code: def dorun(SNR=20, sweeps=20, burn=8, noise_samples=10):
      
      radii = np.linspace(2,10,8, endpoint=False)
      crbs, vals, errs = [], [], []
  
      for radius in radii:
          print 'radius', radius
          s,im = pxint(radius=radius, factor=4)
          goodstate = s.state.copy()
  
          common.set_image(s, im, 1.0/SNR)
          tcrb = crb(s)
          tval, terr = sample(s, im, 1.0/SNR, N=noise_samples, sweeps=sweeps, burn=burn)
          crbs.append(tcrb)
          vals.append(tval)
          errs.append(terr)
  
      return np.array(crbs), np.array(vals), np.array(errs), radii
docs: we want to display the errors introduced by pixelation so we plot:
          * zero noise, cg image, fit
          * SNR 20, cg image, fit
          * CRB for both
  
      a = dorun(noise_samples=30, sweeps=24, burn=12, SNR=20)