code: def test_multi_ts_scaling(self):
      transformer1 = Scaler(MinMaxScaler(feature_range=(0, 2)))
      transformer2 = Scaler(StandardScaler())
  
      series_array = [self.series1, self.series2]
  
      series_array_tr1 = transformer1.fit_transform(series_array)
      series_array_tr2 = transformer2.fit_transform(series_array)
  
      for index in range(len(series_array)):
          assert (
              round(
                  abs(
                      min(series_array_tr1[index].values().flatten())
                      - 0.0
                  ),
                  7,
              )
              == 0
          )
          assert (
              round(
                  abs(
                      max(series_array_tr1[index].values().flatten())
                      - 2.0
                  ),
                  7,
              )
              == 0
          )
          assert (
              round(
                  abs(
                      np.mean(
                          series_array_tr2[index].values().flatten()
                      )
                      - 0.0
                  ),
                  7,
              )
              == 0
          )
          assert (
              round(
                  abs(
                      np.std(series_array_tr2[index].values().flatten())
                      - 1.0
                  ),
                  7,
              )
              == 0
          )
  
      series_array_rec1 = transformer1.inverse_transform(
          series_array_tr1
      )
      series_array_rec2 = transformer2.inverse_transform(
          series_array_tr2
      )
  
      for index in range(len(series_array)):
          np.testing.assert_almost_equal(
              series_array_rec1[index].values().flatten(),
              series_array[index].values().flatten(),
          )
          np.testing.assert_almost_equal(
              series_array_rec2[index].values().flatten(),
              series_array[index].values().flatten(),
          )
  
file_path: darts/darts/tests/dataprocessing/transformers/test_data_transformer.py
imports: import numpy
  from sklearn.preprocessing import MinMaxScaler, StandardScaler
  from darts import TimeSeries
  from darts.dataprocessing.transformers import Scaler
  from darts.utils import timeseries_generation
  from darts.utils.timeseries_generation import linear_timeseries, sine_timeseries
label_desc: Use image node_id 2 for calling the TestDataTransformer obj's underlying member method code with example usage: obj.test_multi_ts_scaling() without return types