"""Calculate the absolute value element-wise."""
from __future__ import annotations
from typing import Any, Optional
import numpy
import numpy.typing
from ..baseclass import ndpoly, PolyLike
from ..dispatch import implements, simple_dispatch
[docs]@implements(numpy.absolute)
def absolute(
x: PolyLike,
out: Optional[ndpoly] = None,
where: numpy.typing.ArrayLike = True,
**kwargs: Any,
) -> ndpoly:
r"""
Calculate the absolute value element-wise.
Args:
x:
Input array.
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:
An ndarray containing the absolute value of. each element in `x`.
For complex input, ``a + ib``, the absolute value is
:math:`\sqrt{a^2+b^2}`. This is a scalar if `x` is a scalar.
Example:
>>> q0 = numpoly.variable()
>>> poly = numpoly.polynomial([-1, 1, -2.3*q0, 2.3*q0])
>>> poly
polynomial([-1.0, 1.0, -2.3*q0, 2.3*q0])
>>> numpoly.absolute(poly)
polynomial([1.0, 1.0, 2.3*q0, 2.3*q0])
>>> poly = numpoly.polynomial([q0, 1j*q0, (3+4j)*q0])
>>> poly
polynomial([q0, 1j*q0, (3+4j)*q0])
>>> numpoly.absolute(poly)
polynomial([q0, q0, 5.0*q0])
"""
return simple_dispatch(
numpy_func=numpy.absolute,
inputs=(x,),
out=None if out is None else (out,),
where=where,
**kwargs,
)