UFOV.setTitle("UFOV")
UFOV.show()
CFOV_fraction = 0.75 # choose the fraction of the UFOV that defines the CFOV
IJ.run(original, "Scale... ", "x=" + str(CFOV_fraction) + " y=" +
str(CFOV_fraction) + " centered") # rescale bounding box to get CFOV
CFOV = Duplicator().run(
original) # duplicate the original image, only the CFOV
CFOV.setTitle("CFOV")
CFOV.show()
######### Nema process including Re-bin image to larger pixels ################################################################################
desired_pixel_width = getPixel(
) # 6.4 mm default, remember tolerance is +/-30%
current_pixel_width = CFOV.getCalibration(
).pixelWidth #get pixel width, 1.16 mm
shrink_factor = int(desired_pixel_width /
current_pixel_width) # must be an integer
IJ.run(CFOV, "Bin...", "x=" + str(shrink_factor) + " y=" + str(shrink_factor) +
" bin=Sum") # run the bin plugin
IJ.run(CFOV, "Convolve...",
"text1=[1 2 1\n2 4 2\n1 2 1\n] normalize") # apply the nema filter
######## Analyse pixels
CFOVpixels = CFOV.getProcessor().convertToFloat().getPixels(
) # access processor, get float array of pixels
CFOVmean = sum(CFOVpixels) / len(CFOVpixels)
#pixels_above_threshold = filter(lambda pix: pix > 0.75*mean, pixels) # return a new array with values above zero, use anonymous function
CFOVunifiormity = getUniformity(min(CFOVpixels), max(CFOVpixels))
UFOV = Duplicator().run(original) # duplicate the original image, only the CFOV
UFOV.setTitle("UFOV")
UFOV.show()
CFOV_fraction = 0.75 # choose the fraction of the UFOV that defines the CFOV
IJ.run(original,"Scale... ", "x="+str(CFOV_fraction)+" y="+str(CFOV_fraction)+" centered") # rescale bounding box to get CFOV
CFOV = Duplicator().run(original) # duplicate the original image, only the CFOV
CFOV.setTitle("CFOV")
CFOV.show()
######### Nema process including Re-bin image to larger pixels ################################################################################
desired_pixel_width = getPixel() # 6.4 mm default, remember tolerance is +/-30%
current_pixel_width = CFOV.getCalibration().pixelWidth #get pixel width, 1.16 mm
shrink_factor = int(desired_pixel_width/current_pixel_width) # must be an integer
IJ.run(CFOV, "Bin...", "x="+str(shrink_factor)+" y="+str(shrink_factor)+" bin=Sum") # run the bin plugin
IJ.run(CFOV, "Convolve...", "text1=[1 2 1\n2 4 2\n1 2 1\n] normalize") # apply the nema filter
######## Analyse pixels
CFOVpixels = CFOV.getProcessor().convertToFloat().getPixels() # access processor, get float array of pixels
CFOVmean = sum(CFOVpixels) / len(CFOVpixels)
#pixels_above_threshold = filter(lambda pix: pix > 0.75*mean, pixels) # return a new array with values above zero, use anonymous function
CFOVunifiormity = getUniformity(min(CFOVpixels), max(CFOVpixels))
######## Print results
results_string = "The integral uniformity of the CFOV is: " +str(CFOVunifiormity)+ "% for pixel size of "+str(desired_pixel_width)+" mm"
IJ.log(results_string)
IJ.showMessage(results_string)
