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Code Editor : index_tricks.pyi
import sys from typing import ( Any, Tuple, TypeVar, Generic, overload, List, Union, Sequence, ) from numpy import ( # Circumvent a naming conflict with `AxisConcatenator.matrix` matrix as _Matrix, ndenumerate as ndenumerate, ndindex as ndindex, ndarray, dtype, integer, str_, bytes_, bool_, int_, float_, complex_, intp, _OrderCF, _ModeKind, ) from numpy.typing import ( # Arrays ArrayLike, _NestedSequence, _RecursiveSequence, NDArray, _ArrayLikeInt, # DTypes DTypeLike, _SupportsDType, # Shapes _ShapeLike, ) if sys.version_info >= (3, 8): from typing import Literal, SupportsIndex else: from typing_extensions import Literal, SupportsIndex _T = TypeVar("_T") _DType = TypeVar("_DType", bound=dtype[Any]) _BoolType = TypeVar("_BoolType", Literal[True], Literal[False]) _TupType = TypeVar("_TupType", bound=Tuple[Any, ...]) _ArrayType = TypeVar("_ArrayType", bound=ndarray[Any, Any]) __all__: List[str] @overload def unravel_index( # type: ignore[misc] indices: Union[int, integer[Any]], shape: _ShapeLike, order: _OrderCF = ... ) -> Tuple[intp, ...]: ... @overload def unravel_index( indices: _ArrayLikeInt, shape: _ShapeLike, order: _OrderCF = ... ) -> Tuple[NDArray[intp], ...]: ... @overload def ravel_multi_index( # type: ignore[misc] multi_index: Sequence[Union[int, integer[Any]]], dims: _ShapeLike, mode: Union[_ModeKind, Tuple[_ModeKind, ...]] = ..., order: _OrderCF = ... ) -> intp: ... @overload def ravel_multi_index( multi_index: Sequence[_ArrayLikeInt], dims: _ShapeLike, mode: Union[_ModeKind, Tuple[_ModeKind, ...]] = ..., order: _OrderCF = ... ) -> NDArray[intp]: ... @overload def ix_(*args: _NestedSequence[_SupportsDType[_DType]]) -> Tuple[ndarray[Any, _DType], ...]: ... @overload def ix_(*args: _NestedSequence[str]) -> Tuple[NDArray[str_], ...]: ... @overload def ix_(*args: _NestedSequence[bytes]) -> Tuple[NDArray[bytes_], ...]: ... @overload def ix_(*args: _NestedSequence[bool]) -> Tuple[NDArray[bool_], ...]: ... @overload def ix_(*args: _NestedSequence[int]) -> Tuple[NDArray[int_], ...]: ... @overload def ix_(*args: _NestedSequence[float]) -> Tuple[NDArray[float_], ...]: ... @overload def ix_(*args: _NestedSequence[complex]) -> Tuple[NDArray[complex_], ...]: ... @overload def ix_(*args: _RecursiveSequence) -> Tuple[NDArray[Any], ...]: ... class nd_grid(Generic[_BoolType]): sparse: _BoolType def __init__(self, sparse: _BoolType = ...) -> None: ... @overload def __getitem__( self: nd_grid[Literal[False]], key: Union[slice, Sequence[slice]], ) -> NDArray[Any]: ... @overload def __getitem__( self: nd_grid[Literal[True]], key: Union[slice, Sequence[slice]], ) -> List[NDArray[Any]]: ... class MGridClass(nd_grid[Literal[False]]): def __init__(self) -> None: ... mgrid: MGridClass class OGridClass(nd_grid[Literal[True]]): def __init__(self) -> None: ... ogrid: OGridClass class AxisConcatenator: axis: int matrix: bool ndmin: int trans1d: int def __init__( self, axis: int = ..., matrix: bool = ..., ndmin: int = ..., trans1d: int = ..., ) -> None: ... @staticmethod @overload def concatenate( # type: ignore[misc] *a: ArrayLike, axis: SupportsIndex = ..., out: None = ... ) -> NDArray[Any]: ... @staticmethod @overload def concatenate( *a: ArrayLike, axis: SupportsIndex = ..., out: _ArrayType = ... ) -> _ArrayType: ... @staticmethod def makemat( data: ArrayLike, dtype: DTypeLike = ..., copy: bool = ... ) -> _Matrix: ... # TODO: Sort out this `__getitem__` method def __getitem__(self, key: Any) -> Any: ... class RClass(AxisConcatenator): axis: Literal[0] matrix: Literal[False] ndmin: Literal[1] trans1d: Literal[-1] def __init__(self) -> None: ... r_: RClass class CClass(AxisConcatenator): axis: Literal[-1] matrix: Literal[False] ndmin: Literal[2] trans1d: Literal[0] def __init__(self) -> None: ... c_: CClass class IndexExpression(Generic[_BoolType]): maketuple: _BoolType def __init__(self, maketuple: _BoolType) -> None: ... @overload def __getitem__(self, item: _TupType) -> _TupType: ... # type: ignore[misc] @overload def __getitem__(self: IndexExpression[Literal[True]], item: _T) -> Tuple[_T]: ... @overload def __getitem__(self: IndexExpression[Literal[False]], item: _T) -> _T: ... index_exp: IndexExpression[Literal[True]] s_: IndexExpression[Literal[False]] def fill_diagonal(a: ndarray[Any, Any], val: Any, wrap: bool = ...) -> None: ... def diag_indices(n: int, ndim: int = ...) -> Tuple[NDArray[int_], ...]: ... def diag_indices_from(arr: ArrayLike) -> Tuple[NDArray[int_], ...]: ... # NOTE: see `numpy/__init__.pyi` for `ndenumerate` and `ndindex`
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