R33b = -(dns.wb*utau)**2
R12b = -dns.uv*utau*utau
f = interp1d(ydns, ub)
qtarget[::6] = f(eqn.y)
f = interp1d(ydns, R11b)
qtarget[1::6] = f(eqn.y)
f = interp1d(ydns, R12b)
qtarget[2::6] = f(eqn.y)
f = interp1d(ydns, R22b)
qtarget[3::6] = f(eqn.y)
f = interp1d(ydns, R33b)
qtarget[4::6] = f(eqn.y)
if restart:
eqn.beta = np.loadtxt("beta").astype(np.complex)
else:
eqn.beta[:] = 1.0
beta_prior = np.ones_like(eqn.beta)
sigma_obs = 1e-10
sigma_prior = 1.0
if objective[0] == "ALL":
eqn.objective = BayesianObjectiveAll(qtarget, beta_prior, sigma_obs, sigma_prior)
elif objective[0] == "U":
eqn.objective = BayesianObjectiveU(qtarget, beta_prior, sigma_obs, sigma_prior)
else:
raise ValueError("Objective function not defined!")
inverse_solver = InverseSolver(eqn)
