286 lines
		
	
	
		
			8.0 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			286 lines
		
	
	
		
			8.0 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
import abc
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import decimal
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import numbers
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from collections.abc import Iterator, Mapping, Sequence
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from typing import (
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    Any,
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    ClassVar,
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    Generic,
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    Literal,
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    LiteralString,
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    Self,
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    SupportsIndex,
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    TypeAlias,
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    overload,
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)
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from typing_extensions import TypeIs, TypeVar
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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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    _ArrayLikeComplex_co,
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    _ArrayLikeFloat_co,
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    _FloatLike_co,
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    _NumberLike_co,
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)
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from ._polytypes import (
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    _AnyInt,
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    _Array2,
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    _ArrayLikeCoef_co,
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    _ArrayLikeCoefObject_co,
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    _CoefLike_co,
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    _CoefSeries,
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    _Series,
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    _SeriesLikeCoef_co,
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    _SeriesLikeInt_co,
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    _Tuple2,
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)
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__all__ = ["ABCPolyBase"]
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_NameCo = TypeVar(
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    "_NameCo",
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    bound=LiteralString | None,
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    covariant=True,
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    default=LiteralString | None
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)
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_Other = TypeVar("_Other", bound=ABCPolyBase)
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_AnyOther: TypeAlias = ABCPolyBase | _CoefLike_co | _SeriesLikeCoef_co
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_Hundred: TypeAlias = Literal[100]
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class ABCPolyBase(Generic[_NameCo], abc.ABC):
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    __hash__: ClassVar[None]  # type: ignore[assignment]  # pyright: ignore[reportIncompatibleMethodOverride]
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    __array_ufunc__: ClassVar[None]
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    maxpower: ClassVar[_Hundred]
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    _superscript_mapping: ClassVar[Mapping[int, str]]
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    _subscript_mapping: ClassVar[Mapping[int, str]]
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    _use_unicode: ClassVar[bool]
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    basis_name: _NameCo
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    coef: _CoefSeries
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    domain: _Array2[np.inexact | np.object_]
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    window: _Array2[np.inexact | np.object_]
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    _symbol: LiteralString
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    @property
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    def symbol(self, /) -> LiteralString: ...
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    def __init__(
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        self,
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        /,
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        coef: _SeriesLikeCoef_co,
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        domain: _SeriesLikeCoef_co | None = ...,
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        window: _SeriesLikeCoef_co | None = ...,
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        symbol: str = ...,
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    ) -> None: ...
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    @overload
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    def __call__(self, /, arg: _Other) -> _Other: ...
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    # TODO: Once `_ShapeT@ndarray` is covariant and bounded (see #26081),
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    # additionally include 0-d arrays as input types with scalar return type.
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    @overload
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    def __call__(
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        self,
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        /,
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        arg: _FloatLike_co | decimal.Decimal | numbers.Real | np.object_,
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    ) -> np.float64 | np.complex128: ...
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    @overload
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    def __call__(
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        self,
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        /,
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        arg: _NumberLike_co | numbers.Complex,
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    ) -> np.complex128: ...
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    @overload
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    def __call__(self, /, arg: _ArrayLikeFloat_co) -> (
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        npt.NDArray[np.float64]
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        | npt.NDArray[np.complex128]
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        | npt.NDArray[np.object_]
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    ): ...
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    @overload
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    def __call__(
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        self,
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        /,
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        arg: _ArrayLikeComplex_co,
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    ) -> npt.NDArray[np.complex128] | npt.NDArray[np.object_]: ...
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    @overload
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    def __call__(
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        self,
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        /,
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        arg: _ArrayLikeCoefObject_co,
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    ) -> npt.NDArray[np.object_]: ...
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    def __format__(self, fmt_str: str, /) -> str: ...
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    def __eq__(self, x: object, /) -> bool: ...
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    def __ne__(self, x: object, /) -> bool: ...
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    def __neg__(self, /) -> Self: ...
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    def __pos__(self, /) -> Self: ...
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    def __add__(self, x: _AnyOther, /) -> Self: ...
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    def __sub__(self, x: _AnyOther, /) -> Self: ...
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    def __mul__(self, x: _AnyOther, /) -> Self: ...
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    def __truediv__(self, x: _AnyOther, /) -> Self: ...
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    def __floordiv__(self, x: _AnyOther, /) -> Self: ...
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    def __mod__(self, x: _AnyOther, /) -> Self: ...
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    def __divmod__(self, x: _AnyOther, /) -> _Tuple2[Self]: ...
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    def __pow__(self, x: _AnyOther, /) -> Self: ...
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    def __radd__(self, x: _AnyOther, /) -> Self: ...
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    def __rsub__(self, x: _AnyOther, /) -> Self: ...
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    def __rmul__(self, x: _AnyOther, /) -> Self: ...
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    def __rtruediv__(self, x: _AnyOther, /) -> Self: ...
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    def __rfloordiv__(self, x: _AnyOther, /) -> Self: ...
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    def __rmod__(self, x: _AnyOther, /) -> Self: ...
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    def __rdivmod__(self, x: _AnyOther, /) -> _Tuple2[Self]: ...
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    def __len__(self, /) -> int: ...
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    def __iter__(self, /) -> Iterator[np.inexact | object]: ...
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    def __getstate__(self, /) -> dict[str, Any]: ...
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    def __setstate__(self, dict: dict[str, Any], /) -> None: ...
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    def has_samecoef(self, /, other: ABCPolyBase) -> bool: ...
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    def has_samedomain(self, /, other: ABCPolyBase) -> bool: ...
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    def has_samewindow(self, /, other: ABCPolyBase) -> bool: ...
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    @overload
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    def has_sametype(self, /, other: ABCPolyBase) -> TypeIs[Self]: ...
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    @overload
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    def has_sametype(self, /, other: object) -> Literal[False]: ...
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    def copy(self, /) -> Self: ...
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    def degree(self, /) -> int: ...
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    def cutdeg(self, /) -> Self: ...
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    def trim(self, /, tol: _FloatLike_co = ...) -> Self: ...
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    def truncate(self, /, size: _AnyInt) -> Self: ...
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    @overload
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    def convert(
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        self,
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        /,
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        domain: _SeriesLikeCoef_co | None,
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        kind: type[_Other],
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        window: _SeriesLikeCoef_co | None = ...,
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    ) -> _Other: ...
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    @overload
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    def convert(
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        self,
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        /,
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        domain: _SeriesLikeCoef_co | None = ...,
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        *,
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        kind: type[_Other],
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        window: _SeriesLikeCoef_co | None = ...,
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    ) -> _Other: ...
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    @overload
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    def convert(
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        self,
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        /,
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        domain: _SeriesLikeCoef_co | None = ...,
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        kind: None = None,
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        window: _SeriesLikeCoef_co | None = ...,
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    ) -> Self: ...
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    def mapparms(self, /) -> _Tuple2[Any]: ...
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    def integ(
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        self,
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        /,
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        m: SupportsIndex = ...,
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        k: _CoefLike_co | _SeriesLikeCoef_co = ...,
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        lbnd: _CoefLike_co | None = ...,
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    ) -> Self: ...
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    def deriv(self, /, m: SupportsIndex = ...) -> Self: ...
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    def roots(self, /) -> _CoefSeries: ...
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    def linspace(
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        self,
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        /,
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        n: SupportsIndex = ...,
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        domain: _SeriesLikeCoef_co | None = ...,
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    ) -> _Tuple2[_Series[np.float64 | np.complex128]]: ...
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    @overload
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    @classmethod
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    def fit(
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        cls,
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        x: _SeriesLikeCoef_co,
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        y: _SeriesLikeCoef_co,
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        deg: int | _SeriesLikeInt_co,
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        domain: _SeriesLikeCoef_co | None = ...,
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        rcond: _FloatLike_co = ...,
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        full: Literal[False] = ...,
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        w: _SeriesLikeCoef_co | None = ...,
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        window: _SeriesLikeCoef_co | None = ...,
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        symbol: str = ...,
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    ) -> Self: ...
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    @overload
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    @classmethod
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    def fit(
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        cls,
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        x: _SeriesLikeCoef_co,
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        y: _SeriesLikeCoef_co,
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        deg: int | _SeriesLikeInt_co,
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        domain: _SeriesLikeCoef_co | None = ...,
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        rcond: _FloatLike_co = ...,
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        *,
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        full: Literal[True],
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        w: _SeriesLikeCoef_co | None = ...,
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        window: _SeriesLikeCoef_co | None = ...,
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        symbol: str = ...,
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    ) -> tuple[Self, Sequence[np.inexact | np.int32]]: ...
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    @overload
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    @classmethod
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    def fit(
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        cls,
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        x: _SeriesLikeCoef_co,
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        y: _SeriesLikeCoef_co,
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        deg: int | _SeriesLikeInt_co,
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        domain: _SeriesLikeCoef_co | None,
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        rcond: _FloatLike_co,
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        full: Literal[True], /,
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        w: _SeriesLikeCoef_co | None = ...,
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        window: _SeriesLikeCoef_co | None = ...,
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        symbol: str = ...,
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    ) -> tuple[Self, Sequence[np.inexact | np.int32]]: ...
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    @classmethod
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    def fromroots(
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        cls,
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        roots: _ArrayLikeCoef_co,
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        domain: _SeriesLikeCoef_co | None = ...,
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        window: _SeriesLikeCoef_co | None = ...,
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        symbol: str = ...,
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    ) -> Self: ...
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    @classmethod
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    def identity(
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        cls,
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        domain: _SeriesLikeCoef_co | None = ...,
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        window: _SeriesLikeCoef_co | None = ...,
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        symbol: str = ...,
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    ) -> Self: ...
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    @classmethod
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    def basis(
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        cls,
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        deg: _AnyInt,
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        domain: _SeriesLikeCoef_co | None = ...,
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        window: _SeriesLikeCoef_co | None = ...,
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        symbol: str = ...,
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    ) -> Self: ...
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    @classmethod
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    def cast(
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        cls,
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        series: ABCPolyBase,
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        domain: _SeriesLikeCoef_co | None = ...,
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        window: _SeriesLikeCoef_co | None = ...,
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    ) -> Self: ...
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    @classmethod
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    def _str_term_unicode(cls, /, i: str, arg_str: str) -> str: ...
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    @staticmethod
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    def _str_term_ascii(i: str, arg_str: str) -> str: ...
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    @staticmethod
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    def _repr_latex_term(i: str, arg_str: str, needs_parens: bool) -> str: ...
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