# test_efficiency.py - unit tests for the efficiency module # # Copyright 2015-2019 NetworkX developers. # # This file is part of NetworkX. # # NetworkX is distributed under a BSD license; see LICENSE.txt for more # information. """Unit tests for the :mod:`networkx.algorithms.efficiency` module.""" import networkx as nx class TestEfficiency: def setup_method(self): # G1 is a disconnected graph self.G1 = nx.Graph() self.G1.add_nodes_from([1, 2, 3]) # G2 is a cycle graph self.G2 = nx.cycle_graph(4) # G3 is the triangle graph with one additional edge self.G3 = nx.lollipop_graph(3, 1) def test_efficiency_disconnected_nodes(self): """ When nodes are disconnected, efficiency is 0 """ assert nx.efficiency(self.G1, 1, 2) == 0 def test_local_efficiency_disconnected_graph(self): """ In a disconnected graph the efficiency is 0 """ assert nx.local_efficiency(self.G1) == 0 def test_efficiency(self): assert nx.efficiency(self.G2, 0, 1) == 1 assert nx.efficiency(self.G2, 0, 2) == 1 / 2 def test_global_efficiency(self): assert nx.global_efficiency(self.G2) == 5 / 6 def test_global_efficiency_complete_graph(self): """ Tests that the average global efficiency of the complete graph is one. """ for n in range(2, 10): G = nx.complete_graph(n) assert nx.global_efficiency(G) == 1 def test_local_efficiency_complete_graph(self): """ Test that the local efficiency for a complete graph with at least 3 nodes should be one. For a graph with only 2 nodes, the induced subgraph has no edges. """ for n in range(3, 10): G = nx.complete_graph(n) assert nx.local_efficiency(G) == 1 def test_using_ego_graph(self): """ Test that the ego graph is used when computing local efficiency. For more information, see GitHub issue #2710. """ assert nx.local_efficiency(self.G3) == 7 / 12