def createPeakJpeg(imgdata, peaktree, params, procimgarray=None): if 'templatelist' in params: count = len(params['templatelist']) else: count = 1 bin = int(params["bin"]) diam = float(params["diam"]) apix = float(params["apix"]) binpixrad = diam/apix/2.0/float(bin) imgname = imgdata['filename'] jpegdir = os.path.join(params['rundir'],"jpgs") apParam.createDirectory(jpegdir, warning=False) if params['uncorrected']: imgarray = apDBImage.correctImage(imgdata) else: imgarray = imgdata['image'] if procimgarray is not None: #instead of re-processing image use one that is already processed... imgarray = procimgarray else: imgarray = apImage.preProcessImage(imgarray, bin=bin, planeReg=False, params=params) outfile = os.path.join(jpegdir, imgname+".prtl.jpg") msg = not params['background'] subCreatePeakJpeg(imgarray, peaktree, binpixrad, outfile, bin, msg) return
def createPeakJpeg(imgdata, peaktree, params, procimgarray=None):
if 'templatelist' in params:
count = len(params['templatelist'])
else: count = 1
bin = int(params["bin"])
diam = float(params["diam"])
apix = float(params["apix"])
binpixrad = diam/apix/2.0/float(bin)
imgname = imgdata['filename']
jpegdir = os.path.join(params['rundir'],"jpgs")
apParam.createDirectory(jpegdir, warning=False)
if params['uncorrected']:
imgarray = apDBImage.correctImage(imgdata)
else:
imgarray = imgdata['image']
if procimgarray is not None:
#instead of re-processing image use one that is already processed...
imgarray = procimgarray
else:
imgarray = apImage.preProcessImage(imgarray, bin=bin, planeReg=False, params=params)
outfile = os.path.join(jpegdir, imgname+".prtl.jpg")
msg = not params['background']
subCreatePeakJpeg(imgarray, peaktree, binpixrad, outfile, bin, msg)
return
def processAndSaveImage(imgdata, params):
imgpath = os.path.join(params['rundir'], imgdata['filename'] + ".dwn.mrc")
if os.path.isfile(imgpath):
return False
#downsize and filter leginon image
if params['uncorrected']:
imgarray = apDBImage.correctImage(imgdata)
else:
imgarray = imgdata['image']
imgarray = apImage.preProcessImage(imgarray, params=params, msg=False)
apImage.arrayToMrc(imgarray, imgpath, msg=False)
return True
def processAndSaveImage(imgdata, params): imgpath = os.path.join(params['rundir'], imgdata['filename']+".dwn.mrc") if os.path.isfile(imgpath): return False #downsize and filter leginon image if params['uncorrected']: imgarray = apDBImage.correctImage(imgdata) else: imgarray = imgdata['image'] imgarray = apImage.preProcessImage(imgarray, params=params, msg=False) apImage.arrayToMrc(imgarray, imgpath, msg=False) return True
def runAce(matlab, imgdata, params, showprev=True):
imgname = imgdata['filename']
if showprev is True:
bestctfvalue, bestconf = ctfdb.getBestCtfValueForImage(imgdata)
if bestctfvalue:
print ( "Prev best: '"+bestctfvalue['acerun']['name']+"', conf="+
apDisplay.colorProb(bestconf)+", defocus="+str(round(-1.0*abs(bestctfvalue['defocus1']*1.0e6),2))+
" microns" )
if params['uncorrected']:
tmpname='temporaryCorrectedImage.mrc'
imgarray = apDBImage.correctImage(imgdata)
imgpath = os.path.join(params['rundir'],tmpname)
apImage.arrayToMrc(imgarray, imgpath)
print "processing", imgpath
else:
imgpath = os.path.join(imgdata['session']['image path'], imgname+'.mrc')
nominal = None
if params['nominal'] is not None:
nominal=params['nominal']
elif params['newnominal'] is True:
nominal = ctfdb.getBestDefocusForImage(imgdata, msg=True)
if nominal is None:
nominal = imgdata['scope']['defocus']
if nominal is None or nominal > 0 or nominal < -15e-6:
apDisplay.printWarning("Nominal should be of the form nominal=-1.2e-6"+\
" for -1.2 microns NOT:"+str(nominal))
#Neil's Hack
#if 'autosample' in params and params['autosample']:
# x = abs(nominal*1.0e6)
# val = 1.585 + 0.057587 * x - 0.044106 * x**2 + 0.010877 * x**3
# resamplefr_override = round(val,3)
# print "resamplefr_override=",resamplefr_override
# pymat.eval(matlab, "resamplefr="+str(resamplefr_override)+";")
pymat.eval(matlab,("dforig = %e;" % nominal))
if params['stig'] == 0:
plist = (imgpath, params['outtextfile'], params['display'], params['stig'],\
params['medium'], -nominal, params['tempdir']+"/")
acecmd = makeMatlabCmd("ctfparams = ace(",");",plist)
else:
plist = (imgname, imgpath, params['outtextfile'], params['opimagedir'], \
params['matdir'], params['display'], params['stig'],\
params['medium'], -nominal, params['tempdir']+"/", params['resamplefr'])
acecmd = makeMatlabCmd("ctfparams = measureAstigmatism(",");",plist)
#print acecmd
pymat.eval(matlab,acecmd)
matfile = os.path.join(params['matdir'], imgname+".mrc.mat")
if params['stig']==0:
savematcmd = "save('"+matfile+"','ctfparams','scopeparams', 'dforig');"
pymat.eval(matlab,savematcmd)
ctfvalue = pymat.get(matlab, 'ctfparams')
ctfvalue=ctfvalue[0]
ctfdb.printResults(params, nominal, ctfvalue)
return ctfvalue
def runAce(matlab, imgdata, params, showprev=True):
imgname = imgdata['filename']
if showprev is True:
bestctfvalue = ctfdb.getBestCtfByResolution(imgdata)
if bestctfvalue:
bestconf = ctfdb.calculateConfidenceScore(bestctfvalue)
print ( "Prev best: '"+bestctfvalue['acerun']['name']+"', conf="+
apDisplay.colorProb(bestconf)+", defocus="+str(round(-1.0*abs(bestctfvalue['defocus1']*1.0e6),2))+
" microns" )
if params['uncorrected']:
tmpname='temporaryCorrectedImage.mrc'
imgarray = apDBImage.correctImage(imgdata)
imgpath = os.path.join(params['rundir'],tmpname)
apImage.arrayToMrc(imgarray, imgpath)
print "processing", imgpath
else:
imgpath = os.path.join(imgdata['session']['image path'], imgname+'.mrc')
nominal = None
if params['nominal'] is not None:
nominal=params['nominal']
elif params['newnominal'] is True:
bestctfvalue = ctfdb.getBestCtfByResolution(imgdata)
nominal = bestctfvalue['defocus1']
if nominal is None:
nominal = imgdata['scope']['defocus']
if nominal is None or nominal > 0 or nominal < -15e-6:
apDisplay.printWarning("Nominal should be of the form nominal=-1.2e-6"+\
" for -1.2 microns NOT:"+str(nominal))
#Neil's Hack
#if 'autosample' in params and params['autosample']:
# x = abs(nominal*1.0e6)
# val = 1.585 + 0.057587 * x - 0.044106 * x**2 + 0.010877 * x**3
# resamplefr_override = round(val,3)
# print "resamplefr_override=",resamplefr_override
# pymat.eval(matlab, "resamplefr="+str(resamplefr_override)+";")
pymat.eval(matlab,("dforig = %e;" % nominal))
if params['stig'] == 0:
plist = (imgpath, params['outtextfile'], params['display'], params['stig'],\
params['medium'], -nominal, params['tempdir']+"/")
acecmd = makeMatlabCmd("ctfparams = ace(",");",plist)
else:
plist = (imgname, imgpath, params['outtextfile'], params['opimagedir'], \
params['matdir'], params['display'], params['stig'],\
params['medium'], -nominal, params['tempdir']+"/", params['resamplefr'])
acecmd = makeMatlabCmd("ctfparams = measureAstigmatism(",");",plist)
#print acecmd
pymat.eval(matlab,acecmd)
matfile = os.path.join(params['matdir'], imgname+".mrc.mat")
if params['stig']==0:
savematcmd = "save('"+matfile+"','ctfparams','scopeparams', 'dforig');"
pymat.eval(matlab,savematcmd)
ctfvalue = pymat.get(matlab, 'ctfparams')
ctfvalue=ctfvalue[0]
printResults(params, nominal, ctfvalue)
return ctfvalue
