def find_closest_points_on_cylinder(elc1, elc2, threshold, output_fol,
error_radius):
(electrodes, names, hemis, threshold) = utils.load(
op.join(output_fol, '{}_electrodes.pkl'.format(int(threshold))))
elc_ind1, elc_ind2 = names.index(elc1), names.index(elc2)
_, cylinder, _ = fect.points_in_cylinder(electrodes[elc_ind1],
electrodes[elc_ind2], electrodes,
error_radius)
points_inside_cylinder, too_close_points, dists, dists_to_cylinder = \
fect.find_group_between_pair(elc_ind1, elc_ind2, electrodes, error_radius, min_distance)
fect.find_closest_points_on_cylinder(electrodes, points_inside_cylinder,
cylinder)
def test4(ct_data):
voxel1 = np.array([102, 99, 131])
voxel2 = np.array([104, 102, 131])
points = np.array(
list(product(*[range(voxel1[k], voxel2[k] + 1) for k in range(3)])))
inds, _, _ = fect.points_in_cylinder(voxel1,
voxel2,
points,
1,
metric='cityblock')
path = points[inds]
diffs = [pt2 - pt1 for pt1, pt2 in zip(path[:-1], path[1:])]
path = path[[np.all(d >= 0) for d in diffs]]
path_ct_data = [ct_data[tuple(p)] for p in path]
print(path)
def calc_dist_on_cylinder(elc1, elc2, threshold, output_fol, error_radius):
(electrodes, names, hemis, threshold) = utils.load(
op.join(output_fol, '{}_electrodes.pkl'.format(int(threshold))))
elc_ind1, elc_ind2 = names.index(elc1), names.index(elc2)
groups, noise = utils.load(
op.join(output_fol, '{}_groups.pkl'.format(int(threshold))))
groups_mask = [(elc_ind1 in g) for g in groups]
if sum(groups_mask) == 1:
group = [g for g, m in zip(groups, groups_mask) if m][0]
print('Electrodes belongs to {}-{}'.format(names[group[0]],
names[group[1]]))
else:
print('No group was found!')
return
_, cylinder, _ = fect.points_in_cylinder(electrodes[group[0]],
electrodes[group[-1]], electrodes,
error_radius)
closest_points = fect.find_closest_points_on_cylinder(
electrodes, [elc_ind1, elc_ind2], cylinder)
dist = np.linalg.norm(closest_points[0] - closest_points[1])
print(dist)