Python numpy.core.numeric.power() Examples
The following are 20
code examples of numpy.core.numeric.power().
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Example #1
| Source File: scimath.py From pySINDy with MIT License | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #2
| Source File: scimath.py From keras-lambda with MIT License | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #3
| Source File: scimath.py From twitter-stock-recommendation with MIT License | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #4
| Source File: scimath.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #5
| Source File: scimath.py From Carnets with BSD 3-Clause "New" or "Revised" License | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #6
| Source File: scimath.py From coffeegrindsize with MIT License | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #7
| Source File: scimath.py From elasticintel with GNU General Public License v3.0 | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #8
| Source File: scimath.py From Splunking-Crime with GNU Affero General Public License v3.0 | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #9
| Source File: scimath.py From ImageFusion with MIT License | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #10
| Source File: scimath.py From mxnet-lambda with Apache License 2.0 | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #11
| Source File: scimath.py From recruit with Apache License 2.0 | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #12
| Source File: scimath.py From Fluid-Designer with GNU General Public License v3.0 | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #13
| Source File: scimath.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #14
| Source File: scimath.py From GraphicDesignPatternByPython with MIT License | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #15
| Source File: scimath.py From Mastering-Elasticsearch-7.0 with MIT License | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #16
| Source File: scimath.py From Computable with MIT License | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #17
| Source File: scimath.py From vnpy_crypto with MIT License | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #18
| Source File: scimath.py From auto-alt-text-lambda-api with MIT License | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #19
| Source File: scimath.py From lambda-packs with MIT License | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
Example #20
| Source File: scimath.py From lambda-packs with MIT License | 4 votes |
|
def power(x, p):
"""
Return x to the power p, (x**p).
If `x` contains negative values, the output is converted to the
complex domain.
Parameters
----------
x : array_like
The input value(s).
p : array_like of ints
The power(s) to which `x` is raised. If `x` contains multiple values,
`p` has to either be a scalar, or contain the same number of values
as `x`. In the latter case, the result is
``x[0]**p[0], x[1]**p[1], ...``.
Returns
-------
out : ndarray or scalar
The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
otherwise an array is returned.
See Also
--------
numpy.power
Examples
--------
>>> np.set_printoptions(precision=4)
>>> np.lib.scimath.power([2, 4], 2)
array([ 4, 16])
>>> np.lib.scimath.power([2, 4], -2)
array([ 0.25 , 0.0625])
>>> np.lib.scimath.power([-2, 4], 2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
p = _fix_int_lt_zero(p)
return nx.power(x, p)
