You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
162 lines
4.2 KiB
162 lines
4.2 KiB
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`
|
|
|