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@@ -25,12 +25,23 @@ It provides the following solvers: Some demonstrations (both in Python and Jupyter Notebook format) are available in the examples folder. +#### Using and citing the toolbox + +If you use this toolbox in your research and find it useful, please cite POT using the following bibtex reference: +``` +@article{flamary2017pot, + title={POT Python Optimal Transport library}, + author={Flamary, R{\'e}mi and Courty, Nicolas}, + year={2017} +} +``` + ## Installation The library has been tested on Linux, MacOSX and Windows. It requires a C++ compiler for using the EMD solver and relies on the following Python modules: - Numpy (>=1.11) -- Scipy (>=0.17) +- Scipy (>=1.0) - Cython (>=0.23) - Matplotlib (>=1.5) @@ -156,16 +167,7 @@ This toolbox benefit a lot from open source research and we would like to thank * [Nicolas Bonneel](http://liris.cnrs.fr/~nbonneel/) ( C++ code for EMD) * [Marco Cuturi](http://marcocuturi.net/) (Sinkhorn Knopp in Matlab/Cuda) -## Using and citing the toolbox -If you use this toolbox in your research and find it useful, please cite POT using the following bibtex reference: -``` -@article{flamary2017pot, - title={POT Python Optimal Transport library}, - author={Flamary, R{\'e}mi and Courty, Nicolas}, - year={2017} -} -``` ## Contributions and code of conduct Every contribution is welcome and should respect the [contribution guidelines](CONTRIBUTING.md). Each member of the project is expected to follow the [code of conduct](CODE_OF_CONDUCT.md). |