numpoly.zeros_like¶
- numpoly.zeros_like(a: numpoly.typing.PolyLike, 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, order: Optional[Union[Literal[C], Literal[F]]] = None, subok: bool = True, shape: Optional[Sequence[int]] = None) → numpoly.baseclass.ndpoly[source]¶
Return an array of zeros with the same shape and type as a given array.
- Args:
- a:
The shape and data-type of a define these same attributes of the returned array.
- dtype:
Overrides the data type of the result.
- order:
Overrides the memory layout of the result. ‘C’ means C-order, ‘F’ means F-order. If omitted: ‘F’ if a is Fortran contiguous, ‘C’ otherwise.
- subok:
If True, then the newly created array will use the sub-class type of ‘a’, otherwise it will be a base-class array. Defaults to True.
- shape:
Overrides the shape of the result. If order=’K’ and the number of dimensions is unchanged, will try to keep order, otherwise, order=’C’ is implied.
- Return:
Array of zeros with the same shape and type as a.
- Example:
>>> poly = numpoly.monomial(3) >>> poly polynomial([1, q0, q0**2]) >>> numpoly.zeros_like(poly) polynomial([0, 0, 0])