Ritiek Malhotra Just some of my adventures!

Structuring our Plasma factory

We’re mostly done with structuring our Plasma factory. The PR (#459) just got merged yesterday! I’d have to say we weren’t expecting this to work out this quickly.

The reference to SunPy’s Map source made it a tad easier to understand how things are supposed to work for our PlasmaPy’s Plasma. :D

Also, SunPy’s BasicRegistrationFactory was so generic that we could have directly imported it in PlasmaPy without having to work out on one on our own (wow, that’s a lot of “o”s!). But really, I wonder if it makes more sense that they should just publish a separate PyPi package for just this registration factory.

If we didn’t had any such reference, I am certain that our factory implementation would have consumed a lot more time than we actually took.

Anyway, there are plenty of things that probably would need work in near future, like overriding methods under BasicRegistraionFactory being inherited in PlasmaFactory to make it more specific as we get to know our subclass needs, and defining generic plasma methods which are common in most plasmas (electronTemperature, ionTemperature, etc.) under a GenericPlasma class. We’ll get to learn more about these needs as we work on subclasses for our Plasma factory as well.

Currently, We’ve been discussing about what subclasses would be nice to have (some bits can be found in #458). And so, this is our next plan, to create variety of subclasses that deal with different plasma datasets.

Some of the openly available datasets we’ve located are Dense plasma database, Johns Hopkins Turbulence Database and some example datasets using the OpenPMD stanadard. By the way, if by any chance you’re working on a particle-mesh dataset, I’d recommend you to use the conventions under OpenPMD standard. It has the potential to make particle-mesh databases easier for other people to visually parse and automate!

Lately, I’ve been working with h5py python package which allows parsing the HDF5 binary data format. I’m very excited since this is going to be my first time working in such a close proximity to large scientific datasets!

That will be all for now. See ya later.