def plotCloudImage(self):
"""Generate some additional information and plots about the cloud image, if desired."""
from pImagePlots import PImagePlots
import pylab
im = PImagePlots()
im.setImage(self.cloudimage)
im.showImage(copy=True)
im.hanningFilter()
im.calcAll()
im.showPsd2d()
im.showAcovf2d()
im.showAcovf1d()
im.showSf(linear=True)
#pylab.show()
return
# Start here to invert from FFT (useI = False, and will get perfect reconstruction). im.invertFft(useI=True) # Use im2 to recalculate 1d PSD/ACovF starting from the reconstructed image, without altering the original. im2 = PImagePlots() im2.setImage(im.imageI.real, copy=True) im2.calcAll(min_dr=1.0, min_npix=2) im2.plotMore() # Now start plotting things, in comparison. clims = im.showImage() #print clims im2.showImage(clims=clims) im2.showImage() im.showFft(clims=clims) im2.showFft(clims=clims) im.showPsd2d() im2.showPsd2d() im.showPhases() im2.showPhases() im.showAcovf2d() im2.showAcovf2d(imag=False) im.showPsd1d(comparison=im2) im.showAcovf1d(comparison=im2) im.showSf(linear=True, comparison=im2) pylab.show() exit()