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
Exemplo n.º 2
0
	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
Exemplo n.º 4
0
    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
Exemplo n.º 5
0
			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,
		}