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diff --git a/RELEASES.md b/RELEASES.md new file mode 100644 index 0000000..66eee19 --- /dev/null +++ b/RELEASES.md @@ -0,0 +1,215 @@ +# POT Releases + + +## 0.6 Year 3 +*July 2019* + +This is the first official stable release of POT and this means a jump to 0.6! +The library has been used in +the wild for a while now and we have reached a state where a lot of fundamental +OT solvers are available and tested. It has been quite stable in the last months +but kept the beta flag in its Pypi classifiers until now. + +Note that this release will be the last one supporting officially Python 2.7 (See +https://python3statement.org/ for more reasons). For next release we will keep +the travis tests for Python 2 but will make them non necessary for merge in 2020. + +The features are never complete in a toolbox designed for solving mathematical +problems and research but with the new contributions we now implement algorithms and solvers +from 24 scientific papers (listed in the README.md file). New features include a +direct implementation of the [empirical Sinkhorn divergence](https://pot.readthedocs.io/en/latest/all.html#ot.bregman.empirical_sinkhorn_divergence) +, a new efficient (Cython implementation) solver for [EMD in 1D](https://pot.readthedocs.io/en/latest/all.html#ot.lp.emd_1d) +and corresponding [Wasserstein +1D](https://pot.readthedocs.io/en/latest/all.html#ot.lp.wasserstein_1d). We now also +have implementations for [Unbalanced OT](https://github.com/rflamary/POT/blob/master/notebooks/plot_UOT_1D.ipynb) +and a solver for [Unbalanced OT barycenters](https://github.com/rflamary/POT/blob/master/notebooks/plot_UOT_barycenter_1D.ipynb). +A new variant of Gromov-Wasserstein divergence called [Fused +Gromov-Wasserstein](https://pot.readthedocs.io/en/latest/all.html?highlight=fused_#ot.gromov.fused_gromov_wasserstein) + has been also contributed with exemples of use on [structured data](https://github.com/rflamary/POT/blob/master/notebooks/plot_fgw.ipynb) +and computing [barycenters of labeld graphs](https://github.com/rflamary/POT/blob/master/notebooks/plot_barycenter_fgw.ipynb). + + +A lot of work has been done on the documentation with several new +examples corresponding to the new features and a lot of corrections for the +docstrings. But the most visible change is a new +[quick start guide](https://pot.readthedocs.io/en/latest/quickstart.html) for +POT that gives several pointers about which function or classes allow to solve which +specific OT problem. When possible a link is provided to relevant examples. + +We will also provide with this release some pre-compiled Python wheels for Linux +64bit on +github and pip. This will simplify the install process that before required a C +compiler and numpy/cython already installed. + +Finally we would like to acknowledge and thank the numerous contributors of POT +that has helped in the past build the foundation and are still contributing to +bring new features and solvers to the library. + + + +#### Features + +* Add compiled manylinux 64bits wheels to pip releases (PR #91) +* Add quick start guide (PR #88) +* Make doctest work on travis (PR #90) +* Update documentation (PR #79, PR #84) +* Solver for EMD in 1D (PR #89) +* Solvers for regularized unbalanced OT (PR #87, PR#99) +* Solver for Fused Gromov-Wasserstein (PR #86) +* Add empirical Sinkhorn and empirical Sinkhorn divergences (PR #80) + + +#### Closed issues + +- Issue #59 fail when using "pip install POT" (new details in doc+ hopefully + wheels) +- Issue #85 Cannot run gpu modules +- Issue #75 Greenkhorn do not return log (solved in PR #76) +- Issue #82 Gromov-Wasserstein fails when the cost matrices are slightly different +- Issue #72 Macosx build problem + + +## 0.5.0 Year 2 +*Sep 2018* + +POT is 2 years old! This release brings numerous new features to the +toolbox as listed below but also several bug correction. + +Among the new features, we can highlight a [non-regularized Gromov-Wasserstein +solver](https://github.com/rflamary/POT/blob/master/notebooks/plot_gromov.ipynb), +a new [greedy variant of sinkhorn](https://pot.readthedocs.io/en/latest/all.html#ot.bregman.greenkhorn), +[non-regularized](https://pot.readthedocs.io/en/latest/all.html#ot.lp.barycenter), +[convolutional (2D)](https://github.com/rflamary/POT/blob/master/notebooks/plot_convolutional_barycenter.ipynb) +and [free support](https://github.com/rflamary/POT/blob/master/notebooks/plot_free_support_barycenter.ipynb) + Wasserstein barycenters and [smooth](https://github.com/rflamary/POT/blob/prV0.5/notebooks/plot_OT_1D_smooth.ipynb) + and [stochastic](https://pot.readthedocs.io/en/latest/all.html#ot.stochastic.sgd_entropic_regularization) +implementation of entropic OT. + +POT 0.5 also comes with a rewriting of ot.gpu using the cupy framework instead of +the unmaintained cudamat. Note that while we tried to keed changes to the +minimum, the OTDA classes were deprecated. If you are happy with the cudamat +implementation, we recommend you stay with stable release 0.4 for now. + +The code quality has also improved with 92% code coverage in tests that is now +printed to the log in the Travis builds. The documentation has also been +greatly improved with new modules and examples/notebooks. + +This new release is so full of new stuff and corrections thanks to the old +and new POT contributors (you can see the list in the [readme](https://github.com/rflamary/POT/blob/master/README.md)). + +#### Features + +* Add non regularized Gromov-Wasserstein solver (PR #41) +* Linear OT mapping between empirical distributions and 90\% test coverage (PR #42) +* Add log parameter in class EMDTransport and SinkhornLpL1Transport (PR #44) +* Add Markdown format for Pipy (PR #45) +* Test for Python 3.5 and 3.6 on Travis (PR #46) +* Non regularized Wasserstein barycenter with scipy linear solver and/or cvxopt (PR #47) +* Rename dataset functions to be more sklearn compliant (PR #49) +* Smooth and sparse Optimal transport implementation with entropic and quadratic regularization (PR #50) +* Stochastic OT in the dual and semi-dual (PR #52 and PR #62) +* Free support barycenters (PR #56) +* Speed-up Sinkhorn function (PR #57 and PR #58) +* Add convolutional Wassersein barycenters for 2D images (PR #64) +* Add Greedy Sinkhorn variant (Greenkhorn) (PR #66) +* Big ot.gpu update with cupy implementation (instead of un-maintained cudamat) (PR #67) + +#### Deprecation + +Deprecated OTDA Classes were removed from ot.da and ot.gpu for version 0.5 +(PR #48 and PR #67). The deprecation message has been for a year here since +0.4 and it is time to pull the plug. + +#### Closed issues + +* Issue #35 : remove import plot from ot/__init__.py (See PR #41) +* Issue #43 : Unusable parameter log for EMDTransport (See PR #44) +* Issue #55 : UnicodeDecodeError: 'ascii' while installing with pip + + +## 0.4 Community edition +*15 Sep 2017* + +This release contains a lot of contribution from new contributors. + + +#### Features + +* Automatic notebooks and doc update (PR #27) +* Add gromov Wasserstein solver and Gromov Barycenters (PR #23) +* emd and emd2 can now return dual variables and have max_iter (PR #29 and PR #25) +* New domain adaptation classes compatible with scikit-learn (PR #22) +* Proper tests with pytest on travis (PR #19) +* PEP 8 tests (PR #13) + +#### Closed issues + +* emd convergence problem du to fixed max iterations (#24) +* Semi supervised DA error (#26) + +## 0.3.1 +*11 Jul 2017* + +* Correct bug in emd on windows + +## 0.3 Summer release +*7 Jul 2017* + +* emd* and sinkhorn* are now performed in parallel for multiple target distributions +* emd and sinkhorn are for OT matrix computation +* emd2 and sinkhorn2 are for OT loss computation +* new notebooks for emd computation and Wasserstein Discriminant Analysis +* relocate notebooks +* update documentation +* clean_zeros(a,b,M) for removimg zeros in sparse distributions +* GPU implementations for sinkhorn and group lasso regularization + + +## V0.2 +*7 Apr 2017* + +* New dimensionality reduction method (WDA) +* Efficient method emd2 returns only tarnsport (in paralell if several histograms given) + + + +## V0.1.11 New years resolution +*5 Jan 2017* + +* Add sphinx gallery for better documentation +* Small efficiency tweak in sinkhorn +* Add simple tic() toc() functions for timing + + +## V0.1.10 +*7 Nov 2016* +* numerical stabilization for sinkhorn (log domain and epsilon scaling) + +## V0.1.9 DA classes and mapping +*4 Nov 2016* + +* Update classes and examples for domain adaptation +* Joint OT matrix and mapping estimation + +## V0.1.7 +*31 Oct 2016* + +* Original Domain adaptation classes + + + +## PyPI version 0.1.3 + +* pipy works + +## First pre-release +*28 Oct 2016* + +It provides the following solvers: +* OT solver for the linear program/ Earth Movers Distance. +* Entropic regularization OT solver with Sinkhorn Knopp Algorithm. +* Bregman projections for Wasserstein barycenter [3] and unmixing. +* Optimal transport for domain adaptation with group lasso regularization +* Conditional gradient and Generalized conditional gradient for regularized OT. + +Some demonstrations (both in Python and Jupyter Notebook format) are available in the examples folder. |