263 lines
7.6 KiB
Python
263 lines
7.6 KiB
Python
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import abc
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import decimal
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from collections.abc import Iterator, 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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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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_NameT_co = TypeVar("_NameT_co", bound=str | None, default=str | None, covariant=True)
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_PolyT = TypeVar("_PolyT", bound=ABCPolyBase)
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_AnyOther: TypeAlias = ABCPolyBase | _CoefLike_co | _SeriesLikeCoef_co
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class ABCPolyBase(Generic[_NameT_co], abc.ABC):
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__hash__: ClassVar[None] = None # type: ignore[assignment] # pyright: ignore[reportIncompatibleMethodOverride]
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__array_ufunc__: ClassVar[None] = None
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maxpower: ClassVar[Literal[100]] = 100
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_superscript_mapping: ClassVar[dict[int, str]] = ...
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_subscript_mapping: ClassVar[dict[int, str]] = ...
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_use_unicode: ClassVar[bool] = ...
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_symbol: str
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@property
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def symbol(self, /) -> str: ...
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@property
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@abc.abstractmethod
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def domain(self) -> _Array2[np.float64 | Any]: ...
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@property
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@abc.abstractmethod
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def window(self) -> _Array2[np.float64 | Any]: ...
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@property
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@abc.abstractmethod
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def basis_name(self) -> _NameT_co: ...
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coef: _CoefSeries
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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 = None,
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window: _SeriesLikeCoef_co | None = None,
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symbol: str = "x",
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) -> None: ...
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#
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@overload
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def __call__(self, /, arg: _PolyT) -> _PolyT: ...
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@overload
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def __call__(self, /, arg: _FloatLike_co | decimal.Decimal) -> np.float64 | Any: ...
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@overload
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def __call__(self, /, arg: _NumberLike_co) -> np.complex128 | Any: ...
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@overload
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def __call__(self, /, arg: _ArrayLikeFloat_co) -> npt.NDArray[np.float64 | Any]: ...
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@overload
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def __call__(self, /, arg: _ArrayLikeComplex_co) -> npt.NDArray[np.complex128 | Any]: ...
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@overload
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def __call__(self, /, arg: _ArrayLikeCoefObject_co) -> npt.NDArray[np.object_]: ...
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# unary ops
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def __neg__(self, /) -> Self: ...
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def __pos__(self, /) -> Self: ...
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# binary ops
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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 __pow__(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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# reflected binary ops
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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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# iterable and sized
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def __len__(self, /) -> int: ...
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def __iter__(self, /) -> Iterator[np.float64 | Any]: ...
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# pickling
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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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#
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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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def has_sametype(self, /, other: object) -> TypeIs[Self]: ...
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#
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def copy(self, /) -> Self: ...
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def degree(self, /) -> int: ...
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def cutdeg(self, /, deg: int) -> Self: ...
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def trim(self, /, tol: _FloatLike_co = 0) -> Self: ...
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def truncate(self, /, size: _AnyInt) -> Self: ...
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#
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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[_PolyT],
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window: _SeriesLikeCoef_co | None = None,
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) -> _PolyT: ...
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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 = None,
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*,
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kind: type[_PolyT],
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window: _SeriesLikeCoef_co | None = None,
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) -> _PolyT: ...
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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 = None,
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kind: None = None,
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window: _SeriesLikeCoef_co | None = None,
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) -> Self: ...
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#
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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 = 1,
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k: _CoefLike_co | _SeriesLikeCoef_co = [],
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lbnd: _CoefLike_co | None = None,
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) -> Self: ...
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def deriv(self, /, m: SupportsIndex = 1) -> 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 = 100,
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domain: _SeriesLikeCoef_co | None = None,
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) -> _Tuple2[_Series[np.float64 | np.complex128]]: ...
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#
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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 = None,
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rcond: _FloatLike_co | None = None,
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full: Literal[False] = False,
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w: _SeriesLikeCoef_co | None = None,
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window: _SeriesLikeCoef_co | None = None,
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symbol: str = "x",
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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 = None,
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rcond: _FloatLike_co | None = None,
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*,
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full: Literal[True],
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w: _SeriesLikeCoef_co | None = None,
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window: _SeriesLikeCoef_co | None = None,
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symbol: str = "x",
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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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/,
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w: _SeriesLikeCoef_co | None = None,
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window: _SeriesLikeCoef_co | None = None,
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symbol: str = "x",
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) -> tuple[Self, Sequence[np.inexact | np.int32]]: ...
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#
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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 = None,
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symbol: str = "x",
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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 = None,
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window: _SeriesLikeCoef_co | None = None,
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symbol: str = "x",
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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 = None,
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window: _SeriesLikeCoef_co | None = None,
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symbol: str = "x",
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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 = None,
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window: _SeriesLikeCoef_co | None = 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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@classmethod
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def _str_term_ascii(cls, /, i: str, arg_str: str) -> str: ...
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@classmethod
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def _repr_latex_term(cls, /, i: str, arg_str: str, needs_parens: bool) -> str: ...
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