To get optimal results, it is often necessary to screen several different nominal doses, to find the best dose weighting scheme for the dataset. Currently, I do this adhoc, by rerunning motion correction on a subset of data with different nominal doses, extracting a known set of good particles, and performing a homogeneous refinement on each. This is rather slow and inefficient, though. It would be a lot faster if there was a way to take the alignment parameters from a single run of Patch Motion, and apply these to generate sets with different dose weighting (without rerunning the same motion correction job for each stack). Would this be possible to implement?
Also, in general it might be good to have a separate job for optimizing the dose weighting in a more systematic way (as Bayesian polishing effectively does in Relion). Perhaps this could be incorporated into Patch motion?