This repo contains some convenience classes and notebooks for working with the SuperWASP Variable Stars project data. This is mainly intended to be a starting point for ad-hoc analysis.
- swasputils.py contains classes for loading various data products into Pandas data frames with methods for carrying out common tasks.
- aggregated_classifications.ipynb loads the aggregated classification results and displays a bar chart of the number of subjects in each class.
- display_siblings.ipynb displays all the lightcurves for a given SWASP ID. You can also give it a Zooniverse ID and it will display the lightcurves for subjects with the same SWASP ID.
- junk_vs_real_classifications.ipynb plots a few charts showing the daily numbers of real vs junk classifications in the filtering workflow.
- zooniverse_classifications.ipynb plots an area chart showing the daily classification rate for each workflow.
- zooniverse_retirement.ipynb plots an area chart showing the daily retirement rate for each workflow.
- zooniverse_sets.ipynb plots a bar chart of the number of active subjects per subject set in each workflow.
These scripts assume you have the various .csv and .dat files saved in a folder, given in swasputils.DATA_LOCATION.