code: def test_warp(self):
      # Support different time dimension names
      xa1 = self.series1.data_array().rename({"time": "time1"})
      xa2 = self.series2.data_array().rename({"time": "time2"})
  
      static_covs = pd.DataFrame([[0.0, 1.0]], columns=["st1", "st2"])
      series1 = TimeSeries.from_xarray(xa1).with_static_covariates(
          static_covs
      )
      series2 = TimeSeries.from_xarray(xa2).with_static_covariates(
          static_covs
      )
  
      alignment = dtw.dtw(series1, series2)
  
      warped1, warped2 = alignment.warped()
      assert (
          round(
              abs(alignment.mean_distance() - mae(warped1, warped2)), 7
          )
          == 0
      )
      assert warped1.static_covariates.equals(series1.static_covariates)
      assert warped2.static_covariates.equals(series2.static_covariates)
  
      """
          See DTWAlignment.warped for why this functionality is currently disabled
  
          #Mutually Exclusive Option
          with pytest.raises(ValueError):
              alignment.warped(take_dates=True, range_index=True)
  
          #Take_dates does not support indexing by RangeIndex
          with pytest.raises(ValueError):
              xa3 = xa1.copy()
              xa3["time1"] = pd.RangeIndex(0, len(self.series1))
  
              dtw.dtw(TimeSeries.from_xarray(xa3), series2).warped(take_dates=True)
  
  
          warped1, warped2 = alignment.warped(take_dates=True)
          self.assertTrue(np.all(warped1.time_index == warped2.time_index))
          """
  
imports: import matplotlib.pyplot
  import numpy
  import pandas
  import pytest
  from darts.dataprocessing import dtw
  from darts.metrics import dtw_metric, mae, mape
  from darts.timeseries import TimeSeries
  from darts.utils import timeseries_generation
label_desc: Use image node_id 5 for calling the TestDynamicTimeWarping obj's underlying member method code with example usage: obj.test_warp() without return types