'maxiter': 300,
'disp': True
})
# Results Of Minimization
yh = Function(W)
yh.vector()[:] = res.x
uh = solve_supg(V, bcs, epsilon, b, c, f, yh)
res_phi = phi(yh.vector())
one = project(1., V)
area = assemble(one * dx)
h_average = assemble(h * dx) / area
error_function = Function(V, assemble(abs(uh - u_exact) * v * dx))
l2_norm_of_error = norm(error_function, 'l2')
global_result = {
'V_dofs': V.dofmap().global_dimension(),
'W_dofs': W.dofmap().global_dimension(),
'phi': res_phi,
'phi_30': phi_30,
'h': h_average,
'error_l2': l2_norm_of_error
}
global_results.append(global_result)
rs.make_results('RESULTS/' + str(SC_EXAMPLE) + 'indLim', NUM_CELL, V, W,
uh, u_exact, yh, res_phi, results)
# Global results
rs.make_global_results('RESULTS/' + str(SC_EXAMPLE) + 'indLim', global_results)
]) # ! possible division by 0
# Basic Definitions
p = 1 # Constant(V.ufl_element().degree())
tau = compute_tau(W, h, p, epsilon, b)
uh = solve_supg(V, bcs, epsilon, b, c, f, tau)
tau2 = compute_sold_tau_codina(uh, 0.7, W, h, epsilon, b, c, f)
uh = solve_sold(V, bcs, epsilon, b, b_perp, c, f, tau, tau2)
one = project(1., V)
area = assemble(one * dx)
h_average = assemble(h * dx) / area
error_function = Function(V, assemble(abs(uh - u_exact) * v * dx))
l2_norm_of_error = norm(error_function, 'l2')
global_result = {
'V_dofs': V.dofmap().global_dimension(),
'W_dofs': W.dofmap().global_dimension(),
'phi': 1.,
'phi_30': 1.,
'h': h_average,
'error_l2': l2_norm_of_error
}
global_results.append(global_result)
results = []
rs.make_results(SC_EXAMPLE, NUM_CELL, V, W, uh, u_exact, tau, 1., results)
# Global results
rs.make_global_results(SC_EXAMPLE, global_results)