theta_idx - 1) * D_HEIGHT + z_idx
return region_number
if __name__ == "__main__":
stl_base = "G:\\My Drive\\Project\\HW-9232 Registration method for edentulous" \
"\\Edentulous registration error analysis\\Typodont_scan\\Edentulous_scan\\"
all_regions = []
file = stl_base + 'full_arch.txt'
if os.path.isfile(file):
print('read txt')
full_region = Yomiread.read_csv(file, 3, -1)
else:
stl_file = 'full_arch.stl'
print('read stl')
full_region = region_points.read_regions(stl_base + stl_file,
voxel_size=0.05)
Yomiwrite.write_csv_matrix(stl_base + 'full_arch.txt', full_region)
base = "G:\\My Drive\\Project\\HW-9232 Registration method for edentulous" \
"\\Edentulous registration error analysis\\Stage2_more_regions\\"
target_measurement_file = "targets.txt"
points = Yomiread.read_csv(base + target_measurement_file, 4, 10, flag=1)
targets_original = points[0:4, 1:4]
arch1 = edentulous_arch.Edentulous_arch(full_region, targets_original)
print('angle range is', arch1.target_angle_range)
print('target position is',
arch1.target_origins_cylindrical[:, 1] * 180 / np.pi)
# Set up simulation conditions
D_ANGLE = 3
BIAS_ERROR_FLAG = 0
ORIENTATION = 1
stl_base = "G:\\My Drive\\Project\\HW-9232 Registration method for edentulous\\Edentulous registration error analysis\\Typodont_scan\\Edentulous_scan\\"
all_regions = []
for i in range(5):
file = stl_base + 'region_points_' + np.str(i+1) + '.txt'
if os.path.isfile(file):
print('read txt')
individual_region = Yomiread.read_csv(file,3,-1)
else:
stl_file = 'Fiducial_region_' + np.str(i+1) + '.stl'
print('read stl')
individual_region = region_points.read_regions(stl_base + stl_file, voxel_size = 2.0)
Yomiwrite.write_csv_matrix(stl_base + 'region_points_' + np.str(i + 1) + '.txt', individual_region)
all_regions.append(individual_region)
for i in range(len(all_regions)):
value_95 = []
fiducials_new = np.copy(fiducials_original)
mm = 0
for point in all_regions[i]:
print('checking point ', mm + 1)
fiducials_new[i,:] = point
#print('fiducials are ', fiducials_new)
value_95_tem = check_tre(targets_original, fiducials_new)
value_95.append(value_95_tem)
if np.ndim(targets_original) == 1:
if (value_95_tem < THRESHOLD_0):