search

Exo-TiC / ExoTiC-ISM

This is a repository for the reduction pipeline detailed in Wakeford, et al., 2016, ApJ. The method implements marginalization across a series of models to represent stochastic models for observatory and instrument systematics. This is primarily for HST WFC3, however, may be extended to STIS in the future.
MIT License
8 stars 6 forks source link

Increase CI test coverage #96

Closed ivalaginja closed 3 years ago

ivalaginja commented 4 years ago

We have set up CI with GitHub Actions which runs on every open PR, however our code coverage is extremely low and should be increased in the future to ensure robustness with new code and updates.

ivalaginja commented 3 years ago

Regression tests would be the most important ones I think. Those kind of test make sure that the results from running the full analysis are the same like in a previously run analysis that we confirmed to be true.

@hrwakeford it seems to me like it would be fairly easy to write some simple regression tests, as we would just be comparing numbers to numbers, e.g. the results for the marginalised parameters. I could start writing this for W17 in the case of fit_time. Does that make sense to you or would you prefer I choose a different case as our benchmark?

hrwakeford commented 3 years ago

I think that fit_time is the perfect thing to test it on as that will be used most often. The most comprehensive would be fit_all but that would not be needed in this simple "does it work" test.

hrwakeford commented 3 years ago

@ivalaginja Can we close this issue now?

hrwakeford commented 3 years ago

yes this can now be closed