Python writer for MCPL files

[grzanka]

hi, this is a great tool. I saw a python code to inspect and load binary MCPL files.
Are you planning to provide a python wrapper to generate MCPL files ?
This would simplify working with python to generate phasespace files from binary files generated by other MC codes (i.e. SHIELD-HIT12A). We are discussing with @nbassler a converter (https://github.com/DataMedSci/pymchelper) which would read multiple binary files generated in parallel run of SHIELDHIT12A and then convert them into single MCPL phasespace file.

[tkittel]

Absolutely, this is planned and often discussed (see e.g. #54). However, it is not completely clear when there will be time to work on this - if lucky then maybe in the fall. For that reason, I recommend you either merge them with the mcpltool (compiled) cmdline utility, or with a bit of custom C code (look for the word "merge" in mcpl.h).

What level of custom filtering or editing would your use-case need?

[grzanka]

I believe we don't need any filtering at all. We have a python reader of the binary files generated by SHIELD-HIT12A code (https://github.com/DataMedSci/pymchelper/blob/master/pymchelper/readers/shieldhit/reader_bdo2019.py#L16) . It will be used
once we have implemented a feature of scoring phase space file in the SHIELD-HIT12A. In the reader we will have access to couple of numpy arrays which we would simply like to dump to MCPL file.
So in fact simple numpy to MCPL converter would be enough for us.

[ebknudsen]

While obviously the best thing is to wait for @tkittel to write the python-code, in the meantime, I'd write a python extension in c to do this. It is not very difficult.

[tkittel]

Well, a "numpy to MCPL converter' is basically the entire task, it is not really simple at all.

If you don't care too much about interfaces, features, and efficiency, you can hack something together. You have 4 options, depending on your tastes:

1. Use python c-types to access the functions in libmcpl.so.
2. Write a python extension in C, build against mcpl.h+libmcpl.so.
3. Simply create your own little C-application (or lib) which takes your input data and creates MCPL files via mcpl.h+libmcpl.so. Call that C-application (or lib, via ctypes) from python.
4. Read the appendix in the MCPL paper which gives the details of the MCPL format and simply write custom code for outputting your data from python directly into the MCPL binary format. This should be a lot simpler task than the general MCPL python writer, since you don't have to support any other options for output format than the ones you want to use.

I personally recommend #3, but there is no accounting for taste :-)

[ebknudsen]

Agreed - what I meant was: a hacky "for now"-solution would be simple to write.
To do it right and efficient is not necessarily simple at all.

[ebknudsen]

Hi there,
I couldn't help myself so I put something together here: https://github.com/ebknudsen/np2mcpl
It is far from fast, but works well for me up to ~10^8 particles in a single numpy array.
N.b. so far it only works with double precision.

[grzanka]

That looks good, can I install it via pip and add to my requirements? wt., 11 kwi 2023, 10:06 użytkownik Erik B Knudsen ***@***.***> napisał:

…

Hi there, I couldn't help myself so I put something together here: https://github.com/ebknudsen/np2mcpl It is far from fast, but works well for me up to ~10^8 particles in a single numpy array. — Reply to this email directly, view it on GitHub <#70 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ABYIPDLXSJQPTCZOSQBW65LXAUGJ5ANCNFSM6AAAAAAWOMFFW4> . You are receiving this because you authored the thread.Message ID: ***@***.***>

[tkittel]

Thanks Erik, I am sure some people might find this workaround pretty useful!

One caveat that you might want to make clear though is that the PDG code is hardcoded as neutrons in the output.

[ebknudsen]

@grzanka No pip yet I am afraid - I'll try to set it up though - I'll have to figure out how to deal with the mcpl-lib, but that should be possible (No pip-guru I'm afraid). For now you can simply run "python setup build" to build and then point PYTHONPATH to the build directory.

@tkittel Good point! I'll make sure to document that. The presence of a non-constant PDG could be inferred from the number of columns in the numpy array, allowing ncols to be either 9,10,12, or 13. OTOH perhaps it is better to go for the ability to set it as a flag...or both.

[tkittel]

Or perhaps it is better so simply leave it as a good example for crafty users to be able to hack on, before you get dragged flag by flag towards the complexities of the full-featured final solution ;-)

[ebknudsen]

There is that of course - you do have a point :-) The column number solution would be easy, though. That way all column gymnastics is simply up to numpy usage. I think I'll go for demanding 10 or 13 columns, and that will be that.

[aglavic]

Just want to chime in that it would be really helpful to have a python writer for me, too. It would make it much easier to use external tools when simulating samples as one can just read the events, run the tool and create new events to continue the ray-tracing after that.