def tst_with_old_index_generator(self):
from dials.algorithms.spot_prediction import ScanStaticReflectionPredictor
from dials.array_family import flex
predict = ScanStaticReflectionPredictor(self.experiments[0])
r_old = predict.for_ub_old_index_generator(
self.experiments[0].crystal.get_A())
r_new = predict.for_ub(self.experiments[0].crystal.get_A())
index1 = flex.size_t(
sorted(range(len(r_old)), key=lambda x: r_old['miller_index'][x]))
index2 = flex.size_t(
sorted(range(len(r_new)), key=lambda x: r_new['miller_index'][x]))
r_old = r_old.select(index1)
r_new = r_new.select(index2)
assert (len(r_old) == len(r_new))
eps = 1e-7
for r1, r2 in zip(r_old.rows(), r_new.rows()):
assert (r1['miller_index'] == r2['miller_index'])
assert (r1['panel'] == r2['panel'])
assert (r1['entering'] == r2['entering'])
assert (all(abs(a - b) < eps for a, b in zip(r1['s1'], r2['s1'])))
assert (all(
abs(a - b) < eps
for a, b in zip(r1['xyzcal.px'], r2['xyzcal.px'])))
assert (all(
abs(a - b) < eps
for a, b in zip(r1['xyzcal.mm'], r2['xyzcal.mm'])))
print 'OK'
def test_with_old_index_generator(data):
from dials.algorithms.spot_prediction import ScanStaticReflectionPredictor
from dials.array_family import flex
predict = ScanStaticReflectionPredictor(data.experiments[0])
r_old = predict.for_ub_old_index_generator(
data.experiments[0].crystal.get_A())
r_new = predict.for_ub(data.experiments[0].crystal.get_A())
index1 = flex.size_t(
sorted(range(len(r_old)), key=lambda x: r_old["miller_index"][x]))
index2 = flex.size_t(
sorted(range(len(r_new)), key=lambda x: r_new["miller_index"][x]))
r_old = r_old.select(index1)
r_new = r_new.select(index2)
assert len(r_old) == len(r_new)
for r1, r2 in zip(r_old.rows(), r_new.rows()):
assert r1["miller_index"] == r2["miller_index"]
assert r1["panel"] == r2["panel"]
assert r1["entering"] == r2["entering"]
assert all(a == pytest.approx(b, abs=1e-7)
for a, b in zip(r1["s1"], r2["s1"]))
assert all(a == pytest.approx(b, abs=1e-7)
for a, b in zip(r1["xyzcal.px"], r2["xyzcal.px"]))
assert all(a == pytest.approx(b, abs=1e-7)
for a, b in zip(r1["xyzcal.mm"], r2["xyzcal.mm"]))
def predict_new(self, experiment=None, hkl=None, panel=None):
from dials.algorithms.spot_prediction import ScanStaticReflectionPredictor
if experiment is None: experiment=self.experiments[0]
predict = ScanStaticReflectionPredictor(experiment)
if hkl is None:
return predict.for_ub(experiment.crystal.get_A())
else:
if panel is None:
return predict(hkl)
else:
return predict(hkl, panel)
def predict_new(self, experiment=None, hkl=None, panel=None):
from dials.algorithms.spot_prediction import ScanStaticReflectionPredictor
if experiment is None: experiment = self.experiments[0]
predict = ScanStaticReflectionPredictor(experiment)
if hkl is None:
return predict.for_ub(experiment.crystal.get_A())
else:
if panel is None:
return predict(hkl)
else:
return predict(hkl, panel)
def test_with_reflection_table(data):
from dials.algorithms.spot_prediction import ScanStaticReflectionPredictor
from dials.array_family import flex
r_old = data.reflections
r_new = flex.reflection_table()
r_new['miller_index'] = r_old['miller_index']
r_new['panel'] = r_old['panel']
r_new['entering'] = r_old['entering']
predict = ScanStaticReflectionPredictor(data.experiments[0])
predict.for_reflection_table(r_new, data.experiments[0].crystal.get_A())
for r1, r2 in zip(r_old.rows(), r_new.rows()):
assert r1['miller_index'] == r2['miller_index']
assert r1['panel'] == r2['panel']
assert r1['entering'] == r2['entering']
assert all(a == pytest.approx(b, abs=1e-7) for a, b in zip(r1['s1'], r2['s1']))
assert all(a == pytest.approx(b, abs=1e-7) for a, b in zip(r1['xyzcal.px'], r2['xyzcal.px']))
assert all(a == pytest.approx(b, abs=1e-7) for a, b in zip(r1['xyzcal.mm'], r2['xyzcal.mm']))
def tst_with_reflection_table(self):
from dials.algorithms.spot_prediction import ScanStaticReflectionPredictor
from dials.array_family import flex
r_old = self.reflections
r_new = flex.reflection_table()
r_new['miller_index'] = r_old['miller_index']
r_new['panel'] = r_old['panel']
r_new['entering'] = r_old['entering']
predict = ScanStaticReflectionPredictor(self.experiments[0])
predict.for_reflection_table(r_new, self.experiments[0].crystal.get_A())
eps = 1e-7
for r1, r2 in zip(r_old.rows(), r_new.rows()):
assert(r1['miller_index'] == r2['miller_index'])
assert(r1['panel'] == r2['panel'])
assert(r1['entering'] == r2['entering'])
assert(all(abs(a-b) < eps for a, b in zip(r1['s1'], r2['s1'])))
assert(all(abs(a-b) < eps for a, b in zip(r1['xyzcal.px'], r2['xyzcal.px'])))
assert(all(abs(a-b) < eps for a, b in zip(r1['xyzcal.mm'], r2['xyzcal.mm'])))
print 'OK'
def test_connected_components_centred_cell(dials_data):
experiment = ExperimentList.from_file(
dials_data("insulin_processed").join("scaled.expt").strpath, check_format=False
)[0]
experiment.scan.set_image_range((1, 10))
predict = ScanStaticReflectionPredictor(experiment, dmin=3, margin=1)
refl = predict.for_ub(experiment.crystal.get_A())
miller_set = miller.set(
experiment.crystal.get_crystal_symmetry(),
refl["miller_index"],
anomalous_flag=False,
)
miller_array = miller_set.d_spacings().resolution_filter(d_min=3)
complete_set, unique_ms = missing_reflections.connected_components(miller_array)
assert [ms.size() for ms in unique_ms] == [581, 32, 29, 6, 3, 3, 3, 2]
# Verify that all the indices reported missing are actually missing from the input
for ms in unique_ms:
assert ms.common_set(miller_array.map_to_asu()).size() == 0
assert complete_set.completeness() == 1
def test_for_reflection_table(data):
from dials.algorithms.spot_prediction import (
ScanStaticReflectionPredictor,
ScanVaryingReflectionPredictor,
)
from dials.array_family import flex
predict = ScanStaticReflectionPredictor(data.experiments[0])
preds = predict.for_ub(data.experiments[0].crystal.get_A())
preds["ub_matrix"] = flex.mat3_double(len(preds),
data.experiments[0].crystal.get_A())
preds["s0"] = flex.vec3_double(len(preds),
data.experiments[0].beam.get_s0())
preds["d_matrix"] = flex.mat3_double(len(preds))
preds["S_matrix"] = flex.mat3_double(
len(preds), data.experiments[0].goniometer.get_setting_rotation())
for ipanel, panel in enumerate(data.experiments[0].detector):
sel = preds["panel"] == ipanel
D = panel.get_d_matrix()
preds["d_matrix"].set_selected(sel, D)
predict = ScanVaryingReflectionPredictor(data.experiments[0])
old_preds = copy.deepcopy(preds)
predict.for_reflection_table(preds, preds["ub_matrix"], preds["s0"],
preds["d_matrix"], preds["S_matrix"])
# Because UB, s0, d and S values are the same for all reflections, the new
# reflections should be approx equal to those produced by the scan static
# predictor
old_x, old_y, old_z = old_preds["xyzcal.px"].parts()
new_x, new_y, new_z = preds["xyzcal.px"].parts()
assert old_x.all_approx_equal(new_x)
assert old_y.all_approx_equal(new_y)
assert old_z.all_approx_equal(new_z)
def tst_for_reflection_table(self):
from libtbx.test_utils import approx_equal
from dials.algorithms.spot_prediction import \
ScanVaryingReflectionPredictor, ScanStaticReflectionPredictor
from dials.array_family import flex
predict = ScanStaticReflectionPredictor(self.experiments[0])
preds = predict.for_ub(self.experiments[0].crystal.get_A())
preds['ub_matrix'] = flex.mat3_double(len(preds), self.experiments[0].crystal.get_A())
preds['s0'] = flex.vec3_double(len(preds), self.experiments[0].beam.get_s0())
preds['d_matrix'] = flex.mat3_double(len(preds))
for ipanel, panel in enumerate(self.experiments[0].detector):
sel = preds['panel'] == ipanel
D = panel.get_d_matrix()
preds['d_matrix'].set_selected(sel, D)
predict = ScanVaryingReflectionPredictor(self.experiments[0])
from copy import deepcopy
old_preds = deepcopy(preds)
predict.for_reflection_table(preds,
preds['ub_matrix'],
preds['s0'],
preds['d_matrix'])
# Because UB, s0 and d values are the same for all reflections, the new
# reflections should be approx equal to those produced by the scan static
# predictor
old_x, old_y, old_z = old_preds['xyzcal.px'].parts()
new_x, new_y, new_z = preds['xyzcal.px'].parts()
assert old_x.all_approx_equal(new_x)
assert old_y.all_approx_equal(new_y)
assert old_z.all_approx_equal(new_z)
print "OK"
return
def tst_with_reflection_table(self):
from dials.algorithms.spot_prediction import ScanStaticReflectionPredictor
from dials.array_family import flex
r_old = self.reflections
r_new = flex.reflection_table()
r_new['miller_index'] = r_old['miller_index']
r_new['panel'] = r_old['panel']
r_new['entering'] = r_old['entering']
predict = ScanStaticReflectionPredictor(self.experiments[0])
predict.for_reflection_table(r_new,
self.experiments[0].crystal.get_A())
eps = 1e-7
for r1, r2 in zip(r_old.rows(), r_new.rows()):
assert (r1['miller_index'] == r2['miller_index'])
assert (r1['panel'] == r2['panel'])
assert (r1['entering'] == r2['entering'])
assert (all(abs(a - b) < eps for a, b in zip(r1['s1'], r2['s1'])))
assert (all(
abs(a - b) < eps
for a, b in zip(r1['xyzcal.px'], r2['xyzcal.px'])))
assert (all(
abs(a - b) < eps
for a, b in zip(r1['xyzcal.mm'], r2['xyzcal.mm'])))
print 'OK'
def test_connected_components(dials_data):
experiment = ExperimentList.from_file(
dials_data("centroid_test_data").join("experiments.json").strpath
)[0]
image_ranges = [(1, 9), (1, 100), (1, 1000)]
expected_ms_sizes = [[755], [242, 14, 10, 5, 2, 2, 2], []]
for image_range, expected_sizes in zip(image_ranges, expected_ms_sizes):
experiment.scan.set_image_range(image_range)
predict = ScanStaticReflectionPredictor(experiment, dmin=3, margin=1)
refl = predict.for_ub(experiment.crystal.get_A())
miller_set = miller.set(
experiment.crystal.get_crystal_symmetry(),
refl["miller_index"],
anomalous_flag=False,
)
miller_array = miller_set.d_spacings().resolution_filter(d_min=3)
complete_set, unique_ms = missing_reflections.connected_components(miller_array)
assert len(unique_ms) == len(expected_sizes)
assert [ms.size() for ms in unique_ms] == expected_sizes
# Verify that all the indices reported missing are actually missing from the input
for ms in unique_ms:
assert ms.common_set(miller_array.map_to_asu()).size() == 0
assert complete_set.completeness() == 1
def tst_for_reflection_table(self):
from libtbx.test_utils import approx_equal
from dials.algorithms.spot_prediction import \
ScanVaryingReflectionPredictor, ScanStaticReflectionPredictor
from dials.array_family import flex
predict = ScanStaticReflectionPredictor(self.experiments[0])
preds = predict.for_ub(self.experiments[0].crystal.get_A())
preds['ub_matrix'] = flex.mat3_double(len(preds), self.experiments[0].crystal.get_A())
preds['s0'] = flex.vec3_double(len(preds), self.experiments[0].beam.get_s0())
preds['d_matrix'] = flex.mat3_double(len(preds))
preds['S_matrix'] = flex.mat3_double(len(preds),
self.experiments[0].goniometer.get_setting_rotation())
for ipanel, panel in enumerate(self.experiments[0].detector):
sel = preds['panel'] == ipanel
D = panel.get_d_matrix()
preds['d_matrix'].set_selected(sel, D)
predict = ScanVaryingReflectionPredictor(self.experiments[0])
from copy import deepcopy
old_preds = deepcopy(preds)
predict.for_reflection_table(preds,
preds['ub_matrix'],
preds['s0'],
preds['d_matrix'],
preds['S_matrix'])
# Because UB, s0, d and S values are the same for all reflections, the new
# reflections should be approx equal to those produced by the scan static
# predictor
old_x, old_y, old_z = old_preds['xyzcal.px'].parts()
new_x, new_y, new_z = preds['xyzcal.px'].parts()
assert old_x.all_approx_equal(new_x)
assert old_y.all_approx_equal(new_y)
assert old_z.all_approx_equal(new_z)
print "OK"
return
def __init__(self,
experiment,
dmin=None,
dmax=None,
margin=1,
force_static=False,
padding=0):
'''
Initialise a predictor for each experiment.
:param experiment: The experiment to predict for
:param dmin: The maximum resolution
:param dmax: The minimum resolution
:param margin: The margin of hkl to predict
:param force_static: force scan varying prediction to be static
'''
from dials.algorithms.spot_prediction import ScanStaticReflectionPredictor
from dials.algorithms.spot_prediction import ScanVaryingReflectionPredictor
from dials.algorithms.spot_prediction import StillsReflectionPredictor
from dxtbx.imageset import ImageSweep
from dials.array_family import flex
class Predictor(object):
def __init__(self, name, func):
self.name = name
self.func = func
def __call__(self):
result = self.func()
if dmax is not None:
assert (dmax > 0)
result.compute_d_single(experiment)
mask = result['d'] > dmax
result.del_selected(mask)
return result
# Check prediction to maximum resolution is possible
wl = experiment.beam.get_wavelength()
if dmin is not None and dmin < 0.5 * wl:
raise Sorry("Prediction at d_min of {0} is not possible "
"with wavelength {1}".format(dmin, wl))
# Select the predictor class
if isinstance(experiment.imageset, ImageSweep):
nsp = experiment.crystal.num_scan_points
nim = experiment.scan.get_num_images()
if not force_static and nsp == nim + 1:
predictor = ScanVaryingReflectionPredictor(experiment,
dmin=dmin,
margin=margin,
padding=padding)
A = [
experiment.crystal.get_A_at_scan_point(i)
for i in range(experiment.crystal.num_scan_points)
]
predict = Predictor(
"scan varying prediction",
lambda: predictor.for_ub(flex.mat3_double(A)))
else:
predictor = ScanStaticReflectionPredictor(experiment,
dmin=dmin,
padding=padding)
predict = Predictor(
"scan static prediction",
lambda: predictor.for_ub(experiment.crystal.get_A()))
else:
predictor = StillsReflectionPredictor(experiment, dmin=dmin)
predict = Predictor(
"stills prediction",
lambda: predictor.for_ub(experiment.crystal.get_A()))
# Create and add the predictor class
self._predict = predict
def export_sadabs(integrated_data, experiment_list, params):
"""Export data from integrated_data corresponding to experiment_list to a
file for input to SADABS. FIXME probably need to make a .p4p file as
well..."""
from dials.array_family import flex
# for the moment assume (and assert) that we will convert data from exactly
# one lattice...
assert len(experiment_list) == 1
# select reflections that are assigned to an experiment (i.e. non-negative id)
integrated_data = integrated_data.select(integrated_data["id"] >= 0)
assert max(integrated_data["id"]) == 0
# export for sadabs should only be for non-scaled reflections
assert any(i in integrated_data
for i in ["intensity.sum.value", "intensity.prf.value"])
integrated_data = filter_reflection_table(
integrated_data,
intensity_choice=params.intensity,
partiality_threshold=params.mtz.partiality_threshold,
combine_partials=params.mtz.combine_partials,
min_isigi=params.mtz.min_isigi,
filter_ice_rings=params.mtz.filter_ice_rings,
d_min=params.mtz.d_min,
)
experiment = experiment_list[0]
assert experiment.scan is not None
# sort data before output
nref = len(integrated_data["miller_index"])
indices = flex.size_t_range(nref)
perm = sorted(indices, key=lambda k: integrated_data["miller_index"][k])
integrated_data = integrated_data.select(flex.size_t(perm))
assert experiment.goniometer is not None
# Warn of unhelpful SADABS behaviour for certain multi-sequence data sets
hkl_file_root, _ = os.path.splitext(params.sadabs.hklout)
if not params.sadabs.run or re.search("_0+$", hkl_file_root):
logger.warning(
"It seems SADABS rejects multi-sequence data when the first "
"filename ends "
"'_0', '_00', etc., with a cryptic error message:\n"
"\t'Inconsistent 2theta values in same scan'.\n"
"You may need to begin the numbering of your SADABS HKL files from 1, "
"rather than 0, and ensure the SADABS run/batch number is greater than 0."
)
axis = matrix.col(experiment.goniometer.get_rotation_axis_datum())
beam = matrix.col(experiment.beam.get_sample_to_source_direction())
s0 = matrix.col(experiment.beam.get_s0())
F = matrix.sqr(experiment.goniometer.get_fixed_rotation())
S = matrix.sqr(experiment.goniometer.get_setting_rotation())
unit_cell = experiment.crystal.get_unit_cell()
if params.debug:
m_format = "%6.3f%6.3f%6.3f\n%6.3f%6.3f%6.3f\n%6.3f%6.3f%6.3f"
c_format = "%.2f %.2f %.2f %.2f %.2f %.2f"
logger.info(
"Unit cell parameters from experiment: %s",
c_format % unit_cell.parameters(),
)
logger.info(
"Symmetry: %s",
experiment.crystal.get_space_group().type().lookup_symbol())
logger.info("Goniometer fixed matrix:\n%s", m_format % F.elems)
logger.info("Goniometer setting matrix:\n%s", m_format % S.elems)
logger.info("Goniometer scan axis:\n%6.3f%6.3f%6.3f", axis.elems)
# detector scaling info
assert len(experiment.detector) == 1
panel = experiment.detector[0]
dims = panel.get_image_size()
pixel = panel.get_pixel_size()
fast_axis = matrix.col(panel.get_fast_axis())
slow_axis = matrix.col(panel.get_slow_axis())
normal = fast_axis.cross(slow_axis)
detector2t = s0.angle(normal, deg=True)
if params.debug:
logger.info("Detector fast, slow axes:")
logger.info("%6.3f%6.3f%6.3f", fast_axis.elems)
logger.info("%6.3f%6.3f%6.3f", slow_axis.elems)
logger.info("Detector two theta (degrees): %.2f", detector2t)
scl_x = 512.0 / (dims[0] * pixel[0])
scl_y = 512.0 / (dims[1] * pixel[1])
image_range = experiment.scan.get_image_range()
from cctbx.array_family import flex as cflex # implicit import # noqa: F401
from cctbx.miller import map_to_asu_isym # implicit import # noqa: F401
# gather the required information for the reflection file
nref = len(integrated_data["miller_index"])
miller_index = integrated_data["miller_index"]
if "intensity.sum.value" in integrated_data:
I = integrated_data["intensity.sum.value"]
V = integrated_data["intensity.sum.variance"]
assert V.all_gt(0)
sigI = flex.sqrt(V)
else:
I = integrated_data["intensity.prf.value"]
V = integrated_data["intensity.prf.variance"]
assert V.all_gt(0)
sigI = flex.sqrt(V)
# figure out scaling to make sure data fit into format 2F8.2 i.e. Imax < 1e5
Imax = flex.max(I)
if params.debug:
logger.info("Maximum intensity in file: %8.2f", Imax)
if Imax > 99999.0:
scale = 99999.0 / Imax
I = I * scale
sigI = sigI * scale
phi_start, phi_range = experiment.scan.get_image_oscillation(
image_range[0])
if params.sadabs.predict:
logger.info("Using scan static predicted spot locations")
from dials.algorithms.spot_prediction import ScanStaticReflectionPredictor
predictor = ScanStaticReflectionPredictor(experiment)
UB = experiment.crystal.get_A()
predictor.for_reflection_table(integrated_data, UB)
if not experiment.crystal.num_scan_points:
logger.info("No scan varying model: use static")
static = True
else:
static = False
with open(params.sadabs.hklout, "w") as fout:
for j in range(nref):
h, k, l = miller_index[j]
if params.sadabs.predict:
x_mm, y_mm, z_rad = integrated_data["xyzcal.mm"][j]
else:
x_mm, y_mm, z_rad = integrated_data["xyzobs.mm.value"][j]
z0 = integrated_data["xyzcal.px"][j][2]
istol = int(round(10000 * unit_cell.stol((h, k, l))))
if params.sadabs.predict or static:
# work from a scan static model & assume perfect goniometer
# FIXME maybe should work back in the option to predict spot positions
UB = matrix.sqr(experiment.crystal.get_A())
phi = phi_start + z0 * phi_range
R = axis.axis_and_angle_as_r3_rotation_matrix(phi, deg=True)
RUB = S * R * F * UB
else:
# properly compute RUB for every reflection
UB = matrix.sqr(
experiment.crystal.get_A_at_scan_point(int(round(z0))))
phi = phi_start + z0 * phi_range
R = axis.axis_and_angle_as_r3_rotation_matrix(phi, deg=True)
RUB = S * R * F * UB
x = RUB * (h, k, l)
s = (s0 + x).normalize()
# can also compute s based on centre of mass of spot
# s = (origin + x_mm * fast_axis + y_mm * slow_axis).normalize()
astar = (RUB * (1, 0, 0)).normalize()
bstar = (RUB * (0, 1, 0)).normalize()
cstar = (RUB * (0, 0, 1)).normalize()
ix = beam.dot(astar)
iy = beam.dot(bstar)
iz = beam.dot(cstar)
dx = s.dot(astar)
dy = s.dot(bstar)
dz = s.dot(cstar)
x = x_mm * scl_x
y = y_mm * scl_y
z = (z_rad * 180 / math.pi - phi_start) / phi_range
fout.write("%4d%4d%4d%8.2f%8.2f%4d%8.5f%8.5f%8.5f%8.5f%8.5f%8.5f" %
(h, k, l, I[j], sigI[j], params.sadabs.run, ix, dx, iy,
dy, iz, dz))
fout.write("%7.2f%7.2f%8.2f%7.2f%5d\n" %
(x, y, z, detector2t, istol))
fout.close()
logger.info("Output %d reflections to %s", nref, params.sadabs.hklout)
def export_sadabs(integrated_data, experiment_list, hklout, run=0,
summation=False, include_partials=False, keep_partials=False,
debug=False, predict=True):
'''Export data from integrated_data corresponding to experiment_list to a
file for input to SADABS. FIXME probably need to make a .p4p file as
well...'''
from dials.array_family import flex
from scitbx import matrix
import math
# for the moment assume (and assert) that we will convert data from exactly
# one lattice...
assert(len(experiment_list) == 1)
# select reflections that are assigned to an experiment (i.e. non-negative id)
integrated_data = integrated_data.select(integrated_data['id'] >= 0)
assert max(integrated_data['id']) == 0
if not summation:
assert('intensity.prf.value' in integrated_data)
# strip out negative variance reflections: these should not really be there
# FIXME Doing select on summation results. Should do on profile result if
# present? Yes
if 'intensity.prf.variance' in integrated_data:
selection = integrated_data.get_flags(
integrated_data.flags.integrated,
all=True)
else:
selection = integrated_data.get_flags(
integrated_data.flags.integrated_sum)
integrated_data = integrated_data.select(selection)
selection = integrated_data['intensity.sum.variance'] <= 0
if selection.count(True) > 0:
integrated_data.del_selected(selection)
logger.info('Removing %d reflections with negative variance' % \
selection.count(True))
if 'intensity.prf.variance' in integrated_data:
selection = integrated_data['intensity.prf.variance'] <= 0
if selection.count(True) > 0:
integrated_data.del_selected(selection)
logger.info('Removing %d profile reflections with negative variance' % \
selection.count(True))
if include_partials:
integrated_data = sum_partial_reflections(integrated_data)
integrated_data = scale_partial_reflections(integrated_data)
if 'partiality' in integrated_data:
selection = integrated_data['partiality'] < 0.99
if selection.count(True) > 0 and not keep_partials:
integrated_data.del_selected(selection)
logger.info('Removing %d incomplete reflections' % \
selection.count(True))
experiment = experiment_list[0]
assert(not experiment.scan is None)
# sort data before output
nref = len(integrated_data['miller_index'])
indices = flex.size_t_range(nref)
perm = sorted(indices, key=lambda k: integrated_data['miller_index'][k])
integrated_data = integrated_data.select(flex.size_t(perm))
assert (not experiment.goniometer is None)
axis = matrix.col(experiment.goniometer.get_rotation_axis_datum())
beam = matrix.col(experiment.beam.get_direction())
s0 = matrix.col(experiment.beam.get_s0())
F = matrix.sqr(experiment.goniometer.get_fixed_rotation())
S = matrix.sqr(experiment.goniometer.get_setting_rotation())
unit_cell = experiment.crystal.get_unit_cell()
if debug:
m_format = '%6.3f%6.3f%6.3f\n%6.3f%6.3f%6.3f\n%6.3f%6.3f%6.3f'
c_format = '%.2f %.2f %.2f %.2f %.2f %.2f'
logger.info('Unit cell parameters from experiment: %s' % (c_format %
unit_cell.parameters()))
logger.info('Symmetry: %s' % experiment.crystal.get_space_group().type(
).lookup_symbol())
logger.info('Goniometer fixed matrix:\n%s' % (m_format % F.elems))
logger.info('Goniometer setting matrix:\n%s' % (m_format % S.elems))
logger.info('Goniometer scan axis:\n%6.3f%6.3f%6.3f' % (axis.elems))
# detector scaling info
assert(len(experiment.detector) == 1)
panel = experiment.detector[0]
dims = panel.get_image_size()
pixel = panel.get_pixel_size()
fast_axis = matrix.col(panel.get_fast_axis())
slow_axis = matrix.col(panel.get_slow_axis())
normal = fast_axis.cross(slow_axis)
detector2t = s0.angle(normal, deg=True)
origin = matrix.col(panel.get_origin())
if debug:
logger.info('Detector fast, slow axes:')
logger.info('%6.3f%6.3f%6.3f' % (fast_axis.elems))
logger.info('%6.3f%6.3f%6.3f' % (slow_axis.elems))
logger.info('Detector two theta (degrees): %.2f' % detector2t)
scl_x = 512.0 / (dims[0] * pixel[0])
scl_y = 512.0 / (dims[1] * pixel[1])
image_range = experiment.scan.get_image_range()
from cctbx.array_family import flex as cflex # implicit import
from cctbx.miller import map_to_asu_isym # implicit import
# gather the required information for the reflection file
nref = len(integrated_data['miller_index'])
zdet = flex.double(integrated_data['xyzcal.px'].parts()[2])
miller_index = integrated_data['miller_index']
I = None
sigI = None
# export including scale factors
if 'lp' in integrated_data:
lp = integrated_data['lp']
else:
lp = flex.double(nref, 1.0)
if 'dqe' in integrated_data:
dqe = integrated_data['dqe']
else:
dqe = flex.double(nref, 1.0)
scl = lp / dqe
if summation:
I = integrated_data['intensity.sum.value'] * scl
V = integrated_data['intensity.sum.variance'] * scl * scl
assert V.all_gt(0)
sigI = flex.sqrt(V)
else:
I = integrated_data['intensity.prf.value'] * scl
V = integrated_data['intensity.prf.variance'] * scl * scl
assert V.all_gt(0)
sigI = flex.sqrt(V)
# figure out scaling to make sure data fit into format 2F8.2 i.e. Imax < 1e5
Imax = flex.max(I)
if debug:
logger.info('Maximum intensity in file: %8.2f' % Imax)
if Imax > 99999.0:
scale = 99999.0 / Imax
I = I * scale
sigI = sigI * scale
phi_start, phi_range = experiment.scan.get_image_oscillation(image_range[0])
if predict:
logger.info('Using scan static predicted spot locations')
from dials.algorithms.spot_prediction import ScanStaticReflectionPredictor
predictor = ScanStaticReflectionPredictor(experiment)
UB = experiment.crystal.get_A()
predictor.for_reflection_table(integrated_data, UB)
if not experiment.crystal.num_scan_points:
logger.info('No scan varying model: use static')
static = True
else:
static = False
fout = open(hklout, 'w')
for j in range(nref):
h, k, l = miller_index[j]
if predict:
x_mm, y_mm, z_rad = integrated_data['xyzcal.mm'][j]
else:
x_mm, y_mm, z_rad = integrated_data['xyzobs.mm.value'][j]
z0 = integrated_data['xyzcal.px'][j][2]
istol = int(round(10000 * unit_cell.stol((h, k, l))))
if predict or static:
# work from a scan static model & assume perfect goniometer
# FIXME maybe should work back in the option to predict spot positions
UB = experiment.crystal.get_A()
phi = phi_start + z0 * phi_range
R = axis.axis_and_angle_as_r3_rotation_matrix(phi, deg=True)
RUB = S * R * F * UB
else:
# properly compute RUB for every reflection
UB = experiment.crystal.get_A_at_scan_point(int(round(z0)))
phi = phi_start + z0 * phi_range
R = axis.axis_and_angle_as_r3_rotation_matrix(phi, deg=True)
RUB = S * R * F * UB
x = RUB * (h, k, l)
s = (s0 + x).normalize()
# can also compute s based on centre of mass of spot
# s = (origin + x_mm * fast_axis + y_mm * slow_axis).normalize()
astar = (RUB * (1, 0, 0)).normalize()
bstar = (RUB * (0, 1, 0)).normalize()
cstar = (RUB * (0, 0, 1)).normalize()
ix = beam.dot(astar)
iy = beam.dot(bstar)
iz = beam.dot(cstar)
dx = s.dot(astar)
dy = s.dot(bstar)
dz = s.dot(cstar)
x = x_mm * scl_x
y = y_mm * scl_y
z = (z_rad * 180 / math.pi - phi_start) / phi_range
fout.write('%4d%4d%4d%8.2f%8.2f%4d%8.5f%8.5f%8.5f%8.5f%8.5f%8.5f' % \
(h, k, l, I[j], sigI[j], run, ix, dx, iy, dy, iz, dz))
fout.write('%7.2f%7.2f%8.2f%7.2f%5d\n' % (x, y, z, detector2t, istol))
fout.close()
logger.info('Output %d reflections to %s' % (nref, hklout))
return
def __init__(
self, experiment, dmin=None, dmax=None, margin=1, force_static=False, padding=0
):
"""
Initialise a predictor for each experiment.
:param experiment: The experiment to predict for
:param dmin: The maximum resolution
:param dmax: The minimum resolution
:param margin: The margin of hkl to predict
:param force_static: force scan varying prediction to be static
"""
from dials.algorithms.spot_prediction import ScanStaticReflectionPredictor
from dials.algorithms.spot_prediction import ScanVaryingReflectionPredictor
from dials.algorithms.spot_prediction import StillsReflectionPredictor
from dxtbx.imageset import ImageSweep
from dials.array_family import flex
class Predictor(object):
def __init__(self, name, func):
self.name = name
self.func = func
def __call__(self):
result = self.func()
if dmax is not None:
assert dmax > 0
result.compute_d_single(experiment)
mask = result["d"] > dmax
result.del_selected(mask)
return result
# Check prediction to maximum resolution is possible
wl = experiment.beam.get_wavelength()
if dmin is not None and dmin < 0.5 * wl:
raise Sorry(
"Prediction at d_min of {0} is not possible "
"with wavelength {1}".format(dmin, wl)
)
# Select the predictor class
if isinstance(experiment.imageset, ImageSweep):
xl_nsp = experiment.crystal.num_scan_points
bm_nsp = experiment.beam.num_scan_points
gn_nsp = experiment.goniometer.num_scan_points
nim = experiment.scan.get_num_images()
sv_compatible = (xl_nsp == nim + 1) or (bm_nsp == nim + 1)
if not force_static and sv_compatible:
predictor = ScanVaryingReflectionPredictor(
experiment, dmin=dmin, margin=margin, padding=padding
)
if bm_nsp == 0 and gn_nsp == 0:
# Only varying crystal
A = [
experiment.crystal.get_A_at_scan_point(i)
for i in range(experiment.crystal.num_scan_points)
]
predict = Predictor(
"scan varying crystal prediction",
lambda: predictor.for_ub(flex.mat3_double(A)),
)
else:
# Any allowed model may vary
if xl_nsp == nim + 1:
A = [
experiment.crystal.get_A_at_scan_point(i)
for i in range(experiment.crystal.num_scan_points)
]
else:
A = [experiment.crystal.get_A() for i in range(nim + 1)]
if bm_nsp == nim + 1:
s0 = [
experiment.beam.get_s0_at_scan_point(i)
for i in range(experiment.beam.num_scan_points)
]
else:
s0 = [experiment.beam.get_s0() for i in range(nim + 1)]
if gn_nsp == nim + 1:
S = [
experiment.goniometer.get_setting_rotation_at_scan_point(i)
for i in range(experiment.goniometer.num_scan_points)
]
else:
S = [
experiment.goniometer.get_setting_rotation()
for i in range(nim + 1)
]
predict = Predictor(
"scan varying model prediction",
lambda: predictor.for_varying_models(
flex.mat3_double(A),
flex.vec3_double(s0),
flex.mat3_double(S),
),
)
else:
predictor = ScanStaticReflectionPredictor(
experiment, dmin=dmin, padding=padding
)
# Choose index generation method based on number of images
# https://github.com/dials/dials/issues/585
if experiment.scan.get_num_images() > 50:
predict_method = predictor.for_ub_old_index_generator
else:
predict_method = predictor.for_ub
predict = Predictor(
"scan static prediction",
lambda: predict_method(experiment.crystal.get_A()),
)
else:
predictor = StillsReflectionPredictor(experiment, dmin=dmin)
predict = Predictor(
"stills prediction",
lambda: predictor.for_ub(experiment.crystal.get_A()),
)
# Create and add the predictor class
self._predict = predict
def export_sadabs(integrated_data,
experiment_list,
hklout,
run=0,
summation=False,
include_partials=False,
keep_partials=False,
debug=False,
predict=True):
'''Export data from integrated_data corresponding to experiment_list to a
file for input to SADABS. FIXME probably need to make a .p4p file as
well...'''
from dials.array_family import flex
from scitbx import matrix
import math
# for the moment assume (and assert) that we will convert data from exactly
# one lattice...
assert (len(experiment_list) == 1)
# select reflections that are assigned to an experiment (i.e. non-negative id)
integrated_data = integrated_data.select(integrated_data['id'] >= 0)
assert max(integrated_data['id']) == 0
if not summation:
assert ('intensity.prf.value' in integrated_data)
# strip out negative variance reflections: these should not really be there
# FIXME Doing select on summation results. Should do on profile result if
# present? Yes
if 'intensity.prf.variance' in integrated_data:
selection = integrated_data.get_flags(integrated_data.flags.integrated,
all=True)
else:
selection = integrated_data.get_flags(
integrated_data.flags.integrated_sum)
integrated_data = integrated_data.select(selection)
selection = integrated_data['intensity.sum.variance'] <= 0
if selection.count(True) > 0:
integrated_data.del_selected(selection)
logger.info('Removing %d reflections with negative variance' % \
selection.count(True))
if 'intensity.prf.variance' in integrated_data:
selection = integrated_data['intensity.prf.variance'] <= 0
if selection.count(True) > 0:
integrated_data.del_selected(selection)
logger.info('Removing %d profile reflections with negative variance' % \
selection.count(True))
if include_partials:
integrated_data = sum_partial_reflections(integrated_data)
integrated_data = scale_partial_reflections(integrated_data)
if 'partiality' in integrated_data:
selection = integrated_data['partiality'] < 0.99
if selection.count(True) > 0 and not keep_partials:
integrated_data.del_selected(selection)
logger.info('Removing %d incomplete reflections' % \
selection.count(True))
experiment = experiment_list[0]
assert (not experiment.scan is None)
# sort data before output
nref = len(integrated_data['miller_index'])
indices = flex.size_t_range(nref)
perm = sorted(indices, key=lambda k: integrated_data['miller_index'][k])
integrated_data = integrated_data.select(flex.size_t(perm))
assert (not experiment.goniometer is None)
axis = matrix.col(experiment.goniometer.get_rotation_axis_datum())
beam = matrix.col(experiment.beam.get_direction())
s0 = matrix.col(experiment.beam.get_s0())
F = matrix.sqr(experiment.goniometer.get_fixed_rotation())
S = matrix.sqr(experiment.goniometer.get_setting_rotation())
unit_cell = experiment.crystal.get_unit_cell()
if debug:
m_format = '%6.3f%6.3f%6.3f\n%6.3f%6.3f%6.3f\n%6.3f%6.3f%6.3f'
c_format = '%.2f %.2f %.2f %.2f %.2f %.2f'
logger.info('Unit cell parameters from experiment: %s' %
(c_format % unit_cell.parameters()))
logger.info(
'Symmetry: %s' %
experiment.crystal.get_space_group().type().lookup_symbol())
logger.info('Goniometer fixed matrix:\n%s' % (m_format % F.elems))
logger.info('Goniometer setting matrix:\n%s' % (m_format % S.elems))
logger.info('Goniometer scan axis:\n%6.3f%6.3f%6.3f' % (axis.elems))
# detector scaling info
assert (len(experiment.detector) == 1)
panel = experiment.detector[0]
dims = panel.get_image_size()
pixel = panel.get_pixel_size()
fast_axis = matrix.col(panel.get_fast_axis())
slow_axis = matrix.col(panel.get_slow_axis())
normal = fast_axis.cross(slow_axis)
detector2t = s0.angle(normal, deg=True)
origin = matrix.col(panel.get_origin())
if debug:
logger.info('Detector fast, slow axes:')
logger.info('%6.3f%6.3f%6.3f' % (fast_axis.elems))
logger.info('%6.3f%6.3f%6.3f' % (slow_axis.elems))
logger.info('Detector two theta (degrees): %.2f' % detector2t)
scl_x = 512.0 / (dims[0] * pixel[0])
scl_y = 512.0 / (dims[1] * pixel[1])
image_range = experiment.scan.get_image_range()
from cctbx.array_family import flex as cflex # implicit import
from cctbx.miller import map_to_asu_isym # implicit import
# gather the required information for the reflection file
nref = len(integrated_data['miller_index'])
zdet = flex.double(integrated_data['xyzcal.px'].parts()[2])
miller_index = integrated_data['miller_index']
I = None
sigI = None
# export including scale factors
if 'lp' in integrated_data:
lp = integrated_data['lp']
else:
lp = flex.double(nref, 1.0)
if 'qe' in integrated_data:
qe = integrated_data['qe']
elif 'dqe' in integrated_data:
qe = integrated_data['dqe']
else:
qe = flex.double(nref, 1.0)
scl = lp / qe
if summation:
I = integrated_data['intensity.sum.value'] * scl
V = integrated_data['intensity.sum.variance'] * scl * scl
assert V.all_gt(0)
sigI = flex.sqrt(V)
else:
I = integrated_data['intensity.prf.value'] * scl
V = integrated_data['intensity.prf.variance'] * scl * scl
assert V.all_gt(0)
sigI = flex.sqrt(V)
# figure out scaling to make sure data fit into format 2F8.2 i.e. Imax < 1e5
Imax = flex.max(I)
if debug:
logger.info('Maximum intensity in file: %8.2f' % Imax)
if Imax > 99999.0:
scale = 99999.0 / Imax
I = I * scale
sigI = sigI * scale
phi_start, phi_range = experiment.scan.get_image_oscillation(
image_range[0])
if predict:
logger.info('Using scan static predicted spot locations')
from dials.algorithms.spot_prediction import ScanStaticReflectionPredictor
predictor = ScanStaticReflectionPredictor(experiment)
UB = experiment.crystal.get_A()
predictor.for_reflection_table(integrated_data, UB)
if not experiment.crystal.num_scan_points:
logger.info('No scan varying model: use static')
static = True
else:
static = False
fout = open(hklout, 'w')
for j in range(nref):
h, k, l = miller_index[j]
if predict:
x_mm, y_mm, z_rad = integrated_data['xyzcal.mm'][j]
else:
x_mm, y_mm, z_rad = integrated_data['xyzobs.mm.value'][j]
z0 = integrated_data['xyzcal.px'][j][2]
istol = int(round(10000 * unit_cell.stol((h, k, l))))
if predict or static:
# work from a scan static model & assume perfect goniometer
# FIXME maybe should work back in the option to predict spot positions
UB = matrix.sqr(experiment.crystal.get_A())
phi = phi_start + z0 * phi_range
R = axis.axis_and_angle_as_r3_rotation_matrix(phi, deg=True)
RUB = S * R * F * UB
else:
# properly compute RUB for every reflection
UB = matrix.sqr(
experiment.crystal.get_A_at_scan_point(int(round(z0))))
phi = phi_start + z0 * phi_range
R = axis.axis_and_angle_as_r3_rotation_matrix(phi, deg=True)
RUB = S * R * F * UB
x = RUB * (h, k, l)
s = (s0 + x).normalize()
# can also compute s based on centre of mass of spot
# s = (origin + x_mm * fast_axis + y_mm * slow_axis).normalize()
astar = (RUB * (1, 0, 0)).normalize()
bstar = (RUB * (0, 1, 0)).normalize()
cstar = (RUB * (0, 0, 1)).normalize()
ix = beam.dot(astar)
iy = beam.dot(bstar)
iz = beam.dot(cstar)
dx = s.dot(astar)
dy = s.dot(bstar)
dz = s.dot(cstar)
x = x_mm * scl_x
y = y_mm * scl_y
z = (z_rad * 180 / math.pi - phi_start) / phi_range
fout.write('%4d%4d%4d%8.2f%8.2f%4d%8.5f%8.5f%8.5f%8.5f%8.5f%8.5f' % \
(h, k, l, I[j], sigI[j], run, ix, dx, iy, dy, iz, dz))
fout.write('%7.2f%7.2f%8.2f%7.2f%5d\n' % (x, y, z, detector2t, istol))
fout.close()
logger.info('Output %d reflections to %s' % (nref, hklout))