Repository: numpy/numpy
File: numpy/ma/core.pyi (Python)

Code before:
    @overload  # (dtype: ArrayT, /)
    def view(self, /, dtype: type[_ArrayT], type: None = None, fill_value: _ScalarLike_co | None = None) -> _ArrayT: ...
    @overload  # (dtype: ?)
    def view(
        self,
        /,
        # `_VoidDTypeLike | str | None` is like `DTypeLike` but without `_DTypeLike[Any]` to avoid
        # overlaps with previous overloads.
        dtype: _VoidDTypeLike | str | None,
        type: None = None,
        fill_value: _ScalarLike_co | None = None
    ) -> MaskedArray[_ShapeT_co, dtype]: ...

    def __getitem__(self, indx): ...
    def __setitem__(self, indx, value): ...
    @property
    def shape(self) -> _ShapeT_co: ...
    @shape.setter
    def shape(self: MaskedArray[_ShapeT, Any], shape: _ShapeT, /) -> None: ...
    def __setmask__(self, mask: _ArrayLikeBool_co, copy: bool = False) -> None: ...
    @property
    def mask(self) -> NDArray[MaskType] | MaskType: ...
    @mask.setter
    def mask(self, value: _ArrayLikeBool_co, /) -> None: ...
    @property
    def recordmask(self) -> NDArray[MaskType] | MaskType: ...
    @recordmask.setter
    def recordmask(self, mask: Never) -> NoReturn: ...
    def harden_mask(self) -> Self: ...
    def soften_mask(self) -> Self: ...
    @property
    def hardmask(self) -> bool: ...
    def unshare_mask(self) -> Self: ...
    @property
    def sharedmask(self) -> bool: ...
    def shrink_mask(self) -> Self: ...
    @property
    def baseclass(self) -> type[NDArray[Any]]: ...
    data: Any
    @property
    def flat(self): ...
    @flat.setter
    def flat(self, value): ...
    @property
    def fill_value(self): ...
    @fill_value.setter
    def fill_value(self, value=...): ...
    get_fill_value: Any
    set_fill_value: Any
    def filled(self, /, fill_value: _ScalarLike_co | None = None) -> ndarray[_ShapeT_co, _DTypeT_co]: ...
    def compressed(self) -> ndarray[tuple[int], _DTypeT_co]: ...

Review comment (suggestion):
I've set this the same as `mask`

https://github.com/numpy/numpy/blob/8b2321d03c1abce671a15f9d08a97249bd2d161d/numpy/ma/core.pyi#L511-L512

Code after:
    @overload  # (dtype: ArrayT, /)
    def view(self, /, dtype: type[_ArrayT], type: None = None, fill_value: _ScalarLike_co | None = None) -> _ArrayT: ...
    @overload  # (dtype: ?)
    def view(
        self,
        /,
        # `_VoidDTypeLike | str | None` is like `DTypeLike` but without `_DTypeLike[Any]` to avoid
        # overlaps with previous overloads.
        dtype: _VoidDTypeLike | str | None,
        type: None = None,
        fill_value: _ScalarLike_co | None = None
    ) -> MaskedArray[_ShapeT_co, dtype]: ...

    def __getitem__(self, indx): ...
    def __setitem__(self, indx, value): ...
    @property
    def shape(self) -> _ShapeT_co: ...
    @shape.setter
    def shape(self: MaskedArray[_ShapeT, Any], shape: _ShapeT, /) -> None: ...
    def __setmask__(self, mask: _ArrayLikeBool_co, copy: bool = False) -> None: ...
    @property
    def mask(self) -> np.ndarray[_ShapeT_co, dtype[MaskType]] | MaskType: ...
    @mask.setter
    def mask(self, value: _ArrayLikeBool_co, /) -> None: ...
    @property
    def recordmask(self) -> np.ndarray[_ShapeT_co, dtype[MaskType]] | MaskType: ...
    @recordmask.setter
    def recordmask(self, mask: Never, /) -> NoReturn: ...
    def harden_mask(self) -> Self: ...
    def soften_mask(self) -> Self: ...
    @property
    def hardmask(self) -> bool: ...
    def unshare_mask(self) -> Self: ...
    @property
    def sharedmask(self) -> bool: ...
    def shrink_mask(self) -> Self: ...
    @property
    def baseclass(self) -> type[NDArray[Any]]: ...
    data: Any
    @property
    def flat(self) -> MaskedIterator: ...
    @flat.setter
    def flat(self, value: ArrayLike, /) -> None: ...
    @property
    def fill_value(self): ...
    @fill_value.setter
    def fill_value(self, value=...): ...
    get_fill_value: Any
    set_fill_value: Any
    def filled(self, /, fill_value: _ScalarLike_co | None = None) -> ndarray[_ShapeT_co, _DTypeT_co]: ...
    def compressed(self) -> ndarray[tuple[int], _DTypeT_co]: ...