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

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

AR_LIKE_b = [[True, True], [True, True]]
AR_LIKE_i = [[1, 2], [3, 4]]
AR_LIKE_f = [[1.0, 2.0], [3.0, 4.0]]
AR_LIKE_U = [["1", "2"], ["3", "4"]]

AR_i8: np.ndarray[Any, np.dtype[np.int64]] = np.array(AR_LIKE_i, dtype=np.int64)

np.ndenumerate(AR_i8)
np.ndenumerate(AR_LIKE_f)
np.ndenumerate(AR_LIKE_U)

np.ndenumerate(AR_i8).iter
np.ndenumerate(AR_LIKE_f).iter
np.ndenumerate(AR_LIKE_U).iter

next(np.ndenumerate(AR_i8))
next(np.ndenumerate(AR_LIKE_f))
next(np.ndenumerate(AR_LIKE_U))

iter(np.ndenumerate(AR_i8))
iter(np.ndenumerate(AR_LIKE_f))
iter(np.ndenumerate(AR_LIKE_U))

iter(np.ndindex(1, 2, 3))
next(np.ndindex(1, 2, 3))

np.unravel_index([22, 41, 37], (7, 6))
np.unravel_index([31, 41, 13], (7, 6), order='F')
np.unravel_index(1621, (6, 7, 8, 9))

np.ravel_multi_index(AR_LIKE_i, (7, 6))
np.ravel_multi_index(AR_LIKE_i, (7, 6), order='F')
np.ravel_multi_index(AR_LIKE_i, (4, 6), mode='clip')
np.ravel_multi_index(AR_LIKE_i, (4, 4), mode=('clip', 'wrap'))
np.ravel_multi_index((3, 1, 4, 1), (6, 7, 8, 9))

np.mgrid[1:1:2]
np.mgrid[1:1:2, None:10]

np.ogrid[1:1:2]
np.ogrid[1:1:2, None:10]

np.index_exp[0:1]
np.index_exp[0:1, None:3]
np.index_exp[0, 0:1, ..., [0, 1, 3]]

np.s_[0:1]
np.s_[0:1, None:3]
np.s_[0, 0:1, ..., [0, 1, 3]]

np.ix_(AR_LIKE_b[0])
np.ix_(AR_LIKE_i[0], AR_LIKE_f[0])
np.ix_(AR_i8[0])

np.fill_diagonal(AR_i8, 5)

np.diag_indices(4)
np.diag_indices(2, 3)

np.diag_indices_from(AR_i8)

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