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__init__.py	2.7 KB	Del OK
__init__.pyi	5.46 KB	Del OK
__pycache__	-	Del OK
_datasource.py	22.1 KB	Del OK
_iotools.py	30.14 KB	Del OK
_version.py	4.74 KB	Del OK
_version.pyi	633 B	Del OK
arraypad.py	31.06 KB	Del OK
arraypad.pyi	1.69 KB	Del OK
arraysetops.py	32.87 KB	Del OK
arraysetops.pyi	8.14 KB	Del OK
arrayterator.py	6.9 KB	Del OK
arrayterator.pyi	1.5 KB	Del OK
format.py	33.95 KB	Del OK
format.pyi	748 B	Del OK
function_base.py	184.67 KB	Del OK
function_base.pyi	16.2 KB	Del OK
histograms.py	36.81 KB	Del OK
histograms.pyi	995 B	Del OK
index_tricks.py	30.61 KB	Del OK
index_tricks.pyi	4.15 KB	Del OK
mixins.py	6.91 KB	Del OK
mixins.pyi	3.04 KB	Del OK
nanfunctions.py	64.23 KB	Del OK
nanfunctions.pyi	606 B	Del OK
npyio.py	95.04 KB	Del OK
npyio.pyi	9.5 KB	Del OK
polynomial.py	43.1 KB	Del OK
polynomial.pyi	6.79 KB	Del OK
recfunctions.py	58.03 KB	Del OK
scimath.py	14.68 KB	Del OK
scimath.pyi	2.82 KB	Del OK
setup.py	405 B	Del OK
shape_base.py	38.03 KB	Del OK
shape_base.pyi	5.06 KB	Del OK
stride_tricks.py	17.49 KB	Del OK
stride_tricks.pyi	1.71 KB	Del OK
tests	-	Del OK
twodim_base.py	32.17 KB	Del OK
twodim_base.pyi	5.24 KB	Del OK
type_check.py	19.49 KB	Del OK
type_check.pyi	5.44 KB	Del OK
ufunclike.py	6.18 KB	Del OK
ufunclike.pyi	1.26 KB	Del OK
user_array.py	7.54 KB	Del OK
utils.py	36.92 KB	Del OK
utils.pyi	2.3 KB	Del OK

Edit: function_base.pyi

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