text: 
  ###############################################################################
  # Script for reproducing the results of CQR paper
  ###############################################################################
  
  import numpy as np
  from reproducible_experiments.run_cqr_experiment import run_experiment
  #from run_cqr_experiment import run_experiment
  
  
  # list methods to test
  test_methods = ['linear',
                  'neural_net',
                  'random_forest',
                  'quantile_net',
                  'cqr_quantile_net',
                  'cqr_asymmetric_quantile_net',
                  'rearrangement',
                  'cqr_rearrangement',
                  'cqr_asymmetric_rearrangement',
                  'quantile_forest',
                  'cqr_quantile_forest',
                  'cqr_asymmetric_quantile_forest']
  
  # list of datasets
  dataset_names = ['meps_19',
                   'meps_20',
                   'meps_21',
                   'star',
                   'facebook_1',
                   'facebook_2',
                   'bio',
                   'blog_data',
                   'concrete',
                   'bike',
                   'community']
  
  # vector of random seeds
  random_state_train_test = np.arange(20)
  
  for test_method_id in range(12):
      for dataset_name_id in range(11):
          for random_state_train_test_id in range(20):
              dataset_name = dataset_names[dataset_name_id]
              test_method = test_methods[test_method_id]
              random_state = random_state_train_test[random_state_train_test_id]
  
              # run an experiment and save average results to CSV file
              run_experiment(dataset_name, test_method, random_state)
  