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Source code for dials.algorithms.indexing.indexer
# coding: utf-8
from __future__ import absolute_import, division, print_function
import logging
import math
import pkg_resources
from cctbx import sgtbx
import dials.util
import iotbx.phil
import libtbx
from dials.array_family import flex
from dials.util.multi_dataset_handling import generate_experiment_identifiers
from dials.algorithms.indexing import assign_indices
from dials.algorithms.indexing import DialsIndexError, DialsIndexRefineError
from dials.algorithms.indexing.compare_orientation_matrices import (
difference_rotation_matrix_axis_angle,
)
from dials.algorithms.indexing.symmetry import SymmetryHandler
from dials.algorithms.indexing.max_cell import find_max_cell
from dials.algorithms.refinement import DialsRefineConfigError, DialsRefineRuntimeError
from dxtbx.model import ExperimentList, ImageSequence
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 peform 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 comparision."
.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: refine in increasing resolution cutoffs after indexing."
"repredict_only: do not refine after indexing, just update spot"
"predictions."
"None: turns off all forms of refinement (currently only applies to stills_indexer)"
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."
d_min_start = None
.type = float(value_min=0.0)
d_min_final = None
.type = float(value_min=0.0)
.help = "Do not ever include reflections below this value in refinement."
disable_unit_cell_volume_sanity_check = False
.type = bool
.help = "Disable sanity check on unrealistic increases in unit cell volume"
"during refinement."
.expert_level = 1
}
multiple_lattice_search
.expert_level = 1
{
cluster_analysis_search = False
.type = bool
.help = "Perform cluster analysis search for multiple lattices."
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 candiate 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(object):
def __init__(self, reflections, experiments, params=None):
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:
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._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) >= 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)
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) == n_lattices_previous_cycle:
# 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._check_have_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)
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)
self.unindexed_reflections = self.reflections.select(sel)
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)
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)
del experiments[-1]
break
self._unit_cell_volume_sanity_check(experiments, refined_experiments)
self.refined_reflections = refined_reflections
self.refined_reflections.unset_flags(
self.refined_reflections["id"] < 0,
self.refined_reflections.flags.indexed,
)
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.reflections, d_min=self.d_min
)
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())
)
self._xyzcal_mm_to_px(self.experiments, self.refined_reflections)
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 _check_have_similar_crystal_models(self, experiments):
"""
Checks for similar crystal models.
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
logger.info(
"Crystal models too similar, rejecting crystal %i:"
% (len(experiments))
)
logger.info(
"Rotation matrix to transform crystal %i to crystal %i"
% (i_a + 1, len(experiments))
)
logger.info(R_ab)
logger.info(
"Rotation of %.3f degrees" % angle
+ " about axis (%.3f, %.3f, %.3f)" % axis
)
have_similar_crystal_models = True
del experiments[-1]
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_rad = 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:
z_px = expt.scan.get_array_index_from_angle(z_rad, deg=False)
else:
# must be a still image, z centroid not meaningful
z_px = z_rad
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):
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)
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)
rows.append(
[
str(i),
str(indexed_count),
str(unindexed_count),
"{:.1%}".format(indexed_count / (indexed_count + unindexed_count)),
]
)
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:
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,
).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
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()
reflections["xyzcal.mm"] = predicted["xyzcal.mm"]
reflections["entering"] = predicted["entering"]
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 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())
