numpy.power — NumPy v1.13 Manual (original) (raw)
numpy. power(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, _subok=True_[, signature, _extobj_]) = <ufunc 'power'>¶
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. out : ndarray, None, or tuple of ndarray and None, optional A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs. where : array_like, optional Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. **kwargs For other keyword-only arguments, see theufunc docs. |
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| Returns: | y : ndarray The bases in x1 raised to the exponents in x2. |
See also
power function that promotes integers to float
Examples
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]])