def run_indexing(datablock, strong_spots, crystal_model, rmsds):
cwd = os.path.abspath(os.curdir)
tmp_dir = os.path.abspath(open_tmp_directory(suffix="test_dials_index"))
os.chdir(tmp_dir)
sweep_path = os.path.join(tmp_dir, "datablock.json")
pickle_path = os.path.join(tmp_dir, "strong.pickle")
dump.datablock(datablock, sweep_path)
easy_pickle.dump(pickle_path, strong_spots)
from dials.test.algorithms.indexing.tst_index import run_one_indexing
space_group_info = crystal_model.get_space_group()
symmetry = crystal.symmetry(unit_cell=crystal_model.get_unit_cell(),
space_group=crystal_model.get_space_group())
expected_rmsds = [1.1*r for r in rmsds]
imageset = datablock[0].extract_imagesets()[0]
pixel_size = imageset.get_detector()[0].get_pixel_size()
phi_width = imageset.get_scan().get_oscillation()[1] * math.pi/180
expected_rmsds = [1.1 * rmsds[0] * pixel_size[0],
1.1 * rmsds[1] * pixel_size[1],
1.1 * rmsds[2] * phi_width]
run_one_indexing(pickle_path=pickle_path, sweep_path=sweep_path,
extra_args=[],
expected_unit_cell=symmetry.minimum_cell().unit_cell(),
expected_rmsds=expected_rmsds,
#expected_hall_symbol=crystal_model.get_space_group().type().hall_symbol(),
expected_hall_symbol=' P 1',
)
def run_indexing(datablock, strong_spots, crystal_model, rmsds):
cwd = os.path.abspath(os.curdir)
tmp_dir = os.path.abspath(open_tmp_directory(suffix="test_dials_index"))
os.chdir(tmp_dir)
sweep_path = os.path.join(tmp_dir, "datablock.json")
pickle_path = os.path.join(tmp_dir, "strong.pickle")
dump.datablock(datablock, sweep_path)
easy_pickle.dump(pickle_path, strong_spots)
from dials.test.algorithms.indexing.tst_index import run_one_indexing
space_group_info = crystal_model.get_space_group()
symmetry = crystal.symmetry(unit_cell=crystal_model.get_unit_cell(),
space_group=crystal_model.get_space_group())
expected_rmsds = [1.1 * r for r in rmsds]
imageset = datablock[0].extract_imagesets()[0]
pixel_size = imageset.get_detector()[0].get_pixel_size()
phi_width = imageset.get_scan().get_oscillation()[1] * math.pi / 180
expected_rmsds = [
1.1 * rmsds[0] * pixel_size[0], 1.1 * rmsds[1] * pixel_size[1],
1.1 * rmsds[2] * phi_width
]
run_one_indexing(
pickle_path=pickle_path,
sweep_path=sweep_path,
extra_args=[],
expected_unit_cell=symmetry.minimum_cell().unit_cell(),
expected_rmsds=expected_rmsds,
#expected_hall_symbol=crystal_model.get_space_group().type().hall_symbol(),
expected_hall_symbol=' P 1',
)
def exercise_2():
from dials.test.algorithms.indexing.tst_index import run_one_indexing
if not have_xia2_regression:
print "Skipping exercise_2(): xia2_regression not available."
return
curdir = os.path.abspath(os.curdir)
print curdir
data_dir = os.path.join(xia2_regression, "test_data", "i04_bag_training")
import glob
g = glob.glob(os.path.join(data_dir, "*.cbf*"))
if len(g) == 0:
print "Skipping exercise_2(): xia2_regression files not downloaded."
print "Run xia2_regression.fetch_test_data first."
return
# beam centre from image headers: 205.28,210.76 mm
args = ["dials.import", "mosflm_beam_centre=207,212"] + g
command = " ".join(args)
#print command
result = easy_run.fully_buffered(command=command).raise_if_errors()
assert os.path.exists('datablock.json')
# spot-finding, just need a subset of the data
args = [
"dials.find_spots", "datablock.json", "scan_range=1,10",
"scan_range=531,540"
]
command = " ".join(args)
print command
result = easy_run.fully_buffered(command=command).raise_if_errors()
assert os.path.exists('strong.pickle')
# actually run the beam centre search
args = [
"dials.discover_better_experimental_model", "datablock.json",
"strong.pickle"
]
command = " ".join(args)
print command
result = easy_run.fully_buffered(command=command).raise_if_errors()
result.show_stdout()
assert os.path.exists('optimized_datablock.json')
# look at the results
from dxtbx.serialize import load
datablocks = load.datablock("datablock.json", check_format=False)
original_imageset = datablocks[0].extract_imagesets()[0]
optimized_datablock = load.datablock('optimized_datablock.json',
check_format=False)
detector_1 = original_imageset.get_detector()
detector_2 = optimized_datablock[0].unique_detectors()[0]
shift = (matrix.col(detector_1[0].get_origin()) -
matrix.col(detector_2[0].get_origin()))
print shift
# check we can actually index the resulting optimized datablock
from cctbx import uctbx
expected_unit_cell = uctbx.unit_cell(
(57.780, 57.800, 150.017, 89.991, 89.990, 90.007))
expected_rmsds = (0.06, 0.05, 0.001)
expected_hall_symbol = ' P 1'
result = run_one_indexing(os.path.join(curdir, 'strong.pickle'),
os.path.join(curdir, 'optimized_datablock.json'),
[], expected_unit_cell, expected_rmsds,
expected_hall_symbol)
def exercise_2():
from dials.test.algorithms.indexing.tst_index import run_one_indexing
if not have_xia2_regression:
print "Skipping exercise_2(): xia2_regression not available."
return
curdir = os.path.abspath(os.curdir)
print curdir
data_dir = os.path.join(xia2_regression, "test_data", "i04_bag_training")
import glob
g = glob.glob(os.path.join(data_dir, "*.cbf"))
if len(g) == 0:
print "Skipping exercise_2(): xia2_regression files not downloaded."
print "Run xia2_regression.fetch_test_data first."
return
# beam centre from image headers: 205.28,210.76 mm
args = ["dials.import", "mosflm_beam_centre=207,212"] + g
command = " ".join(args)
# print command
result = easy_run.fully_buffered(command=command).raise_if_errors()
assert os.path.exists("datablock.json")
# spot-finding, just need a subset of the data
args = ["dials.find_spots", "datablock.json", "scan_range=1,10", "scan_range=531,540"]
command = " ".join(args)
print command
result = easy_run.fully_buffered(command=command).raise_if_errors()
assert os.path.exists("strong.pickle")
# actually run the beam centre search
args = ["dials.discover_better_experimental_model", "datablock.json", "strong.pickle"]
command = " ".join(args)
print command
result = easy_run.fully_buffered(command=command).raise_if_errors()
result.show_stdout()
assert os.path.exists("optimized_datablock.json")
# look at the results
from dxtbx.serialize import load
datablocks = load.datablock("datablock.json", check_format=False)
original_imageset = datablocks[0].extract_imagesets()[0]
optimized_datablock = load.datablock("optimized_datablock.json", check_format=False)
detector_1 = original_imageset.get_detector()
detector_2 = optimized_datablock[0].unique_detectors()[0]
shift = matrix.col(detector_1[0].get_origin()) - matrix.col(detector_2[0].get_origin())
print shift
# check we can actually index the resulting optimized datablock
from cctbx import uctbx
expected_unit_cell = uctbx.unit_cell((57.780, 57.800, 150.017, 89.991, 89.990, 90.007))
expected_rmsds = (0.06, 0.05, 0.001)
expected_hall_symbol = " P 1"
result = run_one_indexing(
os.path.join(curdir, "strong.pickle"),
os.path.join(curdir, "optimized_datablock.json"),
[],
expected_unit_cell,
expected_rmsds,
expected_hall_symbol,
)
def run():
have_dials_regression = libtbx.env.has_module("dials_regression")
if not have_dials_regression:
print "Skipped: dials_regression not available"
return
dials_regression = libtbx.env.find_in_repositories(
relative_path="dials_regression", test=os.path.isdir)
from dials.test.algorithms.indexing.tst_index import run_one_indexing
expected_unit_cell = uctbx.unit_cell(
(11.624, 13.550, 30.103, 89.964, 93.721, 90.132))
expected_rmsds = (0.039, 0.035, 0.002)
datablock_old = os.path.join(
dials_regression, "indexing_test_data/phi_scan/datablock_old.json")
datablock_new = os.path.join(dials_regression,
"indexing_test_data/phi_scan/datablock.json")
strong_pickle = os.path.join(dials_regression,
"indexing_test_data/phi_scan/strong.pickle")
from dxtbx.serialize import load
imageset_old = load.datablock(datablock_old,
check_format=False)[0].extract_imagesets()[0]
imageset_new = load.datablock(datablock_new,
check_format=False)[0].extract_imagesets()[0]
gonio_old = imageset_old.get_goniometer()
gonio_new = imageset_new.get_goniometer()
assert approx_equal(
gonio_old.get_rotation_axis(),
(0.7497646259807715, -0.5517923303436749, 0.36520984351713554))
assert approx_equal(gonio_old.get_setting_rotation(),
(1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0))
assert approx_equal(
gonio_old.get_fixed_rotation(),
(0.7497646259807748, -0.20997265900532208, -0.6275065641872948,
-0.5517923303436731, 0.3250014637526764, -0.7680490041218182,
0.3652098435171313, 0.9221092836691605, 0.12781329809272568))
assert approx_equal(gonio_new.get_rotation_axis(),
gonio_old.get_rotation_axis())
assert approx_equal(gonio_new.get_rotation_axis_datum(), (1, 0, 0))
assert approx_equal(
gonio_new.get_setting_rotation(),
(0.7497646259807705, -0.20997265900532142, -0.6275065641873,
-0.5517923303436786, 0.3250014637526763, -0.768049004121814,
0.3652098435171315, 0.9221092836691607, 0.12781329809272335))
assert approx_equal(gonio_new.get_fixed_rotation(),
(1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0))
result_old = run_one_indexing(
pickle_path=strong_pickle,
sweep_path=datablock_old,
extra_args=[],
expected_unit_cell=expected_unit_cell,
expected_rmsds=expected_rmsds,
expected_hall_symbol=' P 1',
)
result_new = run_one_indexing(
pickle_path=strong_pickle,
sweep_path=datablock_new,
extra_args=[],
expected_unit_cell=expected_unit_cell,
expected_rmsds=expected_rmsds,
expected_hall_symbol=' P 1',
)
assert approx_equal(result_old.rmsds, result_new.rmsds)
assert approx_equal(result_old.crystal_model.get_unit_cell().parameters(),
result_new.crystal_model.get_unit_cell().parameters())
# Now test refinement gradients are correct
from dxtbx.model.experiment_list import ExperimentList, Experiment
old_exps = ExperimentList([
Experiment(beam=imageset_old.get_beam(),
detector=imageset_old.get_detector(),
goniometer=gonio_old,
scan=imageset_old.get_scan(),
crystal=result_old.crystal_model,
imageset=None)
])
new_exps = ExperimentList([
Experiment(beam=imageset_new.get_beam(),
detector=imageset_new.get_detector(),
goniometer=gonio_new,
scan=imageset_new.get_scan(),
crystal=result_new.crystal_model,
imageset=None)
])
from libtbx.phil import parse
from dials.algorithms.refinement.refiner import phil_scope
params = phil_scope.fetch(source=parse('')).extract()
from dials.algorithms.refinement.refiner import RefinerFactory
refiner_old = RefinerFactory.from_parameters_data_experiments(
params, result_old.indexed_reflections, old_exps, verbosity=0)
refiner_new = RefinerFactory.from_parameters_data_experiments(
params, result_new.indexed_reflections, new_exps, verbosity=0)
# Analytical gradients should be approximately the same in either case
an_grads_old = refiner_old._pred_param.get_gradients(
refiner_old.get_matches())
an_grads_new = refiner_new._pred_param.get_gradients(
refiner_new.get_matches())
for g1, g2 in zip(an_grads_old, an_grads_new):
assert approx_equal(g1["dX_dp"], g2["dX_dp"], eps=1.e-6)
assert approx_equal(g1["dY_dp"], g2["dY_dp"], eps=1.e-6)
assert approx_equal(g1["dphi_dp"], g2["dphi_dp"], eps=1.e-6)
# Analytical gradients should be approximately equal to finite difference
# gradients in either case
fd_grads_old = calc_fd_grads(refiner_old)
for g1, g2 in zip(fd_grads_old, an_grads_old):
assert approx_equal(g1["dX_dp"], g2["dX_dp"], eps=5.e-6)
assert approx_equal(g1["dY_dp"], g2["dY_dp"], eps=5.e-6)
assert approx_equal(g1["dphi_dp"], g2["dphi_dp"], eps=5.e-6)
fd_grads_new = calc_fd_grads(refiner_new)
for g1, g2 in zip(fd_grads_new, an_grads_new):
assert approx_equal(g1["dX_dp"], g2["dX_dp"], eps=5.e-6)
assert approx_equal(g1["dY_dp"], g2["dY_dp"], eps=5.e-6)
assert approx_equal(g1["dphi_dp"], g2["dphi_dp"], eps=5.e-6)
def run():
have_dials_regression = libtbx.env.has_module("dials_regression")
if not have_dials_regression:
print "Skipped: dials_regression not available"
return
dials_regression = libtbx.env.find_in_repositories(
relative_path="dials_regression", test=os.path.isdir)
from dials.test.algorithms.indexing.tst_index import run_one_indexing
expected_unit_cell = uctbx.unit_cell(
(11.624, 13.550, 30.103, 89.964, 93.721, 90.132))
expected_rmsds = (0.028, 0.031, 0.094)
datablock_old = os.path.join(
dials_regression, "indexing_test_data/phi_scan/datablock_old.json")
datablock_new = os.path.join(dials_regression,
"indexing_test_data/phi_scan/datablock.json")
strong_pickle = os.path.join(dials_regression,
"indexing_test_data/phi_scan/strong.pickle")
from dxtbx.serialize import load
imageset_old = load.datablock(datablock_old,
check_format=False)[0].extract_imagesets()[0]
imageset_new = load.datablock(datablock_new,
check_format=False)[0].extract_imagesets()[0]
gonio_old = imageset_old.get_goniometer()
gonio_new = imageset_new.get_goniometer()
assert approx_equal(
gonio_old.get_rotation_axis(),
(0.7497646259807715, -0.5517923303436749, 0.36520984351713554))
assert approx_equal(gonio_old.get_setting_rotation(),
(1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0))
assert approx_equal(
gonio_old.get_fixed_rotation(),
(0.7497646259807748, -0.20997265900532208, -0.6275065641872948,
-0.5517923303436731, 0.3250014637526764, -0.7680490041218182,
0.3652098435171313, 0.9221092836691605, 0.12781329809272568))
assert approx_equal(gonio_new.get_rotation_axis(),
gonio_old.get_rotation_axis())
assert approx_equal(gonio_new.get_rotation_axis_datum(), (1, 0, 0))
assert approx_equal(
gonio_new.get_setting_rotation(),
(0.7497646259807705, -0.20997265900532142, -0.6275065641873,
-0.5517923303436786, 0.3250014637526763, -0.768049004121814,
0.3652098435171315, 0.9221092836691607, 0.12781329809272335))
assert approx_equal(gonio_new.get_fixed_rotation(),
(1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0))
result_old = run_one_indexing(
pickle_path=strong_pickle,
sweep_path=datablock_old,
extra_args=[],
expected_unit_cell=expected_unit_cell,
expected_rmsds=expected_rmsds,
expected_hall_symbol=' P 1',
)
result_new = run_one_indexing(
pickle_path=strong_pickle,
sweep_path=datablock_new,
extra_args=[],
expected_unit_cell=expected_unit_cell,
expected_rmsds=expected_rmsds,
expected_hall_symbol=' P 1',
)
assert approx_equal(result_old.rmsds, result_new.rmsds)
assert approx_equal(result_old.crystal_model.get_unit_cell().parameters(),
result_new.crystal_model.get_unit_cell().parameters())
def run():
have_dials_regression = libtbx.env.has_module("dials_regression")
if not have_dials_regression:
print "Skipped: dials_regression not available"
return
dials_regression = libtbx.env.find_in_repositories(
relative_path="dials_regression",
test=os.path.isdir)
from dials.test.algorithms.indexing.tst_index import run_one_indexing
expected_unit_cell = uctbx.unit_cell(
(11.624, 13.550, 30.103, 89.964, 93.721, 90.132))
expected_rmsds = (0.039, 0.035, 0.002)
datablock_old = os.path.join(
dials_regression, "indexing_test_data/phi_scan/datablock_old.json")
datablock_new = os.path.join(
dials_regression, "indexing_test_data/phi_scan/datablock.json")
strong_pickle = os.path.join(
dials_regression, "indexing_test_data/phi_scan/strong.pickle")
from dxtbx.serialize import load
imageset_old = load.datablock(
datablock_old, check_format=False)[0].extract_imagesets()[0]
imageset_new = load.datablock(
datablock_new, check_format=False)[0].extract_imagesets()[0]
gonio_old = imageset_old.get_goniometer()
gonio_new = imageset_new.get_goniometer()
assert approx_equal(
gonio_old.get_rotation_axis(),
(0.7497646259807715, -0.5517923303436749, 0.36520984351713554))
assert approx_equal(
gonio_old.get_setting_rotation(),
(1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0))
assert approx_equal(
gonio_old.get_fixed_rotation(),
(0.7497646259807748, -0.20997265900532208, -0.6275065641872948,
-0.5517923303436731, 0.3250014637526764, -0.7680490041218182,
0.3652098435171313, 0.9221092836691605, 0.12781329809272568))
assert approx_equal(
gonio_new.get_rotation_axis(), gonio_old.get_rotation_axis())
assert approx_equal(gonio_new.get_rotation_axis_datum(), (1,0,0))
assert approx_equal(
gonio_new.get_setting_rotation(),
(0.7497646259807705, -0.20997265900532142, -0.6275065641873,
-0.5517923303436786, 0.3250014637526763, -0.768049004121814,
0.3652098435171315, 0.9221092836691607, 0.12781329809272335))
assert approx_equal(
gonio_new.get_fixed_rotation(),
(1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0))
result_old = run_one_indexing(
pickle_path=strong_pickle, sweep_path=datablock_old,
extra_args=[],
expected_unit_cell=expected_unit_cell,
expected_rmsds=expected_rmsds,
expected_hall_symbol=' P 1',
)
result_new = run_one_indexing(
pickle_path=strong_pickle, sweep_path=datablock_new,
extra_args=[],
expected_unit_cell=expected_unit_cell,
expected_rmsds=expected_rmsds,
expected_hall_symbol=' P 1',
)
assert approx_equal(result_old.rmsds, result_new.rmsds)
assert approx_equal(result_old.crystal_model.get_unit_cell().parameters(),
result_new.crystal_model.get_unit_cell().parameters())
