# Load the final step
filename = resultspath + ('/mf_%d.mf' % (NT))
m = gf.Mesh('load', filename)
mf_u = gf.MeshFem('load', filename, m)
filename = resultspath + ('/U_%d.dat' % (NT))
U = np.loadtxt(filename)
# Load the reference solution
m_ref = gf.Mesh('load', refname_mf)
mf_u_ref = gf.MeshFem('load', refname_mf, m_ref)
U_ref = np.loadtxt(refname_U)
mim_ref = gf.MeshIm(m_ref, 6)
# Estimate of the difference in L2 and H1 norms
Ui = gf.compute_interpolate_on(mf_u, U, mf_u_ref)
norm_L2 = gf.compute_L2_norm(mf_u_ref, U_ref, mim_ref)
err_L2 = gf.compute_L2_dist(mf_u_ref, Ui, mim_ref,
mf_u_ref, U_ref)
norm_H1 = gf.compute_H1_semi_norm(mf_u_ref, U_ref, mim_ref)
norm_H1 = np.sqrt(pow(norm_L2, 2) + pow(norm_H1, 2))
err_H1 = gf.compute_H1_semi_dist(mf_u_ref, Ui, mim_ref,
mf_u_ref, U_ref)
print 'Error in L2 norm: %g' % err_L2
print 'Error in H1 semi-norm: %g' % err_H1
errors1[option, i, 0] = err_L2 / norm_L2
errors1[option, i,
1] = np.sqrt(pow(err_H1, 2) + pow(err_L2, 2)) / norm_H1
# Store the result
np.savetxt(resname, errors1.reshape(errors1.size))
E = (np.vdot(MMV0, V0) + np.vdot(KU0, U0)) * 0.5
E_org = E
if (version == 2): # Energy stored in the penalized contact
E += (gamma0_P / h) * pow(min(0., U0[0]), 2) / 2
if (version == 3): # Nitsche Energy
E += (0.5 * theta_N) * (h / gamma0_N) * (s0 * s0 - ux * ux)
# Store the data to be ploted at the end
store_u0[nit] = U0[0]
store_u0_ex[nit] = uExact(0., t)
store_v0[nit] = V0[0]
store_v0_ex[nit] = uExact(0., t, 2)
store_s0[nit] = s0
store_s0_ex[nit] = uExact(0., t, 1)
store_E[nit] = E
store_VL2_ex[nit] = gf.compute_L2_norm(mfu, Vex, mim)
store_UL2_ex[nit] = gf.compute_L2_norm(mfu, Uex, mim)
store_UH1_ex[nit] = gf.compute_H1_norm(mfu, Uex, mim)
store_VL2[nit] = gf.compute_L2_norm(mfu, V0 - Vex, mim)
store_UL2[nit] = gf.compute_L2_norm(mfu, U0 - Uex, mim)
store_UH1[nit] = gf.compute_H1_norm(mfu, U0 - Uex, mim)
# Draw the approximated and exact solutions
if (t >= tplot - (1e-10)):
tplot += dtplot
print(("Time %3f" % t), "/", T, end=' ')
print((" Energy %7f" % E), (" Mech energy %7f" % E_org))
if (do_inter_plot):
UUex = np.copy(Xdraw)
plt.figure(1)
curl_testb_curl_b_exp = '({L}).({M})'.format(L=CURL_VAR_.format(var='Test_b'),
M=CURL_VAR_.format(var='b'))
cross_jump_a = JUMP_VPRODUCT_VAR_.format(var='a')
cross_jump_test_a = JUMP_VPRODUCT_VAR_.format(var='Test_a')
jump_a = JUMP_VVAR_N_.format(v='a')
jump_test_a = JUMP_VVAR_N_.format(v='Test_a')
#magentec potential model
mdmag = gf.Model('real')
######################################################################################################################
#Interpolate and export exact fields
intonme = mfb
CurlBexact = mdmag.interpolation(CurlBexact_exp, intonme)
intonme.export_to_vtk('curl_exact3d.vtk', 'ascii', CurlBexact)
print('exact curl B norm l2', gf.compute_L2_norm(intonme, CurlBexact, mim))
Bexact = mdmag.interpolation(Bexact_exp, intonme)
intonme.export_to_vtk('field_exact3d.vtk', 'ascii', Bexact)
print('exact B norm l2', gf.compute_L2_norm(intonme, Bexact, mim))
#Interpolate and export exact fields END
######################################################################################################################
WITH_B_CROSS_N = True
# Main potential unknown
mdmag.add_fem_variable('b', mfb)
# lagrange augmentation unknown for potential
mdmag.add_fem_variable('p', mfdiv_mult)
tm = time.time()
# building (curl b, curl \tau) term