def test_gaussian_kernel_same_state(self):
"""Tests if the gaussian kernel is 1 for two equal states.
"""
crkr = CrKr(self.S_2x3, self.C_2x2, self.D_2x3)
s = np.array([[1, 2, 3]])
assert_equal(1, crkr._gaussian_kernel(s, s))
def test_gaussian_kernel_same_state(self):
"""Tests if the gaussian kernel is 1 for two equal states.
"""
crkr = CrKr(self.S_2x3, self.C_2x2, self.D_2x3)
s = np.array([[1, 2, 3]])
assert_equal(1, crkr._gaussian_kernel(s, s))
def test_gaussian_kernel(self):
"""Tests if the gaussian kernel is correctly computed.
"""
crkr = CrKr(self.S_2x3, self.C_2x2, self.D_2x3,
self.ridge_factor_05, self.sigma_05, self.a_1)
s1 = np.array([[1, 2, 3]])
s2 = np.array([[4, 5, 6]])
expected_gk = np.exp(-(self.a_1 * np.power(npla.norm(s1 - s2), 2) /
(2 * (self.sigma_05 ** 2))))
assert_equal(expected_gk, crkr._gaussian_kernel(s1, s2))
def test_gaussian_kernel(self):
"""Tests if the gaussian kernel is correctly computed.
"""
crkr = CrKr(self.S_2x3, self.C_2x2, self.D_2x3, self.ridge_factor_05,
self.sigma_05, self.a_1)
s1 = np.array([[1, 2, 3]])
s2 = np.array([[4, 5, 6]])
expected_gk = np.exp(-(self.a_1 * np.power(npla.norm(s1 - s2), 2) /
(2 * (self.sigma_05**2))))
assert_equal(expected_gk, crkr._gaussian_kernel(s1, s2))
