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):