code: def test_multivariate_stochastic_series(self):
      scaler = Scaler(MinMaxScaler())
      vals = np.random.rand(10, 5, 50)
      s = TimeSeries.from_values(vals)
      ss = scaler.fit_transform(s)
      ssi = scaler.inverse_transform(ss)
  
      # Test inverse transform
      np.testing.assert_allclose(s.all_values(), ssi.all_values())
  
      # Test that the transform is done per component (i.e max value over each component should be 1 and min 0)
      np.testing.assert_allclose(
          np.array(
              [
                  ss.all_values(copy=False)[:, i, :].max()
                  for i in range(ss.width)
              ]
          ),
          np.array([1.0] * ss.width),
      )
  
      np.testing.assert_allclose(
          np.array(
              [
                  ss.all_values(copy=False)[:, i, :].min()
                  for i in range(ss.width)
              ]
          ),
          np.array([0.0] * ss.width),
      )
  
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 3 for calling the TestDataTransformer obj's underlying member method code with example usage: obj.test_multivariate_stochastic_series() without return types