def tst_set_mosflm_beam_centre(detector):
from scitbx import matrix
from dxtbx.model import Beam
wavelength = 1
panel = detector[0]
detector_normal = matrix.col(panel.get_normal())
origin = matrix.col(panel.get_origin())
fast_axis = matrix.col(panel.get_fast_axis())
slow_axis = matrix.col(panel.get_slow_axis())
image_size = panel.get_image_size_mm()
s0 = (1.0/wavelength) * detector_normal
beam = Beam(-s0.normalize(), wavelength)
beam_centre = matrix.col(panel.get_beam_centre(beam.get_s0()))
origin_shift = matrix.col((1, 0.5))
new_beam_centre = beam_centre + origin_shift
new_mosflm_beam_centre = tuple(reversed(new_beam_centre))
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
set_mosflm_beam_centre(detector, beam, new_mosflm_beam_centre)
assert (matrix.col(panel.get_beam_centre(beam.get_s0())) -
matrix.col(tuple(reversed(new_mosflm_beam_centre)))).length() < 1e-6
print 'OK'
def set_beam_centre(self, beam_centre):
try:
set_mosflm_beam_centre(self.get_detector(), self.get_beam_obj(),
beam_centre)
self._fp_beam_prov = "user"
except AssertionError as e:
logger.debug("Error setting mosflm beam centre: %s" % e)
def tst_set_mosflm_beam_centre(detector):
from scitbx import matrix
from dxtbx.model import Beam
wavelength = 1
panel = detector[0]
detector_normal = matrix.col(panel.get_normal())
origin = matrix.col(panel.get_origin())
fast_axis = matrix.col(panel.get_fast_axis())
slow_axis = matrix.col(panel.get_slow_axis())
image_size = panel.get_image_size_mm()
s0 = (1.0 / wavelength) * detector_normal
beam = Beam(-s0.normalize(), wavelength)
beam_centre = matrix.col(panel.get_beam_centre(beam.get_s0()))
origin_shift = matrix.col((1, 0.5))
new_beam_centre = beam_centre + origin_shift
new_mosflm_beam_centre = tuple(reversed(new_beam_centre))
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
set_mosflm_beam_centre(detector, beam, new_mosflm_beam_centre)
assert (matrix.col(panel.get_beam_centre(beam.get_s0())) - matrix.col(
tuple(reversed(new_mosflm_beam_centre)))).length() < 1e-6
def test_set_mosflm_beam_centre(detector):
wavelength = 1.0
panel = detector[0]
detector_normal = matrix.col(panel.get_normal())
_ = matrix.col(panel.get_origin())
_ = matrix.col(panel.get_fast_axis())
_ = matrix.col(panel.get_slow_axis())
_ = panel.get_image_size_mm()
s0 = (1.0 / wavelength) * detector_normal
beam = Beam(-s0.normalize(), wavelength)
beam_centre = matrix.col(panel.get_beam_centre(beam.get_s0()))
origin_shift = matrix.col((1, 0.5))
new_beam_centre = beam_centre + origin_shift
new_mosflm_beam_centre = tuple(reversed(new_beam_centre))
set_mosflm_beam_centre(detector, beam, new_mosflm_beam_centre)
assert (
matrix.col(panel.get_beam_centre(beam.get_s0()))
- matrix.col(tuple(reversed(new_mosflm_beam_centre)))
).length() < 1e-6
# test resolution methods
beam = Beam(direction=(0, 0, 1), wavelength=1.0)
d_min1 = detector.get_max_resolution(beam.get_s0())
d_min2 = detector.get_max_inscribed_resolution(beam.get_s0())
assert d_min1 < d_min2
def set_beam_centre(self, beam_centre):
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
try:
set_mosflm_beam_centre(self.get_detector(), self.get_beam_obj(),
beam_centre)
self._fp_beam_prov = 'user'
except AssertionError as e:
Debug.write('Error setting mosflm beam centre: %s' % e)
def set_beam_centre(self, beam_centre):
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
try:
set_mosflm_beam_centre(self.get_detector(),
self.get_beam_obj(),
beam_centre)
self._fp_beam_prov = 'user'
except AssertionError, e:
Debug.write('Error setting mosflm beam centre: %s' % e)
def __call__(self, imageset):
'''
Replace the geometry
'''
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
set_mosflm_beam_centre(
imageset.get_detector(),
imageset.get_beam(),
self.params.geometry.mosflm_beam_centre)
return imageset
def __call__(self, imageset):
'''
Replace the geometry
'''
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
set_mosflm_beam_centre(
imageset.get_detector(),
imageset.get_beam(),
self.params.geometry.mosflm_beam_centre)
return imageset
def from_phil(params, reference=None, beam=None):
"""
Convert phil parameters into detector model
"""
from dxtbx.model.detector_helpers import set_detector_distance
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
from dxtbx.model.detector_helpers import set_slow_fast_beam_centre_mm
# Check the input. If no reference detector is provided then
# Create the detector model from scratch from the parameters
if reference is None:
detector = DetectorFactory.generate_from_phil(params, beam)
else:
detector = DetectorFactory.overwrite_from_phil(
params, reference, beam)
# If the distance is set
if params.detector.distance is not None:
set_detector_distance(detector, params.detector.distance)
# If the mosflm beam centre is set then update
if params.detector.mosflm_beam_centre is not None:
assert beam is not None
set_mosflm_beam_centre(detector, beam,
params.detector.mosflm_beam_centre)
# If the slow fast beam centre is set then update
if params.detector.slow_fast_beam_centre is not None:
panel_id = 0
if len(params.detector.slow_fast_beam_centre) > 2:
panel_id = params.detector.slow_fast_beam_centre[2]
if panel_id >= len(detector):
from libtbx.utils import Sorry
raise Sorry(
"Detector does not have panel index {0}".format(panel_id))
px_size_f, px_size_s = detector[0].get_pixel_size()
slow_fast_beam_centre_mm = (
params.detector.slow_fast_beam_centre[0] * px_size_s,
params.detector.slow_fast_beam_centre[1] * px_size_f,
)
assert beam is not None
set_slow_fast_beam_centre_mm(detector,
beam,
slow_fast_beam_centre_mm,
panel_id=panel_id)
# Return the model
return detector
def update_settings(self, *args, **kwds):
detector = self.imagesets[0].get_detector()
beam = self.imagesets[0].get_beam()
s0 = beam.get_s0()
try:
panel_id, beam_centre = detector.get_ray_intersection(beam.get_s0())
except RuntimeError:
pass
else:
if self.settings.beam_centre != beam_centre:
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
set_mosflm_beam_centre(detector, beam, tuple(reversed(
self.settings.beam_centre)))
self.imagesets[0].set_detector(detector)
self.imagesets[0].set_beam(beam)
self.map_points_to_reciprocal_space()
self.set_points()
self.viewer.update_settings(*args, **kwds)
def update_settings(self, *args, **kwds):
detector = self.imagesets[0].get_detector()
beam = self.imagesets[0].get_beam()
s0 = beam.get_s0()
try:
panel_id, beam_centre = detector.get_ray_intersection(
beam.get_s0())
except RuntimeError:
pass
else:
if self.settings.beam_centre != beam_centre:
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
set_mosflm_beam_centre(
detector, beam, tuple(reversed(self.settings.beam_centre)))
self.imagesets[0].set_detector(detector)
self.imagesets[0].set_beam(beam)
self.map_points_to_reciprocal_space()
self.set_points()
self.viewer.update_settings(*args, **kwds)
def from_phil(params, reference=None, beam=None):
'''
Convert phil parameters into detector model
'''
from dxtbx.model.detector_helpers import set_detector_distance
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
# Check the input. If no reference detector is provided then
# Create the detector model from scratch from the parameters
if reference is None:
detector = DetectorFactory.generate_from_phil(params, beam)
else:
detector = DetectorFactory.overwrite_from_phil(
params, reference, beam)
# If the distance is set
if params.detector.distance is not None:
set_detector_distance(detector, params.detector.distance)
# If the mosflm beam centre is set then update
if params.detector.mosflm_beam_centre is not None:
assert beam is not None
set_mosflm_beam_centre(detector, beam,
params.detector.mosflm_beam_centre)
# If the slow fast beam centre is set then update
if params.detector.slow_fast_beam_centre is not None:
assert beam is not None
beam_s, beam_f = params.detector.slow_fast_beam_centre[0:2]
pnl = 0
if len(params.detector.slow_fast_beam_centre) > 2:
pnl = params.detector.slow_fast_beam_centre[2]
try:
p = detector[pnl]
except RuntimeError:
raise Sorry(
'Detector does not have panel index {0}'.format(pnl))
beam.set_unit_s0(p.get_pixel_lab_coord((beam_f, beam_s)))
# Return the model
return detector
def load_models(self, imagesets, reflections):
self.imagesets = imagesets
self.reflections_input = reflections
if self.imagesets[0].get_goniometer() is not None:
self.viewer.set_rotation_axis(
self.imagesets[0].get_goniometer().get_rotation_axis())
self.viewer.set_beam_vector(self.imagesets[0].get_beam().get_s0())
detector = self.imagesets[0].get_detector()
beam = self.imagesets[0].get_beam()
if self.settings.beam_centre is None:
try:
panel_id, self.settings.beam_centre \
= detector.get_ray_intersection(beam.get_s0())
except RuntimeError:
pass
else:
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
set_mosflm_beam_centre(detector, beam,
tuple(reversed(self.settings.beam_centre)))
self.map_points_to_reciprocal_space()
self.set_points()
def load_models(self, imagesets, reflections):
self.imagesets = imagesets
self.reflections_input = reflections
if self.imagesets[0].get_goniometer() is not None:
self.viewer.set_rotation_axis(
self.imagesets[0].get_goniometer().get_rotation_axis())
self.viewer.set_beam_vector(self.imagesets[0].get_beam().get_s0())
detector = self.imagesets[0].get_detector()
beam = self.imagesets[0].get_beam()
if self.settings.beam_centre is None:
try:
panel_id, self.settings.beam_centre \
= detector.get_ray_intersection(beam.get_s0())
except RuntimeError:
pass
else:
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
set_mosflm_beam_centre(detector, beam, tuple(reversed(
self.settings.beam_centre)))
self.map_points_to_reciprocal_space()
self.set_points()
def __init__(
self,
name,
wavelength,
sample,
directory=None,
image=None,
beam=None,
reversephi=False,
distance=None,
gain=0.0,
dmin=0.0,
dmax=0.0,
polarization=0.0,
frames_to_process=None,
user_lattice=None,
user_cell=None,
epoch=0,
ice=False,
excluded_regions=None,
):
"""Create a new sweep named name, belonging to XWavelength object
wavelength, representing the images in directory starting with image,
with beam centre optionally defined."""
if excluded_regions is None:
excluded_regions = []
# FIXME bug 2221 if DIRECTORY starts with ~/ or ~graeme (say) need to
# interpret this properly - e.g. map it to a full PATH.
directory = expand_path(directory)
self._name = name
self._wavelength = wavelength
self.sample = sample
self._directory = directory
self._image = image
self._reversephi = reversephi
self._epoch = epoch
self._user_lattice = user_lattice
self._user_cell = user_cell
self._header = {}
self._resolution_high = dmin
self._resolution_low = dmax
self._ice = ice
self._excluded_regions = excluded_regions
self._imageset = None
# FIXME in here also need to be able to accumulate the total
# dose from all experimental measurements (complex) and provide
# a _epoch_to_dose dictionary or some such... may be fiddly as
# this will need to parse across multiple templates. c/f Bug # 2798
self._epoch_to_image = {}
self._image_to_epoch = {}
# to allow first, last image for processing to be
# set... c/f integrater interface
self._frames_to_process = frames_to_process
# + derive template, list of images
params = PhilIndex.get_python_object()
if directory and image:
self._template, self._directory = image2template_directory(
os.path.join(directory, image))
from xia2.Schema import load_imagesets
imagesets = load_imagesets(
self._template,
self._directory,
image_range=self._frames_to_process,
reversephi=(params.xia2.settings.input.reverse_phi
or self._reversephi),
)
assert len(
imagesets
) == 1, "one imageset expected, %d found" % len(imagesets)
self._imageset = copy.deepcopy(imagesets[0])
start, end = self._imageset.get_array_range()
self._images = list(range(start + 1, end + 1))
# FIXME in here check that (1) the list of images is continuous
# and (2) that all of the images are readable. This should also
# take into account frames_to_process if set.
if self._frames_to_process is None:
self._frames_to_process = min(self._images), max(self._images)
start, end = self._frames_to_process
error = False
if params.general.check_image_files_readable:
for j in range(start, end + 1):
if j not in self._images:
logger.debug("image %i missing for %s" %
(j, self.get_imageset().get_template()))
error = True
continue
image_name = self.get_imageset().get_path(j - start)
if not os.access(image_name, os.R_OK):
logger.debug("image %s unreadable" % image_name)
error = True
continue
if error:
raise RuntimeError("problem with sweep %s" % self._name)
beam_ = self._imageset.get_beam()
scan = self._imageset.get_scan()
if wavelength is not None:
# If the wavelength value is 0.0 then first set it to the header
# value - note that this assumes that the header value is correct
# (a reasonable assumption)
if wavelength.get_wavelength() == 0.0:
wavelength.set_wavelength(beam_.get_wavelength())
# FIXME 08/DEC/06 in here need to allow for the fact
# that the wavelength in the image header could be wrong and
# in fact it should be replaced with the input value -
# through the user will need to be warned of this and
# also everything using the FrameProcessor interface
# will also have to respect this!
if (math.fabs(beam_.get_wavelength() -
wavelength.get_wavelength()) > 0.0001):
logger.info(
"Header wavelength for sweep %s different"
" to assigned value (%4.2f vs. %4.2f)",
name,
beam_.get_wavelength(),
wavelength.get_wavelength(),
)
# also in here look at the image headers to see if we can
# construct a mapping between exposure epoch and image ...
images = []
if self._frames_to_process:
start, end = self._frames_to_process
for j in self._images:
if j >= start and j <= end:
images.append(j)
else:
images = self._images
for j in images:
epoch = scan.get_image_epoch(j)
if epoch == 0.0:
epoch = float(
os.stat(self._imageset.get_path(j -
images[0])).st_mtime)
self._epoch_to_image[epoch] = j
self._image_to_epoch[j] = epoch
epochs = self._epoch_to_image
logger.debug("Exposure epoch for sweep %s: %d %d" %
(self._template, min(epochs), max(epochs)))
self._input_imageset = copy.deepcopy(self._imageset)
# + get the lattice - can this be a pointer, so that when
# this object updates lattice it is globally-for-this-crystal
# updated? The lattice included directly in here includes an
# exact unit cell for data reduction, the crystal lattice
# contains an approximate unit cell which should be
# from the unit cells from all sweeps contained in the
# XCrystal. FIXME should I be using a LatticeInfo object
# in here? See what the Indexer interface produces. ALT:
# just provide an Indexer implementation "hook".
# See Headnote 001 above. See also _get_indexer,
# _get_integrater below.
self._indexer = None
self._refiner = None
self._integrater = None
# I don't need this - it is equivalent to self.getWavelength(
# ).getCrystal().getLattice()
# self._crystal_lattice = None
# this means that this module will have to present largely the
# same interface as Indexer and Integrater so that the calls
# can be appropriately forwarded.
# finally configure the beam if set
if beam is not None:
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
try:
set_mosflm_beam_centre(
self.get_imageset().get_detector(),
self.get_imageset().get_beam(),
beam,
)
except AssertionError as e:
logger.debug("Error setting mosflm beam centre: %s" % e)
self._beam_centre = beam
self._distance = distance
self._gain = gain
self._polarization = polarization
self._add_detector_identification_to_cif()
def _index(self):
'''Actually index the diffraction pattern. Note well that
this is not going to compute the matrix...'''
# acknowledge this program
Citations.cite('labelit')
Citations.cite('distl')
#self.reset()
_images = []
for i in self._indxr_images:
for j in i:
if not j in _images:
_images.append(j)
_images.sort()
images_str = '%d' % _images[0]
for i in _images[1:]:
images_str += ', %d' % i
cell_str = None
if self._indxr_input_cell:
cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % \
self._indxr_input_cell
if self._indxr_sweep_name:
# then this is a proper autoindexing run - describe this
# to the journal entry
#if len(self._fp_directory) <= 50:
#dirname = self._fp_directory
#else:
#dirname = '...%s' % self._fp_directory[-46:]
dirname = os.path.dirname(self.get_imageset().get_template())
Journal.block(
'autoindexing', self._indxr_sweep_name, 'labelit', {
'images': images_str,
'target cell': cell_str,
'target lattice': self._indxr_input_lattice,
'template': self.get_imageset().get_template(),
'directory': dirname
})
if len(_images) > 4:
raise RuntimeError('cannot use more than 4 images')
from xia2.Wrappers.Labelit.LabelitIndex import LabelitIndex
index = LabelitIndex()
index.set_working_directory(self.get_working_directory())
auto_logfiler(index)
#task = 'Autoindex from images:'
#for i in _images:
#task += ' %s' % self.get_image_name(i)
#self.set_task(task)
Debug.write('Indexing from images:')
for i in _images:
index.add_image(self.get_image_name(i))
Debug.write('%s' % self.get_image_name(i))
xsweep = self.get_indexer_sweep()
if xsweep is not None:
if xsweep.get_distance() is not None:
index.set_distance(xsweep.get_distance())
#if self.get_wavelength_prov() == 'user':
#index.set_wavelength(self.get_wavelength())
if xsweep.get_beam_centre() is not None:
index.set_beam_centre(xsweep.get_beam_centre())
if self._refine_beam is False:
index.set_refine_beam(False)
else:
index.set_refine_beam(True)
index.set_beam_search_scope(self._beam_search_scope)
if ((math.fabs(self.get_wavelength() - 1.54) < 0.01)
or (math.fabs(self.get_wavelength() - 2.29) < 0.01)):
index.set_Cu_KA_or_Cr_KA(True)
#sweep = self.get_indexer_sweep_name()
#FileHandler.record_log_file(
#'%s INDEX' % (sweep), self.get_log_file())
try:
index.run()
except RuntimeError as e:
if self._refine_beam is False:
raise e
# can we improve the situation?
if self._beam_search_scope < 4.0:
self._beam_search_scope += 4.0
# try repeating the indexing!
self.set_indexer_done(False)
return 'failed'
# otherwise this is beyond redemption
raise e
self._solutions = index.get_solutions()
# FIXME this needs to check the smilie status e.g.
# ":)" or ";(" or " ".
# FIXME need to check the value of the RMSD and raise an
# exception if the P1 solution has an RMSD > 1.0...
# Change 27/FEB/08 to support user assigned spacegroups
# (euugh!) have to "ignore" solutions with higher symmetry
# otherwise the rest of xia will override us. Bummer.
for i, solution in self._solutions.iteritems():
if self._indxr_user_input_lattice:
if (lattice_to_spacegroup(solution['lattice']) >
lattice_to_spacegroup(self._indxr_input_lattice)):
Debug.write('Ignoring solution: %s' % solution['lattice'])
del self._solutions[i]
# check the RMSD from the triclinic unit cell
if self._solutions[1]['rmsd'] > 1.0 and False:
# don't know when this is useful - but I know when it is not!
raise RuntimeError('high RMSD for triclinic solution')
# configure the "right" solution
self._solution = self.get_solution()
# now store also all of the other solutions... keyed by the
# lattice - however these should only be added if they
# have a smiley in the appropriate record, perhaps?
for solution in self._solutions.keys():
lattice = self._solutions[solution]['lattice']
if lattice in self._indxr_other_lattice_cell:
if self._indxr_other_lattice_cell[lattice]['goodness'] < \
self._solutions[solution]['metric']:
continue
self._indxr_other_lattice_cell[lattice] = {
'goodness': self._solutions[solution]['metric'],
'cell': self._solutions[solution]['cell']
}
self._indxr_lattice = self._solution['lattice']
self._indxr_cell = tuple(self._solution['cell'])
self._indxr_mosaic = self._solution['mosaic']
lms = LabelitMosflmScript()
lms.set_working_directory(self.get_working_directory())
lms.set_solution(self._solution['number'])
self._indxr_payload['mosflm_orientation_matrix'] = lms.calculate()
# get the beam centre from the mosflm script - mosflm
# may have inverted the beam centre and labelit will know
# this!
mosflm_beam_centre = lms.get_mosflm_beam()
if mosflm_beam_centre:
self._indxr_payload['mosflm_beam_centre'] = tuple(
mosflm_beam_centre)
import copy
detector = copy.deepcopy(self.get_detector())
beam = copy.deepcopy(self.get_beam())
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
set_mosflm_beam_centre(detector, beam, mosflm_beam_centre)
from xia2.Experts.SymmetryExpert import lattice_to_spacegroup_number
from scitbx import matrix
from cctbx import sgtbx, uctbx
from dxtbx.model import CrystalFactory
mosflm_matrix = matrix.sqr([
float(i) for line in lms.calculate()
for i in line.replace("-", " -").split()
][:9])
space_group = sgtbx.space_group_info(
lattice_to_spacegroup_number(self._solution['lattice'])).group()
crystal_model = CrystalFactory.from_mosflm_matrix(
mosflm_matrix,
unit_cell=uctbx.unit_cell(tuple(self._solution['cell'])),
space_group=space_group)
from dxtbx.model import Experiment, ExperimentList
experiment = Experiment(
beam=beam,
detector=detector,
goniometer=self.get_goniometer(),
scan=self.get_scan(),
crystal=crystal_model,
)
experiment_list = ExperimentList([experiment])
self.set_indexer_experiment_list(experiment_list)
# also get an estimate of the resolution limit from the
# labelit.stats_distl output... FIXME the name is wrong!
lsd = LabelitStats_distl()
lsd.set_working_directory(self.get_working_directory())
lsd.stats_distl()
resolution = 1.0e6
for i in _images:
stats = lsd.get_statistics(self.get_image_name(i))
resol = 0.5 * (stats['resol_one'] + stats['resol_two'])
if resol < resolution:
resolution = resol
self._indxr_resolution_estimate = resolution
return 'ok'
def _index(self):
"""Actually index the diffraction pattern. Note well that
this is not going to compute the matrix..."""
# acknowledge this program
if not self._indxr_images:
raise RuntimeError("No good spots found on any images")
Citations.cite("labelit")
Citations.cite("distl")
_images = []
for i in self._indxr_images:
for j in i:
if not j in _images:
_images.append(j)
_images.sort()
images_str = "%d" % _images[0]
for i in _images[1:]:
images_str += ", %d" % i
cell_str = None
if self._indxr_input_cell:
cell_str = "%.2f %.2f %.2f %.2f %.2f %.2f" % self._indxr_input_cell
if self._indxr_sweep_name:
# then this is a proper autoindexing run - describe this
# to the journal entry
if len(self._fp_directory) <= 50:
dirname = self._fp_directory
else:
dirname = "...%s" % self._fp_directory[-46:]
Journal.block(
"autoindexing",
self._indxr_sweep_name,
"labelit",
{
"images": images_str,
"target cell": cell_str,
"target lattice": self._indxr_input_lattice,
"template": self._fp_template,
"directory": dirname,
},
)
# auto_logfiler(self)
from xia2.Wrappers.Labelit.LabelitIndex import LabelitIndex
index = LabelitIndex()
index.set_working_directory(self.get_working_directory())
auto_logfiler(index)
# task = 'Autoindex from images:'
# for i in _images:
# task += ' %s' % self.get_image_name(i)
# self.set_task(task)
# self.add_command_line('--index_only')
Debug.write("Indexing from images:")
for i in _images:
index.add_image(self.get_image_name(i))
Debug.write("%s" % self.get_image_name(i))
if self._primitive_unit_cell:
index.set_primitive_unit_cell(self._primitive_unit_cell)
if self._indxr_input_cell:
index.set_max_cell(1.25 * max(self._indxr_input_cell[:3]))
xsweep = self.get_indexer_sweep()
if xsweep is not None:
if xsweep.get_distance() is not None:
index.set_distance(xsweep.get_distance())
# if self.get_wavelength_prov() == 'user':
# index.set_wavelength(self.get_wavelength())
if xsweep.get_beam_centre() is not None:
index.set_beam_centre(xsweep.get_beam_centre())
if self._refine_beam is False:
index.set_refine_beam(False)
else:
index.set_refine_beam(True)
index.set_beam_search_scope(self._beam_search_scope)
if (math.fabs(self.get_wavelength() - 1.54) <
0.01) or (math.fabs(self.get_wavelength() - 2.29) < 0.01):
index.set_Cu_KA_or_Cr_KA(True)
try:
index.run()
except RuntimeError as e:
if self._refine_beam is False:
raise e
# can we improve the situation?
if self._beam_search_scope < 4.0:
self._beam_search_scope += 4.0
# try repeating the indexing!
self.set_indexer_done(False)
return "failed"
# otherwise this is beyond redemption
raise e
self._solutions = index.get_solutions()
# FIXME this needs to check the smilie status e.g.
# ":)" or ";(" or " ".
# FIXME need to check the value of the RMSD and raise an
# exception if the P1 solution has an RMSD > 1.0...
# Change 27/FEB/08 to support user assigned spacegroups
# (euugh!) have to "ignore" solutions with higher symmetry
# otherwise the rest of xia will override us. Bummer.
for i, solution in self._solutions.iteritems():
if self._indxr_user_input_lattice:
if lattice_to_spacegroup(
solution["lattice"]) > lattice_to_spacegroup(
self._indxr_input_lattice):
Debug.write("Ignoring solution: %s" % solution["lattice"])
del self._solutions[i]
# configure the "right" solution
self._solution = self.get_solution()
# now store also all of the other solutions... keyed by the
# lattice - however these should only be added if they
# have a smiley in the appropriate record, perhaps?
for solution in self._solutions.keys():
lattice = self._solutions[solution]["lattice"]
if lattice in self._indxr_other_lattice_cell:
if (self._indxr_other_lattice_cell[lattice]["goodness"] <
self._solutions[solution]["metric"]):
continue
self._indxr_other_lattice_cell[lattice] = {
"goodness": self._solutions[solution]["metric"],
"cell": self._solutions[solution]["cell"],
}
self._indxr_lattice = self._solution["lattice"]
self._indxr_cell = tuple(self._solution["cell"])
self._indxr_mosaic = self._solution["mosaic"]
lms = LabelitMosflmMatrix()
lms.set_working_directory(self.get_working_directory())
lms.set_solution(self._solution["number"])
self._indxr_payload["mosflm_orientation_matrix"] = lms.calculate()
# get the beam centre from the mosflm script - mosflm
# may have inverted the beam centre and labelit will know
# this!
mosflm_beam_centre = lms.get_mosflm_beam()
if mosflm_beam_centre:
self._indxr_payload["mosflm_beam_centre"] = tuple(
mosflm_beam_centre)
detector = copy.deepcopy(self.get_detector())
beam = copy.deepcopy(self.get_beam())
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
set_mosflm_beam_centre(detector, beam, mosflm_beam_centre)
from xia2.Experts.SymmetryExpert import lattice_to_spacegroup_number
from scitbx import matrix
from cctbx import sgtbx, uctbx
from dxtbx.model import CrystalFactory
mosflm_matrix = matrix.sqr([
float(i) for line in lms.calculate()
for i in line.replace("-", " -").split()
][:9])
space_group = sgtbx.space_group_info(
lattice_to_spacegroup_number(self._solution["lattice"])).group()
crystal_model = CrystalFactory.from_mosflm_matrix(
mosflm_matrix,
unit_cell=uctbx.unit_cell(tuple(self._solution["cell"])),
space_group=space_group,
)
from dxtbx.model import Experiment, ExperimentList
experiment = Experiment(
beam=beam,
detector=detector,
goniometer=self.get_goniometer(),
scan=self.get_scan(),
crystal=crystal_model,
)
experiment_list = ExperimentList([experiment])
self.set_indexer_experiment_list(experiment_list)
# also get an estimate of the resolution limit from the
# labelit.stats_distl output... FIXME the name is wrong!
lsd = LabelitStats_distl()
lsd.set_working_directory(self.get_working_directory())
lsd.stats_distl()
resolution = 1.0e6
for i in _images:
stats = lsd.get_statistics(self.get_image_name(i))
resol = 0.5 * (stats["resol_one"] + stats["resol_two"])
if resol < resolution:
resolution = resol
self._indxr_resolution_estimate = resolution
return "ok"
def _mosflm_refine_cell(self, idxr, set_spacegroup=None):
'''Perform the refinement of the unit cell. This will populate
all of the information needed to perform the integration.'''
# FIXME this will die after #1285
#if not self.get_integrater_indexer():
#Debug.write('Replacing indexer of %s with self at %d' % \
#(str(self.get_integrater_indexer()), __line__))
#self.set_integrater_indexer(self)
#idxr = self.get_integrater_indexer()
if not idxr.get_indexer_payload('mosflm_orientation_matrix'):
raise RuntimeError('unexpected situation in indexing')
lattice = idxr.get_indexer_lattice()
mosaic = idxr.get_indexer_mosaic()
cell = idxr.get_indexer_cell()
beam_centre = idxr.get_indexer_beam_centre()
# bug # 3174 - if mosaic is very small (here defined to be
# 0.25 x osc_width) then set to this minimum value.
phi_width = idxr.get_phi_width()
if mosaic < 0.25 * phi_width:
mosaic = 0.25 * phi_width
if idxr.get_indexer_payload('mosflm_beam_centre'):
beam_centre = idxr.get_indexer_payload('mosflm_beam_centre')
distance = idxr.get_indexer_distance()
matrix = idxr.get_indexer_payload('mosflm_orientation_matrix')
integration_params = idxr.get_indexer_payload(
'mosflm_integration_parameters')
if integration_params is None:
integration_params = {}
if integration_params:
if 'separation' in integration_params:
self.set_refiner_parameter(
'mosflm', 'separation',
'%f %f' % tuple(integration_params['separation']))
if 'raster' in integration_params:
self.set_refiner_parameter(
'mosflm', 'raster',
'%d %d %d %d %d' % tuple(integration_params['raster']))
idxr.set_indexer_payload('mosflm_integration_parameters', None)
spacegroup_number = lattice_to_spacegroup(lattice)
# copy these into myself for later reference, if indexer
# is not myself - everything else is copied via the
# cell refinement process...
from cctbx import sgtbx
from dxtbx.model import Crystal
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
experiment = idxr.get_indexer_experiment_list()[0]
set_mosflm_beam_centre(experiment.detector, experiment.beam,
beam_centre)
space_group = sgtbx.space_group_info(number=spacegroup_number).group()
a, b, c = experiment.crystal.get_real_space_vectors()
experiment.crystal = Crystal(a, b, c, space_group=space_group)
# FIXME surely these have been assigned further up?!
if not self._mosflm_cell_ref_images:
self._mosflm_cell_ref_images = self._refine_select_images(mosaic)
f = open(
os.path.join(self.get_working_directory(),
'xiaindex-%s.mat' % lattice), 'w')
for m in matrix:
f.write(m)
f.close()
# then start the cell refinement
refiner = MosflmRefineCell()
refiner.set_working_directory(self.get_working_directory())
auto_logfiler(refiner)
if self._mosflm_gain:
refiner.set_gain(self._mosflm_gain)
refiner.set_template(os.path.basename(idxr.get_template()))
refiner.set_directory(idxr.get_directory())
refiner.set_input_mat_file('xiaindex-%s.mat' % lattice)
refiner.set_output_mat_file('xiarefine.mat')
refiner.set_beam_centre(beam_centre)
refiner.set_unit_cell(cell)
refiner.set_distance(distance)
if set_spacegroup:
refiner.set_space_group_number(set_spacegroup)
else:
refiner.set_space_group_number(spacegroup_number)
# FIXME 18/JUN/08 - it may help to have an overestimate
# of the mosaic spread in here as it *may* refine down
# better than up... - this is not a good idea as it may
# also not refine at all! - 12972 # integration failed
# Bug # 3103
if self._mosflm_cell_ref_double_mosaic:
mosaic *= 2.0
refiner.set_mosaic(mosaic)
# if set, use the resolution for cell refinement - see
# bug # 2078...
if self._mosflm_cell_ref_resolution:
refiner.set_resolution(self._mosflm_cell_ref_resolution)
refiner.set_fix_mosaic(self._mosflm_postref_fix_mosaic)
# note well that the beam centre is coming from indexing so
# should be already properly handled
#if idxr.get_wavelength_prov() == 'user':
#refiner.set_wavelength(idxr.get_wavelength())
# belt + braces mode - only to be used when considering failover,
# will run an additional step of autoindexing prior to cell
# refinement, to be used only after proving that not going it
# will result in cell refinement failure - will use the first
# wedge... N.B. this is only useful if the indexer is Labelit
# not Mosflm...
refiner.set_add_autoindex(self._mosflm_cell_ref_add_autoindex)
# get all of the stored parameter values
parameters = self.get_refiner_parameters('mosflm')
refiner.update_parameters(parameters)
detector = idxr.get_detector()
detector_width, detector_height = detector[0].get_image_size_mm()
lim_x = 0.5 * detector_width
lim_y = 0.5 * detector_height
Debug.write('Scanner limits: %.1f %.1f' % (lim_x, lim_y))
refiner.set_limits(lim_x, lim_y)
refiner.set_images(self._mosflm_cell_ref_images)
failover = PhilIndex.params.xia2.settings.failover
if failover and not self._mosflm_cell_ref_add_autoindex:
refiner.set_ignore_cell_refinement_failure(True)
refiner.run()
# then look to see if the cell refinement worked ok - if it
# didn't then this may indicate that the lattice was wrongly
# selected.
cell_refinement_ok = refiner.cell_refinement_ok()
if not cell_refinement_ok:
Debug.write('Repeating cell refinement...')
self.set_integrater_prepare_done(False)
self._mosflm_cell_ref_add_autoindex = True
return [0.0], [0.0]
rms_values = refiner.get_rms_values()
background_residual = refiner.get_background_residual()
self._refinr_cell = refiner.get_refined_unit_cell()
distance = refiner.get_refined_distance2()
experiment = idxr.get_indexer_experiment_list()[0]
from xia2.Wrappers.Mosflm.AutoindexHelpers import set_distance
set_distance(experiment.detector, distance)
self.set_refiner_parameter('mosflm', 'distortion yscale',
refiner.get_refined_distortion_yscale())
self.set_refiner_parameter('mosflm', 'raster', refiner.get_raster())
#integration_params['distortion yscale'] \
#= refiner.get_refined_distortion_yscale()
#integration_params['raster'] = refiner.get_raster()
separation = refiner.get_separation()
if separation is not None:
self.set_refiner_parameter('mosflm', 'separation',
'%s %s' % refiner.get_separation())
#integration_params['separation'] = refiner.get_separation()
self.set_refiner_parameter('mosflm', 'beam',
'%s %s' % refiner.get_refined_beam_centre())
self.set_refiner_parameter('mosflm', 'distance',
refiner.get_refined_distance())
self.set_refiner_parameter('mosflm', 'distortion tilt',
refiner.get_refined_distortion_tilt())
self.set_refiner_parameter('mosflm', 'distortion twist',
refiner.get_refined_distortion_twist())
integration_params['beam'] = tuple(
float(b) for b in refiner.get_refined_beam_centre())
integration_params['distance'] = refiner.get_refined_distance()
integration_params[
'distortion tilt'] = refiner.get_refined_distortion_tilt()
integration_params[
'distortion twist'] = refiner.get_refined_distortion_twist()
idxr._indxr_mosaic = refiner.get_refined_mosaic()
idxr.set_indexer_payload(
'mosflm_orientation_matrix',
open(os.path.join(self.get_working_directory(), 'xiarefine.mat'),
'r').readlines())
self.set_refiner_payload(
'mosflm_orientation_matrix',
idxr.get_indexer_payload('mosflm_orientation_matrix'))
self.set_refiner_payload('mosaic', refiner.get_refined_mosaic())
self.set_refiner_payload('beam', integration_params['beam'])
self.set_refiner_payload('distance', integration_params['distance'])
from xia2.Wrappers.Mosflm.AutoindexHelpers import crystal_model_from_mosflm_mat
# make a dxtbx crystal_model object from the mosflm matrix
experiment = idxr.get_indexer_experiment_list()[0]
crystal_model = crystal_model_from_mosflm_mat(
idxr._indxr_payload['mosflm_orientation_matrix'],
unit_cell=refiner.get_refined_unit_cell(),
space_group=experiment.crystal.get_space_group())
experiment.crystal = crystal_model
#self.set_refiner_payload(
#'mosflm_integration_parameters', integration_params)
self._refinr_refined_experiment_list = ExperimentList([experiment])
return rms_values, background_residual
def _index(self):
'''Implement the indexer interface.'''
Citations.cite('mosflm')
indexer = MosflmIndex()
indexer.set_working_directory(self.get_working_directory())
auto_logfiler(indexer)
from xia2.lib.bits import unique_elements
_images = unique_elements(self._indxr_images)
indexer.set_images(_images)
images_str = ', '.join(map(str, _images))
cell_str = None
if self._indxr_input_cell:
cell_str = '%.2f %.2f %.2f %.2f %.2f %.2f' % \
self._indxr_input_cell
if self._indxr_sweep_name:
#if len(self._fp_directory) <= 50:
#dirname = self._fp_directory
#else:
#dirname = '...%s' % self._fp_directory[-46:]
dirname = os.path.dirname(self.get_imageset().get_template())
Journal.block(
'autoindexing', self._indxr_sweep_name, 'mosflm', {
'images': images_str,
'target cell': self._indxr_input_cell,
'target lattice': self._indxr_input_lattice,
'template': self.get_imageset().get_template(),
'directory': dirname
})
#task = 'Autoindex from images:'
#for i in _images:
#task += ' %s' % self.get_image_name(i)
#self.set_task(task)
indexer.set_template(os.path.basename(self.get_template()))
indexer.set_directory(self.get_directory())
xsweep = self.get_indexer_sweep()
if xsweep is not None:
if xsweep.get_distance() is not None:
indexer.set_distance(xsweep.get_distance())
#if self.get_wavelength_prov() == 'user':
#index.set_wavelength(self.get_wavelength())
if xsweep.get_beam_centre() is not None:
indexer.set_beam_centre(xsweep.get_beam_centre())
if self._indxr_input_cell:
indexer.set_unit_cell(self._indxr_input_cell)
if self._indxr_input_lattice is not None:
spacegroup_number = lattice_to_spacegroup(
self._indxr_input_lattice)
indexer.set_space_group_number(spacegroup_number)
if not self._mosflm_autoindex_thresh:
try:
min_peaks = 200
Debug.write('Aiming for at least %d spots...' % min_peaks)
thresholds = []
for i in _images:
p = Printpeaks()
p.set_working_directory(self.get_working_directory())
auto_logfiler(p)
p.set_image(self.get_image_name(i))
thresh = p.threshold(min_peaks)
Debug.write('Autoindex threshold for image %d: %d' % \
(i, thresh))
thresholds.append(thresh)
thresh = min(thresholds)
self._mosflm_autoindex_thresh = thresh
except Exception as e:
print str(e) #XXX this should disappear!
Debug.write('Error computing threshold: %s' % str(e))
Debug.write('Using default of 20.0')
thresh = 20.0
else:
thresh = self._mosflm_autoindex_thresh
Debug.write('Using autoindex threshold: %d' % thresh)
if self._mosflm_autoindex_sol:
indexer.set_solution_number(self._mosflm_autoindex_sol)
indexer.set_threshold(thresh)
# now forget this to prevent weird things happening later on
if self._mosflm_autoindex_sol:
self._mosflm_autoindex_sol = 0
indexer.run()
indxr_cell = indexer.get_refined_unit_cell()
self._indxr_lattice = indexer.get_lattice()
space_group_number = indexer.get_indexed_space_group_number()
detector_distance = indexer.get_refined_distance()
beam_centre = indexer.get_refined_beam_centre()
mosaic_spreads = indexer.get_mosaic_spreads()
if min(list(indxr_cell)) < 10.0 and \
indxr_cell[2] / indxr_cell[0] > 6:
Debug.write('Unrealistic autoindexing solution: ' +
'%.2f %.2f %.2f %.2f %.2f %.2f' % indxr_cell)
# tweak some parameters and try again...
self._mosflm_autoindex_thresh *= 1.5
self.set_indexer_done(False)
return
intgr_params = {}
# look up other possible indexing solutions (not well - in
# standard settings only!) This is moved earlier as it could
# result in returning if Mosflm has selected the wrong
# solution!
try:
self._indxr_other_lattice_cell = indexer.get_solutions()
# Change 27/FEB/08 to support user assigned spacegroups
if self._indxr_user_input_lattice:
lattice_to_spacegroup_dict = {
'aP': 1,
'mP': 3,
'mC': 5,
'oP': 16,
'oC': 20,
'oF': 22,
'oI': 23,
'tP': 75,
'tI': 79,
'hP': 143,
'hR': 146,
'cP': 195,
'cF': 196,
'cI': 197
}
for k in self._indxr_other_lattice_cell.keys():
if lattice_to_spacegroup_dict[k] > \
lattice_to_spacegroup_dict[
self._indxr_input_lattice]:
del (self._indxr_other_lattice_cell[k])
# check that the selected unit cell matches - and if
# not raise a "horrible" exception
if self._indxr_input_cell:
assert indxr_cell is not None
for j in range(6):
if math.fabs(self._indxr_input_cell[j] -
indxr_cell[j]) > 2.0:
Chatter.write('Mosflm autoindexing did not select ' +
'correct (target) unit cell')
raise RuntimeError(
'something horrible happened in indexing')
except RuntimeError as e:
# check if mosflm rejected a solution we have it
if 'horribl' in str(e):
# ok it did - time to break out the big guns...
if not self._indxr_input_cell:
raise RuntimeError(
'error in solution selection when not preset')
# XXX FIXME
self._mosflm_autoindex_sol = _get_indexing_solution_number(
indexer.get_all_output(), self._indxr_input_cell,
self._indxr_input_lattice)
# set the fact that we are not done...
self.set_indexer_done(False)
# and return - hopefully this will restart everything
return
else:
raise e
if len(mosaic_spreads) == 0:
# then consider setting it do a default value...
# equal to the oscillation width (a good guess)
phi_width = self.get_phi_width()
Chatter.write(
'Mosaic estimation failed, so guessing at %4.2f' % \
phi_width)
# only consider this if we have thus far no idea on the
# mosaic spread...
mosaic_spreads.append(phi_width)
intgr_params['raster'] = indexer.get_raster()
intgr_params['separation'] = indexer.get_separation()
self._indxr_resolution_estimate = indexer.get_resolution_estimate()
# compute mosaic as mean(mosaic_spreads)
self._indxr_mosaic = sum(mosaic_spreads) / len(mosaic_spreads)
self._indxr_payload['mosflm_integration_parameters'] = intgr_params
self._indxr_payload['mosflm_orientation_matrix'] = open(
os.path.join(self.get_working_directory(), 'xiaindex.mat'),
'r').readlines()
import copy
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
from xia2.Wrappers.Mosflm.AutoindexHelpers import set_distance
from xia2.Wrappers.Mosflm.AutoindexHelpers import crystal_model_from_mosflm_mat
from cctbx import sgtbx, uctbx
# update the beam centre (i.e. shift the origin of the detector)
detector = copy.deepcopy(self.get_detector())
beam = copy.deepcopy(self.get_beam())
set_mosflm_beam_centre(detector, beam, beam_centre)
if detector_distance is not None:
set_distance(detector, detector_distance)
# make a dxtbx crystal_model object from the mosflm matrix
space_group = sgtbx.space_group_info(number=space_group_number).group()
crystal_model = crystal_model_from_mosflm_mat(
self._indxr_payload['mosflm_orientation_matrix'],
unit_cell=uctbx.unit_cell(tuple(indxr_cell)),
space_group=space_group)
# construct an experiment_list
from dxtbx.model import Experiment, ExperimentList
experiment = Experiment(beam=beam,
detector=detector,
goniometer=self.get_goniometer(),
scan=self.get_scan(),
crystal=crystal_model)
experiment_list = ExperimentList([experiment])
self.set_indexer_experiment_list(experiment_list)
def __init__(self, name,
wavelength,
sample,
directory = None,
image = None,
beam = None,
reversephi = False,
distance = None,
gain = 0.0,
dmin = 0.0,
dmax = 0.0,
polarization = 0.0,
frames_to_process = None,
user_lattice = None,
user_cell = None,
epoch = 0,
ice = False,
excluded_regions = None):
'''Create a new sweep named name, belonging to XWavelength object
wavelength, representing the images in directory starting with image,
with beam centre optionally defined.'''
if excluded_regions is None:
excluded_regions = []
# + check the wavelength is an XWavelength object
# raise an exception if not... or not...
if not wavelength.__class__.__name__ == 'XWavelength':
pass
# FIXME bug 2221 if DIRECTORY starts with ~/ or ~graeme (say) need to
# interpret this properly - e.g. map it to a full PATH.
directory = expand_path(directory)
self._name = name
self._wavelength = wavelength
self._sample = sample
self._directory = directory
self._image = image
self._reversephi = reversephi
self._epoch = epoch
self._user_lattice = user_lattice
self._user_cell = user_cell
self._header = { }
self._resolution_high = dmin
self._resolution_low = dmax
self._ice = ice
self._excluded_regions = excluded_regions
self._imageset = None
# FIXME in here also need to be able to accumulate the total
# dose from all experimental measurements (complex) and provide
# a _epoch_to_dose dictionary or some such... may be fiddly as
# this will need to parse across multiple templates. c/f Bug # 2798
self._epoch_to_image = { }
self._image_to_epoch = { }
# to allow first, last image for processing to be
# set... c/f integrater interface
self._frames_to_process = frames_to_process
# + derive template, list of images
params = PhilIndex.get_python_object()
if directory and image:
self._template, self._directory = \
image2template_directory(os.path.join(directory,
image))
from xia2.Schema import load_imagesets
imagesets = load_imagesets(
self._template, self._directory, image_range=self._frames_to_process,
reversephi=(params.xia2.settings.input.reverse_phi or self._reversephi))
assert len(imagesets) == 1, "one imageset expected, %d found" % \
len(imagesets)
self._imageset = copy.deepcopy(imagesets[0])
start, end = self._imageset.get_array_range()
self._images = list(range(start+1, end+1))
# FIXME in here check that (1) the list of images is continuous
# and (2) that all of the images are readable. This should also
# take into account frames_to_process if set.
if self._frames_to_process is None:
self._frames_to_process = min(self._images), max(self._images)
start, end = self._frames_to_process
error = False
if params.general.check_image_files_readable:
for j in range(start, end + 1):
image_name = self.get_imageset().get_path(j-start)
if not j in self._images:
Debug.write('image %s missing' %image_name)
error = True
continue
if not os.access(image_name, os.R_OK):
Debug.write('image %s unreadable' %image_name)
error = True
continue
if error:
raise RuntimeError, 'problem with sweep %s' % self._name
# + read the image header information into here?
# or don't I need it? it would be useful for checking
# against wavelength.getWavelength() I guess to make
# sure that the plumbing is all sound.
# check that they match by closer than 0.0001A, if wavelength
# is not None
beam_ = self._imageset.get_beam()
scan = self._imageset.get_scan()
if wavelength is not None:
# FIXME 29/NOV/06 if the wavelength wavelength value
# is 0.0 then first set it to the header value - note
# that this assumes that the header value is correct
# (a reasonable assumption)
if wavelength.get_wavelength() == 0.0:
wavelength.set_wavelength(beam_.get_wavelength())
# FIXME 08/DEC/06 in here need to allow for the fact
# that the wavelength in the image header could be wrong and
# in fact it should be replaced with the input value -
# through the user will need to be warned of this and
# also everything using the FrameProcessor interface
# will also have to respect this!
if math.fabs(beam_.get_wavelength() -
wavelength.get_wavelength()) > 0.0001:
# format = 'wavelength for sweep %s does not ' + \
# 'match wavelength %s'
# raise RuntimeError, format % \
# (name, wavelength.get_name())
format = 'Header wavelength for sweep %s different' + \
' to assigned value (%4.2f vs. %4.2f)'
Chatter.write(format % (name, beam_.get_wavelength(),
wavelength.get_wavelength()))
# also in here look at the image headers to see if we can
# construct a mapping between exposure epoch and image ...
images = []
if self._frames_to_process:
start, end = self._frames_to_process
for j in self._images:
if j >= start and j <= end:
images.append(j)
else:
images = self._images
for j in images:
epoch = scan.get_image_epoch(j)
if epoch == 0.0:
epoch = float(os.stat(self._imageset.get_path(j-images[0])).st_mtime)
self._epoch_to_image[epoch] = j
self._image_to_epoch[j] = epoch
epochs = self._epoch_to_image.keys()
Debug.write('Exposure epoch for sweep %s: %d %d' % \
(self._template, min(epochs), max(epochs)))
self._input_imageset = copy.deepcopy(self._imageset)
# + get the lattice - can this be a pointer, so that when
# this object updates lattice it is globally-for-this-crystal
# updated? The lattice included directly in here includes an
# exact unit cell for data reduction, the crystal lattice
# contains an approximate unit cell which should be
# from the unit cells from all sweeps contained in the
# XCrystal. FIXME should I be using a LatticeInfo object
# in here? See what the Indexer interface produces. ALT:
# just provide an Indexer implementation "hook".
# See Headnote 001 above. See also _get_indexer,
# _get_integrater below.
self._indexer = None
self._refiner = None
self._integrater = None
# I don't need this - it is equivalent to self.getWavelength(
# ).getCrystal().getLattice()
# self._crystal_lattice = None
# this means that this module will have to present largely the
# same interface as Indexer and Integrater so that the calls
# can be appropriately forwarded.
# finally configure the beam if set
if beam is not None:
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
try:
set_mosflm_beam_centre(self.get_imageset().get_detector(),
self.get_imageset().get_beam(),
beam)
except AssertionError, e:
Debug.write('Error setting mosflm beam centre: %s' % e)
