FM / array

/opt/cloudlinux/venv/lib/python3.11/site-packages/numpy/array_api/

/opt/cloudlinux/venv/lib/python3.11/site-packages/numpy/array_api

Name	Size	Mode	Actions
tests/	-	0755	rm
__pycache__/	-	0755	rm
linalg.py	18221	0644	edit dl rm
setup.py	341	0644	edit dl rm
_array_object.py	43739	0644	edit dl rm
_constants.py	66	0644	edit dl rm
_creation_functions.py	10050	0644	edit dl rm
_data_type_functions.py	6288	0644	edit dl rm
_dtypes.py	4823	0644	edit dl rm
_elementwise_functions.py	25992	0644	edit dl rm
_indexing_functions.py	601	0644	edit dl rm
_manipulation_functions.py	3317	0644	edit dl rm
_searching_functions.py	1715	0644	edit dl rm
_set_functions.py	2948	0644	edit dl rm
_sorting_functions.py	2031	0644	edit dl rm
_statistical_functions.py	3584	0644	edit dl rm
_typing.py	1228	0644	edit dl rm
_utility_functions.py	824	0644	edit dl rm
__init__.py	10355	0644	edit dl rm

Edit: /opt/cloudlinux/venv/lib/python3.11/site-packages/numpy/array_api/_searching_functions.py (1715B)

from __future__ import annotations

from ._array_object import Array
from ._dtypes import _result_type, _real_numeric_dtypes

from typing import Optional, Tuple

import numpy as np

def argmax(x: Array, /, *, axis: Optional[int] = None, keepdims: bool = False) -> Array:
    """
    Array API compatible wrapper for :py:func:`np.argmax <numpy.argmax>`.

See its docstring for more information.
    """
    if x.dtype not in _real_numeric_dtypes:
        raise TypeError("Only real numeric dtypes are allowed in argmax")
    return Array._new(np.asarray(np.argmax(x._array, axis=axis, keepdims=keepdims)))

def argmin(x: Array, /, *, axis: Optional[int] = None, keepdims: bool = False) -> Array:
    """
    Array API compatible wrapper for :py:func:`np.argmin <numpy.argmin>`.

See its docstring for more information.
    """
    if x.dtype not in _real_numeric_dtypes:
        raise TypeError("Only real numeric dtypes are allowed in argmin")
    return Array._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 tuple(Array._new(i) for i in 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.
    """
    # Call result type here just to raise on disallowed type combinations
    _result_type(x1.dtype, x2.dtype)
    x1, x2 = Array._normalize_two_args(x1, x2)
    return Array._new(np.where(condition._array, x1._array, x2._array))

from __future__ import annotations from ._array_object import Array from ._dtypes import _result_type, _real_numeric_dtypes from typing import Optional, Tuple import numpy as np def argmax(x: Array, /, *, axis: Optional[int] = None, keepdims: bool = False) -> Array: """ Array API compatible wrapper for :py:func:`np.argmax `. See its docstring for more information. """ if x.dtype not in _real_numeric_dtypes: raise TypeError("Only real numeric dtypes are allowed in argmax") return Array._new(np.asarray(np.argmax(x._array, axis=axis, keepdims=keepdims))) def argmin(x: Array, /, *, axis: Optional[int] = None, keepdims: bool = False) -> Array: """ Array API compatible wrapper for :py:func:`np.argmin `. See its docstring for more information. """ if x.dtype not in _real_numeric_dtypes: raise TypeError("Only real numeric dtypes are allowed in argmin") return Array._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 `. See its docstring for more information. """ return tuple(Array._new(i) for i in np.nonzero(x._array)) def where(condition: Array, x1: Array, x2: Array, /) -> Array: """ Array API compatible wrapper for :py:func:`np.where `. See its docstring for more information. """ # Call result type here just to raise on disallowed type combinations _result_type(x1.dtype, x2.dtype) x1, x2 = Array._normalize_two_args(x1, x2) return Array._new(np.where(condition._array, x1._array, x2._array))