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hgmca - A hierarchical component separation algorithm based on sparsity in the wavelet basis.

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HGMCA is a source separation package primarily aimed towards use on the Cosmic Microwave Background. The software package includes implementations of gmca and hgmca as described in Wagner-Carena et al 2019. For ease of use, we have included a number of demos with the code.

Installation

  1. Clone the repo for hgmca:
$ git clone https://github.com/swagnercarena/hgmca
  1. For ease of use and installation, HGMCA includes an implementation of the s2let library in python. To improve the fidelity of the alm transform, healpy requires us to download some weights. Go into the hgmca directory and run the git clone command.
$ cd <HGMCA_path>
$ git clone https://github.com/healpy/healpy-data.git
  1. Now all we need to do is install our package! The -e option allows you to pull any updates to hgmca and have them automatically take effect.
$ pip install -e . -r requirements.txt