#!/usr/bin/env python import random import pytest import networkx as nx from networkx.testing.utils import * class TestFunction(object): def setup_method(self): self.G = nx.Graph({0: [1, 2, 3], 1: [1, 2, 0], 4: []}, name='Test') self.Gdegree = {0: 3, 1: 2, 2: 2, 3: 1, 4: 0} self.Gnodes = list(range(5)) self.Gedges = [(0, 1), (0, 2), (0, 3), (1, 0), (1, 1), (1, 2)] self.DG = nx.DiGraph({0: [1, 2, 3], 1: [1, 2, 0], 4: []}) self.DGin_degree = {0: 1, 1: 2, 2: 2, 3: 1, 4: 0} self.DGout_degree = {0: 3, 1: 3, 2: 0, 3: 0, 4: 0} self.DGnodes = list(range(5)) self.DGedges = [(0, 1), (0, 2), (0, 3), (1, 0), (1, 1), (1, 2)] def test_nodes(self): assert_nodes_equal(self.G.nodes(), list(nx.nodes(self.G))) assert_nodes_equal(self.DG.nodes(), list(nx.nodes(self.DG))) def test_edges(self): assert_edges_equal(self.G.edges(), list(nx.edges(self.G))) assert sorted(self.DG.edges()) == sorted(nx.edges(self.DG)) assert_edges_equal(self.G.edges(nbunch=[0, 1, 3]), list(nx.edges(self.G, nbunch=[0, 1, 3]))) assert (sorted(self.DG.edges(nbunch=[0, 1, 3])) == sorted(nx.edges(self.DG, nbunch=[0, 1, 3]))) def test_degree(self): assert_edges_equal(self.G.degree(), list(nx.degree(self.G))) assert sorted(self.DG.degree()) == sorted(nx.degree(self.DG)) assert_edges_equal(self.G.degree(nbunch=[0, 1]), list(nx.degree(self.G, nbunch=[0, 1]))) assert (sorted(self.DG.degree(nbunch=[0, 1])) == sorted(nx.degree(self.DG, nbunch=[0, 1]))) assert_edges_equal(self.G.degree(weight='weight'), list(nx.degree(self.G, weight='weight'))) assert (sorted(self.DG.degree(weight='weight')) == sorted(nx.degree(self.DG, weight='weight'))) def test_neighbors(self): assert list(self.G.neighbors(1)) == list(nx.neighbors(self.G, 1)) assert list(self.DG.neighbors(1)) == list(nx.neighbors(self.DG, 1)) def test_number_of_nodes(self): assert self.G.number_of_nodes() == nx.number_of_nodes(self.G) assert self.DG.number_of_nodes() == nx.number_of_nodes(self.DG) def test_number_of_edges(self): assert self.G.number_of_edges() == nx.number_of_edges(self.G) assert self.DG.number_of_edges() == nx.number_of_edges(self.DG) def test_is_directed(self): assert self.G.is_directed() == nx.is_directed(self.G) assert self.DG.is_directed() == nx.is_directed(self.DG) def test_add_star(self): G = self.G.copy() nlist = [12, 13, 14, 15] nx.add_star(G, nlist) assert_edges_equal(G.edges(nlist), [(12, 13), (12, 14), (12, 15)]) G = self.G.copy() nx.add_star(G, nlist, weight=2.0) assert_edges_equal(G.edges(nlist, data=True), [(12, 13, {'weight': 2.}), (12, 14, {'weight': 2.}), (12, 15, {'weight': 2.})]) G = self.G.copy() nlist = [12] nx.add_star(G, nlist) assert_nodes_equal(G, list(self.G) + nlist) G = self.G.copy() nlist = [] nx.add_star(G, nlist) assert_nodes_equal(G.nodes, self.Gnodes) assert_edges_equal(G.edges, self.G.edges) def test_add_path(self): G = self.G.copy() nlist = [12, 13, 14, 15] nx.add_path(G, nlist) assert_edges_equal(G.edges(nlist), [(12, 13), (13, 14), (14, 15)]) G = self.G.copy() nx.add_path(G, nlist, weight=2.0) assert_edges_equal(G.edges(nlist, data=True), [(12, 13, {'weight': 2.}), (13, 14, {'weight': 2.}), (14, 15, {'weight': 2.})]) G = self.G.copy() nlist = [None] nx.add_path(G, nlist) assert_edges_equal(G.edges(nlist), []) assert_nodes_equal(G, list(self.G) + [None]) G = self.G.copy() nlist = iter([None]) nx.add_path(G, nlist) assert_edges_equal(G.edges([None]), []) assert_nodes_equal(G, list(self.G) + [None]) G = self.G.copy() nlist = [12] nx.add_path(G, nlist) assert_edges_equal(G.edges(nlist), []) assert_nodes_equal(G, list(self.G) + [12]) G = self.G.copy() nlist = iter([12]) nx.add_path(G, nlist) assert_edges_equal(G.edges([12]), []) assert_nodes_equal(G, list(self.G) + [12]) G = self.G.copy() nlist = [] nx.add_path(G, nlist) assert_edges_equal(G.edges, self.G.edges) assert_nodes_equal(G, list(self.G)) G = self.G.copy() nlist = iter([]) nx.add_path(G, nlist) assert_edges_equal(G.edges, self.G.edges) assert_nodes_equal(G, list(self.G)) def test_add_cycle(self): G = self.G.copy() nlist = [12, 13, 14, 15] oklists = [[(12, 13), (12, 15), (13, 14), (14, 15)], [(12, 13), (13, 14), (14, 15), (15, 12)]] nx.add_cycle(G, nlist) assert sorted(G.edges(nlist)) in oklists G = self.G.copy() oklists = [[(12, 13, {'weight': 1.}), (12, 15, {'weight': 1.}), (13, 14, {'weight': 1.}), (14, 15, {'weight': 1.})], [(12, 13, {'weight': 1.}), (13, 14, {'weight': 1.}), (14, 15, {'weight': 1.}), (15, 12, {'weight': 1.})]] nx.add_cycle(G, nlist, weight=1.0) assert sorted(G.edges(nlist, data=True)) in oklists G = self.G.copy() nlist = [12] nx.add_cycle(G, nlist) assert_nodes_equal(G, list(self.G) + nlist) G = self.G.copy() nlist = [] nx.add_cycle(G, nlist) assert_nodes_equal(G.nodes, self.Gnodes) assert_edges_equal(G.edges, self.G.edges) def test_subgraph(self): assert (self.G.subgraph([0, 1, 2, 4]).adj == nx.subgraph(self.G, [0, 1, 2, 4]).adj) assert (self.DG.subgraph([0, 1, 2, 4]).adj == nx.subgraph(self.DG, [0, 1, 2, 4]).adj) assert (self.G.subgraph([0, 1, 2, 4]).adj == nx.induced_subgraph(self.G, [0, 1, 2, 4]).adj) assert (self.DG.subgraph([0, 1, 2, 4]).adj == nx.induced_subgraph(self.DG, [0, 1, 2, 4]).adj) # subgraph-subgraph chain is allowed in function interface H = nx.induced_subgraph(self.G.subgraph([0, 1, 2, 4]), [0, 1, 4]) assert H._graph is not self.G assert H.adj == self.G.subgraph([0, 1, 4]).adj def test_edge_subgraph(self): assert (self.G.edge_subgraph([(1, 2), (0, 3)]).adj == nx.edge_subgraph(self.G, [(1, 2), (0, 3)]).adj) assert (self.DG.edge_subgraph([(1, 2), (0, 3)]).adj == nx.edge_subgraph(self.DG, [(1, 2), (0, 3)]).adj) def test_restricted_view(self): H = nx.restricted_view(self.G, [0, 2, 5], [(1, 2), (3, 4)]) assert set(H.nodes) == {1, 3, 4} assert set(H.edges) == {(1, 1)} def test_create_empty_copy(self): G = nx.create_empty_copy(self.G, with_data=False) assert_nodes_equal(G, list(self.G)) assert G.graph == {} assert G._node == {}.fromkeys(self.G.nodes(), {}) assert G._adj == {}.fromkeys(self.G.nodes(), {}) G = nx.create_empty_copy(self.G) assert_nodes_equal(G, list(self.G)) assert G.graph == self.G.graph assert G._node == self.G._node assert G._adj == {}.fromkeys(self.G.nodes(), {}) def test_degree_histogram(self): assert nx.degree_histogram(self.G) == [1, 1, 1, 1, 1] def test_density(self): assert nx.density(self.G) == 0.5 assert nx.density(self.DG) == 0.3 G = nx.Graph() G.add_node(1) assert nx.density(G) == 0.0 def test_density_selfloop(self): G = nx.Graph() G.add_edge(1, 1) assert nx.density(G) == 0.0 G.add_edge(1, 2) assert nx.density(G) == 2.0 def test_freeze(self): G = nx.freeze(self.G) assert G.frozen == True pytest.raises(nx.NetworkXError, G.add_node, 1) pytest.raises(nx.NetworkXError, G.add_nodes_from, [1]) pytest.raises(nx.NetworkXError, G.remove_node, 1) pytest.raises(nx.NetworkXError, G.remove_nodes_from, [1]) pytest.raises(nx.NetworkXError, G.add_edge, 1, 2) pytest.raises(nx.NetworkXError, G.add_edges_from, [(1, 2)]) pytest.raises(nx.NetworkXError, G.remove_edge, 1, 2) pytest.raises(nx.NetworkXError, G.remove_edges_from, [(1, 2)]) pytest.raises(nx.NetworkXError, G.clear) def test_is_frozen(self): assert nx.is_frozen(self.G) == False G = nx.freeze(self.G) assert G.frozen == nx.is_frozen(self.G) assert G.frozen == True def test_info(self): G = nx.path_graph(5) G.name = "path_graph(5)" info = nx.info(G) expected_graph_info = '\n'.join(['Name: path_graph(5)', 'Type: Graph', 'Number of nodes: 5', 'Number of edges: 4', 'Average degree: 1.6000']) assert info == expected_graph_info info = nx.info(G, n=1) expected_node_info = '\n'.join( ['Node 1 has the following properties:', 'Degree: 2', 'Neighbors: 0 2']) assert info == expected_node_info def test_info_digraph(self): G = nx.DiGraph(name='path_graph(5)') nx.add_path(G, [0, 1, 2, 3, 4]) info = nx.info(G) expected_graph_info = '\n'.join(['Name: path_graph(5)', 'Type: DiGraph', 'Number of nodes: 5', 'Number of edges: 4', 'Average in degree: 0.8000', 'Average out degree: 0.8000']) assert info == expected_graph_info info = nx.info(G, n=1) expected_node_info = '\n'.join( ['Node 1 has the following properties:', 'Degree: 2', 'Neighbors: 2']) assert info == expected_node_info pytest.raises(nx.NetworkXError, nx.info, G, n=-1) def test_neighbors_complete_graph(self): graph = nx.complete_graph(100) pop = random.sample(list(graph), 1) nbors = list(nx.neighbors(graph, pop[0])) # should be all the other vertices in the graph assert len(nbors) == len(graph) - 1 graph = nx.path_graph(100) node = random.sample(list(graph), 1)[0] nbors = list(nx.neighbors(graph, node)) # should be all the other vertices in the graph if node != 0 and node != 99: assert len(nbors) == 2 else: assert len(nbors) == 1 # create a star graph with 99 outer nodes graph = nx.star_graph(99) nbors = list(nx.neighbors(graph, 0)) assert len(nbors) == 99 def test_non_neighbors(self): graph = nx.complete_graph(100) pop = random.sample(list(graph), 1) nbors = list(nx.non_neighbors(graph, pop[0])) # should be all the other vertices in the graph assert len(nbors) == 0 graph = nx.path_graph(100) node = random.sample(list(graph), 1)[0] nbors = list(nx.non_neighbors(graph, node)) # should be all the other vertices in the graph if node != 0 and node != 99: assert len(nbors) == 97 else: assert len(nbors) == 98 # create a star graph with 99 outer nodes graph = nx.star_graph(99) nbors = list(nx.non_neighbors(graph, 0)) assert len(nbors) == 0 # disconnected graph graph = nx.Graph() graph.add_nodes_from(range(10)) nbors = list(nx.non_neighbors(graph, 0)) assert len(nbors) == 9 def test_non_edges(self): # All possible edges exist graph = nx.complete_graph(5) nedges = list(nx.non_edges(graph)) assert len(nedges) == 0 graph = nx.path_graph(4) expected = [(0, 2), (0, 3), (1, 3)] nedges = list(nx.non_edges(graph)) for (u, v) in expected: assert (u, v) in nedges or (v, u) in nedges graph = nx.star_graph(4) expected = [(1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)] nedges = list(nx.non_edges(graph)) for (u, v) in expected: assert (u, v) in nedges or (v, u) in nedges # Directed graphs graph = nx.DiGraph() graph.add_edges_from([(0, 2), (2, 0), (2, 1)]) expected = [(0, 1), (1, 0), (1, 2)] nedges = list(nx.non_edges(graph)) for e in expected: assert e in nedges def test_is_weighted(self): G = nx.Graph() assert not nx.is_weighted(G) G = nx.path_graph(4) assert not nx.is_weighted(G) assert not nx.is_weighted(G, (2, 3)) G.add_node(4) G.add_edge(3, 4, weight=4) assert not nx.is_weighted(G) assert nx.is_weighted(G, (3, 4)) G = nx.DiGraph() G.add_weighted_edges_from([('0', '3', 3), ('0', '1', -5), ('1', '0', -5), ('0', '2', 2), ('1', '2', 4), ('2', '3', 1)]) assert nx.is_weighted(G) assert nx.is_weighted(G, ('1', '0')) G = G.to_undirected() assert nx.is_weighted(G) assert nx.is_weighted(G, ('1', '0')) pytest.raises(nx.NetworkXError, nx.is_weighted, G, (1, 2)) def test_is_negatively_weighted(self): G = nx.Graph() assert not nx.is_negatively_weighted(G) G.add_node(1) G.add_nodes_from([2, 3, 4, 5]) assert not nx.is_negatively_weighted(G) G.add_edge(1, 2, weight=4) assert not nx.is_negatively_weighted(G, (1, 2)) G.add_edges_from([(1, 3), (2, 4), (2, 6)]) G[1][3]['color'] = 'blue' assert not nx.is_negatively_weighted(G) assert not nx.is_negatively_weighted(G, (1, 3)) G[2][4]['weight'] = -2 assert nx.is_negatively_weighted(G, (2, 4)) assert nx.is_negatively_weighted(G) G = nx.DiGraph() G.add_weighted_edges_from([('0', '3', 3), ('0', '1', -5), ('1', '0', -2), ('0', '2', 2), ('1', '2', -3), ('2', '3', 1)]) assert nx.is_negatively_weighted(G) assert not nx.is_negatively_weighted(G, ('0', '3')) assert nx.is_negatively_weighted(G, ('1', '0')) pytest.raises(nx.NetworkXError, nx.is_negatively_weighted, G, (1, 4)) class TestCommonNeighbors(): @classmethod def setup_class(cls): cls.func = staticmethod(nx.common_neighbors) def test_func(G, u, v, expected): result = sorted(cls.func(G, u, v)) assert result == expected cls.test = staticmethod(test_func) def test_K5(self): G = nx.complete_graph(5) self.test(G, 0, 1, [2, 3, 4]) def test_P3(self): G = nx.path_graph(3) self.test(G, 0, 2, [1]) def test_S4(self): G = nx.star_graph(4) self.test(G, 1, 2, [0]) def test_digraph(self): with pytest.raises(nx.NetworkXNotImplemented): G = nx.DiGraph() G.add_edges_from([(0, 1), (1, 2)]) self.func(G, 0, 2) def test_nonexistent_nodes(self): G = nx.complete_graph(5) pytest.raises(nx.NetworkXError, nx.common_neighbors, G, 5, 4) pytest.raises(nx.NetworkXError, nx.common_neighbors, G, 4, 5) pytest.raises(nx.NetworkXError, nx.common_neighbors, G, 5, 6) def test_custom1(self): """Case of no common neighbors.""" G = nx.Graph() G.add_nodes_from([0, 1]) self.test(G, 0, 1, []) def test_custom2(self): """Case of equal nodes.""" G = nx.complete_graph(4) self.test(G, 0, 0, [1, 2, 3]) def test_set_node_attributes(): graphs = [nx.Graph(), nx.DiGraph(), nx.MultiGraph(), nx.MultiDiGraph()] for G in graphs: # Test single value G = nx.path_graph(3, create_using=G) vals = 100 attr = 'hello' nx.set_node_attributes(G, vals, attr) assert G.nodes[0][attr] == vals assert G.nodes[1][attr] == vals assert G.nodes[2][attr] == vals # Test dictionary G = nx.path_graph(3, create_using=G) vals = dict(zip(sorted(G.nodes()), range(len(G)))) attr = 'hi' nx.set_node_attributes(G, vals, attr) assert G.nodes[0][attr] == 0 assert G.nodes[1][attr] == 1 assert G.nodes[2][attr] == 2 # Test dictionary of dictionaries G = nx.path_graph(3, create_using=G) d = {'hi': 0, 'hello': 200} vals = dict.fromkeys(G.nodes(), d) vals.pop(0) nx.set_node_attributes(G, vals) assert G.nodes[0] == {} assert G.nodes[1]["hi"] == 0 assert G.nodes[2]["hello"] == 200 def test_set_edge_attributes(): graphs = [nx.Graph(), nx.DiGraph()] for G in graphs: # Test single value G = nx.path_graph(3, create_using=G) attr = 'hello' vals = 3 nx.set_edge_attributes(G, vals, attr) assert G[0][1][attr] == vals assert G[1][2][attr] == vals # Test multiple values G = nx.path_graph(3, create_using=G) attr = 'hi' edges = [(0, 1), (1, 2)] vals = dict(zip(edges, range(len(edges)))) nx.set_edge_attributes(G, vals, attr) assert G[0][1][attr] == 0 assert G[1][2][attr] == 1 # Test dictionary of dictionaries G = nx.path_graph(3, create_using=G) d = {'hi': 0, 'hello': 200} edges = [(0, 1)] vals = dict.fromkeys(edges, d) nx.set_edge_attributes(G, vals) assert G[0][1]['hi'] == 0 assert G[0][1]['hello'] == 200 assert G[1][2] == {} def test_set_edge_attributes_multi(): graphs = [nx.MultiGraph(), nx.MultiDiGraph()] for G in graphs: # Test single value G = nx.path_graph(3, create_using=G) attr = 'hello' vals = 3 nx.set_edge_attributes(G, vals, attr) assert G[0][1][0][attr] == vals assert G[1][2][0][attr] == vals # Test multiple values G = nx.path_graph(3, create_using=G) attr = 'hi' edges = [(0, 1, 0), (1, 2, 0)] vals = dict(zip(edges, range(len(edges)))) nx.set_edge_attributes(G, vals, attr) assert G[0][1][0][attr] == 0 assert G[1][2][0][attr] == 1 # Test dictionary of dictionaries G = nx.path_graph(3, create_using=G) d = {'hi': 0, 'hello': 200} edges = [(0, 1, 0)] vals = dict.fromkeys(edges, d) nx.set_edge_attributes(G, vals) assert G[0][1][0]['hi'] == 0 assert G[0][1][0]['hello'] == 200 assert G[1][2][0] == {} def test_get_node_attributes(): graphs = [nx.Graph(), nx.DiGraph(), nx.MultiGraph(), nx.MultiDiGraph()] for G in graphs: G = nx.path_graph(3, create_using=G) attr = 'hello' vals = 100 nx.set_node_attributes(G, vals, attr) attrs = nx.get_node_attributes(G, attr) assert attrs[0] == vals assert attrs[1] == vals assert attrs[2] == vals def test_get_edge_attributes(): graphs = [nx.Graph(), nx.DiGraph(), nx.MultiGraph(), nx.MultiDiGraph()] for G in graphs: G = nx.path_graph(3, create_using=G) attr = 'hello' vals = 100 nx.set_edge_attributes(G, vals, attr) attrs = nx.get_edge_attributes(G, attr) assert len(attrs) == 2 if G.is_multigraph(): keys = [(0, 1, 0), (1, 2, 0)] for u, v, k in keys: try: assert attrs[(u, v, k)] == 100 except KeyError: assert attrs[(v, u, k)] == 100 else: keys = [(0, 1), (1, 2)] for u, v in keys: try: assert attrs[(u, v)] == 100 except KeyError: assert attrs[(v, u)] == 100 def test_is_empty(): graphs = [nx.Graph(), nx.DiGraph(), nx.MultiGraph(), nx.MultiDiGraph()] for G in graphs: assert nx.is_empty(G) G.add_nodes_from(range(5)) assert nx.is_empty(G) G.add_edges_from([(1, 2), (3, 4)]) assert not nx.is_empty(G) def test_selfloops(): graphs = [nx.Graph(), nx.DiGraph(), nx.MultiGraph(), nx.MultiDiGraph()] for graph in graphs: G = nx.complete_graph(3, create_using=graph) G.add_edge(0, 0) assert_nodes_equal(nx.nodes_with_selfloops(G), [0]) assert_edges_equal(nx.selfloop_edges(G), [(0, 0)]) assert_edges_equal(nx.selfloop_edges(G, data=True), [(0, 0, {})]) assert nx.number_of_selfloops(G) == 1 # test selfloop attr G.add_edge(1, 1, weight=2) assert_edges_equal(nx.selfloop_edges(G, data=True), [(0, 0, {}), (1, 1, {'weight': 2})]) assert_edges_equal(nx.selfloop_edges(G, data='weight'), [(0, 0, None), (1, 1, 2)])