xhs-note-crawling/python/py/Lib/site-packages/numpy/polynomial/polyutils.pyi

from collections.abc import Callable, Iterable, Sequence
from typing import (
    Final,
    Literal,
    Protocol,
    SupportsIndex,
    TypeAlias,
    TypeVar,
    overload,
    type_check_only,
)

import numpy as np
import numpy.typing as npt
from numpy._typing import (
    _ArrayLikeComplex_co,
    _ArrayLikeFloat_co,
    _ArrayLikeObject_co,
    _FloatLike_co,
    _NumberLike_co,
)

from ._polytypes import (
    _AnyInt,
    _Array2,
    _ArrayLikeCoef_co,
    _CoefArray,
    _CoefLike_co,
    _CoefSeries,
    _ComplexArray,
    _ComplexSeries,
    _FloatArray,
    _FloatSeries,
    _FuncBinOp,
    _ObjectArray,
    _ObjectSeries,
    _SeriesLikeCoef_co,
    _SeriesLikeComplex_co,
    _SeriesLikeFloat_co,
    _SeriesLikeInt_co,
    _SeriesLikeObject_co,
    _Tuple2,
)

__all__ = ["as_series", "format_float", "getdomain", "mapdomain", "mapparms", "trimcoef", "trimseq"]

_T = TypeVar("_T")
_SeqT = TypeVar("_SeqT", bound=_CoefArray | Sequence[_CoefLike_co])

_AnyLineF: TypeAlias = Callable[[float, float], _CoefArray]
_AnyMulF: TypeAlias = Callable[[np.ndarray | list[int], np.ndarray], _CoefArray]
_AnyVanderF: TypeAlias = Callable[[np.ndarray, int], _CoefArray]

@type_check_only
class _ValFunc(Protocol[_T]):
    def __call__(self, x: np.ndarray, c: _T, /, *, tensor: bool = True) -> _T: ...

###

@overload
def as_series(alist: npt.NDArray[np.integer] | _FloatArray, trim: bool = True) -> list[_FloatSeries]: ...
@overload
def as_series(alist: _ComplexArray, trim: bool = True) -> list[_ComplexSeries]: ...
@overload
def as_series(alist: _ObjectArray, trim: bool = True) -> list[_ObjectSeries]: ...
@overload
def as_series(alist: Iterable[_FloatArray | npt.NDArray[np.integer]], trim: bool = True) -> list[_FloatSeries]: ...
@overload
def as_series(alist: Iterable[_ComplexArray], trim: bool = True) -> list[_ComplexSeries]: ...
@overload
def as_series(alist: Iterable[_ObjectArray], trim: bool = True) -> list[_ObjectSeries]: ...
@overload
def as_series(alist: Iterable[_SeriesLikeFloat_co | float], trim: bool = True) -> list[_FloatSeries]: ...
@overload
def as_series(alist: Iterable[_SeriesLikeComplex_co | complex], trim: bool = True) -> list[_ComplexSeries]: ...
@overload
def as_series(alist: Iterable[_SeriesLikeCoef_co | object], trim: bool = True) -> list[_ObjectSeries]: ...

#
def trimseq(seq: _SeqT) -> _SeqT: ...

#
@overload
def trimcoef(c: npt.NDArray[np.integer] | _FloatArray, tol: _FloatLike_co = 0) -> _FloatSeries: ...
@overload
def trimcoef(c: _ComplexArray, tol: _FloatLike_co = 0) -> _ComplexSeries: ...
@overload
def trimcoef(c: _ObjectArray, tol: _FloatLike_co = 0) -> _ObjectSeries: ...
@overload
def trimcoef(c: _SeriesLikeFloat_co | float, tol: _FloatLike_co = 0) -> _FloatSeries: ...
@overload
def trimcoef(c: _SeriesLikeComplex_co | complex, tol: _FloatLike_co = 0) -> _ComplexSeries: ...
@overload
def trimcoef(c: _SeriesLikeCoef_co | object, tol: _FloatLike_co = 0) -> _ObjectSeries: ...

#
@overload
def getdomain(x: _FloatArray | npt.NDArray[np.integer]) -> _Array2[np.float64]: ...
@overload
def getdomain(x: _ComplexArray) -> _Array2[np.complex128]: ...
@overload
def getdomain(x: _ObjectArray) -> _Array2[np.object_]: ...
@overload
def getdomain(x: _SeriesLikeFloat_co | float) -> _Array2[np.float64]: ...
@overload
def getdomain(x: _SeriesLikeComplex_co | complex) -> _Array2[np.complex128]: ...
@overload
def getdomain(x: _SeriesLikeCoef_co | object) -> _Array2[np.object_]: ...

#
@overload
def mapparms(old: npt.NDArray[np.floating | np.integer], new: npt.NDArray[np.floating | np.integer]) -> _Tuple2[np.floating]: ...
@overload
def mapparms(old: npt.NDArray[np.number], new: npt.NDArray[np.number]) -> _Tuple2[np.complexfloating]: ...
@overload
def mapparms(old: npt.NDArray[np.object_ | np.number], new: npt.NDArray[np.object_ | np.number]) -> _Tuple2[object]: ...
@overload
def mapparms(old: Sequence[float], new: Sequence[float]) -> _Tuple2[float]: ...
@overload
def mapparms(old: Sequence[complex], new: Sequence[complex]) -> _Tuple2[complex]: ...
@overload
def mapparms(old: _SeriesLikeFloat_co, new: _SeriesLikeFloat_co) -> _Tuple2[np.floating]: ...
@overload
def mapparms(old: _SeriesLikeComplex_co, new: _SeriesLikeComplex_co) -> _Tuple2[np.complexfloating]: ...
@overload
def mapparms(old: _SeriesLikeCoef_co, new: _SeriesLikeCoef_co) -> _Tuple2[object]: ...

#
@overload
def mapdomain(x: _FloatLike_co, old: _SeriesLikeFloat_co, new: _SeriesLikeFloat_co) -> np.floating: ...
@overload
def mapdomain(x: _NumberLike_co, old: _SeriesLikeComplex_co, new: _SeriesLikeComplex_co) -> np.complexfloating: ...
@overload
def mapdomain(
    x: npt.NDArray[np.floating | np.integer],
    old: npt.NDArray[np.floating | np.integer],
    new: npt.NDArray[np.floating | np.integer],
) -> _FloatSeries: ...
@overload
def mapdomain(x: npt.NDArray[np.number], old: npt.NDArray[np.number], new: npt.NDArray[np.number]) -> _ComplexSeries: ...
@overload
def mapdomain(
    x: npt.NDArray[np.object_ | np.number],
    old: npt.NDArray[np.object_ | np.number],
    new: npt.NDArray[np.object_ | np.number],
) -> _ObjectSeries: ...
@overload
def mapdomain(x: _SeriesLikeFloat_co, old: _SeriesLikeFloat_co, new: _SeriesLikeFloat_co) -> _FloatSeries: ...
@overload
def mapdomain(x: _SeriesLikeComplex_co, old: _SeriesLikeComplex_co, new: _SeriesLikeComplex_co) -> _ComplexSeries: ...
@overload
def mapdomain(x: _SeriesLikeCoef_co, old: _SeriesLikeCoef_co, new: _SeriesLikeCoef_co) -> _ObjectSeries: ...
@overload
def mapdomain(x: _CoefLike_co, old: _SeriesLikeCoef_co, new: _SeriesLikeCoef_co) -> object: ...

#
def _nth_slice(i: SupportsIndex, ndim: SupportsIndex) -> tuple[slice | None, ...]: ...

# keep in sync with `vander_nd_flat`
@overload
def _vander_nd(
    vander_fs: Sequence[_AnyVanderF],
    points: Sequence[_ArrayLikeFloat_co],
    degrees: Sequence[SupportsIndex],
) -> _FloatArray: ...
@overload
def _vander_nd(
    vander_fs: Sequence[_AnyVanderF],
    points: Sequence[_ArrayLikeComplex_co],
    degrees: Sequence[SupportsIndex],
) -> _ComplexArray: ...
@overload
def _vander_nd(
    vander_fs: Sequence[_AnyVanderF],
    points: Sequence[_ArrayLikeObject_co | _ArrayLikeComplex_co],
    degrees: Sequence[SupportsIndex],
) -> _ObjectArray: ...
@overload
def _vander_nd(
    vander_fs: Sequence[_AnyVanderF],
    points: Sequence[npt.ArrayLike],
    degrees: Sequence[SupportsIndex],
) -> _CoefArray: ...

# keep in sync with `vander_nd`
@overload
def _vander_nd_flat(
    vander_fs: Sequence[_AnyVanderF],
    points: Sequence[_ArrayLikeFloat_co],
    degrees: Sequence[SupportsIndex],
) -> _FloatArray: ...
@overload
def _vander_nd_flat(
    vander_fs: Sequence[_AnyVanderF],
    points: Sequence[_ArrayLikeComplex_co],
    degrees: Sequence[SupportsIndex],
) -> _ComplexArray: ...
@overload
def _vander_nd_flat(
    vander_fs: Sequence[_AnyVanderF],
    points: Sequence[_ArrayLikeObject_co | _ArrayLikeComplex_co],
    degrees: Sequence[SupportsIndex],
) -> _ObjectArray: ...
@overload
def _vander_nd_flat(
    vander_fs: Sequence[_AnyVanderF],
    points: Sequence[npt.ArrayLike],
    degrees: Sequence[SupportsIndex],
) -> _CoefArray: ...

# keep in sync with `._polytypes._FuncFromRoots`
@overload
def _fromroots(line_f: _AnyLineF, mul_f: _AnyMulF, roots: _SeriesLikeFloat_co) -> _FloatSeries: ...
@overload
def _fromroots(line_f: _AnyLineF, mul_f: _AnyMulF, roots: _SeriesLikeComplex_co) -> _ComplexSeries: ...
@overload
def _fromroots(line_f: _AnyLineF, mul_f: _AnyMulF, roots: _SeriesLikeObject_co) -> _ObjectSeries: ...
@overload
def _fromroots(line_f: _AnyLineF, mul_f: _AnyMulF, roots: _SeriesLikeCoef_co) -> _CoefSeries: ...

# keep in sync with `_gridnd`
def _valnd(val_f: _ValFunc[_T], c: _T, *args: npt.ArrayLike) -> _T: ...

# keep in sync with `_valnd`
def _gridnd(val_f: _ValFunc[_T], c: _T, *args: npt.ArrayLike) -> _T: ...

# keep in sync with `_polytypes._FuncBinOp`
@overload
def _div(mul_f: _AnyMulF, c1: _SeriesLikeFloat_co, c2: _SeriesLikeFloat_co) -> _Tuple2[_FloatSeries]: ...
@overload
def _div(mul_f: _AnyMulF, c1: _SeriesLikeComplex_co, c2: _SeriesLikeComplex_co) -> _Tuple2[_ComplexSeries]: ...
@overload
def _div(mul_f: _AnyMulF, c1: _SeriesLikeObject_co, c2: _SeriesLikeObject_co) -> _Tuple2[_ObjectSeries]: ...
@overload
def _div(mul_f: _AnyMulF, c1: _SeriesLikeCoef_co, c2: _SeriesLikeCoef_co) -> _Tuple2[_CoefSeries]: ...

_add: Final[_FuncBinOp] = ...
_sub: Final[_FuncBinOp] = ...

# keep in sync with `_polytypes._FuncPow`
@overload
def _pow(mul_f: _AnyMulF, c: _SeriesLikeFloat_co, pow: _AnyInt, maxpower: _AnyInt | None) -> _FloatSeries: ...
@overload
def _pow(mul_f: _AnyMulF, c: _SeriesLikeComplex_co, pow: _AnyInt, maxpower: _AnyInt | None) -> _ComplexSeries: ...
@overload
def _pow(mul_f: _AnyMulF, c: _SeriesLikeObject_co, pow: _AnyInt, maxpower: _AnyInt | None) -> _ObjectSeries: ...
@overload
def _pow(mul_f: _AnyMulF, c: _SeriesLikeCoef_co, pow: _AnyInt, maxpower: _AnyInt | None) -> _CoefSeries: ...

# keep in sync with `_polytypes._FuncFit`
@overload
def _fit(
    vander_f: _AnyVanderF,
    x: _SeriesLikeFloat_co,
    y: _ArrayLikeFloat_co,
    deg: _SeriesLikeInt_co,
    rcond: _FloatLike_co | None = None,
    full: Literal[False] = False,
    w: _SeriesLikeFloat_co | None = None,
) -> _FloatArray: ...
@overload
def _fit(
    vander_f: _AnyVanderF,
    x: _SeriesLikeComplex_co,
    y: _ArrayLikeComplex_co,
    deg: _SeriesLikeInt_co,
    rcond: _FloatLike_co | None = None,
    full: Literal[False] = False,
    w: _SeriesLikeComplex_co | None = None,
) -> _ComplexArray: ...
@overload
def _fit(
    vander_f: _AnyVanderF,
    x: _SeriesLikeCoef_co,
    y: _ArrayLikeCoef_co,
    deg: _SeriesLikeInt_co,
    rcond: _FloatLike_co | None = None,
    full: Literal[False] = False,
    w: _SeriesLikeCoef_co | None = None,
) -> _CoefArray: ...
@overload
def _fit(
    vander_f: _AnyVanderF,
    x: _SeriesLikeCoef_co,
    y: _SeriesLikeCoef_co,
    deg: _SeriesLikeInt_co,
    rcond: _FloatLike_co | None,
    full: Literal[True],
    w: _SeriesLikeCoef_co | None = None,
) -> tuple[_CoefSeries, Sequence[np.inexact | np.int32]]: ...
@overload
def _fit(
    vander_f: _AnyVanderF,
    x: _SeriesLikeCoef_co,
    y: _SeriesLikeCoef_co,
    deg: _SeriesLikeInt_co,
    rcond: _FloatLike_co | None = None,
    *,
    full: Literal[True],
    w: _SeriesLikeCoef_co | None = None,
) -> tuple[_CoefSeries, Sequence[np.inexact | np.int32]]: ...

#
def _as_int(x: SupportsIndex, desc: str) -> int: ...

#
def format_float(x: _FloatLike_co, parens: bool = False) -> str: ...