Updated script that can be controled by Nodejs web app
This commit is contained in:
431
lib/python3.13/site-packages/numpy/polynomial/polyutils.pyi
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431
lib/python3.13/site-packages/numpy/polynomial/polyutils.pyi
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from collections.abc import Callable, Iterable, Sequence
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from typing import (
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Any,
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Final,
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Literal,
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SupportsIndex,
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TypeAlias,
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TypeVar,
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overload,
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)
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import numpy as np
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import numpy.typing as npt
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from numpy._typing import (
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_FloatLike_co,
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_NumberLike_co,
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_ArrayLikeFloat_co,
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_ArrayLikeComplex_co,
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)
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from ._polytypes import (
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_AnyInt,
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_CoefLike_co,
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_Array2,
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_Tuple2,
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_FloatSeries,
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_CoefSeries,
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_ComplexSeries,
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_ObjectSeries,
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_ComplexArray,
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_FloatArray,
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_CoefArray,
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_ObjectArray,
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_SeriesLikeInt_co,
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_SeriesLikeFloat_co,
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_SeriesLikeComplex_co,
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_SeriesLikeCoef_co,
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_ArrayLikeCoef_co,
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_FuncBinOp,
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_FuncValND,
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_FuncVanderND,
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)
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__all__: Final[Sequence[str]] = [
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"as_series",
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"format_float",
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"getdomain",
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"mapdomain",
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"mapparms",
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"trimcoef",
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"trimseq",
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]
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_AnyLineF: TypeAlias = Callable[
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[_CoefLike_co, _CoefLike_co],
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_CoefArray,
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]
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_AnyMulF: TypeAlias = Callable[
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[npt.ArrayLike, npt.ArrayLike],
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_CoefArray,
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]
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_AnyVanderF: TypeAlias = Callable[
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[npt.ArrayLike, SupportsIndex],
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_CoefArray,
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]
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@overload
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def as_series(
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alist: npt.NDArray[np.integer[Any]] | _FloatArray,
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trim: bool = ...,
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) -> list[_FloatSeries]: ...
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@overload
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def as_series(
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alist: _ComplexArray,
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trim: bool = ...,
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) -> list[_ComplexSeries]: ...
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@overload
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def as_series(
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alist: _ObjectArray,
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trim: bool = ...,
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) -> list[_ObjectSeries]: ...
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@overload
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def as_series( # type: ignore[overload-overlap]
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alist: Iterable[_FloatArray | npt.NDArray[np.integer[Any]]],
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trim: bool = ...,
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) -> list[_FloatSeries]: ...
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@overload
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def as_series(
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alist: Iterable[_ComplexArray],
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trim: bool = ...,
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) -> list[_ComplexSeries]: ...
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@overload
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def as_series(
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alist: Iterable[_ObjectArray],
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trim: bool = ...,
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) -> list[_ObjectSeries]: ...
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@overload
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def as_series( # type: ignore[overload-overlap]
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alist: Iterable[_SeriesLikeFloat_co | float],
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trim: bool = ...,
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) -> list[_FloatSeries]: ...
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@overload
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def as_series(
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alist: Iterable[_SeriesLikeComplex_co | complex],
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trim: bool = ...,
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) -> list[_ComplexSeries]: ...
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@overload
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def as_series(
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alist: Iterable[_SeriesLikeCoef_co | object],
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trim: bool = ...,
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) -> list[_ObjectSeries]: ...
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_T_seq = TypeVar("_T_seq", bound=_CoefArray | Sequence[_CoefLike_co])
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def trimseq(seq: _T_seq) -> _T_seq: ...
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@overload
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def trimcoef( # type: ignore[overload-overlap]
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c: npt.NDArray[np.integer[Any]] | _FloatArray,
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tol: _FloatLike_co = ...,
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) -> _FloatSeries: ...
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@overload
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def trimcoef(
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c: _ComplexArray,
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tol: _FloatLike_co = ...,
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) -> _ComplexSeries: ...
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@overload
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def trimcoef(
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c: _ObjectArray,
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tol: _FloatLike_co = ...,
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) -> _ObjectSeries: ...
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@overload
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def trimcoef( # type: ignore[overload-overlap]
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c: _SeriesLikeFloat_co | float,
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tol: _FloatLike_co = ...,
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) -> _FloatSeries: ...
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@overload
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def trimcoef(
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c: _SeriesLikeComplex_co | complex,
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tol: _FloatLike_co = ...,
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) -> _ComplexSeries: ...
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@overload
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def trimcoef(
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c: _SeriesLikeCoef_co | object,
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tol: _FloatLike_co = ...,
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) -> _ObjectSeries: ...
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@overload
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def getdomain( # type: ignore[overload-overlap]
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x: _FloatArray | npt.NDArray[np.integer[Any]],
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) -> _Array2[np.float64]: ...
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@overload
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def getdomain(
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x: _ComplexArray,
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) -> _Array2[np.complex128]: ...
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@overload
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def getdomain(
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x: _ObjectArray,
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) -> _Array2[np.object_]: ...
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@overload
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def getdomain( # type: ignore[overload-overlap]
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x: _SeriesLikeFloat_co | float,
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) -> _Array2[np.float64]: ...
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@overload
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def getdomain(
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x: _SeriesLikeComplex_co | complex,
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) -> _Array2[np.complex128]: ...
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@overload
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def getdomain(
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x: _SeriesLikeCoef_co | object,
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) -> _Array2[np.object_]: ...
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@overload
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def mapparms( # type: ignore[overload-overlap]
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old: npt.NDArray[np.floating[Any] | np.integer[Any]],
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new: npt.NDArray[np.floating[Any] | np.integer[Any]],
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) -> _Tuple2[np.floating[Any]]: ...
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@overload
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def mapparms(
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old: npt.NDArray[np.number[Any]],
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new: npt.NDArray[np.number[Any]],
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) -> _Tuple2[np.complexfloating[Any, Any]]: ...
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@overload
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def mapparms(
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old: npt.NDArray[np.object_ | np.number[Any]],
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new: npt.NDArray[np.object_ | np.number[Any]],
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) -> _Tuple2[object]: ...
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@overload
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def mapparms( # type: ignore[overload-overlap]
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old: Sequence[float],
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new: Sequence[float],
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) -> _Tuple2[float]: ...
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@overload
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def mapparms(
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old: Sequence[complex],
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new: Sequence[complex],
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) -> _Tuple2[complex]: ...
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@overload
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def mapparms(
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old: _SeriesLikeFloat_co,
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new: _SeriesLikeFloat_co,
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) -> _Tuple2[np.floating[Any]]: ...
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@overload
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def mapparms(
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old: _SeriesLikeComplex_co,
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new: _SeriesLikeComplex_co,
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) -> _Tuple2[np.complexfloating[Any, Any]]: ...
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@overload
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def mapparms(
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old: _SeriesLikeCoef_co,
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new: _SeriesLikeCoef_co,
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) -> _Tuple2[object]: ...
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@overload
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def mapdomain( # type: ignore[overload-overlap]
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x: _FloatLike_co,
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old: _SeriesLikeFloat_co,
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new: _SeriesLikeFloat_co,
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) -> np.floating[Any]: ...
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@overload
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def mapdomain(
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x: _NumberLike_co,
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old: _SeriesLikeComplex_co,
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new: _SeriesLikeComplex_co,
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) -> np.complexfloating[Any, Any]: ...
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@overload
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def mapdomain( # type: ignore[overload-overlap]
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x: npt.NDArray[np.floating[Any] | np.integer[Any]],
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old: npt.NDArray[np.floating[Any] | np.integer[Any]],
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new: npt.NDArray[np.floating[Any] | np.integer[Any]],
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) -> _FloatSeries: ...
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@overload
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def mapdomain(
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x: npt.NDArray[np.number[Any]],
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old: npt.NDArray[np.number[Any]],
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new: npt.NDArray[np.number[Any]],
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) -> _ComplexSeries: ...
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@overload
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def mapdomain(
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x: npt.NDArray[np.object_ | np.number[Any]],
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old: npt.NDArray[np.object_ | np.number[Any]],
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new: npt.NDArray[np.object_ | np.number[Any]],
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) -> _ObjectSeries: ...
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@overload
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def mapdomain( # type: ignore[overload-overlap]
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x: _SeriesLikeFloat_co,
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old: _SeriesLikeFloat_co,
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new: _SeriesLikeFloat_co,
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) -> _FloatSeries: ...
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@overload
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def mapdomain(
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x: _SeriesLikeComplex_co,
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old: _SeriesLikeComplex_co,
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new: _SeriesLikeComplex_co,
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) -> _ComplexSeries: ...
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@overload
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def mapdomain(
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x: _SeriesLikeCoef_co,
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old:_SeriesLikeCoef_co,
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new: _SeriesLikeCoef_co,
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) -> _ObjectSeries: ...
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@overload
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def mapdomain(
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x: _CoefLike_co,
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old: _SeriesLikeCoef_co,
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new: _SeriesLikeCoef_co,
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) -> object: ...
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def _nth_slice(
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i: SupportsIndex,
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ndim: SupportsIndex,
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) -> tuple[None | slice, ...]: ...
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_vander_nd: _FuncVanderND[Literal["_vander_nd"]]
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_vander_nd_flat: _FuncVanderND[Literal["_vander_nd_flat"]]
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# keep in sync with `._polytypes._FuncFromRoots`
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@overload
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def _fromroots( # type: ignore[overload-overlap]
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line_f: _AnyLineF,
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mul_f: _AnyMulF,
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roots: _SeriesLikeFloat_co,
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) -> _FloatSeries: ...
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@overload
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def _fromroots(
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line_f: _AnyLineF,
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mul_f: _AnyMulF,
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roots: _SeriesLikeComplex_co,
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) -> _ComplexSeries: ...
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@overload
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def _fromroots(
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line_f: _AnyLineF,
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mul_f: _AnyMulF,
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roots: _SeriesLikeCoef_co,
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) -> _ObjectSeries: ...
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@overload
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def _fromroots(
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line_f: _AnyLineF,
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mul_f: _AnyMulF,
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roots: _SeriesLikeCoef_co,
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) -> _CoefSeries: ...
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_valnd: _FuncValND[Literal["_valnd"]]
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_gridnd: _FuncValND[Literal["_gridnd"]]
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# keep in sync with `_polytypes._FuncBinOp`
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@overload
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def _div( # type: ignore[overload-overlap]
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mul_f: _AnyMulF,
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c1: _SeriesLikeFloat_co,
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c2: _SeriesLikeFloat_co,
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) -> _Tuple2[_FloatSeries]: ...
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@overload
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def _div(
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mul_f: _AnyMulF,
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c1: _SeriesLikeComplex_co,
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c2: _SeriesLikeComplex_co,
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) -> _Tuple2[_ComplexSeries]: ...
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@overload
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def _div(
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mul_f: _AnyMulF,
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c1: _SeriesLikeCoef_co,
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c2: _SeriesLikeCoef_co,
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) -> _Tuple2[_ObjectSeries]: ...
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@overload
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def _div(
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mul_f: _AnyMulF,
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c1: _SeriesLikeCoef_co,
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c2: _SeriesLikeCoef_co,
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) -> _Tuple2[_CoefSeries]: ...
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_add: Final[_FuncBinOp]
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_sub: Final[_FuncBinOp]
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# keep in sync with `_polytypes._FuncPow`
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@overload
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def _pow( # type: ignore[overload-overlap]
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mul_f: _AnyMulF,
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c: _SeriesLikeFloat_co,
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pow: _AnyInt,
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maxpower: None | _AnyInt = ...,
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) -> _FloatSeries: ...
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@overload
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def _pow(
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mul_f: _AnyMulF,
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c: _SeriesLikeComplex_co,
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pow: _AnyInt,
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maxpower: None | _AnyInt = ...,
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) -> _ComplexSeries: ...
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@overload
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def _pow(
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mul_f: _AnyMulF,
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c: _SeriesLikeCoef_co,
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pow: _AnyInt,
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maxpower: None | _AnyInt = ...,
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) -> _ObjectSeries: ...
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@overload
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def _pow(
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mul_f: _AnyMulF,
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c: _SeriesLikeCoef_co,
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pow: _AnyInt,
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maxpower: None | _AnyInt = ...,
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) -> _CoefSeries: ...
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# keep in sync with `_polytypes._FuncFit`
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@overload
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def _fit( # type: ignore[overload-overlap]
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vander_f: _AnyVanderF,
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x: _SeriesLikeFloat_co,
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y: _ArrayLikeFloat_co,
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deg: _SeriesLikeInt_co,
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domain: None | _SeriesLikeFloat_co = ...,
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rcond: None | _FloatLike_co = ...,
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full: Literal[False] = ...,
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w: None | _SeriesLikeFloat_co = ...,
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) -> _FloatArray: ...
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@overload
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def _fit(
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vander_f: _AnyVanderF,
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x: _SeriesLikeComplex_co,
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y: _ArrayLikeComplex_co,
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deg: _SeriesLikeInt_co,
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domain: None | _SeriesLikeComplex_co = ...,
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rcond: None | _FloatLike_co = ...,
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full: Literal[False] = ...,
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w: None | _SeriesLikeComplex_co = ...,
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) -> _ComplexArray: ...
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@overload
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def _fit(
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vander_f: _AnyVanderF,
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x: _SeriesLikeCoef_co,
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y: _ArrayLikeCoef_co,
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deg: _SeriesLikeInt_co,
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domain: None | _SeriesLikeCoef_co = ...,
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rcond: None | _FloatLike_co = ...,
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full: Literal[False] = ...,
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w: None | _SeriesLikeCoef_co = ...,
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) -> _CoefArray: ...
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@overload
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def _fit(
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vander_f: _AnyVanderF,
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x: _SeriesLikeCoef_co,
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y: _SeriesLikeCoef_co,
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deg: _SeriesLikeInt_co,
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domain: None | _SeriesLikeCoef_co,
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rcond: None | _FloatLike_co ,
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full: Literal[True],
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/,
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w: None | _SeriesLikeCoef_co = ...,
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) -> tuple[_CoefSeries, Sequence[np.inexact[Any] | np.int32]]: ...
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@overload
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def _fit(
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vander_f: _AnyVanderF,
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x: _SeriesLikeCoef_co,
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y: _SeriesLikeCoef_co,
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deg: _SeriesLikeInt_co,
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domain: None | _SeriesLikeCoef_co = ...,
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rcond: None | _FloatLike_co = ...,
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*,
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full: Literal[True],
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w: None | _SeriesLikeCoef_co = ...,
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) -> tuple[_CoefSeries, Sequence[np.inexact[Any] | np.int32]]: ...
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def _as_int(x: SupportsIndex, desc: str) -> int: ...
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def format_float(x: _FloatLike_co, parens: bool = ...) -> str: ...
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Block a user