def _integrate_finish(self): '''Finish the integration - if necessary performing reindexing based on the pointgroup and the reindexing operator.''' if self._intgr_reindex_operator is None and \ self._intgr_spacegroup_number == lattice_to_spacegroup( self.get_integrater_refiner().get_refiner_lattice()): return self._mosflm_hklout if self._intgr_reindex_operator is None and \ self._intgr_spacegroup_number == 0: return self._mosflm_hklout Debug.write('Reindexing to spacegroup %d (%s)' % \ (self._intgr_spacegroup_number, self._intgr_reindex_operator)) hklin = self._mosflm_hklout reindex = Reindex() reindex.set_working_directory(self.get_working_directory()) auto_logfiler(reindex) reindex.set_operator(self._intgr_reindex_operator) if self._intgr_spacegroup_number: reindex.set_spacegroup(self._intgr_spacegroup_number) hklout = '%s_reindex.mtz' % hklin[:-4] reindex.set_hklin(hklin) reindex.set_hklout(hklout) reindex.reindex() return hklout
def _index(self): '''Implement the indexer interface.''' Citations.cite('mosflm') indexer = MosflmIndex() indexer.set_working_directory(self.get_working_directory()) auto_logfiler(indexer) from xia2.lib.bits import unique_elements _images = unique_elements(self._indxr_images) indexer.set_images(_images) images_str = ', '.join(map(str, _images)) cell_str = None if self._indxr_input_cell: cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % \ self._indxr_input_cell if self._indxr_sweep_name: #if len(self._fp_directory) <= 50: #dirname = self._fp_directory #else: #dirname = '...%s' % self._fp_directory[-46:] dirname = os.path.dirname(self.get_imageset().get_template()) Journal.block( 'autoindexing', self._indxr_sweep_name, 'mosflm', { 'images': images_str, 'target cell': self._indxr_input_cell, 'target lattice': self._indxr_input_lattice, 'template': self.get_imageset().get_template(), 'directory': dirname }) #task = 'Autoindex from images:' #for i in _images: #task += ' %s' % self.get_image_name(i) #self.set_task(task) indexer.set_template(os.path.basename(self.get_template())) indexer.set_directory(self.get_directory()) xsweep = self.get_indexer_sweep() if xsweep is not None: if xsweep.get_distance() is not None: indexer.set_distance(xsweep.get_distance()) #if self.get_wavelength_prov() == 'user': #index.set_wavelength(self.get_wavelength()) if xsweep.get_beam_centre() is not None: indexer.set_beam_centre(xsweep.get_beam_centre()) if self._indxr_input_cell: indexer.set_unit_cell(self._indxr_input_cell) if self._indxr_input_lattice is not None: spacegroup_number = lattice_to_spacegroup( self._indxr_input_lattice) indexer.set_space_group_number(spacegroup_number) if not self._mosflm_autoindex_thresh: try: min_peaks = 200 Debug.write('Aiming for at least %d spots...' % min_peaks) thresholds = [] for i in _images: p = Printpeaks() p.set_working_directory(self.get_working_directory()) auto_logfiler(p) p.set_image(self.get_image_name(i)) thresh = p.threshold(min_peaks) Debug.write('Autoindex threshold for image %d: %d' % \ (i, thresh)) thresholds.append(thresh) thresh = min(thresholds) self._mosflm_autoindex_thresh = thresh except Exception as e: print str(e) #XXX this should disappear! Debug.write('Error computing threshold: %s' % str(e)) Debug.write('Using default of 20.0') thresh = 20.0 else: thresh = self._mosflm_autoindex_thresh Debug.write('Using autoindex threshold: %d' % thresh) if self._mosflm_autoindex_sol: indexer.set_solution_number(self._mosflm_autoindex_sol) indexer.set_threshold(thresh) # now forget this to prevent weird things happening later on if self._mosflm_autoindex_sol: self._mosflm_autoindex_sol = 0 indexer.run() indxr_cell = indexer.get_refined_unit_cell() self._indxr_lattice = indexer.get_lattice() space_group_number = indexer.get_indexed_space_group_number() detector_distance = indexer.get_refined_distance() beam_centre = indexer.get_refined_beam_centre() mosaic_spreads = indexer.get_mosaic_spreads() if min(list(indxr_cell)) < 10.0 and \ indxr_cell[2] / indxr_cell[0] > 6: Debug.write('Unrealistic autoindexing solution: ' + '%.2f %.2f %.2f %.2f %.2f %.2f' % indxr_cell) # tweak some parameters and try again... self._mosflm_autoindex_thresh *= 1.5 self.set_indexer_done(False) return intgr_params = {} # look up other possible indexing solutions (not well - in # standard settings only!) This is moved earlier as it could # result in returning if Mosflm has selected the wrong # solution! try: self._indxr_other_lattice_cell = indexer.get_solutions() # Change 27/FEB/08 to support user assigned spacegroups if self._indxr_user_input_lattice: lattice_to_spacegroup_dict = { 'aP': 1, 'mP': 3, 'mC': 5, 'oP': 16, 'oC': 20, 'oF': 22, 'oI': 23, 'tP': 75, 'tI': 79, 'hP': 143, 'hR': 146, 'cP': 195, 'cF': 196, 'cI': 197 } for k in self._indxr_other_lattice_cell.keys(): if lattice_to_spacegroup_dict[k] > \ lattice_to_spacegroup_dict[ self._indxr_input_lattice]: del (self._indxr_other_lattice_cell[k]) # check that the selected unit cell matches - and if # not raise a "horrible" exception if self._indxr_input_cell: assert indxr_cell is not None for j in range(6): if math.fabs(self._indxr_input_cell[j] - indxr_cell[j]) > 2.0: Chatter.write('Mosflm autoindexing did not select ' + 'correct (target) unit cell') raise RuntimeError( 'something horrible happened in indexing') except RuntimeError as e: # check if mosflm rejected a solution we have it if 'horribl' in str(e): # ok it did - time to break out the big guns... if not self._indxr_input_cell: raise RuntimeError( 'error in solution selection when not preset') # XXX FIXME self._mosflm_autoindex_sol = _get_indexing_solution_number( indexer.get_all_output(), self._indxr_input_cell, self._indxr_input_lattice) # set the fact that we are not done... self.set_indexer_done(False) # and return - hopefully this will restart everything return else: raise e if len(mosaic_spreads) == 0: # then consider setting it do a default value... # equal to the oscillation width (a good guess) phi_width = self.get_phi_width() Chatter.write( 'Mosaic estimation failed, so guessing at %4.2f' % \ phi_width) # only consider this if we have thus far no idea on the # mosaic spread... mosaic_spreads.append(phi_width) intgr_params['raster'] = indexer.get_raster() intgr_params['separation'] = indexer.get_separation() self._indxr_resolution_estimate = indexer.get_resolution_estimate() # compute mosaic as mean(mosaic_spreads) self._indxr_mosaic = sum(mosaic_spreads) / len(mosaic_spreads) self._indxr_payload['mosflm_integration_parameters'] = intgr_params self._indxr_payload['mosflm_orientation_matrix'] = open( os.path.join(self.get_working_directory(), 'xiaindex.mat'), 'r').readlines() import copy from dxtbx.model.detector_helpers import set_mosflm_beam_centre from xia2.Wrappers.Mosflm.AutoindexHelpers import set_distance from xia2.Wrappers.Mosflm.AutoindexHelpers import crystal_model_from_mosflm_mat from cctbx import sgtbx, uctbx # update the beam centre (i.e. shift the origin of the detector) detector = copy.deepcopy(self.get_detector()) beam = copy.deepcopy(self.get_beam()) set_mosflm_beam_centre(detector, beam, beam_centre) if detector_distance is not None: set_distance(detector, detector_distance) # make a dxtbx crystal_model object from the mosflm matrix space_group = sgtbx.space_group_info(number=space_group_number).group() crystal_model = crystal_model_from_mosflm_mat( self._indxr_payload['mosflm_orientation_matrix'], unit_cell=uctbx.unit_cell(tuple(indxr_cell)), space_group=space_group) # construct an experiment_list from dxtbx.model import Experiment, ExperimentList experiment = Experiment(beam=beam, detector=detector, goniometer=self.get_goniometer(), scan=self.get_scan(), crystal=crystal_model) experiment_list = ExperimentList([experiment]) self.set_indexer_experiment_list(experiment_list)
def _integrate_finish(self): '''Finish off the integration by running dials.export.''' # FIXME - do we want to export every time we call this method # (the file will not have changed) and also (more important) do # we want a different exported MTZ file every time (I do not think # that we do; these can be very large) - was exporter.get_xpid() -> # now dials exporter = self.ExportMtz() exporter.set_reflections_filename(self._intgr_integrated_pickle) mtz_filename = os.path.join( self.get_working_directory(), '%s_integrated.mtz' % 'dials') exporter.set_mtz_filename(mtz_filename) exporter.run() self._intgr_integrated_filename = mtz_filename # record integrated MTZ file for e.g. BLEND. pname, xname, dname = self.get_integrater_project_info() sweep = self.get_integrater_sweep_name() FileHandler.record_more_data_file( '%s %s %s %s INTEGRATE' % (pname, xname, dname, sweep), mtz_filename) if not os.path.isfile(self._intgr_integrated_filename): raise RuntimeError("dials.export failed: %s does not exist." % self._intgr_integrated_filename) if self._intgr_reindex_operator is None and \ self._intgr_spacegroup_number == lattice_to_spacegroup( self.get_integrater_refiner().get_refiner_lattice()): Debug.write('Not reindexing to spacegroup %d (%s)' % \ (self._intgr_spacegroup_number, self._intgr_reindex_operator)) return mtz_filename if self._intgr_reindex_operator is None and \ self._intgr_spacegroup_number == 0: Debug.write('Not reindexing to spacegroup %d (%s)' % \ (self._intgr_spacegroup_number, self._intgr_reindex_operator)) return mtz_filename Debug.write('Reindexing to spacegroup %d (%s)' % \ (self._intgr_spacegroup_number, self._intgr_reindex_operator)) hklin = mtz_filename reindex = Reindex() reindex.set_working_directory(self.get_working_directory()) auto_logfiler(reindex) reindex.set_operator(self._intgr_reindex_operator) if self._intgr_spacegroup_number: reindex.set_spacegroup(self._intgr_spacegroup_number) else: reindex.set_spacegroup(lattice_to_spacegroup( self.get_integrater_refiner().get_refiner_lattice())) hklout = '%s_reindex.mtz' % hklin[:-4] reindex.set_hklin(hklin) reindex.set_hklout(hklout) reindex.reindex() self._intgr_integrated_filename = hklout self._intgr_cell = reindex.get_cell() pname, xname, dname = self.get_integrater_project_info() sweep = self.get_integrater_sweep_name() FileHandler.record_more_data_file( '%s %s %s %s experiments' % (pname, xname, dname, sweep), self.get_integrated_experiments()) from iotbx.reflection_file_reader import any_reflection_file miller_arrays = any_reflection_file(hklout).as_miller_arrays() # look for profile-fitted intensities intensities = [ma for ma in miller_arrays if ma.info().labels == ['IPR', 'SIGIPR']] if len(intensities) == 0: # look instead for summation-integrated intensities intensities = [ma for ma in miller_arrays if ma.info().labels == ['I', 'SIGI']] assert len(intensities) self._intgr_n_ref = intensities[0].size() return hklout
def _index(self): '''Actually index the diffraction pattern. Note well that this is not going to compute the matrix...''' # acknowledge this program Citations.cite('labelit') Citations.cite('distl') #self.reset() _images = [] for i in self._indxr_images: for j in i: if not j in _images: _images.append(j) _images.sort() images_str = '%d' % _images[0] for i in _images[1:]: images_str += ', %d' % i cell_str = None if self._indxr_input_cell: cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % \ self._indxr_input_cell if self._indxr_sweep_name: # then this is a proper autoindexing run - describe this # to the journal entry #if len(self._fp_directory) <= 50: #dirname = self._fp_directory #else: #dirname = '...%s' % self._fp_directory[-46:] dirname = os.path.dirname(self.get_imageset().get_template()) Journal.block( 'autoindexing', self._indxr_sweep_name, 'labelit', { 'images': images_str, 'target cell': cell_str, 'target lattice': self._indxr_input_lattice, 'template': self.get_imageset().get_template(), 'directory': dirname }) if len(_images) > 4: raise RuntimeError('cannot use more than 4 images') from xia2.Wrappers.Labelit.LabelitIndex import LabelitIndex index = LabelitIndex() index.set_working_directory(self.get_working_directory()) auto_logfiler(index) #task = 'Autoindex from images:' #for i in _images: #task += ' %s' % self.get_image_name(i) #self.set_task(task) Debug.write('Indexing from images:') for i in _images: index.add_image(self.get_image_name(i)) Debug.write('%s' % self.get_image_name(i)) xsweep = self.get_indexer_sweep() if xsweep is not None: if xsweep.get_distance() is not None: index.set_distance(xsweep.get_distance()) #if self.get_wavelength_prov() == 'user': #index.set_wavelength(self.get_wavelength()) if xsweep.get_beam_centre() is not None: index.set_beam_centre(xsweep.get_beam_centre()) if self._refine_beam is False: index.set_refine_beam(False) else: index.set_refine_beam(True) index.set_beam_search_scope(self._beam_search_scope) if ((math.fabs(self.get_wavelength() - 1.54) < 0.01) or (math.fabs(self.get_wavelength() - 2.29) < 0.01)): index.set_Cu_KA_or_Cr_KA(True) #sweep = self.get_indexer_sweep_name() #FileHandler.record_log_file( #'%s INDEX' % (sweep), self.get_log_file()) try: index.run() except RuntimeError as e: if self._refine_beam is False: raise e # can we improve the situation? if self._beam_search_scope < 4.0: self._beam_search_scope += 4.0 # try repeating the indexing! self.set_indexer_done(False) return 'failed' # otherwise this is beyond redemption raise e self._solutions = index.get_solutions() # FIXME this needs to check the smilie status e.g. # ":)" or ";(" or " ". # FIXME need to check the value of the RMSD and raise an # exception if the P1 solution has an RMSD > 1.0... # Change 27/FEB/08 to support user assigned spacegroups # (euugh!) have to "ignore" solutions with higher symmetry # otherwise the rest of xia will override us. Bummer. for i, solution in self._solutions.iteritems(): if self._indxr_user_input_lattice: if (lattice_to_spacegroup(solution['lattice']) > lattice_to_spacegroup(self._indxr_input_lattice)): Debug.write('Ignoring solution: %s' % solution['lattice']) del self._solutions[i] # check the RMSD from the triclinic unit cell if self._solutions[1]['rmsd'] > 1.0 and False: # don't know when this is useful - but I know when it is not! raise RuntimeError('high RMSD for triclinic solution') # configure the "right" solution self._solution = self.get_solution() # now store also all of the other solutions... keyed by the # lattice - however these should only be added if they # have a smiley in the appropriate record, perhaps? for solution in self._solutions.keys(): lattice = self._solutions[solution]['lattice'] if lattice in self._indxr_other_lattice_cell: if self._indxr_other_lattice_cell[lattice]['goodness'] < \ self._solutions[solution]['metric']: continue self._indxr_other_lattice_cell[lattice] = { 'goodness': self._solutions[solution]['metric'], 'cell': self._solutions[solution]['cell'] } self._indxr_lattice = self._solution['lattice'] self._indxr_cell = tuple(self._solution['cell']) self._indxr_mosaic = self._solution['mosaic'] lms = LabelitMosflmScript() lms.set_working_directory(self.get_working_directory()) lms.set_solution(self._solution['number']) self._indxr_payload['mosflm_orientation_matrix'] = lms.calculate() # get the beam centre from the mosflm script - mosflm # may have inverted the beam centre and labelit will know # this! mosflm_beam_centre = lms.get_mosflm_beam() if mosflm_beam_centre: self._indxr_payload['mosflm_beam_centre'] = tuple( mosflm_beam_centre) import copy detector = copy.deepcopy(self.get_detector()) beam = copy.deepcopy(self.get_beam()) from dxtbx.model.detector_helpers import set_mosflm_beam_centre set_mosflm_beam_centre(detector, beam, mosflm_beam_centre) from xia2.Experts.SymmetryExpert import lattice_to_spacegroup_number from scitbx import matrix from cctbx import sgtbx, uctbx from dxtbx.model import CrystalFactory mosflm_matrix = matrix.sqr([ float(i) for line in lms.calculate() for i in line.replace("-", " -").split() ][:9]) space_group = sgtbx.space_group_info( lattice_to_spacegroup_number(self._solution['lattice'])).group() crystal_model = CrystalFactory.from_mosflm_matrix( mosflm_matrix, unit_cell=uctbx.unit_cell(tuple(self._solution['cell'])), space_group=space_group) from dxtbx.model import Experiment, ExperimentList experiment = Experiment( beam=beam, detector=detector, goniometer=self.get_goniometer(), scan=self.get_scan(), crystal=crystal_model, ) experiment_list = ExperimentList([experiment]) self.set_indexer_experiment_list(experiment_list) # also get an estimate of the resolution limit from the # labelit.stats_distl output... FIXME the name is wrong! lsd = LabelitStats_distl() lsd.set_working_directory(self.get_working_directory()) lsd.stats_distl() resolution = 1.0e6 for i in _images: stats = lsd.get_statistics(self.get_image_name(i)) resol = 0.5 * (stats['resol_one'] + stats['resol_two']) if resol < resolution: resolution = resol self._indxr_resolution_estimate = resolution return 'ok'
def _index(self): """Actually index the diffraction pattern. Note well that this is not going to compute the matrix...""" # acknowledge this program if not self._indxr_images: raise RuntimeError("No good spots found on any images") Citations.cite("labelit") Citations.cite("distl") _images = [] for i in self._indxr_images: for j in i: if not j in _images: _images.append(j) _images.sort() images_str = "%d" % _images[0] for i in _images[1:]: images_str += ", %d" % i cell_str = None if self._indxr_input_cell: cell_str = "%.2f %.2f %.2f %.2f %.2f %.2f" % self._indxr_input_cell if self._indxr_sweep_name: # then this is a proper autoindexing run - describe this # to the journal entry if len(self._fp_directory) <= 50: dirname = self._fp_directory else: dirname = "...%s" % self._fp_directory[-46:] Journal.block( "autoindexing", self._indxr_sweep_name, "labelit", { "images": images_str, "target cell": cell_str, "target lattice": self._indxr_input_lattice, "template": self._fp_template, "directory": dirname, }, ) # auto_logfiler(self) from xia2.Wrappers.Labelit.LabelitIndex import LabelitIndex index = LabelitIndex() index.set_working_directory(self.get_working_directory()) auto_logfiler(index) # task = 'Autoindex from images:' # for i in _images: # task += ' %s' % self.get_image_name(i) # self.set_task(task) # self.add_command_line('--index_only') Debug.write("Indexing from images:") for i in _images: index.add_image(self.get_image_name(i)) Debug.write("%s" % self.get_image_name(i)) if self._primitive_unit_cell: index.set_primitive_unit_cell(self._primitive_unit_cell) if self._indxr_input_cell: index.set_max_cell(1.25 * max(self._indxr_input_cell[:3])) xsweep = self.get_indexer_sweep() if xsweep is not None: if xsweep.get_distance() is not None: index.set_distance(xsweep.get_distance()) # if self.get_wavelength_prov() == 'user': # index.set_wavelength(self.get_wavelength()) if xsweep.get_beam_centre() is not None: index.set_beam_centre(xsweep.get_beam_centre()) if self._refine_beam is False: index.set_refine_beam(False) else: index.set_refine_beam(True) index.set_beam_search_scope(self._beam_search_scope) if (math.fabs(self.get_wavelength() - 1.54) < 0.01) or (math.fabs(self.get_wavelength() - 2.29) < 0.01): index.set_Cu_KA_or_Cr_KA(True) try: index.run() except RuntimeError as e: if self._refine_beam is False: raise e # can we improve the situation? if self._beam_search_scope < 4.0: self._beam_search_scope += 4.0 # try repeating the indexing! self.set_indexer_done(False) return "failed" # otherwise this is beyond redemption raise e self._solutions = index.get_solutions() # FIXME this needs to check the smilie status e.g. # ":)" or ";(" or " ". # FIXME need to check the value of the RMSD and raise an # exception if the P1 solution has an RMSD > 1.0... # Change 27/FEB/08 to support user assigned spacegroups # (euugh!) have to "ignore" solutions with higher symmetry # otherwise the rest of xia will override us. Bummer. for i, solution in self._solutions.iteritems(): if self._indxr_user_input_lattice: if lattice_to_spacegroup( solution["lattice"]) > lattice_to_spacegroup( self._indxr_input_lattice): Debug.write("Ignoring solution: %s" % solution["lattice"]) del self._solutions[i] # configure the "right" solution self._solution = self.get_solution() # now store also all of the other solutions... keyed by the # lattice - however these should only be added if they # have a smiley in the appropriate record, perhaps? for solution in self._solutions.keys(): lattice = self._solutions[solution]["lattice"] if lattice in self._indxr_other_lattice_cell: if (self._indxr_other_lattice_cell[lattice]["goodness"] < self._solutions[solution]["metric"]): continue self._indxr_other_lattice_cell[lattice] = { "goodness": self._solutions[solution]["metric"], "cell": self._solutions[solution]["cell"], } self._indxr_lattice = self._solution["lattice"] self._indxr_cell = tuple(self._solution["cell"]) self._indxr_mosaic = self._solution["mosaic"] lms = LabelitMosflmMatrix() lms.set_working_directory(self.get_working_directory()) lms.set_solution(self._solution["number"]) self._indxr_payload["mosflm_orientation_matrix"] = lms.calculate() # get the beam centre from the mosflm script - mosflm # may have inverted the beam centre and labelit will know # this! mosflm_beam_centre = lms.get_mosflm_beam() if mosflm_beam_centre: self._indxr_payload["mosflm_beam_centre"] = tuple( mosflm_beam_centre) detector = copy.deepcopy(self.get_detector()) beam = copy.deepcopy(self.get_beam()) from dxtbx.model.detector_helpers import set_mosflm_beam_centre set_mosflm_beam_centre(detector, beam, mosflm_beam_centre) from xia2.Experts.SymmetryExpert import lattice_to_spacegroup_number from scitbx import matrix from cctbx import sgtbx, uctbx from dxtbx.model import CrystalFactory mosflm_matrix = matrix.sqr([ float(i) for line in lms.calculate() for i in line.replace("-", " -").split() ][:9]) space_group = sgtbx.space_group_info( lattice_to_spacegroup_number(self._solution["lattice"])).group() crystal_model = CrystalFactory.from_mosflm_matrix( mosflm_matrix, unit_cell=uctbx.unit_cell(tuple(self._solution["cell"])), space_group=space_group, ) from dxtbx.model import Experiment, ExperimentList experiment = Experiment( beam=beam, detector=detector, goniometer=self.get_goniometer(), scan=self.get_scan(), crystal=crystal_model, ) experiment_list = ExperimentList([experiment]) self.set_indexer_experiment_list(experiment_list) # also get an estimate of the resolution limit from the # labelit.stats_distl output... FIXME the name is wrong! lsd = LabelitStats_distl() lsd.set_working_directory(self.get_working_directory()) lsd.stats_distl() resolution = 1.0e6 for i in _images: stats = lsd.get_statistics(self.get_image_name(i)) resol = 0.5 * (stats["resol_one"] + stats["resol_two"]) if resol < resolution: resolution = resol self._indxr_resolution_estimate = resolution return "ok"
def _mosflm_refine_cell(self, idxr, set_spacegroup=None): '''Perform the refinement of the unit cell. This will populate all of the information needed to perform the integration.''' # FIXME this will die after #1285 #if not self.get_integrater_indexer(): #Debug.write('Replacing indexer of %s with self at %d' % \ #(str(self.get_integrater_indexer()), __line__)) #self.set_integrater_indexer(self) #idxr = self.get_integrater_indexer() if not idxr.get_indexer_payload('mosflm_orientation_matrix'): raise RuntimeError('unexpected situation in indexing') lattice = idxr.get_indexer_lattice() mosaic = idxr.get_indexer_mosaic() cell = idxr.get_indexer_cell() beam_centre = idxr.get_indexer_beam_centre() # bug # 3174 - if mosaic is very small (here defined to be # 0.25 x osc_width) then set to this minimum value. phi_width = idxr.get_phi_width() if mosaic < 0.25 * phi_width: mosaic = 0.25 * phi_width if idxr.get_indexer_payload('mosflm_beam_centre'): beam_centre = idxr.get_indexer_payload('mosflm_beam_centre') distance = idxr.get_indexer_distance() matrix = idxr.get_indexer_payload('mosflm_orientation_matrix') integration_params = idxr.get_indexer_payload( 'mosflm_integration_parameters') if integration_params is None: integration_params = {} if integration_params: if 'separation' in integration_params: self.set_refiner_parameter( 'mosflm', 'separation', '%f %f' % tuple(integration_params['separation'])) if 'raster' in integration_params: self.set_refiner_parameter( 'mosflm', 'raster', '%d %d %d %d %d' % tuple(integration_params['raster'])) idxr.set_indexer_payload('mosflm_integration_parameters', None) spacegroup_number = lattice_to_spacegroup(lattice) # copy these into myself for later reference, if indexer # is not myself - everything else is copied via the # cell refinement process... from cctbx import sgtbx from dxtbx.model import Crystal from dxtbx.model.detector_helpers import set_mosflm_beam_centre experiment = idxr.get_indexer_experiment_list()[0] set_mosflm_beam_centre(experiment.detector, experiment.beam, beam_centre) space_group = sgtbx.space_group_info(number=spacegroup_number).group() a, b, c = experiment.crystal.get_real_space_vectors() experiment.crystal = Crystal(a, b, c, space_group=space_group) # FIXME surely these have been assigned further up?! if not self._mosflm_cell_ref_images: self._mosflm_cell_ref_images = self._refine_select_images(mosaic) f = open( os.path.join(self.get_working_directory(), 'xiaindex-%s.mat' % lattice), 'w') for m in matrix: f.write(m) f.close() # then start the cell refinement refiner = MosflmRefineCell() refiner.set_working_directory(self.get_working_directory()) auto_logfiler(refiner) if self._mosflm_gain: refiner.set_gain(self._mosflm_gain) refiner.set_template(os.path.basename(idxr.get_template())) refiner.set_directory(idxr.get_directory()) refiner.set_input_mat_file('xiaindex-%s.mat' % lattice) refiner.set_output_mat_file('xiarefine.mat') refiner.set_beam_centre(beam_centre) refiner.set_unit_cell(cell) refiner.set_distance(distance) if set_spacegroup: refiner.set_space_group_number(set_spacegroup) else: refiner.set_space_group_number(spacegroup_number) # FIXME 18/JUN/08 - it may help to have an overestimate # of the mosaic spread in here as it *may* refine down # better than up... - this is not a good idea as it may # also not refine at all! - 12972 # integration failed # Bug # 3103 if self._mosflm_cell_ref_double_mosaic: mosaic *= 2.0 refiner.set_mosaic(mosaic) # if set, use the resolution for cell refinement - see # bug # 2078... if self._mosflm_cell_ref_resolution: refiner.set_resolution(self._mosflm_cell_ref_resolution) refiner.set_fix_mosaic(self._mosflm_postref_fix_mosaic) # note well that the beam centre is coming from indexing so # should be already properly handled #if idxr.get_wavelength_prov() == 'user': #refiner.set_wavelength(idxr.get_wavelength()) # belt + braces mode - only to be used when considering failover, # will run an additional step of autoindexing prior to cell # refinement, to be used only after proving that not going it # will result in cell refinement failure - will use the first # wedge... N.B. this is only useful if the indexer is Labelit # not Mosflm... refiner.set_add_autoindex(self._mosflm_cell_ref_add_autoindex) # get all of the stored parameter values parameters = self.get_refiner_parameters('mosflm') refiner.update_parameters(parameters) detector = idxr.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)) refiner.set_limits(lim_x, lim_y) refiner.set_images(self._mosflm_cell_ref_images) failover = PhilIndex.params.xia2.settings.failover if failover and not self._mosflm_cell_ref_add_autoindex: refiner.set_ignore_cell_refinement_failure(True) refiner.run() # then look to see if the cell refinement worked ok - if it # didn't then this may indicate that the lattice was wrongly # selected. cell_refinement_ok = refiner.cell_refinement_ok() if not cell_refinement_ok: Debug.write('Repeating cell refinement...') self.set_integrater_prepare_done(False) self._mosflm_cell_ref_add_autoindex = True return [0.0], [0.0] rms_values = refiner.get_rms_values() background_residual = refiner.get_background_residual() self._refinr_cell = refiner.get_refined_unit_cell() distance = refiner.get_refined_distance2() experiment = idxr.get_indexer_experiment_list()[0] from xia2.Wrappers.Mosflm.AutoindexHelpers import set_distance set_distance(experiment.detector, distance) self.set_refiner_parameter('mosflm', 'distortion yscale', refiner.get_refined_distortion_yscale()) self.set_refiner_parameter('mosflm', 'raster', refiner.get_raster()) #integration_params['distortion yscale'] \ #= refiner.get_refined_distortion_yscale() #integration_params['raster'] = refiner.get_raster() separation = refiner.get_separation() if separation is not None: self.set_refiner_parameter('mosflm', 'separation', '%s %s' % refiner.get_separation()) #integration_params['separation'] = refiner.get_separation() self.set_refiner_parameter('mosflm', 'beam', '%s %s' % refiner.get_refined_beam_centre()) self.set_refiner_parameter('mosflm', 'distance', refiner.get_refined_distance()) self.set_refiner_parameter('mosflm', 'distortion tilt', refiner.get_refined_distortion_tilt()) self.set_refiner_parameter('mosflm', 'distortion twist', refiner.get_refined_distortion_twist()) integration_params['beam'] = tuple( float(b) for b in refiner.get_refined_beam_centre()) integration_params['distance'] = refiner.get_refined_distance() integration_params[ 'distortion tilt'] = refiner.get_refined_distortion_tilt() integration_params[ 'distortion twist'] = refiner.get_refined_distortion_twist() idxr._indxr_mosaic = refiner.get_refined_mosaic() idxr.set_indexer_payload( 'mosflm_orientation_matrix', open(os.path.join(self.get_working_directory(), 'xiarefine.mat'), 'r').readlines()) self.set_refiner_payload( 'mosflm_orientation_matrix', idxr.get_indexer_payload('mosflm_orientation_matrix')) self.set_refiner_payload('mosaic', refiner.get_refined_mosaic()) self.set_refiner_payload('beam', integration_params['beam']) self.set_refiner_payload('distance', integration_params['distance']) from xia2.Wrappers.Mosflm.AutoindexHelpers import crystal_model_from_mosflm_mat # make a dxtbx crystal_model object from the mosflm matrix experiment = idxr.get_indexer_experiment_list()[0] crystal_model = crystal_model_from_mosflm_mat( idxr._indxr_payload['mosflm_orientation_matrix'], unit_cell=refiner.get_refined_unit_cell(), space_group=experiment.crystal.get_space_group()) experiment.crystal = crystal_model #self.set_refiner_payload( #'mosflm_integration_parameters', integration_params) self._refinr_refined_experiment_list = ExperimentList([experiment]) return rms_values, background_residual
def _mosflm_test_refine_cell(self, idxr, test_lattice): '''Test performing cell refinement in with a different lattice to the one which was selected by the autoindex procedure. This should not change anything in the class.''' #idxr = self.get_integrater_indexer() lattice = idxr.get_indexer_lattice() mosaic = idxr.get_indexer_mosaic() beam_centre = idxr.get_indexer_beam_centre() distance = idxr.get_indexer_distance() matrix = idxr.get_indexer_payload('mosflm_orientation_matrix') phi_width = idxr.get_phi_width() if mosaic < 0.25 * phi_width: mosaic = 0.25 * phi_width input_matrix = '' for m in matrix: input_matrix += '%s\n' % m new_matrix = transmogrify_matrix(lattice, input_matrix, test_lattice, idxr.get_wavelength(), self.get_working_directory()) spacegroup_number = lattice_to_spacegroup(test_lattice) if not self._mosflm_cell_ref_images: raise RuntimeError('wedges must be assigned already') open( os.path.join(self.get_working_directory(), 'test-xiaindex-%s.mat' % lattice), 'w').write(new_matrix) refiner = MosflmRefineCell() refiner.set_working_directory(self.get_working_directory()) auto_logfiler(refiner) if self._mosflm_gain: refiner.set_gain(self._mosflm_gain) refiner.set_template(os.path.basename(idxr.get_template())) refiner.set_directory(idxr.get_directory()) refiner.set_input_mat_file('test-xiaindex-%s.mat' % lattice) refiner.set_output_mat_file('test-xiarefine.mat') refiner.set_beam_centre(beam_centre) refiner.set_distance(distance) refiner.set_space_group_number(spacegroup_number) # FIXME 18/JUN/08 - it may help to have an overestimate # of the mosaic spread in here as it *may* refine down # better than up... - this is not a good idea as it may # also not refine at all! - 12972 # integration failed # Bug # 3103 if self._mosflm_cell_ref_double_mosaic: mosaic *= 2.0 refiner.set_mosaic(mosaic) # if set, use the resolution for cell refinement - see # bug # 2078... if self._mosflm_cell_ref_resolution: refiner.set_resolution(self._mosflm_cell_ref_resolution) refiner.set_fix_mosaic(self._mosflm_postref_fix_mosaic) # note well that the beam centre is coming from indexing so # should be already properly handled #if idxr.get_wavelength_prov() == 'user': #refiner.set_wavelength(idxr.get_wavelength()) # belt + braces mode - only to be used when considering failover, # will run an additional step of autoindexing prior to cell # refinement, to be used only after proving that not going it # will result in cell refinement failure - will use the first # wedge... N.B. this is only useful if the indexer is Labelit # not Mosflm... refiner.set_add_autoindex(self._mosflm_cell_ref_add_autoindex) # XXX # get all of the stored parameter values parameters = self.get_refiner_parameters('mosflm') refiner.update_parameters(parameters) detector = idxr.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)) refiner.set_limits(lim_x, lim_y) refiner.set_images(self._mosflm_cell_ref_images) refiner.run() rms_values = refiner.get_rms_values() background_residual = refiner.get_background_residual() return rms_values, background_residual
def _mosflm_parallel_integrate(self): '''Perform the integration as before, but this time as a number of parallel Mosflm jobs (hence, in separate directories) and including a step of pre-refinement of the mosaic spread and missets. This will all be kind of explicit and hence probably messy!''' refinr = self.get_integrater_refiner() lattice = refinr.get_refiner_lattice() spacegroup_number = lattice_to_spacegroup(lattice) mosaic = refinr.get_refiner_payload('mosaic') beam = refinr.get_refiner_payload('beam') distance = refinr.get_refiner_payload('distance') matrix = refinr.get_refiner_payload('mosflm_orientation_matrix') integration_params = refinr.get_refiner_payload( 'mosflm_integration_parameters') if integration_params: if 'separation' in integration_params: self.set_integrater_parameter( 'mosflm', 'separation', '%s %s' % tuple(integration_params['separation'])) if 'raster' in integration_params: self.set_integrater_parameter( 'mosflm', 'raster', '%d %d %d %d %d' % tuple(integration_params['raster'])) refinr.set_refiner_payload('mosflm_integration_parameters', None) pname, xname, dname = self.get_integrater_project_info() # what follows below should (i) be run in separate directories # and (ii) be repeated N=parallel times. nproc = PhilIndex.params.xia2.settings.multiprocessing.nproc parallel = nproc # FIXME this is something of a kludge - if too few frames refinement # and integration does not work well... ideally want at least 15 # frames / chunk (say) nframes = self._intgr_wedge[1] - self._intgr_wedge[0] + 1 if parallel > nframes / 15: parallel = nframes // 15 if not parallel: raise RuntimeError('parallel not set') if parallel < 2: raise RuntimeError('parallel not parallel: %s' % parallel) jobs = [] hklouts = [] nref = 0 # calculate the chunks to use offset = self.get_frame_offset() start = self._intgr_wedge[0] - offset end = self._intgr_wedge[1] - offset left_images = 1 + end - start left_chunks = parallel chunks = [] while left_images > 0: size = left_images // left_chunks chunks.append((start, start + size - 1)) start += size left_images -= size left_chunks -= 1 summary_files = [] for j in range(parallel): # make some working directories, as necessary - chunk-(0:N-1) wd = os.path.join(self.get_working_directory(), 'chunk-%d' % j) if not os.path.exists(wd): os.makedirs(wd) job = MosflmIntegrate() job.set_working_directory(wd) auto_logfiler(job) l = refinr.get_refiner_lattice() # create the starting point f = open(os.path.join(wd, 'xiaintegrate-%s.mat' % l), 'w') for m in matrix: f.write(m) f.close() spacegroup_number = lattice_to_spacegroup(lattice) job.set_refine_profiles(self._mosflm_refine_profiles) # N.B. for harvesting need to append N to dname. if pname is not None and xname is not None and dname is not None: Debug.write('Harvesting: %s/%s/%s' % (pname, xname, dname)) harvest_dir = self.get_working_directory() temp_dname = '%s_%s' % \ (dname, self.get_integrater_sweep_name()) job.set_pname_xname_dname(pname, xname, temp_dname) job.set_template(os.path.basename(self.get_template())) job.set_directory(self.get_directory()) # check for ice - and if so, exclude (ranges taken from # XDS documentation) if self.get_integrater_ice() != 0: Debug.write('Excluding ice rings') job.set_exclude_ice(True) # exclude specified resolution ranges if len(self.get_integrater_excluded_regions()) != 0: regions = self.get_integrater_excluded_regions() Debug.write('Excluding regions: %s' % repr(regions)) job.set_exclude_regions(regions) mask = standard_mask(self.get_detector()) for m in mask: job.add_instruction(m) job.set_input_mat_file('xiaintegrate-%s.mat' % l) job.set_beam_centre(beam) job.set_distance(distance) job.set_space_group_number(spacegroup_number) job.set_mosaic(mosaic) if self.get_wavelength_prov() == 'user': job.set_wavelength(self.get_wavelength()) parameters = self.get_integrater_parameters('mosflm') job.update_parameters(parameters) if self._mosflm_gain: job.set_gain(self._mosflm_gain) # check for resolution limits if self._intgr_reso_high > 0.0: job.set_d_min(self._intgr_reso_high) if self._intgr_reso_low: job.set_d_max(self._intgr_reso_low) if PhilIndex.params.general.backstop_mask: from xia2.Toolkit.BackstopMask import BackstopMask mask = BackstopMask(PhilIndex.params.general.backstop_mask) mask = mask.calculate_mask_mosflm(self.get_header()) job.set_mask(mask) detector = self.get_detector() detector_width, detector_height = detector[0].get_image_size_mm() lim_x = 0.5 * detector_width lim_y = 0.5 * detector_height Debug.write('Scanner limits: %.1f %.1f' % (lim_x, lim_y)) job.set_limits(lim_x, lim_y) job.set_fix_mosaic(self._mosflm_postref_fix_mosaic) job.set_pre_refinement(True) job.set_image_range(chunks[j]) # these are now running so ... jobs.append(job) continue # ok, at this stage I need to ... # # (i) accumulate the statistics as a function of batch # (ii) mong them into a single block # # This is likely to be a pain in the arse! first_integrated_batch = 1.0e6 last_integrated_batch = -1.0e6 all_residuals = [] threads = [] for j in range(parallel): job = jobs[j] # now wait for them to finish - first wait will really be the # first one, then all should be finished... thread = Background(job, 'run') thread.start() threads.append(thread) mosaics = [] postref_result = {} integrated_images_first = 1.0e6 integrated_images_last = -1.0e6 self._intgr_per_image_statistics = {} for j in range(parallel): thread = threads[j] thread.stop() job = jobs[j] # get the log file output = job.get_all_output() # record a copy of it, perhaps - though not if parallel if self.get_integrater_sweep_name() and False: pname, xname, dname = self.get_integrater_project_info() FileHandler.record_log_file( '%s %s %s %s mosflm integrate' % \ (self.get_integrater_sweep_name(), pname, xname, '%s_%d' % (dname, j)), job.get_log_file()) # look for things that we want to know... # that is, the output reflection file name, the updated # value for the gain (if present,) any warnings, errors, # or just interesting facts. batches = job.get_batches_out() integrated_images_first = min(batches[0], integrated_images_first) integrated_images_last = max(batches[1], integrated_images_last) mosaics.extend(job.get_mosaic_spreads()) if min(mosaics) < 0: raise IntegrationError('negative mosaic spread: %s' % min(mosaic)) if (job.get_detector_gain_error() and not (self.get_imageset().get_detector()[0].get_type() == 'SENSOR_PAD')): gain = job.get_suggested_gain() if gain is not None: self.set_integrater_parameter('mosflm', 'gain', gain) self.set_integrater_export_parameter( 'mosflm', 'gain', gain) if self._mosflm_gain: Debug.write('GAIN updated to %f' % gain) else: Debug.write('GAIN found to be %f' % gain) self._mosflm_gain = gain self._mosflm_rerun_integration = True hklout = job.get_hklout() Debug.write('Integration output: %s' % hklout) hklouts.append(hklout) nref += job.get_nref() # if a BGSIG error happened try not refining the # profile and running again... if job.get_bgsig_too_large(): if not self._mosflm_refine_profiles: raise RuntimeError('BGSIG error with profiles fixed') Debug.write('BGSIG error detected - try fixing profile...') self._mosflm_refine_profiles = False self.set_integrater_done(False) return if job.get_getprof_error(): Debug.write('GETPROF error detected - try fixing profile...') self._mosflm_refine_profiles = False self.set_integrater_done(False) return # here # write the report for each image as .*-#$ to Chatter - # detailed report will be written automagically to science... self._intgr_per_image_statistics.update( job.get_per_image_statistics()) postref_result.update(job.get_postref_result()) # inspect the output for e.g. very high weighted residuals all_residuals.extend(job.get_residuals()) self._intgr_batches_out = (integrated_images_first, integrated_images_last) if mosaics and len(mosaics) > 0: self.set_integrater_mosaic_min_mean_max( min(mosaics), sum(mosaics) / len(mosaics), max(mosaics)) else: m = indxr.get_indexer_mosaic() self.set_integrater_mosaic_min_mean_max(m, m, m) Chatter.write(self.show_per_image_statistics()) Chatter.write('Mosaic spread: %.3f < %.3f < %.3f' % \ self.get_integrater_mosaic_min_mean_max()) # gather the statistics from the postrefinement for all sweeps # now write this to a postrefinement log postref_log = os.path.join(self.get_working_directory(), 'postrefinement.log') fout = open(postref_log, 'w') fout.write('$TABLE: Postrefinement for %s:\n' % \ self._intgr_sweep_name) fout.write('$GRAPHS: Missetting angles:A:1, 2, 3, 4: $$\n') fout.write('Batch PhiX PhiY PhiZ $$ Batch PhiX PhiY PhiZ $$\n') for image in sorted(postref_result): phix = postref_result[image].get('phix', 0.0) phiy = postref_result[image].get('phiy', 0.0) phiz = postref_result[image].get('phiz', 0.0) fout.write('%d %5.2f %5.2f %5.2f\n' % \ (image, phix, phiy, phiz)) fout.write('$$\n') fout.close() if self.get_integrater_sweep_name(): pname, xname, dname = self.get_integrater_project_info() FileHandler.record_log_file('%s %s %s %s postrefinement' % \ (self.get_integrater_sweep_name(), pname, xname, dname), postref_log) hklouts.sort() hklout = os.path.join(self.get_working_directory(), os.path.split(hklouts[0])[-1]) Debug.write('Sorting data to %s' % hklout) for hklin in hklouts: Debug.write('<= %s' % hklin) sortmtz = Sortmtz() sortmtz.set_hklout(hklout) for hklin in hklouts: sortmtz.add_hklin(hklin) sortmtz.sort() self._mosflm_hklout = hklout return self._mosflm_hklout
def _mosflm_integrate(self): '''Perform the actual integration, based on the results of the cell refinement or indexing (they have the equivalent form.)''' refinr = self.get_integrater_refiner() if not refinr.get_refiner_payload('mosflm_orientation_matrix'): raise RuntimeError('unexpected situation in indexing') lattice = refinr.get_refiner_lattice() spacegroup_number = lattice_to_spacegroup(lattice) mosaic = refinr.get_refiner_payload('mosaic') beam = refinr.get_refiner_payload('beam') distance = refinr.get_refiner_payload('distance') matrix = refinr.get_refiner_payload('mosflm_orientation_matrix') integration_params = refinr.get_refiner_payload( 'mosflm_integration_parameters') if integration_params: if 'separation' in integration_params: self.set_integrater_parameter( 'mosflm', 'separation', '%s %s' % tuple(integration_params['separation'])) if 'raster' in integration_params: self.set_integrater_parameter( 'mosflm', 'raster', '%d %d %d %d %d' % tuple(integration_params['raster'])) refinr.set_refiner_payload('mosflm_integration_parameters', None) f = open( os.path.join(self.get_working_directory(), 'xiaintegrate.mat'), 'w') for m in matrix: f.write(m) f.close() # then start the integration integrater = MosflmIntegrate() integrater.set_working_directory(self.get_working_directory()) auto_logfiler(integrater) integrater.set_refine_profiles(self._mosflm_refine_profiles) pname, xname, dname = self.get_integrater_project_info() if pname is not None and xname is not None and dname is not None: Debug.write('Harvesting: %s/%s/%s' % (pname, xname, dname)) harvest_dir = self.get_working_directory() # harvest file name will be %s.mosflm_run_start_end % dname temp_dname = '%s_%s' % \ (dname, self.get_integrater_sweep_name()) integrater.set_pname_xname_dname(pname, xname, temp_dname) integrater.set_template(os.path.basename(self.get_template())) integrater.set_directory(self.get_directory()) # check for ice - and if so, exclude (ranges taken from # XDS documentation) if self.get_integrater_ice() != 0: Debug.write('Excluding ice rings') integrater.set_exclude_ice(True) # exclude specified resolution ranges if len(self.get_integrater_excluded_regions()) != 0: regions = self.get_integrater_excluded_regions() Debug.write('Excluding regions: %s' % repr(regions)) integrater.set_exclude_regions(regions) mask = standard_mask(self.get_detector()) for m in mask: integrater.add_instruction(m) integrater.set_input_mat_file('xiaintegrate.mat') integrater.set_beam_centre(beam) integrater.set_distance(distance) integrater.set_space_group_number(spacegroup_number) integrater.set_mosaic(mosaic) if self.get_wavelength_prov() == 'user': integrater.set_wavelength(self.get_wavelength()) parameters = self.get_integrater_parameters('mosflm') integrater.update_parameters(parameters) if self._mosflm_gain: integrater.set_gain(self._mosflm_gain) # check for resolution limits if self._intgr_reso_high > 0.0: integrater.set_d_min(self._intgr_reso_high) if self._intgr_reso_low: integrater.set_d_max(self._intgr_reso_low) if PhilIndex.params.general.backstop_mask: from xia2.Toolkit.BackstopMask import BackstopMask mask = BackstopMask(PhilIndex.params.general.backstop_mask) mask = mask.calculate_mask_mosflm(self.get_header()) integrater.set_mask(mask) detector = self.get_detector() detector_width, detector_height = detector[0].get_image_size_mm() lim_x = 0.5 * detector_width lim_y = 0.5 * detector_height Debug.write('Scanner limits: %.1f %.1f' % (lim_x, lim_y)) integrater.set_limits(lim_x, lim_y) integrater.set_fix_mosaic(self._mosflm_postref_fix_mosaic) offset = self.get_frame_offset() integrater.set_image_range( (self._intgr_wedge[0] - offset, self._intgr_wedge[1] - offset)) try: integrater.run() except RuntimeError as e: if 'integration failed: reason unknown' in str(e): Chatter.write('Mosflm has failed in integration') message = 'The input was:\n\n' for input in integrater.get_all_input(): message += ' %s' % input Chatter.write(message) raise FileHandler.record_log_file( '%s %s %s %s mosflm integrate' % \ (self.get_integrater_sweep_name(), pname, xname, dname), integrater.get_log_file()) self._intgr_per_image_statistics = integrater.get_per_image_statistics( ) self._mosflm_hklout = integrater.get_hklout() Debug.write('Integration output: %s' % self._mosflm_hklout) self._intgr_n_ref = integrater.get_nref() # if a BGSIG error happened try not refining the # profile and running again... if integrater.get_bgsig_too_large(): if not self._mosflm_refine_profiles: raise RuntimeError('BGSIG error with profiles fixed') Debug.write('BGSIG error detected - try fixing profile...') self._mosflm_refine_profiles = False self.set_integrater_done(False) return if integrater.get_getprof_error(): Debug.write('GETPROF error detected - try fixing profile...') self._mosflm_refine_profiles = False self.set_integrater_done(False) return if (integrater.get_detector_gain_error() and not (self.get_imageset().get_detector()[0].get_type() == 'SENSOR_PAD')): gain = integrater.get_suggested_gain() if gain is not None: self.set_integrater_parameter('mosflm', 'gain', gain) self.set_integrater_export_parameter('mosflm', 'gain', gain) if self._mosflm_gain: Debug.write('GAIN updated to %f' % gain) else: Debug.write('GAIN found to be %f' % gain) self._mosflm_gain = gain self._mosflm_rerun_integration = True if not self._mosflm_hklout: raise RuntimeError('processing abandoned') self._intgr_batches_out = integrater.get_batches_out() mosaics = integrater.get_mosaic_spreads() if mosaics and len(mosaics) > 0: self.set_integrater_mosaic_min_mean_max( min(mosaics), sum(mosaics) / len(mosaics), max(mosaics)) else: m = indxr.get_indexer_mosaic() self.set_integrater_mosaic_min_mean_max(m, m, m) # write the report for each image as .*-#$ to Chatter - # detailed report will be written automagically to science... Chatter.write(self.show_per_image_statistics()) Chatter.write('Mosaic spread: %.3f < %.3f < %.3f' % \ self.get_integrater_mosaic_min_mean_max()) # gather the statistics from the postrefinement postref_result = integrater.get_postref_result() # now write this to a postrefinement log postref_log = os.path.join(self.get_working_directory(), 'postrefinement.log') fout = open(postref_log, 'w') fout.write('$TABLE: Postrefinement for %s:\n' % \ self._intgr_sweep_name) fout.write('$GRAPHS: Missetting angles:A:1, 2, 3, 4: $$\n') fout.write('Batch PhiX PhiY PhiZ $$ Batch PhiX PhiY PhiZ $$\n') for image in sorted(postref_result): phix = postref_result[image].get('phix', 0.0) phiy = postref_result[image].get('phiy', 0.0) phiz = postref_result[image].get('phiz', 0.0) fout.write('%d %5.2f %5.2f %5.2f\n' % \ (image, phix, phiy, phiz)) fout.write('$$\n') fout.close() if self.get_integrater_sweep_name(): pname, xname, dname = self.get_integrater_project_info() FileHandler.record_log_file('%s %s %s %s postrefinement' % \ (self.get_integrater_sweep_name(), pname, xname, dname), postref_log) return self._mosflm_hklout
def _mosflm_parallel_integrate(self): '''Perform the integration as before, but this time as a number of parallel Mosflm jobs (hence, in separate directories) and including a step of pre-refinement of the mosaic spread and missets. This will all be kind of explicit and hence probably messy!''' refinr = self.get_integrater_refiner() lattice = refinr.get_refiner_lattice() spacegroup_number = lattice_to_spacegroup(lattice) mosaic = refinr.get_refiner_payload('mosaic') beam = refinr.get_refiner_payload('beam') distance = refinr.get_refiner_payload('distance') matrix = refinr.get_refiner_payload('mosflm_orientation_matrix') integration_params = refinr.get_refiner_payload( 'mosflm_integration_parameters') if integration_params: if 'separation' in integration_params: self.set_integrater_parameter( 'mosflm', 'separation', '%s %s' % tuple(integration_params['separation'])) if 'raster' in integration_params: self.set_integrater_parameter( 'mosflm', 'raster', '%d %d %d %d %d' % tuple(integration_params['raster'])) refinr.set_refiner_payload('mosflm_integration_parameters', None) pname, xname, dname = self.get_integrater_project_info() # what follows below should (i) be run in separate directories # and (ii) be repeated N=parallel times. nproc = PhilIndex.params.xia2.settings.multiprocessing.nproc parallel = nproc # FIXME this is something of a kludge - if too few frames refinement # and integration does not work well... ideally want at least 15 # frames / chunk (say) nframes = self._intgr_wedge[1] - self._intgr_wedge[0] + 1 if parallel > nframes / 15: parallel = nframes // 15 if not parallel: raise RuntimeError, 'parallel not set' if parallel < 2: raise RuntimeError, 'parallel not parallel: %s' % parallel jobs = [] hklouts = [] nref = 0 # calculate the chunks to use offset = self.get_frame_offset() start = self._intgr_wedge[0] - offset end = self._intgr_wedge[1] - offset left_images = 1 + end - start left_chunks = parallel chunks = [] while left_images > 0: size = left_images // left_chunks chunks.append((start, start + size - 1)) start += size left_images -= size left_chunks -= 1 summary_files = [] for j in range(parallel): # make some working directories, as necessary - chunk-(0:N-1) wd = os.path.join(self.get_working_directory(), 'chunk-%d' % j) if not os.path.exists(wd): os.makedirs(wd) job = MosflmIntegrate() job.set_working_directory(wd) auto_logfiler(job) l = refinr.get_refiner_lattice() # create the starting point f = open(os.path.join(wd, 'xiaintegrate-%s.mat' % l), 'w') for m in matrix: f.write(m) f.close() spacegroup_number = lattice_to_spacegroup(lattice) job.set_refine_profiles(self._mosflm_refine_profiles) # N.B. for harvesting need to append N to dname. if pname is not None and xname is not None and dname is not None: Debug.write('Harvesting: %s/%s/%s' % (pname, xname, dname)) harvest_dir = self.get_working_directory() temp_dname = '%s_%s' % \ (dname, self.get_integrater_sweep_name()) job.set_pname_xname_dname(pname, xname, temp_dname) job.set_template(os.path.basename(self.get_template())) job.set_directory(self.get_directory()) # check for ice - and if so, exclude (ranges taken from # XDS documentation) if self.get_integrater_ice() != 0: Debug.write('Excluding ice rings') job.set_exclude_ice(True) # exclude specified resolution ranges if len(self.get_integrater_excluded_regions()) != 0: regions = self.get_integrater_excluded_regions() Debug.write('Excluding regions: %s' % `regions`) job.set_exclude_regions(regions) mask = standard_mask(self.get_detector()) for m in mask: job.add_instruction(m) job.set_input_mat_file('xiaintegrate-%s.mat' % l) job.set_beam_centre(beam) job.set_distance(distance) job.set_space_group_number(spacegroup_number) job.set_mosaic(mosaic) if self.get_wavelength_prov() == 'user': job.set_wavelength(self.get_wavelength()) parameters = self.get_integrater_parameters('mosflm') job.update_parameters(parameters) if self._mosflm_gain: job.set_gain(self._mosflm_gain) # check for resolution limits if self._intgr_reso_high > 0.0: job.set_d_min(self._intgr_reso_high) if self._intgr_reso_low: job.set_d_max(self._intgr_reso_low) if PhilIndex.params.general.backstop_mask: from xia2.Toolkit.BackstopMask import BackstopMask mask = BackstopMask(PhilIndex.params.general.backstop_mask) mask = mask.calculate_mask_mosflm(self.get_header()) job.set_mask(mask) detector = self.get_detector() detector_width, detector_height = detector[0].get_image_size_mm() lim_x = 0.5 * detector_width lim_y = 0.5 * detector_height Debug.write('Scanner limits: %.1f %.1f' % (lim_x, lim_y)) job.set_limits(lim_x, lim_y) job.set_fix_mosaic(self._mosflm_postref_fix_mosaic) job.set_pre_refinement(True) job.set_image_range(chunks[j]) # these are now running so ... jobs.append(job) continue # ok, at this stage I need to ... # # (i) accumulate the statistics as a function of batch # (ii) mong them into a single block # # This is likely to be a pain in the arse! first_integrated_batch = 1.0e6 last_integrated_batch = -1.0e6 all_residuals = [] threads = [] for j in range(parallel): job = jobs[j] # now wait for them to finish - first wait will really be the # first one, then all should be finished... thread = Background(job, 'run') thread.start() threads.append(thread) mosaics = [] postref_result = { } integrated_images_first = 1.0e6 integrated_images_last = -1.0e6 self._intgr_per_image_statistics = {} for j in range(parallel): thread = threads[j] thread.stop() job = jobs[j] # get the log file output = job.get_all_output() # record a copy of it, perhaps - though not if parallel if self.get_integrater_sweep_name() and False: pname, xname, dname = self.get_integrater_project_info() FileHandler.record_log_file( '%s %s %s %s mosflm integrate' % \ (self.get_integrater_sweep_name(), pname, xname, '%s_%d' % (dname, j)), job.get_log_file()) # look for things that we want to know... # that is, the output reflection file name, the updated # value for the gain (if present,) any warnings, errors, # or just interesting facts. batches = job.get_batches_out() integrated_images_first = min(batches[0], integrated_images_first) integrated_images_last = max(batches[1], integrated_images_last) mosaics.extend(job.get_mosaic_spreads()) if min(mosaics) < 0: raise IntegrationError, 'negative mosaic spread: %s' % min(mosaic) if (job.get_detector_gain_error() and not (self.get_imageset().get_detector()[0].get_type() == 'SENSOR_PAD')): gain = job.get_suggested_gain() if gain is not None: self.set_integrater_parameter('mosflm', 'gain', gain) self.set_integrater_export_parameter('mosflm', 'gain', gain) if self._mosflm_gain: Debug.write('GAIN updated to %f' % gain) else: Debug.write('GAIN found to be %f' % gain) self._mosflm_gain = gain self._mosflm_rerun_integration = True hklout = job.get_hklout() Debug.write('Integration output: %s' % hklout) hklouts.append(hklout) nref += job.get_nref() # if a BGSIG error happened try not refining the # profile and running again... if job.get_bgsig_too_large(): if not self._mosflm_refine_profiles: raise RuntimeError, 'BGSIG error with profiles fixed' Debug.write( 'BGSIG error detected - try fixing profile...') self._mosflm_refine_profiles = False self.set_integrater_done(False) return if job.get_getprof_error(): Debug.write( 'GETPROF error detected - try fixing profile...') self._mosflm_refine_profiles = False self.set_integrater_done(False) return # here # write the report for each image as .*-#$ to Chatter - # detailed report will be written automagically to science... self._intgr_per_image_statistics.update(job.get_per_image_statistics()) postref_result.update(job.get_postref_result()) # inspect the output for e.g. very high weighted residuals all_residuals.extend(job.get_residuals()) self._intgr_batches_out = (integrated_images_first, integrated_images_last) if mosaics and len(mosaics) > 0: self.set_integrater_mosaic_min_mean_max( min(mosaics), sum(mosaics) / len(mosaics), max(mosaics)) else: m = indxr.get_indexer_mosaic() self.set_integrater_mosaic_min_mean_max(m, m, m) Chatter.write(self.show_per_image_statistics()) Chatter.write('Mosaic spread: %.3f < %.3f < %.3f' % \ self.get_integrater_mosaic_min_mean_max()) # gather the statistics from the postrefinement for all sweeps # now write this to a postrefinement log postref_log = os.path.join(self.get_working_directory(), 'postrefinement.log') fout = open(postref_log, 'w') fout.write('$TABLE: Postrefinement for %s:\n' % \ self._intgr_sweep_name) fout.write('$GRAPHS: Missetting angles:A:1, 2, 3, 4: $$\n') fout.write('Batch PhiX PhiY PhiZ $$ Batch PhiX PhiY PhiZ $$\n') for image in sorted(postref_result): phix = postref_result[image].get('phix', 0.0) phiy = postref_result[image].get('phiy', 0.0) phiz = postref_result[image].get('phiz', 0.0) fout.write('%d %5.2f %5.2f %5.2f\n' % \ (image, phix, phiy, phiz)) fout.write('$$\n') fout.close() if self.get_integrater_sweep_name(): pname, xname, dname = self.get_integrater_project_info() FileHandler.record_log_file('%s %s %s %s postrefinement' % \ (self.get_integrater_sweep_name(), pname, xname, dname), postref_log) hklouts.sort() hklout = os.path.join(self.get_working_directory(), os.path.split(hklouts[0])[-1]) Debug.write('Sorting data to %s' % hklout) for hklin in hklouts: Debug.write('<= %s' % hklin) sortmtz = Sortmtz() sortmtz.set_hklout(hklout) for hklin in hklouts: sortmtz.add_hklin(hklin) sortmtz.sort() self._mosflm_hklout = hklout return self._mosflm_hklout
def _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
def _index(self): '''Actually index the diffraction pattern. Note well that this is not going to compute the matrix...''' # acknowledge this program if not self._indxr_images: raise RuntimeError, 'No good spots found on any images' Citations.cite('labelit') Citations.cite('distl') _images = [] for i in self._indxr_images: for j in i: if not j in _images: _images.append(j) _images.sort() images_str = '%d' % _images[0] for i in _images[1:]: images_str += ', %d' % i cell_str = None if self._indxr_input_cell: cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % \ self._indxr_input_cell if self._indxr_sweep_name: # then this is a proper autoindexing run - describe this # to the journal entry if len(self._fp_directory) <= 50: dirname = self._fp_directory else: dirname = '...%s' % self._fp_directory[-46:] Journal.block( 'autoindexing', self._indxr_sweep_name, 'labelit', {'images':images_str, 'target cell':cell_str, 'target lattice':self._indxr_input_lattice, 'template':self._fp_template, 'directory':dirname}) #auto_logfiler(self) from xia2.Wrappers.Labelit.LabelitIndex import LabelitIndex index = LabelitIndex() index.set_working_directory(self.get_working_directory()) auto_logfiler(index) #task = 'Autoindex from images:' #for i in _images: #task += ' %s' % self.get_image_name(i) #self.set_task(task) #self.add_command_line('--index_only') Debug.write('Indexing from images:') for i in _images: index.add_image(self.get_image_name(i)) Debug.write('%s' % self.get_image_name(i)) if self._indxr_input_lattice and False: index.set_space_group_number( lattice_to_spacegroup(self._indxr_input_lattice)) if self._primitive_unit_cell: index.set_primitive_unit_cell(self._primitive_unit_cell) if self._indxr_input_cell: index.set_max_cell(1.25 * max(self._indxr_input_cell[:3])) xsweep = self.get_indexer_sweep() if xsweep is not None: if xsweep.get_distance() is not None: index.set_distance(xsweep.get_distance()) #if self.get_wavelength_prov() == 'user': #index.set_wavelength(self.get_wavelength()) if xsweep.get_beam_centre() is not None: index.set_beam_centre(xsweep.get_beam_centre()) if self._refine_beam is False: index.set_refine_beam(False) else: index.set_refine_beam(True) index.set_beam_search_scope(self._beam_search_scope) if ((math.fabs(self.get_wavelength() - 1.54) < 0.01) or (math.fabs(self.get_wavelength() - 2.29) < 0.01)): index.set_Cu_KA_or_Cr_KA(True) try: index.run() except RuntimeError, e: if self._refine_beam is False: raise e # can we improve the situation? if self._beam_search_scope < 4.0: self._beam_search_scope += 4.0 # try repeating the indexing! self.set_indexer_done(False) return 'failed' # otherwise this is beyond redemption raise e
def _integrate_finish(self): '''Finish off the integration by running dials.export.''' # FIXME - do we want to export every time we call this method # (the file will not have changed) and also (more important) do # we want a different exported MTZ file every time (I do not think # that we do; these can be very large) - was exporter.get_xpid() -> # now dials exporter = self.ExportMtz() exporter.set_reflections_filename(self._intgr_integrated_pickle) mtz_filename = os.path.join(self.get_working_directory(), '%s_integrated.mtz' % 'dials') exporter.set_mtz_filename(mtz_filename) exporter.run() self._intgr_integrated_filename = mtz_filename # record integrated MTZ file for e.g. BLEND. pname, xname, dname = self.get_integrater_project_info() sweep = self.get_integrater_sweep_name() FileHandler.record_more_data_file( '%s %s %s %s INTEGRATE' % (pname, xname, dname, sweep), mtz_filename) from iotbx.reflection_file_reader import any_reflection_file miller_arrays = any_reflection_file( self._intgr_integrated_filename).as_miller_arrays() # look for profile-fitted intensities intensities = [ ma for ma in miller_arrays if ma.info().labels == ['IPR', 'SIGIPR'] ] if len(intensities) == 0: # look instead for summation-integrated intensities intensities = [ ma for ma in miller_arrays if ma.info().labels == ['I', 'SIGI'] ] assert len(intensities) self._intgr_n_ref = intensities[0].size() if not os.path.isfile(self._intgr_integrated_filename): raise RuntimeError("dials.export failed: %s does not exist." % self._intgr_integrated_filename) if self._intgr_reindex_operator is None and \ self._intgr_spacegroup_number == lattice_to_spacegroup( self.get_integrater_refiner().get_refiner_lattice()): Debug.write('Not reindexing to spacegroup %d (%s)' % \ (self._intgr_spacegroup_number, self._intgr_reindex_operator)) return mtz_filename if self._intgr_reindex_operator is None and \ self._intgr_spacegroup_number == 0: Debug.write('Not reindexing to spacegroup %d (%s)' % \ (self._intgr_spacegroup_number, self._intgr_reindex_operator)) return mtz_filename Debug.write('Reindexing to spacegroup %d (%s)' % \ (self._intgr_spacegroup_number, self._intgr_reindex_operator)) hklin = mtz_filename reindex = Reindex() reindex.set_working_directory(self.get_working_directory()) auto_logfiler(reindex) reindex.set_operator(self._intgr_reindex_operator) if self._intgr_spacegroup_number: reindex.set_spacegroup(self._intgr_spacegroup_number) else: reindex.set_spacegroup( lattice_to_spacegroup( self.get_integrater_refiner().get_refiner_lattice())) hklout = '%s_reindex.mtz' % hklin[:-4] reindex.set_hklin(hklin) reindex.set_hklout(hklout) reindex.reindex() self._intgr_integrated_filename = hklout self._intgr_cell = reindex.get_cell() pname, xname, dname = self.get_integrater_project_info() sweep = self.get_integrater_sweep_name() FileHandler.record_more_data_file( '%s %s %s %s experiments' % (pname, xname, dname, sweep), self.get_integrated_experiments()) return hklout
def _index(self): '''Implement the indexer interface.''' Citations.cite('mosflm') indexer = MosflmIndex() indexer.set_working_directory(self.get_working_directory()) auto_logfiler(indexer) from xia2.lib.bits import unique_elements _images = unique_elements(self._indxr_images) indexer.set_images(_images) images_str = ', '.join(map(str, _images)) cell_str = None if self._indxr_input_cell: cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % \ self._indxr_input_cell if self._indxr_sweep_name: #if len(self._fp_directory) <= 50: #dirname = self._fp_directory #else: #dirname = '...%s' % self._fp_directory[-46:] dirname = os.path.dirname(self.get_imageset().get_template()) Journal.block( 'autoindexing', self._indxr_sweep_name, 'mosflm', {'images':images_str, 'target cell':self._indxr_input_cell, 'target lattice':self._indxr_input_lattice, 'template':self.get_imageset().get_template(), 'directory':dirname}) #task = 'Autoindex from images:' #for i in _images: #task += ' %s' % self.get_image_name(i) #self.set_task(task) indexer.set_template(os.path.basename(self.get_template())) indexer.set_directory(self.get_directory()) xsweep = self.get_indexer_sweep() if xsweep is not None: if xsweep.get_distance() is not None: indexer.set_distance(xsweep.get_distance()) #if self.get_wavelength_prov() == 'user': #index.set_wavelength(self.get_wavelength()) if xsweep.get_beam_centre() is not None: indexer.set_beam_centre(xsweep.get_beam_centre()) if self._indxr_input_cell: indexer.set_unit_cell(self._indxr_input_cell) if self._indxr_input_lattice != None: spacegroup_number = lattice_to_spacegroup( self._indxr_input_lattice) indexer.set_space_group_number(spacegroup_number) if not self._mosflm_autoindex_thresh: try: min_peaks = 200 Debug.write('Aiming for at least %d spots...' % min_peaks) thresholds = [] for i in _images: p = Printpeaks() p.set_working_directory(self.get_working_directory()) auto_logfiler(p) p.set_image(self.get_image_name(i)) thresh = p.threshold(min_peaks) Debug.write('Autoindex threshold for image %d: %d' % \ (i, thresh)) thresholds.append(thresh) thresh = min(thresholds) self._mosflm_autoindex_thresh = thresh except Exception as e: print str(e) #XXX this should disappear! Debug.write('Error computing threshold: %s' % str(e)) Debug.write('Using default of 20.0') thresh = 20.0 else: thresh = self._mosflm_autoindex_thresh Debug.write('Using autoindex threshold: %d' % thresh) if self._mosflm_autoindex_sol: indexer.set_solution_number(self._mosflm_autoindex_sol) indexer.set_threshold(thresh) # now forget this to prevent weird things happening later on if self._mosflm_autoindex_sol: self._mosflm_autoindex_sol = 0 indexer.run() #sweep = self.get_indexer_sweep_name() #FileHandler.record_log_file( #'%s INDEX' % (sweep), self.get_log_file()) indxr_cell = indexer.get_refined_unit_cell() self._indxr_lattice = indexer.get_lattice() space_group_number = indexer.get_indexed_space_group_number() detector_distance = indexer.get_refined_distance() beam_centre = indexer.get_refined_beam_centre() mosaic_spreads = indexer.get_mosaic_spreads() if min(list(indxr_cell)) < 10.0 and \ indxr_cell[2] / indxr_cell[0] > 6: Debug.write( 'Unrealistic autoindexing solution: ' + '%.2f %.2f %.2f %.2f %.2f %.2f' % indxr_cell) # tweak some parameters and try again... self._mosflm_autoindex_thresh *= 1.5 self.set_indexer_done(False) return intgr_params = { } # look up other possible indexing solutions (not well - in # standard settings only!) This is moved earlier as it could # result in returning if Mosflm has selected the wrong # solution! try: self._indxr_other_lattice_cell = indexer.get_solutions() # Change 27/FEB/08 to support user assigned spacegroups if self._indxr_user_input_lattice: lattice_to_spacegroup_dict = { 'aP':1, 'mP':3, 'mC':5, 'oP':16, 'oC':20, 'oF':22, 'oI':23, 'tP':75, 'tI':79, 'hP':143, 'hR':146, 'cP':195, 'cF':196, 'cI':197} for k in self._indxr_other_lattice_cell.keys(): if lattice_to_spacegroup_dict[k] > \ lattice_to_spacegroup_dict[ self._indxr_input_lattice]: del(self._indxr_other_lattice_cell[k]) # check that the selected unit cell matches - and if # not raise a "horrible" exception if self._indxr_input_cell: assert indxr_cell is not None for j in range(6): if math.fabs(self._indxr_input_cell[j] - indxr_cell[j]) > 2.0: Chatter.write( 'Mosflm autoindexing did not select ' + 'correct (target) unit cell') raise RuntimeError, \ 'something horrible happened in indexing' except RuntimeError, e: # check if mosflm rejected a solution we have it if 'horribl' in str(e): # ok it did - time to break out the big guns... if not self._indxr_input_cell: raise RuntimeError, \ 'error in solution selection when not preset' # XXX FIXME self._mosflm_autoindex_sol = _get_indexing_solution_number( indexer.get_all_output(), self._indxr_input_cell, self._indxr_input_lattice) # set the fact that we are not done... self.set_indexer_done(False) # and return - hopefully this will restart everything return else: raise e
def _integrate_finish(self): """Finish off the integration by running dials.export.""" # FIXME - do we want to export every time we call this method # (the file will not have changed) and also (more important) do # we want a different exported MTZ file every time (I do not think # that we do; these can be very large) - was exporter.get_xpid() -> # now dials if self._output_format == "hkl": exporter = self.ExportMtz() exporter.set_reflections_filename( self._intgr_integrated_reflections) mtz_filename = os.path.join(self.get_working_directory(), "%s_integrated.mtz" % "dials") exporter.set_mtz_filename(mtz_filename) exporter.run() self._intgr_integrated_filename = mtz_filename # record integrated MTZ file for e.g. BLEND. pname, xname, dname = self.get_integrater_project_info() sweep = self.get_integrater_sweep_name() FileHandler.record_more_data_file( "%s %s %s %s INTEGRATE" % (pname, xname, dname, sweep), mtz_filename) from iotbx.reflection_file_reader import any_reflection_file miller_arrays = any_reflection_file( self._intgr_integrated_filename).as_miller_arrays() # look for profile-fitted intensities intensities = [ ma for ma in miller_arrays if ma.info().labels == ["IPR", "SIGIPR"] ] if len(intensities) == 0: # look instead for summation-integrated intensities intensities = [ ma for ma in miller_arrays if ma.info().labels == ["I", "SIGI"] ] assert len(intensities) self._intgr_n_ref = intensities[0].size() if not os.path.isfile(self._intgr_integrated_filename): raise RuntimeError("dials.export failed: %s does not exist." % self._intgr_integrated_filename) if (self._intgr_reindex_operator is None and self._intgr_spacegroup_number == lattice_to_spacegroup( self.get_integrater_refiner().get_refiner_lattice())): Debug.write("Not reindexing to spacegroup %d (%s)" % (self._intgr_spacegroup_number, self._intgr_reindex_operator)) return mtz_filename if (self._intgr_reindex_operator is None and self._intgr_spacegroup_number == 0): Debug.write("Not reindexing to spacegroup %d (%s)" % (self._intgr_spacegroup_number, self._intgr_reindex_operator)) return mtz_filename Debug.write( "Reindexing to spacegroup %d (%s)" % (self._intgr_spacegroup_number, self._intgr_reindex_operator)) hklin = mtz_filename from xia2.Wrappers.CCP4.Reindex import Reindex reindex = Reindex() reindex.set_working_directory(self.get_working_directory()) auto_logfiler(reindex) reindex.set_operator(self._intgr_reindex_operator) if self._intgr_spacegroup_number: reindex.set_spacegroup(self._intgr_spacegroup_number) else: reindex.set_spacegroup( lattice_to_spacegroup( self.get_integrater_refiner().get_refiner_lattice())) hklout = "%s_reindex.mtz" % hklin[:-4] reindex.set_hklin(hklin) reindex.set_hklout(hklout) reindex.reindex() self._intgr_integrated_filename = hklout self._intgr_cell = reindex.get_cell() pname, xname, dname = self.get_integrater_project_info() sweep = self.get_integrater_sweep_name() FileHandler.record_more_data_file( "%s %s %s %s" % (pname, xname, dname, sweep), self.get_integrated_experiments(), ) FileHandler.record_more_data_file( "%s %s %s %s" % (pname, xname, dname, sweep), self.get_integrated_reflections(), ) return hklout elif self._output_format == "pickle": if (self._intgr_reindex_operator is None and self._intgr_spacegroup_number == lattice_to_spacegroup( self.get_integrater_refiner().get_refiner_lattice())): Debug.write("Not reindexing to spacegroup %d (%s)" % (self._intgr_spacegroup_number, self._intgr_reindex_operator)) return self._intgr_integrated_reflections if (self._intgr_reindex_operator is None and self._intgr_spacegroup_number == 0): Debug.write("Not reindexing to spacegroup %d (%s)" % (self._intgr_spacegroup_number, self._intgr_reindex_operator)) return self._intgr_integrated_reflections Debug.write( "Reindexing to spacegroup %d (%s)" % (self._intgr_spacegroup_number, self._intgr_reindex_operator)) from xia2.Wrappers.Dials.Reindex import Reindex reindex = Reindex() reindex.set_working_directory(self.get_working_directory()) auto_logfiler(reindex) reindex.set_cb_op(self._intgr_reindex_operator) if self._intgr_spacegroup_number: reindex.set_space_group(self._intgr_spacegroup_number) else: reindex.set_space_group( lattice_to_spacegroup( self.get_integrater_refiner().get_refiner_lattice())) reindex.set_experiments_filename(self.get_integrated_experiments()) reindex.set_indexed_filename(self.get_integrated_reflections()) reindex.run() self._intgr_integrated_reflections = ( reindex.get_reindexed_reflections_filename()) self._intgr_integrated_filename = ( reindex.get_reindexed_reflections_filename()) self._intgr_experiments_filename = ( reindex.get_reindexed_experiments_filename()) pname, xname, dname = self.get_integrater_project_info() sweep = self.get_integrater_sweep_name() FileHandler.record_more_data_file( "%s %s %s %s" % (pname, xname, dname, sweep), self.get_integrated_experiments(), ) FileHandler.record_more_data_file( "%s %s %s %s" % (pname, xname, dname, sweep), self.get_integrated_reflections(), ) return None # this will be set to intgr_hklout - better to cause failure