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

NameTypeSizeLast ModifiedActions
arithmetic.pyi File 20805 bytes April 17 2025 13:10:58.
array_constructors.pyi File 11831 bytes April 17 2025 13:10:58.
arraypad.pyi File 694 bytes April 17 2025 13:10:58.
arrayprint.pyi File 686 bytes April 17 2025 13:10:58.
arraysetops.pyi File 4671 bytes April 17 2025 13:10:58.
arrayterator.pyi File 1128 bytes April 17 2025 13:10:58.
bitwise_ops.pyi File 3607 bytes April 17 2025 13:10:58.
char.pyi File 8047 bytes April 17 2025 13:10:58.
chararray.pyi File 6312 bytes April 17 2025 13:10:58.
comparisons.pyi File 8018 bytes April 17 2025 13:10:58.
constants.pyi File 1940 bytes April 17 2025 13:10:58.
ctypeslib.pyi File 5107 bytes April 17 2025 13:10:58.
datasource.pyi File 557 bytes April 17 2025 13:10:58.
dtype.pyi File 2787 bytes April 17 2025 13:10:58.
einsumfunc.pyi File 2173 bytes April 17 2025 13:10:58.
emath.pyi File 2538 bytes April 17 2025 13:10:58.
false_positives.pyi File 349 bytes April 17 2025 13:10:58.
fft.pyi File 1852 bytes April 17 2025 13:10:58.
flatiter.pyi File 819 bytes April 17 2025 13:10:58.
fromnumeric.pyi File 13631 bytes April 17 2025 13:10:58.
getlimits.pyi File 1547 bytes April 17 2025 13:10:58.
histograms.pyi File 1391 bytes April 17 2025 13:10:58.
index_tricks.pyi File 3481 bytes April 17 2025 13:10:58.
lib_function_base.pyi File 9140 bytes April 17 2025 13:10:58.
lib_polynomial.pyi File 6353 bytes April 17 2025 13:10:58.
lib_utils.pyi File 917 bytes April 17 2025 13:10:58.
lib_version.pyi File 605 bytes April 17 2025 13:10:58.
linalg.pyi File 5217 bytes April 17 2025 13:10:58.
matrix.pyi File 3033 bytes April 17 2025 13:10:58.
memmap.pyi File 755 bytes April 17 2025 13:10:58.
mod.pyi File 5989 bytes April 17 2025 13:10:58.
modules.pyi File 1994 bytes April 17 2025 13:10:58.
multiarray.pyi File 5670 bytes April 17 2025 13:10:58.
nbit_base_example.pyi File 500 bytes April 17 2025 13:10:58.
ndarray_conversion.pyi File 1913 bytes April 17 2025 13:10:58.
ndarray_misc.pyi File 7797 bytes April 17 2025 13:10:58.
ndarray_shape_manipulation.pyi File 904 bytes April 17 2025 13:10:58.
nditer.pyi File 2067 bytes April 17 2025 13:10:58.
nested_sequence.pyi File 648 bytes April 17 2025 13:10:58.
npyio.pyi File 4434 bytes April 17 2025 13:10:58.
numeric.pyi File 6802 bytes April 17 2025 13:10:58.
numerictypes.pyi File 1711 bytes April 17 2025 13:10:58.
random.pyi File 129510 bytes April 17 2025 13:10:58.
rec.pyi File 3380 bytes April 17 2025 13:10:58.
scalars.pyi File 5347 bytes April 17 2025 13:10:58.
shape_base.pyi File 2632 bytes April 17 2025 13:10:58.
stride_tricks.pyi File 1563 bytes April 17 2025 13:10:58.
testing.pyi File 8877 bytes April 17 2025 13:10:58.
twodim_base.pyi File 3327 bytes April 17 2025 13:10:58.
type_check.pyi File 3031 bytes April 17 2025 13:10:58.
ufunc_config.pyi File 1304 bytes April 17 2025 13:10:58.
ufunclike.pyi File 1319 bytes April 17 2025 13:10:58.
ufuncs.pyi File 2919 bytes April 17 2025 13:10:58.
version.pyi File 313 bytes April 17 2025 13:10:58.
warnings_and_errors.pyi File 420 bytes April 17 2025 13:10:58.

Reading File: //opt/cloudlinux/venv/lib/python3.11/site-packages/numpy/typing/tests/data/reveal//arraysetops.pyi

import numpy as np
import numpy.typing as npt

AR_b: npt.NDArray[np.bool_]
AR_i8: npt.NDArray[np.int64]
AR_f8: npt.NDArray[np.float64]
AR_M: npt.NDArray[np.datetime64]
AR_O: npt.NDArray[np.object_]

AR_LIKE_f8: list[float]

reveal_type(np.ediff1d(AR_b))  # E: ndarray[Any, dtype[{int8}]]
reveal_type(np.ediff1d(AR_i8, to_end=[1, 2, 3]))  # E: ndarray[Any, dtype[{int64}]]
reveal_type(np.ediff1d(AR_M))  # E: ndarray[Any, dtype[timedelta64]]
reveal_type(np.ediff1d(AR_O))  # E: ndarray[Any, dtype[object_]]
reveal_type(np.ediff1d(AR_LIKE_f8, to_begin=[1, 1.5]))  # E: ndarray[Any, dtype[Any]]

reveal_type(np.intersect1d(AR_i8, AR_i8))  # E: ndarray[Any, dtype[{int64}]]
reveal_type(np.intersect1d(AR_M, AR_M, assume_unique=True))  # E: ndarray[Any, dtype[datetime64]]
reveal_type(np.intersect1d(AR_f8, AR_i8))  # E: ndarray[Any, dtype[Any]]
reveal_type(np.intersect1d(AR_f8, AR_f8, return_indices=True))  # E: Tuple[ndarray[Any, dtype[{float64}]], ndarray[Any, dtype[{intp}]], ndarray[Any, dtype[{intp}]]]

reveal_type(np.setxor1d(AR_i8, AR_i8))  # E: ndarray[Any, dtype[{int64}]]
reveal_type(np.setxor1d(AR_M, AR_M, assume_unique=True))  # E: ndarray[Any, dtype[datetime64]]
reveal_type(np.setxor1d(AR_f8, AR_i8))  # E: ndarray[Any, dtype[Any]]

reveal_type(np.in1d(AR_i8, AR_i8))  # E: ndarray[Any, dtype[bool_]]
reveal_type(np.in1d(AR_M, AR_M, assume_unique=True))  # E: ndarray[Any, dtype[bool_]]
reveal_type(np.in1d(AR_f8, AR_i8))  # E: ndarray[Any, dtype[bool_]]
reveal_type(np.in1d(AR_f8, AR_LIKE_f8, invert=True))  # E: ndarray[Any, dtype[bool_]]

reveal_type(np.isin(AR_i8, AR_i8))  # E: ndarray[Any, dtype[bool_]]
reveal_type(np.isin(AR_M, AR_M, assume_unique=True))  # E: ndarray[Any, dtype[bool_]]
reveal_type(np.isin(AR_f8, AR_i8))  # E: ndarray[Any, dtype[bool_]]
reveal_type(np.isin(AR_f8, AR_LIKE_f8, invert=True))  # E: ndarray[Any, dtype[bool_]]

reveal_type(np.union1d(AR_i8, AR_i8))  # E: ndarray[Any, dtype[{int64}]]
reveal_type(np.union1d(AR_M, AR_M))  # E: ndarray[Any, dtype[datetime64]]
reveal_type(np.union1d(AR_f8, AR_i8))  # E: ndarray[Any, dtype[Any]]

reveal_type(np.setdiff1d(AR_i8, AR_i8))  # E: ndarray[Any, dtype[{int64}]]
reveal_type(np.setdiff1d(AR_M, AR_M, assume_unique=True))  # E: ndarray[Any, dtype[datetime64]]
reveal_type(np.setdiff1d(AR_f8, AR_i8))  # E: ndarray[Any, dtype[Any]]

reveal_type(np.unique(AR_f8))  # E: ndarray[Any, dtype[{float64}]]
reveal_type(np.unique(AR_LIKE_f8, axis=0))  # E: ndarray[Any, dtype[Any]]
reveal_type(np.unique(AR_f8, return_index=True))  # E: Tuple[ndarray[Any, dtype[{float64}]], ndarray[Any, dtype[{intp}]]]
reveal_type(np.unique(AR_LIKE_f8, return_index=True))  # E: Tuple[ndarray[Any, dtype[Any]], ndarray[Any, dtype[{intp}]]]
reveal_type(np.unique(AR_f8, return_inverse=True))  # E: Tuple[ndarray[Any, dtype[{float64}]], ndarray[Any, dtype[{intp}]]]
reveal_type(np.unique(AR_LIKE_f8, return_inverse=True))  # E: Tuple[ndarray[Any, dtype[Any]], ndarray[Any, dtype[{intp}]]]
reveal_type(np.unique(AR_f8, return_counts=True))  # E: Tuple[ndarray[Any, dtype[{float64}]], ndarray[Any, dtype[{intp}]]]
reveal_type(np.unique(AR_LIKE_f8, return_counts=True))  # E: Tuple[ndarray[Any, dtype[Any]], ndarray[Any, dtype[{intp}]]]
reveal_type(np.unique(AR_f8, return_index=True, return_inverse=True))  # E: Tuple[ndarray[Any, dtype[{float64}]], ndarray[Any, dtype[{intp}]], ndarray[Any, dtype[{intp}]]]
reveal_type(np.unique(AR_LIKE_f8, return_index=True, return_inverse=True))  # E: Tuple[ndarray[Any, dtype[Any]], ndarray[Any, dtype[{intp}]], ndarray[Any, dtype[{intp}]]]
reveal_type(np.unique(AR_f8, return_index=True, return_counts=True))  # E: Tuple[ndarray[Any, dtype[{float64}]], ndarray[Any, dtype[{intp}]], ndarray[Any, dtype[{intp}]]]
reveal_type(np.unique(AR_LIKE_f8, return_index=True, return_counts=True))  # E: Tuple[ndarray[Any, dtype[Any]], ndarray[Any, dtype[{intp}]], ndarray[Any, dtype[{intp}]]]
reveal_type(np.unique(AR_f8, return_inverse=True, return_counts=True))  # E: Tuple[ndarray[Any, dtype[{float64}]], ndarray[Any, dtype[{intp}]], ndarray[Any, dtype[{intp}]]]
reveal_type(np.unique(AR_LIKE_f8, return_inverse=True, return_counts=True))  # E: Tuple[ndarray[Any, dtype[Any]], ndarray[Any, dtype[{intp}]], ndarray[Any, dtype[{intp}]]]
reveal_type(np.unique(AR_f8, return_index=True, return_inverse=True, return_counts=True))  # E: Tuple[ndarray[Any, dtype[{float64}]], ndarray[Any, dtype[{intp}]], ndarray[Any, dtype[{intp}]], ndarray[Any, dtype[{intp}]]]
reveal_type(np.unique(AR_LIKE_f8, return_index=True, return_inverse=True, return_counts=True))  # E: Tuple[ndarray[Any, dtype[Any]], ndarray[Any, dtype[{intp}]], ndarray[Any, dtype[{intp}]], ndarray[Any, dtype[{intp}]]]

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