# HG changeset patch
# User Minh Van Nguyen
# Date 1272458371 25200
# Node ID 9188e33e33ed5708fcccff34d429d701dec3baaa
# Parent 5af3155634cd101e69191b123948f78e6981b931
#8786: reviewer patch: autogenerated broken links to Wikipedia
diff git a/sage/graphs/digraph.py b/sage/graphs/digraph.py
 a/sage/graphs/digraph.py
+++ b/sage/graphs/digraph.py
@@ 18,10 +18,9 @@
Directed graph.
A digraph or directed graph is a set of vertices connected by oriented
 edges.

+ edges. For more information, see the
`Wikipedia article on digraphs
 `_
+ `_.
One can very easily create a directed graph in Sage by typing::
@@ 1100,9 +1099,9 @@
The minimum feedback edge set of a digraph is a set of edges
that intersect all the circuits of the digraph.
Equivalently, a minimum feedback arc set of a DiGraph is a set
 `S` of arcs such that the digraph `GS` is acyclic.

 `Wikipedia article on Feedback arc sets
+ `S` of arcs such that the digraph `GS` is acyclic. For more
+ information, see the
+ `Wikipedia article on feedback arc sets
`_.
INPUT :
@@ 1209,9 +1208,9 @@
The minimum feedback vertex set of a digraph is a set of vertices
that intersect all the circuits of the digraph.
Equivalently, a minimum feedback vertex set of a DiGraph is a set
 `S` of vertices such that the digraph `GS` is acyclic.

 `Wikipedia article on Feedback vertex sets
+ `S` of vertices such that the digraph `GS` is acyclic. For more
+ information, see the
+ `Wikipedia article on feedback vertex sets
`_.
INPUT :
diff git a/sage/graphs/digraph_generators.py b/sage/graphs/digraph_generators.py
 a/sage/graphs/digraph_generators.py
+++ b/sage/graphs/digraph_generators.py
@@ 287,9 +287,9 @@
In this digraph, there is an arc `w_1w_2` if `w_2`
can be obtained from `w_1` by removing the leftmost
letter and adding a new letter at its right end.

 `Wikipedia article on the De Bruijn graph
 `_
+ For more information, see the
+ `Wikipedia article on De Bruijn graph
+ `_.
INPUT:
diff git a/sage/graphs/generic_graph.py b/sage/graphs/generic_graph.py
 a/sage/graphs/generic_graph.py
+++ b/sage/graphs/generic_graph.py
@@ 3027,8 +3027,8 @@
A minimum edge cut between two vertices `s` and `t` of self
is a set `A` of edges of minimum weight such that the graph
 obtained by removing `A` from self is disconnected.

+ obtained by removing `A` from self is disconnected. For more
+ information, see the
`Wikipedia article on cuts
`_.
@@ 3154,11 +3154,9 @@
A vertex cut between two non adjacent vertices is a set `U`
of vertices of self such that the graph obtained by removing
 `U` from self is disconnected.

+ `U` from self is disconnected. For more information, see the
`Wikipedia article on cuts
 `_

+ `_.
INPUT:
@@ 3268,8 +3266,7 @@
A minimum vertex cover of a graph is a set `S` of
vertices such that each edge is incident to at least
one element of `S`, and such that `S` is of minimum
 cardinality.

+ cardinality. For more information, see the
`Wikipedia article on vertex cover
`_.
@@ 3359,8 +3356,8 @@
The minimum feedback edge set of a digraph is a set of edges
that intersect all the circuits of the digraph.
Equivalently, a minimum feedback arc set of a DiGraph is a set
 `S` of arcs such that the digraph `GS` is acyclic.

+ `S` of arcs such that the digraph `GS` is acyclic. For more
+ information, see the
`Wikipedia article on feedback arc sets
`_.
@@ 3473,9 +3470,9 @@
The minimum feedback vertex set of a digraph is a set of vertices
that intersect all the circuits of the digraph.
Equivalently, a minimum feedback vertex set of a DiGraph is a set
 `S` of vertices such that the digraph `GS` is acyclic.

 `Wikipedia article on Feedback vertex sets
+ `S` of vertices such that the digraph `GS` is acyclic. For more
+ information, see the
+ `Wikipedia article on feedback vertex sets
`_.
INPUT :
@@ 3581,8 +3578,7 @@
def max_cut(self,value_only=True,use_edge_labels=True, vertices=False):
r"""
 Returns a maximum edge cut of the graph

+ Returns a maximum edge cut of the graph. For more information, see the
`Wikipedia article on cuts
`_.
@@ 3718,11 +3714,10 @@
def flow(self,x,y,value_only=True,integer=False, use_edge_labels=True,vertex_bound=False):
r"""
Returns a maximum flow in the graph from ``x`` to ``y``
 represented by an optimal valuation of the edges.

 `Wikipedia article on flows
 `_.

+ represented by an optimal valuation of the edges. For more
+ information, see the
+ `Wikipedia article on maximum flow
+ `_.
As an optimization problem, is can be expressed this way :
@@ 3982,11 +3977,9 @@
def matching(self,value_only=False, use_edge_labels=True):
r"""
Returns a maximum weighted matching of the graph
 represented by the list of its edges.

+ represented by the list of its edges. For more information, see the
`Wikipedia article on matchings
 `_.

+ `_.
Given a graph `G` such that each edge `e` has a weight `w_e`,
a maximum matching is a subset `S` of the edges of `G` of
@@ 4051,8 +4044,7 @@
def dominating_set(self, independent=False, value_only=False,log=0):
r"""
Returns a minimum dominating set of the graph
 represented by the list of its vertices.

+ represented by the list of its vertices. For more information, see the
`Wikipedia article on dominating sets
`_.
@@ 4138,8 +4130,8 @@
def edge_connectivity(self,value_only=True,use_edge_labels=False, vertices=False):
r"""
 Returns the edge connectivity of the graph

+ Returns the edge connectivity of the graph. For more information, see
+ the
`Wikipedia article on connectivity
`_.
@@ 4332,11 +4324,10 @@
def vertex_connectivity(self,value_only=True, sets=False):
r"""
 Returns the vertex connectivity of the graph

+ Returns the vertex connectivity of the graph. For more information,
+ see the
`Wikipedia article on connectivity
`_.

INPUT:
@@ 8292,10 +8283,10 @@
Performs a Lex BFS on the graph.
A Lex BFS ( or Lexicographic BreadthFirst Search ) is a Breadth
 First Search used for the recognition of Chordal Graphs.

+ First Search used for the recognition of Chordal Graphs. For more
+ information, see the
`Wikipedia article on LexBFS
 `_
+ `_.
INPUT: