148 lines
6 KiB
Python
148 lines
6 KiB
Python
import numpy as np
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import pytest
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from numpy.testing import assert_array_almost_equal
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from scipy.sparse import csr_array, csr_matrix, coo_array, coo_matrix
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from scipy.sparse.csgraph import (breadth_first_tree, depth_first_tree,
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csgraph_to_dense, csgraph_from_dense, csgraph_masked_from_dense)
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def test_graph_breadth_first():
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csgraph = np.array([[0, 1, 2, 0, 0],
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[1, 0, 0, 0, 3],
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[2, 0, 0, 7, 0],
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[0, 0, 7, 0, 1],
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[0, 3, 0, 1, 0]])
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csgraph = csgraph_from_dense(csgraph, null_value=0)
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bfirst = np.array([[0, 1, 2, 0, 0],
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[0, 0, 0, 0, 3],
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[0, 0, 0, 7, 0],
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[0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0]])
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for directed in [True, False]:
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bfirst_test = breadth_first_tree(csgraph, 0, directed)
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assert_array_almost_equal(csgraph_to_dense(bfirst_test),
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bfirst)
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def test_graph_depth_first():
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csgraph = np.array([[0, 1, 2, 0, 0],
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[1, 0, 0, 0, 3],
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[2, 0, 0, 7, 0],
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[0, 0, 7, 0, 1],
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[0, 3, 0, 1, 0]])
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csgraph = csgraph_from_dense(csgraph, null_value=0)
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dfirst = np.array([[0, 1, 0, 0, 0],
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[0, 0, 0, 0, 3],
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[0, 0, 0, 0, 0],
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[0, 0, 7, 0, 0],
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[0, 0, 0, 1, 0]])
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for directed in [True, False]:
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dfirst_test = depth_first_tree(csgraph, 0, directed)
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assert_array_almost_equal(csgraph_to_dense(dfirst_test), dfirst)
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def test_return_type():
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from .._laplacian import laplacian
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from .._min_spanning_tree import minimum_spanning_tree
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np_csgraph = np.array([[0, 1, 2, 0, 0],
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[1, 0, 0, 0, 3],
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[2, 0, 0, 7, 0],
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[0, 0, 7, 0, 1],
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[0, 3, 0, 1, 0]])
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csgraph = csr_array(np_csgraph)
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assert isinstance(laplacian(csgraph), coo_array)
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assert isinstance(minimum_spanning_tree(csgraph), csr_array)
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for directed in [True, False]:
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assert isinstance(depth_first_tree(csgraph, 0, directed), csr_array)
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assert isinstance(breadth_first_tree(csgraph, 0, directed), csr_array)
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csgraph = csgraph_from_dense(np_csgraph, null_value=0)
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assert isinstance(csgraph, csr_array)
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assert isinstance(laplacian(csgraph), coo_array)
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assert isinstance(minimum_spanning_tree(csgraph), csr_array)
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for directed in [True, False]:
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assert isinstance(depth_first_tree(csgraph, 0, directed), csr_array)
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assert isinstance(breadth_first_tree(csgraph, 0, directed), csr_array)
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csgraph = csgraph_masked_from_dense(np_csgraph, null_value=0)
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assert isinstance(csgraph, np.ma.MaskedArray)
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assert csgraph._baseclass is np.ndarray
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# laplacian doesnt work with masked arrays so not here
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assert isinstance(minimum_spanning_tree(csgraph), csr_array)
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for directed in [True, False]:
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assert isinstance(depth_first_tree(csgraph, 0, directed), csr_array)
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assert isinstance(breadth_first_tree(csgraph, 0, directed), csr_array)
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# start of testing with matrix/spmatrix types
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with np.testing.suppress_warnings() as sup:
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sup.filter(DeprecationWarning, "the matrix subclass.*")
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sup.filter(PendingDeprecationWarning, "the matrix subclass.*")
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nm_csgraph = np.matrix([[0, 1, 2, 0, 0],
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[1, 0, 0, 0, 3],
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[2, 0, 0, 7, 0],
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[0, 0, 7, 0, 1],
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[0, 3, 0, 1, 0]])
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csgraph = csr_matrix(nm_csgraph)
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assert isinstance(laplacian(csgraph), coo_matrix)
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assert isinstance(minimum_spanning_tree(csgraph), csr_matrix)
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for directed in [True, False]:
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assert isinstance(depth_first_tree(csgraph, 0, directed), csr_matrix)
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assert isinstance(breadth_first_tree(csgraph, 0, directed), csr_matrix)
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csgraph = csgraph_from_dense(nm_csgraph, null_value=0)
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assert isinstance(csgraph, csr_matrix)
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assert isinstance(laplacian(csgraph), coo_matrix)
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assert isinstance(minimum_spanning_tree(csgraph), csr_matrix)
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for directed in [True, False]:
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assert isinstance(depth_first_tree(csgraph, 0, directed), csr_matrix)
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assert isinstance(breadth_first_tree(csgraph, 0, directed), csr_matrix)
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mm_csgraph = csgraph_masked_from_dense(nm_csgraph, null_value=0)
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assert isinstance(mm_csgraph, np.ma.MaskedArray)
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# laplacian doesnt work with masked arrays so not here
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assert isinstance(minimum_spanning_tree(csgraph), csr_matrix)
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for directed in [True, False]:
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assert isinstance(depth_first_tree(csgraph, 0, directed), csr_matrix)
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assert isinstance(breadth_first_tree(csgraph, 0, directed), csr_matrix)
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# end of testing with matrix/spmatrix types
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def test_graph_breadth_first_trivial_graph():
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csgraph = np.array([[0]])
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csgraph = csgraph_from_dense(csgraph, null_value=0)
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bfirst = np.array([[0]])
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for directed in [True, False]:
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bfirst_test = breadth_first_tree(csgraph, 0, directed)
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assert_array_almost_equal(csgraph_to_dense(bfirst_test), bfirst)
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def test_graph_depth_first_trivial_graph():
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csgraph = np.array([[0]])
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csgraph = csgraph_from_dense(csgraph, null_value=0)
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bfirst = np.array([[0]])
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for directed in [True, False]:
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bfirst_test = depth_first_tree(csgraph, 0, directed)
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assert_array_almost_equal(csgraph_to_dense(bfirst_test),
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bfirst)
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@pytest.mark.parametrize('directed', [True, False])
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@pytest.mark.parametrize('tree_func', [breadth_first_tree, depth_first_tree])
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def test_int64_indices(tree_func, directed):
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# See https://github.com/scipy/scipy/issues/18716
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g = csr_array(([1], np.array([[0], [1]], dtype=np.int64)), shape=(2, 2))
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assert g.indices.dtype == np.int64
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tree = tree_func(g, 0, directed=directed)
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assert_array_almost_equal(csgraph_to_dense(tree), [[0, 1], [0, 0]])
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