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.