code: def sample_image(d, data, u, v, w, i=-1, verbose=0, imager='xy', wres=100):
      
  
      if i == -1:
          i = len(data)/2
  
      if imager == 'xy':
          image = rtlib.imgonefullxy(n.outer(u, d['freq']/d['freq_orig'][0]), n.outer(v, d['freq']/d['freq_orig'][0]), data[i], d['npixx'], d['npixy'], d['uvres'], verbose=verbose)
      elif imager == 'w':
          npix = max(d['npixx'], d['npixy'])
          bls, uvkers = rtlib.genuvkernels(w, wres, npix, d['uvres'], ksize=21, oversample=1)
          image = rtlib.imgonefullw(n.outer(u, d['freq']/d['freq_orig'][0]), n.outer(v, d['freq']/d['freq_orig'][0]), data[i], npix, d['uvres'], bls, uvkers, verbose=verbose)
  
  #        bls, lmkers = rtlib.genlmkernels(w, wres, npix, d['uvres'])
  #        image = rtlib.imgonefullw(n.outer(u, d['freq']/d['freq_orig'][0]), n.outer(v, d['freq']/d['freq_orig'][0]), data[i], npix, d['uvres'], [bls[0]], [lmkers[0]], verbose=verbose)
  
      return image
docs: Samples one integration and returns image
      i is integration to image. Default is mid int.