def test_check_old_vs_new():
from dxtbx.tests.model.crystal_model_old import crystal_model_old
model_1 = Crystal(
real_space_a=(10, 0, 0),
real_space_b=(0, 11, 0),
real_space_c=(0, 0, 12),
space_group_symbol="P 1",
)
model_2 = crystal_model_old(
real_space_a=(10, 0, 0),
real_space_b=(0, 11, 0),
real_space_c=(0, 0, 12),
space_group_symbol="P 1",
)
cov_B = matrix.sqr([1] * (9 * 9))
model_1.set_B_covariance(cov_B)
model_2.set_B_covariance(cov_B)
A_list = [model_1.get_A() for i in range(20)]
model_1.set_A_at_scan_points(A_list)
model_2.set_A_at_scan_points(A_list)
A1 = model_1.get_A()
A2 = model_2.get_A()
U1 = model_1.get_U()
U2 = model_2.get_U()
B1 = model_1.get_B()
B2 = model_2.get_B()
UC1 = model_1.get_unit_cell()
UC2 = model_2.get_unit_cell()
RSV1 = model_1.get_real_space_vectors()
RSV2 = model_2.get_real_space_vectors()
SG1 = model_1.get_space_group()
SG2 = model_2.get_space_group()
assert model_1.num_scan_points == model_2.num_scan_points
A_list_1 = [
model_1.get_A_at_scan_point(i)
for i in range(model_1.get_num_scan_points())
]
A_list_2 = [
model_2.get_A_at_scan_point(i)
for i in range(model_1.get_num_scan_points())
]
B_list_1 = [
model_1.get_B_at_scan_point(i)
for i in range(model_1.get_num_scan_points())
]
B_list_2 = [
model_2.get_B_at_scan_point(i)
for i in range(model_1.get_num_scan_points())
]
U_list_1 = [
model_1.get_U_at_scan_point(i)
for i in range(model_1.get_num_scan_points())
]
U_list_2 = [
model_2.get_U_at_scan_point(i)
for i in range(model_1.get_num_scan_points())
]
assert approx_equal(A1, A2)
assert approx_equal(B1, B2)
assert approx_equal(U1, U2)
assert approx_equal(UC1.parameters(), UC2.parameters())
assert approx_equal(RSV1[0], RSV2[0])
assert approx_equal(RSV1[1], RSV2[1])
assert approx_equal(RSV1[2], RSV2[2])
assert str(SG1.info()) == str(SG2.info())
for i in range(model_1.get_num_scan_points()):
assert approx_equal(A_list_1[i], A_list_2[i])
assert approx_equal(B_list_1[i], B_list_2[i])
assert approx_equal(U_list_1[i], U_list_2[i])
cell_sd_1 = model_1.get_cell_parameter_sd()
cell_sd_2 = model_2.get_cell_parameter_sd()
cell_volume_sd_1 = model_1.get_cell_volume_sd()
cell_volume_sd_2 = model_2.get_cell_volume_sd()
covB1 = model_1.get_B_covariance()
covB2 = model_1.get_B_covariance()
assert approx_equal(covB1, covB2)
assert approx_equal(cell_volume_sd_1, cell_volume_sd_2)
assert approx_equal(cell_sd_1, cell_sd_2)
def test_crystal_model():
real_space_a = matrix.col((10, 0, 0))
real_space_b = matrix.col((0, 11, 0))
real_space_c = matrix.col((0, 0, 12))
model = Crystal(
real_space_a=(10, 0, 0),
real_space_b=(0, 11, 0),
real_space_c=(0, 0, 12),
space_group_symbol="P 1",
)
# This doesn't work as python class uctbx.unit_cell(uctbx_ext.unit_cell)
# so C++ and python classes are different types
# assert isinstance(model.get_unit_cell(), uctbx.unit_cell)
assert model.get_unit_cell().parameters() == (10.0, 11.0, 12.0, 90.0, 90.0,
90.0)
assert approx_equal(model.get_A(),
(1 / 10, 0, 0, 0, 1 / 11, 0, 0, 0, 1 / 12))
assert approx_equal(
matrix.sqr(model.get_A()).inverse(), (10, 0, 0, 0, 11, 0, 0, 0, 12))
assert approx_equal(model.get_B(), model.get_A())
assert approx_equal(model.get_U(), (1, 0, 0, 0, 1, 0, 0, 0, 1))
assert approx_equal(model.get_real_space_vectors(),
(real_space_a, real_space_b, real_space_c))
assert (model.get_crystal_symmetry().unit_cell().parameters() ==
model.get_unit_cell().parameters())
assert model.get_crystal_symmetry().space_group() == model.get_space_group(
)
model2 = Crystal(
real_space_a=(10, 0, 0),
real_space_b=(0, 11, 0),
real_space_c=(0, 0, 12),
space_group_symbol="P 1",
)
assert model == model2
model2a = Crystal(model.get_A(), model.get_space_group())
assert model == model2a
model2b = Crystal(
matrix.sqr(model.get_A()).inverse().elems,
model.get_space_group().type().lookup_symbol(),
reciprocal=False,
)
assert model == model2b
# rotate 45 degrees about x-axis
R1 = matrix.sqr((
1,
0,
0,
0,
math.cos(math.pi / 4),
-math.sin(math.pi / 4),
0,
math.sin(math.pi / 4),
math.cos(math.pi / 4),
))
# rotate 30 degrees about y-axis
R2 = matrix.sqr((
math.cos(math.pi / 6),
0,
math.sin(math.pi / 6),
0,
1,
0,
-math.sin(math.pi / 6),
0,
math.cos(math.pi / 6),
))
# rotate 60 degrees about z-axis
R3 = matrix.sqr((
math.cos(math.pi / 3),
-math.sin(math.pi / 3),
0,
math.sin(math.pi / 3),
math.cos(math.pi / 3),
0,
0,
0,
1,
))
R = R1 * R2 * R3
model.set_U(R)
# B is unchanged
assert approx_equal(model.get_B(),
(1 / 10, 0, 0, 0, 1 / 11, 0, 0, 0, 1 / 12))
assert approx_equal(model.get_U(), R)
assert approx_equal(model.get_A(),
matrix.sqr(model.get_U()) * matrix.sqr(model.get_B()))
a_, b_, c_ = model.get_real_space_vectors()
assert approx_equal(a_, R * real_space_a)
assert approx_equal(b_, R * real_space_b)
assert approx_equal(c_, R * real_space_c)
assert (str(model).replace("-0.0000", " 0.0000") == """\
Crystal:
Unit cell: (10.000, 11.000, 12.000, 90.000, 90.000, 90.000)
Space group: P 1
U matrix: {{ 0.4330, -0.7500, 0.5000},
{ 0.7891, 0.0474, -0.6124},
{ 0.4356, 0.6597, 0.6124}}
B matrix: {{ 0.1000, 0.0000, 0.0000},
{ 0.0000, 0.0909, 0.0000},
{ 0.0000, 0.0000, 0.0833}}
A = UB: {{ 0.0433, -0.0682, 0.0417},
{ 0.0789, 0.0043, -0.0510},
{ 0.0436, 0.0600, 0.0510}}
""")
model.set_B((1 / 12, 0, 0, 0, 1 / 12, 0, 0, 0, 1 / 12))
assert approx_equal(model.get_unit_cell().parameters(),
(12, 12, 12, 90, 90, 90))
U = matrix.sqr((0.3455, -0.2589, -0.9020, 0.8914, 0.3909, 0.2293, 0.2933,
-0.8833, 0.3658))
B = matrix.sqr((1 / 13, 0, 0, 0, 1 / 13, 0, 0, 0, 1 / 13))
model.set_A(U * B)
assert approx_equal(model.get_A(), U * B)
assert approx_equal(model.get_U(), U, 1e-4)
assert approx_equal(model.get_B(), B, 1e-5)
model3 = Crystal(
real_space_a=(10, 0, 0),
real_space_b=(0, 11, 0),
real_space_c=(0, 0, 12),
space_group=sgtbx.space_group_info("P 222").group(),
)
assert model3.get_space_group().type().hall_symbol() == " P 2 2"
assert model != model3
#
sgi_ref = sgtbx.space_group_info(number=230)
model_ref = Crystal(
real_space_a=(44, 0, 0),
real_space_b=(0, 44, 0),
real_space_c=(0, 0, 44),
space_group=sgi_ref.group(),
)
assert approx_equal(model_ref.get_U(), (1, 0, 0, 0, 1, 0, 0, 0, 1))
assert approx_equal(model_ref.get_B(),
(1 / 44, 0, 0, 0, 1 / 44, 0, 0, 0, 1 / 44))
assert approx_equal(model_ref.get_A(), model_ref.get_B())
assert approx_equal(model_ref.get_unit_cell().parameters(),
(44, 44, 44, 90, 90, 90))
a_ref, b_ref, c_ref = map(matrix.col, model_ref.get_real_space_vectors())
cb_op_to_primitive = sgi_ref.change_of_basis_op_to_primitive_setting()
model_primitive = model_ref.change_basis(cb_op_to_primitive)
cb_op_to_reference = (model_primitive.get_space_group().info().
change_of_basis_op_to_reference_setting())
a_prim, b_prim, c_prim = map(matrix.col,
model_primitive.get_real_space_vectors())
assert (cb_op_to_primitive.as_abc() ==
"-1/2*a+1/2*b+1/2*c,1/2*a-1/2*b+1/2*c,1/2*a+1/2*b-1/2*c")
assert approx_equal(a_prim, -1 / 2 * a_ref + 1 / 2 * b_ref + 1 / 2 * c_ref)
assert approx_equal(b_prim, 1 / 2 * a_ref - 1 / 2 * b_ref + 1 / 2 * c_ref)
assert approx_equal(c_prim, 1 / 2 * a_ref + 1 / 2 * b_ref - 1 / 2 * c_ref)
assert cb_op_to_reference.as_abc() == "b+c,a+c,a+b"
assert approx_equal(a_ref, b_prim + c_prim)
assert approx_equal(b_ref, a_prim + c_prim)
assert approx_equal(c_ref, a_prim + b_prim)
assert approx_equal(
model_primitive.get_U(),
[
-0.5773502691896258,
0.40824829046386285,
0.7071067811865476,
0.5773502691896257,
-0.4082482904638631,
0.7071067811865476,
0.5773502691896257,
0.8164965809277259,
0.0,
],
)
assert approx_equal(
model_primitive.get_B(),
[
0.0262431940540739,
0.0,
0.0,
0.00927837023781507,
0.02783511071344521,
0.0,
0.01607060866333063,
0.01607060866333063,
0.03214121732666125,
],
)
assert approx_equal(
model_primitive.get_A(),
(0, 1 / 44, 1 / 44, 1 / 44, 0, 1 / 44, 1 / 44, 1 / 44, 0),
)
assert approx_equal(
model_primitive.get_unit_cell().parameters(),
[
38.1051177665153,
38.1051177665153,
38.1051177665153,
109.47122063449069,
109.47122063449069,
109.47122063449069,
],
)
assert model_ref != model_primitive
model_ref_recycled = model_primitive.change_basis(cb_op_to_reference)
assert approx_equal(model_ref.get_U(), model_ref_recycled.get_U())
assert approx_equal(model_ref.get_B(), model_ref_recycled.get_B())
assert approx_equal(model_ref.get_A(), model_ref_recycled.get_A())
assert approx_equal(
model_ref.get_unit_cell().parameters(),
model_ref_recycled.get_unit_cell().parameters(),
)
assert model_ref == model_ref_recycled
uc = uctbx.unit_cell(
(58.2567, 58.1264, 39.7093, 46.9077, 46.8612, 62.1055))
sg = sgtbx.space_group_info(symbol="P1").group()
cs = crystal.symmetry(unit_cell=uc, space_group=sg)
cb_op_to_minimum = cs.change_of_basis_op_to_minimum_cell()
# the reciprocal matrix
B = matrix.sqr(uc.fractionalization_matrix()).transpose()
U = random_rotation()
direct_matrix = (U * B).inverse()
model = Crystal(direct_matrix[:3],
direct_matrix[3:6],
direct_matrix[6:9],
space_group=sg)
assert uc.is_similar_to(model.get_unit_cell())
uc_minimum = uc.change_basis(cb_op_to_minimum)
model_minimum = model.change_basis(cb_op_to_minimum)
assert uc_minimum.is_similar_to(model_minimum.get_unit_cell())
assert model_minimum != model
model_minimum.update(model)
assert model_minimum == model # lgtm
A_static = matrix.sqr(model.get_A())
A_as_scan_points = [A_static]
num_scan_points = 11
for i in range(num_scan_points - 1):
A_as_scan_points.append(
A_as_scan_points[-1] *
matrix.sqr(euler_angles.xyz_matrix(0.1, 0.2, 0.3)))
model.set_A_at_scan_points(A_as_scan_points)
model_minimum = model.change_basis(cb_op_to_minimum)
assert model.num_scan_points == model_minimum.num_scan_points == num_scan_points
M = matrix.sqr(cb_op_to_minimum.c_inv().r().transpose().as_double())
M_inv = M.inverse()
for i in range(num_scan_points):
A_orig = matrix.sqr(model.get_A_at_scan_point(i))
A_min = matrix.sqr(model_minimum.get_A_at_scan_point(i))
assert approx_equal(A_min, A_orig * M_inv)
assert model.get_unit_cell().parameters() == pytest.approx(
(58.2567, 58.1264, 39.7093, 46.9077, 46.8612, 62.1055))
uc = uctbx.unit_cell((10, 11, 12, 91, 92, 93))
model.set_unit_cell(uc)
assert model.get_unit_cell().parameters() == pytest.approx(uc.parameters())
def dump(experiments, directory):
"""
Dump the experiments in mosflm format
:param experiments: The experiments to dump
:param directory: The directory to write to
"""
for i, experiment in enumerate(experiments):
suffix = ""
if len(experiments) > 1:
suffix = "_%i" % (i + 1)
sub_dir = "%s%s" % (directory, suffix)
if not os.path.isdir(sub_dir):
os.makedirs(sub_dir)
detector = experiment.detector
beam = experiment.beam
goniometer = experiment.goniometer
# XXX imageset is getting the experimental geometry from the image files
# rather than the input models.expt file
imageset = experiment.imageset
R_to_mosflm = align_reference_frame(
beam.get_s0(),
(1.0, 0.0, 0.0),
goniometer.get_rotation_axis(),
(0.0, 0.0, 1.0),
)
cryst = experiment.crystal
cryst = cryst.change_basis(cryst.get_space_group().info().
change_of_basis_op_to_reference_setting())
A = matrix.sqr(cryst.get_A())
A_inv = A.inverse()
real_space_a = R_to_mosflm * A_inv.elems[:3]
real_space_b = R_to_mosflm * A_inv.elems[3:6]
real_space_c = R_to_mosflm * A_inv.elems[6:9]
cryst_mosflm = Crystal(
real_space_a,
real_space_b,
real_space_c,
space_group=cryst.get_space_group(),
)
A_mosflm = matrix.sqr(cryst_mosflm.get_A())
U_mosflm = matrix.sqr(cryst_mosflm.get_U())
assert U_mosflm.is_r3_rotation_matrix(), U_mosflm
w = beam.get_wavelength()
index_mat = os.path.join(sub_dir, "index.mat")
mosflm_in = os.path.join(sub_dir, "mosflm.in")
print("Exporting experiment to %s and %s" % (index_mat, mosflm_in))
with open(index_mat, "w") as f:
f.write(
format_mosflm_mat(w * A_mosflm, U_mosflm,
cryst.get_unit_cell()))
img_dir, template = os.path.split(imageset.get_template())
symmetry = cryst_mosflm.get_space_group().type().number()
beam_centre = tuple(
reversed(detector[0].get_beam_centre(beam.get_s0())))
distance = detector[0].get_directed_distance()
with open(mosflm_in, "w") as f:
f.write(
write_mosflm_input(
directory=img_dir,
template=template,
symmetry=symmetry,
beam_centre=beam_centre,
distance=distance,
mat_file="index.mat",
))
def test_refinement(dials_regression):
"""Test a refinement run"""
# Get a beam and detector from a experiments. This one has a CS-PAD, but that
# is irrelevant
data_dir = os.path.join(dials_regression, "refinement_test_data",
"hierarchy_test")
experiments_path = os.path.join(data_dir, "datablock.json")
assert os.path.exists(experiments_path)
# load models
from dxtbx.model.experiment_list import ExperimentListFactory
experiments = ExperimentListFactory.from_serialized_format(
experiments_path, check_format=False)
im_set = experiments.imagesets()[0]
detector = deepcopy(im_set.get_detector())
beam = im_set.get_beam()
# Invent a crystal, goniometer and scan for this test
from dxtbx.model import Crystal
crystal = Crystal((40.0, 0.0, 0.0), (0.0, 40.0, 0.0), (0.0, 0.0, 40.0),
space_group_symbol="P1")
orig_xl = deepcopy(crystal)
from dxtbx.model import GoniometerFactory
goniometer = GoniometerFactory.known_axis((1.0, 0.0, 0.0))
# Build a mock scan for a 180 degree sequence
from dxtbx.model import ScanFactory
sf = ScanFactory()
scan = sf.make_scan(
image_range=(1, 1800),
exposure_times=0.1,
oscillation=(0, 0.1),
epochs=list(range(1800)),
deg=True,
)
sequence_range = scan.get_oscillation_range(deg=False)
im_width = scan.get_oscillation(deg=False)[1]
assert sequence_range == (0.0, pi)
assert approx_equal(im_width, 0.1 * pi / 180.0)
# Build an experiment list
experiments = ExperimentList()
experiments.append(
Experiment(
beam=beam,
detector=detector,
goniometer=goniometer,
scan=scan,
crystal=crystal,
imageset=None,
))
# simulate some reflections
refs, _ = generate_reflections(experiments)
# change unit cell a bit (=0.1 Angstrom length upsets, 0.1 degree of
# alpha and beta angles)
from dials.algorithms.refinement.parameterisation.crystal_parameters import (
CrystalUnitCellParameterisation, )
xluc_param = CrystalUnitCellParameterisation(crystal)
cell_params = crystal.get_unit_cell().parameters()
cell_params = [
a + b for a, b in zip(cell_params, [0.1, -0.1, 0.1, 0.1, -0.1, 0.0])
]
from cctbx.uctbx import unit_cell
from rstbx.symmetry.constraints.parameter_reduction import symmetrize_reduce_enlarge
from scitbx import matrix
new_uc = unit_cell(cell_params)
newB = matrix.sqr(new_uc.fractionalization_matrix()).transpose()
S = symmetrize_reduce_enlarge(crystal.get_space_group())
S.set_orientation(orientation=newB)
X = tuple([e * 1.0e5 for e in S.forward_independent_parameters()])
xluc_param.set_param_vals(X)
# reparameterise the crystal at the perturbed geometry
xluc_param = CrystalUnitCellParameterisation(crystal)
# Dummy parameterisations for other models
beam_param = None
xlo_param = None
det_param = None
# parameterisation of the prediction equation
from dials.algorithms.refinement.parameterisation.parameter_report import (
ParameterReporter, )
pred_param = TwoThetaPredictionParameterisation(experiments, det_param,
beam_param, xlo_param,
[xluc_param])
param_reporter = ParameterReporter(det_param, beam_param, xlo_param,
[xluc_param])
# reflection manager
refman = TwoThetaReflectionManager(refs, experiments, nref_per_degree=20)
# reflection predictor
ref_predictor = TwoThetaExperimentsPredictor(experiments)
# target function
target = TwoThetaTarget(experiments, ref_predictor, refman, pred_param)
# minimisation engine
from dials.algorithms.refinement.engine import (
LevenbergMarquardtIterations as Refinery, )
refinery = Refinery(
target=target,
prediction_parameterisation=pred_param,
log=None,
max_iterations=20,
)
# Refiner
from dials.algorithms.refinement.refiner import Refiner
refiner = Refiner(
experiments=experiments,
pred_param=pred_param,
param_reporter=param_reporter,
refman=refman,
target=target,
refinery=refinery,
)
refiner.run()
# compare crystal with original crystal
refined_xl = refiner.get_experiments()[0].crystal
# print refined_xl
assert refined_xl.is_similar_to(orig_xl,
uc_rel_length_tolerance=0.001,
uc_abs_angle_tolerance=0.01)
def write_par_file(file_name, experiment):
from scitbx import matrix
from dxtbx.model import Crystal
from rstbx.cftbx.coordinate_frame_helpers import align_reference_frame
from iotbx.mtz.extract_from_symmetry_lib import ccp4_symbol
imageset = experiment.imageset
detector = imageset.get_detector()
goniometer = imageset.get_goniometer()
beam = imageset.get_beam()
scan = imageset.get_scan()
R_to_mosflm = align_reference_frame(beam.get_s0(), (1.0, 0.0, 0.0),
goniometer.get_rotation_axis(),
(0.0, 0.0, 1.0))
cryst = experiment.crystal
cryst = cryst.change_basis(
cryst.get_space_group().info()\
.change_of_basis_op_to_reference_setting())
A = matrix.sqr(cryst.get_A())
A_inv = A.inverse()
real_space_a = R_to_mosflm * A_inv.elems[:3]
real_space_b = R_to_mosflm * A_inv.elems[3:6]
real_space_c = R_to_mosflm * A_inv.elems[6:9]
cryst_mosflm = Crystal(real_space_a,
real_space_b,
real_space_c,
space_group=cryst.get_space_group())
A_mosflm = matrix.sqr(cryst_mosflm.get_A())
U_mosflm = matrix.sqr(cryst_mosflm.get_U())
B_mosflm = matrix.sqr(cryst_mosflm.get_B())
UB_mosflm = U_mosflm * B_mosflm
uc_params = cryst_mosflm.get_unit_cell().parameters()
assert U_mosflm.is_r3_rotation_matrix(), U_mosflm
symmetry = cryst_mosflm.get_space_group().type().number()
beam_centre = tuple(reversed(detector[0].get_beam_centre(beam.get_s0())))
distance = detector[0].get_directed_distance()
polarization = R_to_mosflm * matrix.col(beam.get_polarization_normal())
rotation = matrix.col(goniometer.get_rotation_axis())
if (rotation.angle(matrix.col(detector[0].get_fast_axis())) <
rotation.angle(matrix.col(detector[0].get_slow_axis()))):
direction = 'FAST'
else:
direction = 'SLOW'
rotation = R_to_mosflm * rotation
# Calculate average spot diameter for SEPARATION parameter
# http://xds.mpimf-heidelberg.mpg.de/html_doc/xds_parameters.html
# BEAM_DIVERGENCE=
# This value is approximately arctan(spot diameter/DETECTOR_DISTANCE)
import math
profile = experiment.profile
spot_diameter = math.tan(profile.delta_b() * math.pi / 180) * distance
spot_diameter_px = spot_diameter * detector[0].get_pixel_size()[0]
# determine parameters for RASTER keyword
# http://www.mrc-lmb.cam.ac.uk/harry/cgi-bin/keyword2.cgi?RASTER
# NXS, NYS (odd integers) define the overall dimensions of the rectangular array of pixels for each spot
# NXS and NYS are set to twice the spot size plus 5 pixels
nxs = 2 * int(math.ceil(spot_diameter_px)) + 5
nys = nxs
# NRX, NRY are the number of columns or rows of points in the background rim
# NRX and NRY are set to half the spot size plus 2 pixels
nrx = int(math.ceil(0.5 * spot_diameter_px)) + 2
nry = nrx
# NC the corner background cut-off which corresponds to a half-square of side NC points
# NC is set to the mean of the spot size in X and Y plus 4
nc = int(math.ceil(spot_diameter_px)) + 4
def space_group_symbol(space_group):
symbol = ccp4_symbol(space_group.info(),
lib_name='syminfo.lib',
require_at_least_one_lib=False)
if symbol != 'P 1':
symbol = symbol.replace(' 1', '')
symbol = symbol.replace(' ', '')
return symbol
logger.info('Saving BEST parameter file to %s' % file_name)
with open(file_name, 'wb') as f: #
print >> f, '# parameter file for BEST'
print >> f, 'TITLE From DIALS'
print >> f, 'DETECTOR PILA'
print >> f, 'SITE Not set'
print >> f, 'DIAMETER %6.2f' % (max(
detector[0].get_image_size()) * detector[0].get_pixel_size()[0])
print >> f, 'PIXEL %s' % detector[0].get_pixel_size()[0]
print >> f, 'ROTAXIS %4.2f %4.2f %4.2f' % rotation.elems, direction
print >> f, 'POLAXIS %4.2f %4.2f %4.2f' % polarization.elems
print >> f, 'GAIN 1.00' # correct for Pilatus images
# http://strucbio.biologie.uni-konstanz.de/xdswiki/index.php/FAQ#You_said_that_the_XDS_deals_with_high_mosaicity._How_high_mosaicity_is_still_manageable.3F
# http://journals.iucr.org/d/issues/2012/01/00/wd5161/index.html
# Transform from XDS defintion of sigma_m to FWHM (MOSFLM mosaicity definition)
print >> f, 'CMOSAIC %.2f' % (experiment.profile.sigma_m() *
2.355)
print >> f, 'PHISTART %.2f' % scan.get_oscillation_range()[0]
print >> f, 'PHIWIDTH %.2f' % scan.get_oscillation()[1]
print >> f, 'DISTANCE %7.2f' % distance
print >> f, 'WAVELENGTH %.5f' % beam.get_wavelength()
print >> f, 'POLARISATION %7.5f' % beam.get_polarization_fraction()
print >> f, 'SYMMETRY %s' % space_group_symbol(
cryst.get_space_group())
print >> f, 'UB %9.6f %9.6f %9.6f' % UB_mosflm[:3]
print >> f, ' %9.6f %9.6f %9.6f' % UB_mosflm[3:6]
print >> f, ' %9.6f %9.6f %9.6f' % UB_mosflm[6:]
print >> f, 'CELL %8.2f %8.2f %8.2f %6.2f %6.2f %6.2f' % uc_params
print >> f, 'RASTER %i %i %i %i %i' % (nxs, nys, nc, nrx,
nry)
print >> f, 'SEPARATION %.3f %.3f' % (spot_diameter,
spot_diameter)
print >> f, 'BEAM %8.3f %8.3f' % beam_centre
print >> f, '# end of parameter file for BEST'
def test():
import random
import textwrap
from cctbx.uctbx import unit_cell
from libtbx.test_utils import approx_equal
def random_direction_close_to(vector):
return vector.rotate_around_origin(
matrix.col((random.random(), random.random(),
random.random())).normalize(),
random.gauss(0, 1.0),
deg=True,
)
# make a random P1 crystal and parameterise it
a = random.uniform(10, 50) * random_direction_close_to(
matrix.col((1, 0, 0)))
b = random.uniform(10, 50) * random_direction_close_to(
matrix.col((0, 1, 0)))
c = random.uniform(10, 50) * random_direction_close_to(
matrix.col((0, 0, 1)))
xl = Crystal(a, b, c, space_group_symbol="P 1")
xl_op = CrystalOrientationParameterisation(xl)
xl_ucp = CrystalUnitCellParameterisation(xl)
null_mat = matrix.sqr((0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0))
# compare analytical and finite difference derivatives
an_ds_dp = xl_op.get_ds_dp()
fd_ds_dp = get_fd_gradients(xl_op, [1.0e-6 * pi / 180] * 3)
for e, f in zip(an_ds_dp, fd_ds_dp):
assert approx_equal((e - f), null_mat, eps=1.0e-6)
an_ds_dp = xl_ucp.get_ds_dp()
fd_ds_dp = get_fd_gradients(xl_ucp, [1.0e-7] * xl_ucp.num_free())
for e, f in zip(an_ds_dp, fd_ds_dp):
assert approx_equal((e - f), null_mat, eps=1.0e-6)
# random initial orientations with a random parameter shift at each
attempts = 100
for i in range(attempts):
# make a random P1 crystal and parameterise it
a = random.uniform(10, 50) * random_direction_close_to(
matrix.col((1, 0, 0)))
b = random.uniform(10, 50) * random_direction_close_to(
matrix.col((0, 1, 0)))
c = random.uniform(10, 50) * random_direction_close_to(
matrix.col((0, 0, 1)))
xl = Crystal(a, b, c, space_group_symbol="P 1")
xl_op = CrystalOrientationParameterisation(xl)
xl_uc = CrystalUnitCellParameterisation(xl)
# apply a random parameter shift to the orientation
p_vals = xl_op.get_param_vals()
p_vals = random_param_shift(
p_vals, [1000 * pi / 9, 1000 * pi / 9, 1000 * pi / 9])
xl_op.set_param_vals(p_vals)
# compare analytical and finite difference derivatives
xl_op_an_ds_dp = xl_op.get_ds_dp()
xl_op_fd_ds_dp = get_fd_gradients(xl_op, [1.0e-5 * pi / 180] * 3)
# apply a random parameter shift to the unit cell. We have to
# do this in a way that is respectful to metrical constraints,
# so don't modify the parameters directly; modify the cell
# constants and extract the new parameters
cell_params = xl.get_unit_cell().parameters()
cell_params = random_param_shift(cell_params, [1.0] * 6)
new_uc = unit_cell(cell_params)
newB = matrix.sqr(new_uc.fractionalization_matrix()).transpose()
S = symmetrize_reduce_enlarge(xl.get_space_group())
S.set_orientation(orientation=newB)
X = S.forward_independent_parameters()
xl_uc.set_param_vals(X)
xl_uc_an_ds_dp = xl_ucp.get_ds_dp()
# now doing finite differences about each parameter in turn
xl_uc_fd_ds_dp = get_fd_gradients(xl_ucp, [1.0e-7] * xl_ucp.num_free())
for j in range(3):
assert approx_equal((xl_op_fd_ds_dp[j] - xl_op_an_ds_dp[j]),
null_mat,
eps=1.0e-6), textwrap.dedent("""\
Failure in try {i}
failure for parameter number {j}
of the orientation parameterisation
with fd_ds_dp =
{fd}
and an_ds_dp =
{an}
so that difference fd_ds_dp - an_ds_dp =
{diff}
""").format(
i=i,
j=j,
fd=xl_op_fd_ds_dp[j],
an=xl_op_an_ds_dp[j],
diff=xl_op_fd_ds_dp[j] - xl_op_an_ds_dp[j],
)
for j in range(xl_ucp.num_free()):
assert approx_equal((xl_uc_fd_ds_dp[j] - xl_uc_an_ds_dp[j]),
null_mat,
eps=1.0e-6), textwrap.dedent("""\
Failure in try {i}
failure for parameter number {j}
of the unit cell parameterisation
with fd_ds_dp =
{fd}
and an_ds_dp =
{an}
so that difference fd_ds_dp - an_ds_dp =
{diff}
""").format(
i=i,
j=j,
fd=xl_uc_fd_ds_dp[j],
an=xl_uc_an_ds_dp[j],
diff=xl_uc_fd_ds_dp[j] - xl_uc_an_ds_dp[j],
)
p_vals, [1000 * pi / 9, 1000 * pi / 9, 1000 * pi / 9])
xl_op.set_param_vals(p_vals)
# compare analytical and finite difference derivatives
xl_op_an_ds_dp = xl_op.get_ds_dp()
xl_op_fd_ds_dp = get_fd_gradients(xl_op, [1.e-5 * pi / 180] * 3)
# apply a random parameter shift to the unit cell. We have to
# do this in a way that is respectful to metrical constraints,
# so don't modify the parameters directly; modify the cell
# constants and extract the new parameters
cell_params = xl.get_unit_cell().parameters()
cell_params = random_param_shift(cell_params, [1.] * 6)
new_uc = unit_cell(cell_params)
newB = matrix.sqr(new_uc.fractionalization_matrix()).transpose()
S = symmetrize_reduce_enlarge(xl.get_space_group())
S.set_orientation(orientation=newB)
X = S.forward_independent_parameters()
xl_uc.set_param_vals(X)
xl_uc_an_ds_dp = xl_ucp.get_ds_dp()
# now doing finite differences about each parameter in turn
xl_uc_fd_ds_dp = get_fd_gradients(xl_ucp, [1.e-7] * xl_ucp.num_free())
for j in range(3):
try:
assert (approx_equal((xl_op_fd_ds_dp[j] - xl_op_an_ds_dp[j]),
null_mat,
eps=1.e-6))
except AssertionError:
a_real, b_real, c_real = sqr(
uctbx.unit_cell(
ucell).orthogonalization_matrix()).transpose().as_list_of_lists()
C = Crystal(a_real, b_real, c_real, symbol)
nbr = NBcrystal()
nbr.dxtbx_crystal = C
S = sim_data.SimData(use_default_crystal=True)
S.crystal = nbr
S.instantiate_diffBragg(auto_set_spotscale=True)
S.D.add_diffBragg_spots()
img = S.D.raw_pixels.as_numpy_array()
# simulate the primitive cell directly
to_p1 = C.get_space_group().info().change_of_basis_op_to_primitive_setting()
Cp1 = C.change_basis(to_p1)
nbr2 = NBcrystal()
nbr2.dxtbx_crystal = Cp1
S2 = sim_data.SimData()
S2.crystal = nbr2
S2.instantiate_diffBragg(auto_set_spotscale=True)
S2.D.add_diffBragg_spots()
img2 = S2.D.raw_pixels.as_numpy_array()
# rescale because currently volume is computed incorrectly
img2 = img2 * S.D.spot_scale / S2.D.spot_scale
assert S.D.Omatrix == tuple(to_p1.c_inv().r().transpose().as_double())
assert S2.D.Omatrix == (1, 0, 0, 0, 1, 0, 0, 0, 1)
print("cctbx A")
print_matrix(co.reciprocal_matrix())
dxtbx_a = sqr(crystal.change_basis(op).get_A())
cctbx_a = sqr(
co.change_basis(sqr(
op.c().as_double_array()[0:9]).transpose()).reciprocal_matrix())
print("Crystal A COB")
print_matrix(dxtbx_a)
print("cctbx A COB")
print_matrix(cctbx_a)
good_op = approx_equal(dxtbx_a.elems, cctbx_a.elems, out=None)
print("A matrices approx equal:", good_op)
if good_op:
ok_ops.append(op)
else:
bad_ops.append(op)
print("All possible ops")
for rot in crystal.get_space_group():
op = change_of_basis_op(rot)
test_op(op)
print("Ops that passed")
for op in ok_ops:
print(op)
print("Ops that failed")
for op in bad_ops:
print(op)
