I’m also throwing some ideas in the pot, but you may be interested in using the particle trajectories functionality (although this isn’t exactly covering what you’re interested into). Otherwise, I’ve had some chance with a pseudo-code as follows (to be adapted to your use case) |ds1 = yt.load("/path/to/output_78") ds2 = yt.load("/path/to/other/output") old_ids = ds1.r["PartType0", "particle_identifier"] old_order = np.argsort(old_ids) def _old_density(field, data): ids = data["PartType0", "particle_identifier"] # find ids in old_ids inds = old_order[np.searchsorted(old_ids, ids, sorter=old_order)] # this is just to make sure I haven't messed up the ids matching np.testing.assert_allclose(ids, old_ids[inds]) # Return the value of the density for those matched indices return ds1.r["density"][inds] ds2.add_field(("PartType0", "old_density"), function=_old_density, sampling_type="cell", units=…) | On 04/04/2024 18:41, Jacob Morgan wrote:
Hey! Sorry I have been so long in replying. My current installation of yt is a mess, I had to make another thread about some issues I have to fix before I can test this:
https://mail.python.org/archives/list/yt-users@python.org/thread/GM75POP42EH... _______________________________________________ yt-users mailing list --yt-users@python.org To unsubscribe send an email toyt-users-leave@python.org https://mail.python.org/mailman3/lists/yt-users.python.org/ Member address:contact@cphyc.me