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SPAMS 2.6.1 and python

SPAMS (SPArse Modeling Software) is an optimization toolbox for solving various sparse estimation problems.

  • Dictionary learning and matrix factorization:
    • NMF
    • sparse PCA
  • Solving sparse decomposition problems:
    • LARS
    • coordinate descent
    • OMP
    • proximal methods
  • Solving structured sparse decomposition problems:
    • l1/l2
    • l1/linf
    • sparse group lasso
    • tree-structured regularization
    • structured sparsity with overlapping groups.

Author:

  • Julien Mairal (Inria) with the collaboration of Francis Bach (Inria),
  • Jean Ponce (Ecole Normale Supérieure),
  • Guillermo Sapiro (University of Minnesota),
  • Guillaume Obozinski (Inria),
  • Rodolphe Jenatton (Inria).

Credit:

  • R and Python interfaces by Jean-Paul Chieze (Inria).
  • Archetypal analysis implementation by Yuansi Chen (internship at Inria) with the collaboration of Zaid Harchaoui.

Maintenance:

  • Development and maintenance are done by Ghislain Durif (Inria).

Licence: GPL v3

Manipulated objects are imported from numpy and scipy. Matrices should be stored by columns, and sparse matrices should be "column compressed".

Installation from PyPI:

The standard installation uses the BLAS and LAPACK libraries used by Numpy:

pip install python-spams

Installation from sources

Make sure you have install libblas & liblapack (see below)

pip install -e .

Testing the interface :

python tests/test_spams.py -h # to get help
python tests/test_spams.py    # will run all the tests

Comments

Carefully install libblas & liblapack. For example on ubuntu, necessary to sudo apt-get -y install libblas-dev liblapack-dev gfortran. For MacOs, you most likely need to brew install gcc openblas lapack