docstr: Check that probabilistic multivariate monthly to quarterly is properly transformed
docstr_tok: ["Check","that","probabilistic","multivariate","monthly","to","quarterly","is","properly","transformed"]
code: def test_probabilistic_multivariate_monthly_to_quarterly(self):
      """
      Check that probabilistic multivariate monthly to quarterly is properly transformed
      """
      monthly_ts = self.monthly_ts.stack(
          TimeSeries.from_times_and_values(
              times=self.monthly_ts.time_index,
              values=np.arange(10, 19),
              columns=["other"],
          )
      )
      # generate probabilistic monthly series
      all_vals_monthly = monthly_ts.all_values(copy=False)
      prob_values_monthly = np.concatenate(
          [all_vals_monthly + i * 0.01 for i in range(3)], axis=2
      )
      ts_prob_monthly = TimeSeries.from_times_and_values(
          times=monthly_ts.time_index,
          values=prob_values_monthly,
          columns=monthly_ts.columns.tolist(),
      )
  
      # component components are alternating
      quarterly_ts = TimeSeries.from_times_and_values(
          times=self.quarterly_ts.time_index,
          values=np.array(
              [
                  [1, 10, 2, 11, 3, 12],
                  [4, 13, 5, 14, 6, 15],
                  [7, 16, 8, 17, 9, 18],
              ]
          ),
          columns=[
              "values_midas_0",
              "other_midas_0",
              "values_midas_1",
              "other_midas_1",
              "values_midas_2",
              "other_midas_2",
          ],
      )
      # generate probabilistic quarterly series
      all_vals_quarterly = quarterly_ts.all_values(copy=False)
      prob_values_quarterly = np.concatenate(
          [all_vals_quarterly + i * 0.01 for i in range(3)], axis=2
      )
      ts_prob_quarterly = TimeSeries.from_times_and_values(
          times=quarterly_ts.time_index,
          values=prob_values_quarterly,
          columns=quarterly_ts.columns.tolist(),
      )
  
      midas_1 = MIDAS(low_freq="QS")
      multivar_quarterly_ts_midas = midas_1.fit_transform(
          ts_prob_monthly
      )
      assert multivar_quarterly_ts_midas == ts_prob_quarterly
  
      multivar_inversed_quarterly_ts_midas = midas_1.inverse_transform(
          multivar_quarterly_ts_midas
      )
      assert ts_prob_monthly == multivar_inversed_quarterly_ts_midas
  
imports: import numpy
  import pandas
  import pytest
  from darts import TimeSeries
  from darts.dataprocessing.transformers import MIDAS
  from darts.models import LinearRegressionModel
  from darts.utils.timeseries_generation import generate_index, linear_timeseries
label_desc: Use image node_id 6 for calling the TestMIDAS obj's underlying member method code with example usage: obj.test_probabilistic_multivariate_monthly_to_quarterly() without return types