"""Test element-wise for finiteness (not infinity or not Not a Number)."""
from __future__ import annotations
from typing import Any, Optional
import numpy
import numpy.typing
from ..baseclass import PolyLike
from ..dispatch import implements, simple_dispatch
[docs]@implements(numpy.isfinite)
def isfinite(
x: PolyLike,
out: Optional[numpy.ndarray] = None,
where: numpy.typing.ArrayLike = True,
**kwargs: Any,
) -> numpy.ndarray:
"""
Test element-wise for finiteness (not infinity or not Not a Number).
The result is returned as a boolean array.
Args:
x:
Input values.
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:
True where ``x`` is not positive infinity, negative infinity, or NaN;
false otherwise. This is a scalar if `x` is a scalar.
Note:
Not a Number, positive infinity and negative infinity are considered to
be non-finite.
Example:
>>> numpoly.isfinite(1)
True
>>> numpoly.isfinite(0)
True
>>> numpoly.isfinite(numpy.nan*numpoly.variable())
False
>>> numpoly.isfinite(numpy.inf)
False
>>> numpoly.isfinite(numpy.NINF)
False
>>> numpoly.isfinite([numpy.log(-1.), 1., numpy.log(0)])
array([False, True, False])
"""
out_ = simple_dispatch(
numpy_func=numpy.isfinite, inputs=(x,), where=where, **kwargs
)
if out is None:
out_ = numpy.all(numpy.asarray(out_.coefficients), axis=0)
else:
out_ = numpy.all(numpy.asarray(out_.coefficients), out=out[0], axis=0)
return out_