HealpixML 1.0.0

Package adapted for Machine Learning on the Healpix grid.

HealpixML

the concept

The HealpixML genesis has been built to synthesise data (2D or Healpix) using Cross Scattering Transform. For a detailed method description please refer to https://arxiv.org/abs/2207.12527. This algorithm could be effectively usable for component separation (e.g. denoising).

Authors

J.-M. Delouis, T. Foulquier, L. Mousset, T. Odaka, P. Campeti, E. Allys, F. Paul,

Short tutorial

Exemple of synthesis

https://github.com/jmdelouis/HealpixML/blob/main/Notebooks/Demo_Synthesis.ipynb

A more complete exemple of what is doable with HealpixML is here https://github.com/pcampeti/CMBSCAT

Install HealpixML library

Before installing, make sure you have python installed in your enviroment. The last version of the HealpixML library can be installed using PyPi:

pip install HealpixML

Recommended installing procedures for mac users

It is recomended to use python=3.9*. It is recomended to install tensorflow in advance.

micromamba create -n HEALPIXML
micromamba install -n HEALPIXML ‘python==3.9*’
micromamba install -n HEALPIXML ‘tensorflow’
micromamba activate HEALPIXML
pip install HealpixML

Recommended installing procedures HPC users

It is recomended to install tensorflow in advance. For DATARMOR for using GPU ;

micromamba create -n HEALPIXML
micromamba install -n HEALPIXML ‘python==3.9*’
micromamba install -n HEALPIXML ‘tensorflow==2.11.0’
micromamba activate HEALPIXML
pip install HealpixML