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 _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)
if PhilIndex.params.dials.integrate.d_max:
integrate.set_d_max(PhilIndex.params.dials.integrate.d_max)
else:
integrate.set_d_max(self._intgr_reso_low)
if PhilIndex.params.dials.integrate.d_min:
integrate.set_d_min(PhilIndex.params.dials.integrate.d_min)
else:
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 xia2.Wrappers.Dials.Integrate.DIALSIntegrateError as 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_reflections = 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_reflections)
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 Sorry(e)
self._intgr_experiments_filename = integrate.get_integrated_experiments(
)
# 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 (i) record the log file, (ii) get more information out from the
# integration log on the quality of the data and (iii) the mosaic spread
# range observed and R.M.S. deviations.
self._intgr_integrated_reflections = integrate.get_integrated_reflections(
)
if not os.path.isfile(self._intgr_integrated_reflections):
raise RuntimeError("Integration failed: %s does not exist." %
self._intgr_integrated_reflections)
self._intgr_per_image_statistics = integrate.get_per_image_statistics()
Chatter.write(self.show_per_image_statistics())
report = self.Report()
html_filename = os.path.join(
self.get_working_directory(),
"%i_dials.integrate.report.html" % report.get_xpid(),
)
report.set_html_filename(html_filename)
report.run(wait_for_completion=True)
FileHandler.record_html_file(
"%s %s %s %s INTEGRATE" % (pname, xname, dname, sweep),
html_filename)
from dxtbx.serialize import load
experiments = load.experiment_list(self._intgr_experiments_filename)
profile = experiments.profiles()[0]
mosaic = profile.sigma_m()
try:
m_min, m_max, m_mean = mosaic.min_max_mean().as_tuple()
self.set_integrater_mosaic_min_mean_max(m_min, m_mean, m_max)
except AttributeError as e:
self.set_integrater_mosaic_min_mean_max(mosaic, mosaic, mosaic)
Chatter.write("Mosaic spread: %.3f < %.3f < %.3f" %
self.get_integrater_mosaic_min_mean_max())
return self._intgr_integrated_reflections
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
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(self):
'''Perform all of the operations required to deliver the scaled
data.'''
epochs = self._sweep_handler.get_epochs()
if PhilIndex.params.xia2.settings.optimize_scaling:
self._determine_best_scale_model_8way()
else:
self._scalr_corrections = True
self._scalr_correct_absorption = True
self._scalr_correct_partiality = False
self._scalr_correct_decay = True
if self._scalr_corrections:
Journal.block(
'scaling', self.get_scaler_xcrystal().get_name(), 'CCP4',
{'scaling model':'automatic',
'absorption':self._scalr_correct_absorption,
'tails':self._scalr_correct_partiality,
'decay':self._scalr_correct_decay
})
else:
Journal.block(
'scaling', self.get_scaler_xcrystal().get_name(), 'CCP4',
{'scaling model':'default'})
sc = self._updated_aimless()
sc.set_hklin(self._prepared_reflections)
sc.set_intensities(PhilIndex.params.ccp4.aimless.intensities)
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 not user_resolution_limits.has_key((dname, sname)):
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(),
'%s_%s_scaled_test.mtz' % \
(self._scalr_pname, self._scalr_xname)))
if self.get_scaler_anomalous():
sc.set_anomalous()
# what follows, sucks
if Flags.get_failover():
try:
sc.scale()
except RuntimeError, 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
Chatter.write(
'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
def _index(self):
"""Actually index the diffraction pattern. Note well that
this is not going to compute the matrix..."""
# acknowledge this program
if not self._indxr_images:
raise RuntimeError("No good spots found on any images")
Citations.cite("labelit")
Citations.cite("distl")
_images = []
for i in self._indxr_images:
for j in i:
if not j in _images:
_images.append(j)
_images.sort()
images_str = "%d" % _images[0]
for i in _images[1:]:
images_str += ", %d" % i
cell_str = None
if self._indxr_input_cell:
cell_str = "%.2f %.2f %.2f %.2f %.2f %.2f" % self._indxr_input_cell
if self._indxr_sweep_name:
# 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:]
Journal.block(
"autoindexing",
self._indxr_sweep_name,
"labelit",
{
"images": images_str,
"target cell": cell_str,
"target lattice": self._indxr_input_lattice,
"template": self._fp_template,
"directory": dirname,
},
)
# auto_logfiler(self)
from xia2.Wrappers.Labelit.LabelitIndex import LabelitIndex
index = LabelitIndex()
index.set_working_directory(self.get_working_directory())
auto_logfiler(index)
# task = 'Autoindex from images:'
# for i in _images:
# task += ' %s' % self.get_image_name(i)
# self.set_task(task)
# self.add_command_line('--index_only')
Debug.write("Indexing from images:")
for i in _images:
index.add_image(self.get_image_name(i))
Debug.write("%s" % self.get_image_name(i))
if self._primitive_unit_cell:
index.set_primitive_unit_cell(self._primitive_unit_cell)
if self._indxr_input_cell:
index.set_max_cell(1.25 * max(self._indxr_input_cell[:3]))
xsweep = self.get_indexer_sweep()
if xsweep is not None:
if xsweep.get_distance() is not None:
index.set_distance(xsweep.get_distance())
# if self.get_wavelength_prov() == 'user':
# index.set_wavelength(self.get_wavelength())
if xsweep.get_beam_centre() is not None:
index.set_beam_centre(xsweep.get_beam_centre())
if self._refine_beam is False:
index.set_refine_beam(False)
else:
index.set_refine_beam(True)
index.set_beam_search_scope(self._beam_search_scope)
if (math.fabs(self.get_wavelength() - 1.54) <
0.01) or (math.fabs(self.get_wavelength() - 2.29) < 0.01):
index.set_Cu_KA_or_Cr_KA(True)
try:
index.run()
except RuntimeError as e:
if self._refine_beam is False:
raise e
# can we improve the situation?
if self._beam_search_scope < 4.0:
self._beam_search_scope += 4.0
# try repeating the indexing!
self.set_indexer_done(False)
return "failed"
# otherwise this is beyond redemption
raise e
self._solutions = index.get_solutions()
# FIXME this needs to check the smilie status e.g.
# ":)" or ";(" or " ".
# FIXME need to check the value of the RMSD and raise an
# exception if the P1 solution has an RMSD > 1.0...
# Change 27/FEB/08 to support user assigned spacegroups
# (euugh!) have to "ignore" solutions with higher symmetry
# otherwise the rest of xia will override us. Bummer.
for i, solution in self._solutions.iteritems():
if self._indxr_user_input_lattice:
if lattice_to_spacegroup(
solution["lattice"]) > lattice_to_spacegroup(
self._indxr_input_lattice):
Debug.write("Ignoring solution: %s" % solution["lattice"])
del self._solutions[i]
# configure the "right" solution
self._solution = self.get_solution()
# now store also all of the other solutions... keyed by the
# lattice - however these should only be added if they
# have a smiley in the appropriate record, perhaps?
for solution in self._solutions.keys():
lattice = self._solutions[solution]["lattice"]
if lattice in self._indxr_other_lattice_cell:
if (self._indxr_other_lattice_cell[lattice]["goodness"] <
self._solutions[solution]["metric"]):
continue
self._indxr_other_lattice_cell[lattice] = {
"goodness": self._solutions[solution]["metric"],
"cell": self._solutions[solution]["cell"],
}
self._indxr_lattice = self._solution["lattice"]
self._indxr_cell = tuple(self._solution["cell"])
self._indxr_mosaic = self._solution["mosaic"]
lms = LabelitMosflmMatrix()
lms.set_working_directory(self.get_working_directory())
lms.set_solution(self._solution["number"])
self._indxr_payload["mosflm_orientation_matrix"] = lms.calculate()
# get the beam centre from the mosflm script - mosflm
# may have inverted the beam centre and labelit will know
# this!
mosflm_beam_centre = lms.get_mosflm_beam()
if mosflm_beam_centre:
self._indxr_payload["mosflm_beam_centre"] = tuple(
mosflm_beam_centre)
detector = copy.deepcopy(self.get_detector())
beam = copy.deepcopy(self.get_beam())
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
set_mosflm_beam_centre(detector, beam, mosflm_beam_centre)
from xia2.Experts.SymmetryExpert import lattice_to_spacegroup_number
from scitbx import matrix
from cctbx import sgtbx, uctbx
from dxtbx.model import CrystalFactory
mosflm_matrix = matrix.sqr([
float(i) for line in lms.calculate()
for i in line.replace("-", " -").split()
][:9])
space_group = sgtbx.space_group_info(
lattice_to_spacegroup_number(self._solution["lattice"])).group()
crystal_model = CrystalFactory.from_mosflm_matrix(
mosflm_matrix,
unit_cell=uctbx.unit_cell(tuple(self._solution["cell"])),
space_group=space_group,
)
from dxtbx.model import Experiment, ExperimentList
experiment = Experiment(
beam=beam,
detector=detector,
goniometer=self.get_goniometer(),
scan=self.get_scan(),
crystal=crystal_model,
)
experiment_list = ExperimentList([experiment])
self.set_indexer_experiment_list(experiment_list)
# also get an estimate of the resolution limit from the
# labelit.stats_distl output... FIXME the name is wrong!
lsd = LabelitStats_distl()
lsd.set_working_directory(self.get_working_directory())
lsd.stats_distl()
resolution = 1.0e6
for i in _images:
stats = lsd.get_statistics(self.get_image_name(i))
resol = 0.5 * (stats["resol_one"] + stats["resol_two"])
if resol < resolution:
resolution = resol
self._indxr_resolution_estimate = resolution
return "ok"
def _refine(self):
for epoch, idxr in self._refinr_indexers.iteritems():
#self.digest_template()
gain = idxr._indxr_sweeps[0].get_gain()
if not self._mosflm_gain and gain:
self._mosflm_gain = gain
# if pilatus override GAIN to 1.0
if idxr.get_imageset().get_detector()[0].get_type(
) == 'SENSOR_PAD':
self._mosflm_gain = 1.0
#indxr = self.get_refiner_indexer()
indxr = idxr
if not self._mosflm_cell_ref_images:
mosaic = indxr.get_indexer_mosaic()
self._mosflm_cell_ref_images = self._refine_select_images(
idxr, mosaic)
# generate human readable output
images_str = '%d to %d' % tuple(self._mosflm_cell_ref_images[0])
for i in self._mosflm_cell_ref_images[1:]:
images_str += ', %d to %d' % tuple(i)
cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % \
indxr.get_indexer_cell()
#if len(idxr._fp_directory) <= 50:
#dirname = idxr._fp_directory
#else:
#dirname = '...%s' % idxr._fp_directory[-46:]
dirname = idxr.get_directory()
Journal.block(
'cell refining', idxr._indxr_sweep_name, 'mosflm', {
'images': images_str,
'start cell': cell_str,
'target lattice': indxr.get_indexer_lattice(),
'template': idxr.get_template(),
'directory': dirname
})
# end generate human readable output
# in here, check to see if we have the raster parameters and
# separation from indexing - if we used a different indexer
# we may not, so if this is the case call a function to generate
# them...
if not indxr.get_indexer_payload('mosflm_integration_parameters'):
# generate a list of first images
images = []
for cri in self._mosflm_cell_ref_images:
images.append(cri[0])
images.sort()
integration_params = self._mosflm_generate_raster(
images, indxr)
indxr.set_indexer_payload('mosflm_integration_params',
integration_params)
# copy them over to where they are needed
if 'separation' in integration_params:
self.set_refiner_parameter(
'mosflm', 'separation',
'%f %f' % tuple(integration_params['separation']))
if 'raster' in integration_params:
self.set_refiner_parameter(
'mosflm', 'raster',
'%d %d %d %d %d' % tuple(integration_params['raster']))
# next test the cell refinement with the correct lattice
# and P1 and see how the numbers stack up...
# copy the cell refinement resolution in...
self._mosflm_cell_ref_resolution = indxr.get_indexer_resolution()
Debug.write(
'Using resolution limit of %.2f for cell refinement' % \
self._mosflm_cell_ref_resolution)
# now trap NegativeMosaicError exception - once!
try:
# now reading the background residual values as well - if these
# are > 10 it would indicate that the images are blank (assert)
# so ignore from the analyis / comparison
if not PhilIndex.params.xia2.settings.lattice_rejection or \
idxr.get_indexer_sweep().get_user_lattice():
rms_deviations_p1 = []
br_p1 = []
else:
rms_deviations_p1, br_p1 = self._mosflm_test_refine_cell(
idxr, 'aP')
rms_deviations, br = self._mosflm_refine_cell(idxr)
except NegativeMosaicError:
if self._mosflm_cell_ref_double_mosaic:
# reset flag; half mosaic; raise BadLatticeError
Debug.write('Mosaic negative even x2 -> BadLattice')
self._mosflm_cell_ref_double_mosaic = False
raise BadLatticeError('negative mosaic spread')
else:
# set flag, double mosaic, return to try again
Debug.write('Mosaic negative -> try x2')
self._mosflm_cell_ref_double_mosaic = True
self.set_integrater_prepare_done(False)
return
if not self.get_refiner_done():
return
# compare cell refinement with lattice and in P1
images = []
for cri in self._mosflm_cell_ref_images:
for j in range(cri[0], cri[1] + 1):
images.append(j)
if rms_deviations and rms_deviations_p1:
cycles = []
j = 1
while j in rms_deviations and \
j in rms_deviations_p1:
cycles.append(j)
j += 1
Debug.write('Cell refinement comparison:')
Debug.write('Image correct triclinic')
ratio = 0.0
ratios = []
for c in cycles:
Debug.write('Cycle %d' % c)
for j, image in enumerate(images):
background_residual = max(br_p1[c][image],
br[c][image])
if background_residual > 10:
Debug.write('. %4d %.2f %.2f (ignored)' % \
(images[j], rms_deviations[c][j],
rms_deviations_p1[c][j]))
continue
Debug.write('. %4d %.2f %.2f' % \
(images[j], rms_deviations[c][j],
rms_deviations_p1[c][j]))
ratio += rms_deviations[c][j] / rms_deviations_p1[c][j]
ratios.append(
(rms_deviations[c][j] / rms_deviations_p1[c][j]))
Debug.write('Average ratio: %.2f' % \
(ratio / len(ratios)))
if (ratio / (max(cycles) * len(images))) > \
PhilIndex.params.xia2.settings.lattice_rejection_threshold and \
not self.get_integrater_sweep().get_user_lattice():
raise BadLatticeError('incorrect lattice constraints')
else:
Debug.write('Cell refinement in P1 failed... or was not run')
cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % \
self._refinr_cell
Journal.entry({'refined cell': cell_str})
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):
'''Implement the indexer interface.'''
Citations.cite('mosflm')
indexer = MosflmIndex()
indexer.set_working_directory(self.get_working_directory())
auto_logfiler(indexer)
from xia2.lib.bits import unique_elements
_images = unique_elements(self._indxr_images)
indexer.set_images(_images)
images_str = ', '.join(map(str, _images))
cell_str = None
if self._indxr_input_cell:
cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % \
self._indxr_input_cell
if self._indxr_sweep_name:
#if len(self._fp_directory) <= 50:
#dirname = self._fp_directory
#else:
#dirname = '...%s' % self._fp_directory[-46:]
dirname = os.path.dirname(self.get_imageset().get_template())
Journal.block(
'autoindexing', self._indxr_sweep_name, 'mosflm',
{'images':images_str,
'target cell':self._indxr_input_cell,
'target lattice':self._indxr_input_lattice,
'template':self.get_imageset().get_template(),
'directory':dirname})
#task = 'Autoindex from images:'
#for i in _images:
#task += ' %s' % self.get_image_name(i)
#self.set_task(task)
indexer.set_template(os.path.basename(self.get_template()))
indexer.set_directory(self.get_directory())
xsweep = self.get_indexer_sweep()
if xsweep is not None:
if xsweep.get_distance() is not None:
indexer.set_distance(xsweep.get_distance())
#if self.get_wavelength_prov() == 'user':
#index.set_wavelength(self.get_wavelength())
if xsweep.get_beam_centre() is not None:
indexer.set_beam_centre(xsweep.get_beam_centre())
if self._indxr_input_cell:
indexer.set_unit_cell(self._indxr_input_cell)
if self._indxr_input_lattice != None:
spacegroup_number = lattice_to_spacegroup(
self._indxr_input_lattice)
indexer.set_space_group_number(spacegroup_number)
if not self._mosflm_autoindex_thresh:
try:
min_peaks = 200
Debug.write('Aiming for at least %d spots...' % min_peaks)
thresholds = []
for i in _images:
p = Printpeaks()
p.set_working_directory(self.get_working_directory())
auto_logfiler(p)
p.set_image(self.get_image_name(i))
thresh = p.threshold(min_peaks)
Debug.write('Autoindex threshold for image %d: %d' % \
(i, thresh))
thresholds.append(thresh)
thresh = min(thresholds)
self._mosflm_autoindex_thresh = thresh
except Exception as e:
print str(e) #XXX this should disappear!
Debug.write('Error computing threshold: %s' % str(e))
Debug.write('Using default of 20.0')
thresh = 20.0
else:
thresh = self._mosflm_autoindex_thresh
Debug.write('Using autoindex threshold: %d' % thresh)
if self._mosflm_autoindex_sol:
indexer.set_solution_number(self._mosflm_autoindex_sol)
indexer.set_threshold(thresh)
# now forget this to prevent weird things happening later on
if self._mosflm_autoindex_sol:
self._mosflm_autoindex_sol = 0
indexer.run()
#sweep = self.get_indexer_sweep_name()
#FileHandler.record_log_file(
#'%s INDEX' % (sweep), self.get_log_file())
indxr_cell = indexer.get_refined_unit_cell()
self._indxr_lattice = indexer.get_lattice()
space_group_number = indexer.get_indexed_space_group_number()
detector_distance = indexer.get_refined_distance()
beam_centre = indexer.get_refined_beam_centre()
mosaic_spreads = indexer.get_mosaic_spreads()
if min(list(indxr_cell)) < 10.0 and \
indxr_cell[2] / indxr_cell[0] > 6:
Debug.write(
'Unrealistic autoindexing solution: ' +
'%.2f %.2f %.2f %.2f %.2f %.2f' % indxr_cell)
# tweak some parameters and try again...
self._mosflm_autoindex_thresh *= 1.5
self.set_indexer_done(False)
return
intgr_params = { }
# look up other possible indexing solutions (not well - in
# standard settings only!) This is moved earlier as it could
# result in returning if Mosflm has selected the wrong
# solution!
try:
self._indxr_other_lattice_cell = indexer.get_solutions()
# Change 27/FEB/08 to support user assigned spacegroups
if self._indxr_user_input_lattice:
lattice_to_spacegroup_dict = {
'aP':1, 'mP':3, 'mC':5, 'oP':16, 'oC':20, 'oF':22,
'oI':23, 'tP':75, 'tI':79, 'hP':143, 'hR':146,
'cP':195, 'cF':196, 'cI':197}
for k in self._indxr_other_lattice_cell.keys():
if lattice_to_spacegroup_dict[k] > \
lattice_to_spacegroup_dict[
self._indxr_input_lattice]:
del(self._indxr_other_lattice_cell[k])
# check that the selected unit cell matches - and if
# not raise a "horrible" exception
if self._indxr_input_cell:
assert indxr_cell is not None
for j in range(6):
if math.fabs(self._indxr_input_cell[j] - indxr_cell[j]) > 2.0:
Chatter.write(
'Mosflm autoindexing did not select ' +
'correct (target) unit cell')
raise RuntimeError, \
'something horrible happened in indexing'
except RuntimeError, e:
# check if mosflm rejected a solution we have it
if 'horribl' in str(e):
# ok it did - time to break out the big guns...
if not self._indxr_input_cell:
raise RuntimeError, \
'error in solution selection when not preset'
# XXX FIXME
self._mosflm_autoindex_sol = _get_indexing_solution_number(
indexer.get_all_output(),
self._indxr_input_cell,
self._indxr_input_lattice)
# set the fact that we are not done...
self.set_indexer_done(False)
# and return - hopefully this will restart everything
return
else:
raise e
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
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,
},
)
idxref = self.Idxref()
self._index_remove_masked_regions()
for file in ["SPOT.XDS"]:
idxref.set_input_data_file(file, self._indxr_payload[file])
# edit SPOT.XDS to remove reflections in untrusted regions of the detector
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])
# set the phi start etc correctly
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])
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
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 FIXME should use xds_cell_deviation
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 _scale(self):
"""Perform all of the operations required to deliver the scaled
data."""
sweep_infos = [
self._sweep_handler.get_sweep_information(e)
for e in self._sweep_handler.get_epochs()
]
if self._scalr_corrections:
Journal.block(
"scaling",
self.get_scaler_xcrystal().get_name(),
"Dials",
{
"scaling model": "automatic",
"absorption": self._scalr_correct_absorption,
"decay": self._scalr_correct_decay,
},
)
else:
Journal.block(
"scaling",
self.get_scaler_xcrystal().get_name(),
"Dials",
{"scaling model": "default"},
)
### Set the parameters and datafiles for dials.scale
self._scaler = DialsScale()
self._scaler = self._updated_dials_scaler()
if self._scaled_experiments and self._scaled_reflections:
# going to continue-where-left-off
self._scaler.add_experiments_json(self._scaled_experiments)
self._scaler.add_reflections_file(self._scaled_reflections)
else:
for si in sweep_infos:
self._scaler.add_experiments_json(si.get_experiments())
self._scaler.add_reflections_file(si.get_reflections())
### Set the unmerged mtz filepath
self._scalr_scaled_reflection_files = {}
self._scalr_scaled_reflection_files["mtz_unmerged"] = {}
# First set the unmerged mtz output filename. Note that this is the
# same for MAD datasets too, as need a single unmerged for merging
# stats calc. For the merged mtz this is different.
scaled_unmerged_mtz_path = os.path.join(
self.get_working_directory(),
"%s_%s_scaled_unmerged.mtz" % (self._scalr_pname, self._scalr_xname),
)
self._scaler.set_scaled_unmerged_mtz([scaled_unmerged_mtz_path])
self._scaler.set_crystal_name(self._scalr_xname) # Name goes in mtz
### Set the merged mtz filepath(s), making into account MAD case.
# Find number of dnames (i.e. number of wavelengths)
dnames_set = OrderedSet()
for si in sweep_infos:
dnames_set.add(si.get_project_info()[2])
scaled_mtz_path = os.path.join(
self.get_working_directory(),
"%s_%s_scaled.mtz" % (self._scalr_pname, self._scalr_xname),
)
if len(dnames_set) == 1:
self._scaler.set_scaled_mtz([scaled_mtz_path])
self._scalr_scaled_reflection_files["mtz"] = {
dnames_set[0]: scaled_mtz_path
}
self._scalr_scaled_reflection_files["mtz_unmerged"] = {
dnames_set[0]: scaled_unmerged_mtz_path
}
else:
merged_mtz_files = []
self._scalr_scaled_reflection_files["mtz"] = {}
for dname in dnames_set:
this_mtz_path = scaled_mtz_path.rstrip(".mtz") + ("_%s.mtz" % dname)
merged_mtz_files.append(this_mtz_path)
self._scalr_scaled_reflection_files["mtz"][dname] = scaled_mtz_path
# Note - we aren't logging individual unmerged here as not
# generating until later.
self._scaler.set_scaled_mtz(merged_mtz_files)
### Set the resolution limit if applicable
user_resolution_limits = {}
highest_resolution = 100.0
for si in sweep_infos:
dname = si.get_project_info()[2]
sname = si.get_sweep_name()
intgr = si.get_integrater()
if intgr.get_integrater_user_resolution():
# record user resolution here but don't use it until later - why?
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
if (dname, sname) in self._scalr_resolution_limits:
d_min, _ = self._scalr_resolution_limits[(dname, sname)]
if d_min < highest_resolution:
highest_resolution = d_min
if highest_resolution < 99.9:
self._scaler.set_resolution(d_min=highest_resolution)
### Setup final job details and run scale
self._scaler.set_working_directory(self.get_working_directory())
auto_logfiler(self._scaler)
FileHandler.record_log_file(
"%s %s SCALE" % (self._scalr_pname, self._scalr_xname),
self._scaler.get_log_file(),
)
self._scaler.scale()
self._scaled_experiments = self._scaler.get_scaled_experiments()
self._scaled_reflections = self._scaler.get_scaled_reflections()
FileHandler.record_data_file(scaled_unmerged_mtz_path)
# make it so that only scaled.expt and scaled.refl are
# the files that dials.scale knows about, so that if scale is called again,
# scaling resumes from where it left off.
self._scaler.clear_datafiles()
# log datafiles here, picked up from here in commonscaler methods.
if len(dnames_set) == 1:
hklout = copy.deepcopy(self._scaler.get_scaled_mtz()[0])
self._scalr_scaled_refl_files = {dnames_set[0]: hklout}
FileHandler.record_data_file(hklout)
else:
self._scalr_scaled_refl_files = {}
for i, dname in enumerate(dnames_set):
hklout = copy.deepcopy(self._scaler.get_scaled_mtz()[i])
self._scalr_scaled_refl_files[dname] = hklout
FileHandler.record_data_file(hklout)
### Calculate the resolution limit and set done False if applicable
highest_suggested_resolution = self.assess_resolution_limits(
self._scaler.get_unmerged_reflection_file(),
user_resolution_limits,
use_misigma=False,
)
if not self.get_scaler_done():
# reset for when resolution limit applied
Debug.write("Returning as scaling not finished...")
return
### For MAD case, generate individual unmerged mtz for stats.
if len(dnames_set) > 1:
unmerged_mtz_files = []
scaler = DialsScale()
scaler.set_working_directory(self.get_working_directory())
scaler.set_export_mtz_only()
scaler.add_experiments_json(self._scaled_experiments)
scaler.add_reflections_file(self._scaled_reflections)
for dname in dnames_set:
this_mtz_path = scaled_unmerged_mtz_path.rstrip(".mtz") + (
"_%s.mtz" % dname
)
unmerged_mtz_files.append(this_mtz_path)
self._scalr_scaled_reflection_files["mtz_unmerged"][
dname
] = this_mtz_path
scaler.set_scaled_unmerged_mtz(unmerged_mtz_files)
scaler.scale()
for f in scaler.get_scaled_unmerged_mtz(): # a list
FileHandler.record_data_file(f)
# set refls, exps & unmerged mtz names"
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
# Run twotheta refine
self._update_scaled_unit_cell()
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 dials.symmetry) and generally tidy
things up."""
# AIM discover symmetry and reindex with dials.symmetry, and set the correct
# reflections in si.reflections, si.experiments
self._helper.set_working_directory(self.get_working_directory())
self._factory.set_working_directory(self.get_working_directory())
need_to_return = False
self._sweep_handler = SweepInformationHandler(self._scalr_integraters)
p, x = self._sweep_handler.get_project_info()
self._scalr_pname = p
self._scalr_xname = x
self._helper.set_pname_xname(p, x)
Journal.block(
"gathering",
self.get_scaler_xcrystal().get_name(),
"Dials",
{"working directory": self.get_working_directory()},
)
# First do stuff to work out if excluding any data
# Note - does this actually work? I couldn't seem to get it to work
# in either this pipeline or the standard dials pipeline
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
intgr = si.get_integrater()
_, 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)})
# If multiple files, want to run symmetry to check for consistent indexing
# also
# try to reproduce what CCP4ScalerA is doing
# first assign identifiers to avoid dataset-id collisions
# Idea is that this should be called anytime you get data anew from the
# integrater, to intercept and assign unique ids, then set in the
# sweep_information (si) and always use si.set_reflections/
# si.get_reflections as we process.
# self._sweep_handler = self._helper.assign_and_return_datasets(
# self._sweep_handler
# ) symmetry now sorts out identifiers.
need_to_return = False
if self._scalr_input_pointgroup:
self._input_pointgroup_scale_prepare()
elif (
len(self._sweep_handler.get_epochs()) > 1
and PhilIndex.params.xia2.settings.multi_sweep_indexing
):
need_to_return = self._multi_sweep_scale_prepare()
else:
need_to_return = self._standard_scale_prepare()
if need_to_return:
self.set_scaler_done(False)
self.set_scaler_prepare_done(False)
return
### After this point, point group is good and only need to
### reindex to consistent setting. Don't need to call back to the
### integator, just use the data in the sweep info.
# First work out if we're going to reindex against external reference
param = PhilIndex.params.xia2.settings.scale
using_external_references = False
reference_refl = None
reference_expt = None
if param.reference_reflection_file:
if not param.reference_experiment_file:
Chatter.write(
"""
No DIALS reference experiments file provided, reference reflection file will
not be used. Reference mtz files for reindexing not currently supported for
pipeline=dials (supported for pipeline=dials-aimless).
"""
)
else:
reference_refl = param.reference_reflection_file
reference_expt = param.reference_experiment_file
using_external_references = True
Debug.write("Using reference reflections %s" % reference_refl)
Debug.write("Using reference experiments %s" % reference_expt)
if len(self._sweep_handler.get_epochs()) > 1:
if PhilIndex.params.xia2.settings.unify_setting:
self.unify_setting()
if PhilIndex.params.xia2.settings.use_brehm_diederichs:
self.brehm_diederichs_reindexing()
# If not using Brehm-deidrichs reindexing, set reference as first
# sweep, unless using external reference.
elif not using_external_references:
Debug.write("First sweep will be used as reference for reindexing")
first = self._sweep_handler.get_epochs()[0]
si = self._sweep_handler.get_sweep_information(first)
reference_expt = si.get_experiments()
reference_refl = si.get_reflections()
# Now reindex to be consistent with first dataset - run reindex on each
# dataset with reference (unless did brehm diederichs and didn't supply
# a reference file)
if reference_refl and reference_expt:
exp = load.experiment_list(reference_expt)
reference_cell = exp[0].crystal.get_unit_cell().parameters()
# ---------- REINDEX TO CORRECT (REFERENCE) SETTING ----------
Chatter.write("Reindexing all datasets to common reference")
if using_external_references:
epochs = self._sweep_handler.get_epochs()
else:
epochs = self._sweep_handler.get_epochs()[1:]
for epoch in 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
reindexer = DialsReindex()
reindexer.set_working_directory(self.get_working_directory())
auto_logfiler(reindexer)
si = self._sweep_handler.get_sweep_information(epoch)
reindexer.set_reference_filename(reference_expt)
reindexer.set_reference_reflections(reference_refl)
reindexer.set_indexed_filename(si.get_reflections())
reindexer.set_experiments_filename(si.get_experiments())
reindexer.run()
# At this point, CCP4ScalerA would reset in integrator so that
# the integrater calls reindex, no need to do that here as
# have access to the files and will never need to reintegrate.
si.set_reflections(reindexer.get_reindexed_reflections_filename())
si.set_experiments(reindexer.get_reindexed_experiments_filename())
# FIXME how to get some indication of the reindexing used?
exp = load.experiment_list(
reindexer.get_reindexed_experiments_filename()
)
cell = exp[0].crystal.get_unit_cell().parameters()
# Note - no lattice check as this will already be caught by reindex
Debug.write("Cell: %.2f %.2f %.2f %.2f %.2f %.2f" % cell)
Debug.write("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"
% (reference_expt, si.get_reflections())
)
# Now make sure all batches ok before finish preparing
# This should be made safer, currently after dials.scale there is no
# concept of 'batch', dials.export uses the calculate_batch_offsets
# to assign batches, giving the same result as below.
experiments_to_rebatch = []
for epoch in self._sweep_handler.get_epochs():
si = self._sweep_handler.get_sweep_information(epoch)
experiment = si.get_experiments()
experiments_to_rebatch.append(load.experiment_list(experiment)[0])
offsets = calculate_batch_offsets(experiments_to_rebatch)
for i, epoch in enumerate(self._sweep_handler.get_epochs()):
si = self._sweep_handler.get_sweep_information(epoch)
r = si.get_batch_range()
si.set_batch_offset(offsets[i])
si.set_batches([r[0] + offsets[i], r[1] + offsets[i]])
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
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})
idxref = self.Idxref()
self._index_remove_masked_regions()
for file in ['SPOT.XDS']:
idxref.set_input_data_file(file, self._indxr_payload[file])
# edit SPOT.XDS to remove reflections in untrusted regions of the detector
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])
# set the phi start etc correctly
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])
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
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, 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 FIXME should use xds_cell_deviation
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
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
})
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.get_frame_offset(),
self._intgr_wedge[1] + self.get_frame_offset())
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))
integrate.set_data_range(
self._intgr_wedge[0] + self.get_frame_offset(),
self._intgr_wedge[1] + self.get_frame_offset())
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 'GXPARM.XDS' in self._xds_data_files:
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 _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})
idxref = self.Idxref()
self._index_remove_masked_regions()
for file in ['SPOT.XDS']:
idxref.set_input_data_file(file, self._indxr_payload[file])
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])
# set the phi start etc correctly
if self._i_or_ii == None:
self._i_or_ii = self.decide_i_or_ii()
Debug.write('Selecting I or II, chose %s' % self._i_or_ii)
if self._i_or_ii == 'i':
blocks = self._index_select_images_i()
for block in blocks[:1]:
starting_frame = block[0]
dd = Diffdump()
dd.set_image(self.get_image_name(starting_frame))
starting_angle = dd.readheader()['phi_start']
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]
dd = Diffdump()
dd.set_image(self.get_image_name(starting_frame))
starting_angle = dd.readheader()['phi_start']
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, 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
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 \
not Flags.get_relax():
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 not Flags.get_relax():
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
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.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
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
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)
from xia2.Modules.Scaler.rebatch import rebatch
new_batches = 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...
Debug.write(
"Running multisweep pointless for %d sweeps" % len(refiners)
)
pointgroup, reindex_op, ntr, pt = self._pointless_indexer_multisweep(
pointless_hklin, refiners
)
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
# 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
)
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
# 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]
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
# 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
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
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)
from xia2.Modules.Scaler.rebatch import rebatch
new_batches = 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(),
"%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
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:
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
# 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:
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()
# 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()
Debug.write("Using HKLREF %s" % self._reference)
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)
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()
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():
# 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
)
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())
)
Debug.write("Cell: %.2f %.2f %.2f %.2f %.2f %.2f" % cell)
Debug.write("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 _scale(self):
"""Perform all of the operations required to deliver the scaled
data."""
epochs = self._sweep_handler.get_epochs()
if self._scalr_corrections:
Journal.block(
"scaling",
self.get_scaler_xcrystal().get_name(),
"CCP4",
{
"scaling model": "automatic",
"absorption": self._scalr_correct_absorption,
"decay": self._scalr_correct_decay,
},
)
else:
Journal.block(
"scaling",
self.get_scaler_xcrystal().get_name(),
"CCP4",
{"scaling model": "default"},
)
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(),
"%s_%s_scaled_test.mtz" % (self._scalr_pname, self._scalr_xname),
)
)
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
Chatter.write(
"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.)
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])
# 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():
Debug.write("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(
"%s %s aimless" % (self._scalr_pname, self._scalr_xname), 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(),
"%s_%s_scaled.mtz" % (self._scalr_pname, self._scalr_xname),
)
)
if self.get_scaler_anomalous():
sc.set_anomalous()
sc.scale()
FileHandler.record_xml_file(
"%s %s aimless" % (self._scalr_pname, self._scalr_xname), 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 not dname in self._wavelengths_in_order:
self._wavelengths_in_order.append(dname)
sc.set_hklout(
os.path.join(
self.get_working_directory(),
"%s_%s_scaled.mtz" % (self._scalr_pname, self._scalr_xname),
)
)
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(
"%s_%s_%s" % (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 not dname in self._wavelengths_in_order:
self._wavelengths_in_order.append(dname)
sc.set_hklout(
os.path.join(
self.get_working_directory(),
"%s_%s_chef.mtz" % (self._scalr_pname, self._scalr_xname),
)
)
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
Debug.write("Could not generate absorption map (%s)" % e)
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.multi_sweep_indexing == True
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?
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
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
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)
from xia2.Modules.Scaler.rebatch import rebatch
new_batches = 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
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...
Debug.write('Running multisweep pointless for %d sweeps' %
len(refiners))
pointgroup, reindex_op, ntr, pt = \
self._pointless_indexer_multisweep(pointless_hklin,
refiners)
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.multi_sweep_indexing == True
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
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
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)
from xia2.Modules.Scaler.rebatch import rebatch
new_batches = 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(),
'%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
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
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:
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 = {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 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:
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 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)
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():
# 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)
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()))
Debug.write('Cell: %.2f %.2f %.2f %.2f %.2f %.2f' % cell)
Debug.write('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 _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 _scale(self):
'''Perform all of the operations required to deliver the scaled
data.'''
epochs = self._sweep_handler.get_epochs()
if self._scalr_corrections:
Journal.block(
'scaling', self.get_scaler_xcrystal().get_name(), 'CCP4',
{'scaling model':'automatic',
'absorption':self._scalr_correct_absorption,
'decay':self._scalr_correct_decay
})
else:
Journal.block(
'scaling', self.get_scaler_xcrystal().get_name(), 'CCP4',
{'scaling model':'default'})
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(),
'%s_%s_scaled_test.mtz' % \
(self._scalr_pname, self._scalr_xname)))
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
Chatter.write(
'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.)
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
highest_suggested_resolution = None
# 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:
si = self._sweep_handler.get_sweep_information(epoch)
pname, xname, dname = si.get_project_info()
sname = si.get_sweep_name()
intgr = si.get_integrater()
start, end = si.get_batch_range()
if (dname, sname) in self._scalr_resolution_limits:
continue
elif (dname, sname) in user_resolution_limits:
limit = user_resolution_limits[(dname, sname)]
self._scalr_resolution_limits[(dname, sname)] = (limit, None)
if limit < highest_resolution:
highest_resolution = limit
Chatter.write('Resolution limit for %s: %5.2f (user provided)' % \
(dname, limit))
continue
hklin = sc.get_unmerged_reflection_file()
limit, reasoning = self._estimate_resolution_limit(
hklin, batch_range=(start, end))
if PhilIndex.params.xia2.settings.resolution.keep_all_reflections == True:
suggested = limit
if highest_suggested_resolution is None or limit < highest_suggested_resolution:
highest_suggested_resolution = limit
limit = intgr.get_detector().get_max_resolution(intgr.get_beam_obj().get_s0())
self._scalr_resolution_limits[(dname, sname)] = (limit, suggested)
Debug.write('keep_all_reflections set, using detector limits')
Debug.write('Resolution for sweep %s: %.2f' % \
(sname, limit))
if not (dname, sname) in self._scalr_resolution_limits:
self._scalr_resolution_limits[(dname, sname)] = (limit, None)
self.set_scaler_done(False)
if limit < highest_resolution:
highest_resolution = limit
limit, suggested = self._scalr_resolution_limits[(dname, sname)]
if suggested is None or limit == suggested:
reasoning_str = ''
if reasoning:
reasoning_str = ' (%s)' % reasoning
Chatter.write('Resolution for sweep %s/%s: %.2f%s' % \
(dname, sname, limit, reasoning_str))
else:
Chatter.write('Resolution limit for %s/%s: %5.2f (%5.2f suggested)' % \
(dname, sname, limit, suggested))
if highest_suggested_resolution is not None and \
highest_resolution >= (highest_suggested_resolution - 0.004):
Debug.write('Dropping resolution cut-off suggestion since it is'
' essentially identical to the actual resolution limit.')
highest_suggested_resolution = None
self._scalr_highest_resolution = highest_resolution
self._scalr_highest_suggested_resolution = highest_suggested_resolution
if highest_suggested_resolution is not None:
Debug.write('Suggested highest resolution is %5.2f (%5.2f suggested)' % \
(highest_resolution, highest_suggested_resolution))
else:
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
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('%s %s aimless' % (self._scalr_pname,
self._scalr_xname),
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(),
'%s_%s_scaled.mtz' % \
(self._scalr_pname, self._scalr_xname)))
if self.get_scaler_anomalous():
sc.set_anomalous()
sc.scale()
FileHandler.record_xml_file('%s %s aimless xml' % (self._scalr_pname,
self._scalr_xname),
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 not dname in self._wavelengths_in_order:
self._wavelengths_in_order.append(dname)
sc.set_hklout(os.path.join(self.get_working_directory(),
'%s_%s_scaled.mtz' % \
(self._scalr_pname,
self._scalr_xname)))
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('%s_%s_%s' %
(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 not dname in self._wavelengths_in_order:
self._wavelengths_in_order.append(dname)
sc.set_hklout(os.path.join(self.get_working_directory(),
'%s_%s_chef.mtz' % \
(self._scalr_pname,
self._scalr_xname)))
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
Debug.write("Could not generate absorption map (%s)" % e)
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 _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 xia2.Wrappers.Dials.Integrate.DIALSIntegrateError as 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 Sorry(e)
self._intgr_experiments_filename = integrate.get_integrated_experiments(
)
# 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 (i) record the log file, (ii) get more information out from the
# integration log on the quality of the data and (iii) the mosaic spread
# range observed and R.M.S. deviations.
self._intgr_integrated_pickle = integrate.get_integrated_reflections()
if not os.path.isfile(self._intgr_integrated_pickle):
raise RuntimeError("Integration failed: %s does not exist." %
self._intgr_integrated_pickle)
self._intgr_per_image_statistics = integrate.get_per_image_statistics()
Chatter.write(self.show_per_image_statistics())
report = self.Report()
html_filename = os.path.join(
self.get_working_directory(),
'%i_dials.integrate.report.html' % report.get_xpid())
report.set_html_filename(html_filename)
report.run()
FileHandler.record_html_file('%s %s %s %s INTEGRATE' % \
(pname, xname, dname, sweep),
html_filename)
import dials
from dxtbx.serialize import load
experiments = load.experiment_list(self._intgr_experiments_filename)
profile = experiments.profiles()[0]
mosaic = profile.sigma_m()
self.set_integrater_mosaic_min_mean_max(mosaic, mosaic, mosaic)
Chatter.write('Mosaic spread: %.3f < %.3f < %.3f' % \
self.get_integrater_mosaic_min_mean_max())
return self._intgr_integrated_pickle
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 _index(self):
'''Actually index the diffraction pattern. Note well that
this is not going to compute the matrix...'''
# acknowledge this program
if not self._indxr_images:
raise RuntimeError, 'No good spots found on any images'
Citations.cite('labelit')
Citations.cite('distl')
_images = []
for i in self._indxr_images:
for j in i:
if not j in _images:
_images.append(j)
_images.sort()
images_str = '%d' % _images[0]
for i in _images[1:]:
images_str += ', %d' % i
cell_str = None
if self._indxr_input_cell:
cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % \
self._indxr_input_cell
if self._indxr_sweep_name:
# 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:]
Journal.block(
'autoindexing', self._indxr_sweep_name, 'labelit',
{'images':images_str,
'target cell':cell_str,
'target lattice':self._indxr_input_lattice,
'template':self._fp_template,
'directory':dirname})
#auto_logfiler(self)
from xia2.Wrappers.Labelit.LabelitIndex import LabelitIndex
index = LabelitIndex()
index.set_working_directory(self.get_working_directory())
auto_logfiler(index)
#task = 'Autoindex from images:'
#for i in _images:
#task += ' %s' % self.get_image_name(i)
#self.set_task(task)
#self.add_command_line('--index_only')
Debug.write('Indexing from images:')
for i in _images:
index.add_image(self.get_image_name(i))
Debug.write('%s' % self.get_image_name(i))
if self._indxr_input_lattice and False:
index.set_space_group_number(
lattice_to_spacegroup(self._indxr_input_lattice))
if self._primitive_unit_cell:
index.set_primitive_unit_cell(self._primitive_unit_cell)
if self._indxr_input_cell:
index.set_max_cell(1.25 * max(self._indxr_input_cell[:3]))
xsweep = self.get_indexer_sweep()
if xsweep is not None:
if xsweep.get_distance() is not None:
index.set_distance(xsweep.get_distance())
#if self.get_wavelength_prov() == 'user':
#index.set_wavelength(self.get_wavelength())
if xsweep.get_beam_centre() is not None:
index.set_beam_centre(xsweep.get_beam_centre())
if self._refine_beam is False:
index.set_refine_beam(False)
else:
index.set_refine_beam(True)
index.set_beam_search_scope(self._beam_search_scope)
if ((math.fabs(self.get_wavelength() - 1.54) < 0.01) or
(math.fabs(self.get_wavelength() - 2.29) < 0.01)):
index.set_Cu_KA_or_Cr_KA(True)
try:
index.run()
except RuntimeError, e:
if self._refine_beam is False:
raise e
# can we improve the situation?
if self._beam_search_scope < 4.0:
self._beam_search_scope += 4.0
# try repeating the indexing!
self.set_indexer_done(False)
return 'failed'
# otherwise this is beyond redemption
raise e
def _index(self):
'''Actually index the diffraction pattern. Note well that
this is not going to compute the matrix...'''
# acknowledge this program
Citations.cite('labelit')
Citations.cite('distl')
#self.reset()
_images = []
for i in self._indxr_images:
for j in i:
if not j in _images:
_images.append(j)
_images.sort()
images_str = '%d' % _images[0]
for i in _images[1:]:
images_str += ', %d' % i
cell_str = None
if self._indxr_input_cell:
cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % \
self._indxr_input_cell
if self._indxr_sweep_name:
# 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 = os.path.dirname(self.get_imageset().get_template())
Journal.block(
'autoindexing', self._indxr_sweep_name, 'labelit', {
'images': images_str,
'target cell': cell_str,
'target lattice': self._indxr_input_lattice,
'template': self.get_imageset().get_template(),
'directory': dirname
})
if len(_images) > 4:
raise RuntimeError('cannot use more than 4 images')
from xia2.Wrappers.Labelit.LabelitIndex import LabelitIndex
index = LabelitIndex()
index.set_working_directory(self.get_working_directory())
auto_logfiler(index)
#task = 'Autoindex from images:'
#for i in _images:
#task += ' %s' % self.get_image_name(i)
#self.set_task(task)
Debug.write('Indexing from images:')
for i in _images:
index.add_image(self.get_image_name(i))
Debug.write('%s' % self.get_image_name(i))
xsweep = self.get_indexer_sweep()
if xsweep is not None:
if xsweep.get_distance() is not None:
index.set_distance(xsweep.get_distance())
#if self.get_wavelength_prov() == 'user':
#index.set_wavelength(self.get_wavelength())
if xsweep.get_beam_centre() is not None:
index.set_beam_centre(xsweep.get_beam_centre())
if self._refine_beam is False:
index.set_refine_beam(False)
else:
index.set_refine_beam(True)
index.set_beam_search_scope(self._beam_search_scope)
if ((math.fabs(self.get_wavelength() - 1.54) < 0.01)
or (math.fabs(self.get_wavelength() - 2.29) < 0.01)):
index.set_Cu_KA_or_Cr_KA(True)
#sweep = self.get_indexer_sweep_name()
#FileHandler.record_log_file(
#'%s INDEX' % (sweep), self.get_log_file())
try:
index.run()
except RuntimeError as e:
if self._refine_beam is False:
raise e
# can we improve the situation?
if self._beam_search_scope < 4.0:
self._beam_search_scope += 4.0
# try repeating the indexing!
self.set_indexer_done(False)
return 'failed'
# otherwise this is beyond redemption
raise e
self._solutions = index.get_solutions()
# FIXME this needs to check the smilie status e.g.
# ":)" or ";(" or " ".
# FIXME need to check the value of the RMSD and raise an
# exception if the P1 solution has an RMSD > 1.0...
# Change 27/FEB/08 to support user assigned spacegroups
# (euugh!) have to "ignore" solutions with higher symmetry
# otherwise the rest of xia will override us. Bummer.
for i, solution in self._solutions.iteritems():
if self._indxr_user_input_lattice:
if (lattice_to_spacegroup(solution['lattice']) >
lattice_to_spacegroup(self._indxr_input_lattice)):
Debug.write('Ignoring solution: %s' % solution['lattice'])
del self._solutions[i]
# check the RMSD from the triclinic unit cell
if self._solutions[1]['rmsd'] > 1.0 and False:
# don't know when this is useful - but I know when it is not!
raise RuntimeError('high RMSD for triclinic solution')
# configure the "right" solution
self._solution = self.get_solution()
# now store also all of the other solutions... keyed by the
# lattice - however these should only be added if they
# have a smiley in the appropriate record, perhaps?
for solution in self._solutions.keys():
lattice = self._solutions[solution]['lattice']
if lattice in self._indxr_other_lattice_cell:
if self._indxr_other_lattice_cell[lattice]['goodness'] < \
self._solutions[solution]['metric']:
continue
self._indxr_other_lattice_cell[lattice] = {
'goodness': self._solutions[solution]['metric'],
'cell': self._solutions[solution]['cell']
}
self._indxr_lattice = self._solution['lattice']
self._indxr_cell = tuple(self._solution['cell'])
self._indxr_mosaic = self._solution['mosaic']
lms = LabelitMosflmScript()
lms.set_working_directory(self.get_working_directory())
lms.set_solution(self._solution['number'])
self._indxr_payload['mosflm_orientation_matrix'] = lms.calculate()
# get the beam centre from the mosflm script - mosflm
# may have inverted the beam centre and labelit will know
# this!
mosflm_beam_centre = lms.get_mosflm_beam()
if mosflm_beam_centre:
self._indxr_payload['mosflm_beam_centre'] = tuple(
mosflm_beam_centre)
import copy
detector = copy.deepcopy(self.get_detector())
beam = copy.deepcopy(self.get_beam())
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
set_mosflm_beam_centre(detector, beam, mosflm_beam_centre)
from xia2.Experts.SymmetryExpert import lattice_to_spacegroup_number
from scitbx import matrix
from cctbx import sgtbx, uctbx
from dxtbx.model import CrystalFactory
mosflm_matrix = matrix.sqr([
float(i) for line in lms.calculate()
for i in line.replace("-", " -").split()
][:9])
space_group = sgtbx.space_group_info(
lattice_to_spacegroup_number(self._solution['lattice'])).group()
crystal_model = CrystalFactory.from_mosflm_matrix(
mosflm_matrix,
unit_cell=uctbx.unit_cell(tuple(self._solution['cell'])),
space_group=space_group)
from dxtbx.model import Experiment, ExperimentList
experiment = Experiment(
beam=beam,
detector=detector,
goniometer=self.get_goniometer(),
scan=self.get_scan(),
crystal=crystal_model,
)
experiment_list = ExperimentList([experiment])
self.set_indexer_experiment_list(experiment_list)
# also get an estimate of the resolution limit from the
# labelit.stats_distl output... FIXME the name is wrong!
lsd = LabelitStats_distl()
lsd.set_working_directory(self.get_working_directory())
lsd.stats_distl()
resolution = 1.0e6
for i in _images:
stats = lsd.get_statistics(self.get_image_name(i))
resol = 0.5 * (stats['resol_one'] + stats['resol_two'])
if resol < resolution:
resolution = resol
self._indxr_resolution_estimate = resolution
return 'ok'
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 _index(self):
'''Actually index the diffraction pattern. Note well that
this is not going to compute the matrix...'''
# acknowledge this program
Citations.cite('labelit')
Citations.cite('distl')
#self.reset()
_images = []
for i in self._indxr_images:
for j in i:
if not j in _images:
_images.append(j)
_images.sort()
images_str = '%d' % _images[0]
for i in _images[1:]:
images_str += ', %d' % i
cell_str = None
if self._indxr_input_cell:
cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % \
self._indxr_input_cell
if self._indxr_sweep_name:
# 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 = os.path.dirname(self.get_imageset().get_template())
Journal.block(
'autoindexing', self._indxr_sweep_name, 'labelit',
{'images':images_str,
'target cell':cell_str,
'target lattice':self._indxr_input_lattice,
'template':self.get_imageset().get_template(),
'directory':dirname})
if len(_images) > 4:
raise RuntimeError, 'cannot use more than 4 images'
from xia2.Wrappers.Labelit.LabelitIndex import LabelitIndex
index = LabelitIndex()
index.set_working_directory(self.get_working_directory())
auto_logfiler(index)
#task = 'Autoindex from images:'
#for i in _images:
#task += ' %s' % self.get_image_name(i)
#self.set_task(task)
Debug.write('Indexing from images:')
for i in _images:
index.add_image(self.get_image_name(i))
Debug.write('%s' % self.get_image_name(i))
xsweep = self.get_indexer_sweep()
if xsweep is not None:
if xsweep.get_distance() is not None:
index.set_distance(xsweep.get_distance())
#if self.get_wavelength_prov() == 'user':
#index.set_wavelength(self.get_wavelength())
if xsweep.get_beam_centre() is not None:
index.set_beam_centre(xsweep.get_beam_centre())
if self._refine_beam is False:
index.set_refine_beam(False)
else:
index.set_refine_beam(True)
index.set_beam_search_scope(self._beam_search_scope)
if ((math.fabs(self.get_wavelength() - 1.54) < 0.01) or
(math.fabs(self.get_wavelength() - 2.29) < 0.01)):
index.set_Cu_KA_or_Cr_KA(True)
#sweep = self.get_indexer_sweep_name()
#FileHandler.record_log_file(
#'%s INDEX' % (sweep), self.get_log_file())
try:
index.run()
except RuntimeError, e:
if self._refine_beam is False:
raise e
# can we improve the situation?
if self._beam_search_scope < 4.0:
self._beam_search_scope += 4.0
# try repeating the indexing!
self.set_indexer_done(False)
return 'failed'
# otherwise this is beyond redemption
raise e
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 _index(self):
'''Implement the indexer interface.'''
Citations.cite('mosflm')
indexer = MosflmIndex()
indexer.set_working_directory(self.get_working_directory())
auto_logfiler(indexer)
from xia2.lib.bits import unique_elements
_images = unique_elements(self._indxr_images)
indexer.set_images(_images)
images_str = ', '.join(map(str, _images))
cell_str = None
if self._indxr_input_cell:
cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % \
self._indxr_input_cell
if self._indxr_sweep_name:
#if len(self._fp_directory) <= 50:
#dirname = self._fp_directory
#else:
#dirname = '...%s' % self._fp_directory[-46:]
dirname = os.path.dirname(self.get_imageset().get_template())
Journal.block(
'autoindexing', self._indxr_sweep_name, 'mosflm', {
'images': images_str,
'target cell': self._indxr_input_cell,
'target lattice': self._indxr_input_lattice,
'template': self.get_imageset().get_template(),
'directory': dirname
})
#task = 'Autoindex from images:'
#for i in _images:
#task += ' %s' % self.get_image_name(i)
#self.set_task(task)
indexer.set_template(os.path.basename(self.get_template()))
indexer.set_directory(self.get_directory())
xsweep = self.get_indexer_sweep()
if xsweep is not None:
if xsweep.get_distance() is not None:
indexer.set_distance(xsweep.get_distance())
#if self.get_wavelength_prov() == 'user':
#index.set_wavelength(self.get_wavelength())
if xsweep.get_beam_centre() is not None:
indexer.set_beam_centre(xsweep.get_beam_centre())
if self._indxr_input_cell:
indexer.set_unit_cell(self._indxr_input_cell)
if self._indxr_input_lattice is not None:
spacegroup_number = lattice_to_spacegroup(
self._indxr_input_lattice)
indexer.set_space_group_number(spacegroup_number)
if not self._mosflm_autoindex_thresh:
try:
min_peaks = 200
Debug.write('Aiming for at least %d spots...' % min_peaks)
thresholds = []
for i in _images:
p = Printpeaks()
p.set_working_directory(self.get_working_directory())
auto_logfiler(p)
p.set_image(self.get_image_name(i))
thresh = p.threshold(min_peaks)
Debug.write('Autoindex threshold for image %d: %d' % \
(i, thresh))
thresholds.append(thresh)
thresh = min(thresholds)
self._mosflm_autoindex_thresh = thresh
except Exception as e:
print str(e) #XXX this should disappear!
Debug.write('Error computing threshold: %s' % str(e))
Debug.write('Using default of 20.0')
thresh = 20.0
else:
thresh = self._mosflm_autoindex_thresh
Debug.write('Using autoindex threshold: %d' % thresh)
if self._mosflm_autoindex_sol:
indexer.set_solution_number(self._mosflm_autoindex_sol)
indexer.set_threshold(thresh)
# now forget this to prevent weird things happening later on
if self._mosflm_autoindex_sol:
self._mosflm_autoindex_sol = 0
indexer.run()
indxr_cell = indexer.get_refined_unit_cell()
self._indxr_lattice = indexer.get_lattice()
space_group_number = indexer.get_indexed_space_group_number()
detector_distance = indexer.get_refined_distance()
beam_centre = indexer.get_refined_beam_centre()
mosaic_spreads = indexer.get_mosaic_spreads()
if min(list(indxr_cell)) < 10.0 and \
indxr_cell[2] / indxr_cell[0] > 6:
Debug.write('Unrealistic autoindexing solution: ' +
'%.2f %.2f %.2f %.2f %.2f %.2f' % indxr_cell)
# tweak some parameters and try again...
self._mosflm_autoindex_thresh *= 1.5
self.set_indexer_done(False)
return
intgr_params = {}
# look up other possible indexing solutions (not well - in
# standard settings only!) This is moved earlier as it could
# result in returning if Mosflm has selected the wrong
# solution!
try:
self._indxr_other_lattice_cell = indexer.get_solutions()
# Change 27/FEB/08 to support user assigned spacegroups
if self._indxr_user_input_lattice:
lattice_to_spacegroup_dict = {
'aP': 1,
'mP': 3,
'mC': 5,
'oP': 16,
'oC': 20,
'oF': 22,
'oI': 23,
'tP': 75,
'tI': 79,
'hP': 143,
'hR': 146,
'cP': 195,
'cF': 196,
'cI': 197
}
for k in self._indxr_other_lattice_cell.keys():
if lattice_to_spacegroup_dict[k] > \
lattice_to_spacegroup_dict[
self._indxr_input_lattice]:
del (self._indxr_other_lattice_cell[k])
# check that the selected unit cell matches - and if
# not raise a "horrible" exception
if self._indxr_input_cell:
assert indxr_cell is not None
for j in range(6):
if math.fabs(self._indxr_input_cell[j] -
indxr_cell[j]) > 2.0:
Chatter.write('Mosflm autoindexing did not select ' +
'correct (target) unit cell')
raise RuntimeError(
'something horrible happened in indexing')
except RuntimeError as e:
# check if mosflm rejected a solution we have it
if 'horribl' in str(e):
# ok it did - time to break out the big guns...
if not self._indxr_input_cell:
raise RuntimeError(
'error in solution selection when not preset')
# XXX FIXME
self._mosflm_autoindex_sol = _get_indexing_solution_number(
indexer.get_all_output(), self._indxr_input_cell,
self._indxr_input_lattice)
# set the fact that we are not done...
self.set_indexer_done(False)
# and return - hopefully this will restart everything
return
else:
raise e
if len(mosaic_spreads) == 0:
# then consider setting it do a default value...
# equal to the oscillation width (a good guess)
phi_width = self.get_phi_width()
Chatter.write(
'Mosaic estimation failed, so guessing at %4.2f' % \
phi_width)
# only consider this if we have thus far no idea on the
# mosaic spread...
mosaic_spreads.append(phi_width)
intgr_params['raster'] = indexer.get_raster()
intgr_params['separation'] = indexer.get_separation()
self._indxr_resolution_estimate = indexer.get_resolution_estimate()
# compute mosaic as mean(mosaic_spreads)
self._indxr_mosaic = sum(mosaic_spreads) / len(mosaic_spreads)
self._indxr_payload['mosflm_integration_parameters'] = intgr_params
self._indxr_payload['mosflm_orientation_matrix'] = open(
os.path.join(self.get_working_directory(), 'xiaindex.mat'),
'r').readlines()
import copy
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
from xia2.Wrappers.Mosflm.AutoindexHelpers import set_distance
from xia2.Wrappers.Mosflm.AutoindexHelpers import crystal_model_from_mosflm_mat
from cctbx import sgtbx, uctbx
# update the beam centre (i.e. shift the origin of the detector)
detector = copy.deepcopy(self.get_detector())
beam = copy.deepcopy(self.get_beam())
set_mosflm_beam_centre(detector, beam, beam_centre)
if detector_distance is not None:
set_distance(detector, detector_distance)
# make a dxtbx crystal_model object from the mosflm matrix
space_group = sgtbx.space_group_info(number=space_group_number).group()
crystal_model = crystal_model_from_mosflm_mat(
self._indxr_payload['mosflm_orientation_matrix'],
unit_cell=uctbx.unit_cell(tuple(indxr_cell)),
space_group=space_group)
# construct an experiment_list
from dxtbx.model import Experiment, ExperimentList
experiment = Experiment(beam=beam,
detector=detector,
goniometer=self.get_goniometer(),
scan=self.get_scan(),
crystal=crystal_model)
experiment_list = ExperimentList([experiment])
self.set_indexer_experiment_list(experiment_list)
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,
},
)
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.get_frame_offset(),
self._intgr_wedge[1] + self.get_frame_offset(),
)
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))
integrate.set_data_range(
self._intgr_wedge[0] + self.get_frame_offset(),
self._intgr_wedge[1] + self.get_frame_offset(),
)
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 "GXPARM.XDS" in self._xds_data_files:
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")
