docstr: Return the IntervalArray's data as a numpy array of Interval
  objects (with dtype='object')
docstr_tok: ["Return","the","IntervalArray","'s","data","as","a","numpy","array","of","Interval","objects","(","with","dtype='object","'",")"]
code: def __array__(self, dtype=None):
      """
      Return the IntervalArray's data as a numpy array of Interval
      objects (with dtype='object')
      """
      left = self.left
      right = self.right
      mask = self.isna()
      closed = self._closed
  
      result = np.empty(len(left), dtype=object)
      for i in range(len(left)):
          if mask[i]:
              result[i] = np.nan
          else:
              result[i] = Interval(left[i], right[i], closed)
      return result
  
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 35 for calling the IntervalArray obj's underlying member method code with example usage: obj.__array__(dtype) and returns: result