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47 lines
1.3 KiB
Python
47 lines
1.3 KiB
Python
# Author: Brian M. Clapper, G. Varoquaux, Lars Buitinck
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# License: BSD
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from numpy.testing import assert_array_equal
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from pytest import raises as assert_raises
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import numpy as np
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from scipy.optimize import linear_sum_assignment
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from scipy.sparse.sputils import matrix
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def test_linear_sum_assignment_input_validation():
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assert_raises(ValueError, linear_sum_assignment, [1, 2, 3])
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C = [[1, 2, 3], [4, 5, 6]]
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assert_array_equal(linear_sum_assignment(C),
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linear_sum_assignment(np.asarray(C)))
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assert_array_equal(linear_sum_assignment(C),
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linear_sum_assignment(matrix(C)))
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I = np.identity(3)
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assert_array_equal(linear_sum_assignment(I.astype(np.bool_)),
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linear_sum_assignment(I))
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assert_raises(ValueError, linear_sum_assignment, I.astype(str))
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I[0][0] = np.nan
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assert_raises(ValueError, linear_sum_assignment, I)
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I = np.identity(3)
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I[1][1] = -np.inf
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assert_raises(ValueError, linear_sum_assignment, I)
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I = np.identity(3)
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I[:, 0] = np.inf
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assert_raises(ValueError, linear_sum_assignment, I)
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def test_constant_cost_matrix():
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# Fixes #11602
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n = 8
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C = np.ones((n, n))
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row_ind, col_ind = linear_sum_assignment(C)
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assert_array_equal(row_ind, np.arange(n))
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assert_array_equal(col_ind, np.arange(n))
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