/opt/cloudlinux/venv/lib/python3.11/site-packages/numpy/typing/tests/data/reveal
import numpy as np from numpy._typing import NDArray from typing import Any i8: np.int64 f8: np.float64 AR_b: NDArray[np.bool_] AR_i8: NDArray[np.int64] AR_f8: NDArray[np.float64] AR_LIKE_f8: list[float] reveal_type(np.take_along_axis(AR_f8, AR_i8, axis=1)) # E: ndarray[Any, dtype[{float64}]] reveal_type(np.take_along_axis(f8, AR_i8, axis=None)) # E: ndarray[Any, dtype[{float64}]] reveal_type(np.put_along_axis(AR_f8, AR_i8, "1.0", axis=1)) # E: None reveal_type(np.expand_dims(AR_i8, 2)) # E: ndarray[Any, dtype[{int64}]] reveal_type(np.expand_dims(AR_LIKE_f8, 2)) # E: ndarray[Any, dtype[Any]] reveal_type(np.column_stack([AR_i8])) # E: ndarray[Any, dtype[{int64}]] reveal_type(np.column_stack([AR_LIKE_f8])) # E: ndarray[Any, dtype[Any]] reveal_type(np.dstack([AR_i8])) # E: ndarray[Any, dtype[{int64}]] reveal_type(np.dstack([AR_LIKE_f8])) # E: ndarray[Any, dtype[Any]] reveal_type(np.row_stack([AR_i8])) # E: ndarray[Any, dtype[{int64}]] reveal_type(np.row_stack([AR_LIKE_f8])) # E: ndarray[Any, dtype[Any]] reveal_type(np.array_split(AR_i8, [3, 5, 6, 10])) # E: list[ndarray[Any, dtype[{int64}]]] reveal_type(np.array_split(AR_LIKE_f8, [3, 5, 6, 10])) # E: list[ndarray[Any, dtype[Any]]] reveal_type(np.split(AR_i8, [3, 5, 6, 10])) # E: list[ndarray[Any, dtype[{int64}]]] reveal_type(np.split(AR_LIKE_f8, [3, 5, 6, 10])) # E: list[ndarray[Any, dtype[Any]]] reveal_type(np.hsplit(AR_i8, [3, 5, 6, 10])) # E: list[ndarray[Any, dtype[{int64}]]] reveal_type(np.hsplit(AR_LIKE_f8, [3, 5, 6, 10])) # E: list[ndarray[Any, dtype[Any]]] reveal_type(np.vsplit(AR_i8, [3, 5, 6, 10])) # E: list[ndarray[Any, dtype[{int64}]]] reveal_type(np.vsplit(AR_LIKE_f8, [3, 5, 6, 10])) # E: list[ndarray[Any, dtype[Any]]] reveal_type(np.dsplit(AR_i8, [3, 5, 6, 10])) # E: list[ndarray[Any, dtype[{int64}]]] reveal_type(np.dsplit(AR_LIKE_f8, [3, 5, 6, 10])) # E: list[ndarray[Any, dtype[Any]]] reveal_type(np.lib.shape_base.get_array_prepare(AR_i8)) # E: lib.shape_base._ArrayPrepare reveal_type(np.lib.shape_base.get_array_prepare(AR_i8, 1)) # E: Union[None, lib.shape_base._ArrayPrepare] reveal_type(np.get_array_wrap(AR_i8)) # E: lib.shape_base._ArrayWrap reveal_type(np.get_array_wrap(AR_i8, 1)) # E: Union[None, lib.shape_base._ArrayWrap] reveal_type(np.kron(AR_b, AR_b)) # E: ndarray[Any, dtype[bool_]] reveal_type(np.kron(AR_b, AR_i8)) # E: ndarray[Any, dtype[signedinteger[Any]]] reveal_type(np.kron(AR_f8, AR_f8)) # E: ndarray[Any, dtype[floating[Any]]] reveal_type(np.tile(AR_i8, 5)) # E: ndarray[Any, dtype[{int64}]] reveal_type(np.tile(AR_LIKE_f8, [2, 2])) # E: ndarray[Any, dtype[Any]]
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..
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arithmetic.pyi
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array_constructors.pyi
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arraypad.pyi
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arrayprint.pyi
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arraysetops.pyi
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arrayterator.pyi
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bitwise_ops.pyi
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char.pyi
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chararray.pyi
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comparisons.pyi
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constants.pyi
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ctypeslib.pyi
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datasource.pyi
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dtype.pyi
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einsumfunc.pyi
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emath.pyi
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false_positives.pyi
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fft.pyi
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flatiter.pyi
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fromnumeric.pyi
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getlimits.pyi
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histograms.pyi
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index_tricks.pyi
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lib_function_base.pyi
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lib_polynomial.pyi
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lib_utils.pyi
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lib_version.pyi
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linalg.pyi
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matrix.pyi
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memmap.pyi
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mod.pyi
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modules.pyi
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multiarray.pyi
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nbit_base_example.pyi
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ndarray_conversion.pyi
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ndarray_misc.pyi
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ndarray_shape_manipulation.pyi
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nditer.pyi
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nested_sequence.pyi
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npyio.pyi
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numeric.pyi
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numerictypes.pyi
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random.pyi
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rec.pyi
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scalars.pyi
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shape_base.pyi
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stride_tricks.pyi
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testing.pyi
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twodim_base.pyi
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type_check.pyi
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ufunc_config.pyi
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ufunclike.pyi
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ufuncs.pyi
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version.pyi
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warnings_and_errors.pyi
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