two version of R2R are hereHEADmaster

1 files changed, 108 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/networkx/linalg/tests/test_attrmatrix.py b/.venv/lib/python3.12/site-packages/networkx/linalg/tests/test_attrmatrix.py
new file mode 100644
index 00000000..01574bb3
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/networkx/linalg/tests/test_attrmatrix.py
@@ -0,0 +1,108 @@
+import pytest
+
+np = pytest.importorskip("numpy")
+
+import networkx as nx
+
+
+def test_attr_matrix():
+    G = nx.Graph()
+    G.add_edge(0, 1, thickness=1, weight=3)
+    G.add_edge(0, 1, thickness=1, weight=3)
+    G.add_edge(0, 2, thickness=2)
+    G.add_edge(1, 2, thickness=3)
+
+    def node_attr(u):
+        return G.nodes[u].get("size", 0.5) * 3
+
+    def edge_attr(u, v):
+        return G[u][v].get("thickness", 0.5)
+
+    M = nx.attr_matrix(G, edge_attr=edge_attr, node_attr=node_attr)
+    np.testing.assert_equal(M[0], np.array([[6.0]]))
+    assert M[1] == [1.5]
+
+
+def test_attr_matrix_directed():
+    G = nx.DiGraph()
+    G.add_edge(0, 1, thickness=1, weight=3)
+    G.add_edge(0, 1, thickness=1, weight=3)
+    G.add_edge(0, 2, thickness=2)
+    G.add_edge(1, 2, thickness=3)
+    M = nx.attr_matrix(G, rc_order=[0, 1, 2])
+    # fmt: off
+    data = np.array(
+        [[0., 1., 1.],
+         [0., 0., 1.],
+         [0., 0., 0.]]
+    )
+    # fmt: on
+    np.testing.assert_equal(M, np.array(data))
+
+
+def test_attr_matrix_multigraph():
+    G = nx.MultiGraph()
+    G.add_edge(0, 1, thickness=1, weight=3)
+    G.add_edge(0, 1, thickness=1, weight=3)
+    G.add_edge(0, 1, thickness=1, weight=3)
+    G.add_edge(0, 2, thickness=2)
+    G.add_edge(1, 2, thickness=3)
+    M = nx.attr_matrix(G, rc_order=[0, 1, 2])
+    # fmt: off
+    data = np.array(
+        [[0., 3., 1.],
+         [3., 0., 1.],
+         [1., 1., 0.]]
+    )
+    # fmt: on
+    np.testing.assert_equal(M, np.array(data))
+    M = nx.attr_matrix(G, edge_attr="weight", rc_order=[0, 1, 2])
+    # fmt: off
+    data = np.array(
+        [[0., 9., 1.],
+         [9., 0., 1.],
+         [1., 1., 0.]]
+    )
+    # fmt: on
+    np.testing.assert_equal(M, np.array(data))
+    M = nx.attr_matrix(G, edge_attr="thickness", rc_order=[0, 1, 2])
+    # fmt: off
+    data = np.array(
+        [[0., 3., 2.],
+         [3., 0., 3.],
+         [2., 3., 0.]]
+    )
+    # fmt: on
+    np.testing.assert_equal(M, np.array(data))
+
+
+def test_attr_sparse_matrix():
+    pytest.importorskip("scipy")
+    G = nx.Graph()
+    G.add_edge(0, 1, thickness=1, weight=3)
+    G.add_edge(0, 2, thickness=2)
+    G.add_edge(1, 2, thickness=3)
+    M = nx.attr_sparse_matrix(G)
+    mtx = M[0]
+    data = np.ones((3, 3), float)
+    np.fill_diagonal(data, 0)
+    np.testing.assert_equal(mtx.todense(), np.array(data))
+    assert M[1] == [0, 1, 2]
+
+
+def test_attr_sparse_matrix_directed():
+    pytest.importorskip("scipy")
+    G = nx.DiGraph()
+    G.add_edge(0, 1, thickness=1, weight=3)
+    G.add_edge(0, 1, thickness=1, weight=3)
+    G.add_edge(0, 2, thickness=2)
+    G.add_edge(1, 2, thickness=3)
+    M = nx.attr_sparse_matrix(G, rc_order=[0, 1, 2])
+    # fmt: off
+    data = np.array(
+        [[0., 1., 1.],
+         [0., 0., 1.],
+         [0., 0., 0.]]
+    )
+    # fmt: on
+    np.testing.assert_equal(M.todense(), np.array(data))