NF: graphpartition will raise error if passed weighted matrix, new code to find solitary (unconnected) nodes

Author: CindeeM

brainx/modularity.py

@@ -78,6 +78,11 @@ def __init__(self, graph, index):
 
         # We'll need the graph's adjacency matrix often, so store it once
         self.graph_adj_matrix = nx.adj_matrix(graph)
+        #make sure adj_matrix is binary otherwise raise exception
+        if not self.graph_adj_matrix.sum() == \
+                self.graph_adj_matrix.astype(bool).sum():
+            raise ValueError('Adjacency matrix is weighted, need binary matrix')
+
 
         # Just to be sure, we don't want to count self-links, so we zero out the
         # diagonal.
@@ -175,6 +180,12 @@ def modularity_newman(self):
     modularity = modularity_newman
 
 
+    def find_solitary(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
+
     def compute_module_merge(self, m1, m2):
         """Merges two modules in a given partition.
 

brainx/tests/test_modularity.py

@@ -56,6 +56,21 @@ def test_graphpartition():
     index = {0:set([0,1]), 1:set([2,3])}
     gpart = mod.GraphPartition(graph, index)
     assert gpart._node_set == set([0,1,2,3])
+    # test raise error if matrix unweighted
+    jnk = np.random.random((10,10))
+    jnk = np.triu(jnk,1)
+    graph = nx.from_numpy_matrix(jnk, nx.Graph(weighted=False))
+    npt.assert_raises(ValueError, mod.GraphPartition, graph, index)
+    
+def test_find_solitary():
+    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()
+    npt.assert_equal(solitary_nodes, [6,7,8,9])
 
 def test_index_as_node_names():
     graph = nx.Graph()