/usr/lib/python2.7/dist-packages/networkx/classes/tests/test_function.py is in python-networkx 1.8.1-0ubuntu3.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 | #!/usr/bin/env python
import random
from nose.tools import *
import networkx
import networkx as nx
class TestFunction(object):
def setUp(self):
self.G=networkx.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=networkx.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_equal(self.G.nodes(),networkx.nodes(self.G))
assert_equal(self.DG.nodes(),networkx.nodes(self.DG))
def test_edges(self):
assert_equal(self.G.edges(),networkx.edges(self.G))
assert_equal(self.DG.edges(),networkx.edges(self.DG))
assert_equal(self.G.edges(nbunch=[0,1,3]),networkx.edges(self.G,nbunch=[0,1,3]))
assert_equal(self.DG.edges(nbunch=[0,1,3]),networkx.edges(self.DG,nbunch=[0,1,3]))
def test_nodes_iter(self):
assert_equal(list(self.G.nodes_iter()),list(networkx.nodes_iter(self.G)))
assert_equal(list(self.DG.nodes_iter()),list(networkx.nodes_iter(self.DG)))
def test_edges_iter(self):
assert_equal(list(self.G.edges_iter()),list(networkx.edges_iter(self.G)))
assert_equal(list(self.DG.edges_iter()),list(networkx.edges_iter(self.DG)))
assert_equal(list(self.G.edges_iter(nbunch=[0,1,3])),list(networkx.edges_iter(self.G,nbunch=[0,1,3])))
assert_equal(list(self.DG.edges_iter(nbunch=[0,1,3])),list(networkx.edges_iter(self.DG,nbunch=[0,1,3])))
def test_degree(self):
assert_equal(self.G.degree(),networkx.degree(self.G))
assert_equal(self.DG.degree(),networkx.degree(self.DG))
assert_equal(self.G.degree(nbunch=[0,1]),networkx.degree(self.G,nbunch=[0,1]))
assert_equal(self.DG.degree(nbunch=[0,1]),networkx.degree(self.DG,nbunch=[0,1]))
assert_equal(self.G.degree(weight='weight'),networkx.degree(self.G,weight='weight'))
assert_equal(self.DG.degree(weight='weight'),networkx.degree(self.DG,weight='weight'))
def test_neighbors(self):
assert_equal(self.G.neighbors(1),networkx.neighbors(self.G,1))
assert_equal(self.DG.neighbors(1),networkx.neighbors(self.DG,1))
def test_number_of_nodes(self):
assert_equal(self.G.number_of_nodes(),networkx.number_of_nodes(self.G))
assert_equal(self.DG.number_of_nodes(),networkx.number_of_nodes(self.DG))
def test_number_of_edges(self):
assert_equal(self.G.number_of_edges(),networkx.number_of_edges(self.G))
assert_equal(self.DG.number_of_edges(),networkx.number_of_edges(self.DG))
def test_is_directed(self):
assert_equal(self.G.is_directed(),networkx.is_directed(self.G))
assert_equal(self.DG.is_directed(),networkx.is_directed(self.DG))
def test_subgraph(self):
assert_equal(self.G.subgraph([0,1,2,4]).adj,networkx.subgraph(self.G,[0,1,2,4]).adj)
assert_equal(self.DG.subgraph([0,1,2,4]).adj,networkx.subgraph(self.DG,[0,1,2,4]).adj)
def test_create_empty_copy(self):
G=networkx.create_empty_copy(self.G, with_nodes=False)
assert_equal(G.nodes(),[])
assert_equal(G.graph,{})
assert_equal(G.node,{})
assert_equal(G.edge,{})
G=networkx.create_empty_copy(self.G)
assert_equal(G.nodes(),self.G.nodes())
assert_equal(G.graph,{})
assert_equal(G.node,{}.fromkeys(self.G.nodes(),{}))
assert_equal(G.edge,{}.fromkeys(self.G.nodes(),{}))
def test_degree_histogram(self):
assert_equal(networkx.degree_histogram(self.G), [1,1,1,1,1])
def test_density(self):
assert_equal(networkx.density(self.G), 0.5)
assert_equal(networkx.density(self.DG), 0.3)
G=networkx.Graph()
G.add_node(1)
assert_equal(networkx.density(G), 0.0)
def test_density_selfloop(self):
G = nx.Graph()
G.add_edge(1,1)
assert_equal(networkx.density(G), 0.0)
G.add_edge(1,2)
assert_equal(networkx.density(G), 2.0)
def test_freeze(self):
G=networkx.freeze(self.G)
assert_equal(G.frozen,True)
assert_raises(networkx.NetworkXError, G.add_node, 1)
assert_raises(networkx.NetworkXError, G.add_nodes_from, [1])
assert_raises(networkx.NetworkXError, G.remove_node, 1)
assert_raises(networkx.NetworkXError, G.remove_nodes_from, [1])
assert_raises(networkx.NetworkXError, G.add_edge, 1,2)
assert_raises(networkx.NetworkXError, G.add_edges_from, [(1,2)])
assert_raises(networkx.NetworkXError, G.remove_edge, 1,2)
assert_raises(networkx.NetworkXError, G.remove_edges_from, [(1,2)])
assert_raises(networkx.NetworkXError, G.clear)
def test_is_frozen(self):
assert_equal(networkx.is_frozen(self.G), False)
G=networkx.freeze(self.G)
assert_equal(G.frozen, networkx.is_frozen(self.G))
assert_equal(G.frozen,True)
def test_info(self):
G=networkx.path_graph(5)
info=networkx.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_equal(info,expected_graph_info)
info=networkx.info(G,n=1)
expected_node_info='\n'.join(
['Node 1 has the following properties:',
'Degree: 2',
'Neighbors: 0 2'])
assert_equal(info,expected_node_info)
def test_info_digraph(self):
G=networkx.DiGraph(name='path_graph(5)')
G.add_path([0,1,2,3,4])
info=networkx.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_equal(info,expected_graph_info)
info=networkx.info(G,n=1)
expected_node_info='\n'.join(
['Node 1 has the following properties:',
'Degree: 2',
'Neighbors: 2'])
assert_equal(info,expected_node_info)
assert_raises(networkx.NetworkXError,networkx.info,G,n=-1)
def test_neighbors(self):
graph = nx.complete_graph(100)
pop = random.sample(graph.nodes(), 1)
nbors = list(nx.neighbors(graph, pop[0]))
# should be all the other vertices in the graph
assert_equal(len(nbors), len(graph) - 1)
graph = nx.path_graph(100)
node = random.sample(graph.nodes(), 1)[0]
nbors = list(nx.neighbors(graph, node))
# should be all the other vertices in the graph
if node != 0 and node != 99:
assert_equal(len(nbors), 2)
else:
assert_equal(len(nbors), 1)
# create a star graph with 99 outer nodes
graph = nx.star_graph(99)
nbors = list(nx.neighbors(graph, 0))
assert_equal(len(nbors), 99)
def test_non_neighbors(self):
graph = nx.complete_graph(100)
pop = random.sample(graph.nodes(), 1)
nbors = list(nx.non_neighbors(graph, pop[0]))
# should be all the other vertices in the graph
assert_equal(len(nbors), 0)
graph = nx.path_graph(100)
node = random.sample(graph.nodes(), 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_equal(len(nbors), 97)
else:
assert_equal(len(nbors), 98)
# create a star graph with 99 outer nodes
graph = nx.star_graph(99)
nbors = list(nx.non_neighbors(graph, 0))
assert_equal(len(nbors), 0)
# disconnected graph
graph = nx.Graph()
graph.add_nodes_from(range(10))
nbors = list(nx.non_neighbors(graph, 0))
assert_equal(len(nbors), 9)
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