"""Return the element-wise square of the input."""
from __future__ import annotations
from typing import Any, Optional
import numpy
from ..baseclass import ndpoly, PolyLike
from ..dispatch import implements
from .multiply import multiply
[docs]@implements(numpy.square)
def square(
x: PolyLike,
out: Optional[ndpoly] = None,
where: numpy.typing.ArrayLike = True,
**kwargs: Any,
) -> ndpoly:
"""
Return the element-wise square of the input.
Args:
x:
Input data.
out:
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:
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:
Keyword args passed to numpy.ufunc.
Return:
Element-wise `x*x`, of the same shape and dtype as `x`.
This is a scalar if `x` is a scalar.
Example:
>>> numpoly.square([1j, 1])
polynomial([(-1+0j), (1+0j)])
>>> poly = numpoly.sum(numpoly.variable(2))
>>> poly
polynomial(q1+q0)
>>> numpoly.square(poly)
polynomial(q1**2+2*q0*q1+q0**2)
"""
return multiply(x, x, out=out, where=where, **kwargs)