def showAssessedMask(self,imgfile,imgdata): self.filename = imgfile image = pyami.mrc.read(imgfile) sessiondata = self.params['sessionname'] maskassessname = self.params['checkMask'] mask,maskbin = apMask.makeInspectedMask(sessiondata,maskassessname,imgdata) overlay = apMask.overlayMask(image,mask) self.app.panel.setImage(overlay.astype(numpy.float32))
def processAndSaveAllImages(self):
sys.stderr.write("Pre-processing images before picking\n")
count = 0
total = len(self.imgtree)
# if we are masking based on a previous mask run, and only want to process images with rejected masks,
# remove any images with accepted masks from the imgtree.
newImageTree = []
for imgdata in self.imgtree:
count += 1
# useAccecepted mask is true when the assess flag is used, and an
# accepted mask is found in the indicated mask run that should be retained
self.useAcceptedMask = False
# check to see if this image
# 1. Does not have a mask region
# 2. Has only mask regions that have been rejected
# If both are true, continue, otherwise we do not need to display this image.
filename = imgdata['filename']
maskAssessRunName = self.params['assessname']
sessiondata = apDatabase.getSessionDataFromSessionName(
self.params['sessionname'])
maskimg, maskbin = apMask.makeInspectedMask(
sessiondata, maskAssessRunName, imgdata)
if maskimg is not None and maskimg.size:
apDisplay.printMsg("Skipping image with accepted mask region.")
maskimg = apMask.reshapeMask(imgdata['image'], maskimg)
self.maskimg = maskimg
self.image = imgdata['image']
self.useAcceptedMask = True
self.commitToDatabase(imgdata)
continue
imgpath = os.path.join(self.params['rundir'],
imgdata['filename'] + '.dwn.mrc')
if self.params['continue'] is True and os.path.isfile(imgpath):
sys.stderr.write(".")
#print "already processed: ",apDisplay.short(imgdata['filename'])
else:
if os.path.isfile(imgpath):
os.remove(imgpath)
sys.stderr.write("#")
apFindEM.processAndSaveImage(imgdata, params=self.params)
newImageTree.append(imgdata)
if count % 60 == 0:
sys.stderr.write(" %d left\n" % (total - count))
self.imgtree = newImageTree
def processAndSaveAllImages(self):
sys.stderr.write("Pre-processing images before picking\n")
count = 0
total = len(self.imgtree)
# if we are masking based on a previous mask run, and only want to process images with rejected masks,
# remove any images with accepted masks from the imgtree.
newImageTree = []
for imgdata in self.imgtree:
count += 1
# useAccecepted mask is true when the assess flag is used, and an
# accepted mask is found in the indicated mask run that should be retained
self.useAcceptedMask = False
# check to see if this image
# 1. Does not have a mask region
# 2. Has only mask regions that have been rejected
# If both are true, continue, otherwise we do not need to display this image.
filename = imgdata['filename']
maskAssessRunName = self.params['assessname']
sessiondata = apDatabase.getSessionDataFromSessionName(self.params['sessionname'])
maskimg,maskbin = apMask.makeInspectedMask( sessiondata, maskAssessRunName, imgdata )
if maskimg is not None and maskimg.size:
apDisplay.printMsg("Skipping image with accepted mask region.")
maskimg = apMask.reshapeMask( imgdata['image'], maskimg )
self.maskimg = maskimg
self.image = imgdata['image']
self.useAcceptedMask = True
self.commitToDatabase(imgdata)
continue
imgpath = os.path.join(self.params['rundir'], imgdata['filename']+'.dwn.mrc')
if self.params['continue'] is True and os.path.isfile(imgpath):
sys.stderr.write(".")
#print "already processed: ",apDisplay.short(imgdata['filename'])
else:
if os.path.isfile(imgpath):
os.remove(imgpath)
sys.stderr.write("#")
apFindEM.processAndSaveImage(imgdata, params=self.params)
newImageTree.append(imgdata)
if count % 60 == 0:
sys.stderr.write(" %d left\n" % (total-count))
self.imgtree = newImageTree
def eliminateMaskedParticles(self, particles, imgdata):
newparticles = []
eliminated = 0
sessiondata = apDatabase.getSessionDataFromSessionName(self.params['sessionname'])
if self.params['defocpair']:
imgdata = apDefocalPairs.getTransformedDefocPair(imgdata,2)
maskimg,maskbin = apMask.makeInspectedMask(sessiondata,self.params['maskassess'],imgdata)
if maskimg is not None:
for prtl in particles:
binnedcoord = (int(prtl['ycoord']/maskbin),int(prtl['xcoord']/maskbin))
if maskimg[binnedcoord] != 0:
eliminated += 1
else:
newparticles.append(prtl)
apDisplay.printMsg("%i particle(s) eliminated due to masking"%eliminated)
else:
apDisplay.printMsg("no masking")
newparticles = particles
return newparticles
def eliminateMaskedParticles(self, particles, imgdata):
newparticles = []
eliminated = 0
sessiondata = apDatabase.getSessionDataFromSessionName(
self.params['sessionname'])
if self.params['defocpair']:
imgdata = apDefocalPairs.getTransformedDefocPair(imgdata, 2)
maskimg, maskbin = apMask.makeInspectedMask(sessiondata,
self.params['maskassess'],
imgdata)
if maskimg is not None:
for prtl in particles:
binnedcoord = (int(prtl['ycoord'] / maskbin),
int(prtl['xcoord'] / maskbin))
if maskimg[binnedcoord] != 0:
eliminated += 1
else:
newparticles.append(prtl)
apDisplay.printMsg("%i particle(s) eliminated due to masking" %
eliminated)
else:
apDisplay.printMsg("no masking")
newparticles = particles
return newparticles