Source code for dials.algorithms.indexing.indexer

from __future__ import annotations

import logging
import math

import pkg_resources

import iotbx.phil
import libtbx
from cctbx import sgtbx
from dxtbx.model import ExperimentList, ImageSequence, tof_helpers

import dials.util
from dials.algorithms.indexing import (
    DialsIndexError,
    DialsIndexRefineError,
    assign_indices,
)
from dials.algorithms.indexing.compare_orientation_matrices import (
    difference_rotation_matrix_axis_angle,
)
from dials.algorithms.indexing.max_cell import find_max_cell
from dials.algorithms.indexing.symmetry import SymmetryHandler
from dials.algorithms.refinement import DialsRefineConfigError, DialsRefineRuntimeError
from dials.array_family import flex
from dials.util.multi_dataset_handling import generate_experiment_identifiers

logger = logging.getLogger(__name__)


max_cell_phil_str = """\
max_cell_estimation
  .expert_level = 1
{
  filter_ice = True
    .type = bool
    .help = "Filter out reflections at typical ice ring resolutions"
            "before max_cell estimation."
  filter_overlaps = True
    .type = bool
    .help = "Filter out reflections with overlapping bounding boxes before"
            "max_cell estimation."
  overlaps_border = 0
    .type = int(value_min=0)
    .help = "Optionally add a border around the bounding boxes before finding"
            "overlaps."
  multiplier = 1.3
    .type = float(value_min=0)
    .help = "Multiply the estimated maximum basis vector length by this value."
    .expert_level = 2
  step_size = 45
    .type = float(value_min=0)
    .help = "Step size, in degrees, of the blocks used to perform the max_cell "
            "estimation."
    .expert_level = 2
  nearest_neighbor_percentile = None
    .type = float(value_min=0, value_max=1)
    .help = "Percentile of NN histogram to use for max cell determination."
    .expert_level = 2
  histogram_binning = linear *log
    .type = choice
    .help = "Choose between linear or logarithmic bins for nearest neighbour"
            "histogram analysis."
  nn_per_bin = 5
    .type = int(value_min=1)
    .help = "Target number of nearest neighbours per histogram bin."
  max_height_fraction = 0.25
    .type = float(value_min=0, value_max=1)
    .expert_level=2
}
"""

phil_str = (
    """\
indexing {
  nproc = 1
    .type = int(value_min=1)
    .help = "The number of processes to use."
  mm_search_scope = 4.0
    .help = "Global radius of origin offset search."
    .type = float(value_min=0)
    .expert_level = 1
  wide_search_binning = 2
    .help = "Modify the coarseness of the wide grid search for the beam centre."
    .type = float(value_min=0)
    .expert_level = 1
  min_cell_volume = 25
    .type = float(value_min=0)
    .help = "Minimum unit cell volume (in Angstrom^3)."
    .expert_level = 1
  min_cell = 3
    .type = float(value_min=0)
    .help = "Minimum length of candidate unit cell basis vectors (in Angstrom)."
    .expert_level = 1
  max_cell = Auto
    .type = float(value_min=0)
    .help = "Maximum length of candidate unit cell basis vectors (in Angstrom)."
    .expert_level = 1
  %s
  sigma_phi_deg = None
    .type = float(value_min=0)
    .help = "Override the phi sigmas for refinement. Mainly intended for single-shot"
            "rotation images where the phi sigma is almost certainly incorrect."
    .expert_level = 2

  known_symmetry {
    space_group = None
      .type = space_group
      .help = "Target space group for indexing."
    unit_cell = None
      .type = unit_cell
      .help = "Target unit cell for indexing."
    relative_length_tolerance = 0.1
      .type = float
      .help = "Relative tolerance for unit cell lengths in unit cell comparison."
      .expert_level = 1
    absolute_angle_tolerance = 5
      .type = float
      .help = "Angular tolerance (in degrees) in unit cell comparison."
      .expert_level = 1
    max_delta = 5
      .type = float(value_min=0)
      .help = "Maximum allowed Le Page delta used in searching for basis vector"
              "combinations that are consistent with the given symmetry."
      .expert_level = 1
  }

  index_assignment {
    method = *simple local
      .type = choice
      .help = "Choose between simple 'global' index assignment and xds-style "
              "'local' index assignment."
      .expert_level = 1
    simple {
      hkl_tolerance = 0.3
        .type = float(value_min=0, value_max=0.5)
        .help = "Maximum allowable deviation from integer-ness for assigning "
                "a miller index to a reciprocal lattice vector."
    }
    local
      .expert_level = 1
    {
      epsilon = 0.05
        .type = float
        .help = "This corresponds to the xds parameter INDEX_ERROR="
      delta = 8
        .type = int
        .help = "This corresponds to the xds parameter INDEX_MAGNITUDE="
      l_min = 0.8
        .type = float
        .help = "This corresponds to the xds parameter INDEX_QUALITY="
      nearest_neighbours = 20
        .type = int(value_min=1)
    }
  }
  check_misindexing {
    grid_search_scope = 0
      .type = int
      .help = "Search scope for testing misindexing on h, k, l."
  }
  debug = False
    .type = bool
    .expert_level = 1
  combine_scans = False
    .type = bool
    .expert_level = 1
  refinement_protocol {
    mode = *refine_shells repredict_only None
      .type = choice
      .expert_level = 1
      .help = "refine_shells: if using sequences indexer, refine in increasing"
              "resolution cutoffs after indexing, if using stills indexer,"
              "refine all data up to d_min_start resolution once only."
              "repredict_only: do not refine after indexing, just update spot"
              "predictions."
              "None: do not refine and do not update spot predictions."
    n_macro_cycles = 5
      .type = int(value_min=1)
      .help = "Maximum number of macro cycles of refinement, reindexing all"
              "reflections using updated geometry at the beginning of each"
              "cycle. Does not apply to stills.indexer=stills."
    d_min_step = Auto
      .type = float(value_min=0.0)
      .help = "Reduction per step in d_min for reflections to include"
              "in refinement. Does not apply to stills.indexer=stills."
    d_min_start = None
      .type = float(value_min=0.0)
      .help = "For sequences/stills indexer, the lower limit of d-spacing"
              "of reflections used in the first/the only round of refinement."
    d_min_final = None
      .type = float(value_min=0.0)
      .help = "Do not ever include reflections below this value in refinement."
              "Does not apply to stills.indexer=stills."
    disable_unit_cell_volume_sanity_check = False
      .type = bool
      .help = "Disable sanity check on unrealistic increases in unit cell volume"
              "during refinement. Does not apply to stills.indexer=stills."
      .expert_level = 1
  }
  multiple_lattice_search
    .expert_level = 1
  {
    recycle_unindexed_reflections_cutoff = 0.1
      .type = float(value_min=0, value_max=1)
      .help = "Attempt another cycle of indexing on the unindexed reflections "
              "if more than the fraction of input reflections are unindexed."
    minimum_angular_separation = 5
      .type = float(value_min=0)
      .help = "The minimum angular separation (in degrees) between two lattices."
    max_lattices = 1
      .type = int
    cluster_analysis {
      method = *dbscan hcluster
        .type = choice
      hcluster {
        linkage {
          method = *ward
            .type = choice
          metric = *euclidean
            .type = choice
        }
        cutoff = 15
          .type = float(value_min=0)
        cutoff_criterion = *distance inconsistent
          .type = choice
      }
      dbscan {
        eps = 0.05
          .type = float(value_min=0.0)
        min_samples = 30
          .type = int(value_min=1)
      }
      min_cluster_size = 20
        .type = int(value_min=0)
      intersection_union_ratio_cutoff = 0.4
        .type = float(value_min=0.0, value_max=1.0)
    }
  }
  stills {
    indexer = *Auto stills sequences
      .type = choice
      .help = Use the stills or sequences indexer.  Auto: choose based on the input \
              imagesets (stills or sequences).
      .expert_level = 1
    ewald_proximity_resolution_cutoff = 2.0
      .type = float
      .help = For still images, this high-resolution cutoff is used to calculate
      .help = the acceptable volume of reciprocal space for spot prediction
    refine_all_candidates = True
      .type = bool
      .help = If False, no attempt is made to refine the model from initial basis \
              vector selection. The indexing solution with the best RMSD is chosen.
    candidate_outlier_rejection = True
      .type = bool
      .expert_level = 1
      .help = If True, while refining candidate basis solutions, also apply Sauter/ \
              Poon (2010) outlier rejection
    refine_candidates_with_known_symmetry = False
      .type = bool
      .expert_level = 2
      .help = If False, when choosing the best set of candidate basis solutions, \
              refine the candidates in the P1 setting. If True, after indexing \
              in P1, convert the candidates to the known symmetry and apply the \
              corresponding change of basis to the indexed reflections.
    rmsd_min_px = 2
      .type = float
      .help = Minimum acceptable RMSD for choosing candidate basis solutions \
              (in pixels)
    ewald_proximal_volume_max = 0.0025
      .type = float
      .help = Maximum acceptable ewald proximal volume when choosing candidate \
              basis solutions
    isoforms
      .help = Constrain the unit cell to specific values during refinement after initial indexing.
      .multiple=True
    {
      name=None
        .type=str
      cell=None
        .type=unit_cell
      lookup_symbol=None
        .type=str
        .help=The sgtbx lookup symbol of the reflections pointgroup
      rmsd_target_mm=None
        .type=float
        .help=Maximum acceptable DIALS positional rmsd, in mm
      beam_restraint=None
        .type=floats(size=2)
        .help=Known beam position in mm X,Y, rmsd_target_mm is reused here as a circle of confusion
        .help=to assure that no images are accepted where the lattice is misindexed by a unit shift.
    }
    set_domain_size_ang_value = None
      .type=float
      .help=If specified, will set the domain size ang value and override the value determined from nave refinement
    set_mosaic_half_deg_value = None
      .type=float
      .help=If specified, will set the mosaic half degree value and override the value determined from nave refinement
  }
}
"""
    % max_cell_phil_str
)

phil_scope = iotbx.phil.parse(phil_str, process_includes=True)


[docs] class Indexer:
[docs] def __init__(self, reflections, experiments, params): self.reflections = reflections self.experiments = experiments self.params = params.indexing self.all_params = params self.refined_experiments = None self.hkl_offset = None if self.params.index_assignment.method == "local": self._assign_indices = assign_indices.AssignIndicesLocal( epsilon=self.params.index_assignment.local.epsilon, delta=self.params.index_assignment.local.delta, l_min=self.params.index_assignment.local.l_min, nearest_neighbours=self.params.index_assignment.local.nearest_neighbours, ) else: self._assign_indices = assign_indices.AssignIndicesGlobal( tolerance=self.params.index_assignment.simple.hkl_tolerance ) if self.all_params.refinement.reflections.outlier.algorithm in ( "auto", libtbx.Auto, ): if self.experiments[0].goniometer is None: self.all_params.refinement.reflections.outlier.algorithm = "sauter_poon" else: # different default to dials.refine # tukey is faster and more appropriate at the indexing step self.all_params.refinement.reflections.outlier.algorithm = "tukey" for expt in self.experiments[1:]: if expt.detector.is_similar_to(self.experiments[0].detector): expt.detector = self.experiments[0].detector if expt.goniometer is not None and expt.goniometer.is_similar_to( self.experiments[0].goniometer ): expt.goniometer = self.experiments[0].goniometer # can only share a beam if we share a goniometer? if expt.beam.is_similar_to(self.experiments[0].beam): expt.beam = self.experiments[0].beam if self.params.combine_scans and expt.scan == self.experiments[0].scan: expt.scan = self.experiments[0].scan if "flags" in self.reflections: strong_sel = self.reflections.get_flags(self.reflections.flags.strong) if strong_sel.count(True) > 0: self.reflections = self.reflections.select(strong_sel) if "flags" not in self.reflections or strong_sel.count(True) == 0: # backwards compatibility for testing self.reflections.set_flags( flex.size_t_range(len(self.reflections)), self.reflections.flags.strong ) self._setup_symmetry() self.d_min = None self.setup_indexing()
[docs] @staticmethod def from_parameters( reflections, experiments, known_crystal_models=None, params=None ): if known_crystal_models is not None: from dials.algorithms.indexing.known_orientation import ( IndexerKnownOrientation, ) if params.indexing.known_symmetry.space_group is None: params.indexing.known_symmetry.space_group = ( known_crystal_models[0].get_space_group().info() ) idxr = IndexerKnownOrientation( reflections, experiments, params, known_crystal_models ) else: has_stills = False has_sequences = False for expt in experiments: if isinstance(expt.imageset, ImageSequence): has_sequences = True else: has_stills = True if has_stills and has_sequences: raise ValueError( "Please provide only stills or only sequences, not both" ) use_stills_indexer = has_stills if not ( params.indexing.stills.indexer is libtbx.Auto or params.indexing.stills.indexer.lower() == "auto" ): if params.indexing.stills.indexer == "stills": use_stills_indexer = True elif params.indexing.stills.indexer == "sequences": use_stills_indexer = False else: assert False if params.indexing.basis_vector_combinations.max_refine is libtbx.Auto: if use_stills_indexer: params.indexing.basis_vector_combinations.max_refine = 5 else: params.indexing.basis_vector_combinations.max_refine = 50 if use_stills_indexer: # Ensure the indexer and downstream applications treat this as set of stills from dxtbx.imageset import ImageSet # , MemImageSet for experiment in experiments: # Elsewhere, checks are made for ImageSequence when picking between algorithms # specific to rotations vs. stills, so here reset any ImageSequences to stills. # Note, dials.stills_process resets ImageSequences to ImageSets already, # and it's not free (the ImageSet cache is dropped), only do it if needed if isinstance(experiment.imageset, ImageSequence): experiment.imageset = ImageSet( experiment.imageset.data(), experiment.imageset.indices() ) # if isinstance(imageset, MemImageSet): # imageset = MemImageSet(imagesequence._images, imagesequence.indices()) # else: # imageset = ImageSet(imagesequence.reader(), imagesequence.indices()) # imageset._models = imagesequence._models experiment.imageset.set_scan(None) experiment.imageset.set_goniometer(None) experiment.scan = None experiment.goniometer = None IndexerType = None for entry_point in pkg_resources.iter_entry_points( "dials.index.basis_vector_search" ): if params.indexing.method == entry_point.name: if use_stills_indexer: # do something from dials.algorithms.indexing.stills_indexer import ( StillsIndexerBasisVectorSearch as IndexerType, ) else: from dials.algorithms.indexing.lattice_search import ( BasisVectorSearch as IndexerType, ) if IndexerType is None: for entry_point in pkg_resources.iter_entry_points( "dials.index.lattice_search" ): if params.indexing.method == entry_point.name: if use_stills_indexer: from dials.algorithms.indexing.stills_indexer import ( StillsIndexerLatticeSearch as IndexerType, ) else: from dials.algorithms.indexing.lattice_search import ( LatticeSearch as IndexerType, ) assert IndexerType is not None idxr = IndexerType(reflections, experiments, params=params) return idxr
def _setup_symmetry(self): target_unit_cell = self.params.known_symmetry.unit_cell target_space_group = self.params.known_symmetry.space_group if target_space_group is not None: target_space_group = target_space_group.group() else: target_space_group = sgtbx.space_group() self.params.known_symmetry.space_group = target_space_group.info() self._symmetry_handler = SymmetryHandler( unit_cell=target_unit_cell, space_group=target_space_group, max_delta=self.params.known_symmetry.max_delta, ) return
[docs] def setup_indexing(self): if len(self.reflections) == 0: raise DialsIndexError("No reflections left to index!") if "imageset_id" not in self.reflections: self.reflections["imageset_id"] = self.reflections["id"] self.reflections.centroid_px_to_mm(self.experiments) self.reflections.map_centroids_to_reciprocal_space(self.experiments) self.reflections.calculate_entering_flags(self.experiments) self.find_max_cell() if self.params.sigma_phi_deg is not None: var_x, var_y, _ = self.reflections["xyzobs.mm.variance"].parts() var_phi_rad = flex.double( var_x.size(), (math.pi / 180 * self.params.sigma_phi_deg) ** 2 ) self.reflections["xyzobs.mm.variance"] = flex.vec3_double( var_x, var_y, var_phi_rad ) if self.params.debug: self._debug_write_reciprocal_lattice_points_as_pdb() self.reflections["id"] = flex.int(len(self.reflections), -1)
[docs] def index(self): experiments = ExperimentList() had_refinement_error = False have_similar_crystal_models = False while True: if had_refinement_error or have_similar_crystal_models: break max_lattices = self.params.multiple_lattice_search.max_lattices if max_lattices is not None and len(experiments.crystals()) >= max_lattices: break if len(experiments) > 0: cutoff_fraction = self.params.multiple_lattice_search.recycle_unindexed_reflections_cutoff d_spacings = 1 / self.reflections["rlp"].norms() d_min_indexed = flex.min(d_spacings.select(self.indexed_reflections)) min_reflections_for_indexing = cutoff_fraction * len( self.reflections.select(d_spacings > d_min_indexed) ) crystal_ids = self.reflections.select(d_spacings > d_min_indexed)["id"] if (crystal_ids == -1).count(True) < min_reflections_for_indexing: logger.info( "Finish searching for more lattices: %i unindexed reflections remaining.", (crystal_ids == -1).count(True), ) break n_lattices_previous_cycle = len(experiments.crystals()) if self.d_min is None: self.d_min = self.params.refinement_protocol.d_min_start if len(experiments) == 0: new_expts = self.find_lattices() generate_experiment_identifiers(new_expts) experiments.extend(new_expts) else: try: new = self.find_lattices() generate_experiment_identifiers(new) experiments.extend(new) except DialsIndexError: logger.info("Indexing remaining reflections failed") if self.params.refinement_protocol.d_min_step is libtbx.Auto: n_cycles = self.params.refinement_protocol.n_macro_cycles if self.d_min is None or n_cycles == 1: self.params.refinement_protocol.d_min_step = 0 else: d_spacings = 1 / self.reflections["rlp"].norms() d_min_all = flex.min(d_spacings) self.params.refinement_protocol.d_min_step = ( self.d_min - d_min_all ) / (n_cycles - 1) logger.info( "Using d_min_step %.1f", self.params.refinement_protocol.d_min_step, ) if len(experiments) == 0: raise DialsIndexError("No suitable lattice could be found.") elif len(experiments.crystals()) == n_lattices_previous_cycle: logger.warning("No more suitable lattices could be found") # no more lattices found break for i_cycle in range(self.params.refinement_protocol.n_macro_cycles): if ( i_cycle > 0 and self.d_min is not None and self.params.refinement_protocol.d_min_step > 0 ): d_min = self.d_min - self.params.refinement_protocol.d_min_step d_min = max(d_min, 0) if self.params.refinement_protocol.d_min_final is not None: d_min = max(d_min, self.params.refinement_protocol.d_min_final) if d_min >= 0: self.d_min = d_min logger.info("Increasing resolution to %.2f Angstrom", d_min) # reset reflection lattice flags # the lattice a given reflection belongs to: a value of -1 indicates # that a reflection doesn't belong to any lattice so far self.reflections["id"] = flex.int(len(self.reflections), -1) self.index_reflections(experiments, self.reflections) if i_cycle == 0 and self.params.known_symmetry.space_group is not None: self._apply_symmetry_post_indexing( experiments, self.reflections, n_lattices_previous_cycle ) logger.info("\nIndexed crystal models:") self.show_experiments(experiments, self.reflections, d_min=self.d_min) if self._remove_similar_crystal_models(experiments): have_similar_crystal_models = True break logger.info("") logger.info("#" * 80) logger.info("Starting refinement (macro-cycle %i)", i_cycle + 1) logger.info("#" * 80) logger.info("") self.indexed_reflections = self.reflections["id"] > -1 sel = flex.bool(len(self.reflections), False) # Note, anything below d_min doesn't get indexed so has an id of -1 # so code below is redundant? lengths = 1 / self.reflections["rlp"].norms() if self.d_min is not None: isel = (lengths <= self.d_min).iselection() sel.set_selected(isel, True) sel.set_selected(self.reflections["id"] == -1, True) self.reflections.unset_flags(sel, self.reflections.flags.indexed) # N.B. we don't set self.unindexed_reflections here, as we don't want to overwrite yet # if the refinement cycle below fails unindexed_reflections = self.reflections.select( sel ) # reflections that have an id of -1 reflections_for_refinement = self.reflections.select( self.indexed_reflections ) if self.params.refinement_protocol.mode == "repredict_only": refined_experiments, refined_reflections = ( experiments, reflections_for_refinement, ) from dials.algorithms.refinement.prediction.managed_predictors import ( ExperimentsPredictorFactory, ) ref_predictor = ExperimentsPredictorFactory.from_experiments( experiments, spherical_relp=self.all_params.refinement.parameterisation.spherical_relp_model, ) ref_predictor(refined_reflections) elif self.params.refinement_protocol.mode is None: refined_experiments, refined_reflections = ( experiments, reflections_for_refinement, ) else: try: refined_experiments, refined_reflections = self.refine( experiments, reflections_for_refinement ) except (DialsRefineConfigError, DialsRefineRuntimeError) as e: if len(experiments) == 1: raise DialsIndexRefineError(str(e)) had_refinement_error = True logger.info("Refinement failed:") logger.info(e) # need to remove crystals - may be shared! models_to_remove = experiments.where( crystal=experiments[-1].crystal ) for model_id in sorted(models_to_remove, reverse=True): del experiments[model_id] # remove experiment id from the reflections associated # with this deleted experiment - indexed flag removed # below # note here we are acting on the table from the last macrocycle # This is guaranteed to exist due to the check if len(experiments) == 1: above # N.B. Need to unset the flags here as the break below means we # don't enter the code after self._remove_id_from_reflections(model_id) break self._unit_cell_volume_sanity_check(experiments, refined_experiments) self.refined_reflections = refined_reflections # id can be -1 if some were determined as outliers in self.refine sel = self.refined_reflections["id"] < 0 if sel.count(True): self.refined_reflections.unset_flags( sel, self.refined_reflections.flags.indexed, ) self.refined_reflections["miller_index"].set_selected( sel, (0, 0, 0) ) unindexed_reflections.extend(self.refined_reflections.select(sel)) self.refined_reflections = self.refined_reflections.select(~sel) self.refined_reflections.clean_experiment_identifiers_map() self.unindexed_reflections = unindexed_reflections for i, expt in enumerate(self.experiments): ref_sel = self.refined_reflections.select( self.refined_reflections["imageset_id"] == i ) ref_sel = ref_sel.select(ref_sel["id"] >= 0) for i_expt in set(ref_sel["id"]): refined_expt = refined_experiments[i_expt] expt.detector = refined_expt.detector expt.beam = refined_expt.beam expt.goniometer = refined_expt.goniometer expt.scan = refined_expt.scan refined_expt.imageset = expt.imageset if not ( self.all_params.refinement.parameterisation.beam.fix == "all" and self.all_params.refinement.parameterisation.detector.fix == "all" ): # Experimental geometry may have changed - re-map centroids to # reciprocal space self.reflections.map_centroids_to_reciprocal_space(self.experiments) # update for next cycle experiments = refined_experiments self.refined_experiments = refined_experiments logger.info("\nRefined crystal models:") self.show_experiments( self.refined_experiments, self.refined_reflections, d_min=self.d_min, unindexed_reflections=self.unindexed_reflections, ) if ( i_cycle >= 2 and self.d_min == self.params.refinement_protocol.d_min_final ): logger.info("Target d_min_final reached: finished with refinement") break if self.refined_experiments is None: raise DialsIndexRefineError("None of the experiments could refine.") if len(self.refined_experiments) > 1: from dials.algorithms.indexing.compare_orientation_matrices import ( rotation_matrix_differences, ) logger.info( rotation_matrix_differences(self.refined_experiments.crystals()) ) if "xyzcal.mm" in self.refined_reflections: self._xyzcal_mm_to_px(self.refined_experiments, self.refined_reflections)
def _remove_id_from_reflections(self, model_id): sel = self.refined_reflections["id"] == model_id if sel.count( True ): # not the case if failure on first cycle of refinement of new xtal logger.info( "Removing %d reflections with id %d", sel.count(True), model_id, ) self.refined_reflections["id"].set_selected(sel, -1) del self.refined_reflections.experiment_identifiers()[model_id] self.refined_reflections.unset_flags( sel, self.refined_reflections.flags.indexed ) self.refined_reflections["miller_index"].set_selected(sel, (0, 0, 0)) self.unindexed_reflections.extend(self.refined_reflections.select(sel)) self.refined_reflections = self.refined_reflections.select(~sel) self.refined_reflections.clean_experiment_identifiers_map() def _unit_cell_volume_sanity_check(self, original_experiments, refined_experiments): # sanity check for unrealistic unit cell volume increase during refinement # usually this indicates too many parameters are being refined given the # number of observations provided. if not self.params.refinement_protocol.disable_unit_cell_volume_sanity_check: for orig_expt, refined_expt in zip( original_experiments, refined_experiments ): uc1 = orig_expt.crystal.get_unit_cell() uc2 = refined_expt.crystal.get_unit_cell() volume_change = abs(uc1.volume() - uc2.volume()) / uc1.volume() cutoff = 0.5 if volume_change > cutoff: msg = "\n".join( ( "Unrealistic unit cell volume increase during refinement of %.1f%%.", "Please try refining fewer parameters, either by enforcing symmetry", "constraints (space_group=) and/or disabling experimental geometry", "refinement (detector.fix=all and beam.fix=all). To disable this", "sanity check set disable_unit_cell_volume_sanity_check=True.", ) ) % (100 * volume_change) raise DialsIndexError(msg) def _apply_symmetry_post_indexing( self, experiments, reflections, n_lattices_previous_cycle ): # now apply the space group symmetry only after the first indexing # need to make sure that the symmetrized orientation is similar to the P1 model for cryst in experiments.crystals()[n_lattices_previous_cycle:]: new_cryst, cb_op = self._symmetry_handler.apply_symmetry(cryst) new_cryst = new_cryst.change_basis(cb_op) cryst.update(new_cryst) cryst.set_space_group(self.params.known_symmetry.space_group.group()) for i_expt, expt in enumerate(experiments): if expt.crystal is not cryst: continue if not cb_op.is_identity_op(): miller_indices = reflections["miller_index"].select( reflections["id"] == i_expt ) miller_indices = cb_op.apply(miller_indices) reflections["miller_index"].set_selected( reflections["id"] == i_expt, miller_indices ) def _remove_similar_crystal_models(self, experiments): """ Checks for too-similar crystal models and removes them. Checks whether the most recently added crystal model is similar to previously found crystal models, and if so, deletes the last crystal model from the experiment list. """ have_similar_crystal_models = False cryst_b = experiments.crystals()[-1] for i_a, cryst_a in enumerate(experiments.crystals()[:-1]): R_ab, axis, angle, cb_op_ab = difference_rotation_matrix_axis_angle( cryst_a, cryst_b ) min_angle = self.params.multiple_lattice_search.minimum_angular_separation if abs(angle) < min_angle: # degrees # account for potential shared crystal model models_to_reject = experiments.where(crystal=cryst_b) reject = len(experiments.crystals()) logger.info(f"Crystal models too similar, rejecting crystal {reject}") logger.info( f"Rotation matrix to transform crystal {i_a + 1} to crystal {reject}" ) logger.info(R_ab) logger.info( f"Rotation of {angle:.3f} degrees" + " about axis (%.3f, %.3f, %.3f)" % axis ) have_similar_crystal_models = True for id_ in sorted(models_to_reject, reverse=True): del experiments[id_] # Unset ids in the reflection table self._remove_id_from_reflections(id_) break return have_similar_crystal_models def _xyzcal_mm_to_px(self, experiments, reflections): # set xyzcal.px field in reflections reflections["xyzcal.px"] = flex.vec3_double(len(reflections)) for i, expt in enumerate(experiments): imgset_sel = reflections["imageset_id"] == i refined_reflections = reflections.select(imgset_sel) panel_numbers = flex.size_t(refined_reflections["panel"]) xyzcal_mm = refined_reflections["xyzcal.mm"] x_mm, y_mm, z = xyzcal_mm.parts() xy_cal_mm = flex.vec2_double(x_mm, y_mm) xy_cal_px = flex.vec2_double(len(xy_cal_mm)) for i_panel in range(len(expt.detector)): panel = expt.detector[i_panel] sel = panel_numbers == i_panel xy_cal_px.set_selected( sel, panel.millimeter_to_pixel(xy_cal_mm.select(sel)) ) x_px, y_px = xy_cal_px.parts() if expt.scan is not None: if expt.scan.has_property("time_of_flight"): tof = expt.scan.get_property("time_of_flight") frames = list(range(len(tof))) tof_to_frame = tof_helpers.tof_to_frame_interpolator(tof, frames) z.set_selected(z < min(tof), min(tof)) z.set_selected(z > max(tof), max(tof)) z_px = flex.double(tof_to_frame(z)) else: z_px = expt.scan.get_array_index_from_angle(z, deg=False) else: # must be a still image, z centroid not meaningful z_px = z xyzcal_px = flex.vec3_double(x_px, y_px, z_px) reflections["xyzcal.px"].set_selected(imgset_sel, xyzcal_px)
[docs] def show_experiments( self, experiments, reflections, d_min=None, unindexed_reflections=None ): if d_min is not None: reciprocal_lattice_points = reflections["rlp"] d_spacings = 1 / reciprocal_lattice_points.norms() reflections = reflections.select(d_spacings > d_min) if unindexed_reflections: reciprocal_lattice_points = unindexed_reflections["rlp"] d_spacings = 1 / reciprocal_lattice_points.norms() unindexed_reflections = unindexed_reflections.select(d_spacings > d_min) for i_expt, expt in enumerate(experiments): logger.info( "model %i (%i reflections):", i_expt + 1, (reflections["id"] == i_expt).count(True), ) logger.info(expt.crystal) indexed_flags = reflections.get_flags(reflections.flags.indexed) imageset_id = reflections["imageset_id"] rows = [["Imageset", "# indexed", "# unindexed", "% indexed"]] for i in range(flex.max(imageset_id) + 1): imageset_indexed_flags = indexed_flags.select(imageset_id == i) indexed_count = imageset_indexed_flags.count(True) unindexed_count = imageset_indexed_flags.count(False) if unindexed_reflections: sel = unindexed_reflections["imageset_id"] == i unindexed_count += sel.count(True) rows.append( [ str(i), str(indexed_count), str(unindexed_count), f"{indexed_count / (indexed_count + unindexed_count)*100:.1f}", ] ) logger.info(dials.util.tabulate(rows, headers="firstrow"))
[docs] def find_max_cell(self): params = self.params.max_cell_estimation if self.params.max_cell is libtbx.Auto: if self.params.known_symmetry.unit_cell is not None: uc_params = self._symmetry_handler.target_symmetry_primitive.unit_cell().parameters() self.params.max_cell = params.multiplier * max(uc_params[:3]) logger.info("Using max_cell: %.1f Angstrom", self.params.max_cell) else: convert_reflections_z_to_deg = True all_tof_experiments = False for expt in self.experiments: if expt.scan is not None and expt.scan.has_property( "time_of_flight" ): all_tof_experiments = True elif all_tof_experiments: raise ValueError( "Cannot find max cell for ToF and non-ToF experiments at the same time" ) if all_tof_experiments: if params.step_size < 100: logger.info("Setting default ToF step size to 500 usec") params.step_size = 500 convert_reflections_z_to_deg = False self.params.max_cell = find_max_cell( self.reflections, max_cell_multiplier=params.multiplier, step_size=params.step_size, nearest_neighbor_percentile=params.nearest_neighbor_percentile, histogram_binning=params.histogram_binning, nn_per_bin=params.nn_per_bin, max_height_fraction=params.max_height_fraction, filter_ice=params.filter_ice, filter_overlaps=params.filter_overlaps, overlaps_border=params.overlaps_border, convert_reflections_z_to_deg=convert_reflections_z_to_deg, ).max_cell logger.info("Found max_cell: %.1f Angstrom", self.params.max_cell)
[docs] def index_reflections(self, experiments, reflections): self._assign_indices(reflections, experiments, d_min=self.d_min) if self.hkl_offset is not None and self.hkl_offset != (0, 0, 0): reflections["miller_index"] = apply_hkl_offset( reflections["miller_index"], self.hkl_offset ) self.hkl_offset = None
[docs] def refine(self, experiments, reflections): from dials.algorithms.indexing.refinement import refine properties_to_save = [ "xyzcal.mm", "entering", "wavelength_cal", "s0_cal", "tof_cal", ] refiner, refined, outliers = refine(self.all_params, reflections, experiments) if outliers is not None: reflections["id"].set_selected(outliers, -1) predicted = refiner.predict_for_indexed() for i in properties_to_save: if i in predicted: reflections[i] = predicted[i] reflections.unset_flags( flex.bool(len(reflections), True), reflections.flags.centroid_outlier ) assert ( reflections.get_flags(reflections.flags.centroid_outlier).count(True) == 0 ) reflections.set_flags( predicted.get_flags(predicted.flags.centroid_outlier), reflections.flags.centroid_outlier, ) reflections.set_flags( refiner.selection_used_for_refinement(), reflections.flags.used_in_refinement, ) return refiner.get_experiments(), reflections
def _debug_write_reciprocal_lattice_points_as_pdb( self, file_name="reciprocal_lattice.pdb" ): from cctbx import crystal, xray cs = crystal.symmetry( unit_cell=(1000, 1000, 1000, 90, 90, 90), space_group="P1" ) for i_panel in range(len(self.experiments[0].detector)): if len(self.experiments[0].detector) > 1: file_name = "reciprocal_lattice_%i.pdb" % i_panel with open(file_name, "wb") as f: xs = xray.structure(crystal_symmetry=cs) reflections = self.reflections.select( self.reflections["panel"] == i_panel ) for site in reflections["rlp"]: xs.add_scatterer(xray.scatterer("C", site=site)) xs.sites_mod_short() f.write(xs.as_pdb_file())
[docs] def export_as_json( self, experiments, file_name="indexed_experiments.json", compact=False ): assert experiments.is_consistent() experiments.as_file(file_name)
[docs] def export_reflections(self, reflections, file_name="reflections.pickle"): reflections.as_file(file_name)
[docs] def find_lattices(self): raise NotImplementedError()
[docs] def apply_hkl_offset(indices, offset): h, k, l = indices.as_vec3_double().parts() h += offset[0] k += offset[1] l += offset[2] return flex.miller_index(h.iround(), k.iround(), l.iround())