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Diffstat (limited to '.venv/lib/python3.12/site-packages/numpy/core/tests/test_deprecations.py')
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diff --git a/.venv/lib/python3.12/site-packages/numpy/core/tests/test_deprecations.py b/.venv/lib/python3.12/site-packages/numpy/core/tests/test_deprecations.py new file mode 100644 index 00000000..3ada39e9 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/numpy/core/tests/test_deprecations.py @@ -0,0 +1,817 @@ +""" +Tests related to deprecation warnings. Also a convenient place +to document how deprecations should eventually be turned into errors. + +""" +import datetime +import operator +import warnings +import pytest +import tempfile +import re +import sys + +import numpy as np +from numpy.testing import ( + assert_raises, assert_warns, assert_, assert_array_equal, SkipTest, + KnownFailureException, break_cycles, + ) + +from numpy.core._multiarray_tests import fromstring_null_term_c_api + +try: + import pytz + _has_pytz = True +except ImportError: + _has_pytz = False + + +class _DeprecationTestCase: + # Just as warning: warnings uses re.match, so the start of this message + # must match. + message = '' + warning_cls = DeprecationWarning + + def setup_method(self): + self.warn_ctx = warnings.catch_warnings(record=True) + self.log = self.warn_ctx.__enter__() + + # Do *not* ignore other DeprecationWarnings. Ignoring warnings + # can give very confusing results because of + # https://bugs.python.org/issue4180 and it is probably simplest to + # try to keep the tests cleanly giving only the right warning type. + # (While checking them set to "error" those are ignored anyway) + # We still have them show up, because otherwise they would be raised + warnings.filterwarnings("always", category=self.warning_cls) + warnings.filterwarnings("always", message=self.message, + category=self.warning_cls) + + def teardown_method(self): + self.warn_ctx.__exit__() + + def assert_deprecated(self, function, num=1, ignore_others=False, + function_fails=False, + exceptions=np._NoValue, + args=(), kwargs={}): + """Test if DeprecationWarnings are given and raised. + + This first checks if the function when called gives `num` + DeprecationWarnings, after that it tries to raise these + DeprecationWarnings and compares them with `exceptions`. + The exceptions can be different for cases where this code path + is simply not anticipated and the exception is replaced. + + Parameters + ---------- + function : callable + The function to test + num : int + Number of DeprecationWarnings to expect. This should normally be 1. + ignore_others : bool + Whether warnings of the wrong type should be ignored (note that + the message is not checked) + function_fails : bool + If the function would normally fail, setting this will check for + warnings inside a try/except block. + exceptions : Exception or tuple of Exceptions + Exception to expect when turning the warnings into an error. + The default checks for DeprecationWarnings. If exceptions is + empty the function is expected to run successfully. + args : tuple + Arguments for `function` + kwargs : dict + Keyword arguments for `function` + """ + __tracebackhide__ = True # Hide traceback for py.test + + # reset the log + self.log[:] = [] + + if exceptions is np._NoValue: + exceptions = (self.warning_cls,) + + try: + function(*args, **kwargs) + except (Exception if function_fails else tuple()): + pass + + # just in case, clear the registry + num_found = 0 + for warning in self.log: + if warning.category is self.warning_cls: + num_found += 1 + elif not ignore_others: + raise AssertionError( + "expected %s but got: %s" % + (self.warning_cls.__name__, warning.category)) + if num is not None and num_found != num: + msg = "%i warnings found but %i expected." % (len(self.log), num) + lst = [str(w) for w in self.log] + raise AssertionError("\n".join([msg] + lst)) + + with warnings.catch_warnings(): + warnings.filterwarnings("error", message=self.message, + category=self.warning_cls) + try: + function(*args, **kwargs) + if exceptions != tuple(): + raise AssertionError( + "No error raised during function call") + except exceptions: + if exceptions == tuple(): + raise AssertionError( + "Error raised during function call") + + def assert_not_deprecated(self, function, args=(), kwargs={}): + """Test that warnings are not raised. + + This is just a shorthand for: + + self.assert_deprecated(function, num=0, ignore_others=True, + exceptions=tuple(), args=args, kwargs=kwargs) + """ + self.assert_deprecated(function, num=0, ignore_others=True, + exceptions=tuple(), args=args, kwargs=kwargs) + + +class _VisibleDeprecationTestCase(_DeprecationTestCase): + warning_cls = np.VisibleDeprecationWarning + + +class TestDatetime64Timezone(_DeprecationTestCase): + """Parsing of datetime64 with timezones deprecated in 1.11.0, because + datetime64 is now timezone naive rather than UTC only. + + It will be quite a while before we can remove this, because, at the very + least, a lot of existing code uses the 'Z' modifier to avoid conversion + from local time to UTC, even if otherwise it handles time in a timezone + naive fashion. + """ + def test_string(self): + self.assert_deprecated(np.datetime64, args=('2000-01-01T00+01',)) + self.assert_deprecated(np.datetime64, args=('2000-01-01T00Z',)) + + @pytest.mark.skipif(not _has_pytz, + reason="The pytz module is not available.") + def test_datetime(self): + tz = pytz.timezone('US/Eastern') + dt = datetime.datetime(2000, 1, 1, 0, 0, tzinfo=tz) + self.assert_deprecated(np.datetime64, args=(dt,)) + + +class TestArrayDataAttributeAssignmentDeprecation(_DeprecationTestCase): + """Assigning the 'data' attribute of an ndarray is unsafe as pointed + out in gh-7093. Eventually, such assignment should NOT be allowed, but + in the interests of maintaining backwards compatibility, only a Deprecation- + Warning will be raised instead for the time being to give developers time to + refactor relevant code. + """ + + def test_data_attr_assignment(self): + a = np.arange(10) + b = np.linspace(0, 1, 10) + + self.message = ("Assigning the 'data' attribute is an " + "inherently unsafe operation and will " + "be removed in the future.") + self.assert_deprecated(a.__setattr__, args=('data', b.data)) + + +class TestBinaryReprInsufficientWidthParameterForRepresentation(_DeprecationTestCase): + """ + If a 'width' parameter is passed into ``binary_repr`` that is insufficient to + represent the number in base 2 (positive) or 2's complement (negative) form, + the function used to silently ignore the parameter and return a representation + using the minimal number of bits needed for the form in question. Such behavior + is now considered unsafe from a user perspective and will raise an error in the future. + """ + + def test_insufficient_width_positive(self): + args = (10,) + kwargs = {'width': 2} + + self.message = ("Insufficient bit width provided. This behavior " + "will raise an error in the future.") + self.assert_deprecated(np.binary_repr, args=args, kwargs=kwargs) + + def test_insufficient_width_negative(self): + args = (-5,) + kwargs = {'width': 2} + + self.message = ("Insufficient bit width provided. This behavior " + "will raise an error in the future.") + self.assert_deprecated(np.binary_repr, args=args, kwargs=kwargs) + + +class TestDTypeAttributeIsDTypeDeprecation(_DeprecationTestCase): + # Deprecated 2021-01-05, NumPy 1.21 + message = r".*`.dtype` attribute" + + def test_deprecation_dtype_attribute_is_dtype(self): + class dt: + dtype = "f8" + + class vdt(np.void): + dtype = "f,f" + + self.assert_deprecated(lambda: np.dtype(dt)) + self.assert_deprecated(lambda: np.dtype(dt())) + self.assert_deprecated(lambda: np.dtype(vdt)) + self.assert_deprecated(lambda: np.dtype(vdt(1))) + + +class TestTestDeprecated: + def test_assert_deprecated(self): + test_case_instance = _DeprecationTestCase() + test_case_instance.setup_method() + assert_raises(AssertionError, + test_case_instance.assert_deprecated, + lambda: None) + + def foo(): + warnings.warn("foo", category=DeprecationWarning, stacklevel=2) + + test_case_instance.assert_deprecated(foo) + test_case_instance.teardown_method() + + +class TestNonNumericConjugate(_DeprecationTestCase): + """ + Deprecate no-op behavior of ndarray.conjugate on non-numeric dtypes, + which conflicts with the error behavior of np.conjugate. + """ + def test_conjugate(self): + for a in np.array(5), np.array(5j): + self.assert_not_deprecated(a.conjugate) + for a in (np.array('s'), np.array('2016', 'M'), + np.array((1, 2), [('a', int), ('b', int)])): + self.assert_deprecated(a.conjugate) + + +class TestNPY_CHAR(_DeprecationTestCase): + # 2017-05-03, 1.13.0 + def test_npy_char_deprecation(self): + from numpy.core._multiarray_tests import npy_char_deprecation + self.assert_deprecated(npy_char_deprecation) + assert_(npy_char_deprecation() == 'S1') + + +class TestPyArray_AS1D(_DeprecationTestCase): + def test_npy_pyarrayas1d_deprecation(self): + from numpy.core._multiarray_tests import npy_pyarrayas1d_deprecation + assert_raises(NotImplementedError, npy_pyarrayas1d_deprecation) + + +class TestPyArray_AS2D(_DeprecationTestCase): + def test_npy_pyarrayas2d_deprecation(self): + from numpy.core._multiarray_tests import npy_pyarrayas2d_deprecation + assert_raises(NotImplementedError, npy_pyarrayas2d_deprecation) + + +class TestDatetimeEvent(_DeprecationTestCase): + # 2017-08-11, 1.14.0 + def test_3_tuple(self): + for cls in (np.datetime64, np.timedelta64): + # two valid uses - (unit, num) and (unit, num, den, None) + self.assert_not_deprecated(cls, args=(1, ('ms', 2))) + self.assert_not_deprecated(cls, args=(1, ('ms', 2, 1, None))) + + # trying to use the event argument, removed in 1.7.0, is deprecated + # it used to be a uint8 + self.assert_deprecated(cls, args=(1, ('ms', 2, 'event'))) + self.assert_deprecated(cls, args=(1, ('ms', 2, 63))) + self.assert_deprecated(cls, args=(1, ('ms', 2, 1, 'event'))) + self.assert_deprecated(cls, args=(1, ('ms', 2, 1, 63))) + + +class TestTruthTestingEmptyArrays(_DeprecationTestCase): + # 2017-09-25, 1.14.0 + message = '.*truth value of an empty array is ambiguous.*' + + def test_1d(self): + self.assert_deprecated(bool, args=(np.array([]),)) + + def test_2d(self): + self.assert_deprecated(bool, args=(np.zeros((1, 0)),)) + self.assert_deprecated(bool, args=(np.zeros((0, 1)),)) + self.assert_deprecated(bool, args=(np.zeros((0, 0)),)) + + +class TestBincount(_DeprecationTestCase): + # 2017-06-01, 1.14.0 + def test_bincount_minlength(self): + self.assert_deprecated(lambda: np.bincount([1, 2, 3], minlength=None)) + + + +class TestGeneratorSum(_DeprecationTestCase): + # 2018-02-25, 1.15.0 + def test_generator_sum(self): + self.assert_deprecated(np.sum, args=((i for i in range(5)),)) + + +class TestFromstring(_DeprecationTestCase): + # 2017-10-19, 1.14 + def test_fromstring(self): + self.assert_deprecated(np.fromstring, args=('\x00'*80,)) + + +class TestFromStringAndFileInvalidData(_DeprecationTestCase): + # 2019-06-08, 1.17.0 + # Tests should be moved to real tests when deprecation is done. + message = "string or file could not be read to its end" + + @pytest.mark.parametrize("invalid_str", [",invalid_data", "invalid_sep"]) + def test_deprecate_unparsable_data_file(self, invalid_str): + x = np.array([1.51, 2, 3.51, 4], dtype=float) + + with tempfile.TemporaryFile(mode="w") as f: + x.tofile(f, sep=',', format='%.2f') + f.write(invalid_str) + + f.seek(0) + self.assert_deprecated(lambda: np.fromfile(f, sep=",")) + f.seek(0) + self.assert_deprecated(lambda: np.fromfile(f, sep=",", count=5)) + # Should not raise: + with warnings.catch_warnings(): + warnings.simplefilter("error", DeprecationWarning) + f.seek(0) + res = np.fromfile(f, sep=",", count=4) + assert_array_equal(res, x) + + @pytest.mark.parametrize("invalid_str", [",invalid_data", "invalid_sep"]) + def test_deprecate_unparsable_string(self, invalid_str): + x = np.array([1.51, 2, 3.51, 4], dtype=float) + x_str = "1.51,2,3.51,4{}".format(invalid_str) + + self.assert_deprecated(lambda: np.fromstring(x_str, sep=",")) + self.assert_deprecated(lambda: np.fromstring(x_str, sep=",", count=5)) + + # The C-level API can use not fixed size, but 0 terminated strings, + # so test that as well: + bytestr = x_str.encode("ascii") + self.assert_deprecated(lambda: fromstring_null_term_c_api(bytestr)) + + with assert_warns(DeprecationWarning): + # this is slightly strange, in that fromstring leaves data + # potentially uninitialized (would be good to error when all is + # read, but count is larger then actual data maybe). + res = np.fromstring(x_str, sep=",", count=5) + assert_array_equal(res[:-1], x) + + with warnings.catch_warnings(): + warnings.simplefilter("error", DeprecationWarning) + + # Should not raise: + res = np.fromstring(x_str, sep=",", count=4) + assert_array_equal(res, x) + + +class Test_GetSet_NumericOps(_DeprecationTestCase): + # 2018-09-20, 1.16.0 + def test_get_numeric_ops(self): + from numpy.core._multiarray_tests import getset_numericops + self.assert_deprecated(getset_numericops, num=2) + + # empty kwargs prevents any state actually changing which would break + # other tests. + self.assert_deprecated(np.set_numeric_ops, kwargs={}) + assert_raises(ValueError, np.set_numeric_ops, add='abc') + + +class TestShape1Fields(_DeprecationTestCase): + warning_cls = FutureWarning + + # 2019-05-20, 1.17.0 + def test_shape_1_fields(self): + self.assert_deprecated(np.dtype, args=([('a', int, 1)],)) + + +class TestNonZero(_DeprecationTestCase): + # 2019-05-26, 1.17.0 + def test_zerod(self): + self.assert_deprecated(lambda: np.nonzero(np.array(0))) + self.assert_deprecated(lambda: np.nonzero(np.array(1))) + + +class TestToString(_DeprecationTestCase): + # 2020-03-06 1.19.0 + message = re.escape("tostring() is deprecated. Use tobytes() instead.") + + def test_tostring(self): + arr = np.array(list(b"test\xFF"), dtype=np.uint8) + self.assert_deprecated(arr.tostring) + + def test_tostring_matches_tobytes(self): + arr = np.array(list(b"test\xFF"), dtype=np.uint8) + b = arr.tobytes() + with assert_warns(DeprecationWarning): + s = arr.tostring() + assert s == b + + +class TestDTypeCoercion(_DeprecationTestCase): + # 2020-02-06 1.19.0 + message = "Converting .* to a dtype .*is deprecated" + deprecated_types = [ + # The builtin scalar super types: + np.generic, np.flexible, np.number, + np.inexact, np.floating, np.complexfloating, + np.integer, np.unsignedinteger, np.signedinteger, + # character is a deprecated S1 special case: + np.character, + ] + + def test_dtype_coercion(self): + for scalar_type in self.deprecated_types: + self.assert_deprecated(np.dtype, args=(scalar_type,)) + + def test_array_construction(self): + for scalar_type in self.deprecated_types: + self.assert_deprecated(np.array, args=([], scalar_type,)) + + def test_not_deprecated(self): + # All specific types are not deprecated: + for group in np.sctypes.values(): + for scalar_type in group: + self.assert_not_deprecated(np.dtype, args=(scalar_type,)) + + for scalar_type in [type, dict, list, tuple]: + # Typical python types are coerced to object currently: + self.assert_not_deprecated(np.dtype, args=(scalar_type,)) + + +class BuiltInRoundComplexDType(_DeprecationTestCase): + # 2020-03-31 1.19.0 + deprecated_types = [np.csingle, np.cdouble, np.clongdouble] + not_deprecated_types = [ + np.int8, np.int16, np.int32, np.int64, + np.uint8, np.uint16, np.uint32, np.uint64, + np.float16, np.float32, np.float64, + ] + + def test_deprecated(self): + for scalar_type in self.deprecated_types: + scalar = scalar_type(0) + self.assert_deprecated(round, args=(scalar,)) + self.assert_deprecated(round, args=(scalar, 0)) + self.assert_deprecated(round, args=(scalar,), kwargs={'ndigits': 0}) + + def test_not_deprecated(self): + for scalar_type in self.not_deprecated_types: + scalar = scalar_type(0) + self.assert_not_deprecated(round, args=(scalar,)) + self.assert_not_deprecated(round, args=(scalar, 0)) + self.assert_not_deprecated(round, args=(scalar,), kwargs={'ndigits': 0}) + + +class TestIncorrectAdvancedIndexWithEmptyResult(_DeprecationTestCase): + # 2020-05-27, NumPy 1.20.0 + message = "Out of bound index found. This was previously ignored.*" + + @pytest.mark.parametrize("index", [([3, 0],), ([0, 0], [3, 0])]) + def test_empty_subspace(self, index): + # Test for both a single and two/multiple advanced indices. These + # This will raise an IndexError in the future. + arr = np.ones((2, 2, 0)) + self.assert_deprecated(arr.__getitem__, args=(index,)) + self.assert_deprecated(arr.__setitem__, args=(index, 0.)) + + # for this array, the subspace is only empty after applying the slice + arr2 = np.ones((2, 2, 1)) + index2 = (slice(0, 0),) + index + self.assert_deprecated(arr2.__getitem__, args=(index2,)) + self.assert_deprecated(arr2.__setitem__, args=(index2, 0.)) + + def test_empty_index_broadcast_not_deprecated(self): + arr = np.ones((2, 2, 2)) + + index = ([[3], [2]], []) # broadcast to an empty result. + self.assert_not_deprecated(arr.__getitem__, args=(index,)) + self.assert_not_deprecated(arr.__setitem__, + args=(index, np.empty((2, 0, 2)))) + + +class TestNonExactMatchDeprecation(_DeprecationTestCase): + # 2020-04-22 + def test_non_exact_match(self): + arr = np.array([[3, 6, 6], [4, 5, 1]]) + # misspelt mode check + self.assert_deprecated(lambda: np.ravel_multi_index(arr, (7, 6), mode='Cilp')) + # using completely different word with first character as R + self.assert_deprecated(lambda: np.searchsorted(arr[0], 4, side='Random')) + + +class TestMatrixInOuter(_DeprecationTestCase): + # 2020-05-13 NumPy 1.20.0 + message = (r"add.outer\(\) was passed a numpy matrix as " + r"(first|second) argument.") + + def test_deprecated(self): + arr = np.array([1, 2, 3]) + m = np.array([1, 2, 3]).view(np.matrix) + self.assert_deprecated(np.add.outer, args=(m, m), num=2) + self.assert_deprecated(np.add.outer, args=(arr, m)) + self.assert_deprecated(np.add.outer, args=(m, arr)) + self.assert_not_deprecated(np.add.outer, args=(arr, arr)) + + +class FlatteningConcatenateUnsafeCast(_DeprecationTestCase): + # NumPy 1.20, 2020-09-03 + message = "concatenate with `axis=None` will use same-kind casting" + + def test_deprecated(self): + self.assert_deprecated(np.concatenate, + args=(([0.], [1.]),), + kwargs=dict(axis=None, out=np.empty(2, dtype=np.int64))) + + def test_not_deprecated(self): + self.assert_not_deprecated(np.concatenate, + args=(([0.], [1.]),), + kwargs={'axis': None, 'out': np.empty(2, dtype=np.int64), + 'casting': "unsafe"}) + + with assert_raises(TypeError): + # Tests should notice if the deprecation warning is given first... + np.concatenate(([0.], [1.]), out=np.empty(2, dtype=np.int64), + casting="same_kind") + + +class TestDeprecatedUnpickleObjectScalar(_DeprecationTestCase): + # Deprecated 2020-11-24, NumPy 1.20 + """ + Technically, it should be impossible to create numpy object scalars, + but there was an unpickle path that would in theory allow it. That + path is invalid and must lead to the warning. + """ + message = "Unpickling a scalar with object dtype is deprecated." + + def test_deprecated(self): + ctor = np.core.multiarray.scalar + self.assert_deprecated(lambda: ctor(np.dtype("O"), 1)) + + +class TestSingleElementSignature(_DeprecationTestCase): + # Deprecated 2021-04-01, NumPy 1.21 + message = r"The use of a length 1" + + def test_deprecated(self): + self.assert_deprecated(lambda: np.add(1, 2, signature="d")) + self.assert_deprecated(lambda: np.add(1, 2, sig=(np.dtype("l"),))) + + +class TestCtypesGetter(_DeprecationTestCase): + # Deprecated 2021-05-18, Numpy 1.21.0 + warning_cls = DeprecationWarning + ctypes = np.array([1]).ctypes + + @pytest.mark.parametrize( + "name", ["get_data", "get_shape", "get_strides", "get_as_parameter"] + ) + def test_deprecated(self, name: str) -> None: + func = getattr(self.ctypes, name) + self.assert_deprecated(lambda: func()) + + @pytest.mark.parametrize( + "name", ["data", "shape", "strides", "_as_parameter_"] + ) + def test_not_deprecated(self, name: str) -> None: + self.assert_not_deprecated(lambda: getattr(self.ctypes, name)) + + +PARTITION_DICT = { + "partition method": np.arange(10).partition, + "argpartition method": np.arange(10).argpartition, + "partition function": lambda kth: np.partition(np.arange(10), kth), + "argpartition function": lambda kth: np.argpartition(np.arange(10), kth), +} + + +@pytest.mark.parametrize("func", PARTITION_DICT.values(), ids=PARTITION_DICT) +class TestPartitionBoolIndex(_DeprecationTestCase): + # Deprecated 2021-09-29, NumPy 1.22 + warning_cls = DeprecationWarning + message = "Passing booleans as partition index is deprecated" + + def test_deprecated(self, func): + self.assert_deprecated(lambda: func(True)) + self.assert_deprecated(lambda: func([False, True])) + + def test_not_deprecated(self, func): + self.assert_not_deprecated(lambda: func(1)) + self.assert_not_deprecated(lambda: func([0, 1])) + + +class TestMachAr(_DeprecationTestCase): + # Deprecated 2022-11-22, NumPy 1.25 + warning_cls = DeprecationWarning + + def test_deprecated_module(self): + self.assert_deprecated(lambda: getattr(np.core, "MachAr")) + + +class TestQuantileInterpolationDeprecation(_DeprecationTestCase): + # Deprecated 2021-11-08, NumPy 1.22 + @pytest.mark.parametrize("func", + [np.percentile, np.quantile, np.nanpercentile, np.nanquantile]) + def test_deprecated(self, func): + self.assert_deprecated( + lambda: func([0., 1.], 0., interpolation="linear")) + self.assert_deprecated( + lambda: func([0., 1.], 0., interpolation="nearest")) + + @pytest.mark.parametrize("func", + [np.percentile, np.quantile, np.nanpercentile, np.nanquantile]) + def test_both_passed(self, func): + with warnings.catch_warnings(): + # catch the DeprecationWarning so that it does not raise: + warnings.simplefilter("always", DeprecationWarning) + with pytest.raises(TypeError): + func([0., 1.], 0., interpolation="nearest", method="nearest") + + +class TestMemEventHook(_DeprecationTestCase): + # Deprecated 2021-11-18, NumPy 1.23 + def test_mem_seteventhook(self): + # The actual tests are within the C code in + # multiarray/_multiarray_tests.c.src + import numpy.core._multiarray_tests as ma_tests + with pytest.warns(DeprecationWarning, + match='PyDataMem_SetEventHook is deprecated'): + ma_tests.test_pydatamem_seteventhook_start() + # force an allocation and free of a numpy array + # needs to be larger then limit of small memory cacher in ctors.c + a = np.zeros(1000) + del a + break_cycles() + with pytest.warns(DeprecationWarning, + match='PyDataMem_SetEventHook is deprecated'): + ma_tests.test_pydatamem_seteventhook_end() + + +class TestArrayFinalizeNone(_DeprecationTestCase): + message = "Setting __array_finalize__ = None" + + def test_use_none_is_deprecated(self): + # Deprecated way that ndarray itself showed nothing needs finalizing. + class NoFinalize(np.ndarray): + __array_finalize__ = None + + self.assert_deprecated(lambda: np.array(1).view(NoFinalize)) + +class TestAxisNotMAXDIMS(_DeprecationTestCase): + # Deprecated 2022-01-08, NumPy 1.23 + message = r"Using `axis=32` \(MAXDIMS\) is deprecated" + + def test_deprecated(self): + a = np.zeros((1,)*32) + self.assert_deprecated(lambda: np.repeat(a, 1, axis=np.MAXDIMS)) + + +class TestLoadtxtParseIntsViaFloat(_DeprecationTestCase): + # Deprecated 2022-07-03, NumPy 1.23 + # This test can be removed without replacement after the deprecation. + # The tests: + # * numpy/lib/tests/test_loadtxt.py::test_integer_signs + # * lib/tests/test_loadtxt.py::test_implicit_cast_float_to_int_fails + # Have a warning filter that needs to be removed. + message = r"loadtxt\(\): Parsing an integer via a float is deprecated.*" + + @pytest.mark.parametrize("dtype", np.typecodes["AllInteger"]) + def test_deprecated_warning(self, dtype): + with pytest.warns(DeprecationWarning, match=self.message): + np.loadtxt(["10.5"], dtype=dtype) + + @pytest.mark.parametrize("dtype", np.typecodes["AllInteger"]) + def test_deprecated_raised(self, dtype): + # The DeprecationWarning is chained when raised, so test manually: + with warnings.catch_warnings(): + warnings.simplefilter("error", DeprecationWarning) + try: + np.loadtxt(["10.5"], dtype=dtype) + except ValueError as e: + assert isinstance(e.__cause__, DeprecationWarning) + + +class TestScalarConversion(_DeprecationTestCase): + # 2023-01-02, 1.25.0 + def test_float_conversion(self): + self.assert_deprecated(float, args=(np.array([3.14]),)) + + def test_behaviour(self): + b = np.array([[3.14]]) + c = np.zeros(5) + with pytest.warns(DeprecationWarning): + c[0] = b + + +class TestPyIntConversion(_DeprecationTestCase): + message = r".*stop allowing conversion of out-of-bound.*" + + @pytest.mark.parametrize("dtype", np.typecodes["AllInteger"]) + def test_deprecated_scalar(self, dtype): + dtype = np.dtype(dtype) + info = np.iinfo(dtype) + + # Cover the most common creation paths (all end up in the + # same place): + def scalar(value, dtype): + dtype.type(value) + + def assign(value, dtype): + arr = np.array([0, 0, 0], dtype=dtype) + arr[2] = value + + def create(value, dtype): + np.array([value], dtype=dtype) + + for creation_func in [scalar, assign, create]: + try: + self.assert_deprecated( + lambda: creation_func(info.min - 1, dtype)) + except OverflowError: + pass # OverflowErrors always happened also before and are OK. + + try: + self.assert_deprecated( + lambda: creation_func(info.max + 1, dtype)) + except OverflowError: + pass # OverflowErrors always happened also before and are OK. + + +class TestDeprecatedGlobals(_DeprecationTestCase): + # Deprecated 2022-11-17, NumPy 1.24 + def test_type_aliases(self): + # from builtins + self.assert_deprecated(lambda: np.bool8) + self.assert_deprecated(lambda: np.int0) + self.assert_deprecated(lambda: np.uint0) + self.assert_deprecated(lambda: np.bytes0) + self.assert_deprecated(lambda: np.str0) + self.assert_deprecated(lambda: np.object0) + + +@pytest.mark.parametrize("name", + ["bool", "long", "ulong", "str", "bytes", "object"]) +def test_future_scalar_attributes(name): + # FutureWarning added 2022-11-17, NumPy 1.24, + assert name not in dir(np) # we may want to not add them + with pytest.warns(FutureWarning, + match=f"In the future .*{name}"): + assert not hasattr(np, name) + + # Unfortunately, they are currently still valid via `np.dtype()` + np.dtype(name) + name in np.sctypeDict + + +# Ignore the above future attribute warning for this test. +@pytest.mark.filterwarnings("ignore:In the future:FutureWarning") +class TestRemovedGlobals: + # Removed 2023-01-12, NumPy 1.24.0 + # Not a deprecation, but the large error was added to aid those who missed + # the previous deprecation, and should be removed similarly to one + # (or faster). + @pytest.mark.parametrize("name", + ["object", "bool", "float", "complex", "str", "int"]) + def test_attributeerror_includes_info(self, name): + msg = f".*\n`np.{name}` was a deprecated alias for the builtin" + with pytest.raises(AttributeError, match=msg): + getattr(np, name) + + +class TestDeprecatedFinfo(_DeprecationTestCase): + # Deprecated in NumPy 1.25, 2023-01-16 + def test_deprecated_none(self): + self.assert_deprecated(np.finfo, args=(None,)) + +class TestFromnumeric(_DeprecationTestCase): + # 2023-02-28, 1.25.0 + def test_round_(self): + self.assert_deprecated(lambda: np.round_(np.array([1.5, 2.5, 3.5]))) + + # 2023-03-02, 1.25.0 + def test_cumproduct(self): + self.assert_deprecated(lambda: np.cumproduct(np.array([1, 2, 3]))) + + # 2023-03-02, 1.25.0 + def test_product(self): + self.assert_deprecated(lambda: np.product(np.array([1, 2, 3]))) + + # 2023-03-02, 1.25.0 + def test_sometrue(self): + self.assert_deprecated(lambda: np.sometrue(np.array([True, False]))) + + # 2023-03-02, 1.25.0 + def test_alltrue(self): + self.assert_deprecated(lambda: np.alltrue(np.array([True, False]))) + + +class TestMathAlias(_DeprecationTestCase): + # Deprecated in Numpy 1.25, 2023-04-06 + def test_deprecated_np_math(self): + self.assert_deprecated(lambda: np.math) + + def test_deprecated_np_lib_math(self): + self.assert_deprecated(lambda: np.lib.math) |