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| author | Romain Tavenard <romain.tavenard@univ-rennes2.fr> | 2020-05-04 11:19:35 +0200 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2020-05-04 11:19:35 +0200 |
| commit | e65c1f745cf2eacc6672727e7a3869efd8318768 (patch) | |
| tree | 71590cd404f31806a5a99f0cf8faa8d9dca6b42e /examples/gromov/plot_fgw.py | |
| parent | 98d6cdcfa3a24ba07b9b4428250b7aee7e62f1ea (diff) | |
[WIP] Improved docs and changed scipy version (#163)
* Improved docs and changed scipy version
* Fixed dependency bug in setup.py
* dependencies set to minimal versions for tests
* add requirements file
* added minimal version build for scipy (testing 1.2)
* bugfix in minimal deps build
* (yet another) bugfix in minimal deps build
* minimal deps now reflect README.md
* minimal deps: no autograd nor pymanopt
* refactored workflow names
* minimal deps: no doctests
* minimal deps: numpy 1.16
* trigger GH Actions on PR
* better merge
* re-add minimal-deps...
* bugfix in yaml
* enforce np>=1.16
* enforce scipy and cython versions too
* requires / install_requires
* requires / install_requires / requires
* setup_requires
Co-authored-by: Rémi Flamary <remi.flamary@gmail.com>
Diffstat (limited to 'examples/gromov/plot_fgw.py')
| -rw-r--r-- | examples/gromov/plot_fgw.py | 10 |
1 files changed, 5 insertions, 5 deletions
diff --git a/examples/gromov/plot_fgw.py b/examples/gromov/plot_fgw.py index 73e486e..97fe619 100644 --- a/examples/gromov/plot_fgw.py +++ b/examples/gromov/plot_fgw.py @@ -4,12 +4,12 @@ Plot Fused-gromov-Wasserstein ============================== -This example illustrates the computation of FGW for 1D measures[18]. +This example illustrates the computation of FGW for 1D measures [18]. -.. [18] Vayer Titouan, Chapel Laetitia, Flamary R{\'e}mi, Tavenard Romain - and Courty Nicolas - "Optimal Transport for structured data with application on graphs" - International Conference on Machine Learning (ICML). 2019. +[18] Vayer Titouan, Chapel Laetitia, Flamary Rémi, Tavenard Romain +and Courty Nicolas +"Optimal Transport for structured data with application on graphs" +International Conference on Machine Learning (ICML). 2019. """ |