bbox = [[-1, -1, -1], [1, 1, 1]]
# save calling convention as distmesh 2D
ms, el_pos = mesh.create(h0=0.15, bbox=bbox)
no2xy = ms['node']
el2no = ms['element']
# report the status of the 2D mesh
quality.stats(no2xy, el2no)
""" 1. FEM forward simulations """
# setup EIT scan conditions
el_dist, step = 7, 1
ex_mat = eit_scan_lines(16, el_dist)
# calculate simulated data
fwd = Forward(ms, el_pos)
# in python, index start from 0
ex_line = ex_mat[1].ravel()
# change alpha
anomaly = [{'x': 0.40, 'y': 0.40, 'z': 0.0, 'd': 0.30, 'alpha': 100.0}]
ms_test = mesh.set_alpha(ms, anomaly=anomaly, background=1.0)
tri_perm = ms_test['alpha']
node_perm = pdeprtni(no2xy, el2no, np.real(tri_perm))
# solving once using fem
f, _ = fwd.solve_once(ex_line, tri_perm)
f = np.real(f)
# mplot.tetplot(p, t, edge_color=(0.2, 0.2, 1.0, 1.0), alpha=0.01)
shading='flat',
cmap=plt.cm.viridis)
ax.set_title(r'$\Delta$ Conductivities')
fig.colorbar(im)
ax.axis('equal')
fig.set_size_inches(6, 4)
# fig.savefig('demo_bp_0.png', dpi=96)
plt.show()
""" 2. FEM forward simulations """
# setup EIT scan conditions
# adjacent stimulation (el_dist=1), adjacent measures (step=1)
el_dist, step = 1, 1
ex_mat = eit_scan_lines(16, el_dist)
# calculate simulated data
fwd = Forward(mesh_obj, el_pos)
f0 = fwd.solve_eit(ex_mat, step=step, perm=mesh_obj['perm'])
f1 = fwd.solve_eit(ex_mat, step=step, perm=mesh_new['perm'])
"""
3. naive inverse solver using back-projection
"""
eit = bp.BP(mesh_obj, el_pos, ex_mat=ex_mat, step=1, parser='std')
eit.setup(weight='none')
ds = 192.0 * eit.solve(f1.v, f0.v)
# plot
fig = plt.figure()
ax1 = fig.add_subplot(111)
im = ax1.tripcolor(pts[:, 0], pts[:, 1], tri, ds, cmap=plt.cm.viridis)
ax1.set_title(r'$\Delta$ Conductivities')
ax1.axis('equal')