def config_restraints(params, pred_param):
"""Given a set of user parameters plus a model parameterisation, create
restraints plus a parameterisation of these restraints
Params:
params: The input PHIL parameters
pred_param: A PredictionParameters object
Returns:
A restraints parameterisation or None
"""
if not any([
params.crystal.unit_cell.restraints.tie_to_target,
params.crystal.unit_cell.restraints.tie_to_group,
]):
return None
if params.scan_varying:
logger.warning("Restraints will be ignored for scan_varying=True")
return None
det_params = pred_param.get_detector_parameterisations()
beam_params = pred_param.get_beam_parameterisations()
xl_ori_params = pred_param.get_crystal_orientation_parameterisations()
xl_uc_params = pred_param.get_crystal_unit_cell_parameterisations()
gon_params = pred_param.get_goniometer_parameterisations()
from dials.algorithms.refinement.restraints import RestraintsParameterisation
rp = RestraintsParameterisation(
detector_parameterisations=det_params,
beam_parameterisations=beam_params,
xl_orientation_parameterisations=xl_ori_params,
xl_unit_cell_parameterisations=xl_uc_params,
goniometer_parameterisations=gon_params,
)
# Shorten params path
# FIXME Only unit cell restraints currently supported
# beam_r = params.beam.restraints
cell_r = params.crystal.unit_cell.restraints
# orientation_r = params.crystal.orientation.restraints
# detector_r = params.detector.restraints
for tie in cell_r.tie_to_target:
if len(tie.values) != 6:
raise DialsRefineConfigError(
"6 cell parameters must be provided as the tie_to_target.values."
)
if len(tie.sigmas) != 6:
raise DialsRefineConfigError(
"6 sigmas must be provided as the tie_to_target.sigmas. "
"Note that individual sigmas of 0.0 will remove "
"the restraint for the corresponding cell parameter.")
if tie.id is None:
# get one experiment id for each parameterisation to apply to all
tie.id = [e.get_experiment_ids()[0] for e in xl_uc_params]
for exp_id in tie.id:
rp.add_restraints_to_target_xl_unit_cell(
exp_id, tie.values, tie.sigmas)
for tie in cell_r.tie_to_group:
if len(tie.sigmas) != 6:
raise DialsRefineConfigError(
"6 sigmas must be provided as the tie_to_group.sigmas. "
"Note that individual sigmas of 0.0 will remove "
"the restraint for the corresponding cell parameter.")
if tie.id is None:
rp.add_restraints_to_group_xl_unit_cell(
tie.target, "all", tie.sigmas)
else:
rp.add_restraints_to_group_xl_unit_cell(
tie.target, tie.id, tie.sigmas)
return rp
def test_single_crystal_restraints_gradients():
"""Simple test with a single triclinic crystal restrained to a target unit cell"""
from dxtbx.model.experiment_list import Experiment, ExperimentList
from dials.algorithms.refinement.parameterisation.beam_parameters import (
BeamParameterisation, )
from dials.algorithms.refinement.parameterisation.crystal_parameters import (
CrystalOrientationParameterisation,
CrystalUnitCellParameterisation,
)
from dials.algorithms.refinement.parameterisation.detector_parameters import (
DetectorParameterisationSinglePanel, )
from dials.algorithms.refinement.parameterisation.prediction_parameters import (
XYPhiPredictionParameterisation, )
from dials.test.algorithms.refinement.setup_geometry import Extract
overrides = """geometry.parameters.crystal.a.length.range = 10 50
geometry.parameters.crystal.b.length.range = 10 50
geometry.parameters.crystal.c.length.range = 10 50"""
master_phil = parse(
"""
include scope dials.test.algorithms.refinement.geometry_phil
""",
process_includes=True,
)
models = Extract(master_phil, overrides)
mydetector = models.detector
mygonio = models.goniometer
mycrystal = models.crystal
mybeam = models.beam
# Build a mock scan for a 72 degree sequence
from dxtbx.model import ScanFactory
sf = ScanFactory()
myscan = sf.make_scan(
image_range=(1, 720),
exposure_times=0.1,
oscillation=(0, 0.1),
epochs=list(range(720)),
deg=True,
)
# Create parameterisations of these models
det_param = DetectorParameterisationSinglePanel(mydetector)
s0_param = BeamParameterisation(mybeam, mygonio)
xlo_param = CrystalOrientationParameterisation(mycrystal)
xluc_param = CrystalUnitCellParameterisation(mycrystal)
# Create an ExperimentList
experiments = ExperimentList()
experiments.append(
Experiment(
beam=mybeam,
detector=mydetector,
goniometer=mygonio,
scan=myscan,
crystal=mycrystal,
imageset=None,
))
# Build a prediction parameterisation
pred_param = XYPhiPredictionParameterisation(
experiments,
detector_parameterisations=[det_param],
beam_parameterisations=[s0_param],
xl_orientation_parameterisations=[xlo_param],
xl_unit_cell_parameterisations=[xluc_param],
)
# Build a restraints parameterisation
rp = RestraintsParameterisation(
detector_parameterisations=[det_param],
beam_parameterisations=[s0_param],
xl_orientation_parameterisations=[xlo_param],
xl_unit_cell_parameterisations=[xluc_param],
)
# make a unit cell target
sigma = 1.0
uc = mycrystal.get_unit_cell().parameters()
target_uc = [random.gauss(e, sigma) for e in uc]
rp.add_restraints_to_target_xl_unit_cell(experiment_id=0,
values=target_uc,
sigma=[sigma] * 6)
# get analytical values and gradients
vals, grads, weights = rp.get_residuals_gradients_and_weights()
assert len(vals) == rp.num_residuals
# get finite difference gradients
p_vals = pred_param.get_param_vals()
deltas = [1.0e-7] * len(p_vals)
fd_grad = []
for i, delta in enumerate(deltas):
val = p_vals[i]
p_vals[i] -= delta / 2.0
pred_param.set_param_vals(p_vals)
rev_state, foo, bar = rp.get_residuals_gradients_and_weights()
rev_state = flex.double(rev_state)
p_vals[i] += delta
pred_param.set_param_vals(p_vals)
fwd_state, foo, bar = rp.get_residuals_gradients_and_weights()
fwd_state = flex.double(fwd_state)
p_vals[i] = val
fd = (fwd_state - rev_state) / delta
fd_grad.append(fd)
# for comparison, fd_grad is a list of flex.doubles, each of which corresponds
# to a column of the sparse matrix grads.
for i, fd in enumerate(fd_grad):
# extract dense column from the sparse matrix
an = grads.col(i).as_dense_vector()
assert an == pytest.approx(fd, abs=1e-5)
def test1():
'''Simple test with a single triclinic crystal restrained to a target unit cell'''
from math import pi
from random import gauss
from dials.test.algorithms.refinement.setup_geometry import Extract
from dxtbx.model.experiment.experiment_list import ExperimentList, Experiment
#### Import model parameterisations
from dials.algorithms.refinement.parameterisation.prediction_parameters import \
XYPhiPredictionParameterisation
from dials.algorithms.refinement.parameterisation.detector_parameters import \
DetectorParameterisationSinglePanel
from dials.algorithms.refinement.parameterisation.beam_parameters import \
BeamParameterisation
from dials.algorithms.refinement.parameterisation.crystal_parameters import \
CrystalOrientationParameterisation, \
CrystalUnitCellParameterisation
overrides = """geometry.parameters.crystal.a.length.range = 10 50
geometry.parameters.crystal.b.length.range = 10 50
geometry.parameters.crystal.c.length.range = 10 50"""
master_phil = parse("""
include scope dials.test.algorithms.refinement.geometry_phil
""", process_includes=True)
models = Extract(master_phil, overrides)
mydetector = models.detector
mygonio = models.goniometer
mycrystal = models.crystal
mybeam = models.beam
# Build a mock scan for a 72 degree sweep
sweep_range = (0., pi/5.)
from dxtbx.model.scan import scan_factory
sf = scan_factory()
myscan = sf.make_scan(image_range = (1,720),
exposure_times = 0.1,
oscillation = (0, 0.1),
epochs = range(720),
deg = True)
# Create parameterisations of these models
det_param = DetectorParameterisationSinglePanel(mydetector)
s0_param = BeamParameterisation(mybeam, mygonio)
xlo_param = CrystalOrientationParameterisation(mycrystal)
xluc_param = CrystalUnitCellParameterisation(mycrystal)
# Create an ExperimentList
experiments = ExperimentList()
experiments.append(Experiment(
beam=mybeam, detector=mydetector, goniometer=mygonio, scan=myscan,
crystal=mycrystal, imageset=None))
# Build a prediction parameterisation
pred_param = XYPhiPredictionParameterisation(experiments,
detector_parameterisations = [det_param],
beam_parameterisations = [s0_param],
xl_orientation_parameterisations = [xlo_param],
xl_unit_cell_parameterisations = [xluc_param])
# Build a restraints parameterisation
rp = RestraintsParameterisation(detector_parameterisations = [det_param],
beam_parameterisations = [s0_param],
xl_orientation_parameterisations = [xlo_param],
xl_unit_cell_parameterisations = [xluc_param])
# make a unit cell target
sigma = 1.
uc = mycrystal.get_unit_cell().parameters()
target_uc = [gauss(e, sigma) for e in uc]
rp.add_restraints_to_target_xl_unit_cell(experiment_id=0, values=target_uc,
sigma=[sigma]*6)
# get analytical values and gradients
vals, grads, weights = rp.get_residuals_gradients_and_weights()
# get finite difference gradients
p_vals = pred_param.get_param_vals()
deltas = [1.e-7] * len(p_vals)
fd_grad=[]
for i in range(len(deltas)):
val = p_vals[i]
p_vals[i] -= deltas[i] / 2.
pred_param.set_param_vals(p_vals)
rev_state, foo, bar = rp.get_residuals_gradients_and_weights()
rev_state = flex.double(rev_state)
p_vals[i] += deltas[i]
pred_param.set_param_vals(p_vals)
fwd_state, foo, bar = rp.get_residuals_gradients_and_weights()
fwd_state = flex.double(fwd_state)
p_vals[i] = val
fd = (fwd_state - rev_state) / deltas[i]
fd_grad.append(fd)
# for comparison, fd_grad is a list of flex.doubles, each of which corresponds
# to a column of the sparse matrix grads.
for i, fd in enumerate(fd_grad):
# extract dense column from the sparse matrix
an = grads.col(i).as_dense_vector()
assert approx_equal(an, fd, eps=1e-5)
print "OK"
def test2():
'''Simple test with two triclinic crystals restrained to a target unit cell'''
from math import pi
from random import gauss
from dials.test.algorithms.refinement.setup_geometry import Extract
from dxtbx.model.experiment.experiment_list import ExperimentList, Experiment
#### Import model parameterisations
from dials.algorithms.refinement.parameterisation.prediction_parameters import \
XYPhiPredictionParameterisation
from dials.algorithms.refinement.parameterisation.detector_parameters import \
DetectorParameterisationSinglePanel
from dials.algorithms.refinement.parameterisation.beam_parameters import \
BeamParameterisation
from dials.algorithms.refinement.parameterisation.crystal_parameters import \
CrystalOrientationParameterisation, \
CrystalUnitCellParameterisation
overrides = """geometry.parameters.crystal.a.length.range = 10 50
geometry.parameters.crystal.b.length.range = 10 50
geometry.parameters.crystal.c.length.range = 10 50"""
master_phil = parse("""
include scope dials.test.algorithms.refinement.geometry_phil
""",
process_includes=True)
models = Extract(master_phil, overrides)
mydetector = models.detector
mygonio = models.goniometer
mycrystal = models.crystal
# duplicate the crystal
from copy import deepcopy
mycrystal2 = deepcopy(mycrystal)
mybeam = models.beam
# Build a mock scan for a 72 degree sweep
sweep_range = (0., pi / 5.)
from dxtbx.model.scan import scan_factory
sf = scan_factory()
myscan = sf.make_scan(image_range=(1, 720),
exposure_times=0.1,
oscillation=(0, 0.1),
epochs=range(720),
deg=True)
# Create parameterisations of these models
det_param = DetectorParameterisationSinglePanel(mydetector)
s0_param = BeamParameterisation(mybeam, mygonio)
xlo_param = CrystalOrientationParameterisation(mycrystal)
xluc_param = CrystalUnitCellParameterisation(mycrystal)
xluc_param2 = CrystalUnitCellParameterisation(mycrystal2,
experiment_ids=[1])
# Create an ExperimentList with the crystal duplicated
experiments = ExperimentList()
experiments.append(
Experiment(beam=mybeam,
detector=mydetector,
goniometer=mygonio,
scan=myscan,
crystal=mycrystal,
imageset=None))
experiments.append(
Experiment(beam=mybeam,
detector=mydetector,
goniometer=mygonio,
scan=myscan,
crystal=mycrystal2,
imageset=None))
# Build a prediction parameterisation
pred_param = XYPhiPredictionParameterisation(
experiments,
detector_parameterisations=[det_param],
beam_parameterisations=[s0_param],
xl_orientation_parameterisations=[xlo_param],
xl_unit_cell_parameterisations=[xluc_param, xluc_param2])
# Build a restraints parameterisation
rp = RestraintsParameterisation(
detector_parameterisations=[det_param],
beam_parameterisations=[s0_param],
xl_orientation_parameterisations=[xlo_param],
xl_unit_cell_parameterisations=[xluc_param, xluc_param2])
# make a unit cell target
sigma = 1.
uc = mycrystal.get_unit_cell().parameters()
target_uc = [gauss(e, sigma) for e in uc]
rp.add_restraints_to_target_xl_unit_cell(experiment_id=0,
values=target_uc,
sigma=[sigma] * 6)
rp.add_restraints_to_target_xl_unit_cell(experiment_id=1,
values=target_uc,
sigma=[sigma] * 6)
# get analytical values and gradients
vals, grads, weights = rp.get_residuals_gradients_and_weights()
# get finite difference gradients
p_vals = pred_param.get_param_vals()
deltas = [1.e-7] * len(p_vals)
fd_grad = []
for i in range(len(deltas)):
val = p_vals[i]
p_vals[i] -= deltas[i] / 2.
pred_param.set_param_vals(p_vals)
rev_state, foo, bar = rp.get_residuals_gradients_and_weights()
rev_state = flex.double(rev_state)
p_vals[i] += deltas[i]
pred_param.set_param_vals(p_vals)
fwd_state, foo, bar = rp.get_residuals_gradients_and_weights()
fwd_state = flex.double(fwd_state)
p_vals[i] = val
fd = (fwd_state - rev_state) / deltas[i]
fd_grad.append(fd)
# for comparison, fd_grad is a list of flex.doubles, each of which corresponds
# to a column of the sparse matrix grads.
for i, fd in enumerate(fd_grad):
# extract dense column from the sparse matrix
an = grads.col(i).as_dense_vector()
assert approx_equal(an, fd, eps=1e-5)
print "OK"