from typing import Any import numpy as np from pandas._typing import npt class Infinity: """ Provide a positive Infinity comparison method for ranking. """ def __eq__(self, other) -> bool: ... def __ne__(self, other) -> bool: ... def __lt__(self, other) -> bool: ... def __le__(self, other) -> bool: ... def __gt__(self, other) -> bool: ... def __ge__(self, other) -> bool: ... class NegInfinity: """ Provide a negative Infinity comparison method for ranking. """ def __eq__(self, other) -> bool: ... def __ne__(self, other) -> bool: ... def __lt__(self, other) -> bool: ... def __le__(self, other) -> bool: ... def __gt__(self, other) -> bool: ... def __ge__(self, other) -> bool: ... def unique_deltas( arr: np.ndarray, # const int64_t[:] ) -> np.ndarray: ... # np.ndarray[np.int64, ndim=1] def is_lexsorted(list_of_arrays: list[npt.NDArray[np.int64]]) -> bool: ... def groupsort_indexer( index: np.ndarray, # const int64_t[:] ngroups: int, ) -> tuple[ np.ndarray, # ndarray[int64_t, ndim=1] np.ndarray, # ndarray[int64_t, ndim=1] ]: ... def kth_smallest( arr: np.ndarray, # numeric[:] k: int, ) -> Any: ... # numeric # ---------------------------------------------------------------------- # Pairwise correlation/covariance def nancorr( mat: npt.NDArray[np.float64], # const float64_t[:, :] cov: bool = ..., minp: int | None = ..., ) -> npt.NDArray[np.float64]: ... # ndarray[float64_t, ndim=2] def nancorr_spearman( mat: npt.NDArray[np.float64], # ndarray[float64_t, ndim=2] minp: int = ..., ) -> npt.NDArray[np.float64]: ... # ndarray[float64_t, ndim=2] # ---------------------------------------------------------------------- def validate_limit(nobs: int | None, limit=...) -> int: ... def pad( old: np.ndarray, # ndarray[numeric_object_t] new: np.ndarray, # ndarray[numeric_object_t] limit=..., ) -> npt.NDArray[np.intp]: ... # np.ndarray[np.intp, ndim=1] def pad_inplace( values: np.ndarray, # numeric_object_t[:] mask: np.ndarray, # uint8_t[:] limit=..., ) -> None: ... def pad_2d_inplace( values: np.ndarray, # numeric_object_t[:, :] mask: np.ndarray, # const uint8_t[:, :] limit=..., ) -> None: ... def backfill( old: np.ndarray, # ndarray[numeric_object_t] new: np.ndarray, # ndarray[numeric_object_t] limit=..., ) -> npt.NDArray[np.intp]: ... # np.ndarray[np.intp, ndim=1] def backfill_inplace( values: np.ndarray, # numeric_object_t[:] mask: np.ndarray, # uint8_t[:] limit=..., ) -> None: ... def backfill_2d_inplace( values: np.ndarray, # numeric_object_t[:, :] mask: np.ndarray, # const uint8_t[:, :] limit=..., ) -> None: ... def is_monotonic( arr: np.ndarray, # ndarray[numeric_object_t, ndim=1] timelike: bool, ) -> tuple[bool, bool, bool]: ... # ---------------------------------------------------------------------- # rank_1d, rank_2d # ---------------------------------------------------------------------- def rank_1d( values: np.ndarray, # ndarray[numeric_object_t, ndim=1] labels: np.ndarray | None = ..., # const int64_t[:]=None is_datetimelike: bool = ..., ties_method=..., ascending: bool = ..., pct: bool = ..., na_option=..., mask: npt.NDArray[np.bool_] | None = ..., ) -> np.ndarray: ... # np.ndarray[float64_t, ndim=1] def rank_2d( in_arr: np.ndarray, # ndarray[numeric_object_t, ndim=2] axis: int = ..., is_datetimelike: bool = ..., ties_method=..., ascending: bool = ..., na_option=..., pct: bool = ..., ) -> np.ndarray: ... # np.ndarray[float64_t, ndim=1] def diff_2d( arr: np.ndarray, # ndarray[diff_t, ndim=2] out: np.ndarray, # ndarray[out_t, ndim=2] periods: int, axis: int, datetimelike: bool = ..., ) -> None: ... def ensure_platform_int(arr: object) -> npt.NDArray[np.intp]: ... def ensure_object(arr: object) -> npt.NDArray[np.object_]: ... def ensure_float64(arr: object, copy=...) -> npt.NDArray[np.float64]: ... def ensure_int8(arr: object, copy=...) -> npt.NDArray[np.int8]: ... def ensure_int16(arr: object, copy=...) -> npt.NDArray[np.int16]: ... def ensure_int32(arr: object, copy=...) -> npt.NDArray[np.int32]: ... def ensure_int64(arr: object, copy=...) -> npt.NDArray[np.int64]: ... def ensure_uint64(arr: object, copy=...) -> npt.NDArray[np.uint64]: ... def take_1d_int8_int8( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_int8_int32( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_int8_int64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_int8_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_int16_int16( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_int16_int32( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_int16_int64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_int16_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_int32_int32( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_int32_int64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_int32_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_int64_int64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_int64_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_float32_float32( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_float32_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_float64_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_object_object( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_bool_bool( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_1d_bool_object( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_int8_int8( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_int8_int32( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_int8_int64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_int8_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_int16_int16( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_int16_int32( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_int16_int64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_int16_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_int32_int32( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_int32_int64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_int32_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_int64_int64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_int64_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_float32_float32( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_float32_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_float64_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_object_object( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_bool_bool( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis0_bool_object( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_int8_int8( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_int8_int32( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_int8_int64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_int8_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_int16_int16( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_int16_int32( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_int16_int64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_int16_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_int32_int32( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_int32_int64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_int32_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_int64_int64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_int64_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_float32_float32( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_float32_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_float64_float64( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_object_object( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_bool_bool( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_axis1_bool_object( values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=... ) -> None: ... def take_2d_multi_int8_int8( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_int8_int32( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_int8_int64( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_int8_float64( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_int16_int16( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_int16_int32( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_int16_int64( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_int16_float64( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_int32_int32( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_int32_int64( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_int32_float64( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_int64_float64( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_float32_float32( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_float32_float64( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_float64_float64( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_object_object( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_bool_bool( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_bool_object( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ... def take_2d_multi_int64_int64( values: np.ndarray, indexer: tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]], out: np.ndarray, fill_value=..., ) -> None: ...