698 lines
16 KiB
Python
698 lines
16 KiB
Python
import sys
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from collections.abc import Sequence, Iterator, Callable, Iterable
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from typing import (
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Literal as L,
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Any,
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TypeVar,
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overload,
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Protocol,
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SupportsIndex,
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SupportsInt,
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)
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if sys.version_info >= (3, 10):
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from typing import TypeGuard
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else:
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from typing_extensions import TypeGuard
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from numpy import (
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vectorize as vectorize,
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ufunc,
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generic,
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floating,
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complexfloating,
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intp,
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float64,
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complex128,
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timedelta64,
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datetime64,
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object_,
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_OrderKACF,
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)
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from numpy._typing import (
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NDArray,
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ArrayLike,
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DTypeLike,
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_ShapeLike,
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_ScalarLike_co,
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_DTypeLike,
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_ArrayLike,
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_ArrayLikeInt_co,
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_ArrayLikeFloat_co,
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_ArrayLikeComplex_co,
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_ArrayLikeTD64_co,
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_ArrayLikeDT64_co,
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_ArrayLikeObject_co,
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_FloatLike_co,
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_ComplexLike_co,
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)
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from numpy.core.function_base import (
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add_newdoc as add_newdoc,
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)
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from numpy.core.multiarray import (
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add_docstring as add_docstring,
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bincount as bincount,
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)
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from numpy.core.umath import _add_newdoc_ufunc
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_T = TypeVar("_T")
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_T_co = TypeVar("_T_co", covariant=True)
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_SCT = TypeVar("_SCT", bound=generic)
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_ArrayType = TypeVar("_ArrayType", bound=NDArray[Any])
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_2Tuple = tuple[_T, _T]
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class _TrimZerosSequence(Protocol[_T_co]):
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def __len__(self) -> int: ...
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def __getitem__(self, key: slice, /) -> _T_co: ...
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def __iter__(self) -> Iterator[Any]: ...
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class _SupportsWriteFlush(Protocol):
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def write(self, s: str, /) -> object: ...
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def flush(self) -> object: ...
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__all__: list[str]
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# NOTE: This is in reality a re-export of `np.core.umath._add_newdoc_ufunc`
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def add_newdoc_ufunc(ufunc: ufunc, new_docstring: str, /) -> None: ...
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@overload
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def rot90(
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m: _ArrayLike[_SCT],
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k: int = ...,
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axes: tuple[int, int] = ...,
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) -> NDArray[_SCT]: ...
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@overload
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def rot90(
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m: ArrayLike,
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k: int = ...,
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axes: tuple[int, int] = ...,
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) -> NDArray[Any]: ...
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@overload
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def flip(m: _SCT, axis: None = ...) -> _SCT: ...
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@overload
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def flip(m: _ScalarLike_co, axis: None = ...) -> Any: ...
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@overload
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def flip(m: _ArrayLike[_SCT], axis: None | _ShapeLike = ...) -> NDArray[_SCT]: ...
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@overload
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def flip(m: ArrayLike, axis: None | _ShapeLike = ...) -> NDArray[Any]: ...
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def iterable(y: object) -> TypeGuard[Iterable[Any]]: ...
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@overload
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def average(
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a: _ArrayLikeFloat_co,
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axis: None = ...,
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weights: None | _ArrayLikeFloat_co= ...,
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returned: L[False] = ...,
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keepdims: L[False] = ...,
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) -> floating[Any]: ...
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@overload
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def average(
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a: _ArrayLikeComplex_co,
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axis: None = ...,
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weights: None | _ArrayLikeComplex_co = ...,
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returned: L[False] = ...,
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keepdims: L[False] = ...,
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) -> complexfloating[Any, Any]: ...
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@overload
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def average(
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a: _ArrayLikeObject_co,
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axis: None = ...,
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weights: None | Any = ...,
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returned: L[False] = ...,
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keepdims: L[False] = ...,
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) -> Any: ...
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@overload
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def average(
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a: _ArrayLikeFloat_co,
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axis: None = ...,
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weights: None | _ArrayLikeFloat_co= ...,
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returned: L[True] = ...,
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keepdims: L[False] = ...,
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) -> _2Tuple[floating[Any]]: ...
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@overload
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def average(
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a: _ArrayLikeComplex_co,
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axis: None = ...,
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weights: None | _ArrayLikeComplex_co = ...,
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returned: L[True] = ...,
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keepdims: L[False] = ...,
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) -> _2Tuple[complexfloating[Any, Any]]: ...
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@overload
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def average(
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a: _ArrayLikeObject_co,
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axis: None = ...,
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weights: None | Any = ...,
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returned: L[True] = ...,
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keepdims: L[False] = ...,
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) -> _2Tuple[Any]: ...
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@overload
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def average(
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a: _ArrayLikeComplex_co | _ArrayLikeObject_co,
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axis: None | _ShapeLike = ...,
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weights: None | Any = ...,
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returned: L[False] = ...,
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keepdims: bool = ...,
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) -> Any: ...
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@overload
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def average(
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a: _ArrayLikeComplex_co | _ArrayLikeObject_co,
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axis: None | _ShapeLike = ...,
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weights: None | Any = ...,
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returned: L[True] = ...,
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keepdims: bool = ...,
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) -> _2Tuple[Any]: ...
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@overload
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def asarray_chkfinite(
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a: _ArrayLike[_SCT],
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dtype: None = ...,
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order: _OrderKACF = ...,
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) -> NDArray[_SCT]: ...
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@overload
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def asarray_chkfinite(
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a: object,
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dtype: None = ...,
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order: _OrderKACF = ...,
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) -> NDArray[Any]: ...
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@overload
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def asarray_chkfinite(
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a: Any,
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dtype: _DTypeLike[_SCT],
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order: _OrderKACF = ...,
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) -> NDArray[_SCT]: ...
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@overload
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def asarray_chkfinite(
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a: Any,
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dtype: DTypeLike,
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order: _OrderKACF = ...,
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) -> NDArray[Any]: ...
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# TODO: Use PEP 612 `ParamSpec` once mypy supports `Concatenate`
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# xref python/mypy#8645
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@overload
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def piecewise(
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x: _ArrayLike[_SCT],
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condlist: ArrayLike,
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funclist: Sequence[Any | Callable[..., Any]],
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*args: Any,
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**kw: Any,
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) -> NDArray[_SCT]: ...
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@overload
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def piecewise(
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x: ArrayLike,
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condlist: ArrayLike,
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funclist: Sequence[Any | Callable[..., Any]],
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*args: Any,
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**kw: Any,
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) -> NDArray[Any]: ...
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def select(
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condlist: Sequence[ArrayLike],
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choicelist: Sequence[ArrayLike],
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default: ArrayLike = ...,
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) -> NDArray[Any]: ...
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@overload
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def copy(
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a: _ArrayType,
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order: _OrderKACF,
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subok: L[True],
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) -> _ArrayType: ...
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@overload
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def copy(
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a: _ArrayType,
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order: _OrderKACF = ...,
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*,
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subok: L[True],
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) -> _ArrayType: ...
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@overload
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def copy(
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a: _ArrayLike[_SCT],
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order: _OrderKACF = ...,
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subok: L[False] = ...,
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) -> NDArray[_SCT]: ...
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@overload
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def copy(
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a: ArrayLike,
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order: _OrderKACF = ...,
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subok: L[False] = ...,
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) -> NDArray[Any]: ...
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def gradient(
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f: ArrayLike,
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*varargs: ArrayLike,
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axis: None | _ShapeLike = ...,
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edge_order: L[1, 2] = ...,
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) -> Any: ...
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@overload
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def diff(
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a: _T,
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n: L[0],
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axis: SupportsIndex = ...,
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prepend: ArrayLike = ...,
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append: ArrayLike = ...,
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) -> _T: ...
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@overload
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def diff(
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a: ArrayLike,
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n: int = ...,
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axis: SupportsIndex = ...,
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prepend: ArrayLike = ...,
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append: ArrayLike = ...,
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) -> NDArray[Any]: ...
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@overload
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def interp(
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x: _ArrayLikeFloat_co,
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xp: _ArrayLikeFloat_co,
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fp: _ArrayLikeFloat_co,
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left: None | _FloatLike_co = ...,
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right: None | _FloatLike_co = ...,
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period: None | _FloatLike_co = ...,
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) -> NDArray[float64]: ...
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@overload
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def interp(
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x: _ArrayLikeFloat_co,
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xp: _ArrayLikeFloat_co,
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fp: _ArrayLikeComplex_co,
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left: None | _ComplexLike_co = ...,
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right: None | _ComplexLike_co = ...,
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period: None | _FloatLike_co = ...,
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) -> NDArray[complex128]: ...
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@overload
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def angle(z: _ComplexLike_co, deg: bool = ...) -> floating[Any]: ...
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@overload
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def angle(z: object_, deg: bool = ...) -> Any: ...
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@overload
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def angle(z: _ArrayLikeComplex_co, deg: bool = ...) -> NDArray[floating[Any]]: ...
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@overload
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def angle(z: _ArrayLikeObject_co, deg: bool = ...) -> NDArray[object_]: ...
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@overload
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def unwrap(
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p: _ArrayLikeFloat_co,
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discont: None | float = ...,
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axis: int = ...,
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*,
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period: float = ...,
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) -> NDArray[floating[Any]]: ...
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@overload
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def unwrap(
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p: _ArrayLikeObject_co,
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discont: None | float = ...,
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axis: int = ...,
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*,
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period: float = ...,
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) -> NDArray[object_]: ...
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def sort_complex(a: ArrayLike) -> NDArray[complexfloating[Any, Any]]: ...
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def trim_zeros(
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filt: _TrimZerosSequence[_T],
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trim: L["f", "b", "fb", "bf"] = ...,
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) -> _T: ...
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@overload
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def extract(condition: ArrayLike, arr: _ArrayLike[_SCT]) -> NDArray[_SCT]: ...
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@overload
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def extract(condition: ArrayLike, arr: ArrayLike) -> NDArray[Any]: ...
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def place(arr: NDArray[Any], mask: ArrayLike, vals: Any) -> None: ...
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def disp(
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mesg: object,
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device: None | _SupportsWriteFlush = ...,
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linefeed: bool = ...,
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) -> None: ...
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@overload
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def cov(
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m: _ArrayLikeFloat_co,
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y: None | _ArrayLikeFloat_co = ...,
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rowvar: bool = ...,
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bias: bool = ...,
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ddof: None | SupportsIndex | SupportsInt = ...,
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fweights: None | ArrayLike = ...,
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aweights: None | ArrayLike = ...,
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*,
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dtype: None = ...,
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) -> NDArray[floating[Any]]: ...
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@overload
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def cov(
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m: _ArrayLikeComplex_co,
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y: None | _ArrayLikeComplex_co = ...,
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rowvar: bool = ...,
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bias: bool = ...,
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ddof: None | SupportsIndex | SupportsInt = ...,
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fweights: None | ArrayLike = ...,
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aweights: None | ArrayLike = ...,
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*,
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dtype: None = ...,
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) -> NDArray[complexfloating[Any, Any]]: ...
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@overload
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def cov(
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m: _ArrayLikeComplex_co,
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y: None | _ArrayLikeComplex_co = ...,
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rowvar: bool = ...,
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bias: bool = ...,
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ddof: None | SupportsIndex | SupportsInt = ...,
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fweights: None | ArrayLike = ...,
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aweights: None | ArrayLike = ...,
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*,
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dtype: _DTypeLike[_SCT],
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) -> NDArray[_SCT]: ...
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@overload
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def cov(
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m: _ArrayLikeComplex_co,
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y: None | _ArrayLikeComplex_co = ...,
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rowvar: bool = ...,
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bias: bool = ...,
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ddof: None | SupportsIndex | SupportsInt = ...,
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fweights: None | ArrayLike = ...,
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aweights: None | ArrayLike = ...,
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*,
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dtype: DTypeLike,
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) -> NDArray[Any]: ...
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# NOTE `bias` and `ddof` have been deprecated
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@overload
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def corrcoef(
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m: _ArrayLikeFloat_co,
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y: None | _ArrayLikeFloat_co = ...,
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rowvar: bool = ...,
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*,
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dtype: None = ...,
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) -> NDArray[floating[Any]]: ...
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@overload
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def corrcoef(
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m: _ArrayLikeComplex_co,
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y: None | _ArrayLikeComplex_co = ...,
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rowvar: bool = ...,
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*,
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dtype: None = ...,
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) -> NDArray[complexfloating[Any, Any]]: ...
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@overload
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def corrcoef(
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m: _ArrayLikeComplex_co,
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y: None | _ArrayLikeComplex_co = ...,
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rowvar: bool = ...,
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*,
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dtype: _DTypeLike[_SCT],
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) -> NDArray[_SCT]: ...
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@overload
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def corrcoef(
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m: _ArrayLikeComplex_co,
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y: None | _ArrayLikeComplex_co = ...,
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rowvar: bool = ...,
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*,
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dtype: DTypeLike,
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) -> NDArray[Any]: ...
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def blackman(M: _FloatLike_co) -> NDArray[floating[Any]]: ...
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def bartlett(M: _FloatLike_co) -> NDArray[floating[Any]]: ...
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def hanning(M: _FloatLike_co) -> NDArray[floating[Any]]: ...
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def hamming(M: _FloatLike_co) -> NDArray[floating[Any]]: ...
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def i0(x: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ...
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def kaiser(
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M: _FloatLike_co,
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beta: _FloatLike_co,
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) -> NDArray[floating[Any]]: ...
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|
@overload
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def sinc(x: _FloatLike_co) -> floating[Any]: ...
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@overload
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def sinc(x: _ComplexLike_co) -> complexfloating[Any, Any]: ...
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@overload
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def sinc(x: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ...
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@overload
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def sinc(x: _ArrayLikeComplex_co) -> NDArray[complexfloating[Any, Any]]: ...
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# NOTE: Deprecated
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# def msort(a: ArrayLike) -> NDArray[Any]: ...
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@overload
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def median(
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a: _ArrayLikeFloat_co,
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axis: None = ...,
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out: None = ...,
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overwrite_input: bool = ...,
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|
keepdims: L[False] = ...,
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) -> floating[Any]: ...
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@overload
|
|
def median(
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a: _ArrayLikeComplex_co,
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axis: None = ...,
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|
out: None = ...,
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|
overwrite_input: bool = ...,
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|
keepdims: L[False] = ...,
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) -> complexfloating[Any, Any]: ...
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@overload
|
|
def median(
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a: _ArrayLikeTD64_co,
|
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axis: None = ...,
|
|
out: None = ...,
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|
overwrite_input: bool = ...,
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|
keepdims: L[False] = ...,
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) -> timedelta64: ...
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@overload
|
|
def median(
|
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a: _ArrayLikeObject_co,
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|
axis: None = ...,
|
|
out: None = ...,
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|
overwrite_input: bool = ...,
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|
keepdims: L[False] = ...,
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) -> Any: ...
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@overload
|
|
def median(
|
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a: _ArrayLikeFloat_co | _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeObject_co,
|
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axis: None | _ShapeLike = ...,
|
|
out: None = ...,
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|
overwrite_input: bool = ...,
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|
keepdims: bool = ...,
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) -> Any: ...
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@overload
|
|
def median(
|
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a: _ArrayLikeFloat_co | _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeObject_co,
|
|
axis: None | _ShapeLike = ...,
|
|
out: _ArrayType = ...,
|
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overwrite_input: bool = ...,
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|
keepdims: bool = ...,
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) -> _ArrayType: ...
|
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|
_MethodKind = L[
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"inverted_cdf",
|
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"averaged_inverted_cdf",
|
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"closest_observation",
|
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"interpolated_inverted_cdf",
|
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"hazen",
|
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"weibull",
|
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"linear",
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"median_unbiased",
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"normal_unbiased",
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"lower",
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"higher",
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"midpoint",
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"nearest",
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]
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@overload
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def percentile(
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a: _ArrayLikeFloat_co,
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q: _FloatLike_co,
|
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axis: None = ...,
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out: None = ...,
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overwrite_input: bool = ...,
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method: _MethodKind = ...,
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keepdims: L[False] = ...,
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) -> floating[Any]: ...
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@overload
|
|
def percentile(
|
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a: _ArrayLikeComplex_co,
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q: _FloatLike_co,
|
|
axis: None = ...,
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out: None = ...,
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|
overwrite_input: bool = ...,
|
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method: _MethodKind = ...,
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keepdims: L[False] = ...,
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) -> complexfloating[Any, Any]: ...
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@overload
|
|
def percentile(
|
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a: _ArrayLikeTD64_co,
|
|
q: _FloatLike_co,
|
|
axis: None = ...,
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out: None = ...,
|
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overwrite_input: bool = ...,
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method: _MethodKind = ...,
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|
keepdims: L[False] = ...,
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) -> timedelta64: ...
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@overload
|
|
def percentile(
|
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a: _ArrayLikeDT64_co,
|
|
q: _FloatLike_co,
|
|
axis: None = ...,
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out: None = ...,
|
|
overwrite_input: bool = ...,
|
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method: _MethodKind = ...,
|
|
keepdims: L[False] = ...,
|
|
) -> datetime64: ...
|
|
@overload
|
|
def percentile(
|
|
a: _ArrayLikeObject_co,
|
|
q: _FloatLike_co,
|
|
axis: None = ...,
|
|
out: None = ...,
|
|
overwrite_input: bool = ...,
|
|
method: _MethodKind = ...,
|
|
keepdims: L[False] = ...,
|
|
) -> Any: ...
|
|
@overload
|
|
def percentile(
|
|
a: _ArrayLikeFloat_co,
|
|
q: _ArrayLikeFloat_co,
|
|
axis: None = ...,
|
|
out: None = ...,
|
|
overwrite_input: bool = ...,
|
|
method: _MethodKind = ...,
|
|
keepdims: L[False] = ...,
|
|
) -> NDArray[floating[Any]]: ...
|
|
@overload
|
|
def percentile(
|
|
a: _ArrayLikeComplex_co,
|
|
q: _ArrayLikeFloat_co,
|
|
axis: None = ...,
|
|
out: None = ...,
|
|
overwrite_input: bool = ...,
|
|
method: _MethodKind = ...,
|
|
keepdims: L[False] = ...,
|
|
) -> NDArray[complexfloating[Any, Any]]: ...
|
|
@overload
|
|
def percentile(
|
|
a: _ArrayLikeTD64_co,
|
|
q: _ArrayLikeFloat_co,
|
|
axis: None = ...,
|
|
out: None = ...,
|
|
overwrite_input: bool = ...,
|
|
method: _MethodKind = ...,
|
|
keepdims: L[False] = ...,
|
|
) -> NDArray[timedelta64]: ...
|
|
@overload
|
|
def percentile(
|
|
a: _ArrayLikeDT64_co,
|
|
q: _ArrayLikeFloat_co,
|
|
axis: None = ...,
|
|
out: None = ...,
|
|
overwrite_input: bool = ...,
|
|
method: _MethodKind = ...,
|
|
keepdims: L[False] = ...,
|
|
) -> NDArray[datetime64]: ...
|
|
@overload
|
|
def percentile(
|
|
a: _ArrayLikeObject_co,
|
|
q: _ArrayLikeFloat_co,
|
|
axis: None = ...,
|
|
out: None = ...,
|
|
overwrite_input: bool = ...,
|
|
method: _MethodKind = ...,
|
|
keepdims: L[False] = ...,
|
|
) -> NDArray[object_]: ...
|
|
@overload
|
|
def percentile(
|
|
a: _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeTD64_co | _ArrayLikeObject_co,
|
|
q: _ArrayLikeFloat_co,
|
|
axis: None | _ShapeLike = ...,
|
|
out: None = ...,
|
|
overwrite_input: bool = ...,
|
|
method: _MethodKind = ...,
|
|
keepdims: bool = ...,
|
|
) -> Any: ...
|
|
@overload
|
|
def percentile(
|
|
a: _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeTD64_co | _ArrayLikeObject_co,
|
|
q: _ArrayLikeFloat_co,
|
|
axis: None | _ShapeLike = ...,
|
|
out: _ArrayType = ...,
|
|
overwrite_input: bool = ...,
|
|
method: _MethodKind = ...,
|
|
keepdims: bool = ...,
|
|
) -> _ArrayType: ...
|
|
|
|
# NOTE: Not an alias, but they do have identical signatures
|
|
# (that we can reuse)
|
|
quantile = percentile
|
|
|
|
# TODO: Returns a scalar for <= 1D array-likes; returns an ndarray otherwise
|
|
def trapz(
|
|
y: _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeObject_co,
|
|
x: None | _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeObject_co = ...,
|
|
dx: float = ...,
|
|
axis: SupportsIndex = ...,
|
|
) -> Any: ...
|
|
|
|
def meshgrid(
|
|
*xi: ArrayLike,
|
|
copy: bool = ...,
|
|
sparse: bool = ...,
|
|
indexing: L["xy", "ij"] = ...,
|
|
) -> list[NDArray[Any]]: ...
|
|
|
|
@overload
|
|
def delete(
|
|
arr: _ArrayLike[_SCT],
|
|
obj: slice | _ArrayLikeInt_co,
|
|
axis: None | SupportsIndex = ...,
|
|
) -> NDArray[_SCT]: ...
|
|
@overload
|
|
def delete(
|
|
arr: ArrayLike,
|
|
obj: slice | _ArrayLikeInt_co,
|
|
axis: None | SupportsIndex = ...,
|
|
) -> NDArray[Any]: ...
|
|
|
|
@overload
|
|
def insert(
|
|
arr: _ArrayLike[_SCT],
|
|
obj: slice | _ArrayLikeInt_co,
|
|
values: ArrayLike,
|
|
axis: None | SupportsIndex = ...,
|
|
) -> NDArray[_SCT]: ...
|
|
@overload
|
|
def insert(
|
|
arr: ArrayLike,
|
|
obj: slice | _ArrayLikeInt_co,
|
|
values: ArrayLike,
|
|
axis: None | SupportsIndex = ...,
|
|
) -> NDArray[Any]: ...
|
|
|
|
def append(
|
|
arr: ArrayLike,
|
|
values: ArrayLike,
|
|
axis: None | SupportsIndex = ...,
|
|
) -> NDArray[Any]: ...
|
|
|
|
@overload
|
|
def digitize(
|
|
x: _FloatLike_co,
|
|
bins: _ArrayLikeFloat_co,
|
|
right: bool = ...,
|
|
) -> intp: ...
|
|
@overload
|
|
def digitize(
|
|
x: _ArrayLikeFloat_co,
|
|
bins: _ArrayLikeFloat_co,
|
|
right: bool = ...,
|
|
) -> NDArray[intp]: ...
|