"""Return a new array of given shape and type, filled with ones."""
from __future__ import annotations
from typing import Any, Sequence
import numpy
import numpy.typing
import numpoly
from ..baseclass import ndpoly
from ..dispatch import implements
Order = Any
try:
from typing import Literal, Union
Order = Union[Literal["C"], Literal["F"], None] # type: ignore
except ImportError:
pass
[docs]@implements(numpy.ones)
def ones(
shape: Union[int, Sequence[int]],
dtype: numpy.typing.DTypeLike = float,
order: Order = "C",
) -> ndpoly:
"""
Return a new array of given shape and type, filled with ones.
Args:
shape:
Shape of the new array, e.g., ``(2, 3)`` or ``2``.
dtype:
The desired data-type for the array, e.g., `numpy.int8`.
Default is `numpy.float64`.
order:
Whether to store multi-dimensional data in row-major
(C-style) or column-major (Fortran-style) order in
memory.
Return:
Array of ones with the given shape, dtype, and order.
Example:
>>> numpoly.ones(5)
polynomial([1.0, 1.0, 1.0, 1.0, 1.0])
"""
return numpoly.polynomial(numpy.ones(shape, dtype=dtype, order=order))