Fix some sphinx formatting errors

make all doc_strings raw format r''' ''' correct underline lengths for headings fix latex issue in harmonic_centrality replace 🎫, :url:, :doi:, :arxiv: with links to webpages fix spacing with commas before colons so sphinx can parse well add "methods" heading in graph class rst files
networkx · Oct 4, 2015 · fdbf0ef · fdbf0ef
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diff --git a/doc/source/bibliography.rst b/doc/source/bibliography.rst
@@ -5,7 +5,7 @@ Bibliography
 
 .. [BA02] R. Albert and A.-L. Barabási, "Statistical mechanics of complex
    networks", Reviews of Modern Physics, 74, pp. 47-97, 2002. 
-   :arxiv:`cond-mat/0106096`
+   http://arxiv.org/abs/cond-mat/0106096
 
 .. [Bollobas01] B. Bollobás, "Random Graphs", Second Edition,
    Cambridge University Press, 2001.
@@ -19,17 +19,17 @@ Bibliography
 
 .. [choudum1986] S.A. Choudum. "A simple proof of the Erdős-Gallai theorem on 
    graph sequences." Bulletin of the Australian Mathematical Society, 33, 
-   pp 67-70, 1986. :doi:`10.1017/S0004972700002872`
+   pp 67-70, 1986. http://dx.doi.org/10.1017/S0004972700002872
 
 .. [Diestel97] R. Diestel, "Graph Theory", Springer-Verlag, 1997. 
-   :url:`http://diestel-graph-theory.com/index.html`
+   http://diestel-graph-theory.com/index.html
 
 .. [DM03] S.N. Dorogovtsev and J.F.F. Mendes, "Evolution of Networks",
    Oxford University Press, 2003.
 
 .. [EppsteinPads] David Eppstein.
    PADS, A library of Python Algorithms and Data Structures.
-   :url:`http://www.ics.uci.edu/~eppstein/PADS`
+   http://www.ics.uci.edu/~eppstein/PADS
    
 .. [EG1960] Erdős and Gallai, Mat. Lapok 11 264, 1960.
 
@@ -48,7 +48,7 @@ Bibliography
 
 .. [Newman03] M.E.J. Newman, "The Structure and Function of Complex
    Networks", SIAM Review, 45, pp. 167-256, 2003. 
-   :url:`http://epubs.siam.org/doi/abs/10.1137/S003614450342480`
+   http://epubs.siam.org/doi/abs/10.1137/S003614450342480
 
 .. [Sedgewick02] R. Sedgewick, "Algorithms in C: Parts 1-4: 
    Fundamentals, Data Structure, Sorting, Searching", Addison Wesley
@@ -61,5 +61,5 @@ Bibliography
     2nd ed., 2001.
 
 .. [vanRossum98] Guido van Rossum. Python Patterns - Implementing Graphs, 1998.
-   :url:`http://www.python.org/doc/essays/graphs`
+   http://www.python.org/doc/essays/graphs
 
diff --git a/doc/source/conf.py b/doc/source/conf.py
@@ -55,7 +55,7 @@ def cd(newpath):
         # from networkx/doc/source (which holds conf.py).
         py = sys.executable
         subprocess.call([py, 'make_gallery.py'])
-        subprocess.call([py, 'make_examples.py', '../examples', 'source'])
+        subprocess.call([py, 'make_examples_rst.py', '../examples', 'source'])
 
 # If your extensions are in another directory, add it here.
 # These locations are relative to conf.py

diff --git a/doc/source/install.rst b/doc/source/install.rst
@@ -74,11 +74,11 @@ GitHub
 ------
 
   1. Clone the networkx repostitory
-    ::
+     (see https://github.com/networkx/networkx/ for options)
+     ::
 
        git clone https://github.com/networkx/networkx.git
 
-  (see https://github.com/networkx/networkx/ for other options)
 
   2. Change directory to :samp:`networkx`
 

diff --git a/doc/source/reference/algorithms.rst b/doc/source/reference/algorithms.rst
@@ -41,7 +41,6 @@ Algorithms
    algorithms.matching
    algorithms.minors
    algorithms.mis
-   algorithms.mst
    algorithms.operators
    algorithms.rich_club
    algorithms.shortest_paths

diff --git a/doc/source/reference/api_1.5.rst b/doc/source/reference/api_1.5.rst
@@ -12,7 +12,7 @@ Weighted graph algorithms
 
 Many 'weighted' graph algorithms now take optional parameter to 
 specifiy which edge attribute should be used for the weight
-(default='weight') (:ticket:`509`)
+(default='weight') (ticket https://networkx.lanl.gov/trac/ticket/509)
 
 In some cases the parameter name was changed from weighted_edges,
 or weighted, to weight.  Here is how to specify which edge attribute 

diff --git a/doc/source/reference/api_1.6.rst b/doc/source/reference/api_1.6.rst
@@ -21,7 +21,7 @@ Weighted graph algorithms
 
 Many 'weighted' graph algorithms now take optional parameter to 
 specifiy which edge attribute should be used for the weight
-(default='weight') (:ticket:`573`)
+(default='weight') (ticket https://networkx.lanl.gov/trac/ticket/573)
 
 In some cases the parameter name was changed from weighted, to weight.  Here is
 how to specify which edge attribute will be used in the algorithms:

diff --git a/doc/source/reference/classes.digraph.rst b/doc/source/reference/classes.digraph.rst
@@ -9,6 +9,9 @@ Overview
 .. currentmodule:: networkx
 .. autofunction:: DiGraph
 
+=======
+Methods
+=======
 
 Adding and removing nodes and edges
 ===================================

diff --git a/doc/source/reference/classes.graph.rst b/doc/source/reference/classes.graph.rst
@@ -9,6 +9,10 @@ Overview
 .. currentmodule:: networkx
 .. autofunction:: Graph
 
+=======
+Methods
+=======
+
 Adding and removing nodes and edges
 ===================================
 

diff --git a/doc/source/reference/classes.multidigraph.rst b/doc/source/reference/classes.multidigraph.rst
@@ -10,6 +10,10 @@ Overview
 .. currentmodule:: networkx
 .. autofunction:: MultiDiGraph
 
+=======
+Methods
+=======
+
 Adding and Removing Nodes and Edges
 ===================================
 

diff --git a/doc/source/reference/classes.multigraph.rst b/doc/source/reference/classes.multigraph.rst
@@ -9,6 +9,10 @@ Overview
 .. currentmodule:: networkx
 .. autofunction:: MultiGraph
 
+=======
+Methods
+=======
+
 Adding and removing nodes and edges
 ===================================
 

diff --git a/doc/source/reference/functions.rst b/doc/source/reference/functions.rst
@@ -24,7 +24,6 @@ Nodes
 
    nodes
    number_of_nodes
-   nodes_iter
    all_neighbors
    non_neighbors
    common_neighbors
@@ -38,7 +37,6 @@ Edges
 
    edges
    number_of_edges
-   edges_iter
    non_edges
 
 

diff --git a/doc/source/reference/news.rst b/doc/source/reference/news.rst
@@ -8,6 +8,10 @@ NetworkX 2.0
 ------------
 Release date: TBD
 
+.. toctree::
+
+   migration_guide_from_1.x_to_2.0
+
 NetworkX 1.10
 --------------
 Release date: 2 August 2015
@@ -18,11 +22,13 @@ Highlights
 ~~~~~~~~~~
 - Connected components now return generators
 - new functions including
-  - enumerate_all_cliques, greedy_coloring, edge_dfs, find_cycle
+
+  + enumerate_all_cliques, greedy_coloring, edge_dfs, find_cycle
     immediate_dominators, harmonic_centrality
-  - Hopcraft--Karp algorithm for maximum matchings
-  - optimum branchings and arborescences.
-  - all_simple_paths
+  + Hopcraft--Karp algorithm for maximum matchings
+  + optimum branchings and arborescences.
+  + all_simple_paths
+
 - pyparsing dependence removed from GML reader/parser
 - improve flow algorithms
 - new generators releated to expander graphs.
@@ -188,7 +194,8 @@ New features
    that handle subsets of nodes
  - :mod:`In-place node relabeling <networkx.relabel>` 
  - Many 'weighted' graph algorithms now take optional parameter to use 
-   specified edge attribute (default='weight') (:ticket:`509`)
+   specified edge attribute (default='weight')
+   (ticket https://networkx.lanl.gov/trac/ticket/509)
 
  - Test for :mod:`distance regular <networkx.algorithms.distance_regular>` graphs
  - Fast :mod:`directed Erdős-Renyi graph  <networkx.generators.random_graphs>` generator
@@ -206,21 +213,34 @@ See :doc:`api_1.5`
 
 Bug fixes
 ~~~~~~~~~
- - Fix edge handling for multigraphs in networkx/graphviz interface 
-   (:ticket:`507`)
- - Update networkx/pydot interface for new versions of pydot 
-   (:ticket:`506`), (:ticket:`535`)
- - Fix negative cycle handling in Bellman-Ford (:ticket:`502`)
- - Write more attributes with GraphML and GML formats (:ticket:`480`)
- - Handle white space better in read_edgelist (:ticket:`513`)
- - Better parsing of Pajek format files (:ticket:`524`) (:ticket:`542`)
- - Isolates functions work with directed graphs (:ticket:`526`)
- - Faster conversion to numpy matrices (:ticket:`529`)
- - Add graph['name'] and use properties to access Graph.name (:ticket:`544`)
- - Topological sort confused None and 0 (:ticket:`546`)
- - GEXF writer mishandled weight=0 (:ticket:`550`)
- - Speedup in SciPy version of PageRank (:ticket:`554`)
- - Numpy PageRank node order incorrect + speedups (:ticket:`555`)
+ - Fix edge handling for multigraphs in networkx/graphviz interface
+   (ticket https://networkx.lanl.gov/trac/ticket/507)
+ - Update networkx/pydot interface for new versions of pydot
+   (ticket https://networkx.lanl.gov/trac/ticket/506)
+   (ticket https://networkx.lanl.gov/trac/ticket/535)
+ - Fix negative cycle handling in Bellman-Ford
+   (ticket https://networkx.lanl.gov/trac/ticket/502)
+ - Write more attributes with GraphML and GML formats
+   (ticket https://networkx.lanl.gov/trac/ticket/480)
+ - Handle white space better in read_edgelist
+   (ticket https://networkx.lanl.gov/trac/ticket/513)
+ - Better parsing of Pajek format files
+   (ticket https://networkx.lanl.gov/trac/ticket/524)
+   (ticket https://networkx.lanl.gov/trac/ticket/542)
+ - Isolates functions work with directed graphs
+   (ticket https://networkx.lanl.gov/trac/ticket/526)
+ - Faster conversion to numpy matrices
+   (ticket https://networkx.lanl.gov/trac/ticket/529)
+ - Add graph['name'] and use properties to access Graph.name
+   (ticket https://networkx.lanl.gov/trac/ticket/544)
+ - Topological sort confused None and 0
+   (ticket https://networkx.lanl.gov/trac/ticket/546)
+ - GEXF writer mishandled weight=0
+   (ticket https://networkx.lanl.gov/trac/ticket/550)
+ - Speedup in SciPy version of PageRank
+   (ticket https://networkx.lanl.gov/trac/ticket/554)
+ - Numpy PageRank node order incorrect + speedups
+   (ticket https://networkx.lanl.gov/trac/ticket/555)
 
 NetworkX 1.4
 ------------

diff --git a/doc/source/reference/release_2.0.rst b/doc/source/reference/release_2.0.rst
@@ -11,7 +11,7 @@ Please send comments and questions to the networkx-discuss [mailing list](http:/
 
 API changes
 -----------
-* [`<>`_]
+* Base Graph Class Changes
   With the release of NetworkX 2.0 we are moving towards an iterator reporting API.
   We used to have two methods for the same property of the graph, one that returns a
   list and one that returns an iterator. With 2.0 we have removed the one that returns

diff --git a/networkx/algorithms/assortativity/connectivity.py b/networkx/algorithms/assortativity/connectivity.py
@@ -48,18 +48,17 @@ def _avg_deg_conn(G, neighbors, source_degree, target_degree,
 
 def average_degree_connectivity(G, source="in+out", target="in+out",
                                 nodes=None, weight=None):
-    """Compute the average degree connectivity of graph.
+    r"""Compute the average degree connectivity of graph.
 
     The average degree connectivity is the average nearest neighbor degree of
     nodes with degree k. For weighted graphs, an analogous measure can
     be computed using the weighted average neighbors degree defined in
-    [1]_, for a node `i`, as:
+    [1]_, for a node `i`, as
 
     .. math::
 
         k_{nn,i}^{w} = \frac{1}{s_i} \sum_{j \in N(i)} w_{ij} k_j
 
-
     where `s_i` is the weighted degree of node `i`,
     `w_{ij}` is the weight of the edge that links `i` and `j`,
     and `N(i)` are the neighbors of node `i`.
@@ -74,7 +73,7 @@ def average_degree_connectivity(G, source="in+out", target="in+out",
     target : "in"|"out"|"in+out" (default:"in+out"
        Directed graphs only. Use "in"- or "out"-degree for target node.
 
-    nodes: list or iterable (optional)
+    nodes : list or iterable (optional)
         Compute neighbor connectivity for these nodes. The default is all
         nodes.
 
@@ -84,7 +83,7 @@ def average_degree_connectivity(G, source="in+out", target="in+out",
 
     Returns
     -------
-    d: dict
+    d : dict
        A dictionary keyed by degree k with the value of average connectivity.
 
     Examples

diff --git a/networkx/algorithms/bipartite/projection.py b/networkx/algorithms/bipartite/projection.py
@@ -63,7 +63,7 @@ def projected_graph(B, nodes, multigraph=False):
     [['a', 'b'], ['a', 'b']]
 
     Notes
-    ------
+    -----
     No attempt is made to verify that the input graph B is bipartite.
     Returns a simple graph that is the projection of the bipartite graph B
     onto the set of nodes given in list nodes.  If multigraph=True then
@@ -158,7 +158,7 @@ def weighted_projected_graph(B, nodes, ratio=False):
     [(1, 3, {'weight': 0.5})]
     
     Notes
-    ------
+    -----
     No attempt is made to verify that the input graph B is bipartite.
     The graph and node properties are (shallow) copied to the projected graph.
 
@@ -252,7 +252,7 @@ def collaboration_weighted_projected_graph(B, nodes):
     (2, 5, {'weight': 0.5})
     
     Notes
-    ------
+    -----
     No attempt is made to verify that the input graph B is bipartite.
     The graph and node properties are (shallow) copied to the projected graph.
 
@@ -344,7 +344,7 @@ def overlap_weighted_projected_graph(B, nodes, jaccard=True):
     [(0, 2, {'weight': 1.0}), (2, 4, {'weight': 1.0})]
     
     Notes
-    ------
+    -----
     No attempt is made to verify that the input graph B is bipartite.
     The graph and node properties are (shallow) copied to the projected graph.
 
@@ -457,7 +457,7 @@ def generic_weighted_projected_graph(B, nodes, weight_function=None):
     [(0, 1, {'weight': 10})]
     
     Notes
-    ------
+    -----
     No attempt is made to verify that the input graph B is bipartite.
     The graph and node properties are (shallow) copied to the projected graph.
 

diff --git a/networkx/algorithms/centrality/betweenness.py b/networkx/algorithms/centrality/betweenness.py
@@ -25,7 +25,7 @@ def betweenness_centrality(G, k=None, normalized=True, weight=None,
     r"""Compute the shortest-path betweenness centrality for nodes.
 
     Betweenness centrality of a node `v` is the sum of the
-    fraction of all-pairs shortest paths that pass through `v`:
+    fraction of all-pairs shortest paths that pass through `v`
 
     .. math::
 
@@ -134,7 +134,7 @@ def edge_betweenness_centrality(G, k=None, normalized=True, weight=None,
     r"""Compute betweenness centrality for edges.
 
     Betweenness centrality of an edge `e` is the sum of the
-    fraction of all-pairs shortest paths that pass through `e`:
+    fraction of all-pairs shortest paths that pass through `e`
 
     .. math::
 

diff --git a/networkx/algorithms/centrality/betweenness_subset.py b/networkx/algorithms/centrality/betweenness_subset.py
@@ -24,7 +24,7 @@
 def betweenness_centrality_subset(G,sources,targets,
                                   normalized=False,
                                   weight=None):
-    """Compute betweenness centrality for a subset of nodes.
+    r"""Compute betweenness centrality for a subset of nodes.
 
     .. math::
 
@@ -106,7 +106,7 @@ def betweenness_centrality_subset(G,sources,targets,
 def edge_betweenness_centrality_subset(G,sources,targets,
                                        normalized=False,
                                        weight=None):
-    """Compute betweenness centrality for edges for a subset of nodes.
+    r"""Compute betweenness centrality for edges for a subset of nodes.
 
     .. math::
 

diff --git a/networkx/algorithms/centrality/eigenvector.py b/networkx/algorithms/centrality/eigenvector.py
@@ -68,7 +68,7 @@ def eigenvector_centrality(G, max_iter=100, tol=1.0e-6, nstart=None,
     hits
 
     Notes
-    ------
+    -----
     The measure was introduced by [1]_ and is discussed in [2]_.
 
     Eigenvector convergence: The power iteration method is used to compute
@@ -179,7 +179,7 @@ def eigenvector_centrality_numpy(G, weight='weight'):
     hits
 
     Notes
-    ------
+    -----
     The measure was introduced by [1]_.
 
     This algorithm uses the SciPy sparse eigenvalue solver (ARPACK) to