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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/multiarray.pyi

import datetime as dt
from typing import Any, TypeVar
from pathlib import Path

import numpy as np
import numpy.typing as npt

_SCT = TypeVar("_SCT", bound=np.generic, covariant=True)

class SubClass(np.ndarray[Any, np.dtype[_SCT]]): ...

subclass: SubClass[np.float64]

AR_f8: npt.NDArray[np.float64]
AR_i8: npt.NDArray[np.int64]
AR_u1: npt.NDArray[np.uint8]
AR_m: npt.NDArray[np.timedelta64]
AR_M: npt.NDArray[np.datetime64]

AR_LIKE_f: list[float]
AR_LIKE_i: list[int]

m: np.timedelta64
M: np.datetime64

b_f8 = np.broadcast(AR_f8)
b_i8_f8_f8 = np.broadcast(AR_i8, AR_f8, AR_f8)

nditer_obj: np.nditer

date_scalar: dt.date
date_seq: list[dt.date]
timedelta_seq: list[dt.timedelta]

def func(a: int) -> bool: ...

reveal_type(next(b_f8))  # E: tuple[Any, ...]
reveal_type(b_f8.reset())  # E: None
reveal_type(b_f8.index)  # E: int
reveal_type(b_f8.iters)  # E: tuple[flatiter[Any], ...]
reveal_type(b_f8.nd)  # E: int
reveal_type(b_f8.ndim)  # E: int
reveal_type(b_f8.numiter)  # E: int
reveal_type(b_f8.shape)  # E: tuple[builtins.int, ...]
reveal_type(b_f8.size)  # E: int

reveal_type(next(b_i8_f8_f8))  # E: tuple[Any, ...]
reveal_type(b_i8_f8_f8.reset())  # E: None
reveal_type(b_i8_f8_f8.index)  # E: int
reveal_type(b_i8_f8_f8.iters)  # E: tuple[flatiter[Any], ...]
reveal_type(b_i8_f8_f8.nd)  # E: int
reveal_type(b_i8_f8_f8.ndim)  # E: int
reveal_type(b_i8_f8_f8.numiter)  # E: int
reveal_type(b_i8_f8_f8.shape)  # E: tuple[builtins.int, ...]
reveal_type(b_i8_f8_f8.size)  # E: int

reveal_type(np.inner(AR_f8, AR_i8))  # E: Any

reveal_type(np.where([True, True, False]))  # E: tuple[ndarray[Any, dtype[{intp}]], ...]
reveal_type(np.where([True, True, False], 1, 0))  # E: ndarray[Any, dtype[Any]]

reveal_type(np.lexsort([0, 1, 2]))  # E: Any

reveal_type(np.can_cast(np.dtype("i8"), int))  # E: bool
reveal_type(np.can_cast(AR_f8, "f8"))  # E: bool
reveal_type(np.can_cast(AR_f8, np.complex128, casting="unsafe"))  # E: bool

reveal_type(np.min_scalar_type([1]))  # E: dtype[Any]
reveal_type(np.min_scalar_type(AR_f8))  # E: dtype[Any]

reveal_type(np.result_type(int, [1]))  # E: dtype[Any]
reveal_type(np.result_type(AR_f8, AR_u1))  # E: dtype[Any]
reveal_type(np.result_type(AR_f8, np.complex128))  # E: dtype[Any]

reveal_type(np.dot(AR_LIKE_f, AR_i8))  # E: Any
reveal_type(np.dot(AR_u1, 1))  # E: Any
reveal_type(np.dot(1.5j, 1))  # E: Any
reveal_type(np.dot(AR_u1, 1, out=AR_f8))  # E: ndarray[Any, dtype[{float64}]]

reveal_type(np.vdot(AR_LIKE_f, AR_i8))  # E: floating[Any]
reveal_type(np.vdot(AR_u1, 1))  # E: signedinteger[Any]
reveal_type(np.vdot(1.5j, 1))  # E: complexfloating[Any, Any]

reveal_type(np.bincount(AR_i8))  # E: ndarray[Any, dtype[{intp}]]

reveal_type(np.copyto(AR_f8, [1., 1.5, 1.6]))  # E: None

reveal_type(np.putmask(AR_f8, [True, True, False], 1.5))  # E: None

reveal_type(np.packbits(AR_i8))  # ndarray[Any, dtype[{uint8}]]
reveal_type(np.packbits(AR_u1))  # ndarray[Any, dtype[{uint8}]]

reveal_type(np.unpackbits(AR_u1))  # ndarray[Any, dtype[{uint8}]]

reveal_type(np.shares_memory(1, 2))  # E: bool
reveal_type(np.shares_memory(AR_f8, AR_f8, max_work=1))  # E: bool

reveal_type(np.may_share_memory(1, 2))  # E: bool
reveal_type(np.may_share_memory(AR_f8, AR_f8, max_work=1))  # E: bool

reveal_type(np.geterrobj())  # E: list[Any]

reveal_type(np.seterrobj([8192, 521, None]))  # E: None

reveal_type(np.promote_types(np.int32, np.int64))  # E: dtype[Any]
reveal_type(np.promote_types("f4", float))  # E: dtype[Any]

reveal_type(np.frompyfunc(func, 1, 1, identity=None))  # ufunc

reveal_type(np.datetime_data("m8[D]"))  # E: Tuple[builtins.str, builtins.int]
reveal_type(np.datetime_data(np.datetime64))  # E: Tuple[builtins.str, builtins.int]
reveal_type(np.datetime_data(np.dtype(np.timedelta64)))  # E: Tuple[builtins.str, builtins.int]

reveal_type(np.busday_count("2011-01", "2011-02"))  # E: {int_}
reveal_type(np.busday_count(["2011-01"], "2011-02"))  # E: ndarray[Any, dtype[{int_}]]
reveal_type(np.busday_count(["2011-01"], date_scalar))  # E: ndarray[Any, dtype[{int_}]]

reveal_type(np.busday_offset(M, m))  # E: datetime64
reveal_type(np.busday_offset(date_scalar, m))  # E: datetime64
reveal_type(np.busday_offset(M, 5))  # E: datetime64
reveal_type(np.busday_offset(AR_M, m))  # E: ndarray[Any, dtype[datetime64]]
reveal_type(np.busday_offset(M, timedelta_seq))  # E: ndarray[Any, dtype[datetime64]]
reveal_type(np.busday_offset("2011-01", "2011-02", roll="forward"))  # E: datetime64
reveal_type(np.busday_offset(["2011-01"], "2011-02", roll="forward"))  # E: ndarray[Any, dtype[datetime64]]

reveal_type(np.is_busday("2012"))  # E: bool_
reveal_type(np.is_busday(date_scalar))  # E: bool_
reveal_type(np.is_busday(["2012"]))  # E: ndarray[Any, dtype[bool_]]

reveal_type(np.datetime_as_string(M))  # E: str_
reveal_type(np.datetime_as_string(AR_M))  # E: ndarray[Any, dtype[str_]]

reveal_type(np.busdaycalendar(holidays=date_seq))  # E: busdaycalendar
reveal_type(np.busdaycalendar(holidays=[M]))  # E: busdaycalendar

reveal_type(np.compare_chararrays("a", "b", "!=", rstrip=False))  # E: ndarray[Any, dtype[bool_]]
reveal_type(np.compare_chararrays(b"a", b"a", "==", True))  # E: ndarray[Any, dtype[bool_]]

reveal_type(np.add_docstring(func, "test"))  # E: None

reveal_type(np.nested_iters([AR_i8, AR_i8], [[0], [1]], flags=["c_index"]))  # E: tuple[nditer, ...]
reveal_type(np.nested_iters([AR_i8, AR_i8], [[0], [1]], op_flags=[["readonly", "readonly"]]))  # E: tuple[nditer, ...]
reveal_type(np.nested_iters([AR_i8, AR_i8], [[0], [1]], op_dtypes=np.int_))  # E: tuple[nditer, ...]
reveal_type(np.nested_iters([AR_i8, AR_i8], [[0], [1]], order="C", casting="no"))  # E: tuple[nditer, ...]

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