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)
python类less_equal()的实例源码
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)
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)
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)
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)
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)
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)
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)
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)
def approx(a, b, fill_value=True, rtol=1e-5, atol=1e-8):
"""
Returns true if all components of a and b are equal to given tolerances.
If fill_value is True, masked values considered equal. Otherwise,
masked values are considered unequal. The relative error rtol should
be positive and << 1.0 The absolute error atol comes into play for
those elements of b that are very small or zero; it says how small a
must be also.
"""
m = mask_or(getmask(a), getmask(b))
d1 = filled(a)
d2 = filled(b)
if d1.dtype.char == "O" or d2.dtype.char == "O":
return np.equal(d1, d2).ravel()
x = filled(masked_array(d1, copy=False, mask=m), fill_value).astype(float_)
y = filled(masked_array(d2, copy=False, mask=m), 1).astype(float_)
d = np.less_equal(umath.absolute(x - y), atol + rtol * umath.absolute(y))
return d.ravel()
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)
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)
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)
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)
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)
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)
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)
def approx(a, b, fill_value=True, rtol=1e-5, atol=1e-8):
"""
Returns true if all components of a and b are equal to given tolerances.
If fill_value is True, masked values considered equal. Otherwise,
masked values are considered unequal. The relative error rtol should
be positive and << 1.0 The absolute error atol comes into play for
those elements of b that are very small or zero; it says how small a
must be also.
"""
m = mask_or(getmask(a), getmask(b))
d1 = filled(a)
d2 = filled(b)
if d1.dtype.char == "O" or d2.dtype.char == "O":
return np.equal(d1, d2).ravel()
x = filled(masked_array(d1, copy=False, mask=m), fill_value).astype(float_)
y = filled(masked_array(d2, copy=False, mask=m), 1).astype(float_)
d = np.less_equal(umath.absolute(x - y), atol + rtol * umath.absolute(y))
return d.ravel()
def atmax(a,upperlimit,dimension=None,inclusive=1):
"""
Returns the maximum value of a, along dimension, including only values greater
than (or equal to, if inclusive=1) upperlimit. If the limit is set to None,
a limit larger than the max value in the array is used.
Usage: atmax(a,upperlimit,dimension=None,inclusive=1)
"""
if inclusive: upperfcn = N.less
else: upperfcn = N.less_equal
if dimension == None:
a = N.ravel(a)
dimension = 0
if upperlimit == None:
upperlimit = N.maximum.reduce(N.ravel(a))+1
smallest = N.minimum.reduce(N.ravel(a))
ta = N.where(upperfcn(a,upperlimit),a,smallest)
return N.maximum.reduce(ta,dimension)
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)
