ꦫꦣꦺꦤ꧀ꦄꦤ꧀ꦠꦱꦺꦤ

PATH: opt / cloudlinux / venv / lib / python3.11 / site-packages / numpy / lib

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`

[-] arraysetops.pyi [open]
[-] arraysetops.py [open]
[-] user_array.py [open]
[+] ..
[-] stride_tricks.pyi [open]
[-] index_tricks.py [open]
[-] format.py [open]
[+] __pycache__
[-] arrayterator.py [open]
[+] tests
[-] _version.py [open]
[-] mixins.py [open]
[-] npyio.pyi [open]
[-] _version.pyi [open]
[-] index_tricks.pyi [open]
[-] ufunclike.pyi [open]
[-] arrayterator.pyi [open]
[-] _iotools.py [open]
[-] ufunclike.py [open]
[-] twodim_base.py [open]
[-] type_check.py [open]
[-] shape_base.py [open]
[-] histograms.py [open]
[-] stride_tricks.py [open]
[-] arraypad.py [open]
[-] __init__.pyi [open]
[-] format.pyi [open]
[-] polynomial.pyi [open]
[-] twodim_base.pyi [open]
[-] utils.py [open]
[-] function_base.pyi [open]
[-] recfunctions.py [open]
[-] histograms.pyi [open]
[-] utils.pyi [open]
[-] function_base.py [open]
[-] scimath.py [open]
[-] type_check.pyi [open]
[-] polynomial.py [open]
[-] scimath.pyi [open]
[-] __init__.py [open]
[-] _datasource.py [open]
[-] setup.py [open]
[-] nanfunctions.pyi [open]
[-] mixins.pyi [open]
[-] arraypad.pyi [open]
[-] nanfunctions.py [open]
[-] npyio.py [open]
[-] shape_base.pyi [open]