def runAceCorrect(imgdict,params):
imgname = imgdict['filename']
imgpath = os.path.join(imgdict['session']['image path'], imgname+'.mrc')
voltage = (imgdict['scope']['high tension'])
apix = apDatabase.getPixelSize(imgdict)
ctfvalues = ctfdb.getBestCtfByResolution(imgdata)
conf = ctfdb.calculateConfidenceScore(bestctfvalue)
ctdimname = imgname
ctdimpath = os.path.join(params['rundir'],ctdimname)
print "Corrected Image written to " + ctdimpath
#pdb.set_trace()
acecorrectcommand=("ctfcorrect1('%s', '%s', '%.32f', '%.32f', '%f', '%f', '%f');" % \
(imgpath, ctdimpath, ctfvalues['defocus1'], ctfvalues['defocus2'], -ctfvalues['angle_astigmatism'], voltage, apix))
print acecorrectcommand
try:
matlab = pymat.open("matlab -nosplash")
except:
apDisplay.environmentError()
raise
pymat.eval(matlab, acecorrectcommand)
pymat.close(matlab)
return
def reprocessImage(self, imgdata): """ Returns True, if an image should be reprocessed False, if an image was processed and should NOT be reprocessed None, if image has not yet been processed e.g. a confidence less than 80% """ if self.params['reprocess'] is None: return True ctfvalue = ctfdb.getBestCtfByResolution(imgdata, msg=False) if ctfvalue is None: return True if conf > self.params['reprocess']: # small, unbinned images can give same defocus values for 1 & 2: if self.params['bin'] == 1 or ctfvalue['defocus1'] != ctfvalue['defocus2']: return False return True
def reprocessImage(self, imgdata):
"""
Returns
True, if an image should be reprocessed
False, if an image was processed and should NOT be reprocessed
None, if image has not yet been processed
e.g. a confidence less than 80%
"""
if self.params['reprocess'] is None:
return True
ctfvalue = ctfdb.getBestCtfByResolution(imgdata, msg=False)
if ctfvalue is None:
return None
avgres = (ctfvalue['resolution_80_percent'] + ctfvalue['resolution_50_percent'])/2.0
if avgres < self.params['reprocess']:
return False
return True
def reprocessImage(self, imgdata):
"""
Returns
True, if an image should be reprocessed
False, if an image was processed and should NOT be reprocessed
None, if image has not yet been processed
e.g. a confidence less than 80%
"""
if self.params['reprocess'] is None:
return True
ctfvalue = ctfdb.getBestCtfByResolution(imgdata, msg=False)
if ctfvalue is None:
return None
avgres = (ctfvalue['resolution_80_percent'] +
ctfvalue['resolution_50_percent']) / 2.0
if avgres < self.params['reprocess']:
return False
return True
def reprocessImage(self, imgdata):
"""
Returns
True, if an image should be reprocessed
False, if an image was processed and should NOT be reprocessed
None, if image has not yet been processed
e.g. a confidence less than 80%
"""
if self.params['reprocess'] is None:
return True
ctfvalue = ctfdb.getBestCtfByResolution(imgdata, msg=False)
if ctfvalue is None:
return True
if conf > self.params['reprocess']:
# small, unbinned images can give same defocus values for 1 & 2:
if self.params['bin'] == 1 or ctfvalue['defocus1'] != ctfvalue[
'defocus2']:
return False
return True
def processImage(self, imgdata):
"""
time ./ctffind3.exe << eof
micrograph.mrc
montage.pow
2.0, 200.0, 0.07, 60000, 7.0, 2 #! CS[mm], HT[kV], AmpCnst, XMAG, DStep[um], PAve
128, 200.0, 8.0, 5000.0, 40000.0, 5000.0 #! Box, ResMin[A], ResMax[A], dFMin[A], dFMax[A], FStep
eof
CARD 1: Input file name for image
CARD 2: Output file name to check result
CARD 3: CS[mm], HT[kV], AmpCnst, XMAG, DStep[um],PAve
CARD 4: Box, ResMin[A], ResMax[A], dFMin[A], dFMax[A], FStep, dAst[A]
CTFTILT also asks for TiltA[deg], TiltR[deg] at CARD4
The output image file to check the result of the fitting
shows the filtered average power spectrum of the input
image in one half, and the fitted CTF (squared) in the
other half. The two halves should agree very well for a
successful fit.
CS: Spherical aberration coefficient of the objective in mm
HT: Electron beam voltage in kV
AmpCnst: Amount of amplitude contrast (fraction). For ice
images 0.07, for negative stain about 0.15.
XMAG: Magnification of original image
DStep: Pixel size on scanner in microns, or apix*mag/10000
PAve: Pixel averaging (PAve x PAve) for input image
Box: Tile size. The program divides the image into square
tiles and calculates the average power spectrum. Tiles
with a significantly higher or lower variance are
excluded; these are parts of the image which are unlikely
to contain useful information (beam edge, film number
etc). IMPORTANT: Box must have a even pixel dimensions.
ResMin: Low resolution end of data to be fitted.
ResMaX: High resolution end of data to be fitted.
dFMin: Starting defocus value for grid search in Angstrom.
Positive values represent an underfocus. The program
performs a systematic grid search of defocus values
and astigmatism before fitting a CTF to machine
precision.
dFMax: End defocus value for grid search in Angstrom.
FStep: Step width for grid search in Angstrom.
dAst: An additional parameter, dAst, was added to CARD 4 to restrain
the amount of astigmatism in the CTF fit. This makes the
fitting procedure more robust, especially in cases where
the Thon rings are not easily visible.
TiltA: guessed tilt angle
TiltR: angular range for initial coarse search
"""
#get Defocus in Angstroms
self.ctfvalues = {}
nominal = abs(imgdata['scope']['defocus'] * -1.0e10)
ctfvalue = ctfdb.getBestCtfByResolution(imgdata)
if ctfvalue is not None:
bestdef = abs(ctfvalue['defocus1'] +
ctfvalue['defocus2']) / 2.0 * 1.0e10
else:
bestdef = nominal
if ctfvalue is not None and self.params['bestdb'] is True:
bestampcontrast = ctfvalue['amplitude_contrast']
beststigdiff = abs(ctfvalue['defocus1'] -
ctfvalue['defocus2']) * 1e10
else:
bestampcontrast = self.params['amp' + self.params['medium']]
beststigdiff = self.params['dast']
# dstep is the physical detector pixel size
dstep = None
if 'camera' in imgdata and imgdata['camera'] and imgdata['camera'][
'pixel size']:
dstep = imgdata['camera']['pixel size']['x']
if dstep is None:
dstep = apDatabase.getPixelSize(
imgdata) * imgdata['scope']['magnification'] / 10000.0
dstep /= 1e6
dstep = float(dstep)
mpixelsize = apDatabase.getPixelSize(imgdata) * 1e-10
xmag = dstep / mpixelsize
apDisplay.printMsg("Xmag=%d, dstep=%.2e, mpix=%.2e" %
(xmag, dstep, mpixelsize))
inputparams = {
'orig':
os.path.join(imgdata['session']['image path'],
imgdata['filename'] + ".mrc"),
'input':
apDisplay.short(imgdata['filename']) + ".mrc",
'output':
apDisplay.short(imgdata['filename']) + "-pow.mrc",
'cs':
self.params['cs'],
'kv':
imgdata['scope']['high tension'] / 1000.0,
'ampcnst':
bestampcontrast,
'xmag':
xmag,
'dstep':
dstep * 1e6,
'pixavg':
self.params['bin'],
'box':
self.params['fieldsize'],
'resmin':
self.params['resmin'],
'resmax':
self.params['resmax'],
'defstep':
self.params['defstep'], #round(defocus/32.0, 1),
'dast':
beststigdiff,
}
defrange = self.params['defstep'] * self.params[
'numstep'] ## do 25 steps in either direction
inputparams['defmin'] = round(bestdef - defrange, 1) #in meters
if inputparams['defmin'] < 0:
apDisplay.printWarning("Defocus minimum is less than zero")
inputparams['defmin'] = inputparams['defstep']
inputparams['defmax'] = round(bestdef + defrange, 1) #in meters
apDisplay.printColor(
"Defocus search range: %d A to %d A (%.2f to %.2f um)" %
(inputparams['defmin'], inputparams['defmax'],
inputparams['defmin'] * 1e-4, inputparams['defmax'] * 1e-4),
"cyan")
### create local link to image
if not os.path.exists(inputparams['input']):
cmd = "ln -s " + inputparams['orig'] + " " + inputparams[
'input'] + "\n"
proc = subprocess.Popen(cmd, shell=True)
proc.wait()
### make standard input for ctf estimation
line1cmd = inputparams['input'] + "\n"
line2cmd = inputparams['output'] + "\n"
line3cmd = (str(inputparams['cs']) + "," + str(inputparams['kv']) +
"," + str(inputparams['ampcnst']) + "," +
str(inputparams['xmag']) + "," +
str(inputparams['dstep']) + "," +
str(inputparams['pixavg']) + "\n")
line4cmd = (str(inputparams['box']) + "," +
str(inputparams['resmin']) + "," +
str(inputparams['resmax']) + "," +
str(inputparams['defmin']) + "," +
str(inputparams['defmax']) + "," +
str(inputparams['defstep']) + "," +
str(inputparams['dast']))
### additional ctftilt parameters
if self.params['ctftilt'] is True:
tiltang = apDatabase.getTiltAngleDeg(imgdata)
line4cmd += ("," + str(tiltang) + ",10")
line4cmd += "\n"
if os.path.isfile(inputparams['output']):
# program crashes if this file exists
apFile.removeFile(inputparams['output'])
t0 = time.time()
apDisplay.printMsg("running ctf estimation at " + time.asctime())
ctfproglog = os.path.join(
self.logdir,
os.path.splitext(imgdata['filename'])[0] + "-ctfprog.log")
logf = open(ctfproglog, "w")
ctfprogproc = subprocess.Popen(self.ctfprgmexe,
shell=True,
stdin=subprocess.PIPE,
stdout=logf)
apDisplay.printColor(self.ctfprgmexe, "magenta")
apDisplay.printColor(line1cmd.strip(), "magenta")
apDisplay.printColor(line2cmd.strip(), "magenta")
apDisplay.printColor(line3cmd.strip(), "magenta")
apDisplay.printColor(line4cmd.strip(), "magenta")
ctfprogproc.stdin.write(line1cmd)
ctfprogproc.stdin.write(line2cmd)
ctfprogproc.stdin.write(line3cmd)
ctfprogproc.stdin.write(line4cmd)
ctfprogproc.communicate()
logf.close()
apDisplay.printMsg("ctf estimation completed in " +
apDisplay.timeString(time.time() - t0))
#apFile.removeFile(inputparams['input'])
### parse ctf estimation output
self.ctfvalues = {}
logf = open(ctfproglog, "r")
## ctffind & ctftilt have diff # values
numvals = 6
if self.params['ctftilt'] is True:
numvals = 8
for line in logf:
sline = line.strip()
if sline[-12:] == "Final Values":
#print sline
if '**********' in sline:
sline = re.sub('**********', ' **********', sline)
bits = sline.split()
if len(bits) != numvals:
apDisplay.printError("wrong number of values in " +
str(bits))
for i, bit in enumerate(bits[0:(numvals - 2)]):
bits[i] = float(bit)
self.ctfvalues = {
'defocus1':
float(bits[0]) * 1e-10,
'defocus2':
float(bits[1]) * 1e-10,
# WARNING: this is the negative of the direct result
'angle_astigmatism':
float(bits[2]),
'amplitude_contrast':
inputparams['ampcnst'],
'cross_correlation':
float(bits[numvals - 3]),
'nominal':
nominal * 1e-10,
'defocusinit':
bestdef * 1e-10,
'cs':
self.params['cs'],
'volts':
imgdata['scope']['high tension'],
'confidence':
float(bits[numvals - 3]),
'confidence_d':
round(math.sqrt(abs(float(bits[numvals - 3]))), 5)
}
if self.params['ctftilt'] is True:
self.ctfvalues['tilt_axis_angle'] = float(bits[3])
self.ctfvalues['tilt_angle'] = float(bits[4])
### write to log file
f = open("ctfvalues.log", "a")
f.write("=== " + imgdata['filename'] + " ===\n")
line1 = ("nominal=%.1e, bestdef=%.1e," %
(self.ctfvalues['nominal'], self.ctfvalues['defocusinit']))
if self.params['ctftilt'] is True:
self.ctfvalues['origtiltang'] = tiltang
line1 += " tilt=%.1f," % tiltang
apDisplay.printMsg(line1)
f.write(line1)
line2 = (
"def_1=%.1e, def_2=%.1e, astig_angle=%.1f, cross_corr=%.3f,\n" %
(self.ctfvalues['defocus1'], self.ctfvalues['defocus2'],
self.ctfvalues['angle_astigmatism'],
self.ctfvalues['cross_correlation']))
if self.params['ctftilt'] is True:
line2 += ("tilt_angle=%.1f, tilt_axis_angle=%.1f,\n" %
(self.ctfvalues['tilt_angle'],
self.ctfvalues['tilt_axis_angle']))
apDisplay.printMsg(line2)
f.write(line2)
f.close()
#convert powerspectra to JPEG
outputjpgbase = os.path.basename(
os.path.splitext(inputparams['output'])[0] + ".jpg")
self.lastjpg = outputjpgbase
outputjpg = os.path.join(self.powerspecdir, self.lastjpg)
powspec = apImage.mrcToArray(inputparams['output'])
apImage.arrayToJpeg(powspec, outputjpg)
shutil.move(inputparams['output'],
os.path.join(self.powerspecdir, inputparams['output']))
self.ctfvalues['graph1'] = outputjpg
#apFile.removeFile(inputparams['input'])
return
def processImage(self, imgdata):
"""
time ./ctffind3.exe << eof
micrograph.mrc
montage.pow
2.0, 200.0, 0.07, 60000, 7.0, 2 #! CS[mm], HT[kV], AmpCnst, XMAG, DStep[um], PAve
128, 200.0, 8.0, 5000.0, 40000.0, 5000.0 #! Box, ResMin[A], ResMax[A], dFMin[A], dFMax[A], FStep
eof
CARD 1: Input file name for image
CARD 2: Output file name to check result
CARD 3: CS[mm], HT[kV], AmpCnst, XMAG, DStep[um],PAve
CARD 4: Box, ResMin[A], ResMax[A], dFMin[A], dFMax[A], FStep, dAst[A]
CTFTILT also asks for TiltA[deg], TiltR[deg] at CARD4
The output image file to check the result of the fitting
shows the filtered average power spectrum of the input
image in one half, and the fitted CTF (squared) in the
other half. The two halves should agree very well for a
successful fit.
CS: Spherical aberration coefficient of the objective in mm
HT: Electron beam voltage in kV
AmpCnst: Amount of amplitude contrast (fraction). For ice
images 0.07, for negative stain about 0.15.
XMAG: Magnification of original image
DStep: Pixel size on scanner in microns, or apix*mag/10000
PAve: Pixel averaging (PAve x PAve) for input image
Box: Tile size. The program divides the image into square
tiles and calculates the average power spectrum. Tiles
with a significantly higher or lower variance are
excluded; these are parts of the image which are unlikely
to contain useful information (beam edge, film number
etc). IMPORTANT: Box must have a even pixel dimensions.
ResMin: Low resolution end of data to be fitted.
ResMaX: High resolution end of data to be fitted.
dFMin: Starting defocus value for grid search in Angstrom.
Positive values represent an underfocus. The program
performs a systematic grid search of defocus values
and astigmatism before fitting a CTF to machine
precision.
dFMax: End defocus value for grid search in Angstrom.
FStep: Step width for grid search in Angstrom.
dAst: An additional parameter, dAst, was added to CARD 4 to restrain
the amount of astigmatism in the CTF fit. This makes the
fitting procedure more robust, especially in cases where
the Thon rings are not easily visible.
TiltA: guessed tilt angle
TiltR: angular range for initial coarse search
"""
#get Defocus in Angstroms
self.ctfvalues = {}
if self.params['nominal'] is not None:
nominal = abs(self.params['nominal']*1e4)
else:
nominal = abs(imgdata['scope']['defocus']*-1.0e10)
ctfvalue = ctfdb.getBestCtfByResolution(imgdata)
if ctfvalue is not None:
"""
## CTFFIND V3.5 (7-March-2012) prefers the smaller of the two values for astigmatic images
I found that say you have an image with 1.1um and 1.5um defocus astigmatism. If you give
CTFFIND the average value of 1.3um for the defocus and 0.4um astig (dast) then it will
try to fit 1.3um and 1.8um, so you need to give it the minimum value (1.1um) for it to
fit 1.1um and 1.5um.
"""
bestdef = min(ctfvalue['defocus1'],ctfvalue['defocus2'])*1.0e10
else:
bestdef = nominal
if ctfvalue is not None and self.params['bestdb'] is True:
bestampcontrast = round(ctfvalue['amplitude_contrast'],3)
beststigdiff = round(abs(ctfvalue['defocus1'] - ctfvalue['defocus2'])*1e10,1)
else:
bestampcontrast = self.params['amp'+self.params['medium']]
beststigdiff = self.params['dast']
if ctfvalue is not None and self.params['bestdb'] is True:
### set res max from resolution_80_percent
gmean = (ctfvalue['resolution_80_percent']*ctfvalue['resolution_50_percent']*self.params['resmax'])**(1/3.)
if gmean < self.params['resmin']:
# replace only if valid Issue #3291, #3547
self.params['resmax'] = round(gmean,2)
apDisplay.printColor("Setting resmax to the geometric mean of resolution values", "purple")
# dstep is the physical detector pixel size
dstep = None
if 'camera' in imgdata and imgdata['camera'] and imgdata['camera']['pixel size']:
dstep = imgdata['camera']['pixel size']['x']
if dstep is None:
dstep = apDatabase.getPixelSize(imgdata)*imgdata['scope']['magnification']/10000.0
dstep /=1e6
dstep = float(dstep)
mpixelsize = apDatabase.getPixelSize(imgdata)*1e-10
if self.params['apix_man'] is not None:
mpixelsize = self.params['apix_man']*1e-10
xmag = dstep / mpixelsize
apDisplay.printMsg("Xmag=%d, dstep=%.2e, mpix=%.2e"%(xmag, dstep, mpixelsize))
inputparams = {
'orig': os.path.join(imgdata['session']['image path'], imgdata['filename']+".mrc"),
'input': apDisplay.short(imgdata['filename'])+".mrc",
'output': apDisplay.short(imgdata['filename'])+"-pow.mrc",
'cs': self.params['cs'],
'kv': imgdata['scope']['high tension']/1000.0,
'ampcnst': bestampcontrast,
'xmag': xmag,
'dstep': dstep*1e6,
'pixavg': self.params['bin'],
'box': self.params['fieldsize'],
'resmin': self.params['resmin'],
'resmax': self.params['resmax'],
'defstep': self.params['defstep'], #round(defocus/32.0, 1),
'dast': beststigdiff,
}
defrange = self.params['defstep'] * self.params['numstep'] ## do 25 steps in either direction
inputparams['defmin']= round(bestdef-defrange, 1) #in meters
if inputparams['defmin'] < 0:
apDisplay.printWarning("Defocus minimum is less than zero")
inputparams['defmin'] = inputparams['defstep']
inputparams['defmax']= round(bestdef+defrange, 1) #in meters
apDisplay.printColor("Defocus search range: %d A to %d A (%.2f to %.2f um)"
%(inputparams['defmin'], inputparams['defmax'],
inputparams['defmin']*1e-4, inputparams['defmax']*1e-4), "cyan")
### secondary lock check right before it starts on the real part
if self.params['parallel'] and os.path.isfile(apDisplay.short(imgdata['filename'])+".mrc"):
# This is a secondary image lock check, checking the first output of the process.
# It alone is not good enough
apDisplay.printWarning('Some other parallel process is working on the same image. Skipping')
return
### create local link to image
if not os.path.exists(inputparams['input']):
os.symlink(inputparams['orig'], inputparams['input'])
### make standard input for ctf estimation
line1cmd = inputparams['input']+"\n"
line2cmd = inputparams['output']+"\n"
line3cmd = (
str(inputparams['cs'])+","
+ str(inputparams['kv'])+","
+ str(inputparams['ampcnst'])+","
+ str(inputparams['xmag'])+","
+ str(inputparams['dstep'])+","
+ str(inputparams['pixavg'])+"\n")
line4cmd = (
str(inputparams['box'])+","
+ str(inputparams['resmin'])+","
+ str(inputparams['resmax'])+","
+ str(inputparams['defmin'])+","
+ str(inputparams['defmax'])+","
+ str(inputparams['defstep'])+","
+ str(inputparams['dast']))
### additional ctftilt parameters
if self.params['ctftilt'] is True:
tiltang = apDatabase.getTiltAngleDeg(imgdata)
line4cmd += (","+str(tiltang)+",10")
line4cmd += "\n"
if os.path.isfile(inputparams['output']):
# program crashes if this file exists
apFile.removeFile(inputparams['output'])
t0 = time.time()
apDisplay.printMsg("running ctf estimation at "+time.asctime())
ctfproglog = os.path.join(self.logdir, os.path.splitext(imgdata['filename'])[0]+"-ctfprog.log")
logf = open(ctfproglog, "w")
ctfprogproc = subprocess.Popen(self.ctfprgmexe, shell=True, stdin=subprocess.PIPE, stdout=logf)
apDisplay.printColor(self.ctfprgmexe, "magenta")
apDisplay.printColor(line1cmd.strip(),"magenta")
apDisplay.printColor(line2cmd.strip(),"magenta")
apDisplay.printColor(line3cmd.strip(),"magenta")
apDisplay.printColor(line4cmd.strip(),"magenta")
ctfprogproc.stdin.write(line1cmd)
ctfprogproc.stdin.write(line2cmd)
ctfprogproc.stdin.write(line3cmd)
ctfprogproc.stdin.write(line4cmd)
ctfprogproc.communicate()
logf.close()
apDisplay.printMsg("ctf estimation completed in "+apDisplay.timeString(time.time()-t0))
#apFile.removeFile(inputparams['input'])
### parse ctf estimation output
self.ctfvalues = {}
logf = open(ctfproglog, "r")
## ctffind & ctftilt have diff # values
numvals = 6
if self.params['ctftilt'] is True:
numvals=8
for line in logf:
sline = line.strip()
if sline[-12:] == "Final Values":
#print sline
if '**********' in sline:
sline = re.sub('**********', ' **********', sline)
bits = sline.split()
if len(bits) != numvals:
apDisplay.printError("wrong number of values in "+str(bits))
for i,bit in enumerate(bits[0:(numvals-2)]):
bits[i] = float(bit)
self.ctfvalues = {
'defocus1': float(bits[0])*1e-10,
'defocus2': float(bits[1])*1e-10,
# WARNING: this is the negative of the direct result
'angle_astigmatism': float(bits[2]),
'amplitude_contrast': inputparams['ampcnst'],
'cross_correlation': float(bits[numvals-3]),
'nominal': nominal*1e-10,
'defocusinit': bestdef*1e-10,
'cs': self.params['cs'],
'volts': imgdata['scope']['high tension'],
'confidence': float(bits[numvals-3]),
'confidence_d': round(math.sqrt(abs(float(bits[numvals-3]))), 5)
}
if self.params['ctftilt'] is True:
self.ctfvalues['tilt_axis_angle']=float(bits[3])
self.ctfvalues['tilt_angle']=float(bits[4])
### write to log file
f = open("ctfvalues.log", "a")
f.write("=== "+imgdata['filename']+" ===\n")
if not self.ctfvalues:
nominaldf = imgdata['scope']['defocus']
else:
nominaldf = self.ctfvalues['nominal']
line1 = ("nominal=%.1e, bestdef=%.1e," %
( nominaldf, self.ctfvalues['defocusinit']))
if self.params['ctftilt'] is True:
self.ctfvalues['origtiltang'] = tiltang
line1+=" tilt=%.1f,"%tiltang
apDisplay.printMsg(line1)
f.write(line1)
line2 = ("def_1=%.1e, def_2=%.1e, astig_angle=%.1f, cross_corr=%.3f,\n" %
( self.ctfvalues['defocus1'], self.ctfvalues['defocus2'], self.ctfvalues['angle_astigmatism'],
self.ctfvalues['cross_correlation'] ))
if self.params['ctftilt'] is True:
line2+= ("tilt_angle=%.1f, tilt_axis_angle=%.1f,\n" %
(self.ctfvalues['tilt_angle'], self.ctfvalues['tilt_axis_angle']))
apDisplay.printMsg(line2)
f.write(line2)
f.close()
#convert powerspectra to JPEG
outputjpgbase = os.path.basename(os.path.splitext(inputparams['output'])[0]+".jpg")
self.lastjpg = outputjpgbase
outputjpg = os.path.join(self.powerspecdir, self.lastjpg)
powspec = apImage.mrcToArray(inputparams['output'])
apImage.arrayToJpeg(powspec, outputjpg)
shutil.move(inputparams['output'], os.path.join(self.powerspecdir, inputparams['output']))
self.ctfvalues['graph1'] = outputjpg
#apFile.removeFile(inputparams['input'])
return
def runRefineCTF(self, imgdata, fftpath):
### reset important values
self.bestres = 1e10
self.bestellipse = None
self.bestvalues = {}
self.volts = imgdata['scope']['high tension']
self.wavelength = ctftools.getTEMLambda(self.volts)
## get value in meters
self.cs = apInstrument.getCsValueFromSession(
self.getSessionData()) * 1e-3
self.ctfvalues = {
'volts': self.volts,
'wavelength': self.wavelength,
'cs': self.cs,
}
### need to get FFT file open and freq of said file
fftarray = mrc.read(fftpath).astype(numpy.float64)
self.freq = self.freqdict[fftpath]
### convert resolution limit into pixel distance
fftwidth = fftarray.shape[0]
maxres = 2.0 / (self.freq * fftwidth)
if maxres > self.params['reslimit']:
apDisplay.printWarning(
"Cannot get requested res %.1fA higher than max Nyquist resolution %.1fA"
% (self.params['reslimit'], maxres))
self.params['reslimit'] = math.ceil(maxres)
limitwidth = int(math.ceil(2.0 /
(self.params['reslimit'] * self.freq)))
limitwidth = primefactor.getNextEvenPrime(limitwidth)
requestres = 2.0 / (self.freq * limitwidth)
if limitwidth > fftwidth:
apDisplay.printError("Cannot get requested resolution" + (
" request res %.1fA higher than max res %.1fA for new widths %d > %d"
% (requestres, maxres, limitwidth, fftwidth)))
apDisplay.printColor(
"Requested resolution OK: " +
(" request res %.1fA less than max res %.1fA with fft widths %d < %d"
% (requestres, maxres, limitwidth, fftwidth)), "green")
newshape = (limitwidth, limitwidth)
fftarray = imagefilter.frame_cut(fftarray, newshape)
### spacing parameters
self.mfreq = self.freq * 1e10
fftwidth = min(fftarray.shape)
self.apix = 1.0 / (fftwidth * self.freq)
self.ctfvalues['apix'] = self.apix
### print message
bestDbValues = ctfdb.getBestCtfByResolution(imgdata)
if bestDbValues is None:
apDisplay.printColor(
"SKIPPING: No CTF values for image %s" %
(apDisplay.short(imgdata['filename'])), "red")
self.badprocess = True
return
### skip if resolution > 90.
if bestDbValues['resolution_50_percent'] > 90.:
apDisplay.printColor(
"SKIPPING: No decent CTF values for image %s" %
(apDisplay.short(imgdata['filename'])), "yellow")
self.badprocess = True
return
self.ctfvalues['amplitude_contrast'] = bestDbValues[
'amplitude_contrast']
lowerrad1 = ctftools.getCtfExtrema(
bestDbValues['defocus1'], self.mfreq, self.cs, self.volts,
self.ctfvalues['amplitude_contrast'], 1, "valley")
lowerrad2 = ctftools.getCtfExtrema(
bestDbValues['defocus2'], self.mfreq, self.cs, self.volts,
self.ctfvalues['amplitude_contrast'], 1, "valley")
meanRad = (lowerrad1[0] + lowerrad2[0]) / 2.0
self.ellipseParams = {
'a': lowerrad1[0],
'b': lowerrad2[0],
'alpha': math.radians(bestDbValues['angle_astigmatism']),
}
ellipratio = self.ellipseParams['a'] / self.ellipseParams['b']
defratio = bestDbValues['defocus2'] / bestDbValues['defocus1']
print "ellr=%.3f, defr=%.3f, sqrt(defr)=%.3f" % (ellipratio, defratio,
math.sqrt(defratio))
self.bestvalues['defocus'] = (bestDbValues['defocus1'] +
bestDbValues['defocus2']) / 2.0
raddata, PSDarray = self.from2Dinto1D(fftarray)
lowerbound = numpy.searchsorted(raddata, meanRad * self.freq)
upperbound = numpy.searchsorted(raddata, 1 / 10.)
###
# This is the start of the actual program
###
self.refineEllipseLoop(fftarray, lowerbound, upperbound)
##==================================
## FINISH UP
##==================================
apDisplay.printColor("Finishing up using best found CTF values",
"blue")
self.printBestValues()
### take best values and use them
self.ctfvalues = self.bestvalues
self.ellipseParams = self.bestellipse
### stupid fix, get value in millimeters
self.ctfvalues['cs'] = apInstrument.getCsValueFromSession(
self.getSessionData())
### translate ellipse into ctf values
if self.ellipseParams is not None:
self.ctfvalues['angle_astigmatism'] = math.degrees(
self.ellipseParams['alpha'])
ellipratio = self.ellipseParams['a'] / self.ellipseParams['b']
phi = math.asin(self.ctfvalues['amplitude_contrast'])
#note: a > b then def1 < def2
#major axis
self.ctfvalues['defocus1'] = self.ctfvalues['defocus'] / ellipratio
#minor axis
self.ctfvalues['defocus2'] = self.ctfvalues['defocus'] * ellipratio
defdiff = 1.0 - 2 * self.ctfvalues['defocus'] / (
self.ctfvalues['defocus1'] + self.ctfvalues['defocus2'])
print "%.3e --> %.3e,%.3e" % (self.ctfvalues['defocus'],
self.ctfvalues['defocus2'],
self.ctfvalues['defocus1'])
print defdiff * 100
if defdiff * 100 > 1:
apDisplay.printWarning("Large astigmatism")
#sys.exit(1)
else:
ellipratio = 1.0
self.ctfvalues['angle_astigmatism'] = 0.0
self.ctfvalues['defocus1'] = self.ctfvalues['defocus']
self.ctfvalues['defocus2'] = self.ctfvalues['defocus']
self.badprocess = True
return
try:
if self.ctfvalues['amplitude_contrast'] < self.minAmpCon:
self.ctfvalues['amplitude_contrast'] = self.minAmpCon
if self.ctfvalues['amplitude_contrast'] > self.maxAmpCon:
self.ctfvalues['amplitude_contrast'] = self.maxAmpCon
except KeyError:
pass
if abs(self.ctfvalues['defocus1']) > abs(self.ctfvalues['defocus2']):
# incorrect, need to shift angle by 90 degrees
apDisplay.printWarning("|def1| > |def2|, flipping defocus axes")
tempdef = self.ctfvalues['defocus1']
self.ctfvalues['defocus1'] = self.ctfvalues['defocus2']
self.ctfvalues['defocus2'] = tempdef
self.ctfvalues['angle_astigmatism'] += 90
# get astig_angle within range -90 < angle <= 90
while self.ctfvalues['angle_astigmatism'] > 90:
self.ctfvalues['angle_astigmatism'] -= 180
while self.ctfvalues['angle_astigmatism'] < -90:
self.ctfvalues['angle_astigmatism'] += 180
avgres = self.getResolution(self.ctfvalues['defocus'], raddata,
PSDarray, lowerbound)
apDisplay.printColor(
"Final defocus values %.3e -> %.3e, %.3e; ac=%.2f, res=%.1f" %
(self.ctfvalues['defocus'], self.ctfvalues['defocus1'],
self.ctfvalues['defocus2'], self.ctfvalues['amplitude_contrast'],
avgres / 2.0), "green")
for i in range(10):
print "===================================="
print "PREVIOUS VALUES"
ctfdb.getBestCtfByResolution(imgdata)
print "CURRENT VALUES"
defocusratio = self.ctfvalues['defocus2'] / self.ctfvalues['defocus1']
apDisplay.printColor(
"def1: %.2e | def2: %.2e | angle: %.1f | ampcontr %.2f | defratio %.3f"
% (self.ctfvalues['defocus1'], self.ctfvalues['defocus2'],
self.ctfvalues['angle_astigmatism'],
self.ctfvalues['amplitude_contrast'], defocusratio), "blue")
self.printBestValues()
#ellipratio = self.ellipseParams['a']/self.ellipseParams['b']
print "ellr=%.3f, defr=%.3f, sqrt(defr)=%.3f" % (
ellipratio, defocusratio, math.sqrt(defocusratio))
print "===================================="
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
def runRefineCTF(self, imgdata, fftpath):
### reset important values
self.bestres = 1e10
self.bestellipse = None
self.bestvalues = {}
self.volts = imgdata['scope']['high tension']
self.wavelength = ctftools.getTEMLambda(self.volts)
## get value in meters
self.cs = apInstrument.getCsValueFromSession(self.getSessionData())*1e-3
self.ctfvalues = {
'volts': self.volts,
'wavelength': self.wavelength,
'cs': self.cs,
}
### need to get FFT file open and freq of said file
fftarray = mrc.read(fftpath).astype(numpy.float64)
self.freq = self.freqdict[fftpath]
### convert resolution limit into pixel distance
fftwidth = fftarray.shape[0]
maxres = 2.0/(self.freq*fftwidth)
if maxres > self.params['reslimit']:
apDisplay.printError("Cannot get requested res %.1fA higher than max res %.1fA"
%(maxres, self.params['reslimit']))
limitwidth = int(math.ceil(2.0/(self.params['reslimit']*self.freq)))
limitwidth = primefactor.getNextEvenPrime(limitwidth)
requestres = 2.0/(self.freq*limitwidth)
if limitwidth > fftwidth:
apDisplay.printError("Cannot get requested resolution"
+(" request res %.1fA higher than max res %.1fA for new widths %d > %d"
%(requestres, maxres, limitwidth, fftwidth)))
apDisplay.printColor("Requested resolution OK: "
+(" request res %.1fA less than max res %.1fA with fft widths %d < %d"
%(requestres, maxres, limitwidth, fftwidth)), "green")
newshape = (limitwidth, limitwidth)
fftarray = imagefilter.frame_cut(fftarray, newshape)
### spacing parameters
self.mfreq = self.freq*1e10
fftwidth = min(fftarray.shape)
self.apix = 1.0/(fftwidth*self.freq)
self.ctfvalues['apix'] = self.apix
### print message
bestDbValues = ctfdb.getBestCtfByResolution(imgdata)
if bestDbValues is None:
apDisplay.printColor("SKIPPING: No CTF values for image %s"
%(apDisplay.short(imgdata['filename'])), "red")
self.badprocess = True
return
### skip if resolution > 90.
if bestDbValues['resolution_50_percent'] > 90.:
apDisplay.printColor("SKIPPING: No decent CTF values for image %s"
%(apDisplay.short(imgdata['filename'])), "yellow")
self.badprocess = True
return
self.ctfvalues['amplitude_contrast'] = bestDbValues['amplitude_contrast']
lowerrad1 = ctftools.getCtfExtrema(bestDbValues['defocus1'], self.mfreq, self.cs, self.volts,
self.ctfvalues['amplitude_contrast'], 1, "valley")
lowerrad2 = ctftools.getCtfExtrema(bestDbValues['defocus2'], self.mfreq, self.cs, self.volts,
self.ctfvalues['amplitude_contrast'], 1, "valley")
meanRad = (lowerrad1[0] + lowerrad2[0])/2.0
self.ellipseParams = {
'a': lowerrad1[0],
'b': lowerrad2[0],
'alpha': math.radians(bestDbValues['angle_astigmatism']),
}
ellipratio = self.ellipseParams['a']/self.ellipseParams['b']
defratio = bestDbValues['defocus2']/bestDbValues['defocus1']
print "ellr=%.3f, defr=%.3f, sqrt(defr)=%.3f"%(ellipratio, defratio, math.sqrt(defratio))
self.bestvalues['defocus'] = (bestDbValues['defocus1']+bestDbValues['defocus2'])/2.0
raddata, PSDarray = self.from2Dinto1D(fftarray)
lowerbound = numpy.searchsorted(raddata, meanRad*self.freq)
upperbound = numpy.searchsorted(raddata, 1/10.)
###
# This is the start of the actual program
###
self.refineEllipseLoop(fftarray, lowerbound, upperbound)
##==================================
## FINISH UP
##==================================
apDisplay.printColor("Finishing up using best found CTF values", "blue")
self.printBestValues()
### take best values and use them
self.ctfvalues = self.bestvalues
self.ellipseParams = self.bestellipse
### stupid fix, get value in millimeters
self.ctfvalues['cs'] = apInstrument.getCsValueFromSession(self.getSessionData())
### translate ellipse into ctf values
if self.ellipseParams is not None:
self.ctfvalues['angle_astigmatism'] = math.degrees(self.ellipseParams['alpha'])
ellipratio = self.ellipseParams['a']/self.ellipseParams['b']
phi = math.asin(self.ctfvalues['amplitude_contrast'])
#note: a > b then def1 < def2
#major axis
self.ctfvalues['defocus1'] = self.ctfvalues['defocus']/ellipratio
#minor axis
self.ctfvalues['defocus2'] = self.ctfvalues['defocus']*ellipratio
defdiff = 1.0 - 2*self.ctfvalues['defocus']/(self.ctfvalues['defocus1']+self.ctfvalues['defocus2'])
print "%.3e --> %.3e,%.3e"%(self.ctfvalues['defocus'],
self.ctfvalues['defocus2'], self.ctfvalues['defocus1'])
print defdiff*100
if defdiff*100 > 1:
apDisplay.printWarning("Large astigmatism")
#sys.exit(1)
else:
ellipratio = 1.0
self.ctfvalues['angle_astigmatism'] = 0.0
self.ctfvalues['defocus1'] = self.ctfvalues['defocus']
self.ctfvalues['defocus2'] = self.ctfvalues['defocus']
if self.ctfvalues['amplitude_contrast'] < 0.0:
self.ctfvalues['amplitude_contrast'] = 0.0
if self.ctfvalues['amplitude_contrast'] > self.maxAmpCon:
self.ctfvalues['amplitude_contrast'] = self.maxAmpCon
if abs(self.ctfvalues['defocus1']) > abs(self.ctfvalues['defocus2']):
# incorrect, need to shift angle by 90 degrees
apDisplay.printWarning("|def1| > |def2|, flipping defocus axes")
tempdef = self.ctfvalues['defocus1']
self.ctfvalues['defocus1'] = self.ctfvalues['defocus2']
self.ctfvalues['defocus2'] = tempdef
self.ctfvalues['angle_astigmatism'] += 90
# get astig_angle within range -90 < angle <= 90
while self.ctfvalues['angle_astigmatism'] > 90:
self.ctfvalues['angle_astigmatism'] -= 180
while self.ctfvalues['angle_astigmatism'] < -90:
self.ctfvalues['angle_astigmatism'] += 180
avgres = self.getResolution(self.ctfvalues['defocus'], raddata, PSDarray, lowerbound)
apDisplay.printColor("Final defocus values %.3e -> %.3e, %.3e; ac=%.2f, res=%.1f"
%(self.ctfvalues['defocus'], self.ctfvalues['defocus1'], self.ctfvalues['defocus2'],
self.ctfvalues['amplitude_contrast'], avgres/2.0), "green")
for i in range(10):
print "===================================="
print "PREVIOUS VALUES"
ctfdb.getBestCtfByResolution(imgdata)
print "CURRENT VALUES"
defocusratio = self.ctfvalues['defocus2']/self.ctfvalues['defocus1']
apDisplay.printColor("def1: %.2e | def2: %.2e | angle: %.1f | ampcontr %.2f | defratio %.3f"
%(self.ctfvalues['defocus1'], self.ctfvalues['defocus2'], self.ctfvalues['angle_astigmatism'],
self.ctfvalues['amplitude_contrast'], defocusratio), "blue")
self.printBestValues()
#ellipratio = self.ellipseParams['a']/self.ellipseParams['b']
print "ellr=%.3f, defr=%.3f, sqrt(defr)=%.3f"%(ellipratio, defocusratio, math.sqrt(defocusratio))
print "===================================="
return
def runPhasorCTF(self, imgdata, fftpath):
### reset important values
self.bestres = 1e10
self.bestellipse = None
self.bestvalues = None
self.ellipseParams = None
self.volts = imgdata['scope']['high tension']
self.wavelength = ctftools.getTEMLambda(self.volts)
## get value in meters
self.cs = apInstrument.getCsValueFromSession(self.getSessionData())*1e-3
self.ctfvalues = {
'volts': self.volts,
'wavelength': self.wavelength,
'cs': self.cs,
}
if self.params['astig'] is False:
self.maxRatio=1.3
else:
self.maxRatio=2.0
### need to get FFT file open and freq of said file
fftarray = mrc.read(fftpath).astype(numpy.float64)
self.freq = self.freqdict[fftpath]
### print message
ctfdb.getBestCtfByResolution(imgdata)
### convert resolution limit into pixel distance
fftwidth = fftarray.shape[0]
maxres = 2.0/(self.freq*fftwidth)
if maxres > self.params['reslimit']:
apDisplay.printError("Cannot get requested res %.1fA higher than max res %.1fA"
%(maxres, self.params['reslimit']))
limitwidth = int(math.ceil(2.0/(self.params['reslimit']*self.freq)))
limitwidth = primefactor.getNextEvenPrime(limitwidth)
requestres = 2.0/(self.freq*limitwidth)
if limitwidth > fftwidth:
apDisplay.printError("Cannot get requested resolution"
+(" request res %.1fA higher than max res %.1fA for new widths %d > %d"
%(requestres, maxres, limitwidth, fftwidth)))
apDisplay.printColor("Requested resolution OK: "
+(" request res %.1fA less than max res %.1fA with fft widths %d < %d"
%(requestres, maxres, limitwidth, fftwidth)), "green")
newshape = (limitwidth, limitwidth)
fftarray = imagefilter.frame_cut(fftarray, newshape)
### spacing parameters
self.mfreq = self.freq*1e10
fftwidth = min(fftarray.shape)
self.apix = 1.0/(fftwidth*self.freq)
self.ctfvalues['apix'] = self.apix
if self.params['sample'] is 'stain':
self.ctfvalues['amplitude_contrast'] = 0.14
else:
self.ctfvalues['amplitude_contrast'] = 0.07
###
# This is the start of the actual program
###
### this is either simple rotational average,
### or complex elliptical average with edge find and RANSAC
raddata, PSDarray = self.from2Dinto1D(fftarray)
lowerrad = ctftools.getCtfExtrema(self.params['maxdef'], self.mfreq, self.cs, self.volts,
self.ctfvalues['amplitude_contrast'], 1, "valley")
lowerbound = numpy.searchsorted(raddata, lowerrad[0]*self.freq)
if self.params['sample'] is 'stain':
upperbound = numpy.searchsorted(raddata, 1/8.)
else:
upperbound = numpy.searchsorted(raddata, 1/12.)
### fun way to get initial defocus estimate
fitData = self.fitLinearPlus(raddata, PSDarray)
#lowessFit = lowess.lowess(raddata**2, PSDarray, smoothing=0.6666)
if self.debug is True:
from matplotlib import pyplot
pyplot.clf()
pyplot.plot(raddata**2, PSDarray)
pyplot.plot(raddata**2, fitData)
pyplot.show()
flatPSDarray = PSDarray-fitData
flatPSDarray /= numpy.abs(flatPSDarray[lowerbound:upperbound]).max()
defocus = self.gridSearch(raddata, flatPSDarray, lowerbound)
#defocus = findroots.estimateDefocus(raddata[lowerbound:upperbound], flatPSDarray[lowerbound:upperbound],
# cs=self.cs, wavelength=self.wavelength, amp_con=self.ctfvalues['amplitude_contrast'],
# mindef=self.params['mindef'], maxdef=self.params['maxdef'], volts=self.volts)
amplitudecontrast = sinefit.refineAmplitudeContrast(raddata[lowerbound:upperbound]*1e10, defocus,
flatPSDarray[lowerbound:upperbound], self.ctfvalues['cs'], self.wavelength, msg=self.debug)
if amplitudecontrast is not None:
print "amplitudecontrast", amplitudecontrast
self.ctfvalues['amplitude_contrast'] = amplitudecontrast
defocus = self.defocusLoop(defocus, raddata, flatPSDarray, lowerbound, upperbound)
#lowerrad = ctftools.getCtfExtrema(defocus, self.mfreq, self.cs, self.volts,
# self.ctfvalues['amplitude_contrast'], 1, "valley")
#lowerbound = numpy.searchsorted(raddata, lowerrad[0]*self.freq)
normPSDarray = self.fullTriSectionNormalize(raddata, PSDarray, defocus)
defocus = self.defocusLoop(defocus, raddata, normPSDarray, lowerbound, upperbound)
self.findEllipseLoop(fftarray, lowerbound, upperbound)
self.refineEllipseLoop(fftarray, lowerbound, upperbound)
##==================================
## FINISH UP
##==================================
apDisplay.printColor("Finishing up using best found CTF values", "blue")
self.printBestValues()
if self.bestvalues is None:
apDisplay.printColor("No CTF estimate found for this image", "red")
self.badprocess = True
return
### take best values and use them
self.ctfvalues = self.bestvalues
self.ellipseParams = self.bestellipse
### stupid fix, get value in millimeters
self.ctfvalues['cs'] = apInstrument.getCsValueFromSession(self.getSessionData())
### translate ellipse into ctf values
if self.ellipseParams is not None:
self.ctfvalues['angle_astigmatism'] = math.degrees(self.ellipseParams['alpha'])
ellipratio = self.ellipseParams['a']/self.ellipseParams['b']
phi = math.asin(self.ctfvalues['amplitude_contrast'])
#note: a > b then def1 < def2
#major axis
self.ctfvalues['defocus1'] = self.ctfvalues['defocus']/ellipratio
#minor axis
self.ctfvalues['defocus2'] = self.ctfvalues['defocus']*ellipratio
defdiff = 1.0 - 2*self.ctfvalues['defocus']/(self.ctfvalues['defocus1']+self.ctfvalues['defocus2'])
print "%.3e --> %.3e,%.3e"%(self.ctfvalues['defocus'],
self.ctfvalues['defocus2'], self.ctfvalues['defocus1'])
print defdiff*100
if defdiff*100 > 1:
apDisplay.printWarning("Large astigmatism")
#sys.exit(1)
else:
self.ctfvalues['angle_astigmatism'] = 0.0
self.ctfvalues['defocus1'] = self.ctfvalues['defocus']
self.ctfvalues['defocus2'] = self.ctfvalues['defocus']
if self.ctfvalues['amplitude_contrast'] < 0.0:
self.ctfvalues['amplitude_contrast'] = 0.0
if self.ctfvalues['amplitude_contrast'] > self.maxAmpCon:
self.ctfvalues['amplitude_contrast'] = self.maxAmpCon
if abs(self.ctfvalues['defocus1']) > abs(self.ctfvalues['defocus2']):
# incorrect, need to shift angle by 90 degrees
apDisplay.printWarning("|def1| > |def2|, flipping defocus axes")
tempdef = self.ctfvalues['defocus1']
self.ctfvalues['defocus1'] = self.ctfvalues['defocus2']
self.ctfvalues['defocus2'] = tempdef
self.ctfvalues['angle_astigmatism'] += 90
# get astig_angle within range -90 < angle <= 90
while self.ctfvalues['angle_astigmatism'] > 90:
self.ctfvalues['angle_astigmatism'] -= 180
while self.ctfvalues['angle_astigmatism'] < -90:
self.ctfvalues['angle_astigmatism'] += 180
avgres = self.getResolution(self.ctfvalues['defocus'], raddata, PSDarray, lowerbound)
apDisplay.printColor("Final defocus values %.3e -> %.3e, %.3e; ac=%.2f, res=%.1f"
%(self.ctfvalues['defocus'], self.ctfvalues['defocus1'], self.ctfvalues['defocus2'],
self.ctfvalues['amplitude_contrast'], avgres/2.0), "green")
for i in range(10):
print "===================================="
print "PREVIOUS VALUES"
ctfdb.getBestCtfByResolution(imgdata)
print "CURRENT VALUES"
defocusratio = self.ctfvalues['defocus2']/self.ctfvalues['defocus1']
apDisplay.printColor("def1: %.2e | def2: %.2e | angle: %.1f | ampcontr %.2f | defratio %.3f"
%(self.ctfvalues['defocus1'], self.ctfvalues['defocus2'], self.ctfvalues['angle_astigmatism'],
self.ctfvalues['amplitude_contrast'], defocusratio), "blue")
self.printBestValues()
print "===================================="
return
count += 1
imagename = os.path.basename(imgfile)
imagename = imagename.replace(".mrc", "")
imgdata = apDatabase.getImageData(imagename)
### change project
projid = apProject.getProjectIdFromImageData(imgdata)
newdbname = apProject.getAppionDBFromProjectId(projid)
sinedon.setConfig('appiondata', db=newdbname)
powerspecfile = apDisplay.short(imagename)+"-powerspec.jpg"
if os.path.isfile(powerspecfile):
apDisplay.printColor("Skipping image %s, already complete"%(apDisplay.short(imagename)), "cyan")
continue
ctfdata = ctfdb.getBestCtfByResolution(imgdata)
#ctfdata, bestconf = ctfdb.getBestCtfValueForImage(imgdata, method="ctffind")
#ctfdata, bestconf = ctfdb.getBestCtfValueForImage(imgdata, method="ace2")
if ctfdata is None:
apDisplay.printColor("Skipping image %s, no CTF data"%(apDisplay.short(imagename)), "red")
continue
#print ctfdata
if ctfdata['confidence_30_10'] < 0.88:
apDisplay.printColor("Skipping image %s, poor confidence"%(apDisplay.short(imagename)), "red")
continue
"""
if ctfdata['resolution_50_percent'] > 10 or ctfdata['resolution_50_percent'] < 7.5:
apDisplay.printColor("Skipping image %s, not right 50per resolution"%(apDisplay.short(imagename)), "red")
continue
if ctfdata['resolution_80_percent'] > 13 or ctfdata['resolution_80_percent'] < 8.5:
apDisplay.printColor("Skipping image %s, not right 80per resolution"%(apDisplay.short(imagename)), "red")
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):
"""
time ./ctffind3.exe << eof
Input image file name [input.mrc] : 15aug13neil2_14jul14d_05sq_012hl_02ed-a.mrc
Output diagnostic filename
[diagnostic_output.mrc] : 15aug13neil2_14jul14d_05sq_012hl_02ed-a-pow.mrc
Pixel size [1.0] : 2.7
Acceleration voltage [300.0] : 300
Spherical aberration [2.7] : 2.7
Amplitude contrast [0.07] : 0.07
Size of power spectrum to compute [512] : 512
Minimum resolution [30.0] : 20
Maximum resolution [5.0] : 5
Minimum defocus [5000.0] :
Maximum defocus [50000.0] :
Defocus search step [500.0] :
Expected (tolerated) astigmatism [100.0] :
Find additional phase shift? [no] :
"""
paramInputOrder = ['input', 'output', 'apix', 'kv', 'cs', 'ampcontrast', 'fieldsize',
'resmin', 'resmax', 'defmin', 'defmax', 'defstep', 'expect_astig', 'phase', 'newline',]
#get Defocus in Angstroms
self.ctfvalues = {}
nominal = abs(imgdata['scope']['defocus']*-1.0e10)
ctfvalue = ctfdb.getBestCtfByResolution(imgdata)
if ctfvalue is not None:
"""
## CTFFIND V3.5 (7-March-2012) prefers the smaller of the two values for astigmatic images
I found that say you have an image with 1.1um and 1.5um defocus astigmatism. If you give
CTFFIND the average value of 1.3um for the defocus and 0.4um astig (dast) then it will
try to fit 1.3um and 1.8um, so you need to give it the minimum value (1.1um) for it to
fit 1.1um and 1.5um.
"""
bestdef = min(ctfvalue['defocus1'],ctfvalue['defocus2'])*1.0e10
else:
bestdef = nominal
if ctfvalue is not None and self.params['bestdb'] is True:
bestampcontrast = round(ctfvalue['amplitude_contrast'],3)
beststigdiff = round(abs(ctfvalue['defocus1'] - ctfvalue['defocus2'])*1e10,1)
else:
bestampcontrast = self.params['ampcontrast']
beststigdiff = self.params['dast']*10000.
if ctfvalue is not None and self.params['bestdb'] is True:
### set res max from resolution_80_percent
gmean = (ctfvalue['resolution_80_percent']*ctfvalue['resolution_50_percent']*self.params['resmax'])**(1/3.)
if gmean < self.params['resmin']*0.9:
# replace only if valid Issue #3291
self.params['resmax'] = round(gmean,2)
apDisplay.printColor("Setting resmax to the geometric mean of resolution values", "purple")
# dstep is the physical detector pixel size
apix = apDatabase.getPixelSize(imgdata)
# inputparams defocii and astig are in Angstroms
inputparams = {
'orig': os.path.join(imgdata['session']['image path'], imgdata['filename']+".mrc"),
'input': apDisplay.short(imgdata['filename'])+".mrc",
'output': apDisplay.short(imgdata['filename'])+"-pow.mrc",
'apix': apix,
'kv': imgdata['scope']['high tension']/1000.0,
'cs': self.params['cs'],
'ampcontrast': bestampcontrast,
'fieldsize': self.params['fieldsize'],
'resmin': self.params['resmin'],
'resmax': self.params['resmax'],
'defstep': self.params['defstep']*10000., #round(defocus/32.0, 1),
'expect_astig': beststigdiff,
'phase': 'no', # this is a secondary amp contrast term for phase plates
'newline': '\n',
}
defrange = self.params['defstep'] * self.params['numstep'] * 1e4 ## do 25 steps in either direction # in angstrum
inputparams['defmin']= round(bestdef-defrange, 1) #in angstrom
if inputparams['defmin'] < 0:
apDisplay.printWarning("Defocus minimum is less than zero")
inputparams['defmin'] = inputparams['defstep']
inputparams['defmax']= round(bestdef+defrange, 1) #in angstrom
apDisplay.printColor("Defocus search range: %d A to %d A (%.2f to %.2f um)"
%(inputparams['defmin'], inputparams['defmax'],
inputparams['defmin']*1e-4, inputparams['defmax']*1e-4), "cyan")
### secondary lock check right before it starts on the real part
if self.params['parallel'] and os.path.isfile(apDisplay.short(imgdata['filename'])+".mrc"):
# This is a secondary image lock check, checking the first output of the process.
# It alone is not good enough
apDisplay.printWarning('Some other parallel process is working on the same image. Skipping')
return
### create local link to image
if not os.path.exists(inputparams['input']):
os.symlink(inputparams['orig'], inputparams['input'])
if os.path.isfile(inputparams['output']):
# program crashes if this file exists
apFile.removeFile(inputparams['output'])
t0 = time.time()
apDisplay.printMsg("running ctf estimation at "+time.asctime())
for paramName in paramInputOrder:
apDisplay.printColor("%s = %s"%(paramName,inputparams[paramName]),"magenta")
print ""
ctfprogproc = subprocess.Popen(self.ctfprgmexe, shell=True, stdin=subprocess.PIPE,)
apDisplay.printColor(self.ctfprgmexe, "magenta")
for paramName in paramInputOrder:
apDisplay.printColor(inputparams[paramName],"magenta")
ctfprogproc.stdin.write(str(inputparams[paramName])+'\n')
ctfprogproc.communicate()
tdiff = time.time()-t0
apDisplay.printMsg("ctf estimation completed in "+apDisplay.timeString(tdiff))
if tdiff < 1.0:
apDisplay.printError("Failed to run CTFFIND4 program...")
### cannot run ctffind_plot_results.sh on CentOS 6
# This script requires gnuplot version >= 4.6, but you have version 4.2
### parse ctf estimation output
self.ctfvalues = {}
ctfproglog = apDisplay.short(imgdata['filename'])+"-pow.txt"
apDisplay.printMsg("reading %s"%(ctfproglog))
logf = open(ctfproglog, "r")
for line in logf:
sline = line.strip()
if sline.startswith('#'):
continue
bits = sline.split()
self.ctfvalues = {
'imagenum': int(float(bits[0])),
'defocus2': float(bits[1])*1e-10,
'defocus1': float(bits[2])*1e-10,
'angle_astigmatism': float(bits[3]),
'extra_phase': float(bits[4]),
'amplitude_contrast': inputparams['ampcontrast'],
'cross_correlation': float(bits[5]),
'ctffind4_resolution': float(bits[6]),
'defocusinit': bestdef*1e-10,
'cs': self.params['cs'],
'volts': imgdata['scope']['high tension'],
'confidence': float(bits[5]),
'confidence_d': round(math.sqrt(abs(float(bits[5]))), 5)
}
print self.ctfvalues
#convert powerspectra to JPEG
outputjpgbase = apDisplay.short(imgdata['filename'])+"-pow.jpg"
self.lastjpg = outputjpgbase
outputjpg = os.path.join(self.powerspecdir, self.lastjpg)
powspec = apImage.mrcToArray(inputparams['output'])
apImage.arrayToJpeg(powspec, outputjpg)
shutil.move(inputparams['output'], os.path.join(self.powerspecdir, inputparams['output']))
self.ctfvalues['graph1'] = outputjpg
#apFile.removeFile(inputparams['input'])
return
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
