import time from nose.tools import * from networkx.generators.joint_degree_seq import is_valid_joint_degree, joint_degree_graph from networkx.algorithms.assortativity import degree_mixing_dict from networkx.generators import powerlaw_cluster_graph def test_is_valid_joint_degree(): ''' Tests for conditions that invalidate a joint degree dict ''' # valid joint degree that satisfies all five conditions joint_degrees = {1: {4: 1}, 2: {2: 2, 3: 2, 4: 2}, 3: {2: 2, 4: 1}, 4: {1: 1, 2: 2, 3: 1}} assert_true(is_valid_joint_degree(joint_degrees)) # test condition 1 # joint_degrees_1[1][4] not integer joint_degrees_1 = {1: {4: 1.5}, 2: {2: 2, 3: 2, 4: 2}, 3: {2: 2, 4: 1}, 4: {1: 1.5, 2: 2, 3: 1}} assert_false(is_valid_joint_degree(joint_degrees_1)) # test condition 2 # degree_count[2] = sum(joint_degrees_2[2][j)/2, is not an int # degree_count[4] = sum(joint_degrees_2[4][j)/4, is not an int joint_degrees_2 = {1: {4: 1}, 2: {2: 2, 3: 2, 4: 3}, 3: {2: 2, 4: 1}, 4: {1: 1, 2: 3, 3: 1}} assert_false(is_valid_joint_degree(joint_degrees_2)) # test conditions 3 and 4 # joint_degrees_3[1][4]>degree_count[1]*degree_count[4] joint_degrees_3 = {1: {4: 2}, 2: {2: 2, 3: 2, 4: 2}, 3: {2: 2, 4: 1}, 4: {1: 2, 2: 2, 3: 1}} assert_false(is_valid_joint_degree(joint_degrees_3)) # test condition 5 # joint_degrees_5[1][1] not even joint_degrees_5 = {1: {1: 9}} assert_false(is_valid_joint_degree(joint_degrees_5)) def test_joint_degree_graph(ntimes=100): for _ in range(ntimes): seed = time.time() n, m, p = 20, 10, 1 # generate random graph with model powerlaw_cluster and calculate # its joint degree g = powerlaw_cluster_graph(n, m, p, seed=seed) joint_degrees_g = degree_mixing_dict(g, normalized=False) # generate simple undirected graph with given joint degree # joint_degrees_g G = joint_degree_graph(joint_degrees_g) joint_degrees_G = degree_mixing_dict(G, normalized=False) # assert that the given joint degree is equal to the generated # graph's joint degree assert_true(joint_degrees_g == joint_degrees_G)