128 lines
3.9 KiB
Python
128 lines
3.9 KiB
Python
import pytest
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import types
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import numpy as np
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import warnings
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from sklearn.dummy import DummyClassifier
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from sklearn.utils import all_estimators
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from sklearn.utils.estimator_checks import choose_check_classifiers_labels
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from sklearn.utils.estimator_checks import NotAnArray
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from sklearn.utils.estimator_checks import enforce_estimator_tags_y
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from sklearn.utils.estimator_checks import is_public_parameter
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from sklearn.utils.estimator_checks import pairwise_estimator_convert_X
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from sklearn.utils.estimator_checks import set_checking_parameters
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from sklearn.utils.optimize import newton_cg
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from sklearn.utils.random import random_choice_csc
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from sklearn.utils import safe_indexing
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# This file tests the utils that are deprecated
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# TODO: remove in 0.24
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def test_choose_check_classifiers_labels_deprecated():
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with pytest.warns(FutureWarning,
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match="removed in version 0.24"):
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choose_check_classifiers_labels(None, None, None)
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# TODO: remove in 0.24
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def test_enforce_estimator_tags_y():
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with pytest.warns(FutureWarning,
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match="removed in version 0.24"):
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enforce_estimator_tags_y(DummyClassifier(), np.array([0, 1]))
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# TODO: remove in 0.24
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def test_notanarray():
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with pytest.warns(FutureWarning,
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match="removed in version 0.24"):
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NotAnArray([1, 2])
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# TODO: remove in 0.24
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def test_is_public_parameter():
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with pytest.warns(FutureWarning,
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match="removed in version 0.24"):
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is_public_parameter('hello')
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# TODO: remove in 0.24
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def test_pairwise_estimator_convert_X():
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with pytest.warns(FutureWarning,
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match="removed in version 0.24"):
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pairwise_estimator_convert_X([[1, 2]], DummyClassifier())
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# TODO: remove in 0.24
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def test_set_checking_parameters():
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with pytest.warns(FutureWarning,
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match="removed in version 0.24"):
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set_checking_parameters(DummyClassifier())
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# TODO: remove in 0.24
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def test_newton_cg():
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rng = np.random.RandomState(0)
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A = rng.normal(size=(10, 10))
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x0 = np.ones(10)
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def func(x):
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Ax = A.dot(x)
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return .5 * (Ax).dot(Ax)
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def grad(x):
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return A.T.dot(A.dot(x))
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def grad_hess(x):
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return grad(x), lambda x: A.T.dot(A.dot(x))
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with pytest.warns(FutureWarning,
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match="removed in version 0.24"):
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newton_cg(grad_hess, func, grad, x0)
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# TODO: remove in 0.24
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def test_random_choice_csc():
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with pytest.warns(FutureWarning,
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match="removed in version 0.24"):
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random_choice_csc(10, [[2]])
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# TODO: remove in 0.24
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def test_safe_indexing():
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with pytest.warns(FutureWarning,
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match="removed in version 0.24"):
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safe_indexing([1, 2], 0)
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# TODO: remove in 0.24
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def test_partial_dependence_no_shadowing():
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# Non-regression test for:
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# https://github.com/scikit-learn/scikit-learn/issues/15842
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", category=FutureWarning)
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from sklearn.inspection.partial_dependence import partial_dependence as _ # noqa
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# Calling all_estimators() also triggers a recursive import of all
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# submodules, including deprecated ones.
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all_estimators()
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from sklearn.inspection import partial_dependence
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assert isinstance(partial_dependence, types.FunctionType)
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# TODO: remove in 0.24
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def test_dict_learning_no_shadowing():
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# Non-regression test for:
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# https://github.com/scikit-learn/scikit-learn/issues/15842
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", category=FutureWarning)
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from sklearn.decomposition.dict_learning import dict_learning as _ # noqa
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# Calling all_estimators() also triggers a recursive import of all
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# submodules, including deprecated ones.
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all_estimators()
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from sklearn.decomposition import dict_learning
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assert isinstance(dict_learning, types.FunctionType)
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