square(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])

Some inconsistencies with the Dask version may exist.

Return the element-wise square of the input.

Parameters

x : array_like

Input data.

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

This condition is broadcast over the input. At locations where the condition is True, the :None:None:`out` array will be set to the ufunc result. Elsewhere, the :None:None:`out` array will retain its original value. Note that if an uninitialized :None:None:`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 <ufuncs.kwargs> .

Returns

out : ndarray or scalar

Element-wise :None:None:`x*x`, of the same shape and dtype as x. This is a scalar if x is a scalar.

This docstring was copied from numpy.square.

See Also

numpy.linalg.matrix_power

power

sqrt

Examples

This example is valid syntax, but we were not able to check execution

>>> np.square([-1j, 1])  # doctest: +SKIP
array([-1.-0.j,  1.+0.j])

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