Remove commented out code

2 files changed, 6 insertions, 124 deletions

diff --git a/networkx/algorithms/approximation/kcomponents.py b/networkx/algorithms/approximation/kcomponents.py
index da4608db..f7b8a49d 100644
--- a/networkx/algorithms/approximation/kcomponents.py
+++ b/networkx/algorithms/approximation/kcomponents.py
@@ -186,7 +186,7 @@ def _cliques_heuristic(G, H, k, min_density):
             sh_cnumber = nx.core_number(SH)
             sh_deg = dict(SH.degree())
             min_deg = min(sh_deg.values())
-            SH.remove_nodes_from((n for n, d in sh_deg.items() if d == min_deg))
+            SH.remove_nodes_from(n for n, d in sh_deg.items() if d == min_deg)
             SG = nx.k_core(G.subgraph(SH), k)
         else:
             yield SG
@@ -236,31 +236,6 @@ class _AntiGraph(nx.Graph):
         return dict((node, all_edge_dict) for node in 
                     set(self.adj) - set(self.adj[n]) - set([n]))
 
-    # def neighbors(self, n):
-    #     """Return a list of the nodes connected to the node n in 
-    #        the dense graph.
-
-    #     Parameters
-    #     ----------
-    #     n : node
-    #        A node in the graph
-
-    #     Returns
-    #     -------
-    #     nlist : list
-    #         A list of nodes that are adjacent to n.
-
-    #     Raises
-    #     ------
-    #     NetworkXError
-    #         If the node n is not in the graph.
-
-    #     """
-    #     try:
-    #         return list(set(self.adj) - set(self.adj[n]) - set([n]))
-    #     except KeyError:
-    #         raise NetworkXError("The node %s is not in the graph."%(n,))
-
     def neighbors(self, n):
         """Return an iterator over all neighbors of node n in the 
            dense graph.
@@ -271,16 +246,8 @@ class _AntiGraph(nx.Graph):
         except KeyError:
             raise NetworkXError("The node %s is not in the graph."%(n,))
 
-    # def degree(self, nbunch=None, weight=None):
-    #     """Return the degree of a node or nodes in the dense graph.
-    #     """
-    #     if nbunch in self:      # return a single node
-    #         return next(self.degree_iter(nbunch,weight))[1]
-    #     else:           # return a dict
-    #         return dict(self.degree_iter(nbunch,weight))
-
     def degree(self, nbunch=None, weight=None):
-        """Return an iterator for (node, degree) in the dense graph.
+        """Return an iterator for (node, degree) and degree for single node.
 
         The node degree is the number of edges adjacent to the node.
 
@@ -297,6 +264,8 @@ class _AntiGraph(nx.Graph):
 
         Returns
         -------
+        deg:
+            Degree of the node, if a single node is passed as argument.
         nd_iter : an iterator
             The iterator returns two-tuples of (node, degree).
 
@@ -315,7 +284,8 @@ class _AntiGraph(nx.Graph):
 
         """
         if nbunch in self:
-            nbrs = {v: self.all_edge_dict for v in set(self.adj) - set(self.adj[nbunch]) - set([nbunch])}
+            nbrs = {v: self.all_edge_dict for v in set(self.adj) - \
+                    set(self.adj[nbunch]) - set([nbunch])}
             if weight is None:
                 return len(nbrs) + (nbunch in nbrs)
             return sum((nbrs[nbr].get(weight, 1) for nbr in nbrs)) + \
diff --git a/networkx/classes/graph.py b/networkx/classes/graph.py
index 953d6f23..9967953e 100644
--- a/networkx/classes/graph.py
+++ b/networkx/classes/graph.py
@@ -1279,94 +1279,6 @@ class Graph(object):
                         (nbrs[n].get(weight, 1) if n in nbrs else 0))
         return d_iter()
 
-    # def degree(self, nbunch=None, weight=None):
-    #     """Return the degree of a node or nodes.
-
-    #     The node degree is the number of edges adjacent to that node.
-
-    #     Parameters
-    #     ----------
-    #     nbunch : iterable container, optional (default=all nodes)
-    #         A container of nodes.  The container will be iterated
-    #         through once.
-
-    #     weight : string or None, optional (default=None)
-    #        The edge attribute that holds the numerical value used
-    #        as a weight.  If None, then each edge has weight 1.
-    #        The degree is the sum of the edge weights adjacent to the node.
-
-    #     Returns
-    #     -------
-    #     nd : dictionary, or number
-    #         A dictionary with nodes as keys and degree as values or
-    #         a number if a single node is specified.
-
-    #     Examples
-    #     --------
-    #     >>> G = nx.Graph()   # or DiGraph, MultiGraph, MultiDiGraph, etc
-    #     >>> G.add_path([0,1,2,3])
-    #     >>> G.degree(0)
-    #     1
-    #     >>> G.degree([0,1])
-    #     {0: 1, 1: 2}
-    #     >>> list(G.degree([0,1]).values())
-    #     [1, 2]
-
-    #     """
-    #     if nbunch in self:      # return a single node
-    #         return next(self.degree_iter(nbunch, weight))[1]
-    #     else:           # return a dict
-    #         return dict(self.degree_iter(nbunch, weight))
-
-    # def degree_iter(self, nbunch=None, weight=None):
-    #     """Return an iterator for (node, degree).
-
-    #     The node degree is the number of edges adjacent to the node.
-
-    #     Parameters
-    #     ----------
-    #     nbunch : iterable container, optional (default=all nodes)
-    #         A container of nodes.  The container will be iterated
-    #         through once.
-
-    #     weight : string or None, optional (default=None)
-    #        The edge attribute that holds the numerical value used
-    #        as a weight.  If None, then each edge has weight 1.
-    #        The degree is the sum of the edge weights adjacent to the node.
-
-    #     Returns
-    #     -------
-    #     nd_iter : an iterator
-    #         The iterator returns two-tuples of (node, degree).
-
-    #     See Also
-    #     --------
-    #     degree
-
-    #     Examples
-    #     --------
-    #     >>> G = nx.Graph()   # or DiGraph, MultiGraph, MultiDiGraph, etc
-    #     >>> G.add_path([0,1,2,3])
-    #     >>> list(G.degree_iter(0)) # node 0 with degree 1
-    #     [(0, 1)]
-    #     >>> list(G.degree_iter([0,1]))
-    #     [(0, 1), (1, 2)]
-
-    #     """
-    #     if nbunch is None:
-    #         nodes_nbrs = self.adj.items()
-    #     else:
-    #         nodes_nbrs = ((n, self.adj[n]) for n in self.nbunch_iter(nbunch))
-
-    #     if weight is None:
-    #         for n, nbrs in nodes_nbrs:
-    #             yield (n, len(nbrs) + (n in nbrs))  # return tuple (n,degree)
-    #     else:
-    #         # edge weighted graph - degree is sum of nbr edge weights
-    #         for n, nbrs in nodes_nbrs:
-    #             yield (n, sum((nbrs[nbr].get(weight, 1) for nbr in nbrs)) +
-    #                 (n in nbrs and nbrs[n].get(weight, 1)))
-
     def clear(self):
         """Remove all nodes and edges from the graph.