml</span><span class="p">,</span> <span class="n">graphml_keys</span><span class="p">,</span> <span class="n">defaults</span><span class="p">,</span> <span class="n">G</span><span class="p">)</span> <span class="k">def</span> <span class="nf">add_edge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">G</span><span class="p">,</span> <span class="n">edge_element</span><span class="p">,</span> <span class="n">graphml_keys</span><span class="p">):</span> - <span class="sd">"""Add an edge to the graph."""</span> +<span class="w"> </span><span class="sd">"""Add an edge to the graph."""</span> <span class="c1"># warn on finding unsupported ports tag</span> <span class="n">ports</span> <span class="o">=</span> <span class="n">edge_element</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">{{</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">NS_GRAPHML</span><span class="si">}</span><span class="se">}}</span><span class="s2">port"</span><span class="p">)</span> <span class="k">if</span> <span class="n">ports</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> @@ -1420,7 +1420,7 @@ <span class="n">G</span><span class="o">.</span><span class="n">add_edges_from</span><span class="p">([(</span><span class="n">source</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">edge_id</span><span class="p">,</span> <span class="n">data</span><span class="p">)])</span> <span class="k">def</span> <span class="nf">decode_data_elements</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">graphml_keys</span><span class="p">,</span> <span class="n">obj_xml</span><span class="p">):</span> - <span class="sd">"""Use the key information to decode the data XML if present."""</span> +<span class="w"> </span><span class="sd">"""Use the key information to decode the data XML if present."""</span> <span class="n">data</span> <span class="o">=</span> <span class="p">{}</span> <span class="k">for</span> <span class="n">data_element</span> <span class="ow">in</span> <span class="n">obj_xml</span><span class="o">.</span><span class="n">findall</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">{{</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">NS_GRAPHML</span><span class="si">}</span><span class="se">}}</span><span class="s2">data"</span><span class="p">):</span> <span class="n">key</span> <span class="o">=</span> <span class="n">data_element</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"key"</span><span class="p">)</span> @@ -1478,7 +1478,7 @@ <span class="k">return</span> <span class="n">data</span> <span class="k">def</span> <span class="nf">find_graphml_keys</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">graph_element</span><span class="p">):</span> - <span class="sd">"""Extracts all the keys and key defaults from the xml."""</span> +<span class="w"> </span><span class="sd">"""Extracts all the keys and key defaults from the xml."""</span> <span class="n">graphml_keys</span> <span class="o">=</span> <span class="p">{}</span> <span class="n">graphml_key_defaults</span> <span class="o">=</span> <span class="p">{}</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">graph_element</span><span class="o">.</span><span class="n">findall</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">{{</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">NS_GRAPHML</span><span class="si">}</span><span class="se">}}</span><span class="s2">key"</span><span class="p">):</span> @@ -1562,7 +1562,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/readwrite/json_graph/adjacency.html b/_modules/networkx/readwrite/json_graph/adjacency.html index 7258c8d8..2a77623f 100644 --- a/_modules/networkx/readwrite/json_graph/adjacency.html +++ b/_modules/networkx/readwrite/json_graph/adjacency.html @@ -471,7 +471,7 @@ <div class="viewcode-block" id="adjacency_data"><a class="viewcode-back" href="../../../../reference/readwrite/generated/networkx.readwrite.json_graph.adjacency_data.html#networkx.readwrite.json_graph.adjacency_data">[docs]</a><span class="k">def</span> <span class="nf">adjacency_data</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">attrs</span><span class="o">=</span><span class="n">_attrs</span><span class="p">):</span> - <span class="sd">"""Returns data in adjacency format that is suitable for JSON serialization</span> +<span class="w"> </span><span class="sd">"""Returns data in adjacency format that is suitable for JSON serialization</span> <span class="sd"> and use in Javascript documents.</span> <span class="sd"> Parameters</span> @@ -547,7 +547,7 @@ <div class="viewcode-block" id="adjacency_graph"><a class="viewcode-back" href="../../../../reference/readwrite/generated/networkx.readwrite.json_graph.adjacency_graph.html#networkx.readwrite.json_graph.adjacency_graph">[docs]</a><span class="k">def</span> <span class="nf">adjacency_graph</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">directed</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">multigraph</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">attrs</span><span class="o">=</span><span class="n">_attrs</span><span class="p">):</span> - <span class="sd">"""Returns graph from adjacency data format.</span> +<span class="w"> </span><span class="sd">"""Returns graph from adjacency data format.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -669,7 +669,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/readwrite/json_graph/cytoscape.html b/_modules/networkx/readwrite/json_graph/cytoscape.html index c54f4f9a..aa278968 100644 --- a/_modules/networkx/readwrite/json_graph/cytoscape.html +++ b/_modules/networkx/readwrite/json_graph/cytoscape.html @@ -467,7 +467,7 @@ <div class="viewcode-block" id="cytoscape_data"><a class="viewcode-back" href="../../../../reference/readwrite/generated/networkx.readwrite.json_graph.cytoscape_data.html#networkx.readwrite.json_graph.cytoscape_data">[docs]</a><span class="k">def</span> <span class="nf">cytoscape_data</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">"name"</span><span class="p">,</span> <span class="n">ident</span><span class="o">=</span><span class="s2">"id"</span><span class="p">):</span> - <span class="sd">"""Returns data in Cytoscape JSON format (cyjs).</span> +<span class="w"> </span><span class="sd">"""Returns data in Cytoscape JSON format (cyjs).</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -544,7 +544,7 @@ <div class="viewcode-block" id="cytoscape_graph"><a class="viewcode-back" href="../../../../reference/readwrite/generated/networkx.readwrite.json_graph.cytoscape_graph.html#networkx.readwrite.json_graph.cytoscape_graph">[docs]</a><span class="k">def</span> <span class="nf">cytoscape_graph</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">"name"</span><span class="p">,</span> <span class="n">ident</span><span class="o">=</span><span class="s2">"id"</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Create a NetworkX graph from a dictionary in cytoscape JSON format.</span> <span class="sd"> Parameters</span> @@ -685,7 +685,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/readwrite/json_graph/node_link.html b/_modules/networkx/readwrite/json_graph/node_link.html index 1e56e9f1..681057c3 100644 --- a/_modules/networkx/readwrite/json_graph/node_link.html +++ b/_modules/networkx/readwrite/json_graph/node_link.html @@ -472,7 +472,7 @@ <span class="k">def</span> <span class="nf">_to_tuple</span><span class="p">(</span><span class="n">x</span><span class="p">):</span> - <span class="sd">"""Converts lists to tuples, including nested lists.</span> +<span class="w"> </span><span class="sd">"""Converts lists to tuples, including nested lists.</span> <span class="sd"> All other non-list inputs are passed through unmodified. This function is</span> <span class="sd"> intended to be used to convert potentially nested lists from json files</span> @@ -498,7 +498,7 @@ <span class="n">key</span><span class="o">=</span><span class="s2">"key"</span><span class="p">,</span> <span class="n">link</span><span class="o">=</span><span class="s2">"links"</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns data in node-link format that is suitable for JSON serialization</span> +<span class="w"> </span><span class="sd">"""Returns data in node-link format that is suitable for JSON serialization</span> <span class="sd"> and use in Javascript documents.</span> <span class="sd"> Parameters</span> @@ -653,7 +653,7 @@ <span class="n">key</span><span class="o">=</span><span class="s2">"key"</span><span class="p">,</span> <span class="n">link</span><span class="o">=</span><span class="s2">"links"</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Returns graph from node-link data format.</span> +<span class="w"> </span><span class="sd">"""Returns graph from node-link data format.</span> <span class="sd"> Useful for de-serialization from JSON.</span> <span class="sd"> Parameters</span> @@ -845,7 +845,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/readwrite/json_graph/tree.html b/_modules/networkx/readwrite/json_graph/tree.html index 8e67fb6e..3f234250 100644 --- a/_modules/networkx/readwrite/json_graph/tree.html +++ b/_modules/networkx/readwrite/json_graph/tree.html @@ -469,7 +469,7 @@ <div class="viewcode-block" id="tree_data"><a class="viewcode-back" href="../../../../reference/readwrite/generated/networkx.readwrite.json_graph.tree_data.html#networkx.readwrite.json_graph.tree_data">[docs]</a><span class="k">def</span> <span class="nf">tree_data</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">root</span><span class="p">,</span> <span class="n">ident</span><span class="o">=</span><span class="s2">"id"</span><span class="p">,</span> <span class="n">children</span><span class="o">=</span><span class="s2">"children"</span><span class="p">):</span> - <span class="sd">"""Returns data in tree format that is suitable for JSON serialization</span> +<span class="w"> </span><span class="sd">"""Returns data in tree format that is suitable for JSON serialization</span> <span class="sd"> and use in Javascript documents.</span> <span class="sd"> Parameters</span> @@ -549,7 +549,7 @@ <div class="viewcode-block" id="tree_graph"><a class="viewcode-back" href="../../../../reference/readwrite/generated/networkx.readwrite.json_graph.tree_graph.html#networkx.readwrite.json_graph.tree_graph">[docs]</a><span class="k">def</span> <span class="nf">tree_graph</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">ident</span><span class="o">=</span><span class="s2">"id"</span><span class="p">,</span> <span class="n">children</span><span class="o">=</span><span class="s2">"children"</span><span class="p">):</span> - <span class="sd">"""Returns graph from tree data format.</span> +<span class="w"> </span><span class="sd">"""Returns graph from tree data format.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -650,7 +650,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/readwrite/leda.html b/_modules/networkx/readwrite/leda.html index 13b69cac..9bf80df0 100644 --- a/_modules/networkx/readwrite/leda.html +++ b/_modules/networkx/readwrite/leda.html @@ -483,7 +483,7 @@ <div class="viewcode-block" id="read_leda"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.leda.read_leda.html#networkx.readwrite.leda.read_leda">[docs]</a><span class="nd">@open_file</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"rb"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">read_leda</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"UTF-8"</span><span class="p">):</span> - <span class="sd">"""Read graph in LEDA format from path.</span> +<span class="w"> </span><span class="sd">"""Read graph in LEDA format from path.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -509,7 +509,7 @@ <div class="viewcode-block" id="parse_leda"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.leda.parse_leda.html#networkx.readwrite.leda.parse_leda">[docs]</a><span class="k">def</span> <span class="nf">parse_leda</span><span class="p">(</span><span class="n">lines</span><span class="p">):</span> - <span class="sd">"""Read graph in LEDA format from string or iterable.</span> +<span class="w"> </span><span class="sd">"""Read graph in LEDA format from string or iterable.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -618,7 +618,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/readwrite/multiline_adjlist.html b/_modules/networkx/readwrite/multiline_adjlist.html index f30bb23b..10e68a3c 100644 --- a/_modules/networkx/readwrite/multiline_adjlist.html +++ b/_modules/networkx/readwrite/multiline_adjlist.html @@ -500,7 +500,7 @@ <div class="viewcode-block" id="generate_multiline_adjlist"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.multiline_adjlist.generate_multiline_adjlist.html#networkx.readwrite.multiline_adjlist.generate_multiline_adjlist">[docs]</a><span class="k">def</span> <span class="nf">generate_multiline_adjlist</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">delimiter</span><span class="o">=</span><span class="s2">" "</span><span class="p">):</span> - <span class="sd">"""Generate a single line of the graph G in multiline adjacency list format.</span> +<span class="w"> </span><span class="sd">"""Generate a single line of the graph G in multiline adjacency list format.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -598,7 +598,7 @@ <div class="viewcode-block" id="write_multiline_adjlist"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.multiline_adjlist.write_multiline_adjlist.html#networkx.readwrite.multiline_adjlist.write_multiline_adjlist">[docs]</a><span class="nd">@open_file</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"wb"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">write_multiline_adjlist</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">path</span><span class="p">,</span> <span class="n">delimiter</span><span class="o">=</span><span class="s2">" "</span><span class="p">,</span> <span class="n">comments</span><span class="o">=</span><span class="s2">"#"</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">):</span> - <span class="sd">"""Write the graph G in multiline adjacency list format to path</span> +<span class="w"> </span><span class="sd">"""Write the graph G in multiline adjacency list format to path</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -657,7 +657,7 @@ <div class="viewcode-block" id="parse_multiline_adjlist"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.multiline_adjlist.parse_multiline_adjlist.html#networkx.readwrite.multiline_adjlist.parse_multiline_adjlist">[docs]</a><span class="k">def</span> <span class="nf">parse_multiline_adjlist</span><span class="p">(</span> <span class="n">lines</span><span class="p">,</span> <span class="n">comments</span><span class="o">=</span><span class="s2">"#"</span><span class="p">,</span> <span class="n">delimiter</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">nodetype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">edgetype</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Parse lines of a multiline adjacency list representation of a graph.</span> +<span class="w"> </span><span class="sd">"""Parse lines of a multiline adjacency list representation of a graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -772,7 +772,7 @@ <span class="n">edgetype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">,</span> <span class="p">):</span> - <span class="sd">"""Read graph in multi-line adjacency list format from path.</span> +<span class="w"> </span><span class="sd">"""Read graph in multi-line adjacency list format from path.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -903,7 +903,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/readwrite/pajek.html b/_modules/networkx/readwrite/pajek.html index 657fdc1f..81b03f30 100644 --- a/_modules/networkx/readwrite/pajek.html +++ b/_modules/networkx/readwrite/pajek.html @@ -486,7 +486,7 @@ <div class="viewcode-block" id="generate_pajek"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.pajek.generate_pajek.html#networkx.readwrite.pajek.generate_pajek">[docs]</a><span class="k">def</span> <span class="nf">generate_pajek</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Generate lines in Pajek graph format.</span> +<span class="w"> </span><span class="sd">"""Generate lines in Pajek graph format.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -536,7 +536,7 @@ <span class="n">s</span> <span class="o">+=</span> <span class="sa">f</span><span class="s2">" </span><span class="si">{</span><span class="n">make_qstr</span><span class="p">(</span><span class="n">k</span><span class="p">)</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="n">make_qstr</span><span class="p">(</span><span class="n">v</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span> <span class="k">else</span><span class="p">:</span> <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span> - <span class="sa">f</span><span class="s2">"Node attribute </span><span class="si">{</span><span class="n">k</span><span class="si">}</span><span class="s2"> is not processed. </span><span class="si">{</span><span class="p">(</span><span class="s1">'Empty attribute'</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">v</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> <span class="k">else</span> <span class="s1">'Non-string attribute'</span><span class="p">)</span><span class="si">}</span><span class="s2">."</span> + <span class="sa">f</span><span class="s2">"Node attribute </span><span class="si">{</span><span class="n">k</span><span class="si">}</span><span class="s2"> is not processed. </span><span class="si">{</span><span class="p">(</span><span class="s1">'Empty attribute'</span><span class="w"> </span><span class="k">if</span><span class="w"> </span><span class="nb">isinstance</span><span class="p">(</span><span class="n">v</span><span class="p">,</span><span class="w"> </span><span class="nb">str</span><span class="p">)</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="s1">'Non-string attribute'</span><span class="p">)</span><span class="si">}</span><span class="s2">."</span> <span class="p">)</span> <span class="k">yield</span> <span class="n">s</span> @@ -554,14 +554,14 @@ <span class="n">s</span> <span class="o">+=</span> <span class="sa">f</span><span class="s2">" </span><span class="si">{</span><span class="n">make_qstr</span><span class="p">(</span><span class="n">k</span><span class="p">)</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="n">make_qstr</span><span class="p">(</span><span class="n">v</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span> <span class="k">else</span><span class="p">:</span> <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span> - <span class="sa">f</span><span class="s2">"Edge attribute </span><span class="si">{</span><span class="n">k</span><span class="si">}</span><span class="s2"> is not processed. </span><span class="si">{</span><span class="p">(</span><span class="s1">'Empty attribute'</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">v</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> <span class="k">else</span> <span class="s1">'Non-string attribute'</span><span class="p">)</span><span class="si">}</span><span class="s2">."</span> + <span class="sa">f</span><span class="s2">"Edge attribute </span><span class="si">{</span><span class="n">k</span><span class="si">}</span><span class="s2"> is not processed. </span><span class="si">{</span><span class="p">(</span><span class="s1">'Empty attribute'</span><span class="w"> </span><span class="k">if</span><span class="w"> </span><span class="nb">isinstance</span><span class="p">(</span><span class="n">v</span><span class="p">,</span><span class="w"> </span><span class="nb">str</span><span class="p">)</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="s1">'Non-string attribute'</span><span class="p">)</span><span class="si">}</span><span class="s2">."</span> <span class="p">)</span> <span class="k">yield</span> <span class="n">s</span></div> <div class="viewcode-block" id="write_pajek"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.pajek.write_pajek.html#networkx.readwrite.pajek.write_pajek">[docs]</a><span class="nd">@open_file</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"wb"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">write_pajek</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">path</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"UTF-8"</span><span class="p">):</span> - <span class="sd">"""Write graph in Pajek format to path.</span> +<span class="w"> </span><span class="sd">"""Write graph in Pajek format to path.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -594,7 +594,7 @@ <div class="viewcode-block" id="read_pajek"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.pajek.read_pajek.html#networkx.readwrite.pajek.read_pajek">[docs]</a><span class="nd">@open_file</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"rb"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">read_pajek</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"UTF-8"</span><span class="p">):</span> - <span class="sd">"""Read graph in Pajek format from path.</span> +<span class="w"> </span><span class="sd">"""Read graph in Pajek format from path.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -626,7 +626,7 @@ <div class="viewcode-block" id="parse_pajek"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.pajek.parse_pajek.html#networkx.readwrite.pajek.parse_pajek">[docs]</a><span class="k">def</span> <span class="nf">parse_pajek</span><span class="p">(</span><span class="n">lines</span><span class="p">):</span> - <span class="sd">"""Parse Pajek format graph from string or iterable.</span> +<span class="w"> </span><span class="sd">"""Parse Pajek format graph from string or iterable.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -737,7 +737,7 @@ <span class="k">def</span> <span class="nf">make_qstr</span><span class="p">(</span><span class="n">t</span><span class="p">):</span> - <span class="sd">"""Returns the string representation of t.</span> +<span class="w"> </span><span class="sd">"""Returns the string representation of t.</span> <span class="sd"> Add outer double-quotes if the string has a space.</span> <span class="sd"> """</span> <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span> @@ -796,7 +796,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/readwrite/sparse6.html b/_modules/networkx/readwrite/sparse6.html index 4f2e7a69..586dd651 100644 --- a/_modules/networkx/readwrite/sparse6.html +++ b/_modules/networkx/readwrite/sparse6.html @@ -483,7 +483,7 @@ <span class="k">def</span> <span class="nf">_generate_sparse6_bytes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">header</span><span class="p">):</span> - <span class="sd">"""Yield bytes in the sparse6 encoding of a graph.</span> +<span class="w"> </span><span class="sd">"""Yield bytes in the sparse6 encoding of a graph.</span> <span class="sd"> `G` is an undirected simple graph. `nodes` is the list of nodes for</span> <span class="sd"> which the node-induced subgraph will be encoded; if `nodes` is the</span> @@ -519,7 +519,7 @@ <span class="n">k</span> <span class="o">+=</span> <span class="mi">1</span> <span class="k">def</span> <span class="nf">enc</span><span class="p">(</span><span class="n">x</span><span class="p">):</span> - <span class="sd">"""Big endian k-bit encoding of x"""</span> +<span class="w"> </span><span class="sd">"""Big endian k-bit encoding of x"""</span> <span class="k">return</span> <span class="p">[</span><span class="mi">1</span> <span class="k">if</span> <span class="p">(</span><span class="n">x</span> <span class="o">&</span> <span class="mi">1</span> <span class="o"><<</span> <span class="p">(</span><span class="n">k</span> <span class="o">-</span> <span class="mi">1</span> <span class="o">-</span> <span class="n">i</span><span class="p">))</span> <span class="k">else</span> <span class="mi">0</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">k</span><span class="p">)]</span> <span class="n">edges</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">((</span><span class="nb">max</span><span class="p">(</span><span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">),</span> <span class="nb">min</span><span class="p">(</span><span class="n">u</span><span class="p">,</span> <span class="n">v</span><span class="p">))</span> <span class="k">for</span> <span class="n">u</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">G</span><span class="o">.</span><span class="n">edges</span><span class="p">())</span> @@ -565,7 +565,7 @@ <div class="viewcode-block" id="from_sparse6_bytes"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.sparse6.from_sparse6_bytes.html#networkx.readwrite.sparse6.from_sparse6_bytes">[docs]</a><span class="k">def</span> <span class="nf">from_sparse6_bytes</span><span class="p">(</span><span class="n">string</span><span class="p">):</span> - <span class="sd">"""Read an undirected graph in sparse6 format from string.</span> +<span class="w"> </span><span class="sd">"""Read an undirected graph in sparse6 format from string.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -609,7 +609,7 @@ <span class="n">k</span> <span class="o">+=</span> <span class="mi">1</span> <span class="k">def</span> <span class="nf">parseData</span><span class="p">():</span> - <span class="sd">"""Returns stream of pairs b[i], x[i] for sparse6 format."""</span> +<span class="w"> </span><span class="sd">"""Returns stream of pairs b[i], x[i] for sparse6 format."""</span> <span class="n">chunks</span> <span class="o">=</span> <span class="nb">iter</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> <span class="n">d</span> <span class="o">=</span> <span class="kc">None</span> <span class="c1"># partial data word</span> <span class="n">dLen</span> <span class="o">=</span> <span class="mi">0</span> <span class="c1"># how many unparsed bits are left in d</span> @@ -662,7 +662,7 @@ <div class="viewcode-block" id="to_sparse6_bytes"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.sparse6.to_sparse6_bytes.html#networkx.readwrite.sparse6.to_sparse6_bytes">[docs]</a><span class="k">def</span> <span class="nf">to_sparse6_bytes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">header</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Convert an undirected graph to bytes in sparse6 format.</span> +<span class="w"> </span><span class="sd">"""Convert an undirected graph to bytes in sparse6 format.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -713,7 +713,7 @@ <div class="viewcode-block" id="read_sparse6"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.sparse6.read_sparse6.html#networkx.readwrite.sparse6.read_sparse6">[docs]</a><span class="nd">@open_file</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"rb"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">read_sparse6</span><span class="p">(</span><span class="n">path</span><span class="p">):</span> - <span class="sd">"""Read an undirected graph in sparse6 format from path.</span> +<span class="w"> </span><span class="sd">"""Read an undirected graph in sparse6 format from path.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -777,7 +777,7 @@ <div class="viewcode-block" id="write_sparse6"><a class="viewcode-back" href="../../../reference/readwrite/generated/networkx.readwrite.sparse6.write_sparse6.html#networkx.readwrite.sparse6.write_sparse6">[docs]</a><span class="nd">@not_implemented_for</span><span class="p">(</span><span class="s2">"directed"</span><span class="p">)</span> <span class="nd">@open_file</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"wb"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">write_sparse6</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">path</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">header</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Write graph G to given path in sparse6 format.</span> +<span class="w"> </span><span class="sd">"""Write graph G to given path in sparse6 format.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -886,7 +886,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/relabel.html b/_modules/networkx/relabel.html index 636eacb3..6b65465e 100644 --- a/_modules/networkx/relabel.html +++ b/_modules/networkx/relabel.html @@ -467,7 +467,7 @@ <div class="viewcode-block" id="relabel_nodes"><a class="viewcode-back" href="../../reference/generated/networkx.relabel.relabel_nodes.html#networkx.relabel.relabel_nodes">[docs]</a><span class="k">def</span> <span class="nf">relabel_nodes</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">mapping</span><span class="p">,</span> <span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Relabel the nodes of the graph G according to a given mapping.</span> +<span class="w"> </span><span class="sd">"""Relabel the nodes of the graph G according to a given mapping.</span> <span class="sd"> The original node ordering may not be preserved if `copy` is `False` and the</span> <span class="sd"> mapping includes overlap between old and new labels.</span> @@ -686,7 +686,7 @@ <div class="viewcode-block" id="convert_node_labels_to_integers"><a class="viewcode-back" href="../../reference/generated/networkx.relabel.convert_node_labels_to_integers.html#networkx.relabel.convert_node_labels_to_integers">[docs]</a><span class="k">def</span> <span class="nf">convert_node_labels_to_integers</span><span class="p">(</span> <span class="n">G</span><span class="p">,</span> <span class="n">first_label</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">ordering</span><span class="o">=</span><span class="s2">"default"</span><span class="p">,</span> <span class="n">label_attribute</span><span class="o">=</span><span class="kc">None</span> <span class="p">):</span> - <span class="sd">"""Returns a copy of the graph G with the nodes relabeled using</span> +<span class="w"> </span><span class="sd">"""Returns a copy of the graph G with the nodes relabeled using</span> <span class="sd"> consecutive integers.</span> <span class="sd"> Parameters</span> @@ -793,7 +793,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/utils/decorators.html b/_modules/networkx/utils/decorators.html index 09fcad82..f2bddfee 100644 --- a/_modules/networkx/utils/decorators.html +++ b/_modules/networkx/utils/decorators.html @@ -486,7 +486,7 @@ <div class="viewcode-block" id="not_implemented_for"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.decorators.not_implemented_for.html#networkx.utils.decorators.not_implemented_for">[docs]</a><span class="k">def</span> <span class="nf">not_implemented_for</span><span class="p">(</span><span class="o">*</span><span class="n">graph_types</span><span class="p">):</span> - <span class="sd">"""Decorator to mark algorithms as not implemented</span> +<span class="w"> </span><span class="sd">"""Decorator to mark algorithms as not implemented</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -564,7 +564,7 @@ <div class="viewcode-block" id="open_file"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.decorators.open_file.html#networkx.utils.decorators.open_file">[docs]</a><span class="k">def</span> <span class="nf">open_file</span><span class="p">(</span><span class="n">path_arg</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"r"</span><span class="p">):</span> - <span class="sd">"""Decorator to ensure clean opening and closing of files.</span> +<span class="w"> </span><span class="sd">"""Decorator to ensure clean opening and closing of files.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -656,7 +656,7 @@ <div class="viewcode-block" id="nodes_or_number"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.decorators.nodes_or_number.html#networkx.utils.decorators.nodes_or_number">[docs]</a><span class="k">def</span> <span class="nf">nodes_or_number</span><span class="p">(</span><span class="n">which_args</span><span class="p">):</span> - <span class="sd">"""Decorator to allow number of nodes or container of nodes.</span> +<span class="w"> </span><span class="sd">"""Decorator to allow number of nodes or container of nodes.</span> <span class="sd"> With this decorator, the specified argument can be either a number or a container</span> <span class="sd"> of nodes. If it is a number, the nodes used are `range(n)`.</span> @@ -720,7 +720,7 @@ <div class="viewcode-block" id="np_random_state"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.decorators.np_random_state.html#networkx.utils.decorators.np_random_state">[docs]</a><span class="k">def</span> <span class="nf">np_random_state</span><span class="p">(</span><span class="n">random_state_argument</span><span class="p">):</span> - <span class="sd">"""Decorator to generate a `numpy.random.RandomState` instance.</span> +<span class="w"> </span><span class="sd">"""Decorator to generate a `numpy.random.RandomState` instance.</span> <span class="sd"> The decorator processes the argument indicated by `random_state_argument`</span> <span class="sd"> using :func:`nx.utils.create_random_state`.</span> @@ -764,7 +764,7 @@ <div class="viewcode-block" id="py_random_state"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.decorators.py_random_state.html#networkx.utils.decorators.py_random_state">[docs]</a><span class="k">def</span> <span class="nf">py_random_state</span><span class="p">(</span><span class="n">random_state_argument</span><span class="p">):</span> - <span class="sd">"""Decorator to generate a random.Random instance (or equiv).</span> +<span class="w"> </span><span class="sd">"""Decorator to generate a random.Random instance (or equiv).</span> <span class="sd"> The decorator processes the argument indicated by `random_state_argument`</span> <span class="sd"> using :func:`nx.utils.create_py_random_state`.</span> @@ -817,7 +817,7 @@ <div class="viewcode-block" id="argmap"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.decorators.argmap.html#networkx.utils.decorators.argmap">[docs]</a><span class="k">class</span> <span class="nc">argmap</span><span class="p">:</span> - <span class="sd">"""A decorator to apply a map to arguments before calling the function</span> +<span class="w"> </span><span class="sd">"""A decorator to apply a map to arguments before calling the function</span> <span class="sd"> This class provides a decorator that maps (transforms) arguments of the function</span> <span class="sd"> before the function is called. Thus for example, we have similar code</span> @@ -1159,7 +1159,7 @@ <span class="nd">@staticmethod</span> <span class="k">def</span> <span class="nf">_lazy_compile</span><span class="p">(</span><span class="n">func</span><span class="p">):</span> - <span class="sd">"""Compile the source of a wrapped function</span> +<span class="w"> </span><span class="sd">"""Compile the source of a wrapped function</span> <span class="sd"> Assemble and compile the decorated function, and intrusively replace its</span> <span class="sd"> code with the compiled version's. The thinly wrapped function becomes</span> @@ -1205,7 +1205,7 @@ <span class="k">return</span> <span class="n">func</span> <span class="k">def</span> <span class="fm">__call__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">f</span><span class="p">):</span> - <span class="sd">"""Construct a lazily decorated wrapper of f.</span> +<span class="w"> </span><span class="sd">"""Construct a lazily decorated wrapper of f.</span> <span class="sd"> The decorated function will be compiled when it is called for the first time,</span> <span class="sd"> and it will replace its own __code__ object so subsequent calls are fast.</span> @@ -1270,7 +1270,7 @@ <span class="nd">@classmethod</span> <span class="k">def</span> <span class="nf">_count</span><span class="p">(</span><span class="bp">cls</span><span class="p">):</span> - <span class="sd">"""Maintain a globally-unique identifier for function names and "file" names</span> +<span class="w"> </span><span class="sd">"""Maintain a globally-unique identifier for function names and "file" names</span> <span class="sd"> Note that this counter is a class method reporting a class variable</span> <span class="sd"> so the count is unique within a Python session. It could differ from</span> @@ -1293,7 +1293,7 @@ <span class="nd">@classmethod</span> <span class="k">def</span> <span class="nf">_name</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">f</span><span class="p">):</span> - <span class="sd">"""Mangle the name of a function to be unique but somewhat human-readable</span> +<span class="w"> </span><span class="sd">"""Mangle the name of a function to be unique but somewhat human-readable</span> <span class="sd"> The names are unique within a Python session and set using `_count`.</span> @@ -1312,7 +1312,7 @@ <span class="k">return</span> <span class="sa">f</span><span class="s2">"argmap_</span><span class="si">{</span><span class="n">fname</span><span class="si">}</span><span class="s2">_</span><span class="si">{</span><span class="bp">cls</span><span class="o">.</span><span class="n">_count</span><span class="p">()</span><span class="si">}</span><span class="s2">"</span> <div class="viewcode-block" id="argmap.compile"><a class="viewcode-back" href="../../../reference/generated/generated/networkx.utils.decorators.argmap.compile.html#networkx.utils.decorators.argmap.compile">[docs]</a> <span class="k">def</span> <span class="nf">compile</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">f</span><span class="p">):</span> - <span class="sd">"""Compile the decorated function.</span> +<span class="w"> </span><span class="sd">"""Compile the decorated function.</span> <span class="sd"> Called once for a given decorated function -- collects the code from all</span> <span class="sd"> argmap decorators in the stack, and compiles the decorated function.</span> @@ -1360,7 +1360,7 @@ <span class="k">return</span> <span class="n">func</span></div> <div class="viewcode-block" id="argmap.assemble"><a class="viewcode-back" href="../../../reference/generated/generated/networkx.utils.decorators.argmap.assemble.html#networkx.utils.decorators.argmap.assemble">[docs]</a> <span class="k">def</span> <span class="nf">assemble</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">f</span><span class="p">):</span> - <span class="sd">"""Collects components of the source for the decorated function wrapping f.</span> +<span class="w"> </span><span class="sd">"""Collects components of the source for the decorated function wrapping f.</span> <span class="sd"> If `f` has multiple argmap decorators, we recursively assemble the stack of</span> <span class="sd"> decorators into a single flattened function.</span> @@ -1472,7 +1472,7 @@ <span class="sa">f</span><span class="s2">"index </span><span class="si">{</span><span class="n">arg</span><span class="si">}</span><span class="s2"> not a parameter index and this function doesn't have args"</span> <span class="p">)</span> <span class="n">mutable_args</span> <span class="o">=</span> <span class="kc">True</span> - <span class="k">return</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">sig</span><span class="o">.</span><span class="n">args</span><span class="si">}</span><span class="s2">[</span><span class="si">{</span><span class="n">arg</span> <span class="o">-</span> <span class="n">sig</span><span class="o">.</span><span class="n">n_positional</span><span class="si">}</span><span class="s2">]"</span> + <span class="k">return</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">sig</span><span class="o">.</span><span class="n">args</span><span class="si">}</span><span class="s2">[</span><span class="si">{</span><span class="n">arg</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="n">sig</span><span class="o">.</span><span class="n">n_positional</span><span class="si">}</span><span class="s2">]"</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_finally</span><span class="p">:</span> <span class="c1"># here's where we handle try_finally decorators. Such a decorator</span> @@ -1503,7 +1503,7 @@ <div class="viewcode-block" id="argmap.signature"><a class="viewcode-back" href="../../../reference/generated/generated/networkx.utils.decorators.argmap.signature.html#networkx.utils.decorators.argmap.signature">[docs]</a> <span class="nd">@classmethod</span> <span class="k">def</span> <span class="nf">signature</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">f</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Construct a Signature object describing `f`</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Construct a Signature object describing `f`</span> <span class="sd"> Compute a Signature so that we can write a function wrapping f with</span> <span class="sd"> the same signature and call-type.</span> @@ -1603,7 +1603,7 @@ <span class="nd">@staticmethod</span> <span class="k">def</span> <span class="nf">_flatten</span><span class="p">(</span><span class="n">nestlist</span><span class="p">,</span> <span class="n">visited</span><span class="p">):</span> - <span class="sd">"""flattens a recursive list of lists that doesn't have cyclic references</span> +<span class="w"> </span><span class="sd">"""flattens a recursive list of lists that doesn't have cyclic references</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -1633,7 +1633,7 @@ <span class="nd">@staticmethod</span> <span class="k">def</span> <span class="nf">_indent</span><span class="p">(</span><span class="o">*</span><span class="n">lines</span><span class="p">):</span> - <span class="sd">"""Indent list of code lines to make executable Python code</span> +<span class="w"> </span><span class="sd">"""Indent list of code lines to make executable Python code</span> <span class="sd"> Indents a tree-recursive list of strings, following the rule that one</span> <span class="sd"> space is added to the tab after a line that ends in a colon, and one is</span> @@ -1721,7 +1721,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/utils/mapped_queue.html b/_modules/networkx/utils/mapped_queue.html index 912d7dbb..b5bf4ed7 100644 --- a/_modules/networkx/utils/mapped_queue.html +++ b/_modules/networkx/utils/mapped_queue.html @@ -470,7 +470,7 @@ <span class="k">class</span> <span class="nc">_HeapElement</span><span class="p">:</span> - <span class="sd">"""This proxy class separates the heap element from its priority.</span> +<span class="w"> </span><span class="sd">"""This proxy class separates the heap element from its priority.</span> <span class="sd"> The idea is that using a 2-tuple (priority, element) works</span> <span class="sd"> for sorting, but not for dict lookup because priorities are</span> @@ -553,7 +553,7 @@ <div class="viewcode-block" id="MappedQueue"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.mapped_queue.MappedQueue.html#networkx.utils.mapped_queue.MappedQueue">[docs]</a><span class="k">class</span> <span class="nc">MappedQueue</span><span class="p">:</span> - <span class="sd">"""The MappedQueue class implements a min-heap with removal and update-priority.</span> +<span class="w"> </span><span class="sd">"""The MappedQueue class implements a min-heap with removal and update-priority.</span> <span class="sd"> The min heap uses heapq as well as custom written _siftup and _siftdown</span> <span class="sd"> methods to allow the heap positions to be tracked by an additional dict</span> @@ -615,7 +615,7 @@ <span class="sd"> """</span> <div class="viewcode-block" id="MappedQueue.__init__"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.mapped_queue.MappedQueue.html#networkx.utils.mapped_queue.MappedQueue.__init__">[docs]</a> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Priority queue class with updatable priorities."""</span> +<span class="w"> </span><span class="sd">"""Priority queue class with updatable priorities."""</span> <span class="k">if</span> <span class="n">data</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">heap</span> <span class="o">=</span> <span class="nb">list</span><span class="p">()</span> <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span> @@ -626,7 +626,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">_heapify</span><span class="p">()</span></div> <span class="k">def</span> <span class="nf">_heapify</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Restore heap invariant and recalculate map."""</span> +<span class="w"> </span><span class="sd">"""Restore heap invariant and recalculate map."""</span> <span class="n">heapq</span><span class="o">.</span><span class="n">heapify</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">heap</span><span class="p">)</span> <span class="bp">self</span><span class="o">.</span><span class="n">position</span> <span class="o">=</span> <span class="p">{</span><span class="n">elt</span><span class="p">:</span> <span class="n">pos</span> <span class="k">for</span> <span class="n">pos</span><span class="p">,</span> <span class="n">elt</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">heap</span><span class="p">)}</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">heap</span><span class="p">)</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">position</span><span class="p">):</span> @@ -636,7 +636,7 @@ <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">heap</span><span class="p">)</span> <div class="viewcode-block" id="MappedQueue.push"><a class="viewcode-back" href="../../../reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.push.html#networkx.utils.mapped_queue.MappedQueue.push">[docs]</a> <span class="k">def</span> <span class="nf">push</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">elt</span><span class="p">,</span> <span class="n">priority</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Add an element to the queue."""</span> +<span class="w"> </span><span class="sd">"""Add an element to the queue."""</span> <span class="k">if</span> <span class="n">priority</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> <span class="n">elt</span> <span class="o">=</span> <span class="n">_HeapElement</span><span class="p">(</span><span class="n">priority</span><span class="p">,</span> <span class="n">elt</span><span class="p">)</span> <span class="c1"># If element is already in queue, do nothing</span> @@ -651,7 +651,7 @@ <span class="k">return</span> <span class="kc">True</span></div> <div class="viewcode-block" id="MappedQueue.pop"><a class="viewcode-back" href="../../../reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.pop.html#networkx.utils.mapped_queue.MappedQueue.pop">[docs]</a> <span class="k">def</span> <span class="nf">pop</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Remove and return the smallest element in the queue."""</span> +<span class="w"> </span><span class="sd">"""Remove and return the smallest element in the queue."""</span> <span class="c1"># Remove smallest element</span> <span class="n">elt</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">heap</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">del</span> <span class="bp">self</span><span class="o">.</span><span class="n">position</span><span class="p">[</span><span class="n">elt</span><span class="p">]</span> @@ -669,7 +669,7 @@ <span class="k">return</span> <span class="n">elt</span></div> <div class="viewcode-block" id="MappedQueue.update"><a class="viewcode-back" href="../../../reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.update.html#networkx.utils.mapped_queue.MappedQueue.update">[docs]</a> <span class="k">def</span> <span class="nf">update</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">elt</span><span class="p">,</span> <span class="n">new</span><span class="p">,</span> <span class="n">priority</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Replace an element in the queue with a new one."""</span> +<span class="w"> </span><span class="sd">"""Replace an element in the queue with a new one."""</span> <span class="k">if</span> <span class="n">priority</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> <span class="n">new</span> <span class="o">=</span> <span class="n">_HeapElement</span><span class="p">(</span><span class="n">priority</span><span class="p">,</span> <span class="n">new</span><span class="p">)</span> <span class="c1"># Replace</span> @@ -681,7 +681,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">_siftup</span><span class="p">(</span><span class="n">pos</span><span class="p">)</span></div> <div class="viewcode-block" id="MappedQueue.remove"><a class="viewcode-back" href="../../../reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.remove.html#networkx.utils.mapped_queue.MappedQueue.remove">[docs]</a> <span class="k">def</span> <span class="nf">remove</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">elt</span><span class="p">):</span> - <span class="sd">"""Remove an element from the queue."""</span> +<span class="w"> </span><span class="sd">"""Remove an element from the queue."""</span> <span class="c1"># Find and remove element</span> <span class="k">try</span><span class="p">:</span> <span class="n">pos</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">position</span><span class="p">[</span><span class="n">elt</span><span class="p">]</span> @@ -701,7 +701,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">_siftup</span><span class="p">(</span><span class="n">pos</span><span class="p">)</span></div> <span class="k">def</span> <span class="nf">_siftup</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">pos</span><span class="p">):</span> - <span class="sd">"""Move smaller child up until hitting a leaf.</span> +<span class="w"> </span><span class="sd">"""Move smaller child up until hitting a leaf.</span> <span class="sd"> Built to mimic code for heapq._siftup</span> <span class="sd"> only updating position dict too.</span> @@ -740,7 +740,7 @@ <span class="n">position</span><span class="p">[</span><span class="n">newitem</span><span class="p">]</span> <span class="o">=</span> <span class="n">pos</span> <span class="k">def</span> <span class="nf">_siftdown</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">start_pos</span><span class="p">,</span> <span class="n">pos</span><span class="p">):</span> - <span class="sd">"""Restore invariant. keep swapping with parent until smaller.</span> +<span class="w"> </span><span class="sd">"""Restore invariant. keep swapping with parent until smaller.</span> <span class="sd"> Built to mimic code for heapq._siftdown</span> <span class="sd"> only updating position dict too.</span> @@ -810,7 +810,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/utils/misc.html b/_modules/networkx/utils/misc.html index f0318b02..cd739238 100644 --- a/_modules/networkx/utils/misc.html +++ b/_modules/networkx/utils/misc.html @@ -505,7 +505,7 @@ <div class="viewcode-block" id="flatten"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.misc.flatten.html#networkx.utils.misc.flatten">[docs]</a><span class="k">def</span> <span class="nf">flatten</span><span class="p">(</span><span class="n">obj</span><span class="p">,</span> <span class="n">result</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Return flattened version of (possibly nested) iterable object."""</span> +<span class="w"> </span><span class="sd">"""Return flattened version of (possibly nested) iterable object."""</span> <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">obj</span><span class="p">,</span> <span class="p">(</span><span class="n">Iterable</span><span class="p">,</span> <span class="n">Sized</span><span class="p">))</span> <span class="ow">or</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">obj</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span> <span class="k">return</span> <span class="n">obj</span> <span class="k">if</span> <span class="n">result</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> @@ -519,7 +519,7 @@ <div class="viewcode-block" id="make_list_of_ints"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.misc.make_list_of_ints.html#networkx.utils.misc.make_list_of_ints">[docs]</a><span class="k">def</span> <span class="nf">make_list_of_ints</span><span class="p">(</span><span class="n">sequence</span><span class="p">):</span> - <span class="sd">"""Return list of ints from sequence of integral numbers.</span> +<span class="w"> </span><span class="sd">"""Return list of ints from sequence of integral numbers.</span> <span class="sd"> All elements of the sequence must satisfy int(element) == element</span> <span class="sd"> or a ValueError is raised. Sequence is iterated through once.</span> @@ -555,7 +555,7 @@ <div class="viewcode-block" id="dict_to_numpy_array"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.misc.dict_to_numpy_array.html#networkx.utils.misc.dict_to_numpy_array">[docs]</a><span class="k">def</span> <span class="nf">dict_to_numpy_array</span><span class="p">(</span><span class="n">d</span><span class="p">,</span> <span class="n">mapping</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Convert a dictionary of dictionaries to a numpy array</span> +<span class="w"> </span><span class="sd">"""Convert a dictionary of dictionaries to a numpy array</span> <span class="sd"> with optional mapping."""</span> <span class="k">try</span><span class="p">:</span> <span class="k">return</span> <span class="n">_dict_to_numpy_array2</span><span class="p">(</span><span class="n">d</span><span class="p">,</span> <span class="n">mapping</span><span class="p">)</span> @@ -566,7 +566,7 @@ <span class="k">def</span> <span class="nf">_dict_to_numpy_array2</span><span class="p">(</span><span class="n">d</span><span class="p">,</span> <span class="n">mapping</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Convert a dictionary of dictionaries to a 2d numpy array</span> +<span class="w"> </span><span class="sd">"""Convert a dictionary of dictionaries to a 2d numpy array</span> <span class="sd"> with optional mapping.</span> <span class="sd"> """</span> @@ -589,7 +589,7 @@ <span class="k">def</span> <span class="nf">_dict_to_numpy_array1</span><span class="p">(</span><span class="n">d</span><span class="p">,</span> <span class="n">mapping</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Convert a dictionary of numbers to a 1d numpy array with optional mapping."""</span> +<span class="w"> </span><span class="sd">"""Convert a dictionary of numbers to a 1d numpy array with optional mapping."""</span> <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span> <span class="k">if</span> <span class="n">mapping</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> @@ -604,7 +604,7 @@ <div class="viewcode-block" id="arbitrary_element"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.misc.arbitrary_element.html#networkx.utils.misc.arbitrary_element">[docs]</a><span class="k">def</span> <span class="nf">arbitrary_element</span><span class="p">(</span><span class="n">iterable</span><span class="p">):</span> - <span class="sd">"""Returns an arbitrary element of `iterable` without removing it.</span> +<span class="w"> </span><span class="sd">"""Returns an arbitrary element of `iterable` without removing it.</span> <span class="sd"> This is most useful for "peeking" at an arbitrary element of a set,</span> <span class="sd"> but can be used for any list, dictionary, etc., as well.</span> @@ -683,7 +683,7 @@ <div class="viewcode-block" id="groups"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.misc.groups.html#networkx.utils.misc.groups">[docs]</a><span class="k">def</span> <span class="nf">groups</span><span class="p">(</span><span class="n">many_to_one</span><span class="p">):</span> - <span class="sd">"""Converts a many-to-one mapping into a one-to-many mapping.</span> +<span class="w"> </span><span class="sd">"""Converts a many-to-one mapping into a one-to-many mapping.</span> <span class="sd"> `many_to_one` must be a dictionary whose keys and values are all</span> <span class="sd"> :term:`hashable`.</span> @@ -705,7 +705,7 @@ <div class="viewcode-block" id="create_random_state"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.misc.create_random_state.html#networkx.utils.misc.create_random_state">[docs]</a><span class="k">def</span> <span class="nf">create_random_state</span><span class="p">(</span><span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a numpy.random.RandomState or numpy.random.Generator instance</span> +<span class="w"> </span><span class="sd">"""Returns a numpy.random.RandomState or numpy.random.Generator instance</span> <span class="sd"> depending on input.</span> <span class="sd"> Parameters</span> @@ -811,7 +811,7 @@ <div class="viewcode-block" id="create_py_random_state"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.misc.create_py_random_state.html#networkx.utils.misc.create_py_random_state">[docs]</a><span class="k">def</span> <span class="nf">create_py_random_state</span><span class="p">(</span><span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a random.Random instance depending on input.</span> +<span class="w"> </span><span class="sd">"""Returns a random.Random instance depending on input.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -851,7 +851,7 @@ <div class="viewcode-block" id="nodes_equal"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.misc.nodes_equal.html#networkx.utils.misc.nodes_equal">[docs]</a><span class="k">def</span> <span class="nf">nodes_equal</span><span class="p">(</span><span class="n">nodes1</span><span class="p">,</span> <span class="n">nodes2</span><span class="p">):</span> - <span class="sd">"""Check if nodes are equal.</span> +<span class="w"> </span><span class="sd">"""Check if nodes are equal.</span> <span class="sd"> Equality here means equal as Python objects.</span> <span class="sd"> Node data must match if included.</span> @@ -878,7 +878,7 @@ <div class="viewcode-block" id="edges_equal"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.misc.edges_equal.html#networkx.utils.misc.edges_equal">[docs]</a><span class="k">def</span> <span class="nf">edges_equal</span><span class="p">(</span><span class="n">edges1</span><span class="p">,</span> <span class="n">edges2</span><span class="p">):</span> - <span class="sd">"""Check if edges are equal.</span> +<span class="w"> </span><span class="sd">"""Check if edges are equal.</span> <span class="sd"> Equality here means equal as Python objects.</span> <span class="sd"> Edge data must match if included.</span> @@ -933,7 +933,7 @@ <div class="viewcode-block" id="graphs_equal"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.misc.graphs_equal.html#networkx.utils.misc.graphs_equal">[docs]</a><span class="k">def</span> <span class="nf">graphs_equal</span><span class="p">(</span><span class="n">graph1</span><span class="p">,</span> <span class="n">graph2</span><span class="p">):</span> - <span class="sd">"""Check if graphs are equal.</span> +<span class="w"> </span><span class="sd">"""Check if graphs are equal.</span> <span class="sd"> Equality here means equal as Python objects (not isomorphism).</span> <span class="sd"> Node, edge and graph data must match.</span> @@ -1003,7 +1003,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/utils/random_sequence.html b/_modules/networkx/utils/random_sequence.html index 55fde26a..2bdf5609 100644 --- a/_modules/networkx/utils/random_sequence.html +++ b/_modules/networkx/utils/random_sequence.html @@ -486,7 +486,7 @@ <div class="viewcode-block" id="powerlaw_sequence"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.random_sequence.powerlaw_sequence.html#networkx.utils.random_sequence.powerlaw_sequence">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">powerlaw_sequence</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">exponent</span><span class="o">=</span><span class="mf">2.0</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Return sample sequence of length n from a power law distribution.</span> <span class="sd"> """</span> <span class="k">return</span> <span class="p">[</span><span class="n">seed</span><span class="o">.</span><span class="n">paretovariate</span><span class="p">(</span><span class="n">exponent</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n</span><span class="p">)]</span></div> @@ -494,7 +494,7 @@ <div class="viewcode-block" id="zipf_rv"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.random_sequence.zipf_rv.html#networkx.utils.random_sequence.zipf_rv">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">zipf_rv</span><span class="p">(</span><span class="n">alpha</span><span class="p">,</span> <span class="n">xmin</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sa">r</span><span class="sd">"""Returns a random value chosen from the Zipf distribution.</span> +<span class="w"> </span><span class="sa">r</span><span class="sd">"""Returns a random value chosen from the Zipf distribution.</span> <span class="sd"> The return value is an integer drawn from the probability distribution</span> @@ -558,7 +558,7 @@ <div class="viewcode-block" id="cumulative_distribution"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.random_sequence.cumulative_distribution.html#networkx.utils.random_sequence.cumulative_distribution">[docs]</a><span class="k">def</span> <span class="nf">cumulative_distribution</span><span class="p">(</span><span class="n">distribution</span><span class="p">):</span> - <span class="sd">"""Returns normalized cumulative distribution from discrete distribution."""</span> +<span class="w"> </span><span class="sd">"""Returns normalized cumulative distribution from discrete distribution."""</span> <span class="n">cdf</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="n">psum</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">distribution</span><span class="p">)</span> @@ -569,7 +569,7 @@ <div class="viewcode-block" id="discrete_sequence"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.random_sequence.discrete_sequence.html#networkx.utils.random_sequence.discrete_sequence">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> <span class="k">def</span> <span class="nf">discrete_sequence</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">distribution</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cdistribution</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Return sample sequence of length n from a given discrete distribution</span> <span class="sd"> or discrete cumulative distribution.</span> @@ -601,7 +601,7 @@ <div class="viewcode-block" id="random_weighted_sample"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.random_sequence.random_weighted_sample.html#networkx.utils.random_sequence.random_weighted_sample">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">random_weighted_sample</span><span class="p">(</span><span class="n">mapping</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns k items without replacement from a weighted sample.</span> +<span class="w"> </span><span class="sd">"""Returns k items without replacement from a weighted sample.</span> <span class="sd"> The input is a dictionary of items with weights as values.</span> <span class="sd"> """</span> @@ -615,7 +615,7 @@ <div class="viewcode-block" id="weighted_choice"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.random_sequence.weighted_choice.html#networkx.utils.random_sequence.weighted_choice">[docs]</a><span class="nd">@py_random_state</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="k">def</span> <span class="nf">weighted_choice</span><span class="p">(</span><span class="n">mapping</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Returns a single element from a weighted sample.</span> +<span class="w"> </span><span class="sd">"""Returns a single element from a weighted sample.</span> <span class="sd"> The input is a dictionary of items with weights as values.</span> <span class="sd"> """</span> @@ -676,7 +676,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/utils/rcm.html b/_modules/networkx/utils/rcm.html index 6607f6ed..6137ccc1 100644 --- a/_modules/networkx/utils/rcm.html +++ b/_modules/networkx/utils/rcm.html @@ -475,7 +475,7 @@ <div class="viewcode-block" id="cuthill_mckee_ordering"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.rcm.cuthill_mckee_ordering.html#networkx.utils.rcm.cuthill_mckee_ordering">[docs]</a><span class="k">def</span> <span class="nf">cuthill_mckee_ordering</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">heuristic</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Generate an ordering (permutation) of the graph nodes to make</span> +<span class="w"> </span><span class="sd">"""Generate an ordering (permutation) of the graph nodes to make</span> <span class="sd"> a sparse matrix.</span> <span class="sd"> Uses the Cuthill-McKee heuristic (based on breadth-first search) [1]_.</span> @@ -532,7 +532,7 @@ <div class="viewcode-block" id="reverse_cuthill_mckee_ordering"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.rcm.reverse_cuthill_mckee_ordering.html#networkx.utils.rcm.reverse_cuthill_mckee_ordering">[docs]</a><span class="k">def</span> <span class="nf">reverse_cuthill_mckee_ordering</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">heuristic</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Generate an ordering (permutation) of the graph nodes to make</span> +<span class="w"> </span><span class="sd">"""Generate an ordering (permutation) of the graph nodes to make</span> <span class="sd"> a sparse matrix.</span> <span class="sd"> Uses the reverse Cuthill-McKee heuristic (based on breadth-first search)</span> @@ -670,7 +670,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/_modules/networkx/utils/union_find.html b/_modules/networkx/utils/union_find.html index 9b5c176a..5c46b002 100644 --- a/_modules/networkx/utils/union_find.html +++ b/_modules/networkx/utils/union_find.html @@ -469,7 +469,7 @@ <span class="k">class</span> <span class="nc">UnionFind</span><span class="p">:</span> - <span class="sd">"""Union-find data structure.</span> +<span class="w"> </span><span class="sd">"""Union-find data structure.</span> <span class="sd"> Each unionFind instance X maintains a family of disjoint sets of</span> <span class="sd"> hashable objects, supporting the following two methods:</span> @@ -492,7 +492,7 @@ <span class="sd"> """</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">elements</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Create a new empty union-find structure.</span> +<span class="w"> </span><span class="sd">"""Create a new empty union-find structure.</span> <span class="sd"> If *elements* is an iterable, this structure will be initialized</span> <span class="sd"> with the discrete partition on the given set of elements.</span> @@ -507,7 +507,7 @@ <span class="bp">self</span><span class="o">.</span><span class="n">parents</span><span class="p">[</span><span class="n">x</span><span class="p">]</span> <span class="o">=</span> <span class="n">x</span> <span class="k">def</span> <span class="fm">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="nb">object</span><span class="p">):</span> - <span class="sd">"""Find and return the name of the set containing the object."""</span> +<span class="w"> </span><span class="sd">"""Find and return the name of the set containing the object."""</span> <span class="c1"># check for previously unknown object</span> <span class="k">if</span> <span class="nb">object</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">parents</span><span class="p">:</span> @@ -529,11 +529,11 @@ <span class="k">return</span> <span class="n">root</span> <span class="k">def</span> <span class="fm">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Iterate through all items ever found or unioned by this structure."""</span> +<span class="w"> </span><span class="sd">"""Iterate through all items ever found or unioned by this structure."""</span> <span class="k">return</span> <span class="nb">iter</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">parents</span><span class="p">)</span> <span class="k">def</span> <span class="nf">to_sets</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Iterates over the sets stored in this structure.</span> +<span class="w"> </span><span class="sd">"""Iterates over the sets stored in this structure.</span> <span class="sd"> For example::</span> @@ -552,7 +552,7 @@ <span class="k">yield from</span> <span class="n">groups</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">parents</span><span class="p">)</span><span class="o">.</span><span class="n">values</span><span class="p">()</span> <div class="viewcode-block" id="UnionFind.union"><a class="viewcode-back" href="../../../reference/generated/networkx.utils.union_find.UnionFind.union.html#networkx.utils.union_find.UnionFind.union">[docs]</a> <span class="k">def</span> <span class="nf">union</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">objects</span><span class="p">):</span> - <span class="sd">"""Find the sets containing the objects and merge them all."""</span> +<span class="w"> </span><span class="sd">"""Find the sets containing the objects and merge them all."""</span> <span class="c1"># Find the heaviest root according to its weight.</span> <span class="n">roots</span> <span class="o">=</span> <span class="nb">iter</span><span class="p">(</span> <span class="nb">sorted</span><span class="p">(</span> @@ -618,7 +618,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/3d_drawing/index.html b/auto_examples/3d_drawing/index.html index b13b8267..bf15b24d 100644 --- a/auto_examples/3d_drawing/index.html +++ b/auto_examples/3d_drawing/index.html @@ -550,7 +550,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/3d_drawing/mayavi2_spring.html b/auto_examples/3d_drawing/mayavi2_spring.html index 29ac9af9..ddd03ebf 100644 --- a/auto_examples/3d_drawing/mayavi2_spring.html +++ b/auto_examples/3d_drawing/mayavi2_spring.html @@ -595,7 +595,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/3d_drawing/plot_basic.html b/auto_examples/3d_drawing/plot_basic.html index 92b69005..7bcc911c 100644 --- a/auto_examples/3d_drawing/plot_basic.html +++ b/auto_examples/3d_drawing/plot_basic.html @@ -523,7 +523,7 @@ to download the full example code</p> <span class="k">def</span> <span class="nf">_format_axes</span><span class="p">(</span><span class="n">ax</span><span class="p">):</span> - <span class="sd">"""Visualization options for the 3D axes."""</span> +<span class="w"> </span><span class="sd">"""Visualization options for the 3D axes."""</span> <span class="c1"># Turn gridlines off</span> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.grid.html#matplotlib.axes.Axes.grid" title="matplotlib.axes.Axes.grid" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-method"><span class="n">ax</span><span class="o">.</span><span class="n">grid</span></a><span class="p">(</span><span class="kc">False</span><span class="p">)</span> <span class="c1"># Suppress tick labels</span> @@ -540,7 +540,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.078 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.111 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-3d-drawing-plot-basic-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/79beefddd68fa45123e60db5559f52aa/plot_basic.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_basic.py</span></code></a></p> @@ -602,7 +602,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/3d_drawing/sg_execution_times.html b/auto_examples/3d_drawing/sg_execution_times.html index 2a8c64d4..cc3b2701 100644 --- a/auto_examples/3d_drawing/sg_execution_times.html +++ b/auto_examples/3d_drawing/sg_execution_times.html @@ -463,11 +463,11 @@ <section id="computation-times"> <span id="sphx-glr-auto-examples-3d-drawing-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this heading">#</a></h1> -<p><strong>00:00.078</strong> total execution time for <strong>auto_examples_3d_drawing</strong> files:</p> +<p><strong>00:00.111</strong> total execution time for <strong>auto_examples_3d_drawing</strong> files:</p> <table class="table"> <tbody> <tr class="row-odd"><td><p><a class="reference internal" href="plot_basic.html#sphx-glr-auto-examples-3d-drawing-plot-basic-py"><span class="std std-ref">Basic matplotlib</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_basic.py</span></code>)</p></td> -<td><p>00:00.078</p></td> +<td><p>00:00.111</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="mayavi2_spring.html#sphx-glr-auto-examples-3d-drawing-mayavi2-spring-py"><span class="std std-ref">Mayavi2</span></a> (<code class="docutils literal notranslate"><span class="pre">mayavi2_spring.py</span></code>)</p></td> @@ -528,7 +528,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/algorithms/index.html b/auto_examples/algorithms/index.html index daecf4f3..90fa57e7 100644 --- a/auto_examples/algorithms/index.html +++ b/auto_examples/algorithms/index.html @@ -590,7 +590,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/algorithms/plot_beam_search.html b/auto_examples/algorithms/plot_beam_search.html index 6ada0913..2b67881a 100644 --- a/auto_examples/algorithms/plot_beam_search.html +++ b/auto_examples/algorithms/plot_beam_search.html @@ -515,7 +515,7 @@ with increasing beam width until the target node is found.</p> <span class="k">def</span> <span class="nf">progressive_widening_search</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">source</span></a><span class="p">,</span> <span class="n">value</span><span class="p">,</span> <span class="n">condition</span><span class="p">,</span> <span class="n">initial_width</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span> - <span class="sd">"""Progressive widening beam search to find a node.</span> +<span class="w"> </span><span class="sd">"""Progressive widening beam search to find a node.</span> <span class="sd"> The progressive widening beam search involves a repeated beam</span> <span class="sd"> search, starting with a small beam width then extending to</span> @@ -612,7 +612,7 @@ the progressive widening search in order to find a node of high centrality.</p> <img src="../../_images/sphx_glr_plot_beam_search_001.png" srcset="../../_images/sphx_glr_plot_beam_search_001.png" alt="plot beam search" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>found node 73 with centrality 0.12598283530728402 </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.208 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.286 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-algorithms-plot-beam-search-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/ccbccb63fd600240faf98d07876c0e92/plot_beam_search.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_beam_search.py</span></code></a></p> @@ -692,7 +692,7 @@ the progressive widening search in order to find a node of high centrality.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/algorithms/plot_betweenness_centrality.html b/auto_examples/algorithms/plot_betweenness_centrality.html index 2d4650d6..c623a337 100644 --- a/auto_examples/algorithms/plot_betweenness_centrality.html +++ b/auto_examples/algorithms/plot_betweenness_centrality.html @@ -582,7 +582,7 @@ using WormNet v.3-GS.</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 3.814 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 5.094 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-algorithms-plot-betweenness-centrality-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/b3018a1aab7bffbd1426574de5a8c65a/plot_betweenness_centrality.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_betweenness_centrality.py</span></code></a></p> @@ -644,7 +644,7 @@ using WormNet v.3-GS.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/algorithms/plot_blockmodel.html b/auto_examples/algorithms/plot_blockmodel.html index f9b47d10..73a3ee27 100644 --- a/auto_examples/algorithms/plot_blockmodel.html +++ b/auto_examples/algorithms/plot_blockmodel.html @@ -531,7 +531,7 @@ used is the Hartford, CT drug users network:</p> <span class="k">def</span> <span class="nf">create_hc</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Creates hierarchical cluster of graph G from distance matrix"""</span> +<span class="w"> </span><span class="sd">"""Creates hierarchical cluster of graph G from distance matrix"""</span> <span class="n">path_length</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">all_pairs_shortest_path_length</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> <span class="n">distances</span> <span class="o">=</span> <a href="https://numpy.org/doc/stable/reference/generated/numpy.zeros.html#numpy.zeros" title="numpy.zeros" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-function"><span class="n">np</span><span class="o">.</span><span class="n">zeros</span></a><span class="p">((</span><span class="nb">len</span><span class="p">(</span><span class="n">G</span><span class="p">),</span> <span class="nb">len</span><span class="p">(</span><span class="n">G</span><span class="p">)))</span> <span class="k">for</span> <span class="n">u</span><span class="p">,</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">path_length</span><span class="p">:</span> @@ -579,7 +579,7 @@ used is the Hartford, CT drug users network:</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.366 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.518 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-algorithms-plot-blockmodel-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/efbe368eaa1e457c6c03d3f5a636063a/plot_blockmodel.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_blockmodel.py</span></code></a></p> @@ -641,7 +641,7 @@ used is the Hartford, CT drug users network:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/algorithms/plot_circuits.html b/auto_examples/algorithms/plot_circuits.html index 8fa22897..3b824024 100644 --- a/auto_examples/algorithms/plot_circuits.html +++ b/auto_examples/algorithms/plot_circuits.html @@ -537,7 +537,7 @@ in this way may be infeasible if the circuit is large.</p> <span class="c1"># If one child, the label must be a NOT operator.</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">children</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span> <span class="n">child</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">arbitrary_element</span><span class="p">(</span><span class="n">children</span><span class="p">)</span> - <span class="k">return</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">label</span><span class="si">}</span><span class="s2">(</span><span class="si">{</span><span class="n">_to_string</span><span class="p">(</span><span class="n">formula</span><span class="p">,</span> <span class="n">child</span><span class="p">)</span><span class="si">}</span><span class="s2">)"</span> + <span class="k">return</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">label</span><span class="si">}</span><span class="s2">(</span><span class="si">{</span><span class="n">_to_string</span><span class="p">(</span><span class="n">formula</span><span class="p">,</span><span class="w"> </span><span class="n">child</span><span class="p">)</span><span class="si">}</span><span class="s2">)"</span> <span class="c1"># NB "left" and "right" here are a little misleading: there is</span> <span class="c1"># no order on the children of a node. That's okay because the</span> <span class="c1"># Boolean AND and OR operators are symmetric. It just means that</span> @@ -603,7 +603,7 @@ fourth layer.</p> <img src="../../_images/sphx_glr_plot_circuits_001.png" srcset="../../_images/sphx_glr_plot_circuits_001.png" alt="((x ∨ y) ∧ (y ∨ ¬(z)))" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>((x ∨ y) ∧ (y ∨ ¬(z))) </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.105 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.151 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-algorithms-plot-circuits-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/bd2ce07c5ba253eb7b45764c94237a4c/plot_circuits.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_circuits.py</span></code></a></p> @@ -683,7 +683,7 @@ fourth layer.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/algorithms/plot_davis_club.html b/auto_examples/algorithms/plot_davis_club.html index 74f684a5..e2648654 100644 --- a/auto_examples/algorithms/plot_davis_club.html +++ b/auto_examples/algorithms/plot_davis_club.html @@ -632,14 +632,14 @@ The graph is bipartite (clubs, women).</p> <span class="nb">print</span><span class="p">()</span> <span class="nb">print</span><span class="p">(</span><span class="s2">"#Friend meetings, Member"</span><span class="p">)</span> <span class="k">for</span> <a href="https://docs.python.org/3/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">w</span></a> <span class="ow">in</span> <a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">women</span></a><span class="p">:</span> - <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">W</span><span class="o">.</span><span class="n">degree</span><span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">w</span></a><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s1">'weight'</span><span class="p">)</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><a href="https://docs.python.org/3/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">w</span></a><span class="si">}</span><span class="s2">"</span><span class="p">)</span> + <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">W</span><span class="o">.</span><span class="n">degree</span><span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">w</span></a><span class="p">,</span><span class="w"> </span><span class="n">weight</span><span class="o">=</span><span class="s1">'weight'</span><span class="p">)</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><a href="https://docs.python.org/3/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">w</span></a><span class="si">}</span><span class="s2">"</span><span class="p">)</span> <a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">pos</span></a> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">spring_layout</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="mi">648</span><span class="p">)</span> <span class="c1"># Seed layout for reproducible node positions</span> <span class="n">nx</span><span class="o">.</span><span class="n">draw</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">pos</span></a><span class="p">)</span> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.071 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.109 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-algorithms-plot-davis-club-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/6a1e333663010969e61d07b33c7845f0/plot_davis_club.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_davis_club.py</span></code></a></p> @@ -701,7 +701,7 @@ The graph is bipartite (clubs, women).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/algorithms/plot_dedensification.html b/auto_examples/algorithms/plot_dedensification.html index d93246e1..982b3fba 100644 --- a/auto_examples/algorithms/plot_dedensification.html +++ b/auto_examples/algorithms/plot_dedensification.html @@ -593,7 +593,7 @@ would result in fewer edges in the compressed graph.</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.242 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.382 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-algorithms-plot-dedensification-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/868e28431bab2565b22bfbab847e1153/plot_dedensification.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_dedensification.py</span></code></a></p> @@ -655,7 +655,7 @@ would result in fewer edges in the compressed graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/algorithms/plot_iterated_dynamical_systems.html b/auto_examples/algorithms/plot_iterated_dynamical_systems.html index 362a94f5..ce9657d8 100644 --- a/auto_examples/algorithms/plot_iterated_dynamical_systems.html +++ b/auto_examples/algorithms/plot_iterated_dynamical_systems.html @@ -578,7 +578,7 @@ fixed points are [] <span class="k">def</span> <span class="nf">digitsrep</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">b</span><span class="o">=</span><span class="mi">10</span><span class="p">):</span> - <span class="sd">"""Return list of digits comprising n represented in base b.</span> +<span class="w"> </span><span class="sd">"""Return list of digits comprising n represented in base b.</span> <span class="sd"> n must be a nonnegative integer"""</span> <span class="k">if</span> <span class="n">n</span> <span class="o"><=</span> <span class="mi">0</span><span class="p">:</span> @@ -594,7 +594,7 @@ fixed points are [] <span class="k">def</span> <span class="nf">powersum</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">p</span></a><span class="p">,</span> <span class="n">b</span><span class="o">=</span><span class="mi">10</span><span class="p">):</span> - <span class="sd">"""Return sum of digits of n (in base b) raised to the power p."""</span> +<span class="w"> </span><span class="sd">"""Return sum of digits of n (in base b) raised to the power p."""</span> <span class="n">dlist</span> <span class="o">=</span> <span class="n">digitsrep</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">b</span><span class="p">)</span> <span class="nb">sum</span> <span class="o">=</span> <span class="mi">0</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">dlist</span><span class="p">:</span> @@ -603,7 +603,7 @@ fixed points are [] <span class="k">def</span> <span class="nf">attractor153_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">p</span></a><span class="p">,</span> <span class="n">multiple</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">b</span><span class="o">=</span><span class="mi">10</span><span class="p">):</span> - <span class="sd">"""Return digraph of iterations of powersum(n,3,10)."""</span> +<span class="w"> </span><span class="sd">"""Return digraph of iterations of powersum(n,3,10)."""</span> <span class="n">G</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">DiGraph</span><span class="p">()</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">):</span> <span class="k">if</span> <span class="n">k</span> <span class="o">%</span> <span class="n">multiple</span> <span class="o">==</span> <span class="mi">0</span> <span class="ow">and</span> <span class="n">k</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">G</span><span class="p">:</span> @@ -617,7 +617,7 @@ fixed points are [] <span class="k">def</span> <span class="nf">squaring_cycle_graph_old</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">b</span><span class="o">=</span><span class="mi">10</span><span class="p">):</span> - <span class="sd">"""Return digraph of iterations of powersum(n,2,10)."""</span> +<span class="w"> </span><span class="sd">"""Return digraph of iterations of powersum(n,2,10)."""</span> <span class="n">G</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">DiGraph</span><span class="p">()</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">):</span> <span class="n">k1</span> <span class="o">=</span> <span class="n">k</span> @@ -684,7 +684,7 @@ fixed points are [] <span class="k">def</span> <span class="nf">fixed_points</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="sd">"""Return a list of fixed points for the discrete dynamical</span> +<span class="w"> </span><span class="sd">"""Return a list of fixed points for the discrete dynamical</span> <span class="sd"> system represented by the digraph G.</span> <span class="sd"> """</span> <span class="k">return</span> <span class="p">[</span><span class="n">n</span> <span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="n">G</span> <span class="k">if</span> <span class="n">G</span><span class="o">.</span><span class="n">out_degree</span><span class="p">(</span><span class="n">n</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">]</span> @@ -699,7 +699,7 @@ fixed points are [] <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"fixed points are </span><span class="si">{</span><span class="n">fixed_points</span><span class="p">(</span><span class="n">G</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.094 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.127 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-algorithms-plot-iterated-dynamical-systems-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/d947686c24b50c278c1228ff766cda27/plot_iterated_dynamical_systems.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_iterated_dynamical_systems.py</span></code></a></p> @@ -789,7 +789,7 @@ fixed points are [] <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/algorithms/plot_krackhardt_centrality.html b/auto_examples/algorithms/plot_krackhardt_centrality.html index 2c82fb26..52a49101 100644 --- a/auto_examples/algorithms/plot_krackhardt_centrality.html +++ b/auto_examples/algorithms/plot_krackhardt_centrality.html @@ -569,7 +569,7 @@ Closeness centrality <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.060 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.090 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-algorithms-plot-krackhardt-centrality-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/e77acafa90a347f4353549d3bffbb72c/plot_krackhardt_centrality.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_krackhardt_centrality.py</span></code></a></p> @@ -631,7 +631,7 @@ Closeness centrality <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/algorithms/plot_parallel_betweenness.html b/auto_examples/algorithms/plot_parallel_betweenness.html index a48e7d16..fa707947 100644 --- a/auto_examples/algorithms/plot_parallel_betweenness.html +++ b/auto_examples/algorithms/plot_parallel_betweenness.html @@ -517,29 +517,29 @@ faster. This is a limitation of our CI/CD pipeline running on a single core.</p> <img src="../../_images/sphx_glr_plot_parallel_betweenness_001.png" srcset="../../_images/sphx_glr_plot_parallel_betweenness_001.png" alt="plot parallel betweenness" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Computing betweenness centrality for: Graph with 1000 nodes and 2991 edges Parallel version - Time: 1.7654 seconds - Betweenness centrality for node 0: 0.14984 + Time: 2.3222 seconds + Betweenness centrality for node 0: 0.13594 Non-Parallel version - Time: 2.9646 seconds - Betweenness centrality for node 0: 0.14984 + Time: 3.7747 seconds + Betweenness centrality for node 0: 0.13594 Computing betweenness centrality for: -Graph with 1000 nodes and 4947 edges +Graph with 1000 nodes and 4875 edges Parallel version - Time: 2.2769 seconds - Betweenness centrality for node 0: 0.00263 + Time: 2.8966 seconds + Betweenness centrality for node 0: 0.00110 Non-Parallel version - Time: 3.9447 seconds - Betweenness centrality for node 0: 0.00263 + Time: 4.9253 seconds + Betweenness centrality for node 0: 0.00110 Computing betweenness centrality for: Graph with 1000 nodes and 2000 edges Parallel version - Time: 1.5304 seconds - Betweenness centrality for node 0: 0.00269 + Time: 2.0504 seconds + Betweenness centrality for node 0: 0.00281 Non-Parallel version - Time: 2.7154 seconds - Betweenness centrality for node 0: 0.00269 + Time: 3.4283 seconds + Betweenness centrality for node 0: 0.00281 </pre></div> </div> <div class="line-block"> @@ -554,7 +554,7 @@ Graph with 1000 nodes and 2000 edges <span class="k">def</span> <span class="nf">chunks</span><span class="p">(</span><span class="n">l</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span> - <span class="sd">"""Divide a list of nodes `l` in `n` chunks"""</span> +<span class="w"> </span><span class="sd">"""Divide a list of nodes `l` in `n` chunks"""</span> <span class="n">l_c</span> <span class="o">=</span> <span class="nb">iter</span><span class="p">(</span><span class="n">l</span><span class="p">)</span> <span class="k">while</span> <span class="mi">1</span><span class="p">:</span> <span class="n">x</span> <span class="o">=</span> <span class="nb">tuple</span><span class="p">(</span><a href="https://docs.python.org/3/library/itertools.html#itertools.islice" title="itertools.islice" class="sphx-glr-backref-module-itertools sphx-glr-backref-type-py-function"><span class="n">itertools</span><span class="o">.</span><span class="n">islice</span></a><span class="p">(</span><span class="n">l_c</span><span class="p">,</span> <span class="n">n</span><span class="p">))</span> @@ -564,7 +564,7 @@ Graph with 1000 nodes and 2000 edges <span class="k">def</span> <span class="nf">betweenness_centrality_parallel</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">processes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Parallel betweenness centrality function"""</span> +<span class="w"> </span><span class="sd">"""Parallel betweenness centrality function"""</span> <span class="n">p</span> <span class="o">=</span> <span class="n">Pool</span><span class="p">(</span><span class="n">processes</span><span class="o">=</span><span class="n">processes</span><span class="p">)</span> <span class="n">node_divisor</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">p</span><span class="o">.</span><span class="n">_pool</span><span class="p">)</span> <span class="o">*</span> <span class="mi">4</span> <span class="n">node_chunks</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">chunks</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">nodes</span><span class="p">(),</span> <span class="n">G</span><span class="o">.</span><span class="n">order</span><span class="p">()</span> <span class="o">//</span> <span class="n">node_divisor</span><span class="p">))</span> @@ -598,12 +598,12 @@ Graph with 1000 nodes and 2000 edges <span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\t</span><span class="s2">Parallel version"</span><span class="p">)</span> <a href="https://docs.python.org/3/library/functions.html#float" title="builtins.float" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">start</span></a> <span class="o">=</span> <a href="https://docs.python.org/3/library/time.html#time.time" title="time.time" class="sphx-glr-backref-module-time sphx-glr-backref-type-py-function"><span class="n">time</span><span class="o">.</span><span class="n">time</span></a><span class="p">()</span> <a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">bt</span></a> <span class="o">=</span> <span class="n">betweenness_centrality_parallel</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> - <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\t\t</span><span class="s2">Time: </span><span class="si">{</span><span class="p">(</span><a href="https://docs.python.org/3/library/time.html#time.time" title="time.time" class="sphx-glr-backref-module-time sphx-glr-backref-type-py-function"><span class="n">time</span><span class="o">.</span><span class="n">time</span></a><span class="p">()</span> <span class="o">-</span> <a href="https://docs.python.org/3/library/functions.html#float" title="builtins.float" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">start</span></a><span class="p">)</span><span class="si">:</span><span class="s2">.4F</span><span class="si">}</span><span class="s2"> seconds"</span><span class="p">)</span> + <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\t\t</span><span class="s2">Time: </span><span class="si">{</span><span class="p">(</span><a href="https://docs.python.org/3/library/time.html#time.time" title="time.time" class="sphx-glr-backref-module-time sphx-glr-backref-type-py-function"><span class="n">time</span><span class="o">.</span><span class="n">time</span></a><span class="p">()</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><a href="https://docs.python.org/3/library/functions.html#float" title="builtins.float" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">start</span></a><span class="p">)</span><span class="si">:</span><span class="s2">.4F</span><span class="si">}</span><span class="s2"> seconds"</span><span class="p">)</span> <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\t\t</span><span class="s2">Betweenness centrality for node 0: </span><span class="si">{</span><a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">bt</span></a><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.5f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> <span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\t</span><span class="s2">Non-Parallel version"</span><span class="p">)</span> <a href="https://docs.python.org/3/library/functions.html#float" title="builtins.float" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">start</span></a> <span class="o">=</span> <a href="https://docs.python.org/3/library/time.html#time.time" title="time.time" class="sphx-glr-backref-module-time sphx-glr-backref-type-py-function"><span class="n">time</span><span class="o">.</span><span class="n">time</span></a><span class="p">()</span> <a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">bt</span></a> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">betweenness_centrality</span><span class="p">(</span><span class="n">G</span><span class="p">)</span> - <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\t\t</span><span class="s2">Time: </span><span class="si">{</span><span class="p">(</span><a href="https://docs.python.org/3/library/time.html#time.time" title="time.time" class="sphx-glr-backref-module-time sphx-glr-backref-type-py-function"><span class="n">time</span><span class="o">.</span><span class="n">time</span></a><span class="p">()</span> <span class="o">-</span> <a href="https://docs.python.org/3/library/functions.html#float" title="builtins.float" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">start</span></a><span class="p">)</span><span class="si">:</span><span class="s2">.4F</span><span class="si">}</span><span class="s2"> seconds"</span><span class="p">)</span> + <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\t\t</span><span class="s2">Time: </span><span class="si">{</span><span class="p">(</span><a href="https://docs.python.org/3/library/time.html#time.time" title="time.time" class="sphx-glr-backref-module-time sphx-glr-backref-type-py-function"><span class="n">time</span><span class="o">.</span><span class="n">time</span></a><span class="p">()</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><a href="https://docs.python.org/3/library/functions.html#float" title="builtins.float" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">start</span></a><span class="p">)</span><span class="si">:</span><span class="s2">.4F</span><span class="si">}</span><span class="s2"> seconds"</span><span class="p">)</span> <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\t\t</span><span class="s2">Betweenness centrality for node 0: </span><span class="si">{</span><a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">bt</span></a><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.5f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> <span class="nb">print</span><span class="p">(</span><span class="s2">""</span><span class="p">)</span> @@ -611,7 +611,7 @@ Graph with 1000 nodes and 2000 edges <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 20.575 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 28.196 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-algorithms-plot-parallel-betweenness-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/8a9ce246f32a6cf6abd470292c7ffa6a/plot_parallel_betweenness.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_parallel_betweenness.py</span></code></a></p> @@ -673,7 +673,7 @@ Graph with 1000 nodes and 2000 edges <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/algorithms/plot_rcm.html b/auto_examples/algorithms/plot_rcm.html index b3944d15..a4ff5a05 100644 --- a/auto_examples/algorithms/plot_rcm.html +++ b/auto_examples/algorithms/plot_rcm.html @@ -600,7 +600,7 @@ bandwidth: 7 <a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">x</span></a><span class="p">,</span> <a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">y</span></a> <span class="o">=</span> <a href="https://numpy.org/doc/stable/reference/generated/numpy.nonzero.html#numpy.nonzero" title="numpy.nonzero" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-function"><span class="n">np</span><span class="o">.</span><span class="n">nonzero</span></a><span class="p">(</span><a href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.csr_array.html#scipy.sparse.csr_array" title="scipy.sparse.csr_array" class="sphx-glr-backref-module-scipy-sparse sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">A</span></a><span class="p">)</span> <span class="c1"># print(f"lower bandwidth: {(y - x).max()}")</span> <span class="c1"># print(f"upper bandwidth: {(x - y).max()}")</span> -<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"bandwidth: </span><span class="si">{</span><span class="p">(</span><a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">y</span></a> <span class="o">-</span> <a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">x</span></a><span class="p">)</span><span class="o">.</span><span class="n">max</span><span class="p">()</span> <span class="o">+</span> <span class="p">(</span><a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">x</span></a> <span class="o">-</span> <a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">y</span></a><span class="p">)</span><span class="o">.</span><span class="n">max</span><span class="p">()</span> <span class="o">+</span> <span class="mi">1</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"bandwidth: </span><span class="si">{</span><span class="p">(</span><a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">y</span></a><span class="w"> </span><span class="o">-</span><span class="w"> </span><a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">x</span></a><span class="p">)</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="p">(</span><a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">x</span></a><span class="w"> </span><span class="o">-</span><span class="w"> </span><a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">y</span></a><span class="p">)</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">1</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> <span class="nb">print</span><span class="p">(</span><a href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.csr_array.html#scipy.sparse.csr_array" title="scipy.sparse.csr_array" class="sphx-glr-backref-module-scipy-sparse sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">A</span></a><span class="p">)</span> <a href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.csr_array.html#scipy.sparse.csr_array" title="scipy.sparse.csr_array" class="sphx-glr-backref-module-scipy-sparse sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">B</span></a> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">laplacian_matrix</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">nodelist</span><span class="o">=</span><a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">rcm</span></a><span class="p">)</span> @@ -608,14 +608,14 @@ bandwidth: 7 <a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">x</span></a><span class="p">,</span> <a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">y</span></a> <span class="o">=</span> <a href="https://numpy.org/doc/stable/reference/generated/numpy.nonzero.html#numpy.nonzero" title="numpy.nonzero" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-function"><span class="n">np</span><span class="o">.</span><span class="n">nonzero</span></a><span class="p">(</span><a href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.csr_array.html#scipy.sparse.csr_array" title="scipy.sparse.csr_array" class="sphx-glr-backref-module-scipy-sparse sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">B</span></a><span class="p">)</span> <span class="c1"># print(f"lower bandwidth: {(y - x).max()}")</span> <span class="c1"># print(f"upper bandwidth: {(x - y).max()}")</span> -<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"bandwidth: </span><span class="si">{</span><span class="p">(</span><a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">y</span></a> <span class="o">-</span> <a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">x</span></a><span class="p">)</span><span class="o">.</span><span class="n">max</span><span class="p">()</span> <span class="o">+</span> <span class="p">(</span><a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">x</span></a> <span class="o">-</span> <a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">y</span></a><span class="p">)</span><span class="o">.</span><span class="n">max</span><span class="p">()</span> <span class="o">+</span> <span class="mi">1</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"bandwidth: </span><span class="si">{</span><span class="p">(</span><a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">y</span></a><span class="w"> </span><span class="o">-</span><span class="w"> </span><a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">x</span></a><span class="p">)</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="p">(</span><a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">x</span></a><span class="w"> </span><span class="o">-</span><span class="w"> </span><a href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">y</span></a><span class="p">)</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">1</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> <span class="nb">print</span><span class="p">(</span><a href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.csr_array.html#scipy.sparse.csr_array" title="scipy.sparse.csr_array" class="sphx-glr-backref-module-scipy-sparse sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">B</span></a><span class="p">)</span> <span class="n">sns</span><span class="o">.</span><span class="n">heatmap</span><span class="p">(</span><a href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.csr_array.todense.html#scipy.sparse.csr_array.todense" title="scipy.sparse.csr_array.todense" class="sphx-glr-backref-module-scipy-sparse sphx-glr-backref-type-py-method"><span class="n">B</span><span class="o">.</span><span class="n">todense</span></a><span class="p">(),</span> <span class="n">cbar</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">square</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">linewidths</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">annot</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.931 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 1.285 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-algorithms-plot-rcm-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/544d21367fbc1520a180d8891369bb49/plot_rcm.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_rcm.py</span></code></a></p> @@ -677,7 +677,7 @@ bandwidth: 7 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/algorithms/plot_snap.html b/auto_examples/algorithms/plot_snap.html index af826549..b4fd7f66 100644 --- a/auto_examples/algorithms/plot_snap.html +++ b/auto_examples/algorithms/plot_snap.html @@ -610,7 +610,7 @@ graph.</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.174 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.272 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-algorithms-plot-snap-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/0a756ab7ea4b899fa151e327a4dce8d2/plot_snap.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_snap.py</span></code></a></p> @@ -672,7 +672,7 @@ graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/algorithms/plot_subgraphs.html b/auto_examples/algorithms/plot_subgraphs.html index fc539258..456efc61 100644 --- a/auto_examples/algorithms/plot_subgraphs.html +++ b/auto_examples/algorithms/plot_subgraphs.html @@ -515,7 +515,7 @@ Adopted from <span class="k">def</span> <span class="nf">graph_partitioning</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">plotting</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span> - <span class="sd">"""Partition a directed graph into a list of subgraphs that contain</span> +<span class="w"> </span><span class="sd">"""Partition a directed graph into a list of subgraphs that contain</span> <span class="sd"> only entirely supported or entirely unsupported nodes.</span> <span class="sd"> """</span> <span class="c1"># Categorize nodes by their node_type attribute</span> @@ -678,7 +678,7 @@ of subgraphs that contain only entirely <code class="xref py py-obj docutils lit <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<img src="../../_images/sphx_glr_plot_subgraphs_007.png" srcset="../../_images/sphx_glr_plot_subgraphs_007.png" alt="The reconstructed graph." class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.652 seconds)</p> +<img src="../../_images/sphx_glr_plot_subgraphs_007.png" srcset="../../_images/sphx_glr_plot_subgraphs_007.png" alt="The reconstructed graph." class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.937 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-algorithms-plot-subgraphs-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/7c14530887a80b15e4b4f3d68b23d114/plot_subgraphs.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_subgraphs.py</span></code></a></p> @@ -788,7 +788,7 @@ of subgraphs that contain only entirely <code class="xref py py-obj docutils lit <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/algorithms/sg_execution_times.html b/auto_examples/algorithms/sg_execution_times.html index 5469f6ce..cd6c6d05 100644 --- a/auto_examples/algorithms/sg_execution_times.html +++ b/auto_examples/algorithms/sg_execution_times.html @@ -463,55 +463,55 @@ <section id="computation-times"> <span id="sphx-glr-auto-examples-algorithms-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this heading">#</a></h1> -<p><strong>00:27.291</strong> total execution time for <strong>auto_examples_algorithms</strong> files:</p> +<p><strong>00:37.446</strong> total execution time for <strong>auto_examples_algorithms</strong> files:</p> <table class="table"> <tbody> <tr class="row-odd"><td><p><a class="reference internal" href="plot_parallel_betweenness.html#sphx-glr-auto-examples-algorithms-plot-parallel-betweenness-py"><span class="std std-ref">Parallel Betweenness</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_parallel_betweenness.py</span></code>)</p></td> -<td><p>00:20.575</p></td> +<td><p>00:28.196</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_betweenness_centrality.html#sphx-glr-auto-examples-algorithms-plot-betweenness-centrality-py"><span class="std std-ref">Betweeness Centrality</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_betweenness_centrality.py</span></code>)</p></td> -<td><p>00:03.814</p></td> +<td><p>00:05.094</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" href="plot_rcm.html#sphx-glr-auto-examples-algorithms-plot-rcm-py"><span class="std std-ref">Reverse Cuthill–McKee</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_rcm.py</span></code>)</p></td> -<td><p>00:00.931</p></td> +<td><p>00:01.285</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_subgraphs.html#sphx-glr-auto-examples-algorithms-plot-subgraphs-py"><span class="std std-ref">Subgraphs</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_subgraphs.py</span></code>)</p></td> -<td><p>00:00.652</p></td> +<td><p>00:00.937</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" href="plot_blockmodel.html#sphx-glr-auto-examples-algorithms-plot-blockmodel-py"><span class="std std-ref">Blockmodel</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_blockmodel.py</span></code>)</p></td> -<td><p>00:00.366</p></td> +<td><p>00:00.518</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_dedensification.html#sphx-glr-auto-examples-algorithms-plot-dedensification-py"><span class="std std-ref">Dedensification</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_dedensification.py</span></code>)</p></td> -<td><p>00:00.242</p></td> +<td><p>00:00.382</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" href="plot_beam_search.html#sphx-glr-auto-examples-algorithms-plot-beam-search-py"><span class="std std-ref">Beam Search</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_beam_search.py</span></code>)</p></td> -<td><p>00:00.208</p></td> +<td><p>00:00.286</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_snap.html#sphx-glr-auto-examples-algorithms-plot-snap-py"><span class="std std-ref">SNAP Graph Summary</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_snap.py</span></code>)</p></td> -<td><p>00:00.174</p></td> +<td><p>00:00.272</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" href="plot_circuits.html#sphx-glr-auto-examples-algorithms-plot-circuits-py"><span class="std std-ref">Circuits</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_circuits.py</span></code>)</p></td> -<td><p>00:00.105</p></td> +<td><p>00:00.151</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_iterated_dynamical_systems.html#sphx-glr-auto-examples-algorithms-plot-iterated-dynamical-systems-py"><span class="std std-ref">Iterated Dynamical Systems</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_iterated_dynamical_systems.py</span></code>)</p></td> -<td><p>00:00.094</p></td> +<td><p>00:00.127</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" href="plot_davis_club.html#sphx-glr-auto-examples-algorithms-plot-davis-club-py"><span class="std std-ref">Davis Club</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_davis_club.py</span></code>)</p></td> -<td><p>00:00.071</p></td> +<td><p>00:00.109</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_krackhardt_centrality.html#sphx-glr-auto-examples-algorithms-plot-krackhardt-centrality-py"><span class="std std-ref">Krackhardt Centrality</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_krackhardt_centrality.py</span></code>)</p></td> -<td><p>00:00.060</p></td> +<td><p>00:00.090</p></td> <td><p>0.0 MB</p></td> </tr> </tbody> @@ -568,7 +568,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/basic/index.html b/auto_examples/basic/index.html index 3ab0fc07..d48547ca 100644 --- a/auto_examples/basic/index.html +++ b/auto_examples/basic/index.html @@ -554,7 +554,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/basic/plot_properties.html b/auto_examples/basic/plot_properties.html index 2d8d36fd..30c0f1ee 100644 --- a/auto_examples/basic/plot_properties.html +++ b/auto_examples/basic/plot_properties.html @@ -546,7 +546,7 @@ density: 0.26666666666666666 <a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">pathlengths</span></a><span class="o">.</span><span class="n">append</span><span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">spl</span></a><span class="p">[</span><a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">p</span></a><span class="p">])</span> <span class="nb">print</span><span class="p">()</span> -<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"average shortest path length </span><span class="si">{</span><span class="nb">sum</span><span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">pathlengths</span></a><span class="p">)</span> <span class="o">/</span> <span class="nb">len</span><span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">pathlengths</span></a><span class="p">)</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> +<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"average shortest path length </span><span class="si">{</span><span class="nb">sum</span><span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">pathlengths</span></a><span class="p">)</span><span class="w"> </span><span class="o">/</span><span class="w"> </span><span class="nb">len</span><span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">pathlengths</span></a><span class="p">)</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> <span class="c1"># histogram of path lengths</span> <a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">dist</span></a> <span class="o">=</span> <span class="p">{}</span> @@ -574,7 +574,7 @@ density: 0.26666666666666666 <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.090 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.122 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-basic-plot-properties-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/40632926e1e0842cea9103529e4bea12/plot_properties.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_properties.py</span></code></a></p> @@ -636,7 +636,7 @@ density: 0.26666666666666666 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/basic/plot_read_write.html b/auto_examples/basic/plot_read_write.html index 877a8762..4958bad7 100644 --- a/auto_examples/basic/plot_read_write.html +++ b/auto_examples/basic/plot_read_write.html @@ -545,7 +545,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.061 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.088 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-basic-plot-read-write-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/63b2264e53e5d28aeb43b6aa768515b9/plot_read_write.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_read_write.py</span></code></a></p> @@ -607,7 +607,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/basic/plot_simple_graph.html b/auto_examples/basic/plot_simple_graph.html index d52ab919..0cf2a21d 100644 --- a/auto_examples/basic/plot_simple_graph.html +++ b/auto_examples/basic/plot_simple_graph.html @@ -550,7 +550,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<img src="../../_images/sphx_glr_plot_simple_graph_002.png" srcset="../../_images/sphx_glr_plot_simple_graph_002.png" alt="plot simple graph" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.318 seconds)</p> +<img src="../../_images/sphx_glr_plot_simple_graph_002.png" srcset="../../_images/sphx_glr_plot_simple_graph_002.png" alt="plot simple graph" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.488 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-basic-plot-simple-graph-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/0f222beedce48fe624efff9ff2fdc89f/plot_simple_graph.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_simple_graph.py</span></code></a></p> @@ -612,7 +612,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/basic/sg_execution_times.html b/auto_examples/basic/sg_execution_times.html index 69c56292..e5eca5e5 100644 --- a/auto_examples/basic/sg_execution_times.html +++ b/auto_examples/basic/sg_execution_times.html @@ -463,19 +463,19 @@ <section id="computation-times"> <span id="sphx-glr-auto-examples-basic-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this heading">#</a></h1> -<p><strong>00:00.469</strong> total execution time for <strong>auto_examples_basic</strong> files:</p> +<p><strong>00:00.698</strong> total execution time for <strong>auto_examples_basic</strong> files:</p> <table class="table"> <tbody> <tr class="row-odd"><td><p><a class="reference internal" href="plot_simple_graph.html#sphx-glr-auto-examples-basic-plot-simple-graph-py"><span class="std std-ref">Simple graph</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_simple_graph.py</span></code>)</p></td> -<td><p>00:00.318</p></td> +<td><p>00:00.488</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_properties.html#sphx-glr-auto-examples-basic-plot-properties-py"><span class="std std-ref">Properties</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_properties.py</span></code>)</p></td> -<td><p>00:00.090</p></td> +<td><p>00:00.122</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" href="plot_read_write.html#sphx-glr-auto-examples-basic-plot-read-write-py"><span class="std std-ref">Read and write graphs.</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_read_write.py</span></code>)</p></td> -<td><p>00:00.061</p></td> +<td><p>00:00.088</p></td> <td><p>0.0 MB</p></td> </tr> </tbody> @@ -532,7 +532,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/index.html b/auto_examples/drawing/index.html index c2207181..024eaccf 100644 --- a/auto_examples/drawing/index.html +++ b/auto_examples/drawing/index.html @@ -634,7 +634,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_center_node.html b/auto_examples/drawing/plot_center_node.html index 420d7356..69f836a4 100644 --- a/auto_examples/drawing/plot_center_node.html +++ b/auto_examples/drawing/plot_center_node.html @@ -530,7 +530,7 @@ to download the full example code</p> <span class="n">nx</span><span class="o">.</span><span class="n">draw</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">pos</span></a><span class="p">,</span> <span class="n">with_labels</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.066 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.093 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-center-node-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/8561539ed0b99621dbdbe53646ac5075/plot_center_node.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_center_node.py</span></code></a></p> @@ -592,7 +592,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_chess_masters.html b/auto_examples/drawing/plot_chess_masters.html index 586e38c8..bf9409ad 100644 --- a/auto_examples/drawing/plot_chess_masters.html +++ b/auto_examples/drawing/plot_chess_masters.html @@ -536,7 +536,7 @@ to black and contains selected game info.</p> <img src="../../_images/sphx_glr_plot_chess_masters_001.png" srcset="../../_images/sphx_glr_plot_chess_masters_001.png" alt="World Chess Championship Games: 1886 - 1985" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Loaded 685 chess games between 25 players Note the disconnected component consisting of: -['Kasparov, Gary', 'Karpov, Anatoly', 'Korchnoi, Viktor L'] +['Kasparov, Gary', 'Korchnoi, Viktor L', 'Karpov, Anatoly'] From a total of 237 different openings, the following games used the Sicilian opening @@ -584,7 +584,7 @@ findfont: Font family 'Helvetica' not found. <span class="k">def</span> <span class="nf">chess_pgn_graph</span><span class="p">(</span><span class="n">pgn_file</span><span class="o">=</span><span class="s2">"chess_masters_WCC.pgn.bz2"</span><span class="p">):</span> - <span class="sd">"""Read chess games in pgn format in pgn_file.</span> +<span class="w"> </span><span class="sd">"""Read chess games in pgn format in pgn_file.</span> <span class="sd"> Filenames ending in .bz2 will be uncompressed.</span> @@ -702,7 +702,7 @@ findfont: Font family 'Helvetica' not found. <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.384 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.526 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-chess-masters-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/388158421a67216f605c1bbf9aa310bf/plot_chess_masters.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_chess_masters.py</span></code></a></p> @@ -764,7 +764,7 @@ findfont: Font family 'Helvetica' not found. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_custom_node_icons.html b/auto_examples/drawing/plot_custom_node_icons.html index c399eff7..12011819 100644 --- a/auto_examples/drawing/plot_custom_node_icons.html +++ b/auto_examples/drawing/plot_custom_node_icons.html @@ -585,7 +585,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.279 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.413 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-custom-node-icons-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/b580b9776494e714c1fb1880f03524a8/plot_custom_node_icons.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_custom_node_icons.py</span></code></a></p> @@ -647,7 +647,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_degree.html b/auto_examples/drawing/plot_degree.html index 0961e0be..fa6eeb5c 100644 --- a/auto_examples/drawing/plot_degree.html +++ b/auto_examples/drawing/plot_degree.html @@ -561,7 +561,7 @@ each node is determined, and a figure is generated showing three things: <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.266 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.391 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-degree-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/70eaef0d99343cf8d3d6e70c803ad5a8/plot_degree.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_degree.py</span></code></a></p> @@ -623,7 +623,7 @@ each node is determined, and a figure is generated showing three things: <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_directed.html b/auto_examples/drawing/plot_directed.html index 741c697d..a38656ca 100644 --- a/auto_examples/drawing/plot_directed.html +++ b/auto_examples/drawing/plot_directed.html @@ -556,7 +556,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.221 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.363 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-directed-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/6c2f9c3544cb695b31867eecc0f7fb1e/plot_directed.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_directed.py</span></code></a></p> @@ -618,7 +618,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_edge_colormap.html b/auto_examples/drawing/plot_edge_colormap.html index 4f0b7e62..8daf0065 100644 --- a/auto_examples/drawing/plot_edge_colormap.html +++ b/auto_examples/drawing/plot_edge_colormap.html @@ -534,7 +534,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.062 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.085 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-edge-colormap-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/7ea4dc8cf44604668540ed81d6abebda/plot_edge_colormap.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_edge_colormap.py</span></code></a></p> @@ -596,7 +596,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_ego_graph.html b/auto_examples/drawing/plot_ego_graph.html index fda8da3f..fe63eb00 100644 --- a/auto_examples/drawing/plot_ego_graph.html +++ b/auto_examples/drawing/plot_ego_graph.html @@ -546,7 +546,7 @@ the largest hub in a Barabási-Albert network.</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.097 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.130 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-ego-graph-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/773fa56bdb128b8bd2a4f4a0e4dd38aa/plot_ego_graph.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_ego_graph.py</span></code></a></p> @@ -608,7 +608,7 @@ the largest hub in a Barabási-Albert network.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_eigenvalues.html b/auto_examples/drawing/plot_eigenvalues.html index dd96864c..453a04e1 100644 --- a/auto_examples/drawing/plot_eigenvalues.html +++ b/auto_examples/drawing/plot_eigenvalues.html @@ -517,8 +517,8 @@ to download the full example code</p> <section class="sphx-glr-example-title" id="eigenvalues"> <span id="sphx-glr-auto-examples-drawing-plot-eigenvalues-py"></span><h1>Eigenvalues<a class="headerlink" href="#eigenvalues" title="Permalink to this heading">#</a></h1> <p>Create an G{n,m} random graph and compute the eigenvalues.</p> -<img src="../../_images/sphx_glr_plot_eigenvalues_001.png" srcset="../../_images/sphx_glr_plot_eigenvalues_001.png" alt="plot eigenvalues" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Largest eigenvalue: 1.592461791177574 -Smallest eigenvalue: -2.5363890312656235e-16 +<img src="../../_images/sphx_glr_plot_eigenvalues_001.png" srcset="../../_images/sphx_glr_plot_eigenvalues_001.png" alt="plot eigenvalues" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Largest eigenvalue: 1.5924617911775805 +Smallest eigenvalue: 4.0699282104742547e-16 </pre></div> </div> <div class="line-block"> @@ -541,7 +541,7 @@ Smallest eigenvalue: -2.5363890312656235e-16 <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.630 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.953 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-eigenvalues-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/a8660a7bb6b65b5a644025485c973cb9/plot_eigenvalues.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_eigenvalues.py</span></code></a></p> @@ -603,7 +603,7 @@ Smallest eigenvalue: -2.5363890312656235e-16 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_four_grids.html b/auto_examples/drawing/plot_four_grids.html index 65fa6559..0e45bcba 100644 --- a/auto_examples/drawing/plot_four_grids.html +++ b/auto_examples/drawing/plot_four_grids.html @@ -562,7 +562,7 @@ customize the visualization of a simple Graph comprising a 4x4 grid.</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.327 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.501 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-four-grids-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/4136c066ab1d073cf527e9dc02bfec77/plot_four_grids.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_four_grids.py</span></code></a></p> @@ -624,7 +624,7 @@ customize the visualization of a simple Graph comprising a 4x4 grid.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_house_with_colors.html b/auto_examples/drawing/plot_house_with_colors.html index 245a380a..90a3c070 100644 --- a/auto_examples/drawing/plot_house_with_colors.html +++ b/auto_examples/drawing/plot_house_with_colors.html @@ -538,7 +538,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.074 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.106 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-house-with-colors-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/98363b3c011ceaffb10684a5ba5de25b/plot_house_with_colors.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_house_with_colors.py</span></code></a></p> @@ -600,7 +600,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_knuth_miles.html b/auto_examples/drawing/plot_knuth_miles.html index ec71c1be..6e78bf9c 100644 --- a/auto_examples/drawing/plot_knuth_miles.html +++ b/auto_examples/drawing/plot_knuth_miles.html @@ -550,7 +550,7 @@ Graph with 128 nodes and 8128 edges <span class="k">def</span> <span class="nf">miles_graph</span><span class="p">():</span> - <span class="sd">"""Return the cites example graph in miles_dat.txt</span> +<span class="w"> </span><span class="sd">"""Return the cites example graph in miles_dat.txt</span> <span class="sd"> from the Stanford GraphBase.</span> <span class="sd"> """</span> <span class="c1"># open file miles_dat.txt.gz (or miles_dat.txt)</span> @@ -660,7 +660,7 @@ Graph with 128 nodes and 8128 edges <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.098 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.126 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-knuth-miles-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/e921c603ea1764485dc9acff178a2f05/plot_knuth_miles.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_knuth_miles.py</span></code></a></p> @@ -722,7 +722,7 @@ Graph with 128 nodes and 8128 edges <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_labels_and_colors.html b/auto_examples/drawing/plot_labels_and_colors.html index a2fcec41..408eb7c3 100644 --- a/auto_examples/drawing/plot_labels_and_colors.html +++ b/auto_examples/drawing/plot_labels_and_colors.html @@ -566,7 +566,7 @@ components of a graph.</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.189 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.257 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-labels-and-colors-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/cff4f78bc18685caa50507ced57e7c6f/plot_labels_and_colors.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_labels_and_colors.py</span></code></a></p> @@ -628,7 +628,7 @@ components of a graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_multipartite_graph.html b/auto_examples/drawing/plot_multipartite_graph.html index f8074c0e..a71870db 100644 --- a/auto_examples/drawing/plot_multipartite_graph.html +++ b/auto_examples/drawing/plot_multipartite_graph.html @@ -553,7 +553,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.076 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.098 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-multipartite-graph-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/6cb4bf689cf53c849bce13cbab13eaec/plot_multipartite_graph.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_multipartite_graph.py</span></code></a></p> @@ -615,7 +615,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_node_colormap.html b/auto_examples/drawing/plot_node_colormap.html index 1bd41cdd..c6507901 100644 --- a/auto_examples/drawing/plot_node_colormap.html +++ b/auto_examples/drawing/plot_node_colormap.html @@ -526,7 +526,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.051 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.068 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-node-colormap-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/19db6fb1da12c9b9c0afca26691448c8/plot_node_colormap.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_node_colormap.py</span></code></a></p> @@ -588,7 +588,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_rainbow_coloring.html b/auto_examples/drawing/plot_rainbow_coloring.html index 30212364..10df64d0 100644 --- a/auto_examples/drawing/plot_rainbow_coloring.html +++ b/auto_examples/drawing/plot_rainbow_coloring.html @@ -578,7 +578,7 @@ helpful in determining how to place the tree copies.</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.125 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.166 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-rainbow-coloring-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/b64fd85d6e5ba509e65b2cb30a8274ed/plot_rainbow_coloring.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_rainbow_coloring.py</span></code></a></p> @@ -658,7 +658,7 @@ helpful in determining how to place the tree copies.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_random_geometric_graph.html b/auto_examples/drawing/plot_random_geometric_graph.html index 7b17d369..3fea9848 100644 --- a/auto_examples/drawing/plot_random_geometric_graph.html +++ b/auto_examples/drawing/plot_random_geometric_graph.html @@ -555,7 +555,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.102 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.134 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-random-geometric-graph-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/f8f8cacecc651443537b92fc341fba08/plot_random_geometric_graph.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_random_geometric_graph.py</span></code></a></p> @@ -617,7 +617,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_sampson.html b/auto_examples/drawing/plot_sampson.html index 624fb262..7e1eaffa 100644 --- a/auto_examples/drawing/plot_sampson.html +++ b/auto_examples/drawing/plot_sampson.html @@ -557,7 +557,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.245 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.366 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-sampson-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/838bbb120e1c43a61657821eddf29c25/plot_sampson.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_sampson.py</span></code></a></p> @@ -619,7 +619,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_selfloops.html b/auto_examples/drawing/plot_selfloops.html index 4b115143..51db7cc7 100644 --- a/auto_examples/drawing/plot_selfloops.html +++ b/auto_examples/drawing/plot_selfloops.html @@ -540,7 +540,7 @@ This example shows how to draw self-loops with <code class="xref py py-obj docut <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.079 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.117 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-selfloops-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/b6f62567cb843f23abdd4b7268921c0b/plot_selfloops.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_selfloops.py</span></code></a></p> @@ -602,7 +602,7 @@ This example shows how to draw self-loops with <code class="xref py py-obj docut <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_simple_path.html b/auto_examples/drawing/plot_simple_path.html index f5a07323..b67c8326 100644 --- a/auto_examples/drawing/plot_simple_path.html +++ b/auto_examples/drawing/plot_simple_path.html @@ -526,7 +526,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.057 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.080 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-simple-path-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/2c281c05b18d8d3cf43a312fc3d67a3b/plot_simple_path.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_simple_path.py</span></code></a></p> @@ -588,7 +588,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_spectral_grid.html b/auto_examples/drawing/plot_spectral_grid.html index 07f590c3..c80cc34f 100644 --- a/auto_examples/drawing/plot_spectral_grid.html +++ b/auto_examples/drawing/plot_spectral_grid.html @@ -568,7 +568,7 @@ As you remove internal nodes, this effect increases.</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.223 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.386 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-spectral-grid-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/5479a9bd23bf1ace2ef03c13b4ac9d7f/plot_spectral_grid.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_spectral_grid.py</span></code></a></p> @@ -630,7 +630,7 @@ As you remove internal nodes, this effect increases.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_tsp.html b/auto_examples/drawing/plot_tsp.html index 705ad268..4e5e8cf2 100644 --- a/auto_examples/drawing/plot_tsp.html +++ b/auto_examples/drawing/plot_tsp.html @@ -568,7 +568,7 @@ that the traveler has to follow in order to minimize the total cost.</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.086 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.135 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-tsp-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/cc9848c15dd2eeae1872b955a8f34d15/plot_tsp.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_tsp.py</span></code></a></p> @@ -630,7 +630,7 @@ that the traveler has to follow in order to minimize the total cost.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_unix_email.html b/auto_examples/drawing/plot_unix_email.html index 423cc453..3f9d0e73 100644 --- a/auto_examples/drawing/plot_unix_email.html +++ b/auto_examples/drawing/plot_unix_email.html @@ -583,7 +583,7 @@ From: ted@com To: alice@edu Subject: get together for lunch to discuss Networks? <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.109 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.197 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-unix-email-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/213697eef7dec7ebca6ee2e064eb9c24/plot_unix_email.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_unix_email.py</span></code></a></p> @@ -645,7 +645,7 @@ From: ted@com To: alice@edu Subject: get together for lunch to discuss Networks? <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/plot_weighted_graph.html b/auto_examples/drawing/plot_weighted_graph.html index 0ae4df28..4556c42c 100644 --- a/auto_examples/drawing/plot_weighted_graph.html +++ b/auto_examples/drawing/plot_weighted_graph.html @@ -556,7 +556,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.084 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.138 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-drawing-plot-weighted-graph-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/32d3b6ab4dec83957a1981fa91e52e14/plot_weighted_graph.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_weighted_graph.py</span></code></a></p> @@ -618,7 +618,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/drawing/sg_execution_times.html b/auto_examples/drawing/sg_execution_times.html index 6d5a256b..14f7e4c7 100644 --- a/auto_examples/drawing/sg_execution_times.html +++ b/auto_examples/drawing/sg_execution_times.html @@ -463,99 +463,99 @@ <section id="computation-times"> <span id="sphx-glr-auto-examples-drawing-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this heading">#</a></h1> -<p><strong>00:03.931</strong> total execution time for <strong>auto_examples_drawing</strong> files:</p> +<p><strong>00:05.829</strong> total execution time for <strong>auto_examples_drawing</strong> files:</p> <table class="table"> <tbody> <tr class="row-odd"><td><p><a class="reference internal" href="plot_eigenvalues.html#sphx-glr-auto-examples-drawing-plot-eigenvalues-py"><span class="std std-ref">Eigenvalues</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_eigenvalues.py</span></code>)</p></td> -<td><p>00:00.630</p></td> +<td><p>00:00.953</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_chess_masters.html#sphx-glr-auto-examples-drawing-plot-chess-masters-py"><span class="std std-ref">Chess Masters</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_chess_masters.py</span></code>)</p></td> -<td><p>00:00.384</p></td> +<td><p>00:00.526</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" href="plot_four_grids.html#sphx-glr-auto-examples-drawing-plot-four-grids-py"><span class="std std-ref">Four Grids</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_four_grids.py</span></code>)</p></td> -<td><p>00:00.327</p></td> +<td><p>00:00.501</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_custom_node_icons.html#sphx-glr-auto-examples-drawing-plot-custom-node-icons-py"><span class="std std-ref">Custom node icons</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_custom_node_icons.py</span></code>)</p></td> -<td><p>00:00.279</p></td> +<td><p>00:00.413</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" href="plot_degree.html#sphx-glr-auto-examples-drawing-plot-degree-py"><span class="std std-ref">Degree Analysis</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_degree.py</span></code>)</p></td> -<td><p>00:00.266</p></td> +<td><p>00:00.391</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-even"><td><p><a class="reference internal" href="plot_sampson.html#sphx-glr-auto-examples-drawing-plot-sampson-py"><span class="std std-ref">Sampson</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_sampson.py</span></code>)</p></td> -<td><p>00:00.245</p></td> +<tr class="row-even"><td><p><a class="reference internal" href="plot_spectral_grid.html#sphx-glr-auto-examples-drawing-plot-spectral-grid-py"><span class="std std-ref">Spectral Embedding</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_spectral_grid.py</span></code>)</p></td> +<td><p>00:00.386</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-odd"><td><p><a class="reference internal" href="plot_spectral_grid.html#sphx-glr-auto-examples-drawing-plot-spectral-grid-py"><span class="std std-ref">Spectral Embedding</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_spectral_grid.py</span></code>)</p></td> -<td><p>00:00.223</p></td> +<tr class="row-odd"><td><p><a class="reference internal" href="plot_sampson.html#sphx-glr-auto-examples-drawing-plot-sampson-py"><span class="std std-ref">Sampson</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_sampson.py</span></code>)</p></td> +<td><p>00:00.366</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_directed.html#sphx-glr-auto-examples-drawing-plot-directed-py"><span class="std std-ref">Directed Graph</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_directed.py</span></code>)</p></td> -<td><p>00:00.221</p></td> +<td><p>00:00.363</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" href="plot_labels_and_colors.html#sphx-glr-auto-examples-drawing-plot-labels-and-colors-py"><span class="std std-ref">Labels And Colors</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_labels_and_colors.py</span></code>)</p></td> -<td><p>00:00.189</p></td> +<td><p>00:00.257</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-even"><td><p><a class="reference internal" href="plot_rainbow_coloring.html#sphx-glr-auto-examples-drawing-plot-rainbow-coloring-py"><span class="std std-ref">Rainbow Coloring</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_rainbow_coloring.py</span></code>)</p></td> -<td><p>00:00.125</p></td> +<tr class="row-even"><td><p><a class="reference internal" href="plot_unix_email.html#sphx-glr-auto-examples-drawing-plot-unix-email-py"><span class="std std-ref">Unix Email</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_unix_email.py</span></code>)</p></td> +<td><p>00:00.197</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-odd"><td><p><a class="reference internal" href="plot_unix_email.html#sphx-glr-auto-examples-drawing-plot-unix-email-py"><span class="std std-ref">Unix Email</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_unix_email.py</span></code>)</p></td> -<td><p>00:00.109</p></td> +<tr class="row-odd"><td><p><a class="reference internal" href="plot_rainbow_coloring.html#sphx-glr-auto-examples-drawing-plot-rainbow-coloring-py"><span class="std std-ref">Rainbow Coloring</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_rainbow_coloring.py</span></code>)</p></td> +<td><p>00:00.166</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-even"><td><p><a class="reference internal" href="plot_random_geometric_graph.html#sphx-glr-auto-examples-drawing-plot-random-geometric-graph-py"><span class="std std-ref">Random Geometric Graph</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_random_geometric_graph.py</span></code>)</p></td> -<td><p>00:00.102</p></td> +<tr class="row-even"><td><p><a class="reference internal" href="plot_weighted_graph.html#sphx-glr-auto-examples-drawing-plot-weighted-graph-py"><span class="std std-ref">Weighted Graph</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_weighted_graph.py</span></code>)</p></td> +<td><p>00:00.138</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-odd"><td><p><a class="reference internal" href="plot_knuth_miles.html#sphx-glr-auto-examples-drawing-plot-knuth-miles-py"><span class="std std-ref">Knuth Miles</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_knuth_miles.py</span></code>)</p></td> -<td><p>00:00.098</p></td> +<tr class="row-odd"><td><p><a class="reference internal" href="plot_tsp.html#sphx-glr-auto-examples-drawing-plot-tsp-py"><span class="std std-ref">Traveling Salesman Problem</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_tsp.py</span></code>)</p></td> +<td><p>00:00.135</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-even"><td><p><a class="reference internal" href="plot_ego_graph.html#sphx-glr-auto-examples-drawing-plot-ego-graph-py"><span class="std std-ref">Ego Graph</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_ego_graph.py</span></code>)</p></td> -<td><p>00:00.097</p></td> +<tr class="row-even"><td><p><a class="reference internal" href="plot_random_geometric_graph.html#sphx-glr-auto-examples-drawing-plot-random-geometric-graph-py"><span class="std std-ref">Random Geometric Graph</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_random_geometric_graph.py</span></code>)</p></td> +<td><p>00:00.134</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-odd"><td><p><a class="reference internal" href="plot_tsp.html#sphx-glr-auto-examples-drawing-plot-tsp-py"><span class="std std-ref">Traveling Salesman Problem</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_tsp.py</span></code>)</p></td> -<td><p>00:00.086</p></td> +<tr class="row-odd"><td><p><a class="reference internal" href="plot_ego_graph.html#sphx-glr-auto-examples-drawing-plot-ego-graph-py"><span class="std std-ref">Ego Graph</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_ego_graph.py</span></code>)</p></td> +<td><p>00:00.130</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-even"><td><p><a class="reference internal" href="plot_weighted_graph.html#sphx-glr-auto-examples-drawing-plot-weighted-graph-py"><span class="std std-ref">Weighted Graph</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_weighted_graph.py</span></code>)</p></td> -<td><p>00:00.084</p></td> +<tr class="row-even"><td><p><a class="reference internal" href="plot_knuth_miles.html#sphx-glr-auto-examples-drawing-plot-knuth-miles-py"><span class="std std-ref">Knuth Miles</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_knuth_miles.py</span></code>)</p></td> +<td><p>00:00.126</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" href="plot_selfloops.html#sphx-glr-auto-examples-drawing-plot-selfloops-py"><span class="std std-ref">Self-loops</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_selfloops.py</span></code>)</p></td> -<td><p>00:00.079</p></td> +<td><p>00:00.117</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-even"><td><p><a class="reference internal" href="plot_multipartite_graph.html#sphx-glr-auto-examples-drawing-plot-multipartite-graph-py"><span class="std std-ref">Multipartite Layout</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_multipartite_graph.py</span></code>)</p></td> -<td><p>00:00.076</p></td> +<tr class="row-even"><td><p><a class="reference internal" href="plot_house_with_colors.html#sphx-glr-auto-examples-drawing-plot-house-with-colors-py"><span class="std std-ref">House With Colors</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_house_with_colors.py</span></code>)</p></td> +<td><p>00:00.106</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-odd"><td><p><a class="reference internal" href="plot_house_with_colors.html#sphx-glr-auto-examples-drawing-plot-house-with-colors-py"><span class="std std-ref">House With Colors</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_house_with_colors.py</span></code>)</p></td> -<td><p>00:00.074</p></td> +<tr class="row-odd"><td><p><a class="reference internal" href="plot_multipartite_graph.html#sphx-glr-auto-examples-drawing-plot-multipartite-graph-py"><span class="std std-ref">Multipartite Layout</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_multipartite_graph.py</span></code>)</p></td> +<td><p>00:00.098</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_center_node.html#sphx-glr-auto-examples-drawing-plot-center-node-py"><span class="std std-ref">Custom Node Position</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_center_node.py</span></code>)</p></td> -<td><p>00:00.066</p></td> +<td><p>00:00.093</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" 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class="pre">plot_node_colormap.py</span></code>)</p></td> -<td><p>00:00.051</p></td> +<td><p>00:00.068</p></td> <td><p>0.0 MB</p></td> </tr> </tbody> @@ -612,7 +612,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/external/index.html b/auto_examples/external/index.html index ac6a3452..4f25baa1 100644 --- a/auto_examples/external/index.html +++ b/auto_examples/external/index.html @@ -551,7 +551,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/external/javascript_force.html b/auto_examples/external/javascript_force.html index 1d1892ce..a7e79c94 100644 --- a/auto_examples/external/javascript_force.html +++ b/auto_examples/external/javascript_force.html @@ -592,7 +592,7 @@ to produce an HTML/Javascript drawing.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/external/plot_igraph.html b/auto_examples/external/plot_igraph.html index 587f0bb1..a9a8f9b4 100644 --- a/auto_examples/external/plot_igraph.html +++ b/auto_examples/external/plot_igraph.html @@ -539,7 +539,7 @@ provides (among many other things) functions to convert to/from NetworkX.</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<img src="../../_images/sphx_glr_plot_igraph_002.png" srcset="../../_images/sphx_glr_plot_igraph_002.png" alt="plot igraph" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.430 seconds)</p> +<img src="../../_images/sphx_glr_plot_igraph_002.png" srcset="../../_images/sphx_glr_plot_igraph_002.png" alt="plot igraph" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.568 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-external-plot-igraph-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/a390de783800778d34acc914fb8a3f84/plot_igraph.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_igraph.py</span></code></a></p> @@ -624,7 +624,7 @@ provides (among many other things) functions to convert to/from NetworkX.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/external/sg_execution_times.html b/auto_examples/external/sg_execution_times.html index f48d225b..4d2e3e23 100644 --- a/auto_examples/external/sg_execution_times.html +++ b/auto_examples/external/sg_execution_times.html @@ -463,11 +463,11 @@ <section id="computation-times"> <span id="sphx-glr-auto-examples-external-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this heading">#</a></h1> -<p><strong>00:00.430</strong> total execution time for <strong>auto_examples_external</strong> files:</p> +<p><strong>00:00.568</strong> total execution time for <strong>auto_examples_external</strong> files:</p> <table class="table"> <tbody> <tr class="row-odd"><td><p><a class="reference internal" href="plot_igraph.html#sphx-glr-auto-examples-external-plot-igraph-py"><span class="std std-ref">igraph</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_igraph.py</span></code>)</p></td> -<td><p>00:00.430</p></td> +<td><p>00:00.568</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="javascript_force.html#sphx-glr-auto-examples-external-javascript-force-py"><span class="std std-ref">Javascript</span></a> (<code class="docutils literal notranslate"><span class="pre">javascript_force.py</span></code>)</p></td> @@ -528,7 +528,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/geospatial/extended_description.html b/auto_examples/geospatial/extended_description.html index ecc2c53d..09cdd082 100644 --- a/auto_examples/geospatial/extended_description.html +++ b/auto_examples/geospatial/extended_description.html @@ -669,7 +669,7 @@ available at <a class="reference external" href="https://doi.org/10.1016/j.compe <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/geospatial/index.html b/auto_examples/geospatial/index.html index 77ff3e44..c9ccb1da 100644 --- a/auto_examples/geospatial/index.html +++ b/auto_examples/geospatial/index.html @@ -566,7 +566,7 @@ See the <a class="reference external" href="geospatial/extended_description.html <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/geospatial/plot_delaunay.html b/auto_examples/geospatial/plot_delaunay.html index 05ea7d75..14b0f8d0 100644 --- a/auto_examples/geospatial/plot_delaunay.html +++ b/auto_examples/geospatial/plot_delaunay.html @@ -565,7 +565,7 @@ directly with polygonal data using their centroids as representative points.</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 2.793 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 4.809 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-geospatial-plot-delaunay-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/2b63e3aade568b3f182ba20240be7234/plot_delaunay.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_delaunay.py</span></code></a></p> @@ -627,7 +627,7 @@ directly with polygonal data using their centroids as representative points.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/geospatial/plot_lines.html b/auto_examples/geospatial/plot_lines.html index ff100389..57a70993 100644 --- a/auto_examples/geospatial/plot_lines.html +++ b/auto_examples/geospatial/plot_lines.html @@ -598,7 +598,7 @@ Create PySAL weights (graph).</p> <span class="n">G_dual</span> <span class="o">=</span> <span class="n">W</span><span class="o">.</span><span class="n">to_networkx</span><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 2.676 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 4.332 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-geospatial-plot-lines-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/8ca1ed8a4cf00870baa5a8020931ba46/plot_lines.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_lines.py</span></code></a></p> @@ -660,7 +660,7 @@ Create PySAL weights (graph).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/geospatial/plot_osmnx.html b/auto_examples/geospatial/plot_osmnx.html index 91c0ef48..1dac9b9c 100644 --- a/auto_examples/geospatial/plot_osmnx.html +++ b/auto_examples/geospatial/plot_osmnx.html @@ -541,7 +541,7 @@ retrieve any other spatial data from OSM as geopandas GeoDataFrames. See <span class="n">ox</span><span class="o">.</span><span class="n">save_graphml</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">filepath</span><span class="o">=</span><span class="s2">"./graph.graphml"</span><span class="p">)</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 3.644 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 6.540 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-geospatial-plot-osmnx-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/769ba4a0ffbf9feb2f308b434010db7f/plot_osmnx.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_osmnx.py</span></code></a></p> @@ -603,7 +603,7 @@ retrieve any other spatial data from OSM as geopandas GeoDataFrames. See <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/geospatial/plot_points.html b/auto_examples/geospatial/plot_points.html index f9e50b4e..4b17f1b0 100644 --- a/auto_examples/geospatial/plot_points.html +++ b/auto_examples/geospatial/plot_points.html @@ -552,7 +552,7 @@ centroids as representative points.</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 3.323 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 5.293 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-geospatial-plot-points-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/c79825a60948ea589076f8f2b52b4981/plot_points.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_points.py</span></code></a></p> @@ -614,7 +614,7 @@ centroids as representative points.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/geospatial/plot_polygons.html b/auto_examples/geospatial/plot_polygons.html index c17b9dc2..8a184d5a 100644 --- a/auto_examples/geospatial/plot_polygons.html +++ b/auto_examples/geospatial/plot_polygons.html @@ -549,7 +549,7 @@ as well as other kinds of graphs from the polygon centroids.</p> <span class="c1"># by the pygeos package.</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.435 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.552 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-geospatial-plot-polygons-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/9be63872be08214edeb4d5a2d5f66987/plot_polygons.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_polygons.py</span></code></a></p> @@ -611,7 +611,7 @@ as well as other kinds of graphs from the polygon centroids.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/geospatial/sg_execution_times.html b/auto_examples/geospatial/sg_execution_times.html index 6f7a868e..08559969 100644 --- a/auto_examples/geospatial/sg_execution_times.html +++ b/auto_examples/geospatial/sg_execution_times.html @@ -463,27 +463,27 @@ <section id="computation-times"> <span id="sphx-glr-auto-examples-geospatial-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this heading">#</a></h1> -<p><strong>00:12.871</strong> total execution time for <strong>auto_examples_geospatial</strong> files:</p> +<p><strong>00:21.525</strong> total execution time for <strong>auto_examples_geospatial</strong> files:</p> <table class="table"> <tbody> <tr class="row-odd"><td><p><a class="reference internal" href="plot_osmnx.html#sphx-glr-auto-examples-geospatial-plot-osmnx-py"><span class="std std-ref">OpenStreetMap with OSMnx</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_osmnx.py</span></code>)</p></td> -<td><p>00:03.644</p></td> +<td><p>00:06.540</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_points.html#sphx-glr-auto-examples-geospatial-plot-points-py"><span class="std std-ref">Graphs from geographic points</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_points.py</span></code>)</p></td> -<td><p>00:03.323</p></td> +<td><p>00:05.293</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" href="plot_delaunay.html#sphx-glr-auto-examples-geospatial-plot-delaunay-py"><span class="std std-ref">Delaunay graphs from geographic points</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_delaunay.py</span></code>)</p></td> -<td><p>00:02.793</p></td> +<td><p>00:04.809</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_lines.html#sphx-glr-auto-examples-geospatial-plot-lines-py"><span class="std std-ref">Graphs from a set of lines</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_lines.py</span></code>)</p></td> -<td><p>00:02.676</p></td> +<td><p>00:04.332</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" href="plot_polygons.html#sphx-glr-auto-examples-geospatial-plot-polygons-py"><span class="std std-ref">Graphs from Polygons</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_polygons.py</span></code>)</p></td> -<td><p>00:00.435</p></td> +<td><p>00:00.552</p></td> <td><p>0.0 MB</p></td> </tr> </tbody> @@ -540,7 +540,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graph/index.html b/auto_examples/graph/index.html index c4f8f135..b911fd7c 100644 --- a/auto_examples/graph/index.html +++ b/auto_examples/graph/index.html @@ -586,7 +586,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graph/plot_dag_layout.html b/auto_examples/graph/plot_dag_layout.html index 356e557a..a0e99fa3 100644 --- a/auto_examples/graph/plot_dag_layout.html +++ b/auto_examples/graph/plot_dag_layout.html @@ -541,7 +541,7 @@ order.</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.115 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.181 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graph-plot-dag-layout-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/317508b452046ab7944bed07a87a11a5/plot_dag_layout.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_dag_layout.py</span></code></a></p> @@ -603,7 +603,7 @@ order.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graph/plot_degree_sequence.html b/auto_examples/graph/plot_degree_sequence.html index defd9982..cb55f342 100644 --- a/auto_examples/graph/plot_degree_sequence.html +++ b/auto_examples/graph/plot_degree_sequence.html @@ -548,7 +548,7 @@ degree #nodes <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.057 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.084 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graph-plot-degree-sequence-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/27102b9986eea2f742603c5d8496d2f8/plot_degree_sequence.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_degree_sequence.py</span></code></a></p> @@ -610,7 +610,7 @@ degree #nodes <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graph/plot_erdos_renyi.html b/auto_examples/graph/plot_erdos_renyi.html index 1215d07c..b0308aab 100644 --- a/auto_examples/graph/plot_erdos_renyi.html +++ b/auto_examples/graph/plot_erdos_renyi.html @@ -550,7 +550,7 @@ the adjacency list <span class="c1"># some properties</span> <span class="nb">print</span><span class="p">(</span><span class="s2">"node degree clustering"</span><span class="p">)</span> <span class="k">for</span> <a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">v</span></a> <span class="ow">in</span> <span class="n">nx</span><span class="o">.</span><span class="n">nodes</span><span class="p">(</span><span class="n">G</span><span class="p">):</span> - <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">v</span></a><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="n">nx</span><span class="o">.</span><span class="n">degree</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">v</span></a><span class="p">)</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="n">nx</span><span class="o">.</span><span class="n">clustering</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">v</span></a><span class="p">)</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> + <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">v</span></a><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="n">nx</span><span class="o">.</span><span class="n">degree</span><span class="p">(</span><span class="n">G</span><span class="p">,</span><span class="w"> </span><a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">v</span></a><span class="p">)</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="n">nx</span><span class="o">.</span><span class="n">clustering</span><span class="p">(</span><span class="n">G</span><span class="p">,</span><span class="w"> </span><a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">v</span></a><span class="p">)</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> <span class="nb">print</span><span class="p">()</span> <span class="nb">print</span><span class="p">(</span><span class="s2">"the adjacency list"</span><span class="p">)</span> @@ -562,7 +562,7 @@ the adjacency list <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.058 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.081 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graph-plot-erdos-renyi-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/1dae7040b667b61c3253579b3b21fe83/plot_erdos_renyi.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_erdos_renyi.py</span></code></a></p> @@ -624,7 +624,7 @@ the adjacency list <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graph/plot_expected_degree_sequence.html b/auto_examples/graph/plot_expected_degree_sequence.html index 704bc77c..12273e61 100644 --- a/auto_examples/graph/plot_expected_degree_sequence.html +++ b/auto_examples/graph/plot_expected_degree_sequence.html @@ -540,42 +540,45 @@ degree (#nodes) **** 30 ( 0) 31 ( 0) 32 ( 1) * -33 ( 2) ** +33 ( 1) * 34 ( 0) -35 ( 1) * -36 ( 4) **** +35 ( 2) ** +36 ( 3) *** 37 ( 5) ***** -38 ( 5) ***** -39 ( 7) ******* +38 ( 4) **** +39 ( 8) ******** 40 ( 9) ********* -41 (18) ****************** -42 (12) ************ -43 (10) ********** -44 (21) ********************* -45 (33) ********************************* -46 (27) *************************** -47 (28) **************************** -48 (38) ************************************** -49 (29) ***************************** -50 (36) ************************************ -51 (30) ****************************** -52 (30) ****************************** -53 (25) ************************* -54 (20) ******************** -55 (13) ************* -56 (18) ****************** -57 (17) ***************** -58 (15) *************** -59 (11) *********** -60 ( 9) ********* -61 ( 9) ********* -62 ( 6) ****** -63 ( 1) * +41 ( 7) ******* +42 ( 9) ********* +43 (22) ********************** +44 (32) ******************************** +45 (25) ************************* +46 (25) ************************* +47 (26) ************************** +48 (22) ********************** +49 (25) ************************* +50 (31) ******************************* +51 (27) *************************** +52 (29) ***************************** +53 (27) *************************** +54 (25) ************************* +55 (25) ************************* +56 (16) **************** +57 (25) ************************* +58 (14) ************** +59 (15) *************** +60 ( 8) ******** +61 (10) ********** +62 ( 4) **** +63 ( 6) ****** 64 ( 4) **** 65 ( 3) *** -66 ( 2) ** -67 ( 0) +66 ( 1) * +67 ( 1) * 68 ( 1) * +69 ( 1) * +70 ( 0) +71 ( 1) * </pre></div> </div> <div class="line-block"> @@ -595,7 +598,7 @@ degree (#nodes) **** <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">i</span></a><span class="si">:</span><span class="s2">2</span><span class="si">}</span><span class="s2"> (</span><span class="si">{</span><a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">d</span></a><span class="si">:</span><span class="s2">2</span><span class="si">}</span><span class="s2">) </span><span class="si">{</span><span class="s1">'*'</span><span class="o">*</span><a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">d</span></a><span class="si">}</span><span class="s2">"</span><span class="p">)</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.030 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.039 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graph-plot-expected-degree-sequence-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/7378087382f40e96e66bce4a35ba0e52/plot_expected_degree_sequence.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_expected_degree_sequence.py</span></code></a></p> @@ -657,7 +660,7 @@ degree (#nodes) **** <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graph/plot_football.html b/auto_examples/graph/plot_football.html index b16a80db..78efd4be 100644 --- a/auto_examples/graph/plot_football.html +++ b/auto_examples/graph/plot_football.html @@ -686,7 +686,7 @@ Hawaii 11 <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.542 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.468 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graph-plot-football-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/ca0a30060f60faf520286faa348f4700/plot_football.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_football.py</span></code></a></p> @@ -748,7 +748,7 @@ Hawaii 11 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graph/plot_karate_club.html b/auto_examples/graph/plot_karate_club.html index 31b1bd13..7654416c 100644 --- a/auto_examples/graph/plot_karate_club.html +++ b/auto_examples/graph/plot_karate_club.html @@ -562,7 +562,7 @@ Journal of Anthropological Research, 33, 452-473.</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.088 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.134 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graph-plot-karate-club-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/373a1e407e4caee6fc7b7b46704a985c/plot_karate_club.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_karate_club.py</span></code></a></p> @@ -624,7 +624,7 @@ Journal of Anthropological Research, 33, 452-473.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graph/plot_morse_trie.html b/auto_examples/graph/plot_morse_trie.html index bb9e03cd..6a46f709 100644 --- a/auto_examples/graph/plot_morse_trie.html +++ b/auto_examples/graph/plot_morse_trie.html @@ -602,7 +602,7 @@ the path.</p> <span class="nb">print</span><span class="p">(</span><span class="s2">" "</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="n">morse_encode</span><span class="p">(</span><span class="n">ltr</span><span class="p">)</span> <span class="k">for</span> <span class="n">ltr</span> <span class="ow">in</span> <span class="s2">"ilovenetworkx"</span><span class="p">]))</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.180 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.280 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graph-plot-morse-trie-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/60379a4283563d425090aaae07ab115a/plot_morse_trie.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_morse_trie.py</span></code></a></p> @@ -664,7 +664,7 @@ the path.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graph/plot_napoleon_russian_campaign.html b/auto_examples/graph/plot_napoleon_russian_campaign.html index d42c00cc..f4a9b331 100644 --- a/auto_examples/graph/plot_napoleon_russian_campaign.html +++ b/auto_examples/graph/plot_napoleon_russian_campaign.html @@ -632,7 +632,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.126 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.174 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graph-plot-napoleon-russian-campaign-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/87e75a2d09fb817a4616bb71aa44546f/plot_napoleon_russian_campaign.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_napoleon_russian_campaign.py</span></code></a></p> @@ -694,7 +694,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graph/plot_roget.html b/auto_examples/graph/plot_roget.html index 66a1df98..cfb3f5e4 100644 --- a/auto_examples/graph/plot_roget.html +++ b/auto_examples/graph/plot_roget.html @@ -537,7 +537,7 @@ DiGraph with 1022 nodes and 5075 edges <span class="k">def</span> <span class="nf">roget_graph</span><span class="p">():</span> - <span class="sd">"""Return the thesaurus graph from the roget.dat example in</span> +<span class="w"> </span><span class="sd">"""Return the thesaurus graph from the roget.dat example in</span> <span class="sd"> the Stanford Graph Base.</span> <span class="sd"> """</span> <span class="c1"># open file roget_dat.txt.gz</span> @@ -588,7 +588,7 @@ DiGraph with 1022 nodes and 5075 edges <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.228 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.301 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graph-plot-roget-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/118b3a0c87610e4910d74143c904d290/plot_roget.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_roget.py</span></code></a></p> @@ -650,7 +650,7 @@ DiGraph with 1022 nodes and 5075 edges <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graph/plot_triad_types.html b/auto_examples/graph/plot_triad_types.html index 34b5ecaf..e045f309 100644 --- a/auto_examples/graph/plot_triad_types.html +++ b/auto_examples/graph/plot_triad_types.html @@ -563,7 +563,7 @@ the Orientation as Up (U), Down (D) , Cyclical (C) or Transitive (T).</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 1.054 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 1.676 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graph-plot-triad-types-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/b7a826e19c8bd8bafecaae1ae69c7d1d/plot_triad_types.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_triad_types.py</span></code></a></p> @@ -625,7 +625,7 @@ the Orientation as Up (U), Down (D) , Cyclical (C) or Transitive (T).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graph/plot_words.html b/auto_examples/graph/plot_words.html index 69b9ca4c..425da26f 100644 --- a/auto_examples/graph/plot_words.html +++ b/auto_examples/graph/plot_words.html @@ -583,7 +583,7 @@ None <span class="k">def</span> <span class="nf">words_graph</span><span class="p">():</span> - <span class="sd">"""Return the words example graph from the Stanford GraphBase"""</span> +<span class="w"> </span><span class="sd">"""Return the words example graph from the Stanford GraphBase"""</span> <span class="n">fh</span> <span class="o">=</span> <a href="https://docs.python.org/3/library/gzip.html#gzip.open" title="gzip.open" class="sphx-glr-backref-module-gzip sphx-glr-backref-type-py-function"><span class="n">gzip</span><span class="o">.</span><span class="n">open</span></a><span class="p">(</span><span class="s2">"words_dat.txt.gz"</span><span class="p">,</span> <span class="s2">"r"</span><span class="p">)</span> <span class="n">words</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span> <span class="k">for</span> <span class="n">line</span> <span class="ow">in</span> <span class="n">fh</span><span class="o">.</span><span class="n">readlines</span><span class="p">():</span> @@ -624,7 +624,7 @@ None <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.375 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.528 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graph-plot-words-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/e6a489a8b2deb49ed237fac38a28f429/plot_words.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_words.py</span></code></a></p> @@ -686,7 +686,7 @@ None <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graph/sg_execution_times.html b/auto_examples/graph/sg_execution_times.html index a70bf79b..22ad4700 100644 --- a/auto_examples/graph/sg_execution_times.html +++ b/auto_examples/graph/sg_execution_times.html @@ -463,51 +463,51 @@ <section id="computation-times"> <span id="sphx-glr-auto-examples-graph-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this heading">#</a></h1> -<p><strong>00:02.852</strong> total execution time for <strong>auto_examples_graph</strong> files:</p> +<p><strong>00:03.946</strong> total execution time for <strong>auto_examples_graph</strong> files:</p> <table class="table"> <tbody> <tr class="row-odd"><td><p><a class="reference internal" href="plot_triad_types.html#sphx-glr-auto-examples-graph-plot-triad-types-py"><span class="std std-ref">Triads</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_triad_types.py</span></code>)</p></td> -<td><p>00:01.054</p></td> +<td><p>00:01.676</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-even"><td><p><a class="reference internal" href="plot_football.html#sphx-glr-auto-examples-graph-plot-football-py"><span class="std std-ref">Football</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_football.py</span></code>)</p></td> -<td><p>00:00.542</p></td> +<tr class="row-even"><td><p><a class="reference internal" href="plot_words.html#sphx-glr-auto-examples-graph-plot-words-py"><span class="std std-ref">Words/Ladder Graph</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_words.py</span></code>)</p></td> +<td><p>00:00.528</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-odd"><td><p><a class="reference internal" href="plot_words.html#sphx-glr-auto-examples-graph-plot-words-py"><span class="std std-ref">Words/Ladder Graph</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_words.py</span></code>)</p></td> -<td><p>00:00.375</p></td> +<tr class="row-odd"><td><p><a class="reference internal" href="plot_football.html#sphx-glr-auto-examples-graph-plot-football-py"><span class="std std-ref">Football</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_football.py</span></code>)</p></td> +<td><p>00:00.468</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_roget.html#sphx-glr-auto-examples-graph-plot-roget-py"><span class="std std-ref">Roget</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_roget.py</span></code>)</p></td> -<td><p>00:00.228</p></td> +<td><p>00:00.301</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" href="plot_morse_trie.html#sphx-glr-auto-examples-graph-plot-morse-trie-py"><span class="std std-ref">Morse Trie</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_morse_trie.py</span></code>)</p></td> -<td><p>00:00.180</p></td> +<td><p>00:00.280</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-even"><td><p><a class="reference internal" href="plot_napoleon_russian_campaign.html#sphx-glr-auto-examples-graph-plot-napoleon-russian-campaign-py"><span class="std std-ref">Napoleon Russian Campaign</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_napoleon_russian_campaign.py</span></code>)</p></td> -<td><p>00:00.126</p></td> +<tr class="row-even"><td><p><a class="reference internal" href="plot_dag_layout.html#sphx-glr-auto-examples-graph-plot-dag-layout-py"><span class="std std-ref">DAG - Topological Layout</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_dag_layout.py</span></code>)</p></td> +<td><p>00:00.181</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-odd"><td><p><a class="reference internal" href="plot_dag_layout.html#sphx-glr-auto-examples-graph-plot-dag-layout-py"><span class="std std-ref">DAG - Topological Layout</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_dag_layout.py</span></code>)</p></td> -<td><p>00:00.115</p></td> +<tr class="row-odd"><td><p><a class="reference internal" href="plot_napoleon_russian_campaign.html#sphx-glr-auto-examples-graph-plot-napoleon-russian-campaign-py"><span class="std std-ref">Napoleon Russian Campaign</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_napoleon_russian_campaign.py</span></code>)</p></td> +<td><p>00:00.174</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_karate_club.html#sphx-glr-auto-examples-graph-plot-karate-club-py"><span class="std std-ref">Karate Club</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_karate_club.py</span></code>)</p></td> -<td><p>00:00.088</p></td> +<td><p>00:00.134</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-odd"><td><p><a class="reference internal" href="plot_erdos_renyi.html#sphx-glr-auto-examples-graph-plot-erdos-renyi-py"><span class="std std-ref">Erdos Renyi</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_erdos_renyi.py</span></code>)</p></td> -<td><p>00:00.058</p></td> +<tr class="row-odd"><td><p><a class="reference internal" href="plot_degree_sequence.html#sphx-glr-auto-examples-graph-plot-degree-sequence-py"><span class="std std-ref">Degree Sequence</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_degree_sequence.py</span></code>)</p></td> +<td><p>00:00.084</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-even"><td><p><a class="reference internal" href="plot_degree_sequence.html#sphx-glr-auto-examples-graph-plot-degree-sequence-py"><span class="std std-ref">Degree Sequence</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_degree_sequence.py</span></code>)</p></td> -<td><p>00:00.057</p></td> +<tr class="row-even"><td><p><a class="reference internal" href="plot_erdos_renyi.html#sphx-glr-auto-examples-graph-plot-erdos-renyi-py"><span class="std std-ref">Erdos Renyi</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_erdos_renyi.py</span></code>)</p></td> +<td><p>00:00.081</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" href="plot_expected_degree_sequence.html#sphx-glr-auto-examples-graph-plot-expected-degree-sequence-py"><span class="std std-ref">Expected Degree Sequence</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_expected_degree_sequence.py</span></code>)</p></td> -<td><p>00:00.030</p></td> +<td><p>00:00.039</p></td> <td><p>0.0 MB</p></td> </tr> </tbody> @@ -564,7 +564,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graphviz_drawing/index.html b/auto_examples/graphviz_drawing/index.html index 5a6778f7..86ce5184 100644 --- a/auto_examples/graphviz_drawing/index.html +++ b/auto_examples/graphviz_drawing/index.html @@ -560,7 +560,7 @@ These examples need Graphviz and <a class="reference external" href="https://pyg <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graphviz_drawing/plot_attributes.html b/auto_examples/graphviz_drawing/plot_attributes.html index ec4c31c4..5f62be49 100644 --- a/auto_examples/graphviz_drawing/plot_attributes.html +++ b/auto_examples/graphviz_drawing/plot_attributes.html @@ -532,7 +532,7 @@ node node attributes <span class="nb">print</span><span class="p">(</span><span class="n">X</span><span class="o">.</span><span class="n">nodes</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="kc">True</span><span class="p">))</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.028 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.089 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graphviz-drawing-plot-attributes-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/52bb0ebd52824aa460a3ecb45c1cb5e5/plot_attributes.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_attributes.py</span></code></a></p> @@ -594,7 +594,7 @@ node node attributes <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graphviz_drawing/plot_conversion.html b/auto_examples/graphviz_drawing/plot_conversion.html index bebe3865..52aa0c0d 100644 --- a/auto_examples/graphviz_drawing/plot_conversion.html +++ b/auto_examples/graphviz_drawing/plot_conversion.html @@ -514,7 +514,7 @@ to download the full example code</p> <a href="https://pygraphviz.github.io/documentation/stable/reference/agraph.html#pygraphviz.AGraph.draw" title="pygraphviz.AGraph.draw" class="sphx-glr-backref-module-pygraphviz sphx-glr-backref-type-py-method"><span class="n">A</span><span class="o">.</span><span class="n">draw</span></a><span class="p">(</span><span class="s2">"k5.png"</span><span class="p">,</span> <span class="n">prog</span><span class="o">=</span><span class="s2">"neato"</span><span class="p">)</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.026 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.032 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graphviz-drawing-plot-conversion-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/27aa0c08bacf20ba3f5ce4f8d02ac226/plot_conversion.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_conversion.py</span></code></a></p> @@ -576,7 +576,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graphviz_drawing/plot_grid.html b/auto_examples/graphviz_drawing/plot_grid.html index 5daf25fd..2b55aa63 100644 --- a/auto_examples/graphviz_drawing/plot_grid.html +++ b/auto_examples/graphviz_drawing/plot_grid.html @@ -519,7 +519,7 @@ Graphviz command line interface to create visualizations.</p> <img src="../../_images/sphx_glr_plot_grid_001.png" srcset="../../_images/sphx_glr_plot_grid_001.png" alt="plot grid" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Now run: neato -Tps grid.dot >grid.ps </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.068 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.083 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graphviz-drawing-plot-grid-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/26e3cd745ae317a76a0df34cbf4999d8/plot_grid.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_grid.py</span></code></a></p> @@ -581,7 +581,7 @@ Graphviz command line interface to create visualizations.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graphviz_drawing/plot_mini_atlas.html b/auto_examples/graphviz_drawing/plot_mini_atlas.html index 21820239..d851360e 100644 --- a/auto_examples/graphviz_drawing/plot_mini_atlas.html +++ b/auto_examples/graphviz_drawing/plot_mini_atlas.html @@ -543,7 +543,7 @@ Graph named 'G19' with 5 nodes and 0 edges <a href="https://pygraphviz.github.io/documentation/stable/reference/agraph.html#pygraphviz.AGraph.draw" title="pygraphviz.AGraph.draw" class="sphx-glr-backref-module-pygraphviz sphx-glr-backref-type-py-method"><span class="n">A</span><span class="o">.</span><span class="n">draw</span></a><span class="p">(</span><span class="s2">"A20.png"</span><span class="p">,</span> <span class="n">prog</span><span class="o">=</span><span class="s2">"neato"</span><span class="p">)</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.079 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.101 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graphviz-drawing-plot-mini-atlas-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/cc271806f4fdfe8710206c593b90e506/plot_mini_atlas.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_mini_atlas.py</span></code></a></p> @@ -605,7 +605,7 @@ Graph named 'G19' with 5 nodes and 0 edges <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graphviz_drawing/sg_execution_times.html b/auto_examples/graphviz_drawing/sg_execution_times.html index 4aeb056a..bebaea4a 100644 --- a/auto_examples/graphviz_drawing/sg_execution_times.html +++ b/auto_examples/graphviz_drawing/sg_execution_times.html @@ -463,23 +463,23 @@ <section id="computation-times"> <span id="sphx-glr-auto-examples-graphviz-drawing-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this heading">#</a></h1> -<p><strong>00:00.201</strong> total execution time for <strong>auto_examples_graphviz_drawing</strong> files:</p> +<p><strong>00:00.305</strong> total execution time for <strong>auto_examples_graphviz_drawing</strong> files:</p> <table class="table"> <tbody> <tr class="row-odd"><td><p><a class="reference internal" href="plot_mini_atlas.html#sphx-glr-auto-examples-graphviz-drawing-plot-mini-atlas-py"><span class="std std-ref">Atlas</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_mini_atlas.py</span></code>)</p></td> -<td><p>00:00.079</p></td> +<td><p>00:00.101</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-even"><td><p><a class="reference internal" href="plot_grid.html#sphx-glr-auto-examples-graphviz-drawing-plot-grid-py"><span class="std std-ref">2D Grid</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_grid.py</span></code>)</p></td> -<td><p>00:00.068</p></td> +<tr class="row-even"><td><p><a class="reference internal" href="plot_attributes.html#sphx-glr-auto-examples-graphviz-drawing-plot-attributes-py"><span class="std std-ref">Attributes</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_attributes.py</span></code>)</p></td> +<td><p>00:00.089</p></td> <td><p>0.0 MB</p></td> </tr> -<tr class="row-odd"><td><p><a class="reference internal" href="plot_attributes.html#sphx-glr-auto-examples-graphviz-drawing-plot-attributes-py"><span class="std std-ref">Attributes</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_attributes.py</span></code>)</p></td> -<td><p>00:00.028</p></td> +<tr class="row-odd"><td><p><a class="reference internal" href="plot_grid.html#sphx-glr-auto-examples-graphviz-drawing-plot-grid-py"><span class="std std-ref">2D Grid</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_grid.py</span></code>)</p></td> +<td><p>00:00.083</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_conversion.html#sphx-glr-auto-examples-graphviz-drawing-plot-conversion-py"><span class="std std-ref">Conversion</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_conversion.py</span></code>)</p></td> -<td><p>00:00.026</p></td> +<td><p>00:00.032</p></td> <td><p>0.0 MB</p></td> </tr> </tbody> @@ -536,7 +536,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graphviz_layout/index.html b/auto_examples/graphviz_layout/index.html index 0c2eec74..86d7332c 100644 --- a/auto_examples/graphviz_layout/index.html +++ b/auto_examples/graphviz_layout/index.html @@ -564,7 +564,7 @@ These examples need Graphviz and <a class="reference external" href="https://pyg <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graphviz_layout/plot_atlas.html b/auto_examples/graphviz_layout/plot_atlas.html index d3ac832e..1a7ba2e3 100644 --- a/auto_examples/graphviz_layout/plot_atlas.html +++ b/auto_examples/graphviz_layout/plot_atlas.html @@ -520,7 +520,7 @@ We don’t plot the empty graph nor the single node graph. <span class="k">def</span> <span class="nf">atlas6</span><span class="p">():</span> - <span class="sd">"""Return the atlas of all connected graphs with at most 6 nodes"""</span> +<span class="w"> </span><span class="sd">"""Return the atlas of all connected graphs with at most 6 nodes"""</span> <span class="n">Atlas</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">graph_atlas_g</span><span class="p">()[</span><span class="mi">3</span><span class="p">:</span><span class="mi">209</span><span class="p">]</span> <span class="c1"># 0, 1, 2 => no edges. 208 is last 6 node graph</span> <span class="n">U</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">Graph</span><span class="p">()</span> <span class="c1"># graph for union of all graphs in atlas</span> @@ -549,7 +549,7 @@ We don’t plot the empty graph nor the single node graph. <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 3.703 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 5.043 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graphviz-layout-plot-atlas-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/37c712582f2a7575f32a59a1389228a7/plot_atlas.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_atlas.py</span></code></a></p> @@ -611,7 +611,7 @@ We don’t plot the empty graph nor the single node graph. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graphviz_layout/plot_circular_tree.html b/auto_examples/graphviz_layout/plot_circular_tree.html index 7ef9aa5c..daf2dead 100644 --- a/auto_examples/graphviz_layout/plot_circular_tree.html +++ b/auto_examples/graphviz_layout/plot_circular_tree.html @@ -510,7 +510,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.151 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.192 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graphviz-layout-plot-circular-tree-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/e854482dd498b1c5f7f158a5717b999d/plot_circular_tree.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_circular_tree.py</span></code></a></p> @@ -572,7 +572,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graphviz_layout/plot_decomposition.html b/auto_examples/graphviz_layout/plot_decomposition.html index f7e2f015..0f5749bb 100644 --- a/auto_examples/graphviz_layout/plot_decomposition.html +++ b/auto_examples/graphviz_layout/plot_decomposition.html @@ -535,7 +535,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.295 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.439 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graphviz-layout-plot-decomposition-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/533257c084adfbb38066f806a87784c5/plot_decomposition.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_decomposition.py</span></code></a></p> @@ -597,7 +597,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graphviz_layout/plot_giant_component.html b/auto_examples/graphviz_layout/plot_giant_component.html index 4b2ba59e..a73b815b 100644 --- a/auto_examples/graphviz_layout/plot_giant_component.html +++ b/auto_examples/graphviz_layout/plot_giant_component.html @@ -543,7 +543,7 @@ giant connected component in a binomial random graph.</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.812 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 1.106 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graphviz-layout-plot-giant-component-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/f5d29b33ff492f40e4749050b3f5e7dd/plot_giant_component.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_giant_component.py</span></code></a></p> @@ -605,7 +605,7 @@ giant connected component in a binomial random graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graphviz_layout/plot_lanl_routes.html b/auto_examples/graphviz_layout/plot_lanl_routes.html index 3d70c4f0..ffa76a67 100644 --- a/auto_examples/graphviz_layout/plot_lanl_routes.html +++ b/auto_examples/graphviz_layout/plot_lanl_routes.html @@ -516,7 +516,7 @@ to download the full example code</p> <span class="k">def</span> <span class="nf">lanl_graph</span><span class="p">():</span> - <span class="sd">"""Return the lanl internet view graph from lanl.edges"""</span> +<span class="w"> </span><span class="sd">"""Return the lanl internet view graph from lanl.edges"""</span> <span class="k">try</span><span class="p">:</span> <span class="n">fh</span> <span class="o">=</span> <span class="nb">open</span><span class="p">(</span><span class="s2">"lanl_routes.edgelist"</span><span class="p">)</span> <span class="k">except</span> <span class="ne">OSError</span><span class="p">:</span> @@ -561,7 +561,7 @@ to download the full example code</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.334 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.459 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-graphviz-layout-plot-lanl-routes-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/30e04b92b8aefc7afe7f634d84ae925a/plot_lanl_routes.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_lanl_routes.py</span></code></a></p> @@ -623,7 +623,7 @@ to download the full example code</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/graphviz_layout/sg_execution_times.html b/auto_examples/graphviz_layout/sg_execution_times.html index e3bf5b59..8f2320e0 100644 --- a/auto_examples/graphviz_layout/sg_execution_times.html +++ b/auto_examples/graphviz_layout/sg_execution_times.html @@ -463,27 +463,27 @@ <section id="computation-times"> <span id="sphx-glr-auto-examples-graphviz-layout-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this heading">#</a></h1> -<p><strong>00:05.294</strong> total execution time for <strong>auto_examples_graphviz_layout</strong> files:</p> +<p><strong>00:07.239</strong> total execution time for <strong>auto_examples_graphviz_layout</strong> files:</p> <table class="table"> <tbody> <tr class="row-odd"><td><p><a class="reference internal" href="plot_atlas.html#sphx-glr-auto-examples-graphviz-layout-plot-atlas-py"><span class="std std-ref">Atlas</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_atlas.py</span></code>)</p></td> -<td><p>00:03.703</p></td> +<td><p>00:05.043</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_giant_component.html#sphx-glr-auto-examples-graphviz-layout-plot-giant-component-py"><span class="std std-ref">Giant Component</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_giant_component.py</span></code>)</p></td> -<td><p>00:00.812</p></td> +<td><p>00:01.106</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" href="plot_lanl_routes.html#sphx-glr-auto-examples-graphviz-layout-plot-lanl-routes-py"><span class="std std-ref">Lanl Routes</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_lanl_routes.py</span></code>)</p></td> -<td><p>00:00.334</p></td> +<td><p>00:00.459</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_decomposition.html#sphx-glr-auto-examples-graphviz-layout-plot-decomposition-py"><span class="std std-ref">Decomposition</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_decomposition.py</span></code>)</p></td> -<td><p>00:00.295</p></td> +<td><p>00:00.439</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-odd"><td><p><a class="reference internal" href="plot_circular_tree.html#sphx-glr-auto-examples-graphviz-layout-plot-circular-tree-py"><span class="std std-ref">Circular Tree</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_circular_tree.py</span></code>)</p></td> -<td><p>00:00.151</p></td> +<td><p>00:00.192</p></td> <td><p>0.0 MB</p></td> </tr> </tbody> @@ -540,7 +540,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/index.html b/auto_examples/index.html index 8bb42997..fbe1409d 100644 --- a/auto_examples/index.html +++ b/auto_examples/index.html @@ -834,7 +834,7 @@ See the <a class="reference external" href="geospatial/extended_description.html <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/subclass/index.html b/auto_examples/subclass/index.html index f388e1d1..f6f908ec 100644 --- a/auto_examples/subclass/index.html +++ b/auto_examples/subclass/index.html @@ -550,7 +550,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/subclass/plot_antigraph.html b/auto_examples/subclass/plot_antigraph.html index 6201cfff..7a6e4ad5 100644 --- a/auto_examples/subclass/plot_antigraph.html +++ b/auto_examples/subclass/plot_antigraph.html @@ -509,7 +509,7 @@ algorithms.</p> <span class="k">class</span> <span class="nc">AntiGraph</span><span class="p">(</span><span class="n">Graph</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Class for complement graphs.</span> <span class="sd"> The main goal is to be able to work with big and dense graphs with</span> @@ -529,7 +529,7 @@ algorithms.</p> <span class="n">edge_attr_dict_factory</span> <span class="o">=</span> <span class="n">single_edge_dict</span> <span class="k">def</span> <span class="fm">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span> - <span class="sd">"""Return a dict of neighbors of node n in the dense graph.</span> +<span class="w"> </span><span class="sd">"""Return a dict of neighbors of node n in the dense graph.</span> <span class="sd"> Parameters</span> <span class="sd"> ----------</span> @@ -547,7 +547,7 @@ algorithms.</p> <span class="p">}</span> <span class="k">def</span> <span class="nf">neighbors</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span> - <span class="sd">"""Return an iterator over all neighbors of node n in the</span> +<span class="w"> </span><span class="sd">"""Return an iterator over all neighbors of node n in the</span> <span class="sd"> dense graph.</span> <span class="sd"> """</span> @@ -557,7 +557,7 @@ algorithms.</p> <span class="k">raise</span> <a href="https://docs.python.org/3/library/exceptions.html#Exception" title="builtins.Exception" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-exception"><span class="n">nx</span><span class="o">.</span><span class="n">NetworkXError</span></a><span class="p">(</span><span class="sa">f</span><span class="s2">"The node </span><span class="si">{</span><span class="n">n</span><span class="si">}</span><span class="s2"> is not in the graph."</span><span class="p">)</span> <span class="kn">from</span> <span class="nn">err</span> <span class="k">def</span> <span class="nf">degree</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">nbunch</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Return an iterator for (node, degree) in the dense graph.</span> +<span class="w"> </span><span class="sd">"""Return an iterator for (node, degree) in the dense graph.</span> <span class="sd"> The node degree is the number of edges adjacent to the node.</span> @@ -626,7 +626,7 @@ algorithms.</p> <span class="p">)</span> <span class="k">def</span> <span class="nf">adjacency</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="sd">"""Return an iterator of (node, adjacency set) tuples for all nodes</span> +<span class="w"> </span><span class="sd">"""Return an iterator of (node, adjacency set) tuples for all nodes</span> <span class="sd"> in the dense graph.</span> <span class="sd"> This is the fastest way to look at every edge.</span> @@ -680,7 +680,7 @@ algorithms.</p> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.090 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.122 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-subclass-plot-antigraph-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/652afbfc3c52c8cdd7689321df2e696a/plot_antigraph.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_antigraph.py</span></code></a></p> @@ -742,7 +742,7 @@ algorithms.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/subclass/plot_printgraph.html b/auto_examples/subclass/plot_printgraph.html index b3dd8913..38c85ba4 100644 --- a/auto_examples/subclass/plot_printgraph.html +++ b/auto_examples/subclass/plot_printgraph.html @@ -540,7 +540,7 @@ Add edge: 9-12 <span class="k">class</span> <span class="nc">PrintGraph</span><span class="p">(</span><span class="n">Graph</span><span class="p">):</span> - <span class="sd">"""</span> +<span class="w"> </span><span class="sd">"""</span> <span class="sd"> Example subclass of the Graph class.</span> <span class="sd"> Prints activity log to file or standard output.</span> @@ -616,7 +616,7 @@ Add edge: 9-12 <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span> </pre></div> </div> -<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.057 seconds)</p> +<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.087 seconds)</p> <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-subclass-plot-printgraph-py"> <div class="sphx-glr-download sphx-glr-download-python docutils container"> <p><a class="reference download internal" download="" href="../../_downloads/1b5e7bf8d2514d71280314171170de85/plot_printgraph.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_printgraph.py</span></code></a></p> @@ -678,7 +678,7 @@ Add edge: 9-12 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/auto_examples/subclass/sg_execution_times.html b/auto_examples/subclass/sg_execution_times.html index 2023d65a..b9259933 100644 --- a/auto_examples/subclass/sg_execution_times.html +++ b/auto_examples/subclass/sg_execution_times.html @@ -463,15 +463,15 @@ <section id="computation-times"> <span id="sphx-glr-auto-examples-subclass-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this heading">#</a></h1> -<p><strong>00:00.147</strong> total execution time for <strong>auto_examples_subclass</strong> files:</p> +<p><strong>00:00.210</strong> total execution time for <strong>auto_examples_subclass</strong> files:</p> <table class="table"> <tbody> <tr class="row-odd"><td><p><a class="reference internal" href="plot_antigraph.html#sphx-glr-auto-examples-subclass-plot-antigraph-py"><span class="std std-ref">Antigraph</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_antigraph.py</span></code>)</p></td> -<td><p>00:00.090</p></td> +<td><p>00:00.122</p></td> <td><p>0.0 MB</p></td> </tr> <tr class="row-even"><td><p><a class="reference internal" href="plot_printgraph.html#sphx-glr-auto-examples-subclass-plot-printgraph-py"><span class="std std-ref">Print Graph</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_printgraph.py</span></code>)</p></td> -<td><p>00:00.057</p></td> +<td><p>00:00.087</p></td> <td><p>0.0 MB</p></td> </tr> </tbody> @@ -528,7 +528,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/about_us.html b/developer/about_us.html index f4292fe9..c472d47f 100644 --- a/developer/about_us.html +++ b/developer/about_us.html @@ -989,7 +989,7 @@ contract number W911NF-13-1-0340</p></li> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/code_of_conduct.html b/developer/code_of_conduct.html index 7283c5aa..e3be4405 100644 --- a/developer/code_of_conduct.html +++ b/developer/code_of_conduct.html @@ -711,7 +711,7 @@ within 72 hours.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/contribute.html b/developer/contribute.html index ac000fb7..70b50b01 100644 --- a/developer/contribute.html +++ b/developer/contribute.html @@ -1063,7 +1063,7 @@ and decorate it as follows:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/core_developer.html b/developer/core_developer.html index 9dccc12f..95e4cb23 100644 --- a/developer/core_developer.html +++ b/developer/core_developer.html @@ -725,7 +725,7 @@ list</a></p></li> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/deprecations.html b/developer/deprecations.html index 65149d41..38b193fa 100644 --- a/developer/deprecations.html +++ b/developer/deprecations.html @@ -638,7 +638,7 @@ for the <code class="docutils literal notranslate"><span class="pre">scale_free_ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/index.html b/developer/index.html index 61efe80e..179fa412 100644 --- a/developer/index.html +++ b/developer/index.html @@ -493,7 +493,7 @@ <dd class="field-odd"><p>3.0rc2.dev0</p> </dd> <dt class="field-even">Date<span class="colon">:</span></dt> -<dd class="field-even"><p>Dec 27, 2022</p> +<dd class="field-even"><p>Jan 02, 2023</p> </dd> </dl> <div class="toctree-wrapper compound"> @@ -630,7 +630,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/new_contributor_faq.html b/developer/new_contributor_faq.html index f144bd1d..676f6bb0 100644 --- a/developer/new_contributor_faq.html +++ b/developer/new_contributor_faq.html @@ -540,7 +540,7 @@ from Python scripts stored in the <code class="docutils literal notranslate"><sp Assuming you have already followed the procedure for <a class="reference internal" href="contribute.html#dev-workflow"><span class="std std-ref">setting up a development environment</span></a>, start by creating a new branch:</p> -<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>git checkout -b complete-graph-circular-layout-example +<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>git<span class="w"> </span>checkout<span class="w"> </span>-b<span class="w"> </span>complete-graph-circular-layout-example </pre></div> </div> <div class="admonition note"> @@ -598,8 +598,8 @@ Type: function </div> <p>Command line utilities like <code class="docutils literal notranslate"><span class="pre">grep</span></code> or <code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">grep</span></code> are also very useful. For example, from the NetworkX source directory:</p> -<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>$ grep -r <span class="s2">"def kamada_kawai_layout"</span> . -./networkx/drawing/layout.py:def kamada_kawai_layout<span class="o">(</span> +<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>$<span class="w"> </span>grep<span class="w"> </span>-r<span class="w"> </span><span class="s2">"def kamada_kawai_layout"</span><span class="w"> </span>. +./networkx/drawing/layout.py:def<span class="w"> </span>kamada_kawai_layout<span class="o">(</span> </pre></div> </div> </section> @@ -699,7 +699,7 @@ citations is how well proposed additions fit the project <a class="reference int <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/nxeps/index.html b/developer/nxeps/index.html index ace140ef..3ebb5749 100644 --- a/developer/nxeps/index.html +++ b/developer/nxeps/index.html @@ -560,7 +560,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/nxeps/nxep-0000.html b/developer/nxeps/nxep-0000.html index 36a9fd18..b8742f5b 100644 --- a/developer/nxeps/nxep-0000.html +++ b/developer/nxeps/nxep-0000.html @@ -845,7 +845,7 @@ for retrieving older revisions, and can also be browsed on <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/nxeps/nxep-0001.html b/developer/nxeps/nxep-0001.html index 696373c1..87ecf2d5 100644 --- a/developer/nxeps/nxep-0001.html +++ b/developer/nxeps/nxep-0001.html @@ -750,7 +750,7 @@ The workflow of a NXEP is detailed in <a class="reference internal" href="nxep-0 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/nxeps/nxep-0002.html b/developer/nxeps/nxep-0002.html index b1c44b9e..fd8d9ba5 100644 --- a/developer/nxeps/nxep-0002.html +++ b/developer/nxeps/nxep-0002.html @@ -921,7 +921,7 @@ discussion above. Users will now see <code class="xref py py-obj docutils litera <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/nxeps/nxep-0003.html b/developer/nxeps/nxep-0003.html index d16c9828..c17994d4 100644 --- a/developer/nxeps/nxep-0003.html +++ b/developer/nxeps/nxep-0003.html @@ -806,13 +806,13 @@ that shown above in the description of Edgelist should be used.</p> <p>Example developer usage:</p> <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nd">@node_and_edge_builder</span> <span class="k">def</span> <span class="nf">path_graph</span><span class="p">(</span><span class="n">n</span><span class="p">):</span> - <span class="sd">"""an overly simplified path graph implementation"""</span> +<span class="w"> </span><span class="sd">"""an overly simplified path graph implementation"""</span> <span class="k">return</span> <span class="n">pairwise</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="n">n</span><span class="p">))</span> <span class="nd">@graph_builder</span> <span class="k">def</span> <span class="nf">complete_graph</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">create_using</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""an overly simplified complete graph implementation"""</span> +<span class="w"> </span><span class="sd">"""an overly simplified complete graph implementation"""</span> <span class="k">if</span> <span class="n">create_using</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> <span class="n">create_using</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">Graph</span> <span class="n">g</span> <span class="o">=</span> <span class="n">empty_graph</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">create_using</span><span class="p">)</span> @@ -966,7 +966,7 @@ which built on discussion from <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/nxeps/nxep-0004.html b/developer/nxeps/nxep-0004.html index 480903ba..baa8e7b7 100644 --- a/developer/nxeps/nxep-0004.html +++ b/developer/nxeps/nxep-0004.html @@ -619,7 +619,7 @@ as the seed. For example, let’s take the following function:</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="nd">@np_random_state</span><span class="p">(</span><span class="s2">"seed"</span><span class="p">)</span> <span class="k">def</span> <span class="nf">bar</span><span class="p">(</span><span class="n">num</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> - <span class="sd">"""Return an array of `num` uniform random numbers."""</span> +<span class="w"> </span><span class="sd">"""Return an array of `num` uniform random numbers."""</span> <span class="k">return</span> <span class="n">seed</span><span class="o">.</span><span class="n">random</span><span class="p">(</span><span class="n">num</span><span class="p">)</span> </pre></div> </div> @@ -896,7 +896,7 @@ regarding the NXEP:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/nxeps/nxep-template.html b/developer/nxeps/nxep-template.html index 88790a2c..9633c893 100644 --- a/developer/nxeps/nxep-template.html +++ b/developer/nxeps/nxep-template.html @@ -687,7 +687,7 @@ regarding the NXEP:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/projects.html b/developer/projects.html index 45f6f119..02ef3740 100644 --- a/developer/projects.html +++ b/developer/projects.html @@ -668,7 +668,7 @@ for the long duration project.</p></li> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/release.html b/developer/release.html index 748a03a4..32dc239b 100644 --- a/developer/release.html +++ b/developer/release.html @@ -671,7 +671,7 @@ creates headaches.</p></li> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/roadmap.html b/developer/roadmap.html index f02cea6d..9957611c 100644 --- a/developer/roadmap.html +++ b/developer/roadmap.html @@ -683,7 +683,7 @@ We need to enhance the drawing tools for NetworkX.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/team.html b/developer/team.html index 4c7e5e57..79160625 100644 --- a/developer/team.html +++ b/developer/team.html @@ -770,7 +770,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/developer/values.html b/developer/values.html index a42c0dfb..68293ee7 100644 --- a/developer/values.html +++ b/developer/values.html @@ -616,7 +616,7 @@ function is used in a scientific application.</p></li> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/genindex.html b/genindex.html index 36aa732a..13904a36 100644 --- a/genindex.html +++ b/genindex.html @@ -5151,7 +5151,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> @@ -464,7 +464,7 @@ <dd class="field-odd"><p>3.0rc2.dev0</p> </dd> <dt class="field-even">Date<span class="colon">:</span></dt> -<dd class="field-even"><p>Dec 27, 2022</p> +<dd class="field-even"><p>Jan 02, 2023</p> </dd> </dl> <p>NetworkX is a Python package for the creation, manipulation, and study @@ -708,7 +708,7 @@ Addison Wesley Professional, 3rd ed., 2001.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/install.html b/install.html index 416aaef1..431730db 100644 --- a/install.html +++ b/install.html @@ -670,7 +670,7 @@ about pytest on their <a class="reference external" href="https://pytest.org">ho <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/py-modindex.html b/py-modindex.html index 65b0e7c3..68e3fbf3 100644 --- a/py-modindex.html +++ b/py-modindex.html @@ -1581,7 +1581,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/approximation.html b/reference/algorithms/approximation.html index 9d5a534f..752d044f 100644 --- a/reference/algorithms/approximation.html +++ b/reference/algorithms/approximation.html @@ -955,7 +955,7 @@ is incident to at least one node in the subset.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/assortativity.html b/reference/algorithms/assortativity.html index 4e33c365..90bc55a4 100644 --- a/reference/algorithms/assortativity.html +++ b/reference/algorithms/assortativity.html @@ -727,7 +727,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/asteroidal.html b/reference/algorithms/asteroidal.html index 75b0e6de..ba8ace0f 100644 --- a/reference/algorithms/asteroidal.html +++ b/reference/algorithms/asteroidal.html @@ -631,7 +631,7 @@ independent set and coloring.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/bipartite.html b/reference/algorithms/bipartite.html index 98d82872..41f99a26 100644 --- a/reference/algorithms/bipartite.html +++ b/reference/algorithms/bipartite.html @@ -999,7 +999,7 @@ edges included in the matching is minimal.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/boundary.html b/reference/algorithms/boundary.html index 0b638ae8..d37fa182 100644 --- a/reference/algorithms/boundary.html +++ b/reference/algorithms/boundary.html @@ -628,7 +628,7 @@ nodes in <em>S</em> that are outside <em>S</em>.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/bridges.html b/reference/algorithms/bridges.html index 9a1afdde..8e9893db 100644 --- a/reference/algorithms/bridges.html +++ b/reference/algorithms/bridges.html @@ -626,7 +626,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/centrality.html b/reference/algorithms/centrality.html index 6244e337..6918c6f3 100644 --- a/reference/algorithms/centrality.html +++ b/reference/algorithms/centrality.html @@ -955,7 +955,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/chains.html b/reference/algorithms/chains.html index f00b4a13..76c06a7d 100644 --- a/reference/algorithms/chains.html +++ b/reference/algorithms/chains.html @@ -620,7 +620,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/chordal.html b/reference/algorithms/chordal.html index 8ea987dd..bda0a0b5 100644 --- a/reference/algorithms/chordal.html +++ b/reference/algorithms/chordal.html @@ -635,7 +635,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/clique.html b/reference/algorithms/clique.html index a5057332..81554848 100644 --- a/reference/algorithms/clique.html +++ b/reference/algorithms/clique.html @@ -659,7 +659,7 @@ see the Wikipedia article on the clique problem <a class="reference internal" hr <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/clustering.html b/reference/algorithms/clustering.html index 622f8878..73f2ded0 100644 --- a/reference/algorithms/clustering.html +++ b/reference/algorithms/clustering.html @@ -635,7 +635,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/coloring.html b/reference/algorithms/coloring.html index dde9460f..851ba979 100644 --- a/reference/algorithms/coloring.html +++ b/reference/algorithms/coloring.html @@ -651,7 +651,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/communicability_alg.html b/reference/algorithms/communicability_alg.html index 21f78214..f47facd3 100644 --- a/reference/algorithms/communicability_alg.html +++ b/reference/algorithms/communicability_alg.html @@ -623,7 +623,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/community.html b/reference/algorithms/community.html index 9faaab43..2a03755f 100644 --- a/reference/algorithms/community.html +++ b/reference/algorithms/community.html @@ -811,7 +811,7 @@ communities).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/component.html b/reference/algorithms/component.html index f5433417..2b2bda69 100644 --- a/reference/algorithms/component.html +++ b/reference/algorithms/component.html @@ -759,7 +759,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/connectivity.html b/reference/algorithms/connectivity.html index 3cac2076..969d937c 100644 --- a/reference/algorithms/connectivity.html +++ b/reference/algorithms/connectivity.html @@ -836,7 +836,7 @@ least k.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/core.html b/reference/algorithms/core.html index ee95dcc9..b0be1659 100644 --- a/reference/algorithms/core.html +++ b/reference/algorithms/core.html @@ -656,7 +656,7 @@ Scientific Reports 6, 31708 (2016) <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/covering.html b/reference/algorithms/covering.html index bb253b36..61eea6d1 100644 --- a/reference/algorithms/covering.html +++ b/reference/algorithms/covering.html @@ -623,7 +623,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/cuts.html b/reference/algorithms/cuts.html index 9822fcd5..61e3bf90 100644 --- a/reference/algorithms/cuts.html +++ b/reference/algorithms/cuts.html @@ -641,7 +641,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/cycles.html b/reference/algorithms/cycles.html index a16220b9..254fa011 100644 --- a/reference/algorithms/cycles.html +++ b/reference/algorithms/cycles.html @@ -631,7 +631,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/d_separation.html b/reference/algorithms/d_separation.html index 265aa7db..a83bc205 100644 --- a/reference/algorithms/d_separation.html +++ b/reference/algorithms/d_separation.html @@ -774,7 +774,7 @@ Probabilistic graphical models: principles and techniques. The MIT Press.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/dag.html b/reference/algorithms/dag.html index d4794a0f..0a49ab51 100644 --- a/reference/algorithms/dag.html +++ b/reference/algorithms/dag.html @@ -665,7 +665,7 @@ to the user to check for that.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/distance_measures.html b/reference/algorithms/distance_measures.html index e6c831c4..4d78453e 100644 --- a/reference/algorithms/distance_measures.html +++ b/reference/algorithms/distance_measures.html @@ -638,7 +638,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/distance_regular.html b/reference/algorithms/distance_regular.html index 29e59436..f9366612 100644 --- a/reference/algorithms/distance_regular.html +++ b/reference/algorithms/distance_regular.html @@ -628,7 +628,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/dominance.html b/reference/algorithms/dominance.html index f49de56e..17211b6f 100644 --- a/reference/algorithms/dominance.html +++ b/reference/algorithms/dominance.html @@ -623,7 +623,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/dominating.html b/reference/algorithms/dominating.html index f9c628eb..b6fd405b 100644 --- a/reference/algorithms/dominating.html +++ b/reference/algorithms/dominating.html @@ -623,7 +623,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/efficiency_measures.html b/reference/algorithms/efficiency_measures.html index 3662d2b9..349ee6fb 100644 --- a/reference/algorithms/efficiency_measures.html +++ b/reference/algorithms/efficiency_measures.html @@ -626,7 +626,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/euler.html b/reference/algorithms/euler.html index 57d35186..64657957 100644 --- a/reference/algorithms/euler.html +++ b/reference/algorithms/euler.html @@ -635,7 +635,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/flow.html b/reference/algorithms/flow.html index 50dfac90..d0cb1b48 100644 --- a/reference/algorithms/flow.html +++ b/reference/algorithms/flow.html @@ -795,7 +795,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.construct.html b/reference/algorithms/generated/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.construct.html index 9d5b8696..75ddf76c 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.construct.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.construct.html @@ -657,7 +657,7 @@ node.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.k_edge_components.html b/reference/algorithms/generated/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.k_edge_components.html index 6d745fc9..3ca969d7 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.k_edge_components.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.k_edge_components.html @@ -657,7 +657,7 @@ k-edge-ccs in the original graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.k_edge_subgraphs.html b/reference/algorithms/generated/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.k_edge_subgraphs.html index 3ca0d0c6..7b9bf8d4 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.k_edge_subgraphs.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.k_edge_subgraphs.html @@ -659,7 +659,7 @@ then use this method.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.analyze_symmetry.html b/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.analyze_symmetry.html index 0ff7b055..1bdd030b 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.analyze_symmetry.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.analyze_symmetry.html @@ -670,7 +670,7 @@ without changing nodes less than <code class="docutils literal notranslate"><spa <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.find_isomorphisms.html b/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.find_isomorphisms.html index f3888b06..7ea95b5b 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.find_isomorphisms.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.find_isomorphisms.html @@ -655,7 +655,7 @@ isomorphisms may be symmetrically equivalent.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.is_isomorphic.html b/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.is_isomorphic.html index 4fe9b95f..d2f85433 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.is_isomorphic.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.is_isomorphic.html @@ -647,7 +647,7 @@ False otherwise.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.isomorphisms_iter.html b/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.isomorphisms_iter.html index 229436e5..8f355988 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.isomorphisms_iter.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.isomorphisms_iter.html @@ -640,7 +640,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.largest_common_subgraph.html b/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.largest_common_subgraph.html index 440335e9..0d60cdca 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.largest_common_subgraph.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.largest_common_subgraph.html @@ -655,7 +655,7 @@ largest common subgraphs may be symmetrically equivalent.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.subgraph_is_isomorphic.html b/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.subgraph_is_isomorphic.html index 52fd2d41..8a5b7887 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.subgraph_is_isomorphic.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.subgraph_is_isomorphic.html @@ -647,7 +647,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.subgraph_isomorphisms_iter.html b/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.subgraph_isomorphisms_iter.html index d8460328..78c85236 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.subgraph_isomorphisms_iter.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.isomorphism.ISMAGS.subgraph_isomorphisms_iter.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_edge.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_edge.html index 2bcd6b56..57ede3ea 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_edge.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_edge.html @@ -686,7 +686,7 @@ an edge attribute (by default <code class="xref py py-obj docutils literal notra <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_edges_from.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_edges_from.html index 180b57c6..11faed13 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_edges_from.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_edges_from.html @@ -694,7 +694,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_ccw.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_ccw.html index a0146b74..a741c1bc 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_ccw.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_ccw.html @@ -667,7 +667,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_cw.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_cw.html index ceedc75a..3dc31ee6 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_cw.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_cw.html @@ -667,7 +667,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_first.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_first.html index a5e8c620..fc7f8d0f 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_first.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_first.html @@ -655,7 +655,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_node.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_node.html index 2bd5ec0b..59e13055 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_node.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_node.html @@ -677,7 +677,7 @@ doesn’t change on mutables.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_nodes_from.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_nodes_from.html index 1be46c53..759d98b7 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_nodes_from.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_nodes_from.html @@ -700,7 +700,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_weighted_edges_from.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_weighted_edges_from.html index 55a848a6..d6b17746 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_weighted_edges_from.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.add_weighted_edges_from.html @@ -688,7 +688,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.adj.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.adj.html index 7c23a118..7f61b1a8 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.adj.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.adj.html @@ -648,7 +648,7 @@ So <code class="xref py py-obj docutils literal notranslate"><span class="pre">f <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.adjacency.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.adjacency.html index 6ec04fe1..92718baf 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.adjacency.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.adjacency.html @@ -655,7 +655,7 @@ the graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.check_structure.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.check_structure.html index a6dca181..d124d2da 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.check_structure.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.check_structure.html @@ -656,7 +656,7 @@ PlanarEmbedding is invalid.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.clear.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.clear.html index 510d2e16..cbad9906 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.clear.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.clear.html @@ -649,7 +649,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.clear_edges.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.clear_edges.html index fd30d103..7a39e85c 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.clear_edges.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.clear_edges.html @@ -648,7 +648,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.connect_components.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.connect_components.html index f95ddf8c..c82e1b8d 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.connect_components.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.connect_components.html @@ -661,7 +661,7 @@ all set correctly after the first call.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.copy.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.copy.html index 536e1ee7..e22ae17d 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.copy.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.copy.html @@ -711,7 +711,7 @@ and deep copies, <a class="reference external" href="https://docs.python.org/3/l <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.degree.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.degree.html index cb091344..bd347d8b 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.degree.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.degree.html @@ -679,7 +679,7 @@ If a single node is requested, returns the degree of the node as an integer.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.edge_subgraph.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.edge_subgraph.html index 0dc3a317..ce3204c9 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.edge_subgraph.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.edge_subgraph.html @@ -674,7 +674,7 @@ of the edge or node attributes, use:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.edges.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.edges.html index c89f1a71..3c2fd0c2 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.edges.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.edges.html @@ -697,7 +697,7 @@ For directed graphs this returns the out-edges.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.get_data.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.get_data.html index b1b69d82..bcd6380a 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.get_data.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.get_data.html @@ -654,7 +654,7 @@ clockwise order.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.get_edge_data.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.get_edge_data.html index 4c670c07..6fcec056 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.get_edge_data.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.get_edge_data.html @@ -681,7 +681,7 @@ But it is safe to assign attributes <code class="xref py py-obj docutils literal <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.has_edge.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.has_edge.html index 031866b4..c5a337b6 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.has_edge.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.has_edge.html @@ -674,7 +674,7 @@ Nodes must be hashable (and not None) Python objects.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.has_node.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.has_node.html index ac201526..9e7f5b98 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.has_node.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.has_node.html @@ -658,7 +658,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.has_predecessor.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.has_predecessor.html index 83511b9a..a2ba4d70 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.has_predecessor.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.has_predecessor.html @@ -640,7 +640,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.has_successor.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.has_successor.html index a53a0962..055c0bc0 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.has_successor.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.has_successor.html @@ -640,7 +640,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.in_degree.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.in_degree.html index 3596ec0d..14237bb9 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.in_degree.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.in_degree.html @@ -681,7 +681,7 @@ The degree is the sum of the edge weights adjacent to the node.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.in_edges.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.in_edges.html index e18e70b8..8f6ca102 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.in_edges.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.in_edges.html @@ -694,7 +694,7 @@ attribute lookup as <code class="xref py py-obj docutils literal notranslate"><s <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.is_directed.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.is_directed.html index fbf1c44e..1db09870 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.is_directed.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.is_directed.html @@ -642,7 +642,7 @@ contained.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.is_multigraph.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.is_multigraph.html index 632968a0..2075b019 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.is_multigraph.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.is_multigraph.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.name.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.name.html index 6b6dbc0a..e01d20a5 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.name.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.name.html @@ -642,7 +642,7 @@ a property) <code class="xref py py-obj docutils literal notranslate"><span clas <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.nbunch_iter.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.nbunch_iter.html index 7ad96c24..03737d86 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.nbunch_iter.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.nbunch_iter.html @@ -678,7 +678,7 @@ nbunch is not hashable, a <code class="xref py py-exc docutils literal notransla <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.neighbors.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.neighbors.html index 6423cbd0..926dfb47 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.neighbors.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.neighbors.html @@ -663,7 +663,7 @@ edge from n to m.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.neighbors_cw_order.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.neighbors_cw_order.html index cac2466b..ffccd8b5 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.neighbors_cw_order.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.neighbors_cw_order.html @@ -651,7 +651,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.next_face_half_edge.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.next_face_half_edge.html index 3387a07b..adba63b5 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.next_face_half_edge.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.next_face_half_edge.html @@ -652,7 +652,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.nodes.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.nodes.html index 369cc863..d59c79da 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.nodes.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.nodes.html @@ -726,7 +726,7 @@ to guarantee the value is never None:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.number_of_edges.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.number_of_edges.html index 0247a781..3d5159ad 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.number_of_edges.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.number_of_edges.html @@ -686,7 +686,7 @@ directed edges from <code class="xref py py-obj docutils literal notranslate"><s <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.number_of_nodes.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.number_of_nodes.html index baf97463..6302a379 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.number_of_nodes.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.number_of_nodes.html @@ -662,7 +662,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.order.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.order.html index 7f54c110..63f51c3c 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.order.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.order.html @@ -662,7 +662,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.out_degree.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.out_degree.html index c341a0bb..34e05c14 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.out_degree.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.out_degree.html @@ -681,7 +681,7 @@ The degree is the sum of the edge weights adjacent to the node.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.out_edges.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.out_edges.html index 1a710d2d..9fb3d65b 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.out_edges.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.out_edges.html @@ -697,7 +697,7 @@ For directed graphs this returns the out-edges.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.pred.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.pred.html index 1cd02366..48af554b 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.pred.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.pred.html @@ -647,7 +647,7 @@ A default can be set via a <code class="xref py py-obj docutils literal notransl <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.predecessors.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.predecessors.html index aedcf304..86b46b8c 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.predecessors.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.predecessors.html @@ -661,7 +661,7 @@ edge from m to n.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.remove_edge.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.remove_edge.html index abff671d..66491911 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.remove_edge.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.remove_edge.html @@ -670,7 +670,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.remove_edges_from.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.remove_edges_from.html index 85c4fb82..45d9f8af 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.remove_edges_from.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.remove_edges_from.html @@ -669,7 +669,7 @@ from the graph. The edges can be:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.remove_node.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.remove_node.html index e2ab6365..514c5494 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.remove_node.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.remove_node.html @@ -670,7 +670,7 @@ Attempting to remove a non-existent node will raise an exception.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.remove_nodes_from.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.remove_nodes_from.html index b3567866..684ee40d 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.remove_nodes_from.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.remove_nodes_from.html @@ -680,7 +680,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.reverse.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.reverse.html index 753bc636..9b215b1d 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.reverse.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.reverse.html @@ -651,7 +651,7 @@ the original graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.set_data.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.set_data.html index 0e86a108..487cf53a 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.set_data.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.set_data.html @@ -655,7 +655,7 @@ clockwise order.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.size.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.size.html index 848cbc70..ec8a0ab4 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.size.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.size.html @@ -678,7 +678,7 @@ as a weight. If None, then each edge has weight 1.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.subgraph.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.subgraph.html index e727754b..f4fac60f 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.subgraph.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.subgraph.html @@ -690,7 +690,7 @@ more sense to just create the subgraph as its own graph with code like:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.succ.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.succ.html index fd2be735..54fd1e8f 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.succ.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.succ.html @@ -650,7 +650,7 @@ So <code class="xref py py-obj docutils literal notranslate"><span class="pre">f <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.successors.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.successors.html index 5a10bb08..e733a776 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.successors.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.successors.html @@ -663,7 +663,7 @@ edge from n to m.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.to_directed.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.to_directed.html index 92dd7831..5b18538c 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.to_directed.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.to_directed.html @@ -676,7 +676,7 @@ DiGraph created by this method.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.to_directed_class.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.to_directed_class.html index fa9d0d40..8a857241 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.to_directed_class.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.to_directed_class.html @@ -641,7 +641,7 @@ what directed class to use for <a class="reference internal" href="networkx.algo <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.to_undirected.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.to_undirected.html index 20b4b135..fe7df85c 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.to_undirected.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.to_undirected.html @@ -693,7 +693,7 @@ Graph created by this method.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.to_undirected_class.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.to_undirected_class.html index 069b39f9..d3c96af3 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.to_undirected_class.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.to_undirected_class.html @@ -641,7 +641,7 @@ what directed class to use for <a class="reference internal" href="networkx.algo <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.traverse_face.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.traverse_face.html index cccc5cae..024c9ed6 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.traverse_face.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.traverse_face.html @@ -662,7 +662,7 @@ any half-edges that belong to the face.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.update.html b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.update.html index e0ac4d82..cdaac7ab 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.update.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.planarity.PlanarEmbedding.update.html @@ -739,7 +739,7 @@ be slightly different and require tweaks of these examples:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/generated/networkx.algorithms.tree.branchings.Edmonds.find_optimum.html b/reference/algorithms/generated/generated/networkx.algorithms.tree.branchings.Edmonds.find_optimum.html index 93788429..d3111dc3 100644 --- a/reference/algorithms/generated/generated/networkx.algorithms.tree.branchings.Edmonds.find_optimum.html +++ b/reference/algorithms/generated/generated/networkx.algorithms.tree.branchings.Edmonds.find_optimum.html @@ -673,7 +673,7 @@ See <a class="reference internal" href="../../../randomness.html#randomness"><sp <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.clique.clique_removal.html b/reference/algorithms/generated/networkx.algorithms.approximation.clique.clique_removal.html index 2fa47dc4..36c28d63 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.clique.clique_removal.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.clique.clique_removal.html @@ -672,7 +672,7 @@ BIT Numerical Mathematics, 32(2), 180–196. Springer.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.clique.large_clique_size.html b/reference/algorithms/generated/networkx.algorithms.approximation.clique.large_clique_size.html index 4e53a2b2..cd28f00e 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.clique.large_clique_size.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.clique.large_clique_size.html @@ -690,7 +690,7 @@ with Applications to Overlapping Community Detection.” <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.clique.max_clique.html b/reference/algorithms/generated/networkx.algorithms.approximation.clique.max_clique.html index b5dfc309..22e04444 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.clique.max_clique.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.clique.max_clique.html @@ -683,7 +683,7 @@ doi:10.1007/BF01994876</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.clique.maximum_independent_set.html b/reference/algorithms/generated/networkx.algorithms.approximation.clique.maximum_independent_set.html index dc6b86af..9ad8cb9c 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.clique.maximum_independent_set.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.clique.maximum_independent_set.html @@ -686,7 +686,7 @@ BIT Numerical Mathematics, 32(2), 180–196. Springer.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.clustering_coefficient.average_clustering.html b/reference/algorithms/generated/networkx.algorithms.approximation.clustering_coefficient.average_clustering.html index 0f81666d..8a1fa01b 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.clustering_coefficient.average_clustering.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.clustering_coefficient.average_clustering.html @@ -684,7 +684,7 @@ Informatik, 2004. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.connectivity.all_pairs_node_connectivity.html b/reference/algorithms/generated/networkx.algorithms.approximation.connectivity.all_pairs_node_connectivity.html index 76da07fe..db7925ea 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.connectivity.all_pairs_node_connectivity.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.connectivity.all_pairs_node_connectivity.html @@ -696,7 +696,7 @@ nodes in the cycle and connectivity 1 between the extra node and the rest:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.connectivity.local_node_connectivity.html b/reference/algorithms/generated/networkx.algorithms.approximation.connectivity.local_node_connectivity.html index e97a2bb0..0dd0eef1 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.connectivity.local_node_connectivity.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.connectivity.local_node_connectivity.html @@ -703,7 +703,7 @@ Node-Independent Paths. Santa Fe Institute Working Paper #01-07-035 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.connectivity.node_connectivity.html b/reference/algorithms/generated/networkx.algorithms.approximation.connectivity.node_connectivity.html index 947c5ce3..dae220d1 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.connectivity.node_connectivity.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.connectivity.node_connectivity.html @@ -701,7 +701,7 @@ Node-Independent Paths. Santa Fe Institute Working Paper #01-07-035 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.distance_measures.diameter.html b/reference/algorithms/generated/networkx.algorithms.approximation.distance_measures.diameter.html index 81caa542..21639063 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.distance_measures.diameter.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.distance_measures.diameter.html @@ -699,7 +699,7 @@ International Symposium on Experimental Algorithms. Springer, Berlin, Heidelberg <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.dominating_set.min_edge_dominating_set.html b/reference/algorithms/generated/networkx.algorithms.approximation.dominating_set.min_edge_dominating_set.html index 56f02865..56384cde 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.dominating_set.min_edge_dominating_set.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.dominating_set.min_edge_dominating_set.html @@ -658,7 +658,7 @@ Runtime of the algorithm is <span class="math notranslate nohighlight">\(O(|E|)\ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.dominating_set.min_weighted_dominating_set.html b/reference/algorithms/generated/networkx.algorithms.approximation.dominating_set.min_weighted_dominating_set.html index 28c2cdea..bc2941d9 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.dominating_set.min_weighted_dominating_set.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.dominating_set.min_weighted_dominating_set.html @@ -679,7 +679,7 @@ Springer Science & Business Media, 2001.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.kcomponents.k_components.html b/reference/algorithms/generated/networkx.algorithms.approximation.kcomponents.k_components.html index 5772cc50..232b5236 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.kcomponents.k_components.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.kcomponents.k_components.html @@ -732,7 +732,7 @@ American Sociological Review 68(1), 103–28. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.matching.min_maximal_matching.html b/reference/algorithms/generated/networkx.algorithms.approximation.matching.min_maximal_matching.html index d0964241..99d98a25 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.matching.min_maximal_matching.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.matching.min_maximal_matching.html @@ -668,7 +668,7 @@ Runtime is <span class="math notranslate nohighlight">\(O(|E|)\)</span>.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.maxcut.one_exchange.html b/reference/algorithms/generated/networkx.algorithms.approximation.maxcut.one_exchange.html index 615a0156..7595d65c 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.maxcut.one_exchange.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.maxcut.one_exchange.html @@ -668,7 +668,7 @@ have weight one.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.maxcut.randomized_partitioning.html b/reference/algorithms/generated/networkx.algorithms.approximation.maxcut.randomized_partitioning.html index b48cdb2d..410fbe3c 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.maxcut.randomized_partitioning.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.maxcut.randomized_partitioning.html @@ -667,7 +667,7 @@ have weight one.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.ramsey.ramsey_R2.html b/reference/algorithms/generated/networkx.algorithms.approximation.ramsey.ramsey_R2.html index 6838e6c7..43c9f398 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.ramsey.ramsey_R2.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.ramsey.ramsey_R2.html @@ -663,7 +663,7 @@ for large recursions. Note that self-loop edges are ignored.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.steinertree.metric_closure.html b/reference/algorithms/generated/networkx.algorithms.approximation.steinertree.metric_closure.html index b5c4cd56..bae89542 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.steinertree.metric_closure.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.steinertree.metric_closure.html @@ -654,7 +654,7 @@ is weighted by the shortest path distance between the nodes in <em>G</em> .</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.steinertree.steiner_tree.html b/reference/algorithms/generated/networkx.algorithms.approximation.steinertree.steiner_tree.html index 761bbfcd..105ae1ac 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.steinertree.steiner_tree.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.steinertree.steiner_tree.html @@ -709,7 +709,7 @@ Information Processing Letters 27 (3): 125–28. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.asadpour_atsp.html b/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.asadpour_atsp.html index 0490cc2e..b3c8cd83 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.asadpour_atsp.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.asadpour_atsp.html @@ -709,7 +709,7 @@ pp. 1043–1061</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.christofides.html b/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.christofides.html index f6c1112b..a6f5f0dd 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.christofides.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.christofides.html @@ -672,7 +672,7 @@ Pittsburgh Pa Management Sciences Research Group, 1976.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.greedy_tsp.html b/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.greedy_tsp.html index 6768cf6c..a7d7b903 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.greedy_tsp.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.greedy_tsp.html @@ -701,7 +701,7 @@ as Simulated Annealing, or Threshold Accepting.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.simulated_annealing_tsp.html b/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.simulated_annealing_tsp.html index 45d9f9f2..b067416c 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.simulated_annealing_tsp.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.simulated_annealing_tsp.html @@ -767,7 +767,7 @@ outer loop, this algorithm has running time <span class="math notranslate nohigh <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.threshold_accepting_tsp.html b/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.threshold_accepting_tsp.html index a4ffafe6..e74b9a7c 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.threshold_accepting_tsp.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.threshold_accepting_tsp.html @@ -774,7 +774,7 @@ of times the outer and inner loop run respectively.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.traveling_salesman_problem.html b/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.traveling_salesman_problem.html index e1df5a18..d146d6ad 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.traveling_salesman_problem.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.traveling_salesman.traveling_salesman_problem.html @@ -726,7 +726,7 @@ complete version cannot be generated.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.treewidth.treewidth_min_degree.html b/reference/algorithms/generated/networkx.algorithms.approximation.treewidth.treewidth_min_degree.html index 6c81bf00..6c161e28 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.treewidth.treewidth_min_degree.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.treewidth.treewidth_min_degree.html @@ -656,7 +656,7 @@ degree is chosen, and so on.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.treewidth.treewidth_min_fill_in.html b/reference/algorithms/generated/networkx.algorithms.approximation.treewidth.treewidth_min_fill_in.html index 16d87719..88ec6bff 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.treewidth.treewidth_min_fill_in.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.treewidth.treewidth_min_fill_in.html @@ -655,7 +655,7 @@ small as possible.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.approximation.vertex_cover.min_weighted_vertex_cover.html b/reference/algorithms/generated/networkx.algorithms.approximation.vertex_cover.min_weighted_vertex_cover.html index 627fb934..97076622 100644 --- a/reference/algorithms/generated/networkx.algorithms.approximation.vertex_cover.min_weighted_vertex_cover.html +++ b/reference/algorithms/generated/networkx.algorithms.approximation.vertex_cover.min_weighted_vertex_cover.html @@ -688,7 +688,7 @@ approximating the weighted vertex cover problem.” <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.assortativity.attribute_assortativity_coefficient.html b/reference/algorithms/generated/networkx.algorithms.assortativity.attribute_assortativity_coefficient.html index fee59853..f500b1a7 100644 --- a/reference/algorithms/generated/networkx.algorithms.assortativity.attribute_assortativity_coefficient.html +++ b/reference/algorithms/generated/networkx.algorithms.assortativity.attribute_assortativity_coefficient.html @@ -680,7 +680,7 @@ Physical Review E, 67 026126, 2003</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.assortativity.attribute_mixing_dict.html b/reference/algorithms/generated/networkx.algorithms.assortativity.attribute_mixing_dict.html index 938e96ce..8c38f3c6 100644 --- a/reference/algorithms/generated/networkx.algorithms.assortativity.attribute_mixing_dict.html +++ b/reference/algorithms/generated/networkx.algorithms.assortativity.attribute_mixing_dict.html @@ -671,7 +671,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.assortativity.attribute_mixing_matrix.html b/reference/algorithms/generated/networkx.algorithms.assortativity.attribute_mixing_matrix.html index cd325469..655594f0 100644 --- a/reference/algorithms/generated/networkx.algorithms.assortativity.attribute_mixing_matrix.html +++ b/reference/algorithms/generated/networkx.algorithms.assortativity.attribute_mixing_matrix.html @@ -685,7 +685,7 @@ by inputting a <code class="xref py py-obj docutils literal notranslate"><span c <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.assortativity.average_degree_connectivity.html b/reference/algorithms/generated/networkx.algorithms.assortativity.average_degree_connectivity.html index ea10a611..d2bfde7f 100644 --- a/reference/algorithms/generated/networkx.algorithms.assortativity.average_degree_connectivity.html +++ b/reference/algorithms/generated/networkx.algorithms.assortativity.average_degree_connectivity.html @@ -704,7 +704,7 @@ PNAS 101 (11): 3747–3752 (2004).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.assortativity.average_neighbor_degree.html b/reference/algorithms/generated/networkx.algorithms.assortativity.average_neighbor_degree.html index 21194a3e..f6ea863c 100644 --- a/reference/algorithms/generated/networkx.algorithms.assortativity.average_neighbor_degree.html +++ b/reference/algorithms/generated/networkx.algorithms.assortativity.average_neighbor_degree.html @@ -729,7 +729,7 @@ PNAS 101 (11): 3747–3752 (2004).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.assortativity.degree_assortativity_coefficient.html b/reference/algorithms/generated/networkx.algorithms.assortativity.degree_assortativity_coefficient.html index 99a678c0..27c6869c 100644 --- a/reference/algorithms/generated/networkx.algorithms.assortativity.degree_assortativity_coefficient.html +++ b/reference/algorithms/generated/networkx.algorithms.assortativity.degree_assortativity_coefficient.html @@ -699,7 +699,7 @@ Edge direction and the structure of networks, PNAS 107, 10815-20 (2010).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.assortativity.degree_mixing_dict.html b/reference/algorithms/generated/networkx.algorithms.assortativity.degree_mixing_dict.html index 791a4a2e..e648ce96 100644 --- a/reference/algorithms/generated/networkx.algorithms.assortativity.degree_mixing_dict.html +++ b/reference/algorithms/generated/networkx.algorithms.assortativity.degree_mixing_dict.html @@ -663,7 +663,7 @@ The degree is the sum of the edge weights adjacent to the node.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.assortativity.degree_mixing_matrix.html b/reference/algorithms/generated/networkx.algorithms.assortativity.degree_mixing_matrix.html index b84e5e12..e7af3787 100644 --- a/reference/algorithms/generated/networkx.algorithms.assortativity.degree_mixing_matrix.html +++ b/reference/algorithms/generated/networkx.algorithms.assortativity.degree_mixing_matrix.html @@ -690,7 +690,7 @@ have that degree, use <code class="xref py py-obj docutils literal notranslate"> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.assortativity.degree_pearson_correlation_coefficient.html b/reference/algorithms/generated/networkx.algorithms.assortativity.degree_pearson_correlation_coefficient.html index 0c3eed1b..f078d735 100644 --- a/reference/algorithms/generated/networkx.algorithms.assortativity.degree_pearson_correlation_coefficient.html +++ b/reference/algorithms/generated/networkx.algorithms.assortativity.degree_pearson_correlation_coefficient.html @@ -689,7 +689,7 @@ Edge direction and the structure of networks, PNAS 107, 10815-20 (2010).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.assortativity.mixing_dict.html b/reference/algorithms/generated/networkx.algorithms.assortativity.mixing_dict.html index 7c20280e..161d9b79 100644 --- a/reference/algorithms/generated/networkx.algorithms.assortativity.mixing_dict.html +++ b/reference/algorithms/generated/networkx.algorithms.assortativity.mixing_dict.html @@ -657,7 +657,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.assortativity.node_attribute_xy.html b/reference/algorithms/generated/networkx.algorithms.assortativity.node_attribute_xy.html index ab997a45..16b42f04 100644 --- a/reference/algorithms/generated/networkx.algorithms.assortativity.node_attribute_xy.html +++ b/reference/algorithms/generated/networkx.algorithms.assortativity.node_attribute_xy.html @@ -670,7 +670,7 @@ which only appear once.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.assortativity.node_degree_xy.html b/reference/algorithms/generated/networkx.algorithms.assortativity.node_degree_xy.html index 14406322..f8612106 100644 --- a/reference/algorithms/generated/networkx.algorithms.assortativity.node_degree_xy.html +++ b/reference/algorithms/generated/networkx.algorithms.assortativity.node_degree_xy.html @@ -676,7 +676,7 @@ which only appear once.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.assortativity.numeric_assortativity_coefficient.html b/reference/algorithms/generated/networkx.algorithms.assortativity.numeric_assortativity_coefficient.html index 82a7ff38..9e09fe60 100644 --- a/reference/algorithms/generated/networkx.algorithms.assortativity.numeric_assortativity_coefficient.html +++ b/reference/algorithms/generated/networkx.algorithms.assortativity.numeric_assortativity_coefficient.html @@ -679,7 +679,7 @@ Physical Review E, 67 026126, 2003</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.asteroidal.find_asteroidal_triple.html b/reference/algorithms/generated/networkx.algorithms.asteroidal.find_asteroidal_triple.html index d713a096..8c51d6b8 100644 --- a/reference/algorithms/generated/networkx.algorithms.asteroidal.find_asteroidal_triple.html +++ b/reference/algorithms/generated/networkx.algorithms.asteroidal.find_asteroidal_triple.html @@ -684,7 +684,7 @@ Journal of Discrete Algorithms 2, pages 439-452, 2004. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.asteroidal.is_at_free.html b/reference/algorithms/generated/networkx.algorithms.asteroidal.is_at_free.html index 7ff12415..0b715e55 100644 --- a/reference/algorithms/generated/networkx.algorithms.asteroidal.is_at_free.html +++ b/reference/algorithms/generated/networkx.algorithms.asteroidal.is_at_free.html @@ -668,7 +668,7 @@ found the graph is not AT-free and False is returned.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.basic.color.html b/reference/algorithms/generated/networkx.algorithms.bipartite.basic.color.html index 20827091..d541dfb3 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.basic.color.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.basic.color.html @@ -675,7 +675,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.basic.degrees.html b/reference/algorithms/generated/networkx.algorithms.bipartite.basic.degrees.html index b7fd883a..7b136527 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.basic.degrees.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.basic.degrees.html @@ -679,7 +679,7 @@ for further details on how bipartite graphs are handled in NetworkX.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.basic.density.html b/reference/algorithms/generated/networkx.algorithms.bipartite.basic.density.html index b13cbe83..5af18520 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.basic.density.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.basic.density.html @@ -677,7 +677,7 @@ for further details on how bipartite graphs are handled in NetworkX.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.basic.is_bipartite.html b/reference/algorithms/generated/networkx.algorithms.bipartite.basic.is_bipartite.html index 94b632cd..00e439e9 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.basic.is_bipartite.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.basic.is_bipartite.html @@ -659,7 +659,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.basic.is_bipartite_node_set.html b/reference/algorithms/generated/networkx.algorithms.bipartite.basic.is_bipartite_node_set.html index 776bfc3a..0ea6ce37 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.basic.is_bipartite_node_set.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.basic.is_bipartite_node_set.html @@ -661,7 +661,7 @@ disconnected graphs.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.basic.sets.html b/reference/algorithms/generated/networkx.algorithms.bipartite.basic.sets.html index 98e72271..707ebaef 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.basic.sets.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.basic.sets.html @@ -689,7 +689,7 @@ possible if the input graph is disconnected.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.centrality.betweenness_centrality.html b/reference/algorithms/generated/networkx.algorithms.bipartite.centrality.betweenness_centrality.html index 3824395b..e8950ecb 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.centrality.betweenness_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.centrality.betweenness_centrality.html @@ -700,7 +700,7 @@ of Social Network Analysis. Sage Publications. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.centrality.closeness_centrality.html b/reference/algorithms/generated/networkx.algorithms.bipartite.centrality.closeness_centrality.html index cc93d84d..3d3b0083 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.centrality.closeness_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.centrality.closeness_centrality.html @@ -703,7 +703,7 @@ of Social Network Analysis. Sage Publications. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.centrality.degree_centrality.html b/reference/algorithms/generated/networkx.algorithms.bipartite.centrality.degree_centrality.html index 54e3f5c3..44e5ec21 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.centrality.degree_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.centrality.degree_centrality.html @@ -692,7 +692,7 @@ of Social Network Analysis. Sage Publications. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.cluster.average_clustering.html b/reference/algorithms/generated/networkx.algorithms.bipartite.cluster.average_clustering.html index df875d0a..c962e7c3 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.cluster.average_clustering.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.cluster.average_clustering.html @@ -703,7 +703,7 @@ Social Networks 30(1), 31–48.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.cluster.clustering.html b/reference/algorithms/generated/networkx.algorithms.bipartite.cluster.clustering.html index 8efdd2cc..7708f616 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.cluster.clustering.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.cluster.clustering.html @@ -705,7 +705,7 @@ Social Networks 30(1), 31–48.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.cluster.latapy_clustering.html b/reference/algorithms/generated/networkx.algorithms.bipartite.cluster.latapy_clustering.html index d18017b0..6feac48f 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.cluster.latapy_clustering.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.cluster.latapy_clustering.html @@ -705,7 +705,7 @@ Social Networks 30(1), 31–48.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.cluster.robins_alexander_clustering.html b/reference/algorithms/generated/networkx.algorithms.bipartite.cluster.robins_alexander_clustering.html index 1f3062ed..d5074e90 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.cluster.robins_alexander_clustering.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.cluster.robins_alexander_clustering.html @@ -682,7 +682,7 @@ Computational & Mathematical Organization Theory 10(1), 69–94.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.covering.min_edge_cover.html b/reference/algorithms/generated/networkx.algorithms.bipartite.covering.min_edge_cover.html index ca15c971..c890e174 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.covering.min_edge_cover.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.covering.min_edge_cover.html @@ -674,7 +674,7 @@ is bounded by the worst-case running time of the function <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.generate_edgelist.html b/reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.generate_edgelist.html index 5b8cf34d..526530a3 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.generate_edgelist.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.generate_edgelist.html @@ -688,7 +688,7 @@ values corresponding to the keys.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.parse_edgelist.html b/reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.parse_edgelist.html index 34f1a402..cedd1e3d 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.parse_edgelist.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.parse_edgelist.html @@ -696,7 +696,7 @@ key names and types for edge data.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.read_edgelist.html b/reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.read_edgelist.html index aa5dbb7b..e794b49d 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.read_edgelist.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.read_edgelist.html @@ -711,7 +711,7 @@ types (e.g. int, float, str, frozenset - or tuples of those, etc.)</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.write_edgelist.html b/reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.write_edgelist.html index 9dc11def..5ef8b66f 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.write_edgelist.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.edgelist.write_edgelist.html @@ -686,7 +686,7 @@ in the list.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.generators.alternating_havel_hakimi_graph.html b/reference/algorithms/generated/networkx.algorithms.bipartite.generators.alternating_havel_hakimi_graph.html index c48fe145..67f19210 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.generators.alternating_havel_hakimi_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.generators.alternating_havel_hakimi_graph.html @@ -667,7 +667,7 @@ To use it use nx.bipartite.alternating_havel_hakimi_graph</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.generators.complete_bipartite_graph.html b/reference/algorithms/generated/networkx.algorithms.bipartite.generators.complete_bipartite_graph.html index e5f5c3b6..627ed83f 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.generators.complete_bipartite_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.generators.complete_bipartite_graph.html @@ -661,7 +661,7 @@ To use it use nx.bipartite.complete_bipartite_graph</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.generators.configuration_model.html b/reference/algorithms/generated/networkx.algorithms.bipartite.generators.configuration_model.html index 2ca2fd30..de3e1d4e 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.generators.configuration_model.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.generators.configuration_model.html @@ -667,7 +667,7 @@ To use it use nx.bipartite.configuration_model</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.generators.gnmk_random_graph.html b/reference/algorithms/generated/networkx.algorithms.bipartite.generators.gnmk_random_graph.html index 236f4c66..e694aa12 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.generators.gnmk_random_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.generators.gnmk_random_graph.html @@ -676,7 +676,7 @@ G = bipartite.gnmk_random_graph(10,20,50)</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.generators.havel_hakimi_graph.html b/reference/algorithms/generated/networkx.algorithms.bipartite.generators.havel_hakimi_graph.html index 2e54cd17..e9338d23 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.generators.havel_hakimi_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.generators.havel_hakimi_graph.html @@ -666,7 +666,7 @@ To use it use nx.bipartite.havel_hakimi_graph</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.generators.preferential_attachment_graph.html b/reference/algorithms/generated/networkx.algorithms.bipartite.generators.preferential_attachment_graph.html index ff430c64..52c85c7c 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.generators.preferential_attachment_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.generators.preferential_attachment_graph.html @@ -680,7 +680,7 @@ Inf. Process. Lett. 90, 2004, pg. 215-221 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.generators.random_graph.html b/reference/algorithms/generated/networkx.algorithms.bipartite.generators.random_graph.html index 6f29cb74..660c40b1 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.generators.random_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.generators.random_graph.html @@ -683,7 +683,7 @@ Phys. Rev. E, 71, 036113, 2005.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.generators.reverse_havel_hakimi_graph.html b/reference/algorithms/generated/networkx.algorithms.bipartite.generators.reverse_havel_hakimi_graph.html index d4b0eb9b..deb992fb 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.generators.reverse_havel_hakimi_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.generators.reverse_havel_hakimi_graph.html @@ -666,7 +666,7 @@ To use it use nx.bipartite.reverse_havel_hakimi_graph</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.matching.eppstein_matching.html b/reference/algorithms/generated/networkx.algorithms.bipartite.matching.eppstein_matching.html index c2199f0f..01560a84 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.matching.eppstein_matching.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.matching.eppstein_matching.html @@ -681,7 +681,7 @@ for further details on how bipartite graphs are handled in NetworkX.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.matching.hopcroft_karp_matching.html b/reference/algorithms/generated/networkx.algorithms.bipartite.matching.hopcroft_karp_matching.html index dbf3e31c..95d2f9e7 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.matching.hopcroft_karp_matching.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.matching.hopcroft_karp_matching.html @@ -696,7 +696,7 @@ Maximum Matchings in Bipartite Graphs” In: <strong>SIAM Journal of Computing</ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.matching.maximum_matching.html b/reference/algorithms/generated/networkx.algorithms.bipartite.matching.maximum_matching.html index bd171c45..63ed4056 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.matching.maximum_matching.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.matching.maximum_matching.html @@ -640,7 +640,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.matching.minimum_weight_full_matching.html b/reference/algorithms/generated/networkx.algorithms.bipartite.matching.minimum_weight_full_matching.html index a2635d73..ab9705c2 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.matching.minimum_weight_full_matching.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.matching.minimum_weight_full_matching.html @@ -695,7 +695,7 @@ Networks, 10(2):143–152, 1980.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.matching.to_vertex_cover.html b/reference/algorithms/generated/networkx.algorithms.bipartite.matching.to_vertex_cover.html index 9e99dc71..bb726d2f 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.matching.to_vertex_cover.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.matching.to_vertex_cover.html @@ -690,7 +690,7 @@ for further details on how bipartite graphs are handled in NetworkX.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.matrix.biadjacency_matrix.html b/reference/algorithms/generated/networkx.algorithms.bipartite.matrix.biadjacency_matrix.html index 9cdaccd3..d7471a4e 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.matrix.biadjacency_matrix.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.matrix.biadjacency_matrix.html @@ -700,7 +700,7 @@ one to the transpose of the other.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.matrix.from_biadjacency_matrix.html b/reference/algorithms/generated/networkx.algorithms.bipartite.matrix.from_biadjacency_matrix.html index 8469a119..b835ac3c 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.matrix.from_biadjacency_matrix.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.matrix.from_biadjacency_matrix.html @@ -670,7 +670,7 @@ will be ignored.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.projection.collaboration_weighted_projected_graph.html b/reference/algorithms/generated/networkx.algorithms.bipartite.projection.collaboration_weighted_projected_graph.html index 1c24c0f3..cdfe723a 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.projection.collaboration_weighted_projected_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.projection.collaboration_weighted_projected_graph.html @@ -711,7 +711,7 @@ M. E. J. Newman, Phys. Rev. E 64, 016132 (2001).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.projection.generic_weighted_projected_graph.html b/reference/algorithms/generated/networkx.algorithms.bipartite.projection.generic_weighted_projected_graph.html index 3f61dde5..7f4c683f 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.projection.generic_weighted_projected_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.projection.generic_weighted_projected_graph.html @@ -726,7 +726,7 @@ for further details on how bipartite graphs are handled in NetworkX.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.projection.overlap_weighted_projected_graph.html b/reference/algorithms/generated/networkx.algorithms.bipartite.projection.overlap_weighted_projected_graph.html index 17739be1..fbbf42ee 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.projection.overlap_weighted_projected_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.projection.overlap_weighted_projected_graph.html @@ -711,7 +711,7 @@ of Social Network Analysis. Sage Publications.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.projection.projected_graph.html b/reference/algorithms/generated/networkx.algorithms.bipartite.projection.projected_graph.html index 24f331a3..28b875a5 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.projection.projected_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.projection.projected_graph.html @@ -705,7 +705,7 @@ building a multigraph results in two edges in the projection onto <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.projection.weighted_projected_graph.html b/reference/algorithms/generated/networkx.algorithms.bipartite.projection.weighted_projected_graph.html index b3b6b164..ffc0e8d7 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.projection.weighted_projected_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.projection.weighted_projected_graph.html @@ -708,7 +708,7 @@ of Social Network Analysis. Sage Publications.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.redundancy.node_redundancy.html b/reference/algorithms/generated/networkx.algorithms.bipartite.redundancy.node_redundancy.html index 07659728..597b3d59 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.redundancy.node_redundancy.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.redundancy.node_redundancy.html @@ -711,7 +711,7 @@ Social Networks 30(1), 31–48.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bipartite.spectral.spectral_bipartivity.html b/reference/algorithms/generated/networkx.algorithms.bipartite.spectral.spectral_bipartivity.html index dab40d28..496f4284 100644 --- a/reference/algorithms/generated/networkx.algorithms.bipartite.spectral.spectral_bipartivity.html +++ b/reference/algorithms/generated/networkx.algorithms.bipartite.spectral.spectral_bipartivity.html @@ -682,7 +682,7 @@ bipartivity in complex networks”, PhysRev E 72, 046105 (2005)</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.boundary.edge_boundary.html b/reference/algorithms/generated/networkx.algorithms.boundary.edge_boundary.html index c5ecf07c..f2fd86a5 100644 --- a/reference/algorithms/generated/networkx.algorithms.boundary.edge_boundary.html +++ b/reference/algorithms/generated/networkx.algorithms.boundary.edge_boundary.html @@ -682,7 +682,7 @@ the interest of speed and generality, that is not required here.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.boundary.node_boundary.html b/reference/algorithms/generated/networkx.algorithms.boundary.node_boundary.html index 406cb02f..3b1b8cbf 100644 --- a/reference/algorithms/generated/networkx.algorithms.boundary.node_boundary.html +++ b/reference/algorithms/generated/networkx.algorithms.boundary.node_boundary.html @@ -670,7 +670,7 @@ the interest of speed and generality, that is not required here.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bridges.bridges.html b/reference/algorithms/generated/networkx.algorithms.bridges.bridges.html index a87fd37c..3ef556d1 100644 --- a/reference/algorithms/generated/networkx.algorithms.bridges.bridges.html +++ b/reference/algorithms/generated/networkx.algorithms.bridges.bridges.html @@ -695,7 +695,7 @@ the number of edges.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bridges.has_bridges.html b/reference/algorithms/generated/networkx.algorithms.bridges.has_bridges.html index 551ae7a9..0e914bc7 100644 --- a/reference/algorithms/generated/networkx.algorithms.bridges.has_bridges.html +++ b/reference/algorithms/generated/networkx.algorithms.bridges.has_bridges.html @@ -685,7 +685,7 @@ graph and <span class="math notranslate nohighlight">\(m\)</span> is the number <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.bridges.local_bridges.html b/reference/algorithms/generated/networkx.algorithms.bridges.local_bridges.html index e379d3bb..11b5a149 100644 --- a/reference/algorithms/generated/networkx.algorithms.bridges.local_bridges.html +++ b/reference/algorithms/generated/networkx.algorithms.bridges.local_bridges.html @@ -676,7 +676,7 @@ as a 3-tuple <code class="xref py py-obj docutils literal notranslate"><span cla <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.approximate_current_flow_betweenness_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.approximate_current_flow_betweenness_centrality.html index 44cd3493..cddd2ae3 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.approximate_current_flow_betweenness_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.approximate_current_flow_betweenness_centrality.html @@ -700,7 +700,7 @@ LNCS 3404, pp. 533-544. Springer-Verlag, 2005. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.betweenness_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.betweenness_centrality.html index f7f292dc..fde1c9f4 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.betweenness_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.betweenness_centrality.html @@ -745,7 +745,7 @@ Sociometry 40: 35–41, 1977 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.betweenness_centrality_subset.html b/reference/algorithms/generated/networkx.algorithms.centrality.betweenness_centrality_subset.html index 0b901284..b02bf31d 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.betweenness_centrality_subset.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.betweenness_centrality_subset.html @@ -719,7 +719,7 @@ Social Networks 30(2):136-145, 2008. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.closeness_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.closeness_centrality.html index 52eb355a..c1a906fd 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.closeness_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.closeness_centrality.html @@ -725,7 +725,7 @@ Cambridge University Press.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.communicability_betweenness_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.communicability_betweenness_centrality.html index 79c74c1d..d882d159 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.communicability_betweenness_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.communicability_betweenness_centrality.html @@ -700,7 +700,7 @@ Physica A 388 (2009) 764-774. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.current_flow_betweenness_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.current_flow_betweenness_centrality.html index e660cede..a01a7643 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.current_flow_betweenness_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.current_flow_betweenness_centrality.html @@ -709,7 +709,7 @@ M. E. J. Newman, Social Networks 27, 39-54 (2005).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.current_flow_betweenness_centrality_subset.html b/reference/algorithms/generated/networkx.algorithms.centrality.current_flow_betweenness_centrality_subset.html index a15647b6..0b31a128 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.current_flow_betweenness_centrality_subset.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.current_flow_betweenness_centrality_subset.html @@ -713,7 +713,7 @@ M. E. J. Newman, Social Networks 27, 39-54 (2005).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.current_flow_closeness_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.current_flow_closeness_centrality.html index 8c850622..81ae2d2a 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.current_flow_closeness_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.current_flow_closeness_centrality.html @@ -695,7 +695,7 @@ Social Networks 11(1):1-37, 1989. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.degree_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.degree_centrality.html index 42b7b7ef..f0adb51f 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.degree_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.degree_centrality.html @@ -673,7 +673,7 @@ are possible.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.dispersion.html b/reference/algorithms/generated/networkx.algorithms.centrality.dispersion.html index 411e532e..604c393d 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.dispersion.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.dispersion.html @@ -687,7 +687,7 @@ Lars Backstrom, Jon Kleinberg. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.edge_betweenness_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.edge_betweenness_centrality.html index d6f766d2..e7d9c75b 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.edge_betweenness_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.edge_betweenness_centrality.html @@ -706,7 +706,7 @@ Social Networks 30(2):136-145, 2008. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.edge_betweenness_centrality_subset.html b/reference/algorithms/generated/networkx.algorithms.centrality.edge_betweenness_centrality_subset.html index c56b8813..6e3ed031 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.edge_betweenness_centrality_subset.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.edge_betweenness_centrality_subset.html @@ -705,7 +705,7 @@ Social Networks 30(2):136-145, 2008. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.edge_current_flow_betweenness_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.edge_current_flow_betweenness_centrality.html index 3b031c02..89159547 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.edge_current_flow_betweenness_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.edge_current_flow_betweenness_centrality.html @@ -716,7 +716,7 @@ M. E. J. Newman, Social Networks 27, 39-54 (2005).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.edge_current_flow_betweenness_centrality_subset.html b/reference/algorithms/generated/networkx.algorithms.centrality.edge_current_flow_betweenness_centrality_subset.html index 3f2e7871..25ced1bf 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.edge_current_flow_betweenness_centrality_subset.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.edge_current_flow_betweenness_centrality_subset.html @@ -713,7 +713,7 @@ M. E. J. Newman, Social Networks 27, 39-54 (2005).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.edge_load_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.edge_load_centrality.html index bdcb9192..5184d7ef 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.edge_load_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.edge_load_centrality.html @@ -661,7 +661,7 @@ This function is for demonstration and testing purposes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.eigenvector_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.eigenvector_centrality.html index e1ae68cb..a4efd8cd 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.eigenvector_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.eigenvector_centrality.html @@ -730,7 +730,7 @@ Oxford University Press, USA, 2010, pp. 169.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.eigenvector_centrality_numpy.html b/reference/algorithms/generated/networkx.algorithms.centrality.eigenvector_centrality_numpy.html index bc97b663..c82b0b26 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.eigenvector_centrality_numpy.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.eigenvector_centrality_numpy.html @@ -715,7 +715,7 @@ Oxford University Press, USA, 2010, pp. 169.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.estrada_index.html b/reference/algorithms/generated/networkx.algorithms.centrality.estrada_index.html index 644a9c77..2bf228b6 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.estrada_index.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.estrada_index.html @@ -690,7 +690,7 @@ Linear Algebra and its Applications. 427, 1 (2007). <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.global_reaching_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.global_reaching_centrality.html index 609228c7..98aec1a6 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.global_reaching_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.global_reaching_centrality.html @@ -694,7 +694,7 @@ weights.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.group_betweenness_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.group_betweenness_centrality.html index e40af544..f5b49f7b 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.group_betweenness_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.group_betweenness_centrality.html @@ -734,7 +734,7 @@ SIAM International Conference on Data Mining, SDM 2018, 126–134. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.group_closeness_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.group_closeness_centrality.html index bef2d861..bd7a8dbf 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.group_closeness_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.group_closeness_centrality.html @@ -711,7 +711,7 @@ WWWConference Proceedings, 2014. 689-694. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.group_degree_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.group_degree_centrality.html index 262c7fec..ce45fc80 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.group_degree_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.group_degree_centrality.html @@ -687,7 +687,7 @@ Journal of Mathematical Sociology. 23(3): 181-201. 1999. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.group_in_degree_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.group_in_degree_centrality.html index 652eb80c..d03adde9 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.group_in_degree_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.group_in_degree_centrality.html @@ -680,7 +680,7 @@ so for group in-degree centrality, the reverse graph is used.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.group_out_degree_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.group_out_degree_centrality.html index 4d4f0f4b..915811be 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.group_out_degree_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.group_out_degree_centrality.html @@ -680,7 +680,7 @@ so for group out-degree centrality, the graph itself is used.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.harmonic_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.harmonic_centrality.html index 10b0f953..b02b0818 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.harmonic_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.harmonic_centrality.html @@ -691,7 +691,7 @@ Internet Mathematics 10.3-4 (2014): 222-262.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.in_degree_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.in_degree_centrality.html index 2def886c..285551ee 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.in_degree_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.in_degree_centrality.html @@ -679,7 +679,7 @@ are possible.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.incremental_closeness_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.incremental_closeness_centrality.html index 8a45b2b2..0cd265ef 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.incremental_closeness_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.incremental_closeness_centrality.html @@ -723,7 +723,7 @@ Algorithms for Closeness Centrality. 2013 IEEE International Conference on Big D <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.information_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.information_centrality.html index e9c5744e..06ceb02e 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.information_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.information_centrality.html @@ -695,7 +695,7 @@ Social Networks 11(1):1-37, 1989. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.katz_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.katz_centrality.html index c8905cfc..34c14353 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.katz_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.katz_centrality.html @@ -755,7 +755,7 @@ Psychometrika 18(1):39–43, 1953 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.katz_centrality_numpy.html b/reference/algorithms/generated/networkx.algorithms.centrality.katz_centrality_numpy.html index 12c0efce..c227eace 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.katz_centrality_numpy.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.katz_centrality_numpy.html @@ -742,7 +742,7 @@ Psychometrika 18(1):39–43, 1953 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.load_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.load_centrality.html index 87255446..d8c66b49 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.load_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.load_centrality.html @@ -691,7 +691,7 @@ Physical Review Letters 87(27):1–4, 2001. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.local_reaching_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.local_reaching_centrality.html index c19c07f3..7f33cc1c 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.local_reaching_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.local_reaching_centrality.html @@ -698,7 +698,7 @@ weights.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.out_degree_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.out_degree_centrality.html index 4ab733ab..d8e24ead 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.out_degree_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.out_degree_centrality.html @@ -679,7 +679,7 @@ are possible.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.percolation_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.percolation_centrality.html index baf3ecf9..2b86f074 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.percolation_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.percolation_centrality.html @@ -706,7 +706,7 @@ Journal of Mathematical Sociology 25(2):163-177, 2001. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.prominent_group.html b/reference/algorithms/generated/networkx.algorithms.centrality.prominent_group.html index 4ead9099..20bc3c81 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.prominent_group.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.prominent_group.html @@ -740,7 +740,7 @@ SIAM International Conference on Data Mining, SDM 2018, 126–134. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.second_order_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.second_order_centrality.html index 3cada15d..04f9240f 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.second_order_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.second_order_centrality.html @@ -696,7 +696,7 @@ complex networks”, Elsevier Computer Communications 34(5):619-628, 2011.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.subgraph_centrality.html b/reference/algorithms/generated/networkx.algorithms.centrality.subgraph_centrality.html index 05d384a1..32c56168 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.subgraph_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.subgraph_centrality.html @@ -711,7 +711,7 @@ Physical Review E 71, 056103 (2005). <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.subgraph_centrality_exp.html b/reference/algorithms/generated/networkx.algorithms.centrality.subgraph_centrality_exp.html index ba0a5756..91154361 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.subgraph_centrality_exp.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.subgraph_centrality_exp.html @@ -708,7 +708,7 @@ Physical Review E 71, 056103 (2005). <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.trophic_differences.html b/reference/algorithms/generated/networkx.algorithms.centrality.trophic_differences.html index 2a75da33..6571fbd5 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.trophic_differences.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.trophic_differences.html @@ -667,7 +667,7 @@ Munoz (2014) PNAS “Trophic coherence determines food-web stability”</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.trophic_incoherence_parameter.html b/reference/algorithms/generated/networkx.algorithms.centrality.trophic_incoherence_parameter.html index fcce2444..0aae5f0f 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.trophic_incoherence_parameter.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.trophic_incoherence_parameter.html @@ -668,7 +668,7 @@ Munoz (2014) PNAS “Trophic coherence determines food-web stability”</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.trophic_levels.html b/reference/algorithms/generated/networkx.algorithms.centrality.trophic_levels.html index 9bf3bdf6..ada50367 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.trophic_levels.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.trophic_levels.html @@ -669,7 +669,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.centrality.voterank.html b/reference/algorithms/generated/networkx.algorithms.centrality.voterank.html index f272de9c..f1a599aa 100644 --- a/reference/algorithms/generated/networkx.algorithms.centrality.voterank.html +++ b/reference/algorithms/generated/networkx.algorithms.centrality.voterank.html @@ -686,7 +686,7 @@ However, the directed version is different in two ways: <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.chains.chain_decomposition.html b/reference/algorithms/generated/networkx.algorithms.chains.chain_decomposition.html index 1ccac40a..aebf9a8c 100644 --- a/reference/algorithms/generated/networkx.algorithms.chains.chain_decomposition.html +++ b/reference/algorithms/generated/networkx.algorithms.chains.chain_decomposition.html @@ -694,7 +694,7 @@ and 2-edge-connectivity.” <em>Information Processing Letters</em>, <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.chordal.chordal_graph_cliques.html b/reference/algorithms/generated/networkx.algorithms.chordal.chordal_graph_cliques.html index d8e07949..5e93d30b 100644 --- a/reference/algorithms/generated/networkx.algorithms.chordal.chordal_graph_cliques.html +++ b/reference/algorithms/generated/networkx.algorithms.chordal.chordal_graph_cliques.html @@ -685,7 +685,7 @@ graph is found to be non-chordal, a <code class="xref py py-exc docutils literal <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.chordal.chordal_graph_treewidth.html b/reference/algorithms/generated/networkx.algorithms.chordal.chordal_graph_treewidth.html index 8088c762..a4a02f31 100644 --- a/reference/algorithms/generated/networkx.algorithms.chordal.chordal_graph_treewidth.html +++ b/reference/algorithms/generated/networkx.algorithms.chordal.chordal_graph_treewidth.html @@ -688,7 +688,7 @@ graph is found to be non-chordal, a <code class="xref py py-exc docutils literal <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.chordal.complete_to_chordal_graph.html b/reference/algorithms/generated/networkx.algorithms.chordal.complete_to_chordal_graph.html index 2801cf69..e13e0fb0 100644 --- a/reference/algorithms/generated/networkx.algorithms.chordal.complete_to_chordal_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.chordal.complete_to_chordal_graph.html @@ -679,7 +679,7 @@ Graphs. Algorithmica. 39. 287-298. 10.1007/s00453-004-1084-3.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.chordal.find_induced_nodes.html b/reference/algorithms/generated/networkx.algorithms.chordal.find_induced_nodes.html index c8c82fc6..03311e47 100644 --- a/reference/algorithms/generated/networkx.algorithms.chordal.find_induced_nodes.html +++ b/reference/algorithms/generated/networkx.algorithms.chordal.find_induced_nodes.html @@ -693,7 +693,7 @@ Gal Elidan, Stephen Gould; JMLR, 9(Dec):2699–2731, 2008. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.chordal.is_chordal.html b/reference/algorithms/generated/networkx.algorithms.chordal.is_chordal.html index 2a0e4d59..e1b8b345 100644 --- a/reference/algorithms/generated/networkx.algorithms.chordal.is_chordal.html +++ b/reference/algorithms/generated/networkx.algorithms.chordal.is_chordal.html @@ -693,7 +693,7 @@ pp. 566–579.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.clique.cliques_containing_node.html b/reference/algorithms/generated/networkx.algorithms.clique.cliques_containing_node.html index e246b1b5..ef160907 100644 --- a/reference/algorithms/generated/networkx.algorithms.clique.cliques_containing_node.html +++ b/reference/algorithms/generated/networkx.algorithms.clique.cliques_containing_node.html @@ -641,7 +641,7 @@ Optional list of cliques can be input if already computed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.clique.enumerate_all_cliques.html b/reference/algorithms/generated/networkx.algorithms.clique.enumerate_all_cliques.html index 779d2d45..e865d72c 100644 --- a/reference/algorithms/generated/networkx.algorithms.clique.enumerate_all_cliques.html +++ b/reference/algorithms/generated/networkx.algorithms.clique.enumerate_all_cliques.html @@ -682,7 +682,7 @@ Conference, pp. 12, 12–18 Nov. 2005. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.clique.find_cliques.html b/reference/algorithms/generated/networkx.algorithms.clique.find_cliques.html index f434c0cd..31f82b8e 100644 --- a/reference/algorithms/generated/networkx.algorithms.clique.find_cliques.html +++ b/reference/algorithms/generated/networkx.algorithms.clique.find_cliques.html @@ -724,7 +724,7 @@ Volume 407, Issues 1–3, 6 November 2008, Pages 564–568, <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.clique.find_cliques_recursive.html b/reference/algorithms/generated/networkx.algorithms.clique.find_cliques_recursive.html index 5c19d40b..c1ec806a 100644 --- a/reference/algorithms/generated/networkx.algorithms.clique.find_cliques_recursive.html +++ b/reference/algorithms/generated/networkx.algorithms.clique.find_cliques_recursive.html @@ -722,7 +722,7 @@ Volume 407, Issues 1–3, 6 November 2008, Pages 564–568, <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.clique.graph_clique_number.html b/reference/algorithms/generated/networkx.algorithms.clique.graph_clique_number.html index 1edf4bcd..3aa97657 100644 --- a/reference/algorithms/generated/networkx.algorithms.clique.graph_clique_number.html +++ b/reference/algorithms/generated/networkx.algorithms.clique.graph_clique_number.html @@ -663,7 +663,7 @@ maximal cliques.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.clique.graph_number_of_cliques.html b/reference/algorithms/generated/networkx.algorithms.clique.graph_number_of_cliques.html index 15cbceb7..4bc31baa 100644 --- a/reference/algorithms/generated/networkx.algorithms.clique.graph_number_of_cliques.html +++ b/reference/algorithms/generated/networkx.algorithms.clique.graph_number_of_cliques.html @@ -661,7 +661,7 @@ maximal cliques.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.clique.make_clique_bipartite.html b/reference/algorithms/generated/networkx.algorithms.clique.make_clique_bipartite.html index 5d1f7a72..8f695183 100644 --- a/reference/algorithms/generated/networkx.algorithms.clique.make_clique_bipartite.html +++ b/reference/algorithms/generated/networkx.algorithms.clique.make_clique_bipartite.html @@ -669,7 +669,7 @@ convention for bipartite graphs in NetworkX.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.clique.make_max_clique_graph.html b/reference/algorithms/generated/networkx.algorithms.clique.make_max_clique_graph.html index d7ca4a0d..becc5234 100644 --- a/reference/algorithms/generated/networkx.algorithms.clique.make_max_clique_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.clique.make_max_clique_graph.html @@ -668,7 +668,7 @@ steps.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.clique.max_weight_clique.html b/reference/algorithms/generated/networkx.algorithms.clique.max_weight_clique.html index e9a7fdf5..46ebe6f2 100644 --- a/reference/algorithms/generated/networkx.algorithms.clique.max_weight_clique.html +++ b/reference/algorithms/generated/networkx.algorithms.clique.max_weight_clique.html @@ -689,7 +689,7 @@ Texas A&M University (2016).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.clique.node_clique_number.html b/reference/algorithms/generated/networkx.algorithms.clique.node_clique_number.html index 992e8f69..ac5d20fb 100644 --- a/reference/algorithms/generated/networkx.algorithms.clique.node_clique_number.html +++ b/reference/algorithms/generated/networkx.algorithms.clique.node_clique_number.html @@ -669,7 +669,7 @@ of the largest maximal clique containing that node.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.clique.number_of_cliques.html b/reference/algorithms/generated/networkx.algorithms.clique.number_of_cliques.html index 479f8946..d8f4d3d8 100644 --- a/reference/algorithms/generated/networkx.algorithms.clique.number_of_cliques.html +++ b/reference/algorithms/generated/networkx.algorithms.clique.number_of_cliques.html @@ -641,7 +641,7 @@ Optional list of cliques can be input if already computed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cluster.average_clustering.html b/reference/algorithms/generated/networkx.algorithms.cluster.average_clustering.html index f105b085..24e83d23 100644 --- a/reference/algorithms/generated/networkx.algorithms.cluster.average_clustering.html +++ b/reference/algorithms/generated/networkx.algorithms.cluster.average_clustering.html @@ -690,7 +690,7 @@ nodes and leafs on clustering measures for small-world networks. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cluster.clustering.html b/reference/algorithms/generated/networkx.algorithms.cluster.clustering.html index c5e8d98d..d6f1bf81 100644 --- a/reference/algorithms/generated/networkx.algorithms.cluster.clustering.html +++ b/reference/algorithms/generated/networkx.algorithms.cluster.clustering.html @@ -720,7 +720,7 @@ Physical Review E, 76(2), 026107 (2007).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cluster.generalized_degree.html b/reference/algorithms/generated/networkx.algorithms.cluster.generalized_degree.html index 0eeee28b..acc65014 100644 --- a/reference/algorithms/generated/networkx.algorithms.cluster.generalized_degree.html +++ b/reference/algorithms/generated/networkx.algorithms.cluster.generalized_degree.html @@ -695,7 +695,7 @@ Volume 97, Number 2 (2012). <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cluster.square_clustering.html b/reference/algorithms/generated/networkx.algorithms.cluster.square_clustering.html index caff2b02..626242e9 100644 --- a/reference/algorithms/generated/networkx.algorithms.cluster.square_clustering.html +++ b/reference/algorithms/generated/networkx.algorithms.cluster.square_clustering.html @@ -695,7 +695,7 @@ Bipartite Networks. Physica A: Statistical Mechanics and its Applications 387.27 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cluster.transitivity.html b/reference/algorithms/generated/networkx.algorithms.cluster.transitivity.html index c53baaa9..ee631069 100644 --- a/reference/algorithms/generated/networkx.algorithms.cluster.transitivity.html +++ b/reference/algorithms/generated/networkx.algorithms.cluster.transitivity.html @@ -665,7 +665,7 @@ present in G.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cluster.triangles.html b/reference/algorithms/generated/networkx.algorithms.cluster.triangles.html index ed70ad1c..57486dc3 100644 --- a/reference/algorithms/generated/networkx.algorithms.cluster.triangles.html +++ b/reference/algorithms/generated/networkx.algorithms.cluster.triangles.html @@ -669,7 +669,7 @@ three times, once at each node. Self loops are ignored.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.coloring.equitable_color.html b/reference/algorithms/generated/networkx.algorithms.coloring.equitable_color.html index 877f97e0..1b05f560 100644 --- a/reference/algorithms/generated/networkx.algorithms.coloring.equitable_color.html +++ b/reference/algorithms/generated/networkx.algorithms.coloring.equitable_color.html @@ -683,7 +683,7 @@ in the graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.coloring.greedy_color.html b/reference/algorithms/generated/networkx.algorithms.coloring.greedy_color.html index f81dafb9..71b9aab1 100644 --- a/reference/algorithms/generated/networkx.algorithms.coloring.greedy_color.html +++ b/reference/algorithms/generated/networkx.algorithms.coloring.greedy_color.html @@ -722,7 +722,7 @@ ISBN 0-486-45353-7.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.coloring.strategy_connected_sequential.html b/reference/algorithms/generated/networkx.algorithms.coloring.strategy_connected_sequential.html index 9d2976a8..fac77de3 100644 --- a/reference/algorithms/generated/networkx.algorithms.coloring.strategy_connected_sequential.html +++ b/reference/algorithms/generated/networkx.algorithms.coloring.strategy_connected_sequential.html @@ -646,7 +646,7 @@ the first, at least one neighbor appeared earlier in the sequence.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.coloring.strategy_connected_sequential_bfs.html b/reference/algorithms/generated/networkx.algorithms.coloring.strategy_connected_sequential_bfs.html index 399e6ae6..183c1b63 100644 --- a/reference/algorithms/generated/networkx.algorithms.coloring.strategy_connected_sequential_bfs.html +++ b/reference/algorithms/generated/networkx.algorithms.coloring.strategy_connected_sequential_bfs.html @@ -643,7 +643,7 @@ the first, at least one neighbor appeared earlier in the sequence.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.coloring.strategy_connected_sequential_dfs.html b/reference/algorithms/generated/networkx.algorithms.coloring.strategy_connected_sequential_dfs.html index c9fb98d5..0cf2a493 100644 --- a/reference/algorithms/generated/networkx.algorithms.coloring.strategy_connected_sequential_dfs.html +++ b/reference/algorithms/generated/networkx.algorithms.coloring.strategy_connected_sequential_dfs.html @@ -643,7 +643,7 @@ the first, at least one neighbor appeared earlier in the sequence.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.coloring.strategy_independent_set.html b/reference/algorithms/generated/networkx.algorithms.coloring.strategy_independent_set.html index 238085dd..a279a81d 100644 --- a/reference/algorithms/generated/networkx.algorithms.coloring.strategy_independent_set.html +++ b/reference/algorithms/generated/networkx.algorithms.coloring.strategy_independent_set.html @@ -648,7 +648,7 @@ instead of a maximal independent set.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.coloring.strategy_largest_first.html b/reference/algorithms/generated/networkx.algorithms.coloring.strategy_largest_first.html index c8a628fc..8b24f7a9 100644 --- a/reference/algorithms/generated/networkx.algorithms.coloring.strategy_largest_first.html +++ b/reference/algorithms/generated/networkx.algorithms.coloring.strategy_largest_first.html @@ -641,7 +641,7 @@ degree.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.coloring.strategy_random_sequential.html b/reference/algorithms/generated/networkx.algorithms.coloring.strategy_random_sequential.html index 062a18d5..da9a3da4 100644 --- a/reference/algorithms/generated/networkx.algorithms.coloring.strategy_random_sequential.html +++ b/reference/algorithms/generated/networkx.algorithms.coloring.strategy_random_sequential.html @@ -645,7 +645,7 @@ See <a class="reference internal" href="../../randomness.html#randomness"><span <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.coloring.strategy_saturation_largest_first.html b/reference/algorithms/generated/networkx.algorithms.coloring.strategy_saturation_largest_first.html index 8d1b5715..e5a2a0e3 100644 --- a/reference/algorithms/generated/networkx.algorithms.coloring.strategy_saturation_largest_first.html +++ b/reference/algorithms/generated/networkx.algorithms.coloring.strategy_saturation_largest_first.html @@ -642,7 +642,7 @@ known as “DSATUR”).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.coloring.strategy_smallest_last.html b/reference/algorithms/generated/networkx.algorithms.coloring.strategy_smallest_last.html index 3d47a031..2d362544 100644 --- a/reference/algorithms/generated/networkx.algorithms.coloring.strategy_smallest_last.html +++ b/reference/algorithms/generated/networkx.algorithms.coloring.strategy_smallest_last.html @@ -651,7 +651,7 @@ maximal independent set.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.communicability_alg.communicability.html b/reference/algorithms/generated/networkx.algorithms.communicability_alg.communicability.html index 2503a63c..26ca7df4 100644 --- a/reference/algorithms/generated/networkx.algorithms.communicability_alg.communicability.html +++ b/reference/algorithms/generated/networkx.algorithms.communicability_alg.communicability.html @@ -697,7 +697,7 @@ Phys. Rev. E 77, 036111 (2008). <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.communicability_alg.communicability_exp.html b/reference/algorithms/generated/networkx.algorithms.communicability_alg.communicability_exp.html index 0051b785..4369d963 100644 --- a/reference/algorithms/generated/networkx.algorithms.communicability_alg.communicability_exp.html +++ b/reference/algorithms/generated/networkx.algorithms.communicability_alg.communicability_exp.html @@ -694,7 +694,7 @@ Phys. Rev. E 77, 036111 (2008). <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.community.asyn_fluid.asyn_fluidc.html b/reference/algorithms/generated/networkx.algorithms.community.asyn_fluid.asyn_fluidc.html index d5bb3a46..85d51674 100644 --- a/reference/algorithms/generated/networkx.algorithms.community.asyn_fluid.asyn_fluidc.html +++ b/reference/algorithms/generated/networkx.algorithms.community.asyn_fluid.asyn_fluidc.html @@ -688,7 +688,7 @@ Competitive and Highly Scalable Community Detection Algorithm”. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.community.centrality.girvan_newman.html b/reference/algorithms/generated/networkx.algorithms.community.centrality.girvan_newman.html index 761d3cb3..77e6e54e 100644 --- a/reference/algorithms/generated/networkx.algorithms.community.centrality.girvan_newman.html +++ b/reference/algorithms/generated/networkx.algorithms.community.centrality.girvan_newman.html @@ -748,7 +748,7 @@ highest betweenness centrality:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.community.community_utils.is_partition.html b/reference/algorithms/generated/networkx.algorithms.community.community_utils.is_partition.html index 8b1822e3..05c2f3bd 100644 --- a/reference/algorithms/generated/networkx.algorithms.community.community_utils.is_partition.html +++ b/reference/algorithms/generated/networkx.algorithms.community.community_utils.is_partition.html @@ -651,7 +651,7 @@ If it is an iterator it is exhausted.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.community.kclique.k_clique_communities.html b/reference/algorithms/generated/networkx.algorithms.community.kclique.k_clique_communities.html index b4f5e2d8..1eeeea37 100644 --- a/reference/algorithms/generated/networkx.algorithms.community.kclique.k_clique_communities.html +++ b/reference/algorithms/generated/networkx.algorithms.community.kclique.k_clique_communities.html @@ -679,7 +679,7 @@ doi:10.1038/nature03607</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.community.kernighan_lin.kernighan_lin_bisection.html b/reference/algorithms/generated/networkx.algorithms.community.kernighan_lin.kernighan_lin_bisection.html index 620dd2ae..9717d7d7 100644 --- a/reference/algorithms/generated/networkx.algorithms.community.kernighan_lin.kernighan_lin_bisection.html +++ b/reference/algorithms/generated/networkx.algorithms.community.kernighan_lin.kernighan_lin_bisection.html @@ -687,7 +687,7 @@ Oxford University Press 2011.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.community.label_propagation.asyn_lpa_communities.html b/reference/algorithms/generated/networkx.algorithms.community.label_propagation.asyn_lpa_communities.html index f9b038ea..fd51d970 100644 --- a/reference/algorithms/generated/networkx.algorithms.community.label_propagation.asyn_lpa_communities.html +++ b/reference/algorithms/generated/networkx.algorithms.community.label_propagation.asyn_lpa_communities.html @@ -686,7 +686,7 @@ networks.” Physical Review E 76.3 (2007): 036106.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.community.label_propagation.label_propagation_communities.html b/reference/algorithms/generated/networkx.algorithms.community.label_propagation.label_propagation_communities.html index c2839162..ea1720af 100644 --- a/reference/algorithms/generated/networkx.algorithms.community.label_propagation.label_propagation_communities.html +++ b/reference/algorithms/generated/networkx.algorithms.community.label_propagation.label_propagation_communities.html @@ -672,7 +672,7 @@ Workshop on (pp. 1-8). IEEE.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.community.louvain.louvain_communities.html b/reference/algorithms/generated/networkx.algorithms.community.louvain.louvain_communities.html index f1214706..6a500a9e 100644 --- a/reference/algorithms/generated/networkx.algorithms.community.louvain.louvain_communities.html +++ b/reference/algorithms/generated/networkx.algorithms.community.louvain.louvain_communities.html @@ -733,7 +733,7 @@ well-connected communities. Sci Rep 9, 5233 (2019). <a class="reference external <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.community.louvain.louvain_partitions.html b/reference/algorithms/generated/networkx.algorithms.community.louvain.louvain_partitions.html index 25b3fc65..7caad751 100644 --- a/reference/algorithms/generated/networkx.algorithms.community.louvain.louvain_partitions.html +++ b/reference/algorithms/generated/networkx.algorithms.community.louvain.louvain_partitions.html @@ -689,7 +689,7 @@ large networks. J. Stat. Mech 10008, 1-12(2008)</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.community.lukes.lukes_partitioning.html b/reference/algorithms/generated/networkx.algorithms.community.lukes.lukes_partitioning.html index 49943011..7ae30f07 100644 --- a/reference/algorithms/generated/networkx.algorithms.community.lukes.lukes_partitioning.html +++ b/reference/algorithms/generated/networkx.algorithms.community.lukes.lukes_partitioning.html @@ -676,7 +676,7 @@ partition.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.community.modularity_max.greedy_modularity_communities.html b/reference/algorithms/generated/networkx.algorithms.community.modularity_max.greedy_modularity_communities.html index 92c1bcb2..bea0857b 100644 --- a/reference/algorithms/generated/networkx.algorithms.community.modularity_max.greedy_modularity_communities.html +++ b/reference/algorithms/generated/networkx.algorithms.community.modularity_max.greedy_modularity_communities.html @@ -729,7 +729,7 @@ Physical Review E 70(5 Pt 2):056131, 2004.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.community.modularity_max.naive_greedy_modularity_communities.html b/reference/algorithms/generated/networkx.algorithms.community.modularity_max.naive_greedy_modularity_communities.html index c37d39e4..15160ee6 100644 --- a/reference/algorithms/generated/networkx.algorithms.community.modularity_max.naive_greedy_modularity_communities.html +++ b/reference/algorithms/generated/networkx.algorithms.community.modularity_max.naive_greedy_modularity_communities.html @@ -685,7 +685,7 @@ Sorted by length with largest communities first.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.community.quality.modularity.html b/reference/algorithms/generated/networkx.algorithms.community.quality.modularity.html index a06d3f1c..09a0c64d 100644 --- a/reference/algorithms/generated/networkx.algorithms.community.quality.modularity.html +++ b/reference/algorithms/generated/networkx.algorithms.community.quality.modularity.html @@ -724,7 +724,7 @@ Phys. Rev. E 94, 052315, 2016. <a class="reference external" href="https://doi.o <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.community.quality.partition_quality.html b/reference/algorithms/generated/networkx.algorithms.community.quality.partition_quality.html index d34eb5c3..0f524e78 100644 --- a/reference/algorithms/generated/networkx.algorithms.community.quality.partition_quality.html +++ b/reference/algorithms/generated/networkx.algorithms.community.quality.partition_quality.html @@ -687,7 +687,7 @@ community.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.articulation_points.html b/reference/algorithms/generated/networkx.algorithms.components.articulation_points.html index c625bb8c..ba80f315 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.articulation_points.html +++ b/reference/algorithms/generated/networkx.algorithms.components.articulation_points.html @@ -706,7 +706,7 @@ Communications of the ACM 16: 372–378. doi:10.1145/362248.362272</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.attracting_components.html b/reference/algorithms/generated/networkx.algorithms.components.attracting_components.html index fe9b1096..17979505 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.attracting_components.html +++ b/reference/algorithms/generated/networkx.algorithms.components.attracting_components.html @@ -674,7 +674,7 @@ the node will be visited infinitely often.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.biconnected_component_edges.html b/reference/algorithms/generated/networkx.algorithms.components.biconnected_component_edges.html index d7b68ccb..fe340165 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.biconnected_component_edges.html +++ b/reference/algorithms/generated/networkx.algorithms.components.biconnected_component_edges.html @@ -709,7 +709,7 @@ Communications of the ACM 16: 372–378. doi:10.1145/362248.362272</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.biconnected_components.html b/reference/algorithms/generated/networkx.algorithms.components.biconnected_components.html index d1a27791..680bebd7 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.biconnected_components.html +++ b/reference/algorithms/generated/networkx.algorithms.components.biconnected_components.html @@ -728,7 +728,7 @@ efficient to use max instead of sort.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.condensation.html b/reference/algorithms/generated/networkx.algorithms.components.condensation.html index fb5c4dc4..3fb50cbe 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.condensation.html +++ b/reference/algorithms/generated/networkx.algorithms.components.condensation.html @@ -696,7 +696,7 @@ using the barbell graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.connected_components.html b/reference/algorithms/generated/networkx.algorithms.components.connected_components.html index 1591c12a..6e762667 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.connected_components.html +++ b/reference/algorithms/generated/networkx.algorithms.components.connected_components.html @@ -685,7 +685,7 @@ efficient to use max instead of sort.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.is_attracting_component.html b/reference/algorithms/generated/networkx.algorithms.components.is_attracting_component.html index 6d705687..046ab1a5 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.is_attracting_component.html +++ b/reference/algorithms/generated/networkx.algorithms.components.is_attracting_component.html @@ -666,7 +666,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.is_biconnected.html b/reference/algorithms/generated/networkx.algorithms.components.is_biconnected.html index 392cee5b..01019b97 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.is_biconnected.html +++ b/reference/algorithms/generated/networkx.algorithms.components.is_biconnected.html @@ -705,7 +705,7 @@ Communications of the ACM 16: 372–378. doi:10.1145/362248.362272</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.is_connected.html b/reference/algorithms/generated/networkx.algorithms.components.is_connected.html index eef420e0..d4616e97 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.is_connected.html +++ b/reference/algorithms/generated/networkx.algorithms.components.is_connected.html @@ -677,7 +677,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.is_semiconnected.html b/reference/algorithms/generated/networkx.algorithms.components.is_semiconnected.html index da1ff627..e8bcb75c 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.is_semiconnected.html +++ b/reference/algorithms/generated/networkx.algorithms.components.is_semiconnected.html @@ -683,7 +683,7 @@ is reachable from the other, or they are mutually reachable.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.is_strongly_connected.html b/reference/algorithms/generated/networkx.algorithms.components.is_strongly_connected.html index d78ca99f..855789e9 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.is_strongly_connected.html +++ b/reference/algorithms/generated/networkx.algorithms.components.is_strongly_connected.html @@ -682,7 +682,7 @@ the graph is reachable from every other vertex.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.is_weakly_connected.html b/reference/algorithms/generated/networkx.algorithms.components.is_weakly_connected.html index 393635b4..ae062793 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.is_weakly_connected.html +++ b/reference/algorithms/generated/networkx.algorithms.components.is_weakly_connected.html @@ -686,7 +686,7 @@ connected as well.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.kosaraju_strongly_connected_components.html b/reference/algorithms/generated/networkx.algorithms.components.kosaraju_strongly_connected_components.html index 823afe18..8b152f3f 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.kosaraju_strongly_connected_components.html +++ b/reference/algorithms/generated/networkx.algorithms.components.kosaraju_strongly_connected_components.html @@ -686,7 +686,7 @@ use max instead of sort.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.node_connected_component.html b/reference/algorithms/generated/networkx.algorithms.components.node_connected_component.html index 51f569f4..e01f0c63 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.node_connected_component.html +++ b/reference/algorithms/generated/networkx.algorithms.components.node_connected_component.html @@ -675,7 +675,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.number_attracting_components.html b/reference/algorithms/generated/networkx.algorithms.components.number_attracting_components.html index 1221d334..9187b0c6 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.number_attracting_components.html +++ b/reference/algorithms/generated/networkx.algorithms.components.number_attracting_components.html @@ -666,7 +666,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.number_connected_components.html b/reference/algorithms/generated/networkx.algorithms.components.number_connected_components.html index 641acf09..5dfef77c 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.number_connected_components.html +++ b/reference/algorithms/generated/networkx.algorithms.components.number_connected_components.html @@ -669,7 +669,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.number_strongly_connected_components.html b/reference/algorithms/generated/networkx.algorithms.components.number_strongly_connected_components.html index 1f950dfe..f47b4b50 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.number_strongly_connected_components.html +++ b/reference/algorithms/generated/networkx.algorithms.components.number_strongly_connected_components.html @@ -675,7 +675,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.number_weakly_connected_components.html b/reference/algorithms/generated/networkx.algorithms.components.number_weakly_connected_components.html index e7807fd2..f9633e65 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.number_weakly_connected_components.html +++ b/reference/algorithms/generated/networkx.algorithms.components.number_weakly_connected_components.html @@ -675,7 +675,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.strongly_connected_components.html b/reference/algorithms/generated/networkx.algorithms.components.strongly_connected_components.html index 970ac9e5..74fd47b3 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.strongly_connected_components.html +++ b/reference/algorithms/generated/networkx.algorithms.components.strongly_connected_components.html @@ -701,7 +701,7 @@ use max instead of sort.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.strongly_connected_components_recursive.html b/reference/algorithms/generated/networkx.algorithms.components.strongly_connected_components_recursive.html index 27b56ef8..7cd4e2e9 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.strongly_connected_components_recursive.html +++ b/reference/algorithms/generated/networkx.algorithms.components.strongly_connected_components_recursive.html @@ -703,7 +703,7 @@ use max instead of sort.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.components.weakly_connected_components.html b/reference/algorithms/generated/networkx.algorithms.components.weakly_connected_components.html index 8581f645..c54bccdf 100644 --- a/reference/algorithms/generated/networkx.algorithms.components.weakly_connected_components.html +++ b/reference/algorithms/generated/networkx.algorithms.components.weakly_connected_components.html @@ -685,7 +685,7 @@ use max instead of sort:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.all_pairs_node_connectivity.html b/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.all_pairs_node_connectivity.html index e1b7c2fa..5ce21f40 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.all_pairs_node_connectivity.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.all_pairs_node_connectivity.html @@ -678,7 +678,7 @@ in G, or in nbunch if provided.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.average_node_connectivity.html b/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.average_node_connectivity.html index d41a3795..7314f76b 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.average_node_connectivity.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.average_node_connectivity.html @@ -688,7 +688,7 @@ connectivity of a graph. Discrete mathematics 252(1-3), 31-45. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.edge_connectivity.html b/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.edge_connectivity.html index ce4cd191..22c793e0 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.edge_connectivity.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.edge_connectivity.html @@ -737,7 +737,7 @@ the data structures used in the maximum flow computations. See <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.local_edge_connectivity.html b/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.local_edge_connectivity.html index 8a15f074..e6b1a4bb 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.local_edge_connectivity.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.local_edge_connectivity.html @@ -768,7 +768,7 @@ functions have to be explicitly imported from the flow package.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.local_node_connectivity.html b/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.local_node_connectivity.html index d6a6bb3c..96c07ae3 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.local_node_connectivity.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.local_node_connectivity.html @@ -779,7 +779,7 @@ functions have to be explicitly imported from the flow package.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.node_connectivity.html b/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.node_connectivity.html index ec0b4e3e..cfb2031b 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.node_connectivity.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.connectivity.node_connectivity.html @@ -728,7 +728,7 @@ the data structures used in the maximum flow computations. See <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_edge_cut.html b/reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_edge_cut.html index 1c6a726a..b51da2fb 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_edge_cut.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_edge_cut.html @@ -733,7 +733,7 @@ the data structures used in the maximum flow computations. See <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_node_cut.html b/reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_node_cut.html index 227b7ad8..8be28629 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_node_cut.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_node_cut.html @@ -730,7 +730,7 @@ the data structures used in the maximum flow computations. See <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_st_edge_cut.html b/reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_st_edge_cut.html index c74252c8..9438661c 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_st_edge_cut.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_st_edge_cut.html @@ -744,7 +744,7 @@ functions have to be explicitly imported from the flow package.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_st_node_cut.html b/reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_st_node_cut.html index 6e462663..955193e0 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_st_node_cut.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.cuts.minimum_st_node_cut.html @@ -752,7 +752,7 @@ functions have to be explicitly imported from the flow package.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.disjoint_paths.edge_disjoint_paths.html b/reference/algorithms/generated/networkx.algorithms.connectivity.disjoint_paths.edge_disjoint_paths.html index 9724a283..880c3a23 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.disjoint_paths.edge_disjoint_paths.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.disjoint_paths.edge_disjoint_paths.html @@ -756,7 +756,7 @@ functions have to be explicitly imported from the flow package.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.disjoint_paths.node_disjoint_paths.html b/reference/algorithms/generated/networkx.algorithms.connectivity.disjoint_paths.node_disjoint_paths.html index d3f25c81..42061586 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.disjoint_paths.node_disjoint_paths.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.disjoint_paths.node_disjoint_paths.html @@ -750,7 +750,7 @@ functions have to be explicitly imported from the flow package.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.is_k_edge_connected.html b/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.is_k_edge_connected.html index 2b41ee89..6d785bde 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.is_k_edge_connected.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.is_k_edge_connected.html @@ -671,7 +671,7 @@ If so, then G is k-edge-connected.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.is_locally_k_edge_connected.html b/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.is_locally_k_edge_connected.html index 356e9522..00af796a 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.is_locally_k_edge_connected.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.is_locally_k_edge_connected.html @@ -678,7 +678,7 @@ If so, then s and t are locally k-edge-connected in G.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation.html b/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation.html index 82f037cc..44d0c19c 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation.html @@ -740,7 +740,7 @@ solution weight.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.html b/reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.html index d900e69f..3b3b2b63 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.html @@ -737,7 +737,7 @@ search space.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.bridge_components.html b/reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.bridge_components.html index 14d8b73f..a60ab2d7 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.bridge_components.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.bridge_components.html @@ -676,7 +676,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.k_edge_components.html b/reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.k_edge_components.html index ef9a5c9d..5bf311b3 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.k_edge_components.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.k_edge_components.html @@ -707,7 +707,7 @@ k-edge-connected components. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.k_edge_subgraphs.html b/reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.k_edge_subgraphs.html index 7925acca..66a214c9 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.k_edge_subgraphs.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.edge_kcomponents.k_edge_subgraphs.html @@ -700,7 +700,7 @@ Technology 2012 480-–491. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.kcomponents.k_components.html b/reference/algorithms/generated/networkx.algorithms.connectivity.kcomponents.k_components.html index f4723123..8359795e 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.kcomponents.k_components.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.kcomponents.k_components.html @@ -730,7 +730,7 @@ Visualization and Heuristics for Fast Computation. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.kcutsets.all_node_cuts.html b/reference/algorithms/generated/networkx.algorithms.connectivity.kcutsets.all_node_cuts.html index 15a5ab66..2af5e42b 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.kcutsets.all_node_cuts.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.kcutsets.all_node_cuts.html @@ -705,7 +705,7 @@ sets in a graph. Networks 23(6), 533–541. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.stoerwagner.stoer_wagner.html b/reference/algorithms/generated/networkx.algorithms.connectivity.stoerwagner.stoer_wagner.html index 8909bfb3..4f7148dc 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.stoerwagner.stoer_wagner.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.stoerwagner.stoer_wagner.html @@ -716,7 +716,7 @@ negative-weighted edge.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.utils.build_auxiliary_edge_connectivity.html b/reference/algorithms/generated/networkx.algorithms.connectivity.utils.build_auxiliary_edge_connectivity.html index 42bd188c..1d7299b8 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.utils.build_auxiliary_edge_connectivity.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.utils.build_auxiliary_edge_connectivity.html @@ -652,7 +652,7 @@ chapter, look for the reference of the book). <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.connectivity.utils.build_auxiliary_node_connectivity.html b/reference/algorithms/generated/networkx.algorithms.connectivity.utils.build_auxiliary_node_connectivity.html index 7d7e8b2e..14380c74 100644 --- a/reference/algorithms/generated/networkx.algorithms.connectivity.utils.build_auxiliary_node_connectivity.html +++ b/reference/algorithms/generated/networkx.algorithms.connectivity.utils.build_auxiliary_node_connectivity.html @@ -664,7 +664,7 @@ Notes in Computer Science, Volume 3418, Springer-Verlag, 2005. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.core.core_number.html b/reference/algorithms/generated/networkx.algorithms.core.core_number.html index 681a7153..b0de29f8 100644 --- a/reference/algorithms/generated/networkx.algorithms.core.core_number.html +++ b/reference/algorithms/generated/networkx.algorithms.core.core_number.html @@ -676,7 +676,7 @@ Vladimir Batagelj and Matjaz Zaversnik, 2003. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.core.k_core.html b/reference/algorithms/generated/networkx.algorithms.core.k_core.html index eeac9b7f..c0b16c33 100644 --- a/reference/algorithms/generated/networkx.algorithms.core.k_core.html +++ b/reference/algorithms/generated/networkx.algorithms.core.k_core.html @@ -685,7 +685,7 @@ Vladimir Batagelj and Matjaz Zaversnik, 2003. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.core.k_corona.html b/reference/algorithms/generated/networkx.algorithms.core.k_corona.html index c7850aa8..f691af62 100644 --- a/reference/algorithms/generated/networkx.algorithms.core.k_corona.html +++ b/reference/algorithms/generated/networkx.algorithms.core.k_corona.html @@ -688,7 +688,7 @@ Phys. Rev. E 73, 056101 (2006) <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.core.k_crust.html b/reference/algorithms/generated/networkx.algorithms.core.k_crust.html index 9254d19e..d3bb689f 100644 --- a/reference/algorithms/generated/networkx.algorithms.core.k_crust.html +++ b/reference/algorithms/generated/networkx.algorithms.core.k_crust.html @@ -690,7 +690,7 @@ and Eran Shir, PNAS July 3, 2007 vol. 104 no. 27 11150-11154 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.core.k_shell.html b/reference/algorithms/generated/networkx.algorithms.core.k_shell.html index c4590e87..e2a185e8 100644 --- a/reference/algorithms/generated/networkx.algorithms.core.k_shell.html +++ b/reference/algorithms/generated/networkx.algorithms.core.k_shell.html @@ -690,7 +690,7 @@ and Eran Shir, PNAS July 3, 2007 vol. 104 no. 27 11150-11154 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.core.k_truss.html b/reference/algorithms/generated/networkx.algorithms.core.k_truss.html index ee7ef094..53c03dce 100644 --- a/reference/algorithms/generated/networkx.algorithms.core.k_truss.html +++ b/reference/algorithms/generated/networkx.algorithms.core.k_truss.html @@ -686,7 +686,7 @@ Cohen, 2005.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.core.onion_layers.html b/reference/algorithms/generated/networkx.algorithms.core.onion_layers.html index 66791aa5..bea221dd 100644 --- a/reference/algorithms/generated/networkx.algorithms.core.onion_layers.html +++ b/reference/algorithms/generated/networkx.algorithms.core.onion_layers.html @@ -691,7 +691,7 @@ Physical Review X 9, 011023 (2019) <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.covering.is_edge_cover.html b/reference/algorithms/generated/networkx.algorithms.covering.is_edge_cover.html index dcfc0a9e..b0e6d755 100644 --- a/reference/algorithms/generated/networkx.algorithms.covering.is_edge_cover.html +++ b/reference/algorithms/generated/networkx.algorithms.covering.is_edge_cover.html @@ -668,7 +668,7 @@ the graph is incident to at least one edge of the set.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.covering.min_edge_cover.html b/reference/algorithms/generated/networkx.algorithms.covering.min_edge_cover.html index 02648cb0..53b5ac41 100644 --- a/reference/algorithms/generated/networkx.algorithms.covering.min_edge_cover.html +++ b/reference/algorithms/generated/networkx.algorithms.covering.min_edge_cover.html @@ -692,7 +692,7 @@ simply this function with a default matching algorithm of <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cuts.boundary_expansion.html b/reference/algorithms/generated/networkx.algorithms.cuts.boundary_expansion.html index 8b41797c..8a41072d 100644 --- a/reference/algorithms/generated/networkx.algorithms.cuts.boundary_expansion.html +++ b/reference/algorithms/generated/networkx.algorithms.cuts.boundary_expansion.html @@ -675,7 +675,7 @@ of the node boundary and the cardinality of <em>S</em>. [1]</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cuts.conductance.html b/reference/algorithms/generated/networkx.algorithms.cuts.conductance.html index 70d7b263..4b577bf5 100644 --- a/reference/algorithms/generated/networkx.algorithms.cuts.conductance.html +++ b/reference/algorithms/generated/networkx.algorithms.cuts.conductance.html @@ -679,7 +679,7 @@ have weight one.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cuts.cut_size.html b/reference/algorithms/generated/networkx.algorithms.cuts.cut_size.html index 6fca57ac..f0202a3c 100644 --- a/reference/algorithms/generated/networkx.algorithms.cuts.cut_size.html +++ b/reference/algorithms/generated/networkx.algorithms.cuts.cut_size.html @@ -688,7 +688,7 @@ cut size:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cuts.edge_expansion.html b/reference/algorithms/generated/networkx.algorithms.cuts.edge_expansion.html index 3e51c933..a105f4f0 100644 --- a/reference/algorithms/generated/networkx.algorithms.cuts.edge_expansion.html +++ b/reference/algorithms/generated/networkx.algorithms.cuts.edge_expansion.html @@ -680,7 +680,7 @@ American Mathematical Society, 1997, ISBN 0-8218-0315-8 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cuts.mixing_expansion.html b/reference/algorithms/generated/networkx.algorithms.cuts.mixing_expansion.html index 38b0f606..84f4db1e 100644 --- a/reference/algorithms/generated/networkx.algorithms.cuts.mixing_expansion.html +++ b/reference/algorithms/generated/networkx.algorithms.cuts.mixing_expansion.html @@ -680,7 +680,7 @@ in Theoretical Computer Science</em> 7.1–3 (2011): 1–336. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cuts.node_expansion.html b/reference/algorithms/generated/networkx.algorithms.cuts.node_expansion.html index cb5588ea..b193f0bd 100644 --- a/reference/algorithms/generated/networkx.algorithms.cuts.node_expansion.html +++ b/reference/algorithms/generated/networkx.algorithms.cuts.node_expansion.html @@ -675,7 +675,7 @@ in Theoretical Computer Science</em> 7.1–3 (2011): 1–336. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cuts.normalized_cut_size.html b/reference/algorithms/generated/networkx.algorithms.cuts.normalized_cut_size.html index 86a7a59f..8228981d 100644 --- a/reference/algorithms/generated/networkx.algorithms.cuts.normalized_cut_size.html +++ b/reference/algorithms/generated/networkx.algorithms.cuts.normalized_cut_size.html @@ -682,7 +682,7 @@ multiplicity.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cuts.volume.html b/reference/algorithms/generated/networkx.algorithms.cuts.volume.html index ebd4f5dd..b96fec9c 100644 --- a/reference/algorithms/generated/networkx.algorithms.cuts.volume.html +++ b/reference/algorithms/generated/networkx.algorithms.cuts.volume.html @@ -679,7 +679,7 @@ have weight one.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cycles.cycle_basis.html b/reference/algorithms/generated/networkx.algorithms.cycles.cycle_basis.html index c4068ed5..296c2eef 100644 --- a/reference/algorithms/generated/networkx.algorithms.cycles.cycle_basis.html +++ b/reference/algorithms/generated/networkx.algorithms.cycles.cycle_basis.html @@ -684,7 +684,7 @@ cycles of a graph. Comm. ACM 12, 9 (Sept 1969), 514-518.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cycles.find_cycle.html b/reference/algorithms/generated/networkx.algorithms.cycles.find_cycle.html index 0e91dbe1..fe3a1810 100644 --- a/reference/algorithms/generated/networkx.algorithms.cycles.find_cycle.html +++ b/reference/algorithms/generated/networkx.algorithms.cycles.find_cycle.html @@ -625,7 +625,7 @@ is also known as a polytree).</p> <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">G</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">DiGraph</span><span class="p">([(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">2</span><span class="p">),</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">)])</span> <span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">find_cycle</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">orientation</span><span class="o">=</span><span class="s2">"original"</span><span class="p">)</span> <span class="gt">Traceback (most recent call last):</span> - <span class="o">...</span> +<span class="w"> </span><span class="o">...</span> <span class="gr">networkx.exception.NetworkXNoCycle</span>: <span class="n">No cycle found.</span> <span class="gp">>>> </span><span class="nb">list</span><span class="p">(</span><span class="n">nx</span><span class="o">.</span><span class="n">find_cycle</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="n">orientation</span><span class="o">=</span><span class="s2">"ignore"</span><span class="p">))</span> <span class="go">[(0, 1, 'forward'), (1, 2, 'forward'), (0, 2, 'reverse')]</span> @@ -706,7 +706,7 @@ is also known as a polytree).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cycles.minimum_cycle_basis.html b/reference/algorithms/generated/networkx.algorithms.cycles.minimum_cycle_basis.html index b7ed6a1b..0d73d4dc 100644 --- a/reference/algorithms/generated/networkx.algorithms.cycles.minimum_cycle_basis.html +++ b/reference/algorithms/generated/networkx.algorithms.cycles.minimum_cycle_basis.html @@ -679,7 +679,7 @@ Ph.D. thesis, University of Amsterdam, Netherlands</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cycles.recursive_simple_cycles.html b/reference/algorithms/generated/networkx.algorithms.cycles.recursive_simple_cycles.html index 47fe01d7..af8802a7 100644 --- a/reference/algorithms/generated/networkx.algorithms.cycles.recursive_simple_cycles.html +++ b/reference/algorithms/generated/networkx.algorithms.cycles.recursive_simple_cycles.html @@ -696,7 +696,7 @@ D. B. Johnson, SIAM Journal on Computing 4, no. 1, 77-84, 1975. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.cycles.simple_cycles.html b/reference/algorithms/generated/networkx.algorithms.cycles.simple_cycles.html index c2146079..2514876c 100644 --- a/reference/algorithms/generated/networkx.algorithms.cycles.simple_cycles.html +++ b/reference/algorithms/generated/networkx.algorithms.cycles.simple_cycles.html @@ -706,7 +706,7 @@ For example, to exclude self-loops from the above example:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.d_separation.d_separated.html b/reference/algorithms/generated/networkx.algorithms.d_separation.d_separated.html index b7fea4cb..b2fe7179 100644 --- a/reference/algorithms/generated/networkx.algorithms.d_separation.d_separated.html +++ b/reference/algorithms/generated/networkx.algorithms.d_separation.d_separated.html @@ -677,7 +677,7 @@ is <code class="docutils literal notranslate"><span class="pre">...</span> <span <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dag.all_topological_sorts.html b/reference/algorithms/generated/networkx.algorithms.dag.all_topological_sorts.html index e2722b00..12e47fec 100644 --- a/reference/algorithms/generated/networkx.algorithms.dag.all_topological_sorts.html +++ b/reference/algorithms/generated/networkx.algorithms.dag.all_topological_sorts.html @@ -685,7 +685,7 @@ Elsevier (North-Holland), Amsterdam</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dag.ancestors.html b/reference/algorithms/generated/networkx.algorithms.dag.ancestors.html index 59882a7d..43f41d94 100644 --- a/reference/algorithms/generated/networkx.algorithms.dag.ancestors.html +++ b/reference/algorithms/generated/networkx.algorithms.dag.ancestors.html @@ -676,7 +676,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dag.antichains.html b/reference/algorithms/generated/networkx.algorithms.dag.antichains.html index 5484fd01..d908d6cd 100644 --- a/reference/algorithms/generated/networkx.algorithms.dag.antichains.html +++ b/reference/algorithms/generated/networkx.algorithms.dag.antichains.html @@ -684,7 +684,7 @@ AMS, Vol 42, 1995, p. 226.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dag.dag_longest_path.html b/reference/algorithms/generated/networkx.algorithms.dag.dag_longest_path.html index e87c780f..475fdd3c 100644 --- a/reference/algorithms/generated/networkx.algorithms.dag.dag_longest_path.html +++ b/reference/algorithms/generated/networkx.algorithms.dag.dag_longest_path.html @@ -694,7 +694,7 @@ can be used to specify a specific ordering:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dag.dag_longest_path_length.html b/reference/algorithms/generated/networkx.algorithms.dag.dag_longest_path_length.html index fa7b65da..339b2dfd 100644 --- a/reference/algorithms/generated/networkx.algorithms.dag.dag_longest_path_length.html +++ b/reference/algorithms/generated/networkx.algorithms.dag.dag_longest_path_length.html @@ -679,7 +679,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dag.dag_to_branching.html b/reference/algorithms/generated/networkx.algorithms.dag.dag_to_branching.html index 5b4afbe2..e27af0c6 100644 --- a/reference/algorithms/generated/networkx.algorithms.dag.dag_to_branching.html +++ b/reference/algorithms/generated/networkx.algorithms.dag.dag_to_branching.html @@ -717,7 +717,7 @@ example:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dag.descendants.html b/reference/algorithms/generated/networkx.algorithms.dag.descendants.html index 302f8d42..caba6468 100644 --- a/reference/algorithms/generated/networkx.algorithms.dag.descendants.html +++ b/reference/algorithms/generated/networkx.algorithms.dag.descendants.html @@ -676,7 +676,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dag.is_aperiodic.html b/reference/algorithms/generated/networkx.algorithms.dag.is_aperiodic.html index b61be4c9..7eb0aee9 100644 --- a/reference/algorithms/generated/networkx.algorithms.dag.is_aperiodic.html +++ b/reference/algorithms/generated/networkx.algorithms.dag.is_aperiodic.html @@ -707,7 +707,7 @@ the graph is <em>not aperiodic</em>:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dag.is_directed_acyclic_graph.html b/reference/algorithms/generated/networkx.algorithms.dag.is_directed_acyclic_graph.html index ec2ea423..4e0e7ea7 100644 --- a/reference/algorithms/generated/networkx.algorithms.dag.is_directed_acyclic_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.dag.is_directed_acyclic_graph.html @@ -678,7 +678,7 @@ False if not.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dag.lexicographical_topological_sort.html b/reference/algorithms/generated/networkx.algorithms.dag.lexicographical_topological_sort.html index 9ac9aed3..dbf9fb9e 100644 --- a/reference/algorithms/generated/networkx.algorithms.dag.lexicographical_topological_sort.html +++ b/reference/algorithms/generated/networkx.algorithms.dag.lexicographical_topological_sort.html @@ -730,7 +730,7 @@ This groups the strings and integers separately so they can be compared only amo <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dag.topological_generations.html b/reference/algorithms/generated/networkx.algorithms.dag.topological_generations.html index 60854551..4f931951 100644 --- a/reference/algorithms/generated/networkx.algorithms.dag.topological_generations.html +++ b/reference/algorithms/generated/networkx.algorithms.dag.topological_generations.html @@ -686,7 +686,7 @@ be obtained with this function using <code class="xref py py-obj docutils litera <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dag.topological_sort.html b/reference/algorithms/generated/networkx.algorithms.dag.topological_sort.html index d53cdd4e..2f24b9b7 100644 --- a/reference/algorithms/generated/networkx.algorithms.dag.topological_sort.html +++ b/reference/algorithms/generated/networkx.algorithms.dag.topological_sort.html @@ -704,7 +704,7 @@ with <code class="xref py py-func docutils literal notranslate"><span class="pre <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dag.transitive_closure.html b/reference/algorithms/generated/networkx.algorithms.dag.transitive_closure.html index 8ab49743..5b436f34 100644 --- a/reference/algorithms/generated/networkx.algorithms.dag.transitive_closure.html +++ b/reference/algorithms/generated/networkx.algorithms.dag.transitive_closure.html @@ -713,7 +713,7 @@ when <code class="docutils literal notranslate"><span class="pre">reflexive=Fals <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dag.transitive_closure_dag.html b/reference/algorithms/generated/networkx.algorithms.dag.transitive_closure_dag.html index 12712660..9851a865 100644 --- a/reference/algorithms/generated/networkx.algorithms.dag.transitive_closure_dag.html +++ b/reference/algorithms/generated/networkx.algorithms.dag.transitive_closure_dag.html @@ -678,7 +678,7 @@ a mention in the literature.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dag.transitive_reduction.html b/reference/algorithms/generated/networkx.algorithms.dag.transitive_reduction.html index d2886874..83362f74 100644 --- a/reference/algorithms/generated/networkx.algorithms.dag.transitive_reduction.html +++ b/reference/algorithms/generated/networkx.algorithms.dag.transitive_reduction.html @@ -685,7 +685,7 @@ To perform transitive reduction on a DiGraph and transfer node/edge data:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.distance_measures.barycenter.html b/reference/algorithms/generated/networkx.algorithms.distance_measures.barycenter.html index c92223f9..1b18ae70 100644 --- a/reference/algorithms/generated/networkx.algorithms.distance_measures.barycenter.html +++ b/reference/algorithms/generated/networkx.algorithms.distance_measures.barycenter.html @@ -693,7 +693,7 @@ lengths for any pairs.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.distance_measures.center.html b/reference/algorithms/generated/networkx.algorithms.distance_measures.center.html index d1f74622..ba56371b 100644 --- a/reference/algorithms/generated/networkx.algorithms.distance_measures.center.html +++ b/reference/algorithms/generated/networkx.algorithms.distance_measures.center.html @@ -684,7 +684,7 @@ errors in distances. Use integer weights to avoid this.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.distance_measures.diameter.html b/reference/algorithms/generated/networkx.algorithms.distance_measures.diameter.html index e140d077..c3633ef0 100644 --- a/reference/algorithms/generated/networkx.algorithms.distance_measures.diameter.html +++ b/reference/algorithms/generated/networkx.algorithms.distance_measures.diameter.html @@ -683,7 +683,7 @@ errors in distances. Use integer weights to avoid this.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.distance_measures.eccentricity.html b/reference/algorithms/generated/networkx.algorithms.distance_measures.eccentricity.html index 76fbecd9..5d691660 100644 --- a/reference/algorithms/generated/networkx.algorithms.distance_measures.eccentricity.html +++ b/reference/algorithms/generated/networkx.algorithms.distance_measures.eccentricity.html @@ -684,7 +684,7 @@ errors in distances. Use integer weights to avoid this.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.distance_measures.periphery.html b/reference/algorithms/generated/networkx.algorithms.distance_measures.periphery.html index be1f93bc..53b225c2 100644 --- a/reference/algorithms/generated/networkx.algorithms.distance_measures.periphery.html +++ b/reference/algorithms/generated/networkx.algorithms.distance_measures.periphery.html @@ -684,7 +684,7 @@ errors in distances. Use integer weights to avoid this.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.distance_measures.radius.html b/reference/algorithms/generated/networkx.algorithms.distance_measures.radius.html index 9a71661c..ede1ca6f 100644 --- a/reference/algorithms/generated/networkx.algorithms.distance_measures.radius.html +++ b/reference/algorithms/generated/networkx.algorithms.distance_measures.radius.html @@ -677,7 +677,7 @@ errors in distances. Use integer weights to avoid this.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.distance_measures.resistance_distance.html b/reference/algorithms/generated/networkx.algorithms.distance_measures.resistance_distance.html index c799da62..e4e11ffb 100644 --- a/reference/algorithms/generated/networkx.algorithms.distance_measures.resistance_distance.html +++ b/reference/algorithms/generated/networkx.algorithms.distance_measures.resistance_distance.html @@ -701,7 +701,7 @@ Mestrado, Mathematisch Instituut Universiteit Leiden, 2016 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.distance_regular.global_parameters.html b/reference/algorithms/generated/networkx.algorithms.distance_regular.global_parameters.html index 77cd704e..7be19c77 100644 --- a/reference/algorithms/generated/networkx.algorithms.distance_regular.global_parameters.html +++ b/reference/algorithms/generated/networkx.algorithms.distance_regular.global_parameters.html @@ -683,7 +683,7 @@ From MathWorld–A Wolfram Web Resource. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.distance_regular.intersection_array.html b/reference/algorithms/generated/networkx.algorithms.distance_regular.intersection_array.html index fe7adf73..6ddd5948 100644 --- a/reference/algorithms/generated/networkx.algorithms.distance_regular.intersection_array.html +++ b/reference/algorithms/generated/networkx.algorithms.distance_regular.intersection_array.html @@ -678,7 +678,7 @@ From MathWorld–A Wolfram Web Resource. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.distance_regular.is_distance_regular.html b/reference/algorithms/generated/networkx.algorithms.distance_regular.is_distance_regular.html index fe7735f1..5fea1c52 100644 --- a/reference/algorithms/generated/networkx.algorithms.distance_regular.is_distance_regular.html +++ b/reference/algorithms/generated/networkx.algorithms.distance_regular.is_distance_regular.html @@ -684,7 +684,7 @@ Distance-Regular Graphs. New York: Springer-Verlag, 1989.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.distance_regular.is_strongly_regular.html b/reference/algorithms/generated/networkx.algorithms.distance_regular.is_strongly_regular.html index f5a50542..232795ae 100644 --- a/reference/algorithms/generated/networkx.algorithms.distance_regular.is_strongly_regular.html +++ b/reference/algorithms/generated/networkx.algorithms.distance_regular.is_strongly_regular.html @@ -675,7 +675,7 @@ and each pair of nonadjacent vertices has one shared neighbor:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dominance.dominance_frontiers.html b/reference/algorithms/generated/networkx.algorithms.dominance.dominance_frontiers.html index be74fe9f..3dc1f9e0 100644 --- a/reference/algorithms/generated/networkx.algorithms.dominance.dominance_frontiers.html +++ b/reference/algorithms/generated/networkx.algorithms.dominance.dominance_frontiers.html @@ -679,7 +679,7 @@ Software Practice & Experience, 4:110, 2001.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dominance.immediate_dominators.html b/reference/algorithms/generated/networkx.algorithms.dominance.immediate_dominators.html index aeb75069..c42aa4c8 100644 --- a/reference/algorithms/generated/networkx.algorithms.dominance.immediate_dominators.html +++ b/reference/algorithms/generated/networkx.algorithms.dominance.immediate_dominators.html @@ -682,7 +682,7 @@ Software Practice & Experience, 4:110, 2001.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dominating.dominating_set.html b/reference/algorithms/generated/networkx.algorithms.dominating.dominating_set.html index 9f685b55..6692d879 100644 --- a/reference/algorithms/generated/networkx.algorithms.dominating.dominating_set.html +++ b/reference/algorithms/generated/networkx.algorithms.dominating.dominating_set.html @@ -678,7 +678,7 @@ finds some dominating set, not necessarily the smallest one.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.dominating.is_dominating_set.html b/reference/algorithms/generated/networkx.algorithms.dominating.is_dominating_set.html index 0b6a24e5..b62a472e 100644 --- a/reference/algorithms/generated/networkx.algorithms.dominating.is_dominating_set.html +++ b/reference/algorithms/generated/networkx.algorithms.dominating.is_dominating_set.html @@ -664,7 +664,7 @@ member of <em>D</em> <a class="reference internal" href="#rf92913515997-1" id="i <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.efficiency_measures.efficiency.html b/reference/algorithms/generated/networkx.algorithms.efficiency_measures.efficiency.html index 94103f0f..84b74de4 100644 --- a/reference/algorithms/generated/networkx.algorithms.efficiency_measures.efficiency.html +++ b/reference/algorithms/generated/networkx.algorithms.efficiency_measures.efficiency.html @@ -683,7 +683,7 @@ between nodes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.efficiency_measures.global_efficiency.html b/reference/algorithms/generated/networkx.algorithms.efficiency_measures.global_efficiency.html index 3cf28dec..9f99e6c7 100644 --- a/reference/algorithms/generated/networkx.algorithms.efficiency_measures.global_efficiency.html +++ b/reference/algorithms/generated/networkx.algorithms.efficiency_measures.global_efficiency.html @@ -681,7 +681,7 @@ nodes <a class="reference internal" href="#r9f26066558a1-1" id="id1">[1]</a>.</p <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.efficiency_measures.local_efficiency.html b/reference/algorithms/generated/networkx.algorithms.efficiency_measures.local_efficiency.html index 09483405..2cea11eb 100644 --- a/reference/algorithms/generated/networkx.algorithms.efficiency_measures.local_efficiency.html +++ b/reference/algorithms/generated/networkx.algorithms.efficiency_measures.local_efficiency.html @@ -682,7 +682,7 @@ efficiency</em> is the average of the local efficiencies of each node <a class=" <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.euler.eulerian_circuit.html b/reference/algorithms/generated/networkx.algorithms.euler.eulerian_circuit.html index ec1af461..71aacb7e 100644 --- a/reference/algorithms/generated/networkx.algorithms.euler.eulerian_circuit.html +++ b/reference/algorithms/generated/networkx.algorithms.euler.eulerian_circuit.html @@ -703,7 +703,7 @@ Mathematical programming, Volume 5, Issue 1 (1973), 111-114.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.euler.eulerian_path.html b/reference/algorithms/generated/networkx.algorithms.euler.eulerian_path.html index 75d0ee07..4983d5f6 100644 --- a/reference/algorithms/generated/networkx.algorithms.euler.eulerian_path.html +++ b/reference/algorithms/generated/networkx.algorithms.euler.eulerian_path.html @@ -660,7 +660,7 @@ The default yields edge 2-tuples</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.euler.eulerize.html b/reference/algorithms/generated/networkx.algorithms.euler.eulerize.html index c31f2334..d5c5791a 100644 --- a/reference/algorithms/generated/networkx.algorithms.euler.eulerize.html +++ b/reference/algorithms/generated/networkx.algorithms.euler.eulerize.html @@ -691,7 +691,7 @@ Mathematical programming, Volume 5, Issue 1 (1973), 111-114.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.euler.has_eulerian_path.html b/reference/algorithms/generated/networkx.algorithms.euler.has_eulerian_path.html index 0bd354b9..6a33e23d 100644 --- a/reference/algorithms/generated/networkx.algorithms.euler.has_eulerian_path.html +++ b/reference/algorithms/generated/networkx.algorithms.euler.has_eulerian_path.html @@ -705,7 +705,7 @@ you can first remove such vertices and then call <a class="reference internal" h <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.euler.is_eulerian.html b/reference/algorithms/generated/networkx.algorithms.euler.is_eulerian.html index 295ca016..b0f2e6c8 100644 --- a/reference/algorithms/generated/networkx.algorithms.euler.is_eulerian.html +++ b/reference/algorithms/generated/networkx.algorithms.euler.is_eulerian.html @@ -676,7 +676,7 @@ you can first remove such vertices and then call <a class="reference internal" h <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.euler.is_semieulerian.html b/reference/algorithms/generated/networkx.algorithms.euler.is_semieulerian.html index 8188935d..22b93d9c 100644 --- a/reference/algorithms/generated/networkx.algorithms.euler.is_semieulerian.html +++ b/reference/algorithms/generated/networkx.algorithms.euler.is_semieulerian.html @@ -647,7 +647,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.boykov_kolmogorov.html b/reference/algorithms/generated/networkx.algorithms.flow.boykov_kolmogorov.html index 13be5ac6..48320ce2 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.boykov_kolmogorov.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.boykov_kolmogorov.html @@ -776,7 +776,7 @@ in the graph attribute <code class="xref py py-obj docutils literal notranslate" <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.build_residual_network.html b/reference/algorithms/generated/networkx.algorithms.flow.build_residual_network.html index 05d1f08e..27da8aa1 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.build_residual_network.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.build_residual_network.html @@ -657,7 +657,7 @@ that <code class="samp docutils literal notranslate"><span class="pre">R[u][v][' <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.capacity_scaling.html b/reference/algorithms/generated/networkx.algorithms.flow.capacity_scaling.html index fc53dc0d..8175f645 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.capacity_scaling.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.capacity_scaling.html @@ -761,7 +761,7 @@ algorithm.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.cost_of_flow.html b/reference/algorithms/generated/networkx.algorithms.flow.cost_of_flow.html index 4f5315a2..8317f8ee 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.cost_of_flow.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.cost_of_flow.html @@ -678,7 +678,7 @@ constant factor (eg 100).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.dinitz.html b/reference/algorithms/generated/networkx.algorithms.flow.dinitz.html index 48429362..81dd1aab 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.dinitz.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.dinitz.html @@ -754,7 +754,7 @@ namespace, so you have to explicitly import them from the flow package.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.edmonds_karp.html b/reference/algorithms/generated/networkx.algorithms.flow.edmonds_karp.html index d505bb86..e5b71915 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.edmonds_karp.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.edmonds_karp.html @@ -744,7 +744,7 @@ namespace, so you have to explicitly import them from the flow package.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.gomory_hu_tree.html b/reference/algorithms/generated/networkx.algorithms.flow.gomory_hu_tree.html index fb7716bd..302bfab3 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.gomory_hu_tree.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.gomory_hu_tree.html @@ -752,7 +752,7 @@ SIAM J Comput 19(1):143-155, 1990.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.max_flow_min_cost.html b/reference/algorithms/generated/networkx.algorithms.flow.max_flow_min_cost.html index f146ad4a..b6033ecf 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.max_flow_min_cost.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.max_flow_min_cost.html @@ -730,7 +730,7 @@ constant factor (eg 100).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.maximum_flow.html b/reference/algorithms/generated/networkx.algorithms.flow.maximum_flow.html index 2d9dc2af..6ad2f1a7 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.maximum_flow.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.maximum_flow.html @@ -757,7 +757,7 @@ maximum flow by using the flow_func parameter.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.maximum_flow_value.html b/reference/algorithms/generated/networkx.algorithms.flow.maximum_flow_value.html index b64cdfbd..8357e187 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.maximum_flow_value.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.maximum_flow_value.html @@ -752,7 +752,7 @@ maximum flow by using the flow_func parameter.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.min_cost_flow.html b/reference/algorithms/generated/networkx.algorithms.flow.min_cost_flow.html index 96b3774e..01f4e9ff 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.min_cost_flow.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.min_cost_flow.html @@ -722,7 +722,7 @@ constant factor (eg 100).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.min_cost_flow_cost.html b/reference/algorithms/generated/networkx.algorithms.flow.min_cost_flow_cost.html index a064cf78..cff4e31e 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.min_cost_flow_cost.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.min_cost_flow_cost.html @@ -723,7 +723,7 @@ constant factor (eg 100).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.minimum_cut.html b/reference/algorithms/generated/networkx.algorithms.flow.minimum_cut.html index 849170b0..0a6e6265 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.minimum_cut.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.minimum_cut.html @@ -760,7 +760,7 @@ minimum cut by using the flow_func parameter.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.minimum_cut_value.html b/reference/algorithms/generated/networkx.algorithms.flow.minimum_cut_value.html index 9883faa7..15e18cc6 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.minimum_cut_value.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.minimum_cut_value.html @@ -749,7 +749,7 @@ minimum cut by using the flow_func parameter.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.network_simplex.html b/reference/algorithms/generated/networkx.algorithms.flow.network_simplex.html index 57fea9b8..ed3d1eeb 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.network_simplex.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.network_simplex.html @@ -803,7 +803,7 @@ algorithm.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.preflow_push.html b/reference/algorithms/generated/networkx.algorithms.flow.preflow_push.html index 1c6a9332..2a367ea8 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.preflow_push.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.preflow_push.html @@ -757,7 +757,7 @@ namespace, so you have to explicitly import them from the flow package.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.flow.shortest_augmenting_path.html b/reference/algorithms/generated/networkx.algorithms.flow.shortest_augmenting_path.html index 0ee9fad3..fcb033a0 100644 --- a/reference/algorithms/generated/networkx.algorithms.flow.shortest_augmenting_path.html +++ b/reference/algorithms/generated/networkx.algorithms.flow.shortest_augmenting_path.html @@ -749,7 +749,7 @@ namespace, so you have to explicitly import them from the flow package.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.graph_hashing.weisfeiler_lehman_graph_hash.html b/reference/algorithms/generated/networkx.algorithms.graph_hashing.weisfeiler_lehman_graph_hash.html index 09b1d5ec..7b62e7cc 100644 --- a/reference/algorithms/generated/networkx.algorithms.graph_hashing.weisfeiler_lehman_graph_hash.html +++ b/reference/algorithms/generated/networkx.algorithms.graph_hashing.weisfeiler_lehman_graph_hash.html @@ -731,7 +731,7 @@ the same hash digest.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.graph_hashing.weisfeiler_lehman_subgraph_hashes.html b/reference/algorithms/generated/networkx.algorithms.graph_hashing.weisfeiler_lehman_subgraph_hashes.html index 1233b167..c2aeeddb 100644 --- a/reference/algorithms/generated/networkx.algorithms.graph_hashing.weisfeiler_lehman_subgraph_hashes.html +++ b/reference/algorithms/generated/networkx.algorithms.graph_hashing.weisfeiler_lehman_subgraph_hashes.html @@ -752,7 +752,7 @@ is similar.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.graphical.is_digraphical.html b/reference/algorithms/generated/networkx.algorithms.graphical.is_digraphical.html index 4c5f970f..d731a5ff 100644 --- a/reference/algorithms/generated/networkx.algorithms.graphical.is_digraphical.html +++ b/reference/algorithms/generated/networkx.algorithms.graphical.is_digraphical.html @@ -670,7 +670,7 @@ and Factors, Discrete Mathematics, 6(1), pp. 79-88 (1973)</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.graphical.is_graphical.html b/reference/algorithms/generated/networkx.algorithms.graphical.is_graphical.html index 2a5cde4e..ebfbfd68 100644 --- a/reference/algorithms/generated/networkx.algorithms.graphical.is_graphical.html +++ b/reference/algorithms/generated/networkx.algorithms.graphical.is_graphical.html @@ -695,7 +695,7 @@ Chapman and Hall/CRC, 1996.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.graphical.is_multigraphical.html b/reference/algorithms/generated/networkx.algorithms.graphical.is_multigraphical.html index d83da080..779345ab 100644 --- a/reference/algorithms/generated/networkx.algorithms.graphical.is_multigraphical.html +++ b/reference/algorithms/generated/networkx.algorithms.graphical.is_multigraphical.html @@ -665,7 +665,7 @@ degrees of the vertices of a linear graph”, J. SIAM, 10, pp. 496-506 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.graphical.is_pseudographical.html b/reference/algorithms/generated/networkx.algorithms.graphical.is_pseudographical.html index 21f216f5..0b567f1d 100644 --- a/reference/algorithms/generated/networkx.algorithms.graphical.is_pseudographical.html +++ b/reference/algorithms/generated/networkx.algorithms.graphical.is_pseudographical.html @@ -667,7 +667,7 @@ pp. 778-782 (1976).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.graphical.is_valid_degree_sequence_erdos_gallai.html b/reference/algorithms/generated/networkx.algorithms.graphical.is_valid_degree_sequence_erdos_gallai.html index 09a75667..d142d755 100644 --- a/reference/algorithms/generated/networkx.algorithms.graphical.is_valid_degree_sequence_erdos_gallai.html +++ b/reference/algorithms/generated/networkx.algorithms.graphical.is_valid_degree_sequence_erdos_gallai.html @@ -691,7 +691,7 @@ of graphic sequences”, Discrete Mathematics, 105, pp. 292-303 (1992).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.graphical.is_valid_degree_sequence_havel_hakimi.html b/reference/algorithms/generated/networkx.algorithms.graphical.is_valid_degree_sequence_havel_hakimi.html index 2fc323ef..a191233d 100644 --- a/reference/algorithms/generated/networkx.algorithms.graphical.is_valid_degree_sequence_havel_hakimi.html +++ b/reference/algorithms/generated/networkx.algorithms.graphical.is_valid_degree_sequence_havel_hakimi.html @@ -686,7 +686,7 @@ Chapman and Hall/CRC, 1996.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.hierarchy.flow_hierarchy.html b/reference/algorithms/generated/networkx.algorithms.hierarchy.flow_hierarchy.html index 88e953f2..2c4b0a62 100644 --- a/reference/algorithms/generated/networkx.algorithms.hierarchy.flow_hierarchy.html +++ b/reference/algorithms/generated/networkx.algorithms.hierarchy.flow_hierarchy.html @@ -676,7 +676,7 @@ DOI: 10.1002/cplx.20368 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.hybrid.is_kl_connected.html b/reference/algorithms/generated/networkx.algorithms.hybrid.is_kl_connected.html index ba4babca..df9f5629 100644 --- a/reference/algorithms/generated/networkx.algorithms.hybrid.is_kl_connected.html +++ b/reference/algorithms/generated/networkx.algorithms.hybrid.is_kl_connected.html @@ -680,7 +680,7 @@ Power Law Graphs.” <em>Complex Networks</em>. Springer Berlin Heidelberg, <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.hybrid.kl_connected_subgraph.html b/reference/algorithms/generated/networkx.algorithms.hybrid.kl_connected_subgraph.html index b78f23f7..0692e4b0 100644 --- a/reference/algorithms/generated/networkx.algorithms.hybrid.kl_connected_subgraph.html +++ b/reference/algorithms/generated/networkx.algorithms.hybrid.kl_connected_subgraph.html @@ -689,7 +689,7 @@ Power Law Graphs.” <em>Complex Networks</em>. Springer Berlin Heidelberg, <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isolate.is_isolate.html b/reference/algorithms/generated/networkx.algorithms.isolate.is_isolate.html index 394a6627..3d91bc96 100644 --- a/reference/algorithms/generated/networkx.algorithms.isolate.is_isolate.html +++ b/reference/algorithms/generated/networkx.algorithms.isolate.is_isolate.html @@ -667,7 +667,7 @@ out-neighbors.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isolate.isolates.html b/reference/algorithms/generated/networkx.algorithms.isolate.isolates.html index 6fa09a46..abeb88a1 100644 --- a/reference/algorithms/generated/networkx.algorithms.isolate.isolates.html +++ b/reference/algorithms/generated/networkx.algorithms.isolate.isolates.html @@ -679,7 +679,7 @@ isolates, then use <code class="xref py py-meth docutils literal notranslate"><s <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isolate.number_of_isolates.html b/reference/algorithms/generated/networkx.algorithms.isolate.number_of_isolates.html index 3b039792..3d4c97af 100644 --- a/reference/algorithms/generated/networkx.algorithms.isolate.number_of_isolates.html +++ b/reference/algorithms/generated/networkx.algorithms.isolate.number_of_isolates.html @@ -655,7 +655,7 @@ out-neighbors.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.__init__.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.__init__.html index 4b4cbc69..8861e588 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.__init__.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.__init__.html @@ -668,7 +668,7 @@ considered when testing for an isomorphism.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.candidate_pairs_iter.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.candidate_pairs_iter.html index 104c7595..0c88d856 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.candidate_pairs_iter.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.candidate_pairs_iter.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.initialize.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.initialize.html index 272c743c..ef2c8b55 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.initialize.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.initialize.html @@ -641,7 +641,7 @@ If only subclassing GraphMatcher, a redefinition is not necessary.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.is_isomorphic.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.is_isomorphic.html index 0b6b983d..3989154e 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.is_isomorphic.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.is_isomorphic.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.isomorphisms_iter.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.isomorphisms_iter.html index 6f703d79..a0cce5de 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.isomorphisms_iter.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.isomorphisms_iter.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.match.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.match.html index f375ec42..ca399b45 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.match.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.match.html @@ -643,7 +643,7 @@ we yield the mapping.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.semantic_feasibility.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.semantic_feasibility.html index 7bd7fb7d..82d31c7c 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.semantic_feasibility.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.semantic_feasibility.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.subgraph_is_isomorphic.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.subgraph_is_isomorphic.html index ce8a2c33..b55361b6 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.subgraph_is_isomorphic.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.subgraph_is_isomorphic.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.subgraph_isomorphisms_iter.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.subgraph_isomorphisms_iter.html index 109dad3d..a84aca43 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.subgraph_isomorphisms_iter.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.subgraph_isomorphisms_iter.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.syntactic_feasibility.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.syntactic_feasibility.html index b6f9e7a0..946f6ac2 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.syntactic_feasibility.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.DiGraphMatcher.syntactic_feasibility.html @@ -643,7 +643,7 @@ not make it impossible for an isomorphism/monomorphism to be found.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.__init__.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.__init__.html index b55f859b..746a9d0a 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.__init__.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.__init__.html @@ -668,7 +668,7 @@ considered when testing for an isomorphism.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.candidate_pairs_iter.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.candidate_pairs_iter.html index 06da30fd..9c2d2d72 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.candidate_pairs_iter.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.candidate_pairs_iter.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.initialize.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.initialize.html index 6dc8f05a..3100537e 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.initialize.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.initialize.html @@ -641,7 +641,7 @@ If only subclassing GraphMatcher, a redefinition is not necessary.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.is_isomorphic.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.is_isomorphic.html index 886a123d..f3334f30 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.is_isomorphic.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.is_isomorphic.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.isomorphisms_iter.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.isomorphisms_iter.html index 70abdfca..76d772d8 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.isomorphisms_iter.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.isomorphisms_iter.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.match.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.match.html index 905cd7c0..a30fb6ae 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.match.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.match.html @@ -643,7 +643,7 @@ we yield the mapping.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.semantic_feasibility.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.semantic_feasibility.html index 7f8dc87a..a7bdeca8 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.semantic_feasibility.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.semantic_feasibility.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.subgraph_is_isomorphic.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.subgraph_is_isomorphic.html index ce88f879..4d2cb95d 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.subgraph_is_isomorphic.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.subgraph_is_isomorphic.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.subgraph_isomorphisms_iter.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.subgraph_isomorphisms_iter.html index 2afe735c..8a6a8fdc 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.subgraph_isomorphisms_iter.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.subgraph_isomorphisms_iter.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.syntactic_feasibility.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.syntactic_feasibility.html index fb8a6182..2272fa6d 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.syntactic_feasibility.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.GraphMatcher.syntactic_feasibility.html @@ -643,7 +643,7 @@ not make it impossible for an isomorphism/monomorphism to be found.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.ISMAGS.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.ISMAGS.html index 3108828b..b9a14171 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.ISMAGS.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.ISMAGS.html @@ -750,7 +750,7 @@ If <a class="reference external" href="https://docs.python.org/3/library/constan <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.categorical_edge_match.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.categorical_edge_match.html index 2948bfab..6e4cb0f1 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.categorical_edge_match.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.categorical_edge_match.html @@ -666,7 +666,7 @@ default values for the categorical edge attributes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.categorical_multiedge_match.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.categorical_multiedge_match.html index d7f7d2ec..fecc09aa 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.categorical_multiedge_match.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.categorical_multiedge_match.html @@ -666,7 +666,7 @@ default values for the categorical edge attributes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.categorical_node_match.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.categorical_node_match.html index f8ba3484..15879979 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.categorical_node_match.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.categorical_node_match.html @@ -666,7 +666,7 @@ default values for the categorical node attributes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.could_be_isomorphic.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.could_be_isomorphic.html index 70e80bb9..6e4a0fee 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.could_be_isomorphic.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.could_be_isomorphic.html @@ -653,7 +653,7 @@ involving that node.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.fast_could_be_isomorphic.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.fast_could_be_isomorphic.html index 20bdb4e4..71883e4d 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.fast_could_be_isomorphic.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.fast_could_be_isomorphic.html @@ -651,7 +651,7 @@ sequence contains the number of triangles each node is part of.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.faster_could_be_isomorphic.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.faster_could_be_isomorphic.html index 90a61305..c5c9bb0f 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.faster_could_be_isomorphic.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.faster_could_be_isomorphic.html @@ -650,7 +650,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.generic_edge_match.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.generic_edge_match.html index 31e0bd0a..4fb4c3db 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.generic_edge_match.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.generic_edge_match.html @@ -672,7 +672,7 @@ of operators to use when comparing values for each attribute.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.generic_multiedge_match.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.generic_multiedge_match.html index 6181a8ef..6573af92 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.generic_multiedge_match.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.generic_multiedge_match.html @@ -675,7 +675,7 @@ of operators to use when comparing values for each attribute.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.generic_node_match.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.generic_node_match.html index 929efd6d..8bca8f97 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.generic_node_match.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.generic_node_match.html @@ -672,7 +672,7 @@ of operators to use when comparing values for each attribute.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.is_isomorphic.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.is_isomorphic.html index 7c3d55c3..6f3923e8 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.is_isomorphic.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.is_isomorphic.html @@ -735,7 +735,7 @@ default value ‘red’.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.numerical_edge_match.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.numerical_edge_match.html index 441593a7..7bc200ca 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.numerical_edge_match.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.numerical_edge_match.html @@ -670,7 +670,7 @@ default values for the numerical edge attributes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.numerical_multiedge_match.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.numerical_multiedge_match.html index 8171d262..a36b21dc 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.numerical_multiedge_match.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.numerical_multiedge_match.html @@ -670,7 +670,7 @@ default values for the numerical edge attributes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.numerical_node_match.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.numerical_node_match.html index d0badc3b..cc26610b 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.numerical_node_match.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.numerical_node_match.html @@ -670,7 +670,7 @@ default values for the numerical node attributes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.tree_isomorphism.rooted_tree_isomorphism.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.tree_isomorphism.rooted_tree_isomorphism.html index d1a261ff..fd81aa18 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.tree_isomorphism.rooted_tree_isomorphism.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.tree_isomorphism.rooted_tree_isomorphism.html @@ -672,7 +672,7 @@ will not necessarily be unique.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.tree_isomorphism.tree_isomorphism.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.tree_isomorphism.tree_isomorphism.html index a1c71863..04390860 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.tree_isomorphism.tree_isomorphism.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.tree_isomorphism.tree_isomorphism.html @@ -667,7 +667,7 @@ will not necessarily be unique.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.vf2pp.vf2pp_all_isomorphisms.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.vf2pp.vf2pp_all_isomorphisms.html index b87703e6..a7486837 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.vf2pp.vf2pp_all_isomorphisms.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.vf2pp.vf2pp_all_isomorphisms.html @@ -661,7 +661,7 @@ named <code class="xref py py-obj docutils literal notranslate"><span class="pre <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.vf2pp.vf2pp_is_isomorphic.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.vf2pp.vf2pp_is_isomorphic.html index f0953d5a..d02bb3e2 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.vf2pp.vf2pp_is_isomorphic.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.vf2pp.vf2pp_is_isomorphic.html @@ -661,7 +661,7 @@ named <code class="xref py py-obj docutils literal notranslate"><span class="pre <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.isomorphism.vf2pp.vf2pp_isomorphism.html b/reference/algorithms/generated/networkx.algorithms.isomorphism.vf2pp.vf2pp_isomorphism.html index 05e5c782..90efb052 100644 --- a/reference/algorithms/generated/networkx.algorithms.isomorphism.vf2pp.vf2pp_isomorphism.html +++ b/reference/algorithms/generated/networkx.algorithms.isomorphism.vf2pp.vf2pp_isomorphism.html @@ -661,7 +661,7 @@ named <code class="xref py py-obj docutils literal notranslate"><span class="pre <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.link_analysis.hits_alg.hits.html b/reference/algorithms/generated/networkx.algorithms.link_analysis.hits_alg.hits.html index f64be45f..c5bd6987 100644 --- a/reference/algorithms/generated/networkx.algorithms.link_analysis.hits_alg.hits.html +++ b/reference/algorithms/generated/networkx.algorithms.link_analysis.hits_alg.hits.html @@ -703,7 +703,7 @@ http://www.cs.cornell.edu/home/kleinber/auth.pdf.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.link_analysis.pagerank_alg.google_matrix.html b/reference/algorithms/generated/networkx.algorithms.link_analysis.pagerank_alg.google_matrix.html index 9a6f852f..0224cdc9 100644 --- a/reference/algorithms/generated/networkx.algorithms.link_analysis.pagerank_alg.google_matrix.html +++ b/reference/algorithms/generated/networkx.algorithms.link_analysis.pagerank_alg.google_matrix.html @@ -691,7 +691,7 @@ between those nodes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.link_analysis.pagerank_alg.pagerank.html b/reference/algorithms/generated/networkx.algorithms.link_analysis.pagerank_alg.pagerank.html index 735f26f7..695b34cb 100644 --- a/reference/algorithms/generated/networkx.algorithms.link_analysis.pagerank_alg.pagerank.html +++ b/reference/algorithms/generated/networkx.algorithms.link_analysis.pagerank_alg.pagerank.html @@ -726,7 +726,7 @@ The PageRank citation ranking: Bringing order to the Web. 1999 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.link_prediction.adamic_adar_index.html b/reference/algorithms/generated/networkx.algorithms.link_prediction.adamic_adar_index.html index db1f11c5..383ffedb 100644 --- a/reference/algorithms/generated/networkx.algorithms.link_prediction.adamic_adar_index.html +++ b/reference/algorithms/generated/networkx.algorithms.link_prediction.adamic_adar_index.html @@ -685,7 +685,7 @@ The Link Prediction Problem for Social Networks (2004). <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.link_prediction.cn_soundarajan_hopcroft.html b/reference/algorithms/generated/networkx.algorithms.link_prediction.cn_soundarajan_hopcroft.html index 31ace9e6..4f011491 100644 --- a/reference/algorithms/generated/networkx.algorithms.link_prediction.cn_soundarajan_hopcroft.html +++ b/reference/algorithms/generated/networkx.algorithms.link_prediction.cn_soundarajan_hopcroft.html @@ -699,7 +699,7 @@ World Wide Web (WWW ‘12 Companion). ACM, New York, NY, USA, 607-608. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.link_prediction.common_neighbor_centrality.html b/reference/algorithms/generated/networkx.algorithms.link_prediction.common_neighbor_centrality.html index 9f767633..fa5c2155 100644 --- a/reference/algorithms/generated/networkx.algorithms.link_prediction.common_neighbor_centrality.html +++ b/reference/algorithms/generated/networkx.algorithms.link_prediction.common_neighbor_centrality.html @@ -704,7 +704,7 @@ Sci Rep 10, 364 (2020). <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.link_prediction.jaccard_coefficient.html b/reference/algorithms/generated/networkx.algorithms.link_prediction.jaccard_coefficient.html index 86a8470e..7f21fc50 100644 --- a/reference/algorithms/generated/networkx.algorithms.link_prediction.jaccard_coefficient.html +++ b/reference/algorithms/generated/networkx.algorithms.link_prediction.jaccard_coefficient.html @@ -683,7 +683,7 @@ The Link Prediction Problem for Social Networks (2004). <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.link_prediction.preferential_attachment.html b/reference/algorithms/generated/networkx.algorithms.link_prediction.preferential_attachment.html index 3463b230..fbc2314e 100644 --- a/reference/algorithms/generated/networkx.algorithms.link_prediction.preferential_attachment.html +++ b/reference/algorithms/generated/networkx.algorithms.link_prediction.preferential_attachment.html @@ -683,7 +683,7 @@ The Link Prediction Problem for Social Networks (2004). <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.link_prediction.ra_index_soundarajan_hopcroft.html b/reference/algorithms/generated/networkx.algorithms.link_prediction.ra_index_soundarajan_hopcroft.html index 0a5429ec..2d395c79 100644 --- a/reference/algorithms/generated/networkx.algorithms.link_prediction.ra_index_soundarajan_hopcroft.html +++ b/reference/algorithms/generated/networkx.algorithms.link_prediction.ra_index_soundarajan_hopcroft.html @@ -699,7 +699,7 @@ World Wide Web (WWW ‘12 Companion). ACM, New York, NY, USA, 607-608. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.link_prediction.resource_allocation_index.html b/reference/algorithms/generated/networkx.algorithms.link_prediction.resource_allocation_index.html index 4ca3497c..ad940034 100644 --- a/reference/algorithms/generated/networkx.algorithms.link_prediction.resource_allocation_index.html +++ b/reference/algorithms/generated/networkx.algorithms.link_prediction.resource_allocation_index.html @@ -684,7 +684,7 @@ Eur. Phys. J. B 71 (2009) 623. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.link_prediction.within_inter_cluster.html b/reference/algorithms/generated/networkx.algorithms.link_prediction.within_inter_cluster.html index 329bd2fa..e6ea1b69 100644 --- a/reference/algorithms/generated/networkx.algorithms.link_prediction.within_inter_cluster.html +++ b/reference/algorithms/generated/networkx.algorithms.link_prediction.within_inter_cluster.html @@ -705,7 +705,7 @@ Artificial Intelligence (SBIA’12) <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.lowest_common_ancestors.all_pairs_lowest_common_ancestor.html b/reference/algorithms/generated/networkx.algorithms.lowest_common_ancestors.all_pairs_lowest_common_ancestor.html index 97242d96..6abbfade 100644 --- a/reference/algorithms/generated/networkx.algorithms.lowest_common_ancestors.all_pairs_lowest_common_ancestor.html +++ b/reference/algorithms/generated/networkx.algorithms.lowest_common_ancestors.all_pairs_lowest_common_ancestor.html @@ -687,7 +687,7 @@ specified node pairings:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.lowest_common_ancestors.lowest_common_ancestor.html b/reference/algorithms/generated/networkx.algorithms.lowest_common_ancestors.lowest_common_ancestor.html index 1f0c0284..d4880695 100644 --- a/reference/algorithms/generated/networkx.algorithms.lowest_common_ancestors.lowest_common_ancestor.html +++ b/reference/algorithms/generated/networkx.algorithms.lowest_common_ancestors.lowest_common_ancestor.html @@ -669,7 +669,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.lowest_common_ancestors.tree_all_pairs_lowest_common_ancestor.html b/reference/algorithms/generated/networkx.algorithms.lowest_common_ancestors.tree_all_pairs_lowest_common_ancestor.html index 79439fd5..9fa29076 100644 --- a/reference/algorithms/generated/networkx.algorithms.lowest_common_ancestors.tree_all_pairs_lowest_common_ancestor.html +++ b/reference/algorithms/generated/networkx.algorithms.lowest_common_ancestors.tree_all_pairs_lowest_common_ancestor.html @@ -698,7 +698,7 @@ want to compute lowest common ancestors. Here is an example:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.matching.is_matching.html b/reference/algorithms/generated/networkx.algorithms.matching.is_matching.html index c2fbb7eb..c592fced 100644 --- a/reference/algorithms/generated/networkx.algorithms.matching.is_matching.html +++ b/reference/algorithms/generated/networkx.algorithms.matching.is_matching.html @@ -679,7 +679,7 @@ Or if the matching is not a collection of 2-tuple edges.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.matching.is_maximal_matching.html b/reference/algorithms/generated/networkx.algorithms.matching.is_maximal_matching.html index ce7e13d0..4585ed48 100644 --- a/reference/algorithms/generated/networkx.algorithms.matching.is_maximal_matching.html +++ b/reference/algorithms/generated/networkx.algorithms.matching.is_maximal_matching.html @@ -667,7 +667,7 @@ matching in the graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.matching.is_perfect_matching.html b/reference/algorithms/generated/networkx.algorithms.matching.is_perfect_matching.html index 0c3b54df..1fb34149 100644 --- a/reference/algorithms/generated/networkx.algorithms.matching.is_perfect_matching.html +++ b/reference/algorithms/generated/networkx.algorithms.matching.is_perfect_matching.html @@ -668,7 +668,7 @@ matching in the graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.matching.max_weight_matching.html b/reference/algorithms/generated/networkx.algorithms.matching.max_weight_matching.html index 6c6529ff..00fa4920 100644 --- a/reference/algorithms/generated/networkx.algorithms.matching.max_weight_matching.html +++ b/reference/algorithms/generated/networkx.algorithms.matching.max_weight_matching.html @@ -692,7 +692,7 @@ Zvi Galil, ACM Computing Surveys, 1986.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.matching.maximal_matching.html b/reference/algorithms/generated/networkx.algorithms.matching.maximal_matching.html index c039c174..3c1c8b10 100644 --- a/reference/algorithms/generated/networkx.algorithms.matching.maximal_matching.html +++ b/reference/algorithms/generated/networkx.algorithms.matching.maximal_matching.html @@ -665,7 +665,7 @@ A maximal matching cannot add more edges and still be a matching.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.matching.min_weight_matching.html b/reference/algorithms/generated/networkx.algorithms.matching.min_weight_matching.html index 44975a94..5da4aa38 100644 --- a/reference/algorithms/generated/networkx.algorithms.matching.min_weight_matching.html +++ b/reference/algorithms/generated/networkx.algorithms.matching.min_weight_matching.html @@ -682,7 +682,7 @@ If key not found, uses 1 as weight.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.minors.contracted_edge.html b/reference/algorithms/generated/networkx.algorithms.minors.contracted_edge.html index 6be352f0..4cdbc5d1 100644 --- a/reference/algorithms/generated/networkx.algorithms.minors.contracted_edge.html +++ b/reference/algorithms/generated/networkx.algorithms.minors.contracted_edge.html @@ -612,7 +612,7 @@ appear in the returned graph.</p> <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">G</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">cycle_graph</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">contracted_edge</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span> <span class="gt">Traceback (most recent call last):</span> - <span class="c">...</span> +<span class="w"> </span><span class="c">...</span> <span class="gr">ValueError</span>: <span class="n">Edge (1, 3) does not exist in graph G; cannot contract it</span> </pre></div> </div> @@ -700,7 +700,7 @@ cycle graph on <em>n - 1</em> nodes:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.minors.contracted_nodes.html b/reference/algorithms/generated/networkx.algorithms.minors.contracted_nodes.html index e5d5398a..36d10b3c 100644 --- a/reference/algorithms/generated/networkx.algorithms.minors.contracted_nodes.html +++ b/reference/algorithms/generated/networkx.algorithms.minors.contracted_nodes.html @@ -710,7 +710,7 @@ yields the path graph (ignoring parallel edges):</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.minors.equivalence_classes.html b/reference/algorithms/generated/networkx.algorithms.minors.equivalence_classes.html index 016e0ca3..ed366914 100644 --- a/reference/algorithms/generated/networkx.algorithms.minors.equivalence_classes.html +++ b/reference/algorithms/generated/networkx.algorithms.minors.equivalence_classes.html @@ -688,7 +688,7 @@ remainder <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.minors.identified_nodes.html b/reference/algorithms/generated/networkx.algorithms.minors.identified_nodes.html index 55a03f55..d5da3441 100644 --- a/reference/algorithms/generated/networkx.algorithms.minors.identified_nodes.html +++ b/reference/algorithms/generated/networkx.algorithms.minors.identified_nodes.html @@ -710,7 +710,7 @@ yields the path graph (ignoring parallel edges):</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.minors.quotient_graph.html b/reference/algorithms/generated/networkx.algorithms.minors.quotient_graph.html index a980018a..edc9f3a2 100644 --- a/reference/algorithms/generated/networkx.algorithms.minors.quotient_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.minors.quotient_graph.html @@ -819,7 +819,7 @@ in the right form, in order to call <a class="reference internal" href="#network <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.mis.maximal_independent_set.html b/reference/algorithms/generated/networkx.algorithms.mis.maximal_independent_set.html index f786298a..9635d537 100644 --- a/reference/algorithms/generated/networkx.algorithms.mis.maximal_independent_set.html +++ b/reference/algorithms/generated/networkx.algorithms.mis.maximal_independent_set.html @@ -682,7 +682,7 @@ do not form an independent set, an exception is raised.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.moral.moral_graph.html b/reference/algorithms/generated/networkx.algorithms.moral.moral_graph.html index 021497d0..c5df2bd6 100644 --- a/reference/algorithms/generated/networkx.algorithms.moral.moral_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.moral.moral_graph.html @@ -682,7 +682,7 @@ in artificial intelligence (UAI’95)</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.node_classification.harmonic_function.html b/reference/algorithms/generated/networkx.algorithms.node_classification.harmonic_function.html index 3460902f..decdfa72 100644 --- a/reference/algorithms/generated/networkx.algorithms.node_classification.harmonic_function.html +++ b/reference/algorithms/generated/networkx.algorithms.node_classification.harmonic_function.html @@ -681,7 +681,7 @@ In ICML (Vol. 3, pp. 912-919).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.node_classification.local_and_global_consistency.html b/reference/algorithms/generated/networkx.algorithms.node_classification.local_and_global_consistency.html index 1310718d..70f8c076 100644 --- a/reference/algorithms/generated/networkx.algorithms.node_classification.local_and_global_consistency.html +++ b/reference/algorithms/generated/networkx.algorithms.node_classification.local_and_global_consistency.html @@ -683,7 +683,7 @@ Advances in neural information processing systems, 16(16), 321-328.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.non_randomness.non_randomness.html b/reference/algorithms/generated/networkx.algorithms.non_randomness.non_randomness.html index 1c0b2dc5..73c22a77 100644 --- a/reference/algorithms/generated/networkx.algorithms.non_randomness.non_randomness.html +++ b/reference/algorithms/generated/networkx.algorithms.non_randomness.non_randomness.html @@ -697,7 +697,7 @@ SIAM International Conference on Data Mining. 2009</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.all.compose_all.html b/reference/algorithms/generated/networkx.algorithms.operators.all.compose_all.html index f77d0b76..cb8ec263 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.all.compose_all.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.all.compose_all.html @@ -666,7 +666,7 @@ from the last graph in the list with that attribute is used.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.all.disjoint_union_all.html b/reference/algorithms/generated/networkx.algorithms.operators.all.disjoint_union_all.html index c29fd48f..92e0572f 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.all.disjoint_union_all.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.all.disjoint_union_all.html @@ -665,7 +665,7 @@ from the last graph in the list with that attribute is used.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.all.intersection_all.html b/reference/algorithms/generated/networkx.algorithms.operators.all.intersection_all.html index 9e04087a..21e921d0 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.all.intersection_all.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.all.intersection_all.html @@ -662,7 +662,7 @@ graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.all.union_all.html b/reference/algorithms/generated/networkx.algorithms.operators.all.union_all.html index 9bec58ba..7cc1177c 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.all.union_all.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.all.union_all.html @@ -677,7 +677,7 @@ from the last graph in the list with that attribute is used.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.binary.compose.html b/reference/algorithms/generated/networkx.algorithms.operators.binary.compose.html index c5645511..728fcd94 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.binary.compose.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.binary.compose.html @@ -711,7 +711,7 @@ If you prefer another way of combining attributes, you can update them after the <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.binary.difference.html b/reference/algorithms/generated/networkx.algorithms.operators.binary.difference.html index 4313d6ad..e34d24dd 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.binary.difference.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.binary.difference.html @@ -674,7 +674,7 @@ as follows:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.binary.disjoint_union.html b/reference/algorithms/generated/networkx.algorithms.operators.binary.disjoint_union.html index 4f7eadab..35eb5007 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.binary.disjoint_union.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.binary.disjoint_union.html @@ -685,7 +685,7 @@ or the method, Graph.update().</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.binary.full_join.html b/reference/algorithms/generated/networkx.algorithms.operators.binary.full_join.html index c8518f5c..68f85458 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.binary.full_join.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.binary.full_join.html @@ -687,7 +687,7 @@ G and H the value from H is used.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.binary.intersection.html b/reference/algorithms/generated/networkx.algorithms.operators.binary.intersection.html index 9173e03c..515adbce 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.binary.intersection.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.binary.intersection.html @@ -681,7 +681,7 @@ as follows</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.binary.symmetric_difference.html b/reference/algorithms/generated/networkx.algorithms.operators.binary.symmetric_difference.html index 766cdb90..0f29be6e 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.binary.symmetric_difference.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.binary.symmetric_difference.html @@ -666,7 +666,7 @@ graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.binary.union.html b/reference/algorithms/generated/networkx.algorithms.operators.binary.union.html index f0331061..2a03e8de 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.binary.union.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.binary.union.html @@ -684,7 +684,7 @@ then the value from H is used.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.product.cartesian_product.html b/reference/algorithms/generated/networkx.algorithms.operators.product.cartesian_product.html index 0729c06b..9d28acd8 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.product.cartesian_product.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.product.cartesian_product.html @@ -682,7 +682,7 @@ new product graph</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.product.corona_product.html b/reference/algorithms/generated/networkx.algorithms.operators.product.corona_product.html index 6b1780e3..1d546d86 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.product.corona_product.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.product.corona_product.html @@ -684,7 +684,7 @@ doi: 10.22108/toc.2014.5542.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.product.lexicographic_product.html b/reference/algorithms/generated/networkx.algorithms.operators.product.lexicographic_product.html index deb7a51c..b37ff5de 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.product.lexicographic_product.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.product.lexicographic_product.html @@ -681,7 +681,7 @@ new product graph</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.product.power.html b/reference/algorithms/generated/networkx.algorithms.operators.product.power.html index cfd9076b..48d80cff 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.product.power.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.product.power.html @@ -705,7 +705,7 @@ powers:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.product.rooted_product.html b/reference/algorithms/generated/networkx.algorithms.operators.product.rooted_product.html index 945643c8..0a00cf15 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.product.rooted_product.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.product.rooted_product.html @@ -662,7 +662,7 @@ The nodes of G and H are not relabeled.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.product.strong_product.html b/reference/algorithms/generated/networkx.algorithms.operators.product.strong_product.html index 6e992d18..75eb87f7 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.product.strong_product.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.product.strong_product.html @@ -683,7 +683,7 @@ new product graph</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.product.tensor_product.html b/reference/algorithms/generated/networkx.algorithms.operators.product.tensor_product.html index 65cb4649..e7faa529 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.product.tensor_product.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.product.tensor_product.html @@ -683,7 +683,7 @@ new product graph</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.unary.complement.html b/reference/algorithms/generated/networkx.algorithms.operators.unary.complement.html index 0687b45b..ffd64f0f 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.unary.complement.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.unary.complement.html @@ -663,7 +663,7 @@ does not produce parallel edges for MultiGraphs.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.operators.unary.reverse.html b/reference/algorithms/generated/networkx.algorithms.operators.unary.reverse.html index d28772f7..a4406090 100644 --- a/reference/algorithms/generated/networkx.algorithms.operators.unary.reverse.html +++ b/reference/algorithms/generated/networkx.algorithms.operators.unary.reverse.html @@ -669,7 +669,7 @@ reversed in place.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.planar_drawing.combinatorial_embedding_to_pos.html b/reference/algorithms/generated/networkx.algorithms.planar_drawing.combinatorial_embedding_to_pos.html index 967f1ba9..d293eeb8 100644 --- a/reference/algorithms/generated/networkx.algorithms.planar_drawing.combinatorial_embedding_to_pos.html +++ b/reference/algorithms/generated/networkx.algorithms.planar_drawing.combinatorial_embedding_to_pos.html @@ -670,7 +670,7 @@ A Linear-time Algorithm for Drawing a Planar Graph on a Grid 1989 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.planarity.PlanarEmbedding.html b/reference/algorithms/generated/networkx.algorithms.planarity.PlanarEmbedding.html index b6e1aead..c0ca073a 100644 --- a/reference/algorithms/generated/networkx.algorithms.planarity.PlanarEmbedding.html +++ b/reference/algorithms/generated/networkx.algorithms.planarity.PlanarEmbedding.html @@ -950,7 +950,7 @@ SciPy sparse array, or a PyGraphviz graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.planarity.check_planarity.html b/reference/algorithms/generated/networkx.algorithms.planarity.check_planarity.html index c867644d..0b55235d 100644 --- a/reference/algorithms/generated/networkx.algorithms.planarity.check_planarity.html +++ b/reference/algorithms/generated/networkx.algorithms.planarity.check_planarity.html @@ -704,7 +704,7 @@ Lecture Notes Series on Computing: Volume 12 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.planarity.is_planar.html b/reference/algorithms/generated/networkx.algorithms.planarity.is_planar.html index d03e2d21..4f1398ef 100644 --- a/reference/algorithms/generated/networkx.algorithms.planarity.is_planar.html +++ b/reference/algorithms/generated/networkx.algorithms.planarity.is_planar.html @@ -669,7 +669,7 @@ any edge intersections.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.polynomials.chromatic_polynomial.html b/reference/algorithms/generated/networkx.algorithms.polynomials.chromatic_polynomial.html index c3411087..06b7f229 100644 --- a/reference/algorithms/generated/networkx.algorithms.polynomials.chromatic_polynomial.html +++ b/reference/algorithms/generated/networkx.algorithms.polynomials.chromatic_polynomial.html @@ -748,7 +748,7 @@ Discrete Mathematics, 2006 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.polynomials.tutte_polynomial.html b/reference/algorithms/generated/networkx.algorithms.polynomials.tutte_polynomial.html index e4f835fb..20f3b704 100644 --- a/reference/algorithms/generated/networkx.algorithms.polynomials.tutte_polynomial.html +++ b/reference/algorithms/generated/networkx.algorithms.polynomials.tutte_polynomial.html @@ -770,7 +770,7 @@ Structural Analysis of Complex Networks, 2011 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.reciprocity.overall_reciprocity.html b/reference/algorithms/generated/networkx.algorithms.reciprocity.overall_reciprocity.html index f4d75c72..2e24fdba 100644 --- a/reference/algorithms/generated/networkx.algorithms.reciprocity.overall_reciprocity.html +++ b/reference/algorithms/generated/networkx.algorithms.reciprocity.overall_reciprocity.html @@ -648,7 +648,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.reciprocity.reciprocity.html b/reference/algorithms/generated/networkx.algorithms.reciprocity.reciprocity.html index 5f44f5e8..f03e447e 100644 --- a/reference/algorithms/generated/networkx.algorithms.reciprocity.reciprocity.html +++ b/reference/algorithms/generated/networkx.algorithms.reciprocity.reciprocity.html @@ -666,7 +666,7 @@ In such cases this function will return None.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.regular.is_k_regular.html b/reference/algorithms/generated/networkx.algorithms.regular.is_k_regular.html index f4c741a7..897b90f5 100644 --- a/reference/algorithms/generated/networkx.algorithms.regular.is_k_regular.html +++ b/reference/algorithms/generated/networkx.algorithms.regular.is_k_regular.html @@ -659,7 +659,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.regular.is_regular.html b/reference/algorithms/generated/networkx.algorithms.regular.is_regular.html index 7562d2a6..f8ca17eb 100644 --- a/reference/algorithms/generated/networkx.algorithms.regular.is_regular.html +++ b/reference/algorithms/generated/networkx.algorithms.regular.is_regular.html @@ -661,7 +661,7 @@ vertex are equal.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.regular.k_factor.html b/reference/algorithms/generated/networkx.algorithms.regular.k_factor.html index 99e80864..729f8f01 100644 --- a/reference/algorithms/generated/networkx.algorithms.regular.k_factor.html +++ b/reference/algorithms/generated/networkx.algorithms.regular.k_factor.html @@ -677,7 +677,7 @@ Information processing letters, 2009.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.richclub.rich_club_coefficient.html b/reference/algorithms/generated/networkx.algorithms.richclub.rich_club_coefficient.html index 91e78560..4dda637f 100644 --- a/reference/algorithms/generated/networkx.algorithms.richclub.rich_club_coefficient.html +++ b/reference/algorithms/generated/networkx.algorithms.richclub.rich_club_coefficient.html @@ -700,7 +700,7 @@ sequences”, 2006. <a class="reference external" href="https://arxiv.org/abs/co <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.astar.astar_path.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.astar.astar_path.html index de0313f9..be99cbae 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.astar.astar_path.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.astar.astar_path.html @@ -705,7 +705,7 @@ will find the shortest red path.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.astar.astar_path_length.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.astar.astar_path_length.html index 1268f2fb..0464cd3d 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.astar.astar_path_length.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.astar.astar_path_length.html @@ -682,7 +682,7 @@ return a number or None to indicate a hidden edge.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.floyd_warshall.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.floyd_warshall.html index f5afab2c..690bd9ef 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.floyd_warshall.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.floyd_warshall.html @@ -670,7 +670,7 @@ It has running time <span class="math notranslate nohighlight">\(O(n^3)\)</span> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.floyd_warshall_numpy.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.floyd_warshall_numpy.html index ae7c71d7..baebd43e 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.floyd_warshall_numpy.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.floyd_warshall_numpy.html @@ -678,7 +678,7 @@ cycles. It has running time <span class="math notranslate nohighlight">\(O(n^3)\ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.floyd_warshall_predecessor_and_distance.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.floyd_warshall_predecessor_and_distance.html index 4354c1ff..d4c4745d 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.floyd_warshall_predecessor_and_distance.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.floyd_warshall_predecessor_and_distance.html @@ -691,7 +691,7 @@ It has running time <span class="math notranslate nohighlight">\(O(n^3)\)</span> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.reconstruct_path.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.reconstruct_path.html index 5b3db4fc..c74df4d3 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.reconstruct_path.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.dense.reconstruct_path.html @@ -669,7 +669,7 @@ floyd_warshall_predecessor_and_distance function</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.all_shortest_paths.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.all_shortest_paths.html index 9055ff49..ece88a39 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.all_shortest_paths.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.all_shortest_paths.html @@ -700,7 +700,7 @@ length – instead, we only produce the shortest simple paths.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.average_shortest_path_length.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.average_shortest_path_length.html index f9934c5e..5636dc6b 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.average_shortest_path_length.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.average_shortest_path_length.html @@ -699,7 +699,7 @@ length for each component</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.has_path.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.has_path.html index a757d211..771e07bc 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.has_path.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.has_path.html @@ -650,7 +650,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.shortest_path.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.shortest_path.html index dfeeaf94..ac22940c 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.shortest_path.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.shortest_path.html @@ -720,7 +720,7 @@ This returns only one of them.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.shortest_path_length.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.shortest_path_length.html index ef96625e..8484cb5d 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.shortest_path_length.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.shortest_path_length.html @@ -725,7 +725,7 @@ the edge orientation.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path.html index e6a21367..8af004fc 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path.html @@ -668,7 +668,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path_length.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path_length.html index 7c8ceb80..a5e73b5d 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path_length.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path_length.html @@ -674,7 +674,7 @@ shortest path length as the key value.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.bidirectional_shortest_path.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.bidirectional_shortest_path.html index 742f2154..7b02ee28 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.bidirectional_shortest_path.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.bidirectional_shortest_path.html @@ -670,7 +670,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.predecessor.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.predecessor.html index 143fc236..542e8680 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.predecessor.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.predecessor.html @@ -678,7 +678,7 @@ during breadth-first-search).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path.html index aa6cadba..9c42cc39 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path.html @@ -675,7 +675,7 @@ only one of those paths.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path_length.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path_length.html index 26ff04d9..4efe791f 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path_length.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path_length.html @@ -676,7 +676,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path.html index 1122ec5c..893cf43f 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path.html @@ -674,7 +674,7 @@ only one of those paths.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path_length.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path_length.html index 583b550c..407c9084 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path_length.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path_length.html @@ -676,7 +676,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_bellman_ford_path.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_bellman_ford_path.html index 3f543ebd..d3edf61d 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_bellman_ford_path.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_bellman_ford_path.html @@ -679,7 +679,7 @@ Distances are calculated as sums of weighted edges traversed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_bellman_ford_path_length.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_bellman_ford_path_length.html index aa2dd5f4..ff7030c5 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_bellman_ford_path_length.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_bellman_ford_path_length.html @@ -684,7 +684,7 @@ Distances are calculated as sums of weighted edges traversed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra.html index 77464f63..7a29416e 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra.html @@ -697,7 +697,7 @@ Distances are calculated as sums of weighted edges traversed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra_path.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra_path.html index e09cb97a..dfcec6e2 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra_path.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra_path.html @@ -682,7 +682,7 @@ Distances are calculated as sums of weighted edges traversed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra_path_length.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra_path_length.html index de5212c7..3a0b7574 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra_path_length.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra_path_length.html @@ -687,7 +687,7 @@ Distances are calculated as sums of weighted edges traversed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bellman_ford_path.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bellman_ford_path.html index b2475d8c..1cc268ec 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bellman_ford_path.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bellman_ford_path.html @@ -690,7 +690,7 @@ Distances are calculated as sums of weighted edges traversed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bellman_ford_path_length.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bellman_ford_path_length.html index 66035310..2c4c92eb 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bellman_ford_path_length.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bellman_ford_path_length.html @@ -691,7 +691,7 @@ Distances are calculated as sums of weighted edges traversed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bellman_ford_predecessor_and_distance.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bellman_ford_predecessor_and_distance.html index 78c4798d..493937aa 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bellman_ford_predecessor_and_distance.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bellman_ford_predecessor_and_distance.html @@ -654,7 +654,7 @@ In NetworkX v2.2 this changed to the source node having predecessor <code class= <span class="gp">>>> </span><span class="n">G</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="mi">2</span><span class="p">][</span><span class="s2">"weight"</span><span class="p">]</span> <span class="o">=</span> <span class="o">-</span><span class="mi">7</span> <span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">bellman_ford_predecessor_and_distance</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span> <span class="gt">Traceback (most recent call last):</span> - <span class="o">...</span> +<span class="w"> </span><span class="o">...</span> <span class="gr">networkx.exception.NetworkXUnbounded</span>: <span class="n">Negative cycle detected.</span> </pre></div> </div> @@ -733,7 +733,7 @@ In NetworkX v2.2 this changed to the source node having predecessor <code class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bidirectional_dijkstra.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bidirectional_dijkstra.html index 03f92807..9cfa68a8 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bidirectional_dijkstra.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.bidirectional_dijkstra.html @@ -709,7 +709,7 @@ are negative or are floating point numbers <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.dijkstra_path.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.dijkstra_path.html index ccfb1b32..3b3e6761 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.dijkstra_path.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.dijkstra_path.html @@ -709,7 +709,7 @@ path and length-of-path if you need both, use that.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.dijkstra_path_length.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.dijkstra_path_length.html index a645b0e3..f0160133 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.dijkstra_path_length.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.dijkstra_path_length.html @@ -699,7 +699,7 @@ path and length-of-path if you need both, use that.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.dijkstra_predecessor_and_distance.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.dijkstra_predecessor_and_distance.html index 78985307..ec7f846c 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.dijkstra_predecessor_and_distance.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.dijkstra_predecessor_and_distance.html @@ -699,7 +699,7 @@ there are more than one shortest paths to the key node.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.find_negative_cycle.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.find_negative_cycle.html index c1a7c8a4..5b3c1bf1 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.find_negative_cycle.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.find_negative_cycle.html @@ -688,7 +688,7 @@ equals the first to indicate a cycle.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.goldberg_radzik.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.goldberg_radzik.html index e78bb105..acb2777d 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.goldberg_radzik.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.goldberg_radzik.html @@ -630,7 +630,7 @@ will not be detected.</p> <span class="gp">>>> </span><span class="n">G</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="mi">2</span><span class="p">][</span><span class="s2">"weight"</span><span class="p">]</span> <span class="o">=</span> <span class="o">-</span><span class="mi">7</span> <span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">goldberg_radzik</span><span class="p">(</span><span class="n">G</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span> <span class="gt">Traceback (most recent call last):</span> - <span class="o">...</span> +<span class="w"> </span><span class="o">...</span> <span class="gr">networkx.exception.NetworkXUnbounded</span>: <span class="n">Negative cycle detected.</span> </pre></div> </div> @@ -709,7 +709,7 @@ will not be detected.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.johnson.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.johnson.html index acba93c7..f38152df 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.johnson.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.johnson.html @@ -704,7 +704,7 @@ algorithm.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra.html index bda599e2..ee79a841 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra.html @@ -731,7 +731,7 @@ are negative or are floating point numbers <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra_path.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra_path.html index 8c6c24f7..ae4ece83 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra_path.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra_path.html @@ -703,7 +703,7 @@ will find the shortest red path.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra_path_length.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra_path_length.html index 5af370ee..33770e1b 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra_path_length.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra_path_length.html @@ -706,7 +706,7 @@ will find the shortest red path.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.negative_edge_cycle.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.negative_edge_cycle.html index 3048e1ae..977cc6bf 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.negative_edge_cycle.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.negative_edge_cycle.html @@ -683,7 +683,7 @@ node. It then removes that extra node.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford.html index 341ddc86..114e7470 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford.html @@ -711,7 +711,7 @@ Distances are calculated as sums of weighted edges traversed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path.html index 72d04f46..409cd282 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path.html @@ -688,7 +688,7 @@ Distances are calculated as sums of weighted edges traversed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path_length.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path_length.html index 5b4f4c3e..e1c81faf 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path_length.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path_length.html @@ -695,7 +695,7 @@ Distances are calculated as sums of weighted edges traversed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_dijkstra.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_dijkstra.html index 2257714d..313566e8 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_dijkstra.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_dijkstra.html @@ -726,7 +726,7 @@ are negative or are floating point numbers <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path.html index 74e4916a..35e9ebe5 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path.html @@ -695,7 +695,7 @@ will find the shortest red path.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path_length.html b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path_length.html index ec068061..7f90479e 100644 --- a/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path_length.html +++ b/reference/algorithms/generated/networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path_length.html @@ -702,7 +702,7 @@ will find the shortest red path.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.similarity.generate_random_paths.html b/reference/algorithms/generated/networkx.algorithms.similarity.generate_random_paths.html index ae853180..36cc9534 100644 --- a/reference/algorithms/generated/networkx.algorithms.similarity.generate_random_paths.html +++ b/reference/algorithms/generated/networkx.algorithms.similarity.generate_random_paths.html @@ -689,7 +689,7 @@ inverted index mapping of nodes to the paths in which that node is present:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.similarity.graph_edit_distance.html b/reference/algorithms/generated/networkx.algorithms.similarity.graph_edit_distance.html index 3ab4a020..5cf0ead0 100644 --- a/reference/algorithms/generated/networkx.algorithms.similarity.graph_edit_distance.html +++ b/reference/algorithms/generated/networkx.algorithms.similarity.graph_edit_distance.html @@ -761,7 +761,7 @@ Lisbon, Portugal. 2015, <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.similarity.optimal_edit_paths.html b/reference/algorithms/generated/networkx.algorithms.similarity.optimal_edit_paths.html index e430dd0f..37fff626 100644 --- a/reference/algorithms/generated/networkx.algorithms.similarity.optimal_edit_paths.html +++ b/reference/algorithms/generated/networkx.algorithms.similarity.optimal_edit_paths.html @@ -753,7 +753,7 @@ Lisbon, Portugal. 2015, <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.similarity.optimize_edit_paths.html b/reference/algorithms/generated/networkx.algorithms.similarity.optimize_edit_paths.html index e691ee5e..82730c0b 100644 --- a/reference/algorithms/generated/networkx.algorithms.similarity.optimize_edit_paths.html +++ b/reference/algorithms/generated/networkx.algorithms.similarity.optimize_edit_paths.html @@ -755,7 +755,7 @@ Lisbon, Portugal. 2015, <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.similarity.optimize_graph_edit_distance.html b/reference/algorithms/generated/networkx.algorithms.similarity.optimize_graph_edit_distance.html index bca62e28..5548c505 100644 --- a/reference/algorithms/generated/networkx.algorithms.similarity.optimize_graph_edit_distance.html +++ b/reference/algorithms/generated/networkx.algorithms.similarity.optimize_graph_edit_distance.html @@ -750,7 +750,7 @@ Lisbon, Portugal. 2015, <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.similarity.panther_similarity.html b/reference/algorithms/generated/networkx.algorithms.similarity.panther_similarity.html index 0e4421df..d1de4549 100644 --- a/reference/algorithms/generated/networkx.algorithms.similarity.panther_similarity.html +++ b/reference/algorithms/generated/networkx.algorithms.similarity.panther_similarity.html @@ -691,7 +691,7 @@ Association for Computing Machinery. <a class="reference external" href="https:/ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.similarity.simrank_similarity.html b/reference/algorithms/generated/networkx.algorithms.similarity.simrank_similarity.html index 74389293..11956e12 100644 --- a/reference/algorithms/generated/networkx.algorithms.similarity.simrank_similarity.html +++ b/reference/algorithms/generated/networkx.algorithms.similarity.simrank_similarity.html @@ -733,7 +733,7 @@ Other ordering of nodes is also possible.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.simple_paths.all_simple_edge_paths.html b/reference/algorithms/generated/networkx.algorithms.simple_paths.all_simple_edge_paths.html index b20620df..8653f4f7 100644 --- a/reference/algorithms/generated/networkx.algorithms.simple_paths.all_simple_edge_paths.html +++ b/reference/algorithms/generated/networkx.algorithms.simple_paths.all_simple_edge_paths.html @@ -707,7 +707,7 @@ their associated keys:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.simple_paths.all_simple_paths.html b/reference/algorithms/generated/networkx.algorithms.simple_paths.all_simple_paths.html index 616080d5..cea2406c 100644 --- a/reference/algorithms/generated/networkx.algorithms.simple_paths.all_simple_paths.html +++ b/reference/algorithms/generated/networkx.algorithms.simple_paths.all_simple_paths.html @@ -787,7 +787,7 @@ nodes, this sequence of nodes will be returned multiple times:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.simple_paths.is_simple_path.html b/reference/algorithms/generated/networkx.algorithms.simple_paths.is_simple_path.html index b4cd142a..eba3e50f 100644 --- a/reference/algorithms/generated/networkx.algorithms.simple_paths.is_simple_path.html +++ b/reference/algorithms/generated/networkx.algorithms.simple_paths.is_simple_path.html @@ -688,7 +688,7 @@ like the following:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.simple_paths.shortest_simple_paths.html b/reference/algorithms/generated/networkx.algorithms.simple_paths.shortest_simple_paths.html index a6e88e6e..d470a71f 100644 --- a/reference/algorithms/generated/networkx.algorithms.simple_paths.shortest_simple_paths.html +++ b/reference/algorithms/generated/networkx.algorithms.simple_paths.shortest_simple_paths.html @@ -723,7 +723,7 @@ paths between two nodes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.smallworld.lattice_reference.html b/reference/algorithms/generated/networkx.algorithms.smallworld.lattice_reference.html index d64546b7..a750bf9e 100644 --- a/reference/algorithms/generated/networkx.algorithms.smallworld.lattice_reference.html +++ b/reference/algorithms/generated/networkx.algorithms.smallworld.lattice_reference.html @@ -686,7 +686,7 @@ Science 296.5569 (2002): 910-913.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.smallworld.omega.html b/reference/algorithms/generated/networkx.algorithms.smallworld.omega.html index 7eafad3e..ac1fa42c 100644 --- a/reference/algorithms/generated/networkx.algorithms.smallworld.omega.html +++ b/reference/algorithms/generated/networkx.algorithms.smallworld.omega.html @@ -684,7 +684,7 @@ doi:10.1089/brain.2011.0038.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.smallworld.random_reference.html b/reference/algorithms/generated/networkx.algorithms.smallworld.random_reference.html index 422903e1..5c649fe8 100644 --- a/reference/algorithms/generated/networkx.algorithms.smallworld.random_reference.html +++ b/reference/algorithms/generated/networkx.algorithms.smallworld.random_reference.html @@ -678,7 +678,7 @@ Science 296.5569 (2002): 910-913.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.smallworld.sigma.html b/reference/algorithms/generated/networkx.algorithms.smallworld.sigma.html index ed6001cc..4ca6bec3 100644 --- a/reference/algorithms/generated/networkx.algorithms.smallworld.sigma.html +++ b/reference/algorithms/generated/networkx.algorithms.smallworld.sigma.html @@ -687,7 +687,7 @@ PLoS One. 3 (4). PMID 18446219. doi:10.1371/journal.pone.0002051.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.smetric.s_metric.html b/reference/algorithms/generated/networkx.algorithms.smetric.s_metric.html index 155b4cbc..d07abf3a 100644 --- a/reference/algorithms/generated/networkx.algorithms.smetric.s_metric.html +++ b/reference/algorithms/generated/networkx.algorithms.smetric.s_metric.html @@ -669,7 +669,7 @@ Definition, Properties, and Implications (Extended Version), 2005. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.sparsifiers.spanner.html b/reference/algorithms/generated/networkx.algorithms.sparsifiers.spanner.html index 22a77ea4..c34268d6 100644 --- a/reference/algorithms/generated/networkx.algorithms.sparsifiers.spanner.html +++ b/reference/algorithms/generated/networkx.algorithms.sparsifiers.spanner.html @@ -684,7 +684,7 @@ Random Struct. Algorithms 30(4): 532-563 (2007).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.structuralholes.constraint.html b/reference/algorithms/generated/networkx.algorithms.structuralholes.constraint.html index 5adc26a8..79a6361f 100644 --- a/reference/algorithms/generated/networkx.algorithms.structuralholes.constraint.html +++ b/reference/algorithms/generated/networkx.algorithms.structuralholes.constraint.html @@ -685,7 +685,7 @@ American Journal of Sociology (110): 349–399.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.structuralholes.effective_size.html b/reference/algorithms/generated/networkx.algorithms.structuralholes.effective_size.html index b4b7c80a..c172758c 100644 --- a/reference/algorithms/generated/networkx.algorithms.structuralholes.effective_size.html +++ b/reference/algorithms/generated/networkx.algorithms.structuralholes.effective_size.html @@ -716,7 +716,7 @@ CONNECTIONS 20(1):35-38. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.structuralholes.local_constraint.html b/reference/algorithms/generated/networkx.algorithms.structuralholes.local_constraint.html index 65ac0a22..39fe4c77 100644 --- a/reference/algorithms/generated/networkx.algorithms.structuralholes.local_constraint.html +++ b/reference/algorithms/generated/networkx.algorithms.structuralholes.local_constraint.html @@ -688,7 +688,7 @@ American Journal of Sociology (110): 349–399.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.summarization.dedensify.html b/reference/algorithms/generated/networkx.algorithms.summarization.dedensify.html index 6b0eb8b4..1701866a 100644 --- a/reference/algorithms/generated/networkx.algorithms.summarization.dedensify.html +++ b/reference/algorithms/generated/networkx.algorithms.summarization.dedensify.html @@ -743,7 +743,7 @@ original graph:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.summarization.snap_aggregation.html b/reference/algorithms/generated/networkx.algorithms.summarization.snap_aggregation.html index 58cf005a..8a6c7fca 100644 --- a/reference/algorithms/generated/networkx.algorithms.summarization.snap_aggregation.html +++ b/reference/algorithms/generated/networkx.algorithms.summarization.snap_aggregation.html @@ -739,7 +739,7 @@ analyze the information represented by the graph</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.swap.connected_double_edge_swap.html b/reference/algorithms/generated/networkx.algorithms.swap.connected_double_edge_swap.html index 0ba540c0..cf721c14 100644 --- a/reference/algorithms/generated/networkx.algorithms.swap.connected_double_edge_swap.html +++ b/reference/algorithms/generated/networkx.algorithms.swap.connected_double_edge_swap.html @@ -700,7 +700,7 @@ power law random graphs, 2003. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.swap.directed_edge_swap.html b/reference/algorithms/generated/networkx.algorithms.swap.directed_edge_swap.html index a1592f84..86cec27a 100644 --- a/reference/algorithms/generated/networkx.algorithms.swap.directed_edge_swap.html +++ b/reference/algorithms/generated/networkx.algorithms.swap.directed_edge_swap.html @@ -695,7 +695,7 @@ Degree Sequence with 2-Edge Swaps.” Mathematics Stack Exchange, <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.swap.double_edge_swap.html b/reference/algorithms/generated/networkx.algorithms.swap.double_edge_swap.html index 311ff9c1..1c33f84d 100644 --- a/reference/algorithms/generated/networkx.algorithms.swap.double_edge_swap.html +++ b/reference/algorithms/generated/networkx.algorithms.swap.double_edge_swap.html @@ -682,7 +682,7 @@ If there are fewer than 4 nodes or 2 edges in <code class="xref py py-obj docuti <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.threshold.find_threshold_graph.html b/reference/algorithms/generated/networkx.algorithms.threshold.find_threshold_graph.html index 74421e2a..ca453740 100644 --- a/reference/algorithms/generated/networkx.algorithms.threshold.find_threshold_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.threshold.find_threshold_graph.html @@ -672,7 +672,7 @@ If <a class="reference external" href="https://docs.python.org/3/library/constan <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.threshold.is_threshold_graph.html b/reference/algorithms/generated/networkx.algorithms.threshold.is_threshold_graph.html index 2a00d044..14f32ce9 100644 --- a/reference/algorithms/generated/networkx.algorithms.threshold.is_threshold_graph.html +++ b/reference/algorithms/generated/networkx.algorithms.threshold.is_threshold_graph.html @@ -670,7 +670,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tournament.hamiltonian_path.html b/reference/algorithms/generated/networkx.algorithms.tournament.hamiltonian_path.html index 739d08df..13f5d78b 100644 --- a/reference/algorithms/generated/networkx.algorithms.tournament.hamiltonian_path.html +++ b/reference/algorithms/generated/networkx.algorithms.tournament.hamiltonian_path.html @@ -668,7 +668,7 @@ of <span class="math notranslate nohighlight">\(O(n^2)\)</span>, ignoring multip <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tournament.is_reachable.html b/reference/algorithms/generated/networkx.algorithms.tournament.is_reachable.html index b5177a22..3fdaa2bc 100644 --- a/reference/algorithms/generated/networkx.algorithms.tournament.is_reachable.html +++ b/reference/algorithms/generated/networkx.algorithms.tournament.is_reachable.html @@ -689,7 +689,7 @@ tournaments.” <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tournament.is_strongly_connected.html b/reference/algorithms/generated/networkx.algorithms.tournament.is_strongly_connected.html index 305c9f07..4741ad8a 100644 --- a/reference/algorithms/generated/networkx.algorithms.tournament.is_strongly_connected.html +++ b/reference/algorithms/generated/networkx.algorithms.tournament.is_strongly_connected.html @@ -685,7 +685,7 @@ tournaments.” <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tournament.is_tournament.html b/reference/algorithms/generated/networkx.algorithms.tournament.is_tournament.html index a136909d..4733afb1 100644 --- a/reference/algorithms/generated/networkx.algorithms.tournament.is_tournament.html +++ b/reference/algorithms/generated/networkx.algorithms.tournament.is_tournament.html @@ -666,7 +666,7 @@ the convention used here.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tournament.random_tournament.html b/reference/algorithms/generated/networkx.algorithms.tournament.random_tournament.html index 9f169681..f87c8561 100644 --- a/reference/algorithms/generated/networkx.algorithms.tournament.random_tournament.html +++ b/reference/algorithms/generated/networkx.algorithms.tournament.random_tournament.html @@ -662,7 +662,7 @@ graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tournament.score_sequence.html b/reference/algorithms/generated/networkx.algorithms.tournament.score_sequence.html index 1cdae9c2..5bf4d6bc 100644 --- a/reference/algorithms/generated/networkx.algorithms.tournament.score_sequence.html +++ b/reference/algorithms/generated/networkx.algorithms.tournament.score_sequence.html @@ -662,7 +662,7 @@ nodes of the graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.traversal.beamsearch.bfs_beam_edges.html b/reference/algorithms/generated/networkx.algorithms.traversal.beamsearch.bfs_beam_edges.html index 4dcac653..cc147438 100644 --- a/reference/algorithms/generated/networkx.algorithms.traversal.beamsearch.bfs_beam_edges.html +++ b/reference/algorithms/generated/networkx.algorithms.traversal.beamsearch.bfs_beam_edges.html @@ -701,7 +701,7 @@ value of the node:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_edges.html b/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_edges.html index 0e75ba50..d58c107c 100644 --- a/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_edges.html +++ b/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_edges.html @@ -713,7 +713,7 @@ as described in <a class="reference internal" href="#reccb7b97bcd5-2" id="id2">[ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_layers.html b/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_layers.html index 4477f3dd..467075bc 100644 --- a/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_layers.html +++ b/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_layers.html @@ -667,7 +667,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_predecessors.html b/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_predecessors.html index 7434357d..1c8822fb 100644 --- a/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_predecessors.html +++ b/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_predecessors.html @@ -693,7 +693,7 @@ to allow depth limits based on the Wikipedia article <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_successors.html b/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_successors.html index 304cca29..c9a0e473 100644 --- a/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_successors.html +++ b/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_successors.html @@ -693,7 +693,7 @@ to allow depth limits based on the Wikipedia article <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_tree.html b/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_tree.html index 7fca2a5d..c21cc80c 100644 --- a/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_tree.html +++ b/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.bfs_tree.html @@ -686,7 +686,7 @@ to allow depth limits based on the Wikipedia article <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.descendants_at_distance.html b/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.descendants_at_distance.html index fac7cbe4..31fb386d 100644 --- a/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.descendants_at_distance.html +++ b/reference/algorithms/generated/networkx.algorithms.traversal.breadth_first_search.descendants_at_distance.html @@ -669,7 +669,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_edges.html b/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_edges.html index 3aace4d4..2c3ab867 100644 --- a/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_edges.html +++ b/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_edges.html @@ -696,7 +696,7 @@ to allow depth limits based on the Wikipedia article <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_labeled_edges.html b/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_labeled_edges.html index f4b7f0b8..b665562c 100644 --- a/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_labeled_edges.html +++ b/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_labeled_edges.html @@ -698,7 +698,7 @@ algorithm in more detail than, for example, <a class="reference internal" href=" <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_postorder_nodes.html b/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_postorder_nodes.html index 37ff1633..ec25a668 100644 --- a/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_postorder_nodes.html +++ b/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_postorder_nodes.html @@ -681,7 +681,7 @@ to allow depth limits based on the Wikipedia article <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_predecessors.html b/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_predecessors.html index cf59d1b3..6b898484 100644 --- a/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_predecessors.html +++ b/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_predecessors.html @@ -681,7 +681,7 @@ to allow depth limits based on the Wikipedia article <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_preorder_nodes.html b/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_preorder_nodes.html index e2cc0d43..6205d826 100644 --- a/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_preorder_nodes.html +++ b/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_preorder_nodes.html @@ -681,7 +681,7 @@ to allow depth limits based on the Wikipedia article <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_successors.html b/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_successors.html index d544f29e..e22d925e 100644 --- a/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_successors.html +++ b/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_successors.html @@ -681,7 +681,7 @@ to allow depth limits based on the Wikipedia article <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_tree.html b/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_tree.html index c5fb5771..ee67a200 100644 --- a/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_tree.html +++ b/reference/algorithms/generated/networkx.algorithms.traversal.depth_first_search.dfs_tree.html @@ -676,7 +676,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.traversal.edgebfs.edge_bfs.html b/reference/algorithms/generated/networkx.algorithms.traversal.edgebfs.edge_bfs.html index 2ae66ea1..3baa9bc7 100644 --- a/reference/algorithms/generated/networkx.algorithms.traversal.edgebfs.edge_bfs.html +++ b/reference/algorithms/generated/networkx.algorithms.traversal.edgebfs.edge_bfs.html @@ -728,7 +728,7 @@ while ‘edge_bfs’ reports all edges in the order they are explored.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.traversal.edgedfs.edge_dfs.html b/reference/algorithms/generated/networkx.algorithms.traversal.edgedfs.edge_dfs.html index 739e045f..b5f7bbbe 100644 --- a/reference/algorithms/generated/networkx.algorithms.traversal.edgedfs.edge_dfs.html +++ b/reference/algorithms/generated/networkx.algorithms.traversal.edgedfs.edge_dfs.html @@ -718,7 +718,7 @@ if not for the functionality provided by this function.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.branchings.ArborescenceIterator.html b/reference/algorithms/generated/networkx.algorithms.tree.branchings.ArborescenceIterator.html index c66611f6..cdcb44b0 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.branchings.ArborescenceIterator.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.branchings.ArborescenceIterator.html @@ -696,7 +696,7 @@ the arborescences, <code class="xref py py-obj docutils literal notranslate"><sp <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.branchings.Edmonds.html b/reference/algorithms/generated/networkx.algorithms.tree.branchings.Edmonds.html index 227f6ab5..89418806 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.branchings.Edmonds.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.branchings.Edmonds.html @@ -679,7 +679,7 @@ Bureau of Standards, 1967, Vol. 71B, p.233-240, <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.branchings.branching_weight.html b/reference/algorithms/generated/networkx.algorithms.tree.branchings.branching_weight.html index 88fee247..8ccc7d3c 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.branchings.branching_weight.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.branchings.branching_weight.html @@ -667,7 +667,7 @@ treated equally with a weight of 1.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.branchings.greedy_branching.html b/reference/algorithms/generated/networkx.algorithms.tree.branchings.greedy_branching.html index 58837e65..3ca8d006 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.branchings.greedy_branching.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.branchings.greedy_branching.html @@ -669,7 +669,7 @@ See <a class="reference internal" href="../../randomness.html#randomness"><span <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.branchings.maximum_branching.html b/reference/algorithms/generated/networkx.algorithms.tree.branchings.maximum_branching.html index 2f03aadb..0646ceb9 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.branchings.maximum_branching.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.branchings.maximum_branching.html @@ -665,7 +665,7 @@ data on the graph. Edges can be included, excluded or open using the <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.branchings.maximum_spanning_arborescence.html b/reference/algorithms/generated/networkx.algorithms.tree.branchings.maximum_spanning_arborescence.html index c571a655..1b7951dd 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.branchings.maximum_spanning_arborescence.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.branchings.maximum_spanning_arborescence.html @@ -671,7 +671,7 @@ data on the graph. Edges can be included, excluded or open using the <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.branchings.minimum_branching.html b/reference/algorithms/generated/networkx.algorithms.tree.branchings.minimum_branching.html index 58e6d6f5..f9a50db0 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.branchings.minimum_branching.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.branchings.minimum_branching.html @@ -665,7 +665,7 @@ data on the graph. Edges can be included, excluded or open using the <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.branchings.minimum_spanning_arborescence.html b/reference/algorithms/generated/networkx.algorithms.tree.branchings.minimum_spanning_arborescence.html index b5594d13..830a826d 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.branchings.minimum_spanning_arborescence.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.branchings.minimum_spanning_arborescence.html @@ -671,7 +671,7 @@ data on the graph. Edges can be included, excluded or open using the <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.coding.NotATree.html b/reference/algorithms/generated/networkx.algorithms.tree.coding.NotATree.html index 760de62b..1135b423 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.coding.NotATree.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.coding.NotATree.html @@ -641,7 +641,7 @@ instead.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.coding.from_nested_tuple.html b/reference/algorithms/generated/networkx.algorithms.tree.coding.from_nested_tuple.html index e54b87be..abe84b6c 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.coding.from_nested_tuple.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.coding.from_nested_tuple.html @@ -685,7 +685,7 @@ starting at 0:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.coding.from_prufer_sequence.html b/reference/algorithms/generated/networkx.algorithms.tree.coding.from_prufer_sequence.html index 383cdf77..ac3b5501 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.coding.from_prufer_sequence.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.coding.from_prufer_sequence.html @@ -700,7 +700,7 @@ function:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.coding.to_nested_tuple.html b/reference/algorithms/generated/networkx.algorithms.tree.coding.to_nested_tuple.html index f3765a01..912bb293 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.coding.to_nested_tuple.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.coding.to_nested_tuple.html @@ -700,7 +700,7 @@ nested tuples will be sorted:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.coding.to_prufer_sequence.html b/reference/algorithms/generated/networkx.algorithms.tree.coding.to_prufer_sequence.html index c30253ba..74b40ece 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.coding.to_prufer_sequence.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.coding.to_prufer_sequence.html @@ -710,7 +710,7 @@ function:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.decomposition.junction_tree.html b/reference/algorithms/generated/networkx.algorithms.tree.decomposition.junction_tree.html index fb4bb741..d0689647 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.decomposition.junction_tree.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.decomposition.junction_tree.html @@ -692,7 +692,7 @@ Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 360–366.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.mst.SpanningTreeIterator.html b/reference/algorithms/generated/networkx.algorithms.tree.mst.SpanningTreeIterator.html index 3ec077ed..e11668e9 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.mst.SpanningTreeIterator.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.mst.SpanningTreeIterator.html @@ -693,7 +693,7 @@ If <code class="xref py py-obj docutils literal notranslate"><span class="pre">i <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.mst.maximum_spanning_edges.html b/reference/algorithms/generated/networkx.algorithms.tree.mst.maximum_spanning_edges.html index 723a76f6..988f6903 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.mst.maximum_spanning_edges.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.mst.maximum_spanning_edges.html @@ -707,7 +707,7 @@ attribute a default weight of 1 will be used.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.mst.maximum_spanning_tree.html b/reference/algorithms/generated/networkx.algorithms.tree.mst.maximum_spanning_tree.html index cecf4254..eae803c9 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.mst.maximum_spanning_tree.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.mst.maximum_spanning_tree.html @@ -679,7 +679,7 @@ See <code class="xref py py-mod docutils literal notranslate"><span class="pre"> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.mst.minimum_spanning_edges.html b/reference/algorithms/generated/networkx.algorithms.tree.mst.minimum_spanning_edges.html index 81420e45..807e104f 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.mst.minimum_spanning_edges.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.mst.minimum_spanning_edges.html @@ -707,7 +707,7 @@ attribute a default weight of 1 will be used.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.mst.minimum_spanning_tree.html b/reference/algorithms/generated/networkx.algorithms.tree.mst.minimum_spanning_tree.html index b9c49e87..98cf041e 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.mst.minimum_spanning_tree.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.mst.minimum_spanning_tree.html @@ -679,7 +679,7 @@ See <code class="xref py py-mod docutils literal notranslate"><span class="pre"> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.mst.random_spanning_tree.html b/reference/algorithms/generated/networkx.algorithms.tree.mst.random_spanning_tree.html index ec47ebc6..af86f3e9 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.mst.random_spanning_tree.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.mst.random_spanning_tree.html @@ -680,7 +680,7 @@ Algorithms, 11 (1990), pp. 185–207</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.operations.join.html b/reference/algorithms/generated/networkx.algorithms.tree.operations.join.html index 49a53bee..32179347 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.operations.join.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.operations.join.html @@ -681,7 +681,7 @@ balanced binary tree of depth <em>h</em> + 1:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.recognition.is_arborescence.html b/reference/algorithms/generated/networkx.algorithms.tree.recognition.is_arborescence.html index 22d40ccd..e58fa3df 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.recognition.is_arborescence.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.recognition.is_arborescence.html @@ -672,7 +672,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.recognition.is_branching.html b/reference/algorithms/generated/networkx.algorithms.tree.recognition.is_branching.html index 8fede871..db51b164 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.recognition.is_branching.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.recognition.is_branching.html @@ -672,7 +672,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.recognition.is_forest.html b/reference/algorithms/generated/networkx.algorithms.tree.recognition.is_forest.html index 0fba0647..32b66b12 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.recognition.is_forest.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.recognition.is_forest.html @@ -682,7 +682,7 @@ then <em>forest</em> corresponds to a <em>branching</em>.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.tree.recognition.is_tree.html b/reference/algorithms/generated/networkx.algorithms.tree.recognition.is_tree.html index e5749c11..fa922f47 100644 --- a/reference/algorithms/generated/networkx.algorithms.tree.recognition.is_tree.html +++ b/reference/algorithms/generated/networkx.algorithms.tree.recognition.is_tree.html @@ -682,7 +682,7 @@ undirected edge in a multigraph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.triads.all_triads.html b/reference/algorithms/generated/networkx.algorithms.triads.all_triads.html index 11698833..e38cd9ec 100644 --- a/reference/algorithms/generated/networkx.algorithms.triads.all_triads.html +++ b/reference/algorithms/generated/networkx.algorithms.triads.all_triads.html @@ -663,7 +663,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.triads.all_triplets.html b/reference/algorithms/generated/networkx.algorithms.triads.all_triplets.html index d7ef31fb..f40bf61b 100644 --- a/reference/algorithms/generated/networkx.algorithms.triads.all_triplets.html +++ b/reference/algorithms/generated/networkx.algorithms.triads.all_triplets.html @@ -659,7 +659,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.triads.is_triad.html b/reference/algorithms/generated/networkx.algorithms.triads.is_triad.html index 9c5f595e..682de859 100644 --- a/reference/algorithms/generated/networkx.algorithms.triads.is_triad.html +++ b/reference/algorithms/generated/networkx.algorithms.triads.is_triad.html @@ -662,7 +662,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.triads.random_triad.html b/reference/algorithms/generated/networkx.algorithms.triads.random_triad.html index d16814ef..cd986c7d 100644 --- a/reference/algorithms/generated/networkx.algorithms.triads.random_triad.html +++ b/reference/algorithms/generated/networkx.algorithms.triads.random_triad.html @@ -663,7 +663,7 @@ See <a class="reference internal" href="../../randomness.html#randomness"><span <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.triads.triad_type.html b/reference/algorithms/generated/networkx.algorithms.triads.triad_type.html index 5c099cce..428b12a1 100644 --- a/reference/algorithms/generated/networkx.algorithms.triads.triad_type.html +++ b/reference/algorithms/generated/networkx.algorithms.triads.triad_type.html @@ -689,7 +689,7 @@ Oxford. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.triads.triadic_census.html b/reference/algorithms/generated/networkx.algorithms.triads.triadic_census.html index f0112cd7..74eb66a2 100644 --- a/reference/algorithms/generated/networkx.algorithms.triads.triadic_census.html +++ b/reference/algorithms/generated/networkx.algorithms.triads.triadic_census.html @@ -709,7 +709,7 @@ University of Ljubljana, <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.triads.triads_by_type.html b/reference/algorithms/generated/networkx.algorithms.triads.triads_by_type.html index c35c99c1..21724dd5 100644 --- a/reference/algorithms/generated/networkx.algorithms.triads.triads_by_type.html +++ b/reference/algorithms/generated/networkx.algorithms.triads.triads_by_type.html @@ -694,7 +694,7 @@ Oxford. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.vitality.closeness_vitality.html b/reference/algorithms/generated/networkx.algorithms.vitality.closeness_vitality.html index 76d1f167..cce03c51 100644 --- a/reference/algorithms/generated/networkx.algorithms.vitality.closeness_vitality.html +++ b/reference/algorithms/generated/networkx.algorithms.vitality.closeness_vitality.html @@ -698,7 +698,7 @@ Springer, 2005. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.voronoi.voronoi_cells.html b/reference/algorithms/generated/networkx.algorithms.voronoi.voronoi_cells.html index d4c6d7c4..569a2655 100644 --- a/reference/algorithms/generated/networkx.algorithms.voronoi.voronoi_cells.html +++ b/reference/algorithms/generated/networkx.algorithms.voronoi.voronoi_cells.html @@ -702,7 +702,7 @@ take the collection of all values in the returned dictionary:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/generated/networkx.algorithms.wiener.wiener_index.html b/reference/algorithms/generated/networkx.algorithms.wiener.wiener_index.html index 4d5ae9ba..45abdcf7 100644 --- a/reference/algorithms/generated/networkx.algorithms.wiener.wiener_index.html +++ b/reference/algorithms/generated/networkx.algorithms.wiener.wiener_index.html @@ -688,7 +688,7 @@ nodes is at distance one:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/graph_hashing.html b/reference/algorithms/graph_hashing.html index 4721ab14..5d2112b3 100644 --- a/reference/algorithms/graph_hashing.html +++ b/reference/algorithms/graph_hashing.html @@ -625,7 +625,7 @@ For now, only Weisfeiler-Lehman hashing is implemented.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/graphical.html b/reference/algorithms/graphical.html index 747ec46f..2c596274 100644 --- a/reference/algorithms/graphical.html +++ b/reference/algorithms/graphical.html @@ -635,7 +635,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/hierarchy.html b/reference/algorithms/hierarchy.html index 584a4709..e78d69e7 100644 --- a/reference/algorithms/hierarchy.html +++ b/reference/algorithms/hierarchy.html @@ -620,7 +620,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/hybrid.html b/reference/algorithms/hybrid.html index 7775fd5b..24fade9b 100644 --- a/reference/algorithms/hybrid.html +++ b/reference/algorithms/hybrid.html @@ -624,7 +624,7 @@ graphs.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/index.html b/reference/algorithms/index.html index 1416f035..58ae5e29 100644 --- a/reference/algorithms/index.html +++ b/reference/algorithms/index.html @@ -1157,7 +1157,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/isolates.html b/reference/algorithms/isolates.html index 93a776ee..f464aeda 100644 --- a/reference/algorithms/isolates.html +++ b/reference/algorithms/isolates.html @@ -626,7 +626,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/isomorphism.html b/reference/algorithms/isomorphism.html index 58b5253c..a30d3194 100644 --- a/reference/algorithms/isomorphism.html +++ b/reference/algorithms/isomorphism.html @@ -791,7 +791,7 @@ by Matthew Suderman <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/isomorphism.ismags.html b/reference/algorithms/isomorphism.ismags.html index d80d49f2..39e63e04 100644 --- a/reference/algorithms/isomorphism.ismags.html +++ b/reference/algorithms/isomorphism.ismags.html @@ -764,7 +764,7 @@ Enumeration”, PLoS One 9(5): e97896, 2014. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/isomorphism.vf2.html b/reference/algorithms/isomorphism.vf2.html index b71d26cd..99e3da1d 100644 --- a/reference/algorithms/isomorphism.vf2.html +++ b/reference/algorithms/isomorphism.vf2.html @@ -890,7 +890,7 @@ polynomial-time algorithm is known to exist).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/link_analysis.html b/reference/algorithms/link_analysis.html index 3a83a5ad..669b78af 100644 --- a/reference/algorithms/link_analysis.html +++ b/reference/algorithms/link_analysis.html @@ -659,7 +659,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/link_prediction.html b/reference/algorithms/link_prediction.html index 401940c8..d60091d9 100644 --- a/reference/algorithms/link_prediction.html +++ b/reference/algorithms/link_prediction.html @@ -641,7 +641,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/lowest_common_ancestors.html b/reference/algorithms/lowest_common_ancestors.html index c5f0065a..ca7144b6 100644 --- a/reference/algorithms/lowest_common_ancestors.html +++ b/reference/algorithms/lowest_common_ancestors.html @@ -626,7 +626,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/matching.html b/reference/algorithms/matching.html index 78b67098..e14c16aa 100644 --- a/reference/algorithms/matching.html +++ b/reference/algorithms/matching.html @@ -635,7 +635,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/minors.html b/reference/algorithms/minors.html index 599c08b2..91a35a74 100644 --- a/reference/algorithms/minors.html +++ b/reference/algorithms/minors.html @@ -661,7 +661,7 @@ can be formed from G by deleting edges and vertices and by contracting edges <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/mis.html b/reference/algorithms/mis.html index 559a857a..e942e8ff 100644 --- a/reference/algorithms/mis.html +++ b/reference/algorithms/mis.html @@ -620,7 +620,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/moral.html b/reference/algorithms/moral.html index c69472ca..c802989e 100644 --- a/reference/algorithms/moral.html +++ b/reference/algorithms/moral.html @@ -620,7 +620,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/node_classification.html b/reference/algorithms/node_classification.html index 3784d073..70ee0f64 100644 --- a/reference/algorithms/node_classification.html +++ b/reference/algorithms/node_classification.html @@ -662,7 +662,7 @@ In ICML (Vol. 3, pp. 912-919).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/non_randomness.html b/reference/algorithms/non_randomness.html index 343d2256..eb925902 100644 --- a/reference/algorithms/non_randomness.html +++ b/reference/algorithms/non_randomness.html @@ -620,7 +620,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/operators.html b/reference/algorithms/operators.html index 4a5c9c44..02b8cd65 100644 --- a/reference/algorithms/operators.html +++ b/reference/algorithms/operators.html @@ -692,7 +692,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/planar_drawing.html b/reference/algorithms/planar_drawing.html index e4337c2d..c46b1565 100644 --- a/reference/algorithms/planar_drawing.html +++ b/reference/algorithms/planar_drawing.html @@ -619,7 +619,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/planarity.html b/reference/algorithms/planarity.html index 26c78117..8f44b226 100644 --- a/reference/algorithms/planarity.html +++ b/reference/algorithms/planarity.html @@ -625,7 +625,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/polynomials.html b/reference/algorithms/polynomials.html index 662bc2e1..a38dc0ea 100644 --- a/reference/algorithms/polynomials.html +++ b/reference/algorithms/polynomials.html @@ -646,7 +646,7 @@ matrix of a graph. Consider the complete graph <code class="docutils literal not <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/reciprocity.html b/reference/algorithms/reciprocity.html index 51492cdc..c6df96c2 100644 --- a/reference/algorithms/reciprocity.html +++ b/reference/algorithms/reciprocity.html @@ -623,7 +623,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/regular.html b/reference/algorithms/regular.html index 5e5063de..0cb98ac1 100644 --- a/reference/algorithms/regular.html +++ b/reference/algorithms/regular.html @@ -626,7 +626,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/rich_club.html b/reference/algorithms/rich_club.html index 3fbe98ce..8834a270 100644 --- a/reference/algorithms/rich_club.html +++ b/reference/algorithms/rich_club.html @@ -620,7 +620,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/shortest_paths.html b/reference/algorithms/shortest_paths.html index 3e8b0904..692774f5 100644 --- a/reference/algorithms/shortest_paths.html +++ b/reference/algorithms/shortest_paths.html @@ -808,7 +808,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/similarity.html b/reference/algorithms/similarity.html index 8f62e9e1..0a263e74 100644 --- a/reference/algorithms/similarity.html +++ b/reference/algorithms/similarity.html @@ -647,7 +647,7 @@ alternative GED algorithms, in order to improve the choices available.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/simple_paths.html b/reference/algorithms/simple_paths.html index 90b04d98..b39f1af4 100644 --- a/reference/algorithms/simple_paths.html +++ b/reference/algorithms/simple_paths.html @@ -628,7 +628,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/smallworld.html b/reference/algorithms/smallworld.html index be64305b..d498a1b7 100644 --- a/reference/algorithms/smallworld.html +++ b/reference/algorithms/smallworld.html @@ -642,7 +642,7 @@ or lattice graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/smetric.html b/reference/algorithms/smetric.html index 8dbff0cc..fb902e2c 100644 --- a/reference/algorithms/smetric.html +++ b/reference/algorithms/smetric.html @@ -619,7 +619,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/sparsifiers.html b/reference/algorithms/sparsifiers.html index 01b37227..72dfe1e5 100644 --- a/reference/algorithms/sparsifiers.html +++ b/reference/algorithms/sparsifiers.html @@ -620,7 +620,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/structuralholes.html b/reference/algorithms/structuralholes.html index fefadd64..f0282dcd 100644 --- a/reference/algorithms/structuralholes.html +++ b/reference/algorithms/structuralholes.html @@ -626,7 +626,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/summarization.html b/reference/algorithms/summarization.html index 3886eca6..5d32a0b8 100644 --- a/reference/algorithms/summarization.html +++ b/reference/algorithms/summarization.html @@ -674,7 +674,7 @@ and Applications: A Survey</a></p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/swap.html b/reference/algorithms/swap.html index a399f170..3aa58858 100644 --- a/reference/algorithms/swap.html +++ b/reference/algorithms/swap.html @@ -626,7 +626,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/threshold.html b/reference/algorithms/threshold.html index b57c233e..15352527 100644 --- a/reference/algorithms/threshold.html +++ b/reference/algorithms/threshold.html @@ -623,7 +623,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/tournament.html b/reference/algorithms/tournament.html index 63990749..2c3d6076 100644 --- a/reference/algorithms/tournament.html +++ b/reference/algorithms/tournament.html @@ -649,7 +649,7 @@ graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/traversal.html b/reference/algorithms/traversal.html index 8fddb159..7a2afc46 100644 --- a/reference/algorithms/traversal.html +++ b/reference/algorithms/traversal.html @@ -739,7 +739,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/tree.html b/reference/algorithms/tree.html index 4e28debd..59505e07 100644 --- a/reference/algorithms/tree.html +++ b/reference/algorithms/tree.html @@ -877,7 +877,7 @@ sequences to labeled trees.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/triads.html b/reference/algorithms/triads.html index 8df00e07..bc0d3ee3 100644 --- a/reference/algorithms/triads.html +++ b/reference/algorithms/triads.html @@ -638,7 +638,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/vitality.html b/reference/algorithms/vitality.html index 9e1550ee..df5d0379 100644 --- a/reference/algorithms/vitality.html +++ b/reference/algorithms/vitality.html @@ -620,7 +620,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/voronoi.html b/reference/algorithms/voronoi.html index 13cfb47c..81282393 100644 --- a/reference/algorithms/voronoi.html +++ b/reference/algorithms/voronoi.html @@ -620,7 +620,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/algorithms/wiener.html b/reference/algorithms/wiener.html index 8314b653..f79fb4db 100644 --- a/reference/algorithms/wiener.html +++ b/reference/algorithms/wiener.html @@ -620,7 +620,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/digraph.html b/reference/classes/digraph.html index cfe83ad1..f9e5566e 100644 --- a/reference/classes/digraph.html +++ b/reference/classes/digraph.html @@ -1020,7 +1020,7 @@ This reduces the memory used, but you lose edge attributes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.copy.html b/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.copy.html index 732368f7..34928788 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.copy.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.copy.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.get.html b/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.get.html index be742edf..ccaacfcf 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.get.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.get.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.items.html b/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.items.html index d42fbe54..a79afdd6 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.items.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.items.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.keys.html b/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.keys.html index 16a796df..780f9f1e 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.keys.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.keys.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.values.html b/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.values.html index e03cc3ea..6929d5c6 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.values.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.AdjacencyView.values.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.copy.html b/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.copy.html index ab37a4ee..9a487ddb 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.copy.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.copy.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.get.html b/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.get.html index 97014686..9425725a 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.get.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.get.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.items.html b/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.items.html index f02a8c76..525aa821 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.items.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.items.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.keys.html b/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.keys.html index ad1ed4d7..7d15ee27 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.keys.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.keys.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.values.html b/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.values.html index bbc7c222..4ac2e227 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.values.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.AtlasView.values.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.FilterAdjacency.get.html b/reference/classes/generated/generated/networkx.classes.coreviews.FilterAdjacency.get.html index 916f5575..2cb6fda3 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.FilterAdjacency.get.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.FilterAdjacency.get.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.FilterAdjacency.items.html b/reference/classes/generated/generated/networkx.classes.coreviews.FilterAdjacency.items.html index 7b22258a..55f7dcd8 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.FilterAdjacency.items.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.FilterAdjacency.items.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.FilterAdjacency.keys.html b/reference/classes/generated/generated/networkx.classes.coreviews.FilterAdjacency.keys.html index 5fec3ff1..c002a482 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.FilterAdjacency.keys.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.FilterAdjacency.keys.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.FilterAdjacency.values.html b/reference/classes/generated/generated/networkx.classes.coreviews.FilterAdjacency.values.html index 9ff9fb29..eb01da36 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.FilterAdjacency.values.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.FilterAdjacency.values.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.FilterAtlas.get.html b/reference/classes/generated/generated/networkx.classes.coreviews.FilterAtlas.get.html index 7d471d65..383a611e 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.FilterAtlas.get.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.FilterAtlas.get.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.FilterAtlas.items.html b/reference/classes/generated/generated/networkx.classes.coreviews.FilterAtlas.items.html index 69c14039..62822a9f 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.FilterAtlas.items.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.FilterAtlas.items.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.FilterAtlas.keys.html b/reference/classes/generated/generated/networkx.classes.coreviews.FilterAtlas.keys.html index 0b61ec39..8dcfa53e 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.FilterAtlas.keys.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.FilterAtlas.keys.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.FilterAtlas.values.html b/reference/classes/generated/generated/networkx.classes.coreviews.FilterAtlas.values.html index a3d2bb84..bb985f70 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.FilterAtlas.values.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.FilterAtlas.values.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiAdjacency.get.html b/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiAdjacency.get.html index 2a2cc376..73da0e32 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiAdjacency.get.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiAdjacency.get.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiAdjacency.items.html b/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiAdjacency.items.html index ef9edcf0..bf105fa7 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiAdjacency.items.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiAdjacency.items.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiAdjacency.keys.html b/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiAdjacency.keys.html index e793b28f..5d4fb3da 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiAdjacency.keys.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiAdjacency.keys.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiAdjacency.values.html b/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiAdjacency.values.html index 2f5e5e63..29bef589 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiAdjacency.values.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiAdjacency.values.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiInner.get.html b/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiInner.get.html index 632fc04f..da620064 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiInner.get.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiInner.get.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiInner.items.html b/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiInner.items.html index 5f6d2c7b..b4ca7329 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiInner.items.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiInner.items.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiInner.keys.html b/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiInner.keys.html index 32631993..bf3b7f3f 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiInner.keys.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiInner.keys.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiInner.values.html b/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiInner.values.html index b545be8a..e01c4652 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiInner.values.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.FilterMultiInner.values.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.copy.html b/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.copy.html index 2b7aa9c4..abad92fa 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.copy.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.copy.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.get.html b/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.get.html index 6f73f162..62e00a3a 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.get.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.get.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.items.html b/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.items.html index 57088002..0e7ee4d0 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.items.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.items.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.keys.html b/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.keys.html index 86bd10b1..145fcc06 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.keys.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.keys.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.values.html b/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.values.html index f0d06e78..448b59f1 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.values.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.MultiAdjacencyView.values.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.copy.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.copy.html index 865d0ab4..3bedb01f 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.copy.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.copy.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.get.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.get.html index c8874dea..6e10ae7a 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.get.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.get.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.items.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.items.html index 0d87fe0b..f5d1eb3a 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.items.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.items.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.keys.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.keys.html index 69486ec7..577a4bfb 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.keys.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.keys.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.values.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.values.html index 24459b5f..e956b11f 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.values.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAdjacency.values.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.copy.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.copy.html index 684567de..af5e6a4f 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.copy.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.copy.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.get.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.get.html index 456419d5..51afcfe3 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.get.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.get.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.items.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.items.html index 30fbb329..862a8a3f 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.items.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.items.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.keys.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.keys.html index 7cfb117f..d7c9692d 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.keys.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.keys.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.values.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.values.html index 328edda7..85e615e9 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.values.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionAtlas.values.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.copy.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.copy.html index 712a9248..1e71d4e0 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.copy.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.copy.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.get.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.get.html index b3d8b30b..2b02b298 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.get.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.get.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.items.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.items.html index e672b9eb..2660dbe1 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.items.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.items.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.keys.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.keys.html index e502e3cc..55982867 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.keys.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.keys.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.values.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.values.html index 65156b47..9444deb0 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.values.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiAdjacency.values.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.copy.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.copy.html index 0b6464bd..6242105e 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.copy.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.copy.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.get.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.get.html index 645f7eaa..6e9e0e36 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.get.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.get.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.items.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.items.html index 76b70e50..97c716d9 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.items.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.items.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.keys.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.keys.html index daf5c685..808618ee 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.keys.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.keys.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.values.html b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.values.html index 5516d9e2..d3aa99b5 100644 --- a/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.values.html +++ b/reference/classes/generated/generated/networkx.classes.coreviews.UnionMultiInner.values.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.__contains__.html b/reference/classes/generated/networkx.DiGraph.__contains__.html index dae01456..820b535a 100644 --- a/reference/classes/generated/networkx.DiGraph.__contains__.html +++ b/reference/classes/generated/networkx.DiGraph.__contains__.html @@ -607,7 +607,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.__getitem__.html b/reference/classes/generated/networkx.DiGraph.__getitem__.html index 5207de62..dedcff9a 100644 --- a/reference/classes/generated/networkx.DiGraph.__getitem__.html +++ b/reference/classes/generated/networkx.DiGraph.__getitem__.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.__init__.html b/reference/classes/generated/networkx.DiGraph.__init__.html index b898ae85..6860b576 100644 --- a/reference/classes/generated/networkx.DiGraph.__init__.html +++ b/reference/classes/generated/networkx.DiGraph.__init__.html @@ -634,7 +634,7 @@ SciPy sparse array, or a PyGraphviz graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.__iter__.html b/reference/classes/generated/networkx.DiGraph.__iter__.html index 73b80d21..8e58411f 100644 --- a/reference/classes/generated/networkx.DiGraph.__iter__.html +++ b/reference/classes/generated/networkx.DiGraph.__iter__.html @@ -617,7 +617,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.__len__.html b/reference/classes/generated/networkx.DiGraph.__len__.html index f17ba879..a0be0ac2 100644 --- a/reference/classes/generated/networkx.DiGraph.__len__.html +++ b/reference/classes/generated/networkx.DiGraph.__len__.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.add_edge.html b/reference/classes/generated/networkx.DiGraph.add_edge.html index 849ed6ef..b9bf0549 100644 --- a/reference/classes/generated/networkx.DiGraph.add_edge.html +++ b/reference/classes/generated/networkx.DiGraph.add_edge.html @@ -648,7 +648,7 @@ an edge attribute (by default <code class="xref py py-obj docutils literal notra <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.add_edges_from.html b/reference/classes/generated/networkx.DiGraph.add_edges_from.html index df2b76eb..9922945e 100644 --- a/reference/classes/generated/networkx.DiGraph.add_edges_from.html +++ b/reference/classes/generated/networkx.DiGraph.add_edges_from.html @@ -656,7 +656,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.add_node.html b/reference/classes/generated/networkx.DiGraph.add_node.html index 3589b0f7..84567ea9 100644 --- a/reference/classes/generated/networkx.DiGraph.add_node.html +++ b/reference/classes/generated/networkx.DiGraph.add_node.html @@ -639,7 +639,7 @@ doesn’t change on mutables.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.add_nodes_from.html b/reference/classes/generated/networkx.DiGraph.add_nodes_from.html index b1d9dabe..08c68a86 100644 --- a/reference/classes/generated/networkx.DiGraph.add_nodes_from.html +++ b/reference/classes/generated/networkx.DiGraph.add_nodes_from.html @@ -662,7 +662,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.add_weighted_edges_from.html b/reference/classes/generated/networkx.DiGraph.add_weighted_edges_from.html index e0fcaddc..5330c1b5 100644 --- a/reference/classes/generated/networkx.DiGraph.add_weighted_edges_from.html +++ b/reference/classes/generated/networkx.DiGraph.add_weighted_edges_from.html @@ -650,7 +650,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.adj.html b/reference/classes/generated/networkx.DiGraph.adj.html index e8a51651..90899f99 100644 --- a/reference/classes/generated/networkx.DiGraph.adj.html +++ b/reference/classes/generated/networkx.DiGraph.adj.html @@ -610,7 +610,7 @@ So <code class="xref py py-obj docutils literal notranslate"><span class="pre">f <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.adjacency.html b/reference/classes/generated/networkx.DiGraph.adjacency.html index 63e6fa6c..ee087710 100644 --- a/reference/classes/generated/networkx.DiGraph.adjacency.html +++ b/reference/classes/generated/networkx.DiGraph.adjacency.html @@ -617,7 +617,7 @@ the graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.clear.html b/reference/classes/generated/networkx.DiGraph.clear.html index f236e164..d533b6a0 100644 --- a/reference/classes/generated/networkx.DiGraph.clear.html +++ b/reference/classes/generated/networkx.DiGraph.clear.html @@ -611,7 +611,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.clear_edges.html b/reference/classes/generated/networkx.DiGraph.clear_edges.html index 059f4948..cbab1a16 100644 --- a/reference/classes/generated/networkx.DiGraph.clear_edges.html +++ b/reference/classes/generated/networkx.DiGraph.clear_edges.html @@ -610,7 +610,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.copy.html b/reference/classes/generated/networkx.DiGraph.copy.html index 9c8c50f6..5e9016e6 100644 --- a/reference/classes/generated/networkx.DiGraph.copy.html +++ b/reference/classes/generated/networkx.DiGraph.copy.html @@ -673,7 +673,7 @@ and deep copies, <a class="reference external" href="https://docs.python.org/3/l <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.degree.html b/reference/classes/generated/networkx.DiGraph.degree.html index bc613ff4..75874d02 100644 --- a/reference/classes/generated/networkx.DiGraph.degree.html +++ b/reference/classes/generated/networkx.DiGraph.degree.html @@ -641,7 +641,7 @@ If a single node is requested, returns the degree of the node as an integer.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.edge_subgraph.html b/reference/classes/generated/networkx.DiGraph.edge_subgraph.html index 3eb841fb..ef3e2ab3 100644 --- a/reference/classes/generated/networkx.DiGraph.edge_subgraph.html +++ b/reference/classes/generated/networkx.DiGraph.edge_subgraph.html @@ -636,7 +636,7 @@ of the edge or node attributes, use:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.edges.html b/reference/classes/generated/networkx.DiGraph.edges.html index aaf050ea..be90f7bd 100644 --- a/reference/classes/generated/networkx.DiGraph.edges.html +++ b/reference/classes/generated/networkx.DiGraph.edges.html @@ -659,7 +659,7 @@ For directed graphs this returns the out-edges.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.get_edge_data.html b/reference/classes/generated/networkx.DiGraph.get_edge_data.html index 68cdf621..611235ca 100644 --- a/reference/classes/generated/networkx.DiGraph.get_edge_data.html +++ b/reference/classes/generated/networkx.DiGraph.get_edge_data.html @@ -643,7 +643,7 @@ But it is safe to assign attributes <code class="xref py py-obj docutils literal <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.has_edge.html b/reference/classes/generated/networkx.DiGraph.has_edge.html index 6b52d077..0eb68985 100644 --- a/reference/classes/generated/networkx.DiGraph.has_edge.html +++ b/reference/classes/generated/networkx.DiGraph.has_edge.html @@ -636,7 +636,7 @@ Nodes must be hashable (and not None) Python objects.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.has_node.html b/reference/classes/generated/networkx.DiGraph.has_node.html index 29ec67c3..216047c5 100644 --- a/reference/classes/generated/networkx.DiGraph.has_node.html +++ b/reference/classes/generated/networkx.DiGraph.has_node.html @@ -620,7 +620,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.in_degree.html b/reference/classes/generated/networkx.DiGraph.in_degree.html index 0623f2c6..a4fe1a8b 100644 --- a/reference/classes/generated/networkx.DiGraph.in_degree.html +++ b/reference/classes/generated/networkx.DiGraph.in_degree.html @@ -643,7 +643,7 @@ The degree is the sum of the edge weights adjacent to the node.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.in_edges.html b/reference/classes/generated/networkx.DiGraph.in_edges.html index b229c85a..c8bda365 100644 --- a/reference/classes/generated/networkx.DiGraph.in_edges.html +++ b/reference/classes/generated/networkx.DiGraph.in_edges.html @@ -656,7 +656,7 @@ attribute lookup as <code class="xref py py-obj docutils literal notranslate"><s <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.nbunch_iter.html b/reference/classes/generated/networkx.DiGraph.nbunch_iter.html index 526d111a..a03e182f 100644 --- a/reference/classes/generated/networkx.DiGraph.nbunch_iter.html +++ b/reference/classes/generated/networkx.DiGraph.nbunch_iter.html @@ -640,7 +640,7 @@ nbunch is not hashable, a <a class="reference internal" href="../../exceptions.h <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.neighbors.html b/reference/classes/generated/networkx.DiGraph.neighbors.html index cb59ea89..646cfec8 100644 --- a/reference/classes/generated/networkx.DiGraph.neighbors.html +++ b/reference/classes/generated/networkx.DiGraph.neighbors.html @@ -625,7 +625,7 @@ edge from n to m.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.nodes.html b/reference/classes/generated/networkx.DiGraph.nodes.html index 3fb81ef3..c1774e78 100644 --- a/reference/classes/generated/networkx.DiGraph.nodes.html +++ b/reference/classes/generated/networkx.DiGraph.nodes.html @@ -688,7 +688,7 @@ to guarantee the value is never None:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.number_of_edges.html b/reference/classes/generated/networkx.DiGraph.number_of_edges.html index 5a4c52fe..5250bf67 100644 --- a/reference/classes/generated/networkx.DiGraph.number_of_edges.html +++ b/reference/classes/generated/networkx.DiGraph.number_of_edges.html @@ -648,7 +648,7 @@ directed edges from <code class="xref py py-obj docutils literal notranslate"><s <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.number_of_nodes.html b/reference/classes/generated/networkx.DiGraph.number_of_nodes.html index 31ede758..121bc425 100644 --- a/reference/classes/generated/networkx.DiGraph.number_of_nodes.html +++ b/reference/classes/generated/networkx.DiGraph.number_of_nodes.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.order.html b/reference/classes/generated/networkx.DiGraph.order.html index 96266c4c..11309768 100644 --- a/reference/classes/generated/networkx.DiGraph.order.html +++ b/reference/classes/generated/networkx.DiGraph.order.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.out_degree.html b/reference/classes/generated/networkx.DiGraph.out_degree.html index 381b4b21..a66a6691 100644 --- a/reference/classes/generated/networkx.DiGraph.out_degree.html +++ b/reference/classes/generated/networkx.DiGraph.out_degree.html @@ -643,7 +643,7 @@ The degree is the sum of the edge weights adjacent to the node.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.out_edges.html b/reference/classes/generated/networkx.DiGraph.out_edges.html index dce530aa..d5a3f908 100644 --- a/reference/classes/generated/networkx.DiGraph.out_edges.html +++ b/reference/classes/generated/networkx.DiGraph.out_edges.html @@ -659,7 +659,7 @@ For directed graphs this returns the out-edges.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.pred.html b/reference/classes/generated/networkx.DiGraph.pred.html index f455e3b6..c90e275f 100644 --- a/reference/classes/generated/networkx.DiGraph.pred.html +++ b/reference/classes/generated/networkx.DiGraph.pred.html @@ -609,7 +609,7 @@ A default can be set via a <code class="xref py py-obj docutils literal notransl <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.predecessors.html b/reference/classes/generated/networkx.DiGraph.predecessors.html index 986a3f5d..5fd576f1 100644 --- a/reference/classes/generated/networkx.DiGraph.predecessors.html +++ b/reference/classes/generated/networkx.DiGraph.predecessors.html @@ -623,7 +623,7 @@ edge from m to n.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.remove_edge.html b/reference/classes/generated/networkx.DiGraph.remove_edge.html index 0e1ffa40..dd7335a8 100644 --- a/reference/classes/generated/networkx.DiGraph.remove_edge.html +++ b/reference/classes/generated/networkx.DiGraph.remove_edge.html @@ -632,7 +632,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.remove_edges_from.html b/reference/classes/generated/networkx.DiGraph.remove_edges_from.html index cdcfcea1..833a54c6 100644 --- a/reference/classes/generated/networkx.DiGraph.remove_edges_from.html +++ b/reference/classes/generated/networkx.DiGraph.remove_edges_from.html @@ -631,7 +631,7 @@ from the graph. The edges can be:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.remove_node.html b/reference/classes/generated/networkx.DiGraph.remove_node.html index 6f74422c..4ab1b40f 100644 --- a/reference/classes/generated/networkx.DiGraph.remove_node.html +++ b/reference/classes/generated/networkx.DiGraph.remove_node.html @@ -632,7 +632,7 @@ Attempting to remove a non-existent node will raise an exception.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.remove_nodes_from.html b/reference/classes/generated/networkx.DiGraph.remove_nodes_from.html index 8ac877e9..33ef243c 100644 --- a/reference/classes/generated/networkx.DiGraph.remove_nodes_from.html +++ b/reference/classes/generated/networkx.DiGraph.remove_nodes_from.html @@ -642,7 +642,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.reverse.html b/reference/classes/generated/networkx.DiGraph.reverse.html index 5c9697f2..eb0bff8d 100644 --- a/reference/classes/generated/networkx.DiGraph.reverse.html +++ b/reference/classes/generated/networkx.DiGraph.reverse.html @@ -613,7 +613,7 @@ the original graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.size.html b/reference/classes/generated/networkx.DiGraph.size.html index e50f7ba9..18537279 100644 --- a/reference/classes/generated/networkx.DiGraph.size.html +++ b/reference/classes/generated/networkx.DiGraph.size.html @@ -640,7 +640,7 @@ as a weight. If None, then each edge has weight 1.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.subgraph.html b/reference/classes/generated/networkx.DiGraph.subgraph.html index d160f299..4cee5832 100644 --- a/reference/classes/generated/networkx.DiGraph.subgraph.html +++ b/reference/classes/generated/networkx.DiGraph.subgraph.html @@ -652,7 +652,7 @@ more sense to just create the subgraph as its own graph with code like:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.succ.html b/reference/classes/generated/networkx.DiGraph.succ.html index 576641a5..05b56d8c 100644 --- a/reference/classes/generated/networkx.DiGraph.succ.html +++ b/reference/classes/generated/networkx.DiGraph.succ.html @@ -612,7 +612,7 @@ So <code class="xref py py-obj docutils literal notranslate"><span class="pre">f <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.successors.html b/reference/classes/generated/networkx.DiGraph.successors.html index 179ca9e0..bbd52cf9 100644 --- a/reference/classes/generated/networkx.DiGraph.successors.html +++ b/reference/classes/generated/networkx.DiGraph.successors.html @@ -625,7 +625,7 @@ edge from n to m.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.to_directed.html b/reference/classes/generated/networkx.DiGraph.to_directed.html index 1b0758ed..17a84600 100644 --- a/reference/classes/generated/networkx.DiGraph.to_directed.html +++ b/reference/classes/generated/networkx.DiGraph.to_directed.html @@ -638,7 +638,7 @@ DiGraph created by this method.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.to_undirected.html b/reference/classes/generated/networkx.DiGraph.to_undirected.html index 0357b937..fc59eb54 100644 --- a/reference/classes/generated/networkx.DiGraph.to_undirected.html +++ b/reference/classes/generated/networkx.DiGraph.to_undirected.html @@ -655,7 +655,7 @@ Graph created by this method.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.DiGraph.update.html b/reference/classes/generated/networkx.DiGraph.update.html index 1cfceb0b..e1e91987 100644 --- a/reference/classes/generated/networkx.DiGraph.update.html +++ b/reference/classes/generated/networkx.DiGraph.update.html @@ -701,7 +701,7 @@ be slightly different and require tweaks of these examples:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.__contains__.html b/reference/classes/generated/networkx.Graph.__contains__.html index bbbd17c9..2fc84bbc 100644 --- a/reference/classes/generated/networkx.Graph.__contains__.html +++ b/reference/classes/generated/networkx.Graph.__contains__.html @@ -607,7 +607,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.__getitem__.html b/reference/classes/generated/networkx.Graph.__getitem__.html index 930c9074..7a1a1f69 100644 --- a/reference/classes/generated/networkx.Graph.__getitem__.html +++ b/reference/classes/generated/networkx.Graph.__getitem__.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.__init__.html b/reference/classes/generated/networkx.Graph.__init__.html index 12c06573..d8936d5d 100644 --- a/reference/classes/generated/networkx.Graph.__init__.html +++ b/reference/classes/generated/networkx.Graph.__init__.html @@ -634,7 +634,7 @@ SciPy sparse array, or a PyGraphviz graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.__iter__.html b/reference/classes/generated/networkx.Graph.__iter__.html index 9cfad235..266da33a 100644 --- a/reference/classes/generated/networkx.Graph.__iter__.html +++ b/reference/classes/generated/networkx.Graph.__iter__.html @@ -617,7 +617,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.__len__.html b/reference/classes/generated/networkx.Graph.__len__.html index 603787f0..a1c89e68 100644 --- a/reference/classes/generated/networkx.Graph.__len__.html +++ b/reference/classes/generated/networkx.Graph.__len__.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.add_edge.html b/reference/classes/generated/networkx.Graph.add_edge.html index 5031f3d9..97e6540d 100644 --- a/reference/classes/generated/networkx.Graph.add_edge.html +++ b/reference/classes/generated/networkx.Graph.add_edge.html @@ -648,7 +648,7 @@ an edge attribute (by default <code class="xref py py-obj docutils literal notra <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.add_edges_from.html b/reference/classes/generated/networkx.Graph.add_edges_from.html index d48e90f6..a266f8b0 100644 --- a/reference/classes/generated/networkx.Graph.add_edges_from.html +++ b/reference/classes/generated/networkx.Graph.add_edges_from.html @@ -656,7 +656,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.add_node.html b/reference/classes/generated/networkx.Graph.add_node.html index 524b4a59..17680514 100644 --- a/reference/classes/generated/networkx.Graph.add_node.html +++ b/reference/classes/generated/networkx.Graph.add_node.html @@ -639,7 +639,7 @@ doesn’t change on mutables.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.add_nodes_from.html b/reference/classes/generated/networkx.Graph.add_nodes_from.html index 8c48720c..d26876ab 100644 --- a/reference/classes/generated/networkx.Graph.add_nodes_from.html +++ b/reference/classes/generated/networkx.Graph.add_nodes_from.html @@ -662,7 +662,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.add_weighted_edges_from.html b/reference/classes/generated/networkx.Graph.add_weighted_edges_from.html index 7fc6d6b0..287591ad 100644 --- a/reference/classes/generated/networkx.Graph.add_weighted_edges_from.html +++ b/reference/classes/generated/networkx.Graph.add_weighted_edges_from.html @@ -650,7 +650,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.adj.html b/reference/classes/generated/networkx.Graph.adj.html index 49b2664e..4189d394 100644 --- a/reference/classes/generated/networkx.Graph.adj.html +++ b/reference/classes/generated/networkx.Graph.adj.html @@ -610,7 +610,7 @@ So <code class="xref py py-obj docutils literal notranslate"><span class="pre">f <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.adjacency.html b/reference/classes/generated/networkx.Graph.adjacency.html index 5e925f19..28057f4e 100644 --- a/reference/classes/generated/networkx.Graph.adjacency.html +++ b/reference/classes/generated/networkx.Graph.adjacency.html @@ -617,7 +617,7 @@ the graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.clear.html b/reference/classes/generated/networkx.Graph.clear.html index 44dcf8ad..ed681c3b 100644 --- a/reference/classes/generated/networkx.Graph.clear.html +++ b/reference/classes/generated/networkx.Graph.clear.html @@ -611,7 +611,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.clear_edges.html b/reference/classes/generated/networkx.Graph.clear_edges.html index ccc4e29b..e2d786a3 100644 --- a/reference/classes/generated/networkx.Graph.clear_edges.html +++ b/reference/classes/generated/networkx.Graph.clear_edges.html @@ -610,7 +610,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.copy.html b/reference/classes/generated/networkx.Graph.copy.html index 30484474..98857b4a 100644 --- a/reference/classes/generated/networkx.Graph.copy.html +++ b/reference/classes/generated/networkx.Graph.copy.html @@ -673,7 +673,7 @@ and deep copies, <a class="reference external" href="https://docs.python.org/3/l <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.degree.html b/reference/classes/generated/networkx.Graph.degree.html index 5a3a122c..1ef06e5b 100644 --- a/reference/classes/generated/networkx.Graph.degree.html +++ b/reference/classes/generated/networkx.Graph.degree.html @@ -634,7 +634,7 @@ If a single node is requested, returns the degree of the node as an integer.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.edge_subgraph.html b/reference/classes/generated/networkx.Graph.edge_subgraph.html index 78582f93..cc782b58 100644 --- a/reference/classes/generated/networkx.Graph.edge_subgraph.html +++ b/reference/classes/generated/networkx.Graph.edge_subgraph.html @@ -636,7 +636,7 @@ of the edge or node attributes, use:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.edges.html b/reference/classes/generated/networkx.Graph.edges.html index bae9268d..ce2181c1 100644 --- a/reference/classes/generated/networkx.Graph.edges.html +++ b/reference/classes/generated/networkx.Graph.edges.html @@ -652,7 +652,7 @@ For directed graphs this returns the out-edges.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.get_edge_data.html b/reference/classes/generated/networkx.Graph.get_edge_data.html index e0fff419..0547d4da 100644 --- a/reference/classes/generated/networkx.Graph.get_edge_data.html +++ b/reference/classes/generated/networkx.Graph.get_edge_data.html @@ -643,7 +643,7 @@ But it is safe to assign attributes <code class="xref py py-obj docutils literal <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.has_edge.html b/reference/classes/generated/networkx.Graph.has_edge.html index 6ec79418..cfe16c7b 100644 --- a/reference/classes/generated/networkx.Graph.has_edge.html +++ b/reference/classes/generated/networkx.Graph.has_edge.html @@ -636,7 +636,7 @@ Nodes must be hashable (and not None) Python objects.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.has_node.html b/reference/classes/generated/networkx.Graph.has_node.html index 8d28a23c..1ae205a5 100644 --- a/reference/classes/generated/networkx.Graph.has_node.html +++ b/reference/classes/generated/networkx.Graph.has_node.html @@ -620,7 +620,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.nbunch_iter.html b/reference/classes/generated/networkx.Graph.nbunch_iter.html index ded510a4..94cdfc7f 100644 --- a/reference/classes/generated/networkx.Graph.nbunch_iter.html +++ b/reference/classes/generated/networkx.Graph.nbunch_iter.html @@ -640,7 +640,7 @@ nbunch is not hashable, a <a class="reference internal" href="../../exceptions.h <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.neighbors.html b/reference/classes/generated/networkx.Graph.neighbors.html index 0c637831..e346e709 100644 --- a/reference/classes/generated/networkx.Graph.neighbors.html +++ b/reference/classes/generated/networkx.Graph.neighbors.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.nodes.html b/reference/classes/generated/networkx.Graph.nodes.html index 8e0f5a5a..64589676 100644 --- a/reference/classes/generated/networkx.Graph.nodes.html +++ b/reference/classes/generated/networkx.Graph.nodes.html @@ -688,7 +688,7 @@ to guarantee the value is never None:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.number_of_edges.html b/reference/classes/generated/networkx.Graph.number_of_edges.html index e0b29fff..f9e174f2 100644 --- a/reference/classes/generated/networkx.Graph.number_of_edges.html +++ b/reference/classes/generated/networkx.Graph.number_of_edges.html @@ -648,7 +648,7 @@ directed edges from <code class="xref py py-obj docutils literal notranslate"><s <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.number_of_nodes.html b/reference/classes/generated/networkx.Graph.number_of_nodes.html index 69ccfc54..81c1b7aa 100644 --- a/reference/classes/generated/networkx.Graph.number_of_nodes.html +++ b/reference/classes/generated/networkx.Graph.number_of_nodes.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.order.html b/reference/classes/generated/networkx.Graph.order.html index 4b52ad4a..3f8fab41 100644 --- a/reference/classes/generated/networkx.Graph.order.html +++ b/reference/classes/generated/networkx.Graph.order.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.remove_edge.html b/reference/classes/generated/networkx.Graph.remove_edge.html index 67193c65..2e412b61 100644 --- a/reference/classes/generated/networkx.Graph.remove_edge.html +++ b/reference/classes/generated/networkx.Graph.remove_edge.html @@ -631,7 +631,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.remove_edges_from.html b/reference/classes/generated/networkx.Graph.remove_edges_from.html index b096b870..f735f78d 100644 --- a/reference/classes/generated/networkx.Graph.remove_edges_from.html +++ b/reference/classes/generated/networkx.Graph.remove_edges_from.html @@ -631,7 +631,7 @@ from the graph. The edges can be:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.remove_node.html b/reference/classes/generated/networkx.Graph.remove_node.html index 2909e5e7..925ca0fe 100644 --- a/reference/classes/generated/networkx.Graph.remove_node.html +++ b/reference/classes/generated/networkx.Graph.remove_node.html @@ -632,7 +632,7 @@ Attempting to remove a non-existent node will raise an exception.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.remove_nodes_from.html b/reference/classes/generated/networkx.Graph.remove_nodes_from.html index b2cd0b0c..1ff5a4ec 100644 --- a/reference/classes/generated/networkx.Graph.remove_nodes_from.html +++ b/reference/classes/generated/networkx.Graph.remove_nodes_from.html @@ -643,7 +643,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.size.html b/reference/classes/generated/networkx.Graph.size.html index 19bf3bca..9bd84da0 100644 --- a/reference/classes/generated/networkx.Graph.size.html +++ b/reference/classes/generated/networkx.Graph.size.html @@ -640,7 +640,7 @@ as a weight. If None, then each edge has weight 1.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.subgraph.html b/reference/classes/generated/networkx.Graph.subgraph.html index be28ad29..ad891440 100644 --- a/reference/classes/generated/networkx.Graph.subgraph.html +++ b/reference/classes/generated/networkx.Graph.subgraph.html @@ -652,7 +652,7 @@ more sense to just create the subgraph as its own graph with code like:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.to_directed.html b/reference/classes/generated/networkx.Graph.to_directed.html index 964a5c64..10794684 100644 --- a/reference/classes/generated/networkx.Graph.to_directed.html +++ b/reference/classes/generated/networkx.Graph.to_directed.html @@ -638,7 +638,7 @@ DiGraph created by this method.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.to_undirected.html b/reference/classes/generated/networkx.Graph.to_undirected.html index b93db8f4..8edc7e98 100644 --- a/reference/classes/generated/networkx.Graph.to_undirected.html +++ b/reference/classes/generated/networkx.Graph.to_undirected.html @@ -642,7 +642,7 @@ Graph created by this method.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.Graph.update.html b/reference/classes/generated/networkx.Graph.update.html index 88d1b3e2..fdb55adc 100644 --- a/reference/classes/generated/networkx.Graph.update.html +++ b/reference/classes/generated/networkx.Graph.update.html @@ -701,7 +701,7 @@ be slightly different and require tweaks of these examples:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.__contains__.html b/reference/classes/generated/networkx.MultiDiGraph.__contains__.html index 8d84dd7e..7c31d327 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.__contains__.html +++ b/reference/classes/generated/networkx.MultiDiGraph.__contains__.html @@ -607,7 +607,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.__getitem__.html b/reference/classes/generated/networkx.MultiDiGraph.__getitem__.html index 736e2a7c..2a69b6ff 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.__getitem__.html +++ b/reference/classes/generated/networkx.MultiDiGraph.__getitem__.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.__init__.html b/reference/classes/generated/networkx.MultiDiGraph.__init__.html index c6a7749a..a682b4a7 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.__init__.html +++ b/reference/classes/generated/networkx.MultiDiGraph.__init__.html @@ -646,7 +646,7 @@ the treatment for False is tried.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.__iter__.html b/reference/classes/generated/networkx.MultiDiGraph.__iter__.html index 1a985377..03ef660e 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.__iter__.html +++ b/reference/classes/generated/networkx.MultiDiGraph.__iter__.html @@ -617,7 +617,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.__len__.html b/reference/classes/generated/networkx.MultiDiGraph.__len__.html index ac9ebb43..cac59723 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.__len__.html +++ b/reference/classes/generated/networkx.MultiDiGraph.__len__.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.add_edge.html b/reference/classes/generated/networkx.MultiDiGraph.add_edge.html index cfed7491..0c05138e 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.add_edge.html +++ b/reference/classes/generated/networkx.MultiDiGraph.add_edge.html @@ -664,7 +664,7 @@ providing a custom <a class="reference internal" href="networkx.MultiDiGraph.new <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.add_edges_from.html b/reference/classes/generated/networkx.MultiDiGraph.add_edges_from.html index 59fbf7d6..fb806968 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.add_edges_from.html +++ b/reference/classes/generated/networkx.MultiDiGraph.add_edges_from.html @@ -671,7 +671,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.add_node.html b/reference/classes/generated/networkx.MultiDiGraph.add_node.html index 55cf7b72..159483a9 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.add_node.html +++ b/reference/classes/generated/networkx.MultiDiGraph.add_node.html @@ -639,7 +639,7 @@ doesn’t change on mutables.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.add_nodes_from.html b/reference/classes/generated/networkx.MultiDiGraph.add_nodes_from.html index af855547..b082937f 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.add_nodes_from.html +++ b/reference/classes/generated/networkx.MultiDiGraph.add_nodes_from.html @@ -662,7 +662,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.add_weighted_edges_from.html b/reference/classes/generated/networkx.MultiDiGraph.add_weighted_edges_from.html index 8bc5c7b8..ac157752 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.add_weighted_edges_from.html +++ b/reference/classes/generated/networkx.MultiDiGraph.add_weighted_edges_from.html @@ -650,7 +650,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.adj.html b/reference/classes/generated/networkx.MultiDiGraph.adj.html index 01e61699..3fac22f5 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.adj.html +++ b/reference/classes/generated/networkx.MultiDiGraph.adj.html @@ -610,7 +610,7 @@ So <code class="xref py py-obj docutils literal notranslate"><span class="pre">f <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.adjacency.html b/reference/classes/generated/networkx.MultiDiGraph.adjacency.html index abb9fac0..b799d1bd 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.adjacency.html +++ b/reference/classes/generated/networkx.MultiDiGraph.adjacency.html @@ -617,7 +617,7 @@ the graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.clear.html b/reference/classes/generated/networkx.MultiDiGraph.clear.html index d6a315ae..e532386d 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.clear.html +++ b/reference/classes/generated/networkx.MultiDiGraph.clear.html @@ -611,7 +611,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.clear_edges.html b/reference/classes/generated/networkx.MultiDiGraph.clear_edges.html index 399cfe0d..ae525fef 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.clear_edges.html +++ b/reference/classes/generated/networkx.MultiDiGraph.clear_edges.html @@ -610,7 +610,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.copy.html b/reference/classes/generated/networkx.MultiDiGraph.copy.html index fc8e09bc..48c5605e 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.copy.html +++ b/reference/classes/generated/networkx.MultiDiGraph.copy.html @@ -673,7 +673,7 @@ and deep copies, <a class="reference external" href="https://docs.python.org/3/l <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.degree.html b/reference/classes/generated/networkx.MultiDiGraph.degree.html index a09eee04..b7891806 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.degree.html +++ b/reference/classes/generated/networkx.MultiDiGraph.degree.html @@ -645,7 +645,7 @@ If a single node is requested, returns the degree of the node as an integer.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.edge_subgraph.html b/reference/classes/generated/networkx.MultiDiGraph.edge_subgraph.html index aad90f2a..57482266 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.edge_subgraph.html +++ b/reference/classes/generated/networkx.MultiDiGraph.edge_subgraph.html @@ -636,7 +636,7 @@ of the edge or node attributes, use:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.edges.html b/reference/classes/generated/networkx.MultiDiGraph.edges.html index 33726c6f..e30c9061 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.edges.html +++ b/reference/classes/generated/networkx.MultiDiGraph.edges.html @@ -677,7 +677,7 @@ For directed graphs this returns the out-edges.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.get_edge_data.html b/reference/classes/generated/networkx.MultiDiGraph.get_edge_data.html index d9a18097..57c86063 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.get_edge_data.html +++ b/reference/classes/generated/networkx.MultiDiGraph.get_edge_data.html @@ -668,7 +668,7 @@ to assign to the edge data associated with an edge.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.has_edge.html b/reference/classes/generated/networkx.MultiDiGraph.has_edge.html index 4fb6a3d6..1569db76 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.has_edge.html +++ b/reference/classes/generated/networkx.MultiDiGraph.has_edge.html @@ -650,7 +650,7 @@ or an edge tuple (u, v, key).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.has_node.html b/reference/classes/generated/networkx.MultiDiGraph.has_node.html index da7e89e0..a4f250f3 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.has_node.html +++ b/reference/classes/generated/networkx.MultiDiGraph.has_node.html @@ -620,7 +620,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.in_degree.html b/reference/classes/generated/networkx.MultiDiGraph.in_degree.html index 0ad54f2e..8ad7b9d1 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.in_degree.html +++ b/reference/classes/generated/networkx.MultiDiGraph.in_degree.html @@ -647,7 +647,7 @@ The degree is the sum of the edge weights adjacent to the node.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.in_edges.html b/reference/classes/generated/networkx.MultiDiGraph.in_edges.html index 90834079..ca700539 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.in_edges.html +++ b/reference/classes/generated/networkx.MultiDiGraph.in_edges.html @@ -634,7 +634,7 @@ used for attribute lookup as <code class="xref py py-obj docutils literal notran <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.nbunch_iter.html b/reference/classes/generated/networkx.MultiDiGraph.nbunch_iter.html index 5c4e8504..1a37e246 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.nbunch_iter.html +++ b/reference/classes/generated/networkx.MultiDiGraph.nbunch_iter.html @@ -640,7 +640,7 @@ nbunch is not hashable, a <a class="reference internal" href="../../exceptions.h <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.neighbors.html b/reference/classes/generated/networkx.MultiDiGraph.neighbors.html index 7419a9fb..d56617ea 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.neighbors.html +++ b/reference/classes/generated/networkx.MultiDiGraph.neighbors.html @@ -625,7 +625,7 @@ edge from n to m.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.new_edge_key.html b/reference/classes/generated/networkx.MultiDiGraph.new_edge_key.html index aaeab2be..f0853602 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.new_edge_key.html +++ b/reference/classes/generated/networkx.MultiDiGraph.new_edge_key.html @@ -619,7 +619,7 @@ further new_edge_keys may not be in this order.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.nodes.html b/reference/classes/generated/networkx.MultiDiGraph.nodes.html index e86cc53f..f48c5b4d 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.nodes.html +++ b/reference/classes/generated/networkx.MultiDiGraph.nodes.html @@ -688,7 +688,7 @@ to guarantee the value is never None:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.number_of_edges.html b/reference/classes/generated/networkx.MultiDiGraph.number_of_edges.html index 64464fb3..5a4d8236 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.number_of_edges.html +++ b/reference/classes/generated/networkx.MultiDiGraph.number_of_edges.html @@ -652,7 +652,7 @@ of directed edges from <code class="xref py py-obj docutils literal notranslate" <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.number_of_nodes.html b/reference/classes/generated/networkx.MultiDiGraph.number_of_nodes.html index dd737e62..3357c953 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.number_of_nodes.html +++ b/reference/classes/generated/networkx.MultiDiGraph.number_of_nodes.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.order.html b/reference/classes/generated/networkx.MultiDiGraph.order.html index e6c89ef7..1ca6d339 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.order.html +++ b/reference/classes/generated/networkx.MultiDiGraph.order.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.out_degree.html b/reference/classes/generated/networkx.MultiDiGraph.out_degree.html index ac3b9e40..692cecc6 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.out_degree.html +++ b/reference/classes/generated/networkx.MultiDiGraph.out_degree.html @@ -646,7 +646,7 @@ The degree is the sum of the edge weights.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.out_edges.html b/reference/classes/generated/networkx.MultiDiGraph.out_edges.html index 51445130..3a2024ec 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.out_edges.html +++ b/reference/classes/generated/networkx.MultiDiGraph.out_edges.html @@ -677,7 +677,7 @@ For directed graphs this returns the out-edges.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.predecessors.html b/reference/classes/generated/networkx.MultiDiGraph.predecessors.html index 6a067090..126a97eb 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.predecessors.html +++ b/reference/classes/generated/networkx.MultiDiGraph.predecessors.html @@ -623,7 +623,7 @@ edge from m to n.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.remove_edge.html b/reference/classes/generated/networkx.MultiDiGraph.remove_edge.html index a21ae84e..2764b620 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.remove_edge.html +++ b/reference/classes/generated/networkx.MultiDiGraph.remove_edge.html @@ -660,7 +660,7 @@ order that they were added:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.remove_edges_from.html b/reference/classes/generated/networkx.MultiDiGraph.remove_edges_from.html index 69388839..5e1d787d 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.remove_edges_from.html +++ b/reference/classes/generated/networkx.MultiDiGraph.remove_edges_from.html @@ -656,7 +656,7 @@ order) is removed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.remove_node.html b/reference/classes/generated/networkx.MultiDiGraph.remove_node.html index 8f79eca6..b41ec5db 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.remove_node.html +++ b/reference/classes/generated/networkx.MultiDiGraph.remove_node.html @@ -632,7 +632,7 @@ Attempting to remove a non-existent node will raise an exception.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.remove_nodes_from.html b/reference/classes/generated/networkx.MultiDiGraph.remove_nodes_from.html index 219dca45..98e32217 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.remove_nodes_from.html +++ b/reference/classes/generated/networkx.MultiDiGraph.remove_nodes_from.html @@ -642,7 +642,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.reverse.html b/reference/classes/generated/networkx.MultiDiGraph.reverse.html index 3f535a2b..8a7e1826 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.reverse.html +++ b/reference/classes/generated/networkx.MultiDiGraph.reverse.html @@ -613,7 +613,7 @@ the original graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.size.html b/reference/classes/generated/networkx.MultiDiGraph.size.html index 509c6373..036d37ae 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.size.html +++ b/reference/classes/generated/networkx.MultiDiGraph.size.html @@ -640,7 +640,7 @@ as a weight. If None, then each edge has weight 1.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.subgraph.html b/reference/classes/generated/networkx.MultiDiGraph.subgraph.html index a81922ee..863733e8 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.subgraph.html +++ b/reference/classes/generated/networkx.MultiDiGraph.subgraph.html @@ -652,7 +652,7 @@ more sense to just create the subgraph as its own graph with code like:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.succ.html b/reference/classes/generated/networkx.MultiDiGraph.succ.html index ae912191..58e74406 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.succ.html +++ b/reference/classes/generated/networkx.MultiDiGraph.succ.html @@ -610,7 +610,7 @@ So <code class="xref py py-obj docutils literal notranslate"><span class="pre">f <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.successors.html b/reference/classes/generated/networkx.MultiDiGraph.successors.html index 191909fd..54a4978b 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.successors.html +++ b/reference/classes/generated/networkx.MultiDiGraph.successors.html @@ -625,7 +625,7 @@ edge from n to m.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.to_directed.html b/reference/classes/generated/networkx.MultiDiGraph.to_directed.html index cbce83a1..dc418ef2 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.to_directed.html +++ b/reference/classes/generated/networkx.MultiDiGraph.to_directed.html @@ -642,7 +642,7 @@ MultiDiGraph created by this method.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.to_undirected.html b/reference/classes/generated/networkx.MultiDiGraph.to_undirected.html index 6fb4936a..7f912ac4 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.to_undirected.html +++ b/reference/classes/generated/networkx.MultiDiGraph.to_undirected.html @@ -650,7 +650,7 @@ to the MultiGraph created by this method.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiDiGraph.update.html b/reference/classes/generated/networkx.MultiDiGraph.update.html index d61ce151..3522d2d8 100644 --- a/reference/classes/generated/networkx.MultiDiGraph.update.html +++ b/reference/classes/generated/networkx.MultiDiGraph.update.html @@ -701,7 +701,7 @@ be slightly different and require tweaks of these examples:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.__contains__.html b/reference/classes/generated/networkx.MultiGraph.__contains__.html index 536e8612..fb0c30c7 100644 --- a/reference/classes/generated/networkx.MultiGraph.__contains__.html +++ b/reference/classes/generated/networkx.MultiGraph.__contains__.html @@ -607,7 +607,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.__getitem__.html b/reference/classes/generated/networkx.MultiGraph.__getitem__.html index d07a4a25..72d62286 100644 --- a/reference/classes/generated/networkx.MultiGraph.__getitem__.html +++ b/reference/classes/generated/networkx.MultiGraph.__getitem__.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.__init__.html b/reference/classes/generated/networkx.MultiGraph.__init__.html index f3bd1e9c..a8043d47 100644 --- a/reference/classes/generated/networkx.MultiGraph.__init__.html +++ b/reference/classes/generated/networkx.MultiGraph.__init__.html @@ -646,7 +646,7 @@ the treatment for False is tried.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.__iter__.html b/reference/classes/generated/networkx.MultiGraph.__iter__.html index 7360a2f0..9b2edc58 100644 --- a/reference/classes/generated/networkx.MultiGraph.__iter__.html +++ b/reference/classes/generated/networkx.MultiGraph.__iter__.html @@ -617,7 +617,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.__len__.html b/reference/classes/generated/networkx.MultiGraph.__len__.html index d93c7d0b..b526207e 100644 --- a/reference/classes/generated/networkx.MultiGraph.__len__.html +++ b/reference/classes/generated/networkx.MultiGraph.__len__.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.add_edge.html b/reference/classes/generated/networkx.MultiGraph.add_edge.html index b8f1e987..f7e98ddc 100644 --- a/reference/classes/generated/networkx.MultiGraph.add_edge.html +++ b/reference/classes/generated/networkx.MultiGraph.add_edge.html @@ -664,7 +664,7 @@ providing a custom <a class="reference internal" href="networkx.MultiGraph.new_e <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.add_edges_from.html b/reference/classes/generated/networkx.MultiGraph.add_edges_from.html index bf61c35e..106516d8 100644 --- a/reference/classes/generated/networkx.MultiGraph.add_edges_from.html +++ b/reference/classes/generated/networkx.MultiGraph.add_edges_from.html @@ -671,7 +671,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.add_node.html b/reference/classes/generated/networkx.MultiGraph.add_node.html index 962b6054..5efc4863 100644 --- a/reference/classes/generated/networkx.MultiGraph.add_node.html +++ b/reference/classes/generated/networkx.MultiGraph.add_node.html @@ -639,7 +639,7 @@ doesn’t change on mutables.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.add_nodes_from.html b/reference/classes/generated/networkx.MultiGraph.add_nodes_from.html index 06f5a351..1964c6ef 100644 --- a/reference/classes/generated/networkx.MultiGraph.add_nodes_from.html +++ b/reference/classes/generated/networkx.MultiGraph.add_nodes_from.html @@ -662,7 +662,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.add_weighted_edges_from.html b/reference/classes/generated/networkx.MultiGraph.add_weighted_edges_from.html index 4ec58875..0b06e95c 100644 --- a/reference/classes/generated/networkx.MultiGraph.add_weighted_edges_from.html +++ b/reference/classes/generated/networkx.MultiGraph.add_weighted_edges_from.html @@ -650,7 +650,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.adj.html b/reference/classes/generated/networkx.MultiGraph.adj.html index 576c1f1d..afd09a33 100644 --- a/reference/classes/generated/networkx.MultiGraph.adj.html +++ b/reference/classes/generated/networkx.MultiGraph.adj.html @@ -620,7 +620,7 @@ the color of the edge <code class="xref py py-obj docutils literal notranslate"> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.adjacency.html b/reference/classes/generated/networkx.MultiGraph.adjacency.html index 06f66344..b8584660 100644 --- a/reference/classes/generated/networkx.MultiGraph.adjacency.html +++ b/reference/classes/generated/networkx.MultiGraph.adjacency.html @@ -617,7 +617,7 @@ the graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.clear.html b/reference/classes/generated/networkx.MultiGraph.clear.html index 5e8f0d79..2113b855 100644 --- a/reference/classes/generated/networkx.MultiGraph.clear.html +++ b/reference/classes/generated/networkx.MultiGraph.clear.html @@ -611,7 +611,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.clear_edges.html b/reference/classes/generated/networkx.MultiGraph.clear_edges.html index 72b09a56..ac8eede6 100644 --- a/reference/classes/generated/networkx.MultiGraph.clear_edges.html +++ b/reference/classes/generated/networkx.MultiGraph.clear_edges.html @@ -610,7 +610,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.copy.html b/reference/classes/generated/networkx.MultiGraph.copy.html index 6c4a769d..8b2f499e 100644 --- a/reference/classes/generated/networkx.MultiGraph.copy.html +++ b/reference/classes/generated/networkx.MultiGraph.copy.html @@ -673,7 +673,7 @@ and deep copies, <a class="reference external" href="https://docs.python.org/3/l <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.degree.html b/reference/classes/generated/networkx.MultiGraph.degree.html index f3aa9ae9..42d7403a 100644 --- a/reference/classes/generated/networkx.MultiGraph.degree.html +++ b/reference/classes/generated/networkx.MultiGraph.degree.html @@ -635,7 +635,7 @@ If a single node is requested, returns the degree of the node as an integer.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.edge_subgraph.html b/reference/classes/generated/networkx.MultiGraph.edge_subgraph.html index db1bbc1b..b7115006 100644 --- a/reference/classes/generated/networkx.MultiGraph.edge_subgraph.html +++ b/reference/classes/generated/networkx.MultiGraph.edge_subgraph.html @@ -636,7 +636,7 @@ of the edge or node attributes, use:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.edges.html b/reference/classes/generated/networkx.MultiGraph.edges.html index 5a813d8e..1b87b9dd 100644 --- a/reference/classes/generated/networkx.MultiGraph.edges.html +++ b/reference/classes/generated/networkx.MultiGraph.edges.html @@ -670,7 +670,7 @@ For directed graphs this returns the out-edges.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.get_edge_data.html b/reference/classes/generated/networkx.MultiGraph.get_edge_data.html index 3d2557a1..774995df 100644 --- a/reference/classes/generated/networkx.MultiGraph.get_edge_data.html +++ b/reference/classes/generated/networkx.MultiGraph.get_edge_data.html @@ -668,7 +668,7 @@ to assign to the edge data associated with an edge.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.has_edge.html b/reference/classes/generated/networkx.MultiGraph.has_edge.html index 541fa107..dcdad4e9 100644 --- a/reference/classes/generated/networkx.MultiGraph.has_edge.html +++ b/reference/classes/generated/networkx.MultiGraph.has_edge.html @@ -650,7 +650,7 @@ or an edge tuple (u, v, key).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.has_node.html b/reference/classes/generated/networkx.MultiGraph.has_node.html index 20c0c2f9..cca75651 100644 --- a/reference/classes/generated/networkx.MultiGraph.has_node.html +++ b/reference/classes/generated/networkx.MultiGraph.has_node.html @@ -620,7 +620,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.nbunch_iter.html b/reference/classes/generated/networkx.MultiGraph.nbunch_iter.html index 06ce667c..d70631ed 100644 --- a/reference/classes/generated/networkx.MultiGraph.nbunch_iter.html +++ b/reference/classes/generated/networkx.MultiGraph.nbunch_iter.html @@ -640,7 +640,7 @@ nbunch is not hashable, a <a class="reference internal" href="../../exceptions.h <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.neighbors.html b/reference/classes/generated/networkx.MultiGraph.neighbors.html index c507bfdc..432a71a2 100644 --- a/reference/classes/generated/networkx.MultiGraph.neighbors.html +++ b/reference/classes/generated/networkx.MultiGraph.neighbors.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.new_edge_key.html b/reference/classes/generated/networkx.MultiGraph.new_edge_key.html index 0383f567..0b00d067 100644 --- a/reference/classes/generated/networkx.MultiGraph.new_edge_key.html +++ b/reference/classes/generated/networkx.MultiGraph.new_edge_key.html @@ -619,7 +619,7 @@ further new_edge_keys may not be in this order.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.nodes.html b/reference/classes/generated/networkx.MultiGraph.nodes.html index e96a89c9..796583eb 100644 --- a/reference/classes/generated/networkx.MultiGraph.nodes.html +++ b/reference/classes/generated/networkx.MultiGraph.nodes.html @@ -688,7 +688,7 @@ to guarantee the value is never None:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.number_of_edges.html b/reference/classes/generated/networkx.MultiGraph.number_of_edges.html index a26843a7..3faf7083 100644 --- a/reference/classes/generated/networkx.MultiGraph.number_of_edges.html +++ b/reference/classes/generated/networkx.MultiGraph.number_of_edges.html @@ -652,7 +652,7 @@ of directed edges from <code class="xref py py-obj docutils literal notranslate" <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.number_of_nodes.html b/reference/classes/generated/networkx.MultiGraph.number_of_nodes.html index 6f51ae65..8bc7d4b2 100644 --- a/reference/classes/generated/networkx.MultiGraph.number_of_nodes.html +++ b/reference/classes/generated/networkx.MultiGraph.number_of_nodes.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.order.html b/reference/classes/generated/networkx.MultiGraph.order.html index c187071e..344dc1af 100644 --- a/reference/classes/generated/networkx.MultiGraph.order.html +++ b/reference/classes/generated/networkx.MultiGraph.order.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.remove_edge.html b/reference/classes/generated/networkx.MultiGraph.remove_edge.html index f2efcf9f..debf74f6 100644 --- a/reference/classes/generated/networkx.MultiGraph.remove_edge.html +++ b/reference/classes/generated/networkx.MultiGraph.remove_edge.html @@ -663,7 +663,7 @@ order that they were added:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.remove_edges_from.html b/reference/classes/generated/networkx.MultiGraph.remove_edges_from.html index 9cb698eb..6878bfd2 100644 --- a/reference/classes/generated/networkx.MultiGraph.remove_edges_from.html +++ b/reference/classes/generated/networkx.MultiGraph.remove_edges_from.html @@ -656,7 +656,7 @@ order) is removed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.remove_node.html b/reference/classes/generated/networkx.MultiGraph.remove_node.html index 7898ab7f..e2ea8c16 100644 --- a/reference/classes/generated/networkx.MultiGraph.remove_node.html +++ b/reference/classes/generated/networkx.MultiGraph.remove_node.html @@ -632,7 +632,7 @@ Attempting to remove a non-existent node will raise an exception.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.remove_nodes_from.html b/reference/classes/generated/networkx.MultiGraph.remove_nodes_from.html index 9f56c443..4c997785 100644 --- a/reference/classes/generated/networkx.MultiGraph.remove_nodes_from.html +++ b/reference/classes/generated/networkx.MultiGraph.remove_nodes_from.html @@ -643,7 +643,7 @@ object to <code class="xref py py-obj docutils literal notranslate"><span class= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.size.html b/reference/classes/generated/networkx.MultiGraph.size.html index fb3e0acd..3f9937bf 100644 --- a/reference/classes/generated/networkx.MultiGraph.size.html +++ b/reference/classes/generated/networkx.MultiGraph.size.html @@ -640,7 +640,7 @@ as a weight. If None, then each edge has weight 1.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.subgraph.html b/reference/classes/generated/networkx.MultiGraph.subgraph.html index 4b8b5357..f23efd76 100644 --- a/reference/classes/generated/networkx.MultiGraph.subgraph.html +++ b/reference/classes/generated/networkx.MultiGraph.subgraph.html @@ -652,7 +652,7 @@ more sense to just create the subgraph as its own graph with code like:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.to_directed.html b/reference/classes/generated/networkx.MultiGraph.to_directed.html index 7af9b88a..c44feb39 100644 --- a/reference/classes/generated/networkx.MultiGraph.to_directed.html +++ b/reference/classes/generated/networkx.MultiGraph.to_directed.html @@ -642,7 +642,7 @@ MultiDiGraph created by this method.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.to_undirected.html b/reference/classes/generated/networkx.MultiGraph.to_undirected.html index a1109902..28f2d8b2 100644 --- a/reference/classes/generated/networkx.MultiGraph.to_undirected.html +++ b/reference/classes/generated/networkx.MultiGraph.to_undirected.html @@ -636,7 +636,7 @@ to the MultiGraph created by this method.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.MultiGraph.update.html b/reference/classes/generated/networkx.MultiGraph.update.html index a705200a..aab3cac6 100644 --- a/reference/classes/generated/networkx.MultiGraph.update.html +++ b/reference/classes/generated/networkx.MultiGraph.update.html @@ -701,7 +701,7 @@ be slightly different and require tweaks of these examples:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.backends._dispatch.html b/reference/classes/generated/networkx.classes.backends._dispatch.html index 876a540c..b8d7b4d6 100644 --- a/reference/classes/generated/networkx.classes.backends._dispatch.html +++ b/reference/classes/generated/networkx.classes.backends._dispatch.html @@ -602,7 +602,7 @@ when the first argument is a backend graph-like object.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.coreviews.AdjacencyView.html b/reference/classes/generated/networkx.classes.coreviews.AdjacencyView.html index 430d512f..252a96f4 100644 --- a/reference/classes/generated/networkx.classes.coreviews.AdjacencyView.html +++ b/reference/classes/generated/networkx.classes.coreviews.AdjacencyView.html @@ -649,7 +649,7 @@ outer levels are read-only.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.coreviews.AtlasView.html b/reference/classes/generated/networkx.classes.coreviews.AtlasView.html index ae07e107..6f7f13f5 100644 --- a/reference/classes/generated/networkx.classes.coreviews.AtlasView.html +++ b/reference/classes/generated/networkx.classes.coreviews.AtlasView.html @@ -649,7 +649,7 @@ outer level is read-only.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.coreviews.FilterAdjacency.html b/reference/classes/generated/networkx.classes.coreviews.FilterAdjacency.html index 5f4d8aeb..4859f7da 100644 --- a/reference/classes/generated/networkx.classes.coreviews.FilterAdjacency.html +++ b/reference/classes/generated/networkx.classes.coreviews.FilterAdjacency.html @@ -633,7 +633,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.coreviews.FilterAtlas.html b/reference/classes/generated/networkx.classes.coreviews.FilterAtlas.html index de5a4293..f028ba94 100644 --- a/reference/classes/generated/networkx.classes.coreviews.FilterAtlas.html +++ b/reference/classes/generated/networkx.classes.coreviews.FilterAtlas.html @@ -633,7 +633,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.coreviews.FilterMultiAdjacency.html b/reference/classes/generated/networkx.classes.coreviews.FilterMultiAdjacency.html index 865de9c0..cffddc39 100644 --- a/reference/classes/generated/networkx.classes.coreviews.FilterMultiAdjacency.html +++ b/reference/classes/generated/networkx.classes.coreviews.FilterMultiAdjacency.html @@ -633,7 +633,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.coreviews.FilterMultiInner.html b/reference/classes/generated/networkx.classes.coreviews.FilterMultiInner.html index a4839f8f..85fc48e0 100644 --- a/reference/classes/generated/networkx.classes.coreviews.FilterMultiInner.html +++ b/reference/classes/generated/networkx.classes.coreviews.FilterMultiInner.html @@ -633,7 +633,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.coreviews.MultiAdjacencyView.html b/reference/classes/generated/networkx.classes.coreviews.MultiAdjacencyView.html index e29d39a6..96faacd7 100644 --- a/reference/classes/generated/networkx.classes.coreviews.MultiAdjacencyView.html +++ b/reference/classes/generated/networkx.classes.coreviews.MultiAdjacencyView.html @@ -649,7 +649,7 @@ outer levels are read-only.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.coreviews.UnionAdjacency.html b/reference/classes/generated/networkx.classes.coreviews.UnionAdjacency.html index 3529454d..953fdedc 100644 --- a/reference/classes/generated/networkx.classes.coreviews.UnionAdjacency.html +++ b/reference/classes/generated/networkx.classes.coreviews.UnionAdjacency.html @@ -653,7 +653,7 @@ The keys for the two dicts should be the same</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.coreviews.UnionAtlas.html b/reference/classes/generated/networkx.classes.coreviews.UnionAtlas.html index 90021028..a6504f73 100644 --- a/reference/classes/generated/networkx.classes.coreviews.UnionAtlas.html +++ b/reference/classes/generated/networkx.classes.coreviews.UnionAtlas.html @@ -650,7 +650,7 @@ pairs and is read-write. But the outer level is read-only.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.coreviews.UnionMultiAdjacency.html b/reference/classes/generated/networkx.classes.coreviews.UnionMultiAdjacency.html index 59227120..8a2c74a0 100644 --- a/reference/classes/generated/networkx.classes.coreviews.UnionMultiAdjacency.html +++ b/reference/classes/generated/networkx.classes.coreviews.UnionMultiAdjacency.html @@ -649,7 +649,7 @@ The inner level of dict is read-write. But the outer levels are read-only.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.coreviews.UnionMultiInner.html b/reference/classes/generated/networkx.classes.coreviews.UnionMultiInner.html index 2d9c0732..74b72de0 100644 --- a/reference/classes/generated/networkx.classes.coreviews.UnionMultiInner.html +++ b/reference/classes/generated/networkx.classes.coreviews.UnionMultiInner.html @@ -652,7 +652,7 @@ The inner level of dict is read-write. But the outer levels are read-only.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.filters.hide_diedges.html b/reference/classes/generated/networkx.classes.filters.hide_diedges.html index 819ae515..74b16b84 100644 --- a/reference/classes/generated/networkx.classes.filters.hide_diedges.html +++ b/reference/classes/generated/networkx.classes.filters.hide_diedges.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.filters.hide_edges.html b/reference/classes/generated/networkx.classes.filters.hide_edges.html index b72cad9a..b48ea75a 100644 --- a/reference/classes/generated/networkx.classes.filters.hide_edges.html +++ b/reference/classes/generated/networkx.classes.filters.hide_edges.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.filters.hide_multidiedges.html b/reference/classes/generated/networkx.classes.filters.hide_multidiedges.html index 2f660eb2..3b1c1912 100644 --- a/reference/classes/generated/networkx.classes.filters.hide_multidiedges.html +++ b/reference/classes/generated/networkx.classes.filters.hide_multidiedges.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.filters.hide_multiedges.html b/reference/classes/generated/networkx.classes.filters.hide_multiedges.html index 2fd97a12..6bcaf924 100644 --- a/reference/classes/generated/networkx.classes.filters.hide_multiedges.html +++ b/reference/classes/generated/networkx.classes.filters.hide_multiedges.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.filters.hide_nodes.html b/reference/classes/generated/networkx.classes.filters.hide_nodes.html index 247f4909..f13ddf32 100644 --- a/reference/classes/generated/networkx.classes.filters.hide_nodes.html +++ b/reference/classes/generated/networkx.classes.filters.hide_nodes.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.filters.no_filter.html b/reference/classes/generated/networkx.classes.filters.no_filter.html index 9e5dced1..e61b6d34 100644 --- a/reference/classes/generated/networkx.classes.filters.no_filter.html +++ b/reference/classes/generated/networkx.classes.filters.no_filter.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.filters.show_diedges.html b/reference/classes/generated/networkx.classes.filters.show_diedges.html index 2884fad6..ce991d2a 100644 --- a/reference/classes/generated/networkx.classes.filters.show_diedges.html +++ b/reference/classes/generated/networkx.classes.filters.show_diedges.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.filters.show_edges.html b/reference/classes/generated/networkx.classes.filters.show_edges.html index 07301b86..73d73cac 100644 --- a/reference/classes/generated/networkx.classes.filters.show_edges.html +++ b/reference/classes/generated/networkx.classes.filters.show_edges.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.filters.show_multidiedges.html b/reference/classes/generated/networkx.classes.filters.show_multidiedges.html index 2a35a3a5..fca53139 100644 --- a/reference/classes/generated/networkx.classes.filters.show_multidiedges.html +++ b/reference/classes/generated/networkx.classes.filters.show_multidiedges.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.filters.show_multiedges.html b/reference/classes/generated/networkx.classes.filters.show_multiedges.html index b8e72901..f2d46a03 100644 --- a/reference/classes/generated/networkx.classes.filters.show_multiedges.html +++ b/reference/classes/generated/networkx.classes.filters.show_multiedges.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.filters.show_nodes.html b/reference/classes/generated/networkx.classes.filters.show_nodes.html index f6fb8b12..84124f8e 100644 --- a/reference/classes/generated/networkx.classes.filters.show_nodes.html +++ b/reference/classes/generated/networkx.classes.filters.show_nodes.html @@ -621,7 +621,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.graphviews.generic_graph_view.html b/reference/classes/generated/networkx.classes.graphviews.generic_graph_view.html index 21f89bb3..358c7e89 100644 --- a/reference/classes/generated/networkx.classes.graphviews.generic_graph_view.html +++ b/reference/classes/generated/networkx.classes.graphviews.generic_graph_view.html @@ -600,7 +600,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.graphviews.reverse_view.html b/reference/classes/generated/networkx.classes.graphviews.reverse_view.html index ed4e75c3..04ea4aa9 100644 --- a/reference/classes/generated/networkx.classes.graphviews.reverse_view.html +++ b/reference/classes/generated/networkx.classes.graphviews.reverse_view.html @@ -629,7 +629,7 @@ edge directions are reversed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/generated/networkx.classes.graphviews.subgraph_view.html b/reference/classes/generated/networkx.classes.graphviews.subgraph_view.html index b8da0488..9f1d4397 100644 --- a/reference/classes/generated/networkx.classes.graphviews.subgraph_view.html +++ b/reference/classes/generated/networkx.classes.graphviews.subgraph_view.html @@ -666,7 +666,7 @@ data — for example, filtering on edge data attached to the graph:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/graph.html b/reference/classes/graph.html index ea32493b..c68ce943 100644 --- a/reference/classes/graph.html +++ b/reference/classes/graph.html @@ -991,7 +991,7 @@ This reduces the memory used, but you lose edge attributes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/index.html b/reference/classes/index.html index 71f79ad4..09a6ca77 100644 --- a/reference/classes/index.html +++ b/reference/classes/index.html @@ -893,7 +893,7 @@ test can be marked as xfail.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/multidigraph.html b/reference/classes/multidigraph.html index 6eacc86e..96fbcac1 100644 --- a/reference/classes/multidigraph.html +++ b/reference/classes/multidigraph.html @@ -1054,7 +1054,7 @@ This reduces the memory used, but you lose edge attributes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/classes/multigraph.html b/reference/classes/multigraph.html index 5ced452d..f947a207 100644 --- a/reference/classes/multigraph.html +++ b/reference/classes/multigraph.html @@ -1026,7 +1026,7 @@ This reduces the memory used, but you lose edge attributes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/convert.html b/reference/convert.html index 1063e7f9..1ff27edb 100644 --- a/reference/convert.html +++ b/reference/convert.html @@ -752,7 +752,7 @@ function which attempts to guess the input type and convert it automatically.</p <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/drawing.html b/reference/drawing.html index bc977d54..5e7a168f 100644 --- a/reference/drawing.html +++ b/reference/drawing.html @@ -875,7 +875,7 @@ Changing <code class="xref py py-obj docutils literal notranslate"><span class=" <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/exceptions.html b/reference/exceptions.html index 05f5a9d0..547e6955 100644 --- a/reference/exceptions.html +++ b/reference/exceptions.html @@ -793,7 +793,7 @@ completed when this exception was raised.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/functions.html b/reference/functions.html index 09ae3b92..5e3ed397 100644 --- a/reference/functions.html +++ b/reference/functions.html @@ -801,7 +801,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/generated/networkx.utils.decorators.argmap.assemble.html b/reference/generated/generated/networkx.utils.decorators.argmap.assemble.html index bf2fabb9..249fad80 100644 --- a/reference/generated/generated/networkx.utils.decorators.argmap.assemble.html +++ b/reference/generated/generated/networkx.utils.decorators.argmap.assemble.html @@ -637,7 +637,7 @@ tuple into a list so that the arguments can be modified.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/generated/networkx.utils.decorators.argmap.compile.html b/reference/generated/generated/networkx.utils.decorators.argmap.compile.html index 7d63242d..9f505ca8 100644 --- a/reference/generated/generated/networkx.utils.decorators.argmap.compile.html +++ b/reference/generated/generated/networkx.utils.decorators.argmap.compile.html @@ -624,7 +624,7 @@ to describe where the function comes from. The name is something like: <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/generated/networkx.utils.decorators.argmap.signature.html b/reference/generated/generated/networkx.utils.decorators.argmap.signature.html index 89bcc841..40a868e9 100644 --- a/reference/generated/generated/networkx.utils.decorators.argmap.signature.html +++ b/reference/generated/generated/networkx.utils.decorators.argmap.signature.html @@ -628,7 +628,7 @@ to construct a string of source code for the decorated function.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.pop.html b/reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.pop.html index f6111050..58022a28 100644 --- a/reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.pop.html +++ b/reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.pop.html @@ -598,7 +598,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.push.html b/reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.push.html index 78b47608..88c4bd07 100644 --- a/reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.push.html +++ b/reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.push.html @@ -598,7 +598,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.remove.html b/reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.remove.html index 066f7dbf..b7726b27 100644 --- a/reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.remove.html +++ b/reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.remove.html @@ -598,7 +598,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.update.html b/reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.update.html index 812d767d..9d4ad49c 100644 --- a/reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.update.html +++ b/reference/generated/generated/networkx.utils.mapped_queue.MappedQueue.update.html @@ -598,7 +598,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.add_cycle.html b/reference/generated/networkx.classes.function.add_cycle.html index 43fe59c5..047d5687 100644 --- a/reference/generated/networkx.classes.function.add_cycle.html +++ b/reference/generated/networkx.classes.function.add_cycle.html @@ -636,7 +636,7 @@ the nodes (in order) and added to the graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.add_path.html b/reference/generated/networkx.classes.function.add_path.html index 4a22ba4b..7451c9ab 100644 --- a/reference/generated/networkx.classes.function.add_path.html +++ b/reference/generated/networkx.classes.function.add_path.html @@ -636,7 +636,7 @@ the nodes (in order) and added to the graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.add_star.html b/reference/generated/networkx.classes.function.add_star.html index 88f6670a..943853d3 100644 --- a/reference/generated/networkx.classes.function.add_star.html +++ b/reference/generated/networkx.classes.function.add_star.html @@ -637,7 +637,7 @@ It is connected to all other nodes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.all_neighbors.html b/reference/generated/networkx.classes.function.all_neighbors.html index 588e7840..0a9e8909 100644 --- a/reference/generated/networkx.classes.function.all_neighbors.html +++ b/reference/generated/networkx.classes.function.all_neighbors.html @@ -628,7 +628,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.common_neighbors.html b/reference/generated/networkx.classes.function.common_neighbors.html index 5b65fcde..e32cf208 100644 --- a/reference/generated/networkx.classes.function.common_neighbors.html +++ b/reference/generated/networkx.classes.function.common_neighbors.html @@ -639,7 +639,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.create_empty_copy.html b/reference/generated/networkx.classes.function.create_empty_copy.html index c60065b2..49b2134b 100644 --- a/reference/generated/networkx.classes.function.create_empty_copy.html +++ b/reference/generated/networkx.classes.function.create_empty_copy.html @@ -627,7 +627,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.degree.html b/reference/generated/networkx.classes.function.degree.html index 291d8568..e607577f 100644 --- a/reference/generated/networkx.classes.function.degree.html +++ b/reference/generated/networkx.classes.function.degree.html @@ -612,7 +612,7 @@ If nbunch is omitted, then return degrees of <em>all</em> nodes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.degree_histogram.html b/reference/generated/networkx.classes.function.degree_histogram.html index 72f0e5ef..f1d2466c 100644 --- a/reference/generated/networkx.classes.function.degree_histogram.html +++ b/reference/generated/networkx.classes.function.degree_histogram.html @@ -629,7 +629,7 @@ The degree values are the index in the list.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.density.html b/reference/generated/networkx.classes.function.density.html index fd617a62..f5fb5b99 100644 --- a/reference/generated/networkx.classes.function.density.html +++ b/reference/generated/networkx.classes.function.density.html @@ -624,7 +624,7 @@ loops can have density higher than 1.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.edge_subgraph.html b/reference/generated/networkx.classes.function.edge_subgraph.html index 46f824a4..799d92a2 100644 --- a/reference/generated/networkx.classes.function.edge_subgraph.html +++ b/reference/generated/networkx.classes.function.edge_subgraph.html @@ -648,7 +648,7 @@ can be created.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.edges.html b/reference/generated/networkx.classes.function.edges.html index 4dca2adb..efc667c3 100644 --- a/reference/generated/networkx.classes.function.edges.html +++ b/reference/generated/networkx.classes.function.edges.html @@ -613,7 +613,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.freeze.html b/reference/generated/networkx.classes.function.freeze.html index d3803787..60bf70f6 100644 --- a/reference/generated/networkx.classes.function.freeze.html +++ b/reference/generated/networkx.classes.function.freeze.html @@ -646,7 +646,7 @@ nodes or edges.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.get_edge_attributes.html b/reference/generated/networkx.classes.function.get_edge_attributes.html index b3f77cd9..a459a979 100644 --- a/reference/generated/networkx.classes.function.get_edge_attributes.html +++ b/reference/generated/networkx.classes.function.get_edge_attributes.html @@ -635,7 +635,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.get_node_attributes.html b/reference/generated/networkx.classes.function.get_node_attributes.html index 31420b90..f1530f6b 100644 --- a/reference/generated/networkx.classes.function.get_node_attributes.html +++ b/reference/generated/networkx.classes.function.get_node_attributes.html @@ -633,7 +633,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.induced_subgraph.html b/reference/generated/networkx.classes.function.induced_subgraph.html index d12ece98..1165003b 100644 --- a/reference/generated/networkx.classes.function.induced_subgraph.html +++ b/reference/generated/networkx.classes.function.induced_subgraph.html @@ -649,7 +649,7 @@ chains or not, as you wish. The returned subgraph is a view on <code class="xref <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.is_directed.html b/reference/generated/networkx.classes.function.is_directed.html index 9f53e741..b7ef5b2c 100644 --- a/reference/generated/networkx.classes.function.is_directed.html +++ b/reference/generated/networkx.classes.function.is_directed.html @@ -611,7 +611,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.is_empty.html b/reference/generated/networkx.classes.function.is_empty.html index ca733fec..6bd1fd19 100644 --- a/reference/generated/networkx.classes.function.is_empty.html +++ b/reference/generated/networkx.classes.function.is_empty.html @@ -630,7 +630,7 @@ is the number of nodes in the graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.is_frozen.html b/reference/generated/networkx.classes.function.is_frozen.html index 18c09dc5..6d6efcda 100644 --- a/reference/generated/networkx.classes.function.is_frozen.html +++ b/reference/generated/networkx.classes.function.is_frozen.html @@ -625,7 +625,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.is_negatively_weighted.html b/reference/generated/networkx.classes.function.is_negatively_weighted.html index aac0d295..1de15304 100644 --- a/reference/generated/networkx.classes.function.is_negatively_weighted.html +++ b/reference/generated/networkx.classes.function.is_negatively_weighted.html @@ -653,7 +653,7 @@ weighted.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.is_path.html b/reference/generated/networkx.classes.function.is_path.html index baaa99d6..b288d891 100644 --- a/reference/generated/networkx.classes.function.is_path.html +++ b/reference/generated/networkx.classes.function.is_path.html @@ -629,7 +629,7 @@ each consecutive pair must be connected via one or more edges.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.is_weighted.html b/reference/generated/networkx.classes.function.is_weighted.html index 1840552d..d85dd1cd 100644 --- a/reference/generated/networkx.classes.function.is_weighted.html +++ b/reference/generated/networkx.classes.function.is_weighted.html @@ -650,7 +650,7 @@ None, then every edge in <code class="xref py py-obj docutils literal notranslat <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.neighbors.html b/reference/generated/networkx.classes.function.neighbors.html index 07e0f3fc..f37372c8 100644 --- a/reference/generated/networkx.classes.function.neighbors.html +++ b/reference/generated/networkx.classes.function.neighbors.html @@ -611,7 +611,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.nodes.html b/reference/generated/networkx.classes.function.nodes.html index 58f7fb72..dfc67904 100644 --- a/reference/generated/networkx.classes.function.nodes.html +++ b/reference/generated/networkx.classes.function.nodes.html @@ -611,7 +611,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.nodes_with_selfloops.html b/reference/generated/networkx.classes.function.nodes_with_selfloops.html index 0675cacb..d9aace20 100644 --- a/reference/generated/networkx.classes.function.nodes_with_selfloops.html +++ b/reference/generated/networkx.classes.function.nodes_with_selfloops.html @@ -635,7 +635,7 @@ to that node.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.non_edges.html b/reference/generated/networkx.classes.function.non_edges.html index aae5f125..aaacd68a 100644 --- a/reference/generated/networkx.classes.function.non_edges.html +++ b/reference/generated/networkx.classes.function.non_edges.html @@ -625,7 +625,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.non_neighbors.html b/reference/generated/networkx.classes.function.non_neighbors.html index 64e3f6d7..3f6df7c2 100644 --- a/reference/generated/networkx.classes.function.non_neighbors.html +++ b/reference/generated/networkx.classes.function.non_neighbors.html @@ -627,7 +627,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.number_of_edges.html b/reference/generated/networkx.classes.function.number_of_edges.html index f8f1d5ea..ec631f0e 100644 --- a/reference/generated/networkx.classes.function.number_of_edges.html +++ b/reference/generated/networkx.classes.function.number_of_edges.html @@ -611,7 +611,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.number_of_nodes.html b/reference/generated/networkx.classes.function.number_of_nodes.html index 656193b1..aec68397 100644 --- a/reference/generated/networkx.classes.function.number_of_nodes.html +++ b/reference/generated/networkx.classes.function.number_of_nodes.html @@ -611,7 +611,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.number_of_selfloops.html b/reference/generated/networkx.classes.function.number_of_selfloops.html index 350067f5..bab6236c 100644 --- a/reference/generated/networkx.classes.function.number_of_selfloops.html +++ b/reference/generated/networkx.classes.function.number_of_selfloops.html @@ -634,7 +634,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.path_weight.html b/reference/generated/networkx.classes.function.path_weight.html index c4b0f453..697ff5ed 100644 --- a/reference/generated/networkx.classes.function.path_weight.html +++ b/reference/generated/networkx.classes.function.path_weight.html @@ -636,7 +636,7 @@ specified weight of the specified path</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.restricted_view.html b/reference/generated/networkx.classes.function.restricted_view.html index 9c868241..b28b031c 100644 --- a/reference/generated/networkx.classes.function.restricted_view.html +++ b/reference/generated/networkx.classes.function.restricted_view.html @@ -649,7 +649,7 @@ can be created.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.reverse_view.html b/reference/generated/networkx.classes.function.reverse_view.html index 58a903ce..f10c73d1 100644 --- a/reference/generated/networkx.classes.function.reverse_view.html +++ b/reference/generated/networkx.classes.function.reverse_view.html @@ -639,7 +639,7 @@ edge directions are reversed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.selfloop_edges.html b/reference/generated/networkx.classes.function.selfloop_edges.html index 2ea68a92..b0c2e13b 100644 --- a/reference/generated/networkx.classes.function.selfloop_edges.html +++ b/reference/generated/networkx.classes.function.selfloop_edges.html @@ -655,7 +655,7 @@ Only relevant if data is not True or False.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.set_edge_attributes.html b/reference/generated/networkx.classes.function.set_edge_attributes.html index 8c2d5ecd..c1111e46 100644 --- a/reference/generated/networkx.classes.function.set_edge_attributes.html +++ b/reference/generated/networkx.classes.function.set_edge_attributes.html @@ -709,7 +709,7 @@ overwrite the previous values. Continuing from the previous case we get:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.set_node_attributes.html b/reference/generated/networkx.classes.function.set_node_attributes.html index d82971eb..808cc3f3 100644 --- a/reference/generated/networkx.classes.function.set_node_attributes.html +++ b/reference/generated/networkx.classes.function.set_node_attributes.html @@ -689,7 +689,7 @@ values are silently ignored:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.subgraph.html b/reference/generated/networkx.classes.function.subgraph.html index 10f792e4..391e22a8 100644 --- a/reference/generated/networkx.classes.function.subgraph.html +++ b/reference/generated/networkx.classes.function.subgraph.html @@ -628,7 +628,7 @@ ignored.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.subgraph_view.html b/reference/generated/networkx.classes.function.subgraph_view.html index 7bdc0418..97794423 100644 --- a/reference/generated/networkx.classes.function.subgraph_view.html +++ b/reference/generated/networkx.classes.function.subgraph_view.html @@ -676,7 +676,7 @@ data — for example, filtering on edge data attached to the graph:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.to_directed.html b/reference/generated/networkx.classes.function.to_directed.html index 1d00a9b5..3f95dd68 100644 --- a/reference/generated/networkx.classes.function.to_directed.html +++ b/reference/generated/networkx.classes.function.to_directed.html @@ -614,7 +614,7 @@ while this function always provides a view.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.classes.function.to_undirected.html b/reference/generated/networkx.classes.function.to_undirected.html index a5e5afc3..8615ffd0 100644 --- a/reference/generated/networkx.classes.function.to_undirected.html +++ b/reference/generated/networkx.classes.function.to_undirected.html @@ -614,7 +614,7 @@ while this function always provides a view.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.convert.from_dict_of_dicts.html b/reference/generated/networkx.convert.from_dict_of_dicts.html index 05c7ff48..fd135bb1 100644 --- a/reference/generated/networkx.convert.from_dict_of_dicts.html +++ b/reference/generated/networkx.convert.from_dict_of_dicts.html @@ -611,7 +611,7 @@ node to neighbor to edge data.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.convert.from_dict_of_lists.html b/reference/generated/networkx.convert.from_dict_of_lists.html index 62cc0241..ef5d34a2 100644 --- a/reference/generated/networkx.convert.from_dict_of_lists.html +++ b/reference/generated/networkx.convert.from_dict_of_lists.html @@ -605,7 +605,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.convert.from_edgelist.html b/reference/generated/networkx.convert.from_edgelist.html index 235b0460..0a49e01e 100644 --- a/reference/generated/networkx.convert.from_edgelist.html +++ b/reference/generated/networkx.convert.from_edgelist.html @@ -605,7 +605,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.convert.to_dict_of_dicts.html b/reference/generated/networkx.convert.to_dict_of_dicts.html index 4ca32887..6365e584 100644 --- a/reference/generated/networkx.convert.to_dict_of_dicts.html +++ b/reference/generated/networkx.convert.to_dict_of_dicts.html @@ -684,7 +684,7 @@ replaced:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.convert.to_dict_of_lists.html b/reference/generated/networkx.convert.to_dict_of_lists.html index d0fe2a27..10e6d63f 100644 --- a/reference/generated/networkx.convert.to_dict_of_lists.html +++ b/reference/generated/networkx.convert.to_dict_of_lists.html @@ -598,7 +598,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.convert.to_edgelist.html b/reference/generated/networkx.convert.to_edgelist.html index 42a2ec22..23c1f5f0 100644 --- a/reference/generated/networkx.convert.to_edgelist.html +++ b/reference/generated/networkx.convert.to_edgelist.html @@ -596,7 +596,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.convert.to_networkx_graph.html b/reference/generated/networkx.convert.to_networkx_graph.html index 0f7ed651..3871f286 100644 --- a/reference/generated/networkx.convert.to_networkx_graph.html +++ b/reference/generated/networkx.convert.to_networkx_graph.html @@ -623,7 +623,7 @@ a multigraph from a multigraph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.convert_matrix.from_numpy_array.html b/reference/generated/networkx.convert_matrix.from_numpy_array.html index 7800a909..bf66bb4a 100644 --- a/reference/generated/networkx.convert_matrix.from_numpy_array.html +++ b/reference/generated/networkx.convert_matrix.from_numpy_array.html @@ -664,7 +664,7 @@ as the number of parallel edges joining those two vertices:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.convert_matrix.from_pandas_adjacency.html b/reference/generated/networkx.convert_matrix.from_pandas_adjacency.html index 8921926e..8223ffc2 100644 --- a/reference/generated/networkx.convert_matrix.from_pandas_adjacency.html +++ b/reference/generated/networkx.convert_matrix.from_pandas_adjacency.html @@ -626,7 +626,7 @@ NetworkX graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.convert_matrix.from_pandas_edgelist.html b/reference/generated/networkx.convert_matrix.from_pandas_edgelist.html index 714180a4..1d1538e8 100644 --- a/reference/generated/networkx.convert_matrix.from_pandas_edgelist.html +++ b/reference/generated/networkx.convert_matrix.from_pandas_edgelist.html @@ -680,7 +680,7 @@ is a multigraph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.convert_matrix.from_scipy_sparse_array.html b/reference/generated/networkx.convert_matrix.from_scipy_sparse_array.html index 0176ba83..50da1b0c 100644 --- a/reference/generated/networkx.convert_matrix.from_scipy_sparse_array.html +++ b/reference/generated/networkx.convert_matrix.from_scipy_sparse_array.html @@ -644,7 +644,7 @@ as the number of parallel edges joining those two vertices:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.convert_matrix.to_numpy_array.html b/reference/generated/networkx.convert_matrix.to_numpy_array.html index 92456b1d..d1fc6474 100644 --- a/reference/generated/networkx.convert_matrix.to_numpy_array.html +++ b/reference/generated/networkx.convert_matrix.to_numpy_array.html @@ -731,7 +731,7 @@ makes it much clearer to differentiate such 0-weighted edges and actual nonedge <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.convert_matrix.to_pandas_adjacency.html b/reference/generated/networkx.convert_matrix.to_pandas_adjacency.html index 1cb77940..04841b11 100644 --- a/reference/generated/networkx.convert_matrix.to_pandas_adjacency.html +++ b/reference/generated/networkx.convert_matrix.to_pandas_adjacency.html @@ -660,7 +660,7 @@ resulting Pandas DataFrame can be modified as follows:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.convert_matrix.to_pandas_edgelist.html b/reference/generated/networkx.convert_matrix.to_pandas_edgelist.html index 7615255d..97c4aebd 100644 --- a/reference/generated/networkx.convert_matrix.to_pandas_edgelist.html +++ b/reference/generated/networkx.convert_matrix.to_pandas_edgelist.html @@ -636,7 +636,7 @@ multigraph case). If None, edge keys are not stored in the DataFrame.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.convert_matrix.to_scipy_sparse_array.html b/reference/generated/networkx.convert_matrix.to_scipy_sparse_array.html index 4e2ac475..987dcd96 100644 --- a/reference/generated/networkx.convert_matrix.to_scipy_sparse_array.html +++ b/reference/generated/networkx.convert_matrix.to_scipy_sparse_array.html @@ -661,7 +661,7 @@ resulting SciPy sparse array can be modified as follows:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.layout.bipartite_layout.html b/reference/generated/networkx.drawing.layout.bipartite_layout.html index af1281fe..d18e004d 100644 --- a/reference/generated/networkx.drawing.layout.bipartite_layout.html +++ b/reference/generated/networkx.drawing.layout.bipartite_layout.html @@ -642,7 +642,7 @@ try to minimize edge crossings.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.layout.circular_layout.html b/reference/generated/networkx.drawing.layout.circular_layout.html index 07cfa747..926e3b10 100644 --- a/reference/generated/networkx.drawing.layout.circular_layout.html +++ b/reference/generated/networkx.drawing.layout.circular_layout.html @@ -645,7 +645,7 @@ try to minimize edge crossings.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.layout.kamada_kawai_layout.html b/reference/generated/networkx.drawing.layout.kamada_kawai_layout.html index b9205d7a..bbbffa21 100644 --- a/reference/generated/networkx.drawing.layout.kamada_kawai_layout.html +++ b/reference/generated/networkx.drawing.layout.kamada_kawai_layout.html @@ -644,7 +644,7 @@ the edge weight. If None, then all edge weights are 1.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.layout.multipartite_layout.html b/reference/generated/networkx.drawing.layout.multipartite_layout.html index 80bd8cbe..f9a6c4a8 100644 --- a/reference/generated/networkx.drawing.layout.multipartite_layout.html +++ b/reference/generated/networkx.drawing.layout.multipartite_layout.html @@ -640,7 +640,7 @@ have subset_key data, they will be placed in the corresponding layers.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.layout.planar_layout.html b/reference/generated/networkx.drawing.layout.planar_layout.html index ea71255e..53b374d5 100644 --- a/reference/generated/networkx.drawing.layout.planar_layout.html +++ b/reference/generated/networkx.drawing.layout.planar_layout.html @@ -640,7 +640,7 @@ nx.PlanarEmbedding, the positions are selected accordingly.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.layout.random_layout.html b/reference/generated/networkx.drawing.layout.random_layout.html index 15b2d3b2..096b624f 100644 --- a/reference/generated/networkx.drawing.layout.random_layout.html +++ b/reference/generated/networkx.drawing.layout.random_layout.html @@ -641,7 +641,7 @@ by numpy.random.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.layout.rescale_layout.html b/reference/generated/networkx.drawing.layout.rescale_layout.html index 4c1a1338..7641974c 100644 --- a/reference/generated/networkx.drawing.layout.rescale_layout.html +++ b/reference/generated/networkx.drawing.layout.rescale_layout.html @@ -637,7 +637,7 @@ The resulting NumPy Array is returned (order of rows unchanged).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.layout.rescale_layout_dict.html b/reference/generated/networkx.drawing.layout.rescale_layout_dict.html index 4e3a805e..981e670e 100644 --- a/reference/generated/networkx.drawing.layout.rescale_layout_dict.html +++ b/reference/generated/networkx.drawing.layout.rescale_layout_dict.html @@ -640,7 +640,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.layout.shell_layout.html b/reference/generated/networkx.drawing.layout.shell_layout.html index 9bfdcf9c..2d0bb7c9 100644 --- a/reference/generated/networkx.drawing.layout.shell_layout.html +++ b/reference/generated/networkx.drawing.layout.shell_layout.html @@ -650,7 +650,7 @@ try to minimize edge crossings.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.layout.spectral_layout.html b/reference/generated/networkx.drawing.layout.spectral_layout.html index a73af10e..1f167871 100644 --- a/reference/generated/networkx.drawing.layout.spectral_layout.html +++ b/reference/generated/networkx.drawing.layout.spectral_layout.html @@ -645,7 +645,7 @@ eigenvalue solver (ARPACK).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.layout.spiral_layout.html b/reference/generated/networkx.drawing.layout.spiral_layout.html index 6b2fac83..a6050fa5 100644 --- a/reference/generated/networkx.drawing.layout.spiral_layout.html +++ b/reference/generated/networkx.drawing.layout.spiral_layout.html @@ -651,7 +651,7 @@ from each other by increasing separation further from center.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.layout.spring_layout.html b/reference/generated/networkx.drawing.layout.spring_layout.html index ed516507..a5286176 100644 --- a/reference/generated/networkx.drawing.layout.spring_layout.html +++ b/reference/generated/networkx.drawing.layout.spring_layout.html @@ -677,7 +677,7 @@ by numpy.random.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_agraph.from_agraph.html b/reference/generated/networkx.drawing.nx_agraph.from_agraph.html index 9ee30e75..db5bd3d1 100644 --- a/reference/generated/networkx.drawing.nx_agraph.from_agraph.html +++ b/reference/generated/networkx.drawing.nx_agraph.from_agraph.html @@ -633,7 +633,7 @@ attribute or the value 1 if no edge weight attribute is found.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_agraph.graphviz_layout.html b/reference/generated/networkx.drawing.nx_agraph.graphviz_layout.html index 4edcb99d..dcbcd441 100644 --- a/reference/generated/networkx.drawing.nx_agraph.graphviz_layout.html +++ b/reference/generated/networkx.drawing.nx_agraph.graphviz_layout.html @@ -637,7 +637,7 @@ see <a class="gitlab reference external" href="https://gitlab.com/graphviz/graph <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_agraph.pygraphviz_layout.html b/reference/generated/networkx.drawing.nx_agraph.pygraphviz_layout.html index 18e7d696..963e9733 100644 --- a/reference/generated/networkx.drawing.nx_agraph.pygraphviz_layout.html +++ b/reference/generated/networkx.drawing.nx_agraph.pygraphviz_layout.html @@ -647,7 +647,7 @@ see <a class="gitlab reference external" href="https://gitlab.com/graphviz/graph <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_agraph.read_dot.html b/reference/generated/networkx.drawing.nx_agraph.read_dot.html index 3578c826..c1d7d161 100644 --- a/reference/generated/networkx.drawing.nx_agraph.read_dot.html +++ b/reference/generated/networkx.drawing.nx_agraph.read_dot.html @@ -616,7 +616,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_agraph.to_agraph.html b/reference/generated/networkx.drawing.nx_agraph.to_agraph.html index e4a4785e..425eac45 100644 --- a/reference/generated/networkx.drawing.nx_agraph.to_agraph.html +++ b/reference/generated/networkx.drawing.nx_agraph.to_agraph.html @@ -625,7 +625,7 @@ and then updated with the calling arguments if any.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_agraph.write_dot.html b/reference/generated/networkx.drawing.nx_agraph.write_dot.html index 6a1667b7..ec873c58 100644 --- a/reference/generated/networkx.drawing.nx_agraph.write_dot.html +++ b/reference/generated/networkx.drawing.nx_agraph.write_dot.html @@ -622,7 +622,7 @@ see <a class="gitlab reference external" href="https://gitlab.com/graphviz/graph <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pydot.from_pydot.html b/reference/generated/networkx.drawing.nx_pydot.from_pydot.html index 373dfe9b..8f45c114 100644 --- a/reference/generated/networkx.drawing.nx_pydot.from_pydot.html +++ b/reference/generated/networkx.drawing.nx_pydot.from_pydot.html @@ -630,7 +630,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pydot.graphviz_layout.html b/reference/generated/networkx.drawing.nx_pydot.graphviz_layout.html index 863469e4..e0cccf07 100644 --- a/reference/generated/networkx.drawing.nx_pydot.graphviz_layout.html +++ b/reference/generated/networkx.drawing.nx_pydot.graphviz_layout.html @@ -636,7 +636,7 @@ Options depend on GraphViz version but may include: <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pydot.pydot_layout.html b/reference/generated/networkx.drawing.nx_pydot.pydot_layout.html index 75524ef2..8024464c 100644 --- a/reference/generated/networkx.drawing.nx_pydot.pydot_layout.html +++ b/reference/generated/networkx.drawing.nx_pydot.pydot_layout.html @@ -645,7 +645,7 @@ for the layout computation using something similar to:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pydot.read_dot.html b/reference/generated/networkx.drawing.nx_pydot.read_dot.html index 84ca7278..ca3119b2 100644 --- a/reference/generated/networkx.drawing.nx_pydot.read_dot.html +++ b/reference/generated/networkx.drawing.nx_pydot.read_dot.html @@ -628,7 +628,7 @@ returned. All graphs _except_ the first are silently ignored.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pydot.to_pydot.html b/reference/generated/networkx.drawing.nx_pydot.to_pydot.html index e81b16c9..8ca0d06e 100644 --- a/reference/generated/networkx.drawing.nx_pydot.to_pydot.html +++ b/reference/generated/networkx.drawing.nx_pydot.to_pydot.html @@ -621,7 +621,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pydot.write_dot.html b/reference/generated/networkx.drawing.nx_pydot.write_dot.html index f470c32f..d5cde93b 100644 --- a/reference/generated/networkx.drawing.nx_pydot.write_dot.html +++ b/reference/generated/networkx.drawing.nx_pydot.write_dot.html @@ -609,7 +609,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pylab.draw.html b/reference/generated/networkx.drawing.nx_pylab.draw.html index db2979ba..ee8e4008 100644 --- a/reference/generated/networkx.drawing.nx_pylab.draw.html +++ b/reference/generated/networkx.drawing.nx_pylab.draw.html @@ -658,7 +658,7 @@ so beware when using <code class="xref py py-obj docutils literal notranslate">< <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pylab.draw_circular.html b/reference/generated/networkx.drawing.nx_pylab.draw_circular.html index 05878dea..e14530c9 100644 --- a/reference/generated/networkx.drawing.nx_pylab.draw_circular.html +++ b/reference/generated/networkx.drawing.nx_pylab.draw_circular.html @@ -639,7 +639,7 @@ repeated drawing it is much more efficient to call <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pylab.draw_kamada_kawai.html b/reference/generated/networkx.drawing.nx_pylab.draw_kamada_kawai.html index 391fad48..1195fcfc 100644 --- a/reference/generated/networkx.drawing.nx_pylab.draw_kamada_kawai.html +++ b/reference/generated/networkx.drawing.nx_pylab.draw_kamada_kawai.html @@ -640,7 +640,7 @@ result:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pylab.draw_networkx.html b/reference/generated/networkx.drawing.nx_pylab.draw_networkx.html index 0a0d299d..9d4f80a1 100644 --- a/reference/generated/networkx.drawing.nx_pylab.draw_networkx.html +++ b/reference/generated/networkx.drawing.nx_pylab.draw_networkx.html @@ -724,7 +724,7 @@ turned off with keyword arrows=False.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pylab.draw_networkx_edge_labels.html b/reference/generated/networkx.drawing.nx_pylab.draw_networkx_edge_labels.html index a0b4044f..25b43591 100644 --- a/reference/generated/networkx.drawing.nx_pylab.draw_networkx_edge_labels.html +++ b/reference/generated/networkx.drawing.nx_pylab.draw_networkx_edge_labels.html @@ -670,7 +670,7 @@ Default is {boxstyle=’round’, ec=(1.0, 1.0, 1.0), fc=(1.0, 1.0, 1.0)}.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pylab.draw_networkx_edges.html b/reference/generated/networkx.drawing.nx_pylab.draw_networkx_edges.html index 3b8c3edf..b9be333f 100644 --- a/reference/generated/networkx.drawing.nx_pylab.draw_networkx_edges.html +++ b/reference/generated/networkx.drawing.nx_pylab.draw_networkx_edges.html @@ -740,7 +740,7 @@ returned, but can always be accessed via the <code class="docutils literal notra <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pylab.draw_networkx_labels.html b/reference/generated/networkx.drawing.nx_pylab.draw_networkx_labels.html index cc8d0bb2..99ee1521 100644 --- a/reference/generated/networkx.drawing.nx_pylab.draw_networkx_labels.html +++ b/reference/generated/networkx.drawing.nx_pylab.draw_networkx_labels.html @@ -666,7 +666,7 @@ If needed use: <code class="xref py py-obj docutils literal notranslate"><span c <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pylab.draw_networkx_nodes.html b/reference/generated/networkx.drawing.nx_pylab.draw_networkx_nodes.html index 59abb60c..fa336a19 100644 --- a/reference/generated/networkx.drawing.nx_pylab.draw_networkx_nodes.html +++ b/reference/generated/networkx.drawing.nx_pylab.draw_networkx_nodes.html @@ -678,7 +678,7 @@ for details. The default is <a class="reference external" href="https://docs.pyt <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pylab.draw_planar.html b/reference/generated/networkx.drawing.nx_pylab.draw_planar.html index c6bc1596..1a11fff1 100644 --- a/reference/generated/networkx.drawing.nx_pylab.draw_planar.html +++ b/reference/generated/networkx.drawing.nx_pylab.draw_planar.html @@ -645,7 +645,7 @@ For repeated drawing it is much more efficient to call <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pylab.draw_random.html b/reference/generated/networkx.drawing.nx_pylab.draw_random.html index a87f5d70..a1d0e8f5 100644 --- a/reference/generated/networkx.drawing.nx_pylab.draw_random.html +++ b/reference/generated/networkx.drawing.nx_pylab.draw_random.html @@ -639,7 +639,7 @@ For repeated drawing it is much more efficient to call <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pylab.draw_shell.html b/reference/generated/networkx.drawing.nx_pylab.draw_shell.html index 0f31b0ea..fabdebd7 100644 --- a/reference/generated/networkx.drawing.nx_pylab.draw_shell.html +++ b/reference/generated/networkx.drawing.nx_pylab.draw_shell.html @@ -643,7 +643,7 @@ For repeated drawing it is much more efficient to call <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pylab.draw_spectral.html b/reference/generated/networkx.drawing.nx_pylab.draw_spectral.html index 6d6afa33..54c3fb0a 100644 --- a/reference/generated/networkx.drawing.nx_pylab.draw_spectral.html +++ b/reference/generated/networkx.drawing.nx_pylab.draw_spectral.html @@ -641,7 +641,7 @@ For repeated drawing it is much more efficient to call <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.drawing.nx_pylab.draw_spring.html b/reference/generated/networkx.drawing.nx_pylab.draw_spring.html index 98c01d9d..c8d557d4 100644 --- a/reference/generated/networkx.drawing.nx_pylab.draw_spring.html +++ b/reference/generated/networkx.drawing.nx_pylab.draw_spring.html @@ -642,7 +642,7 @@ For repeated drawing it is much more efficient to call <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.atlas.graph_atlas.html b/reference/generated/networkx.generators.atlas.graph_atlas.html index 9ba84c5e..82cfbf50 100644 --- a/reference/generated/networkx.generators.atlas.graph_atlas.html +++ b/reference/generated/networkx.generators.atlas.graph_atlas.html @@ -739,7 +739,7 @@ Oxford University Press, 1998.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.atlas.graph_atlas_g.html b/reference/generated/networkx.generators.atlas.graph_atlas_g.html index 42a1fb5d..fb8904af 100644 --- a/reference/generated/networkx.generators.atlas.graph_atlas_g.html +++ b/reference/generated/networkx.generators.atlas.graph_atlas_g.html @@ -753,7 +753,7 @@ Oxford University Press, 1998.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.balanced_tree.html b/reference/generated/networkx.generators.classic.balanced_tree.html index 15d617bd..1ac16449 100644 --- a/reference/generated/networkx.generators.classic.balanced_tree.html +++ b/reference/generated/networkx.generators.classic.balanced_tree.html @@ -729,7 +729,7 @@ have degree <code class="xref py py-obj docutils literal notranslate"><span clas <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.barbell_graph.html b/reference/generated/networkx.generators.classic.barbell_graph.html index 3d3de7ad..46f6a07c 100644 --- a/reference/generated/networkx.generators.classic.barbell_graph.html +++ b/reference/generated/networkx.generators.classic.barbell_graph.html @@ -738,7 +738,7 @@ and Jim Fill’s e-text on Random Walks on Graphs.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.binomial_tree.html b/reference/generated/networkx.generators.classic.binomial_tree.html index dea9f3d3..bcb602e3 100644 --- a/reference/generated/networkx.generators.classic.binomial_tree.html +++ b/reference/generated/networkx.generators.classic.binomial_tree.html @@ -724,7 +724,7 @@ the leftmost child of the root of the other.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.circulant_graph.html b/reference/generated/networkx.generators.classic.circulant_graph.html index dedb1b08..eea25568 100644 --- a/reference/generated/networkx.generators.classic.circulant_graph.html +++ b/reference/generated/networkx.generators.classic.circulant_graph.html @@ -767,7 +767,7 @@ on 5 points with the set of offsets [1, 2]:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.circular_ladder_graph.html b/reference/generated/networkx.generators.classic.circular_ladder_graph.html index 3b14cf70..068a5baa 100644 --- a/reference/generated/networkx.generators.classic.circular_ladder_graph.html +++ b/reference/generated/networkx.generators.classic.circular_ladder_graph.html @@ -708,7 +708,7 @@ each of the n pairs of concentric nodes are joined by an edge.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.complete_graph.html b/reference/generated/networkx.generators.classic.complete_graph.html index 9322746d..facba18f 100644 --- a/reference/generated/networkx.generators.classic.complete_graph.html +++ b/reference/generated/networkx.generators.classic.complete_graph.html @@ -733,7 +733,7 @@ resulting graph may not be as desired. Make sure you have no duplicates.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.complete_multipartite_graph.html b/reference/generated/networkx.generators.classic.complete_multipartite_graph.html index 858ccd38..4ea4b9fd 100644 --- a/reference/generated/networkx.generators.classic.complete_multipartite_graph.html +++ b/reference/generated/networkx.generators.classic.complete_multipartite_graph.html @@ -760,7 +760,7 @@ nodes, respectively.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.cycle_graph.html b/reference/generated/networkx.generators.classic.cycle_graph.html index 75031a26..81ea5f2d 100644 --- a/reference/generated/networkx.generators.classic.cycle_graph.html +++ b/reference/generated/networkx.generators.classic.cycle_graph.html @@ -721,7 +721,7 @@ resulting graph may not be as desired. Make sure you have no duplicates.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.dorogovtsev_goltsev_mendes_graph.html b/reference/generated/networkx.generators.classic.dorogovtsev_goltsev_mendes_graph.html index 84b7371c..05070cbb 100644 --- a/reference/generated/networkx.generators.classic.dorogovtsev_goltsev_mendes_graph.html +++ b/reference/generated/networkx.generators.classic.dorogovtsev_goltsev_mendes_graph.html @@ -706,7 +706,7 @@ See: arXiv:/cond-mat/0112143 by Dorogovtsev, Goltsev and Mendes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.empty_graph.html b/reference/generated/networkx.generators.classic.empty_graph.html index 59888c76..5a800321 100644 --- a/reference/generated/networkx.generators.classic.empty_graph.html +++ b/reference/generated/networkx.generators.classic.empty_graph.html @@ -775,7 +775,7 @@ default constructor to be other than nx.Graph, specify <code class="xref py py-o <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.full_rary_tree.html b/reference/generated/networkx.generators.classic.full_rary_tree.html index 60c799be..7f7ba858 100644 --- a/reference/generated/networkx.generators.classic.full_rary_tree.html +++ b/reference/generated/networkx.generators.classic.full_rary_tree.html @@ -735,7 +735,7 @@ James Andrew Storer, Birkhauser Boston 2001, (page 225).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.ladder_graph.html b/reference/generated/networkx.generators.classic.ladder_graph.html index 4aa4d7cb..06fa36c1 100644 --- a/reference/generated/networkx.generators.classic.ladder_graph.html +++ b/reference/generated/networkx.generators.classic.ladder_graph.html @@ -707,7 +707,7 @@ each pair connected by a single edge.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.lollipop_graph.html b/reference/generated/networkx.generators.classic.lollipop_graph.html index 88d1f04d..24cc1131 100644 --- a/reference/generated/networkx.generators.classic.lollipop_graph.html +++ b/reference/generated/networkx.generators.classic.lollipop_graph.html @@ -726,7 +726,7 @@ Fill’s etext on Random Walks on Graphs.)</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.null_graph.html b/reference/generated/networkx.generators.classic.null_graph.html index bba96e7b..fb7b53c1 100644 --- a/reference/generated/networkx.generators.classic.null_graph.html +++ b/reference/generated/networkx.generators.classic.null_graph.html @@ -705,7 +705,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.path_graph.html b/reference/generated/networkx.generators.classic.path_graph.html index eb38faeb..be6684ed 100644 --- a/reference/generated/networkx.generators.classic.path_graph.html +++ b/reference/generated/networkx.generators.classic.path_graph.html @@ -717,7 +717,7 @@ resulting graph may not be as desired. Make sure you have no duplicates.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.star_graph.html b/reference/generated/networkx.generators.classic.star_graph.html index c05a5a3a..4350dd46 100644 --- a/reference/generated/networkx.generators.classic.star_graph.html +++ b/reference/generated/networkx.generators.classic.star_graph.html @@ -721,7 +721,7 @@ So star_graph(3) is the same as star_graph(range(4)).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.trivial_graph.html b/reference/generated/networkx.generators.classic.trivial_graph.html index 5ccbc121..cd20095f 100644 --- a/reference/generated/networkx.generators.classic.trivial_graph.html +++ b/reference/generated/networkx.generators.classic.trivial_graph.html @@ -704,7 +704,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.turan_graph.html b/reference/generated/networkx.generators.classic.turan_graph.html index 983cf8e7..5540efb6 100644 --- a/reference/generated/networkx.generators.classic.turan_graph.html +++ b/reference/generated/networkx.generators.classic.turan_graph.html @@ -725,7 +725,7 @@ The graph has <span class="math notranslate nohighlight">\((r-1)(n^2)/(2r)\)</sp <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.classic.wheel_graph.html b/reference/generated/networkx.generators.classic.wheel_graph.html index 9d1029c4..c3a396d9 100644 --- a/reference/generated/networkx.generators.classic.wheel_graph.html +++ b/reference/generated/networkx.generators.classic.wheel_graph.html @@ -719,7 +719,7 @@ resulting graph may not be as desired. Make sure you have no duplicates.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.cographs.random_cograph.html b/reference/generated/networkx.generators.cographs.random_cograph.html index a36f3e5c..cca54be6 100644 --- a/reference/generated/networkx.generators.cographs.random_cograph.html +++ b/reference/generated/networkx.generators.cographs.random_cograph.html @@ -744,7 +744,7 @@ ISSN 0166-218X.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.community.LFR_benchmark_graph.html b/reference/generated/networkx.generators.community.LFR_benchmark_graph.html index 2f0e70d3..47de1d3d 100644 --- a/reference/generated/networkx.generators.community.LFR_benchmark_graph.html +++ b/reference/generated/networkx.generators.community.LFR_benchmark_graph.html @@ -863,7 +863,7 @@ node attributes of the graph:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.community.caveman_graph.html b/reference/generated/networkx.generators.community.caveman_graph.html index a26d88e5..c95799b8 100644 --- a/reference/generated/networkx.generators.community.caveman_graph.html +++ b/reference/generated/networkx.generators.community.caveman_graph.html @@ -744,7 +744,7 @@ Amer. J. Soc. 105, 493-527, 1999.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.community.connected_caveman_graph.html b/reference/generated/networkx.generators.community.connected_caveman_graph.html index e73816a4..8f21996d 100644 --- a/reference/generated/networkx.generators.community.connected_caveman_graph.html +++ b/reference/generated/networkx.generators.community.connected_caveman_graph.html @@ -747,7 +747,7 @@ Amer. J. Soc. 105, 493-527, 1999.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.community.gaussian_random_partition_graph.html b/reference/generated/networkx.generators.community.gaussian_random_partition_graph.html index 6354c570..10af5395 100644 --- a/reference/generated/networkx.generators.community.gaussian_random_partition_graph.html +++ b/reference/generated/networkx.generators.community.gaussian_random_partition_graph.html @@ -767,7 +767,7 @@ In the proceedings of the 11th Europ. Symp. Algorithms, 2003.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.community.planted_partition_graph.html b/reference/generated/networkx.generators.community.planted_partition_graph.html index a0152167..ec362cbc 100644 --- a/reference/generated/networkx.generators.community.planted_partition_graph.html +++ b/reference/generated/networkx.generators.community.planted_partition_graph.html @@ -763,7 +763,7 @@ Volume 486, Issue 3-5 p. 75-174. <a class="reference external" href="https://arx <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.community.random_partition_graph.html b/reference/generated/networkx.generators.community.random_partition_graph.html index 267913e2..93356b53 100644 --- a/reference/generated/networkx.generators.community.random_partition_graph.html +++ b/reference/generated/networkx.generators.community.random_partition_graph.html @@ -758,7 +758,7 @@ Volume 486, Issue 3-5 p. 75-174. <a class="reference external" href="https://arx <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.community.relaxed_caveman_graph.html b/reference/generated/networkx.generators.community.relaxed_caveman_graph.html index 8b647357..237b305d 100644 --- a/reference/generated/networkx.generators.community.relaxed_caveman_graph.html +++ b/reference/generated/networkx.generators.community.relaxed_caveman_graph.html @@ -746,7 +746,7 @@ Physics Reports Volume 486, Issues 3-5, February 2010, Pages 75-174. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.community.ring_of_cliques.html b/reference/generated/networkx.generators.community.ring_of_cliques.html index 6dc99969..be320e50 100644 --- a/reference/generated/networkx.generators.community.ring_of_cliques.html +++ b/reference/generated/networkx.generators.community.ring_of_cliques.html @@ -743,7 +743,7 @@ simply adds the link without removing any link from the cliques.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.community.stochastic_block_model.html b/reference/generated/networkx.generators.community.stochastic_block_model.html index 53759507..76c38c60 100644 --- a/reference/generated/networkx.generators.community.stochastic_block_model.html +++ b/reference/generated/networkx.generators.community.stochastic_block_model.html @@ -788,7 +788,7 @@ Social networks, 5(2), 109-137, 1983.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.community.windmill_graph.html b/reference/generated/networkx.generators.community.windmill_graph.html index 193121ca..8e77317a 100644 --- a/reference/generated/networkx.generators.community.windmill_graph.html +++ b/reference/generated/networkx.generators.community.windmill_graph.html @@ -741,7 +741,7 @@ are in the opposite order as the parameters of this method.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.degree_seq.configuration_model.html b/reference/generated/networkx.generators.degree_seq.configuration_model.html index 9abe5d19..15d7af55 100644 --- a/reference/generated/networkx.generators.degree_seq.configuration_model.html +++ b/reference/generated/networkx.generators.degree_seq.configuration_model.html @@ -791,7 +791,7 @@ edges. To remove any parallel edges from the returned graph:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.degree_seq.degree_sequence_tree.html b/reference/generated/networkx.generators.degree_seq.degree_sequence_tree.html index 833dfecb..eb6b0245 100644 --- a/reference/generated/networkx.generators.degree_seq.degree_sequence_tree.html +++ b/reference/generated/networkx.generators.degree_seq.degree_sequence_tree.html @@ -707,7 +707,7 @@ len(deg_sequence)-sum(deg_sequence)/2=1</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.degree_seq.directed_configuration_model.html b/reference/generated/networkx.generators.degree_seq.directed_configuration_model.html index b9c6414e..1fd779b2 100644 --- a/reference/generated/networkx.generators.degree_seq.directed_configuration_model.html +++ b/reference/generated/networkx.generators.degree_seq.directed_configuration_model.html @@ -784,7 +784,7 @@ edges. To remove any parallel edges from the returned graph:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.degree_seq.directed_havel_hakimi_graph.html b/reference/generated/networkx.generators.degree_seq.directed_havel_hakimi_graph.html index 1c7cc737..07db0fa2 100644 --- a/reference/generated/networkx.generators.degree_seq.directed_havel_hakimi_graph.html +++ b/reference/generated/networkx.generators.degree_seq.directed_havel_hakimi_graph.html @@ -747,7 +747,7 @@ and Factors Discrete Mathematics, 6(1), pp. 79-88 (1973)</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.degree_seq.expected_degree_graph.html b/reference/generated/networkx.generators.degree_seq.expected_degree_graph.html index 0ac17389..94218a17 100644 --- a/reference/generated/networkx.generators.degree_seq.expected_degree_graph.html +++ b/reference/generated/networkx.generators.degree_seq.expected_degree_graph.html @@ -769,7 +769,7 @@ pp. 115-126, 2011.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.degree_seq.havel_hakimi_graph.html b/reference/generated/networkx.generators.degree_seq.havel_hakimi_graph.html index 6f8c5f1a..61228979 100644 --- a/reference/generated/networkx.generators.degree_seq.havel_hakimi_graph.html +++ b/reference/generated/networkx.generators.degree_seq.havel_hakimi_graph.html @@ -747,7 +747,7 @@ and Factors Discrete Mathematics, 6(1), pp. 79-88 (1973)</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.degree_seq.random_degree_sequence_graph.html b/reference/generated/networkx.generators.degree_seq.random_degree_sequence_graph.html index 1b873a91..f04e002a 100644 --- a/reference/generated/networkx.generators.degree_seq.random_degree_sequence_graph.html +++ b/reference/generated/networkx.generators.degree_seq.random_degree_sequence_graph.html @@ -762,7 +762,7 @@ DOI: 10.1007/s00453-009-9340-1</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.directed.gn_graph.html b/reference/generated/networkx.generators.directed.gn_graph.html index aa3d4fea..704cf2be 100644 --- a/reference/generated/networkx.generators.directed.gn_graph.html +++ b/reference/generated/networkx.generators.directed.gn_graph.html @@ -744,7 +744,7 @@ method:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.directed.gnc_graph.html b/reference/generated/networkx.generators.directed.gnc_graph.html index 56c7140c..01ac0367 100644 --- a/reference/generated/networkx.generators.directed.gnc_graph.html +++ b/reference/generated/networkx.generators.directed.gnc_graph.html @@ -729,7 +729,7 @@ Phys. Rev. E, 71, 036118, 2005k.},</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.directed.gnr_graph.html b/reference/generated/networkx.generators.directed.gnr_graph.html index 2914f733..71b96bd9 100644 --- a/reference/generated/networkx.generators.directed.gnr_graph.html +++ b/reference/generated/networkx.generators.directed.gnr_graph.html @@ -741,7 +741,7 @@ method:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.directed.random_k_out_graph.html b/reference/generated/networkx.generators.directed.random_k_out_graph.html index debbf6aa..8dbd7611 100644 --- a/reference/generated/networkx.generators.directed.random_k_out_graph.html +++ b/reference/generated/networkx.generators.directed.random_k_out_graph.html @@ -765,7 +765,7 @@ arXiv preprint arXiv:1311.5961 (2013). <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.directed.scale_free_graph.html b/reference/generated/networkx.generators.directed.scale_free_graph.html index 7c19385b..9806d1de 100644 --- a/reference/generated/networkx.generators.directed.scale_free_graph.html +++ b/reference/generated/networkx.generators.directed.scale_free_graph.html @@ -762,7 +762,7 @@ Discrete Algorithms, 132–139, 2003.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.duplication.duplication_divergence_graph.html b/reference/generated/networkx.generators.duplication.duplication_divergence_graph.html index 6c47e1c4..ed581e17 100644 --- a/reference/generated/networkx.generators.duplication.duplication_divergence_graph.html +++ b/reference/generated/networkx.generators.duplication.duplication_divergence_graph.html @@ -745,7 +745,7 @@ Phys. Rev. E, 71, 061911, 2005.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.duplication.partial_duplication_graph.html b/reference/generated/networkx.generators.duplication.partial_duplication_graph.html index 7dfb2f8e..e19df407 100644 --- a/reference/generated/networkx.generators.duplication.partial_duplication_graph.html +++ b/reference/generated/networkx.generators.duplication.partial_duplication_graph.html @@ -746,7 +746,7 @@ randomly grown graphs.” Journal of Applied Mathematics 2008. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.ego.ego_graph.html b/reference/generated/networkx.generators.ego.ego_graph.html index 3471d56b..ecbccd17 100644 --- a/reference/generated/networkx.generators.ego.ego_graph.html +++ b/reference/generated/networkx.generators.ego.ego_graph.html @@ -731,7 +731,7 @@ directions use the keyword argument undirected=True.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.expanders.chordal_cycle_graph.html b/reference/generated/networkx.generators.expanders.chordal_cycle_graph.html index 8ef15364..e216a6ca 100644 --- a/reference/generated/networkx.generators.expanders.chordal_cycle_graph.html +++ b/reference/generated/networkx.generators.expanders.chordal_cycle_graph.html @@ -740,7 +740,7 @@ Birkhäuser Verlag, Basel, 1994.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.expanders.margulis_gabber_galil_graph.html b/reference/generated/networkx.generators.expanders.margulis_gabber_galil_graph.html index 83cd0588..83b2250e 100644 --- a/reference/generated/networkx.generators.expanders.margulis_gabber_galil_graph.html +++ b/reference/generated/networkx.generators.expanders.margulis_gabber_galil_graph.html @@ -729,7 +729,7 @@ is at most <code class="xref py py-obj docutils literal notranslate"><span class <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.expanders.paley_graph.html b/reference/generated/networkx.generators.expanders.paley_graph.html index 8b54a64a..eb742eda 100644 --- a/reference/generated/networkx.generators.expanders.paley_graph.html +++ b/reference/generated/networkx.generators.expanders.paley_graph.html @@ -740,7 +740,7 @@ Cambridge University Press, Cambridge (2001).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.geometric.geographical_threshold_graph.html b/reference/generated/networkx.generators.geometric.geographical_threshold_graph.html index 9bfc8676..482c777b 100644 --- a/reference/generated/networkx.generators.geometric.geographical_threshold_graph.html +++ b/reference/generated/networkx.generators.geometric.geographical_threshold_graph.html @@ -812,7 +812,7 @@ default <a class="reference external" href="https://en.wikipedia.org/wiki/Euclid <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.geometric.geometric_edges.html b/reference/generated/networkx.generators.geometric.geometric_edges.html index 06ddac5d..efe79007 100644 --- a/reference/generated/networkx.generators.geometric.geometric_edges.html +++ b/reference/generated/networkx.generators.geometric.geometric_edges.html @@ -748,7 +748,7 @@ coordinates.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.geometric.navigable_small_world_graph.html b/reference/generated/networkx.generators.geometric.navigable_small_world_graph.html index 15d19921..67c72a99 100644 --- a/reference/generated/networkx.generators.geometric.navigable_small_world_graph.html +++ b/reference/generated/networkx.generators.geometric.navigable_small_world_graph.html @@ -752,7 +752,7 @@ perspective. Proc. 32nd ACM Symposium on Theory of Computing, 2000.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.geometric.random_geometric_graph.html b/reference/generated/networkx.generators.geometric.random_geometric_graph.html index 83a5f3c0..8e35b213 100644 --- a/reference/generated/networkx.generators.geometric.random_geometric_graph.html +++ b/reference/generated/networkx.generators.geometric.random_geometric_graph.html @@ -770,7 +770,7 @@ an edge if their distance is at most 0.1:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.geometric.soft_random_geometric_graph.html b/reference/generated/networkx.generators.geometric.soft_random_geometric_graph.html index 0203f1ac..cdd0a895 100644 --- a/reference/generated/networkx.generators.geometric.soft_random_geometric_graph.html +++ b/reference/generated/networkx.generators.geometric.soft_random_geometric_graph.html @@ -795,7 +795,7 @@ Euclidean distance is at most 0.2.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.geometric.thresholded_random_geometric_graph.html b/reference/generated/networkx.generators.geometric.thresholded_random_geometric_graph.html index 0d02a77e..2ba87e77 100644 --- a/reference/generated/networkx.generators.geometric.thresholded_random_geometric_graph.html +++ b/reference/generated/networkx.generators.geometric.thresholded_random_geometric_graph.html @@ -792,7 +792,7 @@ Euclidean distance is at most 0.2.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.geometric.waxman_graph.html b/reference/generated/networkx.generators.geometric.waxman_graph.html index 2bc7846a..5f068cd2 100644 --- a/reference/generated/networkx.generators.geometric.waxman_graph.html +++ b/reference/generated/networkx.generators.geometric.waxman_graph.html @@ -783,7 +783,7 @@ default <a class="reference external" href="https://en.wikipedia.org/wiki/Euclid <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.harary_graph.hkn_harary_graph.html b/reference/generated/networkx.generators.harary_graph.hkn_harary_graph.html index 58b9aee6..ad41ba54 100644 --- a/reference/generated/networkx.generators.harary_graph.hkn_harary_graph.html +++ b/reference/generated/networkx.generators.harary_graph.hkn_harary_graph.html @@ -749,7 +749,7 @@ Proc. Nat. Acad. Sci. USA 48, 1142-1146, 1962.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.harary_graph.hnm_harary_graph.html b/reference/generated/networkx.generators.harary_graph.hnm_harary_graph.html index 5a8b4ecb..3dcd21fa 100644 --- a/reference/generated/networkx.generators.harary_graph.hnm_harary_graph.html +++ b/reference/generated/networkx.generators.harary_graph.hnm_harary_graph.html @@ -750,7 +750,7 @@ Proc. Nat. Acad. Sci. USA 48, 1142-1146, 1962.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.internet_as_graphs.random_internet_as_graph.html b/reference/generated/networkx.generators.internet_as_graphs.random_internet_as_graph.html index 62ce7559..9e36533c 100644 --- a/reference/generated/networkx.generators.internet_as_graphs.random_internet_as_graph.html +++ b/reference/generated/networkx.generators.internet_as_graphs.random_internet_as_graph.html @@ -746,7 +746,7 @@ in Communications, vol. 28, no. 8, pp. 1250-1261, October 2010.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.intersection.general_random_intersection_graph.html b/reference/generated/networkx.generators.intersection.general_random_intersection_graph.html index ed36aa5e..204bfb5a 100644 --- a/reference/generated/networkx.generators.intersection.general_random_intersection_graph.html +++ b/reference/generated/networkx.generators.intersection.general_random_intersection_graph.html @@ -737,7 +737,7 @@ of Lecture Notes in Computer Science, Springer, pp. 1029–1040.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.intersection.k_random_intersection_graph.html b/reference/generated/networkx.generators.intersection.k_random_intersection_graph.html index 836150ad..441b2b2e 100644 --- a/reference/generated/networkx.generators.intersection.k_random_intersection_graph.html +++ b/reference/generated/networkx.generators.intersection.k_random_intersection_graph.html @@ -735,7 +735,7 @@ Electronic Notes in Discrete Mathematics 10 (2001), 129–132.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.intersection.uniform_random_intersection_graph.html b/reference/generated/networkx.generators.intersection.uniform_random_intersection_graph.html index dad11fe1..e5a1ccbc 100644 --- a/reference/generated/networkx.generators.intersection.uniform_random_intersection_graph.html +++ b/reference/generated/networkx.generators.intersection.uniform_random_intersection_graph.html @@ -740,7 +740,7 @@ and g(n, p) models. Random Struct. Algorithms 16, 2 (2000), 156–176.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.interval_graph.interval_graph.html b/reference/generated/networkx.generators.interval_graph.interval_graph.html index c78db38d..ef1f919b 100644 --- a/reference/generated/networkx.generators.interval_graph.interval_graph.html +++ b/reference/generated/networkx.generators.interval_graph.interval_graph.html @@ -740,7 +740,7 @@ where min1,max1 = interval</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.joint_degree_seq.directed_joint_degree_graph.html b/reference/generated/networkx.generators.joint_degree_seq.directed_joint_degree_graph.html index 15e6a73f..d650e8d6 100644 --- a/reference/generated/networkx.generators.joint_degree_seq.directed_joint_degree_graph.html +++ b/reference/generated/networkx.generators.joint_degree_seq.directed_joint_degree_graph.html @@ -764,7 +764,7 @@ reached their target values and the construction is complete.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.joint_degree_seq.is_valid_directed_joint_degree.html b/reference/generated/networkx.generators.joint_degree_seq.is_valid_directed_joint_degree.html index 74e6cb72..10be6987 100644 --- a/reference/generated/networkx.generators.joint_degree_seq.is_valid_directed_joint_degree.html +++ b/reference/generated/networkx.generators.joint_degree_seq.is_valid_directed_joint_degree.html @@ -746,7 +746,7 @@ nkk) need to satisfy for simple directed graph realizability:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.joint_degree_seq.is_valid_joint_degree.html b/reference/generated/networkx.generators.joint_degree_seq.is_valid_joint_degree.html index 0b5348f5..261e7bf7 100644 --- a/reference/generated/networkx.generators.joint_degree_seq.is_valid_joint_degree.html +++ b/reference/generated/networkx.generators.joint_degree_seq.is_valid_joint_degree.html @@ -749,7 +749,7 @@ Algorithmics, 2012.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.joint_degree_seq.joint_degree_graph.html b/reference/generated/networkx.generators.joint_degree_seq.joint_degree_graph.html index e7df7155..203e9ca5 100644 --- a/reference/generated/networkx.generators.joint_degree_seq.joint_degree_graph.html +++ b/reference/generated/networkx.generators.joint_degree_seq.joint_degree_graph.html @@ -761,7 +761,7 @@ Graphs with a Target Joint Degree Matrix and Beyond”, IEEE Infocom, ‘15</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.lattice.grid_2d_graph.html b/reference/generated/networkx.generators.lattice.grid_2d_graph.html index 180e86c0..3db47364 100644 --- a/reference/generated/networkx.generators.lattice.grid_2d_graph.html +++ b/reference/generated/networkx.generators.lattice.grid_2d_graph.html @@ -727,7 +727,7 @@ periodic.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.lattice.grid_graph.html b/reference/generated/networkx.generators.lattice.grid_graph.html index b03fc45d..fd291dc2 100644 --- a/reference/generated/networkx.generators.lattice.grid_graph.html +++ b/reference/generated/networkx.generators.lattice.grid_graph.html @@ -739,7 +739,7 @@ corresponding axis is periodic.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.lattice.hexagonal_lattice_graph.html b/reference/generated/networkx.generators.lattice.hexagonal_lattice_graph.html index 9edbd531..71f384a5 100644 --- a/reference/generated/networkx.generators.lattice.hexagonal_lattice_graph.html +++ b/reference/generated/networkx.generators.lattice.hexagonal_lattice_graph.html @@ -742,7 +742,7 @@ If graph is directed, edges will point up or right.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.lattice.hypercube_graph.html b/reference/generated/networkx.generators.lattice.hypercube_graph.html index 10cfbff8..dbcd22a2 100644 --- a/reference/generated/networkx.generators.lattice.hypercube_graph.html +++ b/reference/generated/networkx.generators.lattice.hypercube_graph.html @@ -722,7 +722,7 @@ The number of nodes in the graph will be <code class="docutils literal notransla <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.lattice.triangular_lattice_graph.html b/reference/generated/networkx.generators.lattice.triangular_lattice_graph.html index 7f6cb8f7..cb717fda 100644 --- a/reference/generated/networkx.generators.lattice.triangular_lattice_graph.html +++ b/reference/generated/networkx.generators.lattice.triangular_lattice_graph.html @@ -748,7 +748,7 @@ the edges don’t overlap so much.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.line.inverse_line_graph.html b/reference/generated/networkx.generators.line.inverse_line_graph.html index 57d268bc..177ce3de 100644 --- a/reference/generated/networkx.generators.line.inverse_line_graph.html +++ b/reference/generated/networkx.generators.line.inverse_line_graph.html @@ -749,7 +749,7 @@ its line graph G”, Information Processing Letters 2, (1973), 108–112.</p></l <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.line.line_graph.html b/reference/generated/networkx.generators.line.line_graph.html index a07fe815..6ff2c3e9 100644 --- a/reference/generated/networkx.generators.line.line_graph.html +++ b/reference/generated/networkx.generators.line.line_graph.html @@ -793,7 +793,7 @@ attributes can be copied manually:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.mycielski.mycielski_graph.html b/reference/generated/networkx.generators.mycielski.mycielski_graph.html index 1b98d703..2386d5c3 100644 --- a/reference/generated/networkx.generators.mycielski.mycielski_graph.html +++ b/reference/generated/networkx.generators.mycielski.mycielski_graph.html @@ -731,7 +731,7 @@ The remaining graphs are generated using the Mycielski operation.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.mycielski.mycielskian.html b/reference/generated/networkx.generators.mycielski.mycielskian.html index e73d7062..422beb53 100644 --- a/reference/generated/networkx.generators.mycielski.mycielskian.html +++ b/reference/generated/networkx.generators.mycielski.mycielskian.html @@ -738,7 +738,7 @@ perform on G. Defaults to 1. Must be a non-negative integer.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.nonisomorphic_trees.nonisomorphic_trees.html b/reference/generated/networkx.generators.nonisomorphic_trees.nonisomorphic_trees.html index a1e4d1e0..792efe08 100644 --- a/reference/generated/networkx.generators.nonisomorphic_trees.nonisomorphic_trees.html +++ b/reference/generated/networkx.generators.nonisomorphic_trees.nonisomorphic_trees.html @@ -722,7 +722,7 @@ be returned</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.nonisomorphic_trees.number_of_nonisomorphic_trees.html b/reference/generated/networkx.generators.nonisomorphic_trees.number_of_nonisomorphic_trees.html index 7ac8ce76..1ccbef87 100644 --- a/reference/generated/networkx.generators.nonisomorphic_trees.number_of_nonisomorphic_trees.html +++ b/reference/generated/networkx.generators.nonisomorphic_trees.number_of_nonisomorphic_trees.html @@ -717,7 +717,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_clustered.random_clustered_graph.html b/reference/generated/networkx.generators.random_clustered.random_clustered_graph.html index 0b952b04..0b3ad3a0 100644 --- a/reference/generated/networkx.generators.random_clustered.random_clustered_graph.html +++ b/reference/generated/networkx.generators.random_clustered.random_clustered_graph.html @@ -783,7 +783,7 @@ In: Physical Review Letters 103 (5 July 2009)</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.barabasi_albert_graph.html b/reference/generated/networkx.generators.random_graphs.barabasi_albert_graph.html index 8e1f1b30..1c9d46b2 100644 --- a/reference/generated/networkx.generators.random_graphs.barabasi_albert_graph.html +++ b/reference/generated/networkx.generators.random_graphs.barabasi_albert_graph.html @@ -745,7 +745,7 @@ random networks”, Science 286, pp 509-512, 1999.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.binomial_graph.html b/reference/generated/networkx.generators.random_graphs.binomial_graph.html index b54d1363..66311db2 100644 --- a/reference/generated/networkx.generators.random_graphs.binomial_graph.html +++ b/reference/generated/networkx.generators.random_graphs.binomial_graph.html @@ -757,7 +757,7 @@ aliases for <a class="reference internal" href="networkx.generators.random_graph <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.connected_watts_strogatz_graph.html b/reference/generated/networkx.generators.random_graphs.connected_watts_strogatz_graph.html index 41d6807b..d47d48cb 100644 --- a/reference/generated/networkx.generators.random_graphs.connected_watts_strogatz_graph.html +++ b/reference/generated/networkx.generators.random_graphs.connected_watts_strogatz_graph.html @@ -750,7 +750,7 @@ Nature, 393, pp. 440–442, 1998.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.dense_gnm_random_graph.html b/reference/generated/networkx.generators.random_graphs.dense_gnm_random_graph.html index 42cfe20a..6304d2d6 100644 --- a/reference/generated/networkx.generators.random_graphs.dense_gnm_random_graph.html +++ b/reference/generated/networkx.generators.random_graphs.dense_gnm_random_graph.html @@ -740,7 +740,7 @@ Volume 2/Seminumerical algorithms, Third Edition, Addison-Wesley, 1997.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.dual_barabasi_albert_graph.html b/reference/generated/networkx.generators.random_graphs.dual_barabasi_albert_graph.html index f38b7ffe..612ea78a 100644 --- a/reference/generated/networkx.generators.random_graphs.dual_barabasi_albert_graph.html +++ b/reference/generated/networkx.generators.random_graphs.dual_barabasi_albert_graph.html @@ -752,7 +752,7 @@ the initial graph number of nodes m0 does not satisfy m1, m2 <= m0 <= n.</ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.erdos_renyi_graph.html b/reference/generated/networkx.generators.random_graphs.erdos_renyi_graph.html index bb794d63..c8199254 100644 --- a/reference/generated/networkx.generators.random_graphs.erdos_renyi_graph.html +++ b/reference/generated/networkx.generators.random_graphs.erdos_renyi_graph.html @@ -757,7 +757,7 @@ aliases for <a class="reference internal" href="networkx.generators.random_graph <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.extended_barabasi_albert_graph.html b/reference/generated/networkx.generators.random_graphs.extended_barabasi_albert_graph.html index 3c8e4de8..c08cdd2d 100644 --- a/reference/generated/networkx.generators.random_graphs.extended_barabasi_albert_graph.html +++ b/reference/generated/networkx.generators.random_graphs.extended_barabasi_albert_graph.html @@ -753,7 +753,7 @@ Physical review letters, 85(24), 5234.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.fast_gnp_random_graph.html b/reference/generated/networkx.generators.random_graphs.fast_gnp_random_graph.html index 469e82de..6b9324e2 100644 --- a/reference/generated/networkx.generators.random_graphs.fast_gnp_random_graph.html +++ b/reference/generated/networkx.generators.random_graphs.fast_gnp_random_graph.html @@ -743,7 +743,7 @@ Phys. Rev. E, 71, 036113, 2005.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.gnm_random_graph.html b/reference/generated/networkx.generators.random_graphs.gnm_random_graph.html index 4a32ee78..0da4167a 100644 --- a/reference/generated/networkx.generators.random_graphs.gnm_random_graph.html +++ b/reference/generated/networkx.generators.random_graphs.gnm_random_graph.html @@ -730,7 +730,7 @@ See <a class="reference internal" href="../randomness.html#randomness"><span cla <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.gnp_random_graph.html b/reference/generated/networkx.generators.random_graphs.gnp_random_graph.html index 98cc2153..93a6da57 100644 --- a/reference/generated/networkx.generators.random_graphs.gnp_random_graph.html +++ b/reference/generated/networkx.generators.random_graphs.gnp_random_graph.html @@ -757,7 +757,7 @@ aliases for <a class="reference internal" href="#networkx.generators.random_grap <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.newman_watts_strogatz_graph.html b/reference/generated/networkx.generators.random_graphs.newman_watts_strogatz_graph.html index 85b1e00d..ba3eafa5 100644 --- a/reference/generated/networkx.generators.random_graphs.newman_watts_strogatz_graph.html +++ b/reference/generated/networkx.generators.random_graphs.newman_watts_strogatz_graph.html @@ -745,7 +745,7 @@ Physics Letters A, 263, 341, 1999. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.powerlaw_cluster_graph.html b/reference/generated/networkx.generators.random_graphs.powerlaw_cluster_graph.html index ce44ceae..ed2ff52b 100644 --- a/reference/generated/networkx.generators.random_graphs.powerlaw_cluster_graph.html +++ b/reference/generated/networkx.generators.random_graphs.powerlaw_cluster_graph.html @@ -749,7 +749,7 @@ Phys. Rev. E, 65, 026107, 2002.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.random_kernel_graph.html b/reference/generated/networkx.generators.random_graphs.random_kernel_graph.html index c4765b71..8b54258c 100644 --- a/reference/generated/networkx.generators.random_graphs.random_kernel_graph.html +++ b/reference/generated/networkx.generators.random_graphs.random_kernel_graph.html @@ -766,7 +766,7 @@ PLoS ONE 10(9): e0135177, 2015. doi:10.1371/journal.pone.0135177</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.random_lobster.html b/reference/generated/networkx.generators.random_graphs.random_lobster.html index d4c0b97e..c5ca6afa 100644 --- a/reference/generated/networkx.generators.random_graphs.random_lobster.html +++ b/reference/generated/networkx.generators.random_graphs.random_lobster.html @@ -732,7 +732,7 @@ See <a class="reference internal" href="../randomness.html#randomness"><span cla <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.random_powerlaw_tree.html b/reference/generated/networkx.generators.random_graphs.random_powerlaw_tree.html index 2f2be614..1d42b041 100644 --- a/reference/generated/networkx.generators.random_graphs.random_powerlaw_tree.html +++ b/reference/generated/networkx.generators.random_graphs.random_powerlaw_tree.html @@ -731,7 +731,7 @@ edges is one smaller than the number of nodes).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.random_powerlaw_tree_sequence.html b/reference/generated/networkx.generators.random_graphs.random_powerlaw_tree_sequence.html index 93be52c4..11fba5b0 100644 --- a/reference/generated/networkx.generators.random_graphs.random_powerlaw_tree_sequence.html +++ b/reference/generated/networkx.generators.random_graphs.random_powerlaw_tree_sequence.html @@ -731,7 +731,7 @@ edges is one smaller than the number of nodes).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.random_regular_graph.html b/reference/generated/networkx.generators.random_graphs.random_regular_graph.html index fbf4ac6e..ad11bd99 100644 --- a/reference/generated/networkx.generators.random_graphs.random_regular_graph.html +++ b/reference/generated/networkx.generators.random_graphs.random_regular_graph.html @@ -748,7 +748,7 @@ San Diego, CA, USA, pp 213–222, 2003. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.random_shell_graph.html b/reference/generated/networkx.generators.random_graphs.random_shell_graph.html index 2c0db188..e84f1b65 100644 --- a/reference/generated/networkx.generators.random_graphs.random_shell_graph.html +++ b/reference/generated/networkx.generators.random_graphs.random_shell_graph.html @@ -726,7 +726,7 @@ See <a class="reference internal" href="../randomness.html#randomness"><span cla <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.random_graphs.watts_strogatz_graph.html b/reference/generated/networkx.generators.random_graphs.watts_strogatz_graph.html index 453dd03c..36617aae 100644 --- a/reference/generated/networkx.generators.random_graphs.watts_strogatz_graph.html +++ b/reference/generated/networkx.generators.random_graphs.watts_strogatz_graph.html @@ -747,7 +747,7 @@ Nature, 393, pp. 440–442, 1998.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.LCF_graph.html b/reference/generated/networkx.generators.small.LCF_graph.html index 6ddf0803..03fc8257 100644 --- a/reference/generated/networkx.generators.small.LCF_graph.html +++ b/reference/generated/networkx.generators.small.LCF_graph.html @@ -734,7 +734,7 @@ and references.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.bull_graph.html b/reference/generated/networkx.generators.small.bull_graph.html index cec69ffa..2e157100 100644 --- a/reference/generated/networkx.generators.small.bull_graph.html +++ b/reference/generated/networkx.generators.small.bull_graph.html @@ -729,7 +729,7 @@ respectively the body and legs of a bull.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.chvatal_graph.html b/reference/generated/networkx.generators.small.chvatal_graph.html index 1dc8e26a..82eae926 100644 --- a/reference/generated/networkx.generators.small.chvatal_graph.html +++ b/reference/generated/networkx.generators.small.chvatal_graph.html @@ -732,7 +732,7 @@ LCF notation of order 4, two of order 6 , and 43 of order 1 <a class="reference <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.cubical_graph.html b/reference/generated/networkx.generators.small.cubical_graph.html index ce46312a..a5ac60fa 100644 --- a/reference/generated/networkx.generators.small.cubical_graph.html +++ b/reference/generated/networkx.generators.small.cubical_graph.html @@ -730,7 +730,7 @@ Such graphs arise in parallel processing in computers.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.desargues_graph.html b/reference/generated/networkx.generators.small.desargues_graph.html index 11a449cf..8663bd58 100644 --- a/reference/generated/networkx.generators.small.desargues_graph.html +++ b/reference/generated/networkx.generators.small.desargues_graph.html @@ -733,7 +733,7 @@ as [5,-5,9,-9]^5 <a class="reference internal" href="#r536f09c2ef21-2" id="id2"> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.diamond_graph.html b/reference/generated/networkx.generators.small.diamond_graph.html index 46730816..5456ec38 100644 --- a/reference/generated/networkx.generators.small.diamond_graph.html +++ b/reference/generated/networkx.generators.small.diamond_graph.html @@ -727,7 +727,7 @@ It is also sometimes known as the double triangle graph or kite graph <a class=" <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.dodecahedral_graph.html b/reference/generated/networkx.generators.small.dodecahedral_graph.html index 5d7a5a37..a0dbb6ba 100644 --- a/reference/generated/networkx.generators.small.dodecahedral_graph.html +++ b/reference/generated/networkx.generators.small.dodecahedral_graph.html @@ -733,7 +733,7 @@ It can be described in LCF notation as: <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.frucht_graph.html b/reference/generated/networkx.generators.small.frucht_graph.html index 442b4e84..ef4dcfdd 100644 --- a/reference/generated/networkx.generators.small.frucht_graph.html +++ b/reference/generated/networkx.generators.small.frucht_graph.html @@ -733,7 +733,7 @@ It is planar and Hamiltonian <a class="reference internal" href="#r647c8523432a- <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.heawood_graph.html b/reference/generated/networkx.generators.small.heawood_graph.html index f7d863ab..ca4672a2 100644 --- a/reference/generated/networkx.generators.small.heawood_graph.html +++ b/reference/generated/networkx.generators.small.heawood_graph.html @@ -739,7 +739,7 @@ minimal number of vertices <a class="reference internal" href="#r0e71c64cef3f-3" <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.hoffman_singleton_graph.html b/reference/generated/networkx.generators.small.hoffman_singleton_graph.html index fc7c04eb..8db74c75 100644 --- a/reference/generated/networkx.generators.small.hoffman_singleton_graph.html +++ b/reference/generated/networkx.generators.small.hoffman_singleton_graph.html @@ -737,7 +737,7 @@ and five pentagrams <span class="math notranslate nohighlight">\(Q_i\)</span> . <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.house_graph.html b/reference/generated/networkx.generators.small.house_graph.html index 19ef03cf..d6a4463f 100644 --- a/reference/generated/networkx.generators.small.house_graph.html +++ b/reference/generated/networkx.generators.small.house_graph.html @@ -727,7 +727,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.house_x_graph.html b/reference/generated/networkx.generators.small.house_x_graph.html index aa093861..fdc2d8eb 100644 --- a/reference/generated/networkx.generators.small.house_x_graph.html +++ b/reference/generated/networkx.generators.small.house_x_graph.html @@ -728,7 +728,7 @@ obtained by removing two edges from the pentatope graph <a class="reference inte <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.icosahedral_graph.html b/reference/generated/networkx.generators.small.icosahedral_graph.html index 006ce90b..58eba26e 100644 --- a/reference/generated/networkx.generators.small.icosahedral_graph.html +++ b/reference/generated/networkx.generators.small.icosahedral_graph.html @@ -728,7 +728,7 @@ regular and Hamiltonian <a class="reference internal" href="#r569fa285d8d2-1" id <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.krackhardt_kite_graph.html b/reference/generated/networkx.generators.small.krackhardt_kite_graph.html index 584a63dc..1901cb5c 100644 --- a/reference/generated/networkx.generators.small.krackhardt_kite_graph.html +++ b/reference/generated/networkx.generators.small.krackhardt_kite_graph.html @@ -733,7 +733,7 @@ Cognition, and Power in Organizations”. Administrative Science Quarterly. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.moebius_kantor_graph.html b/reference/generated/networkx.generators.small.moebius_kantor_graph.html index 2123b349..5de552b4 100644 --- a/reference/generated/networkx.generators.small.moebius_kantor_graph.html +++ b/reference/generated/networkx.generators.small.moebius_kantor_graph.html @@ -728,7 +728,7 @@ Petersen graph <a class="reference internal" href="#r76a9799b473e-1" id="id1">[1 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.octahedral_graph.html b/reference/generated/networkx.generators.small.octahedral_graph.html index c33c6534..7741a727 100644 --- a/reference/generated/networkx.generators.small.octahedral_graph.html +++ b/reference/generated/networkx.generators.small.octahedral_graph.html @@ -734,7 +734,7 @@ for this reason it is also called the cocktail party graph <a class="reference i <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.pappus_graph.html b/reference/generated/networkx.generators.small.pappus_graph.html index cef6d617..6a6ad119 100644 --- a/reference/generated/networkx.generators.small.pappus_graph.html +++ b/reference/generated/networkx.generators.small.pappus_graph.html @@ -722,7 +722,7 @@ and 27 edges. It is Hamiltonian and can be represented in LCF notation as <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.petersen_graph.html b/reference/generated/networkx.generators.small.petersen_graph.html index 6c07001c..01aef6ce 100644 --- a/reference/generated/networkx.generators.small.petersen_graph.html +++ b/reference/generated/networkx.generators.small.petersen_graph.html @@ -733,7 +733,7 @@ has an edge colouring with three colours <a class="reference internal" href="#r4 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.sedgewick_maze_graph.html b/reference/generated/networkx.generators.small.sedgewick_maze_graph.html index 1bf5bfe3..fbe394f5 100644 --- a/reference/generated/networkx.generators.small.sedgewick_maze_graph.html +++ b/reference/generated/networkx.generators.small.sedgewick_maze_graph.html @@ -728,7 +728,7 @@ Nodes are numbered 0,..,7</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.tetrahedral_graph.html b/reference/generated/networkx.generators.small.tetrahedral_graph.html index 2158346d..ca7a16d3 100644 --- a/reference/generated/networkx.generators.small.tetrahedral_graph.html +++ b/reference/generated/networkx.generators.small.tetrahedral_graph.html @@ -728,7 +728,7 @@ It is one of the 5 platonic graphs <a class="reference internal" href="#rb51c473 <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.truncated_cube_graph.html b/reference/generated/networkx.generators.small.truncated_cube_graph.html index 28a4ff09..6bbafe0b 100644 --- a/reference/generated/networkx.generators.small.truncated_cube_graph.html +++ b/reference/generated/networkx.generators.small.truncated_cube_graph.html @@ -733,7 +733,7 @@ of the cube one third of the way into each edge <a class="reference internal" hr <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.truncated_tetrahedron_graph.html b/reference/generated/networkx.generators.small.truncated_tetrahedron_graph.html index e1bd5dc5..ae8e987e 100644 --- a/reference/generated/networkx.generators.small.truncated_tetrahedron_graph.html +++ b/reference/generated/networkx.generators.small.truncated_tetrahedron_graph.html @@ -728,7 +728,7 @@ all 4 vertices of a regular tetrahedron at one third of the original edge length <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.small.tutte_graph.html b/reference/generated/networkx.generators.small.tutte_graph.html index 8013859f..bfe2ae58 100644 --- a/reference/generated/networkx.generators.small.tutte_graph.html +++ b/reference/generated/networkx.generators.small.tutte_graph.html @@ -731,7 +731,7 @@ three of its vertices <a class="reference internal" href="#r075c9a57dabd-1" id=" <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.social.davis_southern_women_graph.html b/reference/generated/networkx.generators.social.davis_southern_women_graph.html index adfe0b09..1b9199cb 100644 --- a/reference/generated/networkx.generators.social.davis_southern_women_graph.html +++ b/reference/generated/networkx.generators.social.davis_southern_women_graph.html @@ -713,7 +713,7 @@ University of Chicago Press, Chicago, IL.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.social.florentine_families_graph.html b/reference/generated/networkx.generators.social.florentine_families_graph.html index c70fa28c..67baacd2 100644 --- a/reference/generated/networkx.generators.social.florentine_families_graph.html +++ b/reference/generated/networkx.generators.social.florentine_families_graph.html @@ -713,7 +713,7 @@ Social Networks, Volume 8, Issue 3, September 1986, Pages 215-256</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.social.karate_club_graph.html b/reference/generated/networkx.generators.social.karate_club_graph.html index 371867d9..a3ef0145 100644 --- a/reference/generated/networkx.generators.social.karate_club_graph.html +++ b/reference/generated/networkx.generators.social.karate_club_graph.html @@ -726,7 +726,7 @@ number of contexts in which that edge’s incident node members interacted.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.social.les_miserables_graph.html b/reference/generated/networkx.generators.social.les_miserables_graph.html index 91f5f007..9252247e 100644 --- a/reference/generated/networkx.generators.social.les_miserables_graph.html +++ b/reference/generated/networkx.generators.social.les_miserables_graph.html @@ -713,7 +713,7 @@ pp. 74-87. New York: AcM Press.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.spectral_graph_forge.spectral_graph_forge.html b/reference/generated/networkx.generators.spectral_graph_forge.spectral_graph_forge.html index 3b92ff96..49882ca4 100644 --- a/reference/generated/networkx.generators.spectral_graph_forge.spectral_graph_forge.html +++ b/reference/generated/networkx.generators.spectral_graph_forge.spectral_graph_forge.html @@ -777,7 +777,7 @@ Graph Generation Targeting Modularity”, IEEE Infocom, ‘18. <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.stochastic.stochastic_graph.html b/reference/generated/networkx.generators.stochastic.stochastic_graph.html index 170cc817..5641af95 100644 --- a/reference/generated/networkx.generators.stochastic.stochastic_graph.html +++ b/reference/generated/networkx.generators.stochastic.stochastic_graph.html @@ -725,7 +725,7 @@ has a weight, it must be a positive number.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.sudoku.sudoku_graph.html b/reference/generated/networkx.generators.sudoku.sudoku_graph.html index 3de68256..75df1519 100644 --- a/reference/generated/networkx.generators.sudoku.sudoku_graph.html +++ b/reference/generated/networkx.generators.sudoku.sudoku_graph.html @@ -755,7 +755,7 @@ Encyclopedia, 3 Dec. 2019. Web. 22 Dec. 2019.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.trees.prefix_tree.html b/reference/generated/networkx.generators.trees.prefix_tree.html index fa2d0ed2..9bd1c4f9 100644 --- a/reference/generated/networkx.generators.trees.prefix_tree.html +++ b/reference/generated/networkx.generators.trees.prefix_tree.html @@ -782,7 +782,7 @@ traverse up the tree from the node <code class="xref py py-obj docutils literal <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.trees.random_tree.html b/reference/generated/networkx.generators.trees.random_tree.html index ec7f593d..fa8850de 100644 --- a/reference/generated/networkx.generators.trees.random_tree.html +++ b/reference/generated/networkx.generators.trees.random_tree.html @@ -766,7 +766,7 @@ all trees on <em>n</em> nodes.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.generators.triads.triad_graph.html b/reference/generated/networkx.generators.triads.triad_graph.html index 4091e072..299ebd09 100644 --- a/reference/generated/networkx.generators.triads.triad_graph.html +++ b/reference/generated/networkx.generators.triads.triad_graph.html @@ -738,7 +738,7 @@ graph are the single-character strings ‘a’, ‘b’, and ‘c’.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.algebraicconnectivity.algebraic_connectivity.html b/reference/generated/networkx.linalg.algebraicconnectivity.algebraic_connectivity.html index 24912b99..d635498c 100644 --- a/reference/generated/networkx.linalg.algebraicconnectivity.algebraic_connectivity.html +++ b/reference/generated/networkx.linalg.algebraicconnectivity.algebraic_connectivity.html @@ -665,7 +665,7 @@ weights of parallel edges are summed. Zero-weighted edges are ignored.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.algebraicconnectivity.fiedler_vector.html b/reference/generated/networkx.linalg.algebraicconnectivity.fiedler_vector.html index cc5277da..b01427d7 100644 --- a/reference/generated/networkx.linalg.algebraicconnectivity.fiedler_vector.html +++ b/reference/generated/networkx.linalg.algebraicconnectivity.fiedler_vector.html @@ -665,7 +665,7 @@ used to partition the graph into two components.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.algebraicconnectivity.spectral_ordering.html b/reference/generated/networkx.linalg.algebraicconnectivity.spectral_ordering.html index bd93bf34..7224911b 100644 --- a/reference/generated/networkx.linalg.algebraicconnectivity.spectral_ordering.html +++ b/reference/generated/networkx.linalg.algebraicconnectivity.spectral_ordering.html @@ -653,7 +653,7 @@ weights of parallel edges are summed. Zero-weighted edges are ignored.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.attrmatrix.attr_matrix.html b/reference/generated/networkx.linalg.attrmatrix.attr_matrix.html index 2b857c6b..965dc085 100644 --- a/reference/generated/networkx.linalg.attrmatrix.attr_matrix.html +++ b/reference/generated/networkx.linalg.attrmatrix.attr_matrix.html @@ -700,7 +700,7 @@ Pr( v is blue | u is blue) = 0</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.attrmatrix.attr_sparse_matrix.html b/reference/generated/networkx.linalg.attrmatrix.attr_sparse_matrix.html index 6d19db37..040d03a9 100644 --- a/reference/generated/networkx.linalg.attrmatrix.attr_sparse_matrix.html +++ b/reference/generated/networkx.linalg.attrmatrix.attr_sparse_matrix.html @@ -700,7 +700,7 @@ Pr( v is blue | u is blue) = 0</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.bethehessianmatrix.bethe_hessian_matrix.html b/reference/generated/networkx.linalg.bethehessianmatrix.bethe_hessian_matrix.html index 46dbcf63..84caa2d1 100644 --- a/reference/generated/networkx.linalg.bethehessianmatrix.bethe_hessian_matrix.html +++ b/reference/generated/networkx.linalg.bethehessianmatrix.bethe_hessian_matrix.html @@ -652,7 +652,7 @@ arXiv:1507.00827, 2015.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.graphmatrix.adjacency_matrix.html b/reference/generated/networkx.linalg.graphmatrix.adjacency_matrix.html index 89d2ee09..aa7a2976 100644 --- a/reference/generated/networkx.linalg.graphmatrix.adjacency_matrix.html +++ b/reference/generated/networkx.linalg.graphmatrix.adjacency_matrix.html @@ -644,7 +644,7 @@ resulting SciPy sparse array can be modified as follows:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.graphmatrix.incidence_matrix.html b/reference/generated/networkx.linalg.graphmatrix.incidence_matrix.html index 5383a434..2247dfe6 100644 --- a/reference/generated/networkx.linalg.graphmatrix.incidence_matrix.html +++ b/reference/generated/networkx.linalg.graphmatrix.incidence_matrix.html @@ -636,7 +636,7 @@ applied mathematics” <a class="reference internal" href="#rc00baef831a0-1" id= <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.laplacianmatrix.directed_combinatorial_laplacian_matrix.html b/reference/generated/networkx.linalg.laplacianmatrix.directed_combinatorial_laplacian_matrix.html index 1acc9b9e..304d2879 100644 --- a/reference/generated/networkx.linalg.laplacianmatrix.directed_combinatorial_laplacian_matrix.html +++ b/reference/generated/networkx.linalg.laplacianmatrix.directed_combinatorial_laplacian_matrix.html @@ -641,7 +641,7 @@ Annals of Combinatorics, 9(1), 2005</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.laplacianmatrix.directed_laplacian_matrix.html b/reference/generated/networkx.linalg.laplacianmatrix.directed_laplacian_matrix.html index 2cfc7633..9f443961 100644 --- a/reference/generated/networkx.linalg.laplacianmatrix.directed_laplacian_matrix.html +++ b/reference/generated/networkx.linalg.laplacianmatrix.directed_laplacian_matrix.html @@ -642,7 +642,7 @@ Annals of Combinatorics, 9(1), 2005</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.laplacianmatrix.laplacian_matrix.html b/reference/generated/networkx.linalg.laplacianmatrix.laplacian_matrix.html index f1627eed..7e1c782e 100644 --- a/reference/generated/networkx.linalg.laplacianmatrix.laplacian_matrix.html +++ b/reference/generated/networkx.linalg.laplacianmatrix.laplacian_matrix.html @@ -635,7 +635,7 @@ matrix for each component.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.laplacianmatrix.normalized_laplacian_matrix.html b/reference/generated/networkx.linalg.laplacianmatrix.normalized_laplacian_matrix.html index 871af6ac..0ced3b33 100644 --- a/reference/generated/networkx.linalg.laplacianmatrix.normalized_laplacian_matrix.html +++ b/reference/generated/networkx.linalg.laplacianmatrix.normalized_laplacian_matrix.html @@ -642,7 +642,7 @@ March 2007.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.modularitymatrix.directed_modularity_matrix.html b/reference/generated/networkx.linalg.modularitymatrix.directed_modularity_matrix.html index c74d73ea..4db898e3 100644 --- a/reference/generated/networkx.linalg.modularitymatrix.directed_modularity_matrix.html +++ b/reference/generated/networkx.linalg.modularitymatrix.directed_modularity_matrix.html @@ -662,7 +662,7 @@ Phys. Rev Lett., vol. 100, no. 11, p. 118703, 2008.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.modularitymatrix.modularity_matrix.html b/reference/generated/networkx.linalg.modularitymatrix.modularity_matrix.html index f74b2ce6..1007cf36 100644 --- a/reference/generated/networkx.linalg.modularitymatrix.modularity_matrix.html +++ b/reference/generated/networkx.linalg.modularitymatrix.modularity_matrix.html @@ -643,7 +643,7 @@ Proc. Natl. Acad. Sci. USA, vol. 103, pp. 8577-8582, 2006.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.spectrum.adjacency_spectrum.html b/reference/generated/networkx.linalg.spectrum.adjacency_spectrum.html index 89b5d6b1..3d63f6c5 100644 --- a/reference/generated/networkx.linalg.spectrum.adjacency_spectrum.html +++ b/reference/generated/networkx.linalg.spectrum.adjacency_spectrum.html @@ -616,7 +616,7 @@ See to_numpy_array for other options.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.spectrum.bethe_hessian_spectrum.html b/reference/generated/networkx.linalg.spectrum.bethe_hessian_spectrum.html index ae0cc81a..ce5e69ef 100644 --- a/reference/generated/networkx.linalg.spectrum.bethe_hessian_spectrum.html +++ b/reference/generated/networkx.linalg.spectrum.bethe_hessian_spectrum.html @@ -621,7 +621,7 @@ Advances in Neural Information Processing Systems. 2014.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.spectrum.laplacian_spectrum.html b/reference/generated/networkx.linalg.spectrum.laplacian_spectrum.html index 74f52c06..a1a9ba3b 100644 --- a/reference/generated/networkx.linalg.spectrum.laplacian_spectrum.html +++ b/reference/generated/networkx.linalg.spectrum.laplacian_spectrum.html @@ -626,7 +626,7 @@ to the number of connected components of G.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.spectrum.modularity_spectrum.html b/reference/generated/networkx.linalg.spectrum.modularity_spectrum.html index 9676ad0c..8b6aadfb 100644 --- a/reference/generated/networkx.linalg.spectrum.modularity_spectrum.html +++ b/reference/generated/networkx.linalg.spectrum.modularity_spectrum.html @@ -618,7 +618,7 @@ Proc. Natl. Acad. Sci. USA, vol. 103, pp. 8577-8582, 2006.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.linalg.spectrum.normalized_laplacian_spectrum.html b/reference/generated/networkx.linalg.spectrum.normalized_laplacian_spectrum.html index 524c3e66..0e01153e 100644 --- a/reference/generated/networkx.linalg.spectrum.normalized_laplacian_spectrum.html +++ b/reference/generated/networkx.linalg.spectrum.normalized_laplacian_spectrum.html @@ -616,7 +616,7 @@ See to_numpy_array for other options.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.relabel.convert_node_labels_to_integers.html b/reference/generated/networkx.relabel.convert_node_labels_to_integers.html index e9c6091d..afef2bcf 100644 --- a/reference/generated/networkx.relabel.convert_node_labels_to_integers.html +++ b/reference/generated/networkx.relabel.convert_node_labels_to_integers.html @@ -604,7 +604,7 @@ Use the <code class="xref py py-obj docutils literal notranslate"><span class="p <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.relabel.relabel_nodes.html b/reference/generated/networkx.relabel.relabel_nodes.html index 30c2cc79..61904fe8 100644 --- a/reference/generated/networkx.relabel.relabel_nodes.html +++ b/reference/generated/networkx.relabel.relabel_nodes.html @@ -678,7 +678,7 @@ will retain all edges, but may change the edge keys in the process:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.decorators.argmap.html b/reference/generated/networkx.utils.decorators.argmap.html index 6239b0cc..e9e40cbd 100644 --- a/reference/generated/networkx.utils.decorators.argmap.html +++ b/reference/generated/networkx.utils.decorators.argmap.html @@ -941,7 +941,7 @@ the caller has a chance to exhaust the iterator.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.decorators.nodes_or_number.html b/reference/generated/networkx.utils.decorators.nodes_or_number.html index 20944608..4499cce1 100644 --- a/reference/generated/networkx.utils.decorators.nodes_or_number.html +++ b/reference/generated/networkx.utils.decorators.nodes_or_number.html @@ -642,7 +642,7 @@ If more than one node argument is allowed, can be a list of locations.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.decorators.not_implemented_for.html b/reference/generated/networkx.utils.decorators.not_implemented_for.html index eff19aac..4937647a 100644 --- a/reference/generated/networkx.utils.decorators.not_implemented_for.html +++ b/reference/generated/networkx.utils.decorators.not_implemented_for.html @@ -639,7 +639,7 @@ For “or” use multiple @not_implemented_for() lines.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.decorators.np_random_state.html b/reference/generated/networkx.utils.decorators.np_random_state.html index 443e4f3d..ba9ffe0c 100644 --- a/reference/generated/networkx.utils.decorators.np_random_state.html +++ b/reference/generated/networkx.utils.decorators.np_random_state.html @@ -640,7 +640,7 @@ to a <a class="reference external" href="https://numpy.org/doc/stable/reference/ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.decorators.open_file.html b/reference/generated/networkx.utils.decorators.open_file.html index d0ba91ab..bb0fcebb 100644 --- a/reference/generated/networkx.utils.decorators.open_file.html +++ b/reference/generated/networkx.utils.decorators.open_file.html @@ -665,7 +665,7 @@ When we exit the function, fobj will be closed, if it should be, by the decorato <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.decorators.py_random_state.html b/reference/generated/networkx.utils.decorators.py_random_state.html index a548ca74..636416cc 100644 --- a/reference/generated/networkx.utils.decorators.py_random_state.html +++ b/reference/generated/networkx.utils.decorators.py_random_state.html @@ -649,7 +649,7 @@ instance that mimics basic methods of random.Random.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.mapped_queue.MappedQueue.html b/reference/generated/networkx.utils.mapped_queue.MappedQueue.html index f891bf68..c6686bdd 100644 --- a/reference/generated/networkx.utils.mapped_queue.MappedQueue.html +++ b/reference/generated/networkx.utils.mapped_queue.MappedQueue.html @@ -695,7 +695,7 @@ to be the sort order of the items in the list.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.misc.arbitrary_element.html b/reference/generated/networkx.utils.misc.arbitrary_element.html index 48309d8e..b07989e8 100644 --- a/reference/generated/networkx.utils.misc.arbitrary_element.html +++ b/reference/generated/networkx.utils.misc.arbitrary_element.html @@ -580,7 +580,7 @@ ordered, sequential calls will return the same value:</p> <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">iterator</span> <span class="o">=</span> <span class="nb">iter</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span> <span class="c1"># Iterator, *not* Iterable</span> <span class="gp">>>> </span><span class="n">nx</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">arbitrary_element</span><span class="p">(</span><span class="n">iterator</span><span class="p">)</span> <span class="gt">Traceback (most recent call last):</span> - <span class="o">...</span> +<span class="w"> </span><span class="o">...</span> <span class="gr">ValueError</span>: <span class="n">cannot return an arbitrary item from an iterator</span> </pre></div> </div> @@ -659,7 +659,7 @@ ordered, sequential calls will return the same value:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.misc.create_py_random_state.html b/reference/generated/networkx.utils.misc.create_py_random_state.html index 76d04cf5..718f8725 100644 --- a/reference/generated/networkx.utils.misc.create_py_random_state.html +++ b/reference/generated/networkx.utils.misc.create_py_random_state.html @@ -614,7 +614,7 @@ if a PythonRandomInterface instance, return it</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.misc.create_random_state.html b/reference/generated/networkx.utils.misc.create_random_state.html index 1e84053e..21b33690 100644 --- a/reference/generated/networkx.utils.misc.create_random_state.html +++ b/reference/generated/networkx.utils.misc.create_random_state.html @@ -611,7 +611,7 @@ by numpy.random.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.misc.dict_to_numpy_array.html b/reference/generated/networkx.utils.misc.dict_to_numpy_array.html index e7c9f2b2..e67dc79d 100644 --- a/reference/generated/networkx.utils.misc.dict_to_numpy_array.html +++ b/reference/generated/networkx.utils.misc.dict_to_numpy_array.html @@ -599,7 +599,7 @@ with optional mapping.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.misc.edges_equal.html b/reference/generated/networkx.utils.misc.edges_equal.html index caa9a9ad..ba596990 100644 --- a/reference/generated/networkx.utils.misc.edges_equal.html +++ b/reference/generated/networkx.utils.misc.edges_equal.html @@ -617,7 +617,7 @@ edge tuples with keys and data dicts (u, v, k, d)</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.misc.flatten.html b/reference/generated/networkx.utils.misc.flatten.html index 795f69e0..5894f044 100644 --- a/reference/generated/networkx.utils.misc.flatten.html +++ b/reference/generated/networkx.utils.misc.flatten.html @@ -598,7 +598,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.misc.graphs_equal.html b/reference/generated/networkx.utils.misc.graphs_equal.html index 8cb1c89d..6f370c21 100644 --- a/reference/generated/networkx.utils.misc.graphs_equal.html +++ b/reference/generated/networkx.utils.misc.graphs_equal.html @@ -613,7 +613,7 @@ Node, edge and graph data must match.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.misc.groups.html b/reference/generated/networkx.utils.misc.groups.html index ebf150bb..2931adee 100644 --- a/reference/generated/networkx.utils.misc.groups.html +++ b/reference/generated/networkx.utils.misc.groups.html @@ -609,7 +609,7 @@ to sets of keys from <code class="xref py py-obj docutils literal notranslate">< <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.misc.make_list_of_ints.html b/reference/generated/networkx.utils.misc.make_list_of_ints.html index 823c126f..35d1834c 100644 --- a/reference/generated/networkx.utils.misc.make_list_of_ints.html +++ b/reference/generated/networkx.utils.misc.make_list_of_ints.html @@ -602,7 +602,7 @@ So, no new list is created</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.misc.nodes_equal.html b/reference/generated/networkx.utils.misc.nodes_equal.html index 742aca1c..2f73f0d7 100644 --- a/reference/generated/networkx.utils.misc.nodes_equal.html +++ b/reference/generated/networkx.utils.misc.nodes_equal.html @@ -614,7 +614,7 @@ The order of nodes is not relevant.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.misc.pairwise.html b/reference/generated/networkx.utils.misc.pairwise.html index f306cfb9..acbb70ad 100644 --- a/reference/generated/networkx.utils.misc.pairwise.html +++ b/reference/generated/networkx.utils.misc.pairwise.html @@ -598,7 +598,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.random_sequence.cumulative_distribution.html b/reference/generated/networkx.utils.random_sequence.cumulative_distribution.html index 4074e580..d9a3ea60 100644 --- a/reference/generated/networkx.utils.random_sequence.cumulative_distribution.html +++ b/reference/generated/networkx.utils.random_sequence.cumulative_distribution.html @@ -598,7 +598,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.random_sequence.discrete_sequence.html b/reference/generated/networkx.utils.random_sequence.discrete_sequence.html index 32747878..7535b691 100644 --- a/reference/generated/networkx.utils.random_sequence.discrete_sequence.html +++ b/reference/generated/networkx.utils.random_sequence.discrete_sequence.html @@ -602,7 +602,7 @@ or discrete cumulative distribution.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.random_sequence.powerlaw_sequence.html b/reference/generated/networkx.utils.random_sequence.powerlaw_sequence.html index 9a07374b..87c6e7ae 100644 --- a/reference/generated/networkx.utils.random_sequence.powerlaw_sequence.html +++ b/reference/generated/networkx.utils.random_sequence.powerlaw_sequence.html @@ -598,7 +598,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.random_sequence.random_weighted_sample.html b/reference/generated/networkx.utils.random_sequence.random_weighted_sample.html index f217f168..3a35ebfb 100644 --- a/reference/generated/networkx.utils.random_sequence.random_weighted_sample.html +++ b/reference/generated/networkx.utils.random_sequence.random_weighted_sample.html @@ -599,7 +599,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.random_sequence.weighted_choice.html b/reference/generated/networkx.utils.random_sequence.weighted_choice.html index 8a1d549e..c78d2e63 100644 --- a/reference/generated/networkx.utils.random_sequence.weighted_choice.html +++ b/reference/generated/networkx.utils.random_sequence.weighted_choice.html @@ -599,7 +599,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.random_sequence.zipf_rv.html b/reference/generated/networkx.utils.random_sequence.zipf_rv.html index d68afac2..98eeec16 100644 --- a/reference/generated/networkx.utils.random_sequence.zipf_rv.html +++ b/reference/generated/networkx.utils.random_sequence.zipf_rv.html @@ -646,7 +646,7 @@ Springer-Verlag, New York, 1986.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.rcm.cuthill_mckee_ordering.html b/reference/generated/networkx.utils.rcm.cuthill_mckee_ordering.html index 5b1ef0b0..6d985168 100644 --- a/reference/generated/networkx.utils.rcm.cuthill_mckee_ordering.html +++ b/reference/generated/networkx.utils.rcm.cuthill_mckee_ordering.html @@ -654,7 +654,7 @@ Springer-Verlag New York, Inc., New York, NY, USA.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.rcm.reverse_cuthill_mckee_ordering.html b/reference/generated/networkx.utils.rcm.reverse_cuthill_mckee_ordering.html index 8aadf291..d369c555 100644 --- a/reference/generated/networkx.utils.rcm.reverse_cuthill_mckee_ordering.html +++ b/reference/generated/networkx.utils.rcm.reverse_cuthill_mckee_ordering.html @@ -655,7 +655,7 @@ Springer-Verlag New York, Inc., New York, NY, USA.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generated/networkx.utils.union_find.UnionFind.union.html b/reference/generated/networkx.utils.union_find.UnionFind.union.html index 719fd9b2..5260eb33 100644 --- a/reference/generated/networkx.utils.union_find.UnionFind.union.html +++ b/reference/generated/networkx.utils.union_find.UnionFind.union.html @@ -598,7 +598,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/generators.html b/reference/generators.html index 4e587ee1..60cc8ace 100644 --- a/reference/generators.html +++ b/reference/generators.html @@ -1623,7 +1623,7 @@ Encyclopedia, 3 Dec. 2019. Web. 22 Dec. 2019.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/glossary.html b/reference/glossary.html index f50a4ff5..bd32366c 100644 --- a/reference/glossary.html +++ b/reference/glossary.html @@ -570,7 +570,7 @@ specified node <code class="xref py py-obj docutils literal notranslate"><span c <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/index.html b/reference/index.html index af120adb..aaa1b53c 100644 --- a/reference/index.html +++ b/reference/index.html @@ -496,7 +496,7 @@ <dd class="field-odd"><p>3.0rc2.dev0</p> </dd> <dt class="field-even">Date<span class="colon">:</span></dt> -<dd class="field-even"><p>Dec 27, 2022</p> +<dd class="field-even"><p>Jan 02, 2023</p> </dd> </dl> </div></blockquote> @@ -759,7 +759,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/introduction-7.hires.png b/reference/introduction-7.hires.png Binary files differindex 7ee912b5..a338d753 100644 --- a/reference/introduction-7.hires.png +++ b/reference/introduction-7.hires.png diff --git a/reference/introduction-7.pdf b/reference/introduction-7.pdf Binary files differindex 6e401c8a..24078ffd 100644 --- a/reference/introduction-7.pdf +++ b/reference/introduction-7.pdf diff --git a/reference/introduction-7.png b/reference/introduction-7.png Binary files differindex a8f22d18..1a5a2c98 100644 --- a/reference/introduction-7.png +++ b/reference/introduction-7.png diff --git a/reference/introduction.html b/reference/introduction.html index 259e5d35..f5f1534b 100644 --- a/reference/introduction.html +++ b/reference/introduction.html @@ -898,7 +898,7 @@ and edges. So <code class="docutils literal notranslate"><span class="pre">G[u][ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/introduction.ipynb b/reference/introduction.ipynb index 8982e097..78824535 100644 --- a/reference/introduction.ipynb +++ b/reference/introduction.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "9d5533ae", + "id": "460bb211", "metadata": {}, "source": [ "## Introduction\n", @@ -34,7 +34,7 @@ { "cell_type": "code", "execution_count": null, - "id": "76e4aa8f", + "id": "1ea1fa59", "metadata": {}, "outputs": [], "source": [ @@ -43,7 +43,7 @@ }, { "cell_type": "markdown", - "id": "bfd347b0", + "id": "e548cbe6", "metadata": {}, "source": [ "To save repetition, in the documentation we assume that\n", @@ -82,7 +82,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7a7f6002", + "id": "85de9aeb", "metadata": {}, "outputs": [], "source": [ @@ -94,7 +94,7 @@ }, { "cell_type": "markdown", - "id": "ab96731c", + "id": "aeefd720", "metadata": {}, "source": [ "All graph classes allow any [hashable](https://docs.python.org/3/glossary.html#term-hashable) object as a node.\n", @@ -193,7 +193,7 @@ { "cell_type": "code", "execution_count": null, - "id": "22ef1e39", + "id": "37e6adfb", "metadata": {}, "outputs": [], "source": [ @@ -205,7 +205,7 @@ }, { "cell_type": "markdown", - "id": "1ee1e93a", + "id": "1ee398d6", "metadata": {}, "source": [ "Edge attributes can be anything:" @@ -214,7 +214,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8ff42fba", + "id": "a13afd73", "metadata": {}, "outputs": [], "source": [ @@ -225,7 +225,7 @@ }, { "cell_type": "markdown", - "id": "3ebfa9f2", + "id": "9b4f6830", "metadata": {}, "source": [ "You can add many edges at one time:" @@ -234,7 +234,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e03def6b", + "id": "8577401d", "metadata": {}, "outputs": [], "source": [ @@ -246,7 +246,7 @@ }, { "cell_type": "markdown", - "id": "17934fe1", + "id": "5d054728", "metadata": {}, "source": [ "See the Tutorial for more examples.\n", @@ -311,7 +311,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7d1c8923", + "id": "2d598f2f", "metadata": {}, "outputs": [], "source": [ @@ -323,7 +323,7 @@ }, { "cell_type": "markdown", - "id": "89d24b8a", + "id": "e20d6c24", "metadata": {}, "source": [ "# Drawing\n", @@ -344,7 +344,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1ba5345b", + "id": "0777150c", "metadata": {}, "outputs": [], "source": [ @@ -358,7 +358,7 @@ }, { "cell_type": "markdown", - "id": "646a54d7", + "id": "b7fc5217", "metadata": {}, "source": [ "See the examples for more ideas.\n", @@ -398,7 +398,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7e22369f", + "id": "d8ddc593", "metadata": {}, "outputs": [], "source": [ @@ -410,7 +410,7 @@ }, { "cell_type": "markdown", - "id": "b526c8f3", + "id": "26cc6ce1", "metadata": {}, "source": [ "The data structure gets morphed slightly for each base graph class.\n", @@ -428,7 +428,7 @@ { "cell_type": "code", "execution_count": null, - "id": "bde32d2a", + "id": "097de0f5", "metadata": {}, "outputs": [], "source": [ diff --git a/reference/introduction_full.ipynb b/reference/introduction_full.ipynb index 623ebc6f..cd8b5130 100644 --- a/reference/introduction_full.ipynb +++ b/reference/introduction_full.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "9d5533ae", + "id": "460bb211", "metadata": {}, "source": [ "## Introduction\n", @@ -34,13 +34,13 @@ { "cell_type": "code", "execution_count": 1, - "id": "76e4aa8f", + "id": "1ea1fa59", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:45.908976Z", - "iopub.status.busy": "2022-12-27T10:11:45.908396Z", - "iopub.status.idle": "2022-12-27T10:11:45.981875Z", - "shell.execute_reply": "2022-12-27T10:11:45.981223Z" + "iopub.execute_input": "2023-01-02T13:06:41.690885Z", + "iopub.status.busy": "2023-01-02T13:06:41.690301Z", + "iopub.status.idle": "2023-01-02T13:06:41.790926Z", + "shell.execute_reply": "2023-01-02T13:06:41.789837Z" } }, "outputs": [], @@ -50,7 +50,7 @@ }, { "cell_type": "markdown", - "id": "bfd347b0", + "id": "e548cbe6", "metadata": {}, "source": [ "To save repetition, in the documentation we assume that\n", @@ -89,13 +89,13 @@ { "cell_type": "code", "execution_count": 2, - "id": "7a7f6002", + "id": "85de9aeb", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:45.985479Z", - "iopub.status.busy": "2022-12-27T10:11:45.985259Z", - "iopub.status.idle": "2022-12-27T10:11:45.988574Z", - "shell.execute_reply": "2022-12-27T10:11:45.988041Z" + "iopub.execute_input": "2023-01-02T13:06:41.795235Z", + "iopub.status.busy": "2023-01-02T13:06:41.794963Z", + "iopub.status.idle": "2023-01-02T13:06:41.798977Z", + "shell.execute_reply": "2023-01-02T13:06:41.798159Z" } }, "outputs": [], @@ -108,7 +108,7 @@ }, { "cell_type": "markdown", - "id": "ab96731c", + "id": "aeefd720", "metadata": {}, "source": [ "All graph classes allow any [hashable](https://docs.python.org/3/glossary.html#term-hashable) object as a node.\n", @@ -207,13 +207,13 @@ { "cell_type": "code", "execution_count": 3, - "id": "22ef1e39", + "id": "37e6adfb", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:45.991227Z", - "iopub.status.busy": "2022-12-27T10:11:45.991018Z", - "iopub.status.idle": "2022-12-27T10:11:45.994342Z", - "shell.execute_reply": "2022-12-27T10:11:45.993719Z" + "iopub.execute_input": "2023-01-02T13:06:41.803233Z", + "iopub.status.busy": "2023-01-02T13:06:41.802967Z", + "iopub.status.idle": "2023-01-02T13:06:41.807197Z", + "shell.execute_reply": "2023-01-02T13:06:41.806363Z" } }, "outputs": [], @@ -226,7 +226,7 @@ }, { "cell_type": "markdown", - "id": "1ee1e93a", + "id": "1ee398d6", "metadata": {}, "source": [ "Edge attributes can be anything:" @@ -235,13 +235,13 @@ { "cell_type": "code", "execution_count": 4, - "id": "8ff42fba", + "id": "a13afd73", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:45.997271Z", - "iopub.status.busy": "2022-12-27T10:11:45.997066Z", - "iopub.status.idle": "2022-12-27T10:11:46.000114Z", - "shell.execute_reply": "2022-12-27T10:11:45.999488Z" + "iopub.execute_input": "2023-01-02T13:06:41.811069Z", + "iopub.status.busy": "2023-01-02T13:06:41.810810Z", + "iopub.status.idle": "2023-01-02T13:06:41.814696Z", + "shell.execute_reply": "2023-01-02T13:06:41.813827Z" } }, "outputs": [], @@ -253,7 +253,7 @@ }, { "cell_type": "markdown", - "id": "3ebfa9f2", + "id": "9b4f6830", "metadata": {}, "source": [ "You can add many edges at one time:" @@ -262,13 +262,13 @@ { "cell_type": "code", "execution_count": 5, - "id": "e03def6b", + "id": "8577401d", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:46.003106Z", - "iopub.status.busy": "2022-12-27T10:11:46.002901Z", - "iopub.status.idle": "2022-12-27T10:11:46.008311Z", - "shell.execute_reply": "2022-12-27T10:11:46.007368Z" + "iopub.execute_input": "2023-01-02T13:06:41.818445Z", + "iopub.status.busy": "2023-01-02T13:06:41.818145Z", + "iopub.status.idle": "2023-01-02T13:06:41.823261Z", + "shell.execute_reply": "2023-01-02T13:06:41.822449Z" } }, "outputs": [], @@ -281,7 +281,7 @@ }, { "cell_type": "markdown", - "id": "17934fe1", + "id": "5d054728", "metadata": {}, "source": [ "See the Tutorial for more examples.\n", @@ -346,13 +346,13 @@ { "cell_type": "code", "execution_count": 6, - "id": "7d1c8923", + "id": "2d598f2f", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:46.011509Z", - "iopub.status.busy": "2022-12-27T10:11:46.011111Z", - "iopub.status.idle": "2022-12-27T10:11:46.017660Z", - "shell.execute_reply": "2022-12-27T10:11:46.017053Z" + "iopub.execute_input": "2023-01-02T13:06:41.826834Z", + "iopub.status.busy": "2023-01-02T13:06:41.826598Z", + "iopub.status.idle": "2023-01-02T13:06:41.835198Z", + "shell.execute_reply": "2023-01-02T13:06:41.834223Z" } }, "outputs": [ @@ -373,7 +373,7 @@ }, { "cell_type": "markdown", - "id": "89d24b8a", + "id": "e20d6c24", "metadata": {}, "source": [ "# Drawing\n", @@ -394,19 +394,19 @@ { "cell_type": "code", "execution_count": 7, - "id": "1ba5345b", + "id": "0777150c", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:46.020632Z", - "iopub.status.busy": "2022-12-27T10:11:46.020289Z", - "iopub.status.idle": "2022-12-27T10:11:46.584477Z", - "shell.execute_reply": "2022-12-27T10:11:46.583674Z" + "iopub.execute_input": "2023-01-02T13:06:41.839092Z", + "iopub.status.busy": "2023-01-02T13:06:41.838825Z", + "iopub.status.idle": "2023-01-02T13:06:42.599406Z", + "shell.execute_reply": "2023-01-02T13:06:42.598612Z" } }, "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "<Figure size 640x480 with 2 Axes>" ] @@ -426,7 +426,7 @@ }, { "cell_type": "markdown", - "id": "646a54d7", + "id": "b7fc5217", "metadata": {}, "source": [ "See the examples for more ideas.\n", @@ -466,13 +466,13 @@ { "cell_type": "code", "execution_count": 8, - "id": "7e22369f", + "id": "d8ddc593", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:46.588763Z", - "iopub.status.busy": "2022-12-27T10:11:46.588111Z", - "iopub.status.idle": "2022-12-27T10:11:46.592193Z", - "shell.execute_reply": "2022-12-27T10:11:46.591664Z" + "iopub.execute_input": "2023-01-02T13:06:42.604374Z", + "iopub.status.busy": "2023-01-02T13:06:42.603650Z", + "iopub.status.idle": "2023-01-02T13:06:42.609093Z", + "shell.execute_reply": "2023-01-02T13:06:42.608292Z" } }, "outputs": [ @@ -493,7 +493,7 @@ }, { "cell_type": "markdown", - "id": "b526c8f3", + "id": "26cc6ce1", "metadata": {}, "source": [ "The data structure gets morphed slightly for each base graph class.\n", @@ -511,13 +511,13 @@ { "cell_type": "code", "execution_count": 9, - "id": "bde32d2a", + "id": "097de0f5", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:46.594914Z", - "iopub.status.busy": "2022-12-27T10:11:46.594501Z", - "iopub.status.idle": "2022-12-27T10:11:46.598557Z", - "shell.execute_reply": "2022-12-27T10:11:46.598051Z" + "iopub.execute_input": "2023-01-02T13:06:42.613625Z", + "iopub.status.busy": "2023-01-02T13:06:42.613122Z", + "iopub.status.idle": "2023-01-02T13:06:42.618868Z", + "shell.execute_reply": "2023-01-02T13:06:42.618069Z" } }, "outputs": [ diff --git a/reference/linalg.html b/reference/linalg.html index ad734966..e4edc260 100644 --- a/reference/linalg.html +++ b/reference/linalg.html @@ -723,7 +723,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/randomness.html b/reference/randomness.html index 6160e758..48374aba 100644 --- a/reference/randomness.html +++ b/reference/randomness.html @@ -615,7 +615,7 @@ your computations.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/adjlist.html b/reference/readwrite/adjlist.html index 94862ff6..216e50bf 100644 --- a/reference/readwrite/adjlist.html +++ b/reference/readwrite/adjlist.html @@ -605,7 +605,7 @@ adjacency list (anything following the # in a line is a comment):</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/edgelist.html b/reference/readwrite/edgelist.html index 9977958d..a08cb901 100644 --- a/reference/readwrite/edgelist.html +++ b/reference/readwrite/edgelist.html @@ -616,7 +616,7 @@ self-loop edge.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.adjlist.generate_adjlist.html b/reference/readwrite/generated/networkx.readwrite.adjlist.generate_adjlist.html index ab546c83..c47cf530 100644 --- a/reference/readwrite/generated/networkx.readwrite.adjlist.generate_adjlist.html +++ b/reference/readwrite/generated/networkx.readwrite.adjlist.generate_adjlist.html @@ -621,7 +621,7 @@ valid in node names.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.adjlist.parse_adjlist.html b/reference/readwrite/generated/networkx.readwrite.adjlist.parse_adjlist.html index fe5b8926..78f59151 100644 --- a/reference/readwrite/generated/networkx.readwrite.adjlist.parse_adjlist.html +++ b/reference/readwrite/generated/networkx.readwrite.adjlist.parse_adjlist.html @@ -621,7 +621,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.adjlist.read_adjlist.html b/reference/readwrite/generated/networkx.readwrite.adjlist.read_adjlist.html index 8977fc28..b82193bc 100644 --- a/reference/readwrite/generated/networkx.readwrite.adjlist.read_adjlist.html +++ b/reference/readwrite/generated/networkx.readwrite.adjlist.read_adjlist.html @@ -644,7 +644,7 @@ To read the data as a directed graph use</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.adjlist.write_adjlist.html b/reference/readwrite/generated/networkx.readwrite.adjlist.write_adjlist.html index a1f19002..93fdc780 100644 --- a/reference/readwrite/generated/networkx.readwrite.adjlist.write_adjlist.html +++ b/reference/readwrite/generated/networkx.readwrite.adjlist.write_adjlist.html @@ -621,7 +621,7 @@ filehandle is provided, it has to be opened in ‘wb’ mode.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.edgelist.generate_edgelist.html b/reference/readwrite/generated/networkx.readwrite.edgelist.generate_edgelist.html index fdd66294..dc97b75a 100644 --- a/reference/readwrite/generated/networkx.readwrite.edgelist.generate_edgelist.html +++ b/reference/readwrite/generated/networkx.readwrite.edgelist.generate_edgelist.html @@ -650,7 +650,7 @@ values corresponding to the keys.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.edgelist.parse_edgelist.html b/reference/readwrite/generated/networkx.readwrite.edgelist.parse_edgelist.html index 6a8e5ff4..2fa22d70 100644 --- a/reference/readwrite/generated/networkx.readwrite.edgelist.parse_edgelist.html +++ b/reference/readwrite/generated/networkx.readwrite.edgelist.parse_edgelist.html @@ -644,7 +644,7 @@ key names and types for edge data.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.edgelist.read_edgelist.html b/reference/readwrite/generated/networkx.readwrite.edgelist.read_edgelist.html index 18c40bf3..1af8ca51 100644 --- a/reference/readwrite/generated/networkx.readwrite.edgelist.read_edgelist.html +++ b/reference/readwrite/generated/networkx.readwrite.edgelist.read_edgelist.html @@ -650,7 +650,7 @@ types (e.g. int, float, str, frozenset - or tuples of those, etc.)</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.edgelist.read_weighted_edgelist.html b/reference/readwrite/generated/networkx.readwrite.edgelist.read_weighted_edgelist.html index 8b90dc0e..2237fbfb 100644 --- a/reference/readwrite/generated/networkx.readwrite.edgelist.read_weighted_edgelist.html +++ b/reference/readwrite/generated/networkx.readwrite.edgelist.read_weighted_edgelist.html @@ -627,7 +627,7 @@ types (e.g. int, float, str, frozenset - or tuples of those, etc.)</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.edgelist.write_edgelist.html b/reference/readwrite/generated/networkx.readwrite.edgelist.write_edgelist.html index 92766e57..a3efe27b 100644 --- a/reference/readwrite/generated/networkx.readwrite.edgelist.write_edgelist.html +++ b/reference/readwrite/generated/networkx.readwrite.edgelist.write_edgelist.html @@ -628,7 +628,7 @@ in the list.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.edgelist.write_weighted_edgelist.html b/reference/readwrite/generated/networkx.readwrite.edgelist.write_weighted_edgelist.html index 452e4706..6a534edb 100644 --- a/reference/readwrite/generated/networkx.readwrite.edgelist.write_weighted_edgelist.html +++ b/reference/readwrite/generated/networkx.readwrite.edgelist.write_weighted_edgelist.html @@ -614,7 +614,7 @@ Filenames ending in .gz or .bz2 will be compressed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.gexf.generate_gexf.html b/reference/readwrite/generated/networkx.readwrite.gexf.generate_gexf.html index 94fdbb5c..71911daa 100644 --- a/reference/readwrite/generated/networkx.readwrite.gexf.generate_gexf.html +++ b/reference/readwrite/generated/networkx.readwrite.gexf.generate_gexf.html @@ -622,7 +622,7 @@ node[‘a’][‘id’]=1 to set the id of node ‘a’ to 1.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.gexf.read_gexf.html b/reference/readwrite/generated/networkx.readwrite.gexf.read_gexf.html index 70b5daae..5b4818ce 100644 --- a/reference/readwrite/generated/networkx.readwrite.gexf.read_gexf.html +++ b/reference/readwrite/generated/networkx.readwrite.gexf.read_gexf.html @@ -618,7 +618,7 @@ edges together).</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.gexf.relabel_gexf_graph.html b/reference/readwrite/generated/networkx.readwrite.gexf.relabel_gexf_graph.html index e74d0cb0..5c228730 100644 --- a/reference/readwrite/generated/networkx.readwrite.gexf.relabel_gexf_graph.html +++ b/reference/readwrite/generated/networkx.readwrite.gexf.relabel_gexf_graph.html @@ -606,7 +606,7 @@ node attributes “parents”, and “pid”.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.gexf.write_gexf.html b/reference/readwrite/generated/networkx.readwrite.gexf.write_gexf.html index 8e6c3871..53b5b4c1 100644 --- a/reference/readwrite/generated/networkx.readwrite.gexf.write_gexf.html +++ b/reference/readwrite/generated/networkx.readwrite.gexf.write_gexf.html @@ -630,7 +630,7 @@ node[‘a’][‘id’]=1 to set the id of node ‘a’ to 1.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.gml.generate_gml.html b/reference/readwrite/generated/networkx.readwrite.gml.generate_gml.html index f7fa0d0a..2108453f 100644 --- a/reference/readwrite/generated/networkx.readwrite.gml.generate_gml.html +++ b/reference/readwrite/generated/networkx.readwrite.gml.generate_gml.html @@ -663,7 +663,7 @@ than <a class="reference external" href="https://docs.python.org/3/library/stdty <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.gml.literal_destringizer.html b/reference/readwrite/generated/networkx.readwrite.gml.literal_destringizer.html index 4f435ab1..cb97b159 100644 --- a/reference/readwrite/generated/networkx.readwrite.gml.literal_destringizer.html +++ b/reference/readwrite/generated/networkx.readwrite.gml.literal_destringizer.html @@ -602,7 +602,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.gml.literal_stringizer.html b/reference/readwrite/generated/networkx.readwrite.gml.literal_stringizer.html index 6584f890..0c1332d4 100644 --- a/reference/readwrite/generated/networkx.readwrite.gml.literal_stringizer.html +++ b/reference/readwrite/generated/networkx.readwrite.gml.literal_stringizer.html @@ -610,7 +610,7 @@ Python 2 and Python 3.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.gml.parse_gml.html b/reference/readwrite/generated/networkx.readwrite.gml.parse_gml.html index 01886b04..85daf9ac 100644 --- a/reference/readwrite/generated/networkx.readwrite.gml.parse_gml.html +++ b/reference/readwrite/generated/networkx.readwrite.gml.parse_gml.html @@ -627,7 +627,7 @@ than <a class="reference external" href="https://docs.python.org/3/library/stdty <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.gml.read_gml.html b/reference/readwrite/generated/networkx.readwrite.gml.read_gml.html index 3e6486bb..b0c4857b 100644 --- a/reference/readwrite/generated/networkx.readwrite.gml.read_gml.html +++ b/reference/readwrite/generated/networkx.readwrite.gml.read_gml.html @@ -644,7 +644,7 @@ For example, integer nodes can be recovered as shown below:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.gml.write_gml.html b/reference/readwrite/generated/networkx.readwrite.gml.write_gml.html index 7a3b96a9..b7d465fe 100644 --- a/reference/readwrite/generated/networkx.readwrite.gml.write_gml.html +++ b/reference/readwrite/generated/networkx.readwrite.gml.write_gml.html @@ -638,7 +638,7 @@ For additional documentation on the GML file format, please see the <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.graph6.from_graph6_bytes.html b/reference/readwrite/generated/networkx.readwrite.graph6.from_graph6_bytes.html index c32fdc04..09df5a84 100644 --- a/reference/readwrite/generated/networkx.readwrite.graph6.from_graph6_bytes.html +++ b/reference/readwrite/generated/networkx.readwrite.graph6.from_graph6_bytes.html @@ -624,7 +624,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.graph6.read_graph6.html b/reference/readwrite/generated/networkx.readwrite.graph6.read_graph6.html index 6bc479ee..0c98c18d 100644 --- a/reference/readwrite/generated/networkx.readwrite.graph6.read_graph6.html +++ b/reference/readwrite/generated/networkx.readwrite.graph6.read_graph6.html @@ -637,7 +637,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.graph6.to_graph6_bytes.html b/reference/readwrite/generated/networkx.readwrite.graph6.to_graph6_bytes.html index 8a12d8eb..542d8d55 100644 --- a/reference/readwrite/generated/networkx.readwrite.graph6.to_graph6_bytes.html +++ b/reference/readwrite/generated/networkx.readwrite.graph6.to_graph6_bytes.html @@ -626,7 +626,7 @@ self loops. If self loops are present they are silently ignored.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.graph6.write_graph6.html b/reference/readwrite/generated/networkx.readwrite.graph6.write_graph6.html index 3b4a4e32..7e86fd38 100644 --- a/reference/readwrite/generated/networkx.readwrite.graph6.write_graph6.html +++ b/reference/readwrite/generated/networkx.readwrite.graph6.write_graph6.html @@ -634,7 +634,7 @@ self loops. If self loops are present they are silently ignored.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.graphml.generate_graphml.html b/reference/readwrite/generated/networkx.readwrite.graphml.generate_graphml.html index 9769fcdf..69eab2c1 100644 --- a/reference/readwrite/generated/networkx.readwrite.graphml.generate_graphml.html +++ b/reference/readwrite/generated/networkx.readwrite.graphml.generate_graphml.html @@ -613,7 +613,7 @@ edges together) hyperedges, nested graphs, or ports.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.graphml.parse_graphml.html b/reference/readwrite/generated/networkx.readwrite.graphml.parse_graphml.html index be43e2cf..c6a134b9 100644 --- a/reference/readwrite/generated/networkx.readwrite.graphml.parse_graphml.html +++ b/reference/readwrite/generated/networkx.readwrite.graphml.parse_graphml.html @@ -635,7 +635,7 @@ will be provided.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.graphml.read_graphml.html b/reference/readwrite/generated/networkx.readwrite.graphml.read_graphml.html index eb94fb39..6e0ef3ee 100644 --- a/reference/readwrite/generated/networkx.readwrite.graphml.read_graphml.html +++ b/reference/readwrite/generated/networkx.readwrite.graphml.read_graphml.html @@ -631,7 +631,7 @@ the file to “file.graphml.gz”.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.graphml.write_graphml.html b/reference/readwrite/generated/networkx.readwrite.graphml.write_graphml.html index c70f6321..861b432e 100644 --- a/reference/readwrite/generated/networkx.readwrite.graphml.write_graphml.html +++ b/reference/readwrite/generated/networkx.readwrite.graphml.write_graphml.html @@ -617,7 +617,7 @@ and unidirected edges together) hyperedges, nested graphs, or ports.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.json_graph.adjacency_data.html b/reference/readwrite/generated/networkx.readwrite.json_graph.adjacency_data.html index 37812e6f..07d76c88 100644 --- a/reference/readwrite/generated/networkx.readwrite.json_graph.adjacency_data.html +++ b/reference/readwrite/generated/networkx.readwrite.json_graph.adjacency_data.html @@ -631,7 +631,7 @@ data with JSON.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.json_graph.adjacency_graph.html b/reference/readwrite/generated/networkx.readwrite.json_graph.adjacency_graph.html index 365eb2e3..fae43279 100644 --- a/reference/readwrite/generated/networkx.readwrite.json_graph.adjacency_graph.html +++ b/reference/readwrite/generated/networkx.readwrite.json_graph.adjacency_graph.html @@ -620,7 +620,7 @@ data. The values should be unique. Default value: <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.json_graph.cytoscape_data.html b/reference/readwrite/generated/networkx.readwrite.json_graph.cytoscape_data.html index 154b7971..4a8598a3 100644 --- a/reference/readwrite/generated/networkx.readwrite.json_graph.cytoscape_data.html +++ b/reference/readwrite/generated/networkx.readwrite.json_graph.cytoscape_data.html @@ -634,7 +634,7 @@ Must not have the same value as <code class="xref py py-obj docutils literal not <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.json_graph.cytoscape_graph.html b/reference/readwrite/generated/networkx.readwrite.json_graph.cytoscape_graph.html index 1f5475b4..38f72eac 100644 --- a/reference/readwrite/generated/networkx.readwrite.json_graph.cytoscape_graph.html +++ b/reference/readwrite/generated/networkx.readwrite.json_graph.cytoscape_graph.html @@ -644,7 +644,7 @@ Must not have the same value as <code class="xref py py-obj docutils literal not <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.json_graph.node_link_data.html b/reference/readwrite/generated/networkx.readwrite.json_graph.node_link_data.html index 85b1f8c1..e8d8523e 100644 --- a/reference/readwrite/generated/networkx.readwrite.json_graph.node_link_data.html +++ b/reference/readwrite/generated/networkx.readwrite.json_graph.node_link_data.html @@ -670,7 +670,7 @@ be specified as keyword options.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.json_graph.node_link_graph.html b/reference/readwrite/generated/networkx.readwrite.json_graph.node_link_graph.html index a916033d..f7485673 100644 --- a/reference/readwrite/generated/networkx.readwrite.json_graph.node_link_graph.html +++ b/reference/readwrite/generated/networkx.readwrite.json_graph.node_link_graph.html @@ -660,7 +660,7 @@ the keyword names for the attributes must match.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.json_graph.tree_data.html b/reference/readwrite/generated/networkx.readwrite.json_graph.tree_data.html index 424fd11d..ba287ec1 100644 --- a/reference/readwrite/generated/networkx.readwrite.json_graph.tree_data.html +++ b/reference/readwrite/generated/networkx.readwrite.json_graph.tree_data.html @@ -632,7 +632,7 @@ for attributes must be strings if you want to serialize with JSON.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.json_graph.tree_graph.html b/reference/readwrite/generated/networkx.readwrite.json_graph.tree_graph.html index a919e6e5..a3b626e4 100644 --- a/reference/readwrite/generated/networkx.readwrite.json_graph.tree_graph.html +++ b/reference/readwrite/generated/networkx.readwrite.json_graph.tree_graph.html @@ -614,7 +614,7 @@ must have a different value than <code class="xref py py-obj docutils literal no <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.leda.parse_leda.html b/reference/readwrite/generated/networkx.readwrite.leda.parse_leda.html index c7907f6f..4563b987 100644 --- a/reference/readwrite/generated/networkx.readwrite.leda.parse_leda.html +++ b/reference/readwrite/generated/networkx.readwrite.leda.parse_leda.html @@ -604,7 +604,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.leda.read_leda.html b/reference/readwrite/generated/networkx.readwrite.leda.read_leda.html index 0f75ea4e..2e053871 100644 --- a/reference/readwrite/generated/networkx.readwrite.leda.read_leda.html +++ b/reference/readwrite/generated/networkx.readwrite.leda.read_leda.html @@ -605,7 +605,7 @@ uncompressed.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.multiline_adjlist.generate_multiline_adjlist.html b/reference/readwrite/generated/networkx.readwrite.multiline_adjlist.generate_multiline_adjlist.html index d12514f5..b3640fa0 100644 --- a/reference/readwrite/generated/networkx.readwrite.multiline_adjlist.generate_multiline_adjlist.html +++ b/reference/readwrite/generated/networkx.readwrite.multiline_adjlist.generate_multiline_adjlist.html @@ -625,7 +625,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.multiline_adjlist.parse_multiline_adjlist.html b/reference/readwrite/generated/networkx.readwrite.multiline_adjlist.parse_multiline_adjlist.html index 95af609c..24e25586 100644 --- a/reference/readwrite/generated/networkx.readwrite.multiline_adjlist.parse_multiline_adjlist.html +++ b/reference/readwrite/generated/networkx.readwrite.multiline_adjlist.parse_multiline_adjlist.html @@ -619,7 +619,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.multiline_adjlist.read_multiline_adjlist.html b/reference/readwrite/generated/networkx.readwrite.multiline_adjlist.read_multiline_adjlist.html index 8cfdac2f..bc4991ff 100644 --- a/reference/readwrite/generated/networkx.readwrite.multiline_adjlist.read_multiline_adjlist.html +++ b/reference/readwrite/generated/networkx.readwrite.multiline_adjlist.read_multiline_adjlist.html @@ -648,7 +648,7 @@ a directed graph use</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.multiline_adjlist.write_multiline_adjlist.html b/reference/readwrite/generated/networkx.readwrite.multiline_adjlist.write_multiline_adjlist.html index acd34c22..f32dec77 100644 --- a/reference/readwrite/generated/networkx.readwrite.multiline_adjlist.write_multiline_adjlist.html +++ b/reference/readwrite/generated/networkx.readwrite.multiline_adjlist.write_multiline_adjlist.html @@ -619,7 +619,7 @@ file handle is provided, it has to be opened in ‘wb’ mode.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.pajek.generate_pajek.html b/reference/readwrite/generated/networkx.readwrite.pajek.generate_pajek.html index 5720698e..747b16c3 100644 --- a/reference/readwrite/generated/networkx.readwrite.pajek.generate_pajek.html +++ b/reference/readwrite/generated/networkx.readwrite.pajek.generate_pajek.html @@ -593,7 +593,7 @@ for format information.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.pajek.parse_pajek.html b/reference/readwrite/generated/networkx.readwrite.pajek.parse_pajek.html index a7952e7f..79bd625c 100644 --- a/reference/readwrite/generated/networkx.readwrite.pajek.parse_pajek.html +++ b/reference/readwrite/generated/networkx.readwrite.pajek.parse_pajek.html @@ -601,7 +601,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.pajek.read_pajek.html b/reference/readwrite/generated/networkx.readwrite.pajek.read_pajek.html index 08cfe51d..bb824ef1 100644 --- a/reference/readwrite/generated/networkx.readwrite.pajek.read_pajek.html +++ b/reference/readwrite/generated/networkx.readwrite.pajek.read_pajek.html @@ -609,7 +609,7 @@ for format information.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.pajek.write_pajek.html b/reference/readwrite/generated/networkx.readwrite.pajek.write_pajek.html index c22db28f..7d271168 100644 --- a/reference/readwrite/generated/networkx.readwrite.pajek.write_pajek.html +++ b/reference/readwrite/generated/networkx.readwrite.pajek.write_pajek.html @@ -607,7 +607,7 @@ for format information.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.sparse6.from_sparse6_bytes.html b/reference/readwrite/generated/networkx.readwrite.sparse6.from_sparse6_bytes.html index 6b270e1e..1490bed7 100644 --- a/reference/readwrite/generated/networkx.readwrite.sparse6.from_sparse6_bytes.html +++ b/reference/readwrite/generated/networkx.readwrite.sparse6.from_sparse6_bytes.html @@ -621,7 +621,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.sparse6.read_sparse6.html b/reference/readwrite/generated/networkx.readwrite.sparse6.read_sparse6.html index 71304d75..31c3bcd7 100644 --- a/reference/readwrite/generated/networkx.readwrite.sparse6.read_sparse6.html +++ b/reference/readwrite/generated/networkx.readwrite.sparse6.read_sparse6.html @@ -637,7 +637,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.sparse6.to_sparse6_bytes.html b/reference/readwrite/generated/networkx.readwrite.sparse6.to_sparse6_bytes.html index 180c6e4f..cd50ca75 100644 --- a/reference/readwrite/generated/networkx.readwrite.sparse6.to_sparse6_bytes.html +++ b/reference/readwrite/generated/networkx.readwrite.sparse6.to_sparse6_bytes.html @@ -625,7 +625,7 @@ is only defined for graphs of order less than <code class="docutils literal notr <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/generated/networkx.readwrite.sparse6.write_sparse6.html b/reference/readwrite/generated/networkx.readwrite.sparse6.write_sparse6.html index 8a613839..6ea4609d 100644 --- a/reference/readwrite/generated/networkx.readwrite.sparse6.write_sparse6.html +++ b/reference/readwrite/generated/networkx.readwrite.sparse6.write_sparse6.html @@ -635,7 +635,7 @@ given by G.nodes() is used.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/gexf.html b/reference/readwrite/gexf.html index 2434f64d..7d8b60c4 100644 --- a/reference/readwrite/gexf.html +++ b/reference/readwrite/gexf.html @@ -604,7 +604,7 @@ specification and <a class="reference external" href="http://gexf.net/basic.html <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/gml.html b/reference/readwrite/gml.html index 761a6b1d..9e334b4d 100644 --- a/reference/readwrite/gml.html +++ b/reference/readwrite/gml.html @@ -599,7 +599,7 @@ than <a class="reference external" href="https://docs.python.org/3/library/stdty <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/graphml.html b/reference/readwrite/graphml.html index b6b16fa9..0b724eec 100644 --- a/reference/readwrite/graphml.html +++ b/reference/readwrite/graphml.html @@ -624,7 +624,7 @@ for examples.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/index.html b/reference/readwrite/index.html index 6df234c2..649a5408 100644 --- a/reference/readwrite/index.html +++ b/reference/readwrite/index.html @@ -644,7 +644,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/json_graph.html b/reference/readwrite/json_graph.html index 6473f573..bd35547a 100644 --- a/reference/readwrite/json_graph.html +++ b/reference/readwrite/json_graph.html @@ -593,7 +593,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/leda.html b/reference/readwrite/leda.html index 1d55bd58..50589667 100644 --- a/reference/readwrite/leda.html +++ b/reference/readwrite/leda.html @@ -588,7 +588,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/matrix_market.html b/reference/readwrite/matrix_market.html index 29e7d094..89da69c7 100644 --- a/reference/readwrite/matrix_market.html +++ b/reference/readwrite/matrix_market.html @@ -666,7 +666,7 @@ sparse matrices:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/multiline_adjlist.html b/reference/readwrite/multiline_adjlist.html index ab075305..cd0c7f1b 100644 --- a/reference/readwrite/multiline_adjlist.html +++ b/reference/readwrite/multiline_adjlist.html @@ -608,7 +608,7 @@ adjacency list (anything following the # in a line is a comment):</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/pajek.html b/reference/readwrite/pajek.html index 176241b4..cc7b16fc 100644 --- a/reference/readwrite/pajek.html +++ b/reference/readwrite/pajek.html @@ -596,7 +596,7 @@ for format information.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/readwrite/sparsegraph6.html b/reference/readwrite/sparsegraph6.html index 6c7e4cf6..854383e2 100644 --- a/reference/readwrite/sparsegraph6.html +++ b/reference/readwrite/sparsegraph6.html @@ -635,7 +635,7 @@ format.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/relabel.html b/reference/relabel.html index e58b43b7..9092bf0d 100644 --- a/reference/relabel.html +++ b/reference/relabel.html @@ -576,7 +576,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/reference/utils.html b/reference/utils.html index 860548f1..ad85d590 100644 --- a/reference/utils.html +++ b/reference/utils.html @@ -751,7 +751,7 @@ random selections.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/api_0.99.html b/release/api_0.99.html index da4fb2ce..4002d710 100644 --- a/release/api_0.99.html +++ b/release/api_0.99.html @@ -1121,7 +1121,7 @@ does not work well when you are changing the graph.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/api_1.0.html b/release/api_1.0.html index 67251a96..89c3c05c 100644 --- a/release/api_1.0.html +++ b/release/api_1.0.html @@ -1121,7 +1121,7 @@ weight key is</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/api_1.10.html b/release/api_1.10.html index a4602f25..12f39abd 100644 --- a/release/api_1.10.html +++ b/release/api_1.10.html @@ -805,7 +805,7 @@ Support for Python 2.6 is dropped.</p></li> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/api_1.11.html b/release/api_1.11.html index fbb2f853..fabea301 100644 --- a/release/api_1.11.html +++ b/release/api_1.11.html @@ -630,7 +630,7 @@ readthedocs.org by changing requirements.txt</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/api_1.4.html b/release/api_1.4.html index 8b524c42..16295be5 100644 --- a/release/api_1.4.html +++ b/release/api_1.4.html @@ -672,7 +672,7 @@ a NetworkXNoPath exception.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/api_1.5.html b/release/api_1.5.html index 42d466ef..b0256801 100644 --- a/release/api_1.5.html +++ b/release/api_1.5.html @@ -700,7 +700,7 @@ An optional pos keyword was added to allow specification of node positions.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/api_1.6.html b/release/api_1.6.html index 5f76049b..59286c75 100644 --- a/release/api_1.6.html +++ b/release/api_1.6.html @@ -708,7 +708,7 @@ have been replaced with</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/api_1.7.html b/release/api_1.7.html index e167ea4e..86049677 100644 --- a/release/api_1.7.html +++ b/release/api_1.7.html @@ -606,7 +606,7 @@ independent set, max clique, and min-weighted vertex cover.</p></li> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/api_1.8.html b/release/api_1.8.html index c8f0348f..c39d4fef 100644 --- a/release/api_1.8.html +++ b/release/api_1.8.html @@ -619,7 +619,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/api_1.9.html b/release/api_1.9.html index b2211328..d17fca12 100644 --- a/release/api_1.9.html +++ b/release/api_1.9.html @@ -827,7 +827,7 @@ IronPython 2.7, although they remain not officially supported.</p></li> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/index.html b/release/index.html index fd1e0bee..288f2780 100644 --- a/release/index.html +++ b/release/index.html @@ -844,7 +844,7 @@ for you to use <code class="docutils literal notranslate"><span class="pre">~=</ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/migration_guide_from_1.x_to_2.0.html b/release/migration_guide_from_1.x_to_2.0.html index 0abdd561..82ed0f6b 100644 --- a/release/migration_guide_from_1.x_to_2.0.html +++ b/release/migration_guide_from_1.x_to_2.0.html @@ -840,7 +840,7 @@ and edges to a fresh graph. Try something similar to this:</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/migration_guide_from_2.x_to_3.0.html b/release/migration_guide_from_2.x_to_3.0.html index e729ccfa..5f3c7873 100644 --- a/release/migration_guide_from_2.x_to_3.0.html +++ b/release/migration_guide_from_2.x_to_3.0.html @@ -752,7 +752,7 @@ using pyyaml.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/old_release_log.html b/release/old_release_log.html index 9565b0ba..88974199 100644 --- a/release/old_release_log.html +++ b/release/old_release_log.html @@ -2528,7 +2528,7 @@ protect name-spaces</p></li> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/release_2.0.html b/release/release_2.0.html index d5e4e1f8..46c048b7 100644 --- a/release/release_2.0.html +++ b/release/release_2.0.html @@ -1105,7 +1105,7 @@ deprecated in favor of <code class="docutils literal notranslate"><span class="p <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/release_2.1.html b/release/release_2.1.html index 4d436013..5cecd1aa 100644 --- a/release/release_2.1.html +++ b/release/release_2.1.html @@ -839,7 +839,7 @@ Instead use: <code class="docutils literal notranslate"><span class="pre">[G.sub <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/release_2.2.html b/release/release_2.2.html index f5659261..f8b6590e 100644 --- a/release/release_2.2.html +++ b/release/release_2.2.html @@ -745,7 +745,7 @@ are derecated in favor of <code class="xref py py-obj docutils literal notransla <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/release_2.3.html b/release/release_2.3.html index 0ec70cf9..ead5dc04 100644 --- a/release/release_2.3.html +++ b/release/release_2.3.html @@ -699,7 +699,7 @@ of the same type as G.</p></li> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/release_2.4.html b/release/release_2.4.html index 4651b114..7597d464 100644 --- a/release/release_2.4.html +++ b/release/release_2.4.html @@ -1007,7 +1007,7 @@ integer values to lists of integers</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/release_2.5.html b/release/release_2.5.html index 774f3baf..44e11bd8 100644 --- a/release/release_2.5.html +++ b/release/release_2.5.html @@ -1086,7 +1086,7 @@ Rename <code class="xref py py-obj docutils literal notranslate"><span class="pr <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/release_2.6.html b/release/release_2.6.html index a7c68fb5..ae27ae0a 100644 --- a/release/release_2.6.html +++ b/release/release_2.6.html @@ -1331,7 +1331,7 @@ Deprecate <code class="docutils literal notranslate"><span class="pre">k_nearest <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/release_2.7.1.html b/release/release_2.7.1.html index 43895056..129307e6 100644 --- a/release/release_2.7.1.html +++ b/release/release_2.7.1.html @@ -610,7 +610,7 @@ <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/release_2.7.html b/release/release_2.7.html index 2a14f79d..395b7acd 100644 --- a/release/release_2.7.html +++ b/release/release_2.7.html @@ -1027,7 +1027,7 @@ Deprecate redundant <code class="docutils literal notranslate"><span class="pre" <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/release_2.8.1.html b/release/release_2.8.1.html index 01d5e71b..74caeeeb 100644 --- a/release/release_2.8.1.html +++ b/release/release_2.8.1.html @@ -716,7 +716,7 @@ algorithms, for example it yields incorrect results for <code class="xref py py- <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/release_2.8.2.html b/release/release_2.8.2.html index f17a026f..5ad330b7 100644 --- a/release/release_2.8.2.html +++ b/release/release_2.8.2.html @@ -619,7 +619,7 @@ Please send comments and questions to the <a class="reference external" href="ht <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/release_2.8.3.html b/release/release_2.8.3.html index 88be6062..c49cd961 100644 --- a/release/release_2.8.3.html +++ b/release/release_2.8.3.html @@ -639,7 +639,7 @@ Please send comments and questions to the <a class="reference external" href="ht <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/release/release_2.8.4.html b/release/release_2.8.4.html index 92d790e1..9dfe34c0 100644 --- a/release/release_2.8.4.html +++ b/release/release_2.8.4.html @@ -640,7 +640,7 @@ Please send comments and questions to the <a class="reference external" href="ht <p class="copyright"> - 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751, 762, 767, 770, 775, 786, 791, 796, 850, 853, 854, 855, 856, 857, 862, 865, 867, 870, 871, 873, 874, 878, 879, 882, 887, 888, 892, 895, 898, 899, 900, 901, 902, 907, 910, 912, 914, 916, 917, 921, 925, 928, 931, 934, 935, 936, 937, 938, 943, 946, 947, 948, 951, 952, 955, 956, 960, 963, 968, 973, 976, 979, 980, 981, 982, 983, 988, 991, 992, 993, 995, 998, 999, 1003, 1007, 1010, 1036, 1037, 1038, 1039, 1040, 1042, 1045, 1047, 1059, 1060, 1061, 1063, 1066, 1068, 1082, 1085, 1088, 1102, 1103, 1105, 1129, 1133, 1135, 1137, 1148, 1151, 1154, 1164, 1165, 1166, 1167, 1174, 1175, 1177, 1193, 1196, 1197, 1198, 1206, 1207, 1217, 1218, 1219, 1222, 1235, 1246, 1248, 1250, 1258, 1263, 1264, 1269, 1272, 1275, 1276, 1278, 1279, 1281, 1282, 1283, 1284, 1295, 1296, 1297, 1299, 1301, 1302, 1303, 1320, 1321, 1323, 1324, 1326, 1328, 1329, 1330, 1333, 1334, 1347, 1349, 1352, 1354, 1356, 1357, 1362, 1363, 1371, 1372, 1378, 1380, 1382, 1385, 1387, 1388, 1392, 1393, 1394, 1395, 1396, 1399, 1402, 1404, 1405, 1406, 1408, 1409, 1412, 1425, 1426], "more": [8, 43, 53, 67, 86, 92, 93, 94, 97, 99, 100, 101, 102, 103, 107, 109, 110, 111, 114, 115, 121, 127, 128, 143, 165, 172, 198, 199, 202, 204, 215, 216, 218, 219, 220, 221, 230, 231, 235, 256, 267, 277, 278, 281, 289, 299, 310, 314, 324, 325, 335, 338, 361, 378, 383, 385, 387, 389, 390, 392, 399, 405, 406, 407, 422, 427, 428, 432, 433, 437, 460, 464, 480, 520, 521, 559, 560, 581, 582, 583, 590, 593, 614, 619, 626, 631, 635, 653, 656, 660, 661, 662, 676, 679, 683, 691, 698, 699, 703, 711, 717, 718, 735, 737, 748, 760, 782, 786, 796, 862, 868, 886, 887, 890, 891, 907, 913, 924, 925, 926, 927, 943, 949, 967, 968, 971, 972, 988, 994, 1006, 1007, 1008, 1009, 1037, 1039, 1040, 1042, 1043, 1071, 1094, 1100, 1116, 1119, 1120, 1123, 1130, 1131, 1132, 1133, 1135, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1185, 1192, 1193, 1206, 1214, 1217, 1218, 1219, 1272, 1287, 1288, 1295, 1296, 1297, 1323, 1326, 1328, 1337, 1345, 1348, 1349, 1350, 1390, 1394, 1395, 1397, 1398, 1399, 1401, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426], "express": [8, 92, 110, 184, 315, 329, 330, 383, 384, 618, 619, 873, 916, 955, 998, 1199, 1287, 1326], "than": [8, 11, 34, 43, 55, 97, 99, 101, 102, 103, 115, 128, 142, 143, 144, 161, 199, 214, 215, 216, 218, 219, 221, 227, 231, 235, 241, 256, 277, 278, 281, 288, 289, 297, 298, 299, 304, 306, 307, 310, 311, 315, 316, 321, 324, 325, 326, 328, 329, 330, 341, 352, 358, 361, 374, 380, 381, 383, 384, 385, 387, 389, 390, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 425, 426, 429, 435, 464, 468, 469, 500, 527, 537, 559, 560, 581, 582, 583, 590, 625, 626, 635, 636, 652, 653, 656, 658, 659, 673, 676, 678, 679, 681, 683, 686, 690, 692, 693, 694, 698, 699, 711, 731, 735, 737, 748, 752, 761, 786, 887, 925, 947, 968, 992, 1007, 1038, 1042, 1043, 1060, 1102, 1135, 1146, 1154, 1162, 1165, 1167, 1172, 1174, 1185, 1187, 1194, 1198, 1226, 1230, 1231, 1236, 1237, 1238, 1239, 1275, 1276, 1296, 1297, 1326, 1328, 1345, 1348, 1349, 1350, 1353, 1354, 1358, 1365, 1366, 1379, 1382, 1395, 1402, 1404, 1405, 1408, 1413, 1423, 1425], "worst": [8, 210, 211, 212, 221, 228, 235, 264, 293, 294, 338, 345, 346, 347, 440, 513, 515, 516, 517, 518], "reus": [8, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 1131, 1132, 1138, 1139, 1140, 1141, 1142, 1328, 1402], "subcircuit": 8, "multipl": [8, 11, 25, 40, 45, 77, 93, 94, 99, 103, 107, 109, 143, 157, 158, 166, 175, 188, 195, 207, 287, 311, 357, 385, 386, 423, 443, 447, 458, 460, 464, 485, 486, 487, 594, 595, 597, 615, 616, 641, 643, 678, 690, 691, 697, 705, 738, 762, 786, 796, 856, 857, 863, 869, 877, 884, 892, 901, 902, 908, 923, 928, 937, 938, 944, 946, 950, 959, 960, 962, 963, 965, 973, 982, 983, 989, 991, 1002, 1003, 1005, 1010, 1037, 1039, 1040, 1045, 1046, 1102, 1103, 1105, 1127, 1135, 1137, 1216, 1217, 1219, 1285, 1291, 1296, 1298, 1326, 1352, 1378, 1393, 1405, 1406, 1412, 1413, 1417, 1425, 1426], "wherea": [8, 103, 682, 762, 786, 791, 1165, 1417], "cannot": [8, 101, 103, 127, 132, 199, 232, 300, 362, 394, 476, 581, 582, 583, 584, 632, 722, 887, 925, 934, 968, 979, 1007, 1043, 1165, 1208, 1209, 1296, 1298, 1302, 1303, 1326, 1345, 1347, 1348, 1349, 1350], "subformula": 8, "onc": [8, 38, 54, 55, 88, 93, 94, 99, 100, 112, 127, 199, 227, 230, 231, 232, 246, 247, 360, 374, 380, 388, 422, 423, 428, 488, 491, 492, 581, 582, 583, 652, 678, 679, 717, 718, 887, 925, 968, 1007, 1046, 1066, 1087, 1217, 1311, 1326, 1403, 1407], "thu": [8, 88, 101, 103, 115, 215, 216, 220, 256, 258, 331, 418, 419, 427, 428, 462, 477, 500, 512, 583, 679, 698, 699, 760, 762, 796, 1037, 1039, 1040, 1043, 1087, 1112, 1148, 1215, 1217, 1234, 1278, 1279, 1296, 1328, 1402, 1405, 1407], "wai": [8, 27, 52, 53, 55, 75, 86, 88, 93, 97, 99, 100, 101, 102, 103, 104, 107, 110, 115, 132, 152, 157, 158, 165, 184, 226, 281, 297, 298, 315, 330, 337, 356, 588, 598, 615, 618, 678, 691, 730, 760, 791, 796, 854, 856, 857, 862, 873, 899, 901, 902, 907, 915, 916, 935, 937, 938, 943, 955, 980, 982, 983, 988, 996, 998, 1037, 1039, 1040, 1041, 1097, 1165, 1213, 1215, 1217, 1239, 1262, 1269, 1272, 1326, 1328, 1330, 1393, 1394, 1404, 1406, 1411, 1426], "infeas": [8, 422], "circuit_to_formula": 8, "dag_to_branch": [8, 758, 1408], "transfer": [8, 202, 204, 230, 231, 469, 890, 891, 926, 927, 971, 972, 1008, 1009, 1420], "oper": [8, 30, 52, 95, 101, 112, 115, 168, 184, 189, 227, 374, 423, 460, 546, 547, 548, 552, 553, 554, 577, 595, 598, 601, 671, 672, 673, 674, 679, 680, 758, 786, 865, 873, 878, 910, 916, 946, 955, 960, 991, 998, 1036, 1068, 1088, 1103, 1164, 1218, 1219, 1295, 1302, 1319, 1323, 1325, 1326, 1393, 1394, 1400, 1404, 1405, 1406, 1407, 1408, 1411, 1412, 1413, 1414, 1417], "variabl": [8, 94, 132, 373, 530, 540, 618, 619, 732, 796, 1037, 1038, 1039, 1040, 1154, 1165, 1326, 1408, 1412, 1413, 1414, 1420], "formula_to_str": 8, "_to_str": 8, "root": [8, 67, 84, 293, 294, 338, 387, 389, 390, 394, 449, 460, 559, 577, 609, 671, 673, 678, 704, 728, 730, 739, 760, 791, 1119, 1120, 1125, 1126, 1145, 1147, 1235, 1271, 1272, 1323, 1365, 1366, 1393, 1406, 1407, 1408, 1412, 1413, 1423, 1425], "children": [8, 460, 577, 1145, 1155, 1272, 1365, 1366], "otherwis": [8, 92, 110, 146, 149, 171, 178, 184, 185, 198, 217, 230, 249, 250, 284, 297, 298, 303, 306, 307, 311, 315, 316, 322, 323, 324, 325, 326, 329, 330, 343, 353, 358, 393, 394, 395, 396, 397, 398, 410, 411, 412, 418, 419, 422, 425, 426, 462, 463, 464, 470, 479, 488, 490, 494, 495, 496, 498, 499, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 521, 555, 562, 563, 568, 572, 574, 584, 586, 588, 597, 601, 616, 618, 619, 633, 663, 673, 687, 688, 689, 696, 698, 699, 734, 735, 736, 737, 751, 848, 867, 873, 874, 886, 893, 912, 916, 917, 924, 929, 934, 948, 955, 956, 967, 974, 979, 993, 998, 999, 1006, 1068, 1091, 1135, 1137, 1165, 1185, 1197, 1217, 1270, 1282, 1283, 1284, 1307, 1309, 1312, 1342, 1356, 1357, 1376, 1409, 1413, 1426], "child": [8, 1147, 1272], "must": [8, 11, 93, 94, 95, 99, 100, 103, 110, 151, 152, 158, 161, 171, 204, 206, 207, 214, 215, 216, 219, 230, 231, 232, 252, 253, 257, 258, 259, 260, 261, 262, 264, 267, 268, 269, 271, 273, 276, 281, 285, 297, 298, 306, 307, 315, 316, 317, 318, 319, 324, 325, 327, 329, 330, 342, 361, 362, 363, 378, 382, 385, 391, 410, 411, 412, 413, 425, 429, 440, 471, 472, 473, 474, 475, 545, 546, 547, 548, 549, 550, 551, 553, 555, 556, 557, 558, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 577, 578, 579, 580, 584, 585, 586, 587, 588, 589, 593, 597, 599, 601, 602, 603, 604, 615, 626, 627, 632, 633, 635, 636, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 671, 672, 673, 674, 680, 690, 692, 698, 699, 707, 721, 734, 735, 736, 737, 789, 796, 853, 854, 857, 867, 891, 892, 898, 899, 902, 912, 928, 934, 938, 972, 973, 979, 983, 1010, 1037, 1038, 1039, 1040, 1063, 1071, 1085, 1102, 1133, 1137, 1146, 1162, 1165, 1173, 1176, 1186, 1188, 1190, 1193, 1197, 1199, 1209, 1213, 1217, 1219, 1235, 1239, 1240, 1270, 1275, 1276, 1277, 1278, 1279, 1295, 1296, 1298, 1307, 1309, 1310, 1311, 1312, 1315, 1333, 1337, 1338, 1339, 1340, 1359, 1361, 1362, 1363, 1364, 1365, 1366, 1376, 1393, 1394, 1395, 1407, 1426], "NOT": [8, 110, 199, 549, 550, 551, 748, 887, 925, 968, 1007], "util": [8, 14, 36, 44, 45, 93, 97, 102, 103, 229, 230, 231, 316, 374, 423, 425, 426, 429, 460, 496, 678, 679, 758, 1044, 1242, 1299, 1301, 1303, 1310, 1319, 1320, 1321, 1325, 1402, 1406, 1407, 1411, 1413, 1416, 1419], "arbitrary_el": [8, 1392, 1413], "nb": [8, 1331, 1334], "left": [8, 71, 115, 183, 311, 312, 322, 324, 325, 385, 559, 560, 584, 616, 688, 689, 739, 1106, 1134, 1136, 1146, 1179, 1206, 1280, 1355, 1358, 1404], "right": [8, 71, 110, 111, 115, 152, 206, 322, 385, 427, 428, 500, 559, 560, 584, 585, 587, 588, 615, 616, 688, 689, 739, 854, 935, 980, 1134, 1136, 1146, 1155, 1157, 1179, 1206, 1213, 1215, 1270, 1280], "littl": [8, 94, 298, 307], "mislead": 8, "That": [8, 97, 132, 165, 212, 221, 227, 295, 385, 436, 465, 525, 535, 555, 588, 657, 671, 672, 673, 674, 691, 704, 717, 791, 862, 907, 943, 988, 1046, 1162, 1210, 1296, 1388, 1404, 1409], "okai": 8, "becaus": [8, 11, 54, 69, 94, 99, 101, 102, 103, 112, 132, 161, 215, 216, 220, 255, 311, 378, 387, 389, 390, 394, 411, 412, 427, 494, 498, 499, 500, 510, 569, 585, 587, 615, 616, 632, 652, 934, 979, 1038, 1236, 1273, 1296, 1303, 1326, 1345, 1350, 1404, 1407, 1416], "AND": [8, 110, 598, 748, 762], "OR": [8, 110, 157, 175, 188, 856, 869, 877, 901, 937, 947, 950, 959, 982, 992], "symmetr": [8, 145, 148, 237, 545, 586, 593, 761, 1173, 1192, 1235, 1246, 1250, 1251, 1256, 1258, 1269, 1320, 1321, 1387], "It": [8, 52, 56, 58, 92, 93, 94, 97, 99, 101, 102, 104, 107, 110, 112, 115, 132, 172, 184, 207, 214, 215, 216, 229, 230, 231, 249, 260, 261, 262, 264, 278, 310, 316, 324, 325, 326, 343, 346, 347, 351, 353, 412, 414, 415, 416, 417, 418, 419, 429, 438, 440, 452, 457, 464, 480, 496, 500, 508, 530, 540, 545, 559, 560, 565, 566, 567, 582, 588, 594, 595, 598, 600, 601, 615, 619, 628, 629, 630, 652, 658, 659, 663, 671, 674, 692, 717, 718, 719, 760, 761, 762, 791, 796, 868, 873, 892, 913, 916, 928, 949, 955, 973, 994, 998, 1010, 1012, 1013, 1018, 1037, 1038, 1039, 1040, 1054, 1117, 1170, 1174, 1200, 1201, 1206, 1207, 1210, 1217, 1223, 1227, 1234, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1253, 1254, 1258, 1261, 1263, 1264, 1269, 1275, 1276, 1277, 1280, 1296, 1297, 1323, 1324, 1326, 1328, 1343, 1382, 1383, 1393, 1395, 1398, 1402, 1404, 1407, 1408, 1409, 1411, 1412, 1413, 1426], "just": [8, 99, 102, 103, 104, 184, 199, 338, 374, 439, 464, 559, 560, 577, 660, 661, 662, 692, 791, 873, 887, 916, 925, 946, 955, 960, 968, 991, 998, 1007, 1120, 1126, 1229, 1278, 1279, 1296, 1328, 1393, 1404, 1406], "operand": 8, "predict": [8, 567, 568, 569, 570, 571, 572, 573, 574, 591, 592, 758, 1325, 1402, 1406, 1412], "henc": [8, 168, 189, 521, 865, 878, 910, 946, 960, 991, 1059, 1202, 1383], "doe": [8, 77, 93, 94, 99, 101, 102, 103, 104, 114, 115, 132, 147, 153, 154, 165, 168, 189, 207, 208, 227, 228, 229, 230, 231, 232, 293, 308, 339, 340, 342, 343, 352, 357, 373, 382, 385, 410, 414, 426, 450, 469, 494, 495, 496, 497, 498, 499, 500, 502, 503, 506, 507, 509, 510, 511, 512, 534, 544, 549, 550, 551, 564, 566, 583, 584, 586, 589, 601, 612, 626, 627, 678, 691, 693, 694, 698, 699, 717, 718, 721, 722, 723, 724, 725, 726, 762, 862, 865, 878, 892, 907, 910, 928, 943, 946, 960, 973, 988, 991, 1010, 1038, 1043, 1066, 1070, 1072, 1081, 1102, 1103, 1105, 1106, 1107, 1109, 1114, 1173, 1175, 1177, 1192, 1207, 1222, 1223, 1227, 1229, 1234, 1241, 1296, 1300, 1303, 1326, 1333, 1334, 1341, 1342, 1344, 1351, 1353, 1354, 1355, 1356, 1357, 1358, 1371, 1379, 1380, 1381, 1383, 1393, 1404, 1405, 1406, 1410, 1417, 1426], "necessarili": [8, 99, 341, 451, 483, 559, 560, 641, 643, 1038, 1219], "behav": [8, 88, 103, 159, 190, 200, 220, 351, 858, 879, 888, 903, 939, 969, 984, 1229, 1296, 1395, 1404], "everi": [8, 11, 57, 88, 93, 109, 112, 120, 144, 157, 161, 177, 211, 212, 220, 221, 229, 230, 231, 235, 243, 264, 287, 295, 300, 324, 325, 343, 352, 380, 397, 437, 439, 440, 450, 462, 471, 472, 473, 474, 475, 477, 483, 484, 491, 512, 516, 565, 606, 614, 615, 619, 632, 633, 635, 636, 663, 685, 687, 688, 717, 718, 791, 856, 901, 937, 982, 1052, 1053, 1054, 1070, 1071, 1072, 1085, 1086, 1102, 1103, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1114, 1115, 1116, 1117, 1148, 1162, 1195, 1216, 1217, 1257, 1264, 1278, 1279, 1296, 1407], "left_subformula": 8, "right_subformula": 8, "in_degre": [8, 166, 188, 491, 678, 863, 877, 944, 959, 1177, 1207, 1208, 1404, 1406, 1407, 1426], "ha": [8, 11, 16, 44, 67, 88, 91, 93, 94, 95, 97, 99, 100, 101, 102, 103, 105, 107, 110, 112, 116, 120, 127, 152, 161, 165, 166, 173, 174, 175, 184, 188, 198, 207, 212, 214, 215, 219, 220, 226, 227, 229, 230, 231, 232, 235, 238, 239, 240, 241, 242, 243, 244, 247, 249, 252, 269, 271, 272, 273, 274, 275, 276, 282, 289, 291, 293, 294, 295, 300, 305, 310, 324, 331, 343, 352, 355, 356, 363, 364, 365, 373, 378, 380, 381, 383, 384, 385, 386, 391, 393, 394, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 424, 427, 428, 429, 439, 450, 458, 460, 466, 467, 468, 471, 472, 473, 474, 475, 476, 477, 480, 491, 492, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 522, 564, 566, 577, 578, 581, 590, 593, 605, 607, 610, 611, 622, 623, 624, 628, 629, 630, 632, 633, 634, 635, 636, 638, 646, 647, 649, 652, 657, 658, 682, 688, 690, 692, 697, 711, 717, 718, 729, 730, 731, 739, 749, 786, 791, 854, 862, 863, 869, 873, 877, 886, 892, 899, 907, 908, 916, 924, 928, 935, 943, 944, 948, 950, 955, 959, 967, 973, 980, 988, 989, 993, 998, 1006, 1010, 1040, 1043, 1045, 1066, 1068, 1070, 1072, 1075, 1080, 1084, 1098, 1099, 1101, 1102, 1103, 1105, 1122, 1130, 1145, 1154, 1160, 1162, 1165, 1176, 1180, 1185, 1193, 1195, 1196, 1197, 1198, 1199, 1207, 1210, 1211, 1215, 1217, 1222, 1234, 1239, 1243, 1244, 1248, 1249, 1254, 1259, 1261, 1264, 1267, 1269, 1270, 1272, 1275, 1276, 1277, 1278, 1279, 1281, 1282, 1283, 1284, 1285, 1286, 1289, 1291, 1293, 1296, 1300, 1326, 1328, 1330, 1333, 1334, 1353, 1354, 1371, 1372, 1379, 1382, 1393, 1394, 1395, 1398, 1403, 1404, 1405, 1406, 1407, 1409, 1413, 1414, 1416, 1423, 1425], "output": [8, 13, 16, 89, 93, 101, 102, 103, 109, 197, 287, 288, 345, 374, 380, 494, 498, 499, 509, 510, 575, 588, 677, 678, 691, 722, 1045, 1193, 1197, 1199, 1269, 1296, 1326, 1334, 1341, 1344, 1355, 1358, 1399, 1402, 1404, 1406, 1411, 1413, 1414, 1426], "two": [8, 11, 16, 27, 34, 38, 43, 54, 55, 57, 58, 65, 67, 71, 88, 93, 95, 99, 100, 102, 109, 112, 114, 115, 120, 132, 151, 171, 175, 184, 185, 188, 202, 207, 211, 212, 213, 214, 215, 216, 217, 220, 221, 226, 227, 230, 231, 232, 245, 249, 251, 252, 253, 257, 258, 260, 261, 262, 265, 269, 270, 271, 272, 273, 274, 275, 276, 282, 285, 286, 287, 289, 305, 311, 315, 316, 322, 326, 329, 330, 337, 341, 343, 345, 351, 352, 358, 359, 377, 380, 381, 383, 391, 411, 412, 419, 423, 428, 429, 430, 431, 442, 443, 444, 445, 447, 452, 453, 454, 457, 462, 471, 472, 473, 474, 475, 476, 480, 491, 494, 498, 499, 500, 502, 503, 506, 508, 509, 510, 511, 521, 545, 549, 550, 551, 555, 559, 560, 561, 562, 563, 564, 565, 566, 568, 569, 572, 574, 578, 584, 585, 586, 587, 588, 593, 598, 605, 607, 608, 610, 611, 615, 619, 626, 627, 629, 632, 633, 635, 636, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 671, 672, 673, 674, 675, 676, 680, 692, 694, 731, 732, 738, 739, 760, 761, 762, 780, 786, 791, 796, 853, 867, 869, 873, 874, 877, 890, 892, 898, 912, 916, 917, 926, 928, 934, 946, 948, 950, 955, 956, 959, 960, 971, 973, 979, 991, 993, 998, 999, 1008, 1010, 1019, 1020, 1021, 1022, 1036, 1037, 1039, 1040, 1056, 1084, 1088, 1098, 1100, 1101, 1106, 1107, 1108, 1109, 1114, 1116, 1134, 1146, 1147, 1149, 1151, 1152, 1156, 1174, 1185, 1186, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1204, 1207, 1210, 1211, 1215, 1217, 1218, 1243, 1244, 1253, 1271, 1272, 1275, 1276, 1294, 1295, 1296, 1323, 1324, 1326, 1328, 1359, 1360, 1363, 1393, 1394, 1395, 1397, 1402, 1404, 1405, 1406, 1407, 1410, 1411, 1413, 1425], "layer": [8, 36, 55, 61, 67, 103, 438, 705, 1038, 1109, 1420], "third": [8, 102, 114, 249, 422, 467, 585, 587, 734, 736, 1217, 1226, 1262, 1263, 1326, 1407], "appear": [8, 83, 93, 95, 99, 100, 102, 179, 204, 230, 231, 238, 243, 246, 247, 277, 363, 364, 365, 378, 451, 452, 453, 455, 466, 470, 584, 585, 587, 588, 675, 679, 707, 730, 734, 736, 891, 972, 1036, 1088, 1102, 1136, 1150, 1152, 1154, 1157, 1159, 1187, 1188, 1277, 1282, 1323, 1324, 1345, 1348, 1349, 1350, 1382, 1407, 1413, 1414], "both": [8, 52, 55, 92, 93, 94, 100, 101, 102, 103, 115, 161, 164, 204, 214, 215, 216, 217, 240, 257, 258, 259, 264, 282, 286, 287, 289, 337, 358, 379, 383, 415, 417, 418, 419, 423, 427, 440, 470, 502, 506, 545, 575, 581, 598, 600, 601, 602, 603, 604, 605, 606, 607, 610, 611, 615, 621, 635, 636, 653, 654, 655, 676, 711, 720, 760, 761, 762, 782, 891, 972, 1020, 1036, 1066, 1075, 1080, 1084, 1088, 1097, 1120, 1126, 1144, 1165, 1189, 1192, 1199, 1207, 1210, 1211, 1213, 1215, 1282, 1296, 1326, 1328, 1358, 1363, 1364, 1387, 1393, 1395, 1402, 1413, 1416, 1417, 1425, 1426], "negat": 8, "sole": [8, 786, 1278, 1279, 1326], "fourth": [8, 230, 231, 1326, 1404], "digraph": [8, 10, 11, 16, 21, 25, 41, 45, 56, 61, 67, 69, 70, 82, 88, 101, 102, 115, 132, 151, 152, 156, 157, 158, 160, 162, 163, 165, 166, 168, 170, 171, 172, 175, 176, 185, 186, 187, 188, 189, 192, 193, 194, 195, 196, 198, 199, 202, 204, 207, 208, 216, 227, 229, 230, 231, 240, 246, 247, 299, 308, 314, 318, 319, 321, 327, 328, 334, 335, 336, 337, 339, 340, 342, 343, 388, 391, 393, 396, 397, 398, 399, 401, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 430, 431, 437, 450, 452, 453, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 481, 482, 492, 494, 495, 496, 497, 498, 499, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 513, 514, 518, 519, 523, 555, 566, 575, 576, 577, 588, 590, 613, 615, 623, 630, 636, 643, 644, 652, 656, 657, 658, 659, 663, 678, 688, 690, 693, 696, 697, 698, 699, 700, 701, 702, 706, 707, 708, 709, 711, 716, 717, 718, 719, 721, 722, 723, 724, 725, 726, 740, 741, 744, 745, 746, 747, 748, 749, 750, 752, 760, 789, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 904, 905, 906, 907, 908, 911, 912, 913, 915, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 935, 936, 937, 938, 940, 941, 942, 943, 949, 957, 958, 963, 964, 965, 966, 967, 968, 972, 973, 974, 975, 977, 978, 980, 981, 982, 983, 985, 986, 987, 988, 989, 994, 996, 1000, 1001, 1003, 1004, 1005, 1006, 1007, 1010, 1035, 1037, 1038, 1039, 1040, 1041, 1052, 1062, 1066, 1070, 1072, 1075, 1080, 1083, 1084, 1098, 1099, 1101, 1118, 1135, 1150, 1154, 1168, 1169, 1170, 1173, 1177, 1178, 1180, 1182, 1183, 1184, 1185, 1189, 1217, 1270, 1272, 1273, 1274, 1283, 1284, 1287, 1290, 1292, 1298, 1323, 1326, 1333, 1337, 1342, 1356, 1357, 1362, 1365, 1366, 1371, 1393, 1399, 1401, 1402, 1404, 1405, 1406, 1407, 1408, 1409, 1411, 1412, 1413, 1414, 1416, 1417, 1424, 1425, 1426], "add_nod": [8, 11, 26, 34, 69, 74, 89, 102, 157, 184, 246, 339, 340, 398, 422, 491, 492, 496, 504, 505, 508, 522, 523, 605, 607, 610, 611, 691, 796, 856, 873, 901, 916, 937, 955, 982, 998, 1037, 1039, 1040, 1086, 1275, 1326, 1345, 1407, 1408, 1417, 1426], "get_node_attribut": [8, 39, 44, 71, 1213, 1404], "600": [8, 10, 12], "font_siz": [8, 16, 21, 25, 32, 35, 38, 45, 46, 1133, 1134, 1136], "22": [8, 35, 64, 66, 383, 384, 1271, 1323, 1403, 1408, 1412, 1422], "multipartite_layout": [8, 36, 61, 67, 1412, 1414, 1420], "subset_kei": [8, 36, 61, 67, 1109], "equal": [8, 36, 81, 144, 214, 215, 216, 230, 231, 238, 269, 271, 273, 276, 288, 297, 298, 300, 303, 306, 307, 310, 311, 312, 315, 316, 320, 323, 324, 325, 329, 330, 331, 373, 410, 411, 412, 413, 418, 419, 428, 471, 474, 476, 491, 494, 495, 496, 498, 499, 502, 503, 504, 505, 506, 507, 508, 509, 510, 525, 535, 545, 552, 553, 554, 555, 568, 572, 605, 623, 657, 671, 672, 673, 674, 687, 688, 689, 690, 721, 722, 740, 741, 753, 761, 791, 1112, 1116, 1162, 1165, 1198, 1204, 1230, 1239, 1271, 1280, 1291, 1307, 1309, 1312, 1398, 1399], "105": [8, 17, 517, 518, 1166, 1167], "plot_circuit": [8, 17], "southern": [9, 1265], "women": [9, 1265, 1398, 1406], "unipartit": [9, 115, 258, 259, 358], "properti": [9, 11, 18, 22, 33, 63, 86, 101, 102, 103, 112, 134, 159, 161, 166, 168, 175, 176, 179, 184, 188, 189, 190, 200, 284, 285, 286, 287, 288, 363, 364, 365, 388, 476, 500, 545, 569, 619, 685, 858, 863, 865, 869, 870, 873, 877, 878, 879, 888, 903, 908, 910, 916, 939, 944, 946, 950, 951, 955, 959, 960, 969, 984, 989, 991, 998, 1085, 1086, 1122, 1134, 1136, 1193, 1202, 1217, 1219, 1269, 1283, 1284, 1326, 1328, 1383, 1398, 1405, 1406, 1407, 1408, 1413, 1417, 1426], "These": [9, 52, 58, 73, 79, 86, 93, 94, 105, 112, 336, 385, 494, 512, 559, 671, 673, 732, 748, 779, 786, 1038, 1045, 1047, 1323, 1326, 1385, 1387, 1392, 1394, 1395, 1397, 1399, 1404, 1405, 1411, 1426], "were": [9, 65, 88, 99, 101, 104, 215, 216, 220, 289, 305, 410, 437, 460, 588, 962, 1002, 1199, 1393, 1395, 1399, 1402, 1405, 1406, 1407, 1413, 1416], "et": [9, 210, 226, 227, 315, 316, 322, 330, 334, 337, 345, 352, 358, 373, 380, 381, 423, 425, 426, 451, 569, 591, 592, 681, 682, 684, 693, 1202], "al": [9, 210, 226, 227, 315, 316, 322, 330, 334, 337, 345, 352, 358, 373, 380, 381, 423, 425, 426, 451, 569, 591, 592, 681, 682, 684, 693, 1202, 1407, 1413], "1930": [9, 1396], "thei": [9, 54, 58, 65, 71, 92, 93, 94, 97, 99, 100, 101, 102, 103, 104, 105, 107, 112, 132, 151, 165, 207, 213, 220, 249, 285, 287, 288, 296, 297, 298, 301, 302, 306, 307, 308, 309, 351, 362, 374, 391, 396, 427, 451, 452, 453, 454, 464, 465, 471, 472, 473, 474, 475, 496, 504, 505, 508, 512, 546, 547, 548, 559, 560, 576, 583, 586, 588, 600, 604, 675, 676, 704, 717, 750, 760, 786, 853, 862, 892, 898, 907, 928, 934, 943, 962, 973, 979, 988, 1002, 1010, 1036, 1038, 1066, 1085, 1088, 1109, 1120, 1126, 1133, 1135, 1137, 1151, 1159, 1165, 1193, 1197, 1198, 1217, 1271, 1272, 1323, 1328, 1353, 1354, 1356, 1357, 1359, 1363, 1394, 1396, 1402, 1404, 1406, 1409, 1414, 1426], "repres": [9, 11, 26, 43, 52, 54, 57, 67, 92, 99, 107, 115, 230, 231, 265, 281, 283, 286, 287, 288, 291, 292, 338, 350, 361, 362, 363, 377, 378, 380, 381, 382, 385, 386, 391, 448, 452, 453, 455, 457, 460, 465, 466, 494, 495, 498, 499, 500, 502, 503, 506, 507, 509, 510, 521, 565, 577, 578, 579, 580, 586, 588, 609, 615, 618, 619, 656, 660, 664, 667, 676, 679, 691, 692, 695, 697, 698, 699, 700, 702, 728, 730, 731, 734, 736, 739, 752, 786, 791, 796, 1019, 1020, 1021, 1022, 1037, 1038, 1039, 1040, 1045, 1081, 1102, 1140, 1151, 1185, 1193, 1194, 1196, 1197, 1198, 1199, 1209, 1217, 1240, 1243, 1246, 1250, 1258, 1267, 1269, 1272, 1273, 1278, 1279, 1323, 1324, 1326, 1329, 1330, 1346, 1347, 1388, 1393, 1406], "observ": [9, 13, 132, 223, 1414, 1426], "attend": 9, "14": [9, 11, 16, 19, 25, 38, 44, 64, 66, 71, 229, 230, 231, 383, 384, 405, 406, 501, 619, 690, 1150, 1242, 1250, 1262, 1406, 1408, 1426], "event": [9, 25, 99, 100, 110, 1165, 1229, 1300], "18": [9, 44, 64, 66, 93, 324, 325, 345, 383, 384, 618, 1169, 1249, 1255, 1258, 1260, 1263, 1269, 1393, 1406, 1416, 1417, 1421, 1426], "bipartit": [9, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 350, 351, 358, 377, 439, 440, 443, 581, 588, 758, 1043, 1106, 1151, 1203, 1204, 1205, 1265, 1325, 1395, 1398, 1399, 1400, 1401, 1406, 1407, 1411, 1413, 1417, 1421, 1425], "biadjac": [9, 282, 283, 1400, 1406], "7": [9, 12, 14, 19, 25, 35, 44, 46, 63, 64, 65, 66, 68, 89, 99, 101, 102, 115, 125, 151, 158, 170, 171, 192, 207, 232, 268, 297, 299, 314, 322, 327, 332, 333, 339, 340, 342, 362, 374, 380, 391, 403, 410, 413, 414, 415, 423, 424, 425, 426, 441, 445, 446, 483, 496, 501, 508, 511, 512, 555, 581, 586, 618, 619, 630, 652, 658, 663, 671, 674, 680, 695, 703, 706, 707, 708, 730, 747, 750, 761, 796, 853, 857, 866, 867, 881, 892, 898, 902, 911, 912, 915, 920, 928, 934, 938, 947, 973, 979, 983, 992, 996, 1010, 1037, 1039, 1040, 1052, 1053, 1085, 1100, 1104, 1148, 1212, 1242, 1248, 1250, 1251, 1255, 1258, 1260, 1273, 1323, 1326, 1330, 1339, 1340, 1345, 1348, 1349, 1350, 1382, 1392, 1394, 1402, 1403, 1405, 1408, 1409, 1410, 1411, 1412, 1413, 1426], "12": [9, 11, 19, 25, 44, 50, 55, 58, 59, 64, 65, 66, 89, 91, 93, 229, 230, 231, 265, 345, 380, 381, 392, 399, 405, 406, 407, 449, 486, 501, 516, 568, 572, 574, 606, 616, 1052, 1053, 1054, 1133, 1136, 1150, 1244, 1245, 1249, 1254, 1257, 1263, 1335, 1406, 1408, 1412, 1426], "9": [9, 11, 12, 19, 25, 35, 44, 46, 63, 64, 65, 66, 68, 82, 89, 101, 102, 111, 115, 125, 232, 293, 295, 339, 340, 342, 346, 347, 356, 374, 380, 405, 406, 424, 438, 449, 494, 496, 501, 504, 505, 508, 545, 566, 581, 586, 676, 706, 707, 708, 761, 1100, 1104, 1148, 1150, 1194, 1199, 1212, 1217, 1235, 1246, 1255, 1267, 1273, 1283, 1284, 1323, 1326, 1328, 1396, 1403, 1412, 1413, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426], "11": [9, 25, 33, 44, 64, 65, 66, 68, 89, 102, 110, 115, 157, 210, 239, 240, 297, 298, 303, 306, 307, 323, 392, 399, 405, 406, 407, 413, 415, 417, 422, 501, 514, 517, 606, 618, 680, 721, 738, 856, 901, 937, 982, 1052, 1053, 1054, 1100, 1150, 1287, 1403, 1410, 1413, 1414, 1419, 1424, 1425, 1426], "13": [9, 11, 38, 44, 64, 66, 89, 91, 156, 229, 230, 231, 343, 501, 703, 855, 900, 936, 981, 1150, 1192, 1406, 1420, 1426], "16": [9, 19, 31, 44, 45, 64, 66, 70, 229, 230, 231, 346, 347, 387, 389, 390, 394, 453, 508, 511, 512, 519, 571, 592, 606, 748, 749, 750, 1109, 1205, 1256, 1271, 1286, 1323, 1406, 1411, 1426], "17": [9, 21, 44, 64, 66, 103, 229, 230, 231, 297, 508, 680, 693, 1405, 1406, 1426], "friend": [9, 545, 1407, 1412], "member": [9, 92, 93, 94, 100, 112, 315, 317, 318, 319, 330, 391, 483, 484, 586, 691, 1222, 1267, 1403], "evelyn": 9, "jefferson": 9, "laura": 9, "mandevil": 9, "theresa": 9, "anderson": 9, "brenda": 9, "roger": 9, "charlott": 9, "mcdowd": 9, "franc": 9, "eleanor": 9, "nye": 9, "pearl": [9, 132], "oglethorp": 9, "ruth": 9, "desand": 9, "vern": 9, "sanderson": 9, "myra": 9, "liddel": 9, "katherina": 9, "sylvia": 9, "avondal": 9, "nora": 9, "fayett": 9, "helen": 9, "lloyd": 9, "dorothi": 9, "murchison": 9, "olivia": 9, "carleton": 9, "flora": 9, "price": 9, "meet": [9, 94, 1165, 1196, 1197, 1198], "50": [9, 25, 30, 34, 40, 50, 54, 55, 56, 57, 64, 65, 272, 312, 1117, 1193, 1197, 1198, 1251, 1297, 1302], "45": [9, 58, 64, 110, 226, 300, 409, 1175], "57": [9, 64], "46": [9, 64, 235, 564, 619, 1264], "24": [9, 19, 37, 64, 66, 68, 103, 383, 384, 496, 505, 508, 703, 1212, 1229, 1244, 1262, 1271, 1403], "32": [9, 64, 66, 68, 209, 211, 212, 383, 384, 564, 703, 1403, 1411], "36": [9, 21, 64, 68, 752, 1150, 1262, 1271, 1353, 1354, 1379, 1403], "31": [9, 64, 66, 229, 230, 231, 260, 261, 262, 289, 383, 384, 409, 703, 1226, 1235, 1403], "40": [9, 50, 64, 80, 101, 297, 300, 555, 672, 1173, 1240, 1271], "38": [9, 64, 688, 1271], "33": [9, 58, 64, 66, 68, 93, 383, 384, 500, 514, 703, 1267, 1271, 1403, 1414], "37": [9, 56, 64, 68, 303, 311, 312, 323, 324, 325, 496, 508, 1039, 1040, 1271, 1393, 1403, 1408, 1425], "43": [9, 64, 324, 325, 606, 1244, 1271], "34": [9, 64, 68, 331, 508, 762, 1271, 1403], "algorithm": [9, 14, 15, 44, 52, 54, 88, 93, 94, 95, 96, 102, 103, 107, 109, 110, 111, 112, 114, 115, 117, 120, 121, 122, 125, 127, 128, 132, 133, 136, 141, 151, 210, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 226, 227, 228, 229, 230, 231, 232, 235, 249, 251, 252, 253, 254, 255, 256, 258, 260, 261, 262, 263, 264, 265, 266, 267, 272, 275, 277, 278, 280, 282, 284, 285, 286, 287, 288, 289, 290, 293, 296, 297, 298, 299, 301, 302, 303, 306, 307, 308, 309, 311, 312, 315, 320, 322, 323, 324, 325, 326, 329, 330, 331, 332, 333, 337, 339, 340, 341, 342, 343, 345, 346, 347, 352, 358, 361, 362, 366, 371, 372, 373, 374, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 389, 390, 394, 399, 405, 406, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 421, 422, 424, 425, 426, 427, 428, 429, 430, 432, 433, 435, 437, 440, 449, 451, 452, 453, 454, 455, 460, 464, 466, 468, 481, 482, 483, 488, 494, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 512, 513, 514, 516, 519, 520, 521, 527, 537, 546, 547, 548, 552, 553, 554, 555, 556, 557, 558, 564, 566, 569, 577, 581, 582, 583, 589, 591, 592, 593, 600, 614, 616, 618, 619, 624, 625, 626, 627, 628, 629, 630, 632, 633, 635, 636, 639, 652, 653, 657, 658, 659, 660, 663, 664, 667, 671, 672, 673, 674, 676, 677, 678, 680, 681, 682, 683, 686, 690, 691, 692, 693, 695, 696, 697, 698, 699, 700, 701, 702, 711, 717, 721, 722, 729, 731, 732, 734, 735, 736, 737, 738, 749, 764, 765, 768, 770, 775, 776, 780, 786, 789, 790, 791, 853, 898, 934, 979, 1011, 1038, 1042, 1043, 1105, 1106, 1107, 1109, 1114, 1116, 1117, 1125, 1126, 1155, 1165, 1168, 1169, 1177, 1178, 1179, 1180, 1181, 1185, 1186, 1187, 1188, 1193, 1195, 1200, 1201, 1202, 1205, 1207, 1209, 1210, 1216, 1223, 1224, 1226, 1227, 1228, 1230, 1231, 1232, 1234, 1235, 1239, 1260, 1269, 1275, 1276, 1277, 1298, 1302, 1319, 1320, 1321, 1323, 1325, 1328, 1367, 1368, 1386, 1393, 1394, 1395, 1400, 1401, 1402, 1403, 1406, 1407, 1408, 1410, 1411, 1412, 1413, 1414, 1416, 1417, 1419, 1422, 1424, 1425, 1426], "davis_southern_women_graph": [9, 88, 263], "top": [9, 34, 52, 67, 106, 111, 112, 115, 125, 260, 272, 284, 350, 381, 670, 675, 770, 1106, 1134, 1136, 1252, 1396, 1399, 1407, 1412, 1413, 1416], "bottom": [9, 91, 115, 260, 272, 274, 284, 285, 286, 287, 288, 350, 381, 1134, 1136, 1155, 1404, 1416], "biadjacency_matrix": [9, 283], "onto": [9, 284, 285, 286, 287, 288, 559, 560], "projected_graph": [9, 115, 284, 285, 286, 288, 351], "keep": [9, 92, 93, 94, 115, 204, 345, 346, 347, 362, 377, 387, 389, 390, 394, 583, 598, 693, 694, 891, 972, 1117, 1207, 1210, 1278, 1279, 1296, 1376, 1394, 1411, 1414], "co": [9, 26, 94, 99, 144, 752, 1326], "occur": [9, 93, 95, 100, 230, 231, 277, 278, 280, 383, 581, 582, 583, 588, 1043, 1117, 1120, 1126, 1282, 1296], "count": [9, 185, 237, 238, 242, 243, 245, 297, 298, 310, 315, 330, 360, 386, 443, 568, 597, 619, 749, 753, 874, 917, 944, 950, 956, 959, 999, 1060, 1179, 1278, 1279, 1406, 1407, 1416], "share": [9, 54, 58, 92, 94, 112, 165, 199, 214, 215, 216, 221, 278, 285, 287, 288, 294, 358, 359, 376, 418, 419, 460, 462, 480, 569, 578, 691, 732, 862, 887, 907, 925, 943, 968, 988, 1007, 1217, 1328], "contact": [9, 92, 688, 1195, 1326], "weighted_projected_graph": [9, 284, 285, 286, 287, 1417], "648": 9, "071": [9, 17], "plot_davis_club": [9, 17], "retain": [10, 102, 110, 230, 284, 285, 286, 287, 288, 1100, 1187, 1295], "pattern": [10, 54, 93, 103, 236, 241, 244, 248, 385, 494, 519, 555, 671, 672, 673, 674, 690, 691, 693, 762, 786, 1036, 1088, 1388, 1413], "add": [10, 11, 26, 34, 41, 45, 49, 52, 61, 71, 88, 89, 91, 93, 94, 101, 102, 105, 106, 115, 151, 152, 153, 154, 156, 157, 158, 164, 207, 222, 223, 229, 282, 285, 341, 374, 411, 412, 423, 428, 430, 431, 450, 460, 581, 582, 583, 589, 614, 615, 618, 619, 654, 690, 701, 717, 718, 796, 850, 853, 854, 855, 856, 857, 892, 895, 898, 899, 900, 901, 902, 928, 931, 934, 935, 936, 937, 938, 973, 976, 979, 980, 981, 982, 983, 984, 1010, 1037, 1038, 1039, 1040, 1042, 1049, 1052, 1053, 1054, 1100, 1154, 1165, 1172, 1185, 1207, 1210, 1217, 1219, 1233, 1234, 1236, 1302, 1326, 1353, 1354, 1356, 1357, 1379, 1380, 1383, 1393, 1394, 1395, 1398, 1404, 1406, 1407, 1408, 1409, 1411, 1412, 1413, 1414, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426], "compressor": [10, 690, 786], "do": [10, 55, 75, 88, 92, 93, 94, 96, 99, 101, 102, 106, 107, 109, 111, 115, 133, 165, 184, 199, 202, 204, 230, 231, 238, 243, 277, 278, 280, 362, 380, 410, 411, 412, 418, 419, 458, 459, 467, 470, 589, 598, 632, 690, 692, 734, 735, 736, 737, 791, 796, 862, 873, 887, 890, 891, 907, 916, 925, 926, 927, 943, 954, 955, 968, 971, 972, 988, 997, 998, 1007, 1008, 1009, 1037, 1038, 1039, 1040, 1061, 1082, 1102, 1165, 1177, 1189, 1193, 1207, 1210, 1216, 1217, 1227, 1272, 1328, 1393, 1401, 1402, 1407, 1411, 1426], "would": [10, 92, 93, 95, 96, 100, 101, 102, 103, 104, 105, 107, 289, 305, 414, 415, 416, 417, 422, 428, 579, 583, 588, 632, 679, 690, 693, 717, 718, 751, 1217, 1236, 1295, 1296, 1300, 1303, 1326, 1416, 1417], "result": [10, 11, 25, 71, 92, 95, 101, 103, 109, 110, 112, 142, 165, 209, 218, 220, 230, 231, 255, 269, 271, 273, 276, 283, 284, 285, 286, 287, 288, 289, 299, 300, 305, 324, 325, 330, 374, 380, 381, 382, 385, 386, 391, 411, 412, 416, 418, 440, 464, 466, 467, 490, 494, 498, 499, 509, 510, 511, 512, 564, 565, 566, 584, 585, 587, 601, 609, 615, 626, 627, 629, 676, 678, 690, 692, 704, 710, 717, 786, 791, 862, 907, 943, 984, 988, 1038, 1042, 1082, 1094, 1098, 1099, 1102, 1103, 1105, 1112, 1113, 1114, 1116, 1131, 1132, 1138, 1139, 1140, 1141, 1142, 1150, 1152, 1154, 1157, 1159, 1160, 1163, 1175, 1177, 1180, 1201, 1222, 1225, 1239, 1278, 1279, 1281, 1296, 1299, 1303, 1308, 1326, 1328, 1331, 1334, 1359, 1402, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1416, 1417, 1425, 1426], "fewer": [10, 420, 421, 681, 683, 690, 692, 693, 694, 762, 786, 1213, 1215], "compress": [10, 25, 268, 512, 577, 690, 786, 1116, 1242, 1333, 1334, 1339, 1340, 1344, 1350, 1357, 1358, 1371, 1372, 1376], "suptitl": [10, 15], "original_graph": [10, 15, 690], "white_nod": 10, "red_nod": 10, "250": [10, 32, 1165], "white": [10, 21, 25, 82, 83, 127, 214, 215, 216, 220, 427, 1395, 1398, 1406], "add_nodes_from": [10, 15, 16, 36, 70, 71, 82, 89, 115, 156, 165, 199, 207, 236, 237, 248, 265, 267, 268, 423, 425, 426, 469, 555, 690, 796, 855, 862, 887, 892, 900, 907, 925, 928, 936, 943, 968, 973, 981, 988, 1007, 1010, 1037, 1039, 1040, 1065, 1194, 1217, 1291, 1404, 1406, 1413, 1426], "add_edges_from": [10, 15, 16, 36, 41, 70, 82, 89, 115, 132, 151, 158, 165, 199, 204, 207, 236, 248, 287, 327, 376, 422, 423, 425, 426, 460, 469, 501, 511, 512, 572, 574, 588, 688, 690, 705, 706, 707, 709, 730, 742, 743, 796, 853, 857, 862, 887, 891, 892, 898, 902, 907, 925, 927, 928, 934, 938, 943, 956, 962, 963, 968, 972, 973, 979, 983, 988, 999, 1002, 1003, 1007, 1009, 1010, 1037, 1039, 1040, 1070, 1085, 1094, 1135, 1154, 1217, 1287, 1291, 1326, 1404, 1407, 1426], "base_opt": [10, 15], "dict": [10, 15, 19, 25, 39, 54, 57, 58, 67, 70, 88, 101, 102, 107, 109, 144, 145, 148, 157, 159, 160, 165, 168, 169, 176, 179, 184, 189, 190, 195, 197, 200, 202, 204, 207, 220, 237, 239, 240, 252, 290, 309, 310, 329, 334, 336, 353, 408, 411, 412, 416, 422, 427, 470, 473, 481, 482, 496, 502, 512, 545, 561, 563, 565, 566, 575, 577, 578, 579, 580, 588, 614, 628, 631, 636, 637, 638, 640, 642, 644, 645, 646, 647, 648, 649, 662, 666, 669, 687, 688, 691, 705, 706, 707, 713, 715, 749, 750, 760, 796, 849, 856, 858, 859, 862, 865, 870, 873, 878, 879, 884, 888, 890, 891, 892, 894, 901, 903, 904, 907, 910, 916, 923, 926, 927, 928, 930, 931, 935, 937, 939, 940, 943, 946, 947, 951, 955, 960, 965, 969, 971, 972, 973, 975, 976, 980, 982, 984, 985, 988, 991, 992, 998, 1005, 1008, 1009, 1010, 1012, 1013, 1018, 1019, 1020, 1021, 1022, 1037, 1038, 1039, 1040, 1041, 1045, 1047, 1085, 1086, 1091, 1094, 1097, 1106, 1107, 1108, 1109, 1110, 1111, 1114, 1115, 1116, 1117, 1120, 1122, 1126, 1134, 1136, 1193, 1196, 1197, 1198, 1207, 1208, 1213, 1295, 1296, 1302, 1303, 1307, 1324, 1326, 1345, 1348, 1349, 1350, 1355, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1364, 1365, 1366, 1382, 1393, 1394, 1395, 1402, 1404, 1406, 1407, 1408, 1409, 1411, 1412, 1413, 1415, 1416, 1425, 1426], "edgecolor": [10, 15, 21, 32, 34, 35, 38, 54, 58, 82, 83, 1137], "black": [10, 15, 21, 25, 65, 69, 93, 598, 1133, 1134, 1136, 1412, 1413, 1414, 1416, 1426], "ax1": [10, 15, 27, 50, 82], "number_of_edg": [10, 15, 25, 28, 198, 690, 886, 924, 967, 1006, 1059, 1154, 1271, 1406, 1407, 1426], "nonexp_graph": 10, "compression_nod": 10, "summar": [10, 15, 100, 101, 690, 691, 758, 791, 1325, 1328, 1413], "dedensifi": [10, 758], "threshold": [10, 57, 83, 112, 220, 229, 231, 380, 381, 690, 692, 695, 696, 758, 786, 1117, 1193, 1194, 1196, 1197, 1198, 1325, 1398, 1406, 1407, 1408, 1412, 1414], "copi": [10, 16, 38, 44, 93, 95, 106, 167, 196, 199, 202, 203, 204, 205, 284, 285, 286, 287, 288, 341, 388, 390, 392, 406, 433, 434, 435, 436, 437, 453, 460, 469, 521, 584, 585, 587, 596, 599, 602, 603, 605, 606, 607, 610, 611, 613, 614, 633, 636, 690, 864, 885, 887, 890, 891, 909, 925, 926, 927, 945, 963, 966, 968, 971, 972, 990, 1003, 1007, 1008, 1009, 1035, 1038, 1057, 1061, 1063, 1066, 1082, 1083, 1122, 1183, 1189, 1217, 1223, 1227, 1251, 1270, 1294, 1295, 1296, 1403, 1404, 1406, 1407, 1408, 1409, 1412, 1413, 1422, 1425], "nonexp_node_color": 10, "nonexp_node_s": 10, "yellow": [10, 15, 598, 760, 1426], "nonexp_po": 10, "75": [10, 34, 239, 260, 299, 314, 355, 356, 386, 682, 1169, 1170, 1171, 1173, 1404, 1408, 1426], "c_node": [10, 690], "spot": 10, "242": [10, 17], "plot_dedensif": [10, 17], "153": [11, 455], "curiou": 11, "let": [11, 55, 58, 93, 97, 101, 103, 217, 257, 280, 282, 299, 300, 313, 322, 371, 372, 383, 586, 619, 762, 1219, 1278, 1279, 1326, 1425], "defin": [11, 24, 52, 58, 69, 97, 112, 127, 213, 222, 223, 239, 240, 260, 261, 262, 263, 285, 289, 311, 316, 329, 334, 335, 345, 346, 347, 356, 385, 386, 390, 424, 425, 426, 429, 432, 433, 434, 435, 436, 437, 449, 464, 465, 466, 469, 494, 495, 498, 499, 500, 502, 503, 506, 507, 509, 510, 519, 567, 569, 570, 571, 573, 574, 575, 577, 586, 614, 615, 619, 621, 625, 652, 671, 673, 674, 676, 684, 685, 686, 687, 688, 689, 728, 730, 738, 751, 752, 753, 762, 791, 796, 1037, 1038, 1039, 1040, 1045, 1047, 1071, 1081, 1098, 1147, 1154, 1170, 1172, 1195, 1197, 1280, 1286, 1287, 1288, 1296, 1320, 1321, 1326, 1344, 1353, 1354, 1359, 1363, 1379, 1395, 1402, 1407, 1408, 1412, 1426], "an": [11, 15, 24, 25, 31, 34, 38, 41, 44, 46, 49, 52, 54, 55, 58, 63, 66, 67, 71, 75, 76, 77, 88, 91, 92, 93, 94, 95, 96, 99, 100, 101, 102, 103, 104, 107, 110, 112, 114, 115, 116, 120, 121, 127, 128, 132, 141, 151, 152, 157, 158, 160, 165, 166, 167, 168, 170, 175, 179, 180, 181, 184, 188, 189, 191, 192, 193, 194, 195, 198, 199, 201, 204, 206, 207, 208, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 226, 227, 229, 230, 231, 232, 235, 238, 239, 240, 243, 249, 250, 251, 255, 256, 264, 266, 267, 269, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 291, 292, 293, 294, 295, 297, 298, 299, 301, 302, 306, 307, 308, 309, 311, 312, 315, 316, 318, 319, 320, 322, 324, 325, 326, 329, 330, 332, 341, 342, 343, 345, 346, 347, 348, 349, 350, 351, 353, 357, 362, 363, 364, 365, 366, 370, 373, 374, 375, 377, 378, 379, 380, 381, 383, 384, 385, 387, 388, 389, 390, 392, 394, 395, 400, 402, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 427, 428, 429, 431, 432, 433, 437, 438, 439, 440, 449, 450, 451, 455, 456, 457, 460, 462, 466, 467, 468, 469, 471, 472, 473, 474, 475, 477, 480, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 516, 517, 519, 520, 521, 522, 523, 524, 525, 530, 534, 535, 540, 544, 545, 555, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 577, 578, 579, 580, 584, 586, 588, 589, 590, 593, 594, 595, 596, 597, 598, 601, 604, 605, 607, 610, 611, 615, 616, 618, 619, 624, 626, 627, 631, 632, 633, 635, 636, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 678, 679, 680, 681, 682, 683, 684, 686, 690, 691, 692, 694, 695, 696, 697, 701, 703, 704, 705, 706, 707, 708, 716, 717, 719, 721, 722, 723, 724, 725, 726, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 743, 748, 752, 760, 761, 762, 767, 775, 782, 791, 796, 801, 806, 810, 814, 818, 822, 827, 832, 837, 842, 847, 849, 850, 851, 853, 854, 856, 857, 859, 862, 863, 864, 865, 866, 869, 871, 872, 873, 877, 878, 880, 881, 882, 883, 884, 886, 887, 889, 891, 892, 894, 895, 896, 898, 899, 901, 902, 904, 907, 908, 909, 910, 911, 914, 915, 916, 920, 921, 922, 923, 924, 925, 927, 928, 930, 931, 932, 934, 935, 937, 938, 940, 943, 944, 945, 946, 947, 948, 950, 952, 953, 954, 955, 959, 960, 961, 962, 963, 964, 965, 967, 968, 970, 972, 973, 975, 976, 977, 979, 980, 982, 983, 985, 988, 989, 990, 991, 992, 993, 995, 996, 997, 998, 1002, 1003, 1004, 1005, 1006, 1007, 1009, 1010, 1012, 1013, 1018, 1020, 1036, 1037, 1038, 1039, 1040, 1042, 1043, 1045, 1046, 1049, 1050, 1051, 1061, 1062, 1066, 1068, 1074, 1075, 1081, 1082, 1084, 1085, 1086, 1087, 1088, 1090, 1094, 1098, 1099, 1100, 1101, 1102, 1103, 1105, 1115, 1117, 1122, 1133, 1135, 1137, 1143, 1144, 1146, 1149, 1150, 1151, 1152, 1154, 1155, 1157, 1159, 1160, 1163, 1166, 1167, 1175, 1177, 1178, 1179, 1181, 1182, 1185, 1186, 1187, 1188, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1202, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1216, 1217, 1218, 1222, 1224, 1225, 1227, 1228, 1229, 1230, 1232, 1234, 1235, 1236, 1239, 1242, 1244, 1250, 1259, 1262, 1263, 1267, 1269, 1270, 1271, 1272, 1273, 1275, 1276, 1277, 1278, 1279, 1281, 1282, 1287, 1288, 1291, 1294, 1295, 1296, 1300, 1302, 1303, 1319, 1320, 1321, 1323, 1324, 1326, 1328, 1329, 1331, 1333, 1334, 1336, 1341, 1344, 1352, 1362, 1363, 1365, 1371, 1377, 1378, 1379, 1380, 1381, 1383, 1387, 1393, 1394, 1395, 1397, 1398, 1399, 1402, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1412, 1413, 1414, 1416, 1417, 1424, 1425, 1426], "process": [11, 13, 52, 76, 92, 93, 94, 96, 97, 98, 102, 104, 180, 222, 226, 232, 274, 331, 338, 373, 383, 405, 406, 440, 455, 464, 465, 466, 592, 624, 691, 760, 786, 871, 914, 952, 995, 1045, 1100, 1175, 1177, 1180, 1216, 1219, 1222, 1225, 1245, 1280, 1290, 1295, 1296, 1299, 1301, 1383, 1395, 1407, 1408, 1412, 1413, 1414, 1419, 1426], "follow": [11, 25, 44, 49, 52, 53, 65, 67, 83, 86, 91, 92, 93, 94, 95, 97, 99, 100, 101, 102, 103, 108, 110, 111, 128, 132, 151, 161, 171, 183, 207, 213, 227, 229, 230, 231, 243, 280, 305, 338, 343, 351, 362, 373, 378, 380, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 440, 452, 453, 465, 466, 496, 502, 503, 504, 505, 506, 507, 508, 588, 598, 599, 602, 615, 636, 679, 748, 750, 760, 762, 791, 853, 867, 892, 898, 912, 928, 934, 948, 973, 979, 993, 1010, 1102, 1103, 1105, 1144, 1165, 1175, 1179, 1185, 1188, 1200, 1201, 1209, 1219, 1225, 1233, 1234, 1241, 1251, 1260, 1274, 1275, 1276, 1277, 1281, 1296, 1315, 1323, 1326, 1328, 1329, 1388, 1393, 1395, 1399, 1404, 1406, 1407, 1409, 1411, 1412, 1413, 1425, 1426], "given": [11, 38, 44, 62, 64, 67, 91, 99, 101, 103, 112, 116, 141, 142, 144, 152, 158, 193, 197, 208, 211, 212, 227, 229, 235, 236, 248, 249, 260, 264, 266, 269, 271, 273, 274, 276, 279, 281, 283, 284, 285, 286, 287, 288, 320, 329, 331, 338, 344, 351, 353, 357, 362, 363, 364, 365, 373, 378, 380, 381, 385, 439, 454, 455, 460, 462, 470, 477, 478, 480, 497, 511, 512, 513, 559, 560, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 576, 578, 579, 580, 588, 589, 590, 614, 615, 616, 622, 623, 659, 660, 661, 662, 676, 677, 678, 679, 681, 683, 684, 686, 690, 691, 693, 697, 698, 699, 700, 702, 703, 704, 706, 707, 708, 709, 728, 729, 730, 731, 732, 739, 748, 753, 761, 782, 786, 854, 857, 882, 899, 902, 921, 935, 938, 963, 980, 983, 1003, 1046, 1085, 1086, 1094, 1101, 1102, 1135, 1144, 1151, 1162, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1189, 1199, 1200, 1201, 1206, 1207, 1208, 1209, 1210, 1221, 1222, 1240, 1269, 1273, 1274, 1276, 1295, 1300, 1302, 1315, 1323, 1353, 1354, 1379, 1380, 1394, 1395, 1406], "digit": [11, 70, 99], "base": [11, 15, 38, 43, 55, 58, 69, 93, 94, 100, 101, 102, 103, 107, 128, 132, 199, 203, 205, 212, 216, 220, 229, 296, 297, 301, 302, 303, 308, 309, 310, 311, 312, 322, 323, 324, 325, 329, 330, 337, 343, 346, 347, 362, 371, 373, 374, 380, 381, 382, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 423, 425, 426, 427, 428, 430, 431, 449, 464, 466, 494, 498, 499, 500, 509, 510, 545, 555, 564, 566, 569, 574, 581, 614, 616, 660, 667, 680, 688, 691, 704, 706, 707, 708, 710, 711, 712, 713, 714, 715, 717, 732, 738, 758, 761, 762, 786, 791, 796, 887, 925, 934, 935, 968, 979, 980, 1007, 1036, 1037, 1038, 1041, 1043, 1082, 1088, 1182, 1229, 1235, 1253, 1267, 1296, 1320, 1321, 1323, 1326, 1383, 1387, 1392, 1395, 1402, 1403, 1404, 1406, 1407, 1408, 1409, 1411, 1412, 1421, 1425], "obtain": [11, 91, 165, 207, 282, 345, 346, 347, 380, 383, 387, 388, 389, 390, 394, 465, 511, 606, 618, 619, 656, 722, 742, 743, 760, 796, 862, 892, 907, 928, 943, 973, 988, 1010, 1037, 1039, 1040, 1164, 1253, 1272, 1278, 1279, 1323, 1326, 1356, 1357, 1402, 1426], "seri": [11, 444, 616, 680, 1215, 1286], "finit": [11, 462, 494, 495, 498, 499, 502, 503, 506, 507, 509, 510, 514, 518, 1177, 1179, 1192, 1222], "end": [11, 25, 36, 52, 95, 101, 106, 153, 154, 206, 215, 227, 267, 268, 300, 332, 333, 342, 371, 372, 427, 614, 618, 619, 626, 627, 631, 632, 634, 635, 636, 639, 640, 650, 651, 652, 653, 654, 655, 660, 664, 667, 677, 678, 680, 734, 736, 1038, 1061, 1066, 1075, 1080, 1082, 1084, 1117, 1133, 1135, 1152, 1165, 1206, 1229, 1326, 1333, 1334, 1337, 1338, 1339, 1340, 1342, 1344, 1350, 1353, 1357, 1358, 1368, 1371, 1372, 1375, 1376, 1379, 1404, 1413], "In": [11, 16, 27, 43, 54, 57, 58, 88, 92, 93, 94, 95, 97, 99, 100, 101, 103, 110, 115, 127, 132, 133, 175, 184, 199, 217, 229, 230, 231, 235, 240, 257, 258, 259, 278, 283, 286, 288, 289, 299, 311, 312, 324, 325, 329, 350, 357, 378, 379, 380, 410, 413, 414, 415, 422, 429, 443, 447, 450, 458, 460, 494, 498, 499, 501, 510, 565, 568, 572, 574, 590, 591, 615, 619, 621, 652, 653, 654, 657, 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1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426], "108": [11, 1216], "513": [11, 1398, 1406], "reach": [11, 99, 100, 314, 324, 327, 376, 383, 387, 389, 390, 394, 410, 411, 412, 418, 419, 494, 498, 499, 510, 564, 566, 626, 627, 632, 640, 643, 652, 693, 711, 758, 1188, 1207, 1210, 1407], "orbit": 11, "up": [11, 70, 80, 93, 94, 97, 99, 100, 101, 104, 107, 132, 133, 346, 347, 377, 423, 427, 509, 530, 540, 577, 619, 652, 653, 657, 748, 1036, 1038, 1061, 1066, 1082, 1088, 1102, 1144, 1148, 1173, 1213, 1215, 1272, 1326, 1328, 1355, 1358, 1395, 1396, 1402, 1404, 1406, 1410, 1411, 1413, 1414, 1416, 1417, 1420, 1426], "reveal": [11, 711, 786], "maximum": [11, 112, 115, 209, 210, 211, 212, 214, 215, 217, 222, 224, 227, 257, 259, 264, 277, 278, 279, 281, 288, 296, 304, 311, 312, 315, 316, 317, 318, 319, 321, 324, 328, 330, 339, 341, 342, 343, 346, 347, 352, 356, 361, 373, 377, 380, 382, 383, 385, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 428, 440, 472, 473, 494, 498, 499, 500, 501, 502, 503, 506, 507, 509, 510, 520, 521, 564, 566, 581, 583, 589, 591, 592, 670, 671, 672, 673, 674, 676, 691, 693, 694, 704, 706, 707, 708, 710, 711, 712, 713, 714, 715, 716, 720, 723, 724, 732, 734, 735, 736, 737, 740, 741, 749, 758, 768, 791, 1117, 1133, 1135, 1137, 1165, 1181, 1198, 1199, 1200, 1201, 1208, 1225, 1237, 1238, 1302, 1323, 1395, 1402, 1406, 1407, 1412, 1413], "cycl": [11, 38, 44, 95, 120, 214, 227, 228, 229, 230, 231, 232, 263, 293, 294, 295, 338, 341, 343, 358, 449, 450, 451, 452, 453, 457, 462, 463, 464, 466, 467, 468, 480, 496, 501, 504, 505, 508, 519, 584, 585, 587, 608, 628, 629, 630, 632, 652, 657, 658, 663, 697, 727, 742, 743, 758, 791, 1043, 1052, 1135, 1137, 1148, 1149, 1152, 1163, 1186, 1190, 1242, 1244, 1260, 1264, 1325, 1395, 1397, 1398, 1401, 1403, 1404, 1406, 1407, 1408, 1411, 1412, 1414, 1424, 1425], "requir": [11, 38, 65, 93, 94, 95, 99, 100, 101, 102, 104, 106, 107, 109, 111, 115, 165, 207, 291, 292, 293, 296, 301, 302, 308, 309, 316, 437, 476, 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481, 482, 729, 731, 1426], "power": [11, 45, 94, 110, 207, 311, 312, 324, 371, 372, 520, 521, 564, 566, 692, 758, 892, 928, 973, 1010, 1043, 1165, 1175, 1237, 1238, 1255, 1316, 1319, 1395, 1406, 1407, 1426], "abov": [11, 92, 93, 100, 101, 102, 103, 110, 291, 292, 315, 316, 325, 330, 380, 383, 386, 453, 460, 491, 494, 498, 499, 502, 503, 509, 510, 521, 686, 692, 730, 762, 1038, 1102, 1148, 1165, 1185, 1219, 1234, 1274, 1278, 1279, 1300, 1399, 1404, 1407, 1417], "correspond": [11, 67, 101, 103, 144, 161, 167, 222, 223, 227, 228, 229, 230, 231, 232, 233, 234, 265, 266, 281, 311, 312, 324, 325, 331, 332, 350, 361, 362, 380, 391, 415, 417, 418, 419, 422, 460, 476, 482, 511, 514, 581, 583, 588, 609, 615, 616, 624, 628, 629, 630, 677, 678, 679, 728, 729, 731, 732, 742, 743, 748, 791, 850, 864, 895, 909, 931, 945, 976, 990, 1098, 1099, 1101, 1102, 1103, 1105, 1109, 1115, 1135, 1143, 1144, 1175, 1177, 1178, 1179, 1180, 1181, 1193, 1194, 1212, 1222, 1271, 1272, 1274, 1276, 1277, 1278, 1279, 1281, 1323, 1332, 1333, 1335, 1336, 1355, 1358, 1359, 1360, 1363, 1364, 1370, 1394, 1405, 1406], "below": [11, 13, 25, 92, 94, 99, 100, 111, 151, 206, 330, 383, 408, 410, 411, 412, 413, 414, 415, 417, 419, 429, 464, 491, 492, 494, 496, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 565, 615, 692, 796, 853, 898, 934, 979, 1037, 1039, 1040, 1117, 1144, 1175, 1177, 1217, 1222, 1242, 1275, 1276, 1277, 1296, 1349, 1393, 1402, 1404, 1417, 1426], "powersum": 11, "over": [11, 34, 38, 49, 71, 88, 94, 95, 99, 101, 102, 103, 109, 152, 157, 158, 159, 160, 168, 175, 176, 180, 181, 184, 188, 189, 190, 191, 195, 200, 201, 213, 214, 220, 230, 235, 291, 295, 299, 314, 315, 316, 320, 329, 330, 345, 346, 347, 362, 363, 364, 365, 369, 373, 374, 381, 385, 408, 409, 429, 477, 488, 489, 496, 497, 523, 526, 529, 533, 536, 539, 543, 598, 636, 678, 690, 703, 704, 705, 706, 707, 708, 710, 711, 719, 733, 734, 736, 738, 762, 849, 851, 854, 856, 857, 858, 859, 865, 869, 870, 871, 872, 873, 877, 878, 879, 880, 884, 888, 889, 894, 896, 899, 901, 902, 903, 904, 910, 914, 915, 916, 923, 930, 932, 935, 937, 938, 939, 940, 946, 951, 952, 953, 955, 960, 961, 965, 969, 970, 975, 977, 980, 982, 983, 984, 985, 991, 995, 996, 998, 1005, 1074, 1075, 1084, 1100, 1192, 1217, 1225, 1233, 1241, 1278, 1279, 1288, 1326, 1328, 1393, 1402, 1404, 1405, 1407, 1409, 1410, 1411, 1412, 1413, 1414, 1416, 1425, 1426], "converg": [11, 311, 324, 373, 564, 565, 566, 676, 1043, 1407, 1408], "singl": [11, 13, 58, 80, 93, 94, 99, 101, 102, 104, 107, 143, 151, 152, 156, 158, 166, 168, 175, 176, 180, 188, 189, 193, 220, 265, 274, 290, 293, 294, 299, 315, 322, 327, 331, 344, 353, 354, 391, 393, 424, 427, 443, 462, 464, 491, 494, 498, 499, 502, 503, 509, 510, 577, 584, 585, 587, 598, 621, 635, 660, 661, 662, 677, 678, 690, 705, 742, 743, 786, 791, 796, 853, 854, 855, 857, 863, 865, 869, 870, 871, 877, 878, 882, 898, 899, 900, 902, 908, 910, 914, 921, 934, 935, 936, 938, 944, 946, 950, 951, 952, 959, 960, 962, 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1282, 1283, 1284, 1285, 1286, 1287, 1288, 1392, 1399, 1406, 1408, 1416, 1417], "infer": [15, 695, 1104, 1118, 1358, 1412], "differ": [15, 25, 27, 28, 33, 41, 53, 54, 57, 63, 71, 86, 92, 93, 94, 95, 99, 103, 112, 161, 164, 165, 204, 207, 215, 216, 223, 280, 282, 297, 298, 314, 315, 326, 330, 334, 335, 337, 341, 358, 361, 371, 372, 373, 374, 378, 410, 413, 414, 415, 435, 437, 509, 511, 512, 593, 602, 615, 704, 717, 718, 738, 750, 758, 772, 786, 862, 891, 892, 907, 928, 943, 972, 973, 988, 1010, 1102, 1105, 1133, 1165, 1169, 1170, 1171, 1193, 1198, 1207, 1255, 1269, 1287, 1296, 1326, 1365, 1366, 1382, 1394, 1404, 1405, 1406, 1413, 1414, 1425, 1426], "relat": [15, 34, 67, 92, 93, 95, 99, 100, 115, 129, 132, 220, 230, 297, 366, 370, 586, 588, 619, 688, 762, 767, 795, 1202, 1205, 1269, 1323, 1395, 1402, 1406, 1413, 1416, 1425], "strong": [15, 397, 511, 512, 517, 610, 619, 691, 699, 758, 1408], "weak": [15, 398, 691, 758, 1425], "number_of_nod": [15, 25, 80, 156, 187, 311, 324, 337, 383, 564, 581, 852, 855, 876, 897, 900, 919, 933, 936, 958, 978, 981, 1001, 1154, 1271, 1426], "7482934": 15, "_": [15, 16, 26, 38, 93, 105, 300, 333, 356, 372, 405, 406, 425, 426, 502, 503, 506, 507, 569, 588, 630, 1352, 1354, 1378, 1380, 1411], "edge_type_visual_weight_lookup": 15, "edge_weight": [15, 382, 583], "node_attribut": [15, 691], "edge_attribut": [15, 283, 691, 1101], "summary_graph": [15, 691], "snap_aggreg": [15, 758, 1413], "prefix": [15, 67, 512, 690, 691, 1272, 1326, 1347, 1413, 1421], "aggreg": [15, 511, 512, 691, 786], "summary_po": 15, "8375428": 15, "edge_typ": 15, "get_edge_data": [15, 25, 1411], "174": [15, 17, 386, 1164, 1169, 1170, 1171, 1323], "plot_snap": [15, 17], "support": [16, 52, 77, 92, 93, 96, 100, 101, 102, 103, 226, 308, 322, 339, 340, 342, 343, 356, 373, 410, 411, 412, 418, 419, 464, 494, 496, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 597, 626, 627, 632, 633, 635, 636, 690, 738, 762, 775, 786, 796, 1037, 1038, 1039, 1040, 1114, 1116, 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"graph_partit": 16, "categor": [16, 546, 547, 548, 611], "node_typ": [16, 1342, 1356, 1357], "supported_nod": 16, "unsupported_nod": 16, "remove_edges_from": [16, 89, 192, 453, 602, 881, 920, 962, 1002, 1175, 1177, 1222, 1393, 1394, 1412, 1420, 1426], "nbr": [16, 88, 159, 190, 199, 200, 207, 229, 230, 231, 285, 500, 506, 796, 858, 879, 887, 888, 892, 903, 925, 928, 939, 968, 969, 973, 984, 1007, 1010, 1037, 1039, 1040, 1094, 1326, 1404, 1426], "adj": [16, 88, 199, 200, 207, 324, 325, 796, 849, 887, 888, 892, 894, 915, 925, 928, 930, 968, 969, 973, 975, 996, 1007, 1010, 1037, 1039, 1040, 1094, 1326, 1404, 1411, 1417, 1425, 1426], "g_minus_h": 16, "strip": [16, 25, 69, 1215], "_node_color": 16, "_po": 16, "draw_networkx_edg": [16, 25, 26, 27, 28, 33, 35, 38, 39, 40, 41, 44, 46, 68, 83, 1130, 1133, 1134, 1136, 1137, 1411, 1413], "draw_networkx_label": [16, 25, 35, 38, 46, 71, 1130, 1133, 1134, 1135, 1137], "ncl": 16, "undirect": [16, 25, 34, 71, 93, 112, 177, 185, 204, 205, 209, 211, 212, 214, 215, 216, 217, 218, 219, 220, 221, 224, 227, 228, 229, 230, 231, 232, 237, 239, 240, 246, 247, 264, 267, 275, 277, 278, 280, 281, 293, 294, 295, 297, 298, 300, 313, 315, 318, 319, 321, 322, 328, 330, 331, 332, 333, 337, 338, 341, 345, 346, 347, 348, 349, 350, 352, 353, 371, 372, 379, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 428, 430, 431, 437, 439, 440, 450, 463, 464, 465, 466, 467, 478, 479, 480, 481, 482, 485, 486, 487, 488, 490, 491, 492, 500, 559, 560, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 581, 582, 583, 590, 594, 595, 598, 600, 601, 605, 606, 607, 610, 611, 613, 615, 618, 619, 624, 625, 652, 658, 681, 682, 683, 684, 686, 687, 688, 689, 692, 694, 717, 718, 727, 730, 731, 732, 734, 735, 736, 737, 738, 742, 743, 753, 760, 761, 762, 767, 779, 791, 874, 891, 917, 927, 956, 972, 999, 1009, 1036, 1038, 1056, 1060, 1088, 1090, 1098, 1101, 1115, 1133, 1135, 1146, 1166, 1167, 1173, 1175, 1182, 1184, 1187, 1189, 1190, 1191, 1193, 1196, 1197, 1198, 1199, 1202, 1206, 1207, 1217, 1219, 1230, 1243, 1244, 1247, 1250, 1251, 1252, 1254, 1259, 1273, 1275, 1276, 1278, 1279, 1282, 1298, 1323, 1326, 1327, 1333, 1341, 1342, 1344, 1351, 1352, 1353, 1354, 1371, 1377, 1378, 1379, 1380, 1381, 1383, 1389, 1390, 1395, 1401, 1402, 1404, 1406, 1408, 1411, 1414, 1417, 1426], "And": [16, 23, 47, 86, 93, 101, 107, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 467, 502, 503, 506, 507, 688, 1296, 1297, 1328, 1408, 1409, 1411, 1416, 1425], "specifi": [16, 24, 25, 62, 102, 151, 152, 157, 158, 167, 184, 185, 193, 207, 222, 223, 226, 232, 236, 238, 240, 241, 243, 244, 246, 247, 248, 260, 264, 266, 267, 268, 269, 271, 273, 276, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 299, 305, 310, 311, 320, 324, 326, 329, 338, 348, 349, 353, 356, 357, 374, 377, 410, 411, 412, 413, 414, 415, 418, 419, 433, 435, 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1402, 1403, 1404, 1406, 1407, 1412, 1416, 1426], "to_undirect": [16, 25, 69, 796, 1037, 1039, 1040, 1182, 1184, 1404, 1413, 1426], "magenta": 16, "six": 16, "classifi": [16, 512, 684, 750], "four": [16, 23, 47, 86, 99, 102, 165, 263, 585, 587, 692, 862, 907, 943, 988, 1039, 1040, 1164, 1193, 1199, 1211, 1323, 1407, 1408, 1414, 1426], "green": [16, 32, 38, 70, 93, 115, 464, 598, 760, 1302, 1330, 1394, 1412, 1426], "goal": [16, 88, 92, 99, 105, 107, 127, 383, 626, 627, 717, 718, 1042], "g_ex": 16, "m": [16, 25, 28, 30, 31, 63, 65, 67, 91, 93, 96, 102, 106, 110, 112, 128, 181, 191, 201, 209, 211, 212, 219, 227, 231, 235, 236, 238, 239, 240, 241, 243, 244, 248, 257, 258, 259, 263, 272, 274, 275, 278, 280, 282, 284, 293, 294, 296, 300, 301, 302, 308, 309, 315, 316, 317, 330, 338, 341, 343, 345, 352, 355, 356, 361, 362, 370, 380, 383, 385, 412, 429, 431, 432, 433, 451, 462, 479, 494, 498, 499, 509, 510, 511, 512, 519, 545, 555, 569, 582, 584, 585, 587, 588, 606, 614, 619, 625, 652, 658, 659, 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494, 495, 498, 499, 502, 503, 506, 507, 509, 510, 585, 587, 615, 660, 664, 667, 719, 733, 739, 762, 786, 796, 857, 902, 938, 983, 1037, 1038, 1039, 1040, 1046, 1085, 1086, 1101, 1102, 1104, 1165, 1170, 1193, 1196, 1197, 1198, 1199, 1213, 1215, 1278, 1294, 1296, 1330, 1333, 1334, 1345, 1348, 1349, 1350, 1359, 1360, 1363, 1364, 1365, 1366, 1371, 1382, 1388, 1390, 1394, 1404, 1414], "assert": [16, 67, 88, 102, 1411, 1414, 1424, 1425, 1426], "is_isomorph": [16, 584, 585, 587, 588, 608, 671, 690, 739, 758, 761, 762, 1399, 1406], "652": [16, 17], "plot_subgraph": [16, 17, 1414], "27": [17, 64, 66, 68, 96, 102, 110, 226, 235, 266, 301, 302, 308, 309, 326, 358, 383, 384, 435, 436, 453, 703, 1258, 1295, 1325, 1336, 1403], "291": [17, 377], "auto_examples_algorithm": 17, "03": [17, 21, 25, 47, 59, 85, 112, 217, 274, 300], "read": [18, 22, 25, 40, 52, 54, 55, 57, 58, 65, 75, 86, 93, 94, 100, 115, 159, 165, 167, 190, 200, 267, 583, 618, 796, 858, 862, 864, 879, 888, 903, 907, 909, 939, 943, 945, 947, 969, 984, 988, 990, 992, 1012, 1013, 1018, 1019, 1020, 1021, 1022, 1035, 1036, 1037, 1038, 1039, 1040, 1042, 1043, 1061, 1066, 1082, 1083, 1088, 1121, 1143, 1144, 1270, 1296, 1325, 1326, 1329, 1330, 1333, 1337, 1338, 1342, 1343, 1345, 1348, 1349, 1350, 1351, 1352, 1354, 1356, 1357, 1367, 1368, 1371, 1375, 1377, 1378, 1380, 1381, 1382, 1383, 1386, 1387, 1388, 1389, 1390, 1394, 1395, 1397, 1398, 1401, 1402, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1413, 1414, 1418, 1424, 1425], "write": [18, 22, 49, 52, 75, 76, 77, 86, 89, 93, 99, 105, 110, 115, 267, 268, 470, 1012, 1013, 1018, 1019, 1020, 1021, 1022, 1047, 1123, 1129, 1300, 1325, 1326, 1329, 1330, 1334, 1337, 1339, 1340, 1344, 1345, 1348, 1349, 1350, 1352, 1354, 1357, 1358, 1372, 1375, 1376, 1378, 1380, 1381, 1382, 1383, 1387, 1388, 1390, 1395, 1397, 1398, 1399, 1401, 1402, 1405, 1406, 1411, 1412, 1414, 1425, 1426], "simpl": [18, 22, 23, 32, 47, 86, 93, 94, 97, 100, 103, 109, 110, 132, 184, 220, 229, 230, 231, 249, 287, 293, 300, 304, 313, 321, 328, 332, 333, 338, 343, 371, 372, 373, 380, 381, 423, 425, 438, 452, 453, 468, 479, 481, 482, 490, 496, 500, 504, 505, 508, 514, 517, 518, 594, 608, 624, 632, 677, 678, 679, 680, 686, 693, 758, 775, 780, 796, 873, 916, 955, 998, 1037, 1038, 1039, 1040, 1098, 1099, 1100, 1130, 1133, 1175, 1177, 1180, 1181, 1207, 1208, 1209, 1210, 1217, 1219, 1222, 1252, 1269, 1296, 1323, 1325, 1326, 1328, 1330, 1351, 1352, 1353, 1354, 1382, 1388, 1395, 1401, 1404, 1406, 1407, 1412, 1413, 1421, 1426], "lollipop": [19, 1157, 1426], "vertex": [19, 115, 211, 235, 249, 281, 289, 315, 322, 330, 338, 359, 360, 373, 387, 394, 397, 427, 428, 432, 438, 477, 491, 580, 606, 615, 616, 619, 622, 623, 624, 688, 689, 758, 1164, 1185, 1190, 1206, 1218, 1219, 1222, 1251, 1323, 1326, 1400, 1406, 1407], "length": [19, 39, 52, 67, 102, 120, 151, 232, 288, 295, 297, 298, 299, 306, 307, 310, 314, 315, 316, 320, 322, 326, 327, 329, 330, 332, 333, 341, 343, 345, 346, 347, 371, 372, 383, 384, 451, 459, 462, 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1229, 1233], "crutchfield": 91, "institut": [91, 112, 214, 215, 216, 220], "discoveri": [91, 670, 675, 676, 690], "madison": 91, "jessica": 91, "flack": 91, "david": [91, 277, 362, 437, 442, 447, 448, 624, 685, 710, 711, 712, 713, 714, 715, 734, 736, 1146, 1157, 1255, 1408, 1409, 1412], "krakauer": 91, "financi": 91, "summer": [91, 105, 1405, 1413, 1414], "foundat": [91, 110, 412, 431, 441, 445, 446, 619, 751], "grant": [91, 100, 105, 1202], "w911nf": 91, "0288": 91, "darpa": 91, "intellig": [91, 132, 494, 574, 590, 732, 762, 1207, 1210], "subcontract": 91, "No": [91, 92, 228, 282, 284, 285, 286, 287, 288, 444, 450, 460, 680, 1038, 1393, 1394, 1396, 1411], "9060": 91, "000709": 91, "nsf": 91, "phy": [91, 275, 284, 313, 371, 372, 383, 385, 434, 573, 1165, 1177, 1182, 1183, 1184, 1187, 1230, 1234, 1287], "0748828": 91, "templeton": 91, "santa": [91, 214, 215, 216, 220], "fe": [91, 214, 215, 216, 220], "under": [91, 324, 325, 525, 535, 555, 566, 577, 586, 588, 606, 671, 672, 673, 674, 739, 1326, 1412, 1413, 1417], "contract": [91, 110, 391, 500, 584, 585, 587, 618, 619, 767, 1174, 1395, 1413], "0340": 91, "space": [92, 101, 109, 231, 296, 301, 302, 308, 309, 355, 423, 628, 629, 630, 760, 786, 1112, 1144, 1193, 1196, 1197, 1198, 1199, 1239, 1296, 1326, 1331, 1334, 1390, 1398, 1406, 1412, 1417], "manag": [92, 93, 100, 111, 228, 680, 691, 1402, 1411, 1412], "privat": [92, 100, 1412, 1413, 1421, 1425], "tracker": [92, 97, 100, 107], "wiki": [92, 112, 120, 121, 132, 211, 226, 230, 282, 283, 293, 340, 341, 425, 454, 469, 476, 483, 484, 488, 490, 590, 676, 695, 696, 704, 710, 732, 761, 767, 782, 1206, 1219, 1243, 1244, 1245, 1246, 1248, 1249, 1250, 1251, 1256, 1257, 1258, 1259, 1261, 1262, 1263, 1264], "channel": 92, "honor": 92, "particip": [92, 100, 357, 519, 569], "formal": [92, 100, 114, 132, 220, 289, 342, 621, 687, 688, 689], "claim": [92, 94, 1259], "affili": [92, 257, 258, 259, 286, 288, 1165], "role": [92, 103, 355, 1199, 1202, 1266, 1407], "exhaust": [92, 180, 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1325, 1414, 1426], "hello": [156, 157, 855, 856, 900, 901, 936, 937, 981, 982, 1303], "k3": [156, 157, 855, 856, 900, 901, 936, 937, 981, 982, 1217], "utm": [156, 855, 900, 936, 981], "382871": [156, 855, 900, 936, 981], "3972649": [156, 855, 900, 936, 981], "nodes_for_ad": [157, 856, 901, 937, 982], "iterator_of_nod": [157, 195, 856, 884, 901, 923, 937, 965, 982, 1005], "datadict": [159, 190, 200, 207, 734, 736, 858, 879, 888, 892, 903, 928, 939, 969, 973, 1010, 1084, 1312, 1326], "foovalu": [159, 190, 200, 858, 879, 888, 903, 939, 969], "nbrdict": [160, 859, 904, 940, 985, 1019, 1094], "fulfil": [161, 615], "cw": [161, 615], "ccw": [161, 615], "planar": [161, 614, 616, 617, 758, 1110, 1138, 1243, 1246, 1247, 1249, 1325, 1409, 1410], "first_nbr": [161, 615], "invalid": [161, 615, 1413], "alter": [163, 861, 906, 942, 987], "afterward": 164, "as_view": [165, 202, 204, 862, 890, 891, 907, 926, 927, 943, 971, 972, 988, 1008, 1009, 1089, 1090], "shallow": [165, 202, 204, 284, 285, 286, 287, 288, 862, 890, 891, 907, 926, 927, 943, 971, 972, 988, 1008, 1009, 1394], "deepcopi": [165, 202, 204, 862, 890, 891, 907, 926, 927, 943, 971, 972, 988, 1008, 1009, 1409], "__class__": [165, 199, 862, 887, 907, 925, 943, 968, 988, 1007, 1404, 1407, 1409, 1410, 1411], "fresh": [165, 862, 907, 943, 988, 1404], "inspir": [165, 230, 231, 342, 681, 862, 907, 943, 988, 1226, 1323, 1404], "deep": [165, 202, 204, 862, 890, 891, 907, 926, 927, 943, 971, 972, 988, 1008, 1009, 1265, 1394], "degreeview": [166, 863, 908, 944, 950, 989, 1404, 1426], "didegreeview": [166, 863], "outedgeview": [168, 189, 467, 468, 613, 747, 750, 865, 878, 1035, 1083, 1404, 1418], "ddict": [168, 176, 184, 189, 865, 870, 873, 878, 910, 916, 946, 951, 955, 960, 991, 998], "in_edg": [168, 189, 865, 878, 946, 960, 1404, 1406, 1407], "out_edg": [168, 865, 946, 1062, 1404, 1406, 1407, 1426], "quietli": [168, 189, 865, 878, 910, 946, 960, 991, 1087, 1426], "outedgedataview": [168, 189, 865, 878, 1404, 1411], "set_data": 169, "edge_dict": [170, 866, 911, 947, 992], "safe": [170, 866, 911, 1404, 1412], "edge_ind": [171, 867, 912, 948, 993], "data_dictionari": [171, 867, 912], "simpler": [172, 184, 868, 873, 913, 916, 949, 955, 994, 998, 1406, 1407, 1417], "indegreeview": [175, 869, 1404], "deg": [175, 188, 243, 259, 356, 361, 685, 869, 877, 950, 959, 1165, 1179, 1222, 1404], "inedgeview": [176, 870, 1404], "inedgedataview": [176, 870], "silent": [180, 193, 195, 320, 871, 882, 884, 914, 921, 923, 952, 963, 965, 995, 1003, 1005, 1085, 1086, 1127, 1353, 1354, 1359, 1363, 1406, 1413], "niter": [180, 681, 682, 683, 684, 851, 871, 896, 914, 932, 952, 977, 995, 1414], "__iter__": [180, 871, 914, 952, 995, 1303], "nodedata": [184, 873, 916, 955, 998], "5pm": [184, 796, 873, 916, 955, 998, 1037, 1039, 1040, 1394, 1426], "Not": [184, 379, 432, 433, 434, 435, 436, 437, 438, 476, 873, 916, 955, 998, 1117, 1216], "nedg": [185, 588, 874, 917, 956, 999], "__len__": [186, 187, 875, 876, 918, 919, 957, 958, 1000, 1001], "outdegreeview": [188, 877], "Will": [193, 362, 605, 607, 610, 882, 921, 963, 1003, 1404, 1414], "get_data": [197, 616], "inplac": [199, 690, 887, 925, 968, 1007, 1066, 1393], "reduct": [199, 469, 618, 786, 887, 925, 968, 1007, 1066, 1320, 1321, 1413, 1414], "sg": [199, 887, 925, 968, 1007], "largest_wcc": [199, 887, 925, 968, 1007], "is_multigraph": [199, 758, 887, 925, 968, 1007, 1154, 1412], "keydict": [199, 207, 887, 892, 925, 928, 968, 973, 1007, 1010, 1039, 1040], "contrast": [202, 204, 301, 302, 308, 309, 890, 891, 926, 927, 971, 972, 1008, 1009, 1066, 1233, 1241, 1426], "reciproc": [204, 299, 320, 322, 356, 411, 430, 447, 476, 620, 758, 891, 972, 1325, 1416, 1425], "mark_half_edg": 206, "li": [206, 619, 670, 675, 685, 775, 1207, 1210, 1425], "straightforward": [207, 892, 928, 973, 1010], "slightli": [207, 326, 437, 520, 521, 581, 892, 928, 973, 1010, 1165, 1326, 1404, 1407, 1412, 1414, 1425], "singleton": [207, 588, 892, 928, 973, 1010, 1218, 1251, 1407], "preserve_attr": [208, 723, 724, 725, 726], "optimum": [208, 231, 583, 720, 722, 791, 1395, 1406], "arboresc": [208, 460, 719, 720, 722, 724, 726, 740, 743, 758, 1272, 1395, 1406], "span": [208, 226, 227, 228, 295, 508, 618, 619, 624, 719, 720, 722, 724, 726, 732, 733, 734, 735, 736, 737, 738, 758, 1394, 1397, 1406, 1407, 1420], "max_ind_cliqu": 209, "networkxnotimpl": [209, 210, 211, 212, 220, 224, 227, 293, 294, 295, 318, 319, 321, 328, 343, 379, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 403, 404, 405, 406, 407, 422, 424, 425, 426, 427, 429, 455, 457, 458, 459, 460, 468, 481, 482, 500, 589, 590, 608, 680, 732, 1043, 1216, 1275, 1276, 1298, 1325, 1353, 1354, 1379, 1407, 1408], "boppana": [209, 211, 212], "halld\u00f3rsson": [209, 211, 212], "1992": [209, 211, 212, 517, 518, 1407], "exclud": [209, 211, 212, 215, 216, 261, 262, 453, 688, 719, 723, 724, 725, 726, 733, 751, 1036, 1038, 1088, 1217, 1412], "196": [209, 211, 212], "heurist": [210, 220, 228, 233, 234, 377, 380, 381, 427, 494, 509, 626, 627, 652, 663, 703, 758, 1173, 1320, 1321, 1325, 1395, 1408, 1412, 1413], "max_cliqu": 210, "rigor": 210, "pattabiraman": 210, "bharath": 210, "massiv": [210, 217], "421": 210, "448": 210, "1080": [210, 297, 298, 306, 307, 329], "15427951": 210, "986778": 210, "apx": [211, 212], "subseteq": [211, 280, 289, 618, 675], "omega": [211, 758, 782, 1414], "maximum_cliqu": 211, "1007": [211, 226, 296, 301, 302, 303, 308, 309, 323, 324, 325, 341, 431, 451, 498, 574, 1144, 1181], "bf01994876": 211, "iset": 212, "trial": [213, 230, 231, 1195, 1237, 1238], "estim": [213, 224, 297, 306, 313, 564, 625, 626, 627, 782, 1280, 1407], "coeffici": [213, 248, 260, 261, 262, 263, 289, 355, 356, 358, 570, 618, 619, 625, 682, 684, 778, 782, 1397, 1398, 1399, 1406, 1413], "fraction": [213, 257, 259, 286, 289, 297, 299, 304, 306, 315, 317, 318, 319, 321, 322, 326, 328, 330, 356, 358, 359, 519, 1165, 1234], "schank": 213, "thoma": [213, 751, 1407, 1409, 1413], "dorothea": [213, 1168], "wagner": [213, 429, 758, 1168, 1402, 1406], "universit\u00e4t": 213, "karlsruh": 213, "fakult\u00e4t": 213, "f\u00fcr": 213, "informatik": [213, 412], "5445": 213, "ir": [213, 606], "1000001239": 213, "erdos_renyi_graph": [213, 1224, 1232, 1326, 1406, 1426], "214": 213, "cutoff": [214, 215, 310, 326, 383, 410, 411, 412, 418, 419, 494, 495, 498, 499, 510, 637, 638, 640, 641, 642, 643, 644, 647, 648, 649, 656, 660, 661, 662, 667, 668, 669, 677, 678, 1234, 1398, 1402, 1406, 1413, 1416, 1424, 1425], "distinct": [214, 215, 255, 281, 288, 352, 391, 452, 453, 460, 578, 595, 608, 618, 700, 701, 734, 735, 736, 737, 789, 1150, 1244, 1271, 1323, 1326, 1328, 1395, 1417], "nonadjac": [214, 215, 480, 584, 585, 587], "cutset": [214, 215, 414, 415, 416, 417, 427, 428, 500, 506, 758], "menger": [214, 215, 216], "theorem": [214, 215, 216, 220, 235, 281, 311, 312, 322, 411, 506, 507, 514, 517, 518, 618, 1190, 1205], "local_node_connect": [214, 216, 408, 409, 410, 411, 413], "node_connect": [214, 215, 409, 410, 411, 412, 414, 415, 416, 417, 419, 427, 428, 1402], "dougla": [214, 215, 216, 220, 1413, 1425], "035": [214, 215, 216, 220], "eclect": [214, 215, 216], "ss": [214, 215, 216], "uci": [214, 215, 216, 467, 704, 706, 707, 708, 710, 734, 736], "drwhite": [214, 215, 216], "pprint": [214, 577, 711], "all_pairs_node_connect": [215, 216, 1402, 1424, 1425], "bf": [215, 216, 217, 363, 588, 704, 706, 707, 708, 717, 1397, 1401, 1406, 1409, 1412, 1413], "lose": [215, 796, 1037, 1039, 1040], "accuraci": [215, 312, 786], "platon": [215, 216, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 1245, 1248, 1254, 1257, 1261, 1263], "octahedr": [215, 216, 1257], "approx": [215, 216, 227, 229, 230, 231, 1413], "octahedral_graph": [215, 216], "vari": [217, 238, 243, 373, 378, 569, 695], "sweep": [217, 1412], "dsweep": 217, "a_1": [217, 477], "a_2": 217, "magnien": [217, 260, 261, 262, 289], "cl\u00e9menc": [217, 260, 261, 262, 289], "matthieu": [217, 260, 261, 262, 274, 289], "latapi": [217, 260, 261, 262, 274, 289], "michel": 217, "habib": 217, "empir": 217, "tight": 217, "jea": 217, "0904": 217, "2728": 217, "crescenzi": 217, "pierluigi": 217, "roberto": 217, "grossi": 217, "leonardo": 217, "lanzi": 217, "andrea": [217, 1165, 1413], "marino": 217, "symposium": [217, 619, 1186, 1195, 1239], "berlin": [217, 520, 521, 1413], "heidelberg": [217, 520, 521], "ut": 217, "ee": [217, 313], "mtat": 217, "238": 217, "2014_fall": 217, "domin": [218, 219, 311, 410, 414, 481, 482, 483, 484, 758, 1325, 1395, 1400, 1406, 1407], "opt": [218, 221, 1425], "min_weight_dominating_set": 219, "vazirani": [219, 221], "vijai": [219, 221, 517], "min_dens": 220, "95": [220, 590, 1283, 1284, 1382], "nest": [220, 427, 728, 730, 791, 1038, 1045, 1061, 1094, 1296, 1308, 1348, 1355, 1356, 1357, 1358, 1383, 1406], "forth": [220, 427], "relax": [220, 227, 1171, 1413], "narrow": [220, 1165], "whitnei": 220, "bicompon": [220, 387, 389, 390, 394], "ferraro": [220, 427], "cohes": [220, 427, 437], "1503": [220, 427], "04476v1": [220, 427], "santaf": 220, "ind": 220, "embedded": [220, 305, 427], "sociolog": [220, 427, 748], "103": [220, 427, 1222, 1288, 1292], "2307": [220, 297, 1255], "3088904": 220, "petersen": [220, 427, 761, 1251, 1256, 1259], "triconnect": [220, 427], "apxa": 220, "petersen_graph": [220, 380, 427, 492, 761, 1119, 1120, 1426], "fo": 221, "initial_cut": 222, "highest": [222, 269, 273, 276, 337, 357, 374, 387, 389, 390, 394, 428, 509, 688, 703, 1180], "suppli": [222, 256, 277, 278, 280, 281, 594, 1197, 1320, 1321, 1326, 1345, 1348, 1349, 1350, 1382, 1408, 1413], "cut_valu": [222, 429, 500, 506, 507, 1402], "probabl": [223, 227, 230, 231, 236, 237, 238, 241, 242, 243, 245, 274, 275, 296, 358, 452, 468, 593, 675, 738, 758, 796, 1037, 1039, 1040, 1168, 1169, 1170, 1171, 1173, 1175, 1179, 1182, 1184, 1185, 1186, 1187, 1188, 1193, 1195, 1196, 1197, 1198, 1199, 1203, 1205, 1224, 1225, 1227, 1228, 1229, 1230, 1232, 1233, 1234, 1235, 1236, 1239, 1241, 1278, 1279, 1283, 1284, 1319, 1403, 1404, 1406, 1414, 1417, 1426], "cut_siz": [223, 442, 447, 448, 758], "ramsei": [224, 758], "max_pair": 224, "closur": [225, 226, 467, 468, 1036, 1088, 1395, 1406, 1408, 1411], "terminal_nod": 226, "steiner": [226, 758, 1408, 1425], "leaf": [226, 355, 460, 465, 678, 1155, 1236, 1272], "across": [226, 248, 625, 1038, 1100, 1326, 1405], "kou": 226, "mehlhorn": [226, 511, 512, 1425], "proce": [226, 231, 232, 373, 378, 518, 1165], "steiner_tree_problem": 226, "markowski": 226, "berman": 226, "1981": [226, 1164, 1323], "acta": [226, 508], "informatica": [226, 508], "bf00288961": 226, "kurt": [226, 511, 512], "1988": [226, 1199, 1407], "0020": [226, 455], "0190": [226, 455], "88": [226, 513, 1178, 1180], "90066": 226, "held": [227, 1105], "karp": [227, 277, 278, 280, 499, 758, 1169, 1395, 1402, 1406], "entropi": 227, "scheme": [227, 337, 719, 733, 1393], "lceil": 227, "rceil": 227, "augment": [227, 422, 496, 510, 581, 758, 1408], "tour": [227, 488, 490], "pari": 227, "inequ": [227, 1283, 1284], "trip": [227, 229, 230, 231], "goeman": 227, "madri": 227, "gharan": 227, "saberi": [227, 1181], "1043": 227, "1061": 227, "set_edge_attribut": [227, 374, 500, 598, 626, 1402, 1404, 1407], "minimum_spanning_tre": [228, 1406, 1407], "hamiltonian": [228, 232, 697, 1242, 1244, 1249, 1250, 1254, 1258, 1264], "nico": 228, "rr": 228, "388": [228, 300], "carnegi": 228, "mellon": 228, "univ": 228, "pa": 228, "1976": [228, 453, 516, 1407], "essenc": 229, "feasibl": [229, 422, 494, 496, 498, 499, 502, 503, 504, 505, 508, 509, 510, 531, 534, 541, 544, 762, 1043], "init_cycl": [230, 231, 1413], "temp": [230, 232, 1098], "max_iter": [230, 231, 676], "n_inner": [230, 231], "suboptim": [230, 231, 581], "perturb": [230, 231], "wors": [230, 231, 301, 302, 308, 309, 494], "escap": [230, 231, 1407, 1413], "decreas": [230, 231, 332, 333, 337, 367, 383, 608, 673, 692, 703, 719, 733, 1116, 1175, 1177, 1222, 1234, 1294], "temperatur": [230, 1117], "steel": 230, "harden": 230, "cool": 230, "goe": 230, "greedy_tsp": [230, 231, 232, 1413], "threshold_accepting_tsp": [230, 232, 1413], "transpos": [230, 231, 282], "swap_two_nod": [230, 231], "transposit": [230, 231], "move_one_nod": [230, 231], "enact": [230, 231], "declar": [230, 231], "outer": [230, 231, 380, 436, 606, 615, 796, 1012, 1013, 1018, 1019, 1020, 1021, 1022, 1037, 1039, 1040, 1086, 1160, 1326], "percentag": [230, 231, 1269], "metaheurist": [230, 231], "characterist": [230, 231, 682, 775], "thoughtfulli": [230, 231], "exp": [230, 1197, 1199], "n_i": 230, "n_o": 230, "simulated_ann": 230, "incycl": [230, 231], "amount": [231, 496, 504, 505, 508, 676, 786, 1042, 1296, 1424, 1425], "minima": 231, "slowli": 231, "simulated_annealing_tsp": [231, 232, 1413], "unchang": [231, 1112, 1296], "presenc": [231, 652, 658, 1425], "0021": 231, "9991": 231, "90": [231, 274, 332, 333, 1286], "90201": 231, "asadpour_atsp": [232, 1414], "biggest": 232, "callabl": [232, 525, 535, 545, 552, 553, 554, 555, 671, 672, 673, 674, 796, 1036, 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"Subgraph": [[118, "subgraph"]], "Harmonic Centrality": [[118, "harmonic-centrality"]], "Dispersion": [[118, "dispersion"]], "Reaching": [[118, "reaching"]], "Percolation": [[118, "percolation"]], "Second Order Centrality": [[118, "second-order-centrality"]], "Trophic": [[118, "trophic"]], "VoteRank": [[118, "voterank"]], "Chains": [[119, "module-networkx.algorithms.chains"]], "Chordal": [[120, "chordal"]], "Coloring": [[123, "module-networkx.algorithms.coloring"]], "Communicability": [[124, "module-networkx.algorithms.communicability_alg"]], "Communities": [[125, "module-networkx.algorithms.community"]], "Bipartitions": [[125, "module-networkx.algorithms.community.kernighan_lin"]], "K-Clique": [[125, "module-networkx.algorithms.community.kclique"]], "Modularity-based communities": [[125, "module-networkx.algorithms.community.modularity_max"]], "Tree partitioning": [[125, "module-networkx.algorithms.community.lukes"]], "Label propagation": [[125, "module-networkx.algorithms.community.label_propagation"]], "Louvain Community Detection": [[125, "module-networkx.algorithms.community.louvain"]], "Fluid Communities": [[125, "module-networkx.algorithms.community.asyn_fluid"]], "Measuring partitions": [[125, "module-networkx.algorithms.community.quality"]], "Partitions via centrality measures": [[125, "module-networkx.algorithms.community.centrality"]], "Validating partitions": [[125, "module-networkx.algorithms.community.community_utils"]], "Components": [[126, "module-networkx.algorithms.components"]], "Strong connectivity": [[126, "strong-connectivity"]], "Weak connectivity": [[126, "weak-connectivity"]], "Attracting components": [[126, "attracting-components"]], "Biconnected components": [[126, "biconnected-components"]], "Semiconnectedness": [[126, "semiconnectedness"]], "Edge-augmentation": [[127, "module-networkx.algorithms.connectivity.edge_augmentation"]], "See Also": [[127, "see-also"], [762, "see-also"], [1041, "see-also"], [1041, "id2"], [1042, "see-also"], [1042, "id3"], [1042, "id5"]], "K-edge-components": [[127, "module-networkx.algorithms.connectivity.edge_kcomponents"]], "K-node-components": [[127, "module-networkx.algorithms.connectivity.kcomponents"]], "K-node-cutsets": [[127, "module-networkx.algorithms.connectivity.kcutsets"]], "Flow-based disjoint paths": [[127, "module-networkx.algorithms.connectivity.disjoint_paths"]], "Flow-based Connectivity": [[127, "module-networkx.algorithms.connectivity.connectivity"]], "Flow-based Minimum Cuts": [[127, "module-networkx.algorithms.connectivity.cuts"]], "Stoer-Wagner minimum cut": [[127, "module-networkx.algorithms.connectivity.stoerwagner"]], "Utils for flow-based connectivity": [[127, "module-networkx.algorithms.connectivity.utils"]], "Cores": [[128, "module-networkx.algorithms.core"]], "Cuts": [[130, "module-networkx.algorithms.cuts"]], "Cycles": [[131, "module-networkx.algorithms.cycles"]], "D-Separation": [[132, "module-networkx.algorithms.d_separation"]], "Blocking paths": [[132, "blocking-paths"]], "Illustration of D-separation with examples": [[132, "illustration-of-d-separation-with-examples"]], "D-separation and its applications in probability": [[132, "d-separation-and-its-applications-in-probability"]], "Examples": [[132, "examples"], [760, "examples"], [762, "examples"], [1041, "examples"], [1041, "id1"], [1042, "examples"], [1042, "id2"], [1042, "id4"], [1387, "examples"], [1393, "examples"], [1394, "examples"], [1402, "examples"], [1406, "examples"], [1406, "id29"], [1406, "id32"], [1406, "id35"], [1406, "id44"], [1406, "id47"], [1406, "id50"], [1406, "id53"], [1406, "id57"], [1406, "id60"], [1406, "id63"], [1406, "id66"], [1406, "id70"], [1406, "id74"]], "Directed Acyclic Graphs": [[133, "module-networkx.algorithms.dag"]], "Distance-Regular Graphs": [[135, "module-networkx.algorithms.distance_regular"]], "Dominance": [[136, "module-networkx.algorithms.dominance"]], "Dominating Sets": [[137, "module-networkx.algorithms.dominating"]], "Efficiency": [[138, "module-networkx.algorithms.efficiency_measures"]], "Eulerian": [[139, "module-networkx.algorithms.euler"]], "Flows": [[140, "module-networkx.algorithms.flow"]], "Maximum Flow": [[140, "maximum-flow"]], "Edmonds-Karp": [[140, "edmonds-karp"]], "Shortest Augmenting Path": [[140, "shortest-augmenting-path"]], "Preflow-Push": [[140, "preflow-push"]], "Dinitz": [[140, "dinitz"]], "Boykov-Kolmogorov": [[140, "boykov-kolmogorov"]], "Gomory-Hu Tree": [[140, "gomory-hu-tree"]], "Utils": [[140, "utils"]], "Network Simplex": [[140, "network-simplex"]], "Capacity Scaling Minimum Cost Flow": [[140, "capacity-scaling-minimum-cost-flow"]], "EdgeComponentAuxGraph.construct": [[141, "edgecomponentauxgraph-construct"]], "EdgeComponentAuxGraph.k_edge_components": [[142, "edgecomponentauxgraph-k-edge-components"]], "EdgeComponentAuxGraph.k_edge_subgraphs": [[143, "edgecomponentauxgraph-k-edge-subgraphs"]], "ISMAGS.analyze_symmetry": [[144, "ismags-analyze-symmetry"]], "ISMAGS.find_isomorphisms": [[145, "ismags-find-isomorphisms"]], "ISMAGS.is_isomorphic": [[146, "ismags-is-isomorphic"]], "ISMAGS.isomorphisms_iter": [[147, "ismags-isomorphisms-iter"]], "ISMAGS.largest_common_subgraph": [[148, "ismags-largest-common-subgraph"]], "ISMAGS.subgraph_is_isomorphic": [[149, "ismags-subgraph-is-isomorphic"]], "ISMAGS.subgraph_isomorphisms_iter": [[150, "ismags-subgraph-isomorphisms-iter"]], "PlanarEmbedding.add_edge": [[151, "planarembedding-add-edge"]], "PlanarEmbedding.add_edges_from": [[152, "planarembedding-add-edges-from"]], "PlanarEmbedding.add_half_edge_ccw": [[153, "planarembedding-add-half-edge-ccw"]], "PlanarEmbedding.add_half_edge_cw": [[154, "planarembedding-add-half-edge-cw"]], "PlanarEmbedding.add_half_edge_first": [[155, "planarembedding-add-half-edge-first"]], "PlanarEmbedding.add_node": [[156, "planarembedding-add-node"]], "PlanarEmbedding.add_nodes_from": [[157, "planarembedding-add-nodes-from"]], "PlanarEmbedding.add_weighted_edges_from": [[158, "planarembedding-add-weighted-edges-from"]], "PlanarEmbedding.adj": [[159, "planarembedding-adj"]], "PlanarEmbedding.adjacency": [[160, "planarembedding-adjacency"]], "PlanarEmbedding.check_structure": [[161, "planarembedding-check-structure"]], "PlanarEmbedding.clear": [[162, "planarembedding-clear"]], "PlanarEmbedding.clear_edges": [[163, "planarembedding-clear-edges"]], "PlanarEmbedding.connect_components": [[164, "planarembedding-connect-components"]], "PlanarEmbedding.copy": [[165, "planarembedding-copy"]], "PlanarEmbedding.degree": [[166, "planarembedding-degree"]], "PlanarEmbedding.edge_subgraph": [[167, "planarembedding-edge-subgraph"]], "PlanarEmbedding.edges": [[168, "planarembedding-edges"]], "PlanarEmbedding.get_data": [[169, "planarembedding-get-data"]], "PlanarEmbedding.get_edge_data": [[170, "planarembedding-get-edge-data"]], "PlanarEmbedding.has_edge": [[171, 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"PlanarEmbedding.succ": [[200, "planarembedding-succ"]], "PlanarEmbedding.successors": [[201, "planarembedding-successors"]], "PlanarEmbedding.to_directed": [[202, "planarembedding-to-directed"]], "PlanarEmbedding.to_directed_class": [[203, "planarembedding-to-directed-class"]], "PlanarEmbedding.to_undirected": [[204, "planarembedding-to-undirected"]], "PlanarEmbedding.to_undirected_class": [[205, "planarembedding-to-undirected-class"]], "PlanarEmbedding.traverse_face": [[206, "planarembedding-traverse-face"]], "PlanarEmbedding.update": [[207, "planarembedding-update"]], "Edmonds.find_optimum": [[208, "edmonds-find-optimum"]], "clique_removal": [[209, "clique-removal"]], "large_clique_size": [[210, "large-clique-size"]], "max_clique": [[211, "max-clique"]], "maximum_independent_set": [[212, "maximum-independent-set"]], "average_clustering": [[213, "average-clustering"], [260, "average-clustering"], [355, "average-clustering"]], "all_pairs_node_connectivity": [[214, 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"node_degree_xy": [[247, "node-degree-xy"]], "numeric_assortativity_coefficient": [[248, "numeric-assortativity-coefficient"]], "find_asteroidal_triple": [[249, "find-asteroidal-triple"]], "is_at_free": [[250, "is-at-free"]], "color": [[251, "color"]], "degrees": [[252, "degrees"]], "density": [[253, "density"], [1060, "density"]], "is_bipartite": [[254, "is-bipartite"]], "is_bipartite_node_set": [[255, "is-bipartite-node-set"]], "sets": [[256, "sets"]], "betweenness_centrality": [[257, "betweenness-centrality"], [297, "betweenness-centrality"]], "closeness_centrality": [[258, "closeness-centrality"], [299, "closeness-centrality"]], "degree_centrality": [[259, "degree-centrality"], [304, "degree-centrality"]], "clustering": [[261, "clustering"], [356, "clustering"]], "latapy_clustering": [[262, "latapy-clustering"]], "robins_alexander_clustering": [[263, "robins-alexander-clustering"]], "min_edge_cover": [[264, "min-edge-cover"], [440, "min-edge-cover"]], "generate_edgelist": [[265, 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"minimum_weight_full_matching": [[280, "minimum-weight-full-matching"]], "to_vertex_cover": [[281, "to-vertex-cover"]], "biadjacency_matrix": [[282, "biadjacency-matrix"]], "from_biadjacency_matrix": [[283, "from-biadjacency-matrix"]], "collaboration_weighted_projected_graph": [[284, "collaboration-weighted-projected-graph"]], "generic_weighted_projected_graph": [[285, "generic-weighted-projected-graph"]], "overlap_weighted_projected_graph": [[286, "overlap-weighted-projected-graph"]], "projected_graph": [[287, "projected-graph"]], "weighted_projected_graph": [[288, "weighted-projected-graph"]], "node_redundancy": [[289, "node-redundancy"]], "spectral_bipartivity": [[290, "spectral-bipartivity"]], "edge_boundary": [[291, "edge-boundary"]], "node_boundary": [[292, "node-boundary"]], "bridges": [[293, "bridges"]], "has_bridges": [[294, "has-bridges"]], "local_bridges": [[295, "local-bridges"]], "approximate_current_flow_betweenness_centrality": [[296, 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"local-reaching-centrality"]], "out_degree_centrality": [[328, "out-degree-centrality"]], "percolation_centrality": [[329, "percolation-centrality"]], "prominent_group": [[330, "prominent-group"]], "second_order_centrality": [[331, "second-order-centrality"]], "subgraph_centrality": [[332, "subgraph-centrality"]], "subgraph_centrality_exp": [[333, "subgraph-centrality-exp"]], "trophic_differences": [[334, "trophic-differences"]], "trophic_incoherence_parameter": [[335, "trophic-incoherence-parameter"]], "trophic_levels": [[336, "trophic-levels"]], "voterank": [[337, "voterank"]], "chain_decomposition": [[338, "chain-decomposition"]], "chordal_graph_cliques": [[339, "chordal-graph-cliques"]], "chordal_graph_treewidth": [[340, "chordal-graph-treewidth"]], "complete_to_chordal_graph": [[341, "complete-to-chordal-graph"]], "find_induced_nodes": [[342, "find-induced-nodes"]], "is_chordal": [[343, "is-chordal"]], "cliques_containing_node": [[344, "cliques-containing-node"]], "enumerate_all_cliques": [[345, "enumerate-all-cliques"]], "find_cliques": [[346, "find-cliques"]], "find_cliques_recursive": [[347, "find-cliques-recursive"]], "graph_clique_number": [[348, "graph-clique-number"]], "graph_number_of_cliques": [[349, "graph-number-of-cliques"]], "make_clique_bipartite": [[350, "make-clique-bipartite"]], "make_max_clique_graph": [[351, "make-max-clique-graph"]], "max_weight_clique": [[352, "max-weight-clique"]], "node_clique_number": [[353, "node-clique-number"]], "number_of_cliques": [[354, "number-of-cliques"]], "generalized_degree": [[357, "generalized-degree"]], "square_clustering": [[358, "square-clustering"]], "transitivity": [[359, "transitivity"]], "triangles": [[360, "triangles"]], "equitable_color": [[361, "equitable-color"]], "greedy_color": [[362, "greedy-color"]], "strategy_connected_sequential": [[363, "strategy-connected-sequential"]], "strategy_connected_sequential_bfs": [[364, "strategy-connected-sequential-bfs"]], 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[[457, "antichains"]], "dag_longest_path": [[458, "dag-longest-path"]], "dag_longest_path_length": [[459, "dag-longest-path-length"]], "dag_to_branching": [[460, "dag-to-branching"]], "descendants": [[461, "descendants"]], "is_aperiodic": [[462, "is-aperiodic"]], "is_directed_acyclic_graph": [[463, "is-directed-acyclic-graph"]], "lexicographical_topological_sort": [[464, "lexicographical-topological-sort"]], "topological_generations": [[465, "topological-generations"]], "topological_sort": [[466, "topological-sort"]], "transitive_closure": [[467, "transitive-closure"]], "transitive_closure_dag": [[468, "transitive-closure-dag"]], "transitive_reduction": [[469, "transitive-reduction"]], "barycenter": [[470, "barycenter"]], "center": [[471, "center"]], "eccentricity": [[473, "eccentricity"]], "periphery": [[474, "periphery"]], "radius": [[475, "radius"]], "resistance_distance": [[476, "resistance-distance"]], "global_parameters": [[477, "global-parameters"]], "intersection_array": [[478, "intersection-array"]], "is_distance_regular": [[479, "is-distance-regular"]], "is_strongly_regular": [[480, "is-strongly-regular"]], "dominance_frontiers": [[481, "dominance-frontiers"]], "immediate_dominators": [[482, "immediate-dominators"]], "dominating_set": [[483, "dominating-set"]], "is_dominating_set": [[484, "is-dominating-set"]], "efficiency": [[485, "efficiency"]], "global_efficiency": [[486, "global-efficiency"]], "local_efficiency": [[487, "local-efficiency"]], "eulerian_circuit": [[488, "eulerian-circuit"]], "eulerian_path": [[489, "eulerian-path"]], "eulerize": [[490, "eulerize"]], "has_eulerian_path": [[491, "has-eulerian-path"]], "is_eulerian": [[492, "is-eulerian"]], "is_semieulerian": [[493, "is-semieulerian"]], "boykov_kolmogorov": [[494, "boykov-kolmogorov"]], "build_residual_network": [[495, "build-residual-network"]], "capacity_scaling": [[496, "capacity-scaling"]], "cost_of_flow": [[497, "cost-of-flow"]], "dinitz": [[498, "dinitz"]], "edmonds_karp": [[499, "edmonds-karp"]], "gomory_hu_tree": [[500, "gomory-hu-tree"]], "max_flow_min_cost": [[501, "max-flow-min-cost"]], "maximum_flow": [[502, "maximum-flow"]], "maximum_flow_value": [[503, "maximum-flow-value"]], "min_cost_flow": [[504, "min-cost-flow"]], "min_cost_flow_cost": [[505, "min-cost-flow-cost"]], "minimum_cut": [[506, "minimum-cut"]], "minimum_cut_value": [[507, "minimum-cut-value"]], "network_simplex": [[508, "network-simplex"]], "preflow_push": [[509, "preflow-push"]], "shortest_augmenting_path": [[510, "shortest-augmenting-path"]], "weisfeiler_lehman_graph_hash": [[511, "weisfeiler-lehman-graph-hash"]], "weisfeiler_lehman_subgraph_hashes": [[512, "weisfeiler-lehman-subgraph-hashes"]], "is_digraphical": [[513, "is-digraphical"]], "is_graphical": [[514, "is-graphical"]], "is_multigraphical": [[515, "is-multigraphical"]], "is_pseudographical": [[516, "is-pseudographical"]], "is_valid_degree_sequence_erdos_gallai": [[517, "is-valid-degree-sequence-erdos-gallai"]], "is_valid_degree_sequence_havel_hakimi": [[518, "is-valid-degree-sequence-havel-hakimi"]], "flow_hierarchy": [[519, "flow-hierarchy"]], "is_kl_connected": [[520, "is-kl-connected"]], "kl_connected_subgraph": [[521, "kl-connected-subgraph"]], "is_isolate": [[522, "is-isolate"]], "isolates": [[523, "isolates"]], "number_of_isolates": [[524, "number-of-isolates"]], "DiGraphMatcher.__init__": [[525, "digraphmatcher-init"]], "DiGraphMatcher.candidate_pairs_iter": [[526, "digraphmatcher-candidate-pairs-iter"]], "DiGraphMatcher.initialize": [[527, "digraphmatcher-initialize"]], "DiGraphMatcher.is_isomorphic": [[528, "digraphmatcher-is-isomorphic"]], "DiGraphMatcher.isomorphisms_iter": [[529, "digraphmatcher-isomorphisms-iter"]], "DiGraphMatcher.match": [[530, "digraphmatcher-match"]], "DiGraphMatcher.semantic_feasibility": [[531, "digraphmatcher-semantic-feasibility"]], "DiGraphMatcher.subgraph_is_isomorphic": [[532, "digraphmatcher-subgraph-is-isomorphic"]], "DiGraphMatcher.subgraph_isomorphisms_iter": [[533, "digraphmatcher-subgraph-isomorphisms-iter"]], "DiGraphMatcher.syntactic_feasibility": [[534, "digraphmatcher-syntactic-feasibility"]], "GraphMatcher.__init__": [[535, "graphmatcher-init"]], "GraphMatcher.candidate_pairs_iter": [[536, "graphmatcher-candidate-pairs-iter"]], "GraphMatcher.initialize": [[537, "graphmatcher-initialize"]], "GraphMatcher.is_isomorphic": [[538, "graphmatcher-is-isomorphic"]], "GraphMatcher.isomorphisms_iter": [[539, "graphmatcher-isomorphisms-iter"]], "GraphMatcher.match": [[540, "graphmatcher-match"]], "GraphMatcher.semantic_feasibility": [[541, "graphmatcher-semantic-feasibility"]], "GraphMatcher.subgraph_is_isomorphic": [[542, "graphmatcher-subgraph-is-isomorphic"]], "GraphMatcher.subgraph_isomorphisms_iter": [[543, "graphmatcher-subgraph-isomorphisms-iter"]], "GraphMatcher.syntactic_feasibility": [[544, "graphmatcher-syntactic-feasibility"]], "networkx.algorithms.isomorphism.ISMAGS": [[545, "networkx-algorithms-isomorphism-ismags"]], "categorical_edge_match": [[546, "categorical-edge-match"]], "categorical_multiedge_match": [[547, "categorical-multiedge-match"]], "categorical_node_match": [[548, "categorical-node-match"]], "could_be_isomorphic": [[549, "could-be-isomorphic"]], "fast_could_be_isomorphic": [[550, "fast-could-be-isomorphic"]], "faster_could_be_isomorphic": [[551, "faster-could-be-isomorphic"]], "generic_edge_match": [[552, "generic-edge-match"]], "generic_multiedge_match": [[553, "generic-multiedge-match"]], "generic_node_match": [[554, "generic-node-match"]], "is_isomorphic": [[555, "is-isomorphic"]], "numerical_edge_match": [[556, "numerical-edge-match"]], "numerical_multiedge_match": [[557, "numerical-multiedge-match"]], "numerical_node_match": [[558, "numerical-node-match"]], "rooted_tree_isomorphism": [[559, "rooted-tree-isomorphism"]], "tree_isomorphism": [[560, "tree-isomorphism"]], "vf2pp_all_isomorphisms": [[561, "vf2pp-all-isomorphisms"]], "vf2pp_is_isomorphic": [[562, "vf2pp-is-isomorphic"]], "vf2pp_isomorphism": [[563, "vf2pp-isomorphism"]], "hits": [[564, "hits"]], "google_matrix": [[565, "google-matrix"]], "pagerank": [[566, "pagerank"]], "adamic_adar_index": [[567, "adamic-adar-index"]], "cn_soundarajan_hopcroft": [[568, "cn-soundarajan-hopcroft"]], "common_neighbor_centrality": [[569, "common-neighbor-centrality"]], "jaccard_coefficient": [[570, "jaccard-coefficient"]], "preferential_attachment": [[571, "preferential-attachment"]], "ra_index_soundarajan_hopcroft": [[572, "ra-index-soundarajan-hopcroft"]], "resource_allocation_index": [[573, "resource-allocation-index"]], "within_inter_cluster": [[574, "within-inter-cluster"]], "all_pairs_lowest_common_ancestor": [[575, "all-pairs-lowest-common-ancestor"]], "lowest_common_ancestor": [[576, "lowest-common-ancestor"]], "tree_all_pairs_lowest_common_ancestor": [[577, "tree-all-pairs-lowest-common-ancestor"]], "is_matching": [[578, "is-matching"]], "is_maximal_matching": [[579, "is-maximal-matching"]], "is_perfect_matching": [[580, "is-perfect-matching"]], "max_weight_matching": [[581, "max-weight-matching"]], "maximal_matching": [[582, "maximal-matching"]], "min_weight_matching": [[583, "min-weight-matching"]], "contracted_edge": [[584, "contracted-edge"]], "contracted_nodes": [[585, "contracted-nodes"]], "equivalence_classes": [[586, "equivalence-classes"]], "identified_nodes": [[587, "identified-nodes"]], "quotient_graph": [[588, "quotient-graph"]], "maximal_independent_set": [[589, "maximal-independent-set"]], "moral_graph": [[590, "moral-graph"]], "harmonic_function": [[591, "harmonic-function"]], "local_and_global_consistency": [[592, "local-and-global-consistency"]], "non_randomness": [[593, "non-randomness"]], "compose_all": [[594, "compose-all"]], "disjoint_union_all": [[595, "disjoint-union-all"]], "intersection_all": [[596, "intersection-all"]], "union_all": [[597, "union-all"]], "compose": [[598, "compose"]], "difference": [[599, "difference"]], "disjoint_union": [[600, "disjoint-union"]], "full_join": [[601, "full-join"]], "intersection": [[602, "intersection"]], "symmetric_difference": [[603, "symmetric-difference"]], "union": [[604, "union"]], "cartesian_product": [[605, "cartesian-product"]], "corona_product": [[606, "corona-product"]], "lexicographic_product": [[607, "lexicographic-product"]], "power": [[608, "power"]], "rooted_product": [[609, "rooted-product"]], "strong_product": [[610, "strong-product"]], "tensor_product": [[611, "tensor-product"]], "complement": [[612, "complement"]], "reverse": [[613, "reverse"]], "combinatorial_embedding_to_pos": [[614, "combinatorial-embedding-to-pos"]], "networkx.algorithms.planarity.PlanarEmbedding": [[615, "networkx-algorithms-planarity-planarembedding"]], "check_planarity": [[616, "check-planarity"]], "is_planar": [[617, "is-planar"]], "chromatic_polynomial": [[618, "chromatic-polynomial"]], "tutte_polynomial": [[619, "tutte-polynomial"]], "overall_reciprocity": [[620, "overall-reciprocity"]], "reciprocity": [[621, "reciprocity"]], "is_k_regular": [[622, "is-k-regular"]], "is_regular": [[623, "is-regular"]], "k_factor": [[624, "k-factor"]], "rich_club_coefficient": [[625, "rich-club-coefficient"]], "astar_path": [[626, "astar-path"]], "astar_path_length": [[627, "astar-path-length"]], "floyd_warshall": [[628, "floyd-warshall"]], "floyd_warshall_numpy": [[629, "floyd-warshall-numpy"]], "floyd_warshall_predecessor_and_distance": [[630, "floyd-warshall-predecessor-and-distance"]], "reconstruct_path": [[631, "reconstruct-path"]], "all_shortest_paths": [[632, "all-shortest-paths"]], "average_shortest_path_length": [[633, "average-shortest-path-length"]], "has_path": [[634, "has-path"]], "shortest_path": [[635, "shortest-path"]], "shortest_path_length": [[636, "shortest-path-length"]], "all_pairs_shortest_path": [[637, "all-pairs-shortest-path"]], "all_pairs_shortest_path_length": [[638, "all-pairs-shortest-path-length"]], "bidirectional_shortest_path": [[639, "bidirectional-shortest-path"]], "predecessor": [[640, "predecessor"]], "single_source_shortest_path": [[641, "single-source-shortest-path"]], "single_source_shortest_path_length": [[642, "single-source-shortest-path-length"]], "single_target_shortest_path": [[643, "single-target-shortest-path"]], "single_target_shortest_path_length": [[644, "single-target-shortest-path-length"]], "all_pairs_bellman_ford_path": [[645, "all-pairs-bellman-ford-path"]], "all_pairs_bellman_ford_path_length": [[646, "all-pairs-bellman-ford-path-length"]], "all_pairs_dijkstra": [[647, "all-pairs-dijkstra"]], "all_pairs_dijkstra_path": [[648, "all-pairs-dijkstra-path"]], "all_pairs_dijkstra_path_length": [[649, "all-pairs-dijkstra-path-length"]], "bellman_ford_path": [[650, "bellman-ford-path"]], "bellman_ford_path_length": [[651, "bellman-ford-path-length"]], "bellman_ford_predecessor_and_distance": [[652, "bellman-ford-predecessor-and-distance"]], "bidirectional_dijkstra": [[653, "bidirectional-dijkstra"]], "dijkstra_path": [[654, "dijkstra-path"]], "dijkstra_path_length": [[655, "dijkstra-path-length"]], "dijkstra_predecessor_and_distance": [[656, "dijkstra-predecessor-and-distance"]], "find_negative_cycle": [[657, "find-negative-cycle"]], "goldberg_radzik": [[658, "goldberg-radzik"]], "johnson": [[659, "johnson"]], "multi_source_dijkstra": [[660, "multi-source-dijkstra"]], "multi_source_dijkstra_path": [[661, "multi-source-dijkstra-path"]], "multi_source_dijkstra_path_length": [[662, "multi-source-dijkstra-path-length"]], "negative_edge_cycle": [[663, "negative-edge-cycle"]], "single_source_bellman_ford": [[664, "single-source-bellman-ford"]], "single_source_bellman_ford_path": [[665, "single-source-bellman-ford-path"]], "single_source_bellman_ford_path_length": [[666, "single-source-bellman-ford-path-length"]], "single_source_dijkstra": [[667, "single-source-dijkstra"]], "single_source_dijkstra_path": [[668, "single-source-dijkstra-path"]], "single_source_dijkstra_path_length": [[669, "single-source-dijkstra-path-length"]], "generate_random_paths": [[670, "generate-random-paths"]], "graph_edit_distance": [[671, "graph-edit-distance"]], "optimal_edit_paths": [[672, "optimal-edit-paths"]], "optimize_edit_paths": [[673, "optimize-edit-paths"]], "optimize_graph_edit_distance": [[674, "optimize-graph-edit-distance"]], "panther_similarity": [[675, "panther-similarity"]], "simrank_similarity": [[676, "simrank-similarity"]], "all_simple_edge_paths": [[677, "all-simple-edge-paths"]], "all_simple_paths": [[678, "all-simple-paths"]], "is_simple_path": [[679, "is-simple-path"]], "shortest_simple_paths": [[680, "shortest-simple-paths"]], "lattice_reference": [[681, "lattice-reference"]], "omega": [[682, "omega"]], "random_reference": [[683, "random-reference"]], "sigma": [[684, "sigma"]], "s_metric": [[685, "s-metric"]], "spanner": [[686, "spanner"]], "constraint": [[687, "constraint"]], "effective_size": [[688, "effective-size"]], "local_constraint": [[689, "local-constraint"]], "dedensify": [[690, "dedensify"]], "snap_aggregation": [[691, "snap-aggregation"]], "connected_double_edge_swap": [[692, "connected-double-edge-swap"]], "directed_edge_swap": [[693, "directed-edge-swap"]], "double_edge_swap": [[694, "double-edge-swap"]], "find_threshold_graph": [[695, "find-threshold-graph"]], "is_threshold_graph": [[696, "is-threshold-graph"]], "hamiltonian_path": [[697, "hamiltonian-path"]], "is_reachable": [[698, "is-reachable"]], "is_tournament": [[700, "is-tournament"]], "random_tournament": [[701, "random-tournament"]], "score_sequence": [[702, "score-sequence"]], "bfs_beam_edges": [[703, "bfs-beam-edges"]], "bfs_edges": [[704, "bfs-edges"]], "bfs_layers": [[705, "bfs-layers"]], "bfs_predecessors": [[706, "bfs-predecessors"]], "bfs_successors": [[707, "bfs-successors"]], "bfs_tree": [[708, "bfs-tree"]], "descendants_at_distance": [[709, "descendants-at-distance"]], "dfs_edges": [[710, "dfs-edges"]], "dfs_labeled_edges": [[711, "dfs-labeled-edges"]], "dfs_postorder_nodes": [[712, "dfs-postorder-nodes"]], "dfs_predecessors": [[713, "dfs-predecessors"]], "dfs_preorder_nodes": [[714, "dfs-preorder-nodes"]], "dfs_successors": [[715, "dfs-successors"]], "dfs_tree": [[716, "dfs-tree"]], "edge_bfs": [[717, "edge-bfs"]], "edge_dfs": [[718, "edge-dfs"]], "networkx.algorithms.tree.branchings.ArborescenceIterator": [[719, "networkx-algorithms-tree-branchings-arborescenceiterator"]], "networkx.algorithms.tree.branchings.Edmonds": [[720, "networkx-algorithms-tree-branchings-edmonds"]], "branching_weight": [[721, "branching-weight"]], "greedy_branching": [[722, "greedy-branching"]], "maximum_branching": [[723, "maximum-branching"]], "maximum_spanning_arborescence": [[724, "maximum-spanning-arborescence"]], "minimum_branching": [[725, "minimum-branching"]], "minimum_spanning_arborescence": [[726, "minimum-spanning-arborescence"]], "NotATree": [[727, "notatree"]], "from_nested_tuple": [[728, "from-nested-tuple"]], "from_prufer_sequence": [[729, "from-prufer-sequence"]], "to_nested_tuple": [[730, "to-nested-tuple"]], "to_prufer_sequence": [[731, "to-prufer-sequence"]], "junction_tree": [[732, "junction-tree"]], "networkx.algorithms.tree.mst.SpanningTreeIterator": [[733, "networkx-algorithms-tree-mst-spanningtreeiterator"]], "maximum_spanning_edges": [[734, "maximum-spanning-edges"]], "maximum_spanning_tree": [[735, "maximum-spanning-tree"]], "minimum_spanning_edges": [[736, "minimum-spanning-edges"]], "minimum_spanning_tree": [[737, "minimum-spanning-tree"]], "random_spanning_tree": [[738, "random-spanning-tree"]], "join": [[739, "join"]], "is_arborescence": [[740, "is-arborescence"]], "is_branching": [[741, "is-branching"]], "is_forest": [[742, "is-forest"]], "is_tree": [[743, "is-tree"]], "all_triads": [[744, "all-triads"]], "all_triplets": [[745, "all-triplets"]], "is_triad": [[746, "is-triad"]], "random_triad": [[747, "random-triad"]], "triad_type": [[748, "triad-type"]], "triadic_census": [[749, "triadic-census"]], "triads_by_type": [[750, "triads-by-type"]], "closeness_vitality": [[751, "closeness-vitality"]], "voronoi_cells": [[752, "voronoi-cells"]], "wiener_index": [[753, "wiener-index"]], "Graph Hashing": [[754, "module-networkx.algorithms.graph_hashing"]], "Graphical degree sequence": [[755, "module-networkx.algorithms.graphical"]], "Hierarchy": [[756, "module-networkx.algorithms.hierarchy"]], "Hybrid": [[757, "module-networkx.algorithms.hybrid"]], "Isolates": [[759, "module-networkx.algorithms.isolate"]], "Isomorphism": [[760, "isomorphism"]], "VF2++": [[760, "module-networkx.algorithms.isomorphism.vf2pp"]], "VF2++ Algorithm": [[760, "vf2-algorithm"]], "Tree Isomorphism": [[760, "module-networkx.algorithms.isomorphism.tree_isomorphism"]], "Advanced Interfaces": [[760, "advanced-interfaces"]], "ISMAGS Algorithm": [[761, "module-networkx.algorithms.isomorphism.ismags"]], "Notes": [[761, "notes"], [762, "notes"]], "ISMAGS object": [[761, "ismags-object"]], "VF2 Algorithm": [[762, "module-networkx.algorithms.isomorphism.isomorphvf2"]], "Subgraph Isomorphism": [[762, "subgraph-isomorphism"]], "Graph Matcher": [[762, "graph-matcher"]], "DiGraph Matcher": [[762, "digraph-matcher"]], "Match helpers": [[762, "match-helpers"]], "Link Analysis": [[763, "link-analysis"]], "PageRank": [[763, "module-networkx.algorithms.link_analysis.pagerank_alg"]], "Hits": [[763, "module-networkx.algorithms.link_analysis.hits_alg"]], "Link Prediction": [[764, "module-networkx.algorithms.link_prediction"]], "Lowest Common Ancestor": [[765, "module-networkx.algorithms.lowest_common_ancestors"]], "Minors": [[767, "module-networkx.algorithms.minors"]], "Maximal independent set": [[768, "module-networkx.algorithms.mis"]], "Moral": [[769, "module-networkx.algorithms.moral"]], "Node Classification": [[770, "module-networkx.algorithms.node_classification"]], "non-randomness": [[771, "module-networkx.algorithms.non_randomness"]], "Operators": [[772, "operators"]], "Planar Drawing": [[773, "module-networkx.algorithms.planar_drawing"]], "Planarity": [[774, "module-networkx.algorithms.planarity"]], "Graph Polynomials": [[775, "module-networkx.algorithms.polynomials"]], "Reciprocity": [[776, "module-networkx.algorithms.reciprocity"]], "Regular": [[777, "module-networkx.algorithms.regular"]], "Rich Club": [[778, "module-networkx.algorithms.richclub"]], "Shortest Paths": [[779, "module-networkx.algorithms.shortest_paths.generic"]], "Advanced Interface": [[779, "module-networkx.algorithms.shortest_paths.unweighted"]], "Dense Graphs": [[779, "module-networkx.algorithms.shortest_paths.dense"]], "A* Algorithm": [[779, "module-networkx.algorithms.shortest_paths.astar"]], "Similarity Measures": [[780, "module-networkx.algorithms.similarity"]], "Simple Paths": [[781, "module-networkx.algorithms.simple_paths"]], "Small-world": [[782, "module-networkx.algorithms.smallworld"]], "s metric": [[783, "module-networkx.algorithms.smetric"]], "Sparsifiers": [[784, "module-networkx.algorithms.sparsifiers"]], "Structural holes": [[785, "module-networkx.algorithms.structuralholes"]], "Summarization": [[786, "module-networkx.algorithms.summarization"]], "Swap": [[787, "module-networkx.algorithms.swap"]], "Threshold Graphs": [[788, "module-networkx.algorithms.threshold"]], "Tournament": [[789, "module-networkx.algorithms.tournament"]], "Traversal": [[790, "traversal"]], "Depth First Search": [[790, "module-networkx.algorithms.traversal.depth_first_search"]], "Breadth First Search": [[790, "module-networkx.algorithms.traversal.breadth_first_search"]], "Beam search": [[790, "module-networkx.algorithms.traversal.beamsearch"]], "Depth First Search on Edges": [[790, "module-networkx.algorithms.traversal.edgedfs"]], "Breadth First Search on Edges": [[790, "module-networkx.algorithms.traversal.edgebfs"]], "Tree": [[791, "tree"]], "Recognition": [[791, 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"FilterMultiInner.get": [[819, "filtermultiinner-get"]], "FilterMultiInner.items": [[820, "filtermultiinner-items"]], "FilterMultiInner.keys": [[821, "filtermultiinner-keys"]], "FilterMultiInner.values": [[822, "filtermultiinner-values"]], "MultiAdjacencyView.copy": [[823, "multiadjacencyview-copy"]], "MultiAdjacencyView.get": [[824, "multiadjacencyview-get"]], "MultiAdjacencyView.items": [[825, "multiadjacencyview-items"]], "MultiAdjacencyView.keys": [[826, "multiadjacencyview-keys"]], "MultiAdjacencyView.values": [[827, "multiadjacencyview-values"]], "UnionAdjacency.copy": [[828, "unionadjacency-copy"]], "UnionAdjacency.get": [[829, "unionadjacency-get"]], "UnionAdjacency.items": [[830, "unionadjacency-items"]], "UnionAdjacency.keys": [[831, "unionadjacency-keys"]], "UnionAdjacency.values": [[832, "unionadjacency-values"]], "UnionAtlas.copy": [[833, "unionatlas-copy"]], "UnionAtlas.get": [[834, "unionatlas-get"]], "UnionAtlas.items": [[835, "unionatlas-items"]], "UnionAtlas.keys": 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"DiGraph.nodes": [[873, "digraph-nodes"]], "DiGraph.number_of_edges": [[874, "digraph-number-of-edges"]], "DiGraph.number_of_nodes": [[875, "digraph-number-of-nodes"]], "DiGraph.order": [[876, "digraph-order"]], "DiGraph.out_degree": [[877, "digraph-out-degree"]], "DiGraph.out_edges": [[878, "digraph-out-edges"]], "DiGraph.pred": [[879, "digraph-pred"]], "DiGraph.predecessors": [[880, "digraph-predecessors"]], "DiGraph.remove_edge": [[881, "digraph-remove-edge"]], "DiGraph.remove_edges_from": [[882, "digraph-remove-edges-from"]], "DiGraph.remove_node": [[883, "digraph-remove-node"]], "DiGraph.remove_nodes_from": [[884, "digraph-remove-nodes-from"]], "DiGraph.reverse": [[885, "digraph-reverse"]], "DiGraph.size": [[886, "digraph-size"]], "DiGraph.subgraph": [[887, "digraph-subgraph"]], "DiGraph.succ": [[888, "digraph-succ"]], "DiGraph.successors": [[889, "digraph-successors"]], "DiGraph.to_directed": [[890, "digraph-to-directed"]], "DiGraph.to_undirected": [[891, 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"MultiDiGraph.__iter__": [[932, "multidigraph-iter"]], "MultiDiGraph.__len__": [[933, "multidigraph-len"]], "MultiDiGraph.add_edge": [[934, "multidigraph-add-edge"]], "MultiDiGraph.add_edges_from": [[935, "multidigraph-add-edges-from"]], "MultiDiGraph.add_node": [[936, "multidigraph-add-node"]], "MultiDiGraph.add_nodes_from": [[937, "multidigraph-add-nodes-from"]], "MultiDiGraph.add_weighted_edges_from": [[938, "multidigraph-add-weighted-edges-from"]], "MultiDiGraph.adj": [[939, "multidigraph-adj"]], "MultiDiGraph.adjacency": [[940, "multidigraph-adjacency"]], "MultiDiGraph.clear": [[941, "multidigraph-clear"]], "MultiDiGraph.clear_edges": [[942, "multidigraph-clear-edges"]], "MultiDiGraph.copy": [[943, "multidigraph-copy"]], "MultiDiGraph.degree": [[944, "multidigraph-degree"]], "MultiDiGraph.edge_subgraph": [[945, "multidigraph-edge-subgraph"]], "MultiDiGraph.edges": [[946, "multidigraph-edges"]], "MultiDiGraph.get_edge_data": [[947, "multidigraph-get-edge-data"]], "MultiDiGraph.has_edge": [[948, "multidigraph-has-edge"]], "MultiDiGraph.has_node": [[949, "multidigraph-has-node"]], "MultiDiGraph.in_degree": [[950, "multidigraph-in-degree"]], "MultiDiGraph.in_edges": [[951, "multidigraph-in-edges"]], "MultiDiGraph.nbunch_iter": [[952, "multidigraph-nbunch-iter"]], "MultiDiGraph.neighbors": [[953, "multidigraph-neighbors"]], "MultiDiGraph.new_edge_key": [[954, "multidigraph-new-edge-key"]], "MultiDiGraph.nodes": [[955, "multidigraph-nodes"]], "MultiDiGraph.number_of_edges": [[956, "multidigraph-number-of-edges"]], "MultiDiGraph.number_of_nodes": [[957, "multidigraph-number-of-nodes"]], "MultiDiGraph.order": [[958, "multidigraph-order"]], "MultiDiGraph.out_degree": [[959, "multidigraph-out-degree"]], "MultiDiGraph.out_edges": [[960, "multidigraph-out-edges"]], "MultiDiGraph.predecessors": [[961, "multidigraph-predecessors"]], "MultiDiGraph.remove_edge": [[962, "multidigraph-remove-edge"]], "MultiDiGraph.remove_edges_from": [[963, 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[[1013, "networkx-classes-coreviews-atlasview"]], "networkx.classes.coreviews.FilterAdjacency": [[1014, "networkx-classes-coreviews-filteradjacency"]], "networkx.classes.coreviews.FilterAtlas": [[1015, "networkx-classes-coreviews-filteratlas"]], "networkx.classes.coreviews.FilterMultiAdjacency": [[1016, "networkx-classes-coreviews-filtermultiadjacency"]], "networkx.classes.coreviews.FilterMultiInner": [[1017, "networkx-classes-coreviews-filtermultiinner"]], "networkx.classes.coreviews.MultiAdjacencyView": [[1018, "networkx-classes-coreviews-multiadjacencyview"]], "networkx.classes.coreviews.UnionAdjacency": [[1019, "networkx-classes-coreviews-unionadjacency"]], "networkx.classes.coreviews.UnionAtlas": [[1020, "networkx-classes-coreviews-unionatlas"]], "networkx.classes.coreviews.UnionMultiAdjacency": [[1021, "networkx-classes-coreviews-unionmultiadjacency"]], "networkx.classes.coreviews.UnionMultiInner": [[1022, "networkx-classes-coreviews-unionmultiinner"]], "hide_diedges": [[1023, "hide-diedges"]], "hide_edges": [[1024, "hide-edges"]], "hide_multidiedges": [[1025, "hide-multidiedges"]], "hide_multiedges": [[1026, "hide-multiedges"]], "hide_nodes": [[1027, "hide-nodes"]], "no_filter": [[1028, "no-filter"]], "show_diedges": [[1029, "show-diedges"]], "show_edges": [[1030, "show-edges"]], "show_multidiedges": [[1031, "show-multidiedges"]], "show_multiedges": [[1032, "show-multiedges"]], "networkx.classes.filters.show_nodes": [[1033, "networkx-classes-filters-show-nodes"]], "generic_graph_view": [[1034, "generic-graph-view"]], "reverse_view": [[1035, "reverse-view"], [1083, "reverse-view"]], "subgraph_view": [[1036, "subgraph-view"], [1088, "subgraph-view"]], "Graph\u2014Undirected graphs with self loops": [[1037, "graph-undirected-graphs-with-self-loops"]], "Graph types": [[1038, "graph-types"]], "Which graph class should I use?": [[1038, "which-graph-class-should-i-use"]], "Basic graph types": [[1038, "basic-graph-types"]], "Graph Views": [[1038, "module-networkx.classes.graphviews"]], "Core Views": [[1038, "module-networkx.classes.coreviews"]], "Filters": [[1038, "filters"]], "Backends": [[1038, "backends"]], "Create a Dispatcher": [[1038, "create-a-dispatcher"]], "MultiDiGraph\u2014Directed graphs with self loops and parallel edges": [[1039, "multidigraph-directed-graphs-with-self-loops-and-parallel-edges"]], "Adding and Removing Nodes and Edges": [[1039, "adding-and-removing-nodes-and-edges"]], "MultiGraph\u2014Undirected graphs with self loops and parallel edges": [[1040, "multigraph-undirected-graphs-with-self-loops-and-parallel-edges"]], "Converting to and from other data formats": [[1041, "converting-to-and-from-other-data-formats"]], "To NetworkX Graph": [[1041, "module-networkx.convert"]], "Dictionaries": [[1041, "dictionaries"]], "Lists": [[1041, "lists"]], "Numpy": [[1041, "module-networkx.convert_matrix"]], "Scipy": [[1041, "scipy"]], "Pandas": [[1041, "pandas"]], "Matplotlib": [[1042, 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Applying classic graph operations, such as:": [[1426, "applying-classic-graph-operations-such-as"]], "2. Using a call to one of the classic small graphs, e.g.,": [[1426, "using-a-call-to-one-of-the-classic-small-graphs-e-g"]], "3. Using a (constructive) generator for a classic graph, e.g.,": [[1426, "using-a-constructive-generator-for-a-classic-graph-e-g"]], "4. Using a stochastic graph generator, e.g,": [[1426, "using-a-stochastic-graph-generator-e-g"]], "5. 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"module-networkx.algorithms.approximation.clustering_coefficient"]], "networkx.algorithms.approximation.connectivity": [[112, "module-networkx.algorithms.approximation.connectivity"]], "networkx.algorithms.approximation.distance_measures": [[112, "module-networkx.algorithms.approximation.distance_measures"]], "networkx.algorithms.approximation.dominating_set": [[112, "module-networkx.algorithms.approximation.dominating_set"]], "networkx.algorithms.approximation.kcomponents": [[112, "module-networkx.algorithms.approximation.kcomponents"]], "networkx.algorithms.approximation.matching": [[112, "module-networkx.algorithms.approximation.matching"]], "networkx.algorithms.approximation.maxcut": [[112, "module-networkx.algorithms.approximation.maxcut"]], "networkx.algorithms.approximation.ramsey": [[112, "module-networkx.algorithms.approximation.ramsey"]], "networkx.algorithms.approximation.steinertree": [[112, "module-networkx.algorithms.approximation.steinertree"]], "networkx.algorithms.approximation.traveling_salesman": [[112, "module-networkx.algorithms.approximation.traveling_salesman"]], "networkx.algorithms.approximation.treewidth": [[112, "module-networkx.algorithms.approximation.treewidth"]], "networkx.algorithms.approximation.vertex_cover": [[112, "module-networkx.algorithms.approximation.vertex_cover"]], "networkx.algorithms.assortativity": [[113, "module-networkx.algorithms.assortativity"]], "networkx.algorithms.asteroidal": [[114, "module-networkx.algorithms.asteroidal"]], "networkx.algorithms.bipartite": [[115, "module-networkx.algorithms.bipartite"]], "networkx.algorithms.bipartite.basic": [[115, "module-networkx.algorithms.bipartite.basic"]], "networkx.algorithms.bipartite.centrality": [[115, "module-networkx.algorithms.bipartite.centrality"]], "networkx.algorithms.bipartite.cluster": [[115, "module-networkx.algorithms.bipartite.cluster"]], "networkx.algorithms.bipartite.covering": [[115, "module-networkx.algorithms.bipartite.covering"]], "networkx.algorithms.bipartite.edgelist": [[115, "module-networkx.algorithms.bipartite.edgelist"]], "networkx.algorithms.bipartite.generators": [[115, "module-networkx.algorithms.bipartite.generators"]], "networkx.algorithms.bipartite.matching": [[115, "module-networkx.algorithms.bipartite.matching"]], "networkx.algorithms.bipartite.matrix": [[115, "module-networkx.algorithms.bipartite.matrix"]], "networkx.algorithms.bipartite.projection": [[115, "module-networkx.algorithms.bipartite.projection"]], "networkx.algorithms.bipartite.redundancy": [[115, "module-networkx.algorithms.bipartite.redundancy"]], "networkx.algorithms.bipartite.spectral": [[115, "module-networkx.algorithms.bipartite.spectral"]], "networkx.algorithms.boundary": [[116, "module-networkx.algorithms.boundary"]], "networkx.algorithms.bridges": [[117, "module-networkx.algorithms.bridges"]], "networkx.algorithms.centrality": [[118, "module-networkx.algorithms.centrality"]], "networkx.algorithms.chains": [[119, "module-networkx.algorithms.chains"]], "networkx.algorithms.chordal": [[120, "module-networkx.algorithms.chordal"]], "networkx.algorithms.clique": [[121, "module-networkx.algorithms.clique"]], "networkx.algorithms.cluster": [[122, "module-networkx.algorithms.cluster"]], "networkx.algorithms.coloring": [[123, "module-networkx.algorithms.coloring"]], "networkx.algorithms.communicability_alg": [[124, "module-networkx.algorithms.communicability_alg"]], "networkx.algorithms.community": [[125, "module-networkx.algorithms.community"]], "networkx.algorithms.community.asyn_fluid": [[125, "module-networkx.algorithms.community.asyn_fluid"]], "networkx.algorithms.community.centrality": [[125, "module-networkx.algorithms.community.centrality"]], "networkx.algorithms.community.community_utils": [[125, "module-networkx.algorithms.community.community_utils"]], "networkx.algorithms.community.kclique": [[125, "module-networkx.algorithms.community.kclique"]], "networkx.algorithms.community.kernighan_lin": [[125, "module-networkx.algorithms.community.kernighan_lin"]], "networkx.algorithms.community.label_propagation": [[125, "module-networkx.algorithms.community.label_propagation"]], "networkx.algorithms.community.louvain": [[125, "module-networkx.algorithms.community.louvain"]], "networkx.algorithms.community.lukes": [[125, "module-networkx.algorithms.community.lukes"]], "networkx.algorithms.community.modularity_max": [[125, "module-networkx.algorithms.community.modularity_max"]], "networkx.algorithms.community.quality": [[125, "module-networkx.algorithms.community.quality"]], "networkx.algorithms.components": [[126, "module-networkx.algorithms.components"]], "networkx.algorithms.connectivity": [[127, "module-networkx.algorithms.connectivity"]], "networkx.algorithms.connectivity.connectivity": [[127, "module-networkx.algorithms.connectivity.connectivity"]], "networkx.algorithms.connectivity.cuts": [[127, "module-networkx.algorithms.connectivity.cuts"]], "networkx.algorithms.connectivity.disjoint_paths": [[127, "module-networkx.algorithms.connectivity.disjoint_paths"]], "networkx.algorithms.connectivity.edge_augmentation": [[127, "module-networkx.algorithms.connectivity.edge_augmentation"]], "networkx.algorithms.connectivity.edge_kcomponents": [[127, "module-networkx.algorithms.connectivity.edge_kcomponents"]], "networkx.algorithms.connectivity.kcomponents": [[127, "module-networkx.algorithms.connectivity.kcomponents"]], "networkx.algorithms.connectivity.kcutsets": [[127, "module-networkx.algorithms.connectivity.kcutsets"]], "networkx.algorithms.connectivity.stoerwagner": [[127, "module-networkx.algorithms.connectivity.stoerwagner"]], "networkx.algorithms.connectivity.utils": [[127, "module-networkx.algorithms.connectivity.utils"]], "networkx.algorithms.core": [[128, "module-networkx.algorithms.core"]], "networkx.algorithms.covering": [[129, "module-networkx.algorithms.covering"]], "networkx.algorithms.cuts": [[130, "module-networkx.algorithms.cuts"]], "networkx.algorithms.cycles": [[131, "module-networkx.algorithms.cycles"]], "networkx.algorithms.d_separation": [[132, "module-networkx.algorithms.d_separation"]], "networkx.algorithms.dag": [[133, "module-networkx.algorithms.dag"]], "networkx.algorithms.distance_measures": [[134, "module-networkx.algorithms.distance_measures"]], "networkx.algorithms.distance_regular": [[135, "module-networkx.algorithms.distance_regular"]], "networkx.algorithms.dominance": [[136, "module-networkx.algorithms.dominance"]], "networkx.algorithms.dominating": [[137, "module-networkx.algorithms.dominating"]], "networkx.algorithms.efficiency_measures": [[138, "module-networkx.algorithms.efficiency_measures"]], "networkx.algorithms.euler": [[139, "module-networkx.algorithms.euler"]], "networkx.algorithms.flow": [[140, "module-networkx.algorithms.flow"]], "construct() (edgecomponentauxgraph class method)": [[141, "networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.construct"]], "k_edge_components() (edgecomponentauxgraph method)": [[142, "networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.k_edge_components"]], "k_edge_subgraphs() (edgecomponentauxgraph method)": [[143, "networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.k_edge_subgraphs"]], "analyze_symmetry() (ismags method)": [[144, "networkx.algorithms.isomorphism.ISMAGS.analyze_symmetry"]], "find_isomorphisms() (ismags method)": [[145, "networkx.algorithms.isomorphism.ISMAGS.find_isomorphisms"]], "is_isomorphic() (ismags method)": [[146, "networkx.algorithms.isomorphism.ISMAGS.is_isomorphic"]], "isomorphisms_iter() (ismags method)": [[147, "networkx.algorithms.isomorphism.ISMAGS.isomorphisms_iter"]], "largest_common_subgraph() (ismags method)": [[148, "networkx.algorithms.isomorphism.ISMAGS.largest_common_subgraph"]], "subgraph_is_isomorphic() (ismags method)": [[149, "networkx.algorithms.isomorphism.ISMAGS.subgraph_is_isomorphic"]], "subgraph_isomorphisms_iter() (ismags method)": [[150, "networkx.algorithms.isomorphism.ISMAGS.subgraph_isomorphisms_iter"]], "add_edge() (planarembedding method)": [[151, "networkx.algorithms.planarity.PlanarEmbedding.add_edge"]], "add_edges_from() (planarembedding method)": [[152, "networkx.algorithms.planarity.PlanarEmbedding.add_edges_from"]], "add_half_edge_ccw() (planarembedding method)": [[153, "networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_ccw"]], "add_half_edge_cw() (planarembedding method)": [[154, "networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_cw"]], "add_half_edge_first() (planarembedding method)": [[155, "networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_first"]], "add_node() (planarembedding method)": [[156, "networkx.algorithms.planarity.PlanarEmbedding.add_node"]], "add_nodes_from() (planarembedding method)": [[157, "networkx.algorithms.planarity.PlanarEmbedding.add_nodes_from"]], "add_weighted_edges_from() (planarembedding method)": [[158, "networkx.algorithms.planarity.PlanarEmbedding.add_weighted_edges_from"]], "adj (planarembedding property)": [[159, "networkx.algorithms.planarity.PlanarEmbedding.adj"]], "adjacency() (planarembedding method)": [[160, "networkx.algorithms.planarity.PlanarEmbedding.adjacency"]], "check_structure() (planarembedding method)": [[161, "networkx.algorithms.planarity.PlanarEmbedding.check_structure"]], "clear() (planarembedding method)": [[162, "networkx.algorithms.planarity.PlanarEmbedding.clear"]], "clear_edges() (planarembedding method)": [[163, "networkx.algorithms.planarity.PlanarEmbedding.clear_edges"]], "connect_components() (planarembedding method)": [[164, "networkx.algorithms.planarity.PlanarEmbedding.connect_components"]], "copy() (planarembedding method)": [[165, "networkx.algorithms.planarity.PlanarEmbedding.copy"]], "degree (planarembedding property)": [[166, "networkx.algorithms.planarity.PlanarEmbedding.degree"]], "edge_subgraph() (planarembedding method)": [[167, "networkx.algorithms.planarity.PlanarEmbedding.edge_subgraph"]], "edges (planarembedding property)": [[168, "networkx.algorithms.planarity.PlanarEmbedding.edges"]], "get_data() (planarembedding method)": [[169, "networkx.algorithms.planarity.PlanarEmbedding.get_data"]], "get_edge_data() (planarembedding method)": [[170, "networkx.algorithms.planarity.PlanarEmbedding.get_edge_data"]], "has_edge() (planarembedding method)": [[171, "networkx.algorithms.planarity.PlanarEmbedding.has_edge"]], "has_node() (planarembedding method)": [[172, "networkx.algorithms.planarity.PlanarEmbedding.has_node"]], "has_predecessor() (planarembedding method)": [[173, "networkx.algorithms.planarity.PlanarEmbedding.has_predecessor"]], "has_successor() (planarembedding method)": [[174, "networkx.algorithms.planarity.PlanarEmbedding.has_successor"]], "in_degree (planarembedding property)": [[175, "networkx.algorithms.planarity.PlanarEmbedding.in_degree"]], "in_edges (planarembedding property)": [[176, "networkx.algorithms.planarity.PlanarEmbedding.in_edges"]], "is_directed() (planarembedding method)": [[177, "networkx.algorithms.planarity.PlanarEmbedding.is_directed"]], "is_multigraph() (planarembedding method)": [[178, "networkx.algorithms.planarity.PlanarEmbedding.is_multigraph"]], "name (planarembedding property)": [[179, "networkx.algorithms.planarity.PlanarEmbedding.name"]], "nbunch_iter() (planarembedding method)": [[180, "networkx.algorithms.planarity.PlanarEmbedding.nbunch_iter"]], "neighbors() (planarembedding method)": [[181, "networkx.algorithms.planarity.PlanarEmbedding.neighbors"]], "neighbors_cw_order() (planarembedding method)": [[182, "networkx.algorithms.planarity.PlanarEmbedding.neighbors_cw_order"]], "next_face_half_edge() (planarembedding method)": [[183, "networkx.algorithms.planarity.PlanarEmbedding.next_face_half_edge"]], "nodes (planarembedding property)": [[184, "networkx.algorithms.planarity.PlanarEmbedding.nodes"]], "number_of_edges() (planarembedding method)": [[185, "networkx.algorithms.planarity.PlanarEmbedding.number_of_edges"]], "number_of_nodes() (planarembedding method)": [[186, "networkx.algorithms.planarity.PlanarEmbedding.number_of_nodes"]], "order() (planarembedding method)": [[187, "networkx.algorithms.planarity.PlanarEmbedding.order"]], "out_degree (planarembedding property)": [[188, "networkx.algorithms.planarity.PlanarEmbedding.out_degree"]], "out_edges (planarembedding property)": [[189, "networkx.algorithms.planarity.PlanarEmbedding.out_edges"]], "pred (planarembedding property)": [[190, "networkx.algorithms.planarity.PlanarEmbedding.pred"]], "predecessors() (planarembedding method)": [[191, "networkx.algorithms.planarity.PlanarEmbedding.predecessors"]], "remove_edge() (planarembedding method)": [[192, "networkx.algorithms.planarity.PlanarEmbedding.remove_edge"]], "remove_edges_from() (planarembedding method)": [[193, "networkx.algorithms.planarity.PlanarEmbedding.remove_edges_from"]], "remove_node() (planarembedding method)": [[194, "networkx.algorithms.planarity.PlanarEmbedding.remove_node"]], "remove_nodes_from() (planarembedding method)": [[195, "networkx.algorithms.planarity.PlanarEmbedding.remove_nodes_from"]], "reverse() (planarembedding method)": [[196, "networkx.algorithms.planarity.PlanarEmbedding.reverse"]], "set_data() (planarembedding method)": [[197, "networkx.algorithms.planarity.PlanarEmbedding.set_data"]], "size() (planarembedding method)": [[198, "networkx.algorithms.planarity.PlanarEmbedding.size"]], "subgraph() (planarembedding method)": [[199, "networkx.algorithms.planarity.PlanarEmbedding.subgraph"]], "succ (planarembedding property)": [[200, "networkx.algorithms.planarity.PlanarEmbedding.succ"]], "successors() (planarembedding method)": [[201, "networkx.algorithms.planarity.PlanarEmbedding.successors"]], "to_directed() (planarembedding method)": [[202, "networkx.algorithms.planarity.PlanarEmbedding.to_directed"]], "to_directed_class() (planarembedding method)": [[203, "networkx.algorithms.planarity.PlanarEmbedding.to_directed_class"]], "to_undirected() (planarembedding method)": [[204, "networkx.algorithms.planarity.PlanarEmbedding.to_undirected"]], "to_undirected_class() (planarembedding method)": [[205, "networkx.algorithms.planarity.PlanarEmbedding.to_undirected_class"]], "traverse_face() (planarembedding method)": [[206, "networkx.algorithms.planarity.PlanarEmbedding.traverse_face"]], "update() (planarembedding method)": [[207, "networkx.algorithms.planarity.PlanarEmbedding.update"]], "find_optimum() (edmonds method)": [[208, "networkx.algorithms.tree.branchings.Edmonds.find_optimum"]], "clique_removal() (in module networkx.algorithms.approximation.clique)": [[209, "networkx.algorithms.approximation.clique.clique_removal"]], "large_clique_size() (in module networkx.algorithms.approximation.clique)": [[210, "networkx.algorithms.approximation.clique.large_clique_size"]], "max_clique() (in module networkx.algorithms.approximation.clique)": [[211, "networkx.algorithms.approximation.clique.max_clique"]], "maximum_independent_set() (in module networkx.algorithms.approximation.clique)": [[212, "networkx.algorithms.approximation.clique.maximum_independent_set"]], "average_clustering() (in module networkx.algorithms.approximation.clustering_coefficient)": [[213, "networkx.algorithms.approximation.clustering_coefficient.average_clustering"]], "all_pairs_node_connectivity() (in module networkx.algorithms.approximation.connectivity)": [[214, "networkx.algorithms.approximation.connectivity.all_pairs_node_connectivity"]], "local_node_connectivity() (in module networkx.algorithms.approximation.connectivity)": [[215, "networkx.algorithms.approximation.connectivity.local_node_connectivity"]], "node_connectivity() (in module networkx.algorithms.approximation.connectivity)": [[216, "networkx.algorithms.approximation.connectivity.node_connectivity"]], "diameter() (in module networkx.algorithms.approximation.distance_measures)": [[217, "networkx.algorithms.approximation.distance_measures.diameter"]], "min_edge_dominating_set() (in module networkx.algorithms.approximation.dominating_set)": [[218, "networkx.algorithms.approximation.dominating_set.min_edge_dominating_set"]], "min_weighted_dominating_set() (in module networkx.algorithms.approximation.dominating_set)": [[219, "networkx.algorithms.approximation.dominating_set.min_weighted_dominating_set"]], "k_components() (in module networkx.algorithms.approximation.kcomponents)": [[220, "networkx.algorithms.approximation.kcomponents.k_components"]], "min_maximal_matching() (in module networkx.algorithms.approximation.matching)": [[221, "networkx.algorithms.approximation.matching.min_maximal_matching"]], "one_exchange() (in module networkx.algorithms.approximation.maxcut)": [[222, "networkx.algorithms.approximation.maxcut.one_exchange"]], "randomized_partitioning() (in module networkx.algorithms.approximation.maxcut)": [[223, "networkx.algorithms.approximation.maxcut.randomized_partitioning"]], "ramsey_r2() (in module networkx.algorithms.approximation.ramsey)": [[224, "networkx.algorithms.approximation.ramsey.ramsey_R2"]], "metric_closure() (in module networkx.algorithms.approximation.steinertree)": [[225, "networkx.algorithms.approximation.steinertree.metric_closure"]], "steiner_tree() (in module networkx.algorithms.approximation.steinertree)": [[226, "networkx.algorithms.approximation.steinertree.steiner_tree"]], "asadpour_atsp() (in module networkx.algorithms.approximation.traveling_salesman)": [[227, "networkx.algorithms.approximation.traveling_salesman.asadpour_atsp"]], "christofides() (in module networkx.algorithms.approximation.traveling_salesman)": [[228, "networkx.algorithms.approximation.traveling_salesman.christofides"]], "greedy_tsp() (in module networkx.algorithms.approximation.traveling_salesman)": [[229, "networkx.algorithms.approximation.traveling_salesman.greedy_tsp"]], "simulated_annealing_tsp() (in module networkx.algorithms.approximation.traveling_salesman)": [[230, "networkx.algorithms.approximation.traveling_salesman.simulated_annealing_tsp"]], "threshold_accepting_tsp() (in module networkx.algorithms.approximation.traveling_salesman)": [[231, "networkx.algorithms.approximation.traveling_salesman.threshold_accepting_tsp"]], "traveling_salesman_problem() (in module networkx.algorithms.approximation.traveling_salesman)": [[232, "networkx.algorithms.approximation.traveling_salesman.traveling_salesman_problem"]], "treewidth_min_degree() (in module networkx.algorithms.approximation.treewidth)": [[233, "networkx.algorithms.approximation.treewidth.treewidth_min_degree"]], "treewidth_min_fill_in() (in module networkx.algorithms.approximation.treewidth)": [[234, "networkx.algorithms.approximation.treewidth.treewidth_min_fill_in"]], "min_weighted_vertex_cover() (in module networkx.algorithms.approximation.vertex_cover)": [[235, "networkx.algorithms.approximation.vertex_cover.min_weighted_vertex_cover"]], "attribute_assortativity_coefficient() (in module networkx.algorithms.assortativity)": [[236, "networkx.algorithms.assortativity.attribute_assortativity_coefficient"]], "attribute_mixing_dict() (in module networkx.algorithms.assortativity)": [[237, "networkx.algorithms.assortativity.attribute_mixing_dict"]], "attribute_mixing_matrix() (in module networkx.algorithms.assortativity)": [[238, "networkx.algorithms.assortativity.attribute_mixing_matrix"]], "average_degree_connectivity() (in module networkx.algorithms.assortativity)": [[239, "networkx.algorithms.assortativity.average_degree_connectivity"]], "average_neighbor_degree() (in module networkx.algorithms.assortativity)": [[240, "networkx.algorithms.assortativity.average_neighbor_degree"]], "degree_assortativity_coefficient() (in module networkx.algorithms.assortativity)": [[241, "networkx.algorithms.assortativity.degree_assortativity_coefficient"]], "degree_mixing_dict() (in module networkx.algorithms.assortativity)": [[242, "networkx.algorithms.assortativity.degree_mixing_dict"]], "degree_mixing_matrix() (in module networkx.algorithms.assortativity)": [[243, "networkx.algorithms.assortativity.degree_mixing_matrix"]], "degree_pearson_correlation_coefficient() (in module networkx.algorithms.assortativity)": [[244, "networkx.algorithms.assortativity.degree_pearson_correlation_coefficient"]], "mixing_dict() (in module networkx.algorithms.assortativity)": [[245, "networkx.algorithms.assortativity.mixing_dict"]], "node_attribute_xy() (in module networkx.algorithms.assortativity)": [[246, "networkx.algorithms.assortativity.node_attribute_xy"]], "node_degree_xy() (in module networkx.algorithms.assortativity)": [[247, "networkx.algorithms.assortativity.node_degree_xy"]], "numeric_assortativity_coefficient() (in module networkx.algorithms.assortativity)": [[248, "networkx.algorithms.assortativity.numeric_assortativity_coefficient"]], "find_asteroidal_triple() (in module networkx.algorithms.asteroidal)": [[249, "networkx.algorithms.asteroidal.find_asteroidal_triple"]], "is_at_free() (in module networkx.algorithms.asteroidal)": [[250, "networkx.algorithms.asteroidal.is_at_free"]], "color() (in module networkx.algorithms.bipartite.basic)": [[251, "networkx.algorithms.bipartite.basic.color"]], "degrees() (in module networkx.algorithms.bipartite.basic)": [[252, "networkx.algorithms.bipartite.basic.degrees"]], "density() (in module networkx.algorithms.bipartite.basic)": [[253, "networkx.algorithms.bipartite.basic.density"]], "is_bipartite() (in module networkx.algorithms.bipartite.basic)": [[254, "networkx.algorithms.bipartite.basic.is_bipartite"]], "is_bipartite_node_set() (in module networkx.algorithms.bipartite.basic)": [[255, "networkx.algorithms.bipartite.basic.is_bipartite_node_set"]], "sets() (in module networkx.algorithms.bipartite.basic)": [[256, "networkx.algorithms.bipartite.basic.sets"]], "betweenness_centrality() (in module networkx.algorithms.bipartite.centrality)": [[257, "networkx.algorithms.bipartite.centrality.betweenness_centrality"]], "closeness_centrality() (in module networkx.algorithms.bipartite.centrality)": [[258, "networkx.algorithms.bipartite.centrality.closeness_centrality"]], "degree_centrality() (in module networkx.algorithms.bipartite.centrality)": [[259, "networkx.algorithms.bipartite.centrality.degree_centrality"]], "average_clustering() (in module networkx.algorithms.bipartite.cluster)": [[260, "networkx.algorithms.bipartite.cluster.average_clustering"]], "clustering() (in module networkx.algorithms.bipartite.cluster)": [[261, "networkx.algorithms.bipartite.cluster.clustering"]], "latapy_clustering() (in module networkx.algorithms.bipartite.cluster)": [[262, "networkx.algorithms.bipartite.cluster.latapy_clustering"]], "robins_alexander_clustering() (in module networkx.algorithms.bipartite.cluster)": [[263, "networkx.algorithms.bipartite.cluster.robins_alexander_clustering"]], "min_edge_cover() (in module networkx.algorithms.bipartite.covering)": [[264, "networkx.algorithms.bipartite.covering.min_edge_cover"]], "generate_edgelist() (in module networkx.algorithms.bipartite.edgelist)": [[265, "networkx.algorithms.bipartite.edgelist.generate_edgelist"]], "parse_edgelist() (in module networkx.algorithms.bipartite.edgelist)": [[266, "networkx.algorithms.bipartite.edgelist.parse_edgelist"]], "read_edgelist() (in module networkx.algorithms.bipartite.edgelist)": [[267, "networkx.algorithms.bipartite.edgelist.read_edgelist"]], "write_edgelist() (in module networkx.algorithms.bipartite.edgelist)": [[268, "networkx.algorithms.bipartite.edgelist.write_edgelist"]], "alternating_havel_hakimi_graph() (in module networkx.algorithms.bipartite.generators)": [[269, "networkx.algorithms.bipartite.generators.alternating_havel_hakimi_graph"]], "complete_bipartite_graph() (in module networkx.algorithms.bipartite.generators)": [[270, "networkx.algorithms.bipartite.generators.complete_bipartite_graph"]], "configuration_model() (in module networkx.algorithms.bipartite.generators)": [[271, "networkx.algorithms.bipartite.generators.configuration_model"]], "gnmk_random_graph() (in module networkx.algorithms.bipartite.generators)": [[272, "networkx.algorithms.bipartite.generators.gnmk_random_graph"]], "havel_hakimi_graph() (in module networkx.algorithms.bipartite.generators)": [[273, "networkx.algorithms.bipartite.generators.havel_hakimi_graph"]], "preferential_attachment_graph() (in module networkx.algorithms.bipartite.generators)": [[274, "networkx.algorithms.bipartite.generators.preferential_attachment_graph"]], "random_graph() (in module networkx.algorithms.bipartite.generators)": [[275, "networkx.algorithms.bipartite.generators.random_graph"]], "reverse_havel_hakimi_graph() (in module networkx.algorithms.bipartite.generators)": [[276, "networkx.algorithms.bipartite.generators.reverse_havel_hakimi_graph"]], "eppstein_matching() (in module networkx.algorithms.bipartite.matching)": [[277, "networkx.algorithms.bipartite.matching.eppstein_matching"]], "hopcroft_karp_matching() (in module networkx.algorithms.bipartite.matching)": [[278, "networkx.algorithms.bipartite.matching.hopcroft_karp_matching"]], "maximum_matching() (in module networkx.algorithms.bipartite.matching)": [[279, "networkx.algorithms.bipartite.matching.maximum_matching"]], "minimum_weight_full_matching() (in module networkx.algorithms.bipartite.matching)": [[280, "networkx.algorithms.bipartite.matching.minimum_weight_full_matching"]], "to_vertex_cover() (in module networkx.algorithms.bipartite.matching)": [[281, "networkx.algorithms.bipartite.matching.to_vertex_cover"]], "biadjacency_matrix() (in module networkx.algorithms.bipartite.matrix)": [[282, "networkx.algorithms.bipartite.matrix.biadjacency_matrix"]], "from_biadjacency_matrix() (in module networkx.algorithms.bipartite.matrix)": [[283, "networkx.algorithms.bipartite.matrix.from_biadjacency_matrix"]], "collaboration_weighted_projected_graph() (in module networkx.algorithms.bipartite.projection)": [[284, "networkx.algorithms.bipartite.projection.collaboration_weighted_projected_graph"]], "generic_weighted_projected_graph() (in module networkx.algorithms.bipartite.projection)": [[285, "networkx.algorithms.bipartite.projection.generic_weighted_projected_graph"]], "overlap_weighted_projected_graph() (in module networkx.algorithms.bipartite.projection)": [[286, "networkx.algorithms.bipartite.projection.overlap_weighted_projected_graph"]], "projected_graph() (in module networkx.algorithms.bipartite.projection)": [[287, "networkx.algorithms.bipartite.projection.projected_graph"]], "weighted_projected_graph() (in module networkx.algorithms.bipartite.projection)": [[288, "networkx.algorithms.bipartite.projection.weighted_projected_graph"]], "node_redundancy() (in module networkx.algorithms.bipartite.redundancy)": [[289, "networkx.algorithms.bipartite.redundancy.node_redundancy"]], "spectral_bipartivity() (in module networkx.algorithms.bipartite.spectral)": [[290, "networkx.algorithms.bipartite.spectral.spectral_bipartivity"]], "edge_boundary() (in module networkx.algorithms.boundary)": [[291, "networkx.algorithms.boundary.edge_boundary"]], "node_boundary() (in module networkx.algorithms.boundary)": [[292, "networkx.algorithms.boundary.node_boundary"]], "bridges() (in module networkx.algorithms.bridges)": [[293, "networkx.algorithms.bridges.bridges"]], "has_bridges() (in module networkx.algorithms.bridges)": [[294, "networkx.algorithms.bridges.has_bridges"]], "local_bridges() (in module networkx.algorithms.bridges)": [[295, "networkx.algorithms.bridges.local_bridges"]], "approximate_current_flow_betweenness_centrality() (in module networkx.algorithms.centrality)": [[296, "networkx.algorithms.centrality.approximate_current_flow_betweenness_centrality"]], "betweenness_centrality() (in module networkx.algorithms.centrality)": [[297, "networkx.algorithms.centrality.betweenness_centrality"]], "betweenness_centrality_subset() (in module networkx.algorithms.centrality)": [[298, "networkx.algorithms.centrality.betweenness_centrality_subset"]], "closeness_centrality() (in module networkx.algorithms.centrality)": [[299, "networkx.algorithms.centrality.closeness_centrality"]], "communicability_betweenness_centrality() (in module networkx.algorithms.centrality)": [[300, "networkx.algorithms.centrality.communicability_betweenness_centrality"]], "current_flow_betweenness_centrality() (in module networkx.algorithms.centrality)": [[301, "networkx.algorithms.centrality.current_flow_betweenness_centrality"]], "current_flow_betweenness_centrality_subset() (in module networkx.algorithms.centrality)": [[302, "networkx.algorithms.centrality.current_flow_betweenness_centrality_subset"]], "current_flow_closeness_centrality() (in module networkx.algorithms.centrality)": [[303, "networkx.algorithms.centrality.current_flow_closeness_centrality"]], "degree_centrality() (in module networkx.algorithms.centrality)": [[304, "networkx.algorithms.centrality.degree_centrality"]], "dispersion() (in module networkx.algorithms.centrality)": [[305, "networkx.algorithms.centrality.dispersion"]], "edge_betweenness_centrality() (in module networkx.algorithms.centrality)": [[306, "networkx.algorithms.centrality.edge_betweenness_centrality"]], "edge_betweenness_centrality_subset() (in module networkx.algorithms.centrality)": [[307, "networkx.algorithms.centrality.edge_betweenness_centrality_subset"]], "edge_current_flow_betweenness_centrality() (in module networkx.algorithms.centrality)": [[308, "networkx.algorithms.centrality.edge_current_flow_betweenness_centrality"]], "edge_current_flow_betweenness_centrality_subset() (in module networkx.algorithms.centrality)": [[309, "networkx.algorithms.centrality.edge_current_flow_betweenness_centrality_subset"]], "edge_load_centrality() (in module networkx.algorithms.centrality)": [[310, "networkx.algorithms.centrality.edge_load_centrality"]], "eigenvector_centrality() (in module networkx.algorithms.centrality)": [[311, "networkx.algorithms.centrality.eigenvector_centrality"]], "eigenvector_centrality_numpy() (in module networkx.algorithms.centrality)": [[312, "networkx.algorithms.centrality.eigenvector_centrality_numpy"]], "estrada_index() (in module networkx.algorithms.centrality)": [[313, "networkx.algorithms.centrality.estrada_index"]], "global_reaching_centrality() (in module networkx.algorithms.centrality)": [[314, "networkx.algorithms.centrality.global_reaching_centrality"]], "group_betweenness_centrality() (in module networkx.algorithms.centrality)": [[315, "networkx.algorithms.centrality.group_betweenness_centrality"]], "group_closeness_centrality() (in module networkx.algorithms.centrality)": [[316, "networkx.algorithms.centrality.group_closeness_centrality"]], "group_degree_centrality() (in module networkx.algorithms.centrality)": [[317, "networkx.algorithms.centrality.group_degree_centrality"]], "group_in_degree_centrality() (in module networkx.algorithms.centrality)": [[318, "networkx.algorithms.centrality.group_in_degree_centrality"]], "group_out_degree_centrality() (in module networkx.algorithms.centrality)": [[319, "networkx.algorithms.centrality.group_out_degree_centrality"]], "harmonic_centrality() (in module networkx.algorithms.centrality)": [[320, "networkx.algorithms.centrality.harmonic_centrality"]], "in_degree_centrality() (in module networkx.algorithms.centrality)": [[321, "networkx.algorithms.centrality.in_degree_centrality"]], "incremental_closeness_centrality() (in module networkx.algorithms.centrality)": [[322, "networkx.algorithms.centrality.incremental_closeness_centrality"]], "information_centrality() (in module networkx.algorithms.centrality)": [[323, "networkx.algorithms.centrality.information_centrality"]], "katz_centrality() (in module networkx.algorithms.centrality)": [[324, "networkx.algorithms.centrality.katz_centrality"]], "katz_centrality_numpy() (in module networkx.algorithms.centrality)": [[325, "networkx.algorithms.centrality.katz_centrality_numpy"]], "load_centrality() (in module networkx.algorithms.centrality)": [[326, "networkx.algorithms.centrality.load_centrality"]], "local_reaching_centrality() (in module networkx.algorithms.centrality)": [[327, "networkx.algorithms.centrality.local_reaching_centrality"]], "out_degree_centrality() (in module networkx.algorithms.centrality)": [[328, "networkx.algorithms.centrality.out_degree_centrality"]], "percolation_centrality() (in module networkx.algorithms.centrality)": [[329, "networkx.algorithms.centrality.percolation_centrality"]], "prominent_group() (in module networkx.algorithms.centrality)": [[330, "networkx.algorithms.centrality.prominent_group"]], "second_order_centrality() (in module networkx.algorithms.centrality)": [[331, "networkx.algorithms.centrality.second_order_centrality"]], "subgraph_centrality() (in module networkx.algorithms.centrality)": [[332, "networkx.algorithms.centrality.subgraph_centrality"]], "subgraph_centrality_exp() (in module networkx.algorithms.centrality)": [[333, "networkx.algorithms.centrality.subgraph_centrality_exp"]], "trophic_differences() (in module networkx.algorithms.centrality)": [[334, "networkx.algorithms.centrality.trophic_differences"]], "trophic_incoherence_parameter() (in module networkx.algorithms.centrality)": [[335, "networkx.algorithms.centrality.trophic_incoherence_parameter"]], "trophic_levels() (in module networkx.algorithms.centrality)": [[336, "networkx.algorithms.centrality.trophic_levels"]], "voterank() (in module networkx.algorithms.centrality)": [[337, "networkx.algorithms.centrality.voterank"]], "chain_decomposition() (in module networkx.algorithms.chains)": [[338, "networkx.algorithms.chains.chain_decomposition"]], "chordal_graph_cliques() (in module networkx.algorithms.chordal)": [[339, "networkx.algorithms.chordal.chordal_graph_cliques"]], "chordal_graph_treewidth() (in module networkx.algorithms.chordal)": [[340, "networkx.algorithms.chordal.chordal_graph_treewidth"]], "complete_to_chordal_graph() (in module networkx.algorithms.chordal)": [[341, "networkx.algorithms.chordal.complete_to_chordal_graph"]], "find_induced_nodes() (in module networkx.algorithms.chordal)": [[342, "networkx.algorithms.chordal.find_induced_nodes"]], "is_chordal() (in module networkx.algorithms.chordal)": [[343, "networkx.algorithms.chordal.is_chordal"]], "cliques_containing_node() (in module networkx.algorithms.clique)": [[344, "networkx.algorithms.clique.cliques_containing_node"]], "enumerate_all_cliques() (in module networkx.algorithms.clique)": [[345, "networkx.algorithms.clique.enumerate_all_cliques"]], "find_cliques() (in module networkx.algorithms.clique)": [[346, "networkx.algorithms.clique.find_cliques"]], "find_cliques_recursive() (in module networkx.algorithms.clique)": [[347, "networkx.algorithms.clique.find_cliques_recursive"]], "graph_clique_number() (in module networkx.algorithms.clique)": [[348, "networkx.algorithms.clique.graph_clique_number"]], "graph_number_of_cliques() (in module networkx.algorithms.clique)": [[349, "networkx.algorithms.clique.graph_number_of_cliques"]], "make_clique_bipartite() (in module networkx.algorithms.clique)": [[350, "networkx.algorithms.clique.make_clique_bipartite"]], "make_max_clique_graph() (in module networkx.algorithms.clique)": [[351, "networkx.algorithms.clique.make_max_clique_graph"]], "max_weight_clique() (in module networkx.algorithms.clique)": [[352, "networkx.algorithms.clique.max_weight_clique"]], "node_clique_number() (in module networkx.algorithms.clique)": [[353, "networkx.algorithms.clique.node_clique_number"]], "number_of_cliques() (in module networkx.algorithms.clique)": [[354, "networkx.algorithms.clique.number_of_cliques"]], "average_clustering() (in module networkx.algorithms.cluster)": [[355, "networkx.algorithms.cluster.average_clustering"]], "clustering() (in module networkx.algorithms.cluster)": [[356, "networkx.algorithms.cluster.clustering"]], "generalized_degree() (in module networkx.algorithms.cluster)": [[357, "networkx.algorithms.cluster.generalized_degree"]], "square_clustering() (in module networkx.algorithms.cluster)": [[358, "networkx.algorithms.cluster.square_clustering"]], "transitivity() (in module networkx.algorithms.cluster)": [[359, "networkx.algorithms.cluster.transitivity"]], "triangles() (in module networkx.algorithms.cluster)": [[360, "networkx.algorithms.cluster.triangles"]], "equitable_color() (in module networkx.algorithms.coloring)": [[361, "networkx.algorithms.coloring.equitable_color"]], "greedy_color() (in module networkx.algorithms.coloring)": [[362, "networkx.algorithms.coloring.greedy_color"]], "strategy_connected_sequential() (in module networkx.algorithms.coloring)": [[363, "networkx.algorithms.coloring.strategy_connected_sequential"]], "strategy_connected_sequential_bfs() (in module networkx.algorithms.coloring)": [[364, "networkx.algorithms.coloring.strategy_connected_sequential_bfs"]], "strategy_connected_sequential_dfs() (in module networkx.algorithms.coloring)": [[365, "networkx.algorithms.coloring.strategy_connected_sequential_dfs"]], "strategy_independent_set() (in module networkx.algorithms.coloring)": [[366, "networkx.algorithms.coloring.strategy_independent_set"]], "strategy_largest_first() (in module networkx.algorithms.coloring)": [[367, "networkx.algorithms.coloring.strategy_largest_first"]], "strategy_random_sequential() (in module networkx.algorithms.coloring)": [[368, "networkx.algorithms.coloring.strategy_random_sequential"]], "strategy_saturation_largest_first() (in module networkx.algorithms.coloring)": [[369, "networkx.algorithms.coloring.strategy_saturation_largest_first"]], "strategy_smallest_last() (in module networkx.algorithms.coloring)": [[370, "networkx.algorithms.coloring.strategy_smallest_last"]], "communicability() (in module networkx.algorithms.communicability_alg)": [[371, "networkx.algorithms.communicability_alg.communicability"]], "communicability_exp() (in module networkx.algorithms.communicability_alg)": [[372, "networkx.algorithms.communicability_alg.communicability_exp"]], "asyn_fluidc() (in module networkx.algorithms.community.asyn_fluid)": [[373, "networkx.algorithms.community.asyn_fluid.asyn_fluidc"]], "girvan_newman() (in module networkx.algorithms.community.centrality)": [[374, "networkx.algorithms.community.centrality.girvan_newman"]], "is_partition() (in module networkx.algorithms.community.community_utils)": [[375, "networkx.algorithms.community.community_utils.is_partition"]], "k_clique_communities() (in module networkx.algorithms.community.kclique)": [[376, "networkx.algorithms.community.kclique.k_clique_communities"]], "kernighan_lin_bisection() (in module networkx.algorithms.community.kernighan_lin)": [[377, "networkx.algorithms.community.kernighan_lin.kernighan_lin_bisection"]], "asyn_lpa_communities() (in module networkx.algorithms.community.label_propagation)": [[378, "networkx.algorithms.community.label_propagation.asyn_lpa_communities"]], "label_propagation_communities() (in module networkx.algorithms.community.label_propagation)": [[379, "networkx.algorithms.community.label_propagation.label_propagation_communities"]], "louvain_communities() (in module networkx.algorithms.community.louvain)": [[380, "networkx.algorithms.community.louvain.louvain_communities"]], "louvain_partitions() (in module networkx.algorithms.community.louvain)": [[381, "networkx.algorithms.community.louvain.louvain_partitions"]], "lukes_partitioning() (in module networkx.algorithms.community.lukes)": [[382, "networkx.algorithms.community.lukes.lukes_partitioning"]], "greedy_modularity_communities() (in module networkx.algorithms.community.modularity_max)": [[383, "networkx.algorithms.community.modularity_max.greedy_modularity_communities"]], "naive_greedy_modularity_communities() (in module networkx.algorithms.community.modularity_max)": [[384, "networkx.algorithms.community.modularity_max.naive_greedy_modularity_communities"]], "modularity() (in module networkx.algorithms.community.quality)": [[385, "networkx.algorithms.community.quality.modularity"]], "partition_quality() (in module networkx.algorithms.community.quality)": [[386, "networkx.algorithms.community.quality.partition_quality"]], "articulation_points() (in module networkx.algorithms.components)": [[387, "networkx.algorithms.components.articulation_points"]], "attracting_components() (in module networkx.algorithms.components)": [[388, "networkx.algorithms.components.attracting_components"]], "biconnected_component_edges() (in module networkx.algorithms.components)": [[389, "networkx.algorithms.components.biconnected_component_edges"]], "biconnected_components() (in module networkx.algorithms.components)": [[390, "networkx.algorithms.components.biconnected_components"]], "condensation() (in module networkx.algorithms.components)": [[391, "networkx.algorithms.components.condensation"]], "connected_components() (in module networkx.algorithms.components)": [[392, "networkx.algorithms.components.connected_components"]], "is_attracting_component() (in module networkx.algorithms.components)": [[393, "networkx.algorithms.components.is_attracting_component"]], "is_biconnected() (in module networkx.algorithms.components)": [[394, "networkx.algorithms.components.is_biconnected"]], "is_connected() (in module networkx.algorithms.components)": [[395, "networkx.algorithms.components.is_connected"]], "is_semiconnected() (in module networkx.algorithms.components)": [[396, "networkx.algorithms.components.is_semiconnected"]], "is_strongly_connected() (in module networkx.algorithms.components)": [[397, "networkx.algorithms.components.is_strongly_connected"]], "is_weakly_connected() (in module networkx.algorithms.components)": [[398, "networkx.algorithms.components.is_weakly_connected"]], "kosaraju_strongly_connected_components() (in module networkx.algorithms.components)": [[399, "networkx.algorithms.components.kosaraju_strongly_connected_components"]], "node_connected_component() (in module networkx.algorithms.components)": [[400, "networkx.algorithms.components.node_connected_component"]], "number_attracting_components() (in module networkx.algorithms.components)": [[401, "networkx.algorithms.components.number_attracting_components"]], "number_connected_components() (in module networkx.algorithms.components)": [[402, "networkx.algorithms.components.number_connected_components"]], "number_strongly_connected_components() (in module networkx.algorithms.components)": [[403, "networkx.algorithms.components.number_strongly_connected_components"]], "number_weakly_connected_components() (in module networkx.algorithms.components)": [[404, "networkx.algorithms.components.number_weakly_connected_components"]], "strongly_connected_components() (in module networkx.algorithms.components)": [[405, "networkx.algorithms.components.strongly_connected_components"]], "strongly_connected_components_recursive() (in module networkx.algorithms.components)": [[406, "networkx.algorithms.components.strongly_connected_components_recursive"]], "weakly_connected_components() (in module networkx.algorithms.components)": [[407, "networkx.algorithms.components.weakly_connected_components"]], "all_pairs_node_connectivity() (in module networkx.algorithms.connectivity.connectivity)": [[408, "networkx.algorithms.connectivity.connectivity.all_pairs_node_connectivity"]], "average_node_connectivity() (in module networkx.algorithms.connectivity.connectivity)": [[409, "networkx.algorithms.connectivity.connectivity.average_node_connectivity"]], "edge_connectivity() (in module networkx.algorithms.connectivity.connectivity)": [[410, "networkx.algorithms.connectivity.connectivity.edge_connectivity"]], "local_edge_connectivity() (in module networkx.algorithms.connectivity.connectivity)": [[411, "networkx.algorithms.connectivity.connectivity.local_edge_connectivity"]], "local_node_connectivity() (in module networkx.algorithms.connectivity.connectivity)": [[412, "networkx.algorithms.connectivity.connectivity.local_node_connectivity"]], "node_connectivity() (in module networkx.algorithms.connectivity.connectivity)": [[413, "networkx.algorithms.connectivity.connectivity.node_connectivity"]], "minimum_edge_cut() (in module networkx.algorithms.connectivity.cuts)": [[414, "networkx.algorithms.connectivity.cuts.minimum_edge_cut"]], "minimum_node_cut() (in module networkx.algorithms.connectivity.cuts)": [[415, "networkx.algorithms.connectivity.cuts.minimum_node_cut"]], "minimum_st_edge_cut() (in module networkx.algorithms.connectivity.cuts)": [[416, "networkx.algorithms.connectivity.cuts.minimum_st_edge_cut"]], "minimum_st_node_cut() (in module networkx.algorithms.connectivity.cuts)": [[417, "networkx.algorithms.connectivity.cuts.minimum_st_node_cut"]], "edge_disjoint_paths() (in module networkx.algorithms.connectivity.disjoint_paths)": [[418, "networkx.algorithms.connectivity.disjoint_paths.edge_disjoint_paths"]], "node_disjoint_paths() (in module networkx.algorithms.connectivity.disjoint_paths)": [[419, "networkx.algorithms.connectivity.disjoint_paths.node_disjoint_paths"]], "is_k_edge_connected() (in module networkx.algorithms.connectivity.edge_augmentation)": [[420, "networkx.algorithms.connectivity.edge_augmentation.is_k_edge_connected"]], "is_locally_k_edge_connected() (in module networkx.algorithms.connectivity.edge_augmentation)": [[421, "networkx.algorithms.connectivity.edge_augmentation.is_locally_k_edge_connected"]], "k_edge_augmentation() (in module networkx.algorithms.connectivity.edge_augmentation)": [[422, "networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation"]], "edgecomponentauxgraph (class in networkx.algorithms.connectivity.edge_kcomponents)": [[423, "networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph"]], "__init__() (edgecomponentauxgraph method)": [[423, "networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.__init__"]], "bridge_components() (in module networkx.algorithms.connectivity.edge_kcomponents)": [[424, "networkx.algorithms.connectivity.edge_kcomponents.bridge_components"]], "k_edge_components() (in module networkx.algorithms.connectivity.edge_kcomponents)": [[425, "networkx.algorithms.connectivity.edge_kcomponents.k_edge_components"]], "k_edge_subgraphs() (in module networkx.algorithms.connectivity.edge_kcomponents)": [[426, "networkx.algorithms.connectivity.edge_kcomponents.k_edge_subgraphs"]], "k_components() (in module networkx.algorithms.connectivity.kcomponents)": [[427, "networkx.algorithms.connectivity.kcomponents.k_components"]], "all_node_cuts() (in module networkx.algorithms.connectivity.kcutsets)": [[428, "networkx.algorithms.connectivity.kcutsets.all_node_cuts"]], "stoer_wagner() (in module networkx.algorithms.connectivity.stoerwagner)": [[429, "networkx.algorithms.connectivity.stoerwagner.stoer_wagner"]], "build_auxiliary_edge_connectivity() (in module networkx.algorithms.connectivity.utils)": [[430, "networkx.algorithms.connectivity.utils.build_auxiliary_edge_connectivity"]], "build_auxiliary_node_connectivity() (in module networkx.algorithms.connectivity.utils)": [[431, "networkx.algorithms.connectivity.utils.build_auxiliary_node_connectivity"]], "core_number() (in module networkx.algorithms.core)": [[432, "networkx.algorithms.core.core_number"]], "k_core() (in module networkx.algorithms.core)": [[433, "networkx.algorithms.core.k_core"]], "k_corona() (in module networkx.algorithms.core)": [[434, "networkx.algorithms.core.k_corona"]], "k_crust() (in module networkx.algorithms.core)": [[435, "networkx.algorithms.core.k_crust"]], "k_shell() (in module networkx.algorithms.core)": [[436, "networkx.algorithms.core.k_shell"]], "k_truss() (in module networkx.algorithms.core)": [[437, "networkx.algorithms.core.k_truss"]], "onion_layers() (in module networkx.algorithms.core)": [[438, "networkx.algorithms.core.onion_layers"]], "is_edge_cover() (in module networkx.algorithms.covering)": [[439, "networkx.algorithms.covering.is_edge_cover"]], "min_edge_cover() (in module networkx.algorithms.covering)": [[440, "networkx.algorithms.covering.min_edge_cover"]], "boundary_expansion() (in module networkx.algorithms.cuts)": [[441, "networkx.algorithms.cuts.boundary_expansion"]], "conductance() (in module networkx.algorithms.cuts)": [[442, "networkx.algorithms.cuts.conductance"]], "cut_size() (in module networkx.algorithms.cuts)": [[443, "networkx.algorithms.cuts.cut_size"]], "edge_expansion() (in module networkx.algorithms.cuts)": [[444, "networkx.algorithms.cuts.edge_expansion"]], "mixing_expansion() (in module networkx.algorithms.cuts)": [[445, "networkx.algorithms.cuts.mixing_expansion"]], "node_expansion() (in module networkx.algorithms.cuts)": [[446, "networkx.algorithms.cuts.node_expansion"]], "normalized_cut_size() (in module networkx.algorithms.cuts)": [[447, "networkx.algorithms.cuts.normalized_cut_size"]], "volume() (in module networkx.algorithms.cuts)": [[448, "networkx.algorithms.cuts.volume"]], "cycle_basis() (in module networkx.algorithms.cycles)": [[449, "networkx.algorithms.cycles.cycle_basis"]], "find_cycle() (in module networkx.algorithms.cycles)": [[450, "networkx.algorithms.cycles.find_cycle"]], "minimum_cycle_basis() (in module networkx.algorithms.cycles)": [[451, "networkx.algorithms.cycles.minimum_cycle_basis"]], "recursive_simple_cycles() (in module networkx.algorithms.cycles)": [[452, "networkx.algorithms.cycles.recursive_simple_cycles"]], "simple_cycles() (in module networkx.algorithms.cycles)": [[453, "networkx.algorithms.cycles.simple_cycles"]], "d_separated() (in module networkx.algorithms.d_separation)": [[454, "networkx.algorithms.d_separation.d_separated"]], "all_topological_sorts() (in module networkx.algorithms.dag)": [[455, "networkx.algorithms.dag.all_topological_sorts"]], "ancestors() (in module networkx.algorithms.dag)": [[456, "networkx.algorithms.dag.ancestors"]], "antichains() (in module networkx.algorithms.dag)": [[457, "networkx.algorithms.dag.antichains"]], "dag_longest_path() (in module networkx.algorithms.dag)": [[458, "networkx.algorithms.dag.dag_longest_path"]], "dag_longest_path_length() (in module networkx.algorithms.dag)": [[459, "networkx.algorithms.dag.dag_longest_path_length"]], "dag_to_branching() (in module networkx.algorithms.dag)": [[460, "networkx.algorithms.dag.dag_to_branching"]], "descendants() (in module networkx.algorithms.dag)": [[461, "networkx.algorithms.dag.descendants"]], "is_aperiodic() (in module networkx.algorithms.dag)": [[462, "networkx.algorithms.dag.is_aperiodic"]], "is_directed_acyclic_graph() (in module networkx.algorithms.dag)": [[463, "networkx.algorithms.dag.is_directed_acyclic_graph"]], "lexicographical_topological_sort() (in module networkx.algorithms.dag)": [[464, "networkx.algorithms.dag.lexicographical_topological_sort"]], "topological_generations() (in module networkx.algorithms.dag)": [[465, "networkx.algorithms.dag.topological_generations"]], "topological_sort() (in module networkx.algorithms.dag)": [[466, "networkx.algorithms.dag.topological_sort"]], "transitive_closure() (in module networkx.algorithms.dag)": [[467, "networkx.algorithms.dag.transitive_closure"]], "transitive_closure_dag() (in module networkx.algorithms.dag)": [[468, "networkx.algorithms.dag.transitive_closure_dag"]], "transitive_reduction() (in module networkx.algorithms.dag)": [[469, "networkx.algorithms.dag.transitive_reduction"]], "barycenter() (in module networkx.algorithms.distance_measures)": [[470, "networkx.algorithms.distance_measures.barycenter"]], "center() (in module networkx.algorithms.distance_measures)": [[471, "networkx.algorithms.distance_measures.center"]], "diameter() (in module networkx.algorithms.distance_measures)": [[472, "networkx.algorithms.distance_measures.diameter"]], "eccentricity() (in module networkx.algorithms.distance_measures)": [[473, "networkx.algorithms.distance_measures.eccentricity"]], "periphery() (in module networkx.algorithms.distance_measures)": [[474, "networkx.algorithms.distance_measures.periphery"]], "radius() (in module networkx.algorithms.distance_measures)": [[475, "networkx.algorithms.distance_measures.radius"]], "resistance_distance() (in module networkx.algorithms.distance_measures)": [[476, "networkx.algorithms.distance_measures.resistance_distance"]], "global_parameters() (in module networkx.algorithms.distance_regular)": [[477, "networkx.algorithms.distance_regular.global_parameters"]], "intersection_array() (in module networkx.algorithms.distance_regular)": [[478, "networkx.algorithms.distance_regular.intersection_array"]], "is_distance_regular() (in module networkx.algorithms.distance_regular)": [[479, "networkx.algorithms.distance_regular.is_distance_regular"]], "is_strongly_regular() (in module networkx.algorithms.distance_regular)": [[480, "networkx.algorithms.distance_regular.is_strongly_regular"]], "dominance_frontiers() (in module networkx.algorithms.dominance)": [[481, "networkx.algorithms.dominance.dominance_frontiers"]], "immediate_dominators() (in module networkx.algorithms.dominance)": [[482, "networkx.algorithms.dominance.immediate_dominators"]], "dominating_set() (in module networkx.algorithms.dominating)": [[483, "networkx.algorithms.dominating.dominating_set"]], "is_dominating_set() (in module networkx.algorithms.dominating)": [[484, "networkx.algorithms.dominating.is_dominating_set"]], "efficiency() (in module networkx.algorithms.efficiency_measures)": [[485, "networkx.algorithms.efficiency_measures.efficiency"]], "global_efficiency() (in module networkx.algorithms.efficiency_measures)": [[486, "networkx.algorithms.efficiency_measures.global_efficiency"]], "local_efficiency() (in module networkx.algorithms.efficiency_measures)": [[487, "networkx.algorithms.efficiency_measures.local_efficiency"]], "eulerian_circuit() (in module networkx.algorithms.euler)": [[488, "networkx.algorithms.euler.eulerian_circuit"]], "eulerian_path() (in module networkx.algorithms.euler)": [[489, "networkx.algorithms.euler.eulerian_path"]], "eulerize() (in module networkx.algorithms.euler)": [[490, "networkx.algorithms.euler.eulerize"]], "has_eulerian_path() (in module networkx.algorithms.euler)": [[491, "networkx.algorithms.euler.has_eulerian_path"]], "is_eulerian() (in module networkx.algorithms.euler)": [[492, "networkx.algorithms.euler.is_eulerian"]], "is_semieulerian() (in module networkx.algorithms.euler)": [[493, "networkx.algorithms.euler.is_semieulerian"]], "boykov_kolmogorov() (in module networkx.algorithms.flow)": [[494, "networkx.algorithms.flow.boykov_kolmogorov"]], "build_residual_network() (in module networkx.algorithms.flow)": [[495, "networkx.algorithms.flow.build_residual_network"]], "capacity_scaling() (in module networkx.algorithms.flow)": [[496, "networkx.algorithms.flow.capacity_scaling"]], "cost_of_flow() (in module networkx.algorithms.flow)": [[497, "networkx.algorithms.flow.cost_of_flow"]], "dinitz() (in module networkx.algorithms.flow)": [[498, "networkx.algorithms.flow.dinitz"]], "edmonds_karp() (in module networkx.algorithms.flow)": [[499, "networkx.algorithms.flow.edmonds_karp"]], "gomory_hu_tree() (in module networkx.algorithms.flow)": [[500, "networkx.algorithms.flow.gomory_hu_tree"]], "max_flow_min_cost() (in module networkx.algorithms.flow)": [[501, "networkx.algorithms.flow.max_flow_min_cost"]], "maximum_flow() (in module networkx.algorithms.flow)": [[502, "networkx.algorithms.flow.maximum_flow"]], "maximum_flow_value() (in module networkx.algorithms.flow)": [[503, "networkx.algorithms.flow.maximum_flow_value"]], "min_cost_flow() (in module networkx.algorithms.flow)": [[504, "networkx.algorithms.flow.min_cost_flow"]], "min_cost_flow_cost() (in module networkx.algorithms.flow)": [[505, "networkx.algorithms.flow.min_cost_flow_cost"]], "minimum_cut() (in module networkx.algorithms.flow)": [[506, "networkx.algorithms.flow.minimum_cut"]], "minimum_cut_value() (in module networkx.algorithms.flow)": [[507, "networkx.algorithms.flow.minimum_cut_value"]], "network_simplex() (in module networkx.algorithms.flow)": [[508, "networkx.algorithms.flow.network_simplex"]], "preflow_push() (in module networkx.algorithms.flow)": [[509, "networkx.algorithms.flow.preflow_push"]], "shortest_augmenting_path() (in module networkx.algorithms.flow)": [[510, "networkx.algorithms.flow.shortest_augmenting_path"]], "weisfeiler_lehman_graph_hash() (in module networkx.algorithms.graph_hashing)": [[511, "networkx.algorithms.graph_hashing.weisfeiler_lehman_graph_hash"]], "weisfeiler_lehman_subgraph_hashes() (in module networkx.algorithms.graph_hashing)": [[512, "networkx.algorithms.graph_hashing.weisfeiler_lehman_subgraph_hashes"]], "is_digraphical() (in module networkx.algorithms.graphical)": [[513, "networkx.algorithms.graphical.is_digraphical"]], "is_graphical() (in module networkx.algorithms.graphical)": [[514, "networkx.algorithms.graphical.is_graphical"]], "is_multigraphical() (in module networkx.algorithms.graphical)": [[515, "networkx.algorithms.graphical.is_multigraphical"]], "is_pseudographical() (in module networkx.algorithms.graphical)": [[516, "networkx.algorithms.graphical.is_pseudographical"]], "is_valid_degree_sequence_erdos_gallai() (in module networkx.algorithms.graphical)": [[517, "networkx.algorithms.graphical.is_valid_degree_sequence_erdos_gallai"]], "is_valid_degree_sequence_havel_hakimi() (in module networkx.algorithms.graphical)": [[518, "networkx.algorithms.graphical.is_valid_degree_sequence_havel_hakimi"]], "flow_hierarchy() (in module networkx.algorithms.hierarchy)": [[519, "networkx.algorithms.hierarchy.flow_hierarchy"]], "is_kl_connected() (in module networkx.algorithms.hybrid)": [[520, "networkx.algorithms.hybrid.is_kl_connected"]], "kl_connected_subgraph() (in module networkx.algorithms.hybrid)": [[521, "networkx.algorithms.hybrid.kl_connected_subgraph"]], "is_isolate() (in module networkx.algorithms.isolate)": [[522, "networkx.algorithms.isolate.is_isolate"]], "isolates() (in module networkx.algorithms.isolate)": [[523, "networkx.algorithms.isolate.isolates"]], "number_of_isolates() (in module networkx.algorithms.isolate)": [[524, "networkx.algorithms.isolate.number_of_isolates"]], "__init__() (digraphmatcher method)": [[525, "networkx.algorithms.isomorphism.DiGraphMatcher.__init__"]], "candidate_pairs_iter() (digraphmatcher method)": [[526, "networkx.algorithms.isomorphism.DiGraphMatcher.candidate_pairs_iter"]], "initialize() (digraphmatcher method)": [[527, "networkx.algorithms.isomorphism.DiGraphMatcher.initialize"]], "is_isomorphic() (digraphmatcher method)": [[528, "networkx.algorithms.isomorphism.DiGraphMatcher.is_isomorphic"]], "isomorphisms_iter() (digraphmatcher method)": [[529, "networkx.algorithms.isomorphism.DiGraphMatcher.isomorphisms_iter"]], "match() (digraphmatcher method)": [[530, "networkx.algorithms.isomorphism.DiGraphMatcher.match"]], "semantic_feasibility() (digraphmatcher method)": [[531, "networkx.algorithms.isomorphism.DiGraphMatcher.semantic_feasibility"]], "subgraph_is_isomorphic() (digraphmatcher method)": [[532, "networkx.algorithms.isomorphism.DiGraphMatcher.subgraph_is_isomorphic"]], "subgraph_isomorphisms_iter() (digraphmatcher method)": [[533, "networkx.algorithms.isomorphism.DiGraphMatcher.subgraph_isomorphisms_iter"]], "syntactic_feasibility() (digraphmatcher method)": [[534, "networkx.algorithms.isomorphism.DiGraphMatcher.syntactic_feasibility"]], "__init__() (graphmatcher method)": [[535, "networkx.algorithms.isomorphism.GraphMatcher.__init__"]], "candidate_pairs_iter() (graphmatcher method)": [[536, "networkx.algorithms.isomorphism.GraphMatcher.candidate_pairs_iter"]], "initialize() (graphmatcher method)": [[537, "networkx.algorithms.isomorphism.GraphMatcher.initialize"]], "is_isomorphic() (graphmatcher method)": [[538, "networkx.algorithms.isomorphism.GraphMatcher.is_isomorphic"]], "isomorphisms_iter() (graphmatcher method)": [[539, "networkx.algorithms.isomorphism.GraphMatcher.isomorphisms_iter"]], "match() (graphmatcher method)": [[540, "networkx.algorithms.isomorphism.GraphMatcher.match"]], "semantic_feasibility() (graphmatcher method)": [[541, "networkx.algorithms.isomorphism.GraphMatcher.semantic_feasibility"]], "subgraph_is_isomorphic() (graphmatcher method)": [[542, "networkx.algorithms.isomorphism.GraphMatcher.subgraph_is_isomorphic"]], "subgraph_isomorphisms_iter() (graphmatcher method)": [[543, "networkx.algorithms.isomorphism.GraphMatcher.subgraph_isomorphisms_iter"]], "syntactic_feasibility() (graphmatcher method)": [[544, "networkx.algorithms.isomorphism.GraphMatcher.syntactic_feasibility"]], "ismags (class in networkx.algorithms.isomorphism)": [[545, "networkx.algorithms.isomorphism.ISMAGS"]], "__init__() (ismags method)": [[545, "networkx.algorithms.isomorphism.ISMAGS.__init__"]], "categorical_edge_match() (in module networkx.algorithms.isomorphism)": [[546, "networkx.algorithms.isomorphism.categorical_edge_match"]], "categorical_multiedge_match() (in module networkx.algorithms.isomorphism)": [[547, "networkx.algorithms.isomorphism.categorical_multiedge_match"]], "categorical_node_match() (in module networkx.algorithms.isomorphism)": [[548, "networkx.algorithms.isomorphism.categorical_node_match"]], "could_be_isomorphic() (in module networkx.algorithms.isomorphism)": [[549, "networkx.algorithms.isomorphism.could_be_isomorphic"]], "fast_could_be_isomorphic() (in module networkx.algorithms.isomorphism)": [[550, "networkx.algorithms.isomorphism.fast_could_be_isomorphic"]], "faster_could_be_isomorphic() (in module networkx.algorithms.isomorphism)": [[551, "networkx.algorithms.isomorphism.faster_could_be_isomorphic"]], "generic_edge_match() (in module networkx.algorithms.isomorphism)": [[552, "networkx.algorithms.isomorphism.generic_edge_match"]], "generic_multiedge_match() (in module networkx.algorithms.isomorphism)": [[553, "networkx.algorithms.isomorphism.generic_multiedge_match"]], "generic_node_match() (in module networkx.algorithms.isomorphism)": [[554, "networkx.algorithms.isomorphism.generic_node_match"]], "is_isomorphic() (in module networkx.algorithms.isomorphism)": [[555, "networkx.algorithms.isomorphism.is_isomorphic"]], "numerical_edge_match() (in module networkx.algorithms.isomorphism)": [[556, "networkx.algorithms.isomorphism.numerical_edge_match"]], "numerical_multiedge_match() (in module networkx.algorithms.isomorphism)": [[557, "networkx.algorithms.isomorphism.numerical_multiedge_match"]], "numerical_node_match() (in module networkx.algorithms.isomorphism)": [[558, "networkx.algorithms.isomorphism.numerical_node_match"]], "rooted_tree_isomorphism() (in module networkx.algorithms.isomorphism.tree_isomorphism)": [[559, "networkx.algorithms.isomorphism.tree_isomorphism.rooted_tree_isomorphism"]], "tree_isomorphism() (in module networkx.algorithms.isomorphism.tree_isomorphism)": [[560, "networkx.algorithms.isomorphism.tree_isomorphism.tree_isomorphism"]], "vf2pp_all_isomorphisms() (in module networkx.algorithms.isomorphism.vf2pp)": [[561, "networkx.algorithms.isomorphism.vf2pp.vf2pp_all_isomorphisms"]], "vf2pp_is_isomorphic() (in module networkx.algorithms.isomorphism.vf2pp)": [[562, "networkx.algorithms.isomorphism.vf2pp.vf2pp_is_isomorphic"]], "vf2pp_isomorphism() (in module networkx.algorithms.isomorphism.vf2pp)": [[563, "networkx.algorithms.isomorphism.vf2pp.vf2pp_isomorphism"]], "hits() (in module networkx.algorithms.link_analysis.hits_alg)": [[564, "networkx.algorithms.link_analysis.hits_alg.hits"]], "google_matrix() (in module networkx.algorithms.link_analysis.pagerank_alg)": [[565, "networkx.algorithms.link_analysis.pagerank_alg.google_matrix"]], "pagerank() (in module networkx.algorithms.link_analysis.pagerank_alg)": [[566, "networkx.algorithms.link_analysis.pagerank_alg.pagerank"]], "adamic_adar_index() (in module networkx.algorithms.link_prediction)": [[567, "networkx.algorithms.link_prediction.adamic_adar_index"]], "cn_soundarajan_hopcroft() (in module networkx.algorithms.link_prediction)": [[568, "networkx.algorithms.link_prediction.cn_soundarajan_hopcroft"]], "common_neighbor_centrality() (in module networkx.algorithms.link_prediction)": [[569, "networkx.algorithms.link_prediction.common_neighbor_centrality"]], "jaccard_coefficient() (in module networkx.algorithms.link_prediction)": [[570, "networkx.algorithms.link_prediction.jaccard_coefficient"]], "preferential_attachment() (in module networkx.algorithms.link_prediction)": [[571, "networkx.algorithms.link_prediction.preferential_attachment"]], "ra_index_soundarajan_hopcroft() (in module networkx.algorithms.link_prediction)": [[572, "networkx.algorithms.link_prediction.ra_index_soundarajan_hopcroft"]], "resource_allocation_index() (in module networkx.algorithms.link_prediction)": [[573, "networkx.algorithms.link_prediction.resource_allocation_index"]], "within_inter_cluster() (in module networkx.algorithms.link_prediction)": [[574, "networkx.algorithms.link_prediction.within_inter_cluster"]], "all_pairs_lowest_common_ancestor() (in module networkx.algorithms.lowest_common_ancestors)": [[575, "networkx.algorithms.lowest_common_ancestors.all_pairs_lowest_common_ancestor"]], "lowest_common_ancestor() (in module networkx.algorithms.lowest_common_ancestors)": [[576, "networkx.algorithms.lowest_common_ancestors.lowest_common_ancestor"]], "tree_all_pairs_lowest_common_ancestor() (in module networkx.algorithms.lowest_common_ancestors)": [[577, "networkx.algorithms.lowest_common_ancestors.tree_all_pairs_lowest_common_ancestor"]], "is_matching() (in module networkx.algorithms.matching)": [[578, "networkx.algorithms.matching.is_matching"]], "is_maximal_matching() (in module networkx.algorithms.matching)": [[579, "networkx.algorithms.matching.is_maximal_matching"]], "is_perfect_matching() (in module networkx.algorithms.matching)": [[580, "networkx.algorithms.matching.is_perfect_matching"]], "max_weight_matching() (in module networkx.algorithms.matching)": [[581, "networkx.algorithms.matching.max_weight_matching"]], "maximal_matching() (in module networkx.algorithms.matching)": [[582, "networkx.algorithms.matching.maximal_matching"]], "min_weight_matching() (in module networkx.algorithms.matching)": [[583, "networkx.algorithms.matching.min_weight_matching"]], "contracted_edge() (in module networkx.algorithms.minors)": [[584, "networkx.algorithms.minors.contracted_edge"]], "contracted_nodes() (in module networkx.algorithms.minors)": [[585, "networkx.algorithms.minors.contracted_nodes"]], "equivalence_classes() (in module networkx.algorithms.minors)": [[586, "networkx.algorithms.minors.equivalence_classes"]], "identified_nodes() (in module networkx.algorithms.minors)": [[587, "networkx.algorithms.minors.identified_nodes"]], "quotient_graph() (in module networkx.algorithms.minors)": [[588, "networkx.algorithms.minors.quotient_graph"]], "maximal_independent_set() (in module networkx.algorithms.mis)": [[589, "networkx.algorithms.mis.maximal_independent_set"]], "moral_graph() (in module networkx.algorithms.moral)": [[590, "networkx.algorithms.moral.moral_graph"]], "harmonic_function() (in module networkx.algorithms.node_classification)": [[591, "networkx.algorithms.node_classification.harmonic_function"]], "local_and_global_consistency() (in module networkx.algorithms.node_classification)": [[592, "networkx.algorithms.node_classification.local_and_global_consistency"]], "non_randomness() (in module networkx.algorithms.non_randomness)": [[593, "networkx.algorithms.non_randomness.non_randomness"]], "compose_all() (in module networkx.algorithms.operators.all)": [[594, "networkx.algorithms.operators.all.compose_all"]], "disjoint_union_all() (in module networkx.algorithms.operators.all)": [[595, "networkx.algorithms.operators.all.disjoint_union_all"]], "intersection_all() (in module networkx.algorithms.operators.all)": [[596, "networkx.algorithms.operators.all.intersection_all"]], "union_all() (in module networkx.algorithms.operators.all)": [[597, "networkx.algorithms.operators.all.union_all"]], "compose() (in module networkx.algorithms.operators.binary)": [[598, "networkx.algorithms.operators.binary.compose"]], "difference() (in module networkx.algorithms.operators.binary)": [[599, "networkx.algorithms.operators.binary.difference"]], "disjoint_union() (in module networkx.algorithms.operators.binary)": [[600, "networkx.algorithms.operators.binary.disjoint_union"]], "full_join() (in module networkx.algorithms.operators.binary)": [[601, "networkx.algorithms.operators.binary.full_join"]], "intersection() (in module networkx.algorithms.operators.binary)": [[602, "networkx.algorithms.operators.binary.intersection"]], "symmetric_difference() (in module networkx.algorithms.operators.binary)": [[603, "networkx.algorithms.operators.binary.symmetric_difference"]], "union() (in module networkx.algorithms.operators.binary)": [[604, "networkx.algorithms.operators.binary.union"]], "cartesian_product() (in module networkx.algorithms.operators.product)": [[605, "networkx.algorithms.operators.product.cartesian_product"]], "corona_product() (in module networkx.algorithms.operators.product)": [[606, "networkx.algorithms.operators.product.corona_product"]], "lexicographic_product() (in module networkx.algorithms.operators.product)": [[607, "networkx.algorithms.operators.product.lexicographic_product"]], "power() (in module networkx.algorithms.operators.product)": [[608, "networkx.algorithms.operators.product.power"]], "rooted_product() (in module networkx.algorithms.operators.product)": [[609, "networkx.algorithms.operators.product.rooted_product"]], "strong_product() (in module networkx.algorithms.operators.product)": [[610, "networkx.algorithms.operators.product.strong_product"]], "tensor_product() (in module networkx.algorithms.operators.product)": [[611, "networkx.algorithms.operators.product.tensor_product"]], "complement() (in module networkx.algorithms.operators.unary)": [[612, "networkx.algorithms.operators.unary.complement"]], "reverse() (in module networkx.algorithms.operators.unary)": [[613, "networkx.algorithms.operators.unary.reverse"]], "combinatorial_embedding_to_pos() (in module networkx.algorithms.planar_drawing)": [[614, "networkx.algorithms.planar_drawing.combinatorial_embedding_to_pos"]], "planarembedding (class in networkx.algorithms.planarity)": [[615, "networkx.algorithms.planarity.PlanarEmbedding"]], "__init__() (planarembedding method)": [[615, "networkx.algorithms.planarity.PlanarEmbedding.__init__"]], "check_planarity() (in module networkx.algorithms.planarity)": [[616, "networkx.algorithms.planarity.check_planarity"]], "is_planar() (in module networkx.algorithms.planarity)": [[617, "networkx.algorithms.planarity.is_planar"]], "chromatic_polynomial() (in module networkx.algorithms.polynomials)": [[618, "networkx.algorithms.polynomials.chromatic_polynomial"]], "tutte_polynomial() (in module networkx.algorithms.polynomials)": [[619, "networkx.algorithms.polynomials.tutte_polynomial"]], "overall_reciprocity() (in module networkx.algorithms.reciprocity)": [[620, "networkx.algorithms.reciprocity.overall_reciprocity"]], "reciprocity() (in module networkx.algorithms.reciprocity)": [[621, "networkx.algorithms.reciprocity.reciprocity"]], "is_k_regular() (in module networkx.algorithms.regular)": [[622, "networkx.algorithms.regular.is_k_regular"]], "is_regular() (in module networkx.algorithms.regular)": [[623, "networkx.algorithms.regular.is_regular"]], "k_factor() (in module networkx.algorithms.regular)": [[624, "networkx.algorithms.regular.k_factor"]], "rich_club_coefficient() (in module networkx.algorithms.richclub)": [[625, "networkx.algorithms.richclub.rich_club_coefficient"]], "astar_path() (in module networkx.algorithms.shortest_paths.astar)": [[626, "networkx.algorithms.shortest_paths.astar.astar_path"]], "astar_path_length() (in module networkx.algorithms.shortest_paths.astar)": [[627, "networkx.algorithms.shortest_paths.astar.astar_path_length"]], "floyd_warshall() (in module networkx.algorithms.shortest_paths.dense)": [[628, "networkx.algorithms.shortest_paths.dense.floyd_warshall"]], "floyd_warshall_numpy() (in module networkx.algorithms.shortest_paths.dense)": [[629, "networkx.algorithms.shortest_paths.dense.floyd_warshall_numpy"]], "floyd_warshall_predecessor_and_distance() (in module networkx.algorithms.shortest_paths.dense)": [[630, "networkx.algorithms.shortest_paths.dense.floyd_warshall_predecessor_and_distance"]], "reconstruct_path() (in module networkx.algorithms.shortest_paths.dense)": [[631, "networkx.algorithms.shortest_paths.dense.reconstruct_path"]], "all_shortest_paths() (in module networkx.algorithms.shortest_paths.generic)": [[632, "networkx.algorithms.shortest_paths.generic.all_shortest_paths"]], "average_shortest_path_length() (in module networkx.algorithms.shortest_paths.generic)": [[633, "networkx.algorithms.shortest_paths.generic.average_shortest_path_length"]], "has_path() (in module networkx.algorithms.shortest_paths.generic)": [[634, "networkx.algorithms.shortest_paths.generic.has_path"]], "shortest_path() (in module networkx.algorithms.shortest_paths.generic)": [[635, "networkx.algorithms.shortest_paths.generic.shortest_path"]], "shortest_path_length() (in module networkx.algorithms.shortest_paths.generic)": [[636, "networkx.algorithms.shortest_paths.generic.shortest_path_length"]], "all_pairs_shortest_path() (in module networkx.algorithms.shortest_paths.unweighted)": [[637, "networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path"]], "all_pairs_shortest_path_length() (in module networkx.algorithms.shortest_paths.unweighted)": [[638, "networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path_length"]], "bidirectional_shortest_path() (in module networkx.algorithms.shortest_paths.unweighted)": [[639, "networkx.algorithms.shortest_paths.unweighted.bidirectional_shortest_path"]], "predecessor() (in module networkx.algorithms.shortest_paths.unweighted)": [[640, "networkx.algorithms.shortest_paths.unweighted.predecessor"]], "single_source_shortest_path() (in module networkx.algorithms.shortest_paths.unweighted)": [[641, "networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path"]], "single_source_shortest_path_length() (in module networkx.algorithms.shortest_paths.unweighted)": [[642, "networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path_length"]], "single_target_shortest_path() (in module networkx.algorithms.shortest_paths.unweighted)": [[643, "networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path"]], "single_target_shortest_path_length() (in module networkx.algorithms.shortest_paths.unweighted)": [[644, "networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path_length"]], "all_pairs_bellman_ford_path() (in module networkx.algorithms.shortest_paths.weighted)": [[645, "networkx.algorithms.shortest_paths.weighted.all_pairs_bellman_ford_path"]], "all_pairs_bellman_ford_path_length() (in module networkx.algorithms.shortest_paths.weighted)": [[646, "networkx.algorithms.shortest_paths.weighted.all_pairs_bellman_ford_path_length"]], "all_pairs_dijkstra() (in module networkx.algorithms.shortest_paths.weighted)": [[647, "networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra"]], "all_pairs_dijkstra_path() (in module networkx.algorithms.shortest_paths.weighted)": [[648, "networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra_path"]], "all_pairs_dijkstra_path_length() (in module networkx.algorithms.shortest_paths.weighted)": [[649, "networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra_path_length"]], "bellman_ford_path() (in module networkx.algorithms.shortest_paths.weighted)": [[650, "networkx.algorithms.shortest_paths.weighted.bellman_ford_path"]], "bellman_ford_path_length() (in module networkx.algorithms.shortest_paths.weighted)": [[651, "networkx.algorithms.shortest_paths.weighted.bellman_ford_path_length"]], "bellman_ford_predecessor_and_distance() (in module networkx.algorithms.shortest_paths.weighted)": [[652, "networkx.algorithms.shortest_paths.weighted.bellman_ford_predecessor_and_distance"]], "bidirectional_dijkstra() (in module networkx.algorithms.shortest_paths.weighted)": [[653, "networkx.algorithms.shortest_paths.weighted.bidirectional_dijkstra"]], "dijkstra_path() (in module networkx.algorithms.shortest_paths.weighted)": [[654, "networkx.algorithms.shortest_paths.weighted.dijkstra_path"]], "dijkstra_path_length() (in module networkx.algorithms.shortest_paths.weighted)": [[655, "networkx.algorithms.shortest_paths.weighted.dijkstra_path_length"]], "dijkstra_predecessor_and_distance() (in module networkx.algorithms.shortest_paths.weighted)": [[656, "networkx.algorithms.shortest_paths.weighted.dijkstra_predecessor_and_distance"]], "find_negative_cycle() (in module networkx.algorithms.shortest_paths.weighted)": [[657, "networkx.algorithms.shortest_paths.weighted.find_negative_cycle"]], "goldberg_radzik() (in module networkx.algorithms.shortest_paths.weighted)": [[658, "networkx.algorithms.shortest_paths.weighted.goldberg_radzik"]], "johnson() (in module networkx.algorithms.shortest_paths.weighted)": [[659, "networkx.algorithms.shortest_paths.weighted.johnson"]], "multi_source_dijkstra() (in module networkx.algorithms.shortest_paths.weighted)": [[660, "networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra"]], "multi_source_dijkstra_path() (in module networkx.algorithms.shortest_paths.weighted)": [[661, "networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra_path"]], "multi_source_dijkstra_path_length() (in module networkx.algorithms.shortest_paths.weighted)": [[662, "networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra_path_length"]], "negative_edge_cycle() (in module networkx.algorithms.shortest_paths.weighted)": [[663, "networkx.algorithms.shortest_paths.weighted.negative_edge_cycle"]], "single_source_bellman_ford() (in module networkx.algorithms.shortest_paths.weighted)": [[664, "networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford"]], "single_source_bellman_ford_path() (in module networkx.algorithms.shortest_paths.weighted)": [[665, "networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path"]], "single_source_bellman_ford_path_length() (in module networkx.algorithms.shortest_paths.weighted)": [[666, "networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path_length"]], "single_source_dijkstra() (in module networkx.algorithms.shortest_paths.weighted)": [[667, "networkx.algorithms.shortest_paths.weighted.single_source_dijkstra"]], "single_source_dijkstra_path() (in module networkx.algorithms.shortest_paths.weighted)": [[668, "networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path"]], "single_source_dijkstra_path_length() (in module networkx.algorithms.shortest_paths.weighted)": [[669, "networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path_length"]], "generate_random_paths() (in module networkx.algorithms.similarity)": [[670, "networkx.algorithms.similarity.generate_random_paths"]], "graph_edit_distance() (in module networkx.algorithms.similarity)": [[671, "networkx.algorithms.similarity.graph_edit_distance"]], "optimal_edit_paths() (in module networkx.algorithms.similarity)": [[672, "networkx.algorithms.similarity.optimal_edit_paths"]], "optimize_edit_paths() (in module networkx.algorithms.similarity)": [[673, "networkx.algorithms.similarity.optimize_edit_paths"]], "optimize_graph_edit_distance() (in module networkx.algorithms.similarity)": [[674, "networkx.algorithms.similarity.optimize_graph_edit_distance"]], "panther_similarity() (in module networkx.algorithms.similarity)": [[675, "networkx.algorithms.similarity.panther_similarity"]], "simrank_similarity() (in module networkx.algorithms.similarity)": [[676, "networkx.algorithms.similarity.simrank_similarity"]], "all_simple_edge_paths() (in module networkx.algorithms.simple_paths)": [[677, "networkx.algorithms.simple_paths.all_simple_edge_paths"]], "all_simple_paths() (in module networkx.algorithms.simple_paths)": [[678, "networkx.algorithms.simple_paths.all_simple_paths"]], "is_simple_path() (in module networkx.algorithms.simple_paths)": [[679, "networkx.algorithms.simple_paths.is_simple_path"]], "shortest_simple_paths() (in module networkx.algorithms.simple_paths)": [[680, "networkx.algorithms.simple_paths.shortest_simple_paths"]], "lattice_reference() (in module networkx.algorithms.smallworld)": [[681, "networkx.algorithms.smallworld.lattice_reference"]], "omega() (in module networkx.algorithms.smallworld)": [[682, "networkx.algorithms.smallworld.omega"]], "random_reference() (in module networkx.algorithms.smallworld)": [[683, "networkx.algorithms.smallworld.random_reference"]], "sigma() (in module networkx.algorithms.smallworld)": [[684, "networkx.algorithms.smallworld.sigma"]], "s_metric() (in module networkx.algorithms.smetric)": [[685, "networkx.algorithms.smetric.s_metric"]], "spanner() (in module networkx.algorithms.sparsifiers)": [[686, "networkx.algorithms.sparsifiers.spanner"]], "constraint() (in module networkx.algorithms.structuralholes)": [[687, "networkx.algorithms.structuralholes.constraint"]], "effective_size() (in module networkx.algorithms.structuralholes)": [[688, "networkx.algorithms.structuralholes.effective_size"]], "local_constraint() (in module networkx.algorithms.structuralholes)": [[689, "networkx.algorithms.structuralholes.local_constraint"]], "dedensify() (in module networkx.algorithms.summarization)": [[690, "networkx.algorithms.summarization.dedensify"]], "snap_aggregation() (in module networkx.algorithms.summarization)": [[691, "networkx.algorithms.summarization.snap_aggregation"]], "connected_double_edge_swap() (in module networkx.algorithms.swap)": [[692, "networkx.algorithms.swap.connected_double_edge_swap"]], "directed_edge_swap() (in module networkx.algorithms.swap)": [[693, "networkx.algorithms.swap.directed_edge_swap"]], "double_edge_swap() (in module networkx.algorithms.swap)": [[694, "networkx.algorithms.swap.double_edge_swap"]], "find_threshold_graph() (in module networkx.algorithms.threshold)": [[695, "networkx.algorithms.threshold.find_threshold_graph"]], "is_threshold_graph() (in module networkx.algorithms.threshold)": [[696, "networkx.algorithms.threshold.is_threshold_graph"]], "hamiltonian_path() (in module networkx.algorithms.tournament)": [[697, "networkx.algorithms.tournament.hamiltonian_path"]], "is_reachable() (in module networkx.algorithms.tournament)": [[698, "networkx.algorithms.tournament.is_reachable"]], "is_strongly_connected() (in module networkx.algorithms.tournament)": [[699, "networkx.algorithms.tournament.is_strongly_connected"]], "is_tournament() (in module networkx.algorithms.tournament)": [[700, "networkx.algorithms.tournament.is_tournament"]], "random_tournament() (in module networkx.algorithms.tournament)": [[701, "networkx.algorithms.tournament.random_tournament"]], "score_sequence() (in module networkx.algorithms.tournament)": [[702, "networkx.algorithms.tournament.score_sequence"]], "bfs_beam_edges() (in module networkx.algorithms.traversal.beamsearch)": [[703, "networkx.algorithms.traversal.beamsearch.bfs_beam_edges"]], "bfs_edges() (in module networkx.algorithms.traversal.breadth_first_search)": [[704, "networkx.algorithms.traversal.breadth_first_search.bfs_edges"]], "bfs_layers() (in module networkx.algorithms.traversal.breadth_first_search)": [[705, "networkx.algorithms.traversal.breadth_first_search.bfs_layers"]], "bfs_predecessors() (in module networkx.algorithms.traversal.breadth_first_search)": [[706, "networkx.algorithms.traversal.breadth_first_search.bfs_predecessors"]], "bfs_successors() (in module networkx.algorithms.traversal.breadth_first_search)": [[707, "networkx.algorithms.traversal.breadth_first_search.bfs_successors"]], "bfs_tree() (in module networkx.algorithms.traversal.breadth_first_search)": [[708, "networkx.algorithms.traversal.breadth_first_search.bfs_tree"]], "descendants_at_distance() (in module networkx.algorithms.traversal.breadth_first_search)": [[709, "networkx.algorithms.traversal.breadth_first_search.descendants_at_distance"]], "dfs_edges() (in module networkx.algorithms.traversal.depth_first_search)": [[710, "networkx.algorithms.traversal.depth_first_search.dfs_edges"]], "dfs_labeled_edges() (in module networkx.algorithms.traversal.depth_first_search)": [[711, "networkx.algorithms.traversal.depth_first_search.dfs_labeled_edges"]], "dfs_postorder_nodes() (in module networkx.algorithms.traversal.depth_first_search)": [[712, "networkx.algorithms.traversal.depth_first_search.dfs_postorder_nodes"]], "dfs_predecessors() (in module networkx.algorithms.traversal.depth_first_search)": [[713, "networkx.algorithms.traversal.depth_first_search.dfs_predecessors"]], "dfs_preorder_nodes() (in module networkx.algorithms.traversal.depth_first_search)": [[714, "networkx.algorithms.traversal.depth_first_search.dfs_preorder_nodes"]], "dfs_successors() (in module networkx.algorithms.traversal.depth_first_search)": [[715, "networkx.algorithms.traversal.depth_first_search.dfs_successors"]], "dfs_tree() (in module networkx.algorithms.traversal.depth_first_search)": [[716, "networkx.algorithms.traversal.depth_first_search.dfs_tree"]], "edge_bfs() (in module networkx.algorithms.traversal.edgebfs)": [[717, "networkx.algorithms.traversal.edgebfs.edge_bfs"]], "edge_dfs() (in module networkx.algorithms.traversal.edgedfs)": [[718, "networkx.algorithms.traversal.edgedfs.edge_dfs"]], "arborescenceiterator (class in networkx.algorithms.tree.branchings)": [[719, "networkx.algorithms.tree.branchings.ArborescenceIterator"]], "__init__() (arborescenceiterator method)": [[719, "networkx.algorithms.tree.branchings.ArborescenceIterator.__init__"]], "edmonds (class in networkx.algorithms.tree.branchings)": [[720, "networkx.algorithms.tree.branchings.Edmonds"]], "__init__() (edmonds method)": [[720, "networkx.algorithms.tree.branchings.Edmonds.__init__"]], "branching_weight() (in module networkx.algorithms.tree.branchings)": [[721, "networkx.algorithms.tree.branchings.branching_weight"]], "greedy_branching() (in module networkx.algorithms.tree.branchings)": [[722, "networkx.algorithms.tree.branchings.greedy_branching"]], "maximum_branching() (in module networkx.algorithms.tree.branchings)": [[723, "networkx.algorithms.tree.branchings.maximum_branching"]], "maximum_spanning_arborescence() (in module networkx.algorithms.tree.branchings)": [[724, "networkx.algorithms.tree.branchings.maximum_spanning_arborescence"]], "minimum_branching() (in module networkx.algorithms.tree.branchings)": [[725, "networkx.algorithms.tree.branchings.minimum_branching"]], "minimum_spanning_arborescence() (in module networkx.algorithms.tree.branchings)": [[726, "networkx.algorithms.tree.branchings.minimum_spanning_arborescence"]], "notatree": [[727, "networkx.algorithms.tree.coding.NotATree"]], "from_nested_tuple() (in module networkx.algorithms.tree.coding)": [[728, "networkx.algorithms.tree.coding.from_nested_tuple"]], "from_prufer_sequence() (in module networkx.algorithms.tree.coding)": [[729, "networkx.algorithms.tree.coding.from_prufer_sequence"]], "to_nested_tuple() (in module networkx.algorithms.tree.coding)": [[730, "networkx.algorithms.tree.coding.to_nested_tuple"]], "to_prufer_sequence() (in module networkx.algorithms.tree.coding)": [[731, "networkx.algorithms.tree.coding.to_prufer_sequence"]], "junction_tree() (in module networkx.algorithms.tree.decomposition)": [[732, "networkx.algorithms.tree.decomposition.junction_tree"]], "spanningtreeiterator (class in networkx.algorithms.tree.mst)": [[733, "networkx.algorithms.tree.mst.SpanningTreeIterator"]], "__init__() (spanningtreeiterator method)": [[733, "networkx.algorithms.tree.mst.SpanningTreeIterator.__init__"]], "maximum_spanning_edges() (in module networkx.algorithms.tree.mst)": [[734, "networkx.algorithms.tree.mst.maximum_spanning_edges"]], "maximum_spanning_tree() (in module networkx.algorithms.tree.mst)": [[735, "networkx.algorithms.tree.mst.maximum_spanning_tree"]], "minimum_spanning_edges() (in module networkx.algorithms.tree.mst)": [[736, "networkx.algorithms.tree.mst.minimum_spanning_edges"]], "minimum_spanning_tree() (in module networkx.algorithms.tree.mst)": [[737, "networkx.algorithms.tree.mst.minimum_spanning_tree"]], "random_spanning_tree() (in module networkx.algorithms.tree.mst)": [[738, 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"order() (multigraph method)": [[1001, "networkx.MultiGraph.order"]], "remove_edge() (multigraph method)": [[1002, "networkx.MultiGraph.remove_edge"]], "remove_edges_from() (multigraph method)": [[1003, "networkx.MultiGraph.remove_edges_from"]], "remove_node() (multigraph method)": [[1004, "networkx.MultiGraph.remove_node"]], "remove_nodes_from() (multigraph method)": [[1005, "networkx.MultiGraph.remove_nodes_from"]], "size() (multigraph method)": [[1006, "networkx.MultiGraph.size"]], "subgraph() (multigraph method)": [[1007, "networkx.MultiGraph.subgraph"]], "to_directed() (multigraph method)": [[1008, "networkx.MultiGraph.to_directed"]], "to_undirected() (multigraph method)": [[1009, "networkx.MultiGraph.to_undirected"]], "update() (multigraph method)": [[1010, "networkx.MultiGraph.update"]], "_dispatch() (in module networkx.classes.backends)": [[1011, "networkx.classes.backends._dispatch"]], "adjacencyview (class in networkx.classes.coreviews)": [[1012, "networkx.classes.coreviews.AdjacencyView"]], "__init__() (adjacencyview method)": [[1012, "networkx.classes.coreviews.AdjacencyView.__init__"]], "atlasview (class in networkx.classes.coreviews)": [[1013, "networkx.classes.coreviews.AtlasView"]], "__init__() (atlasview method)": [[1013, "networkx.classes.coreviews.AtlasView.__init__"]], "filteradjacency (class in networkx.classes.coreviews)": [[1014, "networkx.classes.coreviews.FilterAdjacency"]], "__init__() (filteradjacency method)": [[1014, "networkx.classes.coreviews.FilterAdjacency.__init__"]], "filteratlas (class in networkx.classes.coreviews)": [[1015, "networkx.classes.coreviews.FilterAtlas"]], "__init__() (filteratlas method)": [[1015, "networkx.classes.coreviews.FilterAtlas.__init__"]], "filtermultiadjacency (class in networkx.classes.coreviews)": [[1016, "networkx.classes.coreviews.FilterMultiAdjacency"]], "__init__() (filtermultiadjacency method)": [[1016, "networkx.classes.coreviews.FilterMultiAdjacency.__init__"]], "filtermultiinner (class in networkx.classes.coreviews)": [[1017, "networkx.classes.coreviews.FilterMultiInner"]], "__init__() (filtermultiinner method)": [[1017, "networkx.classes.coreviews.FilterMultiInner.__init__"]], "multiadjacencyview (class in networkx.classes.coreviews)": [[1018, "networkx.classes.coreviews.MultiAdjacencyView"]], "__init__() (multiadjacencyview method)": [[1018, "networkx.classes.coreviews.MultiAdjacencyView.__init__"]], "unionadjacency (class in networkx.classes.coreviews)": [[1019, "networkx.classes.coreviews.UnionAdjacency"]], "__init__() (unionadjacency method)": [[1019, "networkx.classes.coreviews.UnionAdjacency.__init__"]], "unionatlas (class in networkx.classes.coreviews)": [[1020, "networkx.classes.coreviews.UnionAtlas"]], "__init__() (unionatlas method)": [[1020, "networkx.classes.coreviews.UnionAtlas.__init__"]], "unionmultiadjacency (class in networkx.classes.coreviews)": [[1021, "networkx.classes.coreviews.UnionMultiAdjacency"]], "__init__() 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networkx.classes.filters)": [[1029, "networkx.classes.filters.show_diedges"]], "show_edges() (in module networkx.classes.filters)": [[1030, "networkx.classes.filters.show_edges"]], "show_multidiedges() (in module networkx.classes.filters)": [[1031, "networkx.classes.filters.show_multidiedges"]], "show_multiedges() (in module networkx.classes.filters)": [[1032, "networkx.classes.filters.show_multiedges"]], "__init__() (show_nodes method)": [[1033, "networkx.classes.filters.show_nodes.__init__"]], "show_nodes (class in networkx.classes.filters)": [[1033, "networkx.classes.filters.show_nodes"]], "generic_graph_view() (in module networkx.classes.graphviews)": [[1034, "networkx.classes.graphviews.generic_graph_view"]], "reverse_view() (in module networkx.classes.graphviews)": [[1035, "networkx.classes.graphviews.reverse_view"]], "subgraph_view() (in module networkx.classes.graphviews)": [[1036, "networkx.classes.graphviews.subgraph_view"]], "graph (class in networkx)": [[1037, "networkx.Graph"]], "networkx.classes.backends": [[1038, "module-networkx.classes.backends"]], "networkx.classes.coreviews": [[1038, "module-networkx.classes.coreviews"]], "networkx.classes.filters": [[1038, "module-networkx.classes.filters"]], "networkx.classes.graphviews": [[1038, "module-networkx.classes.graphviews"]], "multidigraph (class in networkx)": [[1039, "networkx.MultiDiGraph"]], "multigraph (class in networkx)": [[1040, "networkx.MultiGraph"]], "networkx.convert": [[1041, "module-networkx.convert"]], "networkx.convert_matrix": [[1041, "module-networkx.convert_matrix"]], "networkx.drawing.layout": [[1042, "module-networkx.drawing.layout"]], "networkx.drawing.nx_agraph": [[1042, "module-networkx.drawing.nx_agraph"]], "networkx.drawing.nx_pydot": [[1042, "module-networkx.drawing.nx_pydot"]], "networkx.drawing.nx_pylab": [[1042, "module-networkx.drawing.nx_pylab"]], "ambiguoussolution (class in networkx)": [[1043, "networkx.AmbiguousSolution"]], "exceededmaxiterations (class in networkx)": [[1043, "networkx.ExceededMaxIterations"]], "hasacycle (class in networkx)": [[1043, "networkx.HasACycle"]], "networkxalgorithmerror (class in networkx)": [[1043, "networkx.NetworkXAlgorithmError"]], "networkxerror (class in networkx)": [[1043, "networkx.NetworkXError"]], "networkxexception (class in networkx)": [[1043, "networkx.NetworkXException"]], "networkxnocycle (class in networkx)": [[1043, "networkx.NetworkXNoCycle"]], "networkxnopath (class in networkx)": [[1043, "networkx.NetworkXNoPath"]], "networkxnotimplemented (class in networkx)": [[1043, "networkx.NetworkXNotImplemented"]], "networkxpointlessconcept (class in networkx)": [[1043, "networkx.NetworkXPointlessConcept"]], "networkxunbounded (class in networkx)": [[1043, "networkx.NetworkXUnbounded"]], "networkxunfeasible (class in networkx)": [[1043, "networkx.NetworkXUnfeasible"]], "nodenotfound (class in networkx)": [[1043, "networkx.NodeNotFound"]], "poweriterationfailedconvergence (class in networkx)": [[1043, "networkx.PowerIterationFailedConvergence"]], "networkx.exception": [[1043, "module-networkx.exception"]], "networkx.classes.function": [[1044, "module-networkx.classes.function"]], "assemble() (argmap method)": [[1045, "networkx.utils.decorators.argmap.assemble"]], "compile() (argmap method)": [[1046, "networkx.utils.decorators.argmap.compile"]], "signature() (argmap class method)": [[1047, "networkx.utils.decorators.argmap.signature"]], "pop() (mappedqueue method)": [[1048, "networkx.utils.mapped_queue.MappedQueue.pop"]], "push() (mappedqueue method)": [[1049, "networkx.utils.mapped_queue.MappedQueue.push"]], "remove() (mappedqueue method)": [[1050, "networkx.utils.mapped_queue.MappedQueue.remove"]], "update() (mappedqueue method)": [[1051, "networkx.utils.mapped_queue.MappedQueue.update"]], "add_cycle() (in module networkx.classes.function)": [[1052, "networkx.classes.function.add_cycle"]], "add_path() (in module networkx.classes.function)": [[1053, "networkx.classes.function.add_path"]], "add_star() (in module networkx.classes.function)": [[1054, "networkx.classes.function.add_star"]], "all_neighbors() (in module networkx.classes.function)": [[1055, "networkx.classes.function.all_neighbors"]], "common_neighbors() (in module networkx.classes.function)": [[1056, "networkx.classes.function.common_neighbors"]], "create_empty_copy() (in module networkx.classes.function)": [[1057, "networkx.classes.function.create_empty_copy"]], "degree() (in module networkx.classes.function)": [[1058, "networkx.classes.function.degree"]], "degree_histogram() (in module networkx.classes.function)": [[1059, "networkx.classes.function.degree_histogram"]], "density() (in module networkx.classes.function)": [[1060, "networkx.classes.function.density"]], "edge_subgraph() (in module networkx.classes.function)": [[1061, "networkx.classes.function.edge_subgraph"]], "edges() (in module networkx.classes.function)": [[1062, "networkx.classes.function.edges"]], "freeze() (in module networkx.classes.function)": [[1063, "networkx.classes.function.freeze"]], "get_edge_attributes() (in module networkx.classes.function)": [[1064, "networkx.classes.function.get_edge_attributes"]], "get_node_attributes() (in module networkx.classes.function)": [[1065, "networkx.classes.function.get_node_attributes"]], "induced_subgraph() (in module networkx.classes.function)": [[1066, "networkx.classes.function.induced_subgraph"]], "is_directed() (in module networkx.classes.function)": [[1067, "networkx.classes.function.is_directed"]], "is_empty() (in module networkx.classes.function)": [[1068, "networkx.classes.function.is_empty"]], "is_frozen() (in module networkx.classes.function)": [[1069, "networkx.classes.function.is_frozen"]], "is_negatively_weighted() (in module networkx.classes.function)": [[1070, "networkx.classes.function.is_negatively_weighted"]], "is_path() (in module networkx.classes.function)": [[1071, "networkx.classes.function.is_path"]], "is_weighted() (in module networkx.classes.function)": [[1072, "networkx.classes.function.is_weighted"]], "neighbors() (in module networkx.classes.function)": [[1073, "networkx.classes.function.neighbors"]], "nodes() (in module networkx.classes.function)": [[1074, "networkx.classes.function.nodes"]], "nodes_with_selfloops() (in module networkx.classes.function)": [[1075, "networkx.classes.function.nodes_with_selfloops"]], "non_edges() (in module networkx.classes.function)": [[1076, "networkx.classes.function.non_edges"]], "non_neighbors() (in module networkx.classes.function)": [[1077, "networkx.classes.function.non_neighbors"]], "number_of_edges() (in module networkx.classes.function)": [[1078, "networkx.classes.function.number_of_edges"]], "number_of_nodes() (in module networkx.classes.function)": [[1079, "networkx.classes.function.number_of_nodes"]], "number_of_selfloops() (in module networkx.classes.function)": [[1080, "networkx.classes.function.number_of_selfloops"]], "path_weight() (in module networkx.classes.function)": [[1081, "networkx.classes.function.path_weight"]], "restricted_view() (in module networkx.classes.function)": [[1082, "networkx.classes.function.restricted_view"]], "reverse_view() (in module networkx.classes.function)": [[1083, "networkx.classes.function.reverse_view"]], "selfloop_edges() (in module networkx.classes.function)": [[1084, "networkx.classes.function.selfloop_edges"]], "set_edge_attributes() (in module networkx.classes.function)": [[1085, "networkx.classes.function.set_edge_attributes"]], "set_node_attributes() (in module networkx.classes.function)": [[1086, "networkx.classes.function.set_node_attributes"]], "subgraph() (in module networkx.classes.function)": [[1087, "networkx.classes.function.subgraph"]], "subgraph_view() (in module networkx.classes.function)": [[1088, "networkx.classes.function.subgraph_view"]], "to_directed() (in module networkx.classes.function)": [[1089, "networkx.classes.function.to_directed"]], "to_undirected() (in module networkx.classes.function)": [[1090, "networkx.classes.function.to_undirected"]], "from_dict_of_dicts() (in module networkx.convert)": [[1091, "networkx.convert.from_dict_of_dicts"]], "from_dict_of_lists() (in module networkx.convert)": [[1092, "networkx.convert.from_dict_of_lists"]], "from_edgelist() (in module networkx.convert)": [[1093, "networkx.convert.from_edgelist"]], "to_dict_of_dicts() (in module networkx.convert)": [[1094, "networkx.convert.to_dict_of_dicts"]], "to_dict_of_lists() (in module networkx.convert)": [[1095, "networkx.convert.to_dict_of_lists"]], "to_edgelist() (in module networkx.convert)": [[1096, "networkx.convert.to_edgelist"]], "to_networkx_graph() (in module networkx.convert)": [[1097, "networkx.convert.to_networkx_graph"]], "from_numpy_array() (in module networkx.convert_matrix)": [[1098, "networkx.convert_matrix.from_numpy_array"]], "from_pandas_adjacency() (in module networkx.convert_matrix)": [[1099, "networkx.convert_matrix.from_pandas_adjacency"]], "from_pandas_edgelist() (in module networkx.convert_matrix)": [[1100, "networkx.convert_matrix.from_pandas_edgelist"]], "from_scipy_sparse_array() (in module networkx.convert_matrix)": [[1101, "networkx.convert_matrix.from_scipy_sparse_array"]], "to_numpy_array() (in module networkx.convert_matrix)": [[1102, "networkx.convert_matrix.to_numpy_array"]], "to_pandas_adjacency() (in module networkx.convert_matrix)": [[1103, "networkx.convert_matrix.to_pandas_adjacency"]], "to_pandas_edgelist() (in module networkx.convert_matrix)": [[1104, "networkx.convert_matrix.to_pandas_edgelist"]], "to_scipy_sparse_array() (in module networkx.convert_matrix)": [[1105, "networkx.convert_matrix.to_scipy_sparse_array"]], "bipartite_layout() (in module networkx.drawing.layout)": [[1106, "networkx.drawing.layout.bipartite_layout"]], "circular_layout() (in module networkx.drawing.layout)": [[1107, "networkx.drawing.layout.circular_layout"]], "kamada_kawai_layout() (in module networkx.drawing.layout)": [[1108, "networkx.drawing.layout.kamada_kawai_layout"]], "multipartite_layout() (in module networkx.drawing.layout)": [[1109, "networkx.drawing.layout.multipartite_layout"]], "planar_layout() (in module networkx.drawing.layout)": [[1110, "networkx.drawing.layout.planar_layout"]], "random_layout() (in module networkx.drawing.layout)": [[1111, "networkx.drawing.layout.random_layout"]], "rescale_layout() (in module networkx.drawing.layout)": [[1112, "networkx.drawing.layout.rescale_layout"]], "rescale_layout_dict() (in module networkx.drawing.layout)": [[1113, "networkx.drawing.layout.rescale_layout_dict"]], "shell_layout() (in module networkx.drawing.layout)": [[1114, "networkx.drawing.layout.shell_layout"]], "spectral_layout() (in module networkx.drawing.layout)": [[1115, "networkx.drawing.layout.spectral_layout"]], "spiral_layout() (in module networkx.drawing.layout)": [[1116, "networkx.drawing.layout.spiral_layout"]], "spring_layout() (in module networkx.drawing.layout)": [[1117, "networkx.drawing.layout.spring_layout"]], "from_agraph() (in module networkx.drawing.nx_agraph)": [[1118, "networkx.drawing.nx_agraph.from_agraph"]], "graphviz_layout() (in module networkx.drawing.nx_agraph)": [[1119, "networkx.drawing.nx_agraph.graphviz_layout"]], "pygraphviz_layout() (in module networkx.drawing.nx_agraph)": [[1120, "networkx.drawing.nx_agraph.pygraphviz_layout"]], "read_dot() (in module networkx.drawing.nx_agraph)": [[1121, "networkx.drawing.nx_agraph.read_dot"]], "to_agraph() (in module networkx.drawing.nx_agraph)": [[1122, "networkx.drawing.nx_agraph.to_agraph"]], "write_dot() (in module networkx.drawing.nx_agraph)": [[1123, "networkx.drawing.nx_agraph.write_dot"]], "from_pydot() (in module networkx.drawing.nx_pydot)": [[1124, "networkx.drawing.nx_pydot.from_pydot"]], "graphviz_layout() (in module networkx.drawing.nx_pydot)": [[1125, "networkx.drawing.nx_pydot.graphviz_layout"]], "pydot_layout() (in module networkx.drawing.nx_pydot)": [[1126, "networkx.drawing.nx_pydot.pydot_layout"]], "read_dot() (in module networkx.drawing.nx_pydot)": [[1127, "networkx.drawing.nx_pydot.read_dot"]], "to_pydot() (in module networkx.drawing.nx_pydot)": [[1128, "networkx.drawing.nx_pydot.to_pydot"]], "write_dot() (in module networkx.drawing.nx_pydot)": [[1129, "networkx.drawing.nx_pydot.write_dot"]], "draw() (in module networkx.drawing.nx_pylab)": [[1130, "networkx.drawing.nx_pylab.draw"]], "draw_circular() (in module networkx.drawing.nx_pylab)": [[1131, "networkx.drawing.nx_pylab.draw_circular"]], "draw_kamada_kawai() (in module networkx.drawing.nx_pylab)": [[1132, "networkx.drawing.nx_pylab.draw_kamada_kawai"]], "draw_networkx() (in module networkx.drawing.nx_pylab)": [[1133, "networkx.drawing.nx_pylab.draw_networkx"]], "draw_networkx_edge_labels() (in module networkx.drawing.nx_pylab)": [[1134, "networkx.drawing.nx_pylab.draw_networkx_edge_labels"]], "draw_networkx_edges() (in module networkx.drawing.nx_pylab)": [[1135, "networkx.drawing.nx_pylab.draw_networkx_edges"]], "draw_networkx_labels() (in module networkx.drawing.nx_pylab)": [[1136, "networkx.drawing.nx_pylab.draw_networkx_labels"]], "draw_networkx_nodes() (in module networkx.drawing.nx_pylab)": [[1137, "networkx.drawing.nx_pylab.draw_networkx_nodes"]], "draw_planar() (in module networkx.drawing.nx_pylab)": [[1138, "networkx.drawing.nx_pylab.draw_planar"]], "draw_random() (in module networkx.drawing.nx_pylab)": [[1139, "networkx.drawing.nx_pylab.draw_random"]], "draw_shell() (in module networkx.drawing.nx_pylab)": [[1140, "networkx.drawing.nx_pylab.draw_shell"]], "draw_spectral() (in module networkx.drawing.nx_pylab)": [[1141, "networkx.drawing.nx_pylab.draw_spectral"]], "draw_spring() (in module networkx.drawing.nx_pylab)": [[1142, "networkx.drawing.nx_pylab.draw_spring"]], "graph_atlas() (in module networkx.generators.atlas)": [[1143, "networkx.generators.atlas.graph_atlas"]], "graph_atlas_g() (in module networkx.generators.atlas)": [[1144, "networkx.generators.atlas.graph_atlas_g"]], "balanced_tree() (in module networkx.generators.classic)": [[1145, "networkx.generators.classic.balanced_tree"]], "barbell_graph() (in module networkx.generators.classic)": [[1146, "networkx.generators.classic.barbell_graph"]], "binomial_tree() (in module networkx.generators.classic)": [[1147, "networkx.generators.classic.binomial_tree"]], "circulant_graph() (in module networkx.generators.classic)": [[1148, "networkx.generators.classic.circulant_graph"]], "circular_ladder_graph() (in module networkx.generators.classic)": [[1149, "networkx.generators.classic.circular_ladder_graph"]], "complete_graph() (in module networkx.generators.classic)": [[1150, "networkx.generators.classic.complete_graph"]], "complete_multipartite_graph() (in module networkx.generators.classic)": [[1151, "networkx.generators.classic.complete_multipartite_graph"]], "cycle_graph() (in module networkx.generators.classic)": [[1152, "networkx.generators.classic.cycle_graph"]], "dorogovtsev_goltsev_mendes_graph() (in module networkx.generators.classic)": [[1153, "networkx.generators.classic.dorogovtsev_goltsev_mendes_graph"]], "empty_graph() (in module networkx.generators.classic)": [[1154, "networkx.generators.classic.empty_graph"]], "full_rary_tree() (in module networkx.generators.classic)": [[1155, "networkx.generators.classic.full_rary_tree"]], "ladder_graph() (in module networkx.generators.classic)": [[1156, "networkx.generators.classic.ladder_graph"]], "lollipop_graph() (in module networkx.generators.classic)": [[1157, "networkx.generators.classic.lollipop_graph"]], "null_graph() (in module networkx.generators.classic)": [[1158, "networkx.generators.classic.null_graph"]], "path_graph() (in module networkx.generators.classic)": [[1159, "networkx.generators.classic.path_graph"]], "star_graph() (in module networkx.generators.classic)": [[1160, "networkx.generators.classic.star_graph"]], "trivial_graph() (in module networkx.generators.classic)": [[1161, "networkx.generators.classic.trivial_graph"]], "turan_graph() (in module networkx.generators.classic)": [[1162, "networkx.generators.classic.turan_graph"]], "wheel_graph() (in module networkx.generators.classic)": [[1163, "networkx.generators.classic.wheel_graph"]], "random_cograph() (in module networkx.generators.cographs)": [[1164, "networkx.generators.cographs.random_cograph"]], "lfr_benchmark_graph() (in module networkx.generators.community)": [[1165, "networkx.generators.community.LFR_benchmark_graph"]], "caveman_graph() (in module networkx.generators.community)": [[1166, "networkx.generators.community.caveman_graph"]], "connected_caveman_graph() (in module networkx.generators.community)": [[1167, "networkx.generators.community.connected_caveman_graph"]], "gaussian_random_partition_graph() (in module networkx.generators.community)": [[1168, "networkx.generators.community.gaussian_random_partition_graph"]], "planted_partition_graph() (in module networkx.generators.community)": [[1169, "networkx.generators.community.planted_partition_graph"]], "random_partition_graph() (in module networkx.generators.community)": [[1170, "networkx.generators.community.random_partition_graph"]], "relaxed_caveman_graph() (in module networkx.generators.community)": [[1171, "networkx.generators.community.relaxed_caveman_graph"]], "ring_of_cliques() (in module networkx.generators.community)": [[1172, "networkx.generators.community.ring_of_cliques"]], "stochastic_block_model() (in module networkx.generators.community)": [[1173, "networkx.generators.community.stochastic_block_model"]], "windmill_graph() (in module networkx.generators.community)": [[1174, "networkx.generators.community.windmill_graph"]], "configuration_model() (in module networkx.generators.degree_seq)": [[1175, "networkx.generators.degree_seq.configuration_model"]], "degree_sequence_tree() (in module networkx.generators.degree_seq)": [[1176, "networkx.generators.degree_seq.degree_sequence_tree"]], "directed_configuration_model() (in module networkx.generators.degree_seq)": [[1177, "networkx.generators.degree_seq.directed_configuration_model"]], "directed_havel_hakimi_graph() (in module networkx.generators.degree_seq)": [[1178, "networkx.generators.degree_seq.directed_havel_hakimi_graph"]], "expected_degree_graph() (in module networkx.generators.degree_seq)": [[1179, "networkx.generators.degree_seq.expected_degree_graph"]], "havel_hakimi_graph() (in module networkx.generators.degree_seq)": [[1180, "networkx.generators.degree_seq.havel_hakimi_graph"]], "random_degree_sequence_graph() (in module networkx.generators.degree_seq)": [[1181, "networkx.generators.degree_seq.random_degree_sequence_graph"]], "gn_graph() (in module networkx.generators.directed)": [[1182, "networkx.generators.directed.gn_graph"]], "gnc_graph() (in module networkx.generators.directed)": [[1183, "networkx.generators.directed.gnc_graph"]], "gnr_graph() (in module networkx.generators.directed)": [[1184, "networkx.generators.directed.gnr_graph"]], "random_k_out_graph() (in module networkx.generators.directed)": [[1185, "networkx.generators.directed.random_k_out_graph"]], "scale_free_graph() (in module networkx.generators.directed)": [[1186, "networkx.generators.directed.scale_free_graph"]], "duplication_divergence_graph() (in module networkx.generators.duplication)": [[1187, "networkx.generators.duplication.duplication_divergence_graph"]], "partial_duplication_graph() (in module networkx.generators.duplication)": [[1188, "networkx.generators.duplication.partial_duplication_graph"]], "ego_graph() (in module networkx.generators.ego)": [[1189, "networkx.generators.ego.ego_graph"]], "chordal_cycle_graph() (in module networkx.generators.expanders)": [[1190, "networkx.generators.expanders.chordal_cycle_graph"]], "margulis_gabber_galil_graph() (in module networkx.generators.expanders)": [[1191, "networkx.generators.expanders.margulis_gabber_galil_graph"]], "paley_graph() (in module networkx.generators.expanders)": [[1192, "networkx.generators.expanders.paley_graph"]], "geographical_threshold_graph() (in module networkx.generators.geometric)": [[1193, "networkx.generators.geometric.geographical_threshold_graph"]], "geometric_edges() (in module networkx.generators.geometric)": [[1194, "networkx.generators.geometric.geometric_edges"]], "navigable_small_world_graph() (in module networkx.generators.geometric)": [[1195, "networkx.generators.geometric.navigable_small_world_graph"]], "random_geometric_graph() (in module networkx.generators.geometric)": [[1196, "networkx.generators.geometric.random_geometric_graph"]], "soft_random_geometric_graph() (in module networkx.generators.geometric)": [[1197, "networkx.generators.geometric.soft_random_geometric_graph"]], "thresholded_random_geometric_graph() (in module networkx.generators.geometric)": [[1198, "networkx.generators.geometric.thresholded_random_geometric_graph"]], "waxman_graph() (in module networkx.generators.geometric)": [[1199, "networkx.generators.geometric.waxman_graph"]], "hkn_harary_graph() (in module networkx.generators.harary_graph)": [[1200, "networkx.generators.harary_graph.hkn_harary_graph"]], "hnm_harary_graph() (in module networkx.generators.harary_graph)": [[1201, "networkx.generators.harary_graph.hnm_harary_graph"]], "random_internet_as_graph() (in module networkx.generators.internet_as_graphs)": [[1202, "networkx.generators.internet_as_graphs.random_internet_as_graph"]], "general_random_intersection_graph() (in module networkx.generators.intersection)": [[1203, "networkx.generators.intersection.general_random_intersection_graph"]], "k_random_intersection_graph() (in module networkx.generators.intersection)": [[1204, "networkx.generators.intersection.k_random_intersection_graph"]], "uniform_random_intersection_graph() (in module networkx.generators.intersection)": [[1205, "networkx.generators.intersection.uniform_random_intersection_graph"]], "interval_graph() (in module networkx.generators.interval_graph)": [[1206, "networkx.generators.interval_graph.interval_graph"]], "directed_joint_degree_graph() (in module networkx.generators.joint_degree_seq)": [[1207, "networkx.generators.joint_degree_seq.directed_joint_degree_graph"]], "is_valid_directed_joint_degree() (in module networkx.generators.joint_degree_seq)": [[1208, "networkx.generators.joint_degree_seq.is_valid_directed_joint_degree"]], "is_valid_joint_degree() (in module networkx.generators.joint_degree_seq)": [[1209, "networkx.generators.joint_degree_seq.is_valid_joint_degree"]], "joint_degree_graph() (in module networkx.generators.joint_degree_seq)": [[1210, "networkx.generators.joint_degree_seq.joint_degree_graph"]], "grid_2d_graph() (in module networkx.generators.lattice)": [[1211, "networkx.generators.lattice.grid_2d_graph"]], "grid_graph() (in module networkx.generators.lattice)": [[1212, "networkx.generators.lattice.grid_graph"]], "hexagonal_lattice_graph() (in module networkx.generators.lattice)": [[1213, "networkx.generators.lattice.hexagonal_lattice_graph"]], "hypercube_graph() (in module networkx.generators.lattice)": [[1214, "networkx.generators.lattice.hypercube_graph"]], "triangular_lattice_graph() (in module networkx.generators.lattice)": [[1215, "networkx.generators.lattice.triangular_lattice_graph"]], "inverse_line_graph() (in module networkx.generators.line)": [[1216, "networkx.generators.line.inverse_line_graph"]], "line_graph() (in module networkx.generators.line)": [[1217, "networkx.generators.line.line_graph"]], "mycielski_graph() (in module networkx.generators.mycielski)": [[1218, "networkx.generators.mycielski.mycielski_graph"]], "mycielskian() (in module networkx.generators.mycielski)": [[1219, "networkx.generators.mycielski.mycielskian"]], "nonisomorphic_trees() (in module networkx.generators.nonisomorphic_trees)": [[1220, "networkx.generators.nonisomorphic_trees.nonisomorphic_trees"]], "number_of_nonisomorphic_trees() (in module networkx.generators.nonisomorphic_trees)": [[1221, "networkx.generators.nonisomorphic_trees.number_of_nonisomorphic_trees"]], "random_clustered_graph() (in module networkx.generators.random_clustered)": [[1222, "networkx.generators.random_clustered.random_clustered_graph"]], "barabasi_albert_graph() (in module networkx.generators.random_graphs)": [[1223, "networkx.generators.random_graphs.barabasi_albert_graph"]], "binomial_graph() (in module networkx.generators.random_graphs)": [[1224, "networkx.generators.random_graphs.binomial_graph"]], "connected_watts_strogatz_graph() (in module networkx.generators.random_graphs)": [[1225, "networkx.generators.random_graphs.connected_watts_strogatz_graph"]], "dense_gnm_random_graph() (in module networkx.generators.random_graphs)": [[1226, "networkx.generators.random_graphs.dense_gnm_random_graph"]], "dual_barabasi_albert_graph() (in module networkx.generators.random_graphs)": [[1227, "networkx.generators.random_graphs.dual_barabasi_albert_graph"]], "erdos_renyi_graph() (in module networkx.generators.random_graphs)": [[1228, "networkx.generators.random_graphs.erdos_renyi_graph"]], "extended_barabasi_albert_graph() (in module networkx.generators.random_graphs)": [[1229, "networkx.generators.random_graphs.extended_barabasi_albert_graph"]], "fast_gnp_random_graph() (in module networkx.generators.random_graphs)": [[1230, "networkx.generators.random_graphs.fast_gnp_random_graph"]], "gnm_random_graph() (in module networkx.generators.random_graphs)": [[1231, "networkx.generators.random_graphs.gnm_random_graph"]], "gnp_random_graph() (in module networkx.generators.random_graphs)": [[1232, "networkx.generators.random_graphs.gnp_random_graph"]], "newman_watts_strogatz_graph() (in module networkx.generators.random_graphs)": [[1233, "networkx.generators.random_graphs.newman_watts_strogatz_graph"]], "powerlaw_cluster_graph() (in module networkx.generators.random_graphs)": [[1234, "networkx.generators.random_graphs.powerlaw_cluster_graph"]], "random_kernel_graph() (in module networkx.generators.random_graphs)": [[1235, "networkx.generators.random_graphs.random_kernel_graph"]], "random_lobster() (in module networkx.generators.random_graphs)": [[1236, "networkx.generators.random_graphs.random_lobster"]], "random_powerlaw_tree() (in module networkx.generators.random_graphs)": [[1237, "networkx.generators.random_graphs.random_powerlaw_tree"]], "random_powerlaw_tree_sequence() (in module networkx.generators.random_graphs)": [[1238, "networkx.generators.random_graphs.random_powerlaw_tree_sequence"]], "random_regular_graph() (in module networkx.generators.random_graphs)": [[1239, "networkx.generators.random_graphs.random_regular_graph"]], "random_shell_graph() (in module networkx.generators.random_graphs)": [[1240, "networkx.generators.random_graphs.random_shell_graph"]], "watts_strogatz_graph() (in module networkx.generators.random_graphs)": [[1241, "networkx.generators.random_graphs.watts_strogatz_graph"]], "lcf_graph() (in module networkx.generators.small)": [[1242, "networkx.generators.small.LCF_graph"]], "bull_graph() (in module networkx.generators.small)": [[1243, "networkx.generators.small.bull_graph"]], "chvatal_graph() (in module networkx.generators.small)": [[1244, "networkx.generators.small.chvatal_graph"]], "cubical_graph() (in module networkx.generators.small)": [[1245, "networkx.generators.small.cubical_graph"]], "desargues_graph() (in module networkx.generators.small)": [[1246, "networkx.generators.small.desargues_graph"]], "diamond_graph() (in module networkx.generators.small)": [[1247, "networkx.generators.small.diamond_graph"]], "dodecahedral_graph() (in module networkx.generators.small)": [[1248, "networkx.generators.small.dodecahedral_graph"]], "frucht_graph() (in module networkx.generators.small)": [[1249, "networkx.generators.small.frucht_graph"]], "heawood_graph() (in module networkx.generators.small)": [[1250, "networkx.generators.small.heawood_graph"]], "hoffman_singleton_graph() (in module networkx.generators.small)": [[1251, "networkx.generators.small.hoffman_singleton_graph"]], "house_graph() (in module networkx.generators.small)": [[1252, "networkx.generators.small.house_graph"]], "house_x_graph() (in module networkx.generators.small)": [[1253, "networkx.generators.small.house_x_graph"]], "icosahedral_graph() (in module networkx.generators.small)": [[1254, "networkx.generators.small.icosahedral_graph"]], "krackhardt_kite_graph() (in module networkx.generators.small)": [[1255, "networkx.generators.small.krackhardt_kite_graph"]], "moebius_kantor_graph() (in module networkx.generators.small)": [[1256, "networkx.generators.small.moebius_kantor_graph"]], "octahedral_graph() (in module networkx.generators.small)": [[1257, "networkx.generators.small.octahedral_graph"]], "pappus_graph() (in module networkx.generators.small)": [[1258, "networkx.generators.small.pappus_graph"]], "petersen_graph() (in module networkx.generators.small)": [[1259, "networkx.generators.small.petersen_graph"]], "sedgewick_maze_graph() (in module networkx.generators.small)": [[1260, "networkx.generators.small.sedgewick_maze_graph"]], "tetrahedral_graph() (in module networkx.generators.small)": [[1261, "networkx.generators.small.tetrahedral_graph"]], "truncated_cube_graph() (in module networkx.generators.small)": [[1262, "networkx.generators.small.truncated_cube_graph"]], "truncated_tetrahedron_graph() (in module networkx.generators.small)": [[1263, "networkx.generators.small.truncated_tetrahedron_graph"]], "tutte_graph() (in module networkx.generators.small)": [[1264, "networkx.generators.small.tutte_graph"]], "davis_southern_women_graph() (in module networkx.generators.social)": [[1265, "networkx.generators.social.davis_southern_women_graph"]], "florentine_families_graph() (in module networkx.generators.social)": [[1266, "networkx.generators.social.florentine_families_graph"]], "karate_club_graph() (in module networkx.generators.social)": [[1267, "networkx.generators.social.karate_club_graph"]], "les_miserables_graph() (in module networkx.generators.social)": [[1268, "networkx.generators.social.les_miserables_graph"]], "spectral_graph_forge() (in module networkx.generators.spectral_graph_forge)": [[1269, "networkx.generators.spectral_graph_forge.spectral_graph_forge"]], "stochastic_graph() (in module networkx.generators.stochastic)": [[1270, "networkx.generators.stochastic.stochastic_graph"]], "sudoku_graph() (in module networkx.generators.sudoku)": [[1271, "networkx.generators.sudoku.sudoku_graph"]], "prefix_tree() (in module networkx.generators.trees)": [[1272, "networkx.generators.trees.prefix_tree"]], "random_tree() (in module networkx.generators.trees)": [[1273, "networkx.generators.trees.random_tree"]], "triad_graph() (in module networkx.generators.triads)": [[1274, "networkx.generators.triads.triad_graph"]], "algebraic_connectivity() (in module networkx.linalg.algebraicconnectivity)": [[1275, "networkx.linalg.algebraicconnectivity.algebraic_connectivity"]], "fiedler_vector() (in module networkx.linalg.algebraicconnectivity)": [[1276, "networkx.linalg.algebraicconnectivity.fiedler_vector"]], "spectral_ordering() (in module networkx.linalg.algebraicconnectivity)": [[1277, "networkx.linalg.algebraicconnectivity.spectral_ordering"]], "attr_matrix() (in module networkx.linalg.attrmatrix)": [[1278, "networkx.linalg.attrmatrix.attr_matrix"]], "attr_sparse_matrix() (in module networkx.linalg.attrmatrix)": [[1279, "networkx.linalg.attrmatrix.attr_sparse_matrix"]], "bethe_hessian_matrix() (in module networkx.linalg.bethehessianmatrix)": [[1280, "networkx.linalg.bethehessianmatrix.bethe_hessian_matrix"]], "adjacency_matrix() (in module networkx.linalg.graphmatrix)": [[1281, "networkx.linalg.graphmatrix.adjacency_matrix"]], "incidence_matrix() (in module networkx.linalg.graphmatrix)": [[1282, "networkx.linalg.graphmatrix.incidence_matrix"]], "directed_combinatorial_laplacian_matrix() (in module networkx.linalg.laplacianmatrix)": [[1283, "networkx.linalg.laplacianmatrix.directed_combinatorial_laplacian_matrix"]], "directed_laplacian_matrix() (in module networkx.linalg.laplacianmatrix)": [[1284, "networkx.linalg.laplacianmatrix.directed_laplacian_matrix"]], "laplacian_matrix() (in module networkx.linalg.laplacianmatrix)": [[1285, "networkx.linalg.laplacianmatrix.laplacian_matrix"]], "normalized_laplacian_matrix() (in module networkx.linalg.laplacianmatrix)": [[1286, "networkx.linalg.laplacianmatrix.normalized_laplacian_matrix"]], "directed_modularity_matrix() (in module networkx.linalg.modularitymatrix)": [[1287, "networkx.linalg.modularitymatrix.directed_modularity_matrix"]], "modularity_matrix() (in module networkx.linalg.modularitymatrix)": [[1288, "networkx.linalg.modularitymatrix.modularity_matrix"]], "adjacency_spectrum() (in module networkx.linalg.spectrum)": [[1289, "networkx.linalg.spectrum.adjacency_spectrum"]], "bethe_hessian_spectrum() (in module networkx.linalg.spectrum)": [[1290, "networkx.linalg.spectrum.bethe_hessian_spectrum"]], "laplacian_spectrum() (in module networkx.linalg.spectrum)": [[1291, "networkx.linalg.spectrum.laplacian_spectrum"]], "modularity_spectrum() (in module networkx.linalg.spectrum)": [[1292, "networkx.linalg.spectrum.modularity_spectrum"]], "normalized_laplacian_spectrum() (in module networkx.linalg.spectrum)": [[1293, "networkx.linalg.spectrum.normalized_laplacian_spectrum"]], "convert_node_labels_to_integers() (in module networkx.relabel)": [[1294, "networkx.relabel.convert_node_labels_to_integers"]], "relabel_nodes() (in module networkx.relabel)": [[1295, "networkx.relabel.relabel_nodes"]], "__init__() (argmap method)": [[1296, "networkx.utils.decorators.argmap.__init__"]], "argmap (class in networkx.utils.decorators)": [[1296, "networkx.utils.decorators.argmap"]], "nodes_or_number() (in module networkx.utils.decorators)": [[1297, "networkx.utils.decorators.nodes_or_number"]], "not_implemented_for() (in module networkx.utils.decorators)": [[1298, "networkx.utils.decorators.not_implemented_for"]], "np_random_state() (in module networkx.utils.decorators)": [[1299, "networkx.utils.decorators.np_random_state"]], "open_file() (in module networkx.utils.decorators)": [[1300, "networkx.utils.decorators.open_file"]], "py_random_state() (in module networkx.utils.decorators)": [[1301, "networkx.utils.decorators.py_random_state"]], "mappedqueue (class in networkx.utils.mapped_queue)": [[1302, "networkx.utils.mapped_queue.MappedQueue"]], "__init__() (mappedqueue method)": [[1302, "networkx.utils.mapped_queue.MappedQueue.__init__"]], "arbitrary_element() (in module networkx.utils.misc)": [[1303, "networkx.utils.misc.arbitrary_element"]], "create_py_random_state() (in module networkx.utils.misc)": [[1304, "networkx.utils.misc.create_py_random_state"]], "create_random_state() (in module networkx.utils.misc)": [[1305, "networkx.utils.misc.create_random_state"]], "dict_to_numpy_array() (in module networkx.utils.misc)": [[1306, "networkx.utils.misc.dict_to_numpy_array"]], "edges_equal() (in module networkx.utils.misc)": [[1307, "networkx.utils.misc.edges_equal"]], "flatten() (in module networkx.utils.misc)": [[1308, "networkx.utils.misc.flatten"]], "graphs_equal() (in module networkx.utils.misc)": [[1309, "networkx.utils.misc.graphs_equal"]], "groups() (in module networkx.utils.misc)": [[1310, "networkx.utils.misc.groups"]], "make_list_of_ints() (in module networkx.utils.misc)": [[1311, "networkx.utils.misc.make_list_of_ints"]], "nodes_equal() (in module networkx.utils.misc)": [[1312, "networkx.utils.misc.nodes_equal"]], "pairwise() (in module networkx.utils.misc)": [[1313, "networkx.utils.misc.pairwise"]], "cumulative_distribution() (in module networkx.utils.random_sequence)": [[1314, "networkx.utils.random_sequence.cumulative_distribution"]], "discrete_sequence() (in module networkx.utils.random_sequence)": [[1315, "networkx.utils.random_sequence.discrete_sequence"]], "powerlaw_sequence() (in module networkx.utils.random_sequence)": [[1316, "networkx.utils.random_sequence.powerlaw_sequence"]], "random_weighted_sample() (in module networkx.utils.random_sequence)": [[1317, "networkx.utils.random_sequence.random_weighted_sample"]], "weighted_choice() (in module networkx.utils.random_sequence)": [[1318, "networkx.utils.random_sequence.weighted_choice"]], "zipf_rv() (in module networkx.utils.random_sequence)": [[1319, "networkx.utils.random_sequence.zipf_rv"]], "cuthill_mckee_ordering() (in module networkx.utils.rcm)": [[1320, "networkx.utils.rcm.cuthill_mckee_ordering"]], "reverse_cuthill_mckee_ordering() (in module networkx.utils.rcm)": [[1321, "networkx.utils.rcm.reverse_cuthill_mckee_ordering"]], "union() (unionfind method)": [[1322, "networkx.utils.union_find.UnionFind.union"]], "networkx.generators.atlas": [[1323, "module-networkx.generators.atlas"]], "networkx.generators.classic": [[1323, "module-networkx.generators.classic"]], "networkx.generators.cographs": [[1323, "module-networkx.generators.cographs"]], "networkx.generators.community": [[1323, "module-networkx.generators.community"]], "networkx.generators.degree_seq": [[1323, "module-networkx.generators.degree_seq"]], "networkx.generators.directed": [[1323, "module-networkx.generators.directed"]], "networkx.generators.duplication": [[1323, "module-networkx.generators.duplication"]], "networkx.generators.ego": [[1323, "module-networkx.generators.ego"]], "networkx.generators.expanders": [[1323, "module-networkx.generators.expanders"]], "networkx.generators.geometric": [[1323, "module-networkx.generators.geometric"]], "networkx.generators.harary_graph": [[1323, 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"PlanarEmbedding.connect_components", "PlanarEmbedding.copy", "PlanarEmbedding.degree", "PlanarEmbedding.edge_subgraph", "PlanarEmbedding.edges", "PlanarEmbedding.get_data", "PlanarEmbedding.get_edge_data", "PlanarEmbedding.has_edge", "PlanarEmbedding.has_node", "PlanarEmbedding.has_predecessor", "PlanarEmbedding.has_successor", "PlanarEmbedding.in_degree", "PlanarEmbedding.in_edges", "PlanarEmbedding.is_directed", "PlanarEmbedding.is_multigraph", "PlanarEmbedding.name", "PlanarEmbedding.nbunch_iter", "PlanarEmbedding.neighbors", "PlanarEmbedding.neighbors_cw_order", "PlanarEmbedding.next_face_half_edge", "PlanarEmbedding.nodes", "PlanarEmbedding.number_of_edges", "PlanarEmbedding.number_of_nodes", "PlanarEmbedding.order", "PlanarEmbedding.out_degree", "PlanarEmbedding.out_edges", "PlanarEmbedding.pred", "PlanarEmbedding.predecessors", "PlanarEmbedding.remove_edge", "PlanarEmbedding.remove_edges_from", "PlanarEmbedding.remove_node", "PlanarEmbedding.remove_nodes_from", 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523, 524, 561, 562, 563, 586, 619, 682, 691, 703, 704, 717, 730, 753, 762, 786, 1036, 1085, 1086, 1088, 1112, 1117, 1140, 1150, 1168, 1175, 1185, 1196, 1197, 1198, 1215, 1235, 1295, 1307, 1309, 1312, 1326, 1336, 1393, 1405, 1412, 1414, 1426], "posbm": 7, "xy": [7, 245], "212": 7, "518": [7, 17, 449], "plot_blockmodel": [7, 17], "convert": [8, 34, 50, 52, 54, 55, 56, 57, 58, 74, 75, 99, 102, 112, 169, 266, 267, 293, 375, 464, 565, 566, 615, 676, 679, 850, 895, 931, 934, 976, 979, 1038, 1085, 1097, 1098, 1099, 1166, 1167, 1273, 1281, 1296, 1297, 1299, 1301, 1306, 1310, 1325, 1332, 1333, 1336, 1337, 1338, 1342, 1345, 1346, 1347, 1348, 1349, 1350, 1353, 1356, 1357, 1361, 1362, 1363, 1364, 1370, 1371, 1376, 1379, 1403, 1404, 1406, 1409, 1411, 1412, 1413, 1416, 1421, 1426], "formula": [8, 299, 316, 322, 380, 385, 618, 688, 1421], "can": [8, 15, 24, 34, 38, 40, 43, 52, 54, 55, 56, 57, 58, 67, 69, 70, 71, 75, 76, 84, 88, 91, 92, 93, 94, 95, 96, 99, 100, 101, 102, 103, 105, 107, 110, 111, 112, 115, 125, 132, 141, 142, 143, 144, 151, 152, 156, 157, 158, 165, 168, 171, 176, 180, 184, 185, 189, 190, 193, 199, 200, 207, 220, 222, 224, 227, 229, 230, 231, 238, 239, 240, 243, 251, 260, 261, 262, 264, 278, 281, 282, 297, 298, 301, 302, 305, 306, 307, 308, 309, 315, 316, 324, 325, 329, 330, 332, 333, 337, 339, 340, 342, 344, 345, 346, 347, 353, 354, 357, 358, 361, 362, 374, 376, 380, 382, 383, 385, 387, 388, 389, 390, 394, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 422, 423, 427, 439, 440, 449, 454, 456, 458, 460, 461, 464, 465, 466, 471, 472, 473, 474, 475, 491, 492, 494, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 530, 540, 553, 575, 577, 581, 586, 588, 597, 598, 601, 602, 604, 615, 616, 617, 619, 626, 628, 629, 630, 633, 641, 643, 647, 652, 653, 654, 655, 657, 658, 660, 661, 662, 667, 668, 669, 676, 677, 678, 679, 680, 687, 688, 689, 690, 691, 720, 722, 723, 724, 725, 726, 729, 730, 731, 748, 749, 751, 762, 767, 770, 775, 786, 791, 796, 850, 853, 854, 855, 856, 857, 862, 865, 867, 870, 871, 873, 874, 878, 879, 882, 887, 888, 892, 895, 898, 899, 900, 901, 902, 907, 910, 912, 914, 916, 917, 921, 925, 928, 931, 934, 935, 936, 937, 938, 943, 946, 947, 948, 951, 952, 955, 956, 960, 963, 968, 973, 976, 979, 980, 981, 982, 983, 988, 991, 992, 993, 995, 998, 999, 1003, 1007, 1010, 1036, 1037, 1038, 1039, 1040, 1042, 1045, 1047, 1059, 1060, 1061, 1063, 1066, 1068, 1082, 1085, 1088, 1102, 1103, 1105, 1129, 1133, 1135, 1137, 1148, 1151, 1154, 1164, 1165, 1166, 1167, 1174, 1175, 1177, 1193, 1196, 1197, 1198, 1206, 1207, 1217, 1218, 1219, 1222, 1235, 1246, 1248, 1250, 1258, 1263, 1264, 1269, 1272, 1275, 1276, 1278, 1279, 1281, 1282, 1283, 1284, 1295, 1296, 1297, 1299, 1301, 1302, 1303, 1320, 1321, 1323, 1324, 1326, 1328, 1329, 1330, 1333, 1334, 1347, 1349, 1352, 1354, 1356, 1357, 1362, 1363, 1371, 1372, 1378, 1380, 1382, 1385, 1387, 1388, 1392, 1393, 1394, 1395, 1396, 1399, 1402, 1404, 1405, 1406, 1408, 1409, 1412, 1425, 1426], "more": [8, 43, 53, 67, 86, 92, 93, 94, 97, 99, 100, 101, 102, 103, 107, 109, 110, 111, 114, 115, 121, 127, 128, 143, 165, 172, 198, 199, 202, 204, 215, 216, 218, 219, 220, 221, 230, 231, 235, 256, 267, 277, 278, 281, 289, 299, 310, 314, 324, 325, 335, 338, 361, 378, 383, 385, 387, 389, 390, 392, 399, 405, 406, 407, 422, 427, 428, 432, 433, 437, 460, 464, 480, 520, 521, 559, 560, 581, 582, 583, 590, 593, 614, 619, 626, 631, 635, 653, 656, 660, 661, 662, 676, 679, 683, 691, 698, 699, 703, 711, 717, 718, 735, 737, 748, 760, 782, 786, 796, 862, 868, 886, 887, 890, 891, 907, 913, 924, 925, 926, 927, 943, 949, 967, 968, 971, 972, 988, 994, 1006, 1007, 1008, 1009, 1037, 1039, 1040, 1042, 1043, 1071, 1094, 1100, 1116, 1119, 1120, 1123, 1130, 1131, 1132, 1133, 1135, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1185, 1192, 1193, 1206, 1214, 1217, 1218, 1219, 1272, 1287, 1288, 1295, 1296, 1297, 1323, 1326, 1328, 1337, 1345, 1348, 1349, 1350, 1390, 1394, 1395, 1397, 1398, 1399, 1401, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426], "express": [8, 92, 110, 184, 315, 329, 330, 383, 384, 618, 619, 873, 916, 955, 998, 1199, 1287, 1326], "than": [8, 11, 34, 43, 55, 97, 99, 101, 102, 103, 115, 128, 142, 143, 144, 161, 199, 214, 215, 216, 218, 219, 221, 227, 231, 235, 241, 256, 277, 278, 281, 288, 289, 297, 298, 299, 304, 306, 307, 310, 311, 315, 316, 321, 324, 325, 326, 328, 329, 330, 341, 352, 358, 361, 374, 380, 381, 383, 384, 385, 387, 389, 390, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 425, 426, 429, 435, 464, 468, 469, 500, 527, 537, 559, 560, 581, 582, 583, 590, 625, 626, 635, 636, 652, 653, 656, 658, 659, 673, 676, 678, 679, 681, 683, 686, 690, 692, 693, 694, 698, 699, 711, 731, 735, 737, 748, 752, 761, 786, 887, 925, 947, 968, 992, 1007, 1038, 1042, 1043, 1060, 1102, 1135, 1146, 1154, 1162, 1165, 1167, 1172, 1174, 1185, 1187, 1194, 1198, 1226, 1230, 1231, 1236, 1237, 1238, 1239, 1275, 1276, 1296, 1297, 1326, 1328, 1345, 1348, 1349, 1350, 1353, 1354, 1358, 1365, 1366, 1379, 1382, 1395, 1402, 1404, 1405, 1408, 1413, 1423, 1425], "worst": [8, 210, 211, 212, 221, 228, 235, 264, 293, 294, 338, 345, 346, 347, 440, 513, 515, 516, 517, 518], "reus": [8, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 1131, 1132, 1138, 1139, 1140, 1141, 1142, 1328, 1402], "subcircuit": 8, "multipl": [8, 11, 25, 40, 45, 77, 93, 94, 99, 103, 107, 109, 143, 157, 158, 166, 175, 188, 195, 207, 287, 311, 357, 385, 386, 423, 443, 447, 458, 460, 464, 485, 486, 487, 594, 595, 597, 615, 616, 641, 643, 678, 690, 691, 697, 705, 738, 762, 786, 796, 856, 857, 863, 869, 877, 884, 892, 901, 902, 908, 923, 928, 937, 938, 944, 946, 950, 959, 960, 962, 963, 965, 973, 982, 983, 989, 991, 1002, 1003, 1005, 1010, 1037, 1039, 1040, 1045, 1046, 1102, 1103, 1105, 1127, 1135, 1137, 1216, 1217, 1219, 1285, 1291, 1296, 1298, 1326, 1352, 1378, 1393, 1405, 1406, 1412, 1413, 1417, 1425, 1426], "wherea": [8, 103, 682, 762, 786, 791, 1165, 1417], "cannot": [8, 101, 103, 127, 132, 199, 232, 300, 362, 394, 476, 581, 582, 583, 584, 632, 722, 887, 925, 934, 968, 979, 1007, 1043, 1165, 1208, 1209, 1296, 1298, 1302, 1303, 1326, 1345, 1347, 1348, 1349, 1350], "subformula": 8, "onc": [8, 38, 54, 55, 88, 93, 94, 99, 100, 112, 127, 199, 227, 230, 231, 232, 246, 247, 360, 374, 380, 388, 422, 423, 428, 488, 491, 492, 581, 582, 583, 652, 678, 679, 717, 718, 887, 925, 968, 1007, 1046, 1066, 1087, 1217, 1311, 1326, 1403, 1407], "thu": [8, 88, 101, 103, 115, 215, 216, 220, 256, 258, 331, 418, 419, 427, 428, 462, 477, 500, 512, 583, 679, 698, 699, 760, 762, 796, 1037, 1039, 1040, 1043, 1087, 1112, 1148, 1215, 1217, 1234, 1278, 1279, 1296, 1328, 1402, 1405, 1407], "wai": [8, 27, 52, 53, 55, 75, 86, 88, 93, 97, 99, 100, 101, 102, 103, 104, 107, 110, 115, 132, 152, 157, 158, 165, 184, 226, 281, 297, 298, 315, 330, 337, 356, 588, 598, 615, 618, 678, 691, 730, 760, 791, 796, 854, 856, 857, 862, 873, 899, 901, 902, 907, 915, 916, 935, 937, 938, 943, 955, 980, 982, 983, 988, 996, 998, 1037, 1039, 1040, 1041, 1097, 1165, 1213, 1215, 1217, 1239, 1262, 1269, 1272, 1326, 1328, 1330, 1393, 1394, 1404, 1406, 1411, 1426], "infeas": [8, 422], "circuit_to_formula": 8, "dag_to_branch": [8, 758, 1408], "transfer": [8, 202, 204, 230, 231, 469, 890, 891, 926, 927, 971, 972, 1008, 1009, 1420], "oper": [8, 30, 52, 95, 101, 112, 115, 168, 184, 189, 227, 374, 423, 460, 546, 547, 548, 552, 553, 554, 577, 595, 598, 601, 671, 672, 673, 674, 679, 680, 758, 786, 865, 873, 878, 910, 916, 946, 955, 960, 991, 998, 1036, 1068, 1088, 1103, 1164, 1218, 1219, 1295, 1302, 1319, 1323, 1325, 1326, 1393, 1394, 1400, 1404, 1405, 1406, 1407, 1408, 1411, 1412, 1413, 1414, 1417], "variabl": [8, 94, 132, 373, 530, 540, 618, 619, 732, 796, 1037, 1038, 1039, 1040, 1154, 1165, 1326, 1408, 1412, 1413, 1414, 1420], "formula_to_str": 8, "_to_str": 8, "root": [8, 67, 84, 293, 294, 338, 387, 389, 390, 394, 449, 460, 559, 577, 609, 671, 673, 678, 704, 728, 730, 739, 760, 791, 1119, 1120, 1125, 1126, 1145, 1147, 1235, 1271, 1272, 1323, 1365, 1366, 1393, 1406, 1407, 1408, 1412, 1413, 1423, 1425], "children": [8, 460, 577, 1145, 1155, 1272, 1365, 1366], "otherwis": [8, 92, 110, 146, 149, 171, 178, 184, 185, 198, 217, 230, 249, 250, 284, 297, 298, 303, 306, 307, 311, 315, 316, 322, 323, 324, 325, 326, 329, 330, 343, 353, 358, 393, 394, 395, 396, 397, 398, 410, 411, 412, 418, 419, 422, 425, 426, 462, 463, 464, 470, 479, 488, 490, 494, 495, 496, 498, 499, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 521, 555, 562, 563, 568, 572, 574, 584, 586, 588, 597, 601, 616, 618, 619, 633, 663, 673, 687, 688, 689, 696, 698, 699, 734, 735, 736, 737, 751, 848, 867, 873, 874, 886, 893, 912, 916, 917, 924, 929, 934, 948, 955, 956, 967, 974, 979, 993, 998, 999, 1006, 1068, 1091, 1135, 1137, 1165, 1185, 1197, 1217, 1270, 1282, 1283, 1284, 1307, 1309, 1312, 1342, 1356, 1357, 1376, 1409, 1413, 1426], "child": [8, 1147, 1272], "must": [8, 11, 93, 94, 95, 99, 100, 103, 110, 151, 152, 158, 161, 171, 204, 206, 207, 214, 215, 216, 219, 230, 231, 232, 252, 253, 257, 258, 259, 260, 261, 262, 264, 267, 268, 269, 271, 273, 276, 281, 285, 297, 298, 306, 307, 315, 316, 317, 318, 319, 324, 325, 327, 329, 330, 342, 361, 362, 363, 378, 382, 385, 391, 410, 411, 412, 413, 425, 429, 440, 471, 472, 473, 474, 475, 545, 546, 547, 548, 549, 550, 551, 553, 555, 556, 557, 558, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 577, 578, 579, 580, 584, 585, 586, 587, 588, 589, 593, 597, 599, 601, 602, 603, 604, 615, 626, 627, 632, 633, 635, 636, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 671, 672, 673, 674, 680, 690, 692, 698, 699, 707, 721, 734, 735, 736, 737, 789, 796, 853, 854, 857, 867, 891, 892, 898, 899, 902, 912, 928, 934, 938, 972, 973, 979, 983, 1010, 1037, 1038, 1039, 1040, 1063, 1071, 1085, 1102, 1133, 1137, 1146, 1162, 1165, 1173, 1176, 1186, 1188, 1190, 1193, 1197, 1199, 1209, 1213, 1217, 1219, 1235, 1239, 1240, 1270, 1275, 1276, 1277, 1278, 1279, 1295, 1296, 1298, 1307, 1309, 1310, 1311, 1312, 1315, 1333, 1337, 1338, 1339, 1340, 1359, 1361, 1362, 1363, 1364, 1365, 1366, 1376, 1393, 1394, 1395, 1407, 1426], "NOT": [8, 110, 199, 549, 550, 551, 748, 887, 925, 968, 1007], "util": [8, 14, 36, 44, 45, 93, 97, 102, 103, 229, 230, 231, 316, 374, 423, 425, 426, 429, 460, 496, 678, 679, 758, 1044, 1242, 1299, 1301, 1303, 1310, 1319, 1320, 1321, 1325, 1402, 1406, 1407, 1411, 1413, 1416, 1419], "arbitrary_el": [8, 1392, 1413], "nb": [8, 1331, 1334], "left": [8, 71, 115, 183, 311, 312, 322, 324, 325, 385, 559, 560, 584, 616, 688, 689, 739, 1106, 1134, 1136, 1146, 1179, 1206, 1280, 1355, 1358, 1404], "right": [8, 71, 110, 111, 115, 152, 206, 322, 385, 427, 428, 500, 559, 560, 584, 585, 587, 588, 615, 616, 688, 689, 739, 854, 935, 980, 1134, 1136, 1146, 1155, 1157, 1179, 1206, 1213, 1215, 1270, 1280], "littl": [8, 94, 298, 307], "mislead": 8, "That": [8, 97, 132, 165, 212, 221, 227, 295, 385, 436, 465, 525, 535, 555, 588, 657, 671, 672, 673, 674, 691, 704, 717, 791, 862, 907, 943, 988, 1046, 1162, 1210, 1296, 1388, 1404, 1409], "okai": 8, "becaus": [8, 11, 54, 69, 94, 99, 101, 102, 103, 112, 132, 161, 215, 216, 220, 255, 311, 378, 387, 389, 390, 394, 411, 412, 427, 494, 498, 499, 500, 510, 569, 585, 587, 615, 616, 632, 652, 934, 979, 1038, 1236, 1273, 1296, 1303, 1326, 1345, 1350, 1404, 1407, 1416], "AND": [8, 110, 598, 748, 762], "OR": [8, 110, 157, 175, 188, 856, 869, 877, 901, 937, 947, 950, 959, 982, 992], "symmetr": [8, 145, 148, 237, 545, 586, 593, 761, 1173, 1192, 1235, 1246, 1250, 1251, 1256, 1258, 1269, 1320, 1321, 1387], "It": [8, 52, 56, 58, 92, 93, 94, 97, 99, 101, 102, 104, 107, 110, 112, 115, 132, 172, 184, 207, 214, 215, 216, 229, 230, 231, 249, 260, 261, 262, 264, 278, 310, 316, 324, 325, 326, 343, 346, 347, 351, 353, 412, 414, 415, 416, 417, 418, 419, 429, 438, 440, 452, 457, 464, 480, 496, 500, 508, 530, 540, 545, 559, 560, 565, 566, 567, 582, 588, 594, 595, 598, 600, 601, 615, 619, 628, 629, 630, 652, 658, 659, 663, 671, 674, 692, 717, 718, 719, 760, 761, 762, 791, 796, 868, 873, 892, 913, 916, 928, 949, 955, 973, 994, 998, 1010, 1012, 1013, 1018, 1037, 1038, 1039, 1040, 1054, 1117, 1170, 1174, 1200, 1201, 1206, 1207, 1210, 1217, 1223, 1227, 1234, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1253, 1254, 1258, 1261, 1263, 1264, 1269, 1275, 1276, 1277, 1280, 1296, 1297, 1323, 1324, 1326, 1328, 1343, 1382, 1383, 1393, 1395, 1398, 1402, 1404, 1407, 1408, 1409, 1411, 1412, 1413, 1426], "just": [8, 99, 102, 103, 104, 184, 199, 338, 374, 439, 464, 559, 560, 577, 660, 661, 662, 692, 791, 873, 887, 916, 925, 946, 955, 960, 968, 991, 998, 1007, 1120, 1126, 1229, 1278, 1279, 1296, 1328, 1393, 1404, 1406], "operand": 8, "predict": [8, 567, 568, 569, 570, 571, 572, 573, 574, 591, 592, 758, 1325, 1402, 1406, 1412], "henc": [8, 168, 189, 521, 865, 878, 910, 946, 960, 991, 1059, 1202, 1383], "doe": [8, 77, 93, 94, 99, 101, 102, 103, 104, 114, 115, 132, 147, 153, 154, 165, 168, 189, 207, 208, 227, 228, 229, 230, 231, 232, 293, 308, 339, 340, 342, 343, 352, 357, 373, 382, 385, 410, 414, 426, 450, 469, 494, 495, 496, 497, 498, 499, 500, 502, 503, 506, 507, 509, 510, 511, 512, 534, 544, 549, 550, 551, 564, 566, 583, 584, 586, 589, 601, 612, 626, 627, 678, 691, 693, 694, 698, 699, 717, 718, 721, 722, 723, 724, 725, 726, 762, 862, 865, 878, 892, 907, 910, 928, 943, 946, 960, 973, 988, 991, 1010, 1038, 1043, 1066, 1070, 1072, 1081, 1102, 1103, 1105, 1106, 1107, 1109, 1114, 1173, 1175, 1177, 1192, 1207, 1222, 1223, 1227, 1229, 1234, 1241, 1296, 1300, 1303, 1326, 1333, 1334, 1341, 1342, 1344, 1351, 1353, 1354, 1355, 1356, 1357, 1358, 1371, 1379, 1380, 1381, 1383, 1393, 1404, 1405, 1406, 1410, 1417, 1426], "necessarili": [8, 99, 341, 451, 483, 559, 560, 641, 643, 1038, 1219], "behav": [8, 88, 103, 159, 190, 200, 220, 351, 858, 879, 888, 903, 939, 969, 984, 1229, 1296, 1395, 1404], "everi": [8, 11, 57, 88, 93, 109, 112, 120, 144, 157, 161, 177, 211, 212, 220, 221, 229, 230, 231, 235, 243, 264, 287, 295, 300, 324, 325, 343, 352, 380, 397, 437, 439, 440, 450, 462, 471, 472, 473, 474, 475, 477, 483, 484, 491, 512, 516, 565, 606, 614, 615, 619, 632, 633, 635, 636, 663, 685, 687, 688, 717, 718, 791, 856, 901, 937, 982, 1052, 1053, 1054, 1070, 1071, 1072, 1085, 1086, 1102, 1103, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1114, 1115, 1116, 1117, 1148, 1162, 1195, 1216, 1217, 1257, 1264, 1278, 1279, 1296, 1407], "left_subformula": 8, "right_subformula": 8, "in_degre": [8, 166, 188, 491, 678, 863, 877, 944, 959, 1177, 1207, 1208, 1404, 1406, 1407, 1426], "ha": [8, 11, 16, 44, 67, 88, 91, 93, 94, 95, 97, 99, 100, 101, 102, 103, 105, 107, 110, 112, 116, 120, 127, 152, 161, 165, 166, 173, 174, 175, 184, 188, 198, 207, 212, 214, 215, 219, 220, 226, 227, 229, 230, 231, 232, 235, 238, 239, 240, 241, 242, 243, 244, 247, 249, 252, 269, 271, 272, 273, 274, 275, 276, 282, 289, 291, 293, 294, 295, 300, 305, 310, 324, 331, 343, 352, 355, 356, 363, 364, 365, 373, 378, 380, 381, 383, 384, 385, 386, 391, 393, 394, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 424, 427, 428, 429, 439, 450, 458, 460, 466, 467, 468, 471, 472, 473, 474, 475, 476, 477, 480, 491, 492, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 522, 564, 566, 577, 578, 581, 590, 593, 605, 607, 610, 611, 622, 623, 624, 628, 629, 630, 632, 633, 634, 635, 636, 638, 646, 647, 649, 652, 657, 658, 682, 688, 690, 692, 697, 711, 717, 718, 729, 730, 731, 739, 749, 786, 791, 854, 862, 863, 869, 873, 877, 886, 892, 899, 907, 908, 916, 924, 928, 935, 943, 944, 948, 950, 955, 959, 967, 973, 980, 988, 989, 993, 998, 1006, 1010, 1040, 1043, 1045, 1066, 1068, 1070, 1072, 1075, 1080, 1084, 1098, 1099, 1101, 1102, 1103, 1105, 1122, 1130, 1145, 1154, 1160, 1162, 1165, 1176, 1180, 1185, 1193, 1195, 1196, 1197, 1198, 1199, 1207, 1210, 1211, 1215, 1217, 1222, 1234, 1239, 1243, 1244, 1248, 1249, 1254, 1259, 1261, 1264, 1267, 1269, 1270, 1272, 1275, 1276, 1277, 1278, 1279, 1281, 1282, 1283, 1284, 1285, 1286, 1289, 1291, 1293, 1296, 1300, 1326, 1328, 1330, 1333, 1334, 1353, 1354, 1371, 1372, 1379, 1382, 1393, 1394, 1395, 1398, 1403, 1404, 1405, 1406, 1407, 1409, 1413, 1414, 1416, 1423, 1425], "output": [8, 13, 16, 89, 93, 101, 102, 103, 109, 197, 287, 288, 345, 374, 380, 494, 498, 499, 509, 510, 575, 588, 677, 678, 691, 722, 1045, 1193, 1197, 1199, 1269, 1296, 1326, 1334, 1341, 1344, 1355, 1358, 1399, 1402, 1404, 1406, 1411, 1413, 1414, 1426], "two": [8, 11, 16, 27, 34, 38, 43, 54, 55, 57, 58, 65, 67, 71, 88, 93, 95, 99, 100, 102, 109, 112, 114, 115, 120, 132, 151, 171, 175, 184, 185, 188, 202, 207, 211, 212, 213, 214, 215, 216, 217, 220, 221, 226, 227, 230, 231, 232, 245, 249, 251, 252, 253, 257, 258, 260, 261, 262, 265, 269, 270, 271, 272, 273, 274, 275, 276, 282, 285, 286, 287, 289, 305, 311, 315, 316, 322, 326, 329, 330, 337, 341, 343, 345, 351, 352, 358, 359, 377, 380, 381, 383, 391, 411, 412, 419, 423, 428, 429, 430, 431, 442, 443, 444, 445, 447, 452, 453, 454, 457, 462, 471, 472, 473, 474, 475, 476, 480, 491, 494, 498, 499, 500, 502, 503, 506, 508, 509, 510, 511, 521, 545, 549, 550, 551, 555, 559, 560, 561, 562, 563, 564, 565, 566, 568, 569, 572, 574, 578, 584, 585, 586, 587, 588, 593, 598, 605, 607, 608, 610, 611, 615, 619, 626, 627, 629, 632, 633, 635, 636, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 671, 672, 673, 674, 675, 676, 680, 692, 694, 731, 732, 738, 739, 760, 761, 762, 780, 786, 791, 796, 853, 867, 869, 873, 874, 877, 890, 892, 898, 912, 916, 917, 926, 928, 934, 946, 948, 950, 955, 956, 959, 960, 971, 973, 979, 991, 993, 998, 999, 1008, 1010, 1019, 1020, 1021, 1022, 1036, 1037, 1039, 1040, 1056, 1084, 1088, 1098, 1100, 1101, 1106, 1107, 1108, 1109, 1114, 1116, 1134, 1146, 1147, 1149, 1151, 1152, 1156, 1174, 1185, 1186, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1204, 1207, 1210, 1211, 1215, 1217, 1218, 1243, 1244, 1253, 1271, 1272, 1275, 1276, 1294, 1295, 1296, 1323, 1324, 1326, 1328, 1359, 1360, 1363, 1393, 1394, 1395, 1397, 1402, 1404, 1405, 1406, 1407, 1410, 1411, 1413, 1425], "layer": [8, 36, 55, 61, 67, 103, 438, 705, 1038, 1109, 1420], "third": [8, 102, 114, 249, 422, 467, 585, 587, 734, 736, 1217, 1226, 1262, 1263, 1326, 1407], "appear": [8, 83, 93, 95, 99, 100, 102, 179, 204, 230, 231, 238, 243, 246, 247, 277, 363, 364, 365, 378, 451, 452, 453, 455, 466, 470, 584, 585, 587, 588, 675, 679, 707, 730, 734, 736, 891, 972, 1036, 1088, 1102, 1136, 1150, 1152, 1154, 1157, 1159, 1187, 1188, 1277, 1282, 1323, 1324, 1345, 1348, 1349, 1350, 1382, 1407, 1413, 1414], "both": [8, 52, 55, 92, 93, 94, 100, 101, 102, 103, 115, 161, 164, 204, 214, 215, 216, 217, 240, 257, 258, 259, 264, 282, 286, 287, 289, 337, 358, 379, 383, 415, 417, 418, 419, 423, 427, 440, 470, 502, 506, 545, 575, 581, 598, 600, 601, 602, 603, 604, 605, 606, 607, 610, 611, 615, 621, 635, 636, 653, 654, 655, 676, 711, 720, 760, 761, 762, 782, 891, 972, 1020, 1036, 1066, 1075, 1080, 1084, 1088, 1097, 1120, 1126, 1144, 1165, 1189, 1192, 1199, 1207, 1210, 1211, 1213, 1215, 1282, 1296, 1326, 1328, 1358, 1363, 1364, 1387, 1393, 1395, 1402, 1413, 1416, 1417, 1425, 1426], "negat": 8, "sole": [8, 786, 1278, 1279, 1326], "fourth": [8, 230, 231, 1326, 1404], "digraph": [8, 10, 11, 16, 21, 25, 41, 45, 56, 61, 67, 69, 70, 82, 88, 101, 102, 115, 132, 151, 152, 156, 157, 158, 160, 162, 163, 165, 166, 168, 170, 171, 172, 175, 176, 185, 186, 187, 188, 189, 192, 193, 194, 195, 196, 198, 199, 202, 204, 207, 208, 216, 227, 229, 230, 231, 240, 246, 247, 299, 308, 314, 318, 319, 321, 327, 328, 334, 335, 336, 337, 339, 340, 342, 343, 388, 391, 393, 396, 397, 398, 399, 401, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 430, 431, 437, 450, 452, 453, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 481, 482, 492, 494, 495, 496, 497, 498, 499, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 513, 514, 518, 519, 523, 555, 566, 575, 576, 577, 588, 590, 613, 615, 623, 630, 636, 643, 644, 652, 656, 657, 658, 659, 663, 678, 688, 690, 693, 696, 697, 698, 699, 700, 701, 702, 706, 707, 708, 709, 711, 716, 717, 718, 719, 721, 722, 723, 724, 725, 726, 740, 741, 744, 745, 746, 747, 748, 749, 750, 752, 760, 789, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 904, 905, 906, 907, 908, 911, 912, 913, 915, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 935, 936, 937, 938, 940, 941, 942, 943, 949, 957, 958, 963, 964, 965, 966, 967, 968, 972, 973, 974, 975, 977, 978, 980, 981, 982, 983, 985, 986, 987, 988, 989, 994, 996, 1000, 1001, 1003, 1004, 1005, 1006, 1007, 1010, 1035, 1037, 1038, 1039, 1040, 1041, 1052, 1062, 1066, 1070, 1072, 1075, 1080, 1083, 1084, 1098, 1099, 1101, 1118, 1135, 1150, 1154, 1168, 1169, 1170, 1173, 1177, 1178, 1180, 1182, 1183, 1184, 1185, 1189, 1217, 1270, 1272, 1273, 1274, 1283, 1284, 1287, 1290, 1292, 1298, 1323, 1326, 1333, 1337, 1342, 1356, 1357, 1362, 1365, 1366, 1371, 1393, 1399, 1401, 1402, 1404, 1405, 1406, 1407, 1408, 1409, 1411, 1412, 1413, 1414, 1416, 1417, 1424, 1425, 1426], "add_nod": [8, 11, 26, 34, 69, 74, 89, 102, 157, 184, 246, 339, 340, 398, 422, 491, 492, 496, 504, 505, 508, 522, 523, 605, 607, 610, 611, 691, 796, 856, 873, 901, 916, 937, 955, 982, 998, 1037, 1039, 1040, 1086, 1275, 1326, 1345, 1407, 1408, 1417, 1426], "get_node_attribut": [8, 39, 44, 71, 1213, 1404], "600": [8, 10, 12], "font_siz": [8, 16, 21, 25, 32, 35, 38, 45, 46, 1133, 1134, 1136], "22": [8, 35, 64, 66, 383, 384, 1271, 1323, 1403, 1408, 1412, 1422], "multipartite_layout": [8, 36, 61, 67, 1412, 1414, 1420], "subset_kei": [8, 36, 61, 67, 1109], "equal": [8, 36, 81, 144, 214, 215, 216, 230, 231, 238, 269, 271, 273, 276, 288, 297, 298, 300, 303, 306, 307, 310, 311, 312, 315, 316, 320, 323, 324, 325, 329, 330, 331, 373, 410, 411, 412, 413, 418, 419, 428, 471, 474, 476, 491, 494, 495, 496, 498, 499, 502, 503, 504, 505, 506, 507, 508, 509, 510, 525, 535, 545, 552, 553, 554, 555, 568, 572, 605, 623, 657, 671, 672, 673, 674, 687, 688, 689, 690, 721, 722, 740, 741, 753, 761, 791, 1112, 1116, 1162, 1165, 1198, 1204, 1230, 1239, 1271, 1280, 1291, 1307, 1309, 1312, 1398, 1399], "151": [8, 17], "plot_circuit": [8, 17], "southern": [9, 1265], "women": [9, 1265, 1398, 1406], "unipartit": [9, 115, 258, 259, 358], "properti": [9, 11, 18, 22, 33, 63, 86, 101, 102, 103, 112, 134, 159, 161, 166, 168, 175, 176, 179, 184, 188, 189, 190, 200, 284, 285, 286, 287, 288, 363, 364, 365, 388, 476, 500, 545, 569, 619, 685, 858, 863, 865, 869, 870, 873, 877, 878, 879, 888, 903, 908, 910, 916, 939, 944, 946, 950, 951, 955, 959, 960, 969, 984, 989, 991, 998, 1085, 1086, 1122, 1134, 1136, 1193, 1202, 1217, 1219, 1269, 1283, 1284, 1326, 1328, 1383, 1398, 1405, 1406, 1407, 1408, 1413, 1417, 1426], "These": [9, 52, 58, 73, 79, 86, 93, 94, 105, 112, 336, 385, 494, 512, 559, 671, 673, 732, 748, 779, 786, 1038, 1045, 1047, 1323, 1326, 1385, 1387, 1392, 1394, 1395, 1397, 1399, 1404, 1405, 1411, 1426], "were": [9, 65, 88, 99, 101, 104, 215, 216, 220, 289, 305, 410, 437, 460, 588, 962, 1002, 1199, 1393, 1395, 1399, 1402, 1405, 1406, 1407, 1413, 1416], "et": [9, 210, 226, 227, 315, 316, 322, 330, 334, 337, 345, 352, 358, 373, 380, 381, 423, 425, 426, 451, 569, 591, 592, 681, 682, 684, 693, 1202], "al": [9, 210, 226, 227, 315, 316, 322, 330, 334, 337, 345, 352, 358, 373, 380, 381, 423, 425, 426, 451, 569, 591, 592, 681, 682, 684, 693, 1202, 1407, 1413], "1930": [9, 1396], "thei": [9, 54, 58, 65, 71, 92, 93, 94, 97, 99, 100, 101, 102, 103, 104, 105, 107, 112, 132, 151, 165, 207, 213, 220, 249, 285, 287, 288, 296, 297, 298, 301, 302, 306, 307, 308, 309, 351, 362, 374, 391, 396, 427, 451, 452, 453, 454, 464, 465, 471, 472, 473, 474, 475, 496, 504, 505, 508, 512, 546, 547, 548, 559, 560, 576, 583, 586, 588, 600, 604, 675, 676, 704, 717, 750, 760, 786, 853, 862, 892, 898, 907, 928, 934, 943, 962, 973, 979, 988, 1002, 1010, 1036, 1038, 1066, 1085, 1088, 1109, 1120, 1126, 1133, 1135, 1137, 1151, 1159, 1165, 1193, 1197, 1198, 1217, 1271, 1272, 1323, 1328, 1353, 1354, 1356, 1357, 1359, 1363, 1394, 1396, 1402, 1404, 1406, 1409, 1414, 1426], "repres": [9, 11, 26, 43, 52, 54, 57, 67, 92, 99, 107, 115, 230, 231, 265, 281, 283, 286, 287, 288, 291, 292, 338, 350, 361, 362, 363, 377, 378, 380, 381, 382, 385, 386, 391, 448, 452, 453, 455, 457, 460, 465, 466, 494, 495, 498, 499, 500, 502, 503, 506, 507, 509, 510, 521, 565, 577, 578, 579, 580, 586, 588, 609, 615, 618, 619, 656, 660, 664, 667, 676, 679, 691, 692, 695, 697, 698, 699, 700, 702, 728, 730, 731, 734, 736, 739, 752, 786, 791, 796, 1019, 1020, 1021, 1022, 1037, 1038, 1039, 1040, 1045, 1081, 1102, 1140, 1151, 1185, 1193, 1194, 1196, 1197, 1198, 1199, 1209, 1217, 1240, 1243, 1246, 1250, 1258, 1267, 1269, 1272, 1273, 1278, 1279, 1323, 1324, 1326, 1329, 1330, 1346, 1347, 1388, 1393, 1406], "observ": [9, 13, 132, 223, 1414, 1426], "attend": 9, "14": [9, 11, 16, 19, 25, 38, 44, 64, 66, 71, 229, 230, 231, 383, 384, 405, 406, 501, 619, 690, 1150, 1242, 1250, 1262, 1406, 1408, 1426], "event": [9, 25, 99, 100, 110, 1165, 1229, 1300], "18": [9, 44, 64, 66, 93, 324, 325, 345, 383, 384, 618, 1169, 1249, 1255, 1258, 1260, 1263, 1269, 1393, 1406, 1416, 1417, 1421, 1426], "bipartit": [9, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 350, 351, 358, 377, 439, 440, 443, 581, 588, 758, 1043, 1106, 1151, 1203, 1204, 1205, 1265, 1325, 1395, 1398, 1399, 1400, 1401, 1406, 1407, 1411, 1413, 1417, 1421, 1425], "biadjac": [9, 282, 283, 1400, 1406], "7": [9, 12, 14, 19, 25, 35, 44, 46, 63, 64, 65, 66, 68, 89, 99, 101, 102, 115, 125, 151, 158, 170, 171, 192, 207, 232, 268, 297, 299, 314, 322, 327, 332, 333, 339, 340, 342, 362, 374, 380, 391, 403, 410, 413, 414, 415, 423, 424, 425, 426, 441, 445, 446, 483, 496, 501, 508, 511, 512, 555, 581, 586, 618, 619, 630, 652, 658, 663, 671, 674, 680, 695, 703, 706, 707, 708, 730, 747, 750, 761, 796, 853, 857, 866, 867, 881, 892, 898, 902, 911, 912, 915, 920, 928, 934, 938, 947, 973, 979, 983, 992, 996, 1010, 1037, 1039, 1040, 1052, 1053, 1085, 1100, 1104, 1148, 1212, 1242, 1248, 1250, 1251, 1255, 1258, 1260, 1273, 1323, 1326, 1330, 1339, 1340, 1345, 1348, 1349, 1350, 1382, 1392, 1394, 1402, 1403, 1405, 1408, 1409, 1410, 1411, 1412, 1413, 1426], "12": [9, 11, 19, 25, 44, 50, 55, 58, 64, 65, 66, 89, 91, 93, 229, 230, 231, 265, 345, 380, 381, 392, 399, 405, 406, 407, 449, 486, 501, 516, 568, 572, 574, 606, 616, 1052, 1053, 1054, 1133, 1136, 1150, 1244, 1245, 1249, 1254, 1257, 1263, 1335, 1406, 1408, 1412, 1426], "9": [9, 11, 12, 19, 25, 35, 44, 46, 63, 64, 65, 66, 68, 82, 89, 101, 102, 111, 115, 125, 232, 293, 295, 339, 340, 342, 346, 347, 356, 374, 380, 405, 406, 424, 438, 449, 494, 496, 501, 504, 505, 508, 545, 566, 581, 586, 676, 706, 707, 708, 761, 1100, 1104, 1148, 1150, 1194, 1199, 1212, 1217, 1235, 1246, 1255, 1267, 1273, 1283, 1284, 1323, 1326, 1328, 1396, 1403, 1412, 1413, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426], "11": [9, 25, 33, 44, 64, 65, 66, 68, 89, 102, 110, 115, 157, 210, 239, 240, 297, 298, 303, 306, 307, 323, 392, 399, 405, 406, 407, 413, 415, 417, 422, 501, 514, 517, 606, 618, 680, 721, 738, 856, 901, 937, 982, 1052, 1053, 1054, 1100, 1150, 1287, 1403, 1410, 1413, 1414, 1419, 1424, 1425, 1426], "13": [9, 11, 38, 44, 64, 66, 89, 91, 156, 229, 230, 231, 343, 501, 703, 855, 900, 936, 981, 1150, 1192, 1406, 1420, 1426], "16": [9, 19, 31, 44, 45, 64, 66, 70, 229, 230, 231, 346, 347, 387, 389, 390, 394, 453, 508, 511, 512, 519, 571, 592, 606, 748, 749, 750, 1109, 1205, 1256, 1271, 1286, 1323, 1406, 1411, 1426], "17": [9, 21, 44, 64, 66, 103, 229, 230, 231, 297, 508, 680, 693, 1405, 1406, 1426], "friend": [9, 545, 1407, 1412], "member": [9, 92, 93, 94, 100, 112, 315, 317, 318, 319, 330, 391, 483, 484, 586, 691, 1222, 1267, 1403], "evelyn": 9, "jefferson": 9, "laura": 9, "mandevil": 9, "theresa": 9, "anderson": 9, "brenda": 9, "roger": 9, "charlott": 9, "mcdowd": 9, "franc": 9, "eleanor": 9, "nye": 9, "pearl": [9, 132], "oglethorp": 9, "ruth": 9, "desand": 9, "vern": 9, "sanderson": 9, "myra": 9, "liddel": 9, "katherina": 9, "sylvia": 9, "avondal": 9, "nora": 9, "fayett": 9, "helen": 9, "lloyd": 9, "dorothi": 9, "murchison": 9, "olivia": 9, "carleton": 9, "flora": 9, "price": 9, "meet": [9, 94, 1165, 1196, 1197, 1198], "50": [9, 25, 30, 34, 40, 50, 54, 55, 56, 57, 64, 65, 272, 312, 1117, 1193, 1197, 1198, 1251, 1297, 1302], "45": [9, 58, 64, 110, 226, 300, 409, 1175], "57": [9, 64], "46": [9, 64, 235, 564, 619, 1264], "24": [9, 19, 37, 64, 66, 68, 103, 383, 384, 496, 505, 508, 703, 1212, 1229, 1244, 1262, 1271, 1403], "32": [9, 64, 66, 68, 209, 211, 212, 383, 384, 564, 703, 1403, 1411], "36": [9, 21, 64, 68, 752, 1150, 1262, 1271, 1353, 1354, 1379, 1403], "31": [9, 64, 66, 229, 230, 231, 260, 261, 262, 289, 383, 384, 409, 703, 1226, 1235, 1403], "40": [9, 50, 64, 80, 101, 297, 300, 555, 672, 1173, 1240, 1271], "38": [9, 64, 688, 1271], "33": [9, 58, 64, 66, 68, 93, 383, 384, 500, 514, 703, 1267, 1271, 1403, 1414], "37": [9, 17, 56, 64, 68, 303, 311, 312, 323, 324, 325, 496, 508, 1039, 1040, 1271, 1393, 1403, 1408, 1425], "43": [9, 64, 324, 325, 606, 1244, 1271], "34": [9, 64, 68, 331, 508, 762, 1271, 1403], "algorithm": [9, 14, 15, 44, 52, 54, 88, 93, 94, 95, 96, 102, 103, 107, 109, 110, 111, 112, 114, 115, 117, 120, 121, 122, 125, 127, 128, 132, 133, 136, 141, 151, 210, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 226, 227, 228, 229, 230, 231, 232, 235, 249, 251, 252, 253, 254, 255, 256, 258, 260, 261, 262, 263, 264, 265, 266, 267, 272, 275, 277, 278, 280, 282, 284, 285, 286, 287, 288, 289, 290, 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559, 560], "projected_graph": [9, 115, 284, 285, 286, 288, 351], "keep": [9, 92, 93, 94, 115, 204, 345, 346, 347, 362, 377, 387, 389, 390, 394, 583, 598, 693, 694, 891, 972, 1117, 1207, 1210, 1278, 1279, 1296, 1376, 1394, 1411, 1414], "co": [9, 26, 94, 99, 144, 752, 1326], "occur": [9, 93, 95, 100, 230, 231, 277, 278, 280, 383, 581, 582, 583, 588, 1043, 1117, 1120, 1126, 1282, 1296], "count": [9, 185, 237, 238, 242, 243, 245, 297, 298, 310, 315, 330, 360, 386, 443, 568, 597, 619, 749, 753, 874, 917, 944, 950, 956, 959, 999, 1060, 1179, 1278, 1279, 1406, 1407, 1416], "share": [9, 54, 58, 92, 94, 112, 165, 199, 214, 215, 216, 221, 278, 285, 287, 288, 294, 358, 359, 376, 418, 419, 460, 462, 480, 569, 578, 691, 732, 862, 887, 907, 925, 943, 968, 988, 1007, 1217, 1328], "contact": [9, 92, 688, 1195, 1326], "weighted_projected_graph": [9, 284, 285, 286, 287, 1417], "648": 9, "109": [9, 17, 494, 1173], "plot_davis_club": [9, 17], "retain": [10, 102, 110, 230, 284, 285, 286, 287, 288, 1100, 1187, 1295], "pattern": [10, 54, 93, 103, 236, 241, 244, 248, 385, 494, 519, 555, 671, 672, 673, 674, 690, 691, 693, 762, 786, 1036, 1088, 1388, 1413], "add": [10, 11, 26, 34, 41, 45, 49, 52, 61, 71, 88, 89, 91, 93, 94, 101, 102, 105, 106, 115, 151, 152, 153, 154, 156, 157, 158, 164, 207, 222, 223, 229, 282, 285, 341, 374, 411, 412, 423, 428, 430, 431, 450, 460, 581, 582, 583, 589, 614, 615, 618, 619, 654, 690, 701, 717, 718, 796, 850, 853, 854, 855, 856, 857, 892, 895, 898, 899, 900, 901, 902, 928, 931, 934, 935, 936, 937, 938, 973, 976, 979, 980, 981, 982, 983, 984, 1010, 1037, 1038, 1039, 1040, 1042, 1049, 1052, 1053, 1054, 1100, 1154, 1165, 1172, 1185, 1207, 1210, 1217, 1219, 1233, 1234, 1236, 1302, 1326, 1353, 1354, 1356, 1357, 1379, 1380, 1383, 1393, 1394, 1395, 1398, 1404, 1406, 1407, 1408, 1409, 1411, 1412, 1413, 1414, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426], "compressor": [10, 690, 786], "do": [10, 55, 75, 88, 92, 93, 94, 96, 99, 101, 102, 106, 107, 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69, 93, 598, 1133, 1134, 1136, 1412, 1413, 1414, 1416, 1426], "ax1": [10, 15, 27, 50, 82], "number_of_edg": [10, 15, 25, 28, 198, 690, 886, 924, 967, 1006, 1059, 1154, 1271, 1406, 1407, 1426], "nonexp_graph": 10, "compression_nod": 10, "summar": [10, 15, 100, 101, 690, 691, 758, 791, 1325, 1328, 1413], "dedensifi": [10, 758], "threshold": [10, 57, 83, 112, 220, 229, 231, 380, 381, 690, 692, 695, 696, 758, 786, 1117, 1193, 1194, 1196, 1197, 1198, 1325, 1398, 1406, 1407, 1408, 1412, 1414], "copi": [10, 16, 38, 44, 93, 95, 106, 167, 196, 199, 202, 203, 204, 205, 284, 285, 286, 287, 288, 341, 388, 390, 392, 406, 433, 434, 435, 436, 437, 453, 460, 469, 521, 584, 585, 587, 596, 599, 602, 603, 605, 606, 607, 610, 611, 613, 614, 633, 636, 690, 864, 885, 887, 890, 891, 909, 925, 926, 927, 945, 963, 966, 968, 971, 972, 990, 1003, 1007, 1008, 1009, 1035, 1038, 1057, 1061, 1063, 1066, 1082, 1083, 1122, 1183, 1189, 1217, 1223, 1227, 1251, 1270, 1294, 1295, 1296, 1403, 1404, 1406, 1407, 1408, 1409, 1412, 1413, 1422, 1425], "nonexp_node_color": 10, "nonexp_node_s": 10, "yellow": [10, 15, 598, 760, 1426], "nonexp_po": 10, "75": [10, 34, 239, 260, 299, 314, 355, 356, 386, 682, 1169, 1170, 1171, 1173, 1404, 1408, 1426], "c_node": [10, 690], "spot": 10, "382": [10, 17], "plot_dedensif": [10, 17], "153": [11, 455], "curiou": 11, "let": [11, 55, 58, 93, 97, 101, 103, 217, 257, 280, 282, 299, 300, 313, 322, 371, 372, 383, 586, 619, 762, 1219, 1278, 1279, 1326, 1425], "defin": [11, 24, 52, 58, 69, 97, 112, 127, 213, 222, 223, 239, 240, 260, 261, 262, 263, 285, 289, 311, 316, 329, 334, 335, 345, 346, 347, 356, 385, 386, 390, 424, 425, 426, 429, 432, 433, 434, 435, 436, 437, 449, 464, 465, 466, 469, 494, 495, 498, 499, 500, 502, 503, 506, 507, 509, 510, 519, 567, 569, 570, 571, 573, 574, 575, 577, 586, 614, 615, 619, 621, 625, 652, 671, 673, 674, 676, 684, 685, 686, 687, 688, 689, 728, 730, 738, 751, 752, 753, 762, 791, 796, 1037, 1038, 1039, 1040, 1045, 1047, 1071, 1081, 1098, 1147, 1154, 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141, 142, 144, 152, 158, 193, 197, 208, 211, 212, 227, 229, 235, 236, 248, 249, 260, 264, 266, 269, 271, 273, 274, 276, 279, 281, 283, 284, 285, 286, 287, 288, 320, 329, 331, 338, 344, 351, 353, 357, 362, 363, 364, 365, 373, 378, 380, 381, 385, 439, 454, 455, 460, 462, 470, 477, 478, 480, 497, 511, 512, 513, 559, 560, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 576, 578, 579, 580, 588, 589, 590, 614, 615, 616, 622, 623, 659, 660, 661, 662, 676, 677, 678, 679, 681, 683, 684, 686, 690, 691, 693, 697, 698, 699, 700, 702, 703, 704, 706, 707, 708, 709, 728, 729, 730, 731, 732, 739, 748, 753, 761, 782, 786, 854, 857, 882, 899, 902, 921, 935, 938, 963, 980, 983, 1003, 1046, 1085, 1086, 1094, 1101, 1102, 1135, 1144, 1151, 1162, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1189, 1199, 1200, 1201, 1206, 1207, 1208, 1209, 1210, 1221, 1222, 1240, 1269, 1273, 1274, 1276, 1295, 1300, 1302, 1315, 1323, 1353, 1354, 1379, 1380, 1394, 1395, 1406], "digit": [11, 70, 99], "base": [11, 15, 38, 43, 55, 58, 69, 93, 94, 100, 101, 102, 103, 107, 128, 132, 199, 203, 205, 212, 216, 220, 229, 296, 297, 301, 302, 303, 308, 309, 310, 311, 312, 322, 323, 324, 325, 329, 330, 337, 343, 346, 347, 362, 371, 373, 374, 380, 381, 382, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 423, 425, 426, 427, 428, 430, 431, 449, 464, 466, 494, 498, 499, 500, 509, 510, 545, 555, 564, 566, 569, 574, 581, 614, 616, 660, 667, 680, 688, 691, 704, 706, 707, 708, 710, 711, 712, 713, 714, 715, 717, 732, 738, 758, 761, 762, 786, 791, 796, 887, 925, 934, 935, 968, 979, 980, 1007, 1036, 1037, 1038, 1041, 1043, 1082, 1088, 1182, 1229, 1235, 1253, 1267, 1296, 1320, 1321, 1323, 1326, 1383, 1387, 1392, 1395, 1402, 1403, 1404, 1406, 1407, 1408, 1409, 1411, 1412, 1421, 1425], "obtain": [11, 91, 165, 207, 282, 345, 346, 347, 380, 383, 387, 388, 389, 390, 394, 465, 511, 606, 618, 619, 656, 722, 742, 743, 760, 796, 862, 892, 907, 928, 943, 973, 988, 1010, 1037, 1039, 1040, 1164, 1253, 1272, 1278, 1279, 1323, 1326, 1356, 1357, 1402, 1426], "seri": [11, 444, 616, 680, 1215, 1286], "finit": [11, 462, 494, 495, 498, 499, 502, 503, 506, 507, 509, 510, 514, 518, 1177, 1179, 1192, 1222], "end": [11, 25, 36, 52, 95, 101, 106, 153, 154, 206, 215, 227, 267, 268, 300, 332, 333, 342, 371, 372, 427, 614, 618, 619, 626, 627, 631, 632, 634, 635, 636, 639, 640, 650, 651, 652, 653, 654, 655, 660, 664, 667, 677, 678, 680, 734, 736, 1038, 1061, 1066, 1075, 1080, 1082, 1084, 1117, 1133, 1135, 1152, 1165, 1206, 1229, 1326, 1333, 1334, 1337, 1338, 1339, 1340, 1342, 1344, 1350, 1353, 1357, 1358, 1368, 1371, 1372, 1375, 1376, 1379, 1404, 1413], "In": [11, 16, 27, 43, 54, 57, 58, 88, 92, 93, 94, 95, 97, 99, 100, 101, 103, 110, 115, 127, 132, 133, 175, 184, 199, 217, 229, 230, 231, 235, 240, 257, 258, 259, 278, 283, 286, 288, 289, 299, 311, 312, 324, 325, 329, 350, 357, 378, 379, 380, 410, 413, 414, 415, 422, 429, 443, 447, 450, 458, 460, 494, 498, 499, 501, 510, 565, 568, 572, 574, 590, 591, 615, 619, 621, 652, 653, 654, 657, 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1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426], "108": [11, 1216], "513": [11, 1398, 1406], "reach": [11, 99, 100, 314, 324, 327, 376, 383, 387, 389, 390, 394, 410, 411, 412, 418, 419, 494, 498, 499, 510, 564, 566, 626, 627, 632, 640, 643, 652, 693, 711, 758, 1188, 1207, 1210, 1407], "orbit": 11, "up": [11, 70, 80, 93, 94, 97, 99, 100, 101, 104, 107, 132, 133, 346, 347, 377, 423, 427, 509, 530, 540, 577, 619, 652, 653, 657, 748, 1036, 1038, 1061, 1066, 1082, 1088, 1102, 1144, 1148, 1173, 1213, 1215, 1272, 1326, 1328, 1355, 1358, 1395, 1396, 1402, 1404, 1406, 1410, 1411, 1413, 1414, 1416, 1417, 1420, 1426], "reveal": [11, 711, 786], "maximum": [11, 112, 115, 209, 210, 211, 212, 214, 215, 217, 222, 224, 227, 257, 259, 264, 277, 278, 279, 281, 288, 296, 304, 311, 312, 315, 316, 317, 318, 319, 321, 324, 328, 330, 339, 341, 342, 343, 346, 347, 352, 356, 361, 373, 377, 380, 382, 383, 385, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 428, 440, 472, 473, 494, 498, 499, 500, 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215, 229, 230, 231, 261, 262, 375, 423, 425, 426, 460, 678, 679, 691, 1217], "confus": [15, 101, 102, 165, 691, 862, 907, 943, 988, 1196, 1197, 1198, 1398, 1406, 1412], "stanford": [15, 34, 65, 69, 71, 566, 691, 1268], "analysi": [15, 23, 47, 50, 52, 55, 86, 100, 101, 103, 105, 107, 110, 228, 232, 257, 258, 259, 260, 261, 262, 286, 288, 289, 299, 305, 379, 383, 412, 431, 437, 462, 494, 500, 619, 691, 751, 758, 760, 762, 1042, 1201, 1233, 1325, 1405, 1409, 1410, 1412, 1414], "uniqu": [15, 27, 238, 255, 278, 311, 312, 378, 460, 464, 469, 559, 560, 565, 585, 587, 600, 604, 618, 619, 641, 643, 691, 732, 748, 934, 979, 1047, 1244, 1250, 1251, 1296, 1326, 1343, 1359, 1360, 1363, 1364, 1426], "combin": [15, 61, 102, 204, 207, 379, 380, 385, 411, 412, 416, 418, 423, 575, 598, 600, 604, 678, 691, 891, 892, 928, 973, 1010, 1387, 1408], "type": [15, 70, 93, 95, 97, 100, 101, 102, 103, 104, 110, 165, 208, 241, 242, 243, 244, 247, 266, 267, 269, 270, 271, 273, 274, 276, 282, 283, 296, 301, 302, 303, 308, 309, 315, 323, 350, 351, 429, 496, 549, 550, 551, 555, 584, 585, 587, 588, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 652, 658, 671, 672, 673, 674, 690, 691, 693, 695, 711, 722, 748, 749, 750, 786, 862, 907, 943, 988, 1041, 1043, 1047, 1087, 1091, 1092, 1093, 1094, 1097, 1098, 1099, 1100, 1101, 1102, 1104, 1105, 1110, 1118, 1145, 1146, 1147, 1148, 1150, 1152, 1154, 1155, 1157, 1159, 1160, 1163, 1175, 1177, 1178, 1180, 1182, 1183, 1184, 1190, 1191, 1192, 1200, 1201, 1202, 1211, 1213, 1215, 1217, 1222, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1252, 1253, 1254, 1255, 1256, 1257, 1259, 1260, 1261, 1262, 1263, 1264, 1273, 1278, 1279, 1281, 1298, 1325, 1326, 1332, 1333, 1336, 1337, 1338, 1342, 1345, 1348, 1349, 1350, 1356, 1357, 1358, 1370, 1371, 1382, 1386, 1390, 1393, 1395, 1404, 1406, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1417, 1425, 1426], "other": [15, 16, 24, 41, 43, 50, 52, 56, 57, 58, 83, 88, 91, 92, 93, 94, 97, 99, 100, 101, 102, 103, 104, 105, 107, 109, 110, 115, 132, 134, 165, 208, 214, 215, 216, 226, 230, 231, 232, 235, 256, 258, 264, 267, 268, 282, 288, 289, 294, 297, 298, 305, 316, 320, 322, 324, 325, 327, 352, 358, 366, 373, 396, 397, 428, 452, 453, 460, 462, 473, 491, 502, 503, 506, 507, 527, 537, 559, 560, 565, 588, 602, 632, 633, 635, 636, 641, 653, 660, 661, 662, 665, 666, 667, 668, 669, 675, 676, 688, 691, 701, 723, 724, 725, 726, 734, 735, 736, 737, 751, 752, 762, 789, 791, 796, 862, 907, 943, 948, 988, 993, 1037, 1038, 1039, 1040, 1042, 1054, 1102, 1103, 1114, 1116, 1133, 1145, 1147, 1151, 1154, 1165, 1174, 1180, 1186, 1194, 1195, 1197, 1198, 1222, 1229, 1269, 1278, 1279, 1281, 1286, 1289, 1291, 1293, 1296, 1302, 1324, 1325, 1326, 1328, 1337, 1338, 1339, 1345, 1348, 1349, 1350, 1382, 1383, 1394, 1396, 1398, 1403, 1404, 1405, 1406, 1407, 1408, 1410, 1411, 1412, 1413, 1414, 1417, 1425, 1426], "produc": [15, 44, 49, 103, 115, 226, 246, 247, 272, 280, 297, 298, 306, 307, 315, 316, 329, 330, 422, 460, 565, 601, 612, 629, 632, 633, 635, 636, 677, 678, 680, 691, 786, 1097, 1102, 1103, 1105, 1165, 1179, 1181, 1189, 1212, 1236, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1392, 1399, 1406, 1408, 1416, 1417], "infer": [15, 695, 1104, 1118, 1358, 1412], "differ": [15, 25, 27, 28, 33, 41, 53, 54, 57, 63, 71, 86, 92, 93, 94, 95, 99, 103, 112, 161, 164, 165, 204, 207, 215, 216, 223, 280, 282, 297, 298, 314, 315, 326, 330, 334, 335, 337, 341, 358, 361, 371, 372, 373, 374, 378, 410, 413, 414, 415, 435, 437, 509, 511, 512, 593, 602, 615, 704, 717, 718, 738, 750, 758, 772, 786, 862, 891, 892, 907, 928, 943, 972, 973, 988, 1010, 1102, 1105, 1133, 1165, 1169, 1170, 1171, 1193, 1198, 1207, 1255, 1269, 1287, 1296, 1326, 1365, 1366, 1382, 1394, 1404, 1405, 1406, 1413, 1414, 1425, 1426], "relat": [15, 34, 67, 92, 93, 95, 99, 100, 115, 129, 132, 220, 230, 297, 366, 370, 586, 588, 619, 688, 762, 767, 795, 1202, 1205, 1269, 1323, 1395, 1402, 1406, 1413, 1416, 1425], "strong": [15, 397, 511, 512, 517, 610, 619, 691, 699, 758, 1408], "weak": [15, 398, 691, 758, 1425], "number_of_nod": [15, 25, 80, 156, 187, 311, 324, 337, 383, 564, 581, 852, 855, 876, 897, 900, 919, 933, 936, 958, 978, 981, 1001, 1154, 1271, 1426], "7482934": 15, "_": [15, 16, 26, 38, 93, 105, 300, 333, 356, 372, 405, 406, 425, 426, 502, 503, 506, 507, 569, 588, 630, 1352, 1354, 1378, 1380, 1411], "edge_type_visual_weight_lookup": 15, "edge_weight": [15, 382, 583], "node_attribut": [15, 691], "edge_attribut": [15, 283, 691, 1101], "summary_graph": [15, 691], "snap_aggreg": [15, 758, 1413], "prefix": [15, 67, 512, 690, 691, 1272, 1326, 1347, 1413, 1421], "aggreg": [15, 511, 512, 691, 786], "summary_po": 15, "8375428": 15, "edge_typ": 15, "get_edge_data": [15, 25, 1411], "272": [15, 17], "plot_snap": [15, 17], "support": [16, 52, 77, 92, 93, 96, 100, 101, 102, 103, 226, 308, 322, 339, 340, 342, 343, 356, 373, 410, 411, 412, 418, 419, 464, 494, 496, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 597, 626, 627, 632, 633, 635, 636, 690, 738, 762, 775, 786, 796, 1037, 1038, 1039, 1040, 1114, 1116, 1146, 1302, 1326, 1341, 1342, 1344, 1353, 1354, 1355, 1356, 1357, 1358, 1379, 1380, 1381, 1383, 1387, 1394, 1395, 1396, 1398, 1402, 1404, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426], "unsupport": 16, "contain": [16, 25, 34, 45, 65, 69, 71, 88, 99, 102, 104, 114, 115, 151, 152, 157, 158, 165, 166, 167, 168, 172, 175, 176, 177, 180, 188, 189, 193, 195, 199, 207, 212, 214, 220, 226, 236, 237, 238, 240, 241, 243, 245, 248, 249, 252, 253, 255, 256, 257, 258, 259, 260, 264, 266, 267, 270, 277, 278, 280, 281, 290, 293, 294, 299, 315, 320, 322, 338, 344, 346, 347, 350, 352, 353, 355, 356, 357, 358, 360, 373, 377, 379, 380, 381, 388, 400, 408, 414, 415, 427, 432, 433, 437, 440, 457, 481, 482, 494, 495, 498, 499, 500, 502, 503, 506, 507, 509, 510, 512, 513, 514, 516, 549, 550, 564, 568, 572, 574, 589, 593, 596, 599, 602, 621, 624, 631, 632, 652, 656, 658, 660, 661, 662, 687, 688, 689, 695, 723, 724, 725, 726, 749, 786, 796, 853, 854, 856, 857, 862, 863, 864, 865, 868, 869, 870, 871, 877, 878, 882, 884, 887, 892, 898, 899, 901, 902, 907, 908, 909, 910, 913, 914, 921, 923, 925, 928, 934, 935, 937, 938, 943, 944, 945, 946, 949, 950, 951, 952, 959, 960, 963, 965, 968, 973, 979, 980, 982, 983, 988, 989, 990, 991, 994, 995, 1003, 1005, 1007, 1010, 1037, 1038, 1039, 1040, 1041, 1052, 1053, 1054, 1061, 1066, 1085, 1086, 1087, 1094, 1097, 1100, 1102, 1103, 1105, 1106, 1118, 1127, 1140, 1150, 1151, 1152, 1154, 1157, 1164, 1173, 1200, 1201, 1206, 1207, 1208, 1211, 1251, 1286, 1296, 1297, 1298, 1302, 1322, 1323, 1324, 1326, 1331, 1334, 1352, 1356, 1359, 1360, 1363, 1364, 1371, 1378, 1390, 1395, 1403, 1404, 1406, 1407, 1409, 1411, 1412, 1414, 1423, 1425, 1426], "entir": [16, 95, 101, 165, 179, 184, 260, 360, 375, 577, 862, 873, 907, 916, 943, 955, 988, 998, 1038, 1085, 1100, 1225, 1406, 1409], "adopt": [16, 96, 98, 101, 102, 107, 1405, 1414], "lobpcg": [16, 91, 1275, 1276, 1277], "python_exampl": 16, "graph_partit": 16, "categor": [16, 546, 547, 548, 611], "node_typ": [16, 1342, 1356, 1357], "supported_nod": 16, "unsupported_nod": 16, "remove_edges_from": [16, 89, 192, 453, 602, 881, 920, 962, 1002, 1175, 1177, 1222, 1393, 1394, 1412, 1420, 1426], "nbr": [16, 88, 159, 190, 199, 200, 207, 229, 230, 231, 285, 500, 506, 796, 858, 879, 887, 888, 892, 903, 925, 928, 939, 968, 969, 973, 984, 1007, 1010, 1037, 1039, 1040, 1094, 1326, 1404, 1426], "adj": [16, 88, 199, 200, 207, 324, 325, 796, 849, 887, 888, 892, 894, 915, 925, 928, 930, 968, 969, 973, 975, 996, 1007, 1010, 1037, 1039, 1040, 1094, 1326, 1404, 1411, 1417, 1425, 1426], "g_minus_h": 16, "strip": [16, 25, 69, 1215], "_node_color": 16, "_po": 16, "draw_networkx_edg": [16, 25, 26, 27, 28, 33, 35, 38, 39, 40, 41, 44, 46, 68, 83, 1130, 1133, 1134, 1136, 1137, 1411, 1413], "draw_networkx_label": [16, 25, 35, 38, 46, 71, 1130, 1133, 1134, 1135, 1137], "ncl": 16, "undirect": [16, 25, 34, 71, 93, 112, 177, 185, 204, 205, 209, 211, 212, 214, 215, 216, 217, 218, 219, 220, 221, 224, 227, 228, 229, 230, 231, 232, 237, 239, 240, 246, 247, 264, 267, 275, 277, 278, 280, 281, 293, 294, 295, 297, 298, 300, 313, 315, 318, 319, 321, 322, 328, 330, 331, 332, 333, 337, 338, 341, 345, 346, 347, 348, 349, 350, 352, 353, 371, 372, 379, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 428, 430, 431, 437, 439, 440, 450, 463, 464, 465, 466, 467, 478, 479, 480, 481, 482, 485, 486, 487, 488, 490, 491, 492, 500, 559, 560, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 581, 582, 583, 590, 594, 595, 598, 600, 601, 605, 606, 607, 610, 611, 613, 615, 618, 619, 624, 625, 652, 658, 681, 682, 683, 684, 686, 687, 688, 689, 692, 694, 717, 718, 727, 730, 731, 732, 734, 735, 736, 737, 738, 742, 743, 753, 760, 761, 762, 767, 779, 791, 874, 891, 917, 927, 956, 972, 999, 1009, 1036, 1038, 1056, 1060, 1088, 1090, 1098, 1101, 1115, 1133, 1135, 1146, 1166, 1167, 1173, 1175, 1182, 1184, 1187, 1189, 1190, 1191, 1193, 1196, 1197, 1198, 1199, 1202, 1206, 1207, 1217, 1219, 1230, 1243, 1244, 1247, 1250, 1251, 1252, 1254, 1259, 1273, 1275, 1276, 1278, 1279, 1282, 1298, 1323, 1326, 1327, 1333, 1341, 1342, 1344, 1351, 1352, 1353, 1354, 1371, 1377, 1378, 1379, 1380, 1381, 1383, 1389, 1390, 1395, 1401, 1402, 1404, 1406, 1408, 1411, 1414, 1417, 1426], "And": [16, 23, 47, 86, 93, 101, 107, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 467, 502, 503, 506, 507, 688, 1296, 1297, 1328, 1408, 1409, 1411, 1416, 1425], "specifi": [16, 24, 25, 62, 102, 151, 152, 157, 158, 167, 184, 185, 193, 207, 222, 223, 226, 232, 236, 238, 240, 241, 243, 244, 246, 247, 248, 260, 264, 266, 267, 268, 269, 271, 273, 276, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 299, 305, 310, 311, 320, 324, 326, 329, 338, 348, 349, 353, 356, 357, 374, 377, 410, 411, 412, 413, 414, 415, 418, 419, 433, 435, 436, 440, 442, 443, 444, 445, 447, 448, 449, 458, 473, 491, 494, 495, 498, 499, 510, 518, 552, 553, 554, 555, 564, 565, 566, 575, 577, 584, 588, 597, 601, 604, 608, 609, 635, 636, 660, 671, 672, 673, 674, 676, 686, 691, 692, 704, 705, 706, 707, 708, 710, 711, 712, 713, 714, 715, 716, 721, 722, 751, 760, 853, 854, 856, 857, 864, 873, 874, 882, 892, 898, 899, 901, 902, 909, 916, 917, 921, 928, 934, 935, 937, 938, 945, 947, 948, 955, 956, 962, 963, 973, 979, 980, 982, 983, 990, 992, 993, 998, 999, 1002, 1003, 1010, 1043, 1061, 1070, 1071, 1072, 1081, 1094, 1095, 1096, 1098, 1099, 1104, 1117, 1130, 1133, 1134, 1135, 1136, 1137, 1151, 1154, 1165, 1175, 1177, 1178, 1181, 1182, 1189, 1193, 1196, 1197, 1198, 1199, 1202, 1207, 1210, 1211, 1212, 1219, 1222, 1235, 1242, 1275, 1276, 1277, 1278, 1279, 1294, 1295, 1296, 1297, 1300, 1315, 1323, 1324, 1326, 1328, 1331, 1334, 1336, 1337, 1338, 1339, 1340, 1341, 1344, 1345, 1348, 1349, 1350, 1356, 1357, 1360, 1363, 1364, 1382, 1393, 1397, 1398, 1399, 1402, 1403, 1404, 1406, 1407, 1412, 1416, 1426], "to_undirect": [16, 25, 69, 796, 1037, 1039, 1040, 1182, 1184, 1404, 1413, 1426], "magenta": 16, "six": 16, "classifi": [16, 512, 684, 750], "four": [16, 23, 47, 86, 99, 102, 165, 263, 585, 587, 692, 862, 907, 943, 988, 1039, 1040, 1164, 1193, 1199, 1211, 1323, 1407, 1408, 1414, 1426], "green": [16, 32, 38, 70, 93, 115, 464, 598, 760, 1302, 1330, 1394, 1412, 1426], "goal": [16, 88, 92, 99, 105, 107, 127, 383, 626, 627, 717, 718, 1042], "g_ex": 16, "m": [16, 25, 28, 30, 31, 63, 65, 67, 91, 93, 96, 102, 106, 110, 112, 128, 181, 191, 201, 209, 211, 212, 219, 227, 231, 235, 236, 238, 239, 240, 241, 243, 244, 248, 257, 258, 259, 263, 272, 274, 275, 278, 280, 282, 284, 293, 294, 296, 300, 301, 302, 308, 309, 315, 316, 317, 330, 338, 341, 343, 345, 352, 355, 356, 361, 362, 370, 380, 383, 385, 412, 429, 431, 432, 433, 451, 462, 479, 494, 498, 499, 509, 510, 511, 512, 519, 545, 555, 569, 582, 584, 585, 587, 588, 606, 614, 619, 625, 652, 658, 659, 684, 686, 691, 692, 706, 748, 749, 761, 762, 775, 872, 880, 889, 953, 961, 970, 1060, 1151, 1155, 1157, 1169, 1175, 1177, 1179, 1181, 1199, 1201, 1202, 1203, 1204, 1205, 1207, 1208, 1209, 1210, 1211, 1213, 1215, 1216, 1218, 1219, 1220, 1222, 1223, 1226, 1229, 1230, 1231, 1233, 1234, 1235, 1240, 1256, 1265, 1269, 1271, 1278, 1279, 1280, 1287, 1288, 1292, 1323, 1387, 1406, 1409, 1426], "node_color_list": 16, "nc": [16, 56], "spectral_layout": [16, 43, 1141, 1399, 1406], "subgraphs_of_g_ex": 16, "removed_edg": 16, "node_color_list_c": 16, "One": [16, 52, 55, 101, 102, 103, 115, 545, 559, 560, 679, 684, 761, 1177, 1186, 1272, 1315, 1326, 1404, 1426], "g_ex_r": 16, "compos": [16, 269, 270, 271, 272, 273, 274, 275, 276, 600, 604, 758, 1400, 1406, 1407, 1417, 1423, 1425], "previous": [16, 91, 108, 112, 322, 614, 1182, 1183, 1184, 1395, 1407, 1417], "store": [16, 25, 39, 53, 54, 55, 57, 67, 86, 93, 97, 101, 102, 110, 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619], "explan": [52, 94, 105, 161, 679], "represent": [52, 110, 202, 204, 237, 242, 245, 246, 247, 265, 266, 268, 282, 283, 327, 512, 555, 629, 728, 730, 762, 786, 890, 891, 926, 971, 972, 1008, 1091, 1092, 1094, 1095, 1098, 1099, 1100, 1101, 1117, 1120, 1126, 1130, 1270, 1281, 1326, 1332, 1335, 1336, 1339, 1341, 1347, 1370, 1383, 1393, 1399, 1405, 1406, 1413], "primal": [52, 55, 508, 581], "dual": [52, 54, 55, 581, 1227, 1410, 1413], "sens": [52, 97, 99, 104, 199, 310, 460, 586, 791, 887, 925, 968, 1007, 1217, 1234, 1269, 1326, 1403, 1404], "approach": [52, 55, 99, 101, 103, 104, 107, 115, 341, 345, 462, 464, 466, 500, 519, 616, 678, 1094, 1175, 1188, 1202, 1222, 1407, 1413], "segment": [52, 55, 338], "major": [52, 95, 98, 99, 100, 102, 103, 104, 106, 107, 1393, 1394, 1403, 1404, 1407], "studi": [52, 91, 110, 606, 1192, 1196, 1323, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425], "topologi": [52, 55, 435, 436, 512, 681, 683, 748, 1202, 1217, 1225, 1229, 1233, 1241, 1326], "encod": [52, 55, 58, 67, 99, 141, 249, 267, 268, 619, 758, 775, 1326, 1333, 1334, 1337, 1338, 1339, 1340, 1341, 1344, 1345, 1348, 1349, 1350, 1354, 1355, 1358, 1363, 1368, 1371, 1372, 1375, 1376, 1382, 1406, 1407, 1412], "angular": [52, 55], "inform": [52, 66, 92, 93, 99, 100, 101, 102, 103, 107, 111, 112, 121, 132, 159, 165, 200, 202, 204, 220, 226, 230, 231, 249, 301, 302, 303, 308, 309, 314, 323, 324, 325, 338, 405, 406, 438, 453, 455, 480, 488, 500, 512, 564, 566, 568, 572, 573, 574, 583, 592, 614, 619, 624, 691, 775, 782, 786, 796, 858, 862, 888, 890, 891, 903, 907, 926, 927, 939, 943, 969, 971, 972, 984, 988, 1008, 1009, 1037, 1039, 1040, 1042, 1112, 1141, 1143, 1185, 1206, 1214, 1216, 1217, 1218, 1219, 1267, 1280, 1290, 1296, 1356, 1373, 1375, 1376, 1381, 1383, 1389, 1390, 1393, 1394, 1404, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426], "angl": [52, 55, 1114, 1116], "instead": [52, 93, 94, 101, 102, 103, 106, 141, 165, 170, 282, 320, 338, 366, 370, 390, 392, 399, 405, 406, 407, 411, 412, 416, 417, 418, 419, 424, 425, 427, 500, 561, 562, 563, 585, 587, 632, 727, 729, 731, 733, 734, 735, 736, 737, 796, 862, 866, 907, 911, 943, 947, 988, 992, 1037, 1038, 1039, 1040, 1097, 1102, 1103, 1124, 1127, 1135, 1172, 1179, 1184, 1186, 1192, 1193, 1199, 1207, 1217, 1300, 1342, 1375, 1383, 1393, 1394, 1395, 1397, 1399, 1401, 1402, 1404, 1405, 1406, 1407, 1408, 1410, 1411, 1412, 1413, 1414, 1416, 1417, 1419, 1420, 1421, 1423, 1424, 1425, 1426], "nonplanar": [52, 1250], "form": [52, 55, 110, 151, 170, 220, 238, 377, 381, 391, 422, 427, 440, 449, 450, 451, 488, 500, 517, 521, 567, 568, 569, 570, 571, 572, 573, 574, 578, 579, 580, 588, 589, 677, 679, 697, 711, 717, 718, 719, 729, 730, 731, 748, 752, 767, 786, 791, 853, 866, 898, 911, 934, 947, 979, 992, 1038, 1064, 1085, 1146, 1167, 1199, 1206, 1215, 1217, 1222, 1240, 1243, 1245, 1248, 1252, 1399, 1406, 1407, 1426], "flow": [52, 66, 105, 278, 296, 301, 302, 303, 308, 309, 323, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 423, 427, 428, 430, 431, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 519, 559, 756, 758, 1267, 1325, 1395, 1399, 1400, 1403, 1406, 1407, 1408, 1411, 1414, 1425], "dead": 52, "detail": [52, 53, 86, 92, 93, 97, 99, 100, 128, 252, 253, 256, 257, 258, 259, 260, 277, 278, 281, 282, 284, 285, 286, 287, 288, 297, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 422, 427, 476, 494, 498, 499, 500, 509, 510, 511, 512, 574, 691, 711, 720, 735, 737, 791, 796, 1037, 1039, 1040, 1102, 1105, 1133, 1137, 1140, 1207, 1296, 1319, 1345, 1348, 1349, 1350, 1393, 1399, 1400, 1401, 1402, 1406, 1413, 1414, 1426], "methodologi": 52, "avail": [52, 93, 99, 100, 101, 103, 141, 184, 226, 232, 280, 422, 425, 426, 585, 587, 780, 873, 916, 955, 998, 1039, 1042, 1194, 1196, 1197, 1198, 1328, 1331, 1334, 1393, 1394, 1396, 1402, 1405, 1406, 1409, 1412, 1413, 1426], "1016": [52, 112, 226, 231, 274, 297, 298, 299, 303, 306, 307, 313, 322, 323, 338, 346, 347, 455, 1233], "compenvurbsi": 52, "2017": [52, 227, 512, 1207, 1208, 1406, 1407], "004": [52, 341], "scienc": [52, 91, 101, 105, 107, 109, 110, 112, 219, 228, 249, 296, 301, 302, 303, 308, 309, 323, 346, 347, 409, 412, 431, 441, 445, 446, 453, 476, 498, 618, 619, 680, 681, 683, 1203, 1223, 1255], "pydata": [52, 1413, 1423, 1424, 1425], "stack": [52, 111, 346, 693, 1045, 1046], "showcas": [53, 86, 93, 109], "analys": [53, 70, 86, 310], "ecosystem": [53, 86, 99, 100, 104, 107, 110, 1425], "descript": [53, 86, 93, 97, 464, 466, 704, 717, 786, 1130, 1131, 1132, 1133, 1138, 1139, 1140, 1141, 1142, 1207, 1222, 1242, 1407, 1411, 1413, 1421, 1422, 1425], "plu": [54, 386, 583, 1036, 1088, 1148, 1253], "voronoi": [54, 752, 758, 1325, 1407], "cholera": [54, 57], "broad": [54, 57, 1296], "pump": [54, 57], "record": [54, 57, 94, 99, 691, 1426], "john": [54, 57, 91, 278, 568, 572, 685, 1205, 1250, 1408, 1413], "snow": [54, 57], "1853": [54, 57], "method": [54, 57, 58, 75, 88, 92, 93, 95, 101, 102, 103, 107, 112, 143, 161, 164, 165, 185, 186, 187, 190, 200, 202, 204, 206, 207, 226, 231, 232, 250, 260, 261, 262, 299, 301, 302, 303, 308, 309, 311, 312, 323, 324, 336, 374, 376, 379, 380, 381, 385, 423, 440, 451, 462, 476, 500, 514, 527, 537, 545, 564, 566, 568, 572, 581, 583, 600, 604, 615, 632, 633, 635, 636, 654, 655, 656, 671, 672, 673, 674, 684, 692, 719, 720, 733, 738, 752, 775, 786, 852, 862, 874, 875, 876, 879, 888, 890, 891, 892, 897, 907, 917, 918, 919, 926, 927, 928, 933, 934, 935, 943, 956, 957, 958, 971, 972, 973, 978, 979, 980, 988, 999, 1000, 1001, 1008, 1009, 1010, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1033, 1038, 1043, 1044, 1045, 1046, 1066, 1174, 1182, 1184, 1193, 1197, 1275, 1276, 1277, 1280, 1296, 1301, 1302, 1323, 1326, 1363, 1395, 1399, 1403, 1404, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1416, 1417, 1422, 1425, 1426], "shown": [54, 57, 100, 102, 517, 518, 947, 992, 1275, 1276, 1277, 1300, 1349, 1404], "centroid": [54, 57, 58], "libpys": [54, 55, 57, 58], "cg": [54, 102, 296, 301, 302, 303, 308, 309, 323, 588], "voronoi_fram": 54, "contextili": [54, 55, 57], "add_basemap": [54, 55, 57], "geopackag": [54, 55, 56, 57], "sqlite": [54, 57], "reli": [54, 57, 99, 103, 362, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 502, 503, 506, 507, 1393, 1407, 1411, 1425], "fiona": [54, 57], "level": [54, 57, 101, 103, 104, 106, 111, 112, 115, 125, 165, 220, 322, 334, 336, 374, 380, 381, 387, 389, 390, 394, 423, 427, 640, 691, 770, 786, 862, 907, 943, 988, 1012, 1013, 1018, 1019, 1020, 1021, 1022, 1094, 1108, 1155, 1202, 1207, 1208, 1236, 1296, 1323, 1328, 1396, 1399, 1407, 1412, 1413, 1414], "interfac": [54, 57, 58, 75, 76, 96, 98, 99, 101, 102, 107, 109, 110, 184, 429, 496, 673, 758, 761, 762, 780, 873, 916, 955, 998, 1042, 1044, 1326, 1328, 1393, 1396, 1398, 1402, 1404, 1405, 1406, 1409, 1413, 1414, 1426], "kind": [54, 57, 58, 92, 93, 94, 99, 208, 466, 722, 1202, 1326, 1383], "read_fil": [54, 55, 57, 58], "cholera_cas": [54, 57], "gpkg": [54, 56, 57], "correctli": [54, 164, 324, 325, 1393, 1404, 1406, 1411, 1412, 1419], "construct": [54, 55, 56, 57, 58, 67, 94, 102, 227, 229, 230, 231, 232, 269, 273, 276, 352, 423, 450, 460, 513, 545, 546, 547, 548, 552, 553, 554, 556, 557, 558, 609, 685, 695, 708, 716, 732, 1046, 1047, 1052, 1053, 1101, 1102, 1103, 1104, 1105, 1153, 1154, 1175, 1177, 1178, 1180, 1186, 1190, 1191, 1192, 1195, 1203, 1207, 1208, 1209, 1210, 1217, 1219, 1222, 1229, 1236, 1251, 1259, 1263, 1269, 1272, 1278, 1279, 1296, 1323, 1327, 1395, 1399, 1406, 1409, 1415], "column_stack": [54, 57, 58], "could": [54, 93, 101, 102, 103, 165, 215, 216, 224, 581, 679, 862, 907, 943, 988, 1066, 1094, 1102, 1103, 1120, 1126, 1174, 1296, 1300, 1326, 1393, 1404, 1414, 1426], "present": [54, 58, 93, 107, 110, 132, 184, 220, 226, 315, 316, 330, 357, 359, 429, 494, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 567, 581, 594, 595, 597, 600, 601, 604, 632, 633, 635, 636, 659, 670, 749, 786, 873, 916, 955, 998, 1043, 1045, 1061, 1082, 1150, 1152, 1157, 1159, 1160, 1163, 1165, 1278, 1279, 1353, 1354, 1357, 1381, 1383, 1407, 1411, 1426], "alongsid": [54, 438], "diagram": [54, 132, 381, 752], "intrins": 54, "put": [54, 92, 95, 102, 226, 1326, 1404, 1406], "underli": [54, 101, 102, 132, 152, 157, 158, 161, 195, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 427, 428, 490, 491, 500, 615, 742, 743, 791, 854, 856, 857, 884, 899, 901, 902, 923, 935, 937, 938, 965, 980, 982, 983, 1005, 1038, 1225, 1233, 1241, 1326, 1393, 1394, 1402], "quickli": [54, 1239], "Be": [54, 92, 1038, 1135, 1404], "care": [54, 92, 100, 102, 106, 107, 109, 115, 156, 855, 900, 936, 981, 1038, 1326, 1404, 1406], "bound": [54, 112, 214, 215, 216, 217, 220, 224, 227, 264, 300, 342, 352, 437, 440, 675, 1043, 1165, 1235, 1319, 1413, 1414, 1416], "box": [54, 107, 1134, 1136, 1271, 1323], "control": [54, 168, 179, 189, 204, 230, 231, 324, 325, 450, 467, 865, 878, 891, 910, 946, 960, 991, 1328, 1402, 1408, 1409, 1413], "cell": [54, 58, 752, 758, 1271, 1323, 1325, 1407], "convex": 54, "hull": 54, "contigu": [54, 58, 438, 1102, 1277, 1278], "being": [54, 92, 94, 95, 99, 101, 102, 109, 217, 227, 464, 465, 466, 559, 560, 711, 1038, 1045, 1144, 1175, 1236, 1296, 1393, 1394, 1407, 1412, 1413, 1416, 1425], "face": [54, 101, 102, 115, 183, 206, 615, 1043, 1262, 1263], "analogu": [54, 58, 230], "von": 54, "neuman": 54, "neighborhood": [54, 58, 114, 213, 240, 249, 285, 286, 324, 325, 512, 690, 786, 1189], "cardin": [54, 115, 218, 221, 264, 277, 278, 279, 280, 339, 341, 343, 345, 414, 415, 416, 417, 428, 440, 441, 444, 446, 581, 583, 611, 691, 1395], "regular": [54, 58, 65, 88, 99, 477, 478, 479, 480, 622, 623, 624, 758, 1038, 1185, 1190, 1191, 1192, 1239, 1245, 1250, 1251, 1254, 1258, 1261, 1262, 1263, 1264, 1280, 1290, 1323, 1325, 1394, 1395, 1398, 1406, 1412, 1413], "come": [54, 93, 100, 101, 102, 517, 577, 588, 598, 608, 677, 698, 699, 1046, 1243, 1326, 1402, 1413], "piec": [54, 374], "move": [54, 94, 95, 100, 101, 230, 231, 377, 380, 1117, 1207, 1210, 1393, 1395, 1404, 1405, 1406, 1407, 1411, 1413, 1416, 1419, 1421, 1425], "chessboard": 54, "from_datafram": [54, 55, 57, 58], "built": [54, 69, 93, 102, 103, 106, 230, 231, 362, 464, 1102, 1103, 1105, 1182, 1183, 1184, 1296, 1328, 1396, 1426], "relev": [54, 93, 99, 101, 103, 104, 106, 132, 168, 176, 184, 189, 497, 501, 504, 505, 508, 657, 865, 870, 873, 878, 910, 916, 946, 951, 955, 960, 991, 998, 1084, 1307, 1312, 1323, 1411, 1417], "delaunay_graph": 54, "merg": [54, 57, 58, 93, 99, 100, 106, 383, 584, 585, 587, 1322, 1403], "nice": [54, 57, 58, 101, 214, 494, 1061, 1328, 1410], "basemap": [54, 57, 58], "lightblu": [54, 58], "cornsilk": 54, "809": [54, 59, 80], "plot_delaunai": [54, 59], "sometim": [55, 63, 92, 94, 99, 102, 109, 199, 346, 347, 611, 729, 731, 887, 925, 968, 1007, 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385, 434, 573, 1165, 1177, 1182, 1183, 1184, 1187, 1230, 1234, 1287], "0748828": 91, "templeton": 91, "santa": [91, 214, 215, 216, 220], "fe": [91, 214, 215, 216, 220], "under": [91, 324, 325, 525, 535, 555, 566, 577, 586, 588, 606, 671, 672, 673, 674, 739, 1326, 1412, 1413, 1417], "contract": [91, 110, 391, 500, 584, 585, 587, 618, 619, 767, 1174, 1395, 1413], "0340": 91, "space": [92, 101, 109, 231, 296, 301, 302, 308, 309, 355, 423, 628, 629, 630, 760, 786, 1112, 1144, 1193, 1196, 1197, 1198, 1199, 1239, 1296, 1326, 1331, 1334, 1390, 1398, 1406, 1412, 1417], "manag": [92, 93, 100, 111, 228, 680, 691, 1402, 1411, 1412], "privat": [92, 100, 1412, 1413, 1421, 1425], "tracker": [92, 97, 100, 107], "wiki": [92, 112, 120, 121, 132, 211, 226, 230, 282, 283, 293, 340, 341, 425, 454, 469, 476, 483, 484, 488, 490, 590, 676, 695, 696, 704, 710, 732, 761, 767, 782, 1206, 1219, 1243, 1244, 1245, 1246, 1248, 1249, 1250, 1251, 1256, 1257, 1258, 1259, 1261, 1262, 1263, 1264], "channel": 92, 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1413, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425], "strict": [95, 110, 214, 215, 216, 619, 1408, 1413], "rule": [95, 100, 199, 508, 760, 887, 925, 968, 1007, 1061, 1082, 1144, 1298], "procedur": [95, 97, 99, 217, 220, 281, 305, 377, 508, 680, 1188, 1417], "upon": [95, 102, 580, 1296, 1413, 1416], "justif": [95, 104], "literal_string": [95, 1345, 1350, 1384, 1412], "literal_destring": [95, 1347, 1349, 1384, 1412], "coreview": [95, 1413], "filter": [95, 322, 453, 1036, 1061, 1082, 1088, 1269, 1324, 1325, 1413], "link_analysi": [95, 1405], "pagerank_alg": [95, 1405], "replac": [95, 99, 102, 103, 202, 232, 270, 385, 411, 412, 430, 431, 512, 583, 796, 890, 926, 934, 971, 979, 1008, 1037, 1039, 1040, 1051, 1094, 1225, 1241, 1295, 1296, 1297, 1311, 1317, 1326, 1347, 1363, 1364, 1393, 1394, 1396, 1399, 1404, 1406, 1407, 1408, 1409, 1411, 1412, 1413, 1414, 1417, 1422, 1424, 1425], "pagerank": [95, 311, 312, 324, 325, 565, 758, 1283, 1284, 1394, 1398, 1405, 1406, 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"fundament": [100, 107, 110, 338, 449, 618, 619, 1217, 1413], "flaw": 100, "forward": [100, 217, 450, 711, 717, 718], "typo": [100, 1396, 1406, 1407, 1408, 1411, 1412, 1413, 1414, 1416, 1417, 1419, 1421], "land": 100, "outlin": [100, 249, 336, 462, 1407], "templat": [100, 1413], "taken": [100, 101, 145, 148, 207, 443, 450, 717, 718, 749, 761, 892, 928, 973, 1010, 1117, 1409], "suffici": [100, 101, 1326], "scikit": [100, 103, 109], "expos": [101, 374, 1405], "nodeview": [101, 184, 391, 598, 599, 601, 602, 603, 604, 695, 873, 916, 955, 998, 1036, 1088, 1349, 1362, 1404, 1407], "nodedataview": [101, 184, 391, 591, 592, 600, 873, 916, 955, 998, 1217, 1426], "edgeview": [101, 590, 591, 592, 598, 599, 600, 601, 602, 603, 604, 612, 624, 770, 910, 1036, 1088, 1098, 1404, 1413], "edgedataview": [101, 168, 189, 865, 878, 910, 946, 960, 991, 1098, 1217, 1362, 1412, 1426], "semant": [101, 531, 541, 762, 1403, 1405], "inher": [101, 220, 427], "impli": [101, 110, 132, 220, 312, 314, 327, 455, 466, 511, 512, 545, 1296], "element": [101, 102, 230, 231, 270, 291, 292, 311, 350, 371, 391, 457, 464, 518, 559, 560, 578, 579, 580, 586, 640, 656, 671, 673, 675, 677, 728, 730, 739, 749, 752, 1036, 1038, 1048, 1049, 1050, 1051, 1087, 1088, 1135, 1137, 1173, 1206, 1211, 1212, 1217, 1237, 1238, 1240, 1249, 1272, 1277, 1278, 1279, 1282, 1287, 1288, 1296, 1302, 1303, 1311, 1318, 1323, 1355, 1358, 1361, 1362, 1405], "intend": [101, 104, 107, 111, 327, 567, 1038, 1269, 1296, 1393], "impos": [101, 103, 545, 791], "due": [101, 102, 109, 231, 264, 440, 581, 583, 626, 627, 1217, 1405, 1412, 1414, 1423, 1425], "bit": [101, 209, 211, 212, 453, 511, 512, 786, 1345, 1348, 1349, 1350, 1382, 1411], "lot": [101, 452, 1326, 1405], "screen": 101, "instinct": 101, "error": [101, 102, 152, 157, 158, 195, 280, 288, 296, 311, 324, 414, 422, 471, 472, 473, 474, 475, 489, 497, 501, 504, 505, 508, 556, 557, 558, 564, 566, 581, 584, 653, 660, 667, 675, 676, 796, 854, 856, 857, 884, 899, 901, 902, 923, 935, 937, 938, 965, 980, 982, 983, 1005, 1037, 1043, 1117, 1144, 1396, 1401, 1404, 1406, 1407, 1411, 1412, 1413, 1414, 1417, 1419, 1425], "definit": [101, 132, 235, 238, 243, 289, 291, 292, 303, 323, 342, 356, 398, 435, 437, 464, 467, 549, 550, 551, 608, 618, 619, 620, 625, 676, 685, 687, 700, 735, 737, 791, 1192, 1193, 1197, 1217, 1235, 1287, 1326, 1406, 1413, 1426], "coupl": [101, 102, 132, 1257, 1402, 1404], "realis": 101, "But": [101, 102, 107, 143, 170, 238, 243, 256, 277, 278, 281, 297, 298, 583, 796, 866, 911, 1012, 1013, 1018, 1019, 1020, 1021, 1022, 1037, 1039, 1040, 1094, 1328, 1393, 1425], "seem": [101, 102, 298, 307, 791, 1234], "eas": [101, 107, 1409], "idiom": [101, 159, 190, 200, 858, 879, 888, 903, 939, 969, 984, 1296, 1394, 1404, 1411], "subscript": [101, 151, 159, 200, 796, 853, 858, 888, 898, 903, 934, 939, 969, 979, 984, 1037, 1039, 1040, 1394, 1426], "repr": [101, 1347, 1413], "4950": [101, 1414], "traceback": [101, 450, 464, 584, 652, 658, 1302, 1303], "recent": [101, 437, 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720, 1331, 1334, 1406, 1414, 1425], "leav": [102, 231, 388, 500, 508, 584, 585, 586, 587, 678, 1145, 1155, 1296, 1404, 1409, 1426], "dg": [102, 207, 322, 455, 456, 457, 458, 459, 461, 462, 464, 465, 466, 467, 468, 469, 892, 928, 973, 1010, 1041, 1404, 1426], "mdg": [102, 207, 892, 928, 973, 1010, 1420], "customgraph": 102, "elist": [102, 1326], "isol": [102, 355, 380, 435, 491, 492, 522, 524, 621, 735, 737, 758, 1218, 1325, 1330, 1398, 1401, 1406, 1407, 1417], "ekei": [102, 207, 892, 928, 934, 973, 979, 1010, 1084, 1104], "protocol": [102, 1404], "hashabl": [102, 144, 151, 156, 171, 180, 267, 545, 546, 547, 548, 761, 796, 853, 855, 867, 871, 898, 900, 912, 914, 934, 936, 947, 948, 952, 962, 979, 981, 992, 993, 995, 1002, 1037, 1038, 1039, 1040, 1087, 1207, 1278, 1279, 1295, 1310, 1324, 1326, 1333, 1337, 1338, 1426], "logic": [102, 103, 220, 760, 762, 1298, 1406, 1407, 1419, 1425], "denot": [102, 114, 212, 219, 299, 300, 322, 567, 568, 569, 570, 571, 572, 573, 608, 619, 687, 688, 689, 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"presum": [102, 1297], "rewritten": [102, 1395, 1402, 1406], "gradual": 102, "accomplish": [102, 109, 1165], "wrap": [102, 1045, 1047, 1296, 1301, 1304], "custom_graph": 102, "ichain": 102, "tripl": [102, 114, 249, 250, 711, 1411], "overli": 102, "empty_graph": [102, 753, 1057, 1158, 1297, 1323, 1406, 1409, 1410], "3036": 102, "1393": 102, "canon": [102, 684, 730, 1412], "huge": 102, "path_edgelist": 102, "disallow": [102, 796, 1037, 1039, 1040, 1187, 1417], "2022": [103, 105, 110, 693, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424], "pseudo": [103, 104, 676, 1320, 1321, 1405, 1407], "nep19": 103, "legaci": [103, 1395, 1402, 1408], "randomst": [103, 1100, 1111, 1117, 1299, 1301, 1304, 1305, 1328, 1405, 1409], "statist": [103, 110, 128, 274, 358, 383, 385, 438, 1222, 1328, 1405], "strategi": [103, 123, 222, 362, 366, 370, 453], "engin": [103, 107, 729, 731, 1412], "modern": [103, 110, 1405], "prng": 103, "np_random_st": [103, 1301, 1405, 1414], "random_st": [103, 208, 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[132, 732], "koller": 132, "friedman": 132, "mit": [132, 342, 519, 618], "causal_markov_condit": 132, "ness": [133, 684, 782], "classmethod": [141, 1047], "auxiliari": [141, 142, 143, 220, 411, 412, 413, 415, 416, 417, 418, 419, 423, 430, 431, 1402], "sink": [141, 302, 309, 416, 418, 494, 495, 498, 499, 501, 502, 503, 506, 507, 509, 510, 565], "pick": [141, 217, 331, 657, 1188, 1207, 1210, 1407], "st": [141, 415, 417], "cut": [141, 222, 223, 293, 377, 382, 387, 389, 390, 394, 411, 412, 414, 415, 416, 417, 419, 427, 428, 429, 442, 443, 444, 445, 447, 494, 495, 498, 499, 500, 502, 503, 506, 507, 509, 510, 619, 758, 760, 1038, 1066, 1115, 1262, 1325, 1395, 1402, 1406, 1413], "refin": [143, 215, 423, 438], "auxgraph": [143, 423], "node_partit": 144, "permut": [144, 368, 452, 453, 455, 466, 748, 1285, 1320, 1321], "containin": 144, "frozenset": [144, 267, 339, 383, 586, 588, 752, 1165, 1333, 1337, 1338, 1412], "abc": [144, 545, 1154, 1206, 1303, 1412, 1413], "interchang": [144, 362], "bool": [145, 146, 148, 149, 165, 168, 171, 176, 184, 189, 196, 204, 208, 232, 237, 238, 242, 243, 245, 249, 250, 258, 265, 266, 267, 268, 272, 275, 286, 287, 288, 291, 294, 295, 296, 297, 298, 299, 301, 302, 305, 306, 307, 308, 309, 310, 314, 315, 322, 324, 325, 326, 327, 330, 343, 350, 355, 362, 393, 394, 395, 396, 397, 398, 439, 454, 462, 463, 467, 479, 480, 488, 489, 491, 494, 498, 499, 509, 510, 513, 514, 515, 516, 517, 518, 520, 521, 522, 545, 562, 564, 578, 579, 580, 581, 588, 613, 614, 616, 617, 622, 623, 625, 640, 652, 663, 673, 679, 685, 690, 696, 698, 699, 700, 704, 708, 719, 723, 724, 725, 726, 728, 730, 733, 734, 735, 736, 737, 738, 740, 741, 742, 743, 862, 865, 867, 870, 873, 878, 885, 891, 907, 910, 912, 916, 927, 931, 943, 946, 948, 951, 955, 960, 966, 972, 976, 988, 991, 993, 998, 1039, 1040, 1045, 1057, 1068, 1070, 1071, 1072, 1084, 1091, 1097, 1116, 1133, 1134, 1135, 1136, 1169, 1179, 1185, 1189, 1209, 1211, 1212, 1213, 1215, 1224, 1228, 1230, 1231, 1232, 1275, 1276, 1277, 1278, 1279, 1282, 1295, 1296, 1307, 1309, 1312, 1335, 1336, 1337, 1339, 1341, 1342, 1344, 1353, 1354, 1355, 1356, 1357, 1358, 1360, 1364, 1379, 1380], "account": [145, 148, 398, 448, 749, 761, 1270, 1393, 1413], "graph_nod": [145, 148], "subgraph_nod": [145, 148], "find_isomorph": [147, 150], "induc": [148, 167, 199, 211, 226, 342, 388, 392, 406, 427, 436, 437, 470, 487, 494, 495, 498, 499, 502, 503, 506, 507, 509, 510, 512, 586, 589, 752, 761, 762, 864, 887, 909, 925, 945, 968, 990, 1007, 1038, 1061, 1066, 1087, 1102, 1103, 1105, 1189, 1283, 1284, 1393], "u_of_edg": [151, 853, 898], "v_of_edg": [151, 853, 898], "capac": [151, 265, 296, 301, 302, 303, 308, 309, 323, 411, 412, 415, 416, 417, 418, 419, 430, 431, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 758, 853, 898, 934, 979, 1335, 1402], "342": [151, 853, 898, 934, 979, 1255], "ebunch_to_add": [152, 158, 854, 857, 899, 902, 935, 938, 980, 983], "add_weighted_edges_from": [152, 229, 230, 231, 508, 581, 630, 657, 659, 721, 854, 899, 935, 980, 1070, 1326, 1404, 1407, 1426], "runtimeerror": [152, 157, 158, 195, 464, 465, 466, 854, 856, 857, 884, 899, 901, 902, 923, 935, 937, 938, 965, 980, 982, 983, 1005], "happen": [152, 157, 158, 195, 380, 584, 854, 856, 857, 884, 899, 901, 902, 923, 935, 937, 938, 965, 980, 982, 983, 1005, 1403, 1404, 1425], "iterator_of_edg": [152, 158, 854, 857, 899, 902, 935, 938, 980, 983], "wn2898": [152, 854, 899, 935, 980], "wrong": [152, 157, 158, 722, 854, 856, 857, 899, 901, 902, 935, 937, 938, 980, 982, 983, 1406, 1411, 1416, 1425], "start_nod": [153, 154, 155], "end_nod": [153, 154, 155], "reference_neighbor": [153, 154], "half": [153, 154, 155, 164, 177, 183, 206, 297, 298, 615, 653], "clockwis": [153, 154, 169, 182, 197, 615], "networkxexcept": [153, 154, 161, 331, 588, 593, 724, 726, 1043, 1110, 1138, 1180, 1325], "add_half_edge_cw": [153, 155, 164, 615], "connect_compon": [153, 154, 155, 615], "add_half_edge_first": [153, 154, 164, 615], "add_half_edge_ccw": [154, 155, 164, 615], "node_for_ad": [156, 855, 900, 936, 981], "mutabl": [156, 855, 900, 936, 981, 1061, 1066, 1082, 1085, 1086], "hash": [156, 511, 512, 758, 855, 900, 936, 981, 1324, 1325, 1414, 1426], "hello": [156, 157, 855, 856, 900, 901, 936, 937, 981, 982, 1303], "k3": [156, 157, 855, 856, 900, 901, 936, 937, 981, 982, 1217], "utm": [156, 855, 900, 936, 981], "382871": [156, 855, 900, 936, 981], "3972649": [156, 855, 900, 936, 981], "nodes_for_ad": [157, 856, 901, 937, 982], "iterator_of_nod": [157, 195, 856, 884, 901, 923, 937, 965, 982, 1005], "datadict": [159, 190, 200, 207, 734, 736, 858, 879, 888, 892, 903, 928, 939, 969, 973, 1010, 1084, 1312, 1326], "foovalu": [159, 190, 200, 858, 879, 888, 903, 939, 969], "nbrdict": [160, 859, 904, 940, 985, 1019, 1094], "fulfil": [161, 615], "cw": [161, 615], "ccw": [161, 615], "planar": [161, 614, 616, 617, 758, 1110, 1138, 1243, 1246, 1247, 1249, 1325, 1409, 1410], "first_nbr": [161, 615], "invalid": [161, 615, 1413], "alter": [163, 861, 906, 942, 987], "afterward": 164, "as_view": [165, 202, 204, 862, 890, 891, 907, 926, 927, 943, 971, 972, 988, 1008, 1009, 1089, 1090], "shallow": [165, 202, 204, 284, 285, 286, 287, 288, 862, 890, 891, 907, 926, 927, 943, 971, 972, 988, 1008, 1009, 1394], "deepcopi": [165, 202, 204, 862, 890, 891, 907, 926, 927, 943, 971, 972, 988, 1008, 1009, 1409], "__class__": [165, 199, 862, 887, 907, 925, 943, 968, 988, 1007, 1404, 1407, 1409, 1410, 1411], "fresh": [165, 862, 907, 943, 988, 1404], "inspir": [165, 230, 231, 342, 681, 862, 907, 943, 988, 1226, 1323, 1404], "deep": [165, 202, 204, 862, 890, 891, 907, 926, 927, 943, 971, 972, 988, 1008, 1009, 1265, 1394], "degreeview": [166, 863, 908, 944, 950, 989, 1404, 1426], "didegreeview": [166, 863], "outedgeview": [168, 189, 467, 468, 613, 747, 750, 865, 878, 1035, 1083, 1404, 1418], "ddict": [168, 176, 184, 189, 865, 870, 873, 878, 910, 916, 946, 951, 955, 960, 991, 998], "in_edg": [168, 189, 865, 878, 946, 960, 1404, 1406, 1407], "out_edg": [168, 865, 946, 1062, 1404, 1406, 1407, 1426], "quietli": [168, 189, 865, 878, 910, 946, 960, 991, 1087, 1426], "outedgedataview": [168, 189, 865, 878, 1404, 1411], "set_data": 169, "edge_dict": [170, 866, 911, 947, 992], "safe": [170, 866, 911, 1404, 1412], "edge_ind": [171, 867, 912, 948, 993], "data_dictionari": [171, 867, 912], "simpler": [172, 184, 868, 873, 913, 916, 949, 955, 994, 998, 1406, 1407, 1417], "indegreeview": [175, 869, 1404], "deg": [175, 188, 243, 259, 356, 361, 685, 869, 877, 950, 959, 1165, 1179, 1222, 1404], "inedgeview": [176, 870, 1404], "inedgedataview": [176, 870], "silent": [180, 193, 195, 320, 871, 882, 884, 914, 921, 923, 952, 963, 965, 995, 1003, 1005, 1085, 1086, 1127, 1353, 1354, 1359, 1363, 1406, 1413], "niter": [180, 681, 682, 683, 684, 851, 871, 896, 914, 932, 952, 977, 995, 1414], "__iter__": [180, 871, 914, 952, 995, 1303], "nodedata": [184, 873, 916, 955, 998], "5pm": [184, 796, 873, 916, 955, 998, 1037, 1039, 1040, 1394, 1426], "Not": [184, 379, 432, 433, 434, 435, 436, 437, 438, 476, 873, 916, 955, 998, 1117, 1216], "nedg": [185, 588, 874, 917, 956, 999], "__len__": [186, 187, 875, 876, 918, 919, 957, 958, 1000, 1001], "outdegreeview": [188, 877], "Will": [193, 362, 605, 607, 610, 882, 921, 963, 1003, 1404, 1414], "get_data": [197, 616], "inplac": [199, 690, 887, 925, 968, 1007, 1066, 1393], "reduct": [199, 469, 618, 786, 887, 925, 968, 1007, 1066, 1320, 1321, 1413, 1414], "sg": [199, 887, 925, 968, 1007], "largest_wcc": [199, 887, 925, 968, 1007], "is_multigraph": [199, 758, 887, 925, 968, 1007, 1154, 1412], "keydict": [199, 207, 887, 892, 925, 928, 968, 973, 1007, 1010, 1039, 1040], "contrast": [202, 204, 301, 302, 308, 309, 890, 891, 926, 927, 971, 972, 1008, 1009, 1066, 1233, 1241, 1426], "reciproc": [204, 299, 320, 322, 356, 411, 430, 447, 476, 620, 758, 891, 972, 1325, 1416, 1425], "mark_half_edg": 206, "li": [206, 619, 670, 675, 685, 775, 1207, 1210, 1425], "straightforward": [207, 892, 928, 973, 1010], "slightli": [207, 326, 437, 520, 521, 581, 892, 928, 973, 1010, 1165, 1326, 1404, 1407, 1412, 1414, 1425], "singleton": [207, 588, 892, 928, 973, 1010, 1218, 1251, 1407], "preserve_attr": [208, 723, 724, 725, 726], "optimum": [208, 231, 583, 720, 722, 791, 1395, 1406], "arboresc": [208, 460, 719, 720, 722, 724, 726, 740, 743, 758, 1272, 1395, 1406], "span": [208, 226, 227, 228, 295, 508, 618, 619, 624, 719, 720, 722, 724, 726, 732, 733, 734, 735, 736, 737, 738, 758, 1394, 1397, 1406, 1407, 1420], "max_ind_cliqu": 209, "networkxnotimpl": [209, 210, 211, 212, 220, 224, 227, 293, 294, 295, 318, 319, 321, 328, 343, 379, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 403, 404, 405, 406, 407, 422, 424, 425, 426, 427, 429, 455, 457, 458, 459, 460, 468, 481, 482, 500, 589, 590, 608, 680, 732, 1043, 1216, 1275, 1276, 1298, 1325, 1353, 1354, 1379, 1407, 1408], "boppana": [209, 211, 212], "halld\u00f3rsson": [209, 211, 212], "1992": [209, 211, 212, 517, 518, 1407], "exclud": [209, 211, 212, 215, 216, 261, 262, 453, 688, 719, 723, 724, 725, 726, 733, 751, 1036, 1038, 1088, 1217, 1412], "180": [209, 211, 212, 238], "heurist": [210, 220, 228, 233, 234, 377, 380, 381, 427, 494, 509, 626, 627, 652, 663, 703, 758, 1173, 1320, 1321, 1325, 1395, 1408, 1412, 1413], "max_cliqu": 210, "rigor": 210, "pattabiraman": 210, "bharath": 210, "massiv": [210, 217], "421": 210, "448": 210, "1080": [210, 297, 298, 306, 307, 329], "15427951": 210, "986778": 210, "apx": [211, 212], "subseteq": [211, 280, 289, 618, 675], "omega": [211, 758, 782, 1414], "maximum_cliqu": 211, "1007": [211, 226, 296, 301, 302, 303, 308, 309, 323, 324, 325, 341, 431, 451, 498, 574, 1144, 1181], "bf01994876": 211, "iset": 212, "trial": [213, 230, 231, 1195, 1237, 1238], "estim": [213, 224, 297, 306, 313, 564, 625, 626, 627, 782, 1280, 1407], "coeffici": [213, 248, 260, 261, 262, 263, 289, 355, 356, 358, 570, 618, 619, 625, 682, 684, 778, 782, 1397, 1398, 1399, 1406, 1413], "fraction": [213, 257, 259, 286, 289, 297, 299, 304, 306, 315, 317, 318, 319, 321, 322, 326, 328, 330, 356, 358, 359, 519, 1165, 1234], "schank": 213, "thoma": [213, 751, 1407, 1409, 1413], "dorothea": [213, 1168], "wagner": [213, 429, 758, 1168, 1402, 1406], "universit\u00e4t": 213, "karlsruh": 213, "fakult\u00e4t": 213, "f\u00fcr": 213, "informatik": [213, 412], "5445": 213, "ir": [213, 606], "1000001239": 213, "erdos_renyi_graph": [213, 1224, 1232, 1326, 1406, 1426], "214": 213, "cutoff": [214, 215, 310, 326, 383, 410, 411, 412, 418, 419, 494, 495, 498, 499, 510, 637, 638, 640, 641, 642, 643, 644, 647, 648, 649, 656, 660, 661, 662, 667, 668, 669, 677, 678, 1234, 1398, 1402, 1406, 1413, 1416, 1424, 1425], "distinct": [214, 215, 255, 281, 288, 352, 391, 452, 453, 460, 578, 595, 608, 618, 700, 701, 734, 735, 736, 737, 789, 1150, 1244, 1271, 1323, 1326, 1328, 1395, 1417], "nonadjac": [214, 215, 480, 584, 585, 587], "cutset": [214, 215, 414, 415, 416, 417, 427, 428, 500, 506, 758], "menger": [214, 215, 216], "theorem": [214, 215, 216, 220, 235, 281, 311, 312, 322, 411, 506, 507, 514, 517, 518, 618, 1190, 1205], "local_node_connect": [214, 216, 408, 409, 410, 411, 413], "node_connect": [214, 215, 409, 410, 411, 412, 414, 415, 416, 417, 419, 427, 428, 1402], "dougla": [214, 215, 216, 220, 1413, 1425], "035": [214, 215, 216, 220], "eclect": [214, 215, 216], "ss": [214, 215, 216], "uci": [214, 215, 216, 467, 704, 706, 707, 708, 710, 734, 736], "drwhite": [214, 215, 216], "pprint": [214, 577, 711], "all_pairs_node_connect": [215, 216, 1402, 1424, 1425], "bf": [215, 216, 217, 363, 588, 704, 706, 707, 708, 717, 1397, 1401, 1406, 1409, 1412, 1413], "lose": [215, 796, 1037, 1039, 1040], "accuraci": [215, 312, 786], "platon": [215, 216, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 1245, 1248, 1254, 1257, 1261, 1263], "octahedr": [215, 216, 1257], "approx": [215, 216, 227, 229, 230, 231, 1413], "octahedral_graph": [215, 216], "vari": [217, 238, 243, 373, 378, 569, 695], "sweep": [217, 1412], "dsweep": 217, "a_1": [217, 477], "a_2": 217, "magnien": [217, 260, 261, 262, 289], "cl\u00e9menc": [217, 260, 261, 262, 289], "matthieu": [217, 260, 261, 262, 274, 289], "latapi": [217, 260, 261, 262, 274, 289], "michel": 217, "habib": 217, "empir": 217, "tight": 217, "jea": 217, "0904": 217, "2728": 217, "crescenzi": 217, "pierluigi": 217, "roberto": 217, "grossi": 217, "leonardo": 217, "lanzi": 217, "andrea": [217, 1165, 1413], "marino": 217, "symposium": [217, 619, 1186, 1195, 1239], "berlin": [217, 520, 521, 1413], "heidelberg": [217, 520, 521], "ut": 217, "ee": [217, 313], "mtat": 217, "238": 217, "2014_fall": 217, "domin": [218, 219, 311, 410, 414, 481, 482, 483, 484, 758, 1325, 1395, 1400, 1406, 1407], "opt": [218, 221, 1425], "min_weight_dominating_set": 219, "vazirani": [219, 221], "vijai": [219, 221, 517], "min_dens": 220, "95": [220, 590, 1283, 1284, 1382], "nest": [220, 427, 728, 730, 791, 1038, 1045, 1061, 1094, 1296, 1308, 1348, 1355, 1356, 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"license"]], "Bibliography": [[110, "bibliography"]], "Install": [[111, "install"]], "Install the released version": [[111, "install-the-released-version"]], "Install the development version": [[111, "install-the-development-version"]], "Extra packages": [[111, "extra-packages"]], "Test a source distribution": [[111, "test-a-source-distribution"]], "Test an installed package": [[111, "test-an-installed-package"]], "Approximations and Heuristics": [[112, "module-networkx.algorithms.approximation"]], "Connectivity": [[112, "module-networkx.algorithms.approximation.connectivity"], [126, "connectivity"], [127, "module-networkx.algorithms.connectivity"]], "K-components": [[112, "module-networkx.algorithms.approximation.kcomponents"]], "Clique": [[112, "module-networkx.algorithms.approximation.clique"], [121, "module-networkx.algorithms.clique"]], "Clustering": [[112, "module-networkx.algorithms.approximation.clustering_coefficient"], [115, "module-networkx.algorithms.bipartite.cluster"], 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"effective_size": [[688, "effective-size"]], "local_constraint": [[689, "local-constraint"]], "dedensify": [[690, "dedensify"]], "snap_aggregation": [[691, "snap-aggregation"]], "connected_double_edge_swap": [[692, "connected-double-edge-swap"]], "directed_edge_swap": [[693, "directed-edge-swap"]], "double_edge_swap": [[694, "double-edge-swap"]], "find_threshold_graph": [[695, "find-threshold-graph"]], "is_threshold_graph": [[696, "is-threshold-graph"]], "hamiltonian_path": [[697, "hamiltonian-path"]], "is_reachable": [[698, "is-reachable"]], "is_tournament": [[700, "is-tournament"]], "random_tournament": [[701, "random-tournament"]], "score_sequence": [[702, "score-sequence"]], "bfs_beam_edges": [[703, "bfs-beam-edges"]], "bfs_edges": [[704, "bfs-edges"]], "bfs_layers": [[705, "bfs-layers"]], "bfs_predecessors": [[706, "bfs-predecessors"]], "bfs_successors": [[707, "bfs-successors"]], "bfs_tree": [[708, "bfs-tree"]], "descendants_at_distance": [[709, "descendants-at-distance"]], "dfs_edges": [[710, "dfs-edges"]], "dfs_labeled_edges": [[711, "dfs-labeled-edges"]], "dfs_postorder_nodes": [[712, "dfs-postorder-nodes"]], "dfs_predecessors": [[713, "dfs-predecessors"]], "dfs_preorder_nodes": [[714, "dfs-preorder-nodes"]], "dfs_successors": [[715, "dfs-successors"]], "dfs_tree": [[716, "dfs-tree"]], "edge_bfs": [[717, "edge-bfs"]], "edge_dfs": [[718, "edge-dfs"]], "networkx.algorithms.tree.branchings.ArborescenceIterator": [[719, "networkx-algorithms-tree-branchings-arborescenceiterator"]], "networkx.algorithms.tree.branchings.Edmonds": [[720, "networkx-algorithms-tree-branchings-edmonds"]], "branching_weight": [[721, "branching-weight"]], "greedy_branching": [[722, "greedy-branching"]], "maximum_branching": [[723, "maximum-branching"]], "maximum_spanning_arborescence": [[724, "maximum-spanning-arborescence"]], "minimum_branching": [[725, "minimum-branching"]], "minimum_spanning_arborescence": [[726, "minimum-spanning-arborescence"]], "NotATree": [[727, "notatree"]], "from_nested_tuple": [[728, "from-nested-tuple"]], "from_prufer_sequence": [[729, "from-prufer-sequence"]], "to_nested_tuple": [[730, "to-nested-tuple"]], "to_prufer_sequence": [[731, "to-prufer-sequence"]], "junction_tree": [[732, "junction-tree"]], "networkx.algorithms.tree.mst.SpanningTreeIterator": [[733, "networkx-algorithms-tree-mst-spanningtreeiterator"]], "maximum_spanning_edges": [[734, "maximum-spanning-edges"]], "maximum_spanning_tree": [[735, "maximum-spanning-tree"]], "minimum_spanning_edges": [[736, "minimum-spanning-edges"]], "minimum_spanning_tree": [[737, "minimum-spanning-tree"]], "random_spanning_tree": [[738, "random-spanning-tree"]], "join": [[739, "join"]], "is_arborescence": [[740, "is-arborescence"]], "is_branching": [[741, "is-branching"]], "is_forest": [[742, "is-forest"]], "is_tree": [[743, "is-tree"]], "all_triads": [[744, "all-triads"]], "all_triplets": [[745, "all-triplets"]], "is_triad": [[746, "is-triad"]], "random_triad": [[747, "random-triad"]], "triad_type": [[748, "triad-type"]], "triadic_census": [[749, "triadic-census"]], "triads_by_type": [[750, "triads-by-type"]], "closeness_vitality": [[751, "closeness-vitality"]], "voronoi_cells": [[752, "voronoi-cells"]], "wiener_index": [[753, "wiener-index"]], "Graph Hashing": [[754, "module-networkx.algorithms.graph_hashing"]], "Graphical degree sequence": [[755, "module-networkx.algorithms.graphical"]], "Hierarchy": [[756, "module-networkx.algorithms.hierarchy"]], "Hybrid": [[757, "module-networkx.algorithms.hybrid"]], "Isolates": [[759, "module-networkx.algorithms.isolate"]], "Isomorphism": [[760, "isomorphism"]], "VF2++": [[760, "module-networkx.algorithms.isomorphism.vf2pp"]], "VF2++ Algorithm": [[760, "vf2-algorithm"]], "Tree Isomorphism": [[760, "module-networkx.algorithms.isomorphism.tree_isomorphism"]], "Advanced Interfaces": [[760, "advanced-interfaces"]], "ISMAGS Algorithm": [[761, "module-networkx.algorithms.isomorphism.ismags"]], "Notes": [[761, "notes"], [762, "notes"]], "ISMAGS object": [[761, "ismags-object"]], "VF2 Algorithm": [[762, "module-networkx.algorithms.isomorphism.isomorphvf2"]], "Subgraph Isomorphism": [[762, "subgraph-isomorphism"]], "Graph Matcher": [[762, "graph-matcher"]], "DiGraph Matcher": [[762, "digraph-matcher"]], "Match helpers": [[762, "match-helpers"]], "Link Analysis": [[763, "link-analysis"]], "PageRank": [[763, "module-networkx.algorithms.link_analysis.pagerank_alg"]], "Hits": [[763, "module-networkx.algorithms.link_analysis.hits_alg"]], "Link Prediction": [[764, "module-networkx.algorithms.link_prediction"]], "Lowest Common Ancestor": [[765, "module-networkx.algorithms.lowest_common_ancestors"]], "Minors": [[767, "module-networkx.algorithms.minors"]], "Maximal independent set": [[768, "module-networkx.algorithms.mis"]], "Moral": [[769, "module-networkx.algorithms.moral"]], "Node Classification": [[770, "module-networkx.algorithms.node_classification"]], "non-randomness": [[771, "module-networkx.algorithms.non_randomness"]], "Operators": [[772, "operators"]], "Planar Drawing": [[773, "module-networkx.algorithms.planar_drawing"]], "Planarity": [[774, "module-networkx.algorithms.planarity"]], "Graph Polynomials": [[775, "module-networkx.algorithms.polynomials"]], "Reciprocity": [[776, "module-networkx.algorithms.reciprocity"]], "Regular": [[777, "module-networkx.algorithms.regular"]], "Rich Club": [[778, "module-networkx.algorithms.richclub"]], "Shortest Paths": [[779, "module-networkx.algorithms.shortest_paths.generic"]], "Advanced Interface": [[779, "module-networkx.algorithms.shortest_paths.unweighted"]], "Dense Graphs": [[779, "module-networkx.algorithms.shortest_paths.dense"]], "A* Algorithm": [[779, "module-networkx.algorithms.shortest_paths.astar"]], "Similarity Measures": [[780, "module-networkx.algorithms.similarity"]], "Simple Paths": [[781, "module-networkx.algorithms.simple_paths"]], "Small-world": [[782, "module-networkx.algorithms.smallworld"]], "s metric": [[783, "module-networkx.algorithms.smetric"]], "Sparsifiers": [[784, "module-networkx.algorithms.sparsifiers"]], "Structural holes": [[785, "module-networkx.algorithms.structuralholes"]], "Summarization": [[786, "module-networkx.algorithms.summarization"]], "Swap": [[787, "module-networkx.algorithms.swap"]], "Threshold Graphs": [[788, "module-networkx.algorithms.threshold"]], "Tournament": [[789, "module-networkx.algorithms.tournament"]], "Traversal": [[790, "traversal"]], "Depth First Search": [[790, "module-networkx.algorithms.traversal.depth_first_search"]], "Breadth First Search": [[790, "module-networkx.algorithms.traversal.breadth_first_search"]], "Beam search": [[790, "module-networkx.algorithms.traversal.beamsearch"]], "Depth First Search on Edges": [[790, "module-networkx.algorithms.traversal.edgedfs"]], "Breadth First Search on Edges": [[790, "module-networkx.algorithms.traversal.edgebfs"]], "Tree": [[791, "tree"]], "Recognition": [[791, 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"AdjacencyView.values": [[801, "adjacencyview-values"]], "AtlasView.copy": [[802, "atlasview-copy"]], "AtlasView.get": [[803, "atlasview-get"]], "AtlasView.items": [[804, "atlasview-items"]], "AtlasView.keys": [[805, "atlasview-keys"]], "AtlasView.values": [[806, "atlasview-values"]], "FilterAdjacency.get": [[807, "filteradjacency-get"]], "FilterAdjacency.items": [[808, "filteradjacency-items"]], "FilterAdjacency.keys": [[809, "filteradjacency-keys"]], "FilterAdjacency.values": [[810, "filteradjacency-values"]], "FilterAtlas.get": [[811, "filteratlas-get"]], "FilterAtlas.items": [[812, "filteratlas-items"]], "FilterAtlas.keys": [[813, "filteratlas-keys"]], "FilterAtlas.values": [[814, "filteratlas-values"]], "FilterMultiAdjacency.get": [[815, "filtermultiadjacency-get"]], "FilterMultiAdjacency.items": [[816, "filtermultiadjacency-items"]], "FilterMultiAdjacency.keys": [[817, "filtermultiadjacency-keys"]], "FilterMultiAdjacency.values": [[818, "filtermultiadjacency-values"]], "FilterMultiInner.get": [[819, "filtermultiinner-get"]], "FilterMultiInner.items": [[820, "filtermultiinner-items"]], "FilterMultiInner.keys": [[821, "filtermultiinner-keys"]], "FilterMultiInner.values": [[822, "filtermultiinner-values"]], "MultiAdjacencyView.copy": [[823, "multiadjacencyview-copy"]], "MultiAdjacencyView.get": [[824, "multiadjacencyview-get"]], "MultiAdjacencyView.items": [[825, "multiadjacencyview-items"]], "MultiAdjacencyView.keys": [[826, "multiadjacencyview-keys"]], "MultiAdjacencyView.values": [[827, "multiadjacencyview-values"]], "UnionAdjacency.copy": [[828, "unionadjacency-copy"]], "UnionAdjacency.get": [[829, "unionadjacency-get"]], "UnionAdjacency.items": [[830, "unionadjacency-items"]], "UnionAdjacency.keys": [[831, "unionadjacency-keys"]], "UnionAdjacency.values": [[832, "unionadjacency-values"]], "UnionAtlas.copy": [[833, "unionatlas-copy"]], "UnionAtlas.get": [[834, "unionatlas-get"]], "UnionAtlas.items": [[835, "unionatlas-items"]], "UnionAtlas.keys": 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"DiGraph.add_edges_from": [[854, "digraph-add-edges-from"]], "DiGraph.add_node": [[855, "digraph-add-node"]], "DiGraph.add_nodes_from": [[856, "digraph-add-nodes-from"]], "DiGraph.add_weighted_edges_from": [[857, "digraph-add-weighted-edges-from"]], "DiGraph.adj": [[858, "digraph-adj"]], "DiGraph.adjacency": [[859, "digraph-adjacency"]], "DiGraph.clear": [[860, "digraph-clear"]], "DiGraph.clear_edges": [[861, "digraph-clear-edges"]], "DiGraph.copy": [[862, "digraph-copy"]], "DiGraph.degree": [[863, "digraph-degree"]], "DiGraph.edge_subgraph": [[864, "digraph-edge-subgraph"]], "DiGraph.edges": [[865, "digraph-edges"]], "DiGraph.get_edge_data": [[866, "digraph-get-edge-data"]], "DiGraph.has_edge": [[867, "digraph-has-edge"]], "DiGraph.has_node": [[868, "digraph-has-node"]], "DiGraph.in_degree": [[869, "digraph-in-degree"]], "DiGraph.in_edges": [[870, "digraph-in-edges"]], "DiGraph.nbunch_iter": [[871, "digraph-nbunch-iter"]], "DiGraph.neighbors": [[872, "digraph-neighbors"]], "DiGraph.nodes": [[873, "digraph-nodes"]], "DiGraph.number_of_edges": [[874, "digraph-number-of-edges"]], "DiGraph.number_of_nodes": [[875, "digraph-number-of-nodes"]], "DiGraph.order": [[876, "digraph-order"]], "DiGraph.out_degree": [[877, "digraph-out-degree"]], "DiGraph.out_edges": [[878, "digraph-out-edges"]], "DiGraph.pred": [[879, "digraph-pred"]], "DiGraph.predecessors": [[880, "digraph-predecessors"]], "DiGraph.remove_edge": [[881, "digraph-remove-edge"]], "DiGraph.remove_edges_from": [[882, "digraph-remove-edges-from"]], "DiGraph.remove_node": [[883, "digraph-remove-node"]], "DiGraph.remove_nodes_from": [[884, "digraph-remove-nodes-from"]], "DiGraph.reverse": [[885, "digraph-reverse"]], "DiGraph.size": [[886, "digraph-size"]], "DiGraph.subgraph": [[887, "digraph-subgraph"]], "DiGraph.succ": [[888, "digraph-succ"]], "DiGraph.successors": [[889, "digraph-successors"]], "DiGraph.to_directed": [[890, "digraph-to-directed"]], "DiGraph.to_undirected": [[891, 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"graph-has-edge"]], "Graph.has_node": [[913, "graph-has-node"]], "Graph.nbunch_iter": [[914, "graph-nbunch-iter"]], "Graph.neighbors": [[915, "graph-neighbors"]], "Graph.nodes": [[916, "graph-nodes"]], "Graph.number_of_edges": [[917, "graph-number-of-edges"]], "Graph.number_of_nodes": [[918, "graph-number-of-nodes"]], "Graph.order": [[919, "graph-order"]], "Graph.remove_edge": [[920, "graph-remove-edge"]], "Graph.remove_edges_from": [[921, "graph-remove-edges-from"]], "Graph.remove_node": [[922, "graph-remove-node"]], "Graph.remove_nodes_from": [[923, "graph-remove-nodes-from"]], "Graph.size": [[924, "graph-size"]], "Graph.subgraph": [[925, "graph-subgraph"]], "Graph.to_directed": [[926, "graph-to-directed"]], "Graph.to_undirected": [[927, "graph-to-undirected"]], "Graph.update": [[928, "graph-update"]], "MultiDiGraph.__contains__": [[929, "multidigraph-contains"]], "MultiDiGraph.__getitem__": [[930, "multidigraph-getitem"]], "MultiDiGraph.__init__": [[931, "multidigraph-init"]], "MultiDiGraph.__iter__": [[932, "multidigraph-iter"]], "MultiDiGraph.__len__": [[933, "multidigraph-len"]], "MultiDiGraph.add_edge": [[934, "multidigraph-add-edge"]], "MultiDiGraph.add_edges_from": [[935, "multidigraph-add-edges-from"]], "MultiDiGraph.add_node": [[936, "multidigraph-add-node"]], "MultiDiGraph.add_nodes_from": [[937, "multidigraph-add-nodes-from"]], "MultiDiGraph.add_weighted_edges_from": [[938, "multidigraph-add-weighted-edges-from"]], "MultiDiGraph.adj": [[939, "multidigraph-adj"]], "MultiDiGraph.adjacency": [[940, "multidigraph-adjacency"]], "MultiDiGraph.clear": [[941, "multidigraph-clear"]], "MultiDiGraph.clear_edges": [[942, "multidigraph-clear-edges"]], "MultiDiGraph.copy": [[943, "multidigraph-copy"]], "MultiDiGraph.degree": [[944, "multidigraph-degree"]], "MultiDiGraph.edge_subgraph": [[945, "multidigraph-edge-subgraph"]], "MultiDiGraph.edges": [[946, "multidigraph-edges"]], "MultiDiGraph.get_edge_data": [[947, "multidigraph-get-edge-data"]], "MultiDiGraph.has_edge": [[948, "multidigraph-has-edge"]], "MultiDiGraph.has_node": [[949, "multidigraph-has-node"]], "MultiDiGraph.in_degree": [[950, "multidigraph-in-degree"]], "MultiDiGraph.in_edges": [[951, "multidigraph-in-edges"]], "MultiDiGraph.nbunch_iter": [[952, "multidigraph-nbunch-iter"]], "MultiDiGraph.neighbors": [[953, "multidigraph-neighbors"]], "MultiDiGraph.new_edge_key": [[954, "multidigraph-new-edge-key"]], "MultiDiGraph.nodes": [[955, "multidigraph-nodes"]], "MultiDiGraph.number_of_edges": [[956, "multidigraph-number-of-edges"]], "MultiDiGraph.number_of_nodes": [[957, "multidigraph-number-of-nodes"]], "MultiDiGraph.order": [[958, "multidigraph-order"]], "MultiDiGraph.out_degree": [[959, "multidigraph-out-degree"]], "MultiDiGraph.out_edges": [[960, "multidigraph-out-edges"]], "MultiDiGraph.predecessors": [[961, "multidigraph-predecessors"]], "MultiDiGraph.remove_edge": [[962, "multidigraph-remove-edge"]], "MultiDiGraph.remove_edges_from": [[963, 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"multigraph-new-edge-key"]], "MultiGraph.nodes": [[998, "multigraph-nodes"]], "MultiGraph.number_of_edges": [[999, "multigraph-number-of-edges"]], "MultiGraph.number_of_nodes": [[1000, "multigraph-number-of-nodes"]], "MultiGraph.order": [[1001, "multigraph-order"]], "MultiGraph.remove_edge": [[1002, "multigraph-remove-edge"]], "MultiGraph.remove_edges_from": [[1003, "multigraph-remove-edges-from"]], "MultiGraph.remove_node": [[1004, "multigraph-remove-node"]], "MultiGraph.remove_nodes_from": [[1005, "multigraph-remove-nodes-from"]], "MultiGraph.size": [[1006, "multigraph-size"]], "MultiGraph.subgraph": [[1007, "multigraph-subgraph"]], "MultiGraph.to_directed": [[1008, "multigraph-to-directed"]], "MultiGraph.to_undirected": [[1009, "multigraph-to-undirected"]], "MultiGraph.update": [[1010, "multigraph-update"]], "_dispatch": [[1011, "dispatch"]], "networkx.classes.coreviews.AdjacencyView": [[1012, "networkx-classes-coreviews-adjacencyview"]], "networkx.classes.coreviews.AtlasView": 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Applying classic graph operations, such as:": [[1426, "applying-classic-graph-operations-such-as"]], "2. Using a call to one of the classic small graphs, e.g.,": [[1426, "using-a-call-to-one-of-the-classic-small-graphs-e-g"]], "3. Using a (constructive) generator for a classic graph, e.g.,": [[1426, "using-a-constructive-generator-for-a-classic-graph-e-g"]], "4. Using a stochastic graph generator, e.g,": [[1426, "using-a-stochastic-graph-generator-e-g"]], "5. Reading a graph stored in a file using common graph formats": [[1426, "reading-a-graph-stored-in-a-file-using-common-graph-formats"]], "Analyzing graphs": [[1426, "analyzing-graphs"]], "Drawing graphs": [[1426, "drawing-graphs"]]}, "indexentries": {"module": [[112, "module-networkx.algorithms.approximation"], [112, "module-networkx.algorithms.approximation.clique"], [112, "module-networkx.algorithms.approximation.clustering_coefficient"], [112, "module-networkx.algorithms.approximation.connectivity"], [112, "module-networkx.algorithms.approximation.distance_measures"], [112, "module-networkx.algorithms.approximation.dominating_set"], [112, "module-networkx.algorithms.approximation.kcomponents"], [112, "module-networkx.algorithms.approximation.matching"], [112, "module-networkx.algorithms.approximation.maxcut"], [112, "module-networkx.algorithms.approximation.ramsey"], [112, "module-networkx.algorithms.approximation.steinertree"], [112, 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"module-networkx.algorithms.approximation.clustering_coefficient"]], "networkx.algorithms.approximation.connectivity": [[112, "module-networkx.algorithms.approximation.connectivity"]], "networkx.algorithms.approximation.distance_measures": [[112, "module-networkx.algorithms.approximation.distance_measures"]], "networkx.algorithms.approximation.dominating_set": [[112, "module-networkx.algorithms.approximation.dominating_set"]], "networkx.algorithms.approximation.kcomponents": [[112, "module-networkx.algorithms.approximation.kcomponents"]], "networkx.algorithms.approximation.matching": [[112, "module-networkx.algorithms.approximation.matching"]], "networkx.algorithms.approximation.maxcut": [[112, "module-networkx.algorithms.approximation.maxcut"]], "networkx.algorithms.approximation.ramsey": [[112, "module-networkx.algorithms.approximation.ramsey"]], "networkx.algorithms.approximation.steinertree": [[112, "module-networkx.algorithms.approximation.steinertree"]], 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"module-networkx.algorithms.bipartite.covering"]], "networkx.algorithms.bipartite.edgelist": [[115, "module-networkx.algorithms.bipartite.edgelist"]], "networkx.algorithms.bipartite.generators": [[115, "module-networkx.algorithms.bipartite.generators"]], "networkx.algorithms.bipartite.matching": [[115, "module-networkx.algorithms.bipartite.matching"]], "networkx.algorithms.bipartite.matrix": [[115, "module-networkx.algorithms.bipartite.matrix"]], "networkx.algorithms.bipartite.projection": [[115, "module-networkx.algorithms.bipartite.projection"]], "networkx.algorithms.bipartite.redundancy": [[115, "module-networkx.algorithms.bipartite.redundancy"]], "networkx.algorithms.bipartite.spectral": [[115, "module-networkx.algorithms.bipartite.spectral"]], "networkx.algorithms.boundary": [[116, "module-networkx.algorithms.boundary"]], "networkx.algorithms.bridges": [[117, "module-networkx.algorithms.bridges"]], "networkx.algorithms.centrality": [[118, "module-networkx.algorithms.centrality"]], "networkx.algorithms.chains": [[119, "module-networkx.algorithms.chains"]], "networkx.algorithms.chordal": [[120, "module-networkx.algorithms.chordal"]], "networkx.algorithms.clique": [[121, "module-networkx.algorithms.clique"]], "networkx.algorithms.cluster": [[122, "module-networkx.algorithms.cluster"]], "networkx.algorithms.coloring": [[123, "module-networkx.algorithms.coloring"]], "networkx.algorithms.communicability_alg": [[124, "module-networkx.algorithms.communicability_alg"]], "networkx.algorithms.community": [[125, "module-networkx.algorithms.community"]], "networkx.algorithms.community.asyn_fluid": [[125, "module-networkx.algorithms.community.asyn_fluid"]], "networkx.algorithms.community.centrality": [[125, "module-networkx.algorithms.community.centrality"]], "networkx.algorithms.community.community_utils": [[125, "module-networkx.algorithms.community.community_utils"]], "networkx.algorithms.community.kclique": [[125, "module-networkx.algorithms.community.kclique"]], "networkx.algorithms.community.kernighan_lin": [[125, "module-networkx.algorithms.community.kernighan_lin"]], "networkx.algorithms.community.label_propagation": [[125, "module-networkx.algorithms.community.label_propagation"]], "networkx.algorithms.community.louvain": [[125, "module-networkx.algorithms.community.louvain"]], "networkx.algorithms.community.lukes": [[125, "module-networkx.algorithms.community.lukes"]], "networkx.algorithms.community.modularity_max": [[125, "module-networkx.algorithms.community.modularity_max"]], "networkx.algorithms.community.quality": [[125, "module-networkx.algorithms.community.quality"]], "networkx.algorithms.components": [[126, "module-networkx.algorithms.components"]], "networkx.algorithms.connectivity": [[127, "module-networkx.algorithms.connectivity"]], "networkx.algorithms.connectivity.connectivity": [[127, "module-networkx.algorithms.connectivity.connectivity"]], "networkx.algorithms.connectivity.cuts": [[127, "module-networkx.algorithms.connectivity.cuts"]], "networkx.algorithms.connectivity.disjoint_paths": [[127, "module-networkx.algorithms.connectivity.disjoint_paths"]], "networkx.algorithms.connectivity.edge_augmentation": [[127, "module-networkx.algorithms.connectivity.edge_augmentation"]], "networkx.algorithms.connectivity.edge_kcomponents": [[127, "module-networkx.algorithms.connectivity.edge_kcomponents"]], "networkx.algorithms.connectivity.kcomponents": [[127, "module-networkx.algorithms.connectivity.kcomponents"]], "networkx.algorithms.connectivity.kcutsets": [[127, "module-networkx.algorithms.connectivity.kcutsets"]], "networkx.algorithms.connectivity.stoerwagner": [[127, "module-networkx.algorithms.connectivity.stoerwagner"]], "networkx.algorithms.connectivity.utils": [[127, "module-networkx.algorithms.connectivity.utils"]], "networkx.algorithms.core": [[128, "module-networkx.algorithms.core"]], "networkx.algorithms.covering": [[129, "module-networkx.algorithms.covering"]], "networkx.algorithms.cuts": [[130, "module-networkx.algorithms.cuts"]], "networkx.algorithms.cycles": [[131, "module-networkx.algorithms.cycles"]], "networkx.algorithms.d_separation": [[132, "module-networkx.algorithms.d_separation"]], "networkx.algorithms.dag": [[133, "module-networkx.algorithms.dag"]], "networkx.algorithms.distance_measures": [[134, "module-networkx.algorithms.distance_measures"]], "networkx.algorithms.distance_regular": [[135, "module-networkx.algorithms.distance_regular"]], "networkx.algorithms.dominance": [[136, "module-networkx.algorithms.dominance"]], "networkx.algorithms.dominating": [[137, "module-networkx.algorithms.dominating"]], "networkx.algorithms.efficiency_measures": [[138, "module-networkx.algorithms.efficiency_measures"]], "networkx.algorithms.euler": [[139, "module-networkx.algorithms.euler"]], "networkx.algorithms.flow": [[140, "module-networkx.algorithms.flow"]], "construct() (edgecomponentauxgraph class method)": [[141, "networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.construct"]], "k_edge_components() (edgecomponentauxgraph method)": [[142, "networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.k_edge_components"]], "k_edge_subgraphs() (edgecomponentauxgraph method)": [[143, "networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.k_edge_subgraphs"]], "analyze_symmetry() (ismags method)": [[144, "networkx.algorithms.isomorphism.ISMAGS.analyze_symmetry"]], "find_isomorphisms() (ismags method)": [[145, "networkx.algorithms.isomorphism.ISMAGS.find_isomorphisms"]], "is_isomorphic() (ismags method)": [[146, "networkx.algorithms.isomorphism.ISMAGS.is_isomorphic"]], "isomorphisms_iter() (ismags method)": [[147, "networkx.algorithms.isomorphism.ISMAGS.isomorphisms_iter"]], "largest_common_subgraph() (ismags method)": [[148, "networkx.algorithms.isomorphism.ISMAGS.largest_common_subgraph"]], "subgraph_is_isomorphic() (ismags method)": [[149, "networkx.algorithms.isomorphism.ISMAGS.subgraph_is_isomorphic"]], "subgraph_isomorphisms_iter() (ismags method)": [[150, "networkx.algorithms.isomorphism.ISMAGS.subgraph_isomorphisms_iter"]], "add_edge() (planarembedding method)": [[151, "networkx.algorithms.planarity.PlanarEmbedding.add_edge"]], "add_edges_from() (planarembedding method)": [[152, "networkx.algorithms.planarity.PlanarEmbedding.add_edges_from"]], "add_half_edge_ccw() (planarembedding method)": [[153, "networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_ccw"]], "add_half_edge_cw() (planarembedding method)": [[154, "networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_cw"]], "add_half_edge_first() (planarembedding method)": [[155, "networkx.algorithms.planarity.PlanarEmbedding.add_half_edge_first"]], "add_node() (planarembedding method)": [[156, "networkx.algorithms.planarity.PlanarEmbedding.add_node"]], "add_nodes_from() (planarembedding method)": [[157, "networkx.algorithms.planarity.PlanarEmbedding.add_nodes_from"]], "add_weighted_edges_from() (planarembedding method)": [[158, "networkx.algorithms.planarity.PlanarEmbedding.add_weighted_edges_from"]], "adj (planarembedding property)": [[159, "networkx.algorithms.planarity.PlanarEmbedding.adj"]], "adjacency() (planarembedding method)": [[160, "networkx.algorithms.planarity.PlanarEmbedding.adjacency"]], "check_structure() (planarembedding method)": [[161, "networkx.algorithms.planarity.PlanarEmbedding.check_structure"]], "clear() (planarembedding method)": [[162, "networkx.algorithms.planarity.PlanarEmbedding.clear"]], "clear_edges() (planarembedding method)": [[163, "networkx.algorithms.planarity.PlanarEmbedding.clear_edges"]], "connect_components() (planarembedding method)": [[164, "networkx.algorithms.planarity.PlanarEmbedding.connect_components"]], "copy() (planarembedding method)": [[165, "networkx.algorithms.planarity.PlanarEmbedding.copy"]], "degree (planarembedding property)": 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"networkx.algorithms.planarity.PlanarEmbedding.in_degree"]], "in_edges (planarembedding property)": [[176, "networkx.algorithms.planarity.PlanarEmbedding.in_edges"]], "is_directed() (planarembedding method)": [[177, "networkx.algorithms.planarity.PlanarEmbedding.is_directed"]], "is_multigraph() (planarembedding method)": [[178, "networkx.algorithms.planarity.PlanarEmbedding.is_multigraph"]], "name (planarembedding property)": [[179, "networkx.algorithms.planarity.PlanarEmbedding.name"]], "nbunch_iter() (planarembedding method)": [[180, "networkx.algorithms.planarity.PlanarEmbedding.nbunch_iter"]], "neighbors() (planarembedding method)": [[181, "networkx.algorithms.planarity.PlanarEmbedding.neighbors"]], "neighbors_cw_order() (planarembedding method)": [[182, "networkx.algorithms.planarity.PlanarEmbedding.neighbors_cw_order"]], "next_face_half_edge() (planarembedding method)": [[183, "networkx.algorithms.planarity.PlanarEmbedding.next_face_half_edge"]], "nodes (planarembedding property)": [[184, "networkx.algorithms.planarity.PlanarEmbedding.nodes"]], "number_of_edges() (planarembedding method)": [[185, "networkx.algorithms.planarity.PlanarEmbedding.number_of_edges"]], "number_of_nodes() (planarembedding method)": [[186, "networkx.algorithms.planarity.PlanarEmbedding.number_of_nodes"]], "order() (planarembedding method)": [[187, "networkx.algorithms.planarity.PlanarEmbedding.order"]], "out_degree (planarembedding property)": [[188, "networkx.algorithms.planarity.PlanarEmbedding.out_degree"]], "out_edges (planarembedding property)": [[189, "networkx.algorithms.planarity.PlanarEmbedding.out_edges"]], "pred (planarembedding property)": [[190, "networkx.algorithms.planarity.PlanarEmbedding.pred"]], "predecessors() (planarembedding method)": [[191, "networkx.algorithms.planarity.PlanarEmbedding.predecessors"]], "remove_edge() (planarembedding method)": [[192, "networkx.algorithms.planarity.PlanarEmbedding.remove_edge"]], "remove_edges_from() (planarembedding method)": [[193, "networkx.algorithms.planarity.PlanarEmbedding.remove_edges_from"]], "remove_node() (planarembedding method)": [[194, "networkx.algorithms.planarity.PlanarEmbedding.remove_node"]], "remove_nodes_from() (planarembedding method)": [[195, "networkx.algorithms.planarity.PlanarEmbedding.remove_nodes_from"]], "reverse() (planarembedding method)": [[196, "networkx.algorithms.planarity.PlanarEmbedding.reverse"]], "set_data() (planarembedding method)": [[197, "networkx.algorithms.planarity.PlanarEmbedding.set_data"]], "size() (planarembedding method)": [[198, "networkx.algorithms.planarity.PlanarEmbedding.size"]], "subgraph() (planarembedding method)": [[199, "networkx.algorithms.planarity.PlanarEmbedding.subgraph"]], "succ (planarembedding property)": [[200, "networkx.algorithms.planarity.PlanarEmbedding.succ"]], "successors() (planarembedding method)": [[201, "networkx.algorithms.planarity.PlanarEmbedding.successors"]], "to_directed() (planarembedding method)": [[202, "networkx.algorithms.planarity.PlanarEmbedding.to_directed"]], "to_directed_class() (planarembedding method)": [[203, "networkx.algorithms.planarity.PlanarEmbedding.to_directed_class"]], "to_undirected() (planarembedding method)": [[204, "networkx.algorithms.planarity.PlanarEmbedding.to_undirected"]], "to_undirected_class() (planarembedding method)": [[205, "networkx.algorithms.planarity.PlanarEmbedding.to_undirected_class"]], "traverse_face() (planarembedding method)": [[206, "networkx.algorithms.planarity.PlanarEmbedding.traverse_face"]], "update() (planarembedding method)": [[207, "networkx.algorithms.planarity.PlanarEmbedding.update"]], "find_optimum() (edmonds method)": [[208, "networkx.algorithms.tree.branchings.Edmonds.find_optimum"]], "clique_removal() (in module networkx.algorithms.approximation.clique)": [[209, "networkx.algorithms.approximation.clique.clique_removal"]], "large_clique_size() (in module networkx.algorithms.approximation.clique)": [[210, "networkx.algorithms.approximation.clique.large_clique_size"]], "max_clique() (in module networkx.algorithms.approximation.clique)": [[211, "networkx.algorithms.approximation.clique.max_clique"]], "maximum_independent_set() (in module networkx.algorithms.approximation.clique)": [[212, "networkx.algorithms.approximation.clique.maximum_independent_set"]], "average_clustering() (in module networkx.algorithms.approximation.clustering_coefficient)": [[213, "networkx.algorithms.approximation.clustering_coefficient.average_clustering"]], "all_pairs_node_connectivity() (in module networkx.algorithms.approximation.connectivity)": [[214, "networkx.algorithms.approximation.connectivity.all_pairs_node_connectivity"]], "local_node_connectivity() (in module networkx.algorithms.approximation.connectivity)": [[215, "networkx.algorithms.approximation.connectivity.local_node_connectivity"]], "node_connectivity() (in module networkx.algorithms.approximation.connectivity)": [[216, "networkx.algorithms.approximation.connectivity.node_connectivity"]], "diameter() (in module networkx.algorithms.approximation.distance_measures)": [[217, "networkx.algorithms.approximation.distance_measures.diameter"]], "min_edge_dominating_set() (in module networkx.algorithms.approximation.dominating_set)": [[218, "networkx.algorithms.approximation.dominating_set.min_edge_dominating_set"]], "min_weighted_dominating_set() (in module networkx.algorithms.approximation.dominating_set)": [[219, "networkx.algorithms.approximation.dominating_set.min_weighted_dominating_set"]], "k_components() (in module networkx.algorithms.approximation.kcomponents)": [[220, "networkx.algorithms.approximation.kcomponents.k_components"]], "min_maximal_matching() (in module networkx.algorithms.approximation.matching)": [[221, "networkx.algorithms.approximation.matching.min_maximal_matching"]], "one_exchange() (in module networkx.algorithms.approximation.maxcut)": [[222, "networkx.algorithms.approximation.maxcut.one_exchange"]], "randomized_partitioning() (in module networkx.algorithms.approximation.maxcut)": [[223, "networkx.algorithms.approximation.maxcut.randomized_partitioning"]], "ramsey_r2() (in module networkx.algorithms.approximation.ramsey)": [[224, "networkx.algorithms.approximation.ramsey.ramsey_R2"]], "metric_closure() (in module networkx.algorithms.approximation.steinertree)": [[225, "networkx.algorithms.approximation.steinertree.metric_closure"]], "steiner_tree() (in module networkx.algorithms.approximation.steinertree)": [[226, "networkx.algorithms.approximation.steinertree.steiner_tree"]], "asadpour_atsp() (in module networkx.algorithms.approximation.traveling_salesman)": [[227, "networkx.algorithms.approximation.traveling_salesman.asadpour_atsp"]], "christofides() (in module networkx.algorithms.approximation.traveling_salesman)": [[228, "networkx.algorithms.approximation.traveling_salesman.christofides"]], "greedy_tsp() (in module networkx.algorithms.approximation.traveling_salesman)": [[229, "networkx.algorithms.approximation.traveling_salesman.greedy_tsp"]], "simulated_annealing_tsp() (in module networkx.algorithms.approximation.traveling_salesman)": [[230, "networkx.algorithms.approximation.traveling_salesman.simulated_annealing_tsp"]], "threshold_accepting_tsp() (in module networkx.algorithms.approximation.traveling_salesman)": [[231, "networkx.algorithms.approximation.traveling_salesman.threshold_accepting_tsp"]], "traveling_salesman_problem() (in module networkx.algorithms.approximation.traveling_salesman)": [[232, "networkx.algorithms.approximation.traveling_salesman.traveling_salesman_problem"]], "treewidth_min_degree() (in module networkx.algorithms.approximation.treewidth)": [[233, "networkx.algorithms.approximation.treewidth.treewidth_min_degree"]], "treewidth_min_fill_in() (in module networkx.algorithms.approximation.treewidth)": [[234, "networkx.algorithms.approximation.treewidth.treewidth_min_fill_in"]], "min_weighted_vertex_cover() (in module networkx.algorithms.approximation.vertex_cover)": [[235, "networkx.algorithms.approximation.vertex_cover.min_weighted_vertex_cover"]], "attribute_assortativity_coefficient() (in module networkx.algorithms.assortativity)": [[236, "networkx.algorithms.assortativity.attribute_assortativity_coefficient"]], "attribute_mixing_dict() (in module networkx.algorithms.assortativity)": [[237, "networkx.algorithms.assortativity.attribute_mixing_dict"]], "attribute_mixing_matrix() (in module networkx.algorithms.assortativity)": [[238, "networkx.algorithms.assortativity.attribute_mixing_matrix"]], "average_degree_connectivity() (in module networkx.algorithms.assortativity)": [[239, "networkx.algorithms.assortativity.average_degree_connectivity"]], "average_neighbor_degree() (in module networkx.algorithms.assortativity)": [[240, "networkx.algorithms.assortativity.average_neighbor_degree"]], "degree_assortativity_coefficient() (in module networkx.algorithms.assortativity)": [[241, "networkx.algorithms.assortativity.degree_assortativity_coefficient"]], "degree_mixing_dict() (in module networkx.algorithms.assortativity)": [[242, "networkx.algorithms.assortativity.degree_mixing_dict"]], "degree_mixing_matrix() (in module networkx.algorithms.assortativity)": [[243, "networkx.algorithms.assortativity.degree_mixing_matrix"]], "degree_pearson_correlation_coefficient() (in module networkx.algorithms.assortativity)": [[244, "networkx.algorithms.assortativity.degree_pearson_correlation_coefficient"]], "mixing_dict() (in module networkx.algorithms.assortativity)": [[245, "networkx.algorithms.assortativity.mixing_dict"]], "node_attribute_xy() (in module networkx.algorithms.assortativity)": [[246, "networkx.algorithms.assortativity.node_attribute_xy"]], "node_degree_xy() (in module networkx.algorithms.assortativity)": [[247, "networkx.algorithms.assortativity.node_degree_xy"]], "numeric_assortativity_coefficient() (in module networkx.algorithms.assortativity)": [[248, "networkx.algorithms.assortativity.numeric_assortativity_coefficient"]], "find_asteroidal_triple() (in module networkx.algorithms.asteroidal)": [[249, "networkx.algorithms.asteroidal.find_asteroidal_triple"]], "is_at_free() (in module networkx.algorithms.asteroidal)": [[250, "networkx.algorithms.asteroidal.is_at_free"]], "color() (in module networkx.algorithms.bipartite.basic)": [[251, "networkx.algorithms.bipartite.basic.color"]], "degrees() (in module networkx.algorithms.bipartite.basic)": [[252, "networkx.algorithms.bipartite.basic.degrees"]], "density() (in module networkx.algorithms.bipartite.basic)": [[253, "networkx.algorithms.bipartite.basic.density"]], "is_bipartite() (in module networkx.algorithms.bipartite.basic)": [[254, "networkx.algorithms.bipartite.basic.is_bipartite"]], "is_bipartite_node_set() (in module networkx.algorithms.bipartite.basic)": [[255, "networkx.algorithms.bipartite.basic.is_bipartite_node_set"]], "sets() (in module networkx.algorithms.bipartite.basic)": [[256, "networkx.algorithms.bipartite.basic.sets"]], "betweenness_centrality() (in module networkx.algorithms.bipartite.centrality)": [[257, "networkx.algorithms.bipartite.centrality.betweenness_centrality"]], "closeness_centrality() (in module networkx.algorithms.bipartite.centrality)": [[258, "networkx.algorithms.bipartite.centrality.closeness_centrality"]], "degree_centrality() (in module networkx.algorithms.bipartite.centrality)": [[259, "networkx.algorithms.bipartite.centrality.degree_centrality"]], "average_clustering() (in module networkx.algorithms.bipartite.cluster)": [[260, "networkx.algorithms.bipartite.cluster.average_clustering"]], "clustering() (in module networkx.algorithms.bipartite.cluster)": [[261, "networkx.algorithms.bipartite.cluster.clustering"]], "latapy_clustering() (in module networkx.algorithms.bipartite.cluster)": [[262, "networkx.algorithms.bipartite.cluster.latapy_clustering"]], "robins_alexander_clustering() (in module networkx.algorithms.bipartite.cluster)": [[263, "networkx.algorithms.bipartite.cluster.robins_alexander_clustering"]], "min_edge_cover() (in module networkx.algorithms.bipartite.covering)": [[264, "networkx.algorithms.bipartite.covering.min_edge_cover"]], "generate_edgelist() (in module networkx.algorithms.bipartite.edgelist)": [[265, "networkx.algorithms.bipartite.edgelist.generate_edgelist"]], "parse_edgelist() (in module networkx.algorithms.bipartite.edgelist)": [[266, "networkx.algorithms.bipartite.edgelist.parse_edgelist"]], "read_edgelist() (in module networkx.algorithms.bipartite.edgelist)": [[267, "networkx.algorithms.bipartite.edgelist.read_edgelist"]], "write_edgelist() (in module networkx.algorithms.bipartite.edgelist)": [[268, "networkx.algorithms.bipartite.edgelist.write_edgelist"]], "alternating_havel_hakimi_graph() (in module networkx.algorithms.bipartite.generators)": [[269, "networkx.algorithms.bipartite.generators.alternating_havel_hakimi_graph"]], "complete_bipartite_graph() (in module networkx.algorithms.bipartite.generators)": [[270, "networkx.algorithms.bipartite.generators.complete_bipartite_graph"]], "configuration_model() (in module networkx.algorithms.bipartite.generators)": [[271, "networkx.algorithms.bipartite.generators.configuration_model"]], "gnmk_random_graph() (in module networkx.algorithms.bipartite.generators)": [[272, "networkx.algorithms.bipartite.generators.gnmk_random_graph"]], "havel_hakimi_graph() (in module networkx.algorithms.bipartite.generators)": [[273, "networkx.algorithms.bipartite.generators.havel_hakimi_graph"]], "preferential_attachment_graph() (in module networkx.algorithms.bipartite.generators)": [[274, "networkx.algorithms.bipartite.generators.preferential_attachment_graph"]], "random_graph() (in module networkx.algorithms.bipartite.generators)": [[275, "networkx.algorithms.bipartite.generators.random_graph"]], "reverse_havel_hakimi_graph() (in module networkx.algorithms.bipartite.generators)": [[276, "networkx.algorithms.bipartite.generators.reverse_havel_hakimi_graph"]], "eppstein_matching() (in module networkx.algorithms.bipartite.matching)": [[277, "networkx.algorithms.bipartite.matching.eppstein_matching"]], "hopcroft_karp_matching() (in module networkx.algorithms.bipartite.matching)": [[278, "networkx.algorithms.bipartite.matching.hopcroft_karp_matching"]], "maximum_matching() (in module networkx.algorithms.bipartite.matching)": [[279, "networkx.algorithms.bipartite.matching.maximum_matching"]], "minimum_weight_full_matching() (in module networkx.algorithms.bipartite.matching)": [[280, "networkx.algorithms.bipartite.matching.minimum_weight_full_matching"]], "to_vertex_cover() (in module networkx.algorithms.bipartite.matching)": [[281, "networkx.algorithms.bipartite.matching.to_vertex_cover"]], "biadjacency_matrix() (in module networkx.algorithms.bipartite.matrix)": [[282, "networkx.algorithms.bipartite.matrix.biadjacency_matrix"]], "from_biadjacency_matrix() (in module networkx.algorithms.bipartite.matrix)": [[283, "networkx.algorithms.bipartite.matrix.from_biadjacency_matrix"]], "collaboration_weighted_projected_graph() (in module networkx.algorithms.bipartite.projection)": [[284, "networkx.algorithms.bipartite.projection.collaboration_weighted_projected_graph"]], "generic_weighted_projected_graph() (in module networkx.algorithms.bipartite.projection)": [[285, "networkx.algorithms.bipartite.projection.generic_weighted_projected_graph"]], "overlap_weighted_projected_graph() (in module networkx.algorithms.bipartite.projection)": [[286, "networkx.algorithms.bipartite.projection.overlap_weighted_projected_graph"]], "projected_graph() (in module networkx.algorithms.bipartite.projection)": [[287, "networkx.algorithms.bipartite.projection.projected_graph"]], "weighted_projected_graph() (in module networkx.algorithms.bipartite.projection)": [[288, "networkx.algorithms.bipartite.projection.weighted_projected_graph"]], "node_redundancy() (in module networkx.algorithms.bipartite.redundancy)": [[289, "networkx.algorithms.bipartite.redundancy.node_redundancy"]], "spectral_bipartivity() (in module networkx.algorithms.bipartite.spectral)": [[290, "networkx.algorithms.bipartite.spectral.spectral_bipartivity"]], "edge_boundary() (in module networkx.algorithms.boundary)": [[291, "networkx.algorithms.boundary.edge_boundary"]], "node_boundary() (in module networkx.algorithms.boundary)": [[292, "networkx.algorithms.boundary.node_boundary"]], "bridges() (in module networkx.algorithms.bridges)": [[293, "networkx.algorithms.bridges.bridges"]], "has_bridges() (in module networkx.algorithms.bridges)": [[294, "networkx.algorithms.bridges.has_bridges"]], "local_bridges() (in module networkx.algorithms.bridges)": [[295, "networkx.algorithms.bridges.local_bridges"]], "approximate_current_flow_betweenness_centrality() (in module networkx.algorithms.centrality)": [[296, "networkx.algorithms.centrality.approximate_current_flow_betweenness_centrality"]], "betweenness_centrality() (in module networkx.algorithms.centrality)": [[297, "networkx.algorithms.centrality.betweenness_centrality"]], "betweenness_centrality_subset() (in module networkx.algorithms.centrality)": [[298, "networkx.algorithms.centrality.betweenness_centrality_subset"]], "closeness_centrality() (in module networkx.algorithms.centrality)": [[299, "networkx.algorithms.centrality.closeness_centrality"]], "communicability_betweenness_centrality() (in module networkx.algorithms.centrality)": [[300, "networkx.algorithms.centrality.communicability_betweenness_centrality"]], "current_flow_betweenness_centrality() (in module networkx.algorithms.centrality)": [[301, "networkx.algorithms.centrality.current_flow_betweenness_centrality"]], "current_flow_betweenness_centrality_subset() (in module networkx.algorithms.centrality)": [[302, "networkx.algorithms.centrality.current_flow_betweenness_centrality_subset"]], "current_flow_closeness_centrality() (in module networkx.algorithms.centrality)": [[303, "networkx.algorithms.centrality.current_flow_closeness_centrality"]], "degree_centrality() (in module networkx.algorithms.centrality)": [[304, "networkx.algorithms.centrality.degree_centrality"]], "dispersion() (in module networkx.algorithms.centrality)": [[305, "networkx.algorithms.centrality.dispersion"]], "edge_betweenness_centrality() (in module networkx.algorithms.centrality)": [[306, "networkx.algorithms.centrality.edge_betweenness_centrality"]], "edge_betweenness_centrality_subset() (in module networkx.algorithms.centrality)": [[307, "networkx.algorithms.centrality.edge_betweenness_centrality_subset"]], "edge_current_flow_betweenness_centrality() (in module networkx.algorithms.centrality)": [[308, "networkx.algorithms.centrality.edge_current_flow_betweenness_centrality"]], "edge_current_flow_betweenness_centrality_subset() (in module networkx.algorithms.centrality)": [[309, "networkx.algorithms.centrality.edge_current_flow_betweenness_centrality_subset"]], "edge_load_centrality() (in module networkx.algorithms.centrality)": [[310, "networkx.algorithms.centrality.edge_load_centrality"]], "eigenvector_centrality() (in module networkx.algorithms.centrality)": [[311, "networkx.algorithms.centrality.eigenvector_centrality"]], "eigenvector_centrality_numpy() (in module networkx.algorithms.centrality)": [[312, "networkx.algorithms.centrality.eigenvector_centrality_numpy"]], "estrada_index() (in module networkx.algorithms.centrality)": [[313, "networkx.algorithms.centrality.estrada_index"]], "global_reaching_centrality() (in module networkx.algorithms.centrality)": [[314, "networkx.algorithms.centrality.global_reaching_centrality"]], "group_betweenness_centrality() (in module networkx.algorithms.centrality)": [[315, "networkx.algorithms.centrality.group_betweenness_centrality"]], "group_closeness_centrality() (in module networkx.algorithms.centrality)": [[316, "networkx.algorithms.centrality.group_closeness_centrality"]], "group_degree_centrality() (in module networkx.algorithms.centrality)": [[317, "networkx.algorithms.centrality.group_degree_centrality"]], "group_in_degree_centrality() (in module networkx.algorithms.centrality)": [[318, "networkx.algorithms.centrality.group_in_degree_centrality"]], "group_out_degree_centrality() (in module networkx.algorithms.centrality)": [[319, "networkx.algorithms.centrality.group_out_degree_centrality"]], "harmonic_centrality() (in module networkx.algorithms.centrality)": [[320, "networkx.algorithms.centrality.harmonic_centrality"]], "in_degree_centrality() (in module networkx.algorithms.centrality)": [[321, "networkx.algorithms.centrality.in_degree_centrality"]], "incremental_closeness_centrality() (in module networkx.algorithms.centrality)": [[322, "networkx.algorithms.centrality.incremental_closeness_centrality"]], "information_centrality() (in module networkx.algorithms.centrality)": [[323, "networkx.algorithms.centrality.information_centrality"]], "katz_centrality() (in module networkx.algorithms.centrality)": [[324, "networkx.algorithms.centrality.katz_centrality"]], "katz_centrality_numpy() (in module networkx.algorithms.centrality)": [[325, "networkx.algorithms.centrality.katz_centrality_numpy"]], "load_centrality() (in module networkx.algorithms.centrality)": [[326, "networkx.algorithms.centrality.load_centrality"]], "local_reaching_centrality() (in module networkx.algorithms.centrality)": [[327, "networkx.algorithms.centrality.local_reaching_centrality"]], "out_degree_centrality() (in module networkx.algorithms.centrality)": [[328, "networkx.algorithms.centrality.out_degree_centrality"]], "percolation_centrality() (in module networkx.algorithms.centrality)": [[329, "networkx.algorithms.centrality.percolation_centrality"]], "prominent_group() (in module networkx.algorithms.centrality)": [[330, "networkx.algorithms.centrality.prominent_group"]], "second_order_centrality() (in module networkx.algorithms.centrality)": [[331, "networkx.algorithms.centrality.second_order_centrality"]], "subgraph_centrality() (in module networkx.algorithms.centrality)": [[332, "networkx.algorithms.centrality.subgraph_centrality"]], "subgraph_centrality_exp() (in module networkx.algorithms.centrality)": [[333, "networkx.algorithms.centrality.subgraph_centrality_exp"]], "trophic_differences() (in module networkx.algorithms.centrality)": [[334, "networkx.algorithms.centrality.trophic_differences"]], "trophic_incoherence_parameter() (in module networkx.algorithms.centrality)": [[335, "networkx.algorithms.centrality.trophic_incoherence_parameter"]], "trophic_levels() (in module networkx.algorithms.centrality)": [[336, "networkx.algorithms.centrality.trophic_levels"]], "voterank() (in module networkx.algorithms.centrality)": [[337, "networkx.algorithms.centrality.voterank"]], "chain_decomposition() (in module networkx.algorithms.chains)": [[338, "networkx.algorithms.chains.chain_decomposition"]], "chordal_graph_cliques() (in module networkx.algorithms.chordal)": [[339, "networkx.algorithms.chordal.chordal_graph_cliques"]], "chordal_graph_treewidth() (in module networkx.algorithms.chordal)": [[340, "networkx.algorithms.chordal.chordal_graph_treewidth"]], "complete_to_chordal_graph() (in module networkx.algorithms.chordal)": [[341, "networkx.algorithms.chordal.complete_to_chordal_graph"]], "find_induced_nodes() (in module networkx.algorithms.chordal)": [[342, "networkx.algorithms.chordal.find_induced_nodes"]], "is_chordal() (in module networkx.algorithms.chordal)": [[343, "networkx.algorithms.chordal.is_chordal"]], "cliques_containing_node() (in module networkx.algorithms.clique)": [[344, "networkx.algorithms.clique.cliques_containing_node"]], "enumerate_all_cliques() (in module networkx.algorithms.clique)": [[345, "networkx.algorithms.clique.enumerate_all_cliques"]], "find_cliques() (in module networkx.algorithms.clique)": [[346, "networkx.algorithms.clique.find_cliques"]], "find_cliques_recursive() (in module networkx.algorithms.clique)": [[347, "networkx.algorithms.clique.find_cliques_recursive"]], "graph_clique_number() (in module networkx.algorithms.clique)": [[348, "networkx.algorithms.clique.graph_clique_number"]], "graph_number_of_cliques() (in module networkx.algorithms.clique)": [[349, "networkx.algorithms.clique.graph_number_of_cliques"]], "make_clique_bipartite() (in module networkx.algorithms.clique)": [[350, "networkx.algorithms.clique.make_clique_bipartite"]], "make_max_clique_graph() (in module networkx.algorithms.clique)": [[351, "networkx.algorithms.clique.make_max_clique_graph"]], "max_weight_clique() (in module networkx.algorithms.clique)": [[352, "networkx.algorithms.clique.max_weight_clique"]], "node_clique_number() (in module networkx.algorithms.clique)": [[353, "networkx.algorithms.clique.node_clique_number"]], "number_of_cliques() (in module networkx.algorithms.clique)": [[354, "networkx.algorithms.clique.number_of_cliques"]], "average_clustering() (in module networkx.algorithms.cluster)": [[355, "networkx.algorithms.cluster.average_clustering"]], "clustering() (in module networkx.algorithms.cluster)": [[356, "networkx.algorithms.cluster.clustering"]], "generalized_degree() (in module networkx.algorithms.cluster)": [[357, "networkx.algorithms.cluster.generalized_degree"]], "square_clustering() (in module networkx.algorithms.cluster)": [[358, "networkx.algorithms.cluster.square_clustering"]], "transitivity() (in module networkx.algorithms.cluster)": [[359, "networkx.algorithms.cluster.transitivity"]], "triangles() (in module networkx.algorithms.cluster)": [[360, "networkx.algorithms.cluster.triangles"]], "equitable_color() (in module networkx.algorithms.coloring)": [[361, "networkx.algorithms.coloring.equitable_color"]], "greedy_color() (in module networkx.algorithms.coloring)": [[362, "networkx.algorithms.coloring.greedy_color"]], "strategy_connected_sequential() (in module networkx.algorithms.coloring)": [[363, "networkx.algorithms.coloring.strategy_connected_sequential"]], "strategy_connected_sequential_bfs() (in module networkx.algorithms.coloring)": [[364, "networkx.algorithms.coloring.strategy_connected_sequential_bfs"]], "strategy_connected_sequential_dfs() (in module networkx.algorithms.coloring)": [[365, "networkx.algorithms.coloring.strategy_connected_sequential_dfs"]], "strategy_independent_set() (in module networkx.algorithms.coloring)": [[366, "networkx.algorithms.coloring.strategy_independent_set"]], "strategy_largest_first() (in module networkx.algorithms.coloring)": [[367, "networkx.algorithms.coloring.strategy_largest_first"]], "strategy_random_sequential() (in module networkx.algorithms.coloring)": [[368, "networkx.algorithms.coloring.strategy_random_sequential"]], "strategy_saturation_largest_first() (in module networkx.algorithms.coloring)": [[369, "networkx.algorithms.coloring.strategy_saturation_largest_first"]], "strategy_smallest_last() (in module networkx.algorithms.coloring)": [[370, "networkx.algorithms.coloring.strategy_smallest_last"]], "communicability() (in module networkx.algorithms.communicability_alg)": [[371, "networkx.algorithms.communicability_alg.communicability"]], "communicability_exp() (in module networkx.algorithms.communicability_alg)": [[372, "networkx.algorithms.communicability_alg.communicability_exp"]], "asyn_fluidc() (in module networkx.algorithms.community.asyn_fluid)": [[373, "networkx.algorithms.community.asyn_fluid.asyn_fluidc"]], "girvan_newman() (in module networkx.algorithms.community.centrality)": [[374, "networkx.algorithms.community.centrality.girvan_newman"]], "is_partition() (in module networkx.algorithms.community.community_utils)": [[375, "networkx.algorithms.community.community_utils.is_partition"]], "k_clique_communities() (in module networkx.algorithms.community.kclique)": [[376, "networkx.algorithms.community.kclique.k_clique_communities"]], "kernighan_lin_bisection() (in module networkx.algorithms.community.kernighan_lin)": [[377, "networkx.algorithms.community.kernighan_lin.kernighan_lin_bisection"]], "asyn_lpa_communities() (in module networkx.algorithms.community.label_propagation)": [[378, "networkx.algorithms.community.label_propagation.asyn_lpa_communities"]], "label_propagation_communities() (in module networkx.algorithms.community.label_propagation)": [[379, "networkx.algorithms.community.label_propagation.label_propagation_communities"]], "louvain_communities() (in module networkx.algorithms.community.louvain)": [[380, "networkx.algorithms.community.louvain.louvain_communities"]], "louvain_partitions() (in module networkx.algorithms.community.louvain)": [[381, "networkx.algorithms.community.louvain.louvain_partitions"]], "lukes_partitioning() (in module networkx.algorithms.community.lukes)": [[382, "networkx.algorithms.community.lukes.lukes_partitioning"]], "greedy_modularity_communities() (in module networkx.algorithms.community.modularity_max)": [[383, "networkx.algorithms.community.modularity_max.greedy_modularity_communities"]], "naive_greedy_modularity_communities() (in module networkx.algorithms.community.modularity_max)": [[384, "networkx.algorithms.community.modularity_max.naive_greedy_modularity_communities"]], "modularity() (in module networkx.algorithms.community.quality)": [[385, "networkx.algorithms.community.quality.modularity"]], "partition_quality() (in module networkx.algorithms.community.quality)": [[386, "networkx.algorithms.community.quality.partition_quality"]], "articulation_points() (in module networkx.algorithms.components)": [[387, "networkx.algorithms.components.articulation_points"]], "attracting_components() (in module networkx.algorithms.components)": [[388, "networkx.algorithms.components.attracting_components"]], "biconnected_component_edges() (in module networkx.algorithms.components)": [[389, "networkx.algorithms.components.biconnected_component_edges"]], "biconnected_components() (in module networkx.algorithms.components)": [[390, "networkx.algorithms.components.biconnected_components"]], "condensation() (in module networkx.algorithms.components)": [[391, "networkx.algorithms.components.condensation"]], "connected_components() (in module networkx.algorithms.components)": [[392, "networkx.algorithms.components.connected_components"]], "is_attracting_component() (in module networkx.algorithms.components)": [[393, "networkx.algorithms.components.is_attracting_component"]], "is_biconnected() (in module networkx.algorithms.components)": [[394, "networkx.algorithms.components.is_biconnected"]], "is_connected() (in module networkx.algorithms.components)": [[395, "networkx.algorithms.components.is_connected"]], "is_semiconnected() (in module networkx.algorithms.components)": [[396, "networkx.algorithms.components.is_semiconnected"]], "is_strongly_connected() (in module networkx.algorithms.components)": [[397, "networkx.algorithms.components.is_strongly_connected"]], "is_weakly_connected() (in module networkx.algorithms.components)": [[398, "networkx.algorithms.components.is_weakly_connected"]], "kosaraju_strongly_connected_components() (in module networkx.algorithms.components)": [[399, "networkx.algorithms.components.kosaraju_strongly_connected_components"]], "node_connected_component() (in module networkx.algorithms.components)": [[400, "networkx.algorithms.components.node_connected_component"]], "number_attracting_components() (in module networkx.algorithms.components)": [[401, "networkx.algorithms.components.number_attracting_components"]], "number_connected_components() (in module networkx.algorithms.components)": [[402, "networkx.algorithms.components.number_connected_components"]], "number_strongly_connected_components() (in module networkx.algorithms.components)": [[403, "networkx.algorithms.components.number_strongly_connected_components"]], "number_weakly_connected_components() (in module networkx.algorithms.components)": [[404, "networkx.algorithms.components.number_weakly_connected_components"]], "strongly_connected_components() (in module networkx.algorithms.components)": [[405, "networkx.algorithms.components.strongly_connected_components"]], "strongly_connected_components_recursive() (in module networkx.algorithms.components)": [[406, "networkx.algorithms.components.strongly_connected_components_recursive"]], "weakly_connected_components() (in module networkx.algorithms.components)": [[407, "networkx.algorithms.components.weakly_connected_components"]], "all_pairs_node_connectivity() (in module networkx.algorithms.connectivity.connectivity)": [[408, "networkx.algorithms.connectivity.connectivity.all_pairs_node_connectivity"]], "average_node_connectivity() (in module networkx.algorithms.connectivity.connectivity)": [[409, "networkx.algorithms.connectivity.connectivity.average_node_connectivity"]], "edge_connectivity() (in module networkx.algorithms.connectivity.connectivity)": [[410, "networkx.algorithms.connectivity.connectivity.edge_connectivity"]], "local_edge_connectivity() (in module networkx.algorithms.connectivity.connectivity)": [[411, "networkx.algorithms.connectivity.connectivity.local_edge_connectivity"]], "local_node_connectivity() (in module networkx.algorithms.connectivity.connectivity)": [[412, "networkx.algorithms.connectivity.connectivity.local_node_connectivity"]], "node_connectivity() (in module networkx.algorithms.connectivity.connectivity)": [[413, "networkx.algorithms.connectivity.connectivity.node_connectivity"]], "minimum_edge_cut() (in module networkx.algorithms.connectivity.cuts)": [[414, "networkx.algorithms.connectivity.cuts.minimum_edge_cut"]], "minimum_node_cut() (in module networkx.algorithms.connectivity.cuts)": [[415, "networkx.algorithms.connectivity.cuts.minimum_node_cut"]], "minimum_st_edge_cut() (in module networkx.algorithms.connectivity.cuts)": [[416, "networkx.algorithms.connectivity.cuts.minimum_st_edge_cut"]], "minimum_st_node_cut() (in module networkx.algorithms.connectivity.cuts)": [[417, "networkx.algorithms.connectivity.cuts.minimum_st_node_cut"]], "edge_disjoint_paths() (in module networkx.algorithms.connectivity.disjoint_paths)": [[418, "networkx.algorithms.connectivity.disjoint_paths.edge_disjoint_paths"]], "node_disjoint_paths() (in module networkx.algorithms.connectivity.disjoint_paths)": [[419, "networkx.algorithms.connectivity.disjoint_paths.node_disjoint_paths"]], "is_k_edge_connected() (in module networkx.algorithms.connectivity.edge_augmentation)": [[420, "networkx.algorithms.connectivity.edge_augmentation.is_k_edge_connected"]], "is_locally_k_edge_connected() (in module networkx.algorithms.connectivity.edge_augmentation)": [[421, "networkx.algorithms.connectivity.edge_augmentation.is_locally_k_edge_connected"]], "k_edge_augmentation() (in module networkx.algorithms.connectivity.edge_augmentation)": [[422, "networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation"]], "edgecomponentauxgraph (class in networkx.algorithms.connectivity.edge_kcomponents)": [[423, "networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph"]], "__init__() (edgecomponentauxgraph method)": [[423, "networkx.algorithms.connectivity.edge_kcomponents.EdgeComponentAuxGraph.__init__"]], "bridge_components() (in module networkx.algorithms.connectivity.edge_kcomponents)": [[424, "networkx.algorithms.connectivity.edge_kcomponents.bridge_components"]], "k_edge_components() (in module networkx.algorithms.connectivity.edge_kcomponents)": [[425, "networkx.algorithms.connectivity.edge_kcomponents.k_edge_components"]], "k_edge_subgraphs() (in module networkx.algorithms.connectivity.edge_kcomponents)": [[426, "networkx.algorithms.connectivity.edge_kcomponents.k_edge_subgraphs"]], "k_components() (in module networkx.algorithms.connectivity.kcomponents)": [[427, "networkx.algorithms.connectivity.kcomponents.k_components"]], "all_node_cuts() (in module networkx.algorithms.connectivity.kcutsets)": [[428, "networkx.algorithms.connectivity.kcutsets.all_node_cuts"]], "stoer_wagner() (in module networkx.algorithms.connectivity.stoerwagner)": [[429, "networkx.algorithms.connectivity.stoerwagner.stoer_wagner"]], "build_auxiliary_edge_connectivity() (in module networkx.algorithms.connectivity.utils)": [[430, "networkx.algorithms.connectivity.utils.build_auxiliary_edge_connectivity"]], "build_auxiliary_node_connectivity() (in module networkx.algorithms.connectivity.utils)": [[431, "networkx.algorithms.connectivity.utils.build_auxiliary_node_connectivity"]], "core_number() (in module networkx.algorithms.core)": [[432, "networkx.algorithms.core.core_number"]], "k_core() (in module networkx.algorithms.core)": [[433, "networkx.algorithms.core.k_core"]], "k_corona() (in module networkx.algorithms.core)": [[434, "networkx.algorithms.core.k_corona"]], "k_crust() (in module networkx.algorithms.core)": [[435, "networkx.algorithms.core.k_crust"]], "k_shell() (in module networkx.algorithms.core)": [[436, "networkx.algorithms.core.k_shell"]], "k_truss() (in module networkx.algorithms.core)": [[437, "networkx.algorithms.core.k_truss"]], "onion_layers() (in module networkx.algorithms.core)": [[438, "networkx.algorithms.core.onion_layers"]], "is_edge_cover() (in module networkx.algorithms.covering)": [[439, "networkx.algorithms.covering.is_edge_cover"]], "min_edge_cover() (in module networkx.algorithms.covering)": [[440, "networkx.algorithms.covering.min_edge_cover"]], "boundary_expansion() (in module networkx.algorithms.cuts)": [[441, "networkx.algorithms.cuts.boundary_expansion"]], "conductance() (in module networkx.algorithms.cuts)": [[442, "networkx.algorithms.cuts.conductance"]], "cut_size() (in module networkx.algorithms.cuts)": [[443, "networkx.algorithms.cuts.cut_size"]], "edge_expansion() (in module networkx.algorithms.cuts)": [[444, "networkx.algorithms.cuts.edge_expansion"]], "mixing_expansion() (in module networkx.algorithms.cuts)": [[445, "networkx.algorithms.cuts.mixing_expansion"]], "node_expansion() (in module networkx.algorithms.cuts)": [[446, "networkx.algorithms.cuts.node_expansion"]], "normalized_cut_size() (in module networkx.algorithms.cuts)": [[447, "networkx.algorithms.cuts.normalized_cut_size"]], "volume() (in module networkx.algorithms.cuts)": [[448, "networkx.algorithms.cuts.volume"]], "cycle_basis() (in module networkx.algorithms.cycles)": [[449, "networkx.algorithms.cycles.cycle_basis"]], "find_cycle() (in module networkx.algorithms.cycles)": [[450, "networkx.algorithms.cycles.find_cycle"]], "minimum_cycle_basis() (in module networkx.algorithms.cycles)": [[451, "networkx.algorithms.cycles.minimum_cycle_basis"]], "recursive_simple_cycles() (in module networkx.algorithms.cycles)": [[452, "networkx.algorithms.cycles.recursive_simple_cycles"]], "simple_cycles() (in module networkx.algorithms.cycles)": [[453, "networkx.algorithms.cycles.simple_cycles"]], "d_separated() (in module networkx.algorithms.d_separation)": [[454, "networkx.algorithms.d_separation.d_separated"]], "all_topological_sorts() (in module networkx.algorithms.dag)": [[455, "networkx.algorithms.dag.all_topological_sorts"]], "ancestors() (in module networkx.algorithms.dag)": [[456, "networkx.algorithms.dag.ancestors"]], "antichains() (in module networkx.algorithms.dag)": [[457, "networkx.algorithms.dag.antichains"]], "dag_longest_path() (in module networkx.algorithms.dag)": [[458, "networkx.algorithms.dag.dag_longest_path"]], "dag_longest_path_length() (in module networkx.algorithms.dag)": [[459, "networkx.algorithms.dag.dag_longest_path_length"]], "dag_to_branching() (in module networkx.algorithms.dag)": [[460, "networkx.algorithms.dag.dag_to_branching"]], "descendants() (in module networkx.algorithms.dag)": [[461, "networkx.algorithms.dag.descendants"]], "is_aperiodic() (in module networkx.algorithms.dag)": [[462, "networkx.algorithms.dag.is_aperiodic"]], "is_directed_acyclic_graph() (in module networkx.algorithms.dag)": [[463, "networkx.algorithms.dag.is_directed_acyclic_graph"]], "lexicographical_topological_sort() (in module networkx.algorithms.dag)": [[464, "networkx.algorithms.dag.lexicographical_topological_sort"]], "topological_generations() (in module networkx.algorithms.dag)": [[465, "networkx.algorithms.dag.topological_generations"]], "topological_sort() (in module networkx.algorithms.dag)": [[466, "networkx.algorithms.dag.topological_sort"]], "transitive_closure() (in module networkx.algorithms.dag)": [[467, "networkx.algorithms.dag.transitive_closure"]], "transitive_closure_dag() (in module networkx.algorithms.dag)": [[468, "networkx.algorithms.dag.transitive_closure_dag"]], "transitive_reduction() (in module networkx.algorithms.dag)": [[469, "networkx.algorithms.dag.transitive_reduction"]], "barycenter() (in module networkx.algorithms.distance_measures)": [[470, "networkx.algorithms.distance_measures.barycenter"]], "center() (in module networkx.algorithms.distance_measures)": [[471, "networkx.algorithms.distance_measures.center"]], "diameter() (in module networkx.algorithms.distance_measures)": [[472, "networkx.algorithms.distance_measures.diameter"]], "eccentricity() (in module networkx.algorithms.distance_measures)": [[473, "networkx.algorithms.distance_measures.eccentricity"]], "periphery() (in module networkx.algorithms.distance_measures)": [[474, "networkx.algorithms.distance_measures.periphery"]], "radius() (in module networkx.algorithms.distance_measures)": [[475, "networkx.algorithms.distance_measures.radius"]], "resistance_distance() (in module networkx.algorithms.distance_measures)": [[476, "networkx.algorithms.distance_measures.resistance_distance"]], "global_parameters() (in module networkx.algorithms.distance_regular)": [[477, "networkx.algorithms.distance_regular.global_parameters"]], "intersection_array() (in module networkx.algorithms.distance_regular)": [[478, "networkx.algorithms.distance_regular.intersection_array"]], "is_distance_regular() (in module networkx.algorithms.distance_regular)": [[479, "networkx.algorithms.distance_regular.is_distance_regular"]], "is_strongly_regular() (in module networkx.algorithms.distance_regular)": [[480, "networkx.algorithms.distance_regular.is_strongly_regular"]], "dominance_frontiers() (in module networkx.algorithms.dominance)": [[481, "networkx.algorithms.dominance.dominance_frontiers"]], "immediate_dominators() (in module networkx.algorithms.dominance)": [[482, "networkx.algorithms.dominance.immediate_dominators"]], "dominating_set() (in module networkx.algorithms.dominating)": [[483, "networkx.algorithms.dominating.dominating_set"]], "is_dominating_set() (in module networkx.algorithms.dominating)": [[484, "networkx.algorithms.dominating.is_dominating_set"]], "efficiency() (in module networkx.algorithms.efficiency_measures)": [[485, "networkx.algorithms.efficiency_measures.efficiency"]], "global_efficiency() (in module networkx.algorithms.efficiency_measures)": [[486, "networkx.algorithms.efficiency_measures.global_efficiency"]], "local_efficiency() (in module networkx.algorithms.efficiency_measures)": [[487, "networkx.algorithms.efficiency_measures.local_efficiency"]], "eulerian_circuit() (in module networkx.algorithms.euler)": [[488, "networkx.algorithms.euler.eulerian_circuit"]], "eulerian_path() (in module networkx.algorithms.euler)": [[489, "networkx.algorithms.euler.eulerian_path"]], "eulerize() (in module networkx.algorithms.euler)": [[490, "networkx.algorithms.euler.eulerize"]], "has_eulerian_path() (in module networkx.algorithms.euler)": [[491, "networkx.algorithms.euler.has_eulerian_path"]], "is_eulerian() (in module networkx.algorithms.euler)": [[492, "networkx.algorithms.euler.is_eulerian"]], "is_semieulerian() (in module networkx.algorithms.euler)": [[493, "networkx.algorithms.euler.is_semieulerian"]], "boykov_kolmogorov() (in module networkx.algorithms.flow)": [[494, "networkx.algorithms.flow.boykov_kolmogorov"]], "build_residual_network() (in module networkx.algorithms.flow)": [[495, "networkx.algorithms.flow.build_residual_network"]], "capacity_scaling() (in module networkx.algorithms.flow)": [[496, "networkx.algorithms.flow.capacity_scaling"]], "cost_of_flow() (in module networkx.algorithms.flow)": [[497, "networkx.algorithms.flow.cost_of_flow"]], "dinitz() (in module networkx.algorithms.flow)": [[498, "networkx.algorithms.flow.dinitz"]], "edmonds_karp() (in module networkx.algorithms.flow)": [[499, "networkx.algorithms.flow.edmonds_karp"]], "gomory_hu_tree() (in module networkx.algorithms.flow)": [[500, "networkx.algorithms.flow.gomory_hu_tree"]], "max_flow_min_cost() (in module networkx.algorithms.flow)": [[501, "networkx.algorithms.flow.max_flow_min_cost"]], "maximum_flow() (in module networkx.algorithms.flow)": [[502, "networkx.algorithms.flow.maximum_flow"]], "maximum_flow_value() (in module networkx.algorithms.flow)": [[503, "networkx.algorithms.flow.maximum_flow_value"]], "min_cost_flow() (in module networkx.algorithms.flow)": [[504, "networkx.algorithms.flow.min_cost_flow"]], "min_cost_flow_cost() (in module networkx.algorithms.flow)": [[505, "networkx.algorithms.flow.min_cost_flow_cost"]], "minimum_cut() (in module networkx.algorithms.flow)": [[506, "networkx.algorithms.flow.minimum_cut"]], "minimum_cut_value() (in module networkx.algorithms.flow)": [[507, "networkx.algorithms.flow.minimum_cut_value"]], "network_simplex() (in module networkx.algorithms.flow)": [[508, "networkx.algorithms.flow.network_simplex"]], "preflow_push() (in module networkx.algorithms.flow)": [[509, "networkx.algorithms.flow.preflow_push"]], "shortest_augmenting_path() (in module networkx.algorithms.flow)": [[510, "networkx.algorithms.flow.shortest_augmenting_path"]], "weisfeiler_lehman_graph_hash() (in module networkx.algorithms.graph_hashing)": [[511, "networkx.algorithms.graph_hashing.weisfeiler_lehman_graph_hash"]], "weisfeiler_lehman_subgraph_hashes() (in module networkx.algorithms.graph_hashing)": [[512, "networkx.algorithms.graph_hashing.weisfeiler_lehman_subgraph_hashes"]], "is_digraphical() (in module networkx.algorithms.graphical)": [[513, "networkx.algorithms.graphical.is_digraphical"]], "is_graphical() (in module networkx.algorithms.graphical)": [[514, "networkx.algorithms.graphical.is_graphical"]], "is_multigraphical() (in module networkx.algorithms.graphical)": [[515, "networkx.algorithms.graphical.is_multigraphical"]], "is_pseudographical() (in module networkx.algorithms.graphical)": [[516, "networkx.algorithms.graphical.is_pseudographical"]], "is_valid_degree_sequence_erdos_gallai() (in module networkx.algorithms.graphical)": [[517, "networkx.algorithms.graphical.is_valid_degree_sequence_erdos_gallai"]], "is_valid_degree_sequence_havel_hakimi() (in module networkx.algorithms.graphical)": [[518, "networkx.algorithms.graphical.is_valid_degree_sequence_havel_hakimi"]], "flow_hierarchy() (in module networkx.algorithms.hierarchy)": [[519, "networkx.algorithms.hierarchy.flow_hierarchy"]], "is_kl_connected() (in module networkx.algorithms.hybrid)": [[520, "networkx.algorithms.hybrid.is_kl_connected"]], "kl_connected_subgraph() (in module networkx.algorithms.hybrid)": [[521, "networkx.algorithms.hybrid.kl_connected_subgraph"]], "is_isolate() (in module networkx.algorithms.isolate)": [[522, "networkx.algorithms.isolate.is_isolate"]], "isolates() (in module networkx.algorithms.isolate)": [[523, "networkx.algorithms.isolate.isolates"]], "number_of_isolates() (in module networkx.algorithms.isolate)": [[524, "networkx.algorithms.isolate.number_of_isolates"]], "__init__() (digraphmatcher method)": [[525, "networkx.algorithms.isomorphism.DiGraphMatcher.__init__"]], "candidate_pairs_iter() (digraphmatcher method)": [[526, "networkx.algorithms.isomorphism.DiGraphMatcher.candidate_pairs_iter"]], "initialize() (digraphmatcher method)": [[527, "networkx.algorithms.isomorphism.DiGraphMatcher.initialize"]], "is_isomorphic() (digraphmatcher method)": [[528, "networkx.algorithms.isomorphism.DiGraphMatcher.is_isomorphic"]], "isomorphisms_iter() (digraphmatcher method)": [[529, "networkx.algorithms.isomorphism.DiGraphMatcher.isomorphisms_iter"]], "match() (digraphmatcher method)": [[530, "networkx.algorithms.isomorphism.DiGraphMatcher.match"]], "semantic_feasibility() (digraphmatcher method)": [[531, "networkx.algorithms.isomorphism.DiGraphMatcher.semantic_feasibility"]], "subgraph_is_isomorphic() (digraphmatcher method)": [[532, "networkx.algorithms.isomorphism.DiGraphMatcher.subgraph_is_isomorphic"]], "subgraph_isomorphisms_iter() (digraphmatcher method)": [[533, "networkx.algorithms.isomorphism.DiGraphMatcher.subgraph_isomorphisms_iter"]], "syntactic_feasibility() (digraphmatcher method)": [[534, "networkx.algorithms.isomorphism.DiGraphMatcher.syntactic_feasibility"]], "__init__() (graphmatcher method)": [[535, "networkx.algorithms.isomorphism.GraphMatcher.__init__"]], "candidate_pairs_iter() (graphmatcher method)": [[536, "networkx.algorithms.isomorphism.GraphMatcher.candidate_pairs_iter"]], "initialize() (graphmatcher method)": [[537, "networkx.algorithms.isomorphism.GraphMatcher.initialize"]], "is_isomorphic() (graphmatcher method)": [[538, "networkx.algorithms.isomorphism.GraphMatcher.is_isomorphic"]], "isomorphisms_iter() (graphmatcher method)": [[539, "networkx.algorithms.isomorphism.GraphMatcher.isomorphisms_iter"]], "match() (graphmatcher method)": [[540, "networkx.algorithms.isomorphism.GraphMatcher.match"]], "semantic_feasibility() (graphmatcher method)": [[541, "networkx.algorithms.isomorphism.GraphMatcher.semantic_feasibility"]], "subgraph_is_isomorphic() (graphmatcher method)": [[542, "networkx.algorithms.isomorphism.GraphMatcher.subgraph_is_isomorphic"]], "subgraph_isomorphisms_iter() (graphmatcher method)": [[543, "networkx.algorithms.isomorphism.GraphMatcher.subgraph_isomorphisms_iter"]], "syntactic_feasibility() (graphmatcher method)": [[544, "networkx.algorithms.isomorphism.GraphMatcher.syntactic_feasibility"]], "ismags (class in networkx.algorithms.isomorphism)": [[545, "networkx.algorithms.isomorphism.ISMAGS"]], "__init__() (ismags method)": [[545, "networkx.algorithms.isomorphism.ISMAGS.__init__"]], "categorical_edge_match() (in module networkx.algorithms.isomorphism)": [[546, "networkx.algorithms.isomorphism.categorical_edge_match"]], "categorical_multiedge_match() (in module networkx.algorithms.isomorphism)": [[547, "networkx.algorithms.isomorphism.categorical_multiedge_match"]], "categorical_node_match() (in module networkx.algorithms.isomorphism)": [[548, "networkx.algorithms.isomorphism.categorical_node_match"]], "could_be_isomorphic() (in module networkx.algorithms.isomorphism)": [[549, "networkx.algorithms.isomorphism.could_be_isomorphic"]], "fast_could_be_isomorphic() (in module networkx.algorithms.isomorphism)": [[550, "networkx.algorithms.isomorphism.fast_could_be_isomorphic"]], "faster_could_be_isomorphic() (in module networkx.algorithms.isomorphism)": [[551, "networkx.algorithms.isomorphism.faster_could_be_isomorphic"]], "generic_edge_match() (in module networkx.algorithms.isomorphism)": [[552, "networkx.algorithms.isomorphism.generic_edge_match"]], "generic_multiedge_match() (in module networkx.algorithms.isomorphism)": [[553, "networkx.algorithms.isomorphism.generic_multiedge_match"]], "generic_node_match() (in module networkx.algorithms.isomorphism)": [[554, "networkx.algorithms.isomorphism.generic_node_match"]], "is_isomorphic() (in module networkx.algorithms.isomorphism)": [[555, "networkx.algorithms.isomorphism.is_isomorphic"]], "numerical_edge_match() (in module networkx.algorithms.isomorphism)": [[556, "networkx.algorithms.isomorphism.numerical_edge_match"]], "numerical_multiedge_match() (in module networkx.algorithms.isomorphism)": [[557, "networkx.algorithms.isomorphism.numerical_multiedge_match"]], "numerical_node_match() (in module networkx.algorithms.isomorphism)": [[558, "networkx.algorithms.isomorphism.numerical_node_match"]], "rooted_tree_isomorphism() (in module networkx.algorithms.isomorphism.tree_isomorphism)": [[559, "networkx.algorithms.isomorphism.tree_isomorphism.rooted_tree_isomorphism"]], "tree_isomorphism() (in module networkx.algorithms.isomorphism.tree_isomorphism)": [[560, "networkx.algorithms.isomorphism.tree_isomorphism.tree_isomorphism"]], "vf2pp_all_isomorphisms() (in module networkx.algorithms.isomorphism.vf2pp)": [[561, "networkx.algorithms.isomorphism.vf2pp.vf2pp_all_isomorphisms"]], "vf2pp_is_isomorphic() (in module networkx.algorithms.isomorphism.vf2pp)": [[562, "networkx.algorithms.isomorphism.vf2pp.vf2pp_is_isomorphic"]], "vf2pp_isomorphism() (in module networkx.algorithms.isomorphism.vf2pp)": [[563, "networkx.algorithms.isomorphism.vf2pp.vf2pp_isomorphism"]], "hits() (in module networkx.algorithms.link_analysis.hits_alg)": [[564, "networkx.algorithms.link_analysis.hits_alg.hits"]], "google_matrix() (in module networkx.algorithms.link_analysis.pagerank_alg)": [[565, "networkx.algorithms.link_analysis.pagerank_alg.google_matrix"]], "pagerank() (in module networkx.algorithms.link_analysis.pagerank_alg)": [[566, "networkx.algorithms.link_analysis.pagerank_alg.pagerank"]], "adamic_adar_index() (in module networkx.algorithms.link_prediction)": [[567, "networkx.algorithms.link_prediction.adamic_adar_index"]], "cn_soundarajan_hopcroft() (in module networkx.algorithms.link_prediction)": [[568, "networkx.algorithms.link_prediction.cn_soundarajan_hopcroft"]], "common_neighbor_centrality() (in module networkx.algorithms.link_prediction)": [[569, "networkx.algorithms.link_prediction.common_neighbor_centrality"]], "jaccard_coefficient() (in module networkx.algorithms.link_prediction)": [[570, "networkx.algorithms.link_prediction.jaccard_coefficient"]], "preferential_attachment() (in module networkx.algorithms.link_prediction)": [[571, "networkx.algorithms.link_prediction.preferential_attachment"]], "ra_index_soundarajan_hopcroft() (in module networkx.algorithms.link_prediction)": [[572, "networkx.algorithms.link_prediction.ra_index_soundarajan_hopcroft"]], "resource_allocation_index() (in module networkx.algorithms.link_prediction)": [[573, "networkx.algorithms.link_prediction.resource_allocation_index"]], "within_inter_cluster() (in module networkx.algorithms.link_prediction)": [[574, "networkx.algorithms.link_prediction.within_inter_cluster"]], "all_pairs_lowest_common_ancestor() (in module networkx.algorithms.lowest_common_ancestors)": [[575, "networkx.algorithms.lowest_common_ancestors.all_pairs_lowest_common_ancestor"]], "lowest_common_ancestor() (in module networkx.algorithms.lowest_common_ancestors)": [[576, "networkx.algorithms.lowest_common_ancestors.lowest_common_ancestor"]], "tree_all_pairs_lowest_common_ancestor() (in module networkx.algorithms.lowest_common_ancestors)": [[577, "networkx.algorithms.lowest_common_ancestors.tree_all_pairs_lowest_common_ancestor"]], "is_matching() (in module networkx.algorithms.matching)": [[578, "networkx.algorithms.matching.is_matching"]], "is_maximal_matching() (in module networkx.algorithms.matching)": [[579, "networkx.algorithms.matching.is_maximal_matching"]], "is_perfect_matching() (in module networkx.algorithms.matching)": [[580, "networkx.algorithms.matching.is_perfect_matching"]], "max_weight_matching() (in module networkx.algorithms.matching)": [[581, "networkx.algorithms.matching.max_weight_matching"]], "maximal_matching() (in module networkx.algorithms.matching)": [[582, "networkx.algorithms.matching.maximal_matching"]], "min_weight_matching() (in module networkx.algorithms.matching)": [[583, "networkx.algorithms.matching.min_weight_matching"]], "contracted_edge() (in module networkx.algorithms.minors)": [[584, "networkx.algorithms.minors.contracted_edge"]], "contracted_nodes() (in module networkx.algorithms.minors)": [[585, "networkx.algorithms.minors.contracted_nodes"]], "equivalence_classes() (in module networkx.algorithms.minors)": [[586, "networkx.algorithms.minors.equivalence_classes"]], "identified_nodes() (in module networkx.algorithms.minors)": [[587, "networkx.algorithms.minors.identified_nodes"]], "quotient_graph() (in module networkx.algorithms.minors)": [[588, "networkx.algorithms.minors.quotient_graph"]], "maximal_independent_set() (in module networkx.algorithms.mis)": [[589, "networkx.algorithms.mis.maximal_independent_set"]], "moral_graph() (in module networkx.algorithms.moral)": [[590, "networkx.algorithms.moral.moral_graph"]], "harmonic_function() (in module networkx.algorithms.node_classification)": [[591, "networkx.algorithms.node_classification.harmonic_function"]], "local_and_global_consistency() (in module networkx.algorithms.node_classification)": [[592, "networkx.algorithms.node_classification.local_and_global_consistency"]], "non_randomness() (in module networkx.algorithms.non_randomness)": [[593, "networkx.algorithms.non_randomness.non_randomness"]], "compose_all() (in module networkx.algorithms.operators.all)": [[594, "networkx.algorithms.operators.all.compose_all"]], "disjoint_union_all() (in module networkx.algorithms.operators.all)": [[595, "networkx.algorithms.operators.all.disjoint_union_all"]], "intersection_all() (in module networkx.algorithms.operators.all)": [[596, "networkx.algorithms.operators.all.intersection_all"]], "union_all() (in module networkx.algorithms.operators.all)": [[597, "networkx.algorithms.operators.all.union_all"]], "compose() (in module networkx.algorithms.operators.binary)": [[598, "networkx.algorithms.operators.binary.compose"]], "difference() (in module networkx.algorithms.operators.binary)": [[599, "networkx.algorithms.operators.binary.difference"]], "disjoint_union() (in module networkx.algorithms.operators.binary)": [[600, "networkx.algorithms.operators.binary.disjoint_union"]], "full_join() (in module networkx.algorithms.operators.binary)": [[601, "networkx.algorithms.operators.binary.full_join"]], "intersection() (in module networkx.algorithms.operators.binary)": [[602, "networkx.algorithms.operators.binary.intersection"]], "symmetric_difference() (in module networkx.algorithms.operators.binary)": [[603, "networkx.algorithms.operators.binary.symmetric_difference"]], "union() (in module networkx.algorithms.operators.binary)": [[604, "networkx.algorithms.operators.binary.union"]], "cartesian_product() (in module networkx.algorithms.operators.product)": [[605, "networkx.algorithms.operators.product.cartesian_product"]], "corona_product() (in module networkx.algorithms.operators.product)": [[606, "networkx.algorithms.operators.product.corona_product"]], "lexicographic_product() (in module networkx.algorithms.operators.product)": [[607, "networkx.algorithms.operators.product.lexicographic_product"]], "power() (in module networkx.algorithms.operators.product)": [[608, "networkx.algorithms.operators.product.power"]], "rooted_product() (in module networkx.algorithms.operators.product)": [[609, "networkx.algorithms.operators.product.rooted_product"]], "strong_product() (in module networkx.algorithms.operators.product)": [[610, "networkx.algorithms.operators.product.strong_product"]], "tensor_product() (in module networkx.algorithms.operators.product)": [[611, "networkx.algorithms.operators.product.tensor_product"]], "complement() (in module networkx.algorithms.operators.unary)": [[612, "networkx.algorithms.operators.unary.complement"]], "reverse() (in module networkx.algorithms.operators.unary)": [[613, "networkx.algorithms.operators.unary.reverse"]], "combinatorial_embedding_to_pos() (in module networkx.algorithms.planar_drawing)": [[614, "networkx.algorithms.planar_drawing.combinatorial_embedding_to_pos"]], "planarembedding (class in networkx.algorithms.planarity)": [[615, "networkx.algorithms.planarity.PlanarEmbedding"]], "__init__() (planarembedding method)": [[615, "networkx.algorithms.planarity.PlanarEmbedding.__init__"]], "check_planarity() (in module networkx.algorithms.planarity)": [[616, "networkx.algorithms.planarity.check_planarity"]], "is_planar() (in module networkx.algorithms.planarity)": [[617, "networkx.algorithms.planarity.is_planar"]], "chromatic_polynomial() (in module networkx.algorithms.polynomials)": [[618, "networkx.algorithms.polynomials.chromatic_polynomial"]], "tutte_polynomial() (in module networkx.algorithms.polynomials)": [[619, "networkx.algorithms.polynomials.tutte_polynomial"]], "overall_reciprocity() (in module networkx.algorithms.reciprocity)": [[620, "networkx.algorithms.reciprocity.overall_reciprocity"]], "reciprocity() (in module networkx.algorithms.reciprocity)": [[621, "networkx.algorithms.reciprocity.reciprocity"]], "is_k_regular() (in module networkx.algorithms.regular)": [[622, "networkx.algorithms.regular.is_k_regular"]], "is_regular() (in module networkx.algorithms.regular)": [[623, "networkx.algorithms.regular.is_regular"]], "k_factor() (in module networkx.algorithms.regular)": [[624, "networkx.algorithms.regular.k_factor"]], "rich_club_coefficient() (in module networkx.algorithms.richclub)": [[625, "networkx.algorithms.richclub.rich_club_coefficient"]], "astar_path() (in module networkx.algorithms.shortest_paths.astar)": [[626, "networkx.algorithms.shortest_paths.astar.astar_path"]], "astar_path_length() (in module networkx.algorithms.shortest_paths.astar)": [[627, "networkx.algorithms.shortest_paths.astar.astar_path_length"]], "floyd_warshall() (in module networkx.algorithms.shortest_paths.dense)": [[628, "networkx.algorithms.shortest_paths.dense.floyd_warshall"]], "floyd_warshall_numpy() (in module networkx.algorithms.shortest_paths.dense)": [[629, "networkx.algorithms.shortest_paths.dense.floyd_warshall_numpy"]], "floyd_warshall_predecessor_and_distance() (in module networkx.algorithms.shortest_paths.dense)": [[630, "networkx.algorithms.shortest_paths.dense.floyd_warshall_predecessor_and_distance"]], "reconstruct_path() (in module networkx.algorithms.shortest_paths.dense)": [[631, "networkx.algorithms.shortest_paths.dense.reconstruct_path"]], "all_shortest_paths() (in module networkx.algorithms.shortest_paths.generic)": [[632, "networkx.algorithms.shortest_paths.generic.all_shortest_paths"]], "average_shortest_path_length() (in module networkx.algorithms.shortest_paths.generic)": [[633, "networkx.algorithms.shortest_paths.generic.average_shortest_path_length"]], "has_path() (in module networkx.algorithms.shortest_paths.generic)": [[634, "networkx.algorithms.shortest_paths.generic.has_path"]], "shortest_path() (in module networkx.algorithms.shortest_paths.generic)": [[635, "networkx.algorithms.shortest_paths.generic.shortest_path"]], "shortest_path_length() (in module networkx.algorithms.shortest_paths.generic)": [[636, "networkx.algorithms.shortest_paths.generic.shortest_path_length"]], "all_pairs_shortest_path() (in module networkx.algorithms.shortest_paths.unweighted)": [[637, "networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path"]], "all_pairs_shortest_path_length() (in module networkx.algorithms.shortest_paths.unweighted)": [[638, "networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path_length"]], "bidirectional_shortest_path() (in module networkx.algorithms.shortest_paths.unweighted)": [[639, "networkx.algorithms.shortest_paths.unweighted.bidirectional_shortest_path"]], "predecessor() (in module networkx.algorithms.shortest_paths.unweighted)": [[640, "networkx.algorithms.shortest_paths.unweighted.predecessor"]], "single_source_shortest_path() (in module networkx.algorithms.shortest_paths.unweighted)": [[641, "networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path"]], "single_source_shortest_path_length() (in module networkx.algorithms.shortest_paths.unweighted)": [[642, "networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path_length"]], "single_target_shortest_path() (in module networkx.algorithms.shortest_paths.unweighted)": [[643, "networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path"]], "single_target_shortest_path_length() (in module networkx.algorithms.shortest_paths.unweighted)": [[644, "networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path_length"]], "all_pairs_bellman_ford_path() (in module networkx.algorithms.shortest_paths.weighted)": [[645, "networkx.algorithms.shortest_paths.weighted.all_pairs_bellman_ford_path"]], "all_pairs_bellman_ford_path_length() (in module networkx.algorithms.shortest_paths.weighted)": [[646, "networkx.algorithms.shortest_paths.weighted.all_pairs_bellman_ford_path_length"]], "all_pairs_dijkstra() (in module networkx.algorithms.shortest_paths.weighted)": [[647, "networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra"]], "all_pairs_dijkstra_path() (in module networkx.algorithms.shortest_paths.weighted)": [[648, "networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra_path"]], "all_pairs_dijkstra_path_length() (in module networkx.algorithms.shortest_paths.weighted)": [[649, "networkx.algorithms.shortest_paths.weighted.all_pairs_dijkstra_path_length"]], "bellman_ford_path() (in module networkx.algorithms.shortest_paths.weighted)": [[650, "networkx.algorithms.shortest_paths.weighted.bellman_ford_path"]], "bellman_ford_path_length() (in module networkx.algorithms.shortest_paths.weighted)": [[651, "networkx.algorithms.shortest_paths.weighted.bellman_ford_path_length"]], "bellman_ford_predecessor_and_distance() (in module networkx.algorithms.shortest_paths.weighted)": [[652, "networkx.algorithms.shortest_paths.weighted.bellman_ford_predecessor_and_distance"]], "bidirectional_dijkstra() (in module networkx.algorithms.shortest_paths.weighted)": [[653, "networkx.algorithms.shortest_paths.weighted.bidirectional_dijkstra"]], "dijkstra_path() (in module networkx.algorithms.shortest_paths.weighted)": [[654, "networkx.algorithms.shortest_paths.weighted.dijkstra_path"]], "dijkstra_path_length() (in module networkx.algorithms.shortest_paths.weighted)": [[655, "networkx.algorithms.shortest_paths.weighted.dijkstra_path_length"]], "dijkstra_predecessor_and_distance() (in module networkx.algorithms.shortest_paths.weighted)": [[656, "networkx.algorithms.shortest_paths.weighted.dijkstra_predecessor_and_distance"]], "find_negative_cycle() (in module networkx.algorithms.shortest_paths.weighted)": [[657, "networkx.algorithms.shortest_paths.weighted.find_negative_cycle"]], "goldberg_radzik() (in module networkx.algorithms.shortest_paths.weighted)": [[658, "networkx.algorithms.shortest_paths.weighted.goldberg_radzik"]], "johnson() (in module networkx.algorithms.shortest_paths.weighted)": [[659, "networkx.algorithms.shortest_paths.weighted.johnson"]], "multi_source_dijkstra() (in module networkx.algorithms.shortest_paths.weighted)": [[660, "networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra"]], "multi_source_dijkstra_path() (in module networkx.algorithms.shortest_paths.weighted)": [[661, "networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra_path"]], "multi_source_dijkstra_path_length() (in module networkx.algorithms.shortest_paths.weighted)": [[662, "networkx.algorithms.shortest_paths.weighted.multi_source_dijkstra_path_length"]], "negative_edge_cycle() (in module networkx.algorithms.shortest_paths.weighted)": [[663, "networkx.algorithms.shortest_paths.weighted.negative_edge_cycle"]], "single_source_bellman_ford() (in module networkx.algorithms.shortest_paths.weighted)": [[664, "networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford"]], "single_source_bellman_ford_path() (in module networkx.algorithms.shortest_paths.weighted)": [[665, "networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path"]], "single_source_bellman_ford_path_length() (in module networkx.algorithms.shortest_paths.weighted)": [[666, "networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path_length"]], "single_source_dijkstra() (in module networkx.algorithms.shortest_paths.weighted)": [[667, "networkx.algorithms.shortest_paths.weighted.single_source_dijkstra"]], "single_source_dijkstra_path() (in module networkx.algorithms.shortest_paths.weighted)": [[668, "networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path"]], "single_source_dijkstra_path_length() (in module networkx.algorithms.shortest_paths.weighted)": [[669, "networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path_length"]], "generate_random_paths() (in module networkx.algorithms.similarity)": [[670, "networkx.algorithms.similarity.generate_random_paths"]], "graph_edit_distance() (in module networkx.algorithms.similarity)": [[671, "networkx.algorithms.similarity.graph_edit_distance"]], "optimal_edit_paths() (in module networkx.algorithms.similarity)": [[672, "networkx.algorithms.similarity.optimal_edit_paths"]], "optimize_edit_paths() (in module networkx.algorithms.similarity)": [[673, "networkx.algorithms.similarity.optimize_edit_paths"]], "optimize_graph_edit_distance() (in module networkx.algorithms.similarity)": [[674, "networkx.algorithms.similarity.optimize_graph_edit_distance"]], "panther_similarity() (in module networkx.algorithms.similarity)": [[675, "networkx.algorithms.similarity.panther_similarity"]], "simrank_similarity() (in module networkx.algorithms.similarity)": [[676, "networkx.algorithms.similarity.simrank_similarity"]], "all_simple_edge_paths() (in module networkx.algorithms.simple_paths)": [[677, "networkx.algorithms.simple_paths.all_simple_edge_paths"]], "all_simple_paths() (in module networkx.algorithms.simple_paths)": [[678, "networkx.algorithms.simple_paths.all_simple_paths"]], "is_simple_path() (in module networkx.algorithms.simple_paths)": [[679, "networkx.algorithms.simple_paths.is_simple_path"]], "shortest_simple_paths() (in module networkx.algorithms.simple_paths)": [[680, "networkx.algorithms.simple_paths.shortest_simple_paths"]], "lattice_reference() (in module networkx.algorithms.smallworld)": [[681, "networkx.algorithms.smallworld.lattice_reference"]], "omega() (in module networkx.algorithms.smallworld)": [[682, "networkx.algorithms.smallworld.omega"]], "random_reference() (in module networkx.algorithms.smallworld)": [[683, "networkx.algorithms.smallworld.random_reference"]], "sigma() (in module networkx.algorithms.smallworld)": [[684, "networkx.algorithms.smallworld.sigma"]], "s_metric() (in module networkx.algorithms.smetric)": [[685, "networkx.algorithms.smetric.s_metric"]], "spanner() (in module networkx.algorithms.sparsifiers)": [[686, "networkx.algorithms.sparsifiers.spanner"]], "constraint() (in module networkx.algorithms.structuralholes)": [[687, "networkx.algorithms.structuralholes.constraint"]], "effective_size() (in module networkx.algorithms.structuralholes)": [[688, "networkx.algorithms.structuralholes.effective_size"]], "local_constraint() (in module networkx.algorithms.structuralholes)": [[689, "networkx.algorithms.structuralholes.local_constraint"]], "dedensify() (in module networkx.algorithms.summarization)": [[690, "networkx.algorithms.summarization.dedensify"]], "snap_aggregation() (in module networkx.algorithms.summarization)": [[691, "networkx.algorithms.summarization.snap_aggregation"]], "connected_double_edge_swap() (in module networkx.algorithms.swap)": [[692, "networkx.algorithms.swap.connected_double_edge_swap"]], "directed_edge_swap() (in module networkx.algorithms.swap)": [[693, "networkx.algorithms.swap.directed_edge_swap"]], "double_edge_swap() (in module networkx.algorithms.swap)": [[694, "networkx.algorithms.swap.double_edge_swap"]], "find_threshold_graph() (in module networkx.algorithms.threshold)": [[695, "networkx.algorithms.threshold.find_threshold_graph"]], "is_threshold_graph() (in module networkx.algorithms.threshold)": [[696, "networkx.algorithms.threshold.is_threshold_graph"]], "hamiltonian_path() (in module networkx.algorithms.tournament)": [[697, "networkx.algorithms.tournament.hamiltonian_path"]], "is_reachable() (in module networkx.algorithms.tournament)": [[698, "networkx.algorithms.tournament.is_reachable"]], "is_strongly_connected() (in module networkx.algorithms.tournament)": [[699, "networkx.algorithms.tournament.is_strongly_connected"]], "is_tournament() (in module networkx.algorithms.tournament)": [[700, "networkx.algorithms.tournament.is_tournament"]], "random_tournament() (in module networkx.algorithms.tournament)": [[701, "networkx.algorithms.tournament.random_tournament"]], "score_sequence() (in module networkx.algorithms.tournament)": [[702, "networkx.algorithms.tournament.score_sequence"]], "bfs_beam_edges() (in module networkx.algorithms.traversal.beamsearch)": [[703, "networkx.algorithms.traversal.beamsearch.bfs_beam_edges"]], "bfs_edges() (in module networkx.algorithms.traversal.breadth_first_search)": [[704, "networkx.algorithms.traversal.breadth_first_search.bfs_edges"]], "bfs_layers() (in module networkx.algorithms.traversal.breadth_first_search)": [[705, "networkx.algorithms.traversal.breadth_first_search.bfs_layers"]], "bfs_predecessors() (in module networkx.algorithms.traversal.breadth_first_search)": [[706, "networkx.algorithms.traversal.breadth_first_search.bfs_predecessors"]], "bfs_successors() (in module networkx.algorithms.traversal.breadth_first_search)": [[707, "networkx.algorithms.traversal.breadth_first_search.bfs_successors"]], "bfs_tree() (in module networkx.algorithms.traversal.breadth_first_search)": [[708, "networkx.algorithms.traversal.breadth_first_search.bfs_tree"]], "descendants_at_distance() (in module networkx.algorithms.traversal.breadth_first_search)": [[709, "networkx.algorithms.traversal.breadth_first_search.descendants_at_distance"]], "dfs_edges() (in module networkx.algorithms.traversal.depth_first_search)": [[710, "networkx.algorithms.traversal.depth_first_search.dfs_edges"]], "dfs_labeled_edges() (in module networkx.algorithms.traversal.depth_first_search)": [[711, "networkx.algorithms.traversal.depth_first_search.dfs_labeled_edges"]], "dfs_postorder_nodes() (in module networkx.algorithms.traversal.depth_first_search)": [[712, "networkx.algorithms.traversal.depth_first_search.dfs_postorder_nodes"]], "dfs_predecessors() (in module networkx.algorithms.traversal.depth_first_search)": [[713, "networkx.algorithms.traversal.depth_first_search.dfs_predecessors"]], "dfs_preorder_nodes() (in module networkx.algorithms.traversal.depth_first_search)": [[714, "networkx.algorithms.traversal.depth_first_search.dfs_preorder_nodes"]], "dfs_successors() (in module networkx.algorithms.traversal.depth_first_search)": [[715, "networkx.algorithms.traversal.depth_first_search.dfs_successors"]], "dfs_tree() (in module networkx.algorithms.traversal.depth_first_search)": [[716, "networkx.algorithms.traversal.depth_first_search.dfs_tree"]], "edge_bfs() (in module networkx.algorithms.traversal.edgebfs)": [[717, "networkx.algorithms.traversal.edgebfs.edge_bfs"]], "edge_dfs() (in module networkx.algorithms.traversal.edgedfs)": [[718, "networkx.algorithms.traversal.edgedfs.edge_dfs"]], "arborescenceiterator (class in networkx.algorithms.tree.branchings)": [[719, "networkx.algorithms.tree.branchings.ArborescenceIterator"]], "__init__() (arborescenceiterator method)": [[719, "networkx.algorithms.tree.branchings.ArborescenceIterator.__init__"]], "edmonds (class in networkx.algorithms.tree.branchings)": [[720, "networkx.algorithms.tree.branchings.Edmonds"]], "__init__() (edmonds method)": [[720, "networkx.algorithms.tree.branchings.Edmonds.__init__"]], "branching_weight() (in module networkx.algorithms.tree.branchings)": [[721, "networkx.algorithms.tree.branchings.branching_weight"]], "greedy_branching() (in module networkx.algorithms.tree.branchings)": [[722, "networkx.algorithms.tree.branchings.greedy_branching"]], "maximum_branching() (in module networkx.algorithms.tree.branchings)": [[723, "networkx.algorithms.tree.branchings.maximum_branching"]], "maximum_spanning_arborescence() (in module networkx.algorithms.tree.branchings)": [[724, "networkx.algorithms.tree.branchings.maximum_spanning_arborescence"]], "minimum_branching() (in module networkx.algorithms.tree.branchings)": [[725, "networkx.algorithms.tree.branchings.minimum_branching"]], "minimum_spanning_arborescence() (in module networkx.algorithms.tree.branchings)": [[726, "networkx.algorithms.tree.branchings.minimum_spanning_arborescence"]], "notatree": [[727, "networkx.algorithms.tree.coding.NotATree"]], "from_nested_tuple() (in module networkx.algorithms.tree.coding)": [[728, "networkx.algorithms.tree.coding.from_nested_tuple"]], "from_prufer_sequence() (in module networkx.algorithms.tree.coding)": [[729, "networkx.algorithms.tree.coding.from_prufer_sequence"]], "to_nested_tuple() (in module networkx.algorithms.tree.coding)": [[730, "networkx.algorithms.tree.coding.to_nested_tuple"]], "to_prufer_sequence() (in module networkx.algorithms.tree.coding)": [[731, "networkx.algorithms.tree.coding.to_prufer_sequence"]], "junction_tree() (in module networkx.algorithms.tree.decomposition)": [[732, "networkx.algorithms.tree.decomposition.junction_tree"]], "spanningtreeiterator (class in networkx.algorithms.tree.mst)": [[733, "networkx.algorithms.tree.mst.SpanningTreeIterator"]], "__init__() (spanningtreeiterator method)": [[733, "networkx.algorithms.tree.mst.SpanningTreeIterator.__init__"]], "maximum_spanning_edges() (in module networkx.algorithms.tree.mst)": [[734, "networkx.algorithms.tree.mst.maximum_spanning_edges"]], "maximum_spanning_tree() (in module networkx.algorithms.tree.mst)": [[735, "networkx.algorithms.tree.mst.maximum_spanning_tree"]], "minimum_spanning_edges() (in module networkx.algorithms.tree.mst)": [[736, "networkx.algorithms.tree.mst.minimum_spanning_edges"]], "minimum_spanning_tree() (in module networkx.algorithms.tree.mst)": [[737, "networkx.algorithms.tree.mst.minimum_spanning_tree"]], "random_spanning_tree() (in module networkx.algorithms.tree.mst)": [[738, "networkx.algorithms.tree.mst.random_spanning_tree"]], "join() (in module networkx.algorithms.tree.operations)": [[739, "networkx.algorithms.tree.operations.join"]], "is_arborescence() (in module networkx.algorithms.tree.recognition)": [[740, "networkx.algorithms.tree.recognition.is_arborescence"]], "is_branching() (in module networkx.algorithms.tree.recognition)": [[741, "networkx.algorithms.tree.recognition.is_branching"]], "is_forest() (in module networkx.algorithms.tree.recognition)": [[742, "networkx.algorithms.tree.recognition.is_forest"]], "is_tree() (in module networkx.algorithms.tree.recognition)": [[743, "networkx.algorithms.tree.recognition.is_tree"]], "all_triads() (in module networkx.algorithms.triads)": [[744, "networkx.algorithms.triads.all_triads"]], "all_triplets() (in module networkx.algorithms.triads)": [[745, "networkx.algorithms.triads.all_triplets"]], "is_triad() (in module networkx.algorithms.triads)": [[746, "networkx.algorithms.triads.is_triad"]], "random_triad() (in module networkx.algorithms.triads)": [[747, "networkx.algorithms.triads.random_triad"]], "triad_type() (in module networkx.algorithms.triads)": [[748, "networkx.algorithms.triads.triad_type"]], "triadic_census() (in module networkx.algorithms.triads)": [[749, "networkx.algorithms.triads.triadic_census"]], "triads_by_type() (in module networkx.algorithms.triads)": [[750, "networkx.algorithms.triads.triads_by_type"]], "closeness_vitality() (in module networkx.algorithms.vitality)": [[751, "networkx.algorithms.vitality.closeness_vitality"]], "voronoi_cells() (in module networkx.algorithms.voronoi)": [[752, "networkx.algorithms.voronoi.voronoi_cells"]], "wiener_index() (in module networkx.algorithms.wiener)": [[753, "networkx.algorithms.wiener.wiener_index"]], "networkx.algorithms.graph_hashing": [[754, "module-networkx.algorithms.graph_hashing"]], "networkx.algorithms.graphical": [[755, "module-networkx.algorithms.graphical"]], "networkx.algorithms.hierarchy": [[756, "module-networkx.algorithms.hierarchy"]], "networkx.algorithms.hybrid": [[757, "module-networkx.algorithms.hybrid"]], "networkx.algorithms.isolate": [[759, "module-networkx.algorithms.isolate"]], "networkx.algorithms.isomorphism": [[760, "module-networkx.algorithms.isomorphism"]], "networkx.algorithms.isomorphism.tree_isomorphism": [[760, "module-networkx.algorithms.isomorphism.tree_isomorphism"]], "networkx.algorithms.isomorphism.vf2pp": [[760, "module-networkx.algorithms.isomorphism.vf2pp"]], "networkx.algorithms.isomorphism.ismags": [[761, "module-networkx.algorithms.isomorphism.ismags"]], "networkx.algorithms.isomorphism.isomorphvf2": [[762, "module-networkx.algorithms.isomorphism.isomorphvf2"]], "networkx.algorithms.link_analysis.hits_alg": [[763, "module-networkx.algorithms.link_analysis.hits_alg"]], "networkx.algorithms.link_analysis.pagerank_alg": [[763, "module-networkx.algorithms.link_analysis.pagerank_alg"]], "networkx.algorithms.link_prediction": [[764, "module-networkx.algorithms.link_prediction"]], "networkx.algorithms.lowest_common_ancestors": [[765, "module-networkx.algorithms.lowest_common_ancestors"]], "networkx.algorithms.matching": [[766, "module-networkx.algorithms.matching"]], "networkx.algorithms.minors": [[767, "module-networkx.algorithms.minors"]], "networkx.algorithms.mis": [[768, "module-networkx.algorithms.mis"]], "networkx.algorithms.moral": [[769, "module-networkx.algorithms.moral"]], "networkx.algorithms.node_classification": [[770, "module-networkx.algorithms.node_classification"]], "networkx.algorithms.non_randomness": [[771, "module-networkx.algorithms.non_randomness"]], "networkx.algorithms.operators.all": [[772, "module-networkx.algorithms.operators.all"]], "networkx.algorithms.operators.binary": [[772, "module-networkx.algorithms.operators.binary"]], "networkx.algorithms.operators.product": [[772, "module-networkx.algorithms.operators.product"]], "networkx.algorithms.operators.unary": [[772, "module-networkx.algorithms.operators.unary"]], "networkx.algorithms.planar_drawing": [[773, "module-networkx.algorithms.planar_drawing"]], "networkx.algorithms.planarity": [[774, "module-networkx.algorithms.planarity"]], "networkx.algorithms.polynomials": [[775, "module-networkx.algorithms.polynomials"]], "networkx.algorithms.reciprocity": [[776, "module-networkx.algorithms.reciprocity"]], "networkx.algorithms.regular": [[777, "module-networkx.algorithms.regular"]], "networkx.algorithms.richclub": [[778, "module-networkx.algorithms.richclub"]], "networkx.algorithms.shortest_paths.astar": [[779, "module-networkx.algorithms.shortest_paths.astar"]], "networkx.algorithms.shortest_paths.dense": [[779, "module-networkx.algorithms.shortest_paths.dense"]], "networkx.algorithms.shortest_paths.generic": [[779, "module-networkx.algorithms.shortest_paths.generic"]], "networkx.algorithms.shortest_paths.unweighted": [[779, "module-networkx.algorithms.shortest_paths.unweighted"]], "networkx.algorithms.shortest_paths.weighted": [[779, "module-networkx.algorithms.shortest_paths.weighted"]], "networkx.algorithms.similarity": [[780, "module-networkx.algorithms.similarity"]], "networkx.algorithms.simple_paths": [[781, "module-networkx.algorithms.simple_paths"]], "networkx.algorithms.smallworld": [[782, "module-networkx.algorithms.smallworld"]], "networkx.algorithms.smetric": [[783, "module-networkx.algorithms.smetric"]], "networkx.algorithms.sparsifiers": [[784, "module-networkx.algorithms.sparsifiers"]], "networkx.algorithms.structuralholes": [[785, "module-networkx.algorithms.structuralholes"]], "networkx.algorithms.summarization": [[786, "module-networkx.algorithms.summarization"]], "networkx.algorithms.swap": [[787, "module-networkx.algorithms.swap"]], "networkx.algorithms.threshold": [[788, "module-networkx.algorithms.threshold"]], "networkx.algorithms.tournament": [[789, "module-networkx.algorithms.tournament"]], "networkx.algorithms.traversal.beamsearch": [[790, "module-networkx.algorithms.traversal.beamsearch"]], "networkx.algorithms.traversal.breadth_first_search": [[790, "module-networkx.algorithms.traversal.breadth_first_search"]], "networkx.algorithms.traversal.depth_first_search": [[790, "module-networkx.algorithms.traversal.depth_first_search"]], "networkx.algorithms.traversal.edgebfs": [[790, "module-networkx.algorithms.traversal.edgebfs"]], "networkx.algorithms.traversal.edgedfs": [[790, "module-networkx.algorithms.traversal.edgedfs"]], "networkx.algorithms.tree.branchings": [[791, "module-networkx.algorithms.tree.branchings"]], "networkx.algorithms.tree.coding": [[791, "module-networkx.algorithms.tree.coding"]], "networkx.algorithms.tree.decomposition": [[791, "module-networkx.algorithms.tree.decomposition"]], "networkx.algorithms.tree.mst": [[791, "module-networkx.algorithms.tree.mst"]], "networkx.algorithms.tree.operations": [[791, "module-networkx.algorithms.tree.operations"]], "networkx.algorithms.tree.recognition": [[791, "module-networkx.algorithms.tree.recognition"]], "networkx.algorithms.triads": [[792, "module-networkx.algorithms.triads"]], "networkx.algorithms.vitality": [[793, "module-networkx.algorithms.vitality"]], "networkx.algorithms.voronoi": [[794, "module-networkx.algorithms.voronoi"]], "networkx.algorithms.wiener": [[795, "module-networkx.algorithms.wiener"]], "digraph (class in networkx)": [[796, "networkx.DiGraph"]], "copy() (adjacencyview method)": [[797, "networkx.classes.coreviews.AdjacencyView.copy"]], "get() (adjacencyview method)": [[798, "networkx.classes.coreviews.AdjacencyView.get"]], "items() (adjacencyview method)": [[799, "networkx.classes.coreviews.AdjacencyView.items"]], "keys() (adjacencyview method)": [[800, "networkx.classes.coreviews.AdjacencyView.keys"]], "values() (adjacencyview method)": [[801, "networkx.classes.coreviews.AdjacencyView.values"]], "copy() (atlasview method)": [[802, "networkx.classes.coreviews.AtlasView.copy"]], "get() (atlasview method)": [[803, 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"networkx.classes.coreviews.UnionAtlas.get"]], "items() (unionatlas method)": [[835, "networkx.classes.coreviews.UnionAtlas.items"]], "keys() (unionatlas method)": [[836, "networkx.classes.coreviews.UnionAtlas.keys"]], "values() (unionatlas method)": [[837, "networkx.classes.coreviews.UnionAtlas.values"]], "copy() (unionmultiadjacency method)": [[838, "networkx.classes.coreviews.UnionMultiAdjacency.copy"]], "get() (unionmultiadjacency method)": [[839, "networkx.classes.coreviews.UnionMultiAdjacency.get"]], "items() (unionmultiadjacency method)": [[840, "networkx.classes.coreviews.UnionMultiAdjacency.items"]], "keys() (unionmultiadjacency method)": [[841, "networkx.classes.coreviews.UnionMultiAdjacency.keys"]], "values() (unionmultiadjacency method)": [[842, "networkx.classes.coreviews.UnionMultiAdjacency.values"]], "copy() (unionmultiinner method)": [[843, "networkx.classes.coreviews.UnionMultiInner.copy"]], "get() (unionmultiinner method)": [[844, 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"add_weighted_edges_from() (digraph method)": [[857, "networkx.DiGraph.add_weighted_edges_from"]], "adj (digraph property)": [[858, "networkx.DiGraph.adj"]], "adjacency() (digraph method)": [[859, "networkx.DiGraph.adjacency"]], "clear() (digraph method)": [[860, "networkx.DiGraph.clear"]], "clear_edges() (digraph method)": [[861, "networkx.DiGraph.clear_edges"]], "copy() (digraph method)": [[862, "networkx.DiGraph.copy"]], "degree (digraph property)": [[863, "networkx.DiGraph.degree"]], "edge_subgraph() (digraph method)": [[864, "networkx.DiGraph.edge_subgraph"]], "edges (digraph property)": [[865, "networkx.DiGraph.edges"]], "get_edge_data() (digraph method)": [[866, "networkx.DiGraph.get_edge_data"]], "has_edge() (digraph method)": [[867, "networkx.DiGraph.has_edge"]], "has_node() (digraph method)": [[868, "networkx.DiGraph.has_node"]], "in_degree (digraph property)": [[869, "networkx.DiGraph.in_degree"]], "in_edges (digraph property)": [[870, "networkx.DiGraph.in_edges"]], "nbunch_iter() (digraph method)": [[871, "networkx.DiGraph.nbunch_iter"]], "neighbors() (digraph method)": [[872, "networkx.DiGraph.neighbors"]], "nodes (digraph property)": [[873, "networkx.DiGraph.nodes"]], "number_of_edges() (digraph method)": [[874, "networkx.DiGraph.number_of_edges"]], "number_of_nodes() (digraph method)": [[875, "networkx.DiGraph.number_of_nodes"]], "order() (digraph method)": [[876, "networkx.DiGraph.order"]], "out_degree (digraph property)": [[877, "networkx.DiGraph.out_degree"]], "out_edges (digraph property)": [[878, "networkx.DiGraph.out_edges"]], "pred (digraph property)": [[879, "networkx.DiGraph.pred"]], "predecessors() (digraph method)": [[880, "networkx.DiGraph.predecessors"]], "remove_edge() (digraph method)": [[881, "networkx.DiGraph.remove_edge"]], "remove_edges_from() (digraph method)": [[882, "networkx.DiGraph.remove_edges_from"]], "remove_node() (digraph method)": [[883, "networkx.DiGraph.remove_node"]], "remove_nodes_from() (digraph method)": 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method)": [[988, "networkx.MultiGraph.copy"]], "degree (multigraph property)": [[989, "networkx.MultiGraph.degree"]], "edge_subgraph() (multigraph method)": [[990, "networkx.MultiGraph.edge_subgraph"]], "edges (multigraph property)": [[991, "networkx.MultiGraph.edges"]], "get_edge_data() (multigraph method)": [[992, "networkx.MultiGraph.get_edge_data"]], "has_edge() (multigraph method)": [[993, "networkx.MultiGraph.has_edge"]], "has_node() (multigraph method)": [[994, "networkx.MultiGraph.has_node"]], "nbunch_iter() (multigraph method)": [[995, "networkx.MultiGraph.nbunch_iter"]], "neighbors() (multigraph method)": [[996, "networkx.MultiGraph.neighbors"]], "new_edge_key() (multigraph method)": [[997, "networkx.MultiGraph.new_edge_key"]], "nodes (multigraph property)": [[998, "networkx.MultiGraph.nodes"]], "number_of_edges() (multigraph method)": [[999, "networkx.MultiGraph.number_of_edges"]], "number_of_nodes() (multigraph method)": [[1000, "networkx.MultiGraph.number_of_nodes"]], "order() (multigraph method)": [[1001, "networkx.MultiGraph.order"]], "remove_edge() (multigraph method)": [[1002, "networkx.MultiGraph.remove_edge"]], "remove_edges_from() (multigraph method)": [[1003, "networkx.MultiGraph.remove_edges_from"]], "remove_node() (multigraph method)": [[1004, "networkx.MultiGraph.remove_node"]], "remove_nodes_from() (multigraph method)": [[1005, "networkx.MultiGraph.remove_nodes_from"]], "size() (multigraph method)": [[1006, "networkx.MultiGraph.size"]], "subgraph() (multigraph method)": [[1007, "networkx.MultiGraph.subgraph"]], "to_directed() (multigraph method)": [[1008, "networkx.MultiGraph.to_directed"]], "to_undirected() (multigraph method)": [[1009, "networkx.MultiGraph.to_undirected"]], "update() (multigraph method)": [[1010, "networkx.MultiGraph.update"]], "_dispatch() (in module networkx.classes.backends)": [[1011, "networkx.classes.backends._dispatch"]], "adjacencyview (class in networkx.classes.coreviews)": [[1012, "networkx.classes.coreviews.AdjacencyView"]], "__init__() (adjacencyview method)": [[1012, "networkx.classes.coreviews.AdjacencyView.__init__"]], "atlasview (class in networkx.classes.coreviews)": [[1013, "networkx.classes.coreviews.AtlasView"]], "__init__() (atlasview method)": [[1013, "networkx.classes.coreviews.AtlasView.__init__"]], "filteradjacency (class in networkx.classes.coreviews)": [[1014, "networkx.classes.coreviews.FilterAdjacency"]], "__init__() (filteradjacency method)": [[1014, "networkx.classes.coreviews.FilterAdjacency.__init__"]], "filteratlas (class in networkx.classes.coreviews)": [[1015, "networkx.classes.coreviews.FilterAtlas"]], "__init__() (filteratlas method)": [[1015, "networkx.classes.coreviews.FilterAtlas.__init__"]], "filtermultiadjacency (class in networkx.classes.coreviews)": [[1016, "networkx.classes.coreviews.FilterMultiAdjacency"]], "__init__() (filtermultiadjacency method)": [[1016, "networkx.classes.coreviews.FilterMultiAdjacency.__init__"]], "filtermultiinner (class in networkx.classes.coreviews)": [[1017, "networkx.classes.coreviews.FilterMultiInner"]], "__init__() (filtermultiinner method)": [[1017, "networkx.classes.coreviews.FilterMultiInner.__init__"]], "multiadjacencyview (class in networkx.classes.coreviews)": [[1018, "networkx.classes.coreviews.MultiAdjacencyView"]], "__init__() (multiadjacencyview method)": [[1018, "networkx.classes.coreviews.MultiAdjacencyView.__init__"]], "unionadjacency (class in networkx.classes.coreviews)": [[1019, "networkx.classes.coreviews.UnionAdjacency"]], "__init__() (unionadjacency method)": [[1019, "networkx.classes.coreviews.UnionAdjacency.__init__"]], "unionatlas (class in networkx.classes.coreviews)": [[1020, "networkx.classes.coreviews.UnionAtlas"]], "__init__() (unionatlas method)": [[1020, "networkx.classes.coreviews.UnionAtlas.__init__"]], "unionmultiadjacency (class in networkx.classes.coreviews)": [[1021, "networkx.classes.coreviews.UnionMultiAdjacency"]], "__init__() (unionmultiadjacency method)": [[1021, "networkx.classes.coreviews.UnionMultiAdjacency.__init__"]], "unionmultiinner (class in networkx.classes.coreviews)": [[1022, "networkx.classes.coreviews.UnionMultiInner"]], "__init__() (unionmultiinner method)": [[1022, "networkx.classes.coreviews.UnionMultiInner.__init__"]], "hide_diedges() (in module networkx.classes.filters)": [[1023, "networkx.classes.filters.hide_diedges"]], "hide_edges() (in module networkx.classes.filters)": [[1024, "networkx.classes.filters.hide_edges"]], "hide_multidiedges() (in module networkx.classes.filters)": [[1025, "networkx.classes.filters.hide_multidiedges"]], "hide_multiedges() (in module networkx.classes.filters)": [[1026, "networkx.classes.filters.hide_multiedges"]], "hide_nodes() (in module networkx.classes.filters)": [[1027, "networkx.classes.filters.hide_nodes"]], "no_filter() (in module networkx.classes.filters)": [[1028, "networkx.classes.filters.no_filter"]], "show_diedges() (in module networkx.classes.filters)": [[1029, "networkx.classes.filters.show_diedges"]], "show_edges() (in module networkx.classes.filters)": [[1030, "networkx.classes.filters.show_edges"]], "show_multidiedges() (in module networkx.classes.filters)": [[1031, "networkx.classes.filters.show_multidiedges"]], "show_multiedges() (in module networkx.classes.filters)": [[1032, "networkx.classes.filters.show_multiedges"]], "__init__() (show_nodes method)": [[1033, "networkx.classes.filters.show_nodes.__init__"]], "show_nodes (class in networkx.classes.filters)": [[1033, "networkx.classes.filters.show_nodes"]], "generic_graph_view() (in module networkx.classes.graphviews)": [[1034, "networkx.classes.graphviews.generic_graph_view"]], "reverse_view() (in module networkx.classes.graphviews)": [[1035, "networkx.classes.graphviews.reverse_view"]], "subgraph_view() (in module networkx.classes.graphviews)": [[1036, "networkx.classes.graphviews.subgraph_view"]], "graph (class in networkx)": [[1037, "networkx.Graph"]], "networkx.classes.backends": [[1038, "module-networkx.classes.backends"]], "networkx.classes.coreviews": [[1038, "module-networkx.classes.coreviews"]], "networkx.classes.filters": [[1038, "module-networkx.classes.filters"]], "networkx.classes.graphviews": [[1038, "module-networkx.classes.graphviews"]], "multidigraph (class in networkx)": [[1039, "networkx.MultiDiGraph"]], "multigraph (class in networkx)": [[1040, "networkx.MultiGraph"]], "networkx.convert": [[1041, "module-networkx.convert"]], "networkx.convert_matrix": [[1041, "module-networkx.convert_matrix"]], "networkx.drawing.layout": [[1042, "module-networkx.drawing.layout"]], "networkx.drawing.nx_agraph": [[1042, "module-networkx.drawing.nx_agraph"]], "networkx.drawing.nx_pydot": [[1042, "module-networkx.drawing.nx_pydot"]], "networkx.drawing.nx_pylab": [[1042, "module-networkx.drawing.nx_pylab"]], "ambiguoussolution (class in networkx)": [[1043, "networkx.AmbiguousSolution"]], "exceededmaxiterations (class in networkx)": [[1043, "networkx.ExceededMaxIterations"]], "hasacycle (class in networkx)": [[1043, "networkx.HasACycle"]], "networkxalgorithmerror (class in networkx)": [[1043, "networkx.NetworkXAlgorithmError"]], "networkxerror (class in networkx)": [[1043, "networkx.NetworkXError"]], "networkxexception (class in networkx)": [[1043, "networkx.NetworkXException"]], "networkxnocycle (class in networkx)": [[1043, "networkx.NetworkXNoCycle"]], "networkxnopath (class in networkx)": [[1043, "networkx.NetworkXNoPath"]], "networkxnotimplemented (class in networkx)": [[1043, "networkx.NetworkXNotImplemented"]], "networkxpointlessconcept (class in networkx)": [[1043, "networkx.NetworkXPointlessConcept"]], "networkxunbounded (class in networkx)": [[1043, "networkx.NetworkXUnbounded"]], "networkxunfeasible (class in networkx)": [[1043, "networkx.NetworkXUnfeasible"]], "nodenotfound (class in networkx)": [[1043, "networkx.NodeNotFound"]], "poweriterationfailedconvergence (class in networkx)": [[1043, "networkx.PowerIterationFailedConvergence"]], "networkx.exception": [[1043, "module-networkx.exception"]], "networkx.classes.function": [[1044, "module-networkx.classes.function"]], "assemble() (argmap method)": [[1045, "networkx.utils.decorators.argmap.assemble"]], "compile() (argmap method)": [[1046, "networkx.utils.decorators.argmap.compile"]], "signature() (argmap class method)": [[1047, "networkx.utils.decorators.argmap.signature"]], "pop() (mappedqueue method)": [[1048, "networkx.utils.mapped_queue.MappedQueue.pop"]], "push() (mappedqueue method)": [[1049, "networkx.utils.mapped_queue.MappedQueue.push"]], "remove() (mappedqueue method)": [[1050, "networkx.utils.mapped_queue.MappedQueue.remove"]], "update() (mappedqueue method)": [[1051, "networkx.utils.mapped_queue.MappedQueue.update"]], "add_cycle() (in module networkx.classes.function)": [[1052, "networkx.classes.function.add_cycle"]], "add_path() (in module networkx.classes.function)": [[1053, "networkx.classes.function.add_path"]], "add_star() (in module networkx.classes.function)": [[1054, "networkx.classes.function.add_star"]], "all_neighbors() (in module networkx.classes.function)": [[1055, "networkx.classes.function.all_neighbors"]], "common_neighbors() (in module networkx.classes.function)": [[1056, "networkx.classes.function.common_neighbors"]], "create_empty_copy() (in module networkx.classes.function)": [[1057, "networkx.classes.function.create_empty_copy"]], "degree() (in module networkx.classes.function)": [[1058, "networkx.classes.function.degree"]], "degree_histogram() (in module networkx.classes.function)": [[1059, "networkx.classes.function.degree_histogram"]], "density() (in module networkx.classes.function)": [[1060, "networkx.classes.function.density"]], "edge_subgraph() (in module networkx.classes.function)": [[1061, "networkx.classes.function.edge_subgraph"]], "edges() (in module networkx.classes.function)": [[1062, "networkx.classes.function.edges"]], "freeze() (in module networkx.classes.function)": [[1063, "networkx.classes.function.freeze"]], "get_edge_attributes() (in module networkx.classes.function)": [[1064, "networkx.classes.function.get_edge_attributes"]], "get_node_attributes() (in module networkx.classes.function)": [[1065, "networkx.classes.function.get_node_attributes"]], "induced_subgraph() (in module networkx.classes.function)": [[1066, "networkx.classes.function.induced_subgraph"]], "is_directed() (in module networkx.classes.function)": [[1067, "networkx.classes.function.is_directed"]], "is_empty() (in module networkx.classes.function)": [[1068, "networkx.classes.function.is_empty"]], "is_frozen() (in module networkx.classes.function)": [[1069, "networkx.classes.function.is_frozen"]], "is_negatively_weighted() (in module networkx.classes.function)": [[1070, "networkx.classes.function.is_negatively_weighted"]], "is_path() (in module networkx.classes.function)": [[1071, "networkx.classes.function.is_path"]], "is_weighted() (in module networkx.classes.function)": [[1072, "networkx.classes.function.is_weighted"]], "neighbors() (in module networkx.classes.function)": [[1073, "networkx.classes.function.neighbors"]], "nodes() (in module networkx.classes.function)": [[1074, "networkx.classes.function.nodes"]], "nodes_with_selfloops() (in module networkx.classes.function)": [[1075, "networkx.classes.function.nodes_with_selfloops"]], "non_edges() (in module networkx.classes.function)": [[1076, "networkx.classes.function.non_edges"]], "non_neighbors() (in module networkx.classes.function)": [[1077, "networkx.classes.function.non_neighbors"]], "number_of_edges() (in module networkx.classes.function)": [[1078, "networkx.classes.function.number_of_edges"]], "number_of_nodes() (in module networkx.classes.function)": [[1079, "networkx.classes.function.number_of_nodes"]], "number_of_selfloops() (in module networkx.classes.function)": [[1080, "networkx.classes.function.number_of_selfloops"]], "path_weight() (in module networkx.classes.function)": [[1081, "networkx.classes.function.path_weight"]], "restricted_view() (in module networkx.classes.function)": [[1082, "networkx.classes.function.restricted_view"]], "reverse_view() (in module networkx.classes.function)": [[1083, "networkx.classes.function.reverse_view"]], "selfloop_edges() (in module networkx.classes.function)": [[1084, "networkx.classes.function.selfloop_edges"]], "set_edge_attributes() (in module networkx.classes.function)": [[1085, "networkx.classes.function.set_edge_attributes"]], "set_node_attributes() (in module networkx.classes.function)": [[1086, "networkx.classes.function.set_node_attributes"]], "subgraph() (in module networkx.classes.function)": [[1087, "networkx.classes.function.subgraph"]], "subgraph_view() (in module networkx.classes.function)": [[1088, "networkx.classes.function.subgraph_view"]], "to_directed() (in module networkx.classes.function)": [[1089, "networkx.classes.function.to_directed"]], "to_undirected() (in module networkx.classes.function)": [[1090, "networkx.classes.function.to_undirected"]], "from_dict_of_dicts() (in module networkx.convert)": [[1091, "networkx.convert.from_dict_of_dicts"]], "from_dict_of_lists() (in module networkx.convert)": [[1092, "networkx.convert.from_dict_of_lists"]], "from_edgelist() (in module networkx.convert)": [[1093, "networkx.convert.from_edgelist"]], "to_dict_of_dicts() (in module networkx.convert)": [[1094, "networkx.convert.to_dict_of_dicts"]], "to_dict_of_lists() (in module networkx.convert)": [[1095, "networkx.convert.to_dict_of_lists"]], "to_edgelist() (in module networkx.convert)": [[1096, "networkx.convert.to_edgelist"]], "to_networkx_graph() (in module networkx.convert)": [[1097, "networkx.convert.to_networkx_graph"]], "from_numpy_array() (in module networkx.convert_matrix)": [[1098, "networkx.convert_matrix.from_numpy_array"]], "from_pandas_adjacency() (in module networkx.convert_matrix)": [[1099, "networkx.convert_matrix.from_pandas_adjacency"]], "from_pandas_edgelist() (in module networkx.convert_matrix)": [[1100, "networkx.convert_matrix.from_pandas_edgelist"]], "from_scipy_sparse_array() (in module networkx.convert_matrix)": [[1101, "networkx.convert_matrix.from_scipy_sparse_array"]], "to_numpy_array() (in module networkx.convert_matrix)": [[1102, "networkx.convert_matrix.to_numpy_array"]], "to_pandas_adjacency() (in module networkx.convert_matrix)": [[1103, "networkx.convert_matrix.to_pandas_adjacency"]], "to_pandas_edgelist() (in module networkx.convert_matrix)": [[1104, "networkx.convert_matrix.to_pandas_edgelist"]], "to_scipy_sparse_array() (in module networkx.convert_matrix)": [[1105, "networkx.convert_matrix.to_scipy_sparse_array"]], "bipartite_layout() (in module networkx.drawing.layout)": [[1106, "networkx.drawing.layout.bipartite_layout"]], "circular_layout() (in module networkx.drawing.layout)": [[1107, "networkx.drawing.layout.circular_layout"]], "kamada_kawai_layout() (in module networkx.drawing.layout)": [[1108, "networkx.drawing.layout.kamada_kawai_layout"]], "multipartite_layout() (in module networkx.drawing.layout)": [[1109, "networkx.drawing.layout.multipartite_layout"]], "planar_layout() (in module networkx.drawing.layout)": [[1110, "networkx.drawing.layout.planar_layout"]], "random_layout() (in module networkx.drawing.layout)": [[1111, "networkx.drawing.layout.random_layout"]], "rescale_layout() (in module networkx.drawing.layout)": [[1112, "networkx.drawing.layout.rescale_layout"]], "rescale_layout_dict() (in module networkx.drawing.layout)": [[1113, "networkx.drawing.layout.rescale_layout_dict"]], "shell_layout() (in module networkx.drawing.layout)": [[1114, "networkx.drawing.layout.shell_layout"]], "spectral_layout() (in module networkx.drawing.layout)": [[1115, "networkx.drawing.layout.spectral_layout"]], "spiral_layout() (in module networkx.drawing.layout)": [[1116, "networkx.drawing.layout.spiral_layout"]], 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module networkx.drawing.nx_pydot)": [[1126, "networkx.drawing.nx_pydot.pydot_layout"]], "read_dot() (in module networkx.drawing.nx_pydot)": [[1127, "networkx.drawing.nx_pydot.read_dot"]], "to_pydot() (in module networkx.drawing.nx_pydot)": [[1128, "networkx.drawing.nx_pydot.to_pydot"]], "write_dot() (in module networkx.drawing.nx_pydot)": [[1129, "networkx.drawing.nx_pydot.write_dot"]], "draw() (in module networkx.drawing.nx_pylab)": [[1130, "networkx.drawing.nx_pylab.draw"]], "draw_circular() (in module networkx.drawing.nx_pylab)": [[1131, "networkx.drawing.nx_pylab.draw_circular"]], "draw_kamada_kawai() (in module networkx.drawing.nx_pylab)": [[1132, "networkx.drawing.nx_pylab.draw_kamada_kawai"]], "draw_networkx() (in module networkx.drawing.nx_pylab)": [[1133, "networkx.drawing.nx_pylab.draw_networkx"]], "draw_networkx_edge_labels() (in module networkx.drawing.nx_pylab)": [[1134, "networkx.drawing.nx_pylab.draw_networkx_edge_labels"]], "draw_networkx_edges() (in module networkx.drawing.nx_pylab)": [[1135, "networkx.drawing.nx_pylab.draw_networkx_edges"]], "draw_networkx_labels() (in module networkx.drawing.nx_pylab)": [[1136, "networkx.drawing.nx_pylab.draw_networkx_labels"]], "draw_networkx_nodes() (in module networkx.drawing.nx_pylab)": [[1137, "networkx.drawing.nx_pylab.draw_networkx_nodes"]], "draw_planar() (in module networkx.drawing.nx_pylab)": [[1138, "networkx.drawing.nx_pylab.draw_planar"]], "draw_random() (in module networkx.drawing.nx_pylab)": [[1139, "networkx.drawing.nx_pylab.draw_random"]], "draw_shell() (in module networkx.drawing.nx_pylab)": [[1140, "networkx.drawing.nx_pylab.draw_shell"]], "draw_spectral() (in module networkx.drawing.nx_pylab)": [[1141, "networkx.drawing.nx_pylab.draw_spectral"]], "draw_spring() (in module networkx.drawing.nx_pylab)": [[1142, "networkx.drawing.nx_pylab.draw_spring"]], "graph_atlas() (in module networkx.generators.atlas)": [[1143, "networkx.generators.atlas.graph_atlas"]], "graph_atlas_g() (in module networkx.generators.atlas)": [[1144, "networkx.generators.atlas.graph_atlas_g"]], "balanced_tree() (in module networkx.generators.classic)": [[1145, "networkx.generators.classic.balanced_tree"]], "barbell_graph() (in module networkx.generators.classic)": [[1146, "networkx.generators.classic.barbell_graph"]], "binomial_tree() (in module networkx.generators.classic)": [[1147, "networkx.generators.classic.binomial_tree"]], "circulant_graph() (in module networkx.generators.classic)": [[1148, "networkx.generators.classic.circulant_graph"]], "circular_ladder_graph() (in module networkx.generators.classic)": [[1149, "networkx.generators.classic.circular_ladder_graph"]], "complete_graph() (in module networkx.generators.classic)": [[1150, "networkx.generators.classic.complete_graph"]], "complete_multipartite_graph() (in module networkx.generators.classic)": [[1151, "networkx.generators.classic.complete_multipartite_graph"]], "cycle_graph() (in module networkx.generators.classic)": [[1152, 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module networkx.generators.classic)": [[1161, "networkx.generators.classic.trivial_graph"]], "turan_graph() (in module networkx.generators.classic)": [[1162, "networkx.generators.classic.turan_graph"]], "wheel_graph() (in module networkx.generators.classic)": [[1163, "networkx.generators.classic.wheel_graph"]], "random_cograph() (in module networkx.generators.cographs)": [[1164, "networkx.generators.cographs.random_cograph"]], "lfr_benchmark_graph() (in module networkx.generators.community)": [[1165, "networkx.generators.community.LFR_benchmark_graph"]], "caveman_graph() (in module networkx.generators.community)": [[1166, "networkx.generators.community.caveman_graph"]], "connected_caveman_graph() (in module networkx.generators.community)": [[1167, "networkx.generators.community.connected_caveman_graph"]], "gaussian_random_partition_graph() (in module networkx.generators.community)": [[1168, "networkx.generators.community.gaussian_random_partition_graph"]], "planted_partition_graph() 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"networkx.generators.degree_seq.degree_sequence_tree"]], "directed_configuration_model() (in module networkx.generators.degree_seq)": [[1177, "networkx.generators.degree_seq.directed_configuration_model"]], "directed_havel_hakimi_graph() (in module networkx.generators.degree_seq)": [[1178, "networkx.generators.degree_seq.directed_havel_hakimi_graph"]], "expected_degree_graph() (in module networkx.generators.degree_seq)": [[1179, "networkx.generators.degree_seq.expected_degree_graph"]], "havel_hakimi_graph() (in module networkx.generators.degree_seq)": [[1180, "networkx.generators.degree_seq.havel_hakimi_graph"]], "random_degree_sequence_graph() (in module networkx.generators.degree_seq)": [[1181, "networkx.generators.degree_seq.random_degree_sequence_graph"]], "gn_graph() (in module networkx.generators.directed)": [[1182, "networkx.generators.directed.gn_graph"]], "gnc_graph() (in module networkx.generators.directed)": [[1183, "networkx.generators.directed.gnc_graph"]], "gnr_graph() 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networkx.generators.intersection)": [[1205, "networkx.generators.intersection.uniform_random_intersection_graph"]], "interval_graph() (in module networkx.generators.interval_graph)": [[1206, "networkx.generators.interval_graph.interval_graph"]], "directed_joint_degree_graph() (in module networkx.generators.joint_degree_seq)": [[1207, "networkx.generators.joint_degree_seq.directed_joint_degree_graph"]], "is_valid_directed_joint_degree() (in module networkx.generators.joint_degree_seq)": [[1208, "networkx.generators.joint_degree_seq.is_valid_directed_joint_degree"]], "is_valid_joint_degree() (in module networkx.generators.joint_degree_seq)": [[1209, "networkx.generators.joint_degree_seq.is_valid_joint_degree"]], "joint_degree_graph() (in module networkx.generators.joint_degree_seq)": [[1210, "networkx.generators.joint_degree_seq.joint_degree_graph"]], "grid_2d_graph() (in module networkx.generators.lattice)": [[1211, "networkx.generators.lattice.grid_2d_graph"]], "grid_graph() (in module networkx.generators.lattice)": [[1212, "networkx.generators.lattice.grid_graph"]], "hexagonal_lattice_graph() (in module networkx.generators.lattice)": [[1213, "networkx.generators.lattice.hexagonal_lattice_graph"]], "hypercube_graph() (in module networkx.generators.lattice)": [[1214, "networkx.generators.lattice.hypercube_graph"]], "triangular_lattice_graph() (in module networkx.generators.lattice)": [[1215, "networkx.generators.lattice.triangular_lattice_graph"]], "inverse_line_graph() (in module networkx.generators.line)": [[1216, "networkx.generators.line.inverse_line_graph"]], "line_graph() (in module networkx.generators.line)": [[1217, "networkx.generators.line.line_graph"]], "mycielski_graph() (in module networkx.generators.mycielski)": [[1218, "networkx.generators.mycielski.mycielski_graph"]], "mycielskian() (in module networkx.generators.mycielski)": [[1219, "networkx.generators.mycielski.mycielskian"]], "nonisomorphic_trees() (in module networkx.generators.nonisomorphic_trees)": [[1220, "networkx.generators.nonisomorphic_trees.nonisomorphic_trees"]], "number_of_nonisomorphic_trees() (in module networkx.generators.nonisomorphic_trees)": [[1221, "networkx.generators.nonisomorphic_trees.number_of_nonisomorphic_trees"]], "random_clustered_graph() (in module networkx.generators.random_clustered)": [[1222, "networkx.generators.random_clustered.random_clustered_graph"]], "barabasi_albert_graph() (in module networkx.generators.random_graphs)": [[1223, "networkx.generators.random_graphs.barabasi_albert_graph"]], "binomial_graph() (in module networkx.generators.random_graphs)": [[1224, "networkx.generators.random_graphs.binomial_graph"]], "connected_watts_strogatz_graph() (in module networkx.generators.random_graphs)": [[1225, "networkx.generators.random_graphs.connected_watts_strogatz_graph"]], "dense_gnm_random_graph() (in module networkx.generators.random_graphs)": [[1226, 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"networkx.generators.random_graphs.random_shell_graph"]], "watts_strogatz_graph() (in module networkx.generators.random_graphs)": [[1241, "networkx.generators.random_graphs.watts_strogatz_graph"]], "lcf_graph() (in module networkx.generators.small)": [[1242, "networkx.generators.small.LCF_graph"]], "bull_graph() (in module networkx.generators.small)": [[1243, "networkx.generators.small.bull_graph"]], "chvatal_graph() (in module networkx.generators.small)": [[1244, "networkx.generators.small.chvatal_graph"]], "cubical_graph() (in module networkx.generators.small)": [[1245, "networkx.generators.small.cubical_graph"]], "desargues_graph() (in module networkx.generators.small)": [[1246, "networkx.generators.small.desargues_graph"]], "diamond_graph() (in module networkx.generators.small)": [[1247, "networkx.generators.small.diamond_graph"]], "dodecahedral_graph() (in module networkx.generators.small)": [[1248, "networkx.generators.small.dodecahedral_graph"]], "frucht_graph() (in module networkx.generators.small)": [[1249, "networkx.generators.small.frucht_graph"]], "heawood_graph() (in module networkx.generators.small)": [[1250, "networkx.generators.small.heawood_graph"]], "hoffman_singleton_graph() (in module networkx.generators.small)": [[1251, "networkx.generators.small.hoffman_singleton_graph"]], "house_graph() (in module networkx.generators.small)": [[1252, "networkx.generators.small.house_graph"]], "house_x_graph() (in module networkx.generators.small)": [[1253, "networkx.generators.small.house_x_graph"]], "icosahedral_graph() (in module networkx.generators.small)": [[1254, "networkx.generators.small.icosahedral_graph"]], "krackhardt_kite_graph() (in module networkx.generators.small)": [[1255, "networkx.generators.small.krackhardt_kite_graph"]], "moebius_kantor_graph() (in module networkx.generators.small)": [[1256, "networkx.generators.small.moebius_kantor_graph"]], "octahedral_graph() (in module networkx.generators.small)": [[1257, "networkx.generators.small.octahedral_graph"]], "pappus_graph() (in module networkx.generators.small)": [[1258, "networkx.generators.small.pappus_graph"]], "petersen_graph() (in module networkx.generators.small)": [[1259, "networkx.generators.small.petersen_graph"]], "sedgewick_maze_graph() (in module networkx.generators.small)": [[1260, "networkx.generators.small.sedgewick_maze_graph"]], "tetrahedral_graph() (in module networkx.generators.small)": [[1261, "networkx.generators.small.tetrahedral_graph"]], "truncated_cube_graph() (in module networkx.generators.small)": [[1262, "networkx.generators.small.truncated_cube_graph"]], "truncated_tetrahedron_graph() (in module networkx.generators.small)": [[1263, "networkx.generators.small.truncated_tetrahedron_graph"]], "tutte_graph() (in module networkx.generators.small)": [[1264, "networkx.generators.small.tutte_graph"]], "davis_southern_women_graph() (in module networkx.generators.social)": [[1265, "networkx.generators.social.davis_southern_women_graph"]], "florentine_families_graph() (in module networkx.generators.social)": [[1266, "networkx.generators.social.florentine_families_graph"]], "karate_club_graph() (in module networkx.generators.social)": [[1267, "networkx.generators.social.karate_club_graph"]], "les_miserables_graph() (in module networkx.generators.social)": [[1268, "networkx.generators.social.les_miserables_graph"]], "spectral_graph_forge() (in module networkx.generators.spectral_graph_forge)": [[1269, "networkx.generators.spectral_graph_forge.spectral_graph_forge"]], "stochastic_graph() (in module networkx.generators.stochastic)": [[1270, "networkx.generators.stochastic.stochastic_graph"]], "sudoku_graph() (in module networkx.generators.sudoku)": [[1271, "networkx.generators.sudoku.sudoku_graph"]], "prefix_tree() (in module networkx.generators.trees)": [[1272, "networkx.generators.trees.prefix_tree"]], "random_tree() (in module networkx.generators.trees)": [[1273, "networkx.generators.trees.random_tree"]], "triad_graph() (in module networkx.generators.triads)": [[1274, "networkx.generators.triads.triad_graph"]], "algebraic_connectivity() (in module networkx.linalg.algebraicconnectivity)": [[1275, "networkx.linalg.algebraicconnectivity.algebraic_connectivity"]], "fiedler_vector() (in module networkx.linalg.algebraicconnectivity)": [[1276, "networkx.linalg.algebraicconnectivity.fiedler_vector"]], "spectral_ordering() (in module networkx.linalg.algebraicconnectivity)": [[1277, "networkx.linalg.algebraicconnectivity.spectral_ordering"]], "attr_matrix() (in module networkx.linalg.attrmatrix)": [[1278, "networkx.linalg.attrmatrix.attr_matrix"]], "attr_sparse_matrix() (in module networkx.linalg.attrmatrix)": [[1279, "networkx.linalg.attrmatrix.attr_sparse_matrix"]], "bethe_hessian_matrix() (in module networkx.linalg.bethehessianmatrix)": [[1280, "networkx.linalg.bethehessianmatrix.bethe_hessian_matrix"]], "adjacency_matrix() (in module networkx.linalg.graphmatrix)": [[1281, "networkx.linalg.graphmatrix.adjacency_matrix"]], "incidence_matrix() (in module networkx.linalg.graphmatrix)": [[1282, "networkx.linalg.graphmatrix.incidence_matrix"]], "directed_combinatorial_laplacian_matrix() (in module networkx.linalg.laplacianmatrix)": [[1283, "networkx.linalg.laplacianmatrix.directed_combinatorial_laplacian_matrix"]], "directed_laplacian_matrix() (in module networkx.linalg.laplacianmatrix)": [[1284, "networkx.linalg.laplacianmatrix.directed_laplacian_matrix"]], "laplacian_matrix() (in module networkx.linalg.laplacianmatrix)": [[1285, "networkx.linalg.laplacianmatrix.laplacian_matrix"]], "normalized_laplacian_matrix() (in module networkx.linalg.laplacianmatrix)": [[1286, "networkx.linalg.laplacianmatrix.normalized_laplacian_matrix"]], "directed_modularity_matrix() (in module networkx.linalg.modularitymatrix)": [[1287, "networkx.linalg.modularitymatrix.directed_modularity_matrix"]], "modularity_matrix() (in module networkx.linalg.modularitymatrix)": [[1288, "networkx.linalg.modularitymatrix.modularity_matrix"]], "adjacency_spectrum() (in module networkx.linalg.spectrum)": [[1289, "networkx.linalg.spectrum.adjacency_spectrum"]], "bethe_hessian_spectrum() (in module networkx.linalg.spectrum)": [[1290, "networkx.linalg.spectrum.bethe_hessian_spectrum"]], "laplacian_spectrum() (in module networkx.linalg.spectrum)": [[1291, "networkx.linalg.spectrum.laplacian_spectrum"]], "modularity_spectrum() (in module networkx.linalg.spectrum)": [[1292, "networkx.linalg.spectrum.modularity_spectrum"]], "normalized_laplacian_spectrum() (in module networkx.linalg.spectrum)": [[1293, "networkx.linalg.spectrum.normalized_laplacian_spectrum"]], "convert_node_labels_to_integers() (in module networkx.relabel)": [[1294, "networkx.relabel.convert_node_labels_to_integers"]], "relabel_nodes() (in module networkx.relabel)": [[1295, "networkx.relabel.relabel_nodes"]], "__init__() (argmap method)": [[1296, "networkx.utils.decorators.argmap.__init__"]], "argmap (class in networkx.utils.decorators)": [[1296, "networkx.utils.decorators.argmap"]], "nodes_or_number() (in module networkx.utils.decorators)": [[1297, "networkx.utils.decorators.nodes_or_number"]], "not_implemented_for() (in module networkx.utils.decorators)": [[1298, "networkx.utils.decorators.not_implemented_for"]], "np_random_state() (in module networkx.utils.decorators)": [[1299, "networkx.utils.decorators.np_random_state"]], "open_file() (in module networkx.utils.decorators)": [[1300, "networkx.utils.decorators.open_file"]], "py_random_state() (in module networkx.utils.decorators)": [[1301, "networkx.utils.decorators.py_random_state"]], "mappedqueue (class in networkx.utils.mapped_queue)": [[1302, "networkx.utils.mapped_queue.MappedQueue"]], "__init__() (mappedqueue method)": [[1302, "networkx.utils.mapped_queue.MappedQueue.__init__"]], "arbitrary_element() (in module networkx.utils.misc)": [[1303, "networkx.utils.misc.arbitrary_element"]], "create_py_random_state() (in module networkx.utils.misc)": [[1304, "networkx.utils.misc.create_py_random_state"]], "create_random_state() (in module networkx.utils.misc)": [[1305, "networkx.utils.misc.create_random_state"]], "dict_to_numpy_array() (in module networkx.utils.misc)": [[1306, "networkx.utils.misc.dict_to_numpy_array"]], "edges_equal() (in module networkx.utils.misc)": [[1307, "networkx.utils.misc.edges_equal"]], "flatten() (in module networkx.utils.misc)": [[1308, "networkx.utils.misc.flatten"]], "graphs_equal() (in module networkx.utils.misc)": [[1309, "networkx.utils.misc.graphs_equal"]], "groups() (in module networkx.utils.misc)": [[1310, "networkx.utils.misc.groups"]], "make_list_of_ints() (in module networkx.utils.misc)": [[1311, "networkx.utils.misc.make_list_of_ints"]], "nodes_equal() (in module networkx.utils.misc)": [[1312, "networkx.utils.misc.nodes_equal"]], "pairwise() (in module networkx.utils.misc)": [[1313, "networkx.utils.misc.pairwise"]], "cumulative_distribution() (in module networkx.utils.random_sequence)": [[1314, "networkx.utils.random_sequence.cumulative_distribution"]], "discrete_sequence() (in module networkx.utils.random_sequence)": [[1315, "networkx.utils.random_sequence.discrete_sequence"]], "powerlaw_sequence() (in module networkx.utils.random_sequence)": [[1316, "networkx.utils.random_sequence.powerlaw_sequence"]], "random_weighted_sample() (in module networkx.utils.random_sequence)": [[1317, "networkx.utils.random_sequence.random_weighted_sample"]], "weighted_choice() (in module networkx.utils.random_sequence)": [[1318, "networkx.utils.random_sequence.weighted_choice"]], "zipf_rv() (in module networkx.utils.random_sequence)": [[1319, "networkx.utils.random_sequence.zipf_rv"]], "cuthill_mckee_ordering() (in module networkx.utils.rcm)": [[1320, "networkx.utils.rcm.cuthill_mckee_ordering"]], "reverse_cuthill_mckee_ordering() (in module networkx.utils.rcm)": [[1321, "networkx.utils.rcm.reverse_cuthill_mckee_ordering"]], "union() (unionfind method)": [[1322, "networkx.utils.union_find.UnionFind.union"]], "networkx.generators.atlas": [[1323, "module-networkx.generators.atlas"]], "networkx.generators.classic": [[1323, "module-networkx.generators.classic"]], "networkx.generators.cographs": [[1323, "module-networkx.generators.cographs"]], "networkx.generators.community": [[1323, "module-networkx.generators.community"]], "networkx.generators.degree_seq": [[1323, "module-networkx.generators.degree_seq"]], "networkx.generators.directed": [[1323, "module-networkx.generators.directed"]], "networkx.generators.duplication": [[1323, "module-networkx.generators.duplication"]], "networkx.generators.ego": [[1323, "module-networkx.generators.ego"]], "networkx.generators.expanders": [[1323, "module-networkx.generators.expanders"]], "networkx.generators.geometric": [[1323, "module-networkx.generators.geometric"]], "networkx.generators.harary_graph": [[1323, "module-networkx.generators.harary_graph"]], "networkx.generators.internet_as_graphs": [[1323, "module-networkx.generators.internet_as_graphs"]], "networkx.generators.intersection": [[1323, "module-networkx.generators.intersection"]], "networkx.generators.interval_graph": [[1323, "module-networkx.generators.interval_graph"]], "networkx.generators.joint_degree_seq": [[1323, "module-networkx.generators.joint_degree_seq"]], "networkx.generators.lattice": [[1323, "module-networkx.generators.lattice"]], "networkx.generators.line": [[1323, "module-networkx.generators.line"]], "networkx.generators.mycielski": [[1323, "module-networkx.generators.mycielski"]], "networkx.generators.nonisomorphic_trees": [[1323, "module-networkx.generators.nonisomorphic_trees"]], "networkx.generators.random_clustered": [[1323, "module-networkx.generators.random_clustered"]], "networkx.generators.random_graphs": [[1323, "module-networkx.generators.random_graphs"]], "networkx.generators.small": [[1323, "module-networkx.generators.small"]], "networkx.generators.social": [[1323, "module-networkx.generators.social"]], "networkx.generators.spectral_graph_forge": [[1323, "module-networkx.generators.spectral_graph_forge"]], "networkx.generators.stochastic": [[1323, "module-networkx.generators.stochastic"]], "networkx.generators.sudoku": [[1323, "module-networkx.generators.sudoku"]], "networkx.generators.trees": [[1323, "module-networkx.generators.trees"]], "networkx.generators.triads": [[1323, "module-networkx.generators.triads"]], "dictionary": [[1324, "term-dictionary"]], "ebunch": [[1324, "term-ebunch"]], "edge": [[1324, "term-edge"]], "edge attribute": [[1324, "term-edge-attribute"]], "nbunch": [[1324, "term-nbunch"]], "node": [[1324, "term-node"]], "node attribute": [[1324, "term-node-attribute"]], "networkx.linalg.algebraicconnectivity": [[1327, "module-networkx.linalg.algebraicconnectivity"]], "networkx.linalg.attrmatrix": [[1327, "module-networkx.linalg.attrmatrix"]], "networkx.linalg.bethehessianmatrix": [[1327, "module-networkx.linalg.bethehessianmatrix"]], "networkx.linalg.graphmatrix": [[1327, "module-networkx.linalg.graphmatrix"]], "networkx.linalg.laplacianmatrix": [[1327, "module-networkx.linalg.laplacianmatrix"]], "networkx.linalg.modularitymatrix": [[1327, "module-networkx.linalg.modularitymatrix"]], "networkx.linalg.spectrum": [[1327, "module-networkx.linalg.spectrum"]], "networkx.readwrite.adjlist": [[1329, "module-networkx.readwrite.adjlist"]], "networkx.readwrite.edgelist": [[1330, "module-networkx.readwrite.edgelist"]], "generate_adjlist() (in module networkx.readwrite.adjlist)": [[1331, "networkx.readwrite.adjlist.generate_adjlist"]], "parse_adjlist() (in module networkx.readwrite.adjlist)": [[1332, "networkx.readwrite.adjlist.parse_adjlist"]], "read_adjlist() (in module networkx.readwrite.adjlist)": [[1333, "networkx.readwrite.adjlist.read_adjlist"]], "write_adjlist() (in module networkx.readwrite.adjlist)": [[1334, "networkx.readwrite.adjlist.write_adjlist"]], "generate_edgelist() (in module networkx.readwrite.edgelist)": [[1335, "networkx.readwrite.edgelist.generate_edgelist"]], "parse_edgelist() (in module networkx.readwrite.edgelist)": [[1336, "networkx.readwrite.edgelist.parse_edgelist"]], "read_edgelist() (in module networkx.readwrite.edgelist)": [[1337, "networkx.readwrite.edgelist.read_edgelist"]], "read_weighted_edgelist() (in module networkx.readwrite.edgelist)": [[1338, "networkx.readwrite.edgelist.read_weighted_edgelist"]], "write_edgelist() (in module networkx.readwrite.edgelist)": [[1339, "networkx.readwrite.edgelist.write_edgelist"]], "write_weighted_edgelist() (in module networkx.readwrite.edgelist)": [[1340, "networkx.readwrite.edgelist.write_weighted_edgelist"]], "generate_gexf() (in module networkx.readwrite.gexf)": [[1341, "networkx.readwrite.gexf.generate_gexf"]], "read_gexf() (in module networkx.readwrite.gexf)": [[1342, "networkx.readwrite.gexf.read_gexf"]], "relabel_gexf_graph() (in module networkx.readwrite.gexf)": [[1343, "networkx.readwrite.gexf.relabel_gexf_graph"]], "write_gexf() (in module networkx.readwrite.gexf)": [[1344, "networkx.readwrite.gexf.write_gexf"]], "generate_gml() (in module networkx.readwrite.gml)": [[1345, "networkx.readwrite.gml.generate_gml"]], "literal_destringizer() (in module networkx.readwrite.gml)": [[1346, "networkx.readwrite.gml.literal_destringizer"]], "literal_stringizer() (in module networkx.readwrite.gml)": [[1347, "networkx.readwrite.gml.literal_stringizer"]], "parse_gml() (in module networkx.readwrite.gml)": [[1348, "networkx.readwrite.gml.parse_gml"]], "read_gml() (in module networkx.readwrite.gml)": [[1349, "networkx.readwrite.gml.read_gml"]], "write_gml() (in module networkx.readwrite.gml)": [[1350, "networkx.readwrite.gml.write_gml"]], "from_graph6_bytes() (in module networkx.readwrite.graph6)": [[1351, "networkx.readwrite.graph6.from_graph6_bytes"]], "read_graph6() (in module networkx.readwrite.graph6)": [[1352, "networkx.readwrite.graph6.read_graph6"]], "to_graph6_bytes() (in module networkx.readwrite.graph6)": [[1353, "networkx.readwrite.graph6.to_graph6_bytes"]], "write_graph6() (in module networkx.readwrite.graph6)": [[1354, "networkx.readwrite.graph6.write_graph6"]], "generate_graphml() (in module networkx.readwrite.graphml)": [[1355, "networkx.readwrite.graphml.generate_graphml"]], "parse_graphml() (in module networkx.readwrite.graphml)": [[1356, "networkx.readwrite.graphml.parse_graphml"]], "read_graphml() (in module networkx.readwrite.graphml)": [[1357, "networkx.readwrite.graphml.read_graphml"]], "write_graphml() (in module networkx.readwrite.graphml)": [[1358, "networkx.readwrite.graphml.write_graphml"]], "adjacency_data() (in module networkx.readwrite.json_graph)": [[1359, "networkx.readwrite.json_graph.adjacency_data"]], "adjacency_graph() (in module networkx.readwrite.json_graph)": [[1360, "networkx.readwrite.json_graph.adjacency_graph"]], "cytoscape_data() (in module networkx.readwrite.json_graph)": [[1361, "networkx.readwrite.json_graph.cytoscape_data"]], "cytoscape_graph() (in module networkx.readwrite.json_graph)": [[1362, "networkx.readwrite.json_graph.cytoscape_graph"]], "node_link_data() (in module networkx.readwrite.json_graph)": [[1363, "networkx.readwrite.json_graph.node_link_data"]], "node_link_graph() (in module networkx.readwrite.json_graph)": [[1364, "networkx.readwrite.json_graph.node_link_graph"]], "tree_data() (in module networkx.readwrite.json_graph)": [[1365, "networkx.readwrite.json_graph.tree_data"]], "tree_graph() (in module networkx.readwrite.json_graph)": [[1366, "networkx.readwrite.json_graph.tree_graph"]], "parse_leda() (in module networkx.readwrite.leda)": [[1367, "networkx.readwrite.leda.parse_leda"]], "read_leda() (in module networkx.readwrite.leda)": [[1368, "networkx.readwrite.leda.read_leda"]], "generate_multiline_adjlist() (in module networkx.readwrite.multiline_adjlist)": [[1369, "networkx.readwrite.multiline_adjlist.generate_multiline_adjlist"]], "parse_multiline_adjlist() (in module networkx.readwrite.multiline_adjlist)": [[1370, "networkx.readwrite.multiline_adjlist.parse_multiline_adjlist"]], "read_multiline_adjlist() (in module networkx.readwrite.multiline_adjlist)": [[1371, "networkx.readwrite.multiline_adjlist.read_multiline_adjlist"]], "write_multiline_adjlist() (in module networkx.readwrite.multiline_adjlist)": [[1372, "networkx.readwrite.multiline_adjlist.write_multiline_adjlist"]], "generate_pajek() (in module networkx.readwrite.pajek)": [[1373, "networkx.readwrite.pajek.generate_pajek"]], "parse_pajek() (in module networkx.readwrite.pajek)": [[1374, "networkx.readwrite.pajek.parse_pajek"]], "read_pajek() (in module networkx.readwrite.pajek)": [[1375, "networkx.readwrite.pajek.read_pajek"]], "write_pajek() (in module networkx.readwrite.pajek)": [[1376, "networkx.readwrite.pajek.write_pajek"]], "from_sparse6_bytes() (in module networkx.readwrite.sparse6)": [[1377, "networkx.readwrite.sparse6.from_sparse6_bytes"]], "read_sparse6() (in module networkx.readwrite.sparse6)": [[1378, "networkx.readwrite.sparse6.read_sparse6"]], "to_sparse6_bytes() (in module networkx.readwrite.sparse6)": [[1379, "networkx.readwrite.sparse6.to_sparse6_bytes"]], "write_sparse6() (in module networkx.readwrite.sparse6)": [[1380, "networkx.readwrite.sparse6.write_sparse6"]], "networkx.readwrite.gexf": [[1381, "module-networkx.readwrite.gexf"]], "networkx.readwrite.gml": [[1382, "module-networkx.readwrite.gml"]], "networkx.readwrite.graphml": [[1383, "module-networkx.readwrite.graphml"]], "networkx.readwrite.json_graph": [[1385, "module-networkx.readwrite.json_graph"]], "networkx.readwrite.leda": [[1386, "module-networkx.readwrite.leda"]], "networkx.readwrite.multiline_adjlist": [[1388, "module-networkx.readwrite.multiline_adjlist"]], "networkx.readwrite.pajek": [[1389, "module-networkx.readwrite.pajek"]], "networkx.readwrite.graph6": [[1390, "module-networkx.readwrite.graph6"]], "networkx.readwrite.sparse6": [[1390, "module-networkx.readwrite.sparse6"]], "networkx.relabel": [[1391, "module-networkx.relabel"]], "networkx.utils": [[1392, "module-networkx.utils"]], "networkx.utils.decorators": [[1392, "module-networkx.utils.decorators"]], "networkx.utils.mapped_queue": [[1392, "module-networkx.utils.mapped_queue"]], "networkx.utils.misc": [[1392, "module-networkx.utils.misc"]], "networkx.utils.random_sequence": [[1392, "module-networkx.utils.random_sequence"]], "networkx.utils.rcm": [[1392, "module-networkx.utils.rcm"]], "networkx.utils.union_find": [[1392, "module-networkx.utils.union_find"]]}})
\ No newline at end of file diff --git a/tutorial-34.pdf b/tutorial-34.pdf Binary files differindex f9991169..3592bbe7 100644 --- a/tutorial-34.pdf +++ b/tutorial-34.pdf diff --git a/tutorial-35.hires.png b/tutorial-35.hires.png Binary files differindex 95fa708b..51b54532 100644 --- a/tutorial-35.hires.png +++ b/tutorial-35.hires.png diff --git a/tutorial-35.pdf b/tutorial-35.pdf Binary files differindex dac636b8..e3fec9e7 100644 --- a/tutorial-35.pdf +++ b/tutorial-35.pdf diff --git a/tutorial-35.png b/tutorial-35.png Binary files differindex d7651092..5ae1b78d 100644 --- a/tutorial-35.png +++ b/tutorial-35.png diff --git a/tutorial-36.pdf b/tutorial-36.pdf Binary files differindex acc3626a..4bb35b7f 100644 --- a/tutorial-36.pdf +++ b/tutorial-36.pdf diff --git a/tutorial.html b/tutorial.html index a3413666..24cc95bf 100644 --- a/tutorial.html +++ b/tutorial.html @@ -1239,7 +1239,7 @@ the graph in dot format for further processing.</p> <p class="copyright"> - © Copyright 2004-2022, NetworkX Developers.<br> + © Copyright 2004-2023, NetworkX Developers.<br> </p> diff --git a/tutorial.ipynb b/tutorial.ipynb index d23d7651..a1eef26c 100644 --- a/tutorial.ipynb +++ b/tutorial.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "90937821", + "id": "09acc732", "metadata": {}, "source": [ "## Tutorial\n", @@ -17,7 +17,7 @@ { "cell_type": "code", "execution_count": null, - "id": "59049f51", + "id": "36cfb0a2", "metadata": {}, "outputs": [], "source": [ @@ -27,7 +27,7 @@ }, { "cell_type": "markdown", - "id": "538cf811", + "id": "c63b6961", "metadata": {}, "source": [ "By definition, a `Graph` is a collection of nodes (vertices) along with\n", @@ -47,7 +47,7 @@ { "cell_type": "code", "execution_count": null, - "id": "f6698902", + "id": "e5028e1f", "metadata": {}, "outputs": [], "source": [ @@ -56,7 +56,7 @@ }, { "cell_type": "markdown", - "id": "5de3e8ef", + "id": "aa375677", "metadata": {}, "source": [ "or add nodes from any [iterable](https://docs.python.org/3/glossary.html#term-iterable) container, such as a list" @@ -65,7 +65,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6405beaa", + "id": "7e1e53f0", "metadata": {}, "outputs": [], "source": [ @@ -74,7 +74,7 @@ }, { "cell_type": "markdown", - "id": "c8f17656", + "id": "943c9b7e", "metadata": {}, "source": [ "You can also add nodes along with node\n", @@ -96,7 +96,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0ada7cc5", + "id": "268f654d", "metadata": {}, "outputs": [], "source": [ @@ -106,7 +106,7 @@ }, { "cell_type": "markdown", - "id": "8ca64757", + "id": "d7b8f39b", "metadata": {}, "source": [ "`G` now contains the nodes of `H` as nodes of `G`.\n", @@ -116,7 +116,7 @@ { "cell_type": "code", "execution_count": null, - "id": "88575925", + "id": "6f7a04cb", "metadata": {}, "outputs": [], "source": [ @@ -125,7 +125,7 @@ }, { "cell_type": "markdown", - "id": "b37b79c1", + "id": "6f7d863a", "metadata": {}, "source": [ "The graph `G` now contains `H` as a node. This flexibility is very powerful as\n", @@ -143,7 +143,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9d5a38ba", + "id": "e5deadb8", "metadata": {}, "outputs": [], "source": [ @@ -154,7 +154,7 @@ }, { "cell_type": "markdown", - "id": "08482fe6", + "id": "873b8364", "metadata": {}, "source": [ "by adding a list of edges," @@ -163,7 +163,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d66dcae5", + "id": "81f1e49b", "metadata": {}, "outputs": [], "source": [ @@ -172,7 +172,7 @@ }, { "cell_type": "markdown", - "id": "bddd430d", + "id": "e451cd9a", "metadata": {}, "source": [ "or by adding any ebunch of edges. An *ebunch* is any iterable\n", @@ -185,7 +185,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7e713e69", + "id": "466844ea", "metadata": {}, "outputs": [], "source": [ @@ -194,7 +194,7 @@ }, { "cell_type": "markdown", - "id": "b0fd3d0c", + "id": "9fa30d52", "metadata": {}, "source": [ "There are no complaints when adding existing nodes or edges. For example,\n", @@ -204,7 +204,7 @@ { "cell_type": "code", "execution_count": null, - "id": "cf723a75", + "id": "fe5d7a63", "metadata": {}, "outputs": [], "source": [ @@ -213,7 +213,7 @@ }, { "cell_type": "markdown", - "id": "c1cba503", + "id": "64214131", "metadata": {}, "source": [ "we add new nodes/edges and NetworkX quietly ignores any that are\n", @@ -223,7 +223,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7ef878a4", + "id": "b14b30c4", "metadata": {}, "outputs": [], "source": [ @@ -237,7 +237,7 @@ }, { "cell_type": "markdown", - "id": "c5c7da7b", + "id": "2e2f7f9d", "metadata": {}, "source": [ "At this stage the graph `G` consists of 8 nodes and 3 edges, as can be seen by:" @@ -246,7 +246,7 @@ { "cell_type": "code", "execution_count": null, - "id": "d4197f8c", + "id": "d0d78b40", "metadata": {}, "outputs": [], "source": [ @@ -257,7 +257,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e428178e", + "id": "0a1b3f69", "metadata": {}, "outputs": [], "source": [ @@ -272,7 +272,7 @@ }, { "cell_type": "markdown", - "id": "a7334ec7", + "id": "26fb3c24", "metadata": {}, "source": [ "# Examining elements of a graph\n", @@ -292,7 +292,7 @@ { "cell_type": "code", "execution_count": null, - "id": "6ad604cf", + "id": "60073a2a", "metadata": {}, "outputs": [], "source": [ @@ -304,7 +304,7 @@ }, { "cell_type": "markdown", - "id": "253640bb", + "id": "568d047d", "metadata": {}, "source": [ "One can specify to report the edges and degree from a subset of all nodes\n", @@ -316,7 +316,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9f801d29", + "id": "e139feda", "metadata": {}, "outputs": [], "source": [ @@ -326,7 +326,7 @@ }, { "cell_type": "markdown", - "id": "809a5504", + "id": "8c580f0e", "metadata": {}, "source": [ "# Removing elements from a graph\n", @@ -343,7 +343,7 @@ { "cell_type": "code", "execution_count": null, - "id": "29738670", + "id": "60a057e7", "metadata": {}, "outputs": [], "source": [ @@ -355,7 +355,7 @@ }, { "cell_type": "markdown", - "id": "0f10edf8", + "id": "5d2f0a3e", "metadata": {}, "source": [ "# Using the graph constructors\n", @@ -370,7 +370,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5058d816", + "id": "0dd2e93d", "metadata": {}, "outputs": [], "source": [ @@ -387,7 +387,7 @@ }, { "cell_type": "markdown", - "id": "78b07e07", + "id": "efd1be5f", "metadata": {}, "source": [ "# What to use as nodes and edges\n", @@ -416,7 +416,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9fd5b954", + "id": "2cca9ec0", "metadata": {}, "outputs": [], "source": [ @@ -428,7 +428,7 @@ }, { "cell_type": "markdown", - "id": "6e5cdbe0", + "id": "af094850", "metadata": {}, "source": [ "You can get/set the attributes of an edge using subscript notation\n", @@ -438,7 +438,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a2fae2a3", + "id": "576d0b8e", "metadata": {}, "outputs": [], "source": [ @@ -450,7 +450,7 @@ }, { "cell_type": "markdown", - "id": "929a414f", + "id": "a47c1fc9", "metadata": {}, "source": [ "Fast examination of all (node, adjacency) pairs is achieved using\n", @@ -461,7 +461,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4eb00c76", + "id": "6071604a", "metadata": {}, "outputs": [], "source": [ @@ -475,7 +475,7 @@ }, { "cell_type": "markdown", - "id": "40710665", + "id": "f9806f8c", "metadata": {}, "source": [ "Convenient access to all edges is achieved with the edges property." @@ -484,7 +484,7 @@ { "cell_type": "code", "execution_count": null, - "id": "3d18acf6", + "id": "5545ab2e", "metadata": {}, "outputs": [], "source": [ @@ -495,7 +495,7 @@ }, { "cell_type": "markdown", - "id": "428e300d", + "id": "e36d0fa6", "metadata": {}, "source": [ "# Adding attributes to graphs, nodes, and edges\n", @@ -517,7 +517,7 @@ { "cell_type": "code", "execution_count": null, - "id": "13ebf06e", + "id": "02147c02", "metadata": {}, "outputs": [], "source": [ @@ -527,7 +527,7 @@ }, { "cell_type": "markdown", - "id": "4c50340d", + "id": "370316f1", "metadata": {}, "source": [ "Or you can modify attributes later" @@ -536,7 +536,7 @@ { "cell_type": "code", "execution_count": null, - "id": "9ba4b2dc", + "id": "a166455b", "metadata": {}, "outputs": [], "source": [ @@ -546,7 +546,7 @@ }, { "cell_type": "markdown", - "id": "8c966e8e", + "id": "d1aec45b", "metadata": {}, "source": [ "# Node attributes\n", @@ -557,7 +557,7 @@ { "cell_type": "code", "execution_count": null, - "id": "81d527a6", + "id": "6559df75", "metadata": {}, "outputs": [], "source": [ @@ -570,7 +570,7 @@ }, { "cell_type": "markdown", - "id": "bab5d9b5", + "id": "8414f740", "metadata": {}, "source": [ "Note that adding a node to `G.nodes` does not add it to the graph, use\n", @@ -585,7 +585,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7dff455a", + "id": "66ad40c7", "metadata": {}, "outputs": [], "source": [ @@ -598,7 +598,7 @@ }, { "cell_type": "markdown", - "id": "0e40282f", + "id": "86b86661", "metadata": {}, "source": [ "The special attribute `weight` should be numeric as it is used by\n", @@ -619,7 +619,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1ce9ad47", + "id": "510da4e2", "metadata": {}, "outputs": [], "source": [ @@ -633,7 +633,7 @@ }, { "cell_type": "markdown", - "id": "5425c7f1", + "id": "eb3106f6", "metadata": {}, "source": [ "Some algorithms work only for directed graphs and others are not well\n", @@ -646,7 +646,7 @@ { "cell_type": "code", "execution_count": null, - "id": "00e70ab7", + "id": "4ce14fcf", "metadata": {}, "outputs": [], "source": [ @@ -655,7 +655,7 @@ }, { "cell_type": "markdown", - "id": "0e62e4f9", + "id": "1c4cac99", "metadata": {}, "source": [ "# Multigraphs\n", @@ -675,7 +675,7 @@ { "cell_type": "code", "execution_count": null, - "id": "8cdebcee", + "id": "ecc058cb", "metadata": {}, "outputs": [], "source": [ @@ -693,7 +693,7 @@ }, { "cell_type": "markdown", - "id": "83d8c968", + "id": "0d509efb", "metadata": {}, "source": [ "# Graph generators and graph operations\n", @@ -713,7 +713,7 @@ { "cell_type": "code", "execution_count": null, - "id": "0854d6d5", + "id": "36872fe5", "metadata": {}, "outputs": [], "source": [ @@ -725,7 +725,7 @@ }, { "cell_type": "markdown", - "id": "7e19840b", + "id": "f8aa2bc4", "metadata": {}, "source": [ "# 4. Using a stochastic graph generator, e.g,\n", @@ -736,7 +736,7 @@ { "cell_type": "code", "execution_count": null, - "id": "337abf3c", + "id": "018c814b", "metadata": {}, "outputs": [], "source": [ @@ -748,7 +748,7 @@ }, { "cell_type": "markdown", - "id": "b5bef502", + "id": "1f2ee001", "metadata": {}, "source": [ "# 5. Reading a graph stored in a file using common graph formats\n", @@ -760,7 +760,7 @@ { "cell_type": "code", "execution_count": null, - "id": "75cdd2c4", + "id": "0958110d", "metadata": {}, "outputs": [], "source": [ @@ -770,7 +770,7 @@ }, { "cell_type": "markdown", - "id": "8ba69968", + "id": "a3bfafb7", "metadata": {}, "source": [ "For details on graph formats see Reading and writing graphs\n", @@ -785,7 +785,7 @@ { "cell_type": "code", "execution_count": null, - "id": "42b38c47", + "id": "ff811ef3", "metadata": {}, "outputs": [], "source": [ @@ -799,7 +799,7 @@ }, { "cell_type": "markdown", - "id": "d731579b", + "id": "51824ba9", "metadata": {}, "source": [ "Some functions with large output iterate over (node, value) 2-tuples.\n", @@ -809,7 +809,7 @@ { "cell_type": "code", "execution_count": null, - "id": "ce458635", + "id": "1df52a7a", "metadata": {}, "outputs": [], "source": [ @@ -819,7 +819,7 @@ }, { "cell_type": "markdown", - "id": "020161fc", + "id": "1b996922", "metadata": {}, "source": [ "See Algorithms for details on graph algorithms\n", @@ -838,7 +838,7 @@ { "cell_type": "code", "execution_count": null, - "id": "1db0fd84", + "id": "c22301f3", "metadata": {}, "outputs": [], "source": [ @@ -847,7 +847,7 @@ }, { "cell_type": "markdown", - "id": "13602902", + "id": "28bb8512", "metadata": {}, "source": [ "To test if the import of `nx_pylab` was successful draw `G`\n", @@ -857,7 +857,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5a6bd124", + "id": "c9a9ea9b", "metadata": {}, "outputs": [], "source": [ @@ -870,7 +870,7 @@ }, { "cell_type": "markdown", - "id": "4b0563c7", + "id": "410e7b3d", "metadata": {}, "source": [ "when drawing to an interactive display. Note that you may need to issue a\n", @@ -880,7 +880,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a102647c", + "id": "62b634c9", "metadata": {}, "outputs": [], "source": [ @@ -889,7 +889,7 @@ }, { "cell_type": "markdown", - "id": "d9c5131e", + "id": "d67a317b", "metadata": {}, "source": [ "command if you are not using matplotlib in interactive mode." @@ -898,7 +898,7 @@ { "cell_type": "code", "execution_count": null, - "id": "26bd2caf", + "id": "29d6266e", "metadata": {}, "outputs": [], "source": [ @@ -919,7 +919,7 @@ }, { "cell_type": "markdown", - "id": "af3fc4c6", + "id": "0d2b3db8", "metadata": {}, "source": [ "You can find additional options via `draw_networkx()` and\n", @@ -930,7 +930,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a97da429", + "id": "0dc65281", "metadata": {}, "outputs": [], "source": [ @@ -941,7 +941,7 @@ }, { "cell_type": "markdown", - "id": "67ffbe4d", + "id": "7bfd3c65", "metadata": {}, "source": [ "To save drawings to a file, use, for example" @@ -950,7 +950,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4091ed0e", + "id": "251b1df9", "metadata": {}, "outputs": [], "source": [ @@ -960,7 +960,7 @@ }, { "cell_type": "markdown", - "id": "d33f4f6d", + "id": "22fa85d4", "metadata": {}, "source": [ "This function writes to the file `path.png` in the local directory. If Graphviz and\n", @@ -973,7 +973,7 @@ { "cell_type": "code", "execution_count": null, - "id": "83db308c", + "id": "c92c0580", "metadata": {}, "outputs": [], "source": [ @@ -985,7 +985,7 @@ }, { "cell_type": "markdown", - "id": "020647dc", + "id": "98f275f7", "metadata": {}, "source": [ "See Drawing for additional details." diff --git a/tutorial_full.ipynb b/tutorial_full.ipynb index fca1e3c2..c5a4cece 100644 --- a/tutorial_full.ipynb +++ b/tutorial_full.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "90937821", + "id": "09acc732", "metadata": {}, "source": [ "## Tutorial\n", @@ -17,13 +17,13 @@ { "cell_type": "code", "execution_count": 1, - "id": "59049f51", + "id": "36cfb0a2", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:47.820385Z", - "iopub.status.busy": "2022-12-27T10:11:47.820143Z", - "iopub.status.idle": "2022-12-27T10:11:47.893309Z", - "shell.execute_reply": "2022-12-27T10:11:47.892670Z" + "iopub.execute_input": "2023-01-02T13:06:44.172035Z", + "iopub.status.busy": "2023-01-02T13:06:44.171100Z", + "iopub.status.idle": "2023-01-02T13:06:44.266446Z", + "shell.execute_reply": "2023-01-02T13:06:44.265507Z" } }, "outputs": [], @@ -34,7 +34,7 @@ }, { "cell_type": "markdown", - "id": "538cf811", + "id": "c63b6961", "metadata": {}, "source": [ "By definition, a `Graph` is a collection of nodes (vertices) along with\n", @@ -54,13 +54,13 @@ { "cell_type": "code", "execution_count": 2, - "id": "f6698902", + "id": "e5028e1f", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:47.896732Z", - "iopub.status.busy": "2022-12-27T10:11:47.896508Z", - "iopub.status.idle": "2022-12-27T10:11:47.899552Z", - "shell.execute_reply": "2022-12-27T10:11:47.898903Z" + "iopub.execute_input": "2023-01-02T13:06:44.270855Z", + "iopub.status.busy": "2023-01-02T13:06:44.270597Z", + "iopub.status.idle": "2023-01-02T13:06:44.274699Z", + "shell.execute_reply": "2023-01-02T13:06:44.273713Z" } }, "outputs": [], @@ -70,7 +70,7 @@ }, { "cell_type": "markdown", - "id": "5de3e8ef", + "id": "aa375677", "metadata": {}, "source": [ "or add nodes from any [iterable](https://docs.python.org/3/glossary.html#term-iterable) container, such as a list" @@ -79,13 +79,13 @@ { "cell_type": "code", "execution_count": 3, - "id": "6405beaa", + "id": "7e1e53f0", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:47.902915Z", - "iopub.status.busy": "2022-12-27T10:11:47.902692Z", - "iopub.status.idle": "2022-12-27T10:11:47.907055Z", - "shell.execute_reply": "2022-12-27T10:11:47.906305Z" + "iopub.execute_input": "2023-01-02T13:06:44.278248Z", + "iopub.status.busy": "2023-01-02T13:06:44.277982Z", + "iopub.status.idle": "2023-01-02T13:06:44.281926Z", + "shell.execute_reply": "2023-01-02T13:06:44.280997Z" } }, "outputs": [], @@ -95,7 +95,7 @@ }, { "cell_type": "markdown", - "id": "c8f17656", + "id": "943c9b7e", "metadata": {}, "source": [ "You can also add nodes along with node\n", @@ -117,13 +117,13 @@ { "cell_type": "code", "execution_count": 4, - "id": "0ada7cc5", + "id": "268f654d", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:47.910073Z", - "iopub.status.busy": "2022-12-27T10:11:47.909537Z", - "iopub.status.idle": "2022-12-27T10:11:47.912880Z", - "shell.execute_reply": "2022-12-27T10:11:47.912388Z" + "iopub.execute_input": "2023-01-02T13:06:44.286108Z", + "iopub.status.busy": "2023-01-02T13:06:44.285796Z", + "iopub.status.idle": "2023-01-02T13:06:44.290267Z", + "shell.execute_reply": "2023-01-02T13:06:44.289319Z" } }, "outputs": [], @@ -134,7 +134,7 @@ }, { "cell_type": "markdown", - "id": "8ca64757", + "id": "d7b8f39b", "metadata": {}, "source": [ "`G` now contains the nodes of `H` as nodes of `G`.\n", @@ -144,13 +144,13 @@ { "cell_type": "code", "execution_count": 5, - "id": "88575925", + "id": "6f7a04cb", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:47.915782Z", - "iopub.status.busy": "2022-12-27T10:11:47.915443Z", - "iopub.status.idle": "2022-12-27T10:11:47.918410Z", - "shell.execute_reply": "2022-12-27T10:11:47.917785Z" + "iopub.execute_input": "2023-01-02T13:06:44.294167Z", + "iopub.status.busy": "2023-01-02T13:06:44.293896Z", + "iopub.status.idle": "2023-01-02T13:06:44.297829Z", + "shell.execute_reply": "2023-01-02T13:06:44.297000Z" } }, "outputs": [], @@ -160,7 +160,7 @@ }, { "cell_type": "markdown", - "id": "b37b79c1", + "id": "6f7d863a", "metadata": {}, "source": [ "The graph `G` now contains `H` as a node. This flexibility is very powerful as\n", @@ -178,13 +178,13 @@ { "cell_type": "code", "execution_count": 6, - "id": "9d5a38ba", + "id": "e5deadb8", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:47.921639Z", - "iopub.status.busy": "2022-12-27T10:11:47.921149Z", - "iopub.status.idle": "2022-12-27T10:11:47.924411Z", - "shell.execute_reply": "2022-12-27T10:11:47.923781Z" + "iopub.execute_input": "2023-01-02T13:06:44.302405Z", + "iopub.status.busy": "2023-01-02T13:06:44.302169Z", + "iopub.status.idle": "2023-01-02T13:06:44.306059Z", + "shell.execute_reply": "2023-01-02T13:06:44.305218Z" } }, "outputs": [], @@ -196,7 +196,7 @@ }, { "cell_type": "markdown", - "id": "08482fe6", + "id": "873b8364", "metadata": {}, "source": [ "by adding a list of edges," @@ -205,13 +205,13 @@ { "cell_type": "code", "execution_count": 7, - "id": "d66dcae5", + "id": "81f1e49b", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:47.927571Z", - "iopub.status.busy": "2022-12-27T10:11:47.927233Z", - "iopub.status.idle": "2022-12-27T10:11:47.930371Z", - "shell.execute_reply": "2022-12-27T10:11:47.929744Z" + "iopub.execute_input": "2023-01-02T13:06:44.310030Z", + "iopub.status.busy": "2023-01-02T13:06:44.309791Z", + "iopub.status.idle": "2023-01-02T13:06:44.313681Z", + "shell.execute_reply": "2023-01-02T13:06:44.312781Z" } }, "outputs": [], @@ -221,7 +221,7 @@ }, { "cell_type": "markdown", - "id": "bddd430d", + "id": "e451cd9a", "metadata": {}, "source": [ "or by adding any ebunch of edges. An *ebunch* is any iterable\n", @@ -234,13 +234,13 @@ { "cell_type": "code", "execution_count": 8, - "id": "7e713e69", + "id": "466844ea", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:47.933397Z", - "iopub.status.busy": "2022-12-27T10:11:47.932989Z", - "iopub.status.idle": "2022-12-27T10:11:47.935997Z", - "shell.execute_reply": "2022-12-27T10:11:47.935372Z" + "iopub.execute_input": "2023-01-02T13:06:44.318227Z", + "iopub.status.busy": "2023-01-02T13:06:44.317805Z", + "iopub.status.idle": "2023-01-02T13:06:44.322291Z", + "shell.execute_reply": "2023-01-02T13:06:44.321329Z" } }, "outputs": [], @@ -250,7 +250,7 @@ }, { "cell_type": "markdown", - "id": "b0fd3d0c", + "id": "9fa30d52", "metadata": {}, "source": [ "There are no complaints when adding existing nodes or edges. For example,\n", @@ -260,13 +260,13 @@ { "cell_type": "code", "execution_count": 9, - "id": "cf723a75", + "id": "fe5d7a63", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:47.938907Z", - "iopub.status.busy": "2022-12-27T10:11:47.938569Z", - "iopub.status.idle": "2022-12-27T10:11:47.941506Z", - "shell.execute_reply": "2022-12-27T10:11:47.940878Z" + "iopub.execute_input": "2023-01-02T13:06:44.326255Z", + "iopub.status.busy": "2023-01-02T13:06:44.326005Z", + "iopub.status.idle": "2023-01-02T13:06:44.329502Z", + "shell.execute_reply": "2023-01-02T13:06:44.328674Z" } }, "outputs": [], @@ -276,7 +276,7 @@ }, { "cell_type": "markdown", - "id": "c1cba503", + "id": "64214131", "metadata": {}, "source": [ "we add new nodes/edges and NetworkX quietly ignores any that are\n", @@ -286,13 +286,13 @@ { "cell_type": "code", "execution_count": 10, - "id": "7ef878a4", + "id": "b14b30c4", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:47.944530Z", - "iopub.status.busy": "2022-12-27T10:11:47.944191Z", - "iopub.status.idle": "2022-12-27T10:11:47.948098Z", - "shell.execute_reply": "2022-12-27T10:11:47.947471Z" + "iopub.execute_input": "2023-01-02T13:06:44.333425Z", + "iopub.status.busy": "2023-01-02T13:06:44.333182Z", + "iopub.status.idle": "2023-01-02T13:06:44.337843Z", + "shell.execute_reply": "2023-01-02T13:06:44.336974Z" } }, "outputs": [], @@ -307,7 +307,7 @@ }, { "cell_type": "markdown", - "id": "c5c7da7b", + "id": "2e2f7f9d", "metadata": {}, "source": [ "At this stage the graph `G` consists of 8 nodes and 3 edges, as can be seen by:" @@ -316,13 +316,13 @@ { "cell_type": "code", "execution_count": 11, - "id": "d4197f8c", + "id": "d0d78b40", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:47.951231Z", - "iopub.status.busy": "2022-12-27T10:11:47.950822Z", - "iopub.status.idle": "2022-12-27T10:11:47.957230Z", - "shell.execute_reply": "2022-12-27T10:11:47.956604Z" + "iopub.execute_input": "2023-01-02T13:06:44.341911Z", + "iopub.status.busy": "2023-01-02T13:06:44.341576Z", + "iopub.status.idle": "2023-01-02T13:06:44.350017Z", + "shell.execute_reply": "2023-01-02T13:06:44.349155Z" } }, "outputs": [ @@ -345,13 +345,13 @@ { "cell_type": "code", "execution_count": 12, - "id": "e428178e", + "id": "0a1b3f69", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:47.961521Z", - "iopub.status.busy": "2022-12-27T10:11:47.961183Z", - "iopub.status.idle": "2022-12-27T10:11:47.965476Z", - "shell.execute_reply": "2022-12-27T10:11:47.964871Z" + "iopub.execute_input": "2023-01-02T13:06:44.358042Z", + "iopub.status.busy": "2023-01-02T13:06:44.357706Z", + "iopub.status.idle": "2023-01-02T13:06:44.363630Z", + "shell.execute_reply": "2023-01-02T13:06:44.362379Z" } }, "outputs": [], @@ -367,7 +367,7 @@ }, { "cell_type": "markdown", - "id": "a7334ec7", + "id": "26fb3c24", "metadata": {}, "source": [ "# Examining elements of a graph\n", @@ -387,13 +387,13 @@ { "cell_type": "code", "execution_count": 13, - "id": "6ad604cf", + "id": "60073a2a", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:47.968541Z", - "iopub.status.busy": "2022-12-27T10:11:47.967950Z", - "iopub.status.idle": "2022-12-27T10:11:47.972703Z", - "shell.execute_reply": "2022-12-27T10:11:47.972053Z" + "iopub.execute_input": "2023-01-02T13:06:44.368341Z", + "iopub.status.busy": "2023-01-02T13:06:44.368082Z", + "iopub.status.idle": "2023-01-02T13:06:44.374612Z", + "shell.execute_reply": "2023-01-02T13:06:44.373752Z" } }, "outputs": [ @@ -417,7 +417,7 @@ }, { "cell_type": "markdown", - "id": "253640bb", + "id": "568d047d", "metadata": {}, "source": [ "One can specify to report the edges and degree from a subset of all nodes\n", @@ -429,13 +429,13 @@ { "cell_type": "code", "execution_count": 14, - "id": "9f801d29", + "id": "e139feda", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:47.976042Z", - "iopub.status.busy": "2022-12-27T10:11:47.975638Z", - "iopub.status.idle": "2022-12-27T10:11:47.979944Z", - "shell.execute_reply": "2022-12-27T10:11:47.979328Z" + "iopub.execute_input": "2023-01-02T13:06:44.379911Z", + "iopub.status.busy": "2023-01-02T13:06:44.379639Z", + "iopub.status.idle": "2023-01-02T13:06:44.385996Z", + "shell.execute_reply": "2023-01-02T13:06:44.385123Z" } }, "outputs": [ @@ -457,7 +457,7 @@ }, { "cell_type": "markdown", - "id": "809a5504", + "id": "8c580f0e", "metadata": {}, "source": [ "# Removing elements from a graph\n", @@ -474,13 +474,13 @@ { "cell_type": "code", "execution_count": 15, - "id": "29738670", + "id": "60a057e7", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:47.983715Z", - "iopub.status.busy": "2022-12-27T10:11:47.983210Z", - "iopub.status.idle": "2022-12-27T10:11:47.986550Z", - "shell.execute_reply": "2022-12-27T10:11:47.985913Z" + "iopub.execute_input": "2023-01-02T13:06:44.391322Z", + "iopub.status.busy": "2023-01-02T13:06:44.390961Z", + "iopub.status.idle": "2023-01-02T13:06:44.395330Z", + "shell.execute_reply": "2023-01-02T13:06:44.394450Z" } }, "outputs": [], @@ -493,7 +493,7 @@ }, { "cell_type": "markdown", - "id": "0f10edf8", + "id": "5d2f0a3e", "metadata": {}, "source": [ "# Using the graph constructors\n", @@ -508,13 +508,13 @@ { "cell_type": "code", "execution_count": 16, - "id": "5058d816", + "id": "0dd2e93d", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:47.989557Z", - "iopub.status.busy": "2022-12-27T10:11:47.989066Z", - "iopub.status.idle": "2022-12-27T10:11:48.249192Z", - "shell.execute_reply": "2022-12-27T10:11:48.248411Z" + "iopub.execute_input": "2023-01-02T13:06:44.399196Z", + "iopub.status.busy": "2023-01-02T13:06:44.398921Z", + "iopub.status.idle": "2023-01-02T13:06:44.713313Z", + "shell.execute_reply": "2023-01-02T13:06:44.712497Z" } }, "outputs": [ @@ -543,7 +543,7 @@ }, { "cell_type": "markdown", - "id": "78b07e07", + "id": "efd1be5f", "metadata": {}, "source": [ "# What to use as nodes and edges\n", @@ -572,13 +572,13 @@ { "cell_type": "code", "execution_count": 17, - "id": "9fd5b954", + "id": "2cca9ec0", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:48.252503Z", - "iopub.status.busy": "2022-12-27T10:11:48.252153Z", - "iopub.status.idle": "2022-12-27T10:11:48.258091Z", - "shell.execute_reply": "2022-12-27T10:11:48.257484Z" + "iopub.execute_input": "2023-01-02T13:06:44.717607Z", + "iopub.status.busy": "2023-01-02T13:06:44.717192Z", + "iopub.status.idle": "2023-01-02T13:06:44.723755Z", + "shell.execute_reply": "2023-01-02T13:06:44.722977Z" } }, "outputs": [ @@ -602,7 +602,7 @@ }, { "cell_type": "markdown", - "id": "6e5cdbe0", + "id": "af094850", "metadata": {}, "source": [ "You can get/set the attributes of an edge using subscript notation\n", @@ -612,13 +612,13 @@ { "cell_type": "code", "execution_count": 18, - "id": "a2fae2a3", + "id": "576d0b8e", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:48.261035Z", - "iopub.status.busy": "2022-12-27T10:11:48.260622Z", - "iopub.status.idle": "2022-12-27T10:11:48.265416Z", - "shell.execute_reply": "2022-12-27T10:11:48.264785Z" + "iopub.execute_input": "2023-01-02T13:06:44.728432Z", + "iopub.status.busy": "2023-01-02T13:06:44.728097Z", + "iopub.status.idle": "2023-01-02T13:06:44.733749Z", + "shell.execute_reply": "2023-01-02T13:06:44.732957Z" } }, "outputs": [ @@ -642,7 +642,7 @@ }, { "cell_type": "markdown", - "id": "929a414f", + "id": "a47c1fc9", "metadata": {}, "source": [ "Fast examination of all (node, adjacency) pairs is achieved using\n", @@ -653,13 +653,13 @@ { "cell_type": "code", "execution_count": 19, - "id": "4eb00c76", + "id": "6071604a", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:48.269074Z", - "iopub.status.busy": "2022-12-27T10:11:48.268660Z", - "iopub.status.idle": "2022-12-27T10:11:48.273531Z", - "shell.execute_reply": "2022-12-27T10:11:48.272886Z" + "iopub.execute_input": "2023-01-02T13:06:44.738677Z", + "iopub.status.busy": "2023-01-02T13:06:44.738397Z", + "iopub.status.idle": "2023-01-02T13:06:44.744231Z", + "shell.execute_reply": "2023-01-02T13:06:44.743467Z" } }, "outputs": [ @@ -685,7 +685,7 @@ }, { "cell_type": "markdown", - "id": "40710665", + "id": "f9806f8c", "metadata": {}, "source": [ "Convenient access to all edges is achieved with the edges property." @@ -694,13 +694,13 @@ { "cell_type": "code", "execution_count": 20, - "id": "3d18acf6", + "id": "5545ab2e", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:48.277120Z", - "iopub.status.busy": "2022-12-27T10:11:48.276900Z", - "iopub.status.idle": "2022-12-27T10:11:48.280647Z", - "shell.execute_reply": "2022-12-27T10:11:48.280132Z" + "iopub.execute_input": "2023-01-02T13:06:44.748148Z", + "iopub.status.busy": "2023-01-02T13:06:44.747467Z", + "iopub.status.idle": "2023-01-02T13:06:44.752426Z", + "shell.execute_reply": "2023-01-02T13:06:44.751519Z" } }, "outputs": [ @@ -721,7 +721,7 @@ }, { "cell_type": "markdown", - "id": "428e300d", + "id": "e36d0fa6", "metadata": {}, "source": [ "# Adding attributes to graphs, nodes, and edges\n", @@ -743,13 +743,13 @@ { "cell_type": "code", "execution_count": 21, - "id": "13ebf06e", + "id": "02147c02", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:48.283373Z", - "iopub.status.busy": "2022-12-27T10:11:48.282850Z", - "iopub.status.idle": "2022-12-27T10:11:48.289648Z", - "shell.execute_reply": "2022-12-27T10:11:48.288348Z" + "iopub.execute_input": "2023-01-02T13:06:44.758595Z", + "iopub.status.busy": "2023-01-02T13:06:44.758286Z", + "iopub.status.idle": "2023-01-02T13:06:44.763664Z", + "shell.execute_reply": "2023-01-02T13:06:44.762599Z" } }, "outputs": [ @@ -771,7 +771,7 @@ }, { "cell_type": "markdown", - "id": "4c50340d", + "id": "370316f1", "metadata": {}, "source": [ "Or you can modify attributes later" @@ -780,13 +780,13 @@ { "cell_type": "code", "execution_count": 22, - "id": "9ba4b2dc", + "id": "a166455b", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:48.292611Z", - "iopub.status.busy": "2022-12-27T10:11:48.292290Z", - "iopub.status.idle": "2022-12-27T10:11:48.297434Z", - "shell.execute_reply": "2022-12-27T10:11:48.296821Z" + "iopub.execute_input": "2023-01-02T13:06:44.768644Z", + "iopub.status.busy": "2023-01-02T13:06:44.767953Z", + "iopub.status.idle": "2023-01-02T13:06:44.773379Z", + "shell.execute_reply": "2023-01-02T13:06:44.772547Z" } }, "outputs": [ @@ -808,7 +808,7 @@ }, { "cell_type": "markdown", - "id": "8c966e8e", + "id": "d1aec45b", "metadata": {}, "source": [ "# Node attributes\n", @@ -819,13 +819,13 @@ { "cell_type": "code", "execution_count": 23, - "id": "81d527a6", + "id": "6559df75", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:48.300814Z", - "iopub.status.busy": "2022-12-27T10:11:48.300404Z", - "iopub.status.idle": "2022-12-27T10:11:48.305410Z", - "shell.execute_reply": "2022-12-27T10:11:48.304785Z" + "iopub.execute_input": "2023-01-02T13:06:44.778154Z", + "iopub.status.busy": "2023-01-02T13:06:44.777910Z", + "iopub.status.idle": "2023-01-02T13:06:44.784020Z", + "shell.execute_reply": "2023-01-02T13:06:44.782894Z" } }, "outputs": [ @@ -850,7 +850,7 @@ }, { "cell_type": "markdown", - "id": "bab5d9b5", + "id": "8414f740", "metadata": {}, "source": [ "Note that adding a node to `G.nodes` does not add it to the graph, use\n", @@ -865,13 +865,13 @@ { "cell_type": "code", "execution_count": 24, - "id": "7dff455a", + "id": "66ad40c7", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:48.309070Z", - "iopub.status.busy": "2022-12-27T10:11:48.308663Z", - "iopub.status.idle": "2022-12-27T10:11:48.312887Z", - "shell.execute_reply": "2022-12-27T10:11:48.312237Z" + "iopub.execute_input": "2023-01-02T13:06:44.789613Z", + "iopub.status.busy": "2023-01-02T13:06:44.789354Z", + "iopub.status.idle": "2023-01-02T13:06:44.794799Z", + "shell.execute_reply": "2023-01-02T13:06:44.793653Z" } }, "outputs": [], @@ -885,7 +885,7 @@ }, { "cell_type": "markdown", - "id": "0e40282f", + "id": "86b86661", "metadata": {}, "source": [ "The special attribute `weight` should be numeric as it is used by\n", @@ -906,13 +906,13 @@ { "cell_type": "code", "execution_count": 25, - "id": "1ce9ad47", + "id": "510da4e2", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:48.315706Z", - "iopub.status.busy": "2022-12-27T10:11:48.315488Z", - "iopub.status.idle": "2022-12-27T10:11:48.320816Z", - "shell.execute_reply": "2022-12-27T10:11:48.320205Z" + "iopub.execute_input": "2023-01-02T13:06:44.798865Z", + "iopub.status.busy": "2023-01-02T13:06:44.798561Z", + "iopub.status.idle": "2023-01-02T13:06:44.805046Z", + "shell.execute_reply": "2023-01-02T13:06:44.804215Z" } }, "outputs": [ @@ -938,7 +938,7 @@ }, { "cell_type": "markdown", - "id": "5425c7f1", + "id": "eb3106f6", "metadata": {}, "source": [ "Some algorithms work only for directed graphs and others are not well\n", @@ -951,13 +951,13 @@ { "cell_type": "code", "execution_count": 26, - "id": "00e70ab7", + "id": "4ce14fcf", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:48.323477Z", - "iopub.status.busy": "2022-12-27T10:11:48.323136Z", - "iopub.status.idle": "2022-12-27T10:11:48.326282Z", - "shell.execute_reply": "2022-12-27T10:11:48.325642Z" + "iopub.execute_input": "2023-01-02T13:06:44.810077Z", + "iopub.status.busy": "2023-01-02T13:06:44.809788Z", + "iopub.status.idle": "2023-01-02T13:06:44.813430Z", + "shell.execute_reply": "2023-01-02T13:06:44.812634Z" } }, "outputs": [], @@ -967,7 +967,7 @@ }, { "cell_type": "markdown", - "id": "0e62e4f9", + "id": "1c4cac99", "metadata": {}, "source": [ "# Multigraphs\n", @@ -987,13 +987,13 @@ { "cell_type": "code", "execution_count": 27, - "id": "8cdebcee", + "id": "ecc058cb", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:48.329127Z", - "iopub.status.busy": "2022-12-27T10:11:48.328788Z", - "iopub.status.idle": "2022-12-27T10:11:48.335265Z", - "shell.execute_reply": "2022-12-27T10:11:48.334630Z" + "iopub.execute_input": "2023-01-02T13:06:44.817671Z", + "iopub.status.busy": "2023-01-02T13:06:44.817425Z", + "iopub.status.idle": "2023-01-02T13:06:44.825347Z", + "shell.execute_reply": "2023-01-02T13:06:44.824506Z" } }, "outputs": [ @@ -1023,7 +1023,7 @@ }, { "cell_type": "markdown", - "id": "83d8c968", + "id": "0d509efb", "metadata": {}, "source": [ "# Graph generators and graph operations\n", @@ -1043,13 +1043,13 @@ { "cell_type": "code", "execution_count": 28, - "id": "0854d6d5", + "id": "36872fe5", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:48.338758Z", - "iopub.status.busy": "2022-12-27T10:11:48.338417Z", - "iopub.status.idle": "2022-12-27T10:11:48.342841Z", - "shell.execute_reply": "2022-12-27T10:11:48.342199Z" + "iopub.execute_input": "2023-01-02T13:06:44.830432Z", + "iopub.status.busy": "2023-01-02T13:06:44.830187Z", + "iopub.status.idle": "2023-01-02T13:06:44.836070Z", + "shell.execute_reply": "2023-01-02T13:06:44.835000Z" } }, "outputs": [], @@ -1062,7 +1062,7 @@ }, { "cell_type": "markdown", - "id": "7e19840b", + "id": "f8aa2bc4", "metadata": {}, "source": [ "# 4. Using a stochastic graph generator, e.g,\n", @@ -1073,13 +1073,13 @@ { "cell_type": "code", "execution_count": 29, - "id": "337abf3c", + "id": "018c814b", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:48.345806Z", - "iopub.status.busy": "2022-12-27T10:11:48.345587Z", - "iopub.status.idle": "2022-12-27T10:11:48.425762Z", - "shell.execute_reply": "2022-12-27T10:11:48.425042Z" + "iopub.execute_input": "2023-01-02T13:06:44.840131Z", + "iopub.status.busy": "2023-01-02T13:06:44.839862Z", + "iopub.status.idle": "2023-01-02T13:06:44.926006Z", + "shell.execute_reply": "2023-01-02T13:06:44.924883Z" } }, "outputs": [], @@ -1092,7 +1092,7 @@ }, { "cell_type": "markdown", - "id": "b5bef502", + "id": "1f2ee001", "metadata": {}, "source": [ "# 5. Reading a graph stored in a file using common graph formats\n", @@ -1104,13 +1104,13 @@ { "cell_type": "code", "execution_count": 30, - "id": "75cdd2c4", + "id": "0958110d", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:48.429564Z", - "iopub.status.busy": "2022-12-27T10:11:48.429103Z", - "iopub.status.idle": "2022-12-27T10:11:49.525847Z", - "shell.execute_reply": "2022-12-27T10:11:49.524708Z" + "iopub.execute_input": "2023-01-02T13:06:44.930470Z", + "iopub.status.busy": "2023-01-02T13:06:44.930203Z", + "iopub.status.idle": "2023-01-02T13:06:47.012922Z", + "shell.execute_reply": "2023-01-02T13:06:47.011621Z" } }, "outputs": [], @@ -1121,7 +1121,7 @@ }, { "cell_type": "markdown", - "id": "8ba69968", + "id": "a3bfafb7", "metadata": {}, "source": [ "For details on graph formats see Reading and writing graphs\n", @@ -1136,13 +1136,13 @@ { "cell_type": "code", "execution_count": 31, - "id": "42b38c47", + "id": "ff811ef3", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:49.529841Z", - "iopub.status.busy": "2022-12-27T10:11:49.529428Z", - "iopub.status.idle": "2022-12-27T10:11:49.535729Z", - "shell.execute_reply": "2022-12-27T10:11:49.535088Z" + "iopub.execute_input": "2023-01-02T13:06:47.017450Z", + "iopub.status.busy": "2023-01-02T13:06:47.017205Z", + "iopub.status.idle": "2023-01-02T13:06:47.024635Z", + "shell.execute_reply": "2023-01-02T13:06:47.023673Z" } }, "outputs": [ @@ -1168,7 +1168,7 @@ }, { "cell_type": "markdown", - "id": "d731579b", + "id": "51824ba9", "metadata": {}, "source": [ "Some functions with large output iterate over (node, value) 2-tuples.\n", @@ -1178,13 +1178,13 @@ { "cell_type": "code", "execution_count": 32, - "id": "ce458635", + "id": "1df52a7a", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:49.539801Z", - "iopub.status.busy": "2022-12-27T10:11:49.539579Z", - "iopub.status.idle": "2022-12-27T10:11:49.543928Z", - "shell.execute_reply": "2022-12-27T10:11:49.543283Z" + "iopub.execute_input": "2023-01-02T13:06:47.030119Z", + "iopub.status.busy": "2023-01-02T13:06:47.029863Z", + "iopub.status.idle": "2023-01-02T13:06:47.036049Z", + "shell.execute_reply": "2023-01-02T13:06:47.035153Z" } }, "outputs": [ @@ -1206,7 +1206,7 @@ }, { "cell_type": "markdown", - "id": "020161fc", + "id": "1b996922", "metadata": {}, "source": [ "See Algorithms for details on graph algorithms\n", @@ -1225,13 +1225,13 @@ { "cell_type": "code", "execution_count": 33, - "id": "1db0fd84", + "id": "c22301f3", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:49.547545Z", - "iopub.status.busy": "2022-12-27T10:11:49.547333Z", - "iopub.status.idle": "2022-12-27T10:11:49.912590Z", - "shell.execute_reply": "2022-12-27T10:11:49.911608Z" + "iopub.execute_input": "2023-01-02T13:06:47.040596Z", + "iopub.status.busy": "2023-01-02T13:06:47.040313Z", + "iopub.status.idle": "2023-01-02T13:06:47.454119Z", + "shell.execute_reply": "2023-01-02T13:06:47.453099Z" } }, "outputs": [], @@ -1241,7 +1241,7 @@ }, { "cell_type": "markdown", - "id": "13602902", + "id": "28bb8512", "metadata": {}, "source": [ "To test if the import of `nx_pylab` was successful draw `G`\n", @@ -1251,19 +1251,19 @@ { "cell_type": "code", "execution_count": 34, - "id": "5a6bd124", + "id": "c9a9ea9b", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:49.916523Z", - "iopub.status.busy": "2022-12-27T10:11:49.916149Z", - "iopub.status.idle": "2022-12-27T10:11:50.121281Z", - "shell.execute_reply": "2022-12-27T10:11:50.120219Z" + "iopub.execute_input": "2023-01-02T13:06:47.458882Z", + "iopub.status.busy": "2023-01-02T13:06:47.458405Z", + "iopub.status.idle": "2023-01-02T13:06:47.762965Z", + "shell.execute_reply": "2023-01-02T13:06:47.762082Z" } }, "outputs": [ { "data": { - "image/png": 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VYZOolQPs4C5nkygCQdk8evQI7du3x5kzZ+Dm5qaQNVJSUtC4cWO4urri33//Vcgaonj9+jVWrVqFEydOwNraGkuXLsXYsWNJa3YVQpyBXwgLC4OTkxMOHz6MMWPGSDz37NmzGDx4MJKTk4lW9//h8XgICQnBiRMncOrUKaSnp6NJkyZwd3eHu7s7GjVqJNN8dLVune/aCDNcbOSeh0BQFm5ubnj9+jVevXql0PDb4cOHMW7cOAQFBaFXr14KW0cUL1++xMqVK3Hq1CnUr18fy5Ytw6hRo1SWh1SVIc7AT1AUhW7duiE5ORnPnj0DiyW5VfG+ffvg4eGBwsLCMs+tihQUFODmzZsICAjAuXPnkJWVhVatWsHd3R3Dhw9H3bp1JY4PCI+H95lI2uzxG2wvdxtpAkEZvH79Gk2bNlVKPJ+iKPTo0QPv3r3Dy5cvoaenp9D1RPH8+XOsXLkSZ8+ehY2NDZYtW4aRI0eS66oSIc7AT9y4cQOurq44f/48BgwYUOb5vr6+2Lx5M5KTk5VgXcUmLy8PQUFBCAgIwKVLl5CXl4d27drB3d0dw4YNQ82aNUuc/yktF903h4DLE5T4ff7HF0g87iN2HaOOI2HceZTIY1psJm56cUgOAUHtmTBhAq5du4a4uDilJNnFxsbC3t4eM2bMwPr16xW+njiePn2KFStW4OLFi7C1tcXy5csxfPhw4hQoAcWmflcgKIrC4sWL0b59e/Tv31+qMcnJyahWrZqCLasc6OjoYPDgwcU5Bf/++y8sLCywYMEC1KpVCy4uLtizZw9SUlIAAD5nI8GTIT9AGngCCj5n6dtpIBAUwefPn3H06FHMnTtXadn2DRs2xLJly7B582ZEREQoZU1RtG7dGhcuXEBYWBgaNGiA3377Dc2bN0dgYCAEAkHZExDKDdkZ+D+nTp3CsGHDZKoMGD16ND59+oSQkBAFW1d5SU9Px7lz5xAQEIBbt24BALr0G464JqKf7n/eGTDp7gHN6vVLHGcbVgPbyELimje9uqChBSk7JKgn8+fPx4EDBxAfHw8DA+X9nRYWFqJ169bQ0tJCaGioWjyNh4aGYvny5bh27Rrs7e2xYsUKDBo0SOElzFUR8j+KoqS3P/74A71795apRDAlJYUkDsqJiYkJfv/9d1y7dg0JCQnYtm0bko0bgxLwyxyrWa0OtGvblfhXliPAYjJw9FE8XeYTCLSSnp6OPXv2YPr06Up1BABAQ0MD+/btw9OnT7Ft2zalri0OJycnXL16Fffu3YOFhQWGDBmCNm3a4Pz58yDPsfRCnAEABw8exNu3b+Hr6yvTOBImoBcLCwtMmzYNpnadwWCW/VSScnEDPq4fhE+bRyAxYCnyPjwrcwxfQCH4bRIN1hII9LNz504UFhZi1qxZKlm/Xbt28PT0xJIlS/Dx40eV2CCKjh074ubNmwgJCYGxsTEGDRoEBwcHXL58mTgFNFHlnYG8vDysWLEC7u7uaNmypUxjiTNAP9lcHuLTcqU6l5+dBvB5EHBzkP8hAkkBS5H94maZ4+JTc5HD5clrKoFAK3l5ediyZQsmTJigFAEgcfz1118wNjaGp6en2t1ou3TpguDgYPz333/Q0dFBv3790K5dO1y9elXtbK1oVHlnYOfOnUhMTMTq1atlHpuSkkKcAZr5mJoDiV9pJhNa1s1h0sMDFsNXwnzAAmjWEOoHUEi7tQ+CgnyJa1AAPqTm0GQxgUAP//zzD1JTUzF//nyV2mFoaIjt27fj8uXLOHXqlEptEYeLiwvu3LmDGzdugMVioXfv3ujYsSNu3LhBnIJyUqWdgYyMDPj6+mLSpElo2LChTGNzcnKQl5dHcgZopoAnOWNYu3Yz1PjNF4Zt+kOnfhvoNeWguvtqMLSKaqMpbg64X17LvQ6BoEx4PB42bNiAYcOGoX79+mUPUDCDBg2Cm5sbZs6cifT0dFWbIxIGg4Hu3bvj/v37CAoKAp/Ph6ura/HuAUE2qrQzsGHDBuTl5YntSigJobYA2RmgF0227H+STG19aJj80CkQ5GYoZB0CQVGcOnUK79+/x6JFi1RtSjHbtm1Dbm4uvL29VW2KRBgMBnr16oVHjx4Va5h07dq1ePeAIB1V9oqYmJiITZs2Yfbs2aUEb6SBOAOKoa6ZHiR1MeB+iy31O0F+NgrTvxT/zNQzlrgG4//rEAjqAEVR8PPzg6urK1q1aqVqc4qxsrLCmjVrsHfvXty7d0/V5pQJg8FA3759ER4ejvPnzyM9PR0cDqd494AgmSrrDPz555/Q1NTEwoULyzVeKI5DwgT0oqfFhrUEhcD0W/uR8PdMZIadRd6HZ8h5FYLEgKWguEVJh0wdQ2hZSW4aZW2mCz0ton1OUA+uX7+OZ8+eqdWugJCpU6eiXbt2mDJlCrhcrqrNkQoGg4EBAwbg6dOnOH36NJKSktCpUyf07NkTjx49UrV5akuVdAbev3+PPXv2YNGiRTAxMSnXHGRnQHG42FqAxRS/P1CY9B7p/x1AUsASpFxYj4JvMUUHmGyY9Z4JpoZ41TYWkwGXRpK1CAgEZeLn54e2bdvCxcVF1aaUgsViYe/evYiJiYGfn5+qzZEJJpOJwYMH49mzZzh58iQ+f/6M9u3bo2/fvnj8+LGqzVM7qqQzsHz5cpibm8tVy5ucnAwDAwOlyYVWJUY5WYttVWzSdQIM2g6ERrW6YOoYAkwWWPqm0G3SBZZjN0K3UXuJc/MFFEa3I82KCOpBWFgYgoOD4e3tLVebb0Vib2+PBQsW4K+//sKbN29UbY7MMJlMDBs2DC9evMDx48fx7t07ODg4YMCAASqVXlY3qpwccWRkJFq0aIGdO3di6tSp5Z7H29sbgYGBePfuHY3WEYSMORCKB3GpYp2C8sBiMtChvhmOTHSibU4CQR6GDBmCyMhIvH79Wi3kf8WRl5cHe3t7WFlZITg4uELLAfP5fBw/fhyrVq1CTEwM3NzcsGLFCjRv3lzVpqmUivuJlpM//vgD9evXx8SJE+Wah0gRKxZfN3uwJYQKygObyYCvmz2tcxII5SU6Ohpnz57FggUL1NoRAIoaje3Zswd37tzBP//8o2pz5ILFYmH06NF49eoVDh48iOfPn6NFixYYNmwYXr58qWrzVEaVcgbu37+Pixcv4s8//4SGhoZccxH1QcVS21QXKwfY0TrnqgF2pH0xQW3YsGEDatSogbFjx6raFKno1q0bxo0bh/nz5yMxMVHV5sgNm83GuHHj8ObNGxw4cACPHz9G8+bN4e7ujtevy9YqqWxUGWdA2KK4ZcuWGD58uNzzEWdA8bg7WGO+ayMAkFtVbIGrLUY4kFwBgnqQkJCAw4cPY86cORUq72jDhg1gsViYM2eOqk2hDQ0NDUyYMAHR0dHYvXs3Hjx4ADs7O4wePRpv375VtXlKo8o4A1evXsXdu3fh6+tLS7yLhAmUgy3vA1KvbIUGg5JYYSAKFpMBLTYTfoPt4ekim8IkgaBI/P39oa2tDQ8PD1WbIhPm5ubYvHkzAgICEBQUpGpzaEVTUxNTpkxBTEwMduzYgdu3b6NJkyYYN24cYmNL65tUNqqEMyAQCLB48WJ06dIFvXr1omVOsjOgeNLS0jB+/Hi0r07h1jwXdKhvBgBlOgXC4x3qm+GmF4fsCBDUiu/fv2P37t2YPn06jIyMVG2OzIwePRrdu3fHtGnTkJNT+Xp8aGlpYdq0aYiNjYW/vz9u3LiBxo0bY8KECYiLi1O1eQqjSjgDJ06cwPPnz7FmzRpayncKCwvx/ft34gwoGE9PT+Tm5uKff/5BHXN9HJnohBtzumCMUx3UMdMtrVRIUdDI/44xTnVw06sLjkx0IjkCBLVj9+7dKCgowOzZs1VtSrlgMBjYvXs3EhMTsXz5clWbozC0tbUxc+ZMvHv3Dhs2bMCVK1dga2uLKVOmqFV7Z9qgKjlcLpeqX78+NWDAANrmTEhIoABQFy9epG1OQkmOHz9OAaD+/fdfsedk5xdSL798p55+TKNefvlO/bl2PaWnp0cVFBQo0VICQXry8vKo6tWrU1OmTFG1KXKzZs0aislkUk+ePFG1KUohJyeH2rBhA1WtWjVKQ0ODmjp1KhUfH0/rGr9e07LzC2mdXxKVXmdg165d8PT0xIsXL9CsWTNa5oyMjETz5s3x8OFDtGvXjpY5CT/48uULmjVrhp49eyIgIEDqcaGhoWjXrh35XAhqy549ezBt2jRER0fDxsam7AFqTGFhIdq0aQNNTU08evQIbHbVkPjOzs7Gjh07sH79emRlZWHKlClYvHhxuXrcAEBMYhaOhcYjODoJ8Wm5JVq4MwBYm+rCxdYCo5ysYVPdgJb3IIpK7Qzk5OSgYcOG6NGjBw4fPkzbvP/99x+6deuG2NhYNGjQgLZ5CUVVA7169cLLly8RGRkJU1NTqccWFhbC1NQUS5YsUUudd0LVhs/nw9bWFq1bt8bJkydVbQ4thIaGon379ti4cSO8vLxUbY5SycrKwrZt27Bhwwbk5uZi6tSp8Pb2Ro0aNaQa/yktFz5nI3E3NgUsJkOiwJrweOeG5vB1s1dI+LNS5wxs27YNqampWLlyJa3zkr4EimPnzp24fv06/v77b5kcAaCoRKhjx464ffu2YowjEOTg9OnTePfuXaVyVJ2cnODp6YklS5ZUzji6BAwMDODj44P379/jjz/+wMGDB1G/fn3MmzcPSUlJEscGhMej++YQPIhLBYAylVaFxx/EpaL75hAEhMfT8yZ+otI6A+np6fDz88PUqVNRr149WudOSUmBhoYGDAwUt2VTFYmOjsaCBQvg6emJnj17lmsODoeDe/fugcfj0WwdgVB+qP+3Ke7WrRvatGmjanNo5a+//oKJiQk8PT3l1gOpiBgZGWHp0qX48OEDFixYgP3796NevXpYtGhRcXfbn9keHAPvM5Hg8gQyy63zBRS4PAG8z0Rie3AMXW8BQCUOE3h7e2P79u149+4dqlevTuvcK1aswL59+/Dlyxda563KFBYWomPHjsjIyEBERAR0dcu3Dfbw4UN06NABoaGhcHR0pNlKAqF83Lx5Ez169MCNGzfQvXt3VZtDO+fPn8egQYNw4sQJWkTdKjJpaWnYtGkTtmzZAoqiMGvWLMybNw9mZmYICI+H95nIUmMKkj4gM/QUuN9iwc9OB1WYD6aWHjQt6kK/uSv07JxFruU32J620ulK6Qx8+fIFDRs2xIIFC7Bq1Sra5/f09MT9+/fx7Nkz2ueuqqxcuRKrV6/GgwcP5LqJFxYWwtjYGCtWrMCCBQtotJBAKD/du3dHeno6Hj9+rLbdCeVlyJAhuH//Pl6/fl3u1vCViZSUFGzcuBFbt24Fi8XCxNmLcAWtweUJSp2b/TIYqZc2ip3LmDMWRu1LO1labCZuenFoySGolGGC1atXQ1dXF/PmzVPI/ERwiF7Cw8OxevVq/PHHH3I/zZO8AYK68eTJE9y6dQuLFi2qtI4AAGzduhW5ubmVKidCHszNzbFmzRq8f/8eHh4eCHjHQH5BochzWTr60G/RE2b95sHC/U+YD/KGllXj4uNZjy+KHMcTUPA5W3qnoTxUOmcgJiYG+/fvh4+Pj8LUvYgUMX3k5uZizJgxaNWqFZYsWULLnCRvgKBO+Pn5oUGDBhgyZIiqTVEoVlZWWLt2Lfbt24e7d++q2hy1wcLCAlPmL4NWnRZgMEV3p9Rp4ACz3jOh38wFOnVbQq9xJ5i6Ti8+LijIEzmOL6BwNzYFsUlZcttZ6ZyBZcuWwdLSEtOnTy/75HJCdgbow9vbGx8/fsSRI0fk7iQpxNnZGZmZmSSMQ1A5MTExOH36dIVoU0wHU6dORfv27TFlyhRwuVxVm6M2HAuNl7q3CkUJwMtKRdazH70ftK3Ft15nMRk4+kj+6oJK5QxEREQgICAAK1asgI6OjsLWIc4APdy4cQPbtm3DunXr0Lhx47IHSImDgwN0dHQQEhJC25wEQnnYsGEDqlWrhnHjxqnaFKXAZDKxd+9exMbGYu3atao2R20Ijk6SqnLg6+F5iPcbgC87xiE7IggAo2jXoI946Wq+gELwW8mljNJQqZwBHx8f2NraKvSLR1EUCRPQQHp6On7//Xd0794dnp6etM6tqamJDh06EGeAoFK+ffuGQ4cOYfbs2dDW1la1OUqjWbNmWLhwIXx9ffHmzRtVm6Nysrk8xKfllm8wgwEwWUAZef7xqbnI4coXFq00zsDt27dx9epV/PnnnwqVxfz+/Tv4fD7ZGZATT09P5OTk4J9//qGlpfSvcDgc3LlzB3w+n/a5CQRp2LJlCzQ1NTFt2jRVm6J0lixZAmtra0yZMgUCQens+arEx9QcSFuyZ9ZrBqr/tgZm/eZBy6oJQAmQF/MISackV8VRAD6kytdBslI4AxRFYfHixWjTpo3Ck3SI+qD8nDhxAsePH8eOHTtQq1YthazB4XCQkZGBFy9eKGR+AkESGRkZ2LlzJ6ZOnQpjY2NVm6N0dHR0sGfPHty9exd///23qs1RKQUiSgnFoWlRD9rW9tBv5gIL99VgsDWL5vgWg8I0ybo2sqwjikrhDFy8eBGPHj3C2rVrFV66Q5wB+fjy5QumTZuG4cOHY+TIkQpbx9HREdra2qTEkKAS9uzZg/z8fMyZM0fVpiicHC4PUQkZiIhPR1RCRvF2ddeuXTFu3DgsWLAA3759U7GVqkOTXfZtVlAoLtnyx/1MkJ8t9zqSqPBtpvh8Pnx8fNCtWzelKHsJ5SVJzoDsUBSFiRMnQltbG7t27VKo46atrY127dohJCSkyjVQIaiW/Px8bN68GWPHji13Jzt1R9pOe9MXr8Lly5fh5eWF48ePq8pclVLXTA8MQGKo4NshL2jWtIV2raZgGVaDIDcDWU8vg+IVOQkMthY0zGqLHc/4/zryUOGdgWPHjiEqKgr//POPUtZLTk4Gg8GAmZmZUtarTOzatQvXrl3D1atXZW5CVB6cnZ2xZcsWCAQCheQlEAiiOHLkCBITEyulAqY0nfYoAB/TcnEk9CMOPqTQfPY+nNowFWOuXEGfPn2Ub7SK0dNiw9pUFx8lJBEKCvKR8+IGcl7cEHncpOsEMLXEqwxam+lCT0u+23mFvkJyuVwsW7YMQ4YMgYODg1LWTE5OhqmpaZWoGaaTt2/fYv78+Zg+fXq5mxDJCofDQXp6OiIj6VHoIhDKgs/nY/369XBzc0OjRo1UbQ6tlLfT3oc8TdTy2IPpG44iO1vyVndlxcXWQqLOgKGTG7TrtQLLwBxgaQAsNlhG1aHblIPqo9bCoHVfsWNZTAZcGlnIbWOF3hnYs2cPPn36hKCgoLJPpglSVig7PB4PY8aMQa1atbBu3TqlrduuXTtoaWnh9u3baNGihdLWJVRdzp07h5iYGBw9elTVptDK9uAYbLj+tlxj+QIKYLIBp1EYsfJvXF4/i2br1J9RTtY4+PCD2OOGbfrDsE3/cs3NF1AY3U7+ZkUVdmcgKysLf/75J8aPH48mTZoobV0iOCQ7vr6+ePLkCY4cOQI9PfniWrKgra0NJycnojdAUArCNsUuLi6VqmNmQHh8uR2BX4liN8C60/domasiYVPdAJ0bmkutQigtLCYDnRuao6GFgdxzVdidAX9/f2RmZmL58uVKXZc4A7Lx+PFjrFq1Cj4+PnByclL6+s7OztixYwfJGyAonODgYISHh+Pq1auqNoU2PqXlYvmFKJHH8j++QOJxH7FjjTqOhHHnUSV/SVHYGZqCYV0yUa+aIZ2mqj2+bvbovjlEKiVCaWEzGfB1Ey9VLAsV8uqYkpKC9evXw9PTE9bW9PRylhbiDEhPXl4exowZg5YtW2Lp0qUqsYHD4SA1NRVRUaIvaAQCXfj5+aFly5ZwdXVVtSm04XM2Ejwab15gMECBgbHbKo/DJC21TXWxcoAdrXOuGmBHS/tioILuDKxZswYAsHjxYqWvTXIGpMfb2xsfPnzA06dPaWtCJCvt2rWDpqYmQkJCYG9PjwdNIPxKREQErl+/juPHj1eaNsUxiVm4G5si1bkm3T2gWb1+id+xDUU/NDFYbHwqZCMkIhqcVrZy21mRcHewRko2l5awywJXW4xwoO9huMLtDMTHx2PHjh2YP3++Sm7KZGdAOm7evImtW7fCz89PqTkdv6KrqwtHR0ciPkRQKH5+fqhXrx6GDh2qalNoQ5ZOe5rV6kC7tl2Jf2wj8RnulIAPrx1nQJWhuV8ZmeFig7WD7aHFZsqcQ8BiMqDFZsJvsD08XRrSaleF2xlYuXIlDA0NVSIkk5ubi9zcXOIMlIGwCVG3bt0wY8YMVZsDDoeDPXv2gKKoSvPURlAf3r17h8DAQGzbtk2hfVGUjbSd9gAg5eIG8PMywWRrQdOyEQzbDYFO3ZZiz2cwWUhkmePkyZMYMWIETRZXHNwdrNGxgXmxZgMl4IPBFF+uLtR06FDfDL5u9rSFBn6mQu0MvHnzBgcPHsSSJUtgYCB/9qSsEPVB6ZgxYwaysrIU1oRIVpydnZGSkoJXr16p2hRCJWTjxo0wMzPD77//rmpTaEPWTnv87DSAz4OAm4P8DxFICliK7Bc3JY7RMLHErLkLkJ6eLq+5FZLapro4MtEJffEUha9uoY6pDn59VGEAqGOmizFOdXDTqwuOTHRSiCMAVLCdgSVLlqB27drw8PBQyfqkL0HZnDx5Ev/++y+OHj2K2rXFy2cqk/bt24PNZiMkJAR2dvQm8BCqNomJifj777+xdOlS6OjoqNoc2pCq0x6TCS3r5tC1bQ8Nk5oQ5GcjM+wcCr7FAKCQdmsfdBt3AlNTTPtmBgOFWsZYtGgR9u7dS/M7qBhQFIVrgYfQx9kZ+xd0RQ6Xh6v3n+C30WPx79HD6NWxjdzKgtKi+sc2KQkPD8fp06exatUqaGlpqcQG4gxIJiEhAVOnTsWwYcPw22+/qdqcYvT09EjeAEEhbN26FRoaGpg+fbqqTaEVaTrgadduhhq/+cKwTX/o1G8DvaYcVHdfDYZWkZYIxc0B98triXN4zpqNffv24c6dO7TYXdF49uwZ3r17h+HDhwMoki6uZ6yBgq9vUc9YQ2mOAFCBnIHFixfDzs4Oo0aNKvtkBSF0BkiYoDQURWHChAlKaUJUHjgcDkJCQqpkwhJBMWRlZWHnzp3w8PCAiYmJqs2hlfJ2wGNq60PD5EdzJkFuhsTzRwwdgvbt22PKlCngcsV17qu8BAYGwtTUFC4uLqo2pWI4Azdv3sStW7fw119/qbQnQEpKCvT09CrVdiBd7N69G9euXcPff/+tlk2cnJ2dkZSUhDdv3qjaFEIlYe/evcjJyamUXTGFnfYkwf0WW+p3gvxsFKZ/Kf6ZqWcsdjwDQL1q+ti7dy/evXtXXDJeVaAoCoGBgXBzc1NZ6fXPqL0zQFEUFi9ejHbt2mHAgAEqtYWUFYomJiYG8+fPx7Rp09CrVy9VmyOSDh06gMViEWliAi1wuVxs2rQJo0ePhpWVlarNoR1hpz1JpN/aj4S/ZyIz7CzyPjxDzqsQJAYsBcUtSjxk6hhCy0p8WbGw016zZs2waNEirFmzBq9fSw4rVCaePXuG2NhYDBs2TNWmAKgAzsCZM2fw+PFjrF27VuVbz8QZKI2wCZGVlRXWr1+vanPEoq+vDwcHB+IMEGjh2LFjSEhIqJRtioWU1WkPAAqT3iP9vwNICliClAvr/588CIDJhlnvmWBqiM7v+rXT3pIlS1CnTh14eHhAICg7X6EyIAwRdO3aVdWmAFBzZ4DH4+GPP/5Ar169wOFwVG0OUR8UwZo1axAeHo7Dhw8rtQlReeBwOLh9+zbJGyDIhUAgwLp16zBo0CCVCmopmlFO1hJ1Bky6ToBB24HQqFYXTB1DgMkCS98Uuk26wHLsRug2ai927K+d9rS1tbF7927cvXsXBw4coPV9qCPqFiIA1Ly08NChQ4iOjsbx48dVbQqAop2BBg0aqNoMteHJkyfFTYjatWunanPKhMPhwM/PDzExMZWu1zxBeZw/fx7R0dE4ePCgqk1RKDbVDdCpoRnux6aAEpFBoGXZCFqWsn+PWEwGOtQ3K9Vpr2vXrhg/fjwWLlyI/v37o0aNGuW2Xd15/vw5YmNjsX37dlWbUoza7gzk5eVhxYoVGDFiBFq1aqVqcwCQMMHP5OXlYfTo0WjevDmWLVumanOkomPHjmCxWKTEkFBuhG2Ku3TpUiEcYHlIT09H0qUt4BcWAGWrDkiNpE57GzZsAJvNxpw5c2hbTx05efKkWoUIADV2Bnbu3ImvX79i9erVqjalGOIM/GDx4sV4//49jhw5ojbbXGVhaGiI1q1bk7wBQrm5c+cOQkND4e3trWpTFMqzZ8/Qtm1bPA65hjFNtYEyawukR1KnPTMzM/j7++PEiRO4fPkybWuqE+oYIgDU1BnIyMjAmjVrMGnSJNjY2KjaHABF+Qvp6ekkZwDArVu3sGXLFvj5+aFp06aqNkcmnJ2dSd4AodysXbsWzZs3V9uqGTo4dOgQ2rdvD2NjYzx58gR/TeiD+a70hNWk6bT322+/wdXVFdOnT0d2djYt66oTwhCBulQRCFFLZ2Djxo3IyclRq+3n1NRUAER98Pv37xg/fjy6deuGmTNnqtocmeFwOEhISMC7d+9UbQqhgvH8+XNcvXoVCxcuVHllkyLgcrmYNm0axo8fj99++w33799HvXr1ACi30x6DwcCuXbuQnJyM5cuXl+u9qDPqVkUgRO2cgcTERGzatAmzZ89GzZo1yx6gJIgUcRHq1oRIVjp16gQmk0nyBggys27dOtStW7dSdtn79OkTunTpgr///hv79u3DgQMHoK1dsqeAu4M1bnpx0KF+kagYqwyfQOg0dKhvhptenDJ3BH6mfv36WLFiBfz9/fHkyRPZ3owaIwwRDBo0SK1CBIAaOgN//fUXNDQ0sGjRIlWbUgJhx8Kq7AwEBgbi2LFj2L59u9o0IZIVIyMjtGrViuQNEGTi/fv3OHHiBObNm1ep2hQDRQqvrVu3xrdv33D//n1MmjRJ7LnCTns35nRB97paKExLKHUORVEwYhXI3WnPy8sLzZo1w+TJk8Hj8WQer448f/4cMTExahciAABQSiY7v5B6+eU79fRjGvXyy3cqO7+w+FhcXByloaFB+fr6KtusMjl58iQFgEpPT1e1KSohISGBMjU1pYYOHUoJBAJVmyMX8+bNo2rXrl3h3wdBeXh6elLm5uZUTk6Oqk2hDT6fT/n6+lJMJpNydXWlkpOTZRq/efNmSltbm0rPyi1xTW/XiUO5u7vTYmNoaCjFYDCojRs30jKfqvHx8aFMTEyogoICsec8efKEAkA9efJEiZZRlFJc3JjELBwLjUdwdBLi03JLFKkwAFib6sLF1gIvz++GmZkZZs2apQyzZCI5ORkaGhowMjJStSlKh6IoTJw4EZqamti9e3eFj5dyOBxs3LgR79+/R/369VVtDkHNSU5Oxt9//w1vb2/o6iqml7yy+f79O8aNG4cLFy5gyZIlWLFihcx9X8LDw9GyZUsY6+vAWP9HvxanNi1x6dIlWux0dHTEzJkzsXTpUgwePBh169alZV5VQKlpFYEQhYYJPqXlYsyBUPTwv4MjoR/x8RdHACiqXv2YlovDjz7gsUUv2HpsQxpX/W42ycnJMDc3r/A3wvKwZ88eBAUFqW0TIlnp3LkzGAwGCRUQpGLbtm1gMpnw9PRUtSm0EBkZWSzNffHiRaxevbpcDeDCw8Ph6OhY6veOjo549+4d0tLS6DAXf/75J0xNTTFt2rQKXQX04sUL9Q0RQIHOQEB4PLpvDsGDuKIsfEmylgAgPPypUBfdN4cgIDxeUaaVi6oqRRwTE4N58+Zh6tSp6N27t6rNoQVjY2O0bNmSJBESyiQ7Oxvbt2/H5MmTK4UjfOzYMTg5OUFPTw9PnjxBv379yjVPeno6YmJi4ODgUOqY8Hfh4eFy2SrEwMAAO3bswNWrV3HixAla5lQFJ0+ehImJCbp166ZqU0SiEGdge3AMvM9EgssTlOkE/ApfQIHLE8D7TCS2B8cowrxyURUFh3g8HsaOHYuaNWtiw4YNqjaHVjgcDtkZIJTJvn37kJWVhblz56raFLkoKCjAzJkzMXr0aAwbNgwPHjyQS1r98ePHACDSGWjYsCGMjY1pcwYAYMCAARgyZAhmz56N9PR02uZVFuoeIgAU4AwEhMdjw/W3tMy14fpbnFCTHYKq6AysXbsWYWFhOHLkiNo3IZIVZ2dnfPz4ER8+fFC1KQQ1paCgAJs2bcKoUaMqbPUMAHz58gXOzs7Ys2cPdu3ahYMHD8qd+xAeHg4jIyORonAMBgMODg60OgMAsHXrVuTn52PhwoW0zqsM1D1EANDsDHxKy8XyC1FijxemJyDl4kZ83j4WH9cNwuftY5F6ZSt4WSlixyy7EIVPabl0mlkuqpoz8OTJE6xcuRKLFy+ulBrsJG+AUBbHjx/H58+fK+TNR0hwcDBat26NT58+4e7du5g6dSoteU9hYWFo27atWK0RBwcHhIWF0Rrjr1mzJvz8/LB///4K970NDAxU6xABQLMz4HM2EjwxYYGCxDh8PTgHOVHB4GenAQIe+NlpyH5xHd8OzQXve6LIcTwBBZ+zkXSaWS6qUs5AXl4exowZA3t7e7VSgaQTU1NTNG/enOQNEEQiEAjg5+eH/v37VzjJbaBoW3r9+vXo3r07mjVrhqdPn8LJyYm2+cPDw0WGCIQ4ODjg27dv+PLlC21rAsCUKVPQoUMHeHh4gMvl0jq3oqAoCidPnlRLoaGfoc0ZiEnMwt3YFLE5Amk39oDiFj3h6zXvAYvhK6Hfskjfm5+dhrQbu0WO4wso3I1NQWxSFl2mygxFUUhJSakyOwM+Pj6Ii4vD0aNHoampqWpzFAbJGyCI49KlS3j9+rXaiZ9JQ2ZmJoYOHYqFCxdi4cKFuHbtGq3Xri9fviAhIUFkJYEQ4TG6QwVMJhN79+5FXFwc1qxZQ+vcikIYIhg+fLiqTZEIbc7AsdB4sZrVgoI8cD+/KvqBxYZZz+nQqd8Gpq7TwNAsqk/Ne/cYvMxkkeNZTAaOPlJd7kBGRgYKCwurhDPw33//wd/fH2vXrq2QT0Sy4OzsjPfv3yM+Xj3yUgjqAUVRWLt2LTp16oSOHTuq2hyZiIqKgqOjI27evImzZ89izZo1tCsmCm/wknYGatasiZo1ayIsLIzWtQHAzs4OixYtgq+vL16/fk37/HRTEUIEAI3OQHB0kthdAQE3F8J+2AwmGwyWxv9fs4pfAxS4X96IHM8XUAh+m0SXqTIjlCKu7GECYROirl27qqXwE9107twZAMjuAKEE9+7dw8OHDyvcrsCJEyfg5OQEDQ0NPH78GIMGDVLIOuHh4bC0tISVlZXE8xSRRCjkjz/+QN26dTFlyhQIBAKFrEEHlBr3IvgVWpyBbC4P8RKS/Fh6xmBoFWWjU4X5yIoIgqAwH9kvbkKQl1l8Hl/MzgAAxKfmIoerGn3qqtKkaNasWcjIyKiwTYhkxdzcHPb29sQZIJTAz88PdnZ26NOnj6pNkYrCwkJ4eXnB3d0dAwcOxKNHjxTa+j0sLAwODg5lJiI6Ojri8ePHCrlZa2trY8+ePbh37x4OHDhA+/x08eLFC7x9+1atqwiE0HLF/5iaU0pZ8GcYTBYM2w4o/jnt2g582jgUqVf8S5xH8QvFzkEB+JCaI5+h5aQqOAOnTp3CkSNHsH37dlhbS99drKLD4XBIEiGhmMjISFy+fBmLFi2qEA7x169f0bVrV2zfvh3btm3D0aNHFVoGTFEUHj9+LDFEIMTBwQEZGRmIiVGMXoyLiwt+//13LFiwAF+/flXIGvISGBgIY2NjtQ8RADQ5AwW8sj0/o04jYdh+OBhsreLfsQyrQdOy0Q9jtCT/EUuzjiIQOgOVQYFMFF+/foWHhweGDBmC0aNHq9ocpcLhcPDu3Tt8/vxZ1aYQ1IB169bB2toa7u7uqjalTO7evYvWrVsjLi4OISEhmDFjhsLl0mNjY/H9+3eJyYNC2rZtC4D+JMKfWb9+PTQ1NTFnzhyFrVFefhYaqgiJ2LQ4A5rssqdhMJgw4YxFrdnHUGO8P2pO3g2rqfvB1PzRM1vDXPITqTTrKIKUlBSYmJhUutalwI8mRBoaGpWiCZGsdOnSBQDJGyAAHz9+xPHjxzF37ly1ju9SFIXNmzfDxcUFtra2ePr0KTp06KCUtYUJgcIbvSRMTExgY2OjUGfAzMwMmzdvxsmTJ3H58mWFrVMeIiMjK0yIAKDJGahrpgdpbyFMDW1o1WgIDbNaKEh6j/z4l0W/1zGEllVjseMY/19HFVRmwaG9e/ciKCgIBw4cqPQJkqKwsLBA06ZNiTNAwKZNm2BkZIRJkyap2hSxZGdnw93dHXPnzoWXlxdu3ryJ6tWrK2398PBwNGjQAKamplKdLxQfUiS//fYbXF1dMX36dGRnZyt0LVk4efJkhQkRADQ5A3pabFibSpa3zI0NR/IZX2S/uIm890+RGXoGSQFLAKpo69/QaTAYbPFbKdZmutDTUs2TeWV1BmJjYzF37lx4eHigb9++qjZHZTg7O5O8gSpOSkoK9u/fj5kzZ6qt9PabN2/g6OiIK1euIDAwEOvXr1f6bqW4ToXicHBwwLNnz1BYKD4fTF4YDAZ27dqF5ORktRFJ+7mKoCKECAAaSwtdbC3E6gwAAAQ85L59gNQr/kg6sQzpwX9DkF/kxek27gRDRzexQ1lMBlwaWdBlqsxURvVBYRMiS0vLSteESFY4HA5iYmKQkJCgalMIKmL79u2gKAozZsxQtSkiOX36dIlugEOHDlW6DYWFhXj69KlUyYNCHB0dkZ+fj5cvXyrQMqB+/fpYuXIltmzZUtxESZUIQwTqLjT0M7Q5A6OcrCV2KNQwqw1d2w5gGVYDWBpgaOlCq1ZTmPX1gvnARWAwxffT5gsojG6nugz3yrgz4Ofnh9DQUBw5cgT6+vqqNkelcDgcACRvoKqSk5ODbdu2YdKkSWrn9PN4PCxYsABDhw5Fnz59EBYWhsaNxYdTFUlUVBTy8/NlcgZatmwJFoul8FABAMyZMwf29vaYPHkyeDzVlKELqUhVBEJo22OyqW6Azg3N8SAuVaRToGFWC9XcfGSel8VkoEN9MzS0MKDDzHJR2ZyBp0+fYsWKFfD29kb79u1VbY7KqV69Oho3boyQkBCMHDlS1eYQlMyBAweQkZGBefPmqdqUEiQmJsLd3R13797Fpk2bMGfOHJUm+IaHh4PFYqFVq1ZSj9HV1UWzZs0QHh4ODw8PBVoHaGhoYN++fXBycsKWLVtU9nn+3IugooQIAJobFfm62YMtKVRQDthMBnzd7GmdU1YqkzOQn59f3IRo+fLlqjZHbXB2diY7A1WQwsJCbNy4ESNHjkSdOnVUbU4xDx48QOvWrfHmzRsEBwfDy8tL5ZU+YWFhsLOzkzmnwtHRUSk7A0BRjsKsWbOwbNkyvH//Xilr/kpFqyIQQqszUNtUFysH2NE5JVYNsEPtMpITFUleXh5ycnLUbvuwvPj4+ODdu3c4cuRIhfJaFQ2Hw8GbN2/w7ds3VZtCUCIBAQGIj49XmzbFFEVh+/bt4HA4qF+/Pp4+fVosm61qyupUKA4HBwdERUUhJ0c5onGrV6+Gqakppk+fTmsLZWkRhgi6d++u9LXlgfbCfXcHa8x3bVT2iVKQde8Y9BJf0DJXeRH2JagMOwPBwcHYvHkzfH19YWdHr9NW0RHmDdy5c0fFlhCUhbBNcd++fWFvr9rdR6Aod2H06NGYOXMmZs6cif/++w+WlpaqNgsAkJubi5cvX8pUSSDE0dERAoEAERERCrCsNAYGBti5cyeuXr2KEydOKGVNIRWxikCIQlR8ZrjYYO1ge2ixmZIrDETAYjKgxWbizwFNwKmWDzc3NwQGBirCTKmoLFLEGRkZGDduHFxcXNRSrUvVWFpaolGjRqTEsApx5coVREVFqUVDopiYGLRr1w7nz59HQEAANm3apFbCRxEREeDz+eXaGbCzs4OOjo7SQgUA0L9/fwwdOhSzZ89GWlqa0taNjIxEdHR0hQsRAApyBoCiHYKbXhx0qF8k4VuWUyA83qG+GW56cTC6fX2cPHkSI0aMgLu7Ow4ePKgoUyVSWToWCpsQHTx4sEJorqsCDodD8gaqEH5+fmjfvj06deqkUjvOnz+Ptm3borCwEKGhoRgxYoRK7RFFeHg4tLW10axZM5nHstlstGrVSqFKhKLYunUruFyuUkNAFTVEACjQGQCKcgiOTHTCjTldMMapDuqY6ZZSKmQAqGOmizFOdXDTqwuOTHQqzhFgs9k4dOgQJk6ciN9//x07duxQpLkiqQw7A6dPn8bhw4exbdu2KtWESFacnZ3x6tUrJCWprl02QTk8ePAA9+7dg7e3t8oS83g8HhYvXoxBgwahe/fuxQl66khYWBhatWpV7t0KR0dHpTsDlpaWWLt2LQ4cOKAUJ78ihwgAAJSSyc4vpKrZtKLmrPanXn75TmXnF5Y5RiAQUF5eXhQAau3atUqw8gebN2+mdHV1lbomnSQkJFBmZmbU4MGDKYFAoGpz1JrPnz9TAKjAwEBVm0JQMAMGDKCaNm1K8fl8layflJREdevWjWIymdS6devU/rvZsGFDatasWeUef+zYMQoAlZKSQqNVZcPn86kOHTpQtra2VF5enkLXevHiBQWAunz5slzzPHnyhAJAPXnyhCbLpEPp+8V6WmwI0uJRQyMfdjWNpJIYZjAY2LhxI5YtWwZvb28sXbpUaVmiFbmskKIoTJo0CWw2G3v27FF5aZK6Y2VlhYYNG5K8gUpOVFQULly4gAULFqgkZBYaGorWrVsjMjISN2/exIIFC9T6u5mWlobY2NhyJQ8KEeYaKFsdkMlkYu/evYiLi8OaNWsUulZFDhEACg4TiKM8N3IGg4GVK1fCz88Pf/75J+bNm6cUh6AiSxHv27cPV65cqbJNiMoDyRuo/Kxfvx61atXCb7/9ptR1KYrC7t270blzZ9SuXRtPnz6Fi4uLUm0oD8IbeHmSB4U0bNgQxsbGSg8VAEUJjN7e3lizZg1evXqlkDWo/wsNDRw4sGKGCKAiZwBAuT3hhQsXYseOHdi8eTM8PDzA5/NptqwkFXVn4N27d5g7dy6mTJlSpZsQyYqzszNevnxZnDhKqFx8+vQJx44dw9y5c5V60c7NzcX48eMxbdo0eHh44Pbt27CyskIOl4eohAxExKcjKiEDOVzVyuiKIjw8HEZGRmjYsGG552AwGErpYCgOHx8f1KtXD1OmTIFAICh1XN7P4eXLlxW2ikCIatoAysn06dOhp6eHCRMmICcnB4cOHVJY967k5GTUq1dPIXMrCj6fj7Fjx6JGjRrYuHGjqs2pUPysNzB48GAVW0Ogm02bNsHAwACTJ09W2prv3r3DkCFD8PbtWxw9ehSO3QfA92oMgqOTEJ+Wi5/3NxkArE114WJrgVFO1rCprjoZdiFCsSF5QyoODg74+++/QVGU0sMi2tra2LNnD1xcXLB//35MmTIFMYlZOBYaT8vnEBgYCCMjI/To0UOh70ORVJgwwa+MGzcOAQEBOHnyJIYNGwYul0uDZaWpiGGCdevW4dGjRzh8+HCVb0IkK7Vr10b9+vVJqKASkpaWhn379sHT01Np34tLly6hTZs2yMnJwflb93E1vyF6+N/BkdCP+PjLDQgAKAAf03JxJPQjevjfwZgDofiUlqsUW8URFhYmV4hAiKOjI759+4YvX77QYJXsODs7Y8KECfBevR7Dd96h7XOgKnoVwf+pcGGCnxk2bBjOnTuHoKAgDBgwALm59H9pKlqYICIiAsuWLcOiRYvQoUMHVZtTIeFwOCSJsBKyY8cOCAQCzJo1S+Fr8fl8LF26FP3794ezszN8DlzCjCvf8CAutei4hA6vPx9/EJeK7ptDEBAer3CbRfHlyxd8/fqVFmdAOIeqQgUA0GHMfBi4r0NYfAYAej6Hly9f4s2bNxU6RABU4J0BIX379sWVK1dw//599OrVC5mZmbTNzefzkZaWVmGcgfz8fIwePRrNmjXDihUrVG1OhYXD4SAyMlKpymUExZKbm4utW7diwoQJCv8+p6amok+fPvD19YWvry+6zVyHlUGx4PIEZd58foUvoMDlCeB9JhLbg2MUZLF4hAl/8lQSCKlZsyZq1qypkiRCANgeHIPV1+LAYGsADNlufZI+h8oQIgAq+M6AkK5du+L69et48eIFunfvTttFPDU1FRRFVRhn4I8//kBsbCxpQiQnHA4HFEWRPgWViL///hvp6ekKb2v7+PFjtGnTBk+fPsW1a9dQr/sobLxJz018w/W3OKHkHYKwsDBYWlrCysqKlvlUIT4EAAHh8dhw/e3/f5Lv3vPz51BZQgRABU0gFEWHDh3w33//wdXVFc7Ozrhx4waqV68u15wVSYr49u3b2Lx5M9avX18uyVDCD+rWrYs6deogJCQEgwYNUrU5BDnh8XjYuHEjRowYodBk4P3798PT0xMtW7bEqVOnAD0zeG4Wn3vCy0hCxsOTyHsfAX52KpgaOmCb1IBuo/Ywaj9c5JhlF6LQoYG50jq5lrdToTgcHBzg5+cHgUCgNI2HT2m5WH4hSuzxwvQEZNw7jvyPz8HPzQRL1xA69dvCqPNvYBuIvvYLP4eMhDi8efMGGzZsUJT5SqPChwl+pnXr1rhz5w5SUlLQpUsXfPr0Sa751EGKWJqSF2ETIg6HAy8vLxVYWflwdnYmeQOVhJMnT+LDhw8K06jPy8vDxIkTMXnyZEyYMAF37txB7dq14XM2EjwxYYH8z6+Q8PcMZD+7Cn5GIsDnQZCfhYKvMch+fkPsWjwBBZ+zkQp5H78iEAjw+PFjWkIEQhwcHJCZmYmYGOWFPCR9DgWJcfh6cA5yooLBz04DBDzws9OQ/eI6vh2aC973RJHjhJ/DyZMnK0WIAFDhzoCiSkuaNm2Ku3fvolu3bujcuTNu3bqFBg0alGsuVTkDspa8zJ49G9+/fydNiGiEw+Hg8OHDSE9Ph4mJiarNIZQTiqLg5+eHXr16oUWLFrTP//79ewwdOhSvXr3CwYMHMW7cOABF3+G7saK1KgT52Ug5txYUNxdgMKHfsid06rUGg60J3vdvKEz9LHY9voDC3dgUxCZloaGFYssOY2Nj8f37d1p3Btq2bQugaMfB1taWtnnFIelzAIC0G3uKPgcAes17QK9xJ+S+fVjkpGWnIe3GblgMW15qnPBzCLsZUqGFhn5GJc6AopUDGzRoUOwQdOnSBTdv3kSTJk1kniclJQUsFgtGRkYKsLI0n9Jy4XM2EndjU8BiMkQmG/1c8nLw4Qc0MhQg+NxV7N+6FXXq1FGKnVUBZ2dnUBSFu3fvYsCAAao2h1BOrl69ihcvXmDLli20zx0UFIRRo0bB2NgYDx8+RMuWLYuPHQuNF/sdznp+regpFIBRp99g3NFdpnVZTAaOPorHigGKbWokjO0Lb+B0YGJiAhsbG4SFhWH06NG0zSsOSZ+DoCAP3M//VyRksWHWczoYLA1o122JnFchoArykPfuMXiZyWAbln4gZDKAZOPGGD68clwfKkUCoShq166NO3fuwNTUFF26dEFERITMcyQnJ8Pc3FwpT9sB4fHovjlE5tKj6O8UannsgWYT9Zc1rUjUrVsXtWvXJnoDFRw/Pz84OTkVi0nRgUAgwKpVq9C3b1906NABT548KeEIAEBwdJLY73BezE+ldRSFhAOeiN8wGJ93/o702wdB8Qokrs8XUAh+q/jOmmFhYWjYsCFMTU1pndfBwUFpSYSSPgcBNxf4/74rg8kGg6Xx/9es4tcABe6XN6LHU4BeQ8dKESIAVOgMKIMaNWrg9u3bqFu3LlxcXPDw4UOZxitLY2B7cAy8z0SWq/SIwWSBYrKx+KxqSo8qKwwGA87OzsQZqMA8evQIISEhWLRoEW0PH2lpaejfvz9WrFiBVatW4cKFC6XCSNlcHuIlCAUVpv7IZcq4dwyFyR9B8QrAz0xG5qNTSDq9uszd0/jUXIVLF9OdPCjE0dERERERKCiQ7PTIS1mfA0vPGAwtPQAAVZiPrIggCArzkf3iJgR5P0rU+ZnJ4ucwqo5C5ff7UwiVMkzwM2ZmZrh16xb69u2LHj164OLFi1I3B1GGM1Cy5EU+Nlx/i2r6WhjhYE3LfFUdDoeDY8eOISMjQ2mhIgJ9+Pn5wdbWFgMHDqRlvoiICAwZMgQZGRkICgpCz549RZ73MTWnlKLdzwjys4tfM7X1YdJ9CgAg/eZeCPKzkf8+AnkxodBt1E7sHBSAq/efoJ6xhthz5IHH4+HJkydo3749nj59SuvchoaG4HK5CAwMLFf4Vlrefy+U+DkwmCwYth2AjPvHAQBp13Yg7dqOUudR/EIJkzDwITUHdjUr/vWh0iUQisLQ0BBXr16Fm5sb+vTpg9OnT6NPnz5ljlO0FHFZJS8UrxCZYWeRExWMwu/fwNTQhlZtOxh1dIdWDdFNQ5RdelSZcXZ2hkAgwL1790izpwrG69evce7cORw4cICWMN/Bgwcxbdo02NnZ4b///kPdunXFnlvAK90I52cYbA1QhUXy6fqt+kC/WVcARTsGmQ8DAQD5H55JdAYA4LfRY1HwlZ4HCXFs2rQJmzZtUsjcis4Z0LRsBMtxkm036jQSlICPrPDzoHhFnwnLsBpYeibF/7fM/+8eiKOsz7uiUOl3BoTo6enh4sWLGDFiBAYNGoR///0XQ4cOlTgmOTkZjRo1UphNkkpeKAEfSYErkP/xefHvBPxC5MU8Ql7cE1gMWw6dui1LjROWvByZ6KQos6sM9evXh5WVFW7fvk2cgQrG+vXrUbNmTYwaNUquebhcLmbNmoW9e/di0qRJ2LZtG7S1tSWO0WRLdj5YhtXA+3/FANvIovj3bMMfrwUFZUur/3v0sMJ2Bs6cOYM1a9bgzp070NHRoX3+kSNHonHjxli+vHSmPl28/16IeTckdx9lMJgw4YyFUYfhKEz9DKaGNtgmlkg6sbT4HA1zyTutZX3eFYUqsTMgREtLC4GBgRg/fjxGjBiBf/75B2PHjhV7viLDBGWVvGQ9vVzsCGhUqwPjTqNQkPgOGQ9OAPxCpF72h5XHviJpzZ9QZulRZYfBYIDD4ZC8gQrG58+fcfToUfj6+kJLS6vc88THx2Po0KF48eIF9u/fj4kTJ0o1rq6ZHhiA2C1qbaumyP6/M8D7KR7982uWiOz1n2EA6NWxDfS0FHMJ37VrF+zt7dGxY0eFzM/hcPDo0SO0bt1aIfMDgC2Xh/k3rkkMFQhhamgX77Zyv8UiP/5l0e91DKFl1VjsOAaKPu/KQOVwaWRAQ0MDhw8fxoQJEzBu3Djs2rVL5HkURSk0TCAseRFHdkRQ8WuzXjOha9sBxl3GQLte0ZeHn5WC3FjRDT+EpUcE+XF2dsaTJ09o7XlBUCz+/v7Q09PDlClTyj3HjRs30Lp1ayQlJeH+/ftSOwIAoKfFhrWEMJ1+C1cIJXGzn15B9svgon8/fef1GkluMmZtpqswRwCgr1OhOBwdHREVFYWcnByFrVHW5wAAubHhSD7ji+wXN5H3/ikyQ88gKWAJQBVt/Rs6DQaDLV5DQNGfgzKpVAqE0sJisbB3717Mnj0b06dPx/r160udk5WVhYKCAoXtDEgqeeHnZf3IOGayoWlpU3xMy+pHwg33s+h8A2WVHlUFOBwOBAIB7t+/r2pTCFKQnp6OPXv2YPr06TA0NJR5vEAggK+vL3r27AkHBwc8efIEbdq0kXkeF1sLsc6+llVjGDq5Fa2Xn4XUSxuRemkjBPlZAADDdkOhWUO8UBqLyYBLIwuxx+UlNzcXUVFRCnUGHBwcIBAIaE9O/BVJnwMAQMBD7tsHSL3ij6QTy5Ae/Hdxgqdu404wdHQTO1TRn4OyqbQ6A9Ksv3nzZixZsgQLFy7E8uXLSzgpilQfLKvkhZfxQwKTpWMABpP142e9H1mr4qQyAeWUHlUFbGxsYGlpSaSJKwg7d+5EYWFhudoUf//+HYMGDcIff/yBZcuW4dKlSzAzMyuXHaOcrCWWCZu4TIBZXy9oWtqAoaEFhoYWNGvawqz/PJg4j5c4N19AYXQ7xVUMRUREgM/n0ypD/Ct2dnbQ0dFRuN5AWZ+Dhllt6Np2KArLsDTA0NKFVq2mMOvrBfOBi0pce39F0Z+DsqkyCYSiYDAYWL16NfT09LB48WJkZ2djw4YNYDAYCnUGyio9ogrzf/zAKvkRMZhs0ef9OgdQaUpeVAnJG6g45OXlYcuWLfj9999lblL24sULDB48GKmpqbh06ZLcCaM21Q3QuaE5HsSlir0Z6dt3g759N5nmZTEZ6FDfTKH5QGFhYdDW1oadneIUDtlsNlq3bq1wZ6Csz0HDrBaqufnIPK8yPgdlU2V3Bn7G29sb27Ztw6ZNmzBt2jQIBAKFdiwss/RI40e28q81rpSAJ/K88qxDkA5nZ2c8fvwYWVlZqjaFIIGDBw8iNTUV8+fPl2nc0aNH0a5dOxgYGODJkye0VY74utmDLWmLuhywmQz4utnTOuevhIeHo1WrVtDQUEylghAHBweEhYnOe6IT2j8HilLK56BsqlwCoThmzJiBv//+G/v27cO4cePw7ds3AIpxBsoqRWEb/XiqEeRlgRLwi3/mZ6f/OM9Y8tNPZSl5UTUcDgd8Ph8PHjxQtSkEMfB4PKxfvx7Dhg2TujFZQUEBPD09MWbMGAwfPhwPHjxA/fr1abOptqkuVtLcP2DVADuFa4iEh4crNEQgxMHBAXFxcUhNTVXoOrR/DgyGUj4HZVMlEwjF8fvvv+Pff/9FQEAA/P39YWRkpBDvWFh6JA6WjgE0zGoX/SDglxAW4Sb80MnWqiX+D7wylbyoGltbW1SvXp2ECtSYU6dO4f3791i0aJFU53/+/BkcDgf79+/H7t278c8//yiknt7dwRrzXeXUKvn/9XJcSxOFq4umpaUhNjZWocmDQoQOx+PHjxW+Vi8bQ2i+uSrnLEWfg1fXBpVS5ZWECX5hxIgROHPmDN68eYPCwkLk5pYt/iEr0pS86LfqXfw6NWgbcqMfIP3OEeS/L2q4xDIwh25D8d57ZSp5UTXCvAGSRKieCNsUu7q6olWrVmWeHxwcjNatW+PLly+4d+8ePDw8FHo9muFig7WD7aHFZkrObBcBi8mAlgYLOi9O4+DCkUhISFCQlUUIb8zKcAYaNGgAExMThYcKuFwu3NzckBJyDLPbm5f7cwCfB5v0MMzuIV53oCJDdgZE0L9/f3Tr1g35+fno06ePQmLFZZW8GLTuC+06Rf3XC1PikXzWF5kPThQdZGnArO+cUoJDQipbyYs6wOFwEB4ertC6aEL5uH79Op49e1bmrgBFUVi3bh26d++OFi1a4OnTp0q56QFFOwQ3vTjoUL+oOqGsm5HweIf6ZrjpxcHNvashEAjQp08fhWpehIWFwdjYGA0bipY7pxMGg4G2bdsqNIlQIBDg999/x8OHD3HhwgV4DXAq1+fQvLoWvuydill96WvnrG6QnQExaGhooH379oiIiED37t2Rnp5e9iAZKKvkhcFkwWLYChh3GQu2WS2ApQGmtgF0Gjqhxpj1IqWIhVS2khd1wNnZGTwej+QNqIgcLg9RCRmIiE9HVEJGibJZPz8/tG3bVmIDsszMTAwZMgSLFi2Ct7c3rl69qtC+I6KobaqLIxOdcGNOF4xxqoM6ZrqlwoUMAHXMdDHGqQ5uenXBkYlOqG2qCysrKwQFBeHDhw8YOnQoCgslNM+Rg/DwcLRt21YpbduBolBBWFiYwh4QfXx8EBAQgKNHj6JTp04Ayvc5tEi7C10qD66urgqxUx0g+8hiSE5Ohr29PbZu3QpXV1e4uLjg+vXrsLCg54lbmtIjBlsDRh2Gw6jDcKnnrYwlL+pAkyZNUK1aNYSEhFSa/uXqTkxiFo6FxiM4OgnxabklynEZAKxNddHUhMK9F7E4vmez2AeMqKgoDB48GN++fcP58+cxYMAApdgvDpvqBlgxwA4rYIccLg8fUnNwKzgE8+fOwZvwu6hvbSVyXLNmzXDu3Dn07NkTkydPxj///EPrQxVFUQgLC8Pvv/9O25xl4eDggL/++gufP39G7dq1aZ17x44d8PPzw+bNm0X2oRH1ORTwBNBkM1HXTK9EmDUwMBADBw6US95a3SFhAjEIpYhbt26NkJAQJCYmokuXLvj8+TNta1TU0qOqCMkbUB6f0nIx5kAoevjfwZHQj/j4iyMAFKVyfUzLRVBsDmpO3oWz6Vb4JELIKyAgAI6OjtDS0sKTJ09U7gj8ip4WG3Y1jdC+kSUKk94jI1WycqizszMOHjyIQ4cO0d7k58uXL/j27ZtSKgmECMM0dIcKzp07h5kzZ8LLywtz5swp83zh59DK2gR2NY1KOAJRUVF49eoVhg0bRquN6gYJE4jh5yZFdnZ2uHv3LvLy8tC5c2fExcXRskZFLT2qqnA4HISFhSkkqZRQREB4PLpvDsGDuKJyM0mhNAAAo+gS9vB9GrpvDkFAeFFPjsLCQsyZMwcjR47E4MGD8ejRI6XEwctLjRo1AKC4pFkSI0eOxLp167B69Wrs27ePNhuEN2Rl5VEAQM2aNWFlZUWrM/Dw4UOMHDkSQ4cOxYYNG+SeLzAwEIaGhpU6RACQnQGRcLlcZGVllVAfbNiwIe7evQs2m43OnTvjzZs3EmaQnp9Lj+T9f1ngalspS17UBWdnZxQWFuLhw4eqNqVSsj04Bt5nIsHlCcp2An6BL6DA5QngfSYSvuefwsXFBTt37sT27dtx+PBh6Oqqt4MsVEz8+vWrVOfPnz8fM2bMwLRp03D58mVabAgPDy++OSsTOsWH3r59i/79+6Nt27Y4fPgwLbkPgYGBGDBgQKUOEQBkZ0Ak4qSIra2tcefOHZiYmKBLly549uwZLetN5zSA2burAL8QLBn/W1hMBrTYTPgNtoeni/o++VQGmjZtCjMzM6I3oAACwuOx4frbsk+Ugr2PvuIj2wohISHw9PRU62uNEE1NTZibm0vtDDAYDPj7+6N///4YPnw4LbX6iu5UKA4HBwc8fvwYAoF8iqlJSUno3bs3qlWrhvPnz0NbW7JCqzS8evWqSoQIAKJAKBJJUsSWlpYICQmBtbU1XFxc8OjRI7nX27p1K54Gbsd6Z0N0aFC0pqylR2RHQPEwmUzSp0ABfErLxfILojtwAgDFK0TGg5NI2DcNH9e74ZP/SCSd/hPcb7FiBlDQ7TQOtWxbKMhixVCjRg2pwgRCWCwW/v33X7Ro0QJ9+/aVK3wpEAjw+PFjlTgDjo6OyMzMxNu35XcGc3Jy0K9fP+Tm5iIoKAimpqa02FZVQgQACROIpKwmRWZmZrh16xaaNWuGHj16yJVU9ubNGyxevBizZs3C8L7dSpS8WOiU/r8SV3pEUA4cDgePHj1CXl6eqk2pNPicjQRPTFiAEvCRFLgC3+8cLmrrzS+EID8LeTGP8O3IAuR9eFZ6EIMBHlU0b0XC0tJS6p0BITo6Orhw4QKMjIzQq1ev4gcZWYmNjUVGRoZSkweFtG1bVLtf3rwBHo8Hd3d3vH79GleuXEHdunVps+3kyZMYMGAALbsM6g4JE4hAmo6FRkZGuHr1Ktq1a4fevXsjKChI5nV4PB7Gjh0La2trrFmzpvj3wpKX36vF4+vWkbgwvT3OTuuAyzM74eWKngiZ74IVA+xI+aAKcHZ2RkFBAUJDQ1VtSqUgJjELd2NTxOYIZD29jPyPzwEAGtXqoJqbD4w6jCg6yC9E6mV/ULzSNfd8AYW7sSmITao4zaXK4wwARTuYV69eRUZGBgYMGFAuR1UYsxfemJWJsbExbGxsyuUMUBQFT09PBAUF4dSpU1IpUEpLVQoRAGRnQCQpKSnQ1tYuM+lIT08PFy9ehKurKwYOHIjTp0/LtM7atWvx5MkTsQlOsbGxqFvLEs1rm4oseSEon2bNmsHU1JSUGNLEsdB4iSGx7IgfTrZZr5nQte0A4y5joF2vNQCAn5WC3FjRyWcsJgNHH8XTa7ACKa8zAAD169fHpUuX8Pz5c4waNQp8Pr/sQT8RHh6Ohg0bwsTEpFzry4tQfEhW1qxZg71792Lfvn3o2bMnrTYFBgbCwMCgSoQIALIzIBJhWaE0Nmpra+PUqVMYMmQIhg8fjiNHjki1RkREBFauXInFixfDyclJ5DkxMTFqXQ5VFWEymejcuTPJG6CJ4OgksbsC/LysotAAADDZ0LS0KT6mZdWk+DX3s+h8A76AQvBbyXX76oQwZ6C8D0sODg44efIkzp8/jzlz5sg0j7I6FYrDwcEBz549Q0FBgdRjDh8+jD/++AMrV65UiFCSUGioKoQIAJJAKJKfNQakQUNDA0ePHsX48eMxbtw47NmzR+L5XC4XY8eOhZ2dHZYtWyb2vNjYWOIMqCHOzs54+PAh8vPzVW1KhSaby0O8CKEgIbyMxOLXLB0DMJisHz/rGf0473sixBGfmltCulidsbS0RF5enly9B/r27Ytdu3Zh+/bt2Lhxo1RjCgsLERERoZLkQSEODg7gcrl4+fKlVOffuHEDEydOxMSJE7F06VLa7Xn16hWioqKqTIgAIGECkcjqDABFmb379u3DzJkzMXXqVIlfxGXLliE6OhqHDx+GpqamyHP4fD7evXsHGxsbkccJqoPD4YDL5Sq821pl52NqTillwZ+hCn9ytlglw2MMJlv0eb/OAeBDasVoLmVpaQlAeq0BcUyZMgVLlizBggULEBAQUOb5L1++RH5+vkqdgVatWoHFYkn1nXr+/DmGDBmCHj16YNeuXQrZZa5qIQKAhAlEIpQilhUmkwl/f3/4+Phg/vz5WLlyZSnH5/79+1i/fj1WrVqF5s2bi53r8+fPKCgoIDsDakjz5s1hbGxM8gbkpIAnua6cofFje5bil0wSpAQ8keeVZx11gS5nAABWrVqFsWPHYty4cWX+nYaFhYHFYtGafCcrOjo6sLe3LzOJMD4+Hn369IGNjQ1OnjwJDQ3RnVvlRSg0VFVCBICKGhVVhJ2B1q1bl2ssg8HAX3/9BX19ffj4+CA7Oxvr1q0Dg8FATk4Oxo0bh3bt2mHBggUS54mNLaqhJjsD6geLxSJ5AzSgyZb8LMI2ql78WpCXBUrALw4V8LN/dBFlG1cvNVaWddQFWSSJy4LBYGDfvn34+vUrBg0ahPv378POTrT0eXh4OJo1a6ZylUZHR0eJ6p7p6eno3bs3NDU1cfnyZejr6yvEDmGIwNfXVyHzqytkZ0AE5QkT/MrixYuxZcsWbNiwAdOnT4dAIMDChQvx9etXHDp0CCwWS+L4mJgYsFgs1KlTRy47CIrB2dkZDx48AJfLVbUpFZa6ZnqlWsf+DEvHABpm/+9kJ+Cj4OsPURpuwg85cK1a4vt7MP6/TkXAwMAAenp6tOwMAEWqhqdOnULdunXRu3dvfPnyReR54eHhKg0RCHFwcEBUVBRyckqHdbhcLtzc3PDt2zdcvXq12HFSBFUxRACQBMJS8Pl8pKWl0dLrfNasWThw4AD27NmDnj17YufOnVi3bp1UT/uxsbGoW7euwrbBCPLB4XCQn59Pe7e1qoSeFhvWZQhm6bfqXfw6NWgbcqMfIP3OEeS/jwAAsAzModtQfBa8tZluhSrHlae8UBSGhoa4cuUKAKBPnz6lkhNzcnLw8uVLlVYSCHFwcIBAIMDTp09L/F4gEGD8+PF49OgRLly4AFtbW4XaURVDBABJICxFeno6BAKB3DsDQiZMmIB9+/bh5s2bsLCwwMSJE6UaFxsbS0IEakzLli1haGhIQgVy4mJrIVFnwKB1X2jXKZIVLkyJR/JZX2Q+OFF0kKUBs75zwGCLdphZTAZcGlnQbrMiodsZAIo6AwYFBSE+Ph5DhgwpUb4XEREBgUCgFjsDdnZ20NHRKeVge3t748SJEzh27Bg6duyoUBtev35d5aoIhJAwwS9Ioz4oKyEhIdDR0cH3798xePBgqRTCiMaAeiPMGyBJhPIxyslaYodCBpMFi2ErYNxlLNhmtQCWBpjaBtBp6IQaY9ZDp25LsWP5Agqj21Wsnh2y9ieQFjs7O5w7dw537tzBpEmTih/IwsPDoaOjIzafQJmw2Wy0bt26REXBtm3bsH79evj7+2PIkCEKt0EYIqBbwKgiQHYGfoFuZ+Ds2bM4cuQIdu3ahUuXLiEkJAR9+vRBVpZ4mVSBQEDKCisAHA4HDx48kEkohVASm+oG6NzQXOLuAIOtAaMOw2E1eTfqLDiL2nOOw2LoUmjVEO8ss5gMdG5oXuEkuxWxMyCEw+Hg8OHDOHLkSHFtflhYGFq1aqU24UgHB4finYGzZ89i9uzZmDdvHmbNmqWU9atSL4JfITsDvyCpY6GsJCUlwcPDAwMHDsTYsWPRo0cPXLt2DU+fPkWPHj2Qnp4uctznz5/B5XLJzoCa4+zsjNzcXFrax1ZlfN3swS6jS6essJkM+LrZ0zqnMlCkMwAAI0aMwIYNG/DXX39hz549apM8KMTR0RFxcXEICgrCb7/9hmHDhmHdunVKWbsqhwgAkkBYiuTkZLBYLLk1uimKwtSpU0FRFPbu3Vvs/HTq1Am3bt1CTEwMXFxckJRUWi6VlBVWDFq1agUDAwOSNyAntU11sXIAvdvUqwbYVchunjVq1EB6erpCq1Tmzp2LWbNmYfr06Xj37p1aJA8KETomI0aMgKOjIw4dOgQmUzm3qaocIgCIM1CK5ORkmJmZyf0HePToUZw9exZ79uyBhUXJJKa2bdsiJCQE3759A4fDKVXyExsbS8oKKwBsNhudOnUieQM04O5gjfmujWiZa4GrLUY4VKxcASFC4SFF5A0IYTAY2LRpE9q3bw8AYlVQVYG+vj6YTCa0tbVx7tw5pW7XBwYGon///lUyRACQMEEpyqs++DOfPn3CzJkzMXr0aAwePFjkOc2aNcPdu3eRk5ODzp074/3798XHYmJiUKdOHbX6khJEw+FwcP/+fRQWlm6jS5CNGS42WDvYHlpspsQcAlGwmAxosZnwG2wPT5eKG16jU4VQEiwWC926dQOLxSreIVA12dnZ6NevHzQ0NNC8eXOldlB8/fo1Xr58ieHDhyttTXVD6c6AOicPAvILDlEUhYkTJ0JfXx9bt26VeK6NjQ3u3r1bnJkeHR0NgJQVViScnZ2Rk5ODJ0+eqNqUSoG7gzVuenHQob4ZAJTpFDD+392gRQ1t3PTiVNgdASHKcgYA4NmzZ+jUqRNMTEzQq1ev4uRpVcDj8TBixAhER0dj9OjRePnypVLvFVU9RACQnYFSyOsM7Nq1Czdu3MCBAwek8mzr1KmDO3fuwMjICF26dMGLFy9IWWEFonXr1tDT0yN5AzRS21QXRyY64cacLhjjVAd1zHRLKRUyANQx08VoR2sUnFsKsxfHK2SOwK+YmZmBzWYrNEwAFD20hIWFoWPHjrh69SoyMzMxYMAA5OaK7yKpSFumT5+O69ev4/Tp0+jfvz8SExPx+fNnpdlQ1UMEAABKyQgEAgoAdeDAAWUvLRUtW7akpk2bVq6xMTExlK6uLjV16lSZxyYnJ1OtW7emTExMKE1NTcrf379cNhCUT8+ePanevXur2oxKTXZ+IfXyy3fq6cc06uWX71R2fmHxMT8/P0pTU5P68uWLCi2kDysrK2rp0qUKXePTp08UAOrs2bMURVFUeHg4paenRw0cOJDi8XgKXftXVq9eTQGgDh48SFEURSUkJFAAqNOnTytl/VevXpX4v1A1T548oQBQT548Ueq6JEzwC+XNGeDz+Rg/fjxq1KiB9evXyzze3Nwc//33Hxo0aICCggKphIkI6gGHw8Hdu3fB4/HKPplQLvS02LCraYRW1iawq2lUQmLYw8MD2tra8Pf3V52BNKLo8kIAxbX8wkqCtm3b4uTJk7h06RJmzZqltOv0wYMHsXTpUqxevRrjxo0DUPT+rayslNYiPDAwEPr6+ujVq5dS1lNXSJjgJyiKKneYYOPGjXjw4AEOHTpU7m5aRkZGWLlyJQBgxYoVuHr1arnmISgXZ2dnZGdnIyIiQtWmVEmMjIwwffp07N69G9+/f1e1OXKjDGcgLCwMNWvWRM2aNYt/16dPH+zevRs7d+4s1wONrFy/fh2TJ0/G5MmT8ccff5Q49rP4kKKpqr0IfoXsDPxEdnY2uFyuzM5AZGQkli5divnz56NTp05y2fDlyxcwGAx069YNAwYMwNmzZ+Waj6B42rZtC11dXVJiqEJmz56NgoIC7N69W9WmyI2iJIl/RpzY0KRJk7Bs2TIsWrQI//77r8LWf/bsGYYMGQJXV1fs3Lmz1MOho6MjHj9+DIFAoDAbAODNmzd4+fJllRUa+hmyM/AT5VEfLCgowNixY2FjY4NVq1bJbUNMTAzq1q2Lc+fOwc3NDcOGDcPRo0flnpegODQ0NNChQweSRKhCatSogXHjxsHf3x/5+fmqNkcuFL0zIBAIEB4eLlZsaMWKFRg/fjzGjx+P4OBg2tf/+PEj+vTpg8aNG+PEiRNgs0t3lXRwcEBmZibevn0rYgb6EIYIqnIVgRAiOvQT5elLsHr1arx8+RKHDx+mZZtJWFaooaGBf//9F2PHjsXYsWOxd+9euecmKA5nZ2fcvXsXfD5f1aZUWebPn4+kpCQcOnRI1abIhaWlJRITExX2txQTE4PMzEyxMsQMBgN79+6Fi4sLBg0ahMjISNrWTk9PR+/evaGtrY1Lly6JDam2bdsWABQeKhBWEejo6Ch0nYoACRP8hKzOQFhYGNasWYOlS5eidevWtNjwc1khi8XC/v374enpCQ8PD2zevJmWNQj0w+FwkJmZiWfPnqnalCqLjY0Nhg4divXr11dop8zS0hJ8Pr94p5JuhDdY4Q1XFBoaGjh16hTq16+PPn360FLml5+fj0GDBiEpKQlXr15F9erVxZ5rbGyMRo0aKTSJ8M2bN4iMjKzSQkM/Q8IEAHK4PEQlZCAiPh0aFvWgY2Bc5pi8vDyMGzcOrVq1wuLFi2mxQ9it8GeNASaTia1bt8Lb2xtz587F6tWr1dqhqqo4ODhAR0eH5A2omEWLFuHdu3c4ffq0qk0pNzVq1ACgOEnisLAw2NjYlKmDYmBggCtXroDJZKJPnz7IyMgo95oCgQDjxo1DWFgYLly4gEaNypaeVnQSIQkRlKR0sEbBqMuNLCYxC8dC4xEcnYT4tNz/65iZoOaEbWjtGwxrU1242FpglJM1bKqXboPq4+OD9+/fIyIigrb2n1+/fkVeXl4p9UEGg4E1a9bAwMAAf/zxB7Kzs7F27Vq1cqiqOlpaWmjfvj1CQkIwb948VZtTZWnTpg26desGPz8/DBs2rEJ+R35WIWzRogXt88vSqdDS0hJXr15Fhw4dMHjwYAQFBZVLJn3hwoUIDAzE6dOn0aFDB6nGODg44NSpUygoKFCINDsJEZSkyu0MfErLxZgDoejhfwdHQj/iY7Ej8AMKwMe0XBwJ/Yge/ncw5kAoPqX9UOa6ffs2/P39sWbNGjRp0oQ222JiYgBArPqgj48PNm/ejHXr1mHGjBkKz7QlyIazszPu3LlTobeoKwPe3t54+vQpbt26pWpTyoVw+1wRSYSFhYWIiIiQqVNhkyZNcOHCBdy7dw8TJkyQ+YFuy5Yt2LhxI7Zu3Qo3Nzepxzk6OoLL5dKasyBEGCIgVQQ/qFIJhAHh8ei+OQQP4lIBAHyB5D9q4fEHcanovjkEAeHxyMzMxPjx49GlSxfMnj2bVvtiY2PBZDJRr149sefMmTMH+/btw65duzBhwgQidKNGcDgcZGRk4MWLF6o2pUrTrVs3tG7dGmvXrlW1KeVCS0sLpqamCgkTREZGgsvlSr0zIKRz5844evQojh07VkoTQBKnT5+Gl5cXFixYgBkzZsi0ZsuWLcFmsxUSKiBCQ6WpMgmE24Nj4H0mElyeoEwn4Ff4AgpcngDeZyLhtmQ3UlNTcfDgQdr7bMfExMDa2hpaWloSz5s0aRKOHTuGo0ePYuTIkSgoKKDVDkL5cHR0hLa2NkJCQkrkoUQlZCCHS5w2ZcFgMLBo0SLcunWrwjaQUlR5YXh4OFgsFlq2bCnz2GHDhmHTpk1Ys2YNdu3aVeb59+/fx6hRozBixIhyOWY6Ojqwt7dXmDNAQgQlUXrOgBBlhgkCwuOx4To99arv9OwwdsVuiU/v5SU2NlbqBkUjR46Erq4uhg8fDjc3N5w6dYr8YauYTxmFsBnhg52fLLBlxbUS4ScGUGYeCoE+hgwZggYNGsDPzw8nT55UtTkyo0hnwN7eHrq65Wvq5OXlhfj4eMyYMQNWVlYYMGCAyPPevHmDAQMGoF27dnI9ODk4OODBgwflGiuO6OhoREZGFqu9Eoqo9AmEn9JysfxClMhjBd/eIefNXXA/vQQvIwn83EwwtXShVdMWhu2GQLt2s9KDKAo3v5viU1ou7V3SYmNj0bFjR6nPHzhwIC5evIhBgwahb9++uHDhQrmlkAnl51NaLnzORuJubAoYlq1AleqxVzIP5eDDD+jc0By+bvaVotOeOsJisbBgwQJMnz4dMTExFa4luKWlJeLi4mifNywsDO3atZNrjo0bN+Lz589wd3dHcHAwnJycShz/9u0bevfuDUtLS5w7d67MnU5JODg4YP/+/cjJyYGenp5cdgshIQLRVPoEQp+zkeCJCQtkPQtC5qNT4H55A352GiDgQZCXibx34Uj81we50SI8UgYDPAEFn7P0JrVQFCXTzoAQV1dXXLt2DY8fP4arq2ul0GavSPyahyLKEfgZUXkoBMUwbtw4VKtWDRs2bFC1KTKjCEninJwcREVFyZwv8CtMJhNHjhxBmzZt0K9fP8TGxhYfy87ORt++fVFQUIArV67A2NhYrrUcHR0hEAjw9OlTueb5mZMnT5IQgQgqdQJhTGIW7samSMwRYOmZwLDDCFgMXwnzAQvANq1VdIASIO3WfpFj+AIKd2NTEJuURZutX79+RW5ubrmeYDp37oxbt24hOjoaLi4uxeJJBMVCVx7K9uAYBVlYtdHW1sbs2bNx6NAhhWv9040wTEDnTmpERAQEAoFMlQTi0NbWxvnz52Fubo5evXohOTkZhYWFGDZsGGJiYnDlyhVYW1vLvU7Tpk2ho6NDm/iQMERAqghKU6kTCI+FxoPFFP+kpmfngppT98Gkyxjo1G8DvaYcVBu4sPg4PzMJ/JzvIseymAwcfUTfU11ZZYVl4eDggNu3byMhIQEcDgcJCQm02UYoDZ15KBuuv8UJskOgEKZNmwZNTU1s2bJF1abIhKWlJXJzc5GVRd8DR1hYGHR0dGBnZ0fLfKampggKCkJOTg769u2LyZMn4+bNmzhz5gxt+ghsNhutW7emLYmQhAjEU6nDBMHRSRKf2LRr24GpUbKfANu0ZomfGRqi4118AYXgt0nyG/l/YmNjwWAwUL9+/XLPYW9vj7t37yIrKwudO3fGhw8faLOP8ANJeSjcL2+QdOYvfN4+Fh/XDUT8hiFIOOCJ73eOQMDNFTkGAJZdiCqhZUGgB2NjY0ydOhU7d+6US0FP2fwsPEQX4eHhaNWqlcjGQOWlbt26uHz5Mp49e4ZDhw5h37596N69O23zA0WhAjqdgX79+pEQgQgq7c5ANpeH+HJcXH/OE9CqZQempvg/mvjUXNpKxmJjY6UqKyyLRo0a4e7du2AwGOjcuTOio6NpsY/wA3F5KPkfX+DbsUXIe/vw/zkofFA8LgqTPyLjwQkknlgq9u9fEXkohCLmzJmD/Px87NmzR9WmSI0iJInDwsJoCRH8yvPnz1FYWAgGg4GwsDDar/EODg6Ii4uTu1dDdHQ0Xrx4QXoRiKHS7gx8TM0ppSxYFtxvsUi78f8LBksDJt0nSzyfAvAhNadc9v3Kzw2K5KVu3bq4c+cODAwM0KVLFyKCQyOS8lAyn1wEBEXqg9p1msNi+EqYuk4HmEVPYgUJ0ShIfCdyXkXkoRCKqFmzJsaOHYvNmzdXmPbGdO8MpKamIi4uTu7kwV+5du0aJk+eDA8Pj2IxND8/P1rXENr8+PFjueYhIQLJVNoEwgKebFK9+Z+ikHjcBxQ3B2CyUG3AAmjVKPvmLOs64hC2LqaLmjVrIiQkBFZWVnB2dlZ4K9CqgqQ8FIr7wzE0cHCDTv02MGjdB5oWP2lSCMRLFdOdh0L4wYIFC5CYmIgjR46o2hSpMDAwgK6uLm3OgPBGSqcz8PTpUwwdOhS9e/fG9u3bMXHiRKxYsQKLFy/G0aNHaVunQYMGMDExkfsaRkIEkqm0YQJNtvRvLe/9UySdXAaKmwuwNFBt0GLo2krXTEOWdcRR3rLCsqhWrRr+++8/NG7cGN26dcOdO3donb8qIikPRcvavvh1VvhZ5L1/iqynV1CQ9B4AoGFuDc3qDcTOTXceCuEHjRo1gpubW4Vpb8xgMGgVHgoLC4OxsTFt15gPHz6gb9++aNKkCQICAorzEJYtW4YJEyZgwoQJtPWGYDAYcHBwkKuiQBgiIFUE4qm0YYK6ZnplVHwXkRv9AEmnVoEq5IKhoQ2LYcuh20g6UQ7G/9eRl2/fviEnJ0chwijGxsa4fv06HBwc0KtXL1y/fp32NaoKZeWhGDkNhX5zV4DBRP7HF0g6sQxp13cCAh70mnVF9ZG+YLAkJ2/RmYdCKMmiRYsQExODc+fOqdoUqaBTa0DYqZCO625aWhp69+4NXV1dXLp0qYQYEIPBwO7du9GtWzcMHjyYthClsJ1xeR8mAwMDoaenh969e9NiT2Wk0u4M6GmxYV2GulvOm3tIPrcW4PMAMGDUaSQYLA3kf4oq/kfxCsWOtzbThZ6W/Jm58pYVloW+vj4uXbqErl27on///jJdDInG/g/KzENhscE2swJTu7QKZP77CHATyk7mpDMPhVASR0dHuLi4wM/PT21aqUuCrp0BiqJoSx7Mz8/HwIEDkZycjKtXr8LCwqLUORoaGggMDETDhg3Rp08ffPr0Se51HR0dkZiYWO65SC+CsqnUvQlcbC1wJPSj2G3dvNhwgBLG/Cl8D/6n1DlWUw+AbVy91O9ZTAZcGpX+IpQHOsoKy0JHRwdnzpzB6NGjMXToUBw+fBi//fabyHNjErNwLDQewdFJiP+lxXNV1tgvKz8k496/yLh/HABg0KY/jLuMAe/7NySeXAZ+TjqSz62B1eQ9Iv+eZFmHUH4WLVqEXr16ITg4GF27dlW1ORKxtLTE69ev5Z7n8+fPSExMlDtfQCAQYMyYMXj8+DGCg4Ml7mTq6+vj8uXLaN++PXr37o179+7JpUYotD08PFxmMaO3b9/ixYsXWL58ebnXrwpU2gRCABjlZC2zMpy08AUURreTX2ELKHIGateuDW1t7bJPlgNNTU38+++/GD16NEaPHo19+/aVOP4pLRdjDoSih/8dHAn9iI+/OAJASY39Hv53MOZAaKWuj8/OzsaTJ0/w77//4sA+yaVp2c+vFb826jACTC1daFavD91G/88/4fOQF1d2RjQdeSgE0bi6uqJly5a0Z7wrArrCBMLEO3mdgfnz5+PMmTMICAiQqr9BjRo1EBQUhISEBLi5uYHL5ZZ7bUtLS1hZWZUriZCECKSjUjcqsqlugM4NzfEgLlWkU2Dezwvm/bxknpfFZKBDfTM0tKDnqZjOssKyYLPZ+Pvvv6Gnp4cpU6YgJycHc+bMQUB4PJZfiCquny/LifpVY3/lADu4O9DjHCkbiqLw5csXREdH482bNyX+ff78ufi8mtb1oDFyKyBmV4ufl1n8WlCYD5Zw/oK8H7//6bUo6MpDIYhG2N545MiRiIiIQKtWrVRtklgsLS2RmpqKgoICaGpqlnue8PBwWFlZoWbNmmWfLIbNmzdj8+bN2L59OwYOHCj1uMaNG+PChQvo3r07fv/9dxw9erTcHQwdHR3LlUR48uRJUkUgBZU6TAAAvm726L45hNYdAjaTAV83+7JPlJLY2NhSnb8UCZPJxPbt26Gvrw8vLy/cS9fH4wLLcs3FF1DgCyh4n4lESjYXM1zUtztcfn4+YmJiSt30o6OjkZ2dDaAo3tmoUSPY2tpi7NixaNy4MRo3bgxbW1sYGhqCsz4YH8XshGia1ynWEUgL2gZDRzfwvn9Dzpt7P86pLjkURFceCkE8Q4cOhY+PD/z8/BAQEKBqc8Qi1Br49u2bXDr/YWFhcu0KBAYGYt68eVi0aBE8PT1lHt+pUyccO3YMw4YNg7W1NdauXVsuOxwcHLB27VoIBAKpHQoSIpCeSr0zAAC1TXWxcoAdvM/Qp+62aoAdba1nKYpCTEwMRo0aRct80sJgMLB27Vp80a6Le+V0BH5lw/W3qKavhREq3CGgKArJycnFN/mfb/rv378v/vszNzeHra0tWrZsCXd39+Kbft26dSXKtUrKQzHqPArJp/8EKAHyPz5H/sfnJY5r12kB7brin0TpzEMhiIfNZmP+/PmYOXMm/vrrLzRoIL7cU5X8LDxUXmdAIBDg8ePHWLRoUbnG3717F2PGjMHIkSPh6+tbrjkAYMiQIdi8eTPmzJmD2rVrl8upcHBwQGZmJt6+fYvGjRtLNYaECKSn0u8MAIC7gzVSsrm0NJZZ4GpL680uMTEROTk5SgsT/Mzn9DyEC+oC4AMiCjF5GUnIeHgSee8jwM9OBVNDB2yTGtBt1B5G7UVLei67EIUODcxpc5bEUVhYiLi4OJFb++np6QCKdkAaNGgAW1tbDB48uMRTvrm5ebnWHeVkjYMPP4g8ptvQEdVHrUVm6BkUJESDn5cJBosNtklN6DXuDEPHQRL/7unMQyFI5vfff8eKFSuwceNG7Ny5U9XmiIQOSeKYmBhkZmaWq5Lg9evXGDhwIDp06IC///673Nv7QmbPno34+HjMnDkTVlZWGDRokEzj27ZtC6Bop0MWZ4CECKSjyuxHznCxgbm+VnFcXJawASXgQ1tTA6sG2NH+1CvsBa4IjYGy+KGxX/oGlf/5FZICVxQJMf0fAT8LBV+zIMjLFusMCDX2j0ykJ+zx/ft3kU/5sbGx4PGKyhwNDQ2Lb/L9+vUrvuk3aNBA7l4Pv1JWHop2rabQrtVU5nnpzkMhSEZHRwezZ8/G6tWrsXz5clSvLrnCQxVUq1YNLBZLrvJCYYxdeCOVlq9fv6J3796wsrLCmTNnaPserV+/Hp8/f8bIkSPx33//oX379lKPNTY2RqNGjRAeHo6xY8eWef7bt2/x/PlzLF26VB6TqwyVPkzwM+4O1ujYwBw+ZyNxNzYFlIAPBpMl9nwWkwG+gELhp5foUzMXIxzo32oSagwosqxQ5Lr/19gXhSA/Gynn1hY5Agwm9Fv2hE691mCwNcH7/g2FqZ9FjgNKauxLe2MTCAT4+PGjyKf8xMTE4vPq1KkDW1tbuLq6YtasWcU3/Ro1aih1p6ki5KEQymb69OlYu3Yttm7dir/++kvV5pSCyWSievXqcjkD4eHhsLGxkamsLysrC3379gWPx8OVK1fkKgn8FSaTiUOHDsHV1RX9+/fHgwcP0KhRI6nHC8WHpIGECGSjSoQJfqa2qS62DbFFs44zYOY0EMZNOpaqpQdFoY65HlwaWWB0O2uc2PcMK1b4Yc7kMbC1taXVHmFZobK3sYQa+6JuaFnPrxV13QNg1Ok3GHd0l2luocb+igEl+6bn5OQgOjq61E3/7du3xQ1kdHR0YGtrC1tbWzg7Oxff8G1sbEoonakSdc9DIUiHiYkJpkyZgp07d8Lb2xsGBuq3KyOv8JCsYkOFhYUYNmwY3r17h3v37qF27drlXlsc2traOHfuHDp16oTevXvj4cOHIsWLROHo6IjAwECpKiyEIQJdXfK9koYqtTMgZNasWcj+EoOHK8ehdu3ayOHy8CE1BwU8Af5cuQKfoyMQcu+Hjv+8efOwf/9+zJ07F5cvX6bVFmWWFf6MJI39vJifyncoCgkHPMFL/wqmrhH0mnJg3Ok3MNjiv4h8AYUrzz7A4nNIiZv+z+phlpaWsLW1RYcOHTBhwoTim37t2rXljk0qg5/zUCiKksu5pTsPhSA9Xl5e2LZtG/bu3Yt58+ap2pxSyKM1UFBQgGfPnmHkyJFSnU9RFDw8PPDff//h6tWrsLdX3E6VqakpgoKC0K5dO/Tr1w/BwcFSOfsODg4oKChAZGQk2rRpI/a8mJgYEiKQkUrbm0AcZ8+exZEjR7B169Zir1dPiw27mkZoZW2CFnXM8CGmpGystrY2Nm7ciCtXruDKlSu02kN3t0JpKEtjvzD1x007494xFCZ/BMUrAD8zGZmPTiHp9OoynbrEXApeC7xx69Yt6OvrY/To0Th06BBCQ0Px/ft3JCQkIDg4GLt27cLs2bPRs2dP1KlTp0I4AkJ+a2EG3oNDYFJ8sZ0MxcFiMqDFZsJvsD08XZTvDBKKqFWrFkaPHo1NmzbJJYqjKOTZGXj58iW4XK7UZYUrV67EP//8g3/++Ucp6ox16tTBlStX8Pr1a7i7uxfnAEmiZcuWYLPZZYYKAgMDoaurS0IEMlBxrrw0kJSUBA8PDwwcOBBjxowReU6DBg2QlJSErKySfeXd3NzQtWtXeHl5oaCggBZ7FNWtsCzK0tgX5GcXv2Zq68Os31yY9ZtbrLmf/z4CeTGhEtdgMBgIf/MBUVFROHPmDHx9fTF27Fg4OjrCyMiIjrehcjw9PZHz4gZOjrdHh/pmAFCmUyA83qG+GW56cciOgBqwYMECJCQk4NixY6o2pRTyOANhYWFgsVhSCSsdOHAAK1euxJo1a5Ra5tyqVSucPn0aV69ehaenZ5kPGTo6OrC3ty9TfEgoNERCBNJTaRsViVrXw8MDFEVh7969YncmhDXHcXFxJX7PYDDg7++P2NhYbNu2jRabhE6Hsp2BsrTvGWyN4tf6rfpAv1nXon+tfnjZ+R+elbkOn1LN7o8yOHHiBAICArBjxw44NKmPIxOdcGNOF4xxqoM6Zrql6jMYAOqY6WKMUx3c9OqCIxOdSI6AmtCkSRMMGjQI69atg0CgXn0hLC0tkZiYWC67wsPDYW9vX2Y+UlBQEDw8PDBt2rRy6xHIg6urK/bt24e9e/dizZo1ZZ5fVhKhMEQwfLjoiieCaKpMAuHRo0dx7tw5nD59WmKyijCr/927d2jRokWJY/b29pg2bRpWrVqF0aNHy12OpKqywrK071mG1cD7f8UA2+jH/xXb8MdrQUHZ/Qgqq8b+169fMX36dAwbNqxEPNamugFWDLDDCtiVyEPRZDNR10yPKAuqMYsWLUL79u1x/vx5uLm5qdqcYmrUqAEej4fU1FRUq1ZNprHh4eFl9hB48uQJhg0bhr59+2Lbtm0qC9+OHz8enz59wh9//IFatWpJLB10dHTE/v37kZ2dDX390h1CSYigfFSJnYFPnz5h5syZGD16NAYPHizx3GrVqkFfXx/v3r0TeXzlypVgsVj4448/5LZLVWWFdc30RCgL/EDb6kedPC8zWeRrlqHkC1Nl1dinKAqTJk2ChoYGdu7cKfbi+XMeil1NI+IIqDnt2rVDly5d1K698c8qhLKQk5ODqKgoiZUE79+/R9++fdGsWTMcP34cLJb4MmtlsGTJEkyaNAkTJ07EjRs3xJ7n4OAAgUCAp0+fijxOqgjKR6VPIKQoChMnToS+vr5U2/sMBgMNGjQQ6wyYmZlh9erV+Pvvv/HkyRO5bIuNjUWtWrWU/kerp8WGtYQtav0WrhAKEWU/vYLsl8FF/yKCfswh7MQnhsqqsb9//35cuXIF+/fvL7eKIUE98fb2RmhoKO7cuVP2yUpCFmcgh8tDVEIGIuLTcfZ2OCiWptjkwdTUVPTu3RsGBga4ePGiWtw4GQwGdu3aBVdXVwwZMgTPnz8XeV7Tpk2ho6OD+2GPi99vVEIGcrg8xMTE4NmzZxg2bJiSra/4VL6r9S/s2rULN27cwLVr16QWz5DkDACAh4dHcRb83bt3y+3YqKqsEJCssa9l1RiGTm7IDD0DQX4WUi9tLHHcsN1QaNYQr+deWTX24+LiMHfuXEycOBH9+vVTtTkEmunVqxeaN28OPz8/cDgcVZsDAMWhSHHlhTGJWTgWGo/g6KRSeim15wZi5vVUdP0YhVFO1rCpXqSjkJeXhwEDBiA1NRUPHz6UOfygSNhsNk6cOAFnZ2f06dMHDx8+LNGXQfh+LafsxZ4UY+zZ9qMJGAOAAYOLar080chBPT6/ikSlDhPExsZiwYIFmDp1KlxdXaUeV5YzwGazsWXLFty/f1+urmeqqCQQMsrJWqKCnonLBJj19YKmpQ0YGlpgaGhBs6YtzPrPg4nzeIlzV0aNfT6fj/Hjx8Pc3BybNm1StTkEBcBgMLBw4UIEBQWJfSpVNtra2jAxMSm1M/ApLRdjDoSih/8dHAn9iI+/Cqeh6P3Ep+XhSOhH9PC/gzEHQvEhOQujR49GREQELl26pLLrjyT09fVx+fJlaGlpoXfv3khPTy/1fvk6JqVaiVMAMikt6LboiQG7wzDmQCg+SSihJpSk0oYJ+Hw+xo0bhxo1amD9+vUyjW3QoAHi4+NRWFgo9pxu3brBzc0NCxYsQE5Ojsz2CcsKVdGTAPihsS+pFE7fvhssx22G9bzTsJ53GpZjN0LfzkXivCwmA50bmlc6jX1/f3/cu3cPBw8ehKGhoarNISiIESNGoE6dOli3bp2qTSnm1/LCgPB4dN8cggdxqQBQpiy28PiDuFR03RiMG3E5CAgIUGrbdFmpXr06goKC8O3bN3T3WCbT+wWj6Lb2IC4V3TeHICA8XtHmVgoq7c7Axo0b8fDhQxw6dEhkxqkkGjRoAD6fj/h4yX9EGzZsQEpKCvz8/GS2Lzk5GZmZmSr1zH3d7MGWUSynLCqjxn5UVBR8fHwwZ84ctdk+JigGYXvjEydO4P3796o2B0BJZ2B7cAy8z0SCyxPI3BuDL6DABxOmvWYi3qCJIkylFVtbW0zceBKpDXqBW8gv1/vl8gTwPhOJ7cExCrKy8lApdwYiIyOxdOlSzJ8/H506dZJ5vFBrQFKoACiqApg3bx7Wr1+PDx8+yLSGKrsVChFq7NNJZdPYLywsxNixY9GgQQO1bGZDoJ8JEybAxMQEGzduLPtkJSCUJA4Ij5e7Dbvwurvh+lucUPMn5oDweJyMLupZ8mtIQFYqwvtVNZUugbCgoABjx46FjY0NVq1aVa45ateuDTabXaYzAACLFy/GwYMHsWDBAgQGBkq9hqrKCn/lZ419eamMGvt//vknnj9/jkePHpGe6FUEXV1dzJw5E2vXrsXy5ctVnmBnaWmJR5ExWH4hqtSxzzsngJ+ZJHF89ZG+0K7TvNTvl12IQocG5mrpvH9KyxX5foVwv7xBRuhpFCREg5+bAQaTDbZJDejatIOh0xAwtUq/J3V+v+pApQsTrF69Gi9fvsThw4ehra1drjnYbDbq1KkjlTOgr68PPz8/nDp1Crdv35Z6jdjYWNSsWVMtOvHNcLHB2sH2YAh4oAR8mcZWZo398PBw/PXXX1i6dKnM/eAJFRtPT08wmUza1EblwdLSErnNBoJX3pbZLNHPfDwBBZ+z9HXepBOfs5Fi32/+xxf4dmwR8t4+LOquKuCD4nFRmPwRGQ9OIPHEUpH3GXV+v+pApQoThIWFYc2aNVi6dClat24t11xlVRT8zG+//YZ27dph9uzZUjXbAFTToEgStQs+4fMeDzTQL3IGqrrGfl5eHsaMGYOWLVvCx8dH1eYQlIyZmRkmT56M7du3Izs7u+wBCoRpYgVN6xYiY+bV3Baj+ii/Ev9Me88sPs7SN4WWZSOR8/IFFO7GpiA2KUvkcVURk5iFu7EpYnMEMp9cBP7/0KJdpzkshq+Eqet0gFnk9BQkRKMgsfS1W13fr7pQaXYG8vLyMHbsWLRq1QqLFy+Wez5ZnAEmk4mtW7fixYsX2L9/v1RjVKkx8CsCgQBeXl5o0bAWbv4xkGjsoyj88+HDBxw5cgQaGhplDyBUOubOnYusrCzs27dPpXa8zDcWu2OnZWkD7dp2Jf4VJv5IfNRv0RMMMTsDQJFTf/SResXSj4XGS3wYobg/qrcMHNygU78NDFr3gaZFvR8nifn/Usf3qy5Umt4EPj4++PDhAyIiImi5eDdo0ACHDx+Wule9g4MDxo8fjyVLlmDEiBEwMTERe66wrFBdVLKOHz+O8PBwhISEgMlkVnmN/eDgYGzZsgWbNm1Ckybqn3VNUAy1a9fGqFGjsGnTJnh6ekJTU1MldkSlAwymdFLBgoJ8ZEf9V/QDkwX9lr0kns8XUAh+m4QVoDeRWB6Co5MkVg5oWdsj/+MLAEBW+FkwWCzw0r+hIKnICdIwt4ZmddGiaOr4ftWFStFJ5vbt2/D398eaNWtou3g3aNAAOTk5SEqSnJzzM2vWrAGXy8WKFSsknpeSkoKMjAy12BnIzc2Ft7c3Bg8ejC5dupQ6XtU09jMyMjB+/HhwOBzMnj1b1eYQVMzChQvx+fNnHD9+XCXrZ3N5+JYlXegRAHKigkFxi4R2dBu1B9vArMwx8am5yOFKv4YiyebyEF+GUJCR01DoN3cFGEzkf3yBpBPLkHZ9JyDgQa9ZV1Qf6StxN0Sd3q86UeHDBJmZmQq5eEtbXvgzNWrUwNKlS7Fjxw5ERYnPhFWHskIhmzZtQmJiolqJrKgSLy8vpKWl4eDBg2AyK4WvTJCDpk2bon///vDz81NJe+OPqTmllAUlkfX0cvFrg9Z9pRpDAfiQKrtwmiKQ6v2y2GCbWYGpXVo/Jv99BLgJ0RKHq9P7VScqfALh3LlzkZqain/++YfWi/fPrYxlYfbs2ahXrx68vLzEOj5CZ0DocKiKhIQErF27FrNmzVK5LerAhQsX8M8//8Df3x9169ZVtTkENWHRokV4/fo1Ll26pPS1C3jSOyD5n6JQmPwBQNFWuba19OJfsqyjSKSxI+Pev/ge/A8EeZkwaNMftb1OwvL3rWDqGYOfk47kc2vA+54o9zpVjQq9M3D58mUcOHAAmzZtQr169coeIAN6enqoXr26zM6AlpYWNm3ahBs3buDChQsiz4mJiYGlpaXKywqXLFkCHR0dLFmyRKV2qAPJycmYPHky+vXrhwkTJqjaHIIa0bFjR3Tq1Alr165VentjTbb0l+isiCvFrw1ay9ZIS5Z1FIk0dmQ/v1b82qjDCDC1dKFZvT50hZ1U+TzkxT2We52qRoXdGUhNTcWkSZPQu3dvTJo0iSarSiJLRcHP9OvXDz179sTcuXPB5XJLHVeHssKIiAgcPHgQK1eulLqbY2WFoihMnToVfD4f+/btU1p7bULFYdGiRXj48CHu3btX9sk0UtdMr1RFjyj4Od+RG30fAMDQ0oVeM8k9RH6lmproaUnzfvl5mcWvBYX5xa+pgrwfv//p9a8w/r8OoSQV1j3y9PQEl8vF/v37FXbxLq8zwGAwsHnzZsTHx2Pz5s2ljqu6rJCiKMydOxeNGzfGlClTVGaHunDs2DGcOXMGu3fvRo0aNVRtDkEN6dOnD+zs7MrVh0Qe9LTYsJaidDf7+TWAX5QUp2/XFUxN6e/uhWkJqFW9Gjp37owVK1bgzp07Ih9ilIE071fTvE7x67Sgbch79xhZTy4h580PR02zunhlV2sz3UqfCF0eKmSY4MSJEzhx4gR27tyJmjVr0mCVaMrrDABAkyZNMGPGDPz5559ISEgo/j1FUYiJiVHpzsCFCxdw+/ZtbNy4EWx21f5SfP78GTNmzMBvv/2GoUOHqtocgprCZDKxaNEiXL58GZGRylWxc7G1AENCWh0l4CPr2dXin6VNHASK6u6HdGgCf39/WFhYYOvWreBwODAxMUHPnj3h5+eH8PBw8PmyKZPKg4uthUSdAaPOo4o7E+Z/fI6kwBVIu7Eb4Bd1mdWu0wLadVuJHMtiMuDSyIJ+oysBFS5M8PXrV0yfPh3Dhw+Hu7s7zVaVpEGDBkhKSkJWVvkUq5YvXw4dHZ0SIkipqakqLSssKCjA/Pnz4erqil69JNcgV3YoisKECROgp6eH7du3q9ocgprj7u4Oa2trpVfejHKyBiVh8zwvNhz8zGQARYp8Gua1pZ6bL6Awq3cLTJ8+HadPn0ZKSgqePn2KVatWgcViYfXq1XB0dISZmRkGDRqErVu3IioqSqG5E6OcrCXqDOg2dET1UWuhY9MOLD0TgMkCQ0MLGhb1YNxlLCyGLRd7f+ELKIxuV7nUUulC6Y+F8vwRURSFSZMmQVNTEzt37qTRKtEIM+zfv3+P5s1LN/ooC2NjY/z111/w8PDA9OnT4eTkVFxJoCpnYMeOHYiLi8PZs2erfGx8165duHHjBq5evSpRJIpAAAANDQ3MnTsX8+bNw59//ok6deqUPYgGbKoboIkx8CqVJ7J+XrdRO9Txlr3SgcVkoEN9MzS0MCj+HZPJRKtWrdCqVSvMnz8fhYWFCAsLw3///Yf//vsPCxYsQEFBASwsLNC1a1d069YNXbt2Rb169Wi7nthUN0DnhuZ4EJcq1inQrtUU2rWayjSvqPdL+EGF2hk4cOAArly5gn379sHMrGwxDXkpj9bAr0ycOBEtWrTArFmzIBAIVOoMpKamYtWqVZgyZQqaNWum9PXViZiYGCxYsABTp05Fz549VW0OoYIwadIkGBkZYdOmTUpdd3YHC5mbiJUFm8mAr5vk8kMNDQ107NgRS5cuRXBwMNLT03Hjxg1MnDgR79+/h4eHBxo0aIB69eph4sSJOHbsWImwaHnxdbMHu4z+KLIizfutylSYBML379/Dy8sLEyZMQL9+spXNlJdq1apBT09PLmeAxWJh69atCAsLw9GjRxETE4MaNWpAX7+0YIaiWblyJQQCAVauXKn0tdUJPp+PcePGwdLSEuvX/6+9+wyI6lj7AP7fQkdAKYoKJlQVe0JUrBiisV80lqiIBmNeu6CCYkREIgKKJWo0xgbG2GOLiT12QSWxXRQQFUQp0jssO+8HL0RD213OFtjn9y2758w8e6+7PGdmnplQZYdDGhA9PT3MmTMHP/30E968eaOwfrvYWiDr3DZO2wwY4SD1uSK6urpwcXHBqlWrcOvWLWRmZuLEiRNwdXXF7du3MWnSJLRq1Qrt27fH7NmzcfToUWRmZkodm0UzXawYwe2WwbJ8XnXSIBYQisViTJ06FcbGxtWuzpcXHo9Xr0WEFfr27YuxY8di8eLFiImJUcriwcePH2PLli1YunQpzMzUewFNaGgobt26hT179iglKSMN2+zZs8EYU+g6E1NTUxQ+PI++RjmctLdooD0nJ40aGhpi+PDhWLduHe7fv4/U1FQcOHAAffr0wZkzZzB69GiYmJjgo48+wqJFi/D7779LfArkeEdLLBxY/YmL0uLq8zZmDWKaYOPGjbh8+TJ27doFAwMDOUZVFRfJAACEhIQgKysLV69eVcoUwaJFi2BhYYG5c+cqvG9Vcu/ePfj5+cHb2xu9evVSdjikATIxMcG0adPw/fffo6BAMdvaCgQCNG/eHFZFsVg9qiO0hPw6jxmv0gafBy0hH8GjOmKWs3x+g8zMzDB27Fhs27YNcXFxePHiBXbu3AkHBwfs27cPQ4YMQdOmTdG7d2/4+fnh8uXLtZYxzna2VenP25io/MjA48ePsWTJEsybNw/OztJtpMEFrpKBNm3awMfHBykpKQpfrHb+/HmcOnUKISEh0NbWVmjfqqSkpASTJ09G27Zt1X6qhNTPggULkJOTgx07diiszxYtWiAlJQXjHS1x3rMfnKzerpuq649kxftOVsY479lPoU/IlpaWmDJlCsLDw/Hy5Us8fvwYGzduhLm5ObZs2YL+/fvDyMgIn332GVavXo2oqCiIRO8fItSQPm9DxmMK3l8zOTkZrVu3xu+//15naZtIJIKTkxNyc3Px119/QUdH8dtkbd26FbNnz0ZRUVG9j0Z++fIlLCws8PHHH+P27dscRVi78vJydO3aFQYGBrh69apaVxAsWbIEa9euRVRUFLp06aLscEgD5+bmhitXriA+Pp6TY9PrMnToUAiFQhw/frzytbjUPPwcmYhLsWlIzCh8bzcCHt5usONsZ4ZJPSxVbhW9WCzG/fv3cfHiRVy4cAFXrlxBfn4+DAwM0L9/fwwYMAADBgxAhw4dKn+3GvLnlVR0dDQ++ugj3L17F926dVNcx0zBXr58yQCw33//vc5rAwICGJ/PZ5GRkQqIrHpnz55lAFh8fHy927p16xbD20Oz2NmzZzmIrm4//vgjA8CioqIU0p+qun79OuPz+ey7775Tdiikkbh//z4DwMLDwxXSn4eHB3N0dKzx/fziMvYwOZtFv8hkD5OzWX5xmULi4kppaSm7ceMGW7lyJXN2dmZaWloMADM1NWXjxo1j27ZtY/Hx8UwsFjPGGv7nrcndu3cZAHb37l2F9qvwZCApKUmiZODu3btMKBSypUuXKiiy6j19+pQBYGfOnKl3W3v37mUAmJOTE2vfvj0rLS3lIMKa5ebmMjMzMzZp0iS59qPq8vPzmY2NDevRowcrK2scPxhENQwdOpQ5ODiw8vJyufe1dOlSZmFhIfd+VEVhYSE7f/488/X1ZT169GACgYABYJaWlmzKlCksIiKCvXz5Utlhck5ZyYBKLiCsmNvt0KED/Pz8FBhVVZaWlhAIBEhISKh3W3FxcWjevDk2bdqEmJgYbN26lYMIaxYUFIS8vDysWrVKrv2oOm9vbyQnJ2PPnj1qv/0y4ZaPjw8ePXqE06dP131xPZmbmyMlJUXhJycqi46ODj799FN89913uHnzJjIzM3Hy5EmMHj0a0dHRcHNzQ+vWrdG2bVvMmjULR44cQUZGhrLDbrAUngwUlIqgYfYhnuUyPHqVg4ISUZVr/Pz8EBcXh/DwcGhqaio6xPcIhUK0adOGk0WEFacVdu3aFdOmTYOfn5/capWfP3+OsLAwLFy4EBYWkm9P2ticPXsWW7ZsQUhICOzsuClTIqRC79690bNnT4UcYGRubo6ysjK1/YNnYGCAYcOGISwsDPfu3UNaWhoOHjyI/v3749y5c/jiiy9gampauXvi6dOnZd5KXh0pZAFh5aKPJ2lIzKxm0UczXTjbm2Fid0ukxd9Hnz59EBQUBB8fH3mHJpGBAwdCX18fR48erVc7PXr0QLt27bBr1y6kp6fD1tYWEyZMkMvWyl9++SUuX76M2NhYta2lz8rKQseOHdGuXTucOXMGfH6D2WOLNCAnTpzAyJEjcf36dTg5Ocmtn5s3b8LJyQn3799Hx460k96/JSUlVW6bfOHCBSQnJ0MoFOKTTz6pXIzYs2dPla6oKigR4Y/rdzFh0mTs2xuOz3t9pLATFuWaDCRlFsL31we4Gv8GAj6v1sMnKt9PeYzmiRdw4+xJCAQCeYUmlRkzZuDGjRu4d+9evdoxNjaGl5cXli5dCgBYt24dFi5ciOjoaHTu3JmLUAH886Oxc+dOTJ06lbN2Gxo3NzecPHkSDx48UOvRESJfYrEYHTt2hI2NzXsr/bn27NkzWFlZ4ezZs/jss8/k1k9jwBhDfHw8Lly4UJkgZGRkQFtbG7169ao8V+Gjjz5S+tShNA/Lts3lVyEht2Rg/+1ELD/xCCIxqzUJ+DcmLoeWhhABIztgvIrUh65Zswb+/v7Iy8uTuTQvMzMTxsbGOHDgAMaOHQsAKCsrQ6dOndCiRQtcvHiRk7I/xhh69uyJ0tJS3LlzR22fho8cOYIvvvgC4eHhcHNzU3Y4pJHbvXs3pk6diocPH8LBgdttdCsUFxdDR0cHe/bsweTJk+XSR2MlFovx4MGDysTg8uXLyMvLQ5MmTdCvX7/KA5c6dOigsN9MWR6W+9iYYJVrR7lsqyyXT73pUhwWH32AEpFYqkQAAHh8AUrLGRYffYBNl+LkEZ7UrK2tUVBQgLS0NJnbqO6AIg0NDaxbtw5//vknjhw5Uu84AWD//v2IjIxEWFiY2iYCqamp+Oabb+Dq6opJkyYpOxyiBiZMmIDWrVvL9awLbW1tGBkZ4fXr13Lro7Hi8/no3LkzPD09cfLkSWRkZODmzZtYvHgxCgsLsXjxYnTu3BktWrTAuHHjKndQlNfA+f7biXBZdxk3Et6u/6jr72TF+zcSMuCy7jL2307kPCbORwb2307E4qMPOGsveFRHpe8gdf/+fXTu3Llec4L79u3DxIkTkZOTU2VL5eHDh+PBgweIiYmp18ZKRUVFaNu2Lbp164Zff/1V5nYaMsYYRo4cicjISDx8+BCmpqbKDomoiXXr1sHb2xsJCQlym5Zq3749Bg4ciPXr18ulfXVVXFyMmzdvVk4rREVFoby8HBYWFpXrDQYMGIDWrVvXu69Nl+Kw5mxsvdtZONAOs525O+eG08mSpMxCLD/xSKJr0w75o+jpncr/bvn1D9AwrvoF8jvxCE7WJko9bcrKygrA26OMZU0G4uLiYGZmVu3ZCmFhYXBwcMCaNWuwbNkymeNct24dXr9+jZCQEJnbaOh2796NkydP4tixY5QIEIX6+uuvsXLlSoSFhcntQLWKLYkJt7S1teHs7Fy55X1eXh6uXLlSOa2wZ88eAICdnV3leoP+/fvDxMREqn72306sNhEoTXmKgsdXUZL0EKKcNJQX5oKvpQutlvYw6DEa2hZVj5xfczYWpvpanD0sczqO7PvrA4gkmBbIf3TpvUSgNiIxg++v3I00yEJfXx/Nmzev114D8fHxNR5QZGtri/nz5yMoKAhJSUkytZ+SkoKgoCDMnj1bKaciqoIXL15g3rx5cHd3x8iRI5UdDlEz+vr6mDVrFrZv3y7Tsb2SMDc3p2kCBWjSpAmGDh2KtWvX4q+//kJ6ejoOHTqETz/9FBcvXsSYMWNgamqKLl26wMvLC7/99htyc3NrbbO2h+W8v39H7q3DKEl+jPL8TEAsgrgoF0VPbyN1ny8Kn9yo9j6/E4+QlFlY788LcJgMxKXm4Wr8m7rnPgpzkHV+OwAeIKh7YKJczHA1/g3i05RbL2plZVWvvQYq9hioybfffgsDAwOZyymXLVsGTU3Neo0sNGRisRhTpkyBkZERNmzYoOxwiJqaO3cuxGIxNm/eLJf2KRlQDhMTE3zxxRfYsmULnjx5gqSkJISHh6NLly44dOgQhg0bhmbNmqFnz5749ttvcfHiRRQXF7/XRl0PywK9pjBwGgezsStgMmIRhM3+NyXBxMi88FO193D5sMxZMvBzZKJER0xmXdgOcVEu9LsMgkCvmURtC/g87L3F/YIJadT39MK4uLhajy42MDBAUFAQfvnlF1y7dk2qtu/du4cdO3bA399f4Sciqorvv/8ef/75J3bv3g1DQ0Nlh0PUlKmpKb766its3LgRhYXcPLG9i5IB1dC6dWu4ublh9+7dSExMRFxcHDZv3gxLS0ts27YNn376KYyMjCp3UDx09lqtD8t6Ds5o+X/b0bSvG3SsPoJe+34wHeld+X55bhrKC7Kr3MflwzJnycClJ2l1jgoUJdxFwaM/IdBvhqb9Ja9/LxczXIqVfSU/F+qTDGRlZSEjI6PO4Xt3d3d89NFHmDdvHsRisURtM8bg5eUFe3t7/N///Z9M8TV0jx8/xuLFizF37lwMGDBA2eEQNbdgwQJkZWVh586dnLfdokUL5OfnIz8/n/O2iWx4PB5sbGzwzTff4MCBA0hNTcW9e/ewevVq6OnpISQkBN+ERoCJy2tsQ9vCAXyN9zdDEjZr+X4/GlrV3svVwzInyUB+iQiJdcxbiEuLkPHH26GzZgNngq+tJ1UfiRmF1W5drCjW1tZITU2V6UtYXVlhdfh8PjZu3Ijo6Gjs2rVLorZPnTqFixcvYs2aNQo5RlXViEQiTJ48GZaWlggKClJ2OITgww8/xLhx47B27VqIRNz+ZpmbmwMALSJUYXw+H506dcL8+fNx4sSJtw+C/f4DHl+6TfTeXSeg1doBfM3qK824eljmJBl4kVGAupYNZl8OR3luGnTb9oauXQ+p+2AAnmcUyBQfF6ytrQFApkWEkiYDAODk5ISJEyfC19cXOTk5tV5bWlqKhQsXwsXFBUOGDJE6rsYgKCgI0dHRiIiIgK6u8ipOCHmXt7c3nj9/joMHD3LabkUyQFMFDUdxOZBWINlIb4WSlHhkntv29j8EGmjq8nWt13PxsMxJMlAqqv2DlmUkIS/6N/C19dHss2/k1o88VSQDskwVxMfHw9TUVOK57NWrVyM/Px8rV66s9bqtW7ciPj4eYWFhnOxe2NDcvXsXAQEBWLJkCT755BNlh0NIpc6dO+Pzzz9HcHAwpxvXtGjRAgCNDDQkkjwsv6s46RFSf/EFKykA+AKYjlgErRa1P0hy8bDMSTKgKay9mfL8LICJIS7Ox8vv3fBi9TC8WD0M5bn/DG282j4Dr3bOqVc/8mRmZgY9PT2ZkoG6Fg/+W+vWreHr64sNGzbgyZMn1V6TmZkJf39/eHh4qOWhJcXFxZg8eTI6duyothUURLX5+Pjg/v37+OOPPzhr08jICFpaWjQy0IBI8xBb9CwaaQf9wEoKAYEGTP+zBLr2ku1tU9+HZU7+un5grAd5P5fy/tePsvB4PFhZWck8TSBt7b+Xlxdat24NLy+vat9fuXIlRCJRnaMHjdW3336L+Ph4lTjmmpDq9OvXD927d+f0eGMej0cVBQ2MpA+xhU9uIO1wAFhZCXga2jAbs1yqKfX6PixzsgOhnpYQls108aKGRYTCpi3R9NOqcx4513+BuPjtgjyDnmOgYVLzTkqWxroKO8qxJrJWFMTFxWHw4MFS3aOjo4O1a9di9OjROH369HtrAmJjY7Fp0yasXLkSzZs3lzqehu7KlSsICwtDcHAwOnSoujMXIaqAx+PBx8cHo0aNwq1bt9Cjh/RrpapDyUDDUvGwXNtUQcHja3hzPARgYgA8GPb+EjyBBoqT/tmkSMvcDjxh9YvEuXhY5uyvq7O9GSIiX1RbXig0MIGBY9Ud4XJvHwf+lwzodxhQ7XbEwNvSCWc7M65ClZm1tTWOHTsm1T3Z2dl48+aNTLsCurq6wtnZGZ6ennBxcal8Al60aBFatWqF+fPnS91mQ5eXlwd3d3f06tWrxlETQlTFyJEjYW9vj+DgYM7OC6EtiRuWuh6WAaAo/vb/EgEAYMi+VLWarNX/7YDQqPqHPy4eljmbhJ/Y3VLqEwolVS5mmNRD+ccZW1tb48WLF1KVC1WMJEizZqACj8fDhg0bEB8fj02bNgEALl68iBMnTiA4OBja2tp1tND4LFiwAOnp6dizZw8EAulKdQhRND6fD29vbxw7dgwxMTGctEkjAw1PZzONd/7Yc4urh2VOTy102xGJGwkZnCYFTFwO8evHWOpkAA8PD6XW0p89exaDBg3C06dPKw8vqsv+/fvx5ZdfIisrC0ZGRjL1O2vWLOzduxcxMTEYMmQIdHV1cf36dbWrIDh9+jSGDh2Kbdu2Yfr06coOhxCJlJSUwMrKCoMGDeJkI6LAwEBs3LixXkeqE8WIi4tDQEAADp65CnMP+WxRDQDnPfvCxqxJvdrgdHn+KteOEEqwJbE0tDSE6Cl8jpkzZ6Jjx444duyY3M6Yross5YXx8fEwMTGROREAgICAAAgEAowfPx737t3DunXr1C4RyMjIgIeHBwYPHoyvv6695pYQVaKlpQVPT0/s3bsXL1++rHd75ubmSE9PR1lZGQfREXl4+vQppkyZgrZt2+LixYtY5++NXlbNJNqyXxoCPg99bEzqnQgAHCcDFs10sWKEA5dNYuXIDji4cwvu3r0LCwsLuLq6om/fvrh16xan/UjC0tISAoFAqmRA2rLC6hgbG8PX1xdXr17F559/ju7du9ervYZo1qxZKCkpwU8//aR2iRBp+KZPnw5dXV2sX7++3m1V7DVAIwOq5/nz55g2bRrs7e1x5swZrFu3Dk+fPsXMmTOxenRnzh+WhXweVrlyU1rOeeH+eEdLLBxox0lbiwbaV57V3LVrV5w7dw5nzpxBbm4uevbsiTFjxiAuLo6TviShoaGBNm3aSD0ywMWRwpmZmeDxeHjz5o3SRkaUZf/+/Thw4AC2bNmCli1b1n0DISrGwMAAs2bNwrZt25CVlVWvtmgXQtWTmJiIb775Bra2tjh58iRCQ0ORkJCAuXPnVq7tksfDcsAIB1g042bnVbns4jPb2RarR3WElpAv9bCIgM+DlpCP4FEdMcu56hP1wIEDER0djd27d+PWrVto37495syZg/T0dK7Cr5W0ew3Ex8fXe2QgMTER69atw5dffok7d+5g//799WqvIXn16hVmzpyJsWPHYvz48coOhxCZzZ07F2VlZdiyZUu92qFkQHW8fPkSM2fOhI2NDY4ePYqgoCAkJCTA09MTOjpVzxKQ18MyF+S2pd94R0uc9+wHJytjAKgzKah438nKGOc9+9X6IQUCAdzd3REbG4vAwECEh4fD2toaq1atksuxoe+SZq+B3NxcpKWl1TsZWLJkCYyMjLB161a4urrC29sbBQXKO6dBURhj8PDwgJaWVr1/QAlRtubNm2Pq1KnYsGEDioqKZG7HzMwMfD6fkgElevXqFebOnQtra2scOHAAAQEBePbsGRYuXAg9vdrr/eX5sFwfct3f16KZLiI8uuPc/L5w694GbYx1q+xUyAPQxlgXbt3b4LxnX0R4dJd42ENHRwc+Pj54+vQpPDw84O/vD1tbW+zcuRPl5TUfF1kfFcmAJEP1FQcU1WeaIDIyEvv27UNgYCCaNGmCNWvWID09ndNdzVTV9u3b8ccff2DHjh0wNjZWdjiE1NvChQuRkZGB3bt3y9yGQCCAqakp7TWgBCkpKfD09IS1tTUiIiLg5+eHZ8+eYfHixdDX15e4HXk+LMuK09JCSRSUiPA8owClIjE0hXx8YKzH2c6CCQkJWLp0Kfbv348OHTogODgYgwcP5nTB2dGjRzF69GikpqbCzKz22s4DBw5g/PjxyMzMRNOmTaXuizGG3r17o6CgAHfv3q2sq1+6dCnCwsIQExODDz74QJaPofISEhLQqVMnTJgwAT/++KOywyGEM+PHj0dUVBRiY2MhFMr229e1a1f06NEDP/zwA8fRkeqkpaUhJCQEW7ZsgaamJry8vDBv3jyJD5+rTVxqHn6OTMSl2DQkZhS+t1MhD283FHK2M8OkHpacVA3UiDVCUVFRrF+/fgwAc3Z2Znfu3OGs7b///psBYDdu3Kjz2sDAQGZsbCxzX/v372cA2IULF957PS8vj5mbm7MxY8bI3LYqE4lErHfv3uzDDz9kubm5yg6HEE5FR0czAOyXX36RuY3BgwezkSNHchcUqVZ6ejrz8fFhurq6rEmTJmzZsmUsMzNTbv3lF5exh8nZLPpFJnuYnM3yi8vk1te/NcpkgDHGxGIxO3nyJGvXrh0DwCZMmMASEhLq3W5ubi4DwCIiIuq81t3dnXXv3l2mfoqKilibNm3YiBEjqn0/PDycAWCXLl2SqX1VFhoayng8Hrt8+bKyQyFELgYOHMi6dOnCxGKxTPdPnTpV5t8WUreMjAzm6+vL9PX1mZ6eHvP19WUZGRnKDkuuGm0yUKGsrIxt376dmZubM01NTebl5VXv/1PNzMyYv79/ndf16tWLTZw4UaY+goKCmFAoZE+ePKn2/fLyctajRw/WqVMnJhKJZOpDFT148IBpamqyBQsWKDsUQuTmwoULDAA7c+aMTPf7+voyS0tLjqMiWVlZzM/PjzVp0oTp6uoyHx8flp6eruywFKLRJwMV8vPzWUBAANPX12dGRkYsJCSEFRUVydRWz549mZubW53XNW/eXKKk4d9SUlJYkyZN2Lx582q9LjIykgFgP/zwg9R9qKKSkhLWtWtX1r59e5n/vyGkIRCLxezjjz9mzs7OMt3//fffM01NTZlHFsj7srOz2YoVK5ihoSHT0dFhCxYsYKmpqcoOS6HUJhmokJKSwmbOnMkEAgGztLRkERERrLy8XKo2Jk6cyHr16lXrNTk5OQwA27t3r9QxTp8+nTVt2lSiEYwpU6YwY2Njuc5jKcq3337LhEIhp2s8CFFVhw4dYgBYVFSU1PcePnyYAWBv3ryRQ2TqIzc3lwUGBrKmTZsyLS0tNn/+fPb69Wtlh6UUapcMVHj8+DEbNWoUA8C6dOnCzp07J/G9fn5+rEWLFrVeU7FIKDIyUqq47t+/z/h8Plu/fr1E17969Yrp6+uzuXPnStWPqomMjGQCgYCtWLFC2aEQohAikYjZ2tqy0aNHS33vtWvXGAD28OFDOUTW+OXl5bHVq1czY2NjpqmpyebMmcOSk5OVHZZSqW0yUOHatWusZ8+eDAAbNGgQ+/vvv+u8Z8+ePQwAy8/Pr/GaAwcOMABSrU8Qi8XMxcWF2dnZsdLSUonvCw4OZgKBgD169Ejie1RJQUEBs7e3Z46OjlJ9bkIauh9//JHxeDz2+PFjqe57+vQpAyDVQwx5+1sTGhrKTExMmIaGBpsxYwZLSkpSdlgqQe2TAcbe/hE+cuQIs7W1ZTwej7m7u7PExMQar6/Iyu/fv1/jNd999x1r2rSpVHGcOnWKAWDHjx+X6r7i4mJmY2PDPvvsswY5hzh37lymra3NYmJilB0KIQpVVFTEWrRowaZNmybVfYWFhQwACw8Pl1NkjUthYSELCwtjzZs3Z0KhkE2fPp09f/5c2WGpFEoG3lFaWso2b97MTE1Nmba2Nlu8eDHLzs6uct3r168ZAPbrr7/W2NbUqVPZJ598IlXfbdu2ZQMGDJDpD/qJEydkSiSUrWJVtaTTIoQ0NsHBwUxTU1PqYWpDQ0MWHBwsp6gah6KiIrZx40Zmbm7OBAIB++qrrzgpMW+MKBmoRk5ODlu2bBnT1dVlxsbGbP369aykpKTyfbFYzPT09NiaNWtqbKN3795swoQJEvf5/fffMx6PJ9E0RXXEYjEbOHAgs7a2ZsXFxTK1oWjZ2dnMwsKCOTs7S72Ik5DGIjs7mxkYGLBFixZJdZ+9vT3z9PSUU1QNW3FxMdu8eTNr1aoV4/P5zN3dncXHxys7LJUm17MJGioDAwMEBAQgLi4Orq6u8PLyQrt27XDw4EEwxsDj8WBlZVXrgUXSHF2clZWF5cuX46uvvkLnzp1lipnH42H9+vV4/vw5J2emK8L8+fORnZ2NXbt2gc+nf4pEPRkaGmLGjBnYunUrsrOzJb7P3NycDiv6l9LSUmzbtg22traYPXs2nJ2dERMTg927d8Pa2lrZ4ak0+gWuRcuWLbF9+3bcv38f7du3x7hx49C9e3dcvny51mQgLy8PKSkpEp9WGBgYiJKSEgQGBtYr3nbt2mH27NkIDAxU+R+J48ePY/fu3diwYQPatGmj7HAIUap58+ahtLQUW7dulfgeSgb+UVZWhh07dsDOzg4zZsxAr1698OjRI0RERMDOjpsjgxs9ZQ9NNCSXLl1iH3/8MQPArKysmIWFRbXX/fXXXwwAu3XrVp1txsbGMg0NDRYYGMhJjJmZmczExIS5u7tz0p48pKWlMTMzMzZ8+PAGueCREHmYPn06a968ucQbbnl5eTE7Ozs5R6XaysrK2K5du5iVlRUDwMaMGUPlljKiZEBK5eXl7JdffmHGxsYMAPPw8GCvXr1675qKzUQk2RDE1dWVWVpassLCQs5i3Lp1q8TJiKKJxWLm6urKTExMWEpKirLDIURlxMbGMh6Px7Zu3SrR9SEhIczAwEDOUakmkUjEIiIimI2NDQPARo0axe7du6fssBo0SgZkVLF638jIiOnq6jI/P7/KE/ZWrVrFjIyM6nzqvXTpEgPA9u3bx2lsIpGIde7cmXXv3l3lFuZVHLB0+PBhZYdCiMr54osvmI2NjUTnjURERDAArKCgQAGRqQaRSMT27dvH7O3tGQA2YsQIFh0dreywGgVKBmQUFxdXWV7o4+PDtLS0mJmZGduyZQubMmUKc3R0rPV+kUjEunbtyrp37y6XofLLly8zAGzPnj2cty2rxMREZmhoyCZNmqTsUAhRSbdv32YA2MGDB+u89vz58wyAWqySLy8vZwcOHGDt27dnANjQoUPZ7du3lR1Wo0LJgIxKS0uZQCCoHNJ78eIFc3d3Zzwej+no6LDevXvX+kd+165dDAC7ceOG3GIcO3YsMzc3rxyxUKby8nLm4uLCWrVqxbKyspQdDiEq69NPP2XdunWr8yHh4cOHDAC7du2agiJTvPLycnbkyBHWoUOHyl1iVXH6szGgZKAePvzwwyq1wX/99RfT1NRkAFivXr2q/WOfl5fHzM3N2bhx4+Qa3/Pnz5m2tjZbsmSJXPuRxKZNmxgAdvbsWWWHQohKO3v2rERbDWdkZDAA7NChQwqKTHHEYjE7duwY69KlCwPAXFxc2PXr15UdVqNGpYX1YG1tXaW80MbGBqWlpVi0aBHy8/Ph5OSEL774ArGxsZXXhIaGIjMzE8HBwXKNr02bNvDx8cHatWtr3RNB3uLi4rBo0SLMnDkTn332mdLiIKQhcHFxQbdu3er8fWjatCm0tLQaVXkhYwynTp2Co6Mj/vOf/6Bp06a4cuUKzp07BycnJ2WH16hRMlAP1e01UPHfrq6uiI6ORnh4OKKiouDg4IDZs2fj77//RmhoKLy8vBRSX+/t7Q0zMzMsXLhQ7n1VRyQSYfLkyWjVqhVCQkKUEgMhDQmPx4OPjw/Onz+Pu3fv1npdixYtGkUywBjDH3/8ge7du2P48OHQ1dXFxYsXcfHiRfTp00fZ4akFSgbqoWJkgDFW+Vp8fDwAwNbWFnw+H25ubnjy5Am+++477N27F46OjuDz+ZgzZ45CYtTV1UVoaCiOHTuG8+fPK6TPd4WGhiIqKgp79uyBnp6ewvsnpCEaPXo0rK2t6xwdaNGiBVJSUhQUFfcYY5VP/YMHD4aGhgbOnTuHy5cvw9nZWdnhqRVKBurB2toa+fn5ePPmTeVrcXFxMDQ0hLGxceVrOjo68Pb2xqFDhyASiVBcXIyPP/4YO3bsQHl5udzjHDduHHr37o158+ZBJBLJvb8K9+7dw/Lly+Ht7U1DfIRIQSAQYNGiRThy5EjlA0Z1GvIuhJcuXULfvn0xcODAypGBa9euwcXFBTweT9nhqR1KBuqhYq/rd6cKKs4k+Pc/ZsYYVqxYgY4dOyImJgb9+vXDtGnT0LlzZ/z222/vjS5wjcfjYePGjYiJicEPP/wgt37eVVJSAjc3N7Rr1w7+/v4K6ZOQxsTd3R2mpqZYs2ZNjdc0xGTgypUr6N+/PwYMGICioiL89ttvuHnzJgYNGkRJgBJRMlAP1SUDcXFx1Z5JcOTIEVy/fh1hYWGwtbXFvn37EBUVBRMTEwwbNgwDBgzAnTt35BZr165dMW3aNPj5+b03kiEvy5cvx+PHjxEREQEtLS2590dIY6OtrY158+Zh9+7dNU4FNKRk4Pr163BxcUG/fv2Qk5OD48eP4/bt2xgyZAglASqAkoF6aNKkCUxNTauMDPw7GSguLoa3tzeGDRsGFxeXytcdHR1x6dIlnDp1CmlpaXB0dMSECRPw7NkzucQbGBgIxhj8/Pzk0n6FGzduIDQ0FAEBAejUqZNc+yKkMZsxYwY0NTWxYcOGat9v0aIF0tPTFTr9J61bt25h0KBB6N27N9LT03H06FFER0djxIgRlASoEuVVNTYOPXr0YJMnT2aMMZafn1/trn/BwcFMKBSymJiYGtspKytjP/30EzM3N2caGhrM09NTorMNpBUWFsb4fL7c9vHOy8tj1tbWrGfPnhJtqUoIqd2iRYuYgYEBy87OrvLeyZMnGQCWnJyshMhqFxUVxQYPHswAMAcHB3bo0CGV2x6d/IOSgXqaOHEi69mnP3uYnM0OXohiGmYfsguX/9kRLDU1lRkYGLA5c+ZI1F5+fj5buXIl09fXZ4aGhiw4OJjTQ4xKSkqYvb0969+/v1y2QZ4xYwbT1dVlsbGxnLdNiDpKTk5mmpqaLDg4uMp7d+7cYQDYnTt3lBBZ9e7evcuGDx/OALC2bduy/fv3UxLQAPAYk+PKtUYsLjUPP0cm4vDNx8hjWu8Nd/EAWDbThbO9GeLP7MZv+35CfHz8exUGdUlLS0NAQAC2bdsGc3NzBAYGYtKkSeDz6z+z88cff2Dw4ME4fPgwRo8eXe/2Kpw5cwaff/45Nm/ejJkzZ3LWLiHqbtq0aTh9+jSePXv23hqcV69eoVWrVjh58iSGDRumxAjfVg/5+/vj2LFjsLW1xfLlyzF+/HgIBAKlxkUkQ8mAlJIyC+H76wNcjX8DAZ+HcnHN//PxeYCYAZYaBfh5/jBYNNOVur/Y2Fj4+vriyJEj6Ny5M0JDQznZxW/YsGF4+PAhYmJioKOjU+/2srKy0KFDBzg4OODMmTM0F0gIh548eYJ27drhxx9/xLRp0ypfF4lE0NTUrPK6Ij18+BArVqzA4cOHYW1tDT8/P0yYMAFCoVAp8RDZ0AJCKey/nQiXdZdxIyEDAGpNBIC3iQAAJJfrw2XdZey/nSh1n3Z2djh8+DCuX78OPT09DBw4EIMGDcK9e/ekbutdYWFhePXqFdauXVuvdirMmTMHBQUF2LlzJyUChHDM3t4erq6uCAkJeW9vEqFQCFNTU6VUFMTExGD8+PHo1KkT7ty5g507dyImJgaTJ0+mRKABomRAQpsuxWHx0QcoEYnrTAL+rVzMUCISY/HRB9h0KU6m/p2cnHDt2jUcPXoUz58/R9euXeHu7o6kpCSZ2rOzs8O8efMQFBSEly9fytRGhcOHD+Pnn3/Gpk2b0Lp163q1RQipno+PD+Li4nDs2LH3Xld0eeGTJ08wceJEODg44ObNm9i2bRuePHmCqVOnQkNDQ2FxEG7RNIEE9t9OxOKjDzhrL3hUR4xztJT5/rKyMvz000/w9/dHTk4O5s+fj8WLF8PIyEiqdnJzc2FrawsXFxf8/PPPMsWSkpKCDh06oH///jh06BCNChAiRwMGDEB+fj4iIyMrv2uff/45dHV1cfToUbn2HR8fj5UrV2Lv3r1o2bIlli5diqlTp9I+Io0EJQN1SMoshMu6yygRiau8V16Uh9zIIyhJfozS13FgohIAgF6HT2EyzLPGNrWEfJz37CfTGoJ35eXlYc2aNVizZg20tbWxbNkyzJgxQ6ov586dO+Hh4YFr166hV69e771XUCLC84wClIrE0BTy8YGxHvS0/hn+Y4xh5MiRiIyMxMOHD2Fqalqvz0MIqV3FIt2LFy9W7t3v9tU0xCS9wfYdu6r9ntZXQkICAgMDER4eDjMzM/j6+mLatGnQ1tbmrA+ifJQM1MFtRyRuJGRUOzVQmpqA17vmVnm9rmRAwOfBycoYER7dOYnx9evXWL58OXbs2IE2bdogKCgIY8aMkajyQCwW45NPPgEAREVF4Wl6AX6OTMSlJ2lIzCzEu5/63SqJid0tcfW3Q/Dw8MDx48cxYsQITj4LIaRmjDF069YNhpZt0d/jW1x6koYXmQV4++1869/fU9vmTWTq68WLFwgMDMTu3bthbGyMJUuWYPr06ZwsOCaqh5KBWsSl5uGz9VdqfL/0TSIyz2yBVqu2KC/MQcH9cwDqTgYqnPfsCxsz2b6o1fnvf/+LxYsX4+TJk3B0dERISAj69+9f5303btxAvyGj0MdrCxKKtOqskqh4vzTxPvrpJOOXnzZx9hkIITVLyizE1B/OIT5fWFmtVJOK72kfGxOscu0o8UhkUlISVq1ahR07dsDIyAg+Pj6YMWMGdHXrN5JJVBstIKzFz5GJEPBrngPXNLFEi4mr0bT/FGiZ20rVtoDPw95b0lcX1KZ9+/Y4ceIE/vzzTwCAs7Mzhg8fjkePHtV6X6JGa1h8sw1PC94OLda1QLLifY3WDog2HypTlQQhRDoV1UzPCt8u0qtrHXPF9/RGQoZE1UzJycmYPXs2bGxscOjQIQQGBuLZs2dYsGABJQJqgJKBWlx6kiZ15YCkysUMl2LT5NJ2v379EBkZiQMHDuC///0vOnXqhK+//hqvXr2qcm1FlYSYLwSPL93mIDy+oN5VEoSQusmzmun169eYN28erK2tsW/fPvj7++PZs2fw9vaGnp4eVx+BqDhKBmqQXyJCYmahXPtIzChEQYl8Dhjh8XgYO3Ys/vvf/yIsLAxHjx6FjY0Nli1bhry8PABvnzTWnI3lpL81Z2NxgEYICOGcvL6nqampWLBgAaysrBAeHo6lS5fi+fPnWLJkCZo04W76kjQMtGagBo9e5WDo99ckvj7vr9PIPLMFgORrBgDgtzm94dDSUKYYpZGdnY3g4GCsX78eTZo0wfxvA7En3aJKlURp2nPkRh5GSUo8yvOzwMqKwdfSg6bZB9DvNBB6Dv1r7IOrKglCyFtyqWYS8PBp6S3s2bwWQqEQnp6emD9/vtSlyaRxoZGBGpRW8+VryP0YGRkhKCgIsbGxGDJkCDbcSENJaVnVeNKeoeDRnxBlvAQrKQDE5RAX5aL4xX28ObkGOTcP1tiHSMzg+yt3+zEQou58f30AUQ3TAuW56ci9dRglSQ8rEwFJFJeJcCxZG15eXnj27Bn8/f0pESCgPSNroClUTJ6kqH4qWFhYYGnw9/izhioJgY4+9DsPgpZFBwj0m0JcnI+828dQkvwYAJB35yQMe46t9t5yMcPV+DeIT8vjtEqCEHUUl5qHq/Fvar5AIISWRYcq1Ux14fEF0LTsDPc5fdGsGX1PyVs0MlCDD4z1IO+99Hj/60fRaquS0LF2hPHgOdDv4AydD7pAr21vNBv4zwmE4tKiWtuWR5UEIeqooVUzkYaNkoEa6GkJYVnH3Le4rBgFj6+h4PE1lKYmVL4uyk2rfF2UU3PFgKWxLqc7hUlK0ioJxsQQ5WUg7+/fK1/TtuxY6z3yrJIgRJ001Gom0jDRNEEtnO3NEBH5osYvpLggB2+Ora7yekniA5Qkvp07Nx4yH/qdXKpcI+Dz4Gxnxm3AEpC0SuJ1+AKUvnryzis86Fh/DOMh8+q8t6JKQhmJDiGNgSKrmeh7SgAaGajVxO6Wcs3MJ/WQ/bAiWb3IKIBMn4jHA/gCQILiEwbgeUaBLL0QQlCP76kU6HtK3kUpYS1smzdBHxuTGs8mEBo1R5vFp6Rut+JsAmUsspO0esH489kQF+dDlPsG+X+dRklyDIribiEtLwPmU9Zx1g8hpKrGVs1EVB+NDNRhlWtHCGtZxCMLIZ+HVa61z73Li6TVC5pmH0LbsiP0OzjDbPxK8ISaAIDSlDiUZSZz1g8hpKrGWs1EVBf9S6iDRTNdrBjhwGmbASMclLYxT11VEuKymuqV/7lLXJxfax/KqpIgpLFozNVMRDXRNIEExjta4k1+CSdbgi4aaI9xjopfK1ChokriRQ2Lk1L2eEKzpT20W7eHwMAU4sIc5EX/VrmpCU+oBQ1ji1r7UFaVBCGNRV3fU+BtNVPR0zsAUG01EwBomdtBaFj9QmX6npJ30b8ECc12toWJvhaWn3gEkZhJtbBQwOdByOchYISDUhOBCrVVSYhLi1Fw/1yNG5g0HfAV+Fo1j2ooq0qCkMamMVYzEdVF0wRSGO9oifOe/eBkZQwAtW4I8u77TlbGOO/ZTyUSAaD2KgmD7q7Q/rArBE1MAIEGIBBCYNgcuu37ofnE1WjSbWitbSurSoKQxqYxVjMR1UUHFckoLjUPP0cm4lJsGhIzCt8rA+Lh7RCcs50ZJvWwVMmted12RNZYJSGriiqJCI/unLVJiDqj7ylRFEoGOFBQIsLzjAKUisTQFPLxgbGeys/F1XYamqzo1EJCuEXfU6IoNE3AAT0tIRxaGqKrZVM4tDRU+UQAaHxVEoQ0RvQ9JYpCyYAaG+9oiYUD7ThpS9lVEoQ0VvQ9JYpA0wQE+28nNooqCUIaM/qeEnmiZIAAeDs36fvrA1yNfwMBn1frj03F+31sTLDKtSMNORKiIPQ9JfJCyQB5T0OvkiBEHdD3lHCNkgFSo4ZYJUGIuqHvKeECJQOEEEKImqNqAkIIIUTNUTJACCGEqDlKBgghhBA1R8kAIYQQouYoGSCEEELUHCUDhBBCiJqjZIAQQghRc5QMEEIIIWqOkgFCCCFEzVEyQAghhKg5SgYIIYQQNUfJACGEEKLmKBkghBBC1BwlA4QQQoiao2SAEEIIUXOUDBBCCCFqjpIBQgghRM1RMkAIIYSoOUoGCCGEEDVHyQAhhBCi5igZIIQQQtQcJQOEEEKImqNkgBBCCFFzlAwQQgghao6SAUIIIUTNUTJACCGEqDlKBgghhBA19//kQWgkULdzVQAAAABJRU5ErkJggg==\n", + "image/png": 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\n", "text/plain": [ "<Figure size 640x480 with 2 Axes>" ] @@ -1282,7 +1282,7 @@ }, { "cell_type": "markdown", - "id": "4b0563c7", + "id": "410e7b3d", "metadata": {}, "source": [ "when drawing to an interactive display. Note that you may need to issue a\n", @@ -1292,13 +1292,13 @@ { "cell_type": "code", "execution_count": 35, - "id": "a102647c", + "id": "62b634c9", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:50.124828Z", - "iopub.status.busy": "2022-12-27T10:11:50.124473Z", - "iopub.status.idle": "2022-12-27T10:11:50.129078Z", - "shell.execute_reply": "2022-12-27T10:11:50.128356Z" + "iopub.execute_input": "2023-01-02T13:06:47.766910Z", + "iopub.status.busy": "2023-01-02T13:06:47.766577Z", + "iopub.status.idle": "2023-01-02T13:06:47.770331Z", + "shell.execute_reply": "2023-01-02T13:06:47.769390Z" } }, "outputs": [], @@ -1308,7 +1308,7 @@ }, { "cell_type": "markdown", - "id": "d9c5131e", + "id": "d67a317b", "metadata": {}, "source": [ "command if you are not using matplotlib in interactive mode." @@ -1317,19 +1317,19 @@ { "cell_type": "code", "execution_count": 36, - "id": "26bd2caf", + "id": "29d6266e", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:50.132031Z", - "iopub.status.busy": "2022-12-27T10:11:50.131728Z", - "iopub.status.idle": "2022-12-27T10:11:50.416679Z", - "shell.execute_reply": "2022-12-27T10:11:50.415878Z" + "iopub.execute_input": "2023-01-02T13:06:47.775156Z", + "iopub.status.busy": "2023-01-02T13:06:47.774865Z", + "iopub.status.idle": "2023-01-02T13:06:48.203569Z", + "shell.execute_reply": "2023-01-02T13:06:48.202634Z" } }, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "<Figure size 640x480 with 4 Axes>" ] @@ -1356,7 +1356,7 @@ }, { "cell_type": "markdown", - "id": "af3fc4c6", + "id": "0d2b3db8", "metadata": {}, "source": [ "You can find additional options via `draw_networkx()` and\n", @@ -1367,13 +1367,13 @@ { "cell_type": "code", "execution_count": 37, - "id": "a97da429", + "id": "0dc65281", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:50.421526Z", - "iopub.status.busy": "2022-12-27T10:11:50.420201Z", - "iopub.status.idle": "2022-12-27T10:11:50.527815Z", - "shell.execute_reply": "2022-12-27T10:11:50.527174Z" + "iopub.execute_input": "2023-01-02T13:06:48.207606Z", + "iopub.status.busy": "2023-01-02T13:06:48.207248Z", + "iopub.status.idle": "2023-01-02T13:06:48.449081Z", + "shell.execute_reply": "2023-01-02T13:06:48.447977Z" } }, "outputs": [ @@ -1396,7 +1396,7 @@ }, { "cell_type": "markdown", - "id": "67ffbe4d", + "id": "7bfd3c65", "metadata": {}, "source": [ "To save drawings to a file, use, for example" @@ -1405,19 +1405,19 @@ { "cell_type": "code", "execution_count": 38, - "id": "4091ed0e", + "id": "251b1df9", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:50.531455Z", - "iopub.status.busy": "2022-12-27T10:11:50.531020Z", - "iopub.status.idle": "2022-12-27T10:11:50.665361Z", - "shell.execute_reply": "2022-12-27T10:11:50.664761Z" + "iopub.execute_input": "2023-01-02T13:06:48.453460Z", + "iopub.status.busy": "2023-01-02T13:06:48.453175Z", + "iopub.status.idle": "2023-01-02T13:06:48.638752Z", + "shell.execute_reply": "2023-01-02T13:06:48.637841Z" } }, "outputs": [ { "data": { - "image/png": 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8LhXBRDlRQUkI+Y+HDx/i559/xuHDh1GjRg0sWLAA48aN4zrbMS8vD/3794e/vz98fX3Rtm1bblmI6pLJZLh9+3bRxp7bt29DJBLB3t6+qPeyRYsW3IaqxySl42BoAvwfJyMhLQsfvkCLAJga6sPZygTDHU1hUU1xPcuEfA0VlISQIg8ePMDPP/+Mo0ePonbt2liwYAHGjh3LfWNDQUEBhg0bhtOnT+P8+fPo0qUL1zxEfSQlJeHSpUu4ePEifHx88O7dO5iYmKB79+7o0aMHunbtqpBRVIlpWVh4KgLXYlOgJRahQPb5l+bCj7c3N8aKfjaoY0hjkwh/VFASQvDXX39h+fLlOH78OMzMzLBw4UK4u7tDR0eHdzTIZDKMHz8e+/btw7Fjx9CvXz/ekYiays/Px40bN4o29kREREBLSwtt27YtWr1s0qSJ4EPVD4clYMnZSEhl7IuF5Me0xCJIxCIsdbPGUHtTQTMRUlJUUBKiwe7evYvly5fj1KlTqFevHhYtWoRRo0YpzRnYjDHMmjULf/zxB/bv348RI0bwjkQ0SGJiYlFx6efnh6ysLNSpU+dfQ9XLOuFgk38M1vpGlznrnK6WmOZsUebrEFJaVFASooHCw8OxbNkynD17Fubm5li0aBGGDx+uNIVkoR9//BHLly/H5s2bMXnyZN5xiAbLzc1FUFBQUe9lTEwMdHR00KFDh6Kd4xYWJSvoDoclYP7JCMEyru5vgyG0Ukk4oYKSEA1y69YtLFu2DBcuXIClpSV++OEHfPPNN0o5PmXNmjWYN28efv31V8ydO5d3HEL+JSYmpuhIyICAAOTl5cHc3LzovHEnJ6cvbmJLTMuCy/pA5EplgmXSlYjhN7sD9VQSLqigJEQD3LhxA0uXLoWPjw8aNmyIxYsXY8iQIdDS0uId7ZO2bNmCyZMn44cffsDy5ct5xyHkizIzM3H16tWi1cvExETo6+ujc+fORY/HTU3/vXI4cmcoQuJSS9Qz+TVaYhHa1DfC/nGOgl2TkOKigpIQNRYcHIylS5fCz88P1tbWWLx4MQYOHKi0hSQAHDhwAKNGjcL06dOxYcMGwTdAECJPjDFERkYW9V4GBwejoKAATZo0KSouq5o3RY9NIXLL4DfbCeYmNFKIKBYVlISoocDAQCxduhT+/v6wsbHBjz/+iP79+3ObrVdcp0+fxsCBAzFq1Cjs2LFD6fMS8jVv377F5cuXcfHiRXh7eyMpKQnVe0yHrk0XQCT897eWWISRjmb4yc1a8GsT8iVUUBKiJhhj8Pf3x9KlSxEUFARbW1v8+OOP6NOnD5fCrKSnfFy+fBm9evVCnz59cOjQIaVeRSWkNGQyGe7evQv3E8+QzuR3SICZkT4C5zjL7fqEfIrydeITQkqEMQY/Pz8sW7YMwcHBaNGiBc6cOYPevXsr/HFxaU/5CA4ORt++feHi4oIDBw5QMUnUklgshlWTZsg4/kqu90lIzUJmrpSOaSQKRd9thKgoxhh8fHywbNky3LhxA/b29jh//jx69Oih8EKyOKd8MADxaVnYHxqPPTeeFZ3y8frZI/Ts2RP29vY4fvy4UgxTJ0Re4lMzIe/HggzAs9RMWNesJOc7EfL/qKAkRMUwxnDx4kUsW7YMt27dQqtWreDt7Q1XV1cuG1g+POUDwFd3rRZ+PCQuFZ3XBeC9/040bNgQ586dQ7ly5eSelxCe8gQcE6QM9yGkEBWUhKgIxhjOnTuHZcuWITw8HG3btoWvry9cXFy47YQuyykfBTIGKWPQcxqLAe3qwMCAdqUS9acjUUw/s6LuQ0gh+o4jRMnJZDKcOnUKzZs3R58+fVC+fHlcuXIF165dQ5cuXbgVk4fDEsp8ZFxh9s3BiTgSliBELEKUWl2j8pD331jR/+5DiCJRQUmIkpLJZDh+/Djs7OzQv39/VKlSBQEBAQgMDESnTp24zmdMTMvCkrORgl7zx7ORSEzLEvSahCib8roSmMr5JBtTI33akEMUjgpKQpRMQUEBjhw5gqZNm2LQoEGoVq0agoKCcPXqVXTo0IF3PADAwlMRRT2TQpHKGBaeEu5cY0KUlbOVCbTE8nlDqCUWwdnSRC7XJuRLqKAkREkUFBTgzz//hI2NDYYOHYo6deogJCQEvr6+aN++Pe94RWKS0nEtNkXQI+OAf3oqr8WmIDY5XdDrEqJshjuaCv73p1CBjGFEK9Ov/0ZCBEYFJSGcSaVS7N+/H40bN8bw4cNRv3593Lx5E97e3mjdujXveP9xMDRBrqsrB25SLyVRbxbVDNDe3Fjwv0daYhHamxvTsYuECyooCeFEKpViz549aNSoEUaNGoWGDRsiLCwM58+fh6OjI+94n+X/OFmuqyv+0clyuTYhymRFPxtIBC4oJWIRVvSzEfSahBQXFZSEKFh+fj527twJKysrjBkzBjY2Nrhz5w7OnDmDli1b8o73RRm5UiTIeeNM4SkfhKizOob6WCrwedvL3KxRR84bfgj5HCooCVGQvLw8bNu2DZaWlhg/fjyaN2+Oe/fu4eTJk7Czs+Mdr1gUecoHIepuqL0p5nS1FORabwL34tnVQ4Jci5DSoLkChMhZbm4udu3ahZUrV+L58+cYPHgwzp07hyZNmvCOVmJ0ygchwprmbAHjCrpFp02VpJ1ESyyCRCzCUjdrPNRphPnz5yMrKws//fQT17FiRDNRQUk0WmauFM9SM5EnlUFHIkZdo/KCzW/LycnBjh07sGrVKrx8+RJDhw7FokWL0LhxY0GuzwOd8kGI8Ibam6JtA2MsPBWBa7EpEIGBfWH8uZZYhAIZQ5v6RljRz+afx9z2S6Gvr19UVP76669UVBKFooKSaJyYpHQcDE2A/+NkJKRl/esRrgiAqaE+nK1MMNzRFBbVSr5bMjs7G9u3b8fq1avx6tUrDB8+HIsWLYKVlZVgXwMvhad8yPOxN53yQTRRHUN97B/niJikdIxctg2vtU0gK2f4359PRvpwtjTBiFam/9nN/f3330NfXx8zZsxAVlYWNm7cCLGY3pwRxaCCkmiMxLSsohWAwnf4H2MA4tOysD80HntuPEN7c+P/XwH4iqysLGzduhW//vorXr9+jZEjR2LhwoWwsLCQw1fDR+EpH/Fy3JhDp3wQTWZRzQBv/Lahp6srVv60rsRPUKZPn45y5cph4sSJRW9utbS0FJSeaDJ660I0wuGwBLisD0RIXCoAfLVPqfDjIXGpcFkfiMNfOGc6MzMTa9euRb169TBv3jz07NkTjx8/xu7du9WqmCzkbGUCLXk9SWMyNDGkx3REc71//x7R0dFo0aIFyutKYF2zEuxMq8C6ZqViv9EaP3489u/fj3379mHEiBHIz8+Xc2pCqKAkGmCTfwzmn4xArlRW4vmJBTKGXKkM809GYJN/zL8+lp6ejtWrV6Nu3bpYuHAh+vbti+joaOzYsQMNGjQQ8ktQGgUFBdB7EYYCeT3zFomxbd5IdOzYEadPn0ZBQYGcbkSIcrp79y4AoHnz5mW6zvDhw3HkyBGcOHECgwcPRm5urhDxCPksKiiJWjscloC1vtGCXGutbzSOhCXg/fv3WLFiBerWrYsff/wRgwYNQkxMDLZu3Yp69eoJci9l5Ofnh+bNm2PBlDGolP1S8FVKLbEIbRsY4U+vdcjPz0e/fv1gaWmJ33//He/fvxf2ZoQoqTt37qBcuXJo1KhRma81YMAAnD59Gt7e3ujbty+ysuQ7Q5ZoNiooidpKTMvCkrORgl5z4cn7qGdjj6VLl+Kbb75BbGwsNm/eDDMzM0Hvo0wePnyIXr16oUuXLjAwMEBoaCjO/zgMEi1hf3xIxCKs6t8UgwYNwvXr1xEaGgpHR0fMmTMHderUwbfffounT58Kek9ClE14eDiaNWsGiUSYPuIePXrgwoULCAoKQs+ePZGeni7IdQn5GBWURG0tPBUBqcBHBEplDPWHLERcXBw2bdqEOnXqCHp9ZfL69WtMmzYNNjY2iIqKwrFjx3Dt2jU4ODgo5JQPBwcH/Pnnn3j69CmmTp2KvXv3wtzcHP3790dQUBAYk/eIdUIULzw8vMyPuz/WuXNn+Pj4IDw8HK6urnj79q2g1ycEoIKSqKmYpHRci00R/MxpkVgLr7WMka1dUdDrKpPc3FysWbMG5ubmOHDgAFatWoWHDx9i4MCB/5prJ+QpH3O7WmGIveknP1a7dm2sWLECiYmJ2Lx5Mx4+fIgOHTqgZcuW2L9/P/Ly8gTJQAhvGRkZePz4MVq0aCH4tdu1a4crV67g0aNH6Ny5M1JSUgS/B9FsVFAStXQwNAFaYvnsFtYSi3Dg5ud3fasqxhiOHTuGRo0aYcGCBRg1ahRiY2MxZ84c6OrqfvJzpjlbYFV/G+hKxCX+89YSi6ArEWN1fxtMdTb/6u/X19eHh4cHIiMj4e3tjapVq2LUqFEwMzPD8uXL8fr16xLdnxBlc+/ePTDG5FJQAoC9vT0CAgKQmJgIZ2dnvHr1Si73IZqJCkqilvwfJwu+OlmoQMbgH50sl2vzEhoainbt2mHw4MGwtrbGgwcPsHHjRhgbG3/1c4fam8Jvdge0qW8EAF8tLAs/3qa+Efxmd/jsyuTniMVidOvWDZcuXUJkZCT69OmDlStXok6dOhg/fjwiIiJKdD1ClEV4eDh0dXXleppW06ZNERQUhLS0NHTo0AHPnz+X272IZqGCkqidjFwpEuQ4eBsAElKzkJkrles9FCE+Ph7Dhg1Dq1atkJGRAT8/P5w7dw4NGzYs0XUKT/m4PMsJIx3NYGak/5+D40QAzIz0MdLRDH6znbB/nGOxBsZ/SePGjbFlyxYkJiZiyZIl8Pb2RtOmTdGlSxdcuHABMhmdCU5Ux507d9C0aVNoa2vL9T4NGzZEUFAQcnNz0b59e9rsRgQhYtTZTtRM5N/v0HNjsNzvc2F6O1jXrCT3+8jD+/fvsWrVKqxbtw5VqlTBL7/8gtGjRwt6ooY8z0n/nPz8fBw/fhzr169HWFgYLCwsMHPmTIwePRoVKlSQ670JKasmTZqgffv28PLyUsj9EhIS0LlzZ2RnZ+PKlStqcTws4YdWKInayZMqZlVKUfcRklQqxdatW2FhYYENGzZg3rx5iImJwdixYwU/nq20p3yUhba2Nr755huEhobi+vXrsLW1xYwZM1CnTh3MmzcPCQnq1/tK1ENmZiYePnwot/7JTzE1NUVQUBAqVaoEJycnahchZUIFJVE7OhLFfFsr6j5C8fHxga2tLSZNmoRu3bohOjoay5YtU8uVO5FIhDZt2uDo0aOIi4vD+PHjsW3bNtSvXx+DBw/GjRs3aOwQUSr379+HTCYTfGTQ19SoUQMBAQGoWbMmOnbsiPDwcIXen6gP1XpFJKQY6hqV/0//ntBE/7uPKoiMjET37t3RrVs3GBkZISwsDHv37kXt2rV5R1MIMzMzrFmzBs+fP8fvv/+Oe/fuoU2bNmjVqhUOHTpE5xwTpXDnzh3o6OigSZMmCr931apVcfXqVVhYWKBTp04ICQlReAai+qigJGqnvK4EpmXc7PE1pkb6CnmEWxZJSUmYNGkSmjZtipiYGJw8eRIBAQFo2bIl72hcVKhQAVOnTsWjR49w7tw5GBgYYNiwYahXrx5WrVqF1NRU3hGJBgsPD4eNjQ10dHS43L9KlSq4fPkybG1t0bVrV/j7+3PJQVQXFZRELTlbmch1DqWzpYlcri2EnJwcrFq1ChYWFjhy5Ah+++03REVFoV+/fv8aTK6pxGIxevXqBT8/P/z1119wdXXFTz/9hDp16mDSpEl4+PAh74hEA8njhJySMjAwgLe3N9q0aYMePXrg0qVLXPMQ1UIFJVFL/WyM5TqHckSrks1OVATGGA4dOoSGDRti8eLFGDt2LGJjYzFr1ixuqx7KzsbGBjt37kRCQgIWLFiA06dPo3HjxujevTt8fHyoz5IoRHZ2NqKiohS6Iedz9PX1cfbsWXTp0gVubm44ffo070hERVBBSdSOr68v+jg7Ii/+PkQQtiDQEovQ3twY5iYGgl63rEJCQtC6dWsMGzYMdnZ2iIyMxIYNG2BkZMQ7mkowMTHB4sWLER8fj3379iEpKQndunWDtbU1tm3bhqws+c41JZrtr7/+QkFBgVIUlACgp6eHEydOoG/fvhg4cCAOHz7MOxJRAVRQErXx5s0bjBkzBq6urjA3N8exef2hIxFyFA6DRCzCin42Al6zbJ4+fYohQ4agbdu2yMvLg7+/P06dOgVLS2HO2NY0urq6GDlyJMLDwxEYGIiGDRti0qRJqFOnDhYuXIgXL17wjkjUUHh4OCQSCZcNOZ+jra2NP//8E8OHD8ewYcOwe/du3pGIkqOCkqiFkydPonHjxjh16hR27NiBy5cvo61tQyx1sxbwLiI0yYlCrcp6Al6zdN69e4d58+ahYcOGCA4Oxp49e3D79m107NiRdzS1IBKJ4OTkhJMnTyI2NhajRo3Cpk2bULduXQwfPhxhYWG8IxI1cufOHTRp0gR6evx/tnxIIpFg9+7d8PDwwNixY+Hp6ck7ElFiVFASlfbq1SsMHDgQAwYMgKOjI6KiojBu3LiizSdD7U0xp6swq3XtK77Bqd/mwt3dnduoGalUis2bN8Pc3Byenp5YuHAhoqOjMXr0aIjF9NdZHurXr4/169fj+fPnWLt2LW7cuAEHBwe0bdsWx44dg1Sq+kdwEr7Cw8OV5nH3x8RiMTZv3ozZs2dj2rRpWLt2Le9IREnRKxBRSYwx7N27F40bN0ZQUBCOHDmCU6dOoWbNmv/5vdOcLbCqvw10JeIS7/zWEougKxFjdX8b7F8wAocOHcLhw4fRt29fZGZmCvXlfBVjDBcuXEDTpk0xbdo09O7dGzExMViyZAnKl1eNeZiqrmLFipg5cyZiYmJw6tQpaGtrY/DgwWjQoAHWrl2Lt2/f8o5IVFBOTg4ePHjAfYf3l4hEIvz2229YtGgR5s6di2XLltGGNfIfVFASlRMfH4/u3bvD3d0dPXv2RFRUFAYPHvzFkThD7U3hN7sD2tT/Z5PK1wrLwo+3qW8Ev9kdMMT+n13dQ4YMwYULFxAYGAgXFxekpaUJ9FV93l9//YWuXbuiV69eqF69Ou7cuYNdu3Z9sngm8qelpYW+ffsiICAAd+7cgbOzMxYuXIjatWtj+vTpiImJ4R2RqJAHDx5AKpUq7QplIZFIhJ9//hm//PILlixZggULFlBRSf5FxOg7gqgImUyGzZs3Y/78+ahSpQq2bNmCnj17lvg6MUnpOBiaAP/oZCSkZv1rH7gI/wwtd7Y0wYhWpp/dzX379m10794dJiYm8PHxkcupM69evcLixYuxa9cumJubY+3atejVqxfNklRCr169gpeXF7y8vJCSkoKePXti1qxZ6NSpE/33Il+0detWTJ06Fenp6ShXrhzvOMWyYcMGzJ49G9OnT8eGDRuo3Yb8gxGiAh49esTatm3LALDJkyezd+/eCXLdjJx89uDFW3YnPo09ePGWZeTkF/tzHz9+zMzMzFidOnVYVFSUIHkYYywzM5MtX76clS9fnhkaGrI//viD5eXlCXZ9Ij/Z2dls586dzMbGhgFgNjY2bOfOnSw7O5t3NKKkJkyYwGxsbHjHKLEtW7YwkUjExo8fz6RSKe84RAlQQUmUWl5eHluxYgXT1dVl5ubmLCAggHekf3nx4gVr0qQJMzQ0ZDdv3izTtQoKCtj+/ftZ7dq1mba2Nvv2229ZWlqaQEmJIslkMnblyhXWu3dvJhKJWNWqVdnixYvZy5cveUcjSqZFixbM3d2dd4xS2bt3LxOLxWz48OEsP7/4b8aJeqKCkiitO3fuMDs7OyYWi9m8efNYVlYW70iflJaWxtq1a8f09fWZt7d3qa4RFBTEWrZsyQCwAQMGsNjYWIFTEl6io6PZtGnTWPny5Zm2tjYbNWoUu3PnDu9YRAnk5uYyHR0dtnHjRt5RSu3o0aNMIpGwAQMGsNzcXN5xCEfU+ECUTk5ODhYtWgR7e3tIpVKEhoZi9erVSttfVKVKFfj6+qJz587o3bs3/vzzz2J/bmxsLAYMGAAnJycAQFBQEI4fP44GDRrIKy5RMAsLC2zcuBHPnz/HihUrEBAQgObNm6NDhw44ffo0CgoKeEcknDx48AB5eXlKvcP7awYNGoSTJ0/i3Llz6NevH7Kzs3lHIrzwrmgJ+VBwcDCzsrJiOjo6bPny5Sr1jjc/P5+NGTOGAWAbNmz44u9NS0tj3377LdPW1ma1a9dm+/fvZwUFBQpKSnjKz89nx44dK+oJrlevHlu/fr1gfcFEdWzfvp2JxWKWmZnJO0qZ+fr6snLlyrFOnTqxjIwM3nEIB1RQEqWQnp7Opk+fzkQiEWvVqhWLjIzkHalUZDIZ+/777xkAtmDBAiaTyf718by8PPb7778zQ0NDVr58efbzzz+rxYsJKZ3Q0FA2bNgwJpFImIGBAZs1axZ78uQJ71hEQSZNmsSsra15xxBMYGAgq1ChAmvbti17+/Yt7zhEwaigJNz5+PgwMzMzpq+vzzZs2KAWOwZ/++03BoCNGzeO5efnM5lMxs6cOcMsLS2ZWCxm48ePpw0apMjz58/ZwoULmaGhIROJRKxv374sMDDwP29IiHqxt7dnI0eO5B1DUDdv3mSVK1dmLVu2ZKmpqbzjEAWiOZSEm7S0NHz33XfYs2cPOnfujG3btqF+/fq8Ywlm//79GDt2LNq2bQsARcPQf/vtNzRt2pRzOqKMsrKycODAAWzYsAEPHz6EnZ0dZs2ahSFDhkBXV5d3PCKg/Px8GBgYYPXq1Zg5cybvOIK6d+8eunTpgpo1a+Ly5cswMTHhHYkoAG3KIVycOHECjRs3xqlTp7Bjxw5cvnxZrYpJAOjcuTOcnZ0RGBiIW7du4ciRI/D19aViknyWvr4+Jk6ciMjISPj4+KBatWoYPXo0zMzMsGzZMiQnJ/OOSAQSFRWF3NxcpT8hpzRsbW0RGBiI5ORkdOjQAS9evOAdiSgAFZREoV69eoWBAwdi4MCBaNWqFaKiojBu3Di1Ok0kMzMTS5cuhYWFBe7evYvvvvsOurq6+OWXX/Dq1Sve8YgKEIlE6Nq1K7y9vREVFYV+/fph1apVMDU1xbhx4/DXX3/xjkjKKDw8HCKRCLa2tryjyEXjxo0RFBSEzMxMODk54dmzZ7wjETmjgpIoBGMMe/fuLfohc+TIEZw6dUqtzqOWyWTYs2cPLC0tsWLFCkybNg2xsbFYu3Ytrl+/jrS0NLRp04bOeiYl0qhRI3h5eSExMRE//fQTfHx80KxZM3Tu3Bnnz5+HTCbjHZGUQnh4OKysrFChQgXeUeTGwsIC165dAwA4OTnRzz41RwUlkbv4+Hh0794d7u7u6NmzJx4+fIjBgwer1aqkv78/WrZsiTFjxqBdu3Z49OgRVq9ejUqVKgH45916SEgI9PT00LZtW4SHh3NOTFSNkZER5s+fj6dPn+LQoUPIyMhA79690bBhQ2zatAkZGRm8I5ISuHPnjlo+7v6YmZkZgoKCUL58eTg5OSEyMpJ3JCInVFASuZHJZNi0aROsra0RGRmJCxcuYP/+/TAyMuIdTTDR0dHo27cvOnXqBB0dHVy/fh1HjhxBvXr1/vN769Spg+DgYNSvXx8dO3bE1atXOSQmqk5bWxtDhw5FaGgoQkJCijbu1K5dG3PnzkV8fDzviOQrpFIp7t+/rxEFJQDUqlULgYGBMDExQceOHXH37l3ekYgcUEFJ5OLx48dwcnLC9OnTMWrUKERGRqJHjx68YwkmLS0Ns2bNgrW1Ne7evYtDhw7hxo0baNOmzRc/z8jICFeuXEG7du3QvXt3HD9+XEGJiTpq3bo1jhw5gri4OEycOBE7duxA/fr1MWjQIISEhICGeCinhw8fIjs7W6VPyCkpExMT+Pv7o169eujUqRNCQ0N5RyJC4zu1iKibvLw8tmLFCqarq8ssLCxYYGAg70iCys3NZevWrWOVK1dmBgYGbOXKlaU6YzwvL48NHz6ciUQitnnzZjkkJZooPT2deXp6MktLSwaA2dvbs4MHD7K8vDze0cgH9uzZwwBo5OlI7969Y+3atWMVKlRQu9cHTUcFJRHMnTt3mJ2dHROLxWzevHmlKrSUlUwmYydPnmTm5uZMLBazSZMmsaSkpDJds6CggM2aNYsBYEuWLKEh1kQwBQUF7Pz588zFxYUBYDVr1mQrVqxgKSkpvKMRxtj06dOZpaUl7xjcZGRksM6dO7Ny5coxHx8f3nGIQKigJGWWnZ3NFixYwLS0tFjTpk1ZWFgY70iCun37NnNycmIAWLdu3diDBw8Eu7ZMJmMrV65kANjkyZPV4pQgolwiIiLY+PHjma6uLitXrhybOHGiyh5tqi7atGnDhg4dyjsGV9nZ2axnz55MR0eHnT17lnccIgAqKEmZBAcHMysrK6ajo8OWL1/OcnNzeUcSTGJiIhs5ciQDwKytrdmlS5fkdq8dO3YwsVjMBg4cyHJycuR2H6K5kpOT2fLly1n16tUZAObq6sq8vb1ZQUEB72gaRSqVMn19fbZmzRreUbjLzc1lAwYMYBKJhB05coR3HFJGVFCSUklPT2fTpk1jIpGItWrVSq1WPNLT09nixYtZuXLlmImJCdu6dSvLz8+X+31Pnz7N9PT0WKdOnTSyt4ooRm5uLtu3bx+zs7NjAFjDhg3Zli1bWGZmJu9oGiEyMpIBYFevXuUdRSnk5+ezESNGMLFYzPbu3cs7DikDKihJifn4+DAzMzOmr6/PNmzYoDaPaaVSKduxYwerXr0609XVZQsWLFB4YRcUFMQqVarEmjdvzl69eqXQexPNIpPJWFBQEOvfvz8Ti8XM0NCQzZ8/nyUmJvKOptb27dvHALA3b97wjqI0CgoK2IQJExgAtmXLFt5xSClRQUmKLTU1lbm7uzMArHPnzuzJkye8Iwnm8uXLrGnTpgwAGzZsGHv27Bm3LPfv32c1atRg5ubmLC4ujlsOojni4uLY7NmzmYGBAZNIJOybb75hoaGhcr9vRk4+e/DiLbsTn8YevHjLMnLk/ySAt1mzZrEGDRrwjqF0ZDIZmzFjBgPA1q9fzzsOKQURYzSojHzdiRMnMHXqVOTk5GDdunUYM2aMWpx08+jRI8ydOxfnz59HmzZtsG7dOjg6OvKOhadPn8LV1RXp6em4dOkSmjVrxjsS0QDv37/Hnj178PvvvyMuLg6tW7fGrFmz0L9/f0gkEkHuEZOUjoOhCfB/nIyEtCx8+AIkAmBqqA9nKxMMdzSFRTUDQe6pTJycnFCjRg0cOXKEdxSlwxjDwoULsWrVKvz8889YtGgR70ikBGiwOfmiV69eYeDAgRg4cCBatWqFqKgojB07VuWLyZSUFEybNg1NmjRBZGQkjh49iuDgYKUoJgGgXr16CA4ORs2aNeHk5ISgoCDekYgGqFixImbMmIHo6GicPn0aurq6GDJkCOrXr481a9bgzZs3pb52YloWRu4MRZcNQdgfGo/4j4pJAGAA4tOysD80Hl02BGHkzlAkpmWV6WtSJjKZDHfv3tWogeYlIRKJsGLFCixfvhw//PADFi1aRMP5VQitUJJPYoxh7969+Pbbb6GtrY1NmzZh4MCBKl9I5ubmYuPGjfj555/BGMPixYsxffp06Orq8o72Se/fv0e/fv2KjnTs06cP70hEw9y7dw8bNmzAoUOHIJFI4O7ujpkzZ8LS0rLY1zgcloAlZyMhlTEUyIr/kqMlFkEiFmGpmzWG2puWJr5Sefz4MRo2bIjLly/DxcWFdxyl9ttvv2HOnDmYNWsW1q1bp/KvPZqAVijJfzx79gzdunXDmDFj0KtXL0RFRWHQoEEq/ReaMYZjx46hUaNGmD9/PkaMGIHY2FjMmTNHaYtJ4J8Vo4sXL8LNzQ39+/fHzp07eUciGsbW1hZ79uxBfHw85s6di2PHjsHKygq9evWCn5/fV1eQNvnHYP7JCORKZSUqJgGgQMaQK5Vh/skIbPKPKcuXoRTCw8MBgFYoi+G7776Dp6cnNmzYgMmTJ0Mmk/GORL6CCkpSRCaTYePGjWjSpAkePnyIixcvYt++fTAyMuIdrUxu3bqFdu3aYfDgwbC2tkZERAQ2bdqEqlWr8o5WLLq6ujh06BAmTZqE8ePHY+XKlfQYiChc9erV8dNPPyEhIQG7du1CYmIiunTpgqZNm2Lnzp3Izs7+z+ccDkvAWt9oQe6/1jcaR8ISBLkWL+Hh4ahbty4MDQ15R1EJU6ZMwe7du7F9+3a4u7tDKpXyjkS+gApKAuCfzSlOTk6YMWMGRo0ahQcPHqB79+68Y5VJQkIChg8fDkdHR2RkZODy5cs4d+4cGjVqxDtaiWlpaWHTpk346aefsHDhQsyePZvesRMu9PT0MGbMGNy7dw9Xr15FvXr1MGHCBJiammLx4sV4+fIlgH96JpecjRT03j+ejVTpnso7d+6gRYsWvGOoFHd3dxw8eBB//vknhg0bhry8PN6RyGdQQanh8vPzsXLlStja2iI5ORmBgYHYvHkzKlasyDtaqb1//x4LFy6ElZUVrl69ih07duDOnTsq37MkEomwZMkSeHl54Y8//sDIkSPphyvhRiQSwdnZGWfPnsXjx4/xzTffYP369TAzM8OoUaMwbd91SEv4iPtrpDKGhaciBL2moshkMiooS2no0KE4ceIEzpw5g4EDByInJ4d3JPIJVFBqsLt378LR0RE//PADZs6cifv378PJyYl3rFKTSqXYtm0bLCwssGHDBsydOxcxMTEYN24ctLS0eMcTzKRJk3D06FEcP34cbm5uyMjI4B2JaDgLCwv88ccfeP78OVatWoWge9G4n5RX4p7JrymQMVyLTUFscrqg11WEJ0+e4P3799Q/WUp9+vTB2bNncfnyZbi5uSErS3VXqtUVFZQaKCcnBwsXLoS9vT0KCgoQGhqK1atXo1y5cryjlZqPjw9sbW3h4eEBV1dXPH78GMuWLUOFChV4R5OLgQMHwtvbGyEhIejcuTNSUlJ4RyIElStXxrfffotRy7dD/J+hQMLQEotw4Kbq9VLeuXMHAGiFsgxcXV2Lfu5169YN6elff2ORmStF5N/vcDfhDSL/fofMXOrDlBdhJtUSlXH9+nWMGzcOT58+xU8//YTvv/8e2travGOVWmRkJObMmYNLly6hffv2CAsLQ8uWLXnHUohOnTohICAA3bt3R7t27eDr6wtTU9UfrUJUX2B0CmSQz1SIAhmDf3QyfoK1XK4vL+Hh4TA1NYWxsTHvKCqtY8eOuHz5Mrp37w4XFxdcunQJVapU+dfv0fTh+bzQCqWGSE9Px/Tp09G+fXtUqVIFd+/exQ8//KCyxWRycjImT56Mpk2bIiYmBidOnEBgYKDGFJOFmjdvjuvXryMvLw9t2rRBVFQU70hEw2XkSpEg540zCalZKrfSFB4eTo+7BdK6dWtcvXoVT548QadOnfD69WsANDyfNyooNYCPjw+aNGmCXbt2Yf369QgODkbjxo15xyqVnJwcrFq1Cubm5jh8+DDWrl2LqKgo9O/fX6XnZJaFubk5rl+/DiMjI7Rr1w43btzgHYlosPjUTDk97P5/DMCz1Ew530U4jDHakCOw5s2bIyAgAC9fvkTHjh2x9XIEXNYHIiQuFQC+2r9b+PGQuFS4rA/EYRUfSaUM6JG3GktLS8O3336LvXv3wsXFBQEBAahXr55c75mZK8Wz1EzkSWXQkYhR16g8yuuW/duMMYYjR45g/vz5ePHiBaZOnYrFixer/IxModSoUQOBgYHo06cPOnfujOPHj6NHjx68YxENlCdVzDirtu07QD87GZUqVULFihW/+uun/l2FChUU8kb06dOnePv2LRWUAmvSpAmCgoLgMnMtVl4tXUFY8L/Tm+afjEBKRi6mOVsInFJzUEGppk6cOIGpU6ciJycHO3fuxJgxY+T2g1Pe/So3btzAt99+i5s3b6JPnz7w9fUt0bFvmqJy5cq4dOkShg0bBjc3N+zevRsjR47kHYtoGB2JYh58TfGYCN3s13j//j3evXtX9OuLFy/+9f+/NAVBLBbDwMCgREXop37V1dX94s9XOiFHfu6804PYVpgjadf6RqNqBV0MUYNjPnmgs7zVzKtXrzB16lScPHkSffv2haenJ2rWrCmXeyWmZWHhqQhci02Bllj0xUcMhR9vb26MFf1sUMdQ/6vXf/r0KRYsWIAjR47A1tYW69atg7Ozs5BfglqSSqWYNGkSdu7cibVr1+K7777jHYlokMxcKZr85CPXx94iAA9+ci3W04+CggKkp6f/q/D8uAgtzq9fmn2ora39xSL0zp07iIqKwqpVqz5bsFasWFFle9p5SUzLgsv6QOQKuCquKxHDb3aHYr1GkX+jglJNMMawd+9efPvtt9DW1samTZswcOBAua1KHg5LwJKzkZD+73FBcWmJRZCIRVjqZo2hn3kX+O7dO6xYsQIbNmyAsbExfvnlF4wcOVKtZknKG2MMP/zwA1asWIG5c+di9erVGttjShSvwxp/xMtxo4OZkT4C5yj2zWVeXl6Ji9HC/x0dHQ2pVAqZTIaCgoLP3qNcuXKlenT/4a8VKlSAWKwZ2yNG7gxFSFyqoPNOtcQitKlvhP3jHAW7pqagR95q4NmzZ/Dw8ICvry9GjhyJ9evXy7W3cJN/TKnP5/1Sv0rhYPIlS5YgKysLCxcuxJw5c1C+fHmhomsMkUiEX375BdWqVcPMmTPx+vVrbN++HRIJ/ZUn8udsZYL9ofGCDzYH/nnBd7Y0Efy6X6OjowNjY+MSj/1hjMHY2BgzZ87E4sWLkZ2d/cXi81O/vnz58l//Pz09HZ9bCxKJRDAwMCjVo/sPf2+5cuWU+k1oTFI6rsUKP3/3w+H55iY0Uqgk6NVFhclkMnh6emLBggUwNDTExYsX5X7+9uGwhFIXkx8r7FcZ3LIOvL29MWfOHDx69AijR4/Gzz//jFq1aglyH002Y8YMGBsbY/To0UhJScGRI0egr0+Pcoh8DXc0xZ4bz+Ry7QIZw4hWqtPjFh8fj7S0NDRv3hwikQj6+vrQ19dH9erVS31NmUyGjIyMEq2WpqWl4enTp//6d186bUYikRS7GP3Sx3R0dEr9dX7JwdCEr7ZalVbh8Pyf3FRr1ilv9MhbRT169Ajjx4/H9evXMWXKFKxcuVLu52/Lo19FR0uEWvd2IeDCCXTs2BHr1q2DnZ2dYNcn//Dx8UH//v1hZ2eHc+fO/WcQMCFCo8eR/zh58iQGDBiAv//+GzVq1OAd51/y8/ORnp7+1Uf2X/s1Pz//s/fQ09Mr04anihUrwsDA4D8tT+rYVqHqaIVSxeTn52PNmjVYunQpzMzMEBgYqLDztxeeioBU4HeDuXn5eGbSGmfOjELv3r2V+hGLKnN1dcXVq1fRs2dPODk54dKlS7QCTORqRT8buKwPFLSglIhFWNHPRrDrKUJ4eDhq1KihdMUk8M9mIkNDQxgaGpb6Gowx5ObmlrgIffLkyb8+5/3795DJPr9YUaFChf/vE61ijOT28wA5vl4UDs8XYuydpqA/KRVy9+5djB07FhEREZgzZw6WLFmisPO35dWvItKSgFVriMatnKiYlDNHR0cEBweja9euaNu2LXx8fGBlZcU7FlFTdQz1sdTNGvNPRgh2zWVu1iq3+1bdT8gRiUTQ09ODnp4eqlWrVurrMMaQmZlZrI1OzzOBZDm/XhQOz7euWUmu91EnVFCqgJycHCxduhRr1qxBkyZNEBoaqvABudSvoh4aNmyIkJAQuLq6ol27drh48SLs7e15xyJqaqi9KVIycgXpu57b1Url5gMWnpAzefJk3lGUnkgkQoUKFVChQoWvPj25m/AG/bxC5J5JUUP61YVmzBZQYcHBwWjWrBnWrVuHpUuXIiwsjMtpC/6Pk+VSTAL/NNn7RyfL5drkv2rXro1r167BwsICzs7OuHz5Mu9IRI1Nc7bAqv420JWIIWIle4HWEougKxFjdX8bTHU2l1NC+Xn+/Dlev35NJ+QITFHD8xV1H3VBf1pKKj09HdOnT4eTkxOMjIxw7949LFq0iMvg24xcKRLk2PwM/H+/ClEMQ0ND+Pn5oUOHDujZsycOHz7MOxJRY0PtTXHGoyVyEx8A+KdQ/JLCj7epbwS/2R1UbmWyEJ2QIx91jcpD3g1Sov/dhxQfPfJWQj4+Ppg4cSJSUlKwfv16TJs2jetQ7/jUTLmeegFQvwoP+vr6OH36NMaPH49hw4bh9evXmD59Ou9YRE0FXjiJpMM/wD/8Ia4m5MM/OhkJqZ84qtVIH86WJhjRylTl5wDeuXMHJiYmtAFOYOV1JTA11JfrLm9TI33akFNC9KelRNLS0vDtt99i7969cHFxQUBAAOrVq8c7lsL6SKhfRfG0tbWxe/dumJiYYMaMGUhOTsayZctogxQRFGMMXl5e6NWrF5xsLeFkC/wEa2TmSvEsNRN5Uhl0JGLUNSqvVi/i4eHhaNGiBf19kgN1HJ6v6tTnb66KO3HiBKZOnYqcnBzs3LkTY8aMUZofQtSvot7EYjHWrFkDExMTzJs3D8nJydi8eTMddUkEc/PmTdy/fx+rVq36178vrytR26cSjDGEh4dj/PjxvKOoJRqer3zoFZyzly9fYsCAARg4cCBat26NqKgojB07VmmKSYD6VTTF3LlzsXv3buzcuRODBg1CTk4O70hETXh5eaF+/fro2rUr7ygK8/LlSyQlJdGGHDmxqGaA9ubGX+3HLSktsQjtzY1Vvt2CByooOWGMYc+ePWjcuDGCg4Nx9OhRnDx5EjVr1uQdDQCQl5cHf39/zJ8/H+1a2SPvzd9yvR/1qygHd3d3nDp1Ct7e3ujWrRvevXvHOxJRcYVHfk6aNAlisea85BRuyKGCUn5W9LOBROCCUhWH5ysLzfnbrUSePXsGV1dXjBkzBm5uboiKisKgQYO4r0rGxsbC09MTbm5uMDIyQqdOnbB79240adIETg2MoCWneNSvolx69+4NPz8/3L9/Hx07dsSrV694RyIqbPfu3RCJRBgzZgzvKAoVHh4OIyMj1KlTh3cUtVU4PF9Iqjg8X1nQWd4KJJPJ4OnpiQULFsDQ0BBbt25F9+7dueVJT0+Hv78/fHx8cOnSJcTFxUEikaBdu3ZwdXWFq6srmjVrBrFYjJikdHTZECS3LH6znegRg5J58OABXF1doaenB19fXzRo0IB3JKJiZDIZLCws0KZNG+zfv593HIVyc3NDbm4ufHx8eEdRe5v8YwQbnq+K806VBT1jVJBHjx5h3LhxCAkJwdSpU7Fy5UoYGCi2gJLJZLh//z4uXboEHx8fhISEID8/Hw0aNEC3bt3g6uoKZ2fnT+Yq7FcJiUsVdFedlliENvWNqJhUQk2aNEFISEjRUY3e3t6ws7PjHYuoEF9fX8TFxWlcMQn8s0I5evRo3jE0wjRnCxhX0MWSs5GQyliJXqO0xCJIxCIsc7NW2XmnyoJWKOUsPz8fa9aswdKlS2FmZoadO3eiffv2Crt/cnIyfH194ePjA19fXyQnJ6N8+fLo1KlT0SqkuXnx3pElpmXBZX0gcgUc76MrEcNvdgd6xKDEXr9+jZ49e+LRo0c4e/YsOnbsyDsSURF9+vRBfHw87t69y72lR5FevXqFGjVq4NixYxg4cCDvOBojMS0LC09F4FpsylePCi78eHtzY6zoZ0OvQQKgglKO7t69i7FjxyIiIgJz587Fjz/+iHLlysn1nnl5ebhx4wZ8fHzg4+ODO3fuAABsbW3h6uqKbt26oU2bNtDR0SnV9Q+HJWD+yQjB8q7ub0PvClVARkYG+vfvj8DAQBw6dAj9+/fnHYkouYSEBNSrVw+bN2+Gh4cH7zgKdfHiRfTs2RNxcXFKMUtY08QkpeNgaMInh+eDMejLsjC4nbVaDM9XJlRQykFOTg6WLl2KNWvWoEmTJti5c6dcd/rFxcUV9UFevXoVGRkZMDY2LlqB7NKlC6pXry7Y/ahfRTPl5eVh9OjROHr0KLy8vDBx4kTekYgSW7x4MX7//Xf8/fffqFChAu84CrV8+XKsX78eqampGrUyq4w+Hp7/8/czEf8kGiEhIbyjqR3qoRRYcHAwxo0bh2fPnmHp0qWYN2+e4OdvZ2RkFG2m8fHxQWxsLCQSCdq0aYMFCxbA1dUVdnZ2chvRQf0qmklHRwcHDx6EsbExPDw8kJSUhB9++IFeMMl/5OXlYfv27Rg1apTGFZMAnZCjTD4ent+iWROcPXkMBQUFdHiDwDS+oBTq6K/09HQsWLAAnp6eaN26NU6fPo1GjRoJkpExhvv37xcVkMHBwcjPz0e9evXg6uqKNWvWoFOnTqhYsaIg9yuOofamaNvAuNj9KkxWAJFYC23qG1G/igoTi8X4448/UK1aNSxevBhJSUn4448/NGq+IPm606dPIykpCZMnT+YdhYvw8HAMGzaMdwzyCba2tsjKykJsbCysrKx4x1ErGvnIu6i/4nEyEtL+3V8hAmBqqA9nKxMMdzSFRbWv91f4+Phg4sSJSElJwcqVKzF16tQyv/N5/fo1Ll++XFREJiUlQV9fH87OzkU7ss3NzZXiHfCX+lVE+GdoufbraNw7thHPo25DT0+PV1QioG3btmHy5MkYNGgQ9u7dC11dXd6RiJJwdnZGQUEBgoLkN2pMWSUnJ6NatWo4cuQIBg8ezDsO+UhKSgqqVq2Kw4cPY8iQIbzjqBWNKiiF3gGWlpaG2bNnY9++fXBxccG2bdtK3YCdn5//n800jDE0bdq0qIBs27at0r9of27FNyYmBpaWlti/fz9GjBjBOyYRyMmTJzFs2DC0b98eJ0+eVPgoLKJ8oqKiYG1tjUOHDmHo0KG84yjcpUuX0L17d8TGxtLsViVVp04dDB8+/D9ny5Oy0ZiC8nBYQpl6/pa6WWPoBz1/x48fx9SpU5GXl4d169bB3d29xKuFT58+LSogr1y5gvT0dBgZGaFr165wdXVF165dUaNGjRJdU5l17twZeXl5uHbtGu8oREABAQHo06cPLC0tcfHiRVStWpV3JMLRjBkzcOTIESQmJpZ6moQq++WXX7BmzRq8efNGKZ4gkf/q3bs38vPzcenSJd5R1IpG9FCWZVdywf8K0PknI5CSkYsBDStg2rRpOHnyJPr16wdPT89iF32ZmZkICAgoKiKjo6OhpaWF1q1bY968eejWrRuaN2+utv1oHh4eGDJkCCIjI2FtLexxWYSfjh07IjAwEN26dUO7du3g4+ODunXr8o5FOMjMzMTevXsxdepUjSomP3wyExz5DLYtHamYVGJ2dnbYtm0b7xhqR+1XKIWem5gVsB2iuBvw9PTEgAEDvvhDgzGGiIiIopE+wcHByMvLg5mZWdFMyE6dOqFSpUqfvYY6ycvLQ506dTB06FD8/vvvvOMQgT158gSurq7Izs7GpUuXYGNjwzsSUbDt27fDw8MDcXFxav+m4ku9+GAMZkblS9SLTxTn5MmTGDBgAF6+fCnoSD1Np9YFpdAnuzDGoIUCnJ7QEk0b1Prk70lJSSnaTOPr64uXL1+iXLlycHZ2LpoLaWlpqbHvXufPn4+tW7fi77//lvuQd6J4SUlJ6NatG549e4Zz586hXbt2vCMRBWGMoUWLFqhVqxbOnTvHO47c0Gksqi8uLg4NGjTAxYsX0b17d95x1IZ6Plv9n4WnIiAV8NxpkUgEkZY21gQ8L/p3UqkUwcHBWLx4MRwcHGBiYoJhw4bhzp07GD58OC5fvoy0tDRcuHABM2bMgJWVlcYWkwAwYcIEvH37FkePHuUdhchBtWrVEBAQAFtbW3Tp0kWtCwvyb7du3cLdu3fVelTQ4bAEuKwPREhcKgB8tR+/8OMhcalwWR+Iw2EJcs9Ivq5u3bqoWLEi7t27xzuKWlHbFcqYpHR02SC/kRUTayUh3P8C/Pz88P79exgaGqJLly5Fm2lq1fr0CiYBunTpgqysLFy/fp13FCInOTk5GD58OM6cOYPt27djzJgxvCMROXN3d0dgYCBiY2PVcmC0UCeEzelqiWnOFgIkImXRoUMHVK9eHUeOHOEdRW2o7aacg6EJX30cUVpMVoDfzt5Cw8xXmDNnDlxdXdGiRQu1/CEqDx4eHhg0aBAePHiAJk2a8I5D5EBPTw9Hjx7FlClTMHbsWLx+/Rpz584t9uq8UAcOEMVITU3F4cOHsXTpUrX8OXg4LEGQYhIA1vpGo2oFXTopjDNbW1t4e3vzjqFW1PYntP/jZLkUkwAgEmuhscsgXJu3RS7XV3d9+vRBtWrVsHXrVmzcuJF3HCInWlpa2LJlC6pVq4bvv/8eSUlJWLNmzWenGAh94ABRnD179oAxhrFjx/KOIrjEtCwsORsp6DV/PBuJNg2MqaeSI1tbW2zcuBHp6ek0P1cgatlDmZErRUJallzv8fxNDjJzpXK9h7rS1tbG2LFjsX//fmRlyfe/E+FLJBJh2bJl2LhxI9avXw93d3fk5+f/6/ckpmVh5M5QdNkQhP2h8Yj/eMcsAAYgPi0L+0Pj0WVDEEbuDEWinP+Ok+KRyWTYsmULBg4cqJYzSIXuxQcAqYxh4Snhpo+QkrOzsyuaxEKEoZYFZXxq5n9ekITGADxLzZTzXdTXhAkT8P79e+pf0RDTpk3DoUOHcPjwYfTt2xeZmf/83aFNDqrPz88PsbGxmDJlCu8ogotJSse12BTBn3YVyBiuxaYgNjld0OuS4mvcuDG0tbVpY46A1LKgzBNoTJCy3Ecd1atXD127dsXWrVt5RyEKMmTIEFy4cAGBgYFwcXHBrxf+wvyTEciVykr8gl0gY8iVyjD/ZAQ2+cfIKTEpDi8vL9jY2KBNmza8owiusBdfHrTEIhy4SW+IeNHR0UHjxo1x9+5d3lHUhloWlDoSxXxZirqPuvLw8EBoaCju37/POwpRkC5duiAgIADPtGpic3CiINdc6xuNI7RSycXz589x9uxZTJ48WS3HocmzF79AxuAfnSyXa5PisbW1pRVKAallRVTXqDzk/aNN9L/7kNLr1asXqlevTkdgaZhq9RvDoOM4QMCJZT+ejaSeSg62bdsGfX19jBgxgncUwSmiFz8hNYt68Tmys7NDREQEpFL6byAEtdzlXV5XAlNDfcTL8YeBqZE+jTEpI21tbYwbNw4bN27Er7/+ivLlqUDXBAtPRaCAARBwRatwk8P+cY6CXZN8WX5+Pnbs2IGRI0cqxS5ZxhikUimys7ORk5NT5l9TCvTAavaUb2b804tvXVMzjt9VNra2tsjNzcWjR49ohJ0A1LYicrYywf7QeLk8rtASi+BsaSL4dTXRhAkTsGLFChw+fBjjxo3jHYfIWeEmB6F9uMnB3IR/caMJzpw5g5cvX/7nZBzGGPLz8wUr7Eryq0xWsr52HR0dlCtXDnp6ev/5VWRcD6gp5J/Yp1EvPj/NmjUDANy7d48KSgGobUE53NEUe248k8u1C2QMI1rRUFohmJmZoVu3bti6dSsVlBpAngcOFG5y+MnNWvBrqyLGGPLy8uRWwN27dw/6+vro16/ffz5e0gPYdHV1P1vYFf5asWJFmJiYfPX3FfdXPT29z85EBYDIv9+h58bgsv5n+CrqxeencuXKqFevHu7du6eWbRuKprYFpUU1A7Q3N0ZIXKqgL15aYhHa1DeiVRABeXh4oG/fvrh79y7s7Ox4xyFypIhNDj9BuQpKxhhyc3MVvmKXk5NT4sKuOIVY5cqVkZubi/T0dLi6usLW1rZMhZ2uru4XCzteCnvx5TmCjnrx+aONOcJR24ISAFb0s4HL+kBBX8AkYhFW9LMR7HoE6NmzJ2rWrImtW7diyxY6fUhdKXKTw6f6m2UyGbfCriREIlGxCjFDQ0NBVuo+LOyKu1N71qxZqFq1Ks6cOQNdXd0SfX2qgnrxNYOtrS1+//13MMbUclKBIqn1d3IdQ30sdbPG/JPCTcJf5mZNx2UJTCKRYNy4cVi/fj3Wrl2LChUq8I5E5EBRBw607uoG6etn/ynscnNzS3QtkUiEcuXKfbUQMzY2FrSw09HRUeoXtszMTOzZsweTJk1S22KyEPXiqz9bW1ukpaXh+fPnqFOnDu84Kk2tC0oAGGpvipSMXKz1jS7zteZ2tcIQe+qdlIfx48fjl19+waFDhzBhwgTecYgcKGrzQZOmtqiu3bDMhZ22trZSF3a8HD58GO/fv4eHhwfvKHJHvfjqr7DN6t69e1RQlpGIlbTJRkUdDkvAkrORkMpYid5taolFkIhFWOZmTcWknPXq1QuvXr3C7du3eUchcqCoTQ4XprejMSxy1LJlS1SrVg0XLlzgHUUhRu4MlVsvPo254o8xBmNjY8yaNQuLFy/mHUelKV8ntJwMtTeF3+wOaFPfCAC+epxW4cfb1DeC3+wOVEwqgIeHB8LDwxEeHs47CpEDOnBA9YWFhSE8PPw/o4LU2Yp+NpAIfPwi9eIrD5FIBFtbWzqCUQAaU1AC//RU7h/niMuznDDS0QxmRvr/eYFjjMHMSB8jHc3gN9sJ+8c5Us+kgnTv3h21a9em873VVOEmB3miTQ7y5eXlBTMzM3Tv3p13FIUp7MUXEvXiKxc7Ozva6S0AjSooC1lUM8BPbtYInOOMBz+54sL0djg1uQ3mN2NIXDcI+wbVx09u1jQaSMEkEgnGjx+PP//8E+/fv+cdh8iBs5XJV58OlBZtcpCvtLQ0HDp0CB4eHtDS0uIdR6GG2ptiTldLQa5FvfjKx9bWFk+fPsXbt295R1FpGllQfqi8rgTWNSvBzrQK+jnbg+Xn4NatW7xjaaxx48YhOzsbf/75J+8oRA6GO5rKdQ4lbXKQn71796KgoEBjDyCY5myBVf1toCsRl/hNkZZYBF2JGKv722Cqs7mcEpLSsrW1BQDcv3+fbxAVp/EF5YeqVasGMzMzKig5ql27Nnr27ImtW7eWeCgzUX6FBw4IvUqpJRahvbkxPVWQE5lMBi8vLwwYMAAmJpq7ClzSXnzICgBQL76ya9iwIXR1demxdxlRQfkRR0dHhIaG8o6h0Tw8PHDv3j3a7a2maJOD6rl69SpiYmIwZcoU3lG4K04vvgiAsR7D+zsXsLG7CfXiKzmJRAIbGxsqKMtIY8YGFddvv/2GH3/8Ee/evYNEQs39PBQUFKB+/fro0qULduzYwTsOkYPDYQmCHjiwur8Nrf7I0YABA/D48WNERETQbM5PyMyV4llqJvKkMuhIxKhrVB46YobatWtj2LBhWL9+Pe+I5CsmTJiA27dv027vMqAVyo84ODggKysLUVFRvKNoLC0tLYwfPx6HDh3Cu3fveMchckCbHFTHixcvcObMGUyePJmKyc/4sBffumYllNeVQFtbGyNGjMDBgweRn5/POyL5CltbW0RGRiIvL493FJVFBeVHmjdvDi0tLeqj5GzcuHHIzc3FwYMHeUchcvLhJgdRCQ9lpE0OirN9+3bo6elh5MiRvKOonNGjR+P169fw9vbmHYV8hZ2dHfLz82kxqQyooPxI+fLl0aRJE+qj5KxmzZro3bs3bc5Rc0PtTeEzox3Yy0cA6MABZZOfn4/t27djxIgRqFixIu84Kqdp06aws7PDnj17eEchX2FjYwORSER9lGVABeUnODg40AqlEvDw8MBff/1Fxb2ai7gZgPi9c7HOxfCLmxzowAHFO3fuHP7++2+NOhlHaO7u7jh37hxev37NOwr5AgMDA5ibm1MPZRnQppxP2LFjBzw8PPD+/XuUL0/HuPFSUFCABg0aoFOnTti1axfvOEROunXrhrS0tH+9ifvUJgc6AUfxunTpgszMTISEhPCOorJSUlJQs2ZNrF27FjNmzOAdh3zBkCFD8OrVKwQGBvKOopJohfITHBwcIJPJcOfOHd5RNJqWlhYmTJiAw4cP0wkGaiomJgY+Pj6YOnXqv/79pzY5EMWKjo6Gn58fjQoqI2NjY/Tq1Ysee6sAW1tb3Lt3j9qsSokKyk+wtrZG+fLl6VGrEhg7dizy8/Nx4MAB3lGIHHh5ecHIyAhDhgzhHYV8ZMuWLTAyMsLAgQN5R1F5o0ePxt27d/HXX3/xjkK+wNbWFu/fv8ezZ894R1FJVFB+gpaWFlq0aEF9lEqgRo0acHNzo805aigrKwu7d+/GuHHjoKenxzsO+UBWVhb27NmDsWPH0n8bAfTo0QNVq1bF3r17eUchX1B4BCP1UZYOFZSfQRtzlIeHhwcePHiAGzdu8I5CBPTnn3/i3bt3mDRpEu8o5CNHjhzB27dv4eHhwTuKWtDW1sbw4cNx4MABmkmpxGrUqIFq1arRTu9SooLyMxwdHREfH4+kpCTeUTSei4sL6tevj61bt/KOQgTCGIOnpyd69uyJevXq8Y5DPuLl5QVXV1c0aNCAdxS14e7ujuTkZFy6dIl3FPIFhX2UpOSooPwMBwcHAKBVSiUgFosxYcIEHD16FG/evOEdhwjgxo0buHfv3n824xD+wsPDERYWRqOCBNasWTPY2trS5hwlZ2trS4+8S4kKys+oU6cOqlWrRgWlknB3d4dUKsX+/ft5RyEC8PT0hLm5Obp27co7CvmIl5cXTE1N0bNnT95R1E7hTMrU1FTeUchn2NnZ4fnz50hJSeEdReVQQfkZIpGI+iiVSPXq1dG3b1/anKMGkpKScOzYMUyePBliMf0IUiZv3rzBn3/+iYkTJ0JLS4t3HLUzbNgwMMZw6NAh3lHIZxRuzLl//z7fICqIfpp/gaOjI27dugWZTMY7CsE/m3OioqJw/fp13lFIGezYsQMSiQRjxozhHYV8ZN++fcjPz8e4ceN4R1FLVatWRc+ePemxtxIzNzeHvr4+9VGWAhWUX+Dg4IC3b98iNjaWdxQCoFOnTmjQoAFtzlFhUqkUW7ZswbBhw1ClShXeccgHGGPw8vJC//79Ub16dd5x1Ja7uzvCw8MRERHBOwr5BC0tLTRt2pT6KEuBCsovaNmyJQDamKMsxGIxJk6ciGPHjlEPkoo6d+4cnj9/TptxlJC/vz8eP35MJ+PIWY8ePWBsbEwzKZWYnZ0drVCWAhWUX1ClShVYWlpSQalE3N3dIZPJsG/fPt5RSCl4enqidevWsLOz4x2FfMTLywuNGzeGk5MT7yhqTUdHp2gmpVQq5R2HfIKtrS0ePXqE7Oxs3lFUChWUX+Ho6EhHMCoRExMT9OvXjzbnqKBHjx7hypUrtDqphP7++2+cPn0akyZNgkgk4h1H7Y0ePRpJSUnw8fHhHYV8gq2tLQoKCvDgwQPeUVQKFZRf4eDggHv37iE3N5d3FPI/Hh4eePz4Ma5du8Y7CimBzZs3o2rVqnQ2tBLasWMHdHR0MGrUKN5RNIKtrS2aNm1Km3OUlI2NDcRiMT32LiEqKL/CwcEBeXl5+Ouvv3hHIf/j7OwMCwsL2pyjQjIyMrB3715MmDABurq6vOOQD0ilUmzbtg3Dhw9HpUqVeMfRCCKRCO7u7jh79iz1gyuhcuXKoWHDhlRQlhAVlF/RrFkz6Ojo0GNvJSISiTBx4kQcP36chs+qiAMHDiAjI4POhlZC58+fx4sXL+hkHAUbPnw4ZDIZDh8+zDsK+QQ6grHkqKD8Cl1dXdja2tLGHCXj7u4OALRTUgUUntvt5uYGU1NT3nHIR7y8vNCqVSvaKKVgJiYm6NGjBz32VlK2tra4f/8+CgoKeEdRGVRQFgOdmKN8jI2NMWDAAGzbto025yi5a9eu4cGDB7QZRwnFxMTA19eXVic5cXd3x+3btxEZGck7CvmInZ0dMjMz8eTJE95RVAYVlMXg4OCAx48f4+3bt7yjkA94eHggOjoaAQEBvKOQL/D09ISVlRU6d+7MOwr5yNatW2FoaIjBgwfzjqKRevbsCSMjI3rSooSaNWsGAPTYuwSooCwGBwcHAEBYWBjnJORDTk5OsLKyos05Suzly5c4efIkpkyZQuNolEx2djZ2796NMWPGQE9Pj3ccjaSjo4Nhw4Zh//79NJNSyVStWhW1atWigrIEqKAsBgsLC1SuXJkeeyuZws05J0+exOvXr3nHIZ+wbds26OrqYvTo0byjkI8cPXoUaWlpmDRpEu8oGs3d3R2vXr2Cr68v7yjkI3Z2dnQEYwlQQVkMYrEY9vb2VFAqodGjR0MsFlNjuxLKz8/H1q1bMWLECBpHo4S8vLzQtWtXmJub846i0ezs7GBjY0M/w5QQ7fQuGSooi8nBwQGhoaG0AUTJGBkZYeDAgdi2bRtkMhnvOOQDp0+fxsuXL2kzjhK6c+cOQkNDaTOOEiicSXnmzBmkpaXxjkM+YGtri1evXuHVq1e8o6gEKiiLycHBAUlJSUhMTOQdhXzEw8MDsbGx8Pf35x2FfMDT0xPt27eHjY0N7yjkI15eXqhduzZ69erFOwrBPzMpCwoKcOTIEd5RyAdsbW0B0Mac4qKCspgKN+bQY2/l065dOzRq1Ig25yiRBw8eIDAwkFYnldC7d+/w559/YuLEiZBIJLzjEADVqlVD9+7d6bG3kqlXrx4qVqxIBWUxUUFZTNWrV4epqSkVlEpIJBLBw8MDp06dQlJSEu84BP+c2129enX069ePdxTykX379iEvLw/jx4/nHYV8wN3dHbdu3UJUVBTvKOR/xGIxmjVrRgVlMVFBWQKFfZRE+YwcORJaWlrYvXs37yga7/3799i/fz8mTpwIHR0d3nHIBxhj8PLyQr9+/VCjRg3eccgHevXqBUNDQ5pJqWRoY07xUUFZAo6Ojrh9+zbNC1NChcOZt2/fTptzONu3bx+ys7MxceJE3lHIRwIDA/Hw4UPajKOEdHV1aSalErKzs0N0dDQyMjJ4R1F6VFCWgIODA7KysvDw4UPeUcgneHh4IC4uDleuXOEdRWMxxrB582b069cPtWrV4h2HfMTLywsNGzZEx44deUchnzB69Gi8fPkSfn5+vKOQ/7G1tQVjDBEREbyjKD0qKEugefPmEIvF1EeppNq0aQNra2vanMORv78/Hj58SJtxlNCrV69w8uRJTJo0iU4tUlItWrSAtbU1bc5RIo0bN4ZEIqHH3sVABWUJVKhQAdbW1tRHqaQKN+ecOXOG5oZx4unpCWtra3To0IF3FPKRHTt2QFtbm04tUmKFMylPnz6NN2/e8I5D8E8rgrW1NZ2YUwxUUJaQo6MjrVAqsZEjR0JbWxu7du3iHUXjPH/+HGfOnKFzu5VQQUEBtm3bhmHDhqFy5cq845AvGD58OKRSKc2kVCK0Mad4qKAsIQcHBzx48ACZmZm8o5BPqFy5MoYMGUKbczjYunUr9PX1MXLkSN5RyEcuXLiAxMRE2oyjAmrUqIFu3brRY28lYmtri4iICNos9RVUUJaQg4MDCgoKaPlbiU2cOBHPnj2Dr68v7ygaIy8vD9u3b8eoUaNgYGDAOw75iJeXFxwcHNCiRQveUUgxuLu7IzQ0FI8ePeIdheCfgjInJwfR0dG8oyg1KihLyNraGvr6+tRHqcRatWoFGxsbbNu2jXcUjXHixAkkJSVhypQpvKOQjzx58gSXLl2i1UkV0rt3b1SpUoVmUiqJwiMYaSHpy6igLCGJRIIWLVpQH6USK9ycc/bsWfz999+842gET09PODs7o3HjxryjkI9s3boVVapUwZAhQ3hHIcWkq6uLb775Bvv27UNBQQHvOBqvcuXKqFu3LvVRfgUVlKXg4OBABaWSGzFiBHR1dWlzjgLcv38f169fp1FBSignJwe7du3CmDFjUK5cOd5xSAm4u7vj77//ppmUSoI25nwdFZSl4ODggGfPniE5OZl3FPIZlSpVwtChQ7F9+3Z6hy9nnp6eqFWrFvr06cM7CvnIsWPHkJqaikmTJvGOQkqoZcuWaNy4MW3OURJ2dna4e/cuGGO8oygtKihLwcHBAQBolVLJeXh4ICEhAT4+PryjqK23b9/i4MGD8PDwgEQi4R2HfMTLywsuLi6wsLDgHYWUUOFMylOnTuHt27e842g8W1tbpKam4sWLF7yjKC0qKEvBzMwMJiYmVFAqOXt7ezRr1oxOzpGjPXv2ID8/HxMmTOAdhXzk3r17uHHjBm2UUmEjRoxAfn4+jh49yjuKxivcmEOPvT+PCspSEIlE1EepAgo355w/fx7Pnz/nHUftyGQybN68GQMGDED16tV5xyEf8fLyQq1atdC7d2/eUUgp1ahRA66urvTYWwnUqVMHVapUoYLyC6igLKXCgpL6KZTb8OHDUa5cOdqcIwd+fn6IiYmhzThK6P379zh48CAmTJhArQgqzt3dHTdu3MDjx495R9FoIpGoqI+SfBoVlKXk4OCAN2/eIDY2lncU8gUVK1bEN998gx07dtDmHIF5enqiadOmaNu2Le8o5CP79+9HTk4Oxo8fzzsKKSM3NzdUrlyZZlIqAdrp/WVUUJaSvb09ANqYowo8PDyQmJgIb29v3lHURnx8PM6fP4+pU6fSud1KhjEGLy8v9O3bF7Vq1eIdh5SRnp4ezaRUEra2toiLi8O7d+94R1FKVFCWkqGhISwsLKigVAEtW7ZE8+bNaXOOgLZs2QIDAwMMHz6cdxTykWvXriEyMpJOxlEj7u7uePHiBa5cucI7ikazs7MD8M/sXfJfVFCWgYODAx3BqCI8PDxw8eJFJCYm8o6i8nJycrBjxw64u7ujfPnyvOOQj3h5ecHS0hKdOnXiHYUIxN7eHg0bNqTH3pxZWVlBV1eXHnt/BhWUZeDg4IC7d+8iLy+PdxTyFd988w309fWxY8cO3lFU3rFjx5CSkkLjaJRQUlISTpw4gcmTJ1MrghopnEl58uRJetzKkba2Npo0aUIF5WdQQVkGjo6OyMvLw19//cU7CvkKAwMDDBs2DDt27IBUKuUdR6V5enqiS5cusLS05B1FY2XmShH59zvcTXiDyL/fITP3n+/pnTt3QiKRYPTo0ZwTEqGNGDECeXl5NJOSM9qY83k0T6IMmjVrBm1tbdy6dQstW7bkHYd8hYeHB7Zt24aLFy/Czc2NdxyVFB4ejtDQUJw+fZp3FI0Tk5SOg6EJ8H+cjIS0LHw4sEwEoI5hOcTfTkPv4RNQpUoVXjGJnNSqVQtdu3bFnj176CABjuzs7LBv3z7k5eVBR0eHdxylQiuUZaCnp4dmzZpRH6WKaN68OVq2bEmbc8rA09MTpqam6NWrF+8oGiMxLQsjd4aiy4Yg7A+NR/xHxSQAMAAJadmAhRNCjbti5M5QJKZl8YhL5Mjd3R0hISGIjo7mHUVj2draIj8/Hw8fPuQdRelQQVlGjo6OtNNbhXh4eMDb2xvx8fG8o6ic1NRUHDp0CJMmTYKWlhbvOBrhcFgCXNYHIiQuFQBQIPvyQQoi8T//XULiUuGyPhCHwxLknpEoTp8+fVCpUiXs27ePdxSN1bRpU4hEInrs/QlUUJaRg4MDHj16RI3SKmLo0KGoUKHCvzbnfK4fjfzb7t27IZPJaFi2gmzyj8H8kxHIlcq+Wkh+rEDGkCuVYf7JCGzyj5FTQqJoenp6GDp0KPbu3UszKTkxMDCAubk5FZSfQD2UZeTg4AAACAsLg4uLC+c05GsqVKiAESNGYOfxi0CLwQiKSflkP5qpoT6crUww3NEUFtUMeMVVGjKZDF5eXhg8eDCqVq3KO47aOxyWgLW+wjzWXOsbjaoVdDHE3lSQ6xG+3N3dsXXrVvj7+9NrDie2trZ0BOMn0AplGVlaWqJSpUr02FtFJKZl4W/L/tDpuwwHv9CPFp+Whf2h8eiyIYj60QBcunQJcXFxdG63AiSmZWHJ2UhBr/nj2UiN/x5WF46OjrCyssKePXt4R9FYhTu9GSvZkwN1RwVlGYnFYtjb21NBqQIK+9EiXv8zN1SGL8/pK3zMSP1o/2zGad68ORwdHXlHUXsLT0VAWsJH3F8jlTEsPBUh6DUJHx/OpHz//j3vOBrJ1tYW7969o178j1BBKYDCE3Po3Yryon600ouLi4O3tzed260AMUnpuBabUuLv0a8pkDFci01BbHK6oNclfIwcORK5ubk4duwY7ygaqfAIRnrs/W9UUArAwcEBr169wvPnz3lHIZ8gdD/aEQ1bqfTy8kLlypUxdOhQ3lHU3sHQBGiJ5VO0a4lFOHBTs7531VWtWrXg4uJCj705qV69OkxMTGhjzkeooBRA4cYceuytfKgfrWyys7Oxa9cujB07Fvr6+rzjqD3/x8mCr04WKpAx+Ecny+XaRPHc3d0RHByM2NhY3lE0jkgkohNzPoEKSgHUqFEDderUoYJSCVE/WtkcPnwYb968weTJk3lHUXsZuVIkyPmNSkJqFo3FUhN9+/ZFxYoVsXfvXt5RNJKdnR3uPXhII+c+IGLU+CeIgQMHIjU1Ff7+/ryjkP+JSUpHlw1Bcru+32wnmJuo70ghxhjs7e1hYmKCixcv8o6jUIwx5OfnIz8/H3l5eQr5NVVWDuFVu8r9a7swvR2sa1aS+32I/BUe1PDs2TOIxbQ+pAiFR6CeDY9Daq7oX33lmj5yjuZQCsTBwQHLly9HQUEBnSKiJAr70eTxCLGwH+0nN2vBr60sbt26hfDwcJw/f77U1ygoKFBYUSbktaRS4VYatLS0oKOjA21t7S/+ygzNAAWM+MyTyuR/E6IQ7u7u2LZtG/z9/dG5c2fecdRaYloWFp6KwLXYlP+9rojx8R7FD0fO7bnxDO3NjbGinw3qGGpGuxCtUAokICAAzs7OiIiIQJMmTXjHIQA6rPFHvBwfIZoZ6SNwjrPcrl+Ix2pZXl4eAgMDkZycDBcXl1LfXyYTrnjR0dEpVmGmTL9qa2sXe+Uo8u936LkxWLA/r8+hFUr1wRiDlZUVWrVqRccxytHhsAQsORsJqYyVaIFCSyyCRCzCUjdrDNWAgwVohVIgLVu2hFgsxq1bt6igVAKK6EeLT83EL6vXguXnyHV1TcjVMolEUqxCSCQSIT4+HhYWFigoKICenh4MDAy4FWZaWlpqP7KorlF5iID/DNoXkuh/9yHqoXAm5c8//4xNmzahYsWKvCOpnU3+MaWeElLwvwJ0/skIpGTkYpqzhcDplAsVlAKpUKECGjdujNDQUIwdO5Z3HI0Xn5op1xfmf4iwYedBaL1/WezCyMDAgNuKmUQiKfZq2cqVK/HXX38hJCQERkZGcv5zJABQXlcCU0N9ua6qmxrpo7wu/dhXJyNHjsQPP/yA48eP02uPwOgI1JKhnywCcnBwoJ3eSkJRfWK+fldhZ1pFIfdSlIKCAmzZsgVDhw6lYlLBnK1MsD80Xm59v86WJoJfl/BVp06dopmUVFAKR14j59o0MFbbnkraFiYgBwcHREREICtLM2YUKjMdiWK+tRV1H0U6f/48EhIS6NxuDoY7msp1DuWIVuq7OqLJ3N3dce3aNTx58oR3FLVBI+dKTv1eDTlydHREQUEBHcekBAr70eRJXfvRPD094eDggJYtW/KOonEsqhmgvbmx4KflaIlFaG9urNZjrjRZ3759YWBgQBtzBEJHoJYOFZQCsra2Rrly5RAaGso7isYr7EeTJ3XsR4uOjsbly5dpdZKjFf1sIBGyoGQMErEIK/rZCHdNolT09fUxZMgQ7N27V9DJCpqKjkAtHSooBaStrY3mzZtTH6WScLYykesPBXXsR9u8eTOMjY0xePBg3lE0Vh1DfSwVcr6pSIT6b26jRkUd4a5JlI67uzvi4+MRGBjIO4rKoyNQS4cKSoE5OjpSQakkqB+tZDIzM7Fnzx6MGzcOenp6vONotKH2ppjT1VKQa7lUzcLlLUsxZMgQ5ObmCnJNonzatGkDc3Nz7Nmzh3cUlUZHoJYeFZQCc3BwwNOnT/H69WveUTQe9aOVzMGDB/H+/XtMmjSJdxQCYJqzBVb1t4GuRFzi72EtsQi6EjFW97fBjm8H4dSpU7hw4QJ69uyJ9HT17N/SdIUzKY8fP07/jctAESPnGIBnqZlyvoviUUEpMAcHBwCgVUolIXg/GqCW/WiMMXh6eqJXr16oW7cu7zjkf4bam8Jvdge0qf/P+KavFZaFH29T3wh+szsUzbzr3bs3fHx8cOvWLbi4uCA1NVW+wQkXI0eORHZ2No4fP847ispS1Mg5dTwClQpKgdWtWxfGxsZUUCoJwfvRACxzs1a7OWLXr1/HX3/9RZtxlFAdQ33sH+eIy7OcMNLRDGZG+v+ZYCDCP0eBjnQ0g99sJ+wf5/if79EOHTogICAAT58+hZOTE168eKGwr4EohqmpKTp16oS9e/fyjqKyaORc6dFZ3nLQq1cvFBQUwNvbm3cU8j9lOT7rQ3O7WmGqs7kAiZTLN998g9u3b+Px48fFPk2H8JOZK8Wz1EzkSWXQkYhR16h8sScOPH78GF26dIFYLMbly5dhYaHex8FpmgMHDmDkyJF48uQJ6tevzzuOSmCMIS4uDn5+fvC9Gojb9YbJ9ahXEYAHP7mq3ZQQeuWQg8ITc6hWVx5C9aOpYzH56tUrnDhxAlOmTKFiUkWU15XAumYl2JlWgXXNSiV6YbKyssL169dRrlw5tGvXDvfu3ZNfUKJw/fr1o5mUxZCcnIzDhw9jwoQJqF+/PszNzTF16lS8THwGA5F8N6+p48g5gApKuXBwcEBaWhqdWqBkPu5HA/tyD8vn+tHUzfbt2yGRSODu7s47ClGQOnXq4Nq1azA1NUXHjh0RHBzMOxIRSPny5TF48GCaSfmRzMxMeHt7Y86cObC1tUW1atXwzTffICQkBG5ubjh79izS0tIQEhKCga0b0si5UqBH3nKQmpoKY2NjHDx4EMOGDeMdh3xCTFI6ukxZhvIWDsgS6f9rV58I/7yDdLY0wYhWpmq3m/tDUqkUdevWRffu3bF9+3becYiCpaeno0+fPrh58yaOHz+OHj168I5EBBAcHIz27dvD398fHTt25B2Hi/z8fISFheHKlSvw8/PDjRs3kJ+fj1q1asHFxQUuLi7o1KkTatas+Z/PjUlKR5cNQXLL5jfbSS1fV6iglBMLCwv07NkTGzZs4B2FfEJycjKqVauGw4cPo1ffAaXuR1N1J06cwMCBA3H37l3Y2tryjkM4yMnJwdChQ3HhwgXs27cP33zzDe9IpIwYY7CwsED79u2xe/du3nEUgjGGqKioogIyICAA6enpqFSpEpydneHi4oLOnTvDysrqi/2ROTk5WL58OXbGlYOeaVNArCVYRi2xCG3qG2H/OEfBrqlMqKCUk+HDhyMuLg43btzgHYV8wvnz59G7d288ffpUo8fkdOrUCbm5ubh+/TrvKIQjqVSKCRMmYO/evdi0aROmTJnCOxIpo+XLl2P16tV49eoVKlSowDuOXDx//ryogPTz88OrV6+go6ODtm3bFhWQLVq0gERSvAWCoKAgTJgwAU+fPsXMhctwtqAZcgUc76MrEcNvdge1mxJSSDOWYThwcHDAiRMnkJeXBx0dOvJM2dy6dQtVq1aFmZkZ7yjcREVFwd/fHwcPHuQdhXAmkUiwc+dOVKlSBVOnTkVqaip++OEHue50JfI1atQo/Pjjjzhx4gRGjx7NO44g3r59i4CAgKIC8vHjxxCJRLCzs8PIkSPh4uKCdu3aQV+/ZAXbu3fv8P3332Pr1q1o06YNTp06hcaNG6NFWALmn4wQLL86jpz7EBWUcuLg4IDc3FxERESgRYsWvOOQj4SGhsLR0VGjXzA3b94MExMTDBgwgHcUogTEYjF+++03GBkZ4YcffkBqairWrVtHO/9VlJmZGTp16oQ9e/YUFZRlGTfFQ05ODm7cuFFUQN6+fRsymQwNGjRA586dsXz5cjg7O8PY2LjU9zhz5gymTJmC9+/fY9OmTZg8eXLR9/xQe1OkZOQKNnJOXTd2FlLe7yQVZ2dnB4lEglu3blFBqWQYY7h16xa+/fZb3lG4SU9Px759+zBjxgzo6uryjkOUhEgkwqJFi2BoaIipU6fizZs32LlzZ7EfGRLl4u7ujnGzF2H2gRu48zIHCWlZ/92AaKgPZysTDHc0hUU1vhtFZDIZ7t27V1RABgcHIzs7G1WrVkWnTp0wYcIEdO7cGfXq1SvzvV69eoXp06cXbUbz8vKCqel/C75pzhYwrqCLJWcjIZUxFMiK3yWoJRZBIhZhmZu12heTAPVQylXLli3RpEkT7Nmzh3cU8oGYmBhYWlri0qVLcHV15R2Hi82bN2P69Ol49uwZ6tSpwzsOUUKHDh3CqFGj0KNHDxw5cgR6enq8I5ESSEzLwvfH7yHk6RuIwMD+c77S/9MSi1AgY2hvbowV/WwU9lj2w4Hifn5+8Pf3R2pqKvT19eHk5FS0G9vGxkawlXLGGPbs2YPvvvsOWlpa+OOPPzB06NCvPq1KTMvCwlMRuBabUvTn9Tm8/jx5o4JSjqZMmYKAgABERUXxjkI+UHiSRGpqKgwNDXnHUTjGGJo0aQIrKyucPHmSdxyixC5evIiBAwfC0dERZ86cQcWKFXlHIsVwOCyhTCtqS92sMVROK2rJycm4evVqUREZHx8PLS0tODg4FBWQrVq1ksvegydPnsDDwwNXrlzBqFGj8Ntvv5X4cXlMUjoOhibAPzoZCamfWPHVkJFzn0IFpRzt2bMHY8eOxYukFKTla6lM34q6mzFjBi5duoTo6LL3xaiigIAAODs7w8/PD507d+Ydhyi54OBg9OrVC+bm5vD29kbVqlV5RyJfINQxs3O6WmKac9mP5czIyMC1a9fg5+eHK1eu4P79+wCAxo0bFxWQHTp0kOubFalUig0bNuDHH3+EiYkJtm7dKsjTKVXrSZU3KijlJCYpHRsv3cOJG4+gXeXfg1OVrW9F0zg6OsLS0hL79+/nHYWLQYMG4cGDB4iKitLoTUmk+O7fvw9XV1dUrlwZly9fpjYJJXVY4F3Jq/vblLj3r3CgeGEBWZKB4vJw7949jB8/Hnfu3MHMmTOxfPlytR2jxBsVlAKjPgvllpubi4oVK2Lt2rWYPn067zgK9+LFC5iZmWH9+vUa+fWT0ouNjUWXLl1QUFCAy5cvw8rKinck8oHEtCy4rA9U+NzE4gwUd3FxgaWlpULfwGZnZ2PZsmVYs2YNGjVqhB07dsDRUT0HiisLKigFpMx9K+QfYWFhcHBwwM2bNzXyh8uSJUvw22+/4cWLF6hUqRLvOETFvHjxAq6urkhKSoKPjw+aN2/OOxL5n5E7QxESl1qi156v+dzJLs+fPy9agfzUQHEXFxc0b96c23SAwMBATJgwAfHx8fjhhx/w/fff0zxoBdDch/0CK0vfSsH/CtD5JyOQkpErSN8K+bTQ0FBoa2tr5DGDeXl52LZtG0aOHEnFJCmVWrVqISgoCD169EDHjh1x7tw5dOjQgXcsjReTlI5rsSmCX7dAxnAtNgV3Yv9GfERoUQH54UDxUaNGoXPnzqUaKC60d+/eYd68edi2bRvatm2LM2fOoFGjRlwzaRIqKAVwOCxBkCZoAFjrG42qFXQ1YmYVD7du3YKtra1Gzl48deoUXr16halTp/KOQlSYoaEh/Pz80K9fP7i6uuLo0aNwc3PjHUujHQxN+GqLVanJCtBlyjKkXd6KBg0awMXFRZCB4kI7ffo0pkyZgvT0dHh6emLSpEk0lF/B6JF3GfHqWyGlY2Vlha5du2Ljxo28oyick5MTRCIRAgMDeUchaiA3NxfDhw/H6dOnsWvXLowaNYp3JI3VYY0/4tOy5Hb9KhIpTo5tKshAcaF9OKC8V69e2Lx5M20a44TK9zJaeCoCUoHfFUplDAtPCbdTj/zjzZs3iI6OhoODA+8oChcREYFr167R6iQRjK6uLo4cOQJ3d3eMHj0av//+O+9IGikjV4oEORaTAPBWKoFJTeUq0hhj2LlzJxo1aoTAwEAcPnwYZ8+epWKSI3rkXQby7luJTU7XuMGo8nT79m0A0MiC0tPTEzVq1EC/fv14RyFqREtLC9u3b4eRkRFmzZqF1NRULF26lMZRKVB8aibk/ZiRAXiWmgnrmsrRex0bGwsPDw9cvXoVo0aNwrp162BkZMQ7lsajgrIM5Nm3oiUW4cDNBPzkZi34tTVVaGgoKleuDAsL9dz09Lkhu+/evcOBAwcwZ84caGtr845J1IxIJMLq1athaGiI+fPnIy0tDX/88Qf1rylInoDtVspwny+RSqVYv349fvzxR1SvXh0+Pj7o2rUr71jkf6igLAP/x8nyaYLGP6uU/tHJ+AlUUArl1q1bsLe3V6sXuqJjwB4nIyHtE8eAGeqjSs7fKKhQFRMnTuQVk2iA77//HoaGhvDw8MCbN2+wZ88eegOjADoSxfw8U9R9PufevXsYN24c7t27VzSgvHz58lwzkX+jgrKUFNG3kpCahcxcqUYf5SQUxhhCQ0PVpqgqzgB9BiA+LQvxMgNUG7MJ33snYkW/yrTZi8jNhAkTULlyZQwfPhzv3r3D0aNHuY+SUXd1jcpDBMj1sbfof/fh4cMB5Y0bN8aNGzc0sm1JFajPUo2CKapvZf+pSwgODsaDBw/w/PlzZGRkgDbml1xCQgKSk5PV4gfR4bAEuKwPREhcKgB8fZVcrAUACIlLhcv6QBwOS5B3RKLBBg0ahPPnz8Pf3x+urq54+/Yt70hqrbyuBKZyfpNoaqTPZWEjICAATZs2xbp167B06VLcvn1bLX6Gqyta+iolRfWTzPz2O+S9/PeMSy0tLVSuXPmL/1SqVOmzH6tQoYLGNc3funULgOpvyKEB+kQVdO3aFVeuXEGPHj3g7OyMS5cuoVq1arxjqS1nKxPsD42XWz+/s6WJ4Nf9krdv32LevHnYvn072rVrh3PnzqFhw4YKzUBKjgrKUlJUP8llH2+YaOfh7du3X/3n+fPnRf/7zZs3yMvL++Q1tbS0vlhwfu0fVSxIQ0NDYWZmptIvajRAn6iSVq1aISgoCF27dkW7du1w+fJl1K1bl3cstWQueiXXfv4RrRT3c+LUqVOYOnUqMjIysHnzZnh4eKhV37s6o4KylBTVt9LC0rTUjxpycnKKVYi+e/cOb9++xd9///2vf5+Tk/PJ64rF4hKtiH6qIFX0D4hbt26p9OpkYloWlpyNFPSaP56NRJsGxtRTSeSmSZMmuH79Orp06YJ27drB19cXjRs35h1LbTx9+hRz587FiRMnYDHxD0iN6kPIurLwLG9FjK97+fIlpk2bhpMnT6J3797YvHkzateuLff7EuFQQVlKhX0r8jydoKx9K3p6eqhevTqqV69eqs/PyckpKjaL88/Lly+LXZCWZoW08HMMDAxKVJBKpVKEh4dj2bJlpfpzUAbyHKC/f5yjoNcl5EP16tVDcHAwXF1d0b59e3h7e6v0mztlkJmZiVWrVmHNmjUwMjLCgQMH0L5bX3TZECToqW0SsQgr+tkIdr1PYYxh165dmDNnDnR0dHDkyBEMGjRI5Z6CESooy0Td+lY+pqenBz09vVI/Jv5UQfqlAvXRo0f/+v/Z2dmfvK5IJCpRQZqSkoKsrCyYmpri3bt3JS5IeaMB+kTVVa9eHQEBAejVqxc6deqE06dPw8XFhXcslcMYw6FDhzBv3jykpKRgzpw5mD9/PipUqAAAWOpmjfknhTtlbZmbtVyfYMTGxmLixInw9/eHu7s71q5dSwPKVRid5V0GMUnp6LIhSG7X95vtpNEv9Lm5uSVaIf34n7IWpJ/7PRUrVlRoQfrT2Ui5vnEZ6WhGA/SJQmRmZmLgwIG4evUqDh06hP79+/OOpDJu376NmTNnIiQkBP3798fatWs/ebZ2WTbufWhuVytMdTYv83U+RSqVYt26dViyZAlq1KiBrVu3okuXLnK5F1EcKijLaOTOUITEpQr6Yl/Yt0KPIssmLy8P7969w5QpU3D//n14enqWqCDNyvp0O4NIJELFihVLvamppAVphzX+cm2tMDPSR+AcZ7ldn5AP5eXlYdSoUTh27Bi2b9+OsWPH8o6k1F69eoVFixZh9+7dsLa2xu+//45OnTp98XMOhyVgydlISP832aG4tMQiSMQiLHOzltuGvbt372LcuHG4f/8+Zs2ahWXLltGAcjVBj7zLaEU/G7isDxS0oFRE34om0NHRQdWqVfH48WN07NixxO+ACwvS4m5qio2N/de/z8zM/OR1P1WQfm41VM+gMuLTdIT44/gsGqBPFElHRwcHDx5ElSpVMG7cOKSlpWHOnDm8YymdvLw8/PHHH1i2bBm0tbWxadMmTJw4ERLJ1/+eDrU3RdsGxl89/KBQ4cfb1DfCin42cnnMnZ2djZ9++gm//fYbrK2tcfPmTdjb2wt+H8IPvYKUUR1DfcH7VibYVaKdtwLJyMhAZGQkZs6cWeLPLSxIq1atWqp75+fnl+iR/ZMnT/5TkGqb1EPNsRtLdf/iYgCepWbCumYlud6HkEJaWlrYvHkzjIyMMHfuXKSlpeGXX36hjRj4p0/y4sWLmD17NuLi4jB58mQsXboUhoaGJbpOHUN97B/n+P/Hs0YnIyH1E8ezGunD2dIEI1qZyq3Fyt/fHxMnTkRiYiKWLVuGuXPn0rGcaogKSgEMtTdFSkauIH0r+jF+WLF1Lzqa+qJly5YCpNNs4eHhkMlkXHaVamtrw9jYGMbGxqX6/Pz8fFx/9ALufwo7LuhTFDWon5BCIpEIP//8MwwNDfHdd98hLS0Nnp6e0NLS4h2Nm0ePHmH27Nm4dOkSOnfujJMnT6JJkyZluqZFNQP85GaNn2CNzFwpnqVmIk8qg45EjLpG5eX6ZOLt27eYO3cuduzYgfbt2+P8+fOwsrKS2/0IX1RQCmSaswWMK+iWuW/F1aItune/ic6dO+PSpUto3bq1HFOrv1u3bqF8+fIqOftOW1sbVY2qKOReihrUT8jHvv32W1SpUgXjx4/HmzdvsH//fujoyLfNQ9m8ffsWy5Ytw8aNG1GnTh2cOnUKffr0EXzFtryuRGFPIk6ePImpU6ciMzMTXl5emDhxokpN1yAlR/91BTTU3hR+szugTf1/xh5oib/8w6Dw423qG8FvdgcMsTdF5cqV4evri2bNmqFr164ICpLfLnJNEBoaipYtW6rsqkfhAH15Ev3vPoTwMmbMGBw/fhynT5+Gm5vbZ/uP1U1BQQG2b98OS0tLbNu2DcuWLUNUVBT69u2rso////77b/Tv3x8DBgyAg4MDHj58iEmTJlExqQHov7DACvtWLs9ywkhHM5gZ6f+nIBDhn521Ix3N4DfbCfvHOf6rZ9LAwKBo+G+3bt1w5coVhX4N6kTVT8gpHKAvT2UdoE+IEPr16wdvb++ik3XS0tJ4R5Kra9euwd7eHhMnTkS3bt3w+PFjLFiwAHp6eryjlQpjDNu3b0fjxo1x/fp1HD16FKdPn0atWrV4RyMKQmODFKC0fSvZ2dno378//P39cerUKXTv3l0BadXHy5cvUbNmTRw/fhwDBgzgHafU5DmHUgSGYfa18Ut/W8GvTUhphIWFoXv37qhRowZ8fX1Ro0YN3pEElZCQgHnz5uHIkSOwt7fHH3/8gVatWvGOVSYxMTGYOHEiAgICMGbMGKxdu7bEm4iI6qMVSgUo7FuxM60C65qVir0aVK5cOZw+fRpdu3ZF3759cebMGTknVS+3bt0CAJVeoQSA4Y6mcikmAYBBhO3fj8Ly5cvVfkWIqAZ7e3tcu3YNb968Qdu2bfHkyRPekQSRlZWFpUuXomHDhggMDMSePXtw8+ZNlS4m8/PzsXr1ajRt2hQJCQm4fPkydu3aRcWkhqKCUsnp6uri+PHjcHNzw8CBA3Hs2DHekVRGaGgoatSogdq1a/OOUiYW1QzQ3tz4qz25JaUlFqFlrfIY7OqEFStWwNTUFLNnz0ZiYqKg9yGkpBo1aoTr169DIpGgXbt2iIgQbiybojHGcPToUTRq1AgrVqzAjBkzEB0djdGjR6t0X+GdO3fg6OiIhQsXYtq0aYiIiKDjNDWc6n43axAdHR0cOnQIgwcPxtChQ3Hw4EHekVRCYf+kqja3f2hFPxtIBC4oJWIR1g9zwKZNmxAfH4/Zs2dj7969qF+/Ptzd3REVFSXo/QgpCTMzMwQHB6N69epwcnJCSEgI70gldu/ePXTs2BFDhgyBra0tIiMjsWrVKhgYqO6RullZWZg3bx4cHBxQUFCA0NBQrFmzBvr6NDtZ01FBqSIkEgn27duHUaNGYeTIkdi9ezfvSEpNJpMhLCxM5R93FyocoC+kZW7WRZvBTExMsHz5csTHx2P16tXw8/ODtbU1+vTpgxs3bgh6X0KKy8TEBAEBAbCxsUGXLl3g4+PDO1KxvH79Gh4eHmjevDlev34NHx8fnDlzBubm8jkbW1GuXr2Kpk2b4o8//sDy5ctx+/ZtmpdMilBBqUK0tLSwc+dOTJw4EWPHjsXWrVt5R1Jajx8/xvv37+HoqD7noQ+1N8WcrpaCXGtuV6tPntVrYGCAb7/9FnFxcdi9ezeio6PRpk0bODk54eLFi6A9fETRKlWqBB8fH3Tq1Am9e/fG0aNHeUf6rPz8fGzYsAEWFhY4evQoNmzYgPv376Nr1668o5XJmzdvMH78eHTu3Bm1atXCX3/9hQULFtBpN+RfqKBUMWKxGF5eXpgxYwYmTZqEP/74g3ckpXTr1i2IRCK1e/c8zdkCq/rbQFciLnFPpZZYBF2JGKv722Cq85dXSnR0dODu7o7IyEicPn0a+fn56NmzJ5o1a4YDBw4gPz+/LF8GISVSrlw5nDx5sqjtZ9u2bbwj/YePjw+aNm2K7777Dt988w2io6MxY8YMlS+6Tpw4gcaNG+PYsWPYunUr/P39YWkpzBtbol6ooFRBIpEIGzZswNy5czFz5kysWbOGdySlExoaioYNG6JSJfU7n1qIAfrFJRaL0adPH4SEhCAwMBB16tTByJEjYWFhgY0bNyIrK6v0XwghJaCtrY19+/Zh2rRp8PDwwKpVq5RixTwmJgZubm7o1q0bqlWrhjt37sDLywtVq1blHa1MCgeUDxw4EI6OjoiKiqLTbsgX0TRjFSUSibB69Wro6upi3rx5yMnJweLFi3nHUhqqPtD8awoH6MckpeNgaAL8o5ORkJqFD19eRfhnaLmzpQlGtDKFuUnpNwKIRCI4OTnByckJf/31F3799VfMnj0bS5cuxYwZMzB16lQYGRmV+esi5EvEYjF+//13GBoaYsGCBUhNTcWvv/7KZePd+/fv8fPPP2PDhg2oWbMmjh07hgEDBqj8JkCZTIYdO3Zg7ty5KFeunNp8XUQBGFF5y5cvZwDYokWLmEwm4x2Hu+zsbCaRSJinpyfvKAqVkZPPHrx4y+7Ep7EHL96yjJx8ud7v6dOnbNq0aaxcuXJMX1+fzZw5k8XHx8v1noQU+v333xkANnbsWJafL9/v9Q8VFBSwXbt2sWrVqrFy5cqxZcuWsaysLIXdX54eP37MOnToUPTnmpaWxjsSUSFUUKqJX3/9lQFgc+bM0fiiMiQkhAFgt2/f5h1FIyQnJ7PFixezKlWqMIlEwkaNGsUePHjAOxbRAPv27WNaWlqsf//+LDs7W+73CwkJYS1btmQA2DfffMMSEhLkfk9FyMvLYytXrmS6urqsfv36zM/Pj3ckooKooFQjhe/Yp0+frtFF5YYNG5iuri7Lzc3lHUWjpKens3Xr1rHatWszAKx3797s+vXrvGMRNXf27Fmmp6fHOnXqxN6/fy+Xezx//pyNGDGCAWDNmzdn165dk8t9eLh9+zaztbVlYrGYzZ07l2VmZvKORFQUddeqkRkzZmDLli3YuHEjJk2aBJlMxjsSF6GhoWjevDl0dHR4R9EoFSpUwOzZs/HkyRPs2bMHsbGxaNu2Ldq3b48LFy4oxQYKon569+4NHx8f3L59G507d0Zqaqpg187JycEvv/wCS0tL+Pr6YseOHbh16xbatWsn2D14ycrKwty5c+Hg4ADGGG7duoVff/2VBpST0uNd0RLh7dq1i4lEIubu7s6kUinvOArXoEEDNnPmTN4xNF5BQQE7c+YMa926NQPAmjRpwvbt28fy8vJ4RyNqKDw8nFWtWpU1atSIJSYmlulaMpmMnThxgtWtW5dJJBL23Xffsbdv3wqUlD8/Pz9Wv359pqury1auXEl/J4kgaIVSDY0ZMwYHDhzA/v37MWrUKEilUt6RFCY1NRVPnjxR6x3eqkIsFsPNzQ3Xr19HUFAQzMzMMGrUKJibm+OPP/5AZmYm74hEjTRv3hzBwcHIzMxEu3btEBMTU6rrFJ5JPWDAADRu3BgPHjzA2rVr1WIE2Zs3bzBu3Di4uLigTp06iIiIwPz581V+ViZRDlRQqqlhw4bh8OHDOHr0KIYOHYq8vDzekRTi1q1bAKBWJ+SoOpFIhPbt2+P8+fP466+/4OTkhG+//RZmZmZYunSpoI8oiWaztLREcHAwypUrh3bt2uHevXvF/tzU1FRMmzYNtra2eP78OS5cuIALFy7AyspKfoEVhDGG48ePo1GjRjhx4gS2bduGq1evwsLCgnc0ok54L5ES+Tpz5gzT0dFhvXv3Zjk5ObzjyN1PP/3EjIyMNHpTkip4+vQpmz59Oo0cInLx+vVr1rJlS1axYkUWFBT0xd+bn5/PNm7cyKpUqcIqVqzIfvvtN7Xa0Pf8+XPWp08fBoD169ePvXjxgnckoqaooNQA3t7eTFdXl3Xr1k1t5qV9Tvfu3Vn37t15xyDFlJyczH788UdmaGjIJBIJGzlyJIuIiOAdi6iB9+/fM2dnZ6anp8fOnz//yd/j5+fHrK2tmUgkYuPHj2evXr1ScEr5KSgoYFu2bGEVK1Zk1atXZ8ePH+cdiag5euStAbp164YLFy4gMDAQvXr1UtveNfa/nYrUP6k6qlatiqVLlyI+Ph5r1qxBQEAAbGxs0Lt3b1y/fp13PKLCDAwMcPHiRbi6uqJv3774888/iz4WFxeH/v37w8XFBZUrV0ZYWBi2b9+OatWqcUwsnOjoaDg7O2PSpEkYNGgQoqKiMGDAAN6xiJqjglJDdO7cGZcuXcKtW7fQvXt3pKen844kuKdPnyI1NZUKShVUoUIFzJo1C0+ePMHevXsRFxeHdu3aoV27djh//rzGjsAiZaOnp4fjx49jxIgRGDFiBNatW4dFixahcePGCAsLw59//olr166hRYsWvKMKIj8/HytXrkTTpk3x4sULXLlyBTt27ECVKlV4RyOagPcSKVGskJAQVrFiRdaqVSv25s0b3nEE9eeffzIA7PXr17yjkDIqKChgZ8+eZW3atGEAmLW1Ndu7dy+NNyGlkp+fz1xdXRkAJpFI2OLFi1lGRgbvWIIKCwtjzZo1Y1paWmzevHk0oJwoHK1QapjWrVvjypUrePz4MVxcXJCWlsY7kmBu3bqF+vXrw9jYmHcUUkZisbjosfe1a9dQr149jB49Gubm5vi/9u48Lsqqfx/4NTMIKu4YmguYoiSKe7kigoqAMkn64JpbmfbkmoKKqBVumAoupaVmahb2FZcZETdEQCxwSSFQQRGGlERAERlim/v3RzW/ejITZ7kHuN5/NnDOB18xXHPucz5n06ZN1XbbBulfQkICnJyccPLkSXTu3Bnl5eUoKChAnTp1xC5NL4qKirBw4UL07t0bEokECQkJCAoKYoNyMjoGyhqoV69eiIqKQmZmJlxcXPDgwQOxS9KL+Ph4tguqhgYMGAClUomkpCQ4OztjwYIFsLGxwYcffojc3FyxyyMTlZ2djalTp6J3795Qq9WIiopCUlISPvvsM2zZsgVTpkxBWVmZ2GXq5MyZM3B0dMSnn36KNWvWICEhAT169BC7LKqpxF4iJfH89NNPQrNmzQQHBwfh3r17Ypejk9LSUsHCwkIIDg4WuxQysIyMDGHOnDnalkNz5swRMjIyxC6LTMSvv/4qBAUFCfXq1ROsrKyEbdu2/e3GsG+++UYwMzMTvLy8qmTni7y8PGHq1KkCAGHQoEFCamqq2CURsW1QTXfjxg2hRYsWQocOHXS+rkxMly9fFgAIFy5cELsUMpIHDx4IK1asEJo0aSLIZDJh4sSJQmJiothlkUg0Go2gUCgEOzs7QSaTCXPnzhXy8/P/8euPHz8u1KlTR3B2dhYKCgqMWOmL02g0woEDBwRra2uhYcOGwo4dO9hzl0wGH3nXcPb29oiJicGvv/4KZ2dnZGZmil3SC4mPj4eZmRm6desmdilkJE2bNsWHH34IlUqFDRs2IDo6Gl26dMGIESNw/vx5scsjI0pJSYG7uzvkcjleeeUVJCYmIiQk5Jmnmz08PHD69GlcvXq1Smz9uXv3LkaOHIkxY8ZgwIABSElJwTvvvAOJRCJ2aUQAuIeSALRr1w4xMTEAgIEDB+L27dsiV1R5CQkJ6NKlS7XZaE/Pz9LSEnPnztW2HMrIyICTkxP69+8PpVLJlkPV2MOHDzFv3jx06dIFt2/fxtGjR3Hy5Ek4ODg81/f3798f0dHRuHv3LpycnKBSqQxcceVpNBps374dDg4OSEhIQFhYGMLCwtCiRQuxSyP6CwZKAgDY2toiOjoatWvXxsCBA3Hz5k2xS6oUHsihWrVqYdKkSUhMTIRSqYREIoFcLoejoyP27NlT5Q9g0P9XUVGBzz//HB06dMCuXbuwatUqJCcnQy6XV3rFrmvXrjh//jxKSkrQv39/3Lhxw0BVV97NmzcxaNAgvPfeexgzZgyuX7+ON998U+yyiJ6KgZK0WrVqhejoaDRq1AjOzs5ITk4Wu6TnUlBQgBs3brChOQH4reXQH4+9z58/j3bt2mHKlClo164dQkJC8OTJE7FLJB1ER0ejZ8+emDlzJkaMGIHU1FQsWrQIFhYWLzymnZ0dzp8/j4YNG8LJyQmXL1/WY8WVV1ZWhlWrVqFr167Izs7G2bNn8cUXX6BRo0ai1kX0LAyU9BfNmzfHuXPn0Lx5cwwaNAjXrl0Tu6R/dfnyZQiCwBVK+pv+/ftDoVAgKSkJLi4u8PX1ha2tLVasWMGWQ1VMZmYmfHx8MGjQINSuXRvx8fHYvXs3Xn75Zb2M37JlS8TExKBdu3ZwcXHBuXPnnvt7i0rKkXyvAD+qHiL5XgGKSspfuI6LFy+iZ8+eWLFiBebNm4fExES4uLi88HhExiIRBEEQuwgyPfn5+XBzc0N6ejpOnTqFXr16iV3SP1qzZg3WrFmDR48eQSrlZyT6ZyqVChs3bsSOHTsgCALeeecdLFiwALa2tmKXRv9ArVYjKCgI69atQ+PGjREUFIQJEyYY7Hf9yZMn8Pb2RmxsLL777jvI5fKnfl3a/ULsj1ch6mYOVPlq/PkPqQSATZO6cLG3xoTeNmjfrP6/zltUVITly5cjJCQE3bp1w86dO9G9e3f9/FBERsBASf/o0aNH8PDwQEpKCk6cOIG+ffuKXdJTeXt74/Hjx4iMjBS7FKoi8vLysHXrVmzZsgWPHj3C2LFjsWjRIjg6OopdGv1OEAQcOHAAvr6+yMnJwcKFC7FkyRLUq1fP4HOXlJRgwoQJOHLkCL788ktMmjRJ+1pWvhr+h5MQeysXMqkEFZp//hP6x+tOdk2x2tsRrZs8/faa06dPY8aMGcjOzsZHH32EDz74AGZmZnr/uYgMics59I8aNWqEU6dOoWvXrnBzc9OeBDclgiDwQA5VmpWVFVasWIHMzExs3LgRsbGx6NKlC4YPH47Y2Fjwc7a4rly5goEDB2LcuHHo1asXrl+/jlWrVhklTAKAhYUFDhw4gClTpmDy5MkICQkBAIReVGFIcDQupOcBwDPD5J9fv5CehyHB0Qi9+NdT5Pn5+ZgyZQrc3NzQpk0bJCUlwc/Pj2GSqiQGSnqm+vXrIyIiAq+//jrc3d1NbhXw7t27yM7O5oEceiGWlpaYM2cObt26hb1790KlUmHgwIHavZdsOWRcOTk5mD59Onr16oWHDx/i9OnTOHz4MNq2bWv0WmQyGXbs2AE/Pz/Mnz8fI5duw+JDSSgp1/xrkPxfFRoBJeUaLD6UhK1RadrV144dO+LIkSPYuXMnIiMjYWdnZ6Cfhsjw+MibnktxcTHefPNNREVF4fDhw/Dw8BC7JABAWFgYRo8ejXv37ultcz7VXIIg4Pjx41i7di3Onz8PBwcH+Pn5Ydy4cTA3Nxe7vGqrtLQUW7duxUcffQSZTIaPP/4YM2fONJmVuskff4Ho4pZ6G6/V3XOI27ceo0aNwpYtW/jeRdUCVyjpudSpUwdHjhyBm5sbRo4cCYVCIXZJAH5raN6qVSu+IZNeSCQS7WPvuLg42NnZaVsOBQcHs+WQAURERKBLly7w9fXFW2+9hbS0NMyaNctkwmRWvho/lLUGoJ+1F0EQkNWsH3Z8ewgHDx7kexdVGwyU9NwsLCxw8OBBeHl5YdSoUTh48KDYJSEhIYGPu8kg+vXrh6NHj+Knn37C4MGD4efnBxsbGyxfvtzkr+mrClJTUzF8+HB4enqiRYsWuHr1KrZu3QorKyuxS/sL/8NJKNcI+O3stu4kEgnMapkjuog33VD1wkBJlWJubo7Q0FD4+PhgzJgx+Oabb0SrpaKiApcuXeKBHDKoTp064auvvsLt27cxefJkbNiwAba2tpg9ezYyMjLELq/KKSgowMKFC9G5c2ekpKQgLCwMkZGRJnnCPu1+IWJv5VZ6z+S/qRCA2Fu5uJVTqNdxicTEQEmVZmZmhr1792LSpEmYOHEidu/eLUod169fx5MnT7hCSUZhY2OD4OBgqFQqLF68GN9++y3s7OwwceJEJCYmil2eydNoNNi1axc6dOiAbdu2YcWKFdqrBCt7XaKx7I9XQSY1TG0yqQRf/2B6d4cTvSgGSnohMpkMu3btwrvvvotp06bh888/N3oN8fHxkEqlJt10naofKysrLF++HJmZmQgODsb58+fRtWtXDB8+HDExMWw59BRxcXF4/fXX8c4772Do0KFITU3F0qVLUbt2bbFLe6aomzl6X538Q4VGQFRqjkHGJhIDAyW9MKlUim3btmHOnDmYOXMmNm/ebNT5ExIS4ODgYLTedER/ZmlpidmzZyMtLQ379u2DSqWCs7Ozdu8lWw4BP//8M8aPH48BAwZAIpEgLi4OX3/9NVq21N+JaUN5UlIOVb7aoHOo8tQ6XdNIZEoYKEknEokEISEh8PX1xdy5c/HJJ58YbW4eyCFTUKtWLe1j7/DwcNSqVQsjR45E586d8dVXX6G0tFTsEo2uuLgYgYGBsLe3x9mzZ/Hll18iPj4e/fr1E7u055aZV6Snc93/TACQkVdk4FmIjIOBknQmkUgQFBSEgIAA+Pn5ITAw0OBzqtVqJCUl8UAOmQyJRAJPT0/ExMQgLi4O7du3x9SpU9GuXTts3LgRhYXV/wCGIAg4ePAgOnbsiMDAQLz//vtITU3F1KlTDXb3tqGUlhtnhdlY8xAZWtX6DSeTJZFIEBgYiMDAQCxfvhwBAQEG3Ut25coVVFRUcIWSTNIfj72Tk5MxZMgQLFq0CLa2tli2bFm1bTmUmJgIV1dX/Oc//4GjoyOSk5Oxbt06NGjQQOzSXoi5mXH+PBprHiJD4//JpFcBAQFYt24dVq1aBT8/P4OFyvj4eNSpUwedO3c2yPhE+uDg4IDdu3cjPT0dU6ZMQXBwMGxsbDBr1izcuXNH7PL0Ijc3F++99x66d++OX375BREREVAqlWjfvr3YpemkjZWlnjpP/jPJ7/MQVQcMlKR3vr6+2LRpE9avX4+5c+caJFQmJCSgZ8+eJnObBtGztG7dGhs3boRKpYK/vz8OHDiA9u3bY8KECbh27ZrY5b2QsrIybN68Ge3bt8e3336LDRs2IDExEe7u7mKXpheWFmawaVLXoHPYWNWFpQXfw6h6YKAkg5gzZw62b9+OLVu2YObMmXo/8coDOVQVNWnSBMuWLUNmZiZCQkIQFxeHbt26wdPTE9HR0Qb58FVUUo7kewX4UfUQyfcK9HKq+PTp0+jWrRvmzZsHHx8fpKWlYd68eahVq5YeKjYdHeqVAYJh9jjKpBK4dLA2yNhEYuBHIzKYGTNmwNzcHG+//TZKS0uxc+dOyGQyncfNyclBRkYGD+RQlVW3bl3MmjULM2bMwHfffYegoCAMGjQIffr0waJFiyCXy3U6xJJ2vxD741WIupkDVb76L6eVJQBsmtSFi701JvS2Qftm9Z973Nu3b2PBggU4evQonJyccPnyZXTv3v2F6zRFgiDgzJkzCAwMxA8pGWgxfZtB5qnQCJjYx8YgYxOJgSuUZFBTp07F119/jX379mHSpEkoL9d9dSQhIQEAuEJJVV6tWrW0j72PHz8Oc3NzeHt7o1OnTti9e3elWw5l5avx1q54DA2Jwb74TGT+T5gEfmtVk5mvxr74TAwNicFbu+KR9S/9FgsLC7FkyRI4ODjgypUrOHDgAKKjo6tVmBQEAceOHUPfvn3h5uaG4uJiHPxyKwbYWen9thyZVAInu6aws37+ME9k6hgoyeDGjx+P0NBQfPfddxg7dqzOffni4+NhbW0NW1tbPVVIJC6JRAIPDw9ER0fjwoULsLe3x7Rp09C2bVts2LDhuVoOhV5UYUhwNC6k5wHAv97w8sfrF9LzMCQ4GqEX/34NoEajwd69e2Fvb49NmzbB398fN27cgI+Pj8lel1hZGo0Ghw4dQs+ePeHl5QWZTIaIiAgkJCRALpdjjXcXmOk5UJpJJVjtbXp3lxPpgoGSjGL06NEICwuDUqnE6NGjUVJS8sJj/bF/srr8QSP6s759++LIkSNISUmBm5sblixZAhsbGwQEBCAn5+lX9W2NSsPiQ0koKddU+qrACo2AknINFh9KwtaoNO1/j4+PR9++fTF58mQMHDgQN27cwIoVK1C3rmEPqhhLRUUFQkND0bVrV4waNQoNGzZEZGQkzp8/D3d3d+37S+smdfGRvJNe5/5Y3gmtDXzgh8jYGCjJaORyOY4ePYpTp05h5MiRKC4ufq7v+8uhgrsFSLhyjY+7qdrr2LEjvvzyS6Snp2PatGkICQmBra0t3n//faSnp2u/LvSiCutPpeplzvWnUvH56SRMnjwZffr0QWlpKWJiYhAaGgobm+qx36+8vBx79uyBg4MDxo0bh5YtWyI2NhZRUVFwdXV96gfVsa/ZYKFbB73M7+tmjzGvVY9/S6I/kwiG7D5N9BSRkZHw8vJC3759oVAoYGn59z5szzpUIAgCrOtIMLx7m0ofKiCqqvLz8/HZZ59h06ZNyM/Px5gxYzDl/QWYfSIHJXq7bUWAUF6G4oP+WOX/AaZNm6aXg3SmoLS0FHv27MGaNWtw584deHl5ISAgoFIfTkMvqrBCkYxyjVCplWCZVAIzqQQfyzsxTFK1xUBJooiJicHw4cPRvXt3hIeHo37930JhVr4a/oeTEHsrFzKp5Jlv2n+87mTXFKu9HfkIiWoEtVqN3bt3Y/369VD3noY6bboBEv09bJIIGvR+pTFCZwzQ25hi+vXXX7Fr1y4EBQUhKysLo0aNQkBAALp16/ZC4/E9iujpGChJNN9//z3c3d3h4OCAiIgInEh7rNOn/4/knTCWn/6phrh+7xE8tsQZbPwz8wdW6VPIarUan3/+OT755BPcv38fY8eOhb+/Pzp10s9+SO1TlNQcqPKe0prJqi5cOlhjYh+bKv3vSPS8GChJVJcuXYKbmxuaD54Ctd1gncdb6NYBs1yq9pVvRM/jQ0Uy9sVnVvoQzvOQSSV4q7ctPtTzYRRjKCwsxGeffYYNGzYgPz8fb731FpYsWYIOHfSzB/JpikrKkZFXhNJyDczNpGhjZckbcKjGYaAk0X0SFodPLz3S23hBbzpynxJVe86fRCHzX/pH6sLWqi6iF7oYbHx9e/ToETZv3oyQkBA8efIEU6dOxeLFi/HKK6+IXRpRjcCPUCSqrHw1dl59rNcxlyuS0a9dU+5XomrrSUk5VAYMkwCgylOjqKTc5FfacnNzERISgi1btqC0tBTTp0+Hn58fWrVqJXZpRDUK2waRqPwPJ6Fcz4/syjUC/A8n6XVMIlOSmVf0txtw9E0AkJFXZOBZXtz9+/fh5+eHNm3aIDg4GNOnT8edO3ewefNmhkkiEZj2R0+q1tLuFyL2Vq7ex63QCIi9lYtbOYXcDE/VUqne2gSZxjyVcffuXaxbtw5ffPEFatWqhTlz5mD+/Pl46aWXxC6NqEbjCiWJZn+8Su935P5BJpXg6x/+fpUcUXVgbmact25jzfM8MjMz8d5776Ft27bYu3cvFi9ejMzMTKxevZphksgEmM67BdU4UTdzDHJCFfhtlTIq9enX1BFVdW2sLGHoi0clv88jtlu3buHtt9+GnZ0dDh48iA8//BCZmZlYsWIFGjduLHZ5RPQ7BkoShTEPFRBVN5YWZrAx8KEzG6u6oh7IuX79OiZOnAh7e3uEh4dj7dq1yMjIwJIlS9CgQQPR6iKip2OgJFHwUAGRblzsrQ26ZcSlg7VBxv43iYmJ8PHxQadOnRAdHY1Nmzbhzp07WLBgwVOvaSUi08BASaKoyYcKiPRhQm8bg24ZmdjHuL1cL126hJEjR6Jr1664ePEitm/fjlu3bmHWrFmoU6eOUWshospjoCRR1MRDBUT61L5ZfTjZNdX7KqVMKoGTXVOjdUi4cOECPDw88NprryElJQVfffUVUlNT8e6778LCwsIoNRCR7vjXlkRRkw4VEBnKam9HmEklgB4vPDOTSrDa21Fv4z2NIAg4d+4cBg8ejP79+0OlUuGbb77B9evXMXnyZNSqVcug8xOR/jFQkiiMcajAUlDjx4s/oKKiwqDzEImlef1aaJkdB0j09/HsY3kng90yJQgCTp48iYEDB8LFxQX5+fk4ePAgkpKSMG7cOMhkMoPMS0SGx0BJojHkoQKJoMGjlAtwcnJCs2bNMHnyZISFhaGwsNAg8xEZW2lpKcaNG4fYPUHwaKmfbga+bvYY85r+904KggClUok+ffrA3d0dpaWlUCqVuHLlCkaNGgWplH+KiKo6/haTaAx5qECQSHH2i4/w/fff491338Xly5cxevRoNG3aFO7u7vjss8+QlZVlkLmJDK2kpAQ+Pj5QKBQICwvDtllvYO2bjrAwk1b6Q5pMKoGFmRRBbzrifRc7vdap0WgQFhaGHj16QC6Xw9zcHCdPnsQPP/yAESNGQKLHlVUiEpdEEPS4+Yaokt7aFY8L6Xl6DZYyqQT92lph39u9//Lf09PToVQqoVAoEBMTg/LycnTr1g1yuRxyuRw9evTgHzgyeb/++itGjx6NM2fO4NChQ/D09NS+lpWvhv/hJMTeyoVMKnnm79UfrzvZNcVqb0e9PuauqKjAgQMHsGrVKqSkpMDV1RXLli2Ds7Mzf8eIqikGShJVVr4aQ4KjUaLH9j4WZlKcme/8zD+Qjx49wokTJ6BQKHD8+HEUFBSgZcuWGDFiBORyOVxdXVG7dm291USkD8XFxfD29kZ0dDSOHj0KNze3p35d2v1C7I9XISo1B6o89V96vkrwW9Nylw7WmNjHRq+nucvKyrB//36sXr0aaWlp8PDwQEBAAPr166e3OYjINDFQkuhCL6qw+FCS3sYLetOxUvvAysrKEBsbC6VSiaNHj+LOnTuwtLSEm5sbvLy8MHz4cFhbi9PkmegParUab7zxBuLi4qBUKjF48ODn+r6iknJk5BWhtFwDczMp2lhZ6v0GnJKSEuzZswdr1qxBRkYG3njjDQQEBKBXr156nYeITBcDJZmErVFpWH8qVedxfN3sddoHJggCUlJStI/Gf/jhBwBA3759IZfL4eXlhY4dO/KxHRlVUVERvLy8kJCQgPDwcDg7O4tdEoDfVkx37tyJdevW4e7duxg9ejQCAgLQpUsXsUsjIiNjoCSTEXpRhRWKZJRrhErtqZRJJTCTSvCxvJPeT6jev38f4eHhUCqVOHXqFNRqNdq1a6fdd9m/f3/2zCODKiwsxPDhw/Hjjz8iIiICAwYMELskFBUVYfv27Vi/fj1ycnIwfvx4+Pv7o2PHjmKXRkQiYaAkk2Iqhwqepri4GGfPntWuXmZnZ6NRo0bw9PSEXC6Hu7s7GjZsaNAaqGZ5/PgxPDw88NNPP+HEiRPo27ev6PV8+umn2LhxIx49eoRJkyZhyZIlsLPT7+lwIqp6GCjJJIl1qOB5aTQaXLlyBQqFAkqlElevXoWZmRmcnZ21j8ZfeeUVo9dF1cejR48wbNgwpKam4uTJk3j99ddFq+Xhw4fYtGkTNm3aBLVajWnTpmHRokVo06aNaDURkWlhoCSTZ4xDBbpSqVTalcuoqCiUlZXB0dERXl5ekMvleO2119i8mZ5bfn4+3NzckJ6ejjNnzqBHjx6i1PHgwQMEBwdj69atKCsrw4wZM+Dr64uWLVuKUg8RmS4GSiI9e/z4MU6dOgWFQoHw8HDk5+ejWbNm2pZEQ4YMQd26hn08T1VXbm4uhg4diqysLERGRqJr165GryE7OxsbNmzAtm3bIJFI8N///hcLFixAs2bNjF4LEVUNDJREBlReXo7vv/8eCoUCCoUCqampqF27NoYOHQovLy+MGDECL7/8sthlkonIycnBkCFD8MsvvyAyMhKOjo5GnT8rKwvr1q3Djh07YGFhgdmzZ2PevHlo2rSpUesgoqqHgZLIiG7evKl9NB4XFweNRoPXX39d+2jc0dGRLYlqqF9++QWDBw9GXl4ezp49CwcHB6PNfefOHaxduxa7d+9GvXr1MH/+fMyePRuNGjUyWg1EVLUxUBKJJDc3FxEREVAoFDhx4gSePHkCW1tb7aEeZ2dnmJubi10mGcG9e/fg6uqKwsJCnD17Fvb29kaZNzU1FWvWrMG+ffvQpEkTLFiwAP/9739Rv77xD7oRUdXGQElkAkpKShAdHa19NJ6VlYUGDRrA3d0dcrkcHh4eaNKkidhlkgH8/PPPcHV1RXFxMaKioozSgic5ORmrVq3CgQMH0KxZM/j6+uLdd9+FpaWlwecmouqJgZLIxAiCgGvXrmkfjV+6dAkymQwDBgzQrl62b99e7DJJDzIzM+Hq6ory8nJERUWhbdu2Bp3v6tWrWLlyJcLCwtC6dWssXrwY06ZN4731RKQzBkoiE3f37l0cO3YMSqUSZ86cQUlJCV599VXtbT19+vSBTCYTu0yqpDt37sDFxQVSqRRRUVGwtbU12FwJCQlYuXIllEol2rZtiyVLlmDSpEncUkFEesNASVSFFBUV4fTp01AoFDh27BgePHiApk2bYvjw4ZDL5XBzc0O9evXELpP+xe3bt+Hi4gJzc3NERUWhdevWBpnn/PnzCAwMxKlTp9ChQwcsXboU48ePh5mZafVxJaKqj4GSqIqqqKhAQkKCdt9lSkoKzM3N4erqqn003qpVK7HLpP+RmpoKV1dXWFpa4uzZs3pvEi4IAqKiohAYGIhz586hU6dOCAgIwH/+8x+uZBORwTBQElUTt2/f1u67jImJQUVFBXr06KFtSdS9e3e2JBLZjRs34OrqikaNGiEyMlKvPUgFQcCJEyewcuVKXLhwAd27d8eyZcvwxhtv8JYmIjI4Bkqiaujhw4c4ceIEFAoFIiIiUFBQgFatWsHLywteXl5wcXHhQQwjS05OhqurK6ytrXHmzBm93TojCAIUCgVWrlyJS5cuoXfv3li2bBk8PT35AYKIjIaBkqiaKysrQ2xsrPbR+J07d2BpaYlhw4ZBLpfD09MTL730kthlVmuJiYkYPHgwWrRogTNnzujl31uj0SAsLAwrV65EYmIinJycsGzZMgwZMoRBkoiMjoGSqAYRBAEpKSnacBkfHw8A6Nevn3bf5auvvspAokc//vgjhgwZAltbW5w+fRpWVlY6jVdeXo7Q0FCsXr0a169fx5AhQ7Bs2TIMHDhQTxUTEVUeAyVRDXb//n2Eh4dDoVDg1KlTKC4uhp2dnbYlUf/+/XkiWAeXLl3C0KFD0b59e5w8eRKNGzd+4bHKysqwb98+rFmzBrdu3YKnpycCAgLQt29fPVZMRPRiGCiJCABQXFyMyMhIKJVKKJVKZGdno3HjxvD09IRcLsewYcPQsGFDscusMuLj4zFs2DB07NgRJ06ceOF/u5KSEuzevRtr165FZmYmvL29sXTpUvTs2VPPFRMRvTgGSiL6G41Gg8uXL0OhUECpVOLatWswMzPDoEGDtI/G27RpI3aZJisuLg4eHh7o0qULjh8/jgYNGlR6DLVajR07dmDdunXIzs6Gj48Pli5dCkdHRwNUTESkGwZKIvpXmZmZ2pXLqKgolJWVwdHRUftovFevXmxN87uYmBh4enqiV69eOHbsWKUbzT958gTbtm3D+vXrkZeXh/Hjx8Pf3x+vvvqqgSomItIdAyURVcrjx49x8uRJKBQKHD9+HPn5+WjevDlGjBgBuVyOwYMHo27dumKXKYqzZ8/Cy8sLffr0gUKhgKWl5XN/b0FBAbZu3Yrg4GAUFBRgypQpWLx4Mdq1a2fAiomI9IOBkoheWHl5OS5cuKA9NZ6WloY6depg6NCh8PLywogRI9C8eXOxyzSK06dPQy6XY+DAgThy5Ajq1KnzXN+Xn5+PTZs2YfPmzVCr1XjnnXewaNEi2NjYGLhiIiL9YaAkIr25efOmNlxeuHABGo0GvXv31u677Ny5c7VsSXTixAmMHDkSrq6uOHTo0HM1jc/JyUFwcDC2bt2KiooKzJgxA76+vmjRooURKiYi0i8GSiIyiNzcXBw/fhwKhQInT57EkydP0KZNG+2+SycnJ5ibm4td5l8UlZQjI68IpeUamJtJ0cbKEpYWz26bdOzYMYwaNQrDhg3D//3f/8HCwuKZX5+dnY1PPvkE27dvh0wmw/vvv48PPvgA1tbW+vxRiIiMioGSiAyupKQE586d065e/vzzz2jQoAE8PDwgl8vh4eGhU49GXaTdL8T+eBWibuZAla/Gn98QJQBsmtSFi701JvS2Qftm9f/yvUeOHIGPjw9GjBiB0NDQZwbkrKwsBAUFYefOnahduzbmzJmDuXPn6tzonIjIFDBQEpFRCYKAq1evQqlUQqFQ4PLly5DJZHByctKuXhrjIEpWvhr+h5MQeysXMqkEFZp/fiv843Unu6ZY7e2I1k3q4uDBgxg3bhy8vb2xf/9+1KpV66nfm56ejjVr1mDPnj2oX78+5s+fj1mzZqFRo0YG+smIiIyPgZKIRHX37l0cO3YMCoUCkZGRKCkpQceOHbXhsnfv3pDJZHqdM/SiCisUySjXCM8Mkv9LJpXATCrBiJfV2DRnDHx8fLB3796n3iZ08+ZNrF69Gvv374eVlRUWLlyImTNnon79+k8ZmYioamOgJCKT8eTJE5w+fRpKpRLHjh3DgwcP8NJLL2H48OGQy+UYOnRopfs6/q+tUWlYfypVhxEEABK0KUhE5Ba/v4Xdn376CatWrcKBAwfw8ssvw8/PD9OnT6+xrZSIqGZgoCQik1RRUYH4+HjtbT0pKSmwsLCAq6ur9tR4y5YtKzVm6EUVFh9K0luNQW86Ysxrv7X3+fHHHxEYGIjDhw/DxsYGixcvxtSpU5/rxDcRUVXHQElEVcKtW7e0t/XExMSgoqICPXv2hJeXF+RyObp16/bMlkRZ+WoMCY5GSblGbzVZmEmx3qUhPt+4GuHh4WjXrh38/f0xceJEkzvBTkRkSAyURFTlPHz4EBEREVAoFIiIiMDjx4/RqlUr7cqli4vL39r3vLUrHhfS8yq1Z/JfCRoUZ1xFk2vfYOnSpRg7duxT91MSEVV3DJREVKWVlpYiNjZW25IoIyMD9erVw7BhwyCXy+Hp6YmHFRYYGhJjsBpOzhkA+5cbGmx8IiJTx0BJRNWGIAhITk7Whsv4+HhIpVJ0nLgcRS16QoD+b+mRSSV4q7ctPpR30vvYRERVBQMlEVVbv/zyC8LDwxGUUgel5oZbQbS1qovohS4GG5+IyNRJxS6AiMhQmjdvjjETJ6PMgGESAFR5ahSVlBt0DiIiU8ZASUTVWmZeEQz9GEYAkJFXZOBZiIhMFwMlEVVrpXpsE2QK8xARmSIGSiKq1szNjPM2Z6x5iIhMEd8Biahaa2NlaYCz3X8l+X0eIqKaioGSiKo1Swsz2DQx7D3aNlZ1YWnBhuZEVHMxUBJRtedibw2Z1DDrlDKpBC4drA0yNhFRVcFASUTV3oTeNvq9cvFPKjQCJvaxMcjYRERVBQMlEVV77ZvVh5NdU72vUsqkEjjZNYWddX29jktEVNUwUBJRjbDa2xFmeg6UZlIJVns76nVMIqKqiIGSiGqE1k3q4iM937f9sbwTWhv4wA8RUVXAQElENcbY12yw0K2DXsbydbPHmNe4d5KICAAkgiAY+lYyIiKTEnpRhRWKZJRrhEod1pFJJTCTSvCxvBPDJBHRnzBQElGNlJWvhv/hJMTeyoVMKnlmsPzjdSe7pljt7cjH3ERE/4OBkohqtLT7hdgfr0JUag5UeWr8+Q1Rgt+alrt0sMbEPjY8zU1E9A8YKImIfldUUo6MvCKUlmtgbiZFGytL3oBDRPQcGCiJiIiISCc85U1EREREOmGgJCIiIiKdMFASERERkU4YKImIiIhIJwyURERERKQTBkoiIiIi0gkDJRERERHphIGSiIiIiHTCQElEREREOmGgJCIiIiKdMFASERERkU4YKImIiIhIJwyURERERKQTBkoiIiIi0gkDJRERERHphIGSiIiIiHTCQElEREREOmGgJCIiIiKdMFASERERkU4YKImIiIhIJwyURERERKQTBkoiIiIi0gkDJRERERHphIGSiIiIiHTCQElEREREOmGgJCIiIiKdMFASERERkU4YKImIiIhIJwyURERERKQTBkoiIiIi0gkDJRERERHphIGSiIiIiHTCQElEREREOmGgJCIiIiKdMFASERERkU4YKImIiIhIJwyURERERKST/wf9Ktuxz7a3iwAAAABJRU5ErkJggg==\n", + "image/png": 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\n", "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] @@ -1433,7 +1433,7 @@ }, { "cell_type": "markdown", - "id": "d33f4f6d", + "id": "22fa85d4", "metadata": {}, "source": [ "This function writes to the file `path.png` in the local directory. If Graphviz and\n", @@ -1446,13 +1446,13 @@ { "cell_type": "code", "execution_count": 39, - "id": "83db308c", + "id": "c92c0580", "metadata": { "execution": { - "iopub.execute_input": "2022-12-27T10:11:50.668789Z", - "iopub.status.busy": "2022-12-27T10:11:50.668408Z", - "iopub.status.idle": "2022-12-27T10:11:50.879037Z", - "shell.execute_reply": "2022-12-27T10:11:50.878476Z" + "iopub.execute_input": "2023-01-02T13:06:48.643208Z", + "iopub.status.busy": "2023-01-02T13:06:48.642893Z", + "iopub.status.idle": "2023-01-02T13:06:48.830067Z", + "shell.execute_reply": "2023-01-02T13:06:48.829260Z" } }, "outputs": [ @@ -1476,7 +1476,7 @@ }, { "cell_type": "markdown", - "id": "020647dc", + "id": "98f275f7", "metadata": {}, "source": [ "See Drawing for additional details." |
