Correct Graph options bug; go over examples.

* Graph options need to be in System context.
* Improve examples for GraphDistance and component sections
* Add GraphDistance summary

Author: rocky

.pre-commit-config.yaml

@@ -9,11 +9,11 @@ repos:
       stages: [commit]
     - id: end-of-file-fixer
       stages: [commit]
--   repo: https://github.com/pycqa/isort
-    rev: 5.10.1
-    hooks:
-      - id: isort
-        stages: [commit]
+# -   repo: https://github.com/pycqa/isort
+#     rev: 5.10.1
+#     hooks:
+#       - id: isort
+#         stages: [commit]
 -   repo: https://github.com/psf/black
     rev: 22.3.0
     hooks:

pymathics/graph/base.py

@@ -124,27 +124,27 @@ def _process_graph_options(g, options: dict) -> None:
     # g is where it is used in format. However we should wrap this as our object.
     # Access in G which might be better, currently isn't used.
     g.G.vertex_labels = g.vertex_labels = (
-        options["Pymathics`VertexLabels"].to_python()
-        if "Pymathics`VertexLabels" in options
+        options["System`VertexLabels"].to_python()
+        if "System`VertexLabels" in options
         else False
     )
     shape = (
-        options["Pymathics`VertexShape"].get_string_value()
-        if "Pymathics`VertexShape" in options
+        options["System`VertexShape"].get_string_value()
+        if "System`VertexShape" in options
         else "Circle"
     )
 
     g.G.node_shape = g.node_shape = WL_MARKER_TO_NETWORKX.get(shape, shape)
 
     color = (
-        options["Pymathics`VertexStyle"].get_string_value()
-        if "Pymathics`VertexStyle" in options
+        options["System`VertexStyle"].get_string_value()
+        if "System`VertexStyle" in options
         else "Blue"
     )
 
     g.graph_layout = (
-        options["Pymathics`GraphLayout"].get_string_value()
-        if "Pymathics`GraphLayout" in options
+        options["System`GraphLayout"].get_string_value()
+        if "System`GraphLayout" in options
         else ""
     )
 
@@ -573,7 +573,6 @@ def __init__(self, G, **kwargs):
         super(Graph, self).__init__()
         self.G = G
         self.mixed = kwargs.get("mixed", False)
-        print("creating", self.G, self.mixed)
 
     def __hash__(self):
         return hash(("Pymathics`Graph", self.G))
@@ -1082,7 +1081,10 @@ def neighbors(v):
 
 class BetweennessCentrality(_Centrality):
     """
-    >> g = Graph[{a -> b, b -> c, d -> c, d -> a, e -> c, d -> b}]; BetweennessCentrality[g]
+    >> g = Graph[{a -> b, b -> c, d -> c, d -> a, e -> c, d -> b}]
+     = -Graph-
+
+    >> BetweennessCentrality[g]
      = {0., 1., 0., 0., 0.}
 
     >> g = Graph[{a -> b, b -> c, c -> d, d -> e, e -> c, e -> a}]; BetweennessCentrality[g]
@@ -1104,11 +1106,17 @@ def eval(self, graph, expression, evaluation, options):
 
 class ClosenessCentrality(_Centrality):
     """
-    >> g = Graph[{a -> b, b -> c, d -> c, d -> a, e -> c, d -> b}]; ClosenessCentrality[g]
-     = {0.666667, 1., 0., 1., 1.}
+     >> g = Graph[{a -> b, b -> c, d -> c, d -> a, e -> c, d -> b}]
+      = -Graph-
+
+     >> ClosenessCentrality[g]
+      = {0.666667, 1., 0., 1., 1.}
 
-    >> g = Graph[{a -> b, b -> c, c -> d, d -> e, e -> c, e -> a}]; ClosenessCentrality[g]
-     = {0.4, 0.4, 0.4, 0.5, 0.666667}
+     >> g = Graph[{a -> b, b -> c, c -> d, d -> e, e -> c, e -> a}]
+      = -Graph-
+
+    >> ClosenessCentrality[g]
+      = {0.4, 0.4, 0.4, 0.5, 0.666667}
     """
 
     def eval(self, graph, expression, evaluation, options):
@@ -1127,7 +1135,9 @@ def eval(self, graph, expression, evaluation, options):
 
 class DegreeCentrality(_Centrality):
     """
-    >> g = Graph[{a -> b, b <-> c, d -> c, d -> a, e <-> c, d -> b}];
+    >> g = Graph[{a -> b, b <-> c, d -> c, d -> a, e <-> c, d -> b}]
+     = -Graph-
+
     >> DegreeCentrality[g]
      = ...
 

pymathics/graph/components.py

@@ -17,16 +17,25 @@ class ConnectedComponents(_NetworkXBuiltin):
     """
     <dl>
       <dt>'ConnectedComponents'[$g$]
-      <dd> gives the connected components of the graph $g$
+      <dd> gives the connected components of the graph $g$.
     </dl>
 
-    >> g = Graph[{1 -> 2, 2 -> 3, 3 <-> 4}]; ConnectedComponents[g]
+    >> g = Graph[{1 -> 2, 2 -> 3, 3 <-> 4}, VertexLabels->True]
+     = -Graph-
+
+    >> ConnectedComponents[g]
      = ...
 
-    >> g = Graph[{1 -> 2, 2 -> 3, 3 -> 1}]; ConnectedComponents[g]
+    >> g = Graph[{1 -> 2, 2 -> 3, 3 -> 1}, VertexLabels->True]
+     = -Graph-
+
+    >> ConnectedComponents[g]
      = ...
 
-    >> g = Graph[{1 <-> 2, 2 <-> 3, 3 -> 4, 4 <-> 5}]; ConnectedComponents[g]
+    >> g = Graph[{1 <-> 2, 2 <-> 3, 3 -> 4, 4 <-> 5}, VertexLabels->True]
+     = -Graph-
+
+    >> ConnectedComponents[g]
      = ...
     """
 
@@ -69,16 +78,25 @@ class WeaklyConnectedComponents(_NetworkXBuiltin):
     """
     <dl>
       <dt>'WeaklyConnectedComponents'[$g$]
-      <dd> gives the weakly connected components of the graph $g$
+      <dd> gives the weakly connected components of the graph $g$.
     </dl>
 
-    >> g = Graph[{1 -> 2, 2 -> 3, 3 <-> 4}]; WeaklyConnectedComponents[g]
+    >> g = Graph[{1 -> 2, 2 -> 3, 3 <-> 4}, VertexLabels->True]
+     = -Graph-
+
+    >> WeaklyConnectedComponents[g]
      = {{1, 2, 3, 4}}
 
-    >> g = Graph[{1 -> 2, 2 -> 3, 3 -> 1}]; WeaklyConnectedComponents[g]
+    >> g = Graph[{1 -> 2, 2 -> 3, 3 -> 1}, VertexLabels->True]
+     = -Graph-
+
+    >> WeaklyConnectedComponents[g]
      = {{1, 2, 3}}
 
-    >> g = Graph[{1 <-> 2, 2 <-> 3, 3 -> 4, 4 <-> 5, 6 <-> 7, 7 <-> 8}]; WeaklyConnectedComponents[g]
+    >> g = Graph[{1 <-> 2, 2 <-> 3, 3 -> 4, 4 <-> 5, 6 <-> 7, 7 <-> 8}, VertexLabels->True]
+     = -Graph-
+
+    >> WeaklyConnectedComponents[g]
      = {{1, 2, 3, 4, 5}, {6, 7, 8}}
     """
 

pymathics/graph/curated.py

@@ -16,6 +16,7 @@ class GraphData(_NetworkXBuiltin):
     </dl>
 
     >> GraphData["PappusGraph"]
+     = -Graph-
     """
 
     def eval(self, name, expression, evaluation: Evaluation, options: dict) -> Graph:

pymathics/graph/measures_and_metrics.py

@@ -97,26 +97,34 @@ class GraphDistance(_NetworkXBuiltin):
       <dd>use rules $v$->$w$ to specify the graph $g$.
     </dl>
 
-    >> GraphDistance[{1 <-> 2, 2 <-> 3, 3 <-> 4, 2 <-> 4, 4 -> 5}, 1, 5]
+    >> g = Graph[{1 -> 2, 2 <-> 3, 4 -> 3, 2 <-> 4, 4 -> 5}, VertexLabels->True]
+     = -Graph-
+
+    >> GraphDistance[g, 1, 5]
      = 3
 
-    >> GraphDistance[{1 <-> 2, 2 <-> 3, 3 <-> 4, 4 -> 2, 4 -> 5}, 1, 5]
-     = 4
+    >> GraphDistance[g, 4, 2]
+     = 1
 
-    >> GraphDistance[{1 <-> 2, 2 <-> 3, 4 -> 3, 4 -> 2, 4 -> 5}, 1, 5]
+    >> GraphDistance[g, 5, 4]
      = Infinity
 
-    >> GraphDistance[{1 <-> 2, 2 <-> 3, 3 <-> 4, 2 <-> 4, 4 -> 5}, 3]
-     = ...
+    >> GraphDistance[g, 5]
+     = [Infinity, Infinity, Infinity, 0]
+
+    >> GraphDistance[g, 3]
+     = {Infinity, 1, 2, 0, 3}
 
-    >> GraphDistance[{1 <-> 2, 3 <-> 4}, 3]
-     = {Infinity, Infinity, 0, 1}
+    >> GraphDistance[g, 4]
+     = {1, 2, 1, 0, 2}
 
     #> GraphDistance[{1 -> 2}, 3, 4]
      : The vertex at position 2 in GraphDistance[{1 -> 2}, 3, 4] does not belong to the graph at position 1.
      = GraphDistance[{1 -> 2}, 3, 4]
     """
 
+    summary_text = "get path distance"
+
     def eval_s(
         self, graph, s, expression, evaluation: Evaluation, options: dict
     ) -> Optional[ListExpression]:

pymathics/graph/parametric.py

@@ -34,8 +34,8 @@ class BalancedTree(_NetworkXBuiltin):
       <dt>'BalancedTree[$r$, $h$]'
       <dd>Returns the perfectly balanced $r$-ary tree of height $h$.
 
-      In this tree produced, all non-leaf nodes will have $r$ children and the height of
-      the path from root $r$ to any leaf will be $h$.
+      In this tree produced, all non-leaf nodes will have $r$ children and \
+      the height of the path from root $r$ to any leaf will be $h$.
     </dl>
 
     >> BalancedTree[2, 3]
@@ -82,8 +82,8 @@ class BarbellGraph(_NetworkXBuiltin):
       <dd>Barbell Graph: two complete graphs connected by a path.
     </dl>
 
-    ## >> BarbellGraph[4, 1]
-    ##  = -Graph-
+    >> BarbellGraph[4, 1]
+     = -Graph-
 
     """
 
@@ -132,11 +132,14 @@ class BinomialTree(_NetworkXBuiltin):
 
       The binomial tree of order $n$ with root $R$ is defined as:
 
-      If $k$=0,  $B[k]$ = $B[0]$ = {$R$}. i.e., the binomial tree of order zero consists of a single node, $R$.
+      If $k$=0,  $B[k]$ = $B[0]$ = {$R$}. i.e., the binomial tree of order \
+      zero consists of a single node, $R$.
 
-      If $k>0$, B[k] = {$R$, $B[0$], $B[1]$ .. $B[k]$, i.e., the binomial tree of order $k$>0 comprises the root $R$, and $k$ binomial subtrees, $B[0] to $B[k].
+      If $k>0$, B[k] = {$R$, $B[0$], $B[1]$ .. $B[k]$, i.e., the binomial tree \
+      of order $k$>0 comprises the root $R$, and $k$ binomial subtrees, \
+      $B[0] to $B[k].
 
-      Binomial trees the underlying datastructre in Binomial Heaps.
+      Binomial trees are the underlying datastructre in Binomial Heaps.
     </dl>
 
     >> BinomialTree[3]
@@ -171,15 +174,11 @@ class CompleteGraph(_NetworkXBuiltin):
     """
     <dl>
       <dt>'CompleteGraph[$n$]'
-      <dd>Returns the complete graph with $n$ vertices, $K_n$
+      <dd>Returns the complete graph with $n$ vertices, $K_n$.
     </dl>
 
     >> CompleteGraph[8]
      = -Graph-
-
-    #> CompleteGraph[0]
-     : Expected a positive integer at position 1 in CompleteGraph[0].
-     = CompleteGraph[0]
     """
 
     messages = {
@@ -192,9 +191,9 @@ def eval(self, n: Integer, expression, evaluation: Evaluation, options: dict):
 
     def eval_multipartite(self, n, evaluation: Evaluation, options: dict):
         "%(name)s[n_List, OptionsPattern[%(name)s]]"
-        if all(isinstance(i, Integer) for i in n.leaves):
+        if all(isinstance(i, Integer) for i in n.elements):
             return Graph(
-                nx.complete_multipartite_graph(*[i.get_int_value() for i in n.leaves])
+                nx.complete_multipartite_graph(*[i.get_int_value() for i in n.elements])
             )
 
 
@@ -204,7 +203,7 @@ class CompleteKaryTree(_NetworkXBuiltin):
       <dd>Creates a complete $k$-ary tree of $n$ levels.
     </dl>
 
-    In the returned tree, with $n$ nodes, the from root $R$ to any
+    In the returned tree, with $n$ nodes, the from root $R$ to any \
     leaf be $k$.
 
     >> CompleteKaryTree[2, 3]
@@ -246,7 +245,7 @@ class CycleGraph(_NetworkXBuiltin):
         <dd>Returns the cycle graph with $n$ vertices $C_n$.
       </dl>
 
-    >> CycleGraph[3, PlotLabel -> "C_i"]
+    >> CycleGraph[5, PlotLabel -> "C_i"]
      = -Graph-
     """
 
@@ -290,8 +289,8 @@ def eval(self, r, n, expression, evaluation: Evaluation, options: dict):
 class GraphAtlas(_NetworkXBuiltin):
     """<dl>
       <dt>'GraphAtlas[$n$]'
-      <dd>Returns graph number $i$ from the Networkx's Graph
-      Atlas. There are about 1200 of them and get large as $i$
+      <dd>Returns graph number $i$ from the Networkx's Graph \
+      Atlas. There are about 1200 of them and get large as $i$ \
       increases.
     </dl>
 
@@ -331,7 +330,8 @@ class HknHararyGraph(_NetworkXBuiltin):
       number of edges in the graph with given node connectivity and   \
       number of nodes.
 
-      Harary, F.  The Maximum Connectivity of a Graph.  Proc. Nat. Acad. Sci. USA 48, 1142-1146, 1962.
+      Harary, F.  The Maximum Connectivity of a Graph.  \
+      Proc. Nat. Acad. Sci. USA 48, 1142-1146, 1962.
     </dl>
 
     >> HknHararyGraph[3, 10]
@@ -359,7 +359,8 @@ class HmnHararyGraph(_NetworkXBuiltin):
       connectivity with given number of nodes and given number of \
       edges.
 
-      Harary, F.  The Maximum Connectivity of a Graph.  Proc. Nat. Acad. Sci. USA 48, 1142-1146, 1962.
+      Harary, F.  The Maximum Connectivity of a Graph.\
+      Proc. Nat. Acad. Sci. USA 48, 1142-1146, 1962.
     </dl>
 
     >> HmnHararyGraph[5, 10]
@@ -475,7 +476,8 @@ class PathGraph(_NetworkXBuiltin):
     """
     <dl>
       <dt>'PathGraph[{$v_1$, $v_2$, ...}]'
-      <dd>Returns a Graph with a path with vertices $v_i$ and edges between $v-i$ and $v_i+1$ .
+      <dd>Returns a Graph with a path with vertices $v_i$ and \
+      edges between $v-i$ and $v_i+1$ .
     </dl>
     >> PathGraph[{1, 2, 3}]
      = -Graph-
@@ -534,7 +536,7 @@ class StarGraph(_NetworkXBuiltin):
     """
     <dl>
       <dt>'StarGraph[$n$]'
-      <dd>Returns a star graph with $n$ vertices
+      <dd>Returns a star graph with $n$ vertices.
     </dl>
 
     >> StarGraph[8]