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authorblackhao <13851610112@163.com>2025-08-22 02:51:50 -0500
committerblackhao <13851610112@163.com>2025-08-22 02:51:50 -0500
commit4aab4087dc97906d0b9890035401175cdaab32d4 (patch)
tree4e2e9d88a711ec5b1cfa02e8ac72a55183b99123 /.venv/lib/python3.12/site-packages/numpy/polynomial/_polybase.pyi
parentafa8f50d1d21c721dabcb31ad244610946ab65a3 (diff)
2.0
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+import abc
+import decimal
+import numbers
+from collections.abc import Iterator, Mapping, Sequence
+from typing import (
+ Any,
+ ClassVar,
+ Generic,
+ Literal,
+ LiteralString,
+ Self,
+ SupportsIndex,
+ TypeAlias,
+ overload,
+)
+
+from typing_extensions import TypeIs, TypeVar
+
+import numpy as np
+import numpy.typing as npt
+from numpy._typing import (
+ _ArrayLikeComplex_co,
+ _ArrayLikeFloat_co,
+ _FloatLike_co,
+ _NumberLike_co,
+)
+
+from ._polytypes import (
+ _AnyInt,
+ _Array2,
+ _ArrayLikeCoef_co,
+ _ArrayLikeCoefObject_co,
+ _CoefLike_co,
+ _CoefSeries,
+ _Series,
+ _SeriesLikeCoef_co,
+ _SeriesLikeInt_co,
+ _Tuple2,
+)
+
+__all__ = ["ABCPolyBase"]
+
+_NameCo = TypeVar(
+ "_NameCo",
+ bound=LiteralString | None,
+ covariant=True,
+ default=LiteralString | None
+)
+_Other = TypeVar("_Other", bound=ABCPolyBase)
+
+_AnyOther: TypeAlias = ABCPolyBase | _CoefLike_co | _SeriesLikeCoef_co
+_Hundred: TypeAlias = Literal[100]
+
+class ABCPolyBase(Generic[_NameCo], abc.ABC):
+ __hash__: ClassVar[None] # type: ignore[assignment] # pyright: ignore[reportIncompatibleMethodOverride]
+ __array_ufunc__: ClassVar[None]
+
+ maxpower: ClassVar[_Hundred]
+ _superscript_mapping: ClassVar[Mapping[int, str]]
+ _subscript_mapping: ClassVar[Mapping[int, str]]
+ _use_unicode: ClassVar[bool]
+
+ basis_name: _NameCo
+ coef: _CoefSeries
+ domain: _Array2[np.inexact | np.object_]
+ window: _Array2[np.inexact | np.object_]
+
+ _symbol: LiteralString
+ @property
+ def symbol(self, /) -> LiteralString: ...
+
+ def __init__(
+ self,
+ /,
+ coef: _SeriesLikeCoef_co,
+ domain: _SeriesLikeCoef_co | None = ...,
+ window: _SeriesLikeCoef_co | None = ...,
+ symbol: str = ...,
+ ) -> None: ...
+
+ @overload
+ def __call__(self, /, arg: _Other) -> _Other: ...
+ # TODO: Once `_ShapeT@ndarray` is covariant and bounded (see #26081),
+ # additionally include 0-d arrays as input types with scalar return type.
+ @overload
+ def __call__(
+ self,
+ /,
+ arg: _FloatLike_co | decimal.Decimal | numbers.Real | np.object_,
+ ) -> np.float64 | np.complex128: ...
+ @overload
+ def __call__(
+ self,
+ /,
+ arg: _NumberLike_co | numbers.Complex,
+ ) -> np.complex128: ...
+ @overload
+ def __call__(self, /, arg: _ArrayLikeFloat_co) -> (
+ npt.NDArray[np.float64]
+ | npt.NDArray[np.complex128]
+ | npt.NDArray[np.object_]
+ ): ...
+ @overload
+ def __call__(
+ self,
+ /,
+ arg: _ArrayLikeComplex_co,
+ ) -> npt.NDArray[np.complex128] | npt.NDArray[np.object_]: ...
+ @overload
+ def __call__(
+ self,
+ /,
+ arg: _ArrayLikeCoefObject_co,
+ ) -> npt.NDArray[np.object_]: ...
+
+ def __format__(self, fmt_str: str, /) -> str: ...
+ def __eq__(self, x: object, /) -> bool: ...
+ def __ne__(self, x: object, /) -> bool: ...
+ def __neg__(self, /) -> Self: ...
+ def __pos__(self, /) -> Self: ...
+ def __add__(self, x: _AnyOther, /) -> Self: ...
+ def __sub__(self, x: _AnyOther, /) -> Self: ...
+ def __mul__(self, x: _AnyOther, /) -> Self: ...
+ def __truediv__(self, x: _AnyOther, /) -> Self: ...
+ def __floordiv__(self, x: _AnyOther, /) -> Self: ...
+ def __mod__(self, x: _AnyOther, /) -> Self: ...
+ def __divmod__(self, x: _AnyOther, /) -> _Tuple2[Self]: ...
+ def __pow__(self, x: _AnyOther, /) -> Self: ...
+ def __radd__(self, x: _AnyOther, /) -> Self: ...
+ def __rsub__(self, x: _AnyOther, /) -> Self: ...
+ def __rmul__(self, x: _AnyOther, /) -> Self: ...
+ def __rtruediv__(self, x: _AnyOther, /) -> Self: ...
+ def __rfloordiv__(self, x: _AnyOther, /) -> Self: ...
+ def __rmod__(self, x: _AnyOther, /) -> Self: ...
+ def __rdivmod__(self, x: _AnyOther, /) -> _Tuple2[Self]: ...
+ def __len__(self, /) -> int: ...
+ def __iter__(self, /) -> Iterator[np.inexact | object]: ...
+ def __getstate__(self, /) -> dict[str, Any]: ...
+ def __setstate__(self, dict: dict[str, Any], /) -> None: ...
+
+ def has_samecoef(self, /, other: ABCPolyBase) -> bool: ...
+ def has_samedomain(self, /, other: ABCPolyBase) -> bool: ...
+ def has_samewindow(self, /, other: ABCPolyBase) -> bool: ...
+ @overload
+ def has_sametype(self, /, other: ABCPolyBase) -> TypeIs[Self]: ...
+ @overload
+ def has_sametype(self, /, other: object) -> Literal[False]: ...
+
+ def copy(self, /) -> Self: ...
+ def degree(self, /) -> int: ...
+ def cutdeg(self, /) -> Self: ...
+ def trim(self, /, tol: _FloatLike_co = ...) -> Self: ...
+ def truncate(self, /, size: _AnyInt) -> Self: ...
+
+ @overload
+ def convert(
+ self,
+ /,
+ domain: _SeriesLikeCoef_co | None,
+ kind: type[_Other],
+ window: _SeriesLikeCoef_co | None = ...,
+ ) -> _Other: ...
+ @overload
+ def convert(
+ self,
+ /,
+ domain: _SeriesLikeCoef_co | None = ...,
+ *,
+ kind: type[_Other],
+ window: _SeriesLikeCoef_co | None = ...,
+ ) -> _Other: ...
+ @overload
+ def convert(
+ self,
+ /,
+ domain: _SeriesLikeCoef_co | None = ...,
+ kind: None = None,
+ window: _SeriesLikeCoef_co | None = ...,
+ ) -> Self: ...
+
+ def mapparms(self, /) -> _Tuple2[Any]: ...
+
+ def integ(
+ self,
+ /,
+ m: SupportsIndex = ...,
+ k: _CoefLike_co | _SeriesLikeCoef_co = ...,
+ lbnd: _CoefLike_co | None = ...,
+ ) -> Self: ...
+
+ def deriv(self, /, m: SupportsIndex = ...) -> Self: ...
+
+ def roots(self, /) -> _CoefSeries: ...
+
+ def linspace(
+ self,
+ /,
+ n: SupportsIndex = ...,
+ domain: _SeriesLikeCoef_co | None = ...,
+ ) -> _Tuple2[_Series[np.float64 | np.complex128]]: ...
+
+ @overload
+ @classmethod
+ def fit(
+ cls,
+ x: _SeriesLikeCoef_co,
+ y: _SeriesLikeCoef_co,
+ deg: int | _SeriesLikeInt_co,
+ domain: _SeriesLikeCoef_co | None = ...,
+ rcond: _FloatLike_co = ...,
+ full: Literal[False] = ...,
+ w: _SeriesLikeCoef_co | None = ...,
+ window: _SeriesLikeCoef_co | None = ...,
+ symbol: str = ...,
+ ) -> Self: ...
+ @overload
+ @classmethod
+ def fit(
+ cls,
+ x: _SeriesLikeCoef_co,
+ y: _SeriesLikeCoef_co,
+ deg: int | _SeriesLikeInt_co,
+ domain: _SeriesLikeCoef_co | None = ...,
+ rcond: _FloatLike_co = ...,
+ *,
+ full: Literal[True],
+ w: _SeriesLikeCoef_co | None = ...,
+ window: _SeriesLikeCoef_co | None = ...,
+ symbol: str = ...,
+ ) -> tuple[Self, Sequence[np.inexact | np.int32]]: ...
+ @overload
+ @classmethod
+ def fit(
+ cls,
+ x: _SeriesLikeCoef_co,
+ y: _SeriesLikeCoef_co,
+ deg: int | _SeriesLikeInt_co,
+ domain: _SeriesLikeCoef_co | None,
+ rcond: _FloatLike_co,
+ full: Literal[True], /,
+ w: _SeriesLikeCoef_co | None = ...,
+ window: _SeriesLikeCoef_co | None = ...,
+ symbol: str = ...,
+ ) -> tuple[Self, Sequence[np.inexact | np.int32]]: ...
+
+ @classmethod
+ def fromroots(
+ cls,
+ roots: _ArrayLikeCoef_co,
+ domain: _SeriesLikeCoef_co | None = ...,
+ window: _SeriesLikeCoef_co | None = ...,
+ symbol: str = ...,
+ ) -> Self: ...
+
+ @classmethod
+ def identity(
+ cls,
+ domain: _SeriesLikeCoef_co | None = ...,
+ window: _SeriesLikeCoef_co | None = ...,
+ symbol: str = ...,
+ ) -> Self: ...
+
+ @classmethod
+ def basis(
+ cls,
+ deg: _AnyInt,
+ domain: _SeriesLikeCoef_co | None = ...,
+ window: _SeriesLikeCoef_co | None = ...,
+ symbol: str = ...,
+ ) -> Self: ...
+
+ @classmethod
+ def cast(
+ cls,
+ series: ABCPolyBase,
+ domain: _SeriesLikeCoef_co | None = ...,
+ window: _SeriesLikeCoef_co | None = ...,
+ ) -> Self: ...
+
+ @classmethod
+ def _str_term_unicode(cls, /, i: str, arg_str: str) -> str: ...
+ @staticmethod
+ def _str_term_ascii(i: str, arg_str: str) -> str: ...
+ @staticmethod
+ def _repr_latex_term(i: str, arg_str: str, needs_parens: bool) -> str: ...