(self)
| 1225 | |
| 1226 | class TestBayesianOptimizer(unittest.TestCase): |
| 1227 | def test_set_max(self): |
| 1228 | # case 1: the estimator is not fitted yet |
| 1229 | regressor = mock.MockEstimator() |
| 1230 | learner = modAL.models.learners.BayesianOptimizer(estimator=regressor) |
| 1231 | self.assertEqual(-np.inf, learner.y_max) |
| 1232 | |
| 1233 | # case 2: the estimator is fitted already |
| 1234 | for n_samples in range(1, 100): |
| 1235 | X = np.random.rand(n_samples, 2) |
| 1236 | y = np.random.rand(n_samples, ) |
| 1237 | max_val = np.max(y) |
| 1238 | |
| 1239 | regressor = mock.MockEstimator() |
| 1240 | learner = modAL.models.learners.BayesianOptimizer( |
| 1241 | estimator=regressor, |
| 1242 | X_training=X, y_training=y |
| 1243 | ) |
| 1244 | np.testing.assert_almost_equal(max_val, learner.y_max) |
| 1245 | |
| 1246 | def test_set_new_max(self): |
| 1247 | for n_reps in range(100): |
nothing calls this directly
no outgoing calls
no test coverage detected