This is a package to apply neural networks and convolutional neural networks to spherical signal projected on the healpix grid.
- Healpy
- Matplotlib
- NumPy
- Numba
- SciPy
- Tensorflow 2+
If you prefer to use PyTorch instead of Keras/TensorFlow, aasensio has implemented a port of the library available here: github.com/aasensio/sphericalCNN.
The code is still under development. To install, use the following command:
[sudo] python setup.py develop [--user]
To automatically install the requirements, use the following command:
pip install -r requirements.txt
To run a suite of tests, you must have either nosetests
or
pytest
. Just run nosetests
or pytest
within the NNhealpix
folder.
If you use this code, please cite the following paper: Convolutional neural networks on the HEALPix sphere: a pixel-based algorithm and its application to CMB data analysis, Krachmalnicoff, N. & Tomasi, M. (A&A, Aug 2019).
@article{ KrachmalnicoffTomasi2019,
author = {{Krachmalnicoff, N.} and {Tomasi, M.}},
title = {Convolutional neural networks on the HEALPix sphere: a pixel-based algorithm and its application to CMB data analysis},
DOI= "10.1051/0004-6361/201935211",
url= "https://doi.org/10.1051/0004-6361/201935211",
journal = {A\&A},
year = 2019,
volume = 628,
pages = "A129",
}
The library is released under a MIT license. See the file LICENSE for more information.