50 lines
1.5 KiB
Python
50 lines
1.5 KiB
Python
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from collections.abc import Generator
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from typing import (
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Any,
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TypeVar,
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Union,
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overload,
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)
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from numpy import ndarray, dtype, generic
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from numpy._typing import DTypeLike
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# TODO: Set a shape bound once we've got proper shape support
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_Shape = TypeVar("_Shape", bound=Any)
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_DType = TypeVar("_DType", bound=dtype[Any])
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_ScalarType = TypeVar("_ScalarType", bound=generic)
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_Index = Union[
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Union[ellipsis, int, slice],
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tuple[Union[ellipsis, int, slice], ...],
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]
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__all__: list[str]
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# NOTE: In reality `Arrayterator` does not actually inherit from `ndarray`,
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# but its ``__getattr__` method does wrap around the former and thus has
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# access to all its methods
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class Arrayterator(ndarray[_Shape, _DType]):
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var: ndarray[_Shape, _DType] # type: ignore[assignment]
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buf_size: None | int
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start: list[int]
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stop: list[int]
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step: list[int]
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@property # type: ignore[misc]
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def shape(self) -> tuple[int, ...]: ...
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@property
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def flat( # type: ignore[override]
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self: ndarray[Any, dtype[_ScalarType]]
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) -> Generator[_ScalarType, None, None]: ...
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def __init__(
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self, var: ndarray[_Shape, _DType], buf_size: None | int = ...
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) -> None: ...
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@overload
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def __array__(self, dtype: None = ...) -> ndarray[Any, _DType]: ...
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@overload
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def __array__(self, dtype: DTypeLike) -> ndarray[Any, dtype[Any]]: ...
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def __getitem__(self, index: _Index) -> Arrayterator[Any, _DType]: ...
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def __iter__(self) -> Generator[ndarray[Any, _DType], None, None]: ...
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