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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//ndarray_misc.pyi

"""
Tests for miscellaneous (non-magic) ``np.ndarray``/``np.generic`` methods.

More extensive tests are performed for the methods'
function-based counterpart in `../from_numeric.py`.

"""

import operator
import ctypes as ct
from typing import Any

import numpy as np
from numpy._typing import NDArray

class SubClass(NDArray[np.object_]): ...

f8: np.float64
B: SubClass
AR_f8: NDArray[np.float64]
AR_i8: NDArray[np.int64]
AR_U: NDArray[np.str_]
AR_V: NDArray[np.void]

ctypes_obj = AR_f8.ctypes

reveal_type(AR_f8.__dlpack__())  # E: Any
reveal_type(AR_f8.__dlpack_device__())  # E: Tuple[int, Literal[0]]

reveal_type(ctypes_obj.data)  # E: int
reveal_type(ctypes_obj.shape)  # E: ctypes.Array[{c_intp}]
reveal_type(ctypes_obj.strides)  # E: ctypes.Array[{c_intp}]
reveal_type(ctypes_obj._as_parameter_)  # E: ctypes.c_void_p

reveal_type(ctypes_obj.data_as(ct.c_void_p))  # E: ctypes.c_void_p
reveal_type(ctypes_obj.shape_as(ct.c_longlong))  # E: ctypes.Array[ctypes.c_longlong]
reveal_type(ctypes_obj.strides_as(ct.c_ubyte))  # E: ctypes.Array[ctypes.c_ubyte]

reveal_type(f8.all())  # E: bool_
reveal_type(AR_f8.all())  # E: bool_
reveal_type(AR_f8.all(axis=0))  # E: Any
reveal_type(AR_f8.all(keepdims=True))  # E: Any
reveal_type(AR_f8.all(out=B))  # E: SubClass

reveal_type(f8.any())  # E: bool_
reveal_type(AR_f8.any())  # E: bool_
reveal_type(AR_f8.any(axis=0))  # E: Any
reveal_type(AR_f8.any(keepdims=True))  # E: Any
reveal_type(AR_f8.any(out=B))  # E: SubClass

reveal_type(f8.argmax())  # E: {intp}
reveal_type(AR_f8.argmax())  # E: {intp}
reveal_type(AR_f8.argmax(axis=0))  # E: Any
reveal_type(AR_f8.argmax(out=B))  # E: SubClass

reveal_type(f8.argmin())  # E: {intp}
reveal_type(AR_f8.argmin())  # E: {intp}
reveal_type(AR_f8.argmin(axis=0))  # E: Any
reveal_type(AR_f8.argmin(out=B))  # E: SubClass

reveal_type(f8.argsort())  # E: ndarray[Any, Any]
reveal_type(AR_f8.argsort())  # E: ndarray[Any, Any]

reveal_type(f8.astype(np.int64).choose([()]))  # E: ndarray[Any, Any]
reveal_type(AR_f8.choose([0]))  # E: ndarray[Any, Any]
reveal_type(AR_f8.choose([0], out=B))  # E: SubClass

reveal_type(f8.clip(1))  # E: Any
reveal_type(AR_f8.clip(1))  # E: Any
reveal_type(AR_f8.clip(None, 1))  # E: Any
reveal_type(AR_f8.clip(1, out=B))  # E: SubClass
reveal_type(AR_f8.clip(None, 1, out=B))  # E: SubClass

reveal_type(f8.compress([0]))  # E: ndarray[Any, Any]
reveal_type(AR_f8.compress([0]))  # E: ndarray[Any, Any]
reveal_type(AR_f8.compress([0], out=B))  # E: SubClass

reveal_type(f8.conj())  # E: {float64}
reveal_type(AR_f8.conj())  # E: ndarray[Any, dtype[{float64}]]
reveal_type(B.conj())  # E: SubClass

reveal_type(f8.conjugate())  # E: {float64}
reveal_type(AR_f8.conjugate())  # E: ndarray[Any, dtype[{float64}]]
reveal_type(B.conjugate())  # E: SubClass

reveal_type(f8.cumprod())  # E: ndarray[Any, Any]
reveal_type(AR_f8.cumprod())  # E: ndarray[Any, Any]
reveal_type(AR_f8.cumprod(out=B))  # E: SubClass

reveal_type(f8.cumsum())  # E: ndarray[Any, Any]
reveal_type(AR_f8.cumsum())  # E: ndarray[Any, Any]
reveal_type(AR_f8.cumsum(out=B))  # E: SubClass

reveal_type(f8.max())  # E: Any
reveal_type(AR_f8.max())  # E: Any
reveal_type(AR_f8.max(axis=0))  # E: Any
reveal_type(AR_f8.max(keepdims=True))  # E: Any
reveal_type(AR_f8.max(out=B))  # E: SubClass

reveal_type(f8.mean())  # E: Any
reveal_type(AR_f8.mean())  # E: Any
reveal_type(AR_f8.mean(axis=0))  # E: Any
reveal_type(AR_f8.mean(keepdims=True))  # E: Any
reveal_type(AR_f8.mean(out=B))  # E: SubClass

reveal_type(f8.min())  # E: Any
reveal_type(AR_f8.min())  # E: Any
reveal_type(AR_f8.min(axis=0))  # E: Any
reveal_type(AR_f8.min(keepdims=True))  # E: Any
reveal_type(AR_f8.min(out=B))  # E: SubClass

reveal_type(f8.newbyteorder())  # E: {float64}
reveal_type(AR_f8.newbyteorder())  # E: ndarray[Any, dtype[{float64}]]
reveal_type(B.newbyteorder('|'))  # E: SubClass

reveal_type(f8.prod())  # E: Any
reveal_type(AR_f8.prod())  # E: Any
reveal_type(AR_f8.prod(axis=0))  # E: Any
reveal_type(AR_f8.prod(keepdims=True))  # E: Any
reveal_type(AR_f8.prod(out=B))  # E: SubClass

reveal_type(f8.ptp())  # E: Any
reveal_type(AR_f8.ptp())  # E: Any
reveal_type(AR_f8.ptp(axis=0))  # E: Any
reveal_type(AR_f8.ptp(keepdims=True))  # E: Any
reveal_type(AR_f8.ptp(out=B))  # E: SubClass

reveal_type(f8.round())  # E: {float64}
reveal_type(AR_f8.round())  # E: ndarray[Any, dtype[{float64}]]
reveal_type(AR_f8.round(out=B))  # E: SubClass

reveal_type(f8.repeat(1))  # E: ndarray[Any, dtype[{float64}]]
reveal_type(AR_f8.repeat(1))  # E: ndarray[Any, dtype[{float64}]]
reveal_type(B.repeat(1))  # E: ndarray[Any, dtype[object_]]

reveal_type(f8.std())  # E: Any
reveal_type(AR_f8.std())  # E: Any
reveal_type(AR_f8.std(axis=0))  # E: Any
reveal_type(AR_f8.std(keepdims=True))  # E: Any
reveal_type(AR_f8.std(out=B))  # E: SubClass

reveal_type(f8.sum())  # E: Any
reveal_type(AR_f8.sum())  # E: Any
reveal_type(AR_f8.sum(axis=0))  # E: Any
reveal_type(AR_f8.sum(keepdims=True))  # E: Any
reveal_type(AR_f8.sum(out=B))  # E: SubClass

reveal_type(f8.take(0))  # E: {float64}
reveal_type(AR_f8.take(0))  # E: {float64}
reveal_type(AR_f8.take([0]))  # E: ndarray[Any, dtype[{float64}]]
reveal_type(AR_f8.take(0, out=B))  # E: SubClass
reveal_type(AR_f8.take([0], out=B))  # E: SubClass

reveal_type(f8.var())  # E: Any
reveal_type(AR_f8.var())  # E: Any
reveal_type(AR_f8.var(axis=0))  # E: Any
reveal_type(AR_f8.var(keepdims=True))  # E: Any
reveal_type(AR_f8.var(out=B))  # E: SubClass

reveal_type(AR_f8.argpartition([0]))  # E: ndarray[Any, dtype[{intp}]]

reveal_type(AR_f8.diagonal())  # E: ndarray[Any, dtype[{float64}]]

reveal_type(AR_f8.dot(1))  # E: ndarray[Any, Any]
reveal_type(AR_f8.dot([1]))  # E: Any
reveal_type(AR_f8.dot(1, out=B))  # E: SubClass

reveal_type(AR_f8.nonzero())  # E: tuple[ndarray[Any, dtype[{intp}]], ...]

reveal_type(AR_f8.searchsorted(1))  # E: {intp}
reveal_type(AR_f8.searchsorted([1]))  # E: ndarray[Any, dtype[{intp}]]

reveal_type(AR_f8.trace())  # E: Any
reveal_type(AR_f8.trace(out=B))  # E: SubClass

reveal_type(AR_f8.item())  # E: float
reveal_type(AR_U.item())  # E: str

reveal_type(AR_f8.ravel())  # E: ndarray[Any, dtype[{float64}]]
reveal_type(AR_U.ravel())  # E: ndarray[Any, dtype[str_]]

reveal_type(AR_f8.flatten())  # E: ndarray[Any, dtype[{float64}]]
reveal_type(AR_U.flatten())  # E: ndarray[Any, dtype[str_]]

reveal_type(AR_f8.reshape(1))  # E: ndarray[Any, dtype[{float64}]]
reveal_type(AR_U.reshape(1))  # E: ndarray[Any, dtype[str_]]

reveal_type(int(AR_f8))  # E: int
reveal_type(int(AR_U))  # E: int

reveal_type(float(AR_f8))  # E: float
reveal_type(float(AR_U))  # E: float

reveal_type(complex(AR_f8))  # E: complex

reveal_type(operator.index(AR_i8))  # E: int

reveal_type(AR_f8.__array_prepare__(B))  # E: ndarray[Any, dtype[object_]]
reveal_type(AR_f8.__array_wrap__(B))  # E: ndarray[Any, dtype[object_]]

reveal_type(AR_V[0])  # E: Any
reveal_type(AR_V[0, 0])  # E: Any
reveal_type(AR_V[AR_i8])  # E: ndarray[Any, dtype[void]]
reveal_type(AR_V[AR_i8, AR_i8])  # E: ndarray[Any, dtype[void]]
reveal_type(AR_V[AR_i8, None])  # E: ndarray[Any, dtype[void]]
reveal_type(AR_V[0, ...])  # E: ndarray[Any, dtype[void]]
reveal_type(AR_V[[0]])  # E: ndarray[Any, dtype[void]]
reveal_type(AR_V[[0], [0]])  # E: ndarray[Any, dtype[void]]
reveal_type(AR_V[:])  # E: ndarray[Any, dtype[void]]
reveal_type(AR_V["a"])  # E: ndarray[Any, dtype[Any]]
reveal_type(AR_V[["a", "b"]])  # E: ndarray[Any, dtype[void]]

reveal_type(AR_f8.dump("test_file"))  # E: None
reveal_type(AR_f8.dump(b"test_file"))  # E: None
with open("test_file", "wb") as f:
    reveal_type(AR_f8.dump(f))  # E: None

reveal_type(AR_f8.__array_finalize__(None))  # E: None
reveal_type(AR_f8.__array_finalize__(B))  # E: None
reveal_type(AR_f8.__array_finalize__(AR_f8))  # E: None

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