def discover_better_experimental_model(imagesets,
spot_lists,
params,
dps_params,
nproc=1,
wide_search_binning=1):
assert len(imagesets) == len(spot_lists)
assert len(imagesets) > 0
# XXX should check that all the detector and beam objects are the same
from dials.algorithms.indexing.indexer import indexer_base
spot_lists_mm = [
indexer_base.map_spots_pixel_to_mm_rad(spots, imageset.get_detector(),
imageset.get_scan())
for spots, imageset in zip(spot_lists, imagesets)
]
spot_lists_mm = []
max_cell_list = []
detector = imagesets[0].get_detector()
beam = imagesets[0].get_beam()
beam_panel = detector.get_panel_intersection(beam.get_s0())
if beam_panel == -1:
from libtbx.utils import Sorry
raise Sorry('input beam does not intersect detector')
for imageset, spots in zip(imagesets, spot_lists):
if 'imageset_id' not in spots:
spots['imageset_id'] = spots['id']
spots_mm = indexer_base.map_spots_pixel_to_mm_rad(
spots=spots,
detector=imageset.get_detector(),
scan=imageset.get_scan())
indexer_base.map_centroids_to_reciprocal_space(
spots_mm,
detector=imageset.get_detector(),
beam=imageset.get_beam(),
goniometer=imageset.get_goniometer())
if dps_params.d_min is not None:
d_spacings = 1 / spots_mm['rlp'].norms()
sel = d_spacings > dps_params.d_min
spots_mm = spots_mm.select(sel)
# derive a max_cell from mm spots
if params.max_cell is None:
from dials.algorithms.indexing.indexer import find_max_cell
max_cell = find_max_cell(spots_mm,
max_cell_multiplier=1.3,
step_size=45).max_cell
max_cell_list.append(max_cell)
if (params.max_reflections is not None
and spots_mm.size() > params.max_reflections):
logger.info('Selecting subset of %i reflections for analysis' %
params.max_reflections)
perm = flex.random_permutation(spots_mm.size())
sel = perm[:params.max_reflections]
spots_mm = spots_mm.select(sel)
spot_lists_mm.append(spots_mm)
if params.max_cell is None:
max_cell = flex.median(flex.double(max_cell_list))
else:
max_cell = params.max_cell
args = [(imageset, spots, max_cell, dps_params)
for imageset, spots in zip(imagesets, spot_lists_mm)]
from libtbx import easy_mp
results = easy_mp.parallel_map(func=run_dps,
iterable=args,
processes=nproc,
method="multiprocessing",
preserve_order=True,
asynchronous=True,
preserve_exception_message=True)
solution_lists = [r["solutions"] for r in results]
amax_list = [r["amax"] for r in results]
assert len(solution_lists) > 0
detector = imagesets[0].get_detector()
beam = imagesets[0].get_beam()
# perform calculation
if dps_params.indexing.improve_local_scope == "origin_offset":
discoverer = better_experimental_model_discovery(
imagesets,
spot_lists_mm,
solution_lists,
amax_list,
dps_params,
wide_search_binning=wide_search_binning)
new_detector = discoverer.optimize_origin_offset_local_scope()
old_panel, old_beam_centre = detector.get_ray_intersection(
beam.get_s0())
new_panel, new_beam_centre = new_detector.get_ray_intersection(
beam.get_s0())
old_beam_centre_px = detector[old_panel].millimeter_to_pixel(
old_beam_centre)
new_beam_centre_px = new_detector[new_panel].millimeter_to_pixel(
new_beam_centre)
logger.info("Old beam centre: %.2f, %.2f mm" % old_beam_centre +
" (%.1f, %.1f px)" % old_beam_centre_px)
logger.info("New beam centre: %.2f, %.2f mm" % new_beam_centre +
" (%.1f, %.1f px)" % new_beam_centre_px)
logger.info(
"Shift: %.2f, %.2f mm" %
(matrix.col(old_beam_centre) - matrix.col(new_beam_centre)).elems +
" (%.1f, %.1f px)" % (matrix.col(old_beam_centre_px) -
matrix.col(new_beam_centre_px)).elems)
return new_detector, beam
elif dps_params.indexing.improve_local_scope == "S0_vector":
raise NotImplementedError()
def discover_better_experimental_model(
experiments,
reflections,
params,
nproc=1,
d_min=None,
mm_search_scope=4.0,
wide_search_binning=1,
plot_search_scope=False,
):
assert len(experiments) == len(reflections)
assert len(experiments) > 0
refl_lists = []
max_cell_list = []
# The detector/beam of the first experiment is used to define the basis for the
# optimisation, so assert that the beam intersects with the detector
detector = experiments[0].detector
beam = experiments[0].beam
beam_panel = detector.get_panel_intersection(beam.get_s0())
if beam_panel == -1:
raise Sorry("input beam does not intersect detector")
for expt, refl in zip(experiments, reflections):
refl = copy.deepcopy(refl)
refl["imageset_id"] = flex.int(len(refl), 0)
refl.centroid_px_to_mm([expt])
refl.map_centroids_to_reciprocal_space([expt])
if d_min is not None:
d_spacings = 1 / refl["rlp"].norms()
sel = d_spacings > d_min
refl = refl.select(sel)
# derive a max_cell from mm spots
if params.max_cell is None:
max_cell = find_max_cell(refl,
max_cell_multiplier=1.3,
step_size=45).max_cell
max_cell_list.append(max_cell)
if params.max_reflections is not None and refl.size(
) > params.max_reflections:
logger.info("Selecting subset of %i reflections for analysis" %
params.max_reflections)
perm = flex.random_permutation(refl.size())
sel = perm[:params.max_reflections]
refl = refl.select(sel)
refl_lists.append(refl)
if params.max_cell is None:
max_cell = flex.median(flex.double(max_cell_list))
else:
max_cell = params.max_cell
with concurrent.futures.ProcessPoolExecutor(max_workers=nproc) as pool:
solution_lists = []
amax_list = []
for result in pool.map(run_dps, experiments, refl_lists,
itertools.repeat(max_cell)):
if result.get("solutions"):
solution_lists.append(result["solutions"])
amax_list.append(result["amax"])
if not solution_lists:
raise Sorry("No solutions found")
new_experiments = optimize_origin_offset_local_scope(
experiments,
refl_lists,
solution_lists,
amax_list,
mm_search_scope=mm_search_scope,
wide_search_binning=wide_search_binning,
plot_search_scope=plot_search_scope,
)
new_detector = new_experiments[0].detector
old_panel, old_beam_centre = detector.get_ray_intersection(beam.get_s0())
new_panel, new_beam_centre = new_detector.get_ray_intersection(
beam.get_s0())
old_beam_centre_px = detector[old_panel].millimeter_to_pixel(
old_beam_centre)
new_beam_centre_px = new_detector[new_panel].millimeter_to_pixel(
new_beam_centre)
logger.info("Old beam centre: %.2f, %.2f mm" % old_beam_centre +
" (%.1f, %.1f px)" % old_beam_centre_px)
logger.info("New beam centre: %.2f, %.2f mm" % new_beam_centre +
" (%.1f, %.1f px)" % new_beam_centre_px)
logger.info(
"Shift: %.2f, %.2f mm" %
(matrix.col(old_beam_centre) - matrix.col(new_beam_centre)).elems +
" (%.1f, %.1f px)" %
(matrix.col(old_beam_centre_px) - matrix.col(new_beam_centre_px)).elems
)
return new_experiments
def run(args):
from dials.util.options import OptionParser
from dials.util.options import flatten_datablocks
from dials.util.options import flatten_experiments
from dials.util.options import flatten_reflections
from dials.util import log
import libtbx.load_env
usage = "%s [options] datablock.json reflections.pickle" % (
libtbx.env.dispatcher_name)
parser = OptionParser(usage=usage,
phil=phil_scope,
read_datablocks=True,
read_experiments=True,
read_reflections=True,
check_format=False,
epilog=help_message)
params, options = parser.parse_args()
datablocks = flatten_datablocks(params.input.datablock)
experiments = flatten_experiments(params.input.experiments)
reflections = flatten_reflections(params.input.reflections)
if (len(datablocks) == 0
and len(experiments) == 0) or len(reflections) == 0:
parser.print_help()
exit(0)
# Configure the logging
log.config(info='dials.rl_png.log')
# Log the diff phil
diff_phil = parser.diff_phil.as_str()
if diff_phil is not '':
logger.info('The following parameters have been modified:\n')
logger.info(diff_phil)
reflections = reflections[0]
if len(datablocks) == 0 and len(experiments) > 0:
imagesets = experiments.imagesets()
else:
imagesets = []
for datablock in datablocks:
imagesets.extend(datablock.extract_imagesets())
f = ReciprocalLatticePng(settings=params)
f.load_models(imagesets, reflections, None)
imageset = imagesets[0]
rotation_axis = matrix.col(imageset.get_goniometer().get_rotation_axis())
s0 = matrix.col(imageset.get_beam().get_s0())
e1 = rotation_axis.normalize()
e2 = s0.normalize()
e3 = e1.cross(e2).normalize()
#print e1
#print e2
#print e3
f.viewer.plot('rl_rotation_axis.png', n=e1.elems)
f.viewer.plot('rl_beam_vector', n=e2.elems)
f.viewer.plot('rl_e3.png', n=e3.elems)
n_solutions = params.basis_vector_search.n_solutions
if len(experiments):
for i, c in enumerate(experiments.crystals()):
A = matrix.sqr(c.get_A())
astar = A[:3]
bstar = A[3:6]
cstar = A[6:9]
direct_matrix = A.inverse()
a = direct_matrix[:3]
b = direct_matrix[3:6]
c = direct_matrix[6:9]
prefix = ''
if len(experiments.crystals()) > 1:
prefix = '%i_' % (i + 1)
f.viewer.plot('rl_%sa.png' % prefix, n=a)
f.viewer.plot('rl_%sb.png' % prefix, n=b)
f.viewer.plot('rl_%sc.png' % prefix, n=c)
elif n_solutions:
from dials.command_line.search_beam_position \
import run_dps, dps_phil_scope
hardcoded_phil = dps_phil_scope.extract()
hardcoded_phil.d_min = params.d_min
imageset = imagesets[0]
from dials.algorithms.indexing.indexer import indexer_base
if 'imageset_id' not in reflections:
reflections['imageset_id'] = reflections['id']
spots_mm = indexer_base.map_spots_pixel_to_mm_rad(
spots=reflections,
detector=imageset.get_detector(),
scan=imageset.get_scan())
indexer_base.map_centroids_to_reciprocal_space(
spots_mm,
detector=imageset.get_detector(),
beam=imageset.get_beam(),
goniometer=imageset.get_goniometer())
if params.d_min is not None:
d_spacings = 1 / spots_mm['rlp'].norms()
sel = d_spacings > params.d_min
spots_mm = spots_mm.select(sel)
# derive a max_cell from mm spots
from dials.algorithms.indexing.indexer import find_max_cell
max_cell = find_max_cell(spots_mm,
max_cell_multiplier=1.3,
step_size=45).max_cell
result = run_dps((imageset, spots_mm, max_cell, hardcoded_phil))
solutions = [matrix.col(v) for v in result['solutions']]
for i in range(min(n_solutions, len(solutions))):
v = solutions[i]
#if i > 0:
#for v1 in solutions[:i-1]:
#angle = v.angle(v1, deg=True)
#print angle
f.viewer.plot('rl_solution_%s.png' % (i + 1), n=v.elems)
def run():
from dials.util.options import OptionParser, reflections_and_experiments_from_files
from dials.util import log
usage = "dials.rl_png [options] experiments.json observations.refl"
parser = OptionParser(
usage=usage,
phil=phil_scope,
read_experiments=True,
read_reflections=True,
check_format=False,
epilog=help_message,
)
params, options = parser.parse_args()
reflections, experiments = reflections_and_experiments_from_files(
params.input.reflections, params.input.experiments)
if len(experiments) == 0 or len(reflections) == 0:
parser.print_help()
exit(0)
# Configure the logging
log.config(logfile="dials.rl_png.log")
# Log the diff phil
diff_phil = parser.diff_phil.as_str()
if diff_phil != "":
logger.info("The following parameters have been modified:\n")
logger.info(diff_phil)
reflections = reflections[0]
f = ReciprocalLatticePng(settings=params)
f.load_models(experiments, reflections)
rotation_axis = matrix.col(experiments[0].goniometer.get_rotation_axis())
s0 = matrix.col(experiments[0].beam.get_s0())
e1 = rotation_axis.normalize()
e2 = s0.normalize()
e3 = e1.cross(e2).normalize()
f.viewer.plot("rl_rotation_axis.png", n=e1.elems)
f.viewer.plot("rl_beam_vector", n=e2.elems)
f.viewer.plot("rl_e3.png", n=e3.elems)
n_solutions = params.basis_vector_search.n_solutions
if experiments.crystals().count(None) < len(experiments):
for i, c in enumerate(experiments.crystals()):
A = matrix.sqr(c.get_A())
direct_matrix = A.inverse()
a = direct_matrix[:3]
b = direct_matrix[3:6]
c = direct_matrix[6:9]
prefix = ""
if len(experiments.crystals()) > 1:
prefix = "%i_" % (i + 1)
f.viewer.plot("rl_%sa.png" % prefix, n=a)
f.viewer.plot("rl_%sb.png" % prefix, n=b)
f.viewer.plot("rl_%sc.png" % prefix, n=c)
elif n_solutions:
if "imageset_id" not in reflections:
reflections["imageset_id"] = reflections["id"]
reflections.centroid_px_to_mm(experiments)
reflections.map_centroids_to_reciprocal_space(experiments)
if params.d_min is not None:
d_spacings = 1 / reflections["rlp"].norms()
sel = d_spacings > params.d_min
reflections = reflections.select(sel)
# derive a max_cell from mm spots
max_cell = find_max_cell(reflections,
max_cell_multiplier=1.3,
step_size=45).max_cell
result = run_dps(experiments[0], reflections, max_cell)
if result:
solutions = [matrix.col(v) for v in result["solutions"]]
for i in range(min(n_solutions, len(solutions))):
v = solutions[i]
f.viewer.plot("rl_solution_%s.png" % (i + 1), n=v.elems)
def discover_better_experimental_model(
imagesets, spot_lists, params, dps_params, nproc=1, wide_search_binning=1):
assert len(imagesets) == len(spot_lists)
assert len(imagesets) > 0
# XXX should check that all the detector and beam objects are the same
from dials.algorithms.indexing.indexer import indexer_base
spot_lists_mm = [
indexer_base.map_spots_pixel_to_mm_rad(
spots, imageset.get_detector(), imageset.get_scan())
for spots, imageset in zip(spot_lists, imagesets)]
spot_lists_mm = []
max_cell_list = []
detector = imagesets[0].get_detector()
beam = imagesets[0].get_beam()
beam_panel = detector.get_panel_intersection(beam.get_s0())
if beam_panel == -1:
from libtbx.utils import Sorry
raise Sorry, 'input beam does not intersect detector'
for imageset, spots in zip(imagesets, spot_lists):
if 'imageset_id' not in spots:
spots['imageset_id'] = spots['id']
spots_mm = indexer_base.map_spots_pixel_to_mm_rad(
spots=spots, detector=imageset.get_detector(), scan=imageset.get_scan())
indexer_base.map_centroids_to_reciprocal_space(
spots_mm, detector=imageset.get_detector(), beam=imageset.get_beam(),
goniometer=imageset.get_goniometer())
if dps_params.d_min is not None:
d_spacings = 1/spots_mm['rlp'].norms()
sel = d_spacings > dps_params.d_min
spots_mm = spots_mm.select(sel)
# derive a max_cell from mm spots
if params.max_cell is None:
from dials.algorithms.indexing.indexer import find_max_cell
max_cell = find_max_cell(spots_mm, max_cell_multiplier=1.3,
step_size=45,
nearest_neighbor_percentile=0.05).max_cell
max_cell_list.append(max_cell)
if (params.max_reflections is not None and
spots_mm.size() > params.max_reflections):
logger.info('Selecting subset of %i reflections for analysis'
%params.max_reflections)
perm = flex.random_permutation(spots_mm.size())
sel = perm[:params.max_reflections]
spots_mm = spots_mm.select(sel)
spot_lists_mm.append(spots_mm)
if params.max_cell is None:
max_cell = flex.median(flex.double(max_cell_list))
else:
max_cell = params.max_cell
args = [(imageset, spots, max_cell, dps_params)
for imageset, spots in zip(imagesets, spot_lists_mm)]
from libtbx import easy_mp
results = easy_mp.parallel_map(
func=run_dps,
iterable=args,
processes=nproc,
method="multiprocessing",
preserve_order=True,
asynchronous=True,
preserve_exception_message=True)
solution_lists = [r["solutions"] for r in results]
amax_list = [r["amax"] for r in results]
assert len(solution_lists) > 0
detector = imagesets[0].get_detector()
beam = imagesets[0].get_beam()
# perform calculation
if dps_params.indexing.improve_local_scope == "origin_offset":
discoverer = better_experimental_model_discovery(
imagesets, spot_lists_mm, solution_lists, amax_list, dps_params,
wide_search_binning=wide_search_binning)
new_detector = discoverer.optimize_origin_offset_local_scope()
old_beam_centre = detector.get_ray_intersection(beam.get_s0())[1]
new_beam_centre = new_detector.get_ray_intersection(beam.get_s0())[1]
logger.info("Old beam centre: %.2f mm, %.2f mm" %old_beam_centre)
logger.info("New beam centre: %.2f mm, %.2f mm" %new_beam_centre)
logger.info("Shift: %.2f mm, %.2f mm" %(
matrix.col(old_beam_centre)-matrix.col(new_beam_centre)).elems)
return new_detector, beam
elif dps_params.indexing.improve_local_scope=="S0_vector":
raise NotImplementedError()