def phi_spacing(labelit_log):
beam, lattice, metric, cell, image = rj_parse_labelit_log_file(labelit_log)
template, directory = rj_get_template_directory(image)
images = rj_find_matching_images(image)
phi = rj_get_phi(image)
if lattice == 'aP':
raise RuntimeError, 'triclinic lattices useless'
# then copy the dataset_preferences.py somewhere safe
if os.path.exists('dataset_preferences.py'):
shutil.copyfile('dataset_preferences.py',
'dataset_preferences.bak')
# write out a dataset preferences file
fout = open('dataset_preferences.py', 'w')
fout.write('beam = (%f, %f)\n' % beam)
fout.write('wedgelimit = 3\n')
fout.write('beam_search_scope = 1.0\n')
fout.close()
# generate the list of phi values...
phis = [float(j + 1) for j in range(5, 45)]
image_numbers = []
for p in phis:
result = calculate_images(images, phi, p)
if not result in image_numbers:
image_numbers.append(result)
# now run labelit with phi spacing 6-45
metrics = []
spacings = []
for i_n in image_numbers:
spacing = phi * (i_n[2] - i_n[1])
image_names = [rj_image_name(template, directory, i) for i in i_n]
output = rj_run_job('labelit.screen --index_only',
image_names, [])
b, l, m, c, i = rj_parse_labelit_log(output)
if l != lattice:
raise RuntimeError, 'incorrect result with %d images' % (count + 1)
metrics.append(m)
spacings.append(spacing)
if os.path.exists('dataset_preferences.bak'):
shutil.copyfile('dataset_preferences.bak', 'dataset_preferences.py')
return metrics, spacings
def no_images(labelit_log):
# first parse this
beam, lattice, metric, cell, image = rj_parse_labelit_log_file(labelit_log)
template, directory = rj_get_template_directory(image)
images = rj_find_matching_images(image)
phi = rj_get_phi(image)
if lattice == 'aP':
raise RuntimeError, 'triclinic lattices useless'
# then copy the dataset_preferences.py somewhere safe
if os.path.exists('dataset_preferences.py'):
shutil.copyfile('dataset_preferences.py',
'dataset_preferences.bak')
# write out a dataset preferences file
fout = open('dataset_preferences.py', 'w')
fout.write('beam = (%f, %f)\n' % beam)
fout.write('wedgelimit = 15\n')
fout.write('beam_search_scope = 1.0\n')
fout.close()
# now run labelit with 1 - 15 images
metrics = []
times = []
for count in range(15):
result = calculate_images(images, phi, count + 1)
image_names = [rj_image_name(template, directory, i) for i in result]
t0 = time.time()
output = rj_run_job('labelit.screen --index_only',
image_names, [])
t1 = time.time()
times.append((t1 - t0))
b, l, m, c, i = rj_parse_labelit_log(output)
if l != lattice:
raise RuntimeError, 'incorrect result with %d images' % (count + 1)
metrics.append(m)
if os.path.exists('dataset_preferences.bak'):
shutil.copyfile('dataset_preferences.bak', 'dataset_preferences.py')
return metrics, times
