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Files and Folders in: //opt/cloudlinux/venv/lib64/python3.11//site-packages/numpy/typing/tests/data//pass/

NameTypeSizeLast ModifiedActions
__pycache__ Directory - -
arithmetic.py File 7455 bytes April 17 2025 13:10:58.
array_constructors.py File 2419 bytes April 17 2025 13:10:58.
array_like.py File 916 bytes April 17 2025 13:10:58.
arrayprint.py File 766 bytes April 17 2025 13:10:58.
arrayterator.py File 393 bytes April 17 2025 13:10:58.
bitwise_ops.py File 970 bytes April 17 2025 13:10:58.
comparisons.py File 2992 bytes April 17 2025 13:10:58.
dtype.py File 1069 bytes April 17 2025 13:10:58.
einsumfunc.py File 1370 bytes April 17 2025 13:10:58.
flatiter.py File 174 bytes April 17 2025 13:10:58.
fromnumeric.py File 3742 bytes April 17 2025 13:10:58.
index_tricks.py File 1492 bytes April 17 2025 13:10:58.
lib_utils.py File 420 bytes April 17 2025 13:10:58.
lib_version.py File 299 bytes April 17 2025 13:10:58.
literal.py File 1331 bytes April 17 2025 13:10:58.
mod.py File 1578 bytes April 17 2025 13:10:58.
modules.py File 595 bytes April 17 2025 13:10:58.
multiarray.py File 1331 bytes April 17 2025 13:10:58.
ndarray_conversion.py File 1626 bytes April 17 2025 13:10:58.
ndarray_misc.py File 2715 bytes April 17 2025 13:10:58.
ndarray_shape_manipulation.py File 640 bytes April 17 2025 13:10:58.
numeric.py File 1490 bytes April 17 2025 13:10:58.
numerictypes.py File 750 bytes April 17 2025 13:10:58.
random.py File 61881 bytes April 17 2025 13:10:58.
scalars.py File 3479 bytes April 17 2025 13:10:58.
simple.py File 2676 bytes April 17 2025 13:10:58.
simple_py3.py File 96 bytes April 17 2025 13:10:58.
ufunc_config.py File 1120 bytes April 17 2025 13:10:58.
ufunclike.py File 1039 bytes April 17 2025 13:10:58.
ufuncs.py File 462 bytes April 17 2025 13:10:58.
warnings_and_errors.py File 150 bytes April 17 2025 13:10:58.

Reading File: //opt/cloudlinux/venv/lib64/python3.11//site-packages/numpy/typing/tests/data//pass//ufunclike.py

from __future__ import annotations
from typing import Any
import numpy as np


class Object:
    def __ceil__(self) -> Object:
        return self

    def __floor__(self) -> Object:
        return self

    def __ge__(self, value: object) -> bool:
        return True

    def __array__(self) -> np.ndarray[Any, np.dtype[np.object_]]:
        ret = np.empty((), dtype=object)
        ret[()] = self
        return ret


AR_LIKE_b = [True, True, False]
AR_LIKE_u = [np.uint32(1), np.uint32(2), np.uint32(3)]
AR_LIKE_i = [1, 2, 3]
AR_LIKE_f = [1.0, 2.0, 3.0]
AR_LIKE_O = [Object(), Object(), Object()]
AR_U: np.ndarray[Any, np.dtype[np.str_]] = np.zeros(3, dtype="U5")

np.fix(AR_LIKE_b)
np.fix(AR_LIKE_u)
np.fix(AR_LIKE_i)
np.fix(AR_LIKE_f)
np.fix(AR_LIKE_O)
np.fix(AR_LIKE_f, out=AR_U)

np.isposinf(AR_LIKE_b)
np.isposinf(AR_LIKE_u)
np.isposinf(AR_LIKE_i)
np.isposinf(AR_LIKE_f)
np.isposinf(AR_LIKE_f, out=AR_U)

np.isneginf(AR_LIKE_b)
np.isneginf(AR_LIKE_u)
np.isneginf(AR_LIKE_i)
np.isneginf(AR_LIKE_f)
np.isneginf(AR_LIKE_f, out=AR_U)

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