# Python: 3.9.2 (tags/v3.9.2:1a79785, Feb 19 2021, 13:44:55) [MSC v.1928 64 bit (AMD64)] # Library: pandas, version: 1.2.4 # Module: pandas._libs.interval, version: unspecified import typing import builtins as _mod_builtins class Float64ClosedBothIntervalNode(_mod_builtins.object): 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' def __init__(self, *args, **kwargs) -> None: 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... __pyx_vtable__: PyCapsule def __reduce__(self) -> typing.Union[str, typing.Tuple[typing.Any, ...]]: ... def __repr__(self) -> str: 'Return repr(self).' ... def __setstate__(self, state: typing.Any) -> None: ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... @property def center_left_indices(self) -> typing.Any: ... @property def center_left_values(self) -> typing.Any: ... @property def center_right_indices(self) -> typing.Any: ... @property def center_right_values(self) -> typing.Any: ... def counts(self) -> typing.Any: '\n Inspect counts on this node\n useful for debugging purposes\n ' ... @property def indices(self) -> typing.Any: ... @property def is_leaf_node(self) -> typing.Any: ... @property def leaf_size(self) -> typing.Any: ... @property def left(self) -> typing.Any: ... @property def left_node(self) -> typing.Any: ... @property def max_right(self) -> typing.Any: ... @property def min_left(self) -> typing.Any: ... @property def n_center(self) -> typing.Any: ... @property def n_elements(self) -> typing.Any: ... @property def pivot(self) -> typing.Any: ... def query(self, result, point) -> typing.Any: 'Recursively query this node and its sub-nodes for intervals that\n overlap with the query point.\n ' ... @property def right(self) -> typing.Any: ... @property def right_node(self) -> typing.Any: ... def __getattr__(self, name) -> typing.Any: ... class Float64ClosedLeftIntervalNode(_mod_builtins.object): 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' def __init__(self, *args, **kwargs) -> None: 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... __pyx_vtable__: PyCapsule def __reduce__(self) -> typing.Union[str, typing.Tuple[typing.Any, ...]]: ... def __repr__(self) -> str: 'Return repr(self).' ... def __setstate__(self, state: typing.Any) -> None: ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... @property def center_left_indices(self) -> typing.Any: ... @property def center_left_values(self) -> typing.Any: ... @property def center_right_indices(self) -> typing.Any: ... @property def center_right_values(self) -> typing.Any: ... def counts(self) -> typing.Any: '\n Inspect counts on this node\n useful for debugging purposes\n ' ... @property def indices(self) -> typing.Any: ... @property def is_leaf_node(self) -> typing.Any: ... @property def leaf_size(self) -> typing.Any: ... @property def left(self) -> typing.Any: ... @property def left_node(self) -> typing.Any: ... @property def max_right(self) -> typing.Any: ... @property def min_left(self) -> typing.Any: ... @property def n_center(self) -> typing.Any: ... @property def n_elements(self) -> typing.Any: ... @property def pivot(self) -> typing.Any: ... def query(self, result, point) -> typing.Any: 'Recursively query this node and its sub-nodes for intervals that\n overlap with the query point.\n ' ... @property def right(self) -> typing.Any: ... @property def right_node(self) -> typing.Any: ... def __getattr__(self, name) -> typing.Any: ... class Float64ClosedNeitherIntervalNode(_mod_builtins.object): 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' def __init__(self, *args, **kwargs) -> None: 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... __pyx_vtable__: PyCapsule def __reduce__(self) -> typing.Union[str, typing.Tuple[typing.Any, ...]]: ... def __repr__(self) -> str: 'Return repr(self).' ... def __setstate__(self, state: typing.Any) -> None: ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... @property def center_left_indices(self) -> typing.Any: ... @property def center_left_values(self) -> typing.Any: ... @property def center_right_indices(self) -> typing.Any: ... @property def center_right_values(self) -> typing.Any: ... def counts(self) -> typing.Any: '\n Inspect counts on this node\n useful for debugging purposes\n ' ... @property def indices(self) -> typing.Any: ... @property def is_leaf_node(self) -> typing.Any: ... @property def leaf_size(self) -> typing.Any: ... @property def left(self) -> typing.Any: ... @property def left_node(self) -> typing.Any: ... @property def max_right(self) -> typing.Any: ... @property def min_left(self) -> typing.Any: ... @property def n_center(self) -> typing.Any: ... @property def n_elements(self) -> typing.Any: ... @property def pivot(self) -> typing.Any: ... def query(self, result, point) -> typing.Any: 'Recursively query this node and its sub-nodes for intervals that\n overlap with the query point.\n ' ... @property def right(self) -> typing.Any: ... @property def right_node(self) -> typing.Any: ... def __getattr__(self, name) -> typing.Any: ... class Float64ClosedRightIntervalNode(_mod_builtins.object): 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' def __init__(self, *args, **kwargs) -> None: 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... __pyx_vtable__: PyCapsule def __reduce__(self) -> typing.Union[str, typing.Tuple[typing.Any, ...]]: ... def __repr__(self) -> str: 'Return repr(self).' ... def __setstate__(self, state: typing.Any) -> None: ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... @property def center_left_indices(self) -> typing.Any: ... @property def center_left_values(self) -> typing.Any: ... @property def center_right_indices(self) -> typing.Any: ... @property def center_right_values(self) -> typing.Any: ... def counts(self) -> typing.Any: '\n Inspect counts on this node\n useful for debugging purposes\n ' ... @property def indices(self) -> typing.Any: ... @property def is_leaf_node(self) -> typing.Any: ... @property def leaf_size(self) -> typing.Any: ... @property def left(self) -> typing.Any: ... @property def left_node(self) -> typing.Any: ... @property def max_right(self) -> typing.Any: ... @property def min_left(self) -> typing.Any: ... @property def n_center(self) -> typing.Any: ... @property def n_elements(self) -> typing.Any: ... @property def pivot(self) -> typing.Any: ... def query(self, result, point) -> typing.Any: 'Recursively query this node and its sub-nodes for intervals that\n overlap with the query point.\n ' ... @property def right(self) -> typing.Any: ... @property def right_node(self) -> typing.Any: ... def __getattr__(self, name) -> typing.Any: ... class Int64ClosedBothIntervalNode(_mod_builtins.object): 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' def __init__(self, *args, **kwargs) -> None: 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... __pyx_vtable__: PyCapsule def __reduce__(self) -> typing.Union[str, typing.Tuple[typing.Any, ...]]: ... def __repr__(self) -> str: 'Return repr(self).' ... def __setstate__(self, state: typing.Any) -> None: ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... @property def center_left_indices(self) -> typing.Any: ... @property def center_left_values(self) -> typing.Any: ... @property def center_right_indices(self) -> typing.Any: ... @property def center_right_values(self) -> typing.Any: ... def counts(self) -> typing.Any: '\n Inspect counts on this node\n useful for debugging purposes\n ' ... @property def indices(self) -> typing.Any: ... @property def is_leaf_node(self) -> typing.Any: ... @property def leaf_size(self) -> typing.Any: ... @property def left(self) -> typing.Any: ... @property def left_node(self) -> typing.Any: ... @property def max_right(self) -> typing.Any: ... @property def min_left(self) -> typing.Any: ... @property def n_center(self) -> typing.Any: ... @property def n_elements(self) -> typing.Any: ... @property def pivot(self) -> typing.Any: ... def query(self, result, point) -> typing.Any: 'Recursively query this node and its sub-nodes for intervals that\n overlap with the query point.\n ' ... @property def right(self) -> typing.Any: ... @property def right_node(self) -> typing.Any: ... def __getattr__(self, name) -> typing.Any: ... class Int64ClosedLeftIntervalNode(_mod_builtins.object): 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' def __init__(self, *args, **kwargs) -> None: 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... __pyx_vtable__: PyCapsule def __reduce__(self) -> typing.Union[str, typing.Tuple[typing.Any, ...]]: ... def __repr__(self) -> str: 'Return repr(self).' ... def __setstate__(self, state: typing.Any) -> None: ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... @property def center_left_indices(self) -> typing.Any: ... @property def center_left_values(self) -> typing.Any: ... @property def center_right_indices(self) -> typing.Any: ... @property def center_right_values(self) -> typing.Any: ... def counts(self) -> typing.Any: '\n Inspect counts on this node\n useful for debugging purposes\n ' ... @property def indices(self) -> typing.Any: ... @property def is_leaf_node(self) -> typing.Any: ... @property def leaf_size(self) -> typing.Any: ... @property def left(self) -> typing.Any: ... @property def left_node(self) -> typing.Any: ... @property def max_right(self) -> typing.Any: ... @property def min_left(self) -> typing.Any: ... @property def n_center(self) -> typing.Any: ... @property def n_elements(self) -> typing.Any: ... @property def pivot(self) -> typing.Any: ... def query(self, result, point) -> typing.Any: 'Recursively query this node and its sub-nodes for intervals that\n overlap with the query point.\n ' ... @property def right(self) -> typing.Any: ... @property def right_node(self) -> typing.Any: ... def __getattr__(self, name) -> typing.Any: ... class Int64ClosedNeitherIntervalNode(_mod_builtins.object): 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' def __init__(self, *args, **kwargs) -> None: 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... __pyx_vtable__: PyCapsule def __reduce__(self) -> typing.Union[str, typing.Tuple[typing.Any, ...]]: ... def __repr__(self) -> str: 'Return repr(self).' ... def __setstate__(self, state: typing.Any) -> None: ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... @property def center_left_indices(self) -> typing.Any: ... @property def center_left_values(self) -> typing.Any: ... @property def center_right_indices(self) -> typing.Any: ... @property def center_right_values(self) -> typing.Any: ... def counts(self) -> typing.Any: '\n Inspect counts on this node\n useful for debugging purposes\n ' ... @property def indices(self) -> typing.Any: ... @property def is_leaf_node(self) -> typing.Any: ... @property def leaf_size(self) -> typing.Any: ... @property def left(self) -> typing.Any: ... @property def left_node(self) -> typing.Any: ... @property def max_right(self) -> typing.Any: ... @property def min_left(self) -> typing.Any: ... @property def n_center(self) -> typing.Any: ... @property def n_elements(self) -> typing.Any: ... @property def pivot(self) -> typing.Any: ... def query(self, result, point) -> typing.Any: 'Recursively query this node and its sub-nodes for intervals that\n overlap with the query point.\n ' ... @property def right(self) -> typing.Any: ... @property def right_node(self) -> typing.Any: ... def __getattr__(self, name) -> typing.Any: ... class Int64ClosedRightIntervalNode(_mod_builtins.object): 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' def __init__(self, *args, **kwargs) -> None: 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... __pyx_vtable__: PyCapsule def __reduce__(self) -> typing.Union[str, typing.Tuple[typing.Any, ...]]: ... def __repr__(self) -> str: 'Return repr(self).' ... def __setstate__(self, state: typing.Any) -> None: ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... @property def center_left_indices(self) -> typing.Any: ... @property def center_left_values(self) -> typing.Any: ... @property def center_right_indices(self) -> typing.Any: ... @property def center_right_values(self) -> typing.Any: ... def counts(self) -> typing.Any: '\n Inspect counts on this node\n useful for debugging purposes\n ' ... @property def indices(self) -> typing.Any: ... @property def is_leaf_node(self) -> typing.Any: ... @property def leaf_size(self) -> typing.Any: ... @property def left(self) -> typing.Any: ... @property def left_node(self) -> typing.Any: ... @property def max_right(self) -> typing.Any: ... @property def min_left(self) -> typing.Any: ... @property def n_center(self) -> typing.Any: ... @property def n_elements(self) -> typing.Any: ... @property def pivot(self) -> typing.Any: ... def query(self, result, point) -> typing.Any: 'Recursively query this node and its sub-nodes for intervals that\n overlap with the query point.\n ' ... @property def right(self) -> typing.Any: ... @property def right_node(self) -> typing.Any: ... def __getattr__(self, name) -> typing.Any: ... class Interval(IntervalMixin): "\n Immutable object implementing an Interval, a bounded slice-like interval.\n\n Parameters\n ----------\n left : orderable scalar\n Left bound for the interval.\n right : orderable scalar\n Right bound for the interval.\n closed : {'right', 'left', 'both', 'neither'}, default 'right'\n Whether the interval is closed on the left-side, right-side, both or\n neither. See the Notes for more detailed explanation.\n\n See Also\n --------\n IntervalIndex : An Index of Interval objects that are all closed on the\n same side.\n cut : Convert continuous data into discrete bins (Categorical\n of Interval objects).\n qcut : Convert continuous data into bins (Categorical of Interval objects)\n based on quantiles.\n Period : Represents a period of time.\n\n Notes\n -----\n The parameters `left` and `right` must be from the same type, you must be\n able to compare them and they must satisfy ``left <= right``.\n\n A closed interval (in mathematics denoted by square brackets) contains\n its endpoints, i.e. the closed interval ``[0, 5]`` is characterized by the\n conditions ``0 <= x <= 5``. This is what ``closed='both'`` stands for.\n An open interval (in mathematics denoted by parentheses) does not contain\n its endpoints, i.e. the open interval ``(0, 5)`` is characterized by the\n conditions ``0 < x < 5``. This is what ``closed='neither'`` stands for.\n Intervals can also be half-open or half-closed, i.e. ``[0, 5)`` is\n described by ``0 <= x < 5`` (``closed='left'``) and ``(0, 5]`` is\n described by ``0 < x <= 5`` (``closed='right'``).\n\n Examples\n --------\n It is possible to build Intervals of different types, like numeric ones:\n\n >>> iv = pd.Interval(left=0, right=5)\n >>> iv\n Interval(0, 5, closed='right')\n\n You can check if an element belongs to it\n\n >>> 2.5 in iv\n True\n\n You can test the bounds (``closed='right'``, so ``0 < x <= 5``):\n\n >>> 0 in iv\n False\n >>> 5 in iv\n True\n >>> 0.0001 in iv\n True\n\n Calculate its length\n\n >>> iv.length\n 5\n\n You can operate with `+` and `*` over an Interval and the operation\n is applied to each of its bounds, so the result depends on the type\n of the bound elements\n\n >>> shifted_iv = iv + 3\n >>> shifted_iv\n Interval(3, 8, closed='right')\n >>> extended_iv = iv * 10.0\n >>> extended_iv\n Interval(0.0, 50.0, closed='right')\n\n To create a time interval you can use Timestamps as the bounds\n\n >>> year_2017 = pd.Interval(pd.Timestamp('2017-01-01 00:00:00'),\n ... pd.Timestamp('2018-01-01 00:00:00'),\n ... closed='left')\n >>> pd.Timestamp('2017-01-01 00:00') in year_2017\n True\n >>> year_2017.length\n Timedelta('365 days 00:00:00')\n " def __add__(self, value) -> Interval: 'Return self+value.' ... __array_priority__: int def __contains__(self, key) -> bool: 'Return key in self.' ... def __eq__(self, value) -> bool: 'Return self==value.' ... def __floordiv__(self, value) -> int: 'Return self//value.' ... def __ge__(self, value) -> bool: 'Return self>=value.' ... def __gt__(self, value) -> bool: 'Return self>value.' ... def __hash__(self) -> int: 'Return hash(self).' ... def __init__(self, *args, **kwargs) -> None: "\n Immutable object implementing an Interval, a bounded slice-like interval.\n\n Parameters\n ----------\n left : orderable scalar\n Left bound for the interval.\n right : orderable scalar\n Right bound for the interval.\n closed : {'right', 'left', 'both', 'neither'}, default 'right'\n Whether the interval is closed on the left-side, right-side, both or\n neither. See the Notes for more detailed explanation.\n\n See Also\n --------\n IntervalIndex : An Index of Interval objects that are all closed on the\n same side.\n cut : Convert continuous data into discrete bins (Categorical\n of Interval objects).\n qcut : Convert continuous data into bins (Categorical of Interval objects)\n based on quantiles.\n Period : Represents a period of time.\n\n Notes\n -----\n The parameters `left` and `right` must be from the same type, you must be\n able to compare them and they must satisfy ``left <= right``.\n\n A closed interval (in mathematics denoted by square brackets) contains\n its endpoints, i.e. the closed interval ``[0, 5]`` is characterized by the\n conditions ``0 <= x <= 5``. This is what ``closed='both'`` stands for.\n An open interval (in mathematics denoted by parentheses) does not contain\n its endpoints, i.e. the open interval ``(0, 5)`` is characterized by the\n conditions ``0 < x < 5``. This is what ``closed='neither'`` stands for.\n Intervals can also be half-open or half-closed, i.e. ``[0, 5)`` is\n described by ``0 <= x < 5`` (``closed='left'``) and ``(0, 5]`` is\n described by ``0 < x <= 5`` (``closed='right'``).\n\n Examples\n --------\n It is possible to build Intervals of different types, like numeric ones:\n\n >>> iv = pd.Interval(left=0, right=5)\n >>> iv\n Interval(0, 5, closed='right')\n\n You can check if an element belongs to it\n\n >>> 2.5 in iv\n True\n\n You can test the bounds (``closed='right'``, so ``0 < x <= 5``):\n\n >>> 0 in iv\n False\n >>> 5 in iv\n True\n >>> 0.0001 in iv\n True\n\n Calculate its length\n\n >>> iv.length\n 5\n\n You can operate with `+` and `*` over an Interval and the operation\n is applied to each of its bounds, so the result depends on the type\n of the bound elements\n\n >>> shifted_iv = iv + 3\n >>> shifted_iv\n Interval(3, 8, closed='right')\n >>> extended_iv = iv * 10.0\n >>> extended_iv\n Interval(0.0, 50.0, closed='right')\n\n To create a time interval you can use Timestamps as the bounds\n\n >>> year_2017 = pd.Interval(pd.Timestamp('2017-01-01 00:00:00'),\n ... pd.Timestamp('2018-01-01 00:00:00'),\n ... closed='left')\n >>> pd.Timestamp('2017-01-01 00:00') in year_2017\n True\n >>> year_2017.length\n Timedelta('365 days 00:00:00')\n " ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... def __le__(self, value) -> bool: 'Return self<=value.' ... def __lt__(self, value) -> bool: 'Return self Interval: 'Return self*value.' ... def __ne__(self, value) -> bool: 'Return self!=value.' ... def __radd__(self, value) -> Interval: 'Return value+self.' ... def __reduce__(self) -> typing.Union[str, typing.Tuple[typing.Any, ...]]: ... def __repr__(self) -> str: 'Return repr(self).' ... def __rfloordiv__(self, value) -> Interval: 'Return value//self.' ... def __rmul__(self, value) -> Interval: 'Return value*self.' ... def __rsub__(self, value) -> Interval: 'Return value-self.' ... def __rtruediv__(self, value) -> Interval: 'Return value/self.' ... def __str__(self) -> str: 'Return str(self).' ... def __sub__(self, value) -> Interval: 'Return self-value.' ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... def __truediv__(self, value) -> float: 'Return self/value.' ... def _repr_base(self) -> typing.Any: ... _typ: str def _validate_endpoint(self) -> typing.Any: ... @property def closed(self) -> typing.Any: '\n Whether the interval is closed on the left-side, right-side, both or\n neither.\n ' ... @property def left(self) -> typing.Any: '\n Left bound for the interval.\n ' ... def overlaps(self) -> typing.Any: "\n Check whether two Interval objects overlap.\n\n Two intervals overlap if they share a common point, including closed\n endpoints. Intervals that only have an open endpoint in common do not\n overlap.\n\n .. versionadded:: 0.24.0\n\n Parameters\n ----------\n other : Interval\n Interval to check against for an overlap.\n\n Returns\n -------\n bool\n True if the two intervals overlap.\n\n See Also\n --------\n IntervalArray.overlaps : The corresponding method for IntervalArray.\n IntervalIndex.overlaps : The corresponding method for IntervalIndex.\n\n Examples\n --------\n >>> i1 = pd.Interval(0, 2)\n >>> i2 = pd.Interval(1, 3)\n >>> i1.overlaps(i2)\n True\n >>> i3 = pd.Interval(4, 5)\n >>> i1.overlaps(i3)\n False\n\n Intervals that share closed endpoints overlap:\n\n >>> i4 = pd.Interval(0, 1, closed='both')\n >>> i5 = pd.Interval(1, 2, closed='both')\n >>> i4.overlaps(i5)\n True\n\n Intervals that only have an open endpoint in common do not overlap:\n\n >>> i6 = pd.Interval(1, 2, closed='neither')\n >>> i4.overlaps(i6)\n False\n " ... @property def right(self) -> typing.Any: '\n Right bound for the interval.\n ' ... def __getattr__(self, name) -> typing.Any: ... class IntervalMixin(_mod_builtins.object): def __init__(self, *args, **kwargs) -> None: ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... def __reduce__(self) -> typing.Union[str, typing.Tuple[typing.Any, ...]]: ... def __setstate__(self, state: typing.Any) -> None: ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... def _check_closed_matches(self) -> typing.Any: "\n Check if the closed attribute of `other` matches.\n\n Note that 'left' and 'right' are considered different from 'both'.\n\n Parameters\n ----------\n other : Interval, IntervalIndex, IntervalArray\n name : str\n Name to use for 'other' in the error message.\n\n Raises\n ------\n ValueError\n When `other` is not closed exactly the same as self.\n " ... @property def closed_left(self) -> typing.Any: '\n Check if the interval is closed on the left side.\n\n For the meaning of `closed` and `open` see :class:`~pandas.Interval`.\n\n Returns\n -------\n bool\n True if the Interval is closed on the left-side.\n ' ... @property def closed_right(self) -> typing.Any: '\n Check if the interval is closed on the right side.\n\n For the meaning of `closed` and `open` see :class:`~pandas.Interval`.\n\n Returns\n -------\n bool\n True if the Interval is closed on the left-side.\n ' ... @property def is_empty(self) -> typing.Any: "\n Indicates if an interval is empty, meaning it contains no points.\n\n .. versionadded:: 0.25.0\n\n Returns\n -------\n bool or ndarray\n A boolean indicating if a scalar :class:`Interval` is empty, or a\n boolean ``ndarray`` positionally indicating if an ``Interval`` in\n an :class:`~arrays.IntervalArray` or :class:`IntervalIndex` is\n empty.\n\n Examples\n --------\n An :class:`Interval` that contains points is not empty:\n\n >>> pd.Interval(0, 1, closed='right').is_empty\n False\n\n An ``Interval`` that does not contain any points is empty:\n\n >>> pd.Interval(0, 0, closed='right').is_empty\n True\n >>> pd.Interval(0, 0, closed='left').is_empty\n True\n >>> pd.Interval(0, 0, closed='neither').is_empty\n True\n\n An ``Interval`` that contains a single point is not empty:\n\n >>> pd.Interval(0, 0, closed='both').is_empty\n False\n\n An :class:`~arrays.IntervalArray` or :class:`IntervalIndex` returns a\n boolean ``ndarray`` positionally indicating if an ``Interval`` is\n empty:\n\n >>> ivs = [pd.Interval(0, 0, closed='neither'),\n ... pd.Interval(1, 2, closed='neither')]\n >>> pd.arrays.IntervalArray(ivs).is_empty\n array([ True, False])\n\n Missing values are not considered empty:\n\n >>> ivs = [pd.Interval(0, 0, closed='neither'), np.nan]\n >>> pd.IntervalIndex(ivs).is_empty\n array([ True, False])\n " ... @property def length(self) -> typing.Any: '\n Return the length of the Interval.\n ' ... @property def mid(self) -> typing.Any: '\n Return the midpoint of the Interval.\n ' ... @property def open_left(self) -> typing.Any: '\n Check if the interval is open on the left side.\n\n For the meaning of `closed` and `open` see :class:`~pandas.Interval`.\n\n Returns\n -------\n bool\n True if the Interval is closed on the left-side.\n ' ... @property def open_right(self) -> typing.Any: '\n Check if the interval is open on the right side.\n\n For the meaning of `closed` and `open` see :class:`~pandas.Interval`.\n\n Returns\n -------\n bool\n True if the Interval is closed on the left-side.\n ' ... def __getattr__(self, name) -> typing.Any: ... class IntervalTree(IntervalMixin): 'A centered interval tree\n\n Based off the algorithm described on Wikipedia:\n https://en.wikipedia.org/wiki/Interval_tree\n\n we are emulating the IndexEngine interface\n ' def __init__(self) -> None: "\n Parameters\n ----------\n left, right : np.ndarray[ndim=1]\n Left and right bounds for each interval. Assumed to contain no\n NaNs.\n closed : {'left', 'right', 'both', 'neither'}, optional\n Whether the intervals are closed on the left-side, right-side, both\n or neither. Defaults to 'right'.\n leaf_size : int, optional\n Parameter that controls when the tree switches from creating nodes\n to brute-force search. Tune this parameter to optimize query\n performance.\n " ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... def __pyx_fuse_0get_indexer(self) -> typing.Any: 'Return the positions corresponding to unique intervals that overlap\n with the given array of scalar targets.\n ' ... def __pyx_fuse_0get_indexer_non_unique(self) -> typing.Any: 'Return the positions corresponding to intervals that overlap with\n the given array of scalar targets. Non-unique positions are repeated.\n ' ... def __pyx_fuse_1get_indexer(self) -> typing.Any: 'Return the positions corresponding to unique intervals that overlap\n with the given array of scalar targets.\n ' ... def __pyx_fuse_1get_indexer_non_unique(self) -> typing.Any: 'Return the positions corresponding to intervals that overlap with\n the given array of scalar targets. Non-unique positions are repeated.\n ' ... def __pyx_fuse_2get_indexer(self) -> typing.Any: 'Return the positions corresponding to unique intervals that overlap\n with the given array of scalar targets.\n ' ... def __pyx_fuse_2get_indexer_non_unique(self) -> typing.Any: 'Return the positions corresponding to intervals that overlap with\n the given array of scalar targets. Non-unique positions are repeated.\n ' ... def __reduce__(self) -> typing.Union[str, typing.Tuple[typing.Any, ...]]: ... def __repr__(self) -> str: 'Return repr(self).' ... def __setstate__(self, state: typing.Any) -> None: ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... @property def _is_overlapping(self) -> typing.Any: ... @property def _left_sorter(self) -> typing.Any: ... @property def _right_sorter(self) -> typing.Any: ... def clear_mapping(self) -> typing.Any: ... @property def closed(self) -> typing.Any: ... @property def dtype(self) -> typing.Any: ... def get_indexer(self, target) -> typing.Any: 'Return the positions corresponding to unique intervals that overlap\n with the given array of scalar targets.\n ' ... def get_indexer_non_unique(self, target) -> typing.Any: 'Return the positions corresponding to intervals that overlap with\n the given array of scalar targets. Non-unique positions are repeated.\n ' ... @property def is_monotonic_increasing(self) -> typing.Any: '\n Return True if the IntervalTree is monotonic increasing (only equal or\n increasing values), else False\n ' ... @property def is_overlapping(self) -> typing.Any: '\n Determine if the IntervalTree contains overlapping intervals.\n Cached as self._is_overlapping.\n ' ... @property def left(self) -> typing.Any: ... @property def left_sorter(self) -> typing.Any: 'How to sort the left labels; this is used for binary search\n ' ... @property def right(self) -> typing.Any: ... @property def right_sorter(self) -> typing.Any: 'How to sort the right labels\n ' ... @property def root(self) -> typing.Any: ... def __getattr__(self, name) -> typing.Any: ... NODE_CLASSES: dict class Uint64ClosedBothIntervalNode(_mod_builtins.object): 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' def __init__(self, *args, **kwargs) -> None: 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... __pyx_vtable__: PyCapsule def __reduce__(self) -> typing.Union[str, typing.Tuple[typing.Any, ...]]: ... def __repr__(self) -> str: 'Return repr(self).' ... def __setstate__(self, state: typing.Any) -> None: ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... @property def center_left_indices(self) -> typing.Any: ... @property def center_left_values(self) -> typing.Any: ... @property def center_right_indices(self) -> typing.Any: ... @property def center_right_values(self) -> typing.Any: ... def counts(self) -> typing.Any: '\n Inspect counts on this node\n useful for debugging purposes\n ' ... @property def indices(self) -> typing.Any: ... @property def is_leaf_node(self) -> typing.Any: ... @property def leaf_size(self) -> typing.Any: ... @property def left(self) -> typing.Any: ... @property def left_node(self) -> typing.Any: ... @property def max_right(self) -> typing.Any: ... @property def min_left(self) -> typing.Any: ... @property def n_center(self) -> typing.Any: ... @property def n_elements(self) -> typing.Any: ... @property def pivot(self) -> typing.Any: ... def query(self, result, point) -> typing.Any: 'Recursively query this node and its sub-nodes for intervals that\n overlap with the query point.\n ' ... @property def right(self) -> typing.Any: ... @property def right_node(self) -> typing.Any: ... def __getattr__(self, name) -> typing.Any: ... class Uint64ClosedLeftIntervalNode(_mod_builtins.object): 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' def __init__(self, *args, **kwargs) -> None: 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... __pyx_vtable__: PyCapsule def __reduce__(self) -> typing.Union[str, typing.Tuple[typing.Any, ...]]: ... def __repr__(self) -> str: 'Return repr(self).' ... def __setstate__(self, state: typing.Any) -> None: ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... @property def center_left_indices(self) -> typing.Any: ... @property def center_left_values(self) -> typing.Any: ... @property def center_right_indices(self) -> typing.Any: ... @property def center_right_values(self) -> typing.Any: ... def counts(self) -> typing.Any: '\n Inspect counts on this node\n useful for debugging purposes\n ' ... @property def indices(self) -> typing.Any: ... @property def is_leaf_node(self) -> typing.Any: ... @property def leaf_size(self) -> typing.Any: ... @property def left(self) -> typing.Any: ... @property def left_node(self) -> typing.Any: ... @property def max_right(self) -> typing.Any: ... @property def min_left(self) -> typing.Any: ... @property def n_center(self) -> typing.Any: ... @property def n_elements(self) -> typing.Any: ... @property def pivot(self) -> typing.Any: ... def query(self, result, point) -> typing.Any: 'Recursively query this node and its sub-nodes for intervals that\n overlap with the query point.\n ' ... @property def right(self) -> typing.Any: ... @property def right_node(self) -> typing.Any: ... def __getattr__(self, name) -> typing.Any: ... class Uint64ClosedNeitherIntervalNode(_mod_builtins.object): 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' def __init__(self, *args, **kwargs) -> None: 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... __pyx_vtable__: PyCapsule def __reduce__(self) -> typing.Union[str, typing.Tuple[typing.Any, ...]]: ... def __repr__(self) -> str: 'Return repr(self).' ... def __setstate__(self, state: typing.Any) -> None: ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... @property def center_left_indices(self) -> typing.Any: ... @property def center_left_values(self) -> typing.Any: ... @property def center_right_indices(self) -> typing.Any: ... @property def center_right_values(self) -> typing.Any: ... def counts(self) -> typing.Any: '\n Inspect counts on this node\n useful for debugging purposes\n ' ... @property def indices(self) -> typing.Any: ... @property def is_leaf_node(self) -> typing.Any: ... @property def leaf_size(self) -> typing.Any: ... @property def left(self) -> typing.Any: ... @property def left_node(self) -> typing.Any: ... @property def max_right(self) -> typing.Any: ... @property def min_left(self) -> typing.Any: ... @property def n_center(self) -> typing.Any: ... @property def n_elements(self) -> typing.Any: ... @property def pivot(self) -> typing.Any: ... def query(self, result, point) -> typing.Any: 'Recursively query this node and its sub-nodes for intervals that\n overlap with the query point.\n ' ... @property def right(self) -> typing.Any: ... @property def right_node(self) -> typing.Any: ... def __getattr__(self, name) -> typing.Any: ... class Uint64ClosedRightIntervalNode(_mod_builtins.object): 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' def __init__(self, *args, **kwargs) -> None: 'Non-terminal node for an IntervalTree\n\n Categorizes intervals by those that fall to the left, those that fall to\n the right, and those that overlap with the pivot.\n ' ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... __pyx_vtable__: PyCapsule def __reduce__(self) -> typing.Union[str, typing.Tuple[typing.Any, ...]]: ... def __repr__(self) -> str: 'Return repr(self).' ... def __setstate__(self, state: typing.Any) -> None: ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... @property def center_left_indices(self) -> typing.Any: ... @property def center_left_values(self) -> typing.Any: ... @property def center_right_indices(self) -> typing.Any: ... @property def center_right_values(self) -> typing.Any: ... def counts(self) -> typing.Any: '\n Inspect counts on this node\n useful for debugging purposes\n ' ... @property def indices(self) -> typing.Any: ... @property def is_leaf_node(self) -> typing.Any: ... @property def leaf_size(self) -> typing.Any: ... @property def left(self) -> typing.Any: ... @property def left_node(self) -> typing.Any: ... @property def max_right(self) -> typing.Any: ... @property def min_left(self) -> typing.Any: ... @property def n_center(self) -> typing.Any: ... @property def n_elements(self) -> typing.Any: ... @property def pivot(self) -> typing.Any: ... def query(self, result, point) -> typing.Any: 'Recursively query this node and its sub-nodes for intervals that\n overlap with the query point.\n ' ... @property def right(self) -> typing.Any: ... @property def right_node(self) -> typing.Any: ... def __getattr__(self, name) -> typing.Any: ... VALID_CLOSED: frozenset __doc__: typing.Any __file__: str __name__: str __package__: str def __pyx_unpickle_Enum() -> typing.Any: ... def __pyx_unpickle_Float64ClosedBothIntervalNode() -> typing.Any: ... def __pyx_unpickle_Float64ClosedLeftIntervalNode() -> typing.Any: ... def __pyx_unpickle_Float64ClosedNeitherIntervalNode() -> typing.Any: ... def __pyx_unpickle_Float64ClosedRightIntervalNode() -> typing.Any: ... def __pyx_unpickle_Int64ClosedBothIntervalNode() -> typing.Any: ... def __pyx_unpickle_Int64ClosedLeftIntervalNode() -> typing.Any: ... def __pyx_unpickle_Int64ClosedNeitherIntervalNode() -> typing.Any: ... def __pyx_unpickle_Int64ClosedRightIntervalNode() -> typing.Any: ... def __pyx_unpickle_IntervalMixin() -> typing.Any: ... def __pyx_unpickle_IntervalTree() -> typing.Any: ... def __pyx_unpickle_Uint64ClosedBothIntervalNode() -> typing.Any: ... def __pyx_unpickle_Uint64ClosedLeftIntervalNode() -> typing.Any: ... def __pyx_unpickle_Uint64ClosedNeitherIntervalNode() -> typing.Any: ... def __pyx_unpickle_Uint64ClosedRightIntervalNode() -> typing.Any: ... __test__: dict def intervals_to_interval_bounds() -> typing.Any: '\n Parameters\n ----------\n intervals : ndarray\n Object array of Intervals / nulls.\n\n validate_closed: bool, default True\n Boolean indicating if all intervals must be closed on the same side.\n Mismatching closed will raise if True, else return None for closed.\n\n Returns\n -------\n tuple of tuples\n left : (ndarray, object, array)\n right : (ndarray, object, array)\n closed: str\n ' ... def is_monotonic(arr, timelike) -> typing.Any: '\n Returns\n -------\n tuple\n is_monotonic_inc : bool\n is_monotonic_dec : bool\n is_unique : bool\n ' ... def le(a, b) -> typing.Any: 'Same as a <= b.' ... def lt(a, b) -> typing.Any: 'Same as a < b.' ... def __getattr__(name) -> typing.Any: ...