| | 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, IntervalClosedType]: ... |
| |
|
| | 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: ... |
| |
|