Buckets:
| from _typeshed import Incomplete | |
| from types import EllipsisType | |
| from typing import Any, Generic, Self, SupportsIndex, TypeAlias, overload | |
| from typing_extensions import TypeVar, deprecated, override | |
| import numpy as np | |
| import numpy.typing as npt | |
| from numpy._typing import ( | |
| _AnyShape, | |
| _ArrayLike, | |
| _ArrayLikeBool_co, | |
| _ArrayLikeInt_co, | |
| _DTypeLike, | |
| ) | |
| ### | |
| _ScalarT = TypeVar("_ScalarT", bound=np.generic) | |
| _ShapeT = TypeVar("_ShapeT", bound=tuple[int, ...]) | |
| _ShapeT_co = TypeVar("_ShapeT_co", bound=tuple[int, ...], default=_AnyShape, covariant=True) | |
| _DTypeT = TypeVar("_DTypeT", bound=np.dtype) | |
| _DTypeT_co = TypeVar("_DTypeT_co", bound=np.dtype, default=np.dtype, covariant=True) | |
| _BoolArrayT = TypeVar("_BoolArrayT", bound=container[Any, np.dtype[np.bool]]) | |
| _IntegralArrayT = TypeVar("_IntegralArrayT", bound=container[Any, np.dtype[np.bool | np.integer | np.object_]]) | |
| _RealContainerT = TypeVar( | |
| "_RealContainerT", | |
| bound=container[Any, np.dtype[np.bool | np.integer | np.floating | np.timedelta64 | np.object_]], | |
| ) | |
| _NumericContainerT = TypeVar("_NumericContainerT", bound=container[Any, np.dtype[np.number | np.timedelta64 | np.object_]]) | |
| _ArrayInt_co: TypeAlias = npt.NDArray[np.integer | np.bool] | |
| _ToIndexSlice: TypeAlias = slice | EllipsisType | _ArrayInt_co | None | |
| _ToIndexSlices: TypeAlias = _ToIndexSlice | tuple[_ToIndexSlice, ...] | |
| _ToIndex: TypeAlias = SupportsIndex | _ToIndexSlice | |
| _ToIndices: TypeAlias = _ToIndex | tuple[_ToIndex, ...] | |
| ### | |
| # pyright: reportDeprecated = false | |
| class container(Generic[_ShapeT_co, _DTypeT_co]): | |
| array: np.ndarray[_ShapeT_co, _DTypeT_co] | |
| def __init__( | |
| self, | |
| /, | |
| data: container[_ShapeT_co, _DTypeT_co] | np.ndarray[_ShapeT_co, _DTypeT_co], | |
| dtype: None = None, | |
| copy: bool = True, | |
| ) -> None: ... | |
| def __init__( | |
| self: container[Any, np.dtype[_ScalarT]], | |
| /, | |
| data: _ArrayLike[_ScalarT], | |
| dtype: None = None, | |
| copy: bool = True, | |
| ) -> None: ... | |
| def __init__( | |
| self: container[Any, np.dtype[_ScalarT]], | |
| /, | |
| data: npt.ArrayLike, | |
| dtype: _DTypeLike[_ScalarT], | |
| copy: bool = True, | |
| ) -> None: ... | |
| def __init__(self, /, data: npt.ArrayLike, dtype: npt.DTypeLike | None = None, copy: bool = True) -> None: ... | |
| # | |
| def __complex__(self, /) -> complex: ... | |
| def __float__(self, /) -> float: ... | |
| def __int__(self, /) -> int: ... | |
| def __hex__(self, /) -> str: ... | |
| def __oct__(self, /) -> str: ... | |
| # | |
| def __eq__(self, other: object, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride] | |
| def __ne__(self, other: object, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride] | |
| # | |
| def __lt__(self, other: npt.ArrayLike, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ... | |
| def __le__(self, other: npt.ArrayLike, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ... | |
| def __gt__(self, other: npt.ArrayLike, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ... | |
| def __ge__(self, other: npt.ArrayLike, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ... | |
| # | |
| def __len__(self, /) -> int: ... | |
| # keep in sync with np.ndarray | |
| def __getitem__(self, key: _ArrayInt_co | tuple[_ArrayInt_co, ...], /) -> container[_ShapeT_co, _DTypeT_co]: ... | |
| def __getitem__(self, key: _ToIndexSlices, /) -> container[_AnyShape, _DTypeT_co]: ... | |
| def __getitem__(self, key: _ToIndices, /) -> Any: ... | |
| def __getitem__(self: container[Any, np.dtype[np.void]], key: list[str], /) -> container[_ShapeT_co, np.dtype[np.void]]: ... | |
| def __getitem__(self: container[Any, np.dtype[np.void]], key: str, /) -> container[_ShapeT_co, np.dtype]: ... | |
| # keep in sync with np.ndarray | |
| def __setitem__(self, index: _ToIndices, value: object, /) -> None: ... | |
| def __setitem__(self: container[Any, np.dtype[np.void]], key: str | list[str], value: object, /) -> None: ... | |
| # keep in sync with np.ndarray | |
| def __abs__(self: container[_ShapeT, np.dtype[np.complex64]], /) -> container[_ShapeT, np.dtype[np.float32]]: ... # type: ignore[overload-overlap] | |
| def __abs__(self: container[_ShapeT, np.dtype[np.complex128]], /) -> container[_ShapeT, np.dtype[np.float64]]: ... | |
| def __abs__(self: container[_ShapeT, np.dtype[np.complex192]], /) -> container[_ShapeT, np.dtype[np.float96]]: ... | |
| def __abs__(self: container[_ShapeT, np.dtype[np.complex256]], /) -> container[_ShapeT, np.dtype[np.float128]]: ... | |
| def __abs__(self: _RealContainerT, /) -> _RealContainerT: ... | |
| # | |
| def __neg__(self: _NumericContainerT, /) -> _NumericContainerT: ... # noqa: PYI019 | |
| def __pos__(self: _NumericContainerT, /) -> _NumericContainerT: ... # noqa: PYI019 | |
| def __invert__(self: _IntegralArrayT, /) -> _IntegralArrayT: ... # noqa: PYI019 | |
| # TODO(jorenham): complete these binary ops | |
| # | |
| def __add__(self, other: npt.ArrayLike, /) -> Incomplete: ... | |
| def __radd__(self, other: npt.ArrayLike, /) -> Incomplete: ... | |
| def __iadd__(self, other: npt.ArrayLike, /) -> Self: ... | |
| # | |
| def __sub__(self, other: npt.ArrayLike, /) -> Incomplete: ... | |
| def __rsub__(self, other: npt.ArrayLike, /) -> Incomplete: ... | |
| def __isub__(self, other: npt.ArrayLike, /) -> Self: ... | |
| # | |
| def __mul__(self, other: npt.ArrayLike, /) -> Incomplete: ... | |
| def __rmul__(self, other: npt.ArrayLike, /) -> Incomplete: ... | |
| def __imul__(self, other: npt.ArrayLike, /) -> Self: ... | |
| # | |
| def __mod__(self, other: npt.ArrayLike, /) -> Incomplete: ... | |
| def __rmod__(self, other: npt.ArrayLike, /) -> Incomplete: ... | |
| def __imod__(self, other: npt.ArrayLike, /) -> Self: ... | |
| # | |
| def __divmod__(self, other: npt.ArrayLike, /) -> tuple[Incomplete, Incomplete]: ... | |
| def __rdivmod__(self, other: npt.ArrayLike, /) -> tuple[Incomplete, Incomplete]: ... | |
| # | |
| def __pow__(self, other: npt.ArrayLike, /) -> Incomplete: ... | |
| def __rpow__(self, other: npt.ArrayLike, /) -> Incomplete: ... | |
| def __ipow__(self, other: npt.ArrayLike, /) -> Self: ... | |
| # | |
| def __lshift__(self, other: _ArrayLikeInt_co, /) -> container[_AnyShape, np.dtype[np.integer]]: ... | |
| def __rlshift__(self, other: _ArrayLikeInt_co, /) -> container[_AnyShape, np.dtype[np.integer]]: ... | |
| def __ilshift__(self, other: _ArrayLikeInt_co, /) -> Self: ... | |
| # | |
| def __rshift__(self, other: _ArrayLikeInt_co, /) -> container[_AnyShape, np.dtype[np.integer]]: ... | |
| def __rrshift__(self, other: _ArrayLikeInt_co, /) -> container[_AnyShape, np.dtype[np.integer]]: ... | |
| def __irshift__(self, other: _ArrayLikeInt_co, /) -> Self: ... | |
| # | |
| def __and__( | |
| self: container[Any, np.dtype[np.bool]], other: _ArrayLikeBool_co, / | |
| ) -> container[_AnyShape, np.dtype[np.bool]]: ... | |
| def __and__(self, other: _ArrayLikeInt_co, /) -> container[_AnyShape, np.dtype[np.bool | np.integer]]: ... | |
| __rand__ = __and__ | |
| def __iand__(self: _BoolArrayT, other: _ArrayLikeBool_co, /) -> _BoolArrayT: ... | |
| def __iand__(self, other: _ArrayLikeInt_co, /) -> Self: ... | |
| # | |
| def __xor__( | |
| self: container[Any, np.dtype[np.bool]], other: _ArrayLikeBool_co, / | |
| ) -> container[_AnyShape, np.dtype[np.bool]]: ... | |
| def __xor__(self, other: _ArrayLikeInt_co, /) -> container[_AnyShape, np.dtype[np.bool | np.integer]]: ... | |
| __rxor__ = __xor__ | |
| def __ixor__(self: _BoolArrayT, other: _ArrayLikeBool_co, /) -> _BoolArrayT: ... | |
| def __ixor__(self, other: _ArrayLikeInt_co, /) -> Self: ... | |
| # | |
| def __or__( | |
| self: container[Any, np.dtype[np.bool]], other: _ArrayLikeBool_co, / | |
| ) -> container[_AnyShape, np.dtype[np.bool]]: ... | |
| def __or__(self, other: _ArrayLikeInt_co, /) -> container[_AnyShape, np.dtype[np.bool | np.integer]]: ... | |
| __ror__ = __or__ | |
| def __ior__(self: _BoolArrayT, other: _ArrayLikeBool_co, /) -> _BoolArrayT: ... | |
| def __ior__(self, other: _ArrayLikeInt_co, /) -> Self: ... | |
| # | |
| def __array__(self, /, t: None = None) -> np.ndarray[_ShapeT_co, _DTypeT_co]: ... | |
| def __array__(self, /, t: _DTypeT) -> np.ndarray[_ShapeT_co, _DTypeT]: ... | |
| # | |
| def __array_wrap__(self, arg0: npt.ArrayLike, /) -> container[_ShapeT_co, _DTypeT_co]: ... | |
| def __array_wrap__(self, a: np.ndarray[_ShapeT, _DTypeT], c: Any = ..., s: Any = ..., /) -> container[_ShapeT, _DTypeT]: ... | |
| # | |
| def copy(self, /) -> Self: ... | |
| def tobytes(self, /) -> bytes: ... | |
| def byteswap(self, /) -> Self: ... | |
| def astype(self, /, typecode: _DTypeLike[_ScalarT]) -> container[_ShapeT_co, np.dtype[_ScalarT]]: ... | |
Xet Storage Details
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·
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