def commitResultsToDB(self):
return
# -- Commit Parameters --
protomodata = apProTomo.insertProtomoParams(self.seriesname)
alignrun = apTomo.insertTomoAlignmentRun(self.sessiondata, None, None,
protomodata, None, 1,
self.params['runname'],
self.params['rundir'],
self.params['description'])
cycle_description = self.params['description']
# create refinement parameter dictionary
refinedict = apProTomo.createRefineDefaults(0, '', '', tmp='')
refinedict['alismp'] = self.params['sample']
refinedict['alibox_x'] = self.params['windowsize_x']
refinedict['alibox_y'] = self.params['windowsize_y']
refinedict['cormod'] = self.params['correlation_mode']
refinedict['imgref'] = self.params['refimg']
alignerdata = apProTomo.insertAlignIteration(
alignrun, protomodata, self.params, refinedict,
self.ordered_imagelist[self.refimg])
# -- Commit Results --
# Parse the results file which holds rotation and Correction Factors
correctionFactors = self.parseCorrectionFactors(
self.correctionFactorFile)
# commit the geometry parameters (psi, theta, phi, azimuth), not sure about this.
if correctionFactors is not None:
self.insertModel(alignerdata, correctionFactors)
# insert results into ApProtomoAlignmentData for each image
for i, imagedata in enumerate(self.ordered_imagelist):
try:
apProTomo.insertTiltAlignment(alignerdata, imagedata, i,
correctionFactors[i],
self.center)
except:
if i is not self.refimg:
apDisplay.printWarning(
"Unable to update ApProtomoAlignmentData database table for image: %d"
% i)
# TODO: raise exception once the refimg is figured out correctly
self.params['description'] = cycle_description
def commitResultsToDB(self):
return
# -- Commit Parameters --
protomodata = apProTomo.insertProtomoParams(self.seriesname)
alignrun = apTomo.insertTomoAlignmentRun(self.sessiondata, None, None, protomodata, None, 1, self.params['runname'],self.params['rundir'],self.params['description'])
cycle_description = self.params['description']
# create refinement parameter dictionary
refinedict = apProTomo.createRefineDefaults(0, '', '', tmp='')
refinedict['alismp'] = self.params['sample']
refinedict['alibox_x'] = self.params['windowsize_x']
refinedict['alibox_y'] = self.params['windowsize_y']
refinedict['cormod'] = self.params['correlation_mode']
refinedict['imgref'] = self.params['refimg']
alignerdata = apProTomo.insertAlignIteration(alignrun, protomodata, self.params, refinedict, self.ordered_imagelist[self.refimg])
# -- Commit Results --
# Parse the results file which holds rotation and Correction Factors
correctionFactors = self.parseCorrectionFactors( self.correctionFactorFile )
# commit the geometry parameters (psi, theta, phi, azimuth), not sure about this.
if correctionFactors is not None:
self.insertModel(alignerdata, correctionFactors)
# insert results into ApProtomoAlignmentData for each image
for i,imagedata in enumerate(self.ordered_imagelist):
try:
apProTomo.insertTiltAlignment(alignerdata,imagedata,i,correctionFactors[i],self.center)
except:
if i is not self.refimg :
apDisplay.printWarning("Unable to update ApProtomoAlignmentData database table for image: %d" % i )
# TODO: raise exception once the refimg is figured out correctly
self.params['description'] = cycle_description
def start(self):
commit = self.params['commit']
tiltdatalist = apTomo.getTiltdataList(self.params['tiltseries'],self.params['othertiltseries'])
sessiondata = tiltdatalist[0]['session']
description = self.params['description']
alignsample = self.params['sample']
cycle = self.params['cycle']
alignmethod = self.params['alignmethod']
apDisplay.printMsg("getting imagelist")
imagelist = apTomo.getImageList(tiltdatalist)
tilts,ordered_imagelist,ordered_mrc_files,refimg = apTomo.orderImageList(imagelist)
# This parameter is needed for protomo, but not protomo2
if self.params['refimg']:
refimg = self.params['refimg']
if alignmethod != 'protomo2':
for file in ordered_mrc_files:
# protomo can not function with a negative origin
# protomo2 CAN function with negative origin
apImage.shiftMRCStartToZero(file)
apDisplay.printMsg("getting pixelsize")
pixelsize = apTomo.getTomoPixelSize(ordered_imagelist[refimg])
if pixelsize is None:
apDisplay.printError('Pixel Size not retrieved. Invalid tilt series for processing')
imgshape = apTomo.getTomoImageShape(ordered_imagelist[refimg])
corr_bin = apTomo.getCorrelatorBinning(imgshape)
center = {'x':imgshape[1]/2,'y':imgshape[0]/2}
default_azimuth = apTomo.getDefaultAzimuthFromLeginon(ordered_imagelist[refimg])
processdir = os.path.abspath(self.params['rundir'])
imodseriesname = apTomo.getFilename(tiltdatalist)
# protomo2 does not write out text files, intermediate info is in memory and the final result is binary
seriesname = 'tomo'+ imodseriesname
# Write tilt series stack images and tilt angles, not needed for protomo2
if alignmethod != 'protomo2':
stackdir = self.params['tiltseriesdir']
stackname = imodseriesname+".st"
apTomo.writeTiltSeriesStack(stackdir,stackname,ordered_mrc_files,1e10*pixelsize)
apImod.writeRawtltFile(stackdir,imodseriesname,tilts)
leginonxcorrlist = []
for tiltdata in tiltdatalist:
settingsdata = apTomo.getTomographySettings(sessiondata,tiltdata)
leginonxcorrlist.append(settingsdata)
# Run protomo2
if alignmethod == 'protomo2':
self.runProtomo2(sessiondata, processdir, seriesname, ordered_imagelist, refimg, center, corr_bin, commit, tilts)
# protomo2 does not need anything beyond this point, so exit
return
if cycle != 1 or alignmethod != 'protomo':
cycles=[cycle,]
else:
# also process and commit protomo cycle 0 if doing cycle 1
cycles=[0,1]
for cycle in cycles:
if alignmethod == 'protomo' or alignmethod == 'leginon':
self.params['aligndir'],self.params['imagedir'] = apProTomo.setProtomoDir(self.params['rundir'],cycle)
aligndir = self.params['aligndir']
# Link images into rundir/raw
rawimagenames = apProTomo.linkImageFiles(ordered_imagelist,self.params['imagedir'])
tltfile = os.path.join(aligndir,seriesname+'-%02d-itr.tlt' % (cycle,))
if cycle == 0:
# get initial shift alignment from leginon tiltcorrelator
# Assume all tiltdata have the same tomography settings
shifts = apTomo.getGlobalShift(ordered_imagelist, corr_bin, refimg)
tltparams = apProTomo.convertShiftsToParams(tilts,shifts,center,default_azimuth,rawimagenames)
apProTomo.writeTiltFile(tltfile,seriesname, tltparams[0], tltparams[1])
refineparamdict=apProTomo.createRefineDefaults(len(tilts),
os.path.join(processdir,'raw'),os.path.join(processdir,'out'))
refineparamdict = apProTomo.updateRefineParams(refineparamdict,imgshape,alignsample,100,refimg)
else:
lasttltfile = os.path.join(aligndir,seriesname+'-%02d-fitted.tlt' % (cycle-1,))
if self.params['goodcycle']:
if (self.params['goodstart'] == 0 and self.params['goodend'] == len(ordered_imagelist) - 1):
# revert goodcycle related params since nothing will be reset
self.params['goodcycle'] = None
self.params['goodstart'] = None
self.params['goodend'] = None
if not self.params['goodcycle']:
#default uses last cycle
shutil.copy(lasttltfile,tltfile)
else:
if not (self.params['goodstart'] or self.params['goodend']):
shutil.copy(lasttltfile,tltfile)
else:
# Reset bad ending tilts before alignment cycle
goodtltfile = os.path.join(aligndir,seriesname+'-%02d-fitted.tlt' % (self.params['goodcycle'],))
goodtltparams = apProTomo.parseTilt(goodtltfile)
lasttltparams = apProTomo.parseTilt(lasttltfile)
tltparams = apProTomo.resetTiltParams(lasttltparams,goodtltparams,self.params['goodstart'],self.params['goodend'])
apProTomo.writeTiltFile(tltfile,seriesname, tltparams[0], tltparams[1])
lastrefineparamfile = os.path.join(aligndir,seriesname+'-%02d.param' % (cycle-1,))
refineparamdict = apProTomo.parseRefineParamFile(lastrefineparamfile)
refineparamdict = apProTomo.updateRefineParams(refineparamdict,imgshape,alignsample,self.params['region'],refimg)
# Write param file in rundir/align
paramfilepath = os.path.join(seriesname+'-%02d.param' % (cycle))
fullparamfilepath = os.path.join(aligndir,paramfilepath)
apProTomo.writeRefineParamFile(refineparamdict,fullparamfilepath)
# run porjalign script
os.chdir(aligndir)
if cycle > 0:
self.runProjalign(paramfilepath)
else:
lasttltfile = os.path.join(aligndir,seriesname+'-%02d-itr.tlt' % (cycle,))
newtltfile = os.path.join(aligndir,seriesname+'-%02d-fitted.tlt' % (cycle,))
shutil.copy(lasttltfile,newtltfile)
# convert to imod alignment
alignpathprefix = os.path.join(processdir, seriesname)
centertuple = (center['x'],center['y'])
apProTomo.convertGlobalTransformProtomoToImod(seriesname+'-%02d' %(cycle),imodseriesname, centertuple)
elif alignmethod == 'imod-shift':
# Correlation by Coarse correlation in IMOD
aligndir = processdir
imodxcorrdata = apImod.coarseAlignment(stackdir, processdir, imodseriesname, commit)
# Global Transformation
gtransforms = apImod.convertToGlobalAlignment(processdir, imodseriesname)
# Create Aligned Stack for record
bin = int(math.ceil(min(imgshape) / 512.0))
apImod.createAlignedStack(stackdir, aligndir, imodseriesname,bin)
if alignmethod == 'protomo' or alignmethod == 'leginon':
alifilename = imodseriesname+'-%02d.ali' % cycle
os.rename(imodseriesname+'.ali',alifilename)
else:
alifilename = imodseriesname+'.ali'
alifilepath = os.path.join(aligndir,alifilename)
# commit to database
if commit:
if alignmethod == 'protomo' or alignmethod == 'leginon':
# -- Commit Parameters --
protomodata = apProTomo.insertProtomoParams(seriesname)
alignrun = apTomo.insertTomoAlignmentRun(sessiondata,leginonxcorrlist[0],None,protomodata,None,1,self.params['runname'],self.params['rundir'],self.params['description'])
self.cycle_description = self.params['description']
self.params['cycle'] = cycle
if cycle == 0:
# temporarily change aligner description on the initial 0 cycle
self.params['description'] = 'leginon correlation results'
# insert sample and window size and all the other user defined params into ApProtomoRefinementParamsData
alignerdata = apProTomo.insertAlignIteration(alignrun, protomodata, self.params, refineparamdict,ordered_imagelist[refimg])
# -- Commit Results --
resulttltfile = os.path.join(aligndir,seriesname+'-%02d-fitted.tlt' % (cycle,))
resulttltparams = apProTomo.parseTilt(resulttltfile)
if resulttltparams:
# commit the geometry parameters (psi, theta, phi, azimuth)
modeldata = apProTomo.insertModel(alignerdata, resulttltparams)
# insert results into ApProtomoAlignmentData (also used by imod) for each image
for i,imagedata in enumerate(ordered_imagelist):
apProTomo.insertTiltAlignment(alignerdata,imagedata,i,resulttltparams[0][i],center)
self.params['description'] = self.cycle_description
else:
alignrun = apTomo.insertTomoAlignmentRun(sessiondata,None,imodxcorrdata,None,None,1,self.params['runname'],self.params['rundir'],self.params['description'])
alignerdata = apTomo.insertAlignerParams(alignrun,self.params)
#results
prexgfile = os.path.join(aligndir,imodseriesname+'.prexg')
shifts = apImod.readShiftPrexgFile(aligndir, imodseriesname)
resulttltparams = apProTomo.convertShiftsToParams(tilts,shifts,center,default_azimuth)
if resulttltparams:
modeldata = apProTomo.insertModel(alignerdata, resulttltparams)
for i,imagedata in enumerate(ordered_imagelist):
apProTomo.insertTiltAlignment(alignerdata,imagedata,i,resulttltparams[0][i],center)
# multiple tilt series in one alignrun
for i in range(0,len(tiltdatalist)):
if i == 0:
primary = True
else:
primary = False
apTomo.insertTiltsInAlignRun(alignrun, tiltdatalist[i],leginonxcorrlist[i],primary)
apTomo.makeAlignStackMovie(alifilepath)
os.chdir(processdir)
zerotilts.append(imdictkey) #print "ref img and tilt is", imdictkey, tilt ptdict[imdictkey]=imdict refimg=zerotilts[-1] #shift first half of series with respect to second print shiftdict=alignZeroShiftImages(imgtree,zerotilts) shiftHalfSeries(shiftdict,ptdict,zerotilts[0]) #modifyShiftByImodprexg(ptdict,imgtree[0]['image'].shape) #write tilt file apProTomo.writeTiltFile(inputparams['tiltfile'],inputparams['seriesname'],ptdict) #write parameter file refineparamdict=apProTomo.createRefineDefaults(refimg, os.path.join(os.getcwd(),'raw'),os.path.join(os.getcwd(),'out')) apProTomo.writeRefineParamFile(refineparamdict,inputparams['seriesname']+'.param') #if tar is specified, create big tarball if inputparams['tar']: files='raw clean out align *.tlt *.param' command='tar cvfh %s %s' % ((inputparams['seriesname']+'.tar'), files) print command os.system(command) print '\n\n Please remember to remove tar file after transfering to processing computer' print "Done!"
ptdict[imdictkey] = imdict
refimg = zerotilts[-1]
#shift first half of series with respect to second
print
shiftdict = alignZeroShiftImages(imgtree, zerotilts)
shiftHalfSeries(shiftdict, ptdict, zerotilts[0])
#modifyShiftByImodprexg(ptdict,imgtree[0]['image'].shape)
#write tilt file
apProTomo.writeTiltFile(inputparams['tiltfile'], inputparams['seriesname'],
ptdict)
#write parameter file
refineparamdict = apProTomo.createRefineDefaults(
refimg, os.path.join(os.getcwd(), 'raw'),
os.path.join(os.getcwd(), 'out'))
apProTomo.writeRefineParamFile(refineparamdict,
inputparams['seriesname'] + '.param')
#if tar is specified, create big tarball
if inputparams['tar']:
files = 'raw clean out align *.tlt *.param'
command = 'tar cvfh %s %s' % (
(inputparams['seriesname'] + '.tar'), files)
print command
os.system(command)
print '\n\n Please remember to remove tar file after transfering to processing computer'
print "Done!"
