def _scale_finish_chunk_8_raddam(self):
crd = CCP4InterRadiationDamageDetector()
crd.set_working_directory(self.get_working_directory())
crd.set_hklin(self._scalr_scaled_reflection_files['mtz'])
if self.get_scaler_anomalous():
crd.set_anomalous(True)
hklout = os.path.join(self.get_working_directory(), 'temp.mtz')
FileHandler.record_temporary_file(hklout)
crd.set_hklout(hklout)
status = crd.detect()
if status:
Chatter.write('')
Chatter.banner('Local Scaling %s' % self._scalr_xname)
for s in status:
Chatter.write('%s %s' % s)
Chatter.banner('')
else:
Debug.write('Local scaling failed')
def _do_indexing(self, method=None):
indexer = self.Index()
for spot_list in self._indxr_payload["spot_lists"]:
indexer.add_spot_filename(spot_list)
for datablock in self._indxr_payload["datablocks"]:
indexer.add_sweep_filename(datablock)
if PhilIndex.params.dials.index.phil_file is not None:
indexer.set_phil_file(PhilIndex.params.dials.index.phil_file)
indexer.set_max_cell(max_cell=PhilIndex.params.dials.index.max_cell,
max_height_fraction=PhilIndex.params.dials.index.
max_cell_estimation.max_height_fraction)
if PhilIndex.params.xia2.settings.small_molecule == True:
indexer.set_min_cell(3)
if PhilIndex.params.dials.fix_geometry:
indexer.set_detector_fix('all')
indexer.set_beam_fix('all')
indexer.set_close_to_spindle_cutoff(
PhilIndex.params.dials.close_to_spindle_cutoff)
if self._indxr_input_lattice:
indexer.set_indexer_input_lattice(self._indxr_input_lattice)
Debug.write('Set lattice: %s' % self._indxr_input_lattice)
if self._indxr_input_cell:
indexer.set_indexer_input_cell(self._indxr_input_cell)
Debug.write('Set cell: %f %f %f %f %f %f' % \
self._indxr_input_cell)
original_cell = self._indxr_input_cell
if method is None:
if PhilIndex.params.dials.index.method is None:
method = 'fft3d'
Debug.write('Choosing indexing method: %s' % method)
else:
method = PhilIndex.params.dials.index.method
FileHandler.record_log_file('%s INDEX' % self.get_indexer_full_name(),
indexer.get_log_file())
indexer.run(method)
if not os.path.exists(indexer.get_experiments_filename()):
raise RuntimeError(
"Indexing has failed: see %s for more details." %
indexer.get_log_file())
elif not os.path.exists(indexer.get_indexed_filename()):
raise RuntimeError("Indexing has failed: %s does not exist." %
indexer.get_indexed_filename())
report = self.Report()
report.set_experiments_filename(indexer.get_experiments_filename())
report.set_reflections_filename(indexer.get_indexed_filename())
html_filename = os.path.join(
self.get_working_directory(),
'%i_dials.index.report.html' % report.get_xpid())
report.set_html_filename(html_filename)
report.run()
FileHandler.record_html_file('%s INDEX' % self.get_indexer_full_name(),
html_filename)
return indexer
def _do_indexing(self, method=None):
indexer = self.Index()
for spot_list in self._indxr_payload["spot_lists"]:
indexer.add_spot_filename(spot_list)
for datablock in self._indxr_payload["datablocks"]:
indexer.add_sweep_filename(datablock)
if PhilIndex.params.dials.index.phil_file is not None:
indexer.set_phil_file(PhilIndex.params.dials.index.phil_file)
if PhilIndex.params.dials.index.max_cell:
indexer.set_max_cell(PhilIndex.params.dials.index.max_cell)
if PhilIndex.params.xia2.settings.small_molecule == True:
indexer.set_min_cell(3)
if PhilIndex.params.dials.fix_geometry:
indexer.set_detector_fix('all')
indexer.set_beam_fix('all')
indexer.set_close_to_spindle_cutoff(
PhilIndex.params.dials.close_to_spindle_cutoff)
if self._indxr_input_lattice:
indexer.set_indexer_input_lattice(self._indxr_input_lattice)
Debug.write('Set lattice: %s' % self._indxr_input_lattice)
if self._indxr_input_cell:
indexer.set_indexer_input_cell(self._indxr_input_cell)
Debug.write('Set cell: %f %f %f %f %f %f' % \
self._indxr_input_cell)
original_cell = self._indxr_input_cell
if method is None:
if PhilIndex.params.dials.index.method is None:
method = 'fft3d'
Debug.write('Choosing indexing method: %s' % method)
else:
method = PhilIndex.params.dials.index.method
FileHandler.record_log_file('%s INDEX' % self.get_indexer_full_name(),
indexer.get_log_file())
indexer.run(method)
if not os.path.exists(indexer.get_experiments_filename()):
raise RuntimeError("Indexing has failed: see %s for more details."
%indexer.get_log_file())
elif not os.path.exists(indexer.get_indexed_filename()):
raise RuntimeError("Indexing has failed: %s does not exist."
%indexer.get_indexed_filename())
report = self.Report()
report.set_experiments_filename(indexer.get_experiments_filename())
report.set_reflections_filename(indexer.get_indexed_filename())
html_filename = os.path.join(
self.get_working_directory(),
'%i_dials.index.report.html' %report.get_xpid())
report.set_html_filename(html_filename)
report.run()
assert os.path.exists(html_filename)
FileHandler.record_html_file(
'%s INDEX' %self.get_indexer_full_name(), html_filename)
return indexer
def _scale_finish_chunk_5_finish_small_molecule(self):
# keep 'mtz' and remove 'mtz_merged' from the dictionary for
# consistency with non-small-molecule workflow
self._scalr_scaled_reflection_files['mtz'] = \
self._scalr_scaled_reflection_files['mtz_merged']
del self._scalr_scaled_reflection_files['mtz_merged']
FileHandler.record_data_file(self._scalr_scaled_reflection_files['mtz'])
def _integrate(self):
'''Implement the integrater interface.'''
# cite the program
Citations.cite('mosflm')
images_str = '%d to %d' % tuple(self._intgr_wedge)
cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % tuple(self._intgr_cell)
if len(self._fp_directory) <= 50:
dirname = self._fp_directory
else:
dirname = '...%s' % self._fp_directory[-46:]
Journal.block(
'integrating', self._intgr_sweep_name, 'mosflm',
{'images':images_str,
'cell':cell_str,
'lattice':self.get_integrater_refiner().get_refiner_lattice(),
'template':self._fp_template,
'directory':dirname,
'resolution':'%.2f' % self._intgr_reso_high})
self._mosflm_rerun_integration = False
wd = self.get_working_directory()
try:
if self.get_integrater_sweep_name():
pname, xname, dname = self.get_integrater_project_info()
nproc = PhilIndex.params.xia2.settings.multiprocessing.nproc
if nproc > 1:
Debug.write('Parallel integration: %d jobs' %nproc)
self._mosflm_hklout = self._mosflm_parallel_integrate()
else:
self._mosflm_hklout = self._mosflm_integrate()
# record integration output for e.g. BLEND.
sweep = self.get_integrater_sweep_name()
if sweep:
FileHandler.record_more_data_file(
'%s %s %s %s INTEGRATE' % (pname, xname, dname, sweep),
self._mosflm_hklout)
except IntegrationError, e:
if 'negative mosaic spread' in str(e):
if self._mosflm_postref_fix_mosaic:
Chatter.write(
'Negative mosaic spread - stopping integration')
raise BadLatticeError, 'negative mosaic spread'
Chatter.write(
'Negative mosaic spread - rerunning integration')
self.set_integrater_done(False)
self._mosflm_postref_fix_mosaic = True
def _prepare_pointless_hklin(working_directory,
hklin,
phi_width):
'''Prepare some data for pointless - this will take only 180 degrees
of data if there is more than this (through a "rebatch" command) else
will simply return hklin.'''
# also remove blank images?
if not Flags.get_microcrystal() and not Flags.get_small_molecule():
Debug.write('Excluding blank images')
hklout = os.path.join(
working_directory,
'%s_noblank.mtz' % (os.path.split(hklin)[-1][:-4]))
FileHandler.record_temporary_file(hklout)
hklin = remove_blank(hklin, hklout)
# find the number of batches
md = Mtzdump()
md.set_working_directory(working_directory)
auto_logfiler(md)
md.set_hklin(hklin)
md.dump()
batches = max(md.get_batches()) - min(md.get_batches())
phi_limit = 180
if batches * phi_width < phi_limit or Flags.get_small_molecule():
return hklin
hklout = os.path.join(
working_directory,
'%s_prepointless.mtz' % (os.path.split(hklin)[-1][:-4]))
rb = Rebatch()
rb.set_working_directory(working_directory)
auto_logfiler(rb)
rb.set_hklin(hklin)
rb.set_hklout(hklout)
first = min(md.get_batches())
last = first + int(phi_limit / phi_width)
Debug.write('Preparing data for pointless - %d batches (%d degrees)' % \
((last - first), phi_limit))
rb.limit_batches(first, last)
# we will want to delete this one exit
FileHandler.record_temporary_file(hklout)
return hklout
def _prepare_pointless_hklin(working_directory, hklin, phi_width):
"""Prepare some data for pointless - this will take only 180 degrees
of data if there is more than this (through a "pointless" command) else
will simply return hklin."""
# also remove blank images?
if not PhilIndex.params.xia2.settings.small_molecule:
Debug.write("Excluding blank images")
hklout = os.path.join(
working_directory, "%s_noblank.mtz" % (os.path.split(hklin)[-1][:-4])
)
FileHandler.record_temporary_file(hklout)
hklin = remove_blank(hklin, hklout)
# find the number of batches
batches = MtzUtils.batches_from_mtz(hklin)
n_batches = max(batches) - min(batches)
phi_limit = 180
if (
n_batches * phi_width < phi_limit
or PhilIndex.params.xia2.settings.small_molecule
):
return hklin
hklout = os.path.join(
working_directory, "%s_prepointless.mtz" % (os.path.split(hklin)[-1][:-4])
)
pl = xia2.Wrappers.CCP4.Pointless.Pointless()
pl.set_working_directory(working_directory)
auto_logfiler(pl)
pl.set_hklin(hklin)
pl.set_hklout(hklout)
first = min(batches)
last = first + int(phi_limit / phi_width)
Debug.write(
"Preparing data for pointless - %d batches (%d degrees)"
% ((last - first), phi_limit)
)
pl.limit_batches(first, last)
# we will want to delete this one exit
FileHandler.record_temporary_file(hklout)
return hklout
def _scale_finish_chunk_3_truncate(self):
for wavelength in self._scalr_scaled_refl_files.keys():
hklin = self._scalr_scaled_refl_files[wavelength]
truncate = self._factory.Truncate()
truncate.set_hklin(hklin)
if self.get_scaler_anomalous():
truncate.set_anomalous(True)
else:
truncate.set_anomalous(False)
FileHandler.record_log_file('%s %s %s truncate' % \
(self._scalr_pname,
self._scalr_xname,
wavelength),
truncate.get_log_file())
hklout = os.path.join(self.get_working_directory(),
'%s_truncated.mtz' % wavelength)
truncate.set_hklout(hklout)
truncate.truncate()
xmlout = truncate.get_xmlout()
if xmlout is not None:
FileHandler.record_xml_file('%s %s %s truncate' % \
(self._scalr_pname,
self._scalr_xname,
wavelength),
xmlout)
Debug.write('%d absent reflections in %s removed' % \
(truncate.get_nabsent(), wavelength))
b_factor = truncate.get_b_factor()
# record the b factor somewhere (hopefully) useful...
self._scalr_statistics[(self._scalr_pname, self._scalr_xname,
wavelength)]['Wilson B factor'] = [
b_factor
]
# and record the reflection file..
self._scalr_scaled_refl_files[wavelength] = hklout
def dials_symmetry_decide_pointgroup(self, experiments, reflections):
"""Run the symmetry analyser and return it for later inspection."""
symmetry_analyser = DialsSymmetry()
symmetry_analyser.set_working_directory(self.get_working_directory())
auto_logfiler(symmetry_analyser)
FileHandler.record_log_file(
"%s %s SYMMETRY" % (self._scalr_pname, self._scalr_xname),
symmetry_analyser.get_log_file(),
)
for (exp, refl) in zip(experiments, reflections):
symmetry_analyser.add_experiments(exp)
symmetry_analyser.add_reflections(refl)
symmetry_analyser.decide_pointgroup()
return symmetry_analyser
def _scale_finish_chunk_2_report(self):
from cctbx.array_family import flex
from iotbx.reflection_file_reader import any_reflection_file
from xia2.lib.bits import auto_logfiler
from xia2.Wrappers.XIA.Report import Report
for wavelength in self._scalr_scaled_refl_files.keys():
mtz_unmerged = self._scalr_scaled_reflection_files['mtz_unmerged'][
wavelength]
reader = any_reflection_file(mtz_unmerged)
mtz_object = reader.file_content()
batches = mtz_object.as_miller_arrays_dict()['HKL_base',
'HKL_base', 'BATCH']
dose = flex.double(batches.size(), -1)
batch_to_dose = self.get_batch_to_dose()
for i, b in enumerate(batches.data()):
dose[i] = batch_to_dose[b]
c = mtz_object.crystals()[0]
d = c.datasets()[0]
d.add_column('DOSE', 'R').set_values(dose.as_float())
tmp_mtz = os.path.join(self.get_working_directory(),
'dose_tmp.mtz')
mtz_object.write(tmp_mtz)
hklin = tmp_mtz
FileHandler.record_temporary_file(hklin)
report = Report()
report.set_working_directory(self.get_working_directory())
report.set_mtz_filename(hklin)
htmlout = os.path.join(
self.get_working_directory(), '%s_%s_%s_report.html' %
(self._scalr_pname, self._scalr_xname, wavelength))
report.set_html_filename(htmlout)
report.set_chef_min_completeness(0.95) # sensible?
auto_logfiler(report)
try:
report.run()
FileHandler.record_html_file(
'%s %s %s report' %
(self._scalr_pname, self._scalr_xname, wavelength),
htmlout)
except Exception as e:
Debug.write('xia2.report failed:')
Debug.write(str(e))
def _do_multisweep_symmetry_analysis(self):
refiners = []
experiments = []
reflections = []
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
integrater = si.get_integrater()
experiments.append(integrater.get_integrated_experiments())
reflections.append(integrater.get_integrated_reflections())
refiners.append(integrater.get_integrater_refiner())
Debug.write("Running multisweep dials.symmetry for %d sweeps" % len(refiners))
pointgroup, reindex_op, ntr, pt, reind_refl, reind_exp, reindex_initial = self._dials_symmetry_indexer_jiffy(
experiments, reflections, refiners, multisweep=True
)
FileHandler.record_temporary_file(reind_refl)
FileHandler.record_temporary_file(reind_exp)
return pointgroup, reindex_op, ntr, pt, reind_refl, reind_exp, reindex_initial
def _scale_finish_chunk_4_mad_mangling(self):
if len(self._scalr_scaled_refl_files.keys()) > 1:
reflection_files = {}
for wavelength in self._scalr_scaled_refl_files.keys():
cad = self._factory.Cad()
cad.add_hklin(self._scalr_scaled_refl_files[wavelength])
cad.set_hklout(
os.path.join(self.get_working_directory(),
'cad-tmp-%s.mtz' % wavelength))
cad.set_new_suffix(wavelength)
cad.update()
reflection_files[wavelength] = cad.get_hklout()
FileHandler.record_temporary_file(cad.get_hklout())
# now merge the reflection files together...
hklout = os.path.join(
self.get_working_directory(),
'%s_%s_merged.mtz' % (self._scalr_pname, self._scalr_xname))
FileHandler.record_temporary_file(hklout)
Debug.write('Merging all data sets to %s' % hklout)
cad = self._factory.Cad()
for wavelength in reflection_files.keys():
cad.add_hklin(reflection_files[wavelength])
cad.set_hklout(hklout)
cad.merge()
self._scalr_scaled_reflection_files['mtz_merged'] = hklout
else:
self._scalr_scaled_reflection_files[
'mtz_merged'] = self._scalr_scaled_refl_files[
self._scalr_scaled_refl_files.keys()[0]]
def _scale_prepare(self):
'''Perform all of the preparation required to deliver the scaled
data. This should sort together the reflection files, ensure that
they are correctly indexed (via pointless) and generally tidy
things up.'''
# acknowledge all of the programs we are about to use...
Citations.cite('pointless')
Citations.cite('aimless')
Citations.cite('ccp4')
# ---------- GATHER ----------
self._sweep_handler = SweepInformationHandler(self._scalr_integraters)
Journal.block(
'gathering', self.get_scaler_xcrystal().get_name(), 'CCP4',
{'working directory':self.get_working_directory()})
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
pname, xname, dname = si.get_project_info()
sname = si.get_sweep_name()
exclude_sweep = False
for sweep in PhilIndex.params.xia2.settings.sweep:
if sweep.id == sname and sweep.exclude:
exclude_sweep = True
break
if exclude_sweep:
self._sweep_handler.remove_epoch(epoch)
Debug.write('Excluding sweep %s' %sname)
else:
Journal.entry({'adding data from':'%s/%s/%s' % \
(xname, dname, sname)})
# gather data for all images which belonged to the parent
# crystal - allowing for the fact that things could go wrong
# e.g. epoch information not available, exposure times not in
# headers etc...
for e in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(e)
assert is_mtz_file(si.get_reflections())
p, x = self._sweep_handler.get_project_info()
self._scalr_pname = p
self._scalr_xname = x
# verify that the lattices are consistent, calling eliminate if
# they are not N.B. there could be corner cases here
need_to_return = False
multi_sweep_indexing = \
PhilIndex.params.xia2.settings.developmental.multi_sweep_indexing
if len(self._sweep_handler.get_epochs()) > 1:
if multi_sweep_indexing and not self._scalr_input_pointgroup:
pointless_hklins = []
max_batches = 0
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
hklin = si.get_reflections()
md = self._factory.Mtzdump()
md.set_hklin(hklin)
md.dump()
batches = md.get_batches()
if 1 + max(batches) - min(batches) > max_batches:
max_batches = max(batches) - min(batches) + 1
datasets = md.get_datasets()
Debug.write('In reflection file %s found:' % hklin)
for d in datasets:
Debug.write('... %s' % d)
dataset_info = md.get_dataset_info(datasets[0])
from xia2.lib.bits import nifty_power_of_ten
Debug.write('Biggest sweep has %d batches' % max_batches)
max_batches = nifty_power_of_ten(max_batches)
counter = 0
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
hklin = si.get_reflections()
integrater = si.get_integrater()
refiner = integrater.get_integrater_refiner()
hklin = self._prepare_pointless_hklin(
hklin, si.get_integrater().get_phi_width())
rb = self._factory.Rebatch()
hklout = os.path.join(self.get_working_directory(),
'%s_%s_%s_%s_prepointless.mtz' % \
(pname, xname, dname, si.get_sweep_name()))
# we will want to delete this one exit
FileHandler.record_temporary_file(hklout)
first_batch = min(si.get_batches())
si.set_batch_offset(counter * max_batches - first_batch + 1)
rb.set_hklin(hklin)
rb.set_first_batch(counter * max_batches + 1)
rb.set_project_info(pname, xname, dname)
rb.set_hklout(hklout)
new_batches = rb.rebatch()
pointless_hklins.append(hklout)
# update the counter & recycle
counter += 1
s = self._factory.Sortmtz()
pointless_hklin = os.path.join(self.get_working_directory(),
'%s_%s_prepointless_sorted.mtz' % \
(self._scalr_pname, self._scalr_xname))
s.set_hklout(pointless_hklin)
for hklin in pointless_hklins:
s.add_hklin(hklin)
s.sort()
pointgroup, reindex_op, ntr, pt = \
self._pointless_indexer_jiffy(
pointless_hklin, refiner)
Debug.write('X1698: %s: %s' % (pointgroup, reindex_op))
lattices = [Syminfo.get_lattice(pointgroup)]
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
intgr = si.get_integrater()
hklin = si.get_reflections()
refiner = intgr.get_integrater_refiner()
if ntr:
intgr.integrater_reset_reindex_operator()
need_to_return = True
else:
lattices = []
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
intgr = si.get_integrater()
hklin = si.get_reflections()
refiner = intgr.get_integrater_refiner()
if self._scalr_input_pointgroup:
pointgroup = self._scalr_input_pointgroup
reindex_op = 'h,k,l'
ntr = False
else:
pointless_hklin = self._prepare_pointless_hklin(
hklin, si.get_integrater().get_phi_width())
pointgroup, reindex_op, ntr, pt = \
self._pointless_indexer_jiffy(
pointless_hklin, refiner)
Debug.write('X1698: %s: %s' % (pointgroup, reindex_op))
lattice = Syminfo.get_lattice(pointgroup)
if not lattice in lattices:
lattices.append(lattice)
if ntr:
intgr.integrater_reset_reindex_operator()
need_to_return = True
if len(lattices) > 1:
# why not using pointless indexer jiffy??!
correct_lattice = sort_lattices(lattices)[0]
Chatter.write('Correct lattice asserted to be %s' % \
correct_lattice)
# transfer this information back to the indexers
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
refiner = si.get_integrater().get_integrater_refiner()
sname = si.get_sweep_name()
state = refiner.set_refiner_asserted_lattice(
correct_lattice)
if state == refiner.LATTICE_CORRECT:
Chatter.write('Lattice %s ok for sweep %s' % \
(correct_lattice, sname))
elif state == refiner.LATTICE_IMPOSSIBLE:
raise RuntimeError, 'Lattice %s impossible for %s' \
% (correct_lattice, sname)
elif state == refiner.LATTICE_POSSIBLE:
Chatter.write('Lattice %s assigned for sweep %s' % \
(correct_lattice, sname))
need_to_return = True
# if one or more of them was not in the lowest lattice,
# need to return here to allow reprocessing
if need_to_return:
self.set_scaler_done(False)
self.set_scaler_prepare_done(False)
return
# ---------- REINDEX ALL DATA TO CORRECT POINTGROUP ----------
# all should share the same pointgroup, unless twinned... in which
# case force them to be...
pointgroups = { }
reindex_ops = { }
probably_twinned = False
need_to_return = False
multi_sweep_indexing = \
PhilIndex.params.xia2.settings.developmental.multi_sweep_indexing
if multi_sweep_indexing and not self._scalr_input_pointgroup:
pointless_hklins = []
max_batches = 0
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
hklin = si.get_reflections()
md = self._factory.Mtzdump()
md.set_hklin(hklin)
md.dump()
batches = md.get_batches()
if 1 + max(batches) - min(batches) > max_batches:
max_batches = max(batches) - min(batches) + 1
datasets = md.get_datasets()
Debug.write('In reflection file %s found:' % hklin)
for d in datasets:
Debug.write('... %s' % d)
dataset_info = md.get_dataset_info(datasets[0])
from xia2.lib.bits import nifty_power_of_ten
Debug.write('Biggest sweep has %d batches' % max_batches)
max_batches = nifty_power_of_ten(max_batches)
counter = 0
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
hklin = si.get_reflections()
integrater = si.get_integrater()
refiner = integrater.get_integrater_refiner()
hklin = self._prepare_pointless_hklin(
hklin, si.get_integrater().get_phi_width())
rb = self._factory.Rebatch()
hklout = os.path.join(self.get_working_directory(),
'%s_%s_%s_%s_prepointless.mtz' % \
(pname, xname, dname, si.get_sweep_name()))
# we will want to delete this one exit
FileHandler.record_temporary_file(hklout)
first_batch = min(si.get_batches())
si.set_batch_offset(counter * max_batches - first_batch + 1)
rb.set_hklin(hklin)
rb.set_first_batch(counter * max_batches + 1)
rb.set_project_info(pname, xname, dname)
rb.set_hklout(hklout)
new_batches = rb.rebatch()
pointless_hklins.append(hklout)
# update the counter & recycle
counter += 1
s = self._factory.Sortmtz()
pointless_hklin = os.path.join(self.get_working_directory(),
'%s_%s_prepointless_sorted.mtz' % \
(self._scalr_pname, self._scalr_xname))
s.set_hklout(pointless_hklin)
for hklin in pointless_hklins:
s.add_hklin(hklin)
s.sort()
pointgroup, reindex_op, ntr, pt = \
self._pointless_indexer_jiffy(
pointless_hklin, refiner)
for epoch in self._sweep_handler.get_epochs():
pointgroups[epoch] = pointgroup
reindex_ops[epoch] = reindex_op
else:
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
hklin = si.get_reflections()
#hklout = os.path.join(
#self.get_working_directory(),
#os.path.split(hklin)[-1].replace('.mtz', '_rdx.mtz'))
#FileHandler.record_temporary_file(hklout)
integrater = si.get_integrater()
refiner = integrater.get_integrater_refiner()
if self._scalr_input_pointgroup:
Debug.write('Using input pointgroup: %s' % \
self._scalr_input_pointgroup)
pointgroup = self._scalr_input_pointgroup
reindex_op = 'h,k,l'
pt = False
else:
pointless_hklin = self._prepare_pointless_hklin(
hklin, si.get_integrater().get_phi_width())
pointgroup, reindex_op, ntr, pt = \
self._pointless_indexer_jiffy(
pointless_hklin, refiner)
Debug.write('X1698: %s: %s' % (pointgroup, reindex_op))
if ntr:
integrater.integrater_reset_reindex_operator()
need_to_return = True
if pt and not probably_twinned:
probably_twinned = True
Debug.write('Pointgroup: %s (%s)' % (pointgroup, reindex_op))
pointgroups[epoch] = pointgroup
reindex_ops[epoch] = reindex_op
overall_pointgroup = None
pointgroup_set = set([pointgroups[e] for e in pointgroups])
if len(pointgroup_set) > 1 and \
not probably_twinned:
raise RuntimeError, 'non uniform pointgroups'
if len(pointgroup_set) > 1:
Debug.write('Probably twinned, pointgroups: %s' % \
' '.join([p.replace(' ', '') for p in \
list(pointgroup_set)]))
numbers = [Syminfo.spacegroup_name_to_number(s) for s in \
pointgroup_set]
overall_pointgroup = Syminfo.spacegroup_number_to_name(
min(numbers))
self._scalr_input_pointgroup = overall_pointgroup
Chatter.write('Twinning detected, assume pointgroup %s' % \
overall_pointgroup)
need_to_return = True
else:
overall_pointgroup = pointgroup_set.pop()
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
integrater = si.get_integrater()
integrater.set_integrater_spacegroup_number(
Syminfo.spacegroup_name_to_number(overall_pointgroup))
integrater.set_integrater_reindex_operator(
reindex_ops[epoch], reason='setting point group')
# This will give us the reflections in the correct point group
si.set_reflections(integrater.get_integrater_intensities())
if need_to_return:
self.set_scaler_done(False)
self.set_scaler_prepare_done(False)
return
# in here now optinally work through the data files which should be
# indexed with a consistent point group, and transform the orientation
# matrices by the lattice symmetry operations (if possible) to get a
# consistent definition of U matrix modulo fixed rotations
if PhilIndex.params.xia2.settings.unify_setting:
from scitbx.matrix import sqr
reference_U = None
i3 = sqr((1, 0, 0, 0, 1, 0, 0, 0, 1))
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
intgr = si.get_integrater()
fixed = sqr(intgr.get_goniometer().get_fixed_rotation())
u, b, s = get_umat_bmat_lattice_symmetry_from_mtz(si.get_reflections())
U = fixed.inverse() * sqr(u).transpose()
B = sqr(b)
if reference_U is None:
reference_U = U
continue
results = []
for op in s.all_ops():
R = B * sqr(op.r().as_double()).transpose() * B.inverse()
nearly_i3 = (U * R).inverse() * reference_U
score = sum([abs(_n - _i) for (_n, _i) in zip(nearly_i3, i3)])
results.append((score, op.r().as_hkl(), op))
results.sort()
best = results[0]
Debug.write('Best reindex: %s %.3f' % (best[1], best[0]))
intgr.set_integrater_reindex_operator(best[2].r().inverse().as_hkl(),
reason='unifying [U] setting')
si.set_reflections(intgr.get_integrater_intensities())
# recalculate to verify
u, b, s = get_umat_bmat_lattice_symmetry_from_mtz(si.get_reflections())
U = fixed.inverse() * sqr(u).transpose()
Debug.write('New reindex: %s' % (U.inverse() * reference_U))
# FIXME I should probably raise an exception at this stage if this
# is not about I3...
if self.get_scaler_reference_reflection_file():
self._reference = self.get_scaler_reference_reflection_file()
Debug.write('Using HKLREF %s' % self._reference)
elif Flags.get_reference_reflection_file():
self._reference = Flags.get_reference_reflection_file()
Debug.write('Using HKLREF %s' % self._reference)
params = PhilIndex.params
use_brehm_diederichs = params.xia2.settings.use_brehm_diederichs
if len(self._sweep_handler.get_epochs()) > 1 and use_brehm_diederichs:
brehm_diederichs_files_in = []
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
hklin = si.get_reflections()
brehm_diederichs_files_in.append(hklin)
# now run cctbx.brehm_diederichs to figure out the indexing hand for
# each sweep
from xia2.Wrappers.Cctbx.BrehmDiederichs import BrehmDiederichs
from xia2.lib.bits import auto_logfiler
brehm_diederichs = BrehmDiederichs()
brehm_diederichs.set_working_directory(self.get_working_directory())
auto_logfiler(brehm_diederichs)
brehm_diederichs.set_input_filenames(brehm_diederichs_files_in)
# 1 or 3? 1 seems to work better?
brehm_diederichs.set_asymmetric(1)
brehm_diederichs.run()
reindexing_dict = brehm_diederichs.get_reindexing_dict()
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
intgr = si.get_integrater()
hklin = si.get_reflections()
reindex_op = reindexing_dict.get(os.path.abspath(hklin))
assert reindex_op is not None
if 1 or reindex_op != 'h,k,l':
# apply the reindexing operator
intgr.set_integrater_reindex_operator(
reindex_op, reason='match reference')
si.set_reflections(intgr.get_integrater_intensities())
elif len(self._sweep_handler.get_epochs()) > 1 and \
not self._reference:
first = self._sweep_handler.get_epochs()[0]
si = self._sweep_handler.get_sweep_information(first)
self._reference = si.get_reflections()
if self._reference:
md = self._factory.Mtzdump()
md.set_hklin(self._reference)
md.dump()
if md.get_batches() and False:
raise RuntimeError, 'reference reflection file %s unmerged' % \
self._reference
datasets = md.get_datasets()
if len(datasets) > 1 and False:
raise RuntimeError, 'more than one dataset in %s' % \
self._reference
# then get the unit cell, lattice etc.
reference_lattice = Syminfo.get_lattice(md.get_spacegroup())
reference_cell = md.get_dataset_info(datasets[0])['cell']
# then compute the pointgroup from this...
# ---------- REINDEX TO CORRECT (REFERENCE) SETTING ----------
for epoch in self._sweep_handler.get_epochs():
pl = self._factory.Pointless()
si = self._sweep_handler.get_sweep_information(epoch)
hklin = si.get_reflections()
pl.set_hklin(self._prepare_pointless_hklin(
hklin, si.get_integrater().get_phi_width()))
hklout = os.path.join(
self.get_working_directory(),
'%s_rdx2.mtz' % os.path.split(hklin)[-1][:-4])
# we will want to delete this one exit
FileHandler.record_temporary_file(hklout)
# now set the initial reflection set as a reference...
pl.set_hklref(self._reference)
# write a pointless log file...
pl.decide_pointgroup()
Debug.write('Reindexing analysis of %s' % pl.get_hklin())
pointgroup = pl.get_pointgroup()
reindex_op = pl.get_reindex_operator()
Debug.write('Operator: %s' % reindex_op)
# apply this...
integrater = si.get_integrater()
integrater.set_integrater_reindex_operator(reindex_op,
reason='match reference')
integrater.set_integrater_spacegroup_number(
Syminfo.spacegroup_name_to_number(pointgroup))
si.set_reflections(integrater.get_integrater_intensities())
md = self._factory.Mtzdump()
md.set_hklin(si.get_reflections())
md.dump()
datasets = md.get_datasets()
if len(datasets) > 1:
raise RuntimeError, 'more than one dataset in %s' % \
si.get_reflections()
# then get the unit cell, lattice etc.
lattice = Syminfo.get_lattice(md.get_spacegroup())
cell = md.get_dataset_info(datasets[0])['cell']
if lattice != reference_lattice:
raise RuntimeError, 'lattices differ in %s and %s' % \
(self._reference, si.get_reflections())
for j in range(6):
if math.fabs((cell[j] - reference_cell[j]) /
reference_cell[j]) > 0.1:
raise RuntimeError, \
'unit cell parameters differ in %s and %s' % \
(self._reference, si.get_reflections())
# ---------- SORT TOGETHER DATA ----------
self._sort_together_data_ccp4()
self._scalr_resolution_limits = { }
# store central resolution limit estimates
batch_ranges = [self._sweep_handler.get_sweep_information(
epoch).get_batch_range() for epoch in
self._sweep_handler.get_epochs()]
self._resolution_limit_estimates = erzatz_resolution(
self._prepared_reflections, batch_ranges)
return
def _integrate_finish(self):
'''Finish off the integration by running correct.'''
# first run the postrefinement etc with spacegroup P1
# and the current unit cell - this will be used to
# obtain a benchmark rmsd in pixels / phi and also
# cell deviations (this is working towards spotting bad
# indexing solutions) - only do this if we have no
# reindex matrix... and no postrefined cell...
p1_deviations = None
# fix for bug # 3264 -
# if we have not run integration with refined parameters, make it so...
# erm? shouldn't this therefore return if this is the principle, or
# set the flag after we have tested the lattice?
if not self._xds_data_files.has_key('GXPARM.XDS') and \
PhilIndex.params.xds.integrate.reintegrate:
Debug.write(
'Resetting integrater, to ensure refined orientation is used')
self.set_integrater_done(False)
if not self.get_integrater_reindex_matrix() and not self._intgr_cell \
and not Flags.get_no_lattice_test() and \
not self.get_integrater_sweep().get_user_lattice():
correct = self.Correct()
correct.set_data_range(self._intgr_wedge[0],
self._intgr_wedge[1])
if self.get_polarization() > 0.0:
correct.set_polarization(self.get_polarization())
# FIXME should this be using the correctly transformed
# cell or are the results ok without it?!
correct.set_spacegroup_number(1)
correct.set_cell(self._intgr_refiner_cell)
correct.run()
# record the log file -
pname, xname, dname = self.get_integrater_project_info()
sweep = self.get_integrater_sweep_name()
FileHandler.record_log_file('%s %s %s %s CORRECT' % \
(pname, xname, dname, sweep),
os.path.join(
self.get_working_directory(),
'CORRECT.LP'))
FileHandler.record_more_data_file(
'%s %s %s %s CORRECT' % (pname, xname, dname, sweep),
os.path.join(self.get_working_directory(), 'XDS_ASCII.HKL'))
cell = correct.get_result('cell')
cell_esd = correct.get_result('cell_esd')
Debug.write('Postrefinement in P1 results:')
Debug.write('%7.3f %7.3f %7.3f %7.3f %7.3f %7.3f' % \
tuple(cell))
Debug.write('%7.3f %7.3f %7.3f %7.3f %7.3f %7.3f' % \
tuple(cell_esd))
Debug.write('Deviations: %.2f pixels %.2f degrees' % \
(correct.get_result('rmsd_pixel'),
correct.get_result('rmsd_phi')))
p1_deviations = (correct.get_result('rmsd_pixel'),
correct.get_result('rmsd_phi'))
# next run the postrefinement etc with the given
# cell / lattice - this will be the assumed result...
correct = self.Correct()
correct.set_data_range(self._intgr_wedge[0],
self._intgr_wedge[1])
if self.get_polarization() > 0.0:
correct.set_polarization(self.get_polarization())
# BUG # 2695 probably comes from here - need to check...
# if the pointless interface comes back with a different
# crystal setting then the unit cell stored in self._intgr_cell
# needs to be set to None...
if self.get_integrater_spacegroup_number():
correct.set_spacegroup_number(
self.get_integrater_spacegroup_number())
if not self._intgr_cell:
raise RuntimeError, 'no unit cell to recycle'
correct.set_cell(self._intgr_cell)
# BUG # 3113 - new version of XDS will try and figure the
# best spacegroup out from the intensities (and get it wrong!)
# unless we set the spacegroup and cell explicitly
if not self.get_integrater_spacegroup_number():
cell = self._intgr_refiner_cell
lattice = self._intgr_refiner.get_refiner_lattice()
spacegroup_number = lattice_to_spacegroup_number(lattice)
# this should not prevent the postrefinement from
# working correctly, else what is above would not
# work correctly (the postrefinement test)
correct.set_spacegroup_number(spacegroup_number)
correct.set_cell(cell)
Debug.write('Setting spacegroup to: %d' % spacegroup_number)
Debug.write(
'Setting cell to: %.2f %.2f %.2f %.2f %.2f %.2f' % tuple(cell))
if self.get_integrater_reindex_matrix():
# bug! if the lattice is not primitive the values in this
# reindex matrix need to be multiplied by a constant which
# depends on the Bravais lattice centering.
lattice = self._intgr_refiner.get_refiner_lattice()
import scitbx.matrix
matrix = self.get_integrater_reindex_matrix()
matrix = scitbx.matrix.sqr(matrix).transpose().elems
matrix = r_to_rt(matrix)
if lattice[1] == 'P':
mult = 1
elif lattice[1] == 'C' or lattice[1] == 'I':
mult = 2
elif lattice[1] == 'R':
mult = 3
elif lattice[1] == 'F':
mult = 4
else:
raise RuntimeError, 'unknown multiplier for lattice %s' % \
lattice
Debug.write('REIDX multiplier for lattice %s: %d' % \
(lattice, mult))
mult_matrix = [mult * m for m in matrix]
Debug.write('REIDX set to %d %d %d %d %d %d %d %d %d %d %d %d' % \
tuple(mult_matrix))
correct.set_reindex_matrix(mult_matrix)
correct.run()
# erm. just to be sure
if self.get_integrater_reindex_matrix() and \
correct.get_reindex_used():
raise RuntimeError, 'Reindex panic!'
# get the reindex operation used, which may be useful if none was
# set but XDS decided to apply one, e.g. #419.
if not self.get_integrater_reindex_matrix() and \
correct.get_reindex_used():
# convert this reindex operation to h, k, l form: n.b. this
# will involve dividing through by the lattice centring multiplier
matrix = rt_to_r(correct.get_reindex_used())
import scitbx.matrix
matrix = scitbx.matrix.sqr(matrix).transpose().elems
lattice = self._intgr_refiner.get_refiner_lattice()
if lattice[1] == 'P':
mult = 1.0
elif lattice[1] == 'C' or lattice[1] == 'I':
mult = 2.0
elif lattice[1] == 'R':
mult = 3.0
elif lattice[1] == 'F':
mult = 4.0
matrix = [m / mult for m in matrix]
reindex_op = mat_to_symop(matrix)
# assign this to self: will this reset?! make for a leaky
# abstraction and just assign this...
# self.set_integrater_reindex_operator(reindex)
self._intgr_reindex_operator = reindex_op
# record the log file -
pname, xname, dname = self.get_integrater_project_info()
sweep = self.get_integrater_sweep_name()
FileHandler.record_log_file('%s %s %s %s CORRECT' % \
(pname, xname, dname, sweep),
os.path.join(self.get_working_directory(),
'CORRECT.LP'))
# should get some interesting stuff from the XDS correct file
# here, for instance the resolution range to use in integration
# (which should be fed back if not fast) and so on...
self._intgr_corrected_hklout = os.path.join(self.get_working_directory(),
'XDS_ASCII.HKL')
# also record the batch range - needed for the analysis of the
# radiation damage in chef...
self._intgr_batches_out = (self._intgr_wedge[0],
self._intgr_wedge[1])
# FIXME perhaps I should also feedback the GXPARM file here??
for file in ['GXPARM.XDS']:
self._xds_data_files[file] = correct.get_output_data_file(file)
# record the postrefined cell parameters
self._intgr_cell = correct.get_result('cell')
self._intgr_n_ref = correct.get_result('n_ref')
Debug.write('Postrefinement in "correct" spacegroup results:')
Debug.write('%7.3f %7.3f %7.3f %7.3f %7.3f %7.3f' % \
tuple(correct.get_result('cell')))
Debug.write('%7.3f %7.3f %7.3f %7.3f %7.3f %7.3f' % \
tuple(correct.get_result('cell_esd')))
Debug.write('Deviations: %.2f pixels %.2f degrees' % \
(correct.get_result('rmsd_pixel'),
correct.get_result('rmsd_phi')))
Debug.write('Error correction parameters: A=%.3f B=%.3f' % \
correct.get_result('sdcorrection'))
# compute misorientation of axes
xparm_file = os.path.join(self.get_working_directory(), 'GXPARM.XDS')
from iotbx.xds import xparm
handle = xparm.reader()
handle.read_file(xparm_file)
rotn = handle.rotation_axis
beam = handle.beam_vector
dot = sum([rotn[j] * beam[j] for j in range(3)])
r = math.sqrt(sum([rotn[j] * rotn[j] for j in range(3)]))
b = math.sqrt(sum([beam[j] * beam[j] for j in range(3)]))
rtod = 180.0 / math.pi
angle = rtod * math.fabs(0.5 * math.pi - math.acos(dot / (r * b)))
Debug.write('Axis misalignment %.2f degrees' % angle)
correct_deviations = (correct.get_result('rmsd_pixel'),
correct.get_result('rmsd_phi'))
if p1_deviations:
# compare and reject if both > 50% higher - though adding a little
# flexibility - 0.5 pixel / osc width slack.
pixel = p1_deviations[0]
phi = math.sqrt(0.05 * 0.05 + \
p1_deviations[1] * p1_deviations[1])
threshold = Flags.get_rejection_threshold()
Debug.write('RMSD ratio: %.2f' % (correct_deviations[0] / pixel))
Debug.write('RMSPhi ratio: %.2f' % (correct_deviations[1] / phi))
if correct_deviations[0] / pixel > threshold and \
correct_deviations[1] / phi > threshold:
Chatter.write(
'Eliminating this indexing solution as postrefinement')
Chatter.write(
'deviations rather high relative to triclinic')
raise BadLatticeError, \
'high relative deviations in postrefinement'
if not Flags.get_quick() and Flags.get_remove():
# check for alien reflections and perhaps recycle - removing them
if len(correct.get_remove()) > 0:
correct_remove = correct.get_remove()
current_remove = []
final_remove = []
# first ensure that there are no duplicate entries...
if os.path.exists(os.path.join(
self.get_working_directory(),
'REMOVE.HKL')):
for line in open(os.path.join(
self.get_working_directory(),
'REMOVE.HKL'), 'r').readlines():
h, k, l = map(int, line.split()[:3])
z = float(line.split()[3])
if not (h, k, l, z) in current_remove:
current_remove.append((h, k, l, z))
for c in correct_remove:
if c in current_remove:
continue
final_remove.append(c)
Debug.write(
'%d alien reflections are already removed' % \
(len(correct_remove) - len(final_remove)))
else:
# we want to remove all of the new dodgy reflections
final_remove = correct_remove
remove_hkl = open(os.path.join(
self.get_working_directory(),
'REMOVE.HKL'), 'w')
z_min = Flags.get_z_min()
rejected = 0
# write in the old reflections
for remove in current_remove:
z = remove[3]
if z >= z_min:
remove_hkl.write('%d %d %d %f\n' % remove)
else:
rejected += 1
Debug.write('Wrote %d old reflections to REMOVE.HKL' % \
(len(current_remove) - rejected))
Debug.write('Rejected %d as z < %f' % \
(rejected, z_min))
# and the new reflections
rejected = 0
used = 0
for remove in final_remove:
z = remove[3]
if z >= z_min:
used += 1
remove_hkl.write('%d %d %d %f\n' % remove)
else:
rejected += 1
Debug.write('Wrote %d new reflections to REMOVE.HKL' % \
(len(final_remove) - rejected))
Debug.write('Rejected %d as z < %f' % \
(rejected, z_min))
remove_hkl.close()
# we want to rerun the finishing step so...
# unless we have added no new reflections... or unless we
# have not confirmed the point group (see SCI-398)
if used and self.get_integrater_reindex_matrix():
self.set_integrater_finish_done(False)
else:
Debug.write(
'Going quickly so not removing %d outlier reflections...' % \
len(correct.get_remove()))
# Convert INTEGRATE.HKL to MTZ format and reapply any reindexing operations
# spacegroup changes to allow use with CCP4 / Aimless for scaling
integrate_hkl = os.path.join(
self.get_working_directory(), 'INTEGRATE.HKL')
hklout = os.path.splitext(integrate_hkl)[0] + ".mtz"
self._factory.set_working_directory(self.get_working_directory())
pointless = self._factory.Pointless()
pointless.set_xdsin(integrate_hkl)
pointless.set_hklout(hklout)
pointless.xds_to_mtz()
integrate_mtz = hklout
if self.get_integrater_reindex_operator() or \
self.get_integrater_spacegroup_number():
Debug.write('Reindexing things to MTZ')
reindex = Reindex()
reindex.set_working_directory(self.get_working_directory())
auto_logfiler(reindex)
if self.get_integrater_reindex_operator():
reindex.set_operator(self.get_integrater_reindex_operator())
if self.get_integrater_spacegroup_number():
reindex.set_spacegroup(self.get_integrater_spacegroup_number())
hklout = '%s_reindex.mtz' % os.path.splitext(integrate_mtz)[0]
reindex.set_hklin(integrate_mtz)
reindex.set_hklout(hklout)
reindex.reindex()
integrate_mtz = hklout
return integrate_mtz
def _index(self):
'''Actually do the autoindexing using the data prepared by the
previous method.'''
images_str = '%d to %d' % tuple(self._indxr_images[0])
for i in self._indxr_images[1:]:
images_str += ', %d to %d' % tuple(i)
cell_str = None
if self._indxr_input_cell:
cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % \
self._indxr_input_cell
# then this is a proper autoindexing run - describe this
# to the journal entry
#if len(self._fp_directory) <= 50:
#dirname = self._fp_directory
#else:
#dirname = '...%s' % self._fp_directory[-46:]
dirname = self.get_directory()
Journal.block(
'autoindexing', self._indxr_sweep_name, 'XDS', {
'images': images_str,
'target cell': cell_str,
'target lattice': self._indxr_input_lattice,
'template': self.get_template(),
'directory': dirname
})
self._index_remove_masked_regions()
if self._i_or_ii is None:
self._i_or_ii = self.decide_i_or_ii()
Debug.write('Selecting I or II, chose %s' % self._i_or_ii)
idxref = self.Idxref()
for file in ['SPOT.XDS']:
idxref.set_input_data_file(file, self._indxr_payload[file])
# set the phi start etc correctly
idxref.set_data_range(self._indxr_images[0][0],
self._indxr_images[0][1])
idxref.set_background_range(self._indxr_images[0][0],
self._indxr_images[0][1])
if self._i_or_ii == 'i':
blocks = self._index_select_images_i()
for block in blocks[:1]:
starting_frame = block[0]
starting_angle = self.get_scan().get_angle_from_image_index(
starting_frame)
idxref.set_starting_frame(starting_frame)
idxref.set_starting_angle(starting_angle)
idxref.add_spot_range(block[0], block[1])
for block in blocks[1:]:
idxref.add_spot_range(block[0], block[1])
else:
for block in self._indxr_images[:1]:
starting_frame = block[0]
starting_angle = self.get_scan().get_angle_from_image_index(
starting_frame)
idxref.set_starting_frame(starting_frame)
idxref.set_starting_angle(starting_angle)
idxref.add_spot_range(block[0], block[1])
for block in self._indxr_images[1:]:
idxref.add_spot_range(block[0], block[1])
# FIXME need to also be able to pass in the known unit
# cell and lattice if already available e.g. from
# the helper... indirectly
if self._indxr_user_input_lattice:
idxref.set_indexer_user_input_lattice(True)
if self._indxr_input_lattice and self._indxr_input_cell:
idxref.set_indexer_input_lattice(self._indxr_input_lattice)
idxref.set_indexer_input_cell(self._indxr_input_cell)
Debug.write('Set lattice: %s' % self._indxr_input_lattice)
Debug.write('Set cell: %f %f %f %f %f %f' % \
self._indxr_input_cell)
original_cell = self._indxr_input_cell
elif self._indxr_input_lattice:
idxref.set_indexer_input_lattice(self._indxr_input_lattice)
original_cell = None
else:
original_cell = None
# FIXED need to set the beam centre here - this needs to come
# from the input .xinfo object or header, and be converted
# to the XDS frame... done.
#mosflm_beam_centre = self.get_beam_centre()
#xds_beam_centre = beam_centre_mosflm_to_xds(
#mosflm_beam_centre[0], mosflm_beam_centre[1], self.get_header())
from dxtbx.serialize.xds import to_xds
converter = to_xds(self.get_imageset())
xds_beam_centre = converter.detector_origin
idxref.set_beam_centre(xds_beam_centre[0], xds_beam_centre[1])
# fixme need to check if the lattice, cell have been set already,
# and if they have, pass these in as input to the indexing job.
done = False
while not done:
try:
done = idxref.run()
# N.B. in here if the IDXREF step was being run in the first
# pass done is FALSE however there should be a refined
# P1 orientation matrix etc. available - so keep it!
except XDSException as e:
# inspect this - if we have complaints about not
# enough reflections indexed, and we have a target
# unit cell, and they are the same, well ignore it
if 'solution is inaccurate' in str(e):
Debug.write('XDS complains solution inaccurate - ignoring')
done = idxref.continue_from_error()
elif ('insufficient percentage (< 70%)' in str(e) or
'insufficient percentage (< 50%)' in str(e)) and \
original_cell:
done = idxref.continue_from_error()
lattice, cell, mosaic = \
idxref.get_indexing_solution()
# compare solutions
check = PhilIndex.params.xia2.settings.xds_check_cell_deviation
for j in range(3):
# allow two percent variation in unit cell length
if math.fabs((cell[j] - original_cell[j]) / \
original_cell[j]) > 0.02 and check:
Debug.write('XDS unhappy and solution wrong')
raise e
# and two degree difference in angle
if math.fabs(cell[j + 3] - original_cell[j + 3]) \
> 2.0 and check:
Debug.write('XDS unhappy and solution wrong')
raise e
Debug.write('XDS unhappy but solution ok')
elif 'insufficient percentage (< 70%)' in str(e) or \
'insufficient percentage (< 50%)' in str(e):
Debug.write('XDS unhappy but solution probably ok')
done = idxref.continue_from_error()
else:
raise e
FileHandler.record_log_file(
'%s INDEX' % self.get_indexer_full_name(),
os.path.join(self.get_working_directory(), 'IDXREF.LP'))
for file in ['SPOT.XDS', 'XPARM.XDS']:
self._indxr_payload[file] = idxref.get_output_data_file(file)
# need to get the indexing solutions out somehow...
self._indxr_other_lattice_cell = idxref.get_indexing_solutions()
self._indxr_lattice, self._indxr_cell, self._indxr_mosaic = \
idxref.get_indexing_solution()
import dxtbx
from dxtbx.serialize.xds import to_crystal
xparm_file = os.path.join(self.get_working_directory(), 'XPARM.XDS')
models = dxtbx.load(xparm_file)
crystal_model = to_crystal(xparm_file)
from dxtbx.model import Experiment, ExperimentList
experiment = Experiment(
beam=models.get_beam(),
detector=models.get_detector(),
goniometer=models.get_goniometer(),
scan=models.get_scan(),
crystal=crystal_model,
#imageset=self.get_imageset(),
)
experiment_list = ExperimentList([experiment])
self.set_indexer_experiment_list(experiment_list)
# I will want this later on to check that the lattice was ok
self._idxref_subtree_problem = idxref.get_index_tree_problem()
return
def json_object(self, command_line=""):
result = {}
for crystal in sorted(self._crystals):
xcrystal = self._crystals[crystal]
cell = xcrystal.get_cell()
spacegroup = xcrystal.get_likely_spacegroups()[0]
result["AutoProc"] = {}
tmp = result["AutoProc"]
tmp["spaceGroup"] = spacegroup
for name, value in zip(["a", "b", "c", "alpha", "beta", "gamma"],
cell):
tmp["refinedCell_%s" % name] = value
result["AutoProcScalingContainer"] = {}
tmp = result["AutoProcScalingContainer"]
tmp["AutoProcScaling"] = {
"recordTimeStamp":
time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
}
statistics_all = xcrystal.get_statistics()
reflection_files = xcrystal.get_scaled_merged_reflections()
for key in list(statistics_all.keys()):
pname, xname, dname = key
# FIXME should assert that the dname is a
# valid wavelength name
keys = [
"High resolution limit",
"Low resolution limit",
"Completeness",
"Multiplicity",
"I/sigma",
"Rmerge(I+/-)",
"CC half",
"Anomalous completeness",
"Anomalous correlation",
"Anomalous multiplicity",
"Total observations",
"Total unique",
"Rmeas(I)",
"Rmeas(I+/-)",
"Rpim(I)",
"Rpim(I+/-)",
"Partial Bias",
]
stats = [k for k in keys if k in statistics_all[key]]
xwavelength = xcrystal.get_xwavelength(dname)
sweeps = xwavelength.get_sweeps()
tmp["AutoProcScalingStatistics"] = []
tmp2 = tmp["AutoProcScalingStatistics"]
for j, name in enumerate(
["overall", "innerShell", "outerShell"]):
statistics_cache = {"scalingStatisticsType": name}
for s in stats:
if s in self._name_map:
n = self._name_map[s]
else:
continue
if isinstance(statistics_all[key][s], type([])):
statistics_cache[n] = statistics_all[key][s][j]
elif isinstance(statistics_all[key][s], type(())):
statistics_cache[n] = statistics_all[key][s][j]
tmp2.append(statistics_cache)
tmp["AutoProcIntegrationContainer"] = []
tmp2 = tmp["AutoProcIntegrationContainer"]
for sweep in sweeps:
if "#" in sweep.get_template():
image_name = sweep.get_image_name(0)
else:
image_name = os.path.join(sweep.get_directory(),
sweep.get_template())
cell = sweep.get_integrater_cell()
intgr_tmp = {}
for name, value in zip(
["a", "b", "c", "alpha", "beta", "gamma"], cell):
intgr_tmp["cell_%s" % name] = value
# FIXME this is naughty
indxr = sweep._get_indexer()
intgr = sweep._get_integrater()
start, end = intgr.get_integrater_wedge()
intgr_tmp["startImageNumber"] = start
intgr_tmp["endImageNumber"] = end
intgr_tmp[
"refinedDetectorDistance"] = indxr.get_indexer_distance(
)
beam = indxr.get_indexer_beam_centre_raw_image()
intgr_tmp["refinedXBeam"] = beam[0]
intgr_tmp["refinedYBeam"] = beam[1]
tmp2.append({
"Image": {
"fileName": os.path.split(image_name)[-1],
"fileLocation":
sanitize(os.path.split(image_name)[0]),
},
"AutoProcIntegration": intgr_tmp,
})
# file unpacking nonsense
result["AutoProcProgramContainer"] = {}
tmp = result["AutoProcProgramContainer"]
tmp2 = {}
if not command_line:
from xia2.Handlers.CommandLine import CommandLine
command_line = CommandLine.get_command_line()
tmp2["processingCommandLine"] = sanitize(command_line)
tmp2["processingProgram"] = "xia2"
tmp["AutoProcProgram"] = tmp2
tmp["AutoProcProgramAttachment"] = []
tmp2 = tmp["AutoProcProgramAttachment"]
data_directory = self._project.path / "DataFiles"
for k in reflection_files:
reflection_file = reflection_files[k]
if not isinstance(reflection_file, type("")):
continue
reflection_file = FileHandler.get_data_file(
self._project.path, reflection_file)
basename = os.path.basename(reflection_file)
if data_directory.joinpath(basename).exists():
# Use file in DataFiles directory in preference (if it exists)
reflection_file = str(data_directory.joinpath(basename))
tmp2.append({
"fileType":
"Result",
"fileName":
os.path.split(reflection_file)[-1],
"filePath":
sanitize(os.path.split(reflection_file)[0]),
})
tmp2.append({
"fileType": "Log",
"fileName": "xia2.txt",
"filePath": sanitize(os.getcwd()),
})
return result
(self._intgr_wedge[0] - offset, self._intgr_wedge[1] - offset))
try:
integrater.run()
except RuntimeError, e:
if 'integration failed: reason unknown' in str(e):
Chatter.write('Mosflm has failed in integration')
message = 'The input was:\n\n'
for input in integrater.get_all_input():
message += ' %s' % input
Chatter.write(message)
raise
FileHandler.record_log_file(
'%s %s %s %s mosflm integrate' % \
(self.get_integrater_sweep_name(),
pname, xname, dname),
integrater.get_log_file())
self._intgr_per_image_statistics = integrater.get_per_image_statistics()
self._mosflm_hklout = integrater.get_hklout()
Debug.write('Integration output: %s' %self._mosflm_hklout)
self._intgr_n_ref = integrater.get_nref()
# if a BGSIG error happened try not refining the
# profile and running again...
if integrater.get_bgsig_too_large():
if not self._mosflm_refine_profiles:
def _index(self):
if PhilIndex.params.dials.index.method in (libtbx.Auto, None):
if self._indxr_input_cell is not None:
indexer = self._do_indexing("real_space_grid_search")
else:
try:
indexer_fft3d = self._do_indexing(method="fft3d")
nref_3d, rmsd_3d = indexer_fft3d.get_nref_rmsds()
except Exception as e:
nref_3d = None
rmsd_3d = None
indexing_failure = e
try:
indexer_fft1d = self._do_indexing(method="fft1d")
nref_1d, rmsd_1d = indexer_fft1d.get_nref_rmsds()
except Exception as e:
nref_1d = None
rmsd_1d = None
indexing_failure = e
if (nref_1d is not None and nref_3d is None or
(nref_1d > nref_3d and rmsd_1d[0] < rmsd_3d[0]
and rmsd_1d[1] < rmsd_3d[1] and rmsd_1d[2] < rmsd_3d[2])):
indexer = indexer_fft1d
elif nref_3d is not None:
indexer = indexer_fft3d
else:
raise RuntimeError(indexing_failure)
else:
indexer = self._do_indexing(
method=PhilIndex.params.dials.index.method)
# not strictly the P1 cell, rather the cell that was used in indexing
self._p1_cell = indexer._p1_cell
self.set_indexer_payload("indexed_filename",
indexer.get_indexed_filename())
indexed_file = indexer.get_indexed_filename()
indexed_experiments = indexer.get_experiments_filename()
fast_mode = PhilIndex.params.dials.fast_mode
trust_beam_centre = PhilIndex.params.xia2.settings.trust_beam_centre
multi_sweep_indexing = PhilIndex.params.xia2.settings.multi_sweep_indexing
check_indexing_symmetry = PhilIndex.params.dials.check_indexing_symmetry
if check_indexing_symmetry and not (trust_beam_centre or fast_mode
or multi_sweep_indexing):
checksym = self.CheckIndexingSymmetry()
checksym.set_experiments_filename(indexed_experiments)
checksym.set_indexed_filename(indexed_file)
checksym.set_grid_search_scope(1)
checksym.run()
hkl_offset = checksym.get_hkl_offset()
logger.debug("hkl_offset: %s", str(hkl_offset))
if hkl_offset is not None and hkl_offset != (0, 0, 0):
reindex = self.Reindex()
reindex.set_hkl_offset(hkl_offset)
reindex.set_indexed_filename(indexed_file)
reindex.run()
indexed_file = reindex.get_reindexed_reflections_filename()
# do some scan-static refinement - run twice, first without outlier
# rejection as the model is too far from reality to do a sensible job of
# outlier rejection
refiner = self.Refine()
refiner.set_experiments_filename(indexed_experiments)
refiner.set_indexed_filename(
reindex.get_reindexed_reflections_filename())
refiner.set_outlier_algorithm(None)
refiner.run()
indexed_experiments = refiner.get_refined_experiments_filename(
)
# now again with outlier rejection (possibly)
refiner = self.Refine()
refiner.set_experiments_filename(indexed_experiments)
refiner.set_indexed_filename(indexed_file)
refiner.run()
indexed_experiments = refiner.get_refined_experiments_filename(
)
if self._indxr_input_lattice is None:
# FIXME in here should respect the input unit cell and lattice if provided
# FIXME from this (i) populate the helper table,
# (ii) try to avoid re-running the indexing
# step if we eliminate a solution as we have all of the refined results
# already available.
rbs = self.RefineBravaisSettings()
rbs.set_experiments_filename(indexed_experiments)
rbs.set_indexed_filename(indexed_file)
if PhilIndex.params.dials.fix_geometry:
rbs.set_detector_fix("all")
rbs.set_beam_fix("all")
elif PhilIndex.params.dials.fix_distance:
rbs.set_detector_fix("distance")
FileHandler.record_log_file(
"%s LATTICE" % self.get_indexer_full_name(),
rbs.get_log_file())
rbs.run()
for k in sorted(rbs.get_bravais_summary()):
summary = rbs.get_bravais_summary()[k]
# FIXME need to do this better - for the moment only accept lattices
# where R.M.S. deviation is less than twice P1 R.M.S. deviation.
if self._indxr_input_lattice is None:
if not summary["recommended"]:
continue
experiments = load.experiment_list(summary["experiments_file"],
check_format=False)
cryst = experiments.crystals()[0]
cs = crystal.symmetry(unit_cell=cryst.get_unit_cell(),
space_group=cryst.get_space_group())
lattice = str(
bravais_types.bravais_lattice(group=cs.space_group()))
cb_op = sgtbx.change_of_basis_op(str(summary["cb_op"]))
self._solutions[k] = {
"number": k,
"mosaic": 0.0,
"metric": summary["max_angular_difference"],
"rmsd": summary["rmsd"],
"nspots": summary["nspots"],
"lattice": lattice,
"cell": cs.unit_cell().parameters(),
"experiments_file": summary["experiments_file"],
"cb_op": str(cb_op),
}
self._solution = self.get_solution()
self._indxr_lattice = self._solution["lattice"]
for solution in self._solutions:
lattice = self._solutions[solution]["lattice"]
if (self._indxr_input_lattice is not None
and self._indxr_input_lattice != lattice):
continue
if lattice in self._indxr_other_lattice_cell:
if (self._indxr_other_lattice_cell[lattice]["metric"] <
self._solutions[solution]["metric"]):
continue
self._indxr_other_lattice_cell[lattice] = {
"metric": self._solutions[solution]["metric"],
"cell": self._solutions[solution]["cell"],
}
self._indxr_mosaic = self._solution["mosaic"]
experiments_file = self._solution["experiments_file"]
experiment_list = load.experiment_list(experiments_file)
self.set_indexer_experiment_list(experiment_list)
self.set_indexer_payload("experiments_filename", experiments_file)
# reindex the output reflection list to this solution
reindex = self.Reindex()
reindex.set_indexed_filename(indexed_file)
reindex.set_cb_op(self._solution["cb_op"])
reindex.set_space_group(
str(lattice_to_spacegroup_number(self._solution["lattice"])))
reindex.run()
indexed_file = reindex.get_reindexed_reflections_filename()
self.set_indexer_payload("indexed_filename", indexed_file)
else:
experiment_list = load.experiment_list(indexed_experiments)
self.set_indexer_experiment_list(experiment_list)
self.set_indexer_payload("experiments_filename",
indexed_experiments)
cryst = experiment_list.crystals()[0]
lattice = str(
bravais_types.bravais_lattice(group=cryst.get_space_group()))
self._indxr_lattice = lattice
self._solutions = {}
self._solutions[0] = {
"number": 0,
"mosaic": 0.0,
"metric": -1,
"rmsd": -1,
"nspots": -1,
"lattice": lattice,
"cell": cryst.get_unit_cell().parameters(),
"experiments_file": indexed_experiments,
"cb_op": "a,b,c",
}
self._indxr_other_lattice_cell[lattice] = {
"metric": self._solutions[0]["metric"],
"cell": self._solutions[0]["cell"],
}
def run_one_sweep(args):
sweep_information = args[0]
pointless_indexer_jiffy = args[1]
factory = args[2]
job_type = args[3]
if job_type:
DriverFactory.set_driver_type(job_type)
intgr = sweep_information['integrater']
hklin = sweep_information['corrected_intensities']
refiner = intgr.get_integrater_refiner()
# in here need to consider what to do if the user has
# assigned the pointgroup on the command line ...
if not self._scalr_input_pointgroup:
pointgroup, reindex_op, ntr = \
self._pointless_indexer_jiffy(hklin, refiner)
if ntr:
# Bug # 3373
Debug.write('Reindex to standard (PIJ): %s' % \
reindex_op)
intgr.set_integrater_reindex_operator(
reindex_op, compose = False)
reindex_op = 'h,k,l'
need_to_return = True
else:
# 27/FEB/08 to support user assignment of pointgroups
Debug.write('Using input pointgroup: %s' % \
self._scalr_input_pointgroup)
pointgroup = self._scalr_input_pointgroup
reindex_op = 'h,k,l'
intgr.set_integrater_reindex_operator(reindex_op)
intgr.set_integrater_spacegroup_number(
Syminfo.spacegroup_name_to_number(pointgroup))
sweep_information['corrected_intensities'] \
= intgr.get_integrater_corrected_intensities()
# convert the XDS_ASCII for this sweep to mtz - on the next
# get this should be in the correct setting...
hklin = sweep_information['corrected_intensities']
# now use pointless to make this conversion
# try with no conversion?!
pointless = self._factory.Pointless()
pointless.set_xdsin(hklin)
hklout = os.path.join(
self.get_working_directory(),
'%d_xds-pointgroup-unsorted.mtz' %pointless.get_xpid())
FileHandler.record_temporary_file(hklout)
pointless.set_hklout(hklout)
pointless.xds_to_mtz()
pointless = self._factory.Pointless()
pointless.set_hklin(hklout)
pointless.set_hklref(self._reference)
pointless.decide_pointgroup()
pointgroup = pointless.get_pointgroup()
reindex_op = pointless.get_reindex_operator()
# for debugging print out the reindexing operations and
# what have you...
Debug.write('Reindex to standard: %s' % reindex_op)
# this should send back enough information that this
# is in the correct pointgroup (from the call above) and
# also in the correct setting, from the interaction
# with the reference set... - though I guess that the
# spacegroup number should not have changed, right?
# set the reindex operation afterwards... though if the
# spacegroup number is the same this should make no
# difference, right?!
intgr.set_integrater_spacegroup_number(
Syminfo.spacegroup_name_to_number(pointgroup))
intgr.set_integrater_reindex_operator(reindex_op)
sweep_information['corrected_intensities'] \
= intgr.get_integrater_corrected_intensities()
# and copy the reflection file to the local directory
dname = sweep_information['dname']
sname = intgr.get_integrater_sweep_name()
hklin = sweep_information['corrected_intensities']
hklout = os.path.join(self.get_working_directory(),
'%s_%s.HKL' % (dname, sname))
Debug.write('Copying %s to %s' % (hklin, hklout))
shutil.copyfile(hklin, hklout)
# record just the local file name...
sweep_information['prepared_reflections'] = os.path.split(hklout)[-1]
return sweep_information
def get_output(self):
result = "Crystal: %s\n" % self._name
if self._aa_sequence:
result += "Sequence: %s\n" % self._aa_sequence.get_sequence()
for wavelength in self._wavelengths.keys():
result += self._wavelengths[wavelength].get_output()
scaler = self._get_scaler()
if scaler.get_scaler_finish_done():
for wname, xwav in self._wavelengths.iteritems():
for xsweep in xwav.get_sweeps():
idxr = xsweep._get_indexer()
if PhilIndex.params.xia2.settings.show_template:
result += "%s\n" % banner(
"Autoindexing %s (%s)" %
(idxr.get_indexer_sweep_name(),
idxr.get_template()))
else:
result += "%s\n" % banner(
"Autoindexing %s" % idxr.get_indexer_sweep_name())
result += "%s\n" % idxr.show_indexer_solutions()
intgr = xsweep._get_integrater()
if PhilIndex.params.xia2.settings.show_template:
result += "%s\n" % banner(
"Integrating %s (%s)" %
(intgr.get_integrater_sweep_name(),
intgr.get_template()))
else:
result += "%s\n" % banner(
"Integrating %s" %
intgr.get_integrater_sweep_name())
result += "%s\n" % intgr.show_per_image_statistics()
result += "%s\n" % banner("Scaling %s" % self.get_name())
for (
(dname, sname),
(limit, suggested),
) in scaler.get_scaler_resolution_limits().iteritems():
if suggested is None or limit == suggested:
result += "Resolution limit for %s/%s: %5.2f\n" % (
dname,
sname,
limit,
)
else:
result += (
"Resolution limit for %s/%s: %5.2f (%5.2f suggested)\n"
% (dname, sname, limit, suggested))
# this is now deprecated - be explicit in what you are
# asking for...
reflections_all = self.get_scaled_merged_reflections()
statistics_all = self._get_scaler().get_scaler_statistics()
# print some of these statistics, perhaps?
for key in statistics_all.keys():
result += format_statistics(statistics_all[key],
caption="For %s/%s/%s" % key)
# then print out some "derived" information based on the
# scaling - this is presented through the Scaler interface
# explicitly...
cell = self._get_scaler().get_scaler_cell()
cell_esd = self._get_scaler().get_scaler_cell_esd()
spacegroups = self._get_scaler().get_scaler_likely_spacegroups()
spacegroup = spacegroups[0]
resolution = self._get_scaler().get_scaler_highest_resolution()
from cctbx import sgtbx
sg = sgtbx.space_group_type(str(spacegroup))
spacegroup = sg.lookup_symbol()
CIF.set_spacegroup(sg)
mmCIF.set_spacegroup(sg)
if len(self._wavelengths) == 1:
CIF.set_wavelengths(
[w.get_wavelength() for w in self._wavelengths.itervalues()])
mmCIF.set_wavelengths(
[w.get_wavelength() for w in self._wavelengths.itervalues()])
else:
for wavelength in self._wavelengths.keys():
full_wave_name = "%s_%s_%s" % (
self._project._name,
self._name,
wavelength,
)
CIF.get_block(full_wave_name)[
"_diffrn_radiation_wavelength"] = self._wavelengths[
wavelength].get_wavelength()
mmCIF.get_block(full_wave_name)[
"_diffrn_radiation_wavelength"] = self._wavelengths[
wavelength].get_wavelength()
CIF.set_wavelengths({
name: wave.get_wavelength()
for name, wave in self._wavelengths.iteritems()
})
mmCIF.set_wavelengths({
name: wave.get_wavelength()
for name, wave in self._wavelengths.iteritems()
})
result += "Assuming spacegroup: %s\n" % spacegroup
if len(spacegroups) > 1:
result += "Other likely alternatives are:\n"
for sg in spacegroups[1:]:
result += "%s\n" % sg
if cell_esd:
from libtbx.utils import format_float_with_standard_uncertainty
def match_formatting(dimA, dimB):
def conditional_split(s):
return ((s[:s.index(".")],
s[s.index("."):]) if "." in s else (s, ""))
A, B = conditional_split(dimA), conditional_split(dimB)
maxlen = (max(len(A[0]), len(B[0])), max(len(A[1]), len(B[1])))
return (
A[0].rjust(maxlen[0]) + A[1].ljust(maxlen[1]),
B[0].rjust(maxlen[0]) + B[1].ljust(maxlen[1]),
)
formatted_cell_esds = tuple(
format_float_with_standard_uncertainty(v, sd)
for v, sd in zip(cell, cell_esd))
formatted_rows = (formatted_cell_esds[0:3],
formatted_cell_esds[3:6])
formatted_rows = zip(*(match_formatting(l, a)
for l, a in zip(*formatted_rows)))
result += "Unit cell (with estimated std devs):\n"
result += "%s %s %s\n%s %s %s\n" % (formatted_rows[0] +
formatted_rows[1])
else:
result += "Unit cell:\n"
result += "%7.3f %7.3f %7.3f\n%7.3f %7.3f %7.3f\n" % tuple(cell)
# now, use this information and the sequence (if provided)
# and also matthews_coef (should I be using this directly, here?)
# to compute a likely number of molecules in the ASU and also
# the solvent content...
if self._aa_sequence:
residues = self._aa_sequence.get_sequence()
if residues:
nres = len(residues)
# first compute the number of molecules using the K&R
# method
nmol = compute_nmol(
cell[0],
cell[1],
cell[2],
cell[3],
cell[4],
cell[5],
spacegroup,
resolution,
nres,
)
# then compute the solvent fraction
solvent = compute_solvent(
cell[0],
cell[1],
cell[2],
cell[3],
cell[4],
cell[5],
spacegroup,
nmol,
nres,
)
result += "Likely number of molecules in ASU: %d\n" % nmol
result += "Giving solvent fraction: %4.2f\n" % solvent
self._nmol = nmol
if isinstance(reflections_all, type({})):
for format in reflections_all.keys():
result += "%s format:\n" % format
reflections = reflections_all[format]
if isinstance(reflections, type({})):
for wavelength in reflections.keys():
target = FileHandler.get_data_file(
reflections[wavelength])
result += "Scaled reflections (%s): %s\n" % (
wavelength, target)
else:
target = FileHandler.get_data_file(reflections)
result += "Scaled reflections: %s\n" % target
CIF.write_cif()
mmCIF.write_cif()
return result
def _scale_finish(self):
# compute anomalous signals if anomalous
if self.get_scaler_anomalous():
for key in self._scalr_scaled_refl_files:
f = self._scalr_scaled_refl_files[key]
from iotbx import mtz
m = mtz.object(f)
if m.space_group().is_centric():
Debug.write('Spacegroup is centric: %s' % f)
continue
Debug.write('Running anomalous signal analysis on %s' % f)
a_s = anomalous_signals(f)
self._scalr_statistics[
(self._scalr_pname, self._scalr_xname, key)
]['dF/F'] = [a_s[0]]
self._scalr_statistics[
(self._scalr_pname, self._scalr_xname, key)
]['dI/s(dI)'] = [a_s[1]]
# next transform to F's from I's etc.
if len(self._scalr_scaled_refl_files.keys()) == 0:
raise RuntimeError, 'no reflection files stored'
# run xia2.report on each unmerged mtz file
from iotbx.reflection_file_reader import any_reflection_file
from iotbx import mtz
from cctbx.array_family import flex
for wavelength in self._scalr_scaled_refl_files.keys():
mtz_unmerged = self._scalr_scaled_reflection_files['mtz_unmerged'][wavelength]
reader = any_reflection_file(mtz_unmerged)
mtz_object = reader.file_content()
batches = mtz_object.as_miller_arrays_dict()['HKL_base', 'HKL_base', 'BATCH']
dose = flex.double(batches.size(), -1)
batch_to_dose = self.get_batch_to_dose()
for i, b in enumerate(batches.data()):
dose[i] = batch_to_dose[b]
c = mtz_object.crystals()[0]
d = c.datasets()[0]
d.add_column('DOSE', 'R').set_values(dose.as_float())
tmp_mtz = os.path.join(self.get_working_directory(), 'dose_tmp.mtz')
mtz_object.write(tmp_mtz)
hklin = tmp_mtz
FileHandler.record_temporary_file(hklin)
from xia2.Wrappers.XIA.Report import Report
report = Report()
report.set_working_directory(self.get_working_directory())
report.set_mtz_filename(hklin)
htmlout = os.path.join(
self.get_working_directory(), '%s_%s_%s_report.html' %(
self._scalr_pname, self._scalr_xname, wavelength))
report.set_html_filename(htmlout)
report.set_chef_min_completeness(0.95) # sensible?
from xia2.lib.bits import auto_logfiler
auto_logfiler(report)
try:
report.run()
except Exception, e:
Debug.write('xia2.report failed:')
Debug.write(str(e))
continue
FileHandler.record_html_file(
'%s %s %s report' %(
self._scalr_pname, self._scalr_xname, wavelength), htmlout)
def _scale_prepare(self):
'''Prepare the data for scaling - this will reindex it the
reflections to the correct pointgroup and setting, for instance,
and move the reflection files to the scale directory.'''
Citations.cite('xds')
Citations.cite('ccp4')
Citations.cite('pointless')
# GATHER phase - get the reflection files together... note that
# it is not necessary in here to keep the batch information as we
# don't wish to rebatch the reflections prior to scaling.
# FIXME need to think about what I will do about the radiation
# damage analysis in here...
self._sweep_information = { }
# FIXME in here I want to record the batch number to
# epoch mapping as per the CCP4 Scaler implementation.
Journal.block(
'gathering', self.get_scaler_xcrystal().get_name(), 'XDS',
{'working directory':self.get_working_directory()})
for epoch in self._scalr_integraters.keys():
intgr = self._scalr_integraters[epoch]
pname, xname, dname = intgr.get_integrater_project_info()
sname = intgr.get_integrater_sweep_name()
self._sweep_information[epoch] = {
'pname':pname,
'xname':xname,
'dname':dname,
'integrater':intgr,
'corrected_intensities':intgr.get_integrater_corrected_intensities(),
'prepared_reflections':None,
'scaled_reflections':None,
'header':intgr.get_header(),
'batches':intgr.get_integrater_batches(),
'image_to_epoch':intgr.get_integrater_sweep(
).get_image_to_epoch(),
'image_to_dose':{},
'batch_offset':0,
'sname':sname
}
Journal.entry({'adding data from':'%s/%s/%s' % \
(xname, dname, sname)})
# what are these used for?
# pname / xname / dname - dataset identifiers
# image to epoch / batch offset / batches - for RD analysis
Debug.write('For EPOCH %s have:' % str(epoch))
Debug.write('ID = %s/%s/%s' % (pname, xname, dname))
Debug.write('SWEEP = %s' % intgr.get_integrater_sweep_name())
# next work through all of the reflection files and make sure that
# they are XDS_ASCII format...
epochs = self._sweep_information.keys()
epochs.sort()
self._first_epoch = min(epochs)
self._scalr_pname = self._sweep_information[epochs[0]]['pname']
self._scalr_xname = self._sweep_information[epochs[0]]['xname']
for epoch in epochs:
intgr = self._scalr_integraters[epoch]
pname = self._sweep_information[epoch]['pname']
xname = self._sweep_information[epoch]['xname']
dname = self._sweep_information[epoch]['dname']
sname = self._sweep_information[epoch]['sname']
if self._scalr_pname != pname:
raise RuntimeError, 'all data must have a common project name'
xname = self._sweep_information[epoch]['xname']
if self._scalr_xname != xname:
raise RuntimeError, \
'all data for scaling must come from one crystal'
xsh = XDSScalerHelper()
xsh.set_working_directory(self.get_working_directory())
hklin = self._sweep_information[epoch]['corrected_intensities']
hklout = os.path.join(self.get_working_directory(),
'%s_%s_%s_%s_CORRECTED.HKL' %(
pname, xname, dname, sname))
sweep = intgr.get_integrater_sweep()
if sweep.get_frames_to_process() is not None:
offset = intgr.get_frame_offset()
#print "offset: %d" %offset
start, end = sweep.get_frames_to_process()
start -= offset
end -= offset
#end += 1 ????
#print "limiting batches: %d-%d" %(start, end)
xsh.limit_batches(hklin, hklout, start, end)
self._sweep_information[epoch]['corrected_intensities'] = hklout
# if there is more than one sweep then compare the lattices
# and eliminate all but the lowest symmetry examples if
# there are more than one...
# -------------------------------------------------
# Ensure that the integration lattices are the same
# -------------------------------------------------
need_to_return = False
if len(self._sweep_information.keys()) > 1:
lattices = []
# FIXME run this stuff in parallel as well...
for epoch in self._sweep_information.keys():
intgr = self._sweep_information[epoch]['integrater']
hklin = self._sweep_information[epoch]['corrected_intensities']
refiner = intgr.get_integrater_refiner()
if self._scalr_input_pointgroup:
pointgroup = self._scalr_input_pointgroup
reindex_op = 'h,k,l'
ntr = False
else:
pointgroup, reindex_op, ntr = \
self._pointless_indexer_jiffy(hklin, refiner)
Debug.write('X1698: %s: %s' % (pointgroup, reindex_op))
lattice = Syminfo.get_lattice(pointgroup)
if not lattice in lattices:
lattices.append(lattice)
if ntr:
# if we need to return, we should logically reset
# any reindexing operator right? right here all
# we are talking about is the correctness of
# individual pointgroups?? Bug # 3373
reindex_op = 'h,k,l'
# actually, should this not be done "by magic"
# when a new pointgroup is assigned in the
# pointless indexer jiffy above?!
intgr.set_integrater_reindex_operator(
reindex_op, compose = False)
need_to_return = True
# bug # 2433 - need to ensure that all of the lattice
# conclusions were the same...
if len(lattices) > 1:
ordered_lattices = []
for l in lattices_in_order():
if l in lattices:
ordered_lattices.append(l)
correct_lattice = ordered_lattices[0]
Debug.write('Correct lattice asserted to be %s' % \
correct_lattice)
# transfer this information back to the indexers
for epoch in self._sweep_information.keys():
integrater = self._sweep_information[
epoch]['integrater']
refiner = integrater.get_integrater_refiner()
sname = integrater.get_integrater_sweep_name()
if not refiner:
continue
state = refiner.set_refiner_asserted_lattice(
correct_lattice)
if state == refiner.LATTICE_CORRECT:
Debug.write('Lattice %s ok for sweep %s' % \
(correct_lattice, sname))
elif state == refiner.LATTICE_IMPOSSIBLE:
raise RuntimeError, 'Lattice %s impossible for %s' % \
(correct_lattice, sname)
elif state == refiner.LATTICE_POSSIBLE:
Debug.write('Lattice %s assigned for sweep %s' % \
(correct_lattice, sname))
need_to_return = True
# if one or more of them was not in the lowest lattice,
# need to return here to allow reprocessing
if need_to_return:
self.set_scaler_done(False)
self.set_scaler_prepare_done(False)
return
# next if there is more than one sweep then generate
# a merged reference reflection file to check that the
# setting for all reflection files is the same...
# if we get to here then all data was processed with the same
# lattice
# ----------------------------------------------------------
# next ensure that all sweeps are set in the correct setting
# ----------------------------------------------------------
if self.get_scaler_reference_reflection_file():
self._reference = self.get_scaler_reference_reflection_file()
Debug.write('Using HKLREF %s' % self._reference)
md = self._factory.Mtzdump()
md.set_hklin(self.get_scaler_reference_reflection_file())
md.dump()
self._xds_spacegroup = Syminfo.spacegroup_name_to_number(
md.get_spacegroup())
Debug.write('Spacegroup %d' % self._xds_spacegroup)
elif PhilIndex.params.xia2.settings.scale.reference_reflection_file:
self._reference = PhilIndex.params.xia2.settings.scale.reference_reflection_file
Debug.write('Using HKLREF %s' % self._reference)
md = self._factory.Mtzdump()
md.set_hklin(PhilIndex.params.xia2.settings.scale.reference_reflection_file)
md.dump()
self._xds_spacegroup = Syminfo.spacegroup_name_to_number(
md.get_spacegroup())
Debug.write('Spacegroup %d' % self._xds_spacegroup)
params = PhilIndex.params
use_brehm_diederichs = params.xia2.settings.use_brehm_diederichs
if len(self._sweep_information.keys()) > 1 and use_brehm_diederichs:
brehm_diederichs_files_in = []
for epoch in self._sweep_information.keys():
intgr = self._sweep_information[epoch]['integrater']
hklin = self._sweep_information[epoch]['corrected_intensities']
refiner = intgr.get_integrater_refiner()
# in here need to consider what to do if the user has
# assigned the pointgroup on the command line ...
if not self._scalr_input_pointgroup:
pointgroup, reindex_op, ntr = \
self._pointless_indexer_jiffy(hklin, refiner)
if ntr:
# Bug # 3373
Debug.write('Reindex to standard (PIJ): %s' % \
reindex_op)
intgr.set_integrater_reindex_operator(
reindex_op, compose = False)
reindex_op = 'h,k,l'
need_to_return = True
else:
# 27/FEB/08 to support user assignment of pointgroups
Debug.write('Using input pointgroup: %s' % \
self._scalr_input_pointgroup)
pointgroup = self._scalr_input_pointgroup
reindex_op = 'h,k,l'
intgr.set_integrater_reindex_operator(reindex_op)
intgr.set_integrater_spacegroup_number(
Syminfo.spacegroup_name_to_number(pointgroup))
self._sweep_information[epoch]['corrected_intensities'] \
= intgr.get_integrater_corrected_intensities()
# convert the XDS_ASCII for this sweep to mtz - on the next
# get this should be in the correct setting...
dname = self._sweep_information[epoch]['dname']
sname = intgr.get_integrater_sweep_name()
hklin = self._sweep_information[epoch]['corrected_intensities']
hklout = os.path.join(self.get_working_directory(),
'%s_%s.mtz' % (dname, sname))
FileHandler.record_temporary_file(hklout)
# now use pointless to make this conversion
pointless = self._factory.Pointless()
pointless.set_xdsin(hklin)
pointless.set_hklout(hklout)
pointless.xds_to_mtz()
brehm_diederichs_files_in.append(hklout)
# now run cctbx.brehm_diederichs to figure out the indexing hand for
# each sweep
from xia2.Wrappers.Cctbx.BrehmDiederichs import BrehmDiederichs
brehm_diederichs = BrehmDiederichs()
brehm_diederichs.set_working_directory(self.get_working_directory())
auto_logfiler(brehm_diederichs)
brehm_diederichs.set_input_filenames(brehm_diederichs_files_in)
# 1 or 3? 1 seems to work better?
brehm_diederichs.set_asymmetric(1)
brehm_diederichs.run()
reindexing_dict = brehm_diederichs.get_reindexing_dict()
for epoch in self._sweep_information.keys():
intgr = self._sweep_information[epoch]['integrater']
dname = self._sweep_information[epoch]['dname']
sname = intgr.get_integrater_sweep_name()
hklin = self._sweep_information[epoch]['corrected_intensities']
hklout = os.path.join(self.get_working_directory(),
'%s_%s.mtz' % (dname, sname))
# apply the reindexing operator
intgr.set_integrater_reindex_operator(reindex_op)
# and copy the reflection file to the local directory
hklin = self._sweep_information[epoch]['corrected_intensities']
hklout = os.path.join(self.get_working_directory(),
'%s_%s.HKL' % (dname, sname))
Debug.write('Copying %s to %s' % (hklin, hklout))
shutil.copyfile(hklin, hklout)
# record just the local file name...
self._sweep_information[epoch][
'prepared_reflections'] = os.path.split(hklout)[-1]
elif len(self._sweep_information.keys()) > 1 and \
not self._reference:
# need to generate a reference reflection file - generate this
# from the reflections in self._first_epoch
#
# FIXME this should really use the Brehm and Diederichs method
# if you have lots of little sweeps...
intgr = self._sweep_information[self._first_epoch]['integrater']
hklin = self._sweep_information[epoch]['corrected_intensities']
refiner = intgr.get_integrater_refiner()
if self._scalr_input_pointgroup:
Debug.write('Using input pointgroup: %s' % \
self._scalr_input_pointgroup)
pointgroup = self._scalr_input_pointgroup
ntr = False
reindex_op = 'h,k,l'
else:
pointgroup, reindex_op, ntr = self._pointless_indexer_jiffy(
hklin, refiner)
Debug.write('X1698: %s: %s' % (pointgroup, reindex_op))
reference_reindex_op = intgr.get_integrater_reindex_operator()
if ntr:
# Bug # 3373
intgr.set_integrater_reindex_operator(
reindex_op, compose = False)
reindex_op = 'h,k,l'
need_to_return = True
self._xds_spacegroup = Syminfo.spacegroup_name_to_number(pointgroup)
# next pass this reindexing operator back to the source
# of the reflections
intgr.set_integrater_reindex_operator(reindex_op)
intgr.set_integrater_spacegroup_number(
Syminfo.spacegroup_name_to_number(pointgroup))
self._sweep_information[epoch]['corrected_intensities'] \
= intgr.get_integrater_corrected_intensities()
hklin = self._sweep_information[epoch]['corrected_intensities']
hklout = os.path.join(self.get_working_directory(),
'xds-pointgroup-reference-unsorted.mtz')
FileHandler.record_temporary_file(hklout)
# now use pointless to handle this conversion
pointless = self._factory.Pointless()
pointless.set_xdsin(hklin)
pointless.set_hklout(hklout)
pointless.xds_to_mtz()
self._reference = hklout
if self._reference:
from xia2.Driver.DriverFactory import DriverFactory
def run_one_sweep(args):
sweep_information = args[0]
pointless_indexer_jiffy = args[1]
factory = args[2]
job_type = args[3]
if job_type:
DriverFactory.set_driver_type(job_type)
intgr = sweep_information['integrater']
hklin = sweep_information['corrected_intensities']
refiner = intgr.get_integrater_refiner()
# in here need to consider what to do if the user has
# assigned the pointgroup on the command line ...
if not self._scalr_input_pointgroup:
pointgroup, reindex_op, ntr = \
self._pointless_indexer_jiffy(hklin, refiner)
if ntr:
# Bug # 3373
Debug.write('Reindex to standard (PIJ): %s' % \
reindex_op)
intgr.set_integrater_reindex_operator(
reindex_op, compose = False)
reindex_op = 'h,k,l'
need_to_return = True
else:
# 27/FEB/08 to support user assignment of pointgroups
Debug.write('Using input pointgroup: %s' % \
self._scalr_input_pointgroup)
pointgroup = self._scalr_input_pointgroup
reindex_op = 'h,k,l'
intgr.set_integrater_reindex_operator(reindex_op)
intgr.set_integrater_spacegroup_number(
Syminfo.spacegroup_name_to_number(pointgroup))
sweep_information['corrected_intensities'] \
= intgr.get_integrater_corrected_intensities()
# convert the XDS_ASCII for this sweep to mtz - on the next
# get this should be in the correct setting...
hklin = sweep_information['corrected_intensities']
# now use pointless to make this conversion
# try with no conversion?!
pointless = self._factory.Pointless()
pointless.set_xdsin(hklin)
hklout = os.path.join(
self.get_working_directory(),
'%d_xds-pointgroup-unsorted.mtz' %pointless.get_xpid())
FileHandler.record_temporary_file(hklout)
pointless.set_hklout(hklout)
pointless.xds_to_mtz()
pointless = self._factory.Pointless()
pointless.set_hklin(hklout)
pointless.set_hklref(self._reference)
pointless.decide_pointgroup()
pointgroup = pointless.get_pointgroup()
reindex_op = pointless.get_reindex_operator()
# for debugging print out the reindexing operations and
# what have you...
Debug.write('Reindex to standard: %s' % reindex_op)
# this should send back enough information that this
# is in the correct pointgroup (from the call above) and
# also in the correct setting, from the interaction
# with the reference set... - though I guess that the
# spacegroup number should not have changed, right?
# set the reindex operation afterwards... though if the
# spacegroup number is the same this should make no
# difference, right?!
intgr.set_integrater_spacegroup_number(
Syminfo.spacegroup_name_to_number(pointgroup))
intgr.set_integrater_reindex_operator(reindex_op)
sweep_information['corrected_intensities'] \
= intgr.get_integrater_corrected_intensities()
# and copy the reflection file to the local directory
dname = sweep_information['dname']
sname = intgr.get_integrater_sweep_name()
hklin = sweep_information['corrected_intensities']
hklout = os.path.join(self.get_working_directory(),
'%s_%s.HKL' % (dname, sname))
Debug.write('Copying %s to %s' % (hklin, hklout))
shutil.copyfile(hklin, hklout)
# record just the local file name...
sweep_information['prepared_reflections'] = os.path.split(hklout)[-1]
return sweep_information
from libtbx import easy_mp
params = PhilIndex.get_python_object()
mp_params = params.xia2.settings.multiprocessing
njob = mp_params.njob
if njob > 1:
# cache drivertype
drivertype = DriverFactory.get_driver_type()
args = [
(self._sweep_information[epoch], self._pointless_indexer_jiffy,
self._factory, mp_params.type)
for epoch in self._sweep_information.keys()]
results_list = easy_mp.parallel_map(
run_one_sweep, args, params=None,
processes=njob,
method="threading",
asynchronous=True,
callback=None,
preserve_order=True,
preserve_exception_message=True)
# restore drivertype
DriverFactory.set_driver_type(drivertype)
# results should be given back in the same order
for i, epoch in enumerate(self._sweep_information.keys()):
self._sweep_information[epoch] = results_list[i]
else:
for epoch in self._sweep_information.keys():
self._sweep_information[epoch] = run_one_sweep(
(self._sweep_information[epoch], self._pointless_indexer_jiffy,
self._factory, None))
else:
# convert the XDS_ASCII for this sweep to mtz
epoch = self._first_epoch
intgr = self._sweep_information[epoch]['integrater']
refiner = intgr.get_integrater_refiner()
sname = intgr.get_integrater_sweep_name()
hklout = os.path.join(self.get_working_directory(),
'%s-pointless.mtz' % sname)
FileHandler.record_temporary_file(hklout)
pointless = self._factory.Pointless()
pointless.set_xdsin(self._sweep_information[epoch]['corrected_intensities'])
pointless.set_hklout(hklout)
pointless.xds_to_mtz()
# run it through pointless interacting with the
# Indexer which belongs to this sweep
hklin = hklout
if self._scalr_input_pointgroup:
Debug.write('Using input pointgroup: %s' % \
self._scalr_input_pointgroup)
pointgroup = self._scalr_input_pointgroup
ntr = False
reindex_op = 'h,k,l'
else:
pointgroup, reindex_op, ntr = self._pointless_indexer_jiffy(
hklin, refiner)
if ntr:
# if we need to return, we should logically reset
# any reindexing operator right? right here all
# we are talking about is the correctness of
# individual pointgroups?? Bug # 3373
reindex_op = 'h,k,l'
intgr.set_integrater_reindex_operator(
reindex_op, compose = False)
need_to_return = True
self._xds_spacegroup = Syminfo.spacegroup_name_to_number(pointgroup)
# next pass this reindexing operator back to the source
# of the reflections
intgr.set_integrater_reindex_operator(reindex_op)
intgr.set_integrater_spacegroup_number(
Syminfo.spacegroup_name_to_number(pointgroup))
self._sweep_information[epoch]['corrected_intensities'] \
= intgr.get_integrater_corrected_intensities()
hklin = self._sweep_information[epoch]['corrected_intensities']
dname = self._sweep_information[epoch]['dname']
hklout = os.path.join(self.get_working_directory(),
'%s_%s.HKL' % (dname, sname))
# and copy the reflection file to the local
# directory
Debug.write('Copying %s to %s' % (hklin, hklout))
shutil.copyfile(hklin, hklout)
# record just the local file name...
self._sweep_information[epoch][
'prepared_reflections'] = os.path.split(hklout)[-1]
if need_to_return:
self.set_scaler_done(False)
self.set_scaler_prepare_done(False)
return
unit_cell_list = []
for epoch in self._sweep_information.keys():
integrater = self._sweep_information[epoch]['integrater']
cell = integrater.get_integrater_cell()
n_ref = integrater.get_integrater_n_ref()
Debug.write('Cell for %s: %.2f %.2f %.2f %.2f %.2f %.2f' % \
(integrater.get_integrater_sweep_name(),
cell[0], cell[1], cell[2],
cell[3], cell[4], cell[5]))
Debug.write('=> %d reflections' % n_ref)
unit_cell_list.append((cell, n_ref))
self._scalr_cell = compute_average_unit_cell(unit_cell_list)
self._scalr_resolution_limits = { }
Debug.write('Determined unit cell: %.2f %.2f %.2f %.2f %.2f %.2f' % \
tuple(self._scalr_cell))
if os.path.exists(os.path.join(
self.get_working_directory(),
'REMOVE.HKL')):
os.remove(os.path.join(
self.get_working_directory(),
'REMOVE.HKL'))
Debug.write('Deleting REMOVE.HKL at end of scale prepare.')
return
def get_output(self):
result = 'Crystal: %s\n' % self._name
if self._aa_sequence:
result += 'Sequence: %s\n' % self._aa_sequence.get_sequence()
for wavelength in self._wavelengths.keys():
result += self._wavelengths[wavelength].get_output()
scaler = self._get_scaler()
if scaler.get_scaler_finish_done():
for wname, xwav in self._wavelengths.iteritems():
for xsweep in xwav.get_sweeps():
idxr = xsweep._get_indexer()
if PhilIndex.params.xia2.settings.show_template:
result += '%s\n' %banner('Autoindexing %s (%s)' %(
idxr.get_indexer_sweep_name(), idxr.get_template()))
else:
result += '%s\n' %banner(
'Autoindexing %s' %idxr.get_indexer_sweep_name())
result += '%s\n' %idxr.show_indexer_solutions()
intgr = xsweep._get_integrater()
if PhilIndex.params.xia2.settings.show_template:
result += '%s\n' %banner('Integrating %s (%s)' %(
intgr.get_integrater_sweep_name(), intgr.get_template()))
else:
result += '%s\n' %banner(
'Integrating %s' %intgr.get_integrater_sweep_name())
result += '%s\n' % intgr.show_per_image_statistics()
result += '%s\n' %banner('Scaling %s' %self.get_name())
for (dname, sname), (limit, suggested) in scaler.get_scaler_resolution_limits().iteritems():
if suggested is None or limit == suggested:
result += 'Resolution limit for %s/%s: %5.2f\n' %(dname, sname, limit)
else:
result += 'Resolution limit for %s/%s: %5.2f (%5.2f suggested)\n' %(dname, sname, limit, suggested)
# this is now deprecated - be explicit in what you are
# asking for...
reflections_all = self.get_scaled_merged_reflections()
statistics_all = self._get_scaler().get_scaler_statistics()
# print some of these statistics, perhaps?
for key in statistics_all.keys():
result += format_statistics(statistics_all[key], caption='For %s/%s/%s' % key)
# then print out some "derived" information based on the
# scaling - this is presented through the Scaler interface
# explicitly...
cell = self._get_scaler().get_scaler_cell()
cell_esd = self._get_scaler().get_scaler_cell_esd()
spacegroups = self._get_scaler().get_scaler_likely_spacegroups()
spacegroup = spacegroups[0]
resolution = self._get_scaler().get_scaler_highest_resolution()
from cctbx import sgtbx
sg = sgtbx.space_group_type(str(spacegroup))
spacegroup = sg.lookup_symbol()
CIF.set_spacegroup(sg)
mmCIF.set_spacegroup(sg)
if len(self._wavelengths) == 1:
CIF.set_wavelengths([w.get_wavelength() for w in self._wavelengths.itervalues()])
mmCIF.set_wavelengths([w.get_wavelength() for w in self._wavelengths.itervalues()])
else:
for wavelength in self._wavelengths.keys():
full_wave_name = '%s_%s_%s' % (self._project._name, self._name, wavelength)
CIF.get_block(full_wave_name)['_diffrn_radiation_wavelength'] = \
self._wavelengths[wavelength].get_wavelength()
mmCIF.get_block(full_wave_name)['_diffrn_radiation_wavelength'] = \
self._wavelengths[wavelength].get_wavelength()
CIF.set_wavelengths({name: wave.get_wavelength() for name, wave in self._wavelengths.iteritems()})
mmCIF.set_wavelengths({name: wave.get_wavelength() for name, wave in self._wavelengths.iteritems()})
result += 'Assuming spacegroup: %s\n' % spacegroup
if len(spacegroups) > 1:
result += 'Other likely alternatives are:\n'
for sg in spacegroups[1:]:
result += '%s\n' % sg
if cell_esd:
from libtbx.utils import format_float_with_standard_uncertainty
def match_formatting(dimA, dimB):
def conditional_split(s):
return (s[:s.index('.')],s[s.index('.'):]) if '.' in s else (s, '')
A, B = conditional_split(dimA), conditional_split(dimB)
maxlen = (max(len(A[0]), len(B[0])), max(len(A[1]), len(B[1])))
return (
A[0].rjust(maxlen[0])+A[1].ljust(maxlen[1]),
B[0].rjust(maxlen[0])+B[1].ljust(maxlen[1])
)
formatted_cell_esds = tuple(format_float_with_standard_uncertainty(v, sd) for v, sd in zip(cell, cell_esd))
formatted_rows = (formatted_cell_esds[0:3], formatted_cell_esds[3:6])
formatted_rows = zip(*(match_formatting(l, a) for l, a in zip(*formatted_rows)))
result += 'Unit cell (with estimated std devs):\n'
result += '%s %s %s\n%s %s %s\n' % (formatted_rows[0] + formatted_rows[1])
else:
result += 'Unit cell:\n'
result += '%7.3f %7.3f %7.3f\n%7.3f %7.3f %7.3f\n' % tuple(cell)
# now, use this information and the sequence (if provided)
# and also matthews_coef (should I be using this directly, here?)
# to compute a likely number of molecules in the ASU and also
# the solvent content...
if self._aa_sequence:
residues = self._aa_sequence.get_sequence()
if residues:
nres = len(residues)
# first compute the number of molecules using the K&R
# method
nmol = compute_nmol(cell[0], cell[1], cell[2],
cell[3], cell[4], cell[5],
spacegroup, resolution, nres)
# then compute the solvent fraction
solvent = compute_solvent(cell[0], cell[1], cell[2],
cell[3], cell[4], cell[5],
spacegroup, nmol, nres)
result += 'Likely number of molecules in ASU: %d\n' % nmol
result += 'Giving solvent fraction: %4.2f\n' % solvent
self._nmol = nmol
if type(reflections_all) == type({}):
for format in reflections_all.keys():
result += '%s format:\n' % format
reflections = reflections_all[format]
if type(reflections) == type({}):
for wavelength in reflections.keys():
target = FileHandler.get_data_file(
reflections[wavelength])
result += 'Scaled reflections (%s): %s\n' % \
(wavelength, target)
else:
target = FileHandler.get_data_file(
reflections)
result += 'Scaled reflections: %s\n' % target
CIF.write_cif()
mmCIF.write_cif()
return result
def _mosflm_parallel_integrate(self):
'''Perform the integration as before, but this time as a
number of parallel Mosflm jobs (hence, in separate directories)
and including a step of pre-refinement of the mosaic spread and
missets. This will all be kind of explicit and hence probably
messy!'''
refinr = self.get_integrater_refiner()
lattice = refinr.get_refiner_lattice()
spacegroup_number = lattice_to_spacegroup(lattice)
mosaic = refinr.get_refiner_payload('mosaic')
beam = refinr.get_refiner_payload('beam')
distance = refinr.get_refiner_payload('distance')
matrix = refinr.get_refiner_payload('mosflm_orientation_matrix')
integration_params = refinr.get_refiner_payload(
'mosflm_integration_parameters')
if integration_params:
if 'separation' in integration_params:
self.set_integrater_parameter(
'mosflm', 'separation',
'%s %s' % tuple(integration_params['separation']))
if 'raster' in integration_params:
self.set_integrater_parameter(
'mosflm', 'raster',
'%d %d %d %d %d' % tuple(integration_params['raster']))
refinr.set_refiner_payload('mosflm_integration_parameters', None)
pname, xname, dname = self.get_integrater_project_info()
# what follows below should (i) be run in separate directories
# and (ii) be repeated N=parallel times.
nproc = PhilIndex.params.xia2.settings.multiprocessing.nproc
parallel = nproc
# FIXME this is something of a kludge - if too few frames refinement
# and integration does not work well... ideally want at least 15
# frames / chunk (say)
nframes = self._intgr_wedge[1] - self._intgr_wedge[0] + 1
if parallel > nframes / 15:
parallel = nframes // 15
if not parallel:
raise RuntimeError, 'parallel not set'
if parallel < 2:
raise RuntimeError, 'parallel not parallel: %s' % parallel
jobs = []
hklouts = []
nref = 0
# calculate the chunks to use
offset = self.get_frame_offset()
start = self._intgr_wedge[0] - offset
end = self._intgr_wedge[1] - offset
left_images = 1 + end - start
left_chunks = parallel
chunks = []
while left_images > 0:
size = left_images // left_chunks
chunks.append((start, start + size - 1))
start += size
left_images -= size
left_chunks -= 1
summary_files = []
for j in range(parallel):
# make some working directories, as necessary - chunk-(0:N-1)
wd = os.path.join(self.get_working_directory(),
'chunk-%d' % j)
if not os.path.exists(wd):
os.makedirs(wd)
job = MosflmIntegrate()
job.set_working_directory(wd)
auto_logfiler(job)
l = refinr.get_refiner_lattice()
# create the starting point
f = open(os.path.join(wd, 'xiaintegrate-%s.mat' % l), 'w')
for m in matrix:
f.write(m)
f.close()
spacegroup_number = lattice_to_spacegroup(lattice)
job.set_refine_profiles(self._mosflm_refine_profiles)
# N.B. for harvesting need to append N to dname.
if pname is not None and xname is not None and dname is not None:
Debug.write('Harvesting: %s/%s/%s' %
(pname, xname, dname))
harvest_dir = self.get_working_directory()
temp_dname = '%s_%s' % \
(dname, self.get_integrater_sweep_name())
job.set_pname_xname_dname(pname, xname, temp_dname)
job.set_template(os.path.basename(self.get_template()))
job.set_directory(self.get_directory())
# check for ice - and if so, exclude (ranges taken from
# XDS documentation)
if self.get_integrater_ice() != 0:
Debug.write('Excluding ice rings')
job.set_exclude_ice(True)
# exclude specified resolution ranges
if len(self.get_integrater_excluded_regions()) != 0:
regions = self.get_integrater_excluded_regions()
Debug.write('Excluding regions: %s' % `regions`)
job.set_exclude_regions(regions)
mask = standard_mask(self.get_detector())
for m in mask:
job.add_instruction(m)
job.set_input_mat_file('xiaintegrate-%s.mat' % l)
job.set_beam_centre(beam)
job.set_distance(distance)
job.set_space_group_number(spacegroup_number)
job.set_mosaic(mosaic)
if self.get_wavelength_prov() == 'user':
job.set_wavelength(self.get_wavelength())
parameters = self.get_integrater_parameters('mosflm')
job.update_parameters(parameters)
if self._mosflm_gain:
job.set_gain(self._mosflm_gain)
# check for resolution limits
if self._intgr_reso_high > 0.0:
job.set_d_min(self._intgr_reso_high)
if self._intgr_reso_low:
job.set_d_max(self._intgr_reso_low)
if PhilIndex.params.general.backstop_mask:
from xia2.Toolkit.BackstopMask import BackstopMask
mask = BackstopMask(PhilIndex.params.general.backstop_mask)
mask = mask.calculate_mask_mosflm(self.get_header())
job.set_mask(mask)
detector = self.get_detector()
detector_width, detector_height = detector[0].get_image_size_mm()
lim_x = 0.5 * detector_width
lim_y = 0.5 * detector_height
Debug.write('Scanner limits: %.1f %.1f' % (lim_x, lim_y))
job.set_limits(lim_x, lim_y)
job.set_fix_mosaic(self._mosflm_postref_fix_mosaic)
job.set_pre_refinement(True)
job.set_image_range(chunks[j])
# these are now running so ...
jobs.append(job)
continue
# ok, at this stage I need to ...
#
# (i) accumulate the statistics as a function of batch
# (ii) mong them into a single block
#
# This is likely to be a pain in the arse!
first_integrated_batch = 1.0e6
last_integrated_batch = -1.0e6
all_residuals = []
threads = []
for j in range(parallel):
job = jobs[j]
# now wait for them to finish - first wait will really be the
# first one, then all should be finished...
thread = Background(job, 'run')
thread.start()
threads.append(thread)
mosaics = []
postref_result = { }
integrated_images_first = 1.0e6
integrated_images_last = -1.0e6
self._intgr_per_image_statistics = {}
for j in range(parallel):
thread = threads[j]
thread.stop()
job = jobs[j]
# get the log file
output = job.get_all_output()
# record a copy of it, perhaps - though not if parallel
if self.get_integrater_sweep_name() and False:
pname, xname, dname = self.get_integrater_project_info()
FileHandler.record_log_file(
'%s %s %s %s mosflm integrate' % \
(self.get_integrater_sweep_name(),
pname, xname, '%s_%d' % (dname, j)),
job.get_log_file())
# look for things that we want to know...
# that is, the output reflection file name, the updated
# value for the gain (if present,) any warnings, errors,
# or just interesting facts.
batches = job.get_batches_out()
integrated_images_first = min(batches[0], integrated_images_first)
integrated_images_last = max(batches[1], integrated_images_last)
mosaics.extend(job.get_mosaic_spreads())
if min(mosaics) < 0:
raise IntegrationError, 'negative mosaic spread: %s' % min(mosaic)
if (job.get_detector_gain_error() and not
(self.get_imageset().get_detector()[0].get_type() == 'SENSOR_PAD')):
gain = job.get_suggested_gain()
if gain is not None:
self.set_integrater_parameter('mosflm', 'gain', gain)
self.set_integrater_export_parameter('mosflm', 'gain', gain)
if self._mosflm_gain:
Debug.write('GAIN updated to %f' % gain)
else:
Debug.write('GAIN found to be %f' % gain)
self._mosflm_gain = gain
self._mosflm_rerun_integration = True
hklout = job.get_hklout()
Debug.write('Integration output: %s' % hklout)
hklouts.append(hklout)
nref += job.get_nref()
# if a BGSIG error happened try not refining the
# profile and running again...
if job.get_bgsig_too_large():
if not self._mosflm_refine_profiles:
raise RuntimeError, 'BGSIG error with profiles fixed'
Debug.write(
'BGSIG error detected - try fixing profile...')
self._mosflm_refine_profiles = False
self.set_integrater_done(False)
return
if job.get_getprof_error():
Debug.write(
'GETPROF error detected - try fixing profile...')
self._mosflm_refine_profiles = False
self.set_integrater_done(False)
return
# here
# write the report for each image as .*-#$ to Chatter -
# detailed report will be written automagically to science...
self._intgr_per_image_statistics.update(job.get_per_image_statistics())
postref_result.update(job.get_postref_result())
# inspect the output for e.g. very high weighted residuals
all_residuals.extend(job.get_residuals())
self._intgr_batches_out = (integrated_images_first,
integrated_images_last)
if mosaics and len(mosaics) > 0:
self.set_integrater_mosaic_min_mean_max(
min(mosaics), sum(mosaics) / len(mosaics), max(mosaics))
else:
m = indxr.get_indexer_mosaic()
self.set_integrater_mosaic_min_mean_max(m, m, m)
Chatter.write(self.show_per_image_statistics())
Chatter.write('Mosaic spread: %.3f < %.3f < %.3f' % \
self.get_integrater_mosaic_min_mean_max())
# gather the statistics from the postrefinement for all sweeps
# now write this to a postrefinement log
postref_log = os.path.join(self.get_working_directory(),
'postrefinement.log')
fout = open(postref_log, 'w')
fout.write('$TABLE: Postrefinement for %s:\n' % \
self._intgr_sweep_name)
fout.write('$GRAPHS: Missetting angles:A:1, 2, 3, 4: $$\n')
fout.write('Batch PhiX PhiY PhiZ $$ Batch PhiX PhiY PhiZ $$\n')
for image in sorted(postref_result):
phix = postref_result[image].get('phix', 0.0)
phiy = postref_result[image].get('phiy', 0.0)
phiz = postref_result[image].get('phiz', 0.0)
fout.write('%d %5.2f %5.2f %5.2f\n' % \
(image, phix, phiy, phiz))
fout.write('$$\n')
fout.close()
if self.get_integrater_sweep_name():
pname, xname, dname = self.get_integrater_project_info()
FileHandler.record_log_file('%s %s %s %s postrefinement' % \
(self.get_integrater_sweep_name(),
pname, xname, dname),
postref_log)
hklouts.sort()
hklout = os.path.join(self.get_working_directory(),
os.path.split(hklouts[0])[-1])
Debug.write('Sorting data to %s' % hklout)
for hklin in hklouts:
Debug.write('<= %s' % hklin)
sortmtz = Sortmtz()
sortmtz.set_hklout(hklout)
for hklin in hklouts:
sortmtz.add_hklin(hklin)
sortmtz.sort()
self._mosflm_hklout = hklout
return self._mosflm_hklout
def __init__(self, name,
wavelength,
sample,
directory = None,
image = None,
beam = None,
reversephi = False,
distance = None,
gain = 0.0,
dmin = 0.0,
dmax = 0.0,
polarization = 0.0,
frames_to_process = None,
user_lattice = None,
user_cell = None,
epoch = 0,
ice = False,
excluded_regions = []):
'''Create a new sweep named name, belonging to XWavelength object
wavelength, representing the images in directory starting with image,
with beam centre optionally defined.'''
# + check the wavelength is an XWavelength object
# raise an exception if not... or not...
if not wavelength.__class__.__name__ == 'XWavelength':
pass
# FIXME bug 2221 if DIRECTORY starts with ~/ or ~graeme (say) need to
# interpret this properly - e.g. map it to a full PATH.
directory = expand_path(directory)
# bug # 2274 - maybe migrate the data to a local disk (this
# will depend if the user has added -migrate_data to the cl)
directory = FileHandler.migrate(directory)
self._name = name
self._wavelength = wavelength
self._sample = sample
self._directory = directory
self._image = image
self._reversephi = reversephi
self._epoch = epoch
self._user_lattice = user_lattice
self._user_cell = user_cell
self._header = { }
self._resolution_high = dmin
self._resolution_low = dmax
self._ice = ice
self._excluded_regions = excluded_regions
self._imageset = None
# FIXME in here also need to be able to accumulate the total
# dose from all experimental measurements (complex) and provide
# a _epoch_to_dose dictionary or some such... may be fiddly as
# this will need to parse across multiple templates. c/f Bug # 2798
self._epoch_to_image = { }
self._image_to_epoch = { }
# to allow first, last image for processing to be
# set... c/f integrater interface
self._frames_to_process = frames_to_process
# + derive template, list of images
if directory and image:
self._template, self._directory = \
image2template_directory(os.path.join(directory,
image))
from xia2.Schema import load_imagesets
imagesets = load_imagesets(
self._template, self._directory, image_range=self._frames_to_process,
reversephi=(Flags.get_reversephi() or self._reversephi))
assert len(imagesets) == 1, "one imageset expected, %d found" % \
len(imagesets)
self._imageset = copy.deepcopy(imagesets[0])
start, end = self._imageset.get_array_range()
self._images = list(range(start+1, end+1))
# FIXME in here check that (1) the list of images is continuous
# and (2) that all of the images are readable. This should also
# take into account frames_to_process if set.
if self._frames_to_process is None:
self._frames_to_process = min(self._images), max(self._images)
start, end = self._frames_to_process
error = False
from xia2.Handlers.Phil import PhilIndex
params = PhilIndex.get_python_object()
if params.general.check_image_files_readable:
for j in range(start, end + 1):
if not j in self._images:
Debug.write('image %s missing' % \
self.get_image_name(j))
error = True
continue
if not os.access(self.get_image_name(j), os.R_OK):
Debug.write('image %s unreadable' % \
self.get_image_name(j))
error = True
continue
if error:
raise RuntimeError, 'problem with sweep %s' % self._name
# + read the image header information into here?
# or don't I need it? it would be useful for checking
# against wavelength.getWavelength() I guess to make
# sure that the plumbing is all sound.
# check that they match by closer than 0.0001A, if wavelength
# is not None
beam_ = self._imageset.get_beam()
scan = self._imageset.get_scan()
if not wavelength == None:
# FIXME 29/NOV/06 if the wavelength wavelength value
# is 0.0 then first set it to the header value - note
# that this assumes that the header value is correct
# (a reasonable assumption)
if wavelength.get_wavelength() == 0.0:
wavelength.set_wavelength(beam_.get_wavelength())
# FIXME 08/DEC/06 in here need to allow for the fact
# that the wavelength in the image header could be wrong and
# in fact it should be replaced with the input value -
# through the user will need to be warned of this and
# also everything using the FrameProcessor interface
# will also have to respect this!
if math.fabs(beam_.get_wavelength() -
wavelength.get_wavelength()) > 0.0001:
# format = 'wavelength for sweep %s does not ' + \
# 'match wavelength %s'
# raise RuntimeError, format % \
# (name, wavelength.get_name())
format = 'Header wavelength for sweep %s different' + \
' to assigned value (%4.2f vs. %4.2f)'
Chatter.write(format % (name, beam_.get_wavelength(),
wavelength.get_wavelength()))
# also in here look at the image headers to see if we can
# construct a mapping between exposure epoch and image ...
images = []
if self._frames_to_process:
start, end = self._frames_to_process
for j in self._images:
if j >= start and j <= end:
images.append(j)
else:
images = self._images
for j in images:
epoch = scan.get_image_epoch(j)
if epoch == 0.0:
epoch = float(os.stat(self._imageset.get_path(j-images[0])).st_mtime)
self._epoch_to_image[epoch] = j
self._image_to_epoch[j] = epoch
epochs = self._epoch_to_image.keys()
Debug.write('Exposure epoch for sweep %s: %d %d' % \
(self._template, min(epochs), max(epochs)))
self._input_imageset = copy.deepcopy(self._imageset)
# + get the lattice - can this be a pointer, so that when
# this object updates lattice it is globally-for-this-crystal
# updated? The lattice included directly in here includes an
# exact unit cell for data reduction, the crystal lattice
# contains an approximate unit cell which should be
# from the unit cells from all sweeps contained in the
# XCrystal. FIXME should I be using a LatticeInfo object
# in here? See what the Indexer interface produces. ALT:
# just provide an Indexer implementation "hook".
# See Headnote 001 above. See also _get_indexer,
# _get_integrater below.
self._indexer = None
self._refiner = None
self._integrater = None
# I don't need this - it is equivalent to self.getWavelength(
# ).getCrystal().getLattice()
# self._crystal_lattice = None
# this means that this module will have to present largely the
# same interface as Indexer and Integrater so that the calls
# can be appropriately forwarded.
# finally configure the beam if set
if beam is not None:
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
try:
set_mosflm_beam_centre(self.get_imageset().get_detector(),
self.get_imageset().get_beam(),
beam)
except AssertionError, e:
Debug.write('Error setting mosflm beam centre: %s' % e)
def _refine(self):
for epoch, idxr in self._refinr_indexers.iteritems():
# decide what images we are going to process, if not already
# specified
#if not self._intgr_wedge:
#images = self.get_matching_images()
#self.set_integrater_wedge(min(images),
#max(images))
#Debug.write('DIALS INTEGRATE PREPARE:')
#Debug.write('Wavelength: %.6f' % self.get_wavelength())
#Debug.write('Distance: %.2f' % self.get_distance())
#if not self._intgr_indexer:
#self.set_integrater_indexer(DialsIndexer())
#self.get_integrater_indexer().set_indexer_sweep(
#self.get_integrater_sweep())
#self._intgr_indexer.set_working_directory(
#self.get_working_directory())
#self._intgr_indexer.setup_from_imageset(self.get_imageset())
#if self.get_frame_wedge():
#wedge = self.get_frame_wedge()
#Debug.write('Propogating wedge limit: %d %d' % wedge)
#self._intgr_indexer.set_frame_wedge(wedge[0], wedge[1],
#apply_offset = False)
## this needs to be set up from the contents of the
## Integrater frame processer - wavelength &c.
#if self.get_beam_centre():
#self._intgr_indexer.set_beam_centre(self.get_beam_centre())
#if self.get_distance():
#self._intgr_indexer.set_distance(self.get_distance())
#if self.get_wavelength():
#self._intgr_indexer.set_wavelength(
#self.get_wavelength())
# get the unit cell from this indexer to initiate processing
# if it is new... and also copy out all of the information for
# the Dials indexer if not...
experiments = idxr.get_indexer_experiment_list()
indexed_experiments = idxr.get_indexer_payload("experiments_filename")
indexed_reflections = idxr.get_indexer_payload("indexed_filename")
if len(experiments) > 1:
xsweeps = idxr._indxr_sweeps
assert len(xsweeps) == len(experiments)
assert len(self._refinr_sweeps) == 1 # don't currently support joint refinement
xsweep = self._refinr_sweeps[0]
i = xsweeps.index(xsweep)
experiments = experiments[i:i+1]
# Extract and output experiment and reflections for current sweep
indexed_experiments = os.path.join(
self.get_working_directory(),
"%s_indexed_experiments.json" %xsweep.get_name())
indexed_reflections = os.path.join(
self.get_working_directory(),
"%s_indexed_reflections.pickle" %xsweep.get_name())
from dxtbx.serialize import dump
dump.experiment_list(experiments, indexed_experiments)
from libtbx import easy_pickle
from scitbx.array_family import flex
reflections = easy_pickle.load(
idxr.get_indexer_payload("indexed_filename"))
sel = reflections['id'] == i
assert sel.count(True) > 0
imageset_id = reflections['imageset_id'].select(sel)
assert imageset_id.all_eq(imageset_id[0])
sel = reflections['imageset_id'] == imageset_id[0]
reflections = reflections.select(sel)
# set indexed reflections to id == 0 and imageset_id == 0
reflections['id'].set_selected(reflections['id'] == i, 0)
reflections['imageset_id'] = flex.int(len(reflections), 0)
easy_pickle.dump(indexed_reflections, reflections)
assert len(experiments.crystals()) == 1 # currently only handle one lattice/sweep
crystal_model = experiments.crystals()[0]
lattice = idxr.get_indexer_lattice()
# check if the lattice was user assigned...
user_assigned = idxr.get_indexer_user_input_lattice()
# XXX check that the indexer is an Dials indexer - if not then
# create one...
# set a low resolution limit (which isn't really used...)
# this should perhaps be done more intelligently from an
# analysis of the spot list or something...?
#if not self.get_integrater_low_resolution():
#dmax = idxr.get_indexer_low_resolution()
#self.set_integrater_low_resolution(dmax)
#Debug.write('Low resolution set to: %s' % \
#self.get_integrater_low_resolution())
## copy the data across
from dxtbx.serialize import load, dump
refiner = self.Refine()
refiner.set_experiments_filename(indexed_experiments)
refiner.set_indexed_filename(indexed_reflections)
# XXX Temporary workaround for dials.refine error for scan_varying
# refinement with smaller wedges
total_phi_range = idxr._indxr_imagesets[0].get_scan().get_oscillation_range()[1]
if total_phi_range < 5: # arbitrary value
refiner.set_scan_varying(False)
elif total_phi_range < 36:
refiner.set_interval_width_degrees(total_phi_range/2)
FileHandler.record_log_file('%s REFINE' % idxr.get_indexer_full_name(),
refiner.get_log_file())
refiner.run()
self._refinr_experiments_filename \
= refiner.get_refined_experiments_filename()
experiments = load.experiment_list(self._refinr_experiments_filename)
self._refinr_indexed_filename = refiner.get_refined_filename()
self.set_refiner_payload("experiments.json", self._refinr_experiments_filename)
self.set_refiner_payload("reflections.pickle", self._refinr_indexed_filename)
# this is the result of the cell refinement
self._refinr_cell = experiments.crystals()[0].get_unit_cell().parameters()
def _scale(self):
'''Actually scale all of the data together.'''
from xia2.Handlers.Environment import debug_memory_usage
debug_memory_usage()
Journal.block(
'scaling', self.get_scaler_xcrystal().get_name(), 'XSCALE',
{'scaling model':'default (all)'})
epochs = self._sweep_information.keys()
epochs.sort()
xscale = self.XScale()
xscale.set_spacegroup_number(self._xds_spacegroup)
xscale.set_cell(self._scalr_cell)
Debug.write('Set CELL: %.2f %.2f %.2f %.2f %.2f %.2f' % \
tuple(self._scalr_cell))
Debug.write('Set SPACEGROUP_NUMBER: %d' % \
self._xds_spacegroup)
Debug.write('Gathering measurements for scaling')
for epoch in epochs:
# get the prepared reflections
reflections = self._sweep_information[epoch][
'prepared_reflections']
# and the get wavelength that this belongs to
dname = self._sweep_information[epoch]['dname']
sname = self._sweep_information[epoch]['sname']
# and the resolution range for the reflections
intgr = self._sweep_information[epoch]['integrater']
Debug.write('Epoch: %d' % epoch)
Debug.write('HKL: %s (%s/%s)' % (reflections, dname, sname))
resolution_low = intgr.get_integrater_low_resolution()
resolution_high, _ = self._scalr_resolution_limits.get((dname, sname), (0.0, None))
resolution = (resolution_high, resolution_low)
xscale.add_reflection_file(reflections, dname, resolution)
# set the global properties of the sample
xscale.set_crystal(self._scalr_xname)
xscale.set_anomalous(self._scalr_anomalous)
debug_memory_usage()
xscale.run()
scale_factor = xscale.get_scale_factor()
Debug.write('XSCALE scale factor found to be: %e' % scale_factor)
# record the log file
pname = self._scalr_pname
xname = self._scalr_xname
FileHandler.record_log_file('%s %s XSCALE' % \
(pname, xname),
os.path.join(self.get_working_directory(),
'XSCALE.LP'))
# check for outlier reflections and if a number are found
# then iterate (that is, rerun XSCALE, rejecting these outliers)
if not PhilIndex.params.dials.fast_mode and not PhilIndex.params.xds.keep_outliers:
xscale_remove = xscale.get_remove()
if xscale_remove:
current_remove = []
final_remove = []
# first ensure that there are no duplicate entries...
if os.path.exists(os.path.join(
self.get_working_directory(),
'REMOVE.HKL')):
for line in open(os.path.join(
self.get_working_directory(),
'REMOVE.HKL'), 'r').readlines():
h, k, l = map(int, line.split()[:3])
z = float(line.split()[3])
if not (h, k, l, z) in current_remove:
current_remove.append((h, k, l, z))
for c in xscale_remove:
if c in current_remove:
continue
final_remove.append(c)
Debug.write(
'%d alien reflections are already removed' % \
(len(xscale_remove) - len(final_remove)))
else:
# we want to remove all of the new dodgy reflections
final_remove = xscale_remove
remove_hkl = open(os.path.join(
self.get_working_directory(),
'REMOVE.HKL'), 'w')
z_min = PhilIndex.params.xds.z_min
rejected = 0
# write in the old reflections
for remove in current_remove:
z = remove[3]
if z >= z_min:
remove_hkl.write('%d %d %d %f\n' % remove)
else:
rejected += 1
Debug.write('Wrote %d old reflections to REMOVE.HKL' % \
(len(current_remove) - rejected))
Debug.write('Rejected %d as z < %f' % \
(rejected, z_min))
# and the new reflections
rejected = 0
used = 0
for remove in final_remove:
z = remove[3]
if z >= z_min:
used += 1
remove_hkl.write('%d %d %d %f\n' % remove)
else:
rejected += 1
Debug.write('Wrote %d new reflections to REMOVE.HKL' % \
(len(final_remove) - rejected))
Debug.write('Rejected %d as z < %f' % \
(rejected, z_min))
remove_hkl.close()
# we want to rerun the finishing step so...
# unless we have added no new reflections
if used:
self.set_scaler_done(False)
if not self.get_scaler_done():
Chatter.write('Excluding outlier reflections Z > %.2f' %
PhilIndex.params.xds.z_min)
return
debug_memory_usage()
# now get the reflection files out and merge them with aimless
output_files = xscale.get_output_reflection_files()
wavelength_names = output_files.keys()
# these are per wavelength - also allow for user defined resolution
# limits a la bug # 3183. No longer...
for epoch in self._sweep_information.keys():
input = self._sweep_information[epoch]
intgr = input['integrater']
rkey = input['dname'], input['sname']
if intgr.get_integrater_user_resolution():
dmin = intgr.get_integrater_high_resolution()
if rkey not in self._user_resolution_limits:
self._scalr_resolution_limits[rkey] = (dmin, None)
self._user_resolution_limits[rkey] = dmin
elif dmin < self._user_resolution_limits[rkey]:
self._scalr_resolution_limits[rkey] = (dmin, None)
self._user_resolution_limits[rkey] = dmin
self._scalr_scaled_refl_files = { }
self._scalr_statistics = { }
max_batches = 0
mtz_dict = { }
project_info = { }
for epoch in self._sweep_information.keys():
pname = self._scalr_pname
xname = self._scalr_xname
dname = self._sweep_information[epoch]['dname']
reflections = os.path.split(
self._sweep_information[epoch]['prepared_reflections'])[-1]
project_info[reflections] = (pname, xname, dname)
for epoch in self._sweep_information.keys():
self._sweep_information[epoch]['scaled_reflections'] = None
debug_memory_usage()
for wavelength in wavelength_names:
hklin = output_files[wavelength]
xsh = XDSScalerHelper()
xsh.set_working_directory(self.get_working_directory())
ref = xsh.split_and_convert_xscale_output(
hklin, 'SCALED_', project_info, 1.0 / scale_factor)
for hklout in ref.keys():
for epoch in self._sweep_information.keys():
if os.path.split(self._sweep_information[epoch][
'prepared_reflections'])[-1] == \
os.path.split(hklout)[-1]:
if self._sweep_information[epoch][
'scaled_reflections'] is not None:
raise RuntimeError, 'duplicate entries'
self._sweep_information[epoch][
'scaled_reflections'] = ref[hklout]
del(xsh)
debug_memory_usage()
for epoch in self._sweep_information.keys():
hklin = self._sweep_information[epoch]['scaled_reflections']
dname = self._sweep_information[epoch]['dname']
sname = self._sweep_information[epoch]['sname']
hkl_copy = os.path.join(self.get_working_directory(),
'R_%s' % os.path.split(hklin)[-1])
if not os.path.exists(hkl_copy):
shutil.copyfile(hklin, hkl_copy)
# let's properly listen to the user's resolution limit needs...
if self._user_resolution_limits.get((dname, sname), False):
resolution = self._user_resolution_limits[(dname, sname)]
else:
if PhilIndex.params.xia2.settings.resolution.keep_all_reflections == True:
try:
resolution = intgr.get_detector().get_max_resolution(intgr.get_beam_obj().get_s0())
Debug.write('keep_all_reflections set, using detector limits')
except Exception:
resolution = self._estimate_resolution_limit(hklin)
else:
resolution = self._estimate_resolution_limit(hklin)
Chatter.write('Resolution for sweep %s/%s: %.2f' % \
(dname, sname, resolution))
if (dname, sname) not in self._scalr_resolution_limits:
self._scalr_resolution_limits[(dname, sname)] = (resolution, None)
self.set_scaler_done(False)
else:
if resolution < self._scalr_resolution_limits[(dname, sname)][0]:
self._scalr_resolution_limits[(dname, sname)] = (resolution, None)
self.set_scaler_done(False)
debug_memory_usage()
if not self.get_scaler_done():
Debug.write('Returning as scaling not finished...')
return
self._sort_together_data_xds()
highest_resolution = min(limit for limit, _ in self._scalr_resolution_limits.values())
self._scalr_highest_resolution = highest_resolution
Debug.write('Scaler highest resolution set to %5.2f' % \
highest_resolution)
if not self.get_scaler_done():
Debug.write('Returning as scaling not finished...')
return
sdadd_full = 0.0
sdb_full = 0.0
# ---------- FINAL MERGING ----------
sc = self._factory.Aimless()
FileHandler.record_log_file('%s %s aimless' % (self._scalr_pname,
self._scalr_xname),
sc.get_log_file())
sc.set_resolution(highest_resolution)
sc.set_hklin(self._prepared_reflections)
sc.set_new_scales_file('%s_final.scales' % self._scalr_xname)
if sdadd_full == 0.0 and sdb_full == 0.0:
pass
else:
sc.add_sd_correction('both', 1.0, sdadd_full, sdb_full)
for epoch in epochs:
input = self._sweep_information[epoch]
start, end = (min(input['batches']), max(input['batches']))
rkey = input['dname'], input['sname']
run_resolution_limit, _ = self._scalr_resolution_limits[rkey]
sc.add_run(start, end, exclude = False,
resolution = run_resolution_limit,
name = input['sname'])
sc.set_hklout(os.path.join(self.get_working_directory(),
'%s_%s_scaled.mtz' % \
(self._scalr_pname, self._scalr_xname)))
if self.get_scaler_anomalous():
sc.set_anomalous()
sc.multi_merge()
FileHandler.record_xml_file('%s %s aimless xml' % (self._scalr_pname,
self._scalr_xname),
sc.get_xmlout())
data = sc.get_summary()
loggraph = sc.parse_ccp4_loggraph()
standard_deviation_info = { }
for key in loggraph.keys():
if 'standard deviation v. Intensity' in key:
dataset = key.split(',')[-1].strip()
standard_deviation_info[dataset] = transpose_loggraph(
loggraph[key])
resolution_info = { }
for key in loggraph.keys():
if 'Analysis against resolution' in key:
dataset = key.split(',')[-1].strip()
resolution_info[dataset] = transpose_loggraph(
loggraph[key])
# and also radiation damage stuff...
batch_info = { }
for key in loggraph.keys():
if 'Analysis against Batch' in key:
dataset = key.split(',')[-1].strip()
batch_info[dataset] = transpose_loggraph(
loggraph[key])
# finally put all of the results "somewhere useful"
self._scalr_statistics = data
self._scalr_scaled_refl_files = copy.deepcopy(
sc.get_scaled_reflection_files())
self._scalr_scaled_reflection_files = { }
# also output the unmerged scalepack format files...
sc = self._factory.Aimless()
sc.set_resolution(highest_resolution)
sc.set_hklin(self._prepared_reflections)
sc.set_scalepack()
for epoch in epochs:
input = self._sweep_information[epoch]
start, end = (min(input['batches']), max(input['batches']))
rkey = input['dname'], input['sname']
run_resolution_limit, _ = self._scalr_resolution_limits[rkey]
sc.add_run(start, end, exclude = False,
resolution = run_resolution_limit,
name = input['sname'])
sc.set_hklout(os.path.join(self.get_working_directory(),
'%s_%s_scaled.mtz' % \
(self._scalr_pname,
self._scalr_xname)))
if self.get_scaler_anomalous():
sc.set_anomalous()
sc.multi_merge()
self._scalr_scaled_reflection_files['sca_unmerged'] = { }
self._scalr_scaled_reflection_files['mtz_unmerged'] = { }
for dataset in sc.get_scaled_reflection_files().keys():
hklout = sc.get_scaled_reflection_files()[dataset]
# then mark the scalepack files for copying...
scalepack = os.path.join(os.path.split(hklout)[0],
os.path.split(hklout)[1].replace(
'_scaled', '_scaled_unmerged').replace('.mtz', '.sca'))
self._scalr_scaled_reflection_files['sca_unmerged'][
dataset] = scalepack
FileHandler.record_data_file(scalepack)
mtz_unmerged = os.path.splitext(scalepack)[0] + '.mtz'
self._scalr_scaled_reflection_files['mtz_unmerged'][dataset] = mtz_unmerged
FileHandler.record_data_file(mtz_unmerged)
if PhilIndex.params.xia2.settings.merging_statistics.source == 'cctbx':
for key in self._scalr_scaled_refl_files:
stats = self._compute_scaler_statistics(
self._scalr_scaled_reflection_files['mtz_unmerged'][key], wave=key)
self._scalr_statistics[
(self._scalr_pname, self._scalr_xname, key)] = stats
# convert reflection files to .sca format - use mtz2various for this
self._scalr_scaled_reflection_files['sca'] = { }
self._scalr_scaled_reflection_files['hkl'] = { }
for key in self._scalr_scaled_refl_files:
f = self._scalr_scaled_refl_files[key]
scaout = '%s.sca' % f[:-4]
m2v = self._factory.Mtz2various()
m2v.set_hklin(f)
m2v.set_hklout(scaout)
m2v.convert()
self._scalr_scaled_reflection_files['sca'][key] = scaout
FileHandler.record_data_file(scaout)
if PhilIndex.params.xia2.settings.small_molecule == True:
hklout = '%s.hkl' % f[:-4]
m2v = self._factory.Mtz2various()
m2v.set_hklin(f)
m2v.set_hklout(hklout)
m2v.convert_shelx()
self._scalr_scaled_reflection_files['hkl'][key] = hklout
FileHandler.record_data_file(hklout)
def _scale(self):
"Perform all of the operations required to deliver the scaled data."
epochs = self._sweep_handler.get_epochs()
sc = self._updated_aimless()
sc.set_hklin(self._prepared_reflections)
sc.set_chef_unmerged(True)
sc.set_new_scales_file("%s.scales" % self._scalr_xname)
user_resolution_limits = {}
for epoch in epochs:
si = self._sweep_handler.get_sweep_information(epoch)
pname, xname, dname = si.get_project_info()
sname = si.get_sweep_name()
intgr = si.get_integrater()
if intgr.get_integrater_user_resolution():
dmin = intgr.get_integrater_high_resolution()
if (dname, sname) not in user_resolution_limits:
user_resolution_limits[(dname, sname)] = dmin
elif dmin < user_resolution_limits[(dname, sname)]:
user_resolution_limits[(dname, sname)] = dmin
start, end = si.get_batch_range()
if (dname, sname) in self._scalr_resolution_limits:
resolution, _ = self._scalr_resolution_limits[(dname, sname)]
sc.add_run(start, end, exclude=False, resolution=resolution, name=sname)
else:
sc.add_run(start, end, name=sname)
sc.set_hklout(
os.path.join(
self.get_working_directory(),
f"{self._scalr_pname}_{self._scalr_xname}_scaled_test.mtz",
)
)
if self.get_scaler_anomalous():
sc.set_anomalous()
# what follows, sucks
failover = PhilIndex.params.xia2.settings.failover
if failover:
try:
sc.scale()
except RuntimeError as e:
es = str(e)
if (
"bad batch" in es
or "negative scales run" in es
or "no observations" in es
):
# first ID the sweep from the batch no
batch = int(es.split()[-1])
epoch = self._identify_sweep_epoch(batch)
sweep = self._scalr_integraters[epoch].get_integrater_sweep()
# then remove it from my parent xcrystal
self.get_scaler_xcrystal().remove_sweep(sweep)
# then remove it from the scaler list of intergraters
# - this should really be a scaler interface method
del self._scalr_integraters[epoch]
# then tell the user what is happening
logger.info(
"Sweep %s gave negative scales - removing", sweep.get_name()
)
# then reset the prepare, do, finish flags
self.set_scaler_prepare_done(False)
self.set_scaler_done(False)
self.set_scaler_finish_done(False)
# and return
return
else:
raise e
else:
sc.scale()
# then gather up all of the resulting reflection files
# and convert them into the required formats (.sca, .mtz.)
loggraph = sc.parse_ccp4_loggraph()
resolution_info = {}
reflection_files = sc.get_scaled_reflection_files()
for dataset in reflection_files:
FileHandler.record_temporary_file(reflection_files[dataset])
for key in loggraph:
if "Analysis against resolution" in key:
dataset = key.split(",")[-1].strip()
resolution_info[dataset] = transpose_loggraph(loggraph[key])
# check in here that there is actually some data to scale..!
if not resolution_info:
raise RuntimeError("no resolution info")
highest_suggested_resolution = self.assess_resolution_limits(
sc.get_unmerged_reflection_file(), user_resolution_limits
)
if not self.get_scaler_done():
logger.debug("Returning as scaling not finished...")
return
batch_info = {}
for key in loggraph:
if "Analysis against Batch" in key:
dataset = key.split(",")[-1].strip()
batch_info[dataset] = transpose_loggraph(loggraph[key])
sc = self._updated_aimless()
FileHandler.record_log_file(
f"{self._scalr_pname} {self._scalr_xname} aimless", sc.get_log_file()
)
sc.set_hklin(self._prepared_reflections)
sc.set_new_scales_file("%s_final.scales" % self._scalr_xname)
for epoch in epochs:
si = self._sweep_handler.get_sweep_information(epoch)
pname, xname, dname = si.get_project_info()
sname = si.get_sweep_name()
start, end = si.get_batch_range()
resolution_limit, _ = self._scalr_resolution_limits[(dname, sname)]
sc.add_run(
start, end, exclude=False, resolution=resolution_limit, name=xname
)
sc.set_hklout(
os.path.join(
self.get_working_directory(),
f"{self._scalr_pname}_{self._scalr_xname}_scaled.mtz",
)
)
if self.get_scaler_anomalous():
sc.set_anomalous()
sc.scale()
FileHandler.record_xml_file(
f"{self._scalr_pname} {self._scalr_xname} aimless", sc.get_xmlout()
)
data = sc.get_summary()
scales_file = sc.get_new_scales_file()
loggraph = sc.parse_ccp4_loggraph()
standard_deviation_info = {}
for key in loggraph:
if "standard deviation v. Intensity" in key:
dataset = key.split(",")[-1].strip()
standard_deviation_info[dataset] = transpose_loggraph(loggraph[key])
resolution_info = {}
for key in loggraph:
if "Analysis against resolution" in key:
dataset = key.split(",")[-1].strip()
resolution_info[dataset] = transpose_loggraph(loggraph[key])
batch_info = {}
for key in loggraph:
if "Analysis against Batch" in key:
dataset = key.split(",")[-1].strip()
batch_info[dataset] = transpose_loggraph(loggraph[key])
# finally put all of the results "somewhere useful"
self._scalr_statistics = data
self._scalr_scaled_refl_files = copy.deepcopy(sc.get_scaled_reflection_files())
sc = self._updated_aimless()
sc.set_hklin(self._prepared_reflections)
sc.set_scales_file(scales_file)
self._wavelengths_in_order = []
for epoch in epochs:
si = self._sweep_handler.get_sweep_information(epoch)
pname, xname, dname = si.get_project_info()
sname = si.get_sweep_name()
start, end = si.get_batch_range()
resolution_limit, _ = self._scalr_resolution_limits[(dname, sname)]
sc.add_run(
start, end, exclude=False, resolution=resolution_limit, name=sname
)
if dname not in self._wavelengths_in_order:
self._wavelengths_in_order.append(dname)
sc.set_hklout(
os.path.join(
self.get_working_directory(),
f"{self._scalr_pname}_{self._scalr_xname}_scaled.mtz",
)
)
sc.set_scalepack()
if self.get_scaler_anomalous():
sc.set_anomalous()
sc.scale()
self._update_scaled_unit_cell()
self._scalr_scaled_reflection_files = {}
self._scalr_scaled_reflection_files["sca"] = {}
self._scalr_scaled_reflection_files["sca_unmerged"] = {}
self._scalr_scaled_reflection_files["mtz_unmerged"] = {}
for key in self._scalr_scaled_refl_files:
hklout = self._scalr_scaled_refl_files[key]
scaout = "%s.sca" % hklout[:-4]
self._scalr_scaled_reflection_files["sca"][key] = scaout
FileHandler.record_data_file(scaout)
scalepack = os.path.join(
os.path.split(hklout)[0],
os.path.split(hklout)[1]
.replace("_scaled", "_scaled_unmerged")
.replace(".mtz", ".sca"),
)
self._scalr_scaled_reflection_files["sca_unmerged"][key] = scalepack
FileHandler.record_data_file(scalepack)
mtz_unmerged = os.path.splitext(scalepack)[0] + ".mtz"
self._scalr_scaled_reflection_files["mtz_unmerged"][key] = mtz_unmerged
FileHandler.record_data_file(mtz_unmerged)
if self._scalr_cell_esd is not None:
# patch .mtz and overwrite unit cell information
import xia2.Modules.Scaler.tools as tools
override_cell = self._scalr_cell_dict.get(
f"{self._scalr_pname}_{self._scalr_xname}_{key}"
)[0]
tools.patch_mtz_unit_cell(mtz_unmerged, override_cell)
tools.patch_mtz_unit_cell(hklout, override_cell)
self._scalr_scaled_reflection_files["mtz_unmerged"][key] = mtz_unmerged
FileHandler.record_data_file(mtz_unmerged)
if PhilIndex.params.xia2.settings.merging_statistics.source == "cctbx":
for key in self._scalr_scaled_refl_files:
stats = self._compute_scaler_statistics(
self._scalr_scaled_reflection_files["mtz_unmerged"][key],
selected_band=(highest_suggested_resolution, None),
wave=key,
)
self._scalr_statistics[
(self._scalr_pname, self._scalr_xname, key)
] = stats
sc = self._updated_aimless()
sc.set_hklin(self._prepared_reflections)
sc.set_scales_file(scales_file)
self._wavelengths_in_order = []
for epoch in epochs:
si = self._sweep_handler.get_sweep_information(epoch)
pname, xname, dname = si.get_project_info()
sname = si.get_sweep_name()
start, end = si.get_batch_range()
resolution_limit, _ = self._scalr_resolution_limits[(dname, sname)]
sc.add_run(
start, end, exclude=False, resolution=resolution_limit, name=sname
)
if dname not in self._wavelengths_in_order:
self._wavelengths_in_order.append(dname)
sc.set_hklout(
os.path.join(
self.get_working_directory(),
f"{self._scalr_pname}_{self._scalr_xname}_chef.mtz",
)
)
sc.set_chef_unmerged(True)
if self.get_scaler_anomalous():
sc.set_anomalous()
sc.scale()
if not PhilIndex.params.dials.fast_mode:
try:
self._generate_absorption_map(sc)
except Exception as e:
# Map generation may fail for number of reasons, eg. matplotlib borken
logger.debug("Could not generate absorption map (%s)", e)
def _sort_together_data_xds(self):
if len(self._sweep_information) == 1:
return self._sort_together_data_xds_one_sweep()
max_batches = 0
for epoch in self._sweep_information.keys():
hklin = self._sweep_information[epoch]['scaled_reflections']
if self._sweep_information[epoch]['batches'] == [0, 0]:
Chatter.write('Getting batches from %s' % hklin)
batches = MtzUtils.batches_from_mtz(hklin)
self._sweep_information[epoch]['batches'] = [
min(batches), max(batches)
]
Chatter.write('=> %d to %d' % (min(batches), max(batches)))
batches = self._sweep_information[epoch]['batches']
if 1 + max(batches) - min(batches) > max_batches:
max_batches = max(batches) - min(batches) + 1
Debug.write('Biggest sweep has %d batches' % max_batches)
max_batches = nifty_power_of_ten(max_batches)
epochs = sorted(self._sweep_information.keys())
counter = 0
for epoch in epochs:
hklin = self._sweep_information[epoch]['scaled_reflections']
pname = self._sweep_information[epoch]['pname']
xname = self._sweep_information[epoch]['xname']
dname = self._sweep_information[epoch]['dname']
sname = self._sweep_information[epoch]['sname']
hklout = os.path.join(self.get_working_directory(),
'%s_%s_%s_%d.mtz' % \
(pname, xname, dname, counter))
# we will want to delete this one exit
FileHandler.record_temporary_file(hklout)
# record this for future reference - will be needed in the
# radiation damage analysis...
# hack - reset this as it gets in a muddle...
intgr = self._sweep_information[epoch]['integrater']
self._sweep_information[epoch][
'batches'] = intgr.get_integrater_batches()
first_batch = min(self._sweep_information[epoch]['batches'])
offset = counter * max_batches - first_batch + 1
self._sweep_information[epoch]['batch_offset'] = offset
from xia2.Modules.Scaler.rebatch import rebatch
new_batches = rebatch(hklin,
hklout,
add_batch=offset,
pname=pname,
xname=xname,
dname=dname)
# update the "input information"
self._sweep_information[epoch]['hklin'] = hklout
self._sweep_information[epoch]['batches'] = new_batches
# update the counter & recycle
counter += 1
s = self._factory.Sortmtz()
hklout = os.path.join(self.get_working_directory(),
'%s_%s_sorted.mtz' % \
(self._scalr_pname, self._scalr_xname))
s.set_hklout(hklout)
for epoch in epochs:
s.add_hklin(self._sweep_information[epoch]['hklin'])
s.sort(vrset=-99999999.0)
self._prepared_reflections = hklout
if self.get_scaler_reference_reflection_file():
spacegroups = [
MtzUtils.space_group_name_from_mtz(
self.get_scaler_reference_reflection_file())
]
reindex_operator = 'h,k,l'
else:
pointless = self._factory.Pointless()
pointless.set_hklin(hklout)
pointless.decide_spacegroup()
FileHandler.record_log_file('%s %s pointless' % \
(self._scalr_pname,
self._scalr_xname),
pointless.get_log_file())
spacegroups = pointless.get_likely_spacegroups()
reindex_operator = pointless.get_spacegroup_reindex_operator()
if self._scalr_input_spacegroup:
Debug.write('Assigning user input spacegroup: %s' % \
self._scalr_input_spacegroup)
spacegroups = [self._scalr_input_spacegroup]
reindex_operator = 'h,k,l'
self._scalr_likely_spacegroups = spacegroups
spacegroup = self._scalr_likely_spacegroups[0]
self._scalr_reindex_operator = reindex_operator
Chatter.write('Likely spacegroups:')
for spag in self._scalr_likely_spacegroups:
Chatter.write('%s' % spag)
Chatter.write(
'Reindexing to first spacegroup setting: %s (%s)' % \
(spacegroup, clean_reindex_operator(reindex_operator)))
hklin = self._prepared_reflections
hklout = os.path.join(self.get_working_directory(),
'%s_%s_reindex.mtz' % \
(self._scalr_pname, self._scalr_xname))
FileHandler.record_temporary_file(hklout)
ri = self._factory.Reindex()
ri.set_hklin(hklin)
ri.set_hklout(hklout)
ri.set_spacegroup(spacegroup)
ri.set_operator(reindex_operator)
ri.reindex()
hklin = hklout
hklout = os.path.join(self.get_working_directory(),
'%s_%s_sorted.mtz' % \
(self._scalr_pname, self._scalr_xname))
s = self._factory.Sortmtz()
s.set_hklin(hklin)
s.set_hklout(hklout)
s.sort(vrset=-99999999.0)
self._prepared_reflections = hklout
Debug.write(
'Updating unit cell to %.2f %.2f %.2f %.2f %.2f %.2f' % \
tuple(ri.get_cell()))
self._scalr_cell = tuple(ri.get_cell())
return
def write_xml(self, file, command_line=''):
fout = open(file, 'w')
fout.write('<?xml version="1.0"?>')
fout.write('<AutoProcContainer>\n')
for crystal in sorted(self._crystals):
xcrystal = self._crystals[crystal]
cell = xcrystal.get_cell()
spacegroup = xcrystal.get_likely_spacegroups()[0]
fout.write('<AutoProc><spaceGroup>%s</spaceGroup>' % spacegroup)
self.write_refined_cell(fout, cell)
fout.write('</AutoProc>')
fout.write('<AutoProcScalingContainer>')
fout.write('<AutoProcScaling>')
self.write_date(fout)
fout.write('</AutoProcScaling>')
statistics_all = xcrystal.get_statistics()
reflection_files = xcrystal.get_scaled_merged_reflections()
wavelength_names = xcrystal.get_wavelength_names()
for key in statistics_all.keys():
pname, xname, dname = key
# FIXME should assert that the dname is a
# valid wavelength name
available = statistics_all[key].keys()
stats = []
keys = [
'High resolution limit',
'Low resolution limit',
'Completeness',
'Multiplicity',
'I/sigma',
'Rmerge(I+/-)',
'CC half',
'Anomalous completeness',
'Anomalous correlation',
'Anomalous multiplicity',
'Total observations',
'Total unique',
'Rmeas(I)',
'Rmeas(I+/-)',
'Rpim(I)',
'Rpim(I+/-)',
'Partial Bias'
]
for k in keys:
if k in available:
stats.append(k)
xwavelength = xcrystal.get_xwavelength(dname)
sweeps = xwavelength.get_sweeps()
for j, name in enumerate(['overall', 'innerShell', 'outerShell']):
statistics_cache = {}
for s in stats:
if isinstance(statistics_all[key][s], type([])):
statistics_cache[s] = statistics_all[key][s][j]
elif isinstance(statistics_all[key][s], type(())):
statistics_cache[s] = statistics_all[key][s][j]
# send these to be written out
self.write_scaling_statistics(fout, name, statistics_cache)
for sweep in sweeps:
fout.write('<AutoProcIntegrationContainer>\n')
if '#' in sweep.get_template():
image_name = sweep.get_image_name(0)
else:
image_name = os.path.join(sweep.get_directory(),
sweep.get_template())
fout.write('<Image><fileName>%s</fileName>' % \
os.path.split(image_name)[-1])
fout.write('<fileLocation>%s</fileLocation></Image>' %
sanitize(os.path.split(image_name)[0]))
fout.write('<AutoProcIntegration>\n')
cell = sweep.get_integrater_cell()
self.write_cell(fout, cell)
# FIXME this is naughty
intgr = sweep._get_integrater()
start, end = intgr.get_integrater_wedge()
fout.write('<startImageNumber>%d</startImageNumber>' % \
start)
fout.write('<endImageNumber>%d</endImageNumber>' % \
end)
# FIXME this is naughty
indxr = sweep._get_indexer()
fout.write(
'<refinedDetectorDistance>%f</refinedDetectorDistance>' % \
indxr.get_indexer_distance())
beam = indxr.get_indexer_beam_centre()
fout.write('<refinedXBeam>%f</refinedXBeam>' % beam[0])
fout.write('<refinedYBeam>%f</refinedYBeam>' % beam[1])
fout.write('</AutoProcIntegration>\n')
fout.write('</AutoProcIntegrationContainer>\n')
fout.write('</AutoProcScalingContainer>')
# file unpacking nonsense
if not command_line:
from xia2.Handlers.CommandLine import CommandLine
command_line = CommandLine.get_command_line()
fout.write('<AutoProcProgramContainer><AutoProcProgram>')
fout.write('<processingCommandLine>%s</processingCommandLine>' \
% sanitize(command_line))
fout.write('<processingPrograms>xia2</processingPrograms>')
fout.write('</AutoProcProgram>')
from xia2.Handlers.Environment import Environment
data_directory = Environment.generate_directory('DataFiles')
log_directory = Environment.generate_directory('LogFiles')
for k in reflection_files:
reflection_file = reflection_files[k]
if not isinstance(reflection_file, type('')):
continue
reflection_file = FileHandler.get_data_file(reflection_file)
basename = os.path.basename(reflection_file)
if os.path.isfile(os.path.join(data_directory, basename)):
# Use file in DataFiles directory in preference (if it exists)
reflection_file = os.path.join(data_directory, basename)
fout.write('<AutoProcProgramAttachment><fileType>Result')
fout.write('</fileType><fileName>%s</fileName>' % \
os.path.split(reflection_file)[-1])
fout.write('<filePath>%s</filePath>' % \
sanitize(os.path.split(reflection_file)[0]))
fout.write('</AutoProcProgramAttachment>\n')
import glob
g = glob.glob(os.path.join(log_directory, '*merging-statistics.json'))
for merging_stats_json in g:
fout.write('<AutoProcProgramAttachment><fileType>Graph')
fout.write('</fileType><fileName>%s</fileName>' %
os.path.split(merging_stats_json)[-1])
fout.write('<filePath>%s</filePath>' % sanitize(log_directory))
fout.write('</AutoProcProgramAttachment>\n')
# add the xia2.txt file...
fout.write('<AutoProcProgramAttachment><fileType>Log')
fout.write('</fileType><fileName>xia2.txt</fileName>')
fout.write('<filePath>%s</filePath>' % sanitize(os.getcwd()))
fout.write('</AutoProcProgramAttachment>\n')
fout.write('</AutoProcProgramContainer>')
fout.write('</AutoProcContainer>\n')
fout.close()
def _sort_together_data_ccp4(self):
'''Sort together in the right order (rebatching as we go) the sweeps
we want to scale together.'''
max_batches = 0
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
pname, xname, dname = si.get_project_info()
sname = si.get_sweep_name()
hklin = si.get_reflections()
# limit the reflections - e.g. if we are re-running the scaling step
# on just a subset of the integrated data
hklin = si.get_reflections()
limit_batch_range = None
for sweep in PhilIndex.params.xia2.settings.sweep:
if sweep.id == sname and sweep.range is not None:
limit_batch_range = sweep.range
break
if limit_batch_range is not None:
Debug.write('Limiting batch range for %s: %s' %
(sname, limit_batch_range))
start, end = limit_batch_range
hklout = os.path.splitext(hklin)[0] + '_tmp.mtz'
FileHandler.record_temporary_file(hklout)
rb = self._factory.Pointless()
rb.set_hklin(hklin)
rb.set_hklout(hklout)
rb.limit_batches(start, end)
si.set_reflections(hklout)
si.set_batches(limit_batch_range)
# keep a count of the maximum number of batches in a block -
# this will be used to make rebatch work below.
hklin = si.get_reflections()
batches = MtzUtils.batches_from_mtz(hklin)
if 1 + max(batches) - min(batches) > max_batches:
max_batches = max(batches) - min(batches) + 1
Debug.write('Biggest sweep has %d batches' % max_batches)
max_batches = nifty_power_of_ten(max_batches)
# then rebatch the files, to make sure that the batch numbers are
# in the same order as the epochs of data collection.
counter = 0
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
hklin = si.get_reflections()
pname, xname, dname = si.get_project_info()
sname = si.get_sweep_name()
hklout = os.path.join(self.get_working_directory(),
'%s_%s_%s_%s_integrated.mtz' % \
(pname, xname, dname, sname))
first_batch = min(si.get_batches())
si.set_batch_offset(counter * max_batches - first_batch + 1)
from xia2.Modules.Scaler.rebatch import rebatch
new_batches = rebatch(hklin,
hklout,
first_batch=counter * max_batches + 1,
pname=pname,
xname=xname,
dname=dname)
# update the "input information"
si.set_reflections(hklout)
si.set_batches(new_batches)
# update the counter & recycle
counter += 1
s = self._factory.Sortmtz()
hklout = os.path.join(self.get_working_directory(),
'%s_%s_sorted.mtz' % \
(self._scalr_pname, self._scalr_xname))
s.set_hklout(hklout)
for epoch in self._sweep_handler.get_epochs():
s.add_hklin(
self._sweep_handler.get_sweep_information(
epoch).get_reflections())
s.sort()
# verify that the measurements are in the correct setting
# choice for the spacegroup
hklin = hklout
hklout = hklin.replace('sorted.mtz', 'temp.mtz')
if not self.get_scaler_reference_reflection_file():
if PhilIndex.params.xia2.settings.symmetry.program == 'dials':
p = self._factory.dials_symmetry()
else:
p = self._factory.Pointless()
FileHandler.record_log_file('%s %s pointless' % \
(self._scalr_pname,
self._scalr_xname),
p.get_log_file())
if len(self._sweep_handler.get_epochs()) > 1:
p.set_hklin(hklin)
else:
# permit the use of pointless preparation...
epoch = self._sweep_handler.get_epochs()[0]
p.set_hklin(
self._prepare_pointless_hklin(
hklin,
self._sweep_handler.get_sweep_information(
epoch).get_integrater().get_phi_width()))
if self._scalr_input_spacegroup:
Debug.write('Assigning user input spacegroup: %s' % \
self._scalr_input_spacegroup)
p.decide_spacegroup()
spacegroup = p.get_spacegroup()
reindex_operator = p.get_spacegroup_reindex_operator()
Debug.write('Pointless thought %s (reindex as %s)' % \
(spacegroup, reindex_operator))
spacegroup = self._scalr_input_spacegroup
reindex_operator = 'h,k,l'
self._spacegroup_reindex_operator = reindex_operator
else:
p.decide_spacegroup()
spacegroup = p.get_spacegroup()
reindex_operator = p.get_spacegroup_reindex_operator()
self._spacegroup_reindex_operator = clean_reindex_operator(
reindex_operator)
Debug.write('Pointless thought %s (reindex as %s)' % \
(spacegroup, reindex_operator))
if self._scalr_input_spacegroup:
self._scalr_likely_spacegroups = [self._scalr_input_spacegroup]
else:
self._scalr_likely_spacegroups = p.get_likely_spacegroups()
Chatter.write('Likely spacegroups:')
for spag in self._scalr_likely_spacegroups:
Chatter.write('%s' % spag)
Chatter.write(
'Reindexing to first spacegroup setting: %s (%s)' % \
(spacegroup, clean_reindex_operator(reindex_operator)))
else:
spacegroup = MtzUtils.space_group_name_from_mtz(
self.get_scaler_reference_reflection_file())
reindex_operator = 'h,k,l'
self._scalr_likely_spacegroups = [spacegroup]
Debug.write('Assigning spacegroup %s from reference' % \
spacegroup)
# then run reindex to set the correct spacegroup
ri = self._factory.Reindex()
ri.set_hklin(hklin)
ri.set_hklout(hklout)
ri.set_spacegroup(spacegroup)
ri.set_operator(reindex_operator)
ri.reindex()
FileHandler.record_temporary_file(hklout)
# then resort the reflections (one last time!)
s = self._factory.Sortmtz()
temp = hklin
hklin = hklout
hklout = temp
s.add_hklin(hklin)
s.set_hklout(hklout)
s.sort()
# done preparing!
self._prepared_reflections = s.get_hklout()
def _mosflm_parallel_integrate(self):
'''Perform the integration as before, but this time as a
number of parallel Mosflm jobs (hence, in separate directories)
and including a step of pre-refinement of the mosaic spread and
missets. This will all be kind of explicit and hence probably
messy!'''
refinr = self.get_integrater_refiner()
lattice = refinr.get_refiner_lattice()
spacegroup_number = lattice_to_spacegroup(lattice)
mosaic = refinr.get_refiner_payload('mosaic')
beam = refinr.get_refiner_payload('beam')
distance = refinr.get_refiner_payload('distance')
matrix = refinr.get_refiner_payload('mosflm_orientation_matrix')
integration_params = refinr.get_refiner_payload(
'mosflm_integration_parameters')
if integration_params:
if 'separation' in integration_params:
self.set_integrater_parameter(
'mosflm', 'separation',
'%s %s' % tuple(integration_params['separation']))
if 'raster' in integration_params:
self.set_integrater_parameter(
'mosflm', 'raster',
'%d %d %d %d %d' % tuple(integration_params['raster']))
refinr.set_refiner_payload('mosflm_integration_parameters', None)
pname, xname, dname = self.get_integrater_project_info()
# what follows below should (i) be run in separate directories
# and (ii) be repeated N=parallel times.
nproc = PhilIndex.params.xia2.settings.multiprocessing.nproc
parallel = nproc
# FIXME this is something of a kludge - if too few frames refinement
# and integration does not work well... ideally want at least 15
# frames / chunk (say)
nframes = self._intgr_wedge[1] - self._intgr_wedge[0] + 1
if parallel > nframes / 15:
parallel = nframes // 15
if not parallel:
raise RuntimeError('parallel not set')
if parallel < 2:
raise RuntimeError('parallel not parallel: %s' % parallel)
jobs = []
hklouts = []
nref = 0
# calculate the chunks to use
offset = self.get_frame_offset()
start = self._intgr_wedge[0] - offset
end = self._intgr_wedge[1] - offset
left_images = 1 + end - start
left_chunks = parallel
chunks = []
while left_images > 0:
size = left_images // left_chunks
chunks.append((start, start + size - 1))
start += size
left_images -= size
left_chunks -= 1
summary_files = []
for j in range(parallel):
# make some working directories, as necessary - chunk-(0:N-1)
wd = os.path.join(self.get_working_directory(), 'chunk-%d' % j)
if not os.path.exists(wd):
os.makedirs(wd)
job = MosflmIntegrate()
job.set_working_directory(wd)
auto_logfiler(job)
l = refinr.get_refiner_lattice()
# create the starting point
f = open(os.path.join(wd, 'xiaintegrate-%s.mat' % l), 'w')
for m in matrix:
f.write(m)
f.close()
spacegroup_number = lattice_to_spacegroup(lattice)
job.set_refine_profiles(self._mosflm_refine_profiles)
# N.B. for harvesting need to append N to dname.
if pname is not None and xname is not None and dname is not None:
Debug.write('Harvesting: %s/%s/%s' % (pname, xname, dname))
harvest_dir = self.get_working_directory()
temp_dname = '%s_%s' % \
(dname, self.get_integrater_sweep_name())
job.set_pname_xname_dname(pname, xname, temp_dname)
job.set_template(os.path.basename(self.get_template()))
job.set_directory(self.get_directory())
# check for ice - and if so, exclude (ranges taken from
# XDS documentation)
if self.get_integrater_ice() != 0:
Debug.write('Excluding ice rings')
job.set_exclude_ice(True)
# exclude specified resolution ranges
if len(self.get_integrater_excluded_regions()) != 0:
regions = self.get_integrater_excluded_regions()
Debug.write('Excluding regions: %s' % repr(regions))
job.set_exclude_regions(regions)
mask = standard_mask(self.get_detector())
for m in mask:
job.add_instruction(m)
job.set_input_mat_file('xiaintegrate-%s.mat' % l)
job.set_beam_centre(beam)
job.set_distance(distance)
job.set_space_group_number(spacegroup_number)
job.set_mosaic(mosaic)
if self.get_wavelength_prov() == 'user':
job.set_wavelength(self.get_wavelength())
parameters = self.get_integrater_parameters('mosflm')
job.update_parameters(parameters)
if self._mosflm_gain:
job.set_gain(self._mosflm_gain)
# check for resolution limits
if self._intgr_reso_high > 0.0:
job.set_d_min(self._intgr_reso_high)
if self._intgr_reso_low:
job.set_d_max(self._intgr_reso_low)
if PhilIndex.params.general.backstop_mask:
from xia2.Toolkit.BackstopMask import BackstopMask
mask = BackstopMask(PhilIndex.params.general.backstop_mask)
mask = mask.calculate_mask_mosflm(self.get_header())
job.set_mask(mask)
detector = self.get_detector()
detector_width, detector_height = detector[0].get_image_size_mm()
lim_x = 0.5 * detector_width
lim_y = 0.5 * detector_height
Debug.write('Scanner limits: %.1f %.1f' % (lim_x, lim_y))
job.set_limits(lim_x, lim_y)
job.set_fix_mosaic(self._mosflm_postref_fix_mosaic)
job.set_pre_refinement(True)
job.set_image_range(chunks[j])
# these are now running so ...
jobs.append(job)
continue
# ok, at this stage I need to ...
#
# (i) accumulate the statistics as a function of batch
# (ii) mong them into a single block
#
# This is likely to be a pain in the arse!
first_integrated_batch = 1.0e6
last_integrated_batch = -1.0e6
all_residuals = []
threads = []
for j in range(parallel):
job = jobs[j]
# now wait for them to finish - first wait will really be the
# first one, then all should be finished...
thread = Background(job, 'run')
thread.start()
threads.append(thread)
mosaics = []
postref_result = {}
integrated_images_first = 1.0e6
integrated_images_last = -1.0e6
self._intgr_per_image_statistics = {}
for j in range(parallel):
thread = threads[j]
thread.stop()
job = jobs[j]
# get the log file
output = job.get_all_output()
# record a copy of it, perhaps - though not if parallel
if self.get_integrater_sweep_name() and False:
pname, xname, dname = self.get_integrater_project_info()
FileHandler.record_log_file(
'%s %s %s %s mosflm integrate' % \
(self.get_integrater_sweep_name(),
pname, xname, '%s_%d' % (dname, j)),
job.get_log_file())
# look for things that we want to know...
# that is, the output reflection file name, the updated
# value for the gain (if present,) any warnings, errors,
# or just interesting facts.
batches = job.get_batches_out()
integrated_images_first = min(batches[0], integrated_images_first)
integrated_images_last = max(batches[1], integrated_images_last)
mosaics.extend(job.get_mosaic_spreads())
if min(mosaics) < 0:
raise IntegrationError('negative mosaic spread: %s' %
min(mosaic))
if (job.get_detector_gain_error()
and not (self.get_imageset().get_detector()[0].get_type()
== 'SENSOR_PAD')):
gain = job.get_suggested_gain()
if gain is not None:
self.set_integrater_parameter('mosflm', 'gain', gain)
self.set_integrater_export_parameter(
'mosflm', 'gain', gain)
if self._mosflm_gain:
Debug.write('GAIN updated to %f' % gain)
else:
Debug.write('GAIN found to be %f' % gain)
self._mosflm_gain = gain
self._mosflm_rerun_integration = True
hklout = job.get_hklout()
Debug.write('Integration output: %s' % hklout)
hklouts.append(hklout)
nref += job.get_nref()
# if a BGSIG error happened try not refining the
# profile and running again...
if job.get_bgsig_too_large():
if not self._mosflm_refine_profiles:
raise RuntimeError('BGSIG error with profiles fixed')
Debug.write('BGSIG error detected - try fixing profile...')
self._mosflm_refine_profiles = False
self.set_integrater_done(False)
return
if job.get_getprof_error():
Debug.write('GETPROF error detected - try fixing profile...')
self._mosflm_refine_profiles = False
self.set_integrater_done(False)
return
# here
# write the report for each image as .*-#$ to Chatter -
# detailed report will be written automagically to science...
self._intgr_per_image_statistics.update(
job.get_per_image_statistics())
postref_result.update(job.get_postref_result())
# inspect the output for e.g. very high weighted residuals
all_residuals.extend(job.get_residuals())
self._intgr_batches_out = (integrated_images_first,
integrated_images_last)
if mosaics and len(mosaics) > 0:
self.set_integrater_mosaic_min_mean_max(
min(mosaics),
sum(mosaics) / len(mosaics), max(mosaics))
else:
m = indxr.get_indexer_mosaic()
self.set_integrater_mosaic_min_mean_max(m, m, m)
Chatter.write(self.show_per_image_statistics())
Chatter.write('Mosaic spread: %.3f < %.3f < %.3f' % \
self.get_integrater_mosaic_min_mean_max())
# gather the statistics from the postrefinement for all sweeps
# now write this to a postrefinement log
postref_log = os.path.join(self.get_working_directory(),
'postrefinement.log')
fout = open(postref_log, 'w')
fout.write('$TABLE: Postrefinement for %s:\n' % \
self._intgr_sweep_name)
fout.write('$GRAPHS: Missetting angles:A:1, 2, 3, 4: $$\n')
fout.write('Batch PhiX PhiY PhiZ $$ Batch PhiX PhiY PhiZ $$\n')
for image in sorted(postref_result):
phix = postref_result[image].get('phix', 0.0)
phiy = postref_result[image].get('phiy', 0.0)
phiz = postref_result[image].get('phiz', 0.0)
fout.write('%d %5.2f %5.2f %5.2f\n' % \
(image, phix, phiy, phiz))
fout.write('$$\n')
fout.close()
if self.get_integrater_sweep_name():
pname, xname, dname = self.get_integrater_project_info()
FileHandler.record_log_file('%s %s %s %s postrefinement' % \
(self.get_integrater_sweep_name(),
pname, xname, dname),
postref_log)
hklouts.sort()
hklout = os.path.join(self.get_working_directory(),
os.path.split(hklouts[0])[-1])
Debug.write('Sorting data to %s' % hklout)
for hklin in hklouts:
Debug.write('<= %s' % hklin)
sortmtz = Sortmtz()
sortmtz.set_hklout(hklout)
for hklin in hklouts:
sortmtz.add_hklin(hklin)
sortmtz.sort()
self._mosflm_hklout = hklout
return self._mosflm_hklout
def _sort_together_data_xds_one_sweep(self):
assert len(self._sweep_information) == 1
epoch = self._sweep_information.keys()[0]
hklin = self._sweep_information[epoch]['scaled_reflections']
if self.get_scaler_reference_reflection_file():
spacegroups = [
MtzUtils.space_group_name_from_mtz(
self.get_scaler_reference_reflection_file())
]
reindex_operator = 'h,k,l'
elif self._scalr_input_spacegroup:
Debug.write('Assigning user input spacegroup: %s' % \
self._scalr_input_spacegroup)
spacegroups = [self._scalr_input_spacegroup]
reindex_operator = 'h,k,l'
else:
pointless = self._factory.Pointless()
pointless.set_hklin(hklin)
pointless.decide_spacegroup()
FileHandler.record_log_file('%s %s pointless' % \
(self._scalr_pname,
self._scalr_xname),
pointless.get_log_file())
spacegroups = pointless.get_likely_spacegroups()
reindex_operator = pointless.get_spacegroup_reindex_operator()
self._scalr_likely_spacegroups = spacegroups
spacegroup = self._scalr_likely_spacegroups[0]
self._scalr_reindex_operator = clean_reindex_operator(reindex_operator)
Chatter.write('Likely spacegroups:')
for spag in self._scalr_likely_spacegroups:
Chatter.write('%s' % spag)
Chatter.write(
'Reindexing to first spacegroup setting: %s (%s)' % \
(spacegroup, clean_reindex_operator(reindex_operator)))
hklout = os.path.join(self.get_working_directory(),
'%s_%s_reindex.mtz' % \
(self._scalr_pname, self._scalr_xname))
FileHandler.record_temporary_file(hklout)
if reindex_operator == '[h,k,l]':
# just assign spacegroup
from cctbx import sgtbx
s = sgtbx.space_group(
sgtbx.space_group_symbols(str(spacegroup)).hall())
m = mtz.object(hklin)
m.set_space_group(s).write(hklout)
self._scalr_cell = m.crystals()[-1].unit_cell().parameters()
Debug.write(
'Updating unit cell to %.2f %.2f %.2f %.2f %.2f %.2f' % \
tuple(self._scalr_cell))
del m
del s
else:
ri = self._factory.Reindex()
ri.set_hklin(hklin)
ri.set_hklout(hklout)
ri.set_spacegroup(spacegroup)
ri.set_operator(reindex_operator)
ri.reindex()
Debug.write(
'Updating unit cell to %.2f %.2f %.2f %.2f %.2f %.2f' % \
tuple(ri.get_cell()))
self._scalr_cell = tuple(ri.get_cell())
hklin = hklout
hklout = os.path.join(self.get_working_directory(),
'%s_%s_sorted.mtz' % \
(self._scalr_pname, self._scalr_xname))
s = self._factory.Sortmtz()
s.set_hklin(hklin)
s.set_hklout(hklout)
s.sort(vrset=-99999999.0)
self._prepared_reflections = hklout
def _do_indexing(self, method=None):
indexer = self.Index()
for spot_list in self._indxr_payload["spot_lists"]:
indexer.add_spot_filename(spot_list)
for filename in self._indxr_payload["experiments"]:
indexer.add_sweep_filename(filename)
if PhilIndex.params.dials.index.phil_file is not None:
indexer.set_phil_file(PhilIndex.params.dials.index.phil_file)
indexer.set_max_cell(
max_cell=PhilIndex.params.dials.index.max_cell,
max_height_fraction=PhilIndex.params.dials.index.
max_cell_estimation.max_height_fraction,
)
if PhilIndex.params.xia2.settings.small_molecule:
indexer.set_min_cell(3)
if PhilIndex.params.dials.fix_geometry:
indexer.set_detector_fix("all")
indexer.set_beam_fix("all")
elif PhilIndex.params.dials.fix_distance:
indexer.set_detector_fix("distance")
indexer.set_close_to_spindle_cutoff(
PhilIndex.params.dials.close_to_spindle_cutoff)
if self._indxr_input_lattice:
indexer.set_indexer_input_lattice(self._indxr_input_lattice)
logger.debug("Set lattice: %s", self._indxr_input_lattice)
if self._indxr_input_cell:
indexer.set_indexer_input_cell(self._indxr_input_cell)
logger.debug("Set cell: %f %f %f %f %f %f" %
self._indxr_input_cell)
if method is None:
if PhilIndex.params.dials.index.method is None:
method = "fft3d"
logger.debug("Choosing indexing method: %s", method)
else:
method = PhilIndex.params.dials.index.method
FileHandler.record_log_file("%s INDEX" % self.get_indexer_full_name(),
indexer.get_log_file())
indexer.run(method)
if not os.path.exists(indexer.get_experiments_filename()):
raise RuntimeError(
"Indexing has failed: see %s for more details." %
indexer.get_log_file())
elif not os.path.exists(indexer.get_indexed_filename()):
raise RuntimeError("Indexing has failed: %s does not exist." %
indexer.get_indexed_filename())
report = self.Report()
report.set_experiments_filename(indexer.get_experiments_filename())
report.set_reflections_filename(indexer.get_indexed_filename())
html_filename = os.path.join(
self.get_working_directory(),
"%i_dials.index.report.html" % report.get_xpid(),
)
report.set_html_filename(html_filename)
report.run()
FileHandler.record_html_file("%s INDEX" % self.get_indexer_full_name(),
html_filename)
return indexer
def _sort_together_data_xds_one_sweep(self):
assert(len(self._sweep_information) == 1)
epoch = self._sweep_information.keys()[0]
hklin = self._sweep_information[epoch]['scaled_reflections']
if Flags.get_chef():
self._sweep_information_to_chef()
if self.get_scaler_reference_reflection_file():
md = self._factory.Mtzdump()
md.set_hklin(self.get_scaler_reference_reflection_file())
md.dump()
spacegroups = [md.get_spacegroup()]
reindex_operator = 'h,k,l'
elif self._scalr_input_spacegroup:
Debug.write('Assigning user input spacegroup: %s' % \
self._scalr_input_spacegroup)
spacegroups = [self._scalr_input_spacegroup]
reindex_operator = 'h,k,l'
else:
pointless = self._factory.Pointless()
pointless.set_hklin(hklin)
pointless.decide_spacegroup()
FileHandler.record_log_file('%s %s pointless' % \
(self._scalr_pname,
self._scalr_xname),
pointless.get_log_file())
spacegroups = pointless.get_likely_spacegroups()
reindex_operator = pointless.get_spacegroup_reindex_operator()
self._scalr_likely_spacegroups = spacegroups
spacegroup = self._scalr_likely_spacegroups[0]
self._scalr_reindex_operator = reindex_operator
Chatter.write('Likely spacegroups:')
for spag in self._scalr_likely_spacegroups:
Chatter.write('%s' % spag)
Chatter.write(
'Reindexing to first spacegroup setting: %s (%s)' % \
(spacegroup, clean_reindex_operator(reindex_operator)))
hklout = os.path.join(self.get_working_directory(),
'%s_%s_reindex.mtz' % \
(self._scalr_pname, self._scalr_xname))
FileHandler.record_temporary_file(hklout)
if reindex_operator == '[h,k,l]':
# just assign spacegroup
from iotbx import mtz
from cctbx import sgtbx
s = sgtbx.space_group(sgtbx.space_group_symbols(
str(spacegroup)).hall())
m = mtz.object(hklin)
m.set_space_group(s).write(hklout)
self._scalr_cell = m.crystals()[-1].unit_cell().parameters()
Debug.write(
'Updating unit cell to %.2f %.2f %.2f %.2f %.2f %.2f' % \
tuple(self._scalr_cell))
del(m)
del(s)
else:
ri = self._factory.Reindex()
ri.set_hklin(hklin)
ri.set_hklout(hklout)
ri.set_spacegroup(spacegroup)
ri.set_operator(reindex_operator)
ri.reindex()
Debug.write(
'Updating unit cell to %.2f %.2f %.2f %.2f %.2f %.2f' % \
tuple(ri.get_cell()))
self._scalr_cell = tuple(ri.get_cell())
hklin = hklout
hklout = os.path.join(self.get_working_directory(),
'%s_%s_sorted.mtz' % \
(self._scalr_pname, self._scalr_xname))
s = self._factory.Sortmtz()
s.set_hklin(hklin)
s.set_hklout(hklout)
s.sort(vrset = -99999999.0)
self._prepared_reflections = hklout
return
def write_xml(self, file, command_line="", working_phil=None):
if working_phil is not None:
PhilIndex.merge_phil(working_phil)
params = PhilIndex.get_python_object()
fout = open(file, "w")
fout.write('<?xml version="1.0"?>')
fout.write("<AutoProcContainer>\n")
for crystal in sorted(self._crystals):
xcrystal = self._crystals[crystal]
cell = xcrystal.get_cell()
spacegroup = xcrystal.get_likely_spacegroups()[0]
fout.write("<AutoProc><spaceGroup>%s</spaceGroup>" % spacegroup)
self.write_refined_cell(fout, cell)
fout.write("</AutoProc>")
fout.write("<AutoProcScalingContainer>")
fout.write("<AutoProcScaling>")
self.write_date(fout)
fout.write("</AutoProcScaling>")
statistics_all = xcrystal.get_statistics()
reflection_files = xcrystal.get_scaled_merged_reflections()
for key in statistics_all:
pname, xname, dname = key
# FIXME should assert that the dname is a
# valid wavelength name
keys = [
"High resolution limit",
"Low resolution limit",
"Completeness",
"Multiplicity",
"I/sigma",
"Rmerge(I+/-)",
"CC half",
"Anomalous completeness",
"Anomalous correlation",
"Anomalous multiplicity",
"Total observations",
"Total unique",
"Rmeas(I)",
"Rmeas(I+/-)",
"Rpim(I)",
"Rpim(I+/-)",
"Partial Bias",
]
stats = [k for k in keys if k in statistics_all[key]]
xwavelength = xcrystal.get_xwavelength(dname)
sweeps = xwavelength.get_sweeps()
for j, name in enumerate(
["overall", "innerShell", "outerShell"]):
statistics_cache = {}
for s in stats:
if isinstance(statistics_all[key][s], type([])):
statistics_cache[s] = statistics_all[key][s][j]
elif isinstance(statistics_all[key][s], type(())):
statistics_cache[s] = statistics_all[key][s][j]
# send these to be written out
self.write_scaling_statistics(fout, name, statistics_cache)
for sweep in sweeps:
fout.write("<AutoProcIntegrationContainer>\n")
if "#" in sweep.get_template():
image_name = sweep.get_image_name(0)
else:
image_name = os.path.join(sweep.get_directory(),
sweep.get_template())
fout.write("<Image><fileName>%s</fileName>" %
os.path.split(image_name)[-1])
fout.write("<fileLocation>%s</fileLocation></Image>" %
sanitize(os.path.split(image_name)[0]))
fout.write("<AutoProcIntegration>\n")
cell = sweep.get_integrater_cell()
self.write_cell(fout, cell)
# FIXME this is naughty
intgr = sweep._get_integrater()
start, end = intgr.get_integrater_wedge()
fout.write("<startImageNumber>%d</startImageNumber>" %
start)
fout.write("<endImageNumber>%d</endImageNumber>" % end)
# FIXME this is naughty
indxr = sweep._get_indexer()
fout.write(
"<refinedDetectorDistance>%f</refinedDetectorDistance>"
% indxr.get_indexer_distance())
beam = indxr.get_indexer_beam_centre_raw_image()
fout.write("<refinedXBeam>%f</refinedXBeam>" % beam[0])
fout.write("<refinedYBeam>%f</refinedYBeam>" % beam[1])
fout.write("</AutoProcIntegration>\n")
fout.write("</AutoProcIntegrationContainer>\n")
fout.write("</AutoProcScalingContainer>")
# file unpacking nonsense
if not command_line:
from xia2.Handlers.CommandLine import CommandLine
command_line = CommandLine.get_command_line()
pipeline = params.xia2.settings.pipeline
fout.write("<AutoProcProgramContainer><AutoProcProgram>")
fout.write("<processingCommandLine>%s</processingCommandLine>" %
sanitize(command_line))
fout.write("<processingPrograms>xia2 %s</processingPrograms>" %
pipeline)
fout.write("</AutoProcProgram>")
data_directory = self._project.path / "DataFiles"
log_directory = self._project.path / "LogFiles"
for k in reflection_files:
reflection_file = reflection_files[k]
if not isinstance(reflection_file, type("")):
continue
reflection_file = FileHandler.get_data_file(
self._project.path, reflection_file)
basename = os.path.basename(reflection_file)
if data_directory.joinpath(basename).exists():
# Use file in DataFiles directory in preference (if it exists)
reflection_file = str(data_directory.joinpath(basename))
fout.write("<AutoProcProgramAttachment><fileType>Result")
fout.write("</fileType><fileName>%s</fileName>" %
os.path.split(reflection_file)[-1])
fout.write("<filePath>%s</filePath>" %
sanitize(os.path.split(reflection_file)[0]))
fout.write("</AutoProcProgramAttachment>\n")
g = log_directory.glob("*merging-statistics.json")
for merging_stats_json in g:
fout.write("<AutoProcProgramAttachment><fileType>Graph")
fout.write("</fileType><fileName>%s</fileName>" %
os.path.split(str(merging_stats_json))[-1])
fout.write("<filePath>%s</filePath>" %
sanitize(str(log_directory)))
fout.write("</AutoProcProgramAttachment>\n")
# add the xia2.txt file...
fout.write("<AutoProcProgramAttachment><fileType>Log")
fout.write("</fileType><fileName>xia2.txt</fileName>")
fout.write("<filePath>%s</filePath>" % sanitize(os.getcwd()))
fout.write("</AutoProcProgramAttachment>\n")
fout.write("</AutoProcProgramContainer>")
fout.write("</AutoProcContainer>\n")
fout.close()
def _integrate(self):
'''Actually do the integration - in XDS terms this will mean running
DEFPIX and INTEGRATE to measure all the reflections.'''
images_str = '%d to %d' % tuple(self._intgr_wedge)
cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % tuple(self._intgr_cell)
if len(self._fp_directory) <= 50:
dirname = self._fp_directory
else:
dirname = '...%s' % self._fp_directory[-46:]
Journal.block(
'integrating', self._intgr_sweep_name, 'DIALS',
{'images':images_str,
'cell':cell_str,
'lattice':self.get_integrater_refiner().get_refiner_lattice(),
'template':self._fp_template,
'directory':dirname,
'resolution':'%.2f' % self._intgr_reso_high})
integrate = self.Integrate()
# decide what images we are going to process, if not already
# specified
if not self._intgr_wedge:
images = self.get_matching_images()
self.set_integrater_wedge(min(images),
max(images))
imageset = self.get_imageset()
beam = imageset.get_beam()
detector = imageset.get_detector()
d_min_limit = detector.get_max_resolution(beam.get_s0())
if d_min_limit > self._intgr_reso_high \
or PhilIndex.params.xia2.settings.resolution.keep_all_reflections:
Debug.write('Overriding high resolution limit: %f => %f' % \
(self._intgr_reso_high, d_min_limit))
self._intgr_reso_high = d_min_limit
integrate.set_experiments_filename(self._intgr_experiments_filename)
integrate.set_reflections_filename(self._intgr_indexed_filename)
integrate.set_d_max(self._intgr_reso_low)
integrate.set_d_min(self._intgr_reso_high)
pname, xname, dname = self.get_integrater_project_info()
sweep = self.get_integrater_sweep_name()
FileHandler.record_log_file('%s %s %s %s INTEGRATE' % \
(pname, xname, dname, sweep),
integrate.get_log_file())
try:
integrate.run()
except RuntimeError, e:
s = str(e)
if ('dials.integrate requires more memory than is available.' in s
and not self._intgr_reso_high):
# Try to estimate a more sensible resolution limit for integration
# in case we were just integrating noise to the edge of the detector
images = self._integrate_select_images_wedges()
Debug.write(
'Integrating subset of images to estimate resolution limit.\n'
'Integrating images %s' %images)
integrate = self.Integrate()
integrate.set_experiments_filename(self._intgr_experiments_filename)
integrate.set_reflections_filename(self._intgr_indexed_filename)
integrate.set_d_max(self._intgr_reso_low)
integrate.set_d_min(self._intgr_reso_high)
for (start, stop) in images:
integrate.add_scan_range(start-self.get_matching_images()[0], stop-self.get_matching_images()[0])
integrate.set_reflections_per_degree(1000)
integrate.run()
integrated_pickle = integrate.get_integrated_filename()
from xia2.Wrappers.Dials.EstimateResolutionLimit import EstimateResolutionLimit
d_min_estimater = EstimateResolutionLimit()
d_min_estimater.set_working_directory(self.get_working_directory())
auto_logfiler(d_min_estimater)
d_min_estimater.set_experiments_filename(self._intgr_experiments_filename)
d_min_estimater.set_reflections_filename(integrated_pickle)
d_min = d_min_estimater.run()
Debug.write('Estimate for d_min: %.2f' %d_min)
Debug.write('Re-running integration to this resolution limit')
self._intgr_reso_high = d_min
self.set_integrater_done(False)
return
raise
else:
sc.scale()
# then gather up all of the resulting reflection files
# and convert them into the required formats (.sca, .mtz.)
data = sc.get_summary()
loggraph = sc.parse_ccp4_loggraph()
resolution_info = { }
reflection_files = sc.get_scaled_reflection_files()
for dataset in reflection_files:
FileHandler.record_temporary_file(reflection_files[dataset])
for key in loggraph:
if 'Analysis against resolution' in key:
dataset = key.split(',')[-1].strip()
resolution_info[dataset] = transpose_loggraph(
loggraph[key])
highest_resolution = 100.0
# check in here that there is actually some data to scale..!
if len(resolution_info) == 0:
raise RuntimeError, 'no resolution info'
for epoch in epochs:
def _sort_together_data_ccp4(self):
'''Sort together in the right order (rebatching as we go) the sweeps
we want to scale together.'''
max_batches = 0
for e in self._sweep_handler.get_epochs():
if Flags.get_small_molecule():
continue
si = self._sweep_handler.get_sweep_information(e)
pname, xname, dname = si.get_project_info()
sname = si.get_sweep_name()
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
hklin = si.get_reflections()
# limit the reflections - e.g. if we are re-running the scaling step
# on just a subset of the integrated data
hklin = si.get_reflections()
limit_batch_range = None
for sweep in PhilIndex.params.xia2.settings.sweep:
if sweep.id == sname and sweep.range is not None:
limit_batch_range = sweep.range
break
if limit_batch_range is not None:
Debug.write('Limiting batch range for %s: %s' %(sname, limit_batch_range))
start, end = limit_batch_range
hklout = os.path.splitext(hklin)[0] + '_tmp.mtz'
FileHandler.record_temporary_file(hklout)
rb = self._factory.Pointless()
rb.set_hklin(hklin)
rb.set_hklout(hklout)
rb.limit_batches(start, end)
si.set_reflections(hklout)
si.set_batches(limit_batch_range)
# keep a count of the maximum number of batches in a block -
# this will be used to make rebatch work below.
hklin = si.get_reflections()
md = self._factory.Mtzdump()
md.set_hklin(hklin)
md.dump()
batches = md.get_batches()
if 1 + max(batches) - min(batches) > max_batches:
max_batches = max(batches) - min(batches) + 1
datasets = md.get_datasets()
Debug.write('In reflection file %s found:' % hklin)
for d in datasets:
Debug.write('... %s' % d)
dataset_info = md.get_dataset_info(datasets[0])
Debug.write('Biggest sweep has %d batches' % max_batches)
max_batches = nifty_power_of_ten(max_batches)
# then rebatch the files, to make sure that the batch numbers are
# in the same order as the epochs of data collection.
counter = 0
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
rb = self._factory.Rebatch()
hklin = si.get_reflections()
pname, xname, dname = si.get_project_info()
sname = si.get_sweep_name()
hklout = os.path.join(self.get_working_directory(),
'%s_%s_%s_%s_integrated.mtz' % \
(pname, xname, dname, sname))
first_batch = min(si.get_batches())
si.set_batch_offset(counter * max_batches - first_batch + 1)
rb.set_hklin(hklin)
rb.set_first_batch(counter * max_batches + 1)
rb.set_project_info(pname, xname, dname)
rb.set_hklout(hklout)
new_batches = rb.rebatch()
# update the "input information"
si.set_reflections(hklout)
si.set_batches(new_batches)
# update the counter & recycle
counter += 1
s = self._factory.Sortmtz()
hklout = os.path.join(self.get_working_directory(),
'%s_%s_sorted.mtz' % \
(self._scalr_pname, self._scalr_xname))
s.set_hklout(hklout)
for epoch in self._sweep_handler.get_epochs():
s.add_hklin(self._sweep_handler.get_sweep_information(
epoch).get_reflections())
s.sort()
# verify that the measurements are in the correct setting
# choice for the spacegroup
hklin = hklout
hklout = hklin.replace('sorted.mtz', 'temp.mtz')
if not self.get_scaler_reference_reflection_file():
p = self._factory.Pointless()
FileHandler.record_log_file('%s %s pointless' % \
(self._scalr_pname,
self._scalr_xname),
p.get_log_file())
if len(self._sweep_handler.get_epochs()) > 1:
p.set_hklin(hklin)
else:
# permit the use of pointless preparation...
epoch = self._sweep_handler.get_epochs()[0]
p.set_hklin(self._prepare_pointless_hklin(
hklin, self._sweep_handler.get_sweep_information(
epoch).get_integrater().get_phi_width()))
if self._scalr_input_spacegroup:
Debug.write('Assigning user input spacegroup: %s' % \
self._scalr_input_spacegroup)
p.decide_spacegroup()
spacegroup = p.get_spacegroup()
reindex_operator = p.get_spacegroup_reindex_operator()
Debug.write('Pointless thought %s (reindex as %s)' % \
(spacegroup, reindex_operator))
spacegroup = self._scalr_input_spacegroup
reindex_operator = 'h,k,l'
elif Flags.get_small_molecule() and False:
p.decide_pointgroup()
spacegroup = p.get_pointgroup()
reindex_operator = p.get_reindex_operator()
Debug.write('Pointless thought %s (reindex as %s)' % \
(spacegroup, reindex_operator))
self._scalr_likely_spacegroups = [spacegroup]
else:
p.decide_spacegroup()
spacegroup = p.get_spacegroup()
reindex_operator = p.get_spacegroup_reindex_operator()
Debug.write('Pointless thought %s (reindex as %s)' % \
(spacegroup, reindex_operator))
if self._scalr_input_spacegroup:
self._scalr_likely_spacegroups = [self._scalr_input_spacegroup]
else:
self._scalr_likely_spacegroups = p.get_likely_spacegroups()
Chatter.write('Likely spacegroups:')
for spag in self._scalr_likely_spacegroups:
Chatter.write('%s' % spag)
Chatter.write(
'Reindexing to first spacegroup setting: %s (%s)' % \
(spacegroup, clean_reindex_operator(reindex_operator)))
else:
md = self._factory.Mtzdump()
md.set_hklin(self.get_scaler_reference_reflection_file())
md.dump()
spacegroup = md.get_spacegroup()
reindex_operator = 'h,k,l'
self._scalr_likely_spacegroups = [spacegroup]
Debug.write('Assigning spacegroup %s from reference' % \
spacegroup)
# then run reindex to set the correct spacegroup
ri = self._factory.Reindex()
ri.set_hklin(hklin)
ri.set_hklout(hklout)
ri.set_spacegroup(spacegroup)
ri.set_operator(reindex_operator)
ri.reindex()
FileHandler.record_temporary_file(hklout)
# then resort the reflections (one last time!)
s = self._factory.Sortmtz()
temp = hklin
hklin = hklout
hklout = temp
s.add_hklin(hklin)
s.set_hklout(hklout)
s.sort()
# done preparing!
self._prepared_reflections = s.get_hklout()
return
def _integrate(self):
'''Actually do the integration - in XDS terms this will mean running
DEFPIX and INTEGRATE to measure all the reflections.'''
experiment = self._intgr_refiner.get_refined_experiment_list(
self.get_integrater_epoch())[0]
crystal_model = experiment.crystal
self._intgr_refiner_cell = crystal_model.get_unit_cell().parameters()
images_str = '%d to %d' % tuple(self._intgr_wedge)
cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' %tuple(self._intgr_refiner_cell)
if len(self._fp_directory) <= 50:
dirname = self._fp_directory
else:
dirname = '...%s' % self._fp_directory[-46:]
Journal.block(
'integrating', self._intgr_sweep_name, 'XDS',
{'images':images_str,
'cell':cell_str,
'lattice':self._intgr_refiner.get_refiner_lattice(),
'template':self._fp_template,
'directory':dirname,
'resolution':'%.2f' % self._intgr_reso_high})
first_image_in_wedge = self.get_image_name(self._intgr_wedge[0])
defpix = self.Defpix()
# pass in the correct data
for file in ['X-CORRECTIONS.cbf',
'Y-CORRECTIONS.cbf',
'BKGINIT.cbf',
'XPARM.XDS']:
defpix.set_input_data_file(file, self._xds_data_files[file])
defpix.set_data_range(self._intgr_wedge[0],
self._intgr_wedge[1])
if self.get_integrater_high_resolution() > 0.0 and \
self.get_integrater_user_resolution():
Debug.write('Setting resolution limit in DEFPIX to %.2f' % \
self.get_integrater_high_resolution())
defpix.set_resolution_high(self.get_integrater_high_resolution())
defpix.set_resolution_low(self.get_integrater_low_resolution())
elif self.get_integrater_low_resolution():
Debug.write('Setting low resolution limit in DEFPIX to %.2f' % \
self.get_integrater_low_resolution())
defpix.set_resolution_high(0.0)
defpix.set_resolution_low(self.get_integrater_low_resolution())
defpix.run()
# and gather the result files
for file in ['BKGPIX.cbf',
'ABS.cbf']:
self._xds_data_files[file] = defpix.get_output_data_file(file)
integrate = self.Integrate()
if self._xds_integrate_parameters:
integrate.set_updates(self._xds_integrate_parameters)
# decide what images we are going to process, if not already
# specified
if not self._intgr_wedge:
images = self.get_matching_images()
self.set_integrater_wedge(min(images),
max(images))
first_image_in_wedge = self.get_image_name(self._intgr_wedge[0])
integrate.set_data_range(self._intgr_wedge[0],
self._intgr_wedge[1])
for file in ['X-CORRECTIONS.cbf',
'Y-CORRECTIONS.cbf',
'BLANK.cbf',
'BKGPIX.cbf',
'GAIN.cbf']:
integrate.set_input_data_file(file, self._xds_data_files[file])
if self._xds_data_files.has_key('GXPARM.XDS'):
Debug.write('Using globally refined parameters')
integrate.set_input_data_file(
'XPARM.XDS', self._xds_data_files['GXPARM.XDS'])
integrate.set_refined_xparm()
else:
integrate.set_input_data_file(
'XPARM.XDS', self._xds_data_files['XPARM.XDS'])
integrate.run()
self._intgr_per_image_statistics = integrate.get_per_image_statistics()
Chatter.write(self.show_per_image_statistics())
# record the log file -
pname, xname, dname = self.get_integrater_project_info()
sweep = self.get_integrater_sweep_name()
FileHandler.record_log_file('%s %s %s %s INTEGRATE' % \
(pname, xname, dname, sweep),
os.path.join(self.get_working_directory(),
'INTEGRATE.LP'))
# and copy the first pass INTEGRATE.HKL...
lattice = self._intgr_refiner.get_refiner_lattice()
if not os.path.exists(os.path.join(
self.get_working_directory(),
'INTEGRATE-%s.HKL' % lattice)):
here = self.get_working_directory()
shutil.copyfile(os.path.join(here, 'INTEGRATE.HKL'),
os.path.join(here, 'INTEGRATE-%s.HKL' % lattice))
# record INTEGRATE.HKL for e.g. BLEND.
FileHandler.record_more_data_file(
'%s %s %s %s INTEGRATE' % (pname, xname, dname, sweep),
os.path.join(self.get_working_directory(), 'INTEGRATE.HKL'))
# should the existence of these require that I rerun the
# integration or can we assume that the application of a
# sensible resolution limit will achieve this??
self._xds_integrate_parameters = integrate.get_updates()
# record the mosaic spread &c.
m_min, m_mean, m_max = integrate.get_mosaic()
self.set_integrater_mosaic_min_mean_max(m_min, m_mean, m_max)
Chatter.write('Mosaic spread: %.3f < %.3f < %.3f' % \
self.get_integrater_mosaic_min_mean_max())
return os.path.join(self.get_working_directory(), 'INTEGRATE.HKL')
def _scale_finish_export_shelxt(self):
'''Read hklin (unmerged reflection file) and generate SHELXT input file
and HKL file'''
from iotbx.reflection_file_reader import any_reflection_file
from iotbx.shelx import writer
from iotbx.shelx.hklf import miller_array_export_as_shelx_hklf
from cctbx.xray.structure import structure
from cctbx.xray import scatterer
for wavelength_name in self._scalr_scaled_refl_files.keys():
prefix = wavelength_name
if len(self._scalr_scaled_refl_files.keys()) == 1:
prefix = 'shelxt'
prefixpath = os.path.join(self.get_working_directory(), prefix)
mtz_unmerged = self._scalr_scaled_reflection_files['mtz_unmerged'][
wavelength_name]
reader = any_reflection_file(mtz_unmerged)
intensities = [
ma for ma in reader.as_miller_arrays(merge_equivalents=False)
if ma.info().labels == ['I', 'SIGI']
][0]
# FIXME do I need to reindex to a conventional setting here
indices = reader.file_content(
).extract_original_index_miller_indices()
intensities = intensities.customized_copy(indices=indices,
info=intensities.info())
with open('%s.hkl' % prefixpath, 'wb') as hkl_file_handle:
# limit values to 4 digits (before decimal point), as this is what shelxt
# writes in its output files, and shelxl seems to read. ShelXL apparently
# does not read values >9999 properly
miller_array_export_as_shelx_hklf(
intensities,
hkl_file_handle,
scale_range=(-9999., 9999.),
normalise_if_format_overflow=True)
crystal_symm = intensities.crystal_symmetry()
unit_cell_dims = self._scalr_cell
unit_cell_esds = self._scalr_cell_esd
cb_op = crystal_symm.change_of_basis_op_to_reference_setting()
if cb_op.c().r().as_hkl() == 'h,k,l':
print('Change of basis to reference setting: %s' % cb_op)
crystal_symm = crystal_symm.change_basis(cb_op)
if str(cb_op) != "a,b,c":
unit_cell_dims = None
unit_cell_esds = None
# Would need to apply operation to cell errors, too. Need a test case for this
# crystal_symm.show_summary()
xray_structure = structure(crystal_symmetry=crystal_symm)
compound = 'CNOH'
if compound:
from xia2.command_line.to_shelx import parse_compound
result = parse_compound(compound)
for element in result:
xray_structure.add_scatterer(
scatterer(label=element, occupancy=result[element]))
wavelength = self._scalr_xcrystal.get_xwavelength(
wavelength_name).get_wavelength()
with open('%s.ins' % prefixpath, 'w') as insfile:
insfile.write(''.join(
writer.generator(xray_structure,
wavelength=wavelength,
full_matrix_least_squares_cycles=0,
title=prefix,
unit_cell_dims=unit_cell_dims,
unit_cell_esds=unit_cell_esds)))
FileHandler.record_data_file('%s.ins' % prefixpath)
FileHandler.record_data_file('%s.hkl' % prefixpath)
def _index(self):
if PhilIndex.params.dials.index.method in (libtbx.Auto, None):
if self._indxr_input_cell is not None:
indexer = self._do_indexing("real_space_grid_search")
else:
try:
indexer_fft3d = self._do_indexing(method="fft3d")
nref_3d, rmsd_3d = indexer_fft3d.get_nref_rmsds()
except Exception as e:
nref_3d = None
rmsd_3d = None
try:
indexer_fft1d = self._do_indexing(method="fft1d")
nref_1d, rmsd_1d = indexer_fft1d.get_nref_rmsds()
except Exception as e:
nref_1d = None
rmsd_1d = None
if (nref_1d is not None and nref_3d is None or
(nref_1d > nref_3d and rmsd_1d[0] < rmsd_3d[0]
and rmsd_1d[1] < rmsd_3d[1] and rmsd_1d[2] < rmsd_3d[2])):
indexer = indexer_fft1d
elif nref_3d is not None:
indexer = indexer_fft3d
else:
raise RuntimeError(e)
else:
indexer = self._do_indexing(
method=PhilIndex.params.dials.index.method)
# not strictly the P1 cell, rather the cell that was used in indexing
self._p1_cell = indexer._p1_cell
self.set_indexer_payload("indexed_filename",
indexer.get_indexed_filename())
from cctbx.sgtbx import bravais_types
from dxtbx.serialize import load
indexed_file = indexer.get_indexed_filename()
indexed_experiments = indexer.get_experiments_filename()
fast_mode = PhilIndex.params.dials.fast_mode
trust_beam_centre = PhilIndex.params.xia2.settings.trust_beam_centre
multi_sweep_indexing = PhilIndex.params.xia2.settings.multi_sweep_indexing == True
if not (trust_beam_centre or fast_mode or multi_sweep_indexing):
checksym = self.CheckIndexingSymmetry()
checksym.set_experiments_filename(indexed_experiments)
checksym.set_indexed_filename(indexed_file)
checksym.set_grid_search_scope(1)
checksym.run()
hkl_offset = checksym.get_hkl_offset()
Debug.write("hkl_offset: %s" % str(hkl_offset))
if hkl_offset is not None and hkl_offset != (0, 0, 0):
reindex = self.Reindex()
reindex.set_hkl_offset(hkl_offset)
reindex.set_indexed_filename(indexed_file)
reindex.run()
indexed_file = reindex.get_reindexed_reflections_filename()
# do some scan-static refinement - run twice, first without outlier
# rejection as the model is too far from reality to do a sensible job of
# outlier rejection
refiner = self.Refine()
refiner.set_experiments_filename(indexed_experiments)
refiner.set_indexed_filename(
reindex.get_reindexed_reflections_filename())
refiner.set_outlier_algorithm(None)
refiner.run()
indexed_experiments = refiner.get_refined_experiments_filename(
)
# now again with outlier rejection (possibly)
refiner = self.Refine()
refiner.set_experiments_filename(indexed_experiments)
refiner.set_indexed_filename(indexed_file)
refiner.run()
indexed_experiments = refiner.get_refined_experiments_filename(
)
if self._indxr_input_lattice is None:
# FIXME in here should respect the input unit cell and lattice if provided
# FIXME from this (i) populate the helper table,
# (ii) try to avoid re-running the indexing
# step if we eliminate a solution as we have all of the refined results
# already available.
rbs = self.RefineBravaisSettings()
rbs.set_experiments_filename(indexed_experiments)
rbs.set_indexed_filename(indexed_file)
if PhilIndex.params.dials.fix_geometry:
rbs.set_detector_fix('all')
rbs.set_beam_fix('all')
FileHandler.record_log_file(
'%s LATTICE' % self.get_indexer_full_name(),
rbs.get_log_file())
rbs.run()
from cctbx import crystal, sgtbx
for k in sorted(rbs.get_bravais_summary()):
summary = rbs.get_bravais_summary()[k]
# FIXME need to do this better - for the moment only accept lattices
# where R.M.S. deviation is less than twice P1 R.M.S. deviation.
if self._indxr_input_lattice is None:
if not summary['recommended']:
continue
experiments = load.experiment_list(summary['experiments_file'],
check_format=False)
cryst = experiments.crystals()[0]
cs = crystal.symmetry(unit_cell=cryst.get_unit_cell(),
space_group=cryst.get_space_group())
cb_op_best_to_ref = cs.change_of_basis_op_to_reference_setting(
)
cs_reference = cs.change_basis(cb_op_best_to_ref)
lattice = str(
bravais_types.bravais_lattice(
group=cs_reference.space_group()))
cb_op = cb_op_best_to_ref * sgtbx.change_of_basis_op(
str(summary['cb_op']))
self._solutions[k] = {
'number': k,
'mosaic': 0.0,
'metric': summary['max_angular_difference'],
'rmsd': summary['rmsd'],
'nspots': summary['nspots'],
'lattice': lattice,
'cell': cs_reference.unit_cell().parameters(),
'experiments_file': summary['experiments_file'],
'cb_op': str(cb_op)
}
self._solution = self.get_solution()
self._indxr_lattice = self._solution['lattice']
for solution in self._solutions.keys():
lattice = self._solutions[solution]['lattice']
if (self._indxr_input_lattice is not None
and self._indxr_input_lattice != lattice):
continue
if lattice in self._indxr_other_lattice_cell:
if self._indxr_other_lattice_cell[lattice]['metric'] < \
self._solutions[solution]['metric']:
continue
self._indxr_other_lattice_cell[lattice] = {
'metric': self._solutions[solution]['metric'],
'cell': self._solutions[solution]['cell']
}
self._indxr_mosaic = self._solution['mosaic']
experiment_list = load.experiment_list(
self._solution['experiments_file'])
self.set_indexer_experiment_list(experiment_list)
# reindex the output experiments list to the reference setting
# (from the best cell/conventional setting)
cb_op_to_ref = experiment_list.crystals()[0].get_space_group().info()\
.change_of_basis_op_to_reference_setting()
reindex = self.Reindex()
reindex.set_experiments_filename(
self._solution['experiments_file'])
reindex.set_cb_op(cb_op_to_ref)
reindex.set_space_group(
str(lattice_to_spacegroup_number(self._solution['lattice'])))
reindex.run()
experiments_file = reindex.get_reindexed_experiments_filename()
experiment_list = load.experiment_list(experiments_file)
self.set_indexer_experiment_list(experiment_list)
self.set_indexer_payload("experiments_filename", experiments_file)
# reindex the output reflection list to this solution
reindex = self.Reindex()
reindex.set_indexed_filename(indexed_file)
reindex.set_cb_op(self._solution['cb_op'])
reindex.set_space_group(
str(lattice_to_spacegroup_number(self._solution['lattice'])))
reindex.run()
indexed_file = reindex.get_reindexed_reflections_filename()
self.set_indexer_payload("indexed_filename", indexed_file)
else:
experiment_list = load.experiment_list(indexed_experiments)
self.set_indexer_experiment_list(experiment_list)
self.set_indexer_payload("experiments_filename",
indexed_experiments)
cryst = experiment_list.crystals()[0]
lattice = str(
bravais_types.bravais_lattice(group=cryst.get_space_group()))
self._indxr_lattice = lattice
self._solutions = {}
self._solutions[0] = {
'number': 0,
'mosaic': 0.0,
'metric': -1,
'rmsd': -1,
'nspots': -1,
'lattice': lattice,
'cell': cryst.get_unit_cell().parameters(),
'experiments_file': indexed_experiments,
'cb_op': 'a,b,c'
}
self._indxr_other_lattice_cell[lattice] = {
'metric': self._solutions[0]['metric'],
'cell': self._solutions[0]['cell']
}
return
def _scale_finish_chunk_6_add_free_r(self):
hklout = os.path.join(
self.get_working_directory(),
'%s_%s_free_temp.mtz' % (self._scalr_pname, self._scalr_xname))
FileHandler.record_temporary_file(hklout)
scale_params = PhilIndex.params.xia2.settings.scale
if self.get_scaler_freer_file():
# e.g. via .xinfo file
freein = self.get_scaler_freer_file()
Debug.write('Copying FreeR_flag from %s' % freein)
c = self._factory.Cad()
c.set_freein(freein)
c.add_hklin(self._scalr_scaled_reflection_files['mtz_merged'])
c.set_hklout(hklout)
c.copyfree()
elif scale_params.freer_file is not None:
# e.g. via -freer_file command line argument
freein = scale_params.freer_file
Debug.write('Copying FreeR_flag from %s' % freein)
c = self._factory.Cad()
c.set_freein(freein)
c.add_hklin(self._scalr_scaled_reflection_files['mtz_merged'])
c.set_hklout(hklout)
c.copyfree()
else:
if scale_params.free_total:
ntot = scale_params.free_total
# need to get a fraction, so...
nref = MtzUtils.nref_from_mtz(hklin)
free_fraction = float(ntot) / float(nref)
else:
free_fraction = scale_params.free_fraction
f = self._factory.Freerflag()
f.set_free_fraction(free_fraction)
f.set_hklin(self._scalr_scaled_reflection_files['mtz_merged'])
f.set_hklout(hklout)
f.add_free_flag()
# then check that this FreeR set is complete
hklin = hklout
hklout = os.path.join(
self.get_working_directory(),
'%s_%s_free.mtz' % (self._scalr_pname, self._scalr_xname))
# default fraction of 0.05
free_fraction = 0.05
if scale_params.free_fraction:
free_fraction = scale_params.free_fraction
elif scale_params.free_total:
ntot = scale_params.free_total()
# need to get a fraction, so...
nref = MtzUtils.nref_from_mtz(hklin)
free_fraction = float(ntot) / float(nref)
f = self._factory.Freerflag()
f.set_free_fraction(free_fraction)
f.set_hklin(hklin)
f.set_hklout(hklout)
f.complete_free_flag()
# remove 'mtz_merged' from the dictionary - this is made
# redundant by the merged free...
del self._scalr_scaled_reflection_files['mtz_merged']
# changed from mtz_merged_free to plain ol' mtz
self._scalr_scaled_reflection_files['mtz'] = hklout
# record this for future reference
FileHandler.record_data_file(hklout)
def _scale_prepare(self):
"""Perform all of the preparation required to deliver the scaled
data. This should sort together the reflection files, ensure that
they are correctly indexed (via pointless) and generally tidy
things up."""
# acknowledge all of the programs we are about to use...
Citations.cite("pointless")
Citations.cite("aimless")
Citations.cite("ccp4")
# ---------- GATHER ----------
self._sweep_handler = SweepInformationHandler(self._scalr_integraters)
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
pname, xname, dname = si.get_project_info()
sname = si.get_sweep_name()
exclude_sweep = False
for sweep in PhilIndex.params.xia2.settings.sweep:
if sweep.id == sname and sweep.exclude:
exclude_sweep = True
break
if exclude_sweep:
self._sweep_handler.remove_epoch(epoch)
logger.debug("Excluding sweep %s", sname)
else:
logger.debug("%-30s %s/%s/%s", "adding data from:", xname, dname, sname)
# gather data for all images which belonged to the parent
# crystal - allowing for the fact that things could go wrong
# e.g. epoch information not available, exposure times not in
# headers etc...
for e in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(e)
assert is_mtz_file(si.get_reflections()), repr(si.get_reflections())
p, x = self._sweep_handler.get_project_info()
self._scalr_pname = p
self._scalr_xname = x
# verify that the lattices are consistent, calling eliminate if
# they are not N.B. there could be corner cases here
need_to_return = False
multi_sweep_indexing = PhilIndex.params.xia2.settings.multi_sweep_indexing
# START OF if more than one epoch
if len(self._sweep_handler.get_epochs()) > 1:
# if we have multi-sweep-indexing going on then logic says all should
# share common lattice & UB definition => this is not used here?
# START OF if multi_sweep indexing and not input pg
if multi_sweep_indexing and not self._scalr_input_pointgroup:
pointless_hklins = []
max_batches = 0
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
hklin = si.get_reflections()
batches = MtzUtils.batches_from_mtz(hklin)
if 1 + max(batches) - min(batches) > max_batches:
max_batches = max(batches) - min(batches) + 1
logger.debug("Biggest sweep has %d batches", max_batches)
max_batches = nifty_power_of_ten(max_batches)
counter = 0
refiners = []
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
hklin = si.get_reflections()
integrater = si.get_integrater()
refiner = integrater.get_integrater_refiner()
refiners.append(refiner)
hklin = self._prepare_pointless_hklin(
hklin, si.get_integrater().get_phi_width()
)
hklout = os.path.join(
self.get_working_directory(),
"%s_%s_%s_%s_prepointless.mtz"
% (pname, xname, dname, si.get_sweep_name()),
)
# we will want to delete this one exit
FileHandler.record_temporary_file(hklout)
first_batch = min(si.get_batches())
si.set_batch_offset(counter * max_batches - first_batch + 1)
rebatch(
hklin,
hklout,
first_batch=counter * max_batches + 1,
pname=pname,
xname=xname,
dname=dname,
)
pointless_hklins.append(hklout)
# update the counter & recycle
counter += 1
# SUMMARY - have added all sweeps to pointless_hklins
s = self._factory.Sortmtz()
pointless_hklin = os.path.join(
self.get_working_directory(),
"%s_%s_prepointless_sorted.mtz"
% (self._scalr_pname, self._scalr_xname),
)
s.set_hklout(pointless_hklin)
for hklin in pointless_hklins:
s.add_hklin(hklin)
s.sort()
# FIXME xia2-51 in here look at running constant scaling on the
# pointless hklin to put the runs on the same scale. Ref=[A]
pointless_const = os.path.join(
self.get_working_directory(),
"%s_%s_prepointless_const.mtz"
% (self._scalr_pname, self._scalr_xname),
)
FileHandler.record_temporary_file(pointless_const)
aimless_const = self._factory.Aimless()
aimless_const.set_hklin(pointless_hklin)
aimless_const.set_hklout(pointless_const)
aimless_const.const()
pointless_const = os.path.join(
self.get_working_directory(),
"%s_%s_prepointless_const_unmerged.mtz"
% (self._scalr_pname, self._scalr_xname),
)
FileHandler.record_temporary_file(pointless_const)
pointless_hklin = pointless_const
# FIXME xia2-51 in here need to pass all refiners to ensure that the
# information is passed back to all of them not just the last one...
logger.debug(
"Running multisweep pointless for %d sweeps", len(refiners)
)
pointgroup, reindex_op, ntr, pt = self._pointless_indexer_multisweep(
pointless_hklin, refiners
)
logger.debug("X1698: %s: %s", pointgroup, reindex_op)
lattices = [Syminfo.get_lattice(pointgroup)]
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
intgr = si.get_integrater()
hklin = si.get_reflections()
refiner = intgr.get_integrater_refiner()
if ntr:
intgr.integrater_reset_reindex_operator()
need_to_return = True
# SUMMARY - added all sweeps together into an mtz, ran
# _pointless_indexer_multisweep on this, made a list of one lattice
# and potentially reset reindex op?
# END OF if multi_sweep indexing and not input pg
# START OF if not multi_sweep, or input pg given
else:
lattices = []
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
intgr = si.get_integrater()
hklin = si.get_reflections()
refiner = intgr.get_integrater_refiner()
if self._scalr_input_pointgroup:
pointgroup = self._scalr_input_pointgroup
reindex_op = "h,k,l"
ntr = False
else:
pointless_hklin = self._prepare_pointless_hklin(
hklin, si.get_integrater().get_phi_width()
)
pointgroup, reindex_op, ntr, pt = self._pointless_indexer_jiffy(
pointless_hklin, refiner
)
logger.debug("X1698: %s: %s", pointgroup, reindex_op)
lattice = Syminfo.get_lattice(pointgroup)
if lattice not in lattices:
lattices.append(lattice)
if ntr:
intgr.integrater_reset_reindex_operator()
need_to_return = True
# SUMMARY do pointless_indexer on each sweep, get lattices and make a list
# of unique lattices, potentially reset reindex op.
# END OF if not multi_sweep, or input pg given
# SUMMARY - still within if more than one epoch, now have a list of number
# of lattices
# START OF if multiple-lattices
if len(lattices) > 1:
# why not using pointless indexer jiffy??!
correct_lattice = sort_lattices(lattices)[0]
logger.info("Correct lattice asserted to be %s", correct_lattice)
# transfer this information back to the indexers
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
refiner = si.get_integrater().get_integrater_refiner()
sname = si.get_sweep_name()
state = refiner.set_refiner_asserted_lattice(correct_lattice)
if state == refiner.LATTICE_CORRECT:
logger.info(
"Lattice %s ok for sweep %s", correct_lattice, sname
)
elif state == refiner.LATTICE_IMPOSSIBLE:
raise RuntimeError(
f"Lattice {correct_lattice} impossible for {sname}"
)
elif state == refiner.LATTICE_POSSIBLE:
logger.info(
"Lattice %s assigned for sweep %s", correct_lattice, sname
)
need_to_return = True
# END OF if multiple-lattices
# SUMMARY - forced all lattices to be same and hope its okay.
# END OF if more than one epoch
# if one or more of them was not in the lowest lattice,
# need to return here to allow reprocessing
if need_to_return:
self.set_scaler_done(False)
self.set_scaler_prepare_done(False)
return
# ---------- REINDEX ALL DATA TO CORRECT POINTGROUP ----------
# all should share the same pointgroup, unless twinned... in which
# case force them to be...
pointgroups = {}
reindex_ops = {}
probably_twinned = False
need_to_return = False
multi_sweep_indexing = PhilIndex.params.xia2.settings.multi_sweep_indexing
# START OF if multi-sweep and not input pg
if multi_sweep_indexing and not self._scalr_input_pointgroup:
pointless_hklins = []
max_batches = 0
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
hklin = si.get_reflections()
batches = MtzUtils.batches_from_mtz(hklin)
if 1 + max(batches) - min(batches) > max_batches:
max_batches = max(batches) - min(batches) + 1
logger.debug("Biggest sweep has %d batches", max_batches)
max_batches = nifty_power_of_ten(max_batches)
counter = 0
refiners = []
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
hklin = si.get_reflections()
integrater = si.get_integrater()
refiner = integrater.get_integrater_refiner()
refiners.append(refiner)
hklin = self._prepare_pointless_hklin(
hklin, si.get_integrater().get_phi_width()
)
hklout = os.path.join(
self.get_working_directory(),
"%s_%s_%s_%s_prepointless.mtz"
% (pname, xname, dname, si.get_sweep_name()),
)
# we will want to delete this one exit
FileHandler.record_temporary_file(hklout)
first_batch = min(si.get_batches())
si.set_batch_offset(counter * max_batches - first_batch + 1)
rebatch(
hklin,
hklout,
first_batch=counter * max_batches + 1,
pname=pname,
xname=xname,
dname=dname,
)
pointless_hklins.append(hklout)
# update the counter & recycle
counter += 1
# FIXME related to xia2-51 - this looks very very similar to the logic
# in [A] above - is this duplicated logic?
s = self._factory.Sortmtz()
pointless_hklin = os.path.join(
self.get_working_directory(),
"%s_%s_prepointless_sorted.mtz"
% (self._scalr_pname, self._scalr_xname),
)
s.set_hklout(pointless_hklin)
for hklin in pointless_hklins:
s.add_hklin(hklin)
s.sort()
pointless_const = os.path.join(
self.get_working_directory(),
f"{self._scalr_pname}_{self._scalr_xname}_prepointless_const.mtz",
)
FileHandler.record_temporary_file(pointless_const)
aimless_const = self._factory.Aimless()
aimless_const.set_hklin(pointless_hklin)
aimless_const.set_hklout(pointless_const)
aimless_const.const()
pointless_const = os.path.join(
self.get_working_directory(),
"%s_%s_prepointless_const_unmerged.mtz"
% (self._scalr_pname, self._scalr_xname),
)
FileHandler.record_temporary_file(pointless_const)
pointless_hklin = pointless_const
pointgroup, reindex_op, ntr, pt = self._pointless_indexer_multisweep(
pointless_hklin, refiners
)
for epoch in self._sweep_handler.get_epochs():
pointgroups[epoch] = pointgroup
reindex_ops[epoch] = reindex_op
# SUMMARY ran pointless multisweep on combined mtz and made a dict
# of pointgroups and reindex_ops (all same)
# END OF if multi-sweep and not input pg
# START OF if not mulit-sweep or pg given
else:
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
hklin = si.get_reflections()
integrater = si.get_integrater()
refiner = integrater.get_integrater_refiner()
if self._scalr_input_pointgroup:
logger.debug(
"Using input pointgroup: %s", self._scalr_input_pointgroup
)
pointgroup = self._scalr_input_pointgroup
reindex_op = "h,k,l"
pt = False
else:
pointless_hklin = self._prepare_pointless_hklin(
hklin, si.get_integrater().get_phi_width()
)
pointgroup, reindex_op, ntr, pt = self._pointless_indexer_jiffy(
pointless_hklin, refiner
)
logger.debug("X1698: %s: %s", pointgroup, reindex_op)
if ntr:
integrater.integrater_reset_reindex_operator()
need_to_return = True
if pt and not probably_twinned:
probably_twinned = True
logger.debug("Pointgroup: %s (%s)", pointgroup, reindex_op)
pointgroups[epoch] = pointgroup
reindex_ops[epoch] = reindex_op
# SUMMARY - for each sweep, run indexer jiffy and get reindex operators
# and pointgroups dictionaries (could be different between sweeps)
# END OF if not mulit-sweep or pg given
overall_pointgroup = None
pointgroup_set = {pointgroups[e] for e in pointgroups}
if len(pointgroup_set) > 1 and not probably_twinned:
raise RuntimeError(
"non uniform pointgroups: %s" % str(list(pointgroup_set))
)
if len(pointgroup_set) > 1:
logger.debug(
"Probably twinned, pointgroups: %s",
" ".join(p.replace(" ", "") for p in pointgroup_set),
)
numbers = (Syminfo.spacegroup_name_to_number(ps) for ps in pointgroup_set)
overall_pointgroup = Syminfo.spacegroup_number_to_name(min(numbers))
self._scalr_input_pointgroup = overall_pointgroup
logger.info("Twinning detected, assume pointgroup %s", overall_pointgroup)
need_to_return = True
else:
overall_pointgroup = pointgroup_set.pop()
# SUMMARY - Have handled if different pointgroups & chosen an overall_pointgroup
# which is the lowest symmetry
# Now go through sweeps and do reindexing
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
integrater = si.get_integrater()
integrater.set_integrater_spacegroup_number(
Syminfo.spacegroup_name_to_number(overall_pointgroup)
)
integrater.set_integrater_reindex_operator(
reindex_ops[epoch], reason="setting point group"
)
# This will give us the reflections in the correct point group
si.set_reflections(integrater.get_integrater_intensities())
if need_to_return:
self.set_scaler_done(False)
self.set_scaler_prepare_done(False)
return
# in here now optionally work through the data files which should be
# indexed with a consistent point group, and transform the orientation
# matrices by the lattice symmetry operations (if possible) to get a
# consistent definition of U matrix modulo fixed rotations
if PhilIndex.params.xia2.settings.unify_setting:
self.unify_setting()
if self.get_scaler_reference_reflection_file():
self._reference = self.get_scaler_reference_reflection_file()
logger.debug("Using HKLREF %s", self._reference)
elif PhilIndex.params.xia2.settings.scale.reference_reflection_file:
self._reference = (
PhilIndex.params.xia2.settings.scale.reference_reflection_file
)
logger.debug("Using HKLREF %s", self._reference)
params = PhilIndex.params
use_brehm_diederichs = params.xia2.settings.use_brehm_diederichs
if len(self._sweep_handler.get_epochs()) > 1 and use_brehm_diederichs:
self.brehm_diederichs_reindexing()
# If not Brehm-deidrichs, set reference as first sweep
elif len(self._sweep_handler.get_epochs()) > 1 and not self._reference:
first = self._sweep_handler.get_epochs()[0]
si = self._sweep_handler.get_sweep_information(first)
self._reference = si.get_reflections()
# Now reindex to be consistent with first dataset - run pointless on each
# dataset with reference
if self._reference:
md = self._factory.Mtzdump()
md.set_hklin(self._reference)
md.dump()
datasets = md.get_datasets()
# then get the unit cell, lattice etc.
reference_lattice = Syminfo.get_lattice(md.get_spacegroup())
reference_cell = md.get_dataset_info(datasets[0])["cell"]
# then compute the pointgroup from this...
# ---------- REINDEX TO CORRECT (REFERENCE) SETTING ----------
for epoch in self._sweep_handler.get_epochs():
# if we are working with unified UB matrix then this should not
# be a problem here (note, *if*; *should*)
# what about e.g. alternative P1 settings?
# see JIRA MXSW-904
if PhilIndex.params.xia2.settings.unify_setting:
continue
pl = self._factory.Pointless()
si = self._sweep_handler.get_sweep_information(epoch)
hklin = si.get_reflections()
pl.set_hklin(
self._prepare_pointless_hklin(
hklin, si.get_integrater().get_phi_width()
)
)
hklout = os.path.join(
self.get_working_directory(),
"%s_rdx2.mtz" % os.path.split(hklin)[-1][:-4],
)
# we will want to delete this one exit
FileHandler.record_temporary_file(hklout)
# now set the initial reflection set as a reference...
pl.set_hklref(self._reference)
# https://github.com/xia2/xia2/issues/115 - should ideally iteratively
# construct a reference or a tree of correlations to ensure correct
# reference setting - however if small molecule assume has been
# multi-sweep-indexed so can ignore "fatal errors" - temporary hack
pl.decide_pointgroup(
ignore_errors=PhilIndex.params.xia2.settings.small_molecule
)
logger.debug("Reindexing analysis of %s", pl.get_hklin())
pointgroup = pl.get_pointgroup()
reindex_op = pl.get_reindex_operator()
logger.debug("Operator: %s", reindex_op)
# apply this...
integrater = si.get_integrater()
integrater.set_integrater_reindex_operator(
reindex_op, reason="match reference"
)
integrater.set_integrater_spacegroup_number(
Syminfo.spacegroup_name_to_number(pointgroup)
)
si.set_reflections(integrater.get_integrater_intensities())
md = self._factory.Mtzdump()
md.set_hklin(si.get_reflections())
md.dump()
datasets = md.get_datasets()
if len(datasets) > 1:
raise RuntimeError(
"more than one dataset in %s" % si.get_reflections()
)
# then get the unit cell, lattice etc.
lattice = Syminfo.get_lattice(md.get_spacegroup())
cell = md.get_dataset_info(datasets[0])["cell"]
if lattice != reference_lattice:
raise RuntimeError(
"lattices differ in %s and %s"
% (self._reference, si.get_reflections())
)
logger.debug("Cell: %.2f %.2f %.2f %.2f %.2f %.2f" % cell)
logger.debug("Ref: %.2f %.2f %.2f %.2f %.2f %.2f" % reference_cell)
for j in range(6):
if (
math.fabs((cell[j] - reference_cell[j]) / reference_cell[j])
> 0.1
):
raise RuntimeError(
"unit cell parameters differ in %s and %s"
% (self._reference, si.get_reflections())
)
# ---------- SORT TOGETHER DATA ----------
self._sort_together_data_ccp4()
self._scalr_resolution_limits = {}
# store central resolution limit estimates
batch_ranges = [
self._sweep_handler.get_sweep_information(epoch).get_batch_range()
for epoch in self._sweep_handler.get_epochs()
]
self._resolution_limit_estimates = ersatz_resolution(
self._prepared_reflections, batch_ranges
)
def _sort_together_data_xds(self):
if len(self._sweep_information) == 1:
return self._sort_together_data_xds_one_sweep()
max_batches = 0
for epoch in self._sweep_information.keys():
hklin = self._sweep_information[epoch]['scaled_reflections']
md = self._factory.Mtzdump()
md.set_hklin(hklin)
md.dump()
if self._sweep_information[epoch]['batches'] == [0, 0]:
Chatter.write('Getting batches from %s' % hklin)
batches = md.get_batches()
self._sweep_information[epoch]['batches'] = [min(batches),
max(batches)]
Chatter.write('=> %d to %d' % (min(batches),
max(batches)))
batches = self._sweep_information[epoch]['batches']
if 1 + max(batches) - min(batches) > max_batches:
max_batches = max(batches) - min(batches) + 1
datasets = md.get_datasets()
Debug.write('In reflection file %s found:' % hklin)
for d in datasets:
Debug.write('... %s' % d)
dataset_info = md.get_dataset_info(datasets[0])
Debug.write('Biggest sweep has %d batches' % max_batches)
max_batches = nifty_power_of_ten(max_batches)
epochs = self._sweep_information.keys()
epochs.sort()
counter = 0
for epoch in epochs:
rb = self._factory.Rebatch()
hklin = self._sweep_information[epoch]['scaled_reflections']
pname = self._sweep_information[epoch]['pname']
xname = self._sweep_information[epoch]['xname']
dname = self._sweep_information[epoch]['dname']
sname = self._sweep_information[epoch]['sname']
hklout = os.path.join(self.get_working_directory(),
'%s_%s_%s_%d.mtz' % \
(pname, xname, dname, counter))
# we will want to delete this one exit
FileHandler.record_temporary_file(hklout)
# record this for future reference - will be needed in the
# radiation damage analysis...
# hack - reset this as it gets in a muddle...
intgr = self._sweep_information[epoch]['integrater']
self._sweep_information[epoch][
'batches'] = intgr.get_integrater_batches()
first_batch = min(self._sweep_information[epoch]['batches'])
self._sweep_information[epoch][
'batch_offset'] = counter * max_batches - first_batch + 1
rb.set_hklin(hklin)
rb.set_first_batch(counter * max_batches + 1)
rb.set_hklout(hklout)
new_batches = rb.rebatch()
# update the "input information"
self._sweep_information[epoch]['hklin'] = hklout
self._sweep_information[epoch]['batches'] = new_batches
# update the counter & recycle
counter += 1
if Flags.get_chef():
self._sweep_information_to_chef()
s = self._factory.Sortmtz()
hklout = os.path.join(self.get_working_directory(),
'%s_%s_sorted.mtz' % \
(self._scalr_pname, self._scalr_xname))
s.set_hklout(hklout)
for epoch in epochs:
s.add_hklin(self._sweep_information[epoch]['hklin'])
s.sort(vrset = -99999999.0)
self._prepared_reflections = hklout
if self.get_scaler_reference_reflection_file():
md = self._factory.Mtzdump()
md.set_hklin(self.get_scaler_reference_reflection_file())
md.dump()
spacegroups = [md.get_spacegroup()]
reindex_operator = 'h,k,l'
else:
pointless = self._factory.Pointless()
pointless.set_hklin(hklout)
pointless.decide_spacegroup()
FileHandler.record_log_file('%s %s pointless' % \
(self._scalr_pname,
self._scalr_xname),
pointless.get_log_file())
spacegroups = pointless.get_likely_spacegroups()
reindex_operator = pointless.get_spacegroup_reindex_operator()
if self._scalr_input_spacegroup:
Debug.write('Assigning user input spacegroup: %s' % \
self._scalr_input_spacegroup)
spacegroups = [self._scalr_input_spacegroup]
reindex_operator = 'h,k,l'
self._scalr_likely_spacegroups = spacegroups
spacegroup = self._scalr_likely_spacegroups[0]
self._scalr_reindex_operator = reindex_operator
Chatter.write('Likely spacegroups:')
for spag in self._scalr_likely_spacegroups:
Chatter.write('%s' % spag)
Chatter.write(
'Reindexing to first spacegroup setting: %s (%s)' % \
(spacegroup, clean_reindex_operator(reindex_operator)))
hklin = self._prepared_reflections
hklout = os.path.join(self.get_working_directory(),
'%s_%s_reindex.mtz' % \
(self._scalr_pname, self._scalr_xname))
FileHandler.record_temporary_file(hklout)
ri = self._factory.Reindex()
ri.set_hklin(hklin)
ri.set_hklout(hklout)
ri.set_spacegroup(spacegroup)
ri.set_operator(reindex_operator)
ri.reindex()
hklin = hklout
hklout = os.path.join(self.get_working_directory(),
'%s_%s_sorted.mtz' % \
(self._scalr_pname, self._scalr_xname))
s = self._factory.Sortmtz()
s.set_hklin(hklin)
s.set_hklout(hklout)
s.sort(vrset = -99999999.0)
self._prepared_reflections = hklout
Debug.write(
'Updating unit cell to %.2f %.2f %.2f %.2f %.2f %.2f' % \
tuple(ri.get_cell()))
self._scalr_cell = tuple(ri.get_cell())
return
def _refine(self):
for epoch, idxr in self._refinr_indexers.iteritems():
experiments = idxr.get_indexer_experiment_list()
indexed_experiments = idxr.get_indexer_payload(
"experiments_filename")
indexed_reflections = idxr.get_indexer_payload("indexed_filename")
if len(experiments) > 1:
xsweeps = idxr._indxr_sweeps
assert len(xsweeps) == len(experiments)
assert len(self._refinr_sweeps
) == 1 # don't currently support joint refinement
xsweep = self._refinr_sweeps[0]
i = xsweeps.index(xsweep)
experiments = experiments[i:i + 1]
# Extract and output experiment and reflections for current sweep
indexed_experiments = os.path.join(
self.get_working_directory(),
"%s_indexed_experiments.json" % xsweep.get_name())
indexed_reflections = os.path.join(
self.get_working_directory(),
"%s_indexed_reflections.pickle" % xsweep.get_name())
from dxtbx.serialize import dump
dump.experiment_list(experiments, indexed_experiments)
from libtbx import easy_pickle
from scitbx.array_family import flex
reflections = easy_pickle.load(
idxr.get_indexer_payload("indexed_filename"))
sel = reflections['id'] == i
assert sel.count(True) > 0
imageset_id = reflections['imageset_id'].select(sel)
assert imageset_id.all_eq(imageset_id[0])
sel = reflections['imageset_id'] == imageset_id[0]
reflections = reflections.select(sel)
# set indexed reflections to id == 0 and imageset_id == 0
reflections['id'].set_selected(reflections['id'] == i, 0)
reflections['imageset_id'] = flex.int(len(reflections), 0)
easy_pickle.dump(indexed_reflections, reflections)
assert len(experiments.crystals()
) == 1 # currently only handle one lattice/sweep
crystal_model = experiments.crystals()[0]
lattice = idxr.get_indexer_lattice()
from dxtbx.serialize import load
scan_static = PhilIndex.params.dials.refine.scan_static
# XXX Temporary workaround for dials.refine error for scan_varying
# refinement with smaller wedges
start, end = experiments[0].scan.get_oscillation_range()
total_phi_range = end - start
if (PhilIndex.params.dials.refine.scan_varying
and total_phi_range > 5
and not PhilIndex.params.dials.fast_mode):
scan_varying = PhilIndex.params.dials.refine.scan_varying
else:
scan_varying = False
if scan_static:
refiner = self.Refine()
refiner.set_experiments_filename(indexed_experiments)
refiner.set_indexed_filename(indexed_reflections)
refiner.set_scan_varying(False)
refiner.run()
self._refinr_experiments_filename \
= refiner.get_refined_experiments_filename()
self._refinr_indexed_filename = refiner.get_refined_filename()
else:
self._refinr_experiments_filename = indexed_experiments
self._refinr_indexed_filename = indexed_reflections
if scan_varying:
refiner = self.Refine()
refiner.set_experiments_filename(
self._refinr_experiments_filename)
refiner.set_indexed_filename(self._refinr_indexed_filename)
if total_phi_range < 36:
refiner.set_interval_width_degrees(total_phi_range / 2)
refiner.run()
self._refinr_experiments_filename \
= refiner.get_refined_experiments_filename()
self._refinr_indexed_filename = refiner.get_refined_filename()
if scan_static or scan_varying:
FileHandler.record_log_file(
'%s REFINE' % idxr.get_indexer_full_name(),
refiner.get_log_file())
report = self.Report()
report.set_experiments_filename(
self._refinr_experiments_filename)
report.set_reflections_filename(self._refinr_indexed_filename)
html_filename = os.path.join(
self.get_working_directory(),
'%i_dials.refine.report.html' % report.get_xpid())
report.set_html_filename(html_filename)
report.run()
FileHandler.record_html_file(
'%s REFINE' % idxr.get_indexer_full_name(), html_filename)
experiments = load.experiment_list(
self._refinr_experiments_filename)
self.set_refiner_payload("experiments.json",
self._refinr_experiments_filename)
self.set_refiner_payload("reflections.pickle",
self._refinr_indexed_filename)
# this is the result of the cell refinement
self._refinr_cell = experiments.crystals()[0].get_unit_cell(
).parameters()
def _integrate(self):
'''Implement the integrater interface.'''
# cite the program
Citations.cite('mosflm')
images_str = '%d to %d' % tuple(self._intgr_wedge)
cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % tuple(self._intgr_cell)
if len(self._fp_directory) <= 50:
dirname = self._fp_directory
else:
dirname = '...%s' % self._fp_directory[-46:]
Journal.block(
'integrating', self._intgr_sweep_name, 'mosflm', {
'images': images_str,
'cell': cell_str,
'lattice': self.get_integrater_refiner().get_refiner_lattice(),
'template': self._fp_template,
'directory': dirname,
'resolution': '%.2f' % self._intgr_reso_high
})
self._mosflm_rerun_integration = False
wd = self.get_working_directory()
try:
if self.get_integrater_sweep_name():
pname, xname, dname = self.get_integrater_project_info()
nproc = PhilIndex.params.xia2.settings.multiprocessing.nproc
if nproc > 1:
Debug.write('Parallel integration: %d jobs' % nproc)
self._mosflm_hklout = self._mosflm_parallel_integrate()
else:
self._mosflm_hklout = self._mosflm_integrate()
# record integration output for e.g. BLEND.
sweep = self.get_integrater_sweep_name()
if sweep:
FileHandler.record_more_data_file(
'%s %s %s %s INTEGRATE' % (pname, xname, dname, sweep),
self._mosflm_hklout)
except IntegrationError as e:
if 'negative mosaic spread' in str(e):
if self._mosflm_postref_fix_mosaic:
Chatter.write(
'Negative mosaic spread - stopping integration')
raise BadLatticeError('negative mosaic spread')
Chatter.write('Negative mosaic spread - rerunning integration')
self.set_integrater_done(False)
self._mosflm_postref_fix_mosaic = True
if self._mosflm_rerun_integration and not PhilIndex.params.dials.fast_mode:
# make sure that this is run again...
Chatter.write('Need to rerun the integration...')
self.set_integrater_done(False)
return self._mosflm_hklout
def _index(self):
"""Actually do the autoindexing using the data prepared by the
previous method."""
self._index_remove_masked_regions()
if self._i_or_ii is None:
self._i_or_ii = self.decide_i_or_ii()
logger.debug("Selecting I or II, chose %s", self._i_or_ii)
idxref = self.Idxref()
for file in ["SPOT.XDS"]:
idxref.set_input_data_file(file, self._indxr_payload[file])
# set the phi start etc correctly
idxref.set_data_range(self._indxr_images[0][0],
self._indxr_images[0][1])
idxref.set_background_range(self._indxr_images[0][0],
self._indxr_images[0][1])
if self._i_or_ii == "i":
blocks = self._index_select_images_i()
for block in blocks[:1]:
starting_frame = block[0]
starting_angle = self.get_scan().get_angle_from_image_index(
starting_frame)
idxref.set_starting_frame(starting_frame)
idxref.set_starting_angle(starting_angle)
idxref.add_spot_range(block[0], block[1])
for block in blocks[1:]:
idxref.add_spot_range(block[0], block[1])
else:
for block in self._indxr_images[:1]:
starting_frame = block[0]
starting_angle = self.get_scan().get_angle_from_image_index(
starting_frame)
idxref.set_starting_frame(starting_frame)
idxref.set_starting_angle(starting_angle)
idxref.add_spot_range(block[0], block[1])
for block in self._indxr_images[1:]:
idxref.add_spot_range(block[0], block[1])
# FIXME need to also be able to pass in the known unit
# cell and lattice if already available e.g. from
# the helper... indirectly
if self._indxr_user_input_lattice:
idxref.set_indexer_user_input_lattice(True)
if self._indxr_input_lattice and self._indxr_input_cell:
idxref.set_indexer_input_lattice(self._indxr_input_lattice)
idxref.set_indexer_input_cell(self._indxr_input_cell)
logger.debug("Set lattice: %s", self._indxr_input_lattice)
logger.debug("Set cell: %f %f %f %f %f %f" %
self._indxr_input_cell)
original_cell = self._indxr_input_cell
elif self._indxr_input_lattice:
idxref.set_indexer_input_lattice(self._indxr_input_lattice)
original_cell = None
else:
original_cell = None
# FIXED need to set the beam centre here - this needs to come
# from the input .xinfo object or header, and be converted
# to the XDS frame... done.
from dxtbx.serialize.xds import to_xds
converter = to_xds(self.get_imageset())
xds_beam_centre = converter.detector_origin
idxref.set_beam_centre(xds_beam_centre[0], xds_beam_centre[1])
# fixme need to check if the lattice, cell have been set already,
# and if they have, pass these in as input to the indexing job.
done = False
while not done:
try:
done = idxref.run()
# N.B. in here if the IDXREF step was being run in the first
# pass done is FALSE however there should be a refined
# P1 orientation matrix etc. available - so keep it!
except XDSException as e:
# inspect this - if we have complaints about not
# enough reflections indexed, and we have a target
# unit cell, and they are the same, well ignore it
if "solution is inaccurate" in str(e):
logger.debug(
"XDS complains solution inaccurate - ignoring")
done = idxref.continue_from_error()
elif ("insufficient percentage (< 70%)" in str(e)
or "insufficient percentage (< 50%)"
in str(e)) and original_cell:
done = idxref.continue_from_error()
lattice, cell, mosaic = idxref.get_indexing_solution()
# compare solutions
check = PhilIndex.params.xia2.settings.xds_check_cell_deviation
for j in range(3):
# allow two percent variation in unit cell length
if (math.fabs(
(cell[j] - original_cell[j]) / original_cell[j]) >
0.02 and check):
logger.debug("XDS unhappy and solution wrong")
raise e
# and two degree difference in angle
if (math.fabs(cell[j + 3] - original_cell[j + 3]) > 2.0
and check):
logger.debug("XDS unhappy and solution wrong")
raise e
logger.debug("XDS unhappy but solution ok")
elif "insufficient percentage (< 70%)" in str(
e) or "insufficient percentage (< 50%)" in str(e):
logger.debug("XDS unhappy but solution probably ok")
done = idxref.continue_from_error()
else:
raise e
FileHandler.record_log_file(
"%s INDEX" % self.get_indexer_full_name(),
os.path.join(self.get_working_directory(), "IDXREF.LP"),
)
for file in ["SPOT.XDS", "XPARM.XDS"]:
self._indxr_payload[file] = idxref.get_output_data_file(file)
# need to get the indexing solutions out somehow...
self._indxr_other_lattice_cell = idxref.get_indexing_solutions()
(
self._indxr_lattice,
self._indxr_cell,
self._indxr_mosaic,
) = idxref.get_indexing_solution()
xparm_file = os.path.join(self.get_working_directory(), "XPARM.XDS")
models = dxtbx.load(xparm_file)
crystal_model = to_crystal(xparm_file)
# this information gets lost when re-creating the models from the
# XDS results - however is not refined so can simply copy from the
# input - https://github.com/xia2/xia2/issues/372
models.get_detector()[0].set_thickness(
converter.get_detector()[0].get_thickness())
experiment = Experiment(
beam=models.get_beam(),
detector=models.get_detector(),
goniometer=models.get_goniometer(),
scan=models.get_scan(),
crystal=crystal_model,
# imageset=self.get_imageset(),
)
experiment_list = ExperimentList([experiment])
self.set_indexer_experiment_list(experiment_list)
# I will want this later on to check that the lattice was ok
self._idxref_subtree_problem = idxref.get_index_tree_problem()
def _mosflm_integrate(self):
'''Perform the actual integration, based on the results of the
cell refinement or indexing (they have the equivalent form.)'''
refinr = self.get_integrater_refiner()
if not refinr.get_refiner_payload('mosflm_orientation_matrix'):
raise RuntimeError('unexpected situation in indexing')
lattice = refinr.get_refiner_lattice()
spacegroup_number = lattice_to_spacegroup(lattice)
mosaic = refinr.get_refiner_payload('mosaic')
beam = refinr.get_refiner_payload('beam')
distance = refinr.get_refiner_payload('distance')
matrix = refinr.get_refiner_payload('mosflm_orientation_matrix')
integration_params = refinr.get_refiner_payload(
'mosflm_integration_parameters')
if integration_params:
if 'separation' in integration_params:
self.set_integrater_parameter(
'mosflm', 'separation',
'%s %s' % tuple(integration_params['separation']))
if 'raster' in integration_params:
self.set_integrater_parameter(
'mosflm', 'raster',
'%d %d %d %d %d' % tuple(integration_params['raster']))
refinr.set_refiner_payload('mosflm_integration_parameters', None)
f = open(
os.path.join(self.get_working_directory(), 'xiaintegrate.mat'),
'w')
for m in matrix:
f.write(m)
f.close()
# then start the integration
integrater = MosflmIntegrate()
integrater.set_working_directory(self.get_working_directory())
auto_logfiler(integrater)
integrater.set_refine_profiles(self._mosflm_refine_profiles)
pname, xname, dname = self.get_integrater_project_info()
if pname is not None and xname is not None and dname is not None:
Debug.write('Harvesting: %s/%s/%s' % (pname, xname, dname))
harvest_dir = self.get_working_directory()
# harvest file name will be %s.mosflm_run_start_end % dname
temp_dname = '%s_%s' % \
(dname, self.get_integrater_sweep_name())
integrater.set_pname_xname_dname(pname, xname, temp_dname)
integrater.set_template(os.path.basename(self.get_template()))
integrater.set_directory(self.get_directory())
# check for ice - and if so, exclude (ranges taken from
# XDS documentation)
if self.get_integrater_ice() != 0:
Debug.write('Excluding ice rings')
integrater.set_exclude_ice(True)
# exclude specified resolution ranges
if len(self.get_integrater_excluded_regions()) != 0:
regions = self.get_integrater_excluded_regions()
Debug.write('Excluding regions: %s' % repr(regions))
integrater.set_exclude_regions(regions)
mask = standard_mask(self.get_detector())
for m in mask:
integrater.add_instruction(m)
integrater.set_input_mat_file('xiaintegrate.mat')
integrater.set_beam_centre(beam)
integrater.set_distance(distance)
integrater.set_space_group_number(spacegroup_number)
integrater.set_mosaic(mosaic)
if self.get_wavelength_prov() == 'user':
integrater.set_wavelength(self.get_wavelength())
parameters = self.get_integrater_parameters('mosflm')
integrater.update_parameters(parameters)
if self._mosflm_gain:
integrater.set_gain(self._mosflm_gain)
# check for resolution limits
if self._intgr_reso_high > 0.0:
integrater.set_d_min(self._intgr_reso_high)
if self._intgr_reso_low:
integrater.set_d_max(self._intgr_reso_low)
if PhilIndex.params.general.backstop_mask:
from xia2.Toolkit.BackstopMask import BackstopMask
mask = BackstopMask(PhilIndex.params.general.backstop_mask)
mask = mask.calculate_mask_mosflm(self.get_header())
integrater.set_mask(mask)
detector = self.get_detector()
detector_width, detector_height = detector[0].get_image_size_mm()
lim_x = 0.5 * detector_width
lim_y = 0.5 * detector_height
Debug.write('Scanner limits: %.1f %.1f' % (lim_x, lim_y))
integrater.set_limits(lim_x, lim_y)
integrater.set_fix_mosaic(self._mosflm_postref_fix_mosaic)
offset = self.get_frame_offset()
integrater.set_image_range(
(self._intgr_wedge[0] - offset, self._intgr_wedge[1] - offset))
try:
integrater.run()
except RuntimeError as e:
if 'integration failed: reason unknown' in str(e):
Chatter.write('Mosflm has failed in integration')
message = 'The input was:\n\n'
for input in integrater.get_all_input():
message += ' %s' % input
Chatter.write(message)
raise
FileHandler.record_log_file(
'%s %s %s %s mosflm integrate' % \
(self.get_integrater_sweep_name(),
pname, xname, dname),
integrater.get_log_file())
self._intgr_per_image_statistics = integrater.get_per_image_statistics(
)
self._mosflm_hklout = integrater.get_hklout()
Debug.write('Integration output: %s' % self._mosflm_hklout)
self._intgr_n_ref = integrater.get_nref()
# if a BGSIG error happened try not refining the
# profile and running again...
if integrater.get_bgsig_too_large():
if not self._mosflm_refine_profiles:
raise RuntimeError('BGSIG error with profiles fixed')
Debug.write('BGSIG error detected - try fixing profile...')
self._mosflm_refine_profiles = False
self.set_integrater_done(False)
return
if integrater.get_getprof_error():
Debug.write('GETPROF error detected - try fixing profile...')
self._mosflm_refine_profiles = False
self.set_integrater_done(False)
return
if (integrater.get_detector_gain_error()
and not (self.get_imageset().get_detector()[0].get_type()
== 'SENSOR_PAD')):
gain = integrater.get_suggested_gain()
if gain is not None:
self.set_integrater_parameter('mosflm', 'gain', gain)
self.set_integrater_export_parameter('mosflm', 'gain', gain)
if self._mosflm_gain:
Debug.write('GAIN updated to %f' % gain)
else:
Debug.write('GAIN found to be %f' % gain)
self._mosflm_gain = gain
self._mosflm_rerun_integration = True
if not self._mosflm_hklout:
raise RuntimeError('processing abandoned')
self._intgr_batches_out = integrater.get_batches_out()
mosaics = integrater.get_mosaic_spreads()
if mosaics and len(mosaics) > 0:
self.set_integrater_mosaic_min_mean_max(
min(mosaics),
sum(mosaics) / len(mosaics), max(mosaics))
else:
m = indxr.get_indexer_mosaic()
self.set_integrater_mosaic_min_mean_max(m, m, m)
# write the report for each image as .*-#$ to Chatter -
# detailed report will be written automagically to science...
Chatter.write(self.show_per_image_statistics())
Chatter.write('Mosaic spread: %.3f < %.3f < %.3f' % \
self.get_integrater_mosaic_min_mean_max())
# gather the statistics from the postrefinement
postref_result = integrater.get_postref_result()
# now write this to a postrefinement log
postref_log = os.path.join(self.get_working_directory(),
'postrefinement.log')
fout = open(postref_log, 'w')
fout.write('$TABLE: Postrefinement for %s:\n' % \
self._intgr_sweep_name)
fout.write('$GRAPHS: Missetting angles:A:1, 2, 3, 4: $$\n')
fout.write('Batch PhiX PhiY PhiZ $$ Batch PhiX PhiY PhiZ $$\n')
for image in sorted(postref_result):
phix = postref_result[image].get('phix', 0.0)
phiy = postref_result[image].get('phiy', 0.0)
phiz = postref_result[image].get('phiz', 0.0)
fout.write('%d %5.2f %5.2f %5.2f\n' % \
(image, phix, phiy, phiz))
fout.write('$$\n')
fout.close()
if self.get_integrater_sweep_name():
pname, xname, dname = self.get_integrater_project_info()
FileHandler.record_log_file('%s %s %s %s postrefinement' % \
(self.get_integrater_sweep_name(),
pname, xname, dname),
postref_log)
return self._mosflm_hklout
def json_object(self, command_line=''):
result = {}
for crystal in sorted(self._crystals):
xcrystal = self._crystals[crystal]
cell = xcrystal.get_cell()
spacegroup = xcrystal.get_likely_spacegroups()[0]
result['AutoProc'] = {}
tmp = result['AutoProc']
tmp['spaceGroup'] = spacegroup
for name, value in zip(['a', 'b', 'c', 'alpha', 'beta', 'gamma'], cell):
tmp['refinedCell_%s' % name] = value
result['AutoProcScalingContainer'] = {}
tmp = result['AutoProcScalingContainer']
tmp['AutoProcScaling'] = {
'recordTimeStamp': time.strftime('%Y-%m-%d %H:%M:%S',
time.localtime())
}
statistics_all = xcrystal.get_statistics()
reflection_files = xcrystal.get_scaled_merged_reflections()
wavelength_names = xcrystal.get_wavelength_names()
for key in statistics_all.keys():
pname, xname, dname = key
# FIXME should assert that the dname is a
# valid wavelength name
available = statistics_all[key].keys()
stats = []
keys = [
'High resolution limit',
'Low resolution limit',
'Completeness',
'Multiplicity',
'I/sigma',
'Rmerge(I+/-)',
'CC half',
'Anomalous completeness',
'Anomalous correlation',
'Anomalous multiplicity',
'Total observations',
'Total unique',
'Rmeas(I)',
'Rmeas(I+/-)',
'Rpim(I)',
'Rpim(I+/-)',
'Partial Bias'
]
for k in keys:
if k in available:
stats.append(k)
xwavelength = xcrystal.get_xwavelength(dname)
sweeps = xwavelength.get_sweeps()
tmp['AutoProcScalingStatistics'] = []
tmp2 = tmp['AutoProcScalingStatistics']
for j, name in enumerate(
['overall', 'innerShell', 'outerShell']):
statistics_cache = {'scalingStatisticsType':name}
for s in stats:
if s in self._name_map:
n = self._name_map[s]
else:
continue
if isinstance(statistics_all[key][s], type([])):
statistics_cache[n] = statistics_all[key][s][j]
elif isinstance(statistics_all[key][s], type(())):
statistics_cache[n] = statistics_all[key][s][j]
tmp2.append(statistics_cache)
tmp['AutoProcIntegrationContainer'] = []
tmp2 = tmp['AutoProcIntegrationContainer']
for sweep in sweeps:
if '#' in sweep.get_template():
image_name = sweep.get_image_name(0)
else:
image_name = os.path.join(sweep.get_directory(),
sweep.get_template())
cell = sweep.get_integrater_cell()
intgr_tmp = {}
for name, value in zip(['a', 'b', 'c', 'alpha', 'beta', 'gamma'],
cell):
intgr_tmp['cell_%s' % name] = value
# FIXME this is naughty
indxr = sweep._get_indexer()
intgr = sweep._get_integrater()
start, end = intgr.get_integrater_wedge()
intgr_tmp['startImageNumber'] = start
intgr_tmp['endImageNumber'] = end
intgr_tmp['refinedDetectorDistance'] = indxr.get_indexer_distance()
beam = indxr.get_indexer_beam_centre()
intgr_tmp['refinedXBeam'] = beam[0]
intgr_tmp['refinedYBeam'] = beam[1]
tmp2.append(
{'Image':{'fileName':os.path.split(image_name)[-1],
'fileLocation':sanitize(os.path.split(image_name)[0])},
'AutoProcIntegration': intgr_tmp})
# file unpacking nonsense
result['AutoProcProgramContainer'] = {}
tmp = result['AutoProcProgramContainer']
tmp2 = {}
if not command_line:
from xia2.Handlers.CommandLine import CommandLine
command_line = CommandLine.get_command_line()
tmp2['processingCommandLine'] = sanitize(command_line)
tmp2['processingProgram'] = 'xia2'
tmp['AutoProcProgram'] = tmp2
tmp['AutoProcProgramAttachment'] = []
tmp2 = tmp['AutoProcProgramAttachment']
from xia2.Handlers.Environment import Environment
data_directory = Environment.generate_directory('DataFiles')
for k in reflection_files:
reflection_file = reflection_files[k]
if not isinstance(reflection_file, type('')):
continue
reflection_file = FileHandler.get_data_file(reflection_file)
basename = os.path.basename(reflection_file)
if os.path.isfile(os.path.join(data_directory, basename)):
# Use file in DataFiles directory in preference (if it exists)
reflection_file = os.path.join(data_directory, basename)
tmp2.append({
'fileType': 'Result',
'fileName': os.path.split(reflection_file)[-1],
'filePath': sanitize(os.path.split(reflection_file)[0]),
})
tmp2.append({'fileType':'Log',
'fileName':'xia2.txt',
'filePath':sanitize(os.getcwd())})
return result
def write_xml(self, file):
fout = open(file, 'w')
fout.write('<?xml version="1.0"?>')
fout.write('<AutoProcContainer>\n')
for crystal in sorted(self._crystals):
xcrystal = self._crystals[crystal]
cell = xcrystal.get_cell()
spacegroup = xcrystal.get_likely_spacegroups()[0]
fout.write('<AutoProc><spaceGroup>%s</spaceGroup>' % spacegroup)
self.write_refined_cell(fout, cell)
fout.write('</AutoProc>')
fout.write('<AutoProcScalingContainer>')
fout.write('<AutoProcScaling>')
self.write_date(fout)
fout.write('</AutoProcScaling>')
statistics_all = xcrystal.get_statistics()
reflection_files = xcrystal.get_scaled_merged_reflections()
wavelength_names = xcrystal.get_wavelength_names()
for key in statistics_all.keys():
pname, xname, dname = key
# FIXME should assert that the dname is a
# valid wavelength name
available = statistics_all[key].keys()
stats = []
keys = [
'High resolution limit',
'Low resolution limit',
'Completeness',
'Multiplicity',
'I/sigma',
'Rmerge(I+/I-)',
'CC half',
'Anomalous completeness',
'Anomalous correlation',
'Anomalous multiplicity',
'Total observations',
'Total unique',
'Rmeas(I)',
'Rmeas(I+,-)',
'Rpim(I)',
'Rpim(I+/-)',
'Partial Bias'
]
for k in keys:
if k in available:
stats.append(k)
xwavelength = xcrystal.get_xwavelength(dname)
sweeps = xwavelength.get_sweeps()
for j, name in enumerate(
['overall', 'innerShell', 'outerShell']):
statistics_cache = { }
for s in stats:
if type(statistics_all[key][s]) == type([]):
statistics_cache[s] = statistics_all[key][s][j]
elif type(statistics_all[key][s]) == type(()):
statistics_cache[s] = statistics_all[key][s][j]
# send these to be written out
self.write_scaling_statistics(fout, name,
statistics_cache)
for sweep in sweeps:
fout.write('<AutoProcIntegrationContainer>\n')
image_name = sweep.get_all_image_names()[0]
fout.write('<Image><fileName>%s</fileName>' % \
os.path.split(image_name)[-1])
fout.write('<fileLocation>%s</fileLocation></Image>' %
sanitize(os.path.split(image_name)[0]))
fout.write('<AutoProcIntegration>\n')
cell = sweep.get_integrater_cell()
self.write_cell(fout, cell)
# FIXME this is naughty
intgr = sweep._get_integrater()
start, end = intgr.get_integrater_wedge()
fout.write('<startImageNumber>%d</startImageNumber>' % \
start)
fout.write('<endImageNumber>%d</endImageNumber>' % \
end)
# FIXME this is naughty
indxr = sweep._get_indexer()
fout.write(
'<refinedDetectorDistance>%f</refinedDetectorDistance>' % \
indxr.get_indexer_distance())
beam = indxr.get_indexer_beam_centre()
fout.write('<refinedXBeam>%f</refinedXBeam>' % beam[0])
fout.write('<refinedYBeam>%f</refinedYBeam>' % beam[1])
fout.write('</AutoProcIntegration>\n')
fout.write('</AutoProcIntegrationContainer>\n')
fout.write('</AutoProcScalingContainer>')
# file unpacking nonsense
from xia2.Handlers.CommandLine import CommandLine
fout.write('<AutoProcProgramContainer><AutoProcProgram>')
fout.write('<processingCommandLine>%s</processingCommandLine>' \
% sanitize(CommandLine.get_command_line()))
fout.write('<processingPrograms>xia2</processingPrograms>')
fout.write('</AutoProcProgram>')
for k in reflection_files:
reflection_file = reflection_files[k]
if not type(reflection_file) == type(''):
continue
reflection_file = FileHandler.get_data_file(reflection_file)
fout.write(
'<AutoProcProgramAttachment><fileType>Result')
fout.write('</fileType><fileName>%s</fileName>' % \
os.path.split(reflection_file)[-1])
fout.write('<filePath>%s</filePath>' % \
sanitize(os.path.split(reflection_file)[0]))
fout.write('</AutoProcProgramAttachment>\n')
# add the xia2.txt file...
fout.write('<AutoProcProgramAttachment><fileType>Log')
fout.write('</fileType><fileName>xia2.txt</fileName>')
fout.write('<filePath>%s</filePath>' % sanitize(os.getcwd()))
fout.write('</AutoProcProgramAttachment>\n')
fout.write('</AutoProcProgramContainer>')
fout.write('</AutoProcContainer>\n')
fout.close()
return
def _integrate_finish(self):
'''Finish off the integration by running dials.export.'''
# FIXME - do we want to export every time we call this method
# (the file will not have changed) and also (more important) do
# we want a different exported MTZ file every time (I do not think
# that we do; these can be very large) - was exporter.get_xpid() ->
# now dials
exporter = self.ExportMtz()
exporter.set_reflections_filename(self._intgr_integrated_pickle)
mtz_filename = os.path.join(
self.get_working_directory(), '%s_integrated.mtz' % 'dials')
exporter.set_mtz_filename(mtz_filename)
exporter.run()
self._intgr_integrated_filename = mtz_filename
# record integrated MTZ file for e.g. BLEND.
pname, xname, dname = self.get_integrater_project_info()
sweep = self.get_integrater_sweep_name()
FileHandler.record_more_data_file(
'%s %s %s %s INTEGRATE' % (pname, xname, dname, sweep), mtz_filename)
if not os.path.isfile(self._intgr_integrated_filename):
raise RuntimeError("dials.export failed: %s does not exist."
% self._intgr_integrated_filename)
if self._intgr_reindex_operator is None and \
self._intgr_spacegroup_number == lattice_to_spacegroup(
self.get_integrater_refiner().get_refiner_lattice()):
Debug.write('Not reindexing to spacegroup %d (%s)' % \
(self._intgr_spacegroup_number,
self._intgr_reindex_operator))
return mtz_filename
if self._intgr_reindex_operator is None and \
self._intgr_spacegroup_number == 0:
Debug.write('Not reindexing to spacegroup %d (%s)' % \
(self._intgr_spacegroup_number,
self._intgr_reindex_operator))
return mtz_filename
Debug.write('Reindexing to spacegroup %d (%s)' % \
(self._intgr_spacegroup_number,
self._intgr_reindex_operator))
hklin = mtz_filename
reindex = Reindex()
reindex.set_working_directory(self.get_working_directory())
auto_logfiler(reindex)
reindex.set_operator(self._intgr_reindex_operator)
if self._intgr_spacegroup_number:
reindex.set_spacegroup(self._intgr_spacegroup_number)
else:
reindex.set_spacegroup(lattice_to_spacegroup(
self.get_integrater_refiner().get_refiner_lattice()))
hklout = '%s_reindex.mtz' % hklin[:-4]
reindex.set_hklin(hklin)
reindex.set_hklout(hklout)
reindex.reindex()
self._intgr_integrated_filename = hklout
self._intgr_cell = reindex.get_cell()
pname, xname, dname = self.get_integrater_project_info()
sweep = self.get_integrater_sweep_name()
FileHandler.record_more_data_file(
'%s %s %s %s experiments' % (pname, xname, dname, sweep),
self.get_integrated_experiments())
from iotbx.reflection_file_reader import any_reflection_file
miller_arrays = any_reflection_file(hklout).as_miller_arrays()
# look for profile-fitted intensities
intensities = [ma for ma in miller_arrays
if ma.info().labels == ['IPR', 'SIGIPR']]
if len(intensities) == 0:
# look instead for summation-integrated intensities
intensities = [ma for ma in miller_arrays
if ma.info().labels == ['I', 'SIGI']]
assert len(intensities)
self._intgr_n_ref = intensities[0].size()
return hklout
# FIXME in here should respect the input unit cell and lattice if provided
# FIXME from this (i) populate the helper table,
# (ii) try to avoid re-running the indexing
# step if we eliminate a solution as we have all of the refined results
# already available.
rbs = self.RefineBravaisSettings()
rbs.set_experiments_filename(indexed_experiments)
rbs.set_indexed_filename(indexed_file)
if PhilIndex.params.dials.fix_geometry:
rbs.set_detector_fix('all')
rbs.set_beam_fix('all')
FileHandler.record_log_file('%s LATTICE' % self.get_indexer_full_name(),
rbs.get_log_file())
rbs.run()
from cctbx import crystal, sgtbx
for k in sorted(rbs.get_bravais_summary()):
summary = rbs.get_bravais_summary()[k]
# FIXME need to do this better - for the moment only accept lattices
# where R.M.S. deviation is less than twice P1 R.M.S. deviation.
if self._indxr_input_lattice is None:
if not summary['recommended']:
continue
experiments = load.experiment_list(