def exercise_labelit_indexer():
if not have_dials_regression:
print "Skipping exercise_labelit_indexer(): dials_regression not configured"
return
xia2_demo_data = os.path.join(dials_regression, "xia2_demo_data")
template = os.path.join(xia2_demo_data, "insulin_1_###.img")
cwd = os.path.abspath(os.curdir)
tmp_dir = os.path.abspath(open_tmp_directory())
os.chdir(tmp_dir)
from xia2.Modules.Indexer.LabelitIndexer import LabelitIndexer
from xia2.DriverExceptions.NotAvailableError import NotAvailableError
try:
ls = LabelitIndexer(indxr_print=True)
except NotAvailableError:
print "Skipping exercise_labelit_indexer(): labelit not found"
return
ls.set_working_directory(tmp_dir)
from dxtbx.datablock import DataBlockTemplateImporter
importer = DataBlockTemplateImporter([template])
datablocks = importer.datablocks
imageset = datablocks[0].extract_imagesets()[0]
ls.add_indexer_imageset(imageset)
ls.index()
assert approx_equal(ls.get_indexer_cell(), (78.58, 78.58, 78.58, 90, 90, 90))
solution = ls.get_solution()
assert approx_equal(solution['rmsd'], 0.076)
assert approx_equal(solution['metric'], 0.1566, eps=1e-3)
assert solution['number'] == 22
assert solution['lattice'] == 'cI'
assert solution['mosaic'] == 0.025
assert abs(solution['nspots'] - 860) <= 1
beam_centre = ls.get_indexer_beam_centre()
assert approx_equal(beam_centre, (94.3416, 94.4994), eps=1e-2)
assert ls.get_indexer_images() == [(1, 1), (22, 22), (45, 45)]
print ls.get_indexer_experiment_list()[0].crystal
print ls.get_indexer_experiment_list()[0].detector
json_str = ls.as_json()
#print ls.to_dict()
print json_str
ls1 = LabelitIndexer.from_json(string=json_str)
ls1.index()
print ls.get_indexer_experiment_list()[0].crystal
assert ls.get_indexer_beam_centre() == ls1.get_indexer_beam_centre()
assert approx_equal(ls.get_indexer_images(), ls1.get_indexer_images())
assert ls.get_distance() == ls1.get_distance()
ls.eliminate()
ls1.eliminate()
print ls1.get_indexer_experiment_list()[0].crystal
assert ls.get_indexer_beam_centre() == ls1.get_indexer_beam_centre()
assert approx_equal(ls.get_indexer_images(), ls1.get_indexer_images())
assert ls.get_distance() == ls1.get_distance()
print ls1.get_indexer_cell()
print ls1.get_solution()
assert approx_equal(ls.get_indexer_cell(),
(111.11, 111.11, 68.08, 90.0, 90.0, 120.0), 1e-1)
solution = ls1.get_solution()
assert solution['rmsd'] >= 0.07, solution['rmsd']
assert approx_equal(solution['metric'], 0.1291, eps=1e-3)
#assert solution['number'] == 8
assert solution['lattice'] == 'hR', solution['lattice']
assert solution['mosaic'] == 0.025, solution['mosaic']
assert abs(solution['nspots'] - 856) <= 3
def test_labelit_indexer(ccp4, xia2_regression_build, tmpdir):
template = os.path.join(xia2_regression_build, "test_data", "insulin",
"insulin_1_###.img")
tmpdir.chdir()
from xia2.Modules.Indexer.LabelitIndexer import LabelitIndexer
from xia2.DriverExceptions.NotAvailableError import NotAvailableError
try:
ls = LabelitIndexer(indxr_print=True)
except NotAvailableError:
pytest.skip("labelit not found")
ls.set_working_directory(tmpdir.strpath)
from dxtbx.datablock import DataBlockTemplateImporter
importer = DataBlockTemplateImporter([template])
datablocks = importer.datablocks
imageset = datablocks[0].extract_imagesets()[0]
ls.add_indexer_imageset(imageset)
ls.index()
assert ls.get_indexer_cell() == pytest.approx(
(78.58, 78.58, 78.58, 90, 90, 90), abs=0.5)
solution = ls.get_solution()
assert solution['rmsd'] <= 0.2
assert solution['metric'] <= 0.16
assert solution['number'] == 22
assert solution['lattice'] == 'cI'
assert solution['mosaic'] <= 0.25
assert solution['nspots'] == pytest.approx(860, abs=30)
beam_centre = ls.get_indexer_beam_centre()
assert beam_centre == pytest.approx((94.3416, 94.4994), abs=2e-1)
assert ls.get_indexer_images() == [(1, 1), (22, 22), (45, 45)]
print(ls.get_indexer_experiment_list()[0].crystal)
print(ls.get_indexer_experiment_list()[0].detector)
json_str = ls.as_json()
# print(json_str)
ls1 = LabelitIndexer.from_json(string=json_str)
ls1.index()
print(ls.get_indexer_experiment_list()[0].crystal)
assert ls.get_indexer_beam_centre() == ls1.get_indexer_beam_centre()
assert ls1.get_indexer_images() == [[1, 1], [22, 22],
[45,
45]] # in JSON tuples become lists
assert ls.get_distance() == ls1.get_distance()
ls.eliminate()
ls1.eliminate()
print(ls1.get_indexer_experiment_list()[0].crystal)
assert ls.get_indexer_beam_centre() == ls1.get_indexer_beam_centre()
assert ls.get_indexer_images() == [(1, 1), (22, 22), (45, 45)]
assert ls1.get_indexer_images() == [[1, 1], [22, 22],
[45,
45]] # in JSON tuples become lists
assert ls.get_distance() == ls1.get_distance()
print(ls1.get_indexer_cell())
print(ls1.get_solution())
assert ls.get_indexer_cell() == pytest.approx(
(111.11, 111.11, 68.08, 90.0, 90.0, 120.0), abs=5e-1)
solution = ls1.get_solution()
assert solution['rmsd'] >= 0.07, solution['rmsd']
assert solution['metric'] == pytest.approx(0.1291, abs=1e-1)
assert solution['lattice'] == 'hR', solution['lattice']
assert solution['mosaic'] <= 0.3, solution['mosaic']
assert solution['nspots'] == pytest.approx(856, abs=30)
def test_labelit_indexer(regression_test, ccp4, dials_data, run_in_tmpdir):
template = dials_data("insulin").join("insulin_1_###.img").strpath
from xia2.Modules.Indexer.LabelitIndexer import LabelitIndexer
from xia2.DriverExceptions.NotAvailableError import NotAvailableError
try:
ls = LabelitIndexer(indxr_print=True)
except NotAvailableError:
pytest.skip("labelit not found")
ls.set_working_directory(run_in_tmpdir.strpath)
from dxtbx.model.experiment_list import ExperimentListTemplateImporter
importer = ExperimentListTemplateImporter([template])
experiments = importer.experiments
imageset = experiments.imagesets()[0]
ls.add_indexer_imageset(imageset)
ls.index()
assert ls.get_indexer_cell() == pytest.approx(
(78.58, 78.58, 78.58, 90, 90, 90), abs=0.5)
solution = ls.get_solution()
assert solution["rmsd"] <= 0.2
assert solution["metric"] <= 0.16
assert solution["number"] == 22
assert solution["lattice"] == "cI"
assert solution["mosaic"] <= 0.25
assert solution["nspots"] == pytest.approx(860, abs=30)
beam_centre = ls.get_indexer_beam_centre()
assert beam_centre == pytest.approx((94.3416, 94.4994), abs=2e-1)
assert ls.get_indexer_images() == [(1, 1), (22, 22), (45, 45)]
print(ls.get_indexer_experiment_list()[0].crystal)
print(ls.get_indexer_experiment_list()[0].detector)
json_str = ls.as_json()
# print(json_str)
ls1 = LabelitIndexer.from_json(string=json_str)
ls1.index()
print(ls.get_indexer_experiment_list()[0].crystal)
assert ls.get_indexer_beam_centre() == ls1.get_indexer_beam_centre()
assert ls1.get_indexer_images() == [
[1, 1],
[22, 22],
[45, 45],
] # in JSON tuples become lists
assert ls.get_distance() == ls1.get_distance()
ls.eliminate()
ls1.eliminate()
print(ls1.get_indexer_experiment_list()[0].crystal)
assert ls.get_indexer_beam_centre() == ls1.get_indexer_beam_centre()
assert ls.get_indexer_images() == [(1, 1), (22, 22), (45, 45)]
assert ls1.get_indexer_images() == [
[1, 1],
[22, 22],
[45, 45],
] # in JSON tuples become lists
assert ls.get_distance() == ls1.get_distance()
print(ls1.get_indexer_cell())
print(ls1.get_solution())
assert ls.get_indexer_cell() == pytest.approx(
(111.11, 111.11, 68.08, 90.0, 90.0, 120.0), abs=5e-1)
solution = ls1.get_solution()
assert solution["rmsd"] >= 0.07, solution["rmsd"]
assert solution["metric"] == pytest.approx(0.1291, abs=1e-1)
assert solution["lattice"] == "hR", solution["lattice"]
assert solution["mosaic"] <= 0.3, solution["mosaic"]
assert solution["nspots"] == pytest.approx(856, abs=30)