def test_split_chunk_sizes(tmpdir, option, with_identifiers):
ids = list(range(0, 5))
experiments = ExperimentList()
reflections = flex.reflection_table()
reflections["id"] = flex.int(ids)
reflections["intensity"] = flex.double([(i + 1) * 100.0 for i in ids])
for i in ids:
exp = generate_exp()
if with_identifiers:
exp.identifier = str(i)
reflections.experiment_identifiers()[i] = str(i)
experiments.append(exp)
experiments.as_json(tmpdir.join("tmp.expt").strpath)
reflections.as_file(tmpdir.join("tmp.refl").strpath)
result = procrunner.run(
[
"dials.split_experiments",
tmpdir.join("tmp.expt").strpath,
tmpdir.join("tmp.refl").strpath,
option,
],
working_directory=tmpdir,
)
assert not result.returncode and not result.stderr
for j, n, intensities in zip(
[0, 1, 2], [2, 2, 1], [[100.0, 200.0], [300.0, 400.0], [500.0]]
):
assert tmpdir.join("split_%s.refl" % j).check()
assert tmpdir.join("split_%s.expt" % j).check()
expts = load.experiment_list(
tmpdir.join("split_%s.expt" % j), check_format=False
)
assert len(expts) == n
refls = flex.reflection_table.from_file(tmpdir.join("split_%s.refl" % j))
assert list(set(refls["id"])) == list(range(0, n))
assert list(refls["intensity"]) == intensities
refls.assert_experiment_identifiers_are_consistent(expts)
def test_split_by_wavelength(tmpdir):
"""Test the split_by_wavelength option of dials.split_experiments"""
experiments = ExperimentList()
exp = generate_exp(wavelength=1.0)
exp.identifier = "0"
experiments.append(exp)
exp = generate_exp(wavelength=0.5)
exp.identifier = "1"
experiments.append(exp)
reflections = flex.reflection_table()
reflections["id"] = flex.int([0, 1])
reflections["intensity"] = flex.double([100.0, 200.0])
reflections.experiment_identifiers()[0] = "0"
reflections.experiment_identifiers()[1] = "1"
experiments.as_json(tmpdir.join("tmp.expt").strpath)
reflections.as_file(tmpdir.join("tmp.refl").strpath)
result = procrunner.run(
[
"dials.split_experiments", "tmp.expt", "tmp.refl",
"by_wavelength=True"
],
working_directory=tmpdir,
)
assert not result.returncode and not result.stderr
for i, (wl, ids,
intensity) in enumerate(zip([0.5, 1.0], ["1", "0"],
[200.0, 100.0])):
assert tmpdir.join("split_%d.expt" % i).check()
assert tmpdir.join("split_%d.refl" % i).check()
exp_single = load.experiment_list(tmpdir.join("split_%d.expt" %
i).strpath,
check_format=False)
ref_single = flex.reflection_table.from_file(
tmpdir.join("split_%d.refl" % i).strpath)
assert exp_single[0].beam.get_wavelength() == wl
assert exp_single[0].identifier == ids
id_ = ref_single["id"][0]
assert ref_single.experiment_identifiers()[id_] == ids
assert list(ref_single["intensity"]) == [intensity]
# Now test for successful error handling if no identifiers set.
experiments[0].identifier = ""
experiments[1].identifier = ""
experiments.as_json(tmpdir.join("tmp.expt").strpath)
result = procrunner.run(
[
"dials.split_experiments", "tmp.expt", "tmp.refl",
"by_wavelength=True"
],
working_directory=tmpdir,
)
assert result.returncode == 1
assert result.stderr.startswith(b"Sorry")
experiments[0].identifier = "0"
experiments[1].identifier = "1"
del reflections.experiment_identifiers()[0]
del reflections.experiment_identifiers()[1]
experiments.as_json(tmpdir.join("tmp.expt").strpath)
reflections.as_file(tmpdir.join("tmp.refl").strpath)
result = procrunner.run(
[
"dials.split_experiments", "tmp.expt", "tmp.refl",
"by_wavelength=True"
],
working_directory=tmpdir,
)
assert result.returncode == 1
assert result.stderr.startswith(b"Sorry")
r["xyzcal.px"][i_ref] = x, y, 0
x,y = cents_mm[ii]
r["xyzcal.mm"][i_ref] = x, y, 0
r = r.select(sel)
r["id"] = flex.int(len(r), new_exper_id)
r_orig = r_orig.select(sel)
r_orig["id"] = flex.int(len(r_orig), new_exper_id)
Rmaster_out.extend(r)
Rmaster_orig.extend(r_orig)
El_out.append(El[exper_id])
Rmaster_out.as_file("%s.refl" % args.tag)
Rmaster_orig.as_file("%s_orig.refl" % args.tag)
El_fname = "%s.expt" % args.tag
El_fname_orig = "%s_orig.expt" % args.tag
El_out.as_json(El_fname)
El_out.as_json(El_fname_orig)
#nref = len(exper_refls_strong)
#sel = flex.bool([i in i_refs for i in range(nref)]
#r = exper_refls_strong.select(sel)
#Rmaster_out.extend(r)
#El_out.append(Exper)
## make the spot integration foreground mask from the predictions
#panel_integration_masks = {}
#for pid in range(n_panels):
# panel_integration_masks[pid] = None
#
## group predictions bty panel name
#refls_predict_bypanel = prediction_utils.refls_by_panelname(refls_predict)
