def grid_wt(vis, model, g): if vis is not None: if model is not None: griddata = create_griddata_from_image(model) griddata = grid_weight_to_griddata(vis, griddata, g[0][1]) return griddata else: return None else: return None
def re_weight(vis, model, gd, g): if gd is not None: if vis is not None: # Ensure that the griddata has the right axes so that the convolution # function mapping works agd = create_griddata_from_image(model) agd.data = gd[0].data vis = griddata_reweight(vis, agd, g[0][1]) return vis else: return None else: return vis