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fixed random walks with weights

This commit is contained in:
Hamlet 2010-11-24 18:46:05 +01:00
parent bdae94f63e
commit 91fd079def
2 changed files with 90 additions and 6 deletions
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8
ext/cIGraph_community.c
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@ -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

88
test/tc_community.rb
View File

@ -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