def all_kernels(kdim, writefile=True, makeimage=False, vb=False):
## Get files -- path hard-coded
allpngs = numpy.sort(file_seek("../Data/GPSF/",
"snap*d0_CFHTLS_03_g*.png"))
## Collect pairs of files
for i in range(0, len(allpngs), 2):
## Extract image info
image1 = png_pix(allpngs[i])
image2 = png_pix(allpngs[i + 1])
## Cut out extraneous white pixels
image1 = pngcropwhite(image1)
image2 = pngcropwhite(image2)
## Deconvolve
A = get_kernel(image1, image2, kdim)
B = get_kernel(image2, image1, kdim)
##------------------------------------------------------------
## Write kernels to file and make images
## Gaussian to PSF
outfile = os.path.splitext(allpngs[i])[0][:-4] + "_GausstoPSF_" + str(
A.shape[0]) + ".krn"
f = open(outfile, "w")
f.write(
"## Convolution kernel taking 2D Gaussian to PSFEx image\n\n\n")
writearray(f, A, True)
if vb: print "DeconvolveToTargetPSF.py: kernel written to", outfile
## PSF to Gaussian
outfile = os.path.splitext(allpngs[i])[0][:-4] + "_PSFtoGauss_" + str(
B.shape[0]) + ".krn"
f = open(outfile, "w")
f.write(
"## Convolution kernel taking PSFEx image to 2D Gaussian\n\n\n")
writearray(f, B, True)
if vb: print "DeconvolveToTargetPSF.py: kernel written to", outfile
print "\n"
##------------------------------------------------------------
return
def all_kernels(kdim, writefile=True,makeimage=False, vb=False):
## Get files
allpngs = numpy.sort(file_seek("../Data/GPSF/","snap*d0_CFHTLS_03_g*.png"))
## Collect pairs of files
for i in range (0,len(allpngs),2):
## Extract image info
image1 = png_pix(allpngs[i])
image2 = png_pix(allpngs[i+1])
## Cut out extraneous white pixels
image1 = pngcropwhite(image1)
image2 = pngcropwhite(image2)
## Deconvolve
A=get_kernel(image1,image2, kdim)
B=get_kernel(image2,image1, kdim)
##------------------------------------------------------------
## Write kernels to file and make images
## Gaussian to PSF
outfile=os.path.splitext(allpngs[i])[0][:-4]+"_GausstoPSF_"+str(A.shape[0])+".krn"
f=open(outfile,"w")
f.write("## Convolution kernel taking 2D Gaussian to PSFEx image\n\n\n")
writearray(f,A,True)
if vb: print "DeconvolveToTargetPSF.py: kernel written to",outfile
## PSF to Gaussian
outfile=os.path.splitext(allpngs[i])[0][:-4]+"_PSFtoGauss_"+str(B.shape[0])+".krn"
f=open(outfile,"w")
f.write("## Convolution kernel taking PSFEx image to 2D Gaussian\n\n\n")
writearray(f,B,True)
if vb: print "DeconvolveToTargetPSF.py: kernel written to",outfile
print "\n"
##------------------------------------------------------------
return
def reconvolve(image1, image2, kernel): ## Read in images & kernel and process into shape arr1 = pngcropwhite(png_pix(image1)) kernel = numpy.loadtxt(kernel) newdim = numpy.array(arr1.shape)-numpy.array(kernel.shape)+1 arr2 = shave(newdim, pngcropwhite(png_pix(image2))) ## Reconvolved image -- should be integer array recon = numpy.around(convolve(arr1, kernel, mode="valid")) ## Residue should be 0 residue = recon-arr2 ## Visualise residue from pylab import imshow, show, colorbar imshow(residue) #colorbar() show() return
