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)