Method test_classifier_uncertainty

tests/core_tests.py:570–595

(self)

class TestUncertainties(unittest.TestCase):

    def test_classifier_uncertainty(self):
        test_cases = (Test(p * np.ones(shape=(k, l)), (1 - p) * np.ones(shape=(k, )))
                      for k in range(1, 100) for l in range(1, 10) for p in np.linspace(0, 1, 11))
        for case in test_cases:
            # testing _proba_uncertainty
            np.testing.assert_almost_equal(
                modAL.uncertainty._proba_uncertainty(case.input),
                case.output
            )

            # fitted estimator
            fitted_estimator = mock.MockEstimator(
                predict_proba_return=case.input)
            np.testing.assert_almost_equal(
                modAL.uncertainty.classifier_uncertainty(
                    fitted_estimator, np.random.rand(10)),
                case.output
            )

            # not fitted estimator
            not_fitted_estimator = mock.MockEstimator(fitted=False)
            np.testing.assert_almost_equal(
                modAL.uncertainty.classifier_uncertainty(
                    not_fitted_estimator, case.input),
                np.ones(shape=(len(case.output)))
            )

    def test_classifier_margin(self):
        test_cases_1 = (Test(p * np.ones(shape=(k, l)), np.zeros(shape=(k,)))