def test_intrinsic_dim_mle_levina(self): """Test against value calc. by matlab reference implementation.""" _, _, vector = load_dexter() ID_MLE_REF = 74.742 id_mle = intrinsic_dimension(vector, k1=6, k2=12, estimator='levina', metric='vector', trafo=None) return self.assertEqual(id_mle, int(ID_MLE_REF))
def test_intrinsic_dim_mle_levina_low_memory(self): """ Same as above, but invoking the speed-memory trade-off. """ _, _, vector = load_dexter() ID_MLE_REF = 74.742 id_mle = intrinsic_dimension(vector, 6, 12, 'levina', 'vector', None, mem_threshold=0) return self.assertEqual(id_mle, int(ID_MLE_REF))
def test_load_dexter(self): """Loading dexter, checking shape of distances, labels, vectors""" self.dist, self.lab, self.vect = load_dexter() symm_dist_shape = self.dist.shape[0] == self.dist.shape[1] corr_dist_shape = self.dist.shape[0] == self.vect.shape[0] corr_label_shape = self.lab.shape[0] == self.vect.shape[0] return self.assertTrue( symm_dist_shape == corr_dist_shape == corr_label_shape)