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
im.makeImageFromSf(sfx=xr, sf=SF)
im.showAcovf1d()
im.showPsd2dI()
# Trim image to desired final size
trim = round((imsize - final_imsize)/2.0)
print 'Trimming about %d pixels from each side' %(trim)
image = im.imageI[trim:trim+final_imsize, trim:trim+final_imsize]
image = rescaleImage(image.real, sigma_goal, kappa)
imsize = len(image)
pixscale = pixscale
rad_fov = imsize/2.0*pixscale
print 'Image After Trimming: Rad_fov', rad_fov, 'Imsize', imsize, 'Pixscale', pixscale, 'deg/pix', '(', pixscale*60.*60., 'arcsec/pix)'
im.setImage(image.real)
imageStats(im.image)
im.showImage(copy=True)
im.hanningFilter()
im.calcAll()
im.showPsd2d()
im.showAcovf2d()
im.showAcovf1d(comparison=im)
# And also try to make an image with the same (final) pixel scale, but that will be created (first)
# larger and then scaled down, to avoid introducing artifacts from the ACovF1d being truncated.
final_imsize = 1500 # pixels desired in final image
final_rad_fov = 1.75*numpy.sqrt(2) # degrees
final_pixscale = 2*final_rad_fov / float(final_imsize)
# Start with larger image
pixscale = final_pixscale
rad_fov = final_rad_fov*2.
imsize = int(2*rad_fov / pixscale)
if (imsize%2 != 0):