nums.numpy.float_power

nums.numpy.float_power(x1, x2, out=None, where=True, **kwargs)[source]

First array elements raised to powers from second array, element-wise.

This docstring was copied from numpy.float_power.

Some inconsistencies with the NumS version may exist.

Raise each base in x1 to the positionally-corresponding power in x2. x1 and x2 must be broadcastable to the same shape. This differs from the power function in that integers, float16, and float32 are promoted to floats with a minimum precision of float64 so that the result is always inexact. The intent is that the function will return a usable result for negative powers and seldom overflow for positive powers.

Parameters

x1 (BlockArray) – The bases.
x2 (BlockArray) – The exponents. If x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output).
out (BlockArray, None, or 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 (BlockArray, optional) – This condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None, locations within it where the condition is False will remain uninitialized.
**kwargs – For other keyword-only arguments, see the ufunc docs.

Returns

y – The bases in x1 raised to the exponents in x2.

Return type

BlockArray