code: def test_with_static_covariates_multivariate(self):
      ts = linear_timeseries(length=10)
      ts_multi = ts.stack(ts)
      static_covs = pd.DataFrame(
          [[0.0, 1.0], [0.0, 1.0]], columns=["st1", "st2"]
      )
  
      # from univariate static covariates
      ts_multi = ts_multi.with_static_covariates(static_covs.loc[0])
      assert ts_multi.static_covariates.index.equals(
          pd.Index([DEFAULT_GLOBAL_STATIC_COV_NAME])
      )
      assert ts_multi.static_covariates.columns.equals(
          static_covs.columns
      )
      np.testing.assert_almost_equal(
          ts_multi.static_covariates_values(copy=False),
          static_covs.loc[0:0].values,
      )
  
      # from multivariate static covariates
      ts_multi = ts_multi.with_static_covariates(static_covs)
      assert ts_multi.static_covariates.index.equals(
          ts_multi.components
      )
      assert ts_multi.static_covariates.columns.equals(
          static_covs.columns
      )
      np.testing.assert_almost_equal(
          ts_multi.static_covariates_values(copy=False),
          static_covs.values,
      )
  
      # raise an error if multivariate static covariates columns don't match the number of components in the series
      with pytest.raises(ValueError):
          _ = ts_multi.with_static_covariates(
              pd.concat([static_covs] * 2, axis=0)
          )
  
imports: import copy
  import os
  import numpy
  import pandas
  import pytest
  from darts import TimeSeries, concatenate
  from darts.dataprocessing.transformers import BoxCox, Scaler
  from darts.timeseries import DEFAULT_GLOBAL_STATIC_COV_NAME, STATIC_COV_TAG
  from darts.utils.timeseries_generation import generate_index, linear_timeseries
label_desc: Use image node_id 5 for calling the TestTimeSeriesStaticCovariate obj's underlying member method code with example usage: obj.test_with_static_covariates_multivariate() without return types