A Jupyter Notebook that calculates RMS and NEG images from user-supplied SCI and WHT drizzles.
Please cite Revalski et al. 2023, ApJS, 265, 40 and this Zenodo DOI when publishing results that used this code.
This Jupyter Notebook was created by Dr. Mitchell Revalski to generate negative (NEG) and root-mean-square (RMS) images from user-supplied Hubble Space Telescope (HST) Wide Field Camera 3 (WFC3) science (SCI) and inverse variance weight map (WHT) drizzles that were produced with DrizzlePac's AstroDrizzle software. These images are useful for determining detection thresholds and estimating noise properties when measuring the photometry of objects in the SCI image with Source Extractor and similar codes. The code is specifically designed to use WHT maps that were generated with final_wht_type='IVM'.
If you prefer to run the code as a terminal script, you can use create_neg_rms_img.py and print the codes help message using:
python -c "import create_neg_rms_img; help(create_neg_rms_img)"
The basic call sequence where the first four arguments are replaced with your corresponding filenames is then:
python -c "import create_neg_rms_img; create_neg_rms_img.create_neg_rms_img('sci_img', 'wht_img', 'neg_out', 'rms_out', True, True, False)"
Please send questions, comments, and suggestions to Mitchell Revalski. Thank you, and have a nice day!
Mitchell Revalski gratefully acknowledges Laura Prichard and Marc Rafelski for helping to improve this code.