92 lines
3.2 KiB
Python
92 lines
3.2 KiB
Python
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# Authors: Gael Varoquaux <gael.varoquaux@normalesup.org>
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# Justin Vincent
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# Lars Buitinck
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# License: BSD 3 clause
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import math
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import numpy as np
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import pytest
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import scipy.stats
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from sklearn.utils._testing import assert_array_equal
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from sklearn.utils.fixes import _joblib_parallel_args
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from sklearn.utils.fixes import _object_dtype_isnan
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from sklearn.utils.fixes import loguniform
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from sklearn.utils.fixes import MaskedArray
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@pytest.mark.parametrize('joblib_version', ('0.11', '0.12.0'))
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def test_joblib_parallel_args(monkeypatch, joblib_version):
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import joblib
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monkeypatch.setattr(joblib, '__version__', joblib_version)
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if joblib_version == '0.12.0':
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# arguments are simply passed through
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assert _joblib_parallel_args(prefer='threads') == {'prefer': 'threads'}
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assert _joblib_parallel_args(prefer='processes', require=None) == {
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'prefer': 'processes', 'require': None}
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assert _joblib_parallel_args(non_existing=1) == {'non_existing': 1}
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elif joblib_version == '0.11':
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# arguments are mapped to the corresponding backend
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assert _joblib_parallel_args(prefer='threads') == {
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'backend': 'threading'}
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assert _joblib_parallel_args(prefer='processes') == {
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'backend': 'multiprocessing'}
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with pytest.raises(ValueError):
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_joblib_parallel_args(prefer='invalid')
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assert _joblib_parallel_args(
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prefer='processes', require='sharedmem') == {
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'backend': 'threading'}
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with pytest.raises(ValueError):
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_joblib_parallel_args(require='invalid')
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with pytest.raises(NotImplementedError):
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_joblib_parallel_args(verbose=True)
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else:
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raise ValueError
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@pytest.mark.parametrize("dtype, val", ([object, 1],
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[object, "a"],
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[float, 1]))
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def test_object_dtype_isnan(dtype, val):
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X = np.array([[val, np.nan],
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[np.nan, val]], dtype=dtype)
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expected_mask = np.array([[False, True],
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[True, False]])
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mask = _object_dtype_isnan(X)
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assert_array_equal(mask, expected_mask)
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@pytest.mark.parametrize("low,high,base",
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[(-1, 0, 10), (0, 2, np.exp(1)), (-1, 1, 2)])
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def test_loguniform(low, high, base):
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rv = loguniform(base ** low, base ** high)
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assert isinstance(rv, scipy.stats._distn_infrastructure.rv_frozen)
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rvs = rv.rvs(size=2000, random_state=0)
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# Test the basics; right bounds, right size
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assert (base ** low <= rvs).all() and (rvs <= base ** high).all()
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assert len(rvs) == 2000
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# Test that it's actually (fairly) uniform
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log_rvs = np.array([math.log(x, base) for x in rvs])
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counts, _ = np.histogram(log_rvs)
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assert counts.mean() == 200
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assert np.abs(counts - counts.mean()).max() <= 40
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# Test that random_state works
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assert (
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loguniform(base ** low, base ** high).rvs(random_state=0)
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== loguniform(base ** low, base ** high).rvs(random_state=0)
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)
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def test_masked_array_deprecated(): # TODO: remove in 0.25
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with pytest.warns(FutureWarning, match='is deprecated'):
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MaskedArray()
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