This package was developed to calculate the galaxy angular two-point correlation functions on actual data. It's under development and currently only contains the calculation of the angular correlation functions within a region of arbitrary outline with one depth. The correlation functions may be calculated with error estimates via single galaxy bootstrapping, block bootstrapping, or jackknifing.
Documentation: https://py2pac.readthedocs.io/en/latest/
Everything is ready for use at the most basic level of functionality: calculating correlations with error estimates. There are some more things that I want to do with the ImageMask class and a lot of fitting and post-processing that I want to put in, but nothing that is necessary for the basic functionality.
- Get the setup straightened out (make sure it knows all the requirements, actually sets up properly, etc)
- Come up with example data sets and add to repository
- Tutorial ipython notebook that walks you from importing py2pac to plotting each kind of CF. Also make sure it has the different ways to create ImageMasks
- Set up an ImageMask classmethod to deal with rotated boxes
- Incorporate variable completeness into the ImageMasks
- Fitting things
- After that, it's multi-bin catalogs.
- Parallel processing for CF calculation?
- Fixing the god-forsaken hand-made WCS instances