15 files changed, 32 insertions, 32 deletions
diff --git a/networkx/algorithms/boundary.py b/networkx/algorithms/boundary.py
index c74f47e9..068ce645 100644
--- a/networkx/algorithms/boundary.py
+++ b/networkx/algorithms/boundary.py
@@ -14,7 +14,7 @@ from itertools import chain
 __all__ = ["edge_boundary", "node_boundary"]
 
 
-@nx.dispatch("edge_boundary")
+@nx.dispatch
 def edge_boundary(G, nbunch1, nbunch2=None, data=False, keys=False, default=None):
     """Returns the edge boundary of `nbunch1`.
 
@@ -91,7 +91,7 @@ def edge_boundary(G, nbunch1, nbunch2=None, data=False, keys=False, default=None
     )
 
 
-@nx.dispatch("node_boundary")
+@nx.dispatch()
 def node_boundary(G, nbunch1, nbunch2=None):
     """Returns the node boundary of `nbunch1`.
 
diff --git a/networkx/algorithms/cluster.py b/networkx/algorithms/cluster.py
index 159aba78..83596c94 100644
--- a/networkx/algorithms/cluster.py
+++ b/networkx/algorithms/cluster.py
@@ -220,7 +220,7 @@ def _directed_weighted_triangles_and_degree_iter(G, nodes=None, weight="weight")
         yield (i, dtotal, dbidirectional, directed_triangles)
 
 
-@nx.dispatch("average_clustering")
+@nx.dispatch(name="average_clustering")
 def average_clustering(G, nodes=None, weight=None, count_zeros=True):
     r"""Compute the average clustering coefficient for the graph G.
 
@@ -280,7 +280,7 @@ def average_clustering(G, nodes=None, weight=None, count_zeros=True):
     return sum(c) / len(c)
 
 
-@nx.dispatch("clustering")
+@nx.dispatch(name="clustering")
 def clustering(G, nodes=None, weight=None):
     r"""Compute the clustering coefficient for nodes.
 
@@ -433,7 +433,7 @@ def transitivity(G):
     return 0 if triangles == 0 else triangles / contri
 
 
-@nx.dispatch("square_clustering")
+@nx.dispatch(name="square_clustering")
 def square_clustering(G, nodes=None):
     r"""Compute the squares clustering coefficient for nodes.
 
diff --git a/networkx/algorithms/core.py b/networkx/algorithms/core.py
index ac339554..faf1f0d0 100644
--- a/networkx/algorithms/core.py
+++ b/networkx/algorithms/core.py
@@ -378,7 +378,7 @@ def k_corona(G, k, core_number=None):
     return _core_subgraph(G, func, k, core_number)
 
 
-@nx.dispatch("k_truss")
+@nx.dispatch
 @not_implemented_for("directed")
 @not_implemented_for("multigraph")
 def k_truss(G, k):
diff --git a/networkx/algorithms/cuts.py b/networkx/algorithms/cuts.py
index 271ff309..2b4794ef 100644
--- a/networkx/algorithms/cuts.py
+++ b/networkx/algorithms/cuts.py
@@ -21,7 +21,7 @@ __all__ = [
 # TODO STILL NEED TO UPDATE ALL THE DOCUMENTATION!
 
 
-@nx.dispatch("cut_size")
+@nx.dispatch
 def cut_size(G, S, T=None, weight=None):
     """Returns the size of the cut between two sets of nodes.
 
@@ -84,7 +84,7 @@ def cut_size(G, S, T=None, weight=None):
     return sum(weight for u, v, weight in edges)
 
 
-@nx.dispatch("volume")
+@nx.dispatch
 def volume(G, S, weight=None):
     """Returns the volume of a set of nodes.
 
@@ -127,7 +127,7 @@ def volume(G, S, weight=None):
     return sum(d for v, d in degree(S, weight=weight))
 
 
-@nx.dispatch("normalized_cut_size")
+@nx.dispatch
 def normalized_cut_size(G, S, T=None, weight=None):
     """Returns the normalized size of the cut between two sets of nodes.
 
@@ -180,7 +180,7 @@ def normalized_cut_size(G, S, T=None, weight=None):
     return num_cut_edges * ((1 / volume_S) + (1 / volume_T))
 
 
-@nx.dispatch("conductance")
+@nx.dispatch
 def conductance(G, S, T=None, weight=None):
     """Returns the conductance of two sets of nodes.
 
@@ -228,7 +228,7 @@ def conductance(G, S, T=None, weight=None):
     return num_cut_edges / min(volume_S, volume_T)
 
 
-@nx.dispatch("edge_expansion")
+@nx.dispatch
 def edge_expansion(G, S, T=None, weight=None):
     """Returns the edge expansion between two node sets.
 
@@ -275,7 +275,7 @@ def edge_expansion(G, S, T=None, weight=None):
     return num_cut_edges / min(len(S), len(T))
 
 
-@nx.dispatch("mixing_expansion")
+@nx.dispatch
 def mixing_expansion(G, S, T=None, weight=None):
     """Returns the mixing expansion between two node sets.
 
@@ -323,7 +323,7 @@ def mixing_expansion(G, S, T=None, weight=None):
 
 # TODO What is the generalization to two arguments, S and T? Does the
 # denominator become `min(len(S), len(T))`?
-@nx.dispatch("node_expansion")
+@nx.dispatch
 def node_expansion(G, S):
     """Returns the node expansion of the set `S`.
 
@@ -363,7 +363,7 @@ def node_expansion(G, S):
 
 # TODO What is the generalization to two arguments, S and T? Does the
 # denominator become `min(len(S), len(T))`?
-@nx.dispatch("boundary_expansion")
+@nx.dispatch
 def boundary_expansion(G, S):
     """Returns the boundary expansion of the set `S`.
 
diff --git a/networkx/algorithms/dag.py b/networkx/algorithms/dag.py
index f7692d1f..381f079c 100644
--- a/networkx/algorithms/dag.py
+++ b/networkx/algorithms/dag.py
@@ -36,7 +36,7 @@ __all__ = [
 chaini = chain.from_iterable
 
 
-@nx.dispatch("descendants")
+@nx.dispatch
 def descendants(G, source):
     """Returns all nodes reachable from `source` in `G`.
 
@@ -73,7 +73,7 @@ def descendants(G, source):
     return {child for parent, child in nx.bfs_edges(G, source)}
 
 
-@nx.dispatch("ancestors")
+@nx.dispatch
 def ancestors(G, source):
     """Returns all nodes having a path to `source` in `G`.
 
diff --git a/networkx/algorithms/dominating.py b/networkx/algorithms/dominating.py
index 3f2da907..f80454b7 100644
--- a/networkx/algorithms/dominating.py
+++ b/networkx/algorithms/dominating.py
@@ -64,7 +64,7 @@ def dominating_set(G, start_with=None):
     return dominating_set
 
 
-@nx.dispatch("is_dominating_set")
+@nx.dispatch
 def is_dominating_set(G, nbunch):
     """Checks if `nbunch` is a dominating set for `G`.
 
diff --git a/networkx/algorithms/isolate.py b/networkx/algorithms/isolate.py
index d59a46c4..0a077177 100644
--- a/networkx/algorithms/isolate.py
+++ b/networkx/algorithms/isolate.py
@@ -6,7 +6,7 @@ import networkx as nx
 __all__ = ["is_isolate", "isolates", "number_of_isolates"]
 
 
-@nx.dispatch("is_isolate")
+@nx.dispatch
 def is_isolate(G, n):
     """Determines whether a node is an isolate.
 
@@ -39,7 +39,7 @@ def is_isolate(G, n):
     return G.degree(n) == 0
 
 
-@nx.dispatch("isolates")
+@nx.dispatch
 def isolates(G):
     """Iterator over isolates in the graph.
 
@@ -85,7 +85,7 @@ def isolates(G):
     return (n for n, d in G.degree() if d == 0)
 
 
-@nx.dispatch("number_of_isolates")
+@nx.dispatch
 def number_of_isolates(G):
     """Returns the number of isolates in the graph.
 
diff --git a/networkx/algorithms/link_analysis/pagerank_alg.py b/networkx/algorithms/link_analysis/pagerank_alg.py
index 346fce03..03054322 100644
--- a/networkx/algorithms/link_analysis/pagerank_alg.py
+++ b/networkx/algorithms/link_analysis/pagerank_alg.py
@@ -6,7 +6,7 @@ import networkx as nx
 __all__ = ["pagerank", "google_matrix"]
 
 
-@nx.dispatch("pagerank")
+@nx.dispatch
 def pagerank(
     G,
     alpha=0.85,
diff --git a/networkx/algorithms/reciprocity.py b/networkx/algorithms/reciprocity.py
index 9819de8b..660d922f 100644
--- a/networkx/algorithms/reciprocity.py
+++ b/networkx/algorithms/reciprocity.py
@@ -7,7 +7,7 @@ from ..utils import not_implemented_for
 __all__ = ["reciprocity", "overall_reciprocity"]
 
 
-@nx.dispatch("reciprocity")
+@nx.dispatch
 @not_implemented_for("undirected", "multigraph")
 def reciprocity(G, nodes=None):
     r"""Compute the reciprocity in a directed graph.
@@ -75,7 +75,7 @@ def _reciprocity_iter(G, nodes):
             yield (node, reciprocity)
 
 
-@nx.dispatch("overall_reciprocity")
+@nx.dispatch
 @not_implemented_for("undirected", "multigraph")
 def overall_reciprocity(G):
     """Compute the reciprocity for the whole graph.
diff --git a/networkx/algorithms/regular.py b/networkx/algorithms/regular.py
index 89b98742..7c0b2709 100644
--- a/networkx/algorithms/regular.py
+++ b/networkx/algorithms/regular.py
@@ -5,7 +5,7 @@ from networkx.utils import not_implemented_for
 __all__ = ["is_regular", "is_k_regular", "k_factor"]
 
 
-@nx.dispatch("is_regular")
+@nx.dispatch
 def is_regular(G):
     """Determines whether the graph ``G`` is a regular graph.
 
@@ -41,7 +41,7 @@ def is_regular(G):
         return in_regular and out_regular
 
 
-@nx.dispatch("is_k_regular")
+@nx.dispatch
 @not_implemented_for("directed")
 def is_k_regular(G, k):
     """Determines whether the graph ``G`` is a k-regular graph.
diff --git a/networkx/algorithms/simple_paths.py b/networkx/algorithms/simple_paths.py
index 0ddacabb..6284f961 100644
--- a/networkx/algorithms/simple_paths.py
+++ b/networkx/algorithms/simple_paths.py
@@ -13,7 +13,7 @@ __all__ = [
 ]
 
 
-@nx.dispatch("is_simple_path")
+@nx.dispatch
 def is_simple_path(G, nodes):
     """Returns True if and only if `nodes` form a simple path in `G`.
 
diff --git a/networkx/algorithms/smetric.py b/networkx/algorithms/smetric.py
index a97bb8d9..a440aff1 100644
--- a/networkx/algorithms/smetric.py
+++ b/networkx/algorithms/smetric.py
@@ -3,7 +3,7 @@ import networkx as nx
 __all__ = ["s_metric"]
 
 
-@nx.dispatch("s_metric")
+@nx.dispatch
 def s_metric(G, normalized=True):
     """Returns the s-metric of graph.
 
diff --git a/networkx/algorithms/structuralholes.py b/networkx/algorithms/structuralholes.py
index 9762587e..417ba028 100644
--- a/networkx/algorithms/structuralholes.py
+++ b/networkx/algorithms/structuralholes.py
@@ -5,7 +5,7 @@ import networkx as nx
 __all__ = ["constraint", "local_constraint", "effective_size"]
 
 
-@nx.dispatch("mutual_weight")
+@nx.dispatch
 def mutual_weight(G, u, v, weight=None):
     """Returns the sum of the weights of the edge from `u` to `v` and
     the edge from `v` to `u` in `G`.
diff --git a/networkx/algorithms/tournament.py b/networkx/algorithms/tournament.py
index 60d09f31..a57c3592 100644
--- a/networkx/algorithms/tournament.py
+++ b/networkx/algorithms/tournament.py
@@ -61,7 +61,7 @@ def index_satisfying(iterable, condition):
         raise ValueError("iterable must be non-empty") from err
 
 
-@nx.dispatch("is_tournament")
+@nx.dispatch
 @not_implemented_for("undirected")
 @not_implemented_for("multigraph")
 def is_tournament(G):
@@ -180,7 +180,7 @@ def random_tournament(n, seed=None):
     return nx.DiGraph(edges)
 
 
-@nx.dispatch("score_sequence")
+@nx.dispatch
 @not_implemented_for("undirected")
 @not_implemented_for("multigraph")
 def score_sequence(G):
@@ -210,7 +210,7 @@ def score_sequence(G):
     return sorted(d for v, d in G.out_degree())
 
 
-@nx.dispatch("tournament_matrix")
+@nx.dispatch
 @not_implemented_for("undirected")
 @not_implemented_for("multigraph")
 def tournament_matrix(G):
diff --git a/networkx/algorithms/triads.py b/networkx/algorithms/triads.py
index 0042f5c3..316643ea 100644
--- a/networkx/algorithms/triads.py
+++ b/networkx/algorithms/triads.py
@@ -275,7 +275,7 @@ def triadic_census(G, nodelist=None):
     return census
 
 
-@nx.dispatch("is_triad")
+@nx.dispatch()
 def is_triad(G):
     """Returns True if the graph G is a triad, else False.