def integrate_cctbx(self, tag, grid_point=0, single_image=False):
""" Runs integration using the Integrator class """
# Check to see if the image is suitable for grid search / integration
if self.fail != None:
self.grid = []
self.final['final'] = None
else:
from prime.iota.iota_cctbx import Integrator
integrator = Integrator(self.conv_img,
self.fin_file,
self.params.cctbx.selection.min_sigma,
self.params.target,
self.params.analysis.charts,
self.viz_path,
self.int_log,
tag,
self.tmp_base,
self.gain,
single_image)
if tag == 'grid search':
self.log_info.append('\nCCTBX grid search:')
for i in range(len(self.grid)):
int_results = integrator.integrate(self.grid[i])
self.grid[i].update(int_results)
img_filename = os.path.basename(self.conv_img)
log_entry ='{:<{width}}: S = {:<3} H = {:<3} ' \
'A = {:<3} ---> {}'.format(img_filename,
self.grid[i]['sih'],
self.grid[i]['sph'],
self.grid[i]['spa'],
self.grid[i]['info'],
width = len(img_filename) + 2)
self.log_info.append(log_entry)
self.gs_results.append(log_entry)
# Throw out grid search results that yielded no integration
self.grid = [i for i in self.grid if "not integrated" not in i['info'] and\
"no data recorded" not in i['info']]
self.status = 'grid search'
# Throw out grid search results that yielded no integration
self.grid = [i for i in self.grid if "not integrated" not in i['info'] and\
"no data recorded" not in i['info']]
self.status = 'grid search'
elif tag == 'split grid':
self.log_info.append('\nCCTBX grid search:')
int_results = integrator.integrate(self.grid[grid_point])
self.grid[grid_point].update(int_results)
img_filename = os.path.basename(self.conv_img)
log_entry ='{:<{width}}: S = {:<3} H = {:<3} ' \
'A = {:<3} ---> {}'.format(img_filename,
self.grid[grid_point]['sih'],
self.grid[grid_point]['sph'],
self.grid[grid_point]['spa'],
self.grid[grid_point]['info'],
width = len(img_filename) + 2)
self.log_info.append(log_entry)
self.gs_results.append(log_entry)
elif tag == 'integrate':
self.log_info.append('\nCCTBX final integration:')
final_results = integrator.integrate(self.final)
self.final.update(final_results)
self.status = 'final'
img_filename = os.path.basename(self.conv_img)
log_entry ='{:<{width}}: S = {:<3} H = {:<3} ' \
'A = {:<3} ---> {}'.format(img_filename,
self.final['sih'],
self.final['sph'],
self.final['spa'],
self.final['info'],
width = len(img_filename) + 2)
self.log_info.append(log_entry)
if self.params.analysis.viz == 'integration':
viz.make_png(self.final['img'], self.final['final'], self.viz_file)
elif self.params.analysis.viz == 'cv_vectors':
viz.cv_png(self.final['img'], self.final['final'], self.viz_file)
# Save image object to file
ep.dump(self.obj_file, self)
return self
