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Mini Shell
Mini Shell
from collections.abc import Sequence
from typing import (
Any,
TypeVar,
Generic,
overload,
Literal,
SupportsIndex,
)
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,
_FiniteNestedSequence,
NDArray,
_ArrayLikeInt,
# DTypes
DTypeLike,
_SupportsDType,
# Shapes
_ShapeLike,
)
from numpy.core.multiarray import (
unravel_index as unravel_index,
ravel_multi_index as ravel_multi_index,
)
_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 ix_(*args: _FiniteNestedSequence[_SupportsDType[_DType]]) -> tuple[ndarray[Any, _DType], ...]: ...
@overload
def ix_(*args: str | _NestedSequence[str]) -> tuple[NDArray[str_], ...]: ...
@overload
def ix_(*args: bytes | _NestedSequence[bytes]) -> tuple[NDArray[bytes_], ...]: ...
@overload
def ix_(*args: bool | _NestedSequence[bool]) -> tuple[NDArray[bool_], ...]: ...
@overload
def ix_(*args: int | _NestedSequence[int]) -> tuple[NDArray[int_], ...]: ...
@overload
def ix_(*args: float | _NestedSequence[float]) -> tuple[NDArray[float_], ...]: ...
@overload
def ix_(*args: complex | _NestedSequence[complex]) -> tuple[NDArray[complex_], ...]: ...
class nd_grid(Generic[_BoolType]):
sparse: _BoolType
def __init__(self, sparse: _BoolType = ...) -> None: ...
@overload
def __getitem__(
self: nd_grid[Literal[False]],
key: slice | Sequence[slice],
) -> NDArray[Any]: ...
@overload
def __getitem__(
self: nd_grid[Literal[True]],
key: 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[Any, Any]: ...
# 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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