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authorCharles Harris <charlesr.harris@gmail.com>2022-06-09 11:55:32 -0600
committerGitHub <noreply@github.com>2022-06-09 11:55:32 -0600
commit5ea81775e0d2d13a4fec6bab882002e050bd3da1 (patch)
treed2dc068c7c06c22393841ddc0dd7ee011996249f /numpy/array_api/_searching_functions.py
parent9d6b102617a92ad41964a5611c8dec87d3053a9f (diff)
parent5447192c8dc5d43d837b93ed5c5d47457e367669 (diff)
downloadnumpy-5ea81775e0d2d13a4fec6bab882002e050bd3da1.tar.gz
Merge branch 'main' into bugfix_16492_segfault_on_pyfragments
Diffstat (limited to 'numpy/array_api/_searching_functions.py')
-rw-r--r--numpy/array_api/_searching_functions.py47
1 files changed, 47 insertions, 0 deletions
diff --git a/numpy/array_api/_searching_functions.py b/numpy/array_api/_searching_functions.py
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+from __future__ import annotations
+
+from ._array_object import Array
+from ._dtypes import _result_type
+
+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.
+ """
+ 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.
+ """
+ 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))