| 360 | ) |
| 361 | |
| 362 | def test_selection(self): |
| 363 | for n_samples in range(1, 100): |
| 364 | for n_instances in range(1, n_samples): |
| 365 | X = np.random.rand(n_samples, 3) |
| 366 | mean = np.random.rand(n_samples, ) |
| 367 | std = np.random.rand(n_samples, ) |
| 368 | max_val = np.random.rand() |
| 369 | |
| 370 | mock_estimator = mock.MockEstimator( |
| 371 | predict_return=(mean, std) |
| 372 | ) |
| 373 | |
| 374 | optimizer = modAL.models.learners.BayesianOptimizer( |
| 375 | estimator=mock_estimator) |
| 376 | optimizer._set_max([0], [max_val]) |
| 377 | |
| 378 | modAL.acquisition.max_PI( |
| 379 | optimizer, X, tradeoff=np.random.rand(), n_instances=n_instances) |
| 380 | modAL.acquisition.max_EI( |
| 381 | optimizer, X, tradeoff=np.random.rand(), n_instances=n_instances) |
| 382 | modAL.acquisition.max_UCB( |
| 383 | optimizer, X, beta=np.random.rand(), n_instances=n_instances) |
| 384 | |
| 385 | |
| 386 | class TestDensity(unittest.TestCase): |