744 lines
22 KiB
Python
744 lines
22 KiB
Python
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import warnings
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import unittest
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import sys
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import os
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import atexit
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import numpy as np
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from scipy import sparse
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import pytest
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from sklearn.utils.deprecation import deprecated
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from sklearn.utils.metaestimators import if_delegate_has_method
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from sklearn.utils._testing import (
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assert_raises,
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assert_warns,
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assert_no_warnings,
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set_random_state,
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assert_raise_message,
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ignore_warnings,
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check_docstring_parameters,
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assert_allclose_dense_sparse,
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assert_raises_regex,
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TempMemmap,
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create_memmap_backed_data,
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_delete_folder,
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_convert_container,
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raises,
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)
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from sklearn.tree import DecisionTreeClassifier
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from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
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def test_set_random_state():
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lda = LinearDiscriminantAnalysis()
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tree = DecisionTreeClassifier()
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# Linear Discriminant Analysis doesn't have random state: smoke test
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set_random_state(lda, 3)
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set_random_state(tree, 3)
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assert tree.random_state == 3
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def test_assert_allclose_dense_sparse():
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x = np.arange(9).reshape(3, 3)
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msg = "Not equal to tolerance "
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y = sparse.csc_matrix(x)
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for X in [x, y]:
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# basic compare
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with pytest.raises(AssertionError, match=msg):
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assert_allclose_dense_sparse(X, X*2)
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assert_allclose_dense_sparse(X, X)
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with pytest.raises(ValueError, match="Can only compare two sparse"):
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assert_allclose_dense_sparse(x, y)
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A = sparse.diags(np.ones(5), offsets=0).tocsr()
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B = sparse.csr_matrix(np.ones((1, 5)))
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with pytest.raises(AssertionError, match="Arrays are not equal"):
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assert_allclose_dense_sparse(B, A)
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def test_assert_raises_msg():
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with assert_raises_regex(AssertionError, 'Hello world'):
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with assert_raises(ValueError, msg='Hello world'):
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pass
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def test_assert_raise_message():
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def _raise_ValueError(message):
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raise ValueError(message)
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def _no_raise():
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pass
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assert_raise_message(ValueError, "test",
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_raise_ValueError, "test")
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assert_raises(AssertionError,
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assert_raise_message, ValueError, "something else",
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_raise_ValueError, "test")
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assert_raises(ValueError,
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assert_raise_message, TypeError, "something else",
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_raise_ValueError, "test")
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assert_raises(AssertionError,
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assert_raise_message, ValueError, "test",
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_no_raise)
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# multiple exceptions in a tuple
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assert_raises(AssertionError,
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assert_raise_message, (ValueError, AttributeError),
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"test", _no_raise)
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def test_ignore_warning():
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# This check that ignore_warning decorateur and context manager are working
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# as expected
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def _warning_function():
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warnings.warn("deprecation warning", DeprecationWarning)
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def _multiple_warning_function():
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warnings.warn("deprecation warning", DeprecationWarning)
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warnings.warn("deprecation warning")
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# Check the function directly
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assert_no_warnings(ignore_warnings(_warning_function))
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assert_no_warnings(ignore_warnings(_warning_function,
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category=DeprecationWarning))
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assert_warns(DeprecationWarning, ignore_warnings(_warning_function,
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category=UserWarning))
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assert_warns(UserWarning,
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ignore_warnings(_multiple_warning_function,
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category=FutureWarning))
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assert_warns(DeprecationWarning,
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ignore_warnings(_multiple_warning_function,
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category=UserWarning))
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assert_no_warnings(ignore_warnings(_warning_function,
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category=(DeprecationWarning,
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UserWarning)))
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# Check the decorator
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@ignore_warnings
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def decorator_no_warning():
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_warning_function()
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_multiple_warning_function()
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@ignore_warnings(category=(DeprecationWarning, UserWarning))
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def decorator_no_warning_multiple():
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_multiple_warning_function()
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@ignore_warnings(category=DeprecationWarning)
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def decorator_no_deprecation_warning():
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_warning_function()
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@ignore_warnings(category=UserWarning)
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def decorator_no_user_warning():
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_warning_function()
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@ignore_warnings(category=DeprecationWarning)
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def decorator_no_deprecation_multiple_warning():
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_multiple_warning_function()
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@ignore_warnings(category=UserWarning)
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def decorator_no_user_multiple_warning():
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_multiple_warning_function()
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assert_no_warnings(decorator_no_warning)
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assert_no_warnings(decorator_no_warning_multiple)
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assert_no_warnings(decorator_no_deprecation_warning)
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assert_warns(DeprecationWarning, decorator_no_user_warning)
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assert_warns(UserWarning, decorator_no_deprecation_multiple_warning)
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assert_warns(DeprecationWarning, decorator_no_user_multiple_warning)
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# Check the context manager
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def context_manager_no_warning():
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with ignore_warnings():
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_warning_function()
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def context_manager_no_warning_multiple():
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with ignore_warnings(category=(DeprecationWarning, UserWarning)):
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_multiple_warning_function()
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def context_manager_no_deprecation_warning():
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with ignore_warnings(category=DeprecationWarning):
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_warning_function()
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def context_manager_no_user_warning():
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with ignore_warnings(category=UserWarning):
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_warning_function()
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def context_manager_no_deprecation_multiple_warning():
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with ignore_warnings(category=DeprecationWarning):
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_multiple_warning_function()
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def context_manager_no_user_multiple_warning():
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with ignore_warnings(category=UserWarning):
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_multiple_warning_function()
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assert_no_warnings(context_manager_no_warning)
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assert_no_warnings(context_manager_no_warning_multiple)
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assert_no_warnings(context_manager_no_deprecation_warning)
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assert_warns(DeprecationWarning, context_manager_no_user_warning)
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assert_warns(UserWarning, context_manager_no_deprecation_multiple_warning)
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assert_warns(DeprecationWarning, context_manager_no_user_multiple_warning)
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# Check that passing warning class as first positional argument
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warning_class = UserWarning
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match = "'obj' should be a callable.+you should use 'category=UserWarning'"
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with pytest.raises(ValueError, match=match):
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silence_warnings_func = ignore_warnings(warning_class)(
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_warning_function)
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silence_warnings_func()
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with pytest.raises(ValueError, match=match):
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@ignore_warnings(warning_class)
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def test():
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pass
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class TestWarns(unittest.TestCase):
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def test_warn(self):
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def f():
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warnings.warn("yo")
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return 3
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", UserWarning)
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filters_orig = warnings.filters[:]
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assert assert_warns(UserWarning, f) == 3
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# test that assert_warns doesn't have side effects on warnings
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# filters
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assert warnings.filters == filters_orig
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with pytest.raises(AssertionError):
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assert_no_warnings(f)
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assert assert_no_warnings(lambda x: x, 1) == 1
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def test_warn_wrong_warning(self):
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def f():
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warnings.warn("yo", FutureWarning)
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failed = False
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filters = sys.modules['warnings'].filters[:]
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try:
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try:
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# Should raise an AssertionError
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# assert_warns has a special handling of "FutureWarning" that
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# pytest.warns does not have
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assert_warns(UserWarning, f)
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failed = True
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except AssertionError:
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pass
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finally:
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sys.modules['warnings'].filters = filters
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if failed:
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raise AssertionError("wrong warning caught by assert_warn")
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# Tests for docstrings:
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def f_ok(a, b):
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"""Function f
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Parameters
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----------
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a : int
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Parameter a
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b : float
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Parameter b
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Returns
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-------
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c : list
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Parameter c
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"""
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c = a + b
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return c
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def f_bad_sections(a, b):
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"""Function f
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Parameters
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----------
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a : int
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Parameter a
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b : float
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Parameter b
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Results
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-------
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c : list
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Parameter c
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"""
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c = a + b
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return c
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def f_bad_order(b, a):
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"""Function f
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Parameters
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----------
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a : int
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Parameter a
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b : float
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Parameter b
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Returns
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-------
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c : list
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Parameter c
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"""
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c = a + b
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return c
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def f_too_many_param_docstring(a, b):
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"""Function f
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Parameters
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----------
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a : int
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Parameter a
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b : int
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Parameter b
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c : int
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Parameter c
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Returns
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-------
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d : list
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Parameter c
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"""
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d = a + b
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return d
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def f_missing(a, b):
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"""Function f
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Parameters
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----------
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a : int
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Parameter a
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Returns
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-------
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c : list
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Parameter c
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"""
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c = a + b
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return c
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def f_check_param_definition(a, b, c, d, e):
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"""Function f
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Parameters
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----------
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a: int
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Parameter a
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b:
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Parameter b
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c :
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Parameter c
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d:int
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Parameter d
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e
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No typespec is allowed without colon
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"""
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return a + b + c + d
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class Klass:
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def f_missing(self, X, y):
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pass
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def f_bad_sections(self, X, y):
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"""Function f
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Parameter
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----------
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a : int
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Parameter a
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b : float
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Parameter b
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Results
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-------
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c : list
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Parameter c
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"""
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pass
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class MockEst:
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def __init__(self):
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"""MockEstimator"""
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def fit(self, X, y):
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return X
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def predict(self, X):
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return X
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def predict_proba(self, X):
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return X
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def score(self, X):
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return 1.
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class MockMetaEstimator:
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def __init__(self, delegate):
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"""MetaEstimator to check if doctest on delegated methods work.
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Parameters
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---------
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delegate : estimator
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Delegated estimator.
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"""
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self.delegate = delegate
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@if_delegate_has_method(delegate=('delegate'))
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def predict(self, X):
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"""This is available only if delegate has predict.
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Parameters
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----------
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y : ndarray
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Parameter y
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"""
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return self.delegate.predict(X)
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@if_delegate_has_method(delegate=('delegate'))
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@deprecated("Testing a deprecated delegated method")
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def score(self, X):
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|
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"""This is available only if delegate has score.
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Parameters
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---------
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y : ndarray
|
||
|
|
Parameter y
|
||
|
|
"""
|
||
|
|
|
||
|
|
@if_delegate_has_method(delegate=('delegate'))
|
||
|
|
def predict_proba(self, X):
|
||
|
|
"""This is available only if delegate has predict_proba.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
---------
|
||
|
|
X : ndarray
|
||
|
|
Parameter X
|
||
|
|
"""
|
||
|
|
return X
|
||
|
|
|
||
|
|
@deprecated('Testing deprecated function with wrong params')
|
||
|
|
def fit(self, X, y):
|
||
|
|
"""Incorrect docstring but should not be tested"""
|
||
|
|
|
||
|
|
|
||
|
|
def test_check_docstring_parameters():
|
||
|
|
pytest.importorskip('numpydoc',
|
||
|
|
reason="numpydoc is required to test the docstrings")
|
||
|
|
|
||
|
|
incorrect = check_docstring_parameters(f_ok)
|
||
|
|
assert incorrect == []
|
||
|
|
incorrect = check_docstring_parameters(f_ok, ignore=['b'])
|
||
|
|
assert incorrect == []
|
||
|
|
incorrect = check_docstring_parameters(f_missing, ignore=['b'])
|
||
|
|
assert incorrect == []
|
||
|
|
with pytest.raises(RuntimeError, match="Unknown section Results"):
|
||
|
|
check_docstring_parameters(f_bad_sections)
|
||
|
|
with pytest.raises(RuntimeError, match="Unknown section Parameter"):
|
||
|
|
check_docstring_parameters(Klass.f_bad_sections)
|
||
|
|
|
||
|
|
incorrect = check_docstring_parameters(f_check_param_definition)
|
||
|
|
assert (
|
||
|
|
incorrect == [
|
||
|
|
"sklearn.utils.tests.test_testing.f_check_param_definition There "
|
||
|
|
"was no space between the param name and colon ('a: int')",
|
||
|
|
|
||
|
|
"sklearn.utils.tests.test_testing.f_check_param_definition There "
|
||
|
|
"was no space between the param name and colon ('b:')",
|
||
|
|
|
||
|
|
"sklearn.utils.tests.test_testing.f_check_param_definition "
|
||
|
|
"Parameter 'c :' has an empty type spec. Remove the colon",
|
||
|
|
|
||
|
|
"sklearn.utils.tests.test_testing.f_check_param_definition There "
|
||
|
|
"was no space between the param name and colon ('d:int')",
|
||
|
|
])
|
||
|
|
|
||
|
|
messages = [
|
||
|
|
["In function: sklearn.utils.tests.test_testing.f_bad_order",
|
||
|
|
"There's a parameter name mismatch in function docstring w.r.t."
|
||
|
|
" function signature, at index 0 diff: 'b' != 'a'",
|
||
|
|
"Full diff:",
|
||
|
|
"- ['b', 'a']",
|
||
|
|
"+ ['a', 'b']"],
|
||
|
|
|
||
|
|
["In function: " +
|
||
|
|
"sklearn.utils.tests.test_testing.f_too_many_param_docstring",
|
||
|
|
"Parameters in function docstring have more items w.r.t. function"
|
||
|
|
" signature, first extra item: c",
|
||
|
|
"Full diff:",
|
||
|
|
"- ['a', 'b']",
|
||
|
|
"+ ['a', 'b', 'c']",
|
||
|
|
"? +++++"],
|
||
|
|
|
||
|
|
["In function: sklearn.utils.tests.test_testing.f_missing",
|
||
|
|
"Parameters in function docstring have less items w.r.t. function"
|
||
|
|
" signature, first missing item: b",
|
||
|
|
"Full diff:",
|
||
|
|
"- ['a', 'b']",
|
||
|
|
"+ ['a']"],
|
||
|
|
|
||
|
|
["In function: sklearn.utils.tests.test_testing.Klass.f_missing",
|
||
|
|
"Parameters in function docstring have less items w.r.t. function"
|
||
|
|
" signature, first missing item: X",
|
||
|
|
"Full diff:",
|
||
|
|
"- ['X', 'y']",
|
||
|
|
"+ []"],
|
||
|
|
|
||
|
|
["In function: " +
|
||
|
|
"sklearn.utils.tests.test_testing.MockMetaEstimator.predict",
|
||
|
|
"There's a parameter name mismatch in function docstring w.r.t."
|
||
|
|
" function signature, at index 0 diff: 'X' != 'y'",
|
||
|
|
"Full diff:",
|
||
|
|
"- ['X']",
|
||
|
|
"? ^",
|
||
|
|
"+ ['y']",
|
||
|
|
"? ^"],
|
||
|
|
|
||
|
|
["In function: " +
|
||
|
|
"sklearn.utils.tests.test_testing.MockMetaEstimator."
|
||
|
|
+ "predict_proba",
|
||
|
|
"Parameters in function docstring have less items w.r.t. function"
|
||
|
|
" signature, first missing item: X",
|
||
|
|
"Full diff:",
|
||
|
|
"- ['X']",
|
||
|
|
"+ []"],
|
||
|
|
|
||
|
|
["In function: " +
|
||
|
|
"sklearn.utils.tests.test_testing.MockMetaEstimator.score",
|
||
|
|
"Parameters in function docstring have less items w.r.t. function"
|
||
|
|
" signature, first missing item: X",
|
||
|
|
"Full diff:",
|
||
|
|
"- ['X']",
|
||
|
|
"+ []"],
|
||
|
|
|
||
|
|
["In function: " +
|
||
|
|
"sklearn.utils.tests.test_testing.MockMetaEstimator.fit",
|
||
|
|
"Parameters in function docstring have less items w.r.t. function"
|
||
|
|
" signature, first missing item: X",
|
||
|
|
"Full diff:",
|
||
|
|
"- ['X', 'y']",
|
||
|
|
"+ []"],
|
||
|
|
|
||
|
|
]
|
||
|
|
|
||
|
|
mock_meta = MockMetaEstimator(delegate=MockEst())
|
||
|
|
|
||
|
|
for msg, f in zip(messages,
|
||
|
|
[f_bad_order,
|
||
|
|
f_too_many_param_docstring,
|
||
|
|
f_missing,
|
||
|
|
Klass.f_missing,
|
||
|
|
mock_meta.predict,
|
||
|
|
mock_meta.predict_proba,
|
||
|
|
mock_meta.score,
|
||
|
|
mock_meta.fit]):
|
||
|
|
incorrect = check_docstring_parameters(f)
|
||
|
|
assert msg == incorrect, ('\n"%s"\n not in \n"%s"' % (msg, incorrect))
|
||
|
|
|
||
|
|
|
||
|
|
class RegistrationCounter:
|
||
|
|
def __init__(self):
|
||
|
|
self.nb_calls = 0
|
||
|
|
|
||
|
|
def __call__(self, to_register_func):
|
||
|
|
self.nb_calls += 1
|
||
|
|
assert to_register_func.func is _delete_folder
|
||
|
|
|
||
|
|
|
||
|
|
def check_memmap(input_array, mmap_data, mmap_mode='r'):
|
||
|
|
assert isinstance(mmap_data, np.memmap)
|
||
|
|
writeable = mmap_mode != 'r'
|
||
|
|
assert mmap_data.flags.writeable is writeable
|
||
|
|
np.testing.assert_array_equal(input_array, mmap_data)
|
||
|
|
|
||
|
|
|
||
|
|
def test_tempmemmap(monkeypatch):
|
||
|
|
registration_counter = RegistrationCounter()
|
||
|
|
monkeypatch.setattr(atexit, 'register', registration_counter)
|
||
|
|
|
||
|
|
input_array = np.ones(3)
|
||
|
|
with TempMemmap(input_array) as data:
|
||
|
|
check_memmap(input_array, data)
|
||
|
|
temp_folder = os.path.dirname(data.filename)
|
||
|
|
if os.name != 'nt':
|
||
|
|
assert not os.path.exists(temp_folder)
|
||
|
|
assert registration_counter.nb_calls == 1
|
||
|
|
|
||
|
|
mmap_mode = 'r+'
|
||
|
|
with TempMemmap(input_array, mmap_mode=mmap_mode) as data:
|
||
|
|
check_memmap(input_array, data, mmap_mode=mmap_mode)
|
||
|
|
temp_folder = os.path.dirname(data.filename)
|
||
|
|
if os.name != 'nt':
|
||
|
|
assert not os.path.exists(temp_folder)
|
||
|
|
assert registration_counter.nb_calls == 2
|
||
|
|
|
||
|
|
|
||
|
|
def test_create_memmap_backed_data(monkeypatch):
|
||
|
|
registration_counter = RegistrationCounter()
|
||
|
|
monkeypatch.setattr(atexit, 'register', registration_counter)
|
||
|
|
|
||
|
|
input_array = np.ones(3)
|
||
|
|
data = create_memmap_backed_data(input_array)
|
||
|
|
check_memmap(input_array, data)
|
||
|
|
assert registration_counter.nb_calls == 1
|
||
|
|
|
||
|
|
data, folder = create_memmap_backed_data(input_array,
|
||
|
|
return_folder=True)
|
||
|
|
check_memmap(input_array, data)
|
||
|
|
assert folder == os.path.dirname(data.filename)
|
||
|
|
assert registration_counter.nb_calls == 2
|
||
|
|
|
||
|
|
mmap_mode = 'r+'
|
||
|
|
data = create_memmap_backed_data(input_array, mmap_mode=mmap_mode)
|
||
|
|
check_memmap(input_array, data, mmap_mode)
|
||
|
|
assert registration_counter.nb_calls == 3
|
||
|
|
|
||
|
|
input_list = [input_array, input_array + 1, input_array + 2]
|
||
|
|
mmap_data_list = create_memmap_backed_data(input_list)
|
||
|
|
for input_array, data in zip(input_list, mmap_data_list):
|
||
|
|
check_memmap(input_array, data)
|
||
|
|
assert registration_counter.nb_calls == 4
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"constructor_name, container_type",
|
||
|
|
[
|
||
|
|
('list', list),
|
||
|
|
('tuple', tuple),
|
||
|
|
('array', np.ndarray),
|
||
|
|
('sparse', sparse.csr_matrix),
|
||
|
|
('sparse_csr', sparse.csr_matrix),
|
||
|
|
('sparse_csc', sparse.csc_matrix),
|
||
|
|
('dataframe', lambda: pytest.importorskip('pandas').DataFrame),
|
||
|
|
('series', lambda: pytest.importorskip('pandas').Series),
|
||
|
|
('index', lambda: pytest.importorskip('pandas').Index),
|
||
|
|
('slice', slice),
|
||
|
|
]
|
||
|
|
)
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"dtype, superdtype",
|
||
|
|
[
|
||
|
|
(np.int32, np.integer),
|
||
|
|
(np.int64, np.integer),
|
||
|
|
(np.float32, np.floating),
|
||
|
|
(np.float64, np.floating),
|
||
|
|
]
|
||
|
|
)
|
||
|
|
def test_convert_container(
|
||
|
|
constructor_name, container_type, dtype, superdtype,
|
||
|
|
):
|
||
|
|
"""Check that we convert the container to the right type of array with the
|
||
|
|
right data type."""
|
||
|
|
if constructor_name in ("dataframe", "series", "index"):
|
||
|
|
# delay the import of pandas within the function to only skip this test
|
||
|
|
# instead of the whole file
|
||
|
|
container_type = container_type()
|
||
|
|
container = [0, 1]
|
||
|
|
container_converted = _convert_container(
|
||
|
|
container, constructor_name, dtype=dtype,
|
||
|
|
)
|
||
|
|
assert isinstance(container_converted, container_type)
|
||
|
|
|
||
|
|
if constructor_name in ("list", "tuple", "index"):
|
||
|
|
# list and tuple will use Python class dtype: int, float
|
||
|
|
# pandas index will always use high precision: np.int64 and np.float64
|
||
|
|
assert np.issubdtype(type(container_converted[0]), superdtype)
|
||
|
|
elif hasattr(container_converted, "dtype"):
|
||
|
|
assert container_converted.dtype == dtype
|
||
|
|
elif hasattr(container_converted, "dtypes"):
|
||
|
|
assert container_converted.dtypes[0] == dtype
|
||
|
|
|
||
|
|
|
||
|
|
def test_raises():
|
||
|
|
# Tests for the raises context manager
|
||
|
|
|
||
|
|
# Proper type, no match
|
||
|
|
with raises(TypeError):
|
||
|
|
raise TypeError()
|
||
|
|
|
||
|
|
# Proper type, proper match
|
||
|
|
with raises(TypeError, match="how are you") as cm:
|
||
|
|
raise TypeError("hello how are you")
|
||
|
|
assert cm.raised_and_matched
|
||
|
|
|
||
|
|
# Proper type, proper match with multiple patterns
|
||
|
|
with raises(TypeError, match=["not this one", "how are you"]) as cm:
|
||
|
|
raise TypeError("hello how are you")
|
||
|
|
assert cm.raised_and_matched
|
||
|
|
|
||
|
|
# bad type, no match
|
||
|
|
with pytest.raises(ValueError, match="this will be raised"):
|
||
|
|
with raises(TypeError) as cm:
|
||
|
|
raise ValueError("this will be raised")
|
||
|
|
assert not cm.raised_and_matched
|
||
|
|
|
||
|
|
# Bad type, no match, with a err_msg
|
||
|
|
with pytest.raises(AssertionError, match="the failure message"):
|
||
|
|
with raises(TypeError, err_msg="the failure message") as cm:
|
||
|
|
raise ValueError()
|
||
|
|
assert not cm.raised_and_matched
|
||
|
|
|
||
|
|
# bad type, with match (is ignored anyway)
|
||
|
|
with pytest.raises(ValueError, match="this will be raised"):
|
||
|
|
with raises(TypeError, match="this is ignored") as cm:
|
||
|
|
raise ValueError("this will be raised")
|
||
|
|
assert not cm.raised_and_matched
|
||
|
|
|
||
|
|
# proper type but bad match
|
||
|
|
with pytest.raises(
|
||
|
|
AssertionError, match="should contain one of the following patterns"
|
||
|
|
):
|
||
|
|
with raises(TypeError, match="hello") as cm:
|
||
|
|
raise TypeError("Bad message")
|
||
|
|
assert not cm.raised_and_matched
|
||
|
|
|
||
|
|
# proper type but bad match, with err_msg
|
||
|
|
with pytest.raises(AssertionError, match="the failure message"):
|
||
|
|
with raises(
|
||
|
|
TypeError, match="hello", err_msg="the failure message"
|
||
|
|
) as cm:
|
||
|
|
raise TypeError("Bad message")
|
||
|
|
assert not cm.raised_and_matched
|
||
|
|
|
||
|
|
# no raise with default may_pass=False
|
||
|
|
with pytest.raises(AssertionError, match="Did not raise"):
|
||
|
|
with raises(TypeError) as cm:
|
||
|
|
pass
|
||
|
|
assert not cm.raised_and_matched
|
||
|
|
|
||
|
|
# no raise with may_pass=True
|
||
|
|
with raises(TypeError, match="hello", may_pass=True) as cm:
|
||
|
|
pass # still OK
|
||
|
|
assert not cm.raised_and_matched
|
||
|
|
|
||
|
|
# Multiple exception types:
|
||
|
|
with raises((TypeError, ValueError)):
|
||
|
|
raise TypeError()
|
||
|
|
with raises((TypeError, ValueError)):
|
||
|
|
raise ValueError()
|
||
|
|
with pytest.raises(AssertionError):
|
||
|
|
with raises((TypeError, ValueError)):
|
||
|
|
pass
|