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.

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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

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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