second round

Author: mmatera

pymathics/graph/components.py

@@ -15,6 +15,10 @@
 
 class ConnectedComponents(_NetworkXBuiltin):
     """
+    <url>
+    :WMA:https://reference.wolfram.com/language/ref/ConnectedComponents.html
+    </url>
+
     <dl>
       <dt>'ConnectedComponents'[$g$]
       <dd> gives the connected components of the graph $g$.
@@ -39,6 +43,8 @@ class ConnectedComponents(_NetworkXBuiltin):
      = ...
     """
 
+    summary_text = "list the connected components"
+
     def eval(
         self, graph, expression, evaluation: Evaluation, options: dict
     ) -> Optional[ListExpression]:
@@ -76,6 +82,10 @@ def eval(
 
 class WeaklyConnectedComponents(_NetworkXBuiltin):
     """
+    <url>
+    :WMA:https://reference.wolfram.com/language/ref/WeaklyConnectedComponents.html
+    </url>
+
     <dl>
       <dt>'WeaklyConnectedComponents'[$g$]
       <dd> gives the weakly connected components of the graph $g$.
@@ -100,6 +110,8 @@ class WeaklyConnectedComponents(_NetworkXBuiltin):
      = {{1, 2, 3, 4, 5}, {6, 7, 8}}
     """
 
+    summary_text = "list the weakly connected components"
+
     def eval(self, graph, expression, evaluation: Evaluation, options):
         "WeaklyConnectedComponents[graph_, OptionsPattern[WeaklyConnectedComponents]]"
         graph = self._build_graph(graph, evaluation, options, expression)

pymathics/graph/curated.py

@@ -10,6 +10,10 @@
 
 class GraphData(_NetworkXBuiltin):
     """
+    <url>
+    :WMA:https://reference.wolfram.com/language/ref/GraphData.html
+    </url>
+
     <dl>
       <dt>'GraphData[$name$]'
       <dd>Returns a graph with the specified name.
@@ -19,6 +23,8 @@ class GraphData(_NetworkXBuiltin):
      = -Graph-
     """
 
+    summary_text = "create a graph by name"
+
     def eval(self, name, expression, evaluation: Evaluation, options: dict) -> Graph:
         "GraphData[name_String, OptionsPattern[GraphData]]"
         py_name = name.get_string_value()

pymathics/graph/parametric.py

@@ -30,6 +30,10 @@
 
 class BalancedTree(_NetworkXBuiltin):
     """
+    <url>
+    :WMA:https://reference.wolfram.com/language/ref/BalancedTree.html
+    </url>
+
     <dl>
       <dt>'BalancedTree[$r$, $h$]'
       <dd>Returns the perfectly balanced $r$-ary tree of height $h$.
@@ -50,6 +54,7 @@ class BalancedTree(_NetworkXBuiltin):
     }
 
     options = DEFAULT_TREE_OPTIONS
+    summary_text = "build a balanced tree graph"
 
     def eval(
         self, r: Integer, h: Integer, expression, evaluation: Evaluation, options: dict
@@ -77,6 +82,14 @@ def eval(
 
 class BarbellGraph(_NetworkXBuiltin):
     """
+    <url>
+    :Barbell graph:https://en.wikipedia.org/wiki/Barbell_graph
+    </url> (
+    <url>
+    :NetworkX:https://networkx.org/documentation/stable/reference/\
+generated/networkx.generators.classic.barbell_graph.html</url>
+)
+
     <dl>
       <dt>'BarbellGraph[$m1$, $m2$]'
       <dd>Barbell Graph: two complete graphs connected by a path.
@@ -91,6 +104,7 @@ class BarbellGraph(_NetworkXBuiltin):
         "ilsmp": "Expected a non-negative integer at position 1 in ``.",
         "ilsmp2": "Expected a non-negative integer at position 2 in ``.",
     }
+    summary_text = "build a n-m Barbell graph"
 
     def eval(
         self,
@@ -126,6 +140,17 @@ def eval(
 
 class BinomialTree(_NetworkXBuiltin):
     """
+    <url>
+    :Binomial tree:https://en.wikipedia.org/wiki/Binomial_tree
+    </url> (
+    <url>
+    :NetworkX:https://networkx.org/documentation/stable/reference/\
+generated/networkx.generators.classic.binomial_tree.html</url>,
+    <url>
+    :WMA:https://reference.wolfram.com/language/ref/BinomialTree.html
+    </url>
+    )
+
     <dl>
       <dt>'BinomialTree[$n$]'
       <dd>Returns the Binomial Tree of order $n$.
@@ -151,6 +176,7 @@ class BinomialTree(_NetworkXBuiltin):
         "ilsmp": "Expected a non-negative integer at position 1 in ``.",
         "mem": "Out of memory",
     }
+    summary_text = "build a binomial tree"
 
     def eval(
         self, n: Integer, expression, evaluation: Evaluation, options: dict
@@ -185,6 +211,8 @@ class CompleteGraph(_NetworkXBuiltin):
         "ilsmp": "Expected a positive integer at position 1 in ``.",
     }
 
+    summary_text = "build a completely connected graph"
+
     def eval(self, n: Integer, expression, evaluation: Evaluation, options: dict):
         "%(name)s[n_Integer, OptionsPattern[%(name)s]]"
         return eval_complete_graph(self, n, expression, evaluation, options)
@@ -215,6 +243,7 @@ class CompleteKaryTree(_NetworkXBuiltin):
     """
 
     options = DEFAULT_TREE_OPTIONS
+    summary_text = "build a complete k-ary tree"
 
     def eval(self, k, n, expression, evaluation: Evaluation, options: dict):
         "%(name)s[n_Integer, k_Integer, OptionsPattern[%(name)s]]"
@@ -249,6 +278,8 @@ class CycleGraph(_NetworkXBuiltin):
      = -Graph-
     """
 
+    summary_text = "build a cycle graph"
+
     def eval(self, n: Integer, expression, evaluation: Evaluation, options: dict):
         "%(name)s[n_Integer, OptionsPattern[%(name)s]]"
         n_int = n.get_int_value()
@@ -259,7 +290,8 @@ def eval(self, n: Integer, expression, evaluation: Evaluation, options: dict):
 
 
 class FullRAryTree(_NetworkXBuiltin):
-    """<dl>
+    """
+    <dl>
       <dt>'FullRAryTree[$r$, $n$]'
       <dd>Creates a full $r$-ary tree of $n$ vertices.
     </dl>
@@ -280,6 +312,7 @@ class FullRAryTree(_NetworkXBuiltin):
     }
 
     options = DEFAULT_TREE_OPTIONS
+    summary_text = "build a full r-ary tree"
 
     def eval(self, r, n, expression, evaluation: Evaluation, options: dict):
         "%(name)s[r_Integer, n_Integer, OptionsPattern[%(name)s]]"
@@ -301,6 +334,7 @@ class GraphAtlas(_NetworkXBuiltin):
     messages = {
         "ilsmp": "Expected a positive integer at position 1 in ``.",
     }
+    summary_text = "build the i-esim graph from the Networkx atlas"
 
     def eval(self, n, expression, evaluation: Evaluation, options: dict):
         "%(name)s[n_Integer, OptionsPattern[%(name)s]]"
@@ -343,6 +377,7 @@ class HknHararyGraph(_NetworkXBuiltin):
         "ilsmp": "Expected a non-negative integer at position 1 in ``.",
         "ilsmp2": "Expected a non-negative integer at position 2 in ``.",
     }
+    summary_text = "build a Hkn Harary graph"
 
     def eval(self, k, n, expression, evaluation: Evaluation, options: dict):
         "%(name)s[k_Integer, n_Integer, OptionsPattern[%(name)s]]"
@@ -372,6 +407,8 @@ class HmnHararyGraph(_NetworkXBuiltin):
         "ilsmp2": "Expected a non-negative integer at position 2 in ``.",
     }
 
+    summary_text = "build a Hmn Harary graph"
+
     def eval(self, n, m, expression, evaluation: Evaluation, options: dict):
         "%(name)s[n_Integer, m_Integer, OptionsPattern[%(name)s]]"
         py_n = n.value
@@ -423,6 +460,7 @@ class KaryTree(_NetworkXBuiltin):
     }
 
     options = DEFAULT_TREE_OPTIONS
+    summary_text = "build a Kary tree"
 
     def eval(
         self, n: Integer, expression, evaluation: Evaluation, options: dict
@@ -451,6 +489,7 @@ class LadderGraph(_NetworkXBuiltin):
     messages = {
         "ilsmp": "Expected a positive integer at position 1 in ``.",
     }
+    summary_text = "build a ladder tree"
 
     def eval(
         self, n: Integer, expression, evaluation: Evaluation, options: dict
@@ -483,6 +522,8 @@ class PathGraph(_NetworkXBuiltin):
      = -Graph-
     """
 
+    summary_text = "build a path graph"
+
     def eval(self, e, evaluation: Evaluation, options: dict) -> Graph:
         "PathGraph[e_List, OptionsPattern[PathGraph]]"
         elements = e.elements
@@ -514,6 +555,8 @@ class RandomTree(_NetworkXBuiltin):
         "ilsmp": "Expected a non-negative integer at position 1 in ``.",
     }
 
+    summary_text = "build a random tree"
+
     def eval(
         self, n: Integer, expression, evaluation: Evaluation, options: dict
     ) -> Graph:
@@ -546,6 +589,7 @@ class StarGraph(_NetworkXBuiltin):
     messages = {
         "ilsmp": "Expected a positive integer at position 1 in ``.",
     }
+    summary_text = "build a star graph"
 
     def eval(
         self, n: Integer, expression, evaluation: Evaluation, options: dict

pymathics/graph/random.py

@@ -19,6 +19,10 @@
 
 class RandomGraph(_NetworkXBuiltin):
     """
+    <url>
+    :WMA:https://reference.wolfram.com/language/ref/RandomGraph.html
+    </url>
+
     <dl>
       <dt>'RandomGraph[{$n$, $m$}]'
       <dd>Returns a pseudorandom graph with $n$ vertices and $m$ edges.
@@ -28,6 +32,8 @@ class RandomGraph(_NetworkXBuiltin):
     </dl>
     """
 
+    summary_text = "build a random graph"
+
     def _generate(
         self, n: Integer, m: Integer, k: Integer, evaluation: Evaluation, options: dict
     ) -> Graph:

pymathics/graph/structured.py

@@ -13,6 +13,10 @@
 
 class PathGraph(_NetworkXBuiltin):
     """
+    <url>
+    :WMA:https://reference.wolfram.com/language/ref/PathGraph.html
+    </url>
+
     <dl>
       <dt>'PathGraph[{$v_1$, $v_2$, ...}]'
       <dd>Returns a Graph with a path with vertices $v_i$ and edges between $v-i$ and $v_i+1$ .
@@ -21,6 +25,8 @@ class PathGraph(_NetworkXBuiltin):
      = -Graph-
     """
 
+    summary_text = "create a graph from a path"
+
     def eval(self, e, evaluation: Evaluation, options: dict) -> Graph:
         "PathGraph[e_List, OptionsPattern[PathGraph]]"
         elements = e.elements
@@ -38,6 +44,16 @@ def edges():
 
 class TreeGraph(Graph):
     """
+    <url>
+    :WMA:https://reference.wolfram.com/language/ref/TreeGraph.html
+    </url>
+
+    <dl>
+      <dt>'TreeGraph[{$edge_1$, $edge_2$, ...}]'
+      <dd>create a tree-like from a list of edges.
+    </dl>
+
+
     >> TreeGraph[{1->2, 2->3, 2->4}]
      = -Graph-
 
@@ -49,6 +65,8 @@ class TreeGraph(Graph):
         "notree": "Graph is not a tree.",
     }
 
+    summary_text = "build a tree graph"
+
     def __init__(self, G, **kwargs):
         super(Graph, self).__init__()
         if not nx.is_tree(G):

pymathics/graph/tree.py

@@ -72,6 +72,8 @@ class TreeGraphQ(_NetworkXBuiltin):
      = False
     """
 
+    summary_text = "test for a tree-like graph"
+
     def eval(
         self, g, expression, evaluation: Evaluation, options: dict
     ) -> SymbolConstant: