Python numpy.core.numeric.signbit() Examples
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code examples of numpy.core.numeric.signbit().
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Example #1
| Source File: ufunclike.py From mxnet-lambda with Apache License 2.0 | 4 votes |
|
def isposinf(x, out=None):
"""
Test element-wise for positive infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
y : array_like, optional
A boolean array with the same shape as `x` to store the result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a boolean array is returned
with values True where the corresponding element of the input is
positive infinity and values False where the element of the input is
not positive infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as zeros
and ones, if the type is boolean then as False and True.
The return value `out` is then a reference to that array.
See Also
--------
isinf, isneginf, isfinite, isnan
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when `x` is a
scalar input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isposinf(np.PINF)
array(True, dtype=bool)
>>> np.isposinf(np.inf)
array(True, dtype=bool)
>>> np.isposinf(np.NINF)
array(False, dtype=bool)
>>> np.isposinf([-np.inf, 0., np.inf])
array([False, False, True], dtype=bool)
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isposinf(x, y)
array([0, 0, 1])
>>> y
array([0, 0, 1])
"""
return nx.logical_and(nx.isinf(x), ~nx.signbit(x), out)
Example #2
| Source File: ufunclike.py From keras-lambda with MIT License | 4 votes |
|
def isposinf(x, y=None):
"""
Test element-wise for positive infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
y : array_like, optional
A boolean array with the same shape as `x` to store the result.
Returns
-------
y : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a boolean array is returned
with values True where the corresponding element of the input is
positive infinity and values False where the element of the input is
not positive infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as zeros
and ones, if the type is boolean then as False and True.
The return value `y` is then a reference to that array.
See Also
--------
isinf, isneginf, isfinite, isnan
Notes
-----
Numpy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when `x` is a
scalar input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isposinf(np.PINF)
array(True, dtype=bool)
>>> np.isposinf(np.inf)
array(True, dtype=bool)
>>> np.isposinf(np.NINF)
array(False, dtype=bool)
>>> np.isposinf([-np.inf, 0., np.inf])
array([False, False, True], dtype=bool)
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isposinf(x, y)
array([0, 0, 1])
>>> y
array([0, 0, 1])
"""
if y is None:
x = nx.asarray(x)
y = nx.empty(x.shape, dtype=nx.bool_)
nx.logical_and(nx.isinf(x), ~nx.signbit(x), y)
return y
Example #3
| Source File: ufunclike.py From twitter-stock-recommendation with MIT License | 4 votes |
|
def isneginf(x, out=None):
"""
Test element-wise for negative infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
out : array_like, optional
A boolean array with the same shape and type as `x` to store the
result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a numpy boolean array is
returned with values True where the corresponding element of the
input is negative infinity and values False where the element of
the input is not negative infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as
zeros and ones, if the type is boolean then as False and True. The
return value `out` is then a reference to that array.
See Also
--------
isinf, isposinf, isnan, isfinite
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when x is a scalar
input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isneginf(np.NINF)
array(True, dtype=bool)
>>> np.isneginf(np.inf)
array(False, dtype=bool)
>>> np.isneginf(np.PINF)
array(False, dtype=bool)
>>> np.isneginf([-np.inf, 0., np.inf])
array([ True, False, False])
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isneginf(x, y)
array([1, 0, 0])
>>> y
array([1, 0, 0])
"""
return nx.logical_and(nx.isinf(x), nx.signbit(x), out)
Example #4
| Source File: ufunclike.py From twitter-stock-recommendation with MIT License | 4 votes |
|
def isposinf(x, out=None):
"""
Test element-wise for positive infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
y : array_like, optional
A boolean array with the same shape as `x` to store the result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a boolean array is returned
with values True where the corresponding element of the input is
positive infinity and values False where the element of the input is
not positive infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as zeros
and ones, if the type is boolean then as False and True.
The return value `out` is then a reference to that array.
See Also
--------
isinf, isneginf, isfinite, isnan
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when `x` is a
scalar input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isposinf(np.PINF)
array(True, dtype=bool)
>>> np.isposinf(np.inf)
array(True, dtype=bool)
>>> np.isposinf(np.NINF)
array(False, dtype=bool)
>>> np.isposinf([-np.inf, 0., np.inf])
array([False, False, True])
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isposinf(x, y)
array([0, 0, 1])
>>> y
array([0, 0, 1])
"""
return nx.logical_and(nx.isinf(x), ~nx.signbit(x), out)
Example #5
| Source File: ufunclike.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 4 votes |
|
def isneginf(x, out=None):
"""
Test element-wise for negative infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
out : array_like, optional
A boolean array with the same shape and type as `x` to store the
result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a numpy boolean array is
returned with values True where the corresponding element of the
input is negative infinity and values False where the element of
the input is not negative infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as
zeros and ones, if the type is boolean then as False and True. The
return value `out` is then a reference to that array.
See Also
--------
isinf, isposinf, isnan, isfinite
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when x is a scalar
input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isneginf(np.NINF)
array(True, dtype=bool)
>>> np.isneginf(np.inf)
array(False, dtype=bool)
>>> np.isneginf(np.PINF)
array(False, dtype=bool)
>>> np.isneginf([-np.inf, 0., np.inf])
array([ True, False, False])
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isneginf(x, y)
array([1, 0, 0])
>>> y
array([1, 0, 0])
"""
return nx.logical_and(nx.isinf(x), nx.signbit(x), out)
Example #6
| Source File: ufunclike.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 4 votes |
|
def isposinf(x, out=None):
"""
Test element-wise for positive infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
y : array_like, optional
A boolean array with the same shape as `x` to store the result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a boolean array is returned
with values True where the corresponding element of the input is
positive infinity and values False where the element of the input is
not positive infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as zeros
and ones, if the type is boolean then as False and True.
The return value `out` is then a reference to that array.
See Also
--------
isinf, isneginf, isfinite, isnan
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when `x` is a
scalar input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isposinf(np.PINF)
array(True, dtype=bool)
>>> np.isposinf(np.inf)
array(True, dtype=bool)
>>> np.isposinf(np.NINF)
array(False, dtype=bool)
>>> np.isposinf([-np.inf, 0., np.inf])
array([False, False, True])
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isposinf(x, y)
array([0, 0, 1])
>>> y
array([0, 0, 1])
"""
return nx.logical_and(nx.isinf(x), ~nx.signbit(x), out)
Example #7
| Source File: ufunclike.py From elasticintel with GNU General Public License v3.0 | 4 votes |
|
def isneginf(x, out=None):
"""
Test element-wise for negative infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
out : array_like, optional
A boolean array with the same shape and type as `x` to store the
result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a numpy boolean array is
returned with values True where the corresponding element of the
input is negative infinity and values False where the element of
the input is not negative infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as
zeros and ones, if the type is boolean then as False and True. The
return value `out` is then a reference to that array.
See Also
--------
isinf, isposinf, isnan, isfinite
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when x is a scalar
input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isneginf(np.NINF)
array(True, dtype=bool)
>>> np.isneginf(np.inf)
array(False, dtype=bool)
>>> np.isneginf(np.PINF)
array(False, dtype=bool)
>>> np.isneginf([-np.inf, 0., np.inf])
array([ True, False, False], dtype=bool)
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isneginf(x, y)
array([1, 0, 0])
>>> y
array([1, 0, 0])
"""
return nx.logical_and(nx.isinf(x), nx.signbit(x), out)
Example #8
| Source File: ufunclike.py From elasticintel with GNU General Public License v3.0 | 4 votes |
|
def isposinf(x, out=None):
"""
Test element-wise for positive infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
y : array_like, optional
A boolean array with the same shape as `x` to store the result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a boolean array is returned
with values True where the corresponding element of the input is
positive infinity and values False where the element of the input is
not positive infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as zeros
and ones, if the type is boolean then as False and True.
The return value `out` is then a reference to that array.
See Also
--------
isinf, isneginf, isfinite, isnan
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when `x` is a
scalar input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isposinf(np.PINF)
array(True, dtype=bool)
>>> np.isposinf(np.inf)
array(True, dtype=bool)
>>> np.isposinf(np.NINF)
array(False, dtype=bool)
>>> np.isposinf([-np.inf, 0., np.inf])
array([False, False, True], dtype=bool)
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isposinf(x, y)
array([0, 0, 1])
>>> y
array([0, 0, 1])
"""
return nx.logical_and(nx.isinf(x), ~nx.signbit(x), out)
Example #9
| Source File: ufunclike.py From Splunking-Crime with GNU Affero General Public License v3.0 | 4 votes |
|
def isneginf(x, out=None):
"""
Test element-wise for negative infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
out : array_like, optional
A boolean array with the same shape and type as `x` to store the
result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a numpy boolean array is
returned with values True where the corresponding element of the
input is negative infinity and values False where the element of
the input is not negative infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as
zeros and ones, if the type is boolean then as False and True. The
return value `out` is then a reference to that array.
See Also
--------
isinf, isposinf, isnan, isfinite
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when x is a scalar
input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isneginf(np.NINF)
array(True, dtype=bool)
>>> np.isneginf(np.inf)
array(False, dtype=bool)
>>> np.isneginf(np.PINF)
array(False, dtype=bool)
>>> np.isneginf([-np.inf, 0., np.inf])
array([ True, False, False], dtype=bool)
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isneginf(x, y)
array([1, 0, 0])
>>> y
array([1, 0, 0])
"""
return nx.logical_and(nx.isinf(x), nx.signbit(x), out)
Example #10
| Source File: ufunclike.py From Splunking-Crime with GNU Affero General Public License v3.0 | 4 votes |
|
def isposinf(x, out=None):
"""
Test element-wise for positive infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
y : array_like, optional
A boolean array with the same shape as `x` to store the result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a boolean array is returned
with values True where the corresponding element of the input is
positive infinity and values False where the element of the input is
not positive infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as zeros
and ones, if the type is boolean then as False and True.
The return value `out` is then a reference to that array.
See Also
--------
isinf, isneginf, isfinite, isnan
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when `x` is a
scalar input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isposinf(np.PINF)
array(True, dtype=bool)
>>> np.isposinf(np.inf)
array(True, dtype=bool)
>>> np.isposinf(np.NINF)
array(False, dtype=bool)
>>> np.isposinf([-np.inf, 0., np.inf])
array([False, False, True], dtype=bool)
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isposinf(x, y)
array([0, 0, 1])
>>> y
array([0, 0, 1])
"""
return nx.logical_and(nx.isinf(x), ~nx.signbit(x), out)
Example #11
| Source File: ufunclike.py From ImageFusion with MIT License | 4 votes |
|
def isposinf(x, y=None):
"""
Test element-wise for positive infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
y : array_like, optional
A boolean array with the same shape as `x` to store the result.
Returns
-------
y : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a boolean array is returned
with values True where the corresponding element of the input is
positive infinity and values False where the element of the input is
not positive infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as zeros
and ones, if the type is boolean then as False and True.
The return value `y` is then a reference to that array.
See Also
--------
isinf, isneginf, isfinite, isnan
Notes
-----
Numpy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when `x` is a
scalar input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isposinf(np.PINF)
array(True, dtype=bool)
>>> np.isposinf(np.inf)
array(True, dtype=bool)
>>> np.isposinf(np.NINF)
array(False, dtype=bool)
>>> np.isposinf([-np.inf, 0., np.inf])
array([False, False, True], dtype=bool)
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isposinf(x, y)
array([0, 0, 1])
>>> y
array([0, 0, 1])
"""
if y is None:
x = nx.asarray(x)
y = nx.empty(x.shape, dtype=nx.bool_)
nx.logical_and(nx.isinf(x), ~nx.signbit(x), y)
return y
Example #12
| Source File: ufunclike.py From mxnet-lambda with Apache License 2.0 | 4 votes |
|
def isneginf(x, out=None):
"""
Test element-wise for negative infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
out : array_like, optional
A boolean array with the same shape and type as `x` to store the
result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a numpy boolean array is
returned with values True where the corresponding element of the
input is negative infinity and values False where the element of
the input is not negative infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as
zeros and ones, if the type is boolean then as False and True. The
return value `out` is then a reference to that array.
See Also
--------
isinf, isposinf, isnan, isfinite
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when x is a scalar
input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isneginf(np.NINF)
array(True, dtype=bool)
>>> np.isneginf(np.inf)
array(False, dtype=bool)
>>> np.isneginf(np.PINF)
array(False, dtype=bool)
>>> np.isneginf([-np.inf, 0., np.inf])
array([ True, False, False], dtype=bool)
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isneginf(x, y)
array([1, 0, 0])
>>> y
array([1, 0, 0])
"""
return nx.logical_and(nx.isinf(x), nx.signbit(x), out)
Example #13
| Source File: ufunclike.py From lambda-packs with MIT License | 4 votes |
|
def isposinf(x, out=None):
"""
Test element-wise for positive infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
y : array_like, optional
A boolean array with the same shape as `x` to store the result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a boolean array is returned
with values True where the corresponding element of the input is
positive infinity and values False where the element of the input is
not positive infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as zeros
and ones, if the type is boolean then as False and True.
The return value `out` is then a reference to that array.
See Also
--------
isinf, isneginf, isfinite, isnan
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when `x` is a
scalar input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isposinf(np.PINF)
array(True, dtype=bool)
>>> np.isposinf(np.inf)
array(True, dtype=bool)
>>> np.isposinf(np.NINF)
array(False, dtype=bool)
>>> np.isposinf([-np.inf, 0., np.inf])
array([False, False, True])
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isposinf(x, y)
array([0, 0, 1])
>>> y
array([0, 0, 1])
"""
return nx.logical_and(nx.isinf(x), ~nx.signbit(x), out)
Example #14
| Source File: ufunclike.py From pySINDy with MIT License | 4 votes |
|
def isneginf(x, out=None):
"""
Test element-wise for negative infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
out : array_like, optional
A boolean array with the same shape and type as `x` to store the
result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a numpy boolean array is
returned with values True where the corresponding element of the
input is negative infinity and values False where the element of
the input is not negative infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as
zeros and ones, if the type is boolean then as False and True. The
return value `out` is then a reference to that array.
See Also
--------
isinf, isposinf, isnan, isfinite
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when x is a scalar
input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isneginf(np.NINF)
array(True, dtype=bool)
>>> np.isneginf(np.inf)
array(False, dtype=bool)
>>> np.isneginf(np.PINF)
array(False, dtype=bool)
>>> np.isneginf([-np.inf, 0., np.inf])
array([ True, False, False])
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isneginf(x, y)
array([1, 0, 0])
>>> y
array([1, 0, 0])
"""
return nx.logical_and(nx.isinf(x), nx.signbit(x), out)
Example #15
| Source File: ufunclike.py From pySINDy with MIT License | 4 votes |
|
def isposinf(x, out=None):
"""
Test element-wise for positive infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
y : array_like, optional
A boolean array with the same shape as `x` to store the result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a boolean array is returned
with values True where the corresponding element of the input is
positive infinity and values False where the element of the input is
not positive infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as zeros
and ones, if the type is boolean then as False and True.
The return value `out` is then a reference to that array.
See Also
--------
isinf, isneginf, isfinite, isnan
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when `x` is a
scalar input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isposinf(np.PINF)
array(True, dtype=bool)
>>> np.isposinf(np.inf)
array(True, dtype=bool)
>>> np.isposinf(np.NINF)
array(False, dtype=bool)
>>> np.isposinf([-np.inf, 0., np.inf])
array([False, False, True])
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isposinf(x, y)
array([0, 0, 1])
>>> y
array([0, 0, 1])
"""
return nx.logical_and(nx.isinf(x), ~nx.signbit(x), out)
Example #16
| Source File: ufunclike.py From Fluid-Designer with GNU General Public License v3.0 | 4 votes |
|
def isposinf(x, y=None):
"""
Test element-wise for positive infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
y : array_like, optional
A boolean array with the same shape as `x` to store the result.
Returns
-------
y : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a boolean array is returned
with values True where the corresponding element of the input is
positive infinity and values False where the element of the input is
not positive infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as zeros
and ones, if the type is boolean then as False and True.
The return value `y` is then a reference to that array.
See Also
--------
isinf, isneginf, isfinite, isnan
Notes
-----
Numpy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when `x` is a
scalar input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isposinf(np.PINF)
array(True, dtype=bool)
>>> np.isposinf(np.inf)
array(True, dtype=bool)
>>> np.isposinf(np.NINF)
array(False, dtype=bool)
>>> np.isposinf([-np.inf, 0., np.inf])
array([False, False, True], dtype=bool)
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isposinf(x, y)
array([0, 0, 1])
>>> y
array([0, 0, 1])
"""
if y is None:
x = nx.asarray(x)
y = nx.empty(x.shape, dtype=nx.bool_)
nx.logical_and(nx.isinf(x), ~nx.signbit(x), y)
return y
Example #17
| Source File: ufunclike.py From GraphicDesignPatternByPython with MIT License | 4 votes |
|
def isneginf(x, out=None):
"""
Test element-wise for negative infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
out : array_like, optional
A boolean array with the same shape and type as `x` to store the
result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a numpy boolean array is
returned with values True where the corresponding element of the
input is negative infinity and values False where the element of
the input is not negative infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as
zeros and ones, if the type is boolean then as False and True. The
return value `out` is then a reference to that array.
See Also
--------
isinf, isposinf, isnan, isfinite
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when x is a scalar
input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isneginf(np.NINF)
array(True, dtype=bool)
>>> np.isneginf(np.inf)
array(False, dtype=bool)
>>> np.isneginf(np.PINF)
array(False, dtype=bool)
>>> np.isneginf([-np.inf, 0., np.inf])
array([ True, False, False])
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isneginf(x, y)
array([1, 0, 0])
>>> y
array([1, 0, 0])
"""
return nx.logical_and(nx.isinf(x), nx.signbit(x), out)
Example #18
| Source File: ufunclike.py From GraphicDesignPatternByPython with MIT License | 4 votes |
|
def isposinf(x, out=None):
"""
Test element-wise for positive infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
y : array_like, optional
A boolean array with the same shape as `x` to store the result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a boolean array is returned
with values True where the corresponding element of the input is
positive infinity and values False where the element of the input is
not positive infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as zeros
and ones, if the type is boolean then as False and True.
The return value `out` is then a reference to that array.
See Also
--------
isinf, isneginf, isfinite, isnan
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when `x` is a
scalar input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isposinf(np.PINF)
array(True, dtype=bool)
>>> np.isposinf(np.inf)
array(True, dtype=bool)
>>> np.isposinf(np.NINF)
array(False, dtype=bool)
>>> np.isposinf([-np.inf, 0., np.inf])
array([False, False, True])
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isposinf(x, y)
array([0, 0, 1])
>>> y
array([0, 0, 1])
"""
return nx.logical_and(nx.isinf(x), ~nx.signbit(x), out)
Example #19
| Source File: ufunclike.py From Computable with MIT License | 4 votes |
|
def isposinf(x, y=None):
"""
Test element-wise for positive infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
y : array_like, optional
A boolean array with the same shape as `x` to store the result.
Returns
-------
y : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a boolean array is returned
with values True where the corresponding element of the input is
positive infinity and values False where the element of the input is
not positive infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as zeros
and ones, if the type is boolean then as False and True.
The return value `y` is then a reference to that array.
See Also
--------
isinf, isneginf, isfinite, isnan
Notes
-----
Numpy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when `x` is a
scalar input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isposinf(np.PINF)
array(True, dtype=bool)
>>> np.isposinf(np.inf)
array(True, dtype=bool)
>>> np.isposinf(np.NINF)
array(False, dtype=bool)
>>> np.isposinf([-np.inf, 0., np.inf])
array([False, False, True], dtype=bool)
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isposinf(x, y)
array([0, 0, 1])
>>> y
array([0, 0, 1])
"""
if y is None:
x = nx.asarray(x)
y = nx.empty(x.shape, dtype=nx.bool_)
nx.logical_and(nx.isinf(x), ~nx.signbit(x), y)
return y
Example #20
| Source File: ufunclike.py From vnpy_crypto with MIT License | 4 votes |
|
def isneginf(x, out=None):
"""
Test element-wise for negative infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
out : array_like, optional
A boolean array with the same shape and type as `x` to store the
result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a numpy boolean array is
returned with values True where the corresponding element of the
input is negative infinity and values False where the element of
the input is not negative infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as
zeros and ones, if the type is boolean then as False and True. The
return value `out` is then a reference to that array.
See Also
--------
isinf, isposinf, isnan, isfinite
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when x is a scalar
input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isneginf(np.NINF)
array(True, dtype=bool)
>>> np.isneginf(np.inf)
array(False, dtype=bool)
>>> np.isneginf(np.PINF)
array(False, dtype=bool)
>>> np.isneginf([-np.inf, 0., np.inf])
array([ True, False, False])
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isneginf(x, y)
array([1, 0, 0])
>>> y
array([1, 0, 0])
"""
return nx.logical_and(nx.isinf(x), nx.signbit(x), out)
Example #21
| Source File: ufunclike.py From vnpy_crypto with MIT License | 4 votes |
|
def isposinf(x, out=None):
"""
Test element-wise for positive infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
y : array_like, optional
A boolean array with the same shape as `x` to store the result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a boolean array is returned
with values True where the corresponding element of the input is
positive infinity and values False where the element of the input is
not positive infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as zeros
and ones, if the type is boolean then as False and True.
The return value `out` is then a reference to that array.
See Also
--------
isinf, isneginf, isfinite, isnan
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when `x` is a
scalar input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isposinf(np.PINF)
array(True, dtype=bool)
>>> np.isposinf(np.inf)
array(True, dtype=bool)
>>> np.isposinf(np.NINF)
array(False, dtype=bool)
>>> np.isposinf([-np.inf, 0., np.inf])
array([False, False, True])
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isposinf(x, y)
array([0, 0, 1])
>>> y
array([0, 0, 1])
"""
return nx.logical_and(nx.isinf(x), ~nx.signbit(x), out)
Example #22
| Source File: ufunclike.py From auto-alt-text-lambda-api with MIT License | 4 votes |
|
def isposinf(x, y=None):
"""
Test element-wise for positive infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
y : array_like, optional
A boolean array with the same shape as `x` to store the result.
Returns
-------
y : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a boolean array is returned
with values True where the corresponding element of the input is
positive infinity and values False where the element of the input is
not positive infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as zeros
and ones, if the type is boolean then as False and True.
The return value `y` is then a reference to that array.
See Also
--------
isinf, isneginf, isfinite, isnan
Notes
-----
Numpy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when `x` is a
scalar input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isposinf(np.PINF)
array(True, dtype=bool)
>>> np.isposinf(np.inf)
array(True, dtype=bool)
>>> np.isposinf(np.NINF)
array(False, dtype=bool)
>>> np.isposinf([-np.inf, 0., np.inf])
array([False, False, True], dtype=bool)
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isposinf(x, y)
array([0, 0, 1])
>>> y
array([0, 0, 1])
"""
if y is None:
x = nx.asarray(x)
y = nx.empty(x.shape, dtype=nx.bool_)
nx.logical_and(nx.isinf(x), ~nx.signbit(x), y)
return y
Example #23
| Source File: ufunclike.py From lambda-packs with MIT License | 4 votes |
|
def isposinf(x, y=None):
"""
Test element-wise for positive infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
y : array_like, optional
A boolean array with the same shape as `x` to store the result.
Returns
-------
y : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a boolean array is returned
with values True where the corresponding element of the input is
positive infinity and values False where the element of the input is
not positive infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as zeros
and ones, if the type is boolean then as False and True.
The return value `y` is then a reference to that array.
See Also
--------
isinf, isneginf, isfinite, isnan
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when `x` is a
scalar input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isposinf(np.PINF)
array(True, dtype=bool)
>>> np.isposinf(np.inf)
array(True, dtype=bool)
>>> np.isposinf(np.NINF)
array(False, dtype=bool)
>>> np.isposinf([-np.inf, 0., np.inf])
array([False, False, True], dtype=bool)
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isposinf(x, y)
array([0, 0, 1])
>>> y
array([0, 0, 1])
"""
if y is None:
x = nx.asarray(x)
y = nx.empty(x.shape, dtype=nx.bool_)
nx.logical_and(nx.isinf(x), ~nx.signbit(x), y)
return y
Example #24
| Source File: ufunclike.py From lambda-packs with MIT License | 4 votes |
|
def isneginf(x, out=None):
"""
Test element-wise for negative infinity, return result as bool array.
Parameters
----------
x : array_like
The input array.
out : array_like, optional
A boolean array with the same shape and type as `x` to store the
result.
Returns
-------
out : ndarray
A boolean array with the same dimensions as the input.
If second argument is not supplied then a numpy boolean array is
returned with values True where the corresponding element of the
input is negative infinity and values False where the element of
the input is not negative infinity.
If a second argument is supplied the result is stored there. If the
type of that array is a numeric type the result is represented as
zeros and ones, if the type is boolean then as False and True. The
return value `out` is then a reference to that array.
See Also
--------
isinf, isposinf, isnan, isfinite
Notes
-----
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
(IEEE 754).
Errors result if the second argument is also supplied when x is a scalar
input, or if first and second arguments have different shapes.
Examples
--------
>>> np.isneginf(np.NINF)
array(True, dtype=bool)
>>> np.isneginf(np.inf)
array(False, dtype=bool)
>>> np.isneginf(np.PINF)
array(False, dtype=bool)
>>> np.isneginf([-np.inf, 0., np.inf])
array([ True, False, False])
>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isneginf(x, y)
array([1, 0, 0])
>>> y
array([1, 0, 0])
"""
return nx.logical_and(nx.isinf(x), nx.signbit(x), out)
