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.
143 lines
7.1 KiB
143 lines
7.1 KiB
1 year ago
|
"""
|
||
|
This type stub file was generated by pyright.
|
||
|
"""
|
||
|
|
||
|
from typing import Any, Literal as L, SupportsIndex, TypeVar, overload
|
||
|
from numpy import bool_, byte, bytes_, cdouble, clongdouble, csingle, datetime64, double, generic, half, int8, int_, intc, intp, longdouble, longlong, number, object_, short, single, str_, timedelta64, ubyte, uint, uintc, ulonglong, ushort, void
|
||
|
from numpy._typing import ArrayLike, NDArray, _ArrayLike, _ArrayLikeBool_co, _ArrayLikeDT64_co, _ArrayLikeNumber_co, _ArrayLikeObject_co, _ArrayLikeTD64_co
|
||
|
|
||
|
_SCT = TypeVar("_SCT", bound=generic)
|
||
|
_NumberType = TypeVar("_NumberType", bound=number[Any])
|
||
|
_SCTNoCast = TypeVar("_SCTNoCast", bool_, ushort, ubyte, uintc, uint, ulonglong, short, byte, intc, int_, longlong, half, single, double, longdouble, csingle, cdouble, clongdouble, timedelta64, datetime64, object_, str_, bytes_, void)
|
||
|
__all__: list[str]
|
||
|
@overload
|
||
|
def ediff1d(ary: _ArrayLikeBool_co, to_end: None | ArrayLike = ..., to_begin: None | ArrayLike = ...) -> NDArray[int8]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def ediff1d(ary: _ArrayLike[_NumberType], to_end: None | ArrayLike = ..., to_begin: None | ArrayLike = ...) -> NDArray[_NumberType]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def ediff1d(ary: _ArrayLikeNumber_co, to_end: None | ArrayLike = ..., to_begin: None | ArrayLike = ...) -> NDArray[Any]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def ediff1d(ary: _ArrayLikeDT64_co | _ArrayLikeTD64_co, to_end: None | ArrayLike = ..., to_begin: None | ArrayLike = ...) -> NDArray[timedelta64]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def ediff1d(ary: _ArrayLikeObject_co, to_end: None | ArrayLike = ..., to_begin: None | ArrayLike = ...) -> NDArray[object_]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def unique(ar: _ArrayLike[_SCT], return_index: L[False] = ..., return_inverse: L[False] = ..., return_counts: L[False] = ..., axis: None | SupportsIndex = ..., *, equal_nan: bool = ...) -> NDArray[_SCT]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def unique(ar: ArrayLike, return_index: L[False] = ..., return_inverse: L[False] = ..., return_counts: L[False] = ..., axis: None | SupportsIndex = ..., *, equal_nan: bool = ...) -> NDArray[Any]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def unique(ar: _ArrayLike[_SCT], return_index: L[True] = ..., return_inverse: L[False] = ..., return_counts: L[False] = ..., axis: None | SupportsIndex = ..., *, equal_nan: bool = ...) -> tuple[NDArray[_SCT], NDArray[intp]]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def unique(ar: ArrayLike, return_index: L[True] = ..., return_inverse: L[False] = ..., return_counts: L[False] = ..., axis: None | SupportsIndex = ..., *, equal_nan: bool = ...) -> tuple[NDArray[Any], NDArray[intp]]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def unique(ar: _ArrayLike[_SCT], return_index: L[False] = ..., return_inverse: L[True] = ..., return_counts: L[False] = ..., axis: None | SupportsIndex = ..., *, equal_nan: bool = ...) -> tuple[NDArray[_SCT], NDArray[intp]]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def unique(ar: ArrayLike, return_index: L[False] = ..., return_inverse: L[True] = ..., return_counts: L[False] = ..., axis: None | SupportsIndex = ..., *, equal_nan: bool = ...) -> tuple[NDArray[Any], NDArray[intp]]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def unique(ar: _ArrayLike[_SCT], return_index: L[False] = ..., return_inverse: L[False] = ..., return_counts: L[True] = ..., axis: None | SupportsIndex = ..., *, equal_nan: bool = ...) -> tuple[NDArray[_SCT], NDArray[intp]]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def unique(ar: ArrayLike, return_index: L[False] = ..., return_inverse: L[False] = ..., return_counts: L[True] = ..., axis: None | SupportsIndex = ..., *, equal_nan: bool = ...) -> tuple[NDArray[Any], NDArray[intp]]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def unique(ar: _ArrayLike[_SCT], return_index: L[True] = ..., return_inverse: L[True] = ..., return_counts: L[False] = ..., axis: None | SupportsIndex = ..., *, equal_nan: bool = ...) -> tuple[NDArray[_SCT], NDArray[intp], NDArray[intp]]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def unique(ar: ArrayLike, return_index: L[True] = ..., return_inverse: L[True] = ..., return_counts: L[False] = ..., axis: None | SupportsIndex = ..., *, equal_nan: bool = ...) -> tuple[NDArray[Any], NDArray[intp], NDArray[intp]]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def unique(ar: _ArrayLike[_SCT], return_index: L[True] = ..., return_inverse: L[False] = ..., return_counts: L[True] = ..., axis: None | SupportsIndex = ..., *, equal_nan: bool = ...) -> tuple[NDArray[_SCT], NDArray[intp], NDArray[intp]]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def unique(ar: ArrayLike, return_index: L[True] = ..., return_inverse: L[False] = ..., return_counts: L[True] = ..., axis: None | SupportsIndex = ..., *, equal_nan: bool = ...) -> tuple[NDArray[Any], NDArray[intp], NDArray[intp]]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def unique(ar: _ArrayLike[_SCT], return_index: L[False] = ..., return_inverse: L[True] = ..., return_counts: L[True] = ..., axis: None | SupportsIndex = ..., *, equal_nan: bool = ...) -> tuple[NDArray[_SCT], NDArray[intp], NDArray[intp]]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def unique(ar: ArrayLike, return_index: L[False] = ..., return_inverse: L[True] = ..., return_counts: L[True] = ..., axis: None | SupportsIndex = ..., *, equal_nan: bool = ...) -> tuple[NDArray[Any], NDArray[intp], NDArray[intp]]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def unique(ar: _ArrayLike[_SCT], return_index: L[True] = ..., return_inverse: L[True] = ..., return_counts: L[True] = ..., axis: None | SupportsIndex = ..., *, equal_nan: bool = ...) -> tuple[NDArray[_SCT], NDArray[intp], NDArray[intp], NDArray[intp]]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def unique(ar: ArrayLike, return_index: L[True] = ..., return_inverse: L[True] = ..., return_counts: L[True] = ..., axis: None | SupportsIndex = ..., *, equal_nan: bool = ...) -> tuple[NDArray[Any], NDArray[intp], NDArray[intp], NDArray[intp]]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def intersect1d(ar1: _ArrayLike[_SCTNoCast], ar2: _ArrayLike[_SCTNoCast], assume_unique: bool = ..., return_indices: L[False] = ...) -> NDArray[_SCTNoCast]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def intersect1d(ar1: ArrayLike, ar2: ArrayLike, assume_unique: bool = ..., return_indices: L[False] = ...) -> NDArray[Any]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def intersect1d(ar1: _ArrayLike[_SCTNoCast], ar2: _ArrayLike[_SCTNoCast], assume_unique: bool = ..., return_indices: L[True] = ...) -> tuple[NDArray[_SCTNoCast], NDArray[intp], NDArray[intp]]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def intersect1d(ar1: ArrayLike, ar2: ArrayLike, assume_unique: bool = ..., return_indices: L[True] = ...) -> tuple[NDArray[Any], NDArray[intp], NDArray[intp]]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def setxor1d(ar1: _ArrayLike[_SCTNoCast], ar2: _ArrayLike[_SCTNoCast], assume_unique: bool = ...) -> NDArray[_SCTNoCast]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def setxor1d(ar1: ArrayLike, ar2: ArrayLike, assume_unique: bool = ...) -> NDArray[Any]:
|
||
|
...
|
||
|
|
||
|
def in1d(ar1: ArrayLike, ar2: ArrayLike, assume_unique: bool = ..., invert: bool = ...) -> NDArray[bool_]:
|
||
|
...
|
||
|
|
||
|
def isin(element: ArrayLike, test_elements: ArrayLike, assume_unique: bool = ..., invert: bool = ..., *, kind: None | str = ...) -> NDArray[bool_]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def union1d(ar1: _ArrayLike[_SCTNoCast], ar2: _ArrayLike[_SCTNoCast]) -> NDArray[_SCTNoCast]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def union1d(ar1: ArrayLike, ar2: ArrayLike) -> NDArray[Any]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def setdiff1d(ar1: _ArrayLike[_SCTNoCast], ar2: _ArrayLike[_SCTNoCast], assume_unique: bool = ...) -> NDArray[_SCTNoCast]:
|
||
|
...
|
||
|
|
||
|
@overload
|
||
|
def setdiff1d(ar1: ArrayLike, ar2: ArrayLike, assume_unique: bool = ...) -> NDArray[Any]:
|
||
|
...
|
||
|
|