Python numpy.not_equal方法代碼示例

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import not_equal [as 別名]
def trim(coefficients):
  """Makes non-zero entry in the final slice along each axis."""
  coefficients = np.asarray(coefficients)
  non_zero = np.not_equal(coefficients, 0)
  ndim = coefficients.ndim

  for axis in range(ndim):
    length = coefficients.shape[axis]
    axis_complement = list(range(0, axis)) + list(range(axis + 1, ndim))
    non_zero_along_axis = np.any(non_zero, axis=tuple(axis_complement))

    slice_to = 0
    for index in range(length - 1, -1, -1):
      if non_zero_along_axis[index]:
        slice_to = index + 1
        break

    if slice_to < length:
      coefficients = coefficients.take(axis=axis, indices=list(range(slice_to)))

  return coefficients 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import not_equal [as 別名]
def test_datetime_compare_nat(self):
        dt_nat = np.datetime64('NaT', 'D')
        dt_other = np.datetime64('2000-01-01')
        td_nat = np.timedelta64('NaT', 'h')
        td_other = np.timedelta64(1, 'h')

        for op in [np.equal, np.less, np.less_equal,
                   np.greater, np.greater_equal]:
            assert_(not op(dt_nat, dt_nat))
            assert_(not op(dt_nat, dt_other))
            assert_(not op(dt_other, dt_nat))

            assert_(not op(td_nat, td_nat))
            assert_(not op(td_nat, td_other))
            assert_(not op(td_other, td_nat))

        assert_(np.not_equal(dt_nat, dt_nat))
        assert_(np.not_equal(dt_nat, dt_other))
        assert_(np.not_equal(dt_other, dt_nat))

        assert_(np.not_equal(td_nat, td_nat))
        assert_(np.not_equal(td_nat, td_other))
        assert_(np.not_equal(td_other, td_nat)) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import not_equal [as 別名]
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,
            np.greater, np.greater_equal, np.less, np.less_equal,
            np.equal, np.not_equal]

        a = np.array('1')
        b = 1
        c = np.array([1., 2.])
        for f in binary_funcs:
            assert_raises(TypeError, f, a, b)
            assert_raises(TypeError, f, c, a) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import not_equal [as 別名]
def test_ignore_object_identity_in_not_equal(self):
        # Check error raised when comparing identical objects whose comparison
        # is not a simple boolean, e.g., arrays that are compared elementwise.
        a = np.array([np.array([1, 2, 3]), None], dtype=object)
        assert_raises(ValueError, np.not_equal, a, a)

        # Check error raised when comparing identical non-comparable objects.
        class FunkyType(object):
            def __ne__(self, other):
                raise TypeError("I won't compare")

        a = np.array([FunkyType()])
        assert_raises(TypeError, np.not_equal, a, a)

        # Check identity doesn't override comparison mismatch.
        a = np.array([np.nan], dtype=object)
        assert_equal(np.not_equal(a, a), [True]) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import not_equal [as 別名]
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) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import not_equal [as 別名]
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) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import not_equal [as 別名]
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) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import not_equal [as 別名]
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) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import not_equal [as 別名]
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) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import not_equal [as 別名]
def less(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, greater
    """
    return compare_chararrays(x1, x2, '<', True) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import not_equal [as 別名]
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) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import not_equal [as 別名]
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) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import not_equal [as 別名]
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)