def getTiltedCoordinates(img1, img2, tiltdiff, picks1=[], angsearch=True, inittiltaxis=-7.2, msg=True):
"""
takes two images tilted
with respect to one another
and tries to find overlap
img1 (as numpy array)
img2 (as numpy array)
tiltdiff (in degrees)
negative, img1 is more compressed (tilted)
positive, img2 is more compressed (tilted)
picks1, list of particles picks for image 1
"""
t0 = time.time()
#shrink images
bin = 2
binned1 = apImage.binImg(img1, bin)
binned2 = apImage.binImg(img2, bin)
#apImage.arrayToJpeg(binned1, "binned1.jpg")
#apImage.arrayToJpeg(binned2, "binned2.jpg")
filt1 = apImage.highPassFilter(binned1, apix=1.0, radius=20.0, localbin=4/bin)
filt2 = apImage.highPassFilter(binned2, apix=1.0, radius=20.0, localbin=4/bin)
#apImage.arrayToJpeg(filt1, "filt1.jpg")
#apImage.arrayToJpeg(filt2, "filt2.jpg")
if angsearch is True:
bestsnr = 0
bestangle = None
### rough refine
#for angle in [-6, -4, -2,]:
# sys.stderr.write(".")
# shift, xfactor, snr = getTiltedRotateShift(filt1, filt2, tiltdiff, angle, bin, msg=False)
# if snr > bestsnr:
# bestsnr = snr
# bestangle = angle
bestangle = inittiltaxis
if msg is True:
apDisplay.printMsg("Best tilt axis angle= %.1f; SNR=%.2f"%(bestangle,bestsnr))
### finer refine
for angle in [bestangle-1, bestangle-0.5, bestangle+0.5, bestangle+1]:
if msg is True:
sys.stderr.write(".")
shift, xfactor, snr = getTiltedRotateShift(filt1, filt2, tiltdiff, angle, bin, msg=False)
if snr > bestsnr:
bestsnr = snr
bestangle = angle
if msg is True:
apDisplay.printMsg("Best tilt axis angle= %.1f; SNR=%.2f"%(bestangle,bestsnr))
### really fine refine
for angle in [bestangle-0.2, bestangle-0.1, bestangle+0.1, bestangle+0.2]:
if msg is True:
sys.stderr.write(".")
shift, xfactor, snr = getTiltedRotateShift(filt1, filt2, tiltdiff, angle, bin, msg=False)
if snr > bestsnr:
bestsnr = snr
bestangle = angle
if msg is True:
apDisplay.printMsg("Best tilt axis angle= %.1f; SNR=%.2f"%(bestangle,bestsnr))
shift, xfactor, snr = getTiltedRotateShift(filt1, filt2, tiltdiff, bestangle, bin, msg=msg)
if msg is True:
apDisplay.printMsg("Best tilt axis angle= %.1f; SNR=%.2f"%(bestangle,bestsnr))
else:
bestangle = 0.0
shift, xfactor, snr = getTiltedRotateShift(img1, img2, tiltdiff, bestangle, bin)
if msg and min(abs(shift)) < min(img1.shape)/16.0:
apDisplay.printWarning("Overlap was too close to the edge and possibly wrong.")
### case 1: find tilted center of first image
center = numpy.asarray(img1.shape)/2.0
newpoint = translatePoint(center, center, shift, bestangle, xfactor)
#print "newpoint=", newpoint
halfsh = (center + newpoint)/2.0
origin = halfsh
### case 2: using a list of picks
if len(picks1) > 1:
#get center most pick
dmin = origin[0]/2.0
for pick in picks1:
da = numpy.hypot(pick[0]-halfsh[0], pick[1]-halfsh[1])
if da < dmin:
dmin = da
origin = pick
# origin is pick from image 1
# newpart is pick from image 2
newpart = translatePoint(origin, center, shift, bestangle, xfactor)
newpart2 = numpy.array([(origin[0]*xfactor-shift[0])*xfactor, origin[1]-shift[1]])
if msg is True:
apDisplay.printMsg("origin=(%d,%d); newpart=(%.1f,%.1f); newpart2=(%.1f,%.1f)"
%(origin[0],origin[1], newpart[0],newpart[1], newpart2[0],newpart2[1],))
apDisplay.printMsg("completed in "+apDisplay.timeString(time.time()-t0))
return origin, newpart, snr, bestangle
### check to make sure points are not off the edge
while newpart[0] < 10:
newpart += numpy.asarray((20,0))
origin += numpy.asarray((20,0))
while newpart[1] < 10:
newpart += numpy.asarray((0,20))
origin += numpy.asarray((0,20))
while newpart[0] > img1.shape[0]-10:
newpart -= numpy.asarray((20,0))
origin -= numpy.asarray((20,0))
while newpart[1] > img1.shape[1]-10:
newpart -= numpy.asarray((0,20))
origin -= numpy.asarray((0,20))
return origin, newpart
def getTiltedCoordinates(img1, img2, tiltdiff, picks1=[], angsearch=True, inittiltaxis=-7.2, msg=True):
"""
takes two images tilted
with respect to one another
and tries to find overlap
img1 (as numpy array)
img2 (as numpy array)
tiltdiff (in degrees)
negative, img1 is more compressed (tilted)
positive, img2 is more compressed (tilted)
picks1, list of particles picks for image 1
"""
t0 = time.time()
#shrink images
bin = 2
binned1 = apImage.binImg(img1, bin)
binned2 = apImage.binImg(img2, bin)
#apImage.arrayToJpeg(binned1, "binned1.jpg")
#apImage.arrayToJpeg(binned2, "binned2.jpg")
filt1 = apImage.highPassFilter(binned1, apix=1.0, radius=20.0, localbin=4/bin)
filt2 = apImage.highPassFilter(binned2, apix=1.0, radius=20.0, localbin=4/bin)
#apImage.arrayToJpeg(filt1, "filt1.jpg")
#apImage.arrayToJpeg(filt2, "filt2.jpg")
if angsearch is True:
bestsnr = 0
bestangle = None
### rough refine
#for angle in [-6, -4, -2,]:
# sys.stderr.write(".")
# shift, xfactor, snr = getTiltedRotateShift(filt1, filt2, tiltdiff, angle, bin, msg=False)
# if snr > bestsnr:
# bestsnr = snr
# bestangle = angle
bestangle = inittiltaxis
if msg is True:
apDisplay.printMsg("Best tilt axis angle= %.1f; SNR=%.2f"%(bestangle,bestsnr))
### finer refine
for angle in [bestangle-1, bestangle-0.5, bestangle+0.5, bestangle+1]:
if msg is True:
sys.stderr.write(".")
shift, xfactor, snr = getTiltedRotateShift(filt1, filt2, tiltdiff, angle, bin, msg=False)
if snr > bestsnr:
bestsnr = snr
bestangle = angle
if msg is True:
apDisplay.printMsg("Best tilt axis angle= %.1f; SNR=%.2f"%(bestangle,bestsnr))
### really fine refine
for angle in [bestangle-0.2, bestangle-0.1, bestangle+0.1, bestangle+0.2]:
if msg is True:
sys.stderr.write(".")
shift, xfactor, snr = getTiltedRotateShift(filt1, filt2, tiltdiff, angle, bin, msg=False)
if snr > bestsnr:
bestsnr = snr
bestangle = angle
if msg is True:
apDisplay.printMsg("Best tilt axis angle= %.1f; SNR=%.2f"%(bestangle,bestsnr))
shift, xfactor, snr = getTiltedRotateShift(filt1, filt2, tiltdiff, bestangle, bin, msg=msg)
if msg is True:
apDisplay.printMsg("Best tilt axis angle= %.1f; SNR=%.2f"%(bestangle,bestsnr))
else:
bestangle = 0.0
shift, xfactor, snr = getTiltedRotateShift(img1, img2, tiltdiff, bestangle, bin)
if msg and min(abs(shift)) < min(img1.shape)/16.0:
apDisplay.printWarning("Overlap was too close to the edge and possibly wrong.")
### case 1: find tilted center of first image
center = numpy.asarray(img1.shape)/2.0
newpoint = translatePoint(center, center, shift, bestangle, xfactor)
#print "newpoint=", newpoint
halfsh = (center + newpoint)/2.0
origin = halfsh
### case 2: using a list of picks
if len(picks1) > 1:
#get center most pick
dmin = origin[0]/2.0
for pick in picks1:
da = numpy.hypot(pick[0]-halfsh[0], pick[1]-halfsh[1])
if da < dmin:
dmin = da
origin = pick
# origin is pick from image 1
# newpart is pick from image 2
newpart = translatePoint(origin, center, shift, bestangle, xfactor)
newpart2 = numpy.array([(origin[0]*xfactor-shift[0])*xfactor, origin[1]-shift[1]])
if msg is True:
apDisplay.printMsg("origin=(%d,%d); newpart=(%.1f,%.1f); newpart2=(%.1f,%.1f)"
%(origin[0],origin[1], newpart[0],newpart[1], newpart2[0],newpart2[1],))
apDisplay.printMsg("completed in "+apDisplay.timeString(time.time()-t0))
return origin, newpart, snr, bestangle
### check to make sure points are not off the edge
while newpart[0] < 10:
newpart += numpy.asarray((20,0))
origin += numpy.asarray((20,0))
while newpart[1] < 10:
newpart += numpy.asarray((0,20))
origin += numpy.asarray((0,20))
while newpart[0] > img1.shape[0]-10:
newpart -= numpy.asarray((20,0))
origin -= numpy.asarray((20,0))
while newpart[1] > img1.shape[1]-10:
newpart -= numpy.asarray((0,20))
origin -= numpy.asarray((0,20))
return origin, newpart
def getTiltedRotateShift(img1, img2, tiltdiff, angle=0, bin=1, msg=True):
"""
takes two images tilted
with respect to one another
and tries to find overlap
img1 (as numpy array)
img2 (as numpy array)
tiltdiff (in degrees)
negative, img1 is more compressed (tilted)
positive, img2 is more compressed (tilted)
"""
### untilt images by stretching and compressing
# choose angle s/t compressFactor = 1/stretchFactor
# this only works if one image is untilted (RCT) of both images are opposite tilt (OTR)
#halftilt = abs(tiltdiff)/2.0
halftiltrad = math.acos(math.sqrt(math.cos(abs(tiltdiff)/180.0*math.pi)))
# go from zero tilt to half tilt
compressFactor = math.cos(halftiltrad)
# go from max tilt to half tilt
stretchFactor = math.cos(halftiltrad) / math.cos(abs(tiltdiff)/180.0*math.pi)
if tiltdiff > 0:
if msg is True:
apDisplay.printMsg("compress image 1")
untilt1 = transformImage(img1, compressFactor, angle)
untilt2 = transformImage(img2, stretchFactor, angle)
xfactor = compressFactor
else:
if msg is True:
apDisplay.printMsg("stretch image 1")
untilt1 = transformImage(img1, stretchFactor, angle)
untilt2 = transformImage(img2, compressFactor, angle)
xfactor = stretchFactor
### filtering was done earlier
filt1 = untilt1
filt2 = untilt2
if filt1.shape != filt2.shape:
newshape = ( max(filt1.shape[0],filt2.shape[0]), max(filt1.shape[1],filt2.shape[1]) )
apDisplay.printMsg("Resizing images to: "+str(newshape))
filt1 = apImage.frame_constant(filt1, newshape, filt1.mean())
filt2 = apImage.frame_constant(filt2, newshape, filt2.mean())
### cross-correlate
cc = correlator.cross_correlate(filt1, filt2, pad=True)
rad = min(cc.shape)/20.0
cc = apImage.highPassFilter(cc, radius=rad)
cc = apImage.normRange(cc)
cc = blackEdges(cc)
cc = apImage.normRange(cc)
cc = blackEdges(cc)
cc = apImage.normRange(cc)
cc = apImage.lowPassFilter(cc, radius=10.0)
#find peak
peakdict = peakfinder.findSubpixelPeak(cc, lpf=0)
#import pprint
#pprint.pprint(peak)
pixpeak = peakdict['subpixel peak']
if msg is True:
apDisplay.printMsg("Pixel peak: "+str(pixpeak))
apImage.arrayToJpegPlusPeak(cc, "guess-cross-ang"+str(abs(angle))+".jpg", pixpeak)
rawpeak = numpy.array([pixpeak[1], pixpeak[0]]) #swap coord
shift = numpy.asarray(correlator.wrap_coord(rawpeak, cc.shape))*bin
if msg is True:
apDisplay.printMsg("Found xy-shift btw two images"
+";\n\t SNR= "+str(round(peakdict['snr'],2))
+";\n\t halftilt= "+str(round(halftiltrad*180/math.pi, 3))
+";\n\t compressFactor= "+str(round(compressFactor, 3))
+";\n\t stretchFactor= "+str(round(stretchFactor, 3))
+";\n\t xFactor= "+str(round(xfactor, 3))
+";\n\t rawpeak= "+str(numpy.around(rawpeak*bin, 1))
+";\n\t shift= "+str(numpy.around(shift, 1))
)
return shift, xfactor, peakdict['snr']
def getTiltedRotateShift(img1, img2, tiltdiff, angle=0, bin=1, msg=True):
"""
takes two images tilted
with respect to one another
and tries to find overlap
img1 (as numpy array)
img2 (as numpy array)
tiltdiff (in degrees)
negative, img1 is more compressed (tilted)
positive, img2 is more compressed (tilted)
"""
### untilt images by stretching and compressing
# choose angle s/t compressFactor = 1/stretchFactor
# this only works if one image is untilted (RCT) of both images are opposite tilt (OTR)
#halftilt = abs(tiltdiff)/2.0
halftiltrad = math.acos(math.sqrt(math.cos(abs(tiltdiff)/180.0*math.pi)))
# go from zero tilt to half tilt
compressFactor = math.cos(halftiltrad)
# go from max tilt to half tilt
stretchFactor = math.cos(halftiltrad) / math.cos(abs(tiltdiff)/180.0*math.pi)
if tiltdiff > 0:
if msg is True:
apDisplay.printMsg("compress image 1")
untilt1 = transformImage(img1, compressFactor, angle)
untilt2 = transformImage(img2, stretchFactor, angle)
xfactor = compressFactor
else:
if msg is True:
apDisplay.printMsg("stretch image 1")
untilt1 = transformImage(img1, stretchFactor, angle)
untilt2 = transformImage(img2, compressFactor, angle)
xfactor = stretchFactor
### filtering was done earlier
filt1 = untilt1
filt2 = untilt2
if filt1.shape != filt2.shape:
newshape = ( max(filt1.shape[0],filt2.shape[0]), max(filt1.shape[1],filt2.shape[1]) )
apDisplay.printMsg("Resizing images to: "+str(newshape))
filt1 = apImage.frame_constant(filt1, newshape, filt1.mean())
filt2 = apImage.frame_constant(filt2, newshape, filt2.mean())
### cross-correlate
cc = correlator.cross_correlate(filt1, filt2, pad=True)
rad = min(cc.shape)/20.0
cc = apImage.highPassFilter(cc, radius=rad)
cc = apImage.normRange(cc)
cc = blackEdges(cc)
cc = apImage.normRange(cc)
cc = blackEdges(cc)
cc = apImage.normRange(cc)
cc = apImage.lowPassFilter(cc, radius=10.0)
#find peak
peakdict = peakfinder.findSubpixelPeak(cc, lpf=0)
#import pprint
#pprint.pprint(peak)
pixpeak = peakdict['subpixel peak']
if msg is True:
apDisplay.printMsg("Pixel peak: "+str(pixpeak))
apImage.arrayToJpegPlusPeak(cc, "guess-cross-ang"+str(abs(angle))+".jpg", pixpeak)
rawpeak = numpy.array([pixpeak[1], pixpeak[0]]) #swap coord
shift = numpy.asarray(correlator.wrap_coord(rawpeak, cc.shape))*bin
if msg is True:
apDisplay.printMsg("Found xy-shift btw two images"
+";\n\t SNR= "+str(round(peakdict['snr'],2))
+";\n\t halftilt= "+str(round(halftiltrad*180/math.pi, 3))
+";\n\t compressFactor= "+str(round(compressFactor, 3))
+";\n\t stretchFactor= "+str(round(stretchFactor, 3))
+";\n\t xFactor= "+str(round(xfactor, 3))
+";\n\t rawpeak= "+str(numpy.around(rawpeak*bin, 1))
+";\n\t shift= "+str(numpy.around(shift, 1))
)
return shift, xfactor, peakdict['snr']