def refine(self, exps, ref, refining_predictions=False, best=None):
exps_out = exps
if not self.params.skip_hopper:
if self.params.dispatch.refine:
print("WARNING: hopper_process will always run its own refinement, ignoring dials.refine phil scope")
self.params.dispatch.refine = False
assert len(exps) == 1
if self.params.reidx_obs:
exps, ref = self._reindex_obs(exps, self.observed)
exp, ref, self.stage1_modeler, x = hopper_utils.refine(exps[0], ref,
self.params.diffBragg,
spec=self.params.refspec,
gpu_device=self.device_id, return_modeler=True, best=best)
orig_exp_name = os.path.abspath(self.params.output.refined_experiments_filename)
refls_name = os.path.abspath(self.params.output.indexed_filename)
self.params.diffBragg.outdir = self.params.output.output_dir
# TODO: what about composite mode ?
self.stage1_df = save_to_pandas(x, self.stage1_modeler.SIM, orig_exp_name, self.params.diffBragg,
self.stage1_modeler.E, 0, refls_name, None)
exps_out = ExperimentList()
exps_out.append(exp)
basename = os.path.splitext(os.path.basename(refls_name))[0]
self._save_modeler_info(basename)
return super(Hopper_Processor, self).refine(exps_out, ref)
def tst_ds1(idx, frame_params):
print("in tst_diffbragg_stage_1")
from libtbx.phil import parse
from simtbx.diffBragg.phil import philz
from simtbx.diffBragg.phil import hopper_phil
philz = hopper_phil + philz
phil_scope_db = parse(philz)
user_phil = parse(ds1_params)
working_phil = phil_scope_db.fetch(sources=[user_phil])
params = working_phil.extract()
#import logging
#logging.disable(level=logging.CRITICAL)
#logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
from simtbx.diffBragg import hopper_utils
BERNINA = os.environ.get("BERNINA")
#params.fix.detz_shift = True
print ("hopper",flush=True)
try:
exp, ref, data_modeler, x = hopper_utils.refine(
exp=os.path.join(BERNINA, "split_cs", "split_%04d.expt"%idx),
ref = os.path.join(BERNINA, "split2b" , "split_%04d.refl"%idx),
params=params, return_modeler=True)
print("1",flush=True)
scale, rotX, rotY, rotZ, Na, Nb, Nc,diff_gam_a, diff_gam_b, diff_gam_c, diff_sig_a, diff_sig_b, diff_sig_c, a,b,c,al,be,ga, detz = hopper_utils.get_param_from_x(x,data_modeler.SIM)
print("The parameters are\n",scale, rotX, rotY, rotZ, Na, Nb, Nc,diff_gam_a, diff_gam_b, diff_gam_c, diff_sig_a, diff_sig_b, diff_sig_c, a,b,c,al,be,ga, detz)
except Exception as e:
print("CATCH EXCEPTION",e)
traceback.print_tb(e.__traceback__)
def thin_ds1(idx, frame_params):
from libtbx.phil import parse
from simtbx.diffBragg.phil import philz
from simtbx.diffBragg.phil import hopper_phil
philz = hopper_phil + philz
phil_scope_db = parse(philz)
from LS49.adse13_187.report_versions import ds1_params_v4 as ds1_params
user_phil = parse(ds1_params)
working_phil = phil_scope_db.fetch(sources=[user_phil])
params = working_phil.extract()
from simtbx.diffBragg import hopper_utils
BERNINA = os.environ.get("BERNINA")
try:
exp, ref, data_modeler, x = hopper_utils.refine(
exp=os.path.join(BERNINA, "split_cs", "split_%04d.expt"%idx),
ref = os.path.join(BERNINA, "split2b" , "split_%04d.refl"%idx),
params=params, return_modeler=True)
(scale, rotX, rotY, rotZ, Na, Nb, Nc,
diff_gam_a, diff_gam_b, diff_gam_c, diff_sig_a, diff_sig_b, diff_sig_c,
a,b,c,al,be,ga, detz) = hopper_utils.get_param_from_x(x,data_modeler.SIM)
from dxtbx.model.experiment_list import ExperimentList
L = ExperimentList()
L.append(exp)
L.as_file("ds1_%04d.expt"%idx)
print("DS1 parameters index %d Na Nb Nc %.3f %.3f %.3f"%(idx,Na,Nb,Nc))
from LS49.adse13_187.adse13_221.basic_runner import run as basic_run
anaparams = mcmc_runner_parse_input()
anaparams.trusted_mask=os.path.join(BERNINA, "trusted_Py3.mask")
anaparams.cryst="ds1_%04d.expt"%idx
anaparams.expt = os.path.join(BERNINA, "split_cs", "split_%04d.expt"%idx)
anaparams.refl=os.path.join(BERNINA, "split2b" , "split_%04d.refl"%idx)
anaparams.output.enable=False
anaparams.output.label="mcmc3"
anaparams.output.index=idx
anaparams.model.mosaic_spread.value=0.001
anaparams.model.Nabc.value=(Na,Nb,Nc)
anaparams.model.Nabc.hyperparameter=0.8
anaparams.model.rot.refine=True
anaparams.model.cell.covariance=os.path.join(
BERNINA,"..", "covariance_cytochrome_form.pickle")
anaparams.simplex.cycles=200
anaparams.mcmc.cycles=2000
anaparams.model.plot=False
print(anaparams.trusted_mask)
print(anaparams.cryst)
print(anaparams.expt)
print(anaparams.refl)
print(anaparams.model.cell.covariance)
basic_run(anaparams)
except Exception as e:
print("CATCH EXCEPTION",e)
traceback.print_exc()
P.method = "L-BFGS-B"
P.ftol = 1e-10
if "eta" in args.perturb:
P.ftol = 1e-8
#P.method="Nelder-Mead"
#P.fix.G = True
#P.fix.Nabc =True
#P.fix.detz_shift=True
import logging
import sys
h = logging.StreamHandler(sys.stdout)
logging.basicConfig(level=logging.DEBUG, handlers=[h])
from simtbx.diffBragg import hopper_utils
Eopt, _, Mod, x = hopper_utils.refine(E, refls, P, return_modeler=True)
G, rotX, rotY, rotZ, Na, Nb, Nc, _, _, _, _, _, _, a, b, c, al, be, ga, detz_shift = hopper_utils.get_param_from_x(
x, Mod.SIM)
eta_abc_opt = hopper_utils.get_mosaicity_from_x(x, Mod.SIM)
print("Na, Nb, Nc= %f %f %f" % (Na, Nb, Nc))
print("eta_abc optimized:", eta_abc_opt)
# check crystal
Copt = Eopt.crystal
misset, misset_init = utils.compare_with_ground_truth(
*C.get_real_space_vectors(),
dxcryst_models=[Copt, E.crystal],
symbol=symbol)
print(misset_init, "init misset with ground truth")