diff --git a/pymathics/graph/base.py b/pymathics/graph/base.py old mode 100644 new mode 100755 index 8cca6ba..8e3bd59 --- a/pymathics/graph/base.py +++ b/pymathics/graph/base.py @@ -911,7 +911,7 @@ class DirectedEdge(GenericDirectedEdge):
-
'DirectedEdge[$u$, $v$]' +
'DirectedEdge'[$u$, $v$]
create a directed edge from $u$ to $v$.
@@ -941,7 +941,7 @@ class EdgeConnectivity(_NetworkXBuiltin): https://reference.wolfram.com/language/ref/EdgeConnectivity.html)
-
'EdgeConnectivity[$g$]' +
'EdgeConnectivity'[$g$]
gives the edge connectivity of the graph $g$.
@@ -1128,9 +1128,9 @@ class FindVertexCut(_NetworkXBuiltin): https://reference.wolfram.com/language/ref/FindVertexCut.html)
-
'FindVertexCut[$g$]' +
'FindVertexCut'[$g$]
finds a set of vertices of minimum cardinality that, if removed, renders $g$ disconnected. -
'FindVertexCut[$g$, $s$, $t$]' +
'FindVertexCut'[$g$, $s$, $t$]
finds a vertex cut that disconnects all paths from $s$ to $t$.
@@ -1185,12 +1185,12 @@ class GraphAtom(AtomBuiltin): :Graph:https://en.wikipedia.org/wiki/graph (:WMA: https://reference.wolfram.com/language/ref/Graph.html)
-
'Graph[{$e1, $e2, ...}]' +
'Graph'[{$e1, $e2, ...}]
returns a graph with edges $e_j$.
-
'Graph[{v1, v2, ...}, {$e1, $e2, ...}]' +
'Graph'[{v1, v2, ...}, {$e1, $e2, ...}]
returns a graph with vertices $v_i$ and edges $e_j$.
@@ -1491,7 +1491,7 @@ class VertexList(_PatternList): :WMA link: https://reference.wolfram.com/language/ref/VertexList.html
-
'VertexList[$edgelist$]' +
'VertexList'[$edgelist$]
list the vertices from a list of directed edges.
@@ -1521,7 +1521,7 @@ class UndirectedEdge(GenericUndirectedEdge): https://reference.wolfram.com/language/ref/UndirectedEdge.html
-
'UndirectedEdge[$u$, $v$]' +
'UndirectedEdge'[$u$, $v$]
create an undirected edge between $u$ and $v$.
diff --git a/pymathics/graph/components.py b/pymathics/graph/components.py index a4a8c65..5d0864a 100644 --- a/pymathics/graph/components.py +++ b/pymathics/graph/components.py @@ -68,7 +68,7 @@ def eval( # class FindHamiltonianPath(_NetworkXBuiltin): # """ #
-#
'FindHamiltonianPath[$g$]' +#
'FindHamiltonianPath'[$g$] #
returns a Hamiltonian path in the given tournament graph. #
# diff --git a/pymathics/graph/curated.py b/pymathics/graph/curated.py index 3a44c44..a50069c 100644 --- a/pymathics/graph/curated.py +++ b/pymathics/graph/curated.py @@ -15,7 +15,7 @@ class GraphData(_NetworkXBuiltin): :WMA link:https://reference.wolfram.com/language/ref/GraphData.html
-
'GraphData[$name$]' +
'GraphData'[$name$]
Returns a graph with the specified name.
diff --git a/pymathics/graph/measures_and_metrics.py b/pymathics/graph/measures_and_metrics.py index e6c22b0..cd7c0f1 100644 --- a/pymathics/graph/measures_and_metrics.py +++ b/pymathics/graph/measures_and_metrics.py @@ -61,13 +61,13 @@ class EdgeCount(_PatternCount): https://reference.wolfram.com/language/ref/EdgeCount.html
-
'EdgeCount[$g$]' +
'EdgeCount'[$g$]
returns a count of the number of edges in graph $g$. -
'EdgeCount[$g$, $patt$]' +
'EdgeCount'[$g$, $patt$]
returns the number of edges that match the pattern $patt$. -
'EdgeCount[{$v$->$w$}, ...}, ...]' +
'EdgeCount'[{$v$->$w$}, ...}, ...]
uses rules $v$->$w$ to specify the graph $g$.
@@ -96,12 +96,12 @@ class GraphDistance(_NetworkXBuiltin):
-
'GraphDistance[$g$, $s$]' +
'GraphDistance'[$g$, $s$]
returns the distance from source vertex $s$ to all vertices in the graph $g$.
-
'GraphDistance[{$v$->$w$, ...}, ...]' +
'GraphDistance'[{$v$->$w$, ...}, ...]
use rules $v$->$w$ to specify the graph $g$.
@@ -169,13 +169,13 @@ class VertexCount(_PatternCount): https://reference.wolfram.com/language/ref/VertexCount.html
-
'VertexCount[$g$]' +
'VertexCount'[$g$]
returns a count of the number of vertices in graph $g$. -
'VertexCount[$g$, $patt$]' +
'VertexCount'[$g$, $patt$]
returns the number of vertices that match the pattern $patt$. -
'VertexCount[{$v$->$w$}, ...}, ...]' +
'VertexCount'[{$v$->$w$}, ...}, ...]
uses rules $v$->$w$ to specify the graph $g$.
@@ -209,13 +209,13 @@ class VertexDegree(_NetworkXBuiltin): https://reference.wolfram.com/language/ref/VertexDegree.html
-
'VertexDegree[$g$]' +
'VertexDegree'[$g$]
returns a list of the degrees of each of the vertices in graph $g$. -
'EdgeCount[$g$, $patt$]' +
'EdgeCount'[$g$, $patt$]
returns the number of edges that match the pattern $patt$. -
'EdgeCount[{$v$->$w$}, ...}, ...]' +
'EdgeCount'[{$v$->$w$}, ...}, ...]
uses rules $v$->$w$ to specify the graph $g$.
diff --git a/pymathics/graph/parametric.py b/pymathics/graph/parametric.py index 7462e98..929e6ed 100644 --- a/pymathics/graph/parametric.py +++ b/pymathics/graph/parametric.py @@ -35,7 +35,7 @@ class BalancedTree(_NetworkXBuiltin): https://reference.wolfram.com/language/ref/BalancedTree.html
-
'BalancedTree[$r$, $h$]' +
'BalancedTree'[$r$, $h$]
Returns the perfectly balanced $r$-ary tree of height $h$. In this tree produced, all non-leaf nodes will have $r$ children and \ @@ -90,7 +90,7 @@ class BarbellGraph(_NetworkXBuiltin): https://mathworld.wolfram.com/BarbellGraph.html)
-
'BarbellGraph[$m1$, $m2$]' +
'BarbellGraph'[$m_1$, $m_2$]
Barbell Graph: two complete graphs connected by a path.
@@ -148,7 +148,7 @@ class BinomialTree(_NetworkXBuiltin): :WMA:https://reference.wolfram.com/language/ref/BinomialTree.html)
-
'BinomialTree[$n$]' +
'BinomialTree'[$n$]
Returns the Binomial Tree of order $n$. The binomial tree of order $n$ with root $R$ is defined as: @@ -206,7 +206,7 @@ class CompleteGraph(_NetworkXBuiltin): https://reference.wolfram.com/language/ref/CompleteGraph.html)
-
'CompleteGraph[$n$]' +
'CompleteGraph'[$n$]
Returns the complete graph with $n$ vertices, $K_n$.
@@ -244,7 +244,7 @@ class CompleteKaryTree(_NetworkXBuiltin): https://reference.wolfram.com/language/ref/CompleteKaryTree.html)
-
'CompleteKaryTree[$n$, $k$]' +
'CompleteKaryTree'[$n$, $k$]
Creates a complete $k$-ary tree of $n$ levels.
@@ -295,7 +295,7 @@ class CycleGraph(_NetworkXBuiltin): https://reference.wolfram.com/language/ref/CycleGraph.html)
-
'CycleGraph[$n$]' +
'CycleGraph'[$n$]
Returns the cycle graph with $n$ vertices $C_n$.
@@ -324,7 +324,7 @@ class GraphAtlas(_NetworkXBuiltin):
-
'GraphAtlas[$n$]' +
'GraphAtlas'[$n$]
Returns graph number $i$ from the NetworkX's Graph \ Atlas. There are about 1200 of them and get large as $i$ \ increases. @@ -368,7 +368,7 @@ class HknHararyGraph(_NetworkXBuiltin): https://reference.wolfram.com/language/ref/HknHararyGraph.html
-
'HknHararyGraph[$k$, $n$]' +
'HknHararyGraph'[$k$, $n$]
Returns the Harary graph with given node connectivity and node number. This second generator gives the Harary graph that minimizes the \ @@ -405,7 +405,7 @@ class HmnHararyGraph(_NetworkXBuiltin): https://reference.wolfram.com/language/ref/HmnHararyGraph.html
-
'HmnHararyGraph[$m$, $n$]' +
'HmnHararyGraph'[$m$, $n$]
Returns the Harary graph with given numbers of nodes and edges. This generator gives the Harary graph that maximizes the node \ @@ -461,12 +461,12 @@ class KaryTree(_NetworkXBuiltin):
-
'KaryTree[$r$, $n$]' +
'KaryTree'[$r$, $n$]
Creates binary tree of $n$ vertices.
-
'KaryTree[$n$, $k$]' +
'KaryTree'[$n$, $k$]
Creates $k$-ary tree with $n$ vertices.
@@ -509,7 +509,7 @@ class LadderGraph(_NetworkXBuiltin): /generated/networkx.generators.classic.ladder_graph.html)
-
'LadderGraph[$n$]' +
'LadderGraph'[$n$]
Returns the Ladder graph of length $n$.
@@ -549,7 +549,7 @@ class PathGraph(_NetworkXBuiltin): (:WMA:https://reference.wolfram.com/language/ref/PathGraph.html )
-
'PathGraph[{$v_1$, $v_2$, ...}]' +
'PathGraph'[{$v_1$, $v_2$, ...}]
Returns a Graph with a path with vertices $v_i$ and \ edges between $v-i$ and $v_i+1$ .
@@ -584,7 +584,7 @@ class RandomTree(_NetworkXBuiltin): https://reference.wolfram.com/language/ref/RandomTree.html
-
'RandomTree[$n$]' +
'RandomTree'[$n$]
Returns a uniformly random tree on $n$ nodes.
@@ -630,7 +630,7 @@ class StarGraph(_NetworkXBuiltin): https://reference.wolfram.com/language/ref/StarGraph.html )
-
'StarGraph[$n$]' +
'StarGraph'[$n$]
Returns a star graph with $n$ vertices.
diff --git a/pymathics/graph/random.py b/pymathics/graph/random.py index 13455b8..f5ccfc8 100644 --- a/pymathics/graph/random.py +++ b/pymathics/graph/random.py @@ -26,10 +26,10 @@ class RandomGraph(_NetworkXBuiltin):
-
'RandomGraph[{$n$, $m$}]' +
'RandomGraph'[{$n$, $m$}]
Returns a pseudorandom graph with $n$ vertices and $m$ edges. -
'RandomGraph[{$n$, $m$}, $k$]' +
'RandomGraph'[{$n$, $m$}, $k$]
Returns list of $k$ RandomGraph[{$n$, $m$}].
""" diff --git a/pymathics/graph/structured.py b/pymathics/graph/structured.py index aa6f73b..6d054ea 100644 --- a/pymathics/graph/structured.py +++ b/pymathics/graph/structured.py @@ -18,7 +18,7 @@ class PathGraph(_NetworkXBuiltin):
-
'PathGraph[{$v_1$, $v_2$, ...}]' +
'PathGraph'[{$v_1$, $v_2$, ...}]
Returns a Graph with a path with vertices $v_i$ and edges between $v-i$ and $v_i+1$ .
@@ -50,7 +50,7 @@ class TreeGraph(Graph):
-
'TreeGraph[{$edge_1$, $edge_2$, ...}]' +
'TreeGraph'[{$edge_1$, $edge_2$, ...}]
create a tree-like from a list of edges.
diff --git a/pymathics/graph/tree.py b/pymathics/graph/tree.py index 0318330..350ac7e 100644 --- a/pymathics/graph/tree.py +++ b/pymathics/graph/tree.py @@ -87,7 +87,7 @@ class TreeGraphQ(_NetworkXBuiltin): (:WMA:https://reference.wolfram.com/language/ref/TreeGraphQ.html)
-
'TreeGraphQ[$g$]' +
'TreeGraphQ'[$g$]
returns $True$ if the graph $g$ is a tree and $False$ otherwise.