d618fe57e23d798f27aed8a50025811823ab0bd2,tests/gpflow/likelihoods/test_heteroskedastic_constant_variance.py,Data,Data_1,#,29

Before Change

    // single "GP" (for the mean):
    f_mean = rng.randn(N, 1)
    f_var = rng.randn(N, 1) ** 2  // ensure positivity
    equivalent_f2 = np.log(g_var)
    f2_mean = np.full((N, 1), equivalent_f2)
    f2_var = np.zeros((N, 1))
    F2_mean = np.c_[f_mean, f2_mean]
    F2_var = np.c_[f_var, f2_var]

After Change

    // single "GP" (for the mean):
    f_mean = rng.randn(N, 1)
    f_var = rng.randn(N, 1) ** 2  // ensure positivity
    equivalent_f2 = np.log(g_var) / 2
    f2_mean = np.full((N, 1), equivalent_f2)
    f2_var = np.zeros((N, 1))
    F2_mean = np.c_[f_mean, f2_mean]
    F2_var = np.c_[f_var, f2_var]

Instances