def testSimilarNodesMining(self):
dummy_hypergraph = Hypergraph(example_graphs.snm_dummy_graph)
rballs_database, _ = similar_nodes_mining.extract_rballs_database(dummy_hypergraph, r_in=3, r_out=2, r_all=0)
nodes_count = dummy_hypergraph.number_of_nodes()
ch_matrix = CharacteristicMatrix(rballs_database, nodes_count, wl_iterations=0)
ch_matrix_jaccard_sim = ch_matrix.compute_jaccard_similarity_matrix()
similarity_matrix_exp = np.array(ch_matrix_jaccard_sim >= 0.8, dtype=np.float32)
sketch_matrix = SketchMatrix(25, 265, ch_matrix)
similarity_matrix = similar_nodes_mining.get_node_similarity_matrix(sketch_matrix)
equality = (similarity_matrix_exp == similarity_matrix).all()
self.assertTrue(equality, "The computed similarity matrix is wrong (Keep in mind that the sketch_matrix is probabilistic, therefore, it may not be always correct. The test may pass in another run.).")
def testSimilarNodesMining(self):
dummy_hypergraph = Hypergraph(example_graphs.snm_dummy_graph)
rballs_database, _ = similar_nodes_mining.extract_rballs_database(
dummy_hypergraph, r_in=3, r_out=2, r_all=0)
nodes_count = dummy_hypergraph.number_of_nodes()
ch_matrix = CharacteristicMatrix(rballs_database,
nodes_count,
wl_iterations=0)
ch_matrix_jaccard_sim = ch_matrix.compute_jaccard_similarity_matrix()
similarity_matrix_exp = np.array(ch_matrix_jaccard_sim >= 0.8,
dtype=np.float32)
sketch_matrix = SketchMatrix(25, 265, ch_matrix)
similarity_matrix = similar_nodes_mining.get_node_similarity_matrix(
sketch_matrix)
equality = (similarity_matrix_exp == similarity_matrix).all()
self.assertTrue(
equality,
"The computed similarity matrix is wrong (Keep in mind that the sketch_matrix is probabilistic, therefore, it may not be always correct. The test may pass in another run.)."
)
print "Reading Column index to Node map took", time.time() - start, "s"
print "-----------------------------------------"
return sketch_matrix, index_node_map, node_id_map
if __name__ == '__main__':
ch_matrix, hypergraph, index_node_map, node_id_map = calculate_ch_matrix()
# ch_matrix, hypergraph, index_node_map, node_id_map = load_ch_matrix()
sketch_matrix = calculate_sketch_matrix(ch_matrix, hypergraph)
# sketch_matrix, index_node_map, node_id_map = load_sketch_matrix()
print "Building similarity matrix started at", time.strftime(time_format)
start = time.time()
sim_mat = similar_nodes_mining.get_node_similarity_matrix(sketch_matrix)
print "Building similarity matrix took", time.time() - start, "s"
print "-----------------------------------------"
print "Extracting similar nodes started at", time.strftime(time_format)
start = time.time()
similar_nodes = similar_nodes_mining.get_all_similar_nodes(
sim_mat, index_node_map)
print "Extracting similar nodes took", time.time() - start, "s"
print "-----------------------------------------"
print "Saving similar nodes started at", time.strftime(time_format)
start = time.time()
inout.save_to_file(similar_nodes,
path + "{0}_similar_nodes".format(dataset))
print "Saving similar nodes took", time.time() - start, "s"
index_node_map = inout.load_from_file(path + "{0}_index_node_map".format(dataset))
print "Reading Column index to Node map took", time.time() - start, "s"
print "-----------------------------------------"
return sketch_matrix, index_node_map, node_id_map
if __name__ == '__main__':
ch_matrix, hypergraph, index_node_map, node_id_map = calculate_ch_matrix()
# ch_matrix, hypergraph, index_node_map, node_id_map = load_ch_matrix()
sketch_matrix = calculate_sketch_matrix(ch_matrix, hypergraph)
# sketch_matrix, index_node_map, node_id_map = load_sketch_matrix()
print "Building similarity matrix started at", time.strftime(time_format)
start = time.time()
sim_mat = similar_nodes_mining.get_node_similarity_matrix(sketch_matrix)
print "Building similarity matrix took", time.time() - start, "s"
print "-----------------------------------------"
print "Extracting similar nodes started at", time.strftime(time_format)
start = time.time()
similar_nodes = similar_nodes_mining.get_all_similar_nodes(sim_mat, index_node_map)
print "Extracting similar nodes took", time.time() - start, "s"
print "-----------------------------------------"
print "Saving similar nodes started at", time.strftime(time_format)
start = time.time()
inout.save_to_file(similar_nodes, path + "{0}_similar_nodes".format(dataset))
print "Saving similar nodes took", time.time() - start, "s"
print "-----------------------------------------"
