experiment_list_filename = join(path, "experiments.json")
if len(sys.argv) > 1:
nproc = int(sys.argv[1])
else:
nproc = 1
print("Reading Experiments")
from math import pi
experiments = ExperimentListFactory.from_json_file(
experiment_list_filename)
profile_model = ProfileModelList()
profile_model.append(
ProfileModel(n_sigma=3,
sigma_b=0.024 * pi / 180,
sigma_m=0.044 * pi / 180))
print("Predicting Reflections")
rlist = flex.reflection_table.from_predictions(experiments[0])
rlist["id"] = flex.int(len(rlist), 0)
rlist.compute_bbox(experiments, profile_model)
rlist.compute_zeta_multi(experiments)
rlist.compute_d(experiments)
print("")
print("Creating params")
from dials.algorithms.integration.integrator import IntegratorFactory
from dials.algorithms.integration.integrator import phil_scope
from libtbx import phil
path = '/home/upc86896/Data/Data/i04-BAG-training/dials_processed/'
experiment_list_filename = join(path, "experiments.json")
if len(sys.argv) > 1:
nproc = int(sys.argv[1])
else:
nproc = 1
print "Reading Experiments"
from math import pi
experiments = ExperimentListFactory.from_json_file(experiment_list_filename)
profile_model = ProfileModelList()
profile_model.append(ProfileModel(
n_sigma=3,
sigma_b=0.024*pi/180,
sigma_m=0.044*pi/180))
print "Predicting Reflections"
rlist = flex.reflection_table.from_predictions(experiments[0])
rlist['id'] = flex.int(len(rlist), 0)
rlist.compute_bbox(experiments, profile_model)
rlist.compute_zeta_multi(experiments)
rlist.compute_d(experiments)
print ""
print "Creating params"
from dials.algorithms.integration.integrator import IntegratorFactory
from dials.algorithms.integration.integrator import phil_scope
from libtbx import phil
