Merge branch 'master' into DA

8 files changed, 79 insertions, 18 deletions

diff --git a/MANIFEST.in b/MANIFEST.in
new file mode 100644
index 0000000..8c14549
--- /dev/null
+++ b/MANIFEST.in
@@ -0,0 +1,7 @@
+graft ot/lp/
+include README.md
+include ot/lp/core.h
+include ot/lp/EMD.h
+include ot/lp/emd.pyx
+include ot/lp/full_bipartitegraph.h
+include ot/lp/network_simplex_simple.h
diff --git a/Makefile b/Makefile
index c817639..0b17082 100644
--- a/Makefile
+++ b/Makefile
@@ -33,6 +33,11 @@ sremove :
 
 clean :
 	$(PYTHON) setup.py clean
+	
+uploadpypi:
+	python setup.py register
+	python setup.py sdist upload -r pypi
+
 
 notebook :
 	ipython notebook --matplotlib=inline  --notebook-dir=examples/
diff --git a/README.md b/README.md
index 1be1208..ab7be28 100644
--- a/README.md
+++ b/README.md
@@ -1,14 +1,24 @@
 # POT: Python Optimal Transport
 
+
+[![Documentation Status](https://readthedocs.org/projects/pot/badge/?version=latest)](http://pot.readthedocs.io/en/latest/?badge=latest)
+
 This open source Python library provide several solvers for optimization problems related to Optimal Transport for signal, image processing and machine learning.
 
 It provides the following solvers:
+
 * OT solver for the linear program/ Earth Movers Distance [1].
 * Entropic regularization OT solver  with Sinkhorn Knopp Algorithm [2].
 * Bregman projections for Wasserstein barycenter [3] and unmixing [4].
 * Optimal transport for domain adaptation with group lasso regularization [5]
 * Conditional gradient [6] and Generalized conditional gradient for regularized OT [7].
 
+We are also currently working on the following features:
+
+- [ ] Image color adaptation demo
+- [ ] Scikit-learn inspired classes for domain adaptation
+- [ ] Mapping estimation as proposed in [8]
+
 Some demonstrations (both in Python and Jupyter Notebook format) are available in the examples folder.
 
 ## Installation
@@ -17,13 +27,24 @@ The Library has been tested on Linux and MacOSX. It requires a C++ compiler for
 
 - Numpy (>=1.11)
 - Scipy (>=0.17)
+- Cython (>=0.23)
+- Matplotlib (>=1.5)
+
+
+Under debian based linux the dependencies can be installed with
+```
+sudo apt-get install python-numpy python-scipy python-matplotlib cython
+```
 
 To install the library, you can install it locally (after downloading it) on you machine using
 ```
 python setup.py install --user
 ```
 
-
+The toolbox is also available on PyPI with a possibly slightly older version. You can install it with:
+```
+pip install POT
+```
 
 After a correct installation, you should be able to import the module without errors:
 ```python
@@ -34,19 +55,20 @@ Note that for easier access the module is name ot instead of pot.
 
 ## Examples
 
-The examples folder contain several examples and use case for the library.
+The examples folder contain several examples and use case for the library. The full documentation is available on [Readthedoc](http://pot.readthedocs.io/)
 
  Here is a list of the Python notebook if you want a quick look:
 
-* [1D optimal transport](examples/Demo_1D_OT.ipynb)
-* [2D optimal transport on empirical distributions](examples/Demo_2D_OT_samples.ipynb)
-* [1D Wasserstein barycenter](examples/Demo_1D_barycenter.ipynb)
-* [OT with user provided regularization](examples/Demo_Optim_OTreg.ipynb)
+* [1D optimal transport](https://github.com/rflamary/POT/blob/master/examples/Demo_1D_OT.ipynb)
+* [2D optimal transport on empirical distributions](https://github.com/rflamary/POT/blob/master/examples/Demo_2D_OT_samples.ipynb)
+* [1D Wasserstein barycenter](https://github.com/rflamary/POT/blob/master/examples/Demo_1D_barycenter.ipynb)
+* [OT with user provided regularization](https://github.com/rflamary/POT/blob/master/examples/Demo_Optim_OTreg.ipynb)
 
 
 ## Acknowledgements
 
 The contributors to this library are:
+
 * [Rémi Flamary](http://remi.flamary.com/)
 * [Nicolas Courty](http://people.irisa.fr/Nicolas.Courty/)
 * [Laetitia Chapel](http://people.irisa.fr/Laetitia.Chapel/)
@@ -73,3 +95,5 @@ This toolbox benefit a lot from open source research and we would like to thank
 [6] Ferradans, S., Papadakis, N., Peyré, G., & Aujol, J. F. (2014). Regularized discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3), 1853-1882.
 
 [7] Rakotomamonjy, A., Flamary, R., & Courty, N. (2015). Generalized conditional gradient: analysis of convergence and applications. arXiv preprint arXiv:1510.06567.
+
+[8] M. Perrot, N. Courty, R. Flamary, A. Habrard, "Mapping estimation for discrete optimal transport", Neural Information Processing Systems (NIPS), 2016.
diff --git a/docs/source/conf.py b/docs/source/conf.py
index 1c1bb40..b56df38 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -14,9 +14,19 @@
 
 import sys
 import os
+from unittest.mock import MagicMock
 
 sys.path.insert(0, os.path.abspath("../.."))
 
+
+class Mock(MagicMock):
+    @classmethod
+    def __getattr__(cls, name):
+        return Mock()
+
+MOCK_MODULES = [ 'emd','ot.lp.emd']
+sys.modules.update((mod_name, Mock()) for mod_name in MOCK_MODULES)
+
 # If extensions (or modules to document with autodoc) are in another directory,
 # add these directories to sys.path here. If the directory is relative to the
 # documentation root, use os.path.abspath to make it absolute, like shown here.
diff --git a/docs/source/index.rst b/docs/source/index.rst
index 8452f00..adbabb6 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -30,11 +30,6 @@ Contents
    all
    examples
 
-Examples
---------
-
-
-
 
 References
 ----------
diff --git a/ot/__init__.py b/ot/__init__.py
index 72c820a..cf55711 100644
--- a/ot/__init__.py
+++ b/ot/__init__.py
@@ -17,5 +17,7 @@ from .da import sinkhorn_lpl1_mm
 # utils functions
 from .utils import dist, unif
 
+__version__ = "0.1.6"
+
 __all__ = ["emd", "sinkhorn", "utils", 'datasets', 'bregman', 'lp', 'plot',
            'dist', 'unif', 'barycenter', 'sinkhorn_lpl1_mm', 'da', 'optim']
diff --git a/setup.cfg b/setup.cfg
new file mode 100644
index 0000000..b88034e
--- /dev/null
+++ b/setup.cfg
@@ -0,0 +1,2 @@
+[metadata]
+description-file = README.md
diff --git a/setup.py b/setup.py
index c7870d3..9804422 100755
--- a/setup.py
+++ b/setup.py
@@ -3,25 +3,39 @@
 from setuptools import setup, find_packages
 from codecs import open
 from os import path
-import numpy
 from setuptools.extension import Extension
 from Cython.Build import cythonize
-
+import numpy
+import re
+import os
 
 here = path.abspath(path.dirname(__file__))
 
 
 
-import os
+
 #import glob
 
-version='0.1'
+# dirty but working 
+__version__ = re.search(
+    r'__version__\s*=\s*[\'"]([^\'"]*)[\'"]',  # It excludes inline comment too
+    open('ot/__init__.py').read()).group(1)
+# The beautiful part is, I don't even need to check exceptions here.
+# If something messes up, let the build process fail noisy, BEFORE my release!
 
 ROOT = os.path.abspath(os.path.dirname(__file__))
-README = open(os.path.join(ROOT, 'README.md')).read()
+
+
+# convert markdown readme to rst in pypandoc installed
+try:
+   import pypandoc
+   README = pypandoc.convert('README.md', 'rst')
+except (IOError, ImportError):
+   README = open(os.path.join(ROOT, 'README.md')).read()
+
 
 setup(name='POT',
-      version=version,
+      version=__version__,
       description='Python Optimal Transport Library',
       long_description=README,
       author=u'Remi Flamary, Nicolas Courty',
@@ -35,10 +49,12 @@ setup(name='POT',
                  language="c++",                        # generate and compile C++ code,
                  include_dirs=[numpy.get_include(),os.path.join(ROOT,'ot/lp')])),
       platforms=['linux','macosx','windows'],
+      download_url='https://github.com/rflamary/POT/archive/V{}.tar.gz'.format(__version__),
       license = 'MIT',
       scripts=[],
       data_files=[],
-      requires=["numpy (>=1.11)","scipy (>=0.17)"],
+      requires=["numpy (>=1.11)","scipy (>=0.17)","cython (>=0.23)","matplotlib (>=1.5)"],
+      install_requires=["numpy (>=1.11)","scipy (>=0.17)","cython (>=0.23)","matplotlib (>=1.5)"],
       classifiers=[
         'Development Status :: 4 - Beta',
         'Intended Audience :: Developers',