Trac #33562: Bad error message for weighted adjacency matrix

{{{
H=Graph({0:[1,2,3], 4:[0,2], 6:[1,2,3,4,5]})
H.weighted(True)
H.weighted_adjacency_matrix()
}}}
should give something useful, but instead is an inexplicable error
message
{{{
TypeError: NoneType takes no arguments
}}}
This happens whether or not this graph is said to be weighted.  There
should be an error catch for a useful message.

URL: https://trac.sagemath.org/33562
Reported by: kcrisman
Ticket author(s): David Coudert
Reviewer(s): Dima Pasechnik

src/sage/graphs/generic_graph.py

@@ -2324,7 +2324,8 @@ def distance_matrix(self, vertices=None, *, base_ring=None, **kwds):
  ret.set_immutable()
  return ret
 
- def weighted_adjacency_matrix(self, sparse=True, vertices=None, *, base_ring=None, **kwds):
+ def weighted_adjacency_matrix(self, sparse=True, vertices=None,
+ default_weight=None, *, base_ring=None, **kwds):
  """
  Return the weighted adjacency matrix of the graph.
 
@@ -2341,6 +2342,10 @@ def weighted_adjacency_matrix(self, sparse=True, vertices=None, *, base_ring=Non
  each vertex is represented by its position in the list returned by
  method :meth:`vertices`
 
+ - ``default_weight`` -- (default: ``None``); specifies the weight to
+ replace any ``None`` edge label. When not specified an error is raised
+ if the label of an edge is ``None``.
+
  - ``base_ring`` -- a ring (default: determined from the weights); the base
  ring of the matrix space to use.
 
@@ -2394,6 +2399,22 @@ def weighted_adjacency_matrix(self, sparse=True, vertices=None, *, base_ring=Non
  [0 0 0]
  [1 0 0]
  [1 0 0]
+
+ Check error message for non numerical edge weights (:trac:`33562`)::
+
+ sage: G = Graph([(0, 1)])
+ sage: G.weighted_adjacency_matrix()
+ Traceback (most recent call last):
+ ...
+ ValueError: cannot find the weight of (0, 1, None). Consider setting parameter 'default_weight'
+ sage: G.weighted_adjacency_matrix(default_weight=3)
+ [0 3]
+ [3 0]
+ sage: G = Graph([(0, 1, 'a')])
+ sage: G.weighted_adjacency_matrix()
+ Traceback (most recent call last):
+ ...
+ TypeError: Cannot convert NoneType to sage.structure.parent.Parent
  """
  if self.has_multiple_edges():
  raise NotImplementedError("don't know how to represent weights for a multigraph")
@@ -2404,20 +2425,35 @@ def weighted_adjacency_matrix(self, sparse=True, vertices=None, *, base_ring=Non
  set(vertices) != set(self.vertex_iterator())):
  raise ValueError("``vertices`` must be a permutation of the vertices")
 
- new_indices = {v: i for i, v in enumerate(vertices)}
+ # Method for checking edge weights and setting default weight
+ if default_weight is None:
+ def func(u, v, label):
+ if label is None:
+ raise ValueError(f"cannot find the weight of ({u}, {v}, None). "
+ "Consider setting parameter 'default_weight'")
+ return label
+ else:
+ def func(u, v, label):
+ if label is None:
+ return default_weight
+ return label
+
+ new_indices = {v: i for i,v in enumerate(vertices)}
 
  D = {}
  if self._directed:
- for u, v, l in self.edge_iterator():
+ for u, v, label in self.edge_iterator():
  i = new_indices[u]
  j = new_indices[v]
- D[i, j] = l
+ D[i, j] = func(u, v, label)
  else:
- for u, v, l in self.edge_iterator():
+ for u, v, label in self.edge_iterator():
  i = new_indices[u]
  j = new_indices[v]
- D[i, j] = l
- D[j, i] = l
+ label = func(u, v, label)
+ D[i, j] = label
+ D[j, i] = label
+
  from sage.matrix.constructor import matrix
  if base_ring is None:
  M = matrix(self.num_verts(), D, sparse=sparse, **kwds)