def test_determine_space_group(space_group):
sgi = sgtbx.space_group_info(symbol=space_group)
sg = sgi.group()
cs = sgi.any_compatible_crystal_symmetry(volume=10000)
cs = cs.best_cell()
cs = cs.minimum_cell()
intensities = (
generate_intensities(cs, d_min=1.0)
.generate_bijvoet_mates()
.set_observation_type_xray_intensity()
)
intensities = intensities.expand_to_p1()
# needed to give vaguely sensible E_cc_true values
intensities = intensities.customized_copy(sigmas=intensities.data() / 50)
intensities.set_info(miller.array_info(source="fake", source_type="mtz"))
result = LaueGroupAnalysis([intensities], normalisation=None)
print(result)
assert (
result.best_solution.subgroup["best_subsym"].space_group()
== sg.build_derived_patterson_group()
)
assert result.best_solution.likelihood > 0.8
for score in result.subgroup_scores[1:]:
assert score.likelihood < 0.1
def generate_reflections_in_sg(space_group, id_=0, assign_id=False):
"""Generate reflections with intensities consistent with space group"""
sgi = sgtbx.space_group_info(symbol=space_group)
cs = sgi.any_compatible_crystal_symmetry(volume=3000)
cs = cs.best_cell()
cs = cs.minimum_cell()
intensities = (
generate_intensities(cs, d_min=2.0)
.generate_bijvoet_mates()
.set_observation_type_xray_intensity()
)
intensities = intensities.expand_to_p1()
# needed to give vaguely sensible E_cc_true values
reflections = flex.reflection_table()
reflections["intensity.sum.value"] = intensities.data()
reflections["intensity.sum.variance"] = flex.pow2(intensities.sigmas())
reflections["miller_index"] = intensities.indices()
reflections["d"] = intensities.d_spacings().data()
reflections["id"] = flex.int(reflections.size(), id_)
if assign_id:
reflections.experiment_identifiers()[id_] = str(id_)
reflections.set_flags(
flex.bool(reflections.size(), True), reflections.flags.integrated
)
return reflections
def generate_fake_intensities(crystal_symmetry):
intensities = (generate_intensities(crystal_symmetry,
d_min=1.0).generate_bijvoet_mates().
set_observation_type_xray_intensity())
intensities = intensities.expand_to_p1()
# needed to give vaguely sensible E_cc_true values
intensities = intensities.customized_copy(sigmas=intensities.data() / 50)
intensities.set_info(miller.array_info(source="fake", source_type="mtz"))
return intensities
def test_score_symmetry_element_subgroup(space_group):
sgi = sgtbx.space_group_info(symbol=space_group)
cs = sgi.any_compatible_crystal_symmetry(volume=10000)
cs = cs.best_cell()
cs = cs.minimum_cell()
intensities = (
generate_intensities(cs, d_min=1.0)
.generate_bijvoet_mates()
.set_observation_type_xray_intensity()
)
intensities = intensities.expand_to_p1()
subgroups = metric_subgroups(
intensities.crystal_symmetry(), max_delta=2.0, bravais_types_only=False
)
intensities = intensities.change_basis(subgroups.cb_op_inp_minimum)
cs = cs.change_basis(subgroups.cb_op_inp_minimum)
cb_op_inp_best = subgroups.result_groups[0]["cb_op_inp_best"]
lattice_group = subgroups.result_groups[0]["best_subsym"].space_group()
lattice_group = lattice_group.change_basis(cb_op_inp_best.inverse())
lattice_group = subgroups.result_groups[0]["subsym"].space_group()
sym_op_scores = []
for sym_op in lattice_group.smx():
if sym_op.r().info().sense() < 0:
continue
score = ScoreSymmetryElement(intensities, sym_op, 1.0, 1.0)
sym_op_scores.append(score)
if sym_op in cs.space_group():
assert score.likelihood > 0.9
assert score.cc.coefficient() > 0.9
else:
assert score.likelihood < 0.2
assert score.cc.coefficient() < 0.3
subgroup_scores = [
ScoreSubGroup(subgrp, sym_op_scores) for subgrp in subgroups.result_groups
]
total_likelihood = sum(score.likelihood for score in subgroup_scores)
for score in subgroup_scores:
score.likelihood /= total_likelihood
true_patterson_group = (
cs.space_group_info()
.as_reference_setting()
.group()
.build_derived_patterson_group()
)
for score in subgroup_scores:
if score.subgroup["best_subsym"].space_group() == true_patterson_group:
assert score.likelihood > 0.8
else:
assert score.likelihood < 0.1
