Mercurial > repos > shellac > sam_consensus_v3
annotate env/lib/python3.9/site-packages/networkx/algorithms/bipartite/tests/test_matrix.py @ 0:4f3585e2f14b draft default tip
"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
author | shellac |
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date | Mon, 22 Mar 2021 18:12:50 +0000 |
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1 import pytest |
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2 |
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3 np = pytest.importorskip("numpy") |
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4 sp = pytest.importorskip("scipy") |
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5 sparse = pytest.importorskip("scipy.sparse") |
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6 |
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7 |
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8 import networkx as nx |
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9 from networkx.algorithms import bipartite |
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10 from networkx.testing.utils import assert_edges_equal |
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11 |
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12 |
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13 class TestBiadjacencyMatrix: |
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14 def test_biadjacency_matrix_weight(self): |
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15 G = nx.path_graph(5) |
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16 G.add_edge(0, 1, weight=2, other=4) |
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17 X = [1, 3] |
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18 Y = [0, 2, 4] |
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19 M = bipartite.biadjacency_matrix(G, X, weight="weight") |
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20 assert M[0, 0] == 2 |
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21 M = bipartite.biadjacency_matrix(G, X, weight="other") |
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22 assert M[0, 0] == 4 |
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23 |
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24 def test_biadjacency_matrix(self): |
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25 tops = [2, 5, 10] |
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26 bots = [5, 10, 15] |
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27 for i in range(len(tops)): |
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28 G = bipartite.random_graph(tops[i], bots[i], 0.2) |
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29 top = [n for n, d in G.nodes(data=True) if d["bipartite"] == 0] |
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30 M = bipartite.biadjacency_matrix(G, top) |
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31 assert M.shape[0] == tops[i] |
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32 assert M.shape[1] == bots[i] |
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33 |
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34 def test_biadjacency_matrix_order(self): |
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35 G = nx.path_graph(5) |
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36 G.add_edge(0, 1, weight=2) |
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37 X = [3, 1] |
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38 Y = [4, 2, 0] |
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39 M = bipartite.biadjacency_matrix(G, X, Y, weight="weight") |
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40 assert M[1, 2] == 2 |
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41 |
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42 def test_null_graph(self): |
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43 with pytest.raises(nx.NetworkXError): |
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44 bipartite.biadjacency_matrix(nx.Graph(), []) |
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45 |
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46 def test_empty_graph(self): |
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47 with pytest.raises(nx.NetworkXError): |
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48 bipartite.biadjacency_matrix(nx.Graph([(1, 0)]), []) |
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49 |
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50 def test_duplicate_row(self): |
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51 with pytest.raises(nx.NetworkXError): |
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52 bipartite.biadjacency_matrix(nx.Graph([(1, 0)]), [1, 1]) |
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53 |
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54 def test_duplicate_col(self): |
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55 with pytest.raises(nx.NetworkXError): |
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56 bipartite.biadjacency_matrix(nx.Graph([(1, 0)]), [0], [1, 1]) |
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57 |
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58 def test_format_keyword(self): |
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59 with pytest.raises(nx.NetworkXError): |
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60 bipartite.biadjacency_matrix(nx.Graph([(1, 0)]), [0], format="foo") |
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61 |
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62 def test_from_biadjacency_roundtrip(self): |
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63 B1 = nx.path_graph(5) |
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64 M = bipartite.biadjacency_matrix(B1, [0, 2, 4]) |
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65 B2 = bipartite.from_biadjacency_matrix(M) |
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66 assert nx.is_isomorphic(B1, B2) |
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67 |
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68 def test_from_biadjacency_weight(self): |
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69 M = sparse.csc_matrix([[1, 2], [0, 3]]) |
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70 B = bipartite.from_biadjacency_matrix(M) |
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71 assert_edges_equal(B.edges(), [(0, 2), (0, 3), (1, 3)]) |
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72 B = bipartite.from_biadjacency_matrix(M, edge_attribute="weight") |
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73 e = [(0, 2, {"weight": 1}), (0, 3, {"weight": 2}), (1, 3, {"weight": 3})] |
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74 assert_edges_equal(B.edges(data=True), e) |
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75 |
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76 def test_from_biadjacency_multigraph(self): |
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77 M = sparse.csc_matrix([[1, 2], [0, 3]]) |
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78 B = bipartite.from_biadjacency_matrix(M, create_using=nx.MultiGraph()) |
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79 assert_edges_equal(B.edges(), [(0, 2), (0, 3), (0, 3), (1, 3), (1, 3), (1, 3)]) |