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()
self._symmetry_handler = SymmetryHandler(
unit_cell=target_unit_cell,
space_group=target_space_group,
max_delta=self.params.known_symmetry.max_delta,
)
return
class Indexer(object):
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()
@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
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)
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]
# remove experiment id from the reflections associated
# with this deleted experiment - indexed flag removed
# below
last = len(experiments)
sel = refined_reflections["id"] == last
logger.info("Removing %d reflections with id %d" %
(sel.count(True), last))
refined_reflections["id"].set_selected(sel, -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.refined_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)
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"))
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))
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
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())
def export_as_json(self,
experiments,
file_name="indexed_experiments.json",
compact=False):
assert experiments.is_consistent()
experiments.as_file(file_name)
def export_reflections(self, reflections, file_name="reflections.pickle"):
reflections.as_file(file_name)
def find_lattices(self):
raise NotImplementedError()