classname=os.path.join(classnamepath,'combined.spi')
apEMAN.combineSpiParticleList(spilist,classname)
clhcbasename='combined'
# convert spider lst to EMAN lst
convertlst = apEMAN.convertSpiderToEMAN(classname,clslist[cls])
# change location of start file reference
f=open(convertlst,'r')
fnew = open(convertlst+'.tmp','w')
for l in f:
fnew.write(re.sub('\tstart','\t../../start',l))
f.close()
fnew.close()
os.rename(convertlst+'.tmp',convertlst)
apEMAN.makeClassAverages(convertlst,'goodavgs.hed',e,params['mask'])
### otherwise just use the best class average
else:
bestclass=cclist.index(max(cclist))
print "Using average %d for class %d" % (bestclass, cls)
#get N imgs
clhcbasename = 'clhc_cls'+string.zfill(bestclass+1,4)
classname=os.path.join(classnamepath, clhcbasename+'.spi')
nptcls=apEMAN.getNPtcls(classname,spider=True)
averages[bestclass].setNImg(nptcls)
averages[bestclass].setRAlign(e)
averages[bestclass].writeImage('goodavgs.hed',-1)
classname = os.path.join(classnamepath, 'combined.spi')
apEMAN.combineSpiParticleList(spilist, classname)
clhcbasename = 'combined'
# convert spider lst to EMAN lst
convertlst = apEMAN.convertSpiderToEMAN(classname, clslist[cls])
# change location of start file reference
f = open(convertlst, 'r')
fnew = open(convertlst + '.tmp', 'w')
for l in f:
fnew.write(re.sub('\tstart', '\t../../start', l))
f.close()
fnew.close()
os.rename(convertlst + '.tmp', convertlst)
apEMAN.makeClassAverages(convertlst, 'goodavgs.hed', e,
params['mask'])
### otherwise just use the best class average
else:
bestclass = cclist.index(max(cclist))
print "Using average %d for class %d" % (bestclass, cls)
#get N imgs
clhcbasename = 'clhc_cls' + string.zfill(bestclass + 1, 4)
classname = os.path.join(classnamepath, clhcbasename + '.spi')
nptcls = apEMAN.getNPtcls(classname, spider=True)
averages[bestclass].setNImg(nptcls)
averages[bestclass].setRAlign(e)
averages[bestclass].writeImage('goodavgs.hed', -1)
newline = re.sub('\tstart','\t../../start',lines[line])
if line%2:
nodd+=1
odd.write(newline)
else:
neven+=1
even.write(newline)
odd.close()
even.close()
# create even and odd class stacks
evenstack = 'newavgs.even.hed'
oddstack = 'newavgs.odd.hed'
if neven>0:
apEMAN.makeClassAverages(evenlst,evenstack,e,params['mask'])
if nodd>0:
apEMAN.makeClassAverages(oddlst,oddstack,e,params['mask'])
pad=int(params['boxsize']*1.25)
if pad%2:
pad=pad+1
# create 3d model:
make3dcommand='make3d newavgs.hed out=threed.%d.asym.mrc mask=%d sym=c1 pad=%d mode=2 hard=%d' % (params['iter'], params['mask'], pad, params['hard'])
apEMAN.writeEMANTime('../refine.log', make3dcommand)
print make3dcommand
proc = subprocess.Popen(make3dcommand, shell=True)
proc.wait()
