def obtain_traubs_srcVele(conductivity, run_type='seeg', save=False):
'''Fetch the potentials for the default run - SEEG section For Traubs column'''
mesh = meshes.load_just_mesh()
if run_type == 'seeg':
pos_list, conductivity, path, sbspt = params.default_run(conductivity)
elif run_type == 'ecog':
pos_list, conductivity, path, sbspt = params.ecog_run(size=0.98)
elif run_type == 'heeg':
pos_list, conductivity, path, sbspt = params.hippo_eeg_run()
num_pts = len(pos_list)
ele_list = params.load_traubs_points() # points from traubs colum
num_ele = len(ele_list)
phi_mat = np.zeros((num_pts, num_ele))
num_proc = how_many_procs(path, sbspt)
proc_vals = np.linspace(0, num_pts, num_proc + 1).astype(int)
for kk in range(num_proc):
proc_idx = kk + 1 # as proc ids start from 1
pt_idxs = range(proc_vals[proc_idx - 1], proc_vals[proc_idx])
f_string = sbspt + str(num_proc) + '_' + str(proc_idx) + '.h5'
dump_file = load_file(os.path.join(path, f_string), mesh)
for pt in pt_idxs:
this_phi = load_vector(dump_file, mesh, str(pt))
phi_mat[pt, :] = extract_pots(this_phi, np.array(ele_list))
dump_file.close()
print('Finished processing proc number: ', proc_idx)
if save:
phi_mat_fname = sbspt + conductivity + '_' + run_type + '_traub_phi_mat.npy'
np.save(os.path.join(path, phi_mat_fname), phi_mat)
return
def test_few_points():
mesh = meshes.load_just_mesh()
pos_list = [[5.196, 22.913, -4.9957], [8.4, 31.4, -6.151],
[5.5945, 22.699, -5.6637]]
dump_file = load_file(os.path.join(params.results_path, 'test_del_ih.h5'),
mesh)
phi_1 = load_vector(dump_file, mesh, '0')
phi_2 = load_vector(dump_file, mesh, '1')
phi_3 = load_vector(dump_file, mesh, '2')
print(extract_pots(phi_1, np.array([pos_list[1], pos_list[2]])))
print(extract_pots(phi_2, np.array([pos_list[0], pos_list[2]])))
print(extract_pots(phi_3, np.array([pos_list[0], pos_list[1]])))
def obtain_orth_planes(src_label, orig_label, conductivity, save=False):
''' Sources placed at src_label, with orth planes meeting at orig_label
The pots observed at the corresponding xx, yy, zz planes is reported
- dumps an npz with arrays corres to orig_label corresp to each plane'''
mesh = meshes.load_just_mesh()
pos_list, conductivity, path, sbspt = params.default_run(conductivity)
sp_pts = params.load_special_points()
src_x, src_y, src_z = sp_pts[src_label]
xx, yy, zz = sp_pts[orig_label]
print('Testing if src location has exact probe point')
src_idx = find_nearest_avail_pt(pos_list, src_x, src_y, src_z)
k = np.array((pos_list[src_idx]))
dists = np.linalg.norm(pos_list - k, axis=1)
src_idx = np.argmin(dists)
f_string = which_file(path, sbspt, pos_list, src_idx)
dump_file = load_file(os.path.join(path, f_string), mesh)
this_phi = load_vector(dump_file, mesh, str(src_idx))
planes = fetch_cut_planes(xx, yy, zz, 0.1)
### TODO - FUTURE
### instead get this from params as a special planes
### Planes get dumped from probe_points file instead - so premtively obtain these planes.
phi_planes = []
# plane pots
for ii, label in enumerate(['x', 'y', 'z']):
ele_list = planes[ii]
num_ele = len(ele_list)
phi_mat = np.zeros((1, num_ele))
phi_mat[0, :] = extract_pots(this_phi, np.array(ele_list))
phi_planes.append(phi_mat)
dump_file.close()
if save:
phi_mat_fname = sbspt + conductivity + '_' + src_label + '_' + orig_label + '_phi_mat.npz'
np.savez(os.path.join(path, phi_mat_fname),
xx=phi_planes[0],
yy=phi_planes[1],
zz=phi_planes[2],
x_plane=planes[0],
y_plane=planes[1],
z_plane=planes[2])
return
def obtain_unsorted_srcVele(conductivity, save=False):
'''Fetch the potentials for the default run - SEEG section to test reciprocity'''
mesh = meshes.load_just_mesh()
pos_list, conductivity, path, sbspt = params.default_run(conductivity)
num_pts = len(pos_list)
phi_mat = np.zeros((num_pts, num_pts))
num_proc = how_many_procs(path, sbspt)
proc_vals = np.linspace(0, num_pts, num_proc + 1).astype(int)
for kk in range(num_proc):
proc_idx = kk + 1 # as proc ids start from 1
pt_idxs = range(proc_vals[proc_idx - 1], proc_vals[proc_idx])
f_string = sbspt + str(num_proc) + '_' + str(proc_idx) + '.h5'
dump_file = load_file(os.path.join(path, f_string), mesh)
for pt in pt_idxs:
this_phi = load_vector(dump_file, mesh, str(pt))
phi_mat[pt, :] = extract_pots(this_phi, np.array(pos_list))
dump_file.close()
print('Finished processing proc number: ', proc_idx)
if save:
phi_mat_fname = sbspt + conductivity + '_phi_mat.npy'
np.save(os.path.join(path, phi_mat_fname), phi_mat)
return
def compute_conductivity(conductivity, save=False):
print('Computing sigma tensor for case :', conductivity)
mesh = meshes.load_just_mesh()
cells_all = d.cells(mesh)
idx_out, idx_grnd, idx_csf, np_fa = params.load_barycenters_ids()
points_to_sample = params.load_barycenters()
idx_all = np.arange(len(points_to_sample))
if conductivity == 'anisotropic':
np_v1, np_v2, np_v3 = params.load_eigen_vectors()
longi_sigma = []
trans_sigma = []
for jj in idx_all:
longi_sigma.append(scale_gm_wm(np_fa[jj], sig_brain, sig_wm_long))
trans_sigma.append(scale_gm_wm(np_fa[jj], sig_brain, sig_wm_trans))
print 'Did the scaling, now assigning vals'
c00, c01, c02, c11, c12, c22 = tensor_components(mesh)
for jj in idx_all:
cell = cells_all.next()
if jj in idx_grnd: # Electrode
c00[cell] = sig_ele
c11[cell] = sig_ele
c22[cell] = sig_ele
c01[cell] = sig_zero
c02[cell] = sig_zero
c12[cell] = sig_zero
elif jj in idx_out: # Pt outside brain volume
c00[cell] = sig_air
c01[cell] = sig_zero
c02[cell] = sig_zero
c11[cell] = sig_air
c12[cell] = sig_zero
c22[cell] = sig_air
elif jj in idx_csf:
c00[cell] = sig_csf
c01[cell] = sig_zero
c02[cell] = sig_zero
c11[cell] = sig_csf
c12[cell] = sig_zero
c22[cell] = sig_csf
else:
sig_wm_matrix = np.zeros((3, 3))
np.fill_diagonal(
sig_wm_matrix,
(longi_sigma[jj], trans_sigma[jj], trans_sigma[jj]))
S = np.matrix((np_v1[jj], np_v2[jj], np_v3[jj]))
# This is correct. S is eigen vectors are row vectors
sigma_mat = np.around(S.T * sig_wm_matrix * S, decimals=4)
c00[cell] = sigma_mat[0, 0]
c11[cell] = sigma_mat[1, 1]
c22[cell] = sigma_mat[2, 2]
c01[cell] = sigma_mat[0, 1]
c02[cell] = sigma_mat[0, 2]
c12[cell] = sigma_mat[1, 2]
if save:
c00_file = d.File(
os.path.join(params.anis_path, "sigma_anis_d0.xml.gz"))
c01_file = d.File(
os.path.join(params.anis_path, "sigma_anis_d1.xml.gz"))
c02_file = d.File(
os.path.join(params.anis_path, "sigma_anis_d2.xml.gz"))
c11_file = d.File(
os.path.join(params.anis_path, "sigma_anis_d3.xml.gz"))
c12_file = d.File(
os.path.join(params.anis_path, "sigma_anis_d4.xml.gz"))
c22_file = d.File(
os.path.join(params.anis_path, "sigma_anis_d5.xml.gz"))
c00_file << c00
c01_file << c01
c02_file << c02
c11_file << c11
c12_file << c12
c22_file << c22
elif conductivity == 'inhomogeneous':
c = d.MeshFunction("double", mesh, 3)
fa_scaled_sigma = []
for jj in idx_all:
fa_scaled_sigma.append(scale_gm_wm(np_fa[jj], sig_brain, sig_wm))
print 'Did the scaling, now assigning vals'
for jj in idx_all:
cell = cells_all.next()
if jj in idx_grnd:
c[cell] = sig_ele
elif jj in idx_out:
c[cell] = sig_air
elif jj in idx_csf:
c[cell] = sig_csf
else:
c[cell] = fa_scaled_sigma[jj]
if save:
c00_file = d.File(
os.path.join(params.inhom_path, "sigma_inhom.xml.gz"))
c00_file << c
elif conductivity == 'homogeneous':
c = d.MeshFunction("double", mesh, 3)
for jj in idx_all:
cell = cells_all.next()
if jj in idx_grnd:
c[cell] = sig_ele
elif jj in idx_out:
c[cell] = sig_air
elif jj in idx_csf:
c[cell] = sig_csf
else:
c[cell] = sig_brain
if save:
c00_file = d.File(os.path.join(params.hom_path,
"sigma_hom.xml.gz"))
c00_file << c