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