code: def overlaps(self, other):
      if isinstance(other, (IntervalArray, ABCIntervalIndex)):
          raise NotImplementedError
      elif not isinstance(other, Interval):
          msg = "`other` must be Interval-like, got {other}"
          raise TypeError(msg.format(other=type(other).__name__))
  
      # equality is okay if both endpoints are closed (overlap at a point)
      op1 = le if (self.closed_left and other.closed_right) else lt
      op2 = le if (other.closed_left and self.closed_right) else lt
  
      # overlaps is equivalent negation of two interval being disjoint:
      # disjoint = (A.left > B.right) or (B.left > A.right)
      # (simplifying the negation allows this to be done in less operations)
      return op1(self.left, other.right) & op2(other.left, self.right)
  
imports: from operator import le, lt
  import textwrap
  import numpy
  from pandas._libs.interval import Interval, IntervalMixin, intervals_to_interval_bounds
  from pandas.compat import add_metaclass
  from pandas.compat.numpy import function
  from pandas.util._decorators import Appender
  from pandas.util._doctools import _WritableDoc
  from pandas.core.dtypes.cast import maybe_convert_platform
  from pandas.core.dtypes.common import is_categorical_dtype, is_datetime64_any_dtype, is_float_dtype, is_integer_dtype, is_interval, is_interval_dtype, is_scalar, is_string_dtype, is_timedelta64_dtype, pandas_dtype
  from pandas.core.dtypes.dtypes import IntervalDtype
  from pandas.core.dtypes.generic import ABCDatetimeIndex, ABCInterval, ABCIntervalIndex, ABCPeriodIndex, ABCSeries
  from pandas.core.dtypes.missing import isna, notna
  from pandas.core.arrays.base import ExtensionArray, _extension_array_shared_docs
  from pandas.core.arrays.categorical import Categorical
  import pandas.core.common
  from pandas.core.config import get_option
  from pandas.core.indexes.base import Index, ensure_index
label_desc: Use image node_id 38 for calling the IntervalArray obj's underlying member method code with example usage: obj.overlaps(other) and returns: unknown