Class TestCommittee

tests/core_tests.py:1371–1529

class TestCommittee(unittest.TestCase):

    def test_set_classes(self):
        # 1. test unfitted learners
        for n_learners in range(1, 10):
            learner_list = [modAL.models.learners.ActiveLearner(estimator=mock.MockEstimator(fitted=False))
                            for idx in range(n_learners)]
            committee = modAL.models.learners.Committee(
                learner_list=learner_list)
            self.assertEqual(committee.classes_, None)
            self.assertEqual(committee.n_classes_, 0)

        # 2. test fitted learners
        for n_classes in range(1, 10):
            learner_list = [modAL.models.learners.ActiveLearner(estimator=mock.MockEstimator(classes_=np.asarray([idx])))
                            for idx in range(n_classes)]
            committee = modAL.models.learners.Committee(
                learner_list=learner_list)
            np.testing.assert_equal(
                committee.classes_,
                np.unique(range(n_classes))
            )

    def test_predict(self):
        for n_learners in range(1, 10):
            for n_instances in range(1, 10):
                prediction = np.random.randint(
                    10, size=(n_instances, n_learners))
                committee = modAL.models.learners.Committee(
                    learner_list=[mock.MockActiveLearner(
                        mock.MockEstimator(classes_=np.asarray([0])),
                        predict_return=prediction[:, learner_idx]
                    )
                        for learner_idx in range(n_learners)]
                )
                np.testing.assert_equal(
                    committee.vote(np.random.rand(n_instances, 5)),
                    prediction
                )

    def test_predict_proba(self):
        for n_samples in range(1, 100):
            for n_learners in range(1, 10):
                for n_classes in range(1, 10):
                    vote_proba_output = np.random.rand(
                        n_samples, n_learners, n_classes)
                    # assembling the mock learners
                    learner_list = [mock.MockActiveLearner(
                        predict_proba_return=vote_proba_output[:,
                                                               learner_idx, :],
                        predictor=mock.MockEstimator(
                            classes_=list(range(n_classes)))
                    ) for learner_idx in range(n_learners)]
                    committee = modAL.models.learners.Committee(
                        learner_list=learner_list)
                    np.testing.assert_almost_equal(
                        committee.predict_proba(np.random.rand(n_samples, 1)),
                        np.mean(vote_proba_output, axis=1)