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------------------ 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.
------------------ 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.
------------------ 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
------------------ 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.
------------------ Bug fix version. Still experimental. Bug fixes: * Avoid complex casting to real * Do not stop iterating if the objective function stays at zero
------------------ 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
------------------ 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