PythonOT · rflamary · Apr 21, 2020 · Apr 20, 2020 · Apr 20, 2020 · Apr 20, 2020
diff --git a/.travis.yml b/.travis.yml
@@ -33,7 +33,7 @@ before_install:
 # command to install dependencies
 install:
   - pip install -r requirements.txt
-  - pip install -U "numpy>=1.14" "scipy<1.3"  # for numpy array formatting in doctests + scipy version: otherwise, pymanopt fails, cf <https://github.com/pymanopt/pymanopt/issues/77>
+  - pip install -U "numpy>=1.14" scipy  # for numpy array formatting in doctests
   - pip install flake8 pytest "pytest-cov<2.6"
   - pip install -U "sklearn"
   - pip install .

diff --git a/README.md b/README.md
@@ -2,7 +2,7 @@
 
 [![PyPI version](https://badge.fury.io/py/POT.svg)](https://badge.fury.io/py/POT)
 [![Anaconda Cloud](https://anaconda.org/conda-forge/pot/badges/version.svg)](https://anaconda.org/conda-forge/pot)
-[![Build Status](https://travis-ci.org/rflamary/POT.svg?branch=master)](https://travis-ci.org/PythonOT/POT)
+[![Build Status](https://travis-ci.org/PythonOT/POT.svg?branch=master)](https://travis-ci.org/PythonOT/POT)
 [![Documentation Status](https://readthedocs.org/projects/pot/badge/?version=latest)](http://pot.readthedocs.io/en/latest/?badge=latest)
 [![Downloads](https://pepy.tech/badge/pot)](https://pepy.tech/project/pot)
 [![Anaconda downloads](https://anaconda.org/conda-forge/pot/badges/downloads.svg)](https://anaconda.org/conda-forge/pot)

diff --git a/docs/cache_nbrun b/docs/cache_nbrun
@@ -1 +1 @@
-{"plot_otda_semi_supervised.ipynb": "f6dfb02ba2bbd939408ffcd22a3b007c", "plot_WDA.ipynb": "27f8de4c6d7db46497076523673eedfb", "plot_UOT_1D.ipynb": "fc7dd383e625597bd59fff03a8430c91", "plot_OT_L1_vs_L2.ipynb": "5d565b8aaf03be4309eba731127851dc", "plot_otda_color_images.ipynb": "f804d5806c7ac1a0901e4542b1eaa77b", "plot_fgw.ipynb": "2ba3e100e92ecf4dfbeb605de20b40ab", "plot_otda_d2.ipynb": "e6feae588103f2a8fab942e5f4eff483", "plot_compute_emd.ipynb": "f5cd71cad882ec157dc8222721e9820c", "plot_barycenter_fgw.ipynb": "e14100dd276bff3ffdfdf176f1b6b070", "plot_convolutional_barycenter.ipynb": "a72bb3716a1baaffd81ae267a673f9b6", "plot_optim_OTreg.ipynb": "481801bb0d133ef350a65179cf8f739a", "plot_barycenter_lp_vs_entropic.ipynb": "51833e8c76aaedeba9599ac7a30eb357", "plot_OT_1D_smooth.ipynb": "3a059103652225a0c78ea53895cf79e5", "plot_barycenter_1D.ipynb": "5f6fb8aebd8e2e91ebc77c923cb112b3", "plot_otda_mapping.ipynb": "2f1ebbdc0f855d9e2b7adf9edec24d25", "plot_OT_1D.ipynb": "b5348bdc561c07ec168a1622e5af4b93", "plot_gromov_barycenter.ipynb": "953e5047b886ec69ec621ec52f5e21d1", "plot_UOT_barycenter_1D.ipynb": "c72f0bfb6e1a79710dad3fef9f5c557c", "plot_otda_mapping_colors_images.ipynb": "cc8bf9a857f52e4a159fe71dfda19018", "plot_stochastic.ipynb": "e18253354c8c1d72567a4259eb1094f7", "plot_otda_linear_mapping.ipynb": "a472c767abe82020e0a58125a528785c", "plot_otda_classes.ipynb": "39087b6e98217851575f2271c22853a4", "plot_free_support_barycenter.ipynb": "246dd2feff4b233a4f1a553c5a202fdc", "plot_gromov.ipynb": "24f2aea489714d34779521f46d5e2c47", "plot_OT_2D_samples.ipynb": "912a77c5dd0fc0fafa03fac3d86f1502"}
+{"plot_otda_color_images.ipynb": "128d0435c08ebcf788913e4adcd7dd00", "plot_partial_wass_and_gromov.ipynb": "82242f8390df1d04806b333b745c72cf", "plot_WDA.ipynb": "27f8de4c6d7db46497076523673eedfb", "plot_screenkhorn_1D.ipynb": "af7b8a74a1be0f16f2c3908f5a178de0", "plot_otda_laplacian.ipynb": "d92cc0e528b9277f550daaa6f9d18415", "plot_OT_L1_vs_L2.ipynb": "288230c4e679d752a511353c96c134cb", "plot_otda_semi_supervised.ipynb": "568b39ffbdf6621dd6de162df42f4f21", "plot_fgw.ipynb": "f4de8e6939ce2b1339b3badc1fef0f37", "plot_otda_d2.ipynb": "07ef3212ff3123f16c32a5670e0167f8", "plot_compute_emd.ipynb": "299f6fffcdbf48b7c3268c0136e284f8", "plot_barycenter_fgw.ipynb": "9e813d3b07b7c0c0fcc35a778ca1243f", "plot_convolutional_barycenter.ipynb": "fdd259bfcd6d5fe8001efb4345795d2f", "plot_optim_OTreg.ipynb": "bddd8e49f092873d8980d41ae4974e19", "plot_UOT_1D.ipynb": "2658d5164165941b07539dae3cb80a0f", "plot_OT_1D_smooth.ipynb": "f3e1f0e362c9a78071a40c02b85d2305", "plot_barycenter_1D.ipynb": "f6fa5bc13d9811f09792f73b4de70aa0", "plot_otda_mapping.ipynb": "1bb321763f670fc945d77cfc91471e5e", "plot_OT_1D.ipynb": "0346a8c862606d11f36d0aa087ecab0d", "plot_gromov_barycenter.ipynb": "a7999fcc236d90a0adeb8da2c6370db3", "plot_UOT_barycenter_1D.ipynb": "dd9b857a8c66d71d0124d4a2c30a51dd", "plot_otda_mapping_colors_images.ipynb": "16faae80d6ea8b37d6b1f702149a10de", "plot_stochastic.ipynb": "64f23a8dcbab9823ae92f0fd6c3aceab", "plot_otda_linear_mapping.ipynb": "82417d9141e310bf1f2c2ecdb550094b", "plot_otda_classes.ipynb": "8836a924c9b562ef397af12034fa1abb", "plot_free_support_barycenter.ipynb": "be9d0823f9d7774a289311b9f14548eb", "plot_gromov.ipynb": "de06b1dbe8de99abae51c2e0b64b485d", "plot_otda_jcpot.ipynb": "65482cbfef5c6c1e5e73998aeb5f4b10", "plot_OT_2D_samples.ipynb": "9a9496792fa4216b1059fc70abca851a", "plot_barycenter_lp_vs_entropic.ipynb": "334840b69a86898813e50a6db0f3d0de"}
diff --git a/docs/source/auto_examples/auto_examples_jupyter.zip b/docs/source/auto_examples/auto_examples_jupyter.zip
diff --git a/docs/source/auto_examples/auto_examples_python.zip b/docs/source/auto_examples/auto_examples_python.zip
diff --git a/docs/source/auto_examples/images/sphx_glr_plot_OT_1D_001.png b/docs/source/auto_examples/images/sphx_glr_plot_OT_1D_001.png
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diff --git a/.../source/auto_examples/images/thumb/sphx_glr_plot_otda_semi_supervised_thumb.png b/.../source/auto_examples/images/thumb/sphx_glr_plot_otda_semi_supervised_thumb.png
diff --git a/...urce/auto_examples/images/thumb/sphx_glr_plot_partial_wass_and_gromov_thumb.png b/...urce/auto_examples/images/thumb/sphx_glr_plot_partial_wass_and_gromov_thumb.png
diff --git a/docs/source/auto_examples/images/thumb/sphx_glr_plot_screenkhorn_1D_thumb.png b/docs/source/auto_examples/images/thumb/sphx_glr_plot_screenkhorn_1D_thumb.png
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