def analyze_one(self, solution):
inputpd = self.Org.process()
settings = pickle.load(open("LABELIT_possible", "rb"))
setting = [
setting for setting in settings if setting["counter"] == solution
][0]
from labelit.preferences import labelit_commands as param
pixel_size = float(inputpd['pixel_size'])
self.pixel_size = pixel_size
from labelit.dptbx import AutoIndexEngine, Parameters
ai = AutoIndexEngine(inputpd['endstation'])
P = Parameters(xbeam=setting["refined x beam"],
ybeam=setting["refined y beam"],
distance=setting["refined distance"],
twotheta=float(inputpd["twotheta"]))
ai.setBase(P)
ai.setWavelength(float(inputpd['wavelength']))
ai.setMaxcell(float(inputpd['ref_maxcel']))
print("Deltaphi is", float(inputpd['deltaphi']))
ai.setDeltaphi(float(inputpd['deltaphi']) * math.pi / 180.)
ai.setMosaicity(setting["mosaicity"])
ai.setOrientation(setting["orient"])
#why aren't hexagonal constraints applied here???
print(inputpd["osc_start"])
image_centers = [(math.pi / 180.) * float(x)
for x in inputpd["osc_start"].values()]
limiting_resolution = param.distl_highres_limit
print("Limiting resolution", limiting_resolution)
#predict the spots
spots = ai.predict_all(image_centers[0], limiting_resolution)
pre2m = spots.vec3()
self.pre2m = pre2m
hkllist = spots.hkl()
cell = ai.getOrientation().unit_cell()
print(cell)
for hkl in hkllist:
#print "%25s %5.2f"%(str(hkl),cell.d(hkl))
assert cell.d(hkl) >= limiting_resolution
print("Number of hkls:", (hkllist).size(), end=' ')
print("all inside the %4.2f Angstrom limiting sphere." %
limiting_resolution)
print("The unit cell is", cell)
self.solution_setting_ai = ai
self.solution_pd = inputpd
self.image_centers = image_centers
self.one_setting = setting
return [ai.getOrientation().unit_cell(), hkllist]
def analyze_one(self,solution):
inputpd = self.Org.process()
settings = pickle.load(open("LABELIT_possible","rb"))
setting = [setting for setting in settings if setting["counter"]==solution][0]
from labelit.preferences import labelit_commands as param
pixel_size = float(inputpd['pixel_size'])
self.pixel_size = pixel_size
from labelit.dptbx import AutoIndexEngine, Parameters
ai = AutoIndexEngine(inputpd['endstation'])
P = Parameters(xbeam=setting["refined x beam"],ybeam=setting["refined y beam"],
distance=setting["refined distance"],twotheta=float(inputpd["twotheta"]))
ai.setBase(P)
ai.setWavelength(float(inputpd['wavelength']))
ai.setMaxcell(float(inputpd['ref_maxcel']))
print "Deltaphi is",float(inputpd['deltaphi'])
ai.setDeltaphi(float(inputpd['deltaphi'])*math.pi/180.)
ai.setMosaicity(setting["mosaicity"])
ai.setOrientation(setting["orient"])
#why aren't hexagonal constraints applied here???
print inputpd["osc_start"]
image_centers = [(math.pi/180.)*float(x) for x in inputpd["osc_start"].values()]
limiting_resolution = param.distl_highres_limit
print "Limiting resolution",limiting_resolution
#predict the spots
spots = ai.predict_all(image_centers[0],limiting_resolution)
pre2m = spots.vec3()
self.pre2m = pre2m
hkllist = spots.hkl()
cell = ai.getOrientation().unit_cell()
print cell
for hkl in hkllist:
#print "%25s %5.2f"%(str(hkl),cell.d(hkl))
assert cell.d(hkl)>=limiting_resolution
print "Number of hkls:",(hkllist).size(),
print "all inside the %4.2f Angstrom limiting sphere."%limiting_resolution
print "The unit cell is",cell
self.solution_setting_ai = ai
self.solution_pd = inputpd
self.image_centers = image_centers
self.one_setting = setting
return [ai.getOrientation().unit_cell(),hkllist]
