Python numpy.not_equal() 使用实例

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Example 1

def test_mask_value(self):
        result = self.model.predict(self.data)
        np.testing.assert_array_almost_equal(
            result[:, 1:, :],
            np.zeros((
                self.data_size,
                self.max_length - 1,
                self.encoding_size
            ))
        )
        np.testing.assert_equal(
            np.any(
                np.not_equal(
                    result[:, 0:1, self.cell_units:],
                    np.zeros((self.data_size, 1, self.cell_units))
                )
            ),
            True
        ) 

Example 2

def equal(x1, x2):
    """
    Return (x1 == x2) element-wise.

    Unlike `numpy.equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    not_equal, greater_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '==', True) 

Example 3

def not_equal(x1, x2):
    """
    Return (x1 != x2) element-wise.

    Unlike `numpy.not_equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, greater_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '!=', True) 

Example 4

def greater_equal(x1, x2):
    """
    Return (x1 >= x2) element-wise.

    Unlike `numpy.greater_equal`, this comparison is performed by
    first stripping whitespace characters from the end of the string.
    This behavior is provided for backward-compatibility with
    numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '>=', True) 

Example 5

def less_equal(x1, x2):
    """
    Return (x1 <= x2) element-wise.

    Unlike `numpy.less_equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, greater_equal, greater, less
    """
    return compare_chararrays(x1, x2, '<=', True) 

Example 6

def greater(x1, x2):
    """
    Return (x1 > x2) element-wise.

    Unlike `numpy.greater`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, greater_equal, less_equal, less
    """
    return compare_chararrays(x1, x2, '>', True) 

Example 7

def test_truth_table_logical(self):
        # 2, 3 and 4 serves as true values
        input1 = [0, 0, 3, 2]
        input2 = [0, 4, 0, 2]

        typecodes = (np.typecodes['AllFloat']
                     + np.typecodes['AllInteger']
                     + '?')     # boolean
        for dtype in map(np.dtype, typecodes):
            arg1 = np.asarray(input1, dtype=dtype)
            arg2 = np.asarray(input2, dtype=dtype)

            # OR
            out = [False, True, True, True]
            for func in (np.logical_or, np.maximum):
                assert_equal(func(arg1, arg2).astype(bool), out)
            # AND
            out = [False, False, False, True]
            for func in (np.logical_and, np.minimum):
                assert_equal(func(arg1, arg2).astype(bool), out)
            # XOR
            out = [False, True, True, False]
            for func in (np.logical_xor, np.not_equal):
                assert_equal(func(arg1, arg2).astype(bool), out) 

Example 8

def test_identity_equality_mismatch(self):
        a = np.array([np.nan], dtype=object)

        with warnings.catch_warnings():
            warnings.filterwarnings('always', '', FutureWarning)
            assert_warns(FutureWarning, np.equal, a, a)
            assert_warns(FutureWarning, np.not_equal, a, a)

        with warnings.catch_warnings():
            warnings.filterwarnings('error', '', FutureWarning)
            assert_raises(FutureWarning, np.equal, a, a)
            assert_raises(FutureWarning, np.not_equal, a, a)
            # And the other do not warn:
            with np.errstate(invalid='ignore'):
                np.less(a, a)
                np.greater(a, a)
                np.less_equal(a, a)
                np.greater_equal(a, a) 

Example 9

def testCplxNotEqualGPU(self):
        shapes1 = [(5,4,3), (5,4), (1,), (5,)]
        shapes2 = [(5,4,3), (1,), (5,4), (5,)]
        for [sh0, sh1] in zip(shapes1, shapes2):
            x = (np.random.randn(np.prod(sh0)) +
                 1j*np.random.randn(np.prod(sh0))).astype(np.complex64)
            y = (np.random.randn(np.prod(sh1)) +
                 1j*np.random.randn(np.prod(sh1))).astype(np.complex64)
            if len(sh0) == 1:
                ix = np.random.permutation(
                    np.arange(np.prod(sh1)))[:np.prod(sh1)//2]
                y[ix] = x[0]
            elif len(sh1) == 1:
                ix = np.random.permutation(
                    np.arange(np.prod(sh0)))[:np.prod(sh0)//2]
                x[ix] = y[0]
            else:
                ix = np.random.permutation(
                    np.arange(np.prod(sh0)))[:np.prod(sh0)//2]
                x[ix] = y[ix]
            x = np.reshape(x, sh0)
            y = np.reshape(y, sh1)
            self._compareGpu(x, y, np.not_equal, tf.not_equal) 

Example 10

def equal(x1, x2):
    """
    Return (x1 == x2) element-wise.

    Unlike `numpy.equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    not_equal, greater_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '==', True) 

Example 11

def not_equal(x1, x2):
    """
    Return (x1 != x2) element-wise.

    Unlike `numpy.not_equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, greater_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '!=', True) 

Example 12

def greater_equal(x1, x2):
    """
    Return (x1 >= x2) element-wise.

    Unlike `numpy.greater_equal`, this comparison is performed by
    first stripping whitespace characters from the end of the string.
    This behavior is provided for backward-compatibility with
    numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '>=', True) 

Example 13

def less_equal(x1, x2):
    """
    Return (x1 <= x2) element-wise.

    Unlike `numpy.less_equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, greater_equal, greater, less
    """
    return compare_chararrays(x1, x2, '<=', True) 

Example 14

def greater(x1, x2):
    """
    Return (x1 > x2) element-wise.

    Unlike `numpy.greater`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, greater_equal, less_equal, less
    """
    return compare_chararrays(x1, x2, '>', True) 

Example 15

def test_truth_table_logical(self):
        # 2, 3 and 4 serves as true values
        input1 = [0, 0, 3, 2]
        input2 = [0, 4, 0, 2]

        typecodes = (np.typecodes['AllFloat']
                     + np.typecodes['AllInteger']
                     + '?')     # boolean
        for dtype in map(np.dtype, typecodes):
            arg1 = np.asarray(input1, dtype=dtype)
            arg2 = np.asarray(input2, dtype=dtype)

            # OR
            out = [False, True, True, True]
            for func in (np.logical_or, np.maximum):
                assert_equal(func(arg1, arg2).astype(bool), out)
            # AND
            out = [False, False, False, True]
            for func in (np.logical_and, np.minimum):
                assert_equal(func(arg1, arg2).astype(bool), out)
            # XOR
            out = [False, True, True, False]
            for func in (np.logical_xor, np.not_equal):
                assert_equal(func(arg1, arg2).astype(bool), out) 

Example 16

def test_identity_equality_mismatch(self):
        a = np.array([np.nan], dtype=object)

        with warnings.catch_warnings():
            warnings.filterwarnings('always', '', FutureWarning)
            assert_warns(FutureWarning, np.equal, a, a)
            assert_warns(FutureWarning, np.not_equal, a, a)

        with warnings.catch_warnings():
            warnings.filterwarnings('error', '', FutureWarning)
            assert_raises(FutureWarning, np.equal, a, a)
            assert_raises(FutureWarning, np.not_equal, a, a)
            # And the other do not warn:
            with np.errstate(invalid='ignore'):
                np.less(a, a)
                np.greater(a, a)
                np.less_equal(a, a)
                np.greater_equal(a, a) 

Example 17

def equal(x1, x2):
    """
    Return (x1 == x2) element-wise.

    Unlike `numpy.equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    not_equal, greater_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '==', True) 

Example 18

def not_equal(x1, x2):
    """
    Return (x1 != x2) element-wise.

    Unlike `numpy.not_equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, greater_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '!=', True) 

Example 19

def greater_equal(x1, x2):
    """
    Return (x1 >= x2) element-wise.

    Unlike `numpy.greater_equal`, this comparison is performed by
    first stripping whitespace characters from the end of the string.
    This behavior is provided for backward-compatibility with
    numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '>=', True) 

Example 20

def less_equal(x1, x2):
    """
    Return (x1 <= x2) element-wise.

    Unlike `numpy.less_equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, greater_equal, greater, less
    """
    return compare_chararrays(x1, x2, '<=', True) 

Example 21

def greater(x1, x2):
    """
    Return (x1 > x2) element-wise.

    Unlike `numpy.greater`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, greater_equal, less_equal, less
    """
    return compare_chararrays(x1, x2, '>', True) 

Example 22

def test_truth_table_logical(self):
        # 2, 3 and 4 serves as true values
        input1 = [0, 0, 3, 2]
        input2 = [0, 4, 0, 2]

        typecodes = (np.typecodes['AllFloat']
                     + np.typecodes['AllInteger']
                     + '?')     # boolean
        for dtype in map(np.dtype, typecodes):
            arg1 = np.asarray(input1, dtype=dtype)
            arg2 = np.asarray(input2, dtype=dtype)

            # OR
            out = [False, True, True, True]
            for func in (np.logical_or, np.maximum):
                assert_equal(func(arg1, arg2).astype(bool), out)
            # AND
            out = [False, False, False, True]
            for func in (np.logical_and, np.minimum):
                assert_equal(func(arg1, arg2).astype(bool), out)
            # XOR
            out = [False, True, True, False]
            for func in (np.logical_xor, np.not_equal):
                assert_equal(func(arg1, arg2).astype(bool), out) 

Example 23

def test_NotImplemented_not_returned(self):
        # See gh-5964 and gh-2091. Some of these functions are not operator
        # related and were fixed for other reasons in the past.
        binary_funcs = [
            np.power, np.add, np.subtract, np.multiply, np.divide,
            np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or,
            np.bitwise_xor, np.left_shift, np.right_shift, np.fmax,
            np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2,
            np.logical_and, np.logical_or, np.logical_xor, np.maximum,
            np.minimum, np.mod
            ]

        # These functions still return NotImplemented. Will be fixed in
        # future.
        # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal]

        a = np.array('1')
        b = 1
        for f in binary_funcs:
            assert_raises(TypeError, f, a, b) 

Example 24

def test_identity_equality_mismatch(self):
        a = np.array([np.nan], dtype=object)

        with warnings.catch_warnings():
            warnings.filterwarnings('always', '', FutureWarning)
            assert_warns(FutureWarning, np.equal, a, a)
            assert_warns(FutureWarning, np.not_equal, a, a)

        with warnings.catch_warnings():
            warnings.filterwarnings('error', '', FutureWarning)
            assert_raises(FutureWarning, np.equal, a, a)
            assert_raises(FutureWarning, np.not_equal, a, a)
            # And the other do not warn:
            with np.errstate(invalid='ignore'):
                np.less(a, a)
                np.greater(a, a)
                np.less_equal(a, a)
                np.greater_equal(a, a) 

Example 25

def gen_hull(p, p_mask, f_encode, f_probi, options):
    # p: n_sizes * n_samples * data_dim
    n_sizes = p.shape[0]
    n_samples = p.shape[1] if p.ndim == 3 else 1
    hprev = f_encode(p_mask, p)  # n_sizes * n_samples * data_dim
    points = numpy.zeros((n_samples, n_sizes), dtype='int64')
    h = hprev[-1]
    c = numpy.zeros((n_samples, options['dim_proj']), dtype=config.floatX)
    xi = numpy.zeros((n_samples,), dtype='int64')
    xi_mask = numpy.ones((n_samples,), dtype=config.floatX)
    for i in range(n_sizes):
        h, c, probi = f_probi(p_mask[i], xi, h, c, hprev, p_mask, p)
        xi = probi.argmax(axis=0)
        xi *= xi_mask.astype(numpy.int64)  # Avoid compatibility problem in numpy 1.10
        xi_mask = (numpy.not_equal(xi, 0)).astype(config.floatX)
        if numpy.equal(xi_mask, 0).all():
            break
        points[:, i] = xi
    return points 

Example 26

def equal(x1, x2):
    """
    Return (x1 == x2) element-wise.

    Unlike `numpy.equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    not_equal, greater_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '==', True) 

Example 27

def greater_equal(x1, x2):
    """
    Return (x1 >= x2) element-wise.

    Unlike `numpy.greater_equal`, this comparison is performed by
    first stripping whitespace characters from the end of the string.
    This behavior is provided for backward-compatibility with
    numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '>=', True) 

Example 28

def less_equal(x1, x2):
    """
    Return (x1 <= x2) element-wise.

    Unlike `numpy.less_equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, greater_equal, greater, less
    """
    return compare_chararrays(x1, x2, '<=', True) 

Example 29

def greater(x1, x2):
    """
    Return (x1 > x2) element-wise.

    Unlike `numpy.greater`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, greater_equal, less_equal, less
    """
    return compare_chararrays(x1, x2, '>', True) 

Example 30

def test_truth_table_logical(self):
        # 2, 3 and 4 serves as true values
        input1 = [0, 0, 3, 2]
        input2 = [0, 4, 0, 2]

        typecodes = (np.typecodes['AllFloat']
                     + np.typecodes['AllInteger']
                     + '?')     # boolean
        for dtype in map(np.dtype, typecodes):
            arg1 = np.asarray(input1, dtype=dtype)
            arg2 = np.asarray(input2, dtype=dtype)

            # OR
            out = [False, True, True, True]
            for func in (np.logical_or, np.maximum):
                assert_equal(func(arg1, arg2).astype(bool), out)
            # AND
            out = [False, False, False, True]
            for func in (np.logical_and, np.minimum):
                assert_equal(func(arg1, arg2).astype(bool), out)
            # XOR
            out = [False, True, True, False]
            for func in (np.logical_xor, np.not_equal):
                assert_equal(func(arg1, arg2).astype(bool), out) 

Example 31

def test_NotImplemented_not_returned(self):
        # See gh-5964 and gh-2091. Some of these functions are not operator
        # related and were fixed for other reasons in the past.
        binary_funcs = [
            np.power, np.add, np.subtract, np.multiply, np.divide,
            np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or,
            np.bitwise_xor, np.left_shift, np.right_shift, np.fmax,
            np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2,
            np.logical_and, np.logical_or, np.logical_xor, np.maximum,
            np.minimum, np.mod
            ]

        # These functions still return NotImplemented. Will be fixed in
        # future.
        # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal]

        a = np.array('1')
        b = 1
        for f in binary_funcs:
            assert_raises(TypeError, f, a, b) 

Example 32

def test_identity_equality_mismatch(self):
        a = np.array([np.nan], dtype=object)

        with warnings.catch_warnings():
            warnings.filterwarnings('always', '', FutureWarning)
            assert_warns(FutureWarning, np.equal, a, a)
            assert_warns(FutureWarning, np.not_equal, a, a)

        with warnings.catch_warnings():
            warnings.filterwarnings('error', '', FutureWarning)
            assert_raises(FutureWarning, np.equal, a, a)
            assert_raises(FutureWarning, np.not_equal, a, a)
            # And the other do not warn:
            with np.errstate(invalid='ignore'):
                np.less(a, a)
                np.greater(a, a)
                np.less_equal(a, a)
                np.greater_equal(a, a) 

Example 33

def equal(x1, x2):
    """
    Return (x1 == x2) element-wise.

    Unlike `numpy.equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    not_equal, greater_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '==', True) 

Example 34

def not_equal(x1, x2):
    """
    Return (x1 != x2) element-wise.

    Unlike `numpy.not_equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, greater_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '!=', True) 

Example 35

def greater_equal(x1, x2):
    """
    Return (x1 >= x2) element-wise.

    Unlike `numpy.greater_equal`, this comparison is performed by
    first stripping whitespace characters from the end of the string.
    This behavior is provided for backward-compatibility with
    numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '>=', True) 

Example 36

def less_equal(x1, x2):
    """
    Return (x1 <= x2) element-wise.

    Unlike `numpy.less_equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, greater_equal, greater, less
    """
    return compare_chararrays(x1, x2, '<=', True) 

Example 37

def greater(x1, x2):
    """
    Return (x1 > x2) element-wise.

    Unlike `numpy.greater`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, greater_equal, less_equal, less
    """
    return compare_chararrays(x1, x2, '>', True) 

Example 38

def test_truth_table_logical(self):
        # 2, 3 and 4 serves as true values
        input1 = [0, 0, 3, 2]
        input2 = [0, 4, 0, 2]

        typecodes = (np.typecodes['AllFloat']
                     + np.typecodes['AllInteger']
                     + '?')     # boolean
        for dtype in map(np.dtype, typecodes):
            arg1 = np.asarray(input1, dtype=dtype)
            arg2 = np.asarray(input2, dtype=dtype)

            # OR
            out = [False, True, True, True]
            for func in (np.logical_or, np.maximum):
                assert_equal(func(arg1, arg2).astype(bool), out)
            # AND
            out = [False, False, False, True]
            for func in (np.logical_and, np.minimum):
                assert_equal(func(arg1, arg2).astype(bool), out)
            # XOR
            out = [False, True, True, False]
            for func in (np.logical_xor, np.not_equal):
                assert_equal(func(arg1, arg2).astype(bool), out) 

Example 39

def test_NotImplemented_not_returned(self):
        # See gh-5964 and gh-2091. Some of these functions are not operator
        # related and were fixed for other reasons in the past.
        binary_funcs = [
            np.power, np.add, np.subtract, np.multiply, np.divide,
            np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or,
            np.bitwise_xor, np.left_shift, np.right_shift, np.fmax,
            np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2,
            np.logical_and, np.logical_or, np.logical_xor, np.maximum,
            np.minimum, np.mod
            ]

        # These functions still return NotImplemented. Will be fixed in
        # future.
        # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal]

        a = np.array('1')
        b = 1
        for f in binary_funcs:
            assert_raises(TypeError, f, a, b) 

Example 40

def test_identity_equality_mismatch(self):
        a = np.array([np.nan], dtype=object)

        with warnings.catch_warnings():
            warnings.filterwarnings('always', '', FutureWarning)
            assert_warns(FutureWarning, np.equal, a, a)
            assert_warns(FutureWarning, np.not_equal, a, a)

        with warnings.catch_warnings():
            warnings.filterwarnings('error', '', FutureWarning)
            assert_raises(FutureWarning, np.equal, a, a)
            assert_raises(FutureWarning, np.not_equal, a, a)
            # And the other do not warn:
            with np.errstate(invalid='ignore'):
                np.less(a, a)
                np.greater(a, a)
                np.less_equal(a, a)
                np.greater_equal(a, a) 

Example 41

def equal(x1, x2):
    """
    Return (x1 == x2) element-wise.

    Unlike `numpy.equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    not_equal, greater_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '==', True) 

Example 42

def not_equal(x1, x2):
    """
    Return (x1 != x2) element-wise.

    Unlike `numpy.not_equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, greater_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '!=', True) 

Example 43

def greater_equal(x1, x2):
    """
    Return (x1 >= x2) element-wise.

    Unlike `numpy.greater_equal`, this comparison is performed by
    first stripping whitespace characters from the end of the string.
    This behavior is provided for backward-compatibility with
    numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, less_equal, greater, less
    """
    return compare_chararrays(x1, x2, '>=', True) 

Example 44

def less_equal(x1, x2):
    """
    Return (x1 <= x2) element-wise.

    Unlike `numpy.less_equal`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, greater_equal, greater, less
    """
    return compare_chararrays(x1, x2, '<=', True) 

Example 45

def greater(x1, x2):
    """
    Return (x1 > x2) element-wise.

    Unlike `numpy.greater`, this comparison is performed by first
    stripping whitespace characters from the end of the string.  This
    behavior is provided for backward-compatibility with numarray.

    Parameters
    ----------
    x1, x2 : array_like of str or unicode
        Input arrays of the same shape.

    Returns
    -------
    out : ndarray or bool
        Output array of bools, or a single bool if x1 and x2 are scalars.

    See Also
    --------
    equal, not_equal, greater_equal, less_equal, less
    """
    return compare_chararrays(x1, x2, '>', True) 

Example 46

def test_truth_table_logical(self):
        # 2, 3 and 4 serves as true values
        input1 = [0, 0, 3, 2]
        input2 = [0, 4, 0, 2]

        typecodes = (np.typecodes['AllFloat']
                     + np.typecodes['AllInteger']
                     + '?')     # boolean
        for dtype in map(np.dtype, typecodes):
            arg1 = np.asarray(input1, dtype=dtype)
            arg2 = np.asarray(input2, dtype=dtype)

            # OR
            out = [False, True, True, True]
            for func in (np.logical_or, np.maximum):
                assert_equal(func(arg1, arg2).astype(bool), out)
            # AND
            out = [False, False, False, True]
            for func in (np.logical_and, np.minimum):
                assert_equal(func(arg1, arg2).astype(bool), out)
            # XOR
            out = [False, True, True, False]
            for func in (np.logical_xor, np.not_equal):
                assert_equal(func(arg1, arg2).astype(bool), out) 

Example 47

def test_NotImplemented_not_returned(self):
        # See gh-5964 and gh-2091. Some of these functions are not operator
        # related and were fixed for other reasons in the past.
        binary_funcs = [
            np.power, np.add, np.subtract, np.multiply, np.divide,
            np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or,
            np.bitwise_xor, np.left_shift, np.right_shift, np.fmax,
            np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2,
            np.logical_and, np.logical_or, np.logical_xor, np.maximum,
            np.minimum, np.mod
            ]

        # These functions still return NotImplemented. Will be fixed in
        # future.
        # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal]

        a = np.array('1')
        b = 1
        for f in binary_funcs:
            assert_raises(TypeError, f, a, b) 

Example 48

def test_identity_equality_mismatch(self):
        a = np.array([np.nan], dtype=object)

        with warnings.catch_warnings():
            warnings.filterwarnings('always', '', FutureWarning)
            assert_warns(FutureWarning, np.equal, a, a)
            assert_warns(FutureWarning, np.not_equal, a, a)

        with warnings.catch_warnings():
            warnings.filterwarnings('error', '', FutureWarning)
            assert_raises(FutureWarning, np.equal, a, a)
            assert_raises(FutureWarning, np.not_equal, a, a)
            # And the other do not warn:
            with np.errstate(invalid='ignore'):
                np.less(a, a)
                np.greater(a, a)
                np.less_equal(a, a)
                np.greater_equal(a, a) 

Example 49

def density_slice(rast, rel=np.less_equal, threshold=1000, nodata=-9999):
    '''
    Returns a density slice from a given raster. Arguments:
        rast        A gdal.Dataset or a NumPy array
        rel         A NumPy logic function; defaults to np.less_equal
        threshold   An integer number
    '''
    # Can accept either a gdal.Dataset or numpy.array instance
    if not isinstance(rast, np.ndarray):
        rastr = rast.ReadAsArray()

    else:
        rastr = rast.copy()

    if (len(rastr.shape) > 2 and min(rastr.shape) > 1):
        raise ValueError('Expected a single-band raster array')

    return np.logical_and(
        rel(rastr, np.ones(rast.shape) * threshold),
        np.not_equal(rastr, np.ones(rast.shape) * nodata)).astype(np.int0) 

Example 50

def self_loss(predicts, labels):

    # shape = predicts.shape
    # predicts = predicts.reshape([-1, 20])
    # labels = labels.reshape([-1, 20])

    batch_label = np.argmax(labels, axis = -1).astype(np.float32)
    batch_zeros = np.zeros_like(batch_label).astype(np.float32)
    mask1 = np.not_equal(batch_zeros, batch_label)
    rand_u = np.random.uniform(low=0.0, high=1.0, size=batch_label.shape)
    mask2 = rand_u < ratio
    mask = mask1 | mask2

    loss, backprop = _softmax_cross_entropy(predicts, labels)
    loss = np.where(mask, loss, batch_zeros)
    backprop_zeros = np.zeros_like(backprop)
    backprop = np.where(np.expand_dims(mask, axis=-1), backprop, backprop_zeros)
    backprop = backprop * class_weights
    # backprop = np.reshape(backprop, shape)

    # loss = np.mean(loss)
    # return loss
    return loss, backprop 
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