Python numpy.negative方法代碼示例

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import negative [as 別名]
def test_spacing_nextafter(self):
        """Test np.spacing and np.nextafter"""
        # All non-negative finite #'s
        a = np.arange(0x7c00, dtype=uint16)
        hinf = np.array((np.inf,), dtype=float16)
        a_f16 = a.view(dtype=float16)

        assert_equal(np.spacing(a_f16[:-1]), a_f16[1:]-a_f16[:-1])

        assert_equal(np.nextafter(a_f16[:-1], hinf), a_f16[1:])
        assert_equal(np.nextafter(a_f16[0], -hinf), -a_f16[1])
        assert_equal(np.nextafter(a_f16[1:], -hinf), a_f16[:-1])

        # switch to negatives
        a |= 0x8000

        assert_equal(np.spacing(a_f16[0]), np.spacing(a_f16[1]))
        assert_equal(np.spacing(a_f16[1:]), a_f16[:-1]-a_f16[1:])

        assert_equal(np.nextafter(a_f16[0], hinf), -a_f16[1])
        assert_equal(np.nextafter(a_f16[1:], hinf), a_f16[:-1])
        assert_equal(np.nextafter(a_f16[:-1], -hinf), a_f16[1:]) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import negative [as 別名]
def test_endian(self):
        msg = "big endian"
        a = np.arange(6, dtype='>i4').reshape((2, 3))
        assert_array_equal(umt.inner1d(a, a), np.sum(a*a, axis=-1),
                           err_msg=msg)
        msg = "little endian"
        a = np.arange(6, dtype='<i4').reshape((2, 3))
        assert_array_equal(umt.inner1d(a, a), np.sum(a*a, axis=-1),
                           err_msg=msg)

        # Output should always be native-endian
        Ba = np.arange(1, dtype='>f8')
        La = np.arange(1, dtype='<f8')
        assert_equal((Ba+Ba).dtype, np.dtype('f8'))
        assert_equal((Ba+La).dtype, np.dtype('f8'))
        assert_equal((La+Ba).dtype, np.dtype('f8'))
        assert_equal((La+La).dtype, np.dtype('f8'))

        assert_equal(np.absolute(La).dtype, np.dtype('f8'))
        assert_equal(np.absolute(Ba).dtype, np.dtype('f8'))
        assert_equal(np.negative(La).dtype, np.dtype('f8'))
        assert_equal(np.negative(Ba).dtype, np.dtype('f8')) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import negative [as 別名]
def test_ufunc_override_not_implemented(self):

        class A(object):
            def __array_ufunc__(self, *args, **kwargs):
                return NotImplemented

        msg = ("operand type(s) all returned NotImplemented from "
               "__array_ufunc__(<ufunc 'negative'>, '__call__', <*>): 'A'")
        with assert_raises_regex(TypeError, fnmatch.translate(msg)):
            np.negative(A())

        msg = ("operand type(s) all returned NotImplemented from "
               "__array_ufunc__(<ufunc 'add'>, '__call__', <*>, <object *>, "
               "out=(1,)): 'A', 'object', 'int'")
        with assert_raises_regex(TypeError, fnmatch.translate(msg)):
            np.add(A(), object(), out=1) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import negative [as 別名]
def _lowess_tricube(t):
    """
    The _tricube function applied to a numpy array.
    The tricube function is (1-abs(t)**3)**3.

    Parameters
    ----------
    t : ndarray
        Array the tricube function is applied to elementwise and
        in-place.

    Returns
    -------
    Nothing
    """
    #t = (1-np.abs(t)**3)**3
    t[:] = np.absolute(t) #, out=t) #numpy version?
    _lowess_mycube(t)
    t[:] = np.negative(t) #, out = t)
    t += 1
    _lowess_mycube(t) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import negative [as 別名]
def _lowess_bisquare(t):
    """
    The bisquare function applied to a numpy array.
    The bisquare function is (1-t**2)**2.

    Parameters
    ----------
    t : ndarray
        array bisquare function is applied to, element-wise and in-place.

    Returns
    -------
    Nothing

    """
    #t = (1-t**2)**2
    t *= t
    t[:] = np.negative(t) #, out=t)
    t += 1
    t *= t 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import negative [as 別名]
def test_string_parser_variants(self):
        # Allow space instead of 'T' between date and time
        assert_equal(np.array(['1980-02-29T01:02:03'], np.dtype('M8[s]')),
                     np.array(['1980-02-29 01:02:03'], np.dtype('M8[s]')))
        # Allow negative years
        assert_equal(np.array(['-1980-02-29T01:02:03'], np.dtype('M8[s]')),
                     np.array(['-1980-02-29 01:02:03'], np.dtype('M8[s]')))
        # UTC specifier
        assert_equal(np.array(['-1980-02-29T01:02:03Z'], np.dtype('M8[s]')),
                     np.array(['-1980-02-29 01:02:03Z'], np.dtype('M8[s]')))
        # Time zone offset
        assert_equal(np.array(['1980-02-29T02:02:03Z'], np.dtype('M8[s]')),
                     np.array(['1980-02-29 00:32:03-0130'], np.dtype('M8[s]')))
        assert_equal(np.array(['1980-02-28T22:32:03Z'], np.dtype('M8[s]')),
                     np.array(['1980-02-29 00:02:03+01:30'], np.dtype('M8[s]')))
        assert_equal(np.array(['1980-02-29T02:32:03.506Z'], np.dtype('M8[s]')),
                 np.array(['1980-02-29 00:32:03.506-02'], np.dtype('M8[s]')))
        assert_equal(np.datetime64('1977-03-02T12:30-0230'),
                     np.datetime64('1977-03-02T15:00Z')) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import negative [as 別名]
def __neg__(self):
        name = "Neg({})".format(self.name)
        return self.apply(np.negative).rename(name) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import negative [as 別名]
def test_datetime_unary(self):
        for tda, tdb, tdzero, tdone, tdmone in \
                [
                 # One-dimensional arrays
                 (np.array([3], dtype='m8[D]'),
                  np.array([-3], dtype='m8[D]'),
                  np.array([0], dtype='m8[D]'),
                  np.array([1], dtype='m8[D]'),
                  np.array([-1], dtype='m8[D]')),
                 # NumPy scalars
                 (np.timedelta64(3, '[D]'),
                  np.timedelta64(-3, '[D]'),
                  np.timedelta64(0, '[D]'),
                  np.timedelta64(1, '[D]'),
                  np.timedelta64(-1, '[D]'))]:
            # negative ufunc
            assert_equal(-tdb, tda)
            assert_equal((-tdb).dtype, tda.dtype)
            assert_equal(np.negative(tdb), tda)
            assert_equal(np.negative(tdb).dtype, tda.dtype)

            # positive ufunc
            assert_equal(np.positive(tda), tda)
            assert_equal(np.positive(tda).dtype, tda.dtype)
            assert_equal(np.positive(tdb), tdb)
            assert_equal(np.positive(tdb).dtype, tdb.dtype)

            # absolute ufunc
            assert_equal(np.absolute(tdb), tda)
            assert_equal(np.absolute(tdb).dtype, tda.dtype)

            # sign ufunc
            assert_equal(np.sign(tda), tdone)
            assert_equal(np.sign(tdb), tdmone)
            assert_equal(np.sign(tdzero), tdzero)
            assert_equal(np.sign(tda).dtype, tda.dtype)

            # The ufuncs always produce native-endian results
            assert_ 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import negative [as 別名]
def test_string_parser_variants(self):
        # Allow space instead of 'T' between date and time
        assert_equal(np.array(['1980-02-29T01:02:03'], np.dtype('M8[s]')),
                     np.array(['1980-02-29 01:02:03'], np.dtype('M8[s]')))
        # Allow positive years
        assert_equal(np.array(['+1980-02-29T01:02:03'], np.dtype('M8[s]')),
                     np.array(['+1980-02-29 01:02:03'], np.dtype('M8[s]')))
        # Allow negative years
        assert_equal(np.array(['-1980-02-29T01:02:03'], np.dtype('M8[s]')),
                     np.array(['-1980-02-29 01:02:03'], np.dtype('M8[s]')))
        # UTC specifier
        with assert_warns(DeprecationWarning):
            assert_equal(
                np.array(['+1980-02-29T01:02:03'], np.dtype('M8[s]')),
                np.array(['+1980-02-29 01:02:03Z'], np.dtype('M8[s]')))
        with assert_warns(DeprecationWarning):
            assert_equal(
                np.array(['-1980-02-29T01:02:03'], np.dtype('M8[s]')),
                np.array(['-1980-02-29 01:02:03Z'], np.dtype('M8[s]')))
        # Time zone offset
        with assert_warns(DeprecationWarning):
            assert_equal(
                np.array(['1980-02-29T02:02:03'], np.dtype('M8[s]')),
                np.array(['1980-02-29 00:32:03-0130'], np.dtype('M8[s]')))
        with assert_warns(DeprecationWarning):
            assert_equal(
                np.array(['1980-02-28T22:32:03'], np.dtype('M8[s]')),
                np.array(['1980-02-29 00:02:03+01:30'], np.dtype('M8[s]')))
        with assert_warns(DeprecationWarning):
            assert_equal(
                np.array(['1980-02-29T02:32:03.506'], np.dtype('M8[s]')),
                np.array(['1980-02-29 00:32:03.506-02'], np.dtype('M8[s]')))
        with assert_warns(DeprecationWarning):
            assert_equal(np.datetime64('1977-03-02T12:30-0230'),
                         np.datetime64('1977-03-02T15:00')) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import negative [as 別名]
def test_datetime_busday_holidays_count(self):
        holidays = ['2011-01-01', '2011-10-10', '2011-11-11', '2011-11-24',
                    '2011-12-25', '2011-05-30', '2011-02-21', '2011-01-17',
                    '2011-12-26', '2012-01-02', '2011-02-21', '2011-05-30',
                    '2011-07-01', '2011-07-04', '2011-09-05', '2011-10-10']
        bdd = np.busdaycalendar(weekmask='1111100', holidays=holidays)

        # Validate against busday_offset broadcast against
        # a range of offsets
        dates = np.busday_offset('2011-01-01', np.arange(366),
                        roll='forward', busdaycal=bdd)
        assert_equal(np.busday_count('2011-01-01', dates, busdaycal=bdd),
                     np.arange(366))
        # Returns negative value when reversed
        assert_equal(np.busday_count(dates, '2011-01-01', busdaycal=bdd),
                     -np.arange(366))

        dates = np.busday_offset('2011-12-31', -np.arange(366),
                        roll='forward', busdaycal=bdd)
        assert_equal(np.busday_count(dates, '2011-12-31', busdaycal=bdd),
                     np.arange(366))
        # Returns negative value when reversed
        assert_equal(np.busday_count('2011-12-31', dates, busdaycal=bdd),
                     -np.arange(366))

        # Can't supply both a weekmask/holidays and busdaycal
        assert_raises(ValueError, np.busday_offset, '2012-01-03', '2012-02-03',
                        weekmask='1111100', busdaycal=bdd)
        assert_raises(ValueError, np.busday_offset, '2012-01-03', '2012-02-03',
                        holidays=holidays, busdaycal=bdd)

        # Number of Mondays in March 2011
        assert_equal(np.busday_count('2011-03', '2011-04', weekmask='Mon'), 4)
        # Returns negative value when reversed
        assert_equal(np.busday_count('2011-04', '2011-03', weekmask='Mon'), -4) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import negative [as 別名]
def test_floor_division_signed_zero(self):
        # Check that the sign bit is correctly set when dividing positive and
        # negative zero by one.
        x = np.zeros(10)
        assert_equal(np.signbit(x//1), 0)
        assert_equal(np.signbit((-x)//1), 1) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import negative [as 別名]
def test_power_zero(self):
        # ticket #1271
        zero = np.array([0j])
        one = np.array([1+0j])
        cnan = np.array([complex(np.nan, np.nan)])
        # FIXME cinf not tested.
        #cinf = np.array([complex(np.inf, 0)])

        def assert_complex_equal(x, y):
            x, y = np.asarray(x), np.asarray(y)
            assert_array_equal(x.real, y.real)
            assert_array_equal(x.imag, y.imag)

        # positive powers
        for p in [0.33, 0.5, 1, 1.5, 2, 3, 4, 5, 6.6]:
            assert_complex_equal(np.power(zero, p), zero)

        # zero power
        assert_complex_equal(np.power(zero, 0), one)
        with np.errstate(invalid="ignore"):
            assert_complex_equal(np.power(zero, 0+1j), cnan)

            # negative power
            for p in [0.33, 0.5, 1, 1.5, 2, 3, 4, 5, 6.6]:
                assert_complex_equal(np.power(zero, -p), cnan)
            assert_complex_equal(np.power(zero, -1+0.2j), cnan) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import negative [as 別名]
def test_exceptions(self):
        a = np.ones(1, dtype=np.bool_)
        assert_raises(TypeError, np.negative, a)
        assert_raises(TypeError, np.positive, a)
        assert_raises(TypeError, np.subtract, a, a) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import negative [as 別名]
def test_abs_neg_blocked(self):
        # simd tests on abs, test all alignments for vz + 2 * (vs - 1) + 1
        for dt, sz in [(np.float32, 11), (np.float64, 5)]:
            for out, inp, msg in _gen_alignment_data(dtype=dt, type='unary',
                                                     max_size=sz):
                tgt = [ncu.absolute(i) for i in inp]
                np.absolute(inp, out=out)
                assert_equal(out, tgt, err_msg=msg)
                assert_((out >= 0).all())

                tgt = [-1*(i) for i in inp]
                np.negative(inp, out=out)
                assert_equal(out, tgt, err_msg=msg)

                for v in [np.nan, -np.inf, np.inf]:
                    for i in range(inp.size):
                        d = np.arange(inp.size, dtype=dt)
                        inp[:] = -d
                        inp[i] = v
                        d[i] = -v if v == -np.inf else v
                        assert_array_equal(np.abs(inp), d, err_msg=msg)
                        np.abs(inp, out=out)
                        assert_array_equal(out, d, err_msg=msg)

                        assert_array_equal(-inp, -1*inp, err_msg=msg)
                        d = -1 * inp
                        np.negative(inp, out=out)
                        assert_array_equal(out, d, err_msg=msg) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import negative [as 別名]
def test_lower_align(self):
        # check data that is not aligned to element size
        # i.e doubles are aligned to 4 bytes on i386
        d = np.zeros(23 * 8, dtype=np.int8)[4:-4].view(np.float64)
        assert_equal(np.abs(d), d)
        assert_equal(np.negative(d), -d)
        np.negative(d, out=d)
        np.negative(np.ones_like(d), out=d)
        np.abs(d, out=d)
        np.abs(np.ones_like(d), out=d)