docstr: test the index type of generated index
docstr_tok: ["test","the","index","type","of","generated","index"]
code: def helper_test_index_types(self, ig: CovariatesIndexGenerator):
      """test the index type of generated index"""
      # pd.DatetimeIndex
      idx, _ = ig.generate_train_idx(
          self.target_time, self.cov_time_train
      )
      assert isinstance(idx, pd.DatetimeIndex)
      idx, _ = ig.generate_inference_idx(
          self.n_short, self.target_time, self.cov_time_inf_short
      )
      assert isinstance(idx, pd.DatetimeIndex)
      idx, _ = ig.generate_train_inference_idx(
          self.n_short, self.target_time, self.cov_time_inf_short
      )
      assert isinstance(idx, pd.DatetimeIndex)
      idx, _ = ig.generate_train_idx(self.target_time, None)
      assert isinstance(idx, pd.DatetimeIndex)
  
      # pd.RangeIndex
      idx, _ = ig.generate_train_idx(
          self.target_int, self.cov_int_train
      )
      assert isinstance(idx, pd.RangeIndex)
      idx, _ = ig.generate_inference_idx(
          self.n_short, self.target_int, self.cov_int_inf_short
      )
      assert isinstance(idx, pd.RangeIndex)
      idx, _ = ig.generate_train_inference_idx(
          self.n_short, self.target_int, self.cov_int_inf_short
      )
      assert isinstance(idx, pd.RangeIndex)
      idx, _ = ig.generate_train_idx(self.target_int, None)
      assert isinstance(idx, pd.RangeIndex)
  
file_path: darts/darts/tests/dataprocessing/encoders/test_covariate_index_generators.py
imports: import numpy
  import pandas
  import pytest
  from darts import TimeSeries
  from darts.dataprocessing.encoders.encoder_base import CovariatesIndexGenerator, FutureCovariatesIndexGenerator, PastCovariatesIndexGenerator
  from darts.logging import get_logger
  from darts.utils import timeseries_generation
label_desc: Use image node_id 1 for calling the TestCovariatesIndexGenerator obj's underlying member method code with example usage: obj.helper_test_index_types(ig) without return types