irispreppy

For radiometrically calibrating and PSF deconvolving IRIS data.

To install simply run pip install irispreppy.

I dislike how I need to own proprietary software (IDL) just to simply prepare my data. I use Python for my analysis, why can't I radiometrically calibrate and deconvolve with it? This has been a passion project of mine during my PhD (and beyond). The radiometric calibration keeps itself up to date with the response files by checking https://hesperia.gsfc.nasa.gov/ssw/iris/response/ every time it is run. If it finds new files, it downloads them before continuing.

These scripts should be general purpose and "just work". No janky hacks are present.

tl;dr usage

irispreppy takes a single HDU object. To calibrate and deconvolve,

from astropy.io import fits
import irispreppy as ip

raw=fits.open("iris_raster.fits") #Raw data
rc=ip.radiometric_calibrate(raw)  #Radiometrically calibrated
rc_d=ip.deconvolve(rc)            #Radiometrically calibrated and deconvolved

To calibrate and deconvolve, and save,

from astropy.io import fits
import irispreppy as ip

raw=fits.open("iris_raster.fits")   #Raw data
ip.calibrate_and_save(raw)          #Radiometrically calibrated
rc=fits.open("iris_raster_rc.fits") #Radiometrically calibrated data
ip.deconvolve_and_save(rc)	        #Radiometrically calibrated and deconvolved

Documentation

Documentation for irispreppy can now be found here.

Acknowledgements

Thank you to Dr Graham S. Kerr for IRIS_SG_deconvolve.py and IRIS_SG_PSFs.pkl.

Special thanks to Dr C.M.J. Osborne for putting up with my incessant and innane questions.

Makes use of the excellent WENO4 algorithm (Janett et al. 2019) implemented in Python3 by Dr C.M.J. Osborne here.