def process(work_params, spots, sampling_resolution_factor=0.5):
import libtbx.load_env
libtbx.env.require_module("labelit")
spots_high_res = get_spots_high_resolution(
work_params=work_params, spots=spots)
if (spots_high_res is None):
return
uc = work_params.unit_cell
uc_max_length = max(uc.parameters()[0:3])
sampling = sampling_resolution_factor * spots_high_res / uc_max_length
#
from labelit.preferences import labelit_commands
labelit_commands.model_refinement_minimum_N = 10
labelit_commands.target_cell = uc
print "labelit_commands.target_cell:", labelit_commands.target_cell
#
from scitbx.array_family import flex
raw_spot_input = flex.vec3_double()
dsx,dsy = work_params.detector.size
dpx,dpy = work_params.detector.pixels
sopx,sopy = dsx/dpx, dsy/dpy
for spot in spots: # XXX C++
x, y = spot.ctr_mass_x(), spot.ctr_mass_y()
raw_spot_input.append((x*sopx+0.5, y*sopy+0.5, 0.0))
#
from labelit.dptbx import AutoIndexEngine, Parameters
from iotbx.detectors.context.endstation import EndStation
ai = AutoIndexEngine(EndStation(), sampling)
ai.setData(raw_spot_input)
ai_params = Parameters(
xbeam=dsx/2,
ybeam=dsy/2,
distance=work_params.detector.distance,
twotheta=0.)
ai.setBase(ai_params)
ai.setWavelength(work_params.wavelength)
ai.setMaxcell(1.25*max(uc.parameters()[0:3]))
ai.setDeltaphi(0.0)
f = ai.film_to_camera()
c = ai.camera_to_xyz()
#
from labelit.dptbx.sampling import HemisphereSampler
hem_samp = HemisphereSampler(
max_grid=sampling,
characteristic_grid=sampling,
quick_grid=0.016) # all grid parameters in radians
hem_samp.hemisphere(
ai=ai, size=30, cutoff_divisor=4.) # never change these parameters
#
from labelit.dptbx.basis_choice import SelectBasisMetaprocedure
pd = {}
sbm = SelectBasisMetaprocedure(
input_index_engine=ai,
input_dictionary=pd,
opt_rawframes=False,
opt_target=True,
reduce_target=False)
ai.fixsign()
return ai
