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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 /_modules/networkx/algorithms/tree | |
| parent | 6ae99ab58d8b8ba50f66768c0f3aa4bb82b22196 (diff) | |
| download | networkx-0b9a02d6b3796e8ce4fed6cbce282fced15e486a.tar.gz | |
Deploying to gh-pages from @ networkx/networkx@71ad516a90c89c7294e32bf28e1f05c63c5f17e4 🚀
Diffstat (limited to '_modules/networkx/algorithms/tree')
| -rw-r--r-- | _modules/networkx/algorithms/tree/branchings.html | 36 | ||||
| -rw-r--r-- | _modules/networkx/algorithms/tree/coding.html | 16 | ||||
| -rw-r--r-- | _modules/networkx/algorithms/tree/decomposition.html | 4 | ||||
| -rw-r--r-- | _modules/networkx/algorithms/tree/mst.html | 52 | ||||
| -rw-r--r-- | _modules/networkx/algorithms/tree/operations.html | 4 | ||||
| -rw-r--r-- | _modules/networkx/algorithms/tree/recognition.html | 10 |
6 files changed, 61 insertions, 61 deletions
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> |