In this page you can download the drizzling software library, which reprojects data from HEALPix to local WCS, in IDL and Python languages. The drizzling library uses a strategy where the surface of pixel intersection is computed as presented in Appendix A of Paradis et al., 2012, A&A, 543, 103. This method allows fast ingestion and guarantees the photometric accuracy of the transformation with minimal data loss during the transformation from HEALPix to local WCS FITS.


NEW You can now access a web interface to reproject data from HEALPix to local WCS http://drizzweb.irap.omp.eu/

IDL version


  • Jean-Philippe Bernard (IRAP)
  • Nathalie Baby (IRAP)
  • Caroline Bot (CDS)
  • Laurent Cambrésy (CDS)
  • Ludovic Montier (IRAP)
  • Déborah Paradis (IRAP)
  • Alexandre Sauvé (IRAP)

Download : drizzlib_v08_15_beta.zip

Python version


  • Antoine Goutenoir (IRAP)
  • Déborah Paradis (IRAP)
  • Jean-Michel Glorian (IRAP)


The source tree is available on gitlab.

The python package itself can be downloaded via pip :

pip install drizzlib

Or you can directly grab a tarball here :

:!: There are detailed instructions and troubleshooting tips in the README, which you should read.


First, install the system dependencies :

Debian / Ubuntu
apt-get install python-dev pkg-config libfreetype* gfortran libopenblas-dev liblapack-dev

The easy way

pip install drizzlib
:?: It may complain about numpy. Install it, and try again.

The other way

Uncompress the tarball, move into it.

Then, install the python dependencies using pip :

pip install --upgrade setuptools
pip install -r requirements.txt

Finally, install drizzlib itself :

python setup.py install


Here's a simple usage example, that reads my_healpix.fits and extracts a subset of its data as described by the header in wcs_config.fits, and writes the result into my_wcs.fits :

from drizzlib import healpix2wcs


You can write to cade@irap.omp.eu.