def test_indexing_with_labelit_on_two_images(dials_regression, tmpdir):
template = os.path.join(dials_regression, "xia2_demo_data",
"insulin_1_%03i.img")
tmpdir.chdir()
from xia2.DriverExceptions.NotAvailableError import NotAvailableError
from xia2.Wrappers.Labelit.LabelitIndex import LabelitIndex
try:
indexer = LabelitIndex()
except NotAvailableError:
pytest.skip("labelit not found")
indexer.set_beam_search_scope(4.0)
for image in (1, 45):
indexer.add_image(template % image)
indexer.run()
print(''.join(indexer.get_all_output()))
assert indexer.get_mosflm_beam_centre() == pytest.approx((94.35, 94.52),
abs=1e-1)
assert indexer.get_mosflm_detector_distance() == pytest.approx(159.8,
abs=1e-1)
solutions = indexer.get_solutions()
assert len(solutions) == 22
assert solutions[22]['cell'] == pytest.approx(
[78.6, 78.6, 78.6, 90, 90, 90], abs=1e-1)
assert solutions[22]['lattice'] == 'cI'
assert solutions[22]['rmsd'] <= 0.12
assert solutions[22]['metric'] <= 0.1243
assert solutions[22]['smiley'] == ':) '
assert solutions[22]['number'] == 22
assert solutions[22]['mosaic'] <= 0.2
assert solutions[22]['nspots'] == pytest.approx(563, abs=30)
def test_indexing_with_labelit_on_multiple_images(xia2_regression_build,
tmpdir):
template = os.path.join(xia2_regression_build, "test_data", "insulin",
"insulin_1_%03i.img")
tmpdir.chdir()
from xia2.DriverExceptions.NotAvailableError import NotAvailableError
from xia2.Wrappers.Labelit.LabelitIndex import LabelitIndex
try:
indexer = LabelitIndex()
except NotAvailableError:
pytest.skip("labelit not found")
for image in (1, 22, 45):
indexer.add_image(template % image)
indexer.set_distance(160)
indexer.set_beam_centre((94.24, 94.52))
indexer.set_wavelength(0.98)
indexer.set_refine_beam(False)
indexer.run()
print(''.join(indexer.get_all_output()))
assert indexer.get_mosflm_beam_centre() == pytest.approx((94.35, 94.49),
abs=4e-2)
assert indexer.get_mosflm_detector_distance() == pytest.approx(159.75,
abs=1e-1)
solutions = indexer.get_solutions()
assert len(solutions) == 22
assert solutions[22]['cell'] == pytest.approx(
[78.61, 78.61, 78.61, 90, 90, 90], abs=5e-2)
assert solutions[22]['lattice'] == 'cI'
assert solutions[22]['rmsd'] <= 0.16
assert solutions[22]['metric'] <= 0.18
assert solutions[22]['smiley'] == ':) '
assert solutions[22]['number'] == 22
assert solutions[22]['mosaic'] <= 0.12
assert solutions[22]['nspots'] == pytest.approx(
823, abs=41) # XXX quite a big difference!
def exercise_labelit_index():
if not have_dials_regression:
print "Skipping exercise_labelit_index(): 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_%03i.img")
from xia2.Wrappers.Labelit.LabelitIndex import LabelitIndex
# exercise basic indexing from two images
cwd = os.path.abspath(os.curdir)
tmp_dir = open_tmp_directory()
os.chdir(tmp_dir)
from xia2.DriverExceptions.NotAvailableError import NotAvailableError
try:
indexer = LabelitIndex()
except NotAvailableError:
print "Skipping exercise_labelit_index(): labelit not found"
return
indexer.set_beam_search_scope(4.0)
indexer.add_image(template % 1)
indexer.add_image(template % 45)
indexer.run()
output = "".join(indexer.get_all_output())
print output
assert approx_equal(indexer.get_mosflm_beam_centre(), (94.35, 94.52), eps=1e-1)
assert approx_equal(indexer.get_mosflm_detector_distance(), 159.8, eps=1e-1)
solutions = indexer.get_solutions()
assert len(solutions) == 22
assert approx_equal(solutions[22]["cell"], [78.6, 78.6, 78.6, 90, 90, 90], eps=2e-2)
assert solutions[22]["lattice"] == "cI"
assert solutions[22]["rmsd"] <= 0.076
assert solutions[22]["metric"] <= 0.1243
assert solutions[22]["smiley"] == ":) "
assert solutions[22]["number"] == 22
assert solutions[22]["mosaic"] == 0.05
assert abs(solutions[22]["nspots"] - 563) <= 3
# now exercise indexing off multiple images and test more settings
os.chdir(cwd)
tmp_dir = open_tmp_directory()
os.chdir(tmp_dir)
indexer = LabelitIndex()
indexer.add_image(template % 1)
indexer.add_image(template % 22)
indexer.add_image(template % 45)
indexer.set_distance(160)
indexer.set_beam_centre((94.24, 94.52))
indexer.set_wavelength(0.98)
indexer.set_refine_beam(False)
indexer.run()
output = "".join(indexer.get_all_output())
print output
assert approx_equal(indexer.get_mosflm_beam_centre(), (94.35, 94.49), eps=4e-2)
assert approx_equal(indexer.get_mosflm_detector_distance(), 159.75, eps=1e-1)
solutions = indexer.get_solutions()
assert len(solutions) == 22
assert approx_equal(solutions[22]["cell"], [78.61, 78.61, 78.61, 90, 90, 90], eps=5e-2)
assert solutions[22]["lattice"] == "cI"
assert solutions[22]["rmsd"] <= 0.084
assert solutions[22]["metric"] <= 0.1663
assert solutions[22]["smiley"] == ":) "
assert solutions[22]["number"] == 22
assert solutions[22]["mosaic"] == 0.025
assert abs(solutions[22]["nspots"] - 823) <= 41 # XXX quite a big difference!
