fixed random walks with weights

ext/cIGraph_community.c

@@ -43,7 +43,7 @@ VALUE cIGraph_modularity(VALUE self, VALUE groups){
 }
 
 /* call-seq:
- *   graph.community_to_membership(merge,steps) -> Array
+ *   graph.community_to_membership(merge,steps,nodes) -> Array
  *
  * Create membership vector from community structure dendrogram This function 
  * creates a membership vector from a community structure dendrogram. 
@@ -458,10 +458,10 @@ igraph_arpack_options_init(&arpack_opt);
  *
  */
 
+
 VALUE cIGraph_community_walktrap(VALUE self, VALUE weights, VALUE steps){
 
   igraph_t *graph;
-
   igraph_vector_t weights_vec;
   igraph_vector_t modularity;
   igraph_matrix_t *merges = malloc(sizeof(igraph_matrix_t));
@@ -473,8 +473,8 @@ VALUE cIGraph_community_walktrap(VALUE self, VALUE weights, VALUE steps){
   Data_Get_Struct(self, igraph_t, graph);
 
   igraph_matrix_init(merges,0,0);
-  igraph_vector_init(&weights_vec,0);
   igraph_vector_init(&modularity,0);
+  igraph_vector_init(&weights_vec,RARRAY_LEN(weights));
 
   for(i=0;i<RARRAY_LEN(weights);i++){
     VECTOR(weights_vec)[i] = NUM2DBL(RARRAY_PTR(weights)[i]);
@@ -615,7 +615,7 @@ VALUE cIGraph_community_eb_get_merges(VALUE self, VALUE edges){
 }
 
 /* call-seq:
- *   graph.community_fastgreedy() -> Array
+ *   graph.community_fastgreedy(weights) -> Array
  *
  * Finding community structure by greedy optimization of modularity. 
  * This function implements the fast greedy modularity optimization algorithm 

test/tc_community.rb

@@ -11,7 +11,7 @@ class TestGraph < Test::Unit::TestCase
     groups,mod,temp = g.community_spinglass([],25,false,1,0.01,0.99,IGraph::SPINCOMM_UPDATE_SIMPLE,1.0)
     assert_in_delta 0.25, mod,  0.15
     assert_in_delta 0.200, temp, 0.100
-    assert_equal [['A','B','C','D','E','F']], groups
+    assert_equal [['A','B','C'],['D','E','F']], groups.sort
     commun,coh,adh  = g.community_spinglass_single([],'A',25,IGraph::SPINCOMM_UPDATE_SIMPLE,1.0)
     assert_in_delta 1.25, coh,  0.001
     assert_in_delta(-2.5, adh, 0.100)
@@ -63,10 +63,94 @@ class TestGraph < Test::Unit::TestCase
 
   def test_fastgreedy
     g = IGraph.new(['A','B','B','C','A','C','C','D','D','E','E','F','D','F'],false)
-    merges,mod = g.community_fastgreedy
+    merges,mod = g.community_fastgreedy([])
     groups = g.community_to_membership(merges,4,6)
     assert_equal [['A','B','C'],['D','E','F']], groups.sort
     assert_in_delta 0.19, mod[3], 0.1
   end
 
+
+
+  def test_extend_weights
+    graph = IGraph.new(['A1','B1','A1','C1','B1','C1','C1','D1',\
+                        'A2','B2','A2','C2','A2','D2','B2','C2','B2','D2','C2','D2','D2','E2',\
+                        'A3','B3','A3','C3','A3','D3','A3','E3','B3','C3','B3','D3','B3','E3','C3','D3','C3','E3','D3','E3',\
+                        'A1','A2','B2','B3'],false)
+
+             weights = [5,7,7,5,\
+                        6,6,5,7,5,6,8,\
+                        8,4,3,5,4,6,7,8,3,7,\
+                        3,3]
+    merges,mod = graph.community_walktrap(weights,50)
+    max_idx =  mod.index(mod.max)
+    res = graph.community_to_membership(merges,max_idx,graph.vcount()).sort
+    assert_equal [["A1", "B1", "C1", "D1"], ["A2", "B2", "C2", "D2", "E2"], ["A3", "B3", "C3", "D3", "E3"]], res
+
+    merges,mod = graph.community_walktrap([],50)
+    max_idx =  mod.index(mod.max)
+    res = graph.community_to_membership(merges,max_idx,graph.vcount()).sort
+    assert_equal [["A1", "B1", "C1", "D1"], ["A2", "B2", "C2", "D2", "E2"], ["A3", "B3", "C3", "D3", "E3"]], res
+
+  end
+
+  def test_extend_fastgreedy
+    graph = IGraph.new(['A1','B1','A1','C1','B1','C1','C1','D1',\
+                        'A2','B2','A2','C2','A2','D2','B2','C2','B2','D2','C2','D2','D2','E2',\
+                        'A3','B3','A3','C3','A3','D3','A3','E3','B3','C3','B3','D3','B3','E3','C3','D3','C3','E3','D3','E3',\
+                        'A1','A2','B2','B3'],false)
+
+             weights = [5,7,7,5,\
+                        6,6,5,7,5,6,8,\
+                        8,4,3,5,4,6,7,8,3,7,\
+                        3,3]
+
+    merges,mod = graph.community_fastgreedy(weights)
+    max_idx =  mod.index(mod.max)
+    res = graph.community_to_membership(merges,max_idx,graph.vcount()).sort
+    assert_equal [["A1", "B1", "C1", "D1"], ["A2", "B2", "C2", "D2", "E2"], ["A3", "B3", "C3", "D3", "E3"]], res
+
+    merges,mod = graph.community_fastgreedy([])
+    max_idx =  mod.index(mod.max)
+    res = graph.community_to_membership(merges,max_idx,graph.vcount()).sort
+    assert_equal [["A1", "B1", "C1", "D1"], ["A2", "B2", "C2", "D2", "E2"], ["A3", "B3", "C3", "D3", "E3"]], res
+
+
+  end
+
+  def test_extend_betweenness
+    graph = IGraph.new(['A1','B1','A1','C1','B1','C1','C1','D1',\
+                        'A2','B2','A2','C2','A2','D2','B2','C2','B2','D2','C2','D2','D2','E2',\
+                        'A3','B3','A3','C3','A3','D3','A3','E3','B3','C3','B3','D3','B3','E3','C3','D3','C3','E3','D3','E3',\
+                        'A1','A2','B2','B3'],false)
+
+             weights = [5,7,7,5,\
+                        6,6,5,7,5,6,8,\
+                        8,4,3,5,4,6,7,8,3,7,\
+                        3,3]
+
+
+    merges,result,edge_betw,bridges = graph.community_edge_betweenness(false)
+
+    #max_idx =  mod.index(mod.max)
+    res = graph.community_to_membership(merges,11,graph.vcount()).sort
+    #puts graph.modularity(edge_betw).to_s
+    assert_equal [["A1", "B1", "C1", "D1"], ["A2", "B2", "C2", "D2", "E2"], ["A3", "B3", "C3", "D3", "E3"]], res
+
+  end
+
+  def test_extend_eigenvector
+    graph = IGraph.new(['A1','B1','A1','C1','B1','C1','C1','D1',\
+                        'A2','B2','A2','C2','A2','D2','B2','C2','B2','D2','C2','D2','D2','E2',\
+                        'A3','B3','A3','C3','A3','D3','A3','E3','B3','C3','B3','D3','B3','E3','C3','D3','C3','E3','D3','E3',\
+                        'A1','A2','B2','B3'],false)
+
+             weights = [5,7,7,5,\
+                        6,6,5,7,5,6,8,\
+                        8,4,3,5,4,6,7,8,3,7,\
+                        3,3]
+
+    res = graph.community_leading_eigenvector(10)[0].sort
+    assert_equal [["A1", "B1", "C1", "D1"], ["A2", "B2", "C2", "D2", "E2"], ["A3", "B3", "C3", "D3", "E3"]], res
+  end
+
 end