two version of R2R are hereHEADmaster

1 files changed, 84 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/networkx/algorithms/bipartite/tests/test_matrix.py b/.venv/lib/python3.12/site-packages/networkx/algorithms/bipartite/tests/test_matrix.py
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+++ b/.venv/lib/python3.12/site-packages/networkx/algorithms/bipartite/tests/test_matrix.py
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+import pytest
+
+np = pytest.importorskip("numpy")
+sp = pytest.importorskip("scipy")
+sparse = pytest.importorskip("scipy.sparse")
+
+
+import networkx as nx
+from networkx.algorithms import bipartite
+from networkx.utils import edges_equal
+
+
+class TestBiadjacencyMatrix:
+    def test_biadjacency_matrix_weight(self):
+        G = nx.path_graph(5)
+        G.add_edge(0, 1, weight=2, other=4)
+        X = [1, 3]
+        Y = [0, 2, 4]
+        M = bipartite.biadjacency_matrix(G, X, weight="weight")
+        assert M[0, 0] == 2
+        M = bipartite.biadjacency_matrix(G, X, weight="other")
+        assert M[0, 0] == 4
+
+    def test_biadjacency_matrix(self):
+        tops = [2, 5, 10]
+        bots = [5, 10, 15]
+        for i in range(len(tops)):
+            G = bipartite.random_graph(tops[i], bots[i], 0.2)
+            top = [n for n, d in G.nodes(data=True) if d["bipartite"] == 0]
+            M = bipartite.biadjacency_matrix(G, top)
+            assert M.shape[0] == tops[i]
+            assert M.shape[1] == bots[i]
+
+    def test_biadjacency_matrix_order(self):
+        G = nx.path_graph(5)
+        G.add_edge(0, 1, weight=2)
+        X = [3, 1]
+        Y = [4, 2, 0]
+        M = bipartite.biadjacency_matrix(G, X, Y, weight="weight")
+        assert M[1, 2] == 2
+
+    def test_biadjacency_matrix_empty_graph(self):
+        G = nx.empty_graph(2)
+        M = nx.bipartite.biadjacency_matrix(G, [0])
+        assert np.array_equal(M.toarray(), np.array([[0]]))
+
+    def test_null_graph(self):
+        with pytest.raises(nx.NetworkXError):
+            bipartite.biadjacency_matrix(nx.Graph(), [])
+
+    def test_empty_graph(self):
+        with pytest.raises(nx.NetworkXError):
+            bipartite.biadjacency_matrix(nx.Graph([(1, 0)]), [])
+
+    def test_duplicate_row(self):
+        with pytest.raises(nx.NetworkXError):
+            bipartite.biadjacency_matrix(nx.Graph([(1, 0)]), [1, 1])
+
+    def test_duplicate_col(self):
+        with pytest.raises(nx.NetworkXError):
+            bipartite.biadjacency_matrix(nx.Graph([(1, 0)]), [0], [1, 1])
+
+    def test_format_keyword(self):
+        with pytest.raises(nx.NetworkXError):
+            bipartite.biadjacency_matrix(nx.Graph([(1, 0)]), [0], format="foo")
+
+    def test_from_biadjacency_roundtrip(self):
+        B1 = nx.path_graph(5)
+        M = bipartite.biadjacency_matrix(B1, [0, 2, 4])
+        B2 = bipartite.from_biadjacency_matrix(M)
+        assert nx.is_isomorphic(B1, B2)
+
+    def test_from_biadjacency_weight(self):
+        M = sparse.csc_matrix([[1, 2], [0, 3]])
+        B = bipartite.from_biadjacency_matrix(M)
+        assert edges_equal(B.edges(), [(0, 2), (0, 3), (1, 3)])
+        B = bipartite.from_biadjacency_matrix(M, edge_attribute="weight")
+        e = [(0, 2, {"weight": 1}), (0, 3, {"weight": 2}), (1, 3, {"weight": 3})]
+        assert edges_equal(B.edges(data=True), e)
+
+    def test_from_biadjacency_multigraph(self):
+        M = sparse.csc_matrix([[1, 2], [0, 3]])
+        B = bipartite.from_biadjacency_matrix(M, create_using=nx.MultiGraph())
+        assert edges_equal(B.edges(), [(0, 2), (0, 3), (0, 3), (1, 3), (1, 3), (1, 3)])