def binAndAddCTFlabel(self, image, ht, rpixelsize, binning=1, defocus=None):
pow = imagefun.power(image)
binned = imagefun.bin(pow, binning)
# No ctf estimation until it works better so that this node does not
# depend on coma beam-tilt calibration
s = None
ctfdata = None
'''
try:
ctfdata = fftfun.fitFirstCTFNode(pow,rpixelsize['x'], defocus, ht)
except Exception, e:
self.logger.error("ctf fitting failed: %s" % e)
ctfdata = None
if ctfdata:
self.logger.info('z0 %.3f um, zast %.3f um (%.0f ), angle= %.1f deg' % (ctfdata[0]*1e6,ctfdata[1]*1e6,ctfdata[2]*100, ctfdata[3]*180.0/math.pi))
s = '%d' % int(ctfdata[0]*1e9)
#elif self.ace2exe:
elif False:
ctfdata = self.estimateCTF(imagedata)
z0 = (ctfdata['defocus1'] + ctfdata['defocus2']) / 2
s = '%d' % (int(z0*1e9),)
'''
if s:
t = numpil.textArray(s)
t = ndimage.zoom(t, (min(binned.shape)-40.0)*0.08/(t.shape)[0])
minvalue = arraystats.min(binned)
maxvalue = arraystats.max(binned)
t = minvalue + t * (maxvalue-minvalue)
imagefun.pasteInto(t, binned, (20,20))
return binned, ctfdata
def render(self): rowmin = 0 rowmax = 0 colmin = 0 colmax = 0 for image in self.images: extents = self.imageExtents(image) if extents['row'][0] < rowmin: rowmin = extents['row'][0] if extents['row'][1] > rowmax: rowmax = extents['row'][1] if extents['column'][0] < colmin: colmin = extents['column'][0] if extents['column'][1] > colmax: colmax = extents['column'][1] totalshape = 2*max(rowmax,-rowmin), 2*max(colmax,-colmin) background = self.images[0]['image'][(0,0)] finalimage = numpy.ones(totalshape, self.images[0]['image'].dtype) finalimage = background * finalimage center = finalimage.shape[0]/2, finalimage.shape[1]/2 for image in self.images: extents = self.imageExtents(image) pos = center[0]+extents['row'][0], center[1]+extents['column'][0] imagefun.pasteInto(image['image'], finalimage, pos) if len(self.images) > 1: extents = self.imageExtents(self.images[1]) scalerow = (extents['row'][0]+extents['row'][1])/2 scalecol = (extents['column'][0]+extents['column'][1])/2 scale = math.sqrt(scalerow**2+scalecol**2) else: scale = None return finalimage, scale
def render(self):
rowmin = 0
rowmax = 0
colmin = 0
colmax = 0
for image in self.images:
extents = self.imageExtents(image)
if extents['row'][0] < rowmin:
rowmin = extents['row'][0]
if extents['row'][1] > rowmax:
rowmax = extents['row'][1]
if extents['column'][0] < colmin:
colmin = extents['column'][0]
if extents['column'][1] > colmax:
colmax = extents['column'][1]
# odd number total shape allows center on the pixel and reduce truncation error
totalshape = 2*(max(rowmax,-rowmin))+1, 2*(max(colmax,-colmin))+1
background = self.images[0]['image'][(0,0)]
finalimage = numpy.ones(totalshape, self.images[0]['image'].dtype)
finalimage = background * finalimage
center = finalimage.shape[0]/2, finalimage.shape[1]/2
for image in self.images:
extents = self.imageExtents(image)
pos = center[0]+extents['row'][0], center[1]+extents['column'][0]
imagefun.pasteInto(image['image'], finalimage, pos)
if len(self.images) > 1:
extents = self.imageExtents(self.images[1])
scalerow = (extents['row'][0]+extents['row'][1])/2
scalecol = (extents['column'][0]+extents['column'][1])/2
scale = math.sqrt(scalerow**2+scalecol**2)
else:
scale = None
return finalimage, scale
def binAndAddCTFlabel(self,
image,
ht,
cs,
rpixelsize,
binning=1,
defocus=None):
pow = imagefun.power(image)
binned = imagefun.bin(pow, binning)
# No ctf estimation until it works better so that this node does not
# depend on coma beam-tilt calibration
s = None
ctfdata = None
'''
try:
ctfdata = fftfun.fitFirstCTFNode(pow,rpixelsize['x'], defocus, ht, cs)
except Exception, e:
self.logger.error("ctf fitting failed: %s" % e)
ctfdata = None
if ctfdata:
self.logger.info('z0 %.3f um, zast %.3f um (%.0f ), angle= %.1f deg' % (ctfdata[0]*1e6,ctfdata[1]*1e6,ctfdata[2]*100, ctfdata[3]*180.0/math.pi))
s = '%d' % int(ctfdata[0]*1e9)
#elif self.ace2exe:
elif False:
ctfdata = self.estimateCTF(imagedata)
z0 = (ctfdata['defocus1'] + ctfdata['defocus2']) / 2
s = '%d' % (int(z0*1e9),)
'''
if s:
t = numpil.textArray(s)
t = ndimage.zoom(t,
(min(binned.shape) - 40.0) * 0.08 / (t.shape)[0])
minvalue = arraystats.min(binned)
maxvalue = arraystats.max(binned)
t = minvalue + t * (maxvalue - minvalue)
imagefun.pasteInto(t, binned, (20, 20))
return binned, ctfdata
ctfdata = None
if ctfdata:
self.logger.info('z0 %.3f um, zast %.3f um (%.0f ), angle= %.1f deg' % (ctfdata[0]*1e6,ctfdata[1]*1e6,ctfdata[2]*100, ctfdata[3]*180.0/math.pi))
s = '%d' % int(ctfdata[0]*1e9)
#elif self.ace2exe:
elif False:
ctfdata = self.estimateCTF(imagedata)
z0 = (ctfdata['defocus1'] + ctfdata['defocus2']) / 2
s = '%d' % (int(z0*1e9),)
if s:
t = numpil.textArray(s)
t = ndimage.zoom(t, (min(binned.shape)-40.0)*0.08/(t.shape)[0])
minvalue = arraystats.min(binned)
maxvalue = arraystats.max(binned)
t = minvalue + t * (maxvalue-minvalue)
imagefun.pasteInto(t, binned, (20,20))
return binned, ctfdata
def estimateCTF(self, imagedata):
mag = imagedata['scope']['magnification']
tem = imagedata['scope']['tem']
cam = imagedata['camera']['ccdcamera']
pixelsize = self.btcalclient.getPixelSize(mag, tem, cam)
inputparams = {
'input': os.path.join(imagedata['session']['image path'],imagedata['filename']+".mrc"),
'cs': 2.0,
'kv': imagedata['scope']['high tension']/1000.0,
'apix': pixelsize*1e10,
'binby': 1,
}