def __init__(self, kernel_type, projection=False, **params):
self.kernel_type = kernel_type
self.projection = projection
self.params_keys = set(params.keys())
self.__check_args_coherence()
# Sampling
self.sampling_mode = 'GS' # Gram-Schmidt
self.list_of_samples = []
# when using .sample_k_dpp_*
self.size_k_dpp = None
self.E_poly = None # evaluation of the
# Attributes relative to K correlation kernel:
# K, K_eig_vals, K_eig_vecs, A_zono
self.K = is_symmetric(params.get('K', None))
if self.projection:
self.K = is_projection(self.K)
e_vals, e_vecs = params.get('K_eig_dec', [None, None])
if self.projection:
self.K_eig_vals = is_equal_to_O_or_1(e_vals)
else:
self.K_eig_vals = is_in_01(e_vals)
self.eig_vecs = is_orthonormal(e_vecs)
self.A_zono = is_full_row_rank(params.get('A_zono', None))
# Attributes relative to L likelihood kernel:
# L, L_eig_vals, L_eig_vecs, L_gram_factor, L_dual, L_dual_eig_vals, L_dual_eig_vecs
self.L = is_symmetric(params.get('L', None))
if self.projection:
self.L = is_projection(self.L)
e_vals, e_vecs = params.get('L_eig_dec', [None, None])
if self.projection:
self.L_eig_vals = is_equal_to_O_or_1(e_vals)
else:
self.L_eig_vals = is_geq_0(e_vals)
if self.eig_vecs is None: # K_eig_vecs = L_eig_vecs
self.eig_vecs = is_orthonormal(e_vecs)
# L' "dual" likelihood kernel, L' = Phi Phi.T, Phi = L_gram_factor
self.L_gram_factor = params.get('L_gram_factor', None)
self.L_dual = None
self.L_dual_eig_vals = None
self.L_dual_eig_vecs = None
if self.L_gram_factor is not None:
Phi = self.L_gram_factor
d, N = Phi.shape
if d < N:
self.L_dual = Phi.dot(Phi.T)
print('L_dual = Phi Phi.T was computed: Phi (dxN) with d<N')
else:
if self.L is None:
self.L = Phi.T.dot(Phi)
print('L = Phi.T Phi was computed: Phi (dxN) with d>=N')
def test_orthonormal(self):
N, rank = 30, 10
X = rndm.randn(N, rank)
eig_vecs, _ = qr(X, mode="economic")
self.assertTrue(np.allclose(utils.is_orthonormal(eig_vecs), eig_vecs))
with self.assertRaises(ValueError) as context:
utils.is_orthonormal(X)
self.assertTrue('M.T M != I' in str(context.exception))