prob_data.setup()
state = State(prob_data)
matrices = SpatialD(state)
# We apply the power iteration to the **cmfd** matrices
solver = Solver(state, matrices)
x0 = np.random.rand(prob_data.n_dofs) + 1. #fill(1.0,n)
tolerance = 1.e-10
max_it = 1000
solver.power_iteration(x0,tolerance,max_it)
state.plot(color='blue')
#plt.plot(prob_data.x, phi_fmfd, 'o', color='red' , linewidth=3.0,linestyle='--')
#plt.plot(prob_data.x, phi_cmfd, 'x', color='blue', linewidth=3.0,linestyle='--')
#plt.legend(["phi_1 CMFD"], loc="upper left")
#plt.show()
#plt.savefig('figures/CMFD.png', bbox_inches='tight')
#
# # phi_ref = sin(x*pi/L)/norm(sin(x*pi/L))
# # plot(x, phi_ref, color="black", linewidth=1.0, linestyle="-")
