@@ -8,8 +8,6 @@ import warnings
88from pandas._libs import lib
99from pandas._libs.algos import is_monotonic
1010
11- from pandas._libs.interval import _warning_interval
12-
1311ctypedef fused int_scalar_t:
1412 int64_t
1513 float64_t
@@ -42,18 +40,13 @@ cdef class IntervalTree(IntervalMixin):
4240 object _is_overlapping, _left_sorter, _right_sorter
4341 Py_ssize_t _na_count
4442
45- def __init__(self, left, right, inclusive: str | None = None, closed: None | lib.NoDefault = lib.no_default, leaf_size=100):
43+ def __init__(self, left, right, inclusive: str | None = None, leaf_size=100):
4644 """
4745 Parameters
4846 ----------
4947 left, right : np.ndarray[ndim=1]
5048 Left and right bounds for each interval. Assumed to contain no
5149 NaNs.
52- closed : {'left', 'right', 'both', 'neither'}, optional
53- Whether the intervals are closed on the left-side, right-side, both
54- or neither. Defaults to 'right'.
55-
56- .. deprecated:: 1.5.0
5750
5851 inclusive : {"both", "neither", "left", "right"}, optional
5952 Whether the intervals are closed on the left-side, right-side, both
@@ -66,8 +59,6 @@ cdef class IntervalTree(IntervalMixin):
6659 to brute-force search. Tune this parameter to optimize query
6760 performance.
6861 """
69- inclusive, closed = _warning_interval(inclusive, closed)
70-
7162 if inclusive is None:
7263 inclusive = "right"
7364
@@ -119,7 +110,7 @@ cdef class IntervalTree(IntervalMixin):
119110 if self._is_overlapping is not None:
120111 return self._is_overlapping
121112
122- # <= when both sides closed since endpoints can overlap
113+ # <= when inclusive on both sides since endpoints can overlap
123114 op = le if self.inclusive == 'both' else lt
124115
125116 # overlap if start of current interval < end of previous interval
@@ -263,7 +254,7 @@ cdef class IntervalNode:
263254
264255
265256# we need specialized nodes and leaves to optimize for different dtype and
266- # closed values
257+ # inclusive values
267258
268259{{py:
269260
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