def run():
try:
check_environment()
check()
except exceptions.Exception, e:
traceback.print_exc(file = open('xia2.error', 'w'))
Chatter.write('Status: error "%s"' % str(e))
def run():
if os.path.exists('xia2-working.phil'):
sys.argv.append('xia2-working.phil')
try:
check_environment()
except Exception as e:
traceback.print_exc(file=open('xia2.error', 'w'))
Chatter.write('Status: error "%s"' % str(e))
if len(sys.argv) < 2 or '-help' in sys.argv:
help()
sys.exit()
wd = os.getcwd()
try:
multi_crystal_analysis()
Chatter.write('Status: normal termination')
except Exception as e:
traceback.print_exc(file=open(os.path.join(wd, 'xia2.error'), 'w'))
Chatter.write('Status: error "%s"' % str(e))
Chatter.write(
'Please send the contents of xia2.txt, xia2.error and xia2-debug.txt to:'
)
Chatter.write('*****@*****.**')
sys.exit(1)
def load_reference_geometries(geometry_file_list):
from dxtbx.serialize import load
reference_components = []
for file in geometry_file_list:
try:
experiments = load.experiment_list(file, check_format=False)
assert len(experiments.detectors()) == 1
assert len(experiments.beams()) == 1
reference_detector = experiments.detectors()[0]
reference_beam = experiments.beams()[0]
except Exception:
datablock = load.datablock(file)
assert len(datablock) == 1
imageset = datablock[0].extract_imagesets()[0]
reference_detector = imageset.get_detector()
reference_beam = imageset.get_beam()
reference_components.append({
'detector': reference_detector,
'beam': reference_beam,
'file': file
})
import itertools
for combination in itertools.combinations(reference_components, 2):
if compare_geometries(combination[0]['detector'],
combination[1]['detector']):
from xia2.Handlers.Streams import Chatter
Chatter.write(
'Reference geometries given in %s and %s are too similar' %
(combination[0]['file'], combination[1]['file']))
raise Exception('Reference geometries too similar')
return reference_components
def _scale_finish_chunk_8_raddam(self):
crd = CCP4InterRadiationDamageDetector()
crd.set_working_directory(self.get_working_directory())
crd.set_hklin(self._scalr_scaled_reflection_files['mtz'])
if self.get_scaler_anomalous():
crd.set_anomalous(True)
hklout = os.path.join(self.get_working_directory(), 'temp.mtz')
FileHandler.record_temporary_file(hklout)
crd.set_hklout(hklout)
status = crd.detect()
if status:
Chatter.write('')
Chatter.banner('Local Scaling %s' % self._scalr_xname)
for s in status:
Chatter.write('%s %s' % s)
Chatter.banner('')
else:
Debug.write('Local scaling failed')
def run():
assert os.path.exists("xia2.json")
from xia2.Schema.XProject import XProject
xinfo = XProject.from_json(filename="xia2.json")
Chatter.write(xinfo.get_output())
write_citations()
def run(self):
"""Run dials.space_group"""
self.clear_command_line()
assert self._experiments_filename
assert self._reflections_filename
self.add_command_line(self._reflections_filename)
self.add_command_line(self._experiments_filename)
if not self._symmetrized_experiments:
self._symmetrized_experiments = os.path.join(
self.get_working_directory(),
"%i_symmetrized.expt" % self.get_xpid(),
)
self.add_command_line(
"output.experiments=%s" % self._symmetrized_experiments
)
self.start()
self.close_wait()
# check for errors
try:
self.check_for_errors()
except Exception:
Chatter.write(
"dials.space_group failed, see log file for more details:\n %s"
% self.get_log_file()
)
raise
Debug.write("dials.space_group status: OK")
def run_one_sweep(args):
from xia2.Handlers.Streams import Debug
assert len(args) == 3
s, failover, job_type = args
if job_type:
DriverFactory.set_driver_type(job_type)
Chatter.cache()
Debug.cache()
try:
s.get_integrater_intensities()
except Exception as e:
if failover:
Chatter.write('Processing sweep %s failed: %s' % \
(s.get_name(), str(e)))
s = None
else:
raise
finally:
Chatter.uncache()
Debug.uncache()
return s
def load_reference_geometries(geometry_file_list):
from dxtbx.serialize import load
reference_components = []
for file in geometry_file_list:
try:
experiments = load.experiment_list(file, check_format=False)
assert len(experiments.detectors()) == 1
assert len(experiments.beams()) == 1
reference_detector = experiments.detectors()[0]
reference_beam = experiments.beams()[0]
except Exception:
experiments = load.experiment_list(file)
imageset = experiments.imagesets()[0]
reference_detector = imageset.get_detector()
reference_beam = imageset.get_beam()
reference_components.append(
{"detector": reference_detector, "beam": reference_beam, "file": file}
)
import itertools
for combination in itertools.combinations(reference_components, 2):
if compare_geometries(combination[0]["detector"], combination[1]["detector"]):
from xia2.Handlers.Streams import Chatter
Chatter.write(
"Reference geometries given in %s and %s are too similar"
% (combination[0]["file"], combination[1]["file"])
)
raise Exception("Reference geometries too similar")
return reference_components
def _scale_finish_chunk_7_twinning(self):
hklout = self._scalr_scaled_reflection_files['mtz']
m = mtz.object(hklout)
# FIXME in here should be able to just drop down to the lowest symmetry
# space group with the rotational elements for this calculation? I.e.
# P422 for P4/mmm?
if not m.space_group().is_centric():
from xia2.Toolkit.E4 import E4_mtz
E4s = E4_mtz(hklout, native=True)
self._scalr_twinning_score = E4s.items()[0][1]
if self._scalr_twinning_score > 1.9:
self._scalr_twinning_conclusion = 'Your data do not appear twinned'
elif self._scalr_twinning_score < 1.6:
self._scalr_twinning_conclusion = 'Your data appear to be twinned'
else:
self._scalr_twinning_conclusion = 'Ambiguous score (1.6 < score < 1.9)'
else:
self._scalr_twinning_conclusion = 'Data are centric'
self._scalr_twinning_score = 0
Chatter.write('Overall twinning score: %4.2f' %
self._scalr_twinning_score)
Chatter.write(self._scalr_twinning_conclusion)
def get_new_scales_file(self):
'''Get the file to which the scales have been written.'''
if self._new_scales_file:
if not os.path.isfile(os.path.join(self.get_working_directory(), self._new_scales_file)):
Chatter.write(
"Aimless did not scale the data, see log file for more details:\n %s" %self.get_log_file())
raise RuntimeError, 'data not scaled'
return os.path.join(self.get_working_directory(), self._new_scales_file)
def run():
if os.path.exists('xia2-working.phil'):
sys.argv.append('xia2-working.phil')
try:
check_environment()
except exceptions.Exception, e:
traceback.print_exc(file = open('xia2.error', 'w'))
Chatter.write('Status: error "%s"' % str(e))
def which(pgm, debug=False):
path = os.getenv('PATH')
for p in path.split(os.path.pathsep):
p = os.path.join(p, pgm)
if debug:
Chatter.write('Seeking %s' % p)
if os.path.exists(p) and os.access(p, os.X_OK):
return p
def get_new_scales_file(self):
'''Get the file to which the scales have been written.'''
if self._new_scales_file:
if not os.path.isfile(os.path.join(self.get_working_directory(), self._new_scales_file)):
Chatter.write(
"Aimless did not scale the data, see log file for more details:\n %s" %self.get_log_file())
raise RuntimeError('data not scaled')
return os.path.join(self.get_working_directory(), self._new_scales_file)
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 perform integration until we think we are done...'''
while not self.get_integrater_finish_done():
while not self.get_integrater_done():
while not self.get_integrater_prepare_done():
Debug.write('Preparing to do some integration...')
self.set_integrater_prepare_done(True)
# if this raises an exception, perhaps the autoindexing
# solution has too high symmetry. if this the case, then
# perform a self._intgr_indexer.eliminate() - this should
# reset the indexing system
try:
self._integrate_prepare()
except BadLatticeError, e:
Journal.banner('eliminated this lattice', size = 80)
Chatter.write('Rejecting bad lattice %s' % str(e))
self._intgr_refiner.eliminate()
self._integrater_reset()
# FIXME x1698 - may be the case that _integrate() returns the
# raw intensities, _integrate_finish() returns intensities
# which may have been adjusted or corrected. See #1698 below.
Debug.write('Doing some integration...')
self.set_integrater_done(True)
template = self.get_integrater_sweep().get_template()
if self._intgr_sweep_name:
if PhilIndex.params.xia2.settings.show_template:
Chatter.banner('Integrating %s (%s)' % \
(self._intgr_sweep_name, template))
else:
Chatter.banner('Integrating %s' % \
(self._intgr_sweep_name))
try:
#1698
self._intgr_hklout_raw = self._integrate()
except BadLatticeError, e:
Chatter.write('Rejecting bad lattice %s' % str(e))
Journal.banner('eliminated this lattice', size = 80)
self._intgr_refiner.eliminate()
self._integrater_reset()
def _index_prepare(self):
Chatter.banner('Spotfinding %s' % self.get_indexer_sweep_name())
super(XDSIndexerII, self)._index_prepare()
from dials.array_family import flex
from dials.util.ascii_art import spot_counts_per_image_plot
reflection_pickle = spot_xds_to_reflection_pickle(
self._indxr_payload['SPOT.XDS'],
working_directory=self.get_working_directory())
refl = flex.reflection_table.from_pickle(reflection_pickle)
Chatter.write(spot_counts_per_image_plot(refl), strip=False)
def run():
from libtbx.utils import Sorry
if len(sys.argv) < 2 or '-help' in sys.argv or '--help' in sys.argv:
help()
sys.exit()
try:
check_environment()
except exceptions.Exception, e:
traceback.print_exc(file = open('xia2.error', 'w'))
Chatter.write('Status: error "%s"' % str(e))
def _index_prepare(self):
Chatter.banner('Spotfinding %s' %self.get_indexer_sweep_name())
super(XDSIndexerII, self)._index_prepare()
from dials.array_family import flex
from dials.util.ascii_art import spot_counts_per_image_plot
reflection_pickle = spot_xds_to_reflection_pickle(
self._indxr_payload['SPOT.XDS'],
working_directory=self.get_working_directory())
refl = flex.reflection_table.from_pickle(reflection_pickle)
Chatter.write(spot_counts_per_image_plot(refl), strip=False)
def eliminate(self, indxr_print = True):
'''Eliminate the highest currently allowed lattice.'''
if len(self._sorted_list) <= 1:
raise RuntimeError, 'cannot eliminate only solution'
if indxr_print:
Chatter.write('Eliminating indexing solution:')
Chatter.write(self.repr()[0])
self._sorted_list = self._sorted_list[1:]
def eliminate(self, indxr_print=True):
"""Eliminate the highest currently allowed lattice."""
if len(self._sorted_list) <= 1:
raise RuntimeError("cannot eliminate only solution")
if indxr_print:
Chatter.write("Eliminating indexing solution:")
Chatter.write(self.repr()[0])
self._sorted_list = self._sorted_list[1:]
def which(pgm, debug=False):
# python equivalent to the 'which' command
# http://stackoverflow.com/questions/9877462/is-there-a-python-equivalent-to-the-which-command
# FIXME this will not work on Windows as you need to check that there is a
# .bat or a .exe extension
# FIXME also this is implemented in Driver/DriverHelper.py:executable_exists
path = os.getenv('PATH')
for p in path.split(os.path.pathsep):
p = os.path.join(p, pgm)
if debug:
Chatter.write('Seeking %s' % p)
if os.path.exists(p) and os.access(p, os.X_OK):
return p
def run(self):
from xia2.Handlers.Streams import Chatter, Debug
Debug.write('Running dials.refine')
self.clear_command_line()
self.add_command_line(self._experiments_filename)
self.add_command_line(self._indexed_filename)
self.add_command_line('scan_varying=%s' % self._scan_varying)
if self._close_to_spindle_cutoff is not None:
self.add_command_line(
'close_to_spindle_cutoff=%f' %self._close_to_spindle_cutoff)
if self._outlier_algorithm:
self.add_command_line('outlier.algorithm=%s' % self._outlier_algorithm)
self._refined_experiments_filename = os.path.join(
self.get_working_directory(),
'%s_refined_experiments.json' % self.get_xpid())
self.add_command_line(
'output.experiments=%s' % self._refined_experiments_filename)
self._refined_filename = os.path.join(
self.get_working_directory(), '%s_refined.pickle' % self.get_xpid())
self.add_command_line('output.reflections=%s' % self._refined_filename)
if self._reflections_per_degree is not None:
self.add_command_line(
'reflections_per_degree=%i' %self._reflections_per_degree)
if self._interval_width_degrees is not None:
self.add_command_line(
'unit_cell.smoother.interval_width_degrees=%i' % self._interval_width_degrees)
self.add_command_line(
'orientation.smoother.interval_width_degrees=%i' % self._interval_width_degrees)
if self._detector_fix:
self.add_command_line('detector.fix=%s' % self._detector_fix)
if self._beam_fix:
self.add_command_line('beam.fix=%s' % self._beam_fix)
if self._phil_file is not None:
self.add_command_line('%s' %self._phil_file)
self.start()
self.close_wait()
if not os.path.isfile(self._refined_filename) or \
not os.path.isfile(self._refined_experiments_filename):
Chatter.write(
"DIALS did not refine the data, see log file for more details:\n %s" %self.get_log_file())
raise RuntimeError, 'data not refined'
for record in self.get_all_output():
if 'Sorry: Too few reflections to' in record:
raise RuntimeError, record.strip()
self.check_for_errors()
return
def make_logfile_html(logfile):
tables = extract_loggraph_tables(logfile)
if not tables:
return
rst = []
## local files in xia2 distro
#c3css = os.path.join(xia2_root_dir, 'c3', 'c3.css')
#c3js = os.path.join(xia2_root_dir, 'c3', 'c3.min.js')
#d3js = os.path.join(xia2_root_dir, 'd3', 'd3.min.js')
# webhosted files
c3css = 'https://cdnjs.cloudflare.com/ajax/libs/c3/0.4.10/c3.css'
c3js = 'https://cdnjs.cloudflare.com/ajax/libs/c3/0.4.10/c3.min.js'
d3js = 'https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min.js'
rst.append('.. raw:: html')
rst.append('\n '.join([
'', '<!-- Load c3.css -->',
'<link href="%s" rel="stylesheet" type="text/css">' % c3css,
'<!-- Load d3.js and c3.js -->',
'<script src="%s" charset="utf-8"></script>' % d3js,
'<script src="%s"></script>' % c3js, ''
]))
for table in tables:
try:
#for graph_name, html in table_to_google_charts(table).iteritems():
for graph_name, html in table_to_c3js_charts(table).iteritems():
#rst.append('.. __%s:\n' %graph_name)
rst.append('.. raw:: html')
rst.append('\n '.join(html.split('\n')))
except Exception as e:
Chatter.write('=' * 80)
Chatter.write('Error (%s) while processing table' % str(e))
Chatter.write(" '%s'" % table.title)
Chatter.write('in %s' % logfile)
Chatter.write('=' * 80)
Debug.write(
'Exception raised while processing log file %s, table %s' %
(logfile, table.title))
Debug.write(traceback.format_exc())
rst = '\n'.join(rst)
html_file = '%s.html' % (os.path.splitext(logfile)[0])
with open(html_file, 'wb') as f:
f.write(rst2html(rst))
return html_file
def run():
if os.path.exists("xia2-working.phil"):
sys.argv.append("xia2-working.phil")
try:
check_environment()
except Exception as e:
traceback.print_exc(file=open("xia2.error", "w"))
Chatter.write('Status: error "%s"' % str(e))
# print the version
Chatter.write(Version)
Citations.cite("xia2")
start_time = time.time()
assert os.path.exists("xia2.json")
from xia2.Schema.XProject import XProject
xinfo = XProject.from_json(filename="xia2.json")
crystals = xinfo.get_crystals()
for crystal_id, crystal in crystals.iteritems():
# cwd = os.path.abspath(os.curdir)
from libtbx import Auto
scale_dir = PhilIndex.params.xia2.settings.scale.directory
if scale_dir is Auto:
scale_dir = "scale"
i = 0
while os.path.exists(os.path.join(crystal.get_name(), scale_dir)):
i += 1
scale_dir = "scale%i" % i
PhilIndex.params.xia2.settings.scale.directory = scale_dir
working_directory = Environment.generate_directory(
[crystal.get_name(), scale_dir])
# os.chdir(working_directory)
crystals[crystal_id]._scaler = None # reset scaler
scaler = crystal._get_scaler()
Chatter.write(xinfo.get_output())
crystal.serialize()
duration = time.time() - start_time
# write out the time taken in a human readable way
Chatter.write("Processing took %s" %
time.strftime("%Hh %Mm %Ss", time.gmtime(duration)))
# delete all of the temporary mtz files...
cleanup()
write_citations()
xinfo.as_json(filename="xia2.json")
Environment.cleanup()
def run(self):
"""Run dials.merge"""
self.clear_command_line()
assert self._experiments_filename
assert self._reflections_filename
self.add_command_line(self._reflections_filename)
self.add_command_line(self._experiments_filename)
self.add_command_line("truncate=%s" % self._truncate)
if self._mtz_filename:
self.add_command_line("output.mtz=%s" % self._mtz_filename)
if self._project_name:
self.add_command_line("output.project_name=%s" %
self._project_name)
if self._crystal_names:
self.add_command_line("output.crystal_names=%s" %
self._crystal_names)
if self._dataset_names:
self.add_command_line("output.dataset_names=%s" %
self._dataset_names)
if self._partiality_threshold:
self.add_command_line("partiality_threshold=%s" %
self._partiality_threshold)
self.start()
self.close_wait()
# check for errors
try:
self.check_for_errors()
except Exception:
Chatter.write(
"dials.merge failed, see log file for more details:\n %s"
% self.get_log_file())
raise
Debug.write("dials.merge status: OK")
def run():
try:
check_environment()
except Exception as e:
with open("xia2.error", "w") as fh:
traceback.print_exc(file=fh)
Chatter.write('Status: error "%s"' % str(e))
sys.exit(1)
if len(sys.argv) < 2 or "-help" in sys.argv:
help()
sys.exit()
wd = os.getcwd()
try:
from xia2.command_line.xia2_main import xia2_main
xia2_main(stop_after="integrate")
Chatter.write("Status: normal termination")
except Exception as e:
with open(os.path.join(wd, "xia2.error"), "w") as fh:
traceback.print_exc(file=fh)
Chatter.write('Status: error "%s"' % str(e))
sys.exit(1)
def run_one_sweep(args):
from xia2.Handlers.Streams import Debug
assert len(args) == 3
s, failover, job_type = args
if job_type:
DriverFactory.set_driver_type(job_type)
Chatter.cache()
Debug.cache()
try:
s.get_integrater_intensities()
except Exception, e:
if failover:
Chatter.write('Processing sweep %s failed: %s' % \
(s.get_name(), str(e)))
s = None
else:
raise
def make_logfile_html(logfile):
tables = extract_loggraph_tables(logfile)
if not tables:
return
rst = []
for table in tables:
try:
#for graph_name, html in table_to_google_charts(table).iteritems():
for graph_name, html in table_to_c3js_charts(table).iteritems():
#rst.append('.. __%s:\n' %graph_name)
rst.append('.. raw:: html')
rst.append('\n '.join(html.split('\n')))
except StandardError, e:
Chatter.write('=' * 80)
Chatter.write('Error (%s) while processing table' % str(e))
Chatter.write(" '%s'" % table.title)
Chatter.write('in %s' % logfile)
Chatter.write('=' * 80)
Debug.write('Exception raised while processing log file %s, table %s' % (logfile, table.title))
Debug.write(traceback.format_exc())
def write_citations():
# tell the user which programs were used...
Chatter.write("XIA2 used... %s" % ", ".join(Citations.get_programs()))
Chatter.write(
"Here are the appropriate citations (BIBTeX in xia2-citations.bib.)")
for citation in Citations.get_citations_acta():
Chatter.write(citation)
# and write the bibtex versions
out = open("xia2-citations.bib", "w")
for citation in Citations.get_citations():
out.write("%s\n" % citation)
out.close()
def write_citations():
# tell the user which programs were used...
Chatter.write('XIA2 used... %s' % \
', '.join(Citations.get_programs()))
Chatter.write(
'Here are the appropriate citations (BIBTeX in xia2-citations.bib.)')
for citation in Citations.get_citations_acta():
Chatter.write(citation)
# and write the bibtex versions
out = open('xia2-citations.bib', 'w')
for citation in Citations.get_citations():
out.write('%s\n' % citation)
out.close()
def run():
try:
check_environment()
except Exception as e:
traceback.print_exc(file = open('xia2.error', 'w'))
Chatter.write('Status: error "%s"' % str(e))
if len(sys.argv) < 2 or '-help' in sys.argv:
help()
sys.exit()
wd = os.getcwd()
try:
from xia2.command_line.xia2_main import xia2_main
xia2_main(stop_after='integrate')
Chatter.write('Status: normal termination')
except Exception as e:
traceback.print_exc(file = open(os.path.join(wd, 'xia2.error'), 'w'))
Chatter.write('Status: error "%s"' % str(e))
def _integrate_finish(self):
'''Finish off the integration by running correct.'''
# first run the postrefinement etc with spacegroup P1
# and the current unit cell - this will be used to
# obtain a benchmark rmsd in pixels / phi and also
# cell deviations (this is working towards spotting bad
# indexing solutions) - only do this if we have no
# reindex matrix... and no postrefined cell...
p1_deviations = None
# fix for bug # 3264 -
# if we have not run integration with refined parameters, make it so...
# erm? shouldn't this therefore return if this is the principle, or
# set the flag after we have tested the lattice?
if not self._xds_data_files.has_key('GXPARM.XDS') and \
PhilIndex.params.xds.integrate.reintegrate:
Debug.write(
'Resetting integrater, to ensure refined orientation is used')
self.set_integrater_done(False)
if not self.get_integrater_reindex_matrix() and not self._intgr_cell \
and not Flags.get_no_lattice_test() and \
not self.get_integrater_sweep().get_user_lattice():
correct = self.Correct()
correct.set_data_range(self._intgr_wedge[0],
self._intgr_wedge[1])
if self.get_polarization() > 0.0:
correct.set_polarization(self.get_polarization())
# FIXME should this be using the correctly transformed
# cell or are the results ok without it?!
correct.set_spacegroup_number(1)
correct.set_cell(self._intgr_refiner_cell)
correct.run()
# record the log file -
pname, xname, dname = self.get_integrater_project_info()
sweep = self.get_integrater_sweep_name()
FileHandler.record_log_file('%s %s %s %s CORRECT' % \
(pname, xname, dname, sweep),
os.path.join(
self.get_working_directory(),
'CORRECT.LP'))
FileHandler.record_more_data_file(
'%s %s %s %s CORRECT' % (pname, xname, dname, sweep),
os.path.join(self.get_working_directory(), 'XDS_ASCII.HKL'))
cell = correct.get_result('cell')
cell_esd = correct.get_result('cell_esd')
Debug.write('Postrefinement in P1 results:')
Debug.write('%7.3f %7.3f %7.3f %7.3f %7.3f %7.3f' % \
tuple(cell))
Debug.write('%7.3f %7.3f %7.3f %7.3f %7.3f %7.3f' % \
tuple(cell_esd))
Debug.write('Deviations: %.2f pixels %.2f degrees' % \
(correct.get_result('rmsd_pixel'),
correct.get_result('rmsd_phi')))
p1_deviations = (correct.get_result('rmsd_pixel'),
correct.get_result('rmsd_phi'))
# next run the postrefinement etc with the given
# cell / lattice - this will be the assumed result...
correct = self.Correct()
correct.set_data_range(self._intgr_wedge[0],
self._intgr_wedge[1])
if self.get_polarization() > 0.0:
correct.set_polarization(self.get_polarization())
# BUG # 2695 probably comes from here - need to check...
# if the pointless interface comes back with a different
# crystal setting then the unit cell stored in self._intgr_cell
# needs to be set to None...
if self.get_integrater_spacegroup_number():
correct.set_spacegroup_number(
self.get_integrater_spacegroup_number())
if not self._intgr_cell:
raise RuntimeError, 'no unit cell to recycle'
correct.set_cell(self._intgr_cell)
# BUG # 3113 - new version of XDS will try and figure the
# best spacegroup out from the intensities (and get it wrong!)
# unless we set the spacegroup and cell explicitly
if not self.get_integrater_spacegroup_number():
cell = self._intgr_refiner_cell
lattice = self._intgr_refiner.get_refiner_lattice()
spacegroup_number = lattice_to_spacegroup_number(lattice)
# this should not prevent the postrefinement from
# working correctly, else what is above would not
# work correctly (the postrefinement test)
correct.set_spacegroup_number(spacegroup_number)
correct.set_cell(cell)
Debug.write('Setting spacegroup to: %d' % spacegroup_number)
Debug.write(
'Setting cell to: %.2f %.2f %.2f %.2f %.2f %.2f' % tuple(cell))
if self.get_integrater_reindex_matrix():
# bug! if the lattice is not primitive the values in this
# reindex matrix need to be multiplied by a constant which
# depends on the Bravais lattice centering.
lattice = self._intgr_refiner.get_refiner_lattice()
import scitbx.matrix
matrix = self.get_integrater_reindex_matrix()
matrix = scitbx.matrix.sqr(matrix).transpose().elems
matrix = r_to_rt(matrix)
if lattice[1] == 'P':
mult = 1
elif lattice[1] == 'C' or lattice[1] == 'I':
mult = 2
elif lattice[1] == 'R':
mult = 3
elif lattice[1] == 'F':
mult = 4
else:
raise RuntimeError, 'unknown multiplier for lattice %s' % \
lattice
Debug.write('REIDX multiplier for lattice %s: %d' % \
(lattice, mult))
mult_matrix = [mult * m for m in matrix]
Debug.write('REIDX set to %d %d %d %d %d %d %d %d %d %d %d %d' % \
tuple(mult_matrix))
correct.set_reindex_matrix(mult_matrix)
correct.run()
# erm. just to be sure
if self.get_integrater_reindex_matrix() and \
correct.get_reindex_used():
raise RuntimeError, 'Reindex panic!'
# get the reindex operation used, which may be useful if none was
# set but XDS decided to apply one, e.g. #419.
if not self.get_integrater_reindex_matrix() and \
correct.get_reindex_used():
# convert this reindex operation to h, k, l form: n.b. this
# will involve dividing through by the lattice centring multiplier
matrix = rt_to_r(correct.get_reindex_used())
import scitbx.matrix
matrix = scitbx.matrix.sqr(matrix).transpose().elems
lattice = self._intgr_refiner.get_refiner_lattice()
if lattice[1] == 'P':
mult = 1.0
elif lattice[1] == 'C' or lattice[1] == 'I':
mult = 2.0
elif lattice[1] == 'R':
mult = 3.0
elif lattice[1] == 'F':
mult = 4.0
matrix = [m / mult for m in matrix]
reindex_op = mat_to_symop(matrix)
# assign this to self: will this reset?! make for a leaky
# abstraction and just assign this...
# self.set_integrater_reindex_operator(reindex)
self._intgr_reindex_operator = reindex_op
# record the log file -
pname, xname, dname = self.get_integrater_project_info()
sweep = self.get_integrater_sweep_name()
FileHandler.record_log_file('%s %s %s %s CORRECT' % \
(pname, xname, dname, sweep),
os.path.join(self.get_working_directory(),
'CORRECT.LP'))
# should get some interesting stuff from the XDS correct file
# here, for instance the resolution range to use in integration
# (which should be fed back if not fast) and so on...
self._intgr_corrected_hklout = os.path.join(self.get_working_directory(),
'XDS_ASCII.HKL')
# also record the batch range - needed for the analysis of the
# radiation damage in chef...
self._intgr_batches_out = (self._intgr_wedge[0],
self._intgr_wedge[1])
# FIXME perhaps I should also feedback the GXPARM file here??
for file in ['GXPARM.XDS']:
self._xds_data_files[file] = correct.get_output_data_file(file)
# record the postrefined cell parameters
self._intgr_cell = correct.get_result('cell')
self._intgr_n_ref = correct.get_result('n_ref')
Debug.write('Postrefinement in "correct" spacegroup results:')
Debug.write('%7.3f %7.3f %7.3f %7.3f %7.3f %7.3f' % \
tuple(correct.get_result('cell')))
Debug.write('%7.3f %7.3f %7.3f %7.3f %7.3f %7.3f' % \
tuple(correct.get_result('cell_esd')))
Debug.write('Deviations: %.2f pixels %.2f degrees' % \
(correct.get_result('rmsd_pixel'),
correct.get_result('rmsd_phi')))
Debug.write('Error correction parameters: A=%.3f B=%.3f' % \
correct.get_result('sdcorrection'))
# compute misorientation of axes
xparm_file = os.path.join(self.get_working_directory(), 'GXPARM.XDS')
from iotbx.xds import xparm
handle = xparm.reader()
handle.read_file(xparm_file)
rotn = handle.rotation_axis
beam = handle.beam_vector
dot = sum([rotn[j] * beam[j] for j in range(3)])
r = math.sqrt(sum([rotn[j] * rotn[j] for j in range(3)]))
b = math.sqrt(sum([beam[j] * beam[j] for j in range(3)]))
rtod = 180.0 / math.pi
angle = rtod * math.fabs(0.5 * math.pi - math.acos(dot / (r * b)))
Debug.write('Axis misalignment %.2f degrees' % angle)
correct_deviations = (correct.get_result('rmsd_pixel'),
correct.get_result('rmsd_phi'))
if p1_deviations:
# compare and reject if both > 50% higher - though adding a little
# flexibility - 0.5 pixel / osc width slack.
pixel = p1_deviations[0]
phi = math.sqrt(0.05 * 0.05 + \
p1_deviations[1] * p1_deviations[1])
threshold = Flags.get_rejection_threshold()
Debug.write('RMSD ratio: %.2f' % (correct_deviations[0] / pixel))
Debug.write('RMSPhi ratio: %.2f' % (correct_deviations[1] / phi))
if correct_deviations[0] / pixel > threshold and \
correct_deviations[1] / phi > threshold:
Chatter.write(
'Eliminating this indexing solution as postrefinement')
Chatter.write(
'deviations rather high relative to triclinic')
raise BadLatticeError, \
'high relative deviations in postrefinement'
if not Flags.get_quick() and Flags.get_remove():
# check for alien reflections and perhaps recycle - removing them
if len(correct.get_remove()) > 0:
correct_remove = correct.get_remove()
current_remove = []
final_remove = []
# first ensure that there are no duplicate entries...
if os.path.exists(os.path.join(
self.get_working_directory(),
'REMOVE.HKL')):
for line in open(os.path.join(
self.get_working_directory(),
'REMOVE.HKL'), 'r').readlines():
h, k, l = map(int, line.split()[:3])
z = float(line.split()[3])
if not (h, k, l, z) in current_remove:
current_remove.append((h, k, l, z))
for c in correct_remove:
if c in current_remove:
continue
final_remove.append(c)
Debug.write(
'%d alien reflections are already removed' % \
(len(correct_remove) - len(final_remove)))
else:
# we want to remove all of the new dodgy reflections
final_remove = correct_remove
remove_hkl = open(os.path.join(
self.get_working_directory(),
'REMOVE.HKL'), 'w')
z_min = Flags.get_z_min()
rejected = 0
# write in the old reflections
for remove in current_remove:
z = remove[3]
if z >= z_min:
remove_hkl.write('%d %d %d %f\n' % remove)
else:
rejected += 1
Debug.write('Wrote %d old reflections to REMOVE.HKL' % \
(len(current_remove) - rejected))
Debug.write('Rejected %d as z < %f' % \
(rejected, z_min))
# and the new reflections
rejected = 0
used = 0
for remove in final_remove:
z = remove[3]
if z >= z_min:
used += 1
remove_hkl.write('%d %d %d %f\n' % remove)
else:
rejected += 1
Debug.write('Wrote %d new reflections to REMOVE.HKL' % \
(len(final_remove) - rejected))
Debug.write('Rejected %d as z < %f' % \
(rejected, z_min))
remove_hkl.close()
# we want to rerun the finishing step so...
# unless we have added no new reflections... or unless we
# have not confirmed the point group (see SCI-398)
if used and self.get_integrater_reindex_matrix():
self.set_integrater_finish_done(False)
else:
Debug.write(
'Going quickly so not removing %d outlier reflections...' % \
len(correct.get_remove()))
# Convert INTEGRATE.HKL to MTZ format and reapply any reindexing operations
# spacegroup changes to allow use with CCP4 / Aimless for scaling
integrate_hkl = os.path.join(
self.get_working_directory(), 'INTEGRATE.HKL')
hklout = os.path.splitext(integrate_hkl)[0] + ".mtz"
self._factory.set_working_directory(self.get_working_directory())
pointless = self._factory.Pointless()
pointless.set_xdsin(integrate_hkl)
pointless.set_hklout(hklout)
pointless.xds_to_mtz()
integrate_mtz = hklout
if self.get_integrater_reindex_operator() or \
self.get_integrater_spacegroup_number():
Debug.write('Reindexing things to MTZ')
reindex = Reindex()
reindex.set_working_directory(self.get_working_directory())
auto_logfiler(reindex)
if self.get_integrater_reindex_operator():
reindex.set_operator(self.get_integrater_reindex_operator())
if self.get_integrater_spacegroup_number():
reindex.set_spacegroup(self.get_integrater_spacegroup_number())
hklout = '%s_reindex.mtz' % os.path.splitext(integrate_mtz)[0]
reindex.set_hklin(integrate_mtz)
reindex.set_hklout(hklout)
reindex.reindex()
integrate_mtz = hklout
return integrate_mtz
def index(self):
if not self.get_indexer_finish_done():
f = inspect.currentframe().f_back.f_back
m = f.f_code.co_filename
l = f.f_lineno
Debug.write(
"Index in %s called from %s %d" % (self.__class__.__name__, m, l)
)
while not self.get_indexer_finish_done():
while not self.get_indexer_done():
while not self.get_indexer_prepare_done():
# --------------
# call prepare()
# --------------
self.set_indexer_prepare_done(True)
self._index_prepare()
# --------------------------------------------
# then do the proper indexing - using the best
# solution already stored if available (c/f
# eliminate above)
# --------------------------------------------
self.set_indexer_done(True)
if self.get_indexer_sweeps():
xsweeps = [s.get_name() for s in self.get_indexer_sweeps()]
if len(xsweeps) > 1:
# find "SWEEPn, SWEEP(n+1), (..), SWEEPm" and aggregate to "SWEEPS n-m"
xsweeps = map(
lambda x: (int(x[5:]), int(x[5:]))
if x.startswith("SWEEP")
else x,
xsweeps,
)
xsweeps[0] = [xsweeps[0]]
def compress(seen, nxt):
if (
isinstance(seen[-1], tuple)
and isinstance(nxt, tuple)
and (seen[-1][1] + 1 == nxt[0])
):
seen[-1] = (seen[-1][0], nxt[1])
else:
seen.append(nxt)
return seen
xsweeps = reduce(compress, xsweeps)
xsweeps = map(
lambda x: (
"SWEEP%d" % x[0]
if x[0] == x[1]
else "SWEEPS %d to %d" % (x[0], x[1])
)
if isinstance(x, tuple)
else x,
xsweeps,
)
if len(xsweeps) > 1:
sweep_names = ", ".join(xsweeps[:-1])
sweep_names += " & " + xsweeps[-1]
else:
sweep_names = xsweeps[0]
if PhilIndex.params.xia2.settings.show_template:
template = self.get_indexer_sweep().get_template()
Chatter.banner("Autoindexing %s (%s)" % (sweep_names, template))
else:
Chatter.banner("Autoindexing %s" % sweep_names)
if not self._indxr_helper:
result = self._index()
if not self._indxr_done:
Debug.write("Looks like indexing failed - try again!")
continue
solutions = {}
for k in self._indxr_other_lattice_cell.keys():
solutions[k] = self._indxr_other_lattice_cell[k]["cell"]
# create a helper for the indexer to manage solutions
self._indxr_helper = _IndexerHelper(solutions)
solution = self._indxr_helper.get()
# compare these against the final solution, if different
# reject solution and return - correct solution will
# be used next cycle
if (
self._indxr_lattice != solution[0]
and not self._indxr_input_cell
and not PhilIndex.params.xia2.settings.integrate_p1
):
Chatter.write(
"Rerunning indexing lattice %s to %s"
% (self._indxr_lattice, solution[0])
)
Debug.write(
"Rerunning indexing with target lattice %s" % solution[0]
)
self.set_indexer_done(False)
else:
# rerun autoindexing with the best known current solution
solution = self._indxr_helper.get()
self._indxr_input_lattice = solution[0]
self._indxr_input_cell = solution[1]
result = self._index()
# next finish up...
self.set_indexer_finish_done(True)
self._index_finish()
if self._indxr_print:
Chatter.write(self.show_indexer_solutions())
def _index_prepare(self):
from xia2.Handlers.Citations import Citations
Citations.cite('dials')
#all_images = self.get_matching_images()
#first = min(all_images)
#last = max(all_images)
spot_lists = []
datablocks = []
for imageset, xsweep in zip(self._indxr_imagesets, self._indxr_sweeps):
Chatter.banner('Spotfinding %s' % xsweep.get_name())
first, last = imageset.get_scan().get_image_range()
# at this stage, break out to run the DIALS code: this sets itself up
# now cheat and pass in some information... save re-reading all of the
# image headers
# FIXME need to adjust this to allow (say) three chunks of images
from dxtbx.serialize import dump
from dxtbx.datablock import DataBlock
sweep_filename = os.path.join(
self.get_working_directory(),
'%s_datablock.json' % xsweep.get_name())
dump.datablock(DataBlock([imageset]), sweep_filename)
genmask = self.GenerateMask()
genmask.set_input_datablock(sweep_filename)
genmask.set_output_datablock(
os.path.join(
self.get_working_directory(), '%s_%s_datablock.json' %
(genmask.get_xpid(), xsweep.get_name())))
genmask.set_params(PhilIndex.params.dials.masking)
sweep_filename, mask_pickle = genmask.run()
Debug.write('Generated mask for %s: %s' %
(xsweep.get_name(), mask_pickle))
gain = PhilIndex.params.xia2.settings.input.gain
if gain is libtbx.Auto:
gain_estimater = self.EstimateGain()
gain_estimater.set_sweep_filename(sweep_filename)
gain_estimater.run()
gain = gain_estimater.get_gain()
Chatter.write('Estimated gain: %.2f' % gain)
PhilIndex.params.xia2.settings.input.gain = gain
# FIXME this should really use the assigned spot finding regions
#offset = self.get_frame_offset()
spotfinder = self.Spotfinder()
if last - first > 10:
spotfinder.set_write_hot_mask(True)
spotfinder.set_input_sweep_filename(sweep_filename)
spotfinder.set_output_sweep_filename(
'%s_%s_datablock.json' %
(spotfinder.get_xpid(), xsweep.get_name()))
spotfinder.set_input_spot_filename(
'%s_%s_strong.pickle' %
(spotfinder.get_xpid(), xsweep.get_name()))
if PhilIndex.params.dials.fast_mode:
wedges = self._index_select_images_i(imageset)
spotfinder.set_scan_ranges(wedges)
else:
spotfinder.set_scan_ranges([(first, last)])
if PhilIndex.params.dials.find_spots.phil_file is not None:
spotfinder.set_phil_file(
PhilIndex.params.dials.find_spots.phil_file)
min_spot_size = PhilIndex.params.dials.find_spots.min_spot_size
if min_spot_size is libtbx.Auto:
if imageset.get_detector()[0].get_type() == 'SENSOR_PAD':
min_spot_size = 3
else:
min_spot_size = None
if min_spot_size is not None:
spotfinder.set_min_spot_size(min_spot_size)
min_local = PhilIndex.params.dials.find_spots.min_local
if min_local is not None:
spotfinder.set_min_local(min_local)
sigma_strong = PhilIndex.params.dials.find_spots.sigma_strong
if sigma_strong:
spotfinder.set_sigma_strong(sigma_strong)
gain = PhilIndex.params.xia2.settings.input.gain
if gain:
spotfinder.set_gain(gain)
filter_ice_rings = PhilIndex.params.dials.find_spots.filter_ice_rings
if filter_ice_rings:
spotfinder.set_filter_ice_rings(filter_ice_rings)
kernel_size = PhilIndex.params.dials.find_spots.kernel_size
if kernel_size:
spotfinder.set_kernel_size(kernel_size)
global_threshold = PhilIndex.params.dials.find_spots.global_threshold
if global_threshold is not None:
spotfinder.set_global_threshold(global_threshold)
spotfinder.run()
spot_filename = spotfinder.get_spot_filename()
if not os.path.exists(spot_filename):
raise RuntimeError("Spotfinding failed: %s does not exist." %
os.path.basename(spot_filename))
spot_lists.append(spot_filename)
datablocks.append(spotfinder.get_output_sweep_filename())
from libtbx import easy_pickle
from dials.util.ascii_art import spot_counts_per_image_plot
refl = easy_pickle.load(spot_filename)
if not len(refl):
raise RuntimeError('No spots found in sweep %s' %
xsweep.get_name())
Chatter.write(spot_counts_per_image_plot(refl), strip=False)
if not PhilIndex.params.dials.fast_mode:
detectblanks = self.DetectBlanks()
detectblanks.set_sweep_filename(datablocks[-1])
detectblanks.set_reflections_filename(spot_filename)
detectblanks.run()
json = detectblanks.get_results()
offset = imageset.get_scan().get_image_range()[0]
blank_regions = json['strong']['blank_regions']
if len(blank_regions):
blank_regions = [(int(s), int(e))
for s, e in blank_regions]
for blank_start, blank_end in blank_regions:
Chatter.write(
'WARNING: Potential blank images: %i -> %i' %
(blank_start + 1, blank_end))
if PhilIndex.params.xia2.settings.remove_blanks:
non_blanks = []
start, end = imageset.get_array_range()
last_blank_end = start
for blank_start, blank_end in blank_regions:
if blank_start > start:
non_blanks.append(
(last_blank_end, blank_start))
last_blank_end = blank_end
if last_blank_end + 1 < end:
non_blanks.append((last_blank_end, end))
xsweep = self.get_indexer_sweep()
xwav = xsweep.get_wavelength()
xsample = xsweep.get_xsample()
sweep_name = xsweep.get_name()
import string
for i, (nb_start, nb_end) in enumerate(non_blanks):
assert i < 26
if i == 0:
sub_imageset = imageset[nb_start -
start:nb_end - start]
xsweep._frames_to_process = (nb_start + 1,
nb_end + 1)
self.set_indexer_prepare_done(done=False)
self._indxr_imagesets[
self._indxr_imagesets.index(
imageset)] = sub_imageset
xsweep._integrater._setup_from_imageset(
sub_imageset)
else:
new_name = '_'.join(
(sweep_name, string.ascii_lowercase[i]))
new_sweep = xwav.add_sweep(
new_name,
xsample,
directory=os.path.join(
os.path.basename(
xsweep.get_directory()), new_name),
image=imageset.get_path(nb_start - start),
frames_to_process=(nb_start + 1, nb_end),
)
Chatter.write(
"Generating new sweep: %s (%s:%i:%i)" %
(new_sweep.get_name(),
new_sweep.get_image(),
new_sweep.get_frames_to_process()[0],
new_sweep.get_frames_to_process()[1]))
return
if not PhilIndex.params.xia2.settings.trust_beam_centre:
discovery = self.DiscoverBetterExperimentalModel()
discovery.set_sweep_filename(datablocks[-1])
discovery.set_spot_filename(spot_filename)
#wedges = self._index_select_images_i(imageset)
#discovery.set_scan_ranges(wedges)
#discovery.set_scan_ranges([(first + offset, last + offset)])
try:
discovery.run()
except Exception as e:
Debug.write('DIALS beam centre search failed: %s' % str(e))
else:
# overwrite datablock.json in datablocks list
datablocks[
-1] = discovery.get_optimized_datablock_filename()
self.set_indexer_payload("spot_lists", spot_lists)
self.set_indexer_payload("datablocks", datablocks)
return
def run():
from libtbx.utils import Sorry
if len(sys.argv) < 2 or '-help' in sys.argv or '--help' in sys.argv:
help()
sys.exit()
if '-version' in sys.argv or '--version' in sys.argv:
import xia2.XIA2Version
print xia2.XIA2Version.Version
print dials_version()
ccp4_version = get_ccp4_version()
if ccp4_version is not None:
print 'CCP4 %s' % ccp4_version
sys.exit()
try:
check_environment()
except Exception as e:
traceback.print_exc(file=open('xia2.error', 'w'))
Chatter.write('Error setting up xia2 environment: %s' % str(e))
Chatter.write(
'Please send the contents of xia2.txt, xia2.error and xia2-debug.txt to:'
)
Chatter.write('*****@*****.**')
sys.exit(1)
wd = os.getcwd()
try:
xinfo = xia2_main()
Chatter.write('Status: normal termination')
Debug.write('\n------\nTiming summary:')
import xia2.Driver.DefaultDriver
xia2.Driver.DefaultDriver.output_timing_information()
return xinfo
except Sorry as s:
Chatter.write('Error: %s' % str(s))
sys.exit(1)
except Exception as e:
traceback.print_exc(file=open(os.path.join(wd, 'xia2.error'), 'w'))
Chatter.write('Error: %s' % str(e))
Chatter.write(
'Please send the contents of xia2.txt, xia2.error and xia2-debug.txt to:'
)
Chatter.write('*****@*****.**')
sys.exit(1)
def run(self):
'''Run labelit.index'''
assert len(self._images) > 0
self._images.sort()
if self._max_cell is None and len(self._images) > 4:
raise RuntimeError('cannot use more than 4 images')
#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')
for image in self._images:
self.add_command_line(image)
if self._space_group_number is not None:
self.add_command_line('known_symmetry=%d' %
self._space_group_number)
if self._primitive_unit_cell is not None:
self.add_command_line('target_cell=%f,%f,%f,%f,%f,%f' %
tuple(self._primitive_unit_cell))
if self._max_cell is not None:
self.add_command_line('codecamp.maxcell=%f' % self._max_cell)
self._write_dataset_preferences(len(self._images))
shutil.copyfile(os.path.join(self.get_working_directory(),
'dataset_preferences.py'),
os.path.join(self.get_working_directory(),
'%d_dataset_preferences.py' % \
self.get_xpid()))
self.start()
self.close_wait()
#sweep = self.get_indexer_sweep_name()
#FileHandler.record_log_file(
#'%s INDEX' % (sweep), self.get_log_file())
# check for errors
self.check_for_errors()
# check for labelit errors - if something went wrong, then
# try to address it by e.g. extending the beam search area...
self.check_labelit_errors()
# ok now we're done, let's look through for some useful stuff
output = self.get_all_output()
counter = 0
# FIXME 03/NOV/06 something to do with the new centre search...
# example output:
# Beam center is not immediately clear; rigorously retesting \
# 2 solutions
# Beam x 109.0 y 105.1, initial score 538; refined rmsd: 0.1969
# Beam x 108.8 y 106.1, initial score 354; refined rmsd: 0.1792
# in here want to parse the beam centre search if it was done,
# and check that the highest scoring solution was declared
# the "best" - though should also have a check on the
# R.M.S. deviation of that solution...
# do this first!
for j in range(len(output)):
o = output[j]
if 'Beam centre is not immediately clear' in o:
# read the solutions that it has found and parse the
# information
centres = []
scores = []
rmsds = []
num_solutions = int(o.split()[-2])
for n in range(num_solutions):
record = output[j + n + 1].replace(',', ' ').replace(
';', ' ').split()
x, y = float(record[2]), \
float(record[4])
centres.append((x, y))
scores.append(int(record[7]))
rmsds.append(float(record[-1]))
# next perform some analysis and perhaps assert the
# correct solution - for the moment just raise a warning
# if it looks like wrong solution may have been picked
best_beam_score = (0.0, 0.0, 0)
best_beam_rms = (0.0, 0.0, 1.0e8)
for n in range(num_solutions):
beam = centres[n]
score = scores[n]
rmsd = rmsds[n]
if score > best_beam_score[2]:
best_beam_score = (beam[0], beam[1], score)
if rmsd < best_beam_rmsd[2]:
best_beam_rmsd = (beam[0], beam[1], rmsd)
# allow a difference of 0.1mm in either direction...
if math.fabs(
best_beam_score[0] -
best_beam_rmsd[0]) > 0.1 or \
math.fabs(best_beam_score[1] -
best_beam_rmsd[1]) > 0.1:
Chatter.write(
'Labelit may have picked the wrong beam centre')
# FIXME as soon as I get the indexing loop
# structure set up, this should reset the
# indexing done flag, set the search range to
# 0, correct beam and then return...
# should also allow for the possibility that
# labelit has selected the best solution - so this
# will need to remember the stats for this solution,
# then compare them against the stats (one day) from
# running with the other solution - eventually the
# correct solution will result...
for o in output:
l = o.split()
if l[:3] == ['Beam', 'center', 'x']:
x = float(l[3].replace('mm,', ''))
y = float(l[5].replace('mm,', ''))
self._mosflm_beam_centre = (x, y)
self._mosflm_detector_distance = float(l[7].replace(
'mm', ''))
#self.set_indexer_beam_centre((x, y))
#self.set_indexer_distance(float(l[7].replace('mm', '')))
self._mosaic = float(l[10].replace('mosaicity=', ''))
if l[:3] == ['Solution', 'Metric', 'fit']:
break
counter += 1
# if we've just broken out (counter < len(output)) then
# we need to gather the output
if counter >= len(output):
raise RuntimeError('error in indexing')
# FIXME this needs to check the smilie status e.g.
# ":)" or ";(" or " ".
for i in range(counter + 1, len(output)):
o = output[i][3:]
smiley = output[i][:3]
l = o.split()
if l:
self._solutions[int(l[0])] = {
'number': int(l[0]),
'mosaic': self._mosaic,
'metric': float(l[1]),
'rmsd': float(l[3]),
'nspots': int(l[4]),
'lattice': l[6],
'cell': map(float, l[7:13]),
'volume': int(l[-1]),
'smiley': smiley
}
# remove clearly incorrect solutions i.e. rmsd >> rmsd for P1 i.e. factor
# of 4.0 or more...
for s in sorted(self._solutions):
if self._solutions[s][
'rmsd'] > 4.0 * self._solutions[1]['rmsd']:
del (self._solutions[s])
return 'ok'
def index(self):
if not self.get_indexer_finish_done():
f = inspect.currentframe().f_back.f_back
m = f.f_code.co_filename
l = f.f_lineno
Debug.write('Index in %s called from %s %d' %
(self.__class__.__name__, m, l))
while not self.get_indexer_finish_done():
while not self.get_indexer_done():
while not self.get_indexer_prepare_done():
# --------------
# call prepare()
# --------------
self.set_indexer_prepare_done(True)
self._index_prepare()
# --------------------------------------------
# then do the proper indexing - using the best
# solution already stored if available (c/f
# eliminate above)
# --------------------------------------------
self.set_indexer_done(True)
if self.get_indexer_sweeps():
xsweeps = [ s.get_name() for s in self.get_indexer_sweeps() ]
if len(xsweeps) > 1:
# find "SWEEPn, SWEEP(n+1), (..), SWEEPm" and aggregate to "SWEEPS n-m"
xsweeps = map(lambda x: (int(x[5:]), int(x[5:])) if x.startswith('SWEEP') else x, xsweeps)
xsweeps[0] = [xsweeps[0]]
def compress(seen, nxt):
if isinstance(seen[-1], tuple) and isinstance(nxt, tuple) and (seen[-1][1] + 1 == nxt[0]):
seen[-1] = (seen[-1][0], nxt[1])
else:
seen.append(nxt)
return seen
xsweeps = reduce(compress, xsweeps)
xsweeps = map(lambda x: ('SWEEP%d' % x[0] if x[0] == x[1] else
'SWEEPS %d to %d' % (x[0], x[1])) if isinstance(x, tuple)
else x, xsweeps)
if len(xsweeps) > 1:
sweep_names = ', '.join(xsweeps[:-1])
sweep_names += ' & ' + xsweeps[-1]
else:
sweep_names = xsweeps[0]
if PhilIndex.params.xia2.settings.show_template:
template = self.get_indexer_sweep().get_template()
Chatter.banner(
'Autoindexing %s (%s)' %(sweep_names, template))
else:
Chatter.banner('Autoindexing %s' %sweep_names)
if not self._indxr_helper:
result = self._index()
if not self._indxr_done:
Debug.write(
'Looks like indexing failed - try again!')
continue
solutions = { }
for k in self._indxr_other_lattice_cell.keys():
solutions[k] = self._indxr_other_lattice_cell[k][
'cell']
# create a helper for the indexer to manage solutions
self._indxr_helper = _IndexerHelper(solutions)
solution = self._indxr_helper.get()
# compare these against the final solution, if different
# reject solution and return - correct solution will
# be used next cycle
if self._indxr_lattice != solution[0] and \
not self._indxr_input_cell and \
not PhilIndex.params.xia2.settings.integrate_p1:
Chatter.write('Rerunning indexing lattice %s to %s' %
(self._indxr_lattice, solution[0]))
Debug.write(
'Rerunning indexing with target lattice %s' % \
solution[0])
self.set_indexer_done(False)
else:
# rerun autoindexing with the best known current solution
solution = self._indxr_helper.get()
self._indxr_input_lattice = solution[0]
self._indxr_input_cell = solution[1]
result = self._index()
# next finish up...
self.set_indexer_finish_done(True)
self._index_finish()
if self._indxr_print:
Chatter.write(self.show_indexer_solutions())
from xia2.Applications.xia2 import check, check_cctbx_version, check_environment
from xia2.Applications.xia2 import get_command_line, write_citations, help
def run():
if os.path.exists('xia2-working.phil'):
sys.argv.append('xia2-working.phil')
try:
check_environment()
check()
except exceptions.Exception, e:
traceback.print_exc(file = open('xia2.error', 'w'))
Chatter.write('Status: error "%s"' % str(e))
# print the version
Chatter.write(Version)
Citations.cite('xia2')
start_time = time.time()
assert os.path.exists('xia2.json')
from xia2.Schema.XProject import XProject
xinfo = XProject.from_json(filename='xia2.json')
crystals = xinfo.get_crystals()
for crystal_id, crystal in crystals.iteritems():
#cwd = os.path.abspath(os.curdir)
from libtbx import Auto
scale_dir = PhilIndex.params.xia2.settings.scale.directory
if scale_dir is Auto:
scale_dir = 'scale'
def run():
assert os.path.exists('xia2.json')
from xia2.Schema.XProject import XProject
xinfo = XProject.from_json(filename='xia2.json')
Chatter.write(xinfo.get_output())
write_citations()
def print_command_line(self):
cl = self.get_command_line()
Chatter.write("Command line: %s" % cl)
def setup(self):
"""Set everything up..."""
# check arguments are all ascii
Debug.write("Start parsing command line: " + str(sys.argv))
for token in sys.argv:
try:
token.encode("ascii")
except UnicodeDecodeError:
raise RuntimeError("non-ascii characters in input")
self._argv = copy.deepcopy(sys.argv)
replacements = {
"-2d": "pipeline=2d",
"-2di": "pipeline=2di",
"-3d": "pipeline=3d",
"-3di": "pipeline=3di",
"-3dii": "pipeline=3dii",
"-3dd": "pipeline=3dd",
"-dials": "pipeline=dials",
"-quick": "dials.fast_mode=true",
"-failover": "failover=true",
"-small_molecule": "small_molecule=true",
}
for k, v in replacements.iteritems():
if k in self._argv:
print(
"***\nCommand line option %s is deprecated.\nPlease use %s instead\n***"
% (k, v))
self._argv[self._argv.index(k)] = v
if "-atom" in self._argv:
idx = self._argv.index("-atom")
element = self._argv[idx + 1]
self._argv[idx:idx + 2] = ["atom=%s" % element]
print(
"***\nCommand line option -atom %s is deprecated.\nPlease use atom=%s instead\n***"
% (element, element))
# first of all try to interpret arguments as phil parameters/files
from xia2.Handlers.Phil import master_phil
from libtbx.phil import command_line
cmd_line = command_line.argument_interpreter(master_phil=master_phil)
working_phil, self._argv = cmd_line.process_and_fetch(
args=self._argv, custom_processor="collect_remaining")
PhilIndex.merge_phil(working_phil)
try:
params = PhilIndex.get_python_object()
except RuntimeError as e:
raise Sorry(e)
# sanity check / interpret Auto in input
from libtbx import Auto
if params.xia2.settings.input.atom is None:
if params.xia2.settings.input.anomalous is Auto:
PhilIndex.update("xia2.settings.input.anomalous=false")
else:
if params.xia2.settings.input.anomalous is False:
raise Sorry(
"Setting anomalous=false and atom type inconsistent")
params.xia2.settings.input.anomalous = True
PhilIndex.update("xia2.settings.input.anomalous=true")
if params.xia2.settings.resolution.keep_all_reflections is Auto:
if (params.xia2.settings.small_molecule is True
and params.xia2.settings.resolution.d_min is None
and params.xia2.settings.resolution.d_max is None):
PhilIndex.update(
"xia2.settings.resolution.keep_all_reflections=true")
else:
PhilIndex.update(
"xia2.settings.resolution.keep_all_reflections=false")
if params.xia2.settings.small_molecule is True:
Debug.write("Small molecule selected")
if params.xia2.settings.symmetry.chirality is None:
PhilIndex.update("xia2.settings.symmetry.chirality=nonchiral")
params = PhilIndex.get_python_object()
# pipeline options
self._read_pipeline()
for (parameter, value) in (
("project", params.xia2.settings.project),
("crystal", params.xia2.settings.crystal),
):
validate_project_crystal_name(parameter, value)
Debug.write("Project: %s" % params.xia2.settings.project)
Debug.write("Crystal: %s" % params.xia2.settings.crystal)
# FIXME add some consistency checks in here e.g. that there are
# images assigned, there is a lattice assigned if cell constants
# are given and so on
params = PhilIndex.get_python_object()
mp_params = params.xia2.settings.multiprocessing
from xia2.Handlers.Environment import get_number_cpus
if mp_params.mode == "parallel":
if mp_params.type == "qsub":
if which("qsub") is None:
raise Sorry("qsub not available")
if mp_params.njob is Auto:
mp_params.njob = get_number_cpus()
if mp_params.nproc is Auto:
mp_params.nproc = 1
elif mp_params.nproc is Auto:
mp_params.nproc = get_number_cpus()
elif mp_params.mode == "serial":
if mp_params.type == "qsub":
if which("qsub") is None:
raise Sorry("qsub not available")
if mp_params.njob is Auto:
mp_params.njob = 1
if mp_params.nproc is Auto:
mp_params.nproc = get_number_cpus()
PhilIndex.update("xia2.settings.multiprocessing.njob=%d" %
mp_params.njob)
PhilIndex.update("xia2.settings.multiprocessing.nproc=%d" %
mp_params.nproc)
params = PhilIndex.get_python_object()
mp_params = params.xia2.settings.multiprocessing
if mp_params.nproc > 1 and os.name == "nt":
raise Sorry("nproc > 1 is not supported on Windows.") # #191
if params.xia2.settings.indexer is not None:
add_preference("indexer", params.xia2.settings.indexer)
if params.xia2.settings.refiner is not None:
add_preference("refiner", params.xia2.settings.refiner)
if params.xia2.settings.integrater is not None:
add_preference("integrater", params.xia2.settings.integrater)
if params.xia2.settings.scaler is not None:
add_preference("scaler", params.xia2.settings.scaler)
if params.xia2.settings.multi_sweep_indexing is Auto:
if (params.xia2.settings.small_molecule is True
and "dials" == params.xia2.settings.indexer):
PhilIndex.update("xia2.settings.multi_sweep_indexing=True")
else:
PhilIndex.update("xia2.settings.multi_sweep_indexing=False")
if (params.xia2.settings.multi_sweep_indexing is True
and params.xia2.settings.multiprocessing.mode == "parallel"):
Chatter.write(
"Multi sweep indexing disabled:\nMSI is not available for parallel processing."
)
PhilIndex.update("xia2.settings.multi_sweep_indexing=False")
input_json = params.xia2.settings.input.json
if input_json is not None and len(input_json):
for json_file in input_json:
assert os.path.isfile(json_file)
load_experiments(json_file)
reference_geometry = params.xia2.settings.input.reference_geometry
if reference_geometry is not None and len(reference_geometry) > 0:
reference_geometries = "\n".join([
"xia2.settings.input.reference_geometry=%s" %
os.path.abspath(g)
for g in params.xia2.settings.input.reference_geometry
])
Debug.write(reference_geometries)
PhilIndex.update(reference_geometries)
Debug.write("xia2.settings.trust_beam_centre=true")
PhilIndex.update("xia2.settings.trust_beam_centre=true")
params = PhilIndex.get_python_object()
params = PhilIndex.get_python_object()
if params.xia2.settings.input.xinfo is not None:
xinfo_file = os.path.abspath(params.xia2.settings.input.xinfo)
PhilIndex.update("xia2.settings.input.xinfo=%s" % xinfo_file)
params = PhilIndex.get_python_object()
self.set_xinfo(xinfo_file)
# issue #55 if not set ATOM in xinfo but anomalous=true or atom= set
# on commandline, set here, should be idempotent
if params.xia2.settings.input.anomalous is True:
crystals = self._xinfo.get_crystals()
for xname in crystals:
xtal = crystals[xname]
Debug.write("Setting anomalous for crystal %s" % xname)
xtal.set_anomalous(True)
else:
xinfo_file = "%s/automatic.xinfo" % os.path.abspath(os.curdir)
PhilIndex.update("xia2.settings.input.xinfo=%s" % xinfo_file)
params = PhilIndex.get_python_object()
if params.dials.find_spots.phil_file is not None:
PhilIndex.update(
"dials.find_spots.phil_file=%s" %
os.path.abspath(params.dials.find_spots.phil_file))
if params.dials.index.phil_file is not None:
PhilIndex.update("dials.index.phil_file=%s" %
os.path.abspath(params.dials.index.phil_file))
if params.dials.refine.phil_file is not None:
PhilIndex.update("dials.refine.phil_file=%s" %
os.path.abspath(params.dials.refine.phil_file))
if params.dials.integrate.phil_file is not None:
PhilIndex.update("dials.integrate.phil_file=%s" %
os.path.abspath(params.dials.integrate.phil_file))
if params.xds.index.xparm is not None:
Flags.set_xparm(params.xds.index.xparm)
if params.xds.index.xparm_ub is not None:
Flags.set_xparm_ub(params.xds.index.xparm_ub)
if params.xia2.settings.scale.freer_file is not None:
freer_file = os.path.abspath(params.xia2.settings.scale.freer_file)
if not os.path.exists(freer_file):
raise RuntimeError("%s does not exist" % freer_file)
from xia2.Modules.FindFreeFlag import FindFreeFlag
column = FindFreeFlag(freer_file)
Debug.write("FreeR_flag column in %s found: %s" %
(freer_file, column))
PhilIndex.update("xia2.settings.scale.freer_file=%s" % freer_file)
if params.xia2.settings.scale.reference_reflection_file is not None:
reference_reflection_file = os.path.abspath(
params.xia2.settings.scale.reference_reflection_file)
if not os.path.exists(reference_reflection_file):
raise RuntimeError("%s does not exist" %
reference_reflection_file)
PhilIndex.update(
"xia2.settings.scale.reference_reflection_file=%s" %
reference_reflection_file)
params = PhilIndex.get_python_object()
datasets = unroll_datasets(PhilIndex.params.xia2.settings.input.image)
for dataset in datasets:
start_end = None
# here we only care about ':' which are later than C:\
if ":" in dataset[3:]:
tokens = dataset.split(":")
# cope with windows drives i.e. C:\data\blah\thing_0001.cbf:1:100
if len(tokens[0]) == 1:
tokens = ["%s:%s" % (tokens[0], tokens[1])] + tokens[2:]
if len(tokens) != 3:
raise RuntimeError("/path/to/image_0001.cbf:start:end")
dataset = tokens[0]
start_end = int(tokens[1]), int(tokens[2])
from xia2.Applications.xia2setup import is_hd5f_name
if os.path.exists(os.path.abspath(dataset)):
dataset = os.path.abspath(dataset)
else:
directories = [os.getcwd()] + self._argv[1:]
found = False
for d in directories:
if os.path.exists(os.path.join(d, dataset)):
dataset = os.path.join(d, dataset)
found = True
break
if not found:
raise Sorry("Could not find %s in %s" %
(dataset, " ".join(directories)))
if is_hd5f_name(dataset):
self._hdf5_master_files.append(dataset)
if start_end:
Debug.write("Image range: %d %d" % start_end)
if dataset not in self._default_start_end:
self._default_start_end[dataset] = []
self._default_start_end[dataset].append(start_end)
else:
Debug.write("No image range specified")
else:
template, directory = image2template_directory(
os.path.abspath(dataset))
self._default_template.append(os.path.join(
directory, template))
self._default_directory.append(directory)
Debug.write("Interpreted from image %s:" % dataset)
Debug.write("Template %s" % template)
Debug.write("Directory %s" % directory)
if start_end:
Debug.write("Image range: %d %d" % start_end)
key = os.path.join(directory, template)
if key not in self._default_start_end:
self._default_start_end[key] = []
self._default_start_end[key].append(start_end)
else:
Debug.write("No image range specified")
# finally, check that all arguments were read and raise an exception
# if any of them were nonsense.
with open("xia2-working.phil", "wb") as f:
f.write(PhilIndex.working_phil.as_str())
f.write(
os.linesep
) # temporarily required for https://github.com/dials/dials/issues/522
with open("xia2-diff.phil", "wb") as f:
f.write(PhilIndex.get_diff().as_str())
f.write(
os.linesep
) # temporarily required for https://github.com/dials/dials/issues/522
Debug.write("\nDifference PHIL:")
Debug.write(PhilIndex.get_diff().as_str(), strip=False)
Debug.write("Working PHIL:")
Debug.write(PhilIndex.working_phil.as_str(), strip=False)
nonsense = "Unknown command-line options:"
was_nonsense = False
for j, argv in enumerate(self._argv):
if j == 0:
continue
if argv[0] != "-" and "=" not in argv:
continue
if j not in self._understood:
nonsense += " %s" % argv
was_nonsense = True
if was_nonsense:
raise RuntimeError(nonsense)
def compute_nmol_from_volume(volume, mass, resolution):
file = open(nmolparams, "r")
while True:
line = file.readline()
if not line[0] == "#":
break
resolutions = map(float, line.split(","))[:13]
P0_list = map(float, file.readline().split(","))[:13]
Vm_bar_list = map(float, file.readline().split(","))[:13]
w_list = map(float, file.readline().split(","))[:13]
A_list = map(float, file.readline().split(","))[:13]
s_list = map(float, file.readline().split(","))[:13]
file.close()
if resolution > resolutions[-1]:
Chatter.write(
"Resolution lower than %s -> computing for %f"
% (resolutions[-1], resolution)
)
resolution = resolutions[-1]
if resolution < resolutions[0]:
Chatter.write(
"Resolution higher than peak %f -> %f" % (resolution, resolutions[0])
)
resolution = resolutions[0]
start = 0
for start in range(12):
if resolution > resolutions[start] and resolution < resolutions[start + 1]:
break
# can start at start - interpolate
diff = (resolution - resolutions[start]) / (
resolutions[start + 1] - resolutions[start]
)
P0 = P0_list[start] + diff * (P0_list[start + 1] - P0_list[start])
Vm_bar = Vm_bar_list[start] + diff * (Vm_bar_list[start + 1] - Vm_bar_list[start])
w = w_list[start] + diff * (w_list[start + 1] - w_list[start])
A = A_list[start] + diff * (A_list[start + 1] - A_list[start])
s = s_list[start] + diff * (s_list[start + 1] - s_list[start])
nmols = []
pdfs = []
nmol = 1
Vm = volume / (mass * nmol)
while True:
z = (Vm - Vm_bar) / w
p = P0 + A * math.exp(-math.exp(-z) - z * s + 1)
nmols.append(nmol)
pdfs.append(p)
nmol += 1
Vm = volume / (mass * nmol)
if Vm < 1.0:
break
return nmols, pdfs
def integrate(self):
'''Actually perform integration until we think we are done...'''
while not self.get_integrater_finish_done():
while not self.get_integrater_done():
while not self.get_integrater_prepare_done():
Debug.write('Preparing to do some integration...')
self.set_integrater_prepare_done(True)
# if this raises an exception, perhaps the autoindexing
# solution has too high symmetry. if this the case, then
# perform a self._intgr_indexer.eliminate() - this should
# reset the indexing system
try:
self._integrate_prepare()
except BadLatticeError as e:
Journal.banner('eliminated this lattice', size=80)
Chatter.write('Rejecting bad lattice %s' % str(e))
self._intgr_refiner.eliminate()
self._integrater_reset()
# FIXME x1698 - may be the case that _integrate() returns the
# raw intensities, _integrate_finish() returns intensities
# which may have been adjusted or corrected. See #1698 below.
Debug.write('Doing some integration...')
self.set_integrater_done(True)
template = self.get_integrater_sweep().get_template()
if self._intgr_sweep_name:
if PhilIndex.params.xia2.settings.show_template:
Chatter.banner('Integrating %s (%s)' % \
(self._intgr_sweep_name, template))
else:
Chatter.banner('Integrating %s' % \
(self._intgr_sweep_name))
try:
#1698
self._intgr_hklout_raw = self._integrate()
except BadLatticeError as e:
Chatter.write('Rejecting bad lattice %s' % str(e))
Journal.banner('eliminated this lattice', size=80)
self._intgr_refiner.eliminate()
self._integrater_reset()
self.set_integrater_finish_done(True)
try:
# allow for the fact that postrefinement may be used
# to reject the lattice...
self._intgr_hklout = self._integrate_finish()
except BadLatticeError as e:
Chatter.write('Bad Lattice Error: %s' % str(e))
self._intgr_refiner.eliminate()
self._integrater_reset()
return self._intgr_hklout
raise RuntimeError, 'processing abandoned'
self._intgr_batches_out = integrater.get_batches_out()
mosaics = integrater.get_mosaic_spreads()
if mosaics and len(mosaics) > 0:
self.set_integrater_mosaic_min_mean_max(
min(mosaics), sum(mosaics) / len(mosaics), max(mosaics))
else:
m = indxr.get_indexer_mosaic()
self.set_integrater_mosaic_min_mean_max(m, m, m)
# write the report for each image as .*-#$ to Chatter -
# detailed report will be written automagically to science...
Chatter.write(self.show_per_image_statistics())
Chatter.write('Mosaic spread: %.3f < %.3f < %.3f' % \
self.get_integrater_mosaic_min_mean_max())
# gather the statistics from the postrefinement
postref_result = integrater.get_postref_result()
# now write this to a postrefinement log
postref_log = os.path.join(self.get_working_directory(),
'postrefinement.log')
fout = open(postref_log, 'w')
fout.write('$TABLE: Postrefinement for %s:\n' % \
self._intgr_sweep_name)
def get_output(self):
result = 'Wavelength name: %s\n' % self._name
result += 'Wavelength %7.5f\n' % self._wavelength
if self._f_pr != 0.0 and self._f_prpr != 0.0:
result += 'F\', F\'\' = (%5.2f, %5.2f)\n' % (self._f_pr,
self._f_prpr)
result += 'Sweeps:\n'
from xia2.Driver.DriverFactory import DriverFactory
def run_one_sweep(args):
from xia2.Handlers.Streams import Debug
assert len(args) == 3
s, failover, job_type = args
if job_type:
DriverFactory.set_driver_type(job_type)
Chatter.cache()
Debug.cache()
try:
s.get_integrater_intensities()
except Exception as e:
if failover:
Chatter.write('Processing sweep %s failed: %s' % \
(s.get_name(), str(e)))
s = None
else:
raise
finally:
Chatter.uncache()
Debug.uncache()
return s
remove = []
from xia2.Handlers.Phil import PhilIndex
params = PhilIndex.get_python_object()
failover = params.xia2.settings.failover
for s in self._sweeps:
# would be nice to put this somewhere else in the hierarchy - not
# sure how to do that though (should be handled in Interfaces?)
try:
result += '%s\n' % s.get_output()
except Exception as e:
if failover:
Chatter.write('Processing sweep %s failed: %s' % \
(s.get_name(), str(e)))
remove.append(s)
else:
raise
for s in remove:
self._sweeps.remove(s)
return result[:-1]
def _mosflm_integrate(self):
'''Perform the actual integration, based on the results of the
cell refinement or indexing (they have the equivalent form.)'''
refinr = self.get_integrater_refiner()
if not refinr.get_refiner_payload('mosflm_orientation_matrix'):
raise RuntimeError, 'unexpected situation in indexing'
lattice = refinr.get_refiner_lattice()
spacegroup_number = lattice_to_spacegroup(lattice)
mosaic = refinr.get_refiner_payload('mosaic')
beam = refinr.get_refiner_payload('beam')
distance = refinr.get_refiner_payload('distance')
matrix = refinr.get_refiner_payload('mosflm_orientation_matrix')
integration_params = refinr.get_refiner_payload(
'mosflm_integration_parameters')
if integration_params:
if 'separation' in integration_params:
self.set_integrater_parameter(
'mosflm', 'separation',
'%s %s' % tuple(integration_params['separation']))
if 'raster' in integration_params:
self.set_integrater_parameter(
'mosflm', 'raster',
'%d %d %d %d %d' % tuple(integration_params['raster']))
refinr.set_refiner_payload('mosflm_integration_parameters', None)
f = open(os.path.join(self.get_working_directory(),
'xiaintegrate.mat'), 'w')
for m in matrix:
f.write(m)
f.close()
# then start the integration
integrater = MosflmIntegrate()
integrater.set_working_directory(self.get_working_directory())
auto_logfiler(integrater)
integrater.set_refine_profiles(self._mosflm_refine_profiles)
pname, xname, dname = self.get_integrater_project_info()
if pname is not None and xname is not None and dname is not None:
Debug.write('Harvesting: %s/%s/%s' % (pname, xname, dname))
harvest_dir = self.get_working_directory()
# harvest file name will be %s.mosflm_run_start_end % dname
temp_dname = '%s_%s' % \
(dname, self.get_integrater_sweep_name())
integrater.set_pname_xname_dname(pname, xname, temp_dname)
integrater.set_template(os.path.basename(self.get_template()))
integrater.set_directory(self.get_directory())
# check for ice - and if so, exclude (ranges taken from
# XDS documentation)
if self.get_integrater_ice() != 0:
Debug.write('Excluding ice rings')
integrater.set_exclude_ice(True)
# exclude specified resolution ranges
if len(self.get_integrater_excluded_regions()) != 0:
regions = self.get_integrater_excluded_regions()
Debug.write('Excluding regions: %s' % `regions`)
integrater.set_exclude_regions(regions)
mask = standard_mask(self.get_detector())
for m in mask:
integrater.add_instruction(m)
integrater.set_input_mat_file('xiaintegrate.mat')
integrater.set_beam_centre(beam)
integrater.set_distance(distance)
integrater.set_space_group_number(spacegroup_number)
integrater.set_mosaic(mosaic)
if self.get_wavelength_prov() == 'user':
integrater.set_wavelength(self.get_wavelength())
parameters = self.get_integrater_parameters('mosflm')
integrater.update_parameters(parameters)
if self._mosflm_gain:
integrater.set_gain(self._mosflm_gain)
# check for resolution limits
if self._intgr_reso_high > 0.0:
integrater.set_d_min(self._intgr_reso_high)
if self._intgr_reso_low:
integrater.set_d_max(self._intgr_reso_low)
if PhilIndex.params.general.backstop_mask:
from xia2.Toolkit.BackstopMask import BackstopMask
mask = BackstopMask(PhilIndex.params.general.backstop_mask)
mask = mask.calculate_mask_mosflm(self.get_header())
integrater.set_mask(mask)
detector = self.get_detector()
detector_width, detector_height = detector[0].get_image_size_mm()
lim_x = 0.5 * detector_width
lim_y = 0.5 * detector_height
Debug.write('Scanner limits: %.1f %.1f' % (lim_x, lim_y))
integrater.set_limits(lim_x, lim_y)
integrater.set_fix_mosaic(self._mosflm_postref_fix_mosaic)
offset = self.get_frame_offset()
integrater.set_image_range(
(self._intgr_wedge[0] - offset, self._intgr_wedge[1] - offset))
try:
integrater.run()
except RuntimeError, e:
if 'integration failed: reason unknown' in str(e):
Chatter.write('Mosflm has failed in integration')
message = 'The input was:\n\n'
for input in integrater.get_all_input():
message += ' %s' % input
Chatter.write(message)
raise
if bl_info:
from xia2.Handlers.CIF import CIF, mmCIF
cifblock, mmcifblock = bl_info.CIF_block(), bl_info.mmCIF_block()
if cifblock:
CIF.set_block(bl_info.get_block_name(), cifblock)
if mmcifblock:
mmCIF.set_block(bl_info.get_block_name(), mmcifblock)
if __name__ == '__main__':
directory = os.path.join('z:', 'data', '12287')
image = '12287_1_E1_001.img'
xs = XSweep('DEMO', None, directory, image)
xs_descr = str(xs)
Chatter.write('.')
for record in xs_descr.split('\n'):
Chatter.write(record.strip())
Chatter.write('.')
Chatter.write('Refined beam is: %6.2f %6.2f' % xs.get_indexer_beam_centre())
Chatter.write('Distance: %6.2f' % xs.get_indexer_distance())
Chatter.write('Cell: %6.2f %6.2f %6.2f %6.2f %6.2f %6.2f' % \
xs.get_indexer_cell())
Chatter.write('Lattice: %s' % xs.get_indexer_lattice())
Chatter.write('Mosaic: %6.2f' % xs.get_indexer_mosaic())
Chatter.write('Hklout: %s' % xs.get_integrater_intensities())
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 user_resolution_limits:
resolution = user_resolution_limits[(dname, sname)]
self._scalr_resolution_limits[(dname, sname)] = resolution
if resolution < highest_resolution:
highest_resolution = resolution
Chatter.write('Resolution limit for %s: %5.2f' % \
(dname, resolution))
continue
hklin = sc.get_unmerged_reflection_file()
resolution = self._estimate_resolution_limit(
hklin, batch_range=(start, end))
Debug.write('Resolution for sweep %s: %.2f' % \
(sname, resolution))
if not (dname, sname) in self._scalr_resolution_limits:
self._scalr_resolution_limits[(dname, sname)] = resolution
self.set_scaler_done(False)
if resolution < highest_resolution:
highest_resolution = resolution
def index(self):
if not self.get_indexer_finish_done():
f = inspect.currentframe().f_back.f_back
m = f.f_code.co_filename
l = f.f_lineno
Debug.write('Index in %s called from %s %d' %
(self.__class__.__name__, m, l))
while not self.get_indexer_finish_done():
while not self.get_indexer_done():
while not self.get_indexer_prepare_done():
# --------------
# call prepare()
# --------------
self.set_indexer_prepare_done(True)
self._index_prepare()
# --------------------------------------------
# then do the proper indexing - using the best
# solution already stored if available (c/f
# eliminate above)
# --------------------------------------------
self.set_indexer_done(True)
if self.get_indexer_sweeps():
xsweeps = self.get_indexer_sweeps()
if len(xsweeps) > 1:
sweep_names = ', '.join(x.get_name() for x in xsweeps[:-1])
sweep_names += ' & ' + xsweeps[-1].get_name()
else:
sweep_names = xsweeps[0].get_name()
if PhilIndex.params.xia2.settings.show_template:
template = self.get_indexer_sweep().get_template()
Chatter.banner(
'Autoindexing %s (%s)' %(sweep_names, template))
else:
Chatter.banner('Autoindexing %s' %sweep_names)
if not self._indxr_helper:
result = self._index()
if not self._indxr_done:
Debug.write(
'Looks like indexing failed - try again!')
continue
solutions = { }
for k in self._indxr_other_lattice_cell.keys():
solutions[k] = self._indxr_other_lattice_cell[k][
'cell']
# create a helper for the indexer to manage solutions
self._indxr_helper = _IndexerHelper(solutions)
solution = self._indxr_helper.get()
# compare these against the final solution, if different
# reject solution and return - correct solution will
# be used next cycle
if self._indxr_lattice != solution[0] and \
not self._indxr_input_cell and \
not PhilIndex.params.xia2.settings.integrate_p1:
Chatter.write('Rerunning indexing lattice %s to %s' %
(self._indxr_lattice, solution[0]))
Debug.write(
'Rerunning indexing with target lattice %s' % \
solution[0])
self.set_indexer_done(False)
else:
# rerun autoindexing with the best known current solution
solution = self._indxr_helper.get()
self._indxr_input_lattice = solution[0]
self._indxr_input_cell = solution[1]
result = self._index()
# next finish up...
self.set_indexer_finish_done(True)
self._index_finish()
if self._indxr_print:
Chatter.write(self.show_indexer_solutions())
# FIXED 23/OCT/06 at this stage I need to look at the list of
# reasonable solutions and try to figure out if the indexing
# program has picked the highest - if not, then constrain the
# unit cell (need to implement this somewhere, sure it's
# around!) then rerun the autoindexing (perhaps?) with this
# new target - this means that we are always working from the
# top downwards with these things. Once we decide somewhere
# else (e.g. in cell refinement) that this cell isn't good
# then we can eliminate it from the list, select the next
# lower symmetry solution and continue. This solution is a
# general one, so may be implemented in the general indexer
# interface rather than in specific code...
return
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 _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 run(self):
'''Run defpix.'''
#image_header = self.get_header()
## crank through the header dictionary and replace incorrect
## information with updated values through the indexer
## interface if available...
## need to add distance, wavelength - that should be enough...
#if self.get_distance():
#image_header['distance'] = self.get_distance()
#if self.get_wavelength():
#image_header['wavelength'] = self.get_wavelength()
#if self.get_two_theta():
#image_header['two_theta'] = self.get_two_theta()
header = imageset_to_xds(self.get_imageset())
xds_inp = open(os.path.join(self.get_working_directory(),
'XDS.INP'), 'w')
# what are we doing?
xds_inp.write('JOB=DEFPIX\n')
for record in header:
xds_inp.write('%s\n' % record)
name_template = os.path.join(self.get_directory(),
self.get_template().replace('#', '?'))
record = 'NAME_TEMPLATE_OF_DATA_FRAMES=%s\n' % \
name_template
xds_inp.write(record)
xds_inp.write('DATA_RANGE=%d %d\n' % self._data_range)
# include the resolution range, perhaps
if self._resolution_high > 0.0 or self._resolution_low > 0.0:
xds_inp.write('INCLUDE_RESOLUTION_RANGE=%.2f %.2f\n' % \
(self._resolution_low, self._resolution_high))
xds_inp.close()
# copy the input file...
shutil.copyfile(os.path.join(self.get_working_directory(),
'XDS.INP'),
os.path.join(self.get_working_directory(),
'%d_DEFPIX.INP' % self.get_xpid()))
# write the input data files...
for file_name in self._input_data_files_list:
src = self._input_data_files[file_name]
dst = os.path.join(
self.get_working_directory(), file_name)
if src != dst:
shutil.copyfile(src, dst)
self.start()
self.close_wait()
xds_check_version_supported(self.get_all_output())
# copy the LP file
shutil.copyfile(os.path.join(self.get_working_directory(),
'DEFPIX.LP'),
os.path.join(self.get_working_directory(),
'%d_DEFPIX.LP' % self.get_xpid()))
# check the resolution asked for is achievable (if set)
for record in open(os.path.join(self.get_working_directory(),
'DEFPIX.LP')):
if 'RESOLUTION RANGE RECORDED BY DETECTOR' in record:
real_high = float(record.split()[-1])
if self._resolution_high:
if real_high > self._resolution_high + 0.01:
Chatter.write(
'Warning: resolution limited to %.2f' % \
real_high)
# gather the output files
for file in self._output_data_files_list:
self._output_data_files[file] = os.path.join(
self.get_working_directory(), file)
return
def run(self):
"""Run labelit.index"""
assert len(self._images) > 0
self._images.sort()
if self._max_cell is None and len(self._images) > 4:
raise RuntimeError, "cannot use more than 4 images"
# 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")
for image in self._images:
self.add_command_line(image)
if self._space_group_number is not None:
self.add_command_line("known_symmetry=%d" % self._space_group_number)
if self._primitive_unit_cell is not None:
self.add_command_line("target_cell=%f,%f,%f,%f,%f,%f" % tuple(self._primitive_unit_cell))
if self._max_cell is not None:
self.add_command_line("codecamp.maxcell=%f" % self._max_cell)
self._write_dataset_preferences(len(self._images))
shutil.copyfile(
os.path.join(self.get_working_directory(), "dataset_preferences.py"),
os.path.join(self.get_working_directory(), "%d_dataset_preferences.py" % self.get_xpid()),
)
self.start()
self.close_wait()
# sweep = self.get_indexer_sweep_name()
# FileHandler.record_log_file(
#'%s INDEX' % (sweep), self.get_log_file())
# check for errors
self.check_for_errors()
# check for labelit errors - if something went wrong, then
# try to address it by e.g. extending the beam search area...
self.check_labelit_errors()
# ok now we're done, let's look through for some useful stuff
output = self.get_all_output()
counter = 0
# FIXME 03/NOV/06 something to do with the new centre search...
# example output:
# Beam center is not immediately clear; rigorously retesting \
# 2 solutions
# Beam x 109.0 y 105.1, initial score 538; refined rmsd: 0.1969
# Beam x 108.8 y 106.1, initial score 354; refined rmsd: 0.1792
# in here want to parse the beam centre search if it was done,
# and check that the highest scoring solution was declared
# the "best" - though should also have a check on the
# R.M.S. deviation of that solution...
# do this first!
for j in range(len(output)):
o = output[j]
if "Beam centre is not immediately clear" in o:
# read the solutions that it has found and parse the
# information
centres = []
scores = []
rmsds = []
num_solutions = int(o.split()[-2])
for n in range(num_solutions):
record = output[j + n + 1].replace(",", " ").replace(";", " ").split()
x, y = float(record[2]), float(record[4])
centres.append((x, y))
scores.append(int(record[7]))
rmsds.append(float(record[-1]))
# next perform some analysis and perhaps assert the
# correct solution - for the moment just raise a warning
# if it looks like wrong solution may have been picked
best_beam_score = (0.0, 0.0, 0)
best_beam_rms = (0.0, 0.0, 1.0e8)
for n in range(num_solutions):
beam = centres[n]
score = scores[n]
rmsd = rmsds[n]
if score > best_beam_score[2]:
best_beam_score = (beam[0], beam[1], score)
if rmsd < best_beam_rmsd[2]:
best_beam_rmsd = (beam[0], beam[1], rmsd)
# allow a difference of 0.1mm in either direction...
if (
math.fabs(best_beam_score[0] - best_beam_rmsd[0]) > 0.1
or math.fabs(best_beam_score[1] - best_beam_rmsd[1]) > 0.1
):
Chatter.write("Labelit may have picked the wrong beam centre")
# FIXME as soon as I get the indexing loop
# structure set up, this should reset the
# indexing done flag, set the search range to
# 0, correct beam and then return...
# should also allow for the possibility that
# labelit has selected the best solution - so this
# will need to remember the stats for this solution,
# then compare them against the stats (one day) from
# running with the other solution - eventually the
# correct solution will result...
for o in output:
l = o.split()
if l[:3] == ["Beam", "center", "x"]:
x = float(l[3].replace("mm,", ""))
y = float(l[5].replace("mm,", ""))
self._mosflm_beam_centre = (x, y)
self._mosflm_detector_distance = float(l[7].replace("mm", ""))
# self.set_indexer_beam_centre((x, y))
# self.set_indexer_distance(float(l[7].replace('mm', '')))
self._mosaic = float(l[10].replace("mosaicity=", ""))
if l[:3] == ["Solution", "Metric", "fit"]:
break
counter += 1
# if we've just broken out (counter < len(output)) then
# we need to gather the output
if counter >= len(output):
raise RuntimeError, "error in indexing"
# FIXME this needs to check the smilie status e.g.
# ":)" or ";(" or " ".
for i in range(counter + 1, len(output)):
o = output[i][3:]
smiley = output[i][:3]
l = o.split()
if l:
self._solutions[int(l[0])] = {
"number": int(l[0]),
"mosaic": self._mosaic,
"metric": float(l[1]),
"rmsd": float(l[3]),
"nspots": int(l[4]),
"lattice": l[6],
"cell": map(float, l[7:13]),
"volume": int(l[-1]),
"smiley": smiley,
}
# remove clearly incorrect solutions i.e. rmsd >> rmsd for P1 i.e. factor
# of 4.0 or more...
for s in sorted(self._solutions):
if self._solutions[s]["rmsd"] > 4.0 * self._solutions[1]["rmsd"]:
del (self._solutions[s])
return "ok"
def __init__(self, name,
wavelength,
sample,
directory = None,
image = None,
beam = None,
reversephi = False,
distance = None,
gain = 0.0,
dmin = 0.0,
dmax = 0.0,
polarization = 0.0,
frames_to_process = None,
user_lattice = None,
user_cell = None,
epoch = 0,
ice = False,
excluded_regions = None):
'''Create a new sweep named name, belonging to XWavelength object
wavelength, representing the images in directory starting with image,
with beam centre optionally defined.'''
if excluded_regions is None:
excluded_regions = []
# + check the wavelength is an XWavelength object
# raise an exception if not... or not...
if not wavelength.__class__.__name__ == 'XWavelength':
pass
# FIXME bug 2221 if DIRECTORY starts with ~/ or ~graeme (say) need to
# interpret this properly - e.g. map it to a full PATH.
directory = expand_path(directory)
self._name = name
self._wavelength = wavelength
self._sample = sample
self._directory = directory
self._image = image
self._reversephi = reversephi
self._epoch = epoch
self._user_lattice = user_lattice
self._user_cell = user_cell
self._header = { }
self._resolution_high = dmin
self._resolution_low = dmax
self._ice = ice
self._excluded_regions = excluded_regions
self._imageset = None
# FIXME in here also need to be able to accumulate the total
# dose from all experimental measurements (complex) and provide
# a _epoch_to_dose dictionary or some such... may be fiddly as
# this will need to parse across multiple templates. c/f Bug # 2798
self._epoch_to_image = { }
self._image_to_epoch = { }
# to allow first, last image for processing to be
# set... c/f integrater interface
self._frames_to_process = frames_to_process
# + derive template, list of images
params = PhilIndex.get_python_object()
if directory and image:
self._template, self._directory = \
image2template_directory(os.path.join(directory,
image))
from xia2.Schema import load_imagesets
imagesets = load_imagesets(
self._template, self._directory, image_range=self._frames_to_process,
reversephi=(params.xia2.settings.input.reverse_phi or self._reversephi))
assert len(imagesets) == 1, "one imageset expected, %d found" % \
len(imagesets)
self._imageset = copy.deepcopy(imagesets[0])
start, end = self._imageset.get_array_range()
self._images = list(range(start+1, end+1))
# FIXME in here check that (1) the list of images is continuous
# and (2) that all of the images are readable. This should also
# take into account frames_to_process if set.
if self._frames_to_process is None:
self._frames_to_process = min(self._images), max(self._images)
start, end = self._frames_to_process
error = False
if params.general.check_image_files_readable:
for j in range(start, end + 1):
image_name = self.get_imageset().get_path(j-start)
if not j in self._images:
Debug.write('image %s missing' %image_name)
error = True
continue
if not os.access(image_name, os.R_OK):
Debug.write('image %s unreadable' %image_name)
error = True
continue
if error:
raise RuntimeError, 'problem with sweep %s' % self._name
# + read the image header information into here?
# or don't I need it? it would be useful for checking
# against wavelength.getWavelength() I guess to make
# sure that the plumbing is all sound.
# check that they match by closer than 0.0001A, if wavelength
# is not None
beam_ = self._imageset.get_beam()
scan = self._imageset.get_scan()
if wavelength is not None:
# FIXME 29/NOV/06 if the wavelength wavelength value
# is 0.0 then first set it to the header value - note
# that this assumes that the header value is correct
# (a reasonable assumption)
if wavelength.get_wavelength() == 0.0:
wavelength.set_wavelength(beam_.get_wavelength())
# FIXME 08/DEC/06 in here need to allow for the fact
# that the wavelength in the image header could be wrong and
# in fact it should be replaced with the input value -
# through the user will need to be warned of this and
# also everything using the FrameProcessor interface
# will also have to respect this!
if math.fabs(beam_.get_wavelength() -
wavelength.get_wavelength()) > 0.0001:
# format = 'wavelength for sweep %s does not ' + \
# 'match wavelength %s'
# raise RuntimeError, format % \
# (name, wavelength.get_name())
format = 'Header wavelength for sweep %s different' + \
' to assigned value (%4.2f vs. %4.2f)'
Chatter.write(format % (name, beam_.get_wavelength(),
wavelength.get_wavelength()))
# also in here look at the image headers to see if we can
# construct a mapping between exposure epoch and image ...
images = []
if self._frames_to_process:
start, end = self._frames_to_process
for j in self._images:
if j >= start and j <= end:
images.append(j)
else:
images = self._images
for j in images:
epoch = scan.get_image_epoch(j)
if epoch == 0.0:
epoch = float(os.stat(self._imageset.get_path(j-images[0])).st_mtime)
self._epoch_to_image[epoch] = j
self._image_to_epoch[j] = epoch
epochs = self._epoch_to_image.keys()
Debug.write('Exposure epoch for sweep %s: %d %d' % \
(self._template, min(epochs), max(epochs)))
self._input_imageset = copy.deepcopy(self._imageset)
# + get the lattice - can this be a pointer, so that when
# this object updates lattice it is globally-for-this-crystal
# updated? The lattice included directly in here includes an
# exact unit cell for data reduction, the crystal lattice
# contains an approximate unit cell which should be
# from the unit cells from all sweeps contained in the
# XCrystal. FIXME should I be using a LatticeInfo object
# in here? See what the Indexer interface produces. ALT:
# just provide an Indexer implementation "hook".
# See Headnote 001 above. See also _get_indexer,
# _get_integrater below.
self._indexer = None
self._refiner = None
self._integrater = None
# I don't need this - it is equivalent to self.getWavelength(
# ).getCrystal().getLattice()
# self._crystal_lattice = None
# this means that this module will have to present largely the
# same interface as Indexer and Integrater so that the calls
# can be appropriately forwarded.
# finally configure the beam if set
if beam is not None:
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
try:
set_mosflm_beam_centre(self.get_imageset().get_detector(),
self.get_imageset().get_beam(),
beam)
except AssertionError, e:
Debug.write('Error setting mosflm beam centre: %s' % e)
def xia2_main(stop_after=None):
'''Actually process something...'''
Citations.cite('xia2')
# print versions of related software
Chatter.write(dials_version())
ccp4_version = get_ccp4_version()
if ccp4_version is not None:
Chatter.write('CCP4 %s' % ccp4_version)
start_time = time.time()
CommandLine = get_command_line()
start_dir = Flags.get_starting_directory()
# check that something useful has been assigned for processing...
xtals = CommandLine.get_xinfo().get_crystals()
no_images = True
for name in xtals.keys():
xtal = xtals[name]
if not xtal.get_all_image_names():
Chatter.write('-----------------------------------' + \
'-' * len(name))
Chatter.write('| No images assigned for crystal %s |' % name)
Chatter.write('-----------------------------------' + '-' \
* len(name))
else:
no_images = False
args = []
from xia2.Handlers.Phil import PhilIndex
params = PhilIndex.get_python_object()
mp_params = params.xia2.settings.multiprocessing
njob = mp_params.njob
from libtbx import group_args
xinfo = CommandLine.get_xinfo()
if os.path.exists('xia2.json'):
from xia2.Schema.XProject import XProject
xinfo_new = xinfo
xinfo = XProject.from_json(filename='xia2.json')
crystals = xinfo.get_crystals()
crystals_new = xinfo_new.get_crystals()
for crystal_id in crystals_new.keys():
if crystal_id not in crystals:
crystals[crystal_id] = crystals_new[crystal_id]
continue
crystals[crystal_id]._scaler = None # reset scaler
for wavelength_id in crystals_new[crystal_id].get_wavelength_names(
):
wavelength_new = crystals_new[crystal_id].get_xwavelength(
wavelength_id)
if wavelength_id not in crystals[
crystal_id].get_wavelength_names():
crystals[crystal_id].add_wavelength(
crystals_new[crystal_id].get_xwavelength(
wavelength_new))
continue
wavelength = crystals[crystal_id].get_xwavelength(
wavelength_id)
sweeps_new = wavelength_new.get_sweeps()
sweeps = wavelength.get_sweeps()
sweep_names = [s.get_name() for s in sweeps]
sweep_keys = [(s.get_directory(), s.get_template(),
s.get_image_range()) for s in sweeps]
for sweep in sweeps_new:
if ((sweep.get_directory(), sweep.get_template(),
sweep.get_image_range()) not in sweep_keys):
if sweep.get_name() in sweep_names:
i = 1
while 'SWEEEP%i' % i in sweep_names:
i += 1
sweep._name = 'SWEEP%i' % i
break
wavelength.add_sweep(
name=sweep.get_name(),
sample=sweep.get_xsample(),
directory=sweep.get_directory(),
image=sweep.get_image(),
beam=sweep.get_beam_centre(),
reversephi=sweep.get_reversephi(),
distance=sweep.get_distance(),
gain=sweep.get_gain(),
dmin=sweep.get_resolution_high(),
dmax=sweep.get_resolution_low(),
polarization=sweep.get_polarization(),
frames_to_process=sweep.get_frames_to_process(),
user_lattice=sweep.get_user_lattice(),
user_cell=sweep.get_user_cell(),
epoch=sweep._epoch,
ice=sweep._ice,
excluded_regions=sweep._excluded_regions,
)
sweep_names.append(sweep.get_name())
crystals = xinfo.get_crystals()
failover = params.xia2.settings.failover
if mp_params.mode == 'parallel' and njob > 1:
driver_type = mp_params.type
command_line_args = CommandLine.get_argv()[1:]
for crystal_id in crystals.keys():
for wavelength_id in crystals[crystal_id].get_wavelength_names():
wavelength = crystals[crystal_id].get_xwavelength(
wavelength_id)
sweeps = wavelength.get_sweeps()
for sweep in sweeps:
sweep._get_indexer()
sweep._get_refiner()
sweep._get_integrater()
args.append((group_args(
driver_type=driver_type,
stop_after=stop_after,
failover=failover,
command_line_args=command_line_args,
nproc=mp_params.nproc,
crystal_id=crystal_id,
wavelength_id=wavelength_id,
sweep_id=sweep.get_name(),
), ))
from xia2.Driver.DriverFactory import DriverFactory
default_driver_type = DriverFactory.get_driver_type()
# run every nth job on the current computer (no need to submit to qsub)
for i_job, arg in enumerate(args):
if (i_job % njob) == 0:
arg[0].driver_type = default_driver_type
if mp_params.type == "qsub":
method = "sge"
else:
method = "multiprocessing"
nproc = mp_params.nproc
qsub_command = mp_params.qsub_command
if not qsub_command:
qsub_command = 'qsub'
qsub_command = '%s -V -cwd -pe smp %d' % (qsub_command, nproc)
from libtbx import easy_mp
results = easy_mp.parallel_map(
process_one_sweep,
args,
processes=njob,
#method=method,
method="multiprocessing",
qsub_command=qsub_command,
preserve_order=True,
preserve_exception_message=True)
# Hack to update sweep with the serialized indexers/refiners/integraters
i_sweep = 0
for crystal_id in crystals.keys():
for wavelength_id in crystals[crystal_id].get_wavelength_names():
wavelength = crystals[crystal_id].get_xwavelength(
wavelength_id)
remove_sweeps = []
sweeps = wavelength.get_sweeps()
for sweep in sweeps:
success, output, xsweep_dict = results[i_sweep]
if output is not None:
Chatter.write(output)
if not success:
Chatter.write('Sweep failed: removing %s' %
sweep.get_name())
remove_sweeps.append(sweep)
else:
assert xsweep_dict is not None
Chatter.write('Loading sweep: %s' % sweep.get_name())
from xia2.Schema.XSweep import XSweep
new_sweep = XSweep.from_dict(xsweep_dict)
sweep._indexer = new_sweep._indexer
sweep._refiner = new_sweep._refiner
sweep._integrater = new_sweep._integrater
i_sweep += 1
for sweep in remove_sweeps:
wavelength.remove_sweep(sweep)
sample = sweep.get_xsample()
sample.remove_sweep(sweep)
else:
for crystal_id in crystals.keys():
for wavelength_id in crystals[crystal_id].get_wavelength_names():
wavelength = crystals[crystal_id].get_xwavelength(
wavelength_id)
remove_sweeps = []
sweeps = wavelength.get_sweeps()
for sweep in sweeps:
from dials.command_line.show import show_datablocks
from dxtbx.datablock import DataBlock
Debug.write(sweep.get_name())
Debug.write(
show_datablocks([DataBlock([sweep.get_imageset()])]))
try:
if stop_after == 'index':
sweep.get_indexer_cell()
else:
sweep.get_integrater_intensities()
sweep.serialize()
except Exception as e:
if failover:
Chatter.write('Processing sweep %s failed: %s' % \
(sweep.get_name(), str(e)))
remove_sweeps.append(sweep)
else:
raise
for sweep in remove_sweeps:
wavelength.remove_sweep(sweep)
sample = sweep.get_xsample()
sample.remove_sweep(sweep)
# save intermediate xia2.json file in case scaling step fails
xinfo.as_json(filename='xia2.json')
if stop_after not in ('index', 'integrate'):
Chatter.write(xinfo.get_output(), strip=False)
for crystal in crystals.values():
crystal.serialize()
# save final xia2.json file in case report generation fails
xinfo.as_json(filename='xia2.json')
duration = time.time() - start_time
# write out the time taken in a human readable way
Chatter.write('Processing took %s' % \
time.strftime("%Hh %Mm %Ss", time.gmtime(duration)))
if stop_after not in ('index', 'integrate'):
# and the summary file
with open('xia2-summary.dat', 'w') as fh:
for record in xinfo.summarise():
fh.write('%s\n' % record)
# looks like this import overwrites the initial command line
# Phil overrides so... for https://github.com/xia2/xia2/issues/150
from xia2.command_line.html import generate_xia2_html
if params.xia2.settings.small_molecule == True:
params.xia2.settings.report.xtriage_analysis = False
params.xia2.settings.report.include_radiation_damage = False
generate_xia2_html(xinfo,
filename='xia2.html',
params=params.xia2.settings.report)
write_citations()
# delete all of the temporary mtz files...
cleanup()
Environment.cleanup()
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 compute_nmol_from_volume(volume, mass, resolution):
file = open(nmolparams, 'r')
while 1:
line = file.readline()
if not line[0] == '#':
break
resolutions = map(float, line.split(','))[:13]
P0_list = map(float, file.readline().split(','))[:13]
Vm_bar_list = map(float, file.readline().split(','))[:13]
w_list = map(float, file.readline().split(','))[:13]
A_list = map(float, file.readline().split(','))[:13]
s_list = map(float, file.readline().split(','))[:13]
file.close()
if resolution > resolutions[-1]:
# raise RuntimeError, 'Resolution outside useful range'
Chatter.write('Resolution lower than %s -> computing for %f' % \
(resolutions[-1], resolution))
resolution = resolutions[-1]
if resolution < resolutions[0]:
Chatter.write('Resolution higher than peak %f -> %f' % \
(resolution, resolutions[0]))
resolution = resolutions[0]
start = 0
for start in range(12):
if resolution > resolutions[start] and \
resolution < resolutions[start + 1]:
break
# can start at start - interpolate
diff = (resolution - resolutions[start]) / \
(resolutions[start + 1] - resolutions[start])
P0 = P0_list[start] + diff * (P0_list[start + 1] - P0_list[start])
Vm_bar = Vm_bar_list[start] + \
diff * (Vm_bar_list[start + 1] - Vm_bar_list[start])
w = w_list[start] + diff * (w_list[start + 1] - w_list[start])
A = A_list[start] + diff * (A_list[start + 1] - A_list[start])
s = s_list[start] + diff * (s_list[start + 1] - s_list[start])
nmols = []
pdfs = []
nmol = 1
Vm = volume / (mass * nmol)
while 1:
z = (Vm - Vm_bar) / w
p = P0 + A * math.exp(- math.exp(-z) - z * s + 1)
nmols.append(nmol)
pdfs.append(p)
nmol += 1
Vm = volume / (mass * nmol)
if Vm < 1.0:
break
return nmols, pdfs
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 _mosflm_parallel_integrate(self):
'''Perform the integration as before, but this time as a
number of parallel Mosflm jobs (hence, in separate directories)
and including a step of pre-refinement of the mosaic spread and
missets. This will all be kind of explicit and hence probably
messy!'''
refinr = self.get_integrater_refiner()
lattice = refinr.get_refiner_lattice()
spacegroup_number = lattice_to_spacegroup(lattice)
mosaic = refinr.get_refiner_payload('mosaic')
beam = refinr.get_refiner_payload('beam')
distance = refinr.get_refiner_payload('distance')
matrix = refinr.get_refiner_payload('mosflm_orientation_matrix')
integration_params = refinr.get_refiner_payload(
'mosflm_integration_parameters')
if integration_params:
if 'separation' in integration_params:
self.set_integrater_parameter(
'mosflm', 'separation',
'%s %s' % tuple(integration_params['separation']))
if 'raster' in integration_params:
self.set_integrater_parameter(
'mosflm', 'raster',
'%d %d %d %d %d' % tuple(integration_params['raster']))
refinr.set_refiner_payload('mosflm_integration_parameters', None)
pname, xname, dname = self.get_integrater_project_info()
# what follows below should (i) be run in separate directories
# and (ii) be repeated N=parallel times.
nproc = PhilIndex.params.xia2.settings.multiprocessing.nproc
parallel = nproc
# FIXME this is something of a kludge - if too few frames refinement
# and integration does not work well... ideally want at least 15
# frames / chunk (say)
nframes = self._intgr_wedge[1] - self._intgr_wedge[0] + 1
if parallel > nframes / 15:
parallel = nframes // 15
if not parallel:
raise RuntimeError, 'parallel not set'
if parallel < 2:
raise RuntimeError, 'parallel not parallel: %s' % parallel
jobs = []
hklouts = []
nref = 0
# calculate the chunks to use
offset = self.get_frame_offset()
start = self._intgr_wedge[0] - offset
end = self._intgr_wedge[1] - offset
left_images = 1 + end - start
left_chunks = parallel
chunks = []
while left_images > 0:
size = left_images // left_chunks
chunks.append((start, start + size - 1))
start += size
left_images -= size
left_chunks -= 1
summary_files = []
for j in range(parallel):
# make some working directories, as necessary - chunk-(0:N-1)
wd = os.path.join(self.get_working_directory(),
'chunk-%d' % j)
if not os.path.exists(wd):
os.makedirs(wd)
job = MosflmIntegrate()
job.set_working_directory(wd)
auto_logfiler(job)
l = refinr.get_refiner_lattice()
# create the starting point
f = open(os.path.join(wd, 'xiaintegrate-%s.mat' % l), 'w')
for m in matrix:
f.write(m)
f.close()
spacegroup_number = lattice_to_spacegroup(lattice)
job.set_refine_profiles(self._mosflm_refine_profiles)
# N.B. for harvesting need to append N to dname.
if pname is not None and xname is not None and dname is not None:
Debug.write('Harvesting: %s/%s/%s' %
(pname, xname, dname))
harvest_dir = self.get_working_directory()
temp_dname = '%s_%s' % \
(dname, self.get_integrater_sweep_name())
job.set_pname_xname_dname(pname, xname, temp_dname)
job.set_template(os.path.basename(self.get_template()))
job.set_directory(self.get_directory())
# check for ice - and if so, exclude (ranges taken from
# XDS documentation)
if self.get_integrater_ice() != 0:
Debug.write('Excluding ice rings')
job.set_exclude_ice(True)
# exclude specified resolution ranges
if len(self.get_integrater_excluded_regions()) != 0:
regions = self.get_integrater_excluded_regions()
Debug.write('Excluding regions: %s' % `regions`)
job.set_exclude_regions(regions)
mask = standard_mask(self.get_detector())
for m in mask:
job.add_instruction(m)
job.set_input_mat_file('xiaintegrate-%s.mat' % l)
job.set_beam_centre(beam)
job.set_distance(distance)
job.set_space_group_number(spacegroup_number)
job.set_mosaic(mosaic)
if self.get_wavelength_prov() == 'user':
job.set_wavelength(self.get_wavelength())
parameters = self.get_integrater_parameters('mosflm')
job.update_parameters(parameters)
if self._mosflm_gain:
job.set_gain(self._mosflm_gain)
# check for resolution limits
if self._intgr_reso_high > 0.0:
job.set_d_min(self._intgr_reso_high)
if self._intgr_reso_low:
job.set_d_max(self._intgr_reso_low)
if PhilIndex.params.general.backstop_mask:
from xia2.Toolkit.BackstopMask import BackstopMask
mask = BackstopMask(PhilIndex.params.general.backstop_mask)
mask = mask.calculate_mask_mosflm(self.get_header())
job.set_mask(mask)
detector = self.get_detector()
detector_width, detector_height = detector[0].get_image_size_mm()
lim_x = 0.5 * detector_width
lim_y = 0.5 * detector_height
Debug.write('Scanner limits: %.1f %.1f' % (lim_x, lim_y))
job.set_limits(lim_x, lim_y)
job.set_fix_mosaic(self._mosflm_postref_fix_mosaic)
job.set_pre_refinement(True)
job.set_image_range(chunks[j])
# these are now running so ...
jobs.append(job)
continue
# ok, at this stage I need to ...
#
# (i) accumulate the statistics as a function of batch
# (ii) mong them into a single block
#
# This is likely to be a pain in the arse!
first_integrated_batch = 1.0e6
last_integrated_batch = -1.0e6
all_residuals = []
threads = []
for j in range(parallel):
job = jobs[j]
# now wait for them to finish - first wait will really be the
# first one, then all should be finished...
thread = Background(job, 'run')
thread.start()
threads.append(thread)
mosaics = []
postref_result = { }
integrated_images_first = 1.0e6
integrated_images_last = -1.0e6
self._intgr_per_image_statistics = {}
for j in range(parallel):
thread = threads[j]
thread.stop()
job = jobs[j]
# get the log file
output = job.get_all_output()
# record a copy of it, perhaps - though not if parallel
if self.get_integrater_sweep_name() and False:
pname, xname, dname = self.get_integrater_project_info()
FileHandler.record_log_file(
'%s %s %s %s mosflm integrate' % \
(self.get_integrater_sweep_name(),
pname, xname, '%s_%d' % (dname, j)),
job.get_log_file())
# look for things that we want to know...
# that is, the output reflection file name, the updated
# value for the gain (if present,) any warnings, errors,
# or just interesting facts.
batches = job.get_batches_out()
integrated_images_first = min(batches[0], integrated_images_first)
integrated_images_last = max(batches[1], integrated_images_last)
mosaics.extend(job.get_mosaic_spreads())
if min(mosaics) < 0:
raise IntegrationError, 'negative mosaic spread: %s' % min(mosaic)
if (job.get_detector_gain_error() and not
(self.get_imageset().get_detector()[0].get_type() == 'SENSOR_PAD')):
gain = job.get_suggested_gain()
if gain is not None:
self.set_integrater_parameter('mosflm', 'gain', gain)
self.set_integrater_export_parameter('mosflm', 'gain', gain)
if self._mosflm_gain:
Debug.write('GAIN updated to %f' % gain)
else:
Debug.write('GAIN found to be %f' % gain)
self._mosflm_gain = gain
self._mosflm_rerun_integration = True
hklout = job.get_hklout()
Debug.write('Integration output: %s' % hklout)
hklouts.append(hklout)
nref += job.get_nref()
# if a BGSIG error happened try not refining the
# profile and running again...
if job.get_bgsig_too_large():
if not self._mosflm_refine_profiles:
raise RuntimeError, 'BGSIG error with profiles fixed'
Debug.write(
'BGSIG error detected - try fixing profile...')
self._mosflm_refine_profiles = False
self.set_integrater_done(False)
return
if job.get_getprof_error():
Debug.write(
'GETPROF error detected - try fixing profile...')
self._mosflm_refine_profiles = False
self.set_integrater_done(False)
return
# here
# write the report for each image as .*-#$ to Chatter -
# detailed report will be written automagically to science...
self._intgr_per_image_statistics.update(job.get_per_image_statistics())
postref_result.update(job.get_postref_result())
# inspect the output for e.g. very high weighted residuals
all_residuals.extend(job.get_residuals())
self._intgr_batches_out = (integrated_images_first,
integrated_images_last)
if mosaics and len(mosaics) > 0:
self.set_integrater_mosaic_min_mean_max(
min(mosaics), sum(mosaics) / len(mosaics), max(mosaics))
else:
m = indxr.get_indexer_mosaic()
self.set_integrater_mosaic_min_mean_max(m, m, m)
Chatter.write(self.show_per_image_statistics())
Chatter.write('Mosaic spread: %.3f < %.3f < %.3f' % \
self.get_integrater_mosaic_min_mean_max())
# gather the statistics from the postrefinement for all sweeps
# now write this to a postrefinement log
postref_log = os.path.join(self.get_working_directory(),
'postrefinement.log')
fout = open(postref_log, 'w')
fout.write('$TABLE: Postrefinement for %s:\n' % \
self._intgr_sweep_name)
fout.write('$GRAPHS: Missetting angles:A:1, 2, 3, 4: $$\n')
fout.write('Batch PhiX PhiY PhiZ $$ Batch PhiX PhiY PhiZ $$\n')
for image in sorted(postref_result):
phix = postref_result[image].get('phix', 0.0)
phiy = postref_result[image].get('phiy', 0.0)
phiz = postref_result[image].get('phiz', 0.0)
fout.write('%d %5.2f %5.2f %5.2f\n' % \
(image, phix, phiy, phiz))
fout.write('$$\n')
fout.close()
if self.get_integrater_sweep_name():
pname, xname, dname = self.get_integrater_project_info()
FileHandler.record_log_file('%s %s %s %s postrefinement' % \
(self.get_integrater_sweep_name(),
pname, xname, dname),
postref_log)
hklouts.sort()
hklout = os.path.join(self.get_working_directory(),
os.path.split(hklouts[0])[-1])
Debug.write('Sorting data to %s' % hklout)
for hklin in hklouts:
Debug.write('<= %s' % hklin)
sortmtz = Sortmtz()
sortmtz.set_hklout(hklout)
for hklin in hklouts:
sortmtz.add_hklin(hklin)
sortmtz.sort()
self._mosflm_hklout = hklout
return self._mosflm_hklout