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