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from __future__ import annotations
from ._array_object import ndarray
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from ._types import Tuple, Array
import numpy as np
def argmax(x: Array, /, *, axis: int = None, keepdims: bool = False) -> Array:
"""
Array API compatible wrapper for :py:func:`np.argmax <numpy.argmax>`.
See its docstring for more information.
"""
# Note: this currently fails as np.argmax does not implement keepdims
return ndarray._new(np.asarray(np.argmax(x._array, axis=axis, keepdims=keepdims)))
def argmin(x: Array, /, *, axis: int = None, keepdims: bool = False) -> Array:
"""
Array API compatible wrapper for :py:func:`np.argmin <numpy.argmin>`.
See its docstring for more information.
"""
# Note: this currently fails as np.argmin does not implement keepdims
return ndarray._new(np.asarray(np.argmin(x._array, axis=axis, keepdims=keepdims)))
def nonzero(x: Array, /) -> Tuple[Array, ...]:
"""
Array API compatible wrapper for :py:func:`np.nonzero <numpy.nonzero>`.
See its docstring for more information.
"""
return ndarray._new(np.nonzero(x._array))
def where(condition: Array, x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.where <numpy.where>`.
See its docstring for more information.
"""
return ndarray._new(np.where(condition._array, x1._array, x2._array))
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