Inzynierka/Lib/site-packages/pandas/_libs/interval.pyi

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2023-06-02 12:51:02 +02:00
from typing import (
Any,
Generic,
TypeVar,
overload,
)
import numpy as np
import numpy.typing as npt
from pandas._typing import (
IntervalClosedType,
Timedelta,
Timestamp,
)
VALID_CLOSED: frozenset[str]
_OrderableScalarT = TypeVar("_OrderableScalarT", int, float)
_OrderableTimesT = TypeVar("_OrderableTimesT", Timestamp, Timedelta)
_OrderableT = TypeVar("_OrderableT", int, float, Timestamp, Timedelta)
class _LengthDescriptor:
@overload
def __get__(
self, instance: Interval[_OrderableScalarT], owner: Any
) -> _OrderableScalarT: ...
@overload
def __get__(
self, instance: Interval[_OrderableTimesT], owner: Any
) -> Timedelta: ...
class _MidDescriptor:
@overload
def __get__(self, instance: Interval[_OrderableScalarT], owner: Any) -> float: ...
@overload
def __get__(
self, instance: Interval[_OrderableTimesT], owner: Any
) -> _OrderableTimesT: ...
class IntervalMixin:
@property
def closed_left(self) -> bool: ...
@property
def closed_right(self) -> bool: ...
@property
def open_left(self) -> bool: ...
@property
def open_right(self) -> bool: ...
@property
def is_empty(self) -> bool: ...
def _check_closed_matches(self, other: IntervalMixin, name: str = ...) -> None: ...
class Interval(IntervalMixin, Generic[_OrderableT]):
@property
def left(self: Interval[_OrderableT]) -> _OrderableT: ...
@property
def right(self: Interval[_OrderableT]) -> _OrderableT: ...
@property
def closed(self) -> IntervalClosedType: ...
mid: _MidDescriptor
length: _LengthDescriptor
def __init__(
self,
left: _OrderableT,
right: _OrderableT,
closed: IntervalClosedType = ...,
) -> None: ...
def __hash__(self) -> int: ...
@overload
def __contains__(
self: Interval[Timedelta], key: Timedelta | Interval[Timedelta]
) -> bool: ...
@overload
def __contains__(
self: Interval[Timestamp], key: Timestamp | Interval[Timestamp]
) -> bool: ...
@overload
def __contains__(
self: Interval[_OrderableScalarT],
key: _OrderableScalarT | Interval[_OrderableScalarT],
) -> bool: ...
@overload
def __add__(
self: Interval[_OrderableTimesT], y: Timedelta
) -> Interval[_OrderableTimesT]: ...
@overload
def __add__(
self: Interval[int], y: _OrderableScalarT
) -> Interval[_OrderableScalarT]: ...
@overload
def __add__(self: Interval[float], y: float) -> Interval[float]: ...
@overload
def __radd__(
self: Interval[_OrderableTimesT], y: Timedelta
) -> Interval[_OrderableTimesT]: ...
@overload
def __radd__(
self: Interval[int], y: _OrderableScalarT
) -> Interval[_OrderableScalarT]: ...
@overload
def __radd__(self: Interval[float], y: float) -> Interval[float]: ...
@overload
def __sub__(
self: Interval[_OrderableTimesT], y: Timedelta
) -> Interval[_OrderableTimesT]: ...
@overload
def __sub__(
self: Interval[int], y: _OrderableScalarT
) -> Interval[_OrderableScalarT]: ...
@overload
def __sub__(self: Interval[float], y: float) -> Interval[float]: ...
@overload
def __rsub__(
self: Interval[_OrderableTimesT], y: Timedelta
) -> Interval[_OrderableTimesT]: ...
@overload
def __rsub__(
self: Interval[int], y: _OrderableScalarT
) -> Interval[_OrderableScalarT]: ...
@overload
def __rsub__(self: Interval[float], y: float) -> Interval[float]: ...
@overload
def __mul__(
self: Interval[int], y: _OrderableScalarT
) -> Interval[_OrderableScalarT]: ...
@overload
def __mul__(self: Interval[float], y: float) -> Interval[float]: ...
@overload
def __rmul__(
self: Interval[int], y: _OrderableScalarT
) -> Interval[_OrderableScalarT]: ...
@overload
def __rmul__(self: Interval[float], y: float) -> Interval[float]: ...
@overload
def __truediv__(
self: Interval[int], y: _OrderableScalarT
) -> Interval[_OrderableScalarT]: ...
@overload
def __truediv__(self: Interval[float], y: float) -> Interval[float]: ...
@overload
def __floordiv__(
self: Interval[int], y: _OrderableScalarT
) -> Interval[_OrderableScalarT]: ...
@overload
def __floordiv__(self: Interval[float], y: float) -> Interval[float]: ...
def overlaps(self: Interval[_OrderableT], other: Interval[_OrderableT]) -> bool: ...
def intervals_to_interval_bounds(
intervals: np.ndarray, validate_closed: bool = ...
) -> tuple[np.ndarray, np.ndarray, str]: ...
class IntervalTree(IntervalMixin):
def __init__(
self,
left: np.ndarray,
right: np.ndarray,
closed: IntervalClosedType = ...,
leaf_size: int = ...,
) -> None: ...
@property
def mid(self) -> np.ndarray: ...
@property
def length(self) -> np.ndarray: ...
def get_indexer(self, target) -> npt.NDArray[np.intp]: ...
def get_indexer_non_unique(
self, target
) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
_na_count: int
@property
def is_overlapping(self) -> bool: ...
@property
def is_monotonic_increasing(self) -> bool: ...
def clear_mapping(self) -> None: ...