ddfacet-kernels 0.1.2

Package generating DDFacet W Kernels

This repository reproduces DDFacet’s W Projection Gridding Kernels to machine precision with only NumPy as a dependency.

License

Copyright (C) 2025 South African Radio Astronomy Observatory, Rhodes University, l’Observatoire de Paris

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see <https://www.gnu.org/licenses/>.

Installation

$ pip install ddfacet-kernels

Usage

from ddfacet_kernels import facet_w_kernels

facet_data = facet_w_kernels(
  nwplanes=7,
  cell_size=0.2  # arc-seconds
  support=15,
  maxw=30000.,
  npix=1025,
  oversampling=11,
  lmshift=(1e-5, 2e-5),
  frequencies=np.linspace(.856e9, 2*.856e9, 4096)
)

Testing

The test suite depends on test data produced from the DDFacet code base by the gen-test-data/gen_test_data.py script. With the file test-data.pickle.xz generated by this script, it is possible to run the entire test suite as follows:

$ virtualenv -p 3.10 venv
$ source venv/bin/activate
(venv) $ pip install -e .[tests]
(venv) $ py.test -s -vvv --ddf-test-data test-data.pickle.xz

The rest of the test suite will run without the --ddf-test-data argument. See the github actions workflow to see how to generate the test data.

Acknowledgements

Cyril Tasse and Sunrise Wang contributed valuable discussion and explanation on the Fourier Theory required to document this code base.