code: def test_where_interval_fullop_downcast(self, frame_or_series):
      # GH#45768
      obj = frame_or_series([pd.Interval(0, 0)] * 2)
      other = frame_or_series([1.0, 2.0])
  
      msg = (
          "Downcasting behavior in Series and DataFrame methods 'where'"
      )
      with tm.assert_produces_warning(FutureWarning, match=msg):
          res = obj.where(~obj.notna(), other)
  
      # since all entries are being changed, we will downcast result
      #  from object to ints (not floats)
      tm.assert_equal(res, other.astype(np.int64))
  
      # unlike where, Block.putmask does not downcast
      with tm.assert_produces_warning(
          FutureWarning, match="Setting an item of incompatible dtype"
      ):
          obj.mask(obj.notna(), other, inplace=True)
      tm.assert_equal(obj, other.astype(object))
  
imports: from datetime import datetime
  from hypothesis import given
  import numpy
  import pytest
  from pandas.core.dtypes.common import is_scalar
  import pandas
  from pandas import DataFrame, DatetimeIndex, Index, Series, StringDtype, Timestamp, date_range, isna
  import pandas._testing
  from pandas._testing._hypothesis import OPTIONAL_ONE_OF_ALL
label_desc: Use image node_id 30 for calling the TestDataFrameIndexingWhere obj's underlying member method code with example usage: obj.test_where_interval_fullop_downcast(frame_or_series) without return types