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Current File : //opt/alt/python37/lib64/python3.7/site-packages/numpy/core/tests/test_deprecations.py

"""
Tests related to deprecation warnings. Also a convenient place
to document how deprecations should eventually be turned into errors.

"""
from __future__ import division, absolute_import, print_function

import datetime
import sys
import operator
import warnings

import numpy as np
from numpy.testing import (
    run_module_suite, assert_raises, assert_warns, assert_no_warnings,
    assert_array_equal, assert_, dec)

try:
    import pytz
    _has_pytz = True
except ImportError:
    _has_pytz = False


class _DeprecationTestCase(object):
    # Just as warning: warnings uses re.match, so the start of this message
    # must match.
    message = ''
    warning_cls = DeprecationWarning

    def setUp(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
        # http://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(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`
        """
        # 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.category) 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 TestBooleanBinaryMinusDeprecation(_DeprecationTestCase):
    """Test deprecation of binary boolean `-`. While + and * are well
    defined, binary  - is not and even a corrected form seems to have
    no real uses.

    The deprecation process was started in NumPy 1.9.
    """
    message = r"numpy boolean subtract, the `-` operator, .*"

    def test_operator_deprecation(self):
        array = np.array([True])
        generic = np.bool_(True)

        # Minus operator/subtract ufunc:
        self.assert_deprecated(operator.sub, args=(array, array))
        self.assert_deprecated(operator.sub, args=(generic, generic))


class TestRankDeprecation(_DeprecationTestCase):
    """Test that np.rank is deprecated. The function should simply be
    removed. The VisibleDeprecationWarning may become unnecessary.
    """

    def test(self):
        a = np.arange(10)
        assert_warns(np.VisibleDeprecationWarning, np.rank, a)


class TestComparisonDeprecations(_DeprecationTestCase):
    """This tests the deprecation, for non-element-wise comparison logic.
    This used to mean that when an error occurred during element-wise comparison
    (i.e. broadcasting) NotImplemented was returned, but also in the comparison
    itself, False was given instead of the error.

    Also test FutureWarning for the None comparison.
    """

    message = "elementwise.* comparison failed; .*"

    def test_normal_types(self):
        for op in (operator.eq, operator.ne):
            # Broadcasting errors:
            self.assert_deprecated(op, args=(np.zeros(3), []))
            a = np.zeros(3, dtype='i,i')
            # (warning is issued a couple of times here)
            self.assert_deprecated(op, args=(a, a[:-1]), num=None)

            # Element comparison error (numpy array can't be compared).
            a = np.array([1, np.array([1,2,3])], dtype=object)
            b = np.array([1, np.array([1,2,3])], dtype=object)
            self.assert_deprecated(op, args=(a, b), num=None)

    def test_string(self):
        # For two string arrays, strings always raised the broadcasting error:
        a = np.array(['a', 'b'])
        b = np.array(['a', 'b', 'c'])
        assert_raises(ValueError, lambda x, y: x == y, a, b)

        # The empty list is not cast to string, as this is only to document
        # that fact (it likely should be changed). This means that the
        # following works (and returns False) due to dtype mismatch:
        a == []

    def test_void_dtype_equality_failures(self):
        class NotArray(object):
            def __array__(self):
                raise TypeError

            # Needed so Python 3 does not raise DeprecationWarning twice.
            def __ne__(self, other):
                return NotImplemented

        self.assert_deprecated(lambda: np.arange(2) == NotArray())
        self.assert_deprecated(lambda: np.arange(2) != NotArray())

        struct1 = np.zeros(2, dtype="i4,i4")
        struct2 = np.zeros(2, dtype="i4,i4,i4")

        assert_warns(FutureWarning, lambda: struct1 == 1)
        assert_warns(FutureWarning, lambda: struct1 == struct2)
        assert_warns(FutureWarning, lambda: struct1 != 1)
        assert_warns(FutureWarning, lambda: struct1 != struct2)

    def test_array_richcompare_legacy_weirdness(self):
        # It doesn't really work to use assert_deprecated here, b/c part of
        # the point of assert_deprecated is to check that when warnings are
        # set to "error" mode then the error is propagated -- which is good!
        # But here we are testing a bunch of code that is deprecated *because*
        # it has the habit of swallowing up errors and converting them into
        # different warnings. So assert_warns will have to be sufficient.
        assert_warns(FutureWarning, lambda: np.arange(2) == "a")
        assert_warns(FutureWarning, lambda: np.arange(2) != "a")
        # No warning for scalar comparisons
        with warnings.catch_warnings():
            warnings.filterwarnings("error")
            assert_(not (np.array(0) == "a"))
            assert_(np.array(0) != "a")
            assert_(not (np.int16(0) == "a"))
            assert_(np.int16(0) != "a")

        for arg1 in [np.asarray(0), np.int16(0)]:
            struct = np.zeros(2, dtype="i4,i4")
            for arg2 in [struct, "a"]:
                for f in [operator.lt, operator.le, operator.gt, operator.ge]:
                    if sys.version_info[0] >= 3:
                        # py3
                        with warnings.catch_warnings() as l:
                            warnings.filterwarnings("always")
                            assert_raises(TypeError, f, arg1, arg2)
                            assert_(not l)
                    else:
                        # py2
                        assert_warns(DeprecationWarning, f, arg1, arg2)


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',))

    @dec.skipif(not _has_pytz, "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 TestNonCContiguousViewDeprecation(_DeprecationTestCase):
    """View of non-C-contiguous arrays deprecated in 1.11.0.

    The deprecation will not be raised for arrays that are both C and F
    contiguous, as C contiguous is dominant. There are more such arrays
    with relaxed stride checking than without so the deprecation is not
    as visible with relaxed stride checking in force.
    """

    def test_fortran_contiguous(self):
        self.assert_deprecated(np.ones((2,2)).T.view, args=(np.complex,))
        self.assert_deprecated(np.ones((2,2)).T.view, args=(np.int8,))


class TestInvalidOrderParameterInputForFlattenArrayDeprecation(_DeprecationTestCase):
    """Invalid arguments to the ORDER parameter in array.flatten() should not be
    allowed and should raise an error.  However, in the interests of not breaking
    code that may inadvertently pass invalid arguments to this parameter, a
    DeprecationWarning will be issued instead for the time being to give developers
    time to refactor relevant code.
    """

    def test_flatten_array_non_string_arg(self):
        x = np.zeros((3, 5))
        self.message = ("Non-string object detected for "
                        "the array ordering. Please pass "
                        "in 'C', 'F', 'A', or 'K' instead")
        self.assert_deprecated(x.flatten, args=(np.pi,))

    def test_flatten_array_invalid_string_arg(self):
        # Tests that a DeprecationWarning is raised
        # when a string of length greater than one
        # starting with "C", "F", "A", or "K" (case-
        # and unicode-insensitive) is passed in for
        # the ORDER parameter. Otherwise, a TypeError
        # will be raised!

        x = np.zeros((3, 5))
        self.message = ("Non length-one string passed "
                        "in for the array ordering. Please "
                        "pass in 'C', 'F', 'A', or 'K' instead")
        self.assert_deprecated(x.flatten, args=("FACK",))


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 TestLinspaceInvalidNumParameter(_DeprecationTestCase):
    """Argument to the num parameter in linspace that cannot be
    safely interpreted as an integer is deprecated in 1.12.0.

    Argument to the num parameter in linspace that cannot be
    safely interpreted as an integer should not be allowed.
    In the interest of not breaking code that passes
    an argument that could still be interpreted as an integer, a
    DeprecationWarning will be issued for the time being to give
    developers time to refactor relevant code.
    """
    def test_float_arg(self):
        # 2016-02-25, PR#7328
        self.assert_deprecated(np.linspace, args=(0, 10, 2.5))


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 TestNumericStyleTypecodes(_DeprecationTestCase):
    """
    Deprecate the old numeric-style dtypes, which are especially
    confusing for complex types, e.g. Complex32 -> complex64. When the
    deprecation cycle is complete, the check for the strings should be
    removed from PyArray_DescrConverter in descriptor.c, and the
    deprecated keys should not be added as capitalized aliases in
    _add_aliases in numerictypes.py.
    """
    def test_all_dtypes(self):
        deprecated_types = [
            'Bool', 'Complex32', 'Complex64', 'Float16', 'Float32', 'Float64',
            'Int8', 'Int16', 'Int32', 'Int64', 'Object0', 'Timedelta64',
            'UInt8', 'UInt16', 'UInt32', 'UInt64', 'Void0'
            ]
        if sys.version_info[0] < 3:
            deprecated_types.extend(['Unicode0', 'String0'])

        for dt in deprecated_types:
            self.assert_deprecated(np.dtype, exceptions=(TypeError,),
                                   args=(dt,))


class TestAccumulateKeepDims(_DeprecationTestCase):
    """
    Deprecate the keepdims argument to np.ufunc.accumulate, which was never used or documented
    """
    def test_keepdims(self):
        with warnings.catch_warnings():
            warnings.filterwarnings('always', '', FutureWarning)
            assert_warns(FutureWarning, np.add.accumulate, [1], keepdims=True)


class TestTestDeprecated(object):
    def test_assert_deprecated(self):
        test_case_instance = _DeprecationTestCase()
        test_case_instance.setUp()
        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()


class TestClassicIntDivision(_DeprecationTestCase):
    """
    See #7949. Deprecate the numeric-style dtypes with -3 flag in python 2
    if used for division
    List of data types: http://docs.scipy.org/doc/numpy/user/basics.types.html
    """
    def test_int_dtypes(self):
        #scramble types and do some mix and match testing
        deprecated_types = [
           'bool_', 'int_', 'intc', 'uint8', 'int8', 'uint64', 'int32', 'uint16',
           'intp', 'int64', 'uint32', 'int16'
            ]
        if sys.version_info[0] < 3 and sys.py3kwarning:
            import operator as op
            dt2 = 'bool_'
            for dt1 in deprecated_types:
                a = np.array([1,2,3], dtype=dt1)
                b = np.array([1,2,3], dtype=dt2)
                self.assert_deprecated(op.div, args=(a,b))
                dt2 = dt1


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')


if __name__ == "__main__":
    run_module_suite()

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