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