def test_delta_variance(self):
"""Tests if delta variance is correctly computed.
"""
S = self.S_2x3
C = self.C_2x2
D = self.D_2x3
ridge_factor = self.ridge_factor_05
sigma = self.sigma_05
a = self.a_1
crkr = CrKr(S, C, D, ridge_factor, sigma, a)
new_s = np.array([[1, 1, 1]])
k = crkr._compute_k(new_s)
K = crkr._compute_K()
expected_dv = (a + ridge_factor -
np.dot(k.T, np.dot(npla.inv(K + ridge_factor * C), k)))
assert_true(np.allclose(expected_dv, crkr._delta_variance(k, K)))
def test_delta_variance(self):
"""Tests if delta variance is correctly computed.
"""
S = self.S_2x3
C = self.C_2x2
D = self.D_2x3
ridge_factor = self.ridge_factor_05
sigma = self.sigma_05
a = self.a_1
crkr = CrKr(S, C, D, ridge_factor, sigma, a)
new_s = np.array([[1, 1, 1]])
k = crkr._compute_k(new_s)
K = crkr._compute_K()
expected_dv = (a +
ridge_factor -
np.dot(k.T, np.dot(npla.inv(K + ridge_factor * C), k)))
assert_true(np.allclose(expected_dv, crkr._delta_variance(k, K)))
