numpy.square#
- numpy.square(x/out=None*where=Truecasting='same_kind'order='K'dtype=Nonesubok=True[signature]) = <ufunc 'square'>#
Return the element-wise square of the input.
- Parameters:
- xarray_like
Input data.
- outndarrayNoneor tuple of ndarray and Noneoptional
A location into which the result is stored. If providedit 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.
- wherearray_likeoptional
This condition is broadcast over the input. At locations where the condition is Truethe out array will be set to the ufunc result. Elsewherethe out array will retain its original value. Note that if an uninitialized out array is created via the default
out=Nonelocations within it where the condition is False will remain uninitialized.- **kwargs
For other keyword-only argumentssee the ufunc docs.
- Returns:
- outndarray or scalar
Element-wise x*xof the same shape and dtype as x. This is a scalar if x is a scalar.
See also
Examples
>>> import numpy as np >>> np.square([-1j, 1]) array([-1.-0.j 1.+0.j])