code: def test_combine(self) -> None:
      data = MapData.from_multiple_map_data([])
      self.assertEqual(data.map_df.size, 0)
  
      mmd_double = MapData.from_multiple_map_data([self.mmd, self.mmd])
      self.assertEqual(mmd_double.map_df.size, 2 * self.mmd.map_df.size)
      self.assertEqual(mmd_double.map_key_infos, self.mmd.map_key_infos)
  
      different_map_df = pd.DataFrame(
          [
              {
                  "arm_name": "0_3",
                  "timestamp": 11,
                  "mean": 2.0,
                  "sem": 0.2,
                  "trial_index": 1,
                  "metric_name": "a",
              },
              {
                  "arm_name": "0_3",
                  "timestamp": 18,
                  "mean": 1.8,
                  "sem": 0.3,
                  "trial_index": 1,
                  "metric_name": "b",
              },
          ]
      )
      different_map_key_infos = [
          MapKeyInfo(key="timestamp", default_value=0.0)
      ]
      different_mmd = MapData(
          df=different_map_df, map_key_infos=different_map_key_infos
      )
  
      combined = MapData.from_multiple_map_data(
          [self.mmd, different_mmd]
      )
      self.assertEqual(
          len(combined.map_df),
          len(self.mmd.map_df) + len(different_mmd.map_df),
      )
      self.assertEqual(
          combined.map_df.columns.size, self.mmd.map_df.columns.size + 1
      )
      self.assertEqual(
          combined.map_key_infos,
          self.map_key_infos + different_map_key_infos,
      )
  
      combined_subset = MapData.from_multiple_map_data(
          [self.mmd, different_mmd], ["a"]
      )
      self.assertTrue(
          (combined_subset.map_df["metric_name"] == "a").all()
      )
  
      data_df = pd.DataFrame(
          [
              {
                  "arm_name": "0_4",
                  "mean": 2.0,
                  "sem": 0.2,
                  "trial_index": 1,
                  "metric_name": "a",
              },
              {
                  "arm_name": "0_4",
                  "mean": 1.8,
                  "sem": 0.3,
                  "trial_index": 1,
                  "metric_name": "b",
              },
          ]
      )
      data = Data(df=data_df)
  
      downcast_combined = MapData.from_multiple_data([self.mmd, data])
      self.assertEqual(
          len(downcast_combined.map_df),
          len(self.mmd.map_df) + len(data.df),
      )
      self.assertEqual(
          downcast_combined.map_df.columns.size,
          self.mmd.map_df.columns.size,
      )
      self.assertEqual(
          downcast_combined.map_key_infos, self.map_key_infos
      )
  
      # Check that the Data's rows' epoch cell has the correct default value
      self.assertTrue(
          (
              downcast_combined.map_df[
                  downcast_combined.map_df["arm_name"] == "0_4"
              ]["epoch"]
              == self.mmd.map_key_infos[0].default_value
          ).all()
      )
  
file_path: Ax/ax/core/tests/test_map_data.py
imports: import pandas
  from ax.core.data import Data
  from ax.core.map_data import MapData, MapKeyInfo
  from ax.utils.common.testutils import TestCase
label_desc: Use image node_id 5 for calling the MapDataTest obj's underlying member method code with example usage: obj.test_combine() without return types