numpy.power(x1, x2[, out]) =
First array elements raised to powers from second array, element-wise.
Raise each base in x1
to the positionally-corresponding power in x2
. x1
and x2
must be broadcastable to the same shape. Note that an integer type raised to a negative integer power will raise a ValueError.
Parameters: |
x1 : array_like The bases. x2 : array_like The exponents. |
---|---|
Returns: |
y : ndarray The bases in |
See also
float_power
Cube each element in a list.
>>> x1 = range(6) >>> x1 [0, 1, 2, 3, 4, 5] >>> np.power(x1, 3) array([ 0, 1, 8, 27, 64, 125])
Raise the bases to different exponents.
>>> x2 = [1.0, 2.0, 3.0, 3.0, 2.0, 1.0] >>> np.power(x1, x2) array([ 0., 1., 8., 27., 16., 5.])
The effect of broadcasting.
>>> x2 = np.array([[1, 2, 3, 3, 2, 1], [1, 2, 3, 3, 2, 1]]) >>> x2 array([[1, 2, 3, 3, 2, 1], [1, 2, 3, 3, 2, 1]]) >>> np.power(x1, x2) array([[ 0, 1, 8, 27, 16, 5], [ 0, 1, 8, 27, 16, 5]])
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https://docs.scipy.org/doc/numpy-1.12.0/reference/generated/numpy.power.html