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Changelog

All notable changes to this project will be documented in this file. The format is based on Keep a Changelog and this project adheres to Semantic Versioning.

Unreleased

  • New function: proj_lineq.
  • New function: proj_sdsp.
  • New function: proj_positive.
  • New function: structured_sparsity.
  • Continuous integration with Python 3.6, 3.7, 3.8, 3.9. Dropped 2.7, 3.4, 3.5.
  • Merged all the extra requirements in a single dev requirement.

0.5.2 (2017-12-15)

Mostly a maintenance release. Much cleaning happened and a conda package is now available in conda-forge. Moreover, the package can now be tried online thanks to binder.

0.5.1 (2017-07-04)

Development status updated from Alpha to Beta.

New features:

  • Acceleration module, decoupling acceleration strategies from the solvers
    • Backtracking scheme
    • FISTA acceleration
    • FISTA with backtracking
    • Regularized non-linear acceleration (RNA)
  • Solvers: gradient descent algorithm

Bug fix:

  • Decrease dimensionality of variables in Douglas Rachford tutorial to reduce test time and timeout on Travis CI.

Infrastructure:

  • Continuous integration: dropped 3.3 (matplotlib dropped it), added 3.6
  • We don't build PDF documentation anymore. Less burden, HTML can be downloaded from readthedocs.

0.4.0 (2016-08-01)

New feature:

  • Monotone+Lipschitz forward-backward-forward primal-dual algorithm (MLFBF)

Bug fix:

  • Plots generated when building documentation (not stored in the repository)

Infrastructure:

  • Continuous integration: dropped 2.6 and 3.2, added 3.5
  • Travis-ci: check style and build doc
  • Removed tox config (too cumbersome to use on dev box)
  • Monitor code coverage and report to coveralls.io

0.3.0 (2015-05-29)

New features:

  • Generalized forward-backward splitting algorithm
  • Projection-based primal-dual algorithm
  • TV-norm function (eval, prox)
  • Nuclear-norm function (eval, prox)
  • L2-norm proximal operator supports non-tight frames
  • Two new tutorials using the TV-norm with Forward-Backward and Douglas-Rachford for image reconstruction and denoising
  • New stopping criterion XTOL allows to stop when the variable is stable

Bug fix:

  • Much more memory efficient. Note that the array which contains the initial solution is now modified in place.

0.2.1 (2014-08-20)

Bug fix version. Still experimental.

Bug fixes:

  • Avoid complex casting to real
  • Do not stop iterating if the objective function stays at zero

0.2.0 (2014-08-04)

Second usable version, available on GitHub and released on PyPI. Still experimental.

New features:

  • Douglas-Rachford splitting algorithm
  • Projection on the L2-ball for tight and non tight frames
  • Compressed sensing tutorial using L2-ball, L2-norm and Douglas-Rachford
  • Automatic solver selection

Infrastructure:

  • Unit tests for all functions and solvers
  • Continuous integration testing on Python 2.6, 2.7, 3.2, 3.3 and 3.4

0.1.0 (2014-06-08)

First usable version, available on GitHub and released on PyPI. Still experimental.

Features:

  • Forward-backward splitting algorithm
  • L1-norm function (eval and prox)
  • L2-norm function (eval, grad and prox)
  • Least square problem tutorial using L2-norm and forward-backward
  • Compressed sensing tutorial using L1-norm, L2-norm and forward-backward

Infrastructure:

  • Sphinx generated documentation using Numpy style docstrings
  • Documentation hosted on Read the Docs
  • Code hosted on GitHub
  • Package hosted on PyPI
  • Code checked by flake8
  • Docstring and tutorial examples checked by doctest (as a test suite)
  • Unit tests for functions module (as a test suite)
  • All test suites executed in Python 2.6, 2.7 and 3.2 virtualenvs by tox
  • Distributed automatic testing on Travis CI continuous integration platform