def export_xds_ascii(integrated_data, experiment_list, hklout, summation=False,
include_partials=False, keep_partials=False, var_model=(1,0)):
'''Export data from integrated_data corresponding to experiment_list to
an XDS_ASCII.HKL formatted text file.'''
from dials.array_family import flex
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)
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]
# sort data before output
nref = len(integrated_data['miller_index'])
indices = flex.size_t_range(nref)
import copy
unique = copy.deepcopy(integrated_data['miller_index'])
from cctbx.miller import map_to_asu
map_to_asu(experiment.crystal.get_space_group().type(), False, unique)
perm = sorted(indices, key=lambda k: unique[k])
integrated_data = integrated_data.select(flex.size_t(perm))
from scitbx import matrix
from rstbx.cftbx.coordinate_frame_helpers import align_reference_frame
assert (not experiment.goniometer is None)
unit_cell = experiment.crystal.get_unit_cell()
from scitbx.array_family import flex
from math import floor, sqrt
assert(not experiment.scan is None)
image_range = experiment.scan.get_image_range()
phi_start, phi_range = experiment.scan.get_image_oscillation(image_range[0])
# 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
# profile correlation
if 'profile.correlation' in integrated_data:
prof_corr = 100.0 * integrated_data['profile.correlation']
else:
prof_corr = flex.double(nref, 100.0)
# partiality
if 'partiality' in integrated_data:
partiality = 100 * integrated_data['partiality']
else:
prof_corr = flex.double(nref, 100.0)
if summation:
I = integrated_data['intensity.sum.value'] * scl
V = integrated_data['intensity.sum.variance'] * scl * scl
assert V.all_gt(0)
V = var_model[0] * (V + var_model[1] * I * I)
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)
V = var_model[0] * (V + var_model[1] * I * I)
sigI = flex.sqrt(V)
fout = open(hklout, 'w')
# first write the header - in the "standard" coordinate frame...
panel = experiment.detector[0]
fast = panel.get_fast_axis()
slow = panel.get_slow_axis()
Rd = align_reference_frame(fast, (1,0,0), slow, (0,1,0))
print 'Coordinate change:'
print '%5.2f %5.2f %5.2f\n%5.2f %5.2f %5.2f\n%5.2f %5.2f %5.2f\n' % Rd.elems
fast = Rd * fast
slow = Rd * slow
qx, qy = panel.get_pixel_size()
nx, ny = panel.get_image_size()
distance = matrix.col(Rd * panel.get_origin()).dot(
matrix.col(Rd * panel.get_normal()))
org = Rd * (matrix.col(panel.get_origin()) - distance * matrix.col(
panel.get_normal()))
orgx = - org.dot(fast) / qx
orgy = - org.dot(slow) / qy
UB = Rd * matrix.sqr(experiment.crystal.get_A())
real_space_ABC = UB.inverse().elems
axis = Rd * experiment.goniometer.get_rotation_axis()
beam = Rd * experiment.beam.get_s0()
cell_fmt = '%9.3f %9.3f %9.3f %7.3f %7.3f %7.3f'
axis_fmt = '%9.3f %9.3f %9.3f'
fout.write('\n'.join([
'!FORMAT=XDS_ASCII MERGE=FALSE FRIEDEL\'S_LAW=TRUE',
'!Generated by dials.export',
'!DATA_RANGE= %d %d' % image_range,
'!ROTATION_AXIS= %9.6f %9.6f %9.6f' % axis.elems,
'!OSCILLATION_RANGE= %f' % phi_range,
'!STARTING_ANGLE= %f' % phi_start,
'!STARTING_FRAME= %d' % image_range[0],
'!SPACE_GROUP_NUMBER= %d' % experiment.crystal.get_space_group().type().number(),
'!UNIT_CELL_CONSTANTS= %s' % (cell_fmt % unit_cell.parameters()),
'!UNIT_CELL_A-AXIS= %s' % (axis_fmt % real_space_ABC[0:3]),
'!UNIT_CELL_B-AXIS= %s' % (axis_fmt % real_space_ABC[3:6]),
'!UNIT_CELL_C-AXIS= %s' % (axis_fmt % real_space_ABC[6:9]),
'!X-RAY_WAVELENGTH= %f' % experiment.beam.get_wavelength(),
'!INCIDENT_BEAM_DIRECTION= %f %f %f' % beam.elems,
'!NX= %d NY= %d QX= %f QY= %f' % (nx, ny, qx, qy),
'!ORGX= %9.2f ORGY= %9.2f' % (orgx, orgy),
'!DETECTOR_DISTANCE= %8.3f' % distance,
'!DIRECTION_OF_DETECTOR_X-AXIS= %9.5f %9.5f %9.5f' % fast.elems,
'!DIRECTION_OF_DETECTOR_Y-AXIS= %9.5f %9.5f %9.5f' % slow.elems,
'!VARIANCE_MODEL= %7.3e %7.3e' % var_model,
'!NUMBER_OF_ITEMS_IN_EACH_DATA_RECORD=12',
'!ITEM_H=1',
'!ITEM_K=2',
'!ITEM_L=3',
'!ITEM_IOBS=4',
'!ITEM_SIGMA(IOBS)=5',
'!ITEM_XD=6',
'!ITEM_YD=7',
'!ITEM_ZD=8',
'!ITEM_RLP=9',
'!ITEM_PEAK=10',
'!ITEM_CORR=11',
'!ITEM_PSI=12',
'!END_OF_HEADER',
'']))
# then write the data records
s0 = Rd * matrix.col(experiment.beam.get_s0())
for j in range(nref):
x, y, z = integrated_data['xyzcal.px'][j]
phi = phi_start + z * phi_range
h, k, l = miller_index[j]
X = (UB * (h, k, l)).rotate(axis, phi, deg=True)
s = s0 + X
g = s.cross(s0).normalize()
f = (s - s0).normalize()
# find component of beam perpendicular to f, e
e = - (s + s0).normalize()
if h == k and k == l:
u = (h, -h, 0)
else:
u = (k - l, l - h, h - k)
q = (matrix.col(u).transpose() * UB.inverse()).normalize(
).transpose().rotate(axis, phi, deg=True)
psi = q.angle(g, deg=True)
if q.dot(e) < 0:
psi *= -1
fout.write('%d %d %d %f %f %f %f %f %f %.1f %.1f %f\n' %
(h, k, l, I[j], sigI[j], x, y, z, scl[j], partiality[j], prof_corr[j], psi))
fout.write('!END_OF_DATA\n')
fout.close()
logger.info('Output %d reflections to %s' % (nref, hklout))
return
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 export_xds_ascii(integrated_data,
experiment_list,
hklout,
summation=False,
include_partials=False,
keep_partials=False,
var_model=(1, 0)):
'''Export data from integrated_data corresponding to experiment_list to
an XDS_ASCII.HKL formatted text file.'''
from dials.array_family import flex
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)
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]
# sort data before output
nref = len(integrated_data['miller_index'])
indices = flex.size_t_range(nref)
import copy
unique = copy.deepcopy(integrated_data['miller_index'])
from cctbx.miller import map_to_asu
map_to_asu(experiment.crystal.get_space_group().type(), False, unique)
perm = sorted(indices, key=lambda k: unique[k])
integrated_data = integrated_data.select(flex.size_t(perm))
from scitbx import matrix
from rstbx.cftbx.coordinate_frame_helpers import align_reference_frame
assert (not experiment.goniometer is None)
unit_cell = experiment.crystal.get_unit_cell()
from scitbx.array_family import flex
from math import floor, sqrt
assert (not experiment.scan is None)
image_range = experiment.scan.get_image_range()
phi_start, phi_range = experiment.scan.get_image_oscillation(
image_range[0])
# 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
# profile correlation
if 'profile.correlation' in integrated_data:
prof_corr = 100.0 * integrated_data['profile.correlation']
else:
prof_corr = flex.double(nref, 100.0)
# partiality
if 'partiality' in integrated_data:
partiality = 100 * integrated_data['partiality']
else:
prof_corr = flex.double(nref, 100.0)
if summation:
I = integrated_data['intensity.sum.value'] * scl
V = integrated_data['intensity.sum.variance'] * scl * scl
assert V.all_gt(0)
V = var_model[0] * (V + var_model[1] * I * I)
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)
V = var_model[0] * (V + var_model[1] * I * I)
sigI = flex.sqrt(V)
fout = open(hklout, 'w')
# first write the header - in the "standard" coordinate frame...
panel = experiment.detector[0]
fast = panel.get_fast_axis()
slow = panel.get_slow_axis()
Rd = align_reference_frame(fast, (1, 0, 0), slow, (0, 1, 0))
print 'Coordinate change:'
print '%5.2f %5.2f %5.2f\n%5.2f %5.2f %5.2f\n%5.2f %5.2f %5.2f\n' % Rd.elems
fast = Rd * fast
slow = Rd * slow
qx, qy = panel.get_pixel_size()
nx, ny = panel.get_image_size()
distance = matrix.col(Rd * panel.get_origin()).dot(
matrix.col(Rd * panel.get_normal()))
org = Rd * (matrix.col(panel.get_origin()) -
distance * matrix.col(panel.get_normal()))
orgx = -org.dot(fast) / qx
orgy = -org.dot(slow) / qy
UB = Rd * matrix.sqr(experiment.crystal.get_A())
real_space_ABC = UB.inverse().elems
axis = Rd * experiment.goniometer.get_rotation_axis()
beam = Rd * experiment.beam.get_s0()
cell_fmt = '%9.3f %9.3f %9.3f %7.3f %7.3f %7.3f'
axis_fmt = '%9.3f %9.3f %9.3f'
fout.write('\n'.join([
'!FORMAT=XDS_ASCII MERGE=FALSE FRIEDEL\'S_LAW=TRUE',
'!Generated by dials.export',
'!DATA_RANGE= %d %d' % image_range,
'!ROTATION_AXIS= %9.6f %9.6f %9.6f' % axis.elems,
'!OSCILLATION_RANGE= %f' % phi_range,
'!STARTING_ANGLE= %f' % phi_start,
'!STARTING_FRAME= %d' % image_range[0],
'!SPACE_GROUP_NUMBER= %d' %
experiment.crystal.get_space_group().type().number(),
'!UNIT_CELL_CONSTANTS= %s' % (cell_fmt % unit_cell.parameters()),
'!UNIT_CELL_A-AXIS= %s' % (axis_fmt % real_space_ABC[0:3]),
'!UNIT_CELL_B-AXIS= %s' % (axis_fmt % real_space_ABC[3:6]),
'!UNIT_CELL_C-AXIS= %s' % (axis_fmt % real_space_ABC[6:9]),
'!X-RAY_WAVELENGTH= %f' % experiment.beam.get_wavelength(),
'!INCIDENT_BEAM_DIRECTION= %f %f %f' % beam.elems,
'!NX= %d NY= %d QX= %f QY= %f' % (nx, ny, qx, qy),
'!ORGX= %9.2f ORGY= %9.2f' % (orgx, orgy),
'!DETECTOR_DISTANCE= %8.3f' % distance,
'!DIRECTION_OF_DETECTOR_X-AXIS= %9.5f %9.5f %9.5f' % fast.elems,
'!DIRECTION_OF_DETECTOR_Y-AXIS= %9.5f %9.5f %9.5f' % slow.elems,
'!VARIANCE_MODEL= %7.3e %7.3e' % var_model,
'!NUMBER_OF_ITEMS_IN_EACH_DATA_RECORD=12', '!ITEM_H=1', '!ITEM_K=2',
'!ITEM_L=3', '!ITEM_IOBS=4', '!ITEM_SIGMA(IOBS)=5', '!ITEM_XD=6',
'!ITEM_YD=7', '!ITEM_ZD=8', '!ITEM_RLP=9', '!ITEM_PEAK=10',
'!ITEM_CORR=11', '!ITEM_PSI=12', '!END_OF_HEADER', ''
]))
# then write the data records
s0 = Rd * matrix.col(experiment.beam.get_s0())
for j in range(nref):
x, y, z = integrated_data['xyzcal.px'][j]
phi = phi_start + z * phi_range
h, k, l = miller_index[j]
X = (UB * (h, k, l)).rotate(axis, phi, deg=True)
s = s0 + X
g = s.cross(s0).normalize()
f = (s - s0).normalize()
# find component of beam perpendicular to f, e
e = -(s + s0).normalize()
if h == k and k == l:
u = (h, -h, 0)
else:
u = (k - l, l - h, h - k)
q = (matrix.col(u).transpose() *
UB.inverse()).normalize().transpose().rotate(axis, phi, deg=True)
psi = q.angle(g, deg=True)
if q.dot(e) < 0:
psi *= -1
fout.write('%d %d %d %f %f %f %f %f %f %.1f %.1f %f\n' %
(h, k, l, I[j], sigI[j], x, y, z, scl[j], partiality[j],
prof_corr[j], psi))
fout.write('!END_OF_DATA\n')
fout.close()
logger.info('Output %d reflections to %s' % (nref, hklout))
return