code: def test_scaling_single_series(self):
      # 3 categories for each categorical static covariate column (column idx 1 and 3)
      test_values = np.array(
          [
              [0.0, 0.0, 0.0, 0.0],
              [0.5, 1.0, 0.5, 1.0],
              [1.0, 2.0, 1.0, 2.0],
          ]
      )
      for series in [self.series1, self.series2]:
          scaler = StaticCovariatesTransformer()
          self.helper_test_scaling(series, scaler, test_values)
  
      test_values = np.array(
          [
              [-1.0, 0.0, -1.0, 0.0],
              [0.0, 1.0, 0.0, 1.0],
              [1.0, 2.0, 1.0, 2.0],
          ]
      )
      for series in [self.series1, self.series2]:
          scaler = StaticCovariatesTransformer(
              transformer_num=MinMaxScaler(feature_range=(-1, 1))
          )
          self.helper_test_scaling(series, scaler, test_values)
  
      test_values = np.array(
          [
              [0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0],
              [0.5, 0.0, 1.0, 0.0, 0.5, 0.0, 1.0, 0.0],
              [1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0],
          ]
      )
      for series in [self.series1, self.series2]:
          scaler = StaticCovariatesTransformer(
              transformer_cat=OneHotEncoder()
          )
          self.helper_test_scaling(series, scaler, test_values)
  
file_path: darts/darts/tests/dataprocessing/transformers/test_static_covariates_transformer.py
imports: import numpy
  import pandas
  import pytest
  from sklearn.preprocessing import MinMaxScaler, OneHotEncoder
  from darts import TimeSeries
  from darts.dataprocessing.transformers import StaticCovariatesTransformer
  from darts.utils import timeseries_generation
label_desc: Use image node_id 1 for calling the TestStaticCovariatesTransformer obj's underlying member method code with example usage: obj.test_scaling_single_series() without return types