Repository: networkx/networkx

Issue:
add_cycle, add_path, etc. must be removed from Graph documentation
The documentation for, for example, the `Graph` class includes an entry in autosummary for `add_cycle`, etc., but these methods were removed in #1970 in favor of functions. The autosummary entries must be removed.



Discussion:
Looks like they should be added to the "functions" autosummary entries as well.

There are quite a few other errors in the [sphinx doc builds](http://readthedocs.org/projects/networkx/builds/3764367/) too... 
mostly with communicability and cuts.

I'll try to clean that up.


Resolving patch:
diff --git a/networkx/algorithms/community/quality.py b/networkx/algorithms/community/quality.py
--- a/networkx/algorithms/community/quality.py
+++ b/networkx/algorithms/community/quality.py
@@ -234,13 +234,6 @@ def coverage(G, partition):
     NetworkXError
         If ``partition`` is not a valid partition of the nodes of ``G``.
 
-    References
-    ----------
-    .. [1] Santo Fortunato.
-           "Community Detection in Graphs".
-           *Physical Reports*, Volume 486, Issue 3--5 pp. 75--174
-           <http://arxiv.org/abs/0906.0612>
-
     Notes
     -----
     If ``G`` is a multigraph, the multiplicity of edges is counted.
diff --git a/networkx/algorithms/cuts.py b/networkx/algorithms/cuts.py
--- a/networkx/algorithms/cuts.py
+++ b/networkx/algorithms/cuts.py
@@ -122,7 +122,7 @@ def volume(G, S, weight=None):
     ----------
     .. [1] David Gleich.
            *Hierarchical Directed Spectral Graph Partitioning*.
-          <https://www.cs.purdue.edu/homes/dgleich/publications/Gleich%202005%20-%20hierarchical%20directed%20spectral.pdf>
+           <https://www.cs.purdue.edu/homes/dgleich/publications/Gleich%202005%20-%20hierarchical%20directed%20spectral.pdf>
 
     """
     degree = G.out_degree if G.is_directed() else G.degree
@@ -170,7 +170,7 @@ def normalized_cut_size(G, S, T=None, weight=None):
     ----------
     .. [1] David Gleich.
            *Hierarchical Directed Spectral Graph Partitioning*.
-          <https://www.cs.purdue.edu/homes/dgleich/publications/Gleich%202005%20-%20hierarchical%20directed%20spectral.pdf>
+           <https://www.cs.purdue.edu/homes/dgleich/publications/Gleich%202005%20-%20hierarchical%20directed%20spectral.pdf>
 
     """
     if T is None:
@@ -217,7 +217,7 @@ def conductance(G, S, T=None, weight=None):
     ----------
     .. [1] David Gleich.
            *Hierarchical Directed Spectral Graph Partitioning*.
-          <https://www.cs.purdue.edu/homes/dgleich/publications/Gleich%202005%20-%20hierarchical%20directed%20spectral.pdf>
+           <https://www.cs.purdue.edu/homes/dgleich/publications/Gleich%202005%20-%20hierarchical%20directed%20spectral.pdf>
 
     """
     if T is None:
@@ -310,7 +310,7 @@ def mixing_expansion(G, S, T=None, weight=None):
     .. [1] Vadhan, Salil P.
            "Pseudorandomness."
            *Foundations and Trends
-            in Theoretical Computer Science* 7.1–3 (2011): 1–336.
+           in Theoretical Computer Science* 7.1–3 (2011): 1–336.
            <http://dx.doi.org/10.1561/0400000010>
 
     """
@@ -350,7 +350,7 @@ def node_expansion(G, S):
     .. [1] Vadhan, Salil P.
            "Pseudorandomness."
            *Foundations and Trends
-            in Theoretical Computer Science* 7.1–3 (2011): 1–336.
+           in Theoretical Computer Science* 7.1–3 (2011): 1–336.
            <http://dx.doi.org/10.1561/0400000010>
 
     """
@@ -388,8 +388,8 @@ def boundary_expansion(G, S):
     ----------
     .. [1] Vadhan, Salil P.
            "Pseudorandomness."
-           *Foundations and Trends
-            in Theoretical Computer Science* 7.1–3 (2011): 1–336.
+           *Foundations and Trends in Theoretical Computer Science*
+           7.1–3 (2011): 1–336.
            <http://dx.doi.org/10.1561/0400000010>
 
     """
diff --git a/networkx/algorithms/reciprocity.py b/networkx/algorithms/reciprocity.py
--- a/networkx/algorithms/reciprocity.py
+++ b/networkx/algorithms/reciprocity.py
@@ -19,7 +19,7 @@ def reciprocity(G, nodes=None):
     The reciprocity of a directed graph is defined as the ratio
     of the number of edges pointing in both directions to the total
     number of edges in the graph.
-    Formally, r = |{(u,v) \in G|(v,u) \in G}| / |{(u,v) \in G}|.
+    Formally, :math:`r = |{(u,v) \in G|(v,u) \in G}| / |{(u,v) \in G}|`.
 
     The reciprocity of a single node u is defined similarly,
     it is the ratio of the number of edges in both directions to


Test patch: