deepCR for flc and drc images

deepCR_drc.py

import glob
import numpy as np
import os 
import shutil
from deepCR import deepCR
from astropy.io import fits

# dq flag: http://www.stsci.edu/hst/instrumentation/acs/data-analysis/dq-flag-definitions

# dq flag: http://www.stsci.edu/hst/instrumentation/acs/data-analysis/dq-flag-definitions

def make_crclean(filename, model, threshold=0.5):
    fext = filename.split('_')[-1].split('.fit')[0]
    cleanfile = filename.replace(fext, 'crclean')
    shutil.copy(filename, cleanfile)
    is_drizzled = fext.startswith('dr')

    with fits.open(cleanfile, mode='update') as hdulist:
        if is_drizzled:
            exptime = hdulist[0].header['TEXPTIME']
        for i, ext in enumerate(hdulist):
            if ext.name == 'SCI':
                image = ext.data.copy()
                if is_drizzled:
                    image *= exptime
                    image[~np.isfinite(image)] = 0.
                mask, cleaned_image = model.clean(image, threshold=threshold, inpaint=True, n_jobs=1)
                if is_drizzled:
                    cleaned_image[~np.isfinite(ext.data)] = np.nan
                    cleaned_image /= exptime
                ext.data = cleaned_image.astype(np.float32)
                hdulist.flush()
                if ((len(hdulist) > i+2) & ~is_drizzled):
                    if (hdulist[i+2].name == 'DQ'):
                        hdulist[i+2].data[mask.astype(bool)] += 16384

model = deepCR(mask='ACS-WFC-F606W-2-4', inpaint='ACS-WFC-F606W-2-32', device='CPU')
files = glob.glob('data/*_??c.fits')
for f in files:
    if (f.endswith('drc.fits') | f.endswith('flc.fits')):
        if not os.path.exists(f.replace('drc','crclean').replace('flc','crclean')):
            try:
                make_crclean(f, model)
                print(f'Made crcleaned copy of {f}')
            except Exception as exc:
                print(f'Failed on {f}')
                print(exc)