pypher 0.7.1

Features

1. Warp (rotation + resampling) the PSF images (if necessary),

2. Filter images in Fourier space using a regularized Wiener filter,

3. Produce a homogenization kernel.

Note: pypher needs the pixel scale information to be present in the FITS files. If not, use the provided addpixscl method to add this missing info.

Warning: This code does not

• interpolate NaN values (replaced by 0 instead),

• center PSF images,

• minimize the kernel size.

Installation

PyPHER works both with Python 2.7 and 3.4 or above and relies on numpy, scipy and astropy libraries.

pip install pypher

git clone https://github.com/aboucaud/pypher
cd pypher
python setup.py install

conda install -c conda-forge pypher

Basic example

$ pypher psf_a.fits psf_b.fits kernel_a_to_b.fits -r 1.e-5

This will create the desired kernel kernel_a_to_b.fits and a short log kernel_a_to_b.log with information about the processing.

Acknowledging

If you make use of any product of this code in a scientific publication, please consider acknowledging the work by citing the paper using the BibTeX information in the Cite this repository section at the top right of the page.