text: import unittest
  
  from sklearn.datasets import load_digits, load_diabetes
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.linear_model import RidgeClassifier
  
  
  class TestEvoCore(unittest.TestCase):
  
      def test_class(self):
  
          from meco import MECO
  
          X, y = load_digits(return_X_y=True)
  
          model = MECO(RidgeClassifier(random_state=42), 'both', max_generations=10)
          model.fit(X, y)
          x_reduced = model.transform(X)
          y_reduced = y[model.best_set_['samples']]
  
          score1 = RidgeClassifier(random_state=42).fit(x_reduced, y_reduced).score(X[:, model.best_set_['features']], y)
          score2 = RandomForestClassifier(random_state=42).fit(x_reduced, y_reduced).score(X[:, model.best_set_['features']], y)
  
          print(score1)
          print(score2)
          print(model.best_set_)
          print(model.best_set_['accuracy'])
  
          return
  
      def test_separate_tasks(self):
  
          from meco import MECO
  
          X, y = load_digits(return_X_y=True)
  
          model = MECO(RidgeClassifier(random_state=42), 'samples', max_generations=10)
          model.fit(X, y)
  
          model = MECO(RidgeClassifier(random_state=42), 'features', max_generations=10)
          model.fit(X, y)
  
          return
  
  
  suite = unittest.TestLoader().loadTestsFromTestCase(TestEvoCore)
  unittest.TextTestRunner(verbosity=2).run(suite)
  