27 lines
792 B
Python
27 lines
792 B
Python
import pytest
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import numpy as np
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from sklearn.utils._testing import assert_allclose
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from sklearn.utils.arrayfuncs import min_pos
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def test_min_pos():
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# Check that min_pos returns a positive value and that it's consistent
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# between float and double
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X = np.random.RandomState(0).randn(100)
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min_double = min_pos(X)
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min_float = min_pos(X.astype(np.float32))
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assert_allclose(min_double, min_float)
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assert min_double >= 0
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@pytest.mark.parametrize("dtype", [np.float32, np.float64])
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def test_min_pos_no_positive(dtype):
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# Check that the return value of min_pos is the maximum representable
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# value of the input dtype when all input elements are <= 0 (#19328)
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X = np.full(100, -1.).astype(dtype, copy=False)
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assert min_pos(X) == np.finfo(dtype).max
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