def test_change_of_basis_ops_to_minimum_cell_mpro():
input_ucs = [
(46.023, 55.001, 64.452, 64.744, 78.659, 89.824),
(44.747, 53.916, 62.554, 114.985, 99.610, 90.736),
]
# Setup the input experiments and reflection tables
expts = ExperimentList()
for uc in input_ucs:
uc = uctbx.unit_cell(uc)
sg = sgtbx.space_group_info("P1").group()
B = scitbx.matrix.sqr(uc.fractionalization_matrix()).transpose()
expts.append(
Experiment(crystal=Crystal(B, space_group=sg, reciprocal=True)))
# Actually run the method we are testing
cb_ops = change_of_basis_ops_to_minimum_cell(
expts,
max_delta=5,
relative_length_tolerance=0.05,
absolute_angle_tolerance=2)
expts.change_basis(cb_ops, in_place=True)
assert symmetry.unit_cells_are_similar_to(
expts,
median_unit_cell(expts),
relative_length_tolerance=0.05,
absolute_angle_tolerance=2,
)
def from_dials_data_files(cls, params, experiments, reflection_table):
"""Initialise the class from an experiment list and reflection table.
Args:
params: A damage-analysis phil params object
experiments: An ExperimentList
reflection_table: A reflection table.
"""
reflection_table = filter_reflection_table(
reflection_table, intensity_choice=["scale"], partiality_threshold=0.4
)
# get scaled intensities
intensities = miller.array(
miller.set(
crystal.symmetry(
unit_cell=median_unit_cell(experiments),
space_group=experiments[0].crystal.get_space_group(),
),
indices=reflection_table["miller_index"],
anomalous_flag=params.anomalous,
),
data=reflection_table["intensity.scale.value"],
sigmas=flex.sqrt(reflection_table["intensity.scale.variance"]),
)
intensities.set_observation_type_xray_intensity()
doses = flex.double()
start_doses, doses_per_image = interpret_images_to_doses_options(
experiments,
params.dose.experiments.dose_per_image,
params.dose.experiments.starting_doses,
params.dose.experiments.shared_crystal,
)
logger.info(
"Interpreting data using:\n starting_doses=%s\n dose_per_image=%s",
", ".join("%s" % i for i in start_doses)
if len(set(start_doses)) > 1
else " all %s" % str(start_doses[0]),
", ".join("%s" % i for i in doses_per_image)
if len(set(doses_per_image)) > 1
else " all %s" % str(doses_per_image[0]),
)
for expt, starting_dose, dose_per_img in zip(
experiments, start_doses, doses_per_image
):
refls = reflection_table.select(expt)
imgno = flex.ceil(refls["xyzobs.px.value"].parts()[2])
dose = (imgno * dose_per_img) + starting_dose
doses.extend(dose)
doses = doses.iround()
return cls(intensities, doses, params)
def test_change_of_basis_ops_to_minimum_cell_with_outlier():
symmetries = [
crystal.symmetry(unit_cell=uc, space_group="P1") for uc in (
(52.8868, 52.8868, 333.522, 90, 90, 120),
(52.6503, 53.0292, 333.783, 89.9872, 89.2247, 60.8078),
(52.9571, 53.0005, 334.255, 90.0493, 90.0042, 119.893),
(
54.4465,
56.5677,
355.775,
93.4376,
90.0999,
118.256,
), # This is an outlier
(52.9235, 52.9235, 335.296, 90, 90, 120),
(53.4531, 53.4531, 322.909, 90, 90, 120),
)
]
# Setup the input experiments and reflection tables
expts = ExperimentList()
for cs in symmetries:
B = scitbx.matrix.sqr(
cs.unit_cell().fractionalization_matrix()).transpose()
expts.append(
Experiment(crystal=Crystal(
B, space_group=cs.space_group(), reciprocal=True)))
# Actually run the method we are testing
cb_ops = change_of_basis_ops_to_minimum_cell(
expts,
max_delta=5,
relative_length_tolerance=0.05,
absolute_angle_tolerance=2)
assert cb_ops.count(None) == 1
assert cb_ops[3] is None
expts = ExperimentList(
[expt for expt, cb_op in zip(expts, cb_ops) if cb_op])
cb_ops = [cb_op for cb_op in cb_ops if cb_op]
expts.change_basis(cb_ops, in_place=True)
assert symmetry.unit_cells_are_similar_to(
expts,
median_unit_cell(expts),
relative_length_tolerance=0.05,
absolute_angle_tolerance=2,
)
def test_median_cell():
unit_cells = [
uctbx.unit_cell(uc) for uc in [
(10, 11, 11.9, 90, 85, 90),
(10.1, 11.2, 12, 90, 85.5, 90),
(10.2, 11.1, 12, 90, 84.7, 90),
]
]
expts = ExperimentList()
for uc in unit_cells:
sg = sgtbx.space_group_info("P1").group()
B = scitbx.matrix.sqr(uc.fractionalization_matrix()).transpose()
expts.append(
Experiment(crystal=Crystal(B, space_group=sg, reciprocal=True)))
median = median_unit_cell(expts)
assert median.parameters() == pytest.approx((10.1, 11.1, 12, 90, 85, 90))
