code: def test_river_levels_problem():
      # Initialise pipeline for river levels prediction
      node_encoder = PipelineNode("one_hot_encoding")
      node_scaling = PipelineNode("scaling", nodes_from=[node_encoder])
      node_ridge = PipelineNode("ridge", nodes_from=[node_scaling])
      node_lasso = PipelineNode("lasso", nodes_from=[node_scaling])
      node_final = PipelineNode(
          "rfr", nodes_from=[node_ridge, node_lasso]
      )
  
      init_pipeline = Pipeline(node_final)
  
      file_path_train = fedot_project_root().joinpath(
          "test/data/station_levels.csv"
      )
  
      run_river_experiment(
          file_path=file_path_train,
          pipeline=init_pipeline,
          iterations=1,
          tuner=SimultaneousTuner,
          tuner_iterations=10,
      )
  
      is_experiment_finished = True
  
      assert is_experiment_finished
  
file_path: FEDOT/test/integration/real_applications/test_real_cases.py
imports: import numpy
  from golem.core.tuning.simultaneous import SimultaneousTuner
  from sklearn.metrics import mean_squared_error
  from cases.credit_scoring.credit_scoring_problem import run_credit_scoring_problem
  from cases.metocean_forecasting_problem import run_metocean_forecasting_problem
  from cases.river_levels_prediction.river_level_case_manual import run_river_experiment
  from cases.spam_detection import run_text_problem_from_saved_meta_file
  from cases.time_series_gapfilling_case import run_gapfilling_case
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.utils import fedot_project_root
label_desc: Use image node_id 4 for calling a global function with example usage: test_river_levels_problem() without return types