text: import thresher
  from thresher.tests.sample_data import get_sample_data
  
  t = thresher.Thresher(progress_bar=True)
  
  print('Currently supported algorithms:')
  print(t.get_supported_algorithms())
  
  case_small_scores = [0.1, 0.3, 0.4, 0.7]
  case_small_labels = [-1, -1, 1, 1]
  
  print(f'Optimization result: {t.optimize_threshold(case_small_scores, case_small_labels)}')
  
  t = thresher.Thresher(progress_bar=True, verbose=True)
  
  medium_data = get_sample_data()
  case_medium_scores = list(medium_data['pred'].values)
  case_medium_labels = list(medium_data['actual'].values)
  
  print(f'Optimization result: {t.optimize_threshold(case_medium_scores, case_medium_labels)}')
  
  t = thresher.Thresher(algorithm='gen', progress_bar=True, verbose=True)
  
  medium_data = get_sample_data()
  case_medium_scores = list(medium_data['pred'].values)
  case_medium_labels = list(medium_data['actual'].values)
  
  print(f'Alternative optimization result: {t.optimize_threshold(case_medium_scores, case_medium_labels)}')
  
  print('Done')
  