numpoly.polynomial¶

numpoly.polynomial(poly_like: numpoly.typing.PolyLike = 0, names: Union[None, str, Tuple[str, ...], numpoly.baseclass.ndpoly] = None, dtype: Union[numpy.dtype[Any], None, Type[Any], numpy._typing._dtype_like._SupportsDType[numpy.dtype[Any]], str, Tuple[Any, int], Tuple[Any, Union[SupportsIndex, Sequence[SupportsIndex]]], List[Any], numpy._typing._dtype_like._DTypeDict, Tuple[Any, Any]] = None, allocation: Optional[int] = None) → numpoly.baseclass.ndpoly [source]¶

Attempt to cast an object into a polynomial array.

Supports various casting options:

`dict`	Keys are tuples that represent polynomial exponents, and values are numpy arrays that represents polynomial coefficients.
`numpoly.ndpoly`	Copy of the polynomial.
`numpy.ndarray`	Constant term polynomial.
`sympy.Poly`	Convert polynomial from `sympy` to `numpoly`, if possible.
`Iterable`	Multivariate array construction.
structured array	Assumes that the input are raw polynomial core and can be used to construct a polynomial without changing the data. Used for developer convenience.

Args:

poly_like:: Input to be converted to a numpoly.ndpoly polynomial type.
names:: Name of the indeterminant variables. If possible to infer from poly_like, this argument will be ignored.
dtype:: Data type used for the polynomial coefficients.
allocation:: The maximum number of polynomial exponents. If omitted, use length of exponents for allocation.

Return:

Polynomial based on input poly_like.

Example:

>>> numpoly.polynomial({(1,): 1})
polynomial(q0)
>>> q0, q1 = numpoly.variable(2)
>>> q0**2+q0*q1+2
polynomial(q0*q1+q0**2+2)
>>> -3*q0+q0**2+q1
polynomial(q0**2+q1-3*q0)
>>> numpoly.polynomial([q0*q1, q0, q1])
polynomial([q0*q1, q0, q1])
>>> numpoly.polynomial([1, 2, 3])
polynomial([1, 2, 3])
>>> import sympy
>>> q0_, q1_ = sympy.symbols("q0, q1")
>>> numpoly.polynomial(3*q0_*q1_-4+q0_**5)
polynomial(q0**5+3*q0*q1-4)