numpoly.poly_divide

numpoly.poly_divide(x1: numpoly.typing.PolyLike, x2: numpoly.typing.PolyLike, out: Optional[numpoly.baseclass.ndpoly] = None, where: Union[numpy._typing._array_like._SupportsArray[numpy.dtype], numpy._typing._nested_sequence._NestedSequence[numpy._typing._array_like._SupportsArray[numpy.dtype]], bool, int, float, complex, str, bytes, numpy._typing._nested_sequence._NestedSequence[Union[bool, int, float, complex, str, bytes]]] = True, **kwargs: Any) → numpoly.baseclass.ndpoly

Return a polynomial division of the inputs, element-wise.

Note that if divisor is a polynomial, then the division could have a remainder, as polynomial division is not exactly the same as numerical division.

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.

Example:

>>> q0 = numpoly.variable()
>>> poly = numpoly.polynomial([14, q0**2-3])
>>> numpoly.poly_divide(poly, 4)
polynomial([3.5, 0.25*q0**2-0.75])
>>> numpoly.poly_divide(poly, q0)
polynomial([0.0, q0])