Class TestDisagreements

tests/core_tests.py:407–536

class TestDisagreements(unittest.TestCase):

    def test_vote_entropy(self):
        for n_samples in range(1, 10):
            for n_classes in range(1, 10):
                for true_query_idx in range(n_samples):
                    # 1. fitted committee
                    vote_return = np.zeros(
                        shape=(n_samples, n_classes), dtype=np.int16)
                    vote_return[true_query_idx] = np.asarray(
                        range(n_classes), dtype=np.int16)
                    committee = mock.MockCommittee(classes_=np.asarray(
                        range(n_classes)), vote_return=vote_return)
                    vote_entr = modAL.disagreement.vote_entropy(
                        committee, np.random.rand(n_samples, n_classes)
                    )
                    true_entropy = np.zeros(shape=(n_samples, ))
                    true_entropy[true_query_idx] = entropy(
                        np.ones(n_classes)/n_classes)
                    np.testing.assert_array_almost_equal(
                        vote_entr, true_entropy)

                    # 2. unfitted committee
                    committee = mock.MockCommittee(fitted=False)
                    true_entropy = np.zeros(shape=(n_samples,))
                    vote_entr = modAL.disagreement.vote_entropy(
                        committee, np.random.rand(n_samples, n_classes)
                    )
                    np.testing.assert_almost_equal(vote_entr, true_entropy)

    def test_consensus_entropy(self):
        for n_samples in range(1, 10):
            for n_classes in range(2, 10):
                for true_query_idx in range(n_samples):
                    # 1. fitted committee
                    proba = np.zeros(shape=(n_samples, n_classes))
                    proba[:, 0] = 1.0
                    proba[true_query_idx] = np.ones(n_classes)/n_classes
                    committee = mock.MockCommittee(predict_proba_return=proba)
                    consensus_entropy = modAL.disagreement.consensus_entropy(
                        committee, np.random.rand(n_samples, n_classes)
                    )
                    true_entropy = np.zeros(shape=(n_samples,))
                    true_entropy[true_query_idx] = entropy(
                        np.ones(n_classes) / n_classes)
                    np.testing.assert_array_almost_equal(
                        consensus_entropy, true_entropy)

                    # 2. unfitted committee
                    committee = mock.MockCommittee(fitted=False)
                    true_entropy = np.zeros(shape=(n_samples,))
                    consensus_entropy = modAL.disagreement.consensus_entropy(
                        committee, np.random.rand(n_samples, n_classes)
                    )
                    np.testing.assert_almost_equal(
                        consensus_entropy, true_entropy)

    def test_KL_max_disagreement(self):