code: def _make_index(n_timepoints, index_type=None):
      """Make indices for unit testing."""
      if index_type == "period":
          start = "2000-01"
          freq = "M"
          return pd.period_range(
              start=start, periods=n_timepoints, freq=freq
          )
  
      elif index_type == "datetime" or index_type is None:
          start = "2000-01-01"
          freq = "D"
          return pd.date_range(
              start=start, periods=n_timepoints, freq=freq
          )
  
      elif index_type == "range":
          start = 3  # check non-zero based indices
          return pd.RangeIndex(start=start, stop=start + n_timepoints)
  
      elif index_type == "int":
          start = 3
          return pd.Index(
              np.arange(start, start + n_timepoints), dtype=int
          )
  
      else:
          raise ValueError(
              f"index_class: {index_type} is not supported"
          )
  
imports: import numpy
  import pandas
  from sklearn.utils import check_random_state
label_desc: Use image node_id 2 for calling a global function with example usage: _make_index(n_timepoints, index_type) and returns: pd, pd, pd, pd