##SparsePz

###Sparse Representation of Photometric Redshift PDFs

This package will soon implemented as part as the MLZ package repository. This is the standalone version. The full documentation of MLZ is located here

For more information and a implementation of this technique, check this paper

Requirements:

• scipy
• matplotlib
• numpy
• pyfits (to store output file) >= 3.3
• mpi4py (optional for parallel running)

To run:

python example_sparse.py

To check the results:

python read_sparse.py

The format of the original PDF file is given in a numpy array but can eb easily change and corresponds to a 2D array where each row is the PDF and the very last row are the redshift positions.