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author | S. Solomon Darnell | 2025-03-28 21:52:21 -0500 |
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committer | S. Solomon Darnell | 2025-03-28 21:52:21 -0500 |
commit | 4a52a71956a8d46fcb7294ac71734504bb09bcc2 (patch) | |
tree | ee3dc5af3b6313e921cd920906356f5d4febc4ed /.venv/lib/python3.12/site-packages/networkx/generators/tests/test_stochastic.py | |
parent | cc961e04ba734dd72309fb548a2f97d67d578813 (diff) | |
download | gn-ai-master.tar.gz |
Diffstat (limited to '.venv/lib/python3.12/site-packages/networkx/generators/tests/test_stochastic.py')
-rw-r--r-- | .venv/lib/python3.12/site-packages/networkx/generators/tests/test_stochastic.py | 72 |
1 files changed, 72 insertions, 0 deletions
diff --git a/.venv/lib/python3.12/site-packages/networkx/generators/tests/test_stochastic.py b/.venv/lib/python3.12/site-packages/networkx/generators/tests/test_stochastic.py new file mode 100644 index 00000000..0404d9d8 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/networkx/generators/tests/test_stochastic.py @@ -0,0 +1,72 @@ +"""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 = {"weight": 0.25} + assert sorted(S.edges(data=True)) == [ + (0, 1, d), + (0, 1, d), + (0, 2, d), + (0, 2, d), + ] + + def test_zero_weights(self): + """Smoke test: ensure ZeroDivisionError is not raised.""" + G = nx.DiGraph() + G.add_edge(0, 1, weight=0) + G.add_edge(0, 2, weight=0) + S = nx.stochastic_graph(G) + assert sorted(S.edges(data=True)) == [ + (0, 1, {"weight": 0}), + (0, 2, {"weight": 0}), + ] + + 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()) |