[Openchemistry-developers] Some queries regarding cclib projects

[Geoffrey Hutchison]

Hi Kunal,

Thanks for your message. I think Adam and/or Karol can comment more, but I'll give some in-line comments to your message.

> 1. Machine Learning applied to parsing computational chemistry output: Since parser is used to get a very specific output from a specific input, what is it that we expect from the final ML pipeline. Do we want it to get all the available data from an output file (like most 
> (if not all) of the parameters mentioned in data.py)?


Right. The question is whether it's possible to teach a ML model to find all available data mentioned in data.py. This is clearly more of a research project than some of the other ideas.


> 2. Refactoring parser and Implementing new parsers: I was looking into this and saw that you thought about an approach which utilized decorators and partial parsing of the file, but maybe it was dropped? Also, can you please provide a list of the parsers you would like to extend in cclib in this GSoC ...

There are a lot of example files in the cclib data repository: 
https://github.com/cclib/cclib-data

I think the idea here is that you would choose which parsers you'd want to refactor and/or add. There are, after all, no end to the number of computational packages.


> I was thinking that given the overall duration of GSoC I would like to attempt to do more than one project (Combining two projects). What are your thoughts on this? Given the duration, would it be possible?


It depends a bit on the projects, but I can imagine these two projects could be blended (e.g., refactoring and adding new parsers while trying the ML approach).

As for the application, here's a guide on the wiki:
https://github.com/cclib/cclib-data

We usually recommend students start a proposal with Google Docs (or something similar) and share with mentors/admins to get feedback.

Hope that helps,
-Geoff

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