NOTE: On jamaica we are just using python3 not python or any virtual environment
- Run test/BTK_check.py to generate a set of FITS object
- Generates sample images with BTK + Input Catalog
- Detects with SEP
- Deblends with Scarlet
- Create data frame with all relevant images (original, isolated, reconstructed)
- Stores Scarlet fluxes results
- Run process_fits.py to get SExtractor output
- Creates fits for each noisy / reconstructed image
- Runs SEx on noisy to get background rms
- Runs SEx on reconstructed to get relevant photometry. Uses forced photometry (detection in i-band, measurement in others)
- Run fitspandas.py to get final data frame with just photometry
- Formats all noisy/recon photometry into data frame
- Properly estimates reconstructed errors for photometry
- TODO: Make the scaling nmax read from the fits folder and properly yoink the largest number