#!/usr/bin/env python from nose.tools import * import networkx as nx class TestTriangles: def test_empty(self): G = nx.Graph() assert_equal(list(nx.triangles(G).values()), []) def test_path(self): G = nx.path_graph(10) assert_equal(list(nx.triangles(G).values()), [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]) assert_equal(nx.triangles(G), {0: 0, 1: 0, 2: 0, 3: 0, 4: 0, 5: 0, 6: 0, 7: 0, 8: 0, 9: 0}) def test_cubical(self): G = nx.cubical_graph() assert_equal(list(nx.triangles(G).values()), [0, 0, 0, 0, 0, 0, 0, 0]) assert_equal(nx.triangles(G, 1), 0) assert_equal(list(nx.triangles(G, [1, 2]).values()), [0, 0]) assert_equal(nx.triangles(G, 1), 0) assert_equal(nx.triangles(G, [1, 2]), {1: 0, 2: 0}) def test_k5(self): G = nx.complete_graph(5) assert_equal(list(nx.triangles(G).values()), [6, 6, 6, 6, 6]) assert_equal(sum(nx.triangles(G).values()) / 3.0, 10) assert_equal(nx.triangles(G, 1), 6) G.remove_edge(1, 2) assert_equal(list(nx.triangles(G).values()), [5, 3, 3, 5, 5]) assert_equal(nx.triangles(G, 1), 3) class TestWeightedClustering: def test_clustering(self): G = nx.Graph() assert_equal(list(nx.clustering(G, weight='weight').values()), []) assert_equal(nx.clustering(G), {}) def test_path(self): G = nx.path_graph(10) assert_equal(list(nx.clustering(G, weight='weight').values()), [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]) assert_equal(nx.clustering(G, weight='weight'), {0: 0.0, 1: 0.0, 2: 0.0, 3: 0.0, 4: 0.0, 5: 0.0, 6: 0.0, 7: 0.0, 8: 0.0, 9: 0.0}) def test_cubical(self): G = nx.cubical_graph() assert_equal(list(nx.clustering(G, weight='weight').values()), [0, 0, 0, 0, 0, 0, 0, 0]) assert_equal(nx.clustering(G, 1), 0) assert_equal(list(nx.clustering(G, [1, 2], weight='weight').values()), [0, 0]) assert_equal(nx.clustering(G, 1, weight='weight'), 0) assert_equal(nx.clustering(G, [1, 2], weight='weight'), {1: 0, 2: 0}) def test_k5(self): G = nx.complete_graph(5) assert_equal(list(nx.clustering(G, weight='weight').values()), [1, 1, 1, 1, 1]) assert_equal(nx.average_clustering(G, weight='weight'), 1) G.remove_edge(1, 2) assert_equal(list(nx.clustering(G, weight='weight').values()), [5. / 6., 1.0, 1.0, 5. / 6., 5. / 6.]) assert_equal(nx.clustering(G, [1, 4], weight='weight'), {1: 1.0, 4: 0.83333333333333337}) def test_triangle_and_edge(self): G = nx.cycle_graph(3) G.add_edge(0, 4, weight=2) assert_equal(nx.clustering(G)[0], 1.0 / 3.0) assert_equal(nx.clustering(G, weight='weight')[0], 1.0 / 6.0) class TestClustering: def test_clustering(self): G = nx.Graph() assert_equal(list(nx.clustering(G).values()), []) assert_equal(nx.clustering(G), {}) def test_path(self): G = nx.path_graph(10) assert_equal(list(nx.clustering(G).values()), [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]) assert_equal(nx.clustering(G), {0: 0.0, 1: 0.0, 2: 0.0, 3: 0.0, 4: 0.0, 5: 0.0, 6: 0.0, 7: 0.0, 8: 0.0, 9: 0.0}) def test_cubical(self): G = nx.cubical_graph() assert_equal(list(nx.clustering(G).values()), [0, 0, 0, 0, 0, 0, 0, 0]) assert_equal(nx.clustering(G, 1), 0) assert_equal(list(nx.clustering(G, [1, 2]).values()), [0, 0]) assert_equal(nx.clustering(G, 1), 0) assert_equal(nx.clustering(G, [1, 2]), {1: 0, 2: 0}) def test_k5(self): G = nx.complete_graph(5) assert_equal(list(nx.clustering(G).values()), [1, 1, 1, 1, 1]) assert_equal(nx.average_clustering(G), 1) G.remove_edge(1, 2) assert_equal(list(nx.clustering(G).values()), [5. / 6., 1.0, 1.0, 5. / 6., 5. / 6.]) assert_equal(nx.clustering(G, [1, 4]), {1: 1.0, 4: 0.83333333333333337}) class TestTransitivity: def test_transitivity(self): G = nx.Graph() assert_equal(nx.transitivity(G), 0.0) def test_path(self): G = nx.path_graph(10) assert_equal(nx.transitivity(G), 0.0) def test_cubical(self): G = nx.cubical_graph() assert_equal(nx.transitivity(G), 0.0) def test_k5(self): G = nx.complete_graph(5) assert_equal(nx.transitivity(G), 1.0) G.remove_edge(1, 2) assert_equal(nx.transitivity(G), 0.875) # def test_clustering_transitivity(self): # # check that weighted average of clustering is transitivity # G = nx.complete_graph(5) # G.remove_edge(1,2) # t1=nx.transitivity(G) # (cluster_d2,weights)=nx.clustering(G,weights=True) # trans=[] # for v in G.nodes(): # trans.append(cluster_d2[v]*weights[v]) # t2=sum(trans) # assert_almost_equal(abs(t1-t2),0) class TestSquareClustering: def test_clustering(self): G = nx.Graph() assert_equal(list(nx.square_clustering(G).values()), []) assert_equal(nx.square_clustering(G), {}) def test_path(self): G = nx.path_graph(10) assert_equal(list(nx.square_clustering(G).values()), [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]) assert_equal(nx.square_clustering(G), {0: 0.0, 1: 0.0, 2: 0.0, 3: 0.0, 4: 0.0, 5: 0.0, 6: 0.0, 7: 0.0, 8: 0.0, 9: 0.0}) def test_cubical(self): G = nx.cubical_graph() assert_equal(list(nx.square_clustering(G).values()), [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]) assert_equal(list(nx.square_clustering(G, [1, 2]).values()), [0.5, 0.5]) assert_equal(nx.square_clustering(G, [1])[1], 0.5) assert_equal(nx.square_clustering(G, [1, 2]), {1: 0.5, 2: 0.5}) def test_k5(self): G = nx.complete_graph(5) assert_equal(list(nx.square_clustering(G).values()), [1, 1, 1, 1, 1]) def test_bipartite_k5(self): G = nx.complete_bipartite_graph(5, 5) assert_equal(list(nx.square_clustering(G).values()), [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]) def test_lind_square_clustering(self): """Test C4 for figure 1 Lind et al (2005)""" G = nx.Graph([(1, 2), (1, 3), (1, 6), (1, 7), (2, 4), (2, 5), (3, 4), (3, 5), (6, 7), (7, 8), (6, 8), (7, 9), (7, 10), (6, 11), (6, 12), (2, 13), (2, 14), (3, 15), (3, 16)]) G1 = G.subgraph([1, 2, 3, 4, 5, 13, 14, 15, 16]) G2 = G.subgraph([1, 6, 7, 8, 9, 10, 11, 12]) assert_equal(nx.square_clustering(G, [1])[1], 3 / 75.0) assert_equal(nx.square_clustering(G1, [1])[1], 2 / 6.0) assert_equal(nx.square_clustering(G2, [1])[1], 1 / 5.0) def test_average_clustering(): G = nx.cycle_graph(3) G.add_edge(2, 3) assert_equal(nx.average_clustering(G), (1 + 1 + 1 / 3.0) / 4.0) assert_equal(nx.average_clustering(G, count_zeros=True), (1 + 1 + 1 / 3.0) / 4.0) assert_equal(nx.average_clustering(G, count_zeros=False), (1 + 1 + 1 / 3.0) / 3.0) class TestGeneralizedDegree: def test_generalized_degree(self): G = nx.Graph() assert_equal(nx.generalized_degree(G), {}) def test_path(self): G = nx.path_graph(5) assert_equal(nx.generalized_degree(G, 0), {0: 1}) assert_equal(nx.generalized_degree(G, 1), {0: 2}) def test_cubical(self): G = nx.cubical_graph() assert_equal(nx.generalized_degree(G, 0), {0: 3}) def test_k5(self): G = nx.complete_graph(5) assert_equal(nx.generalized_degree(G, 0), {3: 4}) G.remove_edge(0, 1) assert_equal(nx.generalized_degree(G, 0), {2: 3})