Merge pull request #91 from rflamary/v1.0

[MRG] Release 0.6

Author: rflamary

.travis.yml

@@ -1,27 +1,35 @@
+dist: xenial   # required for Python >= 3.7
 language: python
 matrix:
-#    allow_failures:
-#        - os: osx
-    include:
-#        - os: osx
-#          language: generic
-        - os: linux
-          sudo: required
-          python: 3.4
-        - os: linux
-          sudo: required
-          python: 3.5
-        - os: linux
-          sudo: required
-          python: 3.6
-        - os: linux
-          sudo: required
-          python: 2.7
+  # allow_failures:
+  #     - os: osx
+  #     - os: windows
+  include:
+    - os: linux
+      sudo: required
+      python: 3.5
+    - os: linux
+      sudo: required
+      python: 3.6      
+    - os: linux
+      sudo: required
+      python: 3.7               
+    - os: linux
+      sudo: required
+      python: 2.7
+    # - os: osx
+    #   sudo: required
+    #   language: generic
+    # - name: "Python 3.7.3 on Windows"
+    #   os: windows           # Windows 10.0.17134 N/A Build 17134
+    #   language: shell       # 'language: python' is an error on Travis CI Windows
+    #   before_install: choco install python
+    #   env: PATH=/c/Python37:/c/Python37/Scripts:$PATH
+# before_script: # configure a headless display to test plot generation
+#   - "export DISPLAY=:99.0"
+#   - sleep 3 # give xvfb some time to start
 before_install:
   - ./.travis/before_install.sh
-before_script: # configure a headless display to test plot generation
-  - "export DISPLAY=:99.0"
-  - sleep 3 # give xvfb some time to start
 # command to install dependencies
 install:
   - pip install -r requirements.txt

MANIFEST.in

@@ -1,5 +1,5 @@
-graft ot/lp/
 include README.md
+include RELEASES.md
 include LICENSE
 include ot/lp/core.h
 include ot/lp/EMD.h

Makefile

@@ -3,6 +3,8 @@
 PYTHON=python3
 branch := $(shell git symbolic-ref --short -q HEAD)
 
+
+
 help :
 	@echo "The following make targets are available:"
 	@echo "    help - print this message"
@@ -13,6 +15,7 @@ help :
 	@echo "    sremove - remove the package (system with sudo)"
 	@echo "    clean - remove any temporary files"
 	@echo "    notebook - launch ipython notebook"
+
 build :
 	$(PYTHON) setup.py build
 
@@ -47,14 +50,15 @@ test : FORCE pep8
 pytest : FORCE 
 	$(PYTHON) -m pytest -v test/ --doctest-modules --ignore ot/gpu/  --cov=ot
 
-uploadpypi :
-	#python setup.py register
-	$(PYTHON) setup.py sdist upload -r pypi
+release :
+	twine upload dist/*
+
+release_test :
+	twine upload --repository-url https://test.pypi.org/legacy/ dist/*
 
 rdoc :
 	pandoc --from=markdown --to=rst --output=docs/source/readme.rst README.md
 
-
 notebook :
 	ipython notebook --matplotlib=inline  --notebook-dir=notebooks/
 
@@ -73,6 +77,13 @@ autopep8 :
 
 aautopep8 :
 	autopep8 -air test ot examples --jobs -1
+	
+wheels :
+	CIBW_BEFORE_BUILD="pip install numpy cython" cibuildwheel --platform linux --output-dir dist
+
+dist : wheels
+	$(PYTHON) setup.py sdist
+
 
 pydocstyle :
 	pydocstyle ot

README.md

@@ -45,7 +45,7 @@ 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:
+The library has been tested on Linux, MacOSX and Windows. It requires a C++ compiler for building/installing the EMD solver and relies on the following Python modules:
 
 - Numpy (>=1.11)
 - Scipy (>=1.0)
@@ -152,7 +152,8 @@ Here is a list of the Python notebooks available [here](https://github.com/rflam
 * [Wasserstein Discriminant Analysis](https://github.com/rflamary/POT/blob/master/notebooks/plot_WDA.ipynb)
 * [Gromov Wasserstein](https://github.com/rflamary/POT/blob/master/notebooks/plot_gromov.ipynb)
 * [Gromov Wasserstein Barycenter](https://github.com/rflamary/POT/blob/master/notebooks/plot_gromov_barycenter.ipynb)
-
+* [Fused Gromov Wasserstein](https://github.com/rflamary/POT/blob/master/notebooks/plot_fgw.ipynb)
+* [Fused Gromov Wasserstein Barycenter](https://github.com/rflamary/POT/blob/master/notebooks/plot_barycenter_fgw.ipynb)
 
 
 You can also see the notebooks with [Jupyter nbviewer](https://nbviewer.jupyter.org/github/rflamary/POT/tree/master/notebooks/).
@@ -166,8 +167,6 @@ This toolbox has been created and is maintained by
 
 The contributors to this library are 
 
-* [Rémi Flamary](http://remi.flamary.com/)
-* [Nicolas Courty](http://people.irisa.fr/Nicolas.Courty/)
 * [Alexandre Gramfort](http://alexandre.gramfort.net/)
 * [Laetitia Chapel](http://people.irisa.fr/Laetitia.Chapel/)
 * [Michael Perrot](http://perso.univ-st-etienne.fr/pem82055/) (Mapping estimation)

RELEASES.md

@@ -1,6 +1,74 @@
 # 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*
 

ot/__init__.py

@@ -71,9 +71,9 @@
 # utils functions
 from .utils import dist, unif, tic, toc, toq
 
-__version__ = "0.5.1"
+__version__ = "0.6.0"
 
-__all__ = ["emd", "emd2", 'emd_1d', "sinkhorn", "sinkhorn2", "utils", 'datasets',
+__all__ = ['emd', 'emd2', 'emd_1d', 'sinkhorn', 'sinkhorn2', 'utils', 'datasets',
            'bregman', 'lp', 'tic', 'toc', 'toq', 'gromov',
            'emd_1d', 'emd2_1d', 'wasserstein_1d',
            'dist', 'unif', 'barycenter', 'sinkhorn_lpl1_mm', 'da', 'optim',

ot/lp/__init__.py

@@ -11,7 +11,7 @@
 # License: MIT License
 
 import multiprocessing
-
+import sys
 import numpy as np
 from scipy.sparse import coo_matrix
 
@@ -151,6 +151,8 @@ def emd2(a, b, M, processes=multiprocessing.cpu_count(),
         Target histogram (uniform weight if empty list)
     M : (ns,nt) numpy.ndarray, float64
         Loss matrix (c-order array with type float64)
+    processes : int, optional (default=nb cpu)
+        Nb of processes used for multiple emd computation (not used on windows)
     numItermax : int, optional (default=100000)
         The maximum number of iterations before stopping the optimization
         algorithm if it has not converged.
@@ -200,6 +202,10 @@ def emd2(a, b, M, processes=multiprocessing.cpu_count(),
     b = np.asarray(b, dtype=np.float64)
     M = np.asarray(M, dtype=np.float64)
 
+    # problem with pikling Forks
+    if sys.platform.endswith('win32'):
+        processes=1
+
     # if empty array given then use uniform distributions
     if len(a) == 0:
         a = np.ones((M.shape[0],), dtype=np.float64) / M.shape[0]
@@ -228,7 +234,11 @@ def f(b):
         return f(b)
     nb = b.shape[1]
 
-    res = parmap(f, [b[:, i] for i in range(nb)], processes)
+    if processes>1:
+        res = parmap(f, [b[:, i] for i in range(nb)], processes)
+    else:
+        res = list(map(f, [b[:, i].copy() for i in range(nb)]))
+
     return res
 
 

ot/utils.py

@@ -210,23 +210,28 @@ def fun(f, q_in, q_out):
 
 
 def parmap(f, X, nprocs=multiprocessing.cpu_count()):
-    """ paralell map for multiprocessing """
-    q_in = multiprocessing.Queue(1)
-    q_out = multiprocessing.Queue()
+    """ paralell map for multiprocessing (only map on windows)"""
 
-    proc = [multiprocessing.Process(target=fun, args=(f, q_in, q_out))
-            for _ in range(nprocs)]
-    for p in proc:
-        p.daemon = True
-        p.start()
+    if not sys.platform.endswith('win32'):
 
-    sent = [q_in.put((i, x)) for i, x in enumerate(X)]
-    [q_in.put((None, None)) for _ in range(nprocs)]
-    res = [q_out.get() for _ in range(len(sent))]
+        q_in = multiprocessing.Queue(1)
+        q_out = multiprocessing.Queue()
 
-    [p.join() for p in proc]
+        proc = [multiprocessing.Process(target=fun, args=(f, q_in, q_out))
+                for _ in range(nprocs)]
+        for p in proc:
+            p.daemon = True
+            p.start()
 
-    return [x for i, x in sorted(res)]
+        sent = [q_in.put((i, x)) for i, x in enumerate(X)]
+        [q_in.put((None, None)) for _ in range(nprocs)]
+        res = [q_out.get() for _ in range(len(sent))]
+
+        [p.join() for p in proc]
+
+        return [x for i, x in sorted(res)]
+    else:
+        return list(map(f, X))
 
 
 def check_params(**kwargs):

requirements.txt

@@ -5,4 +5,5 @@ matplotlib
 sphinx-gallery
 autograd
 pymanopt
+cvxopt
 pytest

setup.py

@@ -53,17 +53,26 @@
       license = 'MIT',
       scripts=[],
       data_files=[],
-      requires=["numpy","scipy","cython","matplotlib"],
-      install_requires=["numpy","scipy","cython","matplotlib"],
+      requires=["numpy","scipy","cython"],
+      install_requires=["numpy","scipy","cython"],
       classifiers=[
-        'Development Status :: 4 - Beta',
+        'Development Status :: 5 - Production/Stable',
         'Intended Audience :: Developers',
+        'Intended Audience :: Education',
+        'Intended Audience :: Science/Research',
+        'License :: OSI Approved :: MIT License',
         'Environment :: Console',
         'Operating System :: OS Independent',
         'Operating System :: MacOS',
         'Operating System :: POSIX',
         'Programming Language :: Python',
+        'Programming Language :: C++',
+        'Programming Language :: C',
+        'Programming Language :: Cython',
         'Topic :: Utilities',
+        'Topic :: Scientific/Engineering :: Artificial Intelligence',
+        'Topic :: Scientific/Engineering :: Mathematics',
+        'Topic :: Scientific/Engineering :: Information Analysis',
         'Programming Language :: Python :: 2',
         'Programming Language :: Python :: 2.7',
         'Programming Language :: Python :: 3',