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Description:

properimage 0.7.1

Proper image treatments

This code is inspired on Zackay & Ofek 2017 papers How to coadd images? (see References below).

It can perform a PSF estimation using Karhunen-Löeve expansion, which is based on Lauer 2002 work.

It can perform the statistical proper coadd of several images.

It can also perform a proper-subtraction of images.

Images need to be aligned and registered, or at least astroalign must be installed.

Contains a nice plot module for PSF visualization (needs matplotlib)

Installation
To install from PyPI
$ pip install properimage

Quick usage
PSF estimation
>>> from properimage import singleimage as si
>>> with si.SingleImage(frame, smooth_psf=False) as sim:
... a_fields, psf_basis = sim.get_variable_psf(inf_loss=0.15)

Proper-subtraction of images
To create a proper-subtraction of images:
>>> from properimage import propersubtract as ps
>>> D, P, Scorr, mask = ps.subtract(ref=ref_path, new=new_path, smooth_psf=False, fitted_psf=True,
... align=False, iterative=False, beta=False, shift=False)

Where D, P, Scorr refer to the images defined by the same name in Zackay & Ofek paper.
For the full documentation refer to readthedocs.
Rerefences

Zackay, B., & Ofek, E. O. (2017). How to Coadd Images. I. Optimal Source Detection and Photometry of Point Sources Using Ensembles of Images. The Astrophysical Journal, 836(2), 187. Arxiv version
Zackay, B., & Ofek, E. O. (2017). How to Coadd Images. II. A Coaddition Image that is Optimal for Any Purpose in the Background-dominated Noise Limit. The Astrophysical Journal, 836(2), 188. Arxiv version
Zackay, B., Ofek, E. O., & Gal-Yam, A. (2016). Proper Image Subtrraction-Optimal Transient Detection, Photometry, and Hypothesis Testing. The Astrophysical Journal, 830(1), 27.
Lauer, T. (2002, December). Deconvolution with a spatially-variant PSF. In Astronomical Data Analysis II (Vol. 4847, pp. 167-174). International Society for Optics and Photonics.