def scaleTemplate(templatearray, scalefactor=1.0, boxsize=None):
if(templatearray.shape[0] != templatearray.shape[1]):
apDisplay.printWarning("template shape is NOT square, this may cause errors")
if abs(scalefactor - 1.0) > 0.01:
apDisplay.printMsg("scaling template by a factor of "+str(scalefactor))
templatearray = apImage.scaleImage(templatearray, scalefactor)
#make sure the box size is divisible by 16
if boxsize is not None or (templatearray.shape[0] % 16 != 0):
edgeavg = apImage.meanEdgeValue(templatearray)
origsize = templatearray.shape[0]
if boxsize is None:
# minimal padisize is 16
padsize = max(int(math.floor(float(origsize)/16)*16),16)
else:
padsize = boxsize
padshape = numpy.array([padsize,padsize])
apDisplay.printMsg("changing box size from "+str(origsize)+" to "+str(padsize))
if origsize > padsize:
#shrink image
templatearray = apImage.frame_cut(templatearray, padshape)
else:
#grow image
templatearray = apImage.frame_constant(templatearray, padshape, cval=edgeavg)
if templatearray.shape[0] < 20 or templatearray.shape[1] < 20:
apDisplay.printWarning("template is only "+str(templatearray.shape[0])+" pixels wide\n"+\
" and may only correlation noise in the image")
return templatearray
def transformImage(img, xfactor, angle=0, msg=False):
"""
rotates then stretches or compresses an image only along the x-axis
"""
if xfactor > 1.0:
mystr = "_S"
else:
mystr = "_C"
if msg is True:
if xfactor > 1:
apDisplay.printMsg("stretching image by "+str(round(xfactor,3)))
else:
apDisplay.printMsg("compressing image by "+str(round(xfactor,3)))
### image has swapped coordinates (y,x) from particles
transMat = numpy.array([[ 1.0, 0.0 ], [ 0.0, 1.0/xfactor ]])
#print "transMat\n",transMat
#apImage.arrayToJpeg(img, "img"+mystr+".jpg")
stepimg = ndimage.rotate(img, -1.0*angle, mode='reflect')
stepimg = apImage.frame_cut(stepimg, img.shape)
#apImage.arrayToJpeg(stepimg, "rotate"+mystr+".jpg")
newimg = ndimage.affine_transform(stepimg, transMat, mode='reflect')
#apImage.arrayToJpeg(newimg, "last_transform"+mystr+".jpg")
return newimg
def transformImage(img, xfactor, angle=0, msg=False):
"""
rotates then stretches or compresses an image only along the x-axis
"""
if xfactor > 1.0:
mystr = "_S"
else:
mystr = "_C"
if msg is True:
if xfactor > 1:
apDisplay.printMsg("stretching image by "+str(round(xfactor,3)))
else:
apDisplay.printMsg("compressing image by "+str(round(xfactor,3)))
### image has swapped coordinates (y,x) from particles
transMat = numpy.array([[ 1.0, 0.0 ], [ 0.0, 1.0/xfactor ]])
#print "transMat\n",transMat
#apImage.arrayToJpeg(img, "img"+mystr+".jpg")
stepimg = ndimage.rotate(img, -1.0*angle, mode='reflect')
stepimg = apImage.frame_cut(stepimg, img.shape)
#apImage.arrayToJpeg(stepimg, "rotate"+mystr+".jpg")
newimg = ndimage.affine_transform(stepimg, transMat, mode='reflect')
#apImage.arrayToJpeg(newimg, "last_transform"+mystr+".jpg")
return newimg
def scaleTemplate(templatearray, scalefactor=1.0, boxsize=None):
if (templatearray.shape[0] != templatearray.shape[1]):
apDisplay.printWarning(
"template shape is NOT square, this may cause errors")
if abs(scalefactor - 1.0) > 0.01:
apDisplay.printMsg("scaling template by a factor of " +
str(scalefactor))
templatearray = apImage.scaleImage(templatearray, scalefactor)
#make sure the box size is divisible by 16
if boxsize is not None or (templatearray.shape[0] % 16 != 0):
edgeavg = apImage.meanEdgeValue(templatearray)
origsize = templatearray.shape[0]
if boxsize is None:
# minimal padisize is 16
padsize = max(int(math.floor(float(origsize) / 16) * 16), 16)
else:
padsize = boxsize
padshape = numpy.array([padsize, padsize])
apDisplay.printMsg("changing box size from " + str(origsize) + " to " +
str(padsize))
if origsize > padsize:
#shrink image
templatearray = apImage.frame_cut(templatearray, padshape)
else:
#grow image
templatearray = apImage.frame_constant(templatearray,
padshape,
cval=edgeavg)
if templatearray.shape[0] < 20 or templatearray.shape[1] < 20:
apDisplay.printWarning("template is only "+str(templatearray.shape[0])+" pixels wide\n"+\
" and may only correlation noise in the image")
return templatearray
def processImage(self, imgdata):
self.ctfvalues = {}
bestdef = ctfdb.getBestCtfByResolution(imgdata, msg=True)
apix = apDatabase.getPixelSize(imgdata)
if (not (self.params['onepass'] and self.params['zeropass'])):
maskhighpass = False
ace2inputpath = os.path.join(imgdata['session']['image path'],imgdata['filename']+".mrc")
else:
maskhighpass = True
filterimg = apImage.maskHighPassFilter(imgdata['image'],apix,1,self.params['zeropass'],self.params['onepass'])
ace2inputpath = os.path.join(self.params['rundir'],imgdata['filename']+".mrc")
mrc.write(filterimg,ace2inputpath)
# make sure that the image is a square
dimx = imgdata['camera']['dimension']['x']
dimy = imgdata['camera']['dimension']['y']
if dimx != dimy:
dims = [dimx,dimy]
dims.sort()
apDisplay.printMsg("resizing image: %ix%i to %ix%i" % (dimx,dimy,dims[0],dims[0]))
mrcarray = apImage.mrcToArray(ace2inputpath,msg=False)
clippedmrc = apImage.frame_cut(mrcarray,[dims[0],dims[0]])
ace2inputpath = os.path.join(self.params['rundir'],imgdata['filename']+".mrc")
apImage.arrayToMrc(clippedmrc,ace2inputpath,msg=False)
### pad out image to speed up FFT calculations for non-standard image sizes
print "checking prime factor"
if primefactor.isGoodStack(dimx) is False:
goodsize = primefactor.getNextEvenPrime(dimx)
factor = float(goodsize) / float(dimx)
apDisplay.printMsg("padding image: %ix%i to %ix%i" % (dimx,dimy,dimx*factor,dimy*factor))
mrcarray = apImage.mrcToArray(ace2inputpath,msg=False)
# paddedmrc = imagefun.pad(mrcarray, None, factor)
paddedmrc = apImage.frame_constant(mrcarray, (dimx*factor,dimy*factor), cval=mrcarray.mean())
ace2inputpath = os.path.join(self.params['rundir'],imgdata['filename']+".mrc")
apImage.arrayToMrc(paddedmrc,ace2inputpath,msg=False)
inputparams = {
'input': ace2inputpath,
'cs': self.params['cs'],
'kv': imgdata['scope']['high tension']/1000.0,
'apix': apix,
'binby': self.params['bin'],
}
### make standard input for ACE 2
apDisplay.printMsg("Ace2 executable: "+self.ace2exe)
commandline = ( self.ace2exe
+ " -i " + str(inputparams['input'])
+ " -b " + str(inputparams['binby'])
+ " -c " + str(inputparams['cs'])
+ " -k " + str(inputparams['kv'])
+ " -a " + str(inputparams['apix'])
+ " -e " + str(self.params['edge_b'])+","+str(self.params['edge_t'])
+ " -r " + str(self.params['rotblur'])
+ "\n" )
### run ace2
apDisplay.printMsg("running ace2 at "+time.asctime())
apDisplay.printColor(commandline, "purple")
t0 = time.time()
if self.params['verbose'] is True:
ace2proc = subprocess.Popen(commandline, shell=True)
else:
aceoutf = open("ace2.out", "a")
aceerrf = open("ace2.err", "a")
ace2proc = subprocess.Popen(commandline, shell=True, stderr=aceerrf, stdout=aceoutf)
ace2proc.wait()
### check if ace2 worked
basename = os.path.basename(ace2inputpath)
imagelog = basename+".ctf.txt"
if not os.path.isfile(imagelog) and self.stats['count'] <= 1:
### ace2 always crashes on first image??? .fft_wisdom file??
time.sleep(1)
if self.params['verbose'] is True:
ace2proc = subprocess.Popen(commandline, shell=True)
else:
aceoutf = open("ace2.out", "a")
aceerrf = open("ace2.err", "a")
ace2proc = subprocess.Popen(commandline, shell=True, stderr=aceerrf, stdout=aceoutf)
ace2proc.wait()
if self.params['verbose'] is False:
aceoutf.close()
aceerrf.close()
if not os.path.isfile(imagelog):
lddcmd = "ldd "+self.ace2exe
lddproc = subprocess.Popen(lddcmd, shell=True)
lddproc.wait()
apDisplay.printError("ace2 did not run")
apDisplay.printMsg("ace2 completed in " + apDisplay.timeString(time.time()-t0))
### parse log file
self.ctfvalues = {
'cs': self.params['cs'],
'volts': imgdata['scope']['high tension'],
}
logf = open(imagelog, "r")
apDisplay.printMsg("reading log file %s"%(imagelog))
for line in logf:
sline = line.strip()
if re.search("^Final Defocus: ", sline):
### old ACE2
apDisplay.printError("This old version of ACE2 has a bug in the astigmastism, please upgrade ACE2 now")
#parts = sline.split()
#self.ctfvalues['defocus1'] = float(parts[2])
#self.ctfvalues['defocus2'] = float(parts[3])
### convert to degrees
#self.ctfvalues['angle_astigmatism'] = math.degrees(float(parts[4]))
elif re.search("^Final Defocus \(m,m,deg\):", sline):
### new ACE2
apDisplay.printMsg("Reading new ACE2 defocus")
parts = sline.split()
#print parts
self.ctfvalues['defocus1'] = float(parts[3])
self.ctfvalues['defocus2'] = float(parts[4])
# ace2 defines negative angle from +x toward +y
self.ctfvalues['angle_astigmatism'] = -float(parts[5])
elif re.search("^Amplitude Contrast:",sline):
parts = sline.split()
self.ctfvalues['amplitude_contrast'] = float(parts[2])
elif re.search("^Confidence:",sline):
parts = sline.split()
self.ctfvalues['confidence'] = float(parts[1])
self.ctfvalues['confidence_d'] = float(parts[1])
logf.close()
### summary stats
apDisplay.printMsg("============")
avgdf = (self.ctfvalues['defocus1']+self.ctfvalues['defocus2'])/2.0
ampconst = 100.0*self.ctfvalues['amplitude_contrast']
pererror = 100.0 * (self.ctfvalues['defocus1']-self.ctfvalues['defocus2']) / avgdf
apDisplay.printMsg("Defocus: %.3f x %.3f um (%.2f percent astigmatism)"%
(self.ctfvalues['defocus1']*1.0e6, self.ctfvalues['defocus2']*1.0e6, pererror ))
apDisplay.printMsg("Angle astigmatism: %.2f degrees"%(self.ctfvalues['angle_astigmatism']))
apDisplay.printMsg("Amplitude contrast: %.2f percent"%(ampconst))
apDisplay.printColor("Final confidence: %.3f"%(self.ctfvalues['confidence']),'cyan')
### double check that the values are reasonable
if avgdf > self.params['maxdefocus'] or avgdf < self.params['mindefocus']:
apDisplay.printWarning("bad defocus estimate, not committing values to database")
self.badprocess = True
if ampconst < 0.0 or ampconst > 80.0:
apDisplay.printWarning("bad amplitude contrast, not committing values to database")
self.badprocess = True
if self.ctfvalues['confidence'] < 0.2:
apDisplay.printWarning("bad confidence value, not committing values to database")
self.badprocess = True
## create power spectra jpeg
mrcfile = imgdata['filename']+".mrc.edge.mrc"
if os.path.isfile(mrcfile):
jpegfile = os.path.join(self.powerspecdir, apDisplay.short(imgdata['filename'])+".jpg")
ps = apImage.mrcToArray(mrcfile,msg=False)
c = numpy.array(ps.shape)/2.0
ps[c[0]-0,c[1]-0] = ps.mean()
ps[c[0]-1,c[1]-0] = ps.mean()
ps[c[0]-0,c[1]-1] = ps.mean()
ps[c[0]-1,c[1]-1] = ps.mean()
#print "%.3f -- %.3f -- %.3f"%(ps.min(), ps.mean(), ps.max())
ps = numpy.log(ps+1.0)
ps = (ps-ps.mean())/ps.std()
cutoff = -2.0*ps.min()
ps = numpy.where(ps > cutoff, cutoff, ps)
cutoff = ps.mean()
ps = numpy.where(ps < cutoff, cutoff, ps)
#print "%.3f -- %.3f -- %.3f"%(ps.min(), ps.mean(), ps.max())
apImage.arrayToJpeg(ps, jpegfile, msg=False)
apFile.removeFile(mrcfile)
self.ctfvalues['graph3'] = jpegfile
otherfiles = glob.glob(imgdata['filename']+".*.txt")
### remove extra debugging files
for filename in otherfiles:
if filename[-9:] == ".norm.txt":
continue
elif filename[-8:] == ".ctf.txt":
continue
else:
apFile.removeFile(filename)
if maskhighpass and os.path.isfile(ace2inputpath):
apFile.removeFile(ace2inputpath)
return
def processImage(self, imgdata):
self.ctfvalues = {}
bestdef = ctfdb.getBestCtfByResolution(imgdata, msg=True)
apix = apDatabase.getPixelSize(imgdata)
if (not (self.params['onepass'] and self.params['zeropass'])):
maskhighpass = False
ace2inputpath = os.path.join(imgdata['session']['image path'],
imgdata['filename'] + ".mrc")
else:
maskhighpass = True
filterimg = apImage.maskHighPassFilter(imgdata['image'], apix, 1,
self.params['zeropass'],
self.params['onepass'])
ace2inputpath = os.path.join(self.params['rundir'],
imgdata['filename'] + ".mrc")
mrc.write(filterimg, ace2inputpath)
# make sure that the image is a square
dimx = imgdata['camera']['dimension']['x']
dimy = imgdata['camera']['dimension']['y']
if dimx != dimy:
dims = [dimx, dimy]
dims.sort()
apDisplay.printMsg("resizing image: %ix%i to %ix%i" %
(dimx, dimy, dims[0], dims[0]))
mrcarray = apImage.mrcToArray(ace2inputpath, msg=False)
clippedmrc = apImage.frame_cut(mrcarray, [dims[0], dims[0]])
ace2inputpath = os.path.join(self.params['rundir'],
imgdata['filename'] + ".mrc")
apImage.arrayToMrc(clippedmrc, ace2inputpath, msg=False)
### pad out image to speed up FFT calculations for non-standard image sizes
print "checking prime factor"
if primefactor.isGoodStack(dimx) is False:
goodsize = primefactor.getNextEvenPrime(dimx)
factor = float(goodsize) / float(dimx)
apDisplay.printMsg("padding image: %ix%i to %ix%i" %
(dimx, dimy, dimx * factor, dimy * factor))
mrcarray = apImage.mrcToArray(ace2inputpath, msg=False)
# paddedmrc = imagefun.pad(mrcarray, None, factor)
paddedmrc = apImage.frame_constant(mrcarray,
(dimx * factor, dimy * factor),
cval=mrcarray.mean())
ace2inputpath = os.path.join(self.params['rundir'],
imgdata['filename'] + ".mrc")
apImage.arrayToMrc(paddedmrc, ace2inputpath, msg=False)
inputparams = {
'input': ace2inputpath,
'cs': self.params['cs'],
'kv': imgdata['scope']['high tension'] / 1000.0,
'apix': apix,
'binby': self.params['bin'],
}
### make standard input for ACE 2
apDisplay.printMsg("Ace2 executable: " + self.ace2exe)
commandline = (self.ace2exe + " -i " + str(inputparams['input']) +
" -b " + str(inputparams['binby']) + " -c " +
str(inputparams['cs']) + " -k " +
str(inputparams['kv']) + " -a " +
str(inputparams['apix']) + " -e " +
str(self.params['edge_b']) + "," +
str(self.params['edge_t']) + " -r " +
str(self.params['rotblur']) + "\n")
### run ace2
apDisplay.printMsg("running ace2 at " + time.asctime())
apDisplay.printColor(commandline, "purple")
t0 = time.time()
if self.params['verbose'] is True:
ace2proc = subprocess.Popen(commandline, shell=True)
else:
aceoutf = open("ace2.out", "a")
aceerrf = open("ace2.err", "a")
ace2proc = subprocess.Popen(commandline,
shell=True,
stderr=aceerrf,
stdout=aceoutf)
ace2proc.wait()
### check if ace2 worked
basename = os.path.basename(ace2inputpath)
imagelog = basename + ".ctf.txt"
if not os.path.isfile(imagelog) and self.stats['count'] <= 1:
### ace2 always crashes on first image??? .fft_wisdom file??
time.sleep(1)
if self.params['verbose'] is True:
ace2proc = subprocess.Popen(commandline, shell=True)
else:
aceoutf = open("ace2.out", "a")
aceerrf = open("ace2.err", "a")
ace2proc = subprocess.Popen(commandline,
shell=True,
stderr=aceerrf,
stdout=aceoutf)
ace2proc.wait()
if self.params['verbose'] is False:
aceoutf.close()
aceerrf.close()
if not os.path.isfile(imagelog):
lddcmd = "ldd " + self.ace2exe
lddproc = subprocess.Popen(lddcmd, shell=True)
lddproc.wait()
apDisplay.printError("ace2 did not run")
apDisplay.printMsg("ace2 completed in " +
apDisplay.timeString(time.time() - t0))
### parse log file
self.ctfvalues = {
'cs': self.params['cs'],
'volts': imgdata['scope']['high tension'],
}
logf = open(imagelog, "r")
apDisplay.printMsg("reading log file %s" % (imagelog))
for line in logf:
sline = line.strip()
if re.search("^Final Defocus: ", sline):
### old ACE2
apDisplay.printError(
"This old version of ACE2 has a bug in the astigmastism, please upgrade ACE2 now"
)
#parts = sline.split()
#self.ctfvalues['defocus1'] = float(parts[2])
#self.ctfvalues['defocus2'] = float(parts[3])
### convert to degrees
#self.ctfvalues['angle_astigmatism'] = math.degrees(float(parts[4]))
elif re.search("^Final Defocus \(m,m,deg\):", sline):
### new ACE2
apDisplay.printMsg("Reading new ACE2 defocus")
parts = sline.split()
#print parts
self.ctfvalues['defocus1'] = float(parts[3])
self.ctfvalues['defocus2'] = float(parts[4])
# ace2 defines negative angle from +x toward +y
self.ctfvalues['angle_astigmatism'] = -float(parts[5])
elif re.search("^Amplitude Contrast:", sline):
parts = sline.split()
self.ctfvalues['amplitude_contrast'] = float(parts[2])
elif re.search("^Confidence:", sline):
parts = sline.split()
self.ctfvalues['confidence'] = float(parts[1])
self.ctfvalues['confidence_d'] = float(parts[1])
logf.close()
### summary stats
apDisplay.printMsg("============")
avgdf = (self.ctfvalues['defocus1'] + self.ctfvalues['defocus2']) / 2.0
ampconst = 100.0 * self.ctfvalues['amplitude_contrast']
pererror = 100.0 * (self.ctfvalues['defocus1'] -
self.ctfvalues['defocus2']) / avgdf
apDisplay.printMsg(
"Defocus: %.3f x %.3f um (%.2f percent astigmatism)" %
(self.ctfvalues['defocus1'] * 1.0e6,
self.ctfvalues['defocus2'] * 1.0e6, pererror))
apDisplay.printMsg("Angle astigmatism: %.2f degrees" %
(self.ctfvalues['angle_astigmatism']))
apDisplay.printMsg("Amplitude contrast: %.2f percent" % (ampconst))
apDisplay.printColor(
"Final confidence: %.3f" % (self.ctfvalues['confidence']), 'cyan')
### double check that the values are reasonable
if avgdf > self.params['maxdefocus'] or avgdf < self.params[
'mindefocus']:
apDisplay.printWarning(
"bad defocus estimate, not committing values to database")
self.badprocess = True
if ampconst < 0.0 or ampconst > 80.0:
apDisplay.printWarning(
"bad amplitude contrast, not committing values to database")
self.badprocess = True
if self.ctfvalues['confidence'] < 0.2:
apDisplay.printWarning(
"bad confidence value, not committing values to database")
self.badprocess = True
## create power spectra jpeg
mrcfile = imgdata['filename'] + ".mrc.edge.mrc"
if os.path.isfile(mrcfile):
jpegfile = os.path.join(
self.powerspecdir,
apDisplay.short(imgdata['filename']) + ".jpg")
ps = apImage.mrcToArray(mrcfile, msg=False)
c = numpy.array(ps.shape) / 2.0
ps[c[0] - 0, c[1] - 0] = ps.mean()
ps[c[0] - 1, c[1] - 0] = ps.mean()
ps[c[0] - 0, c[1] - 1] = ps.mean()
ps[c[0] - 1, c[1] - 1] = ps.mean()
#print "%.3f -- %.3f -- %.3f"%(ps.min(), ps.mean(), ps.max())
ps = numpy.log(ps + 1.0)
ps = (ps - ps.mean()) / ps.std()
cutoff = -2.0 * ps.min()
ps = numpy.where(ps > cutoff, cutoff, ps)
cutoff = ps.mean()
ps = numpy.where(ps < cutoff, cutoff, ps)
#print "%.3f -- %.3f -- %.3f"%(ps.min(), ps.mean(), ps.max())
apImage.arrayToJpeg(ps, jpegfile, msg=False)
apFile.removeFile(mrcfile)
self.ctfvalues['graph3'] = jpegfile
otherfiles = glob.glob(imgdata['filename'] + ".*.txt")
### remove extra debugging files
for filename in otherfiles:
if filename[-9:] == ".norm.txt":
continue
elif filename[-8:] == ".ctf.txt":
continue
else:
apFile.removeFile(filename)
if maskhighpass and os.path.isfile(ace2inputpath):
apFile.removeFile(ace2inputpath)
return
