code: def test_mi_intervalindex_slicing_with_scalar(self):
      # GH#27456
      ii = IntervalIndex.from_arrays(
          [0, 1, 10, 11, 0, 1, 10, 11],
          [1, 2, 11, 12, 1, 2, 11, 12],
          name="MP",
      )
      idx = pd.MultiIndex.from_arrays(
          [
              pd.Index(
                  [
                      "FC",
                      "FC",
                      "FC",
                      "FC",
                      "OWNER",
                      "OWNER",
                      "OWNER",
                      "OWNER",
                  ]
              ),
              pd.Index(
                  [
                      "RID1",
                      "RID1",
                      "RID2",
                      "RID2",
                      "RID1",
                      "RID1",
                      "RID2",
                      "RID2",
                  ]
              ),
              ii,
          ]
      )
  
      idx.names = ["Item", "RID", "MP"]
      df = DataFrame({"value": [1, 2, 3, 4, 5, 6, 7, 8]})
      df.index = idx
  
      query_df = DataFrame(
          {
              "Item": ["FC", "OWNER", "FC", "OWNER", "OWNER"],
              "RID": ["RID1", "RID1", "RID1", "RID2", "RID2"],
              "MP": [0.2, 1.5, 1.6, 11.1, 10.9],
          }
      )
  
      query_df = query_df.sort_index()
  
      idx = pd.MultiIndex.from_arrays(
          [query_df.Item, query_df.RID, query_df.MP]
      )
      query_df.index = idx
      result = df.value.loc[query_df.index]
  
      # the IntervalIndex level is indexed with floats, which map to
      #  the intervals containing them.  Matching the behavior we would get
      #  with _only_ an IntervalIndex, we get an IntervalIndex level back.
      sliced_level = ii.take([0, 1, 1, 3, 2])
      expected_index = pd.MultiIndex.from_arrays(
          [
              idx.get_level_values(0),
              idx.get_level_values(1),
              sliced_level,
          ]
      )
      expected = Series(
          [1, 6, 2, 8, 7], index=expected_index, name="value"
      )
      tm.assert_series_equal(result, expected)
  
file_path: pandas/pandas/tests/indexing/interval/test_interval.py
imports: import numpy
  import pytest
  from pandas._libs import index
  from pandas.compat import IS64
  import pandas
  from pandas import DataFrame, IntervalIndex, Series
  import pandas._testing
label_desc: Use image node_id 1 for calling the TestIntervalIndexInsideMultiIndex obj's underlying member method code with example usage: obj.test_mi_intervalindex_slicing_with_scalar() without return types