"""Return true division of the inputs, element-wise."""
from __future__ import division
from typing import Any, Optional
import numpy
import numpy.typing
import numpoly
from ..baseclass import ndpoly, PolyLike
from ..dispatch import implements_ufunc
DIVIDE_ERROR_MSG = """
Divisor in division is a polynomial.
Polynomial division differs from numerical division;
Use ``numpoly.poly_divide`` to get polynomial division."""
[docs]@implements_ufunc(numpy.true_divide)
def true_divide(
x1: PolyLike,
x2: PolyLike,
out: Optional[ndpoly] = None,
where: numpy.typing.ArrayLike = True,
**kwargs: Any,
) -> ndpoly:
"""
Return true division of the inputs, element-wise.
Instead of the Python traditional 'floor division', this returns a true
division. True division adjusts the output type to present the best
answer, regardless of input types.
Args:
x1:
Dividend array.
x2:
Divisor array. If ``x1.shape != x2.shape``, they must be
broadcastable to a common shape (which becomes the shape of the
output).
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:
This is a scalar if both `x1` and `x2` are scalars.
Raise:
numpoly.baseclass.FeatureNotSupported:
If `x2` contains indeterminants, numerical division is no longer
possible and an error is raised instead. For polynomial
division see ``numpoly.poly_divide``.
Example:
>>> q0q1q2 = numpoly.variable(3)
>>> numpoly.true_divide(q0q1q2, 4)
polynomial([0.25*q0, 0.25*q1, 0.25*q2])
>>> numpoly.true_divide(q0q1q2, [1, 2, 4])
polynomial([q0, 0.5*q1, 0.25*q2])
"""
x1, x2 = numpoly.align_polynomials(x1, x2)
if not x2.isconstant():
raise numpoly.FeatureNotSupported(DIVIDE_ERROR_MSG)
x2 = x2.tonumpy()
if out is None:
out_ = numpoly.ndpoly(
exponents=x1.exponents,
shape=x1.shape,
names=x1.indeterminants,
dtype=numpy.common_type(x1, numpy.array(1.0)),
)
else:
assert len(out) == 1
out_ = out[0]
assert isinstance(out_, numpoly.ndpoly)
for key in x1.keys:
out_[key] = 0
numpy.true_divide(
x1.values[key],
x2,
out=out_.values[key],
where=numpy.asarray(where),
**kwargs,
)
if out is None:
out_ = numpoly.clean_attributes(out_)
return out_