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"""Unit tests for the :mod:`networkx.generators.stochastic` module."""
import pytest
import networkx as nx
class TestStochasticGraph:
"""Unit tests for the :func:`~networkx.stochastic_graph` function."""
def test_default_weights(self):
G = nx.DiGraph()
G.add_edge(0, 1)
G.add_edge(0, 2)
S = nx.stochastic_graph(G)
assert nx.is_isomorphic(G, S)
assert sorted(S.edges(data=True)) == [
(0, 1, {"weight": 0.5}),
(0, 2, {"weight": 0.5}),
]
def test_in_place(self):
"""Tests for an in-place reweighting of the edges of the graph."""
G = nx.DiGraph()
G.add_edge(0, 1, weight=1)
G.add_edge(0, 2, weight=1)
nx.stochastic_graph(G, copy=False)
assert sorted(G.edges(data=True)) == [
(0, 1, {"weight": 0.5}),
(0, 2, {"weight": 0.5}),
]
def test_arbitrary_weights(self):
G = nx.DiGraph()
G.add_edge(0, 1, weight=1)
G.add_edge(0, 2, weight=1)
S = nx.stochastic_graph(G)
assert sorted(S.edges(data=True)) == [
(0, 1, {"weight": 0.5}),
(0, 2, {"weight": 0.5}),
]
def test_multidigraph(self):
G = nx.MultiDiGraph()
G.add_edges_from([(0, 1), (0, 1), (0, 2), (0, 2)])
S = nx.stochastic_graph(G)
d = dict(weight=0.25)
assert sorted(S.edges(data=True)) == [
(0, 1, d),
(0, 1, d),
(0, 2, d),
(0, 2, d),
]
def test_graph_disallowed(self):
with pytest.raises(nx.NetworkXNotImplemented):
nx.stochastic_graph(nx.Graph())
def test_multigraph_disallowed(self):
with pytest.raises(nx.NetworkXNotImplemented):
nx.stochastic_graph(nx.MultiGraph())
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