Changelogs » Pyunlocbox

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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.
  * 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)
  * 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


  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
  * 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.
  * 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
  * 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