62 lines
2.0 KiB
Python
62 lines
2.0 KiB
Python
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# test_stochastic.py - unit tests for the stochastic module
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#
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# Copyright 2010, 2011, 2012, 2013, 2014, 2015 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.generators.stochastic` module."""
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import pytest
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import networkx as nx
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class TestStochasticGraph(object):
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"""Unit tests for the :func:`~networkx.stochastic_graph` function.
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"""
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def test_default_weights(self):
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G = nx.DiGraph()
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G.add_edge(0, 1)
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G.add_edge(0, 2)
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S = nx.stochastic_graph(G)
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assert nx.is_isomorphic(G, S)
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assert (sorted(S.edges(data=True)) ==
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[(0, 1, {'weight': 0.5}), (0, 2, {'weight': 0.5})])
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def test_in_place(self):
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"""Tests for an in-place reweighting of the edges of the graph.
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"""
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G = nx.DiGraph()
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G.add_edge(0, 1, weight=1)
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G.add_edge(0, 2, weight=1)
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nx.stochastic_graph(G, copy=False)
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assert (sorted(G.edges(data=True)) ==
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[(0, 1, {'weight': 0.5}), (0, 2, {'weight': 0.5})])
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def test_arbitrary_weights(self):
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G = nx.DiGraph()
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G.add_edge(0, 1, weight=1)
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G.add_edge(0, 2, weight=1)
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S = nx.stochastic_graph(G)
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assert (sorted(S.edges(data=True)) ==
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[(0, 1, {'weight': 0.5}), (0, 2, {'weight': 0.5})])
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def test_multidigraph(self):
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G = nx.MultiDiGraph()
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G.add_edges_from([(0, 1), (0, 1), (0, 2), (0, 2)])
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S = nx.stochastic_graph(G)
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d = dict(weight=0.25)
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assert (sorted(S.edges(data=True)) ==
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[(0, 1, d), (0, 1, d), (0, 2, d), (0, 2, d)])
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def test_graph_disallowed(self):
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with pytest.raises(nx.NetworkXNotImplemented):
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nx.stochastic_graph(nx.Graph())
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def test_multigraph_disallowed(self):
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with pytest.raises(nx.NetworkXNotImplemented):
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nx.stochastic_graph(nx.MultiGraph())
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