def runSymRelax(params, cls):
print "processing class", cls
#set up cls dir
clsdir = cls.split('.')[0] + '.dir'
os.mkdir(clsdir)
# only align particles that passed coran
clscmd = 'clstoaligned.py -c ' + cls + ' --format=eman --clean\n\n'
# create projections of related symmetries
projcmd = "python <<eof\n"
projcmd += "import EMAN\n"
projcmd += "map3d = EMAN.EMData()\n"
projcmd += "map3d.readImage('../threed.%da.asym.mrc')\n" % (
params['iter'] - 1)
projcmd += "proj = EMAN.EMData()\n"
projcmd += "proj.readImage('proj.hed',%d)\n" % int(cls.split('.')[0][-4:])
projcmd += "e=proj.getEuler()\n"
projcmd += "e.setSym('" + params['sym'] + "')\n"
projcmd += "for s in range(e.getMaxSymEl()):\n"
projcmd += " ef = e.SymN(s)\n"
projcmd += " p = map3d.project3d(ef.alt(),ef.az(),ef.phi(),-1)\n"
projcmd += " p.setRAlign(ef)\n"
projcmd += " p.writeImage('%s',s)\n" % os.path.join(clsdir, 'proj.hed')
projcmd += "eof\n\n"
clscmd += projcmd
## if multiprocessor, don't run clstoaligned yet
if params['proc'] == 1:
#make aligned stack
proc = subprocess.Popen(clscmd, shell=True)
proc.wait()
relaxcmd = clscmd
# if no particles, continue
params['nptcls'] = apEMAN.getNPtcls(cls, onlycoran=True)
if params['nptcls'] == 0:
print "WARNING!! no particles in class"
return
emancmd = ("cd %s\n" % clsdir)
emancmd += "classesbymra aligned.hed proj.hed split mask=%d precen norot logit=1 maxshift=0 phase > classesbymra.log\n" % params[
'mask']
for s in range(params['symnum']):
emancmd += "proc2d aligned.hed classes.hed list=cls%04d.lst average\n" % s
## if multiprocessor, don't run yet
if params['proc'] == 1:
proc = subprocess.Popen(emancmd, shell=True)
proc.wait()
relaxcmd += emancmd
return relaxcmd
def runSymRelax(params,cls):
print "processing class",cls
#set up cls dir
clsdir=cls.split('.')[0]+'.dir'
os.mkdir(clsdir)
# only align particles that passed coran
clscmd='clstoaligned.py -c ' + cls + ' --format=eman --clean\n\n'
# create projections of related symmetries
projcmd = "python <<eof\n"
projcmd+= "import EMAN\n"
projcmd+= "map3d = EMAN.EMData()\n"
projcmd+= "map3d.readImage('../threed.%da.asym.mrc')\n" % (params['iter']-1)
projcmd+= "proj = EMAN.EMData()\n"
projcmd+= "proj.readImage('proj.hed',%d)\n" % int(cls.split('.')[0][-4:])
projcmd+= "e=proj.getEuler()\n"
projcmd+= "e.setSym('"+params['sym']+"')\n"
projcmd+= "for s in range(e.getMaxSymEl()):\n"
projcmd+= " ef = e.SymN(s)\n"
projcmd+= " p = map3d.project3d(ef.alt(),ef.az(),ef.phi(),-1)\n"
projcmd+= " p.setRAlign(ef)\n"
projcmd+= " p.writeImage('%s',s)\n" % os.path.join(clsdir,'proj.hed')
projcmd+= "eof\n\n"
clscmd+=projcmd
## if multiprocessor, don't run clstoaligned yet
if params['proc'] == 1:
#make aligned stack
proc = subprocess.Popen(clscmd, shell=True)
proc.wait()
relaxcmd=clscmd
# if no particles, continue
params['nptcls']=apEMAN.getNPtcls(cls,onlycoran=True)
if params['nptcls'] == 0:
print "WARNING!! no particles in class"
return
emancmd = ("cd %s\n" % clsdir)
emancmd+= "classesbymra aligned.hed proj.hed split mask=%d precen norot logit=1 maxshift=0 phase > classesbymra.log\n" % params['mask']
for s in range(params['symnum']):
emancmd+="proc2d aligned.hed classes.hed list=cls%04d.lst average\n" % s
## if multiprocessor, don't run yet
if params['proc'] == 1:
proc = subprocess.Popen(emancmd, shell=True)
proc.wait()
relaxcmd+=emancmd
return relaxcmd
f.close()
### order class averages in order of highest cc value
sortccindex = [
i for (i, j) in sorted(
enumerate(cclist), key=operator.itemgetter(1), reverse=True)
]
classnamepath = os.path.join(clsdir, 'classes')
for n in sortccindex:
## get N imgs
clhcbasename = 'clhc_cls' + string.zfill(n + 1, 4)
classname = os.path.join(classnamepath, clhcbasename + '.spi')
## save if has cc higher than cutoff
if cclist[n] > params['ccCutoff']:
cutofflist.append(n)
nptcls = apEMAN.getNPtcls(classname, spider=True)
apEMAN.writeImageToImage(os.path.join(clsdir, 'classes_avg.spi'),
n,
os.path.join(clsdir, 'sortavg.hed'),
particles=nptcls)
### if multiple classes have values higher than cutoff
if len(cutofflist) > 1:
print "combining " + str(len(cutofflist)) + " of " + str(
len(cclist)) + " classes"
spilist = []
for n in cutofflist:
clhcbasename = 'clhc_cls' + string.zfill(n + 1, 4)
classname = os.path.join(classnamepath, clhcbasename + '.spi')
spilist.append(classname)
classname = os.path.join(classnamepath, 'combined.spi')
f.write(str(ccval)+'\n') avg.setNImg(10) avg.setRAlign(e) f.close() ### order class averages in order of highest cc value sortccindex = [i for (i,j) in sorted(enumerate(cclist),key=operator.itemgetter(1),reverse=True)] classnamepath = os.path.join(clsdir,'classes') for n in sortccindex: ## get N imgs clhcbasename = 'clhc_cls'+string.zfill(n+1,4) classname=os.path.join(classnamepath, clhcbasename+'.spi') ## save if has cc higher than cutoff if cclist[n] > params['ccCutoff']: cutofflist.append(n) nptcls=apEMAN.getNPtcls(classname,spider=True) apEMAN.writeImageToImage(os.path.join(clsdir,'classes_avg.spi'),n,os.path.join(clsdir,'sortavg.hed'),particles=nptcls) ### if multiple classes have values higher than cutoff if len(cutofflist) > 1: print "combining "+str(len(cutofflist))+" of "+str(len(cclist))+" classes" spilist=[] for n in cutofflist: clhcbasename = 'clhc_cls'+string.zfill(n+1,4) classname=os.path.join(classnamepath, clhcbasename+'.spi') spilist.append(classname) classname=os.path.join(classnamepath,'combined.spi') apEMAN.combineSpiParticleList(spilist,classname) clhcbasename='combined' # convert spider lst to EMAN lst
apEMAN.writeBlankImage('newavgs.even.hed',params['boxsize'],-1)
apEMAN.writeBlankImage('newavgs.odd.hed',params['boxsize'],-1)
continue
avgname=os.path.join(clsdir,'classes.hed')
averages=EMAN.readImages(avgname,-1,-1,0)
projname=os.path.join(clsdir,'proj.hed')
projections=EMAN.readImages(projname,-1,-1,0)
for i in range(params['symnum']):
e=projections[i].getEuler()
projections[i].setNImg(-1)
projections[i].writeImage('newavgs.hed',-1)
#get N imgs
clslstname = os.path.join(clsdir,'cls%04d.lst' % i)
nptcls=apEMAN.getNPtcls(clslstname)
averages[i].setNImg(nptcls)
averages[i].setRAlign(e)
averages[i].writeImage('newavgs.hed',-1)
# convert spider lst to EMAN lst
#convertlst = apEMAN.convertSpiderToEMAN(classname,clslist[cls])
if params['eotest'] is True:
f = open(clslstname,'r')
f.readline()
lines=f.readlines()
f.close()
# set up even & odd lst files
evenlst = os.path.join(clsdir, 'cls%04d.even.lst' % i)
def runCoranClass(params,cls):
print "processing class",cls
#set up cls dir
clsdir=cls.split('.')[0]+'.dir'
os.mkdir(clsdir)
clscmd='clstoaligned.py -c ' + cls
## if multiprocessor, don't run clstoaligned yet
if params['proc'] == 1:
#make aligned stack
proc = subprocess.Popen(clscmd, shell=True)
proc.wait()
corancmd=clscmd+'\n'
coranbatch='coranfor'+cls.split('.')[0]+'.bat'
#make spider batch
params['nptcls'] = apEMAN.getNPtcls(cls)
# if no particles, create an empty class average
if params['nptcls'] == 0:
# don't run clscmd, just make directory and empty average
apEMAN.writeBlankImage(os.path.join(clsdir,'classes_avg.spi'),params['boxsize'],0,'spider')
print "WARNING!! no particles in class"
return
# if only 3 particles or less, turn particles into the class averages
elif params['nptcls'] < 4:
#this is an ugly hack, just average the particles together, no ref-free
# don't use mpi, just make directory with clscmd and average particles
proc = subprocess.Popen(clscmd, shell=True)
proc.wait()
avgcmd=("proc2d %s %s average" % (os.path.join(clsdir,'aligned.spi'),os.path.join(clsdir,'classes_avg.spi')))
proc = subprocess.Popen(avgcmd, shell=True)
proc.wait()
dummyclsdir=os.path.join(clsdir,'classes')
os.mkdir(dummyclsdir)
dummyfilename='clhc_cls0001.spi'
dummyfile=open(os.path.join(dummyclsdir,dummyfilename),'w')
dummyfile.write(';bat/spi\n')
for ptcl in range(0,params['nptcls']):
dummyfile.write('%d 1 %d\n' % (ptcl,ptcl+1))
dummyfile.close()
print "WARNING!! not enough particles in class for subclassification"
return
# otherwise, run coran
else:
makeSpiderCoranBatch(params,coranbatch,clsdir)
### this is how we should do this
#mySpider = spyder.SpiderSession(logo=False, nproc=1)
#mySpider.toSpiderQuiet("@%s\n" % coranbatch.split('.')[0])
spidercmd = ("cd %s\n" % clsdir)
if params['hp'] is not None:
spidercmd+=("proc2d aligned.spi alignedhp.spi spiderswap apix=%s hp=%s\n" % (params['apix'],params['hp']))
spidercmd+= ("spider bat/spi @%s\n" % coranbatch.split('.')[0])
## if multiprocessor, don't run spider yet
if params['proc'] == 1:
proc = subprocess.Popen(spidercmd, shell=True)
proc.wait()
corancmd+=spidercmd
return corancmd
def runCoranClass(params, cls):
print "processing class", cls
#set up cls dir
clsdir = cls.split('.')[0] + '.dir'
os.mkdir(clsdir)
clscmd = 'clstoaligned.py -c ' + cls
## if multiprocessor, don't run clstoaligned yet
if params['proc'] == 1:
#make aligned stack
proc = subprocess.Popen(clscmd, shell=True)
proc.wait()
corancmd = clscmd + '\n'
coranbatch = 'coranfor' + cls.split('.')[0] + '.bat'
#make spider batch
params['nptcls'] = apEMAN.getNPtcls(cls)
# if no particles, create an empty class average
if params['nptcls'] == 0:
# don't run clscmd, just make directory and empty average
apEMAN.writeBlankImage(os.path.join(clsdir, 'classes_avg.spi'),
params['boxsize'], 0, 'spider')
print "WARNING!! no particles in class"
return
# if only 3 particles or less, turn particles into the class averages
elif params['nptcls'] < 4:
#this is an ugly hack, just average the particles together, no ref-free
# don't use mpi, just make directory with clscmd and average particles
proc = subprocess.Popen(clscmd, shell=True)
proc.wait()
avgcmd = ("proc2d %s %s average" % (os.path.join(
clsdir, 'aligned.spi'), os.path.join(clsdir, 'classes_avg.spi')))
proc = subprocess.Popen(avgcmd, shell=True)
proc.wait()
dummyclsdir = os.path.join(clsdir, 'classes')
os.mkdir(dummyclsdir)
dummyfilename = 'clhc_cls0001.spi'
dummyfile = open(os.path.join(dummyclsdir, dummyfilename), 'w')
dummyfile.write(';bat/spi\n')
for ptcl in range(0, params['nptcls']):
dummyfile.write('%d 1 %d\n' % (ptcl, ptcl + 1))
dummyfile.close()
print "WARNING!! not enough particles in class for subclassification"
return
# otherwise, run coran
else:
makeSpiderCoranBatch(params, coranbatch, clsdir)
### this is how we should do this
#mySpider = spyder.SpiderSession(logo=False, nproc=1)
#mySpider.toSpiderQuiet("@%s\n" % coranbatch.split('.')[0])
spidercmd = ("cd %s\n" % clsdir)
if params['hp'] is not None:
spidercmd += (
"proc2d aligned.spi alignedhp.spi spiderswap apix=%s hp=%s\n" %
(params['apix'], params['hp']))
spidercmd += ("spider bat/spi @%s\n" % coranbatch.split('.')[0])
## if multiprocessor, don't run spider yet
if params['proc'] == 1:
proc = subprocess.Popen(spidercmd, shell=True)
proc.wait()
corancmd += spidercmd
return corancmd
