RF: fix GraphPartition to calc find_unconnected_nodes no find_solitary based on suggestion by @kbegany

Author: CindeeM

brainx/modularity.py

@@ -177,11 +177,11 @@ def modularity_newman(self):
     modularity = modularity_newman
 
 
-    def find_solitary(self):
+    def find_unconnected_nodes(self):
         """ checks for nodes in graph with no edges """
         graph = nx.from_numpy_matrix(self.graph_adj_matrix)
-        solitary=[ n for n,d in graph.degree_iter() if d==0 ]
-        return solitary
+        unconnected = [ n for n,d in graph.degree_iter() if d==0 ]
+        return unconnected
 
     def compute_module_merge(self, m1, m2):
         """Merges two modules in a given partition.
@@ -1382,9 +1382,9 @@ def _divide_partition(p, max_div=np.inf):
         Bc = (B_ * Bc_mask).sum(axis=0)
         Bc = B_ - Bc
         q = s[None, :].dot(Bc).dot(s) / (4.0 * graph_A_.number_of_edges())
-        q2 = s[None, :].dot(B_).dot(s) / (4.0 * graph_A_.number_of_edges())
+        q2 = s[None, :].dot(B_).dot(s) #/ (4.0 * graph_A_.number_of_edges())
         print 'orig delta q', q2, 'new delta q', q
-        if q <= 0:
+        if q2 <= 0:
             return [p]
 
         # Make the partitioning, and subdivide each

brainx/tests/test_modularity.py

@@ -62,14 +62,14 @@ def test_graphpartition():
     graph = nx.from_numpy_matrix(jnk, nx.Graph(weighted=False))
     npt.assert_raises(ValueError, mod.GraphPartition, graph, index)
 
-def test_find_solitary():
+def test_find_unconnected_nodes():
     jnk = np.zeros((10,10))
     jnk[:6,:6] = 1
     jnk = np.triu(jnk,1)
     graph = nx.from_numpy_matrix(jnk>0, nx.Graph(weighted=False))
     index = {0:set([0,1,2,3,4,5,6,7,8,9])}
     graph_partition = mod.GraphPartition(graph, index)
-    solitary_nodes = graph_partition.find_solitary()
+    solitary_nodes = graph_partition.find_unconnected_nodes()
     npt.assert_equal(solitary_nodes, [6,7,8,9])
 
 def test_index_as_node_names():