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authorRĂ©mi Flamary <remi.flamary@gmail.com>2017-09-15 14:54:21 +0200
committerGitHub <noreply@github.com>2017-09-15 14:54:21 +0200
commit81b2796226f3abde29fc024752728444da77509a (patch)
treec52cec3c38552f9f8c15361758aa9a80c30c3ef3
parente70d5420204db78691af2d0fbe04cc3d4416a8f4 (diff)
parent7fea2cd3e8ad29bf3fa442d7642bae124ee2bab0 (diff)
Merge pull request #27 from rflamary/autonb
auto notebooks + release update (fixes #16)
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-rw-r--r--notebooks/plot_otda_semi_supervised.ipynb294
-rw-r--r--ot/__init__.py2
221 files changed, 12652 insertions, 7009 deletions
diff --git a/.mailmap b/.mailmap
index 73f873e..e1e945e 100644
--- a/.mailmap
+++ b/.mailmap
@@ -1,3 +1,4 @@
Nicolas Courty <ncourty@irisa.fr> Nicolas Courty <Nico@MacBook-Pro-de-Nicolas.local>
Nicolas Courty <ncourty@irisa.fr> ncourty <ncourty@irisa.fr>
+Nicolas Courty <ncourty@irisa.fr> Nicolas Courty <Nico@pc-mna-08.univ-ubs.fr>
LĂ©o Gautheron <leo_g_autheron@hotmail.fr> Leo gautheron <gautheron@iv-cm-359.creatis.insa-lyon.fr>
diff --git a/Makefile b/Makefile
index 98f5614..3f19e8a 100644
--- a/Makefile
+++ b/Makefile
@@ -15,6 +15,9 @@ help :
build :
$(PYTHON) setup.py build
+buildext :
+ $(PYTHON) setup.py build_ext --inplace
+
install :
$(PYTHON) setup.py install --user
diff --git a/README.md b/README.md
index e394fc3..3b59eaa 100644
--- a/README.md
+++ b/README.md
@@ -112,17 +112,21 @@ The examples folder contain several examples and use case for the library. The f
Here is a list of the Python notebooks available [here](https://github.com/rflamary/POT/blob/master/notebooks/) if you want a quick look:
-* [1D optimal transport](https://github.com/rflamary/POT/blob/master/notebooks/Demo_1D_OT.ipynb)
-* [OT Ground Loss](https://github.com/rflamary/POT/blob/master/notebooks/Demo_Ground_Loss.ipynb)
-* [Multiple EMD computation](https://github.com/rflamary/POT/blob/master/notebooks/Demo_Compute_EMD.ipynb)
-* [2D optimal transport on empirical distributions](https://github.com/rflamary/POT/blob/master/notebooks/Demo_2D_OT_samples.ipynb)
-* [1D Wasserstein barycenter](https://github.com/rflamary/POT/blob/master/notebooks/Demo_1D_barycenter.ipynb)
-* [OT with user provided regularization](https://github.com/rflamary/POT/blob/master/notebooks/Demo_Optim_OTreg.ipynb)
-* [Domain adaptation with optimal transport](https://github.com/rflamary/POT/blob/master/notebooks/Demo_2D_OT_DomainAdaptation.ipynb)
-* [Color transfer in images](https://github.com/rflamary/POT/blob/master/notebooks/Demo_Image_ColorAdaptation.ipynb)
-* [OT mapping estimation for domain adaptation](https://github.com/rflamary/POT/blob/master/notebooks/Demo_2D_OTmapping_DomainAdaptation.ipynb)
-* [OT mapping estimation for color transfer in images](https://github.com/rflamary/POT/blob/master/notebooks/Demo_Image_ColorAdaptation_mapping.ipynb)
-* [Wasserstein Discriminant Analysis](https://github.com/rflamary/POT/blob/master/notebooks/Demo_Wasserstein_Discriminant_Analysis.ipynb)
+* [1D optimal transport](https://github.com/rflamary/POT/blob/master/notebooks/plot_OT_1D.ipynb)
+* [OT Ground Loss](https://github.com/rflamary/POT/blob/master/notebooks/plot_OT_L1_vs_L2.ipynb)
+* [Multiple EMD computation](https://github.com/rflamary/POT/blob/master/notebooks/plot_compute_emd.ipynb)
+* [2D optimal transport on empirical distributions](https://github.com/rflamary/POT/blob/master/notebooks/plot_OT_2D_samples.ipynb)
+* [1D Wasserstein barycenter](https://github.com/rflamary/POT/blob/master/notebooks/plot_barycenter_1D.ipynb)
+* [OT with user provided regularization](https://github.com/rflamary/POT/blob/master/notebooks/plot_optim_OTreg.ipynb)
+* [Domain adaptation with optimal transport](https://github.com/rflamary/POT/blob/master/notebooks/plot_otda_d2.ipynb)
+* [Color transfer in images](https://github.com/rflamary/POT/blob/master/notebooks/plot_otda_color_images.ipynb)
+* [OT mapping estimation for domain adaptation](https://github.com/rflamary/POT/blob/master/notebooks/plot_otda_mapping.ipynb)
+* [OT mapping estimation for color transfer in images](https://github.com/rflamary/POT/blob/master/notebooks/plot_otda_mapping_colors_images.ipynb)
+* [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)
+
+
You can also see the notebooks with [Jupyter nbviewer](https://nbviewer.jupyter.org/github/rflamary/POT/tree/master/notebooks/).
diff --git a/RELEASES.md b/RELEASES.md
new file mode 100644
index 0000000..58712c8
--- /dev/null
+++ b/RELEASES.md
@@ -0,0 +1,88 @@
+# POT Releases
+
+## 0.4 Community edition
+*15 Sep 2017*
+
+This release contains a lot of contribution from new contributors.
+
+
+#### Features
+
+* Automatic notebooks and doc update (PR #27)
+* Add gromov Wasserstein solver and Gromov Barycenters (PR #23)
+* emd and emd2 can now return dual variables and have max_iter (PR #29 and PR #25)
+* New domain adaptation classes compatible with scikit-learn (PR #22)
+* Proper tests with pytest on travis (PR #19)
+* PEP 8 tests (PR #13)
+
+#### Closed issues
+
+* emd convergence problem du to fixed max iterations (#24)
+* Semi supervised DA error (#26)
+
+## 0.3.1
+*11 Jul 2017*
+
+* Correct bug in emd on windows
+
+## 0.3 Summer release
+*7 Jul 2017*
+
+* emd* and sinkhorn* are now performed in parallel for multiple target distributions
+* emd and sinkhorn are for OT matrix computation
+* emd2 and sinkhorn2 are for OT loss computation
+* new notebooks for emd computation and Wasserstein Discriminant Analysis
+* relocate notebooks
+* update documentation
+* clean_zeros(a,b,M) for removimg zeros in sparse distributions
+* GPU implementations for sinkhorn and group lasso regularization
+
+
+## V0.2
+*7 Apr 2017*
+
+* New dimensionality reduction method (WDA)
+* Efficient method emd2 returns only tarnsport (in paralell if several histograms given)
+
+
+
+## V0.1.11 New years resolution
+*5 Jan 2017*
+
+* Add sphinx gallery for better documentation
+* Small efficiency tweak in sinkhorn
+* Add simple tic() toc() functions for timing
+
+
+## V0.1.10
+*7 Nov 2016*
+* numerical stabilization for sinkhorn (log domain and epsilon scaling)
+
+## V0.1.9 DA classes and mapping
+*4 Nov 2016*
+
+* Update classes and examples for domain adaptation
+* Joint OT matrix and mapping estimation
+
+## V0.1.7
+*31 Oct 2016*
+
+* Original Domain adaptation classes
+
+
+
+## PyPI version 0.1.3
+
+* pipy works
+
+## First pre-release
+*28 Oct 2016*
+
+It provides the following solvers:
+* OT solver for the linear program/ Earth Movers Distance.
+* Entropic regularization OT solver with Sinkhorn Knopp Algorithm.
+* Bregman projections for Wasserstein barycenter [3] and unmixing.
+* Optimal transport for domain adaptation with group lasso regularization
+* Conditional gradient and Generalized conditional gradient for regularized OT.
+
+Some demonstrations (both in Python and Jupyter Notebook format) are available in the examples folder.
diff --git a/docs/cache_nbrun b/docs/cache_nbrun
new file mode 100644
index 0000000..3f1e6ea
--- /dev/null
+++ b/docs/cache_nbrun
@@ -0,0 +1 @@
+{"plot_otda_mapping_colors_images.ipynb": "4f0587a00a3c082799a75a0ed36e9ce1", "plot_optim_OTreg.ipynb": "71d3c106b3f395a6b1001078a6ca6f8d", "plot_otda_color_images.ipynb": "d047d635f4987c81072383241590e21f", "plot_WDA.ipynb": "27f8de4c6d7db46497076523673eedfb", "plot_OT_L1_vs_L2.ipynb": "e15219bf651a7e39e7c5c3934069894c", "plot_barycenter_1D.ipynb": "6fd8167f98816dc832fe0c58b1d5527b", "plot_otda_classes.ipynb": "44bb8cd93317b5d342cd62e26d9bbe60", "plot_otda_d2.ipynb": "8ac4fd2ff899df0858ce1e5fead37f33", "plot_otda_mapping.ipynb": "d335a15af828aaa3439a1c67570d79d6", "plot_gromov.ipynb": "9d0893ec68851f200d0ca806bcbe847f", "plot_compute_emd.ipynb": "bd95981189df6adcb113d9b360ead734", "plot_OT_1D.ipynb": "e44c83f6112388ae18657cb0ad76d0e9", "plot_gromov_barycenter.ipynb": "a4d9636685394ceb13f26cdc613b9b5b", "plot_otda_semi_supervised.ipynb": "0261d339a692e339e15d3634488905cc", "plot_OT_2D_samples.ipynb": "3f125714daa35ff3cfe5dae1f71265c4"} \ No newline at end of file
diff --git a/docs/nb_build b/docs/nb_build
new file mode 100755
index 0000000..6abc6cf
--- /dev/null
+++ b/docs/nb_build
@@ -0,0 +1,15 @@
+#!/bin/bash
+
+
+# remove comment
+sed -i "s/#'sphinx\_gallery/'sphinx\_gallery/" source/conf.py
+sed -i "s/sys.modules.update/#sys.modules.update/" source/conf.py
+
+make html
+
+# put comment again
+sed -i "s/'sphinx\_gallery/#'sphinx\_gallery/" source/conf.py
+sed -i "s/#sys.modules.update/sys.modules.update/" source/conf.py
+
+#rsync --out-format="%n" --update source/auto_examples/*.ipynb ../notebooks2
+./nb_run_conv
diff --git a/docs/nb_run_conv b/docs/nb_run_conv
new file mode 100755
index 0000000..ad5e432
--- /dev/null
+++ b/docs/nb_run_conv
@@ -0,0 +1,82 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+
+Convert sphinx gallery notebook from empty to image filled
+
+Created on Fri Sep 1 16:43:45 2017
+
+@author: rflamary
+"""
+
+import sys
+import json
+import glob
+import hashlib
+import subprocess
+
+import os
+
+cache_file='cache_nbrun'
+
+path_doc='source/auto_examples/'
+path_nb='../notebooks/'
+
+def load_json(fname):
+ try:
+ f=open(fname)
+ nb=json.load(f)
+ f.close()
+ except (OSError, IOError) :
+ nb={}
+ return nb
+
+def save_json(fname,nb):
+ f=open(fname,'w')
+ f.write(json.dumps(nb))
+ f.close()
+
+
+def md5(fname):
+ hash_md5 = hashlib.md5()
+ with open(fname, "rb") as f:
+ for chunk in iter(lambda: f.read(4096), b""):
+ hash_md5.update(chunk)
+ return hash_md5.hexdigest()
+
+def to_update(fname,cache):
+ if fname in cache:
+ if md5(path_doc+fname)==cache[fname]:
+ res=False
+ else:
+ res=True
+ else:
+ res=True
+
+ return res
+
+def update(fname,cache):
+
+ # jupyter nbconvert --to notebook --execute mynotebook.ipynb --output targte
+ subprocess.check_call(['cp',path_doc+fname,path_nb])
+ print(' '.join(['jupyter','nbconvert','--to','notebook','--ExecutePreprocessor.timeout=600','--execute',path_nb+fname,'--inplace']))
+ subprocess.check_call(['jupyter','nbconvert','--to','notebook','--ExecutePreprocessor.timeout=600','--execute',path_nb+fname,'--inplace'])
+ cache[fname]=md5(path_doc+fname)
+
+
+
+cache=load_json(cache_file)
+
+lst_file=glob.glob(path_doc+'*.ipynb')
+
+lst_file=[os.path.basename(name) for name in lst_file]
+
+for fname in lst_file:
+ if to_update(fname,cache):
+ print('Updating file: {}'.format(fname))
+ update(fname,cache)
+ save_json(cache_file,cache)
+
+
+
+
diff --git a/docs/source/auto_examples/auto_examples_jupyter.zip b/docs/source/auto_examples/auto_examples_jupyter.zip
index 7c3de28..5a3f24c 100644
--- a/docs/source/auto_examples/auto_examples_jupyter.zip
+++ b/docs/source/auto_examples/auto_examples_jupyter.zip
Binary files differ
diff --git a/docs/source/auto_examples/auto_examples_python.zip b/docs/source/auto_examples/auto_examples_python.zip
index 97377e1..aa06bb6 100644
--- a/docs/source/auto_examples/auto_examples_python.zip
+++ b/docs/source/auto_examples/auto_examples_python.zip
Binary files differ
diff --git a/docs/source/auto_examples/demo_OT_1D_test.ipynb b/docs/source/auto_examples/demo_OT_1D_test.ipynb
deleted file mode 100644
index 87317ea..0000000
--- a/docs/source/auto_examples/demo_OT_1D_test.ipynb
+++ /dev/null
@@ -1,54 +0,0 @@
-{
- "nbformat_minor": 0,
- "nbformat": 4,
- "cells": [
- {
- "execution_count": null,
- "cell_type": "code",
- "source": [
- "%matplotlib inline"
- ],
- "outputs": [],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "source": [
- "\nDemo for 1D optimal transport\n\n@author: rflamary\n\n"
- ],
- "cell_type": "markdown",
- "metadata": {}
- },
- {
- "execution_count": null,
- "cell_type": "code",
- "source": [
- "import numpy as np\nimport matplotlib.pylab as pl\nimport ot\nfrom ot.datasets import get_1D_gauss as gauss\n\n\n#%% parameters\n\nn=100 # nb bins\n\n# bin positions\nx=np.arange(n,dtype=np.float64)\n\n# Gaussian distributions\na=gauss(n,m=n*.2,s=5) # m= mean, s= std\nb=gauss(n,m=n*.6,s=10)\n\n# loss matrix\nM=ot.dist(x.reshape((n,1)),x.reshape((n,1)))\nM/=M.max()\n\n#%% plot the distributions\n\npl.figure(1)\npl.plot(x,a,'b',label='Source distribution')\npl.plot(x,b,'r',label='Target distribution')\npl.legend()\n\n#%% plot distributions and loss matrix\n\npl.figure(2)\not.plot.plot1D_mat(a,b,M,'Cost matrix M')\n\n#%% EMD\n\nG0=ot.emd(a,b,M)\n\npl.figure(3)\not.plot.plot1D_mat(a,b,G0,'OT matrix G0')\n\n#%% Sinkhorn\n\nlambd=1e-3\nGs=ot.sinkhorn(a,b,M,lambd,verbose=True)\n\npl.figure(4)\not.plot.plot1D_mat(a,b,Gs,'OT matrix Sinkhorn')\n\n#%% Sinkhorn\n\nlambd=1e-4\nGss,log=ot.bregman.sinkhorn_stabilized(a,b,M,lambd,verbose=True,log=True)\nGss2,log2=ot.bregman.sinkhorn_stabilized(a,b,M,lambd,verbose=True,log=True,warmstart=log['warmstart'])\n\npl.figure(5)\not.plot.plot1D_mat(a,b,Gss,'OT matrix Sinkhorn stabilized')\n\n#%% Sinkhorn\n\nlambd=1e-11\nGss=ot.bregman.sinkhorn_epsilon_scaling(a,b,M,lambd,verbose=True)\n\npl.figure(5)\not.plot.plot1D_mat(a,b,Gss,'OT matrix Sinkhorn stabilized')"
- ],
- "outputs": [],
- "metadata": {
- "collapsed": false
- }
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 2",
- "name": "python2",
- "language": "python"
- },
- "language_info": {
- "mimetype": "text/x-python",
- "nbconvert_exporter": "python",
- "name": "python",
- "file_extension": ".py",
- "version": "2.7.12",
- "pygments_lexer": "ipython2",
- "codemirror_mode": {
- "version": 2,
- "name": "ipython"
- }
- }
- }
-} \ No newline at end of file
diff --git a/docs/source/auto_examples/demo_OT_1D_test.py b/docs/source/auto_examples/demo_OT_1D_test.py
deleted file mode 100644
index 9edc377..0000000
--- a/docs/source/auto_examples/demo_OT_1D_test.py
+++ /dev/null
@@ -1,71 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Demo for 1D optimal transport
-
-@author: rflamary
-"""
-
-import numpy as np
-import matplotlib.pylab as pl
-import ot
-from ot.datasets import get_1D_gauss as gauss
-
-
-#%% parameters
-
-n=100 # nb bins
-
-# bin positions
-x=np.arange(n,dtype=np.float64)
-
-# Gaussian distributions
-a=gauss(n,m=n*.2,s=5) # m= mean, s= std
-b=gauss(n,m=n*.6,s=10)
-
-# loss matrix
-M=ot.dist(x.reshape((n,1)),x.reshape((n,1)))
-M/=M.max()
-
-#%% plot the distributions
-
-pl.figure(1)
-pl.plot(x,a,'b',label='Source distribution')
-pl.plot(x,b,'r',label='Target distribution')
-pl.legend()
-
-#%% plot distributions and loss matrix
-
-pl.figure(2)
-ot.plot.plot1D_mat(a,b,M,'Cost matrix M')
-
-#%% EMD
-
-G0=ot.emd(a,b,M)
-
-pl.figure(3)
-ot.plot.plot1D_mat(a,b,G0,'OT matrix G0')
-
-#%% Sinkhorn
-
-lambd=1e-3
-Gs=ot.sinkhorn(a,b,M,lambd,verbose=True)
-
-pl.figure(4)
-ot.plot.plot1D_mat(a,b,Gs,'OT matrix Sinkhorn')
-
-#%% Sinkhorn
-
-lambd=1e-4
-Gss,log=ot.bregman.sinkhorn_stabilized(a,b,M,lambd,verbose=True,log=True)
-Gss2,log2=ot.bregman.sinkhorn_stabilized(a,b,M,lambd,verbose=True,log=True,warmstart=log['warmstart'])
-
-pl.figure(5)
-ot.plot.plot1D_mat(a,b,Gss,'OT matrix Sinkhorn stabilized')
-
-#%% Sinkhorn
-
-lambd=1e-11
-Gss=ot.bregman.sinkhorn_epsilon_scaling(a,b,M,lambd,verbose=True)
-
-pl.figure(5)
-ot.plot.plot1D_mat(a,b,Gss,'OT matrix Sinkhorn stabilized')
diff --git a/docs/source/auto_examples/demo_OT_1D_test.rst b/docs/source/auto_examples/demo_OT_1D_test.rst
deleted file mode 100644
index aebeb1d..0000000
--- a/docs/source/auto_examples/demo_OT_1D_test.rst
+++ /dev/null
@@ -1,99 +0,0 @@
-
-
-.. _sphx_glr_auto_examples_demo_OT_1D_test.py:
-
-
-Demo for 1D optimal transport
-
-@author: rflamary
-
-
-
-.. code-block:: python
-
-
- import numpy as np
- import matplotlib.pylab as pl
- import ot
- from ot.datasets import get_1D_gauss as gauss
-
-
- #%% parameters
-
- n=100 # nb bins
-
- # bin positions
- x=np.arange(n,dtype=np.float64)
-
- # Gaussian distributions
- a=gauss(n,m=n*.2,s=5) # m= mean, s= std
- b=gauss(n,m=n*.6,s=10)
-
- # loss matrix
- M=ot.dist(x.reshape((n,1)),x.reshape((n,1)))
- M/=M.max()
-
- #%% plot the distributions
-
- pl.figure(1)
- pl.plot(x,a,'b',label='Source distribution')
- pl.plot(x,b,'r',label='Target distribution')
- pl.legend()
-
- #%% plot distributions and loss matrix
-
- pl.figure(2)
- ot.plot.plot1D_mat(a,b,M,'Cost matrix M')
-
- #%% EMD
-
- G0=ot.emd(a,b,M)
-
- pl.figure(3)
- ot.plot.plot1D_mat(a,b,G0,'OT matrix G0')
-
- #%% Sinkhorn
-
- lambd=1e-3
- Gs=ot.sinkhorn(a,b,M,lambd,verbose=True)
-
- pl.figure(4)
- ot.plot.plot1D_mat(a,b,Gs,'OT matrix Sinkhorn')
-
- #%% Sinkhorn
-
- lambd=1e-4
- Gss,log=ot.bregman.sinkhorn_stabilized(a,b,M,lambd,verbose=True,log=True)
- Gss2,log2=ot.bregman.sinkhorn_stabilized(a,b,M,lambd,verbose=True,log=True,warmstart=log['warmstart'])
-
- pl.figure(5)
- ot.plot.plot1D_mat(a,b,Gss,'OT matrix Sinkhorn stabilized')
-
- #%% Sinkhorn
-
- lambd=1e-11
- Gss=ot.bregman.sinkhorn_epsilon_scaling(a,b,M,lambd,verbose=True)
-
- pl.figure(5)
- ot.plot.plot1D_mat(a,b,Gss,'OT matrix Sinkhorn stabilized')
-
-**Total running time of the script:** ( 0 minutes 0.000 seconds)
-
-
-
-.. container:: sphx-glr-footer
-
-
- .. container:: sphx-glr-download
-
- :download:`Download Python source code: demo_OT_1D_test.py <demo_OT_1D_test.py>`
-
-
-
- .. container:: sphx-glr-download
-
- :download:`Download Jupyter notebook: demo_OT_1D_test.ipynb <demo_OT_1D_test.ipynb>`
-
-.. rst-class:: sphx-glr-signature
-
- `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
diff --git a/docs/source/auto_examples/demo_OT_2D_sampleslarge.ipynb b/docs/source/auto_examples/demo_OT_2D_sampleslarge.ipynb
deleted file mode 100644
index 584a936..0000000
--- a/docs/source/auto_examples/demo_OT_2D_sampleslarge.ipynb
+++ /dev/null
@@ -1,54 +0,0 @@
-{
- "nbformat_minor": 0,
- "nbformat": 4,
- "cells": [
- {
- "execution_count": null,
- "cell_type": "code",
- "source": [
- "%matplotlib inline"
- ],
- "outputs": [],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "source": [
- "\nDemo for 2D Optimal transport between empirical distributions\n\n@author: rflamary\n\n"
- ],
- "cell_type": "markdown",
- "metadata": {}
- },
- {
- "execution_count": null,
- "cell_type": "code",
- "source": [
- "import numpy as np\nimport matplotlib.pylab as pl\nimport ot\n\n#%% parameters and data generation\n\nn=5000 # nb samples\n\nmu_s=np.array([0,0])\ncov_s=np.array([[1,0],[0,1]])\n\nmu_t=np.array([4,4])\ncov_t=np.array([[1,-.8],[-.8,1]])\n\nxs=ot.datasets.get_2D_samples_gauss(n,mu_s,cov_s)\nxt=ot.datasets.get_2D_samples_gauss(n,mu_t,cov_t)\n\na,b = ot.unif(n),ot.unif(n) # uniform distribution on samples\n\n# loss matrix\nM=ot.dist(xs,xt)\nM/=M.max()\n\n#%% plot samples\n\n#pl.figure(1)\n#pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n#pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n#pl.legend(loc=0)\n#pl.title('Source and traget distributions')\n#\n#pl.figure(2)\n#pl.imshow(M,interpolation='nearest')\n#pl.title('Cost matrix M')\n#\n\n#%% EMD\n\nG0=ot.emd(a,b,M)\n\n#pl.figure(3)\n#pl.imshow(G0,interpolation='nearest')\n#pl.title('OT matrix G0')\n#\n#pl.figure(4)\n#ot.plot.plot2D_samples_mat(xs,xt,G0,c=[.5,.5,1])\n#pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n#pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n#pl.legend(loc=0)\n#pl.title('OT matrix with samples')\n\n\n#%% sinkhorn\n\n# reg term\nlambd=5e-3\n\nGs=ot.sinkhorn(a,b,M,lambd)\n\n#pl.figure(5)\n#pl.imshow(Gs,interpolation='nearest')\n#pl.title('OT matrix sinkhorn')\n#\n#pl.figure(6)\n#ot.plot.plot2D_samples_mat(xs,xt,Gs,color=[.5,.5,1])\n#pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n#pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n#pl.legend(loc=0)\n#pl.title('OT matrix Sinkhorn with samples')\n#"
- ],
- "outputs": [],
- "metadata": {
- "collapsed": false
- }
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 2",
- "name": "python2",
- "language": "python"
- },
- "language_info": {
- "mimetype": "text/x-python",
- "nbconvert_exporter": "python",
- "name": "python",
- "file_extension": ".py",
- "version": "2.7.12",
- "pygments_lexer": "ipython2",
- "codemirror_mode": {
- "version": 2,
- "name": "ipython"
- }
- }
- }
-} \ No newline at end of file
diff --git a/docs/source/auto_examples/demo_OT_2D_sampleslarge.py b/docs/source/auto_examples/demo_OT_2D_sampleslarge.py
deleted file mode 100644
index ee3e8f7..0000000
--- a/docs/source/auto_examples/demo_OT_2D_sampleslarge.py
+++ /dev/null
@@ -1,78 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Demo for 2D Optimal transport between empirical distributions
-
-@author: rflamary
-"""
-
-import numpy as np
-import matplotlib.pylab as pl
-import ot
-
-#%% parameters and data generation
-
-n=5000 # nb samples
-
-mu_s=np.array([0,0])
-cov_s=np.array([[1,0],[0,1]])
-
-mu_t=np.array([4,4])
-cov_t=np.array([[1,-.8],[-.8,1]])
-
-xs=ot.datasets.get_2D_samples_gauss(n,mu_s,cov_s)
-xt=ot.datasets.get_2D_samples_gauss(n,mu_t,cov_t)
-
-a,b = ot.unif(n),ot.unif(n) # uniform distribution on samples
-
-# loss matrix
-M=ot.dist(xs,xt)
-M/=M.max()
-
-#%% plot samples
-
-#pl.figure(1)
-#pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
-#pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
-#pl.legend(loc=0)
-#pl.title('Source and traget distributions')
-#
-#pl.figure(2)
-#pl.imshow(M,interpolation='nearest')
-#pl.title('Cost matrix M')
-#
-
-#%% EMD
-
-G0=ot.emd(a,b,M)
-
-#pl.figure(3)
-#pl.imshow(G0,interpolation='nearest')
-#pl.title('OT matrix G0')
-#
-#pl.figure(4)
-#ot.plot.plot2D_samples_mat(xs,xt,G0,c=[.5,.5,1])
-#pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
-#pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
-#pl.legend(loc=0)
-#pl.title('OT matrix with samples')
-
-
-#%% sinkhorn
-
-# reg term
-lambd=5e-3
-
-Gs=ot.sinkhorn(a,b,M,lambd)
-
-#pl.figure(5)
-#pl.imshow(Gs,interpolation='nearest')
-#pl.title('OT matrix sinkhorn')
-#
-#pl.figure(6)
-#ot.plot.plot2D_samples_mat(xs,xt,Gs,color=[.5,.5,1])
-#pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
-#pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
-#pl.legend(loc=0)
-#pl.title('OT matrix Sinkhorn with samples')
-#
-
diff --git a/docs/source/auto_examples/demo_OT_2D_sampleslarge.rst b/docs/source/auto_examples/demo_OT_2D_sampleslarge.rst
deleted file mode 100644
index f5dbb0d..0000000
--- a/docs/source/auto_examples/demo_OT_2D_sampleslarge.rst
+++ /dev/null
@@ -1,106 +0,0 @@
-
-
-.. _sphx_glr_auto_examples_demo_OT_2D_sampleslarge.py:
-
-
-Demo for 2D Optimal transport between empirical distributions
-
-@author: rflamary
-
-
-
-.. code-block:: python
-
-
- import numpy as np
- import matplotlib.pylab as pl
- import ot
-
- #%% parameters and data generation
-
- n=5000 # nb samples
-
- mu_s=np.array([0,0])
- cov_s=np.array([[1,0],[0,1]])
-
- mu_t=np.array([4,4])
- cov_t=np.array([[1,-.8],[-.8,1]])
-
- xs=ot.datasets.get_2D_samples_gauss(n,mu_s,cov_s)
- xt=ot.datasets.get_2D_samples_gauss(n,mu_t,cov_t)
-
- a,b = ot.unif(n),ot.unif(n) # uniform distribution on samples
-
- # loss matrix
- M=ot.dist(xs,xt)
- M/=M.max()
-
- #%% plot samples
-
- #pl.figure(1)
- #pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
- #pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
- #pl.legend(loc=0)
- #pl.title('Source and traget distributions')
- #
- #pl.figure(2)
- #pl.imshow(M,interpolation='nearest')
- #pl.title('Cost matrix M')
- #
-
- #%% EMD
-
- G0=ot.emd(a,b,M)
-
- #pl.figure(3)
- #pl.imshow(G0,interpolation='nearest')
- #pl.title('OT matrix G0')
- #
- #pl.figure(4)
- #ot.plot.plot2D_samples_mat(xs,xt,G0,c=[.5,.5,1])
- #pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
- #pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
- #pl.legend(loc=0)
- #pl.title('OT matrix with samples')
-
-
- #%% sinkhorn
-
- # reg term
- lambd=5e-3
-
- Gs=ot.sinkhorn(a,b,M,lambd)
-
- #pl.figure(5)
- #pl.imshow(Gs,interpolation='nearest')
- #pl.title('OT matrix sinkhorn')
- #
- #pl.figure(6)
- #ot.plot.plot2D_samples_mat(xs,xt,Gs,color=[.5,.5,1])
- #pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
- #pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
- #pl.legend(loc=0)
- #pl.title('OT matrix Sinkhorn with samples')
- #
-
-
-**Total running time of the script:** ( 0 minutes 0.000 seconds)
-
-
-
-.. container:: sphx-glr-footer
-
-
- .. container:: sphx-glr-download
-
- :download:`Download Python source code: demo_OT_2D_sampleslarge.py <demo_OT_2D_sampleslarge.py>`
-
-
-
- .. container:: sphx-glr-download
-
- :download:`Download Jupyter notebook: demo_OT_2D_sampleslarge.ipynb <demo_OT_2D_sampleslarge.ipynb>`
-
-.. rst-class:: sphx-glr-signature
-
- `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
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diff --git a/docs/source/auto_examples/images/thumb/sphx_glr_test_OT_2D_samples_stabilized_thumb.png b/docs/source/auto_examples/images/thumb/sphx_glr_test_OT_2D_samples_stabilized_thumb.png
deleted file mode 100644
index cbc8e0f..0000000
--- a/docs/source/auto_examples/images/thumb/sphx_glr_test_OT_2D_samples_stabilized_thumb.png
+++ /dev/null
Binary files differ
diff --git a/docs/source/auto_examples/index.rst b/docs/source/auto_examples/index.rst
index 1695300..eb54ca8 100644
--- a/docs/source/auto_examples/index.rst
+++ b/docs/source/auto_examples/index.rst
@@ -1,9 +1,11 @@
POT Examples
============
+This is a gallery of all the POT example files.
+
.. raw:: html
- <div class="sphx-glr-thumbcontainer" tooltip="@author: rflamary ">
+ <div class="sphx-glr-thumbcontainer" tooltip="This example illustrates the computation of EMD and Sinkhorn transport plans and their visualiz...">
.. only:: html
@@ -23,13 +25,13 @@ POT Examples
.. raw:: html
- <div class="sphx-glr-thumbcontainer" tooltip="@author: rflamary ">
+ <div class="sphx-glr-thumbcontainer" tooltip="Illustrates the use of the generic solver for regularized OT with user-designed regularization ...">
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_WDA_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_optim_OTreg_thumb.png
- :ref:`sphx_glr_auto_examples_plot_WDA.py`
+ :ref:`sphx_glr_auto_examples_plot_optim_OTreg.py`
.. raw:: html
@@ -39,17 +41,17 @@ POT Examples
.. toctree::
:hidden:
- /auto_examples/plot_WDA
+ /auto_examples/plot_optim_OTreg
.. raw:: html
- <div class="sphx-glr-thumbcontainer" tooltip=" ">
+ <div class="sphx-glr-thumbcontainer" tooltip="This example is designed to show how to use the Gromov-Wassertsein distance computation in POT....">
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_optim_OTreg_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_gromov_thumb.png
- :ref:`sphx_glr_auto_examples_plot_optim_OTreg.py`
+ :ref:`sphx_glr_auto_examples_plot_gromov.py`
.. raw:: html
@@ -59,11 +61,11 @@ POT Examples
.. toctree::
:hidden:
- /auto_examples/plot_optim_OTreg
+ /auto_examples/plot_gromov
.. raw:: html
- <div class="sphx-glr-thumbcontainer" tooltip="@author: rflamary ">
+ <div class="sphx-glr-thumbcontainer" tooltip="Illustration of 2D optimal transport between discributions that are weighted sum of diracs. The...">
.. only:: html
@@ -83,7 +85,7 @@ POT Examples
.. raw:: html
- <div class="sphx-glr-thumbcontainer" tooltip="@author: rflamary ">
+ <div class="sphx-glr-thumbcontainer" tooltip="Shows how to compute multiple EMD and Sinkhorn with two differnt ground metrics and plot their ...">
.. only:: html
@@ -103,13 +105,13 @@ POT Examples
.. raw:: html
- <div class="sphx-glr-thumbcontainer" tooltip="[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014). Regularized discrete optima...">
+ <div class="sphx-glr-thumbcontainer" tooltip="This example illustrate the use of WDA as proposed in [11].">
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_OTDA_color_images_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_WDA_thumb.png
- :ref:`sphx_glr_auto_examples_plot_OTDA_color_images.py`
+ :ref:`sphx_glr_auto_examples_plot_WDA.py`
.. raw:: html
@@ -119,17 +121,17 @@ POT Examples
.. toctree::
:hidden:
- /auto_examples/plot_OTDA_color_images
+ /auto_examples/plot_WDA
.. raw:: html
- <div class="sphx-glr-thumbcontainer" tooltip="">
+ <div class="sphx-glr-thumbcontainer" tooltip="This example presents a way of transferring colors between two image with Optimal Transport as ...">
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_OTDA_classes_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_otda_color_images_thumb.png
- :ref:`sphx_glr_auto_examples_plot_OTDA_classes.py`
+ :ref:`sphx_glr_auto_examples_plot_otda_color_images.py`
.. raw:: html
@@ -139,17 +141,17 @@ POT Examples
.. toctree::
:hidden:
- /auto_examples/plot_OTDA_classes
+ /auto_examples/plot_otda_color_images
.. raw:: html
- <div class="sphx-glr-thumbcontainer" tooltip="">
+ <div class="sphx-glr-thumbcontainer" tooltip="This example illustrates the computation of regularized Wassersyein Barycenter as proposed in [...">
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_OTDA_2D_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_barycenter_1D_thumb.png
- :ref:`sphx_glr_auto_examples_plot_OTDA_2D.py`
+ :ref:`sphx_glr_auto_examples_plot_barycenter_1D.py`
.. raw:: html
@@ -159,17 +161,17 @@ POT Examples
.. toctree::
:hidden:
- /auto_examples/plot_OTDA_2D
+ /auto_examples/plot_barycenter_1D
.. raw:: html
- <div class="sphx-glr-thumbcontainer" tooltip="Stole the figure idea from Fig. 1 and 2 in https://arxiv.org/pdf/1706.07650.pdf">
+ <div class="sphx-glr-thumbcontainer" tooltip="OT for domain adaptation with image color adaptation [6] with mapping estimation [8].">
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_OT_L1_vs_L2_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_otda_mapping_colors_images_thumb.png
- :ref:`sphx_glr_auto_examples_plot_OT_L1_vs_L2.py`
+ :ref:`sphx_glr_auto_examples_plot_otda_mapping_colors_images.py`
.. raw:: html
@@ -179,17 +181,17 @@ POT Examples
.. toctree::
:hidden:
- /auto_examples/plot_OT_L1_vs_L2
+ /auto_examples/plot_otda_mapping_colors_images
.. raw:: html
- <div class="sphx-glr-thumbcontainer" tooltip=" @author: rflamary ">
+ <div class="sphx-glr-thumbcontainer" tooltip="This example presents how to use MappingTransport to estimate at the same time both the couplin...">
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_barycenter_1D_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_otda_mapping_thumb.png
- :ref:`sphx_glr_auto_examples_plot_barycenter_1D.py`
+ :ref:`sphx_glr_auto_examples_plot_otda_mapping.py`
.. raw:: html
@@ -199,17 +201,17 @@ POT Examples
.. toctree::
:hidden:
- /auto_examples/plot_barycenter_1D
+ /auto_examples/plot_otda_mapping
.. raw:: html
- <div class="sphx-glr-thumbcontainer" tooltip="[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014). Regularized discrete op...">
+ <div class="sphx-glr-thumbcontainer" tooltip="This example introduces a semi supervised domain adaptation in a 2D setting. It explicits the p...">
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_OTDA_mapping_color_images_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_otda_semi_supervised_thumb.png
- :ref:`sphx_glr_auto_examples_plot_OTDA_mapping_color_images.py`
+ :ref:`sphx_glr_auto_examples_plot_otda_semi_supervised.py`
.. raw:: html
@@ -219,17 +221,77 @@ POT Examples
.. toctree::
:hidden:
- /auto_examples/plot_OTDA_mapping_color_images
+ /auto_examples/plot_otda_semi_supervised
+
+.. raw:: html
+
+ <div class="sphx-glr-thumbcontainer" tooltip="This example introduces a domain adaptation in a 2D setting and the 4 OTDA approaches currently...">
+
+.. only:: html
+
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_otda_classes_thumb.png
+
+ :ref:`sphx_glr_auto_examples_plot_otda_classes.py`
+
+.. raw:: html
+
+ </div>
+
+
+.. toctree::
+ :hidden:
+
+ /auto_examples/plot_otda_classes
+
+.. raw:: html
+
+ <div class="sphx-glr-thumbcontainer" tooltip="This example introduces a domain adaptation in a 2D setting. It explicits the problem of domain...">
+
+.. only:: html
+
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_otda_d2_thumb.png
+
+ :ref:`sphx_glr_auto_examples_plot_otda_d2.py`
+
+.. raw:: html
+
+ </div>
+
+
+.. toctree::
+ :hidden:
+
+ /auto_examples/plot_otda_d2
+
+.. raw:: html
+
+ <div class="sphx-glr-thumbcontainer" tooltip="2D OT on empirical distributio with different gound metric.">
+
+.. only:: html
+
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_OT_L1_vs_L2_thumb.png
+
+ :ref:`sphx_glr_auto_examples_plot_OT_L1_vs_L2.py`
+
+.. raw:: html
+
+ </div>
+
+
+.. toctree::
+ :hidden:
+
+ /auto_examples/plot_OT_L1_vs_L2
.. raw:: html
- <div class="sphx-glr-thumbcontainer" tooltip="[8] M. Perrot, N. Courty, R. Flamary, A. Habrard, "Mapping estimation for discrete optimal ...">
+ <div class="sphx-glr-thumbcontainer" tooltip="This example is designed to show how to use the Gromov-Wasserstein distance computation in POT....">
.. only:: html
- .. figure:: /auto_examples/images/thumb/sphx_glr_plot_OTDA_mapping_thumb.png
+ .. figure:: /auto_examples/images/thumb/sphx_glr_plot_gromov_barycenter_thumb.png
- :ref:`sphx_glr_auto_examples_plot_OTDA_mapping.py`
+ :ref:`sphx_glr_auto_examples_plot_gromov_barycenter.py`
.. raw:: html
@@ -239,7 +301,7 @@ POT Examples
.. toctree::
:hidden:
- /auto_examples/plot_OTDA_mapping
+ /auto_examples/plot_gromov_barycenter
.. raw:: html
<div style='clear:both'></div>
diff --git a/docs/source/auto_examples/plot_OTDA_2D.ipynb b/docs/source/auto_examples/plot_OTDA_2D.ipynb
deleted file mode 100644
index 2ffb256..0000000
--- a/docs/source/auto_examples/plot_OTDA_2D.ipynb
+++ /dev/null
@@ -1,54 +0,0 @@
-{
- "nbformat_minor": 0,
- "nbformat": 4,
- "cells": [
- {
- "execution_count": null,
- "cell_type": "code",
- "source": [
- "%matplotlib inline"
- ],
- "outputs": [],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "source": [
- "\n# OT for empirical distributions\n\n\n\n"
- ],
- "cell_type": "markdown",
- "metadata": {}
- },
- {
- "execution_count": null,
- "cell_type": "code",
- "source": [
- "import numpy as np\nimport matplotlib.pylab as pl\nimport ot\n\n\n\n#%% parameters\n\nn=150 # nb bins\n\nxs,ys=ot.datasets.get_data_classif('3gauss',n)\nxt,yt=ot.datasets.get_data_classif('3gauss2',n)\n\na,b = ot.unif(n),ot.unif(n)\n# loss matrix\nM=ot.dist(xs,xt)\n#M/=M.max()\n\n#%% plot samples\n\npl.figure(1)\n\npl.subplot(2,2,1)\npl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')\npl.legend(loc=0)\npl.title('Source distributions')\n\npl.subplot(2,2,2)\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')\npl.legend(loc=0)\npl.title('target distributions')\n\npl.figure(2)\npl.imshow(M,interpolation='nearest')\npl.title('Cost matrix M')\n\n\n#%% OT estimation\n\n# EMD\nG0=ot.emd(a,b,M)\n\n# sinkhorn\nlambd=1e-1\nGs=ot.sinkhorn(a,b,M,lambd)\n\n\n# Group lasso regularization\nreg=1e-1\neta=1e0\nGg=ot.da.sinkhorn_lpl1_mm(a,ys.astype(np.int),b,M,reg,eta)\n\n\n#%% visu matrices\n\npl.figure(3)\n\npl.subplot(2,3,1)\npl.imshow(G0,interpolation='nearest')\npl.title('OT matrix ')\n\npl.subplot(2,3,2)\npl.imshow(Gs,interpolation='nearest')\npl.title('OT matrix Sinkhorn')\n\npl.subplot(2,3,3)\npl.imshow(Gg,interpolation='nearest')\npl.title('OT matrix Group lasso')\n\npl.subplot(2,3,4)\not.plot.plot2D_samples_mat(xs,xt,G0,c=[.5,.5,1])\npl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')\n\n\npl.subplot(2,3,5)\not.plot.plot2D_samples_mat(xs,xt,Gs,c=[.5,.5,1])\npl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')\n\npl.subplot(2,3,6)\not.plot.plot2D_samples_mat(xs,xt,Gg,c=[.5,.5,1])\npl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')\n\n#%% sample interpolation\n\nxst0=n*G0.dot(xt)\nxsts=n*Gs.dot(xt)\nxstg=n*Gg.dot(xt)\n\npl.figure(4)\npl.subplot(2,3,1)\n\n\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.5)\npl.scatter(xst0[:,0],xst0[:,1],c=ys,marker='+',label='Transp samples',s=30)\npl.title('Interp samples')\npl.legend(loc=0)\n\npl.subplot(2,3,2)\n\n\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.5)\npl.scatter(xsts[:,0],xsts[:,1],c=ys,marker='+',label='Transp samples',s=30)\npl.title('Interp samples Sinkhorn')\n\npl.subplot(2,3,3)\n\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.5)\npl.scatter(xstg[:,0],xstg[:,1],c=ys,marker='+',label='Transp samples',s=30)\npl.title('Interp samples Grouplasso')"
- ],
- "outputs": [],
- "metadata": {
- "collapsed": false
- }
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 2",
- "name": "python2",
- "language": "python"
- },
- "language_info": {
- "mimetype": "text/x-python",
- "nbconvert_exporter": "python",
- "name": "python",
- "file_extension": ".py",
- "version": "2.7.12",
- "pygments_lexer": "ipython2",
- "codemirror_mode": {
- "version": 2,
- "name": "ipython"
- }
- }
- }
-} \ No newline at end of file
diff --git a/docs/source/auto_examples/plot_OTDA_2D.py b/docs/source/auto_examples/plot_OTDA_2D.py
deleted file mode 100644
index a1fb804..0000000
--- a/docs/source/auto_examples/plot_OTDA_2D.py
+++ /dev/null
@@ -1,120 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-==============================
-OT for empirical distributions
-==============================
-
-"""
-
-import numpy as np
-import matplotlib.pylab as pl
-import ot
-
-
-
-#%% parameters
-
-n=150 # nb bins
-
-xs,ys=ot.datasets.get_data_classif('3gauss',n)
-xt,yt=ot.datasets.get_data_classif('3gauss2',n)
-
-a,b = ot.unif(n),ot.unif(n)
-# loss matrix
-M=ot.dist(xs,xt)
-#M/=M.max()
-
-#%% plot samples
-
-pl.figure(1)
-
-pl.subplot(2,2,1)
-pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')
-pl.legend(loc=0)
-pl.title('Source distributions')
-
-pl.subplot(2,2,2)
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')
-pl.legend(loc=0)
-pl.title('target distributions')
-
-pl.figure(2)
-pl.imshow(M,interpolation='nearest')
-pl.title('Cost matrix M')
-
-
-#%% OT estimation
-
-# EMD
-G0=ot.emd(a,b,M)
-
-# sinkhorn
-lambd=1e-1
-Gs=ot.sinkhorn(a,b,M,lambd)
-
-
-# Group lasso regularization
-reg=1e-1
-eta=1e0
-Gg=ot.da.sinkhorn_lpl1_mm(a,ys.astype(np.int),b,M,reg,eta)
-
-
-#%% visu matrices
-
-pl.figure(3)
-
-pl.subplot(2,3,1)
-pl.imshow(G0,interpolation='nearest')
-pl.title('OT matrix ')
-
-pl.subplot(2,3,2)
-pl.imshow(Gs,interpolation='nearest')
-pl.title('OT matrix Sinkhorn')
-
-pl.subplot(2,3,3)
-pl.imshow(Gg,interpolation='nearest')
-pl.title('OT matrix Group lasso')
-
-pl.subplot(2,3,4)
-ot.plot.plot2D_samples_mat(xs,xt,G0,c=[.5,.5,1])
-pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')
-
-
-pl.subplot(2,3,5)
-ot.plot.plot2D_samples_mat(xs,xt,Gs,c=[.5,.5,1])
-pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')
-
-pl.subplot(2,3,6)
-ot.plot.plot2D_samples_mat(xs,xt,Gg,c=[.5,.5,1])
-pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')
-
-#%% sample interpolation
-
-xst0=n*G0.dot(xt)
-xsts=n*Gs.dot(xt)
-xstg=n*Gg.dot(xt)
-
-pl.figure(4)
-pl.subplot(2,3,1)
-
-
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.5)
-pl.scatter(xst0[:,0],xst0[:,1],c=ys,marker='+',label='Transp samples',s=30)
-pl.title('Interp samples')
-pl.legend(loc=0)
-
-pl.subplot(2,3,2)
-
-
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.5)
-pl.scatter(xsts[:,0],xsts[:,1],c=ys,marker='+',label='Transp samples',s=30)
-pl.title('Interp samples Sinkhorn')
-
-pl.subplot(2,3,3)
-
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.5)
-pl.scatter(xstg[:,0],xstg[:,1],c=ys,marker='+',label='Transp samples',s=30)
-pl.title('Interp samples Grouplasso') \ No newline at end of file
diff --git a/docs/source/auto_examples/plot_OTDA_2D.rst b/docs/source/auto_examples/plot_OTDA_2D.rst
deleted file mode 100644
index b535bb0..0000000
--- a/docs/source/auto_examples/plot_OTDA_2D.rst
+++ /dev/null
@@ -1,175 +0,0 @@
-
-
-.. _sphx_glr_auto_examples_plot_OTDA_2D.py:
-
-
-==============================
-OT for empirical distributions
-==============================
-
-
-
-
-
-.. rst-class:: sphx-glr-horizontal
-
-
- *
-
- .. image:: /auto_examples/images/sphx_glr_plot_OTDA_2D_001.png
- :scale: 47
-
- *
-
- .. image:: /auto_examples/images/sphx_glr_plot_OTDA_2D_002.png
- :scale: 47
-
- *
-
- .. image:: /auto_examples/images/sphx_glr_plot_OTDA_2D_003.png
- :scale: 47
-
- *
-
- .. image:: /auto_examples/images/sphx_glr_plot_OTDA_2D_004.png
- :scale: 47
-
-
-
-
-
-.. code-block:: python
-
-
- import numpy as np
- import matplotlib.pylab as pl
- import ot
-
-
-
- #%% parameters
-
- n=150 # nb bins
-
- xs,ys=ot.datasets.get_data_classif('3gauss',n)
- xt,yt=ot.datasets.get_data_classif('3gauss2',n)
-
- a,b = ot.unif(n),ot.unif(n)
- # loss matrix
- M=ot.dist(xs,xt)
- #M/=M.max()
-
- #%% plot samples
-
- pl.figure(1)
-
- pl.subplot(2,2,1)
- pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')
- pl.legend(loc=0)
- pl.title('Source distributions')
-
- pl.subplot(2,2,2)
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')
- pl.legend(loc=0)
- pl.title('target distributions')
-
- pl.figure(2)
- pl.imshow(M,interpolation='nearest')
- pl.title('Cost matrix M')
-
-
- #%% OT estimation
-
- # EMD
- G0=ot.emd(a,b,M)
-
- # sinkhorn
- lambd=1e-1
- Gs=ot.sinkhorn(a,b,M,lambd)
-
-
- # Group lasso regularization
- reg=1e-1
- eta=1e0
- Gg=ot.da.sinkhorn_lpl1_mm(a,ys.astype(np.int),b,M,reg,eta)
-
-
- #%% visu matrices
-
- pl.figure(3)
-
- pl.subplot(2,3,1)
- pl.imshow(G0,interpolation='nearest')
- pl.title('OT matrix ')
-
- pl.subplot(2,3,2)
- pl.imshow(Gs,interpolation='nearest')
- pl.title('OT matrix Sinkhorn')
-
- pl.subplot(2,3,3)
- pl.imshow(Gg,interpolation='nearest')
- pl.title('OT matrix Group lasso')
-
- pl.subplot(2,3,4)
- ot.plot.plot2D_samples_mat(xs,xt,G0,c=[.5,.5,1])
- pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')
-
-
- pl.subplot(2,3,5)
- ot.plot.plot2D_samples_mat(xs,xt,Gs,c=[.5,.5,1])
- pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')
-
- pl.subplot(2,3,6)
- ot.plot.plot2D_samples_mat(xs,xt,Gg,c=[.5,.5,1])
- pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')
-
- #%% sample interpolation
-
- xst0=n*G0.dot(xt)
- xsts=n*Gs.dot(xt)
- xstg=n*Gg.dot(xt)
-
- pl.figure(4)
- pl.subplot(2,3,1)
-
-
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.5)
- pl.scatter(xst0[:,0],xst0[:,1],c=ys,marker='+',label='Transp samples',s=30)
- pl.title('Interp samples')
- pl.legend(loc=0)
-
- pl.subplot(2,3,2)
-
-
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.5)
- pl.scatter(xsts[:,0],xsts[:,1],c=ys,marker='+',label='Transp samples',s=30)
- pl.title('Interp samples Sinkhorn')
-
- pl.subplot(2,3,3)
-
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.5)
- pl.scatter(xstg[:,0],xstg[:,1],c=ys,marker='+',label='Transp samples',s=30)
- pl.title('Interp samples Grouplasso')
-**Total running time of the script:** ( 0 minutes 17.372 seconds)
-
-
-
-.. container:: sphx-glr-footer
-
-
- .. container:: sphx-glr-download
-
- :download:`Download Python source code: plot_OTDA_2D.py <plot_OTDA_2D.py>`
-
-
-
- .. container:: sphx-glr-download
-
- :download:`Download Jupyter notebook: plot_OTDA_2D.ipynb <plot_OTDA_2D.ipynb>`
-
-.. rst-class:: sphx-glr-signature
-
- `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
diff --git a/docs/source/auto_examples/plot_OTDA_classes.ipynb b/docs/source/auto_examples/plot_OTDA_classes.ipynb
deleted file mode 100644
index d9fcb87..0000000
--- a/docs/source/auto_examples/plot_OTDA_classes.ipynb
+++ /dev/null
@@ -1,54 +0,0 @@
-{
- "nbformat_minor": 0,
- "nbformat": 4,
- "cells": [
- {
- "execution_count": null,
- "cell_type": "code",
- "source": [
- "%matplotlib inline"
- ],
- "outputs": [],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "source": [
- "\n# OT for domain adaptation\n\n\n\n"
- ],
- "cell_type": "markdown",
- "metadata": {}
- },
- {
- "execution_count": null,
- "cell_type": "code",
- "source": [
- "import matplotlib.pylab as pl\nimport ot\n\n\n\n\n#%% parameters\n\nn=150 # nb samples in source and target datasets\n\nxs,ys=ot.datasets.get_data_classif('3gauss',n)\nxt,yt=ot.datasets.get_data_classif('3gauss2',n)\n\n\n\n\n#%% plot samples\n\npl.figure(1)\n\npl.subplot(2,2,1)\npl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')\npl.legend(loc=0)\npl.title('Source distributions')\n\npl.subplot(2,2,2)\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')\npl.legend(loc=0)\npl.title('target distributions')\n\n\n#%% OT estimation\n\n# LP problem\nda_emd=ot.da.OTDA() # init class\nda_emd.fit(xs,xt) # fit distributions\nxst0=da_emd.interp() # interpolation of source samples\n\n\n# sinkhorn regularization\nlambd=1e-1\nda_entrop=ot.da.OTDA_sinkhorn()\nda_entrop.fit(xs,xt,reg=lambd)\nxsts=da_entrop.interp()\n\n# non-convex Group lasso regularization\nreg=1e-1\neta=1e0\nda_lpl1=ot.da.OTDA_lpl1()\nda_lpl1.fit(xs,ys,xt,reg=reg,eta=eta)\nxstg=da_lpl1.interp()\n\n\n# True Group lasso regularization\nreg=1e-1\neta=2e0\nda_l1l2=ot.da.OTDA_l1l2()\nda_l1l2.fit(xs,ys,xt,reg=reg,eta=eta,numItermax=20,verbose=True)\nxstgl=da_l1l2.interp()\n\n\n#%% plot interpolated source samples\npl.figure(4,(15,8))\n\nparam_img={'interpolation':'nearest','cmap':'jet'}\n\npl.subplot(2,4,1)\npl.imshow(da_emd.G,**param_img)\npl.title('OT matrix')\n\n\npl.subplot(2,4,2)\npl.imshow(da_entrop.G,**param_img)\npl.title('OT matrix sinkhorn')\n\npl.subplot(2,4,3)\npl.imshow(da_lpl1.G,**param_img)\npl.title('OT matrix non-convex Group Lasso')\n\npl.subplot(2,4,4)\npl.imshow(da_l1l2.G,**param_img)\npl.title('OT matrix Group Lasso')\n\n\npl.subplot(2,4,5)\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3)\npl.scatter(xst0[:,0],xst0[:,1],c=ys,marker='+',label='Transp samples',s=30)\npl.title('Interp samples')\npl.legend(loc=0)\n\npl.subplot(2,4,6)\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3)\npl.scatter(xsts[:,0],xsts[:,1],c=ys,marker='+',label='Transp samples',s=30)\npl.title('Interp samples Sinkhorn')\n\npl.subplot(2,4,7)\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3)\npl.scatter(xstg[:,0],xstg[:,1],c=ys,marker='+',label='Transp samples',s=30)\npl.title('Interp samples non-convex Group Lasso')\n\npl.subplot(2,4,8)\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3)\npl.scatter(xstgl[:,0],xstgl[:,1],c=ys,marker='+',label='Transp samples',s=30)\npl.title('Interp samples Group Lasso')"
- ],
- "outputs": [],
- "metadata": {
- "collapsed": false
- }
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 2",
- "name": "python2",
- "language": "python"
- },
- "language_info": {
- "mimetype": "text/x-python",
- "nbconvert_exporter": "python",
- "name": "python",
- "file_extension": ".py",
- "version": "2.7.12",
- "pygments_lexer": "ipython2",
- "codemirror_mode": {
- "version": 2,
- "name": "ipython"
- }
- }
- }
-} \ No newline at end of file
diff --git a/docs/source/auto_examples/plot_OTDA_classes.py b/docs/source/auto_examples/plot_OTDA_classes.py
deleted file mode 100644
index 089b45b..0000000
--- a/docs/source/auto_examples/plot_OTDA_classes.py
+++ /dev/null
@@ -1,112 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-========================
-OT for domain adaptation
-========================
-
-"""
-
-import matplotlib.pylab as pl
-import ot
-
-
-
-
-#%% parameters
-
-n=150 # nb samples in source and target datasets
-
-xs,ys=ot.datasets.get_data_classif('3gauss',n)
-xt,yt=ot.datasets.get_data_classif('3gauss2',n)
-
-
-
-
-#%% plot samples
-
-pl.figure(1)
-
-pl.subplot(2,2,1)
-pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')
-pl.legend(loc=0)
-pl.title('Source distributions')
-
-pl.subplot(2,2,2)
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')
-pl.legend(loc=0)
-pl.title('target distributions')
-
-
-#%% OT estimation
-
-# LP problem
-da_emd=ot.da.OTDA() # init class
-da_emd.fit(xs,xt) # fit distributions
-xst0=da_emd.interp() # interpolation of source samples
-
-
-# sinkhorn regularization
-lambd=1e-1
-da_entrop=ot.da.OTDA_sinkhorn()
-da_entrop.fit(xs,xt,reg=lambd)
-xsts=da_entrop.interp()
-
-# non-convex Group lasso regularization
-reg=1e-1
-eta=1e0
-da_lpl1=ot.da.OTDA_lpl1()
-da_lpl1.fit(xs,ys,xt,reg=reg,eta=eta)
-xstg=da_lpl1.interp()
-
-
-# True Group lasso regularization
-reg=1e-1
-eta=2e0
-da_l1l2=ot.da.OTDA_l1l2()
-da_l1l2.fit(xs,ys,xt,reg=reg,eta=eta,numItermax=20,verbose=True)
-xstgl=da_l1l2.interp()
-
-
-#%% plot interpolated source samples
-pl.figure(4,(15,8))
-
-param_img={'interpolation':'nearest','cmap':'jet'}
-
-pl.subplot(2,4,1)
-pl.imshow(da_emd.G,**param_img)
-pl.title('OT matrix')
-
-
-pl.subplot(2,4,2)
-pl.imshow(da_entrop.G,**param_img)
-pl.title('OT matrix sinkhorn')
-
-pl.subplot(2,4,3)
-pl.imshow(da_lpl1.G,**param_img)
-pl.title('OT matrix non-convex Group Lasso')
-
-pl.subplot(2,4,4)
-pl.imshow(da_l1l2.G,**param_img)
-pl.title('OT matrix Group Lasso')
-
-
-pl.subplot(2,4,5)
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3)
-pl.scatter(xst0[:,0],xst0[:,1],c=ys,marker='+',label='Transp samples',s=30)
-pl.title('Interp samples')
-pl.legend(loc=0)
-
-pl.subplot(2,4,6)
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3)
-pl.scatter(xsts[:,0],xsts[:,1],c=ys,marker='+',label='Transp samples',s=30)
-pl.title('Interp samples Sinkhorn')
-
-pl.subplot(2,4,7)
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3)
-pl.scatter(xstg[:,0],xstg[:,1],c=ys,marker='+',label='Transp samples',s=30)
-pl.title('Interp samples non-convex Group Lasso')
-
-pl.subplot(2,4,8)
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3)
-pl.scatter(xstgl[:,0],xstgl[:,1],c=ys,marker='+',label='Transp samples',s=30)
-pl.title('Interp samples Group Lasso') \ No newline at end of file
diff --git a/docs/source/auto_examples/plot_OTDA_classes.rst b/docs/source/auto_examples/plot_OTDA_classes.rst
deleted file mode 100644
index 097e9fc..0000000
--- a/docs/source/auto_examples/plot_OTDA_classes.rst
+++ /dev/null
@@ -1,190 +0,0 @@
-
-
-.. _sphx_glr_auto_examples_plot_OTDA_classes.py:
-
-
-========================
-OT for domain adaptation
-========================
-
-
-
-
-
-.. rst-class:: sphx-glr-horizontal
-
-
- *
-
- .. image:: /auto_examples/images/sphx_glr_plot_OTDA_classes_001.png
- :scale: 47
-
- *
-
- .. image:: /auto_examples/images/sphx_glr_plot_OTDA_classes_004.png
- :scale: 47
-
-
-.. rst-class:: sphx-glr-script-out
-
- Out::
-
- It. |Loss |Delta loss
- --------------------------------
- 0|9.171271e+00|0.000000e+00
- 1|2.133783e+00|-3.298127e+00
- 2|1.895941e+00|-1.254484e-01
- 3|1.844628e+00|-2.781709e-02
- 4|1.824983e+00|-1.076467e-02
- 5|1.815453e+00|-5.249337e-03
- 6|1.808104e+00|-4.064733e-03
- 7|1.803558e+00|-2.520475e-03
- 8|1.801061e+00|-1.386155e-03
- 9|1.799391e+00|-9.279565e-04
- 10|1.797176e+00|-1.232778e-03
- 11|1.795465e+00|-9.529479e-04
- 12|1.795316e+00|-8.322362e-05
- 13|1.794523e+00|-4.418932e-04
- 14|1.794444e+00|-4.390599e-05
- 15|1.794395e+00|-2.710318e-05
- 16|1.793713e+00|-3.804028e-04
- 17|1.793110e+00|-3.359479e-04
- 18|1.792829e+00|-1.569563e-04
- 19|1.792621e+00|-1.159469e-04
- It. |Loss |Delta loss
- --------------------------------
- 20|1.791334e+00|-7.187689e-04
-
-
-
-
-|
-
-
-.. code-block:: python
-
-
- import matplotlib.pylab as pl
- import ot
-
-
-
-
- #%% parameters
-
- n=150 # nb samples in source and target datasets
-
- xs,ys=ot.datasets.get_data_classif('3gauss',n)
- xt,yt=ot.datasets.get_data_classif('3gauss2',n)
-
-
-
-
- #%% plot samples
-
- pl.figure(1)
-
- pl.subplot(2,2,1)
- pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')
- pl.legend(loc=0)
- pl.title('Source distributions')
-
- pl.subplot(2,2,2)
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')
- pl.legend(loc=0)
- pl.title('target distributions')
-
-
- #%% OT estimation
-
- # LP problem
- da_emd=ot.da.OTDA() # init class
- da_emd.fit(xs,xt) # fit distributions
- xst0=da_emd.interp() # interpolation of source samples
-
-
- # sinkhorn regularization
- lambd=1e-1
- da_entrop=ot.da.OTDA_sinkhorn()
- da_entrop.fit(xs,xt,reg=lambd)
- xsts=da_entrop.interp()
-
- # non-convex Group lasso regularization
- reg=1e-1
- eta=1e0
- da_lpl1=ot.da.OTDA_lpl1()
- da_lpl1.fit(xs,ys,xt,reg=reg,eta=eta)
- xstg=da_lpl1.interp()
-
-
- # True Group lasso regularization
- reg=1e-1
- eta=2e0
- da_l1l2=ot.da.OTDA_l1l2()
- da_l1l2.fit(xs,ys,xt,reg=reg,eta=eta,numItermax=20,verbose=True)
- xstgl=da_l1l2.interp()
-
-
- #%% plot interpolated source samples
- pl.figure(4,(15,8))
-
- param_img={'interpolation':'nearest','cmap':'jet'}
-
- pl.subplot(2,4,1)
- pl.imshow(da_emd.G,**param_img)
- pl.title('OT matrix')
-
-
- pl.subplot(2,4,2)
- pl.imshow(da_entrop.G,**param_img)
- pl.title('OT matrix sinkhorn')
-
- pl.subplot(2,4,3)
- pl.imshow(da_lpl1.G,**param_img)
- pl.title('OT matrix non-convex Group Lasso')
-
- pl.subplot(2,4,4)
- pl.imshow(da_l1l2.G,**param_img)
- pl.title('OT matrix Group Lasso')
-
-
- pl.subplot(2,4,5)
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3)
- pl.scatter(xst0[:,0],xst0[:,1],c=ys,marker='+',label='Transp samples',s=30)
- pl.title('Interp samples')
- pl.legend(loc=0)
-
- pl.subplot(2,4,6)
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3)
- pl.scatter(xsts[:,0],xsts[:,1],c=ys,marker='+',label='Transp samples',s=30)
- pl.title('Interp samples Sinkhorn')
-
- pl.subplot(2,4,7)
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3)
- pl.scatter(xstg[:,0],xstg[:,1],c=ys,marker='+',label='Transp samples',s=30)
- pl.title('Interp samples non-convex Group Lasso')
-
- pl.subplot(2,4,8)
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3)
- pl.scatter(xstgl[:,0],xstgl[:,1],c=ys,marker='+',label='Transp samples',s=30)
- pl.title('Interp samples Group Lasso')
-**Total running time of the script:** ( 0 minutes 2.225 seconds)
-
-
-
-.. container:: sphx-glr-footer
-
-
- .. container:: sphx-glr-download
-
- :download:`Download Python source code: plot_OTDA_classes.py <plot_OTDA_classes.py>`
-
-
-
- .. container:: sphx-glr-download
-
- :download:`Download Jupyter notebook: plot_OTDA_classes.ipynb <plot_OTDA_classes.ipynb>`
-
-.. rst-class:: sphx-glr-signature
-
- `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
diff --git a/docs/source/auto_examples/plot_OTDA_color_images.ipynb b/docs/source/auto_examples/plot_OTDA_color_images.ipynb
deleted file mode 100644
index d174828..0000000
--- a/docs/source/auto_examples/plot_OTDA_color_images.ipynb
+++ /dev/null
@@ -1,54 +0,0 @@
-{
- "nbformat_minor": 0,
- "nbformat": 4,
- "cells": [
- {
- "execution_count": null,
- "cell_type": "code",
- "source": [
- "%matplotlib inline"
- ],
- "outputs": [],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "source": [
- "\n========================================================\nOT for domain adaptation with image color adaptation [6]\n========================================================\n\n[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014). Regularized discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3), 1853-1882.\n\n"
- ],
- "cell_type": "markdown",
- "metadata": {}
- },
- {
- "execution_count": null,
- "cell_type": "code",
- "source": [
- "import numpy as np\nimport scipy.ndimage as spi\nimport matplotlib.pylab as pl\nimport ot\n\n\n#%% Loading images\n\nI1=spi.imread('../data/ocean_day.jpg').astype(np.float64)/256\nI2=spi.imread('../data/ocean_sunset.jpg').astype(np.float64)/256\n\n#%% Plot images\n\npl.figure(1)\n\npl.subplot(1,2,1)\npl.imshow(I1)\npl.title('Image 1')\n\npl.subplot(1,2,2)\npl.imshow(I2)\npl.title('Image 2')\n\npl.show()\n\n#%% Image conversion and dataset generation\n\ndef im2mat(I):\n \"\"\"Converts and image to matrix (one pixel per line)\"\"\"\n return I.reshape((I.shape[0]*I.shape[1],I.shape[2]))\n\ndef mat2im(X,shape):\n \"\"\"Converts back a matrix to an image\"\"\"\n return X.reshape(shape)\n\nX1=im2mat(I1)\nX2=im2mat(I2)\n\n# training samples\nnb=1000\nidx1=np.random.randint(X1.shape[0],size=(nb,))\nidx2=np.random.randint(X2.shape[0],size=(nb,))\n\nxs=X1[idx1,:]\nxt=X2[idx2,:]\n\n#%% Plot image distributions\n\n\npl.figure(2,(10,5))\n\npl.subplot(1,2,1)\npl.scatter(xs[:,0],xs[:,2],c=xs)\npl.axis([0,1,0,1])\npl.xlabel('Red')\npl.ylabel('Blue')\npl.title('Image 1')\n\npl.subplot(1,2,2)\n#pl.imshow(I2)\npl.scatter(xt[:,0],xt[:,2],c=xt)\npl.axis([0,1,0,1])\npl.xlabel('Red')\npl.ylabel('Blue')\npl.title('Image 2')\n\npl.show()\n\n\n\n#%% domain adaptation between images\n\n# LP problem\nda_emd=ot.da.OTDA() # init class\nda_emd.fit(xs,xt) # fit distributions\n\n\n# sinkhorn regularization\nlambd=1e-1\nda_entrop=ot.da.OTDA_sinkhorn()\nda_entrop.fit(xs,xt,reg=lambd)\n\n\n\n#%% prediction between images (using out of sample prediction as in [6])\n\nX1t=da_emd.predict(X1)\nX2t=da_emd.predict(X2,-1)\n\n\nX1te=da_entrop.predict(X1)\nX2te=da_entrop.predict(X2,-1)\n\n\ndef minmax(I):\n return np.minimum(np.maximum(I,0),1)\n\nI1t=minmax(mat2im(X1t,I1.shape))\nI2t=minmax(mat2im(X2t,I2.shape))\n\nI1te=minmax(mat2im(X1te,I1.shape))\nI2te=minmax(mat2im(X2te,I2.shape))\n\n#%% plot all images\n\npl.figure(2,(10,8))\n\npl.subplot(2,3,1)\n\npl.imshow(I1)\npl.title('Image 1')\n\npl.subplot(2,3,2)\npl.imshow(I1t)\npl.title('Image 1 Adapt')\n\n\npl.subplot(2,3,3)\npl.imshow(I1te)\npl.title('Image 1 Adapt (reg)')\n\npl.subplot(2,3,4)\n\npl.imshow(I2)\npl.title('Image 2')\n\npl.subplot(2,3,5)\npl.imshow(I2t)\npl.title('Image 2 Adapt')\n\n\npl.subplot(2,3,6)\npl.imshow(I2te)\npl.title('Image 2 Adapt (reg)')\n\npl.show()"
- ],
- "outputs": [],
- "metadata": {
- "collapsed": false
- }
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 2",
- "name": "python2",
- "language": "python"
- },
- "language_info": {
- "mimetype": "text/x-python",
- "nbconvert_exporter": "python",
- "name": "python",
- "file_extension": ".py",
- "version": "2.7.12",
- "pygments_lexer": "ipython2",
- "codemirror_mode": {
- "version": 2,
- "name": "ipython"
- }
- }
- }
-} \ No newline at end of file
diff --git a/docs/source/auto_examples/plot_OTDA_color_images.py b/docs/source/auto_examples/plot_OTDA_color_images.py
deleted file mode 100644
index 68eee44..0000000
--- a/docs/source/auto_examples/plot_OTDA_color_images.py
+++ /dev/null
@@ -1,145 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-========================================================
-OT for domain adaptation with image color adaptation [6]
-========================================================
-
-[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014). Regularized discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3), 1853-1882.
-"""
-
-import numpy as np
-import scipy.ndimage as spi
-import matplotlib.pylab as pl
-import ot
-
-
-#%% Loading images
-
-I1=spi.imread('../data/ocean_day.jpg').astype(np.float64)/256
-I2=spi.imread('../data/ocean_sunset.jpg').astype(np.float64)/256
-
-#%% Plot images
-
-pl.figure(1)
-
-pl.subplot(1,2,1)
-pl.imshow(I1)
-pl.title('Image 1')
-
-pl.subplot(1,2,2)
-pl.imshow(I2)
-pl.title('Image 2')
-
-pl.show()
-
-#%% Image conversion and dataset generation
-
-def im2mat(I):
- """Converts and image to matrix (one pixel per line)"""
- return I.reshape((I.shape[0]*I.shape[1],I.shape[2]))
-
-def mat2im(X,shape):
- """Converts back a matrix to an image"""
- return X.reshape(shape)
-
-X1=im2mat(I1)
-X2=im2mat(I2)
-
-# training samples
-nb=1000
-idx1=np.random.randint(X1.shape[0],size=(nb,))
-idx2=np.random.randint(X2.shape[0],size=(nb,))
-
-xs=X1[idx1,:]
-xt=X2[idx2,:]
-
-#%% Plot image distributions
-
-
-pl.figure(2,(10,5))
-
-pl.subplot(1,2,1)
-pl.scatter(xs[:,0],xs[:,2],c=xs)
-pl.axis([0,1,0,1])
-pl.xlabel('Red')
-pl.ylabel('Blue')
-pl.title('Image 1')
-
-pl.subplot(1,2,2)
-#pl.imshow(I2)
-pl.scatter(xt[:,0],xt[:,2],c=xt)
-pl.axis([0,1,0,1])
-pl.xlabel('Red')
-pl.ylabel('Blue')
-pl.title('Image 2')
-
-pl.show()
-
-
-
-#%% domain adaptation between images
-
-# LP problem
-da_emd=ot.da.OTDA() # init class
-da_emd.fit(xs,xt) # fit distributions
-
-
-# sinkhorn regularization
-lambd=1e-1
-da_entrop=ot.da.OTDA_sinkhorn()
-da_entrop.fit(xs,xt,reg=lambd)
-
-
-
-#%% prediction between images (using out of sample prediction as in [6])
-
-X1t=da_emd.predict(X1)
-X2t=da_emd.predict(X2,-1)
-
-
-X1te=da_entrop.predict(X1)
-X2te=da_entrop.predict(X2,-1)
-
-
-def minmax(I):
- return np.minimum(np.maximum(I,0),1)
-
-I1t=minmax(mat2im(X1t,I1.shape))
-I2t=minmax(mat2im(X2t,I2.shape))
-
-I1te=minmax(mat2im(X1te,I1.shape))
-I2te=minmax(mat2im(X2te,I2.shape))
-
-#%% plot all images
-
-pl.figure(2,(10,8))
-
-pl.subplot(2,3,1)
-
-pl.imshow(I1)
-pl.title('Image 1')
-
-pl.subplot(2,3,2)
-pl.imshow(I1t)
-pl.title('Image 1 Adapt')
-
-
-pl.subplot(2,3,3)
-pl.imshow(I1te)
-pl.title('Image 1 Adapt (reg)')
-
-pl.subplot(2,3,4)
-
-pl.imshow(I2)
-pl.title('Image 2')
-
-pl.subplot(2,3,5)
-pl.imshow(I2t)
-pl.title('Image 2 Adapt')
-
-
-pl.subplot(2,3,6)
-pl.imshow(I2te)
-pl.title('Image 2 Adapt (reg)')
-
-pl.show()
diff --git a/docs/source/auto_examples/plot_OTDA_color_images.rst b/docs/source/auto_examples/plot_OTDA_color_images.rst
deleted file mode 100644
index a982a90..0000000
--- a/docs/source/auto_examples/plot_OTDA_color_images.rst
+++ /dev/null
@@ -1,191 +0,0 @@
-
-
-.. _sphx_glr_auto_examples_plot_OTDA_color_images.py:
-
-
-========================================================
-OT for domain adaptation with image color adaptation [6]
-========================================================
-
-[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014). Regularized discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3), 1853-1882.
-
-
-
-
-.. rst-class:: sphx-glr-horizontal
-
-
- *
-
- .. image:: /auto_examples/images/sphx_glr_plot_OTDA_color_images_001.png
- :scale: 47
-
- *
-
- .. image:: /auto_examples/images/sphx_glr_plot_OTDA_color_images_002.png
- :scale: 47
-
-
-
-
-
-.. code-block:: python
-
-
- import numpy as np
- import scipy.ndimage as spi
- import matplotlib.pylab as pl
- import ot
-
-
- #%% Loading images
-
- I1=spi.imread('../data/ocean_day.jpg').astype(np.float64)/256
- I2=spi.imread('../data/ocean_sunset.jpg').astype(np.float64)/256
-
- #%% Plot images
-
- pl.figure(1)
-
- pl.subplot(1,2,1)
- pl.imshow(I1)
- pl.title('Image 1')
-
- pl.subplot(1,2,2)
- pl.imshow(I2)
- pl.title('Image 2')
-
- pl.show()
-
- #%% Image conversion and dataset generation
-
- def im2mat(I):
- """Converts and image to matrix (one pixel per line)"""
- return I.reshape((I.shape[0]*I.shape[1],I.shape[2]))
-
- def mat2im(X,shape):
- """Converts back a matrix to an image"""
- return X.reshape(shape)
-
- X1=im2mat(I1)
- X2=im2mat(I2)
-
- # training samples
- nb=1000
- idx1=np.random.randint(X1.shape[0],size=(nb,))
- idx2=np.random.randint(X2.shape[0],size=(nb,))
-
- xs=X1[idx1,:]
- xt=X2[idx2,:]
-
- #%% Plot image distributions
-
-
- pl.figure(2,(10,5))
-
- pl.subplot(1,2,1)
- pl.scatter(xs[:,0],xs[:,2],c=xs)
- pl.axis([0,1,0,1])
- pl.xlabel('Red')
- pl.ylabel('Blue')
- pl.title('Image 1')
-
- pl.subplot(1,2,2)
- #pl.imshow(I2)
- pl.scatter(xt[:,0],xt[:,2],c=xt)
- pl.axis([0,1,0,1])
- pl.xlabel('Red')
- pl.ylabel('Blue')
- pl.title('Image 2')
-
- pl.show()
-
-
-
- #%% domain adaptation between images
-
- # LP problem
- da_emd=ot.da.OTDA() # init class
- da_emd.fit(xs,xt) # fit distributions
-
-
- # sinkhorn regularization
- lambd=1e-1
- da_entrop=ot.da.OTDA_sinkhorn()
- da_entrop.fit(xs,xt,reg=lambd)
-
-
-
- #%% prediction between images (using out of sample prediction as in [6])
-
- X1t=da_emd.predict(X1)
- X2t=da_emd.predict(X2,-1)
-
-
- X1te=da_entrop.predict(X1)
- X2te=da_entrop.predict(X2,-1)
-
-
- def minmax(I):
- return np.minimum(np.maximum(I,0),1)
-
- I1t=minmax(mat2im(X1t,I1.shape))
- I2t=minmax(mat2im(X2t,I2.shape))
-
- I1te=minmax(mat2im(X1te,I1.shape))
- I2te=minmax(mat2im(X2te,I2.shape))
-
- #%% plot all images
-
- pl.figure(2,(10,8))
-
- pl.subplot(2,3,1)
-
- pl.imshow(I1)
- pl.title('Image 1')
-
- pl.subplot(2,3,2)
- pl.imshow(I1t)
- pl.title('Image 1 Adapt')
-
-
- pl.subplot(2,3,3)
- pl.imshow(I1te)
- pl.title('Image 1 Adapt (reg)')
-
- pl.subplot(2,3,4)
-
- pl.imshow(I2)
- pl.title('Image 2')
-
- pl.subplot(2,3,5)
- pl.imshow(I2t)
- pl.title('Image 2 Adapt')
-
-
- pl.subplot(2,3,6)
- pl.imshow(I2te)
- pl.title('Image 2 Adapt (reg)')
-
- pl.show()
-
-**Total running time of the script:** ( 0 minutes 24.815 seconds)
-
-
-
-.. container:: sphx-glr-footer
-
-
- .. container:: sphx-glr-download
-
- :download:`Download Python source code: plot_OTDA_color_images.py <plot_OTDA_color_images.py>`
-
-
-
- .. container:: sphx-glr-download
-
- :download:`Download Jupyter notebook: plot_OTDA_color_images.ipynb <plot_OTDA_color_images.ipynb>`
-
-.. rst-class:: sphx-glr-signature
-
- `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
diff --git a/docs/source/auto_examples/plot_OTDA_mapping.ipynb b/docs/source/auto_examples/plot_OTDA_mapping.ipynb
deleted file mode 100644
index ec405af..0000000
--- a/docs/source/auto_examples/plot_OTDA_mapping.ipynb
+++ /dev/null
@@ -1,54 +0,0 @@
-{
- "nbformat_minor": 0,
- "nbformat": 4,
- "cells": [
- {
- "execution_count": null,
- "cell_type": "code",
- "source": [
- "%matplotlib inline"
- ],
- "outputs": [],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "source": [
- "\n===============================================\nOT mapping estimation for domain adaptation [8]\n===============================================\n\n[8] M. Perrot, N. Courty, R. Flamary, A. Habrard, \"Mapping estimation for\n discrete optimal transport\", Neural Information Processing Systems (NIPS), 2016.\n\n"
- ],
- "cell_type": "markdown",
- "metadata": {}
- },
- {
- "execution_count": null,
- "cell_type": "code",
- "source": [
- "import numpy as np\nimport matplotlib.pylab as pl\nimport ot\n\n\n\n#%% dataset generation\n\nnp.random.seed(0) # makes example reproducible\n\nn=100 # nb samples in source and target datasets\ntheta=2*np.pi/20\nnz=0.1\nxs,ys=ot.datasets.get_data_classif('gaussrot',n,nz=nz)\nxt,yt=ot.datasets.get_data_classif('gaussrot',n,theta=theta,nz=nz)\n\n# one of the target mode changes its variance (no linear mapping)\nxt[yt==2]*=3\nxt=xt+4\n\n\n#%% plot samples\n\npl.figure(1,(8,5))\npl.clf()\n\npl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')\n\npl.legend(loc=0)\npl.title('Source and target distributions')\n\n\n\n#%% OT linear mapping estimation\n\neta=1e-8 # quadratic regularization for regression\nmu=1e0 # weight of the OT linear term\nbias=True # estimate a bias\n\not_mapping=ot.da.OTDA_mapping_linear()\not_mapping.fit(xs,xt,mu=mu,eta=eta,bias=bias,numItermax = 20,verbose=True)\n\nxst=ot_mapping.predict(xs) # use the estimated mapping\nxst0=ot_mapping.interp() # use barycentric mapping\n\n\npl.figure(2,(10,7))\npl.clf()\npl.subplot(2,2,1)\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.3)\npl.scatter(xst0[:,0],xst0[:,1],c=ys,marker='+',label='barycentric mapping')\npl.title(\"barycentric mapping\")\n\npl.subplot(2,2,2)\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.3)\npl.scatter(xst[:,0],xst[:,1],c=ys,marker='+',label='Learned mapping')\npl.title(\"Learned mapping\")\n\n\n\n#%% Kernel mapping estimation\n\neta=1e-5 # quadratic regularization for regression\nmu=1e-1 # weight of the OT linear term\nbias=True # estimate a bias\nsigma=1 # sigma bandwidth fot gaussian kernel\n\n\not_mapping_kernel=ot.da.OTDA_mapping_kernel()\not_mapping_kernel.fit(xs,xt,mu=mu,eta=eta,sigma=sigma,bias=bias,numItermax = 10,verbose=True)\n\nxst_kernel=ot_mapping_kernel.predict(xs) # use the estimated mapping\nxst0_kernel=ot_mapping_kernel.interp() # use barycentric mapping\n\n\n#%% Plotting the mapped samples\n\npl.figure(2,(10,7))\npl.clf()\npl.subplot(2,2,1)\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.2)\npl.scatter(xst0[:,0],xst0[:,1],c=ys,marker='+',label='Mapped source samples')\npl.title(\"Bary. mapping (linear)\")\npl.legend(loc=0)\n\npl.subplot(2,2,2)\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.2)\npl.scatter(xst[:,0],xst[:,1],c=ys,marker='+',label='Learned mapping')\npl.title(\"Estim. mapping (linear)\")\n\npl.subplot(2,2,3)\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.2)\npl.scatter(xst0_kernel[:,0],xst0_kernel[:,1],c=ys,marker='+',label='barycentric mapping')\npl.title(\"Bary. mapping (kernel)\")\n\npl.subplot(2,2,4)\npl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.2)\npl.scatter(xst_kernel[:,0],xst_kernel[:,1],c=ys,marker='+',label='Learned mapping')\npl.title(\"Estim. mapping (kernel)\")"
- ],
- "outputs": [],
- "metadata": {
- "collapsed": false
- }
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 2",
- "name": "python2",
- "language": "python"
- },
- "language_info": {
- "mimetype": "text/x-python",
- "nbconvert_exporter": "python",
- "name": "python",
- "file_extension": ".py",
- "version": "2.7.12",
- "pygments_lexer": "ipython2",
- "codemirror_mode": {
- "version": 2,
- "name": "ipython"
- }
- }
- }
-} \ No newline at end of file
diff --git a/docs/source/auto_examples/plot_OTDA_mapping.py b/docs/source/auto_examples/plot_OTDA_mapping.py
deleted file mode 100644
index 78b57e7..0000000
--- a/docs/source/auto_examples/plot_OTDA_mapping.py
+++ /dev/null
@@ -1,110 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-===============================================
-OT mapping estimation for domain adaptation [8]
-===============================================
-
-[8] M. Perrot, N. Courty, R. Flamary, A. Habrard, "Mapping estimation for
- discrete optimal transport", Neural Information Processing Systems (NIPS), 2016.
-"""
-
-import numpy as np
-import matplotlib.pylab as pl
-import ot
-
-
-
-#%% dataset generation
-
-np.random.seed(0) # makes example reproducible
-
-n=100 # nb samples in source and target datasets
-theta=2*np.pi/20
-nz=0.1
-xs,ys=ot.datasets.get_data_classif('gaussrot',n,nz=nz)
-xt,yt=ot.datasets.get_data_classif('gaussrot',n,theta=theta,nz=nz)
-
-# one of the target mode changes its variance (no linear mapping)
-xt[yt==2]*=3
-xt=xt+4
-
-
-#%% plot samples
-
-pl.figure(1,(8,5))
-pl.clf()
-
-pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')
-
-pl.legend(loc=0)
-pl.title('Source and target distributions')
-
-
-
-#%% OT linear mapping estimation
-
-eta=1e-8 # quadratic regularization for regression
-mu=1e0 # weight of the OT linear term
-bias=True # estimate a bias
-
-ot_mapping=ot.da.OTDA_mapping_linear()
-ot_mapping.fit(xs,xt,mu=mu,eta=eta,bias=bias,numItermax = 20,verbose=True)
-
-xst=ot_mapping.predict(xs) # use the estimated mapping
-xst0=ot_mapping.interp() # use barycentric mapping
-
-
-pl.figure(2,(10,7))
-pl.clf()
-pl.subplot(2,2,1)
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.3)
-pl.scatter(xst0[:,0],xst0[:,1],c=ys,marker='+',label='barycentric mapping')
-pl.title("barycentric mapping")
-
-pl.subplot(2,2,2)
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.3)
-pl.scatter(xst[:,0],xst[:,1],c=ys,marker='+',label='Learned mapping')
-pl.title("Learned mapping")
-
-
-
-#%% Kernel mapping estimation
-
-eta=1e-5 # quadratic regularization for regression
-mu=1e-1 # weight of the OT linear term
-bias=True # estimate a bias
-sigma=1 # sigma bandwidth fot gaussian kernel
-
-
-ot_mapping_kernel=ot.da.OTDA_mapping_kernel()
-ot_mapping_kernel.fit(xs,xt,mu=mu,eta=eta,sigma=sigma,bias=bias,numItermax = 10,verbose=True)
-
-xst_kernel=ot_mapping_kernel.predict(xs) # use the estimated mapping
-xst0_kernel=ot_mapping_kernel.interp() # use barycentric mapping
-
-
-#%% Plotting the mapped samples
-
-pl.figure(2,(10,7))
-pl.clf()
-pl.subplot(2,2,1)
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.2)
-pl.scatter(xst0[:,0],xst0[:,1],c=ys,marker='+',label='Mapped source samples')
-pl.title("Bary. mapping (linear)")
-pl.legend(loc=0)
-
-pl.subplot(2,2,2)
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.2)
-pl.scatter(xst[:,0],xst[:,1],c=ys,marker='+',label='Learned mapping')
-pl.title("Estim. mapping (linear)")
-
-pl.subplot(2,2,3)
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.2)
-pl.scatter(xst0_kernel[:,0],xst0_kernel[:,1],c=ys,marker='+',label='barycentric mapping')
-pl.title("Bary. mapping (kernel)")
-
-pl.subplot(2,2,4)
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.2)
-pl.scatter(xst_kernel[:,0],xst_kernel[:,1],c=ys,marker='+',label='Learned mapping')
-pl.title("Estim. mapping (kernel)")
diff --git a/docs/source/auto_examples/plot_OTDA_mapping.rst b/docs/source/auto_examples/plot_OTDA_mapping.rst
deleted file mode 100644
index 18da90d..0000000
--- a/docs/source/auto_examples/plot_OTDA_mapping.rst
+++ /dev/null
@@ -1,186 +0,0 @@
-
-
-.. _sphx_glr_auto_examples_plot_OTDA_mapping.py:
-
-
-===============================================
-OT mapping estimation for domain adaptation [8]
-===============================================
-
-[8] M. Perrot, N. Courty, R. Flamary, A. Habrard, "Mapping estimation for
- discrete optimal transport", Neural Information Processing Systems (NIPS), 2016.
-
-
-
-
-.. rst-class:: sphx-glr-horizontal
-
-
- *
-
- .. image:: /auto_examples/images/sphx_glr_plot_OTDA_mapping_001.png
- :scale: 47
-
- *
-
- .. image:: /auto_examples/images/sphx_glr_plot_OTDA_mapping_002.png
- :scale: 47
-
-
-.. rst-class:: sphx-glr-script-out
-
- Out::
-
- It. |Loss |Delta loss
- --------------------------------
- 0|4.009366e+03|0.000000e+00
- 1|3.999933e+03|-2.352753e-03
- 2|3.999520e+03|-1.031984e-04
- 3|3.999362e+03|-3.936391e-05
- 4|3.999281e+03|-2.032868e-05
- 5|3.999238e+03|-1.083083e-05
- 6|3.999229e+03|-2.125291e-06
- It. |Loss |Delta loss
- --------------------------------
- 0|4.026841e+02|0.000000e+00
- 1|3.990791e+02|-8.952439e-03
- 2|3.987954e+02|-7.107124e-04
- 3|3.986554e+02|-3.512453e-04
- 4|3.985721e+02|-2.087997e-04
- 5|3.985141e+02|-1.456184e-04
- 6|3.984729e+02|-1.034624e-04
- 7|3.984435e+02|-7.366943e-05
- 8|3.984199e+02|-5.922497e-05
- 9|3.984016e+02|-4.593063e-05
- 10|3.983867e+02|-3.733061e-05
-
-
-
-
-|
-
-
-.. code-block:: python
-
-
- import numpy as np
- import matplotlib.pylab as pl
- import ot
-
-
-
- #%% dataset generation
-
- np.random.seed(0) # makes example reproducible
-
- n=100 # nb samples in source and target datasets
- theta=2*np.pi/20
- nz=0.1
- xs,ys=ot.datasets.get_data_classif('gaussrot',n,nz=nz)
- xt,yt=ot.datasets.get_data_classif('gaussrot',n,theta=theta,nz=nz)
-
- # one of the target mode changes its variance (no linear mapping)
- xt[yt==2]*=3
- xt=xt+4
-
-
- #%% plot samples
-
- pl.figure(1,(8,5))
- pl.clf()
-
- pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')
-
- pl.legend(loc=0)
- pl.title('Source and target distributions')
-
-
-
- #%% OT linear mapping estimation
-
- eta=1e-8 # quadratic regularization for regression
- mu=1e0 # weight of the OT linear term
- bias=True # estimate a bias
-
- ot_mapping=ot.da.OTDA_mapping_linear()
- ot_mapping.fit(xs,xt,mu=mu,eta=eta,bias=bias,numItermax = 20,verbose=True)
-
- xst=ot_mapping.predict(xs) # use the estimated mapping
- xst0=ot_mapping.interp() # use barycentric mapping
-
-
- pl.figure(2,(10,7))
- pl.clf()
- pl.subplot(2,2,1)
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.3)
- pl.scatter(xst0[:,0],xst0[:,1],c=ys,marker='+',label='barycentric mapping')
- pl.title("barycentric mapping")
-
- pl.subplot(2,2,2)
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.3)
- pl.scatter(xst[:,0],xst[:,1],c=ys,marker='+',label='Learned mapping')
- pl.title("Learned mapping")
-
-
-
- #%% Kernel mapping estimation
-
- eta=1e-5 # quadratic regularization for regression
- mu=1e-1 # weight of the OT linear term
- bias=True # estimate a bias
- sigma=1 # sigma bandwidth fot gaussian kernel
-
-
- ot_mapping_kernel=ot.da.OTDA_mapping_kernel()
- ot_mapping_kernel.fit(xs,xt,mu=mu,eta=eta,sigma=sigma,bias=bias,numItermax = 10,verbose=True)
-
- xst_kernel=ot_mapping_kernel.predict(xs) # use the estimated mapping
- xst0_kernel=ot_mapping_kernel.interp() # use barycentric mapping
-
-
- #%% Plotting the mapped samples
-
- pl.figure(2,(10,7))
- pl.clf()
- pl.subplot(2,2,1)
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.2)
- pl.scatter(xst0[:,0],xst0[:,1],c=ys,marker='+',label='Mapped source samples')
- pl.title("Bary. mapping (linear)")
- pl.legend(loc=0)
-
- pl.subplot(2,2,2)
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.2)
- pl.scatter(xst[:,0],xst[:,1],c=ys,marker='+',label='Learned mapping')
- pl.title("Estim. mapping (linear)")
-
- pl.subplot(2,2,3)
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.2)
- pl.scatter(xst0_kernel[:,0],xst0_kernel[:,1],c=ys,marker='+',label='barycentric mapping')
- pl.title("Bary. mapping (kernel)")
-
- pl.subplot(2,2,4)
- pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.2)
- pl.scatter(xst_kernel[:,0],xst_kernel[:,1],c=ys,marker='+',label='Learned mapping')
- pl.title("Estim. mapping (kernel)")
-
-**Total running time of the script:** ( 0 minutes 0.882 seconds)
-
-
-
-.. container:: sphx-glr-footer
-
-
- .. container:: sphx-glr-download
-
- :download:`Download Python source code: plot_OTDA_mapping.py <plot_OTDA_mapping.py>`
-
-
-
- .. container:: sphx-glr-download
-
- :download:`Download Jupyter notebook: plot_OTDA_mapping.ipynb <plot_OTDA_mapping.ipynb>`
-
-.. rst-class:: sphx-glr-signature
-
- `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
diff --git a/docs/source/auto_examples/plot_OTDA_mapping_color_images.ipynb b/docs/source/auto_examples/plot_OTDA_mapping_color_images.ipynb
deleted file mode 100644
index 1136cc3..0000000
--- a/docs/source/auto_examples/plot_OTDA_mapping_color_images.ipynb
+++ /dev/null
@@ -1,54 +0,0 @@
-{
- "nbformat_minor": 0,
- "nbformat": 4,
- "cells": [
- {
- "execution_count": null,
- "cell_type": "code",
- "source": [
- "%matplotlib inline"
- ],
- "outputs": [],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "source": [
- "\n====================================================================================\nOT for domain adaptation with image color adaptation [6] with mapping estimation [8]\n====================================================================================\n\n[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014). Regularized\n discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3), 1853-1882.\n[8] M. Perrot, N. Courty, R. Flamary, A. Habrard, \"Mapping estimation for\n discrete optimal transport\", Neural Information Processing Systems (NIPS), 2016.\n\n\n"
- ],
- "cell_type": "markdown",
- "metadata": {}
- },
- {
- "execution_count": null,
- "cell_type": "code",
- "source": [
- "import numpy as np\nimport scipy.ndimage as spi\nimport matplotlib.pylab as pl\nimport ot\n\n\n#%% Loading images\n\nI1=spi.imread('../data/ocean_day.jpg').astype(np.float64)/256\nI2=spi.imread('../data/ocean_sunset.jpg').astype(np.float64)/256\n\n#%% Plot images\n\npl.figure(1)\n\npl.subplot(1,2,1)\npl.imshow(I1)\npl.title('Image 1')\n\npl.subplot(1,2,2)\npl.imshow(I2)\npl.title('Image 2')\n\npl.show()\n\n#%% Image conversion and dataset generation\n\ndef im2mat(I):\n \"\"\"Converts and image to matrix (one pixel per line)\"\"\"\n return I.reshape((I.shape[0]*I.shape[1],I.shape[2]))\n\ndef mat2im(X,shape):\n \"\"\"Converts back a matrix to an image\"\"\"\n return X.reshape(shape)\n\nX1=im2mat(I1)\nX2=im2mat(I2)\n\n# training samples\nnb=1000\nidx1=np.random.randint(X1.shape[0],size=(nb,))\nidx2=np.random.randint(X2.shape[0],size=(nb,))\n\nxs=X1[idx1,:]\nxt=X2[idx2,:]\n\n#%% Plot image distributions\n\n\npl.figure(2,(10,5))\n\npl.subplot(1,2,1)\npl.scatter(xs[:,0],xs[:,2],c=xs)\npl.axis([0,1,0,1])\npl.xlabel('Red')\npl.ylabel('Blue')\npl.title('Image 1')\n\npl.subplot(1,2,2)\n#pl.imshow(I2)\npl.scatter(xt[:,0],xt[:,2],c=xt)\npl.axis([0,1,0,1])\npl.xlabel('Red')\npl.ylabel('Blue')\npl.title('Image 2')\n\npl.show()\n\n\n\n#%% domain adaptation between images\ndef minmax(I):\n return np.minimum(np.maximum(I,0),1)\n# LP problem\nda_emd=ot.da.OTDA() # init class\nda_emd.fit(xs,xt) # fit distributions\n\nX1t=da_emd.predict(X1) # out of sample\nI1t=minmax(mat2im(X1t,I1.shape))\n\n# sinkhorn regularization\nlambd=1e-1\nda_entrop=ot.da.OTDA_sinkhorn()\nda_entrop.fit(xs,xt,reg=lambd)\n\nX1te=da_entrop.predict(X1)\nI1te=minmax(mat2im(X1te,I1.shape))\n\n# linear mapping estimation\neta=1e-8 # quadratic regularization for regression\nmu=1e0 # weight of the OT linear term\nbias=True # estimate a bias\n\not_mapping=ot.da.OTDA_mapping_linear()\not_mapping.fit(xs,xt,mu=mu,eta=eta,bias=bias,numItermax = 20,verbose=True)\n\nX1tl=ot_mapping.predict(X1) # use the estimated mapping\nI1tl=minmax(mat2im(X1tl,I1.shape))\n\n# nonlinear mapping estimation\neta=1e-2 # quadratic regularization for regression\nmu=1e0 # weight of the OT linear term\nbias=False # estimate a bias\nsigma=1 # sigma bandwidth fot gaussian kernel\n\n\not_mapping_kernel=ot.da.OTDA_mapping_kernel()\not_mapping_kernel.fit(xs,xt,mu=mu,eta=eta,sigma=sigma,bias=bias,numItermax = 10,verbose=True)\n\nX1tn=ot_mapping_kernel.predict(X1) # use the estimated mapping\nI1tn=minmax(mat2im(X1tn,I1.shape))\n#%% plot images\n\n\npl.figure(2,(10,8))\n\npl.subplot(2,3,1)\n\npl.imshow(I1)\npl.title('Im. 1')\n\npl.subplot(2,3,2)\n\npl.imshow(I2)\npl.title('Im. 2')\n\n\npl.subplot(2,3,3)\npl.imshow(I1t)\npl.title('Im. 1 Interp LP')\n\npl.subplot(2,3,4)\npl.imshow(I1te)\npl.title('Im. 1 Interp Entrop')\n\n\npl.subplot(2,3,5)\npl.imshow(I1tl)\npl.title('Im. 1 Linear mapping')\n\npl.subplot(2,3,6)\npl.imshow(I1tn)\npl.title('Im. 1 nonlinear mapping')\n\npl.show()"
- ],
- "outputs": [],
- "metadata": {
- "collapsed": false
- }
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 2",
- "name": "python2",
- "language": "python"
- },
- "language_info": {
- "mimetype": "text/x-python",
- "nbconvert_exporter": "python",
- "name": "python",
- "file_extension": ".py",
- "version": "2.7.12",
- "pygments_lexer": "ipython2",
- "codemirror_mode": {
- "version": 2,
- "name": "ipython"
- }
- }
- }
-} \ No newline at end of file
diff --git a/docs/source/auto_examples/plot_OTDA_mapping_color_images.py b/docs/source/auto_examples/plot_OTDA_mapping_color_images.py
deleted file mode 100644
index f07dc6c..0000000
--- a/docs/source/auto_examples/plot_OTDA_mapping_color_images.py
+++ /dev/null
@@ -1,158 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-====================================================================================
-OT for domain adaptation with image color adaptation [6] with mapping estimation [8]
-====================================================================================
-
-[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014). Regularized
- discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3), 1853-1882.
-[8] M. Perrot, N. Courty, R. Flamary, A. Habrard, "Mapping estimation for
- discrete optimal transport", Neural Information Processing Systems (NIPS), 2016.
-
-"""
-
-import numpy as np
-import scipy.ndimage as spi
-import matplotlib.pylab as pl
-import ot
-
-
-#%% Loading images
-
-I1=spi.imread('../data/ocean_day.jpg').astype(np.float64)/256
-I2=spi.imread('../data/ocean_sunset.jpg').astype(np.float64)/256
-
-#%% Plot images
-
-pl.figure(1)
-
-pl.subplot(1,2,1)
-pl.imshow(I1)
-pl.title('Image 1')
-
-pl.subplot(1,2,2)
-pl.imshow(I2)
-pl.title('Image 2')
-
-pl.show()
-
-#%% Image conversion and dataset generation
-
-def im2mat(I):
- """Converts and image to matrix (one pixel per line)"""
- return I.reshape((I.shape[0]*I.shape[1],I.shape[2]))
-
-def mat2im(X,shape):
- """Converts back a matrix to an image"""
- return X.reshape(shape)
-
-X1=im2mat(I1)
-X2=im2mat(I2)
-
-# training samples
-nb=1000
-idx1=np.random.randint(X1.shape[0],size=(nb,))
-idx2=np.random.randint(X2.shape[0],size=(nb,))
-
-xs=X1[idx1,:]
-xt=X2[idx2,:]
-
-#%% Plot image distributions
-
-
-pl.figure(2,(10,5))
-
-pl.subplot(1,2,1)
-pl.scatter(xs[:,0],xs[:,2],c=xs)
-pl.axis([0,1,0,1])
-pl.xlabel('Red')
-pl.ylabel('Blue')
-pl.title('Image 1')
-
-pl.subplot(1,2,2)
-#pl.imshow(I2)
-pl.scatter(xt[:,0],xt[:,2],c=xt)
-pl.axis([0,1,0,1])
-pl.xlabel('Red')
-pl.ylabel('Blue')
-pl.title('Image 2')
-
-pl.show()
-
-
-
-#%% domain adaptation between images
-def minmax(I):
- return np.minimum(np.maximum(I,0),1)
-# LP problem
-da_emd=ot.da.OTDA() # init class
-da_emd.fit(xs,xt) # fit distributions
-
-X1t=da_emd.predict(X1) # out of sample
-I1t=minmax(mat2im(X1t,I1.shape))
-
-# sinkhorn regularization
-lambd=1e-1
-da_entrop=ot.da.OTDA_sinkhorn()
-da_entrop.fit(xs,xt,reg=lambd)
-
-X1te=da_entrop.predict(X1)
-I1te=minmax(mat2im(X1te,I1.shape))
-
-# linear mapping estimation
-eta=1e-8 # quadratic regularization for regression
-mu=1e0 # weight of the OT linear term
-bias=True # estimate a bias
-
-ot_mapping=ot.da.OTDA_mapping_linear()
-ot_mapping.fit(xs,xt,mu=mu,eta=eta,bias=bias,numItermax = 20,verbose=True)
-
-X1tl=ot_mapping.predict(X1) # use the estimated mapping
-I1tl=minmax(mat2im(X1tl,I1.shape))
-
-# nonlinear mapping estimation
-eta=1e-2 # quadratic regularization for regression
-mu=1e0 # weight of the OT linear term
-bias=False # estimate a bias
-sigma=1 # sigma bandwidth fot gaussian kernel
-
-
-ot_mapping_kernel=ot.da.OTDA_mapping_kernel()
-ot_mapping_kernel.fit(xs,xt,mu=mu,eta=eta,sigma=sigma,bias=bias,numItermax = 10,verbose=True)
-
-X1tn=ot_mapping_kernel.predict(X1) # use the estimated mapping
-I1tn=minmax(mat2im(X1tn,I1.shape))
-#%% plot images
-
-
-pl.figure(2,(10,8))
-
-pl.subplot(2,3,1)
-
-pl.imshow(I1)
-pl.title('Im. 1')
-
-pl.subplot(2,3,2)
-
-pl.imshow(I2)
-pl.title('Im. 2')
-
-
-pl.subplot(2,3,3)
-pl.imshow(I1t)
-pl.title('Im. 1 Interp LP')
-
-pl.subplot(2,3,4)
-pl.imshow(I1te)
-pl.title('Im. 1 Interp Entrop')
-
-
-pl.subplot(2,3,5)
-pl.imshow(I1tl)
-pl.title('Im. 1 Linear mapping')
-
-pl.subplot(2,3,6)
-pl.imshow(I1tn)
-pl.title('Im. 1 nonlinear mapping')
-
-pl.show()
diff --git a/docs/source/auto_examples/plot_OTDA_mapping_color_images.rst b/docs/source/auto_examples/plot_OTDA_mapping_color_images.rst
deleted file mode 100644
index 60be3a4..0000000
--- a/docs/source/auto_examples/plot_OTDA_mapping_color_images.rst
+++ /dev/null
@@ -1,246 +0,0 @@
-
-
-.. _sphx_glr_auto_examples_plot_OTDA_mapping_color_images.py:
-
-
-====================================================================================
-OT for domain adaptation with image color adaptation [6] with mapping estimation [8]
-====================================================================================
-
-[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014). Regularized
- discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3), 1853-1882.
-[8] M. Perrot, N. Courty, R. Flamary, A. Habrard, "Mapping estimation for
- discrete optimal transport", Neural Information Processing Systems (NIPS), 2016.
-
-
-
-
-
-.. rst-class:: sphx-glr-horizontal
-
-
- *
-
- .. image:: /auto_examples/images/sphx_glr_plot_OTDA_mapping_color_images_001.png
- :scale: 47
-
- *
-
- .. image:: /auto_examples/images/sphx_glr_plot_OTDA_mapping_color_images_002.png
- :scale: 47
-
-
-.. rst-class:: sphx-glr-script-out
-
- Out::
-
- It. |Loss |Delta loss
- --------------------------------
- 0|3.624802e+02|0.000000e+00
- 1|3.547180e+02|-2.141395e-02
- 2|3.545494e+02|-4.753955e-04
- 3|3.544646e+02|-2.391784e-04
- 4|3.544126e+02|-1.466280e-04
- 5|3.543775e+02|-9.921805e-05
- 6|3.543518e+02|-7.245828e-05
- 7|3.543323e+02|-5.491924e-05
- 8|3.543170e+02|-4.342401e-05
- 9|3.543046e+02|-3.472174e-05
- 10|3.542945e+02|-2.878681e-05
- 11|3.542859e+02|-2.417065e-05
- 12|3.542786e+02|-2.058131e-05
- 13|3.542723e+02|-1.768262e-05
- 14|3.542668e+02|-1.551616e-05
- 15|3.542620e+02|-1.371909e-05
- 16|3.542577e+02|-1.213326e-05
- 17|3.542538e+02|-1.085481e-05
- 18|3.542531e+02|-1.996006e-06
- It. |Loss |Delta loss
- --------------------------------
- 0|3.555768e+02|0.000000e+00
- 1|3.510071e+02|-1.285164e-02
- 2|3.509110e+02|-2.736701e-04
- 3|3.508748e+02|-1.031476e-04
- 4|3.508506e+02|-6.910585e-05
- 5|3.508330e+02|-5.014608e-05
- 6|3.508195e+02|-3.839166e-05
- 7|3.508090e+02|-3.004218e-05
- 8|3.508005e+02|-2.417627e-05
- 9|3.507935e+02|-2.004621e-05
- 10|3.507876e+02|-1.681731e-05
-
-
-
-
-|
-
-
-.. code-block:: python
-
-
- import numpy as np
- import scipy.ndimage as spi
- import matplotlib.pylab as pl
- import ot
-
-
- #%% Loading images
-
- I1=spi.imread('../data/ocean_day.jpg').astype(np.float64)/256
- I2=spi.imread('../data/ocean_sunset.jpg').astype(np.float64)/256
-
- #%% Plot images
-
- pl.figure(1)
-
- pl.subplot(1,2,1)
- pl.imshow(I1)
- pl.title('Image 1')
-
- pl.subplot(1,2,2)
- pl.imshow(I2)
- pl.title('Image 2')
-
- pl.show()
-
- #%% Image conversion and dataset generation
-
- def im2mat(I):
- """Converts and image to matrix (one pixel per line)"""
- return I.reshape((I.shape[0]*I.shape[1],I.shape[2]))
-
- def mat2im(X,shape):
- """Converts back a matrix to an image"""
- return X.reshape(shape)
-
- X1=im2mat(I1)
- X2=im2mat(I2)
-
- # training samples
- nb=1000
- idx1=np.random.randint(X1.shape[0],size=(nb,))
- idx2=np.random.randint(X2.shape[0],size=(nb,))
-
- xs=X1[idx1,:]
- xt=X2[idx2,:]
-
- #%% Plot image distributions
-
-
- pl.figure(2,(10,5))
-
- pl.subplot(1,2,1)
- pl.scatter(xs[:,0],xs[:,2],c=xs)
- pl.axis([0,1,0,1])
- pl.xlabel('Red')
- pl.ylabel('Blue')
- pl.title('Image 1')
-
- pl.subplot(1,2,2)
- #pl.imshow(I2)
- pl.scatter(xt[:,0],xt[:,2],c=xt)
- pl.axis([0,1,0,1])
- pl.xlabel('Red')
- pl.ylabel('Blue')
- pl.title('Image 2')
-
- pl.show()
-
-
-
- #%% domain adaptation between images
- def minmax(I):
- return np.minimum(np.maximum(I,0),1)
- # LP problem
- da_emd=ot.da.OTDA() # init class
- da_emd.fit(xs,xt) # fit distributions
-
- X1t=da_emd.predict(X1) # out of sample
- I1t=minmax(mat2im(X1t,I1.shape))
-
- # sinkhorn regularization
- lambd=1e-1
- da_entrop=ot.da.OTDA_sinkhorn()
- da_entrop.fit(xs,xt,reg=lambd)
-
- X1te=da_entrop.predict(X1)
- I1te=minmax(mat2im(X1te,I1.shape))
-
- # linear mapping estimation
- eta=1e-8 # quadratic regularization for regression
- mu=1e0 # weight of the OT linear term
- bias=True # estimate a bias
-
- ot_mapping=ot.da.OTDA_mapping_linear()
- ot_mapping.fit(xs,xt,mu=mu,eta=eta,bias=bias,numItermax = 20,verbose=True)
-
- X1tl=ot_mapping.predict(X1) # use the estimated mapping
- I1tl=minmax(mat2im(X1tl,I1.shape))
-
- # nonlinear mapping estimation
- eta=1e-2 # quadratic regularization for regression
- mu=1e0 # weight of the OT linear term
- bias=False # estimate a bias
- sigma=1 # sigma bandwidth fot gaussian kernel
-
-
- ot_mapping_kernel=ot.da.OTDA_mapping_kernel()
- ot_mapping_kernel.fit(xs,xt,mu=mu,eta=eta,sigma=sigma,bias=bias,numItermax = 10,verbose=True)
-
- X1tn=ot_mapping_kernel.predict(X1) # use the estimated mapping
- I1tn=minmax(mat2im(X1tn,I1.shape))
- #%% plot images
-
-
- pl.figure(2,(10,8))
-
- pl.subplot(2,3,1)
-
- pl.imshow(I1)
- pl.title('Im. 1')
-
- pl.subplot(2,3,2)
-
- pl.imshow(I2)
- pl.title('Im. 2')
-
-
- pl.subplot(2,3,3)
- pl.imshow(I1t)
- pl.title('Im. 1 Interp LP')
-
- pl.subplot(2,3,4)
- pl.imshow(I1te)
- pl.title('Im. 1 Interp Entrop')
-
-
- pl.subplot(2,3,5)
- pl.imshow(I1tl)
- pl.title('Im. 1 Linear mapping')
-
- pl.subplot(2,3,6)
- pl.imshow(I1tn)
- pl.title('Im. 1 nonlinear mapping')
-
- pl.show()
-
-**Total running time of the script:** ( 1 minutes 59.537 seconds)
-
-
-
-.. container:: sphx-glr-footer
-
-
- .. container:: sphx-glr-download
-
- :download:`Download Python source code: plot_OTDA_mapping_color_images.py <plot_OTDA_mapping_color_images.py>`
-
-
-
- .. container:: sphx-glr-download
-
- :download:`Download Jupyter notebook: plot_OTDA_mapping_color_images.ipynb <plot_OTDA_mapping_color_images.ipynb>`
-
-.. rst-class:: sphx-glr-signature
-
- `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
diff --git a/docs/source/auto_examples/plot_OT_1D.ipynb b/docs/source/auto_examples/plot_OT_1D.ipynb
index 8715b97..26748c2 100644
--- a/docs/source/auto_examples/plot_OT_1D.ipynb
+++ b/docs/source/auto_examples/plot_OT_1D.ipynb
@@ -15,7 +15,7 @@
},
{
"source": [
- "\n# 1D optimal transport\n\n\n@author: rflamary\n\n"
+ "\n# 1D optimal transport\n\n\nThis example illustrates the computation of EMD and Sinkhorn transport plans\nand their visualization.\n\n\n"
],
"cell_type": "markdown",
"metadata": {}
@@ -24,7 +24,79 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "import numpy as np\nimport matplotlib.pylab as pl\nimport ot\nfrom ot.datasets import get_1D_gauss as gauss\n\n\n#%% parameters\n\nn=100 # nb bins\n\n# bin positions\nx=np.arange(n,dtype=np.float64)\n\n# Gaussian distributions\na=gauss(n,m=20,s=5) # m= mean, s= std\nb=gauss(n,m=60,s=10)\n\n# loss matrix\nM=ot.dist(x.reshape((n,1)),x.reshape((n,1)))\nM/=M.max()\n\n#%% plot the distributions\n\npl.figure(1)\npl.plot(x,a,'b',label='Source distribution')\npl.plot(x,b,'r',label='Target distribution')\npl.legend()\n\n#%% plot distributions and loss matrix\n\npl.figure(2)\not.plot.plot1D_mat(a,b,M,'Cost matrix M')\n\n#%% EMD\n\nG0=ot.emd(a,b,M)\n\npl.figure(3)\not.plot.plot1D_mat(a,b,G0,'OT matrix G0')\n\n#%% Sinkhorn\n\nlambd=1e-3\nGs=ot.sinkhorn(a,b,M,lambd,verbose=True)\n\npl.figure(4)\not.plot.plot1D_mat(a,b,Gs,'OT matrix Sinkhorn')"
+ "# Author: Remi Flamary <remi.flamary@unice.fr>\n#\n# License: MIT License\n\nimport numpy as np\nimport matplotlib.pylab as pl\nimport ot\nfrom ot.datasets import get_1D_gauss as gauss"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Generate data\n-------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% parameters\n\nn = 100 # nb bins\n\n# bin positions\nx = np.arange(n, dtype=np.float64)\n\n# Gaussian distributions\na = gauss(n, m=20, s=5) # m= mean, s= std\nb = gauss(n, m=60, s=10)\n\n# loss matrix\nM = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)))\nM /= M.max()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Plot distributions and loss matrix\n----------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% plot the distributions\n\npl.figure(1, figsize=(6.4, 3))\npl.plot(x, a, 'b', label='Source distribution')\npl.plot(x, b, 'r', label='Target distribution')\npl.legend()\n\n#%% plot distributions and loss matrix\n\npl.figure(2, figsize=(5, 5))\not.plot.plot1D_mat(a, b, M, 'Cost matrix M')"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Solve EMD\n---------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% EMD\n\nG0 = ot.emd(a, b, M)\n\npl.figure(3, figsize=(5, 5))\not.plot.plot1D_mat(a, b, G0, 'OT matrix G0')"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Solve Sinkhorn\n--------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% Sinkhorn\n\nlambd = 1e-3\nGs = ot.sinkhorn(a, b, M, lambd, verbose=True)\n\npl.figure(4, figsize=(5, 5))\not.plot.plot1D_mat(a, b, Gs, 'OT matrix Sinkhorn')\n\npl.show()"
],
"outputs": [],
"metadata": {
diff --git a/docs/source/auto_examples/plot_OT_1D.py b/docs/source/auto_examples/plot_OT_1D.py
index 6661aa3..719058f 100644
--- a/docs/source/auto_examples/plot_OT_1D.py
+++ b/docs/source/auto_examples/plot_OT_1D.py
@@ -4,53 +4,80 @@
1D optimal transport
====================
-@author: rflamary
+This example illustrates the computation of EMD and Sinkhorn transport plans
+and their visualization.
+
"""
+# Author: Remi Flamary <remi.flamary@unice.fr>
+#
+# License: MIT License
+
import numpy as np
import matplotlib.pylab as pl
import ot
from ot.datasets import get_1D_gauss as gauss
+##############################################################################
+# Generate data
+# -------------
+
#%% parameters
-n=100 # nb bins
+n = 100 # nb bins
# bin positions
-x=np.arange(n,dtype=np.float64)
+x = np.arange(n, dtype=np.float64)
# Gaussian distributions
-a=gauss(n,m=20,s=5) # m= mean, s= std
-b=gauss(n,m=60,s=10)
+a = gauss(n, m=20, s=5) # m= mean, s= std
+b = gauss(n, m=60, s=10)
# loss matrix
-M=ot.dist(x.reshape((n,1)),x.reshape((n,1)))
-M/=M.max()
+M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)))
+M /= M.max()
+
+
+##############################################################################
+# Plot distributions and loss matrix
+# ----------------------------------
#%% plot the distributions
-pl.figure(1)
-pl.plot(x,a,'b',label='Source distribution')
-pl.plot(x,b,'r',label='Target distribution')
+pl.figure(1, figsize=(6.4, 3))
+pl.plot(x, a, 'b', label='Source distribution')
+pl.plot(x, b, 'r', label='Target distribution')
pl.legend()
#%% plot distributions and loss matrix
-pl.figure(2)
-ot.plot.plot1D_mat(a,b,M,'Cost matrix M')
+pl.figure(2, figsize=(5, 5))
+ot.plot.plot1D_mat(a, b, M, 'Cost matrix M')
+
+##############################################################################
+# Solve EMD
+# ---------
+
#%% EMD
-G0=ot.emd(a,b,M)
+G0 = ot.emd(a, b, M)
+
+pl.figure(3, figsize=(5, 5))
+ot.plot.plot1D_mat(a, b, G0, 'OT matrix G0')
+
+##############################################################################
+# Solve Sinkhorn
+# --------------
-pl.figure(3)
-ot.plot.plot1D_mat(a,b,G0,'OT matrix G0')
#%% Sinkhorn
-lambd=1e-3
-Gs=ot.sinkhorn(a,b,M,lambd,verbose=True)
+lambd = 1e-3
+Gs = ot.sinkhorn(a, b, M, lambd, verbose=True)
+
+pl.figure(4, figsize=(5, 5))
+ot.plot.plot1D_mat(a, b, Gs, 'OT matrix Sinkhorn')
-pl.figure(4)
-ot.plot.plot1D_mat(a,b,Gs,'OT matrix Sinkhorn')
+pl.show()
diff --git a/docs/source/auto_examples/plot_OT_1D.rst b/docs/source/auto_examples/plot_OT_1D.rst
index 44b715b..975a923 100644
--- a/docs/source/auto_examples/plot_OT_1D.rst
+++ b/docs/source/auto_examples/plot_OT_1D.rst
@@ -7,7 +7,80 @@
1D optimal transport
====================
-@author: rflamary
+This example illustrates the computation of EMD and Sinkhorn transport plans
+and their visualization.
+
+
+
+
+.. code-block:: python
+
+
+ # Author: Remi Flamary <remi.flamary@unice.fr>
+ #
+ # License: MIT License
+
+ import numpy as np
+ import matplotlib.pylab as pl
+ import ot
+ from ot.datasets import get_1D_gauss as gauss
+
+
+
+
+
+
+
+Generate data
+-------------
+
+
+
+.. code-block:: python
+
+
+
+ #%% parameters
+
+ n = 100 # nb bins
+
+ # bin positions
+ x = np.arange(n, dtype=np.float64)
+
+ # Gaussian distributions
+ a = gauss(n, m=20, s=5) # m= mean, s= std
+ b = gauss(n, m=60, s=10)
+
+ # loss matrix
+ M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)))
+ M /= M.max()
+
+
+
+
+
+
+
+
+Plot distributions and loss matrix
+----------------------------------
+
+
+
+.. code-block:: python
+
+
+ #%% plot the distributions
+
+ pl.figure(1, figsize=(6.4, 3))
+ pl.plot(x, a, 'b', label='Source distribution')
+ pl.plot(x, b, 'r', label='Target distribution')
+ pl.legend()
+
+ #%% plot distributions and loss matrix
+
+ pl.figure(2, figsize=(5, 5))
+ ot.plot.plot1D_mat(a, b, M, 'Cost matrix M')
@@ -25,94 +98,80 @@
.. image:: /auto_examples/images/sphx_glr_plot_OT_1D_002.png
:scale: 47
- *
- .. image:: /auto_examples/images/sphx_glr_plot_OT_1D_003.png
- :scale: 47
- *
- .. image:: /auto_examples/images/sphx_glr_plot_OT_1D_004.png
- :scale: 47
+Solve EMD
+---------
-.. rst-class:: sphx-glr-script-out
- Out::
+.. code-block:: python
- It. |Err
- -------------------
- 0|8.187970e-02|
- 10|3.460174e-02|
- 20|6.633335e-03|
- 30|9.797798e-04|
- 40|1.389606e-04|
- 50|1.959016e-05|
- 60|2.759079e-06|
- 70|3.885166e-07|
- 80|5.470605e-08|
- 90|7.702918e-09|
- 100|1.084609e-09|
- 110|1.527180e-10|
+ #%% EMD
+ G0 = ot.emd(a, b, M)
-|
+ pl.figure(3, figsize=(5, 5))
+ ot.plot.plot1D_mat(a, b, G0, 'OT matrix G0')
-.. code-block:: python
- import numpy as np
- import matplotlib.pylab as pl
- import ot
- from ot.datasets import get_1D_gauss as gauss
+.. image:: /auto_examples/images/sphx_glr_plot_OT_1D_005.png
+ :align: center
- #%% parameters
- n=100 # nb bins
- # bin positions
- x=np.arange(n,dtype=np.float64)
+Solve Sinkhorn
+--------------
- # Gaussian distributions
- a=gauss(n,m=20,s=5) # m= mean, s= std
- b=gauss(n,m=60,s=10)
- # loss matrix
- M=ot.dist(x.reshape((n,1)),x.reshape((n,1)))
- M/=M.max()
- #%% plot the distributions
+.. code-block:: python
- pl.figure(1)
- pl.plot(x,a,'b',label='Source distribution')
- pl.plot(x,b,'r',label='Target distribution')
- pl.legend()
- #%% plot distributions and loss matrix
- pl.figure(2)
- ot.plot.plot1D_mat(a,b,M,'Cost matrix M')
+ #%% Sinkhorn
- #%% EMD
+ lambd = 1e-3
+ Gs = ot.sinkhorn(a, b, M, lambd, verbose=True)
- G0=ot.emd(a,b,M)
+ pl.figure(4, figsize=(5, 5))
+ ot.plot.plot1D_mat(a, b, Gs, 'OT matrix Sinkhorn')
- pl.figure(3)
- ot.plot.plot1D_mat(a,b,G0,'OT matrix G0')
+ pl.show()
- #%% Sinkhorn
- lambd=1e-3
- Gs=ot.sinkhorn(a,b,M,lambd,verbose=True)
- pl.figure(4)
- ot.plot.plot1D_mat(a,b,Gs,'OT matrix Sinkhorn')
+.. image:: /auto_examples/images/sphx_glr_plot_OT_1D_007.png
+ :align: center
+
+
+.. rst-class:: sphx-glr-script-out
+
+ Out::
+
+ It. |Err
+ -------------------
+ 0|8.187970e-02|
+ 10|3.460174e-02|
+ 20|6.633335e-03|
+ 30|9.797798e-04|
+ 40|1.389606e-04|
+ 50|1.959016e-05|
+ 60|2.759079e-06|
+ 70|3.885166e-07|
+ 80|5.470605e-08|
+ 90|7.702918e-09|
+ 100|1.084609e-09|
+ 110|1.527180e-10|
+
-**Total running time of the script:** ( 0 minutes 0.674 seconds)
+**Total running time of the script:** ( 0 minutes 1.198 seconds)
diff --git a/docs/source/auto_examples/plot_OT_2D_samples.ipynb b/docs/source/auto_examples/plot_OT_2D_samples.ipynb
index fad0467..41a37f3 100644
--- a/docs/source/auto_examples/plot_OT_2D_samples.ipynb
+++ b/docs/source/auto_examples/plot_OT_2D_samples.ipynb
@@ -15,7 +15,7 @@
},
{
"source": [
- "\n# 2D Optimal transport between empirical distributions\n\n\n@author: rflamary\n\n"
+ "\n# 2D Optimal transport between empirical distributions\n\n\nIllustration of 2D optimal transport between discributions that are weighted\nsum of diracs. The OT matrix is plotted with the samples.\n\n\n"
],
"cell_type": "markdown",
"metadata": {}
@@ -24,7 +24,79 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "import numpy as np\nimport matplotlib.pylab as pl\nimport ot\n\n#%% parameters and data generation\n\nn=50 # nb samples\n\nmu_s=np.array([0,0])\ncov_s=np.array([[1,0],[0,1]])\n\nmu_t=np.array([4,4])\ncov_t=np.array([[1,-.8],[-.8,1]])\n\nxs=ot.datasets.get_2D_samples_gauss(n,mu_s,cov_s)\nxt=ot.datasets.get_2D_samples_gauss(n,mu_t,cov_t)\n\na,b = ot.unif(n),ot.unif(n) # uniform distribution on samples\n\n# loss matrix\nM=ot.dist(xs,xt)\nM/=M.max()\n\n#%% plot samples\n\npl.figure(1)\npl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\npl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\npl.legend(loc=0)\npl.title('Source and traget distributions')\n\npl.figure(2)\npl.imshow(M,interpolation='nearest')\npl.title('Cost matrix M')\n\n\n#%% EMD\n\nG0=ot.emd(a,b,M)\n\npl.figure(3)\npl.imshow(G0,interpolation='nearest')\npl.title('OT matrix G0')\n\npl.figure(4)\not.plot.plot2D_samples_mat(xs,xt,G0,c=[.5,.5,1])\npl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\npl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\npl.legend(loc=0)\npl.title('OT matrix with samples')\n\n\n#%% sinkhorn\n\n# reg term\nlambd=5e-4\n\nGs=ot.sinkhorn(a,b,M,lambd)\n\npl.figure(5)\npl.imshow(Gs,interpolation='nearest')\npl.title('OT matrix sinkhorn')\n\npl.figure(6)\not.plot.plot2D_samples_mat(xs,xt,Gs,color=[.5,.5,1])\npl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\npl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\npl.legend(loc=0)\npl.title('OT matrix Sinkhorn with samples')"
+ "# Author: Remi Flamary <remi.flamary@unice.fr>\n#\n# License: MIT License\n\nimport numpy as np\nimport matplotlib.pylab as pl\nimport ot"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Generate data\n-------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% parameters and data generation\n\nn = 50 # nb samples\n\nmu_s = np.array([0, 0])\ncov_s = np.array([[1, 0], [0, 1]])\n\nmu_t = np.array([4, 4])\ncov_t = np.array([[1, -.8], [-.8, 1]])\n\nxs = ot.datasets.get_2D_samples_gauss(n, mu_s, cov_s)\nxt = ot.datasets.get_2D_samples_gauss(n, mu_t, cov_t)\n\na, b = np.ones((n,)) / n, np.ones((n,)) / n # uniform distribution on samples\n\n# loss matrix\nM = ot.dist(xs, xt)\nM /= M.max()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Plot data\n---------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% plot samples\n\npl.figure(1)\npl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\npl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\npl.legend(loc=0)\npl.title('Source and target distributions')\n\npl.figure(2)\npl.imshow(M, interpolation='nearest')\npl.title('Cost matrix M')"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Compute EMD\n-----------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% EMD\n\nG0 = ot.emd(a, b, M)\n\npl.figure(3)\npl.imshow(G0, interpolation='nearest')\npl.title('OT matrix G0')\n\npl.figure(4)\not.plot.plot2D_samples_mat(xs, xt, G0, c=[.5, .5, 1])\npl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\npl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\npl.legend(loc=0)\npl.title('OT matrix with samples')"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Compute Sinkhorn\n----------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% sinkhorn\n\n# reg term\nlambd = 1e-3\n\nGs = ot.sinkhorn(a, b, M, lambd)\n\npl.figure(5)\npl.imshow(Gs, interpolation='nearest')\npl.title('OT matrix sinkhorn')\n\npl.figure(6)\not.plot.plot2D_samples_mat(xs, xt, Gs, color=[.5, .5, 1])\npl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\npl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\npl.legend(loc=0)\npl.title('OT matrix Sinkhorn with samples')\n\npl.show()"
],
"outputs": [],
"metadata": {
diff --git a/docs/source/auto_examples/plot_OT_2D_samples.py b/docs/source/auto_examples/plot_OT_2D_samples.py
index edfb781..9818ec5 100644
--- a/docs/source/auto_examples/plot_OT_2D_samples.py
+++ b/docs/source/auto_examples/plot_OT_2D_samples.py
@@ -4,75 +4,98 @@
2D Optimal transport between empirical distributions
====================================================
-@author: rflamary
+Illustration of 2D optimal transport between discributions that are weighted
+sum of diracs. The OT matrix is plotted with the samples.
+
"""
+# Author: Remi Flamary <remi.flamary@unice.fr>
+#
+# License: MIT License
+
import numpy as np
import matplotlib.pylab as pl
import ot
+##############################################################################
+# Generate data
+# -------------
+
#%% parameters and data generation
-n=50 # nb samples
+n = 50 # nb samples
-mu_s=np.array([0,0])
-cov_s=np.array([[1,0],[0,1]])
+mu_s = np.array([0, 0])
+cov_s = np.array([[1, 0], [0, 1]])
-mu_t=np.array([4,4])
-cov_t=np.array([[1,-.8],[-.8,1]])
+mu_t = np.array([4, 4])
+cov_t = np.array([[1, -.8], [-.8, 1]])
-xs=ot.datasets.get_2D_samples_gauss(n,mu_s,cov_s)
-xt=ot.datasets.get_2D_samples_gauss(n,mu_t,cov_t)
+xs = ot.datasets.get_2D_samples_gauss(n, mu_s, cov_s)
+xt = ot.datasets.get_2D_samples_gauss(n, mu_t, cov_t)
-a,b = ot.unif(n),ot.unif(n) # uniform distribution on samples
+a, b = np.ones((n,)) / n, np.ones((n,)) / n # uniform distribution on samples
# loss matrix
-M=ot.dist(xs,xt)
-M/=M.max()
+M = ot.dist(xs, xt)
+M /= M.max()
+
+##############################################################################
+# Plot data
+# ---------
#%% plot samples
pl.figure(1)
-pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
-pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
pl.legend(loc=0)
-pl.title('Source and traget distributions')
+pl.title('Source and target distributions')
pl.figure(2)
-pl.imshow(M,interpolation='nearest')
+pl.imshow(M, interpolation='nearest')
pl.title('Cost matrix M')
+##############################################################################
+# Compute EMD
+# -----------
#%% EMD
-G0=ot.emd(a,b,M)
+G0 = ot.emd(a, b, M)
pl.figure(3)
-pl.imshow(G0,interpolation='nearest')
+pl.imshow(G0, interpolation='nearest')
pl.title('OT matrix G0')
pl.figure(4)
-ot.plot.plot2D_samples_mat(xs,xt,G0,c=[.5,.5,1])
-pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
-pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
+ot.plot.plot2D_samples_mat(xs, xt, G0, c=[.5, .5, 1])
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
pl.legend(loc=0)
pl.title('OT matrix with samples')
+##############################################################################
+# Compute Sinkhorn
+# ----------------
+
#%% sinkhorn
# reg term
-lambd=5e-4
+lambd = 1e-3
-Gs=ot.sinkhorn(a,b,M,lambd)
+Gs = ot.sinkhorn(a, b, M, lambd)
pl.figure(5)
-pl.imshow(Gs,interpolation='nearest')
+pl.imshow(Gs, interpolation='nearest')
pl.title('OT matrix sinkhorn')
pl.figure(6)
-ot.plot.plot2D_samples_mat(xs,xt,Gs,color=[.5,.5,1])
-pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
-pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
+ot.plot.plot2D_samples_mat(xs, xt, Gs, color=[.5, .5, 1])
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
pl.legend(loc=0)
pl.title('OT matrix Sinkhorn with samples')
+
+pl.show()
diff --git a/docs/source/auto_examples/plot_OT_2D_samples.rst b/docs/source/auto_examples/plot_OT_2D_samples.rst
index e05e591..5565c54 100644
--- a/docs/source/auto_examples/plot_OT_2D_samples.rst
+++ b/docs/source/auto_examples/plot_OT_2D_samples.rst
@@ -7,131 +7,191 @@
2D Optimal transport between empirical distributions
====================================================
-@author: rflamary
+Illustration of 2D optimal transport between discributions that are weighted
+sum of diracs. The OT matrix is plotted with the samples.
-.. rst-class:: sphx-glr-horizontal
+.. code-block:: python
- *
+ # Author: Remi Flamary <remi.flamary@unice.fr>
+ #
+ # License: MIT License
- .. image:: /auto_examples/images/sphx_glr_plot_OT_2D_samples_001.png
- :scale: 47
+ import numpy as np
+ import matplotlib.pylab as pl
+ import ot
- *
- .. image:: /auto_examples/images/sphx_glr_plot_OT_2D_samples_002.png
- :scale: 47
- *
- .. image:: /auto_examples/images/sphx_glr_plot_OT_2D_samples_003.png
- :scale: 47
- *
- .. image:: /auto_examples/images/sphx_glr_plot_OT_2D_samples_004.png
- :scale: 47
- *
+Generate data
+-------------
- .. image:: /auto_examples/images/sphx_glr_plot_OT_2D_samples_005.png
- :scale: 47
- *
- .. image:: /auto_examples/images/sphx_glr_plot_OT_2D_samples_006.png
- :scale: 47
+.. code-block:: python
-.. rst-class:: sphx-glr-script-out
+ #%% parameters and data generation
- Out::
+ n = 50 # nb samples
- ('Warning: numerical errors at iteration', 0)
+ mu_s = np.array([0, 0])
+ cov_s = np.array([[1, 0], [0, 1]])
+ mu_t = np.array([4, 4])
+ cov_t = np.array([[1, -.8], [-.8, 1]])
+ xs = ot.datasets.get_2D_samples_gauss(n, mu_s, cov_s)
+ xt = ot.datasets.get_2D_samples_gauss(n, mu_t, cov_t)
+ a, b = np.ones((n,)) / n, np.ones((n,)) / n # uniform distribution on samples
-|
+ # loss matrix
+ M = ot.dist(xs, xt)
+ M /= M.max()
-.. code-block:: python
- import numpy as np
- import matplotlib.pylab as pl
- import ot
- #%% parameters and data generation
- n=50 # nb samples
- mu_s=np.array([0,0])
- cov_s=np.array([[1,0],[0,1]])
+Plot data
+---------
- mu_t=np.array([4,4])
- cov_t=np.array([[1,-.8],[-.8,1]])
- xs=ot.datasets.get_2D_samples_gauss(n,mu_s,cov_s)
- xt=ot.datasets.get_2D_samples_gauss(n,mu_t,cov_t)
- a,b = ot.unif(n),ot.unif(n) # uniform distribution on samples
+.. code-block:: python
- # loss matrix
- M=ot.dist(xs,xt)
- M/=M.max()
#%% plot samples
pl.figure(1)
- pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
- pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
+ pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+ pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
pl.legend(loc=0)
- pl.title('Source and traget distributions')
+ pl.title('Source and target distributions')
pl.figure(2)
- pl.imshow(M,interpolation='nearest')
+ pl.imshow(M, interpolation='nearest')
pl.title('Cost matrix M')
+
+
+.. rst-class:: sphx-glr-horizontal
+
+
+ *
+
+ .. image:: /auto_examples/images/sphx_glr_plot_OT_2D_samples_001.png
+ :scale: 47
+
+ *
+
+ .. image:: /auto_examples/images/sphx_glr_plot_OT_2D_samples_002.png
+ :scale: 47
+
+
+
+
+Compute EMD
+-----------
+
+
+
+.. code-block:: python
+
+
#%% EMD
- G0=ot.emd(a,b,M)
+ G0 = ot.emd(a, b, M)
pl.figure(3)
- pl.imshow(G0,interpolation='nearest')
+ pl.imshow(G0, interpolation='nearest')
pl.title('OT matrix G0')
pl.figure(4)
- ot.plot.plot2D_samples_mat(xs,xt,G0,c=[.5,.5,1])
- pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
- pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
+ ot.plot.plot2D_samples_mat(xs, xt, G0, c=[.5, .5, 1])
+ pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+ pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
pl.legend(loc=0)
pl.title('OT matrix with samples')
+
+
+
+.. rst-class:: sphx-glr-horizontal
+
+
+ *
+
+ .. image:: /auto_examples/images/sphx_glr_plot_OT_2D_samples_005.png
+ :scale: 47
+
+ *
+
+ .. image:: /auto_examples/images/sphx_glr_plot_OT_2D_samples_006.png
+ :scale: 47
+
+
+
+
+Compute Sinkhorn
+----------------
+
+
+
+.. code-block:: python
+
+
#%% sinkhorn
# reg term
- lambd=5e-4
+ lambd = 1e-3
- Gs=ot.sinkhorn(a,b,M,lambd)
+ Gs = ot.sinkhorn(a, b, M, lambd)
pl.figure(5)
- pl.imshow(Gs,interpolation='nearest')
+ pl.imshow(Gs, interpolation='nearest')
pl.title('OT matrix sinkhorn')
pl.figure(6)
- ot.plot.plot2D_samples_mat(xs,xt,Gs,color=[.5,.5,1])
- pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
- pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
+ ot.plot.plot2D_samples_mat(xs, xt, Gs, color=[.5, .5, 1])
+ pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+ pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
pl.legend(loc=0)
pl.title('OT matrix Sinkhorn with samples')
-**Total running time of the script:** ( 0 minutes 0.623 seconds)
+ pl.show()
+
+
+
+.. rst-class:: sphx-glr-horizontal
+
+
+ *
+
+ .. image:: /auto_examples/images/sphx_glr_plot_OT_2D_samples_009.png
+ :scale: 47
+
+ *
+
+ .. image:: /auto_examples/images/sphx_glr_plot_OT_2D_samples_010.png
+ :scale: 47
+
+
+
+
+**Total running time of the script:** ( 0 minutes 3.380 seconds)
diff --git a/docs/source/auto_examples/plot_OT_L1_vs_L2.ipynb b/docs/source/auto_examples/plot_OT_L1_vs_L2.ipynb
index 46283ac..2b9a364 100644
--- a/docs/source/auto_examples/plot_OT_L1_vs_L2.ipynb
+++ b/docs/source/auto_examples/plot_OT_L1_vs_L2.ipynb
@@ -15,7 +15,7 @@
},
{
"source": [
- "\n# 2D Optimal transport for different metrics\n\n\nStole the figure idea from Fig. 1 and 2 in \nhttps://arxiv.org/pdf/1706.07650.pdf\n\n\n@author: rflamary\n\n"
+ "\n# 2D Optimal transport for different metrics\n\n\n2D OT on empirical distributio with different gound metric.\n\nStole the figure idea from Fig. 1 and 2 in\nhttps://arxiv.org/pdf/1706.07650.pdf\n\n\n\n"
],
"cell_type": "markdown",
"metadata": {}
@@ -24,7 +24,79 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "import numpy as np\nimport matplotlib.pylab as pl\nimport ot\n\n#%% parameters and data generation\n\nfor data in range(2):\n\n if data:\n n=20 # nb samples\n xs=np.zeros((n,2))\n xs[:,0]=np.arange(n)+1\n xs[:,1]=(np.arange(n)+1)*-0.001 # to make it strictly convex...\n \n xt=np.zeros((n,2))\n xt[:,1]=np.arange(n)+1\n else:\n \n n=50 # nb samples\n xtot=np.zeros((n+1,2))\n xtot[:,0]=np.cos((np.arange(n+1)+1.0)*0.9/(n+2)*2*np.pi)\n xtot[:,1]=np.sin((np.arange(n+1)+1.0)*0.9/(n+2)*2*np.pi)\n \n xs=xtot[:n,:]\n xt=xtot[1:,:]\n \n \n \n a,b = ot.unif(n),ot.unif(n) # uniform distribution on samples\n \n # loss matrix\n M1=ot.dist(xs,xt,metric='euclidean')\n M1/=M1.max()\n \n # loss matrix\n M2=ot.dist(xs,xt,metric='sqeuclidean')\n M2/=M2.max()\n \n # loss matrix\n Mp=np.sqrt(ot.dist(xs,xt,metric='euclidean'))\n Mp/=Mp.max()\n \n #%% plot samples\n \n pl.figure(1+3*data)\n pl.clf()\n pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n pl.axis('equal')\n pl.title('Source and traget distributions')\n \n pl.figure(2+3*data,(15,5))\n pl.subplot(1,3,1)\n pl.imshow(M1,interpolation='nearest')\n pl.title('Eucidean cost')\n pl.subplot(1,3,2)\n pl.imshow(M2,interpolation='nearest')\n pl.title('Squared Euclidean cost')\n \n pl.subplot(1,3,3)\n pl.imshow(Mp,interpolation='nearest')\n pl.title('Sqrt Euclidean cost')\n #%% EMD\n \n G1=ot.emd(a,b,M1)\n G2=ot.emd(a,b,M2)\n Gp=ot.emd(a,b,Mp)\n \n pl.figure(3+3*data,(15,5))\n \n pl.subplot(1,3,1)\n ot.plot.plot2D_samples_mat(xs,xt,G1,c=[.5,.5,1])\n pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n pl.axis('equal')\n #pl.legend(loc=0)\n pl.title('OT Euclidean')\n \n pl.subplot(1,3,2)\n \n ot.plot.plot2D_samples_mat(xs,xt,G2,c=[.5,.5,1])\n pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n pl.axis('equal')\n #pl.legend(loc=0)\n pl.title('OT squared Euclidean')\n \n pl.subplot(1,3,3)\n \n ot.plot.plot2D_samples_mat(xs,xt,Gp,c=[.5,.5,1])\n pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n pl.axis('equal')\n #pl.legend(loc=0)\n pl.title('OT sqrt Euclidean')"
+ "# Author: Remi Flamary <remi.flamary@unice.fr>\n#\n# License: MIT License\n\nimport numpy as np\nimport matplotlib.pylab as pl\nimport ot"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Dataset 1 : uniform sampling\n----------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "n = 20 # nb samples\nxs = np.zeros((n, 2))\nxs[:, 0] = np.arange(n) + 1\nxs[:, 1] = (np.arange(n) + 1) * -0.001 # to make it strictly convex...\n\nxt = np.zeros((n, 2))\nxt[:, 1] = np.arange(n) + 1\n\na, b = ot.unif(n), ot.unif(n) # uniform distribution on samples\n\n# loss matrix\nM1 = ot.dist(xs, xt, metric='euclidean')\nM1 /= M1.max()\n\n# loss matrix\nM2 = ot.dist(xs, xt, metric='sqeuclidean')\nM2 /= M2.max()\n\n# loss matrix\nMp = np.sqrt(ot.dist(xs, xt, metric='euclidean'))\nMp /= Mp.max()\n\n# Data\npl.figure(1, figsize=(7, 3))\npl.clf()\npl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\npl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\npl.axis('equal')\npl.title('Source and traget distributions')\n\n\n# Cost matrices\npl.figure(2, figsize=(7, 3))\n\npl.subplot(1, 3, 1)\npl.imshow(M1, interpolation='nearest')\npl.title('Euclidean cost')\n\npl.subplot(1, 3, 2)\npl.imshow(M2, interpolation='nearest')\npl.title('Squared Euclidean cost')\n\npl.subplot(1, 3, 3)\npl.imshow(Mp, interpolation='nearest')\npl.title('Sqrt Euclidean cost')\npl.tight_layout()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Dataset 1 : Plot OT Matrices\n----------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% EMD\nG1 = ot.emd(a, b, M1)\nG2 = ot.emd(a, b, M2)\nGp = ot.emd(a, b, Mp)\n\n# OT matrices\npl.figure(3, figsize=(7, 3))\n\npl.subplot(1, 3, 1)\not.plot.plot2D_samples_mat(xs, xt, G1, c=[.5, .5, 1])\npl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\npl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\npl.axis('equal')\n# pl.legend(loc=0)\npl.title('OT Euclidean')\n\npl.subplot(1, 3, 2)\not.plot.plot2D_samples_mat(xs, xt, G2, c=[.5, .5, 1])\npl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\npl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\npl.axis('equal')\n# pl.legend(loc=0)\npl.title('OT squared Euclidean')\n\npl.subplot(1, 3, 3)\not.plot.plot2D_samples_mat(xs, xt, Gp, c=[.5, .5, 1])\npl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\npl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\npl.axis('equal')\n# pl.legend(loc=0)\npl.title('OT sqrt Euclidean')\npl.tight_layout()\n\npl.show()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Dataset 2 : Partial circle\n--------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "n = 50 # nb samples\nxtot = np.zeros((n + 1, 2))\nxtot[:, 0] = np.cos(\n (np.arange(n + 1) + 1.0) * 0.9 / (n + 2) * 2 * np.pi)\nxtot[:, 1] = np.sin(\n (np.arange(n + 1) + 1.0) * 0.9 / (n + 2) * 2 * np.pi)\n\nxs = xtot[:n, :]\nxt = xtot[1:, :]\n\na, b = ot.unif(n), ot.unif(n) # uniform distribution on samples\n\n# loss matrix\nM1 = ot.dist(xs, xt, metric='euclidean')\nM1 /= M1.max()\n\n# loss matrix\nM2 = ot.dist(xs, xt, metric='sqeuclidean')\nM2 /= M2.max()\n\n# loss matrix\nMp = np.sqrt(ot.dist(xs, xt, metric='euclidean'))\nMp /= Mp.max()\n\n\n# Data\npl.figure(4, figsize=(7, 3))\npl.clf()\npl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\npl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\npl.axis('equal')\npl.title('Source and traget distributions')\n\n\n# Cost matrices\npl.figure(5, figsize=(7, 3))\n\npl.subplot(1, 3, 1)\npl.imshow(M1, interpolation='nearest')\npl.title('Euclidean cost')\n\npl.subplot(1, 3, 2)\npl.imshow(M2, interpolation='nearest')\npl.title('Squared Euclidean cost')\n\npl.subplot(1, 3, 3)\npl.imshow(Mp, interpolation='nearest')\npl.title('Sqrt Euclidean cost')\npl.tight_layout()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Dataset 2 : Plot OT Matrices\n-----------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% EMD\nG1 = ot.emd(a, b, M1)\nG2 = ot.emd(a, b, M2)\nGp = ot.emd(a, b, Mp)\n\n# OT matrices\npl.figure(6, figsize=(7, 3))\n\npl.subplot(1, 3, 1)\not.plot.plot2D_samples_mat(xs, xt, G1, c=[.5, .5, 1])\npl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\npl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\npl.axis('equal')\n# pl.legend(loc=0)\npl.title('OT Euclidean')\n\npl.subplot(1, 3, 2)\not.plot.plot2D_samples_mat(xs, xt, G2, c=[.5, .5, 1])\npl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\npl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\npl.axis('equal')\n# pl.legend(loc=0)\npl.title('OT squared Euclidean')\n\npl.subplot(1, 3, 3)\not.plot.plot2D_samples_mat(xs, xt, Gp, c=[.5, .5, 1])\npl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\npl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\npl.axis('equal')\n# pl.legend(loc=0)\npl.title('OT sqrt Euclidean')\npl.tight_layout()\n\npl.show()"
],
"outputs": [],
"metadata": {
diff --git a/docs/source/auto_examples/plot_OT_L1_vs_L2.py b/docs/source/auto_examples/plot_OT_L1_vs_L2.py
index 9bb92fe..090e809 100644
--- a/docs/source/auto_examples/plot_OT_L1_vs_L2.py
+++ b/docs/source/auto_examples/plot_OT_L1_vs_L2.py
@@ -4,105 +4,204 @@
2D Optimal transport for different metrics
==========================================
-Stole the figure idea from Fig. 1 and 2 in
+2D OT on empirical distributio with different gound metric.
+
+Stole the figure idea from Fig. 1 and 2 in
https://arxiv.org/pdf/1706.07650.pdf
-@author: rflamary
"""
+# Author: Remi Flamary <remi.flamary@unice.fr>
+#
+# License: MIT License
+
import numpy as np
import matplotlib.pylab as pl
import ot
-#%% parameters and data generation
-
-for data in range(2):
-
- if data:
- n=20 # nb samples
- xs=np.zeros((n,2))
- xs[:,0]=np.arange(n)+1
- xs[:,1]=(np.arange(n)+1)*-0.001 # to make it strictly convex...
-
- xt=np.zeros((n,2))
- xt[:,1]=np.arange(n)+1
- else:
-
- n=50 # nb samples
- xtot=np.zeros((n+1,2))
- xtot[:,0]=np.cos((np.arange(n+1)+1.0)*0.9/(n+2)*2*np.pi)
- xtot[:,1]=np.sin((np.arange(n+1)+1.0)*0.9/(n+2)*2*np.pi)
-
- xs=xtot[:n,:]
- xt=xtot[1:,:]
-
-
-
- a,b = ot.unif(n),ot.unif(n) # uniform distribution on samples
-
- # loss matrix
- M1=ot.dist(xs,xt,metric='euclidean')
- M1/=M1.max()
-
- # loss matrix
- M2=ot.dist(xs,xt,metric='sqeuclidean')
- M2/=M2.max()
-
- # loss matrix
- Mp=np.sqrt(ot.dist(xs,xt,metric='euclidean'))
- Mp/=Mp.max()
-
- #%% plot samples
-
- pl.figure(1+3*data)
- pl.clf()
- pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
- pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
- pl.axis('equal')
- pl.title('Source and traget distributions')
-
- pl.figure(2+3*data,(15,5))
- pl.subplot(1,3,1)
- pl.imshow(M1,interpolation='nearest')
- pl.title('Eucidean cost')
- pl.subplot(1,3,2)
- pl.imshow(M2,interpolation='nearest')
- pl.title('Squared Euclidean cost')
-
- pl.subplot(1,3,3)
- pl.imshow(Mp,interpolation='nearest')
- pl.title('Sqrt Euclidean cost')
- #%% EMD
-
- G1=ot.emd(a,b,M1)
- G2=ot.emd(a,b,M2)
- Gp=ot.emd(a,b,Mp)
-
- pl.figure(3+3*data,(15,5))
-
- pl.subplot(1,3,1)
- ot.plot.plot2D_samples_mat(xs,xt,G1,c=[.5,.5,1])
- pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
- pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
- pl.axis('equal')
- #pl.legend(loc=0)
- pl.title('OT Euclidean')
-
- pl.subplot(1,3,2)
-
- ot.plot.plot2D_samples_mat(xs,xt,G2,c=[.5,.5,1])
- pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
- pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
- pl.axis('equal')
- #pl.legend(loc=0)
- pl.title('OT squared Euclidean')
-
- pl.subplot(1,3,3)
-
- ot.plot.plot2D_samples_mat(xs,xt,Gp,c=[.5,.5,1])
- pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
- pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
- pl.axis('equal')
- #pl.legend(loc=0)
- pl.title('OT sqrt Euclidean')
+##############################################################################
+# Dataset 1 : uniform sampling
+# ----------------------------
+
+n = 20 # nb samples
+xs = np.zeros((n, 2))
+xs[:, 0] = np.arange(n) + 1
+xs[:, 1] = (np.arange(n) + 1) * -0.001 # to make it strictly convex...
+
+xt = np.zeros((n, 2))
+xt[:, 1] = np.arange(n) + 1
+
+a, b = ot.unif(n), ot.unif(n) # uniform distribution on samples
+
+# loss matrix
+M1 = ot.dist(xs, xt, metric='euclidean')
+M1 /= M1.max()
+
+# loss matrix
+M2 = ot.dist(xs, xt, metric='sqeuclidean')
+M2 /= M2.max()
+
+# loss matrix
+Mp = np.sqrt(ot.dist(xs, xt, metric='euclidean'))
+Mp /= Mp.max()
+
+# Data
+pl.figure(1, figsize=(7, 3))
+pl.clf()
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+pl.axis('equal')
+pl.title('Source and traget distributions')
+
+
+# Cost matrices
+pl.figure(2, figsize=(7, 3))
+
+pl.subplot(1, 3, 1)
+pl.imshow(M1, interpolation='nearest')
+pl.title('Euclidean cost')
+
+pl.subplot(1, 3, 2)
+pl.imshow(M2, interpolation='nearest')
+pl.title('Squared Euclidean cost')
+
+pl.subplot(1, 3, 3)
+pl.imshow(Mp, interpolation='nearest')
+pl.title('Sqrt Euclidean cost')
+pl.tight_layout()
+
+##############################################################################
+# Dataset 1 : Plot OT Matrices
+# ----------------------------
+
+
+#%% EMD
+G1 = ot.emd(a, b, M1)
+G2 = ot.emd(a, b, M2)
+Gp = ot.emd(a, b, Mp)
+
+# OT matrices
+pl.figure(3, figsize=(7, 3))
+
+pl.subplot(1, 3, 1)
+ot.plot.plot2D_samples_mat(xs, xt, G1, c=[.5, .5, 1])
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+pl.axis('equal')
+# pl.legend(loc=0)
+pl.title('OT Euclidean')
+
+pl.subplot(1, 3, 2)
+ot.plot.plot2D_samples_mat(xs, xt, G2, c=[.5, .5, 1])
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+pl.axis('equal')
+# pl.legend(loc=0)
+pl.title('OT squared Euclidean')
+
+pl.subplot(1, 3, 3)
+ot.plot.plot2D_samples_mat(xs, xt, Gp, c=[.5, .5, 1])
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+pl.axis('equal')
+# pl.legend(loc=0)
+pl.title('OT sqrt Euclidean')
+pl.tight_layout()
+
+pl.show()
+
+
+##############################################################################
+# Dataset 2 : Partial circle
+# --------------------------
+
+n = 50 # nb samples
+xtot = np.zeros((n + 1, 2))
+xtot[:, 0] = np.cos(
+ (np.arange(n + 1) + 1.0) * 0.9 / (n + 2) * 2 * np.pi)
+xtot[:, 1] = np.sin(
+ (np.arange(n + 1) + 1.0) * 0.9 / (n + 2) * 2 * np.pi)
+
+xs = xtot[:n, :]
+xt = xtot[1:, :]
+
+a, b = ot.unif(n), ot.unif(n) # uniform distribution on samples
+
+# loss matrix
+M1 = ot.dist(xs, xt, metric='euclidean')
+M1 /= M1.max()
+
+# loss matrix
+M2 = ot.dist(xs, xt, metric='sqeuclidean')
+M2 /= M2.max()
+
+# loss matrix
+Mp = np.sqrt(ot.dist(xs, xt, metric='euclidean'))
+Mp /= Mp.max()
+
+
+# Data
+pl.figure(4, figsize=(7, 3))
+pl.clf()
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+pl.axis('equal')
+pl.title('Source and traget distributions')
+
+
+# Cost matrices
+pl.figure(5, figsize=(7, 3))
+
+pl.subplot(1, 3, 1)
+pl.imshow(M1, interpolation='nearest')
+pl.title('Euclidean cost')
+
+pl.subplot(1, 3, 2)
+pl.imshow(M2, interpolation='nearest')
+pl.title('Squared Euclidean cost')
+
+pl.subplot(1, 3, 3)
+pl.imshow(Mp, interpolation='nearest')
+pl.title('Sqrt Euclidean cost')
+pl.tight_layout()
+
+##############################################################################
+# Dataset 2 : Plot OT Matrices
+# -----------------------------
+
+
+#%% EMD
+G1 = ot.emd(a, b, M1)
+G2 = ot.emd(a, b, M2)
+Gp = ot.emd(a, b, Mp)
+
+# OT matrices
+pl.figure(6, figsize=(7, 3))
+
+pl.subplot(1, 3, 1)
+ot.plot.plot2D_samples_mat(xs, xt, G1, c=[.5, .5, 1])
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+pl.axis('equal')
+# pl.legend(loc=0)
+pl.title('OT Euclidean')
+
+pl.subplot(1, 3, 2)
+ot.plot.plot2D_samples_mat(xs, xt, G2, c=[.5, .5, 1])
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+pl.axis('equal')
+# pl.legend(loc=0)
+pl.title('OT squared Euclidean')
+
+pl.subplot(1, 3, 3)
+ot.plot.plot2D_samples_mat(xs, xt, Gp, c=[.5, .5, 1])
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+pl.axis('equal')
+# pl.legend(loc=0)
+pl.title('OT sqrt Euclidean')
+pl.tight_layout()
+
+pl.show()
diff --git a/docs/source/auto_examples/plot_OT_L1_vs_L2.rst b/docs/source/auto_examples/plot_OT_L1_vs_L2.rst
index 4e94bef..a569b50 100644
--- a/docs/source/auto_examples/plot_OT_L1_vs_L2.rst
+++ b/docs/source/auto_examples/plot_OT_L1_vs_L2.rst
@@ -7,11 +7,86 @@
2D Optimal transport for different metrics
==========================================
-Stole the figure idea from Fig. 1 and 2 in
+2D OT on empirical distributio with different gound metric.
+
+Stole the figure idea from Fig. 1 and 2 in
https://arxiv.org/pdf/1706.07650.pdf
-@author: rflamary
+
+
+
+.. code-block:: python
+
+
+ # Author: Remi Flamary <remi.flamary@unice.fr>
+ #
+ # License: MIT License
+
+ import numpy as np
+ import matplotlib.pylab as pl
+ import ot
+
+
+
+
+
+
+
+Dataset 1 : uniform sampling
+----------------------------
+
+
+
+.. code-block:: python
+
+
+ n = 20 # nb samples
+ xs = np.zeros((n, 2))
+ xs[:, 0] = np.arange(n) + 1
+ xs[:, 1] = (np.arange(n) + 1) * -0.001 # to make it strictly convex...
+
+ xt = np.zeros((n, 2))
+ xt[:, 1] = np.arange(n) + 1
+
+ a, b = ot.unif(n), ot.unif(n) # uniform distribution on samples
+
+ # loss matrix
+ M1 = ot.dist(xs, xt, metric='euclidean')
+ M1 /= M1.max()
+
+ # loss matrix
+ M2 = ot.dist(xs, xt, metric='sqeuclidean')
+ M2 /= M2.max()
+
+ # loss matrix
+ Mp = np.sqrt(ot.dist(xs, xt, metric='euclidean'))
+ Mp /= Mp.max()
+
+ # Data
+ pl.figure(1, figsize=(7, 3))
+ pl.clf()
+ pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+ pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+ pl.axis('equal')
+ pl.title('Source and traget distributions')
+
+
+ # Cost matrices
+ pl.figure(2, figsize=(7, 3))
+
+ pl.subplot(1, 3, 1)
+ pl.imshow(M1, interpolation='nearest')
+ pl.title('Euclidean cost')
+
+ pl.subplot(1, 3, 2)
+ pl.imshow(M2, interpolation='nearest')
+ pl.title('Squared Euclidean cost')
+
+ pl.subplot(1, 3, 3)
+ pl.imshow(Mp, interpolation='nearest')
+ pl.title('Sqrt Euclidean cost')
+ pl.tight_layout()
@@ -29,130 +104,193 @@ https://arxiv.org/pdf/1706.07650.pdf
.. image:: /auto_examples/images/sphx_glr_plot_OT_L1_vs_L2_002.png
:scale: 47
- *
- .. image:: /auto_examples/images/sphx_glr_plot_OT_L1_vs_L2_003.png
- :scale: 47
- *
- .. image:: /auto_examples/images/sphx_glr_plot_OT_L1_vs_L2_004.png
- :scale: 47
+Dataset 1 : Plot OT Matrices
+----------------------------
+
+
+
+.. code-block:: python
+
+
+
+ #%% EMD
+ G1 = ot.emd(a, b, M1)
+ G2 = ot.emd(a, b, M2)
+ Gp = ot.emd(a, b, Mp)
+
+ # OT matrices
+ pl.figure(3, figsize=(7, 3))
+
+ pl.subplot(1, 3, 1)
+ ot.plot.plot2D_samples_mat(xs, xt, G1, c=[.5, .5, 1])
+ pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+ pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+ pl.axis('equal')
+ # pl.legend(loc=0)
+ pl.title('OT Euclidean')
+
+ pl.subplot(1, 3, 2)
+ ot.plot.plot2D_samples_mat(xs, xt, G2, c=[.5, .5, 1])
+ pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+ pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+ pl.axis('equal')
+ # pl.legend(loc=0)
+ pl.title('OT squared Euclidean')
+
+ pl.subplot(1, 3, 3)
+ ot.plot.plot2D_samples_mat(xs, xt, Gp, c=[.5, .5, 1])
+ pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+ pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+ pl.axis('equal')
+ # pl.legend(loc=0)
+ pl.title('OT sqrt Euclidean')
+ pl.tight_layout()
+
+ pl.show()
+
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_OT_L1_vs_L2_005.png
+ :align: center
+
+
+
+
+Dataset 2 : Partial circle
+--------------------------
+
+
+
+.. code-block:: python
+
+
+ n = 50 # nb samples
+ xtot = np.zeros((n + 1, 2))
+ xtot[:, 0] = np.cos(
+ (np.arange(n + 1) + 1.0) * 0.9 / (n + 2) * 2 * np.pi)
+ xtot[:, 1] = np.sin(
+ (np.arange(n + 1) + 1.0) * 0.9 / (n + 2) * 2 * np.pi)
+
+ xs = xtot[:n, :]
+ xt = xtot[1:, :]
+
+ a, b = ot.unif(n), ot.unif(n) # uniform distribution on samples
+
+ # loss matrix
+ M1 = ot.dist(xs, xt, metric='euclidean')
+ M1 /= M1.max()
+
+ # loss matrix
+ M2 = ot.dist(xs, xt, metric='sqeuclidean')
+ M2 /= M2.max()
+
+ # loss matrix
+ Mp = np.sqrt(ot.dist(xs, xt, metric='euclidean'))
+ Mp /= Mp.max()
+
+
+ # Data
+ pl.figure(4, figsize=(7, 3))
+ pl.clf()
+ pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+ pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+ pl.axis('equal')
+ pl.title('Source and traget distributions')
+
+
+ # Cost matrices
+ pl.figure(5, figsize=(7, 3))
+
+ pl.subplot(1, 3, 1)
+ pl.imshow(M1, interpolation='nearest')
+ pl.title('Euclidean cost')
+
+ pl.subplot(1, 3, 2)
+ pl.imshow(M2, interpolation='nearest')
+ pl.title('Squared Euclidean cost')
+
+ pl.subplot(1, 3, 3)
+ pl.imshow(Mp, interpolation='nearest')
+ pl.title('Sqrt Euclidean cost')
+ pl.tight_layout()
+
+
+
+
+.. rst-class:: sphx-glr-horizontal
+
*
- .. image:: /auto_examples/images/sphx_glr_plot_OT_L1_vs_L2_005.png
+ .. image:: /auto_examples/images/sphx_glr_plot_OT_L1_vs_L2_007.png
:scale: 47
*
- .. image:: /auto_examples/images/sphx_glr_plot_OT_L1_vs_L2_006.png
+ .. image:: /auto_examples/images/sphx_glr_plot_OT_L1_vs_L2_008.png
:scale: 47
+Dataset 2 : Plot OT Matrices
+-----------------------------
+
+
.. code-block:: python
- import numpy as np
- import matplotlib.pylab as pl
- import ot
- #%% parameters and data generation
-
- for data in range(2):
-
- if data:
- n=20 # nb samples
- xs=np.zeros((n,2))
- xs[:,0]=np.arange(n)+1
- xs[:,1]=(np.arange(n)+1)*-0.001 # to make it strictly convex...
-
- xt=np.zeros((n,2))
- xt[:,1]=np.arange(n)+1
- else:
-
- n=50 # nb samples
- xtot=np.zeros((n+1,2))
- xtot[:,0]=np.cos((np.arange(n+1)+1.0)*0.9/(n+2)*2*np.pi)
- xtot[:,1]=np.sin((np.arange(n+1)+1.0)*0.9/(n+2)*2*np.pi)
-
- xs=xtot[:n,:]
- xt=xtot[1:,:]
-
-
-
- a,b = ot.unif(n),ot.unif(n) # uniform distribution on samples
-
- # loss matrix
- M1=ot.dist(xs,xt,metric='euclidean')
- M1/=M1.max()
-
- # loss matrix
- M2=ot.dist(xs,xt,metric='sqeuclidean')
- M2/=M2.max()
-
- # loss matrix
- Mp=np.sqrt(ot.dist(xs,xt,metric='euclidean'))
- Mp/=Mp.max()
-
- #%% plot samples
-
- pl.figure(1+3*data)
- pl.clf()
- pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
- pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
- pl.axis('equal')
- pl.title('Source and traget distributions')
-
- pl.figure(2+3*data,(15,5))
- pl.subplot(1,3,1)
- pl.imshow(M1,interpolation='nearest')
- pl.title('Eucidean cost')
- pl.subplot(1,3,2)
- pl.imshow(M2,interpolation='nearest')
- pl.title('Squared Euclidean cost')
-
- pl.subplot(1,3,3)
- pl.imshow(Mp,interpolation='nearest')
- pl.title('Sqrt Euclidean cost')
- #%% EMD
-
- G1=ot.emd(a,b,M1)
- G2=ot.emd(a,b,M2)
- Gp=ot.emd(a,b,Mp)
-
- pl.figure(3+3*data,(15,5))
-
- pl.subplot(1,3,1)
- ot.plot.plot2D_samples_mat(xs,xt,G1,c=[.5,.5,1])
- pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
- pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
- pl.axis('equal')
- #pl.legend(loc=0)
- pl.title('OT Euclidean')
-
- pl.subplot(1,3,2)
-
- ot.plot.plot2D_samples_mat(xs,xt,G2,c=[.5,.5,1])
- pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
- pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
- pl.axis('equal')
- #pl.legend(loc=0)
- pl.title('OT squared Euclidean')
-
- pl.subplot(1,3,3)
-
- ot.plot.plot2D_samples_mat(xs,xt,Gp,c=[.5,.5,1])
- pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
- pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
- pl.axis('equal')
- #pl.legend(loc=0)
- pl.title('OT sqrt Euclidean')
-
-**Total running time of the script:** ( 0 minutes 1.417 seconds)
+ #%% EMD
+ G1 = ot.emd(a, b, M1)
+ G2 = ot.emd(a, b, M2)
+ Gp = ot.emd(a, b, Mp)
+
+ # OT matrices
+ pl.figure(6, figsize=(7, 3))
+
+ pl.subplot(1, 3, 1)
+ ot.plot.plot2D_samples_mat(xs, xt, G1, c=[.5, .5, 1])
+ pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+ pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+ pl.axis('equal')
+ # pl.legend(loc=0)
+ pl.title('OT Euclidean')
+
+ pl.subplot(1, 3, 2)
+ ot.plot.plot2D_samples_mat(xs, xt, G2, c=[.5, .5, 1])
+ pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+ pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+ pl.axis('equal')
+ # pl.legend(loc=0)
+ pl.title('OT squared Euclidean')
+
+ pl.subplot(1, 3, 3)
+ ot.plot.plot2D_samples_mat(xs, xt, Gp, c=[.5, .5, 1])
+ pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+ pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+ pl.axis('equal')
+ # pl.legend(loc=0)
+ pl.title('OT sqrt Euclidean')
+ pl.tight_layout()
+
+ pl.show()
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_OT_L1_vs_L2_011.png
+ :align: center
+
+
+
+
+**Total running time of the script:** ( 0 minutes 1.976 seconds)
diff --git a/docs/source/auto_examples/plot_OT_conv.ipynb b/docs/source/auto_examples/plot_OT_conv.ipynb
deleted file mode 100644
index 7fc4af0..0000000
--- a/docs/source/auto_examples/plot_OT_conv.ipynb
+++ /dev/null
@@ -1,54 +0,0 @@
-{
- "nbformat_minor": 0,
- "nbformat": 4,
- "cells": [
- {
- "execution_count": null,
- "cell_type": "code",
- "source": [
- "%matplotlib inline"
- ],
- "outputs": [],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "source": [
- "\n# 1D Wasserstein barycenter demo\n\n\n\n@author: rflamary\n\n"
- ],
- "cell_type": "markdown",
- "metadata": {}
- },
- {
- "execution_count": null,
- "cell_type": "code",
- "source": [
- "import numpy as np\nimport matplotlib.pylab as pl\nimport ot\nfrom mpl_toolkits.mplot3d import Axes3D #necessary for 3d plot even if not used\nimport scipy as sp\nimport scipy.signal as sps\n#%% parameters\n\nn=10 # nb bins\n\n# bin positions\nx=np.arange(n,dtype=np.float64)\n\nxx,yy=np.meshgrid(x,x)\n\n\nxpos=np.hstack((xx.reshape(-1,1),yy.reshape(-1,1)))\n\nM=ot.dist(xpos)\n\n\nI0=((xx-5)**2+(yy-5)**2<3**2)*1.0\nI1=((xx-7)**2+(yy-7)**2<3**2)*1.0\n\nI0/=I0.sum()\nI1/=I1.sum()\n\ni0=I0.ravel()\ni1=I1.ravel()\n\nM=M[i0>0,:][:,i1>0].copy()\ni0=i0[i0>0]\ni1=i1[i1>0]\nItot=np.concatenate((I0[:,:,np.newaxis],I1[:,:,np.newaxis]),2)\n\n\n#%% plot the distributions\n\npl.figure(1)\npl.subplot(2,2,1)\npl.imshow(I0)\npl.subplot(2,2,2)\npl.imshow(I1)\n\n\n#%% barycenter computation\n\nalpha=0.5 # 0<=alpha<=1\nweights=np.array([1-alpha,alpha])\n\n\ndef conv2(I,k):\n return sp.ndimage.convolve1d(sp.ndimage.convolve1d(I,k,axis=1),k,axis=0)\n\ndef conv2n(I,k):\n res=np.zeros_like(I)\n for i in range(I.shape[2]):\n res[:,:,i]=conv2(I[:,:,i],k)\n return res\n\n\ndef get_1Dkernel(reg,thr=1e-16,wmax=1024):\n w=max(min(wmax,2*int((-np.log(thr)*reg)**(.5))),3)\n x=np.arange(w,dtype=np.float64)\n return np.exp(-((x-w/2)**2)/reg)\n \nthr=1e-16\nreg=1e0\n\nk=get_1Dkernel(reg)\npl.figure(2)\npl.plot(k)\n\nI05=conv2(I0,k)\n\npl.figure(1)\npl.subplot(2,2,1)\npl.imshow(I0)\npl.subplot(2,2,2)\npl.imshow(I05)\n\n#%%\n\nG=ot.emd(i0,i1,M)\nr0=np.sum(M*G)\n\nreg=1e-1\nGs=ot.bregman.sinkhorn_knopp(i0,i1,M,reg=reg)\nrs=np.sum(M*Gs)\n\n#%%\n\ndef mylog(u):\n tmp=np.log(u)\n tmp[np.isnan(tmp)]=0\n return tmp\n\ndef sinkhorn_conv(a,b, reg, numItermax = 1000, stopThr=1e-9, verbose=False, log=False,**kwargs):\n\n\n a=np.asarray(a,dtype=np.float64)\n b=np.asarray(b,dtype=np.float64)\n \n \n if len(b.shape)>2:\n nbb=b.shape[2]\n a=a[:,:,np.newaxis]\n else:\n nbb=0\n \n\n if log:\n log={'err':[]}\n\n # we assume that no distances are null except those of the diagonal of distances\n if nbb:\n u = np.ones((a.shape[0],a.shape[1],nbb))/(np.prod(a.shape[:2]))\n v = np.ones((a.shape[0],a.shape[1],nbb))/(np.prod(b.shape[:2]))\n a0=1.0/(np.prod(b.shape[:2]))\n else:\n u = np.ones((a.shape[0],a.shape[1]))/(np.prod(a.shape[:2]))\n v = np.ones((a.shape[0],a.shape[1]))/(np.prod(b.shape[:2]))\n a0=1.0/(np.prod(b.shape[:2]))\n \n \n k=get_1Dkernel(reg)\n \n if nbb:\n K=lambda I: conv2n(I,k)\n else:\n K=lambda I: conv2(I,k)\n\n cpt = 0\n err=1\n while (err>stopThr and cpt<numItermax):\n uprev = u\n vprev = v\n \n v = np.divide(b, K(u))\n u = np.divide(a, K(v))\n\n if (np.any(np.isnan(u)) or np.any(np.isnan(v)) \n or np.any(np.isinf(u)) or np.any(np.isinf(v))):\n # we have reached the machine precision\n # come back to previous solution and quit loop\n print('Warning: numerical errors at iteration', cpt)\n u = uprev\n v = vprev\n break\n if cpt%10==0:\n # we can speed up the process by checking for the error only all the 10th iterations\n\n err = np.sum((u-uprev)**2)/np.sum((u)**2)+np.sum((v-vprev)**2)/np.sum((v)**2)\n\n if log:\n log['err'].append(err)\n\n if verbose:\n if cpt%200 ==0:\n print('{:5s}|{:12s}'.format('It.','Err')+'\\n'+'-'*19)\n print('{:5d}|{:8e}|'.format(cpt,err))\n cpt = cpt +1\n if log:\n log['u']=u\n log['v']=v\n \n if nbb: #return only loss \n res=np.zeros((nbb))\n for i in range(nbb):\n res[i]=np.sum(u[:,i].reshape((-1,1))*K*v[:,i].reshape((1,-1))*M)\n if log:\n return res,log\n else:\n return res \n \n else: # return OT matrix\n res=reg*a0*np.sum(a*mylog(u+(u==0))+b*mylog(v+(v==0)))\n if log:\n \n return res,log\n else:\n return res\n\nreg=1e0\nr,log=sinkhorn_conv(I0,I1,reg,verbose=True,log=True)\na=I0\nb=I1\nu=log['u']\nv=log['v']\n#%% barycenter interpolation"
- ],
- "outputs": [],
- "metadata": {
- "collapsed": false
- }
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 2",
- "name": "python2",
- "language": "python"
- },
- "language_info": {
- "mimetype": "text/x-python",
- "nbconvert_exporter": "python",
- "name": "python",
- "file_extension": ".py",
- "version": "2.7.12",
- "pygments_lexer": "ipython2",
- "codemirror_mode": {
- "version": 2,
- "name": "ipython"
- }
- }
- }
-} \ No newline at end of file
diff --git a/docs/source/auto_examples/plot_OT_conv.py b/docs/source/auto_examples/plot_OT_conv.py
deleted file mode 100644
index a86e7a2..0000000
--- a/docs/source/auto_examples/plot_OT_conv.py
+++ /dev/null
@@ -1,200 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-==============================
-1D Wasserstein barycenter demo
-==============================
-
-
-@author: rflamary
-"""
-
-import numpy as np
-import matplotlib.pylab as pl
-import ot
-from mpl_toolkits.mplot3d import Axes3D #necessary for 3d plot even if not used
-import scipy as sp
-import scipy.signal as sps
-#%% parameters
-
-n=10 # nb bins
-
-# bin positions
-x=np.arange(n,dtype=np.float64)
-
-xx,yy=np.meshgrid(x,x)
-
-
-xpos=np.hstack((xx.reshape(-1,1),yy.reshape(-1,1)))
-
-M=ot.dist(xpos)
-
-
-I0=((xx-5)**2+(yy-5)**2<3**2)*1.0
-I1=((xx-7)**2+(yy-7)**2<3**2)*1.0
-
-I0/=I0.sum()
-I1/=I1.sum()
-
-i0=I0.ravel()
-i1=I1.ravel()
-
-M=M[i0>0,:][:,i1>0].copy()
-i0=i0[i0>0]
-i1=i1[i1>0]
-Itot=np.concatenate((I0[:,:,np.newaxis],I1[:,:,np.newaxis]),2)
-
-
-#%% plot the distributions
-
-pl.figure(1)
-pl.subplot(2,2,1)
-pl.imshow(I0)
-pl.subplot(2,2,2)
-pl.imshow(I1)
-
-
-#%% barycenter computation
-
-alpha=0.5 # 0<=alpha<=1
-weights=np.array([1-alpha,alpha])
-
-
-def conv2(I,k):
- return sp.ndimage.convolve1d(sp.ndimage.convolve1d(I,k,axis=1),k,axis=0)
-
-def conv2n(I,k):
- res=np.zeros_like(I)
- for i in range(I.shape[2]):
- res[:,:,i]=conv2(I[:,:,i],k)
- return res
-
-
-def get_1Dkernel(reg,thr=1e-16,wmax=1024):
- w=max(min(wmax,2*int((-np.log(thr)*reg)**(.5))),3)
- x=np.arange(w,dtype=np.float64)
- return np.exp(-((x-w/2)**2)/reg)
-
-thr=1e-16
-reg=1e0
-
-k=get_1Dkernel(reg)
-pl.figure(2)
-pl.plot(k)
-
-I05=conv2(I0,k)
-
-pl.figure(1)
-pl.subplot(2,2,1)
-pl.imshow(I0)
-pl.subplot(2,2,2)
-pl.imshow(I05)
-
-#%%
-
-G=ot.emd(i0,i1,M)
-r0=np.sum(M*G)
-
-reg=1e-1
-Gs=ot.bregman.sinkhorn_knopp(i0,i1,M,reg=reg)
-rs=np.sum(M*Gs)
-
-#%%
-
-def mylog(u):
- tmp=np.log(u)
- tmp[np.isnan(tmp)]=0
- return tmp
-
-def sinkhorn_conv(a,b, reg, numItermax = 1000, stopThr=1e-9, verbose=False, log=False,**kwargs):
-
-
- a=np.asarray(a,dtype=np.float64)
- b=np.asarray(b,dtype=np.float64)
-
-
- if len(b.shape)>2:
- nbb=b.shape[2]
- a=a[:,:,np.newaxis]
- else:
- nbb=0
-
-
- if log:
- log={'err':[]}
-
- # we assume that no distances are null except those of the diagonal of distances
- if nbb:
- u = np.ones((a.shape[0],a.shape[1],nbb))/(np.prod(a.shape[:2]))
- v = np.ones((a.shape[0],a.shape[1],nbb))/(np.prod(b.shape[:2]))
- a0=1.0/(np.prod(b.shape[:2]))
- else:
- u = np.ones((a.shape[0],a.shape[1]))/(np.prod(a.shape[:2]))
- v = np.ones((a.shape[0],a.shape[1]))/(np.prod(b.shape[:2]))
- a0=1.0/(np.prod(b.shape[:2]))
-
-
- k=get_1Dkernel(reg)
-
- if nbb:
- K=lambda I: conv2n(I,k)
- else:
- K=lambda I: conv2(I,k)
-
- cpt = 0
- err=1
- while (err>stopThr and cpt<numItermax):
- uprev = u
- vprev = v
-
- v = np.divide(b, K(u))
- u = np.divide(a, K(v))
-
- if (np.any(np.isnan(u)) or np.any(np.isnan(v))
- or np.any(np.isinf(u)) or np.any(np.isinf(v))):
- # we have reached the machine precision
- # come back to previous solution and quit loop
- print('Warning: numerical errors at iteration', cpt)
- u = uprev
- v = vprev
- break
- if cpt%10==0:
- # we can speed up the process by checking for the error only all the 10th iterations
-
- err = np.sum((u-uprev)**2)/np.sum((u)**2)+np.sum((v-vprev)**2)/np.sum((v)**2)
-
- if log:
- log['err'].append(err)
-
- if verbose:
- if cpt%200 ==0:
- print('{:5s}|{:12s}'.format('It.','Err')+'\n'+'-'*19)
- print('{:5d}|{:8e}|'.format(cpt,err))
- cpt = cpt +1
- if log:
- log['u']=u
- log['v']=v
-
- if nbb: #return only loss
- res=np.zeros((nbb))
- for i in range(nbb):
- res[i]=np.sum(u[:,i].reshape((-1,1))*K*v[:,i].reshape((1,-1))*M)
- if log:
- return res,log
- else:
- return res
-
- else: # return OT matrix
- res=reg*a0*np.sum(a*mylog(u+(u==0))+b*mylog(v+(v==0)))
- if log:
-
- return res,log
- else:
- return res
-
-reg=1e0
-r,log=sinkhorn_conv(I0,I1,reg,verbose=True,log=True)
-a=I0
-b=I1
-u=log['u']
-v=log['v']
-#%% barycenter interpolation
diff --git a/docs/source/auto_examples/plot_OT_conv.rst b/docs/source/auto_examples/plot_OT_conv.rst
deleted file mode 100644
index 039bbdb..0000000
--- a/docs/source/auto_examples/plot_OT_conv.rst
+++ /dev/null
@@ -1,241 +0,0 @@
-
-
-.. _sphx_glr_auto_examples_plot_OT_conv.py:
-
-
-==============================
-1D Wasserstein barycenter demo
-==============================
-
-
-@author: rflamary
-
-
-
-
-.. code-block:: pytb
-
- Traceback (most recent call last):
- File "/home/rflamary/.local/lib/python2.7/site-packages/sphinx_gallery/gen_rst.py", line 518, in execute_code_block
- exec(code_block, example_globals)
- File "<string>", line 86, in <module>
- TypeError: unsupported operand type(s) for *: 'float' and 'Mock'
-
-
-
-
-
-.. code-block:: python
-
-
- import numpy as np
- import matplotlib.pylab as pl
- import ot
- from mpl_toolkits.mplot3d import Axes3D #necessary for 3d plot even if not used
- import scipy as sp
- import scipy.signal as sps
- #%% parameters
-
- n=10 # nb bins
-
- # bin positions
- x=np.arange(n,dtype=np.float64)
-
- xx,yy=np.meshgrid(x,x)
-
-
- xpos=np.hstack((xx.reshape(-1,1),yy.reshape(-1,1)))
-
- M=ot.dist(xpos)
-
-
- I0=((xx-5)**2+(yy-5)**2<3**2)*1.0
- I1=((xx-7)**2+(yy-7)**2<3**2)*1.0
-
- I0/=I0.sum()
- I1/=I1.sum()
-
- i0=I0.ravel()
- i1=I1.ravel()
-
- M=M[i0>0,:][:,i1>0].copy()
- i0=i0[i0>0]
- i1=i1[i1>0]
- Itot=np.concatenate((I0[:,:,np.newaxis],I1[:,:,np.newaxis]),2)
-
-
- #%% plot the distributions
-
- pl.figure(1)
- pl.subplot(2,2,1)
- pl.imshow(I0)
- pl.subplot(2,2,2)
- pl.imshow(I1)
-
-
- #%% barycenter computation
-
- alpha=0.5 # 0<=alpha<=1
- weights=np.array([1-alpha,alpha])
-
-
- def conv2(I,k):
- return sp.ndimage.convolve1d(sp.ndimage.convolve1d(I,k,axis=1),k,axis=0)
-
- def conv2n(I,k):
- res=np.zeros_like(I)
- for i in range(I.shape[2]):
- res[:,:,i]=conv2(I[:,:,i],k)
- return res
-
-
- def get_1Dkernel(reg,thr=1e-16,wmax=1024):
- w=max(min(wmax,2*int((-np.log(thr)*reg)**(.5))),3)
- x=np.arange(w,dtype=np.float64)
- return np.exp(-((x-w/2)**2)/reg)
-
- thr=1e-16
- reg=1e0
-
- k=get_1Dkernel(reg)
- pl.figure(2)
- pl.plot(k)
-
- I05=conv2(I0,k)
-
- pl.figure(1)
- pl.subplot(2,2,1)
- pl.imshow(I0)
- pl.subplot(2,2,2)
- pl.imshow(I05)
-
- #%%
-
- G=ot.emd(i0,i1,M)
- r0=np.sum(M*G)
-
- reg=1e-1
- Gs=ot.bregman.sinkhorn_knopp(i0,i1,M,reg=reg)
- rs=np.sum(M*Gs)
-
- #%%
-
- def mylog(u):
- tmp=np.log(u)
- tmp[np.isnan(tmp)]=0
- return tmp
-
- def sinkhorn_conv(a,b, reg, numItermax = 1000, stopThr=1e-9, verbose=False, log=False,**kwargs):
-
-
- a=np.asarray(a,dtype=np.float64)
- b=np.asarray(b,dtype=np.float64)
-
-
- if len(b.shape)>2:
- nbb=b.shape[2]
- a=a[:,:,np.newaxis]
- else:
- nbb=0
-
-
- if log:
- log={'err':[]}
-
- # we assume that no distances are null except those of the diagonal of distances
- if nbb:
- u = np.ones((a.shape[0],a.shape[1],nbb))/(np.prod(a.shape[:2]))
- v = np.ones((a.shape[0],a.shape[1],nbb))/(np.prod(b.shape[:2]))
- a0=1.0/(np.prod(b.shape[:2]))
- else:
- u = np.ones((a.shape[0],a.shape[1]))/(np.prod(a.shape[:2]))
- v = np.ones((a.shape[0],a.shape[1]))/(np.prod(b.shape[:2]))
- a0=1.0/(np.prod(b.shape[:2]))
-
-
- k=get_1Dkernel(reg)
-
- if nbb:
- K=lambda I: conv2n(I,k)
- else:
- K=lambda I: conv2(I,k)
-
- cpt = 0
- err=1
- while (err>stopThr and cpt<numItermax):
- uprev = u
- vprev = v
-
- v = np.divide(b, K(u))
- u = np.divide(a, K(v))
-
- if (np.any(np.isnan(u)) or np.any(np.isnan(v))
- or np.any(np.isinf(u)) or np.any(np.isinf(v))):
- # we have reached the machine precision
- # come back to previous solution and quit loop
- print('Warning: numerical errors at iteration', cpt)
- u = uprev
- v = vprev
- break
- if cpt%10==0:
- # we can speed up the process by checking for the error only all the 10th iterations
-
- err = np.sum((u-uprev)**2)/np.sum((u)**2)+np.sum((v-vprev)**2)/np.sum((v)**2)
-
- if log:
- log['err'].append(err)
-
- if verbose:
- if cpt%200 ==0:
- print('{:5s}|{:12s}'.format('It.','Err')+'\n'+'-'*19)
- print('{:5d}|{:8e}|'.format(cpt,err))
- cpt = cpt +1
- if log:
- log['u']=u
- log['v']=v
-
- if nbb: #return only loss
- res=np.zeros((nbb))
- for i in range(nbb):
- res[i]=np.sum(u[:,i].reshape((-1,1))*K*v[:,i].reshape((1,-1))*M)
- if log:
- return res,log
- else:
- return res
-
- else: # return OT matrix
- res=reg*a0*np.sum(a*mylog(u+(u==0))+b*mylog(v+(v==0)))
- if log:
-
- return res,log
- else:
- return res
-
- reg=1e0
- r,log=sinkhorn_conv(I0,I1,reg,verbose=True,log=True)
- a=I0
- b=I1
- u=log['u']
- v=log['v']
- #%% barycenter interpolation
-
-**Total running time of the script:** ( 0 minutes 0.000 seconds)
-
-
-
-.. container:: sphx-glr-footer
-
-
- .. container:: sphx-glr-download
-
- :download:`Download Python source code: plot_OT_conv.py <plot_OT_conv.py>`
-
-
-
- .. container:: sphx-glr-download
-
- :download:`Download Jupyter notebook: plot_OT_conv.ipynb <plot_OT_conv.ipynb>`
-
-.. rst-class:: sphx-glr-signature
-
- `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
diff --git a/docs/source/auto_examples/plot_WDA.ipynb b/docs/source/auto_examples/plot_WDA.ipynb
index 408a605..1661c53 100644
--- a/docs/source/auto_examples/plot_WDA.ipynb
+++ b/docs/source/auto_examples/plot_WDA.ipynb
@@ -15,7 +15,7 @@
},
{
"source": [
- "\n# Wasserstein Discriminant Analysis\n\n\n@author: rflamary\n\n"
+ "\n# Wasserstein Discriminant Analysis\n\n\nThis example illustrate the use of WDA as proposed in [11].\n\n\n[11] Flamary, R., Cuturi, M., Courty, N., & Rakotomamonjy, A. (2016).\nWasserstein Discriminant Analysis.\n\n\n"
],
"cell_type": "markdown",
"metadata": {}
@@ -24,7 +24,97 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "import numpy as np\nimport matplotlib.pylab as pl\nimport ot\nfrom ot.datasets import get_1D_gauss as gauss\nfrom ot.dr import wda\n\n\n#%% parameters\n\nn=1000 # nb samples in source and target datasets\nnz=0.2\nxs,ys=ot.datasets.get_data_classif('3gauss',n,nz)\nxt,yt=ot.datasets.get_data_classif('3gauss',n,nz)\n\nnbnoise=8\n\nxs=np.hstack((xs,np.random.randn(n,nbnoise)))\nxt=np.hstack((xt,np.random.randn(n,nbnoise)))\n\n#%% plot samples\n\npl.figure(1)\n\n\npl.scatter(xt[:,0],xt[:,1],c=ys,marker='+',label='Source samples')\npl.legend(loc=0)\npl.title('Discriminant dimensions')\n\n\n#%% plot distributions and loss matrix\np=2\nreg=1\nk=10\nmaxiter=100\n\nP,proj = wda(xs,ys,p,reg,k,maxiter=maxiter)\n\n#%% plot samples\n\nxsp=proj(xs)\nxtp=proj(xt)\n\npl.figure(1,(10,5))\n\npl.subplot(1,2,1)\npl.scatter(xsp[:,0],xsp[:,1],c=ys,marker='+',label='Projected samples')\npl.legend(loc=0)\npl.title('Projected training samples')\n\n\npl.subplot(1,2,2)\npl.scatter(xtp[:,0],xtp[:,1],c=ys,marker='+',label='Projected samples')\npl.legend(loc=0)\npl.title('Projected test samples')"
+ "# Author: Remi Flamary <remi.flamary@unice.fr>\n#\n# License: MIT License\n\nimport numpy as np\nimport matplotlib.pylab as pl\n\nfrom ot.dr import wda, fda"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Generate data\n-------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% parameters\n\nn = 1000 # nb samples in source and target datasets\nnz = 0.2\n\n# generate circle dataset\nt = np.random.rand(n) * 2 * np.pi\nys = np.floor((np.arange(n) * 1.0 / n * 3)) + 1\nxs = np.concatenate(\n (np.cos(t).reshape((-1, 1)), np.sin(t).reshape((-1, 1))), 1)\nxs = xs * ys.reshape(-1, 1) + nz * np.random.randn(n, 2)\n\nt = np.random.rand(n) * 2 * np.pi\nyt = np.floor((np.arange(n) * 1.0 / n * 3)) + 1\nxt = np.concatenate(\n (np.cos(t).reshape((-1, 1)), np.sin(t).reshape((-1, 1))), 1)\nxt = xt * yt.reshape(-1, 1) + nz * np.random.randn(n, 2)\n\nnbnoise = 8\n\nxs = np.hstack((xs, np.random.randn(n, nbnoise)))\nxt = np.hstack((xt, np.random.randn(n, nbnoise)))"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Plot data\n---------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% plot samples\npl.figure(1, figsize=(6.4, 3.5))\n\npl.subplot(1, 2, 1)\npl.scatter(xt[:, 0], xt[:, 1], c=ys, marker='+', label='Source samples')\npl.legend(loc=0)\npl.title('Discriminant dimensions')\n\npl.subplot(1, 2, 2)\npl.scatter(xt[:, 2], xt[:, 3], c=ys, marker='+', label='Source samples')\npl.legend(loc=0)\npl.title('Other dimensions')\npl.tight_layout()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Compute Fisher Discriminant Analysis\n------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% Compute FDA\np = 2\n\nPfda, projfda = fda(xs, ys, p)"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Compute Wasserstein Discriminant Analysis\n-----------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% Compute WDA\np = 2\nreg = 1e0\nk = 10\nmaxiter = 100\n\nPwda, projwda = wda(xs, ys, p, reg, k, maxiter=maxiter)"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Plot 2D projections\n-------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% plot samples\n\nxsp = projfda(xs)\nxtp = projfda(xt)\n\nxspw = projwda(xs)\nxtpw = projwda(xt)\n\npl.figure(2)\n\npl.subplot(2, 2, 1)\npl.scatter(xsp[:, 0], xsp[:, 1], c=ys, marker='+', label='Projected samples')\npl.legend(loc=0)\npl.title('Projected training samples FDA')\n\npl.subplot(2, 2, 2)\npl.scatter(xtp[:, 0], xtp[:, 1], c=ys, marker='+', label='Projected samples')\npl.legend(loc=0)\npl.title('Projected test samples FDA')\n\npl.subplot(2, 2, 3)\npl.scatter(xspw[:, 0], xspw[:, 1], c=ys, marker='+', label='Projected samples')\npl.legend(loc=0)\npl.title('Projected training samples WDA')\n\npl.subplot(2, 2, 4)\npl.scatter(xtpw[:, 0], xtpw[:, 1], c=ys, marker='+', label='Projected samples')\npl.legend(loc=0)\npl.title('Projected test samples WDA')\npl.tight_layout()\n\npl.show()"
],
"outputs": [],
"metadata": {
diff --git a/docs/source/auto_examples/plot_WDA.py b/docs/source/auto_examples/plot_WDA.py
index bbe3888..93cc237 100644
--- a/docs/source/auto_examples/plot_WDA.py
+++ b/docs/source/auto_examples/plot_WDA.py
@@ -4,60 +4,124 @@
Wasserstein Discriminant Analysis
=================================
-@author: rflamary
+This example illustrate the use of WDA as proposed in [11].
+
+
+[11] Flamary, R., Cuturi, M., Courty, N., & Rakotomamonjy, A. (2016).
+Wasserstein Discriminant Analysis.
+
"""
+# Author: Remi Flamary <remi.flamary@unice.fr>
+#
+# License: MIT License
+
import numpy as np
import matplotlib.pylab as pl
-import ot
-from ot.datasets import get_1D_gauss as gauss
-from ot.dr import wda
+from ot.dr import wda, fda
+
+
+##############################################################################
+# Generate data
+# -------------
#%% parameters
-n=1000 # nb samples in source and target datasets
-nz=0.2
-xs,ys=ot.datasets.get_data_classif('3gauss',n,nz)
-xt,yt=ot.datasets.get_data_classif('3gauss',n,nz)
+n = 1000 # nb samples in source and target datasets
+nz = 0.2
-nbnoise=8
+# generate circle dataset
+t = np.random.rand(n) * 2 * np.pi
+ys = np.floor((np.arange(n) * 1.0 / n * 3)) + 1
+xs = np.concatenate(
+ (np.cos(t).reshape((-1, 1)), np.sin(t).reshape((-1, 1))), 1)
+xs = xs * ys.reshape(-1, 1) + nz * np.random.randn(n, 2)
-xs=np.hstack((xs,np.random.randn(n,nbnoise)))
-xt=np.hstack((xt,np.random.randn(n,nbnoise)))
+t = np.random.rand(n) * 2 * np.pi
+yt = np.floor((np.arange(n) * 1.0 / n * 3)) + 1
+xt = np.concatenate(
+ (np.cos(t).reshape((-1, 1)), np.sin(t).reshape((-1, 1))), 1)
+xt = xt * yt.reshape(-1, 1) + nz * np.random.randn(n, 2)
-#%% plot samples
+nbnoise = 8
+
+xs = np.hstack((xs, np.random.randn(n, nbnoise)))
+xt = np.hstack((xt, np.random.randn(n, nbnoise)))
-pl.figure(1)
+##############################################################################
+# Plot data
+# ---------
+#%% plot samples
+pl.figure(1, figsize=(6.4, 3.5))
-pl.scatter(xt[:,0],xt[:,1],c=ys,marker='+',label='Source samples')
+pl.subplot(1, 2, 1)
+pl.scatter(xt[:, 0], xt[:, 1], c=ys, marker='+', label='Source samples')
pl.legend(loc=0)
pl.title('Discriminant dimensions')
+pl.subplot(1, 2, 2)
+pl.scatter(xt[:, 2], xt[:, 3], c=ys, marker='+', label='Source samples')
+pl.legend(loc=0)
+pl.title('Other dimensions')
+pl.tight_layout()
+
+##############################################################################
+# Compute Fisher Discriminant Analysis
+# ------------------------------------
-#%% plot distributions and loss matrix
-p=2
-reg=1
-k=10
-maxiter=100
+#%% Compute FDA
+p = 2
-P,proj = wda(xs,ys,p,reg,k,maxiter=maxiter)
+Pfda, projfda = fda(xs, ys, p)
+
+##############################################################################
+# Compute Wasserstein Discriminant Analysis
+# -----------------------------------------
+
+#%% Compute WDA
+p = 2
+reg = 1e0
+k = 10
+maxiter = 100
+
+Pwda, projwda = wda(xs, ys, p, reg, k, maxiter=maxiter)
+
+
+##############################################################################
+# Plot 2D projections
+# -------------------
#%% plot samples
-xsp=proj(xs)
-xtp=proj(xt)
+xsp = projfda(xs)
+xtp = projfda(xt)
-pl.figure(1,(10,5))
+xspw = projwda(xs)
+xtpw = projwda(xt)
-pl.subplot(1,2,1)
-pl.scatter(xsp[:,0],xsp[:,1],c=ys,marker='+',label='Projected samples')
+pl.figure(2)
+
+pl.subplot(2, 2, 1)
+pl.scatter(xsp[:, 0], xsp[:, 1], c=ys, marker='+', label='Projected samples')
pl.legend(loc=0)
-pl.title('Projected training samples')
+pl.title('Projected training samples FDA')
+pl.subplot(2, 2, 2)
+pl.scatter(xtp[:, 0], xtp[:, 1], c=ys, marker='+', label='Projected samples')
+pl.legend(loc=0)
+pl.title('Projected test samples FDA')
-pl.subplot(1,2,2)
-pl.scatter(xtp[:,0],xtp[:,1],c=ys,marker='+',label='Projected samples')
+pl.subplot(2, 2, 3)
+pl.scatter(xspw[:, 0], xspw[:, 1], c=ys, marker='+', label='Projected samples')
pl.legend(loc=0)
-pl.title('Projected test samples')
+pl.title('Projected training samples WDA')
+
+pl.subplot(2, 2, 4)
+pl.scatter(xtpw[:, 0], xtpw[:, 1], c=ys, marker='+', label='Projected samples')
+pl.legend(loc=0)
+pl.title('Projected test samples WDA')
+pl.tight_layout()
+
+pl.show()
diff --git a/docs/source/auto_examples/plot_WDA.rst b/docs/source/auto_examples/plot_WDA.rst
index 540555d..2d83123 100644
--- a/docs/source/auto_examples/plot_WDA.rst
+++ b/docs/source/auto_examples/plot_WDA.rst
@@ -7,108 +7,222 @@
Wasserstein Discriminant Analysis
=================================
-@author: rflamary
+This example illustrate the use of WDA as proposed in [11].
+[11] Flamary, R., Cuturi, M., Courty, N., & Rakotomamonjy, A. (2016).
+Wasserstein Discriminant Analysis.
-.. image:: /auto_examples/images/sphx_glr_plot_WDA_001.png
- :align: center
-.. rst-class:: sphx-glr-script-out
+.. code-block:: python
- Out::
- Compiling cost function...
- Computing gradient of cost function...
- iter cost val grad. norm
- 1 +5.2427396265941129e-01 8.16627951e-01
- 2 +1.7904850059627236e-01 1.91366819e-01
- 3 +1.6985797253002377e-01 1.70940682e-01
- 4 +1.3903474972292729e-01 1.28606342e-01
- 5 +7.4961734618782416e-02 6.41973980e-02
- 6 +7.1900245222486239e-02 4.25693592e-02
- 7 +7.0472023318269614e-02 2.34599232e-02
- 8 +6.9917568641317152e-02 5.66542766e-03
- 9 +6.9885086242452696e-02 4.05756115e-04
- 10 +6.9884967432653489e-02 2.16836017e-04
- 11 +6.9884923649884148e-02 5.74961622e-05
- 12 +6.9884921818258436e-02 3.83257203e-05
- 13 +6.9884920459612282e-02 9.97486224e-06
- 14 +6.9884920414414409e-02 7.33567875e-06
- 15 +6.9884920388431387e-02 5.23889187e-06
- 16 +6.9884920385183902e-02 4.91959084e-06
- 17 +6.9884920373983223e-02 3.56451669e-06
- 18 +6.9884920369701245e-02 2.88858709e-06
- 19 +6.9884920361621208e-02 1.82294279e-07
- Terminated - min grad norm reached after 19 iterations, 9.65 seconds.
+ # Author: Remi Flamary <remi.flamary@unice.fr>
+ #
+ # License: MIT License
+ import numpy as np
+ import matplotlib.pylab as pl
+ from ot.dr import wda, fda
-|
-.. code-block:: python
- import numpy as np
- import matplotlib.pylab as pl
- import ot
- from ot.datasets import get_1D_gauss as gauss
- from ot.dr import wda
+
+
+Generate data
+-------------
+
+
+
+.. code-block:: python
#%% parameters
- n=1000 # nb samples in source and target datasets
- nz=0.2
- xs,ys=ot.datasets.get_data_classif('3gauss',n,nz)
- xt,yt=ot.datasets.get_data_classif('3gauss',n,nz)
+ n = 1000 # nb samples in source and target datasets
+ nz = 0.2
+
+ # generate circle dataset
+ t = np.random.rand(n) * 2 * np.pi
+ ys = np.floor((np.arange(n) * 1.0 / n * 3)) + 1
+ xs = np.concatenate(
+ (np.cos(t).reshape((-1, 1)), np.sin(t).reshape((-1, 1))), 1)
+ xs = xs * ys.reshape(-1, 1) + nz * np.random.randn(n, 2)
+
+ t = np.random.rand(n) * 2 * np.pi
+ yt = np.floor((np.arange(n) * 1.0 / n * 3)) + 1
+ xt = np.concatenate(
+ (np.cos(t).reshape((-1, 1)), np.sin(t).reshape((-1, 1))), 1)
+ xt = xt * yt.reshape(-1, 1) + nz * np.random.randn(n, 2)
+
+ nbnoise = 8
+
+ xs = np.hstack((xs, np.random.randn(n, nbnoise)))
+ xt = np.hstack((xt, np.random.randn(n, nbnoise)))
- nbnoise=8
- xs=np.hstack((xs,np.random.randn(n,nbnoise)))
- xt=np.hstack((xt,np.random.randn(n,nbnoise)))
- #%% plot samples
- pl.figure(1)
- pl.scatter(xt[:,0],xt[:,1],c=ys,marker='+',label='Source samples')
+
+Plot data
+---------
+
+
+
+.. code-block:: python
+
+
+ #%% plot samples
+ pl.figure(1, figsize=(6.4, 3.5))
+
+ pl.subplot(1, 2, 1)
+ pl.scatter(xt[:, 0], xt[:, 1], c=ys, marker='+', label='Source samples')
pl.legend(loc=0)
pl.title('Discriminant dimensions')
+ pl.subplot(1, 2, 2)
+ pl.scatter(xt[:, 2], xt[:, 3], c=ys, marker='+', label='Source samples')
+ pl.legend(loc=0)
+ pl.title('Other dimensions')
+ pl.tight_layout()
+
+
- #%% plot distributions and loss matrix
- p=2
- reg=1
- k=10
- maxiter=100
- P,proj = wda(xs,ys,p,reg,k,maxiter=maxiter)
+.. image:: /auto_examples/images/sphx_glr_plot_WDA_001.png
+ :align: center
+
+
+
+
+Compute Fisher Discriminant Analysis
+------------------------------------
+
+
+
+.. code-block:: python
+
+
+ #%% Compute FDA
+ p = 2
+
+ Pfda, projfda = fda(xs, ys, p)
+
+
+
+
+
+
+
+Compute Wasserstein Discriminant Analysis
+-----------------------------------------
+
+
+
+.. code-block:: python
+
+
+ #%% Compute WDA
+ p = 2
+ reg = 1e0
+ k = 10
+ maxiter = 100
+
+ Pwda, projwda = wda(xs, ys, p, reg, k, maxiter=maxiter)
+
+
+
+
+
+
+.. rst-class:: sphx-glr-script-out
+
+ Out::
+
+ Compiling cost function...
+ Computing gradient of cost function...
+ iter cost val grad. norm
+ 1 +9.0167295050534191e-01 2.28422652e-01
+ 2 +4.8324990550878105e-01 4.89362707e-01
+ 3 +3.4613154515357075e-01 2.84117562e-01
+ 4 +2.5277108387195002e-01 1.24888750e-01
+ 5 +2.4113858393736629e-01 8.07491482e-02
+ 6 +2.3642108593032782e-01 1.67612140e-02
+ 7 +2.3625721372202199e-01 7.68640008e-03
+ 8 +2.3625461994913738e-01 7.42200784e-03
+ 9 +2.3624493441436939e-01 6.43534105e-03
+ 10 +2.3621901383686217e-01 2.17960585e-03
+ 11 +2.3621854258326572e-01 2.03306749e-03
+ 12 +2.3621696458678049e-01 1.37118721e-03
+ 13 +2.3621569489873540e-01 2.76368907e-04
+ 14 +2.3621565599232983e-01 1.41898134e-04
+ 15 +2.3621564465487518e-01 5.96602069e-05
+ 16 +2.3621564232556647e-01 1.08709521e-05
+ 17 +2.3621564230277003e-01 9.17855656e-06
+ 18 +2.3621564224857586e-01 1.73728345e-06
+ 19 +2.3621564224748123e-01 1.17770019e-06
+ 20 +2.3621564224658587e-01 2.16179383e-07
+ Terminated - min grad norm reached after 20 iterations, 9.20 seconds.
+
+
+Plot 2D projections
+-------------------
+
+
+
+.. code-block:: python
+
#%% plot samples
- xsp=proj(xs)
- xtp=proj(xt)
+ xsp = projfda(xs)
+ xtp = projfda(xt)
+
+ xspw = projwda(xs)
+ xtpw = projwda(xt)
- pl.figure(1,(10,5))
+ pl.figure(2)
- pl.subplot(1,2,1)
- pl.scatter(xsp[:,0],xsp[:,1],c=ys,marker='+',label='Projected samples')
+ pl.subplot(2, 2, 1)
+ pl.scatter(xsp[:, 0], xsp[:, 1], c=ys, marker='+', label='Projected samples')
pl.legend(loc=0)
- pl.title('Projected training samples')
+ pl.title('Projected training samples FDA')
+ pl.subplot(2, 2, 2)
+ pl.scatter(xtp[:, 0], xtp[:, 1], c=ys, marker='+', label='Projected samples')
+ pl.legend(loc=0)
+ pl.title('Projected test samples FDA')
+
+ pl.subplot(2, 2, 3)
+ pl.scatter(xspw[:, 0], xspw[:, 1], c=ys, marker='+', label='Projected samples')
+ pl.legend(loc=0)
+ pl.title('Projected training samples WDA')
- pl.subplot(1,2,2)
- pl.scatter(xtp[:,0],xtp[:,1],c=ys,marker='+',label='Projected samples')
+ pl.subplot(2, 2, 4)
+ pl.scatter(xtpw[:, 0], xtpw[:, 1], c=ys, marker='+', label='Projected samples')
pl.legend(loc=0)
- pl.title('Projected test samples')
+ pl.title('Projected test samples WDA')
+ pl.tight_layout()
+
+ pl.show()
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_WDA_003.png
+ :align: center
+
+
+
-**Total running time of the script:** ( 0 minutes 16.902 seconds)
+**Total running time of the script:** ( 0 minutes 16.182 seconds)
diff --git a/docs/source/auto_examples/plot_barycenter_1D.ipynb b/docs/source/auto_examples/plot_barycenter_1D.ipynb
index 36f3975..a19e0fd 100644
--- a/docs/source/auto_examples/plot_barycenter_1D.ipynb
+++ b/docs/source/auto_examples/plot_barycenter_1D.ipynb
@@ -15,7 +15,7 @@
},
{
"source": [
- "\n# 1D Wasserstein barycenter demo\n\n\n\n@author: rflamary\n\n"
+ "\n# 1D Wasserstein barycenter demo\n\n\nThis example illustrates the computation of regularized Wassersyein Barycenter\nas proposed in [3].\n\n\n[3] Benamou, J. D., Carlier, G., Cuturi, M., Nenna, L., & Peyr\u00e9, G. (2015).\nIterative Bregman projections for regularized transportation problems\nSIAM Journal on Scientific Computing, 37(2), A1111-A1138.\n\n\n"
],
"cell_type": "markdown",
"metadata": {}
@@ -24,7 +24,79 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "import numpy as np\nimport matplotlib.pylab as pl\nimport ot\nfrom mpl_toolkits.mplot3d import Axes3D #necessary for 3d plot even if not used\nfrom matplotlib.collections import PolyCollection\n\n\n#%% parameters\n\nn=100 # nb bins\n\n# bin positions\nx=np.arange(n,dtype=np.float64)\n\n# Gaussian distributions\na1=ot.datasets.get_1D_gauss(n,m=20,s=5) # m= mean, s= std\na2=ot.datasets.get_1D_gauss(n,m=60,s=8)\n\n# creating matrix A containing all distributions\nA=np.vstack((a1,a2)).T\nnbd=A.shape[1]\n\n# loss matrix + normalization\nM=ot.utils.dist0(n)\nM/=M.max()\n\n#%% plot the distributions\n\npl.figure(1)\nfor i in range(nbd):\n pl.plot(x,A[:,i])\npl.title('Distributions')\n\n#%% barycenter computation\n\nalpha=0.2 # 0<=alpha<=1\nweights=np.array([1-alpha,alpha])\n\n# l2bary\nbary_l2=A.dot(weights)\n\n# wasserstein\nreg=1e-3\nbary_wass=ot.bregman.barycenter(A,M,reg,weights)\n\npl.figure(2)\npl.clf()\npl.subplot(2,1,1)\nfor i in range(nbd):\n pl.plot(x,A[:,i])\npl.title('Distributions')\n\npl.subplot(2,1,2)\npl.plot(x,bary_l2,'r',label='l2')\npl.plot(x,bary_wass,'g',label='Wasserstein')\npl.legend()\npl.title('Barycenters')\n\n\n#%% barycenter interpolation\n\nnbalpha=11\nalphalist=np.linspace(0,1,nbalpha)\n\n\nB_l2=np.zeros((n,nbalpha))\n\nB_wass=np.copy(B_l2)\n\nfor i in range(0,nbalpha):\n alpha=alphalist[i]\n weights=np.array([1-alpha,alpha])\n B_l2[:,i]=A.dot(weights)\n B_wass[:,i]=ot.bregman.barycenter(A,M,reg,weights)\n\n#%% plot interpolation\n\npl.figure(3,(10,5))\n\n#pl.subplot(1,2,1)\ncmap=pl.cm.get_cmap('viridis')\nverts = []\nzs = alphalist\nfor i,z in enumerate(zs):\n ys = B_l2[:,i]\n verts.append(list(zip(x, ys)))\n\nax = pl.gcf().gca(projection='3d')\n\npoly = PolyCollection(verts,facecolors=[cmap(a) for a in alphalist])\npoly.set_alpha(0.7)\nax.add_collection3d(poly, zs=zs, zdir='y')\n\nax.set_xlabel('x')\nax.set_xlim3d(0, n)\nax.set_ylabel('$\\\\alpha$')\nax.set_ylim3d(0,1)\nax.set_zlabel('')\nax.set_zlim3d(0, B_l2.max()*1.01)\npl.title('Barycenter interpolation with l2')\n\npl.show()\n\npl.figure(4,(10,5))\n\n#pl.subplot(1,2,1)\ncmap=pl.cm.get_cmap('viridis')\nverts = []\nzs = alphalist\nfor i,z in enumerate(zs):\n ys = B_wass[:,i]\n verts.append(list(zip(x, ys)))\n\nax = pl.gcf().gca(projection='3d')\n\npoly = PolyCollection(verts,facecolors=[cmap(a) for a in alphalist])\npoly.set_alpha(0.7)\nax.add_collection3d(poly, zs=zs, zdir='y')\n\nax.set_xlabel('x')\nax.set_xlim3d(0, n)\nax.set_ylabel('$\\\\alpha$')\nax.set_ylim3d(0,1)\nax.set_zlabel('')\nax.set_zlim3d(0, B_l2.max()*1.01)\npl.title('Barycenter interpolation with Wasserstein')\n\npl.show()"
+ "# Author: Remi Flamary <remi.flamary@unice.fr>\n#\n# License: MIT License\n\nimport numpy as np\nimport matplotlib.pylab as pl\nimport ot\n# necessary for 3d plot even if not used\nfrom mpl_toolkits.mplot3d import Axes3D # noqa\nfrom matplotlib.collections import PolyCollection"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Generate data\n-------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% parameters\n\nn = 100 # nb bins\n\n# bin positions\nx = np.arange(n, dtype=np.float64)\n\n# Gaussian distributions\na1 = ot.datasets.get_1D_gauss(n, m=20, s=5) # m= mean, s= std\na2 = ot.datasets.get_1D_gauss(n, m=60, s=8)\n\n# creating matrix A containing all distributions\nA = np.vstack((a1, a2)).T\nn_distributions = A.shape[1]\n\n# loss matrix + normalization\nM = ot.utils.dist0(n)\nM /= M.max()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Plot data\n---------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% plot the distributions\n\npl.figure(1, figsize=(6.4, 3))\nfor i in range(n_distributions):\n pl.plot(x, A[:, i])\npl.title('Distributions')\npl.tight_layout()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Barycenter computation\n----------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% barycenter computation\n\nalpha = 0.2 # 0<=alpha<=1\nweights = np.array([1 - alpha, alpha])\n\n# l2bary\nbary_l2 = A.dot(weights)\n\n# wasserstein\nreg = 1e-3\nbary_wass = ot.bregman.barycenter(A, M, reg, weights)\n\npl.figure(2)\npl.clf()\npl.subplot(2, 1, 1)\nfor i in range(n_distributions):\n pl.plot(x, A[:, i])\npl.title('Distributions')\n\npl.subplot(2, 1, 2)\npl.plot(x, bary_l2, 'r', label='l2')\npl.plot(x, bary_wass, 'g', label='Wasserstein')\npl.legend()\npl.title('Barycenters')\npl.tight_layout()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Barycentric interpolation\n-------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% barycenter interpolation\n\nn_alpha = 11\nalpha_list = np.linspace(0, 1, n_alpha)\n\n\nB_l2 = np.zeros((n, n_alpha))\n\nB_wass = np.copy(B_l2)\n\nfor i in range(0, n_alpha):\n alpha = alpha_list[i]\n weights = np.array([1 - alpha, alpha])\n B_l2[:, i] = A.dot(weights)\n B_wass[:, i] = ot.bregman.barycenter(A, M, reg, weights)\n\n#%% plot interpolation\n\npl.figure(3)\n\ncmap = pl.cm.get_cmap('viridis')\nverts = []\nzs = alpha_list\nfor i, z in enumerate(zs):\n ys = B_l2[:, i]\n verts.append(list(zip(x, ys)))\n\nax = pl.gcf().gca(projection='3d')\n\npoly = PolyCollection(verts, facecolors=[cmap(a) for a in alpha_list])\npoly.set_alpha(0.7)\nax.add_collection3d(poly, zs=zs, zdir='y')\nax.set_xlabel('x')\nax.set_xlim3d(0, n)\nax.set_ylabel('$\\\\alpha$')\nax.set_ylim3d(0, 1)\nax.set_zlabel('')\nax.set_zlim3d(0, B_l2.max() * 1.01)\npl.title('Barycenter interpolation with l2')\npl.tight_layout()\n\npl.figure(4)\ncmap = pl.cm.get_cmap('viridis')\nverts = []\nzs = alpha_list\nfor i, z in enumerate(zs):\n ys = B_wass[:, i]\n verts.append(list(zip(x, ys)))\n\nax = pl.gcf().gca(projection='3d')\n\npoly = PolyCollection(verts, facecolors=[cmap(a) for a in alpha_list])\npoly.set_alpha(0.7)\nax.add_collection3d(poly, zs=zs, zdir='y')\nax.set_xlabel('x')\nax.set_xlim3d(0, n)\nax.set_ylabel('$\\\\alpha$')\nax.set_ylim3d(0, 1)\nax.set_zlabel('')\nax.set_zlim3d(0, B_l2.max() * 1.01)\npl.title('Barycenter interpolation with Wasserstein')\npl.tight_layout()\n\npl.show()"
],
"outputs": [],
"metadata": {
diff --git a/docs/source/auto_examples/plot_barycenter_1D.py b/docs/source/auto_examples/plot_barycenter_1D.py
index 30eecbf..620936b 100644
--- a/docs/source/auto_examples/plot_barycenter_1D.py
+++ b/docs/source/auto_examples/plot_barycenter_1D.py
@@ -4,135 +4,157 @@
1D Wasserstein barycenter demo
==============================
+This example illustrates the computation of regularized Wassersyein Barycenter
+as proposed in [3].
+
+
+[3] Benamou, J. D., Carlier, G., Cuturi, M., Nenna, L., & Peyré, G. (2015).
+Iterative Bregman projections for regularized transportation problems
+SIAM Journal on Scientific Computing, 37(2), A1111-A1138.
-@author: rflamary
"""
+# Author: Remi Flamary <remi.flamary@unice.fr>
+#
+# License: MIT License
+
import numpy as np
import matplotlib.pylab as pl
import ot
-from mpl_toolkits.mplot3d import Axes3D #necessary for 3d plot even if not used
+# necessary for 3d plot even if not used
+from mpl_toolkits.mplot3d import Axes3D # noqa
from matplotlib.collections import PolyCollection
+##############################################################################
+# Generate data
+# -------------
#%% parameters
-n=100 # nb bins
+n = 100 # nb bins
# bin positions
-x=np.arange(n,dtype=np.float64)
+x = np.arange(n, dtype=np.float64)
# Gaussian distributions
-a1=ot.datasets.get_1D_gauss(n,m=20,s=5) # m= mean, s= std
-a2=ot.datasets.get_1D_gauss(n,m=60,s=8)
+a1 = ot.datasets.get_1D_gauss(n, m=20, s=5) # m= mean, s= std
+a2 = ot.datasets.get_1D_gauss(n, m=60, s=8)
# creating matrix A containing all distributions
-A=np.vstack((a1,a2)).T
-nbd=A.shape[1]
+A = np.vstack((a1, a2)).T
+n_distributions = A.shape[1]
# loss matrix + normalization
-M=ot.utils.dist0(n)
-M/=M.max()
+M = ot.utils.dist0(n)
+M /= M.max()
+
+##############################################################################
+# Plot data
+# ---------
#%% plot the distributions
-pl.figure(1)
-for i in range(nbd):
- pl.plot(x,A[:,i])
+pl.figure(1, figsize=(6.4, 3))
+for i in range(n_distributions):
+ pl.plot(x, A[:, i])
pl.title('Distributions')
+pl.tight_layout()
+
+##############################################################################
+# Barycenter computation
+# ----------------------
#%% barycenter computation
-alpha=0.2 # 0<=alpha<=1
-weights=np.array([1-alpha,alpha])
+alpha = 0.2 # 0<=alpha<=1
+weights = np.array([1 - alpha, alpha])
# l2bary
-bary_l2=A.dot(weights)
+bary_l2 = A.dot(weights)
# wasserstein
-reg=1e-3
-bary_wass=ot.bregman.barycenter(A,M,reg,weights)
+reg = 1e-3
+bary_wass = ot.bregman.barycenter(A, M, reg, weights)
pl.figure(2)
pl.clf()
-pl.subplot(2,1,1)
-for i in range(nbd):
- pl.plot(x,A[:,i])
+pl.subplot(2, 1, 1)
+for i in range(n_distributions):
+ pl.plot(x, A[:, i])
pl.title('Distributions')
-pl.subplot(2,1,2)
-pl.plot(x,bary_l2,'r',label='l2')
-pl.plot(x,bary_wass,'g',label='Wasserstein')
+pl.subplot(2, 1, 2)
+pl.plot(x, bary_l2, 'r', label='l2')
+pl.plot(x, bary_wass, 'g', label='Wasserstein')
pl.legend()
pl.title('Barycenters')
+pl.tight_layout()
+##############################################################################
+# Barycentric interpolation
+# -------------------------
#%% barycenter interpolation
-nbalpha=11
-alphalist=np.linspace(0,1,nbalpha)
+n_alpha = 11
+alpha_list = np.linspace(0, 1, n_alpha)
-B_l2=np.zeros((n,nbalpha))
+B_l2 = np.zeros((n, n_alpha))
-B_wass=np.copy(B_l2)
+B_wass = np.copy(B_l2)
-for i in range(0,nbalpha):
- alpha=alphalist[i]
- weights=np.array([1-alpha,alpha])
- B_l2[:,i]=A.dot(weights)
- B_wass[:,i]=ot.bregman.barycenter(A,M,reg,weights)
+for i in range(0, n_alpha):
+ alpha = alpha_list[i]
+ weights = np.array([1 - alpha, alpha])
+ B_l2[:, i] = A.dot(weights)
+ B_wass[:, i] = ot.bregman.barycenter(A, M, reg, weights)
#%% plot interpolation
-pl.figure(3,(10,5))
+pl.figure(3)
-#pl.subplot(1,2,1)
-cmap=pl.cm.get_cmap('viridis')
+cmap = pl.cm.get_cmap('viridis')
verts = []
-zs = alphalist
-for i,z in enumerate(zs):
- ys = B_l2[:,i]
+zs = alpha_list
+for i, z in enumerate(zs):
+ ys = B_l2[:, i]
verts.append(list(zip(x, ys)))
ax = pl.gcf().gca(projection='3d')
-poly = PolyCollection(verts,facecolors=[cmap(a) for a in alphalist])
+poly = PolyCollection(verts, facecolors=[cmap(a) for a in alpha_list])
poly.set_alpha(0.7)
ax.add_collection3d(poly, zs=zs, zdir='y')
-
ax.set_xlabel('x')
ax.set_xlim3d(0, n)
ax.set_ylabel('$\\alpha$')
-ax.set_ylim3d(0,1)
+ax.set_ylim3d(0, 1)
ax.set_zlabel('')
-ax.set_zlim3d(0, B_l2.max()*1.01)
+ax.set_zlim3d(0, B_l2.max() * 1.01)
pl.title('Barycenter interpolation with l2')
+pl.tight_layout()
-pl.show()
-
-pl.figure(4,(10,5))
-
-#pl.subplot(1,2,1)
-cmap=pl.cm.get_cmap('viridis')
+pl.figure(4)
+cmap = pl.cm.get_cmap('viridis')
verts = []
-zs = alphalist
-for i,z in enumerate(zs):
- ys = B_wass[:,i]
+zs = alpha_list
+for i, z in enumerate(zs):
+ ys = B_wass[:, i]
verts.append(list(zip(x, ys)))
ax = pl.gcf().gca(projection='3d')
-poly = PolyCollection(verts,facecolors=[cmap(a) for a in alphalist])
+poly = PolyCollection(verts, facecolors=[cmap(a) for a in alpha_list])
poly.set_alpha(0.7)
ax.add_collection3d(poly, zs=zs, zdir='y')
-
ax.set_xlabel('x')
ax.set_xlim3d(0, n)
ax.set_ylabel('$\\alpha$')
-ax.set_ylim3d(0,1)
+ax.set_ylim3d(0, 1)
ax.set_zlabel('')
-ax.set_zlim3d(0, B_l2.max()*1.01)
+ax.set_zlim3d(0, B_l2.max() * 1.01)
pl.title('Barycenter interpolation with Wasserstein')
+pl.tight_layout()
-pl.show() \ No newline at end of file
+pl.show()
diff --git a/docs/source/auto_examples/plot_barycenter_1D.rst b/docs/source/auto_examples/plot_barycenter_1D.rst
index 1b15c77..f17f2c2 100644
--- a/docs/source/auto_examples/plot_barycenter_1D.rst
+++ b/docs/source/auto_examples/plot_barycenter_1D.rst
@@ -7,171 +7,230 @@
1D Wasserstein barycenter demo
==============================
+This example illustrates the computation of regularized Wassersyein Barycenter
+as proposed in [3].
-@author: rflamary
+[3] Benamou, J. D., Carlier, G., Cuturi, M., Nenna, L., & Peyré, G. (2015).
+Iterative Bregman projections for regularized transportation problems
+SIAM Journal on Scientific Computing, 37(2), A1111-A1138.
-.. rst-class:: sphx-glr-horizontal
+.. code-block:: python
- *
- .. image:: /auto_examples/images/sphx_glr_plot_barycenter_1D_001.png
- :scale: 47
+ # Author: Remi Flamary <remi.flamary@unice.fr>
+ #
+ # License: MIT License
- *
+ import numpy as np
+ import matplotlib.pylab as pl
+ import ot
+ # necessary for 3d plot even if not used
+ from mpl_toolkits.mplot3d import Axes3D # noqa
+ from matplotlib.collections import PolyCollection
- .. image:: /auto_examples/images/sphx_glr_plot_barycenter_1D_002.png
- :scale: 47
- *
- .. image:: /auto_examples/images/sphx_glr_plot_barycenter_1D_003.png
- :scale: 47
- *
- .. image:: /auto_examples/images/sphx_glr_plot_barycenter_1D_004.png
- :scale: 47
+Generate data
+-------------
.. code-block:: python
- import numpy as np
- import matplotlib.pylab as pl
- import ot
- from mpl_toolkits.mplot3d import Axes3D #necessary for 3d plot even if not used
- from matplotlib.collections import PolyCollection
-
-
#%% parameters
- n=100 # nb bins
+ n = 100 # nb bins
# bin positions
- x=np.arange(n,dtype=np.float64)
+ x = np.arange(n, dtype=np.float64)
# Gaussian distributions
- a1=ot.datasets.get_1D_gauss(n,m=20,s=5) # m= mean, s= std
- a2=ot.datasets.get_1D_gauss(n,m=60,s=8)
+ a1 = ot.datasets.get_1D_gauss(n, m=20, s=5) # m= mean, s= std
+ a2 = ot.datasets.get_1D_gauss(n, m=60, s=8)
# creating matrix A containing all distributions
- A=np.vstack((a1,a2)).T
- nbd=A.shape[1]
+ A = np.vstack((a1, a2)).T
+ n_distributions = A.shape[1]
# loss matrix + normalization
- M=ot.utils.dist0(n)
- M/=M.max()
+ M = ot.utils.dist0(n)
+ M /= M.max()
+
+
+
+
+
+
+
+Plot data
+---------
+
+
+
+.. code-block:: python
+
#%% plot the distributions
- pl.figure(1)
- for i in range(nbd):
- pl.plot(x,A[:,i])
+ pl.figure(1, figsize=(6.4, 3))
+ for i in range(n_distributions):
+ pl.plot(x, A[:, i])
pl.title('Distributions')
+ pl.tight_layout()
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_barycenter_1D_001.png
+ :align: center
+
+
+
+
+Barycenter computation
+----------------------
+
+
+
+.. code-block:: python
+
#%% barycenter computation
- alpha=0.2 # 0<=alpha<=1
- weights=np.array([1-alpha,alpha])
+ alpha = 0.2 # 0<=alpha<=1
+ weights = np.array([1 - alpha, alpha])
# l2bary
- bary_l2=A.dot(weights)
+ bary_l2 = A.dot(weights)
# wasserstein
- reg=1e-3
- bary_wass=ot.bregman.barycenter(A,M,reg,weights)
+ reg = 1e-3
+ bary_wass = ot.bregman.barycenter(A, M, reg, weights)
pl.figure(2)
pl.clf()
- pl.subplot(2,1,1)
- for i in range(nbd):
- pl.plot(x,A[:,i])
+ pl.subplot(2, 1, 1)
+ for i in range(n_distributions):
+ pl.plot(x, A[:, i])
pl.title('Distributions')
- pl.subplot(2,1,2)
- pl.plot(x,bary_l2,'r',label='l2')
- pl.plot(x,bary_wass,'g',label='Wasserstein')
+ pl.subplot(2, 1, 2)
+ pl.plot(x, bary_l2, 'r', label='l2')
+ pl.plot(x, bary_wass, 'g', label='Wasserstein')
pl.legend()
pl.title('Barycenters')
+ pl.tight_layout()
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_barycenter_1D_003.png
+ :align: center
+
+
+
+
+Barycentric interpolation
+-------------------------
+
+
+
+.. code-block:: python
#%% barycenter interpolation
- nbalpha=11
- alphalist=np.linspace(0,1,nbalpha)
+ n_alpha = 11
+ alpha_list = np.linspace(0, 1, n_alpha)
- B_l2=np.zeros((n,nbalpha))
+ B_l2 = np.zeros((n, n_alpha))
- B_wass=np.copy(B_l2)
+ B_wass = np.copy(B_l2)
- for i in range(0,nbalpha):
- alpha=alphalist[i]
- weights=np.array([1-alpha,alpha])
- B_l2[:,i]=A.dot(weights)
- B_wass[:,i]=ot.bregman.barycenter(A,M,reg,weights)
+ for i in range(0, n_alpha):
+ alpha = alpha_list[i]
+ weights = np.array([1 - alpha, alpha])
+ B_l2[:, i] = A.dot(weights)
+ B_wass[:, i] = ot.bregman.barycenter(A, M, reg, weights)
#%% plot interpolation
- pl.figure(3,(10,5))
+ pl.figure(3)
- #pl.subplot(1,2,1)
- cmap=pl.cm.get_cmap('viridis')
+ cmap = pl.cm.get_cmap('viridis')
verts = []
- zs = alphalist
- for i,z in enumerate(zs):
- ys = B_l2[:,i]
+ zs = alpha_list
+ for i, z in enumerate(zs):
+ ys = B_l2[:, i]
verts.append(list(zip(x, ys)))
ax = pl.gcf().gca(projection='3d')
- poly = PolyCollection(verts,facecolors=[cmap(a) for a in alphalist])
+ poly = PolyCollection(verts, facecolors=[cmap(a) for a in alpha_list])
poly.set_alpha(0.7)
ax.add_collection3d(poly, zs=zs, zdir='y')
-
ax.set_xlabel('x')
ax.set_xlim3d(0, n)
ax.set_ylabel('$\\alpha$')
- ax.set_ylim3d(0,1)
+ ax.set_ylim3d(0, 1)
ax.set_zlabel('')
- ax.set_zlim3d(0, B_l2.max()*1.01)
+ ax.set_zlim3d(0, B_l2.max() * 1.01)
pl.title('Barycenter interpolation with l2')
+ pl.tight_layout()
- pl.show()
-
- pl.figure(4,(10,5))
-
- #pl.subplot(1,2,1)
- cmap=pl.cm.get_cmap('viridis')
+ pl.figure(4)
+ cmap = pl.cm.get_cmap('viridis')
verts = []
- zs = alphalist
- for i,z in enumerate(zs):
- ys = B_wass[:,i]
+ zs = alpha_list
+ for i, z in enumerate(zs):
+ ys = B_wass[:, i]
verts.append(list(zip(x, ys)))
ax = pl.gcf().gca(projection='3d')
- poly = PolyCollection(verts,facecolors=[cmap(a) for a in alphalist])
+ poly = PolyCollection(verts, facecolors=[cmap(a) for a in alpha_list])
poly.set_alpha(0.7)
ax.add_collection3d(poly, zs=zs, zdir='y')
-
ax.set_xlabel('x')
ax.set_xlim3d(0, n)
ax.set_ylabel('$\\alpha$')
- ax.set_ylim3d(0,1)
+ ax.set_ylim3d(0, 1)
ax.set_zlabel('')
- ax.set_zlim3d(0, B_l2.max()*1.01)
+ ax.set_zlim3d(0, B_l2.max() * 1.01)
pl.title('Barycenter interpolation with Wasserstein')
+ pl.tight_layout()
pl.show()
-**Total running time of the script:** ( 0 minutes 2.274 seconds)
+
+
+
+.. rst-class:: sphx-glr-horizontal
+
+
+ *
+
+ .. image:: /auto_examples/images/sphx_glr_plot_barycenter_1D_005.png
+ :scale: 47
+
+ *
+
+ .. image:: /auto_examples/images/sphx_glr_plot_barycenter_1D_006.png
+ :scale: 47
+
+
+
+
+**Total running time of the script:** ( 0 minutes 0.814 seconds)
diff --git a/docs/source/auto_examples/plot_compute_emd.ipynb b/docs/source/auto_examples/plot_compute_emd.ipynb
index 4162144..b9b8bc5 100644
--- a/docs/source/auto_examples/plot_compute_emd.ipynb
+++ b/docs/source/auto_examples/plot_compute_emd.ipynb
@@ -15,7 +15,7 @@
},
{
"source": [
- "\n# 1D optimal transport\n\n\n@author: rflamary\n\n"
+ "\n# Plot multiple EMD\n\n\nShows how to compute multiple EMD and Sinkhorn with two differnt\nground metrics and plot their values for diffeent distributions.\n\n\n\n"
],
"cell_type": "markdown",
"metadata": {}
@@ -24,7 +24,79 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "import numpy as np\nimport matplotlib.pylab as pl\nimport ot\nfrom ot.datasets import get_1D_gauss as gauss\n\n\n#%% parameters\n\nn=100 # nb bins\nn_target=50 # nb target distributions\n\n\n# bin positions\nx=np.arange(n,dtype=np.float64)\n\nlst_m=np.linspace(20,90,n_target)\n\n# Gaussian distributions\na=gauss(n,m=20,s=5) # m= mean, s= std\n\nB=np.zeros((n,n_target))\n\nfor i,m in enumerate(lst_m):\n B[:,i]=gauss(n,m=m,s=5)\n\n# loss matrix and normalization\nM=ot.dist(x.reshape((n,1)),x.reshape((n,1)),'euclidean')\nM/=M.max()\nM2=ot.dist(x.reshape((n,1)),x.reshape((n,1)),'sqeuclidean')\nM2/=M2.max()\n#%% plot the distributions\n\npl.figure(1)\npl.subplot(2,1,1)\npl.plot(x,a,'b',label='Source distribution')\npl.title('Source distribution')\npl.subplot(2,1,2)\npl.plot(x,B,label='Target distributions')\npl.title('Target distributions')\n\n#%% Compute and plot distributions and loss matrix\n\nd_emd=ot.emd2(a,B,M) # direct computation of EMD\nd_emd2=ot.emd2(a,B,M2) # direct computation of EMD with loss M3\n\n\npl.figure(2)\npl.plot(d_emd,label='Euclidean EMD')\npl.plot(d_emd2,label='Squared Euclidean EMD')\npl.title('EMD distances')\npl.legend()\n\n#%%\nreg=1e-2\nd_sinkhorn=ot.sinkhorn(a,B,M,reg)\nd_sinkhorn2=ot.sinkhorn(a,B,M2,reg)\n\npl.figure(2)\npl.clf()\npl.plot(d_emd,label='Euclidean EMD')\npl.plot(d_emd2,label='Squared Euclidean EMD')\npl.plot(d_sinkhorn,'+',label='Euclidean Sinkhorn')\npl.plot(d_sinkhorn2,'+',label='Squared Euclidean Sinkhorn')\npl.title('EMD distances')\npl.legend()"
+ "# Author: Remi Flamary <remi.flamary@unice.fr>\n#\n# License: MIT License\n\nimport numpy as np\nimport matplotlib.pylab as pl\nimport ot\nfrom ot.datasets import get_1D_gauss as gauss"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Generate data\n-------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% parameters\n\nn = 100 # nb bins\nn_target = 50 # nb target distributions\n\n\n# bin positions\nx = np.arange(n, dtype=np.float64)\n\nlst_m = np.linspace(20, 90, n_target)\n\n# Gaussian distributions\na = gauss(n, m=20, s=5) # m= mean, s= std\n\nB = np.zeros((n, n_target))\n\nfor i, m in enumerate(lst_m):\n B[:, i] = gauss(n, m=m, s=5)\n\n# loss matrix and normalization\nM = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)), 'euclidean')\nM /= M.max()\nM2 = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)), 'sqeuclidean')\nM2 /= M2.max()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Plot data\n---------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% plot the distributions\n\npl.figure(1)\npl.subplot(2, 1, 1)\npl.plot(x, a, 'b', label='Source distribution')\npl.title('Source distribution')\npl.subplot(2, 1, 2)\npl.plot(x, B, label='Target distributions')\npl.title('Target distributions')\npl.tight_layout()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Compute EMD for the different losses\n------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% Compute and plot distributions and loss matrix\n\nd_emd = ot.emd2(a, B, M) # direct computation of EMD\nd_emd2 = ot.emd2(a, B, M2) # direct computation of EMD with loss M2\n\n\npl.figure(2)\npl.plot(d_emd, label='Euclidean EMD')\npl.plot(d_emd2, label='Squared Euclidean EMD')\npl.title('EMD distances')\npl.legend()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Compute Sinkhorn for the different losses\n-----------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%%\nreg = 1e-2\nd_sinkhorn = ot.sinkhorn2(a, B, M, reg)\nd_sinkhorn2 = ot.sinkhorn2(a, B, M2, reg)\n\npl.figure(2)\npl.clf()\npl.plot(d_emd, label='Euclidean EMD')\npl.plot(d_emd2, label='Squared Euclidean EMD')\npl.plot(d_sinkhorn, '+', label='Euclidean Sinkhorn')\npl.plot(d_sinkhorn2, '+', label='Squared Euclidean Sinkhorn')\npl.title('EMD distances')\npl.legend()\n\npl.show()"
],
"outputs": [],
"metadata": {
diff --git a/docs/source/auto_examples/plot_compute_emd.py b/docs/source/auto_examples/plot_compute_emd.py
index c7063e8..73b42c3 100644
--- a/docs/source/auto_examples/plot_compute_emd.py
+++ b/docs/source/auto_examples/plot_compute_emd.py
@@ -1,74 +1,102 @@
# -*- coding: utf-8 -*-
"""
-====================
-1D optimal transport
-====================
+=================
+Plot multiple EMD
+=================
+
+Shows how to compute multiple EMD and Sinkhorn with two differnt
+ground metrics and plot their values for diffeent distributions.
+
-@author: rflamary
"""
+# Author: Remi Flamary <remi.flamary@unice.fr>
+#
+# License: MIT License
+
import numpy as np
import matplotlib.pylab as pl
import ot
from ot.datasets import get_1D_gauss as gauss
+##############################################################################
+# Generate data
+# -------------
+
#%% parameters
-n=100 # nb bins
-n_target=50 # nb target distributions
+n = 100 # nb bins
+n_target = 50 # nb target distributions
# bin positions
-x=np.arange(n,dtype=np.float64)
+x = np.arange(n, dtype=np.float64)
-lst_m=np.linspace(20,90,n_target)
+lst_m = np.linspace(20, 90, n_target)
# Gaussian distributions
-a=gauss(n,m=20,s=5) # m= mean, s= std
+a = gauss(n, m=20, s=5) # m= mean, s= std
-B=np.zeros((n,n_target))
+B = np.zeros((n, n_target))
-for i,m in enumerate(lst_m):
- B[:,i]=gauss(n,m=m,s=5)
+for i, m in enumerate(lst_m):
+ B[:, i] = gauss(n, m=m, s=5)
# loss matrix and normalization
-M=ot.dist(x.reshape((n,1)),x.reshape((n,1)),'euclidean')
-M/=M.max()
-M2=ot.dist(x.reshape((n,1)),x.reshape((n,1)),'sqeuclidean')
-M2/=M2.max()
+M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)), 'euclidean')
+M /= M.max()
+M2 = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)), 'sqeuclidean')
+M2 /= M2.max()
+
+##############################################################################
+# Plot data
+# ---------
+
#%% plot the distributions
pl.figure(1)
-pl.subplot(2,1,1)
-pl.plot(x,a,'b',label='Source distribution')
+pl.subplot(2, 1, 1)
+pl.plot(x, a, 'b', label='Source distribution')
pl.title('Source distribution')
-pl.subplot(2,1,2)
-pl.plot(x,B,label='Target distributions')
+pl.subplot(2, 1, 2)
+pl.plot(x, B, label='Target distributions')
pl.title('Target distributions')
+pl.tight_layout()
+
+
+##############################################################################
+# Compute EMD for the different losses
+# ------------------------------------
#%% Compute and plot distributions and loss matrix
-d_emd=ot.emd2(a,B,M) # direct computation of EMD
-d_emd2=ot.emd2(a,B,M2) # direct computation of EMD with loss M3
+d_emd = ot.emd2(a, B, M) # direct computation of EMD
+d_emd2 = ot.emd2(a, B, M2) # direct computation of EMD with loss M2
pl.figure(2)
-pl.plot(d_emd,label='Euclidean EMD')
-pl.plot(d_emd2,label='Squared Euclidean EMD')
+pl.plot(d_emd, label='Euclidean EMD')
+pl.plot(d_emd2, label='Squared Euclidean EMD')
pl.title('EMD distances')
pl.legend()
+##############################################################################
+# Compute Sinkhorn for the different losses
+# -----------------------------------------
+
#%%
-reg=1e-2
-d_sinkhorn=ot.sinkhorn(a,B,M,reg)
-d_sinkhorn2=ot.sinkhorn(a,B,M2,reg)
+reg = 1e-2
+d_sinkhorn = ot.sinkhorn2(a, B, M, reg)
+d_sinkhorn2 = ot.sinkhorn2(a, B, M2, reg)
pl.figure(2)
pl.clf()
-pl.plot(d_emd,label='Euclidean EMD')
-pl.plot(d_emd2,label='Squared Euclidean EMD')
-pl.plot(d_sinkhorn,'+',label='Euclidean Sinkhorn')
-pl.plot(d_sinkhorn2,'+',label='Squared Euclidean Sinkhorn')
+pl.plot(d_emd, label='Euclidean EMD')
+pl.plot(d_emd2, label='Squared Euclidean EMD')
+pl.plot(d_sinkhorn, '+', label='Euclidean Sinkhorn')
+pl.plot(d_sinkhorn2, '+', label='Squared Euclidean Sinkhorn')
pl.title('EMD distances')
-pl.legend() \ No newline at end of file
+pl.legend()
+
+pl.show()
diff --git a/docs/source/auto_examples/plot_compute_emd.rst b/docs/source/auto_examples/plot_compute_emd.rst
index 4c7445b..cdbc620 100644
--- a/docs/source/auto_examples/plot_compute_emd.rst
+++ b/docs/source/auto_examples/plot_compute_emd.rst
@@ -3,101 +3,166 @@
.. _sphx_glr_auto_examples_plot_compute_emd.py:
-====================
-1D optimal transport
-====================
+=================
+Plot multiple EMD
+=================
-@author: rflamary
+Shows how to compute multiple EMD and Sinkhorn with two differnt
+ground metrics and plot their values for diffeent distributions.
-.. rst-class:: sphx-glr-horizontal
+.. code-block:: python
- *
- .. image:: /auto_examples/images/sphx_glr_plot_compute_emd_001.png
- :scale: 47
+ # Author: Remi Flamary <remi.flamary@unice.fr>
+ #
+ # License: MIT License
- *
+ import numpy as np
+ import matplotlib.pylab as pl
+ import ot
+ from ot.datasets import get_1D_gauss as gauss
- .. image:: /auto_examples/images/sphx_glr_plot_compute_emd_002.png
- :scale: 47
-.. code-block:: python
- import numpy as np
- import matplotlib.pylab as pl
- import ot
- from ot.datasets import get_1D_gauss as gauss
+Generate data
+-------------
+
+
+
+.. code-block:: python
#%% parameters
- n=100 # nb bins
- n_target=50 # nb target distributions
+ n = 100 # nb bins
+ n_target = 50 # nb target distributions
# bin positions
- x=np.arange(n,dtype=np.float64)
+ x = np.arange(n, dtype=np.float64)
- lst_m=np.linspace(20,90,n_target)
+ lst_m = np.linspace(20, 90, n_target)
# Gaussian distributions
- a=gauss(n,m=20,s=5) # m= mean, s= std
+ a = gauss(n, m=20, s=5) # m= mean, s= std
- B=np.zeros((n,n_target))
+ B = np.zeros((n, n_target))
- for i,m in enumerate(lst_m):
- B[:,i]=gauss(n,m=m,s=5)
+ for i, m in enumerate(lst_m):
+ B[:, i] = gauss(n, m=m, s=5)
# loss matrix and normalization
- M=ot.dist(x.reshape((n,1)),x.reshape((n,1)),'euclidean')
- M/=M.max()
- M2=ot.dist(x.reshape((n,1)),x.reshape((n,1)),'sqeuclidean')
- M2/=M2.max()
+ M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)), 'euclidean')
+ M /= M.max()
+ M2 = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)), 'sqeuclidean')
+ M2 /= M2.max()
+
+
+
+
+
+
+
+Plot data
+---------
+
+
+
+.. code-block:: python
+
+
#%% plot the distributions
pl.figure(1)
- pl.subplot(2,1,1)
- pl.plot(x,a,'b',label='Source distribution')
+ pl.subplot(2, 1, 1)
+ pl.plot(x, a, 'b', label='Source distribution')
pl.title('Source distribution')
- pl.subplot(2,1,2)
- pl.plot(x,B,label='Target distributions')
+ pl.subplot(2, 1, 2)
+ pl.plot(x, B, label='Target distributions')
pl.title('Target distributions')
+ pl.tight_layout()
+
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_compute_emd_001.png
+ :align: center
+
+
+
+
+Compute EMD for the different losses
+------------------------------------
+
+
+
+.. code-block:: python
+
#%% Compute and plot distributions and loss matrix
- d_emd=ot.emd2(a,B,M) # direct computation of EMD
- d_emd2=ot.emd2(a,B,M2) # direct computation of EMD with loss M3
+ d_emd = ot.emd2(a, B, M) # direct computation of EMD
+ d_emd2 = ot.emd2(a, B, M2) # direct computation of EMD with loss M2
pl.figure(2)
- pl.plot(d_emd,label='Euclidean EMD')
- pl.plot(d_emd2,label='Squared Euclidean EMD')
+ pl.plot(d_emd, label='Euclidean EMD')
+ pl.plot(d_emd2, label='Squared Euclidean EMD')
pl.title('EMD distances')
pl.legend()
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_compute_emd_003.png
+ :align: center
+
+
+
+
+Compute Sinkhorn for the different losses
+-----------------------------------------
+
+
+
+.. code-block:: python
+
+
#%%
- reg=1e-2
- d_sinkhorn=ot.sinkhorn(a,B,M,reg)
- d_sinkhorn2=ot.sinkhorn(a,B,M2,reg)
+ reg = 1e-2
+ d_sinkhorn = ot.sinkhorn2(a, B, M, reg)
+ d_sinkhorn2 = ot.sinkhorn2(a, B, M2, reg)
pl.figure(2)
pl.clf()
- pl.plot(d_emd,label='Euclidean EMD')
- pl.plot(d_emd2,label='Squared Euclidean EMD')
- pl.plot(d_sinkhorn,'+',label='Euclidean Sinkhorn')
- pl.plot(d_sinkhorn2,'+',label='Squared Euclidean Sinkhorn')
+ pl.plot(d_emd, label='Euclidean EMD')
+ pl.plot(d_emd2, label='Squared Euclidean EMD')
+ pl.plot(d_sinkhorn, '+', label='Euclidean Sinkhorn')
+ pl.plot(d_sinkhorn2, '+', label='Squared Euclidean Sinkhorn')
pl.title('EMD distances')
pl.legend()
-**Total running time of the script:** ( 0 minutes 0.521 seconds)
+
+ pl.show()
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_compute_emd_004.png
+ :align: center
+
+
+
+
+**Total running time of the script:** ( 0 minutes 0.697 seconds)
diff --git a/docs/source/auto_examples/plot_gromov.ipynb b/docs/source/auto_examples/plot_gromov.ipynb
new file mode 100644
index 0000000..865848e
--- /dev/null
+++ b/docs/source/auto_examples/plot_gromov.ipynb
@@ -0,0 +1,126 @@
+{
+ "nbformat_minor": 0,
+ "nbformat": 4,
+ "cells": [
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "%matplotlib inline"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "\n# Gromov-Wasserstein example\n\n\nThis example is designed to show how to use the Gromov-Wassertsein distance\ncomputation in POT.\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# Author: Erwan Vautier <erwan.vautier@gmail.com>\r\n# Nicolas Courty <ncourty@irisa.fr>\r\n#\r\n# License: MIT License\r\n\r\nimport scipy as sp\r\nimport numpy as np\r\nimport matplotlib.pylab as pl\r\nfrom mpl_toolkits.mplot3d import Axes3D # noqa\r\nimport ot"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Sample two Gaussian distributions (2D and 3D)\r\n ---------------------------------------------\r\n\r\n The Gromov-Wasserstein distance allows to compute distances with samples that\r\n do not belong to the same metric space. For demonstration purpose, we sample\r\n two Gaussian distributions in 2- and 3-dimensional spaces.\r\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "n_samples = 30 # nb samples\r\n\r\nmu_s = np.array([0, 0])\r\ncov_s = np.array([[1, 0], [0, 1]])\r\n\r\nmu_t = np.array([4, 4, 4])\r\ncov_t = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])\r\n\r\n\r\nxs = ot.datasets.get_2D_samples_gauss(n_samples, mu_s, cov_s)\r\nP = sp.linalg.sqrtm(cov_t)\r\nxt = np.random.randn(n_samples, 3).dot(P) + mu_t"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Plotting the distributions\r\n--------------------------\r\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "fig = pl.figure()\r\nax1 = fig.add_subplot(121)\r\nax1.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\r\nax2 = fig.add_subplot(122, projection='3d')\r\nax2.scatter(xt[:, 0], xt[:, 1], xt[:, 2], color='r')\r\npl.show()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Compute distance kernels, normalize them and then display\r\n---------------------------------------------------------\r\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "C1 = sp.spatial.distance.cdist(xs, xs)\r\nC2 = sp.spatial.distance.cdist(xt, xt)\r\n\r\nC1 /= C1.max()\r\nC2 /= C2.max()\r\n\r\npl.figure()\r\npl.subplot(121)\r\npl.imshow(C1)\r\npl.subplot(122)\r\npl.imshow(C2)\r\npl.show()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Compute Gromov-Wasserstein plans and distance\r\n---------------------------------------------\r\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "p = ot.unif(n_samples)\r\nq = ot.unif(n_samples)\r\n\r\ngw = ot.gromov_wasserstein(C1, C2, p, q, 'square_loss', epsilon=5e-4)\r\ngw_dist = ot.gromov_wasserstein2(C1, C2, p, q, 'square_loss', epsilon=5e-4)\r\n\r\nprint('Gromov-Wasserstein distances between the distribution: ' + str(gw_dist))\r\n\r\npl.figure()\r\npl.imshow(gw, cmap='jet')\r\npl.colorbar()\r\npl.show()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "name": "python2",
+ "language": "python"
+ },
+ "language_info": {
+ "mimetype": "text/x-python",
+ "nbconvert_exporter": "python",
+ "name": "python",
+ "file_extension": ".py",
+ "version": "2.7.12",
+ "pygments_lexer": "ipython2",
+ "codemirror_mode": {
+ "version": 2,
+ "name": "ipython"
+ }
+ }
+ }
+} \ No newline at end of file
diff --git a/docs/source/auto_examples/plot_gromov.py b/docs/source/auto_examples/plot_gromov.py
new file mode 100644
index 0000000..d3f724c
--- /dev/null
+++ b/docs/source/auto_examples/plot_gromov.py
@@ -0,0 +1,93 @@
+# -*- coding: utf-8 -*-
+"""
+==========================
+Gromov-Wasserstein example
+==========================
+
+This example is designed to show how to use the Gromov-Wassertsein distance
+computation in POT.
+"""
+
+# Author: Erwan Vautier <erwan.vautier@gmail.com>
+# Nicolas Courty <ncourty@irisa.fr>
+#
+# License: MIT License
+
+import scipy as sp
+import numpy as np
+import matplotlib.pylab as pl
+from mpl_toolkits.mplot3d import Axes3D # noqa
+import ot
+
+
+##############################################################################
+# Sample two Gaussian distributions (2D and 3D)
+# ---------------------------------------------
+#
+# The Gromov-Wasserstein distance allows to compute distances with samples that
+# do not belong to the same metric space. For demonstration purpose, we sample
+# two Gaussian distributions in 2- and 3-dimensional spaces.
+
+
+n_samples = 30 # nb samples
+
+mu_s = np.array([0, 0])
+cov_s = np.array([[1, 0], [0, 1]])
+
+mu_t = np.array([4, 4, 4])
+cov_t = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
+
+
+xs = ot.datasets.get_2D_samples_gauss(n_samples, mu_s, cov_s)
+P = sp.linalg.sqrtm(cov_t)
+xt = np.random.randn(n_samples, 3).dot(P) + mu_t
+
+
+##############################################################################
+# Plotting the distributions
+# --------------------------
+
+
+fig = pl.figure()
+ax1 = fig.add_subplot(121)
+ax1.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+ax2 = fig.add_subplot(122, projection='3d')
+ax2.scatter(xt[:, 0], xt[:, 1], xt[:, 2], color='r')
+pl.show()
+
+
+##############################################################################
+# Compute distance kernels, normalize them and then display
+# ---------------------------------------------------------
+
+
+C1 = sp.spatial.distance.cdist(xs, xs)
+C2 = sp.spatial.distance.cdist(xt, xt)
+
+C1 /= C1.max()
+C2 /= C2.max()
+
+pl.figure()
+pl.subplot(121)
+pl.imshow(C1)
+pl.subplot(122)
+pl.imshow(C2)
+pl.show()
+
+##############################################################################
+# Compute Gromov-Wasserstein plans and distance
+# ---------------------------------------------
+
+
+p = ot.unif(n_samples)
+q = ot.unif(n_samples)
+
+gw = ot.gromov_wasserstein(C1, C2, p, q, 'square_loss', epsilon=5e-4)
+gw_dist = ot.gromov_wasserstein2(C1, C2, p, q, 'square_loss', epsilon=5e-4)
+
+print('Gromov-Wasserstein distances between the distribution: ' + str(gw_dist))
+
+pl.figure()
+pl.imshow(gw, cmap='jet')
+pl.colorbar()
+pl.show()
diff --git a/docs/source/auto_examples/plot_gromov.rst b/docs/source/auto_examples/plot_gromov.rst
new file mode 100644
index 0000000..65cf4e4
--- /dev/null
+++ b/docs/source/auto_examples/plot_gromov.rst
@@ -0,0 +1,180 @@
+
+
+.. _sphx_glr_auto_examples_plot_gromov.py:
+
+
+==========================
+Gromov-Wasserstein example
+==========================
+
+This example is designed to show how to use the Gromov-Wassertsein distance
+computation in POT.
+
+
+
+.. code-block:: python
+
+
+ # Author: Erwan Vautier <erwan.vautier@gmail.com>
+ # Nicolas Courty <ncourty@irisa.fr>
+ #
+ # License: MIT License
+
+ import scipy as sp
+ import numpy as np
+ import matplotlib.pylab as pl
+ from mpl_toolkits.mplot3d import Axes3D # noqa
+ import ot
+
+
+
+
+
+
+
+
+Sample two Gaussian distributions (2D and 3D)
+ ---------------------------------------------
+
+ The Gromov-Wasserstein distance allows to compute distances with samples that
+ do not belong to the same metric space. For demonstration purpose, we sample
+ two Gaussian distributions in 2- and 3-dimensional spaces.
+
+
+
+.. code-block:: python
+
+
+
+ n_samples = 30 # nb samples
+
+ mu_s = np.array([0, 0])
+ cov_s = np.array([[1, 0], [0, 1]])
+
+ mu_t = np.array([4, 4, 4])
+ cov_t = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
+
+
+ xs = ot.datasets.get_2D_samples_gauss(n_samples, mu_s, cov_s)
+ P = sp.linalg.sqrtm(cov_t)
+ xt = np.random.randn(n_samples, 3).dot(P) + mu_t
+
+
+
+
+
+
+
+
+Plotting the distributions
+--------------------------
+
+
+
+.. code-block:: python
+
+
+
+ fig = pl.figure()
+ ax1 = fig.add_subplot(121)
+ ax1.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+ ax2 = fig.add_subplot(122, projection='3d')
+ ax2.scatter(xt[:, 0], xt[:, 1], xt[:, 2], color='r')
+ pl.show()
+
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_gromov_001.png
+ :align: center
+
+
+
+
+Compute distance kernels, normalize them and then display
+---------------------------------------------------------
+
+
+
+.. code-block:: python
+
+
+
+ C1 = sp.spatial.distance.cdist(xs, xs)
+ C2 = sp.spatial.distance.cdist(xt, xt)
+
+ C1 /= C1.max()
+ C2 /= C2.max()
+
+ pl.figure()
+ pl.subplot(121)
+ pl.imshow(C1)
+ pl.subplot(122)
+ pl.imshow(C2)
+ pl.show()
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_gromov_002.png
+ :align: center
+
+
+
+
+Compute Gromov-Wasserstein plans and distance
+---------------------------------------------
+
+
+
+.. code-block:: python
+
+
+
+ p = ot.unif(n_samples)
+ q = ot.unif(n_samples)
+
+ gw = ot.gromov_wasserstein(C1, C2, p, q, 'square_loss', epsilon=5e-4)
+ gw_dist = ot.gromov_wasserstein2(C1, C2, p, q, 'square_loss', epsilon=5e-4)
+
+ print('Gromov-Wasserstein distances between the distribution: ' + str(gw_dist))
+
+ pl.figure()
+ pl.imshow(gw, cmap='jet')
+ pl.colorbar()
+ pl.show()
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_gromov_003.png
+ :align: center
+
+
+.. rst-class:: sphx-glr-script-out
+
+ Out::
+
+ Gromov-Wasserstein distances between the distribution: 0.225058076974
+
+
+**Total running time of the script:** ( 0 minutes 4.070 seconds)
+
+
+
+.. container:: sphx-glr-footer
+
+
+ .. container:: sphx-glr-download
+
+ :download:`Download Python source code: plot_gromov.py <plot_gromov.py>`
+
+
+
+ .. container:: sphx-glr-download
+
+ :download:`Download Jupyter notebook: plot_gromov.ipynb <plot_gromov.ipynb>`
+
+.. rst-class:: sphx-glr-signature
+
+ `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
diff --git a/docs/source/auto_examples/plot_gromov_barycenter.ipynb b/docs/source/auto_examples/plot_gromov_barycenter.ipynb
new file mode 100644
index 0000000..d38dfbb
--- /dev/null
+++ b/docs/source/auto_examples/plot_gromov_barycenter.ipynb
@@ -0,0 +1,126 @@
+{
+ "nbformat_minor": 0,
+ "nbformat": 4,
+ "cells": [
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "%matplotlib inline"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "\n# Gromov-Wasserstein Barycenter example\n\n\nThis example is designed to show how to use the Gromov-Wasserstein distance\ncomputation in POT.\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# Author: Erwan Vautier <erwan.vautier@gmail.com>\r\n# Nicolas Courty <ncourty@irisa.fr>\r\n#\r\n# License: MIT License\r\n\r\n\r\nimport numpy as np\r\nimport scipy as sp\r\n\r\nimport scipy.ndimage as spi\r\nimport matplotlib.pylab as pl\r\nfrom sklearn import manifold\r\nfrom sklearn.decomposition import PCA\r\n\r\nimport ot"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Smacof MDS\r\n ----------\r\n\r\n This function allows to find an embedding of points given a dissimilarity matrix\r\n that will be given by the output of the algorithm\r\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "def smacof_mds(C, dim, max_iter=3000, eps=1e-9):\r\n \"\"\"\r\n Returns an interpolated point cloud following the dissimilarity matrix C\r\n using SMACOF multidimensional scaling (MDS) in specific dimensionned\r\n target space\r\n\r\n Parameters\r\n ----------\r\n C : ndarray, shape (ns, ns)\r\n dissimilarity matrix\r\n dim : int\r\n dimension of the targeted space\r\n max_iter : int\r\n Maximum number of iterations of the SMACOF algorithm for a single run\r\n eps : float\r\n relative tolerance w.r.t stress to declare converge\r\n\r\n Returns\r\n -------\r\n npos : ndarray, shape (R, dim)\r\n Embedded coordinates of the interpolated point cloud (defined with\r\n one isometry)\r\n \"\"\"\r\n\r\n rng = np.random.RandomState(seed=3)\r\n\r\n mds = manifold.MDS(\r\n dim,\r\n max_iter=max_iter,\r\n eps=1e-9,\r\n dissimilarity='precomputed',\r\n n_init=1)\r\n pos = mds.fit(C).embedding_\r\n\r\n nmds = manifold.MDS(\r\n 2,\r\n max_iter=max_iter,\r\n eps=1e-9,\r\n dissimilarity=\"precomputed\",\r\n random_state=rng,\r\n n_init=1)\r\n npos = nmds.fit_transform(C, init=pos)\r\n\r\n return npos"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Data preparation\r\n ----------------\r\n\r\n The four distributions are constructed from 4 simple images\r\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "def im2mat(I):\r\n \"\"\"Converts and image to matrix (one pixel per line)\"\"\"\r\n return I.reshape((I.shape[0] * I.shape[1], I.shape[2]))\r\n\r\n\r\nsquare = spi.imread('../data/square.png').astype(np.float64)[:, :, 2] / 256\r\ncross = spi.imread('../data/cross.png').astype(np.float64)[:, :, 2] / 256\r\ntriangle = spi.imread('../data/triangle.png').astype(np.float64)[:, :, 2] / 256\r\nstar = spi.imread('../data/star.png').astype(np.float64)[:, :, 2] / 256\r\n\r\nshapes = [square, cross, triangle, star]\r\n\r\nS = 4\r\nxs = [[] for i in range(S)]\r\n\r\n\r\nfor nb in range(4):\r\n for i in range(8):\r\n for j in range(8):\r\n if shapes[nb][i, j] < 0.95:\r\n xs[nb].append([j, 8 - i])\r\n\r\nxs = np.array([np.array(xs[0]), np.array(xs[1]),\r\n np.array(xs[2]), np.array(xs[3])])"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Barycenter computation\r\n----------------------\r\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "ns = [len(xs[s]) for s in range(S)]\r\nn_samples = 30\r\n\r\n\"\"\"Compute all distances matrices for the four shapes\"\"\"\r\nCs = [sp.spatial.distance.cdist(xs[s], xs[s]) for s in range(S)]\r\nCs = [cs / cs.max() for cs in Cs]\r\n\r\nps = [ot.unif(ns[s]) for s in range(S)]\r\np = ot.unif(n_samples)\r\n\r\n\r\nlambdast = [[float(i) / 3, float(3 - i) / 3] for i in [1, 2]]\r\n\r\nCt01 = [0 for i in range(2)]\r\nfor i in range(2):\r\n Ct01[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[0], Cs[1]],\r\n [ps[0], ps[1]\r\n ], p, lambdast[i], 'square_loss', 5e-4,\r\n max_iter=100, tol=1e-3)\r\n\r\nCt02 = [0 for i in range(2)]\r\nfor i in range(2):\r\n Ct02[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[0], Cs[2]],\r\n [ps[0], ps[2]\r\n ], p, lambdast[i], 'square_loss', 5e-4,\r\n max_iter=100, tol=1e-3)\r\n\r\nCt13 = [0 for i in range(2)]\r\nfor i in range(2):\r\n Ct13[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[1], Cs[3]],\r\n [ps[1], ps[3]\r\n ], p, lambdast[i], 'square_loss', 5e-4,\r\n max_iter=100, tol=1e-3)\r\n\r\nCt23 = [0 for i in range(2)]\r\nfor i in range(2):\r\n Ct23[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[2], Cs[3]],\r\n [ps[2], ps[3]\r\n ], p, lambdast[i], 'square_loss', 5e-4,\r\n max_iter=100, tol=1e-3)"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Visualization\r\n -------------\r\n\r\n The PCA helps in getting consistency between the rotations\r\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "clf = PCA(n_components=2)\r\nnpos = [0, 0, 0, 0]\r\nnpos = [smacof_mds(Cs[s], 2) for s in range(S)]\r\n\r\nnpost01 = [0, 0]\r\nnpost01 = [smacof_mds(Ct01[s], 2) for s in range(2)]\r\nnpost01 = [clf.fit_transform(npost01[s]) for s in range(2)]\r\n\r\nnpost02 = [0, 0]\r\nnpost02 = [smacof_mds(Ct02[s], 2) for s in range(2)]\r\nnpost02 = [clf.fit_transform(npost02[s]) for s in range(2)]\r\n\r\nnpost13 = [0, 0]\r\nnpost13 = [smacof_mds(Ct13[s], 2) for s in range(2)]\r\nnpost13 = [clf.fit_transform(npost13[s]) for s in range(2)]\r\n\r\nnpost23 = [0, 0]\r\nnpost23 = [smacof_mds(Ct23[s], 2) for s in range(2)]\r\nnpost23 = [clf.fit_transform(npost23[s]) for s in range(2)]\r\n\r\n\r\nfig = pl.figure(figsize=(10, 10))\r\n\r\nax1 = pl.subplot2grid((4, 4), (0, 0))\r\npl.xlim((-1, 1))\r\npl.ylim((-1, 1))\r\nax1.scatter(npos[0][:, 0], npos[0][:, 1], color='r')\r\n\r\nax2 = pl.subplot2grid((4, 4), (0, 1))\r\npl.xlim((-1, 1))\r\npl.ylim((-1, 1))\r\nax2.scatter(npost01[1][:, 0], npost01[1][:, 1], color='b')\r\n\r\nax3 = pl.subplot2grid((4, 4), (0, 2))\r\npl.xlim((-1, 1))\r\npl.ylim((-1, 1))\r\nax3.scatter(npost01[0][:, 0], npost01[0][:, 1], color='b')\r\n\r\nax4 = pl.subplot2grid((4, 4), (0, 3))\r\npl.xlim((-1, 1))\r\npl.ylim((-1, 1))\r\nax4.scatter(npos[1][:, 0], npos[1][:, 1], color='r')\r\n\r\nax5 = pl.subplot2grid((4, 4), (1, 0))\r\npl.xlim((-1, 1))\r\npl.ylim((-1, 1))\r\nax5.scatter(npost02[1][:, 0], npost02[1][:, 1], color='b')\r\n\r\nax6 = pl.subplot2grid((4, 4), (1, 3))\r\npl.xlim((-1, 1))\r\npl.ylim((-1, 1))\r\nax6.scatter(npost13[1][:, 0], npost13[1][:, 1], color='b')\r\n\r\nax7 = pl.subplot2grid((4, 4), (2, 0))\r\npl.xlim((-1, 1))\r\npl.ylim((-1, 1))\r\nax7.scatter(npost02[0][:, 0], npost02[0][:, 1], color='b')\r\n\r\nax8 = pl.subplot2grid((4, 4), (2, 3))\r\npl.xlim((-1, 1))\r\npl.ylim((-1, 1))\r\nax8.scatter(npost13[0][:, 0], npost13[0][:, 1], color='b')\r\n\r\nax9 = pl.subplot2grid((4, 4), (3, 0))\r\npl.xlim((-1, 1))\r\npl.ylim((-1, 1))\r\nax9.scatter(npos[2][:, 0], npos[2][:, 1], color='r')\r\n\r\nax10 = pl.subplot2grid((4, 4), (3, 1))\r\npl.xlim((-1, 1))\r\npl.ylim((-1, 1))\r\nax10.scatter(npost23[1][:, 0], npost23[1][:, 1], color='b')\r\n\r\nax11 = pl.subplot2grid((4, 4), (3, 2))\r\npl.xlim((-1, 1))\r\npl.ylim((-1, 1))\r\nax11.scatter(npost23[0][:, 0], npost23[0][:, 1], color='b')\r\n\r\nax12 = pl.subplot2grid((4, 4), (3, 3))\r\npl.xlim((-1, 1))\r\npl.ylim((-1, 1))\r\nax12.scatter(npos[3][:, 0], npos[3][:, 1], color='r')"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "name": "python2",
+ "language": "python"
+ },
+ "language_info": {
+ "mimetype": "text/x-python",
+ "nbconvert_exporter": "python",
+ "name": "python",
+ "file_extension": ".py",
+ "version": "2.7.12",
+ "pygments_lexer": "ipython2",
+ "codemirror_mode": {
+ "version": 2,
+ "name": "ipython"
+ }
+ }
+ }
+} \ No newline at end of file
diff --git a/docs/source/auto_examples/plot_gromov_barycenter.py b/docs/source/auto_examples/plot_gromov_barycenter.py
new file mode 100644
index 0000000..180b0cf
--- /dev/null
+++ b/docs/source/auto_examples/plot_gromov_barycenter.py
@@ -0,0 +1,248 @@
+# -*- coding: utf-8 -*-
+"""
+=====================================
+Gromov-Wasserstein Barycenter example
+=====================================
+
+This example is designed to show how to use the Gromov-Wasserstein distance
+computation in POT.
+"""
+
+# Author: Erwan Vautier <erwan.vautier@gmail.com>
+# Nicolas Courty <ncourty@irisa.fr>
+#
+# License: MIT License
+
+
+import numpy as np
+import scipy as sp
+
+import scipy.ndimage as spi
+import matplotlib.pylab as pl
+from sklearn import manifold
+from sklearn.decomposition import PCA
+
+import ot
+
+##############################################################################
+# Smacof MDS
+# ----------
+#
+# This function allows to find an embedding of points given a dissimilarity matrix
+# that will be given by the output of the algorithm
+
+
+def smacof_mds(C, dim, max_iter=3000, eps=1e-9):
+ """
+ Returns an interpolated point cloud following the dissimilarity matrix C
+ using SMACOF multidimensional scaling (MDS) in specific dimensionned
+ target space
+
+ Parameters
+ ----------
+ C : ndarray, shape (ns, ns)
+ dissimilarity matrix
+ dim : int
+ dimension of the targeted space
+ max_iter : int
+ Maximum number of iterations of the SMACOF algorithm for a single run
+ eps : float
+ relative tolerance w.r.t stress to declare converge
+
+ Returns
+ -------
+ npos : ndarray, shape (R, dim)
+ Embedded coordinates of the interpolated point cloud (defined with
+ one isometry)
+ """
+
+ rng = np.random.RandomState(seed=3)
+
+ mds = manifold.MDS(
+ dim,
+ max_iter=max_iter,
+ eps=1e-9,
+ dissimilarity='precomputed',
+ n_init=1)
+ pos = mds.fit(C).embedding_
+
+ nmds = manifold.MDS(
+ 2,
+ max_iter=max_iter,
+ eps=1e-9,
+ dissimilarity="precomputed",
+ random_state=rng,
+ n_init=1)
+ npos = nmds.fit_transform(C, init=pos)
+
+ return npos
+
+
+##############################################################################
+# Data preparation
+# ----------------
+#
+# The four distributions are constructed from 4 simple images
+
+
+def im2mat(I):
+ """Converts and image to matrix (one pixel per line)"""
+ return I.reshape((I.shape[0] * I.shape[1], I.shape[2]))
+
+
+square = spi.imread('../data/square.png').astype(np.float64)[:, :, 2] / 256
+cross = spi.imread('../data/cross.png').astype(np.float64)[:, :, 2] / 256
+triangle = spi.imread('../data/triangle.png').astype(np.float64)[:, :, 2] / 256
+star = spi.imread('../data/star.png').astype(np.float64)[:, :, 2] / 256
+
+shapes = [square, cross, triangle, star]
+
+S = 4
+xs = [[] for i in range(S)]
+
+
+for nb in range(4):
+ for i in range(8):
+ for j in range(8):
+ if shapes[nb][i, j] < 0.95:
+ xs[nb].append([j, 8 - i])
+
+xs = np.array([np.array(xs[0]), np.array(xs[1]),
+ np.array(xs[2]), np.array(xs[3])])
+
+##############################################################################
+# Barycenter computation
+# ----------------------
+
+
+ns = [len(xs[s]) for s in range(S)]
+n_samples = 30
+
+"""Compute all distances matrices for the four shapes"""
+Cs = [sp.spatial.distance.cdist(xs[s], xs[s]) for s in range(S)]
+Cs = [cs / cs.max() for cs in Cs]
+
+ps = [ot.unif(ns[s]) for s in range(S)]
+p = ot.unif(n_samples)
+
+
+lambdast = [[float(i) / 3, float(3 - i) / 3] for i in [1, 2]]
+
+Ct01 = [0 for i in range(2)]
+for i in range(2):
+ Ct01[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[0], Cs[1]],
+ [ps[0], ps[1]
+ ], p, lambdast[i], 'square_loss', 5e-4,
+ max_iter=100, tol=1e-3)
+
+Ct02 = [0 for i in range(2)]
+for i in range(2):
+ Ct02[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[0], Cs[2]],
+ [ps[0], ps[2]
+ ], p, lambdast[i], 'square_loss', 5e-4,
+ max_iter=100, tol=1e-3)
+
+Ct13 = [0 for i in range(2)]
+for i in range(2):
+ Ct13[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[1], Cs[3]],
+ [ps[1], ps[3]
+ ], p, lambdast[i], 'square_loss', 5e-4,
+ max_iter=100, tol=1e-3)
+
+Ct23 = [0 for i in range(2)]
+for i in range(2):
+ Ct23[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[2], Cs[3]],
+ [ps[2], ps[3]
+ ], p, lambdast[i], 'square_loss', 5e-4,
+ max_iter=100, tol=1e-3)
+
+
+##############################################################################
+# Visualization
+# -------------
+#
+# The PCA helps in getting consistency between the rotations
+
+
+clf = PCA(n_components=2)
+npos = [0, 0, 0, 0]
+npos = [smacof_mds(Cs[s], 2) for s in range(S)]
+
+npost01 = [0, 0]
+npost01 = [smacof_mds(Ct01[s], 2) for s in range(2)]
+npost01 = [clf.fit_transform(npost01[s]) for s in range(2)]
+
+npost02 = [0, 0]
+npost02 = [smacof_mds(Ct02[s], 2) for s in range(2)]
+npost02 = [clf.fit_transform(npost02[s]) for s in range(2)]
+
+npost13 = [0, 0]
+npost13 = [smacof_mds(Ct13[s], 2) for s in range(2)]
+npost13 = [clf.fit_transform(npost13[s]) for s in range(2)]
+
+npost23 = [0, 0]
+npost23 = [smacof_mds(Ct23[s], 2) for s in range(2)]
+npost23 = [clf.fit_transform(npost23[s]) for s in range(2)]
+
+
+fig = pl.figure(figsize=(10, 10))
+
+ax1 = pl.subplot2grid((4, 4), (0, 0))
+pl.xlim((-1, 1))
+pl.ylim((-1, 1))
+ax1.scatter(npos[0][:, 0], npos[0][:, 1], color='r')
+
+ax2 = pl.subplot2grid((4, 4), (0, 1))
+pl.xlim((-1, 1))
+pl.ylim((-1, 1))
+ax2.scatter(npost01[1][:, 0], npost01[1][:, 1], color='b')
+
+ax3 = pl.subplot2grid((4, 4), (0, 2))
+pl.xlim((-1, 1))
+pl.ylim((-1, 1))
+ax3.scatter(npost01[0][:, 0], npost01[0][:, 1], color='b')
+
+ax4 = pl.subplot2grid((4, 4), (0, 3))
+pl.xlim((-1, 1))
+pl.ylim((-1, 1))
+ax4.scatter(npos[1][:, 0], npos[1][:, 1], color='r')
+
+ax5 = pl.subplot2grid((4, 4), (1, 0))
+pl.xlim((-1, 1))
+pl.ylim((-1, 1))
+ax5.scatter(npost02[1][:, 0], npost02[1][:, 1], color='b')
+
+ax6 = pl.subplot2grid((4, 4), (1, 3))
+pl.xlim((-1, 1))
+pl.ylim((-1, 1))
+ax6.scatter(npost13[1][:, 0], npost13[1][:, 1], color='b')
+
+ax7 = pl.subplot2grid((4, 4), (2, 0))
+pl.xlim((-1, 1))
+pl.ylim((-1, 1))
+ax7.scatter(npost02[0][:, 0], npost02[0][:, 1], color='b')
+
+ax8 = pl.subplot2grid((4, 4), (2, 3))
+pl.xlim((-1, 1))
+pl.ylim((-1, 1))
+ax8.scatter(npost13[0][:, 0], npost13[0][:, 1], color='b')
+
+ax9 = pl.subplot2grid((4, 4), (3, 0))
+pl.xlim((-1, 1))
+pl.ylim((-1, 1))
+ax9.scatter(npos[2][:, 0], npos[2][:, 1], color='r')
+
+ax10 = pl.subplot2grid((4, 4), (3, 1))
+pl.xlim((-1, 1))
+pl.ylim((-1, 1))
+ax10.scatter(npost23[1][:, 0], npost23[1][:, 1], color='b')
+
+ax11 = pl.subplot2grid((4, 4), (3, 2))
+pl.xlim((-1, 1))
+pl.ylim((-1, 1))
+ax11.scatter(npost23[0][:, 0], npost23[0][:, 1], color='b')
+
+ax12 = pl.subplot2grid((4, 4), (3, 3))
+pl.xlim((-1, 1))
+pl.ylim((-1, 1))
+ax12.scatter(npos[3][:, 0], npos[3][:, 1], color='r')
diff --git a/docs/source/auto_examples/plot_gromov_barycenter.rst b/docs/source/auto_examples/plot_gromov_barycenter.rst
new file mode 100644
index 0000000..ca2d4e9
--- /dev/null
+++ b/docs/source/auto_examples/plot_gromov_barycenter.rst
@@ -0,0 +1,324 @@
+
+
+.. _sphx_glr_auto_examples_plot_gromov_barycenter.py:
+
+
+=====================================
+Gromov-Wasserstein Barycenter example
+=====================================
+
+This example is designed to show how to use the Gromov-Wasserstein distance
+computation in POT.
+
+
+
+.. code-block:: python
+
+
+ # Author: Erwan Vautier <erwan.vautier@gmail.com>
+ # Nicolas Courty <ncourty@irisa.fr>
+ #
+ # License: MIT License
+
+
+ import numpy as np
+ import scipy as sp
+
+ import scipy.ndimage as spi
+ import matplotlib.pylab as pl
+ from sklearn import manifold
+ from sklearn.decomposition import PCA
+
+ import ot
+
+
+
+
+
+
+
+Smacof MDS
+ ----------
+
+ This function allows to find an embedding of points given a dissimilarity matrix
+ that will be given by the output of the algorithm
+
+
+
+.. code-block:: python
+
+
+
+ def smacof_mds(C, dim, max_iter=3000, eps=1e-9):
+ """
+ Returns an interpolated point cloud following the dissimilarity matrix C
+ using SMACOF multidimensional scaling (MDS) in specific dimensionned
+ target space
+
+ Parameters
+ ----------
+ C : ndarray, shape (ns, ns)
+ dissimilarity matrix
+ dim : int
+ dimension of the targeted space
+ max_iter : int
+ Maximum number of iterations of the SMACOF algorithm for a single run
+ eps : float
+ relative tolerance w.r.t stress to declare converge
+
+ Returns
+ -------
+ npos : ndarray, shape (R, dim)
+ Embedded coordinates of the interpolated point cloud (defined with
+ one isometry)
+ """
+
+ rng = np.random.RandomState(seed=3)
+
+ mds = manifold.MDS(
+ dim,
+ max_iter=max_iter,
+ eps=1e-9,
+ dissimilarity='precomputed',
+ n_init=1)
+ pos = mds.fit(C).embedding_
+
+ nmds = manifold.MDS(
+ 2,
+ max_iter=max_iter,
+ eps=1e-9,
+ dissimilarity="precomputed",
+ random_state=rng,
+ n_init=1)
+ npos = nmds.fit_transform(C, init=pos)
+
+ return npos
+
+
+
+
+
+
+
+
+Data preparation
+ ----------------
+
+ The four distributions are constructed from 4 simple images
+
+
+
+.. code-block:: python
+
+
+
+ def im2mat(I):
+ """Converts and image to matrix (one pixel per line)"""
+ return I.reshape((I.shape[0] * I.shape[1], I.shape[2]))
+
+
+ square = spi.imread('../data/square.png').astype(np.float64)[:, :, 2] / 256
+ cross = spi.imread('../data/cross.png').astype(np.float64)[:, :, 2] / 256
+ triangle = spi.imread('../data/triangle.png').astype(np.float64)[:, :, 2] / 256
+ star = spi.imread('../data/star.png').astype(np.float64)[:, :, 2] / 256
+
+ shapes = [square, cross, triangle, star]
+
+ S = 4
+ xs = [[] for i in range(S)]
+
+
+ for nb in range(4):
+ for i in range(8):
+ for j in range(8):
+ if shapes[nb][i, j] < 0.95:
+ xs[nb].append([j, 8 - i])
+
+ xs = np.array([np.array(xs[0]), np.array(xs[1]),
+ np.array(xs[2]), np.array(xs[3])])
+
+
+
+
+
+
+
+Barycenter computation
+----------------------
+
+
+
+.. code-block:: python
+
+
+
+ ns = [len(xs[s]) for s in range(S)]
+ n_samples = 30
+
+ """Compute all distances matrices for the four shapes"""
+ Cs = [sp.spatial.distance.cdist(xs[s], xs[s]) for s in range(S)]
+ Cs = [cs / cs.max() for cs in Cs]
+
+ ps = [ot.unif(ns[s]) for s in range(S)]
+ p = ot.unif(n_samples)
+
+
+ lambdast = [[float(i) / 3, float(3 - i) / 3] for i in [1, 2]]
+
+ Ct01 = [0 for i in range(2)]
+ for i in range(2):
+ Ct01[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[0], Cs[1]],
+ [ps[0], ps[1]
+ ], p, lambdast[i], 'square_loss', 5e-4,
+ max_iter=100, tol=1e-3)
+
+ Ct02 = [0 for i in range(2)]
+ for i in range(2):
+ Ct02[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[0], Cs[2]],
+ [ps[0], ps[2]
+ ], p, lambdast[i], 'square_loss', 5e-4,
+ max_iter=100, tol=1e-3)
+
+ Ct13 = [0 for i in range(2)]
+ for i in range(2):
+ Ct13[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[1], Cs[3]],
+ [ps[1], ps[3]
+ ], p, lambdast[i], 'square_loss', 5e-4,
+ max_iter=100, tol=1e-3)
+
+ Ct23 = [0 for i in range(2)]
+ for i in range(2):
+ Ct23[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[2], Cs[3]],
+ [ps[2], ps[3]
+ ], p, lambdast[i], 'square_loss', 5e-4,
+ max_iter=100, tol=1e-3)
+
+
+
+
+
+
+
+
+Visualization
+ -------------
+
+ The PCA helps in getting consistency between the rotations
+
+
+
+.. code-block:: python
+
+
+
+ clf = PCA(n_components=2)
+ npos = [0, 0, 0, 0]
+ npos = [smacof_mds(Cs[s], 2) for s in range(S)]
+
+ npost01 = [0, 0]
+ npost01 = [smacof_mds(Ct01[s], 2) for s in range(2)]
+ npost01 = [clf.fit_transform(npost01[s]) for s in range(2)]
+
+ npost02 = [0, 0]
+ npost02 = [smacof_mds(Ct02[s], 2) for s in range(2)]
+ npost02 = [clf.fit_transform(npost02[s]) for s in range(2)]
+
+ npost13 = [0, 0]
+ npost13 = [smacof_mds(Ct13[s], 2) for s in range(2)]
+ npost13 = [clf.fit_transform(npost13[s]) for s in range(2)]
+
+ npost23 = [0, 0]
+ npost23 = [smacof_mds(Ct23[s], 2) for s in range(2)]
+ npost23 = [clf.fit_transform(npost23[s]) for s in range(2)]
+
+
+ fig = pl.figure(figsize=(10, 10))
+
+ ax1 = pl.subplot2grid((4, 4), (0, 0))
+ pl.xlim((-1, 1))
+ pl.ylim((-1, 1))
+ ax1.scatter(npos[0][:, 0], npos[0][:, 1], color='r')
+
+ ax2 = pl.subplot2grid((4, 4), (0, 1))
+ pl.xlim((-1, 1))
+ pl.ylim((-1, 1))
+ ax2.scatter(npost01[1][:, 0], npost01[1][:, 1], color='b')
+
+ ax3 = pl.subplot2grid((4, 4), (0, 2))
+ pl.xlim((-1, 1))
+ pl.ylim((-1, 1))
+ ax3.scatter(npost01[0][:, 0], npost01[0][:, 1], color='b')
+
+ ax4 = pl.subplot2grid((4, 4), (0, 3))
+ pl.xlim((-1, 1))
+ pl.ylim((-1, 1))
+ ax4.scatter(npos[1][:, 0], npos[1][:, 1], color='r')
+
+ ax5 = pl.subplot2grid((4, 4), (1, 0))
+ pl.xlim((-1, 1))
+ pl.ylim((-1, 1))
+ ax5.scatter(npost02[1][:, 0], npost02[1][:, 1], color='b')
+
+ ax6 = pl.subplot2grid((4, 4), (1, 3))
+ pl.xlim((-1, 1))
+ pl.ylim((-1, 1))
+ ax6.scatter(npost13[1][:, 0], npost13[1][:, 1], color='b')
+
+ ax7 = pl.subplot2grid((4, 4), (2, 0))
+ pl.xlim((-1, 1))
+ pl.ylim((-1, 1))
+ ax7.scatter(npost02[0][:, 0], npost02[0][:, 1], color='b')
+
+ ax8 = pl.subplot2grid((4, 4), (2, 3))
+ pl.xlim((-1, 1))
+ pl.ylim((-1, 1))
+ ax8.scatter(npost13[0][:, 0], npost13[0][:, 1], color='b')
+
+ ax9 = pl.subplot2grid((4, 4), (3, 0))
+ pl.xlim((-1, 1))
+ pl.ylim((-1, 1))
+ ax9.scatter(npos[2][:, 0], npos[2][:, 1], color='r')
+
+ ax10 = pl.subplot2grid((4, 4), (3, 1))
+ pl.xlim((-1, 1))
+ pl.ylim((-1, 1))
+ ax10.scatter(npost23[1][:, 0], npost23[1][:, 1], color='b')
+
+ ax11 = pl.subplot2grid((4, 4), (3, 2))
+ pl.xlim((-1, 1))
+ pl.ylim((-1, 1))
+ ax11.scatter(npost23[0][:, 0], npost23[0][:, 1], color='b')
+
+ ax12 = pl.subplot2grid((4, 4), (3, 3))
+ pl.xlim((-1, 1))
+ pl.ylim((-1, 1))
+ ax12.scatter(npos[3][:, 0], npos[3][:, 1], color='r')
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_gromov_barycenter_001.png
+ :align: center
+
+
+
+
+**Total running time of the script:** ( 8 minutes 43.875 seconds)
+
+
+
+.. container:: sphx-glr-footer
+
+
+ .. container:: sphx-glr-download
+
+ :download:`Download Python source code: plot_gromov_barycenter.py <plot_gromov_barycenter.py>`
+
+
+
+ .. container:: sphx-glr-download
+
+ :download:`Download Jupyter notebook: plot_gromov_barycenter.ipynb <plot_gromov_barycenter.ipynb>`
+
+.. rst-class:: sphx-glr-signature
+
+ `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
diff --git a/docs/source/auto_examples/plot_optim_OTreg.ipynb b/docs/source/auto_examples/plot_optim_OTreg.ipynb
index 5ded922..333331b 100644
--- a/docs/source/auto_examples/plot_optim_OTreg.ipynb
+++ b/docs/source/auto_examples/plot_optim_OTreg.ipynb
@@ -15,7 +15,7 @@
},
{
"source": [
- "\n# Regularized OT with generic solver\n\n\n\n\n"
+ "\n# Regularized OT with generic solver\n\n\nIllustrates the use of the generic solver for regularized OT with\nuser-designed regularization term. It uses Conditional gradient as in [6] and\ngeneralized Conditional Gradient as proposed in [5][7].\n\n\n[5] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy, Optimal Transport for\nDomain Adaptation, in IEEE Transactions on Pattern Analysis and Machine\nIntelligence , vol.PP, no.99, pp.1-1.\n\n[6] Ferradans, S., Papadakis, N., Peyr\u00e9, G., & Aujol, J. F. (2014).\nRegularized discrete optimal transport. SIAM Journal on Imaging Sciences,\n7(3), 1853-1882.\n\n[7] Rakotomamonjy, A., Flamary, R., & Courty, N. (2015). Generalized\nconditional gradient: analysis of convergence and applications.\narXiv preprint arXiv:1510.06567.\n\n\n\n\n"
],
"cell_type": "markdown",
"metadata": {}
@@ -24,7 +24,97 @@
"execution_count": null,
"cell_type": "code",
"source": [
- "import numpy as np\nimport matplotlib.pylab as pl\nimport ot\n\n\n\n#%% parameters\n\nn=100 # nb bins\n\n# bin positions\nx=np.arange(n,dtype=np.float64)\n\n# Gaussian distributions\na=ot.datasets.get_1D_gauss(n,m=20,s=5) # m= mean, s= std\nb=ot.datasets.get_1D_gauss(n,m=60,s=10)\n\n# loss matrix\nM=ot.dist(x.reshape((n,1)),x.reshape((n,1)))\nM/=M.max()\n\n#%% EMD\n\nG0=ot.emd(a,b,M)\n\npl.figure(3)\not.plot.plot1D_mat(a,b,G0,'OT matrix G0')\n\n#%% Example with Frobenius norm regularization\n\ndef f(G): return 0.5*np.sum(G**2)\ndef df(G): return G\n\nreg=1e-1\n\nGl2=ot.optim.cg(a,b,M,reg,f,df,verbose=True)\n\npl.figure(3)\not.plot.plot1D_mat(a,b,Gl2,'OT matrix Frob. reg')\n\n#%% Example with entropic regularization\n\ndef f(G): return np.sum(G*np.log(G))\ndef df(G): return np.log(G)+1\n\nreg=1e-3\n\nGe=ot.optim.cg(a,b,M,reg,f,df,verbose=True)\n\npl.figure(4)\not.plot.plot1D_mat(a,b,Ge,'OT matrix Entrop. reg')\n\n#%% Example with Frobenius norm + entropic regularization with gcg\n\ndef f(G): return 0.5*np.sum(G**2)\ndef df(G): return G\n\nreg1=1e-3\nreg2=1e-1\n\nGel2=ot.optim.gcg(a,b,M,reg1,reg2,f,df,verbose=True)\n\npl.figure(5)\not.plot.plot1D_mat(a,b,Gel2,'OT entropic + matrix Frob. reg')\npl.show()"
+ "import numpy as np\nimport matplotlib.pylab as pl\nimport ot"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Generate data\n-------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% parameters\n\nn = 100 # nb bins\n\n# bin positions\nx = np.arange(n, dtype=np.float64)\n\n# Gaussian distributions\na = ot.datasets.get_1D_gauss(n, m=20, s=5) # m= mean, s= std\nb = ot.datasets.get_1D_gauss(n, m=60, s=10)\n\n# loss matrix\nM = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)))\nM /= M.max()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Solve EMD\n---------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% EMD\n\nG0 = ot.emd(a, b, M)\n\npl.figure(3, figsize=(5, 5))\not.plot.plot1D_mat(a, b, G0, 'OT matrix G0')"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Solve EMD with Frobenius norm regularization\n--------------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% Example with Frobenius norm regularization\n\n\ndef f(G):\n return 0.5 * np.sum(G**2)\n\n\ndef df(G):\n return G\n\n\nreg = 1e-1\n\nGl2 = ot.optim.cg(a, b, M, reg, f, df, verbose=True)\n\npl.figure(3)\not.plot.plot1D_mat(a, b, Gl2, 'OT matrix Frob. reg')"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Solve EMD with entropic regularization\n--------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% Example with entropic regularization\n\n\ndef f(G):\n return np.sum(G * np.log(G))\n\n\ndef df(G):\n return np.log(G) + 1.\n\n\nreg = 1e-3\n\nGe = ot.optim.cg(a, b, M, reg, f, df, verbose=True)\n\npl.figure(4, figsize=(5, 5))\not.plot.plot1D_mat(a, b, Ge, 'OT matrix Entrop. reg')"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Solve EMD with Frobenius norm + entropic regularization\n-------------------------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "#%% Example with Frobenius norm + entropic regularization with gcg\n\n\ndef f(G):\n return 0.5 * np.sum(G**2)\n\n\ndef df(G):\n return G\n\n\nreg1 = 1e-3\nreg2 = 1e-1\n\nGel2 = ot.optim.gcg(a, b, M, reg1, reg2, f, df, verbose=True)\n\npl.figure(5, figsize=(5, 5))\not.plot.plot1D_mat(a, b, Gel2, 'OT entropic + matrix Frob. reg')\npl.show()"
],
"outputs": [],
"metadata": {
diff --git a/docs/source/auto_examples/plot_optim_OTreg.py b/docs/source/auto_examples/plot_optim_OTreg.py
index 8abb426..e1a737e 100644
--- a/docs/source/auto_examples/plot_optim_OTreg.py
+++ b/docs/source/auto_examples/plot_optim_OTreg.py
@@ -4,6 +4,24 @@
Regularized OT with generic solver
==================================
+Illustrates the use of the generic solver for regularized OT with
+user-designed regularization term. It uses Conditional gradient as in [6] and
+generalized Conditional Gradient as proposed in [5][7].
+
+
+[5] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy, Optimal Transport for
+Domain Adaptation, in IEEE Transactions on Pattern Analysis and Machine
+Intelligence , vol.PP, no.99, pp.1-1.
+
+[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.
+
+
"""
@@ -12,63 +30,100 @@ import matplotlib.pylab as pl
import ot
+##############################################################################
+# Generate data
+# -------------
#%% parameters
-n=100 # nb bins
+n = 100 # nb bins
# bin positions
-x=np.arange(n,dtype=np.float64)
+x = np.arange(n, dtype=np.float64)
# Gaussian distributions
-a=ot.datasets.get_1D_gauss(n,m=20,s=5) # m= mean, s= std
-b=ot.datasets.get_1D_gauss(n,m=60,s=10)
+a = ot.datasets.get_1D_gauss(n, m=20, s=5) # m= mean, s= std
+b = ot.datasets.get_1D_gauss(n, m=60, s=10)
# loss matrix
-M=ot.dist(x.reshape((n,1)),x.reshape((n,1)))
-M/=M.max()
+M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)))
+M /= M.max()
+
+##############################################################################
+# Solve EMD
+# ---------
#%% EMD
-G0=ot.emd(a,b,M)
+G0 = ot.emd(a, b, M)
-pl.figure(3)
-ot.plot.plot1D_mat(a,b,G0,'OT matrix G0')
+pl.figure(3, figsize=(5, 5))
+ot.plot.plot1D_mat(a, b, G0, 'OT matrix G0')
+
+##############################################################################
+# Solve EMD with Frobenius norm regularization
+# --------------------------------------------
#%% Example with Frobenius norm regularization
-def f(G): return 0.5*np.sum(G**2)
-def df(G): return G
-reg=1e-1
+def f(G):
+ return 0.5 * np.sum(G**2)
+
+
+def df(G):
+ return G
+
-Gl2=ot.optim.cg(a,b,M,reg,f,df,verbose=True)
+reg = 1e-1
+
+Gl2 = ot.optim.cg(a, b, M, reg, f, df, verbose=True)
pl.figure(3)
-ot.plot.plot1D_mat(a,b,Gl2,'OT matrix Frob. reg')
+ot.plot.plot1D_mat(a, b, Gl2, 'OT matrix Frob. reg')
+
+##############################################################################
+# Solve EMD with entropic regularization
+# --------------------------------------
#%% Example with entropic regularization
-def f(G): return np.sum(G*np.log(G))
-def df(G): return np.log(G)+1
-reg=1e-3
+def f(G):
+ return np.sum(G * np.log(G))
+
+
+def df(G):
+ return np.log(G) + 1.
+
+
+reg = 1e-3
-Ge=ot.optim.cg(a,b,M,reg,f,df,verbose=True)
+Ge = ot.optim.cg(a, b, M, reg, f, df, verbose=True)
-pl.figure(4)
-ot.plot.plot1D_mat(a,b,Ge,'OT matrix Entrop. reg')
+pl.figure(4, figsize=(5, 5))
+ot.plot.plot1D_mat(a, b, Ge, 'OT matrix Entrop. reg')
+
+##############################################################################
+# Solve EMD with Frobenius norm + entropic regularization
+# -------------------------------------------------------
#%% Example with Frobenius norm + entropic regularization with gcg
-def f(G): return 0.5*np.sum(G**2)
-def df(G): return G
-reg1=1e-3
-reg2=1e-1
+def f(G):
+ return 0.5 * np.sum(G**2)
+
+
+def df(G):
+ return G
+
+
+reg1 = 1e-3
+reg2 = 1e-1
-Gel2=ot.optim.gcg(a,b,M,reg1,reg2,f,df,verbose=True)
+Gel2 = ot.optim.gcg(a, b, M, reg1, reg2, f, df, verbose=True)
-pl.figure(5)
-ot.plot.plot1D_mat(a,b,Gel2,'OT entropic + matrix Frob. reg')
-pl.show() \ No newline at end of file
+pl.figure(5, figsize=(5, 5))
+ot.plot.plot1D_mat(a, b, Gel2, 'OT entropic + matrix Frob. reg')
+pl.show()
diff --git a/docs/source/auto_examples/plot_optim_OTreg.rst b/docs/source/auto_examples/plot_optim_OTreg.rst
index 70cd26c..480149a 100644
--- a/docs/source/auto_examples/plot_optim_OTreg.rst
+++ b/docs/source/auto_examples/plot_optim_OTreg.rst
@@ -7,28 +7,126 @@
Regularized OT with generic solver
==================================
+Illustrates the use of the generic solver for regularized OT with
+user-designed regularization term. It uses Conditional gradient as in [6] and
+generalized Conditional Gradient as proposed in [5][7].
+[5] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy, Optimal Transport for
+Domain Adaptation, in IEEE Transactions on Pattern Analysis and Machine
+Intelligence , vol.PP, no.99, pp.1-1.
+[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.
-.. rst-class:: sphx-glr-horizontal
- *
- .. image:: /auto_examples/images/sphx_glr_plot_optim_OTreg_003.png
- :scale: 47
- *
- .. image:: /auto_examples/images/sphx_glr_plot_optim_OTreg_004.png
- :scale: 47
+.. code-block:: python
+
+
+ import numpy as np
+ import matplotlib.pylab as pl
+ import ot
+
+
+
+
+
+
+
+
+Generate data
+-------------
+
+
+
+.. code-block:: python
+
+
+ #%% parameters
+
+ n = 100 # nb bins
+
+ # bin positions
+ x = np.arange(n, dtype=np.float64)
+
+ # Gaussian distributions
+ a = ot.datasets.get_1D_gauss(n, m=20, s=5) # m= mean, s= std
+ b = ot.datasets.get_1D_gauss(n, m=60, s=10)
+
+ # loss matrix
+ M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)))
+ M /= M.max()
+
+
+
+
+
+
+
+Solve EMD
+---------
+
+
+
+.. code-block:: python
+
+
+ #%% EMD
+
+ G0 = ot.emd(a, b, M)
+
+ pl.figure(3, figsize=(5, 5))
+ ot.plot.plot1D_mat(a, b, G0, 'OT matrix G0')
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_optim_OTreg_003.png
+ :align: center
+
+
+
+
+Solve EMD with Frobenius norm regularization
+--------------------------------------------
+
+
+
+.. code-block:: python
+
+
+ #%% Example with Frobenius norm regularization
+
+
+ def f(G):
+ return 0.5 * np.sum(G**2)
+
+
+ def df(G):
+ return G
+
+
+ reg = 1e-1
+
+ Gl2 = ot.optim.cg(a, b, M, reg, f, df, verbose=True)
+
+ pl.figure(3)
+ ot.plot.plot1D_mat(a, b, Gl2, 'OT matrix Frob. reg')
+
+
- *
- .. image:: /auto_examples/images/sphx_glr_plot_optim_OTreg_005.png
- :scale: 47
+.. image:: /auto_examples/images/sphx_glr_plot_optim_OTreg_004.png
+ :align: center
.. rst-class:: sphx-glr-script-out
@@ -258,312 +356,287 @@ Regularized OT with generic solver
It. |Loss |Delta loss
--------------------------------
200|1.663543e-01|-8.737134e-08
+
+
+Solve EMD with entropic regularization
+--------------------------------------
+
+
+
+.. code-block:: python
+
+
+ #%% Example with entropic regularization
+
+
+ def f(G):
+ return np.sum(G * np.log(G))
+
+
+ def df(G):
+ return np.log(G) + 1.
+
+
+ reg = 1e-3
+
+ Ge = ot.optim.cg(a, b, M, reg, f, df, verbose=True)
+
+ pl.figure(4, figsize=(5, 5))
+ ot.plot.plot1D_mat(a, b, Ge, 'OT matrix Entrop. reg')
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_optim_OTreg_006.png
+ :align: center
+
+
+.. rst-class:: sphx-glr-script-out
+
+ Out::
+
It. |Loss |Delta loss
--------------------------------
0|1.692289e-01|0.000000e+00
1|1.617643e-01|-4.614437e-02
- 2|1.612546e-01|-3.161037e-03
- 3|1.611040e-01|-9.349544e-04
- 4|1.610346e-01|-4.310179e-04
- 5|1.610072e-01|-1.701719e-04
- 6|1.609947e-01|-7.759814e-05
- 7|1.609934e-01|-7.941439e-06
- 8|1.609841e-01|-5.797180e-05
- 9|1.609838e-01|-1.559407e-06
- 10|1.609685e-01|-9.530282e-05
- 11|1.609666e-01|-1.142129e-05
- 12|1.609541e-01|-7.799970e-05
- 13|1.609496e-01|-2.780416e-05
- 14|1.609385e-01|-6.887105e-05
- 15|1.609334e-01|-3.174241e-05
- 16|1.609231e-01|-6.420777e-05
- 17|1.609115e-01|-7.189949e-05
- 18|1.608815e-01|-1.865331e-04
- 19|1.608799e-01|-1.013039e-05
+ 2|1.612639e-01|-3.102965e-03
+ 3|1.611291e-01|-8.371098e-04
+ 4|1.610468e-01|-5.110558e-04
+ 5|1.610198e-01|-1.672927e-04
+ 6|1.610130e-01|-4.232417e-05
+ 7|1.610090e-01|-2.513455e-05
+ 8|1.610002e-01|-5.443507e-05
+ 9|1.609996e-01|-3.657071e-06
+ 10|1.609948e-01|-2.998735e-05
+ 11|1.609695e-01|-1.569217e-04
+ 12|1.609533e-01|-1.010779e-04
+ 13|1.609520e-01|-8.043897e-06
+ 14|1.609465e-01|-3.415246e-05
+ 15|1.609386e-01|-4.898605e-05
+ 16|1.609324e-01|-3.837052e-05
+ 17|1.609298e-01|-1.617826e-05
+ 18|1.609184e-01|-7.080015e-05
+ 19|1.609083e-01|-6.273206e-05
It. |Loss |Delta loss
--------------------------------
- 20|1.608695e-01|-6.468606e-05
- 21|1.608686e-01|-5.738419e-06
- 22|1.608661e-01|-1.495923e-05
- 23|1.608657e-01|-2.784611e-06
- 24|1.608633e-01|-1.512408e-05
- 25|1.608624e-01|-5.397916e-06
- 26|1.608617e-01|-4.115218e-06
- 27|1.608561e-01|-3.503396e-05
- 28|1.608479e-01|-5.098773e-05
- 29|1.608452e-01|-1.659203e-05
- 30|1.608399e-01|-3.298319e-05
- 31|1.608330e-01|-4.302183e-05
- 32|1.608310e-01|-1.273465e-05
- 33|1.608280e-01|-1.827713e-05
- 34|1.608231e-01|-3.039842e-05
- 35|1.608212e-01|-1.229256e-05
- 36|1.608200e-01|-6.900556e-06
- 37|1.608159e-01|-2.554039e-05
- 38|1.608103e-01|-3.521137e-05
- 39|1.608058e-01|-2.795180e-05
+ 20|1.608988e-01|-5.940805e-05
+ 21|1.608853e-01|-8.380030e-05
+ 22|1.608844e-01|-5.185045e-06
+ 23|1.608824e-01|-1.279113e-05
+ 24|1.608819e-01|-3.156821e-06
+ 25|1.608783e-01|-2.205746e-05
+ 26|1.608764e-01|-1.189894e-05
+ 27|1.608755e-01|-5.474607e-06
+ 28|1.608737e-01|-1.144227e-05
+ 29|1.608676e-01|-3.775335e-05
+ 30|1.608638e-01|-2.348020e-05
+ 31|1.608627e-01|-6.863136e-06
+ 32|1.608529e-01|-6.110230e-05
+ 33|1.608487e-01|-2.641106e-05
+ 34|1.608409e-01|-4.823638e-05
+ 35|1.608373e-01|-2.256641e-05
+ 36|1.608338e-01|-2.132444e-05
+ 37|1.608310e-01|-1.786649e-05
+ 38|1.608260e-01|-3.103848e-05
+ 39|1.608206e-01|-3.321265e-05
It. |Loss |Delta loss
--------------------------------
- 40|1.608040e-01|-1.119118e-05
- 41|1.608027e-01|-8.193369e-06
- 42|1.607994e-01|-2.026719e-05
- 43|1.607985e-01|-5.819902e-06
- 44|1.607978e-01|-4.048170e-06
- 45|1.607978e-01|-3.007470e-07
- 46|1.607950e-01|-1.705375e-05
- 47|1.607927e-01|-1.430186e-05
- 48|1.607925e-01|-1.166526e-06
- 49|1.607911e-01|-9.069406e-06
- 50|1.607910e-01|-3.804209e-07
- 51|1.607910e-01|-5.942399e-08
- 52|1.607910e-01|-2.321380e-07
- 53|1.607907e-01|-1.877655e-06
- 54|1.607906e-01|-2.940224e-07
- 55|1.607877e-01|-1.814208e-05
- 56|1.607841e-01|-2.236496e-05
- 57|1.607810e-01|-1.951355e-05
- 58|1.607804e-01|-3.578228e-06
- 59|1.607789e-01|-9.442277e-06
+ 40|1.608201e-01|-3.054747e-06
+ 41|1.608195e-01|-4.198335e-06
+ 42|1.608193e-01|-8.458736e-07
+ 43|1.608159e-01|-2.153759e-05
+ 44|1.608115e-01|-2.738314e-05
+ 45|1.608108e-01|-3.960032e-06
+ 46|1.608081e-01|-1.675447e-05
+ 47|1.608072e-01|-5.976340e-06
+ 48|1.608046e-01|-1.604130e-05
+ 49|1.608020e-01|-1.617036e-05
+ 50|1.608014e-01|-3.957795e-06
+ 51|1.608011e-01|-1.292411e-06
+ 52|1.607998e-01|-8.431795e-06
+ 53|1.607964e-01|-2.127054e-05
+ 54|1.607947e-01|-1.021878e-05
+ 55|1.607947e-01|-3.560621e-07
+ 56|1.607900e-01|-2.929781e-05
+ 57|1.607890e-01|-5.740229e-06
+ 58|1.607858e-01|-2.039550e-05
+ 59|1.607836e-01|-1.319545e-05
It. |Loss |Delta loss
--------------------------------
- 60|1.607779e-01|-5.997371e-06
- 61|1.607754e-01|-1.564408e-05
- 62|1.607742e-01|-7.693285e-06
- 63|1.607727e-01|-9.030547e-06
- 64|1.607719e-01|-5.103894e-06
- 65|1.607693e-01|-1.605420e-05
- 66|1.607676e-01|-1.047837e-05
- 67|1.607675e-01|-6.026848e-07
- 68|1.607655e-01|-1.240216e-05
- 69|1.607632e-01|-1.434674e-05
- 70|1.607618e-01|-8.829808e-06
- 71|1.607606e-01|-7.581824e-06
- 72|1.607590e-01|-1.009457e-05
- 73|1.607586e-01|-2.222963e-06
- 74|1.607577e-01|-5.564775e-06
- 75|1.607574e-01|-1.932763e-06
- 76|1.607573e-01|-8.148685e-07
- 77|1.607554e-01|-1.187660e-05
- 78|1.607546e-01|-4.557651e-06
- 79|1.607537e-01|-5.911902e-06
+ 60|1.607826e-01|-6.378947e-06
+ 61|1.607808e-01|-1.145102e-05
+ 62|1.607776e-01|-1.941743e-05
+ 63|1.607743e-01|-2.087422e-05
+ 64|1.607741e-01|-1.310249e-06
+ 65|1.607738e-01|-1.682752e-06
+ 66|1.607691e-01|-2.913936e-05
+ 67|1.607671e-01|-1.288855e-05
+ 68|1.607654e-01|-1.002448e-05
+ 69|1.607641e-01|-8.209492e-06
+ 70|1.607632e-01|-5.588467e-06
+ 71|1.607619e-01|-8.050388e-06
+ 72|1.607618e-01|-9.417493e-07
+ 73|1.607598e-01|-1.210509e-05
+ 74|1.607591e-01|-4.392914e-06
+ 75|1.607579e-01|-7.759587e-06
+ 76|1.607574e-01|-2.760280e-06
+ 77|1.607556e-01|-1.146469e-05
+ 78|1.607550e-01|-3.689456e-06
+ 79|1.607550e-01|-4.065631e-08
It. |Loss |Delta loss
--------------------------------
- 80|1.607529e-01|-4.710187e-06
- 81|1.607528e-01|-8.866080e-07
- 82|1.607522e-01|-3.620627e-06
- 83|1.607514e-01|-5.091281e-06
- 84|1.607498e-01|-9.932095e-06
- 85|1.607487e-01|-6.852804e-06
- 86|1.607478e-01|-5.373596e-06
- 87|1.607473e-01|-3.287295e-06
- 88|1.607470e-01|-1.666655e-06
- 89|1.607469e-01|-5.293790e-07
- 90|1.607466e-01|-2.051914e-06
- 91|1.607456e-01|-6.422797e-06
- 92|1.607456e-01|-1.110433e-07
- 93|1.607451e-01|-2.803849e-06
- 94|1.607451e-01|-2.608066e-07
- 95|1.607441e-01|-6.290352e-06
- 96|1.607429e-01|-7.298455e-06
- 97|1.607429e-01|-8.969905e-09
- 98|1.607427e-01|-7.923968e-07
- 99|1.607427e-01|-3.519286e-07
+ 80|1.607539e-01|-6.555681e-06
+ 81|1.607528e-01|-7.177470e-06
+ 82|1.607527e-01|-5.306068e-07
+ 83|1.607514e-01|-7.816045e-06
+ 84|1.607511e-01|-2.301970e-06
+ 85|1.607504e-01|-4.281072e-06
+ 86|1.607503e-01|-7.821886e-07
+ 87|1.607480e-01|-1.403013e-05
+ 88|1.607480e-01|-1.169298e-08
+ 89|1.607473e-01|-4.235982e-06
+ 90|1.607470e-01|-1.717105e-06
+ 91|1.607470e-01|-6.148402e-09
+ 92|1.607462e-01|-5.396481e-06
+ 93|1.607461e-01|-5.194954e-07
+ 94|1.607450e-01|-6.525707e-06
+ 95|1.607442e-01|-5.332060e-06
+ 96|1.607439e-01|-1.682093e-06
+ 97|1.607437e-01|-1.594796e-06
+ 98|1.607435e-01|-7.923812e-07
+ 99|1.607420e-01|-9.738552e-06
It. |Loss |Delta loss
--------------------------------
- 100|1.607426e-01|-3.563804e-07
- 101|1.607410e-01|-1.004042e-05
- 102|1.607410e-01|-2.124801e-07
- 103|1.607398e-01|-7.556935e-06
- 104|1.607398e-01|-7.606853e-08
- 105|1.607385e-01|-8.058684e-06
- 106|1.607383e-01|-7.393061e-07
- 107|1.607381e-01|-1.504958e-06
- 108|1.607377e-01|-2.508807e-06
- 109|1.607371e-01|-4.004631e-06
- 110|1.607365e-01|-3.580156e-06
- 111|1.607364e-01|-2.563573e-07
- 112|1.607354e-01|-6.390137e-06
- 113|1.607348e-01|-4.119553e-06
- 114|1.607339e-01|-5.299475e-06
- 115|1.607335e-01|-2.316767e-06
- 116|1.607330e-01|-3.444737e-06
- 117|1.607324e-01|-3.467980e-06
- 118|1.607320e-01|-2.374632e-06
- 119|1.607319e-01|-7.978255e-07
+ 100|1.607419e-01|-1.022448e-07
+ 101|1.607419e-01|-4.865999e-07
+ 102|1.607418e-01|-7.092012e-07
+ 103|1.607408e-01|-5.861815e-06
+ 104|1.607402e-01|-3.953266e-06
+ 105|1.607395e-01|-3.969572e-06
+ 106|1.607390e-01|-3.612075e-06
+ 107|1.607377e-01|-7.683735e-06
+ 108|1.607365e-01|-7.777599e-06
+ 109|1.607364e-01|-2.335096e-07
+ 110|1.607364e-01|-4.562036e-07
+ 111|1.607360e-01|-2.089538e-06
+ 112|1.607356e-01|-2.755355e-06
+ 113|1.607349e-01|-4.501960e-06
+ 114|1.607347e-01|-1.160544e-06
+ 115|1.607346e-01|-6.289450e-07
+ 116|1.607345e-01|-2.092146e-07
+ 117|1.607336e-01|-5.990866e-06
+ 118|1.607330e-01|-3.348498e-06
+ 119|1.607328e-01|-1.256222e-06
It. |Loss |Delta loss
--------------------------------
- 120|1.607312e-01|-4.221434e-06
- 121|1.607310e-01|-1.324597e-06
- 122|1.607304e-01|-3.650359e-06
- 123|1.607298e-01|-3.732712e-06
- 124|1.607295e-01|-1.994082e-06
- 125|1.607289e-01|-3.954139e-06
- 126|1.607286e-01|-1.532372e-06
- 127|1.607286e-01|-1.167223e-07
- 128|1.607283e-01|-2.157376e-06
- 129|1.607279e-01|-2.253077e-06
- 130|1.607274e-01|-3.301532e-06
- 131|1.607269e-01|-2.650754e-06
- 132|1.607264e-01|-3.595551e-06
- 133|1.607262e-01|-1.159425e-06
- 134|1.607258e-01|-2.512411e-06
- 135|1.607255e-01|-1.998792e-06
- 136|1.607251e-01|-2.486536e-06
- 137|1.607246e-01|-2.782996e-06
- 138|1.607246e-01|-2.922470e-07
- 139|1.607242e-01|-2.071131e-06
+ 120|1.607320e-01|-5.418353e-06
+ 121|1.607318e-01|-8.296189e-07
+ 122|1.607311e-01|-4.381608e-06
+ 123|1.607310e-01|-8.913901e-07
+ 124|1.607309e-01|-3.808821e-07
+ 125|1.607302e-01|-4.608994e-06
+ 126|1.607294e-01|-5.063777e-06
+ 127|1.607290e-01|-2.532835e-06
+ 128|1.607285e-01|-2.870049e-06
+ 129|1.607284e-01|-4.892812e-07
+ 130|1.607281e-01|-1.760452e-06
+ 131|1.607279e-01|-1.727139e-06
+ 132|1.607275e-01|-2.220706e-06
+ 133|1.607271e-01|-2.516930e-06
+ 134|1.607269e-01|-1.201434e-06
+ 135|1.607269e-01|-2.183459e-09
+ 136|1.607262e-01|-4.223011e-06
+ 137|1.607258e-01|-2.530202e-06
+ 138|1.607258e-01|-1.857260e-07
+ 139|1.607256e-01|-1.401957e-06
It. |Loss |Delta loss
--------------------------------
- 140|1.607237e-01|-3.154193e-06
- 141|1.607235e-01|-1.194962e-06
- 142|1.607232e-01|-2.035251e-06
- 143|1.607232e-01|-6.027855e-08
- 144|1.607229e-01|-1.555696e-06
- 145|1.607228e-01|-1.081740e-06
- 146|1.607225e-01|-1.881070e-06
- 147|1.607224e-01|-4.100096e-07
- 148|1.607223e-01|-7.785200e-07
- 149|1.607222e-01|-2.094072e-07
- 150|1.607220e-01|-1.440814e-06
- 151|1.607217e-01|-1.997794e-06
- 152|1.607214e-01|-2.011022e-06
- 153|1.607212e-01|-8.808854e-07
- 154|1.607211e-01|-7.245877e-07
- 155|1.607207e-01|-2.217159e-06
- 156|1.607201e-01|-3.817891e-06
- 157|1.607200e-01|-7.409600e-07
- 158|1.607198e-01|-1.497698e-06
- 159|1.607195e-01|-1.729666e-06
+ 140|1.607250e-01|-3.242751e-06
+ 141|1.607247e-01|-2.308071e-06
+ 142|1.607247e-01|-4.730700e-08
+ 143|1.607246e-01|-4.240229e-07
+ 144|1.607242e-01|-2.484810e-06
+ 145|1.607238e-01|-2.539206e-06
+ 146|1.607234e-01|-2.535574e-06
+ 147|1.607231e-01|-1.954802e-06
+ 148|1.607228e-01|-1.765447e-06
+ 149|1.607228e-01|-1.620007e-08
+ 150|1.607222e-01|-3.615783e-06
+ 151|1.607222e-01|-8.668516e-08
+ 152|1.607215e-01|-4.000673e-06
+ 153|1.607213e-01|-1.774103e-06
+ 154|1.607213e-01|-6.328834e-09
+ 155|1.607209e-01|-2.418783e-06
+ 156|1.607208e-01|-2.848492e-07
+ 157|1.607207e-01|-8.836043e-07
+ 158|1.607205e-01|-1.192836e-06
+ 159|1.607202e-01|-1.638022e-06
It. |Loss |Delta loss
--------------------------------
- 160|1.607195e-01|-2.115187e-07
- 161|1.607192e-01|-1.643727e-06
- 162|1.607192e-01|-1.712969e-07
- 163|1.607189e-01|-1.805877e-06
- 164|1.607189e-01|-1.209827e-07
- 165|1.607185e-01|-2.060002e-06
- 166|1.607182e-01|-1.961341e-06
- 167|1.607181e-01|-1.020366e-06
- 168|1.607179e-01|-9.760982e-07
- 169|1.607178e-01|-7.219236e-07
- 170|1.607175e-01|-1.837718e-06
- 171|1.607174e-01|-3.337578e-07
- 172|1.607173e-01|-5.298564e-07
- 173|1.607173e-01|-6.864278e-08
- 174|1.607173e-01|-2.008419e-07
- 175|1.607171e-01|-1.375630e-06
- 176|1.607168e-01|-1.911257e-06
- 177|1.607167e-01|-2.709815e-07
- 178|1.607167e-01|-1.390953e-07
- 179|1.607165e-01|-1.199675e-06
- It. |Loss |Delta loss
- --------------------------------
- 180|1.607165e-01|-1.457259e-07
- 181|1.607163e-01|-1.049154e-06
- 182|1.607163e-01|-2.753577e-09
- 183|1.607163e-01|-6.972814e-09
- 184|1.607161e-01|-1.552100e-06
- 185|1.607159e-01|-1.068596e-06
- 186|1.607157e-01|-1.247724e-06
- 187|1.607155e-01|-1.158164e-06
- 188|1.607155e-01|-2.616199e-07
- 189|1.607154e-01|-3.595874e-07
- 190|1.607154e-01|-5.334527e-08
- 191|1.607153e-01|-3.452744e-07
- 192|1.607153e-01|-1.239593e-07
- 193|1.607152e-01|-8.184984e-07
- 194|1.607150e-01|-1.316308e-06
- 195|1.607150e-01|-7.100882e-09
- 196|1.607148e-01|-1.393958e-06
- 197|1.607146e-01|-1.242735e-06
- 198|1.607144e-01|-1.123993e-06
- 199|1.607143e-01|-3.512071e-07
- It. |Loss |Delta loss
- --------------------------------
- 200|1.607143e-01|-2.151971e-10
- It. |Loss |Delta loss
- --------------------------------
- 0|1.693084e-01|0.000000e+00
- 1|1.610121e-01|-5.152589e-02
- 2|1.609378e-01|-4.622297e-04
- 3|1.609284e-01|-5.830043e-05
- 4|1.609284e-01|-1.111580e-12
-
+ 160|1.607202e-01|-3.670914e-08
+ 161|1.607197e-01|-3.153709e-06
+ 162|1.607197e-01|-2.419565e-09
+ 163|1.607194e-01|-2.136882e-06
+ 164|1.607194e-01|-1.173754e-09
+ 165|1.607192e-01|-8.169238e-07
+ 166|1.607191e-01|-9.218755e-07
+ 167|1.607189e-01|-9.459255e-07
+ 168|1.607187e-01|-1.294835e-06
+ 169|1.607186e-01|-5.797668e-07
+ 170|1.607186e-01|-4.706272e-08
+ 171|1.607183e-01|-1.753383e-06
+ 172|1.607183e-01|-1.681573e-07
+ 173|1.607183e-01|-2.563971e-10
+Solve EMD with Frobenius norm + entropic regularization
+-------------------------------------------------------
-|
.. code-block:: python
- import numpy as np
- import matplotlib.pylab as pl
- import ot
-
-
-
- #%% parameters
-
- n=100 # nb bins
-
- # bin positions
- x=np.arange(n,dtype=np.float64)
-
- # Gaussian distributions
- a=ot.datasets.get_1D_gauss(n,m=20,s=5) # m= mean, s= std
- b=ot.datasets.get_1D_gauss(n,m=60,s=10)
-
- # loss matrix
- M=ot.dist(x.reshape((n,1)),x.reshape((n,1)))
- M/=M.max()
-
- #%% EMD
+ #%% Example with Frobenius norm + entropic regularization with gcg
- G0=ot.emd(a,b,M)
- pl.figure(3)
- ot.plot.plot1D_mat(a,b,G0,'OT matrix G0')
+ def f(G):
+ return 0.5 * np.sum(G**2)
- #%% Example with Frobenius norm regularization
- def f(G): return 0.5*np.sum(G**2)
- def df(G): return G
+ def df(G):
+ return G
- reg=1e-1
- Gl2=ot.optim.cg(a,b,M,reg,f,df,verbose=True)
+ reg1 = 1e-3
+ reg2 = 1e-1
- pl.figure(3)
- ot.plot.plot1D_mat(a,b,Gl2,'OT matrix Frob. reg')
+ Gel2 = ot.optim.gcg(a, b, M, reg1, reg2, f, df, verbose=True)
- #%% Example with entropic regularization
+ pl.figure(5, figsize=(5, 5))
+ ot.plot.plot1D_mat(a, b, Gel2, 'OT entropic + matrix Frob. reg')
+ pl.show()
- def f(G): return np.sum(G*np.log(G))
- def df(G): return np.log(G)+1
- reg=1e-3
- Ge=ot.optim.cg(a,b,M,reg,f,df,verbose=True)
+.. image:: /auto_examples/images/sphx_glr_plot_optim_OTreg_008.png
+ :align: center
- pl.figure(4)
- ot.plot.plot1D_mat(a,b,Ge,'OT matrix Entrop. reg')
- #%% Example with Frobenius norm + entropic regularization with gcg
+.. rst-class:: sphx-glr-script-out
- def f(G): return 0.5*np.sum(G**2)
- def df(G): return G
+ Out::
- reg1=1e-3
- reg2=1e-1
+ It. |Loss |Delta loss
+ --------------------------------
+ 0|1.693084e-01|0.000000e+00
+ 1|1.610121e-01|-5.152589e-02
+ 2|1.609378e-01|-4.622297e-04
+ 3|1.609284e-01|-5.830043e-05
+ 4|1.609284e-01|-1.111407e-12
- Gel2=ot.optim.gcg(a,b,M,reg1,reg2,f,df,verbose=True)
- pl.figure(5)
- ot.plot.plot1D_mat(a,b,Gel2,'OT entropic + matrix Frob. reg')
- pl.show()
-**Total running time of the script:** ( 0 minutes 2.319 seconds)
+**Total running time of the script:** ( 0 minutes 2.800 seconds)
diff --git a/docs/source/auto_examples/plot_otda_classes.ipynb b/docs/source/auto_examples/plot_otda_classes.ipynb
new file mode 100644
index 0000000..6754fa5
--- /dev/null
+++ b/docs/source/auto_examples/plot_otda_classes.ipynb
@@ -0,0 +1,126 @@
+{
+ "nbformat_minor": 0,
+ "nbformat": 4,
+ "cells": [
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "%matplotlib inline"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "\n# OT for domain adaptation\n\n\nThis example introduces a domain adaptation in a 2D setting and the 4 OTDA\napproaches currently supported in POT.\n\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# Authors: Remi Flamary <remi.flamary@unice.fr>\n# Stanislas Chambon <stan.chambon@gmail.com>\n#\n# License: MIT License\n\nimport matplotlib.pylab as pl\nimport ot"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Generate data\n-------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "n_source_samples = 150\nn_target_samples = 150\n\nXs, ys = ot.datasets.get_data_classif('3gauss', n_source_samples)\nXt, yt = ot.datasets.get_data_classif('3gauss2', n_target_samples)"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Instantiate the different transport algorithms and fit them\n-----------------------------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# EMD Transport\not_emd = ot.da.EMDTransport()\not_emd.fit(Xs=Xs, Xt=Xt)\n\n# Sinkhorn Transport\not_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)\not_sinkhorn.fit(Xs=Xs, Xt=Xt)\n\n# Sinkhorn Transport with Group lasso regularization\not_lpl1 = ot.da.SinkhornLpl1Transport(reg_e=1e-1, reg_cl=1e0)\not_lpl1.fit(Xs=Xs, ys=ys, Xt=Xt)\n\n# Sinkhorn Transport with Group lasso regularization l1l2\not_l1l2 = ot.da.SinkhornL1l2Transport(reg_e=1e-1, reg_cl=2e0, max_iter=20,\n verbose=True)\not_l1l2.fit(Xs=Xs, ys=ys, Xt=Xt)\n\n# transport source samples onto target samples\ntransp_Xs_emd = ot_emd.transform(Xs=Xs)\ntransp_Xs_sinkhorn = ot_sinkhorn.transform(Xs=Xs)\ntransp_Xs_lpl1 = ot_lpl1.transform(Xs=Xs)\ntransp_Xs_l1l2 = ot_l1l2.transform(Xs=Xs)"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Fig 1 : plots source and target samples\n---------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "pl.figure(1, figsize=(10, 5))\npl.subplot(1, 2, 1)\npl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')\npl.xticks([])\npl.yticks([])\npl.legend(loc=0)\npl.title('Source samples')\n\npl.subplot(1, 2, 2)\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')\npl.xticks([])\npl.yticks([])\npl.legend(loc=0)\npl.title('Target samples')\npl.tight_layout()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Fig 2 : plot optimal couplings and transported samples\n------------------------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "param_img = {'interpolation': 'nearest', 'cmap': 'spectral'}\n\npl.figure(2, figsize=(15, 8))\npl.subplot(2, 4, 1)\npl.imshow(ot_emd.coupling_, **param_img)\npl.xticks([])\npl.yticks([])\npl.title('Optimal coupling\\nEMDTransport')\n\npl.subplot(2, 4, 2)\npl.imshow(ot_sinkhorn.coupling_, **param_img)\npl.xticks([])\npl.yticks([])\npl.title('Optimal coupling\\nSinkhornTransport')\n\npl.subplot(2, 4, 3)\npl.imshow(ot_lpl1.coupling_, **param_img)\npl.xticks([])\npl.yticks([])\npl.title('Optimal coupling\\nSinkhornLpl1Transport')\n\npl.subplot(2, 4, 4)\npl.imshow(ot_l1l2.coupling_, **param_img)\npl.xticks([])\npl.yticks([])\npl.title('Optimal coupling\\nSinkhornL1l2Transport')\n\npl.subplot(2, 4, 5)\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n label='Target samples', alpha=0.3)\npl.scatter(transp_Xs_emd[:, 0], transp_Xs_emd[:, 1], c=ys,\n marker='+', label='Transp samples', s=30)\npl.xticks([])\npl.yticks([])\npl.title('Transported samples\\nEmdTransport')\npl.legend(loc=\"lower left\")\n\npl.subplot(2, 4, 6)\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n label='Target samples', alpha=0.3)\npl.scatter(transp_Xs_sinkhorn[:, 0], transp_Xs_sinkhorn[:, 1], c=ys,\n marker='+', label='Transp samples', s=30)\npl.xticks([])\npl.yticks([])\npl.title('Transported samples\\nSinkhornTransport')\n\npl.subplot(2, 4, 7)\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n label='Target samples', alpha=0.3)\npl.scatter(transp_Xs_lpl1[:, 0], transp_Xs_lpl1[:, 1], c=ys,\n marker='+', label='Transp samples', s=30)\npl.xticks([])\npl.yticks([])\npl.title('Transported samples\\nSinkhornLpl1Transport')\n\npl.subplot(2, 4, 8)\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n label='Target samples', alpha=0.3)\npl.scatter(transp_Xs_l1l2[:, 0], transp_Xs_l1l2[:, 1], c=ys,\n marker='+', label='Transp samples', s=30)\npl.xticks([])\npl.yticks([])\npl.title('Transported samples\\nSinkhornL1l2Transport')\npl.tight_layout()\n\npl.show()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "name": "python2",
+ "language": "python"
+ },
+ "language_info": {
+ "mimetype": "text/x-python",
+ "nbconvert_exporter": "python",
+ "name": "python",
+ "file_extension": ".py",
+ "version": "2.7.12",
+ "pygments_lexer": "ipython2",
+ "codemirror_mode": {
+ "version": 2,
+ "name": "ipython"
+ }
+ }
+ }
+} \ No newline at end of file
diff --git a/examples/da/plot_otda_classes.py b/docs/source/auto_examples/plot_otda_classes.py
index ec57a37..b14c11a 100644
--- a/examples/da/plot_otda_classes.py
+++ b/docs/source/auto_examples/plot_otda_classes.py
@@ -19,8 +19,8 @@ import ot
##############################################################################
-# generate data
-##############################################################################
+# Generate data
+# -------------
n_source_samples = 150
n_target_samples = 150
@@ -31,7 +31,7 @@ Xt, yt = ot.datasets.get_data_classif('3gauss2', n_target_samples)
##############################################################################
# Instantiate the different transport algorithms and fit them
-##############################################################################
+# -----------------------------------------------------------
# EMD Transport
ot_emd = ot.da.EMDTransport()
@@ -59,7 +59,7 @@ transp_Xs_l1l2 = ot_l1l2.transform(Xs=Xs)
##############################################################################
# Fig 1 : plots source and target samples
-##############################################################################
+# ---------------------------------------
pl.figure(1, figsize=(10, 5))
pl.subplot(1, 2, 1)
@@ -80,7 +80,7 @@ pl.tight_layout()
##############################################################################
# Fig 2 : plot optimal couplings and transported samples
-##############################################################################
+# ------------------------------------------------------
param_img = {'interpolation': 'nearest', 'cmap': 'spectral'}
diff --git a/docs/source/auto_examples/plot_otda_classes.rst b/docs/source/auto_examples/plot_otda_classes.rst
new file mode 100644
index 0000000..a5ab285
--- /dev/null
+++ b/docs/source/auto_examples/plot_otda_classes.rst
@@ -0,0 +1,258 @@
+
+
+.. _sphx_glr_auto_examples_plot_otda_classes.py:
+
+
+========================
+OT for domain adaptation
+========================
+
+This example introduces a domain adaptation in a 2D setting and the 4 OTDA
+approaches currently supported in POT.
+
+
+
+
+.. code-block:: python
+
+
+ # Authors: Remi Flamary <remi.flamary@unice.fr>
+ # Stanislas Chambon <stan.chambon@gmail.com>
+ #
+ # License: MIT License
+
+ import matplotlib.pylab as pl
+ import ot
+
+
+
+
+
+
+
+
+Generate data
+-------------
+
+
+
+.. code-block:: python
+
+
+ n_source_samples = 150
+ n_target_samples = 150
+
+ Xs, ys = ot.datasets.get_data_classif('3gauss', n_source_samples)
+ Xt, yt = ot.datasets.get_data_classif('3gauss2', n_target_samples)
+
+
+
+
+
+
+
+
+Instantiate the different transport algorithms and fit them
+-----------------------------------------------------------
+
+
+
+.. code-block:: python
+
+
+ # EMD Transport
+ ot_emd = ot.da.EMDTransport()
+ ot_emd.fit(Xs=Xs, Xt=Xt)
+
+ # Sinkhorn Transport
+ ot_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)
+ ot_sinkhorn.fit(Xs=Xs, Xt=Xt)
+
+ # Sinkhorn Transport with Group lasso regularization
+ ot_lpl1 = ot.da.SinkhornLpl1Transport(reg_e=1e-1, reg_cl=1e0)
+ ot_lpl1.fit(Xs=Xs, ys=ys, Xt=Xt)
+
+ # Sinkhorn Transport with Group lasso regularization l1l2
+ ot_l1l2 = ot.da.SinkhornL1l2Transport(reg_e=1e-1, reg_cl=2e0, max_iter=20,
+ verbose=True)
+ ot_l1l2.fit(Xs=Xs, ys=ys, Xt=Xt)
+
+ # transport source samples onto target samples
+ transp_Xs_emd = ot_emd.transform(Xs=Xs)
+ transp_Xs_sinkhorn = ot_sinkhorn.transform(Xs=Xs)
+ transp_Xs_lpl1 = ot_lpl1.transform(Xs=Xs)
+ transp_Xs_l1l2 = ot_l1l2.transform(Xs=Xs)
+
+
+
+
+
+
+.. rst-class:: sphx-glr-script-out
+
+ Out::
+
+ It. |Loss |Delta loss
+ --------------------------------
+ 0|1.003747e+01|0.000000e+00
+ 1|1.953263e+00|-4.138821e+00
+ 2|1.744456e+00|-1.196969e-01
+ 3|1.689268e+00|-3.267022e-02
+ 4|1.666355e+00|-1.374998e-02
+ 5|1.656125e+00|-6.177356e-03
+ 6|1.651753e+00|-2.646960e-03
+ 7|1.647261e+00|-2.726957e-03
+ 8|1.642274e+00|-3.036672e-03
+ 9|1.639926e+00|-1.431818e-03
+ 10|1.638750e+00|-7.173837e-04
+ 11|1.637558e+00|-7.281753e-04
+ 12|1.636248e+00|-8.002067e-04
+ 13|1.634555e+00|-1.036074e-03
+ 14|1.633547e+00|-6.166646e-04
+ 15|1.633531e+00|-1.022614e-05
+ 16|1.632957e+00|-3.510986e-04
+ 17|1.632853e+00|-6.380944e-05
+ 18|1.632704e+00|-9.122988e-05
+ 19|1.632237e+00|-2.861276e-04
+ It. |Loss |Delta loss
+ --------------------------------
+ 20|1.632174e+00|-3.896483e-05
+
+
+Fig 1 : plots source and target samples
+---------------------------------------
+
+
+
+.. code-block:: python
+
+
+ pl.figure(1, figsize=(10, 5))
+ pl.subplot(1, 2, 1)
+ pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')
+ pl.xticks([])
+ pl.yticks([])
+ pl.legend(loc=0)
+ pl.title('Source samples')
+
+ pl.subplot(1, 2, 2)
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')
+ pl.xticks([])
+ pl.yticks([])
+ pl.legend(loc=0)
+ pl.title('Target samples')
+ pl.tight_layout()
+
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_otda_classes_001.png
+ :align: center
+
+
+
+
+Fig 2 : plot optimal couplings and transported samples
+------------------------------------------------------
+
+
+
+.. code-block:: python
+
+
+ param_img = {'interpolation': 'nearest', 'cmap': 'spectral'}
+
+ pl.figure(2, figsize=(15, 8))
+ pl.subplot(2, 4, 1)
+ pl.imshow(ot_emd.coupling_, **param_img)
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Optimal coupling\nEMDTransport')
+
+ pl.subplot(2, 4, 2)
+ pl.imshow(ot_sinkhorn.coupling_, **param_img)
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Optimal coupling\nSinkhornTransport')
+
+ pl.subplot(2, 4, 3)
+ pl.imshow(ot_lpl1.coupling_, **param_img)
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Optimal coupling\nSinkhornLpl1Transport')
+
+ pl.subplot(2, 4, 4)
+ pl.imshow(ot_l1l2.coupling_, **param_img)
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Optimal coupling\nSinkhornL1l2Transport')
+
+ pl.subplot(2, 4, 5)
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.3)
+ pl.scatter(transp_Xs_emd[:, 0], transp_Xs_emd[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Transported samples\nEmdTransport')
+ pl.legend(loc="lower left")
+
+ pl.subplot(2, 4, 6)
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.3)
+ pl.scatter(transp_Xs_sinkhorn[:, 0], transp_Xs_sinkhorn[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Transported samples\nSinkhornTransport')
+
+ pl.subplot(2, 4, 7)
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.3)
+ pl.scatter(transp_Xs_lpl1[:, 0], transp_Xs_lpl1[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Transported samples\nSinkhornLpl1Transport')
+
+ pl.subplot(2, 4, 8)
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.3)
+ pl.scatter(transp_Xs_l1l2[:, 0], transp_Xs_l1l2[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Transported samples\nSinkhornL1l2Transport')
+ pl.tight_layout()
+
+ pl.show()
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_otda_classes_003.png
+ :align: center
+
+
+
+
+**Total running time of the script:** ( 0 minutes 2.308 seconds)
+
+
+
+.. container:: sphx-glr-footer
+
+
+ .. container:: sphx-glr-download
+
+ :download:`Download Python source code: plot_otda_classes.py <plot_otda_classes.py>`
+
+
+
+ .. container:: sphx-glr-download
+
+ :download:`Download Jupyter notebook: plot_otda_classes.ipynb <plot_otda_classes.ipynb>`
+
+.. rst-class:: sphx-glr-signature
+
+ `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
diff --git a/docs/source/auto_examples/plot_otda_color_images.ipynb b/docs/source/auto_examples/plot_otda_color_images.ipynb
new file mode 100644
index 0000000..2daf406
--- /dev/null
+++ b/docs/source/auto_examples/plot_otda_color_images.ipynb
@@ -0,0 +1,144 @@
+{
+ "nbformat_minor": 0,
+ "nbformat": 4,
+ "cells": [
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "%matplotlib inline"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "\n# OT for image color adaptation\n\n\nThis example presents a way of transferring colors between two image\nwith Optimal Transport as introduced in [6]\n\n[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014).\nRegularized discrete optimal transport.\nSIAM Journal on Imaging Sciences, 7(3), 1853-1882.\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# Authors: Remi Flamary <remi.flamary@unice.fr>\n# Stanislas Chambon <stan.chambon@gmail.com>\n#\n# License: MIT License\n\nimport numpy as np\nfrom scipy import ndimage\nimport matplotlib.pylab as pl\nimport ot\n\n\nr = np.random.RandomState(42)\n\n\ndef im2mat(I):\n \"\"\"Converts and image to matrix (one pixel per line)\"\"\"\n return I.reshape((I.shape[0] * I.shape[1], I.shape[2]))\n\n\ndef mat2im(X, shape):\n \"\"\"Converts back a matrix to an image\"\"\"\n return X.reshape(shape)\n\n\ndef minmax(I):\n return np.clip(I, 0, 1)"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Generate data\n-------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# Loading images\nI1 = ndimage.imread('../data/ocean_day.jpg').astype(np.float64) / 256\nI2 = ndimage.imread('../data/ocean_sunset.jpg').astype(np.float64) / 256\n\nX1 = im2mat(I1)\nX2 = im2mat(I2)\n\n# training samples\nnb = 1000\nidx1 = r.randint(X1.shape[0], size=(nb,))\nidx2 = r.randint(X2.shape[0], size=(nb,))\n\nXs = X1[idx1, :]\nXt = X2[idx2, :]"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Plot original image\n-------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "pl.figure(1, figsize=(6.4, 3))\n\npl.subplot(1, 2, 1)\npl.imshow(I1)\npl.axis('off')\npl.title('Image 1')\n\npl.subplot(1, 2, 2)\npl.imshow(I2)\npl.axis('off')\npl.title('Image 2')"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Scatter plot of colors\n----------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "pl.figure(2, figsize=(6.4, 3))\n\npl.subplot(1, 2, 1)\npl.scatter(Xs[:, 0], Xs[:, 2], c=Xs)\npl.axis([0, 1, 0, 1])\npl.xlabel('Red')\npl.ylabel('Blue')\npl.title('Image 1')\n\npl.subplot(1, 2, 2)\npl.scatter(Xt[:, 0], Xt[:, 2], c=Xt)\npl.axis([0, 1, 0, 1])\npl.xlabel('Red')\npl.ylabel('Blue')\npl.title('Image 2')\npl.tight_layout()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Instantiate the different transport algorithms and fit them\n-----------------------------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# EMDTransport\not_emd = ot.da.EMDTransport()\not_emd.fit(Xs=Xs, Xt=Xt)\n\n# SinkhornTransport\not_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)\not_sinkhorn.fit(Xs=Xs, Xt=Xt)\n\n# prediction between images (using out of sample prediction as in [6])\ntransp_Xs_emd = ot_emd.transform(Xs=X1)\ntransp_Xt_emd = ot_emd.inverse_transform(Xt=X2)\n\ntransp_Xs_sinkhorn = ot_emd.transform(Xs=X1)\ntransp_Xt_sinkhorn = ot_emd.inverse_transform(Xt=X2)\n\nI1t = minmax(mat2im(transp_Xs_emd, I1.shape))\nI2t = minmax(mat2im(transp_Xt_emd, I2.shape))\n\nI1te = minmax(mat2im(transp_Xs_sinkhorn, I1.shape))\nI2te = minmax(mat2im(transp_Xt_sinkhorn, I2.shape))"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Plot new images\n---------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "pl.figure(3, figsize=(8, 4))\n\npl.subplot(2, 3, 1)\npl.imshow(I1)\npl.axis('off')\npl.title('Image 1')\n\npl.subplot(2, 3, 2)\npl.imshow(I1t)\npl.axis('off')\npl.title('Image 1 Adapt')\n\npl.subplot(2, 3, 3)\npl.imshow(I1te)\npl.axis('off')\npl.title('Image 1 Adapt (reg)')\n\npl.subplot(2, 3, 4)\npl.imshow(I2)\npl.axis('off')\npl.title('Image 2')\n\npl.subplot(2, 3, 5)\npl.imshow(I2t)\npl.axis('off')\npl.title('Image 2 Adapt')\n\npl.subplot(2, 3, 6)\npl.imshow(I2te)\npl.axis('off')\npl.title('Image 2 Adapt (reg)')\npl.tight_layout()\n\npl.show()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "name": "python2",
+ "language": "python"
+ },
+ "language_info": {
+ "mimetype": "text/x-python",
+ "nbconvert_exporter": "python",
+ "name": "python",
+ "file_extension": ".py",
+ "version": "2.7.12",
+ "pygments_lexer": "ipython2",
+ "codemirror_mode": {
+ "version": 2,
+ "name": "ipython"
+ }
+ }
+ }
+} \ No newline at end of file
diff --git a/examples/da/plot_otda_color_images.py b/docs/source/auto_examples/plot_otda_color_images.py
index 3984afb..e77aec0 100644
--- a/examples/da/plot_otda_color_images.py
+++ b/docs/source/auto_examples/plot_otda_color_images.py
@@ -1,8 +1,8 @@
# -*- coding: utf-8 -*-
"""
-========================================================
-OT for domain adaptation with image color adaptation [6]
-========================================================
+=============================
+OT for image color adaptation
+=============================
This example presents a way of transferring colors between two image
with Optimal Transport as introduced in [6]
@@ -41,12 +41,12 @@ def minmax(I):
##############################################################################
-# generate data
-##############################################################################
+# Generate data
+# -------------
# Loading images
-I1 = ndimage.imread('../../data/ocean_day.jpg').astype(np.float64) / 256
-I2 = ndimage.imread('../../data/ocean_sunset.jpg').astype(np.float64) / 256
+I1 = ndimage.imread('../data/ocean_day.jpg').astype(np.float64) / 256
+I2 = ndimage.imread('../data/ocean_sunset.jpg').astype(np.float64) / 256
X1 = im2mat(I1)
X2 = im2mat(I2)
@@ -61,34 +61,8 @@ Xt = X2[idx2, :]
##############################################################################
-# Instantiate the different transport algorithms and fit them
-##############################################################################
-
-# EMDTransport
-ot_emd = ot.da.EMDTransport()
-ot_emd.fit(Xs=Xs, Xt=Xt)
-
-# SinkhornTransport
-ot_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)
-ot_sinkhorn.fit(Xs=Xs, Xt=Xt)
-
-# prediction between images (using out of sample prediction as in [6])
-transp_Xs_emd = ot_emd.transform(Xs=X1)
-transp_Xt_emd = ot_emd.inverse_transform(Xt=X2)
-
-transp_Xs_sinkhorn = ot_emd.transform(Xs=X1)
-transp_Xt_sinkhorn = ot_emd.inverse_transform(Xt=X2)
-
-I1t = minmax(mat2im(transp_Xs_emd, I1.shape))
-I2t = minmax(mat2im(transp_Xt_emd, I2.shape))
-
-I1te = minmax(mat2im(transp_Xs_sinkhorn, I1.shape))
-I2te = minmax(mat2im(transp_Xt_sinkhorn, I2.shape))
-
-
-##############################################################################
-# plot original image
-##############################################################################
+# Plot original image
+# -------------------
pl.figure(1, figsize=(6.4, 3))
@@ -104,8 +78,8 @@ pl.title('Image 2')
##############################################################################
-# scatter plot of colors
-##############################################################################
+# Scatter plot of colors
+# ----------------------
pl.figure(2, figsize=(6.4, 3))
@@ -126,8 +100,34 @@ pl.tight_layout()
##############################################################################
-# plot new images
+# Instantiate the different transport algorithms and fit them
+# -----------------------------------------------------------
+
+# EMDTransport
+ot_emd = ot.da.EMDTransport()
+ot_emd.fit(Xs=Xs, Xt=Xt)
+
+# SinkhornTransport
+ot_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)
+ot_sinkhorn.fit(Xs=Xs, Xt=Xt)
+
+# prediction between images (using out of sample prediction as in [6])
+transp_Xs_emd = ot_emd.transform(Xs=X1)
+transp_Xt_emd = ot_emd.inverse_transform(Xt=X2)
+
+transp_Xs_sinkhorn = ot_emd.transform(Xs=X1)
+transp_Xt_sinkhorn = ot_emd.inverse_transform(Xt=X2)
+
+I1t = minmax(mat2im(transp_Xs_emd, I1.shape))
+I2t = minmax(mat2im(transp_Xt_emd, I2.shape))
+
+I1te = minmax(mat2im(transp_Xs_sinkhorn, I1.shape))
+I2te = minmax(mat2im(transp_Xt_sinkhorn, I2.shape))
+
+
##############################################################################
+# Plot new images
+# ---------------
pl.figure(3, figsize=(8, 4))
diff --git a/docs/source/auto_examples/plot_otda_color_images.rst b/docs/source/auto_examples/plot_otda_color_images.rst
new file mode 100644
index 0000000..9c31ba7
--- /dev/null
+++ b/docs/source/auto_examples/plot_otda_color_images.rst
@@ -0,0 +1,257 @@
+
+
+.. _sphx_glr_auto_examples_plot_otda_color_images.py:
+
+
+=============================
+OT for image color adaptation
+=============================
+
+This example presents a way of transferring colors between two image
+with Optimal Transport as introduced in [6]
+
+[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014).
+Regularized discrete optimal transport.
+SIAM Journal on Imaging Sciences, 7(3), 1853-1882.
+
+
+
+.. code-block:: python
+
+
+ # Authors: Remi Flamary <remi.flamary@unice.fr>
+ # Stanislas Chambon <stan.chambon@gmail.com>
+ #
+ # License: MIT License
+
+ import numpy as np
+ from scipy import ndimage
+ import matplotlib.pylab as pl
+ import ot
+
+
+ r = np.random.RandomState(42)
+
+
+ def im2mat(I):
+ """Converts and image to matrix (one pixel per line)"""
+ return I.reshape((I.shape[0] * I.shape[1], I.shape[2]))
+
+
+ def mat2im(X, shape):
+ """Converts back a matrix to an image"""
+ return X.reshape(shape)
+
+
+ def minmax(I):
+ return np.clip(I, 0, 1)
+
+
+
+
+
+
+
+
+Generate data
+-------------
+
+
+
+.. code-block:: python
+
+
+ # Loading images
+ I1 = ndimage.imread('../data/ocean_day.jpg').astype(np.float64) / 256
+ I2 = ndimage.imread('../data/ocean_sunset.jpg').astype(np.float64) / 256
+
+ X1 = im2mat(I1)
+ X2 = im2mat(I2)
+
+ # training samples
+ nb = 1000
+ idx1 = r.randint(X1.shape[0], size=(nb,))
+ idx2 = r.randint(X2.shape[0], size=(nb,))
+
+ Xs = X1[idx1, :]
+ Xt = X2[idx2, :]
+
+
+
+
+
+
+
+
+Plot original image
+-------------------
+
+
+
+.. code-block:: python
+
+
+ pl.figure(1, figsize=(6.4, 3))
+
+ pl.subplot(1, 2, 1)
+ pl.imshow(I1)
+ pl.axis('off')
+ pl.title('Image 1')
+
+ pl.subplot(1, 2, 2)
+ pl.imshow(I2)
+ pl.axis('off')
+ pl.title('Image 2')
+
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_otda_color_images_001.png
+ :align: center
+
+
+
+
+Scatter plot of colors
+----------------------
+
+
+
+.. code-block:: python
+
+
+ pl.figure(2, figsize=(6.4, 3))
+
+ pl.subplot(1, 2, 1)
+ pl.scatter(Xs[:, 0], Xs[:, 2], c=Xs)
+ pl.axis([0, 1, 0, 1])
+ pl.xlabel('Red')
+ pl.ylabel('Blue')
+ pl.title('Image 1')
+
+ pl.subplot(1, 2, 2)
+ pl.scatter(Xt[:, 0], Xt[:, 2], c=Xt)
+ pl.axis([0, 1, 0, 1])
+ pl.xlabel('Red')
+ pl.ylabel('Blue')
+ pl.title('Image 2')
+ pl.tight_layout()
+
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_otda_color_images_003.png
+ :align: center
+
+
+
+
+Instantiate the different transport algorithms and fit them
+-----------------------------------------------------------
+
+
+
+.. code-block:: python
+
+
+ # EMDTransport
+ ot_emd = ot.da.EMDTransport()
+ ot_emd.fit(Xs=Xs, Xt=Xt)
+
+ # SinkhornTransport
+ ot_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)
+ ot_sinkhorn.fit(Xs=Xs, Xt=Xt)
+
+ # prediction between images (using out of sample prediction as in [6])
+ transp_Xs_emd = ot_emd.transform(Xs=X1)
+ transp_Xt_emd = ot_emd.inverse_transform(Xt=X2)
+
+ transp_Xs_sinkhorn = ot_emd.transform(Xs=X1)
+ transp_Xt_sinkhorn = ot_emd.inverse_transform(Xt=X2)
+
+ I1t = minmax(mat2im(transp_Xs_emd, I1.shape))
+ I2t = minmax(mat2im(transp_Xt_emd, I2.shape))
+
+ I1te = minmax(mat2im(transp_Xs_sinkhorn, I1.shape))
+ I2te = minmax(mat2im(transp_Xt_sinkhorn, I2.shape))
+
+
+
+
+
+
+
+
+Plot new images
+---------------
+
+
+
+.. code-block:: python
+
+
+ pl.figure(3, figsize=(8, 4))
+
+ pl.subplot(2, 3, 1)
+ pl.imshow(I1)
+ pl.axis('off')
+ pl.title('Image 1')
+
+ pl.subplot(2, 3, 2)
+ pl.imshow(I1t)
+ pl.axis('off')
+ pl.title('Image 1 Adapt')
+
+ pl.subplot(2, 3, 3)
+ pl.imshow(I1te)
+ pl.axis('off')
+ pl.title('Image 1 Adapt (reg)')
+
+ pl.subplot(2, 3, 4)
+ pl.imshow(I2)
+ pl.axis('off')
+ pl.title('Image 2')
+
+ pl.subplot(2, 3, 5)
+ pl.imshow(I2t)
+ pl.axis('off')
+ pl.title('Image 2 Adapt')
+
+ pl.subplot(2, 3, 6)
+ pl.imshow(I2te)
+ pl.axis('off')
+ pl.title('Image 2 Adapt (reg)')
+ pl.tight_layout()
+
+ pl.show()
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_otda_color_images_005.png
+ :align: center
+
+
+
+
+**Total running time of the script:** ( 3 minutes 16.469 seconds)
+
+
+
+.. container:: sphx-glr-footer
+
+
+ .. container:: sphx-glr-download
+
+ :download:`Download Python source code: plot_otda_color_images.py <plot_otda_color_images.py>`
+
+
+
+ .. container:: sphx-glr-download
+
+ :download:`Download Jupyter notebook: plot_otda_color_images.ipynb <plot_otda_color_images.ipynb>`
+
+.. rst-class:: sphx-glr-signature
+
+ `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
diff --git a/docs/source/auto_examples/plot_otda_d2.ipynb b/docs/source/auto_examples/plot_otda_d2.ipynb
new file mode 100644
index 0000000..7bfcc9a
--- /dev/null
+++ b/docs/source/auto_examples/plot_otda_d2.ipynb
@@ -0,0 +1,144 @@
+{
+ "nbformat_minor": 0,
+ "nbformat": 4,
+ "cells": [
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "%matplotlib inline"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "\n# OT for domain adaptation on empirical distributions\n\n\nThis example introduces a domain adaptation in a 2D setting. It explicits\nthe problem of domain adaptation and introduces some optimal transport\napproaches to solve it.\n\nQuantities such as optimal couplings, greater coupling coefficients and\ntransported samples are represented in order to give a visual understanding\nof what the transport methods are doing.\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# Authors: Remi Flamary <remi.flamary@unice.fr>\n# Stanislas Chambon <stan.chambon@gmail.com>\n#\n# License: MIT License\n\nimport matplotlib.pylab as pl\nimport ot"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "generate data\n-------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "n_samples_source = 150\nn_samples_target = 150\n\nXs, ys = ot.datasets.get_data_classif('3gauss', n_samples_source)\nXt, yt = ot.datasets.get_data_classif('3gauss2', n_samples_target)\n\n# Cost matrix\nM = ot.dist(Xs, Xt, metric='sqeuclidean')"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Instantiate the different transport algorithms and fit them\n-----------------------------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# EMD Transport\not_emd = ot.da.EMDTransport()\not_emd.fit(Xs=Xs, Xt=Xt)\n\n# Sinkhorn Transport\not_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)\not_sinkhorn.fit(Xs=Xs, Xt=Xt)\n\n# Sinkhorn Transport with Group lasso regularization\not_lpl1 = ot.da.SinkhornLpl1Transport(reg_e=1e-1, reg_cl=1e0)\not_lpl1.fit(Xs=Xs, ys=ys, Xt=Xt)\n\n# transport source samples onto target samples\ntransp_Xs_emd = ot_emd.transform(Xs=Xs)\ntransp_Xs_sinkhorn = ot_sinkhorn.transform(Xs=Xs)\ntransp_Xs_lpl1 = ot_lpl1.transform(Xs=Xs)"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Fig 1 : plots source and target samples + matrix of pairwise distance\n---------------------------------------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "pl.figure(1, figsize=(10, 10))\npl.subplot(2, 2, 1)\npl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')\npl.xticks([])\npl.yticks([])\npl.legend(loc=0)\npl.title('Source samples')\n\npl.subplot(2, 2, 2)\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')\npl.xticks([])\npl.yticks([])\npl.legend(loc=0)\npl.title('Target samples')\n\npl.subplot(2, 2, 3)\npl.imshow(M, interpolation='nearest')\npl.xticks([])\npl.yticks([])\npl.title('Matrix of pairwise distances')\npl.tight_layout()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Fig 2 : plots optimal couplings for the different methods\n---------------------------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "pl.figure(2, figsize=(10, 6))\n\npl.subplot(2, 3, 1)\npl.imshow(ot_emd.coupling_, interpolation='nearest')\npl.xticks([])\npl.yticks([])\npl.title('Optimal coupling\\nEMDTransport')\n\npl.subplot(2, 3, 2)\npl.imshow(ot_sinkhorn.coupling_, interpolation='nearest')\npl.xticks([])\npl.yticks([])\npl.title('Optimal coupling\\nSinkhornTransport')\n\npl.subplot(2, 3, 3)\npl.imshow(ot_lpl1.coupling_, interpolation='nearest')\npl.xticks([])\npl.yticks([])\npl.title('Optimal coupling\\nSinkhornLpl1Transport')\n\npl.subplot(2, 3, 4)\not.plot.plot2D_samples_mat(Xs, Xt, ot_emd.coupling_, c=[.5, .5, 1])\npl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')\npl.xticks([])\npl.yticks([])\npl.title('Main coupling coefficients\\nEMDTransport')\n\npl.subplot(2, 3, 5)\not.plot.plot2D_samples_mat(Xs, Xt, ot_sinkhorn.coupling_, c=[.5, .5, 1])\npl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')\npl.xticks([])\npl.yticks([])\npl.title('Main coupling coefficients\\nSinkhornTransport')\n\npl.subplot(2, 3, 6)\not.plot.plot2D_samples_mat(Xs, Xt, ot_lpl1.coupling_, c=[.5, .5, 1])\npl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')\npl.xticks([])\npl.yticks([])\npl.title('Main coupling coefficients\\nSinkhornLpl1Transport')\npl.tight_layout()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Fig 3 : plot transported samples\n--------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# display transported samples\npl.figure(4, figsize=(10, 4))\npl.subplot(1, 3, 1)\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n label='Target samples', alpha=0.5)\npl.scatter(transp_Xs_emd[:, 0], transp_Xs_emd[:, 1], c=ys,\n marker='+', label='Transp samples', s=30)\npl.title('Transported samples\\nEmdTransport')\npl.legend(loc=0)\npl.xticks([])\npl.yticks([])\n\npl.subplot(1, 3, 2)\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n label='Target samples', alpha=0.5)\npl.scatter(transp_Xs_sinkhorn[:, 0], transp_Xs_sinkhorn[:, 1], c=ys,\n marker='+', label='Transp samples', s=30)\npl.title('Transported samples\\nSinkhornTransport')\npl.xticks([])\npl.yticks([])\n\npl.subplot(1, 3, 3)\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n label='Target samples', alpha=0.5)\npl.scatter(transp_Xs_lpl1[:, 0], transp_Xs_lpl1[:, 1], c=ys,\n marker='+', label='Transp samples', s=30)\npl.title('Transported samples\\nSinkhornLpl1Transport')\npl.xticks([])\npl.yticks([])\n\npl.tight_layout()\npl.show()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "name": "python2",
+ "language": "python"
+ },
+ "language_info": {
+ "mimetype": "text/x-python",
+ "nbconvert_exporter": "python",
+ "name": "python",
+ "file_extension": ".py",
+ "version": "2.7.12",
+ "pygments_lexer": "ipython2",
+ "codemirror_mode": {
+ "version": 2,
+ "name": "ipython"
+ }
+ }
+ }
+} \ No newline at end of file
diff --git a/examples/da/plot_otda_d2.py b/docs/source/auto_examples/plot_otda_d2.py
index 3daa0a6..e53d7d6 100644
--- a/examples/da/plot_otda_d2.py
+++ b/docs/source/auto_examples/plot_otda_d2.py
@@ -1,8 +1,8 @@
# -*- coding: utf-8 -*-
"""
-==============================
-OT for empirical distributions
-==============================
+===================================================
+OT for domain adaptation on empirical distributions
+===================================================
This example introduces a domain adaptation in a 2D setting. It explicits
the problem of domain adaptation and introduces some optimal transport
@@ -24,7 +24,7 @@ import ot
##############################################################################
# generate data
-##############################################################################
+# -------------
n_samples_source = 150
n_samples_target = 150
@@ -38,7 +38,7 @@ M = ot.dist(Xs, Xt, metric='sqeuclidean')
##############################################################################
# Instantiate the different transport algorithms and fit them
-##############################################################################
+# -----------------------------------------------------------
# EMD Transport
ot_emd = ot.da.EMDTransport()
@@ -60,7 +60,7 @@ transp_Xs_lpl1 = ot_lpl1.transform(Xs=Xs)
##############################################################################
# Fig 1 : plots source and target samples + matrix of pairwise distance
-##############################################################################
+# ---------------------------------------------------------------------
pl.figure(1, figsize=(10, 10))
pl.subplot(2, 2, 1)
@@ -87,8 +87,7 @@ pl.tight_layout()
##############################################################################
# Fig 2 : plots optimal couplings for the different methods
-##############################################################################
-
+# ---------------------------------------------------------
pl.figure(2, figsize=(10, 6))
pl.subplot(2, 3, 1)
@@ -137,7 +136,7 @@ pl.tight_layout()
##############################################################################
# Fig 3 : plot transported samples
-##############################################################################
+# --------------------------------
# display transported samples
pl.figure(4, figsize=(10, 4))
diff --git a/docs/source/auto_examples/plot_otda_d2.rst b/docs/source/auto_examples/plot_otda_d2.rst
new file mode 100644
index 0000000..1bbe6d9
--- /dev/null
+++ b/docs/source/auto_examples/plot_otda_d2.rst
@@ -0,0 +1,264 @@
+
+
+.. _sphx_glr_auto_examples_plot_otda_d2.py:
+
+
+===================================================
+OT for domain adaptation on empirical distributions
+===================================================
+
+This example introduces a domain adaptation in a 2D setting. It explicits
+the problem of domain adaptation and introduces some optimal transport
+approaches to solve it.
+
+Quantities such as optimal couplings, greater coupling coefficients and
+transported samples are represented in order to give a visual understanding
+of what the transport methods are doing.
+
+
+
+.. code-block:: python
+
+
+ # Authors: Remi Flamary <remi.flamary@unice.fr>
+ # Stanislas Chambon <stan.chambon@gmail.com>
+ #
+ # License: MIT License
+
+ import matplotlib.pylab as pl
+ import ot
+
+
+
+
+
+
+
+
+generate data
+-------------
+
+
+
+.. code-block:: python
+
+
+ n_samples_source = 150
+ n_samples_target = 150
+
+ Xs, ys = ot.datasets.get_data_classif('3gauss', n_samples_source)
+ Xt, yt = ot.datasets.get_data_classif('3gauss2', n_samples_target)
+
+ # Cost matrix
+ M = ot.dist(Xs, Xt, metric='sqeuclidean')
+
+
+
+
+
+
+
+
+Instantiate the different transport algorithms and fit them
+-----------------------------------------------------------
+
+
+
+.. code-block:: python
+
+
+ # EMD Transport
+ ot_emd = ot.da.EMDTransport()
+ ot_emd.fit(Xs=Xs, Xt=Xt)
+
+ # Sinkhorn Transport
+ ot_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)
+ ot_sinkhorn.fit(Xs=Xs, Xt=Xt)
+
+ # Sinkhorn Transport with Group lasso regularization
+ ot_lpl1 = ot.da.SinkhornLpl1Transport(reg_e=1e-1, reg_cl=1e0)
+ ot_lpl1.fit(Xs=Xs, ys=ys, Xt=Xt)
+
+ # transport source samples onto target samples
+ transp_Xs_emd = ot_emd.transform(Xs=Xs)
+ transp_Xs_sinkhorn = ot_sinkhorn.transform(Xs=Xs)
+ transp_Xs_lpl1 = ot_lpl1.transform(Xs=Xs)
+
+
+
+
+
+
+
+
+Fig 1 : plots source and target samples + matrix of pairwise distance
+---------------------------------------------------------------------
+
+
+
+.. code-block:: python
+
+
+ pl.figure(1, figsize=(10, 10))
+ pl.subplot(2, 2, 1)
+ pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')
+ pl.xticks([])
+ pl.yticks([])
+ pl.legend(loc=0)
+ pl.title('Source samples')
+
+ pl.subplot(2, 2, 2)
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')
+ pl.xticks([])
+ pl.yticks([])
+ pl.legend(loc=0)
+ pl.title('Target samples')
+
+ pl.subplot(2, 2, 3)
+ pl.imshow(M, interpolation='nearest')
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Matrix of pairwise distances')
+ pl.tight_layout()
+
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_otda_d2_001.png
+ :align: center
+
+
+
+
+Fig 2 : plots optimal couplings for the different methods
+---------------------------------------------------------
+
+
+
+.. code-block:: python
+
+ pl.figure(2, figsize=(10, 6))
+
+ pl.subplot(2, 3, 1)
+ pl.imshow(ot_emd.coupling_, interpolation='nearest')
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Optimal coupling\nEMDTransport')
+
+ pl.subplot(2, 3, 2)
+ pl.imshow(ot_sinkhorn.coupling_, interpolation='nearest')
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Optimal coupling\nSinkhornTransport')
+
+ pl.subplot(2, 3, 3)
+ pl.imshow(ot_lpl1.coupling_, interpolation='nearest')
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Optimal coupling\nSinkhornLpl1Transport')
+
+ pl.subplot(2, 3, 4)
+ ot.plot.plot2D_samples_mat(Xs, Xt, ot_emd.coupling_, c=[.5, .5, 1])
+ pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Main coupling coefficients\nEMDTransport')
+
+ pl.subplot(2, 3, 5)
+ ot.plot.plot2D_samples_mat(Xs, Xt, ot_sinkhorn.coupling_, c=[.5, .5, 1])
+ pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Main coupling coefficients\nSinkhornTransport')
+
+ pl.subplot(2, 3, 6)
+ ot.plot.plot2D_samples_mat(Xs, Xt, ot_lpl1.coupling_, c=[.5, .5, 1])
+ pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Main coupling coefficients\nSinkhornLpl1Transport')
+ pl.tight_layout()
+
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_otda_d2_003.png
+ :align: center
+
+
+
+
+Fig 3 : plot transported samples
+--------------------------------
+
+
+
+.. code-block:: python
+
+
+ # display transported samples
+ pl.figure(4, figsize=(10, 4))
+ pl.subplot(1, 3, 1)
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.5)
+ pl.scatter(transp_Xs_emd[:, 0], transp_Xs_emd[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+ pl.title('Transported samples\nEmdTransport')
+ pl.legend(loc=0)
+ pl.xticks([])
+ pl.yticks([])
+
+ pl.subplot(1, 3, 2)
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.5)
+ pl.scatter(transp_Xs_sinkhorn[:, 0], transp_Xs_sinkhorn[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+ pl.title('Transported samples\nSinkhornTransport')
+ pl.xticks([])
+ pl.yticks([])
+
+ pl.subplot(1, 3, 3)
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.5)
+ pl.scatter(transp_Xs_lpl1[:, 0], transp_Xs_lpl1[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+ pl.title('Transported samples\nSinkhornLpl1Transport')
+ pl.xticks([])
+ pl.yticks([])
+
+ pl.tight_layout()
+ pl.show()
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_otda_d2_006.png
+ :align: center
+
+
+
+
+**Total running time of the script:** ( 0 minutes 47.000 seconds)
+
+
+
+.. container:: sphx-glr-footer
+
+
+ .. container:: sphx-glr-download
+
+ :download:`Download Python source code: plot_otda_d2.py <plot_otda_d2.py>`
+
+
+
+ .. container:: sphx-glr-download
+
+ :download:`Download Jupyter notebook: plot_otda_d2.ipynb <plot_otda_d2.ipynb>`
+
+.. rst-class:: sphx-glr-signature
+
+ `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
diff --git a/docs/source/auto_examples/plot_otda_mapping.ipynb b/docs/source/auto_examples/plot_otda_mapping.ipynb
new file mode 100644
index 0000000..0374146
--- /dev/null
+++ b/docs/source/auto_examples/plot_otda_mapping.ipynb
@@ -0,0 +1,126 @@
+{
+ "nbformat_minor": 0,
+ "nbformat": 4,
+ "cells": [
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "%matplotlib inline"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "\n# OT mapping estimation for domain adaptation\n\n\nThis example presents how to use MappingTransport to estimate at the same\ntime both the coupling transport and approximate the transport map with either\na linear or a kernelized mapping as introduced in [8].\n\n[8] M. Perrot, N. Courty, R. Flamary, A. Habrard,\n \"Mapping estimation for discrete optimal transport\",\n Neural Information Processing Systems (NIPS), 2016.\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# Authors: Remi Flamary <remi.flamary@unice.fr>\n# Stanislas Chambon <stan.chambon@gmail.com>\n#\n# License: MIT License\n\nimport numpy as np\nimport matplotlib.pylab as pl\nimport ot"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Generate data\n-------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "n_source_samples = 100\nn_target_samples = 100\ntheta = 2 * np.pi / 20\nnoise_level = 0.1\n\nXs, ys = ot.datasets.get_data_classif(\n 'gaussrot', n_source_samples, nz=noise_level)\nXs_new, _ = ot.datasets.get_data_classif(\n 'gaussrot', n_source_samples, nz=noise_level)\nXt, yt = ot.datasets.get_data_classif(\n 'gaussrot', n_target_samples, theta=theta, nz=noise_level)\n\n# one of the target mode changes its variance (no linear mapping)\nXt[yt == 2] *= 3\nXt = Xt + 4"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Plot data\n---------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "pl.figure(1, (10, 5))\npl.clf()\npl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')\npl.legend(loc=0)\npl.title('Source and target distributions')"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Instantiate the different transport algorithms and fit them\n-----------------------------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# MappingTransport with linear kernel\not_mapping_linear = ot.da.MappingTransport(\n kernel=\"linear\", mu=1e0, eta=1e-8, bias=True,\n max_iter=20, verbose=True)\n\not_mapping_linear.fit(Xs=Xs, Xt=Xt)\n\n# for original source samples, transform applies barycentric mapping\ntransp_Xs_linear = ot_mapping_linear.transform(Xs=Xs)\n\n# for out of source samples, transform applies the linear mapping\ntransp_Xs_linear_new = ot_mapping_linear.transform(Xs=Xs_new)\n\n\n# MappingTransport with gaussian kernel\not_mapping_gaussian = ot.da.MappingTransport(\n kernel=\"gaussian\", eta=1e-5, mu=1e-1, bias=True, sigma=1,\n max_iter=10, verbose=True)\not_mapping_gaussian.fit(Xs=Xs, Xt=Xt)\n\n# for original source samples, transform applies barycentric mapping\ntransp_Xs_gaussian = ot_mapping_gaussian.transform(Xs=Xs)\n\n# for out of source samples, transform applies the gaussian mapping\ntransp_Xs_gaussian_new = ot_mapping_gaussian.transform(Xs=Xs_new)"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Plot transported samples\n------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "pl.figure(2)\npl.clf()\npl.subplot(2, 2, 1)\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n label='Target samples', alpha=.2)\npl.scatter(transp_Xs_linear[:, 0], transp_Xs_linear[:, 1], c=ys, marker='+',\n label='Mapped source samples')\npl.title(\"Bary. mapping (linear)\")\npl.legend(loc=0)\n\npl.subplot(2, 2, 2)\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n label='Target samples', alpha=.2)\npl.scatter(transp_Xs_linear_new[:, 0], transp_Xs_linear_new[:, 1],\n c=ys, marker='+', label='Learned mapping')\npl.title(\"Estim. mapping (linear)\")\n\npl.subplot(2, 2, 3)\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n label='Target samples', alpha=.2)\npl.scatter(transp_Xs_gaussian[:, 0], transp_Xs_gaussian[:, 1], c=ys,\n marker='+', label='barycentric mapping')\npl.title(\"Bary. mapping (kernel)\")\n\npl.subplot(2, 2, 4)\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n label='Target samples', alpha=.2)\npl.scatter(transp_Xs_gaussian_new[:, 0], transp_Xs_gaussian_new[:, 1], c=ys,\n marker='+', label='Learned mapping')\npl.title(\"Estim. mapping (kernel)\")\npl.tight_layout()\n\npl.show()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "name": "python2",
+ "language": "python"
+ },
+ "language_info": {
+ "mimetype": "text/x-python",
+ "nbconvert_exporter": "python",
+ "name": "python",
+ "file_extension": ".py",
+ "version": "2.7.12",
+ "pygments_lexer": "ipython2",
+ "codemirror_mode": {
+ "version": 2,
+ "name": "ipython"
+ }
+ }
+ }
+} \ No newline at end of file
diff --git a/examples/da/plot_otda_mapping.py b/docs/source/auto_examples/plot_otda_mapping.py
index 09d2cb4..167c3a1 100644
--- a/examples/da/plot_otda_mapping.py
+++ b/docs/source/auto_examples/plot_otda_mapping.py
@@ -1,12 +1,12 @@
# -*- coding: utf-8 -*-
"""
-===============================================
-OT mapping estimation for domain adaptation [8]
-===============================================
+===========================================
+OT mapping estimation for domain adaptation
+===========================================
This example presents how to use MappingTransport to estimate at the same
time both the coupling transport and approximate the transport map with either
-a linear or a kernelized mapping as introduced in [8]
+a linear or a kernelized mapping as introduced in [8].
[8] M. Perrot, N. Courty, R. Flamary, A. Habrard,
"Mapping estimation for discrete optimal transport",
@@ -24,8 +24,8 @@ import ot
##############################################################################
-# generate data
-##############################################################################
+# Generate data
+# -------------
n_source_samples = 100
n_target_samples = 100
@@ -43,10 +43,21 @@ Xt, yt = ot.datasets.get_data_classif(
Xt[yt == 2] *= 3
Xt = Xt + 4
+##############################################################################
+# Plot data
+# ---------
+
+pl.figure(1, (10, 5))
+pl.clf()
+pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')
+pl.legend(loc=0)
+pl.title('Source and target distributions')
+
##############################################################################
# Instantiate the different transport algorithms and fit them
-##############################################################################
+# -----------------------------------------------------------
# MappingTransport with linear kernel
ot_mapping_linear = ot.da.MappingTransport(
@@ -76,20 +87,8 @@ transp_Xs_gaussian_new = ot_mapping_gaussian.transform(Xs=Xs_new)
##############################################################################
-# plot data
-##############################################################################
-
-pl.figure(1, (10, 5))
-pl.clf()
-pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')
-pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')
-pl.legend(loc=0)
-pl.title('Source and target distributions')
-
-
-##############################################################################
-# plot transported samples
-##############################################################################
+# Plot transported samples
+# ------------------------
pl.figure(2)
pl.clf()
diff --git a/docs/source/auto_examples/plot_otda_mapping.rst b/docs/source/auto_examples/plot_otda_mapping.rst
new file mode 100644
index 0000000..1e3a709
--- /dev/null
+++ b/docs/source/auto_examples/plot_otda_mapping.rst
@@ -0,0 +1,230 @@
+
+
+.. _sphx_glr_auto_examples_plot_otda_mapping.py:
+
+
+===========================================
+OT mapping estimation for domain adaptation
+===========================================
+
+This example presents how to use MappingTransport to estimate at the same
+time both the coupling transport and approximate the transport map with either
+a linear or a kernelized mapping as introduced in [8].
+
+[8] M. Perrot, N. Courty, R. Flamary, A. Habrard,
+ "Mapping estimation for discrete optimal transport",
+ Neural Information Processing Systems (NIPS), 2016.
+
+
+
+.. code-block:: python
+
+
+ # Authors: Remi Flamary <remi.flamary@unice.fr>
+ # Stanislas Chambon <stan.chambon@gmail.com>
+ #
+ # License: MIT License
+
+ import numpy as np
+ import matplotlib.pylab as pl
+ import ot
+
+
+
+
+
+
+
+
+Generate data
+-------------
+
+
+
+.. code-block:: python
+
+
+ n_source_samples = 100
+ n_target_samples = 100
+ theta = 2 * np.pi / 20
+ noise_level = 0.1
+
+ Xs, ys = ot.datasets.get_data_classif(
+ 'gaussrot', n_source_samples, nz=noise_level)
+ Xs_new, _ = ot.datasets.get_data_classif(
+ 'gaussrot', n_source_samples, nz=noise_level)
+ Xt, yt = ot.datasets.get_data_classif(
+ 'gaussrot', n_target_samples, theta=theta, nz=noise_level)
+
+ # one of the target mode changes its variance (no linear mapping)
+ Xt[yt == 2] *= 3
+ Xt = Xt + 4
+
+
+
+
+
+
+
+Plot data
+---------
+
+
+
+.. code-block:: python
+
+
+ pl.figure(1, (10, 5))
+ pl.clf()
+ pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')
+ pl.legend(loc=0)
+ pl.title('Source and target distributions')
+
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_otda_mapping_001.png
+ :align: center
+
+
+
+
+Instantiate the different transport algorithms and fit them
+-----------------------------------------------------------
+
+
+
+.. code-block:: python
+
+
+ # MappingTransport with linear kernel
+ ot_mapping_linear = ot.da.MappingTransport(
+ kernel="linear", mu=1e0, eta=1e-8, bias=True,
+ max_iter=20, verbose=True)
+
+ ot_mapping_linear.fit(Xs=Xs, Xt=Xt)
+
+ # for original source samples, transform applies barycentric mapping
+ transp_Xs_linear = ot_mapping_linear.transform(Xs=Xs)
+
+ # for out of source samples, transform applies the linear mapping
+ transp_Xs_linear_new = ot_mapping_linear.transform(Xs=Xs_new)
+
+
+ # MappingTransport with gaussian kernel
+ ot_mapping_gaussian = ot.da.MappingTransport(
+ kernel="gaussian", eta=1e-5, mu=1e-1, bias=True, sigma=1,
+ max_iter=10, verbose=True)
+ ot_mapping_gaussian.fit(Xs=Xs, Xt=Xt)
+
+ # for original source samples, transform applies barycentric mapping
+ transp_Xs_gaussian = ot_mapping_gaussian.transform(Xs=Xs)
+
+ # for out of source samples, transform applies the gaussian mapping
+ transp_Xs_gaussian_new = ot_mapping_gaussian.transform(Xs=Xs_new)
+
+
+
+
+
+
+.. rst-class:: sphx-glr-script-out
+
+ Out::
+
+ It. |Loss |Delta loss
+ --------------------------------
+ 0|4.231423e+03|0.000000e+00
+ 1|4.217955e+03|-3.182835e-03
+ 2|4.217580e+03|-8.885864e-05
+ 3|4.217451e+03|-3.043162e-05
+ 4|4.217368e+03|-1.978325e-05
+ 5|4.217312e+03|-1.338471e-05
+ 6|4.217307e+03|-1.000290e-06
+ It. |Loss |Delta loss
+ --------------------------------
+ 0|4.257004e+02|0.000000e+00
+ 1|4.208978e+02|-1.128168e-02
+ 2|4.205168e+02|-9.052112e-04
+ 3|4.203566e+02|-3.810681e-04
+ 4|4.202570e+02|-2.369884e-04
+ 5|4.201844e+02|-1.726132e-04
+ 6|4.201341e+02|-1.196461e-04
+ 7|4.200941e+02|-9.525441e-05
+ 8|4.200630e+02|-7.405552e-05
+ 9|4.200377e+02|-6.031884e-05
+ 10|4.200168e+02|-4.968324e-05
+
+
+Plot transported samples
+------------------------
+
+
+
+.. code-block:: python
+
+
+ pl.figure(2)
+ pl.clf()
+ pl.subplot(2, 2, 1)
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=.2)
+ pl.scatter(transp_Xs_linear[:, 0], transp_Xs_linear[:, 1], c=ys, marker='+',
+ label='Mapped source samples')
+ pl.title("Bary. mapping (linear)")
+ pl.legend(loc=0)
+
+ pl.subplot(2, 2, 2)
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=.2)
+ pl.scatter(transp_Xs_linear_new[:, 0], transp_Xs_linear_new[:, 1],
+ c=ys, marker='+', label='Learned mapping')
+ pl.title("Estim. mapping (linear)")
+
+ pl.subplot(2, 2, 3)
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=.2)
+ pl.scatter(transp_Xs_gaussian[:, 0], transp_Xs_gaussian[:, 1], c=ys,
+ marker='+', label='barycentric mapping')
+ pl.title("Bary. mapping (kernel)")
+
+ pl.subplot(2, 2, 4)
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=.2)
+ pl.scatter(transp_Xs_gaussian_new[:, 0], transp_Xs_gaussian_new[:, 1], c=ys,
+ marker='+', label='Learned mapping')
+ pl.title("Estim. mapping (kernel)")
+ pl.tight_layout()
+
+ pl.show()
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_otda_mapping_003.png
+ :align: center
+
+
+
+
+**Total running time of the script:** ( 0 minutes 0.970 seconds)
+
+
+
+.. container:: sphx-glr-footer
+
+
+ .. container:: sphx-glr-download
+
+ :download:`Download Python source code: plot_otda_mapping.py <plot_otda_mapping.py>`
+
+
+
+ .. container:: sphx-glr-download
+
+ :download:`Download Jupyter notebook: plot_otda_mapping.ipynb <plot_otda_mapping.ipynb>`
+
+.. rst-class:: sphx-glr-signature
+
+ `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
diff --git a/docs/source/auto_examples/plot_otda_mapping_colors_images.ipynb b/docs/source/auto_examples/plot_otda_mapping_colors_images.ipynb
new file mode 100644
index 0000000..56caa8a
--- /dev/null
+++ b/docs/source/auto_examples/plot_otda_mapping_colors_images.ipynb
@@ -0,0 +1,144 @@
+{
+ "nbformat_minor": 0,
+ "nbformat": 4,
+ "cells": [
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "%matplotlib inline"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "\n# OT for image color adaptation with mapping estimation\n\n\nOT for domain adaptation with image color adaptation [6] with mapping\nestimation [8].\n\n[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014). Regularized\n discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3),\n 1853-1882.\n[8] M. Perrot, N. Courty, R. Flamary, A. Habrard, \"Mapping estimation for\n discrete optimal transport\", Neural Information Processing Systems (NIPS),\n 2016.\n\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# Authors: Remi Flamary <remi.flamary@unice.fr>\n# Stanislas Chambon <stan.chambon@gmail.com>\n#\n# License: MIT License\n\nimport numpy as np\nfrom scipy import ndimage\nimport matplotlib.pylab as pl\nimport ot\n\nr = np.random.RandomState(42)\n\n\ndef im2mat(I):\n \"\"\"Converts and image to matrix (one pixel per line)\"\"\"\n return I.reshape((I.shape[0] * I.shape[1], I.shape[2]))\n\n\ndef mat2im(X, shape):\n \"\"\"Converts back a matrix to an image\"\"\"\n return X.reshape(shape)\n\n\ndef minmax(I):\n return np.clip(I, 0, 1)"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Generate data\n-------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# Loading images\nI1 = ndimage.imread('../data/ocean_day.jpg').astype(np.float64) / 256\nI2 = ndimage.imread('../data/ocean_sunset.jpg').astype(np.float64) / 256\n\n\nX1 = im2mat(I1)\nX2 = im2mat(I2)\n\n# training samples\nnb = 1000\nidx1 = r.randint(X1.shape[0], size=(nb,))\nidx2 = r.randint(X2.shape[0], size=(nb,))\n\nXs = X1[idx1, :]\nXt = X2[idx2, :]"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Domain adaptation for pixel distribution transfer\n-------------------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# EMDTransport\not_emd = ot.da.EMDTransport()\not_emd.fit(Xs=Xs, Xt=Xt)\ntransp_Xs_emd = ot_emd.transform(Xs=X1)\nImage_emd = minmax(mat2im(transp_Xs_emd, I1.shape))\n\n# SinkhornTransport\not_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)\not_sinkhorn.fit(Xs=Xs, Xt=Xt)\ntransp_Xs_sinkhorn = ot_emd.transform(Xs=X1)\nImage_sinkhorn = minmax(mat2im(transp_Xs_sinkhorn, I1.shape))\n\not_mapping_linear = ot.da.MappingTransport(\n mu=1e0, eta=1e-8, bias=True, max_iter=20, verbose=True)\not_mapping_linear.fit(Xs=Xs, Xt=Xt)\n\nX1tl = ot_mapping_linear.transform(Xs=X1)\nImage_mapping_linear = minmax(mat2im(X1tl, I1.shape))\n\not_mapping_gaussian = ot.da.MappingTransport(\n mu=1e0, eta=1e-2, sigma=1, bias=False, max_iter=10, verbose=True)\not_mapping_gaussian.fit(Xs=Xs, Xt=Xt)\n\nX1tn = ot_mapping_gaussian.transform(Xs=X1) # use the estimated mapping\nImage_mapping_gaussian = minmax(mat2im(X1tn, I1.shape))"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Plot original images\n--------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "pl.figure(1, figsize=(6.4, 3))\npl.subplot(1, 2, 1)\npl.imshow(I1)\npl.axis('off')\npl.title('Image 1')\n\npl.subplot(1, 2, 2)\npl.imshow(I2)\npl.axis('off')\npl.title('Image 2')\npl.tight_layout()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Plot pixel values distribution\n------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "pl.figure(2, figsize=(6.4, 5))\n\npl.subplot(1, 2, 1)\npl.scatter(Xs[:, 0], Xs[:, 2], c=Xs)\npl.axis([0, 1, 0, 1])\npl.xlabel('Red')\npl.ylabel('Blue')\npl.title('Image 1')\n\npl.subplot(1, 2, 2)\npl.scatter(Xt[:, 0], Xt[:, 2], c=Xt)\npl.axis([0, 1, 0, 1])\npl.xlabel('Red')\npl.ylabel('Blue')\npl.title('Image 2')\npl.tight_layout()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Plot transformed images\n-----------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "pl.figure(2, figsize=(10, 5))\n\npl.subplot(2, 3, 1)\npl.imshow(I1)\npl.axis('off')\npl.title('Im. 1')\n\npl.subplot(2, 3, 4)\npl.imshow(I2)\npl.axis('off')\npl.title('Im. 2')\n\npl.subplot(2, 3, 2)\npl.imshow(Image_emd)\npl.axis('off')\npl.title('EmdTransport')\n\npl.subplot(2, 3, 5)\npl.imshow(Image_sinkhorn)\npl.axis('off')\npl.title('SinkhornTransport')\n\npl.subplot(2, 3, 3)\npl.imshow(Image_mapping_linear)\npl.axis('off')\npl.title('MappingTransport (linear)')\n\npl.subplot(2, 3, 6)\npl.imshow(Image_mapping_gaussian)\npl.axis('off')\npl.title('MappingTransport (gaussian)')\npl.tight_layout()\n\npl.show()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "name": "python2",
+ "language": "python"
+ },
+ "language_info": {
+ "mimetype": "text/x-python",
+ "nbconvert_exporter": "python",
+ "name": "python",
+ "file_extension": ".py",
+ "version": "2.7.12",
+ "pygments_lexer": "ipython2",
+ "codemirror_mode": {
+ "version": 2,
+ "name": "ipython"
+ }
+ }
+ }
+} \ No newline at end of file
diff --git a/examples/da/plot_otda_mapping_colors_images.py b/docs/source/auto_examples/plot_otda_mapping_colors_images.py
index a628b05..5f1e844 100644
--- a/examples/da/plot_otda_mapping_colors_images.py
+++ b/docs/source/auto_examples/plot_otda_mapping_colors_images.py
@@ -1,8 +1,11 @@
# -*- coding: utf-8 -*-
"""
-====================================================================================
-OT for domain adaptation with image color adaptation [6] with mapping estimation [8]
-====================================================================================
+=====================================================
+OT for image color adaptation with mapping estimation
+=====================================================
+
+OT for domain adaptation with image color adaptation [6] with mapping
+estimation [8].
[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014). Regularized
discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3),
@@ -42,11 +45,11 @@ def minmax(I):
##############################################################################
# Generate data
-##############################################################################
+# -------------
# Loading images
-I1 = ndimage.imread('../../data/ocean_day.jpg').astype(np.float64) / 256
-I2 = ndimage.imread('../../data/ocean_sunset.jpg').astype(np.float64) / 256
+I1 = ndimage.imread('../data/ocean_day.jpg').astype(np.float64) / 256
+I2 = ndimage.imread('../data/ocean_sunset.jpg').astype(np.float64) / 256
X1 = im2mat(I1)
@@ -63,7 +66,7 @@ Xt = X2[idx2, :]
##############################################################################
# Domain adaptation for pixel distribution transfer
-##############################################################################
+# -------------------------------------------------
# EMDTransport
ot_emd = ot.da.EMDTransport()
@@ -93,8 +96,8 @@ Image_mapping_gaussian = minmax(mat2im(X1tn, I1.shape))
##############################################################################
-# plot original images
-##############################################################################
+# Plot original images
+# --------------------
pl.figure(1, figsize=(6.4, 3))
pl.subplot(1, 2, 1)
@@ -110,8 +113,8 @@ pl.tight_layout()
##############################################################################
-# plot pixel values distribution
-##############################################################################
+# Plot pixel values distribution
+# ------------------------------
pl.figure(2, figsize=(6.4, 5))
@@ -132,8 +135,8 @@ pl.tight_layout()
##############################################################################
-# plot transformed images
-##############################################################################
+# Plot transformed images
+# -----------------------
pl.figure(2, figsize=(10, 5))
diff --git a/docs/source/auto_examples/plot_otda_mapping_colors_images.rst b/docs/source/auto_examples/plot_otda_mapping_colors_images.rst
new file mode 100644
index 0000000..8394fb0
--- /dev/null
+++ b/docs/source/auto_examples/plot_otda_mapping_colors_images.rst
@@ -0,0 +1,305 @@
+
+
+.. _sphx_glr_auto_examples_plot_otda_mapping_colors_images.py:
+
+
+=====================================================
+OT for image color adaptation with mapping estimation
+=====================================================
+
+OT for domain adaptation with image color adaptation [6] with mapping
+estimation [8].
+
+[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014). Regularized
+ discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3),
+ 1853-1882.
+[8] M. Perrot, N. Courty, R. Flamary, A. Habrard, "Mapping estimation for
+ discrete optimal transport", Neural Information Processing Systems (NIPS),
+ 2016.
+
+
+
+
+.. code-block:: python
+
+
+ # Authors: Remi Flamary <remi.flamary@unice.fr>
+ # Stanislas Chambon <stan.chambon@gmail.com>
+ #
+ # License: MIT License
+
+ import numpy as np
+ from scipy import ndimage
+ import matplotlib.pylab as pl
+ import ot
+
+ r = np.random.RandomState(42)
+
+
+ def im2mat(I):
+ """Converts and image to matrix (one pixel per line)"""
+ return I.reshape((I.shape[0] * I.shape[1], I.shape[2]))
+
+
+ def mat2im(X, shape):
+ """Converts back a matrix to an image"""
+ return X.reshape(shape)
+
+
+ def minmax(I):
+ return np.clip(I, 0, 1)
+
+
+
+
+
+
+
+
+Generate data
+-------------
+
+
+
+.. code-block:: python
+
+
+ # Loading images
+ I1 = ndimage.imread('../data/ocean_day.jpg').astype(np.float64) / 256
+ I2 = ndimage.imread('../data/ocean_sunset.jpg').astype(np.float64) / 256
+
+
+ X1 = im2mat(I1)
+ X2 = im2mat(I2)
+
+ # training samples
+ nb = 1000
+ idx1 = r.randint(X1.shape[0], size=(nb,))
+ idx2 = r.randint(X2.shape[0], size=(nb,))
+
+ Xs = X1[idx1, :]
+ Xt = X2[idx2, :]
+
+
+
+
+
+
+
+
+Domain adaptation for pixel distribution transfer
+-------------------------------------------------
+
+
+
+.. code-block:: python
+
+
+ # EMDTransport
+ ot_emd = ot.da.EMDTransport()
+ ot_emd.fit(Xs=Xs, Xt=Xt)
+ transp_Xs_emd = ot_emd.transform(Xs=X1)
+ Image_emd = minmax(mat2im(transp_Xs_emd, I1.shape))
+
+ # SinkhornTransport
+ ot_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)
+ ot_sinkhorn.fit(Xs=Xs, Xt=Xt)
+ transp_Xs_sinkhorn = ot_emd.transform(Xs=X1)
+ Image_sinkhorn = minmax(mat2im(transp_Xs_sinkhorn, I1.shape))
+
+ ot_mapping_linear = ot.da.MappingTransport(
+ mu=1e0, eta=1e-8, bias=True, max_iter=20, verbose=True)
+ ot_mapping_linear.fit(Xs=Xs, Xt=Xt)
+
+ X1tl = ot_mapping_linear.transform(Xs=X1)
+ Image_mapping_linear = minmax(mat2im(X1tl, I1.shape))
+
+ ot_mapping_gaussian = ot.da.MappingTransport(
+ mu=1e0, eta=1e-2, sigma=1, bias=False, max_iter=10, verbose=True)
+ ot_mapping_gaussian.fit(Xs=Xs, Xt=Xt)
+
+ X1tn = ot_mapping_gaussian.transform(Xs=X1) # use the estimated mapping
+ Image_mapping_gaussian = minmax(mat2im(X1tn, I1.shape))
+
+
+
+
+
+
+.. rst-class:: sphx-glr-script-out
+
+ Out::
+
+ It. |Loss |Delta loss
+ --------------------------------
+ 0|3.680518e+02|0.000000e+00
+ 1|3.592439e+02|-2.393116e-02
+ 2|3.590632e+02|-5.030248e-04
+ 3|3.589698e+02|-2.601358e-04
+ 4|3.589118e+02|-1.614977e-04
+ 5|3.588724e+02|-1.097608e-04
+ 6|3.588436e+02|-8.035205e-05
+ 7|3.588215e+02|-6.141923e-05
+ 8|3.588042e+02|-4.832627e-05
+ 9|3.587902e+02|-3.909574e-05
+ 10|3.587786e+02|-3.225418e-05
+ 11|3.587688e+02|-2.712592e-05
+ 12|3.587605e+02|-2.314041e-05
+ 13|3.587534e+02|-1.991287e-05
+ 14|3.587471e+02|-1.744348e-05
+ 15|3.587416e+02|-1.544523e-05
+ 16|3.587367e+02|-1.364654e-05
+ 17|3.587323e+02|-1.230435e-05
+ 18|3.587284e+02|-1.093370e-05
+ 19|3.587276e+02|-2.052728e-06
+ It. |Loss |Delta loss
+ --------------------------------
+ 0|3.784758e+02|0.000000e+00
+ 1|3.646352e+02|-3.656911e-02
+ 2|3.642861e+02|-9.574714e-04
+ 3|3.641523e+02|-3.672061e-04
+ 4|3.640788e+02|-2.020990e-04
+ 5|3.640321e+02|-1.282701e-04
+ 6|3.640002e+02|-8.751240e-05
+ 7|3.639765e+02|-6.521203e-05
+ 8|3.639582e+02|-5.007767e-05
+ 9|3.639439e+02|-3.938917e-05
+ 10|3.639323e+02|-3.187865e-05
+
+
+Plot original images
+--------------------
+
+
+
+.. code-block:: python
+
+
+ pl.figure(1, figsize=(6.4, 3))
+ pl.subplot(1, 2, 1)
+ pl.imshow(I1)
+ pl.axis('off')
+ pl.title('Image 1')
+
+ pl.subplot(1, 2, 2)
+ pl.imshow(I2)
+ pl.axis('off')
+ pl.title('Image 2')
+ pl.tight_layout()
+
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_otda_mapping_colors_images_001.png
+ :align: center
+
+
+
+
+Plot pixel values distribution
+------------------------------
+
+
+
+.. code-block:: python
+
+
+ pl.figure(2, figsize=(6.4, 5))
+
+ pl.subplot(1, 2, 1)
+ pl.scatter(Xs[:, 0], Xs[:, 2], c=Xs)
+ pl.axis([0, 1, 0, 1])
+ pl.xlabel('Red')
+ pl.ylabel('Blue')
+ pl.title('Image 1')
+
+ pl.subplot(1, 2, 2)
+ pl.scatter(Xt[:, 0], Xt[:, 2], c=Xt)
+ pl.axis([0, 1, 0, 1])
+ pl.xlabel('Red')
+ pl.ylabel('Blue')
+ pl.title('Image 2')
+ pl.tight_layout()
+
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_otda_mapping_colors_images_003.png
+ :align: center
+
+
+
+
+Plot transformed images
+-----------------------
+
+
+
+.. code-block:: python
+
+
+ pl.figure(2, figsize=(10, 5))
+
+ pl.subplot(2, 3, 1)
+ pl.imshow(I1)
+ pl.axis('off')
+ pl.title('Im. 1')
+
+ pl.subplot(2, 3, 4)
+ pl.imshow(I2)
+ pl.axis('off')
+ pl.title('Im. 2')
+
+ pl.subplot(2, 3, 2)
+ pl.imshow(Image_emd)
+ pl.axis('off')
+ pl.title('EmdTransport')
+
+ pl.subplot(2, 3, 5)
+ pl.imshow(Image_sinkhorn)
+ pl.axis('off')
+ pl.title('SinkhornTransport')
+
+ pl.subplot(2, 3, 3)
+ pl.imshow(Image_mapping_linear)
+ pl.axis('off')
+ pl.title('MappingTransport (linear)')
+
+ pl.subplot(2, 3, 6)
+ pl.imshow(Image_mapping_gaussian)
+ pl.axis('off')
+ pl.title('MappingTransport (gaussian)')
+ pl.tight_layout()
+
+ pl.show()
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_otda_mapping_colors_images_004.png
+ :align: center
+
+
+
+
+**Total running time of the script:** ( 2 minutes 52.212 seconds)
+
+
+
+.. container:: sphx-glr-footer
+
+
+ .. container:: sphx-glr-download
+
+ :download:`Download Python source code: plot_otda_mapping_colors_images.py <plot_otda_mapping_colors_images.py>`
+
+
+
+ .. container:: sphx-glr-download
+
+ :download:`Download Jupyter notebook: plot_otda_mapping_colors_images.ipynb <plot_otda_mapping_colors_images.ipynb>`
+
+.. rst-class:: sphx-glr-signature
+
+ `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
diff --git a/docs/source/auto_examples/plot_otda_semi_supervised.ipynb b/docs/source/auto_examples/plot_otda_semi_supervised.ipynb
new file mode 100644
index 0000000..783bf84
--- /dev/null
+++ b/docs/source/auto_examples/plot_otda_semi_supervised.ipynb
@@ -0,0 +1,144 @@
+{
+ "nbformat_minor": 0,
+ "nbformat": 4,
+ "cells": [
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "%matplotlib inline"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "\n# OTDA unsupervised vs semi-supervised setting\n\n\nThis example introduces a semi supervised domain adaptation in a 2D setting.\nIt explicits the problem of semi supervised domain adaptation and introduces\nsome optimal transport approaches to solve it.\n\nQuantities such as optimal couplings, greater coupling coefficients and\ntransported samples are represented in order to give a visual understanding\nof what the transport methods are doing.\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# Authors: Remi Flamary <remi.flamary@unice.fr>\n# Stanislas Chambon <stan.chambon@gmail.com>\n#\n# License: MIT License\n\nimport matplotlib.pylab as pl\nimport ot"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Generate data\n-------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "n_samples_source = 150\nn_samples_target = 150\n\nXs, ys = ot.datasets.get_data_classif('3gauss', n_samples_source)\nXt, yt = ot.datasets.get_data_classif('3gauss2', n_samples_target)"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Transport source samples onto target samples\n--------------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# unsupervised domain adaptation\not_sinkhorn_un = ot.da.SinkhornTransport(reg_e=1e-1)\not_sinkhorn_un.fit(Xs=Xs, Xt=Xt)\ntransp_Xs_sinkhorn_un = ot_sinkhorn_un.transform(Xs=Xs)\n\n# semi-supervised domain adaptation\not_sinkhorn_semi = ot.da.SinkhornTransport(reg_e=1e-1)\not_sinkhorn_semi.fit(Xs=Xs, Xt=Xt, ys=ys, yt=yt)\ntransp_Xs_sinkhorn_semi = ot_sinkhorn_semi.transform(Xs=Xs)\n\n# semi supervised DA uses available labaled target samples to modify the cost\n# matrix involved in the OT problem. The cost of transporting a source sample\n# of class A onto a target sample of class B != A is set to infinite, or a\n# very large value\n\n# note that in the present case we consider that all the target samples are\n# labeled. For daily applications, some target sample might not have labels,\n# in this case the element of yt corresponding to these samples should be\n# filled with -1.\n\n# Warning: we recall that -1 cannot be used as a class label"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Fig 1 : plots source and target samples + matrix of pairwise distance\n---------------------------------------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "pl.figure(1, figsize=(10, 10))\npl.subplot(2, 2, 1)\npl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')\npl.xticks([])\npl.yticks([])\npl.legend(loc=0)\npl.title('Source samples')\n\npl.subplot(2, 2, 2)\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')\npl.xticks([])\npl.yticks([])\npl.legend(loc=0)\npl.title('Target samples')\n\npl.subplot(2, 2, 3)\npl.imshow(ot_sinkhorn_un.cost_, interpolation='nearest')\npl.xticks([])\npl.yticks([])\npl.title('Cost matrix - unsupervised DA')\n\npl.subplot(2, 2, 4)\npl.imshow(ot_sinkhorn_semi.cost_, interpolation='nearest')\npl.xticks([])\npl.yticks([])\npl.title('Cost matrix - semisupervised DA')\n\npl.tight_layout()\n\n# the optimal coupling in the semi-supervised DA case will exhibit \" shape\n# similar\" to the cost matrix, (block diagonal matrix)"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Fig 2 : plots optimal couplings for the different methods\n---------------------------------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "pl.figure(2, figsize=(8, 4))\n\npl.subplot(1, 2, 1)\npl.imshow(ot_sinkhorn_un.coupling_, interpolation='nearest')\npl.xticks([])\npl.yticks([])\npl.title('Optimal coupling\\nUnsupervised DA')\n\npl.subplot(1, 2, 2)\npl.imshow(ot_sinkhorn_semi.coupling_, interpolation='nearest')\npl.xticks([])\npl.yticks([])\npl.title('Optimal coupling\\nSemi-supervised DA')\n\npl.tight_layout()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "source": [
+ "Fig 3 : plot transported samples\n--------------------------------\n\n"
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "execution_count": null,
+ "cell_type": "code",
+ "source": [
+ "# display transported samples\npl.figure(4, figsize=(8, 4))\npl.subplot(1, 2, 1)\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n label='Target samples', alpha=0.5)\npl.scatter(transp_Xs_sinkhorn_un[:, 0], transp_Xs_sinkhorn_un[:, 1], c=ys,\n marker='+', label='Transp samples', s=30)\npl.title('Transported samples\\nEmdTransport')\npl.legend(loc=0)\npl.xticks([])\npl.yticks([])\n\npl.subplot(1, 2, 2)\npl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n label='Target samples', alpha=0.5)\npl.scatter(transp_Xs_sinkhorn_semi[:, 0], transp_Xs_sinkhorn_semi[:, 1], c=ys,\n marker='+', label='Transp samples', s=30)\npl.title('Transported samples\\nSinkhornTransport')\npl.xticks([])\npl.yticks([])\n\npl.tight_layout()\npl.show()"
+ ],
+ "outputs": [],
+ "metadata": {
+ "collapsed": false
+ }
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "name": "python2",
+ "language": "python"
+ },
+ "language_info": {
+ "mimetype": "text/x-python",
+ "nbconvert_exporter": "python",
+ "name": "python",
+ "file_extension": ".py",
+ "version": "2.7.12",
+ "pygments_lexer": "ipython2",
+ "codemirror_mode": {
+ "version": 2,
+ "name": "ipython"
+ }
+ }
+ }
+} \ No newline at end of file
diff --git a/examples/da/plot_otda_semi_supervised.py b/docs/source/auto_examples/plot_otda_semi_supervised.py
index 8095c4d..7963aef 100644
--- a/examples/da/plot_otda_semi_supervised.py
+++ b/docs/source/auto_examples/plot_otda_semi_supervised.py
@@ -23,8 +23,8 @@ import ot
##############################################################################
-# generate data
-##############################################################################
+# Generate data
+# -------------
n_samples_source = 150
n_samples_target = 150
@@ -35,7 +35,8 @@ Xt, yt = ot.datasets.get_data_classif('3gauss2', n_samples_target)
##############################################################################
# Transport source samples onto target samples
-##############################################################################
+# --------------------------------------------
+
# unsupervised domain adaptation
ot_sinkhorn_un = ot.da.SinkhornTransport(reg_e=1e-1)
@@ -62,7 +63,7 @@ transp_Xs_sinkhorn_semi = ot_sinkhorn_semi.transform(Xs=Xs)
##############################################################################
# Fig 1 : plots source and target samples + matrix of pairwise distance
-##############################################################################
+# ---------------------------------------------------------------------
pl.figure(1, figsize=(10, 10))
pl.subplot(2, 2, 1)
@@ -99,7 +100,7 @@ pl.tight_layout()
##############################################################################
# Fig 2 : plots optimal couplings for the different methods
-##############################################################################
+# ---------------------------------------------------------
pl.figure(2, figsize=(8, 4))
@@ -120,7 +121,7 @@ pl.tight_layout()
##############################################################################
# Fig 3 : plot transported samples
-##############################################################################
+# --------------------------------
# display transported samples
pl.figure(4, figsize=(8, 4))
diff --git a/docs/source/auto_examples/plot_otda_semi_supervised.rst b/docs/source/auto_examples/plot_otda_semi_supervised.rst
new file mode 100644
index 0000000..dc05ed0
--- /dev/null
+++ b/docs/source/auto_examples/plot_otda_semi_supervised.rst
@@ -0,0 +1,240 @@
+
+
+.. _sphx_glr_auto_examples_plot_otda_semi_supervised.py:
+
+
+============================================
+OTDA unsupervised vs semi-supervised setting
+============================================
+
+This example introduces a semi supervised domain adaptation in a 2D setting.
+It explicits the problem of semi supervised domain adaptation and introduces
+some optimal transport approaches to solve it.
+
+Quantities such as optimal couplings, greater coupling coefficients and
+transported samples are represented in order to give a visual understanding
+of what the transport methods are doing.
+
+
+
+.. code-block:: python
+
+
+ # Authors: Remi Flamary <remi.flamary@unice.fr>
+ # Stanislas Chambon <stan.chambon@gmail.com>
+ #
+ # License: MIT License
+
+ import matplotlib.pylab as pl
+ import ot
+
+
+
+
+
+
+
+
+Generate data
+-------------
+
+
+
+.. code-block:: python
+
+
+ n_samples_source = 150
+ n_samples_target = 150
+
+ Xs, ys = ot.datasets.get_data_classif('3gauss', n_samples_source)
+ Xt, yt = ot.datasets.get_data_classif('3gauss2', n_samples_target)
+
+
+
+
+
+
+
+
+Transport source samples onto target samples
+--------------------------------------------
+
+
+
+.. code-block:: python
+
+
+
+ # unsupervised domain adaptation
+ ot_sinkhorn_un = ot.da.SinkhornTransport(reg_e=1e-1)
+ ot_sinkhorn_un.fit(Xs=Xs, Xt=Xt)
+ transp_Xs_sinkhorn_un = ot_sinkhorn_un.transform(Xs=Xs)
+
+ # semi-supervised domain adaptation
+ ot_sinkhorn_semi = ot.da.SinkhornTransport(reg_e=1e-1)
+ ot_sinkhorn_semi.fit(Xs=Xs, Xt=Xt, ys=ys, yt=yt)
+ transp_Xs_sinkhorn_semi = ot_sinkhorn_semi.transform(Xs=Xs)
+
+ # semi supervised DA uses available labaled target samples to modify the cost
+ # matrix involved in the OT problem. The cost of transporting a source sample
+ # of class A onto a target sample of class B != A is set to infinite, or a
+ # very large value
+
+ # note that in the present case we consider that all the target samples are
+ # labeled. For daily applications, some target sample might not have labels,
+ # in this case the element of yt corresponding to these samples should be
+ # filled with -1.
+
+ # Warning: we recall that -1 cannot be used as a class label
+
+
+
+
+
+
+
+
+Fig 1 : plots source and target samples + matrix of pairwise distance
+---------------------------------------------------------------------
+
+
+
+.. code-block:: python
+
+
+ pl.figure(1, figsize=(10, 10))
+ pl.subplot(2, 2, 1)
+ pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')
+ pl.xticks([])
+ pl.yticks([])
+ pl.legend(loc=0)
+ pl.title('Source samples')
+
+ pl.subplot(2, 2, 2)
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')
+ pl.xticks([])
+ pl.yticks([])
+ pl.legend(loc=0)
+ pl.title('Target samples')
+
+ pl.subplot(2, 2, 3)
+ pl.imshow(ot_sinkhorn_un.cost_, interpolation='nearest')
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Cost matrix - unsupervised DA')
+
+ pl.subplot(2, 2, 4)
+ pl.imshow(ot_sinkhorn_semi.cost_, interpolation='nearest')
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Cost matrix - semisupervised DA')
+
+ pl.tight_layout()
+
+ # the optimal coupling in the semi-supervised DA case will exhibit " shape
+ # similar" to the cost matrix, (block diagonal matrix)
+
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_otda_semi_supervised_001.png
+ :align: center
+
+
+
+
+Fig 2 : plots optimal couplings for the different methods
+---------------------------------------------------------
+
+
+
+.. code-block:: python
+
+
+ pl.figure(2, figsize=(8, 4))
+
+ pl.subplot(1, 2, 1)
+ pl.imshow(ot_sinkhorn_un.coupling_, interpolation='nearest')
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Optimal coupling\nUnsupervised DA')
+
+ pl.subplot(1, 2, 2)
+ pl.imshow(ot_sinkhorn_semi.coupling_, interpolation='nearest')
+ pl.xticks([])
+ pl.yticks([])
+ pl.title('Optimal coupling\nSemi-supervised DA')
+
+ pl.tight_layout()
+
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_otda_semi_supervised_003.png
+ :align: center
+
+
+
+
+Fig 3 : plot transported samples
+--------------------------------
+
+
+
+.. code-block:: python
+
+
+ # display transported samples
+ pl.figure(4, figsize=(8, 4))
+ pl.subplot(1, 2, 1)
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.5)
+ pl.scatter(transp_Xs_sinkhorn_un[:, 0], transp_Xs_sinkhorn_un[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+ pl.title('Transported samples\nEmdTransport')
+ pl.legend(loc=0)
+ pl.xticks([])
+ pl.yticks([])
+
+ pl.subplot(1, 2, 2)
+ pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.5)
+ pl.scatter(transp_Xs_sinkhorn_semi[:, 0], transp_Xs_sinkhorn_semi[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+ pl.title('Transported samples\nSinkhornTransport')
+ pl.xticks([])
+ pl.yticks([])
+
+ pl.tight_layout()
+ pl.show()
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_otda_semi_supervised_006.png
+ :align: center
+
+
+
+
+**Total running time of the script:** ( 0 minutes 0.714 seconds)
+
+
+
+.. container:: sphx-glr-footer
+
+
+ .. container:: sphx-glr-download
+
+ :download:`Download Python source code: plot_otda_semi_supervised.py <plot_otda_semi_supervised.py>`
+
+
+
+ .. container:: sphx-glr-download
+
+ :download:`Download Jupyter notebook: plot_otda_semi_supervised.ipynb <plot_otda_semi_supervised.ipynb>`
+
+.. rst-class:: sphx-glr-signature
+
+ `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
diff --git a/docs/source/auto_examples/searchindex b/docs/source/auto_examples/searchindex
new file mode 100644
index 0000000..2cad500
--- /dev/null
+++ b/docs/source/auto_examples/searchindex
Binary files differ
diff --git a/docs/source/conf.py b/docs/source/conf.py
index ff08899..4105d87 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -50,7 +50,7 @@ sys.path.insert(0, os.path.abspath("../.."))
#needs_sphinx = '1.0'
# Add any Sphinx extension module names here, as strings. They can be
-# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
+# extensions coming with Sphinx (named #'sphinx.ext.*') or your custom
# ones.
extensions = [
'sphinx.ext.autodoc',
@@ -62,7 +62,7 @@ extensions = [
'sphinx.ext.ifconfig',
'sphinx.ext.viewcode',
'sphinx.ext.napoleon',
-# 'sphinx_gallery.gen_gallery',
+ #'sphinx_gallery.gen_gallery',
]
# Add any paths that contain templates here, relative to this directory.
@@ -261,7 +261,7 @@ latex_elements = {
# author, documentclass [howto, manual, or own class]).
latex_documents = [
(master_doc, 'POT.tex', u'POT Python Optimal Transport library',
- u'RĂ©mi Flamary, Nicolas Courty', 'manual'),
+ author, 'manual'),
]
# The name of an image file (relative to this directory) to place at the top of
@@ -305,7 +305,7 @@ man_pages = [
# dir menu entry, description, category)
texinfo_documents = [
(master_doc, 'POT', u'POT Python Optimal Transport library Documentation',
- author, 'POT', 'One line description of project.',
+ author, 'POT', 'Python Optimal Transport librar.',
'Miscellaneous'),
]
@@ -326,9 +326,9 @@ texinfo_documents = [
intersphinx_mapping = {'https://docs.python.org/': None}
sphinx_gallery_conf = {
- 'examples_dirs': '../../examples',
+ 'examples_dirs': ['../../examples','../../examples/da'],
'gallery_dirs': 'auto_examples',
- 'mod_example_dir': '../modules/generated/',
+ 'backreferences_dir': '../modules/generated/',
'reference_url': {
'numpy': 'http://docs.scipy.org/doc/numpy-1.9.1',
'scipy': 'http://docs.scipy.org/doc/scipy-0.17.0/reference'}
diff --git a/docs/source/examples.rst b/docs/source/examples.rst
deleted file mode 100644
index f209543..0000000
--- a/docs/source/examples.rst
+++ /dev/null
@@ -1,39 +0,0 @@
-
-
-Examples
-============
-
-1D Optimal transport
----------------------
-
-.. literalinclude:: ../../examples/demo_OT_1D.py
-
-2D Optimal transport on empirical distributions
------------------------------------------------
-
-.. literalinclude:: ../../examples/demo_OT_2D_samples.py
-
-1D Wasserstein barycenter
--------------------------
-
-.. literalinclude:: ../../examples/demo_barycenter_1D.py
-
-OT with user provided regularization
-------------------------------------
-
-.. literalinclude:: ../../examples/demo_optim_OTreg.py
-
-Domain adaptation with optimal transport
-----------------------------------------
-
-.. literalinclude:: ../../examples/demo_OTDA_classes.py
-
-Color transfer in images
-------------------------
-
-.. literalinclude:: ../../examples/demo_OTDA_color_images.py
-
-OT mapping estimation for domain adaptation
--------------------------------------------
-
-.. literalinclude:: ../../examples/demo_OTDA_mapping.py
diff --git a/docs/source/readme.rst b/docs/source/readme.rst
index c1e0017..065093e 100644
--- a/docs/source/readme.rst
+++ b/docs/source/readme.rst
@@ -21,6 +21,7 @@ It provides the following solvers:
- Joint OT matrix and mapping estimation [8].
- Wasserstein Discriminant Analysis [11] (requires autograd +
pymanopt).
+- Gromov-Wasserstein distances and barycenters [12]
Some demonstrations (both in Python and Jupyter Notebook format) are
available in the examples folder.
@@ -150,27 +151,27 @@ Here is a list of the Python notebooks available
want a quick look:
- `1D optimal
- transport <https://github.com/rflamary/POT/blob/master/notebooks/Demo_1D_OT.ipynb>`__
+ transport <https://github.com/rflamary/POT/blob/master/notebooks/plot_OT_1D.ipynb>`__
- `OT Ground
- Loss <https://github.com/rflamary/POT/blob/master/notebooks/Demo_Ground_Loss.ipynb>`__
+ Loss <https://github.com/rflamary/POT/blob/master/notebooks/plot_OT_L1_vs_L2.ipynb>`__
- `Multiple EMD
- computation <https://github.com/rflamary/POT/blob/master/notebooks/Demo_Compute_EMD.ipynb>`__
+ computation <https://github.com/rflamary/POT/blob/master/notebooks/plot_compute_emd.ipynb>`__
- `2D optimal transport on empirical
- distributions <https://github.com/rflamary/POT/blob/master/notebooks/Demo_2D_OT_samples.ipynb>`__
+ distributions <https://github.com/rflamary/POT/blob/master/notebooks/plot_OT_2D_samples.ipynb>`__
- `1D Wasserstein
- barycenter <https://github.com/rflamary/POT/blob/master/notebooks/Demo_1D_barycenter.ipynb>`__
+ barycenter <https://github.com/rflamary/POT/blob/master/notebooks/plot_barycenter_1D.ipynb>`__
- `OT with user provided
- regularization <https://github.com/rflamary/POT/blob/master/notebooks/Demo_Optim_OTreg.ipynb>`__
+ regularization <https://github.com/rflamary/POT/blob/master/notebooks/plot_optim_OTreg.ipynb>`__
- `Domain adaptation with optimal
- transport <https://github.com/rflamary/POT/blob/master/notebooks/Demo_2D_OT_DomainAdaptation.ipynb>`__
+ transport <https://github.com/rflamary/POT/blob/master/notebooks/plot_otda_d2.ipynb>`__
- `Color transfer in
- images <https://github.com/rflamary/POT/blob/master/notebooks/Demo_Image_ColorAdaptation.ipynb>`__
+ images <https://github.com/rflamary/POT/blob/master/notebooks/plot_otda_color_images.ipynb>`__
- `OT mapping estimation for domain
- adaptation <https://github.com/rflamary/POT/blob/master/notebooks/Demo_2D_OTmapping_DomainAdaptation.ipynb>`__
+ adaptation <https://github.com/rflamary/POT/blob/master/notebooks/plot_otda_mapping.ipynb>`__
- `OT mapping estimation for color transfer in
- images <https://github.com/rflamary/POT/blob/master/notebooks/Demo_Image_ColorAdaptation_mapping.ipynb>`__
+ images <https://github.com/rflamary/POT/blob/master/notebooks/plot_otda_mapping_colors_images.ipynb>`__
- `Wasserstein Discriminant
- Analysis <https://github.com/rflamary/POT/blob/master/notebooks/Demo_Wasserstein_Discriminant_Analysis.ipynb>`__
+ Analysis <https://github.com/rflamary/POT/blob/master/notebooks/plot_WDA.ipynb>`__
You can also see the notebooks with `Jupyter
nbviewer <https://nbviewer.jupyter.org/github/rflamary/POT/tree/master/notebooks/>`__.
@@ -187,6 +188,10 @@ The contributors to this library are:
- `Michael Perrot <http://perso.univ-st-etienne.fr/pem82055/>`__
(Mapping estimation)
- `LĂ©o Gautheron <https://github.com/aje>`__ (GPU implementation)
+- `Nathalie
+ Gayraud <https://www.linkedin.com/in/nathalie-t-h-gayraud/?ppe=1>`__
+- `Stanislas Chambon <https://slasnista.github.io/>`__
+- `Antoine Rolet <https://arolet.github.io/>`__
This toolbox benefit a lot from open source research and we would like
to thank the following persons for providing some code (in various
@@ -196,7 +201,6 @@ languages):
in Matlab)
- `Nicolas Bonneel <http://liris.cnrs.fr/~nbonneel/>`__ ( C++ code for
EMD)
-- `Antoine Rolet <https://arolet.github.io/>`__ ( Mex file for EMD )
- `Marco Cuturi <http://marcocuturi.net/>`__ (Sinkhorn Knopp in
Matlab/Cuda)
@@ -277,6 +281,11 @@ arXiv:1607.05816.
Analysis <https://arxiv.org/pdf/1608.08063.pdf>`__. arXiv preprint
arXiv:1608.08063.
+[12] Gabriel Peyré, Marco Cuturi, and Justin Solomon,
+`Gromov-Wasserstein averaging of kernel and distance
+matrices <http://proceedings.mlr.press/v48/peyre16.html>`__
+International Conference on Machine Learning (ICML). 2016.
+
.. |PyPI version| image:: https://badge.fury.io/py/POT.svg
:target: https://badge.fury.io/py/POT
.. |Build Status| image:: https://travis-ci.org/rflamary/POT.svg?branch=master
diff --git a/examples/README.txt b/examples/README.txt
index f8643b8..b08d3f1 100644
--- a/examples/README.txt
+++ b/examples/README.txt
@@ -1,2 +1,4 @@
POT Examples
============
+
+This is a gallery of all the POT example files.
diff --git a/examples/plot_OT_1D.py b/examples/plot_OT_1D.py
index 0f3a26a..719058f 100644
--- a/examples/plot_OT_1D.py
+++ b/examples/plot_OT_1D.py
@@ -4,6 +4,9 @@
1D optimal transport
====================
+This example illustrates the computation of EMD and Sinkhorn transport plans
+and their visualization.
+
"""
# Author: Remi Flamary <remi.flamary@unice.fr>
@@ -15,6 +18,11 @@ import matplotlib.pylab as pl
import ot
from ot.datasets import get_1D_gauss as gauss
+##############################################################################
+# Generate data
+# -------------
+
+
#%% parameters
n = 100 # nb bins
@@ -30,6 +38,11 @@ b = gauss(n, m=60, s=10)
M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)))
M /= M.max()
+
+##############################################################################
+# Plot distributions and loss matrix
+# ----------------------------------
+
#%% plot the distributions
pl.figure(1, figsize=(6.4, 3))
@@ -42,6 +55,11 @@ pl.legend()
pl.figure(2, figsize=(5, 5))
ot.plot.plot1D_mat(a, b, M, 'Cost matrix M')
+##############################################################################
+# Solve EMD
+# ---------
+
+
#%% EMD
G0 = ot.emd(a, b, M)
@@ -49,6 +67,11 @@ G0 = ot.emd(a, b, M)
pl.figure(3, figsize=(5, 5))
ot.plot.plot1D_mat(a, b, G0, 'OT matrix G0')
+##############################################################################
+# Solve Sinkhorn
+# --------------
+
+
#%% Sinkhorn
lambd = 1e-3
diff --git a/examples/plot_OT_2D_samples.py b/examples/plot_OT_2D_samples.py
index 023e645..9818ec5 100644
--- a/examples/plot_OT_2D_samples.py
+++ b/examples/plot_OT_2D_samples.py
@@ -4,6 +4,9 @@
2D Optimal transport between empirical distributions
====================================================
+Illustration of 2D optimal transport between discributions that are weighted
+sum of diracs. The OT matrix is plotted with the samples.
+
"""
# Author: Remi Flamary <remi.flamary@unice.fr>
@@ -14,6 +17,10 @@ import numpy as np
import matplotlib.pylab as pl
import ot
+##############################################################################
+# Generate data
+# -------------
+
#%% parameters and data generation
n = 50 # nb samples
@@ -33,6 +40,10 @@ a, b = np.ones((n,)) / n, np.ones((n,)) / n # uniform distribution on samples
M = ot.dist(xs, xt)
M /= M.max()
+##############################################################################
+# Plot data
+# ---------
+
#%% plot samples
pl.figure(1)
@@ -45,6 +56,9 @@ pl.figure(2)
pl.imshow(M, interpolation='nearest')
pl.title('Cost matrix M')
+##############################################################################
+# Compute EMD
+# -----------
#%% EMD
@@ -62,10 +76,14 @@ pl.legend(loc=0)
pl.title('OT matrix with samples')
+##############################################################################
+# Compute Sinkhorn
+# ----------------
+
#%% sinkhorn
# reg term
-lambd = 5e-4
+lambd = 1e-3
Gs = ot.sinkhorn(a, b, M, lambd)
diff --git a/examples/plot_OT_L1_vs_L2.py b/examples/plot_OT_L1_vs_L2.py
index dfc9462..090e809 100644
--- a/examples/plot_OT_L1_vs_L2.py
+++ b/examples/plot_OT_L1_vs_L2.py
@@ -4,6 +4,8 @@
2D Optimal transport for different metrics
==========================================
+2D OT on empirical distributio with different gound metric.
+
Stole the figure idea from Fig. 1 and 2 in
https://arxiv.org/pdf/1706.07650.pdf
@@ -18,98 +20,188 @@ import numpy as np
import matplotlib.pylab as pl
import ot
-#%% parameters and data generation
-
-for data in range(2):
-
- if data:
- n = 20 # nb samples
- xs = np.zeros((n, 2))
- xs[:, 0] = np.arange(n) + 1
- xs[:, 1] = (np.arange(n) + 1) * -0.001 # to make it strictly convex...
-
- xt = np.zeros((n, 2))
- xt[:, 1] = np.arange(n) + 1
- else:
-
- n = 50 # nb samples
- xtot = np.zeros((n + 1, 2))
- xtot[:, 0] = np.cos(
- (np.arange(n + 1) + 1.0) * 0.9 / (n + 2) * 2 * np.pi)
- xtot[:, 1] = np.sin(
- (np.arange(n + 1) + 1.0) * 0.9 / (n + 2) * 2 * np.pi)
-
- xs = xtot[:n, :]
- xt = xtot[1:, :]
-
- a, b = ot.unif(n), ot.unif(n) # uniform distribution on samples
-
- # loss matrix
- M1 = ot.dist(xs, xt, metric='euclidean')
- M1 /= M1.max()
-
- # loss matrix
- M2 = ot.dist(xs, xt, metric='sqeuclidean')
- M2 /= M2.max()
-
- # loss matrix
- Mp = np.sqrt(ot.dist(xs, xt, metric='euclidean'))
- Mp /= Mp.max()
-
- #%% plot samples
-
- pl.figure(1 + 3 * data, figsize=(7, 3))
- pl.clf()
- pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
- pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
- pl.axis('equal')
- pl.title('Source and traget distributions')
-
- pl.figure(2 + 3 * data, figsize=(7, 3))
-
- pl.subplot(1, 3, 1)
- pl.imshow(M1, interpolation='nearest')
- pl.title('Euclidean cost')
-
- pl.subplot(1, 3, 2)
- pl.imshow(M2, interpolation='nearest')
- pl.title('Squared Euclidean cost')
-
- pl.subplot(1, 3, 3)
- pl.imshow(Mp, interpolation='nearest')
- pl.title('Sqrt Euclidean cost')
- pl.tight_layout()
-
- #%% EMD
- G1 = ot.emd(a, b, M1)
- G2 = ot.emd(a, b, M2)
- Gp = ot.emd(a, b, Mp)
-
- pl.figure(3 + 3 * data, figsize=(7, 3))
-
- pl.subplot(1, 3, 1)
- ot.plot.plot2D_samples_mat(xs, xt, G1, c=[.5, .5, 1])
- pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
- pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
- pl.axis('equal')
- # pl.legend(loc=0)
- pl.title('OT Euclidean')
-
- pl.subplot(1, 3, 2)
- ot.plot.plot2D_samples_mat(xs, xt, G2, c=[.5, .5, 1])
- pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
- pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
- pl.axis('equal')
- # pl.legend(loc=0)
- pl.title('OT squared Euclidean')
-
- pl.subplot(1, 3, 3)
- ot.plot.plot2D_samples_mat(xs, xt, Gp, c=[.5, .5, 1])
- pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
- pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
- pl.axis('equal')
- # pl.legend(loc=0)
- pl.title('OT sqrt Euclidean')
- pl.tight_layout()
+##############################################################################
+# Dataset 1 : uniform sampling
+# ----------------------------
+
+n = 20 # nb samples
+xs = np.zeros((n, 2))
+xs[:, 0] = np.arange(n) + 1
+xs[:, 1] = (np.arange(n) + 1) * -0.001 # to make it strictly convex...
+
+xt = np.zeros((n, 2))
+xt[:, 1] = np.arange(n) + 1
+
+a, b = ot.unif(n), ot.unif(n) # uniform distribution on samples
+
+# loss matrix
+M1 = ot.dist(xs, xt, metric='euclidean')
+M1 /= M1.max()
+
+# loss matrix
+M2 = ot.dist(xs, xt, metric='sqeuclidean')
+M2 /= M2.max()
+
+# loss matrix
+Mp = np.sqrt(ot.dist(xs, xt, metric='euclidean'))
+Mp /= Mp.max()
+
+# Data
+pl.figure(1, figsize=(7, 3))
+pl.clf()
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+pl.axis('equal')
+pl.title('Source and traget distributions')
+
+
+# Cost matrices
+pl.figure(2, figsize=(7, 3))
+
+pl.subplot(1, 3, 1)
+pl.imshow(M1, interpolation='nearest')
+pl.title('Euclidean cost')
+
+pl.subplot(1, 3, 2)
+pl.imshow(M2, interpolation='nearest')
+pl.title('Squared Euclidean cost')
+
+pl.subplot(1, 3, 3)
+pl.imshow(Mp, interpolation='nearest')
+pl.title('Sqrt Euclidean cost')
+pl.tight_layout()
+
+##############################################################################
+# Dataset 1 : Plot OT Matrices
+# ----------------------------
+
+
+#%% EMD
+G1 = ot.emd(a, b, M1)
+G2 = ot.emd(a, b, M2)
+Gp = ot.emd(a, b, Mp)
+
+# OT matrices
+pl.figure(3, figsize=(7, 3))
+
+pl.subplot(1, 3, 1)
+ot.plot.plot2D_samples_mat(xs, xt, G1, c=[.5, .5, 1])
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+pl.axis('equal')
+# pl.legend(loc=0)
+pl.title('OT Euclidean')
+
+pl.subplot(1, 3, 2)
+ot.plot.plot2D_samples_mat(xs, xt, G2, c=[.5, .5, 1])
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+pl.axis('equal')
+# pl.legend(loc=0)
+pl.title('OT squared Euclidean')
+
+pl.subplot(1, 3, 3)
+ot.plot.plot2D_samples_mat(xs, xt, Gp, c=[.5, .5, 1])
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+pl.axis('equal')
+# pl.legend(loc=0)
+pl.title('OT sqrt Euclidean')
+pl.tight_layout()
+
+pl.show()
+
+
+##############################################################################
+# Dataset 2 : Partial circle
+# --------------------------
+
+n = 50 # nb samples
+xtot = np.zeros((n + 1, 2))
+xtot[:, 0] = np.cos(
+ (np.arange(n + 1) + 1.0) * 0.9 / (n + 2) * 2 * np.pi)
+xtot[:, 1] = np.sin(
+ (np.arange(n + 1) + 1.0) * 0.9 / (n + 2) * 2 * np.pi)
+
+xs = xtot[:n, :]
+xt = xtot[1:, :]
+
+a, b = ot.unif(n), ot.unif(n) # uniform distribution on samples
+
+# loss matrix
+M1 = ot.dist(xs, xt, metric='euclidean')
+M1 /= M1.max()
+
+# loss matrix
+M2 = ot.dist(xs, xt, metric='sqeuclidean')
+M2 /= M2.max()
+
+# loss matrix
+Mp = np.sqrt(ot.dist(xs, xt, metric='euclidean'))
+Mp /= Mp.max()
+
+
+# Data
+pl.figure(4, figsize=(7, 3))
+pl.clf()
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+pl.axis('equal')
+pl.title('Source and traget distributions')
+
+
+# Cost matrices
+pl.figure(5, figsize=(7, 3))
+
+pl.subplot(1, 3, 1)
+pl.imshow(M1, interpolation='nearest')
+pl.title('Euclidean cost')
+
+pl.subplot(1, 3, 2)
+pl.imshow(M2, interpolation='nearest')
+pl.title('Squared Euclidean cost')
+
+pl.subplot(1, 3, 3)
+pl.imshow(Mp, interpolation='nearest')
+pl.title('Sqrt Euclidean cost')
+pl.tight_layout()
+
+##############################################################################
+# Dataset 2 : Plot OT Matrices
+# -----------------------------
+
+
+#%% EMD
+G1 = ot.emd(a, b, M1)
+G2 = ot.emd(a, b, M2)
+Gp = ot.emd(a, b, Mp)
+
+# OT matrices
+pl.figure(6, figsize=(7, 3))
+
+pl.subplot(1, 3, 1)
+ot.plot.plot2D_samples_mat(xs, xt, G1, c=[.5, .5, 1])
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+pl.axis('equal')
+# pl.legend(loc=0)
+pl.title('OT Euclidean')
+
+pl.subplot(1, 3, 2)
+ot.plot.plot2D_samples_mat(xs, xt, G2, c=[.5, .5, 1])
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+pl.axis('equal')
+# pl.legend(loc=0)
+pl.title('OT squared Euclidean')
+
+pl.subplot(1, 3, 3)
+ot.plot.plot2D_samples_mat(xs, xt, Gp, c=[.5, .5, 1])
+pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+pl.axis('equal')
+# pl.legend(loc=0)
+pl.title('OT sqrt Euclidean')
+pl.tight_layout()
pl.show()
diff --git a/examples/plot_WDA.py b/examples/plot_WDA.py
index 42789f2..93cc237 100644
--- a/examples/plot_WDA.py
+++ b/examples/plot_WDA.py
@@ -4,6 +4,12 @@
Wasserstein Discriminant Analysis
=================================
+This example illustrate the use of WDA as proposed in [11].
+
+
+[11] Flamary, R., Cuturi, M., Courty, N., & Rakotomamonjy, A. (2016).
+Wasserstein Discriminant Analysis.
+
"""
# Author: Remi Flamary <remi.flamary@unice.fr>
@@ -16,6 +22,10 @@ import matplotlib.pylab as pl
from ot.dr import wda, fda
+##############################################################################
+# Generate data
+# -------------
+
#%% parameters
n = 1000 # nb samples in source and target datasets
@@ -39,6 +49,10 @@ nbnoise = 8
xs = np.hstack((xs, np.random.randn(n, nbnoise)))
xt = np.hstack((xt, np.random.randn(n, nbnoise)))
+##############################################################################
+# Plot data
+# ---------
+
#%% plot samples
pl.figure(1, figsize=(6.4, 3.5))
@@ -53,11 +67,19 @@ pl.legend(loc=0)
pl.title('Other dimensions')
pl.tight_layout()
+##############################################################################
+# Compute Fisher Discriminant Analysis
+# ------------------------------------
+
#%% Compute FDA
p = 2
Pfda, projfda = fda(xs, ys, p)
+##############################################################################
+# Compute Wasserstein Discriminant Analysis
+# -----------------------------------------
+
#%% Compute WDA
p = 2
reg = 1e0
@@ -66,6 +88,11 @@ maxiter = 100
Pwda, projwda = wda(xs, ys, p, reg, k, maxiter=maxiter)
+
+##############################################################################
+# Plot 2D projections
+# -------------------
+
#%% plot samples
xsp = projfda(xs)
diff --git a/examples/plot_barycenter_1D.py b/examples/plot_barycenter_1D.py
index 875f44c..620936b 100644
--- a/examples/plot_barycenter_1D.py
+++ b/examples/plot_barycenter_1D.py
@@ -4,6 +4,14 @@
1D Wasserstein barycenter demo
==============================
+This example illustrates the computation of regularized Wassersyein Barycenter
+as proposed in [3].
+
+
+[3] Benamou, J. D., Carlier, G., Cuturi, M., Nenna, L., & Peyré, G. (2015).
+Iterative Bregman projections for regularized transportation problems
+SIAM Journal on Scientific Computing, 37(2), A1111-A1138.
+
"""
# Author: Remi Flamary <remi.flamary@unice.fr>
@@ -17,6 +25,9 @@ import ot
from mpl_toolkits.mplot3d import Axes3D # noqa
from matplotlib.collections import PolyCollection
+##############################################################################
+# Generate data
+# -------------
#%% parameters
@@ -37,6 +48,10 @@ n_distributions = A.shape[1]
M = ot.utils.dist0(n)
M /= M.max()
+##############################################################################
+# Plot data
+# ---------
+
#%% plot the distributions
pl.figure(1, figsize=(6.4, 3))
@@ -45,6 +60,10 @@ for i in range(n_distributions):
pl.title('Distributions')
pl.tight_layout()
+##############################################################################
+# Barycenter computation
+# ----------------------
+
#%% barycenter computation
alpha = 0.2 # 0<=alpha<=1
@@ -71,6 +90,10 @@ pl.legend()
pl.title('Barycenters')
pl.tight_layout()
+##############################################################################
+# Barycentric interpolation
+# -------------------------
+
#%% barycenter interpolation
n_alpha = 11
diff --git a/examples/plot_compute_emd.py b/examples/plot_compute_emd.py
index 893eecf..73b42c3 100644
--- a/examples/plot_compute_emd.py
+++ b/examples/plot_compute_emd.py
@@ -1,8 +1,12 @@
# -*- coding: utf-8 -*-
"""
-====================
-1D optimal transport
-====================
+=================
+Plot multiple EMD
+=================
+
+Shows how to compute multiple EMD and Sinkhorn with two differnt
+ground metrics and plot their values for diffeent distributions.
+
"""
@@ -16,6 +20,10 @@ import ot
from ot.datasets import get_1D_gauss as gauss
+##############################################################################
+# Generate data
+# -------------
+
#%% parameters
n = 100 # nb bins
@@ -40,6 +48,11 @@ M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)), 'euclidean')
M /= M.max()
M2 = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)), 'sqeuclidean')
M2 /= M2.max()
+
+##############################################################################
+# Plot data
+# ---------
+
#%% plot the distributions
pl.figure(1)
@@ -51,10 +64,15 @@ pl.plot(x, B, label='Target distributions')
pl.title('Target distributions')
pl.tight_layout()
+
+##############################################################################
+# Compute EMD for the different losses
+# ------------------------------------
+
#%% Compute and plot distributions and loss matrix
d_emd = ot.emd2(a, B, M) # direct computation of EMD
-d_emd2 = ot.emd2(a, B, M2) # direct computation of EMD with loss M3
+d_emd2 = ot.emd2(a, B, M2) # direct computation of EMD with loss M2
pl.figure(2)
@@ -63,6 +81,10 @@ pl.plot(d_emd2, label='Squared Euclidean EMD')
pl.title('EMD distances')
pl.legend()
+##############################################################################
+# Compute Sinkhorn for the different losses
+# -----------------------------------------
+
#%%
reg = 1e-2
d_sinkhorn = ot.sinkhorn2(a, B, M, reg)
diff --git a/examples/plot_gromov.py b/examples/plot_gromov.py
index dce66c4..d3f724c 100644
--- a/examples/plot_gromov.py
+++ b/examples/plot_gromov.py
@@ -3,6 +3,7 @@
==========================
Gromov-Wasserstein example
==========================
+
This example is designed to show how to use the Gromov-Wassertsein distance
computation in POT.
"""
@@ -15,17 +16,18 @@ computation in POT.
import scipy as sp
import numpy as np
import matplotlib.pylab as pl
-
+from mpl_toolkits.mplot3d import Axes3D # noqa
import ot
-"""
-Sample two Gaussian distributions (2D and 3D)
-=============================================
-The Gromov-Wasserstein distance allows to compute distances with samples that
-do not belong to the same metric space. For demonstration purpose, we sample
-two Gaussian distributions in 2- and 3-dimensional spaces.
-"""
+##############################################################################
+# Sample two Gaussian distributions (2D and 3D)
+# ---------------------------------------------
+#
+# The Gromov-Wasserstein distance allows to compute distances with samples that
+# do not belong to the same metric space. For demonstration purpose, we sample
+# two Gaussian distributions in 2- and 3-dimensional spaces.
+
n_samples = 30 # nb samples
@@ -41,10 +43,11 @@ P = sp.linalg.sqrtm(cov_t)
xt = np.random.randn(n_samples, 3).dot(P) + mu_t
-"""
-Plotting the distributions
-==========================
-"""
+##############################################################################
+# Plotting the distributions
+# --------------------------
+
+
fig = pl.figure()
ax1 = fig.add_subplot(121)
ax1.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
@@ -53,10 +56,10 @@ ax2.scatter(xt[:, 0], xt[:, 1], xt[:, 2], color='r')
pl.show()
-"""
-Compute distance kernels, normalize them and then display
-=========================================================
-"""
+##############################################################################
+# Compute distance kernels, normalize them and then display
+# ---------------------------------------------------------
+
C1 = sp.spatial.distance.cdist(xs, xs)
C2 = sp.spatial.distance.cdist(xt, xt)
@@ -71,10 +74,10 @@ pl.subplot(122)
pl.imshow(C2)
pl.show()
-"""
-Compute Gromov-Wasserstein plans and distance
-=============================================
-"""
+##############################################################################
+# Compute Gromov-Wasserstein plans and distance
+# ---------------------------------------------
+
p = ot.unif(n_samples)
q = ot.unif(n_samples)
diff --git a/examples/plot_gromov_barycenter.py b/examples/plot_gromov_barycenter.py
index 52f4966..180b0cf 100755
--- a/examples/plot_gromov_barycenter.py
+++ b/examples/plot_gromov_barycenter.py
@@ -3,6 +3,7 @@
=====================================
Gromov-Wasserstein Barycenter example
=====================================
+
This example is designed to show how to use the Gromov-Wasserstein distance
computation in POT.
"""
@@ -23,13 +24,12 @@ from sklearn.decomposition import PCA
import ot
-"""
-
-Smacof MDS
-==========
-This function allows to find an embedding of points given a dissimilarity matrix
-that will be given by the output of the algorithm
-"""
+##############################################################################
+# Smacof MDS
+# ----------
+#
+# This function allows to find an embedding of points given a dissimilarity matrix
+# that will be given by the output of the algorithm
def smacof_mds(C, dim, max_iter=3000, eps=1e-9):
@@ -78,11 +78,11 @@ def smacof_mds(C, dim, max_iter=3000, eps=1e-9):
return npos
-"""
-Data preparation
-================
-The four distributions are constructed from 4 simple images
-"""
+##############################################################################
+# Data preparation
+# ----------------
+#
+# The four distributions are constructed from 4 simple images
def im2mat(I):
@@ -110,12 +110,11 @@ for nb in range(4):
xs = np.array([np.array(xs[0]), np.array(xs[1]),
np.array(xs[2]), np.array(xs[3])])
+##############################################################################
+# Barycenter computation
+# ----------------------
+
-"""
-Barycenter computation
-======================
-The four distributions are constructed from 4 simple images
-"""
ns = [len(xs[s]) for s in range(S)]
n_samples = 30
@@ -134,35 +133,36 @@ for i in range(2):
Ct01[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[0], Cs[1]],
[ps[0], ps[1]
], p, lambdast[i], 'square_loss', 5e-4,
- max_iter=100, stopThr=1e-3)
+ max_iter=100, tol=1e-3)
Ct02 = [0 for i in range(2)]
for i in range(2):
Ct02[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[0], Cs[2]],
[ps[0], ps[2]
], p, lambdast[i], 'square_loss', 5e-4,
- max_iter=100, stopThr=1e-3)
+ max_iter=100, tol=1e-3)
Ct13 = [0 for i in range(2)]
for i in range(2):
Ct13[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[1], Cs[3]],
[ps[1], ps[3]
], p, lambdast[i], 'square_loss', 5e-4,
- max_iter=100, stopThr=1e-3)
+ max_iter=100, tol=1e-3)
Ct23 = [0 for i in range(2)]
for i in range(2):
Ct23[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[2], Cs[3]],
[ps[2], ps[3]
], p, lambdast[i], 'square_loss', 5e-4,
- max_iter=100, stopThr=1e-3)
+ max_iter=100, tol=1e-3)
-"""
-Visualization
-=============
-"""
-"""The PCA helps in getting consistency between the rotations"""
+##############################################################################
+# Visualization
+# -------------
+#
+# The PCA helps in getting consistency between the rotations
+
clf = PCA(n_components=2)
npos = [0, 0, 0, 0]
diff --git a/examples/plot_optim_OTreg.py b/examples/plot_optim_OTreg.py
index 276b250..e1a737e 100644
--- a/examples/plot_optim_OTreg.py
+++ b/examples/plot_optim_OTreg.py
@@ -4,6 +4,24 @@
Regularized OT with generic solver
==================================
+Illustrates the use of the generic solver for regularized OT with
+user-designed regularization term. It uses Conditional gradient as in [6] and
+generalized Conditional Gradient as proposed in [5][7].
+
+
+[5] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy, Optimal Transport for
+Domain Adaptation, in IEEE Transactions on Pattern Analysis and Machine
+Intelligence , vol.PP, no.99, pp.1-1.
+
+[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.
+
+
"""
@@ -12,6 +30,10 @@ import matplotlib.pylab as pl
import ot
+##############################################################################
+# Generate data
+# -------------
+
#%% parameters
n = 100 # nb bins
@@ -27,6 +49,10 @@ b = ot.datasets.get_1D_gauss(n, m=60, s=10)
M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)))
M /= M.max()
+##############################################################################
+# Solve EMD
+# ---------
+
#%% EMD
G0 = ot.emd(a, b, M)
@@ -34,6 +60,10 @@ G0 = ot.emd(a, b, M)
pl.figure(3, figsize=(5, 5))
ot.plot.plot1D_mat(a, b, G0, 'OT matrix G0')
+##############################################################################
+# Solve EMD with Frobenius norm regularization
+# --------------------------------------------
+
#%% Example with Frobenius norm regularization
@@ -52,6 +82,10 @@ Gl2 = ot.optim.cg(a, b, M, reg, f, df, verbose=True)
pl.figure(3)
ot.plot.plot1D_mat(a, b, Gl2, 'OT matrix Frob. reg')
+##############################################################################
+# Solve EMD with entropic regularization
+# --------------------------------------
+
#%% Example with entropic regularization
@@ -70,6 +104,10 @@ Ge = ot.optim.cg(a, b, M, reg, f, df, verbose=True)
pl.figure(4, figsize=(5, 5))
ot.plot.plot1D_mat(a, b, Ge, 'OT matrix Entrop. reg')
+##############################################################################
+# Solve EMD with Frobenius norm + entropic regularization
+# -------------------------------------------------------
+
#%% Example with Frobenius norm + entropic regularization with gcg
diff --git a/examples/plot_otda_classes.py b/examples/plot_otda_classes.py
new file mode 100644
index 0000000..b14c11a
--- /dev/null
+++ b/examples/plot_otda_classes.py
@@ -0,0 +1,150 @@
+# -*- coding: utf-8 -*-
+"""
+========================
+OT for domain adaptation
+========================
+
+This example introduces a domain adaptation in a 2D setting and the 4 OTDA
+approaches currently supported in POT.
+
+"""
+
+# Authors: Remi Flamary <remi.flamary@unice.fr>
+# Stanislas Chambon <stan.chambon@gmail.com>
+#
+# License: MIT License
+
+import matplotlib.pylab as pl
+import ot
+
+
+##############################################################################
+# Generate data
+# -------------
+
+n_source_samples = 150
+n_target_samples = 150
+
+Xs, ys = ot.datasets.get_data_classif('3gauss', n_source_samples)
+Xt, yt = ot.datasets.get_data_classif('3gauss2', n_target_samples)
+
+
+##############################################################################
+# Instantiate the different transport algorithms and fit them
+# -----------------------------------------------------------
+
+# EMD Transport
+ot_emd = ot.da.EMDTransport()
+ot_emd.fit(Xs=Xs, Xt=Xt)
+
+# Sinkhorn Transport
+ot_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)
+ot_sinkhorn.fit(Xs=Xs, Xt=Xt)
+
+# Sinkhorn Transport with Group lasso regularization
+ot_lpl1 = ot.da.SinkhornLpl1Transport(reg_e=1e-1, reg_cl=1e0)
+ot_lpl1.fit(Xs=Xs, ys=ys, Xt=Xt)
+
+# Sinkhorn Transport with Group lasso regularization l1l2
+ot_l1l2 = ot.da.SinkhornL1l2Transport(reg_e=1e-1, reg_cl=2e0, max_iter=20,
+ verbose=True)
+ot_l1l2.fit(Xs=Xs, ys=ys, Xt=Xt)
+
+# transport source samples onto target samples
+transp_Xs_emd = ot_emd.transform(Xs=Xs)
+transp_Xs_sinkhorn = ot_sinkhorn.transform(Xs=Xs)
+transp_Xs_lpl1 = ot_lpl1.transform(Xs=Xs)
+transp_Xs_l1l2 = ot_l1l2.transform(Xs=Xs)
+
+
+##############################################################################
+# Fig 1 : plots source and target samples
+# ---------------------------------------
+
+pl.figure(1, figsize=(10, 5))
+pl.subplot(1, 2, 1)
+pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')
+pl.xticks([])
+pl.yticks([])
+pl.legend(loc=0)
+pl.title('Source samples')
+
+pl.subplot(1, 2, 2)
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')
+pl.xticks([])
+pl.yticks([])
+pl.legend(loc=0)
+pl.title('Target samples')
+pl.tight_layout()
+
+
+##############################################################################
+# Fig 2 : plot optimal couplings and transported samples
+# ------------------------------------------------------
+
+param_img = {'interpolation': 'nearest', 'cmap': 'spectral'}
+
+pl.figure(2, figsize=(15, 8))
+pl.subplot(2, 4, 1)
+pl.imshow(ot_emd.coupling_, **param_img)
+pl.xticks([])
+pl.yticks([])
+pl.title('Optimal coupling\nEMDTransport')
+
+pl.subplot(2, 4, 2)
+pl.imshow(ot_sinkhorn.coupling_, **param_img)
+pl.xticks([])
+pl.yticks([])
+pl.title('Optimal coupling\nSinkhornTransport')
+
+pl.subplot(2, 4, 3)
+pl.imshow(ot_lpl1.coupling_, **param_img)
+pl.xticks([])
+pl.yticks([])
+pl.title('Optimal coupling\nSinkhornLpl1Transport')
+
+pl.subplot(2, 4, 4)
+pl.imshow(ot_l1l2.coupling_, **param_img)
+pl.xticks([])
+pl.yticks([])
+pl.title('Optimal coupling\nSinkhornL1l2Transport')
+
+pl.subplot(2, 4, 5)
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.3)
+pl.scatter(transp_Xs_emd[:, 0], transp_Xs_emd[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+pl.xticks([])
+pl.yticks([])
+pl.title('Transported samples\nEmdTransport')
+pl.legend(loc="lower left")
+
+pl.subplot(2, 4, 6)
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.3)
+pl.scatter(transp_Xs_sinkhorn[:, 0], transp_Xs_sinkhorn[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+pl.xticks([])
+pl.yticks([])
+pl.title('Transported samples\nSinkhornTransport')
+
+pl.subplot(2, 4, 7)
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.3)
+pl.scatter(transp_Xs_lpl1[:, 0], transp_Xs_lpl1[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+pl.xticks([])
+pl.yticks([])
+pl.title('Transported samples\nSinkhornLpl1Transport')
+
+pl.subplot(2, 4, 8)
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.3)
+pl.scatter(transp_Xs_l1l2[:, 0], transp_Xs_l1l2[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+pl.xticks([])
+pl.yticks([])
+pl.title('Transported samples\nSinkhornL1l2Transport')
+pl.tight_layout()
+
+pl.show()
diff --git a/examples/plot_otda_color_images.py b/examples/plot_otda_color_images.py
new file mode 100644
index 0000000..e77aec0
--- /dev/null
+++ b/examples/plot_otda_color_images.py
@@ -0,0 +1,165 @@
+# -*- coding: utf-8 -*-
+"""
+=============================
+OT for image color adaptation
+=============================
+
+This example presents a way of transferring colors between two image
+with Optimal Transport as introduced in [6]
+
+[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014).
+Regularized discrete optimal transport.
+SIAM Journal on Imaging Sciences, 7(3), 1853-1882.
+"""
+
+# Authors: Remi Flamary <remi.flamary@unice.fr>
+# Stanislas Chambon <stan.chambon@gmail.com>
+#
+# License: MIT License
+
+import numpy as np
+from scipy import ndimage
+import matplotlib.pylab as pl
+import ot
+
+
+r = np.random.RandomState(42)
+
+
+def im2mat(I):
+ """Converts and image to matrix (one pixel per line)"""
+ return I.reshape((I.shape[0] * I.shape[1], I.shape[2]))
+
+
+def mat2im(X, shape):
+ """Converts back a matrix to an image"""
+ return X.reshape(shape)
+
+
+def minmax(I):
+ return np.clip(I, 0, 1)
+
+
+##############################################################################
+# Generate data
+# -------------
+
+# Loading images
+I1 = ndimage.imread('../data/ocean_day.jpg').astype(np.float64) / 256
+I2 = ndimage.imread('../data/ocean_sunset.jpg').astype(np.float64) / 256
+
+X1 = im2mat(I1)
+X2 = im2mat(I2)
+
+# training samples
+nb = 1000
+idx1 = r.randint(X1.shape[0], size=(nb,))
+idx2 = r.randint(X2.shape[0], size=(nb,))
+
+Xs = X1[idx1, :]
+Xt = X2[idx2, :]
+
+
+##############################################################################
+# Plot original image
+# -------------------
+
+pl.figure(1, figsize=(6.4, 3))
+
+pl.subplot(1, 2, 1)
+pl.imshow(I1)
+pl.axis('off')
+pl.title('Image 1')
+
+pl.subplot(1, 2, 2)
+pl.imshow(I2)
+pl.axis('off')
+pl.title('Image 2')
+
+
+##############################################################################
+# Scatter plot of colors
+# ----------------------
+
+pl.figure(2, figsize=(6.4, 3))
+
+pl.subplot(1, 2, 1)
+pl.scatter(Xs[:, 0], Xs[:, 2], c=Xs)
+pl.axis([0, 1, 0, 1])
+pl.xlabel('Red')
+pl.ylabel('Blue')
+pl.title('Image 1')
+
+pl.subplot(1, 2, 2)
+pl.scatter(Xt[:, 0], Xt[:, 2], c=Xt)
+pl.axis([0, 1, 0, 1])
+pl.xlabel('Red')
+pl.ylabel('Blue')
+pl.title('Image 2')
+pl.tight_layout()
+
+
+##############################################################################
+# Instantiate the different transport algorithms and fit them
+# -----------------------------------------------------------
+
+# EMDTransport
+ot_emd = ot.da.EMDTransport()
+ot_emd.fit(Xs=Xs, Xt=Xt)
+
+# SinkhornTransport
+ot_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)
+ot_sinkhorn.fit(Xs=Xs, Xt=Xt)
+
+# prediction between images (using out of sample prediction as in [6])
+transp_Xs_emd = ot_emd.transform(Xs=X1)
+transp_Xt_emd = ot_emd.inverse_transform(Xt=X2)
+
+transp_Xs_sinkhorn = ot_emd.transform(Xs=X1)
+transp_Xt_sinkhorn = ot_emd.inverse_transform(Xt=X2)
+
+I1t = minmax(mat2im(transp_Xs_emd, I1.shape))
+I2t = minmax(mat2im(transp_Xt_emd, I2.shape))
+
+I1te = minmax(mat2im(transp_Xs_sinkhorn, I1.shape))
+I2te = minmax(mat2im(transp_Xt_sinkhorn, I2.shape))
+
+
+##############################################################################
+# Plot new images
+# ---------------
+
+pl.figure(3, figsize=(8, 4))
+
+pl.subplot(2, 3, 1)
+pl.imshow(I1)
+pl.axis('off')
+pl.title('Image 1')
+
+pl.subplot(2, 3, 2)
+pl.imshow(I1t)
+pl.axis('off')
+pl.title('Image 1 Adapt')
+
+pl.subplot(2, 3, 3)
+pl.imshow(I1te)
+pl.axis('off')
+pl.title('Image 1 Adapt (reg)')
+
+pl.subplot(2, 3, 4)
+pl.imshow(I2)
+pl.axis('off')
+pl.title('Image 2')
+
+pl.subplot(2, 3, 5)
+pl.imshow(I2t)
+pl.axis('off')
+pl.title('Image 2 Adapt')
+
+pl.subplot(2, 3, 6)
+pl.imshow(I2te)
+pl.axis('off')
+pl.title('Image 2 Adapt (reg)')
+pl.tight_layout()
+
+pl.show()
diff --git a/examples/plot_otda_d2.py b/examples/plot_otda_d2.py
new file mode 100644
index 0000000..e53d7d6
--- /dev/null
+++ b/examples/plot_otda_d2.py
@@ -0,0 +1,172 @@
+# -*- coding: utf-8 -*-
+"""
+===================================================
+OT for domain adaptation on empirical distributions
+===================================================
+
+This example introduces a domain adaptation in a 2D setting. It explicits
+the problem of domain adaptation and introduces some optimal transport
+approaches to solve it.
+
+Quantities such as optimal couplings, greater coupling coefficients and
+transported samples are represented in order to give a visual understanding
+of what the transport methods are doing.
+"""
+
+# Authors: Remi Flamary <remi.flamary@unice.fr>
+# Stanislas Chambon <stan.chambon@gmail.com>
+#
+# License: MIT License
+
+import matplotlib.pylab as pl
+import ot
+
+
+##############################################################################
+# generate data
+# -------------
+
+n_samples_source = 150
+n_samples_target = 150
+
+Xs, ys = ot.datasets.get_data_classif('3gauss', n_samples_source)
+Xt, yt = ot.datasets.get_data_classif('3gauss2', n_samples_target)
+
+# Cost matrix
+M = ot.dist(Xs, Xt, metric='sqeuclidean')
+
+
+##############################################################################
+# Instantiate the different transport algorithms and fit them
+# -----------------------------------------------------------
+
+# EMD Transport
+ot_emd = ot.da.EMDTransport()
+ot_emd.fit(Xs=Xs, Xt=Xt)
+
+# Sinkhorn Transport
+ot_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)
+ot_sinkhorn.fit(Xs=Xs, Xt=Xt)
+
+# Sinkhorn Transport with Group lasso regularization
+ot_lpl1 = ot.da.SinkhornLpl1Transport(reg_e=1e-1, reg_cl=1e0)
+ot_lpl1.fit(Xs=Xs, ys=ys, Xt=Xt)
+
+# transport source samples onto target samples
+transp_Xs_emd = ot_emd.transform(Xs=Xs)
+transp_Xs_sinkhorn = ot_sinkhorn.transform(Xs=Xs)
+transp_Xs_lpl1 = ot_lpl1.transform(Xs=Xs)
+
+
+##############################################################################
+# Fig 1 : plots source and target samples + matrix of pairwise distance
+# ---------------------------------------------------------------------
+
+pl.figure(1, figsize=(10, 10))
+pl.subplot(2, 2, 1)
+pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')
+pl.xticks([])
+pl.yticks([])
+pl.legend(loc=0)
+pl.title('Source samples')
+
+pl.subplot(2, 2, 2)
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')
+pl.xticks([])
+pl.yticks([])
+pl.legend(loc=0)
+pl.title('Target samples')
+
+pl.subplot(2, 2, 3)
+pl.imshow(M, interpolation='nearest')
+pl.xticks([])
+pl.yticks([])
+pl.title('Matrix of pairwise distances')
+pl.tight_layout()
+
+
+##############################################################################
+# Fig 2 : plots optimal couplings for the different methods
+# ---------------------------------------------------------
+pl.figure(2, figsize=(10, 6))
+
+pl.subplot(2, 3, 1)
+pl.imshow(ot_emd.coupling_, interpolation='nearest')
+pl.xticks([])
+pl.yticks([])
+pl.title('Optimal coupling\nEMDTransport')
+
+pl.subplot(2, 3, 2)
+pl.imshow(ot_sinkhorn.coupling_, interpolation='nearest')
+pl.xticks([])
+pl.yticks([])
+pl.title('Optimal coupling\nSinkhornTransport')
+
+pl.subplot(2, 3, 3)
+pl.imshow(ot_lpl1.coupling_, interpolation='nearest')
+pl.xticks([])
+pl.yticks([])
+pl.title('Optimal coupling\nSinkhornLpl1Transport')
+
+pl.subplot(2, 3, 4)
+ot.plot.plot2D_samples_mat(Xs, Xt, ot_emd.coupling_, c=[.5, .5, 1])
+pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')
+pl.xticks([])
+pl.yticks([])
+pl.title('Main coupling coefficients\nEMDTransport')
+
+pl.subplot(2, 3, 5)
+ot.plot.plot2D_samples_mat(Xs, Xt, ot_sinkhorn.coupling_, c=[.5, .5, 1])
+pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')
+pl.xticks([])
+pl.yticks([])
+pl.title('Main coupling coefficients\nSinkhornTransport')
+
+pl.subplot(2, 3, 6)
+ot.plot.plot2D_samples_mat(Xs, Xt, ot_lpl1.coupling_, c=[.5, .5, 1])
+pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')
+pl.xticks([])
+pl.yticks([])
+pl.title('Main coupling coefficients\nSinkhornLpl1Transport')
+pl.tight_layout()
+
+
+##############################################################################
+# Fig 3 : plot transported samples
+# --------------------------------
+
+# display transported samples
+pl.figure(4, figsize=(10, 4))
+pl.subplot(1, 3, 1)
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.5)
+pl.scatter(transp_Xs_emd[:, 0], transp_Xs_emd[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+pl.title('Transported samples\nEmdTransport')
+pl.legend(loc=0)
+pl.xticks([])
+pl.yticks([])
+
+pl.subplot(1, 3, 2)
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.5)
+pl.scatter(transp_Xs_sinkhorn[:, 0], transp_Xs_sinkhorn[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+pl.title('Transported samples\nSinkhornTransport')
+pl.xticks([])
+pl.yticks([])
+
+pl.subplot(1, 3, 3)
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.5)
+pl.scatter(transp_Xs_lpl1[:, 0], transp_Xs_lpl1[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+pl.title('Transported samples\nSinkhornLpl1Transport')
+pl.xticks([])
+pl.yticks([])
+
+pl.tight_layout()
+pl.show()
diff --git a/examples/plot_otda_mapping.py b/examples/plot_otda_mapping.py
new file mode 100644
index 0000000..167c3a1
--- /dev/null
+++ b/examples/plot_otda_mapping.py
@@ -0,0 +1,125 @@
+# -*- coding: utf-8 -*-
+"""
+===========================================
+OT mapping estimation for domain adaptation
+===========================================
+
+This example presents how to use MappingTransport to estimate at the same
+time both the coupling transport and approximate the transport map with either
+a linear or a kernelized mapping as introduced in [8].
+
+[8] M. Perrot, N. Courty, R. Flamary, A. Habrard,
+ "Mapping estimation for discrete optimal transport",
+ Neural Information Processing Systems (NIPS), 2016.
+"""
+
+# Authors: Remi Flamary <remi.flamary@unice.fr>
+# Stanislas Chambon <stan.chambon@gmail.com>
+#
+# License: MIT License
+
+import numpy as np
+import matplotlib.pylab as pl
+import ot
+
+
+##############################################################################
+# Generate data
+# -------------
+
+n_source_samples = 100
+n_target_samples = 100
+theta = 2 * np.pi / 20
+noise_level = 0.1
+
+Xs, ys = ot.datasets.get_data_classif(
+ 'gaussrot', n_source_samples, nz=noise_level)
+Xs_new, _ = ot.datasets.get_data_classif(
+ 'gaussrot', n_source_samples, nz=noise_level)
+Xt, yt = ot.datasets.get_data_classif(
+ 'gaussrot', n_target_samples, theta=theta, nz=noise_level)
+
+# one of the target mode changes its variance (no linear mapping)
+Xt[yt == 2] *= 3
+Xt = Xt + 4
+
+##############################################################################
+# Plot data
+# ---------
+
+pl.figure(1, (10, 5))
+pl.clf()
+pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')
+pl.legend(loc=0)
+pl.title('Source and target distributions')
+
+
+##############################################################################
+# Instantiate the different transport algorithms and fit them
+# -----------------------------------------------------------
+
+# MappingTransport with linear kernel
+ot_mapping_linear = ot.da.MappingTransport(
+ kernel="linear", mu=1e0, eta=1e-8, bias=True,
+ max_iter=20, verbose=True)
+
+ot_mapping_linear.fit(Xs=Xs, Xt=Xt)
+
+# for original source samples, transform applies barycentric mapping
+transp_Xs_linear = ot_mapping_linear.transform(Xs=Xs)
+
+# for out of source samples, transform applies the linear mapping
+transp_Xs_linear_new = ot_mapping_linear.transform(Xs=Xs_new)
+
+
+# MappingTransport with gaussian kernel
+ot_mapping_gaussian = ot.da.MappingTransport(
+ kernel="gaussian", eta=1e-5, mu=1e-1, bias=True, sigma=1,
+ max_iter=10, verbose=True)
+ot_mapping_gaussian.fit(Xs=Xs, Xt=Xt)
+
+# for original source samples, transform applies barycentric mapping
+transp_Xs_gaussian = ot_mapping_gaussian.transform(Xs=Xs)
+
+# for out of source samples, transform applies the gaussian mapping
+transp_Xs_gaussian_new = ot_mapping_gaussian.transform(Xs=Xs_new)
+
+
+##############################################################################
+# Plot transported samples
+# ------------------------
+
+pl.figure(2)
+pl.clf()
+pl.subplot(2, 2, 1)
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=.2)
+pl.scatter(transp_Xs_linear[:, 0], transp_Xs_linear[:, 1], c=ys, marker='+',
+ label='Mapped source samples')
+pl.title("Bary. mapping (linear)")
+pl.legend(loc=0)
+
+pl.subplot(2, 2, 2)
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=.2)
+pl.scatter(transp_Xs_linear_new[:, 0], transp_Xs_linear_new[:, 1],
+ c=ys, marker='+', label='Learned mapping')
+pl.title("Estim. mapping (linear)")
+
+pl.subplot(2, 2, 3)
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=.2)
+pl.scatter(transp_Xs_gaussian[:, 0], transp_Xs_gaussian[:, 1], c=ys,
+ marker='+', label='barycentric mapping')
+pl.title("Bary. mapping (kernel)")
+
+pl.subplot(2, 2, 4)
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=.2)
+pl.scatter(transp_Xs_gaussian_new[:, 0], transp_Xs_gaussian_new[:, 1], c=ys,
+ marker='+', label='Learned mapping')
+pl.title("Estim. mapping (kernel)")
+pl.tight_layout()
+
+pl.show()
diff --git a/examples/plot_otda_mapping_colors_images.py b/examples/plot_otda_mapping_colors_images.py
new file mode 100644
index 0000000..5f1e844
--- /dev/null
+++ b/examples/plot_otda_mapping_colors_images.py
@@ -0,0 +1,174 @@
+# -*- coding: utf-8 -*-
+"""
+=====================================================
+OT for image color adaptation with mapping estimation
+=====================================================
+
+OT for domain adaptation with image color adaptation [6] with mapping
+estimation [8].
+
+[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014). Regularized
+ discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3),
+ 1853-1882.
+[8] M. Perrot, N. Courty, R. Flamary, A. Habrard, "Mapping estimation for
+ discrete optimal transport", Neural Information Processing Systems (NIPS),
+ 2016.
+
+"""
+
+# Authors: Remi Flamary <remi.flamary@unice.fr>
+# Stanislas Chambon <stan.chambon@gmail.com>
+#
+# License: MIT License
+
+import numpy as np
+from scipy import ndimage
+import matplotlib.pylab as pl
+import ot
+
+r = np.random.RandomState(42)
+
+
+def im2mat(I):
+ """Converts and image to matrix (one pixel per line)"""
+ return I.reshape((I.shape[0] * I.shape[1], I.shape[2]))
+
+
+def mat2im(X, shape):
+ """Converts back a matrix to an image"""
+ return X.reshape(shape)
+
+
+def minmax(I):
+ return np.clip(I, 0, 1)
+
+
+##############################################################################
+# Generate data
+# -------------
+
+# Loading images
+I1 = ndimage.imread('../data/ocean_day.jpg').astype(np.float64) / 256
+I2 = ndimage.imread('../data/ocean_sunset.jpg').astype(np.float64) / 256
+
+
+X1 = im2mat(I1)
+X2 = im2mat(I2)
+
+# training samples
+nb = 1000
+idx1 = r.randint(X1.shape[0], size=(nb,))
+idx2 = r.randint(X2.shape[0], size=(nb,))
+
+Xs = X1[idx1, :]
+Xt = X2[idx2, :]
+
+
+##############################################################################
+# Domain adaptation for pixel distribution transfer
+# -------------------------------------------------
+
+# EMDTransport
+ot_emd = ot.da.EMDTransport()
+ot_emd.fit(Xs=Xs, Xt=Xt)
+transp_Xs_emd = ot_emd.transform(Xs=X1)
+Image_emd = minmax(mat2im(transp_Xs_emd, I1.shape))
+
+# SinkhornTransport
+ot_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)
+ot_sinkhorn.fit(Xs=Xs, Xt=Xt)
+transp_Xs_sinkhorn = ot_emd.transform(Xs=X1)
+Image_sinkhorn = minmax(mat2im(transp_Xs_sinkhorn, I1.shape))
+
+ot_mapping_linear = ot.da.MappingTransport(
+ mu=1e0, eta=1e-8, bias=True, max_iter=20, verbose=True)
+ot_mapping_linear.fit(Xs=Xs, Xt=Xt)
+
+X1tl = ot_mapping_linear.transform(Xs=X1)
+Image_mapping_linear = minmax(mat2im(X1tl, I1.shape))
+
+ot_mapping_gaussian = ot.da.MappingTransport(
+ mu=1e0, eta=1e-2, sigma=1, bias=False, max_iter=10, verbose=True)
+ot_mapping_gaussian.fit(Xs=Xs, Xt=Xt)
+
+X1tn = ot_mapping_gaussian.transform(Xs=X1) # use the estimated mapping
+Image_mapping_gaussian = minmax(mat2im(X1tn, I1.shape))
+
+
+##############################################################################
+# Plot original images
+# --------------------
+
+pl.figure(1, figsize=(6.4, 3))
+pl.subplot(1, 2, 1)
+pl.imshow(I1)
+pl.axis('off')
+pl.title('Image 1')
+
+pl.subplot(1, 2, 2)
+pl.imshow(I2)
+pl.axis('off')
+pl.title('Image 2')
+pl.tight_layout()
+
+
+##############################################################################
+# Plot pixel values distribution
+# ------------------------------
+
+pl.figure(2, figsize=(6.4, 5))
+
+pl.subplot(1, 2, 1)
+pl.scatter(Xs[:, 0], Xs[:, 2], c=Xs)
+pl.axis([0, 1, 0, 1])
+pl.xlabel('Red')
+pl.ylabel('Blue')
+pl.title('Image 1')
+
+pl.subplot(1, 2, 2)
+pl.scatter(Xt[:, 0], Xt[:, 2], c=Xt)
+pl.axis([0, 1, 0, 1])
+pl.xlabel('Red')
+pl.ylabel('Blue')
+pl.title('Image 2')
+pl.tight_layout()
+
+
+##############################################################################
+# Plot transformed images
+# -----------------------
+
+pl.figure(2, figsize=(10, 5))
+
+pl.subplot(2, 3, 1)
+pl.imshow(I1)
+pl.axis('off')
+pl.title('Im. 1')
+
+pl.subplot(2, 3, 4)
+pl.imshow(I2)
+pl.axis('off')
+pl.title('Im. 2')
+
+pl.subplot(2, 3, 2)
+pl.imshow(Image_emd)
+pl.axis('off')
+pl.title('EmdTransport')
+
+pl.subplot(2, 3, 5)
+pl.imshow(Image_sinkhorn)
+pl.axis('off')
+pl.title('SinkhornTransport')
+
+pl.subplot(2, 3, 3)
+pl.imshow(Image_mapping_linear)
+pl.axis('off')
+pl.title('MappingTransport (linear)')
+
+pl.subplot(2, 3, 6)
+pl.imshow(Image_mapping_gaussian)
+pl.axis('off')
+pl.title('MappingTransport (gaussian)')
+pl.tight_layout()
+
+pl.show()
diff --git a/examples/plot_otda_semi_supervised.py b/examples/plot_otda_semi_supervised.py
new file mode 100644
index 0000000..7963aef
--- /dev/null
+++ b/examples/plot_otda_semi_supervised.py
@@ -0,0 +1,148 @@
+# -*- coding: utf-8 -*-
+"""
+============================================
+OTDA unsupervised vs semi-supervised setting
+============================================
+
+This example introduces a semi supervised domain adaptation in a 2D setting.
+It explicits the problem of semi supervised domain adaptation and introduces
+some optimal transport approaches to solve it.
+
+Quantities such as optimal couplings, greater coupling coefficients and
+transported samples are represented in order to give a visual understanding
+of what the transport methods are doing.
+"""
+
+# Authors: Remi Flamary <remi.flamary@unice.fr>
+# Stanislas Chambon <stan.chambon@gmail.com>
+#
+# License: MIT License
+
+import matplotlib.pylab as pl
+import ot
+
+
+##############################################################################
+# Generate data
+# -------------
+
+n_samples_source = 150
+n_samples_target = 150
+
+Xs, ys = ot.datasets.get_data_classif('3gauss', n_samples_source)
+Xt, yt = ot.datasets.get_data_classif('3gauss2', n_samples_target)
+
+
+##############################################################################
+# Transport source samples onto target samples
+# --------------------------------------------
+
+
+# unsupervised domain adaptation
+ot_sinkhorn_un = ot.da.SinkhornTransport(reg_e=1e-1)
+ot_sinkhorn_un.fit(Xs=Xs, Xt=Xt)
+transp_Xs_sinkhorn_un = ot_sinkhorn_un.transform(Xs=Xs)
+
+# semi-supervised domain adaptation
+ot_sinkhorn_semi = ot.da.SinkhornTransport(reg_e=1e-1)
+ot_sinkhorn_semi.fit(Xs=Xs, Xt=Xt, ys=ys, yt=yt)
+transp_Xs_sinkhorn_semi = ot_sinkhorn_semi.transform(Xs=Xs)
+
+# semi supervised DA uses available labaled target samples to modify the cost
+# matrix involved in the OT problem. The cost of transporting a source sample
+# of class A onto a target sample of class B != A is set to infinite, or a
+# very large value
+
+# note that in the present case we consider that all the target samples are
+# labeled. For daily applications, some target sample might not have labels,
+# in this case the element of yt corresponding to these samples should be
+# filled with -1.
+
+# Warning: we recall that -1 cannot be used as a class label
+
+
+##############################################################################
+# Fig 1 : plots source and target samples + matrix of pairwise distance
+# ---------------------------------------------------------------------
+
+pl.figure(1, figsize=(10, 10))
+pl.subplot(2, 2, 1)
+pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')
+pl.xticks([])
+pl.yticks([])
+pl.legend(loc=0)
+pl.title('Source samples')
+
+pl.subplot(2, 2, 2)
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')
+pl.xticks([])
+pl.yticks([])
+pl.legend(loc=0)
+pl.title('Target samples')
+
+pl.subplot(2, 2, 3)
+pl.imshow(ot_sinkhorn_un.cost_, interpolation='nearest')
+pl.xticks([])
+pl.yticks([])
+pl.title('Cost matrix - unsupervised DA')
+
+pl.subplot(2, 2, 4)
+pl.imshow(ot_sinkhorn_semi.cost_, interpolation='nearest')
+pl.xticks([])
+pl.yticks([])
+pl.title('Cost matrix - semisupervised DA')
+
+pl.tight_layout()
+
+# the optimal coupling in the semi-supervised DA case will exhibit " shape
+# similar" to the cost matrix, (block diagonal matrix)
+
+
+##############################################################################
+# Fig 2 : plots optimal couplings for the different methods
+# ---------------------------------------------------------
+
+pl.figure(2, figsize=(8, 4))
+
+pl.subplot(1, 2, 1)
+pl.imshow(ot_sinkhorn_un.coupling_, interpolation='nearest')
+pl.xticks([])
+pl.yticks([])
+pl.title('Optimal coupling\nUnsupervised DA')
+
+pl.subplot(1, 2, 2)
+pl.imshow(ot_sinkhorn_semi.coupling_, interpolation='nearest')
+pl.xticks([])
+pl.yticks([])
+pl.title('Optimal coupling\nSemi-supervised DA')
+
+pl.tight_layout()
+
+
+##############################################################################
+# Fig 3 : plot transported samples
+# --------------------------------
+
+# display transported samples
+pl.figure(4, figsize=(8, 4))
+pl.subplot(1, 2, 1)
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.5)
+pl.scatter(transp_Xs_sinkhorn_un[:, 0], transp_Xs_sinkhorn_un[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+pl.title('Transported samples\nEmdTransport')
+pl.legend(loc=0)
+pl.xticks([])
+pl.yticks([])
+
+pl.subplot(1, 2, 2)
+pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',
+ label='Target samples', alpha=0.5)
+pl.scatter(transp_Xs_sinkhorn_semi[:, 0], transp_Xs_sinkhorn_semi[:, 1], c=ys,
+ marker='+', label='Transp samples', s=30)
+pl.title('Transported samples\nSinkhornTransport')
+pl.xticks([])
+pl.yticks([])
+
+pl.tight_layout()
+pl.show()
diff --git a/notebooks/Demo_1D_OT.ipynb b/notebooks/Demo_1D_OT.ipynb
deleted file mode 100644
index 087b3bc..0000000
--- a/notebooks/Demo_1D_OT.ipynb
+++ /dev/null
@@ -1,198 +0,0 @@
-{
- "metadata": {
- "name": "",
- "signature": "sha256:b65d32b626c6b5575ab808a448461a190dd0152a68ce83ddf7bbaf1aefb35c43"
- },
- "nbformat": 3,
- "nbformat_minor": 0,
- "worksheets": [
- {
- "cells": [
- {
- "cell_type": "heading",
- "level": 1,
- "metadata": {},
- "source": [
- "1D optimal transport demo"
- ]
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "# load all relevant modules\n",
- "import numpy as np\n",
- "import matplotlib.pylab as pl\n",
- "import ot"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [],
- "prompt_number": 1
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Dataset generation"
- ]
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "\n",
- "n=100 # nb bins\n",
- "a=ot.datasets.get_1D_gauss(n,m=20,s=20) # m= mean, s= std\n",
- "b=ot.datasets.get_1D_gauss(n,m=60,s=60)\n",
- "\n",
- "# bin positions\n",
- "x=np.arange(n,dtype=np.float64)\n",
- "# loss matrix\n",
- "M=ot.dist(x.reshape((n,1)),x.reshape((n,1)))\n",
- "M/=M.max()"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [],
- "prompt_number": 2
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Plotting the distributions"
- ]
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "\n",
- "pl.figure(1)\n",
- "pl.plot(x,a,'b',label='Source distribution')\n",
- "pl.plot(x,b,'r',label='Target distribution')\n",
- "pl.legend()\n",
- "pl.show()"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "display_data",
- "png": 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mjEkVkQRs5fAxETkRWAJ0Msbs8diHKSuOUDBmDLRpA3//u3MxtGwJixZB69bO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\nz1NSUkhJSfFTaOW3di30Csn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- "text": [
- "<matplotlib.figure.Figure at 0x7fd7a7241990>"
- ]
- }
- ],
- "prompt_number": 3
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Distributions and loss matrix"
- ]
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "# plot distributions and loss matrix\n",
- "\n",
- "pl.figure(2)\n",
- "ot.plot.plot1D_mat(a,b,M,'Cost matrix M')\n"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "display_data",
- "png": 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J3C0yDCMKTMDLmIsvdkMRA28+K1P86ayZ/tpDcd0pFk+8s8oEuVMkoVKYzFYb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\njJrI+ikiQ4GrgZNU9WO4YSR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- "text": [
- "<matplotlib.figure.Figure at 0x7fd7a7241890>"
- ]
- }
- ],
- "prompt_number": 4
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## OT solution (Earth Mover's Distance)"
- ]
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "G0=ot.emd(a,b,M)\n",
- "\n",
- "pl.figure(3)\n",
- "ot.plot.plot1D_mat(a,b,G0,'OT matrix G0')\n"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "display_data",
- "png": 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- "text": [
- "<matplotlib.figure.Figure at 0x7fd7a48bb4d0>"
- ]
- }
- ],
- "prompt_number": 5
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Regularized Optimal transport (Entropic regularization)"
- ]
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "# reg parameter\n",
- "lambd=1e-3\n",
- "\n",
- "Gs=ot.sinkhorn(a,b,M,lambd)\n",
- "\n",
- "pl.figure(4)\n",
- "ot.plot.plot1D_mat(a,b,Gs,'OT matrix Sinkhorn')"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "display_data",
- "png": 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v9svXr4fZs2HWLHj4Ybj88nAx9QtfCG31p5wSPlOmoydS0hQCmqE99gjDC/Tv\nn122cmUYQ/255+DCC8OIjgMGwGmnhYdc7Ldf4fIrElSRrZGvJFsbXw68Gma3dIA1mUe97UV2LJaP\nCN0VM6OQxwfdAtXCa6YAnhL77gunnx6ma64JF06feAKmToWLLw7t7z/+MQwcqKYWaQ7iwXwT2f7e\nK8mOGd6GbMDeje21jC3bEluuQB6nUz2l9tsPzj0XHnwwPB908GAYOTL0lhk/PtypKiLFTQG8COy+\nO3z3u6Hd/K674Kab4OSTQ68XkeZhE9ma+EqyNfEFsWkR8GE0xWvaZYQaeWaSDAXwImIWmlKefz4E\n8H79Qg8XkeYl07yyidBdcD0hoFeSDe7ryAb9uHgwF7WBF6GyMrjkktDMcvLJ8PLLhc6RiOSDAngR\nO/vs0BUx9uQzkWamqtp8/IJlTeFpSw3LSpcCeJG76qpw+75IOlQP6BlqMqmJ2sCL3N5773igLhFJ\nNwXwEtC7d6FzINJYVTVMogBeAtSEIlKccg7gZraTmc02s8nR+25mNtPM5pvZ/Wam9vRmau+9d7xO\nx1UkvepTA78QiPcq/g1wvbv3ANYA5yeZMUlO69a1rtZxFUmpnAK4mXUGTgNujy0+CZgUzY8HvpZs\n1iQpO3rkm46rSLrlWgP/PXAJ4ABm1h5Y7e6fRuuXAZ2Sz54koZaHQ+i4iqRYnQHczE4HKt19DtnR\n16k2L81YTQFcx1Uk/XK5QNUPGGxmpxHGd9wDuBFoa2Y7RbW1zoRBf2s0OnYrYHl5OeXl5Y3IsuSi\noqKCiooKIDx4uQY6riLNSPyczZV5PcYdNbP+wMXuPtjMHgD+6u4PmNltwCvu/scaPuP1SUOSN2sW\nHHec4e411q7TflzHjXuJESOmFDobkmJt2uzC2rWXFTob2zHb8Tmb0Zh+4COBi8xsPuHRGnc0Yl+S\nR1a/RhEdV5GUqFcfX3d/Gng6mn8H0E3aRUDHVSSddCemiEhKKYCXgHo2oYhISiiAi4iklAK4iEhK\nKYCLiKSUAriISEopgIuIpJQCuIhISimAi4iklAK4iEhKKYCLiKSUAriISEopgIuIpJQCuIhISimA\ni4iklAK4iEhKKYCLiKSUAriISEopgIuIpJQCuIhISuUUwM2srZlNNLN5ZvaGmR1nZnua2ZNm9paZ\nPWFmbfOdWUmWjqtIuuVaA78RmOruPYGjgTeBkcA0dz8UmA5clp8sSh7puIqkWJ0B3MzaACe6+10A\n7r7F3deMKTumAAAH8klEQVQCQ4Dx0Wbjga/mLZeSOB1XkfTLpQbeHfjAzO4ys9lmNtbMdgc6uHsl\ngLu/B+ybz4xK4nRcRVIulwBeBvQCbnH3XsBGws9sr7Zd9ffSvOm4iqRcWQ7bLAOWuvuL0ftJhBO9\n0sw6uHulmXUEVu5oB6NHj942X15eTnl5eYMzLLmpqKigoqICgBUratxEx1WkGYmfs7ky97orWGb2\nNPA9d59vZqOA3aNVq9z9N2b2C2BPdx9Zw2c9lzQkf158EXr3Ntzd4suL5biOG/cSI0ZMKXQ2JMXa\ntNmFtWub1/V6s8+es9XlUgMH+Alwn5m1BBYC5wEtgAfN7DvAYmBYYzIrBaHjKpJiOQVwd38F6F3D\nqgHJZkeako6rSLrpTkwRkZRSABcRSSkFcBGRlFIAFxFJKQVwEZGUUgAXEUkpBXARkZRSABcRSSkF\ncBGRlFIAFxFJKQVwEZGUUgAXEUkpBXARkZRSABcRSSkFcBGRlFIAFxFJKQVwEZGUUgAXEUkpBXAR\nkZRSABcRSamcAriZ/czMXjezV83sPjPb2cy6mdlMM5tvZvebWa5PuJdmQsdVJN3qDOBm1gm4AOjl\n7kcRnmQ/HPgNcL279wDWAOfnM6OSLB1XkfTLtQmlBdAqqo3tBqwA/gOYFK0fD3wt+exJnum4iqRY\nnQHc3VcA1wNLgOXAWmA2sMbdP402WwZ0ylcmJXk6riLpl0sTSjtgCNCVcDK3AgblOV+SZzquIumX\nywWqAcBCd18FYGZ/A/oB7cxsp6i21plQi6vR6NGjt82Xl5dTXl7eiCxLLioqKqioqABgxYoaN9Fx\nFWlG4udsrszda9/ArA9wB9Ab2AzcBbwAfAn4q7s/YGa3Aa+4+x9r+LzXlYbk14svQu/ehrtbZlkx\nHddx415ixIgphc6GpFibNruwdu1lhc7Gdsy2P2drkksb+CzgIeBl4BXAgLHASOAiM5sP7EUIBpIS\nOq4i6ZdTH193HwOMqbb4HeC4xHMkTUbHVSTddCemiEhKKYCLiKSUAriISEopgIuIpJQCuIhISimA\ni4iklAK4iEhKKYCLiKSUAriISEopgIuIpJQCuIhISimAi4iklAK4iEhKKYCLiKSUAriISEopgIuI\npJQCuIhISimAi4iklAK4iEhKKYCLiKSUArgkrqKiogCpLlKaSrNRmvp7m0R6CuCSOAVwpZnGNBXA\nRUSkySiAl4B99il0DkQkH8zd85uAWX4TkJy5uyW1Lx1Xkfyr65zNewAXEZH8UBOKiEhKKYCLiKSU\nArgkxsx+a2bzzGyOmU0yszaxdZeZ2YJo/ckJpzvIzN40s/lm9osk9x3tv7OZTTezN8zsNTP7SbR8\nTzN70szeMrMnzKxtHtLeycxmm9nk6H03M5sZlfV+MytLOL22ZjYxOk5vmNlx+S6nmf3MzF43s1fN\n7D4z2znpcprZHWZWaWavxpbtsFxmdlP0fZ1jZsckmGai54gCuCTpSeAIdz8GWABcBmBmhwPDgJ7A\nqcCtZpbIBVUz2wn4A3AKcAQw3MwOS2LfMVuAi9z9CKAv8OMojZHANHc/FJhOVN6EXQjMjb3/DXC9\nu/cA1gDnJ5zejcBUd+8JHA28SR7LaWadgAuAXu5+FFAGDCf5ct5F+I7E1VguMzsVOMjdDwG+D/wx\nwTQTPUcUwCUx7j7N3T+N3s4EOkfzg4EJ7r7F3RcRvrh9Ekq2D7DA3Re7exUwARiS0L4BcPf33H1O\nNL8BmEco2xBgfLTZeOCrSaZrZp2B04DbY4tPAibF0vxagum1AU5097sAouO1ljyXE2gBtIpq2bsB\nK4D/IMFyuvuzwOpqi6uXa0hs+T3R554H2ppZhyTSTPocUQCXfPkOMDWa3x9YGlu3PFqWhOr7Xpbg\nvj/DzLoBxxBOvg7uXgkhyAP7Jpzc74FLAI/Sbg+sjgWAZUCnBNPrDnxgZndFzTZjzWx38lhOd18B\nXA8sIXwv1gKzgTV5LGfGvtXKlQnS+fy+xjX6HFEAl3oxs39EbZWZ6bXo9YzYNpcDVe5+fwGzmjgz\naw08BFwY1cSr98FNrE+umZ0OVEY1//hP6cT68tegDOgF3OLuvYCNhGaGfJazHaHG25UQpFsBg5La\nfz01WZ/qpM6RRC+ASPFz94G1rTezcwk/+0+KLV4OHBB73zlaloTlQJc87Xub6Of9Q8Cf3f3haHGl\nmXVw90oz6wisTDDJfsBgMzuN0KywB6F9uq2Z7RTVTpMu6zJgqbu/GL2fRAjg+SznAGChu68CMLO/\nEcreLo/lzNhRufL5fU30HFENXBJjZoMIP/kHu/vm2KrJwJlR74LuwMHArISSfQE42My6mtnOwJlR\nekm7E5jr7jfGlk0Gzo3mzwEerv6hhnL3X7p7F3c/kFCm6e5+NvAUMDRPaVYCS82sR7Toy8Ab5LGc\nhKaT481s1+iiXSbNfJTT2P4XTLxc58bSmAx8G8DMjic051QmkWbi54i7a9KUyES48LKY0IY5G7g1\ntu4y4G3CBcCTE053EPBWlP7IPJSrH7AVmAO8HJVtELAXMC1K+0mgXZ7+rv2BydF8d+B5YD7wANAy\n4bSOJvxTnAP8FWib73ICo6LvxauEi4ktky4n8BfCxdHNhH8a5wF77qhchJ5NbwOvEHrIJJVmoueI\nbqUXEUkpNaGIiKSUAriISEopgIuIpJQCuIhISimAi4iklAK4iEhKKYCLiKSUAriISEr9fxeVt4Fv\nL+KNAAAAAElFTkSuQmCC\n",
- "text": [
- "<matplotlib.figure.Figure at 0x7fd7a46b23d0>"
- ]
- }
- ],
- "prompt_number": 6
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [],
- "language": "python",
- "metadata": {},
- "outputs": [],
- "prompt_number": 6
- }
- ],
- "metadata": {}
- }
- ]
-} \ No newline at end of file
diff --git a/notebooks/Demo_1D_barycenter.ipynb b/notebooks/Demo_1D_barycenter.ipynb
deleted file mode 100644
index c93d00b..0000000
--- a/notebooks/Demo_1D_barycenter.ipynb
+++ /dev/null
@@ -1,297 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 1D Wasserstein barycenter demo"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "import numpy as np\n",
- "import matplotlib.pylab as pl\n",
- "import ot\n",
- "\n",
- "from mpl_toolkits.mplot3d import Axes3D\n",
- "from matplotlib.collections import PolyCollection\n",
- "from matplotlib.colors import colorConverter"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Dataset Generation"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "n=100 # nb bins\n",
- "\n",
- "# bin positions\n",
- "x=np.arange(n,dtype=np.float64)\n",
- "\n",
- "# Gaussian distributions\n",
- "a1=ot.datasets.get_1D_gauss(n,m=20,s=5) # m= mean, s= std\n",
- "a2=ot.datasets.get_1D_gauss(n,m=60,s=8)\n",
- "\n",
- "# creating matrix A containing all distributions\n",
- "A=np.vstack((a1,a2)).T\n",
- "nbd=A.shape[1]\n",
- "\n",
- "# loss matrix + normalization\n",
- "M=ot.utils.dist0(n)\n",
- "M/=M.max()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Plot distributions"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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tH/b/IY3rNuZ/5v1PrV5XJNGosAiBzZvh4MHkLixAS07l+D228DF27t/Jz86t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\n",
- "text/plain": [
- "<matplotlib.figure.Figure at 0x7fd9188cfed0>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "pl.figure(1)\n",
- "for i in range(nbd):\n",
- " pl.plot(x,A[:,i])\n",
- "pl.title('Distributions')\n",
- "pl.show()\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Barycenter computation (for l2 and Wasserstein)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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eoap2PGAmtm+Hb76Btvl3+f4Jq1DB9cZMm+Z3JsYvKWkpdJ3YldJFS/N+x/eJ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\n",
- "text/plain": [
- "<matplotlib.figure.Figure at 0x7fd9548e8490>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "# l2bary\n",
- "bary_l2=A.mean(1)\n",
- "\n",
- "# wasserstein\n",
- "reg=1e-3\n",
- "bary_wass=ot.bregman.barycenter(A,M,reg)\n",
- "\n",
- "pl.figure(2)\n",
- "pl.clf()\n",
- "pl.subplot(2,1,1)\n",
- "for i in range(nbd):\n",
- " pl.plot(x,A[:,i])\n",
- "pl.title('Distributions')\n",
- "pl.xticks([])\n",
- "\n",
- "pl.subplot(2,1,2)\n",
- "pl.plot(x,bary_l2,'r',label='l2')\n",
- "pl.plot(x,bary_wass,'g',label='Wasserstein')\n",
- "pl.legend()\n",
- "pl.title('Barycenters')\n",
- "\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": false
- },
- "source": [
- "## Barycenter interpolation"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "\n",
- "nbalpha=11\n",
- "alphalist=np.linspace(0,1,nbalpha)\n",
- "\n",
- "\n",
- "B_l2=np.zeros((n,nbalpha))\n",
- "\n",
- "B_wass=np.copy(B_l2)\n",
- "\n",
- "for i in range(0,nbalpha):\n",
- " alpha=alphalist[i]\n",
- " weights=np.array([1-alpha,alpha])\n",
- " B_l2[:,i]=A.dot(weights)\n",
- " B_wass[:,i]=ot.bregman.barycenter(A,M,reg,weights)\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Plot interpolation"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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MnDkTy5cvxw033ICXXnoJJSUlqKysRE5Ojt/+FRUVmDhxIhYsWIBRo0Zh3bp1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Vq1eTmZmpX7P6+vpIL7qEgoKiCKs7pJa6Y5KId6brrO74+KFbIUqSSGHBbs7UFbJgwSzuu+/r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\nFGUrsEpRlMmAPfAJsP4uK6wlknrJ/wOb9inBmId1nwAAAABJRU5ErkJggg==\n",
- "text/plain": [
- "<matplotlib.figure.Figure at 0x7fd9165a66d0>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
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4//KPT/+VhFqiNiEJskSNwC9vSYVYuOCD1Wp1EOLo6GgoFAoAgF6vr8nmS512\nADCM84IcdrsdBoMBCoUCDMMEXD6U/y/FG6GmLnWx1CzpmUuEGkmQJcIKv7ylKyGmFrHNZnMQYlcd\nbDigbZY65tBA7ym1WinBrvPN/5d/DvovfT+F0yaSUEuEA0mQJcKCr0Isl8tdCnE4IYSgoqKCm/ek\nxUb4bZYKXIQOsWInQM0LNT1/VFSUJNQSQUMSZImQwl+LmF9Ziy9qZrMZRqORE2Ja8MNdhxbq+V2L\nxQKTycRdg1qtdihFSTt+ug/gXecvIU5Nr5zlakEO/r/8c5jNZlgsFsjlcp8s6kivny5Rs0iCLBES\n+EJMERPiqqoq2O12TojpHHFNwY/kpm2NjY3lAs/4HarVaoVGo+E6fWr9+2OlSQSHQITa1xxqGhjG\nPwf9l29R84VdTKjFBgMSdRNJkCWChnAtYoow35QvxAqFAtHR0U5BPp4ItoUsFslNF2VwJ578SGI6\nmPDFSpPqOocHb4VamHpHvysUabF1sj25vvnHF7rMxURaeh/qHpIgSwQM7dRMJhNMJhMUCgVnOfCF\n2GQywWg0BiTEwUYoxPx5a+qOFhN+T+50b600m80mugaxJytNIji4e1aeip0AfxWn8WRRAxBN/xKu\nRe1OqIUFTyRuPyRBlvAbvmuOrsBUVVWFqKgoJyGuqqrigmBUKlVQhDgQC9mdELs6l/B8wZz3DFZJ\nytpOpFyPp2InZrOZ8wKFss63J6GWPCy3F5IgS/iMUIgJcV6LmBACo9EIo9HICbFarXbq4PzF347H\nVyEOB546f3dCLc1Phxf6rKjoqtVqAOFfkINf8YzvKpeEunYjCbKE1/CXQKQlDvlCTP81Go3cesVK\npRIqlSpoQuwvkSjEnvBGqD0FkvH3jWShru0V0QIZVIVKqPnfoS5vscpkEpGDJMgSHvEkxEB1wIrR\naARQnQoUaiH2NqgrECHmu90jCV8Cyeh2g8EAQAokCxbCetuuCIf3wxuhtlgs0Ov1UCgU3HH4AWTS\nOxEZSIIs4RKhEAPOq/FQIaZiDABarRZKpTLs7eVTGy3iQHA1P63X68GyLBQKhRRIFkH4ItQWiyVo\nQk0tZHcWNX/QJgl1eJEEWcIJb1ZeEgqxSqWCQqFARUVFWIofuLKQQyXEriJnIx363IRBdP64Uunc\naW259lATivvgTqiFC3L4ku8u/B17Y1ELBwG0bZJQhw5JkCU4vBXiqqoqroSkSqWCSqVyyM2sCRdv\nKITYG5eNyQYwAAAgAElEQVS1t67LSCNSA8lqy70M93N3NajyNt+dQiPDA3F9S0IdOiRBlvBKiG02\nG4xGIyfEarUaSqXS4ccezjlXhmE4d144XNN1pWMJRiCZFPEdHnzNdwf8K/Xqi1DzI74lofYdSZDr\nMN4KcVVVFcxmMyfEKpWqxn9QtJOpqKioE3PENY0vgWT+VCSLtMA5b4jUd01MqGltdrVa7fTM/B1Y\neSvUYt9xVT40Uu9puJAEuQ4SKiEOh4XMt4gBhEWI6ci/rncWQny10NwFktU2Qa6t7RXLevBlYCUW\nUyDEW6EWS88Sq0xWl357kiDXIWhUJX8JROHLbrVauTxilmWh0WigVCpr/AchdE3L5XLY7XZERUWF\n7Jw1fc21FXdC7Wl+WliKUrKcgoere+jLwMrfBTn45xGeg38uKtR0u91u57wyMpkMFosFxcXFaNmy\n5W35TkiCXAfgV9WiQiz80VitVlRVVXHr+/orxK6in/3F1RyxwWCoUSvlduwMQo27+WmLxQKz2QyZ\nTMYNHCO9Illtegf8+a14I9T8eAJ/i53w/+Wfw263czEr9P04deoUHn30UVy4cMHn66kNSIJ8G0OD\nnkwmk8vC9EIh1mq1DrWofSVYguwpWCvYwu8O/sid3sfa5rKMZPidPn8QGMmBZLXx+QfrnvCFmh/5\nHeyqZBT+IK6iogKxsbG1ajDkC5Ig34bQHwKdt9Pr9YiNjXUK8hAuNxiIEAcDahlFSkEPek6DwcBF\nqQqDVNwNdiQCI9SBZHWJcGU+BLN8KL8YEUWn0yEuLi7k11JThL6Cg0TYoKvQmEwmroMSLqBusVhQ\nXl6OiooKEEIQHR2N2NjYoM0T+2O50nZVVFQ4tcvVICHUFrLFYkFlZSXXPq1WC7VaDY1G47Balc1m\n41az0uv10Ov1XJ62xWLhyldKuMfbe8S3zOjKYRqNBlqtlns2UVFRYFnW47OhC6P4S20T+JpqLxVq\nhUIBpVIJtVoNrVbL/aaUSiX3e7JardwzoylaJpMJR48exdq1a3H16lXExsYG3KalS5ciLS0NarUa\nGRkZOHbsmNv9N2zYgPbt20OtViM9PR07duxw+Fyv12Pq1Klo0qQJNBoNOnbsiHfeecfndkkWci2H\nXwKPWnHAXwn7tMOhlrLNZqtxy5MSaRYxUN0hGAwGWK1WzqOg0Wggl8u5QDe63Wq1Qq1WcznR0qpM\nNUcggWRC68xTIFltHGBFYps9WdQWi4UzLLZv344333yT+17btm3RsWNHdOzYEcOGDUNWVpbX512/\nfj1mzJiBd999F71798abb76JnJwcXLhwAYmJiU77FxQUYMKECZg/fz5yc3Oxdu1ajBkzBidPnkSH\nDh0AAE899RT27duHtWvXolmzZti5cyemTJmCxo0bY9SoUd7fEx8eVOQ90TqMUIgJIVxnxJ+DM5lM\n3MICcrmcK3EZKiEoLy8Hy7KIjo5223ahEKvVap/aZTQaYTAYUK9evaC0mz+XTtsjk8mg0+kQHR3t\nIMh0f6PRCI1G4yQC/OsUljukbjhKqF2rBoMBLMtCpVIF7ZihgMY6aLXasAxSxIRa6M1wN9ep1+uh\nVCo5V3qkU1veAz5msxlms5nrS27duoU33ngDP/zwAzp16oQff/wRP/74IyZPnox58+Z5fdyMjAz0\n6dMHixYtAlD9LjRp0gTTpk3D008/7bT/uHHjYDAYsHnzZm5bZmYmunXrhmXLlgEAOnfujHHjxmH2\n7NncPj179sTIkSPx0ksv0U0eX2zJQq5l8KMb+ULMH9ETQmA2m2E0GjmrWaVScdZcKHHnSo5Ui9hV\nUJtQPPl4016G8a7cob+BLxL+48k64w+kXJWitNlsDhkL0vMJLsLypAkJCTCZTOjXrx9f5Jyejzss\nFguOHz+O5557jtvGMAyGDh2KgoIC0e8UFBRgxowZDttycnKwadMm7u++ffti8+bNeOCBB9CoUSPs\n3bsXFy9eRE5OjtdtAyRBrjX4IsRVVVWw2+2Qy+WIiYnhqlnVVIcRSiH2t6ZwsKPLvSUQ12pdcHvX\n9LWICbVwEEUHuVar1UEMIjmQrDbXXOdTXl6ONm3aOGwTDnrdUVJSApvNhuTkZIftycnJ+Omnn0S/\nU1hYKLp/YWEh9/eSJUvwyCOPIDU1FXK5HDKZDCtXrkS/fv28bhsgCXLEQzsCd2sRC4VYoVBwblb+\nPuGAb1mGUoj9/T6/AlkwhDhY9zVQi00oBrWt843EOU6KcBBlt9thMBigVCohk8l8qkhWW59PTSD2\nToQqytrXAYtw/8WLF+Po0aPYunUrmjZtigMHDmDKlClo1KgRBg8e7PVxJUGOULwVYpPJBKPR6FKI\ngfDm7NJ2Rdp6xEIh9qbwCd/zUFN4Y7G5q6BEB0c2m00SgiDDF1g+oQgkC5TaaCGLtbmiogLx8fF+\nHzMxMREymQxFRUUO24uLi52sYEpKSorb/Y1GI2bPno1NmzZh+PDhAIBOnTrh5MmTWLBggSTItRlf\nhLiqqgqEEC79w5XrJlyCTIUiHIs+8MXS3bGFNbkjpRRoIPji9gb+WjITqBtu71Dj6bcUSD6u9Hwc\n4V83ISRgC1mhUKBHjx7Ys2cPRo8ezR13z549mDZtmuh3MjMznT7ftWsXMjMzAYArGiR8RtR74guS\nIEcIQiEG4NTpEkJgNBphNBo5IabRwN4cP5Rt57umgfAs+uAO4XKRt4MQe0JMCAwGAxiGQVRUlNcV\nr/hF/SWCRzCmJfwRavrbr23PU2ywXV5eHrDLevr06Zg8eTJ69OjBpT0ZDAbk5eUBACZNmoTU1FTM\nnTsXAPDkk09i4MCBWLhwIXJzc7Fu3TocP34cK1euBADExMRg4MCBmDlzJlQqFZo1a4Z9+/Zh9erV\neOutt3xqmyTINQy1KN2tvCQUYqVSCZVK5ZUQ0+OFqu3COWKFQgGr1RrSRR8A1+5kag3y120OdLlI\nscFMberc/K14Jc1/uidY98HfaQkgsgPJAsWVICckJAR03LFjx6KkpAQvvPACioqK0LVrV+zcuRNJ\nSUkAgGvXrjl4GzMzM7Fu3TrMnj0bs2fPRuvWrbFp0yYuBxmozm2eNWsWJk6ciJs3b6JZs2Z49dVX\n8cgjj/jUNikPuYbwRohpcXV/hZjiTW6wr213lUdMBw6B/mg8QSt7xcXFca4hvhCrVKqgrNt88+ZN\naDQaREVFOeQh08Aebz0UNYWv+aeB5OcGcq/NZjMsFgu0Wq3fxwgX3uSghwpXQs13jQoHUgzDwGg0\nup3WikQqKysRFRXFDe7tdjvq16+PP/74gxPPWoaUhxxpeCvEVNgAcOXm/P3xB2sOmR+sFSkVv2h5\nRKPRGDSL2BX0Pgq9F7cT3s5/0neYj1CkfUm1u93uY6gIJG2OlgwVTktEokUt5manlQZv51rWkiCH\nCSrEtJa0SqVymtMUCjG18oIxCg+kw/NFiMMd0U3rTQfzXrmiNkaqBotAo71vR7d3JF2Du4EUrQ/N\nrzLHT82qLYFkOp0OMTExtcrK95Xb98oiBL5FbLfbHfJ06Qvvyt0aLHHxVyTFhJj+IFz9WL2NfvYX\n4aAlKioqpK7DcA8wahPurDVh2VCxtB/+3Cf9Tm2gtrQTcAwMjYqK4gQ71IFkgSJmIet0utt66UVA\nEuSQwa8zTYWY/0LTDosfCUxXPgm2uPgqKkIhphW/3AlxqBGLMDebzSG5XxKB4a1bVcztTee8/XF7\nS4gjJm6BBJIJg8hC6fEQCvLt7K4GJEEOOvzylkIh5kMra4V63hPwXpCDIcTBtpDFIszVajVXnSxc\niLnmJXzDnQiYTCbY7XaumEltcHvX9Pl9xVN7PXk8wlmRTKy/Ki8vlyxkCe+gnQitMy0mxLRIBbWO\nQy3EFE+CXBssYmFgG788ZyihUwwGg4ErLsK32mqT+zIS4YsAIYSLBueLAD93WqzalbBkaKjf2dr2\nzANtbyCBZHyh9iWQzJXLWrKQJdzijRDTNAn+ero0VagmCYUQBypUwipk/qZ6BQPa4dCF0uVyOTcV\nQa+PH7ka6UExkYzwfeGLgLAmu1AEhJ4SMUtNmtYIPt5G5NM+0p9AMv7fwSgKEulIguwnfCGmiAkx\nf0UhWi2KRgaHC6GFHEqL2F9BpkJM63J7qkIWSguVb50D4KLKqRuVbzXTe+YqDeh2LdpQU0RCtHdt\ni7YPd6UuT0LtTSAZbTO/7XVBkKVhow/QF8psNsNkMnFiLLSKrVYrKioqUF5eDpvNBq1Wi7i4OM49\nHe7IXX40t9lsRnl5OSorK8EwDGJiYhATE1NjucRU/HQ6HSdwcXFxiI6ODrtVTNtSVlaGqqoqbhUo\nuVzuZGHReyWTyaBUKqHRaKDVaqHRaKBSqRAVFQWWZbmUk6qqKuj1euj1eq62Nr9euYT/8C1pWtdd\n+Dyole3qeZhMptv6eUTCAIIKtatnRH8zVLSB6iC/F198EcOHD8fx48dx5coVHD58GDqdzu92LF26\nFGlpaVCr1cjIyMCxY8fc7r9hwwa0b98earUa6enp2LFjh8PnYgNvlmXxxhtv+Nw2yUL2AjoC57um\naQfNf9H5KxyxrOul/WoqlaaioiLkc8TeWq40KIsuGelLXW7hcQLFXVt8Wfzcl7k2d25WqZZ0cPDF\n7e2rS7U2PZtIHmC4+s0YjUZYrVaoVCq0bt0av/zyC06fPo2rV6/im2++AQA0adIE8+bNw4QJE7w+\n3/r16zFjxgy8++67XB3rnJwcXLhwAYmJiU77FxQUYMKECZg/fz5yc3Oxdu1ajBkzBidPnuRKZ/LX\nRQaA7du34//+7/9wzz33+Ho7pNKZ7uC7WFwJsbsykq5+tDRAKJBlxLxtv8VigcFggN1uh0wmg0aj\nCWmwls1m4xL4ad1kYZuEazer1Wq/kv1pWUtvy0J6aovYoECn00Eul0Oj0XAiSu9dZWUllEql6HV6\nc25fSyD6s0Sfr6UzawoavFeTcRViz0K4Wg9/BR9aKyDSxZl68zQaTU03xWvE2vzAAw+gX79+GDJk\nCM6cOYMffvgBo0eP5lZd8oaMjAz06dMHixYtAlD9O2zSpAmmTZuGp59+2mn/cePGwWAwYPPmzdy2\nzMxMdOvWDcuWLRM9x5gxY6DX67Fr1y7hR1LpTH+gHaVwCUR+Z0jFjo7kfCkjGWoLWaygBwBotdqQ\nV7lxZSEL2+Rq7eZwEAltCSRyVWi5Sbm6wUEs+Es4cKIDcwDckpbBGDiFkki2kF3hKu0pKSkJXbp0\nQZcuXXw+psViwfHjx/Hcc89x2xiGwdChQ1FQUCD6nYKCAsyYMcNhW05ODjZt2iS6f3FxMbZv346P\nP/7Y5/YBkiA74EqI+T9SsYAoX+s5h0qQXQVrAdXu6nAgFGQx8QvWwMCfgidWqxUGg8Hh/rizcL1J\nGQsm7gJi+MEw3gYt1RYiVTTEBk408FCpVPo0cKrJ6PtIGRx4i1jgXKBBXSUlJbDZbEhOTnbYnpyc\njJ9++kn0O4WFhaL7C93UlI8++gixsbG48847/WqjJMjwX4j9nYcNRfEMsbZRoaEBEuHs9PjuYG/F\nL5Tw5/dpCdCaaos/0OAyPt7k6tL9+Cl3kWS91Ubo79afgRMQ/uj7SB3seIJ/Twgh0Ol0IZnm87Uf\ndrf/hx9+iIkTJ/q9/GydFmShEANwGg0L5xmDISzBEmRPQiy2f7igVkQohdgbC5mfehbo6lQ1FYzn\nCm+ClkwmE/cO85FSskKDp4GTNwU0gv1M+LEvtYVQWMiJiYmQyWQoKipy2F5cXOxkBVNSUlK83v/g\nwYO4cOECNmzY4Hcb66Qg01Gs1WqFXq+H3W5HTEyM04hMGHwUrHnGYBTP8EWIw9XR0jZRarLal81m\ng8Fg4HLAXUW8e0MkibA38K03ev1KpdJrUQh35avaiC/3JJjxAnXlmbgS5EAsZIVCgR49emDPnj0Y\nPXo0d549e/Zg2rRpot/JzMx0+nzXrl2igWTvv/8+evTogU6dOvndxjopyAC4FAdq9fBFkl+gIpQB\nP/4Uz/BFiCmhLKIBOLuDgeqVZULtEhazWGl5UuqiDUSI6Tn8+SzSCEZKllCoQ9HG2kCwppqCUUDD\nm2dS2wqZAM5ttlgsqKysREJCQkDHnT59OiZPnowePXpwaU8GgwF5eXkAgEmTJiE1NRVz584FADz5\n5JMYOHAgFi5ciNzcXKxbtw7Hjx/HypUrHY5bXl6OjRs34s033wyofXVSkGnnxC/SIVYpil9QINjn\nB7wXSH+FWOw4wUQoxNQdHEjSvr/Y7Y5LWNKqaLWtIwo3YqLgT+WrSIssrs0E65nUtsA+ilg/VVFR\nwaUfBsLYsWNRUlKCF154AUVFRejatSt27tyJpKQkAMC1a9cc+vzMzEysW7cOs2fPxuzZs9G6dWts\n2rSJy0GmrF+/HkB1mlQg1Nk8ZLPZDEIIDAYDjEYjJ8z+FqjwBU+5uhQxIaY5zr5y69YtqFSqoOR5\nCudlhXnXZWVl3DrFoUSn03EWAn2GdC3pYAkDjU6Pjo6GxWJxGLnr9XrI5XIolcqgnCsUBDMP2VXe\ndDBSsmpLvjRQ3VZaoa2m8eaZAODiDGqD25sQAr1e75Dj/+uvv2LIkCEoLi6ulYOMP5HykF1htzsu\ndE8LVISjXKMnCzlYFnGwEdbmrslKZPy8UACcEAf7x8owjFNxiLpKsFOyIlUQPBFJMQWe3N6eAvsi\nsTocvb/8ttSFpReBOirIhBCuzrRcLofVaoVGownbyMvb4hnBFOJARNJbIQ4HhDguy8iyLGJjY8P2\n7GrjfFyo8Tcliy8IdH/p/gYHKtQsy8JkMiEqKopbrSxci3AE4xooOp1OEuTbFYZhEB0dDYapXqWn\noqIirKNeT8UzQmER+yPI/gZIhcJCpnP8/GUZbTabaKCSRM3jTUoWX6iB6vdNr9eLFuqPtI440trj\nDbUl2ttVla7bfaUnoI4KMlDtoubXqg23G4q6QsNVPMMXkRQKsa8BUsEUZLFgOzq1EI7qY/Ra+NHH\nkeTeq23wXaz0PaexHNR1GukpWZHksvaEmPtXiDdub+HgiRIKt7dYm8vKyiRBvp2hDzvUKUFi0HNR\noYmUOWK+ENd0pLIwD1ws2C4c87u0UyovLxd9R6iLtaZFojbDt9z4FY4iKSWrLuJq8BQut7dwDlkS\n5DpAOAWZ75qmHXm4hNid1Wqz2WA0GoOWMhSIUArd9zW1CAW1zKkAKJVKyGQy7h66C5apDS7XSEPs\n3YzElCxvLM5IItjtDcTtzZ/XdjeAFXsXdDqdJMi3M+G0kMXmiIUjz1AjJpLC3F21Wh3UlCFfIMR5\n4YfY2Fi3QhyquWq+ZU47Ho1GA4vFwm1zVwWLVoHzNAcnzX37TjDnQaVVsoKHN25v/m+Dj/C58MsY\nU8rLywMuClIbqPM9QigFmXbu5eXlqKys5CxiGhUc7kAyvnWn1+tRVlYGs9kMtVqN+Ph4qNXqoFUg\n8uXaLBYLKioqUFFR4XCPwmkV858VDSyKjY3lXKjuLCx+8BJ1rWu1Wmi1WqjVaiiVSq6jMZvNMBqN\nMBgM0Ov13IDIYrE4LO0n4RtUEBQKBZRKpcMzUKlUiIqKcnoGer3+tn8GNW3RC5+LRqOBVqvl1jEX\ney60imJVVRU2bNiAVatWobKyMuC6BkuXLkVaWhrUajUyMjJw7Ngxt/tv2LAB7du3h1qtRnp6Onbs\n2OG0z7lz53DHHXcgPj4e0dHR6NOnD65du+Z3G+u8hQzAYVQWDLyJmq6J/FZhIZRQWcTeCnIwF34I\nBH7FMaFlLnRH+4KnOThv0oEkSy4wgpGSJTbtUNueRyS1152Xg04V0foCX3zxBbZt28Z9b9WqVejc\nuTO6dOmC+++/Hy1btvTqnOvXr8eMGTPw7rvvciUzc3JycOHCBSQmJjrtX1BQgAkTJmD+/PnIzc3F\n2rVrMWbMGJw8eZKr0vXLL78gKysLDz/8MF5++WXExMTgxx9/DKi4TZ2t1GW327mRmE6ng1wuh1ar\nDeiY1MoyGo0eK2vp9XpYrdawzIvY7XZUVFSEvIgGxWAwwGw2uywEL1z4Qa1W+5XX7Ok8nhAOCDQa\njdNiGPxzUAuK3reqqiowDBPUKljCAhsUf+dFa0sFLL1eD4VC4feydYFQUVGBnTt34ubNmzAajejd\nuze6du3q9AyAvwbvcrkcCoUi4uMDLBYLTCYTtFptRLeTD82ooBZxeXk5Jk+ejJYtW0KpVOLMmTM4\nc+YMNm7ciOzsbK+OmZGRgT59+mDRokUAqn9vTZo0wbRp0/D000877T9u3DgYDAZs3ryZ25aZmYlu\n3bph2bJlAIDx48cjKioKq1at8vbSpEpd3hDoXKRQiBUKBTQaTUAL3wcDYTUyAIiPjw/53KWrawv2\nwg/+ImyHJ8s8HC5MdwFMwkUGJGs6ePzvf//DsqULYTRcROMUOex2O948+CW69fgbHn74UdSrV88p\nPgCoHszRudBISsm6HRAWh4mNjUVpaSlmzpyJnJwcbh9vsVgsOH78OJ577jluG8MwGDp0KAoKCkS/\nU1BQgBkzZjhsy8nJwaZNm7jzb9u2DU8//TSGDx+OkydPIi0tDbNmzcIdd9zhdduE1FlBFrqf/Ol0\n/RHiQM/pbbv41ayoW7qqqqpGAolCtfCDr/fQn3Z4clOGUqzdufa8LVVZWypg1cS87bfffot3lr+K\nrh0tmPpwFyTWV4EQgqPf38DK1Vsxd+4feOWV1x28SXa7HQaDgftNRXpKVk3PIfsLv72EEFRUVDgE\ndflyPSUlJbDZbE5rGCcnJ+Onn34S/U5hYaHo/oWFhQCq10SurKzE/Pnz8corr+C1117Djh07cNdd\nd2Hfvn3Iysryun186qwg8/F1PldMiLVarU9BSKGKEOYLMQ1uYVmWs5LD0THzi2lEQhQ331MQSDsi\nJdjH1byoqyhjWgErUmsX+8u5c+dw4MABREdHIzExEdnZ2V4v+HDx4kW8t3IhhmUzePzBdIesi4xe\nDdC4kQYz//M9Vixfhif/9ZRT8GcwUrL4zyCUz6G2PWOxPioUaU++9oX8/alejBkzhlsruUuXLjh8\n+DBWrFghCbKv+GMhC1Ni/BFisWMG+oNxJ8SUmvhRlpWV1WjwmJinIJRz5zWJq7QTvV7PCXikCESg\n6HQ6rF69Ct/u34T4JCMIkUF304Y93+7EM0/PRv369T1+f+Ebc9GqqQ4PT+omeq1NGkdj2sPN8drb\nX6Jtu/YYMWKEx3b5mpJFY1iA0E09RMog0heEfSIh1WsP+BsrkpiYCJlMhqKiIoftxcXFTlYwJSUl\nxe3+iYmJkMvlaN++vcM+7du3R35+vl/tBOqwIPPxpmMXCnGgxSqC9WMT1ndWqVSiK1bxR/ih6myp\nAFZVVQGA6MAgHIjdF3/bEY65/lBCBcJTBSxXAhFpFbDMZjNenfcyLv9+GHfmpaJPViMwDINrV8rx\n4eKjePqZJzHnxXlITU11eYz331sJm/k8nn4yHQqF63eib59kDP/xJj5b/yEGDBgArVbrlwvYXY5u\nOFbJioTn5iv8NtN4D38tZIVCgR49emDPnj0YPXo0gOp7v2fPHs66FZKZmen0+a5du5CZmckds1ev\nXk4u7wsXLqBZs2Z+tROo44JMO1tXnW4ohJh/bnoOf1ynfMHxZg3nUOdb89ujUChgsVhCLsbCeyh8\nXqFe27q2inWg7lZ/g5cIIThx4gS+/uZrsAyDzIy+6N27NxdN6+k4hBCsXPkuLl4+jCnPtkeTtFju\ns9RmsXjqP12xdN4pLHn7Tcx95TXR53727FkcPbID/3q0KerX8xx5ft9dLbA3/3/YvHkzxo8f79V1\neou7lCxfAvncPYfa9n7S6+dTXl4OjUYTUAT+9OnTMXnyZPTo0YNLezIYDMjLywMATJo0CampqZg7\ndy4A4Mknn8TAgQOxcOFC5ObmYt26dTh+/DhWrlzJHXPmzJkYN24csrKyMGjQIOzYsQNbt27F/v37\n/W5nnRZkCu1YXXXsoSjf6I9AUuETW2ghFOfztT3UQrfZbA7WVqgR5n2HqtxmbbQ0vMUXd6tY8JJY\nSUQ+lZWVePGl/+CHn/+H2CZRkClY7Fu8C82SW+HV/87zau53586d2LV3A8Y+1MRBjCnRsVG476E2\nWPbKEWzdutUp2pUQglWr3kObNDMG9kvx6r4kxCvx92EJ2LxtPYYPH46YmBjufoUCb56Dq4UexEq2\nhrKtoYTfZlrHOpDrGDt2LEpKSvDCCy+gqKgIXbt2xc6dO5GUlAQAuHbtmkN/kZmZiXXr1mH27NmY\nPXs2WrdujU2bNnE5yED1/PGKFSswd+5cPPnkk2jbti2++OILzor2hzqbhwyAK4VoNptRWVmJuLg4\nLjeVCrFarQ5JxSir1cotuu3p+MGw/Hw5nyc8tYdW3oqLiwuZdQpUL86h1+u5Na3d5X0Heo6EhASu\n7B/t6IT5kpFIsPKQqdVG19QVCrWwwhW1wmne7qvz5uLYxUP426O90bh1AzAMg7LiCmx+8wBa1euE\nWc88h4SEBJfPrqysDFOmPohOGQbcM6m96D6UTZ9ewPf7WLy54B00atSI275v3z4sX/pvvPrvlmjf\nxvv5yMpKCx6bfgJZgx7B/RMnRkxer/A5UKEW9ukMw3A505EeI8CPYqf91NGjRzF16lScO3cuYtvt\nJR4bf/tFtwRARUWFQ9nEmJiYkJVv9MZipRaoTqdzaFd0dLTPQhcMC5kKsbC8pLA9oXSPU6xWq0Pk\neHR0dESsmHW7ceDAATzz3LO4e8JYTMibiN27dwOAQ6lQlUrlVCqUBpGZTCYsW7YMh8/sx9CHe6BR\nq8Q/hcSO+KRo5D7RF+f/OI3FSxa5fV8+++wzWJk/MOIuz5WZRtzZEsrom/jss/XcNqvVivWfrkL/\nXlE+iTEAREcrMGJofezdu9Uhp7+moZa0u5KtFGHJVlqxL1LLhQbbQq4t1HlBNplMMBgMAKo7mVAL\nMUK1sFYAACAASURBVMWdaLkS4kDaFYhI8oWY1uQO130SYrPZUFlZifLyci71IDo6OiwFRupCh8Bn\n165d+O9b83DGehUxg5rB0kaLV95+Ha/MfUW0pCi1ivl1i8+fP49dh3Yga2IXpLatdhMT8qdFZ7ch\nPjkG2Xld8d2ZAhw5cgRWq9XJyrt27Rq+2f0lhv49Bdpoz/OIUUoZBuSk4NDhb3Djxg0AwOHDh3Gz\n9CLuvTPNr3vxt0GNYTIWuiwkEUnwnwOdTnBVP5rGfgjreos9h3Agdr6ysjLExjpPUdyO1Ok55MrK\nSm49YrvdHjL3tBhiAhnKuVB/BVlY59kbKzQUFrJYUQ+WZVFZWRm0c3jCZrPBZrNFtMsPqK4+df78\neTRr1gypqamitXo9sXfvXixY/hbi+zRF+l39uOst7HoVu1btQ9NPm2LSpEluj2G1WrHq449Qr40a\n7TNbAAD+um3kz/8RNO/UCIltL2LNp58gPT2dS/mhLtbVqz+CNkGH/kNae93+PlmNsHvzcWzduhV5\neXnYtGkDeqUr0KxJtM/3AgAaJKnRo3MUdu/egb59+0b08+dD42IiMSXLVXsBZwvZ35Sn2kadFmRa\nQ5llWZSVlYV1NMgXLaEQeyt8oYQuhWi1Wv1e+CEY99NdUY9wBI7R662srOTORwcFwF/LRkbC3JzV\nasWaNWuw+osN0MsIWLMV9dXReHn2v9G1a1evj1NaWorF7y6FtluKgxgDQEqHpigb1hnrNn2GjIwM\ntGnTxuVx9uzZg4vXzuGOWf1FPmX+/B8DhiHIvLMztsw/jO+++w6DBg3i5kMvXbqEo99/i3seagSG\nJX8OiKq/B4Y+H+d7rlTJkZFdH7v2bEabNm1w7eppPD6xudf3QIxhgxvilTdP4dKlS+jcuXNAx4oU\nXKVkCUU6VClZ7tpF0el0dcZCrtMua4VC4bCYQE3Mo9BgK+HyjMEWY2+v0Wq1oqKignMJR0dHc8sQ\nevtjC1aOdVVVFXQ6HYxGI1QqFeLi4hyWiAz1c6ODAaD6vqhUKiiVSm6OlCKcm/N1KT+r1YozZ86g\npKTE77YSQjD/9dfwzhefImZwD/Sa9Qg6z8jDrXoqvPzaPPz2229eH+uTNZ/gFvRIH9NP9Fm2yU6H\nLUWJt95e7HI1LIPBgLXrP0Gz3olIauJ5HdukJglo0r0+1m1Y45A7vnfvXsTUM6J7RiOwDAuGAQgB\n7OSvQCabzQo7F9BE3awEA/7WFEZrEZa+vRhtWxB0aBeYldWjayIS6xmxf/++gI4TTvytOyCMEeAv\nm8h//61Wq4Pbm85Nm81mv9zeYvvSOeS6QJ0WZEq4BZlaxEB1sAUV4lBbxe7yZvlzszabDVqtFnFx\ncX7NzQY6X200GlFWVoaqqipERUUhPj6ec1GHAxrpWVZWxlkFdFDCsiw3R0o7JeHcnKdOit4Xm82G\n9957D+MnT8aUZ5/Bw1On4ttvv/Xrvh0+fBg7Cw6i2T3D0LRfDzAMA2WMFh3G/x1/KGx44eU5qKio\n8HicixcvYvu+b9B6ZDco1OLztayMRffxA/Hj1Z/w7bffiu6zZ88eFFZcQ8boLl5fQ6/cTrhecpVb\np1an02Hfwe3oO7gBFAoZGJYFy8o4i+6vymLV7wWdm7bbq6cW1FoZ2nSS48ezxzB6ZMNqqzoAZDIW\n2X0TcOy7fU4pR3UBahWLrTkdrHW/xVzWFRUVdcZlXacF2Z/ymYFCU4Jo56hQKDghDkdQkvAaaZ1j\nnU4Hi8UCjUaDuLi4oCz+4Av8QDaDwQCFQoG4uDhotVqXQhzsgRQdDPCt8uhoxznHiooKnD9/nrMM\nhZGuYhHHwk6KBtCsWbMG73++EZXNm6LF2HtQ0bABXnxjAd55912f2q3X67Hs/ZWQt2mCpPaOUcgK\ntRLt7x+N88W/Y+vWrR6v/4OPPoQ9KQrN+7Rzu29sSj3EdWyITds2O91/u92OLds3o2n3RMTU835J\n03oN41CvhQa7dn8DoDqozEpKkZndWGTvalc1w/zpLpXJIJPJ/xRpGWdNN2ujgExRhXpxUbDZrNWu\ncGpN2+3V5rYPr0+/Pskw6Itw5swZ779UQ/hTVcwf+EFkQmuaDlQBZ2tar9c7WdN2u92pvWVlZZKF\nXNdgGN8WmPAVi8WC8vJyVFRUcGk63q5pG0zoj9Rut3NCbDaboVarER8fH5Sa074IpbepVKFEOBjg\nW+X8e/Hbb7/hXzP+Hx771wzcM34CXnt9gcs0GHedlFKpxLlz57Bqw2eo16sn0rL6QZvcAG1yhiGh\nf1+s37IZp06d8trlvXbtWvx6qxitRgwU/VwVF4P4nh2wYfNXKC8vd3mcixcv4vuzJ9EutycYL7wR\nrQZ2xk+//YITJ044bD9+/DiuFv2K9EFtPR5DSPt+aTj2v6O4du0adnz9Fbr3jfEqsvov/gxgYlmA\nAAmJRjRuFoWCYyUOc5w0mIm6vKuF2v6Xi9XFbW/WNBqpKXYcPnzY52urS3iTkkWDafnWNPUgGY1G\n7Nq1C4cPH4bBYAjYQl66dCnS0tKgVquRkZHBeWFcsWHDBrRv3x5qtRrp6enYsWOHw+cPPPCA0/z5\nyJEjA2ojIAkyB12qLtjQOVm+EPPdn+EOJCOEcO5YvhDz52bDBfUW8OfPg5VKZbPZcO7cOWzZsgVb\ntmzh1rHlQ6cO+IMBV1b5+fPnMf3pZ/DLrUqk5YyBok1XbD+Yj48//tjrNtFOymQy4c2334alQRLS\nsvpxVh3DsmjcrRvM9RKwYuVKLi9ezJKglJaW4osd29BgQA+o4mJcnrtZVk/8UVWBLVu2uNxnx9c7\nYI+XI6V9U6+up35aCuSNo7Flm+Mxt+/YjrimSiQ3d7/IgxitejSFXWnChx9+iJKyK8j6m3dtEePm\nrZsAY0bf7DjsK7gOOwHPmq62qFlZ9X1nwICAgNjtsDuINK/YBiFgAPTrk4Dvj+0LazU6fwiXhewL\nYqlxfGuav8zlv//9bwwfPhzbtm3DM888gzFjxuCFF17Axo0bodPpvD7n+vXrMWPGDMyZMwcnT55E\neno6cnJyXMZsFBQUYMKECXj44Ydx6tQpjBkzBmPGjMHZs2cd9hsxYgSKiopQWFiIwsJCrFu3zv8b\n8yd1WpBD6bLmB0fROVlhcFQ4ayHTaG46GhULkgom7q5NbJBy9epVXL9+3edzAM6WOCEECxa8gYen\nPIn/vr4EcxcsxtKlSx3247eBPxgQs8qtVivmL3gDhVYW3caMR73GTdG8Wy807ZONr3Z84/PqLnv2\n7MGvxcVoNyq3+hoYBgz7Z51ouQyth/0Npy/9ioMHD7q0JOi83Ndff41bdhMa9ujs1vUapdUgoVcH\nbNy6WbQz0+l02HNoH1Iz2/oUvNdiQCcUnDqGK1euAACuX7+OY/87gk7ZrXy6J0C1E1oRJUfznsnY\nsWsrGqcxSGnkX5oSQHDjRjHiY1n0yYpDSZkB//vhptMJuWhhGesg0k7W9J8pb4QQ9OudBH3FHzh+\n/HhEFtWobfCtaSrYGo0G+/btw4EDB9C7d29kZ2ejqqoKK1euxL333ovff//d6+O/+eabePTRRzFp\n0iS0a9cOK1asgEajwQcffCC6/6JFizBixAhMnz4dbdu2xZw5c9C9e3e8/fbbDvsplUokJSWhQYMG\naNCgQVDc6nVakPkESxzFhNjVnGw4BJlGK5eVlcFut4NlWb+DpEpLS5Gfn++VZeBqvloYOBYVFYX3\n338fTzwxA48/Pg1btmwJ+J4cOnQIW7/ejSadszHg7qlo0f1vWLdxC1auXAmr1epQWMRThS+GYXDo\n0CH8dOkK2mXnQKH8qwRlo/adIW/UDG8ueRulpaVetc1qteLLrVuhadMKyhhxsYlJSYa2Q3t8/Omn\nsNlsopYELRe69Zuvoe3QEmyUAtY/RcNms8NuJ/gz2Jijaf+eKDRUYO/evU7n/Pbbb6Gz6T3OHQtJ\nTW8Bs4pg3759AFBdyUtjRqsePli2gsfdpndT3NQXI7Wp2qe28DHoDagylCMpUYUmzZSon8Li4OFC\nz1/8U6QZlhVY0zKwMhnAMGjSJAZNGtmRn3/IqaiGv9HFoSASLWRvoO1VqVRIT0/H77//jmeeeQY7\nd+7EH3/8gaKiIrfpdnwsFguOHz+OIUOGOBx/6NChLou8FBQUYOjQoQ7bcnJynPbft28fkpOT0a5d\nO0yZMgU3bwoGfH5QpwU5mBayqyhlT8FRwf7RHjx4EC/NeQmffPIJjh8/7hCtLJfLHYrO+4LBYMDz\ns/+NZ2f8G3mTHsBXX33lddv589X8wDGFQoFnnpmF1R9/gcapGVCqmmP+/EV46623vDqumIVcVlaG\nxW8vg7JeUzRtkw5WJkNqy45omj4Qq9Z8hr1798JisXgdRW61WrHhiy+hSk1DbGIDp/O3GzgMf5Tr\nneaYXPHdd9/h5+vX0KRXT7f7Ncvog+u3buLIkSMO56OWhFKpxA8//IDfbt5As77dIeOeKwPgr/lR\nAlqH2g65Wg1Vq1Ts3rfXwe1tt9uxded21OuSCqXWt5rXrFyGxC6p2Je/H1arFd/u3420Xg0hV/g/\n/89q7YhuEAWz2XmawVtKSkugUNgQF1v9fDt11+C7U0Ww2fyME6HFNVB9hzN71cMPZ75DVFSUQ8S9\nWIlKX9Pg6jKu0p4SEv5KnWvQoIHX8SUlJSWw2WxO6x4nJyejsFB8gFZYWOhx/xEjRmD16tX49ttv\n8dprr2H//v0YOXJkwM+3TgsyH38FmQqxTqeD1Wr1KUo52CPXiooKLFq4GDvW7MKyee9gxrT/h8uX\nL3uMVvaE3W7HggULcPr7C+jcdDAqC6Ow8LUlOHDggMvv0CA5sflqGjh29OhRnDj5A7r3GIOWrboh\nvetgtGiZhU2bvsb58+f9auvq1avxW5EOnTKG/bmFwGa3oXGLjmC0idi6bbtPUeQHDhzAxavX0KJX\nP9HP5VFKJLRqjy07vobJZPJ4vK+2bAGbkoyY5AZu91PHx0HWMAU7d+1yuc/WHdvBNk5CdEriny5v\nBrI/Xa/yP606ftkMu92OpC5t8cPPF3Du3DkuFeXUqVO4VHgVaX07emy/GKndWuHqjd+xZcsWFJX9\njnYZ/pWnrIagtLQELXvXx5nTJbDb/Uids9tx62YJEuspuIvv1C0aZRVVOH/B+7lHd/TsngSDvhg/\n//yzUxqQpzQ4sZiAUAh1bbSQhXnTNpstJGlPvuZnC/cfO3YsRo0ahY4dO2L06NHYunUrvvvuO85T\n5C91XpD9nc/lCzHf6vMlSjmYLmtCCD755BNcu/A7+rUYjCEtckHKZVj/6XqHZdj8Od9XX32FnVv3\nolvLwWiU1By9OgyGlm2A1as+Fs3HpBGs7uarCSHYsOFzKJVJSEz8K62leVoX2IkGa30IkKDXZDAY\nsHP3XjRq3R1KtQZ2e/UykHabDSwrQ8tOGTh55qzTouLujrvxyy+hatwMMfWTXO7XpFM3XC8p9TiX\n/PPPP+P7M2fQyIN1TEnpmo5jZ06Lzq0XFhbi6OmTSOnlomIU82eZSgYAUy3UcpkMSW1bwKSS4+jR\nowCqPQAHDhwAiVMgLrW+k8vbm9clsUVD2LUyfP75RmiS5V4VAnFFZWUljKZKtMtIxi2dCZd/LvP5\nGGU6HWw2o8N6x81aqKCNZ3D0eLHfbfv/7L15cBv3fQf62RO7i5MgwFP3LfnQ4cSN0vMlbt00M41n\nXGcy7ozr9tXj1M0kM86M00ln0vi//mOnzthtqrbpe55O/dy8OvX0cJxUTmzLpmSLokhKFCmKFEnx\nPnCfe/3eH4tdLIAFsAApO37iR4OJAyx3F8BiP7/v9fmUQeHQ/gBCARmDg4OVr7gYg6vXE3C7oulP\nEiEDtTPIFEXVjB+6RSQSAcMwWFlZqXh+dXW1Jgo20dPT09L2ALB3715EIhHcuHGjrfM0cccTsgmT\nrJr9CJzmdtsdF3J7zEYwG7WuXr2KH/3r/4s9/oPwiT6wHIej3ffi/V+ct24a7RAyIQT/819voFPc\njZ5IuS54175fwfjVqQphCLuoByGkYb16bGwMg5dGsP9AJTlRFIWDB38F775zHtevX294btWf98DA\nADYSafTtOwJFNbpkKZoGy3JgGAbdOw9AY7x47cc/dvXeZ2dnMX5jGn1HGsskSqEOeLp34D//+38a\nfr4DAwPIswwi+/e5On704AFkKcpRfOP8+fPIQq+ZO24ICmBYBoG79+Otc+9a6daBwQvoObm3lAas\nTHkblpNlktZJLVFTFIXIPTvx4cgl7L+vv30CoIBYLAaWI9hzdxicn8PIxdYJdGNjHV4JEIRKB7Ij\nxwUMXFze3O/Ntr9PnfBi8KK7hr5m3cVm6WQro+lPYnq8+pxNy9h2s3scx+G+++7D2bNnK45x9uxZ\nfPazn3X8m9OnT1dsDxgz8Y18jufn57GxsYHe3t62ztPEHU/I1TKM9XA75nY3u3K1jw39z//8D+S4\nhsO9x6wZ0p5AH/iChH/+p3+2Bu5b/ZFOT0/jxuQMdvVUNlGE/BF0eHbg5f/rX1AsFmtEPViWtZSU\nnPDaaz8GIV709NSSU/+OQ9A0Ea+88v80PT/7e/rfs2fB+aPgBS8oUGBZFizDVnzHu458Cmd//i7m\n5+eb7ntgYAB5QiG8Y0+dg5f/c8c9pzA8Nl53EUEIwS/OnYNv/15XM74AQLMsAkcO442z/1uTiXj7\nvXMQ9u8Aw7eu7NZ74hjm1pcxOjqK4eFhrKY3sPPUgYqUt10Ji6aNN6rrOnStTNSm3rSuE/j3R1Cg\nZASi7oVAqkEIQSy2jkCHIZKz43gYlz5caemaVRQZqeQGIp2emtfuOenH4moGs7e2xpDk/lNRLC1O\nttTxa0e7s7qtKF99kuCUYjednjZzr3z66adx5swZvPzyyxgfH8dXv/pV5HI5PP744wCAxx57DN/+\n9ret7b/xjW/gjTfewPPPP4+JiQl897vfxeDgIL72ta8BMIR4nnnmGVy4cAGzs7M4e/YsHnroIRw6\ndAgPPvhg2+cJbBOyBfMLrxYHMYn4dszttqs0Zepfm2NDXq8Xo5dH0SX2gqYro4K7eo9j+IMRnDt3\nrq1zPHfuHNQC0BXeUfPaXfvvx/TkLbz++us1oh6NPpt0Oo133nkfu3cfd9yOomgcOPgr+MXb71vj\nNI2g6zpmZmbw/oWL6N17DAzLlkYoai/v/v13Ia/S+MlPftJwn4QQ/Pztd+DbsQc0w4A0kXPq3LUX\nMi/UlZK8efMmphcW0HWktS7mvuP34NbaWoUy1MrKCkYnx9F1t3v3Izv8/d3QAhIGBgbw3vvvgYlI\nCPaGK7YpTWOBNsexbERNM+UGMl03omlVoCD2+rE4tQ5d1yo0pZvB3CKVSkHVigh2GGS672QEqxs5\nLMw2l/w0EYvFQFEqwh21hHzwqAjGo+PDS2uu9+eI0iV7711hcGyuJm29WbiJpgF3OtLm/j4JqOf0\ntNlxoi9/+ct47rnn8J3vfAcnT57EyMgI3nzzTUSjRhlqfn6+omHr9OnTeOWVV3DmzBmcOHECr732\nGl5//XUcO3YMAMAwDEZGRvClL30Jhw8fxhNPPIFPf/rTeOeddzYtfXzHE7L55ZuRnF3J6nYLaLRK\nyPaRKrvIyPr6OuZnF9EV6Kn5m7A3Ao/ixdtvv91yhEwIwc/fehsR305H2zaR98PHRvHeufdqRD0a\nHevy5cvIZovo7a2fbu3fcQjFImmoiGRGBsViEe+++y7yMsHO/cdAOxCxCYZh0dF/AG+/c67hZzE3\nN4eJ6ZvoOXC07jZ2UBSF0O4DODdw3lHx7cKFCygwNEK7drranwlvNApdknDx4kXrufPnzyNLNHQe\nbq95iqIo+A/txrkPL+AXA++i5+QeV9e0RdJUuYGMZY0FYDqbQvR4P6ZHFyySNjWlNU2FrtsENuBM\n1LFYDLyHQBCMa6hnfwAUT+PaqHvTjY2NdXQEGTBM7fvhOBoH7xIwOLxJQi5BEFjce9SDoUuNVZ+2\nAm6i6WqJVnM88ZMWTduvxWQyiWAwuOl77lNPPYWZmRnk83kMDAzgU58ql8reeuutmpnkhx9+GOPj\n48jn8xgZGamIfAVBwE9+8hMsLy+jUChgenoaf/d3f2cR/GZwxxOyCXuEbBLx7RbQcEvITiNVdpGR\n0dFRFDJFRPx1mhT8/Th/7oIl8+j2Bzk5OYmZqTns7ClHYqbdoKoqAAh2dB3A1dFxR0nGescZGhoC\nzwchSvWVpWiaQTC0C++8UxvZ28sHAMCyLAYvDcHftRss13xsp2fXIczOL2FqaqruNu+//z5yOtC5\nc0/T/Zno2ncQi2vrmJycrHieEIK333sP0p7dxixrC6AoCr59e/DehQvW5/nu++9B2N8Plm9FUrIS\nkcP7MDk7g6X1Few82bqIhx2JZAIaUdF7Yic21jJIr+camD9oNSlvQnRomo54YgOBjvJ7Ylga3YeD\nuDrijpDz+RwK+TQ6w7XRsYnDd0sYm4whk9kala2Tx8MYH79UV0L1dqORRKt9NMit4cnHiTvd6QnY\nJmQL5sWQyWQsIr7dLkPNCNneQNZopOry5WFIxAuOcU6X9HfsQmItieHh4YbHq8aFCxegFml0dfQb\ns6wlIiaEgGGMtPCO7n3IZWSra7f6vVWDEILz5y+iI9w8UtzRfwjjE1NWl7EpcpJMJlEsFq1FUqFQ\nwNVrE4j2u2uW6uzZCVmnK2Z8q/HOuffg698NxibjSUr/6mVhQz19kGm2Rid3fn4ek7Mz6DrSurYz\nAEQOHMDs8jJmZmawtraG4YlriN7lThihHkJ7+pHWFRQpBf6uzY2UJOJxcBKLzsPd0BgaM1cWUWP+\nQFeZP9CmlaLR1JhKJaFpRQRCfKk8YDx2HOvAjck48rnmBBrbiIFlNAQC9RcqR+/2QtFVjFzdvIgD\nAJw6HoGmJnHlypUt2d9WwFIfKz2qo2lzHMvJ8MQeTX/U4iZOKes7yQsZ2CZk6yZvui+xLPuR2f3V\nI+TqBrJGI1WEEAxeuIiwVH+u1evxgVM9NaTZDFevjCHgiZbMyRXohJRW46xVQ+Q5AX4uivfeq0wt\n10tZz87OYnFxBd09zdOt3T17USwYQv5OloyiKIKmaYyNjSGTKyLau8fV+6JpBsHuvXXT1rFYDOM3\nphDde8CqF+q6DlVRy01Nqmalpk0zAoqm4duxF++8937FfgcHB5EDEN7r7vyqEdq1E0WawsWLF3Hp\n0iVkdAWdh9rblwmKZqD1hKBSm7vhapqGRCoBKSCA8bDw7enEzdFGEqglgQ2qbKVI0zTi8ThEiQLv\nYYBSFzchwM5jHShqOsZH1qxo2jnlTRCLrSHcwaJRIisc4RDtZXBpuE3v6arrpbdbRE+U4PLly+3t\n7zai+to2o2m3Hsf2cSwzmv4oUt7VNeQ7xXoR2CZkFAoF6yYPwFo9fhSoJuRmQhpOuHnzJtaW19Ed\naNxu3yX14f13Blynp2RZxsjwFQR9ndB1AoY2idgcjSmjL7oPH14YdCX4fvnyZRSLOiKR2iaxajAM\nC3+gH2fP/ryhJePVq1dBe3yQ/O5TWz27D2Nyesax23pkZATZoozwjt3QS8pORCdGM5P5sB3fTtKR\nPftxY2YWs7Oz1s3r0uXL4Ht7QbdpmkEzDIRdO/H+Bx9g8NIlcH1RcGJrilrVyGazYPs6USyqKKRz\nbe8nmUxB1RV4g8b5hI/2YGZiBUrRfUpY03SkUnEEOnhQFmEbD3+nB/5uEddGN2D6HVemvI0GslQq\nBUXJV8we18Ohu0UMjqxuCbFQFIWT93gxMtzaYvejghtxonoex3ZxEzOarpYKLRaLWyZusp2y3iZk\na47Y6/V+JNrSTtB13UrFtlq3vnr1KuScgrA30nC7/o5dWF/ewNjYWMP3aGYMxsbGkEpmEAn1gWPZ\nUu3T+Vz6u/Yhk8zjgw8+sJ6r91levHgRXl83GKYxOZm16p6e/bg2Pol8Pu9oyUhRFAaHLsPf6eSZ\nWx/Rvt3IK8QxbT0yMgLaHwLN8ZZLFMMwYGimTBil7mPrtVKk17lzD/K60YyWz+cRi8Xw4fBlBHft\nLHnwtua/a6Lz4AGMjl/DuQ8vIHRwd+s7qEIykYCwqxuEZ7E8Ntf2fuLxGDiBAcsb32fnkR4UFA23\nxlea/KXtXJIJ6ERBIORU+6XQf1cHrl7ZqIioTb9jQozfz8b6Ojy8DkliYMt4OwbTR+/xYjWWw9x8\ntrU3S8wzqsSp4xGsLE/XlWL8uLCZexlFURXiJmY0bR/HAoxoulrcxGwoazWarpey3ibkOwjmCtH8\n74+DkPP5fEUqtpV0+ezsLAR4wdCNm4WCYghUkcHg4KDjezS7lZPJJPL5PGZmZqApBJFQDxrmAAEI\nvAQv21nTEV19HFVVMXT5CqJd9QmFEAJVU6252/4dB6HIqOgytiMej2P65iwifXsanmM1GJaDP7IL\n596vFIyXZRnvf/ABvN2GwAXLuYxqKYCiKXA8D6l3F4aGRyCKIm7evIl0oYiOvXsMaz+9ZO2napYH\nr0HSjYm6c/8+xLI5LK4st91dbUcsEYcQDYDtiWDpavPRMifouo54MgEpWI5KpagPXFjCTMO0dSXi\n8ThELwWujv71zmMdiMULWJrPwKxLU3Q55U1RFJLJGDrDRoRtoIqRbf+5/6AImtNx2WWzWDPcc6wD\nLJPH0NDQluxvq9CqPGQzVI9j1ZMK1XW9RtzETTTtdL7bKes7GKb+8u2GXdEKMCIsM0pvNV0+fWMa\nItNcjIGiKESFHgycqxzLMZW+ksmkkcZkWQSDQczNzUFig00jWRO9nXtxYeCipefsdCOYnZ1FJp1D\nONxX8xoBKalCqQAxPhOWZcFxHkjebly65Hyzu3r1KrIFBZHe1qPG6I59uDo2gXQ6bWnmTk1NYX5p\nBdHd+yw7uFbRuWsvroyPo1Ao4Nq1a9AlEf6uaEVTk71cYR8PspM0sZE0JwhQ/T5k5CJ83Y2z8mjd\ndgAAIABJREFUIc1QKBSRLeTg8UsQ9/Zi8fp8WwvRVCoNVVcgBSrTxIGDXZgZdxctapqKZCoOf7B+\nI1bP/gAIS+H6mHMjVjKZhK7LRne1Jd5NVT1MEHA8hd2HeAwOr0HXdJvfsatTroEgsDh2iMPw8C8X\nIX9UqJYKrRdNK4rScjS9HSHfYbDfcGmavq0Rsj0KNWui5sXcTt2aEIKpyWkERXcryJ5gH1YWV6yu\nZUVRkEqlkMlkKkQ9GIbB6MhVBCT3c3Vd4Z1IJ3OWTrRTw9rU1BSKsoZQqLIBTdM0o2FK1y0itn8e\n0eguDA2NOOpmj42NgfN2wCO2rhAV6d2NTL6IixcvIplMQtM0TE9Po6gRhHe0YB9Yhc4du5EpFHHt\n2jV8eOkSxB0lOcmSrjRFU2X/XZYpkzRNgwJlkbReTdIdQSiGsuWmkEwmoIPA4xPg3duLXLqA5KI7\n+0g7EokEWJ4CJ1R294cPRLG+nEY61jwlbJJpIFSfkFmeQedePyauOp/jxsYGfBLg8dgi7Go+riLq\nw8ckXL0eQ1FWjcxFxWdtm5l2ImqHRdqJe0IYu/qh4zX6cWGrI+RW0E40bfa35PN5/Mu//Av+67/+\nC6qqbpqQX3rpJezduxeiKOIzn/lMzRRENX70ox/h6NGjEEURx48fb+jk9uSTT4KmaXz/+9/f1Dma\nuOMJ2Y7blbK2E7GpaBUMBi1Fq3aPuba2hnQyjYBLQu70RiBnFYyOjlpKXxRF1Yh6ZDIZzEzPojNY\nKzRSD0FfGESlG45/XL9+HYIQAssaN3Bd163xCrOxxGlhEo3uQiKRrpnvBYDRq9fgd4i4m4PAI/kA\nVsTw8DBEUUQwGMTY2Bj4cBScp/4sazOIwRAgePHBBx9gfGoK4X1NUsy2mjTN0CWSNur2JkkXi0Ug\nFAJoBsnFlVLKu2QCYXofu0QimQQj8aBoGmJ/FBpDY/V6cylROwgB4okYhEDt59RxoAsKIa7qyLFY\nDKKXrpuuNtF3JISJ8RhUtTKDpaoKUqlYw9njCpSI+fBdEvKyghvTGeuzNkaxSgtJi6RtRF3VVW/H\n8bs7USzEmuqv38lwMt6wR9NmIx8APPfcc3j00Ufx7rvv4itf+Qp+8zd/E1//+tfxj//4j8hk3Euf\nvvrqq/jmN7+JZ599FkNDQzh+/DgefPBBrK87lysGBgbw6KOP4oknnsDly5fx0EMP4aGHHsLY2FjN\ntv/xH/+BDz74AP39rfWvNMIdT8j2FeRWE7KZDk6lUhXSkn6/32pO2swx5+bmUMzLriNkhmYhwovR\n0VFL6cvv99fIvU1OTqKQk1siZIqiEBCiuDw0bP1/oDJCHhubgM9njlEZNzmTiBv5m4Y6uqBqdIV8\nJGAsHOZuzSMUbUXQnVS4QAWiO3F1bByiKAIAPhy6jEBfVQd4nSCDqvMCRVGQuvvw83feRUaREd6z\np4XzKx/TmidlaGSyGTCdHaBFAYmb86BomwmEXu7y1kopWNOtqZo4NE1HMp2Cx2ekmWmOBdcfxcp1\n9zVfAMhmM5DVIryB2q5mzstD6A3i1vhSw31ommp0V4eayw32Hw4hV1Bx62alAE08FgcFBR0OUpmN\n0LfTA8kPYx659FlT5uwuY5uZti2KTPlUousVmQtd17F3tw8Bn2LN+v8y4OOMkFuBGU0bEq0MRFHE\n4OAgrly5goMHD+KP//iP0dPTg5/+9Kf4sz/7s5b2/b3vfQ9PPvkkHnvsMRw5cgQ/+MEPIElSjTKX\niRdeeAFf+MIX8PTTT+Pw4cN49tlncerUKbz44osV2y0sLODrX/86/vVf/9UKZLYCdzwhA5UGE1tF\nyHbjB6cotPrY7WBubg5QKIic1HhDS9RDRcjTiSuXr8Dv91tKX9W4efMmdI2CT2otVRQN7cCV0TFH\n1aJ8Po/JySkEglHDhanUMOXGaJyiaPh83RgaqrzZ3bhxA/miilDEDSET6ESvcYHq2rEPUzdnsbGx\ngaWlJaysb6Cjr4FoicuvK7xjD65PTYN4veC9Tb4fF0in0mAkEXxvDxLTc9bNy/Q9Zmi6RNLGiJY5\nHkRQtsPUdWLoResaBL9o7Vva04ul6wvQVc31+SQSSVAM4JGcU83BA1HMjDc2hkgkktCIXKe7uhKR\nXT7QAoPrY5Vp61hsHUE/DZZt3Wlt/1EBQ1fqNHaZ5QXboshq/iwRt0nSRNdBdB33HvXg0uD5LR8H\nulNg/5xomsbOnTsxPz+Pb33rW3j11VcxPm4oArq1YlQUBYODg/j85z9vPUdRFB544AEMDAw4/s3A\nwAAeeOCBiucefPDBiu0JIXjsscfwzDPP4OhRd9K6brFNyDZsBSFXGz+YRFxPdHyzEbIHDUajSkRs\npIUNUY9ObxTLiytYXa1vazc3NweRbd1hpSvcb9WR7RGyoii4cuUKstkCOjp6LSeoehGmE6LR3Rge\nHoUsy9Zzk5OT0CkWUqCx/y4hpYhcVUEBFS5QkZ5dyBZkjI6OYnx8HDlZQai3QQrK5VcV3rEL6UIB\nRGg/9W0/ZjyVBOsVIOzox/rULWs+2vQ9puwmEGyJqGnaKp2aJJ1IJEBxNGiOtVKv3r29KBRkxG+5\n03gmBIjFYxACfN0O/PDBKBKxLBIr9Y0h4vEYRIkGxzW/DdE0ha4DAUzYGruKhQKy2aT7dHUVDh2T\ncH063rKMphVNW4YbxvV88ngnZmevIZ1OO44DfZR60k4jRL/sqI7ozdqyvcvazGS5wfr6OjRNq/Ex\n7u7urjuitry83HT7v/7rvwbP85b701Zim5Bt2Iw/cT3jB47jGv4oNkPIU5NT8HIOetDE6Fi2EzHH\nGXWyiK8LhUwRV69erbvf6ambkDytN1IEvGFAZXDlyhXrPWezWat7WSc0wuHutm4S0ehOpNN5jI+P\nW8+NT0xACEQaynSaI1QEcHSB8ohe8N4OjI6O4vr162ADIXCe2jRsM7enajAeAUT0GyNNm0Qul4Os\nKuAkEdLOfhQLRaQXmnQxl0jajPTM5rFkOgneV35/BASe7jB0jsXS+FxD32MThUIB+WIOUqD+zTG0\nNwKNonCrTrd1OV3tXo+770gINybjKBaMxqmN2AYYRkMo2D4hK7qK0Trd2/VQc7WVPuMT90RAIYsb\nN244NjBpmtbU6/hOR7VKlyAIEITNieBUo9VUvn37wcFBfP/738c///M/b+k5mdgmZFSmrFtFM+MH\nN8duh5B1XcfNGzOV9WNCoGsaFEWFrmmgbURsRjI8y8NDpLqETAjBzelZBH2dLZ8TRVHwl+rI+Xwe\nAKzPZGFhAaIYrrCHbAWBYBQ6Ya06MiEEo1euIRhpNEKlgJQ6tzmWLblA1X4ngehOfHDxEoZHr0CK\nuq+bN0ImnQHX2YV8yr11YD2k02loADhRgKc7CsKwiE23LuZRKBRQKBbh8ZcbaCiKAs0y4Hf1YG3S\n8PWt9T2urEsnEgmA0iH66pMp42Eh7Qhhrg4hl9PV7gm5/3AIRUXH9PUEAIKNjTWEQywamHs1RDjC\nIdzFbJmudWdYwK4+2pLRdDMO1MzruN2U9yc1QrbD1LFu9z1EIhEwDIOVlcrmwtXV1Zoo2ERPT0/D\n7c+dO4e1tTXs3LkTHMeB4zjMzs7i6aefxr597rT0G2GbkG1oxQ7RJOJmxg9ujtnOD255eRnZTA4B\nIVgiYnujFFVulHI4lyDXgaGLztq75n6D3tYJGYSgM9iLoUvDViek1+uFx+PB+Ph1BAL19babwajD\n91p15LW1Naytb1TVj42GLVVRoOsaaJopdW7XVxkDjPGn2VsLuHptHKHe5pKebpDOZCB09SKfTKHg\n4ITVCpKpFGiRL3Vj0+B6uhGfbq0rGiiNGFEEvFQbcUi7e7A6swKqpFde6XsMy1JR0zTE4jHwvlLm\nxwqja6/hwP4o5iac68jldLX7BVqoRwQf4HBjPIZ0Og1FzrmSymyEA8cEXL66NQIhAHDiHh9GRz6o\n+5tu5nXcTE/6k2Kh2Cpuh0oXx3G47777cPbs2YrjnD17Fp/97Gcd/+b06dMV2wPAz372M5w+fRoA\n8Nhjj2FkZATDw8PWo6+vD8888wzefPPNts/VxDYhozZCbpQ6shs/KIrS0PjB7bHbSZMvLy9DLsjw\n8r4SEaugqBIRs2xDda2orwtzN+ccW//n5+chFxQEfI3rspUodS6rKiLBHuSzRSwtlTtsZVnG7Ow8\nAsHN+YVGIjsxesVoGrt+/TryRQWhSJ+xICkd3+zcZq3O7ebfSbh7B5LpLGLJBDoa1Y9b+HqTqRSk\nvn7oGkHiVuvkaYLoBMl0CpxUTg+Lfb2IzcyX68iuzykJVuKt5i87pF3dKBYVxOZWjZq0g+8xwzDG\nQjSXhhQQSsJXpX/mNWx7dOyPIJ0uILZUqXHeTroaMH4rZh15YyMGj4fA591ch+uhoxJuLaaxvtGK\nfWL9C+HEPZ2IbdyyZv1d7c02DtRMT7pZytu8j3zSIuRGTk+beQ9PP/00zpw5g5dffhnj4+P46le/\nilwuh8cffxyAQbDf/va3re2/8Y1v4I033sDzzz+PiYkJfPe738Xg4KBVL+7o6MCxY8cqHhzHoaen\nBwcPHnQ6hZawTcg2mNGAEzm2Y/zgBu3+7eLiIpSiCp426mcsyzYlYvN4EV8X8hlDRaoat27dAtFp\niB43nYykNEtcjszDgS7QOl8xt3fr1i0UiwqCmybkfuSyRdy4cQOTk5NgBB/4UpOHpmmgQIFlOTAM\n21LDGO8RQVgJuYIMKRSueb1iXy52q6oqcvkchGAHGF8ASQcDC7fIZDNQNK2CkIW+HsgFGZnl+o15\n1TDHnez1YzuE7jB0lsX6dP1RJYoy6noEOqSAUE57W/9QQdKBXR1QKWB+YtlGFgSJRAIaURAsdVe3\nshTtOxzCzZsJrCytIBLmWlokOeHgUQk6pblLW7tYNN91pAMcm9+S8Sc3etLmaGV1yltRlNIpt9cT\n83Fhq60Xv/zlL+O5557Dd77zHZw8eRIjIyN48803EY0a96L5+fmKhq3Tp0/jlVdewZkzZ3DixAm8\n9tpreP3113Hs2DFX57xZbN0A1f8P4JSyNpVjzFEes8lgqxyh7Md088WqqopcLofZ2Vl4KMFoGmvx\nXHjWA14XMDY2hl//9V+veM1dhzUppTC10nnTBgmW/sbLhzE+PoHf+73fAyEEs7OzKBZVBIObk3wM\nBCNQNQoTExMYn7gO3tsJUspmMFaNuD0wYghqcqWtHxcBqSDtTCYDVScQRRFCpBvxufYJOZ1Kg9AA\nK5SjSaG7CzpFIzGzgEC/u5p3Op2GqmsI+J0bsSiGBr+jC6s3FnHkgVN195NIJsBLLBjWTDVTqLde\nYT0cpP4OzE+s4O7fOGDx2fr6OiQvBYZrXXas73AQ7ysqFmbTuO9k+yUQE14fg56dLIavbOBzv9GO\nwEwlPB4Gdx3mMTw8hC9+8Yub3l81zJS3fVzQJF2jzl+u/QOw7lt2f2Rz5veXKXqu5/S0FTrWTz31\nFJ566inH1956662a5x5++GE8/PDDrvc/PT3d9rlVYztCRm3K2rzA8/k8EomE5cB0O3yS3datTa1l\ns4s7kUjAQ4ktk7EJHxPElZHaxq6pG9Pweur/CAwXJkO9CDBW8NWaz+FgD66MjFmp/9nZWfAeH1i2\ntRRlNSiKhiRFMDIygitj1+APd1nvfzNkDBBQHh80VYdSyNffqnTTa+bYlMlkAJYBzbEQu3uRXFqB\n4jCb7QbJdAq0KMBOdRTLgI1GkJhxT/SpZBIUR4Ph64twiLu6sXJj0VrkVEPTdCRTCYgO6lyVKA1b\nURSC+yOYvb5mEYGu60hnkka6uqr8TAgpdbPX/3ADEQGcn8H6sgye35rf4YFjIi5fWduySPLE3YaM\nphml3m5UK2CZETQAVxaKTinvjxrbTk8GtgnZAbIsI5FItO3A1AqaEbKmaVbN2t7FvXBrERLXun6z\nibA3gsnxyYq5Xl3XMXNzDgFfbdqWWOIiCgAChmHBskzFCJGJzmA3kvEUFhcXja7tmzPwNCB5t9B1\nHYFAFz788BJS6SzCXb2gt2CVny8UwHlDoFkeieXFusdWFbVCdMOMQqqNIFLpNOjSDVHs6oWu6Ugt\nOO+3EXRNRzqTAefQhCX09WJj2r0pRDyZAO9rTKTS7m4U8jISC86a0YaoiNpw3Kkaof1RpFN5xJfT\nACgkEkkAhtWiXSoRAMyct1GCLtelyyRNQIiOyH4fVha3TjP68DEJ64k85hcba29bn3STS+74PZ1Q\n5ISl6/5xwLwuGIZpavpQnfL+qGem7agee9om5DsQZmOVSU6KooDjOASDwbYcmFo9NlBLyGbNOplM\nQpblii5uAFi4tQCf4DCD3PyAAICwL4JcJl+RblldXa3tsCYEmmYQsU5MIjbNH+qIQgS6UcgrmJqa\nAiEEk5NTm6ofm5rXmqahM7IDa2sx5HIFhDorO6zbRTabBc1LYAUf4ou3Ko+tlZ2AzFSh+bCUsUCs\nMSFZlg0SFQSAEPD+ICheQKKNOnI6Y6SZOW8tAQp9Pcins8itx5vup1gsIl8swONrTKRCbwQaw2Bt\nynnxkEgkwHpocB73la7g7jBUAAvXjXp3PL4ByU+DZW2/Kcr8n/IolvFAFUkDxaKMngNeLC9ryKY1\n2Li6bew7KAKMjuErWzP+tGeXD6GAYo0//TLBremD2eVtRtNml7cZTW81SW87PRnYJmQYBGwaPwAA\nz/OW69HtRjUhV6fKnZrHUqkUMuksvLw7CbmK48G4sQWFINSCWmHYsLi4CLmowu8NAaVZXkUtiYvQ\npZnmBkRsgmN5iGwAN27cQCqVwurqRluEbKTH7Z3TLKLRHchmC5BVrS2HJydks1nQHA+poxvxRYM4\n7YsAU2SDZmgrGwuq3ARI07QlvFEoFKDpBKwgWDVTvrMLsZk5y6DA8j9ugkw6DcI4p5mF3m7oBEjO\nNu/mTaWS0CkdvLfxiBDNMuB6I46ErBOCeCLmIl1dCVbgIO0I4dbEMhRFRjqdsJq5moOqImlAUWTs\nOhqAQijcmMihgpEJah8uwHto7DrAY/iKC8crl9oCp+71YmjogrsTuA1opcvayfTB7PI2o2l7yrtQ\nKLTkc9zu+d5pXsjANiEDgFXfCgQCluH5RwX7qJXpkZzP562atemCYsfKygqUogJvOxEyAICAphmI\n8FW40ywtLUFTdAi8aIiLmLO8bElcpIWWVr8YwcS165ibm4Msqwi00NBlErFpZWeX2uR5ARQtQTHL\nnOaCxvXea5HJZMBwPKRwL2ILC5ALRWhqWW/b9fVAGeROaAqsp5ySFbt6kVhYhK5phouQ6X+sahX+\nx6hyEUqmUqClyvqxCcbjARMOI+6ijpxMpcCIvKt+A2FXN5YnF2turJl0Boomwxtsfe43sC+KuclV\nbGzEQCi1ofdxIyiKCkI0hHtESGEBNybyqFghWWidpA8dEzE8tl7jJtUuTh3vxPzcODY2Wre13Cps\n9j5mj6btKW9JkipS3lslE1p9vtsR8h0KlmUt44fbZcFYD+ax8vm85ZEcDAYb1qwtQm4jQrYdGAE+\nhKsjY9Z53Lp1CzwjQdcJaMocIXIWF2mGzmA3bk7PYmpqCqpK4HOoS9eckqWwVSbi6oYx4/kgNGVr\naog60ZHJ5sB6BEgd3ZALRaTXV+seuxkymYxRP7bxhNTdC1VWkFtbL7sI0UxFdsQi6ZKLkCzLSGez\n4Bpo93p6exC72ZiQdV1HMpWCp053dTWkXd3IZQpIr1SmwuOJOGgO4IXmzkzVCO3tRDKew9yNW/AH\nGDBMe7cdWS6CZQCGodB9KIBrY7lKPrZ4uXWSPnK3F9l8EZNTlTPT7eL43Z2gkcHQ0NCW7K9V3K57\nmBlNN0t5V8uEVqe8q7UenM43nU5vR8h3OiiK+kg0Zc2adTqdto5reiQ3S5WvrKyAISz4trqWbd3Q\n3gjmZuYQi8WQSqUwMzMLD+MziLgNMrKjM9iLQl7G0NAQBCHUtA6vaRpUxfihMgxTlwwVRQHvCUIp\nylDkYtvnZyKXzUFVVTA8DzEYBQGF9Pqyo3hGUxAgmU6DrdLeFcIREIpBcmHB0j02U+D2mjRNM1YU\nmymNKXGSUCu6Ye63rxuZ9QSKmfrNSOl0BqquNq0fm5B2RKERYH26PJtJSElZK+Bpa3EW3NsJRdex\nMLmMYJvKWqYUKu8xfhv9h/1YWFCQTjkszNog6R27POAlgqHRDaPLvCpb0Sr8Pg6HD3C4PHSp/Z1s\nEh9lpq+ZTKjZYV9PJtRqkLSV7rabuu5Q2C9cmqZve4SsKIpRBy5ZMwJG3dptzXplZQU82rux2X+j\nHWIYuXQeIyMjAIDlpRUEfOEt+SEHvB3QFQpXr16D0MCv2azVmkRsSF3WvyxzuRwEMQSKYpFYs9U6\nW/7KjKg0lUpCIwDnEcCwLMRAFIml1ryBTeTzeSiqBlas/G4ohgEf6kRyvs5+7SRdKp9kszmAY8Fw\nrEUhFn2UCFro6Yam6UjMLNZTr0QqlQLFMWA97iJbmufAdocr6si5XBZFpdBSd7UdnMiD7/YjtpCC\nz996hA0YncA0RcCVmsH6DvmNOvJ4/TG1CjQhaZqmsO+IB5dH121d9Kqt7q+7qvvbcep4CKOjF6yM\nz0eJXwYxkFZkQs36czabxR/+4R/ia1/7GjweD2ZmZiwZ3nbw0ksvYe/evRBFEZ/5zGfw4YcfNtz+\nRz/6EY4ePQpRFHH8+HG88cYbFa8/++yzOHr0KHw+H8LhMH77t38bH3zwQdvnV41tQi7hdngiV8Nu\nzQgAfr8fgUCg5UXA4sIieGpzGr6apsHDCCCy0cwlSRKWl1bgl7YmRURRFLx8GDMzM/AHanWxdV2v\naNhqRsQmcrkcOE8ALOtBbLUd4qz0Rc7n82BsRiBCsAuxhco0sFvVr0wmAx0ErINblBDpRrwFCc1E\nKglGFGDqWFLVDwCs3wfKKyE+M29EkFZduuTYpBMkkglwTcadquHZ0YWVqbJiVzyeAMUAgrfdOXIC\ncWcQyZV8e8IrhEBRiuB52lpQekM8fF0iro81HlVqiCqCPny3FxPTcRQKBDRjZCsoUOX581KGwqz7\nl59z3v3JeyMo5Nc/lvGnVh2NPirUkwk1RUs4joPX68Xg4CAGBwfxp3/6pwgEAjh48CAeeeQRFIvu\ns2KvvvoqvvnNb+LZZ5/F0NAQjh8/jgcffNBRMhgwvJAfffRRPPHEE7h8+TIeeughPPTQQxWqg4cP\nH8ZLL72EK1eu4L333sOePXvwO7/zO1vWK7BNyFW4HYRsd4TSdb3CmtE8ZitYuLXYXv24dGMBDLMA\nlmXhowOYnprG6uoqinkZPmnrUkQBqROJWAp+W/3Y3jkNCmA5tqVu9lwuB5bjIUoRJNYWbVTZ/Dtz\n8kXO5HJg+DJhSR3dyCYSKOZav9FnMhlQvLNWtNjVjVwihUK6ufuTIivI5nOO404WSsTM9/QgNbdY\nVl+ijTkhc2wuLxvjTo2IoxrSri6k1lPIJzIgBNiIbzT0Pm4GVVHh3xVEPqMh7aQZ3eS8ZEUGIXqN\nEEjP4QAmxtsTXHHC4WMSFE3F1Ym4RRx2z2PKXByBMsRBdR26PZI2o+kSce/f40dHUMWlSx9f2vqT\nBJqm4fF4cObMGbz//vsAgJ///Of44Q9/iC9+8YvQdd0a+3SD733ve3jyySfx2GOP4ciRI/jBD34A\nSZLwwx/+0HH7F154AV/4whfw9NNP4/Dhw3j22Wdx6tQpvPjii9Y2X/nKV/C5z30Oe/bswdGjR/H8\n888jlUpZWcbNYpuQq7AZT+Rq2I0oVFWF1+tFMBissWZsZRGg6zpWV1Yh8ZL7EyE2W8YSIbMsA5ph\nEJI6MXr5iqGNLatbFiEDgMSHoCo6ON4DgrI3sXF8FmyLmtMAkM3mwLA8vL4oNlYWXH1uzr7IXIm0\n8hURrTfcDV3TkawjENIIyXSqpn5sQoj2QNcIUvXS1jak02lohICXmqeIhd5uJOZXoKsqaFvKm2UY\nK2LnvaZmtE1sw16XroK0sxuqTrA2tYRcLotCMQ9vqL10NWCkmwN7Q9ApBkuTrTZNEcjFInjOSCvb\n0XfQj8VlBYn41ihiRbp4dHQxGBpxiHao8v/YSZqukqEsk7QGXdfwqeMiLpx/Z1NWiu3glzVCrofq\n881kMiCE4Fd/9Vfx+OOP42/+5m/w7//+7673pygKBgcH8fnPf956jqIoPPDAAxgYGHD8m4GBATzw\nwAMVzz344IN1t1cUBX//93+PUCiE48ePuz63Rtgm5BI244lcjWojimbWjK0QciKRQDFfhOTG/MFG\nxKb5g1m3MRH2RrC2soaJiQnoGlyaSriDyPlAERr5fBaqolriGu10LwOlzzWfB8t74PN3oZDJoJAz\n6kvOn14jX2RjREknBJxt1c2JPtCcgMTyQvWu6oOU1I6Kck392Nqv5AUjeZF0odiVSqcAngXFNs8c\niH09UBQV6cVKD1dQdncn2jHlbb6tapJmvQLoDj/Wp5cQi8cBhkD0tpb2NkF0HYoqQwoJEHoCWGyR\nkA0iU+Hx1H4WfYf8UAmF62O5ts7NCYfuEnBxeNXd75EyfruUqRNdImnDutJIeX/6VBQryzcwMzNz\nx1gptotq2czNaEGsr69D07Qa3+Pu7u4KMwk7lpeXXW3/3//93/D7/RAEAS+88AJ+9rOfIRxuPkXi\nBtuEXIVWPJGrYYp6JJPJCv3rZo5QrRDy+vo6FFmFxDcQxSBGOq3GH9mBCMPeCArZIkZHRyGwvi1c\nVRPoGgUP60MivmIR8WZUz/L5vJFq53h4/VHoml7Z2GU/tq6Vbub1fZGz2Sx0AAxXro1SFAUh0FUp\noeniI8mkM9CIbih01QHf2YVEswiZAIlkCqyDXKbjPiOdIAyL5Gzl56CpWuNxJ8e6dHmm27OjC8uT\nC9jYWIcYKH0+VkTt/rchK4bUKsfRCOztxPz11ryhC4UCOJYCwziUAfwcgju8W0rIR++hs9vgAAAg\nAElEQVT1YnE1g8XlevtscjGYDXqllPeJeyIQPAWMjY01tFLcaiWsT2KEbIc5g7zV76HVz8Vp+899\n7nMYHh7GwMAAfvd3fxePPPJI3bp0q9gm5BKcDCbcghBSIeph1792q5Tj9nhra2tQGxCyScQVohoO\ntozm4QROAKtzmJycBM9sRXRskqGKfD4PL9+JZHJ1S+RHc7kcdGIQMu/xguUkxNcr7QLtDVsUTZdn\nqR1upKZCVzWkjm7EFhqkwx2ezmQyoDgOVIMVvRjtQWJxCXppxMMJxWIReblQYbfYCBRNg+uKID5b\n2TCWTKWgEtX1/LGxM1jkLO3qxsb8OnLpNLxBsan3sTNJE8hyEQxr7DO0P4z4WhGZuENjjsPPpFF0\nbKL3UABjV/NbFmUeOCwBjI5Lw7Vp63aOwPMMTt4tYPDihYZjQbdbCeuXGY28kNtFJBIBwzBYWanM\nHK2urtZEwSZ6enpcbS+KIvbt24f7778f//AP/wCWZfFP//RPbZ+rHduEXAW7clYzEEJQLBaRTCYr\nRD1a1b9uNUKGToFjKsdHiK6XzB9sNVqX1owCvLg5PbPJ+jGp7JymKORzefjETsTWapWf2kE+nwfN\ncJahhShGEF81IkOrWczWsMUyjVPjqUzGsSNa6uiCUiggG3ffOZnKpEELjdO6YrQbqqwgvbxSd5tU\nOgWNENeEDJgCIZULiEQiAdpjjE21A2lXN4qKitxqEqLPUxFFO3kfGyStV5C0pmrQNdVqxgrtC0PR\naSxed5e2LhYLYBmAZet/hzuOBrAR17CyJNfdphV4BBp7D/MYGlnbkv0BwKdPRXB94hJSqcrsgFsl\nLEVRHGd3G6W8P0kRcj3ZzM1EyBzH4b777sPZs2crjnP27Fl89rOfdfyb06dPV2wPAD/72c9w+vTp\nhscysx1bgW1CroJJpI0IxBT1SKVSyGazYBjGtaiHE1qNkD2ULQVOiEXExGb+UJeIrQu8fLyQ0IGN\nlQ14xfZWpLWWjBwIjHRlQIqiWMgjm020tW87stksaLa8EPH5o4ivLFiNNASk1LDFwsmFyg5ZkVEs\nymAdujalUBd0jVTMI5N68RFljLNlczlwQhPzBrtASB2kUinQHncylybEvh4UMjnLaILoBPFkHHwr\n0XEVuA4/dNEDJZG1XTOUNYZVkfK2/bOTdLFYBEWjlG4m4LycUUe+3vxaMMhGhSA0/j317PdBZxhM\nXN26tPWReyQMj61Dlh0yGW3ww6dORkCRFC5evNh0WzdKWADqmj9Y+uufcGyFKMjTTz+NM2fO4OWX\nX8b4+Di++tWvIpfL4fHHHwcAPPbYY/j2t79tbf+Nb3wDb7zxBp5//nlMTEzgu9/9LgYHB/G1r30N\ngJGh+8u//EtcuHABc3NzuHTpEv7kT/4Ei4uLeOSRRzZ1ria2CbkEtylrRVGQTqctUY9AIAC/378p\nI4pWCHl1dRWszlvzkEZaj5RrtAztYjyl8nUfH4Aia2DZ1kQb6lsyUigUCiA6QUDqgq7qiMecGyla\nQSabA8uVCdTrj6KYLyCTihupW6thq/ldM5vNQtN1cHxthMxwPDhvR10rRsd9EQKuTkOXiWYCIYQQ\nJJJJsE1MIKrh6ekyjCbmjPNNZzKQVQWCv4VO/Cpoqgq2P4L8SrMxLWeSNmaHZXBVo0qBfWHMjSdR\n431ccfkTFAp5cCwqXaEcwHkYdO71Y2Ir68j3eJGXFVy51txJyw1CQQ+OHeZw/vz7bf29k9+x3fzB\nqS4NlCPrenKVvyy4XV7IX/7yl/Hcc8/hO9/5Dk6ePImRkRG8+eabiEYNo5v5+fmKhq3Tp0/jlVde\nwZkzZ3DixAm89tpreP3113Hs2DEARkPq+Pg4/uAP/gCHDx/G7//+7yMej+PcuXM4evTops7VRHv5\nrDsA1QSpqkZNVFEUMAxToX29WdgXAc32tzi/BIERoCgqAEPAgKHdkLD9eJX3P4HxAhqgKC7TLoRA\nK5kkAJQ1A2snwkI+D50AguADz4iIx5exc1f7F61ZR5N8xmKEgEDydYLoBMn1JYQ6u9BK+JLLZgGa\nAc06/wTEYNRyfjKhazo03Yg+rCYoUhrRoOmK6L0eDIGQW46v5bI5yKoK0dsakTIeD5iOEBKzC+i7\n724kkwmApcGJfNulAllRIO6MIH1+AZqsguFbuVVQhpUpRcDxlfX70P4wps9PI71RgL9TqLgOCSEA\nBSiyDF1X4ZXcHbP/SADXzt6CphHH5q9W0d3LI9BJ4eLQGk4dd2+K0gin7+/ED/91AOl0Gn5/u6Yw\nlTBT3vZggJQW6oVCwZIBtiuFWfPVpfE42taB/3GhUcp6s3jqqafw1FNPOb721ltv1Tz38MMP4+GH\nH3bc3uPxtDR61Q62I+QS7BGyPWK1i3pomlYh6rFVF7GbRjKzXj0/dwseVix3Trdp/mCfP6VUgCM8\n8sVmEnWlhi3VcIIqWzLWNk3lC3nQtDFnLHFhxDaWnHfpErlcDppOQLN8KbKiwHEiPJ4gEuut7zuT\ncW7oMiF1dCO5ugpVkS1RDU3TKq4PM+JIpVOGoYRl3Iu6HUCGQEgSxXTtZ51MJaFRANukFu0Evqcb\n8ZkFgACxeLxldS47zOhW2tMNVSVIzbXoE0yM2WGOL3dumwjt7YRGaCxNpmqJgDLS7YVCATxHgaFh\nl5uu+7n2H/Ejmwdmp7dGJISiKBw7IeH84MqWNVGd/nQ3dD3uKm29GZiECxhyvI3kKrfCoWmrz91E\nIpG443SsgW1CdoS5snQj6rFVxwOcCdler97Y2EAqmUZACjh2TreLYrEICQHEkvUaWUhJc9o2RsVy\nDS0Z8/kCaNr48fvFTmyst9/YRUBKeraUZY9pfmaSN4r4WquETEoNXfVJS+rohqZqiC8tGNaIMFTF\naJqGoii4fHkYl4eHMX1zGolUCpxY6kQmtrley1KxTNKmQIhTHTmZTIKRhLa+V7G3B6mVDSTWY8gX\nCxAC7aerFUWBTgjEvjAIzyNxszVZQFk2lLWM6LgSnJcv1ZGrGrsoQ6LUaI7RSrVj++dgY+Qqgo7u\n8oIRWYxf2YSMZhXuOenFykYWN2dtKftNkFS4w4OjB9i209abQT25ymqHpnp1aVmWbytJbzs9lbFN\nyCXYu6vNaFSWZYii2FDUYyuPXX1hVterZVmGrhF3oiAtoFgsQqJ92Igv1ZyDJTepqaAo05Kx+WIg\nm82BLblR+cROKMUi0ukWIy2UXaByuRwYzlNq1iof2+uPIrm+AlVzL+CfLxSgqIpjh7UJwRcCwCCx\nvFgphUlMbWuDDTY2NpAvFFFQFaSSKaRSKeTzOeN8KNSQNCtIoEUJiVvzZcKGUbNNZTKN5TIbQOjr\ngaYTLF67Dp0BPC3Woe2QZRk0S4FiaPD9XYhPtTBjSQiKxQIYjgJd5xoJ7Ivg1kSytiykqZDlAgQP\nbahy2bWmG7g10TTQcySEqyPZhpF0K9h3SAIvEXx4aeu6rT/7KxGMjgxsyizBDZxSwE6odmiqV5eW\nZdkiabPLeyvr0rerhvxJxDYhl6DruiXqQQgBTdMIBoMQRfG211eqCVnTNKTTaaTTaRBC4PP54Pf7\nEY/HG84gt3o8E/lcHj4uiHw+a6WtzTGiZt7ETtB1wwvVbBLzCWGjsSvuvrGr2gUql8+DdUgx+/xR\naIqKdMz9jdNo6CLgnAjZnLGlaQiBCDKrK9Z71kqd3BzP4dTJUzhx4gS6urrAeHhQtvqxoqjIZXMG\nQZdIOpfLlZrfDIGQ+K35sgeyqiGRTELVdfBtEjIb8IMSBCxfnwbvby/KNt+jqipgOSO6FXZFEZ+J\nQVfd3XhlWYauaw1nhzsOdiIRk5Fas6WYCZDP5cAyBB6HyLqZW9POuwKYnpaRThkNhk6RdCtEzbIU\nDt0t4PzgqnV+5hHbxWfv7wZRYzh//vwm9uIe7dy3zLp0vXlplmWtrF29Uax25qWrz/VOtF4EtgnZ\nginuwfO8IaZhNSp9dNA0zUqTa5oGr9eLQCBgpcnX19ehyhpErv1xFhPWD4YQFApF+LmQkaJNrkLT\njM7pijGqJmNEduTzhZJ5hUGgDMPBw3gRjzVPLdvNJ8zxD53oxogS7zCi5O0E0amW6sjZTBYUWzuj\nbXT+mmJLFMRQF2KL8yV5xFLdWNMtpx8QI7vg8fkQDAath9/vq8moqKqKXC5vzKJKASxcv4HJietI\nJJIgMLxfwTGgSje8eh7I9UBRFNiuKDKLKxCC7S/YZFkGaIApyXaKu7ogF3WkF1yMrRGCQrEA1kF3\n2o7gvjA0MJi/Vt5nvpAH0VWIIuue9WzkvPOuIBRQGL+SQ20kDTRKedcj6btOejE5E8e6kyFGGwh3\neHD8Lh5v/+Js8403ga1OLdvnpZvZKBaLxZbr0k7Pp1Kp7ZT1nQyWZREKhSxRj49jRCCXyzXUvl5f\nXwdP86Umqq2BXPqxCKwXjM5gLbFkjFFZDVvuxojsKBQqCRkAJL6jYWNXRUROwVoUAUYEb4wo1RIy\nzbAQxFAdCU1npDPpCocnu5mI6egDGHXkXDKJYjZTs0CjaMPxJ53NghWFMonCyK4IgoBAIGAjaT88\nggc0TYHvjILoBLGFBczMzGD48jBmZmehMBSy2SwUWbZI2OIMFyTNdkVQ3EiB97Q3PGFGPgzHWF+5\npzcMwnJITDXPQMiyDKJr4BtExwDAelhIOzuwMGEQsqLIUOQiRJFuu0taCnAI7fBibCTrEEnD6Qk0\nI+lj93hBaA0XzCgZ2HTfxv/xG924PnGxrp7yVuJ2Zvbq1aW9Xq/rurSpnVA9XUIIQTKZ3CbkOx3m\nDbdVf+J2YUblpoKPqfRVT/t6fX0dHGnXk9YZxUIBuq6DpVmIxItEet2Y523QsNUM+XweNM1U1F59\nQidiG8uGmpMNxDKAqHKBsr3/XC4HQigwjPNYkeSNIL7qLkLWdQ2ZbM4wlKgg4uobGIEU7oauEySX\nl4x6maaDKhl0MAyDQr5gpJlFySaSUUugBklTEDwC/P4AIrv3QhQl9Pp86OvrMxaAAGiBh1Yar0ul\nUkglk4b4TCZjRK4NSJoQArozbKR+l1qv1QNmM5dupasBgGJocDu6EGtCyETXjeiYbxwdmwgdimJ2\nPGlJrPKcITO5GfTfFcKVq4beeQWc0t1N6tIAgSgyOHDMg3cHlmqu23bxK/d1QRQyePvtt7dkf074\nOOU1jT4T57p0PYlQsxYtyzLeeecd3Lp1a9M15Jdeegl79+6FKIr4zGc+gw8//LDh9j/60Y9w9OhR\niKKI48eP44033rBeU1UV3/rWt3DvvffC5/Ohv78ff/RHf4Slpc1Njjhhm5Ad0IpQRzuoltw01XcM\nA4T6X8nK8go4qv1mHQsUZQRZJVcqXSNgGA4+LohYYnXTUUAhn7c6rE34xDCUoox0qkwWZsOWWSeu\nV6PO5XLGjG+d8/L5u5CKrUFVmssnZrNZqJoGhvdUpKfLN2Xze6fACRJoVkRsaR4UKDBsaeaztGk6\nnQahKDA8b9PGMJqZaJqqS9IUTYPriCC9vIKenh50dXfB45PQEY0iEAhAEMXSgggwBWAKVSSdyWQg\nF8skrakq6I4AaJ5Hbm65HEm3gGKxpDtdRajiri7EphrXkQvFAghpXDu2o+NAJ3JZDbcmVsEwOkRx\n81mfXXcFkUrrmLvpMsXsgqSPf8qHKxPrWF0zhEd0vVyyMMfhWoHHw+BX7/fhnbd/+rES50eJehKh\nJkmbv5NsNouHH34Yd999N9LpNP78z/8czzzzDF555RVcu3bN9ef16quv4pvf/CaeffZZDA0N4fjx\n43jwwQfrGkAMDAzg0UcfxRNPPIHLly/joYcewkMPPYSxsTEAxv3n8uXL+Ku/+isMDQ3hxz/+MSYm\nJvClL31pyz4jE9uE7IDbRcj1JDe9Xq+rYy4tLLfmg1z/RAAQK51E00Zq2ssGkculXMwjN0Y2l69I\nVwNGYxfRdMTiSxUNW2aduNFCJJPJgmHrZwa8vojh/LTeOA2oEx2pVAoEAMt7rPS0rutIJpKlRwr5\nfL4UsVPwBCJIrSyBKSmQ2ZFMJUELQt31SyOSFiJdSNxagK5riMXjpXEnY1sPz8Pv91vpbpOkGRtJ\n65qGQsFG0uk0CEOD6+5CdtbQyq4W3SinvGvP1ZSqZB0EQMQ93ZCLGtLzzspVmqYansUe2nFB5QTf\njgA0lsHyZBJeqXVfbCd07fGC8fK4MrSJ67eKoO+9zwcwOi4MrlsvExCb77HR76Brmo2kG/+OP/8b\nfVhfm8Lo6Gj759kAbrusP07YSdr872AwiIsXL+Lll1+G3+9HIBDAv/3bv+HRRx/Fb/3Wb7ne9/e+\n9z08+eSTeOyxx3DkyBH84Ac/gCRJ+OEPf+i4/QsvvIAvfOELePrpp3H48GE8++yzOHXqFF588UUA\nQCAQwJtvvomHH34YBw8exP33348XX3wRg4ODmJ+fd9xnu9gmZBs24/jUDKqqVoww+f3+CsnNZoRM\nCMHq8urmOqxLUpdmfZxlWSiKCpoyzsHHBozGrlT7ox6E6CgUCjXpZZbh4WF8iG0sWQ1bLMeimeQo\nIQS5fM6xfmxClDoAQtdt7LIbT2RzOdB8ZW3ebNoqbY1isWiIwSSToDwBzE2MY+bmDLLZ8pyrpmnG\nmJLU2gLJJGmpuxf5RBK5ZBLZfA68z2sbpio3mBGUSdrn9yMYCiEYCiEQDEKUJDAsW9peN9LLvV1I\nTS0iWYqk0+k0ioUiiK0nwu7YZD6KhQIohgLtIFXp6ekAYTnEbzhcF8SwHKUYYplINAMhOgh0+PZF\nsD6Tg4sMtyvQDIX+ezpw+dLWzSOLEoOD93jw7nljsUeVFK4s32O6vAgpk7TmTNKln/eRQyHs7lfx\nk5/895adZzV+mcm4GmYNmaZp7N69G7/2a7+GjY0NvP7665iZmcHGxgbefPNNV+9JURQMDg7i85//\nvPUcRVF44IEHMDAw4Pg3AwMDeOCBByqee/DBB+tuDxjCJRRFbXmde1s60wGtSFk2g6Zp1twewzDw\n+XyOKl/NCNkcnelph5BJSepSM6QuzToORdPI5/NgS+llDy2C0RnEU2voi+5t/TgACvkCdE0Hy/El\nswHjRqSDQGSDiG0styQ5ms/noekEIlefkCmahih21jR2ERDrpojSKjxd4fBkJK0NTXK/FdhomgZZ\nlqHICoRgBLqqYWn2JjY2ygIZiqIgryoIetqr6YvRHmgaweL169BYGl6fVJHeLr8Jm62FXV0NAM9x\n4DkOsqIgm8uCE3jo/b3IDg5BWUuCj4as8khRrpRF5Xm+ovFG0VTwEls6RtW1ydDgd3YhNrWOPZX3\nLRSKRWiqAtHrpufAlFzVQVNA5+EIFt5YglzQwAtbcyvac28I75xfweqyjK6erem3OHm/H/92JobV\n9Tx6uksaAKX0tvmdASh9ccRaUJk9CvbFkJmV+b0HuvB3//cvsLr6f6Krq2tLztM6jU9gKrxaNjMQ\nCFjPhcNhhMNhV/tZX1+Hpmk1lond3d2YmJhw/Jvl5WXH7es13hWLRfzFX/wFHn30Ufh8W6sJsR0h\n27CVEbKT0pd9hMnp2I2OZ4w8tTiDXEptKooKXdNKKSLbCBMhKOTL0SxFURDhRSy12mCnjZEv5A3P\nYkvisvw5+qVOJGKtyRFms1mjY5tvdHOlIPmiiK2YhGxIfKpmWrxUn5Zlw+GpPH9cSkASYnEdVerw\nliQJwVAQXTv3QRBERP0SOiOd1hFVVYVOUcgVikgkktbDmDduLlLCSV4wkg+rU9OgBE9lB7f9UUp3\nU5RDTbr0kGUZFGNEap6ebtAsByaeQyAYQCAQgCRJxmiK7Y9kWS5lAVKlpkKDNEiJVMzPESU5UGFX\nN2LTG9AVzVbyUFAs5MELNBim0a2EQCc6VFUD0TUwJQeoziMRFFQKCxPNDCzcY8fRAMCzGBncun3e\ndcIHitPw7vsrjZccxhdmRXt0SWeaYRjQDGON2RFC8Guf6YboSeI///M/a5yatoJQP2kRsh1mQ9dW\nvodWg6t626uqikceeQQUReFv//Zvt+z8TGwTsgM2Q8iEEORyOSQSiZaUvtwQsiJr7gi5NC9bnuc1\ndK/pku61eRqKokBVVbC29LKXCWCjBQGPauTzeVAUA5qiLclJk1T8YgSKLCOddi/FmMvlKjyQ68Hr\niyCTjKGQz0KxzTGzLGeYbxCCdCZjuDIJJUK2EzGqm7sMMBwP3htCIRHDnj17cN+n7sN9n7rPSBmX\npFTtkGUFmUy2gqSzdUjaE+lG/NYCPP7m32k9kjbT8XSpM5rmGLCRTmRnl60/5DjOkH4NBY1HMAiv\nJIFjjRlvgIDhGRCil2bQjTl08/rRCYG4OwqlqCM5t1HqjNdLzXZmqrr62jUWOpqu2ZTeCFiGtrqw\nxU4JfMSP2VF3/shuwPI0uo8EtzRtLQg07v60iP99d6E9snQgaa/Xgwd+swPn3n3T6jLeKtnKT1KE\nXE+lyx4ht4JIJAKGYbCyUuk5vrq6WhMFm+jp6XG1vUnGt27dwk9/+tMtj46BbUKuQHWE3MossjnC\nlEgkUCgUIAhCS0pfbgiZqAQetrFpANErpS45jqure10sFkvWjeV0oZcNIJNJoijnm56zw9GRyxmE\n7LTC9AodIFpril3pTAZMAxMIa9/+CDRVR2x1HhTsc8wEeintm0lnDEEQirZqtBYRN/iOxGBXhfOT\nXJSRLeTh+f/YO+84uerz3H9Pm7azs0XbtEW7aqiBKgIWkEBIQtjYxBib2A4GY18HB+dCDNe5sbGx\nneTjgOMSh9jEOHHcrsEQTAk2BiHRERgkgXrdXa22950+c9r945QpO1u1OPYnej4MknZP+Z0zM+f5\nve/veZ83GCQQ8FNaWuK+iouDePLS2Gohko7FkUrKSQ+PIPtmlloVgHQqhSnYRh72NXjm1hBv73M5\ncsyaMSayrOAP+K0yM4+Mx2sZ4uTXnZt2lkWqCKErMp3vnCI8Osro6AiGqeLxCOiGYb1skZOmaaia\nhqZrmIaOIIIs2TXGebe5dEkVrQcis0oiTavKOHkyxejI1O1UJ8NFl5bQ0Rvh0JEz7+sNgADvvbKB\nZKyDV199dYzyeDzbyvwa3kKYjaW23zfyU9YzXZtVFIV169axY0fGfMU0TXbs2MHFF19ccJ/m5uac\n7QG2b99Oc3Oz+2+HjFtaWtixYwdlZWUzGt9kOEvIBSBmpZYmQ34Jk1NLHAgEpuX0NRkh9/f34xEn\niLJNpzdxpp53sgYUTs/i7Ag5KIcwNJ3hyPSEXY7ndTQaQ5Y9COLYlm6OsGtkuHeco+Qf07Q8sQv0\nLM7bEp+/BFFQCA/1WdeNkEu6CIxGwm65E0xOxA4C5TWE+/vQUtY6bDgSHrf/sSRJBPxjSdrr9eSQ\nkaqqUBzCMAUGW08xMmpF0qqmTbmSxjBNUum0Gx074b63tgY1nEAbiRRId9vZH0zSqTSarqG467cC\noijZNqmK/bLFS5KIt3EuIycH7a5XBl6vgInVhtMwdExTBwwE0UQSQZasfsaSKIx7m+csqyA8ojPY\nMZMJYGE0nleCJoi889bspa0XnuOntFLguRenbkAzGeZWB9h4cYDHH3vIWnaYpDxIluUxNbyFvKX/\nGCPkbIyMjBAKhWZ8zDvuuIMHHniAn/70pxw5coTPfOYzxONxPvGJTwBw44038sUvftHd/vbbb+fp\np5/m29/+NkePHuWrX/0qu3fv5i//8i8BS1Ny3XXXsWfPHn7+85+jqiq9vb309vZa3+NZxFlR1wSY\n7IOtqqrVFlDXURSFYDDo2shNF1MhZMUoEEnZdaqGYdhfaNk25p+caFKpFKKQW87jk4oQDBgO91Ez\nZ96kxzDt85umgWlYkxOfr2zcMpaAp4zBgak91Kx7a+AfR2FtmhnfQ0EQCBRVMNLfTXg0zLHjx9zt\nysrKKAmFiMcTeErn2Ldm6hFEUXk1PZrBaF83cxqaGB0dRfB4MrXCk0CSJPx+P35/xvJUVTU0XUXy\n+kj39lskqqpjvuCKrODxKMiKMmbE6XQawzRQFHtCZa8v+2qrMU2InerBUx7K3U+wJieGYZJMJ5EU\nMWvimP/5s6cygoAkiQQX1TL8dBumqlNU7kUQyQiXwBXwCYCZVdY90UexpKkMw+Oh/eAoFQ2B6bwt\n48JXJFOzrJS3Xo+wccvsRDKCILD+0iAv/bqT/3XjEoqKJu99PRV8+APzeXHXIZ5//nm2bdtW8LyF\neh6bWd97h6Tz97NKGsUxHdL+kFAoZX2mPtbXX389AwMD3H333fT29rJ69WqeeeYZKisrAejo6Mh5\nTjc3N/Pggw9y1113cdddd7F48WKeeOIJli9f7m7/1FNPAbB69Wp33IIg8Pzzz7Nx48YZjzUfZwk5\nC9kp64kIUrPdlFRVRZIkiouLMw/FMzj3RITc092LV87ysDatloi6rZx2rR2nmB4HSCZTCII05nd+\ngpMLu+z1QSutb00EEunEGMvM/PEU+8rpGTzq1iBPhHg8bgnExqSszax7lXnyFwUrGexuxR/woyiK\nRW6mydDgEL29vcSTKYyiElIjYRSP4vqWTwZvsAxB8jDS3Ul5XSNDIyMoZ7h+ZBg6oiThr5qLODJK\naUkJumGQTqdIp9IuNaqaiqrlk7SMoiikUkkEOSMWcu6E6PUgz5lDrLWbsjXnjDm3CcQTcUzTwOvL\njtyF3I2y/mKaJsq8CnQTUj2jlFbVjD1udlrcsJT1YDhaJ1e/IJCJmEVZJLSokrYDg6y9qiaLybMw\nAx5ZdMEcdv14iIG+NBVVs6O2vuCSEM89EebF13p479aGWTlm3dwiLr3AxxOP/5LNmzdP6fPoPJ+y\nvz/OfTcMq+wQGJPWdshZFEX39d9N0uOtIZ9pY4lbb72VW2+9teDvdu7cOeZn1113Hdddd13B7Rsb\nG+3n7LuPsynrcVCIIHVdt5Sp4TC6rhMMBgmFQmdMxuOdLxvdnd2WoCtLOa3r1lQarH8AACAASURB\nVENdUWRXsDUdJBMJJHHsAyAgFU8g7LLPb6fHsj2vk8kChJyHoH+OJewKT97SLxaL5Qm6TCsSN51y\npdwHSlFxJclYlFQiynnnnsvqVatYvXo1y5cvoyhQhCDLCLYPuJpWiUVjWYYg4yukBUHAV1zBSE8n\nkUiEtKbhKTqzjlvpdBokCW9lNcnOPkzTRBJF/D5LBFhqv4qLi3MFgaaJqqpEYzHSqgoiaKrq1pc7\nnyFvfS3Rlp6Cn6l0Oo2qpvH4x3c/y3aUdOpqPaVFKHNKGDlW+L1zSMJyXZNQbBtUy3tdxDQEdB00\n3UDTDDTdQDdMypZV0nEyQWw0e+KRJQk3GfuaBI3nlWAqMnvemL20dWmZwvK1Pp78bduspoWvv3Y+\nwwNHcuwap4tsb2nHvnI6PY9nU+E90/E7+J/a6QnOEnIO8s0inA9ndgmTqqpu84fxSpjO5NyFvhCq\nqtLf109ACYxRTkszIGIHiUQSWRpLyEE5RDgyTFrNrl01bYctDd2wzy8rOZ7Xjof1RJFvkevYNbmw\nyxJ0Wenq/AYQmftu2mcXCBZXYegGw70dGUGeIFguV7JEIFTqKo2Djvgqe113ApIOlNcw2NHB0PAw\npiQhTViGNTF0XUfVdURZxldVg55MkR4s7D9tkbTdqCIUIlRSQrC4GEEAUc74hTspTE3TrMxNTSXJ\nkSjhzj40WyltApquk0jEkTxiQRMQ+2BW9sXWJJiYSJKAJAn45s9l4OigvVw9tWxMYZKWEZAwDYHS\nJRWkDImDrw8SianEkxop1UA38rl36iSteCXqVpbzu12zKxi7fFsZ7d2jvLV3Gj2iJ0FDXZCrNod4\n9D9/wsjILInGbEy15/FsKbyni0LH/p/a6QnOEvK4EATB7ZE8MjJCKpXC7/dTWlo6bvOHMz0fFP6A\n9vT0kEqk8UlWynoqgq3J4HRWkgs0bCiSSzA0nZHIgDsmTdNd5bYsK5YyO+/88XgCUZw4WyBLCl65\nmOGhSWwubZ9t2ePFtEtzBDsqduqH3aewvWSuePwoSpCRgR53YiBgEW0kGkPx+V1id4iupCQ0JZI2\n5CKG+gc4dnA/hiyj6zNX8KZS1nqfKEt4KqoAkUTHOC5jZKWCsT4num4JvzwBL4qioCiW+Co7S+KZ\nW4WJSPjEaaLRCOHwKCMjw4yMDGNgIMqC6ybl9GTWNQ3NLoWzTGQsIpalTIo5sKCG2FCKxIBTViQU\neE2MDEmLyLKEPxQgtLCKzkNxRNGHpkkkEiaRqM5oWMuQdNpA06dO0ovXl3O6U6WzPTV2EDNE00I/\n9QtlHv9N26wdE+CjH1qILHTx0EMPnfGxJlNZO+vS4/U8norCe7a64b1bKes/Vpwl5AJw1mJUVSWR\nSOD1eiktLZ1yCdOZntuBkyJvbW1FS6kU+0NWSmoW+jRnSp7GEmhAKgIdhsJ9dpRkNX231Lfju2zF\nYvEJ09UOijxlDA1OLOyKRqNommGvH9tELOQRsQ3LFMn6WaCogtH+bnuNzLI4TCTi6KZpdWVy9nFe\nJgVIumQMSftKK8CEVHgYFHlMGZMVSU++zmSaJmk1jaBYmQlRlvGUVZDoHHs/XDImqzzLtPpXC0pe\nO0hBQBJFd33ZGwjgm1uD3jOKR/GAKaDrBoIkIHvtsi9HHW3omOggmIi2aYcsWxFx/lvtb6zCECSG\njkwUIU6FpM2crStX1tB5Io5gyLaPcSlFRcX4/EWIkg9Nl0kkTaIxm6SjKvGEQ9JmQZKuWxJELvby\n2guj00p3T3xdcNmVpbx9qI8TLeEzOVgOioMKH71uLi/sfHRcR6l3E9NVeDs9jxOJBKlU6owU3vnP\nk0gkcjZCPgsL6XSa0dFRV7XsNH+YTgnTTJAdITvRoZMij0ajGLpJkS94RlFx1skKljxlfi3iI8Dg\nSDeGaWZ1Yhr/HjhrU0qBmuH8r2ixbw7Dg70Fo0zH6MJpAqF4nGzERETsrCkLBEPVDPV1YxgZchwN\nhxGkTFYh3/VqLEmbY0i6vKKKQEkFZjJOqLx8HEOQ6KQknU5bLQ4lJbNU4K2eS/x0t/swM7FKmvJT\n9AK2VaWhF2wCkQ9v3VwSbb3W0oooICki/iKfu9QhiFIm42AKmIZ1Tw0zU7udD9Ej45lXw8Ch6bq5\nTRw9V6yoJq0LtL0zhGkrs2VZwuvxEPD7KQ4GLZIOFuP3FyHJPnRDJpGEaMxgNKwRziNpURJZfHEl\nu3ZFSCV1zmRNOhvnrQ1SWi3w0K9OTPMeTIyrNtezdGGKf7nvWyQSMysDm83GEtkk7fV6XZIOBAIu\nSYO1pFaIpJ0GMpN59OdjZGTkbIR8Fk7da8z9EDprX78POF8gp6Y5mUy6KfKRkRE8gtcWx8wOCpU8\nAVYZi2ESEIIMjfTZgq3JfYoTibgl6JrAc9pB0D8HTVUZHcl9qGf3RU4kEkiKJWZKJhIuyUXCEZLJ\nFIZupbEdInZctoLFlWjpNJFhJ4IzGRkdRfb5KQi7FnkqJO0JziEdHkWSZMuBLavWOFgcnCJJxyBP\nDe+rmoseS5AeHim4Vu5sqem61bjDK09pguhtqCUdSzHU1oGJji/gQZDs63WaJLg1x7JdHiOCKWDo\noGsmmmai6ya6kSHposV1DJ4cQUtMtwYz++GbG0F7in0UzZ9Dy94Ba35gjn0JAsiShMfjxe8P2KLK\nEoLBYvz+IHI+SUc06leXMhQ22PHMIOGohqabeeOZPklLksC2D5Sxa083h4/N3pqvKArc9pmlhEcO\n8NOf/nTWjjubcJYbHJL2+/1jxGOQmaA7JB2Px12Szl6Xzk+vm6Z5NkI+CwuiKFJaWup2YZqtdZLJ\nYNrKWbCI0uPx5KTI+/v7UZic6KaDZDLpdnmyB5EhAwGKlVLC0aEp+TIDxGNxTBNkOTfiLkTjlmMX\nrmNXdjtGiyQkwpGIbQhiImdFk7pd1hGORBgdDTM6Omp1NEqlME2DQLAC04Bhu9FEKpUikUzi8U+j\nK1MBkjZ0HU9JJXosipZM2ClfE8NwImlpUpI2TQPNMDBFEU3V3Jdcbo05frozJz2dPzGIx+MgkhNd\njwfDNJEqyjAEkeTpXrxFHsZtq+SUJDnWjpOQtHfBXFJpk+79Paiqjm5MFmJmM9z4kXLFeXNpOxQm\nGdVyJ0j2LhlyzvIfF3DXQy2SLraEb8EQfn+QksoSqldUsHN7hCPHE7y9P8z+Q6OcbIvQ05tkNKKi\naVMg6TysvaCYynqRn//y2KyKnuZWB7j5Y7XsfO6XvPLKK9PefzYj5KkiW+FtvQ9+Vzw2mcLbIWdd\n10nZxjujo6NnRMjf+973mD9/Pn6/n4suuog333xzwu0feeQRli1bht/vZ9WqVWPU7o899hhXXXUV\nlZWViKLIvn37Zjy2yXCWkPPgRMSiKP5eSgBUVSUcDrspKictlB0BdXd24xUmc6uaHhJZTSVyojK7\nNjGolKCrGsORqaUmY/E4oqiMawiSDUmU8cshBge7slTjVjtGURRJJpKk0yqK7dAly7LdGzhEKFRM\nIOBHljOTCV23xHejo2EikRgmPo7s30Nffx8jI6PohokyXoQ8RaRVFV9pFQICyYFe14kse6lhIpIu\nKS1BlhVEWbZsLl2YCJKEXDqH4ZNtli1lOEw0GiWVSrkPrGQigaZryL7Cyn4nitdt61RN0zBFEV/d\nXFKn+qa/1DEBSXvLilGqKxg8OEAqYZKIakQjKvGYSjKpZZF0PptNPIaqVXNRTZETb+a7xAm2oG8s\nSTOGpK3zSZLoksPqzfMIR70U+xfQ2LSUUGkDaa2Url6BYydTvH0gzL6Do5xoDdPdk2A0rKKqE5O0\ngMB7P1jO24f72btv6t7sU8GVm+rYdInE/d+/l+PHj8/qsX+fcMqvJlJ4O+9ZNBplwYIFrF+/npKS\nEh566CFeeOGFaavOf/nLX3LnnXfyta99jb1797Jq1Sq2bdvGwEBhzcOuXbv42Mc+xqc//Wnefvtt\nPvCBD/CBD3yAQ4cOudvEYjEuvfRS7r333nd9onOWkMfBmTSYmAp0XScSiRCJWHWSjlF5oTe8s6OL\ngHf2jMxNwyCZTCGLitUazswvJQK/FHSFXVOBY5k5pfNjEvCUM9DfCQKZvsj2gzUajVok6vWNWScW\nRRGPx0swWExpaSmlpaW2VanfnUwFAhWMDvbQ3t7O0aNHSesG4bDVizqdTsO031OTdDqNp7gU2RMg\n0dfjml1YLwFRFCYkaU1VUXUVyWOVismKbL8sr3F/1VzU7j7HhgNd04gnEoQjEYZHhonGYyAL6LZF\nqabr1svxjVZVt6mGiYkoCUiyiLepnkT7AEZqFiz+ski6aEkDoy2jFBeFrGjUV4Qs+TB1iVTCJB7V\niIQ1YjGNZFJHVQ10feJcsFLkIbS0miO7pmKtWoikBVf3l03SdcvK8FV4eWVHN+Xlc6ivb+Ccc5ay\natVaVqxYTdP8ZZSWz0Mz5tDdL3KsJcU7ByO8c2CUEy1huroTjIymSaezM2Ymy1cGaFwicf9/HCSZ\nSOf2Pj6T2ywI3PqpZSxuHOUf7/3auG0AC+G/I0KeDvIV3s6yoKIo/N3f/R3Nzc0MDQ1xzz33sGnT\nJsrKysb1oC6E73znO9xyyy3ceOONLF26lH/9138lEAjwox/9qOD23/3ud3nPe97DHXfcwZIlS/ja\n177G2rVr+Zd/+Rd3mxtuuIEvfelLbN68+V0P0s4S8jh4twg5u6ZZ1/WctoyFzqdpGn09fdNruzgR\nTKsBhNWO0VJMCwWsNkVBxE+AodHJCdkpD5vK+rFDUMX+OURGh9xesdnXHYvFECSnZ/TYdeJ8CIKA\nx+OluNgi6crqJhQMaqoq0U0TyWtFx7qmk4hbkbRTZzwVktY0zRJiyQq+0mriPYUV4hORdDKZAkFE\nLNCmUBAE/HNrEZJpihAoKSl12yY6SyeiIiHIVtMOw8z4RzvdmgQRl4RFKWOY4musx1BN4m1T8w+f\nKorOqScV1xhpHUCSZTxeL/6AnTK213UD/iIUh6STJomYTjSsuZF0Oq2PIenqdfV0n4oz2DnTbk1j\nSVqSBM67sp633uyluyNs3zvLR8zr9VJWVkZdXT2LF5/DqpVrOXfFGprmL6O8ohGdCnoHJY63pHnn\nYIS3D4xy/GSYzu4EI2GVaz5SQdfgKA8/3opp9xx3jFScXtwuSU/jUaIoIn/zuXMJ+lv56lf+hu7u\nwmVx496FP1BCzodpmoiiSCAQ4JOf/CRf+MIXUFWVkZERDh48yM9+9jNuvvnmKR1LVVV2797N5s2b\n3Z8JgsCWLVvYtWtXwX127drFli25Tb63bds27vbvNs5aZ+Yh2z4TZo+QTdPqBmW1JxRcpeJ4ZiQO\nhoaGSKdUivxnSMimlUrVdd2yTTRAkT0TpjIDYoiB4ckfBIlEAl03CiqsnXM7KVWwrjMUqMAY1hke\n7qGyMteGcHQ0jGRH2wJjJwuTobikBlOHVGwYj9dLcWUlkuKxSo7SacsDWrcmArqmk9ASJMioWmXF\nEg4pitWkIp1OgyAiiCL+smoGWt7E0DTEqdgcYqW7VV1D8o1/v72Vlm1krL2DkpKQu4as6zqSV0Hx\neYG8rk3ufXVETyYIlvpJsG40ckkxUkkJseNdBJfUT+s+TgRPdSkEg/Tt66L8nGr7Pc68v7Ks5D5d\nTMtqVc+qe06rGpiW+lmQLLFUcEE5ht/H0V29XPyhBbM0WoFzLqzinadPs/M37fzZn5/raiaMnO+b\nYE/uPHi8Hrujj/W9SadTJBJJEok4iXic/qEoam8KAYMFKxW+88B+BgbTXLCugvlNIWqqrOUW0yZ+\n+8a470tGrCeMm8kvCXn4uy+u5O5/2MdXv/J/+cIX/5ampqYJr/SPqbGEg0I1yIqisHz5ctdPeioY\nGBhA1/UxbROrq6vHLSXr6ekpuP10shKzibOEPA5mi5BN03SFDKZp4vP53FRNoXPmn6+vrw8trREo\nmXnK2rQ9r53ZqKaqgJAr6iqAoFJCR/gkqpZCmaDtYzxuKawLbeNcjaOmdO6r3xsCQ2B4KEPITp1j\nPJHAWzxn3Ih4Mnh9ISTJS9epE4jlTW77RkEQ8Hq9eL2ZcZqmQTqtkrbrsgE0VUdT4/b4TTRdQ/RY\nhO4vq8HUdJKDfQSqaycdi2maJJIJEEWECRT7oseDZ04lifYOSs5bbk3ebK9qxafgZgrEjNjLtE6Q\nS9BGhhjBRBDA21BH7FgLpmHMSg07WPcysLyR7neOcc6frESQhYknT4Lld57d6hN7zVvXtYw5iaER\nWjaXN59toXJ5GYGgjD8g4/PL+P2y60w2XUiyyIrNdbz+2Cnee90i5lQ6Ij8zsyzikDRjo1mvx4vP\n58tqu2cJMeOxOBWVUVqOHOTHD/ex81WQpS4Cfp0FjQoLm4pY0BRkwfwQc6v9CIKTJcqkvwVHROj8\nPYuky8u8/P1dK/m7fzzAl+66nVs/+3+nlML9Y4qQs+H0Qp7tc0znfkx3+9nEWULOw2xFyI5y2ooe\ndVdgMlEZVSFC7unpQU2pFHlnECGbuZ2gHFORZDKJJMiTcl1QLkFPagyHB6gqrxt3u3g8juSmmO1T\n2w86JxVsEYnlfhYOW4YKkhHgdMcJFixc4+4Xi8XQDROvL8BMyBhssghU0t/VTn39ikm2FceQtGEY\nqOk0qXQaXdMtkhFFNF1HDIQwTYmB1hbKi0rweD0osjIuDyWTSTRDR/ZPLirzVdcRaTlAJBxGNw0k\nj4zkcVTrWaIisvlicpL2NtQR23+AcGs/3upSRFFAlET7Nf0MhIPiFY30vHGQoeO9VCyfy7TfL2Fs\nJyMwadq4jLff7CB8SsG3OEj/SAzDTGCi4/WJ+PyiS9I+v93dbApYekk1+585zW8ePcHHP7PSGYS7\nxJAZgjVRsBzirCyNiTXZyQzdso61BHul3P6lUv75bw+yfvUWrti0mVOnTtHW2soruw/z+G87EejG\n59WZP09m4fwACxqLWTA/RN1cP5JD0tnf/awoujTk4etfWs33f3SY737nSxw48BFuuOEGAoGxlQN/\nTBFyofVux8d6JoRYUVGBJEn09uYuz/T19Y2Jgh3U1NRMa/t3G2cJeRycCSFrmuZ6IMuyTCgUmnIX\nl0KE7BG8BZtAjAtz4paMluf05MfLOHb1TkjI0Wg0o9i2ScO0C0ezr8nEdKMBTBO/UkLX6Rb2vr3X\nFehYoiTxjGuuA8FKek+dwDMDdbUoinh9PrxeL6PhsEVcsiWAM0zwl1SR7O911czZcAQqsiJj6DqJ\nVApRUSaO7OzUqVJVg3rgLZL9fQTm1eWtNwu5QZvp/G9ykg7Mq2NU8ULXCL6GuVa9t6qhpVQr7haZ\nPkmb4KkqQSovpfftTiqWT54tmBoEQrWllCydS8f+YTa+/0LAJJFI2DWtceLxKP0jUQwzAeh4vCK+\ngGhF0YHxSVrxSKy9ppFXf9HChi3zaFqUX1qTaWsIuB2RnKlOTiSNtZbv3PSqGj/XfryeR/79ac47\ndyXXXnute9RIJEJrayttbW20trbyu32H+a9n2xHoxaOozJ+nsKDJz8L5IeY3FtNQF0CWcklaluF/\n//lSli7u4icP/Qd7dr/GjTf9Oc3NzX800fB4yB7/mfRCVhSFdevWsWPHDq655hrAuoc7duzgtttu\nK7hPc3PzmN9v376d5ubmScf6buAsIY8D58ZPpxZZ13W3WbgkSQSDQRRFmfKbWIiQu7u78ZhTLHky\nnZaMltCnYEtG0yQWi6PIAScLOsF4RAIUTai0NgydaDSGx1OSWz6VT8Zm5lQlJSFMEyrNekb625FF\nMOy2e7F4HMlbzMjoqHsORbF6AltdtaZ2L70Bq4mFmoqiTKcGOQvpdBrdNJBlrxVFSSIiIkUVtYx0\nHqA4WISqaZb7lmHdc13X0HQNM2E92AVZsuYfmjbmc2DaQh8nxazMqURSvOgDg4jzx7b3E8b8Y2ok\nLUgS3ro64ie7qb5sjRtJO+07ndeUSNo9h6W2DixvpOetAyz9kIY0BfewqaJ+wyKO/8cuuk70U7e4\nikCgiECgiIoK+7pMg0TCcoeKx2PEYlEGRmMYhkXSilfA7xfxBZQckj7nomoOv9jNo784wh1fvjDz\nnthr3E66UhLzm7YUiKTJvH+maXL+xXPpaAvzwx99B6/XS3NzM5IkUVRUxMqVK1m5cqW7ZywWcwm6\ntbWVvUeO8pudbQhmH7KcpqlBYWGTjwVNIRY0BWmoK8KjSFx5RR2rzyvj3356gu988695bOF6PvSh\nj7BmzZoc74Q/BpIuFOycaWOJO+64g5tuuol169ZxwQUX8J3vfId4PM4nPvEJAG688Ubq6+v5+te/\nDsDtt9/OZZddxre//W2uvvpqHnzwQXbv3s0Pf/hD95jDw8O0t7fT2dmJaZocOXIE0zSpqamZ9Uj6\nLCHnITtlXYggC8HpQZpMJhEEgaKiohl1ghIEYcwEoL3tNH5lknS1mZnZO+vEhZo/gGWUoak6fu/U\nWkYGpBCDQ+MLu2KxOLqmoxR5x6wTu2uZ+dkG+49QURXSgER1dSm1dYtJpVLs2fs2cqAYUxDde6Gq\nqmuc4sByCnL6Geddp2kiK8WIokx8qJdAadWUrjX/GMlUCkGSxkS3gTm1DLbsJj08iL+yGp/P5+yC\nYVitMS0TDxFBGVvr7UIQsCy6RfsWCfiqakmd6oL1q6c0zKmStG9hI+EXXiY9GkUJFSGQiQAVRZkx\nSRef20jXK+8wcLiH6lWzJxorX1KNVBFk73OHqVs89v0TBEuZa6VtLZY2Tet7aEXRMWLxGAM90RyS\n9vlFll5Ry8s/PMorO06zYUsDhmG4nzXLCGWq2gXB/i/j+f3BG5aRiB/kBz/8NsHg3axevRpVVXMm\nqpJk1aevWLGCc8891/1dIpHg1KlTtLS00NbayoETx3jmxRZMYwBZStFYr7CgycuCxhDXXzufbZvT\nPPL4m3zzG29RW7eCLVuv5sILLyQQCFjLUlm9j/8QCXq8lPWZrCFff/31DAwMcPfdd9Pb28vq1at5\n5plnqKysBKCjoyMnW9nc3MyDDz7IXXfdxV133cXixYt54okncsRkTz75JDfffLP7bPvoRz8KwFe+\n8hXuvvvuGY+1EIRppGT/eBYnzgCOaxRY6ROPx1NwrQYyyulkMmkJfvz+M+oEFYvF0DTN9XE1TZNr\n3/9B/EOlLJ17buEx5Am2JmvHODw0xKGDR5hTXItoK4cnQl+yk3aOc/1Vf4knr6zJNA26OrtobTtN\nRWWjveYlZImKsjfOIuSs8e0++RjnrFrHinM3MjA4wMmWNspqmrJEbwKGoZNOp0ml0hNOkDweD16P\nB8M0iERjnDqxA09NOU3rr5zwGgshlUoRS8SRff4xhGwaOief+zkV68+nYuVau6LFdMkvGouh6jqy\n32vdXzOT7nSiqbHrhdafseOHGX7ndepu+Riid+YtHvOhp9L0/McvqHvv+ZSvX17wPXIUwNn/NiGr\njMdAN3QrA2CrhwUR+n6xk9KgzupPXYzX7xm/reM00bmrla4n3+F//f2fUFY9s4e09R1N2JF0nFgs\nSiweZe9/Haf1pV7Wnj+X+UsCzJtfwrz5JdQ3hfAHzqy/uaYZ/Oz+Axx/R+Evbvk8W7duHTPRyW9r\n6JCnMyFwfpdKpWhra3Oj6bbWo3R2tqBrMUQhSUOtQioVp28ghUkxuhli/QWbuPDCizj33HPdyaJD\nzM45/hBIWtM0kskkgUDA/b5/5StfQRAEvvWtb/23ju1dwqQ3/GyEnIfJypAAt3wmkUhgGIbr6Xqm\nDSjyzxcOh4mEI1R6x6YvxxNsTYZEIoGAiCRKU4r+g3IJRlJnONJHdXmDfWrTqrE0DaKxGJLkRRRE\nbLrJG2dGaOQST/bxvXMYGrS6M0XCEUTZm3cfTFt45XMfLmCtNVslTClHN+aWNOm6jikI+AKVjPa2\nW6VD0/AkdyZaglRY1SuIEv6yGmJdHcw5b411fgEM0yAei6MaWWQM7nXnuJgVImnDwFNVi5nWiba0\nE1jQaKXJpTN/eEpeD57aWsIHTzHnguX2xCn7op1JhZn9I4AcT/cxkbSmE1p9DoO/foXOd3rxlHiR\nFBHFL+H1e/D4lRmTdM358+jYeYRdT77Dez+9YUbXLQgCfn8Avz/AnDn2dZkG8+ct5qGBZ4mPVkF0\nKS89dYxkqgPdTFBeKVHb6KGhKURDU4j6phCBoqmTtCyL3PTZ8/jVz49w3/1/T2dnJzfccIPbKtPB\nmGyE3cvagaNHWLJkCUuXLnW/E+l0mvb29qyU9zHE0eNoagyREXb/7hH2vPUUJsXISgnXXPMB1q5d\nS11dXY7mwYnW/7tJOvuckUiEefPm/d7H8IeCs4Q8AQoRsqqqrgeroiiu7/VsIft83d3dqCmNYHko\newN024AAxgq2JkM8HrcU1lOEXypC0GFotI/q8np03bA7KVlfZmv92Fcw4nJV1k4au8AQi/0V9A4c\nxTQNRsMRPN4ia1t3GdReEyWbK6xsgN/nw+/PrK/rmk7SbgUnSDKBYCX9AwcZ7u9F8dlpf8GKpD0e\nz7jvWzKZRDdNZM/4D+HAnFoGWnejq1Y9ctr2zDYFAdnvm7w8ZxySlkvKUIpL0E73YDY0YKR1NEyw\nTUZESbTtLKf/8Awsnk/4xZdRI3GU4sCYdLdL0lnr2pmhZd6N/HR39bplxF45QHBUYv7apcRicWLx\nGLGBKGE9gYkxI5KWFIn6zUvZ//g7rL/qXCobyibcfiowTYsEQ6VBrv6LDTx731tcsL6Zf/j6N+jq\n6uLkyZO0tLRw4uRRXv71YRJJm6QrJGqbPNQ3OiRdTFFw/AyGKApc9/GlVFS389gj/8qBg+/wV7ff\nSX19fdY2mXvoIJ+ks9PdgNt5bdGiRSxevNj9naqqnD59mhMnTtDW1sZbb71OJNyPlu7nV4/+O796\n9MeAAvhYs3YtW7duZdmyZRi21aqDbJLOjtjfDRQKCEZGRjjvvPPelfP94MrKbQAAIABJREFUMeAs\nIU+AbELWdZ14PI6qqkiSRHFxcc4XabbPBzYhJ1WC3uAYwZYoSUj5gq0pIBqNIUtTT4UKgoCfIAMj\n3aiqZp1btM6dTKUsgZgik0qm3DZ/2enp8YjYQXGggo7wfjq7WkmrKqGSIjJrc5DZ2RxD0q6+yIZo\nl9CIkoTi9VJcVovYJqJFBzOEbEI6lSadcprWW8dXPJZwzDSstWNxPDGePQb/nDqMY28Q7jqNWDYH\nwzQQFGVCEp8UNkkH6ppInm4lFAq52gDrpaGldQxzZiTtm9/AyAsikaPtlJ+/tNClZd43ZzzkrVUV\niKSRJYrOW0Dr746x8n0XU1ZW7gjprdS/3UggFosRnYikA54xTmZz1zfS+eJxXn38bT7wvzfN9M5i\nCe6sUibLRU2icXkt517VyL/9/AfU1dVx0UUXUV9fz2WXXQZY5NjV1UVLSwstLS2cbDnGK785ZJN0\nktI5AnWNHuqbQjTMt4g6m6QFQeDybY0sXFLGz//1df7qjk/z/qs/woc//OFxl8EKkXTuZ0B3ew87\nkCQr21VbW0ttbS1bt27llltuQdM0Ojs7OXr0KM8++yynT59CIMGePbvYs+d1QEQQJEBk48aNXHHF\nFSxYsKAgSWdH0Rn1+Zmh0Bry/+ROT3CWkMcgP2Wt6zqxWMxqVyiKMxZsTefcjjiqp6cHGQ+SIFnN\nAiYRbE0GXddJJlME5BLGPmnHg0lQKqFvoANREBAl2X3YRqNRNE3D65Uza+n2XpJk9bLNb0mYj6Cv\nHFOHjvYTIFdN4Ic9OUk7JiyCvY6uePz4fCWokQFqFmVm3ZqmkU6nUdMqDrE76W5N10CUEDExVS1T\nppVzPhPRX4wgehjpOEVZRSWyxzuj96QQAg2NRE8cIN3bj6+mypp4OeIwcqMoTdPQs0haEAUQLcFV\nPklLPh+e2rmMHmjNIeT8qDjjIuXe+Zx/FEp3l65bQudbh2nfe5x56xa7imTFo1DmKaO8fCKSjuSR\ntIzXr+AJePD6FRq3LefIg2/RfriHectqpnk3rfph3e6PLYmOSM+6qouuWclIX4RvfOce7v37f2Tx\n4sXunqIoUl9fT319PRs3brSOZpp0d3fnRNKv/fYw8UQnunmS0jkidY0KdY2ZdHdDU4j/87freP7p\nNh7/zffZsfPXvP99H+Y973mP62E/EZwlqWwxkkPSqqpaTnJZSKVSbn13Q0MDjY2NXHmlpaPQdZ32\n9naef/55nn32WQxDR0DnxRd38uKLzwMZi9rLL7+cTZs2MX/+fHeZLntM+SSdLeicKvK3d5y6/qfi\nLCEXgKN2dsUshlHQ6vLdOG82Ojo6kHXFSsFOY514PCQSCQzdQPZNsQmEXXMZlEsZiHeT0uL4pWI7\nODKJRiP4fEWUlpblrN8CVg1uIpHTaF2WZddIw3nKi6JMQC6lp+cU8xbNnyap5ZJ0Op1CNwxkbyaN\nHSyuIdLXmZN5kCUJOeCHQMatSdd0otEoCCKikqmpNu213pyzCnbJz5xaUkP9SLMovgLwVlYjyl6i\nJ1vx1eQqjAVAEsXCJG03l9B0HT2tFSRp/+IFhF98mfRQGMVeCsmPVKaoL875h7+iFE9jLSde3E/T\n+iXucXMdqcYn6WQqSTxmCa+isWhOulv0KWilPh669xk+fOcWahdW4g1Mfs9N08RwS5lEJMmpKc4a\nuiCw9aaLePyfXuDLX7uLr37pb1m6dGz2IHt7JxLdsGGDe57u7m4rij55kpaWE7yx/RA7Yl3o5klK\nygRqGxUamkK8/6P1HDvYx/97+Jv8569+xsZLt7F161YWL1487WeLM7F0vKBFUZwwknYItLGxkU9+\n8pN88pOftO+RwfHjx9mxYwcvvfSSlUUAnn9+J88/v5MMScOGDRvYtGkTixYtGpek89ekx7uu/JS1\naZpnXPb0x46zKus8mKbVIDsej7sfmNLS0llJ0UyGdDpNNBolFAqRTCb5/J1/zanXu7hgwSV5kdrM\n0N/Xx7EjJ6gqbQBBGNdK0TXDt8s50kaKvbFX2HTJB6mvWugO452396FqEsXFc9z0pvO8M01ctyvD\nJulCkBWFzqF99CTaWHvpTW7LxWnDNAlHIuhgRas2RgZbaW99keXvvRGPPzjuhzgej5NS08heH4Ik\nZupLDcczOqOMNrEePuH2I/Qd30X9n96AdIbtHfMx8NqL6IkBGm/80xntb4Lb6EBz/9QwVY2+XzxC\n8YoGyi9dieL3oPg8KH7vlB2vxkOstZveB7ez9bPvo3ZFkzUOe/LmCtjyFOZuba+Q3b3JJulkkng8\nRjyeoP90D3u/9yylgofyuSUUVfgobyiiqnEOVY3lVM0rzyJps0Ap08Tf31Qiza+/9zJ6t48v/81X\nWLVq1RndC9M06enpcUn65MnjnGg5RDQ2hG4mEcQkqpZAFDzIYhlFvkqufu8HuOCCC1i0aNGEzxtN\n03IEpRMFCvnpbifAcJAf5TrQdZ1jx46xc+dOXnrpJaCACt/+e3NzM5s2bXKFZ25DDRuF1qQFQSCZ\nTLrBjjPW5cuX89RTT7F69dTK/v7IMOkX7Cwh58E0TQYGBtzZXSqVory8/PdyboeQHdz0Z58gOFLO\n0trZETm0tbbS09nPnBLLVcki5KyaSzcaNMdMAPaMvsiy885n9TlWVBCPx3nnnX0UFVXi8xVNKawy\nDWtGnUqncmwIByOnaRl+g2XrP4qs+F3RldXzeGokkU6nicZiFqFmPVg0NcmhvQ8yr3kr5Q1LskcD\nJhimSTweJ62qSF7vGL/p7ElGtgmEaZqkY2HaXn6Ysksvw1/faLljiSKCvaZ7JtmM+OlTDLy6naZP\nfgRP2exEDA5J9+54Ee1UGw0f2UYinbRsIjEQvQqyT0bxe62Xb+qmNmB9d0795Glq/DJb7rhuApKw\nRjNdkj787G66nz7Epz72CdLpNEePH+V4y1FiyQiqmSJY6aOsoYiK+jIqG0upnjcHf9DHVD9Dakrj\n6R+8wsgxlU/d8Odce+21s5oRM02T3t7ezJr0yeMcO3HAJWkAUfAgCUECvlKuvfZaLr30Uqqrq119\nSTKZdI2HJrPinWgcMyXplpYWdu7cyc6dO4HxSfr8889n06ZNnHfeeeOStHNOv20rKwgC9fX17Nu3\nj6ampmlfF8D3vvc9vvnNb9LT08OqVau47777WL9+/bjbP/LII9x99920tbVxzjnncM899/Ce97wn\nZ5u7776bf/u3f2NkZIRLLrmE+++/n0WLFs1keGcJeSZIp9PuemQsFqOsrOxdTVU7qR8nKvd4PESj\nUT72oT9jsXcltaWzY7iw/519pOImJUGr/sO0S6YQCiiiM6MDE45E3qaotpjNF34IXTfo7++npeUU\nFRWNMzb8BzB0g/7BHg70PMu8ZZsIlRUuefB6PXg83oJpR9O0+h0bCMjesQ0uju17nED9XOatvSLn\n567FqWEgeT2IojThh1wY8xdoe+k/8dZXUXXRRisS1TSb4ExMx8LSJmlRlGCK98rQNDoe/RmVl62n\nbN3sRAuOaCvZ20ffo09y0aevZ87iJhKJhLumG41FicXj6KaBKZiIXhnZp9gk7UHxTkzS0ROd9D28\ng6tu/xOqlxQo1xtvbDZJG3Z2Jn+pQBDA1A1e+d5T1Kml/PO3/onS0lJXeHX8+HGOHj3KsRNHaTl1\nkoQaQzPTNkkHqWosp7pxDpXzyvD6x093G4bBG/+1nwO/PcWGdVfwmVs+8676GpumSV9fHy0tLRw/\nfpxnnvkt8eQIpqniiK4EJDCt7kebN2/mggsuIBAIzPpkoVCttIPxSNowDE6dOsXOnTt5/vnnUVV1\nzLicf2/ZsoWbb745Z0IAFtGvWbOGBQsWMDAwwOc//3kuvfRSli5dOiXLYQe//OUvuemmm3jggQdc\nl65HHnmEY8eOUeFYvGVh165dbNy4kXvvvZerr76aX/ziF9xzzz3s3bvXNQa59957uffee/nJT37C\n/Pnz+dKXvsT+/fs5fPjwpPqYAjhLyDOBqqpu56FoNPqupqzzy6hUVaW4uJh9+/Zx+5//FRfP3UKR\nd+adnhzomsabb+7GL5cQ8FnHMw0DNz9YiIgB5zPUFW+hV+7kg1tuQZIUWlpaGByMUj5n7hmNS02r\nRGMxjvTuYM78pTQubEbXdFL2mvREsCJphXRaJZlKofj8BdP6Xa2vE053sXzbx8E0UTWNVCqFqmkg\nClZknCVUyo+KGftXFwNHfkdk4ASLPvoJRPvchmmtSetZqWLDJmkQ7M5PGWX0eEsR/S9sxxTjzPvo\ndRPeh8mQrZ520Pngo9Q1VbPqz/5kzPaGYWYZacSIxqLEEw5Jg5RD0l5kb6a5hmmanPqPX1Md8LD1\nzvGj5CmNO6tO2yHp+HCMV//pCS5esJa7vvBFtymI81nx+XzIskxXVxcnTpygtbWVYyeOcezkEeKp\nqBVJV/kobwi66e7KhrEk3Xagi5f+3x68yRAf+/DHed/73pdVB//uwjRN+vv72b9/P7/+9a9pbW1B\nN1LWOrgo25NoEQGR5uZmrrzySs4999xZDxqmQ9I5Dn2mSWdnp0vS8bjVOU0QBO677z6qqqoQRZF4\nPI4gCGiaxgMPPMDevXvZsWMHsZjVC9vv9/O+972Phx9+eErjveiii7jwwgv57ne/646joaGB2267\njb/+678es/1HPvIR4vE4Tz75pPuz5uZm1qxZw/e//30Aamtr+fznP8/nPvc5wPKGqK6u5ic/+QnX\nX3/9dG/ppG/QWVFXAWTbZ0LherkzRaEyKkmSGBkZwTRN2tvbMVSTgOcM+yDbiMViGLqBx289wLJt\nLJ30oDNzlSUpi5WsSKVIKkFNtxJJjFAeqmZ0NIxnJh2o8pBKWQ+aoLeK8FAXLBSQZJmALGeVhpho\nmk46nSKdzhgnWO5dKasLk2yJ35yJRfbDyV9cTV/LIYb7exAUu2ZaEBE9HkRJciudc4jYgVDgr1kf\nh6KqeQyf2keirxd/ZbVbWyzLMrIiu/s4vaidVoOarmOomlW+NA5JB+YvZHDXTtLDIzNKW1tBZ6ai\nOFu0Vbx8Cd2/e5MlI2F8pbkuWKIoEAwWEQwWAZbloK4bJBJx4naNcSQWIzEaJuaQtE9G9nlQ/B7K\nNqym6+EdtL1xhPkXLZv2uB24qeusN6G4ooS1N23mtR88y7//+7/zqU99Kue9dibT1dXV1NbWcvnl\nl7vVEp2dna46+tiJoxz/zTHeSbWhYqW7yxuCVDfNoXJeObWLKvnoV7fx+pP7+cEv/pnHnvoVH/qT\nD7NlyxaKi4tnfE1Tu26BqqoqNm7cyPr16zFNE6/Xy9DQEDt37uS3v/0tyaQleHtt16u8tutVaz+s\ne7Vhwwa2bNnC8uXLz4iknZrk7LR4IZLONjNxSHru3Ll8/OMf58Ybb3T30zTNav9qV4wYhoEkSQQC\nAT73uc/R3t7Oyy+/TEdHB/v27WP37t1TTsmrqsru3bv54he/mDP+LVu2sGvXroL77Nq1izvvvDPn\nZ9u2beOJJ54AoKWlhZ6eHjZv3uz+PhQKceGFF7Jr166ZEPKkOEvIE+DdIGTDMEgkEgXLqDKNGExO\nnTqFj6JZm/VGo1EwBSRRttdv7WsScCO0eDxu90q2YAIexWrWHlRKMJMmQ+E+PGIRqqoRCpyZkMlR\ngoqKl2J/JcPhvWhqClnJTztnyj4y5ZtWe8tINIogSgg2sTqRVDZ8RZVgQHiwi5KGJZawxKmXds/A\nFOav2Rtb8JdXIcpeYh2nCFTV4JRf2UO0BWBZpSs5JJ1VvmTfC9O0SVoQ8FRUAxLDbx+gcmMz4nTc\nxshST0NGdGcjtGIpo2/u4dQrb7HkfVcUOEIuJEkkGAzmlOnouuGKrtxIeiSMYYI6p4zt3/4Vaz94\nMVWL6iibV0WwcmZt9bIhCFC1uI6lH7mYX/3ivxAEgc9+9rOIoujeT0d9nBm7RSo1NTXU1dXlkHRH\nR4crvDp24ijHfn2ct22SLq70UTavmHM21nPqYBf//ONv8rOHfswVG7Zy2WWXsWLFinclc+Z446uq\niizLrgtgbW0tN9xwAzfccAOQeU5s376dZ599FqtdpMnLL7/Eyy+/RPYH9ZJLLmHr1q2sWLHi90LS\n2ZF0viNYtj2xowwH2L9/PwAlJSVs3LjRLTWbCgYGBtB1fczyQnV1NUePHi24T09PT8Hte3p6AOjt\n7UUQhAm3mW2cJeQCeDci5Gzfa2BC32vTNDl5vIUiefZm4pFIFFGQs9LTYkZYZV9fwB8gKSZJp1Iu\nUaXVNKpqPdyElMS+Q7tJ1goYBihjiHN6SKfSmFgmDcX+Ksxhg0i4h7I5jZPua6lwUyBYrRLJeq/y\nX7LsxecrJTHQRahuMVZjKdFO+zF1Ii4AQRApqmggerqNqnUX4ijTc01LxiNpEVku7NSk2baUgbom\nRt8+hKe2DkFREH0Kss+L4vMi+bxjCKFQVFzo8kRFIXjuctrfeIcFVzSjzGByJUkixcXFORGjplmZ\nn5HyKg7f/xBDL7QS39PLUT2N4QF/bSklDRWUz6ukrKGKoorQtIVjum5Qv3ohpm7w2CO/RhAFPnvr\nZ3N6Whcy0yhE0nPnzqW+vn4MSWdH0icOHENLSQjo9Me7+eUzP+XJ536FXwyy+fItbNiwgRUrVsxk\nTXEMnB7qjjf+RN3iBEGgqamJT3/603z60592r7ulpYXnnnuO5557zv3cvfrqq7z66qs5+19yySVs\n2bLljNPdUyXp/CWoPXv28PLLL7NmzRqOHDnCt771LZqbm10fhtnAdI81le1nc3z5OEvIE2A2CHk6\nvtdOqlXXddpOthHyV874vFkDQNM0wqNhPLJvrPLXeXjb4i6f14fP63UjKk3XSacsUi4SionEhhgY\nGECWg4yOWC0SRVHE6/WieDxTrswyDINUKo0oWR9Bj1yEIviIjHRNSsiGYRCLxVA1zao5zlN55n9Z\nTNMkVNrA4OBxRMd21DQxBUd0Jbmq6MmcxQohWDWP7gMnUaMRlKBFTrlEn0/Spkuc7h+Ck6zIJWnx\n3FV0drVR7y9CLi8jGo0RGY6SMEYxTBNBkRF8HhSfF9nnRfIoVvo7Kz09HkpWnUvH2/voeOMd5m+6\naHoXPQ5kWSIUKiYUKobrriKy4y2+fOcXCIVClnDpxHEOHz9K66tvccRQMbwCgTqHpKsom1dJoKy4\nwHuIW8okCBahLrhoGYpX4dGHnqKjq5Mv/PXfuOKdicw0pkrSmzZtctc4s0n66PEjHD1xmKQR46md\nj/H08/+FJCh4RR/nr1vPe9/7XlasWDEtQdJ4UfF0IQgCCxcuZOHChdxyyy3uz1tbW3nuuefYvn27\nq24uRNIXXXQRW7duZeXKlbNK0s4SnWEYyLKMKIqcOHGCH/zgB4yMjABQUVGBoih87Wtf40//9E9z\nOi5NhoqKCiRJore3N+fnfX1944ryampqJty+pqbGVcZnH6Ovr481a9ZMeWzTwVlCngBnSsgz8b12\nHLqikRgN/sUTbjshzEzziZTt7+zPFqWYps1jQg5RZH6PtTYoSQQCfhACpJO1RLVDCCL4fJnUpZOG\nzzYBkWQJr8drEUuB73UiYbl6ybLiXnext5LR4a4JLyujjNbHlDiNB0EQKCmfx0D/QWQ9QaCsOmNF\n6YivNMsW1FJGZ8qWhCl4Rgcq6xBMgcjpNsqXjV+iJmT9z/n7ZCTtq6hGKiomfuo0K+x+uiYmyUSS\nWDxGPBYnEosSHRwlbhgYmIgeBdHrQfb7kH1eZG9hZzk54CewZDGtL79FwyVrkWchwstGQ/Ma9p04\nxX0P/Cvf/853c2p7R0dH3fKf4ydOcOjIEVpe/h1JIw1+CX9dKaUNlZQ1VFJaX4k3ZJUvZVyh7HOs\nWUSwooQ3f7Sdz9x2K5/55J+zefPmgtd7JiRdW1tLQ0MDV1xxhUvSp0+fpqWlhRdffJEDB/eTNlLs\nevNVXn/zNQRBRETC7/Nz1VVXceWVVxYkBtO0ll6yM2fT6aE+VcyfPz8nkgZoa2tjx44dbN++3bXK\nfP3113n99ddz9r3wwgvZsmULq1atmvYkwQlIksmku0QnyzKGYbjlTrfffjsXXnghBw4cYM+ePdx/\n//2sXr16WoSsKArr1q1jx44dXHPNNe65d+zYwW233VZwn+bm5jG/3759O83NzYB1z2pqatixY4fb\nyzocDvPGG2/w2c9+dlr3Yao4q7IugOw1jqGhIfx+v/vhmQp026XKqRcMBAJT9r0eHR1l7969fPGO\nL7Oxfht+ZZqpRDPX81qSJAYGBjh+9CSVJfVZJUpZkw3nM5CV3jSzjucgqSd5K/wCdRWrWdhwfo4S\nOa2mSafSOWtH+ZBl2V0vj0ajiLLHjZAB+sMnOR1+m3Ubb0aWs9Phpmv7mVbTgGiVN00rFWVwaM+D\nVC5fTc2yCwr+XtNyH8yGsx4tZJG0ZEfTeafufPO3mF6dpqs/OOUxjTvWrP+ZwMDbb5E4eYANt/0F\nst9v1eaKVo2uVd9pYJq4pXPxuEXSTvmSbpO0ZEfRTiQtCAJqOELn/3uY5VsvZuHWS8547PlIx+K8\n/f1fcMU5K/m7r35twu/B8PCwu557/MRxDh0/Qs9AL0k9jVikUNRQTuk8i6TL51XhL8mICtPxJG8/\n9hqjezq4eOUF3PTxGyd03JoIk9XpOiTtvByVsaZpOSRnmHpGLOhIrgSRiooKrrzySi6//HK8Xi+a\npqEoCj6f7/diQDQR2tvb3XT3RFUO69evZ8uWLaxZs2bcMTvPQV3X8Xg87hJdb28vt912G4cPH+ZH\nP/oRGzZsyJmAOEtN070XDz/8MDfddBM/+MEP3LKn//zP/+TIkSNUVlZy4403Ul9fz9e//nXAEnVd\ndtll3HPPPVx99dU8+OCD3HPPPezZs8edDHzjG9/g3nvv5cc//jFNTU18+ctf5uDBgxw8ePBs2dPv\nC9PpiZy/n7NOLAgCgUBg2r7X4XCYxx57jAe+9e9sXXTN9NY/CvVGBo4dO85Qf5g5oeoMiWWZgFhr\nyjDu5yUratvVv52yivksa7IFF9lrlFm7OyYg6XQ652FmYpVgIYhIigcr6rGde9QIB7ueYfGq91BS\nXo9hWG0eVdsS0hQEJFlBnEYqMBvtx14grSQ4Z9OHprR9psWgZomu7HtrmqYVmds1xqIoEeluoefQ\niyz604/jCc6uCleNx2h7/BesuGozDevPd8uAMrCV5fZ9dN4RwzRIxBNW56VYjEg0ZpcvmRgCiF4F\nyeshsv8g+vFjXP7Fv8BfOvPm8ONh5FQnx3/6JB/csJn/c+edk2aJsqPG4eFhOjs7aW9v59iJ4xw+\nfoSBkUGShopY7CFQW0KZvR5dNq+S0a5BDj7xBkJ/isvWX8o173s/q1atOuOI80xIeu/evTz99NPs\n27cvp4TLmjRb+9bV1bF161Y2bdr0rqu4p4uOjg53kuFE8tm4//77qazMLK/lR8V+vx9ZljFNk8cf\nf5zPfe5zXHfddXzjG9+Y9Wv9/ve/zze+8Q16e3tZvXo19913H+effz4AV1xxBU1NTfzoRz9yt3/0\n0Ue56667OHXqFIsXL+Yf//Ef2bZtW84xv/rVr/LAAw8wMjLChg0b+N73vnfWGOT3iWyP1tHRUWRZ\npqho/BIfx0QkW4wxnmBrMkQiEe75h3v43VNvc+niydWv9gByeiNnt0zTdZ09u/cgU0QwUJJZM3Yi\nP5hypKmmVQ4NvYVeqrDuHDstlDUGFxOQdDQaJZ1WERVbWe7+0rqPBzt/Q3HtQqrr19iHEmwfZnla\nKuNCGO4/wen2V1hx9c0ovsknWIVgGPqYSNqaZKRpe/lhSlasYM7Kdcje8VPFM0HXyzsQY4Nc8tnP\nAFZEjyBYfaizanVdZJV/ZZO0blhreW75UjRKLBKh+79+TcDQmHvBSopqqyhpmEtxXTX+sjNXRgP0\nHz7JqYef4ePv/RNuvfXWcY+ZHVUVihodJ72MMtoi6cHwMCkjjRTy4a8tITowQrRnlBKliKXzFrF1\n0xbX9Wq2MBOSNk2TkZERdu3axYsvvkhLSwtZRXc5qK+vZ+vWrWzcuPEPjqS7urpcgr755pvdaNEw\nDHeZLjsqHhoa4s477+S1117jhz/8Idu2bXvXhFF/wDhLyDNBNiGHw2FEUSzYlcWZyTtiBSeSPpO0\nUyQS4YaPfhzfYAnLa1dONtBxibinp4eOjg5rfTeeYk6oFo/idRcnhaxyp6kiGonQk+ykRzlN87kf\nHdvG0cz6I/9zJQhoqmUCIkoKkqy4OzlRp2GYtPW9TkxJsGD5e7JSxXbEcYbpPE1NcHjvL2m4aDPl\n82aWzhwLK9LRdY323c+RSvRT3bzJ6lkNCB4PkicrVaxMXfiWjeRgP6d/+yvWXn8tlUuXIIkihfyZ\n8xXm2YVdGYLGnjRZA9F0jdbXf0ffczvY3HwxA6MjdPT1kNBUDK+CXFNOsK6KUF0NofoavKHgjB6m\n3XsP0vnEC3zgsi187q/+aowqOpVK2XXpgruWOhU4bleWZ7RF0kdOHGUoOkpKT1tELUoUSwGCsp9r\n3vd+Lr30Uv4/e+cdHlWdtv/P1PSekITeBBSEACl0kJJGVNx11y52VlRW7O3d8tNVdN1F17Lq+opb\nXl1ddy0raUhHgdBJbyRAQg2EJNPb+f0xOSczk5lkMiQh7M59Lde1Tk7OfE/mzLm/z/Pcz/2MGTOm\n11PE7mrS7p6xoj2sGEkbDAZ27NjBhg0bqK2t9Xj+YcOGSSTtzaSo/oL4LNTr9U6fnyAIFBQU8Mgj\nj7Bw4UL+8Ic/EBV18XOtL1P4CdkXOBJyW1sbQKcdqiQuslja+2ODe6Sq9ITq6mruveM+JoYmk9Du\nOe1mgQ51Ynv7ifhgET/PM2fOcvz4MfR6A2ajlbCAWOl2EEcjqnqQTrdYLLS1tmGWW6m07GXSuAyi\nw4Z0/4vtd43ZbEar1YFMhrKLARLnWuuov7CXq2fehlyukqJRoT07h4FHAAAgAElEQVSyl8nkzqKr\nHj5Qa0q+RT0okpGpGd0f3EO0nKqn8WAh8+68D0VwqFMUqtPrsQrtorEANcoANcoAu+hKrlR1SdKC\nYK8mHy/4mvAwNWl3L/d6TR0pUrokaQQbhz/7B2OVat55803Jt7impobqmhpKKss5da4JvdWCEKRG\nlRBD2NB4wobEEzE0EXWodxmHs+W11P9zA7MnXM1Tjz1OQkKC07AEx6jqYiAOdxBJ+nBpMRXVlRhs\nJmTIUMjkqGRKAhQq0lLTWLp0KRMmTPDJG7o7OF6fO6Gop3S3Xq9n+/btFBYWUl9f7/H8w4cPl0i6\nq0xeX0EUdYq18KCgIGQyGa2trTz//PN8++23/PGPf+x1b/DLEH5C9hXG9gH2Go0Gm81GeLi9tiam\nZBzHnvWmKjI3N5dfP/0ii0dfh9p1NrBUe+pcJ3b3OQqCQPHhYvRtFgJUoe1KYvewC64CUKncz1rW\narSYTGZUqkCKDd8zeNhERsZP8+qaTCYTOq0eZHKnSUzuYLYYONzwDWOnLCE2/gpoN9p2nVpk/xu0\n/5KsXXkrDnXoYrLP6YaDNJ0vY+LSu50EZb0Bm81KxYa/MH5GGuNmL3D6mdVqlQhaq9XSqtFgNBrt\nJC2XIVcHoAiwR9GqgADkSqWD0Yn9I2k7Xs/ZHRtIu+t2okd236vtCZ5I2tDaSulf/o8fz1/A6kcf\nRalUSlkXQRA4f/685LlcXVtDSWUFTS0X0FvNEBqEOiGGsKEJhA+NJ3xIAqog9xuvthNnqPj0WxII\n4P47ljNnzhyp1acvCFG6bsE+JrGyspKCggKqqqswCRZkyJDbpXLIZXKCgzqU0YMGDer+xF28n7ta\nKjibwoj/XEla/Ps7TkjS6XRs27aN7777rkuSHjFiBEuWLGHu3Ll9RtKeFOKCILB9+3YefPBBpk6d\nyh//+Mc+9QO/jOAnZF8hDpjQarVYLBbCw8PR6/WSYCsoKKhP5iO/9dZbfP7+v1g8PsfpdUfBlmt6\n2vEzFB+edlWygeLDJYSoowkK7PhSig8Kk9GEzdb1aMSA9ii6tU2DQq5CoVByxHAYW4SKpLHZXV6L\nzWrfOZvMZmRyJUqVd6rE8oZCghIGMfZK0bJONGpxOLdNkGwo7SljK1abtaOnVyaX+ovl8g6/aIPu\nAlWlXzJqzlIiEkd5tZ6eoOHQNsxtx1l43yPdis8sZotE0KLoymg2YbUJoJAjU6tRBgSgCrRH0jK5\nnKO5/yIiPJDUe5b36r0nkvTJ0jJOF3zH4ytWsHjxYqDDDtHxn3ifuaaKS6oqada0oreYkUeGoU6I\nJnyoPdUdNjgeZfvsaJPeSNX6TRgO15B21RTuu/turr66d6aa9QQ2m426ujoKCwvZuHEjNsHmUtGV\nIZfJiI2NJSMjg4ULFxIREdHteT0pjLtbiyeSduzrdSVprVbL9u3b2bBhA0ePHvV4/pEjR0ok7Y1I\ntbu1in3TjrV+nU7Hr371Kz799FPefPNNbr311kuuHB9A8BOyr3AkZDF9LQgCgYGBfdqe8ODPVnJ0\n5wnSxtrHHHZVJ3b32XWYJ9j7mY/WNRAXOdSrh4HJaMJkMkrpYRFWixWQoVDayfmc5QQn5PXMmHQz\nSnmH7aeAgK2dHM1mc7vgSYZCZZ+k5C0azx3mnOUYU2ff2R7terr1ZA4kLcMm2NqHOrT7RVus9gds\nuzWWmO6uLfuWwMS4PklbG9rOU7vtHyRffwODJ0zq8e8bDUbaNG3otDp0eh0arc6uMhdsyJRKjG0t\nNO3cyKTsdEbOntnrvcMAVRs2IlRW8uJzzzN9+vQuBwu4I+mTJ09SU1PDkSNHKK+spLy2mhadFoPN\ngiIqDGV8NGGD4wkfmoDNbOH4pp2ozrYxO2k6y667juTk5Ev6EHerjHaBDPuowPT0dObPny9FoY61\ncNeo2BdcDElv27aNDRs2cOzYMY/nHzVqlETS3rZ2irVisA/zUKvVCILA3r17eeCBBxg5ciQffvgh\nw4Z5P+3rvwR+QvYVZrMZo9GIRqNBEOwjEfs6pWYwGMjJvJZ443DGJV7ZbZ3YETbBToYgIFcokMtk\nHDp4CLNBRmRY59Fj3sBmtaLV6TAaTBIZAxisWiqsexk7ZD5hQYOgfQgFdNwkMpnCZ2W0Rn+WyjNb\nmJT2Y0LD21NdopK4S3QYbohr6mhd6vCLPnOyhNNnDjJy5nWogkJQBgSiCgiwp9N7Ieo8svPfhIQq\nmHXLXd7/kmBXQAs2ewZE7mBIYjQY7T7ROh0ajYbqrQWYG48QP3IEquhoAgbFEZ6YSHhiIqHxgy5a\njS4IAqVffU3Y2XO88qtfSZFrd57FIkmLqVaxFiraUVZUVFBZWUn1kVpqjtajNRsx2KwoYyNoa76A\n1WAkSh3EiNgEspekM2fOHEaMGDEg6o4mk4nvv/+ewsJCqqur3R4jCILk8LVgwQIiInpHoe4KX0la\no9Gwbds2CgsLaWho8Hj+jIwM7rvvvk5rFwQBvV7fyU3MaDSyZs0aPvjgA15++WVWrFjhj4rdw0/I\nvuL8+fPSLtdms/X5TGSAAwcO8PB9q5geNZuI4Mhu68QymUyKiMVjxYdga2srJcVlRATHoVb5NjbO\nZrXS2tYGKFC117PFKPiwYQexceNJjLwKgY6eZplcgUKh7LaW2xUEwcahY9+QeEUSQ0cmd/RL0065\n0ucgiP/D/e3pYB/pQNJazQVKDn7OFSkLCIgYhEars6uiBQG5ql0VrbanihUqFV58j5zQcrKOxkMb\nmHv7PUQmeBDmOV6vTcDaXjpQyBXdzpdubTrDwc//TNa8WQwbNozSigqq6+rQGI0YBRvK6GiC4gdJ\nJB0SG9Nj8ZvVbKbkn/8i7EIrzz/+OHPmzHG/di9afxwn/IiiH6vVyrFjx6ipqaG2tpby6iqq6mrR\nmk3oLXYPgFClmnB1ANMmJ5GTk8OkSZP6bQSiNxDruYWFhdTV1bnNYgFcccUVpKenM3v27F7xu3YH\nX0m6ra1NiqQdSfqTTz5xWqs7j22AkpISHnjgASIjI/noo48YM2ZMn1zffwj8hOwr2trapBtaq9X2\n6UxkER988AF//sPfWDAyE7lcLqW6DAaDlC4H5zqxu5oy2EeHnT7RRGzEYJ+iPpvNhqZNg9VqQ6UO\nROZyL9UaDkFkAFNGZzlNLLJaLFitNima7VBFK5DLPM/+dUXtqe8xB1uZNP2G9le6MS8BJGoWnP/b\nGfbfLzv0FXHD40ldfGO7gYauvZar61BF2wQEGRJJqwICUQYEoFAqu1yHINio3PgJQyeMZUrmdV0c\nZ9/c2I1GZCjkCq+5v3rXNsy1pbz7xlrGjBmDyWSivr6empoaampqKK2spO74MbQmM2a5DFVsDMHx\n8RJJB0VFdl/GsFopX5+LrP4YP7vzTm688UavMkTivWmxWKRxiI7wpCoWr6G2tpaKigo2b9+G3mrG\nJggoZHZldKBCScKgeHJycliwYMElURU7wlFBHRAQgMlkkkj6xAnPNrBXXXUVS5YsYcaMGV63d/UU\nPSVpd883QbAPxTGZTE5RscViYe3ataxdu5b/+Z//4dFHH+3T7OF/CPyE7Css7e5QZrOZtrY2IiIi\n+uyGE5XbP7v/Z1yo0JM0NBmlUikR7759+5yOV6pUxMbEEBMbK4muHB+uJpOJgwcOoZIFExrc8zm6\nNqsVjVaL1eKejAHOmhtpoJYZk25GpXRWTgsC7cTcQdI2m60jxm0n6Y7e4s7nb2qt42jLPqbNWY46\nIMjtMd7BPUmfaijm9JmDZNz+COqAIAcDDfsarVZ7W5souGrVaDAY7a5jglyOQmVXRavUASgDAjul\nic/WHuJc7R4W3P0zQqKiO63KZrVnNmj3C+9p9sVmtbL3i78xZUgcb/z+d24jL51O52BFWUNxeTkN\np+z9xValEmVsLGGJCYQlJhI+OJFAN+YTgiBQ9/0PnC/aw7ykqaz++c8ZPLj7qN+VqNRqtfO4SZf+\nXEdFsWMEZzAYqK2tZfv27XY7R5ulXXUuqqJBIZOTlJREVlZWl1aOvQlHolIoFF2Ws1paWti8eTMF\nBQWcPXvW4zknT55Meno6ycnJvdJC6W7N7jIankhavEYxGBBdB6uqqlixYgWCILBu3TomTpzY62v9\nD4WfkH2FSMgWi4XW1lbCw8N7/Usi3vB6vZ6TJ0/y0H0PMz5wMnGhCU4Pab1ez4kTJ2huvoDjx+D4\nEA8OCWFQXBxR0dE0HD9Ow7GTxEYM6fHDSfRDFmygVAXYo1p3x9kMlJh+4Mqxi4iLGNntee2q6HbB\nlcUuuBIEB5JuT3GLJG22mig+/g0jJy0gfrD3JvPeQcBk0HL4wGdMXZDJiPFJTj91dLhyNNAwm83O\nqug2DSaLGatNQKZQIle1q6IDApErFVRt/oyhE8aQlLWs453F9LQAcgddgC9oazpLyVf/x23LruXh\nhx7yitTFoQ41NTVUVVdTXFHBmXPn0FnMEBSEKi6W0IQEwhMTiBg8GFW70KelsZHq9XlEWqz89Lrr\n+MlPfiK1AjrCUX3bHVH5GsFpNBp27NhBbm4ujSdOYBNsTptGmcxe2pg7dy4ZGRmMHz++V8tNjulb\nR6LqCc6dO8emTZsoLCykubnZ43HTp08nPT29zzYa3ZE02AdOFBUVMXXqVMrLy1m7di2PPfYYzz77\nbJ9F9/+h8BOyrxDJ2Gq10tLSQlhYWK/dfK4OXwEBARQWFvLbX/6OhSOXOvyl7T7PYCc06DBcb25u\n5syZM+h0uvZz0n6cjbY2DUGKMIKDwlCr1NK4M0/pYtEv2mg0YrVYkckVKJVqt5GxI8r0u4hMGM64\nob4NJRAV2RZx6pLF2iHcksmpPfM9QpiSq5Kus0+F6uUafnVpIfJAIwtvfKC9vOzqctUBmajSlokb\nIXs92mg0om3vL9ZotGi0Gvu1CAKtZ4/TVLObyRlZJIy9kpDo2PbsQM/S013hREUJDd9/x+oV93Pj\njd55dDtCEATOnTtHbW2tRNIllZWca21Bb7YgCwtBHRtH+OBEQuJiaTnewPnDxSQEBZOTnk5OTg6D\nBw926kl1rDP2OPLvAUmLWSSAkydPsmHDBgoKCjAaje33kWPzkh0ZGRmkp6czYkTP+7gdRU3i0Jje\nJMkzZ87w3XffUVhYiEaj8XhcWloaS5Ys6RWPbleIhkdivV8mk/GnP/2JNWvW0NJiH7caHx/PzJkz\nmT59OjfeeKPPQzz+C+EnZF8hTfyx2bhw4QKhoaG9IshwdPhSqVTSl/q5Z59jb+5hZo9ZAHTsXF3r\nb07+xDKZ9JrZbG73+K3DqDcTGhDT7sDksgAZUs1OEAQEmyClk+UyBQqlErnMu9R8g7GKC4EXSLvy\np74/GARnsZr4QLZYrZxurqGueS9jr0pHqQpCoVSjVNkV0Sp14EUbe7ReOEF1RR7zl91B7OCRnRYm\nGnNIU58cvyvtkbNoRSmStH00oh6tVodG08b+DZ8iM10gJiERswDqqFhC4uKJiE8kIn4wIVHRF/1Q\nrdm9A035AV548nEWLVrU/S90A9HlShRcVVRVUVZVRYtOi95ixapWoWlrI1CpJCYwiMnjx3PN/PlM\nmTKFQYMG9WpboGMEJ26QvWm/AqitraWgoIBNmzZ5PH9gYCDp6eksWbKExMREj8e5EzX1h/pb3GgU\nFha6HewgYvbs2aSnp3PVVVf5tC7Hdi3HzIbNZuOvf/0rzz77LPfccw/Tp0+nuLiYffv2sXfvXt5/\n/31++tOfXswl/jfBT8i+Qpz4JAgCzc3NhISEOHnv+nI+0eFL3F2LE1Campq47ae3k2AZwZi4cdLx\ndjKWoVDY66yOk2JczUBkMhkXLlygqrKaIFUkIUFh0jWYTSYsVqtEfpIDFHbRlUKhtCujexiytVrO\nU2M7zLQJ1xMa1LlO2h3sBlFCe49w559brEb2HvmKidPmMWjQFWg0Wtra2jCa7OYZMrkCuVKNSh1o\nr+WqA3rU7ywIAiUHviBh1DBSFnkzNtH+N3OKol1J2uGfIAg01pZSv38DD624h/DwcLvgqqKCumPH\n0ZssWGUKVFExhA1KJDw+gcj4wQSEhvXooSoIAuVbCjEdreKRB+7rE4tCsXVJUkVXVVFaWYnObEJv\ntqCUywhVBxAeEMCsmTPJyclh3LhxfaK78Lb9yl2PdElJCYWFhezcudPj+SMjI8nIyGDRokVERkZK\nKXhHUdOlxPHjxyWStnThvrdgwQLS09O54oorurwfrFarU7ZONDw6efIkjzzyCDU1Naxbt45Zs2Y5\nnUfcKPVFvdsdtm/fzm9/+1v27dvHyZMn+eqrr6TZx56wZcsWHn/8cUpLSxk+fDjPP/88y5d7bz3b\ny/ATsq9wnYkcHBzsU8uFY51YdPhynIwiCAJffPEFf3jlHa4ZkYVSoeroJ3ZoY3J3Xjsf2M9hMBop\nLy3HZpYTGRbXET2DU5uQ5GrVPlLQanH2iZY7Cq7o+sFjE2wcNmxnxIjpDIvrgcuSQ1Rsr9N6PrTs\n2GaCBwVxzeLbpd81mU12G0qtPU3cptHYoyebYO99VgY4kXRXD6PTJ0o5eWIPGbc9TFCIL6MHBYfP\novPUJUEQOLDlKwYFW3jv3bcJDw+XjBtEcquqrqakvIKTp8+gN1sQ1AEERMURNihBiqTV3Zg2CIJA\nbdH3XCjdx83XX8u9997bpy1Corbi6NGjHD9+nLKyMnbu3o2+nSAUcjlymYwAhYIRw4ezdOlS5s6d\ne1Gb2q7ga4+0zWbjwIED5Ofnc+DAAafziYQDMGTIEDIzMwfkeERAchvbsGGD25/Pnj2b1atXO73m\namISHBwsibm++OILHn/8cW6++WbWrFkzIAZZ5Ofn88MPPzBt2jR+/OMf8+WXX3ZJyPX19UyaNImV\nK1dy77338t133/Hoo4+Sm5vLkiVL+nHlEvyE7CscCbm5uZnAwECvnWygw55SVJqKDl+iUYJjlHXf\n3ffRXK5j6rCUTv3E3sBoNFJVVUVbi56Y8ISO/l+nz1Ym/q/9PzvcvqQHmMVeyxU3CtLwAbncbvQh\nl3eKomv0B5FFBTFlTKYXfxTviVjEmQtHqL+wl2t/9DDBwR4IU7C3holiK41GY+8ttrb3FivVKFXt\nvcXqQKd6tNVi4tDeTxmfnMrE1ItN99onVol2pJIoT9vGnvy/cl3GPB5+6CGPYqXz58/bFdHV1RJJ\nn7tgr+UqgsMIiIkjYlAi4fGJhA+Kd2tF2lB2mGM/bGbKFaN4YvVqxo0bd5HX5HKFDupix4e4CIPB\nQHV1NQUFBezatQuT1SptCuXtfxO5TEZaWhqZmZlMmjSpz1K/3vRIu2u/MhqNkhVlVVWVx+/iyJEj\nSU9P75HLVX9BEASqq6vZsGEDmzdv5v7773ea8+to7ekYFTc1NfHYY4+xZ88ePvzwQxYvXjwgjFlc\nIZfLu42Qn376acltTcQtt9xCS0sLubm5/bFMV/gJ2VeIhApw4cIFVCqV1z2PnurEZ8+e5aWXXiIx\nMZGsrCwmTZrE7t27efKRp5kWNZOokBjkcoUk5PIGWq2Wqspq9FoTUWFxKN0MpID2D8/BYAOQSMnZ\nOMPumy1Gz1arA0ljV686KqKbzCdolNcxc9LNKBWeo5/u0tOeYLGa2HfkK6bNWsy48ale/55gE5za\nlto0GvR6A1abzW7n6VCPPnOylOaWKpbcvJKgEN+iH0GwYbXZQBCQyeUoXNq5jtcUc/zQJp598lHm\nzp3rlGrsKsXqWMstr6ikrKqKVq0Og9mKKiKKoJg4IuIHExGfSGhMHHKFAm3zOco2rCdA30pO+mJu\nu+22ixqSIMJXdbHY9pObm8u5c+dw2Sa21+PtgquMjAyGDx9+0Wv1hO5IWjQCApyuURyPWFhY2D7D\n2D3Gjx9PRkYGM2fOHJAKZPG55jrwQhAEcnNzWbVqFRkZGbzxxhtERva8ZbK/4A0hz58/n+nTp/P7\n3/9eeu3jjz9m9erVXSrb+xB+QvYVjoTc1UxkR3RVJxZN7J988knpeKvVSnVVNbazcmaNuIa4uDiC\ng0O8ImSDwcDJkyc5feosWOVEhfXAMlEQOj5MJ5LuiFqdU912JbY0bclikVLdJsFIuXkPI4ekkBAz\nDpUqwB6BOpxfEIlYOnHPUNnwPUKIgcycBy5qt261WNFqte0WlB31aJPZRE1VIWGxEUyYPp+o2EQi\nYhNRdTOZCjqcywTBBqJBi5uLFASBwz/kI7Qc5bVXXmLSpEk+21AeP36c6upqamtrKauspKr2CDqD\nCZMAqohoQuLiCY+Lp+3cWZprK4lUy8m4ZgE5OTmMHTvWJ+WzOF6vt+qoR48epaCggMLCQunv47qu\nkJAQSRUdG+ub/as3EBXiRqOxk4gSPPdIazQatm7dSkFBQZcmIFOmTCEzM5Np06ZdUvMMTwMvWlpa\nePrpp9mwYQPvvfce11133YCMih3hDSGPHz+ee+65h6efflp6LS8vj5ycHHQ6XZ+VT7qAn5AvBuII\nRk8zkUV4UyeGjhRmbW0tubm5/Otf/6Ku4igjFROIVEVJNpAyQCaXERISQnh4uNPD2GQy0drahl6n\nx2aB4MBwggN7JgJycwUOFpS4TXW3/78OkhY6RiKWte1BHh7IiOgke5SIDLlcjUoVgEoVgFrd2Tij\nJ2jVnaXs5CauSb+FhMTRPp+nExzq0RXluzha/z0jRo3AYLJgMFlQB0cQFDmIqNjBRMYlEh7luOlx\nTk+L/uFdfedsVit7N31BlNrI715b06n1xrEOKiqKvU2x1tXVSS5dJRUVHD3egN5kwWi1ojOYUCjk\nRIcEkRAdxU9v/DEzZszo1uDDMZqSyWQEBgb2mbpYFFyJqW5PSEhIICMjgwULFvRKLdf1GkUFta89\n0s3NzWzatImCggLOnz/v8X3T0tLIyMjg6quv7nPy6yoq3rJlCytXrmTGjBm8/fbbxMXF9elaegu+\nEnJubi7XXnster2+z2xMu4CfkC8GnmYii/C2Tiw+OB3diwRB4InHnqThwClmjV6AVqulqanJntIT\nBGxW+wNftFe0vx/IZXICVMEEqIMIUAfiq190t+hBqvuk/hgn5PVcf819WMxW2to0kuDKbDZjs4oe\n13ZFtFoVgFLl/ehKQRA4XJ9H7MjBzJnb815bb2C1Wti8cR05S+dw6623Ul1dTU1NDWXlFVTVHEGr\nM2KyCgSExRAaNYjw6HgiYhIIjYhBoXQfFbuD2WSgqPDvDAqT8+tfvNCty1FXKdbuzDMce4sPl5Zx\npumcvR4tl6FSKAgLVDNqxAhuuOEG0tLSnERgjtGU43i9/oTFYmHv3r3k5+dTUlLi8bjRo0eTkZHB\nnDlzehT19HREoq890qdPn2bDhg1s2LABrVbr8fzz588nPT2dcePG9RpJi1k712vUarX84he/4B//\n+AdvvfUWN99884CPih3hT1n/FxKy60xkxzmoFosFrVYrPbDEOrHrsAdRySmm/BQKBYGBgXzxxRe8\n89v3mDX4GsICO4uVxFYEUaTU1qbBaDBitdqQIUchU6FWBaBSBqBWBvR4eIBP8JDqNttMHNBuZ0Zy\nJqOHXIW9VUshRW86B7FVm0bbXpMWkMtVKFUB9utQBXQ5L/l0cw1HWw6Qc8ODhIT0TW3r+PEKaqs2\n8Zvf/IJZs2ZJr4sey9XV1ZSXl1NSWs7xxhMYzTYEmZKA8FjCYxKJikskMnYwgcFdlzbMJgP7N39J\nMBqeWL2K+fPn9+hh6C0xiKlW8dyiAUhpaSn//vZbDGZL++cgQyGToVTIUatUpKens2DBAgYNGnTR\n4wN7GwaDge3bt1NQUEB9fb3H4yZPnkxGRgbJycmd0sSuUbFYWuopLqZH+vjx45Iq2lPrkkwmIz09\n3ScjEzEN75i1U6lUCILA7t27WbFiBePGjeODDz5gyJAhPb72Sw1vCPmZZ54hLy+PQ4cOSa/deuut\nXLhwwS/quhwhErJYF46MjJR21Z7qxK7pabGtwDHlt337dl78n5eItQxm4uApPVqPo5K4rU2DxWzB\nZhWQy5Uo5WrUSju5qRS972zVGR2p7rLWPYQPiWZBsuMwiM4mJqLbkf06NLS1aaUeSEFwSHWrA1Cr\nOlLdVpuFfUe+5sqpqUyeck3fXI0gULTrGyLCjbz33jvSBszVhSowMBCj0dhhQVlVTXFZOWfOnsNg\nNCNXBxMYHkdke6o7MjYBpco5crNaLRT/kI/uzBGWZi7kZytWuLWi9HbdvhCDINhnF2/bto1vvvkG\nnV4v9auL4z4VcjkjRowgMzOTuXPnDqhpSyJaW1slr+gzZ854PG7mzJksWbKEUaNGYbPZvIqKe4qL\n6ZGuqamhsLCQzZs3ezx/UFCQZGSSkJDg9hjHAECcriUK037zm9/w0Ucf8dprr3Hvvfde8p7qnkBs\nFRQEgWnTpvH73/+ea665hujoaIYNG8azzz7LiRMn+POf/wx0tD099NBD3HPPPWzcuFFqe1q8ePGl\nuAQ/IV8MxEk1er0evV5PYGCg065aVFG6I2LHB7hjW8GePXv45XO/QnUhmOQRMy/qYeBMbnZvZV17\nu49gA4VchUqhliJpxUU6W7lZQHtmW+C0sYEGjnDDkgcIUgdLPbmdDExw8IgWW4+sVnQ6+6QlrUZD\na5sGY/sgB5msPdWtCuDkhUpaZSfJuX4lAYHBvXst7TAadGzb+leWZs/lmWeelj5/0QDBk6BJNHip\nqamxty1V2duWWlq19np0SCTBEYOIjE10qkefqCunev8mhsaFc/utN5OZmdkrta3uiMGVEEwmkzTw\noaKiQkoT2wTB+SnSLs6bOnUqmZmZ/TbMoacQbSgLCgrQarXS30MckSi2Fi5ZsoSMjAxGjhzZZ2vx\ntUdaEARKS0spKChwa2SyZs0axo4d6/Q+4nMHcIqKDx8+zAMPPEBMTAzr1q1j1KhRfXa9fYWtW7dy\nzTXXdHpmLl++nI8++oi7776bo0ePOjmzbd26lccee4yysjmSOi8AACAASURBVDKGDh3KL37xC+64\n447+XroIPyFfDMxmM1arXZkrKq4d+5G7qxM71t50Oh1/+ctf+OKTfxKgDSVt1ByPg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Uk0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\nAlhjjJkMNANWAFvucIW1Uk3S/wOA7iEME+ag6QAAAABJRU5ErkJggg==\n",
- "text/plain": [
- "<matplotlib.figure.Figure at 0x7fd9165a6bd0>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "\n",
- "pl.figure(3)\n",
- "\n",
- "#pl.subplot(1,2,1)\n",
- "cmap=pl.cm.get_cmap('viridis')\n",
- "verts = []\n",
- "zs = alphalist\n",
- "for i,z in enumerate(zs):\n",
- " ys = B_l2[:,i]\n",
- " verts.append(list(zip(x, ys)))\n",
- "\n",
- "ax = pl.gcf().gca(projection='3d')\n",
- "\n",
- "poly = PolyCollection(verts,facecolors=[cmap(a) for a in alphalist])\n",
- "poly.set_alpha(0.7)\n",
- "ax.add_collection3d(poly, zs=zs, zdir='y')\n",
- "\n",
- "ax.set_xlabel('x')\n",
- "ax.set_xlim3d(0, n)\n",
- "ax.set_ylabel('$\\\\alpha$')\n",
- "ax.set_ylim3d(0,1)\n",
- "ax.set_zlabel('')\n",
- "ax.set_zlim3d(0, B_l2.max()*1.01)\n",
- "pl.title('Barycenter interpolation with l2')\n",
- "\n",
- "pl.show()\n",
- "\n",
- "pl.figure(4)\n",
- "\n",
- "#pl.subplot(1,2,1)\n",
- "cmap=pl.cm.get_cmap('viridis')\n",
- "verts = []\n",
- "zs = alphalist\n",
- "for i,z in enumerate(zs):\n",
- " ys = B_wass[:,i]\n",
- " verts.append(list(zip(x, ys)))\n",
- "\n",
- "ax = pl.gcf().gca(projection='3d')\n",
- "\n",
- "poly = PolyCollection(verts,facecolors=[cmap(a) for a in alphalist])\n",
- "poly.set_alpha(0.7)\n",
- "ax.add_collection3d(poly, zs=zs, zdir='y')\n",
- "\n",
- "ax.set_xlabel('x')\n",
- "ax.set_xlim3d(0, n)\n",
- "ax.set_ylabel('$\\\\alpha$')\n",
- "ax.set_ylim3d(0,1)\n",
- "ax.set_zlabel('')\n",
- "ax.set_zlim3d(0, B_l2.max()*1.01)\n",
- "pl.title('Barycenter interpolation with Wasserstein')\n",
- "\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 2",
- "language": "python",
- "name": "python2"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 2
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython2",
- "version": "2.7.12"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 0
-}
diff --git a/notebooks/Demo_2D_OT_DomainAdaptation.ipynb b/notebooks/Demo_2D_OT_DomainAdaptation.ipynb
deleted file mode 100644
index b713d5b..0000000
--- a/notebooks/Demo_2D_OT_DomainAdaptation.ipynb
+++ /dev/null
@@ -1,217 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Domain adaptation with optimal transport"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "import numpy as np\n",
- "import matplotlib.pylab as pl\n",
- "import ot\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Dataset generation (classification problem) "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "n=150 # nb samples in source and target datasets\n",
- "\n",
- "xs,ys=ot.datasets.get_data_classif('3gauss',n)\n",
- "xt,yt=ot.datasets.get_data_classif('3gauss2',n)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Plot datasets"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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mudNPP/2EUoo333zTZvvhw4ejtebHH39MU/1KKfr3729zhUxrzdq1a3n++eep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\nKEXIAQAAShFyAACAUoQcAACglC+qn/WKtzKzIwAAAABJRU5ErkJggg==\n",
- "text/plain": [
- "<matplotlib.figure.Figure at 0x7f7c581e2a50>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "pl.figure(1,(10,7))\n",
- "\n",
- "pl.subplot(2,2,1)\n",
- "pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')\n",
- "pl.legend(loc=0)\n",
- "pl.axis([-4,4,-4,4])\n",
- "pl.title('Source distributions')\n",
- "\n",
- "pl.subplot(2,2,2)\n",
- "pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')\n",
- "pl.legend(loc=0)\n",
- "pl.axis([-4,4,-4,4])\n",
- "pl.title('Target distributions')\n",
- "\n",
- "pl.show()\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": false
- },
- "source": [
- "## Domain adaptation classes"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "# LP problem\n",
- "da_emd=ot.da.OTDA() # init class\n",
- "da_emd.fit(xs,xt) # fit distributions\n",
- "xst0=da_emd.interp() # interpolation of source samples\n",
- "\n",
- "\n",
- "# sinkhorn regularization\n",
- "lambd=1e-1\n",
- "da_entrop=ot.da.OTDA_sinkhorn()\n",
- "da_entrop.fit(xs,xt,reg=lambd)\n",
- "xsts=da_entrop.interp()\n",
- "\n",
- "# Group lasso regularization\n",
- "reg=1e-1\n",
- "eta=1e0\n",
- "da_lpl1=ot.da.OTDA_lpl1()\n",
- "da_lpl1.fit(xs,ys,xt,reg=lambd,eta=eta)\n",
- "xstg=da_lpl1.interp()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Plot OT matrices and interpolated samples "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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artIdDXkv+QcCIUR36Z+GQLd05DLgcx3uqRCims7oSFccGQSR+RPgFc65/y4c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O+Xw+n0Ag+DNQeq3nE2RtYTab6bJ00RbeypaQrcSp56ehqFQqdu9Qcd8OJV2mmbS1nL/aS47p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h5k795u/vjHT+jurmfRooWjvocQYvwppfDz8+Oee+LQ6Sppa1O0tup54YUCtm4NZP36eG6/\nfSHh4Wbmzp171YMWAQEBBAQE8MYbn7B9+4cjHhtth+XC8LVf/GIJzc3lHDzYwUcftbF+vZUtW+LY\ntCl97L9xIcSYCdAHcKu2gT17PiUoqIPvfW82BoOBs2dreP31Wn7xi5WsWpUMQFiYHxERl6/Pp9fr\niY+PByAiYgaPPLKC7OwaHnnknStOOV1T00FNjWv4/IUDK9///hKczno++aSaw4e7WbvWyrJldubO\nnTU8HF+I8SadHg9RXFxMSUkrSUlzKStzzawUFTWDwsISSktLSUlJYfv21Vd8bXi4+YaOktTX15Of\nX8D996fT2WnixIkP8PNzcPhwAaGhISQkyEwqQniK+vpSrFY/5s1Lp6iomRdeKCAtLZGBgSa8vXuB\niwdBruUb38hiyxbXzs2N7rDs2XMOm82Ml5cdaKO83Ivjx6sJCMjBYMiSoSlCeLD6+nrOnKkgOXk2\nFosdAJstiNdfr8XPr+OGpowODzeP+HufOzf8stc/88wxtm/fM2LbT37y2Yiva2r0NDZ6k519llmz\noriQY0KMJ+n0eIjTpyupq9Pj7d0xPAV1WVknBoOOffuKsVodY7Zjcfx4Ibm5vcTF+VJc7Gqrvn6I\n1lYd779/hjvvDJGdGCE8wMDAAFVVjQQEjNypMJutdHXV09zcTHBw8HW91+d3VuD6d1jefrsJaBr+\nOi+vhbw8eP75en74Q+2qB2SEEO7X3NxMby/DHR64eJCktraZoaGhMR3hcaUDLJ939mwjZ882AtDY\nuI8dO+4Zs/aFuBrp9HiI99+v5/e/LwHyh7ddnIK6iMcf9x2zMa+vvVbM889XApVXaOvidNdCCPfS\n6XQYjd50dLgWGLTbTdx//2zMZm/a2lzDTr6I8HB/Hn985RVXQL/SDsvatTYyMlIoKGjinXcKAHjk\nkWQcjj4efnjuF/zuhBATwZUTTpzOQXQ6126f3W7ittsiCA01faFrea+VIVc6wPLNb4YTFBRKVZXG\n7353EoDvfGcRTmcld9wRe8PtC/FFSKfHQ3zrWwsJCenHxyeUpiYvnnrqKF/9aiIORy+rVi0gPT12\nzNp6+OFMrNYeQkISqazsYceOIzz66Fz0+loWL57BypWyEyOEJ/Dy8iIlJY6PPjqFxWInIMDCfffN\npLQ0n7AwPxwOxxd632sNib3SDsvMmSbsdkhKCgRcnZ6WllbmzYuUawCF8HAOh4OQEF/KywuJjk5C\np9Oh1/exerWBJUtSvmCn58aG1SckhFBR0YTNFjG8ra2tg6Ag6O83UlPTISNMxLiTTo+HyMqagU7X\nzZEjubS1dQEQE9PPvfcuIC0tbZRX32hbybS21nDqVDn+/q71gfT6elasCGXDhnn4+fmNaXtCiC8u\nNTWV5uZWcnPzqK72AgYJDfVj5crFNDf388wzB4YXGR1r4eH+/PCHKzh3rpQdOw6OeOz11+t4/fU6\nqqv95cywEB7MZDKxatUiPvnkIEVFRwEvfHw0srJimDlzJjU1HTzzzLFxyZELZ4SKi9t4+ukKoGL4\nseefPwPAP/9zpczgJibEhHd6lFJvAZlACNACfAj8/5qm1VzzhVOcUoo5c+YQExPDxx/n8a//Ws26\ndUtJS5sx+otvkF6vZ/XqFUREnOO9984CMHduFAsWzJQpq8WkMJ1yxGAwsGbNKmbPrqOlpQWDwYDD\n4cBkMpGdXcP27XtGLDI6lsLDzWzfvprKyla2bj3LqVMlvP12HcePuyZbeeaZ9WzYIDMviclpOuVI\nVFQUd98dSFVVFQMDAwQEBBAaGopSipqaxnHLkQtnhGpqOti6NZnjx/N58cVCjh/v4BvfSOGZZ/L4\nzW82cPvts8a0XSGuxB1nenYDPwZqAAfwC+A1YJkbavE4AQEBLFmSxuOP9zNjxvitVGw0GklPTyco\nKJbycm+6ulp46aXdfPZZO9u2zWLDhiWYTKZxa1+ImzStcsTLy4vw8HDCw92zenlkpI3IyCXcffcS\nNmwoY/Hi3wNQUnKWvXurycxMYebMmTLUTUw20ypHfH19SUpKckvbrmGzKaxencKqVTVkZT2LyeS6\nVrG09Aw5OR0YjXMJCAhwS31iepjwTo+maf96yZcVSqmfAn9WSuk0TXNOdD2e6EbHyt6Mrq46Zszo\nQakgIJh33tlLXFwJvr4a69evlTM/wiNN5xy50pTSoy0yOpZtv/POxWFuzc0BnD2rkZ29ny1belm5\nMmtc2hViPEiOTHyO1NR0cPhwMQBnzrjar6018+67lRw/XsfWrbeQkBAy5u0KAW6+pkcpFQA8COyf\n6gFzM7q6uhgaGsLf339MOyFDQ0OcOnUOpaxERsbT19cMQFhYHIWF1WRk1BEWFjZm7QkxHqZbjlxp\nSunRFhkdK08+uZef/zxv+Otnn80Zvl9WdpilSzOGFzQVYjKRHJmYHLm03Q8+cE1Z/fzzZ4cfr6gw\n8NRTW8e8XSHATZ2e80dTHgN8gQPAJnfU4ena2to4ejSb48cr2bOnla1bo1m3bj4RERGjv/g69Pf3\nU1raSmdnAE5n8/D6QNXVfdTX91FUVC+dHuGxpmuOXJhSury8nPfeO8Mzz1Twta+FsWpVHDNmzCA2\nNnDc2r7nnlgGBioYHIxix44jPPbYfBIS7HR1daDX19LT04PZLDMwicljOufILbdEk5ubx7595bzw\nQh2PPhrDbbelERERccWpqMeqXYulgYYGRWen74gcKSsr4JZbQselXSEAxmQAtlLqJ0qpoWvcnEqp\nS6/I/xmuiwdvAZzAf45FHVNJb28vH364h+zsGrq7A/nv/27mxIl23nvvUxobG8ekDYPBwIEDnTz+\n+BG+/e1dw2v17NhxhF/9qoo//al0TNoR4npIjlyf8HAzVms3VVX52GyuHZPo6HDq6mrp7CwmLGx8\ndlYAYmODSEz0IyzMtT6Qj08bXl71GI2thIeb8PHxGbe2hbgekiPXJzjYREvLOZqbm4mNjQLA19dA\nVdU5QkOHxm2IbHi4maysUIKChoiJcWWVwdCCwdBCSMgA0dFyTY8YP2N1pudfgN+N8pziC3c0TWsG\nmoFCpVQerrG0CzVNO3StN/j2t7+N1Wodse2BBx7ggQce+GJVe7Dy8nJKSlpITMyirMw1U1JUVALN\nzWWcO5dPUFDQTbfh5eXFt741D3//D2ls7KWsTM+pU4MkJXWzerWFxx5bfNNtiMnt5Zdf5uWXXx6x\nra2tbbyaG/ccmQoZomkaOTm5OJ1WwsKCgVzs9mBCQ8PIz88nPb2e0NDxOVoaHBxMXFwwL7zwGQB5\neZWUl/cxMFDLHXcsRKfTjUu7YvKa4AwByZHrUl1dTWFhA3FxaVRVuSYUiIyMo6urirNnz33hNcCu\nR1JSIkeP5rFv3xnAi7y8agoKjhMZ6YWf35pxa1dMXmOVI2PS6dE0rQlo+oIvv/Bf0jjaE5988knm\nzp0eC2cWF9dTVQXe3h3Dw86Ki1vx99dz8GAl8fFjs5BXZmYiu3d/xMCADrvdB+gkOTmKqCgDnZ01\nQPBNtyEmryv9I8/OziYra+wvWJ+IHJkKGdLX10dzcwc2WzSaZuL++2djt5vw9zdRXT1ER0fHuHV6\nlFLEx8fg4/Mp6em+mM0mAgNt2O1RNDc7qaysJDo6elzaFpPTRGYISI5cr/b2dpxOb3x8fLHb1XCO\nDA4GUFs7NqNJriYiIgK73Qj0k5lpx273JSIiFR+fQXJyzhITEyMzQYoRxipHJvSaHqXUfGABsA/X\nnPiJwI9wLfF9YCJr8XRvv13N00+XAqXD2y4MPwPo6AgZk4sMc3JK6OgIIDU1iYGBKqCQoCAHXV1O\ndu48TXBwnKySLDzKdM8RvV6Pr6+RtrYOHI4gvvxl1+LFfX09eHsz7kPMmpqaSUtLZ/36BAYG+vH1\n9cVkMlFQkENZWYV0esSkMN1zxMfHB6UGGRwcICDANJwjJSWdBAeP3xBZcB2hHxjw5o47bgO88fJS\nWCxW+vq6qazMpampieBgOeAqxt5ET2TQA9wFPAH44Zob/13gx5qmDUxwLR7t299eTlhYD21t3nR3\nm/n1r4/zla/E43D0s2LFXObMSRyTdv74xwKefroaqB7e9vvfX5yRqafnKNu3rx6TtoQYI9M6R3Q6\nHampSezalU1Tky92ezC9vd1UVOSTkBAw7mv5DA4O4u2tx2IZeTDEy0vHwMCU//jF1DGtcyQyMhKH\nw0xJSS7R0Uno9UYaG2sYGmpl5szxHdrudDpxOjVMJl98fS92sLy99TidQzidU37yPOEmE9rp0TTt\nNLB2ItucrJKSwnnooXXs23eYI0fqAEhMHGLr1sXMmjV2Kxd/85vzsFg68PePpK7OyY4dR/jWt+ah\n09WSkeFg48Z5Y9aWEGNBcgRmzZpFd3cPp04VUVRUjMGgIzk5kOXLl4z7dTVhYaEMDpbQ19eL0eg6\nq9Tf38fgYAcREbKqupgcpnuO+Pj4sGbNMvbuPUhl5SkGB53YbD6sXJlGYuLYHFS9GqvVSnCwmZqa\nKuLikoe319dXERjoJwuUinEjCyp4MIfDwV13bSIpqRSn8yxf/eoS4uPH9pRvWlocmzbVcPhwET4+\nBgB0uloWLrSxceNC7HYZ2iaEp9HpdCxcuICZM1NobW3FaDQSHBw8IePg4+LiSEkpITf3JH5+rglV\nuroaSUkJJi4ubtzbF0KMjeDgYL70pduor69nYGCAwMBA/Pz8xr1dnU7HvHnp7Np1gPz8k/j72+ju\nbsfHp4958+ZhMBjGvQYxPUmnx8Pp9Xrmzk1i7tykcXl/pRSLFy8iODiId989DcDcudHcdtt8bDbb\nuLQphBgbFosFi8UyoW0aDAbWrVtFVNQ5iosrAIiPz2DGjBkYjaPORyOE8CA6nW7ch8ReSVxcHJs3\nG8nPL6ChoZX4+ABSUpKIioqa8FrE9CGdHoFOpyM5ORmLJYLW1kDWr8/CZpMzPEKIK/Px8SEjI4OM\njAx3lyKEmKQiIiLGbLF1Ia6HzAkohoWHm3niiVUyW5sQk0xNTQdPPPEJNTUd7i5FCDFJSY6IqU46\nPZNEf38/dXV1NDU1oWmau8sRQniQ0tImtm/fw7lz1ZIPQogbpmkaeXlVbN++h7KyZneXI8S4kOFt\nk8C5c+c4evQ0xcXtHDzYwX33xbJp0zKZ4USIaU7TNE6fPs0HH2QDsGvXPvr6Kli8eMGEX+sjhJic\n2traOHDgMHv2lAOwa9cnmM3zmDVrFkopN1cnxNiRMz0erqysjA8/PEJ7uy9GYxw7d7aQnd3Mhx9+\nSl9fn7vLE0K40f79ObzwwkEKClxRXl9vZefOMp577j0qK1vdXJ0QwtNVVLTw3HPv8+67FTQ2WgEo\nKPDihRcO8NZbh2Wom5hS5EyPh/vss7MUFyuiomxUVLQA0N8fwIEDtRiNJ1mwYKZcgyPENKRpGv/+\n74d49dWa4W3PP39m+H5FhZEnn/ySO0oTQkwSv/zlp/zqV7kjtr34YvH5e1X88IfdskC5mDKk0+Ph\nXn+9hDfeaAAKh7c9/fRxAH71qxoef7ybJ55Y5Z7ihBBuMzg4yKJFfsycOY+mJsWOHUd47LH5JCTY\nKSs7w513Rru7RCGEh7vzziigkZiYWRQVtQznSGCgBjTy8MNz3F2iEGNGOj0e7p574oiNtRAVlTAc\nSI8+Ogcfn1pWrsxkwYKZ7i5RCOEG3t7exMVZKS93YrO5Fi1OSLDjcPiglGHMFzIWQkw9sbFBxMTo\niYw0DW9LSLDj5VVPbGwwkZGyXp+YOuSaHg+3dOlsEhMVen0zDocPAAZDE0uXhrFxY6YMbRNimlJK\nkZqaArRSX18NQEdHG6WlZ4mPD3LLgoNCiMnF4XCQkBBESckZOjvbAairq0KpdmbPTnZzdUKMLen0\neLjo6GjWrVtAQEAfra2ucbaJiTbWrl2BwWBwc3VCCHdKSEhg3bp5RET0s3GjDR+fejIzw1m9egU6\nnc7d5QkhPJxOp2PVquVkZoZjMNSxcaMNh2OQdevmER8f7+7yhBhTMrxtEkhKSiI2Npa0tGogl7vu\nWoLNJtPRCjHdKaWYNWsWiYmJ3HdfGwaDAavV6u6yhBCTiNls5pZb1rBgQRvbtvVjtVrloKqYkqTT\nM0no9XpSU2P46U9j3F2KEMLDGAwGgoPlGh4hxBcnB0zEVCfD24QQQgghhBBTmnR6hBBCCCGEEFOa\ndHqEEEIIIYQQU5p0eoQQQgghhBBTmnR6hBBCCCGEEFOadHpu0ssvv+zuEq5I6roxUpe4GZP15zQZ\n656MNYPULUY3GT/ryVgzSN0TyZNqdlunRyllUEqdUEoNKaXS3VXHzfKkH+alpK4bI3VNTp6SI5P1\n5zQZ656MNYPU7ckkR764yVgzSN0TyZNqdueZnp8BlYDmxhqEEJOb5IgQ4mZJjggxDbil06OU2gjc\nAvwtoNxRgxBicpMcEULcLMkRIaYP74luUCkVCjwLbAF6Jrp9IcTkJzkihLhZkiNCTC8T3ukBfgf8\nh6Zpx5VSMdf5Gh+A3Nzc8avqC2prayM7O9vdZVxG6roxUtf1u+Tv0MeNZdxojoxrhnjiz+l6TMa6\nJ2PNIHVfykMyBCRHbtpkrBmk7ok0XjV/oRzRNO2mb8BPgKFr3JzADOCvgL2A1/nXxZ5/PH2U9/8y\nrrG2cpOb3Dzn9uWxyI+JyBEkQ+QmN0+8jWmGSI7ITW7T8nbdOaLO/yHfFKVUIBA4ytNKgFeBTZ/b\nrgMGgZc0Tdt2jfe/FSgFem+qWCHEzfLBtYPwvqZpTWP1puOZI5IhQniUcckQkBwRYhq54RwZk07P\n9VJKRQKWSzZFAO8DdwOHNU2rnrBihBCTkuSIEOJmSY4IMf1M6DU9mqZVXvq1UqoL12wpxRIwQojr\nITkihLhZkiNCTD/uXKfngok71SSEmKokR4QQN0tyRIgpbEKHtwkhhBBCCCHERPOEMz1CCCGEEEII\nMW6k0yOEEEIIIYSY0iZlp0cpdbtS6qBSqlsp1ayUesPdNV2glDIopU4opYaUUuluriVGKfWcUqr4\n/GdVoJR6Qimld3zXDBAAAAY8SURBVEMt31JKlSiles7/7OZPdA1XqOn7SqnDSql2pVSdUurPSqkZ\n7q7rUudrHFJK/dIDaolQSv2nUqrx/O/TSaXUXHfX5ak8KQuuxZNyYjSemCPXMhkyZjSelEHTzWTJ\nEJg8OSIZMvE8KUMmXadHKXU38AfgeSANWAL8l1uLGulnQCWecUFkCq7ZaB4BZgHfBr4J/Hgii1BK\n3Qf8AngcmAOcBN5XSgVNZB1XsBz4d2AhsA7QA7uUUia3VnXe+TB+BNfn5e5abMB+oA/XOhUzge8C\nLe6sy8N5UhZci0fkxGg8OEeuxaMzZjSelEHT1GTJEJgEOSIZMvE8LkPGejXk8bzhWjisAviau2u5\nSn0bgTO4/vivubKzG2v8W6Bwgts8CPzrJV8rXEH+d+7+PD5XZ9D5n9syD6jFHzgHrAE+Bn7p5np+\nCuxx9+cyWW6TIQtGqX/Cc+I6apoUOTLK9+AxGXMdtXpUBk2322TPkPPfg0fliGTIhNfqcRky2c70\nzMW1gBhKqWylVLVSaqdSapab60IpFQo8C3wF6HFzOddiA5onqrHzp7azgI8ubNNcfw0fAosnqo7r\nZMN1RG3CPp9reAp4R9O03e4u5LzNwFGl1KvnT7FnK6UedndRnmgSZcG1TGhOjGaS5ci1eFLGjMbT\nMmjamCIZAh6UI5IhbuFxGTLZOj3xuHrmjwM/Am7HNbxmz/nhN+70O+A/NE077uY6rkoplQg8Bvx6\nApsNwnWGru5z2+uAsAms45qUUgr4FbBP07Szbq7lfiAT+L476/iceOBRXEdt1uP6Hfo3pdRX3FqV\nZ/L4LLgWN+XEaCZFjlyLJ2XMaDw0g6aTSZ0h4JE5IhkygTw1Qzyi06OU+sn5i5yudnOev3DrQr3/\npGnam+cDYRuuXu9Wd9WllPorwAz884WXjnUtX6Suz73GAbwLvKJp2m/Hs77rpPCsccr/gWsc8v3u\nLEIpFYkr1L6iadqAO2v5HC/gmKZp/6Bp2klN054FfoOrIzTleWoWjEXNn3uNp+XEaDwtR67FIzJm\nNB6cQZPaZMwQmBY5Ihkyxjw5QzxicVKlVCAQOMrTioFlwG5cYxk/u+T1B4EPNE37BzfUVQK8Cmz6\n3HYdMAi8pGnaNjfUVaxp2uD550fgGk/52VjXMprzp5S7gbs1TXv7ku2/B6yapt05kfVciVJqB67h\nW8s1TSt3cy1fAt4AnFz8Z6fDFcpOwKi54Y9WKVUK7NI07euXbPsm8ANN06Imup6J5qlZcC2TKSdG\nMxly5Fo8KWNG46kZNNlNxgyBqZMjkiETx5MzxCM6PddLKWUG6oG/1DTtd+e36XFNbvD3mqY956a6\nIgHLJZsigPeBu4HDmqZVu6MuGD7ishs4AnzVTTvMB4FDmqb99fmvFVAO/JumaT+f6Ho+V9sO4EvA\nSk3Tit1Zy/l6/ICYz23+PZAL/FTTtNwJLwpQSr0ERGqatvKSbU8C8zVNW+aOmjyRJ2fBtXhCTozG\nk3PkWjwtY0bjqRk0XUzWDAHPzxHJkInhyRni7a6GvwhN0zqUUr8GtiulKoEy4O9w9R5fc2NdlZd+\nrZTqwtW7LXZzhycc+AQoxfU5hbj+xkHTtM+Pax1PvwReUEodAw7jmsrSF9cfgdsopf4DeADYAnQp\n18WjAG2apvW6oyZN07qAEWN1z/8+Nbl5Z+NJYL9S6vu4jkQuBB7GNRWlOM9Ts+BaPCgnRuOROXIt\nnpgxo/HgDJoWJmOGwKTJEcmQCeDJGTKpOj3n/S0wgGutHhNwCFijaVqbW6u6nCcc4ViP6wL0eFxn\nw+Di+FXdRBWhadqryjUP/o+AUOAEcKumaQ0TVcNVfBPXZ/HJ57Zvw/X75Snc/rukadpRpdSduKau\n/gdcwzD+WtO0P7q3sknB7T+/UXhETozGg3PkWiZLxozG03+Hp7rJ8Pl7fI5IhriVR/wOT6rhbUII\nIYQQQghxozxi9jYhhBBCCCGEGC/S6RFCCCGEEEJMadLpEUIIIYQQQkxp0ukRQgghhBBCTGnS6RFC\nCCGEEEJMadLpEUIIIYQQQkxp0ukRQgghhBBCTGnS6RFCCCGEEEJMadLpEUIIIYQQQkxp0ukRQggh\nhBBCTGnS6RFCCCGEEEJMaf8PUJAvj+BeZCgAAAAASUVORK5CYII=\n",
- "text/plain": [
- "<matplotlib.figure.Figure at 0x7f7c581e64d0>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "pl.figure(4,(10,7))\n",
- "\n",
- "param_img={'interpolation':'nearest','cmap':'jet'}\n",
- "\n",
- "pl.subplot(2,3,1)\n",
- "pl.imshow(da_emd.G,**param_img)\n",
- "pl.title('OT matrix')\n",
- "\n",
- "\n",
- "pl.subplot(2,3,2)\n",
- "pl.imshow(da_entrop.G,**param_img)\n",
- "pl.title('OT matrix sinkhorn')\n",
- "\n",
- "pl.subplot(2,3,3)\n",
- "pl.imshow(da_lpl1.G,**param_img)\n",
- "pl.title('OT matrix Group Lasso')\n",
- "\n",
- "pl.subplot(2,3,4)\n",
- "pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3)\n",
- "pl.scatter(xst0[:,0],xst0[:,1],c=ys,marker='+',label='Transp samples',s=30)\n",
- "pl.title('Interp samples')\n",
- "pl.legend(loc=0)\n",
- "\n",
- "pl.subplot(2,3,5)\n",
- "pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3)\n",
- "pl.scatter(xsts[:,0],xsts[:,1],c=ys,marker='+',label='Transp samples',s=30)\n",
- "pl.title('Interp samples Sinkhorn')\n",
- "\n",
- "pl.subplot(2,3,6)\n",
- "pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3)\n",
- "pl.scatter(xstg[:,0],xstg[:,1],c=ys,marker='+',label='Transp samples',s=30)\n",
- "pl.title('Interp samples Group Lasso')\n",
- "\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 2",
- "language": "python",
- "name": "python2"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 2
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython2",
- "version": "2.7.12"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 0
-}
diff --git a/notebooks/Demo_2D_OT_samples.ipynb b/notebooks/Demo_2D_OT_samples.ipynb
deleted file mode 100644
index e20b09b..0000000
--- a/notebooks/Demo_2D_OT_samples.ipynb
+++ /dev/null
@@ -1,234 +0,0 @@
-{
- "metadata": {
- "name": "",
- "signature": "sha256:e01831efa84095a87a681a09f08c8991bbe439e010c2bc4cd3559dc4d3bf0bde"
- },
- "nbformat": 3,
- "nbformat_minor": 0,
- "worksheets": [
- {
- "cells": [
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "import numpy as np\n",
- "import matplotlib.pylab as pl\n",
- "import ot"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [],
- "prompt_number": 1
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Data generation"
- ]
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "n=20 # nb samples\n",
- "\n",
- "mu_s=np.array([0,0])\n",
- "cov_s=np.array([[1,0],[0,1]])\n",
- "\n",
- "mu_t=np.array([4,4])\n",
- "cov_t=np.array([[1,-.8],[-.8,1]])\n",
- "\n",
- "xs=ot.datasets.get_2D_samples_gauss(n,mu_s,cov_s)\n",
- "xt=ot.datasets.get_2D_samples_gauss(n,mu_t,cov_t)\n",
- "\n",
- "a,b = ot.unif(n),ot.unif(n) # uniform distribution on samples\n",
- "\n",
- "# loss matrix\n",
- "M=ot.dist(xs,xt)\n",
- "M/=M.max()"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [],
- "prompt_number": 2
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Plot dataset"
- ]
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "pl.figure(1)\n",
- "pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n",
- "pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n",
- "pl.legend(loc=0)\n",
- "pl.title('Source and traget distributions')\n",
- "\n",
- "pl.figure(2)\n",
- "pl.imshow(M,interpolation='nearest')\n",
- "pl.title('Cost matrix M')\n"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 3,
- "text": [
- "<matplotlib.text.Text at 0x7f4fa73d45d0>"
- ]
- },
- {
- "metadata": {},
- "output_type": "display_data",
- "png": 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Cd5pZEcGPw4Pu/mQE7YqISIJ0BqiISBbTGaAiIgVEyVxEJA8omYuI5AElcxGR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\nXEQkDyiZi4jkASVzEZE88P8B8sPqteLhUE0AAAAASUVORK5CYII=\n",
- "text": [
- "<matplotlib.figure.Figure at 0x7f4fa94e0590>"
- ]
- },
- {
- "metadata": {},
- "output_type": "display_data",
- "png": 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- "text": [
- "<matplotlib.figure.Figure at 0x7f4fa7419e10>"
- ]
- }
- ],
- "prompt_number": 3
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Solve OT"
- ]
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "G0=ot.emd(a,b,M)\n",
- "\n",
- "\n",
- "pl.figure(3)\n",
- "pl.imshow(G0,interpolation='nearest')\n",
- "pl.title('Cost matrix M')\n",
- "\n",
- "pl.figure(4)\n",
- "ot.plot.plot2D_samples_mat(xs,xt,G0,c=[.5,.5,1])\n",
- "pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n",
- "pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n",
- "pl.legend(loc=0)\n",
- "pl.title('OT matrix')\n",
- "\n"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 4,
- "text": [
- "<matplotlib.text.Text at 0x7f4fa724b150>"
- ]
- },
- {
- "metadata": {},
- "output_type": "display_data",
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- "text": [
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wd24wcMtRdH//MKrvPYS17ziXQuT1z8hgFmpYGLs32TXWjz461DN/7jmvxu2n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\n/XWSd0EBCSs62rHnqe6VuXkzf2evOqIabW3Ad75DmWbbNv7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- "text": [
- "<matplotlib.figure.Figure at 0x7f4fa7268ad0>"
- ]
- }
- ],
- "prompt_number": 4
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Solve OT with entropic regularization"
- ]
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "# reg term\n",
- "lambd=5e-3\n",
- "\n",
- "Gs=ot.sinkhorn(a,b,M,lambd)\n",
- "\n",
- "pl.figure(5)\n",
- "pl.imshow(Gs,interpolation='nearest')\n",
- "pl.title('OT matrix sinkhorn')\n",
- "\n",
- "pl.figure(6)\n",
- "ot.plot.plot2D_samples_mat(xs,xt,Gs,color=[.5,.5,1])\n",
- "pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n",
- "pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n",
- "pl.legend(loc=0)\n",
- "pl.title('OT matrix Sinkhorn with samples')"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 5,
- "text": [
- "<matplotlib.text.Text at 0x7f4fa703c550>"
- ]
- },
- {
- "metadata": {},
- "output_type": "display_data",
- "png": 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5eXmorKxEJBLBddddh0gkMq5rFVcNA/CLX/wCmzZtQn9/P2644YaUcnHct7a2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- "text": [
- "<matplotlib.figure.Figure at 0x7f4fa7056ed0>"
- ]
- }
- ],
- "prompt_number": 5
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [],
- "language": "python",
- "metadata": {},
- "outputs": [],
- "prompt_number": 5
- }
- ],
- "metadata": {}
- }
- ]
-} \ No newline at end of file
diff --git a/notebooks/Demo_2D_OTmapping_DomainAdaptation.ipynb b/notebooks/Demo_2D_OTmapping_DomainAdaptation.ipynb
deleted file mode 100644
index 4b75f58..0000000
--- a/notebooks/Demo_2D_OTmapping_DomainAdaptation.ipynb
+++ /dev/null
@@ -1,283 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## OT mapping estimation for domain adaptation"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "import numpy as np\n",
- "import matplotlib.pylab as pl\n",
- "import ot\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Dataset generation"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "np.random.seed(0) # makes example reproducible\n",
- "\n",
- "n=100 # nb samples in source and target datasets\n",
- "theta=2*np.pi/20\n",
- "nz=0.1\n",
- "xs,ys=ot.datasets.get_data_classif('gaussrot',n,nz=nz)\n",
- "xt,yt=ot.datasets.get_data_classif('gaussrot',n,theta=theta,nz=nz)\n",
- "\n",
- "# one of the target mode changes its variance (no linear mapping)\n",
- "xt[yt==2]*=3\n",
- "xt=xt+4\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "### Plot source and target datasets"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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iSpWq5M+fn0KFClGiRClWrVrllOfw4cOEhYVx8+bNDKqlEEI82KRHVAjxwLp2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\nE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- "text/plain": [
- "<matplotlib.figure.Figure at 0x7fb824ddf510>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "pl.figure(1,(8,5))\n",
- "pl.clf()\n",
- "\n",
- "pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')\n",
- "pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')\n",
- "\n",
- "pl.legend(loc=0)\n",
- "pl.title('Source and target distributions')\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### OT linear mapping estimation"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "It. |Loss |Delta loss\n",
- "--------------------------------\n",
- " 0|4.009366e+03|0.000000e+00\n",
- " 1|3.999933e+03|-2.352753e-03\n",
- " 2|3.999520e+03|-1.031984e-04\n",
- " 3|3.999362e+03|-3.936391e-05\n",
- " 4|3.999281e+03|-2.032868e-05\n",
- " 5|3.999238e+03|-1.083083e-05\n",
- " 6|3.999229e+03|-2.125291e-06\n"
- ]
- }
- ],
- "source": [
- "\n",
- "eta=1e-8 # quadratic regularization for regression\n",
- "mu=1e0 # weight of the OT linear term\n",
- "bias=True # estimate a bias\n",
- "\n",
- "ot_mapping=ot.da.OTDA_mapping_linear()\n",
- "ot_mapping.fit(xs,xt,mu=mu,eta=eta,bias=bias,numItermax = 20,verbose=True)\n",
- "\n",
- "xst=ot_mapping.predict(xs) # use the estimated mapping\n",
- "xst0=ot_mapping.interp() # use barycentric mapping\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### OT kernel mapping estimation"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "It. |Loss |Delta loss\n",
- "--------------------------------\n",
- " 0|4.026411e+02|0.000000e+00\n",
- " 1|3.991051e+02|-8.782091e-03\n",
- " 2|3.987950e+02|-7.769290e-04\n",
- " 3|3.986577e+02|-3.442631e-04\n",
- " 4|3.985741e+02|-2.096899e-04\n",
- " 5|3.985159e+02|-1.460105e-04\n",
- " 6|3.984729e+02|-1.078536e-04\n",
- " 7|3.984436e+02|-7.368218e-05\n",
- " 8|3.984214e+02|-5.574123e-05\n",
- " 9|3.984025e+02|-4.740267e-05\n",
- " 10|3.983871e+02|-3.865975e-05\n",
- " 11|3.983744e+02|-3.175451e-05\n",
- " 12|3.983642e+02|-2.561334e-05\n",
- " 13|3.983558e+02|-2.116042e-05\n",
- " 14|3.983479e+02|-1.982104e-05\n",
- " 15|3.983413e+02|-1.643931e-05\n",
- " 16|3.983351e+02|-1.567880e-05\n",
- " 17|3.983296e+02|-1.366612e-05\n",
- " 18|3.983270e+02|-6.571092e-06\n"
- ]
- }
- ],
- "source": [
- "\n",
- "eta=1e-5 # quadratic regularization for regression\n",
- "mu=1e-1 # weight of the OT linear term\n",
- "bias=True # estimate a bias\n",
- "sigma=1 # sigma bandwidth fot gaussian kernel\n",
- "\n",
- "\n",
- "ot_mapping_kernel=ot.da.OTDA_mapping_kernel()\n",
- "ot_mapping_kernel.fit(xs,xt,mu=mu,eta=eta,sigma=sigma,bias=bias,numItermax = 20,verbose=True)\n",
- "\n",
- "xst_kernel=ot_mapping_kernel.predict(xs) # use the estimated mapping\n",
- "xst0_kernel=ot_mapping_kernel.interp() # use barycentric mapping"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Plotting the mapped samples"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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hYQF5eWn4+3uZyUopOXs2FWfnQNzdte/s7e0JCmrIpUuCS5cuXadalWTJkiW0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\nCgpqdHC4a2LZsmXodDp0Oh1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cuHAGDWpOVFQiY8euY/HigXTqFGx1g2uFQnHzoQwZrm6+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dPaytjMDNVaDe3S57+Qy6HodOtKUHeLWq1uRMmWqdfrjN64Qeittwh985sE3/tePAMDDAwNrZOC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mOfNDCCHElqirq0NRFIaHx0kmg9hseg4dapd9m0KITSWJzA7gcrk4ftxFLpdDo9HIGTJCCCG2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\nAOjOJ9ftJm14VELcAAAAAElFTkSuQmCC\n",
- "text/plain": [
- "<matplotlib.figure.Figure at 0x7fb822b4b250>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "\n",
- "pl.figure(2,(10,7))\n",
- "pl.clf()\n",
- "pl.subplot(2,2,1)\n",
- "pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.2)\n",
- "pl.scatter(xst0[:,0],xst0[:,1],c=ys,marker='+',label='Mapped source samples')\n",
- "pl.title(\"Bary. mapping (linear)\")\n",
- "pl.legend(loc=0)\n",
- "\n",
- "pl.subplot(2,2,2)\n",
- "pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.2)\n",
- "pl.scatter(xst[:,0],xst[:,1],c=ys,marker='+',label='Learned mapping')\n",
- "pl.title(\"Estim. mapping (linear)\")\n",
- "\n",
- "pl.subplot(2,2,3)\n",
- "pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.2)\n",
- "pl.scatter(xst0_kernel[:,0],xst0_kernel[:,1],c=ys,marker='+',label='barycentric mapping')\n",
- "pl.title(\"Bary. mapping (kernel)\")\n",
- "\n",
- "pl.subplot(2,2,4)\n",
- "pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=.2)\n",
- "pl.scatter(xst_kernel[:,0],xst_kernel[:,1],c=ys,marker='+',label='Learned mapping')\n",
- "pl.title(\"Estim. mapping (kernel)\")\n",
- "\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Barycentric mapping on the left, estimated mapping on the right. We can see that the change \n",
- "in variance of the mode do not allow for a good linear mapping. In this case the kernel \n",
- "mapping (lower right) allows for a far better estimation\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 2",
- "language": "python",
- "name": "python2"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 2
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython2",
- "version": "2.7.12"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 1
-}
diff --git a/notebooks/Demo_Compute_EMD.ipynb b/notebooks/Demo_Compute_EMD.ipynb
deleted file mode 100644
index cda9a59..0000000
--- a/notebooks/Demo_Compute_EMD.ipynb
+++ /dev/null
@@ -1,167 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Compute and plot EMD"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "import numpy as np\n",
- "import matplotlib.pylab as pl\n",
- "import ot\n",
- "from ot.datasets import get_1D_gauss as gauss"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Generate data"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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EwzCM70VVyU4twlHhbOiq1Lsm1WRkGIbRkDITC1j7wWHSj+YTGhnAiGld6dg/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YVw/XwGT5zA2ea94O/tMtPpdLHWaKLuYhfWfm/u/q6iFgbsLlalm6g6fQK7RYGXX/QxksuGO+0W\nLOc68Di8DQN31OzALdwsjFjI+fPncbm8N3nz1i2g0eC3ZAqtLZ8ghPfjVJxpIzzBn9SEQDa39fjc\neBNCjeQmBl+bbRSeDjGTrsk2Sg1OJTM085plI11SEvqJOZivUTZSq1WkT4nk0vlOnwecLzL+lQ0h\nDrjS2atx6HuKGCGECzADV4/YugkoEEJcmb+9MVQu+pXko44hSdI3JUnKlyQp/7JS9H9CdPTbOVrZ\nydrcON/eRX3NMqc/5zaf3kUtAy0UtBewKtV3KcjR0IDt/AUCV/nOILqaB+io7yf9GuWilspyOutr\nmbRoKXPGRPBpYbOXr7y9uhd3tw3TrGRIngvn3/fyla+srGRgYIA50+eQE5HDluotXh/Yjo7PcLn6\niM/8Gn5ZWZg/2ex1P1vbe7F6PNw/NprgKCOlx70/1NsuNONwe1i/bBIBYRFcPPCZ9xMr2gTCjWbR\nelQmLYMKp7PtNdsRCO6dei86nY6CggIvjHmbLMiLuvVBJElHS4v3ibLidBuSBCvmJaKR4JM2782n\n7PPDSCoVK9euQK2S2HLOeyG3FLSBWsKwcD4gwUXvjffs2bNotVrWzpbPb0obb3Pzh2g0wSTOfRg8\nHvq2ey9W7zZ3E63TcvuUeDweodj03JjfQFKYkRuXz8HldFB+XGHuxbl3ITIb/Zz5CLt7tJUF8oHj\n06pPyQnPYWneUiwWCxUVFaMxbjd927bjP3cusZl3Y7M30909ujTZ226hvbaPsVOjuS06lEqLndNm\n38KxNRNjKWnpo7TF90AlJtwMzYXQVe0TsjJlJRc6L9DQ1+ATE3T9auxlZdgrK31ixk6NwuX0/Ec0\nCV9KU1mSpGzkMtK3rvj2XUOlpLlDX/co/a4Q4mUhRJ4QIi8i4ho8/f/PYtv5ZtwewY3XKhcVfQwI\nyLnVJ2THJflDviLFm5Z5OXo/2gQq1XDKqhTFh5tQaSQyZ/gWx13Ytxut3kDWnPncmBtHU6+VM7Wj\na52Dp1tRGTUYssNh4u3QXQ2N+aMwBQUF+Pv7k56eztq0tVT1VlHSXTIK09KyCb0+gZCQGQSvuwFb\ncTG28tGLw4et3aQb/cgLMpE1K4aWKjO9baNrwR+fbSQrJpDx8SGMX7iE2guF9HVcVZ08/z7ETkaK\nzsI4JRJraTfuK07BQgi2V28nNzKXtLA0cnJyKC4uxmq1jsL0bduOcepUjAljiYpcQUvrZlyukYVI\neAQVp1uJywghLtzEkrBAPmrtwX6Fw6fb5aT40D6SJ04mMS6S2enhbDknv1cuh8fhZvBsO4bx4aij\n42X65oWNozZem81GUVEREyZMICUshSlRU9hWvW3UxutwdNLRsZeYmBvRp47FMGkS5k8/HYVptjk4\n2N3H7TGhRMUHEJEYQPnJ0RtmXdcgJ2u6uWVKPNHpYwmLT6To0FXlp/YyaDoLk+5ElxqMJkyPJX/0\nxlLaXUpVbxVr0mRTwcDAQK+Nd/DkSVzt7QStXUtExFK02lCamj8Yhak80wYSjJkayQ2RwfirVWxo\n9m0cty43Dj+NindOKpc3AblsJKnh7Js+IStSViAhsa1mm09M4IrloFZfM0uITg0iIFRPxekvn230\nr2wITcCVvLf4oe8pYiRJ0gBBQNfQ/8cDm4F7hRDD26sQomnov/3Ae8ilqf81sbmwifFxgYyJUmZA\nIAQUviOXisKUyzwuj4uN5RuZFj2NhAAFaiLgcTjo3bQJ/4UL0cYos4IcNhdlp1pJnxyJIUC50Wkb\nGKD8xFGy5sxHZzCyLDsKo07NJwUjbwX3gANrSRfG3EgkrUoWqWkM8oI7FH19fVRWVjJp0iTUapnD\nrVPp2FK1ZRhjtTbS3fM5sTE3IUkqAlevBq0W8ycjJ+4ai51T5kFui5ZN8zJmRCOpJEqPj9SCK9v6\nOd9o5qbJ8qY7foHMsR+1WLUWyXbSE+8AwDQ1GobKXpejrLuManM116fKG2peXh4ul4vz50fsrq0F\nBThqawlcI7Nn4uLuxO0eoK1tZHGoK+6ir9PGuNkyxfi+2HA6nS52dIzU06vOnGSwt4dJy+Rez215\nCTT1WodHqwJYL3QgbC78pw/9PSfeDj2XoHbkpHzhwgWcTid5QwLE1amrqe2rpahzpC7f0vIJQjiJ\ni5X7U0E3rMVeWYX9CoO5D1u78QB3xMhlzYwZ0XTU99PVNNI/+ii/EZUEN02JR5Ikxi9YQktlOV2N\nV5yUz70LKg3k3IYkSRjzorDXmHF1jWyqW6u3olVpWZ6yHJVKxaRJk6iqqsJ8BXe/b+tWVAEB+C9c\ngEqlIybmRjo7D2C3y9UDj0dQdqKFuLHB+IfoMWnU3BwdyraOXrqdyiWYYKOO63Ni+bSwiQG7jzJN\nYIwsBizcAE7lvk60KZpZcbPYVLEJp0e5V6UJD8c0ZzbmzZsRPibESSqJMdOiaCjtpr/bh0biC4p/\nZUM4A4yRJClFkiQdcDuw9SrMVuSmMcDNwAEhhJAkKRjYATwmhPj8MliSJI0kSeFD/9YC1wPKHaT/\ngVFQ38PFJjM3T1YeYA5AzSHoKIOp3/AJOdxwmJbBFu7MvNMnpn/3btzd3YTceYdPTOWZNpw2N+Pn\n+c5WSo4ewOWwk7NEzkSMOg3X58Sw9XwzvZYhs7aCdnALTNOGsgx9oGxlUbQJHPJJ+dy5cwghyM3N\nBSBQF8jCxIXsurQLp1v+ELW0fAxIxMTcBIAmJISABQswb9uGGPLd/7C1GxVwS7S8UJmC/EgaH0bZ\nyRY8bvnEvamgEbVKYu0k+XkFRkSSnJNL0cF9eDxDdefLC9V4+VraCCO6lCAGT7cON5c/KP8AvVrP\ndcnXARAdHU1cXBz5+fnDp+nuDe+gCgwkaKhpHxQ0BX9TBk1N7w1jLh5qwhikIzVXznTnhwaQYtDx\nRuNIaeDcnh0ERUaRPEkWZC3LjiI6UM/bJ2qHMQMnW9BEGdGlDFFAs9eBIQRO/xOQs5X8/HxiYmKI\nHfL4WZa8DIPGwAflHwxjmpo/JCgoD9MQkylw+XIkrZbej+WN1yME77V0MzfEnySD3PobO1W2Zy87\nIW+8bo9g09lG5o2NICZIputmzV2IpFJRfGSouex2ydTpMdeBv/zcTZOjQILBoSzB6Xays2YnCxMW\nEuQnayEuv0cKCwvlhzGb6ftsL4HLl6Pyk+8nLvZ2hHANvWeg7mInfZ02xs8b+WzdGxuG3SPY2OKb\nuXP3jEQGHW4+LfRtU820b8h6oGLv8uXluDPzTjqsHYoDii5H6F134erouKZyOXtOLAhB0ZFr3M8X\nEP/lhjDUE3gQ2AOUAhuFEMWSJP1OkqTLJODXgDBJkqqAR4DL1NQHgXTg11fRS/2APZIkXQDOIWcY\nr/w7n9h/53j92CUC/DTcnKd8qgfg1EtgipDppj7i/bL3iTZFMz/Bt51Fz3vvo0tOxjRTmc8uht50\nYXEmotOUB/MIIbiwbzfRaWOIShnJVtbPSsHqdPP+6QaEEAyebkWXFIg2yjTyy3lfk6mz59/H4/FQ\nUFBAcnIyYWEjLaZ16evotfeyu3Y3QnhoadlEaOgc9PoRsV7Qjetwd3fTf+gQLo/go9ZuFoQGEO03\nQsXNmhWDxeygvqQbm9PNpvxGFmZEEhEwwmOYsGgZ/V0d1F04J99XwQZ5QTWN3I//tGjc3TbsNb10\nWbvYXr2dNWlrhhcqkLOEzs5O6urqcLa00L93L8G33IzKKDfkJUkiLu4u+geK6es7T2+bhfriLrLn\nxqHWyB87lSSxPi6cM32DFPVb6KivpbG0iIlLV6IaEmRp1Srump7I0cpOqtoHcDT242wcwH96zEjP\nSGuAKetlb6OeOhoaGmhvbx/ODkCeA7w2bS27Lu2i09pJb+8prNba4ewAQB0cTODKlfRu3ozbbOZY\nzwANNgd3xYy8NoYAHckTwyk70YrT4eZoZQetfTZuveK9bAoOISU3j5IjB3C7XLJt+0Ab5N41cq0g\nP/RjQ7CcbUN4BJ/VfUaPvYcb0m8YxoSEhJCamkphYSEej4fejz5CWK2E3DVyADIaUwgOnk5z84cI\n4eHCwUb8Q/xInTQiiBznb2BKoJF3Wrp8NpcnJQSTHRvIOyfrfM9ATp4L4Rlw2vdSNSduDvH+8bxf\n+r5PjGnOHHRJSfRsuJp0ORKB4QaSc8IpOdY87DT7ZcS/1EMQQuwUQowVQqQJIZ4c+t6vhRBbh/5t\nE0LcIoRIF0JME0LUDH3/90II0xXU0klCiHYhxKAQYooQIkcIkS2EeFgoUQX+B0Zzr5VdRa3cPi0B\nfx8iKbqqZfOvvAdAo0zKquqp4lTrKW7LuA2NSvlxbCUlWM+dI+SO232KpNpq++hsGGD8vDifTemm\n8hK6GuuHs4PLMS42kFlpYbx9ohZLdS+uTutIdnA5EmfIZa8TL1JbU0Nvby+TJ4+2I5gZO5O0oDTe\nKn6Lzs5D2OzNxMbcPArjP3cu2thYut98i20dvTTbndwbO1oFnTQhDEOAlqLDTXxc0EjXoIOvzx2t\nGUjLm44hIJCL+/dAwduyp87M743CGMaHIxk0DJ5u5aOKj3B4HNw17q5RmOzsbPz8/Dh79iw978mN\n89A7R2dq0dFrUatNNDW9S9HhJlRqiey5oxXpt0WHYlBJvNnUxfnPdqLWasleMFoLccf0RHRqFRtO\n1DJwsgVJq8I4+Spq8NSvAxKceZWzZ8+i0+m8vIvuHnc3Lo+LD8s/pKn5QzSawGG7jcsRev96hMVC\nz8aNvNvSRbBGzfKrFOATFydgG3RSdryFd07WE2LUsjhr9P1MXLqCwZ5uyo8fgePPQ2AcjBktNDPm\nRePuc2At6eTN4jdJCUphdtzsUZjJkydjNpuprqige8M7GGfOQD/kPns54mJvx2qrp7bscxrLesie\nF4fqKtfge2JlVtfxXh/2EpLE3TOSKGvtp6Deh+OoJMmvc3OB3A9RCJWk4vbM2yloL6Csu0z5YVQq\nQu66C+v581gvejPRLkfOwnhsA04qz3x5jPyvlMpfcrx9Qj6B3Dcr2Tfo9CtyGSPvAZ+QD8o/QKfS\nceMY3xlEz/vvI+n1BK1b5xNTfLgJjZ+asVcv5FfEhX270RmMZCp4Fz0wO4UWs42az2qR9GpvqwpJ\nkhfc7mqO79+G0Wj0sqpQSSruy76P8p4yiqr+hN4vloiI60Y/jEZD6Pr1WM6e5f+U1TLG6Mey8NGq\nWbVaRc7CeC4VdfLPA9XkxAd5UXrVGi3jFy6l+swJPMdfgKQ5EJs7+lpaFabJkZhLWvmg9APmxM0h\nNSh1FEan0zFx4kTKL1ygZ+NGAhYvRhs3uuSm0fgTHb2Wlqa9lBxvIm1yJKarlNvBWg3rokLY2tBC\nydEDZM6ahzFw9AIc7u/H9Tkx7MpvxHKuA+OkSFT6qw4BQfGyZcjZ9ykuLiYnJwc/v9HXSgpMYn78\nfHZUvE97++6hDWu0ylmfmYlx5gxKtu1ke3svt0WHDs+XuBwxaUFEpQSyZ98l9pW2ce/M5FHOpgAp\nk/IIT0iiZttLUHdMfg9cJaw0jAtDHarn0LE9lHWXsT57vZewMjMzE5PJRMUbb+JqayNs/XqujoiI\n69BogincX4Zao5LLLVfFmsgQAjXXbi6vmRiLv5+Gd076FjAy8XbZZPLMaz4hN6TfgEFj4P0y31lC\n0I3rUBmN9Lzzjk9MXEYIobEmLhxs8J21/Jvjqw3hSwyLw8X7p+tZPj6a+BBlrj/2frmZnL0OApQX\n6X5HP1urt7I8ZTmhemUNg9tsxrxtO0Grr0cdqGw3YO13UHm2nYxpUegMyllGX2c75cePMm7eIrR6\nb4uERZmRzAw2ElQvlzFUSgZ9WWtp9s+hqsXMzJkz0Wq9FderUlcxOSAQj7WSxKRvoFJ5Y4Jvvomz\n02ZR6pH4bmIkKoWMZvz8eGoNUG+28s15qYpZz5RVN5AR3IVqoAVmPaj4vP1nxXLEP58uexf3jFMk\nwJGXl0d8TQ0es5mQe+5WxMTF3UXPpck4bR4mLFDuGa2PCyetrACnzcbEZcrU4DULUAEAACAASURB\nVHtnJTPfqQaXB9MMH5YhM77DaXsKLpdrVLnoyrh73N3k6jrwCCcJ8fcpYsLuv593psxCJQTfTvRm\n9kmSRO7SRPZbBtGrVaxXONxIksTUNTeR4c7HrQ2Ayd7XktQSAfPi2ejeRpg2dLhpf2VoNBpmzZxJ\n8JEjqBISMM319s9Sq/2ICr+b1rI4kifpFYkRRrWK26JD2d7RS50P5bLJT8ONk+PYcaGFjn4f6mZ9\nIEy8TWYA+jC8C/ILYlXqKnbU7Bg1GXDUPfv7E3TjjZh37sLV6VvdPGFBPJ0NA7RW+zbF+3fGVxvC\nlxgfFzRhtjr52hzf1gece08uY0z/tk/I5srNWF1W7szy3Uzuee89hM1GyJ2+MQWf1eN2echZ5LuX\ncWqzzG+fukY5E1GpJB7xD8SOoCZV2ZMItYYjxhXosTE1Xtl+Q6fWcXOEiX43DOgnKl/LaGTjLfcQ\n3tPF9QPKH0a9ScuFMAjySMyIVN4ITUHBzEk00+0w0Beaq4hRh+rZEnuERHsM0/yVRYERERGMr6vH\nHBKCdFV55nL4GzPou7QKfWgj4YnK9iTZBi2zi07QFZVAWKryFLucqADWq/SUagTqGJMixhYxkRPS\nNMbq2oiOUtaTTApNY26AhwpnMAZDsiKmb9oMds1ayPUXzxKtU/57aRJNlOvcTNPoCTYqYzIyYkgP\n6KLMMQb8lN8bTalmzvqXsM62FJ1ameGWrVIR2tNDXU6Oz9KnpXElwqUnKNW3MOw7CZGokPhbnW86\n5/pZybg8Hl467FtvwNRvyO4Bp/7pE3JH5h3Y3XY2VfgWs4XcdSc4nfRs9NaQXI6M6dH4GTVcOOTb\neuTfGV9tCF9SuD2CN45dYmJ8EJMTQ5RBLjuceB7ip0K88iJkcVp4reg18qLyyA5TNqlz9/bS9drr\n+C9ejF7BSRRkr5eLhxrJmBZNqI8Fpq+jnaKD+5iwaBmB4cp2Fs4OCzFNFnaoXbySr5xqt7W1Udbu\nYLq6BP3ZlxUx/f3FGJ01HB808paPhlxB3yBn/IO59che+l9/QxGTX9tN5YCNaU4tF/f5+BDVnyDQ\n0UhhTzxntim7WJ5pPUOVqOWG7oUMHFNmegwcPoyhvZ3yMemcPHlSEVOZ34a1J4SQMbtoalIuDxQd\n3Iuht4uDkxf4LGkMnmwhyAN/d1l8MmFOnjqFTWhZ4NjncxZwQ+MbaCTBx51WTrScUMS81NCBR63m\nlo1vYzl1WhHzyrEaVJLEuHYPLT7smtUnX0CotByu1NJUXqqIeav8bQySnmVVU0emqV0V/e++h8dk\n4pRBPzxN7cpwOd1cPNRJcOwAFt5jcNBbtQ0Qq9dxd2wYH7Z2+8wSUiP8uWlyPBtO1tFq9kH5jBon\nU6pPPA+Dyn+vsSFjmRU7izeL3xweY3p1+KWkYJo/j54N7+AeUO5taP3UZM2Kobqgg0Gzb0+mf1d8\ntSF8SbHpbAM1nYN8a36az+Ytp1+B3npY+HOfj/NWyVt027r5wZQf+MR0vfoqnsFBIh5+yCfm7O46\nPG7B1OuTfWJObv4QSYLp63wL4/oPNiBpVKhnRLPzYisXGr0Xh6NHj6LT6ZieOwGKP4WOci9Mbd1L\nqNX+RMbeyu5LuxVtFl6obydIo+auqBDM27fjVFgcXjpcQ7BRy81T4ik70cJAz1UfIiHg8J/AEIon\n53YuHtjDYO/oJqJHeHiu4DkiDZFcn7yKwRMtuAdGc8aFy0X7n/+MLikJw4oVnDx5EotltCjO7fJw\namsN4Qn+pOSaqKt/GZdr9OLgtNs48fEHxGZkETUhl+fq2hh0j+ZXeOwu+g814DcmGE+cib/urcB2\nFfPEarVy4sQJMjPGEhsWBPsel+meV17L2UNj4wYiIlYg6WL4W8Hf8IjRrpodDicbmju5KTKYeDx0\nvviiV/26vd/GxvxGbp4SR4RJR8EehYNAXzOc/wCRezfCGM6Zrd4n5ZaBFnZd2sWNY24kUBdI3yFv\nha+tpISBAwcIueMONCYTR496K6AvHmpioNvOrHU5qFR6LtW+4H0/Q/FQUhQaSeLZWt9ZwkOLxyCE\n4PmDvtXELPqlPGr12F99Qh6e/DC99l7eKFI+vABEfP8h3D09dL36qk9MzqIE1v5gEsZA32aI/674\nakP4EmLA7uKZPRVMSQpRHNACyPzmI89A2mJFP36ALmsXbxa9yZLEJUyMUC6rONva6d7wDoGrr0c/\ndqwipr/bRvHRJrJmRhMUodzLMLe3UnxoHxMWX0dAmPdMA5BnJlvOtWOaHsP6pWMI99fxxPaSUQtI\nZ2cnxcXFTJ06FePCH4LOH/aM3vAGB6tpb99FfPw93J39DTQqDc+efXYU5kK/hZ0dZu6PCyfx3rtB\nCDpf/McozPHqTvaVtvHA7BRmXJcsa/v2XqU+rdgNNQdh/k/JW3cnHpeb/O2jeeW7L+3mYudFHpr8\nEOGL0xEuDwNHR29QvZ98gqOqmogfPcL8RYtwOBycODH6xF18tIm+Thszb0gjLe0HuFxm6htGLw6F\nu7cz2NPN3Dvu4xfpcXQ4XLzWOLqmPHCsGY/FRdCyZB5bnkVTr9VLVXvy5EnsdjsLFi6Cpb+Fzgoo\neGsUpr7+ddxuC2kp3+fhyQ9T0lXiZWfxckMHNo/godQYwr/7HSynTw8Psr8crx69hMvt4TsL05m0\nJIG6oi4ayq4q4R35Mwg36jkPk3vdKqrzT9FSNfog8OzZZ1Gr1Nw3YT3+s2KwFXfhbL1C2S0EbX94\nCnVICFHf+ibTpk2juLiYKy1sbINOzu6qJXFcKCkTkomPv5u2tu3DM5evjmg/LffGhvFRWzeXLMon\n7oRQI7fmJfDhmQbfLqgRGbKY8fQrYFbORMeFjWNFygo2lGzwaeBoGJ9N4PXX0/3mW4o+UgABoXri\nxob4Pkj+G+OrDeFLiJcOVdM5YOeXq7J8/1GP/kXmxS/9nc/HefnCy9jddh6a7Pvk3/mPFxFuNxHf\n/75PTP7OWgDyVvnuZZz8ZCOSSsW0G27xiek7UA8qFQHz4wnQa3lkaQZnanvYXTRyct+/fz9qtZqZ\nM2eCKRzm/0Qe+FMhewoJISiveBy12kRiwnqiTdF8bfzX2FO7h9MtcrnCIwSPVTQSrtPwnYQItHFx\nhN51F70ffTRM23O5Pfx2awlxwQa+OS+VoAgDmTOiKTrUNKKqddnlzSg8A6Z+jZDoWDJnz+Pcnh2Y\n2+V7trlsPFfwHFmhWaxOW402woghJ4KBE83DdhYei4WOv/8dQ24uAUuXEhUVRXZ2NqdOnRrOEhxW\nF2d21BKXEULCuFACA8YTEXEd9fWv4XTKGYltcIAzWzaRMmkK8VnjmRpkYmlYIC/Ut9M7pKr1WJz0\nH21EnxWKLiGAOWPCmTsmnOcPVtFnk0V6VquVkydPkpWVRXR0NGSshMSZcOgpmaQAOBxdNDS+TWTk\nCvz9x7IqdRXZYdk8V/AcVpesvG2wOXitqZM1kcGkG/WE3HYbfmPSaf/jn/DY5cWzqr2fNz6/xLrc\neJLCTExcnEBguJ6jH1TgHhIE0lwI+a/DtG9CaApTVq3DFBLK/tf+MSwIPNN6hl21u7h//P3E+Mfg\nPzsOyaChZ0v18IGif89nWPLziXjoIdQBAcyYMQOtVsu+ffuGMWd312G3uph5o6yPSUz8OiqVjku1\n/8fn+/bBxCi0ksSzdb4dRR9clI4kSfyf/dfIEhY8Bgg4/EefkO9P+j4uj4uXzr/kExPxg4fB7abj\n73/3fa0vKb7aEL7gaOq18srRGtZOiiXXV++gp05uUE26E6KVm5MN/Q1srNjIujHrSAlSXsgd9fX0\nbvqYkFtvQZeg3Cjubhmk9HgL2XPiCAhVHqzSWlVB8aF95CxZTkCocnZgq+rBUtBOwOxY1EOsjlvz\n4smICuCpXWXYXW7KysooLS1l/vz5I0Nwpn0TwtLlhdnloK1tGz09x0lPexSdTr7W/ePvJ9YUy1On\nn8LlcfFeSzcFfRZ+nRZLkFZmQ4V//0E04eG0Pv5bhNvNhpN1lLf186vrs4ZnS8xcl4bWoObw++Wy\n6vjUP6G7Bq77wzAFcs4d9yGpVOx7VS6NbCjZQMtgC49OfXSYAhm4JBHhFvRulRuNXW+8gbujk8hH\nHx3e4OfPn4/T6WTf0Gm6cF89tgEnM9eNlAhTUx7G7R7kUu2LAORv24xtcIDZt987/Lr+LDUGs8vN\n8/Uy97zvUCPC5iZw6chsgJ8uz6TX4uSfQ43P/fv3Y7fbmT9/SKAoSbDs9zDYAZ/LC2NF5RN4PHZS\nUx4GZKrvo1Mfpd3SzpvFbyKE4GcVjQgBv0yTaZuSRkPkY4/hbGyk+623EULwi81FGLRqfrZS1gJo\ntGrm3DKGnlYLFw82gscDO34kiyqHSp9+RiPz7/kabTVVXNy/B5fHxdOnnybGFMMD42VqtdqkJWh5\nMo5LZiwF7XjsdtqfeQa/jAyCb5E1KSaTiQULFlBeXk5paSl9nVYuHGwgc3o04fGyBYyfLpzEhAdo\na9tGV5eCwR4Q5adlfVw4m1p7yPdhehcTZODu6Ul8XNBIWasP07vgRJkaXvgudCpvHAmBCdyScQsf\nV35MrblWEaOLjyfkrrswf7IZ21Vmfl92fLUhfMHxzG5ZnPKT5Zm+Qft/KxtnLfyF4o+FEPzpzJ/Q\nSBq+M/E7yhiPh5Zf/RpJpyPs28oMJbfbw/43S/AzaMhbmayIcTkc7P7Hc5hCQ5l9qzKV0uNw0/NJ\nFZowPYFLEoe/r1Gr+MWqLOq7Lbx5pJIdO3YQGRnJrFmzRn5Zo5MX5K5KnKf/TkXl7wkMyCEubsRa\nQ6/R8+jUR6nqreK10k08Wd3MjCATN0eNbKhqf38if/pTbMXF1Lz3EX/dW8Gc9HCuyx4pyRkCdMy6\nMZ2WKjMVhy7KJbkx18GYEeFXYHgEc26/l9rzBZw8vI1XL77KooRFTI0eGeCijTASuCQR68VO+o+U\n0fXa6wQsW4Zx8ghD6fLzLCgo4EJ+Kef2NZA+JZKo5BGmk79/BnGxt9PQ8AY1RdvJ3/YxGbPmjVJ/\nj/M3cHNUCP9s6KCktJ2Bo40Y86LQXTHBbnxcEGsmxvLasUscLywhPz+fmTNnytnB5YjPk6nLJ56n\no+5D2tq2kZz8vWGbCoApUVNYmrSUN4re4J3GevZ19fFYajQJ+pFatf/s2fgvWkTXSy/x0eFSTl3q\n5rEVWYT7j2gcknPCScwO5cz2S9iPvyGLtpb9HvQjeorMWfNIyM7h2Ptv8+6Ft6noqeDRqY9i0IxM\npzNNjUaXGIB5Zw1dr7yOs6mJqJ89hqQeYWfNmDGD6Ohodu7cyfHNlUhITFszWiOSnPwgRmMKZeW/\nGGUueGX8KDmaGD8tPyirx+pWnk724KJ0Qow6frTxPA5fE8zm/gh0Jtj6EHiUtbXfyvkWfmo/nj7z\ntE89Qfi3v4XK35/2Pz3zpWkOlOKrDeELjANlbXx6rpmvz00hLlh5LCMXN8mc5jk/gCBlL6GPKj7i\nUMMhHsx9kEijMtun+823sJw6RfQvfo42UhlTsLuO9rp+5t+Z4bNBdeLj9+lqrGfZNx7Ez+iDffRZ\nHe5uGyE3jUG6atLbvLERLMiI4Mjhg/T397NmzRrU6qvolmOWQdpiquv+jtPZQ2bm75HnMI3E4sTF\nzIiZwZ9rO+lzuXlqbLxXuS1w1UqM06fzzN5KrA43j68Z54XJmhlDTHoQqv2/RjgtcN2TXs9n0nUr\niU4fy1MFf8TutvNI3iNemIB58WiiDLT8+ufg8RD5I2/MggULCA8L5/A7VahUMOsm72ln6emPodPE\ns+cfL+JnMrHo/m95YX6bHkeMpGJwUxWqID+Cr0/1wvxsZSb+Gti2bSuhoWEsWqTQd1ryOC61RHn5\nrzGZxpKc5H2tH07+IQ6h45eVTUwMMPD1eG/dQdRPHsWMhj/sKmdyYjC3Tx2dfUqSxNxbx6J29aI6\n8DgkzfZy6JUkicUPfBuze4AXzr3I9OjpLEkcrciWVBLB68bg6myh6+VX8F+yGNOMGaMwarWa1atX\n4+w0UH22k0lLE7wyXbXaj6zMp7HZmqiu+Yv36wIEaNT8NTORKoudZy4pl45CTTr+cOMEipv7eP6A\nj9KRfySsfAbqj8Nx5TJVmCGMhyc/zOdNn/NemfIwI3VwMBEPPsjgsWP0vO9b0PZFx1cbwhcUjT0W\nfvjhecbFBPL9RcrccrqqYdvDcr137o8VIdW91Txz5hlmxc7yKZCylZfT8eyz+C9ZTNCNynqB9ro+\n8nfUMmZqFOlTlDeM1qoKzmz5mPELl5KSqyxsstf3MfB5E6bp0filKs85fnhGKOlSGy26eMKjFERU\nkkTPvHtpilSR0OtPgMF74ZQkiQUZP6bfMIskdyFjFLjukiRRcOdD7I6dzC22atLCvTcwSSWxLPcs\nY7QHqfG/FxHmfS2VSo15RSKXwvpYYZtCUqD36EZJrUJyfI67tZSAFd9Al+SN0Wq1jA2ajcpmIiBz\nQLEkp9H4M1i+BEuniuzV4V6qZIAwnYbX2zTEDLr5dGaItyoZuaTxQEo/OreN/uhJimI/QpKpnDsX\nu9rJuMEsVCrvQ0BCYAKJ6U9gx4956kLUCj0ubVISb617hD6h5qeGJsX5HcGRBtamvY3aPUBt4mOK\n8zuCYmMpXCywe+zc5a88v0MTosZe9BpCSATf+T2vnwME+IUSPJCJU9tH1ARlbUdwcB7xcffQ2Pg2\nvWZlm4n5oQHcExvGSw3tnPVROrouO5obJ8fxwqFqzjf4mLyWcxuMuwEOPAkt5xUhd2Tewbz4efw1\n/6+Ud3uz7ABC7r4L0/x5tD/9R2xlyrYXX3R8tSF8AeFwefjee4V4PIIX75qsPC/ZZYdN98u17Jte\nBbX3h97utvOTIz/BqDXy5JwnFecle+x2mn/8KKrgIGKeeELxQ+Zyutn/VimGAC3zbldmHjmsFrlU\nFBLC/Hu+pohxDzrp2ViBOlBH0ArlPkZfXx8Hd21Fb/Rnf18kv97ibWJrtTZwsf5JDJoIUosvebGO\nACoGbTxeZyde56Kv+QWeO/ucF6akuY+fH2tnksHJHbv+Sefzz3vfUNNZ/I//AnPgTPZUrKRwrzdF\n8lz7OV6peYuJqnTC9rdyYd9uL4wlP5/ut17GMGUhHs94LOe9WSNN5T1UnughMMlDWcsZysu9P/h1\nF89RvO8kydOicJq209XlPQ/ZVtVDcEEnF8YF8jvPIIe6vWvYlZWVtNeU4IkcwysFfRyr9Fa7trfv\nptmeT6IjmcCjb8Al75r6u81dnLaGkCWV8tHFpznb5r14vnbsEjsG/bnHXkXgX3+P9bzConf4T4SZ\n91Gs/yZ7PvXQUe/Nvf9bwd8oE/Usa8uk6JX36GwYzZQSQtD6uydwNdXgv+g79O+T/bGuDLfbw2ev\nFaPRaiChiU82fzzKHvvKSEv7MXq/GEpKfozDoawX+HVaLDF+Wh4uq6fPpVzy+c3qbCID/Hhk4zms\nClPekCS4/lmZNPHxNxTtsSVJ4onZTxDoF8hPj/x0uJE/CqNSEfvUU6iDgmj64SN4LD4YTl9gfLUh\nfAHxh52lnG/o5U8355CscGpFCPjsV/JpYu2Lsg+NF0Tw1KmnqOip4InZTxBu8G7uCrebll/+Cntl\nJbFPPokmxLtp7XZ72PNKMd3Ngyy8Nwu9yfsk6XI4+PSZ39Pd3Mjy7/wQvclbVepxuOl6sxhXr53Q\nOzIVT612u513330Xm83G+nvu4tsLM9iY38hH+SP8cpern/MXvoEQbiZN/QDN9AfhzKtwbiRN7nG6\nuO9iDTqVis15k7gz40beKnlrFEWyZ9DBNzfkE2TQ8vIPlxO+bi2dL/6Dvl1XzA4e7IKN94F/FIHf\nfJfUyTGc2FxNzbmRxbzH1sOPD/+YKFMUz9/8Oqm5U9n32otcKhwZ6uPq7qbpx4+iS0gg/oU/4pcS\nRPfGcmxXCLL6u23sfaOE4EgjN31/DtHR0Xz00UejRm32tDSx6/m/EBIbz6rvPIvJNIai4ofo7x8Z\nDuRoGaTr3TI0EQYW3DKOMUY/Hiypp3JwRCTV2NjIxo0biYqK4tH1N5EWYeKRjedo7BlZQHp6TlFU\n/EOCgiaTOn8jhKbBx1+HgRGjtEPdffykooGFoQF8PHMNcf5x/OTwT+iyjiye+0raeHJnKSvGR/PL\nx+9HGxlJ48M/wNV9Bc20ZAsc+gNMvIO07/4Ovb+WXS9dxHqFdmNnzU7eLH6T2zJu41ffeBGNzo9P\nn3kCa//IZte7aRPmTz4h/LvfIeZXsplg51vFeCwjswVOflpD26U+Ft6dxR333YzD4Rh+z10dGo0/\n48f/Dbu9nfPnv67YTwjQqPlbViK1Vjv3XqhR7CcEGbT86eYcajoH+e67Z5X7CcZQuOFF6CyHT7+r\n2E8I1Yfy5OwnqTZX8/uTv/fSgABoQkOJfeYZHLW1tP72d19+P0EI8f/N15QpU8R/5/B4POL5A5Ui\n6afbxeNbi3yBhNj7GyF+EyjErp8pQtwet3jixBNi/JvjxbP5zyo/jNstmh77mSjJyBQd/3hJ+XHc\nHrHnlYvi+W/tFxcONihjXC7x6TNPiD/fukqUHDmgfC2XR3S8USQaHjsiLEUdihiXyyU2bNggHn/8\ncVFZWSmEEMLpcovb/nlcjPnFTrGnqEW43Q5RUHCv2H9grOjqPj70i04h3lglxBORQlQfFA63R9xS\nWCniD54Tp3r6hRBCONwOcd+u+8SUDVNEYVuhsNhd4o6XT4gxP98pCuq65edht4tLt98hSidOEpYL\nF4WwmoV4fYUQvwsXovGsfD92l9j41Bnx0vcPiva6PtFt7Ra3bbtN5L6dK4o65b+X3WoRb//kIfG3\ne24SrTVVwtHWJqpWrRKlOROFpUjGuAcdouWv+aLx158Le1O/6Ouyird/8bl4+eFDor2+TwghRH9/\nv/jb3/4mnnrqKdHa2ip6WprFS9++V7zw9TtFZ0OdEEIIi6VRHD02Wxw+kicGBiqFo31QND1xQjT/\n4aRwdlmFEEJUDFhF9tGLIufYRVE9aBNtbW3i6aefFs8995zo65OvVdJsFuN/s1vMfnq/qO8aFP39\nZeLQ4Yni+IllwuHokV/nlgtCPBElxN/zhDA3i6J+i0g7fF4sOl0q+p0uIYQQpV2lYvLbk8UtW28R\nXdYuUdTUK7J+tUus/vtRYbHLGEtRkSidkCMu3XGncJnNQjSfE+L30UK8slgIh3zPbbVm8Y/vHRSb\n/3JWOOwucb79vMjbkCfu3XmvcLgcQgghmspLxbN3rhUf/vZnwuV0iP7Dh0XphBxRd/8DwuOSr2Wr\n7hUNPz8q2l8+L9xOlzizo0Y8/6394tC7ZcPvu6qqKvHb3/5WvPXWW8I19HtXR3vHPrFvf7ooPHe/\ncLsdipjNrd0i+kChuOd8tXC6PYqYd0/WiaSfbhfffeescLrcihhx7Dn5s/3xN4VwK9/PC4UviPFv\njhe/+fw3wu1Rfpz2vz8vSjIyRfPjjwuP28e1/h8CyBf/whorif9gR/v/NfLy8kR+fv5/DfwPhBCC\np3aV8fIRmWL651smor3KJRKPB/b8TJ51kPcArPwLXOXN4hEenjz5JBsrNrI+ez2PTHnEqwwkPB5a\nf/Mbej/aRPj3vkfE970N2oRHcPCdMkqPtzDzxjQmL/OueXs8bj77598pPrSPheu/yeQVa7wfx+Wh\n55NKLAXtBN+Qjr+CsZrD4WDLli0UFxezevVqpkwZsd3otThY/8YZKltb+cvST9G6jpOV+TSxsVfo\nGwY64O019Pa28LV57/G508hfMxO48wof/i5rF/fsuoe2vkGCe35KTbvgzzdP5KYpI9mVq7OTS7fe\nimTvIWUdqC31cOPLw8NvQLbs2PTHfHo8Xeyd/DKt9hb+suAvLEhYMHI73V2898sfox0cZFZDJ6LX\nTMI//oFp+shQP5fZTseL5xhwuDlhFdjtbtY8NImolBFWUU9PD6+//jrCZsG/sQq3w8Gtv/4DEUkj\n5TaL5RJnC25HawknMf8X4FER8a0ctFcIBksHrNx0ropQm4U1546hQvDAAw8QGjpibHihsZe7Xz1F\nSnAnj0x5HrUkkZe3adRMCeqOw7u3cCF8CveOewKVSsOOKWOI8RvpLRxpPMIjhx4h0JNLT93N6DUa\ntnxvNpGBI/2Qvt27aXr0JwRPDCZ6XA2SPhC+cRACRvyTyk+1sv/NErrHVvNpxD8JN4Tzzsp3RmW6\nxYf3s/vFZxlvCCLxzHn0GRkkvPbqqEx38Gwb3RvLqTTqKG2xkDE9mkX3Zo6yty4sLGTLli2MGzeO\nG264AZ3Ou1fS1PwhZWU/JypqDeOynkal8raVf7Opk8cqGrk5KoTnMhPRKPRKXj1aw+93lHLz/23v\nzMOkKK+F/zvV2/Qy+wzDwKwsguwMyCIGF8AoqNy4ojGb5sO4a+5zEzW5CS5PPmO+JFeNu2I0IBq5\n7kaNIkER2UGWGZaBYYbZ96V7ptd6vz+qBqZnQAkReTLUj6fpqerTb72nTnWdqrfOe86kHB66bNyR\n66F/8jv4+AGYcC1c8mif37hSike3PMoz25/h0uGX8uvpv+4zHKyUouEPf6TpmWdIvvRSsu+/Ly7a\n6p9FRDYppY78YLAHtkWLFh33Rr5pnn766UULFy482d3oQziq88s3dvDC5+V8f3o+D146DntvZxDp\ngnfvNCbsTLsZLnyoz4ESiARYtGYRr5e+znVjruPOSXf2cQaxtjaq776H9rfeIv2GG8i87dY+Ml0d\nYT54bielm+qZPK+AM+b2He/3Nzfx5u8eoHTDWqZddjVTjzABLdoaoun5nQR3t5A0J5/EmX2Htlpa\nWliyZAllZWXMnj2bab2iQhIcNuacFqVAu4cEVUKz7Samjbk+vs9OL2XD5nO5mkKJ8vA/zv0sGB1/\n7HocHkYlns2yj7NoaBeuOTvIrTPji/5oHg9JU08jpfUZtHAj/pybcV0Y2lz5EQAAGD1JREFU7yyd\nCXa0ggAPtf+Slkgzdw96gHlFc+Jl3B5yktLwPv8X9PYO1B23kHNxvLPUEuy0ex2sXF1LOBjlgosL\nGTw5PqGc2+0mkRj73nuDcLCTqT+4gRET43NUORypJLVMxfHBCPRIFNdVkJQfH4SQ6XQwvKkWtfJ9\ngtEoZ1x2JWNz4lM8ZyUlcEbWFka67qMzokjNfZz8rF6hzim5vJp+Ltc5ZuAJtbK00E1hRnw7+Un5\ntDaczt/X5xGTFh6+ZgSje5VedQ0bRmJ6JSnRtwm324h9Zwn2vPicWRk5PtYlfMSLkUfJ6MrhiZlP\nkpMR305mfiGp20pI/vvHtKUmkf3YY/gGxx9jtgEeNpW0sOtAB4VJDs794SjsvbKZZmdn43Q6Wbt2\nLXv27GHo0KG43fFRfUmJY9DExcHK52luXk1a6lk4HPHJDyckebAJPFPZyJpWPzNTE0nslda7KD8V\nTYTnVpfxRWUrM4Zl4O1d1yR/Bihg3eNQXwJDzjGKGJmICFMGTiGmYiwpWUJ5eznTsqfhsrniZDzT\np4EmtLzwAuHychLPO/e4ncK9995bs2jRoiMnEuuB5RD+RTYeaOb6Fzawak8jt5w7jHvmnt73quHA\nalh6BZStgpk/g9mL+kRhrK1Zy40f3sjm+s3cNOEmbplwS58TfWDNGip+/H8I7txJ5p13kHHTTX1k\nKoqbePuRL2ip6eSsK4ZRdH5+H5kDWzex/De/oq2hjvNvuI1J8+b30Su4u5nGxTuI+SOkLRiBb1r8\niUMpxZ49e1i6dCldXV1cddVVh0oe9pSpb3if4p034nWEWNXwX/z+0zw2V7QwKT+VFI8TXSmW17Xw\n4101BB0+ljS9zLfX/hpqtkPuGZCQTExXLFtfwX+9ugun5mbyxLV80vw05e3ljMsYh8/pM/L2rHsS\n23u3oXkSaKifSd3SfxCpqsY9YTyax0NEj/D8juf5742/wOGy8cOOn+Ff5SPQFiJ7aDJ2pw0VDtP4\nxJM03Xc/Tq+P/WdPY/3W9XS2t5Fz+mhsDgexiM76t/fzj1dLcSY6OCvPh2tHIzF/hIShyYhNIxqJ\n8OmyF/j0L8+RlJaGfdQkvti7j87OTgoKCrDZbKioTtvfygj8rQF7mpf6KYupCPyJaKSdlJRpaJqd\naDTKBx98wNoVH5GROYCPJ36LZzui+GMxpiX7sGtCLBZib+lvaKj+PW7vGP646Wae+ixMV0RnckEq\ndpuGPxpjUWk1v6npYorXziubbyV/w8PGWHfuFNDstHVGeODdYp77pJ6J+V5k0GO8W7EUEWFcxjhs\nms24m3vv59i3P4uePZ3y9xJoefVdxOnCPWY0YrNR31nP/WvvZ1nFEqanz2D21uso/7wDZ4KNjLxE\nRITwwYPU/OznhP/2HvYZZ7Im08eOT1fiTUklM68AEaGurJ13HvuCg2XtjJk8gFHBCJ0b6rCnJmDP\n8sQd17m5uQwePJgtW7awadMm0tPTycjIiJNJSZmMzzeS6uq/Ul39Cj7vaXg88RdL01N85LudLK1p\n5qWaJkZ43QzxxN9NTClMI8Pn5KV1Fby66SCnZSX2fVZYcJaR4XXDs0YG4wGnQ9rh8OFup+C0OXlp\n10u8s/8dhqUMi6uNLiJ4p0xBXC46/v4hSfMuwuY7cij4V3GsDsEaMjpOqlu7+NPKUl5aV8Gg5ATu\nmz+G2aN6pRxuLoPVfzRyyqQWwMWPwJD4cpf72/bz5x1/5vXS18lPyueBGQ8wYcCEOJng7j00L15M\n25tv4hw6lEG//S3uMfGZThsqOtj8QTmlm+pJzfZy/vWjyciJfzhcW7qHz197mf2b1pORm89Fd/yc\n9Jy8OJlQeTvtH5UT2tuKPctD+rWnxw1fAFRUVLBixQrKy8vJzMxkwYIFcSUxAVpbN1Ja+iBt7Vvw\n+UYydszjuBLyWLK2nN99sJtITGf+eYVs8sHOQJDxiW6eGl1AgctuxHOvegiUYt2Y/+beA2MorvUz\ntTCN3142jty0BJ7a9hTPbX8Om2j8etAsLty1Cq2+GIbNhnm/RyXl0vDwIzQtXgwuJ+U/mctTmdsp\nbdvHrLxZ3DXlLga4s1j7+j62fFSBK0Fjcm49iR8vIVy6l6SLLiLrnrvRkpP5dNkLbHz7NRISkxk+\n9WqaqjNorulk5JnZnHX5MJwuG23vHzDyHflsNAyq44udH5pV5i7g7O9dj2Z3sGLFCj7//HNSklKY\nnTuV9HI7scYg3unZpMwtRNeilO57kMrKF3G5Cgl2XcGOHZ20trYxdepU5syZQ0iE+0qreaG6iZFu\njf9MWkNK84uEw3Xk5v6IYUN/jj8Mv3m3hJc3HGRolo+xMwbzYbiLpkiMhTmZ/GroIOzBFnj/Ltj2\nCsGM0bw48Jc8ttNOezDCdTMKufvCkTSHGnlw/YN8WP4hI5OG8DtXIflfLEfCnUYdifN+Rbimjtr7\n7yOw6hNkxFBWLpzE863vEdWjXDfmOm4cf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- "text/plain": [
- "<matplotlib.figure.Figure at 0x7f2b0307b850>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "\n",
- "n=100 # nb bins\n",
- "n_target=25 # nb target distributions\n",
- "\n",
- "\n",
- "# bin positions\n",
- "x=np.arange(n,dtype=np.float64)\n",
- "\n",
- "lst_m=np.linspace(20,90,n_target)\n",
- "\n",
- "# Gaussian distributions\n",
- "a=gauss(n,m=20,s=5) # m= mean, s= std\n",
- "\n",
- "B=np.zeros((n,n_target))\n",
- "\n",
- "for i,m in enumerate(lst_m):\n",
- " B[:,i]=gauss(n,m=m,s=5)\n",
- " \n",
- "\n",
- "# loss matrix and normalization\n",
- "M=ot.dist(x.reshape((n,1)),x.reshape((n,1)),'euclidean')\n",
- "M/=M.max()\n",
- "\n",
- "\n",
- "M2=ot.dist(x.reshape((n,1)),x.reshape((n,1)),'sqeuclidean')\n",
- "M2/=M2.max()\n",
- "\n",
- "\n",
- "# plot the distributions\n",
- "\n",
- "pl.figure(1)\n",
- "pl.subplot(2,1,1)\n",
- "pl.plot(x,a,'b',label='Source distribution')\n",
- "pl.xticks([])\n",
- "pl.title('Source distribution')\n",
- "pl.subplot(2,1,2)\n",
- "pl.plot(x,B,label='Target distributions')\n",
- "pl.title('Target distributions')\n",
- "pl.show() "
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Compute EMD and sinkhorn distances "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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8atatW9dYjC2l7HJYWBj29vaMHTsWR0dHunfvnuHO2aSkJEaNGsX06dONj2VW\n1jgsLIzOnTvj4uJCly5duHjxImCo6fPqq6/SqlUrJk+ezMyZMxkzZgydOnWiUaNGLFy4MIf/G0XX\n/YcJ+Ab6MnjJ78TFJ7FqTEs+edZVEruJFYnknleyKpEbFxfH2LFj2bp1K/7+/ly7di1bx1u+fDn+\n/v74+fmxcOFCbt40VEGOiYmhVatWBAYG0qpVqyzL/Y4ePZpFixYRGBj4yPOcO3cuzbBMZkkzNS8v\nLzp27EhgYCDHjh3D0dExy7a+vr5YWloSEhLCrFmzjPV1IiMjmTt3Lnv27OHYsWN4eHiwYMECACZN\nmsTRo0c5ceIEsbGxbNu2zXi8hIQEjhw5wueff86sWbMynG/IkCFs3boVNzc33nrrLf76669M4zpz\n5gwTJ07k5MmTVKlSJU29n4SEBJ5//nmaNm3K3LlzgazLGr/22muMHDmSoKAgnn/+eby8vIzHCQ8P\n5/fffze+rtDQUHbt2sWRI0eYNWsW8fHxj/w5Fwe/n43k6c/3AzCidQN2vdGBjrbmucpacVNok3vE\nosWE2NkTYme41Tvl+4hFi3N9zJQSuUuXLsXa2pqhQ4eycuVKQkNDadiwIU2bNkUpxQsvvJCt4y1c\nuNDYU7x06ZKxiJeFhQWDBg0C0pb7dXNzY+7cuYSHhxMVFUVUVBQdOnQAYMSIEVmeJ2VYJuWrffv2\nj4zr119/Zfz48cZYUkrvZmb//v3G1+vi4oKLiwsAf/zxB8HBwbRr1w43NzdWrVrFhQsXANi7dy+t\nWrXC2dmZX3/91VgEDdKWCk75hJNa3bp1OXXqFB9++CElSpSgS5cu/PLLLxnaNWzYEDc3t0yP9cor\nr+Dk5GR8k4SMZY1T2h8+fJjnnnsOMPyMDx48aHzOs88+m2bIrFevXpQpUwYrKytq1KiRaZnl4uJu\nXDwDv3uPVw49RVTN1wHYFDWcNmuby7x1M1FoBxKtX5tkHGcPsbPHPjQkT46bWYnclCSSmdSlgOGf\ncsD79u1jz549HD58GEtLSzp16mTcV7ZsWWPSyKrc7+MuHGZH6iln+VGmuFu3bsbFN1KfZ8KECfj5\n+VGvXj1mzpyZ5tzZKRVcpkwZevbsSc+ePalZsyabN2+mS5cuGdqksLCwSDMs07ZtW/bu3ctbb71F\n2bJlgUeXNc6KlCnO3J7g60zbfJyIey0Z22EYb3S1xfM7N5m3bmYKbc89P2RVItfOzo6wsDDOnTsH\nkCah2djtUf5pAAAgAElEQVTYcOzYMQCOHTtmnNlx584dqlatiqWlJaGhofzxxx+ZnjOrcr9VqlSh\nSpUqxp5kTsv9AtSsWZOQkBCSkpLYtGmT8fEuXbrg62tY6CQxMZE7d+5keYwOHTrw3XffAYaFQ1KW\nzmvdujWHDh3i7NmzgGHY4/Tp08ZEbmVlRXR0dI4vzB47dowrV64AhnHzoKCgHJcpfumll3jmmWcY\nMmTIYxNw27ZtjYutrFmz5rGfeoqzm9EP8Pr+L15e7UdVy9JsntiOd3vapynLK8xHkUjuVhMn5slx\nsiqRW7ZsWZYuXUqvXr1wd3enRo0axucMGjSIW7du4ejoyOLFi7G1tQUMddATEhKwt7dn6tSptG7d\nOtNzPqrc74oVK5g4cSJubm5ZLsYBGcfcUy72zZs3j969e9O2bVvjyk4AX3zxBXv37sXZ2ZkWLVoQ\nHByc5bHHjx9PdHQ09vb2zJgxgxYtWgBgbW3NypUrGT58OC4uLrRp04bQ0FCqVKnC2LFjcXJy4umn\nn8bT0zObP32DGzdu0KdPH5ycnHBxcaFkyZJMmpTzmVBvvvkmzZs3Z8SIEWk+WaW3aNEiVqxYgYuL\nC9988w1ffPFFjs9V1Gmt2RJ4hW6f7WfHiav8p2tTtkx6Epe6VYxtZN66+ZGSv7mwb98+PvnkkzQX\nCoWAwvM7nF3X78YxbdMJ9oRcx7VuZeYPdqXZE1KW15SyW/I3Wz13pVQPpdQppdRZpVSGlZiVUqOU\nUhFKqYDkr5dzE7QQwvR8AnzQWrPu6EW6LviNA2ci+O8zdmwY31YSeyHy2AuqSikLwBvoBoQDR5VS\nW7TW6T/Lr9Na//s7iQqBlAuuQhRFvoG+/O7XgoNnI2nZsBofDXKhoZWU5c1LeXXj5aNkp+feEjir\ntT6vtX4IrAX65VdAphomEuLfKuy/u0lJmhWHDBMC/rp4mzn9nVg7trUk9nyQVzdePkp2knsd4FKq\n7fDkx9IbpJQKUkqtV0rVy+xASqlxSik/pZRfREREhv1ly5bl5s2bhf6PRBQ/Wmtu3rxpnHpZ2Mw9\n9Dmu37iw4GxfAEo0fof5p3qzJMjXxJEVQbG3C+Q0eTXPfSvwvdb6gVLqFWAV0Dl9I631UmApGC6o\npt9ft25dwsPDySzxC2HuypYtS926dU0dRo4kJCax9MB5Vu9pRrlSnzKjtwMzT/SUOev5IGLR4jQ9\n9pQbMK0mTsyXIZrsJPfLQOqeeN3kx4y01jdTbX4FzM9NMKVKlaJhw4a5eaoQIoeCr9xl8oZATly+\nS0+nJ5jVz5EaFcsy84SpIyuarNtWxPp2BFS1IcQ7Js9uvMxKdpL7UaCpUqohhqQ+DHgudQOlVC2t\n9dXkzb5A/kYthMi1BwmJLP71LL77zlHFshQ+z7vzjPM/90HInPU8lpgAP0+HP32hcRcYvBy82+T7\naR+b3LXWCUqpScAuwAJYrrU+qZSaDfhprbcAXkqpvkACcAsYlY8xCyFy6djF20xZH8SZG9EMbF6H\n//V2oGr50mnaSK31PBR7G34YDef3QusJ0G0OWJTMsxsvH8WsbmISQuQtnwAfJrhNIPZhIp/8fIrl\nh/7miUpl+WCAM0/Z1Xj8AUTuRZ6B74fB7QvQ+zNwz7r4X05k9yamQls4TAjxeL6BvrhVHMLUDce5\neOs+z7eqz9SedlQsK7XW89XZXww9dotSMHIrNMj/YZj0JLkLUUTdizPUm39u2Z80qG7J92Nb06Zx\ndRNHVcRpDX8ugV3/hRoOMPx7qFLfJKEUicJhQoh/+AT44LzKmbbr3AGoaD+VWzW8+OveOhNHVjQZ\n15BIeAhbXoOdU6HZMzBml8kSO0jPXYgi5XbMQ86casu9kAY0rVGBa9UnyZz1fBbp7Y316KHwfyPg\n4mHo8A50+i+UMG3fWZK7EEWA1prtx6/x3pYTRN2Px6tzEyZ2boJHzpcBELmxrDPE3IBBX4PzYFNH\nA0hyF6LQu3E3jv/9eIJdJ6/jXKcyq8e0wqF2JUDmrOeXDHebfpkAVMOq8jWsnU0XV2qS3IUopLTW\nrPcPZ862YOISkpja046Xn2xISYt/hgNkznr+sJ40Eevm8bBnFiFra2F/5FeoVOvxTyxAktyFKITC\nb9/nv5tOsP90BJ42VflokAuNrCuYOqziIeEhbHsDAr4FxwHAn2aX2EGSuxCFivdf3lSM68VHO0LR\nwOx+jrzQqgElSqjHPlfkgZibhgunFw5BxynQcSpW13xMHVWmJLkLUUicj4hmSdAS7oXY0L6pFR8O\ndKZuVUtTh1V8RJyG74bA3Ssw8CtweRYg3xfdyC1J7kKYuYTEJL4++DcLdp+mdFP4eLALg1vURSnp\nrReYc3vh/0ZCydIwahvUa2nqiB5LassIYcZCr91l7JYPiCrzU4Z9413HywXTgnD0a9j+Dlg3g+fW\nmfTGJJDaMkIUag8TkvDeexaffWepVLYL8/q9zjPOT+Cy2kVuSiooSYmwa5qhVG/T7oY57GUrmTqq\nbJPkLoSZCbwUxeT1QZy6fo/+brWZ0ceRaunK8or8YVy4Ou4ubHgJzvxsKNXbfS6UsDB1eDkiyV0I\nMxH7MJHP9pzmqwPnqVGxLMtHedDZrmaaNnJTUv6K9PbG+oU+hlK9EacMpXo9xpg6rFyR5C6EGfjz\n/E2mbAgi7OZ9hresz7vP2FEpk7K8MsZeAJZ1hqR4eGEDNH7K1NHkmiR3IUzEJ8CHEXZj+WhnKN/+\ncZH61Sz57uVWtG1iZerQipUMpQSWlwZKY1X+JNavSXIXQuSQb6Av3+5oxtW7cbz0ZEPe6m6LZWn5\nkyxo1hPHY213Aw59Qcja2tgfOwSW1Uwd1r8mv0lCFLCo+w+ZvS0YAMsyJVn/altaNKhq4qiKqbi7\nsOFlOLPLMLa+dmeRSOyQzcU6lFI9lFKnlFJnlVJTH9FukFJKK6UeOwdTiOLojV0f0f6HFuyONayn\neb36JEbt64BPgHnewl6k3TwHX3WFc79Ar0+h92cFsnB1QXlsz10pZQF4A92AcOCoUmqL1jo4XbuK\nwOvAn/kRqBCF2Y17cbz340l2nHDCsbYP8we7MGz3kzJn3VTO7zPccaoUjNgEDTsA5ltKIDeyMyzT\nEjirtT4PoJRaC/QDgtO1mwN8BLyTpxEKUYhprdl47DKztwUTG5/IO083Y1yHRpSykBUuTUJrOLIU\ndr4LVraGNU6rNTR1VPkiO8m9DnAp1XY40Cp1A6WUO1BPa/2TUkqSuxDAlahY/rvpOPtORdCigaEs\nb5Ma/5TllTnrBSzhIWx/G46tMqxxOnAplKlo6qjyzb++oKqUKgEsAEZlo+04YBxA/fqmrc8gRH5J\nStJ8d+Qi83aEkpikea+PAy+2scEiXVlembNegGIiYd0IuPg7tH8Lnppu8jVO81t2Xt1loF6q7brJ\nj6WoCDgB+5RSYUBrYEtmF1W11ku11h5aaw9ra+vcRy2EmUm5IBoWGcPwZX8wffMJXOtV5uc3OjC6\nXcMMiV0UjIhFi+HacVj6FFw5ZqgP02VGkU/skL2e+1GgqVKqIYakPgx4LmWn1voOYLzrQim1D3hb\nay0lH0Wx4RvoS6m7Pfh09ylKWZTgo0HODPGoJ2V5TSzS2xvrux9A2cowegfUcTd1SAXmsclda52g\nlJoE7AIsgOVa65NKqdmAn9Z6S34HKYQ5O339HgDvbw+hq30N5vZ35onKZU0cVTGXlAT7PzZ8X8Me\nhq2Bik+YNqYCJvXchcilRce8WXp8SYbHpc66aUV89gmRX36d4XGriROLxFRHqecuRD4KCo/ip/3O\n3Ls2jz6utdn38EWZs24OboRiXfJ7rIdfh6ffJ2TUQuxDQ0wdlUkU/asKQuShuPhEPtwRQn/vQ9yK\neciyFz1YNLy5qcMSACc3GSo6xt2FkVuhdfGeaio9dyGy6WjYLaasD+J8ZAxDPerx3172VC5nKMsr\nc9ZNKDEBfpkJvy+Cup4wZDVUqg1QpMoJ5JSMuQvxGDEPEpi/M5TVf1ygTpVyzBvowpNNpSyvWYiJ\nhB9GQdgB8HwZnv7QsIh1ESZj7kLkgQNnIpi64ThX7sQyso0N7zzdjPJl5M/GLFz2h3UvQkwE9POB\n5s+bOiKzIr+lQqTjE+DD87ZjmftTMD/4h9PIujw/vNIGD5uiUQq2SPBfZSglUOEJeOlnqO1m6ojM\njiR3IdLxDfRlxU+23Ip5yIROjfHq0pSypQrX4shFUcSixViPHwvb3zHUh2n0FAxeXmTqr+c1Se5C\nJIuMfsB7W04CYFWhDCtGeeJUp7KJoxIpIr29sS6zwVBG4Mk3ofN0KCFvulmR5C6KPa01r+/8iL03\n1hgfC68ygeF75IYks3H+N8O/kWdg6Ldg38e08RQCktxFsXb1TizTNp3g11BnmtdfwvxBLgzc2VZu\nSDITEQsXEunja9wOWV0RVk/GauKFInG3aX6S5C6KJa013x+5xIfbQ4hPSuJ/vR0Y1TZjWV5hQtE3\nsK7yC9bDroDzEEKmHSy2d5vmhiR3UexcuBnD1A3HOXz+Jm0aVWfeIGcaVC9v3C83JJmBv/cbFq6O\nuwN9F0HzETDNwdRRFSqS3EWxkZikWXHobz75+RQlS5TggwHODG+ZsSyvjLGbUFIiHPgU9n0I1RrD\nCxvhCSegeN9tmhuS3EWR5xPgQ7daI5i8IYi/LkbR2a4G7w9wolblcqYOTaQWfQM2jjUsXu08BHp/\nBmX+WZZQxthzRpK7KNLiE5PwDfTl8x8aUr6MBZ8PdaOfW21ZRMPcZDYMI/9H/4pUhRRF1onLd+i7\n+BAA3RxrsvvNjvRvXkcSuxmIWLTY8E1SIvw2H1b3gzKVYOyv4P6iJPY8IMldFDlx8Yk8t342w/c8\nSXgVw/j5/viRPLXBw7jWqTCtSG9vwzDMtwNh7/vgNBjG7YOajqYOrciQYRlRpPiF3WLyhiDOR7Tg\n2Rb9mN7LgSd/cJd56+ZoyZMyDJOPJLmLIiHmQQIf7zrFqsNh1K5cjtVjWtLB1trUYYlUIhYtNvTY\nk4V8ZQFUw6ryXazdJbHntWwld6VUD+ALDAtkf6W1npdu/6vARCARiAbGaa2D8zhWITJ18EwkUzcG\nEX47lhfbNGByDzsqpCrLK/PWzYP1872wLrcZwo8SsrY29oFH08yGEXnrsWPuSikLwBvoCTgAw5VS\n6e8m+E5r7ay1dgPmAwvyPFIh0rkTG8+U9UG88PWflLIowf+90obZ/ZzSJHaQeesmpzUEfG8Yhok4\nDYOSF6+WxJ6vstNzbwmc1VqfB1BKrQX6Acaeudb6bqr25QHTLO8kijyfAB8muE1gd/B1pm8+TsS9\nB7zasTH/6Splec1S7G3Y9iac3AgN2sGAL6FKPawmXjN1ZEVedpJ7HeBSqu1woFX6RkqpicCbQGmg\nc55EJ0Q6voG+hIS0YWvgFeyeqMiyFz1wqVvF1GGJzIQdhI2vQPQ16DID2v3HWKJXbkjKf3l2QVVr\n7Q14K6WeA6YDI9O3UUqNA8YB1K9fP69OLYoBrTVbg64CsPPEVd7oasv4To0pXVJm85qdxHhD+YAD\nC6BaI8NKSXVamDqqYic7fxmXgXqptusmP5aVtUD/zHZorZdqrT201h7W1jKTQWTP/D8X4rLahWkB\nTwNQ1nYKX10eyFcnlpg4MpHCeFPSzXPwdTdDfRj3EfDKfknsJpKdnvtRoKlSqiGGpD4MeC51A6VU\nU631meTNXsAZhPiXtNb8n98lvtnRjIcJ83m7ezMW/t1P5qyboUhvb6zbVYIdU6BkGRjyDTj0NXVY\nxdpjk7vWOkEpNQnYhWEq5HKt9Uml1GzAT2u9BZiklOoKxAO3yWRIRoicuHTrPu9uPM7Bs5G0aliN\njwa5YGNVnoV/mzoykcH9W4Z/t7wGDTvCgCVQqbZpYxLZG3PXWm8Htqd7bEaq71/P47hEMZWUpFl1\nOIz5O09hUUIxt78Tz7WsT4nkRTRkzrr5yHBT0trawBms7m6UC6ZmQO5QFWbj7I1opmwIwv/CbTo1\ns+aDAc7UrpK2LK/MWTcTcXexrh9qWCXJ2o6QRXdllSQzI1MNhMmkFPGKT0zCe+9Znll4gLM3olkw\nxJUVozwzJHZhJs7tBZ82ELAGnnwDxv1m6ohEJqTnLkzGN9CXjjWeZ/L6IE5eucszzk8wq68T1hXL\nmDo0kZkH0bB7Bvh9DdWbwpifoZ4nIKskmSNJ7sIkHiQkAtBv8SGqWJZmyQvu9HCqZeKoRJb+PgA/\nToCoS9BmEnSeDqX++WQlY+zmR5K7KFA+AT74Bvoat8s1m8ID4HzCeEDG083OwxjYMwuOfGm4IWn0\nDmjQxtRRiWyQ5C4KzP2HCdwM70R0aANqVSrLvdr/kTnrZihi0WJDT/zCYUNv/dZ5aPWqoYRA6fKm\nDk9kkyR3USB+PxfJ1A3HuXjrPiNaN2BKTzvarDV1VCIzkd7eWNtehcPeUKU+jNwGDdubOiyRQ5Lc\nRb66GxfPh9tD+f7IRWyqW7J2XGtaN6oOyJx1s3TpqOHfw4vB4yXoNltK8xZSSmvTVOf18PDQfn5+\nJjm3KBi/hl7nvxtPcONeHC+3b8QbXW0pV1rK8pqjiM8/JXLJVxket5o4US6WmhmllL/W2uNx7aTn\nLvLcrZiHzN56ks0BV2hWsyJfjmiBaz0py2u2Tu3AOulrrIddhZZjCXlzm9yQVARIchd5xvsvbxpY\nDOC9H09yJzae17s0ZeJTTaQsr7m6dw12TIbgH6GGAzy7yjBv/c1tpo5M5AFJ7iJP3Lgbx5KgJdwL\nscGlbmXWjG2F3ROVTB2WyExSEhxbBbvfg4Q46Pw/aOsFJUsDckNSUSHJXfwrWmt+8A9n7rZgaAjv\n9rTjpScbUtJCeutmKeI0bH0dLv4ONu2h9+dg1SRNExljLxrkL1DkWvjt+3RbOY05J59BN3wbgMVh\n/Wn+rauxbowwLeMiGgkPYN88WNIObgRDP28YuTVDYhdFh/TcRY4lJWm+/fMC83aEoujA1J7jeL5V\nA1y/cZGbksxMpLc31n1bGHrrkafAaTD0+BAq1DB1aCKfSXIXOXI+wlCW92jYbdo3teLDgc7UrWpp\n6rBEZmKjDP+u6AGV68Pz66FpN9PGJAqMJHeRLQmJSXx18G8W7D5N2ZIl+HiwC4Nb1EUpZWwjNyWZ\nh4iFi4j0+WdYzLCIRgJWJU9hLcm92JDkLh4r5OpdJq8P4vjlOzztWJM5/ZyoUalshnaykIYZuBqI\nteUWwyIadT0J+eSyzFkvpuSCqsiUT4APDxISWbD7NH0WHeTqnVi8n3NnyQstMk3swsTu34Kf3oKl\nnQyFvvr5GOqti2JLeu4iU76Bvmze68jp69EMaF6HGb0dqFq+tKnDEuklJcFf38AvsyD2NrQcB53e\nhXKGO4Jlznrxla2eu1Kqh1LqlFLqrFJqaib731RKBSulgpRSvyilGuR9qKIgxD5M5P2fggG4G5vA\n8lEefDbUTRK7mTBObQS47A9fdYGtXmDVDF45AD0/MiZ2kDnrxdljk7tSygLwBnoCDsBwpZRDumZ/\nAR5aaxdgPTA/rwMV+e+/ez+h5fdurI0cCkBMnf/w+p9dZc66GYn09oaYm7DFC5Z1gbuXYeAyGL0d\nnnAydXjCjGRnWKYlcFZrfR5AKbUW6AcEpzTQWu9N1f4P4IW8DFLkr3tx8czbEcp3f9pTv9pC5g1y\n5pWDT8mcdXOTZFiakEXu8DAa2kyEjlOgrJR5EBllJ7nXAS6l2g4HWj2i/UvAjsx2KKXGAeMA6tev\nn80QRX7ae+oG0zYe5+rdOF56siFvdbfFsnRJOGjqyESKiEWLDT32ZCErLQFLrKrWwvppSewic3l6\nQVUp9QLgAXTMbL/WeimwFAz13PPy3CJnou4/ZPbWYDb+dZkmNSqwYXxb3OtXNe6XOetmIvIs1taH\nDVMbK9UhZKnGPiQYUt1fIERmspPcLwP1Um3XTX4sDaVUV2Aa0FFr/SBvwhP5Yfvxq8z48QRR9+N5\nrXMTJnVuQpmSaRfRkDnrJhZzE377CPy+hpJlDZUb20yEpe6S2EW2ZCe5HwWaKqUaYkjqw4DnUjdQ\nSjUHvgR6aK1v5HmU4l/xCfBhgtsEbtyLY8bmk+w8eQ2nOpVYNaYljrUrmzo8kVrCA/jzS9j/CTy8\nB+4j4an/GmvByNRGkV2PTe5a6wSl1CRgF2ABLNdan1RKzQb8tNZbgI+BCsAPybejX9Ra983HuEUO\n+Ab6UjOxL7O3BRMbn8jkHs0Y176RlOU1sYhFi/+Zqqg1nNwEe2ZC1AVo2h26zYEadmmeI1MbRXbJ\nGqpF3OWoWHr82JJ7IfNo0aAqHw1yoUkNWfDYHITY2RtKA1w6Arv+C+FHoaYTdJ8LjZ8ydXjCTMka\nqsWc91/eLAlaYtyuaD+V08DPV8bTpIaMp5uN/xsJwZuhwhPQdzG4PQclZBFx8e9Jci+C/o6M4bcj\n7tz7ex5PNrEisNTLMmfdTGSY1jjjCFA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- "text/plain": [
- "<matplotlib.figure.Figure at 0x7f2b49fa7650>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "\n",
- "d_emd=ot.emd2(a,B,M) # direct computation of EMD\n",
- "d_emd2=ot.emd2(a,B,M2) # direct computation of EMD with loss M2\n",
- "\n",
- "reg=1e-2\n",
- "d_sinkhorn=ot.sinkhorn(a,B,M,reg) # sinkhorn returns a list of distance if B is a matrix\n",
- "d_sinkhorn2=ot.sinkhorn(a,B,M2,reg)\n",
- "\n",
- "pl.figure(2)\n",
- "pl.clf()\n",
- "pl.plot(d_emd,label='Euclidean EMD')\n",
- "pl.plot(d_emd2,label='Squared Euclidean EMD')\n",
- "pl.plot(d_sinkhorn,'+',label='Euclidean Sinkhorn')\n",
- "pl.plot(d_sinkhorn2,'+',label='Squared Euclidean Sinkhorn')\n",
- "pl.title('EMD distances')\n",
- "pl.legend()\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 2",
- "language": "python",
- "name": "python2"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 2
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython2",
- "version": "2.7.12"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/Demo_Ground_Loss.ipynb b/notebooks/Demo_Ground_Loss.ipynb
deleted file mode 100644
index a39a07f..0000000
--- a/notebooks/Demo_Ground_Loss.ipynb
+++ /dev/null
@@ -1,345 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Choice of the ground loss\n",
- "\n",
- "Data from [Fig. 1 and 2 in here](https://arxiv.org/pdf/1706.07650.pdf)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "import numpy as np\n",
- "import matplotlib.pylab as pl\n",
- "import ot"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Dataset 1"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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5a2b3A4OBNsBHBFfqPA48BHQC3gfGuPsmMysHJrn7ReFzLwCuCjd1rbv/sa76\nlLkrInJgDiRzV7dsEBFpBHTLBhERSUuBP66UuSsiEVHgjytl7opIRDTmblxpzF0RiYiO+ONMmbsi\nEgEF/jhT5q6IRECBP66UuSsiEVHgjytl7opIRJTAJSLSCCiBS0RE0lLgFxEpMAr8caXMXRGJiAJ/\nXClzV0QioszduFLmrohEREf8cabMXRGJgAJ/nClzV0QiUO/Ab2bdzWxxwuNTM/txUpnBZrYloczU\n7JtcIJS5KyIRqXcfv7uvAMoAzKwpwSDqj6Uo+ld3H1nfegpWbZm76vIRkSzk6uTuN4H33P39HG1P\nrrxy/2VDhijoi0jWctXHfy5wf5p1A81siZk9bWY9023AzCaaWYWZVVRVVeWoWSIikizrwG9mzYFv\nAQ+nWL0I6OzupcBNwOPptuPut7l7ubuXFxUVZdssERFJIxdH/MOBRe7+UfIKd//U3beF03OBQ8ys\nTQ7qbPyUuSsiEclF4B9Lmm4eM/uKmVk43T+sb2MO6mz8lLkrIhHJ6uSumbUCTgcuTlg2CcDdZwKj\ngUvMbDewAzjX43gf6DhS5q6IRCSrwO/u24FjkpbNTJi+Gbg5mzoKWmLm7pQpCvoikhPK3I0zZe6K\nSAQU+ONKmbsiEhEF/rjSmLsiEhGNuSsi0ghozF0REUlLgT+ulMAlIhFR4I8rJXCJSEQ09GJcKYFL\nRCKiI/4409CLIhIBBf44UwKXiERAgT+ulMAlIhFR4I8rJXCJSESUwCUi0ggogUtERNJS4BcRKTC5\nGHN3jZm9aWaLzWy//hkL/KeZrTKzpWbWJ9s6C4Iyd0UkIrk64h/i7mVp+peGA93Cx0TglhzV2bgp\nc1dEInIwunpGAX/ywN+BI82s7UGot2FLzNydOvXLSzuVxCUiWcpF4HdgnpktNLOJKda3B9YmzFeG\ny/ZhZhPNrMLMKqqqqnLQrEZAmbsiEoFcBP5T3b0PQZfOD8zs6/XZiLvf5u7l7l5eVFSUg2Y1Asrc\nFZEIZB343X1d+HcD8BjQP6nIOqBjwnyHcJnURpm7IhKRrAK/mbUys8Orp4EzgGVJxZ4Evhte3XMy\nsMXd12dTb0FQ5q6IRCTb2zIfCzxmZtXbus/dnzGzSQDuPhOYC4wAVgGfAednWWdhuPLK/ZcNGaJ+\nfhHJWlaB391XA6Upls9MmHbgB9nUIyIiuaPMXRGRAqPAH1fK3BWRiCjwx5Uyd0UkIhpzN6405q6I\nRERH/HFO+SeKAAAG5ElEQVSmzF0RiYACf5wpc1dEIqDAH1fK3BWRiCjwx5Uyd0UkIhpzV0SkEdCY\nuyIikpYCv4hIgVHgjytl7opIRBT440qZuyISEWXuxpUyd0UkIjrijzNl7opIBBT440yZuyISgXoH\nfjPraGbzzWy5mb1lZpelKDPYzLaY2eLwMTW75hYQZe6KSESy6ePfDVzu7ovCcXcXmtmz7r48qdxf\n3X1kFvUUptoyd9XlIyJZqHfgDwdMXx9ObzWzt4H2QHLgl/rQmLsiEpGc9PGbWRegN7AgxeqBZrbE\nzJ42s561bGOimVWYWUVVVVUumiUiIilkHfjNrDXwKPBjd/80afUioLO7lwI3AY+n24673+bu5e5e\nXlRUlG2zREQkjawCv5kdQhD073X3Pyevd/dP3X1bOD0XOMTM2mRTZ8FQ5q6IRCSbq3oMuBN4291/\nn6bMV8JymFn/sL6N9a2zoChzV0Qiks1VPacA44A3zWxxuOwqoBOAu88ERgOXmNluYAdwrsfxPtBx\npMxdEYlINlf1vAxYHWVuBm6ubx0FLzFzd8oUBX0RyQll7saZMndFJAIK/HGlzF0RiYgCf1xpzF0R\niYjG3BURaQQ05q6IiKSlwC8iUmAU+ONKmbsiEhEF/rhS5q6IRERj7saVMndFJCI64o8zjbkrIhFQ\n4I8zZe6KSAQU+ONKmbsiEhEF/rhS5q6IRESZuyIijYAyd0VEJC0FfhGRApPtmLvDzGyFma0ys8kp\n1h9qZg+G6xeYWZds6pPaTZ/e8MvFuW1xLxfntuWznOyv3n38ZtYUWAmcDlQCrwNj3X15QpnvAyXu\nPsnMzgXOdvfv1LVt9fHXjxlk8nbGuVyc2xb3cnFuWz7LFYqD1cffH1jl7qvd/QvgAWBUUplRwKxw\n+hHgm9WDr4uISH5kE/jbA2sT5ivDZSnLuPtuYAtwTKqNmdlEM6sws4qqqqosmlVYpk8Pjnyqv06r\np5N/Bse5XJzbFvdycW5bPstJ7bLp6hkNDHP3i8L5ccAAd780ocyysExlOP9eWObj2ratrp76iftP\nbnVXRFsuzm3LZ7lCcbC6etYBHRPmO4TLUpYxs2bAEcDGLOoUEZEsZRP4Xwe6mdlxZtYcOBd4MqnM\nk8D4cHo08ILHMWOskZg2reGXi3Pb4l4uzm3LZznZX1aZu2Y2ArgRaArc5e7XmtkMoMLdnzSzFsBs\noDewCTjX3VfXtV119YiIHJgD6erJ6n787j4XmJu0bGrC9E7gnGzqEBGR3FLmrohIgVHgFxEpMAr8\nIiIFRoFfRKTAxPJ+/GZWBbyfo821AWpNGGsAGsM+QOPYD+1DfDSG/cjlPnR296JMCsYy8OeSmVVk\neolTXDWGfYDGsR/ah/hoDPuRr31QV4+ISIFR4BcRKTCFEPhvy3cDcqAx7AM0jv3QPsRHY9iPvOxD\no+/jFxGRfRXCEb+IiCRQ4BcRKTAFEfjNbLqZrTOzxeFjRL7blKm6BrRvCMxsjZm9Gb72Dea2q2Z2\nl5ltCAcUql52tJk9a2bvhn+Pymcb65JmHxrU/4OZdTSz+Wa23MzeMrPLwuUN5r2oZR/y8l4URB+/\nmU0Htrn7f+S7LQcikwHtGwIzWwOU1zXyWtyY2deBbcCf3L1XuOx6YJO7Xxd+ER/l7j/PZztrk2Yf\nptOA/h/MrC3Q1t0XmdnhwELgLGACDeS9qGUfxpCH96IgjvgbsEwGtJeIuPtLBONIJBoFzAqnZxH8\n88ZWmn1oUNx9vbsvCqe3Am8TjOfdYN6LWvYhLwop8F9qZkvDn76x/UmYJJMB7RsCB+aZ2UIzm5jv\nxmTpWHdfH05/CBybz8ZkoSH+P2BmXQgGdlpAA30vkvYB8vBeNJrAb2bPmdmyFI9RwC3A8UAZsB74\nXV4bW3hOdfc+wHDgB2H3Q4MXDiPaEPtKG+T/g5m1Bh4FfuzunyauayjvRYp9yMt7kdUIXHHi7qdl\nUs7Mbgeeirg5uZLJgPax5+7rwr8bzOwxgi6sl/Lbqnr7yMzauvv6sN92Q74bdKDc/aPq6Yby/2Bm\nhxAEzHvd/c/h4gb1XqTah3y9F43miL824Yei2tnAsnRlYyaTAe1jzcxahSezMLNWwBk0nNc/lSeB\n8eH0eOCJPLalXhra/4OZGXAn8La7/z5hVYN5L9LtQ77ei0K5qmc2wU8pB9YAFyf0DcZaqgHt89yk\nA2JmXYHHwtlmwH0NZR/M7H5gMMGtcz8CpgGPAw8BnQhuHT7G3WN78jTNPgymAf0/mNmpwF+BN4G9\n4eKrCPrIG8R7Ucs+jCUP70VBBH4REflSQXT1iIjIlxT4RUQKjAK/iEiBUeAXESkwCvwiIgVGgV9E\npMAo8IuIFJj/D5MawVJJMT1lAAAAAElFTkSuQmCC\n",
- "text/plain": [
- "<matplotlib.figure.Figure at 0x7f45b625d1d0>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "n=20 # nb samples\n",
- "xs=np.zeros((n,2))\n",
- "xs[:,0]=np.arange(n)+1\n",
- "xs[:,1]=(np.arange(n)+1)*-0.001 # to make it strictly convex...\n",
- "\n",
- "xt=np.zeros((n,2))\n",
- "xt[:,1]=np.arange(n)+1\n",
- "a,b = ot.unif(n),ot.unif(n) # uniform distribution on samples\n",
- "\n",
- "pl.figure(1)\n",
- "pl.clf()\n",
- "pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n",
- "pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n",
- "pl.axis('equal')\n",
- "pl.title('Source and traget distributions')\n",
- "pl.legend()\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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JmhXzSdIiMpskzcTU79Bt8XTgNTtc9+iIeA/wSeCFmfmB7Yoi4nzgfIDB2mkc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\n",
- "text/plain": [
- "<matplotlib.figure.Figure at 0x7f45b402cb50>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "# loss matrix\n",
- "M1=ot.dist(xs,xt,metric='euclidean')\n",
- "M1/=M1.max()\n",
- "\n",
- "# loss matrix\n",
- "M2=ot.dist(xs,xt,metric='sqeuclidean')\n",
- "M2/=M2.max()\n",
- "\n",
- "# loss matrix\n",
- "Mp=np.sqrt(ot.dist(xs,xt,metric='euclidean'))\n",
- "Mp/=Mp.max()\n",
- "\n",
- "pl.figure(2,(15,5))\n",
- "pl.subplot(1,3,1)\n",
- "pl.imshow(M1,interpolation='nearest')\n",
- "pl.title('Eucidean cost')\n",
- "pl.subplot(1,3,2)\n",
- "pl.imshow(M2,interpolation='nearest')\n",
- "pl.title('Squared Euclidean cost')\n",
- "\n",
- "pl.subplot(1,3,3)\n",
- "pl.imshow(Mp,interpolation='nearest')\n",
- "pl.title('Sqrt Euclidean cost')\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 11,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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SjykpKqxxNUgispTDgUOnCuGhxOdRsfHzwJqPPJbEJiIKCYcDGRJIf+1f+GdWKmqtm2lY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\nRU5ErkJggg==\n",
- "text/plain": [
- "<matplotlib.figure.Figure at 0x7f45b3cefb50>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "\n",
- " \n",
- "G1=ot.emd(a,b,M1)\n",
- "G2=ot.emd(a,b,M2)\n",
- "Gp=ot.emd(a,b,Mp)\n",
- "\n",
- "pl.figure(3,(15,5))\n",
- "\n",
- "pl.subplot(1,3,1)\n",
- "ot.plot.plot2D_samples_mat(xs,xt,G1,c=[.5,.5,1])\n",
- "pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n",
- "pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n",
- "pl.axis('equal')\n",
- "#pl.legend(loc=0)\n",
- "pl.title('OT Euclidean')\n",
- "\n",
- "pl.subplot(1,3,2)\n",
- "\n",
- "ot.plot.plot2D_samples_mat(xs,xt,G2,c=[.5,.5,1])\n",
- "pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n",
- "pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n",
- "pl.axis('equal')\n",
- "#pl.legend(loc=0)\n",
- "pl.title('OT squared Euclidean')\n",
- "\n",
- "pl.subplot(1,3,3)\n",
- "\n",
- "ot.plot.plot2D_samples_mat(xs,xt,Gp,c=[.5,.5,1])\n",
- "pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n",
- "pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n",
- "pl.axis('equal')\n",
- "#pl.legend(loc=0)\n",
- "pl.title('OT sqrt Euclidean')\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Dataset 2"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 17,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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3l2bcA0N+cYnBSlfvt/Cyq31cCrAmKBoYRu2VFBFHRMQbhlmuGO21yeZ00x+y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\ngc+fCgAAAABJRU5ErkJggg==\n",
- "text/plain": [
- "<matplotlib.figure.Figure at 0x7f45b3d83750>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "n=50 # nb samples\n",
- "xtot=np.zeros((n+1,2))\n",
- "xtot[:,0]=np.cos((np.arange(n+1)+1.0)*0.9/(n+2)*2*np.pi+.06*np.pi)\n",
- "xtot[:,1]=np.sin((np.arange(n+1)+1.0)*0.9/(n+2)*2*np.pi+.06*np.pi)\n",
- "\n",
- "xs=xtot[:n,:]\n",
- "xt=xtot[1:,:]\n",
- "\n",
- "a,b = ot.unif(n),ot.unif(n) # uniform distribution on samples\n",
- "\n",
- "pl.figure(1)\n",
- "pl.clf()\n",
- "pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n",
- "pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n",
- "pl.axis('equal')\n",
- "pl.title('Source and traget distributions')\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 18,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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AAACJoaMGAAAAAImhowYAAAAAiaGjBgAAAACJGWmYyJR1tXOmv2HW9QSMxPZj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\nGDpqAAAAAJCY/w9AeMfgS1/AXwAAAABJRU5ErkJggg==\n",
- "text/plain": [
- "<matplotlib.figure.Figure at 0x7f45b36bca10>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "# loss matrix\n",
- "M1=ot.dist(xs,xt,metric='euclidean')\n",
- "M1/=M1.max()\n",
- "\n",
- "# loss matrix\n",
- "M2=ot.dist(xs,xt,metric='sqeuclidean')\n",
- "M2/=M2.max()\n",
- "\n",
- "# loss matrix\n",
- "Mp=np.sqrt(ot.dist(xs,xt,metric='euclidean'))\n",
- "Mp/=Mp.max()\n",
- "\n",
- "pl.figure(2,(15,5))\n",
- "pl.subplot(1,3,1)\n",
- "pl.imshow(M1,interpolation='nearest')\n",
- "pl.title('Eucidean cost')\n",
- "pl.subplot(1,3,2)\n",
- "pl.imshow(M2,interpolation='nearest')\n",
- "pl.title('Squared Euclidean cost')\n",
- "\n",
- "pl.subplot(1,3,3)\n",
- "pl.imshow(Mp,interpolation='nearest')\n",
- "pl.title('Sqrt Euclidean cost')\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 19,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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woWJvBcTKmluyWv3ZtM5c3qjZdR0ysonaCYiCiNRN5Thi95Kk/L1IO+RuG+Du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\nO4vGAAAAAElFTkSuQmCC\n",
- "text/plain": [
- "<matplotlib.figure.Figure at 0x7f45b34e2d90>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- " \n",
- "G1=ot.emd(a,b,M1)\n",
- "G2=ot.emd(a,b,M2)\n",
- "Gp=ot.emd(a,b,Mp)\n",
- "\n",
- "pl.figure(3,(15,5))\n",
- "\n",
- "pl.subplot(1,3,1)\n",
- "ot.plot.plot2D_samples_mat(xs,xt,G1,c=[.5,.5,1])\n",
- "pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n",
- "pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n",
- "pl.axis('equal')\n",
- "#pl.legend(loc=0)\n",
- "pl.title('OT Euclidean')\n",
- "\n",
- "pl.subplot(1,3,2)\n",
- "\n",
- "ot.plot.plot2D_samples_mat(xs,xt,G2,c=[.5,.5,1])\n",
- "pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n",
- "pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n",
- "pl.axis('equal')\n",
- "#pl.legend(loc=0)\n",
- "pl.title('OT squared Euclidean')\n",
- "\n",
- "pl.subplot(1,3,3)\n",
- "\n",
- "ot.plot.plot2D_samples_mat(xs,xt,Gp,c=[.5,.5,1])\n",
- "pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')\n",
- "pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')\n",
- "pl.axis('equal')\n",
- "#pl.legend(loc=0)\n",
- "pl.title('OT sqrt Euclidean')\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 2",
- "language": "python",
- "name": "python2"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 2
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython2",
- "version": "2.7.12"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/Demo_Image_ColorAdaptation.ipynb b/notebooks/Demo_Image_ColorAdaptation.ipynb
deleted file mode 100644
index 16e5208..0000000
--- a/notebooks/Demo_Image_ColorAdaptation.ipynb
+++ /dev/null
@@ -1,316 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Demo of OT Domain Adaptation for color transfer in images\n",
- "\n",
- "The color adaptation problem and the out of sample interpolation has been proposed in [6]:\n",
- "\n",
- "[6] Ferradans, S., Papadakis, N., Peyré, G., & Aujol, J. F. (2014). Regularized discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3), 1853-1882.\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "import numpy as np\n",
- "import scipy.ndimage as spi\n",
- "import matplotlib.pylab as pl\n",
- "import ot\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Loading images"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "I1=spi.imread('../data/ocean_day.jpg').astype(np.float64)/256\n",
- "I2=spi.imread('../data/ocean_sunset.jpg').astype(np.float64)/256\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Plotting images"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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mTia0hLGlGUdRPJdlnZfEqBoxOLLbusg0fQycdE60mvwID4Ylse5O2ZcHU+LH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\n41yBpIqq38d4HxfdExL3lJffqz5zh0o6f6MfJwg6URVT45HwJ54UukTc9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QTmuMY+j45F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\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J3EjkYbtwM3Qdo3jh1nsXvllEaJzbyucijKlPqTbJCIUDgUMUGoEURz6MC2t0gm58nCIJ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fhX6o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vmv/VN/ir//kyMtKVkrJRlZY5/KUyHl6EbT0oi8iOlizmAe72NtM+QrmZgkaUrsm5A1ADwx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\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4xz+7HdCiqVAp2wpEYK5NyVtsMyPOf2nBvYT53DtihAdiVAQl50iEL3TOr28hR8uTGCQz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\n",
- "text/plain": [
- "<matplotlib.figure.Figure at 0x7f37f81bdc50>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "pl.figure(1,(10,5))\n",
- "\n",
- "pl.subplot(1,2,1)\n",
- "pl.imshow(I1)\n",
- "pl.title('Image 1')\n",
- "\n",
- "pl.subplot(1,2,2)\n",
- "pl.imshow(I2)\n",
- "pl.title('Image 2')\n",
- "\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Convert image to matrix and dataset generation"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "def im2mat(I):\n",
- " \"\"\"Converts and image to matrix (one pixel per line)\"\"\"\n",
- " return I.reshape((I.shape[0]*I.shape[1],I.shape[2]))\n",
- "\n",
- "def mat2im(X,shape):\n",
- " \"\"\"Converts back a matrix to an image\"\"\"\n",
- " return X.reshape(shape)\n",
- "\n",
- "X1=im2mat(I1)\n",
- "X2=im2mat(I2)\n",
- "\n",
- "# training samples\n",
- "nb=1000\n",
- "idx1=np.random.randint(X1.shape[0],size=(nb,))\n",
- "idx2=np.random.randint(X2.shape[0],size=(nb,))\n",
- "\n",
- "xs=X1[idx1,:]\n",
- "xt=X2[idx2,:]\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Plot the images distributions"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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aA6kPJza2iRMnMnz4cJyccpDdwZFFixZhYWFBzRq1GTn8OwAqUYWiRYrRs3dX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\nWxMkGvgdePr8LjOBSCFEmxou5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kkSP//8MwMHDmThggWU6/WMnnTl57Ir5SHgsh+jLefz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m1m\nyXkzSAwJYW1hIcvycokMDydYglvGjibSoKespZVHNmwhWKvl+ekzUSsUALTYbNyyZiUKWSZIo6Gt\ns5OFV17J2++8w5YtW5gyZQqPTDqbod0CZR6vl9vWraPe1olXCPr368ef7ruPyy677EffWw0NDYwe\nNZKKyioiDUG0d9kRSLz51lvk5uby4QcfYLFYmDBhAo88+iijR4/+0XOc4rbbbmPN3z/ky7nTe5z/\noOA4j+89jNvt/tX7lxs2bGDOnAtxu5zER+gpq+2gd3oqz7/wIrNmzYKf+Hvpt7fHqu0knpJdeFuq\nfLWqvq4S6PWA24ms1aNMG4KwdSDsFoTTzrPPPousUNJ5aCOOqkKcdaV0Ht6I19ZBenoaM2fO5OWX\nX8br9RIcHIzXaUcI3wePJElIsgLhtCMr1V9RCdRhyhyBuaODL774wm9GR0cHy1eswJjcF11oJJIk\nodTqiMgcgdPpZPLkyQi3G4VSTVhaf9R6Iy3H87j22mtJSkryz6nRaH71N32AAAECBAjwv4Qsyzzy\nyCPYnXY67Z2n5PXxer1syd2KpctCRkw68cExuN1uxmaMJEijQ5IkokOiyErqT31bA73TfVkNm72L\nquYajlQe40R9BeYuX9Hcr24jqK6uZtOmTYxKzCTKGAZAq62DDruVMJ2R1PA4ogyh5JQe4x97NvDx\nno24vG4SIyI5O3MwCeERbC86whvbVuL2erjppptYdM89KGSZmYNGoFP7/Ik+MfGMTO2DSlagV2to\n6bTy+eF9JIdHgRAoZQWjeqUzvd9gYowhNFrN/gLASWERnNt3AIUNNVgdvsK85u6fEydOxGzv4nhT\nPa/t3kpOVTkbigp4M3sHMdExxCTE0ys1lXvuuQeL1cpZKSm8nZ2N3e3iwkFZTOzdG5VC5t133sHj\n8SDLMgMGDACg0Wolu6qCtUXHyKurpbl7v1ZRQz3vHzjAJ0cOk5KSQkNTE9eOHEakwfeQOzU8jPMz\n+9JktbJ46yY2l55gTXERD23bQmhYGLfcfjs33X47e/bs4Z1330WWZSZPnsy4sWN5KnsPf8/PY2tF\nOdevXkVlRzvjkuK5dthANO0tzJ8/n1deeeVH31t79uyhorKK5BATMUE6InRaPF4Pd9x2G2+9+irT\nYiP4/aB+VB45xKSJE/0KkT8Wh8NBTU0NzTYbzq/t56vvtBFsNH6rf9nS0sKbb77JM888w969e/ml\nEzhTp06lvLyCJ596hosuv4EPP/yQvPyjZ6TK/a/wm1sKiEIFLdXQ4tvQ6TlZhBQah2wKR3jceMoO\ng8eDHNnr9A3jtPPggw/yz88+w+txg8eNvfRw94C+NtnZ2SArWLt2LQ8uXsxHf/87L7/8Mp3lBeiT\nB4Ak4Wyrp6uuDF1MYk+TtEEolEoaGxv959rb2/F6PKj0hh5tldogFCoVM2bMYMaMGTzzzDM0lB4j\nNCyMBx98kAceeODnuW4BAgQIECBAgDPmiiuuID8/n2eeeYaik8VkJPShuvkkLZYWpmVNJsoUydGT\nRZxsqyNI01M5zaTzffff86d7WPrKUrbn78Pt8aBWqHB6XChkBcHBwUydOtXfp6XFt8om5NSKGiHY\nXZaLVqmmtcuC1dmFy+NBIcs0WdqRJYnMhGRmDBnp93eig0PZXODzb3L25zBy1EhMuqAee6YAwvVG\nXF4PN485j1d3rSPCYGJbcQFeIbhy2FjSI317pEYn9+Zve7ewsTDffy5cb0QANpdvi8WqwkMkJSax\ndu1aHnroIV55+WVKmhoobqxHIcvoDQbqG+pRNsl4heDYsWMA7CotpVdYGHefO9mXWQOy4uJ4Yes2\n1q1bx8yZM5kxYwZGg5FHNm/A5fGgU6rocrtQKRQoJYkPDh3CqNWQERtJSblP9CvG1FPJeWBsDJ/m\nFhCclMRrB/YjyzKzZ8/mueee67EM8xSyLLNm7Vruvfde3n/vPTptNiTguhGDuGhAXwAu6N+Hv+7O\nYfGDD3Lttdei1Wq/Mc63IYTgvj/9iTGJsQyOieT1A/koJAmlJNNhsTA5OYFbRwxCkiTm9e/NtWu2\n8NDixazfsOGMxj/F0aNHOW/aVKpragF4Zt8R7h45GI1SwcH6Jj4uKuOa3//+G/2WL1/OlVdcgdPp\nRKNSYHO4mD1rJss+XX7Gr/HnIDIykjvuuOM/MtdvL7BCIGVMRGhNULoHOltwH9kIsgwI8AqUvYcj\n6wy4q4v8vSorK/03pio2FW2vTJAVuJtP0nX8ANrk/mjiUuksyqG9rZHZs89nyJAhHD58GGdDObJS\nhcPagUql/kae0N5Yg8ft7qESGB8fT3R0NJ311ei71zwD2Jpq8bhcjBo1inHjxnHnnXditVrR6/Uo\nulPUAQIECBAgQID/PMuXL+epp57i2LFjJCUlcdttt3HHHXfwwgsvcLz2OE6XE4PWQJTJt2olwhiG\n2+OmprWOhPDT3/XlTVVIksSNv/89AwYMQKVQMXPgRKJNEXR0Wdh0LBtZrUL5Fcn03r17YzAYKGmq\nJtYUgdPjpsXWgUqh5IKscaSEx9LptLOp6ADlLXV4hSCrV0qPrENWUiqbCw4zOD6NwqNHcbqcNJs7\nqGtvJTbElwUTQnCspooYUwghQXr6RMXRYG3H5nRg0GhJizitGqiQZYYkpPBF/gHM9i62lxRyoLIM\nWZJ4add6XB43kiSTGhmOTqfjmWee4cknn8RqtSJJEtdccw0rVqzgkhHDGJOWgtPtZlVuPjtLSilr\nbmb+8GH+oAogIzqKYJ2O1atXM3PmTJRKJRqNmjClkptGjyZKb+BESwsvZe9Go1Sw+PxzMWk1tNns\n3PnJKgD2VlQxIS3FP+Y/846iUigoLi4ms18//nDrrdx4443fuxrIZDKxdOlSXnzxRV544QUWLVrE\nsrxCPskrZERCLAuGDGBan1TWHd/E/v37mTBhwhndX42NjRSXlHDt0Exezcnj8swMrh7UH6Us81lx\nKX/NOcKXJyqY0TsFtULB9JREXvsWBb/vw+v1MufC3xFk72L1nOnsrW1gyd7D/LO4nGCthhqLlVEj\nR/Loo4/26FddXc38+ZcxrX8sj1w4hNAgDV/mn+TOj9fz6KOPsmTJkh9lx38rv72lgJHpyKYoKN4K\n1mak8ETkXgNBHwpeL2h0SCoNrtLDuMtzfcsFJZkPP/wQvF4klQZd+lBkjQ5ZpUYdm4oqKglnQxWW\nQ1vwWNvRJWWgTuxNQdFxwsLCuemG67jpuqtZvXo1zz77DF01lbTlZtNVX425pABzwX4mn3NOj3Ww\nSqWSxYsXY6kppyE3G2t9Na0nCmgu2MfESZMYO3Ys4HsyYjKZAkFVgAABAgQI8Avy2muvMW/ePE6W\nnyQ9Jp3O1k5uvvlmlEolOTk5zLtkHm6PG6fb6Zf1jjJFEh0cxbZje8itKKCiqZrtx/ZQ1lBJXEgU\nKoWK3Lw8RqVkEW3yiQcE64xM7DOCpqYmNm/e7J9fr9dz7733cqSmmM3H93O0rhQJGJbYh9SIOCRJ\nwqDRMbXfCH+fTru9x2vo7F6WV9xYTd/IePLy8lApFHy0dzvZJ4o4WlPFJ/t3UtbcwMT0TAAsji7k\n7tU7Trcbt7fnsjGLw46MxGs7NnKwsoxRCamck9qfILUGhaxgRuZASk6c4PBhX6ZMofBl40wmE1+u\nXcvgxATG9U5DIcvo1GrmDhuCsTv7kVdTS35NLVuKj7O3vAKz3Y7d5aK0tBSA9evX09zSwrUjRhBt\n8C1d6x0RwdwBA2nutPHSZp88eVt3sd60tDTe2neATw7nsb+qmge/3MCR2joyoyKZ0zsdg9XCzTff\nzEMPPXRG94TZbOb/nnkGg1rFtLRUZvdOJ6+ukbtWb6K8W+77zjvuwP01AbTvIigoCFmW2VNdR69g\nIzcPyyJIpfIpFfbvw6i4aL44XuZv39Jlx2g0fs+I32T37t0cLznBg6MGkxZi4vL+vVlz0XTGxkdT\nY7Hy4osvsmv3bkwmU49+H3zwAUoJshJD2XSsFrPdycxBicwflcJbb7zxo2z4b+Y3l7GSNHq8HfVg\ntyCnDEYR51u/LMf3wVO8F9FSg+vYLlCqUcb1RQ6Nx3l0E14BKNXIOmMPmXMAOciEq7kGJAgdPR2F\n1idp7k1Ix5yzEY1Gw9NPPw34nvSo1Woefewxag/vRqvVcd011/DMM8984+nHTTfdhFKp5C+PPELt\nkd1otFquueoqnn322cC+qQABAgQIEOBXgt1u58/3/ZmUmGSGZwz3f0cH64N5/rnnueOOO2huasao\nM2C2WThSlc/gpIHIskxWYn82FWznSEUBgtNy1c2WNrKS+pJTlkdIUE8nNiTI5yzX19f3OH/dddex\ndOlSjtaedq7D9D37Bqm16FRqPBLsLMonLjQcU5Aeh8vFpoJDqBVKXG43JU21BOuCWDByEttKCthS\nmItXCIwaHXMHjyEjKp7cmgoqW5vQqdQAOD1u1hflMb3fIJSygrqONrLLixEI2rps3DFmCrFGXx3O\n8b1683z2BkqbffW0Ghoa+DpOp5OY4J72y7JMjMmIxW7naF0dBXV1KCQJjxAoZRm310tFRQUej8c/\nZqyx5xhx3UFBSWMLO0rK+WR/LgCV5eW4vV5WHivE6xXIksS09DSuHXZaXObj/AKeevJJbr31ViIj\nI795M3yF119/nbbWVl6dMZWY7n1bs/uk8/s163jnQB6JJiOHDh9m1apVXHjhhd87FoDRaGT27Nms\nW72akXHR3/AFk4NN7KmpAyC/sZkvSiq47qabfnDcr3LqmqWGnL5mKcEmbhmSyfqKkwwaNKhHphR8\npYE+/PBDupxunlmbj9srWPzZYZ6aN5ze0SYad5WcUXHr/wV+c4GVMDf4slCAHHN6bawkScgxqXha\nfAXx1H0moDB01wPQh0FnK8rQSNzNtXjtNuTu4EkIL67mk0iyAlVYlD+oApA1WhRh0Sz79FN27NhJ\nUXERaWlp3HXnnVRVVtLa2orJZEKj0WC1Wrn//vv54MMP6ezsZMq557J48WJuuOEGrrvuOlpaWvxt\nAwQIECBAgAC/HvLz82lrb2Po0KE9nN20uFQKygvYuXMnm7dsJiM+HUmSOFySR2lDORqVhg6bGQkJ\nSZIZ23soaVFJdDq72H38IEcqjyEhUd580i9IAVDeXAP46kjdf//9OB0OZsycSVVVFa1NzQCMSutH\nYW0VJY0nyYhO8vet7Wimy+VEkiQ6XC7e2LyGCGMwbZ1W3F4PWqWa5PBoTjTVMjatH6F6PRcOHsWM\nAcP4Incfxxtq2VCUy4bCI5gdXQAoJZk/jJnC1tJj7K0o4UhNBUaNliarBaUso5BlYo0h/qAKuhUK\nY5LIri5FoVAwaNCgb1zXsPBwcqtPMn1Af/+Sv46uLsqbW0gLDaeyo42Fg4YzNDYBs8PBR/mHONpU\nT0lJCa+88oq/ztLBmpOMSjx9DQ6cPIlWqcTj8fLu7oNIwPD4OK4fNgyr08lrOQcoaWnBKwTnpvXc\nRzUlLZV/Hitk9+7d/O53v/ve+2Lzpk0MiYnyB1UAwVoNYxMT2FxWwf0TJvH47v1s2bLljAIrgJdf\nfpmB27eRU9eA2eHA1O0XOj0etlfV0GZ3cNkXGyhraWP4sGE8/PDDZzTuKU4plG6oOMklfU+rZm+o\nPIlGrfYLgnyVF154geNFRTw+fihz+yRjdjpZkp3HXf/Yz+Be4QwdPOg3EVTBbzCwou0kaLujcJcT\nvrph1OXw/+quPYaiz1ifmkn3eTnIiKTWYs3dijapL5JSg6P2BF5rO6h1eJ0Ovo5wOamsq6PeYkMV\nEU9hVS0LFiygoqKC+++/H/A9kTnnnHM5ePgQuqgEFMZIPl/zJavXrGFvdjYDBgz4waciAQIECBAg\nQIBfhlOlUhyunn6Ao9sv0Ov16IOCcDgdDMsYRFx4NBX1VThcLrpcdjweDwMTM+gdkwyAUatnQsYI\nlu1bg1atIbe6CLfHTWJoDE3WNvJqjmMyGln28Sf0lL0siwAAIABJREFUjkxApTOw4pNPsdpthAeZ\nCDMYGd0nE1OQno35B1h7NJuMqCQ6uqzsqyhEQkIIwaT0LJ+YRaeZPhHxxJhCWX5kF602C14hqO9o\n42BlKWF6I8nhkcwdMoaXtn9JbFIiVVVVvoxO7yyGxCejUaq4ZNAY3j2wnZMdLahkBVqVCrvLhUap\npNPp8EmxfyXw7HQ6cHrcXHf99cTFxfF1Hn74YW6++WZe2bKd8X3SsbtcbDhaSJBKRZ3FzMReaYyI\n9wVMoTodVw0ewb2bVhNnMvHq0qWMGjWKgQMG8Lec/TRYLPQKDSWvvo4tpaWoFQr0ajUTEnvR5XGz\nq7qSJdt38NDks7lx5Aj++OU6ACwOZw+bzA7fe2ow9BQX+zYMBgN1Ttc3zrfb7SSHBpNgMmJxOnuU\n2vkhEhIS2L8/h6GDB3Pjuq1cnpmBRqFgeXEprU4Xly1YgE6nY9KkSVx44YWo1eozHhsgNTWVBfPn\n88SyZdR32hgcFcHe2gY+KDzBbbffTlhY2Df6vPnaa1yQnsT8fr4gNEKn5YkJw9hcXcfBimb++c/A\nUsD/XaLToakSAE/5YRS9RyEpFAhHF56qo/5mXmsLXq8Xb2MpODtBocRZU4oucxTOymK6jh/0NfyK\ncqDb2YWjvgp1tE/1z9lci7O5DlVIBKHDxvvHlo/n88ijj3LTTTcRFhbG8uXL2b9/HzHDJ6EJDvfN\n36sPjQe38Ze//IVPP/30P3BhAgQIECBAgAD/Cv369WPAgAEcqzxGmDEUrVqLy+0mrzyfsLAwpkyZ\nwoIrruDVpa+SHJNIeHAYwYZgCsoLcbp8jnvo15b7BWl0qJVqurqDs2O1pRytPYFSoWDMWWexa+cu\nLh5+DuF6n+R6YmgUX+TtxCO8hBt85/onJOMVgv0nCiluqP6G3Udqy7h0yESGJvoK4J6qTdVsNaNW\nqShpqqOkybe0LMoYTO+oWCxdNt544w3mz5+P2uZkdK+ehW6TQiNoslm4eew5uD0e3ti7Da/wUm8x\ns6uqhLFJvZElifK2Zg7WVqLVarnnnnu+9bredNNNtLS0sOTRR3l7VzYAIVodt46YwJJdG4n72hI/\nvVpNiC4IlSxTVlrK6NGjfTW1gM+PHUUARrWG5OAQWrtsPDFpCobuwOPspBTu376JXZWVnJOaioxv\nNdOHuXncP3E8Ro0Gm8vFB0fyiImO9mfDvo/5l1/OJStXsrmsgskpPrXpnJo69tXUcf3QLD7KP0Zb\np+1H17Pq3bs3u7Ozue3WW1myYwcAQwYPYv3Hy5g0adKPGuvbeOvtt4mMjubN11/ntdxCQoODuf+B\nB1i8ePG3tq+tq+PCzJ6ZPa1SQbLJQHDfAWecjftf4DcXWEnhvSAhC1FxENFSibt9JWiNYGsHpRrV\nwLPxmpvxVObjOLwSPC6koGCEsws8Lrpyd4GsBJWGoPTBKMNi8VrbsBXnoFcrsRzdh6aqCIGE0+Lb\nmGjMyOphgy4xlc6K4+zevZvZs2ezadMmdMFh/qAKQFaq0EYmsGHDxu99PVVVVTz++OOsXr0GtVrN\npZdewj333ENISMj39gsQIECAAAEC/OsIIfj444/561//SkV5BUm9knB6nazd9yWhplDMnWaQ4LPP\nPkOr1fLQQw+xfdt2vty/mYiQcBwuJ5ZOCw888ADvvPMOVa11JEcm+Mdv6GjG4XYSaQzhnMzRaJQq\nCmvKyKk4RnNzM/Ghkf6gqqq1nu3HDyNLEha7jfKmOtweD0qFggGJKaTHJPDOtjUIr2DuqHGEG0ws\n37+LRnM7r+9ZixCCYJ2elDCfop8sSegUKi4bfBbxwWFUt7fwWf5+skuLycjIIDg4mP79+7Nl02as\nTjsGtU9MwisEx5vqiDP5fBClQsHwxBRWHj3MmF5prC7OZWfFcXQqNfXWDmIMJpxeL5fPn8/effu+\n9To/8MAD3HXXXURHRRGEhN3tJiJIT6zBxJH6Ws5KTPZnwWrMHTR1WjHbFciSxC0jRzMoJpZai5k3\nD+ZQYzYTqtFy0mJmSnKaP6gCSDQF0zc8koKGRlSyjBfIjIqgvLWNm1atISk4mKqODtxeLxs2bkSl\nUn2rveDbc7R06VLeeuMNdFot/7c3h38UFiMJQY3Zgl6tZkXRCZo7O3nssce+dRnkD5GVlcW27dtp\naWnB7XYTFRX1k+2/12g0PPfccyxZsoSWlhaioqK+N/M1dOhQNp0o4oZBfZC7bai12ihsNfPMRRf9\nJDb9t/CbC6xE60kkkwPf8wvA4wZbB4rETBTRyUhKNbIhFK+lBWFuRlLrEA4bqkhfFsrVWAVeN0EZ\nw1BHxAMgm8LRpQ3GcnQPL730EgUFBezdu5f8o1a8bl/dqx42uHxp4aCgIP9Pr9v1jRS51+1Ep/tu\n3f/q6mqGDx+B2WpFHxlHp9PNM8/+H6tXryY7O/tHpZYDBAgQIECAAGfOY489xuLFi4kJiybUEEL5\n8TKsVisXX3wxOp2O5ORkrrnmGpKSfEvVQkJCyN6bzaeffsrWrVsxGAwMGjQIs9nMgAEDWL9+PTIS\nKZEJmO1WjlQWIksS07PGoVGqaLK0oVVrSAiNoqy0lGCtbylaZUsda49mo1NrGNQrnfZOC+VN9fxz\n/w6GpvTBK7wcKCvG5fYwZcAQXG43b279EqfHQ7/YeIzaIArrTtLR1cnhmjIkfAHS9H6DSQjxPfBN\nCo1gWsYgVuTto76qmtGjRnPHnXewadMm3ti3hXPSMtGqVOyrLqXe0s6M/qflw7tcTpSyzNCEXmRX\nlhJrCMao0TA5OYOBUXEUtdTz3v695OXlkZWV9Y3rDD4/6b4//5n7778fhSTzwr7t9A2PYmvlCf52\neD/DYhM41lTPwbqTqGUZh8fDxZkDGRLrW16YYArm98NH8uCWTcgKCZ1SSafL+Y15rE4Hdq+Ltw8d\nRqdScu/ZZ2FzudhWWkmt2YLD46amw8yBAwc455xzvvPeWLhwIf/46CPOSopjdloSWytPUm+xMm3a\nNOb26UN7ezuhoaFcfvnlDB8+/Efddy6Xiw0bNtDY2MiIESO+dc/TT4VOpyMhIeEH29375z8zY8YM\nbtiYzfy+KbR0OViad5zIyEgWLlz4s9n3a+Q3F1hRX4yoL+ZUYV8AyRCKMr5Pj2ayPgRPeyPC6yFo\n8GTk7g8w2RCK48RBFP/P3nsHRlWt6/+fPX0mM5kkk94LCSmEhCIgRUDUIwp2RRERBctR9FhR9ByP\n5ahguSL23sCugB5RlN4JhATSe+/JZGaSmcnU/ftjQjAotnu8935/zOcvZs/ea69dwqxnve963oDh\nESHp4KxRQkICS5cu5ZprrqG8oQXXgI2+6hKCx0xBIpfjdbvpqyzCEBrKGWecgdvtpra2Foe1j76m\nKnRxqQiCL9pl72jihqW3nvRSVq5cibmvj4QJM5ApfQJsIC6Z4rztvP/++/z1dzrB+PHjx48fP35+\nnc7OTh599FFGxqUxKslnOy6KIgfLD7F582ZaW1t/1mxKqVSyYMECZs+ezUUXXsTq1auHfV/T2UBV\nRz1SqZTwsHD6TWYAvincRZu5e2g/AYFOp5Gy9noO1pcSoFRx1emzUA5GUQrrq9lTVcw3Bb70OY1c\niYhIfn0VPf19AFw0biKpET7hcXrqSD7Ysx2L3YbL47NLjxhMJzxGxKDxxKToEWypK2bFihUAmAds\nrCs5iIgv0pUZEUNCsM8avtvax76GGkZFxlLW6Ss2e3FGLsE/MvqKHmz3o48+OqmwAli+fDnbtm1j\ny+bNNFlMNJh7AchvbSK/tenYdPkQsSfYgUdpdUgFgXqTCblEwp7mJqbHJ5IWEoooiuxoqqepz4IA\nhKo16DVKFDIpCpmUi0aNBGBDSSWfHSnl4X/+kxtvvJHg4OCf9PPQoUOsXbuWOyaP5ayUBACuyslg\n+Q+76GhvZ+PGjSe9xl/j0KFDXHThBbS0tg1tu+jCC/nwo49Qq9W/cOSfy7nnnssnn3zC/cvu5frv\nfBb2s2bO5OVXXz3lMqhOPWEVmQrWXrBZwONCJpPhsZoQXQMIcp84EUURr7EVvB6khqghUQUgDfKZ\nSLiNbUhjRgxtdxnbEASB7OxswBei/fCjjxBUAbjMRrp2foMsMBh3nwnR7SE4dQQymYwnnniC7zZt\nQhkcSm9VEX3NtUhkCpx9vWRmZvKPf/zjpJfyzcaNBIRFDYkqAJVOjyY4lO+++84vrPz48ePHj58/\nge3bt+N2uxkRc9w1TRAERsSksK1wB0eOHGHChAknPf76668nLy8PgFGxqWTFpOIVvRTUl1Ld2cjG\njRt56qmn2LJlC9tK8zBaLcxIHUuP1UxdTysDLicer4dtFfkIgsBpySOHRBVAbuIISprr6B8YQKNQ\nYh6wIiDgcrkJVgfg9HoYER41tL9cKiMnPomtpUeHtlV1t5NsCGdffSV1PZ1D9an2NlUSotFy0aix\nhOsCqehsY33xYbRyJeNiEthcU8bKrf/GK4o43W5EoLa3m8JWX62obXUVGO1Wuu39hKq1hKh92TUr\nV67k448+QiFXcNElF3PvvfcSGho67P7W1dYiFSSIohelREJqaBhlXZ2MDo/ksvRRBMgV7GisY11l\nKRurKsgKP16suKSrE48ocklmOhsrqpBJBB7bs4OEQD0DbjcdNisAz888h7yOVj4uL8VosxOi8QkW\nURQ53NxGQpCeamMvu3bt4oILLqCiooIVK1awY9s2goKCCIuIQCmVMjPpuAuhXCrh/LQknt2TT29v\n788Ksl/DZrNx3uzZhEtFHr90JvFBWrbVtvL0xm9YtmwZzz77LC+88AJr3n8fi8XM9Jlnsnz5clJT\nU3+98f8Al19+OZdeeimNjY1oNBrCw8P/R877f41TT1i1V4FUDvowcDlx93UDAq6SXUhjMxBkclyt\nVWD1rY8STwgVSxRqBIUae10RoseNTB+K29KDq7mSefPmkZiYCPj+03ziiScxmXrRpY3G63TgsfWj\niElGotZQXV5IQUEBL7z4IgHR8QRn5ODo7cHW3ozH5USwmlmwYMEvKn2VSkWvyfrTLzweVKqTpxD6\n8ePHjx8/fv44dXV1ADhdTvrtVmwOG4EaHa7B1H+j0XjSY1taWvj666/Rq7Xo1VrGJWYNfTc5dQxd\n/b18+OGHZGdns3XLFpp7O5mYNIr8pnIcLhcjwmLwil6qunzlYTxeL84TCsyKoojL68GLF5vLV/RX\nRCQjIo7KrlbcHg9eUUT6o+UHTrdryOhBJkjYVF6ITCJFLpWSGRGD3eWkpL2ZPucAC8afToTOF9HK\niozBZLexubKUhJBQ4ntCaDQZCVUHMD4qgdY+MzW9XQQGBmKxWNjfUkd8YDCjI6KpNfawv8V3LxUS\nKY6eXiKDgnlh1fOs+/JLDuTlERwcTEdHB7feeis1tbWEBwQwOjKKFouZ4s4O1DI51+eMRyGVAnBu\nShp15l6OdrbzSfFRciOjabGY2VBRRkpICHNGjkQtV7D2yFGUUilOjxsEkAxeu0f0Mj02ga9rqvjX\n5t1cmp2OTqVkc1Ut5V09XD9mNNXGXlQqFUePHmXqlCmoEDk9KpKenm42H/WJU4fbjUZxXOzaXO6h\nZ/NH+PLLL+nq7ubFK88mJtAnRv+SGkezuZ933n6LyooKtm7ZwsyEaNLVCr757FPWffEFu/fuJSsr\n61da/88gkUiIjo5my5YtmEwmJk+eTEJCwh9qy2az8cMPP+BwOJg+fToRERG/ftBvbHfz5s2Ulpb+\nR9o7kVNPWAF4XGBshSFPfRHR3o+7Ku8nu3otPTgaSlAm+F5Kt6kT0WknODgYa1sN/Q2lyBUKFl9/\nHatWrRo6zmAw8MwzT7NkyRKUIeHINMejXh7nAH1AfX09He3thGTmIggCqpBQVCG+2ZmuA9tpa2vj\nl5h/1VU88uij2M1JqPU++0tzezNWUw/z5s37b9wgP378+PHjx8/JODbI235kJy73cTttucw3kNbp\ndCc9tqWlBVEUcXu9RJ2wrEAQBII0Ourr62lqOp7e1mu1MOBycvmYmegG0+iyo1P4onA7CqmMkuZ6\nMmISMGgDEUWRoqY6+gd8NaY8gE6hpt9p50Bj5dC58mormZQyEkEQMNms5NfXIJNKAYGkkDBqejqQ\nS6XcNOlMNIPGBWq5gvzmOsK1JxbcDUJE5K2Du4a2WV1OEvQhnDsii211FWyuK0cATotJ4NKMHATB\nZ/n+RdkRDrY0EKRSEx6g5YrMXGYm9vPs/h28+OKLuN1unnziCVyD4rHf6SQpOJiLs7J4cvs2FBLZ\nkKg6RoI+iNLuTnY11PN9TTUA46OjuXaMb7yVFOy773eMm8CoMF9kpcbUy8N7dvJiYT4PTz6Dv0+a\nymtHDrN6z0EADBo1fz1tLHmtbYQaDEyfPp3LLr0UvVTC0zOmoh6MGO5vaWPFvjxW7TvM/WdMQCII\ndNvsfFlShYDP2OKP0NjYiF6tGhJVxxgZGoTVVsH3P/zAs7MmMjU2EoAbctNZ9O1uHnroIb744os/\ndM7fy44dO7jyiito7+wEfELrxhtv5MUXX0R6wjP6Jb744guWLL4ek9kCgFwu48EHfa6E/x2DjvXr\n13P99Yvo7TX/4TZ+jVNPWCWPBX04FG0FmRxJwkjE3i5EUxc4faYW0qhU5FHJiB4XrsZSXC2VuI2t\nCBIZ3sFI1gMPPMCNN95Ic3MzMTEx6PX6n5xq9uzZSCRSHD0dw4SVo9tX1Xr06NGkjRxJc08n2tjE\noe/dNisDFvNQWuHJuOuuu/j3N9+Qd2AHAcGhiF4PNnMvV1511a8WrfPjx48fP378/DHGjRuHgIBM\nImNS+nhCtMF0mLvIry1AEARGjhz5k2M2btzIypUrOVJ4xLdB9NLc24G0voQWYweCIBAbEkmnxUig\n0UhRUREyiRS310OzqZMkQ9SQqAIICQgkNiicPocNk72fj/ZuISrIgN3pwGTrJ0St4/zU8RxoqaCy\np5VUQxRTEzJQSGWsPbKT3ZVlFDU1EKjW0GzsQRAGTSvSc9lZW4YoiuRGxw+JKoCRYVEcbKqlzthN\nsuF4fc2q7g4EBKbFpzA5PgW728Wm6lI+LDrIealZ1PR2IRUEPKLI4bYmCtuaCQ0I4NKMXKbFp5DX\n0kCXtZ8xkT5TsDCNlszQCN5/7z2qa2r4S0oa0xOSsLtdrCsr4c1DB4nQarE6XdhcffQ5HOgG17SJ\nokhJVycJ+iBuGDueB7b8QHZEOLdOmoDL42FTVTWbqqqRCgIH29uI0uowqNWkBAUzMsRAhbGH27f/\nQFyAjmZrPwIgl0kRRHgzvxARmL9gAW63m02bNnF15sghUQUwMToSg1rF3sZWblj3PZG6AEo7e5BJ\nBEINhp+tA/VbyM7OxmwfoKTTSFb48Tb2N3WgUasxKOVMiTke1dEq5MxNjuGd/8aart9DV1cXc+ec\nT3awhveunEGUVsVn5U08/tprJCUlndRS/0TKysq48sp5nJcTwUOXjEerkvHGljoefvhhUlNTmT9/\n/h/qX2VlJVdccTlzpoXx5N/G0dhm55yb9/2htn6JU6MM8o8Q1FrobQO3EyEsBm/VEcTeLiRBkQh6\n338SotMGMgUSlRbFiHEglSM6BxDdjsG6VQL33nsvu3btIjMzc5io6u/v5+uvv+aZZ55hy5YtzJk7\nB1tdGf0NVbgsvVibqrHVlHDxxRczYsQIHnzgAWwdrfSUFODo7cHa3kzPkQNERkb+al2DgIAAdu7Y\nwTvvvMP5Z5/JJXPPZ/369axds+aUqXDtx48fP378/E/T39+PiMi45FzC9WHIpDJiQqLIjs9CFEUa\nGhqG7b9q1SrOP/98Sg4fJSogBL1aS7/DTt+AlfLWWgwaPUFKLcXNVThcToqKiggN0DMyIh6lTI7d\n6cD9M5EOt9eDZDDyc/HFFyMJUGF1OQhR67g6ewYhmkBkEhlqmYLz0sYRrNYSoFBx42nnoFcFYLbb\naDb2oFEoCNUGIgDFbY0MDDr5uU44Z3xQCHKJlM+PHCS/uZ5mUy9bqkrZW19NsFrD2SMyCVAoCdVo\nuSJrHBJB4N9VxSCFiUmJhGg0eLxeEoNCMNpsvHxwF42mHgBkUgmTYo+njbm8Hjo7O8kKj2BOWjo6\npRKdQkmHtd+3PwI6uRxRhOfy9lDY0UqlsZs3Cw9R3dtDmsHAC3n78SJS1t3NlppaVuzczafFJaTo\ngzgjNp6Dba38c/cOOgfXVzlFkfPOO4+FN9xAytTJLFu+nK++/hq1WoPV7eaMmFgmRkXx0dq1nH3W\nWchkMhzu4ffIC7g8XhQSCeEaDV63SGpwEHa3h+UPPkhXVxfr1q1jy5YtuE9I4QRfqtrGjRv56quv\nMJuPR1Zmz55NVmYG/9iSz7eVjRR3GHlxfzHry+oZO24cTo/3JwYeA24PEomAzWYbtr2jo4N169bx\nww8/4HL9tIDx70UURZ588knsNjt3jU8jPTQQvUrBktwULsuI48XVz//mtl5//XVCtEpeWzyG5HAt\n4YEqHrw4g5lZEbz0wupfb+AkvPnmm+i1ctauGEtaopaQoJPb5f93OOUiVmJTKVi6B/9dCRIpsrQJ\nSAZd/TzdTXhqC/FGJCHVhSBIpEgC9AhyOer08Xht/diO7ECQq1l6222DUSmfiHn//fe55ZZbsFqH\nr3uKT0igtaGC/poSpFIp86++mpdfegmAhQsXYjab+ec//0nHYAj99NMn89577/6mqt5KpZJFixax\naNGi/9Qt8uPHjx8/fvz8AvX19QCEnJDKF6L1mRJMmDCBu+++m5UrV2IymVh+/3JGRiYxLilrKAVu\nV0U+zb3tzMmchl7tSx3Mspn5umQnEboQzs+a7DOmiMvgo8M/UNfTRrvFSGSgL1rR2NtBq7kbrUrN\n1KlTueeee7ji8stxuVz0uty0W3uJ1hkYcDuJ0AYhPWHCNT00moK2Om6ddi42l4MP8nYiAq2WXsZF\nJ1HW1UphayNjYxMJDfD1r6i9GZfXQ4Q2kK9LCoHjHsu5kcNtua0uB27Ry6yRaZw1GME7LzOTd/Yf\noNdm5+6JM3ju4E42VBQjEQTmpGYSOGjGVW3spqy7E41GQ3ygb3zm9Lh5/sBuugZFUGt/P8ekRJu1\nj1cO+5ZzyAZTxb6pqkQuk/HRxx9z1513suaIb+3TPeMnkj2Y/ndJ6kge2rOT9VUV5IRHUNdr5Nkl\nS4YVtL3jjjvwulw8d8Z0DIPOexW9Rv6xdy+TTz+djYfzmZEQR0SABlEU+XdVDRankzCNiqIu33gz\nUKfj0UcfpaWlhbjY2CGRHBMVxUeffMK0adMA+Pjjj/nrzTdjGhRUGrWKJ1es5Pbbb0cmk/H9D5u5\n/rrrePz7733tarU88sgjzJo1i6lTp/J5eR2XpychCAItfVY+L6/D6nQRGx3NK6+9xhVXXMEDDzzA\ns888M5RaGRUZwZq1H3LmmWf+5D3/LbS1tXHZpZewd99+AC5bt4dpcaG8+JfxBKkUjI0I5tPSI3i9\n3t806d/Q0MCoGC1K+fDUwXFJej48VP+H+gi+v9nRqVpUyt+ekvhHOOWEFX1GhBE5CCERYLXgrTmK\nuyYfefZMBEFAYojF01SG19SBVBeC6Hbh7Tchj/FVlJZotMhCIvFYLdTX1VFZWUl6ejr79+9n0aJF\nKMKiCc48DRCwNVXjaG+iubmFyy+7lPvuu4+4uLhhLjcAt912GzfccAMVFRXo9fohAww/fvz48ePH\nz59DT08Pzz//PP/++t/IFXLmzZvHX//6199kW52ZmQlAh7mLWEP00PYOcycCAqnhSTz99NPEx8cT\nExPDgGOAjJjkofUhgiAQExxOk7GNrdUHCVRpSQ9PJEYfTnRgGF7RM7SvVCpl1sjT+LZkLxuO7iIy\nMASvKNLZ14tEkCBTKrnzzjuZOWMGeEVCNYE4PC4+K9lNtC4E84ANp8eFw+1CObgGTBRF6no7ERFZ\ndzSPxt4upFIZaampKFUqDhUVo5LJUMnkvL5/G/FBBuwuFx39ZnKi4rggPZd9TTVsri4lJSQUm8tF\njbGLGYlpQ/0u7fStE5+Wctw5USqRMDUlmfcO5OHyehkfFcfuplqyRo3iy6IiCjvbEIAaYzczZ8zw\nFRwuLmG2KPJlWQnt/b5olUYmJ0Au56rMbOJ0eo52tvNRWREikG4Io6HPgt3t4rPPP+fCCy8kICCA\nxYsXI7PahkQVQKBSydTYOL6tq2FXcxOXXXopF1544bBn/fWGDUyOiBwSVQAjg0PICDEw4HAw4PVy\ny3ebyQ4PxWgfoNHSxwUjk2nqsxKVPIL3PviAtLQ03nzzTf75z3+ycFQa5yTFYbQ7eK2whDNnzOCs\ns8/mwosuYunSpZwRHcG1k8agkEj4pLKGv/3tb3i9XvIOHKCkqIjE5GTWrl1LZmYmqampQzVLly5d\nyrMvvsiG6kYMKgX57d2EqVQ8M3k8n9Y0cPXVV3P06FFWrFjBzTlpXJIaj9Hu4LmCci6YO4fKqmqi\no6P5rVRWVvLss8/y0do1KEUPb/zlNMZFBrO3pZt/7C7i7s0FvDVnIjsau0hPS/3NmVSZmZm8sOkb\nLHYXgWrf++rxePn8QAsOt4KxOaOZcsZ07rrrLpKSkn5zf7Oysnhm4wZ6LU6CA09e7Pi/y6mXLxYR\njyQiDkGuQAgKRZI2BgasiObOwR1E8HoRnQN4TJ04yveBAPKI47aZotc7NEMjk/m06UsvvYRMo0U7\nMhepWotUHYA2dTTSAB2CSs3nn3/+s6LqGCqVipycHL+o8uPHjx8/fv5kurq6mDBhAiueXEF7cycN\nNU0su3cZs2adhcPh+NXjc3JymHXmLI40FlHbWY/ZZqayrZqSpnISQ2MZHZdBvCGGVatWDY0TvN7j\niVrNxnYO1B5Fq1YTGW7A7h1gc+UBSttr8YjewWUHxxly65PJiBuZgsagJycnhwcefIBN329i0aJF\niF4vyeGRaNUq+h12QjWBmAdsuCUiXgG+KNnvncomAAAgAElEQVRPfW8nZZ3NfFq8h06rGZ1STb2x\nE1EUSdIbkJj6KSkuQURkfHQSZydlMj1hJCa7jY5+M6MiYpgQk8SR9ia215ajksm5cvRpnBabQIPZ\nyBdlBTSZe6ns6WBvcy3gcy38MW6P77NEEHAPRjH27dvHe++9R+6MMxg9fRrvvvsu323axH333UdN\nTzerDuxmf3MjkVodQUoVNreLa7NzyTCEoVUomBwbzwWp6XhFkdLuLrxSCZu+/54LL7yQp556ijlz\n5mAzmXB7vT9x5XN7vSD6+tPV1fWT9DyZXI5bHH4NAJ02K/n5+cRoAkjR6ynt6qHR0sdZyfGYHQ4K\nWju46JJLyMzMRKPRsHrVKmbGx3BVZioGtYrUED3/mDIeEDm0cyd//etfMaiUPHBaLvE6LZEBGm7P\nHUW6IZi777qLPd9uJNnWR8We3Vx99dW8+uqrmEymof6sXr2ajRs3YlVqKO0yceuodNaecwZjwg08\nNjGXMLWKV19+mbMTo7k5J41wjYp0g56nzxiL6Hbzzjvv/Op7f4z8/HzGjR3D52vep89q44lp2ZyV\nGEGwSsH5KdE8MCmTzfUd3PlDPt/WtHLvfff/5rZvuukmPEg5+8ndvPJDDfuquhn/963Ud1nJCZCR\n7TTx8TtvMW7MGEpKSgBf0eRt27bx7bffDkuf/DFLlixBIlVw3q15fLenk6Iqy2/u0+/hlItYCQEn\nOPVogwAB0WH31a9qrwOPy5cS2N0ECMgi45EofTMVHosRT28HgkJFekYmKYMzMVXV1UgCAoe5lQiC\ngDwwGJepB4/HQ0tLy0mFlR8/fvz48ePnf4ZnnnmG5qZmJo2aimbQEKK3z8j+/ftYs2YNixcv/tU2\nPvv8MxYvXsy6desA329+oiGWMQmjADAEBFFUX86ZZ56JTqfjaFMFp6fmAgIH64qJCg3lzHHjkUgk\nvuLCZaXkN5ThFb2EaoPwil4kggS310NBcyUKuZw9e/cyfvz4Yf247rrr8DpdXHP6TDSDBg51XR18\nc/QQ2REJFHU08Pjjj/Pggw+yrnT/sHU4AXIlRvo5NzWb0ZG+CeTvqo5ytKOZXYMOgnKJlGnxaXTZ\n+ijuaKa4owXwOb7F6IOQS6U0m00opFKqejo40u6zgQ9UqhCAH8ormJs9Cokg4HC72VFdTYxOj8vj\n4VBbI26PhxEpKbz/wQfD3OuMRiPPD7ot1/b6igF7RS/BKhUmxwBJ+uG1oFKCQhCBO8ZM4O3yo3z8\n8cdkZWXx9wcfZPaIZDJCDfzX/oPsbW1hSowvbbHDamVXcyMzkuKYEBPFEzt38sknn3DNNdcMtXvZ\n5Zfz3DPPcF5iEvGDRYd3NjfRY7czNzmJ67IyEAZF4uMHDrKtrgnPoHh79NFHefWVl3nzrbepa2hg\n9pjMYX3WKxXEB+rIDAniQFsn6UH6YSmbgiCQFRxEs6WP92ZMRTqYRvrc0RLeeO013njjDRYvXsxL\nL72EXC5n9uzZ6DQaZiTGsiD9eKRQJpGQFRTIjtYOckYMj0oFKuQkBwVSW1vLb+XuO+8kTq3ghuxE\n7tpWyLiI4YYcYyN8z2ZTo5Gnn36a66677je16/F4ePrpp3E4nFS12Xnw0xIkAnhFeGn6aBaMjAPg\nMYeLWV/tZ/n993Hr0tu4/rpraW3zGcMFaNQ88uhj3H333cPajomJ4fvvN7P4+kWcd8v+33ytv5dT\nTliJ/SbgR576lh5AxNPTjKezHux9gIAQEIg0OByPpQd3ewPWfjOCVIbX3A2CT4iljkgZElJZmZkc\nPlLki2YN/lGIoojL1AMSCQql8qRe/s3NzaxevZpt27cTEhzMwoULueqqq/wGFH78+PHjx8+fwLp1\n6wkPjhgSVQDBuhBCAg1s2LDhNwmr4OBgvvzySx5++GEee+wxzsqcil593Ia8s89IYlISy5cvJyw0\njLq6WlpNnQRrArE57ExNzhn6nRcEgVHJKZTX1xMREUFnZydfHN1BiEpHl9WE0+vmq6++GiaqHA4H\nb731FmvXrCUnNmFIVAEkhUUQotHSYOpiREoKl1xyCX9/8EFUcgWzUrKICQymydzDlmrfjH9isM+8\nq9dupbijhcQgAzNTRqKQyjjYVMfW+jK0cqUvkjYoGmbOnMneXbtxuN1U9nQwIS6BWSPSaO/rQy6V\nEh6g5ZmdW9lfX09lZyfRej1VXV24PB5idUE8d3AHEkHgmuwx5LU2M3fuXMrKyobSuxZcfTV7du7k\n2jG5xAfpWbFjFxIk9Nh9RgyVxh7SDccnq8t7upBLJCQE6pkUHs36deuYOnUqLreb81JTCJDLOT02\nhtePFrCloQ6tQkFJdxcGjYaL0lPRK5Wkhobw9ddfDxNW9957L+u//JJlu3aSHRrKgMdD+WCdsktS\nj48DZRIJF49IobCrG5kgsGLqJOQSKWsqqrj0kktISkigsLOHOSMSh9ruGUwd/EtCLANuD3ltnXxW\nWcPe1g48osiEyHAOdnSSEqgbqjkmCAJXp6awvq6B2fFRvPv22xgMBp588kkA0rMyyd+9G68oIhk8\nxuHxcKTXTEhICHkdPSzITB7qg9HuoNJo4tqMjF995wH6+vrYsWsXT56RTYbB977vbelmzo8E296W\nbiSCQMGRI7+rQPGTTz7JSy+9yN8vSOPS8dHUd9tY/FYhoktkftrxNXxBSjmL02N54JuN/PDDZqaO\nCOTT66agV8t4ZVsD99xzDwkJCVx22WXD2p84cSJFxaWUlJRQUFDAwoULf3Pffiun3si9owlvczWi\nrR9vVyveigJAgP5en6iSKZGERoPbhbu5ClloDEhliE47or0PQRUAEimCMoBvv/uO3sFZlNtuuw2v\ncwBL6SFcZiMuSy99pfl47Fa8dhtLFi/+2WK/VVVV5Obmsmr1akobW9h16DALFixg8eLFf7iInB8/\nfvz48ePn5EgHo0QnIiL+rno7ALfffjv6QD35DUW0mzsx2SwUNBTT0ttGc1Mzb73+JqLZQaguBKfb\nhU10+s51wvmPfX7uuec4dOgQ866+iqScdK67YTFHjhzh3HPPHdrX5XJx/vnns3TpUkSvr9jviW15\nRC8Wh4177r0Xt9uNCJw1IouRYVFolSoywmOYkeKLoBw7vrC9EYVUymXZ44jU6QlWa4aiL8EaDaPC\no1BKZUgFic/Vzuvhw6JDeL0iXlFEJpESE6jH7fVSa+xBKZMRqg6g124ndORIMrOzkUiltPSZGBkS\nyrLTz2B0eBQLs8cgA9544w3ANzb69rvvuDh9JONiogkLCGBaYgJt/RYsTicamZx3iws42NZCnamX\ntSVH+aamkilRcb66UXbbMBdFrygiCAJLxuZwy/ixIIGjXZ3MSk5gfnY6Hf1WPF4vXpGfTGq73W4c\nDgciUGUy0dRnGdbujzn22SuKHGjrJFkfyPJxuegUChKTk9nd1MZrBSXUmSwcauvkoZ15BMjknJUQ\ny/TYKPpdLl47WoZGJiVEqeCDsiqa+21MiAj/2fNMjYng8tQEXnnpJbq6utiyZQuzZ59HpbGXv+8v\noMRoorDLyD178+lzubl+yRJ2NnXw5IEiKowW9rV2ccuWAwgSCddee+0vvOXHOSYkPSKkheiYFhvG\nP3YX8Vl5EzWmfj4oqWfFwUrmzZv3u0SV1+vlhdWruG5aPH87J4XYEDVT0wxcMCYCryhy4p/rsfdS\nIxf4+OaxjE3QkxIewDPzMpmZEcbzq/7rpP0fNWrUn1Y0+ZSLWBEUidhYgdhQPny7IEESHI58RO6Q\nY4+r+giuxnKEgEAkMgXq9LEADNQU4TEbcbtcNDc3ExwcTG5uLuvWrWPxkiV0Hdl7rFEkEgnXX38d\n//VfP/+A77//fvoHHISPm4p0sFZEf1sT7777LkuWLGHKlCl/1p3w48ePHz9+TkkuvexSnlr5FP32\nPrSDjnw95m6M5p5hjnC/hZCQELZs3cL8+fPZVe5zpgsICCAxMRFLVy9npkxALvUNt0rbazjSVklM\nTAxFNdWEBwcjlUoRRZEj1VVD44+xY8fy+uuvn/ScH3/8MVu2bOGCUROo7m6jrLWJ7NgEdCrfsoWq\njjbMdhsLFy7kxhtvZMOGDQDEBg5P2YoJ9KVs1fV2MSYqAZPdSqROj3xQXLZaTBS2NXFeWhbjYnyp\ngjaXk7cP+er/WFwOvFoNVmM3+S1NpISEsqmqjM5BkwkBkEulzJ07d6gPYaGhjNWHcHbS8UG3Qioj\nWhtIdbWvmO+xtLSUH9V8mps+kn6Hk7yWFuxuFzY3vF1UMLT+DOBwVzt72ppwDa7rWn7ffchlMjZU\nVLEgOwuJIJATGc7munokgsD2+kY21dQDEKhQYHE6+dcJdUBXrlxJU1MTSqkE66A1eaBCTp/TxScV\nVdw02pfmaHY4WFXgc0r0Ap9V11BtNnP32FxG6LQo5HJWrFjBvx57jHWVdQAkBGpZccYEAuQy1pZX\n4wVWT5vEKIPvuTT09XPTtj38u76RK0ckI5dI8Ioi71VUoZZJOS0iFAnwYXktCfHx2AcGAIgMD+eg\npZ8fNu8GIC4mhvUbNvDRhx+iVcr5d20zn1T4SgJEBKhwOF0UFBRwzjnnnPSdO4ZWq+WsWbN4t+Ag\n5yVH8fysMSzbfoRlO3z12SQSgSvnzeP1N9781bZ+TH9/P51dPUxKiRu2/apJsby9s5G3yxq4ISsR\ngC67gzfLmoiKiiIjyIVGMXwy5PQUPW/nVf+u8/+nOPWElXsAYkaCw+arZ+Vx+8LaohdZdMowxx5Z\nTApOYxtivwlJlC80LYoiHosRQZAgUyiIi/O9ANXV1WzevJkRKSmMzs5m8uTJTJ8+nVGjRg1VaD8R\nURT56quv0ManDIkqgIDIWKxNtaxfv94vrPz48ePHj5//MPfccw9ffvkl+4v3YNCH4vV66TF3k5GR\nwXvvvcc777zD3LlzufHGG39T6ZMxY8ZQWlrK0aNHsVgsJCYmEh8fz8T47CFRBTAyPJHSrjpmz57N\ne+++yxfbthIVGkqP2YzFaiVYo+Paa68lOzub7Ozsk57vq6++IkofQmyQgWB1AE293azdt4MEQxg2\nl4M2Uy+XXHIJ7777LoIgDKXXNZmNjAyLGmqn2exLadtcU0KNsZMuqwWr08H7+fvQKBQIgkCAXMGY\n6OODXY1cwfiYeDbXlCMCDz/8MDExMVy7cCFrCw8Rpglg0ZjxBKnUFLa3sr2uZlh0IC0tjbrK4YPe\nAbeblj4L8wZt2UeMGAFAVU8PEzW+FDCpREJ6eCh5LS0EKpVYBqNIs1NSmBgTjdFu57OycgY8bu6f\nOBGADTU1dAJb6xqoMJqI0wVQYTRhdbnwiCLTomI4JzEBh9vDJxUV9LlcvPjCC7zx+utccOGFLFmy\nhLVr1uB0uzkzPpbzUgb3La+iqKuH7xsaKeruITVIz4H2dgCWjs5idJiBil4TbxSXcefO3ZgdThJq\narjjzjtpbWvjlVde8dUx9Xj5rLKWSnM/zWYLY8MMQ6IKIEGnZWZMFFuaW7li01bGhhko6zXRYrVx\n/2nZaOQyvqxuBOCi+AjCNCq2NXdQ12vEJUhYs2YNqampjBs3DqlUylXz5jE/K4FFo5Mo77agUchI\nC9Zy0Zd7Wb9+/U+EVXd3Ny+//DLbtmxBq9Ny1fyrufLKK3lu1SrOmDqVmZ/uYFq0gc4BXxR2/vz5\nPPXUU8TExJz03T0ZWq2WyIgw9lQZuWT88bTCII3PGfCePSV8UtNGrEbJlpYe1IF6Lpo7l0/WvEv/\ngButyvd3Jooiu6tMpI1M/919+E9w6qUCejzQXA5djaAOBJ1h6CvR+9PiewB4vUh0QXisFgYqCxDt\nVkSHjeuvu46goCD2799PTk4Or7z+OvlVdezOO8Rjjz3G4cOHTyqq/Pjx48ePHz//Oxz77V6xYgUZ\n2enkjsshJSWFsrIyig4dpayglGX3LmPy5MkndRk7EUEQyMnJYdq0ab8qxtLS0pgydSqIYLXYMKgC\nmZ0xkfMzT0clV/Dyyy//5Jj29nZ27tw5FM3xil5azUYcHjeX5U5mbGwy7eZezA4Ha9asYc2aNRw4\ncIC9e/dy//33IyCwubqYss4WzAM2itub2NlQwdw5c/mv557DMCIRu8eNVCJBp1DSN2CnoqudH5ed\ntTodNJiM2FzOoa3l5eWEhoZyxbx5iKLIgtxxjDCEEhoQwFkpqYyJiuadt98eSnW86+67qerp4svy\nYjr6+6g39fJe8WFEiYQbbrgBgJSUFObOmcPnxSUcaGqmx2Yjr7mZz4tLyQwPI0AhRy6VMikmmgvS\nUokICCAjNJSl48fh9npp6utDLZfzl4QElBIJ8+fPZ8zUqfTrg7nwiivIzc1lpMHA9aOyiNPpiA/U\n+a5TFOmrrKS3uJi777qL6dOmYTaZSA3Wc3NuFgmBOtJCglg2cSwauQyNTEqb1UpRTw8Oj5fFmemc\nkxBHpEbD9JhobhmdRZd9gFGGYDxdnfzlL39h9erVLFu2jMMFBZx1wYV06YI5beaZTJ48+SdukHa3\nm16HA1EUiddp2NrSRqd9gFty0skND2FNWQ2HO3uYHhNOr8PJ6sIKJMCESAN43Cy95RYiIyORSqV4\nPB7cHg/t/XZkEoGxUSGkG4abrv2YlpYWxo8dw4rH/4WirYL2Iwe4+uqrWXjNNWRlZVF49Cg3Lr0d\nc2QiIybP4Ouvv2bNmjXDRJXT6WT//v3k5eX9bDHkHyORSPjbHXfx3u4mnt5YRW2nlW2lXSx8o5Do\nqAjWrl1L9ISp9ESnsPTuezhcWMh9992HwyNwxSuH2V/TS1lrH3/7sISdFd3cceddv3i+PwvhVFnH\nIwjCWCCfkaeD0w51hUhScpEERSBazXjKDyBotChGTRmWCij2tqPWaLANFf0VQIBrFlzD66+/hlKp\nZMzYsZTVNqDNHIsglSGKIrb6SpwdTTQ1Nv5iXYBLL72UbzZ9T2jOxGGpgMaKYnbv3u2PWPnx4+f/\neQ4fPsy4ceMAxomiePh/uz//Vzj2u5Sfn8/YsWP/t7tzyuLxeJg9ezY//PADE0eMxzA44Wqx97G/\nOo9//OMfPPTQQ7+73WlTp1FaWDQ8FbCjhiOtlZSXl3PhBRcgMTuYkDDcNGBHdSEJ2SPZvn07AAMD\nA9xyyy28/977eAYngMPCwujq6ho6JlyrZ1JCGt9XHeW2v93O+PHjuW3pUjoH9xEQGBuXQI+1n3pj\n99BxqampHDp0iMDAQGafey6Hdu/l6uzxaOS+8cim6lIOtzUxOy2Djr5+Ctubh9b3yCUSXF4vwUFB\n9A7afutVKu6dOmPY9RxubeHL0iLsdjsqla8A8PPPP8/fH3yQ/sGxVVxsLO+9/z4zZ84cOs5kMpGY\nkIDZcnxNU1Z4GBPjYng735dytzB7FJNjhxcmfmjHTgbcbixO5+C1+1Izj51LJpWiUCiYGRXJlYMR\nss0NjbxfWso/Jk4gPcQXMao3W/jngTwkUinnJcQyPzNt2Hme3J+P0T6ARiaj1Ohbb//yjKnE6o6L\n6j6nk6s3bWX5uBymREXwfnk1n9fWU1xczBOPP86HH32EdzBtMTs7m+LiYp6fOpGskCA+qa7jg/Jq\n7INrxZQSCeEBGuwKJd09Pb5nIPONOTODtRztNvP3iaOYm+wTNp22ARZ9v5/zL7uCaxYuZMn119PQ\n1AT4zB/unpTB3LQYNtW0cd/WQjZt2jQsYrVkyRI2fPIhn155GtGBvhTTr8tauffbIr7//nvOPvts\nfolPP/2Uv922lPZO3zsYFxPNK6+9zvnnn3/SY7xeL8uWLeOFF1bjdPrSLkePyuKjTz4dqh13Ilu3\nbuW6RQtpbPK5VQbqtPzr8Se47bbbfrF/f9bv0ikprARNIGL5XgS1DmmSL9Turj4M5i4EpQZJYAhe\nixHRYSM3N5cDBw6wb98+6urqCA0NJTc3l9jBP+Tm5mbi4uLQjsxBGRo5dD633Yr58O4h5R4eHs6V\nV17JjTfeOMzEoqqqikmnn05ffz/yIAO4nNiM3SxatIi33377pDMJfvz48fP/Cn5h9fP4hdX/DR5+\n+GEeeeQRQrTBTEqdMOy7I/VFhMQYOFp09He3m5+fzxlnnIHX5SFKF0qfw0q31cSyZctYuXIlc+bM\nIW/nXmanTxj6rfd6vWwo2cO8BfOH1ljddNNNvPP224yLSyE+OJSufjN7ayuQS6WclzEGy4CdvXUV\n9DsHCI+IYMSIEezevZuUkHDGRyfiFUXymmtpshi5evzpyCQSzAN2SttacQaoqKmtxW63ExAQwNnJ\n6YyLPl630+pwsDpvO+Cr83RmQiqpIaF0WPvYVFuBzeVEIZUxJyWDvLYmmvtM3DN1BvpBAQWwrrSY\ngrYWBhwO5HL50Pa+vj7y8vJQq9VMnDjxZ01D1q1bx2WXXoooigSpVQSpVNT3mhABnVJBdlgYC3+U\nMtk7MMCD27ajlctZmJ5FqFLF80UFuLxe5qenk6DTcbS7my+qq9Ep5Dw/YwaCILAy7yASAe4/bbiV\n/eqCIxRZzEQrFUyJiaKwsxu5RML4yHDeLy5nwOPBI4ro9XrMZjNLR2dxTsLxtMkD7Z08fvAwz02d\nSFpwEHa3m6u+307u2LEUFRayeFQKY8INlBtNvF5UjVcqw2q1kqzXUWPu49KUeGYnxmAccPBacSX1\nFit/f+ghLr74Yjo7Oxk9ejRjc3NpbW8nXK3kqwunDxs3vllUzYe1bXg8HkYH67ghIxGVVMqaygY2\nNbaTEaqnrNvMFZdfzseffDLs2NCQYC5LDeHOqcfXwomiyOz395Ez9UwCAwNpa2tl3Ljx3HLLLcTH\nH39v9u7dy7Rp0zg3O4ybz0zA7RV54Yd6dlf1kp9/+BfTXMGXglhQUIDBYGDMmDG/Ohb2eDwcOHAA\nu93OxIkTf1P67p/1u3TqrbEa4sfLHQFBAoIE0e3CY+pCotUjMURSWFhIY2Mj06dPJzk5mdbWVjSa\n4/asx2Yafhy+9QzYsRTlAQItLS3ItIF02Rzcv3w5r73+Ovv27iU83OfwkpqaypHCQp5//vlhduvz\n58/3iyo/fvz48ePnT8TpdLLquVWoFWoE4aerIwRBwOM5yTKBX0GlUiGTyugfGKDV0jkU6dHpfGYZ\nd9xxB2d/8w376kvIivQJoIKWKvoH7FxwwQUA9PT08M477zAmNonRMb6SLUGaAJQyOd+VFuD2ekgy\nhKNXa/ikYC/t7e30dvcQpNJwXlrOkN323PQxvHN4FwVNDZyTMYpgTQC13V30ORzk5eWRnJyM+CN7\n7mNUGH21gaSCwLS4FCbHJgIQptGikStYU5yPKIr8u6aMtOBQWvoFPjxymNlp6QSp1RS2tZLf2vyz\n4xmdTsesWbN+9t5ZrVZeffVV7r//fgJVKhK1OmrMJup7TUyZOpWe7m4a6mrZ19xCqFrDpJhojPYB\nPikrAwFuHz2WxEA9VaZeeh0O7hk3jiyDLxIZrdXi8npZV13N2yUlzElKwuZ2E6iQ/6QfEkFAIkio\nMZmpMVkYHRpCn8PJK4XFCECSXotCKqPc6IvYvVFShlwqJSc0hPJeE68cLUUCfFxVy4Pjc5EIAgJw\n6NAh/pozkgtH+MRIfGAAapmMx/b5DCDarDamRoVxW+6xdUI6UvQ6rvh2J1KplJycnKE+SqVSojSq\nnzw7AKlEwOl0olPIWDUlB5XMJ16fmJRNncVKN3Leeecdrrnmmp88I6/Xi1Ty0zb77E42bNhASkgg\nI3QqXt29m9deeYWt27czZswYAJ5ftYqUCC0vLxo91Mabi/VMe3wfL7zwwi8aswCEhob+akRs2HVK\npb5Uyv8DnJLCSrR0g92CEDloSGHvA3Mn0sgE5HHHQ72icwBPay0HDhzg9r/9jW83bgRArlBw8003\n8eyzzxIXF0dGZiY1LY0ogsMQJBJsDZWDdR5EAtOyUIf7UgHddhuNRb71Vy+88MLQeWJjY3n66af/\n526AHz9+/Pjx44euri7MFjPxhjgae5owWU0EBfiySqwOK+3mDq7966I/1Pbtt9+ORBS5aPw0lHIF\noihS1FjDQw89xPz58znrrLN47bXXuPvuu6kq8rm3HVuKMHfuXKZNncay+5bhcrmICTIMa/vY5167\nlQhdECEaLSqZnPCAQHrs/cTrDcMG2lKJhFh9MM1mX8qaZcBOWUcrDrebiRMnotPpSElJIb+9icyw\nKJQy3/CwvKsDnVxBn8tJUtBwR8Ekve/zmfEjONLVSru1D68oYnYM8Ga+zx1RIgio5XJmzJo1LFp1\nMkRRZOXKlTz+r39hs9pIDzGwJDsHmUSC2+vlneKjHNi3nzUfruWplSvJP3yYr6uq+KqqCgCNWo1a\nKiMxUA9Am82X/pcRMrzvmSEhfAnsaGpme5OvoLEEX/pfot5Xm6m138rBjg7kKhUKqYzHJ59G/GCa\n38GOTp46dAQBgXKjaaiIrcPj5fnCo3gH5+2zDcGclZDKc4dL2N3WQYfNjnNQqI85oajumHDfZ4Vc\nxoDLzdjw4c/coFaSHBxIS0vLsO2dXV2cHxvOl7XNbG3qYFa8L3vK5HCyrqaF0NBQ0qXeIVEFvvds\nUqSB3XaRRYsW/eyzmHvBhXy54Quuzo3DoPHVSPuiuAWjzcHirATuPy0VQRCwOFzM31TAbbfeyu69\nPlfssrISTk/RDxNmCpmECUk6yktLfvZ8/3/h1BNWzWVg9c0seHvbEU0diKYOEEWEHxUKBPD2+/Zb\nuXIlZVVVqEZmItHqcBu7eekl38LS9PR0QoKDKS8vx5K/EyEoFFd3OzJtIKJHjupH7jsytQZFWCSf\nfPrpMGHlx48fP378+PHR29vLm2++ya5duwgKCmLBggWcffbZf0oWh8FgQKPRIJVKCdLo2VeVR0Rg\nOBKJhHZTB+ER4dx5552/u12z2czWrVuZkJKBcnC9kiAIZMYmUdnexPr167nrrru48cYbmT9/Pnfc\ncQdvvfUWoyLiSQyJwDJgo/BwAbfddl02P6cAACAASURBVBsSQUKnxUSY9njx4Q6Lb3wSqPStfbEM\n2Bhwu0gNjaCjwUxrXy/iYO0m8NU9auszYXU6+a6siKrODkRE/pKWQXiAjuKOVgpqalAqlbxRuJcU\nvQGzc4AGsxEBn0Bq7jMRF3h8KUNzn8/UI0wTwNSYJD6rPEqmIYLSng5itDrUcgWt1n7kKiUrn3rq\nZ+/T1q1bee+99zD29DB5yhTkcjnLly9ndGQYR61WzktKRjZYV0omkTA7KYWiQ/tZdO21VFRW0t3d\nTVFREU6nk4yMDEpLS7n5ppvoGbBjUKkJU/vuT43JRGrwcbe9arMZiSAwJjSU/K4uMjIyqKmo4J/7\nDzAuPAyJIOFQR4cvwiSKTImKGBJVAOPDw9DIpDT3+YTbXxJiOTM+CuOAg/dLq7E4XDw0KZf0EN/9\n+qa2iVeLy7E4ndx888289tprlPaYSAg83mZpj++ZLr3tdp5/7jlKjSYu4Xh6ncXpoqnPOuTweIzo\nqEgsTgdnxkbw4J4j/Lu2BYNaybamDpAruHDWLLZsWI/L60U+eC9FUeSo0ULSqNyTvcI8/MgjfL/p\nO857fx9nJYXSbXOyo64LqSCwNDd56N0KVMpZkhXHPTv30dnZSXh4OMnJKRwu2DXsHfR4RQqb+pk+\n+7fXtvp/kVNPWA2KKuRqMHcNutSIqNRqBhorEaRy3xqrvl7EZl/x3sLCQtSjxyAL8c0eSHU6RLeb\nF196CUQRuT4YWYAOV5+ZwIE+XIOnEgTJT34IBIkEl8uFHz9+/Pjx42c4zc3NTJ48mdbWVrTqINxe\nFx988AH33nsvT51kcP7fQaVScdNNN7F69WrSIkYQqjPQburA7rSjVCnZtm0bBoPh1xs6gWPpgycW\nm3W4XYiA5UeGDGq1mq+/+oqRYTGMj/MNOkMDAtGrA/iq5ABTpkzh0MGDKGRy4oINdPVb2FlVSoBC\nSZA6gHaLiV115UgEgREhEeS31NFt62drbRnjY46vsbI4BgjQaOiTSXB5PSzIPY2owchOpC4Qm8vF\ngFrJ7PPOY/euXSSGp3LfvHncf999uGx2djTUoJHJSQ0Jo93ax8bqUkLVASTpQ6js9RkUqAbXSdnd\nbtqs/cyZO5dbb70VmUyG1+sddj8eeughHnvsMSIDdQQpFXy/aRMiMCo8lKnxcRxt7xoSVR6vlw6b\nlT6nw/fZ7ebNN9/kkUceISMjg4qKCoKCgoiNjSUwMJCXigq5Oi2DKE0AeoWS14qKuC4ra2iN1frq\nak6PjOT69HQeP3yYiooKvF4vUQEamqz9SBCI0WmpM1vwOBxDguQYNWYLNreHMJWK5CAdN+Uct/ZO\n1gdy0+Y91Jr7hoSVQipFqdfz6Usvcdlll9He1sZbm75DQCBKq8ZoH+CtklomjB/P00//f+ydd3hU\nVfrHP3f6TCZlZtJ7SEIKvYbQO0jTFayoCHZ0Lax1FRVF/Omqa1tdK4sFXMBGU1wsNOmdkJCEkgBJ\nSM+kTSYz8/7+GBiMFMWy7q7zeZ7zwNw559xzzr0397xz3vN9/0JJSQkffPAB8YFmxibGUN3Swit7\nCtBodW0C+S5cuJDDxUc4JML1me3I7NSefx0pZXdlLQ6P8OSsWZhMJj744AMe3LiHWzqmoFereH9/\nETvLq/n0jjvOeg8nJSWxdfsOLrzwQj7dsR29Wo3NqKPO0Yruey6CerV3fE7Ob2/74+2MGLGUBxbm\nMn14Im638PzKgxRVNDJ9+vSznvPXpKysjLKyMpKTk33uuL8Gvz/DSmdCldITRa1FRJBjeUhtKY7m\nZgBaC3f5svbr14+LLrqInTt3ora0XbIVpzd+QmCnXmgCvBfIWVmGvSCH7t27s3vfPlwOBy01Vegt\n3j/KnlYnzooyLrn8sn9PX/348ePHj5//Ih544AEqyivJTMpCrzMiIhyvKuYvf/kLl19++a8i8vHk\nk09y/PhxFixYwHcFvZqbm+napSs33nQjzzzzDLrvxJv8IaxWK7179aJwfwHxoRF4PMKWA7kUVXpj\nHc2ZM4eKigqee+457HY75RUVdEju3KYOmykQs8HIoEGDCAkJYfny5ae+s9moqqpi3pbVAERFRuJp\nsFNUW0lqaBTbjh0ir7KEveVeNzetSo2iKDw+ezbFxcW8//Zcn1F1ksQQKysLcnnppZfQaDRtznXV\n5Mk4PW4+LTjlxhUZEMilaZ0RETaWFKNCYVd5KUMTkqlqbqKloY69u/cwatQoAFKSk3nl1VcZMWIE\nOTk5PP7444xKacfw5EQURaHW4eDFDVuoa2kh0RKMSavhy+IiMqw2Pj1YQF2L16hSKwqRJpNXQe+F\nF3js0UepPqFKqFIUPCLYUXhy+2ZfWwO1Wp7Zts33uVtYGJkWC/ds+JZqR4uvbGljE3BqF74lJASV\nw8H6kjIuSk7EZvSKcmw97jUkKxwOJoYnthnHMJOBGLOJ4hOrWfur68ipruX111/nkksuAeDVv/+d\n3r178detOb7d/qFWK3fcdRedOnRgX14eAHP3FfL2vsIT1ziCZStWEBnpdfVrbGzkxuuvZ0hMGJEm\nA3NzD+E+cf+eNEjvueceAHQaDRsq7az6bD0ARoOBZ5991reX72yUlJSwbds27u+dyrUd4yiyNzNq\n8QbeyT3CDZ28/Xa6PbyTe5SunTr5VLCHDx/OK6+8wj13/4n3v/Xeg8FBgcybN4/evXuf7XS/CpWV\nldxw/XV8umQpIkKAycgfb7+Diy+++Fc53+/OsFKsUShqr5+voigQmYzUlIAhAAQ0tljctaVIk50H\nH3zQ9+uKp96O+jt/hNzV1ejConxGFYAuNJLWsqNER0ezPz8ft0pNbc4O9LYwVFodLVXHsQYH/yTZ\nVj9+/Pjx4+d/GRFh0aLF2IKi0eu8LlyKohBhi6Oy7hiLFi2ie/fuuN1uPvnkEz7++GPcbjdjx47l\nsssu+1F7eM6EXq/n/fff5/HHH+fiP1xM7r5cUm2JhBiDqGis4pW/vYLb7eZvf/vbedX73F//yvBh\nw/l81ybcbjctra30jE7FZgqmrKGa1/7+Gi6Xi5dffhmz2Uxlo51Ea7ivfH1LM40OB+3bt+eJJ54g\nNzeXnJwc4uPj6dWrF8XFxWzdupXQ0FD69+/PZZddxkcffUR8iA2tSoPL4yIu0IoglDXZ6dShIzfc\ncANvvvkmNY0NNLU6fbLqAKX1dqIiI9sYVU1NTcy46y7MGi29wqNwelzkVlZQ73RiUGvYVHqEwroq\nqpoaCdTrSbOEsr+2imN1tWjUalS1dVyb4RVaWFt6hHHjxrFt2zY++ugjTHo9Q9ol+Dx7QgwGBibG\ns3x/IWpFYUJ6Kh/syWXL8VK6hIcxKD6WZpeLzw4c4mh9PYmVldx5550MiImmSqWioLaW8e2TSAwO\n4vlNOxgYHU0Hm42k4GCsej0bSkt5a98+rkhNJSEwkKe2b6d7TBgdtGrWHS5jbHIcPSLDOFbfyMK8\ng9Q7ndTU1nJPt87Mzc3nT2s20CcqAofLxYZSr6iHRa+joNbO6O9c93pnK6UNTRjVap7ZtocNZRVk\n9e7NVVdd5cvzyCOPcLy0lGs7tqNbhJW86jrm5RxmyjXXkB4SxJzendGpVLxfWMyu6hr++tfnueWW\nW9rc419++SV19fXc3L8jcWYTV6bFs6eyjiMNTbyy5wBdLEHcmN6OVo+HN/MPk1NjZ86cOWRkZDB4\n8OA2CtVnIj8/n1tvvRWdWkW1w0lJg4PEYBNTO8bz1NYCVh+tJM1i5qtjVZQ7Wvls/gttvLRuueUW\nJk+ezDfffINKpWLIkCEEBAScxxP08xERJowbS+G+3bw6qT2dos0sy6nkqaefory8/Fc55+8vQPD3\nVX9Uat9xRaVGbYtB264HGrOFWbNmMXz4cMLCw2nO3YurtgZxuWg9Xoa4WgEFd1Mj8t2gZyoVRqOR\nHdu3M23qtYSG2lA7GgmUVqbfdBPbt28/zT/Wjx8/fvz4+T1RX1/Pvn37Tgu+63K1olJ9X3ZbQaVS\n43Q6cblcTJw4kUmTJrH0k2V8tuxzrr76aoYPH4HD4fhZbWpoaGDX7l10iEgl0RpLiDGI1NAkUmwJ\nvPHGG1SdiB10LkpKSti/fz8ul4t+/fqxectmBg0bSmOLg94xaaSFxhFqCqJjeCKdwxN5++23qamp\n4eabbya34gj7K47hdLuobLSz5lAONpuNSZMmAZCRkcGkSZPo3dsrz56QkMDEiRMZNGgQarWaDz74\ngJdffpnI1HbEJsTRuWtXDOFWLAmxPDRzJmvWrsVsNnPVVVdhMBhYmreXisYGHK5Wth0rZm95KX+8\n/fY2/Vm4cCFHjh5lVFIK3aNiGNUujTt69SMmMIjyVgfVATqGjx/HSy+9xMBhw6gNMNCtfz9Gjx5N\nkN7ANemdaW+x0d5iY0p6ZwI0Gp5//nmcTidaleo0JTudWo0Aaw4X0zkynECdjrigQKZ16Uiq1ULn\n8DBu69kNtaKwe9cuuoeHMyYxkdzqaiZmpDA6OYH0UAv94qLZWFZGq8eDSaPhQF0dK4qKUAHby8tZ\nVFhIfIiZW7Iy2X6sklHt4rg8M4VUazCDE6K5rUcHnwBFqNHAnOyeDI2NJr+mluL6Bjx4V7hcHg9f\nFZfwaWERDc5WiuwNPLVlN4pajRIWjt0WwaOPPc6qL7/0xfAqLy9n7ttvc01mIldkJpJuC+Ki1Dj+\n2C0Vl9vNrRnJ9IkIpXuYlaezOhMfaGbt2rWn/XDgPBGny6hWU+9spd7poneklW5h3r1kf8xMoXeY\nlX4RobyS3Q2zVsPixYu56KKLMJvN7N+//zQhjJMsWbKETh07kr97Fz3DglmQe4wxH25kSWEpM3q2\nY3y7CLYcr+H9/Uc5Wt+E0Wj0raR9l6CgICZMmMC4ceP+7UYVwLp169iwaTP/uCKN67NjyEoI5vEx\nyfxpcBzz57//q5zzd7diJbXliC3WJ6sqld5gaTTXo5wICqgoChIQwqZNm+nVqxe1NTWIR2jeua1N\nXc7jR3EePwqKCl1YFLrQCJx1NWi1WlJSUnjzzTd58803/6398+PHjx8/fv5TaWlp4Z577uH111+n\npaUFnVbHlGun8Pzzz2MymRg5ciRrvllHmCUatco7Ramtr6CpuYELLriA+fPn8+mnn5Ke0BFrUBgA\ndQ01rFu3lldfffUnCU2cZM+ePQCEm9vuqQo329hfcZCCgoKz7rcqKCjghutvYPUar2teZGQkc+bM\nYerUqVx11VUsXbqU6MC2ZaODbOwoO0B+fj6zZ8/m6NGjfPDBB3x7OBfwBs39+JNPfvSEVKPRMH36\n9B/cwxIaGsryFSu4ZNIk/rFtI+Cd99xwww3ce++9bfIuXrwYjUrF/BzvNonYwGDGpqTRPSKapYV5\n7M3J8blI3nbbbb5yPbt3J8kc5HNJA697WlJAELt37uLa56/liSeeYGfpcbpHeyfkTrebTcdKiY6K\n4tO8QpbkFaIoCv1jo9sYYAFaLe0sIeyvqqZDRjqljU0I0Ok7KnqXZqZS7XDwZs4p10W1oqDTqNl/\nwpgPDzBwqMZOY6uLrt9T4MuwhaBRKWi0OpYfLubWTplcnZ7KVZLCP/LyOdLQ6JWnR0GAuTkFzM0p\n8PXzs5UrGT58+BnHf9WqVbS6XPSOanvOXic+lzQ1k2bxCpWoVSq6W4PZvWPHafUMHjwYnVbLnWt2\nUFTfhEsEo1pNmFGHQaUi03JK7MSoUdMr1MKuQ4d49913eeC++zhWWgrAwAEDeP2NN0g7ESzZ4XBw\n3dRr6R8RzHP9Mjne5GTmpjw2l9dyz+p9PLXZ65o4ODaUSSmR3PL1XnRuJ7fecgtfnQhq/Z/Cnj17\nUKsURqa13c4zOt3GX74q/lXO+bszrGiuw1OwCSUwDHHUQ0M1oIBKhcd9SlTC01QPOj279uXhaW3F\n1C0baWlGnC20VlXgrq3CEJOAJigEV30djqNFOMtLULRa5s+fz6BBg7jxxht/u3768ePHjx8//2Hc\ndtttzH17LqEhcZjDQmhsrmPu3LnU1dXxz3/+kyeffJJ+/fqRd3grQSYbre4WauwVjB8/nmHDhjFu\n3DiCzRZAofBoHiKCJchGiNnKggULfpZhFRfnDexa56jHZjqlIFfnqEdRFGJiYs5Yrr6+nsGDBtFY\nW0/vuHQMGh2Ha8qYNm0awcHBxMbGAlDTXE9k4KkJXnVzPeANuaLX61mwYAGPPfYYW7ZsISwsjCFD\nhrRxy/slGThwIEeOHmXVqlXU1tbSt29fEhMT2+RZuXIly5cvp31IKD3ConG4W1lXUsR7e3eQYrUR\nFhp6VvfLuIQEthw42EYVTkQodTTRNzGBfv36cemll/LBokXsLa/AYjCQU1lNo8vFJwsXcfmll2Lw\nuGl1uTlir29Tt8vjoaypGaPBQHF9PcnB3m0axXX1WAx6tpaUs6+ympPb5R5//HEefeQR3B4PfWyh\n9IuIpLqlhY8PH+LvG/ehUSkcrqunU/ipa1PS0ITLI9x43XW88sorlDQ108ESQm5NLfm1dUQYDQyO\nieSfhYdpF2QmQKvhSH0jtc5W5r377lmNqrq6Ou48IRhRWFNPYvApVcDCGm8/w4z6NmUK65uI75J2\nWl2hoaEY9HqONjZxc6ckOliD2Hy8hnl5RahR+Ka0gvXHq1CrFAZFhpJTY0dnsXLNNdcwMj6cmUM6\nU+Vo5c09Oxg6eBD78vYTHBzM119/TWV1DXdl98YtMPWrHWgUhaey0okw6vnwUClLi8qpa2llxeEK\n4swGDHoVX69eTUVFBWFhYWfs+9koLy/n7bffZvfu3cTFxXHdddfRvn37Hy74I4iNjcXtEfaUNtI5\n+tRY7zhWj1oBt5yj8E/k9+cKqNZASxNSWQwNNYACYTEQaEHxeBC3C1f5YaS+Em1YPCqrdyOeSqNB\nE2RBHWTBXVOJMT4ZQ2wimqAQDDEJGBNTACEwvQs6Wzizn3iizSZYP378+PHj5/dMWVkZc+fOJdya\nSIQtkQBjCOHWBCKs7Vi4cCEHDx4kLCyMZcuWcellk9AHQGxCJM8++wwffvghiqLQ1NREs6ORvKI9\n1DfV0eioJ784h4bmehoaGn5W+/r37++V7C4voLqpFo94OF5fSUHVYcaOHeszvL7P+++/T1lZGf0S\nOhAZaMWsN9IrNp3IIBuzZ88mOzubjh07srWskPJGb73H7FXsLj/MqJGj2hg0qampXHnllYwYMeJX\nM6pOotPpGDNmDFdeeeVpRhXAk3OeJC4whEuSO5AcbKWDNYLJaV1wuFzsLj/OrbfddlYJ/OnTp3PM\nXsfywwU0tDppcDpZdqiA0no7t9xyC4qi8P777/PCiy+iiYqhyAOjL7yQzVu2sH37dhobG7m1W2dG\nJMWzt7KKlQcP0+xyUeNw8F5OLg1OJ1OnTWNdSSl51TUkBAYyf08es9du4e1d+yitb6CiyStEUXT4\nMB6Ph642GzekZ5BpsdA/MpK7O3ehqrmFJEsgnxQcZuOx47g8Hg7V1vPythyiIiJ47rnnWLlyJQk9\nerCi+AhF9Q3oVCpiAkwMjIrg1o5pGNUajjc5vCtyiYlceeWVZx3zd955h+qqKtJDAnltZyGbS6tw\nezzsrajlua1eZcfPikupcrRgd7byZu4BdldWM/3WW2lububgwYO++3zJkiXYGxq4v0d7JqfF0zUs\nhBs7JnFDhyRcIvx5Ww6F9Q3sqanjT5v3UO5owajX0yvSylN9M+gTaWVsYgSvDOxIeXkF77zzDoDP\npdasVbP88HHKmlp4a1AXLkqKJDvSwl/6ZNA/0sLuSjuljQ5KG1soqvUKwLWcEBj5sezatYvM9HQe\ne3gmh1d/zpsvv0CHDpksWrTovOo5GxdccAEJcbFMWZDH1iN2Wt0ePtpVzuNfHGZkR+sPV/AT+P2t\nWLlP7IeKboei0SLFeahCo/DkbUPEg3PfGgA0obGorVFIawuu0gM4y46hj0nAcyLYnMbSdglXa7HR\nfAg8LQ60ITaOHMilvr6eoKAg/Pjx48ePn987OTk5uN1uggLavj+DAkI5Rj4jR47kwIEDAHTs2JF5\n78xj8ODBbfJGRkbidDlpH5dBaIhX6KG2vpp9h/f4FMl+KiqViiVLljB27Fg25G/3Hc/Ozmbu3Lln\nLbdz506CjGa2H8unrN4bgNekNRAWEMyePXtQFIUlS5YwZswY/pV3qt6s3r155913flabf0127dpJ\n1yBrG+PJrNUTZQpEE2blz3/+81nLjhgxgueee4777ruPb0u9qnA6nY7nn3+eYcOGAV7Xxdtuu62N\nCyHAE088QUJQIIE6HVlRkZQ3NrG88CDLCg8CEGAy8d577zFx4kR27NjBwo0b8Zz4IbvZ7ea+7K6k\nWIIREdYeKeXNt94CoNv33DijTCbCDAYKquwowEvbTrkNGvQ6Nqxei16vZ+TIkYwcOZINGzbwhwsv\n5HhFBTurarh17SbUikLfyDBuyEzlwa27mHbppecc0w8//BCNSiGv1rs6NXPtLp8qoEalYvYTT/DY\nrFl8dsTrpqcAOq2WZ599linXXEN9QwMGvZ4p3wnq2z86tM05+kfbeG3vIf7UKZnLU2IREVYeLWfm\n1jyOHDvKHzomtLmmUQEG0mxB7NrldfccMGAAep2O9/Yfo9nlJjkogPhAoy+/oigMjw1lfVkNC0Z0\n4Xizkyu+2EmNqM66qns2brhuGpFqN4su60WoUYfD5eG21XlcN20qo0eP/tmy6Js3b8ZkMpFbcIw+\nf93qOz6ig4X7xsTz2Z7qn1X/mfj9GVahCWA/DqWHEJ13I6EndysoCqBCMRjRJXZCdeI7tDpUag3O\nIweRRjtovMve7qYG1IZTN5q70fsLgkqnx1lVjjkw8DfZqOfHjx8/fvz8J3Jy0uVoaUSvM/mOO1q8\n78+So2UkRqWjoFB08CijRo1m69YtdOrUyZf32LFjBJqCfEYVQEigFWuQ7awb8c+HlJQUcnNz+frr\nrykqKiIzM5OsrKxzBicODQ3F3txAq1ZPz9hUDFodh6qOU1R7HKvVyt///nc2b97M+PHjuffeexER\nMjIy6NOnz68S9PiXIiY6hvLjlW2OuTwealpbmH7JJT+ownjXXXdx1VVX8cUXXwAwatQoQkNDz1kG\nvPfJiuZmXB4PGpWKCanJDIiL4e3dOUhwCDk5OQQGBrJgwQI2bNhAr7BwssLDebcgn07hVlIsXtdA\nRVEYEBfF10fKKG9yUNzQ2OY8ja2t1JxYYUkJCSbCaGBvTR0Nra0sX/EZXbu2DZ6bnZ3NjLvv5r77\n7mN4bCRZ4TaONjSx8EAxG49XEh4RcU5X1E8++YTVq1fTLyqUUfGRVDtamJ9fjNPtISEwgPrAEO6/\n/34+/eQTNm/ZQoRRx8DYMHZW1PLt+vVcnhZLr4gk9lXXM+/tt0jLyASgsLaBrmGnFP4Kar3P08Co\nUN84jI6LYOGhMg42O8mvbTsOzS43xfYmJp54PkNDQ3n4kUd48MEHiQ80Ud7koN7pIlB3ymTIrWkg\nwqRHURQiTXqmd4zngY35VFVVeeX833+f2tpaBgwYwGWXXYbRaOT7HDhwgC3btvP28ExCjd59egaN\nikez2rFkwSY+++wzLv0BQ/Vc5OXlMXLEcDpZ9fxjTBp7Kxv5YF85ZU1OXrwylcYW90+u+1z8/lwB\nA62Q2BUQcHqXLtHqQDyAB3E04q4rRzxupNVJ69F8xOPmscceo1NSAiG4CQ4JwVl8EJe9FhHBVV9H\n8+EC1AFmXE2NtJaXctONN6JWf1/ZyI8fP378+Pl9kp6eTv/+/Tlec4iGZu/7s7G5jpLKAhRFRWps\nZ6yB4VgCw0iO7ohapeG5555rU8fhw4fRqE+f0GvUWsrKyn6RdqpUKoYNG8a0adN+lPFjNpvxiDCw\nXSeSbFFEBdnITszAagzEXmfn1unTWbb4I15+8SWuv/56RITs7Ow29ZaXl/8o1cF/J7fcOp3cmgo2\nHz9Kq8dNvbOFZUX7cbhcTJs27YxlRISysjJqarwrd2FhYUyePJnJkyf/KKMK4LrrrqPR2cqC3P3Y\nW1pwut3sPF5Bsb2eBx54wLeKMfvxx+lsszEtLY2OVisqRcGkbbteoCgKJo2G5JQUVpeVsrasFJfH\nQ4WjmdfyctHodMyaNQtDTCyFHmHIBRewYeNGhg4delq7WltbeebppxkZG8VNmal0DbUyLjGWGV3S\nafV4+OsLL5xRGe8kTzz+ON3CrTzUM4PeEVZGJ0TxZHZn6pyt7K6q5ebp05l48cVs2ryZSJMevUbN\nwvyjHKhtZGqHBG7p3I6eERauyYjnrq7t2LV7Nwadjjlb95NbbUdE2HK8hpd2HSDSqCc6wNDm/EEa\n74rS8sPHWVhwDKfbw/EmBzM35uFwe7j22mtpbGzk2LFj3HvvvSxYsICw1HScHuGejbmUNDpwuj0s\nOlDChwfLuCI1yld3iN77TM6aNYsePXow//VX2bLkQ6ZOnUqPbt3Iz88/bTyaT8SPtejbPs8n62ps\nbDytzPnw/PPPE6JV+NclHbksI5zHBySxa1pPAnUa/m95EQ6n52fVfzZ+f4YVoGh0YAyCQCtKUCi4\nW1GndAedAVBwlR7EsXctjtxv0TTV8o9//IOZM2eybetWyo8fZ++ePbRPbkfDvp3UbV5DQ84OPC0t\nuBsbaDqYx7hxY5k9e/Zv3U0/fvz48ePnP4oPPviA1PbJHDy6k70H1nDg6A5UKgg0hbQxmFQqFQH6\nIDZv3tymvFqtprahGkdLs++Ys9VJVV0Fqu+HU/k3cfjwYSwBgZj1bd2l3OJBo6gYk9aD4e06M759\nD5JCwrn5ppsoPaHItnbtWnp0705ERAShoaEMHDDQ55L1W3PLLbdw880388WRQp7evpYXdm/gQGMd\n7773Lunp6aflX7FiBR0yM4mKisJqtTJ61CgKCwvP+7wZGRnMmzePnJo6Zq7dwL1fr+WTggNMnz6d\nm266CfBKje/LzaWL9ZSrYkZIIF2T2AAAIABJREFUCJtLymlsPSVEdtTeQGF1LbfeeiuTLr2Ut/bv\n58Z1a7ln0yaKXC4+/uQTHn74YXbv3Utp2XE++ugjevbsecZ2HTt2jIqqKnp/T0Gwi82CUauluPjc\nKnPbd+4kO6Kta2WM2Uis2UhaejoJCQl8/Mkn3NMzlfcu6MncUT24qXMSbhEGRLc954AYr5F654wZ\nlLe4mPbldvotXs3ta3bR4HJjb22lusXpy1/c0MTG8hp6Z2Vx7dSpzNlaQJ9Faxn16UY2Vjfy1ttv\n89isWVgtFmJjY0mMi6OqqootW7fy7HPPsbq0iiFLN9Jl8Roe2pJPR6uZGzt49xy6PcL8/BI0isLL\nL7/M9MxY1o/vwbJRnflsTDeOHiwkLS2Ngf37sX37KVfYoKAgAgwG5u4raaNJMHffMVQq1RmN2/Nh\n2+ZNjIgPwqg9tchh0qoZnWTl/Q3H6f9/pyst/hL8/lwBAREPOJtRjKEoYbFIXiU4GlGHJ+A+uh+A\nDh06cN999zFu3DgsFkub8rGxsezZvZuvv/6a/Px8YmNjaWpqoqamhj59+py2fOzHjx8/fvz48bp5\n7dy5k2+++Yb9+/fTrl073nzzTT5f8UUbBTkAp8tx2p6N7t27U1xUzO4D2wmzRKJSFMprjiMiZGZm\n/ru7A0BUVBRNzhZcbjeaE54qrW4XdY5GesQkE3jC4FKrVHSNTuJwbQWLFy9m8ODBjBgxgmCtgQEJ\naXjEw74dOxk4cCB79uwhPj7+394Xh8PBwoUL2bBhAzabjTvuuIMZM2bw1VdfYTKZGDdu3BkDy65Z\ns4YJ48eTGBTMZanpOFwu1q9bz4D+/dmXm3vaPOqHmDx5MmPHjmXZsmU0NTUxdOhQUlJSfN9rtVqs\nISGUnBCoABgdF8/OqioeWbOVfrGROFxuNpZW0KFDB6ZOncqtt97Kgw8+yLp16wgJCWH8+PG+LRsN\nDQ3Mnz+f7du3ExUVxZQpU04T9LDZbGg1GoobGukWdkr44Hizg+bW1h/c4xcVEUGR/XQ3vCqni4mj\nR/PII4/4Vmta3B4MGjUDYmy8tvsQB+1NJIecUrU7VOetZ/To0cyaNYs5c+bwr3/9C0VR2L8/D3t1\nNZO/2sbY+Aicbg/Li4+jUyvU1dayZOlS7r33Xr755hsCAwMZO3YsY8dcwJ7t27gtM4Z2QUZWHa3i\ntttuQ0SYNGkSd911F1d0jiQj3MzaQzV8ebCKe9bnkRoSwMriSvbVNJAcbKSquZW7OiegUXmf40yL\nmalp0byee4zK/N0MHTKYnbt2ExUVxagRw1GLmyWHKihd2sLwOCu7KutZcbiKO+64g4SEhB97u5yR\n6NhY9m07dNrxvVXNBAQGERwS8oPG8E9CRH4XCegOCPGdhJAIAUSV2l1UHfp5/x+dIurEjgIIIElJ\nSdLY2Ch+/Pjx4+fnsW3btpN/W7vLf8D74D8lnXwvbdu27WeO8H83q1atEkAiLLHSJbmvdEnpJ1G2\nBAHkww8/bJP3q6++EkACDAGi1ehEq9FKgNEsgCxcuPAXaY/dbpfa2tofnf/QoUOi0WgkLiRcxmf2\nkYmd+0vX6HYCSN/4dLmiywBfuqxzf9FrdTJnzhy5+uqrJchokqu69JUp3frLlG795YpOfcSg08m9\n9977i/TlfCgrK5P0tDQBJDIwSAL0elGpVPL666//YNlRI0dKTGCQzMrqJ4/36S+P9+kvd3frJRq1\nWp555plfpb3333+/aNVquS4tXV7pP0Ce7J0l6RaLqFUqsVksEhsTI3fffbdUV1efs56DBw9KQlyc\nqBRFEkOCxKTTiVajkUWLFp2W95qrrxazXid/7t5RFo8cIH8b0EsyrCFis1p/cM44a9Ys0ahVcne3\nNFk+boDMH9lHBkSHiUatFpVKJSatRhICjaKAxJgN8s9xveWrSwZImFEnVoNW/jaki6yeNEDmjugu\n7SyB0j4lRdxut9TV1UnvXj0FkHYhgRKs0wggGTaz2IxaCTfp5LKMaMmKDpERI0ac1q6Tz9RrgzrI\n3sv7+9JFSeESGR4ura2tMnBAf7EatfLepZ1l35395cZesWLUqESjKKICGRVnk2kZ0ZJgNkjR5AFt\n0qM924lKQfZMzxJrgF5mzJgh7733ngDy9UXdZP6ITOkbGSxWvUaCdBqJjooSj8dzfjfDGVi6dKkA\n8mB2vNTc0U+q7+grD/SJE0CsZp0khJp+lffSb/5i+Xcln2EFgqKIEpMq6k4DRIlOFkDUKd1FCQoV\nNHpBoxMURR555JGfci39+PHjx8938BtW534v/d4NKxGRp556SlQqtSiKIipFJYqiyIMPPnjGCdbT\nTz8t6pN5Vd68DzzwwM+ejOXk5Mjw4cN9P7Bm9+kj33777Y8qu2jRIjEaDKKAqFVqASQ4KEgiAy1y\nWef+PsMqO95ruGzcuFHS2reX9NAon1F1MiWE2GTw4ME/qy8/hcmTJ4vZYJDrOnWVB7L6yT29sqVb\neISo1WopLi4+Z1mrxSJDY+N9RtXJlBQcIpdffvmv0t7m5ma5cMIEAUSr9o65OSBAli5del71jBo5\nUiICTPJs3+7y/vB+8taQPtInMkxMRsNpRllNTY0M6Of9QV6n8Z4z1GaT9evX/+B5Wlpa5NJLL/WW\nVXvvX5PRKBq1WkbGh8vy8X1k1UX95K1h3cRm0MmAGJt8PKGPBGjUotN4jSWD1vtvfFys5OTkiIjI\njBkzJECnldcHdJKNF/WTdROyZUr7WAHkvQndZMvUAfLxpJ6i06jl//7v/05r19NPPy0BOq3suaxf\nG8PqbwMzBZCOHTLFbDaL2hsLWXRqRQAxalSiOvGsbLmkt7wxJEMAeX9YR59RVXB5P+loDZC+ccFy\nZEZ/mZAWKgP795M777xTkq2Bcnxa/zbpmX4pAsiQQYNk165d53Udz8SsWbNEpVKJRq0Stcrb7uEZ\nwdL6al/Z+mCXX+W99Lt0BcQQAG4X7uI8qKsAoxlPSSHSZEcdmYz7+CEUYwD/mDePRx999LdurR8/\nfvz48fM/zb333svkyZNZunQpHo+HMWPGnDG2EsA999zDlVdeydKlS3G73YwZM4akpKTT8jkcDhYt\nWsS2bduIiIjg6quv9gXr/T4lJSUM6N8fl8NJx8h2qBQVebv3MXTIELZs3UrHjh3P2f5JkyYxbNgw\nPv30U+x2O4MGDeLIkSNceOGFfHVwDzGBVupbmjlcW84fLrqI3r17ExkZSeH3VPdEhPpW5zlFEH4N\nnE4nCxcupF9kNOEmr3tcq8dNiN6IeDzcfvvtzJ0794xugAAR4RFUfk98w+3xUO1sISIi4ldps8Fg\n4JNPP2Xbtm2sW7cOi8XCRRdddF5hbiorK1n5xRfckJFCpMnrsmlQq7kmNZFb125hxowZvPTSS5jN\nXje8kJAQVq9dy7p169i2bRuRkZGMHTuWVatWcddddxEcHMyVV155xgC3tbW1ZGVloVar8Xg8DB48\nGLvdzkN//jPTOyahP+FGmhBo4rLUGF7dc4jc6gY0JhO7tu/gwIED7Nu3j8TERMaOHetTZXx33jwm\nxIXR2ebtt0al4ob0eD45XMbTGwvpGhHM0gMVxMbFceONN57WroiICJpaXZQ1tRD1HcGLg/YmbxDd\n0iKaGhq5JjkKg1rFypIqDjU4uKdPAo+t87raFdY1MyTGSlZEENd/s49LkiOIMun59HA5h+qb+WBk\nJ0SEPRXN6Klk69atHLU3YXe2EqQ7tbeyoLYJs05Nyb6tDBo4gJ27dv8sl8CHH36Ya6+9luXLl/P+\n++9zdP92Vt7R4ddV4/wlrbT/5MTJFStbjPfXDa1WNFrtCWtVEcUYKOqoVFECbYKiiCosSqxW20+w\nj/348ePHz3fxr1id+73kX7H65XC73WK326W4uFiSk70eKUEms2g1GtFqtbJ48eIzlnvooYdEp9HK\n8NReMiqtj4xKy5JRaVliNpjkmmuuOa82eDwesdvt4nK55Msvv5TBgweLyWSShPgEmT17trS0tIiI\n+NyhekYnylVd+sqVnbOlU4R3pWHVqlW++hoaGnxlfi3q6+sFkHHtUuWBrH4ypUNnMag1olIUsRoM\n3n+tFtm+ffsZyz/11FOigFzULkUezeonf+7ZR3qFR4oCv8jKw49pv9PpPO9yhw4dEkDu7poh7w/v\n50vvDO0rakURBSQ2Olry8/PPWL62tlayevUSQKIDzWLW60RRFHnppZfa5Pvqq6/EbDKJTqOWhJBA\nUSmKREdGyp133ilmvU6+uLCvrLqony891Mu7snnhhAlnPfdJjAa9/LFDomy8qF+blBhkEp1OK6E2\nq9x0001SWloqDodDmpqa2pS32+1iCQ6WrEiLfD62p2y8OEteH9RBgnUamZAcJjuv7SNxgXoZHWOT\nHROyJPcP2dI7NEg6hXldcKMjIyXNGihfTOguOVdkyyXJ4aJTKaJSkBSLURZd2kn2/zFbekYHCiA2\no15ig7xueJEmney4tKeUTu0nbw1NF4NaJdP7REvh3b3FEqCXP/3pT+d9Tc/GZZddJv1TQ8TzWj9x\n/C1b1t3bye8K+LM6+l1XQJCY2FhZsGCBZGR6lzo5sXSPSiWapPaiMQXIpEmTftLF8+PHjx8/p/Ab\nVud+L/kNq5+P2+2WZ555RiIjI73uSjqdaNUa6ZXUWYZkZMuA9r0lPChUDAaDVFVVnVZ++LBhYgsI\nlnCzxTdPsJmCJDLQJinJKT+qDR6PR1544QWJjo4WQCwhIfLQQw+ddcLv8Xjkjjvu8P7Yq9H49trM\nmTNHRET+9a9/Sc8ePQQQjUYjV1xxhZSUlPz0QfoBunbpIgnBIXJPr2wJ0eslxmyWO3r1kAf7Zcsf\ne3aX6KBASWvf/owul48++qioFK+rlU6l8hklwI92p/wpfPrpp9Kpo3d/vF6vl2uvvVYqKyt/dHm3\n2y0JcXHSK9wm7w3r6zOsbspMFUDu6ZUm0UEB0r9f3zOWv/3228Wk08qcnh3kkxHZsnBoloyLixRF\nUSQ3N1dERBwOh4SHhUrX8BD55wU95bMLs2Xu8G4SH2yWDhle97mHe6X5jKovLuwrPSMsPvfG2Oho\neeGFF8447k6nU1LatZN2gSZZMz7bZ1S9NaizADJ//nwRESkoKJAJE8aLSqUSQAYOGCCbNm3y1bNi\nxQrR6XSiOuHup1aQ+ECDbLiqt6y7spekhBh9bn+ZwQFyRVKE7/p+8cUXEhfjveeDDToBJLVdO7nh\nhhtOuA6qfG6ED3SLl+LJfeTYVX3k7cFpolIQ5YRbIeA7x7DkEBmeHCL9+2afz+1wTl599VVRFGRU\nZohoTrgF/hrvJUXklMTh/zKKonQHthEUjmIMhIYqpLGWBQsWcO9993Hs2DHEFAgBASi1VahcLm64\n4Qb++Mc/kpGR8Vs3348fP37+a9m+fTs9evQA6CEi238o/++Fk++lbdu20b1799+6Ob8ZLS0tfPzx\nxz5FtsmTJxMeHv7DBb/DzJkzmT17NpGWMELMwdibGiipKiMqJJz0qGQAnC4n3xZu5/XXX+eKK67g\nn//8J6tWraK6upqDBw9yoLAQg1pHYkgUKkWhqO44Dc5munTtwo4dPyzNPHv2bGbOnEmiJYzIgGCq\nmhs4WFPOVVddxT/mzTtruby8PFasWIFGo+HCCy8kISGBNWvWMHToUMJNAaRaQml2ucitKicyNoad\nu3b51Ox+ST7//HPGjh2LzWCkoqmRKZ06EhsU6Pv+UG0d83P2sWXLltMkyVPatSOksZGsqEgO1Nah\nValIt1qYm5vHpVOm8Morr/jy1tfX88EHH1BQUEBqaiqXX365LzbV+bBs2TImTJhAujWYrHAb1Y4W\nviqpIDU9nU1btvxgAOOTzJ8/n8mTJ9PBGkKPUAtHG5tYXVJO70grt3dvz4aSSl7cUcChQ4dOc0+1\nhAQzxGJmSqrXXc3hdrO6tIK38osZNnIk8+fPZ926dYwfP56/D+lCQtCpwNjrS6qYvSWfoUOGsG7t\nGkbHhRFnNvJNSRU5VXayw0IYFhXKlqo6Vh6r4PHHH+ehhx5qc/5p06Yxb+5cUCAp0MSYuHCqW1r5\n+HAZwbZQ7v/znxk9ejSDBg5A3dzAFe3D0KtVLC6s5EhTK5s2b6FDhw6MGjmS9Wu+4aruEbSzGflX\nfhVfFtQwpl0oG47V4nC5ub59NDEmAx8XV7C5wo4C3Hjzzbz66qu0tLSwZMkSDh48SFpaGuPGjUOt\nVjN40CA2fLseq15NgEbN2gld27jh3bqugJUldhxOJ3EBOqZnRiEovJFXxpHGFoYMG8HnK1ee971x\nJoqLi2mf0g6LUcWfhkRR1+xm9hfH4Bd+L/3uDCslrhOKIcBrVZbuJ7NdHF9/9RUPP/ww7733Hg2N\njYjHg0ZvAI8HV6uT2bNn8+CDD/7WXfDjx4+f/0r8htWZ8RtW3r1NQ4YMIT8/H5MxgBanA41Gy0cf\nfciIESNQq9WoVN74VC6XC0VRUJ/Yi+J2uxERGhoaiIyMJDzIRlLUKYnyoxWlHCwtIjulOwatHhFh\nfeFW7poxg3feeccXUFir1tDqdqFSVAyJ74Ze452QuzxuVhfvpFd2FmvXrj1nP062IcYQRNeoU3tC\nCqvK2FFWRGFhIe3atfvR4zJ8+HB2b9rM+JRMVCcmorWOZj7M3cXrb7zB9ddf/6PrOh++/PJLbv/j\n7ezL3cdtPbsTrNf7vqtqaubvO3ayatUqhg0b1qZcqM1GZ5OJofFxbY6/lbOP7DFjmD9/PgC7du1i\nxLBhVFVXYzMFUNXUiM1q5V9ffkmXLl3Oq609unWjqfgwt3dJ843Robp6ntqWw+LFi5k4ceKPrmvJ\nkiXcdeedHDp0CKtBx9D4CCYkR6NRqdhfbefRDTns3LmTLl26ICK0trai1WrRaDRMS41nXHwUh+2N\nPLYjlxpnK6F6HdXOVoKCg7njzjt59NFHWTymFwHfCWC8v6aeO9fsZf369Xz++ee89cYblFdW4nG5\nmBAfzh2Zp+6XV/KK+LzCTklZGWazGREhPz+f9PR0jGoVLW4PerUKh9uDSgG3QLTZRHmTA61Wi9vl\nYtkfumDRaxGg1ePh0uU5DLtwIjfceCMDBgzgxYvaMzTVKyO/u6SeqR/so9UjRBh1lDU5CTdomds/\nk6RAA1eszqHIraayutr3fH6fTZs20adPH14bnspHBZU0tXj454i2IRFmby9i3oEq9OJm6x+6Eqjz\njk9Ni4vuH25n1IV/YPHixT/6Op6N2tpaunTpTMnRI+x/qCtJNgPbjzTS85k98Au/l36XAYLBG7xP\nAqzs3bOHgIAAXnnlFWbOnAmALi4VTXJnNCld0IRG89BDD/Htt9/+xi3248ePHz9+/re4+eabKS46\nQlpMR9KiOpIZ2xUNGsaPH49Op8NsNjNx4kQGDRqETqfDYDAwduxYLrjgAvR6PXq9nlGjRtHS0kK4\nJbRN3Sc/25sbAKior6LV5eLTTz+ltqoagE4xyQxJ6441IIgwU7DPqALQqNREBlgpOxHM91zk5OTQ\n2NhIQkjbNsSHhCIibNy48bzGZcOGDSQGWXwGA0CIwUhYYNCvOh8ZNmwYX3/zNRqNht3lFW2+211R\ngUGvP+OPAAMHDSKnpoZWj8d3rKKpmWK7nQEDBgDerSeXXnIJ+hYn92V04Z7UDtyX0QV9i5PLLr2U\n8/mhv7W1le07d9IjrO0YJQUHEm4OYMOGDefV7wkTJvD5ypUIMCE5hotTY9GcMBjWHK3AZrEQExPD\nnXfeSUhwMHq9nm5dupCW1p7PjpZz76bd3LlpN7XOVvqHW3m+VyfezO5KBB7eeO01AFYVtx3PVcUV\nhAQH0a1bNx577DGOlZYyb948PMB1qW1jmA2LslHf2Mi2bdu4++67sYaEkJ6ejlqBMIOOT0d246ux\nvUgNMhFl1LN4UBc+GdiJJUO60N6kQ4Xw1OZDZC/YTNb7m/jTN/l0thlZv24tGzduJECvZXCKN9aY\n2yPcvbSAtBATX4/vxlfju7FybBfMOg33bC1EASbEhVJrt59TBGLDhg0YNGpGJ1jJigxiY7mdonqH\n7/umVjfLjtSiMxgZE2f1GVUAFr2GEbEWykpKzus6no3777+fkqNHyUoIJMlm+OECP4PfpyrgCcTV\ngk6vR6fTAfDmW2+hCrKiDjoR+E1R0ITHojTWMW/ePPr27fsbttaPHz9+/Pj536G6upply5YRa0vA\npPe6tjW1NNLY0kCA0UxocCjOVicff/wJIATpgvCIhxUrVqDT6Ii1RKNSFPbs3AOAw9lCgOGUq5Wj\nxTuJq2uqp67JTqm9gsGDB/PNN99g0hoID7QQfcIQ0qm1NDqavd4s35ksOjytRP+AW6KIUFBQAECD\n04HFeMpNr9HZAniDy54PVouVeoejzTGPeGh0Os+7rvMlPDycGTNm8Je//IUah4O4wECK7HZyKip5\n+OGHzxjsd+bMmfRdsYI39ubQLczruri1ooLk5GSuvvpqADZv3kx+QQE3Jqdj0XlXwiw6PWMiYng9\nP48tW7bQu3fvH9VGjUZDoNlMlaOlzXGHy019y48bIxFh06ZNrFy5Er1ez6RJk5g6dSrvzJtHcX0j\nScFmdlXUsqWsmueff55LJk1k07ffMjoxjMjkUL4tOUJueS0AaUFmbklPpLrFyfIjx5m5M5e/9OjA\n9clx3L0th7Fjx/LGZ59xuL6J9iFmtlXUsb6kiueeew6j0ehr08l2lza3kPqd1a2yZm8/Zz74IFs2\nbeLiuFDi4218VVbF5ko72yvtZISYybc38VT3VOJPqPuF6nXc0yGBq9btZVt5PdOzYjGoFT7MqWDr\ncTsZGZFYrVaanS4qG1sJN+vYesROid3JX4enEm70zo/jzAb+1CWO6WvzKaxv5khjCzZLyDkNK5vN\nhsPl5niTk8vTw5i3r4wLV+5lSvtIzFo18w9UUu2Cjh3bU3Q0/7TyRU2tOOpqmTVrFqNGjSIrK+sn\nqfm53W7efWcewUY1h6sdFJQ38/GeGg5WOH648E/gd7diJR6Xd4NZUx3UlBJoNvvcCqqrq1E0ujb5\nFUVB1Bpqamp+i+b68ePHjx8//1Wc3MT9Q9TV1SEiaDV6X/7S6iOYDAGkx2cQFhJOdGgMgaZAr8tf\nawONrY0AhAXaiLFEERUSSceYDFSKikNlxTS1NANeI+tgWTE6nY6jNaU0q1q59957efjhhwGvkWLU\nnnJzi7GEUu9s4kBtCR7xICIcsZdzvKGa66677qx9aG5uZvTo0Vx99dWoVSp2lxVjd3jb0NTaws7j\nxURHRZ3mOvdDXHf9dRTWVlFUW+11PXO72XismMYWB9dcc8151fVj+e51mzNnDs899xx2g5EVBw7S\nbA7kb3/721lD0HTr1o3Va9bQISuLz4uK2VhRyaQrrmTtunU+qfKT8yirTt+m7Ekjq7q6+ke3VVEU\npk6bxurSCnKrvfdRs8vFBwWHafV4mDx58jnLu1wurrzySrKzs3n2ySd57OGHSU1NJTk5mVmPPUau\nU8Wbew7SEBzGvHnz6NixI9+sXsOMHu2YnBnHsIQwHuqTSrfwYAxqFU/0SGdUTDiXJ8XwcNf2HGxo\nYmNFDWEGb9+mTJnC7CeeYI9TzYu7DlJltvH2229z1113tWnX0KFDiYmK4sW8YipOGI1FDc28eaCE\njh0yWbt+PY90SmJ6WjzjYsN4tkcaA8JDeC3vKLXOVgAijW3HN+rE55t6xnBttygu7xzJO5MysRg0\nmAMDmThxIgEBJmZ9cYiaplbsDhcAMQFt64kxeT+vLqvlg6IKrp12+nPx3ef+oosuIjgwkPvWH6bV\nLSwe34FOoQE8u/sIj24rol3vfqxZt47bbr+dtSW1vJ1XhssjtHo8vJJTwvZyOwfz83nxqSfJzs7m\nissvx+VynfvGOANOp5OmZgdqFRyrayX9iV08/vlR/rmj6ocL/xR+SSWMn5OAW4FDQDOwEeh1jrz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0NVNQyNDmZy+wRmdU7m2W5p9I/0zJ3r4sJ5rUtbXuycSo8QP948eJL1+cVoFHh4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nAw88wMI8N+1Skz8i6EIwcEkF4ezmrKqchywWi3HJxRfx37nzqJViJhjRCIQ0FEWhTnZt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\nZNM0TKy6CdDLl3T12n4226q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- "text/plain": [
- "<matplotlib.figure.Figure at 0x7f37f802c750>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "pl.figure(2,(10,5))\n",
- "\n",
- "pl.subplot(1,2,1)\n",
- "pl.scatter(xs[:,0],xs[:,2],c=xs)\n",
- "pl.axis([0,1,0,1])\n",
- "pl.xlabel('Red')\n",
- "pl.ylabel('Blue')\n",
- "pl.title('Image 1')\n",
- "\n",
- "pl.subplot(1,2,2)\n",
- "#pl.imshow(I2)\n",
- "pl.scatter(xt[:,0],xt[:,2],c=xt)\n",
- "pl.axis([0,1,0,1])\n",
- "pl.xlabel('Red')\n",
- "pl.ylabel('Blue')\n",
- "pl.title('Image 2')\n",
- "\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Domain adaptation between images color spaces"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "# LP problem\n",
- "da_emd=ot.da.OTDA() # init class\n",
- "da_emd.fit(xs,xt) # fit distributions\n",
- "\n",
- "\n",
- "# sinkhorn regularization\n",
- "lambd=1e-1\n",
- "da_entrop=ot.da.OTDA_sinkhorn()\n",
- "da_entrop.fit(xs,xt,reg=lambd)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Image adaptation with out of sample extension as in [6]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "X1t=da_emd.predict(X1)\n",
- "X2t=da_emd.predict(X2,-1)\n",
- "\n",
- "\n",
- "X1te=da_entrop.predict(X1)\n",
- "X2te=da_entrop.predict(X2,-1)\n",
- "\n",
- "\n",
- "def minmax(I):\n",
- " return np.minimum(np.maximum(I,0),1)\n",
- "\n",
- "I1t=minmax(mat2im(X1t,I1.shape))\n",
- "I2t=minmax(mat2im(X2t,I2.shape))\n",
- "\n",
- "I1te=minmax(mat2im(X1te,I1.shape))\n",
- "I2te=minmax(mat2im(X2te,I2.shape))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Plot all adapted images"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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qpBQkrQNdwURS3vH3PqEqSydRaND5u5k2PuWXmN8qfz4pK7N3hTgPfFaXxP+Q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\nhbEAZhnvD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P5nEfnWC58ZROTPichjEbkRkf9BRF594TNvi8j/KiJ3IvKxiPyXIvIPvRdR\nL5oVLQsNSlWdeqXr4Ikaoi1C7xPRSVoGWMQrFTYpL8pvVUIlT6M7trnhGcXWz6gsnwGwrKSgXM22\nqty181l01UoBctp5UkqklNhIYmQthssh7pA0MSenfQ2mWGrR4ZWbWlWZzLMbmWgSl57PRsVYL9dt\n320AJqUUUVN5TqK6ZZgasFrkqU/+LOeOPxLj37I7p8/qc+JgM8e5U07L70/P2X6mmpZ7bz/n5Pqn\n51cNcYo2Lxr84xfu1VSigS6x0ckP/fFzelYpW9wvGl3MdT2XGbUqkJiqAOm5lzcjjMnXlCUlNXni\nqBmy5OumT4ktmS15GYv2bBoiHn3fL/+WnDyqq0pWff6+s5Ly+iyn4PjF8yrQJWE3ZHpdM1W9JAbS\ncu2uU3KXnwPZpVFS/zGPH6cdUVXO5MiGI4bSSYeKcjsohy7HOFQGnbjvWerCblPilTrGWPoG/Mo4\n8s64Z07KnJTHXc+kvtH0VjAxzqfCdzcXVOvpqvCk3/GDdMFZKhzngb+/O0MyPJID7+slH+ctx3lg\nlyZu+o7HeUutiQHoZued73TiDbnhDbnhW/NT/tbwkMEKuzo7GATSlPjBcMGv7c55MBce645REzep\nZ4rwwjPdciDxyCZesT0PypFHduBaex7UAw/qAcF4qd6zs8IunJdnOnBpM4PNZK38vuPnHHKmm13l\nD4wtExvzIOGm+ucu7chd7uitsGPish7YyMTATFeU+87/lC5qSyX+aJtvY8B4bT6g4hnqjVV6GZZs\nbawLRL3p7SQdJk4squJS+rN01E1FpUel54xEb5lX7MiDckTNmIJyvJlhN8Gujhy1Y1bhadcxSeaq\n7OkiUn7BgZKMMzuylZFLOfLSPPLgOPO14zUvHw+8a3dcTDMHMi/JnmdsYc5A4qZ27iKe2JBU4V63\nTLZhkuhHJ8JlvuZM7+gxLmtl29/yshVetsImnn/X3bDrbtDulp6JTahWeW2lB0MGE4YINuXqMs/b\nKuTO6S/N+ckoVv1PiT9d0MZznXnADefcLve+EdyG4MGkbh7J0xTM5i+/DQHfI1UNxOt+tdlcOfVF\natiKEITAHea87Dfu0Gag06hVDrBQtTUZtpgDY4bISngNdwNLyz3B0k+p1fs4bpAF2KmuGRjR9U/H\n6vwjkCMwncSd9IqvFySohCfXrSLM+HpI6FLb0mhaC4qIe5ATMKMtYB1+xKIseBJYbL9DYpzbKeW5\nU8eYBhg1WQGLeFB3kSCPoGaKn2v4hsu5my+CZwzXn7P8vAEdXZ7Jx1bkebpcA4ntMyznl4USuz6B\nX6QJRkmAN2n+nbDQ5JYVGgPtdcvJwfcLdkTNg/5VKlCXsRRLC1BUS3RVGSx70/p2D5b8D57565r/\n0NZ7sKFymwNrVD4fuwVEWdQxmQe7tdZF5EvFyFLp1UVhTn2RHrfZGfVgXokG0b9LduS3e/x2M0x/\nHPivgJ+P7/7nwP8hIj9pZvv4zJ8F/iXgXwOeAX8O+B/ju4Qx+t+AD4F/FvgK8BeAEfhPfquLi7nx\nSSoYhWIdSSpZV6lKtGCkaMBmdFHL4ynZoEEhqHq2R6uDm0WdUJoKmNPoevGGXJM61SGlhElFK4yY\nO7/m1DCplTH4ol2kMNcMzUrtalSqqn7dklz+28zrIKriGRqELmlQ+xwwFvPsQGpOuxU6SdEwDsgu\nKLGIMNAMoW+4SZSjFc/I4VGaHphoFC/iZfLMnInfS5OItCD5theqKFRzCWqpFs17V5F88zQJSYyx\nChsR9jphVUhJIyviG0tKLergst8qiTkUzKABswTWoiAsfFgzQxaKYV2ybCJ+X2kNKLnhJcYZ8zoo\n8+wdyDJeeU3iYzgFC9bGr0stUVcp1RuYdhLqfyQ6hEmLR4vNkHjbFIL2uVIs/bwVZKXlLUvyFKCG\n07rYV3XnZlHWEaFmJZ+kuT1HZFCMIYdDnSqJEudWpNQlC2pxvmQ+Z1YLKaKdaqcVa//Yx4/NjliL\nmqXEA3nGR/KQR+WeV8oRrcUdAxn59f4B19ox6g1vjMLVNPM0b3k0HfgkpLvfkA+9qH264El3xlU5\nMKnSUXiHJ5COTHbJ1493dDLzYbpcJLjVbulsw9/maqG/vFEPnM1H/sbuIcaW7xyfodUj/T/IZ5zb\nxKtlT7JEtYKSeNp3vDPd8t3tBT853vJMR3767ilf9Dv2s6unvTId+TjteNXuUKk8yT2KcZcytznB\nJDxkz6UkEOUuK89kx6v14BZMEvs6cJuUt8Y73rZb3u/POWPk0AnPZMvbdc/nvdJbQc3pzO/YM57k\ngdteOT9WUk1oKny43TFb4u1yjaF80m35gjPeLndcjBPf357x7vFuWeN3ecMkxqNyzw/0nO/Mn/Lz\nZy8jc8euGO8VF8OwF5pzfG26ZpSOxo4vJGbpEFHup3OKfkGuLqGerSLMzNJx3SfOy8GzuRJyKFb5\nfXef0Qt88/C5BxxQNkw8rHuebuBRvUYSvFz3TGpclXuqHEgqnDPxzDJn6ioiVnteSd7rq5piaeRI\noZPMtsxM3QTThr7CbYINlZpHdtkpiEkndDq6A60GugcxNoCVvDa49sUGGNLdQM1ozZilxT4kaQ2y\nJ8wUkUoVYagZktdCiVRK7Vz4x2YGg53ekbp/BBsiGctCGkdK30UdxZfXhgBIVHEkEaoaVtSd79Tq\na3zcrURWAa9fbhmZwFOIIwev8YgsRWvmSfglEtn+HI56MVmK362e1CAHwI1Wn4vyawMKi4/EygpZ\npM1D4KeJGJlV+niOtmcmmqCR/7s1oW2+SAMnyZNA8dzPR+UbdbQBkImVOqfhbM8LWFru1u12ZEV8\nnFqaKwASLH2MlNjXbW3E6p9VDG/7MoePNKnLJ3n9bnJ625K18axKsqaYFzcQ1DrRtNDyG1XPsWDb\ne/3zp0IJaXktT3ytNs6soFXjF1Xa85xUP5ktrU1SNapG7soAqf4MAV5rXDiRKEGAtGUB2AIuhbre\nM60swv3tNtANaC9gF1ZKb8zXc74I4ePC8pn2TFToxcGbpkbD9Nk7tSOc2hEUS5DmQuk0gOnv2I78\nto7fFmAysz9z+m8R+XeBT4E/CPyciFwC/z7wb5rZX47P/HvA3xGRP2xmfw34F4BvA3/KzB4DvyQi\n/ynwX4jIf2a2eMg/dFSFqh21Fjr1jaaKLc57O7qIviiZSYPeEMutLbS2EJryy2mkJp51UYHrQj6x\nRexHUzpVeixoZsIGZa9OdTAzZjG2lpgS1Fpc7rvO7oQHOl4dYTd8WRJT8s1Lg641YZ6OjKM57XOt\nIfldmYutBhU3eBl1WhY49z/us+LAoKmyLOdt2Ski6pGdVtfGRkQY1PmjNSQzJcBBH/VGKSk9M2Ou\nJItyUfP+QSMgOXFfJx7tn5Bzx5P+oRe4Zq8Ns+rPVtwmOG/X2gvRqG0uKtF6B7ghjRooGiBlkZb3\nZrwx93YCrmJTaNmplmE7Ve2Dk9Q9Kw97lLpsNODFoOJ6qp7absDs5FA5oQ+YS703wNVgWWnZxpiW\nF+/pFBS1Q4JS+FxEKZojpph/MwfRXRISs0uuipLFM261uuKiBY+6lsrMSX+Gk2iXqv2O6TQ/Tjsy\n5Zmxm7mt5zxMt9xZZpuObOeOuqwh4935CbNUKBs+3HY8mp/xJJ2x1T0vTd74NeFy18WUZHUx3mJG\nIiE1cZt6iigvF1eAu9GB8zrz//bv8Z36jK+NRw6amEh89fiEXx0e8dOHZ4wqfDJ0fOf2ns+7gR8A\n78z3fCYbNjLRV3WqCJmshSsc3Lw5T3xvc8m70w0pdTwtA5/2wpPe662OZF6fPA75iRrv2T1bm/lg\nc8Ynace3DjdIJ7w9H3h9PPAbg1P/3i53lAKjGjc2cEiJ1yfjFuGsuON/yFtutbDpjpjBZ7qlmyvJ\nhA6j6w58a5oZRfgsb9gU6Gzm81T52njDTe5QEj9z+IgnfYLpEoCvlMeMHdxnIF/yc/1X+Ofvvss5\n1/zq8BqlbMgXtzAp0/SAhHHM9zyxV7jLynvHW5LVpSZiYyO/f/6Mz7uei2PTRDVM3IJelsqddpxZ\n1KNY5aMLn+s3b0c2zK5YitKVQifCy5P3lDMdMKtkmZnFhRZG+WEbsk8zd7gYA8CD3GpmPTs+WceS\nWmvvcd0wj5uIyk6kkphUYRrYBNifNIEKvTgwq0WRuYfhHiyDlGBgTFhxZUHtb+CwRWqj7ClZCiYT\n2+pNmfflDMkzO4xNuqXIFpMNMo6UYaTYJVlvmKQnMz5vQ8IZExF0mr0J8HH8LSzEP/z4sfsihF0V\noyve0KS1I3FTHIFFaRUiuogQWGQFFvbEYt+buNO6jy2pGvE62I6QFC9uhwsOwrIGrc1clGAWV2l1\nSr5Tu2ZpTcubOpy74dW89rnR77w5aSjTBlfKzPcnY3WIW+al9YHUACmuqEY4/gG0YtycRs8S2EhI\nyHHbgqz0BNj5QPjnRWTx27Ke0PXa+1VZ6GKKkFL1e4sebSaVzqIXJcoohcvIEN7VYVFStqVRajSf\nVc/gLM55kyU3V4AyW+mV/vieU2xhTz0BRSc6ZKeYyt8TbeCz+TarH9EAaDuaHZlUVkCGA51WcmCE\nT/GCTxNPFr4IC3WfWKf+f80/DeBottTZ0f6G5VrrlNqSNfT5tRVoAdSooUoevPcdtzq90nyOnAUU\ndMLn7EiMlwg6e5ZK5h9te4LfaQ3TFT7kT+LffzDO+ZfaB8zsV0TkfeCPAn8Nj+T8UhiodvxF4L8G\nfh/wi//Aq4nzu1NydOnKIclRdYkU7PISyVLz0anXfGjQw1pjz8lcNS3jWYVWb1PjlfOomzAWj7BL\npAiaYom3WvHMx9HqEg3IEtkLUwglNOIlnXHjRXKq12jVIyzJXw616GOQ1Ju3NhEFeZ42lyEiNYKm\nUFEzV/+bMSbWKISxpjk9E1T83Ckz2eKdM2j27JOuDnzShFlBdQVYgmeHSoSspKWgqzHlRLay7PXV\nnOJ4drzj22fGt17b8R/9K3+Usj/jD/23fwPLha1t+JkHE4cj/Mmffo9f/JXv8W//iZ/gf/qFv8//\n/mH12h/zeAgWDmmMmS6ACmjRGWk0QL/nTsSfM+rPMuqAU9fvNmDijDnvW9U2LK3GXI12qdYS14zI\n7LV+SO48C3piNFxsIVVZqAHW6pIir34q9OD9rmCowpwbYTquK7pIpTfLK0GXcMCtC7fbzxvzKC4B\nPHQ+F2IOxmegTrHuo+ZBqgZwACpoFJyXJnuvvyf1Bz8yO1K10lflIfdIhnfmx1AHNB2YykAlk2Rm\nNtdiVpl5OO/py46v2hcgZ1hXKNwics7PD6/y1XHPVbnjJm8xYFvgoAM1P+BBZJQ+yZeclxEFjpL4\n9vQMEa8RmYBtmXl/8xL3GbqaeGna8wPdMvVeK5JEKJr5vNuCVb5+uOdad5yXA5/JjoejMZLZ2cwD\nCk/yhs/6gWt6fvJwwzuHkWPumOtMDj74N+c7VKCrhTMRfnJ+xvd2O759/4z/b3fF513P1/ee0bjT\njk4rUhOXcuBsmnimHW9MR/722UMSlbMy8s3DPb+8ueCt8UAW4zonHllBUkEtsU+ezR0qDAhPOnfa\nO6sMpYIYnw+ZjR64DzdrtIQee97kC352/JtcifLWv6zMB+Gv/5UNl8M12/05f7B+n/Fwzavf/Db3\n7/86b7wDH3/wOX9FX/EWiLYlPELEjJenERSOhFJheAICXCyiLd4f7a27ie9vdtz2hQ/0Ed+YnvD9\ns453b6ZFDtnP7Q7jxlxNdRbBdOBsPnIvOWpZoDJSzWVUepm5r0K2RK9wkB4qDHHmjPcf6QpOn7UE\n5hHYTah7Nrehkz3k2Wlz+43z+tIExwG2B2S/9RDv7h40BDMOPge2vUMPZ/EqZsRgb3l5by7tFrpz\nqsyo3VLsgrHf0FdF7Y5RPfPaVcV0fN6GmLdCWGzIizJvv/PjR+qLCEHnQhBJEUXP7jSHrW/iB61x\nLTiVulRDpNX1FlTSIhTRsjyNwuTtIlyMB/EWCE7XigxDDKPFf0S8bMD3l/h9AxpBU/N90u+jU/fU\n1bzvXj7ZTjHfpzwDBa1fYgteNp8ixWdZxsNrslQ8kDuvWMjHbvmeRQNTXfop+mM4U2OKLIY3PV0D\npO7nrb6Iy4P7N9fAob+3LmLUAod+b4PMvJEmXn0w81M/sWfcn/EXfqFiOtEz8O5uZt73vPt64ZMn\nwre+Vvn+R5VfehqeX9uWw440XKEotFo1a+Hb8FnEa5hbw982Z4u0+XMD1H5nMc+RXQu2TMGDm20d\nNsmFhGELo8rCF0kLuGplCgnvcUf4Ed6zK9bjaUbJoEqlP+lsKyfrSSII/1yFmZwSUBvIXX0cLyM3\n+qgzdWVIzw5WFCyFvSBYTinsiPjPseftyJdF9EF8Zf5Z4OfM7Jfjx68Do5k9e+Hjn8Tv2mc++U1+\n3373DzRSrcbDr8+ShXRHN1EiYiKhpJaiktaqA6GpzGxTFz2R/GWbiUWkujQJ1RcyQC0DUfHzJFbQ\nVWpZ+KZJQo0M6FEOlIji+L1YO2draokDo1WNz5+jechZs1Peal0yOqf0rPZ36zSdqoOkHBWYY0Qm\nF2KZGQc1hpQ5loJI9JnCa6JcrOFEka9FBdu4xzW9P4E/12mNUVZlElfZa0aqqfz9B3/sq/wbf+wh\nj7YPEI7c2pE//RD+zyeVq/OZ//Bf/A7fOleurfJn3n2Hx+M1//o/dcVf/OgxVYRsKxhuh2fq1qzR\nTES6QrHwRcU8aODxhwsG1/E8uYIE3aVWuj4xl/XzLkIRG2OEPpzQV587T0eOLFeMW/HsFLomu9tG\nlOPvisvfq7mcfQPlPs4S3czbmvHvTFqXaM+LJiSlGtEhN1JWPWLmEp9R+lvCFNTRKZ8zjAk2lr3R\npxL9hoQDv3vHj9qOJLbLXHf7jlmyC3MkwaznPvVsTNG5FcN2dPSYVSYugGuGcoFyRi6VnypPuckD\ngnEmI/uSybmwsQDpMafnHBml82bC6g7Woctc1ENQqCo7O3LLGU+6ymbKfPt4za/2F7w2zjzijjOb\neLPesYmInGBc5y0fDxveHYOFNLvKniG8s9+jcsfjzY6nonxlnEgqbKcRMA6aqaIkCTETm3hnf+BB\nnflD+8dUhA+2nmG6nN3YJoVfGS756ftr/u7wgJIS39zfAHCfMiULfTiM3TxhOZPE6GpFg2xTEYZk\nTFLpSmFrHWOCLN7YResW3fdcdC69bvMG60b+5Fc25D880uk71MMdevmUYRK3vAAAIABJREFUf3X+\nPv9L91V+In3Ke/90T/faiJVfgDf2zPMz3rkQxl99QJEtUjwqOUqipzIiKBWslVk79XGbCo/Gtso1\nQI6ic2JbjM3ZHTILer9FTuBSs48bm0Jq2pUlN3Jkk+5BNtxGE97BvE4qmzHUFkSvDEyoPh81HeqA\nVaOkiiXIc4nAyhp2XoRdygaK0+ysF6ecR9c2PewiUq/YcYc2gkHYkHJwMGUii5PVnimriwx5re4W\nrEeYUJmYHSaQIqA22d4VQWfhad7ysFT/rE6LDVkQxO/C8ePwRfSkTkTavmSAVAdAfmNLnsEBT3JW\ng8BsxQOnNMZD0PLwgJwLS/ne3aho0DJW4VDH55tSXPs++D5RW8APY2wKbea/K9ZoV/6zAuF8rvMi\nshLBWmaoLkDg5GJ28s+WlIgsVbi7zC3Ad7K/juJ73hyB4na65mSHbx5/B70+vBmRBgxkycwuTU3x\nOMGs4dg36BLA6mffLrz21p6h6zxgUQ586wz+zj5z1c38gW/MPOoP3Jnx9kPjUJVvvg6/dO3tbFON\nWdVFLy5YTAEug9jXMmxtxTThjzX31Py35/fs3xQCRDS9NQeuSzPQE4izoGZIlhYfrNFzk+SllMA0\n6sWWrKefY2FgNZAJ1BSiDPVEgCOC5FWcteIf9u+u7XDg1J0CSFqRLFiJWjwsxCiaf2c0MXsxF+FJ\ns1B0Rkghv776Ii8ygn6vj99JhunPA98BfvYf4bPPv4n/4OO3/MzTv/zfIcPZCZ6F7bf+OGff+dMY\nMNTiKepQnqvim3yOtshKZhaP4CfUu443fC5EjZE3bsvqxfW+wFx5zNO71Wt21FX2iiqaXAkJnNcO\nhPSkZ5pSgJk5jMi0AJJI7cZ/m2BeJWS3JeqaolFgib48XmwHqCJVlrR/y6AUq95gthKFvrHYRRjw\nRbzJobqWE3MpdCl701116XVPx8syzm5snW6Wgoud1LM5nXkqVRW6oogac50h9cxVOKPyZ37/q1x1\nZ3R9xqry4OGWP//v/AH+71/8Po+uzrjqK/lix4N5pr+65I1x5Nl05L/557b8W3/pIzopEbVRakmI\nerQhtWiTQL+kgFZjgrmAwYDL3g7xknWt2DT+TlYpYtS6GgJBoLqKkasHzQGuYSqy1IFZndcNiuCA\nxy3M1DBMQPQNSNqyhs599uvFhnliQFsESk4MQ4lHnMzXV1H/bmdr7VOh9aZSVAqpEk16Cd58XXo9\nrPEpQGZMOpcPz+7sffHd/4eb7/7V8JsiSjTe/1av6W/3+JHakf/+b/0im26zOIsm8DNvv8kfeett\nUPv/qXu3WOuy7L7rN8acc629z+37vrpXpbvdtttuX+KOYjtOSIgSkYAsExIgEClEICF4IIp4iHjg\n8gISEk+IBxR4AgkBL1jhogASChKCBxyHJlfLwXGatmN3d1VXdVV9l3PO3nutOefgYYy59qlKbKcd\nU61a6qrq7zv77L32WnONOcb4XwavyHss9RENDU2gJ3e7LhQqh3TlPa7kScdVP3FRj974qCf2nKDC\nmo1khRMzmSNPpx1v3b/gnemGt47PuS+F0jOld25Lx2zmFycfOPHF41O6KIjxueOB213hRisTK4Y7\nsv3C/jEvcaSZ8mY9cWEHp5QooHBnM9+cJj67LjTg+5c7KsrbOnNBJ+fGkmbW1Lkx46qtWDK0Gi9S\n5mu7me9db3kmM59rC5d2oDXlFy8e8cXlGUk6P7p8gFjjdj/xNS75vuWeBeGtesecKg2YMLQKx5zZ\nryvFjA+mmRvzNbTLJyZZeXT0pHrSE6fTHrm4xVZllT3vXl7zhft3kN9eSIfXSd/zOn2p9Odf4Hv/\n6F/l3/j5v0LL16TrhuVH9KTIm5fk1dGVP/XswJ99/v38vhdfQ9KRuuuc7l5m3jsYIccrunSExmfs\nDlnZspaJhZNlRIzP9xc8L4nPHCt3aeb71g+3xBDgsr/gTi+wLkxWWTQ2/m58i0fsrHHR7xERSlpZ\n+hVFO10z0hbIyqFN7PQQzmKBGOiKrs6koBl3ktmFm1VX87Xc3QFr/A5mQe01p9rJmRhlkUA1cQ2v\nZaOrkWre3MFMfVSqiZCpXMjCYpdeCPQ9MwtLK1scvW+ZC+lIOmLtEuGI5Mw19/yv77zgf3v7/djn\nGohwt/6abLffzPGJ5yL/7S98hV1OWzIOxo+9+To/9tbroEbpTi3f6NWawWK/ornJAvjsK+tnoYC4\nRnc0uGRLwX1PcfTK2SzSCZdXlyX0aKxVGwlynFpQ6A2n/42iSxXaaAJ+TAqykUG3YsiR7jEOZaTT\nIpEnP0j6RyHQ8cQ+J9x8LQ1bfMDE02Lz9NjU9bE9kLUmnNk/jL6TfeSuDDkFhjd9xJkciCFZSM3P\nr+GNq47rZt563fc5d2CbYA//6JdWfvs3T+S9myEdZtfSyD6zX93b+I997z0//dWbrQh0pDdQIIEU\nyA7GR5E6HO8aSFOORq+KQVjxy3huAbGGCUED9AbTyEW6WDgk1mjuu6YtRUPbbDjLtShmYneXsYoY\nlS+rPGQhxaeIbQX5FkfiO4xCdhxjgH01dWRUPRdLD/IVR0ih98jZRNAGNaikoham0P56bU6BFDVM\nwmw++4r8y994ly9/490zvQ841N/SOPIbHr+pgklE/hzwU8DvN7NvPPjRO8AkIjcf6+y8xrlz8w7w\nuz72lq/Hfz/e7fnI8eQP/qtMr32Bh2EKkU1fJMkLCFGvU5Po5qShymZP7ftKQOU4stJqI4dds+AI\nkwEpZv8MZzEJ7rANCDq5f30eznPIyHRp3btJTqVLMdjWdT8p3Lc8UXWb8FGhJ3FtVu0tbL+9gNpL\ndp68CAllMmWRTta0DXCN+wPdjSgGzC0aGhRg8KfNjMViNlN1xKxLOK48gNzHTB9RH7YaMYmsfvm9\nqFRQn3qEKH/md3+Rd955h//pqx/y3/1z38c0K7MuviFkLxBvXrrgJ3/iBzi1hba6fbO1RlHj8mrH\nFU9o+Snf9Re/ytO8g+hGKG684d05QcwpZPogqPoDn+jtHPQ1bNKTKqn7gzYe+kGfSCnmFw2edtDT\nUooByWZUa1i43tmm83Lu8wgqqoO9a+SkwW/3o1voJiTOrZ8D5uamKA+0Vr0jWTc7eb+Fvs7SQLnG\nfUYgFS+QLdZqyizdNnMUTOMcfYaKhAhbtDCQ+mpuDfroC7+XJ9/7+7DeQmzbuX/vq/zK//jv/XqP\n6j/Q8Z2II3/iS1/i849eoqQ7v8+tQCvISTBtdN2dN/Fu9OaakpM7gbMjurGtk00RFRbEjVtWX1tr\n9HxbhZYNlR2pG6aZt5YXpCbUMlE4kbsxmRepn13DXl4dlWkiWHL7d2s+G+hlPYLteLWfKDYhtpAM\nZvPNaI0NcC+dV+zEL00XiMILybyrO37k7hmHBAd2XPUDT46NZ1NiT+W2u619pvIqmY7yXXaHxAwn\n1cZn2507Rkqji9uAv5P2vNnvOYqwR3lxoeRTpzUl547k7s5LGUqr7PvC7VR4fFq4qga4o+DioYNF\nIWvhD//g69hXfo4vH17wT//oB9zvP0dZPKmXnZJ2HdITxK7QZkh5Bq3R+5FMxtIlK9/N8fd8yJ/6\n6b/GN/NjtBmHu0tOGfT+AlDWWZhrx9S4aEskJGEOYkqRyhoYzk1bvTlXO5ccHOWTKwB2kWDUlDZt\nkuGjBZJ5wimakd5Yeub9fMFv67dIa+4UxcJKdrOdGvGqd3rCdZ7RX99LD4a3J9FdQdeI++KzwHy2\nWiNUIrGHJTeYGHQm9eagNBd+P6Q5ITMmFbobJd32S3o3puxr9NhmVBprGA5dqiAURA6YrEBjYU+i\n8Yfeepl/7M3XUDtuMeQXnt7xp//y//trPab/wMd3Khf54z/4BT736Gaz4fZt33wvMhglxabLEW+0\n9kGjV2gdhLY5zLo7Wqd3SMNPIAoUw+/k0Lmm0cY0PjJ7iAeoxpazB4LpjAIgcp+EbDKCkRjb9mVi\n/8PjUB+uid33zEJYnAdVLotrjn3gs21oT9Lh1noeuO4fNParQbGzzZ56DKF3dcuDfY1xrQf9XR5c\nm0j8tZ81ReoF6R98Y+H2mPgbHwp/4ofvkJLJ6eTumRot68vKk88UKp28Ni8KayNlgRnM9ly8vvDK\nVxfuoxGyMTbGmUUx42aCUcltf7ZRp/irNb5V/Iz4Xv7G8Z1GdRPxSNWwJmgyiGKt0WDINpy3x3gT\nQb0g03i2xff0Huskxfgdgk3kpxH5i9mmTZPeHIQYaE5vTpUb8UKcJaWB+D3MRUw994lbi+Azq8ZY\nJ6ket7RHLhJJpUR+LWY08XX0u956jd/zxqtObYw48stPn/Mf/F8/xyd1fNsFUwSoPwb8ATP7lY/9\n+K/gz80fAv77eP33A58DfiZe85eAf0dEXnnAHf4ngGfA3+LXOZIld/uQoBxYCNHCFrmbkpJss44E\n77jWPiyhbRs82vFCRLpvCj2dUQFJ4qgUBPKUokhokP1mZq+S0HBHc+jcHDbFIHi5jeGs52PXRIwp\nhs22oD50zeh4kvCFnwx3fes+sFXMyR8iaYOgl+huVOvOCRfX2xBdn/QgKLoQ3QPQ1JUatLWcBGkd\nQsOSRDcTAbfO7j7Xp1aKFnL2kW1ZfGaPiZKTMpnxwoRZlH/lB6758VcWXvvu1/m3fuq7kdUwGj3N\nUSgS3ZDC7rIzLUIrvhSvri6o64qJcH94zhMy7yVPHrKCWMekBTIUFLZuAVP7w5tEWHqD7sWsxloR\nI8wZejzwtl3vnpTU1Qsx9SQC/H6qJujVr29K3pWNbpIPwk7bpgCjMBtFaadiFHwzWXDtVDUfi9rE\naDkQLHHr3xoi3OGWpPls1T72YXS4yPg/KW3yygjiEezo583OvCs1FRwhjU3N6YWjwGJDwzLizxZG\nNSJYK0nH/Pff/PGdiiOlJvKqLP2SogsynWABKxV6hrb3DmfQosQ6qcOhJC8h+oL3RoW7QIQu6oly\ngm9cPEEt8Xj9gLlXdlqhQ03CRUsc8yVX9QV9gqt+oHTlsBdyM3Kvm2GMYKReOckFqu7eJKbczwIU\ncnrBle3pBvclc7E2nuWX2bd7Rq/azNi3xufbCbWFKVW07XlvehzJWWVlx9v7ldQLh+kIPVMts2sH\n9tWoFPbV1/RJr8GMy7ZwTIWXT0eeF19Pv22Fi7ZSKZgkLqogmrikubORVZ70O2qYVKgW3ji+oHQf\nNHtXLinpyM3B+KvXb/DFw4E/On+d69vnpB9deO1VsJrY11+mTm9i6+wNAwT0C0yfW9Bf/RX68WUA\nevoh+ulX6FOm8DfJt3u+cnOJ3l9wlV+4mcGSkKSYKZcrnjCmhnXXM2U6p/0t6+kGQ8jWXORtUHMh\n1cqd7GiSIv7D8zKhNVPkRM9Ca/78ZQ0L+96oKvSpMi3Cd/UPXOOUjT4fSMfEmlPw9T0B1+7NribG\ntDgD4Kgd7YYlIXmYo2ZfpyJBT9cVi4aKICR1U4uhofRnqtAzH4shI5+1oK1nkIr1QTtf6SjzfI+a\nMa3CmvweW26hxXGSHl1ozKBCZsVauMklIev0bUaMv/f4TuYial7g+ID4gQ9FR108UU881IR40dSi\n2WkISaPpt6XMQatOEeZ9S3/QCPT7bxq5dfZkOgGo+tBPeJCLsFVSw8wgdij86elnGngUbK6BZUu8\nPaV5QHGPPaMRCfEoXuL7Rx0P2HkcUvzX0RI/dx3GEzgjxnXQ9pEhpiPBHs3D0RRt3elt41zGWBc2\n5pBwFGfA/N5Xjzx5UnljXvjBHwRbFFrFSkghbBQzCsXIzeiTozF5Kt70RrB6RFrieVa0Dt2W5z8q\n57LOEJKMPdefxxYVrcS1MWO7NqMIGSidp6feYBkoz0Zj7EODFhofJ4b678S9T6Z0dcp2p2+5iIS+\nqidITcA6TaOAUqH05oXx1paJBksYgUnkJPSG5MKo5Yjz7faxXMTONz/c6H29bOMKegANstHLZTQA\n6OfcLD4onbve0MU9C5Ki6ZMdJfttfZqI/KfAnwT+KHAnIqMb88zMjmb2XET+c+A/EpEPgRfAfwz8\nn2b25XjtX8SD0X8lIv8m8Cbw7wN/zsxWfp1D0tngwIx4WI1FYd+VJUPtjZkcFKdGEXXomgeIgY0g\nhHf8cDh1RqjZucmttZjHhFfmKtQ+EJxGMjj2FsNdbesqjKnY3YiqPgaFgc9X6p2sjhC4CYCwDM3N\n6KIEctN6J5XEYL76a3zxewx1+9fsNjPuxrPh8EI1FwybZCypc/gTtDY6QC5M7jnDCFrWt05V6p3s\nTAJKKSRpmG2mp6R2otcdp0uhLJ0/YB/yH/5LX2IqhWf3K6VkJulcv3rB8fbIEI/C4B3jtEL1zUXT\ngLj9+l/uJ37leM9P/ws/wp/86a/4g6y6ISpmrnlwmoOidEzcpCKLbyxnWkNmscZuK45H5wtqbWQt\nNGtecDdHJJHRwatuciG4c2Dcv3EUcbpm11EU+wWq1imxedXY9FLMfJgCuSgi1Fq9AIpsxYv7CDbm\nCOXSG1PKMZDOf5Y7rHru6nmQsXgPX79oZw5B52QFEWGR5hq2CO6eCCWqNXdWiufEnRYbGWGX3GXJ\n4ZeP8Q2+zeM7GUeSGSWaBie7RFshdeGXHj/i+58/490ZprZS2sSxdHZ2YrcK1htNMkcpUMIgJFXM\nYMm+sb28PmNfM/eTUFUoS+NYoiilkfWeb+nLGPDq+k3UZp73G16yZ9ylC1bxJFLaPT3BpPd0mxGZ\nuGkfsugFs648t1e4kfcxc3MQzXBiR5Yjd/JyXGSnoSzpwFUrVBxFuJSn3PEYIbHngDbjXieu+8rl\neqCbsZSRxCVu7Yo36rt8M73hs8NqZZaZlgySoSw8rpVn+VHcW3hleR8R4ZDh+hTxUKAW4dFp4U4L\nSVfuk3BdbznazAf5CUWf8ae/9WW+558/sNZMvgPTJ0zrC/jic/p7jX6Y0dSxmph2J5bjBKrcv/1D\n5Nf+LvX974IK5fWKLNCmJ7zY7/ln/hH4C//Hib5MTLlxKgv0jKQDve5QMtQC4vpBaUK+u8H9MTxZ\neDFdorLwyuGOo8yYKl2O6FSpFaZlT88LuSt1d0sq90jLSCt0qlt0zw3pUPfbowrAo3t1x6vpQFqU\nNRs1uy7z0V3CFJ5fdy5OXiSJJlhcV5tNqdIxCR9AqZF4CUZDLFExGicymaqNYoVuxiTGafTDI4YM\narCq7wWixmX5EIB5cVv2Y2pUuWKdhMQHqAjzceY4V7plknSSPKfUiTWfyOuMSmGd3Qzioev5b+b4\njuci4kl/itg7OvMtdUpPPgyZTgn2Q4fQFgcsw7nAGP9HZaTc3pJpypZLnInT3pztjPfygmbFkQRn\nhIX5USyw7VJvxVDomLpG4zlsnR/Qyj9StERCvDm9bgVVzMSJ72H4Z5q4+YB/ftDi7OzKZ0k8F8ls\nFHjifU28zByIm88OGddGIo7qA/MELwSzNHpLrEVIHX5YDvzE7zxR6UjVKEiMdCUunhrVqBmWErQ2\nYIuQJml8P7zwmJR2qPzxH4H/4a9d+HM7uI2wAUE+cHa0ph1xUghzhEAXMarI1rwfS0LFaNZQcQnG\n+I7njC5yEUtBzRv0vHN+m6KYdiON7tuASVis+yrqBpZd34hCqs5ayuKjY7xkAaxFsSbeLIrEdK2V\nEmNmVLMbXpnQxTYTi4G++RpqiGbQTvIOzWZmVjFa5CDa3QFZjM1h1ESQrvG+vsZLGs+GO2J/kse3\nW579a/hz8b9/7O//ZeC/jP//Z/GGw58HZuB/Af7MeKGZdRH5I7gTzc8Ad8B/Afy7v+Gny3iAcY4/\nXv3POEI5mRdAzdz/XW04n6VNrCjxUHzEPkCEokodAQVPpCUq7DhvzqZlwiJCFsfNNTis/kPHtwbV\nq6AubOw+MylnL+BkS/qD7mdscwSIrkFKadvItuG347PMyMk1Wc4v/ntd14ZBhUhibeGM11x3Jfim\nmCyxdOftbi58EpTEFOdhXiwQAW9A6K1ccMHK68uH/IV/8cfp6TM8uXmMmXF95fS9eSpYdVt1SQnp\nce3lvEmLSKBpffuuZsaLuwM3s7EnaAiavKujrjVy0w02FayqW/v22CSSanRIvO+WxDzRG5049eBc\nSqF3LwpHsLYIxj6VW5DuMVTjuj08LDjSglCG3amNOU2OGlk/ozh9FDYW9xZHGpdwgNw6wAHn+6Tv\nCBqi0I2W/fdTuOAMy2RBWHsjpxydG0fZeu8cNLnFfWxeSeTcoQmdU2tenrtJcayHGDCx1eL5o9//\nN3F8x+LIZlbCynFSppopZrx5d2RhxyuHhSTGB7MXwEfbMVtjTWlLXJKwDZH2Tcyvz2TG/a65S2E3\nmnY0TVuXDutc44nnKU3cZ7jOzzn1zMw9RUIbFu3lY7qmkXlkH7LvIOmOxXbcpA+cerzFEC9wVYVL\neX/7pkeueRzDZ1d2XOtTDnbJFR+eY4gqKh+iGM/yJTu59bTECkLnOj1joXCjT3nWH1NT4cnpOfdT\nIrP6c5k7mcqlPGftM8vk16P2ifvJ5xnt1xKJvFDkxCnNYMaz+RGvrk/57ff/D7/vH2+wP9Lu3/LE\n42qB1mh6Q//qNWlZSC9fklLFUmU9TUy7ZXtWSW8yPfoaMh+AHTodsH7HzfQ2er0jtc8y6cqpZXa5\ncpTE1OG0jY0QJjnxnHmzAhbVjRt12dZAxC68cQKozYieKDlhFVKfkf0z8unS3UgtUYsysZCqIkdF\nO/S+/8i6bHJLFyMvE8U6eTVsMZ5fuc0uCa7ulaZOubvfV3JTcnU9a+kTUDnkRmpKTx5j5tW/SBsN\nvRYNMYyqCyITsq6u2Q26oK8XYZoUaY2UXsRgzCteZKexFyaUhcSJxgU0OCVY2DPLgiFUuYH8zGNI\n2B2X6qgs+R9ae/AdzUVkrI9oAIIjIcUdkSgGBDPF8Fk+MNgOkTwPXlIs34AUXLcTmh4Ccd5m/sRz\nO0yAMGjizJpR7QznsG2bCTOHZKF3tmGEJRsdfKADGtrsh7kI8MDpdzSd46Rl7GHOlhi/MYq1cbik\noSPiTWNTIfU+MDX/3gK1e9LvMAycYbIwJ9qMqsf19z81yczauMkL/9QPHSE3+i4j5o2/3oPuZc1N\nDCJmmwjSGjxERRyG9YaGOvujL0ZOsNc1XiKbFbpFbtCjOh3ls3VHf31txH2P7yV2drqDsB63YKsQ\nOUegVLa9SrYC1ZvbW1273SfXUMWMIs1RvNp5/qSoAw09chxj424aHdWMtub6JhvSB6IgGkWhnA3M\nrNNpaMro6rPJpBSsNaR3WkpIzmjDNV+4RmlpzY2GxNHa1B/kVebsqCGv66lDC5px1LobpvsPn4t8\nW8e3O4fpN2wtm9kJ+Nfjn1/rNb8K/JFv57PBHxmNhH3oQPx2egfE6Y8+eVh7p6qwiDvUDGpDar4B\niakPLxOJGxU0M4tlmQSouHdCaItwZzszT+5dTQ+ttwf3zYuYKQS2rTe6KGsxpkC6LOCtprLRKLK5\nz00bMj8TRFyc78+2bINd/Vokh8GtgyREkyNSCEPR7tBmCP+ls6bQMYkbTPTeqeomDU1cA2Zdafjg\nsI3/Sjzg4kxhdyoRynLiP/nJz3GRG6cCj+fr7QGe5pj/3I3jsZJS4nh/z/7iwrs52a24SeLzf9xz\n0xNaG4VUIvVGq3CRjFUhtM5YTh7ItJNEqaIszecbtd78WYr75SFoZYdyxOmULYpLDVtekTHnyQOX\nF7wa7kB9EL19EFsUIE4/Cf65+Jyn4Z4IxMwMOwdJVbb5V93XU1dhUUdC5yj+6ogb6oF5S8oNiiaQ\nlSyFHgjmcOQKljRzcQS20WNdKS76NrJ68EZc4TC0Th2jN9fRiQhTIK3JBGKDG+6D/MZh4Nc9vpNx\n5HYSkq3M0hCbWDKs2e/1osZLBoecma3z6Fj51sXMN6/c2KQ0I5txfTxxXwqnnKm4O2ZpvqmXDqsQ\nm0Emh7h9mfwr707GYfYk5s4ec80HqHb66pa+uTXW4jHk8fIUgFWUluCYlIt2cAF4xJCFzERjzwdM\nS0bSidPkjYDL/sKNacSYuQdRLuT2fP0exBAjM+cjR7tiZweSrvHZE4mFUhs39gFP5yfcTpkijbn6\nXKYlC5kjS1ckVwxlkUyRBZonaae5ogZ3u+wT43ulq/Ko3fPPvvkMrjsq1/Q6+d7fFfvs5/w8v3pg\nmr5OswvKi7/N6e53Ur8h7H/8yOnnL5h/6FfZ/8SJ9v4F6bMNxDj87Peze/LzPkh0SWBHnshzjnpB\nCvvyuzKxu++kVMl0nu8mntoj9rbwNDva97ieWBJMzVHCJ/3Es1wolljD2mtqg5DvCVG+92JonTt2\n2pMXYFZawZkAKsj+BXJ09oD1HcfZ57ldro0X+8b10bfmR3eJg6onNhksdy4R9qcO3dysp3c+vDzy\n6C5x1Zwu+3Ty+zedQJORWnR9VZk1IaxkvJgnu+dmryePUSm7pbm5OFvtCqvhSCTGlD+kWqKJslhh\nkhVLnZ46YjcsNvk+rC9Y7YJH1V3D7rNyUX0Iexqd+d/k8R3PRSw6/GHaYIHUDOZCik55woukblC7\nN8ck2As60DwVF+6P6ac4vXIrQGIYkkTvCkC70EOvM2i8KPQWxgye7QftauQDvq+5fXhUUxFHekto\n6l6gqc9O84Tes36hb0WUu8w+uBYx8W9DIQgdkrEl3Ig5rZPuCEsypMq2fxpOVxQ1bI2cLAXlMSht\n+uBDLfZFulPzkjb+ye87obJis+AjYKIZq5BSYHQ1aOY1ELuxh7bIAzhrh4kCoY/v3Cq9CrM4Y2SY\nqrhxh4X1usfbat4o7TETJWHUvgFXlOQW8YGnRd0yru/D/8pWqI4/juK6q7MyO8Oyga3IEgWrrn0G\nB8NG03Z8z6GLpo/PStTmJ5mtxzqM9TEasnaeC+n3o5FJ9NpcU4kgq+udZcqUttAtR/6kSF2R5vdV\nCH2UcKZ4gg+ClrblIsXUl9Wonfugffrt+ySPT5YA+A95FE2Qk4ux7yhJAAAgAElEQVTRQsA/dBhw\ntucW8WGkEoFkEsWSi9ha5HvJgg4ZiELqg6KlDEeaARtuUSrMH5J1JLlJrpm57bi4vfjUDWVMX4a8\nva9sQsYtgGlG8UW/akDt4hbaPYLvcH4b06/HkSMQNQsqmnWfS4Rss4mGC4qIb1hFlUkisHZHoDQ6\nYoZTtEwbexLH0fkJBMjFf/7ZkjygLfMlH9yvvPm5ayYpPD8eeTnvKaVs3YLaqlPSat0KCX9bL5Zk\nnmjLgoh3QWqtKELJvjSf3xd+9XTiHje50CTbZrUkLwhohmpnVsV6Y4z3Tr2yy0LrZxOPYWAxZptY\nGoLJcX09NCQRHwiMsdMxLDjodhL3PFo/eXwfOXdJtrlO8efUIyBIIIc66BE+5NTv/YPAyLlYGmYQ\nY22rJpYoMGmOAqXNI1i3gOuTsGPTw4OoO/mcc42BwuUoElMZouWBfEo4ZQldztziT+vxZD1x9/gJ\nd2ZMA50R30xr8uvYyVy3E8/nKy5r9USvKdoqVeHpbqKmxK52limxAKsqF9WQbkwiHIuyoJQc12vY\nG1KhFS7biZyf0VoBbYgmltxYS+HyBDONwxQuay0hbfHY1BSacNF88GcrBeuJ0uF+30mtUEUp1dHU\nasb16vf/fvpoDNFxTtm8g9cqLR2YanczDMD2K/QZk4aUlSt7wXVrnIriZg0T2RpFGnmzYjeeLI2n\nV5lSnRvvxhGJuXoiv5SJ2TrvlRtON5f0z71Pnr7FdLqAtMB+BmJAcP4Gfb6HJ9/Cnr5O/caM6AGo\nTD9wj7yyo75XSK/8PLTvxX75a1y88XN03VFvE3Z5z+n567xdHvHSsvg97ok3Tne8fXnBk6OBdUrv\nzFbpXXgUduHX/Zaq4oVW90JroLaTGTu5xyKpOEXyufr0F3atcsRYi/AkgsVdvfR4uxzZpcp9uwRV\nLpsjBJaEq2OOotiTatt5Mnd1ryiZRbrPTTMNerownxKqnRp7y+VdNITCUEAH2h4JqkriOJzqmsez\nUsZe6nuZdUNprFb9nuB7Z7dpa20722PntMUOs7xgqjN3RWhWuF7dCEHFeOy5me9ln+4wEpbcZ9E8\nRPMMGztnvDCKw0CisoM6gd9vWITTs8xifZ2p96bmTYd4VPtouwubQ64itCbudDjeRiJPicaf/8oD\nNDpQ02E5bSEw8gS8eKuxp03IT2ebW9g+dvM2A6WUHK0RwZq/91mdpWEdbliCUn3gtqfchFtsoD65\nb4jXjhjGvA1jjKbmQL5wxs1KoS7P2T9WWk2UVJ2uNjiInBG31ARJ8Z0fOPireIM1eqNhfOR6+Zoa\nVjOVzkmE3L3RPPb9GqgIzQeY+3Dgvkk/NIqkwGAYGh6JfFAGdYoHiJI5rU9VaQEGjRD+EW2cspkk\npHidUw0dUQue0Hldjq6wNWclZRhj7hMaJhHjmtn5OmNh/OWUHo8j4uNWJCG9u74ujbjiBY+2Git9\nYlhBq0KyFlRFv0XDhCJ36JJc3hJW5qjrMX20T5yDfPJx5FNVMDWxbZIzIagf6aDI2YFEsW1WkMJm\nL55EWXJnNh8K65OfI5iI5zTZXFfSELdnHhAxI4cwF52ZjRErHvAiKNWAYJN5waLJpxVP6JZsE12h\nbBacTaf5eGjr1DARSCh9kL1NEW1YuC91azGHQ0OoRxQ/jkx1HbMT3CbOGw3ePWgIkjrSzeFOYm4B\nyhS0toLzs1cdHFrbLoSLDRt7Ff7rv/l1/u3XPucdnHVhysLLZXJKUmu0mII+50zJJa6fbwyGIacF\nWYcNtnGqK5ezd2hTSlxeZ37H1RXfM/1dvtkzbRu+7hTEgiNiIj6kjiT0GBYsOUPvHhzN3cay9eCd\nDxw6AsL2xweQtzintottKNJ4zdgnzdz9ioE0xdltYtpIUmxgofHaRveOozlXF9xNS2NArqqSmwfG\n2hzpQ92qtVmKjqYX7oI+gM5tO5fCuauc8HWR0kRr7XxeYVWPQC5pexY2IbOaF1VrJWXfqj5hFPy3\n9LjNE69K4arecjddYNYoVlkkYSo8LzNdhA9lz5qMXDOlN47FIGyEVzEuK5gWTIw5kpiaMyuuK3q0\nNF6UiW6VXassYWpySN5TPGlGe/Op5vjmmyPxdnChUDock1EUjqrMbVA/jEUyqVc3h1HvEJplVBem\n3qlhapLMOJR4gsPadcQQZaUljWLOjVByF5aU0dKiuaOQKqWuSBPmvrCkmW5wKoLQtlwmKSypsG/w\nfO+x86IZz+YUyUHjFDqtq7ow1cpeG1/521/hi9cnlsefYbJfousVp6//CHw9UV7/O8ghI3tB3vk8\nh+ffQ/nsgX78JvLuLbzxLvbuj9N/9T2Wt3+M6Yf/b9LUWJYvUd8rTNdfx+yGsr/mh3ifb+TXoB0Q\nOlWUufucpFPyCH7dXnhSpw3pGtQh4UIONMkYmV2vlN4heV+04iYRO/UhxSdxKjVN0d0tZb2ghzFR\nKj4vq/fMvRUkLSAxnDsaUW6AJUyr36fLVZDuNPPBpMCEU4Jjh0sRriIBfr6DyyMcJyEl43p1rdJS\nV0+E1PUMNRohS+pMVRxh//vEEMQplaiiXSit0dLEXFeqOmKyqDdSvFm4QzCuVmNYC4gaVRKJlZRd\nr/px2+VP2+Ep6DnPcEaEMWZ8jrpmuCOqeYIePbJgPwg5SqOmD2ZpRdKbIwnu6jRuL3yjAIl8wY0n\n/PlX4NwLs83IQXD3i+Qe1BQ5MyZG/qTDrc8MtRZ7QKVKCvA0WvsAXVHtWxwBfL200fCzDQUZIzZ0\n0NdGDaPngcvK0H2HXgmhieu4zKC0jpsnnBuSg5ZnsU9PZvzc1/f86PWRnFfW1d83zz4ewlrfBuiK\nD0x07U23YTjnDdVoRI6mLCFRSBjr3ph74pXSuF3CNEyEMbw2idGG6x7hEAgMdbqO6zgQLBtrKIql\nKKw3IM3GBM1A2YadvETVDRu7RGLdfAQFBEBDK8VGDBkW52q+37cwiBCV84y0jjN+Yj07I3PouwU0\nYQbVctjd21lf/veJIynmURKOoUjzuW69M1wh3Cnav8yWj0VDADwXcTv+FrnIJx9HPlUFk4puF9K1\nLBIP3BkdYvw5CqjtgltU8wJqyirGhbk4E3xRJNWwDR8cXJfJDU7wdm/UE2XbHojzMSryrrDrymrd\ntTbilAsPgGzwPUAZttLxToVOEw36XASGcCk6u9rYVjBZnNvQXJn68zQC8Ojy+BudCwJ/EM7fTQON\nktDLrGLkMHmIXwYgi7CfJl6bjTf2N/zC2wd+5K3MfkosDY7Lyhjgeqr1PJW6d1rtaMmQFa2GVQ/U\nvXsBN4UJx7g2u+KPyH/2J77AT/43X3e9jypqQZfrnWkqbr87RLDD9p1AlPAA20WYemIRcx0ZZyTo\n47qk3js5ZlU91FyN9xzXY+hYHv7eQyRtoEOWHnRsBp0j0K4x+2QSpys0U6xZUPM6ZQLro6vicLcX\n4G47nB5wx0fR7X+xQW0RNPWj10XOeqsx/Pjsxmfb+dZayfF64BOfrv1beVgqXNdbWoKLdscx7ViD\nKmkCy1TIrTK3hsmMibEm4aodvVOO8jxnZms8z8Krh8Zt8SKg2IrpxMSJTmLXD5x0706SLX3sRAwk\nk0w4pMK+nTXmbiJjXtwt97xInWyFmjpzayySOKZCVuGFXqDWeVy9kNkFtaRo5072LCRumifp97qn\nyJF5Wy/GrV5iolzabcS3HOvMY0iJ826afF0FYuGJijFVcbMCcVRssczEAeuFmZXbuXBTK7pJVvz8\n5rxykxZezgsXzLS3C7vlXe5f/S4u2j37N/4GQke00y8bHG7oTUkvvUt5fuB0+G30z7/E8Wd/mPTG\nrzCXBXvjl0nveRHc7ibmL9wiz26Rl74Hne750k8Zf+d/Tsyyo6SV1gqXzZ/fnBO5hWkM3s18mOiJ\nGUUWjlrY98639jM3hwXBu77ddMt0dhEnq8F0dCP6te+D6ur3ooULpyPD/SPx59iV3Wj5EzFEzjGk\nWjiGhQC+G9RAMq9rYyoFaSDVONBIdKZdAkvUdfUYIh5b9+I6hSTGKqct8bqofp/uNPz0xZtyNeyF\nV1FK75w0kWtnwqIQ8Jfbx2JI6iuadaskRD/hTOe3+FAIRgdBV/evqw8KhfgfICO/9T/L+T085o41\nxPYiiQRa4nU9yaZ9jo8+n4tEztl5kKSwdd/N3JioG0iSKODs4UugS9TFMiooIHKRMC4Yf6d17J3j\n/eNbGjEGwffvgQK4dXnsO8b5S8SHS7CENnaGhR5oUC2EzVF4HCOnSRizwM1sXF8Ubp83rm4qRR3p\nse5UckXcpTE5SpF7LMVwFxYDn+aLF1IfO08BJlXQxh/+0i1//q8+CaRrNFf9dTls8MapPtTKexHK\nRvMr5vR7Mb9JY1zNR5AgnA2kGhRCGW/04HrGNfJc9EG21h6agD3IRXSwlrxKFPPnUe2MHmZtkIZh\niRs8iChp6pilMVuDAFp9GG13eYS32+N7jeKJQRsNje9oMuD5z7gu0YU+5yIPUCQzZ0w4MyoukXyy\nceRTVTBlVe+adOgqpEAVRvclh8X2uOg5KWmI02IhFxTUB8mmpLRAIyz4pOMB2mYWZX80azzQqY8q\nPh602Ci2jrwE6pCiIBlFUPCBh8aqYltXycQ/e7WAyznbwWK+ceXkW+Si4nS8LuEOZ6gk13RJJ+Gw\najGn+eUuoU3yxblmo4QlKsk/p8WTn7GA8r1jIt3PcTIX4OXorovApRivzJVdmrg/VZ7dr7x3e+T1\nmz2H1ZiLMofDXu7KIs0H48r5uhg+Iyt1YekV6W68cDwenfLXGvW48OzuxJQzv3t3x19broMjHsYT\n+EOeojOrLYSrqrTqtsfD4cfpBcaEIEHtoxmW3UwCNsCJnNNGI5TmQabDpnPa6JsRu0bhkVLa6CyA\n67PUi87hbmc2Clb/zNLFBypbNASSvyY3F/v6+u60FDS5CG7AVpzlVLbCTw269bDG96J6tb4VRau4\nU6IFxdT1BmzzwtQqptERQtwYgHMR+hHDlE/Zsa+NF2VP6kLXiooPUhY9sWuVSRJHU066Y7I7uu2Z\n6kqz/RZX5iosSdj3Ezold5a0YHObsegcReuOKawPmxlP5z2C8eR4oEVr7DbPIx/dOrQJv/9L6qyB\n9br5R2KxjAjcrI1VE5ph11a6wuN+5GmeQUNr2NpHujlXdgSDD9MFWTrX64GbtsSid2em2zLzqB64\nDCT37XLBy6c7t0mWhhq8Xy64WpZtDV52H+S62BQF3eyU2WlCqnCXMo/aibuU2afKvRUm6eyaMtsd\nafeEtH6Tdkjoz7/g7rsnlsePeVKfsuw/xAzSmpHrD5jtlnq6Yv4dX8b4CcrL3yDzlNP6iDm9TzvO\n2H7HxeO/Qn33Env0HvKthbXtkWnh9x9/gb9++Xnoxr6s1K4c7YKWKrkXTlPj+rSwppmcOrqsLLpn\n7gcOcslsBxDj1eXoyDWuv6w5oTaGa/uRVOi6kpoiutJ74tD2qCmznGgopQkn2THZSrWE5MpOwJrS\ni8f+dR3UTC9KzzFEY4A3TB13Zsu+pyU6fRKmtTFJZDVW0YKb3bST+3gZ2+Ddi55D0iFYaCQvpfhW\n1ztNj1jz+HZKeGKZvFF1JKFZKHXlPhVu+sKzPHPdKiOGiMkZGdjsxT6dx/AFGGWtxj8jqXVF8mhh\nsQ07ZSTiwSoZjVwdPxotWNve0Ju5468t8kcZBUqcz9D2CpvOd4AFw8F35JZpg1NCd+tbxKbDkSJu\nGhdNwrSdWSTp2e9dbZGLSHzWsKnGkZsUaZfC5lcx8l/BjS1KNBDjW3gj2PDh6QyKoyN3PXKnHhqW\nhiBBxb/SlbJUrDX6orzA2HcjtRr0eZ9dpt3Q7Nph1/ieNVQdQ7ubqFQLM6ZmrLhJQpeOLX7hvjAd\n+OV1z7Ba98IiGhnnHD+YHWP+1nmtiP/wjCriPxwGHYy1hM/kalGMSx8N1igu5Ww/bsJmlW54cfzg\n3R3L1GF6JOflqEM9dM5FkESq0KSj2oKh43FEbOQiQEvnIn4AFkHdHwViH2tdiX3Sv6yIf1YzDWaP\nExZzipyOyJFMQ1P+IBf5DsWRT1XBNLpSnpT6Rc3b4JjgBauQQ3DXMCSnbRDa0D2BL8wm54RzJI5D\nK/LwyN05xFWj6B8akbBSRM6IiLSYvzOCyIPFNJxGFA9OYwjd1rnvtiEbjl505GPa1qJe07XtQQ/h\noEjYnJ4Pjb/rGKcCF02ZrNNUosrHNzE9c2J9UwPi2lh8T8MLsJ0pZo1b8WJJS2e323O3Qifx9ecn\n0vN7XrvecXOxIydhTgKt09fKnL3zmNTpLqpKXStrr0zq3e1pmuIEGuvdLS9W4y/9rXf58rJjzrYV\nLb13ShJW86sg1mPArH1kkO82BPZBF/ds1tDo0jc92hToSavO63fL7Rjc2aujK83XYjAgffNTXyM9\nzktI0RmO9WZuqtAlAtTYBMGtUFvMwOreOU4pQ2qBPOLUUXXtQWtnFvm4b701ppwdatcW3UKDCDyu\nyfJrk3Mm56AIRMAZ6JyLmJ2eM2gmCbYicazBT+shYZk9pc79tONUjbIT7OTuXccOH+wueel4T58v\nOFahpkvEjL04vVMqoMKy7rHJxc0+oVzpWUhLpU3elNAogm7qkWzKC1FygVMUTK/UA/eq1KLU4Dpe\nrytM4ZI0w63uANjZQskr95KZ504NylZOQlNhNTBRSj/5nDg1zFZO6aM3bM+RySqCclLBTHliJ+4p\nTLaQFE7dUbPJFjQrJxPe2z3izdMdj5cTz6fCo+6omFlmTcopupmPu9utm8KagwI8+dDuD/KeV9o9\nqVbuy4nXdaax0Kbi1NRL0HcW5m+8Q339yCl9lqv6gtPuBdkSKwfy3ui/+CpqXyPvFk7yiPl4y/qZ\nr1N4A2uNRV9G9hk9Vsgfclpu4K83fvbxGzw6rai4ZjMD19l4rjNtJ9Q2Y6Uh3TithZIFtUbNxZ3g\nZM/OfGDtQfaAsEt39FT51nxNbo1HgeilFVJLIOLDinXiWu4jhgjFjBqFKAZFKjW6z3M6IjUDslFc\nfIhopyXQ1ekvI97fFWXfOqUJyaMZ1MnjU1nR3sm2AzG0QeNyy1N7pDDWVkr2wc3J3seSF0r0FIZH\nlaaPMWtMlkEyu8bW+OlNuM2F1BJNMtm6DwgW/76hfPA1u7mwfVoP2f7jRZPTtvqWyJ0Pt4se9tIP\nkIb4/a0Rt21PZx3TRzJezoluC4R3iN5l0P22pBsw29zbhq0ABIpkbhgxZhS2SOwd7ThrrFQESZ6L\naP/oyWTtPluKB/pmGfvsWQv08DqZQVVh3hL7M81Qoro708rsnIsEAiZhWtQZlHM40Hye5KRYSpHc\nZ05rQ9fGVCqpCKJK6+oNjtpJ2XOw4Yws4kNVrbrbrY8KGbMsDT01ll54/334yjozadsGEfvzazTx\n2W502wqnka8ADwrjj1ya8/cVHxJsBFoFtCg+gc2h1V8v0CVaz+c2pohT1zqD5Rft6bEs8IbuyF9M\nziYsa/Zr7VTKTNHqhY50n8Uk5qYi4sNtup7VVNva70YJoxodzR1GM9ALox5FpsY69hli51xkFKH+\nzFTPn8XOg6I3JIxP9PhUFUyoICUqzVFxg4eq4D56qh3FhJ2pDokohgL2zOLJeQmuf8c+opFScb63\nBSrhTm59QzZISm8OQZ6kMw+qHD2saN0trUSi3umQ3GvecNSnPAirZuYJLxE4kC3wJfN5OxmB3jGU\nPKWtKDCGFSnbMDL/zoAIBUfaLBSn5cFg1SHEHNpHwXmsonKeMdV7oF5eJGTPAfhwqbxxUXhxWFiW\nhbteuFsWvudxwo1pE4+uPCmt3Ts8p9rYFWPSxFzSVlzOqZDmQsoZKwkpmfm0Mu/23PcX/MzXnnM5\nF7AY+msgyfv40nsMrNMzxUziweze03lozW7mcysyrh/BoBDudHYeSjsg4y5gvZOjoLNA2QZ8rtmD\neSPhW4/6+nhwLtCRHFb0ZlivG3VwNkOSW8/mWUg9UCpLjryZzyXw6Dt4GYF4qt97ioQtqc8Ls0ET\n6X0Lml7o+MDhbviMpRD+981uxrUsowPkaJWBuFYOvLP3aT1OcgGzImvlqi6YNXoVjvkGyysgvMQR\nKTukCzpXdsPAo2ZMFuoUaF4WTr0z90SbV7oJh65cTkpHSWth3cc9mJRVEqV3rO0ostBT5iCZSeED\nm3mS/ClcUjRyloqlxA1u+HBqRpsKUxiYpCmzb4s/u+IdxAupIMoUYueN9muNW0tcJOWwNiqZfJmx\nU0XUuNN5o5XcamIXsWfGNTllFV7lnuNuQvrKdc20qSF1osiJq9xYBid+nRAUS419IPT3YeBwdSwc\necRF/1age5XHFwLLFVJfcOpv0ewF++un6HsX7NI7PH358yivMR/fjYzTsOun9Fqw+0fMVweYF9I3\nPo998X3a+iOkl18gs7J87TOUvJJ+6e/ytbcPvJJuMXFL84XZE1atmBT2rdJnZekz87qQcqX0lWou\nQgaYy8qp7jGD+ymxXypHu2BXDzyujbtdptULj69y8GggsCShW6NbCepVUL3NKdBL8QI5tUxPK4LS\no8G3oQ5SPTbX7GJ9qyyqzNa44eQxQAy7uGW6fS1iiFJZ6C1RJy/kWC/9v7oiVshyR6ozZEP6LTIt\n9GOGaj7ge1o86VkLGddptWml5RlrBos7G9bIunruHGuml04nkRffFyuJvXiR3frHKKqfusNCOxiz\n9wAGdQ04F1R+78b0Qs9NAmOJ/SpLGAREPmOjsfogo94QRXxYqnRPXhF/xi0S9FWH9se2fcL3itGg\nG4iEetEEuMb1wTcz2wwePp6LqHnjOMW+YLjxSI89UfCmbUsxmDa+w0BahO7FkjpS4TFHNpQqwTZb\niMF0gTB78teISJgBeJNSTTiacK2VVo3bvtD7ntqEy10FJmarpNk2do6ghEGuO8VmT4YV14y1aE6i\n5rbYa8XyBAfj699K7NXAYqSH+nl6LuLP61azykB5fBceTYrNlpyh4zo33VVCTmJ+rzY3cmGbhTjm\nEtlYM7HU3MBIqOP64QwmG6+Jv0dl04752vHXFEnOqrJO0bYVwGbu5NjN3Qz9vMcaG/dONgqz4myl\nzasj5ANmnluOddG624wbwlbBxbUbEx10SBxqPw9Yjr/rHyvi//8+Pl0Fk8BehRMNtYxT4rwrkMMR\nxBMHDS3JmEET8LLoVgSNogpzal6UweToLLhrmX+sqqApsWo783WTO7doSp6wxgIvpdBaY5ombG2k\nPIqXsP2eClbdPaWNYBIzDipsiI7zm+N7d2NKCQkOLpGIl6GxMadS5fFQ2Rn/jp4SqXiBlcsUHvrR\n+VC3m9ZIuHqvPreqGWkzfEiBhgWa0RNr61hy15hjNbTCB3UlI3z57coPvGRcT5n9tLKbCmsbQdw7\nmifrVDpaK0WF3W6H7mdabW79PqhCzWC55ye/8IRf/PljdCn9wbYHXZNm4yv7g+kws7pVfPcEtGsI\nE61CdZ3WKKCBoEgY2YSUslvCcy6MVgORBOJGDCV5v68NasbY9DSd6RCcdU3DLVFiTXUzch60UbwY\nNi/imvVARX3e1GjI+tDj4dYXKFLQTl3MHTx6ESTmfqXgDPe455nkczi8jeXnFzqyzQMiii2LEOHA\nq6+Vti3MT9+h0nhlfcaH8yVXx86hXDLbLapOMdut96xaOE4J7QsTBXqnqUJp0LKj0cnDzdjIEY9H\nOx1EEqXPDrOIKFJn0qwcNVHyilE4pQvmfgua2Af11sxI2edYXOwnOHby5BvjTgt1reR5B4eKzhLz\nO7rz68V4wexW0P1EiURJxOCUuNgntK6UeUJ6Y62di+KzOlrvqCSuY1Bka54kSRK3MM4d0z1iFc17\nulZECr0Yre1BGjkXHw/AwW3/a2dXK4vuEHww60V+BsD75QmPT89Z9J5qndNqkC+4O71DkZmvffNl\nPn9zT/+Wcjl9wOH6JZ5Or4B1cl/ZHQudju5u6eaDpU/1LWT9YbqtlA9vPO7nxXWO/Z633jzxdz68\nZrd4HJmiBVBtYtdXns1Ou1R1NGidlLw09jReaCLPjefTnrIKu/oCXSdSclew2gsJY2oee6/6iWPa\n+3Bv36VQjA/LRfTejUbn5fUYLmQS3dPmtG8rLFoonLYOcpdCscZJZzIN0R4/S5AXj3lrNIWkUXUl\ntRmxjOqMRHMk2wFoUCvoFK6nRyjmSVib3OnKBOmVZBPaEjavWCvxuxOpVrpOWJ7pvTHJh1QuNhqY\nNtjbyn2sSVNofXLa6qc4hgDeiBSjSfX5MuL98Ej9osg1j+ciW+LZ+9BrGEOkJPGcjri7Ud8Exswm\ntgZw7DUCoyFyRq682WlhAOJJtec03fqGBPqg8+65juMN21mLRJNwuMpuCb9t/85jjlR8LnY2xhqo\nQLHz6xECifGUXQNLyGicl78umRubjOJtFI0dje/t16HHPgreP6wKtlbqJaTqn3Awpw9/8+nMyzeV\nfAnSQJNtTVMRQZPr1k28yMjqKFbKSm2dRKKvTiu11ii18rnXJ775q/PW7s4tGstZaNq3fPN8RIHM\nOe8ce7iIRQFH3ONxJ/xfuYOp5wOj6AF3R/ZxEH4P86C72UdRLCSG4th5/08iW6El9NBHuWlF10Cu\nzEfSeI/etvWrm5kE7vbsvVRfQVG8ghd8ng9F4Y2bPMhoeOHfNYXWsZuDGX3ox7KF+6gFGhaluFf7\n3sxhqDw/ueNTVTDlSEZ3uLV4HrV1cohfLDsf17xQkUBHho2yCx6jCzKc2kaXR22r/t0dyG05ERc1\ngzHFgyHZkYaUM97c9+LpoY7FAClpmyk07KSJJFXwBacqWIOUsnNDoxMkgSBYx61FAUvC1JyDvtIj\nwEjY9nqhtEvFOxTqwTbj1MPWOsXtldCN2+p0DxmwMpA1e0BLDyhsKhSTGIYIiCfdHy7G3dLQYrSc\nKPL/UfcmsbZtWXrWN8acq9h7n/KeW706CkdmFFkqC2wZ27YudmUAACAASURBVJiUM+0EjIyFRYOG\ncQu3EA0EQkakBA2ggdzAQqIJDSQby0LISEi27LSNbSzjzHQWUUdmxHsR79537z313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xbI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\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iUSy42NoPp6YmUnEEVVywLUtWXcLmrS6UBdIRRQzeAAsExH5GUTxFLe8LVTIsxN1qRDwv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UnuQ5yHJuWzLTNSTNiYeRnsQWZF/YFQp2MGcvpc5+zSceO+MnXkMAKlqM6giiVprkADAifSVs\nOxs6d6QD9yWvXXWknMprMTZFlrENFYYwMX82p5QD50ONtgXlTlzNXOxALwldIWmgFwqLWXXE94Zy\nyXS7iVjyWJxXD12phMTqXD4219no48M3mytyXnVETFA2GHMFW0i6bS6/znAxHC9vlGWJJWOsIAdJ\n8yp8BRr0mpQ0EI2P97UCZbo12KVq1IxcATUDQlJ5yQb1Pq2ViNexvFy+3hcNueTRw6lrrnNAY00x\nlry5YRPLGovJUFZYEL6RnLQNdte9XmYfdUS5p/KzepvqCKXvblk6VttFp0ANKw0v+h6mJGptsAYf\nt8J4YDR7bPgrGXD1BINNPugWU/ZKTOiVmPyKJ5PNg+XZck2zHWyhochX2t5AbFtR0C5fb6/ezybW\nu+CpkFxvtV90vICuEBCwaaVDlymUxy48d6qNw5NZqiOvuPDy1OqEvrA65BFtfq0XAV/qrvM3DL38\npAammUGGc/rgKOfmxbCTq4vC2SN5tA7Gcun7lWI1GcsXkjTeSYWTqQSbWs3tt00abmzjn0/J956Z\nHP7gh3aK5HM/qan0q4cPMuHK4nTpziOTb+GMDn5vm5yJoh57mQPr+RHv6C7Ga6wo3WetdJgphIkQ\nenBPoVHLOimZCnrtjpqs9MCugy0urC6pXE37db4V1Ow1NOp1tjcX9cF2DZQks4UkBiISRNGflYQZ\n3xpiOlWnhlCkS+5shqkQWxzLwNfMboYHg2QPofYqggrksN7AYAu9v6KxWTgn92EyE86TL8eNR8LT\nJlFiFh88l6F0sg1jN73HFgSy2EcWFqQAi2euUBCMySRNqH45y7T448NnNqCccsW8hyladN82xmIV\nrJ32b9g8pIfOhxixX3uGX7HjXgsUcwPbGN6EfyX6wNoYvtD5VDKhztcphi6GxvIafKfBCk+ZMbOB\n4Wwr5c9IPt0Uf/wgtOuhJ5+zeRpcYzFdq2HbzTlD2vNqNe33/sqJq1nz4ALIxlZMrH9AVT+9K0tx\nuD2aPjciannC1rDvr6FlU+iJQQ81Cvgu/f56Pnw3yepo6lyekdFqbN3pa1JDRv9+PMBReMacMKGm\nYbuM3F35YWD2fjEbTqy0KfMmS0NbXs+PvRUR8m1GDMgmvz7wQL/fl8mo5NQKXrIOxJiuQ1o2yaV/\nn65wkPnktCGJCxr2t+viOUI1xHTwuy91/iua32Acu9LccsI4AGdeYvCu5/tKnHrqMx43xpDEZiB/\njt/v1FXsx851Ptg+vTFotttBHZskNRT2szv0Jw0J7mQtr9bVXN++sd/fOIbx7Vdf+fLLTzzfi3md\nWOjw/3Y9176bZvv8xjClb/YpX2jcbgyMeQmtjttnzq/fMAY2IK+Hwnn2TYNy9zJ9v76bjb7ks5gV\nhBffv35l//SGZTLuY/lQLkgF6lznO3G8fAILK+lWmI/Jjsk2MN8Q2z2h36RS2As2lwwUw007kQoB\nBOGTKvlM2XTfznPSs4ljZ+w7Pg4q4csvfi7pzBDINs+iU7LE2CTFbF7JYK4o5qlmuqs4r3fKHH98\npyKYJUCoQ74c+wnXEICaUpXgTV8bY8gb0uveZFNT3rGLYcIWC6Em1d3X4IHqTC3Efq5UytC+IjOn\n51xDxVRqa0v6Z1mKgK8WQFkC+WgWiJBLEhuMxYYIsPdl2RPQCHpp1bmiwtVMi4XoHxkdkwctPuRh\nYi2161G9iWR1CP1vMDvJloxb6p8m6lL/9WJTsvGQd2UFXmMB3hp/zIouqYY6p1ilRa9ZqheRSFJN\nd6BehDgUqY36KIuhuG3baB9YSL48PWD1IhrbVh2ZRdbFNjaGGc95ctx28iyKp/yfBo+afOysilCq\nXb5kzVoj8KqNsfqTyrWDL6Bez4bbukVe7sGlImBg7VinAmusOEvhL14lqR1B8oRUX5Z1fsyGkh+q\njsjvr99drlOBAOyiW2EMMYyOXvs2DWvZUKolgXNXL5LdaGHl8j/VWpFhECW2f9t3sAGW1JD3KCvw\nWXgsBY611nOYi9X8SFBukic1YYR63F4+f7zJFdH/m7x+UgNTknzNi9/Jjdvh2JzMOih/Mlq06i8j\nmQ1Wgww9oIVj50PIJ4rDvlrJM9Uy0k8zSC3Zwpwa0p5uDWcq2z9biMrvVvNA0rcfMgkLPJvb64Cr\n5pnND67G9+5N5VwD2lDhcIOUPENiwMFFM8cgrqfCvKrl6eHB4Y4lXIim9yoOW76XAWXNxcXwH1Na\nHou1uJkQmKvBUZa/lbixC9MNGkF3M0u3apgGm24YprhM7yXXch0G5s5wHcjeQpbDpCVmOKOKsEu7\npEzs2BjJnioYMdRgTAxz4+eebFpcwhYKP4g+OLO4mxM2GJtzx8i1jHGPnXk91TTtwWM2lzVXS4IZ\nNWhPMnV4VAQ/zGul0RWDonpgBbsbj4LdhFYplMGXnlkD7lkrWnM2RyRjyfIkWbQla4Beul/df4MI\neWZ2N3YTy7FxSNJD6OBYw1BlMzokLzJTBP5QxHR6E3PKa8XQYdHNVcURot9xXxHL0IS87H4xOqUr\n751ZLL1M015kOH7WkgSs/Q7rni1k8LRZUCaz7k/0imo6J14Dv2+Sm6VRMXVAmu5Fp+jceM2/Dcz3\nd5YIWAxUaZhy1XY1pg0fy02GYsu7jXQlRirQI7HLGDap9F9DZ2vlTK21CCXfgtk6Oqt00JrD8j92\n1schy5JG9L7Tj1NR4W1YOJ3nx+uydYhKQqMYcA+lJXpqoEobOkfrwqugNh4WHAh4cNfag64lZTyT\n3g7J/J5PEslFbZ60H2qQY18yGSGZ9ZjAO2PbxAJvxnj7LB/nZjCabbxhVYy7WKUtdsamVLz6iwex\nrUHFYNt3bneIDvAv7HvQ5ew/v3E+nhyHs22fGFtg3sxL7dntLXj/9p2miePg8RfBRFK4BsYuT8b8\n+k5HcNwG379+w2ZTa0+eUgAL37UbTiFqxthRMxWFlZKszvd3Inb6mmyHWLZ8llKu3OmnpERFrhhf\naNvEIloz/BMdq4YcN/Kc+o7NlepnTj1OYtsx6zVMalkurQXWj8dD9R1nOwZ0cj4vbscN25T8ec1m\nzNZi35XQag71TNw3MQsfNUThPs8yuPReulRb40wmkoO2Ei3kk/wJXw6KmbZgbCGPTDdlS17b4CPE\n4aydbq/7dM4VNW0pQHeF3Lk2eKqOoL/7WiJqZXQrEED+D0mu5LPRuopcUmx1E2Kn21nAmgYxLahd\nS7OJxRio3mh2khwKW/f22qFErdfSqXut5U9yU+rfR8Ldpk9HEmOja4Ur1IV142yc3ezZnKCB3pXO\nGYY8MR5YOh31Yx1ZvYjk0pK9+us1NoTlGgpXfDvaj9mGktBn4K0+BhO4GKHPoK/GVxqdPhfnvjW2\nmJEQdY7fgrwmMYLI0HNiaOecB2PbOc9TMsljMM+iLOmpz9jQe2JOgccOj/Na/jVjaeOAJRXPpVig\n1zoHBVC9xqiqhDYBHlHyaKXOAQ2+LbxMa5KlmkHeRwWM7UrwdcN9X+mrtiSBYlHNWqEeLjmpAk6C\n7ok38pCaYhfDF89ZCt3ADcKU4NxNp1IXzafOuIn6FRmVVqKgAnKukt3CTENkTic8OVvgX19iBL1+\ns8DLT2pgUtsw+KHhcU7FP8dgt407D46S5OuOIpxzamv9M5Qcl9fkE5OrjUcPyZMM9gjOnqtp3T6M\nnNPXgrNKzplrN8rkn+OcZvwyL34WzfdZSh4CDtcwdHQyc6eBy5IvVox2fGjXR1rr0GzpY6udIyfn\neWFDC8B8GMHFNncyDLfGC3Ia1xqWylpLVXsxR5nsaCjb/WS4KF28qHbpbRebpAfF0HaU+kiqMZoD\nX0huy0tRqRj0htjGks7o0BihQUmpcbaaqSTGEuz0xxeIu/M51nK4kCa2a3B1YQzO3dhKyWTRReRk\n3xWz/egiaxXwnsQKcdh2+J7Ge5f2plyTbShJSnwVEEE1nIV2DnjJa2WDwldMq3HvizTl/SvMPZA2\nWQzji7HxcLyE3odWuSPXgxil5MUSBlkKtsC+MzjYmFy98+7G3XYZqoGRMotbBE8PQCleXuDnkyhj\nv5p0cHRwVdXy0Th7w9OarzO5t7P3NzbfeXrjdsf9xM/kL7s5evCgSHf8WRwe2p3xQnnQQVupIIqR\nyfdNb8p/wuCwfHVDjcn3JxGNueOxr0QneK2R7Voxtk+hKmZQ17ViTxfLMjWB2JDZVbJLUQHlSlKk\njK1O6coToXfhZE5u1065om5l+lZc7BKA0LnMPa+YYHf1MyU5SseAvBhvkm/29yf2fslvNbSbRN6n\nO+ul0O8P/SyXvE6rRat+tT5N2gJ28iQ3Ib0+i9lO6MFhtAv5dnm7hi09bIOZ9qY8cOwytqFUtVpJ\nTuPLHWpi1Vzfnoy3HY4Ds8W02dqiAJJV680DsO0bb7c7PkJR3ovZeTye4IYv9nv4TuzFdQbH2xe6\njO/1nT7XMGQP9uOOe/H5y41v307mY7J9ucP7E7+pmc1ZnA32+RPHpWWsEUPNnEvR0ObM54ntO2Yn\nvu1Kv0Of16xkv+36rKugL8ah3Sfn11yz5NrtYmhgmhqEY5ec57htnO/f6C21IJJgXrDdPxG2Hsoy\nNkvG7aDNyPkgYtcajPdUDH3pu8GKOO4YT+Z7cdzFSM02rvMB7MzrxMdGVrPvB1NmFJ7XAyOY15Ld\nzQdfx53jk9O3jcPg8URJqnmJGcsm40naXcqrn/JV0Kkz5WIS3pg5zo6NFIAIYhColfr2GoQEoPqS\ntlVAnGpuLVyyN+AVApWor+xZjGV693LKc6WeFcfcGSEZk+TyMD0YJZlb1wuLl9Thw+PMYsZCQ/NH\n/HjWktDp7cpvmXiKoc9ujClfC5Lb2UpfK+sF+BblYpZ6XqTMzevnxY4bMNpJdzBnjF7SUlvGJ62P\nOZc/3V1LT7uWTHlbfUrrOY0w0k3g4IoFr5ayxF8yaPR7zYPbttPD2EqAccVi3pYHPjC22DBP5mXs\nm1irc7uoU8NJxWQMA0vuY/DMSV0T3zb6auLQgEtpwyJjJ67myiJc91C4+h/xjKzE1fp4Df1KBDT5\n09NKsPhKW/WCOQ1zec0c9baSPbhAihUIFCsYjbEGjtI6gRjqi3SbGAOdZzUMei4/HdQlRkkyfw3X\n5gNnUtPYhnxNs2HOE9jFXrqW7g7fPsJEZl1S+UydPHs+ePYN39SvHgbZrjrSc91jhfvF5cdvvBf5\nSQ1M+GSbpxDIdiyMw4rhRZgSSy6aE8PSOPtiPwJMOfB7N2Swe7JTnJaLG5i8tZE1uOwJbIBYqEYm\nNsmMpzxFJnj5B5ojB7/cikcv83c1Nx+EJ/R3Ko3NtPQwVhDB1sv82U3bUEx5a//TzZ7Mdip2cKcy\nmKGBpiOxhVaSRbp8KNWLSLYmcc6Xltekee5utsXi4M02m3MUUcZsI2yyRRCdnEtHHdharNlr/45J\nq4t+t7cWRRJC1jx8RXgXo8WSxIpMrTZ+5cabbTjv2DA+tRMVksUt3XKGMx0iYY/BjQsiaFfYhqVp\nhDDDXMsU37XXm0kzF5uSfjDWwZCxdmd5sKVxenLisEyUKydG6AzFtCHDMmuZsDVYEhS7y+TPQDIB\nfUCMVphGmX34D9zHQuQmNpqLZtib4mZtl4SK/thP4LaG/6uZo7V40hTUMEjGENo3bRHgtkMbl624\n827eK8kJ+zHIHtx6kFZsNvg+k8PhwVoA11NSGuDNjYzBO4otfVZxzskDoVTdsG/OYc10/xcSCH9q\nl9u1ljjqWVIAU1OVWK1hfyFthqKka4wlF5CWntX4DIzyXuhxoQjhAJ9o/wXk2lmS7Iy+mMsc26np\n5Qp5DvwVprACGVaahw6qiZL5XM2J148RsE5hvpFXYfNUg1DyI5gPxraRs6QnRyxHeSgyjxV8sYIZ\nvBWZ0C+jOq0wGgt5Ho6X6bzpC2rkWtfRagxNm9+jp3Z8xM7WGoCshLCOoXjkEZLY5PMb477Jb7Ai\n981KNZtm29VwcU3yfNLHG+dZfPlZ82XcGeVcS4J0HDeYUyi/DX72KajYeOuDNIfnhX37RO9qNsZx\n4/v3qYj/1sFcneT5ZA+TFDXQAllr9n1XM2joMwAh6RjnfDL2jTmT2LYVobzixV3eVXcYfuO6nvjY\ntRiyJmOPtbNGTAOXTP3b211Ld3PJ566L7fMnvDeI5tgHs5Jt12frpuXsXc77WeT7iW0bHRt7Qnwa\nYqnf1zrvcSxgd8f2k2443ydXXhw/u4sF8W355oL5PPFhPK+nzpvrqfPFgE937r7JDG7F85xc709O\n+zWJ4uaY3RUd/RuW0vzrvixS7IEvBgndtyXrEbHUK6/s9MoL9lVH8B/ZHFO3UUNMNMsvEma0y+w/\n+tfriM6D6epFKFt1ZBIVxBiMbPkks7HtJbFbw/h4Rd5Lst4O1Not2Eu2h+pHmwYRG65o9BIjox1F\nMvBLWqlexFoyde0rlPz8x/NQZ24hxrMXCFTl9JhY6jVoy8I6G6vkh/LBWIlr2kG0lC1dL/hXwHPY\nh9+oHbF7vtxEtgD3luyx9xs+E783b7ERqQAqvVp52suaxrmH1hn0vkCw51R64baGkG3jeuTy+0i6\n1q4ApcHazekwW5Hsw6Ue0Q6/pQdKX4qSkr/xJeVf98l666tGw8pBBBQ4UmuAUie4zqX1buy1lH7t\n85LPbFvJIiH5IpKGvlhIEeeDy5t8isE2BoNJ7y52S0pEzNQvZ2+yETRSKtna5dasNDv1OVraW0rk\nY+3+w+iA9A1x1w5WXFVknVzdnOaSdo4G27BqhXv9Bq+f1MD0B9fJz/ZLzSrOUXA32C1JXhuCm2nw\nvoP3wdfrHcvAYmPn0sNKEnXyC4+1tLWZ5qTBQXNN6ftFiTqnJbMn6UEUvHFByNtjdjHnYLqagmAu\nQ7YOQSw561xJakoze4am/61FY2dChIyQ7nCzwVcLLI3hFwM1DL4yRK2btyyeeTFNCyEVb6lx+8HG\naMNt4m2S22CsFkCRomgBr2PcI7j5BdeOb4rzdDf9vS42W8b4gloo0Ra+Nlgpba0dDZZAjMmdhfzW\ng23c+b+pe3te27YkTeuJiDHmXGvtfc69Nz+qEgqpBV47CKkNwMDCwMHoH4DAwUECtQPCB34CDg7C\nwmgJAxBSI4GJgQO4LSGV1JQ66yPzfp2991pzjhERGDH2yapSdauLrMzkTufce84+Z+291pxjjIh4\n3+fVrIfuFOMeyd+K5HE52VIWcQWO7J+nHg9xUi/sMsscaoXwPqlC88mVzTotBinG9+YVipZFwsv3\nA23WQmBZ5LKNkuw8zqC3dxTYJNTKdBpVJIgWejkyyqSe5fMpOWPlysy1EFkUWCIxPqNoyr3JFjU1\nCKkCNMwIK9/INWtBuufCy9OJbnTgYcpbCD2Tay+yTOFYa6I0tHS/M4yJVEEslXNzzzW0bxttJGHO\n93nhgyeerSRJWZTE0RrnPAmFI6KyZmbl8gTQelEpc1bA3nUmV364BZNNQaJoabE2h4jKItJWsI/3\noqgW/J0YRxVXbQNK5qIzyTjpfcNnrSG5GgykrGlBrnupvCYxqxuYs2StTa26xZIco7E3UAmaOBmG\n94ZiuDgaXqCKpKY6SJmAs5Ea5Diw3nFfwaXbTpigTKbUtMlfD1TLP5KATmH6JDAawTThPdQus/67\nOnula/dFpiJZa63CBmKNvu/4HLWRx5JsaHL58MT53aeaePWSrG4fnxBRWi9supMly6MaL7hhe+O2\nKxnB/eXBFz/+wP0x6V3xmDzenH/p9z7wKpMbcKx7Ph5w98BVeD2D2wU2IAlyB2+Nl+8HJ8HHU7j1\nnZO5cljgNQJZMtXMmpo1Lb+ERTDToQvdGufbUc9SV7hXYWG6Jozr8NP6VhMdq5GZe/0dzY1U6Jfl\nIVl2M0+rZtn6nm3rCAs0sabX5a1ThgSX67Wog15NlAxHptCl4C5+n6gdyNYRT3Blv10q10mEPIOQ\nQUzHto412K/XCsTOrJ8tl/0vGwAAIABJREFUym/CDI7ldeuXK7qte2eD821gW+CvD+aczDOwrlic\n0HZynvgoX6DNKup+uKvIYhMs/15ITZRSag+xFQReJLTKSjLt1W1XqwlQUlCkGaQUqXC+B8Ku8ZtQ\nUsjU8gaJKRq+fGMGXsoOM+NMR5mcs7NLoh6YVDRFUXPfw9UnujLmXLUIlJJIVqQGmZ/hDyALblCN\ntIpWeAdEUFlCSZF604mATWIx1lhz+lov8UKtm0lNPlbmhVmBaHSTKhQRMCoDzqqhoIu8Vg702k/J\n8i1CWQHKOVbNnxT5vI6AsvVqGrtP9svOGI62ICaMI/np8zPTJju6KJKQx+ARwRTh4cHFhY1S9WQX\nmjbOMXGSmwtsHZtRsn8fDAEZ1XAnc3mYlv98KYyklZVhTKeX6KH6WPou5ZRFQsySEibrsyqZnYog\nURK796SPWqpkNcjWz7KKWW25pv+1xusGSOVaNWlIzpoKRYdexesWNan0UWciWq/XcMXagp1RDcAU\nX5/7r+7Lui+kqLBehR0jGb0mnJU/WXE9zaiYAwvMg5GD6Yposi3/lsRgRiu4Vejne+23df2gCqZf\nZuNI53KWSf6U4K7CV6J0BusZR7VzWR6DbuUy2RhsVhke5VcBYdBNmaMq+O1dnKIDo3yxEYmtubQy\nmbbGkFkUmAgr4EQKc1GLppcGXsLZo6h9bz7ZWiuJGVq5RTkRi5JrRaDvwVwiXAlsa+gsI97Q0pKX\nZGrUZELamvS8m7vr0HBhVLL7mrwINfnZMJoETaBrY8ySA5o0DpGij1gjJOkeC+qw19lfnSnCRQKk\nighbSdkudfPGkiWIbowZdE32bccleH5PZo7GL60RbfIvqPBFP0kfGMan6NhsDBOmdc5QXsTYWmMb\nQDu5ROMM5zBlOkzd2Jh8sU0u0zhJvpmNA+ORwtW0fEq+UK5Z+u7RalrUELoVVruoR1JYblFubVbX\nLXdmOHct6o60ytYwqUyoKuATz2WyFWEuko9pYe1Ty4eQWR40VkiyZ/AmCQOmNHKRyCZai3gobydc\nMyHLCzZTaGMgUdP2sbCpR+5ML930lOR0ZbqzpyB555NuWCrSnBk7I5P7/eRhsB8nLkkrTmh1lVGO\ncdZ0IQJmBSbK/P9T5ORf7zqXSFO8Y5Wut+QvCmN81smXobYkURWwvGSnlw0/Jyn1PCeOmRFHHbrD\n63D9nuPUIsmYjNVV0KwGw7sN7GJChnGzIlQWnr82Ap2D9MSkAk5zOHR931VrgqqjpjdW0AOJQuWn\nJK3vaOtcPXAB7xP1ZOI1vDJFszw007PM2wsbX/r/ojxBHd6JkvKaKemC7sZ83LHWoF/olwvj2+9p\nz5cquMLQETz9+CvOlzv7tvF23mna0H2F8eaiRmWyS8ncZDP63jnuB/tV+cnPPvBw58NzgQ4iOvfp\n/OGfvfAHP9n52VZT6p7GH+uGPEo6+3xRXs7J/XWyfTB6CNLguhtvQzhViDHxBgRcPhgfPn7JOZxP\n332ie/nNnr54KtDPDK4tmCsaoTVwn7h2ttZwc8w7IvAYD3pvbNt6v+gc51nTh2Z1KM6aiBdWOJYc\nJ+ltxYNGrcfvWT5oNbkqaLLjm3BfqL2MB5z38hFkcmZNK73NwvS+nriVIe8+A3cn5lw+F8HHqO6z\nNnh5EEwco10b4/Vga8Y5JmpbNQY1mN5pDB5fPzht4m/VpW9RnfFY4KQ5gozGHuVlMpSMH+4aAiXt\nbnEi0Ys5kHVwbKvYyCVzfY9oIKWyz1ge4KaEK/SgezVxS/Zdh3u0nseUCVFQpczBmQqrMIulagC4\nSAWvXteQ6t0z41NRKUqrthW7MsuHw/TPmO5JNXiklQdKl5f13Ucl1tk8qEdi+bSWvyq1mpBpic/6\n/3eFaLHT6n7P1agh5LMcj6ipaKxQb7T8xO8RCtr08yG/a6docuDLf1SenooYeZ+Qa5aENVVpJrgn\nZnDdOy7Btq2J4N54RPCLtzd+/+OF3/944eG1x7+8HegxmVnP4kOd4zHpe6NVPgxdyst8CMjh9d6E\nsl+Vm+zMLTnHAzkpj9+28PNeDSdf3tWuVXiF9JLaahbi32BSII4mqyjKIuExKwiZ7X0PW1mYi6Yc\nkjRZkSGxmoHR63yipRJKAQ0jtsrYDO+QA+ZJWxj8M6oAdnO2ELjPaponC35U8LEajC4/rtSZWM9q\nBsRSMMQsy8wgkFFNZ9VgSMdi4NOZEtghn9eRgmJURlNEEmFcPq8j1Zj7bV4/qIJp5sTTGKn0mFxb\nPZBvDj/qWmnBKGNONlXaSlYPT0YMEmGbk705bSipxozBZhtf6IPu5T+aCSOUu01WXAhixn0dgkTL\nTO0kk1mkKqByATbI5OKxNMKFCE1d/abVxY18D4VLZlT3pq0RvZPMWeGVuWroMedaYIoiUsbNRHwZ\n89LXGLMoKuTEsPJGoIwoH85FatPtKjzsPX4v6OzLWFgHPpFlJs/KVDBR1IRNFRXlMSZijSaNqaOQ\n3qI8wjkyubadwnSUj+i6VYfkYsnbNL5T5TGfkHNy0eBLCz5IBdUeAm8kU4XNPjI9iT7ZU7iY8TZL\n/nNXZ09o2SHhZXOeh/Lj3fh2wkNhjApjpZocmNSB9E7h4nwGVo1XWlbwn+lGSHBGFTlDKtuiMlZY\nki6wldnQFchgRnCGLqBDLNlCoNbw6eXZksYQ4z6Sqb0+u3mQKVw5gJVyPQs9bmMiNmiZjFGempTg\n1ZcbzQfWWgFJfIAl12HcmzBkAs70CiA2v9dGfjTGeGM2w1zZPAkNduk0Ky3xI51zjKWJN85MvoxE\nLRj6g1o2/sJVKRNW3r61GZgC4WhvSycuxDnRbrRtL3LeMZij5J1yjvLxjUYqeJzodkO5l6+nKfgF\nm5OpJ6eDSaKW9TqivNMkIoIZtYZEtW+BelYYa+Kzpie0RbjD1rQGyNogCxyh9fVaXdb5+kZs+2c5\nTtzvq7G71o/w6gL7km+kL59jNX9UlqTlnaiXVPdSjP7FjbbvPBJ0u2ASaL+S11sd6NpOHA9SgvH2\nwC4duTRuzx+57IZujZev39iuDWsb8xioCftuHPfJ8enk+vEDwmDMoEXntm1EwNMXxp/+cvAQ54++\nnvw/Huw7fPHc2DfjtlHS7ExMoX/5oTw8cnIx4fKjje/eDjSFr1+DXbQmaCEcefKhG7effsGn15PH\nmBxvB227kGrszdikYU15sYK1tONAdiMey5cZsOu1VtZYd10eZeBu5f/EITQxCrXOipEQn/ioEPbU\nij0QKiB0jlkHCu0V53acq2gOdFaTI1pb5msjz0ELOO81URUXxv2OmuJzMrwmrJJJ23YyhXl/oJm0\n1sHheHlAeE0jJCEOkuR8CY77ybCCnuhUpjq79ILlaMfv9/IojJKKjqicuJSEH/AaAtVs9SW7TU9m\nU1omzPKuiNUh3+e7qf5XwZ+eCV57raFIlNIhYmDawEYdZBtkFJX1zMmYRVo0kQoHNVh0kYInyah1\nJAVi8nkdyXcvJcuI/76OlB8yMz9PyNNrSlO5aIuE57OmXxLlwfQ6pNa9XVgjyfhVQOsq1i0Fl+WT\nWdL9TK3pGotrtxkqhoeUPyejYhiiDv3FqfHydlZtQGuVW9lUUO0c56xGjrQivRqIKnMG7jXlRQpe\npKNx2yvse9uU7+6TYzp//P3g598+6F14vly47p0vn437dO7DaSn0/QMjnJDJpSlNOnedqAuf+klf\nIKpIY6ZzFWW7Xbmzzq3nxHrJEZu8+8jhlB0TwcYke0UyqNR71bLBu7c0FJdZIKFW60X1sWodwWqS\nmEmt5dMWNOK96HRUWwGwTCEqf20eo0BRzbGj7u+xPOmYkDGXLLTkl5KJj4FoNRRnrqw2d0R7FcW+\ngDArxHm6Q3p5Yw0kKx8wpxL+qKLbV7NQgn1BIzIqn8nTiSjIyiDpuSRPy+3727p+UKvWDbikV6qy\nJEfCs8LNSop1SulkZTfQJSsL40kO3hB6Bjft3KwynMyT6MFbPPiggeqdk50jgje/VKihJ+fyFnzQ\n8hfsdhAuhDQeUlrNGc6uHV+FWUr5mdKUWN6iWNODrPu3gBM0zIx3YQxSo/QmVtGGmRyzyGxEcs2g\nB8X8zyBWYrNGFoVfGkktmkqwI4wsY/uJo6brhqsH6chKgN+ZXJtUJhSlgf52QR6+WlLFpnDxZOrg\nqfcykGfyhSqhwkC4aLHxJeJXY1ltnFodiW/Z+XkTNoRnKb6UsvGND55N+VGrEayL0r3C2V4NhiiX\nLI9Dtuo2XLUxmZwiuBtzbrwKnD64dOWLTHKriVTb6tDvDkjneY3w7z2rADUteZSXlC4+T/Oo8b8V\n4aWtggZW9+w4alNgbQiVgku3zz1GHp6oNU4vGcZxJgeGnA+uIuh8LMPpRoZymJMkdhwlLzwHM6w2\nXA3MoGsZUS2LeDhiAGVwfVHnzMEtrNQdMZhz8sbKwbLqlhOBaSHlq+tbSe2a8DQLbBBZBfIZzi9k\nctWNMc7fxeP/N3K1RY6qnCwKcCGQKyjarBXEYC+Eqe6KlnKbLiXJa3rh8tRKUjCdtI3vPn3Ph+sz\nzU9eX06GDGbu0C5c4o2ZWsGKFEFKLAmX0reb4QpMYV947Mwq0sMTb0rLgKlkW9OIKE14mXkTsQqe\nVGuEVadvu1wIgjiC8XjUaeMdmrI6lBkD0dqUa6d9x7e+o4ejjOgL5RqZzHTyfBSiuynj7YXYGhqT\n/eON4b7qL+fl8UAQ2uh0GpenTjtrMv3Fjz+U9y+Cp9vHgiNMuF0X4l6y8kTkxqbBqQX8fXyC13Gg\nXp3Tt/vgmhufHm983JWvfnwt3LLBh77hY/LKZJpyod5TW53np60TPpkKpwc54RuqSLp+aHxonXHZ\niTgxFc5I8gAR4+mpvF0PKThHv1g1NRb8Y0ZUvszKnWIr0qlpku09XDw4Xt5q0tcFcfCjwpOttc+/\nnjGglQfJ2sCPhBPOMWl7YzzeyEia3ur+mcEM8PO19qEZK7cFZK/pZO8dWjXDxOF4vRcDUuDwkx4D\n7YXSH8fAxwFzQDOmDdwn6bX2hzSkdTwbpx/oADwwrbWvieLiPMbJdi2Z6w/5asXOLpobicwirdFq\nStpCCxNtax1RQelk80JBA1te0Z7EBs2d0M4jnYv0lUFjDJ2MaAuVvYrcZAnO61AbAaEN0ZoAcSb7\nmjjXpKUatIJiGVWg2SpcV/hs+UsWeTMTRT8XTYquNaeACO8NGrTkYcupjKgWRpgEq0Ztrn0xkvJQ\nR51FIgomJeGffYExCpuucmCtkR4r9wjuowJQ+6ZIblUwZZHiLvu2fpZkb3sVqg7bJcmZZMtSVuiF\ndqkIGDx4PJJjDMQSCeOMoB3K23jj9qa8PW+01RjvqlhOXJ1TlOc6JiwAQ7LrRsasSX4kOYVPBH6c\ntM24htLaBY9B6+XJZiREY1ufz9yivFHKWjtqWjOlTknIWkeaFkG51LKr0Z6kD3zKO8WbSCdWEaLv\nnu4cYL3sHzbwIagbIwbWlMyzgF6+laR8eTSdoxrFkdhcB6DVy6s12tcZKBheoegzY0XJDCRb7Sfu\nRM41gRVCreSFYYtNoaCN6YrLKMFdFmVPROvsT/AIZ7eCEv1Wn/vf6qv9mteN4CtpjGqt06RC4naZ\nqHWOdF4Svp0NwpltmQ3jAq1xEOw4jCeE4JnB69EqaykNk6/4qd25yGCPYN93LvFAe/KYNVo0Mzxn\n5RbIyaYbLZS71Pj02sqEHFq687dRFJAmJV9IFTSCaa0qdRV8Rn34Cq9UMbHFQlWHLESjc4pzP5Og\n6EMek64d9aA1rQJIvMy6JCINtTsmhfP9oq0QOhFObzzawRcebCZc40LTg02EXeDFDc8y1X1nxsbE\npmO2c+ugnJw0ZByEbtwwwgrwcCOgF8b24cmuYJ6w7fwiG3JssI36HHW9DhemT1x3iINLF7ZetJ0G\nRAqHXFG/E0NW3sFJp0JYSw4xuUeNrzUGM7VwtgSOcQnjtDoU3sVxrnyRiemDNoM3Nx4MTpItqot8\nyuTKCrY0rWnROKu4IFaoWnKKwKjA0JJUgeSA7J/DiT2M4QcqBSCR4t/TOKrra4Uv7nPSZvLwyYx1\noFFnqII74oLIWbpkjInRZeA58Qm7VdF5jsEtrTbonKswEh76AIwuSp/BQybdGyMO9lYeMzHh9Mor\nO2cFRF+bol649B/qFQGMvsy3kxNn8xKOhBlO+QXql2TO7wsPPkAvG+kDRvByUB24yhOFcO6P79Gs\nCa9mIPON2L9gzI1d7jxmoeyn9kL0SxGzzAwZgAUHYN2YWR1X6YqMA9/6yhsJCitcfrrKgqmsFuvt\nM5EKFeb5INJgONo2Yh54sWAroyyTyEqdf+9qQhUruXJStBnkgcgGCdttX4bw6v75vJevKoQWHaMI\nmH3vvF6uRDg+g9AkYvDp6ztf/ewnXJ8b8/WOPV2Zj/JW7vsFU6epc3qjb3WoG4/J9tTh1dmfd/70\n+weZVaC4CvvztqhdG5+OQXwbCJPtyRg9ka1M0twfpDeOrQIV0xq2DzYa4b8y6z9mIJeasMysIEhf\nh8qbNY5roDK5T+gIz89PhE8kJo9X5W067SLYYbTLhRknrdfpQjdl7zuP4yTCyWOZ7TPIMzlf75Wr\ntm2lX5gwEUhD2qwswm/vpHUYEzQYjxPOiW17xXel4UzsDeY5SLeCeIiQu5S/yIxURw9gq8O9qVTx\nOJy2dUYqvL7StUMk5iX3FNfyaroT24b5JOPEYjA96NsOfhDWSKp7/ThK5t72HRnvdIsf7lW01L1k\nYDoZGgV88YReDVAccsmuT52LbsnCLUweDBggBHhNCtOdVxqKYjoLF+2T2K61tm8Hj1learde2H8p\nT0ujIaFEnxxAN63YkLTlnTyJsCpsau6AZxnxEarRG8uHRxU3NZzw+nvhgJU8P+vne89jmg7tPafP\njEbWHrnotBWwMhCpCWvfSpKVIuBC5RoJtI6xoUx2rbyq04XIB+lF53OZjDHR7cK+FyAiXFcGVbK1\nC9kSiYG3isgITeLutL0hI2ht45usfVCz7A62Go7inVdO8l6Tun41mipzK5+2jomgJemdtY6oDIxG\nOhytipnTSw1AwsjEGQQ1KbugHFulJ52zlC8Xu5DqgNNm+TJTJ5trSa4XjRES2WrCNf2sn3sWSY8s\nWWSsDC6j8PUeQgXZG6KD6Y0Y53qeB2gFXdsq0haQlBCnuTErMG5Nr2uqlUmpGmQWMVhXg5UgZeJR\nhepESD/RNV2s6Iz6b2LyrgSvTNFJk8rBapWCV5aGqPf87k4DmhjMKJvCb/H6axdMIvJvAP8J8HeA\nfw74u5n5P/ylr/nPgH8f+BL434D/IDP/7z/3518B/yXwb1OD4v8O+HuZ+fpPe22TYOMsbW4mMo3R\ngqFldJ5xoWnlHn3NVhK5LKnbOINJ8FgjPEnhm6iRdeiF72NiCb+83xANdh989MEHbXxJshtIepnY\n1pInaTxIXsRp1Mh9UgAAqOnL89aXnvQsOZjJ8rJAiRtAtYyQSTJXAjgtyShT45yTKcIZrLq8KvnW\nGocroJxRssEjpQ5sUlKjZh/oa1Re0r264Z/bSQ5H+oVkcufEpLFZMDPYJfgyWpFfMvkkykbjJYXb\nUZlK3eBmFx55sonRPbm0CsgdCSOSo9XmMVrhu29MfnxZ2TLroZw0XglGdr7twt6eOKXkZhevzpVF\n5+tWn/utVY5FZmOT6lxJlDSQhN23KpKCMre64q6kzvLmqHHzkl6+yuCn1jh58HGHr1BeR5CXQeQg\neuOW9bk41bEalszpVBRArofboF0wLcQ3WYSxI7yoMWMsFLBjnmxRHR/LQL1IYJbHCuVdYahzVLdp\nje+7V0daBAbH2nCqKzP8PfOrDtO3gLeAKYXgFHEieumho9G0c4zJKclFa7qCGI8RHCm8SOA0xqgi\n+AxnR7GA+69JyftdriFlmp2MVDZJcq0h4hP6jr5PMZXKBIlEZ1Y78VGH3F+Zmuu9rzyJtiQHlCdS\n17T49TsQYVhns+qWap5UQj0l7c1JtKItCiwPQTVQMhPd9s/y3nc5n0hNuyunZG2GEYSV1DAeJ3Lb\nFjYc4jg+wypcqWnSXHKv1WIZlM9Bc4XZLiy69qfPgZi6SEWRTr9u3L97oz1/rInZ42CmYdeN4cH1\neaNvXzHnRLpxv9+xbefr71/ob7W5X0mulxtvb3euW0ne+nXnw251f746JsHxKKztOZ2O8ns/2TGr\nAxUC7sLbCNw6w+9s/YIfcH8b1XiRpOXGSwgvL5OnKxW06qC7YJrsqsxH7Rm7Xgp8QPk5xj2YA+y5\nzOK2K3sGQef1+zs//urK68vgw5dXPsqNl9cH/akTmdy2C8ZWtLtFBnu67by+HNCFERUe21qnfbWh\n8Jlu2lpNd9Od8RrYDm5K+igvihpCI5aHxR81EYxReh1/DFIHSEdM0DOWNGx5D1pRqypbrsz8W2sF\nFojyp068KFyyvDWlqcG2KgZzLoreLCLinAeWwoizPDmjtFTujrD8/stc/+tcv9uzSGJUE+uayem1\njhjVbNH1HoWUryVn1mRRBcYkZBXC9T2UjG4aIRU1oiRygFQiOuYviCoDY7NqoGmeKwoFKNwUYf55\nHRkC7azaNCWxvi1p1goJXaju8JIJWmlugRLaZRRJNK0CrgHwBWEa4C1q2pAFnWqVRMucBWgSpXzl\nS85peinqbPJ+iilpniXngK2XjD/yABS1Omz3lqjseCsQy0hHxXg7H5xexV5vxmYbxznZ7EBsY9s2\nWivliJ/B7M70sj+MdHoqt+dFP30HWoRwxIqEGQ9k34iZPA7HGqgIlhsvOOMe2LagT0Fl8mmyheFL\nvaGyf56iJeWJ5xB8o/aNVg3eiM7pd263jfNtctk7l114zIm1gmtt1mnaiUXNdEm27IwoMmha3XuG\nLtIvCyFeCPeRBfUYB6jNZXmvqZ6l1rRxqWLSk1WJ12cySxlVBNkVUk5tix5FDI61n9VVU7n3IO+Z\nyZTyNBVFUcgsUmoTY8ogQ2hWTao64w/UYeQgsi0aak3uu+WyxcQ/42rxN3P9f5kwPQH/F/BfU4vL\nX7hE5D8F/kPg3wP+EPgvgP9ZRP52Zr7Pz/5b4PeBf5OCGP03wH8F/Dv/tBcuSWXSYjCWgVU8iLzS\ntuSXvnOXBx9bskthujMDlw6rg2rrkItIYaEjIUr+ES54q4d+0HiZwaaLoJXOT+n8RJzn7nQLbgK3\nVN5WN6AtlO/Myu0ACrEtdbAdAuHKlMo7aKbVcVkeAbJC4NyUI0qWNnOSGSgTHZ2BkXaweVudmeCu\n1OifSqueVGilZONxwLZXAjup7E34bgS3Ds2Ux9LK3prw7RQe2pl+8GTGVSpMdV/c/qbKlsFdgiN2\nPsRkyKBLMvyNbjvqBeN4WoY+YfB9lO7JaHRLWszKP6A26O9icrPO9IZr45BW6N7WeAC712MRM4jY\neMmkRxLNmAm714G+sUMkb60WsSGNHgf7JuCTYQKh1efJBhpcUzgiCd05Q2jq7FvwmMKu0Ek2rYnL\nMQ5cG10a2azkldRBuWdyEmQvpLqI4rP8YA85eaLhnJzU57O3nY7zdh5oFAq+e3WsZFRBdlEvmcsM\nhmQxCIOSBvbqAnr26taUgJPq31hNuNRrI6SVjwUYnjyaIDFpCq6N6ckmySnJ4ZNPKNOVyQnaSQqL\nHnNRgkL+6gf0n/363a0hLD9RTM6s8EDxIPW64ANGyAHW6l1sBTjAyoQvVjkhuf61eHc3L0IQyUJS\nC50OCiOipjYKenaaQrdgtg0hadLgvNfnah3Rhutkvcjq2NVmVralRBfZrZkWvW+epBYpdCLQ+yKg\nsWQLgbivXBwFJtK0YAbECpFcCGixKiCbkSjzGEg3RIM5Ar0q4+VRDBKEiJOYgV123r6/LxnpG3Z9\nQlsFul62zpTE9kYTitcZynw4h1Qz4dPrK1989ZEd5/Vt8pMPDbsZP/9eeX09ESrAuncwN56+2BdF\nS/j0MnluypiK9WdmBJ71no0BasrpFbrbXPn0qDVkirBRBu7HWet9s2TOwalG8zJbX28bErPWURHO\nkdU91uBy65znIE0YZ8k6b09XHm8nfetczNivILLx+jIJpGS1zyX//qBXTp90bRznpF2k8pXMcA/k\nAWM+aFvh4y0LtnF5eiZTuL98X3tBBrrX8dnvJ/44UEna8zP+WpIalersRnoFc5arv47uaiW7U1ux\nBxM08emYdTLPCtn0s4hbw2uCsG1IFoF2iiDnwUkVseSs+zNBrRPnWJQ2+5ug5P3O1hGQz+vIMKWl\nVO6WXDCDOJWpB2qt6Lbr+S1/4QqtzSWLo3hy1RQpyWwEXKTC5lsq+CiJZQShgfmFTaH3CroVU7Yo\nv0lk0qUw0LH5ktouap9RMsolYZMFOKq8xtJyBSXHnVHAIvMq/DIcCGQGbiBTSfU1Ia3G4cya0gpA\nLOx4VoBx+Lt/M/ApaDfmOYhW/uDI+t6tNY6j1Bv4gVpHWvn6GkYsa0EpqxMVw2ZyysRa8BiDqxlI\n55yD29bRJ+H7U7gfEwW6FAVYQ7jcNnJhy99O56aNTMVtx7OAOWlR2VFhHO+AHE8eI+nhhEkVSaGc\nXt9neZgPxiLBCRWXgs6ypZoUv4d6T4yGnwX28QQNYdPOzJoe9l7rhmrjeC0lkTanR2ds1VCrSY1V\nlpRCeE2ZQhyZjZkHrVmppVKIPCsPFGHMOxIlkcum5bN0J96zJq2BL3DHoqemFPpdFoSomoil6al7\nThBW4HW+gxpG0WlzcZYjFjCizrM1VwKmlzIny56SUrOpTeFw4bLkor/N669dMGXmPwD+AYCI/FUn\np78H/OeZ+T+ur/l3gT8B/i7w90XkbwP/FvB3MvP/XF/zHwH/k4j8x5n5x/+k1/4jGp9Sadb4IiYf\nV0dnStAJvtzvpG88cD5IseDNjKGVmdRZXWXgiJWpnHN1aqsAS3IVVADGQNhnyeJ+uWB00zpPCsPh\nFzPo4Xy1t2W+r3wYRDJbAAAgAElEQVSEq1cS+4wiuLxX5Oivuod4MehdKtROdYWejsR14l7epIZg\naYiePLAKj1NHpW5AiQqEfJ/YiLx3bwaiyssIgp3D1uEB5zULRXqdg9Y634Wwa3KGY61xT+HMes9O\ngo9h7A2uptxdeFnF3+hJzsoE+snlwtdx8DiUlzQ+dviyGzcGZ5yEwDmTS79yjKyUaYQeBRZwDdxP\nqhYQDmu8ZHIV5WIn17SVCSpcXPjFFL4dgTQj5+RJi1YnbmjrXHyy98C8gh4PkeqqhUB7cMmSzjWp\nhV68kPQZFy7bYFNZ3jAtf4DtVAzTysNRZ4837tmY7qga95PqskkSDlOdLaUymgQ2h6ttnJ54K2rP\nqRObyds6IAdC6xvaqjODlT+tS0IqpivW1IOHvJYsL2tMrTEgvTo71okMBg55WRkp62uiFjNNcBNe\nfLBlJ6QxPHBWRlckZB0oPYK/+pH/612/yzXk0OS6CYeXF5BlvD8kSlrWJtDJ9JKxeE1dglxFaB04\nMnNJCyovJbNodjZLa95S6lCRtsyvQouCa4yR+N7YKUmMH68M4LLv6+BAfU5rDUkvktX7GqKiq6OX\ny4R9kFbTyvT1/I+JM3B/J1VB9R5HHWBUV7FWPkiWN+H9qvDYWkMQhTFwaWQfyMsgvEz/RHC+vGHb\njsd9yVoC2XZ8euHVtXH/9D379cblYuyXnW+/fSUjeLsn0QYxqiP75VfJz789ePnuE/8olKePV378\n8cKHS+MxHEy5H3f2D43HfaC6PFkutEtJXF/m4EkSSeXRjE8EVy9P5Zeb4XvnFiUB+uYhfPfNJ9re\nOI+TrV9rsiPC1pRocBMhLOliPKJxtZJKu0xum3E+hO2pM4/JxMjHidHRm3C5aUkU10Tw0htDKvTA\nenLx8lA4wfF4BTFev3vPYulUB7gkhWm69ofg8uEjfk62y1ZGc5+kC+P1WJ9f0PaNdt0ro6t3FMf2\nTnqw708AnI8H83zAytpSa+SYxKiDTN8VNyWWhyqnE90WUbKeodzKwzTPN7COLGokKCo1rRKEyImJ\n4emr9P/1rt/lOvIIx3IyVGguaCs896Cyi3KjkM9Z/qWM93UE3HIF0a51JEsiG1JnkZZW8QeS9IBp\nCxOdNa3qCB6DI5RpnV1qojj9wRDhZju21aQHtA7rUnmNEiX/qnWkpO2ZRQ5OKkfKMj9PDyQCx3Ff\nfiUpGbCGwwJKqRQwKdWQ9HUf1fv0F9YRrAJspaEd5KhMPHddUxgvcEMsBUkUWCqgyKxLotatYar0\n1pjHQUzn1CIU5lLf3C7Cp7cHxzz505nsfePDZecmyrEaUMc8ebpcOc9Zga9QTXirc8TI4EKF/g5p\nvGVyzUQ1SpXROlucWG98d07ifkdkmRV0X3tCgbJCKzP0PX7lpND/pfgJtrXOixkZzkCw6SQVFNy3\n8i01qbNI343hhetKTTZ30rwaRXOUquEsVRGzPGghRXhOoySYIhj7IsFSqgXmklovRHgGTVspoxxS\nitxYPm7BpNfym7EativLaw0ryIp26VY5xMGEFdYbxufma8tVzIcy8yxaoirudTZXgsw6sw+EjZW3\n+usPqv9a19+oh0lE/kXgZ8D/+v57mfm9iPzvwL8O/H3gXwO+eV+g1vW/UP3UfxX47/9J//6mxi21\nJEjZeAvjSYOuJyIbmic/1Tpo+3BChG9J7JyoL3nFkh9lFhVpSvk+lLWo+JIqWO3DZwpOZWw8dedP\nXXmdyT6CL7ZOl2S2G3/osBN0NzaT5b2ZuEnJreJ9nlkp0r46e0WmCk4abVYBddBw12XUBBNnz8QX\ntrjcKDWebJL8qNWUy3Og5ovNXwtXWCIuGAdOsmejtcGI5ElaHcC9YgSHJhHCjHooDeW0xE14pSYg\nH10+hw6eEuRDsBZ87Y0/+f7k9JMuRpfGLxLmW/LRgtul8bN0/pZVsOU3I5n9UtKEMD5Np4XyaUvG\nWZkTUkMgpAkP23iTyh4ao/EUZ2nsFT5GaZIzgpdNGWncGXxU5WoXvtDAKGnhlJKfaBYq+paTZoXg\nDk3uIWWqlo4ENAtUs7DPnoRHaaiXnnpXoQfc1XgRReYq6jwZVmF/QZJZ8pTXWUjrc9ThSkRQ2TgJ\nELBsNCsC0qaVObN10LMoakdOXnMjPcAHpsJF4KA6OCVRLIKTxOBtjdiNUdIrLXT1azM+LXLNfToX\naQglLf3xIhIFwpSSoDWpkFMA0d8cyvM3vYY01eqCijFDMFVCL1VEth0iaFaUr1gSo+GJek3ochZM\nJnNWVzgqA2tGPZFhUdkpS8K2fiaMbVGGTrg0mLOkWK2T1uhaZCVmSaEwqxBa97VKL/LZkj/k/BV8\nRKjJjyhLVrHCVT9TrKjMFKk1xEZtQa71b0iAbB31JHMSJsunRPkwpMAiyiSDhaYFPU7CKiFFxlGg\ngzaXRBHIIKXQv7Y17i+vHMdBaxsxRwUqxuARju6dT989eP105+3779mfntguO/fXN37+j4L90nn6\nsPPxqy/52Y+euPXOL745YKuDvqfzzXeJRWO0O392FrjDon1eQ9yUb8JxHxwjuTDLu9Abm3T2p/Lq\nnNbwOZhycHGjfbHxk0vjMeGjO6EwfaI0wLh1YBNCNyKDN+1Yhx69wpB7YKZsW+N6KWkaWd6FkZ2Y\nwtY7dz0ZHsx51rM3F/XscZT000uSdHz6jtGvjPsrr8vDplK5YdqquacrvHPbbwx70Lcr5/0smfB8\ncI6DOAZ+nqhZATcIxAscklJwgJiBE8uw76SWHEfajhOMOZYnyUlRLCrIotsihnmgGlSSjuPpS0I2\nfqM5TL/xs4gZLkUA89SCP6jVlFaN9MpWSrFfrSMB6hPCiZmVZRa+psDQJMr/nE6afPbJ/rmfCs3O\nGOs91SDPUi1I76DlSx0+GA9dEl77TOWt3Khqn1STGPAq6Itu5DXRBKA8QX95HSkiH7gK5vGrdYRS\nVVjvJXXVd7LmguyErPVQiv47vCS/msgZZFcsQfAKr20FLCgYTUm0RNYeOAbnDFqL9+8KcOYZSFOO\nMzh+MQpkIEZrxjkG3768Frjq0rlen/jR7cJmje+OA41SIQXOp8dAxZgMHmGkacGNA2hCmPLqgfvk\nmMkuj/W9KtaVJ7tVIynKS/+Iwa6CbjvPDcQ6OQaTXOHAZaswTezaGPeS+z6k7BrvFODWaqJy2Tvp\n4B6V+RQwmqHS8Civ+5xRGVdIFehZe0C8K6wA96POtnEuKV5J/3MR8rQQV2ClDoo26zPImszNnPhS\nvFSGaH3eSO1WpVaIz2Hw/q5gIOpeSUEo2MOIiXpNUtMaWtUZm1GFeSZNBzmVXdf/Ay4/bKz4z6jH\n4k/+0u//yfqz96/50z//h5npIvL1n/uav/K6xuCjGVcprbxSxJXJFbrz09joW3By50WuHEzu9168\ne0pO5HNRQ/KsSUNGVd0roXiI0Fjyv1w3g56ICo+ZbGp8PSaXrfPtNKx1bpl80MkjFDErOo0Hukza\niDAoKcW6D5hRGSrAIupVMGVKTa6gCG27lDmzZeEkaY1jZC2+rOwjda7WeZTVkr2VeT2tNkFbk6cz\ntlIOy0R5At5oomymK316ELYRs2AZmclYVBNZkoKvdeHLEbpdOaKyXQRZx4eGZ3UTHyN5ss7bVLbv\nJv9Qlgl1f8FdabzyJI23aOT1ysx7BXb6WQfGPNi6ImnMaYX0XK+kCQ+fiAofAqINNlOeI/hKB3c6\nZhsjH/xjyi/yJMqzdTImBwppnKp8EbC1ks9dUrhrQOw8enVq9xBSnKc+yFY0udmUEbAL+HTaLPpZ\nU2cKDDP6SI4IXluSR9EHLWHmoG/GJW114HwtZEazO0HJQOdIEuP1rDBEjyyPlBfQvrca/cuio5Ul\nt8JsIyiZ1QD2By2eaG0USjp37pEMtDZZl4JXUJOR0hXnGq0HLkGXOjBDwTV+g9dvdA2RSORdKmLV\nFUkTxK7Qkqvd0B9/ZHzzNbFf8eOgPWpjq81+kCOWpOBEMCIECeU95dyl0tuX5aMKh7WGaK7YAxGm\nBhJzHbTqUJkzic2KaOaLKHUuipSdFVSbVSRlVn4KwB7lNQtVZsDyX1enD8oEPYMWlBTQfVHTalqV\nUhksWZod0JpniVUuS7xjkZf/ICXJbSf8oAHaOrJv4F55ke4gvQhZPsnHXLr1ZD6OZTwX+tPO6+sd\neXsDFMFo+xWfwePlTsTg8vErHq9vzHvwy59/X4fR5yv+uKNNaNcrOYJ+q1/lCum+MlwU61fyozHd\nGK+1hnAxNJzHSxUD21UQnN6LGPflVzvHUcbjxzj5x29VXD0/GV9ujdeMoo+mMDS4ckH34oJ93Kmc\notx4Ow9aazy3hmfjYlX8eMC2GyOCq8IbjfbSuL/d0bwQOCHGeDnKE5vBPJM4B5mdeb9j+15ZVuuw\nW4btknyLl5z08fIJacb9+0/EZvg4kZbkIwrTq4JtnYxgv+2MqHtSDmofk0BHIF0w3YuIN09Ut4IA\nNCuPShh4TbaJahLmyv1RL+lZimFr7UiR33Rw7W90HcHXgVJryoK8S+3KU3e1Hd8VcuBakq/2iJVV\nWIHS6azg7AL4OPmrdYS/eBb5y+uIZHnhNCbRS0IbarTM8rO5FMxj1pRIVIlZsr8Up8T2dbANKfIl\nwM7yL0lNBCxYvqeacqOBjKQFuDVkVjQBqeszDqxpeZ/wKr7XAdk11sGcaiRIhbnSO0HJclWt1uWo\nGI6ic678tYwFSqog3V/RWuu9Pz2QcDJ1gWyqOJzDSXFUCyx1f3Ne3r7lz4Iq2pYM0nonPGltJ/1A\netY6YoJjqGykKjOtEP7UeqszGAsfb14TLm3KBjxdO3NSWZdx8vVbgkwuzfjQjUNgzHr/Zgtu7PRb\nvel7wDhPhnR8FSSbCiYXLpeaRoYrA2VENUvfZmDH5CEPdCiB1+cUzgGlaCorJREFH1FriKyzCIvO\nR0FILCA0mLMK9/SoM5DXhLEadOWbVMrm0tZJQXHEa+KUEmjUptSk13QpV4ZWlPe8Zghlx2BRnEWp\nXKrUAktYTTJt5S+l/fqKl7/O9dui5FX79df8mv/jj/4hWzNMaroiIvzLv/cH/Cv//B9gtjG1kqkf\nx+STBZG9RoEjka60qENnRABG1xpRnjhEybK2RQtiYQy1ZRn1Uis5m8CsrYIH+gjCWkmsgG8plPez\ndZ4l2C0ZI5g22VIhG7yjxV0Y2jhzFU5D6WrsBIfU6FIp3bnzLgMKmhWNZCxCTQ8ttj3OZMNzkgsV\nLAIzleEQMRki2Gnseq8upFR6/YwyHVvWRjcWblikJibiyp2sA9vyDbgH1ooyo0AzwVrRWuYMbpp8\nxcGPtuRbvZABP0F5aBVpv2zJeRw8+aSfB4cPfnQ+MzflT1BePXk7k8fDaduOn49KnCdXfoPg5+QX\nZCGZLWiSDOvsDTwnXTaCwTiUr+fJYx7c9o2w4GMmz+F8LYFtHQnntt9KLiJ1EHjNzi/2yVcu/DIH\nuwSaD0ZG0e8Srqo890ot71G/9xrCsWhC4p2pkxQraQ2OWWLiWLQ6GP+/1L3Ljy1Zlub1W2vvbWbn\nHPd740ZExiMrMzs7uxoBQkBTrQIxZYCYIMYMmfE/MGjErCUkJMSIEUyYMGDABIREIwatVomneFTT\nrcqMiszKjNd9uPs5ZrYfazFYdm9lqUSiqnx12Sgeft2v2zHbe6+1vu/3yaADtzZxFSV7Z9EIdAvn\nZRzCJ52YxZE8UUZM61yjX7s6PB35Fd0cIZPLwDXTbdCaso+QPijhTZtGTD2UzAQkic5X1sxA+b9+\n9mP+ny8/J7hK8feovx2s+K9kDen/6L9C8nJ8tYIK+dPfp/zgXyXNC2mZSSXT0oJ5Q0t04OyYepqf\nIvfCKxw69T6ioJRjDYl8kD9dQyyFX+HtGmIK21G4WQqkcEsL2UNaF91gB8kkEqkAtYUJ2zwmyBZy\nveJADioaFrlsEZAJ4p0qgSRWDh/WsYYccyiaaEyIcFwPepkq7oOkGbfj/xGeB3eOiZVguh/ynki3\nZ7O4h3h4W+oOkpApwSEvG+5xyN47Ugq9NWQuR+ikMC0TllMEym6D6TQh2fn44w/oIvStcXc5sY9G\nnl+wrhvb9SnW1FbpDw+8f/4UuUs8ro2x74ztSlvBTyd0vWJHILmcLojAvnVe3lYkGdOpkHPGbCbP\nyq025ik2/do6P/78yh9dV07vnxFxTvPMSYTNKvPz6Pw+v7vgtoefwIW2wc/YOE8LV4HJ4+DcreMW\nkp8ijReLcEkzr2ewtXHrjZqUXqPR4makOQrTUSFPx9/VE9IbnsNHwW1nc5DWWeaZWg+IgIAnmM53\nSO+k5R4ZkfFno5PKRL9d6bWGCsJayH9TSIU6I2TkdTDKHjJlJ1Do1tBDRgOhlFBPSFbqT/4B9pM/\niAOZxSTd6/pLLQa/xPUrWUdu/+d/jUzL2+M/qHD+7t/m9IPfQyRjquScaFvI/nE5uDBRMBlTrCPy\nljznDIPk4906MmkUFXggwT2HRP/dWUSMqul4F508BlUKWcMvGQUSoJlMCoLiiIO2HJONtz7iiVC8\n2IgJIR4kxbcIiCZCOgidHrbEo2Edk6OuglpMRGKiFEWScQQVH6VSFNSxiAyL5oul9k4m6D6ORlGO\nPeeY5gspMixHyE7smFYxQhnk3SC9zTCK3CvP8TF6izNUKsZ9XmgmeI93o3lkE7VeaX2P6alVfOyc\n0jNsyuzdsd4x3xnNsXlG64pbzEtamlGg9sGtR8xDyhpZWpbJU6Ye02LBqM243q582Rp5mVGMkguT\nOs0reYkGxrPlnqIHHAHHmvJGG4sNHutgxugyaD0kdR1YcuY0ZzYmHgtIHazeqZ2j4Xrcs6ThU/SG\nCMeZOh0o8yg0tRNe/BEAh5hPxpTbBVSnsJEc+41JTAPfZieZOTGzs4BKHEOALiO82G1gKSIossaW\n18WiIS5HcW8D9cirvP74f6Z+9j8db2CU+/YbXkd+1QXTz4hX9GP+bGfnI+B/+bmv+ejn/5CIJOAF\nf74b9Geuf/1v/E2+dXnOSU+glZGC1rZkpZSCUdgTtKTIU2LIjs6ODmWtPYoVjYLJPTroi7zVpOR3\n3VM5JlfqscBPB0V1P/ICUrytoXHNM711RDI6V5a+0KXxNJyXeebcNp5n4bvTxOyB4E0UXnmjuWPe\nma0AQtVGnd+uJOF7qF4O6o4i6QYW4bpGgCRUNDrTMRynpJmkgZr2PuJh1cTUoRY9dOSBvVSFpAV1\nYxz3w9pOyoEwHqaMUZFyfKpUVFMYfy00pWWayCJHngtIyuxbxSSTk/JTlK/lFJtyzrxug1pLIMx7\npqQ7bjnxlCrfyZk/6ZnVJopCHhtNE8Oc0ZWpZGRdw5fWosgsArcuMHaeWmZkQxYoEl3xJU+c1bjd\ntsB/t8a1Ki0t/LGG9OHSB+k6mBKU2xN3JRDrO4JPna/lni/NuHkmtYp7YnFFZVAwFh+cRHh/6sw9\nTLGmjVWX6F5ReDYltjbYRSlmTObk0Wl6mBpHp/mK6QQWi/AYThK4qDIdoXiTNW7eaXuiErhQUWW3\nCK89uR0yhEomRuttCE9u9O6YpsC8HxuSWkXT4KyVkyoyhC5gttMM/uVPP+b3P/0kzriE7ODHb17x\nn//B3/tl1olfdP1a15D0T/1bpOd/jVSWkBiKk1Imn2bmZxdKjpyp5f7M9XHF+orlHESy0VEPBPPP\nryGlZJonaDtTKu/WkOqGmVEcaopihnzIAkd0dIsmhkxo3+iSyZMxesGl4xKdT+8dcuby/EP6bUNL\nCh38HkHEZo4QL6mPihaLDrNHlzMmO4SZf7TQj2s0nCYX/MD3koKUpssSFLV0jLt7RVJG9xHBitZj\n8zwKTs0zwgg5sxm27egyofMUE7PWSCVFULd1VEqYfFt4rPL9hXma6fsN0chW2p8aSZRUJvZ140km\n1nWlLIXb1w943TCBeVnI5YSpsNeV8wff4s11RaqSUmFsUaDSjQWFcsa2FcmZ/baCKCkJe9to1xrd\ncnGm8wnTkKpNpzuWc+PVTx7wMajXle22oXPh1XgT8m0L+7HOiZSUu2d3pOlGq045TzxqZl432tgY\nm5JGjYaYdnIqLCm8iffPEs8mY9eM3ZzWhYvNNBdOZ2XfVtoQSllQEdraSCX8Kdt6w+qOTBmqwZRZ\n1z0+o9NMnqY4XO6V2lZ8K1i7Rkc+BUgicujSUexA0hT7Ta3hTxmErw5BpxKH2hEmfMQ5Pbtj7EEj\ntd6hdZbv/D58519B5hKhp55or35I/Xv//i+3Uvzi69e6jtz9i/8m5b3vkPNMfydhCnmnlhKqFSDn\nxKiCS4tn3hQZRwA5f/YskrNSx1uvSsibRJx2vL95OC1zTIbDHzOOs0h4oKaI06CQU8XGjOmAEWh8\ns4Fo5nw6vYslSCT2tuEcTYSco4gZLWR/LsgQyoGNjlz76PC7HOvI0bQNxk2UWM4xLYpjTEycjZhE\nmAfowYPUlji8xZKOyfnRoOk9PD160IzND+RDfL/4/kcmlEHKOc5JtMgrzIW6t0Brp0TrnVt3ukfD\nt657eKdYSamQdMFcaKMyz3cRCTOIKVn3WEfMKHvD04K1iiSlH0G+KkHw82ocycCkGsWzAklnSm6s\na41CokVUC5rBI7Q+hHGOZOFLHpnnBU3bQTEsXKUw2UYvO7Yp2RukCBeBRPFKKsr5VLg3Y5tgrs5w\nPQos5bQIfbTI8rNQS8QzGNO57g23jou++8yaexTuSQ9lhqBu9NGwmhBpobSQID6rx8hIyciR0WQa\n38P9LRgrJoPpuD8uR5CzOln1mDIdXigznn3/9/Dv/140OnEwZXv5Ga/+27/7F14c/rLXr7Rgcvcf\nisjPCOLM/w4gIs8IPfB/cnzZ3wfeE5G/9XPa4X+NWNz+wS/6/g96xymdMBL308KS9TBAC5RCWWYM\nKLcNdOe6Gx2h9Xp0VglZytHpkuOwsaQ5TP/i4c9xUA8pW+rKJJWcYR7Gbjk6wO5Mw6njRtLCTsN2\nwQnTbcohq9E0sbXBP7RELvfMLmRroDOnI9/j5hFK2nWCLqFp1fA5uYwjmMxwm0lqTBIBs0aiamGW\nEZSbsqAeJsnRGmsHTxNlGFoSSkW1MCWjFGWMkB2mImBgwynThA0YHuGpLuFlEldEj8OgRhdCNdOb\nI1oCfesShlEJJChzIg+ljRpBdH2waYzhh09sEj/X1VCZ+InOzJfCWQVrnbIsyIhOfhs9OhAKzRqa\nCrV2qnsYiTXhM7hlxl4xKaR55uXDxjfinEY6yG8ZUkzJmsGyNlouDGmYJCqZx5vj2lgEuDWaDdYl\nDIgzUCXzpQjTSKScyGXhvjs/6sacVpZSKF7pIpRdSCm6b5eUkD6obqhGwdPNabZieaLZGYAlbYCj\nYuBvpaIOo1EtDtqn4ZxKOiSAnVuK52E2Qu7hiY2BWaCxT+KMSSminETYx2AnYXqiy84zn1m8cc4D\n9VjDqyk3k2PTEyYTVpyUf31iml/3GqJlRuZMM2U5z+TTKSarCmVeuDw/06xy+/KK+QOjh7zJR8OO\nMOzk4eVQD/kj5hT1kFDZYM6xwbsbWgQbiYkI8XOc/eiw4k5pTpe3IZ6NWgGia5ZLClOrlghafP0U\nmVAV6thwkYPO5QdgIrLC3MPYbRp/Nz9AN+CMFAe1gH+ENmNM03HgU+b7E64JH53t1vBWQ5PeO77M\njLbFodChnBdGtTgiTTOpHbS80wkZnV5D/pMo4CEvGmmO3wELutWU8bf3d8C+DooNkjhlnkhLYSmZ\nfV2Zl4Vt20hJ4nu4UFuD1iArecmYV/RyokyOrcb5+Zl92zFdMGtY7WGA3ityOmNPb2LqpROpSNCv\nHLanG6kU5g8vvP7pTyOeIvmB2Ve6Gb5ttBGNj/l8ovbBrGdsCC9/+oBkRRX8a4IANs/0WpFpolrI\nbkZLpFPjeklom/jqsZG9cb67OyK2BslLUMGsM88nWK+RYZeBvVOr02tFc2K63MXnpRE7YEf33Q5U\n9X694Yehe8qOlhOi4bmTIBUcsQhBvhq9470HZlgyepIjZHfG9x3UkXRkdE0J8cTp+RzhqkUD57zW\nYy8RhmVohqZfLw74172OIBmyRjxBFiTHNFgO+Ms0zeF1tZDR9dYRF8xayMMkzhguQjKjEdTV6YAw\nDDzgRw7gSA75VeaYdHOAijymNsVg0y2aGF6pnTiLjMhjQg4iL862NiQFLdO9wSHQE4v9Vd6CKpxj\nohQHZ3/rsHePcOw45R7yZmdo4S2yPGcNGa8ZtQdpDZEI+s45GreaSKqR//WWupYS6iMO1Hl698+m\nR2BqErI7I+WQ5vlxFknhG5MEo4HnQKHnt83vLDAKY3SSZroH4l4FOJRHw6IIFI2MS5kWpjywCvlU\n4veg4HTsKCCxjqeCti2kjJTodR/RMr0eXs0psW3XmNjIwExxP2b9o9Nxkg1yyuG1bwVUuF4rEEHb\n4YM2mug7C0cVwXfHLKFTRyYo28TDfiXLoMgcAbTaSf1P1xHSBL7H553BasSmjNEjF1AnILxkIjFF\ntKMBmNwZDOq7Yn3gOlHSOIqbAJ0px/NB2FSEAGGJZFI5wnk0/LxBiCxRkKbIgUox32Ckgg//OUlp\n+Me9hk/rN3n9ZXKYLsDvcswcgB+IyL8AvHT3z4H/CPj3ROQfAz8C/gPgxxwGSnf/QxH5b4D/VET+\nXQLl+R8D/8UvotIAnBa4u8vMWihTYk4pgmSts3km8vAKIhvFNi40bltoXo3wiqhrVMDJObuwemCh\nO4ZJVLrdg3STh3OXnZKNZJ1LTqzu7BYp2u3wBqXRuEfIk/LQozvke6Nq5gHnLNBaxWvom4vm415O\nJOnosXkqIQfUFJ3OpAkfGt9Pj4Pr4QFXgTAn7WRNx0Fp0MzYtw0dxotjKmDp2HiP3IWiUTAkSeGh\nOMg5muVI4R7YGEdhRGDV04RKx0UoJHIpcQgwZ4wb0oXN4ZSWkG+4I81jjCXH5E6clEJOaR4gDDuM\nEWpGl3gJttEA72QAACAASURBVNaCLKewqFJzUNpycpY58rWu+6CkHOSuAS4xcdKUAoEtSttW9r0h\n80RKQafCEuyDYR3LhWsp1BTwi94bpR20sFyYrfIC46Ubl31gmrjkwSJOHxpSmiKkPvFSBnecoApP\nUhE3pkMCydsQUpGYMLhi3VBKJGVrIVdjkad4rVwxWdm7Qx/0pGyHpCYj5KTsIfSlkMkK9565jg5i\n7O5HV0vCizIy2ftRNEcHKalSTBiaGeqsPpCUyKLU4SEZldBMF+HorjlPQ3Hu/qLLxj8xa4jeLZS7\ne07nM6dzYTqfWU4RJDr2ytPjTk+B3ZV9Q1vD2ggQxJFergMkRedXjTDBYiGZcdhGY1Jl0UQlvXu2\nk3WwEpK9IhjOFrsKDMhdoYSnQFyDVuY9TLdDGdqQEdQh0Sim9hRtX6khdeoEcEZkEElaIbsVIk8F\nT4jVAwkrUCZSb0gpgbAfxqidcX1C+ts1Js4GbpU8xdflVLBeSSnAFDrifUrJ0ZIZ28D3CvlY2XIC\nnUnW47Ammel0wcZOH4PtuoasJivlPFEuJ+o+YI38pbfd5HzkUOmUY/N+B6cwvMf6p8PZXlbSgaGd\nTwswMFHK5CzPLpgPHl9V8nkBUkhu2pHHsmRsNSjK49dPcLthpzsGimlMU2pt0AeaE65h6DeE7fE1\n3gLso7mgo1HyzN5CvpgmQU93ZBus2x4Khm3C64W2v+bu/h4z5fV6PXwuMXELUZagKSHzROmD3gdp\nWrAxSNOE7ZEdJ4B0xazjRxHrqTI2OXwKTpomhoTvqJQ5oAEO7XYDnNEj1JOUyGmCyWA4+bzgclDz\nZMYwRNMR7itoOdbgNpAW6/50XphyoYvRemd/vJHn8y+1hvzW15EpU/KClMJUlJQL2QpNO2LG3jsj\nx4RFPaBTY4ygUroy1FELVH97m2vj0eCwNJDDg5pxJofdEskV947KIB1HN82GYezHHTAzUs/kmTj0\nEwTZwcATZEt0sYC5ICGjdGiHtE6OQ2k/CgexwRAnu+Ian3UUSgnxg2anChJTJ9GQskday8DaBgdp\nNJqAAIOSUvwZAi+dEIYH8MZE0eQHkTQkeRCN2DCHZvSIcRBJJAm5r3nAWJz42WUKtPow8Hb8PgdK\nOJkEWEMAPQpPObxieFABbeO2WSiNBFKKGAEnkbJFXpkY2z5ifSMkgW5RLFjWkLCq0PaO9EqXGU0p\niHUobRiMHn53UYZHMWy+4T1kZyKJ1AdZMtX6ITl0RGbSGLQezX/xjPfCziOTThjKjYoeRXEgVeMe\niIQ0Og8P+m3K8JaSOfygBkrICsUOKWconzoxVXQJqIgRz4mkHPc4Cdba0agLGb8f55GU3zb2pgCi\nWARbB6A1pKk9+mEoiep2pBsIKcd7MpSgNyZHmP/iC8cvcf1lJkx/G/jvOXqkwH94/Pf/DPh33P3v\nisiZyDJ4D/gfgX/j53IPAP5tIizuvyMMGv8lgQD9hddHdwt//cULugs6J4okZhF2r0gbYDvVKg/b\nHtMTE+6nzGPv7McI3PNBY5HMZs5FKskrky88hUGGZIGolAQmQqbg7GwWXYmZCZlnnsZAdKIINN04\nM/hrCidxzrnx0DZuVfimnyiZgxikYJ0h8ZaaRKdaFCYXZBCdKCEIMoeeM3Hc7aRYEs5SqOrvFoA+\njM2NuRnfx9E0eCPC6lB9DnOlO4WBe0KGH52SgTiUnNm7oSmQDuc5DvjDQlSW86CNTGkNUmHbGicx\niiqmhZw3DNj7zkmFUhWZClhsEoOgj0lJDIN60MisNoYMig/6UFZgTmFgB3gsnY+u8DqBuPHkEx8s\nwmQ7D3LhbFceKLgnmm1MWUiW6a0zLDJRkCD9tb3FgjElrHt0SvZB9Ra+tF5j/I9Qe+eK8bVnSoFX\nrtArD+MuAmalkBjcyMxjjfBQiVyq5RBIEQBYvHtkGhGTR3EnZZhb4+Ie3a186Mct0TU2wUkVcg5j\nqkThWwYUIGVhUjgPGAzWETr5loTZAzV6EadZo6ohJXEdnS0liqVAexKF4kyhpMytw1MavBlOpZAQ\nUmp8QOTTlJ55UOOR7S+4ZPy567e3hnzvI+6/+wP6AJ2UOSUuWXgzJ6ottNcP+ICHV2+ObpiiU5iq\nuypJgvzmbqhbfDZueN8pMtM10K9tyEEFisw1kZlOZdJ4v7AMJaHWGXJCk0OKQFtMQzabnV4dqmAk\nknuYklXBwgej/QiBxhgqYb4/plfJwSTyK1KKxgIAUpC3/pcEIgVxoe+DVjvSOjMnWnaQSh+BIXeX\nkFqYYXS8B8Vr9CB9ldOJsW74iJiB6W75OTlgeC9cE6wVyYnt8TWpzORS4FJo2xqeouvGdJqRvSNl\nAQ+Ag9PJp8x0KrQK3hqUifH0BB7YXHqEtcb+H1OsdVzJttDahmvi2o1nH9wj7rHJt05vIUGsa+Wk\nguRCX3dGG5BP8bUCbDeGK8wT4jtGIdWNXnfQCepGOuRpdKONHr6iBM2ddh3Ipu/WkBoaHOTxAUe5\nvXnAxVnKQkvCkgq4se7jgOs4010JTPGSqWtkwJkqA2PUAAjESd3wlEnJY0p5UMnCIwJaJsoykyXj\ndNr1hopiYpzeex4eDU2MumJdmd87sa1r7ImqyBwHUsmKdGWZM70a621jv94wKUwHhrHOM/l0ZvKZ\nq2zI/isBx/zW1pH705nLhx8wzClayEmZRdi8s9ZB8iu1N251Z7wFAsghSdSDkBdt0QiMdYjI6kYZ\nU2Q1Ev5jE4KgJoKnme6dYv0AQuQoqL0zfIqGZIp7m2QiJSEXoW0DN2d0SCmg7kkVhh3huvJuHTEB\n8WAZejqCWeWQaqJH9wyQyH3MmhgSa6U4WDfaIZ+bdWYkcI9p25CY4MqIM4rJIbcjppxjRMgq5u/C\nsks5pHd69B6RkDbaQFNi2I6gMRVLGdOOuDN6D6WPcRRskbfpEpN/LWA9H+9nRno9yIQef34M4jgg\nYEJLndQnhjdocPXO6RTqBPeIgRiHDXT0wYzQNUXjy0KaLxLNbu8VM4WSQs5sUXAObYhnsH40gxw8\ngN3dB5KjaUc3pGeS12MdOUAfh7SvpR3HKJIZKhQXcKOaHsRXR0soHtJRmBYxDPAp1EbqHJ97WBeS\npShaowsQ9FGNBomKhD9bO1YbnZBrJj1IoSnyl8wElUy3KKhUY415+wLjmSlBH1BtMEYPFoEPOH6W\npEzqExX/0z3tN3T9ZXKY/gc4hKr/31/zd4C/8wv+/2v+f4Ph/vx1vrxHubvgtTKy8mgTm++c1Tip\n8tRmri9fIaMh9sgqJ8Y2c8uJbjUQwt3RtqHFaT7xyuGehQmjeZiwkxSGDkpJeEo82YEBz04eoJZo\nI6p2s8HmkNPCT9kp4qSe6bYw9zBSuxYKjaKJi0D2xpoHzTI9Z5TAg08uWBrMrhSHfTnIMxp5CZOE\nNymlQRsNNae3kAmW8UTahCl3Pht3dK3YCKy1SjsmDo2eE703FnXOsyFDqJrYekxoGJE9pEwkGWhV\ndEnMwNIGn8ydXYVX6oye6B3u9AnziT0ZqQ1yiXDJ022H3NAivMJ5bzK2q1DLBUsJ9RvPCZP6xz6T\n5ZEfrYk3bTCfhbYVigovNTP3K9/LBcuDF1PibJWf7hPXMvPxuPJq79SUWF49YXPlk9OZ/2NLPMl7\neN3oHIjVrKTeoutke4A7utNb5ET5YYrthxRRk9H3kC7mrHxbn5hnZ1F4UwebFlQmntuNF0TIX0uD\n5I0yVkyUnUJP0Ym2VjlZDPYvGhjUbpGL5SVRZYosLE/kSWkWi53rYAZynhEZzN7D2HqM2KcpOtzF\nnGuOXIQ5G4sl9i5s1nkmJTZNUR6l8KBK6oMhmScGeRZGU64lyF8ZUJ9Y3HjqiQdNJB085F9uDP7b\nXEOeTxfO9wuPW8MFqjm+b2hKFIfNJ15+9scBEBhXss9oz/QiuG2R3SYSBZQERQ6H3OeQjqQpDqXW\nGclIUmhLbLhKoofZIEz8PSQkyXbcwdKMyxWhUB3EZ0T/1Cswm74LbJRhIUNtDnM6zMqCl+gaespx\ni4uiWtCipJxIecLFcPNAYw+n1chD8f2Gtij89wh4YnQOubAdcp+O5RS5LQqU/A5Zu99uAEitQWnT\ne0QHtjbSeSEvE+1x5fKt9wJB3iujOnWv5LGTyxJei62j80J5dibtMHJ0RHvdmU6F6+udeVqCzDdu\npFPhMs08u9zRfOfLz79hf7yyfPge/bqHD2cMxm3lg+9/SkL41ocXHOfVy8ZI0PadV198w/myUP/k\nNVYG3/7d7/OTH/0UzwVrG7cWpC1PivQd7WB2jUK1Ge63I+Az5EtiBpqCetbgbSbNNCnL3Xuc7k48\nvrqGfFkL6onzXBgW8QdlbzQMnQPBSxGmtLBdN7w31AaX04nywYX15UorC35ZQJS+1iM09QB4QGQN\nqjDNOaRMBy5cUqbVQZkumAlJovhqzZkvCfwFdd3wYZzPC8afAktuW2eslbM7T+YRpNwNyoTJoImi\nfki6bjtrG6QkPB0RBb/M9dtcR+6WC8tyYq+ReROqog2ZE3MWbvvEbX0Tcquxo55JNdGKYl4pFiGd\n3nsUG6pxwB0TTmTPiIY6ZqSgofYpihX1FO/EkIOyZ6HeOLD/JhmXDXqmu1C78JaK5yWR3UJRkmJS\nUAW8C0xvi6aEZyE3kJyDIqpHESVvD8hH7gqB9E/m9DEYCPQd6eDJWCXD6O8Q4aMEgCGPwciK08Kr\nlY+JmQRiGgcd8XvZmCIb6Z2XWzATlnPBRKGH16ibk1MEIzvht8sGFCXtzigRqttGJS+ZthtZJkwU\n8Q0viZNnTtOFwc7T00ZrFZ0KjiFNAmTgndPlDhV4dlkQGTw8RRSHe2WtK6kovm5INp6dn/P6esW9\nhDeYICx6VsT7Ad9oRJ64Y75zwAkxsXdqAFXF27H3JiEno+SJkhO6h+RRJPajJYWv3TQUTBGafNBT\ni6BDaX2g6sfZJqElMVqAqjyHN156gKlUAzOflEOO6OSDAq361kuvDFPKaQoYjAeAaoxAorvN7wjS\nc4kiW4cejfYIgT+5sVr4SoMNoQyJUHC1oMym5rQDVnHTf8Ileb/N6wtVsmWkFIpVuu9s28Z1u7Gu\nlaUe6EIdrOVM3Ro57ZwZFA1MKuq8tySKDE7WmAW+7E4uheejcpUSH0wuiKR4KA6Tdx8DtfDQDBlk\nT5EmIcIYnckHluVQsvbASia48yeeHDYykqLjexLljLN5pxRF3TFrFIuquyu8txo/SysiQh4RTlrF\n6TT2oTyzzDPb+XQyPpozX02DL6sy5Yof2VJlKgGayAHIuBfjO+cIVl0N1im0qrOE18XlCIAbA1W4\nmwe7OhdTlunK1RZeaaaiqA9K7uSW+CRtzF34SUmsXfgkC9c0+PhOGJuw5MRPnxIjC9P1iTEG6zTz\n3CunOXGVmR+usFhjzkLaAR8YMx+XgcmJPy6wMrPUzuh3WDLsuvPPneH37nd+vE9886LwRZv4RoRP\nRfnj+nXQqlSoFKxreAvIGMbSD/3wgZgeR8d+kpA6Wd8xDTlMa5nPe+JubfyN041vJUX9ATXlnCsv\n1KmWaGlQrDNrdL9uo9FGjK57yqRk3AmRJyDGbRSKlNCmWyKliYGymJGjzYOgnDQmG6LgcqL3kH/k\nOUJ6u0TIMaPx6JlKwlypaZAjHCqerWJ8r658Uib+SJR65FW836NpqBiNCTFnLoNPdCB0fqc3JD9D\n/motG3/m+iIL826IZopVWhu0x5Xr60fay0fwyGUTH5TphLU9Rv8jDPDuAx8jZBI2UAv6UzWnTIXs\n2zEJzpjMiET3LQw8gz6cbM6QYH9bFcgDV0FYw7ztjqYAwkwHKtxGC6nGyEh2Rk4kDfqnm+M5/AOR\nXBt6cGeQulLHA32VkIISBvW3gd1iJbJ3ivDsxfu8frxhu5GKR55Skmgy+NHdA7Jmnn/4Aa4RR9n3\nitlgThk7QhOn+cR2vZHnQjotkDOLJvr9FKQpBUZ0xsukaF+4nE/Mmnk939jXGx8+e583T2/4zvc/\npV4768i8+pPXkIWnh1v4dpYpGkkfwuOe+fKzz6N7nSPEVfognRcuL854O3N9umGSeLzu9K2hGdaH\nje/+7kf88//S9/nRlytPd2devnzg6enK6f4ZT199gcMhjW5RME8putIEyckJ+XGSkBZFHkkOE3sP\nZUJIvpV+vfL48MT44H2m0xR+FpT5pNzfnY5YiY6NhfOcuT3cWNdGr4LPG8s5kbSwzFOEns4J3p8p\nLZNL4rY37i5nhgllSWQFDLoNlikmVmEUV9ZtAzHunz0nqdK7U5Lw+vGJbh1Mg+YH9NbJy0wqiiRl\nMuF8f8/Dy9e03sklseQC5zPcnsiccINc4HJ/CuhHbSznO8r2Ja9+GwvAr+j6RpR5d0QKZVQ6A9t3\ntscdX2uQ3AzASKUwesWn6Noj4eHBPGAD+OH5KOzemXKmjBpSsdjFY70h4cmDQjs8vDzeGNmRrqAN\nV0EZqAdJTiUmRqWHBM0k/Gw2lJLAKLHHZAmgQyrHM21IdsRLmPFN2cdKeBEjigA3jCMk3QuKRw7R\n6cK11ng/1UN2r6A5Ia5Bi8tRmJ+XEyZG77EG2jBmiegOlCgOPQr7khUj9mZPjg2JUAWbcDopGWqJ\necokn1l1p1nnWcpspfLi/syoRp0Ob5DA7mv4VFNi0oEvhc0qj48PgX8/AlvFAv4wnwuMxN52Bom1\nXbFuoMZozovnJ37wrY/52Zsb29x52ivNGvM0s66Pcb4ywSXCjCVFgapHhIcTTZZMTJTUj4kOAxs9\n/FEePvfRG70Cy0zJ0YxRlKxwWoLk7AMoHt6o3th6PD9ejHL83CkfBEVieqejIJqoOLMUTATJhyxT\novgqmt52hpAs9BaQojnPR+RGTESvtYa36yieHCAJRvg7RYUJYVoy222P2BkRiiqeMt4byWd8QCrO\nNMczkHunpAteZm6/wff+r9TJ52JOrY88vN6p7crTm44Mw+tKV6W4knywZkFH8N5365yycofRkrP3\nmUfpVI2MEFdHJuFiwuwTqwW5hTGFHl9gOk2kujIwigx6ds6eqOJcjwXFRZmHM5nQckfdKRr27a7x\nkl/cgSm0u3lwsc7MQtGGDmcW4aOycxZn6o1pcZLtPOpE0cGpKNcdhnbOc+K0CHe18Id749Ibr+XE\n/TnzTRVOyxISvGlixtFJOemMFOWb0WLSoInkg9TDCOkpMauGRFEMyYkPLPIO/mjvPNfEZRp82Svb\ncOjOt3Xn23kiSeOGctcq31kWPmuJ50n5Zk18qcrUjLvivFDnJjmM8Si1z3w9HCTGzvO0sIwdG3Ca\nC29657OSaWME/cc6YyoYG0/7IFni718L/+v0ATcz8BxhebeGe2chk+dCnxy9NthWLiUQ6NknCpWf\nujMOGdJOo/sU0iuLXAdkRu0J8uBe7hi+0zo8V5gk0US59QlR4azOJzQ0ZyaNPAPM2D1Q0q9cuCG8\nESX7jMgRZAwh3SjGPJRNjJ5ANUNRJA/a6IjNcEQXl6J0czrwmKYI8vWdzYVNhM0zLhEkPDnsOMkn\nmgWRaUL5m2qk1DlrYyWzS2Yx5WeW6WVwb4nJPTDtkhi28iL/VrDiv5LrbAFPuH3xFevtBm9WGJ0x\nenTBWuQPDUDLwHsmaUc0M3psdCIBVtAc/z66IicimqBN6Hzk2/QIZBRAzhf6rTPpoONMaoyaDmwu\nUWSJk0YOOao56s7uhMcxp/DAOAzJvM17oRjqmSHhQ3SfuD9nTs+eM41OSor3C7uAXRv3z2ce3uw0\ncZ6fCi8+uvAsn/mD/+0fkeuIouC0MHpHpymaLaeFNGXKeWJKM7JEzpfWnaLKnJVtc5iEiZnpVNi3\nweXFPakk7i8ntjc3vvrJn5DSiefffsHrl0+09Yr00M1/+p1v08YTT3uF28a3v/9tvvriNcuzE19/\n8UirjdYH82Xi7r0z9WZRpC5Kvw3evLkhb1bMnNOze8a+Qu9cPnzB9enKeDVo2xpdWIT57kJvlfUp\nSFk//MPP+cndPX2vSAKG8/p6w3yAZMqpIFOmPj4ha0NaeDdSyiQRNh+kFgZwOaiC4oGKnnxQNVNs\ni4lROcNobG/ecNI7yrJg2VhvoLlzmiY+mJU8Z2ZJ+HsL3o3W4gD2ukPbndu6UeaC7DuMkE7328q8\nnChJGWsLel9WclKy5AMnPQHhxbqcT2wtusBjRO973xq1OgXYD79n0cTlPnxl7hK+vvnEVAov3nsP\nyc4yp0A2u7NMhXWtaGqUaUZl4nxXqGujj8Yyp9/WEvAruc5m9HalPj3xOCp+C7BF75WcDMYRhGqg\nUwObEGpk+biEJFfjXukRD9KbBJHWnE58PeoUi3wbEdA80faNIsR5JIF6eZdz5RAyuZFoOabOyZ2a\nDrpecrJGNIv5gYHXQ6JJBMMqIdOdC+R0powekyafj3BjYZkSdRvsapxTZjknzix8/uqb8LpJBLW2\n3slpjuKnFFQcLRGvwQS9O8kgpaD17kOQSQIIkWLCkD0w2EvO9Dp4vD2S08w8J/atxTs6nFQS5+nM\nSI29V/DBi8uFh9vOlBPXW6P2iOGYSpCVRzN6EVQG1oWnrYf/U6CkEr4fM8oy0fpg243R+2GFsLgv\no7MfeVRfv+68fKzhY0zxYVxbwBoCdqAIMeXiAEK4BrRCzdkZSIs8TBmDcJo5Q4RiI0iqth/ryAlG\no3ehpBJnOAbdlK06U0pcLqFKmCSjesLN2cdg6421dUYVqg20p3e+peFBPVaPSAfpjnRBspIPzLnK\niKacDFClTCXori4Mjcy61gfDQXtkPg46mch47OYgkTsa/rfEZZlBjJITPdSY9KK0Ckgjp4RSmFLC\nNOPWmMpv9r3/K1UwPf30c3h5wWvoV0/eg1A0Z669cZdnvj4Q1ElzmF7dqcAaTmlGFnrv0ANvGc+I\nhP9HhDuc5pFNYy1jtaPtiQ+Lsljo2xtK2RsPOtNH+G3UG2dx7rKQbGApUdVpJIoKnxbnuTu7V64d\n1hZdmm/lR953mHJGU+fZHMnTr8tBz8mFrSq/MyvPls58Vra28Nk++NmTk+fO711meh2ohBzjPsdA\n18agpE4pmWKN+6yMvTOJUTQHpQ746zNkdtbmlDZ4lqAl4ak3zDo6On/rNLFS+cqVpXZKF373PvHB\nDJ+1lR+9KqCDD+Zn/NHTDZsS32gPTDZBe0sKX9jEcEg9tKuB9Y2x6pIX9iSsI6Qhuw1EKr4LYzh2\n20lp0LvyvMdG0DLUdee0ZyYaNxU0n8Aquu6kSfiw3Xi2Cc/mzvTM+KYLH+aJL/sDH2rnozbxyXlm\njI2fNeUf7iuT2DvPG/2Bb58zDz0x68ZDdz5flW9qGOkncYpXvirCkuIlPyfhPXWWHMGNyQ33wfti\nXCzxOCauY+XRC1nhZoPznKh155yCfLYoTFa5jpmHquQ80YHnsrBIAz+ojoRB+MHgpAuuOwsxRX2w\ngGSs6kguvDJnssKTOurC5Ceq7CTNPDfnjWV20Xj+XHmeIpixmjNbYNopf3UPO1/84Q+x8hTZan2g\nPmi9k/KMj0C0urYIEh4hQURguAeiVxQ04xKEQx2GpoGaMIYwq+A18iRcBG8NrYL3N0GjHLBkoVHI\nNkJWh0eItozw3ZQUgYEpkUYEypo7aZ7J84S3wVhvdE9R1CfjblIudy+Q4nzwwTO++uqBN7UiEqbe\nem189PELPvnePS8Mbo+dH/3wC/74658iZeaf+Wd/wNPLJ3a/o92eSKPHAbAO0pyY72bchOm+sF03\nNMH87EzrIZ/59KMTOcHDl49k4LsfX7huncfVuX7xNXVtfO87v8PujVevH/DrDR3w7X/6e3zr/cJn\nn73km8+/Rn1w/vBjfvR//2PSNPP00CnnC2BY3alTYfuiHlJjpe8ThjDPYf49X+7oKuRL0D4fHx5x\nO6ZgfWfcQspa10Yho2MgxzQqNWG0iolTTktkX20NmTJpF7JnvvXhC1SEN083Pnj/A7746ktenM68\nXAuffPgho+28/PrK7fY6PBjmQbUaO5zuKfUWsAXf8e3GNz/bIYesMSXh6dVEmjLbRx9wviQ+ug/5\nShKhTIXaO8+HcUtOzZnHL5+oAnnK7OsD87ML68MD7z+/o3tn0aBurXtnrY2pCIOd+/mEEVMCDnz9\naPC0Xpl0IkmKglmcbQNn0BrolKh7Jc0z13Wljo0kZ/a6s/WZOcPWOhRj6MA6SBGWYvi+U0phupt4\nePoNn3R+xdfDyy+RFtJFH4aMwfBB0Rm3iN8Ysh9E3YlEi3ssHgf8pBFWq3FG0eFI7qgL1WB2wYfS\nRQ4JreJ7w6yRpwAMLKpUlKkaPaeYQHi0e0xDQh4kvkTuDhO4K2UK35OMQR89Dqca/upzUYoWUOd0\nPnG7rdwY6KhxkG7G+e7C3V2hPhPmrfPqzZWv6w31xMfvfRhFsSkyIhQVoFlMzVNWcCcXpfWKKpRc\naAfo5oP7w0Ncw/JwngrDB+vutLrTu/OtZ8/ZrXOrPUKWDd57fsf5Unj15srTmxV1Y57v+Or1a1JK\n7MNJWohR66CqkFvHCBJg5E0K5Sg6p3xhpJjWucDejgwyDGcwasQe9DFIx6RGFNremHKALMyckoP8\nZj3ADvnIyXt2OqEX4VYr9/Mdb+oT5zRza8rz5TnWK097Y92ejh3eMBGGNpb5goyKS4SM923jsXWQ\n/QDDwKoha2t2Yi4ZOSunt14jVZopc4l9rHbYt0YfhialWyXPE2Os3OWFJoNJMy7G3p02GjlF6ucp\nTWiHt7hwgLHHObdIOUjRkQmKZUQHYwiaE60H5r4TFgbxmS5G7spUQrVh0umHrNckkTQQ4+qZPJ2o\n6Td7FvkrVTDRIZ0yb5oxpx58jJRwh1ngYTScxDkD7ugURv7ZK5tPeDeKb+xHQGPGuShMYiSc4sJ3\nFucbhGrOegTL5WS8l5RkwqNnkiu6wDQG300d7cqjNrIkTjmRNWH/L3tv0jRLcp3pPceniMjpG+5Q\nVQCqZMLnxQAAIABJREFUAI5NtmgmmaS1ljL9Lv0ZLbTWorWQzGS9aZnYTVOr2RxAEkABNdx7vzGH\niHD340cLTzStF60N20DBjLG5qzt9menp7ud9n6cpIXQ3ykaNUSqC8lkSNlvHqVaWBrthwCHMrZKX\nyN+a8FQii3iSObw6sofvi2NTCzOO6oxdBSIonj/NFZHGasIgcO89hwDbKmxjIcjC5ITJlO0uoxrw\nTjiL41LAtMMB3qfE6IxjLnx9cdyMkdEJ3+EY48CcK4+r4U157xqfTpXvl4Gn4iAIN86xDZWva0Qy\neDxBFtBGcL3iemqdgrJJiVwXNARivbL7W2aInhpG1CvOOobWdAE1Ptt6PmsVQ/mZVVbvsAIJY24z\nf5ACr814WU/8SWzMk5Ax3sTCuBSKi7wiLCr8+3XhR9vEr1bHh2p8bQuLRhQlihFYGcOBua6IF16q\n0qxyqoFq/YZ/LpWosHOwCUbLHjPh3zrhqMIe5TY53sZISv0G6p04nDO2thCcZ7KVWQE38Zqh2USw\nhpLJqychvLiZXfGsztj7wMYZLyKcmlF8IBC4ZWbjA29c35BVhNUGjs5YW+IosFg/JLfW4yLOugOh\nuAlVYSsR5xpn10u3iuMbMT6oYxCPD72z92jTP+Yq8A962qrI4PFrpgqd7OU9Xhq1QZBCaa5fDiKY\n69NNj/bCs0KwyuKlX7o4w1e6tuCKBx6GdMWrGjiPSc/5j8OGUrR/KRi0bd+0SOvS1nbtK/qYOhBF\nlTb0SEZsEMRjdeHm7pbdD95wyQvLOXP47C3OOebTkXxWfv6rF9bXJ9QE8bF3Upzj2+9f+O7jK+b6\nIco1j8Q9fhz4i7/5ZY/iSCRNE2G3Y38YiObY7zo4YOMTkze++J3EY4lsg/DUerylXlYuzwt/9JN7\nonM8vRz55hcfufv8Demw4ZKfiO92HL9+oBzPKH0K/s1f/A0fQ2ItBeccIQ6kjeP07NDc+w319QKt\n9njSUrkOtxmmiXw8IsNAppOspBl+HHDjAL+OwlnrkZFq7N/eE3wviD9+9wnxRpt7dKnmM7effcbl\neKZcFj5//5aldsLh3jXiqhA855opc+EXf/03vP3JD3n4dCSfXvj56bmDVLTHlAKVNOwoZel9p3K6\nIoNPqEUQwddCabX7u1yApaHnzC+ffkYz469MSePE/u0b4qbfQr/bd7myWzK7NxuWS2G9rKRhRC8Z\nrY2TX1jmlWXNRBdpdUGIrNbYHraoz8xLZV3WfnHlPdMYGGNi2npMPSJdeF60IuIpJZPXjnxfX480\ngVYjpIZo47gstGlHcyAzBJP+/s+F07ziYgAp6GuDy/r/+Tn9//vTrPvU/KKdvip9HXEo1QQs08xz\ndaeCT2RVgvV1xNRw0n+v/BqXrR3VHTGqODZD6tPp2lDf/yAzIcaAaqOYEei9JLHeH5PmrkqQHtsM\nrpPzbOzriOcaLUYZp4Eh7lnzTNHGNE79Na8rdRWeXy7UutBMOjhGepfmeJo5nq8OOEDM4WRCvPDh\n+QXErjALj09dCxBMiGPAS2N0kdELm+22d3TFMWvhvHRAyloqn91smbzjcbnw8HhmsxlJBF51gejR\nS73qQyD5wMvxhcvZM9fu/AkxEBJYEbR2qIZKBfSqbWkdKmCQYqLpBSPQusGVav39ai5wzVZi0msd\nZjCNIzH0WNrpMneAVwe+oW1hO+4oWiklc7fZdSefNTbJYdnAB4qutKp8mj+x2+85LZlSVj6sHzrV\nuYLR3yeTm6iaGdRR3dqBVqI08/3Ap6VPoVzor3IFCjyur6g2PI2YBsZhwqceMd9uJpqAc5UUPc5L\nJ2+6QF0q4FikoNbIooTiUc14iaylEYeIWWUplVL0SkT2BA9JIikKFjsAqKpD6wrmUWlooTueWn8N\ntTjMZzr3udJqxHwHBfnr2LSVypx7NBzfu7Fa/6nD9J98jgibJvipIW3o4jB6wXpP/0B7K2TXDyqt\n9VuTySrJXajWN5dgRJf74SIkPhsyyfecakXAPF6VjTcCBs1zriuHFNlJRV3iUgPihVU8S1j5Pbdl\nDHOnq1kijI43BByVH41QnXU6ncFZwJxj5wYyCqJsQ6AmY7HuDvB0qeV6jbAGjCwjUZVRwUVj0HZ1\nwCSmsLIgDBjhWp57jsqohoSVORzIbuGDDgzV8KFy64xUYPawj4GP3vNwNpoNfK+VcxnIojxn5VfW\nb86lwsYZJ1WmMHB0ymCRasKDRr5dBWue3CrJddlvcoG59A/lGAKyzmyCUdSYy9o7O2I4Kdy4gUt+\nJbcIoREVBu8grjzXA9k52lr43a3xeHYEv3ITlF+2xJ+XxmCVt4Pw0xnWsLJpkWMLOB+4u1RO3vjR\noPj9yM/PnkUz78QQEwZZcU2ZRamypckL74dELgveGYcwsveN17pwLo0aUh9de+MP08BDdfzZ5UI2\nz4Lj0uD7NvJBZ363Rcz64fcQKlsHO38hkVCpXKzyMSde3ZmXHIkyoU6ZvTG0wDxAwPHcHEcqkcZW\nInvXSPHELY4ng0bgqAOvzvNsQpbEkymmjowiLuJCR852B126ggSEv1fn+b/3G5iwOHq2+NrTuLjf\nqmXjP3r0SrfTAMF6L7DbyQsi6WoW750erm6UIGDaf50bNPVEyQQiSylIHInB4aInNeuYVVOsKBLs\n2nPytPMrbG4w017yrhXnAs07il/Y7N4TZKWsCk1IdweCC1Az79/c0dKv5dLK0kDVuHv/nqUp1jKH\nd7dc5ESbZ/KVlBZCQK+SXLzDDwnTSnA9e14WwdbGMO2Ju0QpjXD98gzJs5wKfoEUG243snj48Nip\nlt4qb24TvvRy/+ef3fBtaXz/9QMmjvMlw7lPqc+vC3/7V79AjwuYIRLIlyNhs6fklegCFSOXxtN3\nn/pNeVXw3bkRpcudHRGfHHaZO8q9gZ5mxAfM9Rhj2m3ID0+AR4JAgzgkaisseSH6xHI8c//lO+aP\nM5mV7TRwXi48fvyue8vu7vjwq29pYwXdcPYO72CrymVZePdmx/i7X/D1158oueDDiAwJK0t312hD\n/C1rOxOHAZUVHNwf7jjsRp6fXlhPMzZMUFeQyu998QMeZuXDt78kWCHTy+3VPOs3XzMdbmm5MR+2\nbPeJu20EVXafTaxr4Pkp8zIbeXAcPz2w2R6o2VCXGcYB1UZMieU8s86Ci4ExDmx2ERkd99uB15NS\nm5KLMZdMziumwno6Yc2R6f4cF1x/X5VMHDcM0TNZ7ygEM1QCIV55DCZUW0Fbx/L7QOO3e8KkreEw\nahSCRUrtE3+TirihJyqK4pLj1+tIdNeLFSqLODyBKJ2GVmhIjAyxd2w7OQ5cbZizrhsBnAiaF0jj\n1UHU0xfi3NXXV9mMN3hf/sOm1IfYAVY0bsctldJjwAK5FUwc2ziwmiEUxiFRxGhl6WoQcQTX+4/9\n2lOurq7+neS8UVs/aESfwP0aUtBhEXjI59Kpw07xsUc3H15Wonokwt0m0fdscLuZeMmZr08LhrBk\n7e40q+S1kvUVy9rPoThaWwhxpNZGtH75WiqUy4KYuwp7pU8A8depUCB4oPawGCLdOUafpPSfbcTq\ngrUeW6R1tLhRKaq01gEV+8NIPjVqbCQv5KIc1xOGMQyJl/lEkxWxkVz7zyWdC8Uqu81Eujvw+Dp3\nPYCPvfMqXeeiTfG2Y/YrKYxUXRDv2PkdY3QsOVNKR/wXU5pvvJ/uuBTl8fRAoFIQ1iZE82R9YrI9\nrRq1nokpMCTPQCNuR2pVcjbmubJaZV21v6ZmqNRORcYIQdCsXKid8OwCQwqQhF2InGu/NCqLUUR7\nBLF5VFesOYplgkQQhzXtEVHXYRGOK7LcrIsx3N/vRSq9htNaP0y1+k8Tpv/ko+JpzghtAFf6zRgd\nynP2nkE60tKjeFU09Mx/JDC1CoPnVBr7q9zxRjxD6CLSZ4MiDvH99o6y4oLnTRXej6CaMIRJNlxq\nIfvIubV+U4TnQRpf+R0/2fY3ylPzlNCYqpAdnFpksIXbNLDNK1UKuV7wbeQuCZem3AXPVBdiSDxr\nI7cLg0TWalcJ2aZ7G670qkPojpVNU6JF8P1wYRRMG7/vlPskBL/jqWTeSqAy8yzwPAceQ6DSGMLA\nT2fl09oFizejR4PxqBXXOnGlrZVqwkZgjJ7t2POrVjw5GlrgIfRoglVlkgC+/+xFhDjEK2GmIVNC\nfaCJkaRTwGiG+IHnUrHYO2eLQKD3R2DLrc9ED8kZpWa+Go1bTycErStrU975yrF4frSH3/ULFgoP\nRUg1sz8YNOWDbniaV/5wCsTpzKkqNx68D0TtN09rzQQfeSgL3/ouDSza+NAMbdqFyNYFscE5/s2s\nvDYjhI6Z36uRvfBI5qXAX9XKbRJuzFgWo0RjapFd9GhLLNIgCp7AnQiXujLXhpHAd9BAkMBd6Ibt\n4B2jVBaMTzryravkFpmL4xgiVhtb6z2uQROvrkcXtC2IhE7F8Y4CV0N5d12JyRWHUemuDSOEgBdH\nqPU6iZF/zGXgH/SIdDSqDxHRfhuJxR4T8J3yI22lWkRqufo1PME7clNiDLSqqEXUgfNjl0a7bpBX\nEYKLpO2WcrpA8iQ8u/c35OOCj55pHHl9fCWKoPNCrbUfCPKR2x99wf2bA4ZxPHXqWmCDmxLn4wyt\n8P5+B+eVc/VcHj/g08APvrjhOC/86PM9H79ZscOOy6XAekZ8/A8bPLkWerWu2Gxs3r3BWiOpdXqa\nNMbtSK0VXTI/fDfx/jAxTpGPT0febw8Eq/ziOfPxpfKcIa+Z3W7Dz/76gdPzK7VkDp+/w0fH5cOn\nXuydBvQ0g3UU9XY7Eje3IMbltcek/VUx0EdI3fnS1QodK+x9oqlSq+GmAUkJT0B0gTiiecWnwPz4\nih96LNusUWslTY1pfwsYISVccNRcubmbuNneEAfHz79W9AybaeAyz/z+H/2Q//qHeyw6/vrjwric\n+OrLOxKNf/uh8uHDzD/7nbe0knl9ObLdGne3P2E9rhSrHJ+f2N58xcPHVz4+rSAwzxdOpyNO+xqi\nLTNaQ2Xgp7/4GfWKoFaJpNZoXrrY14T56RmfEsenyvlT5XvXO7hv376jqFBrIWwGvBnT7YH1uJLn\nmeGw72RkqwiwPWypNDbJ410gq6KL8nenV6jGculGc80F74W8aj/gyoI01ydiOIZxwqeBKA0xo2AE\nF2iW8FYo9MOTmBHSAC4xVkVdQdM/7jrwD30E6aJ255HWOra6SY+bS8c+EVdqE67mGoR+8MhiDM5T\nm3Y8lIcQUsd8u37Lr9difUgDKqVDEnCMm3QFE0FyiSWvhAStVKoaUYSmK9OwYXczYmbMa+7dJHE0\nZ6wZRJTdbiKtSpFCKTPRAvvdxFKU/XbEnytnRnJRXOsRsGqGx3BtACedall7zI8mBOm+nEojSEAx\n0Mbt/cSbaSQFz8Oy8H7cMdvK8/nCeVbOi2JaGYbE149H1rnHbqfN0A+U64pIIwSPNaWb5YQYPDEe\nMGkUGmoOX7RfRKtBax2843qMS0SIvhPfFIePscNbmhFTRelCbB8CdV2vbsr+fdfor62QrrRAxyiR\nUgqbTWIaIubg+XQhrkYKidUqb+4P/M5hR3WOj5cZ3yo3+w3WlMdz4fVceXuzRVriUhbGlBh8Qmhk\nreRFuU9bzpeZeQ2dPqlKbhVa6esIytQa6iIfz5+oFXxwGInBoDmjtYZmuJQTIXUVy5pXThgEx5Qr\n2rq/zQdHMPAS0NIdYuJCf9+TcRaJccCcEp0j+l+vI42zzQjGWugRxmZ418Ee0jr1DoSVzNDCdX/n\nidYdUwUj4Gkt4qkUgyB9HfE+gEViVVpq5N+shum368B0Gz1p2tOZu4lsKyKwL6e+6WuGcw4vgTep\nMGglieeihftgjLGRRyWXgWTCt2hH7TrYm+dBE4RCnDM3MeDNIBlL84SYeJXCateNFZ43zvO5Nk4k\nQlrJYcOnGGjayL7wfr6QYkCd4tfA5IRvq+P71fOqhZum/Lf3SqPyty++Y6ynPQeb+cpXojkmt/IY\neq5zMx6ZS5fsZklsxTM5x9WoxDuXmaLn8dzLipcKi2UeC7RT4vu9cCGSSuAuCq8aWBK85pHiM2PM\nmOy4ULpboVUaypgDmwkSijGgTXikY0szgVUKJTZST6wAfWyqUglNrh+ylTgMiDgmE1ZpNNfYmEMN\ncJ2v7/BYcMTgGDTzgwS4iqNxHwqvOEZgr5UxKGtVPmbP+wR3oZFiYZDMJvZx8a9ePd/XyJ/XgZfL\nwJtQ+EEwbnxhZSVq41QmHgWe5l7CH/G40jh6GOpKCMLGenzK+S5zrc7xql3Saa334TYxUVtFRMim\nKI7JOgkmOMdR+y3fPgnvsE7pAVKIiCnPpct/xcPoG3sXWUS430ycq6eY8uSM5DyzOrbOcZLIwYzP\nQ+ESIqq9E3ND5aFEHmplQ+OQGzV0v1fGkLXSzJhpPZJmxuJ7jDLGiAQhhIi5jipvVcn06cyr/Wdx\nqPyjPMN+g9zuyXPBnOJO3aRuqnCN1eFDz/177VAZP9J0ZfTSs7+uG8q9Dyx17gjlEKFKN9Nbox2P\npM0W7x2Njm2e7vdclszcKvFmwvBMn99AUbJ5hMJ0u6WGiKoSdyMTjhADKkpaHIPf8fE08/SzR9Z1\nJqXIP//JOyqNn/71N0hMbN7fkFJjN0VC23F7GPn28ZXkI/tD4vV1YZkNt49so+ewm9BirKVyewjc\n3I98890KVJ6eFuZ55XltrB9mPv4ocywF3zyH3YZjXVAHjy+ZFiJhP7KZ3lBrJu12lOMrtVRicUzv\n3yLWcHHAmrGc5u4eky6nbL5BNcQ78Ha9EOu356451DLDfot4j5P++W6uEsKAGYRxZNxu0W3fWPno\nmM8rb94m/Dbi8dztEy+XSoqBfVsYJ886Z77+/pW3NxP3X75lSso2CT++mVhV+Vc/febT48Lj8wv2\nlx8IwbO9v+XdUJjPmbZk5uKYXx2/+O4bVoTkA5oD9vQ9rWbcGImSsGVBPAQL+ODIWmnbPd6EqkLY\n/po06LCaMXoZ36QBHm1GEyWlxGG/RRVKg2m/4fR6Zj5lyjojMTDst4TDiLXG7ed3rKdK1cpa+wb8\n9ZQZh4G5NXZp4rP7kWwOLYqJMUXH5dx4eH3FFcOdQa9JDLOu6KjzTG4LLkW0KlV6p2PaHZAhgh+6\nj+W6htS2dkrX6bc7khdjIgy9w4xT/FIRfyVL0tUc5q8RJeHq8YpUzWyC7/HEGvrESRxzKx2X7TrB\n1Zpeb9EzMfQIvZrvHrYQ+2toGQmCM8+47VOAqkAwvBuoRNQa3sMoEKLvoIgmRDdyvCwsp5WsmSCO\nLz7bo814eH5BnO+dSefYjx7HxBSE11LwTRg3gXlVijpEYAqp73X0Ss+Ljs048vpSAGVdCt/klaUY\nloXTpnBp67XsP3LOK8257p3D45MQGClX15K1Ti9NKsg04IZOAqU11lx7DNB6jNlcg9bJuD0qGTDr\n0+q+jhRiCCAed61PiLuKV68x0oDHj79Wi/Q0zC72S2CPYxojS67E4EkyEKMn58zrKbOdBraHPclX\nhrTjbtpQmvLzj0fO55XTcqZ990DwnnEa2IwB1QraKDVQtfKwXqhOiBIwbdg5o9IhPoNNSFOaF7wM\nBC+sLaNpwFuPIIbo+vsHodEPKF7o0Bv363Wkkbxj8JFmgjYYvGehUXLHi4sTvHOElDAzpnHXD1Cm\nVCmIE5ZaukHMIErkZuOvlN8uHE7esZyVY1xwBaiR5o1I9wba9RLaZO0RXozF+l7E+QQi//E6otq7\nfxXc/Jvdi/xWHZjYbhm2e8wvuKZIXRGrjDlwG4xTc6wo2grr1XGyCYUfpO7xOBs81YgA70bj9/3E\nkzWiwSCBw6QsalgYuDTFhkRwIydnTLlPIKoZLo3EIcGvkdRqLJLYqHCpZyRXLHpUjFO7sGTjZXF8\nCB7fujRuEMezi/yvT47qhFIvHLzntirfzAO4ha9G4zPf+KxVNvv+d99H7fQU31iK4WJi48EF4/vL\nyI0r7A+N+VJYw8hZE8E8MjU+XAxCYHAB05mdE3xpRFdppbIOiWaV59rwMnCTlNkiM4lzVV586xGl\n67//MDher/GNqTkG32+xNQSCKCJCkUx0sPFdpppcz2f7rIw0UnCs2tgM/RA0ezC6MTsl+MIV7nYD\nH4/G3lbeSGU3BL6/NL5bBw4CfzgdGYPjfqo8tIlfLYF//Z0S4i3ZgS8vvPWxHwA18tAqqx+w7JlN\nOVYlL4Hkha1XbF0ZXODWHPhIUTrcIQmTB62RrTMOJn3gLY6SPK9toYjrZm8nvJqx1t6DQYwR4Z0Z\noxccZ1zY4mi4NjOlAeeF1XtOYcPiITZI1v0c21AoYmzjlmrGYfAMEki+T4q+dXRqjArHZeGjj5yL\nMhXHpCfAUVYhDJBXzwsdk2rOodIQ59hi3KC8zJUTDfwZ7zzRObZpQMxYWu3xk9/SZ7zdMH5xy/Fh\ngVKYl4pp69OINOF1pWjBSuk3vwJCwW8DHqgZNGq33MfEux9+1V00r6+kuy0xeIpziDguj0+MdwfS\nFLCiXZbsU/d47CbGbeqODbOeay8JwfH09EqdF0KKpMOG88sL87Hw8t0n0rs7xISihogn58a/+de/\n6IXjvOBp+HnDy4dnhMbuzQG/Gm/ud/zgB1tKaXz2ZuD4vHC4Gfl0zOx3wmGT8GHgV4/KbfQcvtpw\nfD6TY+LxeelTsy8jHx5OnTK3EV4vJ3b7PefzwnYTiETY3+NQnl8MPzgO9wPL3KjmyKcZPzjq6xPm\nAmkzsD9smY+F+umC+ESULn6SdBWtApoVEtzcf9YP8N5TDOrxRBgnhimyzIXdzZbtFLmcL7jBA8L2\n9o7PvfL5V+/48HBh1IX7N8I/Owj/598pXz803qTIf/PH9wzB8V/cOH5RA//uY+V//1/+b+LunmyK\nnB9xcY+2ilbh+dOFeQqIZXKuoDOtdqeRhUCdT8TthuQTRRpVISZh98UbpuhQFYLrm7zzaWXYjWiF\nx+MroXpadKjbQFuhdh9Os36r7uOGzW4gn57YvP8hli/oemH75sDUVmrbg0Sqq/jrV7yoMU5Cbond\nPvWo1cHjQ2BSY8I40TDLxOZ4fDpz9J4ln6FGai40rdSlEGIgFwVr/ULACU0zTgQJE9MYuJxmyutT\nl647zzgMpN0GdVCXmfVy+sdcBv7BT5giwybB0hDzZN87Kt57JCbwPZGBGsUpsYdySduRQENXo0jp\n/Z8UuIkHlrXhRPFDQFyklIZzntIKPsRrbUCuN/aJhhJcIA5d/ioYdp2qEIzLPNOsTwNc9KzLTM5G\nriu4jqCuCM4iasbX3z4jQK5KSJDWylIzhjKMI5ISm03iduyk1d3QqPSY20mVIQi7NOEDfHiduYmJ\nw/vEy/mCiWPOBWcgU+PlcsIRIDZOlwtDGsm1Eq57mcF30Msl9xhcnDxVG9VCd1c1A5sx6VO+OEXq\n0mit962i2FWv0OFaTjxWBIt2BSP1aZ+KwxVFfJcPF20MPpGC9AmO9GhzmgL3Q+Dzmxt++XphcJVd\nDNztdnzz6YnnU2MTBn70+Y4xCD++m/hwUb5+PPGXP/87goxkB05PeL/pQDKEy6zdh0T3IrWae6Rb\nPOKFuWaS9yTnEe+p2uOZPgVG71ClOzVtQ1UQL1jqflLJ3ZXW2tAVAWJdkWN9Cugl9KimZULYAEql\nEIdICK77H6Vf+AfrrABpjegNMc+4HaBWXAy4mGilT5JWDNNCzI6jZmag2NoPSq0foK203p+m9JSW\nA3Udou/NoRLwAfJSKH4llFOPAosjjgO5gtVy/fN+g5/73+jf9g98djZzX55Q7RQwF6C5wBqFWmak\nGfcESA3ViDWlaGIOlSCNlAI/tv6hEwscpRvSBc9SFKuNhnAjhTcBgvRxdTBjiX1MGKJniI7VG26a\nmLXiZsXNC0ct7Fpj8o7jWvj2SkzxLTNuBpCIriv3YYN6x9SUV2qHyMnAQ/P8shpfjI0flsCGyqub\n+NulcSfwNjTOqnwxemat1ClCNX6ZYbsAZL6ZheYiCTBpHG3kQCMNyo13qMt9QxgGBoy9KNPQkMWx\n2EoVx0+GwIOduBPhmQ2f1kyYPKHY9QZRufOeZylszJicp0o/CKbosAbDEHBAVCVIIyRHriuj9PHx\nbnDcuszaB+OM3hh85FIds/Z4wEzh3BIv3z3ivHI7VqY4om3ljw8Lu7Aw43jOcKqeP/0+cBbhQZVF\nRp7LwiSBW7/BxcghK5+AD0SGphR6qZmWaL4RWuNRIkMQ3lC5DZ5zc1ykcZCOKO83eI0hOEZrRB/Y\niBEM9q1xyR4L0LQQdGBxrstxzXBSOURP1kJzA1G686QRWFVJrvsL7usMITHGnn0/V6PESHCNoV54\n4xxLa2QZubUIFU7lzFq7LXwrjikrF22MVvm2eY4uUcSzKjSUvSlSK+dqOO8Qb7zxnuiUEz3eWs0R\n5tIPvpcL47WDEM6/vbfD3oFeGo6C3wwE7kCMmjPl9YVGJfmBErqCiJwJdGKVOcHvBw5DJGuP9y3H\nGUnCcHNgPp57+CYI437D+/e3THfbXvYeRtayMkXPZtgzbQMqjmGA07HhnHIqhYdvP+HFM46R9TTz\ndz/7lmEa0Hxme39HmAbKaeb2szeodO9cuXaU8qlS5zPL0wvDYc/WBzaTY42Jb37xyFM23t+MPJ9n\n/uCre17nxvB24PWc+dnPXpjE0axyfDkjuy1+zvgdVAe7EJhuE/shUmql1MawHfES+PztyO6QkGPg\ntK40l/jBu1s+Hc/cbgbO2fHh4YHd53taBXUBTDnc7TnOK1Ir42HX7fJ+0zsUquzf7PBOQBUXAtN2\nw/F0ZDsNaFH27zfcjbCoIg1228QhRV7bjsePLwwhcKmV1+r51f/xF+CMf/6HN3w2bfg4F/6HP9ix\nDyPntvJhhe/Wxv/0Lx+ZnfH0+IrGLfPrEz5EXLohbQb8aWWRitPMeuobT9NesnfSkFZo2smFbT07\njer4AAAgAElEQVShmx1VB5wslJw5nwIlBZxAPEwMZuy+uOFmDEQXmB6EJYMbPGVZeXoJuFi7t6oC\n3vPm3Q2Xp1fCdo8PjTRM1NLIpzPpsKXlFRcdh+2mX44JHE8LbugRdEpjv4vkXFGFbewUq9PLmXIp\nRO/x0RPE01rAPJxzRpthPmG59B4erq+HOffImYMhjqANb71f3DBsUWqemc9z7zE1RZbf3ksXAN8L\nz3jpyO2NjIChqjRdURqDi1R33XM37d2Uar3fMwW2xH45KL1X46LhJVC1Ibl3WLz3jDERY+yXs81R\nrZKckGQijQE1T0qw5IbLlaWtzKfzdUMcyXXhaVZCcH1iFUe8i5SS2aaEDl2fUkv3iYWY0FoouRBT\nZJCJEEEbvBwvXMbKfkwsZeWzmwOnSyUkx6LK0+MT0fUkxS9LJTiHcKWv1caYAmno8TWtV3pcTETv\nGUfHZghYHZm1IGq82W95mWe2w8RS4XU+EafQp0lZgcZmGphrRXwjhdj7WdrwPmBipJi63fh6MZhC\nYtGVQfoUJm337JKQteFEGENkkyKXrJyXmeA9F1Xm0vjzn32D+MZwM3GYdpSy8ic/fsvbaWQule9P\nC69z5l/+u+/I1pjLilpkzgs+OrzbkoaIu8BCw9XCqtKx8NpozuHNkFaofbZMo6F+pFYDK6i53rWy\nnlIx30Fjg+vx+SCRmAPV96GBamWpDmqnJ3ZHnGM7JLJmRAJOGtE7ivUulw+hd118Y/IDKTiaCUsp\nXaeAIVWZrt8HpoXg+57vcrnQrIONcN33RvFYaKxro7UuxTVV7CrzbmaQleZ60iKmruNwXhl6PQ6r\nneg5nyuCUZvS6j9NmP6TT3SR/ZAYUsDJQlBP1orPQm2e7CpeFLVe0iuA+ICnl7utOebgGDEOVvjh\nEKk4qsB2IyCGtoHa+gYksCJOSW3tBBV6nnPNns9j5K5ciOZZfeN58Fy0sSwetTOfC5yjIxDww47T\nUinMDOLw4chDjmQvhCKECCkoB9corYA55v3Amh0nHbGgfOM831UILvL9JdO8sLk0mPrCWlPA1e4I\nn8QgQgqeL8eZwTzNhDTAIMYQJ2YLLGpEbVfRY2OjjbhtONfYVodW5XJ+5o8jhBBwQ6exvFZhzsY2\nRCYHTio3FHaTJzdPaCsbpyTpcTQJCS0XLCjaHH4ojBqpFqgt0fLKI5VhnvnxofsG7reGuJ7ddx7w\nkf/rm8Rz6V2ary971uY5t8BiwsFXigdRYWeCOuXAQKsnios8zgrOk1wgUqgmJNeFxg3FWu1Rn1o7\nhlQiD83IznAtMkfPSY2tCLe+I8If2sBatONIXSA5OFnhjUTGVPmyVeYirM1YvZHxnFU4K2xaYo4B\nbcogHXpRrKE+Qoi/NhZ0gR2V3IQmkQcLuKL4kMgKwXfK1b0NJLdQhY64d/C2KX/mBmY/cCkNkQVp\njVE6yrZKJPruLhsKLKVxqQ2Txt0oXEoXBDXxVFHeeriTwiH+9kbyUhrY3G+5Dz1+4mms54WmlaMK\nuc49oqh0j0oU0u0NuqwdliSemgbGMZDMONwc8GOg1spm+56mRtVO5wRjjMZkDr+uyORoPlCWM88n\n4QefbfkyGMOt8KE4HobEcXfD8dOF9fjM3WGHv9kQ08Cw/4zn7z5xPj2SUsJkZX094vcH8nlmGnu0\ng+0tdblgJoS7Da+vM9aMdLtnqcpPvzkStwN/+tOn/v+sRthEwjTCdkBL7+WlIKQ3Nwy7yK1kbkKi\nGribRHDGex/5KB6tvbNIrcg2MQZ4fx9wOL6/3VNL4+Evv+f37zdM+6lHkXLm0+OF43HlcLMl+4hp\nYVT44ic71hWiV3aDkDw4C7wZEx/nSttE1ODtxtiao5jnr14cWlZ+9enIry6F//6Pbok/3PN+6/r0\nXBxf/Xe/RyLwP/5vX/OwLszPC3+WjYyxFiGXxjh0sadVYTPtqCyMIVIvRwhKfX5CQuzbmNDBHCJ9\n+iOt3+5rjIRaMecxF9A107VaHkmenGdym9jfbRCEl7mRPz3xuNvgnPTN2dMjb3/3h6RtZNwMLBdl\nySt5zZgZr88v5GUlWsIG5SyNIUaq98zHM3KNar+eC9PYuzY19wmIBMcxrzw+K+M4MK+VECGOgTs/\noofYfwYYk/fYtOOX3zzjpkh+PINbya313l+r+NBABGu9J6enM3MuNCcMU8LmgkgjW8K0MGx2jDRM\n9/z22tzAucg4Dng3dNE0jZoVQ8mLQ31GxOFMEIMWrv0Lgdb61ILQRcfeeXbDgFmnzqXBQ220a4QP\nrEfBjR4RDh4xT2mVeS7s9yO3YyINnrV5nmdjXWHJRm0LQ4x4utMvhok5rxRdceJ7l6esKL1/E5wn\nOiAOVOt7ERev0w+64L1o4+M540LgZw9HQAgXkOu/q7nre0h7XSDFRBwc4w621vHdY5zwHt4MG46q\nLEun31pTXIhsMuzebQji2F48tSjHlxPv9xumIeCcBy08LytlaV2aLY4O9Aoc9onuk62MY7r6qmDw\n/XBleNQc02AMdAXB47Ky5szjcuJB4E9+cE+8u+MP3u9p1vHi3sNI4H/+s5/x7elEK8rXDyeqKrUK\ntbWOFb8SDZMMtFiYQqTUBaiUOV97VYL9mugsAiHgrSP8m+/aCQmehqfWSjfjBJqnT9kkMaQOEluy\nUmsBCj6s/XXKC5vthsF5Ugqsaxcd19aAxqrl6snqsb+1NaLrmoZS+0EqqnQI1iI9Mq0NNTAnLGvm\nuMxECWTLHRtvjp3v4IxGlxZP4tCQeDwtPXKnDXELpXVadUM62CEIpkZzBjlTrF0piNfYJNZVGlRC\nSAQPdfzNliF/qw5MaTMxTCOWV8YaOKJUjbRwJvleeAR6cU8bTiOLcyRRJhe4a4aGTAihozwB5zKj\nVZxumKxRx4ITwYv2w4Qzqm1RzQgFdTCZUevKd2uiKsziyGqoNm6lchcC6mc2BRYVllox8WwlkEsF\nGl85JQRQLzTxSHPsfeF2Ghh95VP1PDoPbWUYPJ/FzKLCzgrEQiDgdkLyjVYhxn6TsJYNsxpTuuDV\nE4c31JYpS8aqEQUyC05h7x0tSR+qyxU52la2G89hPiHR82XMaIPgwDVDk+dHoXE8G6fi2U6JjZ0I\nwxZzmVYMca2bmLdAES618qkGLvPAJmbanFEccxWiu7BLwrNNvITM/3NxfCkT/35dWOodr+tMscTc\nGkrPb88tYdJ9Dkh31DQ8uxRoKM5Dco7Pfea7PDCJsL+88m6XAM+pjVyckcSxsYVsynEdeaKxxgBa\nmHzAXGUQ2BA4B0/CMJn4pWXeAhaESY0zvfR84zP7UVjKhdfmidpoQ/dp5UV4DcJIJwi1EJEraW2O\n8DYoUUJfzJ3rmwnnkOApYcAKnBuYOGrasfrKEBzvmRnV8eoaX5eJSy6cFvCmfBG0C2nXwjYIKo2h\nNeK4wdoCNPYycwg7zAq5OS6ToxUlAz4Gmi6M1qe4jsSX7UJxy2/+w/+f6dntRqZxYlZlQJlzo2So\n6pBRGBmBblNfl4xoQmslbibiOHAIE1kym5uJ2lutLOczG++INjD5Qr71/SbRCq4Y4gw/bLgcc5dU\n3kVyVi6nI3+5JF4fZlbnyEuhnS/sp8RXv/c5lUrysBRYjs+YNHaHPfn1TJPG7f0t42FD3vY4nRhs\nk/Hl7/0IVxofFnh8vvD6+MLu/pY3b0bW2bgbjOYdKQa8QIiCt9YjH0ulxYmHl8L9rhJCJF7FuOds\nxKxMXvggDVPlfYA6Ga8kvAhh45mkso+VN03xKfBf/ZdvepTXgbSKbiK82fE3p4XXxfiDL7cEB4lE\no3RClUuE5hj2K20dmXPhl6Y8f2zcvhW+ezVirJwuheV15sc/HPjutOFJF/7F3575nc8C/+KbZ46v\nwsPHB5DAep7R/5e6N+m1LVvTs55vVLNYa+3i7DgRN26Rcck0TpNumaSRSBiRDQSW6CAa+B9Y4g9Q\niA4tQEgIibKHhNsIhISlBCE6FlJaxmBZwk4nzrxF3BsRp9rFKuaco/g+GmNFcIVJG/ImN8nVi9hr\nxzmxizHHGN/7Po8pcZoo64r6jgBPdzfo6YTpzOHTW/LTQho9tzcT+8nx4XHGecf2ky/53mevcSGw\nMXNcz+zuJmRZyKVweYGX8xGJQ4+Lx4RYJeEZbg9XgIPhY+B8esbkQDgMxOA5nk6k0XPzcM88f4vL\nu3eoOUIIWBSiweXUEKm43Q7ZMunmACUj80BpxqvXB4ILnMuR5LvMlBBIQbEwsy6Zcy6YExj2LCoM\ntyMHLyTpNLLnc2F5eeH8eAIR9vsZJ57z0wvEhGnC0Rhvd5S1IE5B4OHVR5y2QoqBsmXKWmi1EMaB\nmnPvggwTKVxF4n9ylxAApjgyx5HVKoMpy2bd1ZY7iMN/7YfRHrkVDV12rY6UIpMEqq/EENHrBa36\nfljHAmMoaAQvA+LofQ/Xhdp5VbBOnzVrbHnhq1KopVFanzhbqQwx8ur2lqyFdhGqQa4ZEyW5RC0Z\ndY5xnLvouPPvEIWUPA93rxic8H5tnC4ra14JYeb+ECgZhiQ4hRC7ZmNOjlwLu2FgbY21BNYlM06K\nl8DdEFir8rJuqBZ2KfJBMtaM/RBR56mt4kVw0w5B+NbBcTftCHg+e5ipTUneI2o02fH9oHz5dOJy\nLtzub/Cu8fF8g0nhvG744AlOGCejqWO5NI4fFs7nxjwJj6syDMaaC0bj7jDysgTOl43/9ccf+PTu\ngb/x099DivC8LJ1eWHv/V2JEm3YqoHI9ICubRYY5okX71FUHpkE4LoaIYGXj7rDvyY3iyFIJ3hPo\n8by8OVbLnarcCj76PqVrXWZdm/ZIpfdspXvccI7RJTZpiHT/Y9rN5LyySafgEsE16Xs0jNp/dXHO\ndw2G73upcRiI3rHp2uELHX/I4Hovr+RGbv2TLe7YFALCLkKU3mk6Z6WWjZwrZjAG12OHJV+nSx4H\nhDGhRXv0Q4z9OLJJjxArvfdo1t1VrXX1hIjDi8NH38W5v8DXn6gDU0TBR3w0UGH2heYKtc7EUKmu\n0zy89nHsEIXYlIrwXDd+0pS4gXOGSWfTT/TS2yfhgvNGqF9/SZQmhlgDLUQP0rpI0rwyxi4nC6nf\nMuYGTY3HqrzJilqfoMySe2xLN2YqLsLoBQnKqWhHa4vjJgXMCxsF1zKf7Ap3i6EuEANM1phGZWuN\n3MCnTpYqpccgWiskyYSkfOyFqo0mR8QuxGEi7GbasvTbHzNqK8TWKNVoKmzNetk/ep6OhpUJsUp0\nCa8bBME7KKrUVSkasBQ41cKLBfy2EoMSbQAxFjztySGm3PjAt+bMOJ8wF5FuTiLieLN4jjqgtbBH\nUIQ3UjmXic0K0TtuvZHEow6yKasIo+udErPa42zes3cVC+BoBJ844vhMVqofaHHurgSvfJfCzldW\nb+QcWBt8PGSyCWqVDyWyNSW70AvoV9jB6jyPLYNztOB4sMKjXwnFCA7WXEgqjN7hLLAmIxSHc577\noTCbR+hgEnF95K6qpA1OzaEOmkRaFkiJVqGJdoeDh71WRuc554WtKA3lB814rhUsIs7hTRhT5VUV\nziESrfA6GUOITHZhMAgURm+EYFSNZFnJxfFsT/yyBZ6rUZKgYeRJElkaN3klyIUfi+fH5U8uEjg6\nYxh6+VeyQwLENFJzo6UbqjbW5w1pjXG3Q7zDSi/cP/3kHc9twfA9Gy+GeWEYJtJ+5va08NH9juF6\nmG9eMdedH9uykZLHVKApcxKm+wlVx8MhIU4oRcnbnjcfTvze3/uqxxWcJ12dciKVyTV2dyP7KRL3\nIx9eFuqSOeUjH33rAT8Hno+Zva/8o/eBd0PCffoJcfDcAw+3jY3CTxbYT8LLWqlHI90mSqkcXGFp\n8OsfCaKNl7UwTIExBP7UbKyrR12XNz5izNZ4rFC3xlYqaT+w4viwCueLx5zxEI2gjVeAd46qG8sK\nog7xkd85Z1qppHYhReNuHDlp5bIU8nvBycpnNwN/7t4z33uqG3AC3haG+8T/cqs85UReV25HjxL4\n0bsXzguclwvztSs1+Fc0gayVVYXdbkeKUHPh9BSZDxN3Q4BdQID5buTLx5WdN/IwkG9GhjliTfn0\nLvLt4Y43zbGtA6fLwvCdxJZvadp491RYTysaPH7wOIzSoHrh9PY9YYr4ITF5z1M5QqvIJjx/8ZYk\nkWFIeBdpXrACw/0N4p9pzWFm7F7f9Zva4KlLd7A8P58Q6aCB1VbG3UzLmeWq3lBRgvPsdpGXl426\nZZZH5XlbWS8rYLgQETrVdIx96tFEmW5nhnGGtuEK+CkxPRyIKdJD2hs79Tx/OHL7asdxWQlzYBh3\nnI8nSquQM7kWlqPRnv6Ed5ic4b0w4JHmmCaoDZp3WHMoSmnaY5rOIfHqAwLWJbPWF0w8DtenMUEI\nLuCdZ9ZKGxIjRhOFAGoOkUZTSL6jvbG+SU/jgJkjTRHnhDUbpVaOy5mnp2f69hi8OKITVPvzKo4D\nY3BI9KxrptVGQTmkGeeNLVfUO759GzilEWNklzyjT0xRuNTGkmsHh2yZko2bcSTXzOA9MVa+d5jZ\nWmMtFfGOT/Yj3592nJ9bJ7eZcc4FR+3P3Ky0WpiGyDxO/Pgxs60NXD8XoI3DlDq1tGYu50Zr3RH4\ndHnpv3vPZ2KAMcw0yeR168AilPv5wPdf75m+HWjO8NbBMqP3/M6b96ybUFtlTB6TwPvjI7VA0UIM\nnskHYuiusdIqVZUpJAgObX0NHFJkDrFH5uhVkHMu/ZDjhFZin7Sb8dFh5JAGVi1sm3IpG/eHQLYR\n0/ZNx8nEkKHH1BBBnZHzhvNg4hm951wvHRBhnnXbcAR8iAz4K33U4b1DpoI26ROzayQOc2jrP29b\n2cil/4xlKQQ3oK2SxTCrvROGIwXPWlZaadRmfLBKKb331duWghfpE6LrOhKTI7iIkwoa8dETp+4Y\nbDiaVNImrGVlmiKr9kOnY6A4oaFIrTSrlCrk/P/jA5OI/OvAvwj8GWAB/ifgXzWzv/sz7xmAfx/4\nl4EB+C3gXzGzNz/znu8B/xnwzwBH4L8A/jX7WhX8B7yWAud1w1FJulAl8kzkpa1MMrB3jSjKYo2E\ndi+BE8wce3WEAFujI6wJqCpHl8l4nlvCKgzZM1GZnEH1jF4Zk2dvXWxrbBAmojYChruOJ6NzRKd8\nKhCTI1vBrLCoY1PjRlzPMbu+aVBr3E0jyVUi8LY28J7HzXhjI60EInDjKrpFzG3sxohfG0kCKoFo\nylIKpT2h1Xg9Bi4YCrxKyhSVrRaWZcVMuZ0DrRriPcUZ49gopaIM3TquR6pGqghjakjxqGVk6GVK\nNRhku4rfjJ1rTLMjRgheWNtILlDMsdPuP/AhcmpwksiJQG2BJzNCG3HALvabkwlHFgEcoWVuDo0R\nQc0zRYcCrQpOGhIdTQvWBCfCczWOLvFOB5acKQp7lEOoFA6IepysvHETq3qa6xuZWpTFIJrHOsST\nrQY+GYyprTxLpeUbFjItBIpljMhj8XzZhBcaf27n+Er7QefzEth5cBYJptzoSkhGY4BciGKo84zW\nJ0hOIbje/bIr0QiFTL858mGgmaeKXYEVwtO2QG00N5CdsGvKgwOiQ4bErIVXZeUhdtHe2ALPsnJs\nGaGxuoEPJbMyYzVwYys3JrzUgsbERSup9VghtjAWZRc94wif55Ehbnz6c06Y/jjXkZcM5VKw1oj9\neo21KM/vzrjoGYeR4d6zngsu+N7VSI5WjMO37lC7I5/P6FJw49RxvtsZkuOrU+HLt0+Mt7e40qNO\n0jxxFHZ3E/c7R2iGScHvJxJ9Git070b0jjAPfG+A4dM7lm3DVDlnyEvlk49GtHRz+nQzsR4Xvvud\nO4IXohO++HBBQuDLnzzBkPjf33UM+mFQGsLnZeHhk4nyoTKMkRINNljaxvbuRN2Uzz4e+YF6nGZe\n+cj37oSt9UmcmfKt8ep98Z4HZ0yx8cqU4iNiHpNMNuNWhDSC14gpaBLQnlUfAkgLHFzmW6lwMyaC\n75LNtQVK6eqEMAWqNmIIPGnlaMozwpvSeNwqvkVE4bND4lkSr25Cv2HFEbPn408jk9xSm/ErN4Gf\nNtfBDNL4aFCW6nnM3Sl0fj3ymAOnS+VlObGtsGvCfkxcqmcIgRaM56xs1dEukHYjaylctCFNMFVK\nrhyfN777S3eMmnj3tKF14NwyQwpsy4odJi7PZ95fvsB7x6/+6e/y058+IRJ4eXrCT8oY9vi1MMxC\nuhl6G2jLuBRR8Uy7HcvLharCdHA0E7yP1GZI7TfQp6cXwjzgrEcne1G+cnx6gdIwFzq1UDzjdYLq\np4RzQjTj5jAizkhu5sPTe5bnBXEGY+L5q694DAOu72IZh5nzh2fCHNm2TMuZ+/tXuNlz+rDx8OqG\n8TDx9vMX4ii0PPLzrCJ/3HuRcwPNuSPTnaIibNVYloILjuQCIWrvBYkHuVL0rG80zSZa6xJUT8LU\neok9Ki9L4flyIUin47kgUB0+GEMKTDHhxFMpDEPCNUM81800DMGRJBEjjJK41BUzI2corTHFALWL\ny7/2tN3c7ogmpCi8Pa+IOJ7PF5rBl88e7xxTEp7PHq1ndncDbS0MMbKZ4ZrjtK1caqMW5buvbllM\nWVrm24eJw5C4FOX9pXAsyseHRKt9LctzYPSVY3UEjYgJl7ZRW4+kffQqUbJglnFDpLV+0ErOKN6R\nWuNuH7iZDgwRZm+szfO4lL6OzANNGyEEXrbMqSgvOVO08eGyktQjzrOfElGNe5tYtSDekZ3jdu+Z\nY0Rb4XY6sNJoVfBSGQdPrY6tNJwPPJ6P5Aa5KOe6UouQxsboAs5FPNIvxptSqiC+4K9I7lUL3rom\nRbfGpsarw9D7reeC08RaNyx2AIZpJRflogurwCev7ng6Ljgcy3bBJyW22KPnEUK8ToVyrx+ICEH6\nvqNZJxwrgpMuRhYAM1a6DgP1iHYvXkNZ1u0arwug1oXBvoNkXAyIg9CsR8VFicwc8wuldIeWE2M5\nnzi7cKX3GUlil5h7qLVipsxxAg9taUwhEncjp0vFudonU7/A1//bCdOfB/5D4K9fP/ffBv47EfnH\nzGy5vuc/AP4C8C8BL8B/DPyX189FRBzwV4CfAr8BfBv4y0AG/s1/0B+e8pkhR5xWPjDwFR7Phmnk\nBeOr5kgY7hruSM3REE6+gxVuneM+CJdWUOdQBc/ImcbW+hfeO49UYZTAwQvvbWCv8PkGjxjiAnPz\n7EJgchVvSizduO1DQsxf2yceHxzS4DaBmXYLs1Oa0EezziAHjr5yO3jUKvPoe6beB/w48l4aQZXD\n9Cnvjs9d6BUj53PjdSzciUM1sZ8axEB0kck5VoMnHagmuLlRa+XDEom+duxxMbJ4Wq1MNAavGJ7Z\nOfbuGrWgIC7SnMOZo1XHUQf2B8+sjXHwEIy1OV5awHvBD4CDWoTWlOY8Axl/pRMmUWKYWVuX9L4p\nQkrd+dMsUIuxxowPOx5bZc0V9SNVldZgM6VloXrI4hhOhRxnPkin8KkbmNX4Mju0DEyhsBL4nrvj\nwfUp3yOeHy1KLZ4hekYPogs7NxACvC/Ga9e7b7+rhbmOqBRuvHKzNRbgfQ68J7A5j1jjrIrKQDNo\n2WgWeUXll/aRoAXveqb6zVJ5lSYiHTyQXOx0I1cIeE7OaM1oAj5XVHqkyyx3cZ5VWhSGcuFgjjBN\n3BB45Rr7cqIG4RHPj01Zyo4TQPM8NfBOOW3CsLtDLPOSDXMze3FcpJFLI7kJGzx6WRldZmNgl41f\ni8aoyrEGVn5u+cEf3zpSFmrOODPOm3HJG9YqWOP8fOGMEYR+sI2Bmo0YHcu2wFYY7u85PDywnS9Y\nSLTLGZvuKZcj1gAR1uOFumVCdIw3t2zZqGvl7duV7Xxiy43bV/fs7ydCAL2KJ6OHkCJCIEkvy/rY\nDxI39zvMjOgD4g01x24/YE6xCqec+e5ntyxb4+b+gfOqeByHm4F364psldcf3/D26czp1Ng7z/vP\n3/Px3cDdPsBmfPJKkCHysQRug3Aqji9z5INWHpLjVIXL6rgJDanGU27UnNDS8AqfjgWphduYOHhD\nkoEuaO63hyaCNuGdGPez59tt5Fv38Nnhjt9++8KpKtNA90E1WItnk5FVIaaAz56kynej8XoY+al6\ninh+b63ESWGIRHOcW+DiL4gfWErm6VT5Qh35tNEa5FYxNaoDa5BPS48D1fJNQd+r591p5a31n1Av\n8PDqlldzYoqBp2Xj7/zohbKszIc9Me1op2dux0B6NfDTNwvf3geC9/ztH37JnA7IcGHeDbgPrUtP\nS2Mtwu/+/pe0ZaNpj+zUS2M5vsUE3JPx+rNv05Yjbhxpa+H4/KH3LYPgTgvx9SuiCTjFqZBXRXPB\nfJccq/bkBdojpM4UTYJrXZw8HXbsdonDFIkS8a7x5mnlzdsnxCXK5YWSL+T10qlZy3vS/S2Uwrqd\nu0ahKFUKdbkW5Z3nRz/8Mc4E9cby+cb967vua8kFtZ9bOPnHuhehbTStOFW2IixawSoiRi6FTBdv\nmvMECuD7x6wiVfExkYaBmjfMBZxV1BJNayfdAUWUzQxfIMbYo8NOOS8XcslUc0w+kIaIBL65eAli\nONd7davLEK7dpAi7eQSUGAPOGa25vhfpuE7OW+HhZqIq7KvvmovqGMbEUTO+Kh893PP+6YltqwxN\nOb4vHMbIbk6YCg83saPQY+KT24HtUvlpddS24uLIZVV+901mHD3NKtu2oDjWrZBiZEoetR7tuxn7\neudcIxFp11jYVvr68+ndDm/G/Z1nlokvlgvnrTDOgddzhG3jnGGtkeiFuyikFogOmjU+ud/xsmaO\nWXi5ZGK8+pV05lKMGhYSkeNSOJXC2+2M1dJx/q31CawDa9IVCfR0T2fvg2+OUzZe2JAArsF+nthH\nR5gTy7by5dOR2hpDCISQ2PLKPESSGk+njcM04IPy1fMLgw2YZVLweHM46X6jbPDVh2doRkThz6kA\nACAASURBVG2Kc466Kost/XCywc1uBgoSepRwXU8w7emNOsWFhEcQUcQLtWp3WYn1iybrnSTTjJgg\ntN7BqhnvAjElkg/MQwdPBGt82DaOy0LTgJYXjPJNT7+2RkwjopXaOgSmClStuFVZUt9Lv9ueu8jc\nG8taOMwTAUdWh/KLPTBJHxv+IT9Z5CPgDfBPm9lfFZEb4C3wF83sv7q+51eBvw38hpn9NRH5C8B/\nA3xqZu+u7/lLwL8DvDb7+yUvIvKPA//zX/4XfpPv3X3E0SWOJfO+zuRaOzVPjYJSsxFSQPz14bFd\nx5kYwTtUBdFKCtaNwd6oBRY1gvRei9B7RaOHKh4LDWsDOQiNvkEONIIJe+e5j5mb1CW5zSCaolKI\n3pjU43z/GjsBJz2i5WUj+EAxRdSDQRF62c95GkI141gqU4gMrTKFxofahYyH+sx+2HjeBop5iB5I\nGJUmU5+yiqOokSVyyhuDF5acMRupbgVv1HM/wAVVAsbObdxF5RCEvW9XF0qPC1btXa3SElmUatIz\nrbXnrwVPqBuSIqN6hlhZiuOldEHoeN00FTNi8lTgUrtXKFtjq56zGs08Zp7qKznD5rv3Bs04hKU5\nQusHqJl+03CqQjVHileOP4YWaBhW+kbkLnS5qKeSvONP+0ZZPX+rdQT891zmtV9Y6eXVOWw850S7\nON45w3tHwfHG4IKnWb8VGUzYtKLa4yymGfMBkYYzz+Arr6wvS02FGDNBO5Xm9huvkhBCJbRAk25S\nzxFGDQRnFO3UoGieIazsnWOXhKMGXprwuU48S5/qaWnkK8KdptQKy5axBi8+MO8nJht5ty2M0TP4\nfmPlBO6t8ZUENlNqEQyD1G/6u+k88ObpLf/tb/8WwK+b2d/4Qy8gv8B15Os15Df/jf8c/+mvoSK8\ne15ZjoV13SiX7SqNNOplYbqdkeixBpf3R+S6v/Pj1Ok+ZSPM3f8jBvnxiVIa4oU4zrjQCUzDNNIk\nYE4ZrhlxxDr5F8XCyDwHdvPAq3uPN2FrnuCUKr0AfvBXv5Pz36whYsqdUwYcF+B03Qw33+/ADl7Z\n8JQGxwxzdIg27iK8Kz2KcWONT+fM55eRs4Pguw9ExDDrHjqHsOGgwpM2Zq88ropvylIVF431pXY8\nOuAxxilwPzu+s3PciyJy7Ug5YdXAosIb7ThqU8XM2HqjGREjWEMkEaSxS3CujqfViNIYxaMCRY0h\nQrNALgXxAdXKuinHY+3RRycUKnVpqHfE6FlLxWHkrUDtAsvBOUortFJpVUnTiJmSa0G3hqj1zQOw\nO0xsuU/ZXYDvf/cVbYHf/cGX4ITbm4kDhRIj1uD+4Hj33CjPjcfLCy52Ktp2OSHSEb9dzuuwVjBz\nV/Jevz01699vBIY0duR6VWxw2LYxHm5IKTLfzCznpStLXECCJ0VPc8IQIyHAUjKWYfQB5yuvpsjt\nq4mnxXg6Fp5OC+tSaa1Q10KjEYZIWzfaptTTCVUF50j3t6Q4cnl+jwxjF5PnCs4RQ2TZNqTVfhmA\n4YKnKT0WiKe8/z3q//hv/YlaQ352Hfnzf+nfI7z+FbZsHNeNnBulFbRUxAutgbZKCFfagDlqaVz5\n34jrlDOxgvOud2JMMK3UAhYUT6cpIkJwnioenBJUruhpUDO8KSa92D+mwM0uEkwo5vBOyapEL0wx\nkUSxn1lHUpRO5YyBLRd8yL2XqR3vNw2RirBcMseLMg+eIRq7IfDVSyZ6x+SE273w+Kis0vAuEoL2\nKQgBrz3CtWnfeH/YNiavHIvigdwa4o289IttXJfjxuC5mRP388DdnIhBcK0T99YmLBW2mllq7497\ngU0VaQKxP/uSRcadME6B47HydC4ED4N4TKCYMQ6OloXztpKGgVwyuRhrqVgTzHWyb9sUpYM6uqOo\n7yekOZopCXqsvhRUhRA7irtYP3hI6z03BMbk/89nahQ+OszU1fHmfOyR2zEwRNfXRzoFcVkabXGs\nLEjoE/tcK6hdgRCGw3+DLIdeMRDnrj63/jMT++m69+t8z9Z4icQUiL4DJsRJB2sAQfreKgSPd/3Q\nT4WIh2TsY79sOZXG5dI4lY1Sel2i1e7bFCegilZDS0avx44wjHiXKPncoRfedxyjCF5cB8y0ipn0\nabj3VDVMOrV6ff9Dnv/7f/ePbB35h71+3g5TV6fDh+s///r1v/k/fP0GM/sdEfkR8E8Cf41+k/O3\nvl6grq/fAv5T4M8Cf/MP+sP+ptyzyC0xGsd6YAsnono+kcrYGjV1iIG2jFilqCIxMgbDDAxDTXFW\nWVoENfYuo84oEjrm2UGMAR88KkYWYWMHUkkOsnZXUzJDaYirLAjPJ6hB8K5xlxIPccSs8uIqzhvO\nEtELKX598zOTLaAOBieICFjDFUddX4jOYQJzM1Y2alUu8YZhVG5dw4VbsiTCXlAGlq0Qk2fbLgxN\ne1k4dPzuRCCOnVwTdUJrwvk9qRaO0Vhr5xUl6cCMl9CjLRcPN0GZHDSBpn1D2awx0ReSrTUkClEg\n+Mil7ilivC0bujqcKtPQc90njChKwrhU42SeSZQggDjmoNxXhwsV0YVzc6wucCyV3WgohTE4Vu+p\nVdHQ4R5tHLnPldoyqxPUlO+7xguOTSsQOFGwFjmi/Ko4DsH43TxwYQEr/JkxULW7qOysbFeaT3CK\n7jx7E7wXQoPRPM8KVYSdOKIoW+uEvM08qOJql+E1oFrknTQEMOeQCs4lUnFcPAwoSSsHiaTYhYUi\nwqEIq27snNBil6s2H3hR41gdlIj3Hi9wFx2xNprA2zSSy0ZeKx7PasLqeva9+ci2GOaeeBg9d7ah\nS2YA7r1wCgGTgTPKKQUavccloR/Gc8l4/cNfsvwBr1/YOvLDx8I4N8ZgtE1ogxJKYP96wJmDwbDt\nQM4V0cZWC3ef7hjGqS/4VMiJZhN53dBNiVGI+wlxEZ8i45CIh5FpSij9Ya7WRdDJObJBLQVn1vPj\nDrIWfvDjheCFaoXXrw483O5pFC55Q/wAXzu8QvexPFVPJmBOGKT3oLw1XIEvbWVwDQRmOtUyiPIk\nIwfXmHwmBOVRJtJOkeaoxRGioUV6TzMJmgvSRiQGRpQSJtJgcG74g+AJvOw2lp9ZQ0CQEPjQHIsX\nxliYBYr04nVxwmSNdF1DzkWIpROohhTI54GCcRG4XJRcKvPssRZRuhB6SHAqSl0v7MeEuI4r3zll\nFxMx9PjJsgjrGHh6LtweIuWkzLcjpTQup4YTaFUJ00hZjWINVWhNeRgPLMt2jZ446nZhq0o5X3j9\n7Y+5vR358RdHzqeNtpz47Nd+mfPLGf9ww/blC26cef9yIU0zEuAwGON+JCbH6WXH5bTgYsDHcMU6\nV7bTCcxRNgUVgvWif0ieki/0TI3r3xcfac8v5HHiUox2PvLw6QPDnNDWN2ZpqeQls78bIATy6YTu\nZ16OK0tRfnLcmFKEMHJ72OP8Qime4hKn4yPLhw13vYipQfAMWDTq8UJ1F+JuZBxHTu+ewDx3twdq\nEGY/sy1nzHVZtvOpdxmotPXUgT1/tK9f6F7ki8fMMFYGL5A9jUxwnjBc40WTITVSDKQ1mjb8FLow\nVQ2kQXE0PGoNrYqPgmogBo8TIXohDB25rRjWoEonDHyzjuTSJ+LX73fVxpv3uaPLnbGfR17t9qir\n5LzQZESSMThHGDytGWVTjquizjPU+Zu9SKjCl+cTyfe83+hgXfulRN4Cty7yrVeBEAyVxDQ1ShXe\nPzZuD8L7DysMxrQbOZjy9tGQFLiZ4CKJWQ1/KcTJoy3wPJ5Yar4mUegIihDJLXFchE9eRyYnqBhe\nha0o0RK76zpyOq7E4vFRGPcz69vuLnx3uqAfOuxiP0VMHVvOhBiJUTjnxnbp7sXoBJcS42Dc1JEQ\njKbKumxswXNZKtMhYVsmDgO19K6aYkg1JDm0DuRaUQQz4zB48lrIWonqUd2u+O7CYdoxj553x411\nK4gV7m9uKa3LpdsCpkq2hpcAMwwt4oj4pKQa2EoFHD44nINSPE0bNGj4fvhoRsPjxWhWe17fHK0W\nHJ7mKrrB5hpCYx5GQhBU6VRDE0rZcNfeZdMOj1lzpeTG87nj13GRaRhxklGLFDO2tqClIdL7l9UJ\nHo85RWtDOROSJyBspdMbJx9pTon0lJiq7wog678fKrWnbn7Brz/0gUlEhD7y/qtm9r9d//W3gGxm\nL/+Xt391/djX7/nq/+bjX3/sD1ykWimcarsSNJTkRxgbH/Ke77kzO8vk4HkpidWMGxqNC9ZSL18i\nxNBIHn7J1v6wIjJ7YXI7tDVyUpDIscJC4bkoVlYWhecGF+/5NERu4oCWjZPB4hKnoRf6nAs8Rc9J\nDANW3+N6LSiRXuA+hB7jiy2zbI2zCIVu+R7FrmVFYQygvrL34EdBowdxLCH2DGrybBcloAx0+ezB\nJ7JYz486IQ2RglC77InFlOobm1Zq7CPPXnD0JBch9BzqFIUixot0rHUUw1slmsOa0Kp2i7j0vlAr\ntYfMRCi1IpKoHlbLHDOIGV4DF92QEJhcYOcro/RCqgGLRZzL5M3xQQXvPeY9Y+gFTUfs/x9A8kay\nwn4eES6oNeLk2bSwmcObY3YdwyuEHrHJhbE4qgpLHbiRZ3512sgt8bQVnlzi+SLc+sR348pBAkXg\n0JQcI1GEWip7K3ws/aF2JwUDNuf5sI18aI1WAy0asXlqMHJVLuK4oTJ6IZXALgS+NGW+xjqnZCS3\n0jalBCW6gScHS6m8z4HbBZ4q6E4QmVAf2UxYrE9EpSpnCX1M3TwlBgo9joOBjf3wPJdGVWMtht/O\neOdI3rM54TEavlZuMO5c5EymWKV6z1bhkvtk7rn+0S1Uv+h1pNZGXS+8hHiNRI7oLayXzP3okOhQ\n18l5ay4k76mXXjINQXAuIlG5uR158BMcJgZT5ujZqWNtSh6MAeG0wQXj+bRxPG+sl42LQBHho/2e\nj+4Sp0vlsmYqhjmHpcTgJ7bm+OplgyosrrvczBvJOUJs3I9zF0FL4+llwTnXHTCu+zWGMFBc4FYr\nazBuAn1z1/rdY/ZGcQFJQrl0YWAioxYQWTEdwCA6IblMoVAxRr2QmdAERaHZyiCOIAFDSD7CEL5Z\nQ6oYVSbOLnOfZpwVHvOKtkCtSmtK8nAbPVveqLlR/ExpirQeNTkuyjk3vPS8/PG4EgXmg+cwDx10\ncL0yLUV7Nn4xPjxdEO8JGri9T5g0xn3qmwkxphuPM+FmNyNkNhNmB1uplNpv/I9j4NYmxuCwdseb\n98+8cEMtSlsdozc+++VbXp4nTu9OXKzw8oML827Pw83AbRrYTAitsrz+mDR6yjkzDJGPPr3Bi3Eb\n+w3wJo6nl1ueHs9oPdDK2mlSQ6CeF6olkhfCYUcosDuMPD4e8YODrTE+3CIY67tnsjcOhxsurnB8\n+8ybN3CTJp6PJ8aP6zdExKzK81MGd+mTEGDLipgS00TTrUdknCNMB1xu1FLAGrYWtmWhph3OD/ik\n5ChQCoZnmnc9EtgqkoSWV+r5gvcDLv/ReZj+OPYitTXCtvLiAoFKdCMNI2vlEB3OQwuOujSKKiE6\nKIbZtRviHH4QxuDZDRMxdPLXbYrcjwOt1u5+FM+Hl8LZGqfjRi6VWiurGg3hsBu4SZGtdEx0M2jB\ngNj/Ds3z5rLhGmziCVbQ1Yji8HFl54fuJ2q5p0+8dB+lcwzOM8ZIcZEbgy0phySMY8QvfVJeRKl4\nJBrrsU+yRlc5nhyf3gZeLr1nHEX4zoOjg68j+1J5d/b4yXFcG0k2Zh8Z6BCCFBJ+jn0dCUJ1xrEA\nO0dKjsEqD9WTW4LrXmS+2zHJdS9ilc+jo1QlYmxeWFZYasaZQvCsT2eC45te2HAVAJvaFXldOa1w\nWi5IDLjmmcaEqeJ96kAOgTA6fIOb+z2ihaVVprij1ELOXUq7+E6i66iqiadlYWPEGrQSiWQeHmZq\nM86XSqZyXpQxDux3gdGPvYPoDJWpX6zlRi2VeRoQ3115BlRVzlvjsm3dXeQUM0e0fviq5onOcDHh\n68AQI+eyIb6DRGL0iDPylmnSgVGXVtly7oRqS6xlxY+xT1OvqSFZFaiI78OJ0gTB8JKo0mj0Q5P3\nI15bTyiZYq32A2Yc8C4hUnvyqjVEIMWEVsUAfO9uaS14C8jfPwT+//T180yY/hPg14B/6v/Be4W+\nJ/6Hvf6B7/mv//pvM6Urd106xeM3/5Ff5p/9/neIGjEGJjJ2MGKe8GrcSWKzRg2JS244mXikoFNg\n5yPBPKtX3reBoys0jT3/nR0bnfmeXUCadAEriS/V85PLRpUZb40xOlIAHwI7ZyTfGH1/iFdv/QCz\n9bG7a0o7B3TIXGpg9NbBCnog1hUbhUr37NQQSOPQ2XGuE9iau1Lb8KynTNCNMST86BhNyB6CRRYL\nNDcgdINyQfEYd1K4bEpgoNYKFGYVPvWZWr7gRvutwpru2OKIJo+GyLN5NnfofaRA7yqp0lS5eJDW\nc+lzAW1KVSM2Yd96nDyXBq1juGcV5tBwyUjW8NYopphM/PCSiQz8ynTFbEph9JCaYxoaTgNbM3Cw\nVsdRTty2wFmMsSrBOcYIdc0EMhc/88VlZZdGim9c6sDRK5/pkeYdf/cy4wZ4NTV+TRUXAi96ohG4\neOXedYHsyZRdMOr1yFasoRTuvPGQwJN5cs99cmmOQSvNC+eceE6eS/aMk+Fp2KAYmVcEjk744hIo\neeWQHEOaWEz5qjTMJzKRasqPVRE3IFslRkFrofguRvSh2+UdPaaXW2EojcUuiBNGrbzaAB84hUzM\nhScVFhf4fQRRh5MBt21IiGAeFLQ5Pv/yB/ydNz/GAPUOmnLOf6Q3O7/QdeSrv/If4abDVeDeHxCf\n/BP/PN/9jX8Oba2b6MUTgrBdEmaVFLv3SMVxflmY9nsuaybdDrxyjmqRE8YXW+XxmPEOcjZaVfLa\nqHo9uGvvnQwp8PKSeff+iBOHmTLsZ+apC0PnUYhj6MJFVZobyeUJ2tjjgCGxXIBROefClCKXqgSL\nmFZwiopjUEWdsHfQyGAFT6A56TjZ6xqSUuAgAzlVRoPsR4J5nori3ER1EK4KRY8R/YbS4SRFO756\n1MjDmEm68cm4UNX4IntKiLQoqI+8y8omE4PzBActKWOjy5k91AheA7ss0KDqyNaEw0f9W5rbhjXh\ndkqYOoakhKEyWWWnjkxg9Y6/935jcpHvf3uH9wG1xuAd1hrfT73D89PmmJ3yvgRW3ZhdINbaN5JD\nxJJyKq6TWBf40U8eub3dUZthaqyXlUsUiIHf++ET/jBy+9HEn7q9R0Lk3dMZc/DSGt/5eM+A56ka\nB29k76EaxfqB8j55/uzk8GL8/g6eH26IGKI7WvQcj8r708jxAoeHxBg7hCRvmY8++phjbXz5+SPn\n5xO7uwPzR/e005k3b5+JKZDVsFJ5ezkjEshfviHt9qgpPoQ+sZt3pP+DuneJtXVLz7Oe7xtj/Jc5\n57rsyzn7nLocu3A5viQIBccgIgGREESORGgBogFSWjRoINFBRCIdhBKJqwCBRAMhhOjRIwJhCYRI\nlCiJDUIOMsbG5XLVuezbWmte/tsY4/tojHX2OWXHkatsVcmjs6W91l57ram53n+M8b3v+4wK9OxH\npdYLZRbCPBFVcSskjYRDz3w8QjHyY0YnlxWxDQ2J5fVbQuoe2/oMilO/87exT/9WK1uKgS3nNmX6\nw1s/9L3Ip3/9v0WHXfuCj3br53/8n+DFn/jTzYIIqDtRA9uaMArDvqPYDASWOROkZ80bqUsMJDR2\nXKzyyeuJU1kJrmzFWgYtO0bBtU2XRaRhKObK+bK8a+2M2tFrQjuli0rsIl1MBHOyKO4XaolQDSOw\nzuC9YdlIGtjqo46QISjZKwMdGuE2KuMuEHQj7JuOgL/TkQXhKgXG98dWbBQgjZkpC0vp0C6Sl0xG\nCChfe6Gc3mS6LrCUiOF0teOj9wKXJfP0phVzSSmsGvCkWIy8eSisMrS9CJDGgXpZMTOs79B9oszG\n0wPUrVCGK9YqzHtwjG2b8AK7XaTvew57SDvo3VBLLEUIYvzqx/cMHvnoxU3j75XC2AV2HVz3I6rt\nWahBOU/G8bJyPfbI1GySxMSQEuclk3C8KK9OZ3bD0FAo5my+ERKICq+PCxKVsQ88H28IIXJaZsBY\nLfNkP7LTjmPeuBoSSypUC2RvU/KbXc9Xbw4ozsfHI8s6gAqBgqkyLZU5V5bZ6PfarHrFgcooV6w1\nc7rMrEul63r6bmAuG6dpI2gre7BiPNQzirLNMzF1mGdEBSegmkjRce+a5jJTc0DL1tJGwVDRphF5\nA4zcuq5a2YM+li2VlSABMJBm1Vy+/cusv/1LyKMzw9ywdfp9/Cr/4a0f6MAkIv8Z8OeAf9zdP/7S\nhz4FOhG5/h03O+/zxc3Np8DP/44v+eLxz9952/M965//k3+KD2+ekmJkL8qVFjwIrwyuOuWFXriE\nHQ9bzxaVdQtMKbDzSsYhRe59Yc7ONieWYDw7dKh3dKHwlZToPJN9JavQx0AW4XUxcheRqlxUuZgR\nxxGxjl42klWea+VKK0kbHHTKIGr0OrB7bCBBIkWU0hVmU07ScaZD0oG5E2I9gBV6MW4j3KiTq7HV\nyrUGVCpddZI4WiduECQJrokN4ajKLAlUuDY4BWNCiDhPqkCsVDWu+jZJmGshe4N3vqqC7J+xPdpp\nTGAzJQFBFsQ7rs1RKirebqOtOWNz6TnT4WKk5EgU+qKMIZM8INXx1G4Mkhthy2xeGQt8VgKv6ohI\noKPyQSccmNvrtZ7oIuzGPdO88N17SAJDTMSQ8Fp4koRzEYZojYSuynlbCV1gYIea8dXemUomemLr\nNoIFimaeq3Ppeo5r5XUa+FRWyEa1xDOpfLUbyKUwRuOZWsskdZARljVwrpHPSuTTzdgn47gopjty\nWUGc58W56mb2aly6a0xbIfUpA9ZzpzNfU6U/JM6rMlsix56lBlyc1TJBAtXXVl36aFOIAgcBl8rq\nzoSzv1ir22cjbE4tF4KvvKBnr/DdYMQsvFDYUs+NCPe28SQkJpTPzOhVuHUhJTit8FA3fvKrX+Pn\nv/o+JW/M9MzV+WQ+8t/9nb/2g0jH96wfhY58+Av/Otx+xLjfEyIc+ogk581d5moHN7eJbI7PCRtg\nXTNdb3SpJ2fn9vbAtKxMW8bvhGUxPnj/psFe04mPno8QIuuyUqoR+kQvxicvVzZArLVYzrJyuB4w\nS8TH8OP1dcftkPDY/Nqlbqg6nRt9vEYHfdzoOCU4c3bmWZmXNul9iJW997y6K+z7hesh0HWJVTq8\nKBGHLtHjJFfUFq6iIFL4SnfF0Qc+2SYsdyDC867jwVaKt+nNDvBQqGqEnfOh7vn49BZkBynzsCra\nFR42WrC4B8rnlcZLg3LSLB+I85Wu57hOVHFW6xAbqGLEznETuqqIryRvrgIPBe16EpnDVpms57rA\nr9XIp1tjwBxS4itPBt4zZ4gQ7IEuKM+fBF6fhP/zTSZJYL+PhBJwLTyNkdNWCH1gwwii3F+Esasc\nYmRLynv5QFmNw3jFZv4OKH19uyf2kfPH9zwQePvy0qwmVbm9SnzwjWePF1SZJ4/Z2n4fyET0XFku\nK59Nlc/OsN913H1aKMPAMp0RLbwYEk8PyofPel4urZSmOtxfMofhik/uTvzksz3xo/c4PVyYLhvJ\nwLTjcB2Zpw0NHWVb6HZ7oDVyduMIsZX5mCiEQth6NFWWaYVizC/fgGaeP32fMUTeHC/4srXw+NMn\nXF6fsXxGhz2qiWWeULTV7F/3bKeVeX4g/Ng/Sv/Nf4xyOWE1IG5w/m3K//6XfwDV+N71o9qLfPCn\n/2Xi+18j+UAYlUEDEpxpqgw9HK4amsKPiidjWwoRJ8YdxZzdkNjq1j7nnNk6472bHpeBFI982I9o\njCzzSrZKtxvwZeN+yRRvOlLE2WphkA6zRHiceIxD4joFtG+v9WVZcHF6jVTvGVNAOzA3ijhLhVKE\nTSASuCQj1oFpqaRY6MMMXc+5dpzeVj68CjB09ND2ImxcdYKENmGeauVcjcsZ0MjtruO+LFzWShR4\nvhsgFKpmbp91RJTLZeP+LOjO+fj1yv6qMmVBQsCSsJwzferbXgTnyb5DCag4fVgfYctCtoZVcJyo\njvRCX5XDqI86ojgDF+0IvhENLltkX+C3jhMP5wlJRqqBF9c7nnQ9MSqXdWLYBT76+oGXn038yscv\n6YncjIH9cGDZZm5S4jhtdEOgYiRR7h5W+jGwI7GZcSuVvBp9HCi+EFGqVcahQ4qyzRuTKdN8BHVq\nFXZRefL8irxV6lB5Mo5IqPSxuYeWKXOqhZeXhc8uE/uu4/40E0PHts4ghcMwcDP07LtE3rUJkATh\nfFnxMHKZL7x/2BFjZJlmNocqDpLoAmy1xQSwlRQ7XAA3FCV0j6VgDq4F3ZQQS3ufVvAyI7qxT1f0\nIXJeZpzM2AXc2wGr5JnYDXhpsRcRIaUO7ZS8FIplhm/8HPuf+DmsbrhHrBby/Xe4/8X/8AdUj+9/\nfd8HpkeB+ueAf9Ldv/07PvxLQAH+KeDzoOUfAz6i1X4C/A3gL4rI8y95h/8Z4AH4v/n7rOeS+WN9\nAd84S+BBIpQVZeRtUWauuffQbGQGY7jhlFeugNEAL7gkvlKdQ79wHWFfI69S5a3t+SjuuAuF3+oK\nqcKtFVyFXbeCB2xpVsBogbpmhAt9iGCFpRbmuRBdWfsDkzrZIdaRQStrUMbYGvjWoGQC+MSVBDqf\n+GpWelkhOlGbzWpDWGNgnwYihSEt9Joa/FF2uDmTt43QQuBCx8WUSuJOjcmUGWePc4yVsQpXJFJw\nAoV9aE/f2aAPmZsS2Dolho7JA69D11ppqpBLgFDYEeltY5ebg2PNC0udSNZhWsCdpIHwedtYNFDH\ni+EivNwiRxdSdrridHHmo2B0apyL8bBUPl2Fre8o+hTNwtu7yBT2RDfUhehCSLCLNLzyXAAAIABJ\nREFUSrdu7FPHNcZ9DcTaLJU4ZBQPbRKjMXMtxjciUDLnOpBk5aNUuOsjZxzYgc8slvis9vzKnBjk\nzD47t/3Gbe3ZqGQRqicmKczW8j5xc4JWIgFJI1e1460uXDywD5GHGY4OZ4tstfDeqJgdeGULxxx5\nXQpP1RmZ+DAEziZoWVjFkSEQa8EE0BmpYCUwaeHaMuMUGfvQpgayETdhjbDreu5EWTYh+I6tc5Za\nuITInQpG4uTC5/25N1r5UCu7TvGyclIhunEW2IJyIJNVYFm/X9n4XetHpSNDF3jvq9ftd2etnJcN\nO7Wg8sPFWHPlshXOS0VkI6SRfNzoHyn27hkk8HwIpJsdz3ZC78YaCg8Pzo+NIw9147N1xWvgRguz\nJ25f9IgpeYPjw4YmwYphtqLaUYHzceb49oIEQUMii2NiKAOdZDxkhm5AqrcsoQprKNwmRarzY9cD\nUTsChR5pbJOYcAqHGLjpr/E489PdSK0rmR2Y8YknXtbKXV6pPnBxRS20+v8MM0ZC2qVODuw65dD1\n4JWv3T5lLoW75ULcwc/qNQ8p8NPPdhy3wt98uXAi4lkY5wyhUNJI7xufzifUnbUUsjmaC8SIkVFp\nwe/nw4EHv7RabRNqNu7KwLco+OqNgZOcr6fC2MPbeeXjY+bbDzOyG8imBIQ3v7JgZXuEHjYGST8k\n+qFDdeP6MHAtxnkurXHMmy2zCiCVbuiQWNntIj+1e06pwmWudMm4sYHvPrtiyU6Xmo22rMbd3cK3\n/t8HhI1hiFzdJJ6MO9aS8aAskzE/QiCnu0wKGRVI6wwpEDbl7WpM5lynntevz9xNC8tk1MvE+z/x\ndVLo+fjuwmlSXn/2kpvbJ/TJeXFzxWVdWcxZAsjhBSkOuEKeH1AqluF8eaAsM9eHG/orpwvKdQ/k\nwvx0z7P3rriXhF824s0BE8eWla0USudI2lOs4tXRIdB3iZsnew7Pd6x2Yh4itha2uhHiQA0NSBlm\n5Q9qpvlR7kW6IfLsZo+5k4uxFsOWStDIZTW23Jg8M45IRnXgdMkkBZEGRRcLXHdCN/bcjJFn+8jL\naeGyCe/vr3lbFt7WDbHIuGTcO3YHRT2wlcq6NKukZwdt7gAzayDbS20HYknNveHW6uK1IFqIcUCt\nZZ7MA1kK+xBQr7zoe1IcCGp0KF2oXEhoLNykQLeLdJ3xbOyRWiiyQ8x4s2zkUlkqHC/OxRXflLel\nkh/aazEE4VxmenVuDoEuCirG1XXH4aDMa0ZvE+/Ljosah37kfDHezAtvQ8CJ8Hbh/v6BdH2g98wh\nFtQbfPbuMnMdhUs2DqMydK2OXT3gsfE3twKpGB/fG/frQjCIrvQBvv68Z0B4WDMvjxMfr/eoB4oI\nCvyN33iL19IqFVwgKlEudH0EFg67geuqnM4ZiYaIk5eCa8TZEEnErtIPkR8fdrjBNGcsOvvQ8bBs\nLMUInxfRFGeaNl6+WhApxLAyjsr1sGOtBWql+KONGGfLxpECGLFuIEoKI6etstWVq/3Aw3lmLhs5\nN6fK4eoakcTdvLItcFxXdqknAO+NHVOnDEshY2g6EFxbH4BkcKMWIXsbFAxE4q4najvQdytsQ+Sw\n23PO4MXQrmV7rRaKONkKhA6z+sgebIiNcQj0Y6K4sCVFrGVMPTSWqD9GSH6Y6/tqyROR/xz4l4A/\nD/zalz704O7Llz7nF4C/QOMa/CeAufuXqzz/D1qV578JfEhjH/yX7v5v/x7/7z8M/NK/+k//WX7q\nyftkjOdeeRKFvjPWtfAmHPgEIVSjF2EnmX0c6KxBRzMb5oHFGkQxxERUp4py0shrHznrAFR2Xugi\nDMAVK4NbI1Bnaw1r0rIEewoE4ypnnnTwRhIbO4pXJiqn0trd1Cu9Ki6pTZ2CUT1ykMqDADJyI85t\nmhrStcIiSpaEaY92A0FARPlOdWJo0xiA5NKCywjmykobO8cW8WuNN3ijJQMuzl6bNWwzZSMwVmGQ\nyta38HcKcFML1wkKyrFE3gSns+Z97cQYrVDcMWsj1VxyA+J6aRTurdWqSgi4t8OTmFOpDEHwtTX+\n1VopBQpGFiNkIKZ2ixCEUDOqgV4CUYzrxzD36EqXlBgcR5m2zFWC1Rakjq3Yw621rvjGDcqKcSqV\nzg2xHSeczzIcLwshCmO/5zYW9pbYxYlpXVHZMeXM1O9544GgsJbWwjVbYCRQbX1X0rFawd0x7cjr\njMSO4JWVwEZqNaq1otZqR6+BVAp9H+iDs5bKeVPe14kU4K46HQEzYx97bsNMVzLGRi89Q6ycamDc\nJz6dVo6245Ur1SKeAl4rR0vU2FFLu6Hf0exi137im7qS04h75bI4h8455uZJp7Zw7KHfeGrtpr24\n8GsPE3/5b/1N+AGbaX4UOvK5hrz4F/8jho9+Fq/CblBubndcXSUe3k7MlWapw4hdI4kf0tgsqBjz\nUtEA65Yxbw12nTaG1+JwXCpbAKgkS6RBGIAA7ERYiqFKA5GOTpeULiZSMpIrX+uMj13JvkM8M/vG\n8U3jOTlG34emIVEYAxQT9ipMBlIKh9BzGDeCZkoZWESpj7wdHXbvNOS4zN+jIUgg0DREjd+nhtA2\nH96aR5NFLCkxLGBKFxoo82eedfQa+eVXhWwzSkdOkU6MwVrm4p2GPLYnFcuoOdkTrkYsgEYiYOoU\nyYzSsbpynBdyLqwXKFIpVrAcSEnJpfE8rDSW09BHNCiHnT6WYSh9akUXgnJcKkMvbSOUDQuRXPOj\nhmSuJbGp82Y29sFAex4uG5+9PvP25QOpj9w8vWY/RvZp4HoPb94cGQ973nxyj497LmWFIKzThq+t\npavXyHlZ2I0d7nCZH9+DMXJ+84bu6rpZSEuhSsDWhbzldgA0IaQe1szw7Jo4RNbLwvr2iEYYh4HT\n+ULUhNXK/uaW3ej4XLBloxsHDtcdp9PKix9/xm/+P99mkY51nhEUUnpstzLoe9hWGMcWCN8K1IV9\nn4i7W4pV1tdH+uuRea3NKqyQ7+/QqNw+uSV7wybk03d4+Kt/8Y+UhnxZR776z/4ldl/9CWqBYRDG\nvqePkXVdWE04r4Vg1qrfVRnTiCgENzZroftsGXdIMTbLq8BmMDktC0Yl5UiQthdJARLC5o3fhHv7\nu9DaYfVxX/LhzcDreSXbjpJXJttY54qqgFjjQElCAvTaoLg7Fc7VSRhXceTJtTGOcHfX9iL+2EQZ\n94d3OvLZ2/P36EiI8Z2OePbft45IdLIrOUMvkXRIWJne6chh3/PedUfZjJcX53g+k0KP7Fvr30ih\n2Bd7kW1r7pdl21Bz5hoQrfQEijVmpqlTfGWX9qy1cpwWcqnkahQx3CpeQssKWWnubTeCBlIIiCpX\nu9Yit9NEH5XhEMGFu+PMk5vE5WyotT3mWr7QkZs0sODcn2ZSBJGeeVm4vyycLhMxtintfoyM0pM6\n4TxfSKnnMi0gkalkCEJZK+Itc9VrYvHS9iIubFbRxynQVpaWv8XBnCoBLFOrNeustVY8qUbsIhpb\nFt1KbbgYFdZcmuPFnCH1xO7xn5ZCH5sNNK+F8TByfHhgQ8lrbu2nQfFqWJXW7mMZQkcI4NVAGqwY\n6XCMOhdip6ylxU9Qo+aV8JhpL9rg8Mvrb/PZX/3hteR9vwemxtj83esvuPt/8/g5PfDv08SsB/4n\n4F/7e8Di/gsaLO4C/NfAv/V7weI+F6n/9Bf+LB9dPaFz51NzTgycgvFQDZVEEmVkI0mzzV0Eqhk9\nkaskfC1VumocYmXOiXMtxCC84gkvbaFoR5C2wRGt3LgQYuUaYylGb5C8nb4vxblR560oc4As11zZ\nPTsXugCLjHhs4cpNYS8BcmVWx2JsGy5vlbuJVunrMROrMgSICDFUihlLHZkjXGSghsgWjK5udNKx\nBkjmhBDoq7KINX5HLaABZ6X62E7kVuhDpZc2Xl0ccm35hJ0aYxFWDHNnlWa3a9Tm1utPMG5KZgzG\ntQcmlCTKm1AZLFJM6baCyUKoLd+UtWu5EN3obUNKIAXwUsAjc94YgPO2gij1sepy597siUEwIjok\ntDQw8VvpIAhvV6GKUyyScHq70MWRWhZuk5ELhNnZ4obKgNrKVCNHa9OVliQqmHZ4KUwEeqBfjEsU\nyqOVc6qwA94PkTmuGJFdEEoJHOsG0elcOFukrBvgRFdYVzw5hySErAiZh+ws7iyh48ZOfIRz6CrI\ngcnhVXGGunGahE0r+xS47SrJYbPAWTo0rlxw8MjbNTDRN5aBGCEIpbaSjxD2XOvGzhwboFZYpE1E\ngrfm1TsLSK2cgpMQlmxYHQlh4iArRSIp9qgIGoRL7vh4uue//9v/C/zgm50fuo58riE/92/8V6QX\nP0UngZcPF/JW2bKxHBfiTvGoLaczdCwXo5aNshq7UYmHgWc3QysKuE6cZ+d4mokxsJXI6eFEjYHw\n2FAlLvT7RIiVJAPVCvGRpn516FlPmf1V4jgV8iPMNbAxxkjaKbIKHh0LjfDeh4BthSLgjxTumFpD\nVBAIIWHBv9CQGL/QkLUjhUx+PAh8j4ZESBU0RCTs8Hxuld8I0SprFwirv9MQHRLpsdlzcZB5bno1\nDL8vDRGUMTp7Aqs3Dcl2YQsHvELI9r0aYgFVRUImiiA10TNTPCKeuMcYrUEyVQJbcULyVkWLMUjL\na+xVWZV3nDhUeLMszXqygarQd+37MYexg62Az8bFnLFTcozU08LDeUNDxEolU1pL3yYsa2boIpaN\nvD0Cp8vGmhtj5vr6iuK5wWeHQKlwOi5IdFSEPFfKsuJWEO1Z3twhnbO/eYZbBXfOb96CF0wTgYnD\ncGDoe7r9gbUYbz97Q8Cw80qRDRmu6KMQuw7zyuqCeGu8jN6R6wohNsyGOI+EFYIBqQXhgypEwa0V\nCrk5YqApUtcM7phXIspaK4EEvuJSkMfQq4pDjHgBLr/F+r/+u3+kNOTLOvIn/5W/QnjvGyRT7peZ\nak7Nxra1qn1S0xGCUubWzltrs4lqSlzt23Nx6CPLJsx5eQzyd0zrRO0aYuBzHQmqhFiJoaNshRAM\nxxm7gbytDKlnqpnsEGqHho2kgdgrsjUdkdhhXhhixDdjo+IxIrUQRCEo4bHt1gPvdKQfunc6crlE\nvG5s9e+vIyo7rJ6xFhZtl4YxEPKXdKRLdF/WkfVRR7rfn46MQ2TXwU3suOS21zqej4SrG+rjFOnL\nOrJsQuoiEnLDDpTEdVqYtggeebCNUYXjdEG8IVlEnb6PmDu72I5/Owlswek64XIWPMDb6YKJ47np\niAJjDKzFuN0HtgqszmSZLkY2AZszU84NF5GNTSoqQi1QvLY9hLdMePXGfMpeiaKMw0CpBSfSp5ZR\nX+eMREc8NpZjaXsRIVLzikSnk74VR1RnKyu4YRoJMjOEHSkFovbkWpm2jWCFuhSKFkLoiV1CaWUN\nRUCkslUnlcBKplU1PjojPLQ9iTvE1PYQSstOuSNecVHk8bfYquNmmHlrzHMjeIM+IxUCiLbJl6vg\nptS3v8XbX/wPfmAd+X7XH4jD9MNa7yZMf+YXuL5+gSY4mHEbFhCnZCXHwKJdu8tIlZSVBykMFW4x\nRq8MYowxMG8zQYQtKE9D874uRFaPTO7cGySUPgh7qUg1iitZSsshAd/oI7NmXtWeXtvG5FQaWyip\ncxsrtxI4iFGDsmpgVaVWZdLATjI7d4IGlseRuQVhqkbvgRBg7xXXTGZPCa0hbxUhy0h2I4fIGIyA\nce3KLrSa7VmV4plq0sbiOCpKEiEHUK+IG5uGVmdqoNoYRwdzYogUlNUVEWUuK7TkAaNWeq8Ut1Yx\nK8LkKwfv6cUZ/EItzrW1582qBqUSVImhZ2+FJbSKbLXS/KquJIPKRK2CWiNKdgEeJZI3foVFYdk2\nrtTwGNi2TJDIpkYnEc2ZG2ZufGtci9hxqYZKGxtrFKK2DImYtkYgApXAyZRThVPLzLPWZjM5l8pF\nHSuRXqD3jaKBAWErGaQ9iaNVLlk4EyilNXqFWjB39sHa90ylemIrQhcyUw1E4JUufFh7vnJwpnNl\nF2eejHvuVmfxwMdZmdTZirKLkLoRCZHLZcVTZvKefadspWKuaIyPJRqtf7CKcbMZGozeE0sxFmCN\niocIxbAU8Fyo1h5I2Rsjp0oAN1wKaj1dmokPZ/69v/PX4YckUn8Y63MNefov/MfIzTfQXulE6fpA\nVaNMQhgcq6lpSKyoOVspbdOdOqIqsVMOQ+LhNBNiy5pdHwbcK7k4XuCyFpZ1RVNgGIbmGvCKWSBv\nC2noyAYfvbfnnDfOC0QJJDXWXFpFbYzsk3O9HzloO9znWtgUzJxaM9olRlNCCCz2hYZsZSVJQDW0\ni4cIm3Xs1N5piGb/Hg1BlV0Y0C5RvU12P9eQsi7vNMT6PdjSovPw2FjUNCQP8ffUEJvu+FxDQp8a\nMe5LGnKqZ67l8HgLvlKLcwUgsIlh1qa7SZXouelYaQUdX9aQc6otKN4Ii8QY6dhYPLHNAlY5R+EQ\nQuM01YJ6IGP0EqjeKuefeGEgUEPlJT2qDpthSdh5YJXW/qb6yDehAXMv88zDZMTiTLlQa+V8zJS8\n4KakPlIrhCAMKXE8XkChiwGxwjxV8rJQtq398I+NdKSOsWu6aB7JSyGk9j7wmsh+okvXfP0rNzx8\nciKFha998xt88smRrcLb+yMiC5ad0HV0N0/QsWP+9DUmFScxXI+sxwuCksaOUg0eNcSoSAWxSjcc\n2KZLu51OisYe3zK666nzArXAY9mGFEFUW2GBtUOhq9NtD5z/5x98wvSjWp/ryAd//i+htz+GppZr\niLFNLXwTSIbnL3QkurPligRI4fFCJShDCkxLC9SbOPvU41qptR1Il+rkvOFR6TwRE49FS4qTEQ9U\nE17c7pg9My1OCoEokHN79hACu07Y9z272INArZlV22VyLZXQB3YWCCGyWH2nI0tZSBIIGtg7VHUq\nPbHUdzoi9Xt1RFTZyUC/71tpxHl5pyM5f6EjnvY4y+cygvkXOlK631tH6vKFjsT0u3Vk4sLB98So\npLRRijfLMrBQ2UogKQwpcj0osxe2qVKqfI+OXOL2iPdo/LrUtShDNmG6NxTjHuMqdaDCvC50IbF5\nm/SYZcZReZqEYh39UHl1aa1vtlbiGOgsUkMhBcMc3Nt+5Hg2pnXitBmxwlIL7saytrZWNyUGHi+E\nnCiJzTaQZi10tdbiWVt7IO7weNkiMdCFNr00j1hxNBjmFbfI6hcG3XF7vWM6rYRg3N484XyeyBXm\nbcElU6sQgxDiCClQ5rnlyCySkjauozcIcP0cVujtQkb9kQdFJNvj+1Skpe39sX7cKv7IfDMMSmtb\nNGnYh6BNR+T4klf/41+BPyIcph/q+jDBi7SweGDxzIVIJLAG4/IYngu1velfe6VH2WtBqUQKZalM\ndeFJb+wFPpuUV6ZchYnSjSiFqwxXQagaWGvgNmykrlG6L6W1T5nDZ+acN6W4sYTKYMqBDXMlujMV\n5SFooydHpzd4TypPYmZkY9BMJfK69miI7ETIGnjiAcO408SddfS0W5iv1Y1zDJyy8RZhDU5nRnTH\nRHljlVcVoijKRiyOB6enRwTet42DVq7rAiqsVGwb2YJRQ/v5zq6UGNg8UDzj2nOpG1cSW/jTA7ua\nOdTMqJXnHKk1E0SwMrMwMpfIqXqruxbhQCFoJm8w+YWNhJeVLsWWBwsKpWIiJO1J6niUdwfLYpWd\nFf4BuQOHGIwpOu57NAYknTlQyJtz7grUjjkPXEQIeSW58FAdVWFdjF5BgvJ6qWwG7HqGWjiuRnaF\nOlOkQ70SESQLB4fZJ3Rr1cpdp7yaKrcqxCEwmJHd2LkwiuGheczFndcl8sqdcxCeO7ht3KaBX98K\nL3qF6nxgkSzGry+xbVyHA99aVo6m7CWwhI1vhsrbuCeq0unGqRYkFK5D4r0+0deVYWyWh5seLjmw\nObi35OVbIguZ1YWQAk+kgjo7F+IYiFZYdwOYkHMLFl/cKMR2iBIneKW68kr/npevfyTW9e2e8GSk\nbsY8z8hjgYiETF2NarVNP4c9JS9oELpdalWrwDpnyrpwfbvnZlQ+eXnh5SdHul6IY//IEJG2YZBA\nscJulxj7NhU9ngdSCOQNXt2vLLkdDlKnlG5s9ksPRDfmRTjnQiTT7Rrr7EmK3PbSbHnJKGXjWA5o\ndXYpkjXgW4dRWR6nLska2f5alSko05o51Uqg0pmBRqRUzusJm5uGSDBMejw4oduj4gwhcNDCdTKe\n7BPfvqzINlCHxvgQcRZrU6li+k5DtuXI0F+TYsG0Z7BM8Mz7w8gfjxvfzjPfjJHfLGc+y22SOhnM\nJBRnp+DjRl2EKYNaZJPCKNKC20GZtVUP77WxajTBliNSnJM0S84394ZKJHhl0sriEQ2RLmVuyeSi\nfOyJFeM+t3bK8AiSfZiNEOFyl9ntnEjls9crtRS6YaAblbs3E7gzXZYGH7dCigHPGTxQ1gvTZxNe\nneHJgbu3bwjSM753S1k2as4IQqfOMAwspxNGoNaC5xNzSUSNbGXh6Xvv8+aTj+kOVyiVUHf4tvKt\n377HMW6ev+CX/+63EakgA87Ms2fvcS5GN4yEWlkvC0Zl//wZw9UB8sp7HzyjFOPm2YHpPJG3BkcV\nrdx9dqSUmWyZ/sk1ooqExh3rx4hVJ/YBM2U+nsnFqGXFSZRlaW1aJtS8UtbLj1oK/kBrHHriLuLV\nW9bEHfEAWvHVqbYh6ljuWS2jQQhJ0CpIgLplpryxG3v2Cd5cVh7OEyFIe66JkMxJKQLtpr5PoWWY\no3JeheABM+d+3lhza670rOTU06kirogay+acc6GTgg486kji+T4xXvX0fUJy5rfvFc2Fq7FrOrL2\nVCrHuXLxTHQlRXhxSJxVyNPGpRpmmc4MkQhWOdUTD+vpnY64P+pIbDry5KrjSivPbneoKue6UU47\nVi/vdOSSwZdMrl/oyLodGVPTkbgbGWvhaqfskvGNq8hp27jtn/LxqV06HdfE/UPmfmkNlKMEdk+F\ncp95e155OHdkXxlCJHjbiyzBqQH240ApFe0i62XDFucomWEMfPSiQz3x41K5uIMLwW4IA1xr4bIq\nd7OjXWXOgfM243OrIr+/rMQeljcLXd8KFV4/TK2lcOgRFaapfHEp5o27JeER3Eqg+sK2tAl6jIFl\nORJCR+gSLvYI2RZidJIptTTkS7GK5fURjC4tt9aPHE/39LsRdWfnA27G24cZxxjSwHff3OOeEe1w\nzez7HdlB5ZEfV0vD/KSeLg1AIYVErc546JtFsjpOOzTNW6VaJlsD0cY2dqLT1Ky+3gpEzJVa1mbT\nLit4wvyxNc8V90r5Aychv7/1R+rA9BteKUtGw0pfhWLCRSqLwwcx8IyO+1TJtnET+tZIpB0v7MjO\nC2+Gjm8Gpw+Bu1o4JOfDuFLduLfMdxaI1kHv3Fkle+BVFXYbqEJAuU4NfNutwgfaRMyrkcrGdYQP\nUmIh8a2U+M6USZK5ORthFI4lMA8KpcPjngdzRhI3URlsYtkWggWGGOg24z0NHGLiVCrfDT05wyCZ\np9GYPfJQtxaCZCMphNwseYayBIEtEmWjqmLWM9hCDjuKK/vifBiUr+tCz0wIM7ugUDYW2XEkAZWg\nwpA2+jwTYgFW8lJZTPGyYEXQFNiPkVsxTpbxC5yXll1atdKrE6TBX7M1MKstK32KeCloDIAjDTOA\n1EwyI2rmW0fjOy5sMhDKhsWVwZVBCypnNiuEPjJkIeqBXg3RgldlkZ7ZCyaRbVmZvePi0OrmHELE\nL5mdN0bVzi/kKvR+IlliDILVTAkLW1Y6X1g90V+Uf+R25H67cNN1dHNjP730ynlLrAqr9NyEmWed\nMQBdiExLYQrKx7bRFWXrEhcyaMdJnEgipMjDkrnyAaNwrkKQjl9yZQd8My08d2dvlZsutNcqb4xU\nhlipXukt8cEQoAq1VtYKP7EPiEWqwzQEtEYolaQzKQnRFJEjFtq4PJcGlcteuKfZG5NtHNLAb24/\n3KDlH+Z6+/IemXbEJIgkMGE+Z7Zt5erJLe9fj8x15ZIrh90eGSJRA4cxMIbK67vIT743IinyalkZ\nxoH3XzS73fG48PEnJwJKv4+cpozayrHrCLFDQ0AkcrhuQGevhTF0HK4CtRoS4PqgvNdFJnouW+a7\nb2dMoPNAH5v9Z5IO5oLHHXN2Bl3Z9Tt629i2QqiBLjqXUnmSdk1DauFUMpethb/f63umatwvhX2o\nGI3uHopylI1QhCQTWACZqap4vMYk83YVfv1S2dXEYej5d/7UDR/2xi/++qf8uZ99wv/wy5/xZ37m\nQ6zruV8jnX/Ae3uIeYZY+Lsf3/Or31lZLPMyGiygIfMnRviHdoG7Cn8tVk6nSH2EZl8tTkQbsFNB\ninM2Y58C5o1H1X61nc5hMXnMfWX+v++0PMNvaNuse1zpNHIY2437PG/Eq0RXjF1UQoIgtAOTBM7z\nhJlwerWSi/Ppp6XVZpuhIXK6nJvVxxxVSCLUsjLEyK7veHh1gmVimiZk2XBR8pvMP/jzP83LT9/y\n9OmeNFfOc+Xlwz3r/UpOAYktcxBDR+x3DIc955evwYTXbz5uDXfZMSuoCpuDYmgMHF++outG1jwj\ntqLa8/LuiLqwuxq5TZGjF8b3bptd5wi7Dq5CyynufOLrX9uR50J2ON/PfO1n3qdLbSJ/oV32lNUZ\n+0K6HommBAo1Ku57locZK85aleM0UaYNm2duP/gq5Y3xq//bj1oNfvB1mmb64YKIIwS8BqoUzCr9\nMPAk9Cy+sFLopQMCKQX6QRmSc5wrXz/s6MfEy/lC1xm3u57qhXnN3E0zgeY0mepKoLKsjxy4x8PQ\nMLRNNGaMXccQA4VWgHB9UL5+c2D2xKdvJ14fJywpXVVSjDwsK7MYfsoQd1y2hUEDh2FPqYXjcSVY\n4GrfDJrvj3sOKXEshZenlVkgBeFpSMwaOdraSnGkIFEIVZkpaBbEJ1gD/qhUce1qAAAgAElEQVQj\nb/M1F1n5zl2DmO6K8PzpwM9/7Zq9ZkpceaIwVwEGTkSKR1J9xq7n3V4kY8yrsZjymSjbg/C0y/zk\nUwgSeCjO/xUqD58ak1dqdA53DQC76xNLbZPoyTK7PpHNHoG5ICHSS8S9IB0wCt/61kaxjV/zx+iA\n/P/svcmuLk12nvesFU1mfs1uTvP3f5EsskhRlqmBYMnWQIAHGsmwAY98L74AD30THnjksSfuYIC2\nZIMSTbMpsrq/Pe1uvyYzo1sexK6SJVESpCKqUABjeoDdnP3lyohY73qehaCecRiQYqw14yZPrDBo\nJI4OV4ziKxThbj5gJjzcr9QipPsZedqLOFXmPOOcItZdeVKhkQlOGZzrfrSae+e3tJ/NsX308Qec\nDwc22wldKrkaj+VEW3qiqCE4Z8QQQAPRe5Z5Rgo8tgdEBDOl1tRnDquh2pMqc5oJeBKKWEEt8Lis\nOBybvWOngTk1wjRgre+NgzNCbNQMgySeXXRHWc3GnBPXuwn96YHI7Cl2COobQ/T41mftzAlmgSU1\nZIlkp5zWFYrSqOzGC9Z2wft/04P6V7x+pSJ5/9U/+Ed8fPkcp4paQZ429J6AiFHViKXw6eTYesNa\nxmmgWuXY4O1sPOZKECNK5sp7grRuY/ZKUGNpntVcR+kKjKVLYw9rxkS5Cp4kQkmZMCihVoIIexeI\nWritoD5yUwoGTM4wN1AtkYi4UjraVyECKWx4sEZpQo2ebQWnhaFVpmaMG8/S+gf4Pvf5qL1CKhXz\nASdCEQf0D1/GqAIVpYpjtNZJT07QJnhV5tZnf7wIzYyxNUQro3icVAYSB/EUFzEqrRpRHZN3OKm4\nqk9/Gc/cMmrWc62SGcXYrImP2xktQpWVVgWTylUDsSObOFGBJjBXz7x2a3RdMiLCvXjOLdOqY9CV\nSw3d4eEaXiYecuHY+hzWmUBphVKVVZTn1vO2ZW0UcZTWI3mp9Xifdw5y+lkUwKT2Qt/AauGxVR5N\niG5kVIW8MIqxZOGTVlDfDdbvzfg2GSk1qneoKRcCz9zKxiujd3ga91XZausCSjUkdETyEIW0eswJ\nszpqBh8rq8HeR+7mjlW1UNHa5YBjcOwlcxkiD+fCoRQWt5DywqeyYRoH7g3et8qI4lS5DvD4pE0K\nTvBe2Q2eYJ67XHg0kCaYzXxixtY89064c47jkrjJcJQepYllIjl4/XDH//BP/3f4FYrT/LSG7P6z\n/wb/4rdw0UOqfVYjKiFGDPp8BY0XH1wyTY5aGjH2PPt5Lty/PXJ6PBBCBwfsr/bgFEpms98SgiOX\nSs3dRSYCrinDxnM4nGkoV5cTtTXWE8SNIjS8KFf7AR+E++OKHzy3j31senKChEApGXOelnqMJjrF\nOwHxHEqBVmnRsymC19pvtcXYbAfWVhlFeHyshLES44ZcMoHK4EfW1sWA1exprtE6TObfsYZ4P3W8\nsGTOrQNZoNCqoWFk8g7VRijC6jyhCWtNiBnmAiaFUYxS4FrPeItUqXgdWMvMXoWNy3wnjDSDL2vi\nWJRkDVMhLfQaYp61JFoVHJVx8P1CxsEGx91aOBYjqLCUSjpXcupk04tJSA3ykqkm1NppZOtaEIw4\nRsqcnn434OmW00woa+J4P7PMD2yvX6DeUVPB051cFyGiJJoE7h8PLPMjZa1Pl0ZK0D4gvbnYMmwG\nPMLDcWGzidAcLig2KHY8M11MpNmQ4GgO1nPBjb0jtb+85Pabd6yHhNs46nlBRBhfPic64erZlndf\nvON0mCltxpUZHzY8/+gTTuuZ08Ohg5HGkcvriYe3j4Dghsh4vWe/HwhD5ObmkfW8dojB+ZGL7Z7d\nuOXYErUV0unMw90DxWr3m5kHcdS7H1F+/xc3rP1XtX5aR178o/+a+PzXUHFIa1Sxp+etz/7RFJPK\nxXYixg7t8doTKWupnE+JnFZUQNSIYQDtB6A4DDiUav3d26DHrZrgo+tCUlM240CzSlnos0rS68g2\nDoQgPM4rGjyHOYEZgwPxgVp7x4Ha0ODwTvHa9SRzKVAqZfBsKqgrKK7PzWwDS61Eg+OaCU4Y4kSq\niWCGJ5L7yNLTXqQhrfWLu3/HOhLchOhTHXlK0fy0jjj/VEek4avQhoBkYSkr+kRP+2kd8V75/ALE\nPHPKPaKGcBF7HO6jYYthzHVlrcq7JWEqLIe+F3lYG6dlpjVhEOPianza3MOoAzeHc1cSmJCa9W5O\n7dG97fgk914zTZRaCyJCLYaIoaHXcvvZbqSACmZCa5W0FgqJoAPq+/yq80bJxkZjnx0Q4VQSae3Q\nCkfviAdxqIcQAj54nAlzLgSvUBWnRvOCtEaInpoMnFCtUYt1imurDH7DvJwpyfr3o8OqnO+Kg+04\ncjrNLGvurr92ZggXDHFDbpl17Z4qcZ5N9CxLhqcOkvOBzdC7/KdlppROQm2yMrmBQSMrmYqR54W5\ndME7rTvIrCn57ic8/E//Lfx1JO9fXWpCk+4PUBGCG4h15YUm4tDnhMoAN9a4O3vaGKE6WutZcnOF\nSR3aOv770ArWPLVW3q5d9GalMvqG0NvLWZVtVi4YSa2b5L8w4dhG4qkxquBojG5BbeDzCVKtSOmb\nzGeycuES10NhzZX/A+V8ihTfmKKxX7q8MrjA39ZGlDOpRW5r5VYEP69ECzTXaG3grvYI4kaEqZ7x\nITC2fivRvHLTIgdT1qfU1GpGlS6j3WonsuEjYg1BGBpUbTTpXY5gnlI9KoJ/wluq811mm4XxKWoi\nqmC9uFjRjuy0iUPtBKnsL9AxUbLDTAi18jY0St6z1IzRkGb4Wkk14DCejwM5Z9ZScE1RcTyw5640\ngjhazkjOUIXV0clRtjBWoWplpxWf+wYpN6OYkVtlUsEjbJz1jot0AIOIsPGBtBqrrxyaRzRywUqg\n8cwyzje0rqQwEQfhvCiLZVzz/O1JOO0itTgOZeXCdXN7tMqohe0QGFNldxnYpjNlUZZJuXs4MeB5\ntr/ktM7sJ4UMJ5uwXLs/aWxk9bhQ2AKvy8QoQFogVkqo4DyLXZJ0wx+3iVKEqkZoDXOddviqBSxU\nBCGLQhmgrIgK1UXKOvcBbRf4gSmSDAlKqBDsgrrPxGxoazjf2Had2a/sUuuzLXVNqHMMw0hrxiZE\n4t4j4jiVyqEunG4UPyqsrjswUka8MF5eoFYwE87nLt9Ly8rjXZ9PstyIo0eioy0FCQPmhd24Y22V\nvBbevT90xOqN4QaPCby+U6IEPvpsTzpX5OkFu90NbLeOF9OWOWX+8OsD5e0KXpkuIeQAqpgP/PY4\nEXxjVeXusPCQEsc8M+E5uUY1x3EWtutMHANVlSzg1WEYGwd3a+bclLuqgGMyyCK0Jnyo7d9cQ1pX\nMpQKKornn9cQzdZjLsNEsQrmWCkU3x136gzayLqcCeOAaqSEhK4dQmAiHJxwm7b84LxirWGhx8tS\nzTj1XI2Oc2p9jqb2F9yxCodDZnCeXDvEQ0yZS2NoQtaKjxEvmWkfkdLJqmaNuhZOS2UzBDyVuNnQ\ncp9dqtZ9IdN2yzKfKLWj6t00sBueg1Mu9gOSIq2u1DCxfTFw/+qGlGZwwkeffkJGKAlOdzdsLvfE\nQdBm7CI8/+iS8a3no9/+kM268ni/whT4wR+9Y9qPfP4ffMK7n7xieLannRNLiDy8faCmxIuPL1n3\n1nHQmxfcLIUhDCy3XUskk2caLpkfhCwB85Fv398j9P+fJkptmbc3/cbdxBAzlveP3L6l49cRyvmM\naZ+Ze30/Y/kBjYpTh4pnuLzG5Qy1S9etNeRXuYgAzrr82az2aJTrnc7BefzosKIkjFNbmY/98gpz\nZKlIrZ2YFwfUSqfblooAzSrLUhHnoLZ+IeIFKUYWR1RhciOrVGrOHFLGEujakD4sya0/E/Bc7jeU\nVBHrHdExePZ7x6Xfk6n8yTcPkDJNjDAYsQZMoGngu2EkbITFGsd55VgS58fMgGfVRmmONVdSPXYv\nz9PPGZuAdArefYZzVWbpdWQw+l7EhL39W+qIFUL5y+uIFCPXigtPdSQpWKE6T/v/1ZElnbnYDKxZ\n8HvBUtcKDNFxty7kHPhqvcVqpYQtrmXW9YwPI9fXW86HmXVeUVWcwrEJjzcLgzpKy9R2RJqQMELt\nPzvO463hff/7qfS9SGuZtcHgBMXw0f/s4GR0+FccBkpJlNr9m+odscb+zgmK+kArhTAEhkk4zYVc\nGiJwvb+gYLQipDTjY4+3OQPvhf00EGbl6mJHFDitGVDeH+7Q5nl+ved+PuH9SKmV1oTlSSy7HSPF\nAcEYvO9+LufIqQvZm7QOCjGhmGctjrkswNOeHRAKj7Og1kmnVEFq5XTOiDMU7d1/dagod61gsj4B\nNAQlEn2PTvaNX+9Aibhf6HP/K1W1ojcutA+xY/aUX4eCsW+JsYC5wE4826GCX2hOCNnhx4JHaM1j\n5nmdE4cqDAY+OEKpnGvhoRqXfuIDJ2RdKCasKIlEsN42/Ht+4te3laArr9bGTx4c+8lxv2S+WYTB\nKbN02MELV5mK511VDpI4lIFBDnyvKt+b4I2PfDEb9y3zz06VtSmFxN+/bLwcHT94cCTfb5cGnl7k\nuSHSuBgaUipFlBCEbxbHY86s4khE0H6QUteYmuK1gYLmBW1dWNvMaCo0aUQRqgSgHyxwjmoCpeCe\nbkEWKlUcoWUmDWyLsaHxsIBYJvqVWDONClKxZjRxJCnkufbYivM0U5DE6Bsfu4qz7i9xCp+NPN2i\nGaGtOOst5WrKoguDi4zSwCkpz2SJ3M2C+Y68vC8CrbCVldEFpgDiGh8NnnQuPMpK1EiujaUUyhDI\ny4GPYj8YBjGOuYIKERDxT6CWyoCxUcFNB0Kb2LWV6Cc+vITXtpJOE8X1+Y75rKxFGQ7C5xG8zqAX\nxLDhkIy0nJlipFlEJfGMzAdbkJKowHlQHmehhshuqCzrSh0yuo58Mgx800a8GcrIToSTGNpgcIVr\nH3hJoenKnAKP6ni19M9Nc5XRoOJZQuh5ZP9EsPEeBtg240Izl3TZaA9oZl4leHC/upG8uIm47UiT\n1ruQrd+6ra0RzWitslfHs6sdk0JxhlMhV08MrXddao+bvrk9sKSENMfoFVNhXTI3NwcuL7a8vBw5\ntdbdKLWS1wVqpXnH73zvQ777YuBaCn9xgB9+/cD1i4mH25XXX98TdxPLvGLV2G4CHxB4e1w4rZnl\nsBC08mJ/zd/8fOLmBN+8PTIvR77/9sx67ljc3/sb13zoJv781crsnuhKzjgW5VQasmae77sNPpdE\nnDxvHxMP55X5L6khm+I7Zc4ZIS/MxVPITxh9IbpEFP6tNcSV+15DpDFpYAoTg8JhMcQKeCO0jAAh\nNdb2U3pbY8mhR1bMAQ5XK0NsvAS8ZU7W2Iix2xh3xeNypUjP+ntvFBt4lMw+OD4KDqFwrJFUlftT\nps19WPnhcKSuRiTz8vk1Y/ToKPzNDbydRx7JbDcD57NxOmcuxz3v3j/wnc+fUVIhOjg89M6LesOr\np4WRfDgTvWezGRmCMYTIuizsX17ya3/nY768P3L/JiGD8sUPvuLH3x7QlPni60euRlB5z/47v8uL\njz/k/fsHjv/sS66uN/gQsI0wlMKHv/MBdloowK2tHB8Kq5vY7bY8vLmhrjPr/cinn37M+8e512Mx\nnHpSmXFNMe+5uNpysY1UKuu5kLJw++otGiKNlegCor7PFTS6sFwMiSM2REJwxCGwGze0mtCo1Fy4\nfXVDPg3kX1oV+PmXOHC+wxqsSRcui3U1BgJqTDjGcc9GoWk/XIof8K72uV/r8ed3xwPLmvAaCE+R\nsLIWjpLYTBPPYuRsfQg+06gl46thXvnsxQW/9ck1kcpX72e+unlkuxm6CPZwxGskaYWcGYMS68C7\n5cBcKiUnvC9cj5d87/ML3t8l3hwOtHzmx7cLpfTN/Pc+u+Rl2PLjd2eKVqQpURpZlVLAW2XrB3or\nLBE3gdd3C+c5/aV1JKA07eQ6lxeKV6plihhNBC2JyL9HHXETkxce1oq0Xkdiyx0hfqg89UeYl5lj\n8bgGTjpUQtPKuHX8xotLvMHbNXE5Kpe7He8OCVcNK4WAp3OSRo7zzDYORHV413hcEqUpxzWjoSHV\nOOeEZYjRuIgj0+ARZ3z35QV3dwv3dSWGQFn6O8LpyGE5s99NVOsDF3NOiAnqlaCdzttq6WCy6DCF\n4AKBwjBMfPLZc749HKiLUZ1w+3jP7eOC1MbNw8p2EJoUpmHDxo0sOfP27sBmjKj3DNKhDJe7C1ot\n1NLIvnA6F4SBIXRwmlilpsbV7orjukLqcWa1foGtFZoqmxjZRE+T3nDIRZiXU6fl+fJEAxRaDFDp\nnUVv0DzmXY85O0eUANIv61srnOeZ5v/6wPSvXaM0gu9EIqkNk77Zy85xLAtXsWKqvK2FagO6FEYU\n9Q3XHGfnWRmeiCYbLjQzaGaqlRQaRsH7wJIW/jy47mrxjWsx9r6x846dCELmB4d73qcdXxP5OGTS\nqgRnDMU4l86xF6f8qAT+SQmMCgOZ5DYkMm8phLPnx8WotvC7buKjTeaZFL6fAt9fd8T1kVgruVTw\nE5eyduloErxmige1HgnLZ2PblNI8WRwpZ5oTTq7irFGB6Iyt77jh1iqreRZTSjOQhqggdf3ZjYdl\nw7lOoTOEYA2nQqyJwYFPmaodLPAiLwxRmFZBOKPWoGZq65hfU5hswUwZc8E/OTqOx5nXjB25DqTU\n5ahb54g2s1SPNIghMEjivnmOJbNUj/fKpURC6zfnZgVa47OxEWrhNsOZxOEEz4eRt8uKDo7D4jiK\nAJ5SCmtOJBvYWGTLQn7CYK619YFxmVla5iODD/bKzTJTa0dxfu8i8L9+NfO/Fc8/HAMxrGzE82wD\n318b34rnTpWjTWS26DzwQo9sZeALn/F5g4ljJ8Zcjc3ccLJnlMQrDcxOKWslr55ahRqFi1b5ro98\nhxPf0YHcKoso+2LECY5zxVnmbQq8PlfePtHAnDOMRy6Z+MQbav15ySYUc5znhVsrvMyOVjKPrfHD\nxZHMAMFFj1bj/Sn9cgvBz7GqKC54nBktCM5VanUMwbPOxnbrcep4dXfESyC3legUpx7nhOqMnITz\nYSFO3ckRveJCj4G0lAjRczjNHOczZc2E3cDVbuLiamDcBK5DoKnyR68eONxmDvPK9eXE7fsFPwq6\nOtJpJURPEeHm9szXP7lFwoCXTo7KKMc18cW7gVcPR5ac+O0PXvDySvjYJf70GPjq9UJxGVc9NWdC\nHAh7ZU/leE6cq6NsDa09EjufjaAQzJPNWI4VP544BfdUQxLPmuBDI8YRkZnVPGvylGYklChGad1l\nogjbVgh/SQ0xy/g4YdWodSY1x2CZYVBCEWo7UJrDglCb45wNJKCud902sfU6pcr7Jyn0skIplXPK\nNCtMMeIV1tywYsTtyBiF9Vx4+3ik5n5bO8ZAoFGy0DQjrfHxR8+ILfP6/Ynj8cjDOfH8gw/4/jkz\nbDx3d/3fXFPOp5WaK6k1iiaCNTKVsB1Z5oW5NOx8Yp4fePHBJd/7nZf86M+/Iq8jul35T3/niv/+\nf/4J//T7hf/4977L82vHyxh4/ruf8adf3HJsBm3l9mSo7Lj5wVscle3FBe/ywt17Qc6VKcC6VtyP\nb3G7HUGNx7UiufLu7ZcQAm3NVJc5zpnhesPHn2ww25PmPrg9umuG3cDDzQFV4eHuzPtv3v6MuqZi\n1PMt4+6a7XaDedhsBmqjzwM+PJLKmQGop8Tjmrg/P0VpTJDg0GaU+4dfdin4uZY5B87jaiOL4qRS\nzXfh6ArjpCjdE3Z4El77oKikjo6WhhXHuSwEp3h1nQrr+mxc9gXfHMu68u269PmQ6Nk6zzR4pm1g\npwM+Ov7wi9ekuXJaC9sYuqvHC2pKbh3F3yTweF65uX8D6nE0nHpyVY555eu3K+8OR7JVPt9f8vmH\nE88n4Y++XXh1M1PdCVc9qWQGN+AnRUtjWRJzcOQYerfMC/N9wYkQxXUvUm24cOZkirPGUCAGI3rt\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XAww7x11u/L/zS85pITxlBZx51mJEhF+zgMlK8oEPfGPIhvOF1Sp/ywv63HNeEw/J8Ydn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c2hPQBgXI4w2WCDguaQSqBNDksZ/28MP0GnEdIOUUXqWf6TJupakRgghEGuWgvEiNsR4iVm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\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s75C4kvoOy0n2JPKCDSceqphRbeSim8k4QR9ri20D3KqYZyu/SCZ5Lixyq8FfDbreInIn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\nC/jbhKET/aLxp4BfDfyWL+K1X+yan/nnMrMPo2D6D2fm+ov51S9yPc/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- "text/plain": [
- "<matplotlib.figure.Figure at 0x7f37f7fd1990>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "pl.figure(2,(10,8))\n",
- "\n",
- "pl.subplot(2,3,1)\n",
- "\n",
- "pl.imshow(I1)\n",
- "pl.title('Image 1')\n",
- "\n",
- "pl.subplot(2,3,2)\n",
- "pl.imshow(I1t)\n",
- "pl.title('Image 1 Adapt')\n",
- "\n",
- "\n",
- "pl.subplot(2,3,3)\n",
- "pl.imshow(I1te)\n",
- "pl.title('Image 1 Adapt (reg)')\n",
- "\n",
- "pl.subplot(2,3,4)\n",
- "\n",
- "pl.imshow(I2)\n",
- "pl.title('Image 2')\n",
- "\n",
- "pl.subplot(2,3,5)\n",
- "pl.imshow(I2t)\n",
- "pl.title('Image 2 Adapt')\n",
- "\n",
- "\n",
- "pl.subplot(2,3,6)\n",
- "pl.imshow(I2te)\n",
- "pl.title('Image 2 Adapt (reg)')\n",
- "\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 2",
- "language": "python",
- "name": "python2"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 2
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython2",
- "version": "2.7.12"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 1
-}
diff --git a/notebooks/Demo_Image_ColorAdaptation_mapping.ipynb b/notebooks/Demo_Image_ColorAdaptation_mapping.ipynb
deleted file mode 100644
index 51b91ed..0000000
--- a/notebooks/Demo_Image_ColorAdaptation_mapping.ipynb
+++ /dev/null
@@ -1,349 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Color adaptation with OT mapping estimation\n",
- "\n",
- "Demo of Optimal transport for domain adaptation with image color adaptation as in [6] with mapping estimation from [8]\n",
- "\n",
- "[6] Ferradans, S., Papadakis, N., Peyré, G., & Aujol, J. F. (2014). Regularized\n",
- " discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3), 1853-1882.\n",
- " \n",
- "[8] M. Perrot, N. Courty, R. Flamary, A. Habrard, \"Mapping estimation for\n",
- " discrete optimal transport\", Neural Information Processing Systems (NIPS), 2016.\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "import numpy as np\n",
- "import scipy.ndimage as spi\n",
- "import matplotlib.pylab as pl\n",
- "import ot\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Loading and plotting images"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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mTia0hLGlGUdRPJdlnZfEqBoxOLLbusg0fQycdE60mvwID4Ylse5O2ZcHU+LH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\n41yBpIqq38d4HxfdExL3lJffqz5zh0o6f6MfJwg6URVT45HwJ54UukTc9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QTmuMY+j45F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\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J3EjkYbtwM3Qdo3jh1nsXvllEaJzbyucijKlPqTbJCIUDgUMUGoEURz6MC2t0gm58nCIJ\niLoic6dkD4MxHQNr2TCPuEViTKRBwSun542NTpV+Z4nhMPKUjcN0x814wW9+zKfViD4xjYXx/Q2f\nTwttXRmPXQJwOTXGKTGPNyCFYpU1Z26GQjYnN/j48ZZhbMCZFO/ZlpWydIoeQbmbYD5MtPweM/j0\ntPDw5Ly/c7Q07m4V6oWxVVpxNoNHT5RP1o0lIrybBUZn+DLwvii1NdAIOfNwWmgEKEfcM9MYmW8i\njUfWU4LWiAQ0jgyT4zEQZoUIwQ/MQai1EOeADEYMgZzXXQIQoZz528+NL94lYk08LgtrVZJvzOMB\no3F+eGbZFPdEjEo7K8ep8vX9zNPTI2XrQD7Exs3thRgHhpTYate/nC+FywZrabw7fqDhtGB4bdwS\nKbGyNccOiWZ93yvWQAIpVA57hthGZCndsOpaM7o1NOQXTY/IQAgT318MQyAujLNyWrZuGW6dug+3\n3E5KYuHx7OR2wTwxAne3gVIzeOOQnEZlaZFi3UF1Q/lmMd7JSJVKLkasga0UmkEaAy6Brz4Iv7pk\nHs6BoBOLGxoaPx4yabzhu5P1/UraHrGxESV0a+8pMhO4iSO/2E58qgPRlarGfVDy2fEUudRGZSOM\nA5daSHHmJsExQZTAp7Ow1t6YXLbOwkHCzkYwGkZDcReCGNEb094kbGaMJLztwGjQ7qS4W+W2HeT0\nPauC+AsQUuRlDwsCmzhVA9V7rbH5HrKLUHV30vsNHr9VgMkdkoEHfzlZKrt99R426bsWQbzTw0Yp\nuME5KGIBQgLrgZaJzBZgMmGMQq2GibCqsDKjDqvBQuMQE0dXXFufMASYQ0WzdqcRbV1ToAPfFecX\nGmkoMTpzzvzYG6MGaroQfWT0gSSZ1UFrJVQhqFHjinrnt34xBM4Evn848e5mZGuBG0mIFWwYd6dA\nWEvP3zHpkydrFQtdeJdUqTQkdhebslZaNSLGEAMSAmLCkhsxjGym/E15YIi3RIUsA9FWNOguSO9h\nhk1sz+3gpcgOui9IL5bhTqOBThzrxiFkvquwpIF5L15T8xeNxNGELA3XfcoXFLWGSaemqSotVIQJ\n98AvSfxcZuRx5fc+HDkvG1EKx6A0q1xq5bI5N8lZpBEVaIU4HpgnZ4qNysjtMeEe+DeXhVPu4CGX\nwt2Uet4PoYs8i3EhIM25bBUNEakZlT4qPsS4TzmN6kZ0rmOXndroL9kIAJogt64HcIcxpk4zcRhT\npK29i0KznjFk9jLtG6QnxW9Xl7zSF5u7w4zIAb1RalVOS+GPxoGv18KH8sgjB45y5u54w+008r/8\nm7/m//Fbsqad4e7oTt/zNwB3Hx2+GqYJIEa4FtxXACNxX+9kF77tjm/eefQ91+kVkJhezSb6P027\nlerV9jo0ZRPF2hsbbgkvuh/bNUEAbsKgAyLSz3W/BPHdSKO75L3pSL3ooHoWTbc5f3WtuwKLq7bq\nOjlLe+4bwq7b2vM6rvB+18BhdKMO7WnrdafNCbvlOdfw2n50B7xOUY3SO24N+UEDqHh4ATBigatj\nnu+GKi4BcSNgV8ND4Ookur+WN+J+Cl+etzskujtv9yDFCb/ZJt5v5XGpgdVntNLDhd2Y08RWG1Wd\nnCLWnJHcBc6udO5o5+ZjrYN/GmsV1lqQoDy57y5WYXeyEmoXqKE6Ig3QfS2QysGF2zQQU9fZ0SrB\nG3MMSKjUWgjmeJh4YuOcN0abmYZEwkjSaGpUNUJ9ZAiKhYxXo8WIVt+DZrs7lnrPkbm0TshGoFlF\nVYhRWNdHHuKBohEru6Dc1p7Rp0La6N3yaeR9A/GM4FiBFBzfNpII9+rImMm2ETVxo8qQnOEApQw4\nCRFjiYXHS+CyHpjGCA7BIvlpQ9xYa2JtG3cxkVg55UKpgUEhaCOFkfsUON42aln5fGoM6tzd94mE\nmfD+64FI13PlrRKHxFKUahduQgQVxumEW4Qwc+GJD1/OJG4otUDqU7Knz47xHYdp4N37yLsPM2FQ\nxCImGRk3XCGwcePWA4+3EWmNOc2QlJY3vCWiCrUtuAtDLLz/cKDV0veN5gyp9BphHRmnuiq+sAAA\nIABJREFUC+njSAsnyDdoAqNC7b7C49HwdxtDncgX5/ykLFsjjSOHaWZ5upCmI/M8893fXJhi4XgT\nmXwhMJJPZ8q2kusBl4iMTjomzg+NnAtoI44Th7QwS+ZmCnx+zFyeBj5tyhoKopUQZswy91NDZOm0\nrqSUouSycTeOu+6v62hpwjCM5Jw5t04n7jSYQEvO0ndPHGcKMA+RVhRrhaetcqoDwyBsuQOV6Im7\nBBUlS8Sa0GzhUhWTHSwQGFWhNdq6othuBnGDmTBOTm7KhrGSOJ2Nz6lwmyJTg4skSuvBsv/p2bBm\nhDjQSJCE7F1ja/mGP3ch5MZE6+s8QsN2d8GJ7BtlgWcqPydTgEzPA5u0SxYSFbXeQDzXsO8JE1uD\n51qRk5G071LdjVdIEtC9GSvSM5FcdyMuU8bUa5rZjSpO8UalNzIH6eH0a2svetkQ+rQc2PXxU2dx\ntMYq7c2qKhTdHfR2dnlrBVVDiW/U9r+547cKME0UhpiJEinNOu9RIElPsS/i3Ve+by3d0cO7FS8O\nWQNRGoPAbAUBNiBYoNVAkz4ZSHT7yl3/jZE60qVrPUwSQuCIIKFRVVB3QhCaBUoMLDiDJ861UW0g\n65nbXBgs8O3QTSXemfOV9g1xirGL46xfTKKBba2EIDAMPG0N6saWE7eHEVsK0xAJ2t2XTkvGpdJ6\nXHyvVbVPWmwvwpacuy1z6K4piLOWbS+iOiBJRfjZPPMPPaJe+PPTxiVO2K7TQECs8+f92pG+MoOk\nF2ZvBgioRG5s4Z8dGn9yE3lokf/j8TN/2UY0DAQCrv0muYSewzSVjTEkDm3F0nueWhf7CgaqaHF+\nOiwkCt9+3rg5jhxOCzeD8nC+YCrMQ6QYnNfMmnvQaWmNw3GitG5IsDXAKuM4gsKf/eFP+ebhwi+/\n/Z7zZaXU7sw3JUGt4J5ouY/rt2tg607SCqETyq600K5V8Z2L3adLpRQkxZf8JZUrhZGXBUND4nld\n2YpSuus4u9S/f8c7Z6x5t+tdt7IX/c48DgjCEJR1XZmmCauVS6kckvCnP/pIkMbtOJGL0ZrzP/yj\nH/Gv/urEv84g3jeUGnZbca7mFB0AmPVE7+tR2ae5CtcwY/NXCBB4zerS8Pr3V8BoZlQvRBXUXulk\n3hrsjoNu3VDiasV/Pa4TMuvjMaDrxdIV6P3ACvuHXajr5KZ3I2UXRL9S0H7NwOcHR3uzUDu9Wylc\nM8q6Kc2VMnmlVbq/mfLIy+ncwVAHvbpP0MVaB5D9YupNIb8aaFyNbxTz+mYC+Ept7H1wf5l4uTvp\naqjRoeGrLcvLZ3b6jNd/AOIg/pDi/Lvj1x4fB+NHc+tW9HUjaG+8SDLMhJgrY+qNFbeAtQBixJg6\n1UX7NehmEIeeyyYws4cih25vH1wYQ0BQ3JWWGlYb0hcEqhU+S4XtOqEP0IRQan+8D5gEJu1Uv+QT\nLQXwSlJjy5GlNTQmjgihGlUHzq11SlMCN6VtEOLKYF33qGpoVEKMXMrC5pBrZJZEaAsmShgjzSph\nPFJKj1m4sHLnzoc4EIaG+MY8CTEkhqgdIFajxcyszkUGDjoh2jhv8N3ZWNrIujWMhDRwDeQqPF0q\nIkaMDfeG0jiOE4NE3gUnjK2bnCzQbMaBkoWUCudvG2I3+HxmCE5IAxIiYoqFHmhvboyToMlRT1QZ\nCDnRLkacwXyjtUg5w1PeOEQIKdDWlVKM8bgQp1uIhXho1FCwHPGtN3w8DnBIlJaopRAUhi+cYIm8\nOjEWwrlhS2NbCtNNwsVo6Y5WI6gRo9EuRm6BqIEUGz7PtMeKtgM2LEBGYqRF6zQ024hPI+0MWoTo\nA211Lmd49IXgkeUh8ZSfkey8uxk5PzSSjD37y4WYDtzeNoY5sl4qWo13c8NLYb49sNYnkIjVA3/z\nfWGev+C8XciHxm2DYTJyPvHQlMUT1fq045AiY4NLiJAj59bIa8GDkmKFfAFA44FmlWqN1QqjKu6B\ndi3MTXnYCmpHRHqkwtwKxRsxzpTSzbwGBfdMiJ1O0+i65lNxijojMJKZBiHGQAiRd+GW//Rw5mTg\nWw9rzZsAjRQaXhOX2rAhEtn2OrMH8noArLJa3xdEhXej475yttjdT3tABPvWy6k1lrKQoyJeu4FD\n6y3I1a57cMOl4akDxmBCsj3OJihjrfQNdCB6JoozpEgujefkbMUQ62AneeJilSWC1oQ0Y4gR0dIN\nYRRoAbPWdfUCJez7vl8h6x4PErRff+IoRrT0sj0Gd4IEKvayN6IRke7EWEOkG3P/5o7fKsD0T+fA\nH9/AvzsXNnNUU79ogzCEyOLG024xivtO5ekd5OhOZGC0wiEpc14wUzaE7I2qibIDgMDr1ARApHTt\nQ6u4d7BRTNjijMZemKj1LAnzQlBhbspZCy0ouJDbQHBBG9wW4TEYNSoLSt4qZCciRDGOuoEqISSm\n2MW7pTUuizNdKodL434SpjExTyO9fy2UknHvFMReUIJZd/666k6aN0TC7orWE6BrybgHQho4SWVQ\nOErmv74vfLx5x7/6ZUVip9BN0ghBOe9ObU0aeHedw/tNKinsdsZOlsafROdPbhuWjPd55Z9/qayf\nlG8s0WLr+U/emCTxFSv/8suJn9wlJgn8X+eV/+0bJe/amKqRj/LAf/PFwLvxwFqMU21Uly4+bo3L\n0r+HtRS2Usm1U6TOlwslX+D2lhgOTCkQHaxWJCpeC1Ea7+5vMRe25vz5X33LTz7c8+HYDeuvov9S\nbafQ7dfJVeRDt7pW7fScPcqPqzV3qYZ44zCNndJohtY+Jq+t7XqaDujYM4p6KOu+4NRGb6b1rB0T\nXrRM8zTi3qjVGMYRB47HGV82YnWCVIYhYShHrRiRYTD+2Y8+8K//+qHbnyJkceL+3m0vsaU36l7q\ncnhhcP2AmhZeFU2dY7xrgK76o56tZLCHRd/soGo3RkLECdptIdwNi0KrlRhjn3y9vHlPMBfXPuGj\nB71y/V30BWLyNsDVpXdRwTvNYH+I7ufQ3uh1XmdG7AWq7+fCd+4eSOznxq7Ahm68EMJuALEbSnTK\nW79Gruy363do+/QH766H/ef75qLsYX+drun7RMvcelG1X3evkz8D6flL8rqA7bqkK43ZX97HdzCn\nOyB7eY7zQrd8S/P73fHrDwn92mo4FvcurAGujAhT6ra9SmNKQrSF4EaLjWWFgwXCAdYcQNtLYHNt\nhZYLtc2spWewNQo1J0QLpXin3SGo1113q6y54qExqCClIePAurY9DLmiLe3rmSFh4+jdBCarM4ow\nSuUbExBjVGXQkVYrQxtRraTYSJKQCWKDbIG8FziDwY/myChGGjqw62YlRq0N04LixJC7OZEqIg23\nwnrpuTMaC5sBWtEUOV8Sn1YwUX7uK+tFKO40jRwkcwjOoBs6GyOF9x8Hhjj09w6ORmGthm/OuhZK\nKcTQUB24nwNbeWQYhRghHSvHJPhyppEI2ljySq0TpTlpHSkh41SGqGguDGNgaIYxko7grRHyxOfn\nR+7uRsZ3ikqltBPju0i7Tai9w7dLd8U9OWE5IK3QQmAjoUujrolWInEIeM2kMlBrxraF56q0OpKm\nzOHLidYEIXL+tmeB3RwOVBWm+4BEYKr4Au20olGoIROCs3nEzwUdIY6NwRttGzqNeTTSduEgAnVA\nbGIcjVgfmcLAhy8jKmCshFhJkmA8ELJRoyOLMXtjWc/cfxyhAEPkm8fIN2dDJeHtiGUHEoM6a82M\nwLvbwDyOzPMtta7U6nx6yFxSpJTKJcHWhOa7qY0FitU9ZqIg7owxMYlTWkHorqxDgtAiqxsMFbeV\nUqduqR/nbiokgSy7rmc3GwhDoBbwkgkCx9b3f5rSkrJlMBeeqRBH7hO8v4l4gc/JuFhl3QztJpeU\n6pz3gYqIcxiEWZSEMwsYkVIzuTnmkaCNnWHemy0aeiNMOhAcvFGjEMxIURHtlF/3TmlbmuLWOntE\nnJgguTAYtLE3fks+USVhwck5U1rfG49Jd4MXp7aNMXZZSh1yrzGtsSl47fTNoBspKs2cQKCnKQmt\nOdUEj/bC7nB65ImKkNWo3r/HPrBuhHDd35TifQpn1uuI8BvOCPytAkxD3DidF36PRphSLw5j58fW\nWjhbI9nAo/cLwgWS96L0NkXuOHGQxkhlGw5cXNlUejK1dEe8qx79LW9fGLp5Qvc47oVQAKfStBMp\nCMImQo53xJB7IjEB9UKVAlpZRifSE+DvinDbjByUEm8YFRKGtsK5CXWrfWPSSG19CrL6Qs5OFhiH\nmZKN03Yi7kYYTu9sD6EXZc0dgva7k76RBpV+AQLny9ILNVFqK4Rm1ApTmJEInm74Sjb+9LCSwsgv\nLo0w9rTpkwjuiVESZqVT9oBKY24RfENC5YMoB8nEOFAVHovRtpl/HOG0ZS6xIm1CXBms8A9uAj+7\nE+ajkHTmpxhjvGBB8NL4GYX/8qcf+Goq5GY9uE8hqVNLJdKziNatsdTuHOfes5eCRmqDZcnY7YHW\nKkMaQZVSjezdQOA6navLQnHjV5/PpOHIYReQdF1OwL0LuIO8mh28GF2449ZrdfceXNesn5O7eeBu\nHMhWSSpYgKhOqUox6zSSEEC6/qW1PgkZhm4e0Yc/0k0zpOdPpRgJ6kTp+QhzSuScqQ4lZ47HHqo4\nhNjd2g4zpRQmU/6xN/7w28p/Wkc8QCwQVXcHPIU9G2i/GV7vx+sECtkLb3+h213Djt27MUSLr6BF\ng+4W2K+UsX6pdjpixGjeM1lEFU39d0j6ek8a0gGcv1IHX7LCpBdW/T7m70yb+vtBXxuuj9mHOdQ3\nRETzvlB36toV7Fxpib5TqPob9lyr/rz2ltRntj/IdzCzfwdvpjZXcCNvQ39fgGl/Xdl/l24U85rn\ndZ1ovp6X/tt3uvgruv3BkEjernP9uw4muxaswynfG01Ye5ke/u74/zlCgjhwkLLDbNk5oEqQBl4x\nevfdvbG5IHvoeggJGzMxwbvDHdty4QBEgTQZw92EbYaYYLWStVKKdSOCOGGirGvhuaTeuDLnFAvb\n7n4nEmgKT8MOnKEHtYt23aIqBzeqGHemnSlRN4KPqIb9XjRMndUWhpBoVTgFoa6FsfZJmYrC2ng3\n3vPQLqQAUvp6VnIHkCklnELQTgtP5ogYbs5hcj7cXXh3CHw6T5gUwlTRQTmkRjyMOMKRgWfduJuF\n5GfubibYJ86qA99+Nh7WgafzhSGNHEPhwx3czAr3C7cAOuA4z48LKU58nASigWVYA+SBbVHG9506\nOUwTclEOacDnioQPKAthfQYZyGvh8qQQDYmZ0Z0hRj58vMFVWU+gIaKDsHxS6rcJmnAz39LSShgG\nKgVbBnLem2bZOW9PHO8ykoxpmFjqypZXbu6OTCsdhIcZJIIJflq5uWm9MFYnxTu2p8+d0mRhnzIM\n/fs/Rvz4RKQQbiNWMzIMnH/5SPijwlhmqJFRA5yfuEt38PhEq4WP729AKn4pnH6hLOvCTGK+nTCt\nbPUZSV9ytgfuDoE5feQ//s0jpQ2UtmIkCn0Kq4NQPSOtsW3CqgPrEtAzDMH5vDy8NJOKejf00W4D\nPqdA2TMsY52BwCAKWhmiEWUhqhPixJbLPikyrD7y7hAZB+2GSnXDLHB/LDRbGAahrYnvLs5SuumK\n0yf1ndWgVKE77ZmQ264hdmFITm6V1pxfPfQg9RQSRxHmYQDJNOtmEEVSb4hJf36l0qwxxsghGeOh\nN9y3Apv1OqWZYc2RnT6re5NeVYjWMw5NDG2NWjtd29w4htin0KX1uqj0laoI3drbDdFE3afaoqC+\n09YdaK2zE7TnMYYQUO9ufxKFwYTNK13frjs1vjfkmnu3PReIQXFJey/OCdK4Zi0GY48ncDbp0R5q\nvb7q9v3suUKdrh5/syZ5v12A6em08vs/jkwBQnRCaAx753YdlJyNX5bIc7nSfpxnFeZoeDuTZe5C\nVx14j/HlGHm2xi+XyqMFRBKvBcebTrM0gnVAJe68VEbu2N5VVCCZMLHxhfXOzQPO70XlD9PAxzTy\nFJW/evrMpVbWYkjbaHrHxsx9zBxoPfCwOedL2Vmku5GCdArWGCOtbFyyEQLdaQdezBaUnv8Q4158\n1z5dMnNUnYTy4XZkCI1WhSqJpXrP9mnOIEJtFRlGVIWvY+Nffj2xbI131tiofCbSwsBWMk7mJilf\nDpEmwn9cGjlc+Cca+ONDhNj1Uc9LZnXjslRCjMxx5T/3xKUF/oM2Vgsc68JP5MCnZeH3h0gZCl/d\nzPxX44mWIikK90fjy7FvKGOAr98diSnw6dMzaZg4nZ7/X/beJVa2NMvv+q3vsR8Rcc49997MrHJ3\nuR+4sbuxkFqCRkYIBAME9pQBnoJgghghIWEJS0yQGCFPLBgDU4+QkCwBAjFBlhhYPTAWSO2udj06\nKzPvvedExN77e6zFYO0452R1VYNAblxS7xzkPXFuPG5E7G9/a63///dHYqAXZdFA7cppjHz+5siP\nv/7E2ozT2yOnw0SSRo6ZmBJ1XVnXdfeoOO75eJj4rV+d+fThSq0FlWkvfpQiN8y6+198aOHTTe9Q\nuR9IduJc10YXR1Ufp5EhBXIc6V2ptZHE6Em4Fv/uOsjj5TvY+0v+wK0ucMKgMKRMiuyZQMI8jaQo\nnm8lTvhb15WlVd69fXB8MBDHjCCs21f8lS8m/vufwO+tK8RhnzUZndte3BfX+Io6YOqjmRtgweS1\nXM038bdiQ+1Fm6zmBcYNpuCYbp8YYe5zclmpTzduUILwUhXseHOXRN64cfKtiZC9KiRenju+iNGe\nJycuu+373OXV9Ed22YNB21/XLdQ2iuz30xfp3PPjvlq04usfXg7Z/X9+EXgB2bw0asLzA3VeTfL+\nb45vy+fkW39SdaLi67DdiGdaxSj8rLJIgn07g+1Pj595TKFzCBUJfZ/kuYTIVMgMBIsYiZwX1i4s\nVXwDrcUxzHEgtEZdVsrgMrfaGwxG05UaIjFH4uiToTyNSOhoN5ay0KIRSvFzRIxTUo5xoGinRd+A\npLhLd0NCYt2BQStXAoeUqBhrUDYaNhqxKSnBiDJIJ0QhjYEoEHoisxCHyNhgGDZCUw7DSM4LpgOq\nmdKvDDkz30/urTUltESrC2+OI+HYeHp64ng8ce4Dn66RP/jRgTKMXK8QPja0nhnInI5nPnv7wN3h\nnlk/gsBSKh+fhOvmsqHTcObzzwLT6YqVI7QOOaCsqA0sX03P54iMb6AZ3//+T5A8olqYDyd+uAib\nbmgbOX01ohSmBFNUfuufvOP81Ve0VZAoSAwcjkY+Jk4BLkug9ZFmEIeBNGVohRALYdqQdqT3yjwY\nLGeQTrAZDpCign1gaAnp3rXPy8jhOwNy11g+XZgPB/p5xYaGPXgTx8IBfrLB2yP6oMQwYecrvW6k\nYWW8m2CoyBaw+wB3F8gjWhvS3xLrmXYwUr+Hryrx8/eEb660x0gogTgkhv5n4Ckg+QNWZpbfG7m0\nJ+7Cd0jpA2/u7ui9c3kcnJTVBtavPlJ64h9+VNZuLHEGfNOdgnKMB1rb0L5wkEAKkxd9Uplio+kF\n4UgenFRHV3Tf990k4nnoxEPkeJro5ROSEnnInkUVGohibebDx4UMLsEORsozoSthq8QDDCfl8gRd\nK0+PlSAjV1O6OmE57KtjR4lDAlGm4laH02EipcBlqbSuDFGpakzT6P4r22imbN0oBT5eM2pCVUV1\n3WV2cI0jKkYzZbWM1YXeKvMwMwwDtnVvMqbIMEBRzyrLLe6Bz9502+hoMKTBmLM38EIgW6BZIefo\nESfdSbAqEGt5vlx0su9zza89IQS0NVJwmXxtLxmEMeKTdIxJAuNh5trrizwdIT7vJUZi2IENVnY5\nHgRzf7m2yiAJDUK0wCSeAyjBJ+jKnhXmmwqq8jOBSf8oj1+ogmnVgFilI9wNiaAbOoxuisNoGO+C\n8TFCtI0pBdYGkYnPpXAMV/oOiBglkLVySpEvpsCPSuf3EZom1AIqO+BAjLHffAhK3U8cIzCX1Ykf\nIVNQQkqc9MxvDpH3E4QhMiZIodC7cTL4zdPoA4imrAz8/qfKU6lsa0OioENmSMJn9ydCb5hEtg4t\nGKkHjglszJRWafWGAt43ccER6gnBquunornXy6VRSrRKwnj/5kAaBnoNfLxeWUvjmDOaFClORvns\n6FKoKMbjunGyle+d7vi4bPzdBT6fAr8SO2jhiJKGie3a+UwbvzwqD0MmWkSHiKpxFyd69A3FRkZr\n4xIMqYE7vfIrg7LJxrLB11141yPfLGckXInVSCERyHxcrsx55O4QGHJHkvCdhwNdAg+nB5bSeFoK\nVldUAnPOZO382nc/Y90q4zRwXdc9x6P7xgZFAuQcqAVEvUgeLfD+bsAlZg0j0BAn56kSo2PR3RMG\n3V68TcF86tLVyEEYxOl7ap1qMEgkpECwSKvKOO/hktWDD71+0OcJU62bT7XMGEyd9JNnFGOa3Ig8\nxkxM3gHKMSGqyD5Ov1bhR58+8W6emYZEzhnEGIeZP/s28i9Y5Pe/XzGPmCdEwZ5JXkdie6LgmwSa\nv29BZ1psSOh0nAoneD5UTzipzhyl6iAHc0Qp3uE2cNyogKDQhVU7Q0xY6/RXBUfwZjUqkPZzEvEi\nKOy36y4ji8E1eWrKjWKgexbGM32OF/qdSSSYfUv2122fFQTvIkYRogQvhPerS9i7ZGH3TQK7z+sm\nCPz2gq62h8z6L3eQhP/Dbp5AADMP70u8SPIkyPMED3gGYdye+cYOfI5WkPA8BVPxYsrlw/s3VALc\nQBy37DTzyYY+6yzFc9L+9Phjj7t55c0hgc5I0OfrRbDmE+MAKXSi3DP3zsMEIXa6Hlm2zlIM7YE8\nCGMoBIFuhVJ3imNMFA08PlZaM+bcmVJkzMZTSd593j2PEoR127z7vW8u6IHvmpGzOZL5KJhVWmi8\n1USO3ZnEEun749jUmUZlyoXYhTl50+KyrUx3M4HO3Rg4a8HkgRih9sJlhXOBoishzsi5MedGa8qm\nME0F08iXj4JcTnyzDjx95bTIuzzxuFW2c+XNlOitURQkJR6vdyyrIe0bYpgxvfDmzYx0RWVgOo1c\nt0ce2wN/+KOV8zXQmtEls2pm64nYzgwpEw1s+MAgwt3pnmM6k+4yX3594fN5ZJyPTgoVaJbIoXB3\nnPjJ48ZZTmi+QOtIPzBKpj4V5gTv30byMWCpIf2MRaX2QtAARanlR6R5xtLBcwZlcr/beUUi9KOQ\nDmAlIck4HVZs9HNzfKfIWji9HdA984a+59P81gnUiLViVgj3A9oMDauvjQswQKiJ6+8ljnfJC4+5\nwZyJbJRvPqGx0X9QmfqE1IxVQVdjLResK1jyeXp4ZIojT9uPmKcTtTdK65TlKzZt3OWJFqA1X+sl\nVsYGIUx0mm+ku+Prjc6QKlE23wCbkeME4xve3jVi6lgyaEKrgfLUGIZIyv4dri2wfCpoMqRcmNKB\nVgNPZ/eEx7ihQZn3LLEgRpdOGH39W1ZYNw/81h5IQ2Ac4TuTw6d6VUxd8t270LvnHoY5klJE7ZF6\n3TikgRqM0DMpGcE2lkXpTcA8L9MQfvl0BjsiKSHaKSYsxVgwalNMMmXbcOVCZpBKSMZDbkQxtHbW\nOLnFojSiDK5kEehJCRKprbLMAWnelOsGVQtBok+ogkIwpujetpaG57XMAPYA9Nq7+97z3kINgZEO\ndEheOHotKygb0uAuRsfay4u6JgQhYSiNZkJUoZljG6pEB0aHTNiJtnQwaQ6IMIfoxNwJmnyfJS79\nG9KfFkw/96gM/OG58f4uszZjziOJ5hMRdZNYYOGfTobmAx+XzhoBu6J0urgpz3qnokgK9FqZUuKz\nmHgsypMVSki++ezK3BSNDe36jEUulmgSKUPyTBkDy4ka4NIe+MN65n70irsbnmgswnXdaGqMOTHG\nRFDlYfTNeY8JQdhKxbpSTZlj5NoaMSfKtqFdsTixqdE7rKV6x25HHMveBY/41CMEJcLewS5oV+bB\n0dLXrSLBqSNilSEIy7IQjyPr5jkXH1vH9nygan4hfbqstN65iyPv+oUvDpk8ZEpdSbnwW8fI9dp5\nOIzM44D2DkQvFMQAvwiua+cnPfJDmQkpM5bKMWW+eVwoSdj0K3QeadPsHY2YiSmz1uaUOlt4f3jP\nXZxoInzoZ1QhxYSE6Bd+g1IaWzDyYcJwgtP50mgtcDoMjDG51G3tlO7UObNIV5eJ1dqeAQNpNy6K\nvsjOwEfrqjsJbj9/055DIjKSk//dcXDaX2tt1/A7pUYNlwX25jlQuxTP8MWttkbOeZfjGSbBZVQ5\nYtpIw4D2Rkh+Ot+gEiklrDfaPjoY8sDaN0QCy1oIMbMsV58wDAOf5TN/8aT8vc3oOTB05WSJt3Hl\n61b4ZjgxdSWaYFmoYkRtjFaoOvi5ELwgMHGJaTef3rBPVBxi4K9HcCIe4tONZ4/Nq5DYUeVZLnej\nt8kOebihz1+r7kxuBcz+s71kNYTgUzDdja7PaHW+PVm6Hem5eLE9Smp/7c/FxK2+uc3gXst4nzVv\nrx5RXu5jLzI597f91N81/dbruU27XiPBJbwUMmIvE7VnGL/sIA1zCAR7wXqTA4rIM100pIB2v7+H\nDT+Xdb+Qh4j8NeA/Bf6Gmf0H+20j8J8D/yYwAn8b+PfM7MtX9/uzwH8J/MvAE/BfAf+RvdY3/oxj\nNIcRmKx4jpkhcpOs+GQ50KjbozcxxCdQKjDNgYdjQdJA1856nXhaKteSeFwCfQ2UYGztioVEs0he\njagbUyysNrCFCN2DnFU91LJ2vx5kEdIATwEkKK0abXMDuRCZwgrNnIZFJGSX6b3PgePBaDKz9YHF\nnAiajm+4ds8d/OEFej0Q20pMu3+qZrYeKOZ+ulQnPpSEagNt9DqzbI3aoakH3KaUuMsVunGnIynA\nm2TkmHja8M5yabQOYZpQVgLC0jsWR67LBr1gdseXP95QNZp2UsqMAnMKDGHHv2tO48K/AAAgAElE\nQVSnCMQsDNEgX4l3J4Zo/Pl/wr2sa/3k3pg4U3tD24iWRgiB07gg80hpCdNM64WYM5tWvn6sTE8u\nTZ/GDNoQOyAakGyEfE/tgSy7UR5FwghSISopTbvn02m+rQdYXPIYpxP6sNK6krKPBoIdaE+V+JMB\nNKLbgU9fR9anhtngDZTemWMmamceI6kK7ScNiZU4HLC5I8dIHhZIE4xC/3QmcU9ZO1EGDlOk1og2\no7ZCtEgYVoJ0tq1SeqWrMgwD83zH8s1HikRyErJsDBhpHPj8i0irDe2VIAsSAimP6Jrdj9IbnY26\nQSmRy2NFZCMOcaf4DcTxTEiOkRfumd80pvdPBHuLbSDSWbeV08k3/UMevUAyz9mU5NM7mmI90MY9\nf1F855THwdUi+oQEQZPrLIwAY8KJohG1yLY1945lgeieKWtw3TrWlRSMFAfMIltTnraNr8PonvHR\nGHqgmLA1CL06MTgIxESMvg+5Nqc/P3Y3+iYCx9hcvh4GnlKnm1K0gcZdYi7k7s1CUd8D5mRs3df/\n2hsaEr1BtP6tS0/cu3kGyB7ejuK0QTX/nMxbdLHvzckoFPPmn8fNuDsJcex4bEYPPiVyM8vLYeJB\n72oe7Cv41CpGh0EFkWeNSGRX2ATv73zLVP0ncPxCFUxow0T4yeNK2QLv7g9IUNZiNIu01jEqOg9s\n65mUMu8J5Nj40AOP68a8G+TzlOkmBIl86Eayxq+NEx9pXERppRK1k6zTb59WV1Z13bAFKCZYiIQo\nBO3caeAuVHqofH3pvOmVtE8geoisrdG6kULYEcKGqrFsldo2pmH00Wv3gNGYEtU667KRJBCzcNkq\nVwHdUeLeA75t3pw0EuVmpNtN58HT3M0MCxAuV4YhMNvAPAQeThOtwYfm8AhTw2qn6E3yJ1TriDrp\nTUW5l5U/dzKGHIBOsMAhZt7PnbEr2Sq9u0E+5wR0erPnsNO308z72vi0XpGe+dXR+PVj4mwHHi9X\nqgaetsLHy0og0ZpyLatLMRFSjHxcVj57MzHEkYfpwFIa53VjrRuX0lnWwlKMqyinuwPXdeGyruSQ\nSHlga8pxNFr3i/d1qWy107XtG2156eIHly2V/X3sz1+KsBco6u/17mUqpRFF2GonBWVM0zP04EZ8\nKVvbSWqCinoQI1Br9ceo/Vk61Vp7kVLJC0AhRXGE9D7pcH+dc87ctPlS8InIsyRLDS/O8enT43lh\nbZ3vJviDtbFYJIrRBSRl/kyoWO0cc+PYha+kUsrINcC9BEQKSuCsLpFTgxShBs9SCBqeX5sndu8I\n7RT2DcJtkRVvZuzf4bZPc9xKZXtB5F4jiYKjsPXZa+TnwWvpXsD2Zof/shGTYOa691uGk+1YZ5PI\n7ZHCbZkWl+Ql8e+zvJry7ABO/wxvt+3//azDvyE/Fa7NPhXipdgJ4eVC4GLB3TvpwpL99ud748hX\nwyw+489fH8HkVdHVbivGXoyqT7nkVsQFXmeD/aIxH0Tkd4B/F/i7P/WrvwH8ZeDfAB6Bvwn8LeBf\n3O8XgP8O+CHwl4BfAv5rnM77H/9xz3mcC/N8JXYBFMSBJJiRxKWmaoFw9O76bSLZVGm9sm7Gp68b\n56twbR9Qm9k0kKQScyZr4DSPHhqqfv64H2NksIChvjamSDchkpliYZ6FmDKtrkxjJkQ3rhMM7QKm\nLP2O69b89XWXgraufCPG03UkJQfjBFMkZ5Zl5RQjWRpzMuYw0PcMQ+9NKFMKSJpYS0VyZesNCQPH\neeapbMxjoqsTHlMQknhDdG0FonFKxmqdtQW20ohZCJI4HiKihSGORAVrncdaEEnUpi4fTMHhNrqh\n1jFzSV4a4H6Yad1QKqk7OGqrna8/PfF2DtwdDBsTp+MJrW33cox7aKdLvCIZ7QULGWHFxKVBrSql\nBbpmYqhggsboocEG0gUpRsxGKJk4uITT4hNCoq1GWyOSRnppXC4J+oxpY56ErhtWMkEyUx44b0rf\nlLYGlq0xz6Nj3w9PJM1MR5jHQFs2NgyVQCkL0yn7pjaPtDdPMG3EN3hRpx46GrYjlMr4JmGbIqbk\no2fg5C2xPUWSJYYkHKbIh68rcUhcG7TryjAdOObI9XrmdJwYh05KAx+/fCKETB4A3Ff89GGhakbk\ndh3dZcOxgbi3b34rxLj5Ws6AhMwgR7CCNaOsE4NdkAQSE/O7XbMdApRKrGGnuRrETgyG9k7MI2kC\nCFhrbFsnqgfLWxg85N0SKSSHDZjtqo9KD52QBsIwojqAQC2VFBpDjLQeXMynAe0ueTukkZyEahWL\nnaaJIURqKa5WkkytIGGlNbdhRFzq/2CZrXdqUD41l7CniGcemZMab91FU6MEI0hEIvuaJOQobLUS\nY9h91QoEYnhptvVgu/dbgLTL6Xd5uEF/9mrjE7cdxCCWXEGySx0au9zP0rMKwnDVh8kzlYlA3JUT\nstOXw46K7w5Ks9s1Nzxfe13ZUXl9FfyTOH6hCqa3A5xGyDkiRD5cNxBj6UI1p2mNGWxpzENkSupk\nsHnmy8dG0cbCzCTCAeFqQrbMNxaw3vms1N2X0IhUl+gQMOk+KZLoWtU4cpZM7hsqgc2UoRvSV9Kc\neBs8pOvjpZOi+zyidLIod1lowbhYZSsbo2TeHxKPTwunceRSOudt430euLYV2QsfLY214RKDbnSE\nRvMLlO5Es+5a0YiS80ythRQMIs+Ti1w7kieWojQW8uBbsC5CHiKivmG3lHZYhG9yewGzjS1OlB4g\nGmbdyUkpcMyOQz5FmB8mP29FqcUpa733vSvmUi6JjbdZ+bXa6aK8n4QWFbaVz4+u079ooDfB1Df9\n3Yy2OhChdvh42fgHX33izXHheBi9yAyJtV64lMp580nWL799BwpTVrIcaF2xpkgPz1OblJ0e92ld\n3VwNfmHVyjwNTDHQu3FZPQ/Cu4+Rpt1D89QX+iBCjC6d6uafV9VAtcq7lJkT5BgYY2Brxta8w7q1\njVKV0qEUX6DM2HXCARVhGDKYB/OttdKq34/T7AU4lRrVjZ+7lG9tRmudEALDqPTLypoiX3/ceLx8\nQ0iJX//OG4ag/MOnC99UeBtGTmKoRD70wrU2vpfhd+bAHDthgGUJfF0LH4CLwa9MgdQrPyjw/ZjI\nNfBg/r4g3tB4IrDg+mTApam3tG4f1NLFyBZ8ohTl2XN0KxRvBtRbAeQXCi+SmjkyO8ZI2AtaM/bP\nYpfS7tlFIsEX5OhSVdnlga8HCY2XC4OZUG2fBr0qIG6EvtfTpb3+u/0Tn4++Vx6vvViYvZAFbzo9\nXooqMyPJS95SsFf3fc5QcqKSgEsz8CDBFiNBG8kab/NA0Y2vyx1ZFLNAHSr0iITkcp79odtekAcT\n33D+CZOI/r8cInIC/hvg3wH++qvb74F/G/irZvY/77f9W8DfE5F/zsz+DvCvAb8J/Ctm9hXwuyLy\n14H/TET+EzNr/Jzjzah8Pvmmv/e+G8CV3hvL2ugk1qIsVzeOB2l7o8ApckEzg3XeHYXv1QnR6gS6\noKhuXKpP2YMIIXp3t7WNzWakLhxSYCRSrGASOQxXGHzjobXRc2UY3WzexTjrSO+NCBy1sIqwaaNJ\nI+VArYVWIr0XUlHugnA/Doh9Ir/JlHLhx9eJx9JIEiFsXDXyuBnGjKpHcIzNIwksF7SthNUIwTdu\ndN1VDkY3Y1YP5A1BqSRMAyKBMCb3XWhk7StBByxeeDdP9Kjcl0ytnUkCw1zIQ6C1xSXUYaC1ketm\nqIjT0zrczcJ0mijtieNd5HoeOByhJoVYSdmQCbpdvclz7UjLaMtoKsg0UctCyoKqW6XitDJKAla0\nBXoVeg8ERiQkQjxzk1lto6CaCIy0LUOD5bKiNaI9uQIgHKhFeVwN8oBo4rQ3mMZpYl0qIsphGjE7\n89g/kXulfjhynGBdz5xlQjtYaFg3jsOB0gqnAWysZFVkUqjNtbq9INsBuVZo0aclS2RbobeA0ei9\nEUYIywR0Ciu9D3sY7kAMnmM45gufvT+wXgJiI48fF7p4UR+ykCdDNXCaj2ztwnycsV5oa6LflAOc\nAEU3o+YALTCEiVYaqkLt+blBFARq3VBx6bwRaLUzpow0odZOyHA8jaTseY8WA2oR6RVSYhz8NVi5\nkmIi5uRB6dFzBEstEKFHZegnugnahbitLJZ53ODh/uD+4A6bGR8/XdA0EZMDH1orjDGTmnt0tBcH\nd5lQWieGTJIDIUSqbpSk5ByJEjgMiY55SDF7czCANcOKA1QkiDfI90lSDJmURm/0IkhItHIjMUdE\nA0WWVw3N4Ehcu/lnE6odtbB73fdfW0cs7rJzf8f9roFNvfnrsAcPtg7qkvm+N+dy9HxFL7j261ho\ntFtxZw6saCI45jFQ7XZdd/qe8HOX5H8kxy9UwVRLo3VlU9k77rBbR0hROIyZnJRxyLTe2Ugue2g+\nNVhzghAYpaOWeFRlEH8T6tYYZuU0ZHLvlBLZesPEh4hJvN9sphxNybtHqiM81kqtjRaFc+38oMDc\nK0Ebp2kkqOtApyQQAgP+ZTvlGZJyOh24uz/w5TcfkTQy2EAMkXEaqcvKxRrf9CuyZUKIqMKUFNk7\nIar2LE1iB1FYKT4hUKX38rzxKzVRWuJ86UyjUNQXQJWExMxWKxIjPTjr3sxYW+Nx2zjen/jUE+uY\nOfXOysR9ErpWiIEQfeuXmnfDp2nkUaojbs3x6No6p8MB7Z3jkKitcV2qZ5PUfSrTOtUCoj7Wzvtk\n5zBNlNr9Qh8ypVZ6SxgjT5crZpHzeaVslbJ1qgqNwKfLimjj/s2IaqSWhTAkNm/lINJYa6PURtwX\niXXbqOoJ1Ftp7glKeQ+Z9ff89ZTAzBwlOziOte6vfRpGqsLj09m9IXOEcXgeiy9bhRBZSqHURmt7\n18evFu4zwpOYYoAxD6xbpbW9KKuNWgqJgaUqIl6APUv7zKeCeU+YH6YT1xtWNyWaKh8er4SQeHe4\n56mtfGh199NE3qnxT91ljnFDBmXqHqi3nK+k2HjfIw8SmLTw7jTxdo1MS+PRCqcemZIxUYmx8A+2\nyJd9pqVXPqH9n+o+GS/4g3mB6O/BrYD5o+/37bjdHnfPjvVvy9leb/eD3TxM/pyynz9OBILXJY7d\npq0Aesu1+dnH6wmXvQJcvH6dP9MJJID90Ud9NqbLPrHAX3OTlwtEtJdCywspL7KDeRr7m2L88sH4\n7V9+4EGUQx75wZeFv/XVhoUDQzU0+nzsW3JCe5HyeZbWL5Q0728C/62Z/Y97sXM7/ll8qf8fbjeY\n2d8Xke8D/zzwd/Cp0u/uxdLt+NvAfwH8Rf7oxOr5+N+/H5GnyJTOYAPahdor4OhjSe4tDaY0Kwyp\nEWNkmjOqBauZwRpBK8O7I+8eDsTjyI9/cGa5brTjTD13ViLrFoi98dmbe045IX2AWmjHwGXp/OSb\nC3GJtJ64LBu9C/eHI2u7uKzbAl9MC3eHIzkm0vANx9FJlIcwUtvC/DD6RjD6a69tI0ojmF8Xh8OB\nL3rj1AoPoxdTdad3HY4fHWQVhboWhmHkYxFSNHpRYsjU9sTdnOk10vag761Hum6s60rKnoukHcYU\nCKwUC4isBEtEORHWK3cPI5KutNI9TBcoWyF1YTwEztcrI8ZxCJgknspGjhPXuqEfPYzz68cnpL/n\n+o03q07TG5Zl4e3be7a28fkXb1D9hFmhN+E4NqQZ27JSJZPiwOW6kqedcKfGu4eRnLxzf71caTXy\nh58O1O6Nzb5diXGkN8N4IkUjWOeQOuMMc5g5f/oB794/8N138PT4E97ev+PTNTAOAyKVxSopQG8f\niTqSQuZ+mrDTwnFOLJfBs5F2JYLQfKPbJ6I2GDI2CHYM2KER5oqsAiF5MOtmhG4cDo1DzN4ZO5z2\nne2Vet4IWWhbJObK9VIJtiH7BKJXpZWLawSyMB073RrTfMY0s64TMSXiNJI48aMffEQYXWodfBIh\n4gH20ToW73w/sMN3JEC+RagANUaGfERqYan4BBUnmW9dyXFGa6FJ8igRMr4qK2POpBjQ2tAwsfWR\nsoyUbtRS6WZs1mkiPknpibfHQFUotXHud2waaZL5P3+4kLPRdZ9uyolcOsfsEjlLBzZN9OZwhOPx\nDrPA1uC8XVEKZxWgEiVhT4MXCHkjJ88XJRoxJlKKlKa0KpQKTV2PYOqxBGqC6YZIBQPt/n6aOLAo\nsl+7ouzN2ZtSIgDBp3BRSLvPVW/qCZNnZVMQpwhidd9zVG9a7raGDqC3uB+/7kZR9sQdmnV2bgSa\nHNRlEn1/u7MUwfy6vmvnDaP8/0Aj+oUqmLoIpRuP1VzyFNx0dj8n7o8T064dv9aN0o2nqgQx7qyT\nc0SrMIox0Whh4SEM3AWj20bPXig8LQulKXTQ1im6Z9LESFfQoIx14y5l2uZhfgczVkn08UgBrm3i\nZGem0JGmzCZcm+1yLwFpvslZXeawqbHUztaFa1mAjqubR661QTfepxM2Keu6MR2OdGu0RUEGQnLv\nS1c/IaJAjH7CxuSSpWEYyDmTBbp0Sm/QRlJyba6HuRm1dXLObKVS2wtNa4yZrRg9H7jXyoHKx6Uh\njjvgMA2+0Rfhuq6MoxcxrbisLITwjEeu/kIJ1rhPMB+9K5uDYd1YLfLxWhmDcQi+ac0pULYFiZmc\nk3cpc0ZCoDaHQfvJnXb0cufjeWVZK4M1xnjCLkZZcTNhEEhK3RyBed1WavNu/uN6pashMROHgV4r\nYJS6ItE7VzHyLFm6ZSVlgXnYfUltl7yZm6y7Go9PZ4SJFAJDyhAEFaPUylIqWzd6ffHcDPFG4nNZ\nZw4C2lBtjEMi5RHLA0mMWjtdXbqnuPRO98kXQNPi8pjdH7VuK4SMIXy8Lt7p7p0vxsopwLXN/EAK\nrVRqMaZTICMMQ6LRmGLkaWtsvWMYV1WOU+UwFL7XA2etWKg8FuXCwBsaR+u80ytnfZGVafAlqLaC\nBp9ymuzobhH0uUCw/QL3s4/bpMmP8Ew18h9fSfToz58bu3wtiJtK5dVjAS9+HoDw4nmyn1FAvBoO\nPUvf4AZPuL2Ml/vdPhdP5P2jj2evXkeUlwnW9Kq4eh2ge8OIR9vhLyb86l3mfVZsOVNOE29i54tT\n5s9/NP5+a0hMhD1bzF4h22/1bADEwj67+sf/EJG/Cvw2Xhz99PEdoJjZ40/d/ofAd/c/f3f/+ad/\nf/vdzy2Yfv0z5bd/KXKWxPVypXdjIjPNkTmOmFbinLgui/s5VQgWKNtKTImnayDIRK0R8olPS2D5\nZmW9gurAtnauF9/kfVwrOSUu16vT956/JwsqkRDvaVuhtcrdOJNjoPfGu9PpWUps3dfap+0T9IEh\ndpDGJXRGGVg+eBhoQbGqnPKBdSuENKNpo7RGNvNz2Y58KhV6JshG+3KgW0W1M473BIWVTteK51BB\nK8ZaYR58kyoYkpR6XngzTEioBJTHTRnjHbpdSFI5HO5YlsIhf593nx1p7Wt6P7hfa7wnLI989jAS\nB6hBOM2RLEq9fOT0/jO+/pHy7rsRoiG9U7aV4c0BeoEwQLgDe0SXQsgd5IiVM6qdOJ5Yl0qaDrTr\nwn264/IYKaLM8wPJruT0hvG0IMc7eKosH1bu7w5cS+U3Pofz9StiHJAWKNvG9amRj4HLNjCGyrVF\nts0wu3A6/BI/+frK4Rg5DF/w4x+vtFLIhwkZ4SEvPskcjFWUIFe2dMewwFbNm4NzgdYJPZFSoBQI\n/SNxSlA64eTNt7AAzYsHrhXbhFAboiMmb5CnR2yesA+PSJmxKRFqpF4qLWa6VnrNaDowykhZC6EW\naoGlFkr1fMJN7lCbkNIh+/u/LY28DMwanJyWYKlCT5FVI9l3+mitjGNCt8o4B2JqbL2SktNepQi1\nG1gkkpHYyVNmrZX6tHFeP9DbzFefzpzG3SsUHJQx3UFFOMbMOFTWx4aMjW1V5ulISGdYKt+dH8hT\n5qms3JtT8zgkOBTOS8dipqvL92ptpD7zcYV5PKA0zqqc28THrVIrbGpMZUWqsBAIRFIY6WFDrdFj\nZ5EKIpgFbHVy8rh78Et1iJfL8H1qqUlosTO1RJSAxdtEyMi5ohqwMGK2YeKY9GzJ1VQKOXV/PyWi\nwfMh262jqLorLISu0fMrzdxGEP1+IXgIL+IDAiXQg3uPgvLi0aveCG6hEVOElDnSKBppzT1/7DHq\nTRvkwBD3AlkDa4ThTzjy4herYDKhSuapXrkslZyFh2QsVfnhTz4y58hxSkgIfGqNUJTTlOh1ZKOi\nrXno2HFiIhO6d+RHOsOdZy0FAmMIhDTBeaFtLtML0alzpk5O2ap3D9feMYRRhC1FqggT8J3TzFid\nUXW5XFh6o6aAXTY0JoLtmFYxLgXW7oS1ISnzMBBUCaK8vZuIvfNmmmHM/B8/+ppfOh34sC6ctxW0\nukleI2hFJZLR3egNh3kiDx4i+PbuRGZja4HO7ItVFRQ33FVtCJFafBP15jhh2ogYOQ58skALG6bK\npXfn46dAorlWGN9gXpZCae7z6fvAdkzZaS29U8yckrP7adaykuLIx4vwuFSuVolAVaOkxDEHX5iC\nkEMkdiOoj3SDKb11R6O39py/9Gkp1AYDnZiEEJ0yeLWFronQlKg4grxXSml0Ak/XM7U1pmnygMDK\nXrQkjjk/b6A1KGtppOBTGsHI48RpdELMp0+Vu9OBN0Om9AVhwExoFWpTrmUjSSQgHMaINQ/YDeZe\nGgmCNnNQRG9sarT9/UrBSTHaK4h3z3p3WZkqhLiP5LlplHn2ZJmZwyBCpLRK7W60RDJmjS9Xo4WE\n2sI9iacQKX1j0YTqwhBOLGvnWgppdBnRVhw40atQpKO90myn7NRAZWVJ3rE6CqR2Rbu/DyUKPU0M\nKKkoS4u0w0RqbhgdQqIsq5N8aHuR+bImvIY2vN7X/zxls76S/4HnU2Avg55Of36cyAvuW/WWRfUi\nobsh0X3ydPOw3eh6O0xhn4BHg4o9fw5x/ywQe5H16cvir68mU8pOExSHuTwX6vtzYA7a+N7c+AuH\nN/zuNxcuCudrIeXGF8cDUzCua2NLgc/Hjd9viVXy7tOyvZ94e492fyUGUdHwJyt7+H9ziMj3cI/S\nv2oubv9/fFe+PYT8eccf+3f+2v/0e9yPv+8Pt9Mx/8pvfMFf/o03KImna6Q14bIEl4XJ3rW1yeW8\nsjLPM2aR8bxSa91Jjz6JygoPo4A8cjo22iZYzSCdPGT/jhHo5utZHALOuAhO24yBIVS6ea7b3X1m\nMGNKA+vaSFEIlrB1YpPA2TZyExDfyPxh2YBALCuDNXIeMBWSVK6XT9gw0TZlGgQ19U2ZCnW9cBwm\nVBLVPFDzUiDFA5cNzkvx58YINdEZWCWS7UiITxweJvoaaXlgykdCVt7eRXJ8oKBM83tav/I2Cmle\nwT6DUiAlZKtEhNo7h/efU3vn9HlH2VCd2K4Lko6UC1CFPBckXlgeR0oZGMeR62V1mEEaicEom3D+\nuDGNM23ZWEIntcqbFcyO9Krcv5noX30iSqI34cPjV9yd7nh8upDHCe3uE2EUDsPMmISeCgcZGeNK\nTBFh5HCAt3pguywuCx8HOoFTCoQ5EAbP2Gq9cjwVYp+hJ9bzGQwOIaEdZPD4cQn+HQhNYKyQK5wG\n4ukHSE7YnaFvJyf2zSN6ztg3DXn8MZ1Gvl8RDfD0CbEJvVyJVbAlMs8zaRnIxxX6wtShPzakR05y\ngDRjCCF3pFZkhqcyMQ2jF1tydb/fNGINDn2A0HnA6Gtiy4maI9UaxzntUkjF0sH3PHHkdG/EeUDX\nK4xuGdBekCfIYWBbR9J4RUKi2oFlU28C24mvPj6xtcA8DAyXiGpE65UYT1Qd0BJZu/JhU5YPK7Ul\nvmkeGk0Q5joCkdo7aTBn5jAgliAperki7J5glucmcgyZbv5ZDr0jGNY3kkb37Ta4ix7k3rtPUaME\n+r7ExWEk7XYAgCwVCx5ubgl6c79jjhGRwBAOtN6p2lCpz7LvzoDu0STWo2u7AxRxz7o13edxXsiC\nqxOkVWJMHpRrs1+POiyyv969YT81I4rvV1Q7dQDrHSQwV6itE3qgxQZEYnzBOeQYSTHwv3z5gf/1\n60/csi67KUv/04Lp5x7Xpnz1dKapMYdMbEI8TJRW0KY0Fbbu6OWcEsOUnOO+rIQI30mRId6hy8qa\nYAi3hGjv0FZVSnWyjpUr0laOQ6ZbonQP+8ohktKeTzzMfPV0pW+d+0kYliunWfjVu5lh3WjZiFG4\nn078war8wY8+MNSRFM4MMTCP2ZHFAnOEd2/uCDRyCuQgnKaJMfimK5hxIXAYIpHK/Wnmw1a4XCql\ngan7PppCChDGgd48Lb3XTrBCPo0uZ+zN6XgSeXsY0dZpJnQVPpVKqRUxOF9XhhSQHAmh8xDgDqNa\n4DpkH0VXI+MdgBQjqpWmkbW6fyemhKmy1u4YSTP0ujqzf5xovWEpsdTCpeL+qq14MaBGrIViTtCZ\ncmJQD3nNwXOorkW9g9V8P1P3heRuyExvB6xn7u5ObNqRanvAnAGNLDAkx0mbOqChdGMQOI4jy14I\nsYfZqlXyrgWOIvQIrW9EYBoH19+LEEPk7eAFrAFjnujNqLXx2BrFlFOfmKNy3bZ9ehGcAPOKfBaT\nmxzzkNh2GZ2qsqrnIKSUfGohkRDDvkB5p6lUR5/WffOu5iFwKSauq8MtSlNMnDZ3LVeaBVLInDfl\n0QJVK70Z76JyWSqbwON6JWDMxwN6uVJ2udiyNnr13JaqwlIb59a41kxPgScdnymDtXaqdJhA4oCF\nQA8JLQ06jH0j7VKH1D1JftsWagzEnPw7dQMS/Ayp3svvcAPs60XkZxEMXhVa8VvyuJsUziUtZg6J\nUP32Y9zACP3VY99IhXhN5FKEG83y9lJu93/+w8tzx289g0vmBC+kXiYKz7gXvpONv/TZA2m58CtR\n+WGBrbs35ZtVucvGKIGlVNY+A40x6DPQ5vW/2i+HL4/9Lc/VP77HPwN8Dth/CHcAACAASURBVPxv\n8vKFiMC/JCL/PvCvA6OI3P/UlOkLXqZIPwZ+56ce9zv7/3968vSt4z/8nT/HX/j8RJwDHo0nSFdq\n8/NyTjAdGt+7n5/hK0EKKWdarfQ+PMNabDBau0lUAyHAelW0B1pLlDBh0pDsk3/MG16RRN06atBK\nI8TogZa4CTzEXeYGfLo2giU+qaODE8k3weaJZGqJY4wMEtHS6D0SY6aEzZsDpXHtrmd/Mw9soqQ0\nEmNjGiJlE7bSaXse4iSdOUIOML6JiBljir4BDA5CSscO44DOkNZGSAfCr2TC+AFJBqU5pMUK9AyW\n0PPCSKY/gZaElYKEmbrAua70lhE58umjutdIBz+TRNAy7c2ISGiN0iuEibRv2rg0kIhZcFhD8Ows\nglAbWEjcZSENAxaMnFfejYbQiDOEoXpzTiYsFh4eCjE3rAuyHaEXb9CMkdNg8Ij7aqpfj4gfGHpk\nfshgV8a501N3/5cUkIxK38EzhbVfCe8+oKHt1wZgNOIJZKhYz9gFbErUYWP8pZH+nSu8vydkQ/qG\nnQ398Uh4CrCt9FHQ7x2wjytldglnGBv6qAzjA/8Xe2/yY1uWpXn91trNObcxe503EaGsqFRJmVIh\nwYQRYgACiVHN+R9ADGBCM0ECITEqIcSACRIqpkgMacSUAokRAzKrKFSq9Mzw8HD35++Z2b33nLOb\ntRjsY+YvAsgsqFJASHlcLvm7/ux2du/ee631fb+vPS0c//Bz3J/wpyf8a6Wb4rWTzwV0xqSg8cK2\nGParhgSlWMfpaGqc3x7o8xE9TDgdb4LeVpyNnlfSdBjysSlg1tBlxlpnXQuHxVETvAurHeF2GflY\n6wZZcDHCXSCSqR+Vh8dMq1BCpfuBbQ1UrWwesXDkoxntSel24RgibivIRveZ5pA1YdVIofGTDASh\nWWfJB0IvHMRJFhFG8HxlxZuw7UG32WGijHgHVaTXMb2RiD0PvUSY0vPe48M0BLj0Ufj4yNN0HbLf\nQnvZa8yEJE5kByQFoRm0vUmDRYRGTgZdX/bJrkbIo+Ha3AfEQSB2cB3qKnGG2kCEam1PKxh5ifZM\nCN5l6659nJMFzAJdOiKZFMfz1+7D09UM5qFiGFK8nVYuwlL2Am63zfxzn7/in/3ibsAoXBEz/t71\nxr/3x1/9w+4R/8jX71TBdM7wxauZOSQeuvH1x48sHwsxDtqdiaA50aoxd+W23kghkDURTei+cGsK\nBKT2YU7bboQU8bqOA405tRhNlFsf+tBgK+gwoOKdoIFDngjJ+ZMfbszM0MahJFTB/YnvgfcfOq0N\nPedyK7x6deb68IE3hyPHOTMoYZFJG5MK5wSHeSJEJeAcopDjgaWueIBYjNenGZYV0TBMtTlxuW1j\ngXVDYqT7mDrknNlaJwt8aIFvfrExJ+OYAlMM3AoUK9yfMqUWtl1uNA7dozvRXSi1c6s6coTE8ARa\nhIMnnnplCoqLUPbgV3vx+XRc60v6/GpjdBxj4KN0km+07mw+8OESnb6slKUMedEuzbpdV6RsvDme\nyHcTYXaOh4D3zs1gaG33CUCEnBNqnVmh7aGtRZxC5WYNmo3J23FmTnEAEmrhcEqcj5GyFoJ37g4T\nroHb7Yb1SpgCtW7jsIMwp8TmhaBKzpFtX8TzlKlt+JKeuhF0xbpTq9E98nRrfHi68nStNDMOh4k3\nxzwkd8hLwOgLuWYPn32ZZsTIWivU+nLIeg5UHfS9/tI5Kjv8QUX3grbQex+LIgNP3vqQ8WHGkRtV\nIlsLZGt4G1Hat8URHQtfsI1DK1xL4MPW2Bi49lqcvJPk3DqLRAqRME10cV7fH+jbQpEzd23jPimH\n6Fyb4X3IUN97oS1ONmFphSUe6AF6Fg4x7V0ne5G97fGvL2vE823PgbLP2OyX65Ni5/n2T61LnxLu\nXGwvsByxgUDX8OulzLMk0z69D2dM8XwYYYVdFbg3DASh+4+UoOd7NJEXO5PYj1OdkVe1W2s/8Ta9\nFGLu3FH5u99/AFdaUxKVV6fIeQ70beFX8URy4/1j4X9dweLEoW6suyTy194DA3l+ROcTqeP/r6//\nHvgnf+O2/xz4Y+A/BH7BsDP8i8B/BSAifwj8HPjb+9//H4F/R0Q++8TH9C8BD8Af/XkPXnaEcPax\nPk7zRC0XNAgpTIgkNHRSnGkCJThN3gzLsjmuZRQzu3k97b8M0UaoV07nTDNhsca2ZtK8UtYF68J1\nhdIToRpRIyGMabR5Q1QxCazWuFxHEypKwMOYZB9tYvOw366EuZF7H14YOqpGKVDbmA44oD4jntBg\nqBc6jckCZhtuK7eeybMyp+E1bT4IoEGdOcPduTPPgxr68PHKlA/jYFgavgrl28pGIGXHvrmQ74Rw\ngr4tTOcTRWfiNRGTQFCKBbZf9eFRWoxab3iPlB5xOlaGmX4OjVfHypSVVq7YGeo6jfDUmDimkdNj\nOtOrMh8awZw8VSKVOUzkOL4QIY7vovlKOAo1VuQsBMmIBSQYvU2EkLldL8PX83SiupCOB2qFNHc8\nXjEDt0A/Q9oqaMO2GyFl9NDouYxDYlZcr9jBoIDT0M8z/jagn3Wm84ZMkVALqgfqeiKEK3K/UCyQ\nq4+FqM+EDzP96074OzP2/SPkiTWdyc3hcsZaRGJB0oY8KLq8If6xYVapmgmz0atg64Hlq0ZZO/M0\n86hgx0h+uGGv7kilouHMVisxBdqbzLJeSRMcy40CrF6IV8efLqgI5baN9+l0IB0dKZW+dfwSoSmy\nPWG1EmrFouKqpDmR4oZaR+KYEGkaOGzfEp4bx8+ELz9T8DBiYkLd8fOCWab3QtglyqoT7nXIFM2p\nvdCCkVzBM90WjEArFSVQ2o1tc5SET1dCiODOKWeCdFQKZTN6DcMfpo3GivqEAK2t9DbhCrU3usTR\nTDZ2EMTYJYIOqwW+EUPEgw91j4G60tTGucsc1ZGtlHRQDh0d6H0NuCcggAwpbrPxnqA7Ja+NPda8\ngQ6K3fA7JUzamCDvyNqKU10wGt0nuo2g2YpR3Ok2JMiiMpoBzmhE1D1eoSvskJjenzcbZ5FIVyht\n+NizjalSCBHrzhaE8g+/P/xjuX6nCiZUCUVYjsJXHx6Zt0wZSrm9T9SQPHItltah6uiqJufYGylN\nbNaoXtGuXJoNElrZeDZMjwPQMLeV2mmmxBhQM4J0wnwgB8g0IpG//tkbaq3M88SvrpVy68S3GVuH\nLKi3xjlGfv7FidOriQ9ZmTJsmyFh4pDAXSnmXOrYdPGMCZS6EULhHCc2xuE34lxE6Wsd0q00yDdP\n2zBbqoJpwj0gIRKy8t1lw10w32jVON+feNxulK5sT8J1aUx5ZGEoOiZ2KrTuNKvEGIZniuGPaKWD\nCfmYST6kRGsbzw8iRZVtWQbeNU3c1jqeS3C6woGR++Mi/HAtPCwX5px4e5q5VOdWYfJOSBk3Z+lK\nIlIEHreVJpHHUsna6AxanfQhXRlZO30g47u9FA6oUHbxTTMf+uqnCofphSiXmrz4sEqtg6Rm5YUe\ns1Xfk+ph8EN0X1Tg8bri1ulRiQYfb5XLttFR1DspRlSVZbuxlBFKV/uO0zU4zZneOikpIejeSXXc\nlds6QgFr79TexuY62th4eJ5k7AucjQOO+cgh6f5jMYVD6QxK4O6TEhFCHCbaViuLK61BkIb3SoiA\nBJo51itd4KlCWISNzmJQXeFwYrlcoTZexcDxkFGbIAeaRuayMl+uzJPz+++OfPP9R87pwDEqZ929\nVWWM/L9+qnwrhoVIDSPsN9iYhuE+dNk7iu6luPHnUQ4jJG806Ha52vg79onkbbz4sQntCRufTKd+\n9Kd9Ko17Lk7jsy1WdC/IbPiMxkhrCOiepXw8S/0+eViV8Xqey739M+r4S4FinyAixozAEJSw+x/B\nCQ4Hb9zpkDpKF5bm3KyOUOfgLMtKiwFdViQqP9QIoRG9s2kg0odMxH8M442qdHe6jMyt34UJk7tf\n+Y2iRkSuwHt3/+P9z/8Z8DdF5AMjY+k/Bv4Hd/+f9x/57/b7+C9E5N8Efgr8+8B/8hfJ/EqFrSY2\nIuagLeLpC+iG0WnmPD4UlrbA1ng7n+jxe6bziS7Ougzv6OFw4PL4RNsK797cI9bYLgdubcNb5agJ\n1UZZC+IyvLM29rGqgtjIuHkVAlGVUioS2qDNSWDAflckAVSIw585iIjjs9sjfGwrRdLoANv4UA4E\n+Jg9JnU+i0JKSs7CfD8mTDFmyiq0WkY+33Jhnma85x0fXseByjo4vDrPmPWRW7c0rAsxJhAjhYjJ\nRFuUvlWs3rN9GDHtsxpVRhOz9YQ25eOls62Cs/L6TWK1M1vpxPhEzMq7L05cGwQG8OhWZ37YNi5t\nJVrE6o0s4PrA4ZAoa+U0v2bqkcOpk6Ybda1IOdFKpVtHqWwfYLkV5HBPYKC557mj4QqyYBZxN6bd\nJ1kfLjxuVzQ7h7MSiqNpvD/rWyXFSHhzQh4EtwXWjSgJayu1vaK1wnxI6JdKfajoN04hkss97XGF\nx9c0KcTJ2PxA5kxOA0nv1llvC9nA8pg0pXDA7jPp8wQ43n9AHiLtoaFd2TwTwhM6C3geR2FpSALN\nGeuVaZooy8g21DkMOuHDbfibfKHZhpyPVBlBpZcHhxaxYpyeZvQUaK1Ra6VxTwyZUAPvqqCzE9OI\nOlGcrWfcI80C7gfW6zqaUtxz6YFrE8rTDcSROHIWT6JY3wgxohKJ/Q6NHUmd3vYzWGk0nimqxtIG\ncES0UquBJ/oeGI84IguCkETwWknZaFzhMuNhRDU8xpWgRtBCCEqcO3PLNDPmmBEaWMeT0OOGxohh\nmF/pvdHbgLQA+xlq+G5zGjqAgf9O1N73xqggEhERWjNaaxAixSJb6ax5GjE21vA2wBohDO/h86Uu\nww9vHQlDSmyMDFLvKz0JouElfoadSCiibHUd54WWsJjo+At0zPdcOHenPIvAHRoVoQ/glgcEEFW6\nFyQMW8vNjAXhNEVqt6Eck/xC0f1tXb9TBdPaGj+0zndfX2kmXFpDTGgOap1pTszTRKagh8xSykhc\n7vBQGr6NgFt3J07K1htraZQ+wiyfpTZuTkVHEKwP0/08JQ5TovfKU4ObAtJINtKblwCf3c+DirNt\nxG78/jni5wMxKHNwWt0o5nx82JhCIDWn1KFlXcvI13gfhbe5Ms0ZVSco9Gx8eLySEO7nmWMKXJph\n6Y52Xel08jwRDolpntGgnLyRBbQXDueZp61xK2DeqebMhxNeA5dtpXfjrgleCxUHcxKRlNOAUfiQ\nfjV3IvuYNwiXshAk4d0Je1EgrYMXREbg2kM1ogrHKNxkBJwFAnFbuTtlPpvgTU6s1Qil8NfuM3+2\nLVybcisVteFXqsCHq9GPgSLDt6FeyOIDiLDDHgZ6Wqg7lUV3X4kBrY0zj+CsLQ7pIrofhAOljAlA\n7+NwPbI3BpK79dFxVxFU2T1D4/NS9pTz21aIcSSoX5dBwCs+Hl1kACBK9WHWFyEhjPWgcl03zjkP\nT5E79M6GEdowj9bB96T0AYmAkWlV9xpgBBgHrHdaG4jt7iP01p0dWABlfx0/wiSEFNkDnZWOU9tG\nDoGc45BkmrE0ofaBFb1Sh1l0yogJ1EYPiqfA3SGRekN0dIUqHbZKplOWxm3tvP/uAc2Jp21hTUOm\nk2Kgrp1l6ywMCYPmtC/Fu6lVBrKUl1Ljx2t4kZ5zrvTXIAayF0EvOUn7VKjsib7CcwbS80RPnq0o\nODYKo08fbx8DebcXGV0QkN37M2R44/ZPQT7P77l98nPCc6bEeH6yS+B+TRi4+9rw/mvyw9CN5EIK\nI9kdh0txiimqnWMM3B0nDsG4O2ayGIdLZTKh0GkBkuuOef3kfi3Q2PjpIfNP3Z/5r//0t5t18Y/x\n+s3Z2L/OqF3/S0Zw7X8D/Ksvf9ndRORvMKh4fxu4MqZU/+5f9EC3zfn4ZEjaBlBnL8LzFOjNCEHJ\nXgbvpzu2PHFyp14fWOlET5jfeLQfCCrcpcTy9XvW3qgm5LFY8dQLodm+5unIfXHnLio0J+dI0kRK\nMsJBNdI00Ay2oqQYmHPEV2FKyhyFS+9Y78xpYl0qmofB+/VewLc+ptxdOofUmXNEtTFHJZ8DMhn0\niVKNbg1Tw8LEh8vIknl6uiCeSAFeHSPCmNKXUvbmT9+z24605rSizLNzeSg4HZGIFZimhW6d0/mE\nzq9oxRDJ3B4bd/cdfCam76k18Mv3D6xq1NqRdmHbnL/7XadOR7RceTcNMly2iXdpZikLb990Zr2R\nT3C6W5EQsPlr9HyA13e4bkR/DTcYmOMO28TcNu5bx+VGLwOmEa+GbGBrQZOADEqf68jm+vxVxbxi\ndPp9ghBAlcMSIQrbrRMfDZWKnA2Ljnx5Zj7csAziJ/j2acievjxhp4ZukSzO0xw4hxPtKhwOR5gd\neW20KdKLk+s9oVfqz++ZwoS3J57kiVdfP7A+GNMp4W1FHu6QMg8/EYrFG/W9oBTi7UDdVuIpEnJk\nvXWyzkh+DUlpdSFP7/BrJVWDi8DjSlgLp9cJeeug73i6LjytlVNzvAtTmpmq8Or+LaaRWxM+fljQ\nLtA2SrvR04G2FU6HV7A2QjyzriuinZyVWC+cPj+yrZ1ehURktYrqkM9NeaKkTm1GK4L4SgwRPWRc\nhid6+PAipsNLfpyFrI8cZ0jpjnkO9GlCutO3zuVm1OrUItRTH8CGZlg/ETHmFGhduN0UneMocKqQ\nYxweYkZw+LpVtlbJdgAEVSfGsY9ryHR7FkrvDT3bz6saaarUPvY6QRAbxVNfhy+3k5AGxjT20dDw\nprQ+2AAvmY8IMaQRu9EN1zAmUNZR2c/QdTznVSFaINjYtzQqLr6/1w3DR5wM7PEfeyC9jAxKMyPE\nGdk9+2UbnvwQIG1jf5zFiTlQMHorhJDwnAnW+PhbrmB+pwqmac5cWuUQlbchkA8zZbuRQ+Q0TZzy\nCNOjCd0605TI6kxkSkp88/A4DhguPF7amCB1f+YV0Puu2FdhjnCMgXfnw577NNTOW+tUMxYbKe6S\nBZ9n1J0vl5X7HLhqpuRCW1aO5yPNG0sXPm6Vrx8rScDViHOiuiDduXXnulZyzsx0unRiDrS1UIrw\nWCrnoLw5J1QCt+vK9XqlbAxi0eHA8fX96BaLQBm8/7ME2q59dTWCpAErCEIlURmH5qV0Yoo0Oiko\nSQObDnKMa8ZzAGuIdWK8G0F4z3pUEVKtZHdO2ZitQ5x4WDuPvaNt4ahQDq9H52bZ+CwnZpz5PLFu\nKxdRcMUvH/j8fOTpodBLR9wxOltzgsFaVuYEU1J+/u7MqzlwnCJBIxqUP/3+ietW2aqRc6Jbp9bK\nWgoxDnPq25RINg68l7Vg7qS4dz0Rah0H9NY6OUJd1112FV4O25OOCVPvnaUPrftSOu1WWdaVKZ+4\nbIXyAgtgl8KFXTLmzAo5BKImbmuB7jwrvp59DqWse4E0xF1rrS/5QGbGVjtmo8gadDylbqMDMwqz\ncfzufaR5tzaQnSr+vEdTzQixE1zREEmzcxcieEfHisxWOpca+MEGOfJtPtIfHlmDkk9HVCPz4czl\n4xNTnilbhX4lCKSumFaMwFI7t6Isl4WZwDwHogopDdDHxRwsDkN8d/IhEvc35RkgMt4ffzkOj5Dm\nPTyyjykge1Hq7gNcEgJBBuDE96C9ID92p/aB3l7w/DiRizImSJ9GET2XM32X6+mezeQ+JHwqP8r2\nRhNmn3ztXTbdfVDPRZ/vk7Afp4qGfHIfY3o45MLPrwmg0NHedunqCA1ca8OCUnqntUY+zJwmuFcn\nu/P5nHgw+GHdRrKwjemYwch7M8fixj9xPlOfvufb6xOhrf+v1uv/ry93/xd+488b8K/t//7f/cyf\nAn/j/+lj/ewMPztvaOh0BNWEWca9E7MirXCQQHulWDXUFZ22lwIbgVbbHgcAWIUUaKZs68Yhjfyf\nD6sjsXGQTBVD1Smb4r4Q+zygDhjbphADrS4cszGFEWsRgo5Jz+SkGUiN1zXiwViacZdsEPyIaK60\nHgi9ckjKlALB4gjMJZDo+HLDbyeqXfbutpBc2daFY+9Mk9KzDkmRGVk6FitigTlE5Oy0TVkuK3fB\nsVRwSzytnbZ1Xr06kU+F0tYRNt9HPgz1Ca+FfDjw2bvE0+3GXd4IBydrAgvIdkNDoPaZD0+Bh0tl\nvr+y3QL37wrHOZBTZZqcWjr5cOT6w43DT08vcqinXzXKV1dy2BBzgty4pIW7uzvO5zNqQDI8OWKB\nGARzpX+eqG5oduZpRHBLnAa6OUUgoRapj4XpIdHKysPlI6fiCIFpDlzulDRHEp1+eyJ979zeQlgj\n07HS7o7E45cwGfF6hUXwcuBuqZT0SP58gqc/xe2EtcOQiYUT4X3A/uQ7yt/6Ix6+S8x65G6e+RBn\n3siJX1E4lXc7oa2R5k5+WimSMTvRtJDbE9+fjhzaxkEcCFz7leOdM2XD20yVH0izwpsDTIa82aCe\nYSk8PVzwsrBcC1++O1JbJJ8y0/0RqvK4LPzwUCBHXCZqKeDOVgQrEylOvH+4kWTBQ6QiaDuSvHK+\n+5KsBc2OHjrlVjjExNoaBixtI8rK8Bl2ahsh0PfnA9NdQdXobUbnSNbhD1vWM5fLzHoI/NkvFdFO\nkEaTM1U6KRyYs+OSeCwbuIycqGe1wbo3pVzhJvT+7IlNgzwH1KjUZoSQUR17jpvhFUKY96acjb8v\nukc+sEtE04BExUa3ESfSZWS8jeJ+ZCC5yCh8vGEETAWTQNZt+FZN8A6bbBznQOgDAhQowztnTtkK\nonHc3pzmdXihw6DYDqCN4XEPou0NkUT34fV1nEGYgAGl2ZAGbkKTiPjIX1QNCMIF29VCTgiZ6g5i\nuESq/XZFeb9TBdMrhb/6s7thvtyr02pvuK0brRlbqfQYaZrHgj3NrMBjWzCUt4cjVisxMEbSnrm0\nQnoOhjR/kd04Nghs1lib7Yt9GCNQjQhKcSUYxB64XW88TAm8MB9mziR+ReP9hydyTBxzolbhkCLf\nP260KEiEtQ852NKE4hENme9qI7RCug2D5yqDJnZdDNp7fjDjsglfP21Yi3SBA53UNnJSpmpMrRFj\nZl1XrnXIs6YQqGulBCEyuidPy8Yqife1EIMhMXCMykIlKMQYMDFi0D0QFFaFeTe/iu20lgS+VLZu\nNOnQG4pz1swtZD7sYILWnSSJXz09UafAqxnWJjzVzqXXQUrqhWWrBBno3a11RJS6Fa4q5DTRDJ6W\nRtkKp0PmFBtr7zyVzg/XjaVBuKx0UQqgPSBrY1qu/Eo6SZSoAY2BZa37mWVAKtSN21ZZSkOscZoz\np9Ph14qZY0pc143SRtd/nifWteyyzsR3y3XAK3CSHhjH/b4HuY2sjmsQsjpPC3z9YeF+Crw6BI6H\nGURY+zZQ9DIoemttbNUGJc5G7lNxdtmdE3VICN4dZkIMXJcrTmCOiaAZVJgPkWUZXr4kMvwpomg3\nAiOVzkPipuvIC2kDMqHTkUtpbGrcx8gpd7Yw8ToKP3udeXsK/PKHlV/2wOV2oxNHh8+NhTEZupSN\npjAfZg75xIcPH7hJJOeJ+IydPwSCJI42Qmh7r9i67dlVOzkoDE+P+piGGo62xs/vXnGMla8eVt6H\nTPSR0zH6/aMq8E/EcZ9Ojey5WPrNa7/t08F/41kCKOhgTO53OJB43X8TRPHJD38KfhAZhEUVRAbW\nXfZiWl5kh2OT8/1J7Gq8kQtlNnxxAYROa45GRW3AM34oxvpx45yUh7nxxTnwe+fET7848r9/U/nV\nZeWzt/c8XTZWUf7gXnk7nfmf/sEv0eioTvzyoe+zkr+8/rzr/db5rkBuidoHVXXdbrh0qg78cAww\nXYwUBekVt7wjxo0YBjmrtQYpIBJRceg3NCo1FFpzclTc4gCvZCEFePNKORzeMeVtHKDEWG+F42lC\n5B5aH4cWN1QhRKFZ4Hp1Lh8n0mFhvdxQ7tBUaHUPC/+g1L4Qk4/8r/ORu+MV2YMrTeoIO8/fEXcZ\n0JCxRvIefCneQPOAMeRBeRQdtK/uhlKw7LhWtjYIo9Yh5Zl5MlJWpAuhpTFhjo5QaPeVOSU0LFjY\neJ3n4fWr82g+hAniABplFb4040s7jqDNZUiBfEqIZbxFUrnic2L+4sv99zFM+68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fhX6o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vmv/VN/ir//kyMtKVkrJRlZY5/KUyHl6EbT0oi8iOlizmAe72NtM+QrmZgkaUrsm5A1ADwx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\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4xz+7HdCiqVAp2wpEYK5NyVtsMyPOf2nBvYT53DtihAdiVAQl50iEL3TOr28hR8uTGCQz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- "text/plain": [
- "<matplotlib.figure.Figure at 0x7fd39a91b410>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "I1=spi.imread('../data/ocean_day.jpg').astype(np.float64)/256\n",
- "I2=spi.imread('../data/ocean_sunset.jpg').astype(np.float64)/256\n",
- "\n",
- "#%% Plot images\n",
- "\n",
- "pl.figure(1,(10,5))\n",
- "\n",
- "pl.subplot(1,2,1)\n",
- "pl.imshow(I1)\n",
- "pl.title('Image 1')\n",
- "\n",
- "pl.subplot(1,2,2)\n",
- "pl.imshow(I2)\n",
- "pl.title('Image 2')\n",
- "\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Image conversion (toi matrices) and subsampling"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "def im2mat(I):\n",
- " \"\"\"Converts and image to matrix (one pixel per line)\"\"\"\n",
- " return I.reshape((I.shape[0]*I.shape[1],I.shape[2]))\n",
- "\n",
- "def mat2im(X,shape):\n",
- " \"\"\"Converts back a matrix to an image\"\"\"\n",
- " return X.reshape(shape)\n",
- "\n",
- "X1=im2mat(I1)\n",
- "X2=im2mat(I2)\n",
- "\n",
- "# training samples\n",
- "nb=1000\n",
- "idx1=np.random.randint(X1.shape[0],size=(nb,))\n",
- "idx2=np.random.randint(X2.shape[0],size=(nb,))\n",
- "\n",
- "xs=X1[idx1,:]\n",
- "xt=X2[idx2,:]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Plot image distributions"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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Tvw3wA9AJ2AfkAWYDFqDfKwo7Xfryyy/5ceRIMpZvQd48ZQi/eooJEydx82Yg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sQKPRMGPGDLvgh9VqZceOHezfvx8PDw9mz55NV1cXO3fuRKVScf311xMUFHRJW3d3d+bMmUN4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4fdbqdm927KbC7a/eRZQ6nVfwyXy8X06dNxuVwMHTqU/gMG8u233zIoMYTbW0VzqMbK4txq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EBrp41+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\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YMIGuXbsSjUaZPXs2GzdupGXLlowYMaIhxdPv9zN9+nRmz5qFTZLw1K/NZAioMUw+qKzD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\nIQQAAAAASUVORK5CYII=\n",
- "text/plain": [
- "<matplotlib.figure.Figure at 0x7fd39a4ebd90>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "pl.figure(2,(10,5))\n",
- "\n",
- "pl.subplot(1,2,1)\n",
- "pl.scatter(xs[:,0],xs[:,2],c=xs)\n",
- "pl.axis([0,1,0,1])\n",
- "pl.xlabel('Red')\n",
- "pl.ylabel('Blue')\n",
- "pl.title('Image 1')\n",
- "\n",
- "pl.subplot(1,2,2)\n",
- "#pl.imshow(I2)\n",
- "pl.scatter(xt[:,0],xt[:,2],c=xt)\n",
- "pl.axis([0,1,0,1])\n",
- "pl.xlabel('Red')\n",
- "pl.ylabel('Blue')\n",
- "pl.title('Image 2')\n",
- "\n",
- "pl.show()\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Domain adaptation and mapping between images"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "It. |Loss |Delta loss\n",
- "--------------------------------\n",
- " 0|3.699980e+02|0.000000e+00\n",
- " 1|3.608346e+02|-2.476614e-02\n",
- " 2|3.606710e+02|-4.534048e-04\n",
- " 3|3.605854e+02|-2.373172e-04\n",
- " 4|3.605308e+02|-1.515104e-04\n",
- " 5|3.604930e+02|-1.048652e-04\n",
- " 6|3.604655e+02|-7.607409e-05\n",
- " 7|3.604444e+02|-5.868306e-05\n",
- " 8|3.604277e+02|-4.642246e-05\n",
- " 9|3.604141e+02|-3.764735e-05\n",
- " 10|3.604028e+02|-3.124268e-05\n",
- " 11|3.603933e+02|-2.632307e-05\n",
- " 12|3.603852e+02|-2.260049e-05\n",
- " 13|3.603782e+02|-1.938188e-05\n",
- " 14|3.603721e+02|-1.706719e-05\n",
- " 15|3.603667e+02|-1.489910e-05\n",
- " 16|3.603619e+02|-1.336306e-05\n",
- " 17|3.603576e+02|-1.189587e-05\n",
- " 18|3.603537e+02|-1.066658e-05\n",
- " 19|3.603534e+02|-9.986781e-07\n",
- "It. |Loss |Delta loss\n",
- "--------------------------------\n",
- " 0|3.619308e+02|0.000000e+00\n",
- " 1|3.568950e+02|-1.391388e-02\n",
- " 2|3.567799e+02|-3.225305e-04\n",
- " 3|3.567404e+02|-1.105949e-04\n",
- " 4|3.567137e+02|-7.490749e-05\n",
- " 5|3.566940e+02|-5.504299e-05\n",
- " 6|3.566790e+02|-4.230200e-05\n",
- " 7|3.566671e+02|-3.324452e-05\n",
- " 8|3.566575e+02|-2.697764e-05\n",
- " 9|3.566496e+02|-2.210773e-05\n",
- " 10|3.566429e+02|-1.873910e-05\n"
- ]
- }
- ],
- "source": [
- "def minmax(I):\n",
- " return np.minimum(np.maximum(I,0),1)\n",
- "# LP problem\n",
- "da_emd=ot.da.OTDA() # init class\n",
- "da_emd.fit(xs,xt) # fit distributions\n",
- "\n",
- "X1t=da_emd.predict(X1) # out of sample\n",
- "I1t=minmax(mat2im(X1t,I1.shape))\n",
- "\n",
- "# sinkhorn regularization\n",
- "lambd=1e-1\n",
- "da_entrop=ot.da.OTDA_sinkhorn()\n",
- "da_entrop.fit(xs,xt,reg=lambd)\n",
- "\n",
- "X1te=da_entrop.predict(X1)\n",
- "I1te=minmax(mat2im(X1te,I1.shape))\n",
- "\n",
- "# linear mapping estimation\n",
- "eta=1e-8 # quadratic regularization for regression\n",
- "mu=1e0 # weight of the OT linear term\n",
- "bias=True # estimate a bias\n",
- "\n",
- "ot_mapping=ot.da.OTDA_mapping_linear()\n",
- "ot_mapping.fit(xs,xt,mu=mu,eta=eta,bias=bias,numItermax = 20,verbose=True)\n",
- "\n",
- "X1tl=ot_mapping.predict(X1) # use the estimated mapping\n",
- "I1tl=minmax(mat2im(X1tl,I1.shape))\n",
- "\n",
- "# nonlinear mapping estimation\n",
- "eta=1e-2 # quadratic regularization for regression\n",
- "mu=1e0 # weight of the OT linear term\n",
- "bias=False # estimate a bias\n",
- "sigma=1 # sigma bandwidth fot gaussian kernel\n",
- "\n",
- "\n",
- "ot_mapping_kernel=ot.da.OTDA_mapping_kernel()\n",
- "ot_mapping_kernel.fit(xs,xt,mu=mu,eta=eta,sigma=sigma,bias=bias,numItermax = 10,verbose=True)\n",
- "\n",
- "X1tn=ot_mapping_kernel.predict(X1) # use the estimated mapping\n",
- "I1tn=minmax(mat2im(X1tn,I1.shape))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Plotting adapted images"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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PZXomc7e3igQf31bumyYO+zpPd/t54T18Vzjv2TYCuGTKm1V4RhVVeGLr3FJy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OnCylcGG+lkYdVBlZ55jjzaDZgK1lgkWfpLxzFmDnXF6ywcx475TiDdszKRD58NXFihGsV4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\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d+Eg2vtKUG4GbmNfyYAppwu8syr7BI48ony91Yf8DpvZ+qBomsAtyM/LYBw1EA6I9U63O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vPgNp6FJACj/xU9c8edb40vfu0Urh03dWPv/WEz7zofI771/wpHtqvLbOSWEVjyxr8a7N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\nqTI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7h8nEpxWi2jHxhphrkl1uo6QgnS7okzSXNnqz2syYJHb/GhD9YbDWS0ZWl7o1dVof\n0qfo7oGSXvT4nsa8WBcj9BhTv5oraOg+EW++qjbGkDirckHmb2ak7lWi64pdNEOfAPvUp1YI2brP\nxrdVlz4oRfm/W6/Nm3iLwck0eqH0SQ+m7DKe8OmumEIMxGHwRrYJKUXUsoeIdtoXQC2VIQdURkSE\nMSVKVZpWgm6kPKA4JvtHrwaA9ZDqynauxOiY7aCClUYcEq0jXJe1cm7K7bSnqLGcV/8Zkxt0QgiY\nCCkFkkVCcD/UHIR1XX3LIYEpR2rZfEAUR2+io1FLZfNu2qVyXRInqjQtfvasK0ZgN2YHGeSJMRWk\nD1O2MpCykKMXx3fXg1MoqzLkwP2p0kwYRFlr49lVhPmG41qZApy20BuWTKnGsiyMWbies9PhtLGf\nEjkqQzL3YQxCbRGsUkslj4mrUXjz7syUI8fSuNlFTqVxvt8IIqyaqFo4rsbnT0Z+eHdgN0Z+8+aE\nVbi7mdhKw66VWrqPFeN0WpmGwH5OnGpDUPa7SF6dgpezyxhVHR+OeUMZrfB2AT8gundHfFg2JffL\nluqbBpNACJUYAqXBlI21CWPyaIeBxqa5I8IVjYm1NA/HNj+DgrjJGbwwNXOCaYz5xxBthRJnom40\nCb3pdymLqkuUt+pSpRCErSopuRPT6HI5BMQlpaqJzaAVlwr5eeENb2gVuASxe6Fjl9iB7mGw4N48\nU3U4Ux/cqRmhnn8v9/u/qtechKdTJkd4vUWusw9FhuCN0KIwivF2bTwfhU0mRIR5TBw2RWtj1o2b\nKZMsuecjA72eUevXX6v85cGYk/DFaLxrgVIqz+fAWuFmgJcn5VyUm6uZq6b86uBj9+sUaOKNQxIY\nc8Jy5ElovCuJz6Pw5lQ4NVgs8pNZeL/0BqxFHquH4N4vjWtpjMEx/BkPvl21ILrx5Rh4d3Kvyot9\nxKqh48TXo8NNigpvbeBqgqvkYJs/uRY0BI7FuB3g1w/Gozm861Qaf3oHcj3y9mQM2fjuHPhHbxpP\npsD7Tfj1QXk2wi9uB1TcT/rFPjIn5XowPhuM3eC1zi40jlW4zYHPd/Dnb5RnoxBW+OWNcVqUv3jv\nT+T7mjg1+M3B+M++FP777xs/2wvvV+Ov18h/8Ez4bg38xzQORTj2YcG3h8oXs/DHV+5pShj/2o3y\nbRbebcbnk/Bh8yFYTgkz5e3qNoKXB38OB7n4Ol1afDtE9gnuV88lEolEa1wlONTAT4bG+024yREL\nlUEKr+rAoRqTKE8ivF4NrxmUVXyQshE/wqjWPjyPKTGgP/qcog9fWlcNtaak6Fu9uyT8sPptn6Pw\nejOuc+jAF3++BPz77OfIqcKqxqEYNxmeDHCyyLkooVbMHKm/9kGCw7iMMTRqikiIzMHBGGKuxloQ\nkhqcfr/nyCfVMIFvQqrB0CcmPs/pHSluuN0nX/U1bb4B6BNznwLBuTgFrFonhXDB6rqXpAgM0Qvs\nVd3XUWmk6Jk9SHKtaGp9CiPkOHAuxpyMY58UEJw8FMT1saMEz3wKfhHWPnGbhgttq1Ojik+aVnED\nZgr+gHctu/Rixkgpfpw65t69K/TQW6c7bTVSa2VMwmlThiCsa6Nm2MXIk44RHkLkvBUkGXnKtLUS\nJPDseiI2pRDYkq+8g/q2IfcsEtTlP6dSeHdUxuz/7WYXebdVrhM8v7th0TNWXd41T4G7qGy6Y7Ej\nb+8bP/ssswuRp09vWdtGbMISYUwD75fCAWVvbkKcZyFZopny1vmlRIu8Pq9cTSPSClkiKblMIOKT\nliBCC44T5UK/g04686Yoh8A0JAxjq5UhJjAjJA9DlhyQBhXXY4/Zp3JNjYZ7WZxaphBD33EZKcYu\nB+2nQvBpU9WGmO+PLLqEIBFYayUNLovbrPskNFJ6kKWiHXEseHyU9tDdPtW9/N88ZlJpnV7ljUGp\nPvnOQbhkqViMROuSxT5owIVGnXLlgPNP9RUwcoo9dweWUlymCaTQC2OBacqUptDKR5jJGKCESGFi\n3RoheNPSunSyRp80B3G/4jD48boW946EizE+BoiJYUoMraDBHwISZ5aijNk4bsK+e+vW6hEE2Tpt\nczNySgwD7isDxiF+hAGUjqbVDolQNULu0kpztHhMjjMfhoxaN+pGo+riFDN1Lf+QPT9q2ZRpiBw3\nIQZPmJ82YzdE8lWkVmMOmcd1Y0qOo12KA0ee3w6YwFJAW+Bq8qwiB2UYOfrPnENgWZU39xvTEBBt\n3F5l7o/uGb292WNqrKUCwn5K7G8y66a0Wnn5YeXnLyaGXLmadmxVaZaIEhmzSwNrMVqAtcHVYI51\nVzgclCn4du7hYeNqP7I1n7A6Pt1jG7Ye01BbZJDLvd2DrHFfz9r8TNjtHL++bJVxnDHcZ6WtMWdl\naZ7pVtUYB5epFXWp1jQkl8C21rcVnifnuOHBv6MqQ4wIza9VMSeS5h2KokEo5xNDTpQGycTBI2os\n1VHNl0GP4FuhIKClcAkiSuK0QkkDijHoRhL3fph6WGhtTupzGbERkwe6oq3nL/Fxey39GazyiZUe\n/49XwAv9U4PbqLxf+gaeTtBrTkj7+T7yobi/WNUopuyTISmytJHfnpRdLNyrb2+m6MjxIbin6Uji\n+eQn+svFs/kWE3YtMHlwIs92imn1830MXKXMD2f4Zm786gTPRlfGHNfCFOGMcJfgdwvc5sgXI5zV\nN5rfzF70Go2XG4Tq2P83fev5dPLnZumKhZAzi8KT2Sg9vPgmKdbObOJhtVcZbkfPj/pwNp7Pwm+W\nxGex8u3RuM/GN7Pwbw3ui94H4+25kQb4bBIOmzGFwH/yuZBo3K/GYxO+3guiFVHjSXZQQCvGHANv\nFuP7t43PZycz/vxa+P5oPB2Nb24CpyZI9ebt6Q6+vvOGBi38zy+Vv/cLmBN884d+tqHGIrAb4MmD\n8mYTnkW4L8KXc+M6BZYm/KNHsBQZRfn7b+Hv3AakGNfZuM7+93cDPG7GMMKxRKauXsh9A72ZRyXc\nF3g2B7659TPi9bnxbD9gBuMUObbKOIGWykkihwqfT05QPJTI1oSns8vmtguMSh3/fp2FhexKi6YM\nOTLg8rgUDKuFOE1kc3T3q2VhN3jz8yCBfVdpvF2UOToldexetIsMda2NQ+lb8RB9cBIyqxqVyj66\n6qGp8W7zf3eXfXi9NcOGkV1w6d0cHYKi5pTXOQqL9qiE3+Prkzq1JHj2AH2Dk3NANyUk6YZSNxaf\nNz/up2HwWb42WnW/Cl0fnknELD1DRLv0KpDESOYdfYyei+IbTF+xtwabFTQq0rz4vEoDFpR9BiX6\n+rd6sR2CbzAMJ5IEMQ+dDIHQsbKYgwsQ324Eg9C1m1ESWl1zWxWmvolqKKV0g2I34TokwDMXmgq1\nS2s8AyVhHRowje7bqQ1Opmytscc4BSWvRizKafOfvZRAkUt6Mzx0P0EApjHy+rFSMdImXHUZU2vO\n5n/5uKJqPIbIOB9dmnRunFrjZkoezCYH5mFgf5U5mPJhq5S20cy3WetSmYdCIHI7CstSfRtTA2dR\nbsZIjpHHtbATiDm7+Ty43HKr6njmeHl/jUES28XP1KezYk7y68w4Wt3oQEOauRnbtH8+VBbsYy6S\nFm8Cmzp5TgySuTy09S1VkguJjR5Q6VK81vRjCLMEkOqZJ0s3+etFbmouP/UtWOihkMDlMw/y8T7J\nIXg4sbgh1mrjR3tTpYkQurwsdmJgIvSv1fqk2YjN5YbakfypB4vGwCf7CmFg/XiIB/ZD4GEtzDEw\npMimzmM7nx5RAtNuR0ZYavUA4eBDjhQFC5FxjKyb48QVD+4MtjkQRJwONQxT12gONPVJWV2Kp9pr\npJXG9U7ICDG7qfhqFLRulJ7anoJjrelF7bZVahRSjE7Ps4vfZYAYEFNydFJnjr5VTTG4B7F7UKI1\n1rWRUsS69OoiIYaAmnBeCmOO3gD0wU5tjevZgQObCeVYHVqTEskyD6URcZlbFGNdBWRwSqjA6/uO\nXw+wGxOvPnjjeTg3dqMflqaOU3/9we+9LQrb6koAD6yt3F0l3n/o0/TdyO11wqoTwdZt9Y1N9kJi\nNzmu9maf+LA08uUcrcLNLjKkysNJGbNv986bITFSW6FWw1L2bX+Hs0w5U9pFDnkh1LnPNFvFrLKu\nbr6OBGoVWl0I4qGQtblPVIJLLk+rP8NaVYgRSsXF3n6emFkPqTSw1WV1fUN3CRI2HE9v5eCyOvUN\n0Fb6bkp8sLKpN6eE1HdWTjpzT6c3PpKym877dLpsZx+y4HKzDuhDa/Ww3lagb1pr3Twa0/rIuPs9\nFd8quGT0091Sg9Mtf1h8MzdHeLYPHI6F3RC4GgIP1eMrfvd4pir89GakiPttT6uQgzr5McNVEOYh\n8ebkvpFigobIno0djZO4MT7MiUX9nD43n/a/3RohQlPfgP/xjasffjY3Vg380R6WsvG2BHZJSMk9\nM6cOIHm7KHfJmLPnJG3dwyoxskuOjn6SjfviUsGl+fbmUeGz6HK6Zsrrk/F8dJmedB9wNb96NoN3\nR+WzEfIkfDH7w+tYha+uPDfo1IRvH41DUb7IwisdGJbKKI3fnYUxVN6d4J6Bq6juWXoVuEsOf/hi\nhn/wqvLYAncPys+vHL19aEKwwD944wX37RB5Mfdt0hL49qD86V3gYTOOavzyNvLLJ4G3VVnWwP2q\nnKrwZIy8WoSf7D1T6PMr4f1BKcHhNy9L5I+ujKts/OrQeD5AEuH7xYETx+JN1m33rFvwweRXe3hf\nhUGMQ/NzZI+h2msRUx5Ovs0NFjgV0G2jSWSIwijKq83YJ+XYjPXktfFhc0y3qDL0c2QziGbsh8hD\ngck2ivnIJ7XGqTaW4sCrIQVk9ab3YTGeDELp2aHR3Ht3LOqY8Bh7KWJ9cNOzL1W4G4TH4nCwirEs\nGw9dpj5FYVGn360K+xR5LI3r7ITWbSsczEEytfuujtUXHdfdYnMV/3/ow//rS0J0Dns0mlWkegaT\n4Pr9i8DIcdpebFZrXdLixfycnDx0tkrApQelQbb2Uet92FxvbBqJI2jP9gBHJLkWuOcdqfKuLUTz\nQrKo31CJeDGNsFYvcpbqlKEhRYYQWJpvkD5KtbrO+1yVMQeyRKq5Rv1U/JCJ0TcDTgOEx2VBcAH8\nVfQ8JKyi4QJ6UNZqFCvUBnfTwKkVcnNwQd0aYzbenwtj1yXvB2U/Dh8TnncIQ3I/0Fal6+EbpnB1\nHUlJ2EpApDKYY8TnZEgZuF835iFRJRKpXF0FnuEwhBAyWy08vRLaGlA23pxHSm+o3p+agzBqYd4H\n7pdCVTgfKyvGLg/8sGzMAUrwn6nilK/7tfF8ihAb6+ZNRshGaYHSBXCYFzuxB2J+DKg1Q3GvWE4R\nQ5Hgt8olNG7Q6Hk1Kfr0VtxTdHmANMG3jIBtyiauA740UKEXNNb9A5Iu0lA3TmUJLqkzz1Ry6Z5j\niH3r6NPMUiFGI2Ns6iXWBVUOPRxXQ09ncXSx/wr2Meg5fZyS9w2nvwk+NTcPsRPpEqO+2f1UXznK\nx0KSVlgbXOfIJoFifu8ApHFPTAltyrE25iEDTreasmfM0JSogZgDWzVEV5fg5cB2rkwpspEZU8a2\nxYtMU0SdLHnS1kOilVfvV1JwHLWqS9NCiMTOQVuK+gNj3RhzYsyREIVaqh/iTgpB64aph0dfTZkc\nI1utiEEp3cNp1X9e/Aw73N9DHMgxMgwOxtHmcsKmimhgqZ4b1hRurxLreXW8a4gcNmVOsJ42zgH2\nU+ZqjNzuE1vfvAYRxuRu0rV5CO3WlEjj+W1mSMK6uRLgIv/YDcJaC/dH4WpKXVYGT64SL26z/72r\nxLI1Pn+SOW6NJAPfva9sTbndZz4cPAfmeDKud4nHY8VMeH3YsNa4mgd+d4IxeyR6rT7EAOXDofL8\nyqWxj+dKTYE5BZ90SqDhPh6z4B7Gnj3UOgHOzBvoFIVkBR2Gfj/52TfGHvKbXQWh9F5J/bMZukqh\nmj9zSnVinYjL0l3i5/41eriuif+5mAcLq6pPlYMHpYYAu5gQMWLy4YAPDUGSy8AMg7r5pjuI0xXN\nz0egqwq6dLWHdPsmyc+7YB5mjvkpYrX65jYEtq0iePH6Kb9yDhwKPB2d/JYqzFMk4kCCoN6k7qaR\nmyGyVOVxbTyZfZJ/qsYXs3HWwKvNN0ZPZ3i7GbMWphi4G4T/80H5bBRWSzxJifPqz3FVj9Z4u3g2\n4G5wKfjf/17ZJSfVfajw1SzeKIkPhN8sDkj4zWPl2Rx5Pgm3SXi9OqlvEmMxqKWwVfh+afzsKnI3\nBA5bZQM+rL5F34/G69W35kOA/+WHhZwyOQf+YCecTNDaWJNvD6LCyzXysLlZ/+8+Eb49Fm5yjwc4\nw2ej8uf3gedp5dk+8pOd8Mu7wGNxYt/PRHkyeBPwhwXusnIs/kz9+QsYknG/CUMUPht9S3Q3CZTK\nrx/g6z2c1SFUX98Zf/eZY/mHBMdV+PxOaJsRo/AXb+CwwS/vjP/9vXBUYT3Az6+Fv3mEpUV+9a7y\nZoVf3sL/cA9fz8ZJ++e9GaMU/vF75T9/3tAC3x7cQnAzBt5vxjFENny4vVrgKjm4LKhi1j4qRMbg\nBD+1iu2yx52oQYw8Sy6nfT568zXSkASPznRhi5G76NvgUzEet8LTAc4SCcFpjO83h9wg7gU1PH9y\nBZ5kQI3H4s/NIMYUYD/78Oh6cFHwu8Uld1GMN6szAE7F8+pE3CdWTTgEVzrcDhD6UHZRXz7MUehm\nbxpOXRT8TDyrcW5ey31/cuXW8fdcinxSDVNdCxIzpbnbQ7qUKEhj6dpJNSVIZNH6MfSvbC5XaM2o\n1R9uwZTYjDMXCXaApjQTTKMb6qmsS4AsWPFpINH8gUMPBlXhOolnakRh7MCHqur5O+rZRwAxOzZX\nxOEMObonamu+nZhjYBWXvpReWMUYHQoQoJg3WSFI3/gYKQ5OCTTh3Jy4lEKgNSPHhImyHyI0GCeg\nr/rnFHpR4ZQ/m8xDFxM8bjCmXlSrI0aXghvZxelAh2VlzCPnTWmn5pOl6FPcsjZa9TC6fY4dWFH8\ns1ABi4RUKK0yysSr+41aK2YeGrcfBmotXI+BRSt19aZ1zL7W/eqzgTcPhSkZx9Z9aKrU7LKTMSb2\nOfFhqYx5QMyLka05Xt6aMeZE1UCMF5O1diS39iWke31K8yahVZ/Ely7RlNAcNqKxB1h2miE/YoAd\nhRm6zUEvuyxQKDSCBlKKVHf4ExBab5BFQMVDD5v6NmTT1iEkykLozgMhVEfrG46xbebbr48Bzkk+\n0jcd9gGY58ZIv/bdewDxcq2KF/JJ3CCck0BwMtbfWmZ9cq/H84ndOFBJfSvrYXzZNhaNZFO2shKS\ne3ouobXL4ijyprAVl0yYNaRt/Z72xPuLbMAdKMKoK+Vc3ENmbtiNRG7mAJJR8zygq+zex9RNtoYR\na+nhfI7lFzGupty3jr4ButDfSik0C8zZr5lhNyAK51IY84TqSoyZokKpnvEWgv/cu/0VrUcSlK0y\n5YhFJykOKRNF2Y8uw7kbXTKqKZEG2Iry/Dr1oFVvy8cIh8WYssvJqhlrdTjLGAURJSbhdN7YT5nD\n4vk+KUIK3iytq1KLIta4niKleaGt1SfkSwtk6fl2MfG7N4sX+wY3u8TtPLE1Y57AauOw+Rm2GyLL\npvzixcQP71d2g3AuG2Mc2GojSiQkYciJ/Zx4OCrTFNDV7721SX9ONPLgJNIofv4KDSFj1mmi0nzJ\nggdinrbKmCJWNlqgX0MVGkiX94YQieYKic2E0AohBKfdYYglKj0HDIc/5OyNfTWXXpUOK2lNe1Ps\nm0WJQitKQB0YIaVbpJS1PzdFxHHp5koFgoeqRr84emQHPW6j9cFNBKIPA4Ln1WX1HMDW/Lq1UslD\nJtVCadb9fp/u6+3DwvMh827LzMEVHlUDV2Hj+80b0vPiHttj6XRfMd6cNgyX8h0WYT8oURVpxl+3\njg7JgeMGRxUqDm/JFF4eGzk7onmKUCTwhzeejbea4/+fTx6MuovuRYkYp9o4a6TWxmfJr4k/vo2s\nza+Ng3rxuim8WRrHFvjZztgQ/uA28dCEulRu5oGruhHGyEML/G6tTDGwCy4n+5PPRu43l3T9cFae\nTIFdN+zfjU4a/cXeA+q/vHG1x+0QeTE2Hjbl33gaWWrg7+DPwpts/PoovJh84LKpg6ZeL8Kc3Ifz\ndDS+PTS+uI787ghLNa6SMSYn4r1fPAMri/HV3je7CaNVf39LgSkZp8U3p3/5urEWHxa+2MOLvTcT\nP93Dh1J5f4bDEvhiB6+L8F/8NPIPXylf741lc9jUw2oUhH2GzyfhZ1eBP/+Q+HwW9vj98O3qw6it\nKJ/PgXsRroK6ukgbj+a5oFIbIo3NzL3eJjysjSdj4HFz7LjT8ZQzMONY+DkGrqT0iALhdVGuEuzF\ncfbVnMZb1JubFAJPxtiDbo0heN6WS9S9eZlDcDtLhLfFoy62qvwQmuerifHYlBYiJsJdDhw1MAdI\nOSIdHjFs1Wtgen6gOl4+dqRaUD9HxhAwMfYpcGxwnZR1gWdThGy83fgoHf59vT6phmmMjl68BGJh\n7iNRh9X7qlPcqxS8hiaIeiaSBCz0fByMi8QuRS8w1frDBTcdn6qSTDBphM23DEsxxg5v0O6navgH\nn8SR46kBQ0SbkkIkRZgl8KFWxhjJ2fWkgn9fM/cf7XJiLZWrkCnqCPQ1GJgX7EOMLqMKvhU41/bx\n4RT6hqQWDzPUIMQcyOoAgM1ReWyrstJY1LivfoCPzROYpzxwKA1R9x1cyHtRYNVGlsBgjRQC96eC\nhEhV93AZwnEtpBS4mSLntZKSkVLmVBrXkzFK4sNipFE5nCs5RMa28fZc2F0LD7XwNAbmJKxbR3xH\n5cnggXoiRpZGyYFlM4aQCSpMY2MKcDg1Dw2MkfO29cZCOK1OQAvBAQhRLuHDfvFvXcN/odCZ90C4\nuNMbDK3ecBf1XCMRxzaIeAMWUyKaT5dzDFQNvWlxc3WrnlMSQ+xbLZ/8xuieuSgextdwFDjNtcAq\ngaaNOQlLK0RJEAxrwXOb8OZ3jdLZwhe5S4c/qPlnJL4/EvHtUxLfsqqAFYeElKrE7JCSVhTruWJV\nHYyhjpV0QMYn3DFNOTInIWRzqqE1tCmSM2FbUBoWsucXpYS0DcHzxVIQzJSYvSjGfOMYk4dOay/q\nLUbmDGUrNNRR0ubv+bo68OFUfNMwDRnp2TRRGsvqD6ddjpyqg2dyFIYUOCwwDY4yXtatZ+H4Yyam\nxDQMbGshZryoD8JARusBQiKJZwdJdJnuea3EKOSU/foUOGijmTfyIQFSGWJk3Qr7lDmslWCNtTTy\n4pTLbfON2fUYOZwrpdPyzAxrxbNnNm+6Q3Is7uPR4xW0+Rg0CJwXJ9MNu8SyVSRHlyIW4WoeidF4\n/7hxkwMPZ0WyoSin48b1HHk4VW6uEikFTmslSfCMt11Ez0byA54puVdql2BrlbvdgER4OGykLTKP\niWU5AaBkDufqoAKBVlyqvFkid0JZre5/LGqgRwz3hEqfrKqCtUZQw6wiaSBa8+FM8E1ySpmIb3TH\naeqURAiowxq2goVISIlBC7U1SmkenI6SgvbnmHgYe7s82zwjbE5G2TZIE5h7Jy10EmIUsnaKaj/7\nU2+Ym1bW1ryZ0vZRRRGjfIwmKLUQg8dpzDlSxHOKovjn6pu35t67mBxx/ylnEwBfzvA8w9Oh8ra4\n/OtUlXXMtLZhprTgMIfrHCi1EkV5RLjODpjaD5G1AzOOatwM7jcpfXiRiXw1Gb87G1fSqGbszf1R\nf3MWPh/hXVXODZ7O7m1aNDBJ5dUJJoxpjBxWl/pdDcIXI/yTh8iLWbgdhTdnv4Zbcnz0bQ787Drx\namn8ZDAem/EiwhsSsp2xELhNjSmCZmGMwm+PRhYh5sxOnNp2PDaOGmh5YMhwI4X9YLxfjDhEvj8q\n39P44WzkHEkCzxbl25Px0+vAr+6N/XCh/Rlba+wifH82PhuEm9H9Xv/swbd991sPwRXhrw7G9QB/\n6ZiqBAAAIABJREFUegOvz0782wf4fg18s4frqPz1vfJsH/j+aDwZYaTxqwfhF1fwZ/fw7z2BmwwP\ni289xhF+uhe+z5CiMQVhyMLbFZ5PEFvhJzeZp1H5p28bP5wiP9kH/rdT6WTKxL94tO4Xh4e1MkdY\nmz/vrwTeFqfcvd8gtDMVH4jtxZ8VrTZOzcnE92vgaoi+JFDzwZTCfozscW/y7Zg5qLCpD4TnJNyf\nK7vooKBglWOBd2tlF4SdNPbZPWuec+WZlzfJm/BzM76ZjO/PjXkYkD58dRqh8dkAH1rmVL2mqAZP\nBnGFVfWmWCUgOEDk2Nzfdup4/WWrjEF4KMrdFMji4bsn8Yb8g18MnFZ/5k4JTr/nPLdPqmFa1Tnw\nG+Fjdk1DqN3QNowJmmslL+nkISXmC3vZHHntVgwhJV/9aYMieEBWbS4XCELpxWe1gnbDdBOfXkgn\nVGWUsjWcV2fEHgg658RjaWy1ccCYQmIphQuaOVlgNdfIBIRT3cghcVClVSVEcQ+M+kRCm2evrB2p\nGHAvQZSe6xFcy6vmSGQa1OQeltTcwD9k31JMJHJSqgpjjkQiObluWaoXyo5HbR5+lnwacazCLMI0\nRLaqnM0PD6mVmOG8Vq7HQJoEas8tEjhshSVnTnUjDgN5FI6rclDh5ibydEhcDZXQdtTWONXCNAjn\n5s3J47qhFYoo8zCyi8JqK+d9IB0DGo3b3eD49b4BGofIeVMG6cZCIGf3gG0GaKNXKCCJJK6lbd2f\n4xtEJ1GNPYPGPfi9iWxeDA0x0GpxSZspS3MvA3QfkQKSPPRUW8d9+9cv5hKv1rc9asYgkSbWmxzt\ndDv3Xa3NG9eG/yxGoEavrHzX5Lrepg66mBPQCX/WfUmCNwkhem5MjZ7DkAY8CFcvIAlD1De4Entj\naD7x+ZShD2sx1mCM0FHi5vk1ayOmRB6vGNQ9c0JjDTNjDGhdOtbdkE4a1ODFfzBvcjzU1IjrwsNW\nScGlCmOOnLfmIcDmFMkpOxQk4EXztnocrqkyZKFuyjwEzqt7gY7mMr3jaUO6P00CHItfhwljOZ1I\nKVMLLKUypuSeEnVqpdZKCNU3reYgEtvoRE+fgo8p+m8pkc2MMY6stdC0UemNoCbGkMhBqc065c6b\nnRuS58WJN/Ei4nLCNCDSOK6wmyLzFDhXgVZJAc7VaZ6PS2U/e1aQY/vdQ/p42thlwapvOafcKZ+q\n3F1lbq8yT68zS/M/r8WYZuF4boQQWc4u513V0eI5K5sJd8PAsVZGibx4skcbrGXDJLGbR87Fg2Jr\nq1QiOc2k6P6+0gpzSmgrIMELP9zLBt0zpIZIJKdGvOj7+7m4bc1BQylRywZiXba5deqlNyVjjKTg\n8uy2br5Z7CoDaRXMvQChb8XHZBd4HwOKJSeVhZjYtoWcI5t6lEEKQtAe9G3qgwCc/Fmash8jyQwR\n97Z0sWFHlPtWTcXz3fIYQSKmLhMO/bwR8wB0f/kG3zGjn+7r5SKsTXinkYDLTjc1DqfKbY48myfQ\nyoFEomFhZD8EntSl+6q7F1IMC4F98mfL2VyuNohRauH12b0obw2ezsLh7AMYM+PchBeTSyWbeC30\n8uxDzKbGNHmD8pMd/MWh8vJs/HMVvp4r3z4A3SV3FY3vHlziNAXlXzwW7obAXy3wfmlcj5GG8qEK\nQzSOpTJE5U1xzPUYlIfFEepJDJLw5ejS930n9i7Z40R2WphNuJqMhxb5KsBdUh4rfLkTdsm3XfHW\nB7Yp+FAzCrxaBcmZFGsP8xW+3BnvVuG+uUzMWuM2w68fjV/eCE9Hv4diEqIar47KMgqvauC2GXcj\nfHsUthb44zt4vof/8sZJf6W5d+suC+/Pfqb9i6NvXj4U4Q+u4MmgvKmw7WbCWiEF/v0vIofmw9oY\nIl9eJX6zBO5EWUvjpIEnVyMvsnJfhVoKaUhI9YHs7SjcBG9SwIe8a3NbwFdj47EGJvHn9lVWXi4e\nH3GTPbsyd6//Ud0b5d4f45wjQSKrKtu5sppnZA0hcGxKAQ5F2Efj3IzPJ8O00/BQdpn/i7o3i5Ut\nS++8ft8a9o6IE2e6Y9bocpmiylO7Xa22aQmwoIEGCV4Qj0gtxCRLSDwiJHhhkEAINWKSEEiNhAWS\nJR54QLgRLUFLFnTb7Zbd2OVy2a4hp5t5894zxbD3Xmt9Hw/fOiez3Xa5sxM57XipypuR98SJ2LH2\nN/z/vz93VXg8Bt49LjxZR/Z9MJJidIqvOiVTe3jc7RFuC3xx25ur4PhzX2KoZ0QFnBQq4hLKwX3c\nu+q1dsR/14AP3Wp/PeCbtD/Kx5+ohkm7rlNwJrz2gFU1KFRKn75IFLRLGbRZzx2BimGdY4+5ZrOa\nyylSDH1j46vcZo4tN1xSkfGbhWc3+YEXY5dZRRgI3UBvrFPkUJSEEodMVNe8D8GnzFE9EC4290VY\n9zBJdDDAOAQWhJUETLxRan1auereoyauNVc1GopWowlUEWSeIQimnotUgFTdKKnqev1jcZqbzo0x\nuTQpdUlWznA4+vuagxPbDiihNSYVxhJZusRsbn5TzApPtoll6UVl8Gwla06GK62h1QuirI0TC6Qo\nrKvw3uGOQwlIODIMwmaVXKJmlaP5BJYsRI2sooecbYaBcjBk6DeaxacWIpGjFdbVm+ZDVTaDPGyU\n0Ohoz944xZjI0l9fjJ3m9KGBUYBFXP6mJlQMFLK4FMqvSektklP3Yi8sIl7U3OeXNHWJTlVxSVRf\nDEWBakqQTuFCHcyAh1Y2wymA4V6EJz5Zwg/GKP67BotYD59MAUqTnrXkRMXS7mV3XbbXvwfulQKa\nv84QXPvsEIsOnFCw0B68TH9SH6YVakPTCTEGSit+yAvu0Wluoo8hYlqRmNhj5Dy4Qb6ns6cgmBZq\nxYlR+JZgEwMVuMyOibZO8RnMz5pmggaXl1hzbLUh3ZNCv6EJmzFymJXEzGq16fIF6dewUrSxTpGU\n3Ac5a5fiBaVUY7sZSeI+SqsTLQwu5YuJEHzb4rcag1ZRdWmwtOqa8sMd6xSZwtA9KpFQA1EKVR0i\nM02OXt8tlbHHPeQUyFoZs3BzdJ19DIGQhDIbVQu7Q+E4jFiZuhyWrgoQPnOxYi7tYaOzGZx4SnP5\n3b6T90orhAh5DKgYb786cpgaSWA1BM42A3PrAdSLIh1wkoIH9pamDEPgphbGlFGB46EQcmRMgcPi\nHg7VxGEpXKwSChTz98osedC5BVIeHOAzHwnj+l7jTaTSSqHZgkq8t7TSqiE4hOM+INfX2UKQCL15\nNQLZmqskVIkopTpxsannXllXKuRotFKJMTMX/566TcjfA7FAi5mUEvdkP7Sg6jEXMQgWcs+GcsJs\nToFS7WHKn/rwRh/ODj9LYjdW1jIjwb28ITgNr3aVgmpzIl+7z+r6k3uGAExNmShcjIEhCqX0DCLE\nZWBFqbUxpMqxKqtcORyU7cpBGzsLaFE2TvrgpsJ18YZjMyTWOZAwvrR2v9Om5+LVHEnqW6UchKsK\nS21sRx/ODMFpbJsA1yXwxibw3T1sw8xqs2KNUSQwjuLwj1Y5GQOrwe/jS+1Qk2jcLPDVi8QNmbOo\naHGlxNQgpciTvk2aza+1qo2p4kqbqkwq6O2OnCMaEqfSuAqJ05C4DIVDNZ6vAm/v4dEIt0cHQ8QY\nOM2QrHE+CG/ulEOBkwDb3HjnCGjlbYWnY+S9uTB3v2CUwFlSfuYzHl7rVDi4HIW5GkcVbgscJ+V3\nCcRWPbNpcDn/L72A3ew5Q49X8JnTgHUU/9XitdQYfPt0uRJKNT67Nm7nmXHw+uGtfePJEDgdhHen\nhi6KtMx3Do0fOg9EE6wVpBmLZk5SZK+BszFzkgPXh4U6jKRu88vSuFoUyswUgsvkBe6q8dKEs0FY\nqpPmVIV9r2eTGNvkuVlnSVkHZVeUUTzzqfb4lLPsHrdZ4VFW9qWxjpH3jn1bWDxbqQCTCkbidJCe\n4ekSwlkbV/fXsyTG6Bvr22acDXC9+HOLGadJuK14HZeEo95n8DnM6mZZkOBn9Sr4/fVYe1SBKsdm\nzDGQArya/2hFeR+7YRKRzwL/MfDPABvgW8C/9NHQKBH594B/BbgAfhH4WTP77Y/8+0vgvwT+Wbw2\n+5+Bf9PM9t/vZ4cYGFMmSuwho8ImRQ5NGVOkNliiEtTI0TWTGv0G5B9u6MVFI2CcRJfelOZ6azX3\nDGnTh2myia+LPfPEV4O1eThbLU5UG0OgCkx92lfUGIAYM7UpOUeHU4ixlMrSJ4QD0Q36EihamZp3\n58uihBQ4WCOYEKIXQTl5Ixd66Gjrko4cXXcfML8K84pVaH0z4UV2SnBzqMQcmI8zuQfSVvGfL3Nj\n7gb/0hQt/mW5SMkNxQWIwjoJhrKWQApKscgQIsTKvHcPToyOYb/ZOfGq6MImeTjjMgsHaWgInK6V\nnRWG1cDJifL6GJAEH9wVNqPLSeKkXJ5EDhOkwbiZHHlrQdgE4Thpn0QL63WiNmGtiVn84o5DwG0C\n/p4Wa+TgRvhxiJTq14OjuZUxerK4iJB6gdXwYrSoH0L3KdME37bkeJ/f5VOUY2uY+mTXGzSXBKYO\nXLgPDE7VmIKSYmRogcm0ByR7417wz9RM700DfWIt/Trw4LnSDdnFCgYuVW2en5TM586lS1ZTJ/uB\nPGzAWn99+MbbBwN9Eq5qDwXtPZ3P+ORymk/rHBlSIq1GSLEHbwZWq0hp0SUIPYS0mJviqyqS1oBS\nOybZLLDU6vS6IbHqIAyJkaIum6udsCDmMmHEi9SEh5kupXqxPBUEp12WFqi1umxBzUEO44balM3g\nzf197hckYgyMXTa57sOWufhnuBxmhuSQgRgCGeM4L6yyOgymX9faKoTEyTiyQjExajXy+JhsB5dk\nBpd95VC4PhRWKXFzNzFmH2aIeVO+a5Xjoh5YOCn7xeV421PfyuwrxJCd0mkNWWWXsjUvUHKAw7x4\n2HZUKomXeyWbMi8zwxBJwbjx4DNWQ+DROlItcDIGLtYeUjukxKubhc0qYeb43bPTkbvDwkkW7vaF\n2rwpGfrWbumf+6N1pLZIGn3glIKxXfl2t6p7NU2dltiWQhoThxpotSIkylQYs1FqRUWwEEjRYQCG\nsWhEkmBaWdSHcUFgc0/ExNAQWeYFqUefsKcNpn6u5iH3xsp9r0r1Kz9mSPkh2NIkehPThzitVbLV\n7rvtUsE+AFplv3ZMC1a9yTV8iJRicqInHtnhwApBe35KxagEDzcNPpBQdWlwEGGgUZqvu2JKDNG6\nzLf+QV/RP/ZnCMA6Rz67zpymwNyNyV/aCt9bEs8H46YYt111cNkl+poGMGVuxjo45v/17JLLL6/h\njU3grnjm0rGHx05LJQaXjKu4PGvB740nWbmaGvsGt7uCAE9HuKuRt2af4lw341FUTlYjt025XCmr\n7APBV4vwWjIxCk9D5dBgk4XbBd6c/F7zzqGyHeFK760D8GrfOF8ZU2mM0SEAh2LEGLjcZEYxBlFe\nLkI8OeczcuCmKOdZEGtsk/LLr4zLdeTF68KTlZ8jkwm7BqE23jz477sz4ebQeDYYP/k4ESPsKjSL\nfGHjjfyXhsgqGMfiG5cY4f2D5yRtszFb4BvXvnG9Oipf3BinyXi1N44Nylr4kVPHgv/AFk4ulN+8\n9o3+r3wAX9gGDhqJtfLjF8Jbd8rncuCbt749kRD47Bp+98YjZVSEL27h0AKf2wi3GjhPytmpcFyU\n2w7p2LXAaXSE+mdP4NUsvL/4WP79feGN0RxAFpxAvBkCTYQB47pFthn2Vbkrfo6sAx0jbiRxcNj3\n9o2pTKwS1DRQtZGTcD5GKsIquMdstMpOA+sciCnwfoGTJJROz51IDAFaD7TGxD9z6d55MZ6uhJsC\nYpWrag9E6w+K1+enyRvYO4NDEc+Tmh3KM5kDIY7mDalo44APpXMQxuC0wiDCyRA4T755VP3ktcjH\neXyshklE7g+dvwr8BeAD4CvA1Uee828B/wbwF4FvA/8B8FdE5IfNbOlP+x+B58CfBwbgvwf+G+Bf\n/H4/f+gTumMrXbqkHKBP6hu1eZeaB7/BT4syqqISyffEIBPWRAKJgxUGAkuf3iF0c7dAL1aVRsXD\nxIbovp0gsCXSknGsXmzTteNVfbOUUnTPh8HdMhMt+OZLjXEcKLWCGHMxUlJiv3hLA1JiTP7ThxBZ\ntDHG6F6i1BGOaoQxEtU9N8EibXFIttZCScnfF3xFPgtcnKzw4MXmB8/SGKJLLmaUEGBQGDUwJ0dY\nv54b2+Thd4JvH/wgCo5nFmPRQiuBfWueFl2VPBgxCbulMOTIfjIojRSN89M1rVZuboW08kyjYUxs\nwoIV4VBmpiViyXPJ5FDZmqIxEMfE5eggibnCRiJXOrMdIte7RqmL5yuZMaTMmAIqjUigLLU3vp5a\nPy8uT4vi0zszY1ZjDJGl+1M8k0J7qFrxwGPxA4rm14cElyZIEEIID9kjKFTUiY33Ta70mXqAKQZE\nAxSYzXXrZvpA7BPovidHxgcREJeimrhBvKg+wB+0N0L3MBQRp+xh6jQaEapVD0MV34Jpx3JqT9nu\nyEYP2hWn8d3LtwTfloX0ydbgn+Y5osGljm06Qh5I/XPEKlob01xZrVacRv/9b6eFWO8gjYz3IARt\nLDHR0oC0goibd3OZQeDu6JIoPhTxYTEzBEeMl1qQIOQkRIPj0jcCktgMTkNrrXCy3rhfpjVudpUY\nlr4dDGzXowfpIkxLI91T9ZLRqrJZrcgpgDYPnq7GxXbDXJVVHvtn3liNA9WMjG9Yd3PBmmJlj42D\nF8Fyn/cDj85HtC4sKDkLu2NjzO7vCq1yEqEF902OQ6I15fZQWA/BX4840GK/wOk69ggIb/7nGtnP\nwlIWhmiMsTCOmZtJOc2B14cG1hgCXG4Hz+/Y1R6+Kmg2xsF9ejfHxm52yfL1UYmxYFSG5L/z49NM\nMWFaDIuKFliNwjtXB4oG1uKFTx5GxiF6nkRcsUzHh4bDtHJkjaljypfqn+OigTEaiyb3+TSXbFZV\npLk8PITefJgP5/Z9UJdiROJAolFCZjbFWmUcVrQ2I7gMXM0hI1kGDz02Q5fJZaAqQOtb5ESIgdq/\n70G6r8iELC7VXvpGKiAstUIfFIH7O5u61wtx+Y5Vc9VFcqT9oA3/GnnYsljrNFHnb3qYuZ9TIsk9\npfGTiVs+7VrkIvo5+b39wsWYOBJ5rxrZGlNpvNoplycD54P7mN68NR7pAWzgYnRfx3VRnuTAOkfe\nXpRHsfFygk2oBIF3d77dE3owtHnz/TgbT1YDN4vDH94YvIn63sHP61kDz9f+949aOd2M5Cjk1vi1\nK2WbfEO+qPC5s4HXFU5MeO9onA7+eT0flNcznGxHno1eO50PXhA/ezzwYoLH40ADpDXON4Foiooy\nhMDtQZkqLFNl3GSGbFSMOASuEf7scwit8A7GxWB86w6ejC7Ju6rGZoDTHmK72QR2xfilK+NrW+PJ\n0K9jM948BL58Jrye/HslYuymyLf3gf3s26PLofB0HfjdW+H5RviNKx9YniblRy4dkf//vjbOs98j\nH43Co9GIpnzrRnh7b5gYv35jnEThcVLG5M3Jn3ks7JpwO8Pz3PiVKfDDW+P/eVF4tQSGZCSEp+vI\ns5Wg0tgMA1eHhUP1IdGuKjBwbO6XOiyNhvCiCc9G46pGjg02tTk5rhpLmxE8J640/37NQdAFl3Qm\n9ymNodGCb4Z3RXm0yZRSyL1G8WFu4CasSUFZmvLy6HXm0tw3buoRC5sYKP0cGYKfAdol+9sE17P2\nPFTh9eISzyH6GTJEl5pqa8wFhiT+z+peursK2uV9xTwaJaEde+7gk9Ps/slBXLWwVFinP1ppr1hH\nhf49PVnkPwL+nJn9zPd5zjvAf2Jmf6n/8xnwHvAXzeznReSHgV8H/oyZ/a3+nL8A/K/A583sxe/z\nd34d+Jv/+ld/iCfrkdCndZig0YvjFF3iJD252Fxt5De2Pu2q6oVfjgFrQkzqkooYHuRKGE5yCsK8\nNPLgGmXHoBpjTJ4L0nqdJcZJToi5jMpzf8RN1/31O+EqsLQPfRP+i0XG+62R+CSQANZcQ9rUV8Fj\nEGb1gNtanWR3XFwKlpJvv6op65hZtLpdy7p4q4fcCuYysBjQqqxT8NfUJ32mPMjULIAWR2OMvVDy\nC9dlWjE64Qnz93QMkENibk7CO8sBS8JxqZyfjBymwtjzrIo6geVYjZMUvQAaAqNk9tY65lxIvUaR\nEBEz5upf0uuDk4JM4G5SkkY2G6U1NyvfLY2MclQnsDQLHx4M+JakaHPKIj65y8EzM7RLI12m2Ull\n/boJITjVSt1cKuLP9Ylrf614Srv71Lzxsa43v/88PD/JpX6Gr5XpV4T7W7qn6AEuoT0fyg9Fu/ff\n9W2QN1ldKiaKiFO7jMg9Gq/11xH4Pd91c08e6jfaakboKyozQYshyV+bBCMTqBXemfb85d/5Dv07\n/Ct8zMencY7cnyH/2hcf8zR7Voi1hWa+oc0oljIrKodWiSH7Z4KTqjKevbR0HPKQArU1hmBUyQw5\nsRQnHFYTxuTXzt2snK3c1VarZ9rk5FvBUl2iF6yxHbvBWb3QzqFhrXiDb+7viXHFXH17qX1zFWNm\nTP55pQePCTQTSlFqa4jVLq9S1qvRg0aDMC0VJfrUv7n0YTNGWikd+tIQiUAjaENxyp2GiCoM2Yti\nLbNfn7inqzaXas2L5wWtskNbqno+VFNvDMbsJ3mpvg2NyeU8qsblJpADHOfG+XbkeFw8d89gacIq\nOep7M/pwaz04YKdq4rA0Nsl9oM18iGEGUzFyaNzs/TOQGLk5KNWUy02kWQACdwfPUQokPwstgPgG\nKIhL6ZYGmMsDW3PcrvYhi+n9FqX1QODoIdQpk1PAWqVaIPR7SVMPtZ6rS86H5Geum7nBu0xD64yF\njIQIrXTojNNZPRJBHgY/vtHuQz9zaiOYY9BbQ2JyyXqXPur9atqMEBJB3ONUOvXV7g+C++3yw1DH\nnMQFD35L0cr9M6eqPRjbiZvah0svp4mfe3/3J+oM6f/+68Df/Je/8IQhZlcNtOqEwxgZgnKSE6vQ\nUM98oCq4W81VJqscuJ49KPvx4I32aTL2ltmOgavZZefBjKeDh2K/OBhPTxzMcrO4/+nZ4N/Z14vn\nMpkp/8DW/c2zwcuSuEgNWvWgVlNWEWIeuJr8PmfqG8KUE8+HxsEiY4TcB3ZHFd5fPNdnTeHJKLyc\n4fPbxN2ibDO8fTAWIpdZOVa4rcIPnggvp/Zwjqj4GVtUoQMCQg95/uKqYSFyPXfkPJGzBK+LbzN3\nU6Ga8Jm1ZzZdVwcs7atxkgNPVr7Jvy1wmYzLbLw/eWzBTzwC+vv3lYvIi33j8QjHBrsaGJPxYq/8\n0NaoKjzduKR03xI3k/F0bAzJz5zYhxy3i3AWG9+4Ec5HMIl881ZYaXUJH4HFhG/eGic0Xlr2zaAF\nqkQODUZRzrJ7oUZcVn1ThSeDb9qmXivuqvtamxqnQ+Bqdn/8k9G9+7vmgB5rjakHZu+XRlBlM7hM\n0Wsuv36rwbQUJCQkBKeTBgBHmt+3A4vCYrAK3gwlMRaF2SIJ5di8uUoxeais+mao9S35YpBjYh0c\n9FCrPmyqmsEg95shr4QE/0yqGpdD4K5Csur3TRVuFmXTIxeGCKdRuC7w/jzzC1fXf9/nyMd9fNwx\nzz8H/IKI/DzwM8DbwH9tZv8dgIj8IPAGPvUBwMxuReSvA38O+HngHwKu7g+o/vg/8OP4p4H/5Q/6\n4dZ9HTEIc22sYw+TFQ+KbcFvVq1/2U0dYIC4JC7iYIepGphrSw0jLICE7isJzGpEFRSlVukGTTcJ\nH+vSC2Iv4EUCV8vCNgrafNJXNTi+WxULLrXx/15JCtuUWPRe1NlBASmRRBH1ZgJc5lL4MNvpWBvS\nfOoSCWQLFJSLMXtmUpldfifJf4doUOFknVmLB2beLAspJPbFWA1CCIlNcBjGYW5cniTKYtQUOE7K\nobq+XcQLzGiRhsM3SlEuxwEpyrhRggmL+ZZskHsqy8LtoqxSJVtmXxZMjLYYRHh+FjnJK966njgU\nGNaRq9d7sgZqMEiRy3FgXeEQKtdqtLuFTU7s1EM59zthlRyeMFVlMw4crFAtsqj5RBZYSejXhmcS\nmPhEamnyADqAnp8kLt+r3X8UxNfRNLBw31wJRMgWCdE/X4BRvBmtD+hvf+rSXCJZ+k/KTq8nq3CQ\nHl4r3tgFcemGmgL+GqL5UKCiqHrgLF0K2CkQhKC+paR96FFSb9boxmBQN2YLDoywLkHr+S7VfCoW\nV+EByS4EgoZO7ZKPd2r83Y9P7RxJWE82UuayMA4uc6syYLVxxKEwh2UmmZOpUgANmZZHvC1vTMsA\nWplUET0yoxAHUnDqXK0RDZCtMs89T0OVYgmZZ5fpmbGOBiFxuy8M2YuL0ioteoC1UjyTSwNLW3qg\nNGwHz8xBKnVR9oswjBsihRAT0+x+Hu1EzmlRhuQ3S2uVQ2lIjKg0pDbOtyuWppQyYdUIeWDW+wxV\n5eJkYJUDpTZ2h0aMkd1inK6ENKxYJ7+29lPj8VlirsaQT9hNSw8tNWIaOEx3iDhVcC4u03uyzSza\nOM/u6SxNmUqD1UBeRfaHxu1RGZKfg7fHwp0pd0tlNUY+/2TFsAq892qm1MJqiHz79YGcPL9qMwyc\nbzNFjOOizDO8fzdzuh5o1Tc1VzslJye+ldK43A7cHipRMks1ApP7IHvejWnf6GolxaHLJLtSAZ8c\nS8gstTGXpd9bjGU+0ggEW2gFVLJnK6EMUahNOvgjgjQ0jIReaKY8MJfGIN7kYcJ6cH+rRUEqD/Lz\ne7f2Us2R4tQHj25M/jli1f1OuHfVgsNvkjXmZoCHHAetVPMt1H3jiDXo1Lyg5tLrGsgxQEwdUhQ5\nHX0o1sj9iPJBVUyf2D79KdciMAqsQuPNfeWHtrBgHEjsFuUgfq5e7xsiytyc6pZSZK2ZNY1KE4lI\nAAAgAElEQVSVGW8ffOL5nWqoHj1kNEUusxBz4oPFjflVGzdHJ/5WNa5a4p295wlWg6ejZwL+jdfK\nD679M393Me6S53JdUJAYuGmBWhsfHBonEb62bXwwQ9BKWYy3DoGz1chpqKQY+e7Bm++5KkUC13t4\nYzTeOii0ym/fuIRwGyqvCnz9cWRf4G4u1CqcDYkXi7BKDnb5ynnks2vjejZ+5UY4y/CtfeRLp4Gz\nceDZyu9N393DTz2Fm1nYrQfevGu8NTv5L4+Ju93Rz4LZuJ3hvSP8o8889+nxJjCI8XoRbmbl0Srw\nxlr4nR387avA89G4HIXfvmkUcxDE7gz+6c/D+RD4pZfw5tT4zEb4xXeVx4PxaobNKvFTj2BrlRdT\n4Df2kZfvV75yZnx7CVykzHev4DOjcbc03jrCP/w08NZVI+bEqwVOZWFRB1zMVbAmvGzuGRxz4v1F\nOjTKz5HzBCkmXk6N11MjR1hHY38sNBMWa0xLoRAZk3AhC+ssfFCESY3PrQBtTDIQxCE9m1XivaPy\nPDVeFt/oPN843GYbjLcXH1YtFaJ5wPK7R/cRBVGG0OEM2fO7shnvTdqJeQISiREizX1V1jjNAtr9\n1eKWikP1Bku1sU3+/5cGL2tgm4UhRe6KN0rbbSSaN51BfBU8GGzsj3bD9HFPrS8DPwv8p8B/iB8q\n/7mITGb2c/gBZfgU56OP9/q/o//v+x/9l2bWROT1R57z+z7u0d9uYk8s5hQxVf/zZn1uH2PPeUgu\nDWjm1DgxVIRRPAArigeoxv6ia1MPY8SnE60XlCqOZh263j6JS/+k+1PWeNbBIII1KBQ3lIdI6HlM\n5mg+qhi3WmgEhuoNVgqBWgtVXIIlGGMQCj6BHpKbGal+YzzJfRoZjGiJo9fUhJCIfSuyzdkzhAaf\nZB/Vb+IrScTgKNlZK8GEQ8/XAWG3b+xrJQXjYjOiCPvFiLEhNriEj250XyspR8djqmfFPAmZnAwL\ncGhKnANfOLe+bWlclIGlKc+fDaQ60yRzs0y8cZ54fahsV7CMK1YpQTOujo0WItPYiEX43GrgShaG\nIEQNTMUlcWMMHBZjOwQOnSZX1dhI8IwsoRcMngMxxL7BqY3WG997H5IE96glicQUqcE9TFHgKL52\njp3UuJj/rlgPB+wbqkCgWpdr9jJhSIEmRrbkHicVFqBEQ3BqWuq4+2JOTxLzIUEQeZgCDyF2Ml6X\nEnYSzv0526HnwIfbS/qk2czlQ1X8SDZ8coa62btYJUjARHuelCAqKI2F5nFlnzx08lM7R0qXKmLG\nOK4QvDDRUt1jYv7e5pyQOLBGvYlRdV8YLnMaY3PjdQwQRw+cRfpzZlKMlKVRzQmUiuda5VAdw5yi\nbyUeaIhGmRdSMFoN1KKklBmCsBAoVchWycEhCdMiD61fVWOVhDLf0SSRkoE2QobcTfo5Bkc/q0Ia\nWK88RDRHYbGRffU1g8QVIbhufD247PUkZUo1DnNhCJATBPEcubJ4Id46lAHg1a5wmCpDUB6fbygV\n6mKkuDCerBnHAfo2/jGutU9dSjjkSNwkhqi+mZkbe5TPPxmJ+Fk6rga0KV85PyFEp/DVqfL5x57P\ntl0HLk+2rHJgbsr13gcLQ0zMsbE9E8IxMOTInVj3iQS2uaN5N9n1+dk9QashMuuGIBCjY9CrKjas\nSSjzsvigo3sUFf++tg5bGfOGhPrgLntB6ZAPJ3Ga8jCwScE3+aUZQSJ1mR4k4UpgNfomLCf3sM7W\nzxYLWLyPqXBiYxOwSM+as4czRDGGQVB1BUWfuzyEYU/mGHBwUWlV86w7QLWgzWEw4Hkuit9PmilT\nU0KdydKR6So9k6zS1AOUoxn1k4NjPtVaZFLhwm9RvHGSuLbAs3VgOTaCGLvm58jJKrHOnl02VT9D\nalVuDKYUeT40vneAsxwouEepGFwtxhMWxhR4cTAW7bAMC0xVeZwrr+fGaRLORunAqcbnRuWtQ+M8\nGcfF2E3GxSq6AseEXRWPF4jCEfjVfXa5k/rZcJ7h5njkToL7JtV4IytXCeYG56NwmsEKaM589UR4\nOanXKCq8NQHaGNLAiQirDD+8dmACq8T1ory1N86z8flRWQVjtYp8MCljdDDDTffxf+O18Z2dcRKV\nP/ssM5XG9yZhExeeXyaerhOjeKBqDL6BeZJhV5ye9qe3yml2y8LrCVZF+Rd+wMEaTZV/8MRBGz/5\nyIO0j4vx3gJffy48um48PRG+dBa5GMCa8ls3DkaIKZFU+cceN745Ri5HYSXK945+Dj8ZA4ca+PGL\nwHcPcDE4oOELa+GmrlgL5OhDpFrgckysQmQ3VybrW3rzYWsMsC/K+RBYrwOzeSjvdh148yCcRQcm\nBDNumnsmDYc9NIPrAmOI3MzFfdPRh7lvbAKTBZ6c+PB4brCzyD4FxqQUFS5XcGyRa4WYjE30ZmcM\nDj6bMJ5tnPT7dBWY1NUVJ6nXHq1HLQAN4Vhhlfz+uzRlqcZFMg7mfq9qcNKtM4fFuJmVTVLUApP6\neyLm9+LF/Iy7W/54Y8UD8DfM7N/t//yrIvKj+MH1c9/nv/OK7fs//tDniHg46H14qMMSrJtw++Qq\npu498UmxiIC4jyQmo5h/MCl4SGRUp8ylHgLpm4D+IVjXaap2aZvfJUozqlbMFt+89BdfJbAahFK7\nDEvBoh+Wc1HWOTE1z7rIvcCN4kCCHLvJv2uWmzl+2EMH/SbX8MO2huAbphCZS2XqmvoVQu1Tv4Sj\nzjQJ2tzomUJyiVmrLEVZpciEshZhHSJ7MWprrNO9TCkQEGQ0ckhO61NlECXhnq2ojbsZJAhPYuIo\njZujb+RWOZLFKEVdnhAGtFTSILzzcmY9Gldt4SzBi/3COgRuXi2s1gO74EUXGlnigbM8YilSFpc3\nIP4zH5+PhAY3x8L2NDFNLovCDGvCLJWIkCVSUawa0cBCpep9av399eUSt9qzmdRcsmIIGUey5xix\nZhRppA5GcIiIZ+2oNZqE3rBb9wL4XsJ/jvVNj/8p95K/XrVYsC7N+9DMaPfNEKDVvVygHSDhWmRX\n/DlpL4iBxQ8bNpWHDDLDi7poHWIiHtEbXGGJWcKoHt7cJYHS/TjR3HSZPqGHiU/xHAnWiCGxFO0e\nEN+glE5tjGaMQ+6yqkKT4Dky99dz8OvCDIbshaJnCTkKPqdIBM/NwcAKapmqHjyKOe2n1cIyTTRJ\nEDNyz2eUyHoUWgtUE4oM5OCB0LtZOB0jU4UY44MOPbbSG7NEk4wJDOm+4TUkDg+FuTbFdPa4gH4e\nWJ1Zin+2OXqeHDk4SEAL5BVWFk6SkcbRiW915u44MQ6ZoEZIgZi90WtNOVklR8EGIw+JFNTjGIJv\nl6LU/v45C/I4eZM2rECasjs0TBc2YyRG4TgtHDuxzUmiA995ObMdheOxsV5FXlzN5CHzaj+xXQ0M\ntnA1uUdRFMZVJHe5jRAQrWzyyPNTz7672Teenq64ORZMq9+Yq9E0I0ykmCi4B6e2QqY5YydGqt0T\nVSNjUKbanH7ZfHubREjJs/w2OVCaSxE9YsDJk9I3MK0sWEiEPBKDctKbZMXlNZ7N5wOXe1r3vric\nybOf4J5+acD98VGDy3SrqodC0ul3IfRhjD9SoEvMA9YaTX0ok0QIMROiYRbQ4M3amHzglt0RSGuK\n1gMWkv9wbSRAQmLuQJuk8x/yNf5DH59qLRK6vO317MGhOcLr2ZjVCW9nYpzmxKQdAiTSMezu1TlJ\ncK2BgwXORqeuzdXR5Bvg8SAgwvtTA/NN8aKJQ/Etw2LedF8X5fWxoLg0C/FAhELgB07gqgYPeiZy\nEuEiwpt74YdOA+9M4oS06EqEM63sNXAxBHZkVsHIubFrvsVKKXLXgVf75pCXuyKsgmOwP5grLyYv\nyp/lxtURRjzwtFpD88ihKp/dKKdDJgfhWCrv7QrP14FXmjhPxvNReGsOLE35ga2wjXASlYvgURmb\n7MTYfVXOo+czbSMMUnnrEAhR+NqqcGuB7+y8Jnq69ibq+tiYFgOBQ/Fm8v98W/n8CXxzJ3zpBP6v\nd41n68CvvFK+dAZvi/Jb18YqKa9r4GtbVy7dzpEZAauMq4F//LERm/Kr18rXHmfeuWsszT2MxwWm\nGlmHwnkO3BX35YRWsaBcF9gmH1BZvwRPui9oCH5tHAoQhGcivHM0zjv573qB0+S5jy8nB+iAcFgK\ne4lsx4wE46LDPuZupVBrYMrUAskvN66PtfuQPGqnWZfcmksVKzDgstqpGSV1eIyq+9z9FofhzVFH\nSLEv6vWWusT0NAWX8iGsg4fyPs/uzwo4tfmmOIY9JOleXt9ipZT8PM+g4Y8x9AF4F/jG7/mzbwD/\nfP//L/D3+jl/52TnGfC3PvKcZx/9C8SF8pf83dOgv+Pxv7/5Pjm+9KDHflP4kYtzfuLJJQDRXNdZ\n1clQtU/sU4xIN+5b7Z4dYGn+35gaRTyDJ5ofOEHw7YI2EhETRZtTw8acPJW+azOb/xIdv6yEIAwx\nefJ8z4UiwNzaw5ZqSMm3Ozg+fMiGFuWweHMG3Xhr5qnyLZFipOaGaSVJQsS1//R05llcj75vhYZv\n4XSppBRozahlcVR4CsTBtbFPNxFr3gzExahE30JEeH1cONZCCLFvX4yzMXJQ7/rXa9/woD59us7G\nSRggNAKRu7nSFE7HgfVGqArEwOk6sQwzZQo82viW7jIaOsPqPCPVqYVPH68pxyM3dcX54OnnpEKs\nicuNcXVw+EXVRkiBV7vCJkTOxoG7uXKyEuYirAf3LzR1E6Eo7vXpM3rPLXAaDXJ/twz92oQ1xr41\nEEWr9A2T+ORXAXHPQZAAIdOK4pI43xYJHkDbcLMi+OFWe2Pnrb4XQtE6mUa9IfRixxv3Zg1J0l+Z\nI8RTkA6mALNOz+u5Uq1voCSK+zHwzVfDOtDEZVQG1NqQFPpNvXtOTPj1Vzf8xs1tb5r8MJzbJ57q\nfGrnyC98sCPL7uE9NzN+7GTkxy/P+mfoAIfSpahq7k+JybXbqjD1MwRttAoWEqL3229Bu5keHINf\nVBidiUpp5lEH44r15gSk0WpD8eZtUQeNSHAi5VJ9m6EKSYSyFIYUORYlj46xnVpmiMaQhbkU7g6F\nUSqNSMoJ0UZrlRojMQgbq33A4+ddC5mmFVWXlQYRpuPsGW7Div3kRLylGfNu70V2SozREbenW5cX\nlqbcWQW8oVyPkdc3E3dTZUx+hgjK2SajzcNgt5sVy1xRa1xV4eTgweGCkSVwt6sUy1ysE5cnvt1c\nauP0JHA2JI5FuTwbXI564lud09PsTUpa8dXHwvWxsj80ttuRw6Ss8LPy8mzg1Z4+dPMm9Huvj2zH\nxHq7gWPldA13i/WtPrRaWarLVFXuzeeVLIlpnhlyxIh9q+vfXxEI0XNZUnBTd+6UNOmkOglOLQ1B\nII6+hWyTX1vmA7Gptr7h7MNBUe6ZQ/7mCq3OnlVi2UELwbOW1NOyQStDzwcL4kHtKfr71o8jp8ZK\nRGJ8kPOGGLsc2F+3Nr9PeeZPQjHmZSLH4B6ocYtpQc3427vCb+6P/T0BzDh+4iX1p1uL/LXXt+gH\n8uD/MjO+vFnx9UenAKyDcj0br2flfOj+lBHORycvvq7Cvk/HVZ1uOcbAoRqTuHfoJLTuHxFOE1xX\nY7v2z+rYjLkaT9eZx6uBlTgyelJvGKS5j3cIwrO18cHiRffU/YXvHRuPB+H9Wfjcxr1BTvhT98dM\nhW9ctW7uDzwehYhyqMo6GY+jI7ajwFkUMpBzAm2UpnygMEb41m1jvzHOxoH9fuHR6HS1m2lmVrjM\ngbNBkBD4qXOnON5VYZgqd+ay5MuV8MsfKN+8Uc7HwKyQaPypS+Gt2lhU+MHzyLtHr//en4VfXyV+\ncOP3zVUwfvnK2Gvka2eBZ2cud8+L8aVT4+lGeD0JX3/sW5k/fWFMqnzxmdMj1ynwY18RDvvGt3fK\nl84CLw4+wlgL/Ngj4deujKjKTgObLPy1typfOhV+7CLxmzvhR8+Mdw/G59fCi8njTt6fPBT+JLj/\nJ1rjIsH39o0nq4Ca348rnsk5ivE4K7+zc2DQfGxc5F6/WGBNQ5N/T4cgpLTmbq5YXVin6O9bgLvZ\npZzbPs84kcZt/VCRoipoKTwahV1zsEuKgU0UpmrMzZg6oMYHgD5EvBjg0L2wReGuOA5/EwNBYUJY\nJa+fFhVWEZZqD7CzvUYqxvWxsE7GOgVSXiFa2TX41n7iO8fJaX19k7/oJz9IPs7j4zZMvwh89ff8\n2VeB7wKY2bdF5AVOnPk1eDBa/jTwX/Xn/9/AhYj85Ee0w38eP9z++vf74f/kF57zmfWml3juMQo4\n8Wtprmtozb0gqo4+DMmnhH4/8U2JWW+XVX2SLz7R9xWiG3nzvVGNHpplgWYNC9C6qfXYpIufrAug\npJvwhd28OK61m+DEfJpatafTl8WBFE05RGFuTuHL2ceBah7aiJqTj6JBaAzNPzaXoCuEQA69hA5+\nwY8dKbuUBiilqhuJRSD4xV4XJYpxKL5BGMQL8BiEqSptBjE3Zq57ho8GYTIh4n//XByqMGYgKll8\no7RKmarGNiXHbJZKUeNslbipjauDMiKkIfDqqrCiklLiEGC5a7xxuqIclRIqRQY2yXg1F55vB+ox\nMa5d5++FvuPbyzyzFseZL2pshsihVBTjsOBo9OBT74ZRW30Iao3BN2lq91AK9wfFEKjVWKK3GxL8\nMBJzn4/WxhS96JTguPVsjuU0E1S8iI7W84wkICofbuqS56nck5CIvtEaEA+vxRv+ghcyuWf61GaY\ntYftY4yRYPZA0nNrnLd8JjyEJIr4pjNmc1qfGtW8eDNH/3kwbSfhCPATF+f8qUdnvurvU8237/b8\n5d/+zt/bifH7Pz61c+SferLls0PsieNulKYj8t0TFKm1EO3DfC01wZaZXWtICMTkQIick3+/m+Pc\nrS7ua5IM0iWYmrovzTdQaJ82lyO1+RChKhiVIv3VhwgG81xZD76RkW6WjjnRWiO0xm7vUszWnI65\n5MwwrNisAmYZml8jZs09nB1msuAddq1K1AmJYzfmG7EPV8K4BoGyTERt1Nk3byoe11CbUUojBuUw\nfThgEjOSNKZFuW0BJHGSlDQmWm1EIq0JIpkonpG0qLFJLhlMUaghsB4iSylsTjLzXNktRq7G5enA\ncTGubmeG5ECHN18dCaLknMkIN7vCs0drdtNMCglVONskdvvK4/PMy51xvvIbP2YsLbo0sVY2K2/m\npDgAYzc1xOBYnEqZh4hE3wSU5ciQBt8mheKNhwlaPWBxLg4Kmavi2YH+/Rlj7BJw41C7zDJmJDjV\nMEftoeorDFcgqNGJU7gMWPzsGodIbUqKXWqaB0x9+412fxKKBm/iQhwR8DDi1kghMNfEKkVMHDQh\n4tLw0pycGgmglXsQ+K56MXxPSZrmhZwCwTxgnYchjZNif/R05Me22XOr1Bu+t48T/8OL27+vw6M/\nPtVa5B95dMqTIXsBJcLU/L5xnpSXs3Enkf1SO3Lb3yrRwMtS2RVlFYSL0bcMw+DRJkttTkxcmgeV\n4n6Ni0G4q/GBzjoIHDtU6rAsRIOr4jhphzv5OC13j/ev7ZUvnngQqJohapwMkdtilNr45pXLOKeq\n3B7hvSHy7CTzma1bEeZeZzRVLrKfV0c1TvBBw/Uc2M8Fi8ZZcn/3eYZdNT6zcVrv1VRQVd7cG2+c\nuA86ifCiwNUEJ6nxu3de0F8M3ryvY+PFAXbVLQmP1/C5dfBMIhFe18AgQojwztFhGG+sBYnCRTZW\nCI9XMBXljXN4dyrcHCFW48sX8Ot7+NXX7jk6TfBX31TOk3KShSKRF6+Vf+IzgZeHxrbnBT3bBr55\nJ/zEI/ita+FybX42oFyXwEkyXs/GF7e+AbutypdPAr9z52Hy3z0GYoycjUKOLh+8nhbKkLieYZua\n47wVds14NAivZ3vYNkURzrN7OccOOrurcH1o7JKwyZ7X17RxnmC1EhqZZn5NRDO2ObCKQq1ePy8K\nT1cOWjgVb8BstWJqxpPkWY+KsRalxgAiPOoUiZvJG/WTLLycI+ejyxurKqsAqxS4XmAdQKPX6UuD\nLMb3DuLXiflu/tW+8mgQH0w2oeDBtXuL5Ag/vl3xo9sRCZ3OGYXvHmb+t1dXf/AX9f/nx8dtmP4S\n8Isi8m/jpsmfxjMO/tWPPOc/A/4dEflt4DvAvw+8RTdQmtlvishfAf5bEflZ3L/1XwD/0+9Hpfno\nQ6tn0kjXWgfzL+ekjSS+BUJ6yjwBCa6dDEHInQjUMDIe2iZmBAkPnhNFiXnABVOuWaqmIC6XGmMm\nmn9Zi3qDlrv0IQUHHtRG17MLKfpUf0h+UwvSc4+aF7UxQpPwkXBQz8q518BLN/tj4thp68W5QIhO\nIolmzOYMpGZ+qDldyauvIfbsqepYVycnCbX/jHGItAZmnhc1Fd+QNZSqjsBeJUEIfZoQEFGm1jAi\nT7aBZVJCzERR3t/NqAgDrlNNEhgHY6qJZhWxgITGUgOzVC42kcF8Cn/e8yde31ZaguWo3NbGxWqk\nlMDVvvD27cxmEAYZEWm8WgpjjmQL7GsnRxkkNZq5D80UAs77T24FI6XIJgulwKK1b35giJFSlDEG\njp1sVc31+KvgZsVWYUgg4sVwtE4nM5DgWwsJoNW3TPfymCb3Uj+fOBcFRN0rJcp9lGhrXhg5WQly\nv74EX12P0SV+ht8AW6f+xegZQWrq1LvujdCHJT/k0aleXa+KNENd3fqhbCu4pzsEwSJoi0g1yD5J\nlT4e+ASPT+0cKVVZkjhu3vqmzRrHxf1IsTu7SBmsJ4obSBwYB/eZaWvk6AnthiEpo82ocSSEzJgH\nMN8GqDaWqh7eaTCOQycROrZVxMjJf0aKwbcXPTw2pEzMCVFjDD4dTjF0X2UmcB9U68W4EallojXf\nUkVfat135Ej1M0RFEPHps4UNqoWleFxC1eRUtXoghUCT5NlrIbgkxBpD9GtR+3mwXg19K+E3uMPs\nEmM1mEolY6xypGCILoToOvxpcUrXG+eZ/eQDrhiEl1cHVJ3GuRRv9i7Wjtiml+0mgd1iaCs83g4g\nSrXAEFxi+sHtQhK4s8r+qJyeJJYqfHBXeOvlke0grNYeCLzf3TEkJ4UdD9XPXVVq8PBRH2AJMfqG\nJvY4gDys2Q7KXNOHn7HcQ4ncl7afK5txRE08jymFLtVT1mMg5+Eh1qL16AEzf2/NCrVqD5ulN3eO\neFdzX1Pr+VEEz4jz0sMlM1H8nmDmEqTUvQVVA8OQwZIX8q3SmmIh9nBsHyTkHqybApjFvsYubFJ4\n8GqBD+miCSkJqtBacWqpuYR+TP8fde/SK1l23fn91tp7nxMR95WZlVnFepAmRerBfkrtluGGDcNu\nwxMDHvkz2DDgL+GhJ/4GdsPwsNtjwyMbfqFhy1JLLVFNd4sUqSpWVVZVvu69EXHO2Xuv5cHaN9Vo\nwAOBcgkVQKEGTFbGvXFi7/X4/3//zNlC3jeNe/jhrPslXn+ltcjt6jzS8PB2J2RF7nx8FK4nQIxF\noIzN6oyxurDLiSc74WyR+XZd4NXaAGeXM8cR0KmiXM4FdyMRapBXNbyD7s77F5lDD9/yywpJjMcl\nFAbXRXi5CXc1/LaXU+bRDCThvcl4sQkXRZAKJokL4DoHqGDSyKs8LRv3NTw7F5nYimuMhl9WY59D\nzl00thlvbM/BK8/PIVU8ttgE3W+VfQ5o1LszZFU+PQl45+kEFwJfWeTIfXiZuKuOCTzbwSdH2BVh\nsZA7zgrf2sfGTbxxUyK65NMT7NT4d94TXi7OvsE+C//jp53VnHey83xxLrLwq4+UF4tTEZI4OxG+\nOMOrCv/608g7OnelZGcS+L2vwku8AT+6je3Ti1X4yWvnv/up8WuXzruXBUz4/ZeVD/ZwPUWDpGKs\npuzVOW7O5tGc7LJz9sZlVrorT/aF714Yr1YJuEQOxP+z7Hy1Os+K8dN7472LibNHo3UzRy1yrs77\nB5jKDD3CaZdR/wmxAU7eeVPhsoS/qVlkI11NytGEKTuvqg9JdjzLSKgrzg1mdU4WsspLda6DzcOL\nlnj/AKtFY74041jjs9yPGqVaPI93LbxWm0VNI9741g6OJm+90mbOYsIuB4X02Ixji0iDiywcinKu\nsWSYx/Jhkl+6FvkLvf5CWHEAEfkPgf8S+AGRbfBfufs/+Ff+zH8B/KdEWNz/Bvzn/0pY3CMiLO4/\nIs7d/54Iizv9f/ydfwf43f/s17/P491E/HqHVntMisGhRyEQGNmQwZkNGpqPL5oEfaj3mLqbdtyV\nIjkgCR6IVxuTsNaNfYmLozOCQ9FxePDWbyJDxicqEZiKcnbDelw8zQIZKzAQm2FG9B5NiUiAByZ1\nFk+IWxRnhGmvZcMbZA8TbnePXCiiKXmLF3BIwcTGCfRrG36YKaVASLrSxVi3HvS1hwZQnP0IKuzi\nb8EFO82sA3ZRHlrL5EiPdXHPMbmYDO5bjcDZBDOJ3RTV+Lo1ujQuUkwheoM33TnkRBNnLtGIfHXa\nuBibFE3KprCsla2Fv+jpVHhZGzvNw/cVh8NpbKToHu/PQ4g7q7C1CG+VsT1R1fBBuTOnhKqjnmgy\nCpY6nhmNTBd3JalDj5DbeWyCHih1gpNTRhFScrbqhBNomB41tlJ7DTkcHmjykkZx4wTu1xW3mC5n\nVQyhuNDEA9RgcZlAdIFJoVv44Uxs6JKj2BnWPTRrkCHN3xbtfTwXKcUmtY/GYbWQWFgsXcgyZGuE\nwdw9SJOfLkf+m3/+M/glUJ5f9znyFiv+7Uc8TRqesb6ClrcbI8aG0fLELg0ICD0kbR5Fuqq+zaip\nQws59TOVFCCa3iOsOsdUr2Sl1cZhigO+j38MjfgB4ks7QGNM0lHNUU9q5rQ1pDfmElNoq+doVqSM\nXKM88PIRVqoYWY0me2rvJKvxPkp4Eqx3NmK7Ya1R5jkCjVMKHDXGZiGbwFpsQwm/DS6sEVoAACAA\nSURBVMB+ykzq4/sjrOv5bRC3DOjObkpvzx5NsbGai7wdxswDbNTtoZH0t88hdO5OW0BxUkgZS4kh\nTx2m+cOsXB6iSembsZ8za4sGpHfn+euV3RTmZh3v67R1zlsHcd672fHlvbGbMvvsmCdSUl6eO7Kd\n43bpK1UmFGMuhdsWBX7xoAumPNElIwglxV2BhoQti7PUQPdmjbvjYYiBx/uYiwaYodYYXAgjGiOa\n294dVKi1YvYQGq3kIohZPI8uQCDwzYfPZWDAS04BJHFBc8jOVSVgEg6mGbcaslMjwCTmeO9v75eH\nUiQ+M48GVxNqnTaieEtOI1MqCrOlh88pNknjLhrfrdYqJkGl/OJ85B98foRv0Bky/vzfAX73P/no\nCT1ucbwFtr/k/BYgda7GnAv7KSTThZCBPWR4XeYYfEFIl7rD1iuO8mRWvlyMtTmP5sTS4XoKtPJ3\nL+DY4p/zyLe4yiHZ2syHRFPYq7HLUaxPSfnkGGTbZzvldYXztoUsnMTTXcjAu0FO0azN4jzKxhe+\nx1qjW0jf3t0pliRojTh3Fe5r59k+c+5RlK8WqpylBZIaizrD3Hm1RY3y4UWEuXYXTq58fowIhasM\ntxZ383cuAra0evhhbjfhg73x+RkOCW6mKObXFgPKtQtdhezGjRp/+No4mfKoOB/uhWdzDA5ebMJ9\ndb5/6fzgCs7V+dmSeO8Ay+Y82wtrd/6nz+C7F3FvTiqcUf703vn8HLlx/8EHyu+8EJ7tlKc757Yn\nLrLw49fO67XGsL5XFs8UMd4/JD45jagDicylizmzepgD3p2iEc2iHO0hyLuBJKYsHAdV7pABN35x\nMt7bCavBqyWUUbOGH25SYafGy03YJeF+a7ysGrWFKO/PsSU3h/uuXEpDUua+h/T31KKmvZmVmyI0\nj23Qqcdn9KbG4NklAuAPCRZzHpXYth67j7yoqClUwmd2VZxPzs6sSjVj8bh3Hs3CdYalx3fls1W5\nmhLnEdNzlXzAsCI/1CQxifHifOYfffnmlzpH/iKvv3DD9FfxepvD9Bs/4IOLfRT3o7hDGNk6NrZF\nPYpPGeO+nJAesruHXB08SFdC6Ie7xXTfNS4jH+ZM17hcnBjSdo+VqEqCgYHu3cYULsWGKikZGdIX\niY2CxUoziWP9QXcTWwZxMDG8R4GuEBdla0HxI35WUnhfCim2PBqa4q3HQZxUqb1TNDwsJTmrEwfo\n0MBnJS5EhOsp6Di9NlQV1EPikVOAMXrDzbnIMT04tWg4ujkXU8gh3ZRJMnORoAcO86iUyG7BFMFY\nTdiPjdqxG2zG9SFzeRDOq7GNQ/R2bTw6zOAhJztJRzfQorG58/F7dMi5cG+N3p2LnbJusM9G8ok3\ntbIn5GhLM4RCl5jS37cenyNDdvbn93k8LgjuUSAjMel52P2IyGhO+9gCJlL06VFsEM0T4mHattAK\nqwRMoEk0Zg8etZhIP0xYfExsZRToTiaBhoTChmw0a2yRmtnQz3cEpaRCJbxRDxQrkZG+ZNEoVg9v\nmXsQelQU8VhvPsDDzQc2vEVD50hg8rvjGr6Fz04L/yAkeV/LIfWX8Xo7dPnuu7w3T1G8je+FqgTx\nrY3CtzdaW8cMJpHzPD6POFsehiWaC0Lg4r0tdJ2YVVktpG9JnDBh95jkSwBkUhoBn8SfOTent4aU\niWSNUua355WOSX43wGKDuvnYoDMM+gKpr1RPqIZfU/OOuh5BA9DQUErZgzfQIPeRJtQrtXmgs1VY\nauOgHfJEEmPr0ZCv3cZWymltQ0jsDxPNE8u6khSKhsxjnhJChNK2VjnMimvhtHbco8Dc7xKFGLjk\nrFxMiaVZYGmJYFMZm9Fundp8gGuEZW2cW+fRZeHRoXBaOscthl3Hc+fxVaETGSTSYRlZI2uP72Lv\nHdPEYY6MODPnclcChZ4aqom7BbI2mjlLF9AJd7jKjdtzBGAzhgt5HCJ9AA26G9mN3isqig16XtIw\nM+ckWAu/hpZdHO9jGGceOF4FJM+ItQfIKzrSlCzNiFXQgGmoZPrwSdqQB9NWerex0YpJr3oLP4JG\n89+H6gEL7L3Me4RoaLYe2/E0VA6bjSvInK4FaUtsigbYQSDOO0lYD7l5MyNrgJg2S/Ed8oZb46va\n+W+fn+AbdIbAv9Qwffdd3p0n3mwdt5AcJY2G4XUNgMmpW0jVPOTY01RiECvR+F/kaCI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B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\nwAMmx3Ecx3Ecx3GcHfgfnCgagBreL0gAAAAASUVORK5CYII=\n",
- "text/plain": [
- "<matplotlib.figure.Figure at 0x7fd39a453890>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "#%% plot images\n",
- "\n",
- "\n",
- "pl.figure(2,(10,8))\n",
- "\n",
- "pl.subplot(2,3,1)\n",
- "\n",
- "pl.imshow(I1)\n",
- "pl.title('Im. 1')\n",
- "\n",
- "pl.subplot(2,3,2)\n",
- "\n",
- "pl.imshow(I2)\n",
- "pl.title('Im. 2')\n",
- "\n",
- "\n",
- "pl.subplot(2,3,3)\n",
- "pl.imshow(I1t)\n",
- "pl.title('Im. 1 Interp LP')\n",
- "\n",
- "pl.subplot(2,3,4)\n",
- "pl.imshow(I1te)\n",
- "pl.title('Im. 1 Interp Entrop')\n",
- "\n",
- "\n",
- "pl.subplot(2,3,5)\n",
- "pl.imshow(I1tl)\n",
- "pl.title('Im. 1 Linear mapping')\n",
- "\n",
- "pl.subplot(2,3,6)\n",
- "pl.imshow(I1tn)\n",
- "pl.title('Im. 1 nonlinear mapping')\n",
- "\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 2",
- "language": "python",
- "name": "python2"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 2
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython2",
- "version": "2.7.12"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 1
-}
diff --git a/notebooks/Demo_Optim_OTreg.ipynb b/notebooks/Demo_Optim_OTreg.ipynb
deleted file mode 100644
index 5731687..0000000
--- a/notebooks/Demo_Optim_OTreg.ipynb
+++ /dev/null
@@ -1,173 +0,0 @@
-{
- "metadata": {
- "name": "",
- "signature": "sha256:4dc159882a3ef225eae256eb2ae57de153d04cc9de52ea36b1644e64a88de96a"
- },
- "nbformat": 3,
- "nbformat_minor": 0,
- "worksheets": [
- {
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Regularized OT with generic solver"
- ]
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "import numpy as np\n",
- "import matplotlib.pylab as pl\n",
- "import ot"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [],
- "prompt_number": 1
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Dataset generation"
- ]
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "n=100 # nb bins\n",
- "\n",
- "# bin positions\n",
- "x=np.arange(n,dtype=np.float64)\n",
- "\n",
- "# Gaussian distributions\n",
- "a=ot.datasets.get_1D_gauss(n,m=20,s=20) # m= mean, s= std\n",
- "b=ot.datasets.get_1D_gauss(n,m=60,s=60)\n",
- "\n",
- "# loss matrix\n",
- "M=ot.dist(x.reshape((n,1)),x.reshape((n,1)))\n",
- "M/=M.max()"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [],
- "prompt_number": 2
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### EMD solution"
- ]
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "G0=ot.emd(a,b,M)\n",
- "\n",
- "pl.figure(3)\n",
- "ot.plot.plot1D_mat(a,b,G0,'OT matrix G0')"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "display_data",
- "png": 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- "text": [
- "<matplotlib.figure.Figure at 0x7fec64763710>"
- ]
- }
- ],
- "prompt_number": 3
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Solution with Frobenius norm regularization"
- ]
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "def f(G): return 0.5*np.sum(G**2)\n",
- "def df(G): return G\n",
- "\n",
- "reg=1e-1\n",
- " \n",
- "Gl2=ot.optim.cg(a,b,M,reg,f,df)\n",
- "\n",
- "pl.figure(3)\n",
- "ot.plot.plot1D_mat(a,b,Gl2,'OT matrix Frob. reg')"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "display_data",
- "png": 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- "text": [
- "<matplotlib.figure.Figure at 0x7fec61ed1790>"
- ]
- }
- ],
- "prompt_number": 4
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Solution with entropic regularization"
- ]
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "def f(G): return np.sum(G*np.log(G))\n",
- "def df(G): return np.log(G)+1\n",
- " \n",
- "reg=1e-3\n",
- " \n",
- "Ge=ot.optim.cg(a,b,M,reg,f,df)\n",
- "\n",
- "pl.figure(4)\n",
- "ot.plot.plot1D_mat(a,b,Ge,'OT matrix Entrop. reg')"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "display_data",
- "png": 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- "text": [
- "<matplotlib.figure.Figure at 0x7fec61ba0550>"
- ]
- }
- ],
- "prompt_number": 5
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [],
- "language": "python",
- "metadata": {},
- "outputs": [],
- "prompt_number": 5
- }
- ],
- "metadata": {}
- }
- ]
-} \ No newline at end of file
diff --git a/notebooks/Demo_Wasserstein_Discriminant_Analysis.ipynb b/notebooks/Demo_Wasserstein_Discriminant_Analysis.ipynb
deleted file mode 100644
index 2d3424e..0000000
--- a/notebooks/Demo_Wasserstein_Discriminant_Analysis.ipynb
+++ /dev/null
@@ -1,257 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Demonstration of Wasserstein Discriminant Analysis"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "import numpy as np\n",
- "import matplotlib.pylab as pl\n",
- "import ot\n",
- "from ot.datasets import get_1D_gauss as gauss\n",
- "from ot.dr import wda, fda"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Generate dataset"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "n=1000 # nb samples in source and target datasets\n",
- "nz=0.2\n",
- "\n",
- "# generate circle dataset\n",
- "t=np.random.rand(n)*2*np.pi\n",
- "ys=np.floor((np.arange(n)*1.0/n*3))+1\n",
- "xs=np.concatenate((np.cos(t).reshape((-1,1)),np.sin(t).reshape((-1,1))),1)\n",
- "xs=xs*ys.reshape(-1,1)+nz*np.random.randn(n,2)\n",
- "\n",
- "t=np.random.rand(n)*2*np.pi\n",
- "yt=np.floor((np.arange(n)*1.0/n*3))+1\n",
- "xt=np.concatenate((np.cos(t).reshape((-1,1)),np.sin(t).reshape((-1,1))),1)\n",
- "xt=xt*yt.reshape(-1,1)+nz*np.random.randn(n,2)\n",
- "\n",
- "nbnoise=8\n",
- "\n",
- "xs=np.hstack((xs,np.random.randn(n,nbnoise)))\n",
- "xt=np.hstack((xt,np.random.randn(n,nbnoise)))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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5xeANtikAcsGvUwnD+38aP71OJsmF72awEYSl6uPA54FXhBD7zPf+RUr5qwCO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\nXQBmO9wcw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- "text/plain": [
- "<matplotlib.figure.Figure at 0x7fc5186f0a10>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "pl.figure(1,(10,5))\n",
- "\n",
- "pl.subplot(1,2,1)\n",
- "pl.scatter(xt[:,0],xt[:,1],c=ys,marker='+',label='Source samples')\n",
- "pl.legend(loc=0)\n",
- "pl.title('Discriminant dimensions')\n",
- "\n",
- "pl.subplot(1,2,2)\n",
- "pl.scatter(xt[:,2],xt[:,3],c=ys,marker='+',label='Source samples')\n",
- "pl.legend(loc=0)\n",
- "pl.title('Other dimensions')\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Compute Fisher discriminant"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "p=2\n",
- "\n",
- "Pfda,projfda = fda(xs,ys,p)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Compute WDA"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Compiling cost function...\n",
- "Computing gradient of cost function...\n",
- " iter\t\t cost val\t grad. norm\n",
- " 1\t+7.3324064745743989e-01\t5.95226695e-01\n",
- " 2\t+4.4853951178403229e-01\t8.20231271e-02\n",
- " 3\t+4.4576445851595303e-01\t1.93811424e-01\n",
- " 4\t+4.3562246733680465e-01\t1.61725387e-01\n",
- " 5\t+4.0969564472790077e-01\t1.32513662e-01\n",
- " 6\t+2.9388094458668662e-01\t2.00393708e-01\n",
- " 7\t+2.7344485803563923e-01\t1.99320846e-01\n",
- " 8\t+2.2883182995370804e-01\t2.82035999e-02\n",
- " 9\t+2.2828598049696755e-01\t7.08646563e-03\n",
- " 10\t+2.2825222787200100e-01\t3.22559822e-04\n",
- " 11\t+2.2825220998825529e-01\t2.82197677e-04\n",
- " 12\t+2.2825216255973643e-01\t9.26049149e-05\n",
- " 13\t+2.2825215676825239e-01\t6.60508771e-06\n",
- " 14\t+2.2825215674473881e-01\t3.35243645e-06\n",
- " 15\t+2.2825215673980734e-01\t1.97305673e-06\n",
- " 16\t+2.2825215673953242e-01\t1.86785394e-06\n",
- " 17\t+2.2825215673856641e-01\t1.41420230e-06\n",
- " 18\t+2.2825215673757782e-01\t6.92577574e-07\n",
- "Terminated - min grad norm reached after 18 iterations, 8.84 seconds.\n",
- "\n"
- ]
- }
- ],
- "source": [
- "p=2\n",
- "reg=1\n",
- "k=10\n",
- "maxiter=100\n",
- "\n",
- "Pwda,projwda = wda(xs,ys,p,reg,k,maxiter=maxiter)\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Project and plot samples"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
- {
- "data": {
- "image/png": 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rT8RMpNEeqBfqlQfqL4dmcdckmF6qsvbunrwRgIrJu4Cwh6onyoS9ZGl5qPIL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\noqvBpVvJL4XokU6vU2wrT6A/XFuEw60L0VNuEJfc/W4/LH1hVNrIZM4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42RCsjRfduqrXD0dCe0pBXubRATPdWQ463F7iXLYLKQmV6sCpVEjENnox2DFRdgvOSH84GvQCf0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\n7Oe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- "text/plain": [
- "<matplotlib.figure.Figure at 0x7fc5186f0690>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "# data projection (also removes center)\n",
- "xsp=projfda(xs)\n",
- "xtp=projfda(xt)\n",
- "\n",
- "xspw=projwda(xs)\n",
- "xtpw=projwda(xt)\n",
- "\n",
- "pl.figure(1,(10,10))\n",
- "\n",
- "pl.subplot(2,2,1)\n",
- "pl.scatter(xsp[:,0],xsp[:,1],c=ys,marker='+',label='Projected samples')\n",
- "pl.legend(loc=0)\n",
- "pl.title('Projected training samples FDA')\n",
- "\n",
- "\n",
- "pl.subplot(2,2,2)\n",
- "pl.scatter(xtp[:,0],xtp[:,1],c=ys,marker='+',label='Projected samples')\n",
- "pl.legend(loc=0)\n",
- "pl.title('Projected test samples FDA')\n",
- "\n",
- "\n",
- "pl.subplot(2,2,3)\n",
- "pl.scatter(xspw[:,0],xspw[:,1],c=ys,marker='+',label='Projected samples')\n",
- "pl.legend(loc=0)\n",
- "pl.title('Projected training samples WDA')\n",
- "\n",
- "\n",
- "pl.subplot(2,2,4)\n",
- "pl.scatter(xtpw[:,0],xtpw[:,1],c=ys,marker='+',label='Projected samples')\n",
- "pl.legend(loc=0)\n",
- "pl.title('Projected test samples WDA')\n",
- "pl.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 2",
- "language": "python",
- "name": "python2"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 2
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython2",
- "version": "2.7.12"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/plot_OT_1D.ipynb b/notebooks/plot_OT_1D.ipynb
new file mode 100644
index 0000000..c4b2e67
--- /dev/null
+++ b/notebooks/plot_OT_1D.ipynb
@@ -0,0 +1,247 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# 1D optimal transport\n",
+ "\n",
+ "\n",
+ "This example illustrates the computation of EMD and Sinkhorn transport plans\n",
+ "and their visualization.\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Author: Remi Flamary <remi.flamary@unice.fr>\n",
+ "#\n",
+ "# License: MIT License\n",
+ "\n",
+ "import numpy as np\n",
+ "import matplotlib.pylab as pl\n",
+ "import ot\n",
+ "from ot.datasets import get_1D_gauss as gauss"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Generate data\n",
+ "-------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "#%% parameters\n",
+ "\n",
+ "n = 100 # nb bins\n",
+ "\n",
+ "# bin positions\n",
+ "x = np.arange(n, dtype=np.float64)\n",
+ "\n",
+ "# Gaussian distributions\n",
+ "a = gauss(n, m=20, s=5) # m= mean, s= std\n",
+ "b = gauss(n, m=60, s=10)\n",
+ "\n",
+ "# loss matrix\n",
+ "M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)))\n",
+ "M /= M.max()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plot distributions and loss matrix\n",
+ "----------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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TlpZG27ZtGT16NA8//HCx2wUaJ/w+XX1pU/OXR/VC61tU5vyNllAiyKJFeh2M2ajr19d2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\ncHFVKfBdXJU4CuLicVXicBK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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f3f95cf5f28>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f3f93c83208>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% plot the distributions\n",
+ "\n",
+ "pl.figure(1, figsize=(6.4, 3))\n",
+ "pl.plot(x, a, 'b', label='Source distribution')\n",
+ "pl.plot(x, b, 'r', label='Target distribution')\n",
+ "pl.legend()\n",
+ "\n",
+ "#%% plot distributions and loss matrix\n",
+ "\n",
+ "pl.figure(2, figsize=(5, 5))\n",
+ "ot.plot.plot1D_mat(a, b, M, 'Cost matrix M')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Solve EMD\n",
+ "---------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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yfTl0MwB7P90UqJg4PRvlTJdCbbVo4aMcjjyyYl8I8MknOy+389xzUFLixzRq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\ngSsiEhMFrohITP4PrQ161dhEqnEAAAAASUVORK5CYII=\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f3f93b3c898>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% EMD\n",
+ "\n",
+ "G0 = ot.emd(a, b, M)\n",
+ "\n",
+ "pl.figure(3, figsize=(5, 5))\n",
+ "ot.plot.plot1D_mat(a, b, G0, 'OT matrix G0')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Solve Sinkhorn\n",
+ "--------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "It. |Err \n",
+ "-------------------\n",
+ " 0|8.187970e-02|\n",
+ " 10|3.460174e-02|\n",
+ " 20|6.633335e-03|\n",
+ " 30|9.797798e-04|\n",
+ " 40|1.389606e-04|\n",
+ " 50|1.959016e-05|\n",
+ " 60|2.759079e-06|\n",
+ " 70|3.885166e-07|\n",
+ " 80|5.470605e-08|\n",
+ " 90|7.702918e-09|\n",
+ " 100|1.084609e-09|\n",
+ " 110|1.527180e-10|\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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y5Mgwe/bsWo/dcgt8//vesY4eDRde6N2spmPFy8zmhBBGApyS9y9qZ5KS+tXN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\niEhMFLgiIjH5/xjX3J71f+OyAAAAAElFTkSuQmCC\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f3f93a2b470>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% Sinkhorn\n",
+ "\n",
+ "lambd = 1e-3\n",
+ "Gs = ot.sinkhorn(a, b, M, lambd, verbose=True)\n",
+ "\n",
+ "pl.figure(4, figsize=(5, 5))\n",
+ "ot.plot.plot1D_mat(a, b, Gs, 'OT matrix Sinkhorn')\n",
+ "\n",
+ "pl.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/notebooks/plot_OT_2D_samples.ipynb b/notebooks/plot_OT_2D_samples.ipynb
new file mode 100644
index 0000000..900eaa7
--- /dev/null
+++ b/notebooks/plot_OT_2D_samples.ipynb
@@ -0,0 +1,288 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# 2D Optimal transport between empirical distributions\n",
+ "\n",
+ "\n",
+ "Illustration of 2D optimal transport between discributions that are weighted\n",
+ "sum of diracs. The OT matrix is plotted with the samples.\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Author: Remi Flamary <remi.flamary@unice.fr>\n",
+ "#\n",
+ "# License: MIT License\n",
+ "\n",
+ "import numpy as np\n",
+ "import matplotlib.pylab as pl\n",
+ "import ot"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Generate data\n",
+ "-------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "#%% parameters and data generation\n",
+ "\n",
+ "n = 50 # nb samples\n",
+ "\n",
+ "mu_s = np.array([0, 0])\n",
+ "cov_s = np.array([[1, 0], [0, 1]])\n",
+ "\n",
+ "mu_t = np.array([4, 4])\n",
+ "cov_t = np.array([[1, -.8], [-.8, 1]])\n",
+ "\n",
+ "xs = ot.datasets.get_2D_samples_gauss(n, mu_s, cov_s)\n",
+ "xt = ot.datasets.get_2D_samples_gauss(n, mu_t, cov_t)\n",
+ "\n",
+ "a, b = np.ones((n,)) / n, np.ones((n,)) / n # uniform distribution on samples\n",
+ "\n",
+ "# loss matrix\n",
+ "M = ot.dist(xs, xt)\n",
+ "M /= M.max()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plot data\n",
+ "---------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.text.Text at 0x7ff7483c3be0>"
+ ]
+ },
+ "execution_count": 4,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7ff74a486438>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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rp67z2kM0XOJrJ1Ooxxe1crW4W0Qf7uLl3KS2NJPpvXyGTfJYPMPnmxPXdLXf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\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7ff748402c88>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% plot samples\n",
+ "\n",
+ "pl.figure(1)\n",
+ "pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\n",
+ "pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\n",
+ "pl.legend(loc=0)\n",
+ "pl.title('Source and target distributions')\n",
+ "\n",
+ "pl.figure(2)\n",
+ "pl.imshow(M, interpolation='nearest')\n",
+ "pl.title('Cost matrix M')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Compute EMD\n",
+ "-----------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.text.Text at 0x7ff7482661d0>"
+ ]
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7ff74a486128>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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meOR7L8bq1bwXHh6cmbTbHY/NvzRicijg9YJt0fL//o+hSo1tygGgdPo8iHkG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7t5E0KLjUUrP38eQvrkJ32X6Hl5eLslJby+c2f7TTdaE/yjj0xNFM1mmTePcWVkQC4BAbx/yRK8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\nAKOf94eua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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7ff7482bb320>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% EMD\n",
+ "\n",
+ "G0 = ot.emd(a, b, M)\n",
+ "\n",
+ "pl.figure(3)\n",
+ "pl.imshow(G0, interpolation='nearest')\n",
+ "pl.title('OT matrix G0')\n",
+ "\n",
+ "pl.figure(4)\n",
+ "ot.plot.plot2D_samples_mat(xs, xt, G0, c=[.5, .5, 1])\n",
+ "pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\n",
+ "pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\n",
+ "pl.legend(loc=0)\n",
+ "pl.title('OT matrix with samples')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Compute Sinkhorn\n",
+ "----------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7ff778595748>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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GhtNx2Qt01tEBusaXX1LHkZVFjtjiYrLSMzKog+uuHbg81tEB0v6//546ypEj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\nr6rCNcjP1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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7ff7483e20b8>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% sinkhorn\n",
+ "\n",
+ "# reg term\n",
+ "lambd = 1e-3\n",
+ "\n",
+ "Gs = ot.sinkhorn(a, b, M, lambd)\n",
+ "\n",
+ "pl.figure(5)\n",
+ "pl.imshow(Gs, interpolation='nearest')\n",
+ "pl.title('OT matrix sinkhorn')\n",
+ "\n",
+ "pl.figure(6)\n",
+ "ot.plot.plot2D_samples_mat(xs, xt, Gs, color=[.5, .5, 1])\n",
+ "pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\n",
+ "pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\n",
+ "pl.legend(loc=0)\n",
+ "pl.title('OT matrix Sinkhorn with samples')\n",
+ "\n",
+ "pl.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/notebooks/plot_OT_L1_vs_L2.ipynb b/notebooks/plot_OT_L1_vs_L2.ipynb
new file mode 100644
index 0000000..5b49e82
--- /dev/null
+++ b/notebooks/plot_OT_L1_vs_L2.ipynb
@@ -0,0 +1,373 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# 2D Optimal transport for different metrics\n",
+ "\n",
+ "\n",
+ "2D OT on empirical distributio with different gound metric.\n",
+ "\n",
+ "Stole the figure idea from Fig. 1 and 2 in\n",
+ "https://arxiv.org/pdf/1706.07650.pdf\n",
+ "\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Author: Remi Flamary <remi.flamary@unice.fr>\n",
+ "#\n",
+ "# License: MIT License\n",
+ "\n",
+ "import numpy as np\n",
+ "import matplotlib.pylab as pl\n",
+ "import ot"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Dataset 1 : uniform sampling\n",
+ "----------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fc3b4ebfcc0>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fc3b2a339e8>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "n = 20 # nb samples\n",
+ "xs = np.zeros((n, 2))\n",
+ "xs[:, 0] = np.arange(n) + 1\n",
+ "xs[:, 1] = (np.arange(n) + 1) * -0.001 # to make it strictly convex...\n",
+ "\n",
+ "xt = np.zeros((n, 2))\n",
+ "xt[:, 1] = np.arange(n) + 1\n",
+ "\n",
+ "a, b = ot.unif(n), ot.unif(n) # uniform distribution on samples\n",
+ "\n",
+ "# loss matrix\n",
+ "M1 = ot.dist(xs, xt, metric='euclidean')\n",
+ "M1 /= M1.max()\n",
+ "\n",
+ "# loss matrix\n",
+ "M2 = ot.dist(xs, xt, metric='sqeuclidean')\n",
+ "M2 /= M2.max()\n",
+ "\n",
+ "# loss matrix\n",
+ "Mp = np.sqrt(ot.dist(xs, xt, metric='euclidean'))\n",
+ "Mp /= Mp.max()\n",
+ "\n",
+ "# Data\n",
+ "pl.figure(1, figsize=(7, 3))\n",
+ "pl.clf()\n",
+ "pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\n",
+ "pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\n",
+ "pl.axis('equal')\n",
+ "pl.title('Source and traget distributions')\n",
+ "\n",
+ "\n",
+ "# Cost matrices\n",
+ "pl.figure(2, figsize=(7, 3))\n",
+ "\n",
+ "pl.subplot(1, 3, 1)\n",
+ "pl.imshow(M1, interpolation='nearest')\n",
+ "pl.title('Euclidean cost')\n",
+ "\n",
+ "pl.subplot(1, 3, 2)\n",
+ "pl.imshow(M2, interpolation='nearest')\n",
+ "pl.title('Squared Euclidean cost')\n",
+ "\n",
+ "pl.subplot(1, 3, 3)\n",
+ "pl.imshow(Mp, interpolation='nearest')\n",
+ "pl.title('Sqrt Euclidean cost')\n",
+ "pl.tight_layout()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Dataset 1 : Plot OT Matrices\n",
+ "----------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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UCfj6awFvb5BHwc12mtFphwnnDNEI3GjCsXeUaXMreP/4I21fWfDevt12cRNr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\nRU5ErkJggg==\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fc3b28fa5c0>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% EMD\n",
+ "G1 = ot.emd(a, b, M1)\n",
+ "G2 = ot.emd(a, b, M2)\n",
+ "Gp = ot.emd(a, b, Mp)\n",
+ "\n",
+ "# OT matrices\n",
+ "pl.figure(3, figsize=(7, 3))\n",
+ "\n",
+ "pl.subplot(1, 3, 1)\n",
+ "ot.plot.plot2D_samples_mat(xs, xt, G1, c=[.5, .5, 1])\n",
+ "pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\n",
+ "pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\n",
+ "pl.axis('equal')\n",
+ "# pl.legend(loc=0)\n",
+ "pl.title('OT Euclidean')\n",
+ "\n",
+ "pl.subplot(1, 3, 2)\n",
+ "ot.plot.plot2D_samples_mat(xs, xt, G2, c=[.5, .5, 1])\n",
+ "pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\n",
+ "pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\n",
+ "pl.axis('equal')\n",
+ "# pl.legend(loc=0)\n",
+ "pl.title('OT squared Euclidean')\n",
+ "\n",
+ "pl.subplot(1, 3, 3)\n",
+ "ot.plot.plot2D_samples_mat(xs, xt, Gp, c=[.5, .5, 1])\n",
+ "pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\n",
+ "pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\n",
+ "pl.axis('equal')\n",
+ "# pl.legend(loc=0)\n",
+ "pl.title('OT sqrt Euclidean')\n",
+ "pl.tight_layout()\n",
+ "\n",
+ "pl.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Dataset 2 : Partial circle\n",
+ "--------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fc3b2a0fd30>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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5sa17ell3FjR8bjKG0yfD2Nbt2Onpujka27rMog3HgHPM7AeBRwHPlPRE4O3A\nRWZ2OnAQeFlXW3ac3uD6dEYV16bTV9bsN5mZUe+wTcc/A84BXhTTLwMuBN7TyUYb7yLj/wkwtnU7\ndno6nb2xrU/0Wp9pb6bWG58EY9tI9sTTnPIztvWj7kyp1aMTYWzrduz0ZLksjW3rWHU1JJUl3Qjc\nA3wS+AawaGbFcbgD2LPKuhdIul7S9d+5N7/3g53RZ736dG06/cbrTqefdNSAm1nFzB4F7AUeDzy8\n0w2Y2cVm9lgze+xJu7r70orjdMJ69enadPqN151OP+kq2Glmi5KuAZ4ELEiaineSe4E711OAehgo\nSRxbY1t3Hz9J07I0tg2YXuuzCEe6sW0Uwul5G9v6UXcWTIaxrcuPnyRpeRrberS4pJMkLcTpzcDT\ngZuBa4Dnx8XOBz7e3aYdZ+O4Pp1RxbXp9JtO+qsnA5dJKhMa/I+a2ZWSbgIul/QW4IvAJWtlZBgV\nqzbeMUbc2Dbmxrb+0RN9VjGO2TIzOrEXOAnGtnx64mlOI29s61nd2Snjamzrdux0yNzY1iGduNC/\nBDy6RfothGc6jjM0XJ/OqOLadPrNCDztcBzHcRynWwY6fpYBK1QaQjltw+ljZ2zr7uMn6bQb2/pL\nFeNwdbnhULULp7uxbRTC6Xkb27qh3ePHVoybsa3rj5/A+Bjb2uA9cMdxHMfJkAH3wI2jtsKsGhKB\nNXriyXJ5G9u6Gzsd3Ng2KKpmLFkVqsv1xHg4JsHYlndPPM1p5I1t66LT6GUr3Ng2vsY274E7juM4\nToZ4A+44juM4GTLQEHoVOGZV0sBELZw+Eca27t4RBze2DYoVxIHKNJSTEHoRTndjW0bh9M6MbTlS\nMQMlemrz+LEVbmxj7Ixt3gN3HMdxnAwZbA/cjENVg1Jqkgj3NZNhbOt27HRwY9tgWLEy91S20rBH\nRW98Ioxt49YTT3M60diWG2GkwBVm0gqr6I27sW1ijW3eA3ccx3GcDPEG3HEcx3EyZKAh9Apiyaag\nmgQhauH08Te29eLjJ+DGtn6wbGXuWtnelBr3yo1tmYfTW+13XhiwjIHVj1stnO7GthqTZmzzHrjj\nOI7jZMiAe+AlFquzUEputYve+AQY27ofO715foEb23rNspXZt7xjlbmTYGybhJ74ajmNPmbGUbPG\n4sfeuBvbWjMJxjbvgTuO4zhOhngD7jiO4zgZ0nGwWFIZuB6408yeI+mhwOXALuAG4CVmdrxdHhUr\nsVjZ0pjqDcKnAAAHP0lEQVRYhNMnwNjW/cdP0un8jG2DohfaPG5T3HlsoYOtjauxrbuPn6Q5pOQV\nTh8MvdBnFXHUREPFVqsT3djWjnE2tnVzaF8J3Jz8fjtwkZmdDhwEXtbLgjlOF7g2nVHG9en0hY76\nl5L2As8Gfhd4tSQB5wAviotcBlwIvKddPitW4kBla+uZbmwbO2PbIOiVNperZb59pPk1snaMm7Ft\n0l4xGwy90mcVOFydglJ6bGLF5sa2jhk3Y1unh/OdwOuon51dwKJZLXZzB7Cn1YqSLpB0vaTrHzi4\n3GoRx9kIPdHmscUj/S+pM4n0RJ8HD1RbLeJMOGs24JKeA9xjZjesZwNmdrGZPdbMHrt1x/DuhJ3x\no5fanFnY3OPSOZNOL/W5Y6f7jZ0T6SQw/GTgJySdC8wC24B3AQuSpuKd5F7gzrUyWqHMd1bm196i\nG9vSQsX/+RnbBkDPtLlcLXHXoW3rLMY4GNu6/fgJeDh9TXqmzyrikE03Rqhr4XQ3tnXLuBjb1jyM\nZvZGM9trZqcBLwCuNrMXA9cAz4+LnQ98vKclc5w1cG06o4zr0+k3G+lLvh64XNJbgC8Cl6y1woqV\n2b/cQQ+8wI1tmRvbhkbX2qxUSxw8tNEwer7GtskbO32odK9PK7FU3dx4+Iuq0I1tGyJnY1tXTZCZ\nXQtcG6dvAR6/4RI4Tg9wbTqjjOvT6QfujHAcx3GcDBnox0xWqiX2H1vlPfC1cGNbWqj4f9SNbflQ\nrZQ4sjTbwxzzMrZ1//ET8HD64KhQ4v5qkz6Lw+/Gtp6Qo7HNe+CO4ziOkyGD7YFbiXuPzW0sEze2\nZWRsy4iKYGmKI/SyFw5ubDsxh5Rh9cRzo2olliqrmCzd2NZzcjG2ZVjTOo7jOI7jDbjjOI7jZMjA\nTWwHjm5Ze8FOcWNbWqj4f5SMbfmgKkwtlVhJTlrfwulubPNwepdUKHFf86eYW+HGtp4yLGNbp3gP\n3HEcx3EyZKA98Eq1xOKRXvdqcGMbORjbRhtVYHpJNN4NhxPnxrbxM7blxoqVOLDShQF43IxtI9DV\nHKSxrVNG4LA4juM4jtMt3oA7juM4ToYMNIRerYrDh/scXh1lY1ufQukwqsa2fFAVNi1B6/c03djW\nKqdxMbblQMVKLC6v0wA8Fsa20XtHHPppbOsM74E7juM4ToYMtAdOVVQOTXN4ENtyY9vQjW05EUxs\nxlrRCje21cna2JYZoQe+wc/dZm1sG71XzKCfxrbOGIFD4DiO4zhOt3gD7jiO4zgZMvAQeulQucFe\nM9Bw+rCNbQMMpcPwjW05oQrMLFXp9HGDG9ta55SlsS0DVqzE4vENhtBTsjO25fHxE+iVsa0zvAfu\nOI7jOBkiM1t7qV5tTPoO4YZ9/8A22j8eRP770e99eIiZndTH/HtG1OZt+HkdJfq5H9loE7zuHFGG\nrs+BNuAAkq43s8cOdKN9YBz2Yxz2odeMwzEZh32A8dmPXjEux8P3o3d4CN1xHMdxMsQbcMdxHMfJ\nkGE04BcPYZv9YBz2Yxz2odeMwzEZh32A8dmPXjEux8P3o0cM/Bm44ziO4zgbx0PojuM4jpMhA23A\nJT1T0n9J+rqkNwxy2+tF0qmSrpF0k6QvS3plTN8p6ZOSvhb/7xh2WddCUlnSFyVdGX8/VNLn4/n4\niKQcPyTWE3LUJrg+J4Uc9TlO2oTR1OfAGnBJZeCPgWcBZwIvlHTmoLa/AVaA15jZmcATgV+L5X4D\ncJWZnQFcFX+POq8Ebk5+vx24yMxOBw4CLxtKqYZMxtoE1+fYk7E+x0mbMIL6HGQP/PHA183sFjM7\nDlwOnDfA7a8LM9tnZv8Wp5cIJ3APoeyXxcUuA543nBJ2hqS9wLOB98bfAs4B/jouMvL70Eey1Ca4\nPieELPU5LtqE0dXnIBvwPcDtye87Ylo2SDoNeDTweWC3me2Ls+4Cdg+pWJ3yTuB11AcV3gUsmtUG\nOc7ufPSQ7LUJrs8xJnt9Zq5NGFF9uomtQyRtBT4GvMrM7k/nWbDyj6ydX9JzgHvM7IZhl8XpD65P\nZ1TJWZsw2voc5NfI7gROTX7vjWkjj6RpggA/ZGZ/E5PvlnSyme2TdDJwz/BKuCZPBn5C0rnALLAN\neBewIGkq3kVmcz76QLbaBNfnBJCtPsdAmzDC+hxkD/w64Izo3NsEvAC4YoDbXxfxWcclwM1m9o5k\n1hXA+XH6fODjgy5bp5jZG81sr5mdRjjuV5vZi4FrgOfHxUZ6H/pMltoE1+eEkKU+x0GbMOL6NLOB\n/QHnAl8FvgH8j0FuewNlfgohxPMl4Mb4dy7hGchVwNeATwE7h13WDvfnbODKOP09wBeArwN/BcwM\nu3xDPC7ZaTOW2/U5AX856nPctBn3aaT06SOxOY7jOE6GuInNcRzHcTLEG3DHcRzHyRBvwB3HcRwn\nQ7wBdxzHcZwM8QbccRzHcTLEG3DHcRzHyRBvwB3HcRwnQ7wBdxzHcZwM+f+FjXrd9xdqlgAAAABJ\nRU5ErkJggg==\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fc3b2971358>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "n = 50 # nb samples\n",
+ "xtot = np.zeros((n + 1, 2))\n",
+ "xtot[:, 0] = np.cos(\n",
+ " (np.arange(n + 1) + 1.0) * 0.9 / (n + 2) * 2 * np.pi)\n",
+ "xtot[:, 1] = np.sin(\n",
+ " (np.arange(n + 1) + 1.0) * 0.9 / (n + 2) * 2 * np.pi)\n",
+ "\n",
+ "xs = xtot[:n, :]\n",
+ "xt = xtot[1:, :]\n",
+ "\n",
+ "a, b = ot.unif(n), ot.unif(n) # uniform distribution on samples\n",
+ "\n",
+ "# loss matrix\n",
+ "M1 = ot.dist(xs, xt, metric='euclidean')\n",
+ "M1 /= M1.max()\n",
+ "\n",
+ "# loss matrix\n",
+ "M2 = ot.dist(xs, xt, metric='sqeuclidean')\n",
+ "M2 /= M2.max()\n",
+ "\n",
+ "# loss matrix\n",
+ "Mp = np.sqrt(ot.dist(xs, xt, metric='euclidean'))\n",
+ "Mp /= Mp.max()\n",
+ "\n",
+ "\n",
+ "# Data\n",
+ "pl.figure(4, figsize=(7, 3))\n",
+ "pl.clf()\n",
+ "pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\n",
+ "pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\n",
+ "pl.axis('equal')\n",
+ "pl.title('Source and traget distributions')\n",
+ "\n",
+ "\n",
+ "# Cost matrices\n",
+ "pl.figure(5, figsize=(7, 3))\n",
+ "\n",
+ "pl.subplot(1, 3, 1)\n",
+ "pl.imshow(M1, interpolation='nearest')\n",
+ "pl.title('Euclidean cost')\n",
+ "\n",
+ "pl.subplot(1, 3, 2)\n",
+ "pl.imshow(M2, interpolation='nearest')\n",
+ "pl.title('Squared Euclidean cost')\n",
+ "\n",
+ "pl.subplot(1, 3, 3)\n",
+ "pl.imshow(Mp, interpolation='nearest')\n",
+ "pl.title('Sqrt Euclidean cost')\n",
+ "pl.tight_layout()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Dataset 2 : Plot OT Matrices\n",
+ "-----------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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SDp5/3gzIX6m3j3lJeznH9fKy0fSSxA/jpT28+SbwxhvhxMvEVODsWWkP7e3m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\n/wfPnU7C6ZZu4AAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fc3b26be320>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% EMD\n",
+ "G1 = ot.emd(a, b, M1)\n",
+ "G2 = ot.emd(a, b, M2)\n",
+ "Gp = ot.emd(a, b, Mp)\n",
+ "\n",
+ "# OT matrices\n",
+ "pl.figure(6, figsize=(7, 3))\n",
+ "\n",
+ "pl.subplot(1, 3, 1)\n",
+ "ot.plot.plot2D_samples_mat(xs, xt, G1, c=[.5, .5, 1])\n",
+ "pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\n",
+ "pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\n",
+ "pl.axis('equal')\n",
+ "# pl.legend(loc=0)\n",
+ "pl.title('OT Euclidean')\n",
+ "\n",
+ "pl.subplot(1, 3, 2)\n",
+ "ot.plot.plot2D_samples_mat(xs, xt, G2, c=[.5, .5, 1])\n",
+ "pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\n",
+ "pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\n",
+ "pl.axis('equal')\n",
+ "# pl.legend(loc=0)\n",
+ "pl.title('OT squared Euclidean')\n",
+ "\n",
+ "pl.subplot(1, 3, 3)\n",
+ "ot.plot.plot2D_samples_mat(xs, xt, Gp, c=[.5, .5, 1])\n",
+ "pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\n",
+ "pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')\n",
+ "pl.axis('equal')\n",
+ "# pl.legend(loc=0)\n",
+ "pl.title('OT sqrt Euclidean')\n",
+ "pl.tight_layout()\n",
+ "\n",
+ "pl.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/notebooks/plot_WDA.ipynb b/notebooks/plot_WDA.ipynb
new file mode 100644
index 0000000..f40dbd0
--- /dev/null
+++ b/notebooks/plot_WDA.ipynb
@@ -0,0 +1,299 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# Wasserstein Discriminant Analysis\n",
+ "\n",
+ "\n",
+ "This example illustrate the use of WDA as proposed in [11].\n",
+ "\n",
+ "\n",
+ "[11] Flamary, R., Cuturi, M., Courty, N., & Rakotomamonjy, A. (2016).\n",
+ "Wasserstein Discriminant Analysis.\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Author: Remi Flamary <remi.flamary@unice.fr>\n",
+ "#\n",
+ "# License: MIT License\n",
+ "\n",
+ "import numpy as np\n",
+ "import matplotlib.pylab as pl\n",
+ "\n",
+ "from ot.dr import wda, fda"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Generate data\n",
+ "-------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "#%% parameters\n",
+ "\n",
+ "n = 1000 # nb samples in source and target datasets\n",
+ "nz = 0.2\n",
+ "\n",
+ "# generate circle dataset\n",
+ "t = np.random.rand(n) * 2 * np.pi\n",
+ "ys = np.floor((np.arange(n) * 1.0 / n * 3)) + 1\n",
+ "xs = np.concatenate(\n",
+ " (np.cos(t).reshape((-1, 1)), np.sin(t).reshape((-1, 1))), 1)\n",
+ "xs = xs * ys.reshape(-1, 1) + nz * np.random.randn(n, 2)\n",
+ "\n",
+ "t = np.random.rand(n) * 2 * np.pi\n",
+ "yt = np.floor((np.arange(n) * 1.0 / n * 3)) + 1\n",
+ "xt = np.concatenate(\n",
+ " (np.cos(t).reshape((-1, 1)), np.sin(t).reshape((-1, 1))), 1)\n",
+ "xt = xt * yt.reshape(-1, 1) + nz * np.random.randn(n, 2)\n",
+ "\n",
+ "nbnoise = 8\n",
+ "\n",
+ "xs = np.hstack((xs, np.random.randn(n, nbnoise)))\n",
+ "xt = np.hstack((xt, np.random.randn(n, nbnoise)))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plot data\n",
+ "---------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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B8rXKt2Xlgf1eH+xFJNoH+6T5VM9Mt314JOLzU98+p8PnzMvLY+fOnbz66qts3ryZefPm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\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f4a7b2a7e48>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% plot samples\n",
+ "pl.figure(1, figsize=(6.4, 3.5))\n",
+ "\n",
+ "pl.subplot(1, 2, 1)\n",
+ "pl.scatter(xt[:, 0], xt[:, 1], c=ys, marker='+', label='Source samples')\n",
+ "pl.legend(loc=0)\n",
+ "pl.title('Discriminant dimensions')\n",
+ "\n",
+ "pl.subplot(1, 2, 2)\n",
+ "pl.scatter(xt[:, 2], xt[:, 3], c=ys, marker='+', label='Source samples')\n",
+ "pl.legend(loc=0)\n",
+ "pl.title('Other dimensions')\n",
+ "pl.tight_layout()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Compute Fisher Discriminant Analysis\n",
+ "------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "#%% Compute FDA\n",
+ "p = 2\n",
+ "\n",
+ "Pfda, projfda = fda(xs, ys, p)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Compute Wasserstein Discriminant Analysis\n",
+ "-----------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Compiling cost function...\n",
+ "Computing gradient of cost function...\n",
+ " iter\t\t cost val\t grad. norm\n",
+ " 1\t+8.7135243329934142e-01\t4.22283975e-01\n",
+ " 2\t+4.5259877952239763e-01\t2.80207825e-01\n",
+ " 3\t+4.2301660192758839e-01\t2.57544116e-01\n",
+ " 4\t+3.6438385605814744e-01\t2.01503900e-01\n",
+ " 5\t+2.6854415219016237e-01\t1.86872752e-01\n",
+ " 6\t+2.3605613971887493e-01\t8.54873065e-02\n",
+ " 7\t+2.3238632608008850e-01\t4.70510545e-02\n",
+ " 8\t+2.3084542185757945e-01\t8.60266814e-03\n",
+ " 9\t+2.3083921287882422e-01\t8.05123557e-03\n",
+ " 10\t+2.3081791779181188e-01\t5.75567680e-03\n",
+ " 11\t+2.3081444006658824e-01\t5.32065675e-03\n",
+ " 12\t+2.3080311057315009e-01\t3.34753227e-03\n",
+ " 13\t+2.3079768318049571e-01\t1.75615642e-03\n",
+ " 14\t+2.3079588611065080e-01\t6.04609566e-04\n",
+ " 15\t+2.3079584350945395e-01\t5.50079922e-04\n",
+ " 16\t+2.3079571065356075e-01\t3.07865387e-04\n",
+ " 17\t+2.3079565041678046e-01\t3.29364280e-05\n",
+ " 18\t+2.3079564985490117e-01\t1.32999543e-05\n",
+ " 19\t+2.3079564975468964e-01\t3.81768629e-06\n",
+ " 20\t+2.3079564974709890e-01\t1.50474730e-06\n",
+ " 21\t+2.3079564974588401e-01\t5.41516789e-07\n",
+ "Terminated - min grad norm reached after 21 iterations, 7.93 seconds.\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "#%% Compute WDA\n",
+ "p = 2\n",
+ "reg = 1e0\n",
+ "k = 10\n",
+ "maxiter = 100\n",
+ "\n",
+ "Pwda, projwda = wda(xs, ys, p, reg, k, maxiter=maxiter)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plot 2D projections\n",
+ "-------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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naGsxA0dn89j6B5g7Vp366IqioHObwy+mnI87KV6nuwu5d0omALMWlZqRsQDZ\nndP0+ypGMXfsAqqS4nl60psAxMUqE9TI9B7My1msrklSgum8WLX9AoGEXVvqUqa/8HugEWLCfdSh\njMLKCIw5ybgP3uLAhTr9Ggy7aFQxmYMzIj67LXWp3q4dFdzgB1mNdnio2cbx+nI60SbMSAjhRDGi\nfCnl65HOkVI+AzwDKg+iLe57OmAwqWkr1fbCMpVRfftVer2m0QFNxtBERsx/hCem/BPHZZIh6UqK\nyxlRy0uffkZCkgbejdzdd19Qu1ZmGDo4fnr+PmRf0LBTFiPJ1M/zOgU+B+BT1xuaWdLDKsekaOxB\n6msayFFCFDWVtfh9dXhqvsDl9gbdK3Tg5Y81ygo1zYyiOL1oTuBrr/Q1beVyuDObZZOnmgKj0hyK\njnvtsslTmfvUAnPbENRM+mgCxnmTUmYAUFtVh9/np2hbMTPu+RJPejzZScrUbWg8T3x1e0SBtG+n\ncqQQdIhR2s3cjD/T21GOK/kik0lkdzIYWbAgmfumYrTvTlVmry++b8gPd9EcNuuVHar7NjZ5zrSV\nyykaFU9ZZwdl+rptcGqE6tOFtoimE8BioFBK+YeT79KJwRgI1gHfHEJNam31MQ0tBiAuIeDQa6iz\no3zPrYe0Cla2wEZWcjmJMV6yY4vRyqfz9KRvuH3VBPP4ogfHUbS1mEdXFlFTWcsvppzP0+8qac40\ndTSBzEEZ5m8rwzrTqvy3FS0R+NoSLTEfnQythErlTY2nSHRsPXfu2AUUbVXaQXM0b2hICxZvx+8L\njkYTEoq2FsNktT1t5XLmLfqEKY2NpondQFKVxoGqFPpmLmXHrvH0ch/ELZQJzZh7DBhWmvoJI4P2\nq/MymTN/Hd17OXElX2TRiJbj0zWpvA3KhLj66rUA5PRbGnjmUcXUVNVBZxXFYbyDpt6VVj7dNPWF\nvuuWfotTjbbQjC4DbgL+I4QwqhP+Ukr5zzZou90gQHhKwnMnRSaAgiOlLL3mTfwaTFx7NauvXktD\nTQPLfq5sDD94ZB12u4083Vbd6UgxgCkBPrb+AdMOPC9HMYy8Daoyr8MjGdq7Jz9reJJ+XSvYX9+d\n7Jhi895DMs5j44P3MfejYIZs+IIGjs6m75WvmfsKykp5eEdus1qZdRCfDM4Fye1Mob0IfK2B8b2t\nAUSGhtRStFSwbAqrKpaY7RiT9S+mqPV/nn4XqpJsPFF8O92fKuByAqvBzstZTC/3QXY0BiLdjnli\nEFJy/aq6flPmAAAgAElEQVRxug9rAXPm1+HuH2OeU7S1GCCMKbw5ZJX64VX0PGd+ccT+GtejC8i2\nej82u83UvKy4/KM606+VkBTP5R/V8diDZzdttUU03UeYWThnHqGqvJXLG5PyogfHkaRLLcxTlSqW\n3X3yGtHcjD+z6FKBNWe1l/sguNFt3oq4/JYT6msacCVEDok0BuHI9B5s3rOPv12xio41cFRCYUUn\nZrwzno0/eBGA/VWliulNCZbOjGe+d3ImmYNP4MEMB7N3o7I16zb+SO/3ZCePKJrEaRP4WuLLCGIw\nnB4NKRQGg6mtUkxk+/sFTEqZ0aSGZOwfcI86ljkoluqaL5jLn7n/fRVybZj1Xv86jaJtdeRtzyX/\nykAVfKc3YNmYM38dXXuUg9TLhHk38upOQZ3HwYOzMoBAoEbmID1HSWdGXdJVkERCkpoHirYVA6OA\nXOprGoirCswPdruNe6dkBj2T1QpUlRRPY3o8B+7MaPZ9NfVerd+wNRrRqdCivpUVGAAzUiahieOR\nJtbQIAlj32PrH6DgSCnnD1ehm4Z92bBH763tRo7Z1gNMSpmB66Zj2Ow2Ml/czYE7s1l1jcpj+nD+\nI6bp8OI/qpC2zMHgSohFxtqpskum/ft68ses5qXvrDHv1ct2kNhED0nz1wVF+Bl4dGURmYMU4SgT\n5QD9PvsZtEj5wbbNuSuiWh+Ixmk9TsUE9m1DexP4WoKAr7Vl37ugrFSZvMqnm0EGBp21VMiprwnk\n6Fnv25Spr3TbKJIITPwLl+xUP7zHyMyG/E5ryEoup7AylZvfv56UUi8X/K2AzNHZZA6Kpb6yArNm\npY74GB8z7nmTX8/oH3QvgO2rh1HfNQ4kxJTUMuhSlYpRlWQjqUojc3AGm/fsQ/NrxJTUmlGEzeHy\nj+qOy4gMxtFUBG97wTnHjJo1M3k3kpmtonGmFSv/ihF00ByMgd29ieNfvTeKxcNtJmMwkJVcjtvh\nITupOEgrq62qQ6I0pP/elIEnQSBjbGCDykDqgElc+WPWUFBWakbv5I9ZTVZyOfvrAz1yO5Szs0t6\nGd6SfgAUbk4kZ4QirGMNTqprKlg4ZQGMUlFCXqcw7dKhKCgrBVLJ6be0WZ+REfFkmA0gqiGdzWhO\nU2ktg2kJtMNDAchOUhp3feUXzJmv6CQU1nFlhE8XbTvIvZMV84qkFRnazq/eVUuq1PZWgtymzesY\novtNH11Zh5QSvw886W4gEBtSWJlK3rpc7JaZsmhrMfdOyWT7+438bsXXDLykFr8UOGxKc+o1qJ4l\nWzdRWpQS9ByuhDg8dhu3r5pA96cKWLhkJ570eGZ//v1AakaMwOGxYbfbGDg624wcjIRIuZRWBH0f\nXyHzckrNqNsTFRJPZeTdOceM1CQK2eE5miY2HSzB7xSUdXaEfQQzIs0ysRaNim8yfPLDUfFMS7Lh\ndQYE12MeJ/EOX5hP52iC8hlN31/LL6Yo7ayhdyLYA9fKWIGjUSO2pJauf9rB7t8OY+P+fcFBDMCX\nFalcPOhtqvcPINbmMQkhIUnDqMxR3zUOg7A6xClH7Ix73mS6zw97wZfZAYdHUo1iotZ3cctSRUQb\nH4z8fnNSm36/VpyKCSyKswfH+95+rQYbEqNYg8vtpesFVTy6ooh7p6jJNjQ4yUDRNmWmq69pQPNr\nbH+/ICwwyT3TqEawJ8g8Hgm/mHI+JXdm80LeOrUjVqqAIbvALyVlnR3U3JSB3W6j/imVw5TZvx4h\nwCECJrzEWC8+TdAlvYzpd61m++o3uaHwB0hykS4HdIaj/5tN7Xl7wCao9njYdCBQaNUXIyDdzYcJ\n/tAuAtZowtzg9xESxBDKOHq4Grm779NMW6l820Y4O6jtM42znhmFcmaD8+ePWRO03zi3oKyUH32U\nayaiWTF37ALqB9tMH07JndlUJQXCJ936saT31flFW4thVDb9ulTg1yyRcvqYr62qY9tOleDzwGw7\nX900jiUz1gOw+7fDkDF2sAvTnGcgb30uWtc4Su7MRsbYmf6vCWgue1DiHcAr9rEM7qiew6cFJDOD\nsPt1rUBKqPbGmFrbeYMbQJM6c6rlpe+sQYpAmwVHSpm2cnlIlGEgyMHMZ9phkaw6OzhwZzZVo3RH\nalQjOuvRnKTbJhqRTrd2fRK3jt9dh1NIqioGPYkh1Dz+1XtqQTgjIvSptSV0SVe5fD/+Ini1gudu\nfAfATLFYxt+xe20MG/oBX703ivqaBu6d3Jvdvx0GvwXpcqC57CrwtQnDqDE/CCEo2ukyzW3WZ3DY\nJAlJUmdWwixOYtDw9LeuZfraCYo5AfFOJ3VeL35dknw99211gR4+fjxN1Qx+IKDtmKZPfZbvEOMh\nK7mceTmLeXjHbJZNnhqmTUWC9d6nMvLurGdGBkLVzkgSvLEvNCMaoM8ff4/tGjeay04twLxh+JLs\nUBWQTlwJcWQOzqD76DpTCln14H1oh1+l1htgbnu2xJDZ309siTLHedLd3L+2iH5dNyumkA5LM/8J\nUpL3gVo0Lyu5HFBmAVuDhgQa0+PBLnTiCA8Lv6DDEexCBjEbKQPMCAR+XaU65omhsDIVu82GrdHP\nkHSVZ5HVsZxdVZ0Zmd6DZZOnsmnzFQD8oET1yxjk0wh+v9Z31xK0VP2Phox/S+ALLx0lJWz/xM2y\nJ1XkaVMa0VHd0Ztp2SeEICHZbZrdjUCFmB76ukO9jJso8/jcsQuYMz9w/dKrVXKrQY8AI9MCZnEh\n4eZ3crngb4rut/u1sOKgdT4HiU4v1Y1O0xJhBCn87buqfXShtc/9KhewSg+g2vjgXKatXM49/RYR\nry8R08t90Gzb6lOzmsiKthVTtDVXhXmj06suSD68YzbzchaTnVxuBh7tr+9Odqc0kx4NjciYE8+k\nBeOsZUahKqgRBj2xRIVBGxL8sn7B56v9+4PaKtpaDB3tSEseUG1VHcnE0/2pAupn9sHv10h6qoD6\npAJ26GaB6Xet5qv31pGZXY3bAbW+WNwOH3aHnYQkjYGX1LD9kwQlYYXwkqGd9aS7K95gZNohc//I\ntIO8ctU/8NqDCcNIQs3bMJEtk14g3uE1pTCrr8ovBXYkNR4nQ96YZfqXDNz43nU4PJLPv/8C8TE+\ndlV15kcf3UB2Z3U8SY/kiftamfcu/48yRW46UGISCRCk4oM+eCcTRRQtQtFOVRsuM1tNktsPduH8\n1HISkt0cuDObeTmL0cqnY0tdGsSUirYWc+uy7+BKiOOvF71CZn9Vr87dwU9mdqlJ5zmjcvlZzydh\nP0zfMJElvdZj31vNr6Z0M4MC+l75ETt2jee3nx/GawtRg0I2pZRofo36moYgLcSKwqOpZHU8SuGx\nVIbGKJo2aNSgQYNWH1ulmMetnw8zTWvLJk9lx67FIf1QFRce3pGrGEuEpWus/tqBo7P5UHcrKIYy\n1fSbF1SmmhqRAYOODSHTiub8Q6dCaDxrmVEorGHQEMzZp61czrycUlMi2LFrPKAY0+Y9+/DpkoR0\nOUBK8kevxtWzhr89kcv2qrowW7MrIc4MKbXC1qjhFxp+X0CbklKa5YA69ApoLwB1PidZHcvD2unX\npYJdhy1rN1gkMFHvI9EZbmKUkiAnarzdy5aJz4NNBDGrLZNeACAxRkluwzqV8P61f0UI2LFrMdm6\n6eP51A04fJJhQz9g2srlYTbmUF8QnFjgQnspRRLF6YXh2F+wSJfEfz424PO4M/I1H46Kp3ZABvW9\nE6gF/L0SkXEelaDtDfZ5LJs8le2rH8WPWo4lLiGO2GTNLC1koGdcCTI24FM1hLfCylQ+K+0GmmT6\n2mvpc/8mrh9dC6MuBOCmu9cAgnsnZ/K7FV+TkOzmtjXjeGbGOrAFmJABu00ErVNmzBHdnypgWcV9\n5rjPTioGLCY/2Uh13Vbu7ruPiWsn6uWI1FxmLd+lNL11ZA6KNaPmDBiBR9mdwjWeZn26EbTXgrJS\nHt6w/JRoTmctM2radhlsA9XKp6uPl1QMXhXV1st9kL21kSvXgjJd2Vx+UwJKf6oAd1I8JMWzqmIJ\nc8cu4O3BNhozS3HGBdY5ObA3hfqaBn4xpbcq0Ihyiq7YU0DvIQGGYDg8O8R48GkiyLR2zONkf303\nkqrqyL/iDbPigmEyKLzpeSItxyRCtC+bHRLt3qBzDemsqeWcrGYBKVS5oUGLnjRV+M9K9mMXgnin\n02Q8y6L+oShOAEbeXfGuBFwJcWYtulk5i6lu3KAiR73F7Ng1nuxOaSrce1S8OcTzx6zG36Dxnedu\n5vKP6lj43Be4EuKwpS5l++phwDCzOOoz579HdSPcsGUS2jUajF1gRqmFVliwNfgRUmKrDwiUsSV1\nuJPiTWa5/f0C5F0BYvOkuzkqYPxWjZyfHMEfE1zlG5QfzO/TcB1uMBlRZv96Xvr0M756b5QqoGzJ\nNwxlZq2BqblNPknhLiTR3Za6lIc3HN/HdKI4a5lRU4ikEVU3Bmo81dZvw+1oJDupWAU5jIF+Lw/B\nr2ls+d6LAHSI8UKMys2pr2lgyeMTaAkyB2VQtK0Yd1I8CckqcGHg6Gz2NVTRM64Ev19gt4cPMoM5\n+DQBCG5ZOo7nhr8GHeNBQlZKQHuyW6J2gv1DStMyEO/wUudxmBLfMY+TwopUZi8eQ4JeAPL8ziov\n6r/HOvP4rjmBzPOjHc2ABrsIJtZ4p1PXkMrMfaEO5tZoSO2lFEkUpw+BaLBMfj2jvwrJvlLt6eU+\niN8VTiNFW4t57p6d+H1+8jZMxHaxn+zkcp6fvo5bGEdMnA9kuLUCAkKYjLVh06eCom3FVCXZGKIv\ndWREwGoxNhJjvQzvVcrne9PMfB+S4ima2Yf/nfkeP2jwM6iX8kX9bsXXeHAza+k4LtiqaP9YYyOf\nlXYjMTZW+WuAh67qzUuffoYrXWPn5wlIKXG5laZUX9PAgb0pdL2giji7wFPnMGtHIhJJjM/iiY25\njEzHNL2Fvs9HV6C0Q28pT0/6Rj/S8rqSzVVhqa91osXauG3lctOcZ1iXcvq93eJ7HA/hLPwsgVY+\nHU1PkDOS5CLB8B0d88RQ64sN0ogKykopKCtVESxCEO/wEu8ITL7de1WYNmljYh0x/xFWXRNPbe8E\nfvj+RCauvZpNZel8/k0aN5xv5/arulFbVce9kzM5mgDTfr+e7KRiEmO92CzSjk8T+DTB5rKu5j6D\nmTx53RpyRhxjZNdDZCWVBZnlrMzHb4n3PuZRAQXxDi8dYlSod4c4L1IqprXrYAqzF48BMGvnGeiX\ndETZo5OKcTsaVSVwS4SfXQgSY2IYmd6Dq5aX0f2pAra/r/6+em8UM+55s8n3H8W5j7ljF4QFGTSH\nom3F1Fd+wfS7Vpvm7rljF7Bs8lTcrkF8faQjW0q6gnMEOf3expa6lMzBGSqAqH89L+StY/h5pbg7\n+LkgcS9vz35JF/L8fPXeKHIuu5CBEzexY2MHPv8mYFr2S4kvRvDWAPju57nc+O4EPt+bxrEGJ2hQ\n53FgawyY0jrWQkKym4Gjs1lVsYScURdis9vQYgPTpifdTb9ulXz885Xct34PyGo6xHjITiojO7mc\n6oYGjtU3UFtVhxZrR9oEfbLrGHRpLXYH2B3ouYCluB2NSAlOl49jHifVjc6gRF4IzHvNwesUnN/5\nqApG8m5U1VNacF1TOLA3pVlLUlvhnNOMrDC4/abNf0ZIids1mJwegcTNW5aqCgf531cTb6hqXLTT\nZZoQmoNf0yDWTtHMPnT90w5AJeDJ2GL6WnxC1d7gCLTCylTyNkwMCtnOH7Na5TfocDu8YWY1wz90\n4YrbAjbuo6qOVlbHo2HJt5ofZuUrG73dbsOHKuK6v767aaNWETeBfhkwQk6fHfU68U5nUJl8A8Y7\nOplk16hGdO7DoDsjJDuzv5/frfiapU9mM2f+Oj0YqJQh6SpJu76ynF9PUSY1U/IHhrgD/iGHTQaZ\n2rr2KKe+soJbNyxnySXVQLVJ1yatVKSS915uIFLVJkxaBHg5TtHjaw+OAZSvqs8ff0/+lWvwayqw\nyGhLc9kprExlaKdDDE0LLGrpcvrw+WtI1Gn5n99sMxNn3R2aNsE5bBIpIdHpZXehYqSZCYXkjzF8\nP2ptIyO4w2pRMCJh8/6t5hFnSNSUSrpfcFz6NJanmDO/WC+wrII+ulPA6kWfAAHflmFG/VYmvYaq\nkNPvUiU8jLVOrC/aONcIYw66HhWFApA4PeD3AfCrtelY8vgEFZlSsdwsKzJt5XLYWgw1PiqT7MSW\n1PLTI9dSngCx/joeW6UyvXMui2VLsTQ1EyFUJI2hwVgnfCumv3UtsSV1fHrHctwdNBrq7Lg7KBuz\nTxPU+RwUHk3F5glIcIUVqeS9n2uqTVsmvUCi02MGNNgd8PHPV1B4NNWM0LOu5QIo+7BeqeKJr3LZ\ndKCExBinuRCYVr4l6P2G5npoh4cyZ74rYuY8RJNez0WckHnW4hRPSNK4YJBH999ksP2DQJmtPVti\nTFN3KOr8Tlw2n8lkrKkNe750U9fLHZREaiAruVxZPgRmfl9WcjkdYjyMTDvIl1OewS4kfimo8zmZ\ntegT8tbrwQCN4cs5xDu85vVgmNn1PupWDjPlwhbs1LWa2I3rQvME0/pWKquIBLybg2pD4isM0OCg\nDN0lEUd2pzQ6rfLx09euZeOD9wUxq0UPtkx71cqnN1nM9VTirGNGrYEqQIi5GJ2xbZQPqa1Sg7/B\nUIU7jaC+8gs0v8ah/akB5hOCJ3NVmPW0f0/Cd56bWr2CQsP5Hag9T9WYq63fxsBunoiOyCBG5Jfk\nrcvF4QcHEkeJWtlS+x87fikpqEhFa7AztNMh/dpO3LRW+bAEvkA5H4v2ZJgarfeOd/iClp+48b3r\nSIyJIX/sGlOyMQbusslT6fvkH6jzesOj3fSFuSIhc1DzZfyjOPcwZ/46au5Sy5McD8YYM/y2ocd+\nc8sMFi7ZiSshjqVPjlNlf64MnGMkreetz2XRpSvMqLcZb+eyeaIKiZ47qTcLtxzmpctXhdGekQ4x\nMu2gmR5R5wufAg1GckHiXnM1VwgEEX055RlA0ZfVCmHcz2AuhUc7MrLrIbNN41xlIZG47T6Qki9K\nOqPF2RmRdjAoIjbBYbVw+AOMCEBWk9GvRpknvaVmaostdSlPT7pCP0n5jAyNyCo0RFp2w6R1XyGZ\n/dUq0HPHLmDg6GABQzG+xVQ3NpK34Wo9gvnkI+zOOmYU6vBe+qRiLJEmQYPpLFisnI0PzI7sW0qy\nVMl1JcRRtNNF3vpcMisCDjujmGi1x4PW1x5UwRcIy/2JBKvkZCbUjVOMbcbbuQzt3ZP7L3iU3nfW\n4o5T2tDwXqX4NGEmt+ZtmEj+d3Wz3rpACKc1JDVSH6ymCoOBZXdOo6GmgaKSYvpeiel7e2w9pJTq\nmlOE8E5QORoqf6FeEYmsVvXzmB6kskcLpZ67MBbJM5YnaWnAyt5d4+kZfwCbELiTB3HD+XZghrkI\nXm1VHTs++tK8JrD8tkrhyO6cxpyPp/DsqNex2yC5ys+eL91cOKya14oLKKzsFHTPQCqFQwUnERDY\njG0piZi3Z2hT1uCg4yHSuVZftBFFa7cnsGW/m7wN16G57GbahXH/8KhXY8VWhfoaQUKSrh3qmtu0\nlct5ZmQFtkaV2HvgzlyKthaTP39NmNDw4ah4pq20MBGD1i2V+ZuqE3gqcNYxI8MU8OiK4P2RorEC\ndZq2m/sWLlEROb+Ycj6PrdqD5tfIzK5RB/WJNTO7mufTVX0qI4kW4NlRr+PXtAAjuXJNUBWFSDjm\niTEHs6kRhfCKrORylly1mp+unIBnUjxabD3WQWcX0jTzGUxn18Fkva2Avm+YDQwYTMwY1Nkp5dj0\nYITYkjq6/72AZRj5Heq9GgPUKAdUUJmqMr+diSbTAYuZLlCcuEUIzVeKon3hRApmZmYrDUkrL2rW\nd2Dkqy26tBHpArezEbwbuX9tGq5DDcyd1BtQeUGRllXJ26Am1rLOSrC58b3rAOiEj1s//z5vD35J\nP08JW/ljVjO006GwKiXWsj0Gmkp36BDjQUpFW4aJPdQsZ7Rl0LpJ50JfB0nAvrru9HAdMK+t8zgo\n/kJy438nmMn2hZWpIGFkFzW/+H0qRQOg9piNhCQ1J0gJDXVOJmdls3CL8lPlfaD8RHMz/qy0Tgcs\nfG4Fe3zpPMzsoEhfUEn9NVWqksxXKaNUrpZV8wJTQwoVMoyIvmkrl1si/E4e7ZoZNRfua+x7bH3w\nuVYElh8uBtAjctSqp5FQ6/WYdZxiS5Q/yVhl8eEds4MqEAAgICvlKFsmvRAkTSnfToD5GBpL3oaJ\n4JfE7alm8ewNZsh2YWUqWR3LeftHf6PwaEeGvzaLJePXBGzcBAoxDu10CIdNMrxXKfmxq1XGd2Wq\nySCtElhDtUBzKR+TU+dtQ3rUkj92DbWVdcQOqTOT9oT4D/dOzqRmQDbb3y8g/9YNAGalcKQv7H0t\nenAcsxZ9Qi+3Rw8HD1fZrUl1BiOy1sSKakjnBoyVgUNp1kqX83JK+d7b1wAEjVl3UjzZmRm4k+zY\nHXZs/Trieu7aMK06MSaG2oQA1zACf3I6HkXza2Yit+H7qfbGHDdfJxJjCk2ZMPIC4x3eoNSKOo8D\nbMp0jlQ5Sv26VQJGOLk0Na/qxkbiE73m/TrEeWnsnsLfer/J7Od1h/cVMiiaz1op3N0hsF8IcLk1\nHlu1h3qPWpIi7utjZE0MpFuAisq7gL3c3fdp8B4kMxsWLmnAk76Ht5aMpeH8DjSglrBQqwKEvJyT\nXFCztWjXzMiKppylZon1ZjL4Mwdn6NnJfjMi57FVe8jsX89/twUi3DS/Zr6R7r0qcLp81Pud7Krq\nTMGRUrOS9Tu3/Q00aUa/WbURUJqMwRTy1gcCC/BLhMdP+lMF2PL8ER2gWcnlJFf5QZfGrJpNGHQf\nkPX+VsIS+oVZHctxelVFZCT0djTgT/ZTVKJqi6iy+eiJul/zv1MvwJYXUjHYORS8m6mvtfHrW1X5\nfCigoaYBLa75asgj5j9CZZIdX4zgs5L99H3yD5Z8pSjOBEKFNyNrv6Xm1Kbyw5oLH87ulMaw7unM\n+XgKdV4v+WPXMKxburlMycIlO/VE1WPMy1E+ILMwL1Bd30j+NW+CXtg3K7kMEGh+icMH6HFIBsOw\npkTYG/z4HILNpV3I++B6ZRLTVFXuRKcnjMYMq4LVhwMqirXOqwTNm95SWs3Sa/7J0M6HVF5fjNdk\nsqEIDWrQXErtaTi/A6Lex/S1E+hz/yb++U0pNnu4tmZlkgVVPanvWse0T79H/pjVLL5lvRJqQ+YC\nY04xkHPZhRSUlZKQFI8RNP5Y8R1AoLi0Ya47XoRcWwuS7ZIZRSoRczK2S8O2XV/5BS5LgI7PYUzE\nSlNKiAloFXHx6nei08OwTiWmw/TrIx2xCYHNJ7HV+0AGS3mG6r65rCt563IRHjWpCyBGD0546JOD\nICI7QDvEeZWGVJnK5rKuYczKzEuSkPd+wBxhPc8wF/jj7KZ2ltPxqHkfI6Fu0KW1rCz8j1nM0a8n\nAGp+jVtf+Q4A2371lcVv5Mfl9jNn/jq6LFIljgalB7TM/DGreeKr2yN+g+Qqv2n680tJtcfDZyX7\noxrSOYKIgS4QZvq5u+8+6KuYiV9T485ITm/ok4ix5El1YyOJsYq7JMbEUFtVD6jQ1KyUo+SPWW1q\nHZ8d6oqtUeMi1xEgIJBZ65juqu7MoMTDDE07rCqbEMxgrEtACAF1XlX0tKE64JexmsuzksvZNO0l\n0+KxZdILEbM2DdNe3vpcs75kKLPKH7MaNKkiZD+BLSVpaC47WcnlQVGxxjMJW6JZygxLtsj0tRNY\n+t1/MjTmkHn+1qNqzbNhndV7taUuJScVLv9oQVANu6B13ywa0emkz3bJjCLBiNRqKnzUIAarE96K\ne6dkMuOeL8ka4qW+1saSxycw7ffrg1RhK0KlEsNkdn7nctwOLzhg07S/Ee/wBiWuGgN2ZNpB8seu\npr+rlMLKTtySP44ef/kSDVTSnCWyLdQsYNyvsDI1qBp3nc+ptLEr3lCJqVe8Qd76iaaGNqLzwaBE\nWCNk9bNSlbBW3egMK3+ixdox1rww3oWhIQkhwBeulmUOyqC+skIPvY1s8oSA9pr0foEq0a9LolG0\nHkKIa4A/obzYz0kp/+9E2gllGgbyx6j/rV0NtCUaUVPI26BqrRUcUYu+FRwpNf2yxjGA6oaARmQU\nFTaiSwEzv8dqQoMATUkJ56eWs+1AFwZ1OaQLbkZlEjWbh/p/zCAITTI08TAOW7CFwsgtGtH5YJCZ\nPri0l57GUZGKaIi8NlEotFgbs59XJjQjoCHouB88dQ10f6qAub9fj88hGKEzt5fHrkHDzuayrmQn\nlfFVWSo/+vwGAL7Qq8sYiBgp7Mg6o/l+bcKM2opQwhtOBE48IdJ42QtTnuQ3fy0383USkjTmv7DC\nTHYzb2cZvNaBZ0hYSpMJTOZCSuo8DmY/N4aPf74yLJpuaNphhCahUjllF36kch80W3AFhFAY0pBV\nvRZCme1UNNz1bJn4vKqh5/FTcNPz5jkOIcPMDlnJZezZ4qK+Sxz9ulQoZoqSwGblj+M/9y8Lev7z\nc5QCb7PbgDhsXTYD1hIgS/n1lGAz6RNftW4Ss+s3i2pEx4cQwg78GfgOquT850KI1VLKguavPH2I\nZLazhgADJMbGcvP71+i+VzV5FxwpNbVkUAnkdpvNXKKk4EipEmCakWGU+UuavlFrXqGBxFivub9D\nSGQbWHL4dCZkBEEY/qdQZCWXm7TeVIWURKeHjUe6KQuGizBz/tBOh4JCvg18esdytFg7uw6lMDwz\nA4dFcLA7oPBwKtN+vz5oQU+AjjVQZZc8VnwH83IWE5dAIDRd11CtZXzyxxgJtGvC3BytNdu2BU6a\nGZ0SQokQYggElZMPxb1TMpkzfx3T79rJL6acH7ZCq5pYA9KJECpSDPRlF0S4XdgKa86AEeViaBmL\nb4pkfgIAACAASURBVFlvRswFSUiaSjgd3quU5258J7wadwtwzBOIAqrzOcxSPUbNuS2TXjBt25Gv\nd1JY0YnZ747h4/9ZQXyMD7tuThiSXsqndyw3rzVMFcY6LcrH5KW2qD+u5IuC2jW+Q3MSsaHJupPi\nmfQvteieESIfRaswAvhaSrkbQAjxCnA90Goaa0qTMfYvO8XLgBi+wqKtxVQm2cm/eo2er6Im/7wN\nE0mMiTErfhhJp3kbJmKr97Np2kvEO7x8sa8zF/VUZjmDPrI6llNY2SkohcJKG46Quo4QYB4OmyTe\n4TMtEhAIkAg140E4Awqtmm9sm3mAxvM7QpLNI0CLtYMNM/ItFH07KaZ20Ru3qH5e8YZZ/f+H6yfi\nSggsL/6X4Q+26J7tAW2hGbUZoZgEEhpi2ALMmb+O7r0q+G9lTNgKrVOOTCW7Io2FKU/StUc5h/an\n0vfKj0jcNZ5+HfZiFwFGZY2EMwbmze9fT0qpl79e9AoAvYd5ibd5zQGa1bHcvMaIdhMiOBrmop5H\nzCi4zw53AwGflXYzpSWrViUE2CNka3eIUdE4IzoHbM7uDpqpEVn9Vcq5C3s2xZC3Nxd6AzYRJom5\n3JrJnHyaUJpcCJwuH9V1W5m4dhYAI3dYI+NObBKLBi+0CunAPsv2fmCk9QQhxG3AbQDnnXfe6etZ\nCKzMLn+U8kEYUnb3pwrovXUT3QdnsG0AOKpU1GpDks00yYGxro/yrxgV40P9osN7lZoTvoF4h4/s\nlPKw6LiAkKW2hYgcyl3ncVBYlcr0f11L/ncDZu8gf00TGppRNd+aTuEQMij/L9SU57DJoHnGcAUY\ngqa29Sg7dh0l57IRgF7TT0/Qz+xfz8ujV3PzO7m66VtQlaQI2YhYBbUsTC/3QRo12FvbjYlrryZ/\nzGo2bb4iWIPU100KFUrONp/RcQkFTpBYWmim08qnq4Km0sugS7281Gs9cQlxTFx7ddi5NrvNDEMF\npeLvqwvUaBNCmd9mvK0IyBcjyB/zBrYGPx7pJiu5jDiHDK9uQLDqboXB4EKT6YCgARr06CHlg6z9\njXcEGKGVOAztznCQHvM4lVN4vzppyCrFTL6c8oxieK7hfF5UzPDzSs227TZBQUNHLkwqw/AlOWwS\n6QtIinabjR8duSHsOa0IjX409mXfqcphRJNg2xZSymeAZwCGDRvWfDwzp74WYEFZKT3jG9lXWRrx\nuDGWMrOVz3FeQmBROa18jUmP1oK9oaj2xoAmiY9RpYEcNkm8aFoLaIqRmMJenBcqJVtufMk8P1Qj\nMhBJW6rzOcNM5Eaek9XHZT1uM3xJelORTIIAO/79JRn9VD6kEXA0xHWIjT940WR0Q9IPsWS8YuIG\nE8pOClS66Ndhb7Pv80zjtFXtllI+I6UcJqUc1rlz58idMVYQdI5Qf44sCipTm12n3YwCsWhTxkRv\n+CUM6WrKf6dy69ZfAyppMzupOGShOjubDndRJXhCFtRDwg835KLF2sMGjEkIFnXYqMrtl4ItR7pS\neLQjxzxOPt+bxq8vSqOwIpXCioC/auPhrubaRlbEWwqlWn1X1m1Q5rxqbwyflwaq6xYeTQ0a+flj\nVpM/ZrWqVyckteWb6ZdWETi/MpVdh1O4+Z1cCitTg8wdobX0rNFwO3aNb7EDe17OYjNsN4oWowTo\nadnuoe9rd9DKp6MdHmrSVnZSMc8NXsjClCfZ/n6BWaVbCIHdEdl3WlAWzMAMeh6yahbHPDFIqRjR\niFdnsqs02Oxd53Hg0wTHPDFBgpx1LEtdgymoyqDWF0udP1CbMqvjURJivGGBPqDuKaWitQtX3GbS\nq/VeocWQjXDu0DlDSqipsjFr6Tgu/f1kbA1+Feigd7P2mB1XQhxLHp+g/G/vTgirLGHMOdlJwflF\noEqchc5hnjoHTq9k9nNjuH94F3Zs7EBRgV7ktImcomWTp542QbEtNKNTRignupiTKyEOKuGl0W8A\nhNltAVOlBejhOqD/8pt+odf6LiOzfz2FlZ0YnqaIY/PUl4iP8QUxB6sa77AF+6UAahsd/PC9XL3s\nj6oSXHJnNnkbRoKmygFlJZeDEGFaj5WAIBDEYKC60amLE3rV4fW5OLzweu7b1FbVcdP668xcBtVh\ngjiYlBJbox+MZHdNklSl8d+f/5xpK3tyt+3pIBs6BLSuLZNeoLAytclQbutS0dZtg2lFWpE3iibx\nOdBXCNEbRVs3Aj9sq8ZPptp6KAyNKNHicvU6BWmZFfxuhSpHU7S1GCll0IrIBgxfh5HzcvP7Q3hp\ntIoetUatJTo97Pjhs9R5HEHCmZWJCBHQngoqO5GVUo7bqXL3HEJyQeJeAGZ8spCfnv80hsUvK7ks\nKFDJQKjvxWA0VlObur7cFHJ3HUxmeK9g5moVIl/IW8es/HGm/8tAXLyf7r0quOnuNRzbtZznbknj\nh2tz+TJvcZi50OUMJKQ7vZK4hDhe+Kmqrv/oiiLwFVK008W9kzM5cGc2EHndp6ZwuqwXbcGM2pxQ\njEgcWH5cc45Z4NO7GYMR1HqDo1PsQgRF7Vz8xwGUJwzg5TFr6NetMihPyIAn3Y0WG9yO2+E1/Sug\nm/Q09EXzghmRWecqzsuWyS8EDe7Ft6xn9vNjVfLrJ35IVvkThhnNqHO35UhX+qceBQIFVw2Gtbms\na1DuQt6GiSDAF6MzVxdo1hUn/ZLZi8fQ8y9f8sirNbiT4i21+7bT0CeRm9Zex/X/quWxK9GrJKCy\nt1GmOWsFCiFUeaH8MWvAW2yuoquKMo4LmtjmzF+HdvgfSvrSo3aMwo6hC4VFEQ4ppU8IcSewFhWx\n+ryUcucZ7lZEGCHa1kKmcz6eQv7YNSQkqxVTVVDR9qDrjIi7z0r2kz9mNdV1Sht6afS+sBy+IDSR\nKlBYmYrdZjOj8xBaWAUFIaDW6+Szb/Yh++o7pbIo2Bo1hp1Xalbwtvp03TYPWyY+b9K0tfK3NVkW\nCFr7KDRoAqBfF2WZCE2I3Xa4K36fBt1Bi22ERoF0Oaj1OYm3+UyBNfQ6v0+jur6BtwaoFaqLth2k\n14U1pGU2kDk4g8yPVAmgWlRR2affPchX740KVN8/g4tcnjQzag+EYktdqpdXrwMRjxE2agzil0a/\ngd1mM2tZgXKcxpTUskskc9v/Z+/M46yq6////Nw7+yIgizKDMjgiMo6CgZKJCe4b6PcraghuYUql\naVGakZJbZf2sTOqLJpkFEQq5UJkrEOQWKCoOLowOyc4M26zMnXs/vz8+53Pu55x77jIb9w6c1+PB\ngzn755z7eX/e+/u94Awem/wSyGhW9DQr8eKYP9Xw1/VlNO9+h3Bb2LbXajQ3CNWxURSkFHgxvHct\nRNRE+dmi9bTkFqus7cO3xthzpYBwRMYYU4NCqqg6kxFZ0PdYt/NQRGuYvg3YrS7K/1TDx18/ln0l\nm5CbGmnc08SmmypoLa1m+KE7+dP5f+eGrWdw8p0P8PuprzCzEia+oO6d1SqVxtWWS2HWPoqzW2ls\ny3UWUm1bR8lgZzMwnXDsLrha0c8PYGgPpJT/AP7R2fuYi01nOvTGQ9RxvoSCrBCj+2/lncveVAJL\nL1WOpvLUMP979AkA3PeGotEpy861zcgAH+3Rpvwovekk8GBAsG53P6bNHUfjkCK7moJ2/LdFBNkh\nyehRS+3qH0+cs4TVtYc7GJtOOtfFiu2KKn1Ugni8VIlAEIitjgVEhdBocNNOZcKLqL5Lpq9JrSUR\n3r1tgR3sZDLcYYftst9pTN4WPrnskRi/l9bGhFSWjrtOOczSfhS+d2k5d7wASPU7F/YqsIMgfrZo\nPSWDW9m8wTvCd38XOe6SPKOuIhQTZk0zc9uNmAg8WU9hlrNZ3JhSZUXUdeYqh73IjPGzmPf+RCb/\nv6U8PvUVvlBWBsDe+ncAOOL/PqRy7LEwsgyoNn6wWpshNewJ8GlVAT/66vH8dX2YvfXvGG2+le1Y\nFzQ98YgdNLVl8dGWPuRva2HrLZW0HBVtxgWxQQ162wx+MEt+uE1ojv4sh29l9WRV6+6alydSMruK\nZuu86+afyfxxz/GzReu57JPRXLlsAvPOVz9f8+H57AvGuhJ771Fan1kySXd/rN9XBCgTQbgtn/eW\nVzFj/CzueWyRMpmaTNoVtQNdaybykRm4f+00vj1sDsN71+LuSlT9bg2Ne9TcGZKlLPpjSgfZVULs\n9hLZJ1NVu51Vtao0yJRlFzF/3HNUHrqTguxszlkTYUVRG0I6/bVZAcmIkm1E6qZSMjvIzu8fZ1dD\n+fO4JTEmMcBOmTCDfzS8KjR89nYO5ceFWbenH5Nfv4RPLn/UPmbCXdJr9Y7DVX5Ra5a9VijfmaIv\nrenkFeXFLwMWD0Kw6aYKWo4+BIB73t6GEIKTDlNaz32vQzArwILvqlp4Rb23kN/7OIaWz0urRqTR\nYyowtBtZw2lsfpcNjQOpHGZ94FqV8BWpm8o13/6Qu645juAGtVB+77vlVK+p4Y5/KqZjOv8Cfecx\n1OqrEqmbSrjlPyAl1R/kc9ukcvbMrODtmr9zwkBvcSmSG7Dq1bUp+/FgWDHySUDwhWeus6VBszAq\nREvNN7VlOyQmMypvzIAtjvp45rGCrBDZYRg15Aiqvx+268MBtA4qZNiAXawe9Uc+3Non6hf7yhME\nggF7QXjy1GcJt0X44SkDeXzlKVSvqeHni6spH1HG/WtVxOETp6igEC0V/mxRI0W9vetz+UgPvEps\n/XyRU0PqKmEgUjeVmZXbqeilGE31uzWUDM7m43dzuG3SECt/Rvkt1u3uy9B+dcysnBvT46h59zu0\nNPSF3Kjfc8qyiTx56rPkFUWrCJz92NU8dtJTDDm20U5sDwaKqKrdzuabzrStHfPO/TvDeu/inc9V\n/6DhfaIFjGOjzIQjBNtdAb/lqGIi+a0My9/N/PFLPGvb6cAmd1BSU6tadhv2BCzBNmwLr9pUj5QE\nWsK8fcnjKv0iS41lb0t21DQZifZCm/D3el4cGcDUJEHnVyoEswJEcoNcN+d1Ih/tpLxiL4S2O0sB\nERUOF1jzYfLihVSvqaHk6apuFRgzjhm5OXQylTBREl9h3VQq8qPHdLgobXUMH9XAD1/+zK6tdsyI\nRUTCEXsy6wXVrIen7xMMqtlVflwzi9e9z6lzKrlu3pk8et2rdgtwuzXxYbW2BOQMBY3OXndmtomg\nkI4scTNENHq9Mv1t3FdKRU6NvT8rIAm3RXhs5D20jYaP6gfY9cA082mLCLvSMIAUQpkGLbRlCYTF\nY6vX1KjS87sb1QIzW03O+o33Wc/bZ33LVvKLAiBV0qyy3sZKXd1hJvLRdeiMtDy40FsY+dmi9RT1\nLqS5oYX8ojzKS9U8rMiLWjIQxSCb2LyhD99YeiH7SgvsiFhQARERq1Nx8/X/oASYsWcIi9e9T7jN\nyu+T9dQ3F/LrSf/gyuW6AaWAgCCSG7DbNGiNyGw7oTGq39YY38y63X0JNIe5aplqcPmn850GIc20\nTGuGGfA0qt9WLhx0AovXva/M+xZMITQoBOGwJHdTE/mFEcyCLQU5bY7xICC/KJcHl34XUDS0olcb\n5SPLOGXkvwBYtfrLhMMRnrx9PJtvqmBm5VyrRcfe6I3TXAoIMpAZ7RfIeoLBqPMQiPZPsUxKRb0L\nHZ1L3dKDhhCCv054CYBya4Ef3X8bb0/8vWdrcS0l6Yka7TgZWxZE3T/6d1Nblp3TpNEWEXy0pQ/X\nzT+TYDDAa1//nLyCsCPhVjez1IzIq8r33tacaJsLlEmzKRTiofXTKZldRWEv1RnyveVV3DbpaE44\nvcLuYWNLtKKY5oYWNm/oo3K5XPXPfKQP8apsQ9cyf2VWn8C3hn7O8N51bGwu4f5d01hwxhXMu36W\nVT2/jLdr/os521XfrFYKs3MUoyoMU16xnYcLlxDMCnD5vy3hzoh0++TVsdzzRAt3XaOaan3QPIDh\n+XUcgjoeaFXzXTMYbYIbbhQN9qLRij51VO3q66QNQ8DUQQmR/CxFL1La/luNKcsm8slljwDe+U3V\nH+SrIs0CInlmxKtUBrugoPnoQ1hVN5BAS9iOyAs1Z9GWBYdYwVXrr1pjXXiz8/5rarjk+msoH1nG\n5T+NEMkNsGJsAbWbNjJx07nkrd/L44WvcGgjzLm33FH3UwuHn7w6luaGFkpmX0jt8ireo3sFxoxh\nRl5mBDCi5UgsoXke06XQrdpq7krC4Yhkb2sO63ccyoM137Sr1+qIMOUINDohZg3ne5PKuecxZzDD\ngPJdFOfl2ZJdU1sWQsCUpROZP/45e/Kv29WXUf23OiJ6dJSOux+SaRKwq0Ls6msVi1REJaXqWXTd\n/DPZV1rAn8ctQUrJ6rqBHNtHmfyGDdxt93kZM2CL3exrb2u2TdTaDyUkduFK9X0ivLlpI/3GFtA8\n8ijK1zhNAF59UPKL8hh6xsro95ZNaHu4/v7694gX/u1j/8OL3hK1ZYkHnUOm+2ANDmxhZuVcInVL\nmH5njYraCm0nr6gMwC7i++tPpjGzci4VveuUMFMRmyyrzNhRYWxnEUQOLeDjq8o45k81XPWCClD6\n6/AnCbeF+eGkgRT2KuD25TWO+6zb1ddhojNx9fKL7ZQQL0xZNhHR3IbwKJbnLiXkzg+84MgT+enC\nj/nZovWM+FIj0BhToNUdlDTl1QnkfVbPG99ciBCCrRv7sKdXwLP+Hjhpymquww9PGcimmyoocvcr\nShErxhbQcHwFpbO7txRixjCjeIinkSS9BmJq25E1nKra7TSFDuHEviq3aN3uvhQX5Tqu1xqRLvS4\n9qO5tolv8v/7L9n5bYTro5Pxw219OLQBSga3EApim+UWfOkZhvXeBQgKskKM6r81pkJDsuZf+pyC\nrJA1q4XNSIRQ1YXnfnUpU/51MZH8IOt29+PKNybwtqtKb/TjSDa8Fy2aum5vP6Ysm0hWqxrHXyfM\npSkU4v610+0omvKRZVSvqcGdn3DdvDPJL8rjjVvfB9Lr/PSRGrrzN1L0YkVKhmoAKMwfQYVqm2Vp\ny5ZZzoqm1AmuunsowNDDsIXCm5dOoHxkGW9fcq8jvHpvaw7BYIArX7gQOSTI2u8fZ/uGGo8sACGo\nfnAMojXMlGUqck9rSFOWe/iIpES0hOnTALc8dQG1/bPUOVIVDc2rrifPMmuVzq5SgQJDihGtYWS+\nXkYT0/ILoYXUfzzcrv0IkBUsojHUapu4+9WGqT00AGEJQaH+oeg8f1sLJ0xcqb5z0Vwq+g2I0Xh1\n14KpN6v3m/dwGYW9Cjj/fXhw6e12QFjJ01U8+X2VgvGg5Q/XjMzu4mwJBL8f9gotDS0seH+8fU53\nRNZlDDPyMiM4qiuE3kpdQnOFETs0pNpzGN671vbFFOfmUtFP1XJSEnq5rRG9uWkj9UP3qTwFA+9s\n7M/1C87msa+8RCQ/yJQ3rCKOR//Rcd6wgbscperjFSx05x+IiNRuFhtNbYbj0pDKIrkBhh+60xEJ\n9PbAPzii7yp61RIIBuxw2PI/fMrHV5Ux96tL7bDxUUNUxGHupiZy0XlGxoS7FC7pcw2BYIBd3/8C\nK4DG/lk8Ou45Gpt3qkARw+IRqZvqyCuCoGfhW/A1onSisxYJN+5fO82qLRet8O54ntaOrXvqpPYF\nw7zvd9rKJn5+6xLa9jkr4hdkhYjkBm1GIAqybEKa/sZl1Dfv87yfxlXPX4AE8jbtpWVIsb2/uaGF\n8j98Su1dx6sdAhBCRaiFJYFWI1E3ADInaESxqsZ6VXvKqN+3z9Z6Pq4fTEtDC9f97G5W3KLXEmVl\neHtjIZFcFf1WkJ3N4/eewrPnFTj6FO0rLeDKZRPI3dRE0X8eUDsrE76eJ8xuy+1B/b59kC1YMbaA\nyYsXZnZod3fAq8xPyhqSPkcvhJZGdP/KhfzfSZsxq2QMLtwCbcqHoqR/yCcap286NoOBAF/5tzIF\nBA4POxLaAsEAJz95rVXL7jmGH1KrkmkPj6rT7pIgbRFBcyjLzvzWjGtV7eGOLq6mXXvKsonkrd/L\na99RpeGn/X48c60W4fGggxLCkQhNh+fx/vcrEAiueiFaoUGbV8p7RZPfZlZud3Ta1NB5CvRXId0f\nbevDN545k7fuTTiM/Q7f/Ld/4M5HGTHnYX43NsTogaVJr03USXboGfDzEWodMBmRNlubGF1SyqrN\nmwiHI+RuaqLeauTYtwFqcyXBYIDpr01izpcWMX/cc9zw+Bk0HZ7HvtICW/sIBoPsKy1UvlGvMbWG\nCQSDbDbCp+ePf5bhvXc6zOzHFG+gKT/bHvOg/M0UFId47Csv2VYTjVCWQIQjSKEW/eePV004j/i/\nD/n868c6zt1XWkCrVcVl4gvnMqZ0EDMrz7E0UbXW/eiR1SpaUVoNQ3srH12gr7L02EVUExQ21mZ2\nLVBMWaZqfI4ZqUz4kxcnL0bQEWQcM3JoSKZk7ZGfkvQehhSmJTC9sGstojB/BG/X/JdvzH6AXlbd\nrHLLNlp8haoFZWeT7zzUfkb+1mau//14CnsV0I82SmZXUT6yjOePh8CYMDtq+xAojNjSkZdWFBTK\nNHDKb65gX2kB66y+RFNfuBCZn+UI+bbHHpY8PuUVCrNCNFoEOe2xcewrLWDeuX8HsB2tANNfm0RF\n/wH25BG0IXOCiNaIzYiyWiUtDS302hMBy65c/W4NkQbVxOuS668BsOuKHf7QWn62aD2tpYV2VN78\n8UuI1L1vf/u4mi6+OS+TkCiwoTO/09dW/i/vTo861eOZzlN6hrEOhKVgXySHQwpHMLrQWVZqxJyH\nqQ/H14jmj1/CoHwl3FWOPZY3P/+crLZo/qpOe3j5in6go/ciEsKSvM/qOeZPNWy+qYJmI1w6sC/C\nul197ei8va3ZMUFGmlGZUasqj0k4TIZTlk20TYH5RRajBFv7M89rD6pqt3P/svYzEG1KNb9xojqh\nnUXGMSMNB5FYGpHel+xj6uPzx0W1qGgSrdqef9jP7Odcd9/dQIteh20NSVeYLs7NZf2OQ3ngrCHk\nXbWXx6e8Qs4gVWdrz8zRNDe0UH3tUVSVFhIOh7lu/pkU9SrgoUkq7FOXBzGjatoignc+789188/k\n8Smv2C0mAP5s1eW67rEzmTttGcP7RMuNvH3pH1QiXUA1CXt8yisAXP+XsxlzxJFU1W63C8QKCe9O\nv5nJixdSnJNDfWurPbEdNeuAbzxzIaetbLJtzXdPU7bn8pEev00wYJVLihKlWQk93fBDxvcvNG3p\nXlU6DLsrpGb3OtDS1sqGxoFUZDnLSs0YX8VZWL6SI+HGd74CwFv3Kj/Jt4b+liMKVM24MQO2MDN3\nLg1H7+Nbiy7gocsUnepF/pFTFiGNQKH5Zywh0BLmh7MH0uenb9MrHLECAgq4a2wpm2+qYO60ZQwr\n3s66PdFipu4SY44adsr9G4VUQmFRrwIa9zTRuKeJ3E1K+NNamIZuPKj9bJf0uYZ7njiEcFuY2yYd\nTSAY4IEnP0FKyW2TBrJn5migBvq3b7mPCgpRBpRqMYKOIGOZkQMdjIFPeI1humscosxNmyzmU2Q1\ntXrDYgq6lMmsufW0llY7btPc0ELT4SosPAgUbG3hsamvMOzw3Q7V3asUfe7mJgTO+lWACvfMCViM\nyFm00V2aZNjA3Xy0pTfNh+czZdkES/qRNmGNWa/sxM0N+yDHFQEUkSBh8G1vcsLp1rv3LrQ1oMY9\nTby3vMo+ppn0M7ue4OQ7H2BnkeAvZ/2NL5Qd6fmtdZivnrDd7TwHv/BqR9Hd2moiDUxDCw26e3DM\nOVnDVXWVfOwAiVTKSs2snMug/DpHhf7BhVvYwEDeuvd23lr7T0BpANVrauhbF2anUTYi/9P6aMPJ\nojybPgAqxx5L5ZoIgX1hPmzsw5Q3La0lLPnwit+pYWsTY0Ta/7R53fT1/nm8EgS/8vKFbL4pGr12\n3+vquGmFAJi8ODXfz2kr1Xh1jpEZ+KDhJfRr9KSq3d0K88Mkq5WUSi2l6N9XxFQED1rqt+4OC+87\njpcf10wkt1XZfQfDg898RtPg7Vy5bAIIQRvQNqTImTdgwKy229SWzb6SAv79nUUQcLaFOHHQDo5d\n+DXmn7HEofK7+yLp3KBp88chS6ViFi7pR4dpT/h7PSuMzre602Y4HLa3mxta+N6l5RaxRQmuek1N\n9Lprj2Ly4oXUWs+J5Aapqt3uCF5IN/yQ8fRAm+U6IhhE6qYy/c4aR5K5Cc/F09j/80U6EEP5St44\n/X2qarfz1tp/cswhOxzFkOtDORQXjLAT4kf3U5UiZmbPhUoYOmwlJ9/5AL+95O98oexI/vRrVZ3l\nhNPL7HycE6zoNFDzbMF3x/Pe8irybtpLUa8CSmZXEZqYRSQ3YEfKBfZF+GhbH6bNH88xf6ohMCXM\nsIHRXEewEnrzs2gpLeC+N7aQs7GRltxiR7sNrTFpPLPrCUAFGBX2it12R8B1BbqDQWU8M+pOuJlY\n9Y4aIMrMdIdKq2Yq2zbVOGL8VQgpMVltug7W6sl/coSjhqUgiLR7nkRyA3GrDhMUuFMZmsPRDrQF\nWSHW7erLLYsuYP441YF23sMTHQwHotrMe8uraDi+wmZC8674J+FIhCnLJrJn5mj2gO330uYtXVSx\nfGSZY0JrBgfwlVcvojgnh4q1C9slFHQV9ncxRx+dQzyNaPqdNRxWWqvMbBZD6Sofo1nyZ3jvOj7e\n25+TjzDyqQxoTeu0lU30Gq8incyEUC+Yws8eqyr5gl2KUen0kIp+AxgzRpVeOh94cNcTTF68kFvy\nfsvw3rV83lLKlUvPsf1WMj+LSI4yh9+y+ELKR5Yxf6CVg7RURfrV9nfOeY1L+jh9vOr7vsL8cWWO\nCvs6rF7V8bQCxUJvKV97Gioy9BhmNGP8LEqI1qOC2AXHy545efHClMMR9SJeay1sJqpqt9PSK0Ao\n2yzf6+IWUpIVUmYvgIKrnCXr7bYSlmYzasA2Pq4fzMQXznVka2cJyYeTHnUkvgIUBEIU5+YiW3SB\n6AAAIABJREFUhNKsrnlpAqNGHkFRb2VTML+NZhg6qqjBMkGetrKJFWMLKMjOtsv2Nze0EA5H7Mlb\naJkpQdXo04VPQdWr0gxJ+wYytYW4rxGlByatpVLo2E6GRVkfUoHbYlK1YwwV/QfYPqSKfjiizP5y\nxt8Y3nsnhfkjWXhNOQuZRfUapW3MmltIa2khN//tTBVKvkjX7VtpP8OcS4nm1Wkrm3jwXqclJlK3\nJOa8tR+do3KyrOTgirw6/jrhRaYsncCcL6lI2TEDlNCrfVpv16j1o2GP8ufSX/mSdLi2qRH1RPQY\nZtRZJJKy3IQSS0DKpPftYXMgEo0LH95bdVjMapX88ewlBIIBfvnRdEpOV1LG2xZDOLZPbBFTUMyp\nonedXU3cDbNacLgNENAUCtm277cu/wPBgLDL8US2jWL+WJVPpYsbamak/WA/X2SZHi2b+5OnPkuv\nygjfOCvaIVbD1JLc38vMWUhFKOgu7M9n+egemMmwyhwlIHtUl0rm4UhE5cINmgdEtZzqa4+itbSa\nSH6Q2v5ZrBhboKqKdKDFicmkzPnoVXrprbXjHddWWVG+Ff0HICRktcX6mL/xjKqHVzp7FQBbb6mk\n+fB8KkrNPElihEr1zGhZs6ra7dy/doJtTVAh4qr6RTpr1GU8M/KKjCpBOTkjdUviMhetEekPrlXS\n9vg2TAamm83pxmEAgeZorlFWm+QLg0pZUHkFn/RRNZ0qD1Nhmo1tVoUHUYyM1Du0HRmp55jiBntf\nuA1amoKMmX05AG98c6Gq2puvyukfc8hmTJhFTb3Qb4cqmljytMVUbnUezyvKgz3RpmduqS+e30WH\n0pomOx8+NFI1n5qBDdXv1gCpa0duDf1Nq+4aRMOR55+6mrZIhFueusBy5M9yCFjhcITr/3I2jUOK\nmD/uOZUE36vGNmWZY+wo3JYaNVaVr6jDtX/9yTTjHHXd/LIl1jHlLnjL0rgumX0N1dceRdPhecj8\nIG9u2sjJdz4AYwvsYIVkyES6zXhm1FnoH1urw6lMME0wkbol0LaOSN1UgyEtpMKq+6ZNcB9etcCq\nErGVSN1Uyo9rpvqDfHRVXN33p6J3HRGU38hEcyjL0S4Z4Pz3lb9H3CRo3ZdN4SCVKzWj7Dcc3X8n\n63b3ZerzF9C3AZZe+0dH36BPXh3LjLIAVy9X0lf1mhrbxKmhv0PlsHnMmD4LqGnPZ1Xvk8Q8tz+1\nlANVIxJC/ByYgOoYWQ1cJ6XcnfiqHoi2dZQfh5rDOvjMojs3UnHEz6ycS0PLPiBMVkCZugITwly/\n4GwOXx49r3S2ajhXfe1RFJ+b6yhlZMJcNxJp4V5MWC/8XuPW1V28gqy8zHsmcjc1OcK+y0eW8eC9\nVyQM3An0nUdlX6hY67ZspJ9+Mp4ZuSOjdNhnsiKO0Y6Tc9v9THeJFJMhzR+3hMZmQUs4J6b/CmBJ\nd/l846yBVhuKQh6/9xRr3APItrrSag1JCFUhQfc/CWbBZx8WMv3OV5hz75kUH/OEPab544CQsiOP\n6reV1Vf8kXuvmwTXOsewx/JttRx9CHnr9+KFqtrtqt7UJKekOGP8LMckNrtGavhBA/sVLwF3WB2V\nHwDuAG5P85iSot3mU3fVlHY+w13mpqJ3HfUt0a7DqhCwJL8oz05V0NC+1vvXHmsXS4auCXc3NTdz\n8dff5ZcfTVfv4lHeJ9pGx7lf+4bMdhELvpUa7blpV1dUyATazXhm1FnocjbzrZyhlCeYWd9O1tsM\nibZ1FGbnRKNPrMoQGnPutZyLJK5wa2pI7uoM4baw1yUONLVmEdgXZvqdr7B5Qx+GnrHStgc/WDPN\nnmxFlvmNlVUORnP/2mlUr6nhNFJT632kB1LKF43NN4BJ6RpLdyKVPCSvskMQR0PPGk5xETZzW7/j\nUL5QdiRv3Xu7Z2Rc0k7S1n3WfnQO3xq6jynLJjoYrT5vwaUqYq7f2AL2lRbQFIrSdn1rq734J3tu\nZ9CewJ1MCj4S0t2GcD9g9OjRctWqVZ26R3ullw6db9bGE1YxRbNWnt5vMCN9/3ianG6lfP/aaXxr\n6G8Z3ruOD3f1Zdrccfx+6isgVcl37XzUUpA9LlcbDEQxjaFWbnjzhw6GqwMYTlvZ5AhN1ZqO6bw0\nz9NwE75ZEsR9TiZIVR2FEGK1lHJ0useRCoQQS4CFUsqYSSyEuAG4AeDII48ctWHDhv09vC5Be5iR\nrkRglh0yMWP8LO55bBFtWXD2Y1fz1r3tVyjdzEgXQZ2ybKKDJsxxf/LqWPb0CvBgzTf59rA5dgoF\neNNRV6E99Li/aLc99NUpzagn2bPbq3I7qoabxVmtSdncqOrCFZZbvZI8chbioaWhRfl+rAKLJx+2\nhce+upRhh+5m3e6+3Pf6Fkev+oSQ9RRm6UKnzsxqUyPSZX5ufMcK225naRAf3QchxMvA4R6HZkop\nn7XOmYkqozbf6x5SykeBR0EJe9001G5HKr7c9pQd0o0eEzGiZD4WcPpYJy9eyJjSKBOK1C2x14VP\nXh3LYaW17Nzdj+o1NYSHqujboBAUZGd3aPE/WGo6dnZFSps9e3/8MF7FPXWvj4bdKjFv3vVaA4pe\nF6nTeQrzHPv0fRZMUklo6znUTqAN7IvYyXkLvvg0eUV53sRhNApsDLXafqv6ffvsgogLLr2CkjiN\nsMzSIBBtD+FGKjb/nqwRZRKklGclOi6EuBa4CDhTpsOU0cNgRuB+Y/lATji9HJjV6bwz1XRzFrj8\nqNXv1lBu7SoZvIv8wggn9drOS9f/0Q5MinaC9dbiOoOO+HAzkXY7xYwOJHt2POkjHtO7bdLRAPz2\nZVWoVOdJJGoGqCezJpKtt1Sy4pYnCewL88NTBvKT/2xjwRef5qQjjXvFG0PWcDbsthJbXWaDGeNn\n2SV8omZCxTxHnK62pyyLDUzwkXkQQpwH3AacLqX0HXykXnZI15o84X3Pw+0qqDtl2QTbx+pMpp/H\nnHuVOTC/MEJ+7xNtLUl1f1bMaPTAUqpq2xcs0JmOuz0RXWmr+SpmeVcXXDbtLnzs/oXu9XHC6Wri\nlo+wcogsZhSvGWCgr5q0Gj9btJ6i3ltUnbs8+O3LWzj8sD12GHgy6BBNHbQwpnSQnfhWvabGLnJa\n/a4KaS938Z5UCULfc8bszkuWPjqE2UAu8JJQyWhvSCmnp3dImQ09T1fc+YC13TljzYzxs6geW0CD\nRVN6G2DGbCVchtvCNDcGuev6cqbfWQOotcJsMuiuhZkI7elwnWrkYqYzs6TMqCvs2ZC5Nu3OSh9e\nrS7ihaeaYepFvbc4Ms9B9VaqHNS+vj9mryaTEWl879Jyh4YUz3ToIzMhpTw63WPIVCRrIaOL+cZb\npFMpqDt58UKqxxaoe/U/hE9/MpoNwaBdQ27y/1vK5W0RinpFgAjT73xFJe1aTKSi3wBbI2p3KoRV\nDeFgodOkzMi3Z3vDU0tIYfLoyc29qv+8PnfoGR2faHpSz5g9y1HCJ2BVITefY0JnvA89w/u+fl8g\nHz5UIJCuVxkMBskvyrWDJ/KK8mhpiOYz6b5eZpPJdmtE4BSO26khpXRPMo+5dTaaLiPt2e1ZNN2B\nCR1lCu35YXWmdDx8b5LKVXpwafvGYEp6ulq3Lv7qpRHp4pSZOjl9+OgI2ptwm2idMO8VTYH4rn3v\nymEvMmP8LHrdqdt7x6992eFw6qzhVgeBzEhO7S501mfUo+3Zuh7WnHvPZOrNysHfFdJ/KjkS0YnZ\n9QxAM6JGw8YN0Xeya4BZfqR4GpLfF8iHjyiSCZFdgfjJvx3vRZRKQnEmoLPRdBllz+6MWUlHx51w\nejcNLgV0lVlMa0NeFbcBu4GZzj2a97DafjCOuc6Hj56IrtQi4lWm15hjmd27ejwHU+mtgzLz0bSh\nlleoKgnV725JaUJ1FPuz1UEyjUZvf/LqK57H493Phw8fUXSnT7UrNKL498xMHFDMqKeblfb3+LWG\n1FmN6ECW1nz4SCcOpn5dBxQzShVeNtShZ+wfM9X+nEy+xuPDR/ch04XfnsbADkhmlGmTor3oKeM/\nmOzZPnykEwcDTR2QzChVZLoN1YcPH5mPTBMee6qQeFAzIx+dw8Fkz/bhw0f3wmdGPnz48HEAoacK\niT4z8tFp9JTJ7sOHj8yFz4x8+PDh4wBETxMS09J2XAixA9jffZH7AbX7+ZkdhT/Wrke8cQ6WUvbf\n34PpTqSJvjqCnjJ3vNCTxw77b/wp01damFE6IIRYlWov9nTDH2vXo6eM82BCT/5NevLYITPHH0j3\nAHz48OHDhw+fGfnw4cOHj7TjYGJGj6Z7AO2AP9auR08Z58GEnvyb9OSxQwaO/6DxGfnw4cOHj8zF\nwaQZ+fDhw4ePDIXPjHz48OHDR9pxUDEjIcTPhRAfCiHeE0I8LYTone4xmRBCnCeE+EgIsV4I8f10\njycehBBHCCGWCiGqhBAfCCFuSfeYkkEIERRCvCOE+Fu6x+JDIdPpMR56Cp26kel0e1AxI+AloFJK\neQLwMXBHmsdjQwgRBH4DnA9UAJOFEBXpHVVctAEzpJQVwBeBb2bwWDVuAdalexA+HMhYeoyHHkan\nbmQ03R5UzEhK+aKUss3afAMYlM7xuHAysF5K+amUshX4C3BxmsfkCSnlFinl29bf9ahFvjS9o4oP\nIcQg4ELgsXSPxUcUGU6P8dBj6NSNTKfbg4oZufBV4Pl0D8JAKfC5sb2RDJoo8SCEKANOBN5M70gS\n4lfAbUAk3QPxEReZRo/x0CPp1I1MpNsDrlCqEOJl4HCPQzOllM9a58xEqazz9+fYDjQIIYqAxcCt\nUsq96R6PF4QQFwHbpZSrhRDj0j2egw0+PWYeMpVuDzhmJKU8K9FxIcS1wEXAmTKzkqw2AUcY24Os\nfRkJIUQ2akLPl1L+Nd3jSYBTgYlCiAuAPOAQIcQ8KeXUNI/roEAPpsd46FF06kYm0+1BlfQqhDgP\n+AVwupRyR7rHY0IIkYVy4p6Jmtz/Aa6UUn6Q1oF5QAghgCeAnVLKW9M9nlRhaUbflVJelO6x+Mhs\neoyHnkSnbmQ63R5sPqPZQDHwkhBijRBiTroHpGE5cm8CXkA5Fp/M4Al+KnAVcIb1HddYmocPH+1B\nxtJjPPQwOnUjo+n2oNKMfPjw4cNHZuJg04x8+PDhw0cGwmdGPnz48OEj7fCZkQ8fPnz4SDt8ZuTD\nhw8fPtIOnxn58OHDh4+0w2dGPnz48OEj7fCZkQ8fPnz4SDt8ZuTDhw8fPtIOnxn58OHDh4+0w2dG\nPnz48OEj7fCZkQ8fPnz4SDt8ZuTDhw8fPtKOjGBGQogfCCHS3hJaCFEjhEjYf6WT958ihHixq8/t\niRBC/EEIcV+6x+EjFgcLPfYkCCHGCSE2pnsc3YkOMyNrojQLIRqEENusxaWoI/eSUv5YSnl9R8di\njadbf6yuWDyllPOllOd09bk+QAhxihCiXggRNPb9Ls6+Odbfy4QQLdY5e4UQq4UQ3xdC5Hrc/1oh\nhBRCXLF/3qh98Omxw/cps37XA67RaDIIIT4y57MQ4lT3HLf21QshsiwaCFtzrEEI8ZkQ4nEhxDEe\n9y6yzkm5lXxnNaMJUsoi4AvAaOCHHoMSQoiM0MC6EwfjZM4wrELN5y8Y+04DNrr2fRn4l7F9k5Sy\nGBgIzAC+AvzDakRm4hpgJ3B1F4+7K+HTo4/24F8oetD4MvChx77XrT5OWH8XAb2As4BmYLUQotJ1\n70uBfcDZQgivtvMx6JJJKaXcBDwPVIItcd4vhPg30AQcJYQoEUI8J4TYKYRYL4T4mr5eCPEjIcQ8\nY/uLQojXhBC7hRDvWh069bFDLW68WQixSwjxjBCi0Hp+icG1S4QQAUvSrRZC1AkhnhRCHGrc6yoh\nxAbr2Mx47yeEuAGYAtxm3XuJtb9GCHG7EOI9oNGSHvTz6oUQVUKI/zHuc60QYqWxLYUQ04UQn1jv\n+hu9CLbz3KAQ4kEhRK0lrdyUSNqzxrzJGuNHQogzrf0nCyFet+6/RQgxWwiR4xrDN6wx1Ash7hVC\nlFu/1V7r++ZY544TQmwUyuRTa32rKQm+8UVCNfvabd3vhGTjNSGlDAFvYBGSEGIAkAM86dp3DE5m\npK9vlFIuAyYCpwAXGs8fDJwO3ACcmypxpQsHMT2WCCEWCyF2WHTwLeOak4UQq6x5uk0I8QvrkJ4L\nu617neLxvHjXIoR4SgixVQixRwjxLyHEccaxPwghfiuEeN6697+FEIcLIX5lfasPhRAnGufXCCHu\nEGrd2GV917w436Aj7+qGmxmdBjzgsc+LXsJSymop5TeA5cCPXKdcA8wB3gOmxnl+zE079A+oAc6y\n/j4C+AC419peBvwXOA7IArKtF/otkAeMBHYAZ1jn/wiYZ/1dCtQBF6CY5dnWdn/r+N+BhUAf676n\nW/vHARtdY7wFtUANAnKBR4AF1rEKoAH14XNR7Y/b9Dt5vO8fgPs8vsEa6/3zrX2XASXW2K8AGoGB\n1rFrgZXG9RL4G9AbONL6Jud14NzpQJX1nn2Al63zszzeYxjwOVBibZcB5dbfo4AvWr9ZGaqT5a2u\nMTwLHGL9tvuAV4CjUJJSFXCN8Xu0Wd81F7WYNwLD3N8TOBHYDowBgqiJXGNdF3e8Hu82C3jW+nsS\n8EfU/DH3fWqcvwy43uM+/wIeMLbvBN6y/n4fmNFRuumufxzk9GiNbTVwF0oIOQr4FDjXOv46cJX1\ndxHwRWM+edKKcW/Pa63tr6K61eYCvwLWuMZYi6KrPOBV4DOUdh0E7gOWun7Dtdbvdyjwb6I0Yn/P\njr6rx3sNBiLWswIoGsxH0Zvetwf4stea5PoG2zzuW4GyNryX0hzu5ORvAHYDG1ATWy/Iy4B7jHOP\nAMJAsbHvJ8AfPCb/7cCfXM96AbVADbReso/HeOwfy9i3DjjT2B4IhFAEeRfwF+NYIdBK+5nRV5N8\npzXAxV4/JooIxhrbTwLf78C5rwI3GsfOIj4zOtqadGcB2UnGfivwtGsMpxrbq4Hbje0HgV8Zv0cb\nUOga853u7wn8H9bCaZz7EYqBtWe841ALpQAeAr6GIsZtxr7HjfOX4c2M/gL8ztj+BIspA3cA73aU\nbrrrHwc5PaIEmf+6zrlD/94o5ns30M91ThnJmZHntR7n9bbu1csYozmPbgbWGdvHA7tdv+F0Y/sC\noNr9PTv6rgnmzcUogfDfxvzX+5qBXGv/tXgzo/OAkLH9QyymjBJmwsCJycbSWTPdJVLK3lLKwVLK\nb0gpm41jnxt/lwA7pZT1xr4N1kDdGAxcZpkEdgshdgNjURP3COs+u1Ic32DgaeM+61Af5jBrTPYY\npZSNqIWsvTDfEyHE1Ya5aTfKVNIvwfVbjb+bUItne891vIt7TCaklOtRTOZHwHYhxF+EECXW2I8R\nQvzNMjvsBX7sMfZtxt/NHtvm+HdZ31VjgzVWNwYDM1y/+REobSjueD3whvX8SpSEvUJK2YD6Hnpf\njMnBA6Uo/xBCiFOBISgCBfgzcLwQYmQK99nfOJjpcTDKLGiO8wfWvQGmoUy0Hwoh/iOEuKgd9/a8\nVijz+E8ts+Ne1MIOTpppD72A83dKRC9d9a7aVPdlYIW1b6Wx7y0p5b4E14NBLxauBuaDbTJejhJe\nEqI7HZnS+HszcKgQotjYdySwyeO6z1GSWG/jX6GU8qfWsUOFEL2TPM+81/mue+VZH2gLipgAEEIU\nAH1TfB/P/UL5Fn4H3AT0lVL2Rqndbmd4V2MLyvShcUS8EwGklH+WUo5FTWqJshOD0lA+BIZKKQ9B\nTfDOjL2P5T/QOBI1F9z4HLjf9TsVSCkXJBmv+71agP8AE1Cm0Q+tQyusfSeQhBkJIY5AmVU0YV6D\n+gZrhBBbgTeN/T0JBzo9fg585rp3sZTyAgAp5SdSysnAANT8WWTNzXh0HX1Q/GuvRGkQZ6HM1GV6\n+MnumQAm7Sail468qxc0MzqN6JxfYexLRXj7H32tEOJLwFDgDkuo3YrS5K4USYK89ktUjZTyc+A1\n4CdCiDyhnNPTgHkep88DJgghzrUkjzyhnOGDpJRbUI7R3woh+gghsoUQ2tm2DegrhOhl3GsOcL/F\nJBBC9BdCXGwdWwRcJIQYK5TT/R4Sf49tKNtsIujJvcN63nVYTuRuxpPALUKIUmthuD3eiUKIYUKI\nM4QKX25BSWcR63AxsBdoEEIcC3y9C8Z2txAiRwhxGnAR8JTHOb8DpgshxgiFQiHEhUKI4iTj9cK/\nUL6J14x9K619W6SU1V4XCSEKhBCno3xib6Ei6vKAy1GBCyONfzeTAnFlKg5QenwLqBcq2CXfGmul\nEOIk61lThRD9pZQRlCkT1DzaYf0fl7YTXFuM8pvWAQUoS0Jn8U0hxCChAjtmovxxbnT0Xb3wL5Q5\n7ssoHxUov+gQYDxxmJH1zCFCiIdRJsS7rUPXAC+h/EWaXipRvqjzE734/gzxnIySHDYDTwOzpJQv\nu0+yCOVilFS+AyUFfI/oWK9C2Zk/RPkSbrWu+xBYAHxqqa4lKB/Bc8CLQoh6lBlnjHX+B8A3UWaX\nLcAuVBhwPMwFKqx7P+N1gpSyCuU3eR1FLMcT/YG7E78DXkRFrrwD/APlrwl7nJsL/BTlWN2Kkp7u\nsI59FyXt1Vv39CKE9mAr6rtuRqnt0w1txYaUchXKvzPbOn89yj6dbLxeWG6ds9LYt9Lat8Lj/NnW\n3NiGckAvRgWGRIBLUMzvj1LKrfof8HuUn+O8JO+fyTig6FFKGUYJOyNRQQK1wGMojQXUb/WBEKLB\nGsdXpJTNUsom4H7g39a9vujxLM9rUQEyG1AaZZX1Pp3Fn1G0/ClQjQpycKCj7+r1MCnlx6jfdauU\ncre1L4JieIfgFOoATrHuuxflizwEOElK+b4hvD1s0ouU8jPgTySxJgjLyZRWCCHuAQZJKb+a7rEc\nCBBCnA/MkVIOTuMYxqGc4IOSnesjs+DTY3oghKhBBdTECAUHA9Ke/CaEECiV7rN0j6WnwlLVLxAq\nz6kUFeL8dLrH5aNrYZlG3hFC/K0bn+HTo4+0IO3MCHgb5Xz/XboH0oMhUDbbXSgz3TpUqKyPAwu3\noH7b7oRPjz7Sgoww0/nw4SMxhBCDgCdQ/o3vSCnbE5rsw0fGIxM0Ix8+fCTHr4DbSBxJ6MNHj0Va\nQlP79esny8rK0vFoHz4cWL16da2Usn+6x5EIQiUtbpdSrhZGXTjXOTegQtApLCwcdeyxx+7HEfrw\n4Y320FdamFFZWRmrVq1Kx6N9+HBACLEh3WNIAacCE4UQF6BqnB0ihJgnpbQLUEopHwUeBRg9erT0\n6ctHJqA99OWb6dKISN1UInXJC9qmep6PAxNSyjuklIOklGWoFhevmozIR2bAp9POwWdGPlKGT2w+\nfPjoLvTIciY9HfaCHnrLsR3oOy/2vLZ1YNWzjHeej4MHUvVcWpbmYfgwkCo9+0gMnxntR3SJVtG2\nznGfZBO+I4ThvsYntp6PUCjExo0baWlpSfdQegxkuBZV6QggGxH0Lr4vwzdaf11r/a+61ovt3Z0S\nlhry8vIYNGgQ2dnZ6R5KQvjMKA0I9J1nLehBEAX2dqRuapQBbBulTrar/AeVlpQ1PC1j9tGzsXHj\nRoqLiykrK0PEdFQ/cCHbPgVAZCWrcexxbagKFUkfAJHneQ91/1JE1lGdelbsPTt/H1D96urq6ti4\ncSNDhgzp9P26Ez4z6iaY2kOMZrFtFMgmIAyyPmqOsxhNpG6qddxEWO2z7uH1HK/9jmdmDU+ozSS7\nxteIei5aWloOOkbkBa+F3r1Ptn0KsoVoneEwyEbFnOIwpejNWpBtn3YJI+kKCCHo27cvO3bsSPdQ\nksJnRl2IhIt1m6Gya0akoRlM6C0no4qB174EcD+zrQNmA8ss6DOgno+DiRFpBoPV29HeTumaFpLl\nFsfcP1SltkWe43h7mFK8MXeWsfWU391nRnHQYS1A+3Rc/hWyhkNotfo7e5RLwwliMxpH800P6H5o\nlhYVTyMK9J1nmfr0vcP28XjvZGtxoliNQ9ar661x+wzJR6bDwXRki+vvCLqXnq39iDx78Ve0grXP\n1IyiiM8YLOZl30vgFazclSa4Aw1+aHc8tK2D0Gp7cXeHNZvb9t+ht9QCbmogbeuse72FY3KLYuzJ\nTzj6t6P5phvWOcn8RpohynrnM62xeQVSROqmKuYVWu1iiIqRRbYOj/qxfPjoAILBICNHjqSyspLL\nLruMpia3KToxLrjgAnbv3u3YJ9s+9dR6RNZRlpYSZNny1bz2+tskb+pqCW0W4xoy9Dxqa5N1VBfW\nP+m6vwTCjvEpBtjkZJKuMatxF4IoRGQdxXXX38NTC3+TVLOL9x16EnzNyAV7odYLcpzFu11w+H/C\nVri2h0/IfG4CeGkobn+P0yRnaF4ejMz2WXmdb44vZsztg+9z6lm44pHXAVh44yldcr/8/HzWrFkD\nwJQpU5gzZw7f+c537ONSSqSUBALeGsXfn5uNyOptb7uPqz+02WwtmjksW/4mRUUFfOmUEdbZSqgT\n2RXWuZaJzTHnveT0cIw5Liks7Svqh4oyKfA1JBO+ZuSGpRHZkPVqgbf+RbaNsjSI6Dah1R4+oSTI\nHqX+ESSqISVDNOAhKYPMGq60rOyT1XOsvwN95zmYgf0utlkuatLzer6vIfnoCpx22ml88vHbfLb+\nXwwbNoyrr76ayspKPv/8cxYsWMDxxx9PZWUlt33vRsUAZAtDjv4ytbW1AMyb9xRjTrmYE0ddwI1f\nv51wWyPIFv75wkpGnXw5I0ddylnnXk9NzSYe+d1T/OrX8zhx9GWsWLmaHTt2MOmyGzlp9AmcNLqS\nf7+mSifV1e3m3AtupHLERK6/8S68OhqEw61cN+0Ojh9xDieMPJdfPvRHQPK7uYs4+ZTJjBw1iUmX\nf5umJtVY9bppP+Dr37yTU079H8qHncOy5f/hq1+7i4rKs7juq4oRy7ZPKSoq5Nvf/ja4MVE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4JLr2B0SamDoSy49AqHtmIeG11SSnFODmNKB/Hu9JvtY/WtrdS3tjreSY9D7wtLyYg5D9vvYRJf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\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f4a791aa4e0>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% plot samples\n",
+ "\n",
+ "xsp = projfda(xs)\n",
+ "xtp = projfda(xt)\n",
+ "\n",
+ "xspw = projwda(xs)\n",
+ "xtpw = projwda(xt)\n",
+ "\n",
+ "pl.figure(2)\n",
+ "\n",
+ "pl.subplot(2, 2, 1)\n",
+ "pl.scatter(xsp[:, 0], xsp[:, 1], c=ys, marker='+', label='Projected samples')\n",
+ "pl.legend(loc=0)\n",
+ "pl.title('Projected training samples FDA')\n",
+ "\n",
+ "pl.subplot(2, 2, 2)\n",
+ "pl.scatter(xtp[:, 0], xtp[:, 1], c=ys, marker='+', label='Projected samples')\n",
+ "pl.legend(loc=0)\n",
+ "pl.title('Projected test samples FDA')\n",
+ "\n",
+ "pl.subplot(2, 2, 3)\n",
+ "pl.scatter(xspw[:, 0], xspw[:, 1], c=ys, marker='+', label='Projected samples')\n",
+ "pl.legend(loc=0)\n",
+ "pl.title('Projected training samples WDA')\n",
+ "\n",
+ "pl.subplot(2, 2, 4)\n",
+ "pl.scatter(xtpw[:, 0], xtpw[:, 1], c=ys, marker='+', label='Projected samples')\n",
+ "pl.legend(loc=0)\n",
+ "pl.title('Projected test samples WDA')\n",
+ "pl.tight_layout()\n",
+ "\n",
+ "pl.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/notebooks/plot_barycenter_1D.ipynb b/notebooks/plot_barycenter_1D.ipynb
new file mode 100644
index 0000000..8acaeec
--- /dev/null
+++ b/notebooks/plot_barycenter_1D.ipynb
@@ -0,0 +1,308 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# 1D Wasserstein barycenter demo\n",
+ "\n",
+ "\n",
+ "This example illustrates the computation of regularized Wassersyein Barycenter\n",
+ "as proposed in [3].\n",
+ "\n",
+ "\n",
+ "[3] Benamou, J. D., Carlier, G., Cuturi, M., Nenna, L., & Peyré, G. (2015).\n",
+ "Iterative Bregman projections for regularized transportation problems\n",
+ "SIAM Journal on Scientific Computing, 37(2), A1111-A1138.\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Author: Remi Flamary <remi.flamary@unice.fr>\n",
+ "#\n",
+ "# License: MIT License\n",
+ "\n",
+ "import numpy as np\n",
+ "import matplotlib.pylab as pl\n",
+ "import ot\n",
+ "# necessary for 3d plot even if not used\n",
+ "from mpl_toolkits.mplot3d import Axes3D # noqa\n",
+ "from matplotlib.collections import PolyCollection"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Generate data\n",
+ "-------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "#%% parameters\n",
+ "\n",
+ "n = 100 # nb bins\n",
+ "\n",
+ "# bin positions\n",
+ "x = np.arange(n, dtype=np.float64)\n",
+ "\n",
+ "# Gaussian distributions\n",
+ "a1 = ot.datasets.get_1D_gauss(n, m=20, s=5) # m= mean, s= std\n",
+ "a2 = ot.datasets.get_1D_gauss(n, m=60, s=8)\n",
+ "\n",
+ "# creating matrix A containing all distributions\n",
+ "A = np.vstack((a1, a2)).T\n",
+ "n_distributions = A.shape[1]\n",
+ "\n",
+ "# loss matrix + normalization\n",
+ "M = ot.utils.dist0(n)\n",
+ "M /= M.max()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plot data\n",
+ "---------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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etbBvLexbD7HJMOBY6H8sDJwAw04Ht7NV/Up1RpNiiFpTUkG028XoAUlOhwLAMYOTEbHG\nTWpSjCCNtbD4j7D4cfDWQVQc9BsHx1wMdRVWgtz0DmAgYySc9WsYfiY4NK5Wqc5oUgxRq4srGDMw\niWhPcNSAJ8ZGkZeZoDPbRAqfD9a+Ah89ANV7YeyFcNJt0Hc0uNxfPbahBrZ9BB/eD3+/1CoxnvUb\n6DfGkdCVOpLg+ERVXeJt9rGupNLxQfttjbc72xijK2aENW8DvD4b/vUDSBwA310Alz4H/cd9PSEC\nxCTAmFlw01I4+0HYvQKePAU2/LPXQ1eqM5oUQ9DWAzXUNTUHXVKckJXCwdpGSsrrnA5F9ZSGavj7\nt2DDGzDjPrj+I8ie5t9rPdFw/E3wo1UwcBL84zpY/lTPxqtUF2lSDEH/XRkj+JIi6IoZYau2DOac\nBzs+hVl/hpNuBddRfITEp8PV/4QRZ8M7P4OFD4LWLqggoUkxBK0priC5TxS56XFOh/IVI/snEuNx\nabtiOKophWfOhgMb4fKXYOKV3TtfdBxc9hJMuBL+/RAsuCswcSrVTdrRJgStLq5gfFaKYytjdCTK\n7WLcoGQtKYYbbyO89h2oLLFKeDknBOa8bg/MegJiEuE/T0D6MJgyOzDnVuooaUkxxNQ2eNmyv5oJ\ng51ZVLgz4wensH5PJU3NPqdDUYFgDMy/DYqWWAksUAmxhQic/VsYfha8e7tVNauUgzQphpj1uyvx\nGYJmJpu2JmSnUN/kY8t+XTEjLCz7P1g5B076GRxzSc9cw+WGi5+CtKFWibR8Z89cRyk/aFIMMWtK\ngmsmm7Za5mLVKtQwsH0RvHcHjDwXTru7Z68VmwxXvALGBy9fYfVyVcoBmhRDzOriCrLS+pCeEON0\nKO3KSutDWny0drYJdTUHYO53IWMEXPTk0fUy7ar0YdZ4x9LN8M5tPX89pdqhSTHErCmuDNpSIlgr\nZowfrJ1tQpox8NZPrJloLn3O6gjTW4adBiffZs2Ws/Ht3ruuUjZNiiHkQHU9uyvqgm7Qflvjs1LY\neqCGmgav06Goo7H2Vdj8Dsy4B/qO6v3rn3SbNYn42z+xxkYq1Ys0KYaQNcXWIr7BnhQnZKVgDKzT\nRYdDT+VumH87ZB8P025yJgZPNFz4V6ivhLd/qgP7Va/SpBhC1hRX4HYJYwcG53CMFuO1s01oMgbm\n3Qy+Jrjgz+3PY9pb+o2FU++EjfNg/evOxaEijl9JUURmishmESkUkTva2R8jIq/a+5eKSG6b/dki\nUiMi2nreDWtKKhjZL5E+0Q5+WPkhNT6anPQ47WwTalY8Z62JeNavrOERTjvhxzB4ijUVXPV+p6NR\nEaLTpCgibuAJ4BxgDHCFiLRd82U2UG6MyQMeAx5us/9R4N3uhxu5fD7D6uKKoB2f2NYEe8UMFSJq\ny+DD+yD3JMgPklll3B644C/QdBg+uMfpaFSE8KekOBUoNMZsN8Y0Aq8As9ocMwuYYz+eC8wQew4y\nEbkA2AFsCEzIkWnHwVqq671fjgMMduMHp7Cvqp59lfVOh6L88eF91oLB3/hDcC0AnDEcpt9idf7Z\nudjpaFQE8CcpDgKKWz0vsbe1e4wxxgtUAukikgD8HPjlkS4gIjeISIGIFJSWlvobe0RZXRScK2N0\npCXOlskGVBArXgarXoTjfwiZI52O5utOvBWSs63p5pqbnI5Ghbme7mhzP/CYMabmSAcZY540xuQb\nY/IzMzN7OKTQtKakgvhoN3l9E5wOxS9jBybhcYlWoQY7X7PVZpc4EE6+3elo2hcdB+c8BAe+gGVP\nOh2NCnP+rJKxG8hq9Xywva29Y0pExAMkAweB44BLROR3QArgE5F6Y8yfuh15hFlZVM6xg1Nwu4Ko\nausIYqPcjBmYxMpd5U6Hoo6k4BnYt9YepB/EX7hGnmtNGr7wQRh3MST2dzoiFab8KSkuB4aLyBAR\niQYuB+a1OWYecI39+BLgY2M5yRiTa4zJBf4X+K0mxK6rbfCycW81+bmpTofSJZNzUllTUqErZgSr\nmlL4+Fcw9FQYc4HT0RyZCMx8CJob4P0enodVRbROk6LdRngzsADYCLxmjNkgIg+IyPn2YU9jtSEW\nArcCXxu2oY7emuIKmn2GSTmhlxTrm3x8safK6VBUexb91upcc84jwdW5piPpw6xON+v+AcXLnY5G\nhSm/Fhk2xswH5rfZdm+rx/XApZ2c4/6jiE8BK+wqyEnZoZcUwYo/VDoIRYwDm6xxiVO+B5kjnI7G\nf9N/AiufhwW/gNnvh0YyVyFFZ7QJAQW7yhnRL4HkPlFOh9IlA5L7MCilz5dJXQWRD+6B6EQ45edO\nR9I1MQlw+t1Qsgy++JfT0agwpEkxyPl8hpVF5UzOSXM6lKMyKSeVgl2HMDp/ZfDYthC2vm+tRhGf\n7nQ0XTfhSug3Dj64D7wNTkejwowmxSC39UAN1fXeL6siQ01+Tir7qxrYXVHndCgKrCEY798NKTlw\n3I1OR3N0XG5rKrqKXTpEQwWcJsUg11L1mB+iSbF1u6IKAqtfgv3r4Yz7wROcC1X7ZdjpkHcm/PsR\nqD3odDQqjGhSDHIrdpWTbk+wHYpG9U8kLtqt4xWDQWMtfPwbGDwVxl7odDTdd9avoLEaPvmd05Go\nMKJJMcit2HWIyTmpSIj2svO4XUzISqFAk6LzPv8z1OyDs34dHr02+46GiVfD8qfh0A6no1FhQpNi\nECuraWDnwcMh257YIj8nlY17q6ht8DodSuSqLYPFj8Oob0L2cU5HEzin3gkuD3z8a6cjUWFCk2IQ\n+7I9McRmsmlrUk4qPqOLDjvqk99DUy3MuM/pSAIraQAcfxOsnwt7VjsdjQoDmhSD2Mpd5US7XYwd\nmOx0KN0yMTsVEe1s45jynbD8KauqMZQG6vtr+i3QJw0+vN/pSFQY0KQYxAp2lXPM4GRio9xOh9It\nyX2iGNE3UdsVnfLxr60qxlPvdDqSnhGbDCf/D2xfCNs+djoaFeI0KQapBm8z60oqQ749scWknFRW\n7SrH59NB/L1q7xprrtDjb7KqGsPVlNmQkm2VFn06Ab06epoUg9T63ZU0NvtCbr7TjuTnpFLd4GXL\ngWqnQ4ksH94PfVKtKsZw5omB0++xvgRseMPpaFQI06QYpJbtsKoaw6Wk2NJZaPmOQw5HEkG22dWJ\nJ91mVTGGu3GXQL9jrOWwvI1OR6NClCbFILVkWxkj+iWQmRjCs460kp0Wx8DkWBYX6uwjvcLns0qJ\nydkw9XtOR9M7XC44836rY9GKZ52ORoUoTYpBqMHbzPKdhzhhWIbToQSMiHBCXgafbz9Is7Yr9rwN\nb8De1XD6XaE9nVtXDZsBQ06Gfz8M9bqOp+o6TYpBaOWuCuqbfEzPC5+kCDA9L53KuiZddLineRut\nKsR+4+CYIy5zGn5ErHldDx+Ez//kdDQqBGlSDEJLtpXhEjhuaGguF9WRlpLvkm1lDkcS5lY8Z1Uh\nnnG/taJEpBk02ZrbdcmfoHq/09GoEKNJMQgtLizj2MEpJMWG1qLCnemXFEte3wQWb9N2xR7TUG1V\nHeaeBHlnOB2Nc06/B5obrPdCqS7QpBhkquubWFNSyfS8EFz81Q/Th6WzfMchGr06lqxHLPl/cLgM\nzvxleEz6fbTSh8Hk66xSc9lWp6NRIUSTYpBZtuMQzT7D9DDqZNPaCXkZ1DU1s6pIZ7cJuKo9sPiP\nVtXhoMlOR+O8U26HqD46/ZvqEk2KQWZx4UFiPC4mhcn4xLamDU3HJWgVak9Y+BswzVZbooKEvnDi\nT2DT27BzsdPRqBChSTHILNlWRn5uasjPd9qR5D5RHDMomSWF2tkmoPatg1UvwdQbIDXX6WiCx7Qf\nQtIgeP8unf5N+UWTYhApq2lg077qsBqf2J4T8jJYXVyh6ysGijHw/t3QJwVOvs3paIJLdJzV6WbP\nKlj/utPRqBCgSTGILLGrFMNtfGJb04dl4PUZlumUb4FR+BFsXwSn/Nya51R91bGXQf9j4KNfQlO9\n09GoIKdJMYgsKSwjMdbDMYPCe57K/NxUoj0uFmsVavc1e61SYuoQyJ/tdDTByeWCs34DlcWw9K9O\nR6OCnCbFILJ4WxnThqbjdoV3V/rYKDeTs1O1s00grJwDpRutIRieaKejCV5DT4HhZ8Mnv9cB/eqI\nNCkGiV0Hayk+VMf0YeE5PrGt6XnpbNxbRWl1g9OhhK7Dh6zp3HJPgtHnOx1N8Dv7N+Cth48ecDoS\nFcT8SooiMlNENotIoYjc0c7+GBF51d6/VERy7e1nisgKEVln/z49sOGHjw++sL69zhjdz+FIesfp\no6y/86ON+q39qC38jTXp9TkPR/ZAfX9lDIdpP4DVL0JJgdPRqCDVaVIUETfwBHAOMAa4QkTGtDls\nNlBujMkDHgNa5lYqA84zxhwDXAO8EKjAw8176/cxekASWWlxTofSK0YPSCQrrQ/vbdjndCihad86\nKHgGplwP/cY6HU3oOOV2SOgH8/9Hh2iodvlTUpwKFBpjthtjGoFXgFltjpkFzLEfzwVmiIgYY1YZ\nY/bY2zcAfUQkgtax8U9pdQMrisqZOba/06H0GhFh5tj+LCk8SHV9k9PhhBZjYP7tEJsCp93pdDSh\nJSYRznwA9qyE1S85HY0KQv4kxUFAcavnJfa2do8xxniBSqBt49jFwEpjjDYitfHBF/sxBs4eFxlV\npy3OHtufxmYfCzeXOh1KaFn/OhQtgRn36hCMo3HsZTB4qjX9W12F09GoINMrHW1EZCxWleqNHey/\nQUQKRKSgtDTyPiAXbNhHTnocI/slOh1Kr5qUnUpGQgwLtArVfw3V8P49MGA8TPqO09GEJhE49xFr\nzcVFDzodjQoy/iTF3UBWq+eD7W3tHiMiHiAZOGg/Hwz8E/iOMWZbexcwxjxpjMk3xuRnZmZ27S8I\ncVX1TSzZVsbZY/sjEdZZwuUSzhzTj0WbDlDf1Ox0OKHhowegei+c+4fIXCsxUAZOgCmzYenfoGSF\n09GoIOJPUlwODBeRISISDVwOzGtzzDysjjQAlwAfG2OMiKQA7wB3GGN0Rt52LNx0gKZmw9kR1J7Y\n2sxx/altbNaB/P4oXgbL/g+mfg+ypjgdTeibcS8k9od5P4JmbddWlk6Tot1GeDOwANgIvGaM2SAi\nD4hIy+Cop4F0ESkEbgVahm3cDOQB94rIavunb8D/ihC2YMM++ibGMDErxelQHHH80HQSYz1ahdoZ\nbyPM+zEkDbQ+zFX3xSbDub+HAxtgyR+djkYFCY8/Bxlj5gPz22y7t9XjeuDSdl73a+DX3YwxbNU3\nNbNwUykXTRqEK8xnselItMfF6aP68sEX+/E2+/C4dT6Jdi1+3Jq55opXrR6UKjBGf9Oa+GDRwzDm\nAmtxYhXR9BPIQZ9uLaOuqZmZ4yKz6rTFzLH9KT/cxPKduvBwu8q2wie/sxYPHjnT6WjCz7mPgCcW\n3rrFGu6iIpomRQct2LCPpFgP04ZGxtRuHTllZCYxHpdWobbH1wxv3mytID/z4c6PV12X2N+aO3bn\np7DiWaejUQ7TpOiQusZm3t+wjzNG9yMqwqsM46I9nDwik3fW7aWpWWcZ+YrPHoXi/8A5j0BiZI1j\n7VWTroGhp8GCu6Cs0OlolIMi+9PYQW+v3UNVvZdvTcnq/OAIcFl+FqXVDToXamu7V8Cih2DcxXDs\nt5yOJry5XHDBX8ATA29cr71RI5gmRYe8tLSIvL4JHDckzelQgsJpo/oyMDmWl5YWOR1KcGiogde/\nBwn94RuP6oTfvSFpAJz3R9izSgf1RzBNig5Yv7uS1cUVXHlcdsQN2O+I2yVcMTWbT7eWsbOs1ulw\nnLfgF3BoO1z0N+gTmcN1HDHmfJh4FXz6KOxa4nQ0ygGaFB3w92VFxEa5uGjiYKdDCSqXTcnC7RJe\nXhbhpcUv5lmLB0+/BXJPdDqayDPzYUjNhTdutNasVBFFk2Ivq2nw8uaq3Zx37ECS46KcDieo9E2K\n5awx/XitoJgGb4RO+3ZgE/zrBzBwEpx2l9PRRKaYBLj4aWs6vddnWz2AVcTQpNjL/rlqN7WNzVw5\nLcfpUILSlcflUH64iXfXReDwjLoKeOXb1vCLy14ET7TTEUWuwZPhG3+AbR/DR790OhrVizQp9iJj\nDC/9ZxfnNdk3AAAPLUlEQVRjByYxfnCy0+EEpROGpZObHsdLS3c5HUrv8vngjRugYhd863lIbrs6\nm+p1k6+B/O9aswmtf93paFQv0aTYi1YWVbBpXzVXHpejHWw64HIJ3z4um+U7y9m8r9rpcHrPot/C\n1gUw8yHIOcHpaFSLmQ9D1jRrAoV965yORvUCTYq96JnPdhAf7eb8CQOdDiWoXTI5i2iPi6c/2+50\nKL1j9cvwySMw8WqYcr3T0ajWPNFWyT02GV6+AipLnI5I9TBNir1kVVE576zby+yThpIQ49c87BEr\nLT6aq47LYe6KErbsD/PS4qb58OYPYcgpVhuW1iAEn8R+8O1XrTbfFy6E2oNOR6R6kCbFXmCM4cH5\nm8hIiOaGk4c6HU5I+NHpecTHeHjo3U1Oh9JzdnwK/7jWWvD28pes2VRUcBowHr79ClQUwUsXQ0OY\nf1mLYJoUe8GHGw+wbOchbjljhJYS/ZQaH80PT8vj400HWLItDBcg3r3Sqo5LGwJXztXloEJB7olw\n6RzYu9b6t2uqdzoi1QM0KfYwb7OPh97dyNDMeC7XeU675NoTchmYHMtD727C5wujJX1KCuDFiyAu\nFa7+J8TpVH8hY+RMuPCv1ooar1xhTcenwoomxR72akEx20pr+fnMURG/GkZXxUa5ue3skawtqeSt\ntXucDicwtn4Ac86D2BT4zjxI0k5XIefYb8GsJ2D7Inj+fG1jDDP6Kd2Dahu8PPbBVvJzUjlrjC77\nczQumDCI0QOSeGTB5tCf5Wbta/Dy5ZCeB7Pft6pOVWiaeBVc9hLs3wDPnA0VxU5HpAJEk2IPeuCt\nLyiraeDOc0fruMSj5HIJd507mpLyOh5+d7PT4RwdY+Czx+CN70H28XDtO5DQ1+moVHeNOteq/q45\nAE+fZa2uoUKeJsUe8uryIl4tKObm0/KYnJPqdDgh7cThGVx7Qi7PLN7B26FWjXr4kNUp48P7YeyF\nVqea2CSno1KBknMCXDcfxGUlxmX/Z30JUiFLk2IPWFdSyT1vbuCk4Rn89MwRTocTFn5x7mgmZadw\n+9y1FB4Ike7wJSvgb6dA4YfWzCiXPAtRsU5HpQKt/zi48RNrrOn822Dud6G+yumo1FHSpBhgFYcb\n+cFLK8iIj+bxyyfidmm1aSBEe1z8+crJ9Ilyc+MLK6hp8DodUse8DbDoYautCeC7C2Da93VgfjiL\nT4dvvwYz7oMv3oS/nWx1xFEhR5NiADU1+/jJq6vZX1XPE1dOIi1eVzkIpP7Jsfy/Kyayo6yW2+eu\noTkYh2lsXwR/OcGay3T0eXDjv60VF1T4c7ngpFvh2ret58/Pgtevh+r9zsalukSTYoBU1Tdx3bPL\nWbS5lPvPH8vEbG1H7Akn5GVwxzmjmL9uHze+UMDhxiApMR7cBnNnWx+Evma46g249FkdgxiJck6A\nm/4Dp9xhlRr/NAU+fwKa6pyOTPlBTJA1Cufn55uCggKnw+iS3RV1XPfsMraX1vLQxcdyyeTBTocU\n9l74fCf3zdvA2IHJPH1tPn0THWqrK9sKn/we1r0G7miYfguceKu2HSpLWSG8+z/WuozxfWH6j63l\nqKLjnY4s4ojICmNMfqfHaVLsnnUllcyes5y6pmb+etVkpudlOB1SxPho435u/vsq0uKjefrafEb1\n76Venb5m2L4QVsyBjW9ZiwJPmQ3H/8iaPFqptnYuhk9+Z1Wvx6XD5GutsY5pOhdyb9Gk2MNKqxv4\n3w+38MryYvonxfLsdVMY0U/nr+xt60oq+e6c5ZTXNnL18TncMmM4KXE90JZrDJRtgXVzYfXfoaoE\n+qRZC9EefzPE65ch5YfiZfDpH2Dr+2B8kHMiTLwSRp4DfbTJpSdpUuwhtQ1enluyk78s2kZ9UzNX\nTbM+iFO1U41jSqsbePSDLby6vIiEGA8/njGcq6blEBvl7t6JG2qgeKn1AbblPSjfCQjkzbC+5Y88\nV1e2UEenao/15WrVi1C+A8QN2dNgxNmQdwZkjrY67qiACWhSFJGZwOOAG3jKGPNQm/0xwPPAZOAg\ncJkxZqe9705gNtAM/NgYs+BI1wrGpFjf1My/t5Ty1po9fLTxAHVNzZw5ph93njOKoZkJToenbJv3\nVfPb+Rv595ZS4qPdnDmmH+eNH8hJwzOJ9nTyAdN42CoJHtgIuwusb/T7N4BpBk8sDD0Vhp9lfaPX\n+UpVoBhjTRC/5T3YsgD2r7O2xyRbvZYHT7WWFsscBSk5mii7IWBJUUTcwBbgTKAEWA5cYYz5otUx\nNwHHGmO+LyKXAxcaYy4TkTHAy8BUYCDwITDCGNPhJJZOJ8X6pmZ2V9SxcW8V63ZXsq6kkrUlldQ0\neEmLj+bcY/pz0aTBTNLepUFr6faD/Gv1buav20dlXRNJsS6mD/QwOdPLMckNDImtIbVpP1HVJdb6\neAcLoXwXYP9fiE6AQZMhaypkTbN6E0bHOfo3qQhRWQI7PrG+lJUshwNfWNWsAJ4+kDkCUnMhOQtS\nsiF5MCT0s6rv4zO1A88RBDIpHg/cb4w5235+J4Ax5sFWxyywj/lcRDzAPiATuKP1sa2P6+h6gUqK\nyz/8B95mLz4fNBtDs8/gbfbR1Gxo9PpobPZR1+jlcKOPw41eKuuaOHS4kZr6/3bxd7uErLQ4hmTE\nMSk7jTEDEnFHwje1LlWptzn2K681bbaZdh4b6z99y2Ofz37us0ppvmbwea3nzU3ga7J+NzdBcwN4\nG63fTfXQVGuV+JoOQ0MVpq4S7+EK3I1VuPB9LfIKEilz9+VgzGAO9hlKRcJQDqcMpy5xCNFRUcR4\nXER73HjcgscluO0flwguARGhZTh+y+OW8flf/uYIA/Z1LL/qhLupmvjKQuIrtxJfWUhcZSF9akuI\nObwHd3PD145vdsfgjUrCG52INyqJZk+c/dMHnycOnysan9v+cUVjXFEY8eBzeTAuD0bcIG6MuOzH\ngsEF4sKIAGJv++/jlhvZIK3u6bY391efmy5MZDFs8pkkJHW/EOJvUvRnxdtBQOsp4EuA4zo6xhjj\nFZFKIN3e/p82rx3UTrA3ADcAZGdn+xFS50Z/+iMS5CjGBbVtGqyyf7YHICgVWK4oq03PHW31AI2K\ns0p0UfGQOADJGElUbDLEJkN8Jo2xaRQ3xLP1cDw7mlIpqhH2VNRTfriRqromqiq8VBc20dS8zem/\nTKk2htg/Z9rPDRlUMUAOki6VZEgV6VSR5q0iseEwSVJHErXESylxNNCHBuKkgWiaiKGJaJpwS3D1\nJ+nIzv4fkZDUaS4LmKBYBt4Y8yTwJFglxUCcs/zSuVQY35ff7t0iRLldRHsEj9uFJxJKfN3ShWLM\n1w5tteHLb4Sti1CtHouLr3zjdLmtbSJW5wOXx97mBrfHSoTuKOt3F/8No4Fh9s+ReJutmoSGJh8N\nXh9en8+qafBZNQ7GgM+ufWhhDBi7ZNxSGD7SjRxsHdxU+Kq3f8rb7vB5EZ8X8TVZv41VI2M9tmpr\nxPgAH+LzYd3Rxt5u/vucll+taoFaka/d612797OzR3bp+O7yJynuBlovGT/Y3tbeMSV29WkyVocb\nf17bI7LGndgbl1FhyON24XG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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fe6f04278d0>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% plot the distributions\n",
+ "\n",
+ "pl.figure(1, figsize=(6.4, 3))\n",
+ "for i in range(n_distributions):\n",
+ " pl.plot(x, A[:, i])\n",
+ "pl.title('Distributions')\n",
+ "pl.tight_layout()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Barycenter computation\n",
+ "----------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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0uQlqNS+5No3vSTvl/EGycTokzIX0UxBcCRpdDI27OY960c6SH6bISjRBiUgf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\n5P8B8+yyfxkpn3sAAAAASUVORK5CYII=\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fe6f04274a8>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% barycenter computation\n",
+ "\n",
+ "alpha = 0.2 # 0<=alpha<=1\n",
+ "weights = np.array([1 - alpha, alpha])\n",
+ "\n",
+ "# l2bary\n",
+ "bary_l2 = A.dot(weights)\n",
+ "\n",
+ "# wasserstein\n",
+ "reg = 1e-3\n",
+ "bary_wass = ot.bregman.barycenter(A, M, reg, weights)\n",
+ "\n",
+ "pl.figure(2)\n",
+ "pl.clf()\n",
+ "pl.subplot(2, 1, 1)\n",
+ "for i in range(n_distributions):\n",
+ " pl.plot(x, A[:, i])\n",
+ "pl.title('Distributions')\n",
+ "\n",
+ "pl.subplot(2, 1, 2)\n",
+ "pl.plot(x, bary_l2, 'r', label='l2')\n",
+ "pl.plot(x, bary_wass, 'g', label='Wasserstein')\n",
+ "pl.legend()\n",
+ "pl.title('Barycenters')\n",
+ "pl.tight_layout()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Barycentric interpolation\n",
+ "-------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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fh8/nQzqdhslkyou47HZ7lmAZzkIDg/IwBMpgUcitYQKyhUmSJExOTmJychKrV6/G7t27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\nvr6ef/qnfwJS51mPPvoo7777bsp+lsVi4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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fe6ee2721d0>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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g448/hlarTcuI9Oqrr+LOO++EIAi4/fbbce+990bcHwgEcNttt+Hjjz9GdXU1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\nsUcynvMIGwAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fe6ee18f240>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% barycenter interpolation\n",
+ "\n",
+ "n_alpha = 11\n",
+ "alpha_list = np.linspace(0, 1, n_alpha)\n",
+ "\n",
+ "\n",
+ "B_l2 = np.zeros((n, n_alpha))\n",
+ "\n",
+ "B_wass = np.copy(B_l2)\n",
+ "\n",
+ "for i in range(0, n_alpha):\n",
+ " alpha = alpha_list[i]\n",
+ " weights = np.array([1 - alpha, alpha])\n",
+ " B_l2[:, i] = A.dot(weights)\n",
+ " B_wass[:, i] = ot.bregman.barycenter(A, M, reg, weights)\n",
+ "\n",
+ "#%% plot interpolation\n",
+ "\n",
+ "pl.figure(3)\n",
+ "\n",
+ "cmap = pl.cm.get_cmap('viridis')\n",
+ "verts = []\n",
+ "zs = alpha_list\n",
+ "for i, z in enumerate(zs):\n",
+ " ys = B_l2[:, i]\n",
+ " verts.append(list(zip(x, ys)))\n",
+ "\n",
+ "ax = pl.gcf().gca(projection='3d')\n",
+ "\n",
+ "poly = PolyCollection(verts, facecolors=[cmap(a) for a in alpha_list])\n",
+ "poly.set_alpha(0.7)\n",
+ "ax.add_collection3d(poly, zs=zs, zdir='y')\n",
+ "ax.set_xlabel('x')\n",
+ "ax.set_xlim3d(0, n)\n",
+ "ax.set_ylabel('$\\\\alpha$')\n",
+ "ax.set_ylim3d(0, 1)\n",
+ "ax.set_zlabel('')\n",
+ "ax.set_zlim3d(0, B_l2.max() * 1.01)\n",
+ "pl.title('Barycenter interpolation with l2')\n",
+ "pl.tight_layout()\n",
+ "\n",
+ "pl.figure(4)\n",
+ "cmap = pl.cm.get_cmap('viridis')\n",
+ "verts = []\n",
+ "zs = alpha_list\n",
+ "for i, z in enumerate(zs):\n",
+ " ys = B_wass[:, i]\n",
+ " verts.append(list(zip(x, ys)))\n",
+ "\n",
+ "ax = pl.gcf().gca(projection='3d')\n",
+ "\n",
+ "poly = PolyCollection(verts, facecolors=[cmap(a) for a in alpha_list])\n",
+ "poly.set_alpha(0.7)\n",
+ "ax.add_collection3d(poly, zs=zs, zdir='y')\n",
+ "ax.set_xlabel('x')\n",
+ "ax.set_xlim3d(0, n)\n",
+ "ax.set_ylabel('$\\\\alpha$')\n",
+ "ax.set_ylim3d(0, 1)\n",
+ "ax.set_zlabel('')\n",
+ "ax.set_zlim3d(0, B_l2.max() * 1.01)\n",
+ "pl.title('Barycenter interpolation with Wasserstein')\n",
+ "pl.tight_layout()\n",
+ "\n",
+ "pl.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/notebooks/plot_compute_emd.ipynb b/notebooks/plot_compute_emd.ipynb
new file mode 100644
index 0000000..c5f47c2
--- /dev/null
+++ b/notebooks/plot_compute_emd.ipynb
@@ -0,0 +1,248 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# Plot multiple EMD\n",
+ "\n",
+ "\n",
+ "Shows how to compute multiple EMD and Sinkhorn with two differnt\n",
+ "ground metrics and plot their values for diffeent distributions.\n",
+ "\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Author: Remi Flamary <remi.flamary@unice.fr>\n",
+ "#\n",
+ "# License: MIT License\n",
+ "\n",
+ "import numpy as np\n",
+ "import matplotlib.pylab as pl\n",
+ "import ot\n",
+ "from ot.datasets import get_1D_gauss as gauss"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Generate data\n",
+ "-------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "#%% parameters\n",
+ "\n",
+ "n = 100 # nb bins\n",
+ "n_target = 50 # nb target distributions\n",
+ "\n",
+ "\n",
+ "# bin positions\n",
+ "x = np.arange(n, dtype=np.float64)\n",
+ "\n",
+ "lst_m = np.linspace(20, 90, n_target)\n",
+ "\n",
+ "# Gaussian distributions\n",
+ "a = gauss(n, m=20, s=5) # m= mean, s= std\n",
+ "\n",
+ "B = np.zeros((n, n_target))\n",
+ "\n",
+ "for i, m in enumerate(lst_m):\n",
+ " B[:, i] = gauss(n, m=m, s=5)\n",
+ "\n",
+ "# loss matrix and normalization\n",
+ "M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)), 'euclidean')\n",
+ "M /= M.max()\n",
+ "M2 = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)), 'sqeuclidean')\n",
+ "M2 /= M2.max()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plot data\n",
+ "---------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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TgAA45xwrQWk3n1KqLmiCaiCmT4cmTeCss1wdydGNHw+pqfqjXaVU3dAE1QDk5Fizl48f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DnO1toKoVXl/Sown5PMfIRCXHlvoiiWYL53c0EQVDidA4S2fvgQ5nNaeRNLsprO8mNtf8gG9Rxo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wQNSg0Fk/C9FwJX5XOsPBBHYhqcgLE0k7ztGmd1CjYaTJytiJ51OfV421J4ESsTGc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\nkfx/0tlkef98PKwAAAAASUVORK5CYII=\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f91fb0dfc50>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% plot the distributions\n",
+ "\n",
+ "pl.figure(1)\n",
+ "pl.subplot(2, 1, 1)\n",
+ "pl.plot(x, a, 'b', label='Source distribution')\n",
+ "pl.title('Source distribution')\n",
+ "pl.subplot(2, 1, 2)\n",
+ "pl.plot(x, B, label='Target distributions')\n",
+ "pl.title('Target distributions')\n",
+ "pl.tight_layout()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Compute EMD for the different losses\n",
+ "------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.legend.Legend at 0x7f91f869ac88>"
+ ]
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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dR5O5OdSHp28Moo6W5S1d6Wdg4b2wexV0uR+ufR7cyla6LFvRKuXC0jJzeG31\nLj5Yu5d6NdyZOzqMvq2ca+50uXBqP3wxCo5Hww3/hk732h3RZdHkrpQT2LD3BFMWRhB7IpVbO/vx\nxPWtqKlleUtf3B9WjZjsTLgjHJr1tTuiy6bJXSkbJaVnMevbnXy64QCN61Tl83u70L15XbvDKp+2\nzoelD0HNRjD6S/BuYXdEV0STu1I2WRN9jCcXRXL4TDpjrwrgseta4FFZfyVLXW4u/PAsrPsPNOkB\nI+ZBtbJf914/SUqVssRUqyzvoj8P0rxedcLv707HJlqW1xYZSbBoPESvhI6jYeDLUNE1Tl4XKbmL\nyABgNtYC2R8YY2YW0m4YEA50MsboAqlK5fNN5GH+9fV2ElMzeahvcyb0ba5lee2SeAA+HwXHd8CA\nWdDlPttrsBeniyZ3EXED3gL6A/HARhFZaoyJyteuBvAw8HtJBKpUWXY8KYNnlm5jZeQRgnxq8snY\nTgT5eNodVvl1YIO1eHVOFtweDs2vsTuiYleUnntnIMYYsxdAROYDg4GofO1mALOAx4s1QqXKMGMM\ni/86yPTlUaRm5jBpQEvG9WxKJS3La5+/PrWqOnr6wq0LyvyJ08IUJbk3AuLyPI4HziusICIdgMbG\nmBUiosldKeBQYhpPLo5kTfRxOjaxyvI2r6dleW2Tk21dcfr7O9C0Dwz/CDzq2B1VibniE6oiUgF4\nFRhdhLbjgfEAfn5+V7prpZxSbq7h8z8OMPObneTkGp65sQ13dfPHTcvy2if1JISPgb1roOs/oP+M\nMnfF6aUqytEdBBrneezreO6sGkBbYI2j7kUDYKmI3JT/pKoxZg4wByAsLMxcQdxKOaXYhBQmL4zg\n930nuaq5FzOHBtO4jpbltdWxHdYap2cOwuC3oP0ddkdUKoqS3DcCgSISgJXURwG3nd1ojDkNnLvq\nQkTWAI/pbBlVnuTkGub+uo9/fx9NJbcKzBrWjhFhjbXQl912rrTWOK1cDUavgMad7Y6o1Fw0uRtj\nskVkArAKayrkXGPMdhGZDmwyxiwt6SCVcmbRR5KYtDCCrXGJ9Gtdj+dubkcDTy3La6vcXFj7b/jp\nefAJhVGfQ00fu6MqVUUadDLGrARW5nvu6ULa9rnysJRyfpnZubyzZg9v/rSbGu6VmD0qlJtCfLS3\nbreMJFh8P+xcDsEj4cbZTrnGaUlz7TMKSpWQyPjTPB6+lZ1HkrgxxIdpN7bBq3oVu8NSCTFW4a8T\nMTBgplUS/ajyAAAdRUlEQVSut5z+sdXkrtQlSM+yyvK+/8te6lavwvt3hdG/jZbldQrR31rj626V\n4K4lENDL7ohspcldqSLaGHuSyeER7E1IYWRYY568oTWeVbUsr+1yc2HtK/DTC9CgHYz6DGrpVGtN\n7kpdREpGNi99u5N5G/bTqFZVPr2nCz0CtSyvU0g/DYsfgOgV5Xp8vSCa3JW6gLW7jzNlYSSHTqdx\ndzd/Hr+uJdWq6K+NUzi6HRbcYRUAu+5F6PpAuR1fL4h+SpUqwOnULJ5bEcVXm+Np6l2Nr+7rRpi/\n616qXuZEfAXLJkKVGnD3cmjSze6InI4md6XyWbX9CFOXbONkSib/6NOMidcE4l5Jy/I6hexMqz7M\nH++BX3e45SOo0cDuqJySJnelHBKSM3hm6XZWRBymTcOafDS6E20baVlep3HmMHx1N8T9Dl0fhP7P\nWjNjVIE0uatyzxjD0q2HmLZ0OykZOTx2bQvu691My/I6k70/w8J7IDPVqubYdqjdETk9Te6qXDt8\nOo2pi7fxw85jtPerxUvDggmsX8PusNRZZ8sIrHkBvAKt8fV6reyOqkzQ5K7KJWMM8zfG8cKKHWTn\nGv41qA2ju2tZXqeSetJa3zTme2g3Aga9BlW0Hn5RaXJX5c7+EylMWRjJ+r0n6N7MKsvr56VleZ1K\n3Eb4ajSkHIMbXoWwsTrN8RJpclflRk6u4aN1+3jlu2gqVajAi0PbMaqTluV1KsbA7+9ZM2Jq+sA9\n34FPe7ujKpM0uatyYfdRqyzvXwcS6duqHs8PaUtDT72S0amknYKvJ1jVHFteDze/DVVr2x1VmaXJ\nXbm0rJxc3l2zhzd+jKFaFTf+MzKUwaFaltfpxG+Cr8ZA0mG47gVrKTz9P7oimtyVy9p28DSTwiOI\nOnyGG4Ib8uxNQdTVsrzOJTcXNrwFq6dZwzBjV4FvR7ujcgma3JXLSc/K4fUfdvPeL3upU60y793Z\nkeuC9CpGp5NyApY8ALtXQesb4aY3oWotu6NyGZrclUvZvP8kk8Ij2HM8hVs6+jL1hjZ4euhVjE4n\ndp1Vez3lOFz/CnS6V4dhipkmd+USUjKyeXlVNJ+sj8XHsyqfjO1M7xbedoel8svJhp9nWfXXawfA\nPd9ba5yqYlek5C4iA4DZWAtkf2CMmZlv+/3Ag0AOkAyMN8ZEFXOsShXo190JTFkUQfypNO7q1oRJ\nA1pRXcvyOp/EA7DwXqs2TOgdMHCWXpRUgi76GyAibsBbQH8gHtgoIkvzJe/PjTHvOtrfBLwKDCiB\neJU653RaFi+s2MGCTXEE1K3Gl/d1o3OAluV1StsXw9KHAQPDPoR2w+2OyOUVpXvTGYgxxuwFEJH5\nwGDgXHI3xpzJ074aYIozSKXyWx11lKeWRHI8KYP7ezfjkX5altcpZabAt1Pgz3ng2wmGfQC1/e2O\nqlwoSnJvBMTleRwPdMnfSEQeBP4PqAz0LZbolMrnRHIGzy6LYunWQ7RqUIP37woj2FdnWDilg39a\nJ01P7IGe/4Q+T2iJ3lJUbAOTxpi3gLdE5DZgKnB3/jYiMh4YD+DnpwvYqqIzxrAs4jDTlm4nKT2L\n/+vfgvt7N6NyRS3L63Ryc+DX12DNi1C9Pty9FAJ62R1VuVOU5H4QaJznsa/jucLMB94paIMxZg4w\nByAsLEyHblSRHD2TzlOLt7F6x1FCGltleVs20LK8TunUflh8HxxYD0FDYdCrWkLAJkVJ7huBQBEJ\nwErqo4Db8jYQkUBjzG7HwxuA3Sh1hYwxfLkpjudW7CAzO5enrm/N2B4BWpbXWUV8CSv+aRX/GvIe\nBI/Uues2umhyN8Zki8gEYBXWVMi5xpjtIjId2GSMWQpMEJF+QBZwigKGZJS6FHEnU3liUSS/xiTQ\nOaAOLw0Lxr9uNbvDUgVJPQkrH4NtC6FxVxj6np40dQJFGnM3xqwEVuZ77uk89x8u5rhUOZWba/hk\nfSwvfRtNBYHnbm7LbZ39qKC9dee0+3urkmNqAlw9FXo8Cm56jYEz0P8F5TRijiUzeWEEm/efoncL\nb14Y2o5GtbQsr1PKSLZqrm/+CLxbw20L9EpTJ6PJXdkuKyeXOb/sZfYPu6layY1XR4QwpH0jLcvr\nrA5ssE6antoP3R+yeuyV3O2OSuWjyV3Zavshqyzv9kNnGNi2Ac8ODqJeDU0UTikr3Vqoet3rUMsP\nRq8A/6vsjkoVQpO7skVGdg5v/BDDuz/voZZHZd65vQMD2zW0OyxVmIObYfEDkBANHe6yFtSootNR\nnZkmd1Xq/jxwisnhEew+lszQDo14elAbanlUtjssVZDsDFgzE9b9B2o0hDsWQvN+dkelikCTuyo1\naZk5vPJdNHPX7aNBTXc+GtOJq1vWszssVZiDf8KSf8DxHdD+Dqu37u5pd1SqiDS5q1Lx254EpiyM\n5MDJVG7v4seUga2o4a51RpxSdgb8/JJVQqB6PbjtK2hxrd1RqUukyV2VqDPpWby4cidf/HEAfy8P\n5o/vStemXnaHpQoT94c1bz0hGkJugwEvaPmAMkqTuyoxP+48ypOLtnEsKZ3xvZryaL8WVK2sZXmd\nUkYy/Pgc/P4uePrC7QshUMfWyzJN7qrYnUrJZPryKBb/dZCW9Wvw7p0dCW2sZXmd1p4fYdnD1kpJ\nncfDNU/rTBgXoMldFRtjDCsiD/PM19s5nZbFw9cE8uDVzbUsr7NKPQnf/Qu2fApegTDmW2jSze6o\nVDHR5K6KxbEz6Uxdso3voo4S7OvJZ+O60KpBTbvDUgUxxiry9e0UK8H3+D/oPVmvMnUxmtzVFTHG\n8NXmeJ5bHkVGdi5PDGzFPT0CqOimvXWndCrWKssbsxp8OsCdi6FBO7ujUiVAk7u6bHEnU3lycSRr\ndyfQ2b8OM4e1o6m3rmbvlHKyYcPb1upIUgEGzILO46CCnuB2VZrc1SXLzTX8d8N+Zn27EwGmDw7i\nji5NtCyvszq4GZY9AkcioOX1cP3L1owY5dI0uatLsve4VZZ3Y+wpegbW5cWh7fCt7WF3WKogaYnw\nw3TYNNday3TEPGh9k66OVE5ocldFkp2Ty/tr9/Ha6l24V6zAy8ODGd7RV8vyOiNjrCXvvnsKUk9A\nl/vh6ifBXU9wlyea3NVF7Th8hknhEUQePM11QfWZMbgt9WrqzAqndDzaOmEauxYahVmFvhqG2B2V\nsoEmd1WojOwc3voxhrfX7MGzaiXeuq0D17droL11Z5SRDGtfgd/ehMrVYNB/oMPdUEFnLZVXmtxV\ngbbEJTIpfCu7jiYzpL1Vlrd2NS3L63SMge2LYNVUSDpk1YPpPx2qe9sdmbJZkZK7iAwAZgNuwAfG\nmJn5tv8fcC+QDRwHxhpj9hdzrKoUpGXm8Or30Xz46z7q13Rn7ugw+raqb3dYqiBHo+CbSdYQTMMQ\nGPEJNO5sd1TKSVw0uYuIG/AW0B+IBzaKyFJjTFSeZn8BYcaYVBF5AHgJGFkSAauSs2HvCaYsjCD2\nRCq3dfHjCS3L65zSEq0FNP6YY50kHfSaYwhG56yr/ylKz70zEGOM2QsgIvOBwcC55G6M+SlP+w3A\nHcUZpCpZSelZzPp2J59uOIB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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f91fb9619b0>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% Compute and plot distributions and loss matrix\n",
+ "\n",
+ "d_emd = ot.emd2(a, B, M) # direct computation of EMD\n",
+ "d_emd2 = ot.emd2(a, B, M2) # direct computation of EMD with loss M2\n",
+ "\n",
+ "\n",
+ "pl.figure(2)\n",
+ "pl.plot(d_emd, label='Euclidean EMD')\n",
+ "pl.plot(d_emd2, label='Squared Euclidean EMD')\n",
+ "pl.title('EMD distances')\n",
+ "pl.legend()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Compute Sinkhorn for the different losses\n",
+ "-----------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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7d6br8/nz56levTrFill+NGvVqmUtxpZSdjk8PByj0ciIESNwc3Oja9euqfoF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\nbkltmULond8/ZcXJRemOS27dvswuRsv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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f91f8ee0278>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%%\n",
+ "reg = 1e-2\n",
+ "d_sinkhorn = ot.sinkhorn2(a, B, M, reg)\n",
+ "d_sinkhorn2 = ot.sinkhorn2(a, B, M2, reg)\n",
+ "\n",
+ "pl.figure(2)\n",
+ "pl.clf()\n",
+ "pl.plot(d_emd, label='Euclidean EMD')\n",
+ "pl.plot(d_emd2, label='Squared Euclidean EMD')\n",
+ "pl.plot(d_sinkhorn, '+', label='Euclidean Sinkhorn')\n",
+ "pl.plot(d_sinkhorn2, '+', label='Squared Euclidean Sinkhorn')\n",
+ "pl.title('EMD distances')\n",
+ "pl.legend()\n",
+ "\n",
+ "pl.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/notebooks/plot_gromov.ipynb b/notebooks/plot_gromov.ipynb
new file mode 100644
index 0000000..11c19d3
--- /dev/null
+++ b/notebooks/plot_gromov.ipynb
@@ -0,0 +1,231 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# Gromov-Wasserstein example\n",
+ "\n",
+ "\n",
+ "This example is designed to show how to use the Gromov-Wassertsein distance\n",
+ "computation in POT.\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Author: Erwan Vautier <erwan.vautier@gmail.com>\r\n",
+ "# Nicolas Courty <ncourty@irisa.fr>\r\n",
+ "#\r\n",
+ "# License: MIT License\r\n",
+ "\r\n",
+ "import scipy as sp\r\n",
+ "import numpy as np\r\n",
+ "import matplotlib.pylab as pl\r\n",
+ "from mpl_toolkits.mplot3d import Axes3D # noqa\r\n",
+ "import ot"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Sample two Gaussian distributions (2D and 3D)\r\n",
+ " ---------------------------------------------\r\n",
+ "\r\n",
+ " The Gromov-Wasserstein distance allows to compute distances with samples that\r\n",
+ " do not belong to the same metric space. For demonstration purpose, we sample\r\n",
+ " two Gaussian distributions in 2- and 3-dimensional spaces.\r\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "n_samples = 30 # nb samples\r\n",
+ "\r\n",
+ "mu_s = np.array([0, 0])\r\n",
+ "cov_s = np.array([[1, 0], [0, 1]])\r\n",
+ "\r\n",
+ "mu_t = np.array([4, 4, 4])\r\n",
+ "cov_t = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])\r\n",
+ "\r\n",
+ "\r\n",
+ "xs = ot.datasets.get_2D_samples_gauss(n_samples, mu_s, cov_s)\r\n",
+ "P = sp.linalg.sqrtm(cov_t)\r\n",
+ "xt = np.random.randn(n_samples, 3).dot(P) + mu_t"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plotting the distributions\r\n",
+ "--------------------------\r\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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7nZKSEq5du4bD4WB0dJQbN24wMjIStqF4rHL1kXJqhf0wcsOxjKyPay479PpH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\nwlBiJ4QQC0OJnRBCLAwldkIIsTD/D1lnmNmlAPxdAAAAAElFTkSuQmCC\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fe3102491d0>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig = pl.figure()\r\n",
+ "ax1 = fig.add_subplot(121)\r\n",
+ "ax1.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')\r\n",
+ "ax2 = fig.add_subplot(122, projection='3d')\r\n",
+ "ax2.scatter(xt[:, 0], xt[:, 1], xt[:, 2], color='r')\r\n",
+ "pl.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Compute distance kernels, normalize them and then display\r\n",
+ "---------------------------------------------------------\r\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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hGD7BFnTDMAyfYAu6YRiGTzjggi4i1SLyrIhsE5GtIvJ3E/YiEXlKROon/tZe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\n8dMc2rnMPuyVi2EYhk+wBd0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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fe30e043a90>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "C1 = sp.spatial.distance.cdist(xs, xs)\r\n",
+ "C2 = sp.spatial.distance.cdist(xt, xt)\r\n",
+ "\r\n",
+ "C1 /= C1.max()\r\n",
+ "C2 /= C2.max()\r\n",
+ "\r\n",
+ "pl.figure()\r\n",
+ "pl.subplot(121)\r\n",
+ "pl.imshow(C1)\r\n",
+ "pl.subplot(122)\r\n",
+ "pl.imshow(C2)\r\n",
+ "pl.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Compute Gromov-Wasserstein plans and distance\r\n",
+ "---------------------------------------------\r\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Gromov-Wasserstein distances between the distribution: 0.201997813845\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fe31024a390>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "p = ot.unif(n_samples)\r\n",
+ "q = ot.unif(n_samples)\r\n",
+ "\r\n",
+ "gw = ot.gromov_wasserstein(C1, C2, p, q, 'square_loss', epsilon=5e-4)\r\n",
+ "gw_dist = ot.gromov_wasserstein2(C1, C2, p, q, 'square_loss', epsilon=5e-4)\r\n",
+ "\r\n",
+ "print('Gromov-Wasserstein distances between the distribution: ' + str(gw_dist))\r\n",
+ "\r\n",
+ "pl.figure()\r\n",
+ "pl.imshow(gw, cmap='jet')\r\n",
+ "pl.colorbar()\r\n",
+ "pl.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/notebooks/plot_gromov_barycenter.ipynb b/notebooks/plot_gromov_barycenter.ipynb
new file mode 100644
index 0000000..8102bcf
--- /dev/null
+++ b/notebooks/plot_gromov_barycenter.ipynb
@@ -0,0 +1,368 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# Gromov-Wasserstein Barycenter example\n",
+ "\n",
+ "\n",
+ "This example is designed to show how to use the Gromov-Wasserstein distance\n",
+ "computation in POT.\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Author: Erwan Vautier <erwan.vautier@gmail.com>\r\n",
+ "# Nicolas Courty <ncourty@irisa.fr>\r\n",
+ "#\r\n",
+ "# License: MIT License\r\n",
+ "\r\n",
+ "\r\n",
+ "import numpy as np\r\n",
+ "import scipy as sp\r\n",
+ "\r\n",
+ "import scipy.ndimage as spi\r\n",
+ "import matplotlib.pylab as pl\r\n",
+ "from sklearn import manifold\r\n",
+ "from sklearn.decomposition import PCA\r\n",
+ "\r\n",
+ "import ot"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Smacof MDS\r\n",
+ " ----------\r\n",
+ "\r\n",
+ " This function allows to find an embedding of points given a dissimilarity matrix\r\n",
+ " that will be given by the output of the algorithm\r\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "def smacof_mds(C, dim, max_iter=3000, eps=1e-9):\r\n",
+ " \"\"\"\r\n",
+ " Returns an interpolated point cloud following the dissimilarity matrix C\r\n",
+ " using SMACOF multidimensional scaling (MDS) in specific dimensionned\r\n",
+ " target space\r\n",
+ "\r\n",
+ " Parameters\r\n",
+ " ----------\r\n",
+ " C : ndarray, shape (ns, ns)\r\n",
+ " dissimilarity matrix\r\n",
+ " dim : int\r\n",
+ " dimension of the targeted space\r\n",
+ " max_iter : int\r\n",
+ " Maximum number of iterations of the SMACOF algorithm for a single run\r\n",
+ " eps : float\r\n",
+ " relative tolerance w.r.t stress to declare converge\r\n",
+ "\r\n",
+ " Returns\r\n",
+ " -------\r\n",
+ " npos : ndarray, shape (R, dim)\r\n",
+ " Embedded coordinates of the interpolated point cloud (defined with\r\n",
+ " one isometry)\r\n",
+ " \"\"\"\r\n",
+ "\r\n",
+ " rng = np.random.RandomState(seed=3)\r\n",
+ "\r\n",
+ " mds = manifold.MDS(\r\n",
+ " dim,\r\n",
+ " max_iter=max_iter,\r\n",
+ " eps=1e-9,\r\n",
+ " dissimilarity='precomputed',\r\n",
+ " n_init=1)\r\n",
+ " pos = mds.fit(C).embedding_\r\n",
+ "\r\n",
+ " nmds = manifold.MDS(\r\n",
+ " 2,\r\n",
+ " max_iter=max_iter,\r\n",
+ " eps=1e-9,\r\n",
+ " dissimilarity=\"precomputed\",\r\n",
+ " random_state=rng,\r\n",
+ " n_init=1)\r\n",
+ " npos = nmds.fit_transform(C, init=pos)\r\n",
+ "\r\n",
+ " return npos"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Data preparation\r\n",
+ " ----------------\r\n",
+ "\r\n",
+ " The four distributions are constructed from 4 simple images\r\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "def im2mat(I):\r\n",
+ " \"\"\"Converts and image to matrix (one pixel per line)\"\"\"\r\n",
+ " return I.reshape((I.shape[0] * I.shape[1], I.shape[2]))\r\n",
+ "\r\n",
+ "\r\n",
+ "square = spi.imread('../data/square.png').astype(np.float64)[:, :, 2] / 256\r\n",
+ "cross = spi.imread('../data/cross.png').astype(np.float64)[:, :, 2] / 256\r\n",
+ "triangle = spi.imread('../data/triangle.png').astype(np.float64)[:, :, 2] / 256\r\n",
+ "star = spi.imread('../data/star.png').astype(np.float64)[:, :, 2] / 256\r\n",
+ "\r\n",
+ "shapes = [square, cross, triangle, star]\r\n",
+ "\r\n",
+ "S = 4\r\n",
+ "xs = [[] for i in range(S)]\r\n",
+ "\r\n",
+ "\r\n",
+ "for nb in range(4):\r\n",
+ " for i in range(8):\r\n",
+ " for j in range(8):\r\n",
+ " if shapes[nb][i, j] < 0.95:\r\n",
+ " xs[nb].append([j, 8 - i])\r\n",
+ "\r\n",
+ "xs = np.array([np.array(xs[0]), np.array(xs[1]),\r\n",
+ " np.array(xs[2]), np.array(xs[3])])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Barycenter computation\r\n",
+ "----------------------\r\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "ns = [len(xs[s]) for s in range(S)]\r\n",
+ "n_samples = 30\r\n",
+ "\r\n",
+ "\"\"\"Compute all distances matrices for the four shapes\"\"\"\r\n",
+ "Cs = [sp.spatial.distance.cdist(xs[s], xs[s]) for s in range(S)]\r\n",
+ "Cs = [cs / cs.max() for cs in Cs]\r\n",
+ "\r\n",
+ "ps = [ot.unif(ns[s]) for s in range(S)]\r\n",
+ "p = ot.unif(n_samples)\r\n",
+ "\r\n",
+ "\r\n",
+ "lambdast = [[float(i) / 3, float(3 - i) / 3] for i in [1, 2]]\r\n",
+ "\r\n",
+ "Ct01 = [0 for i in range(2)]\r\n",
+ "for i in range(2):\r\n",
+ " Ct01[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[0], Cs[1]],\r\n",
+ " [ps[0], ps[1]\r\n",
+ " ], p, lambdast[i], 'square_loss', 5e-4,\r\n",
+ " max_iter=100, tol=1e-3)\r\n",
+ "\r\n",
+ "Ct02 = [0 for i in range(2)]\r\n",
+ "for i in range(2):\r\n",
+ " Ct02[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[0], Cs[2]],\r\n",
+ " [ps[0], ps[2]\r\n",
+ " ], p, lambdast[i], 'square_loss', 5e-4,\r\n",
+ " max_iter=100, tol=1e-3)\r\n",
+ "\r\n",
+ "Ct13 = [0 for i in range(2)]\r\n",
+ "for i in range(2):\r\n",
+ " Ct13[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[1], Cs[3]],\r\n",
+ " [ps[1], ps[3]\r\n",
+ " ], p, lambdast[i], 'square_loss', 5e-4,\r\n",
+ " max_iter=100, tol=1e-3)\r\n",
+ "\r\n",
+ "Ct23 = [0 for i in range(2)]\r\n",
+ "for i in range(2):\r\n",
+ " Ct23[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[2], Cs[3]],\r\n",
+ " [ps[2], ps[3]\r\n",
+ " ], p, lambdast[i], 'square_loss', 5e-4,\r\n",
+ " max_iter=100, tol=1e-3)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Visualization\r\n",
+ " -------------\r\n",
+ "\r\n",
+ " The PCA helps in getting consistency between the rotations\r\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.collections.PathCollection at 0x7fd293df1e50>"
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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SZcmhT6vqV2L3O/PK+s+Vld/VnWMf1URIf2az38/P6uqqb25upj6MbXauGZNm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\nKWMAABMpYwAAE30Dk13yOM0vHUgAAAAASUVORK5CYII=\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fd294476ed0>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "clf = PCA(n_components=2)\r\n",
+ "npos = [0, 0, 0, 0]\r\n",
+ "npos = [smacof_mds(Cs[s], 2) for s in range(S)]\r\n",
+ "\r\n",
+ "npost01 = [0, 0]\r\n",
+ "npost01 = [smacof_mds(Ct01[s], 2) for s in range(2)]\r\n",
+ "npost01 = [clf.fit_transform(npost01[s]) for s in range(2)]\r\n",
+ "\r\n",
+ "npost02 = [0, 0]\r\n",
+ "npost02 = [smacof_mds(Ct02[s], 2) for s in range(2)]\r\n",
+ "npost02 = [clf.fit_transform(npost02[s]) for s in range(2)]\r\n",
+ "\r\n",
+ "npost13 = [0, 0]\r\n",
+ "npost13 = [smacof_mds(Ct13[s], 2) for s in range(2)]\r\n",
+ "npost13 = [clf.fit_transform(npost13[s]) for s in range(2)]\r\n",
+ "\r\n",
+ "npost23 = [0, 0]\r\n",
+ "npost23 = [smacof_mds(Ct23[s], 2) for s in range(2)]\r\n",
+ "npost23 = [clf.fit_transform(npost23[s]) for s in range(2)]\r\n",
+ "\r\n",
+ "\r\n",
+ "fig = pl.figure(figsize=(10, 10))\r\n",
+ "\r\n",
+ "ax1 = pl.subplot2grid((4, 4), (0, 0))\r\n",
+ "pl.xlim((-1, 1))\r\n",
+ "pl.ylim((-1, 1))\r\n",
+ "ax1.scatter(npos[0][:, 0], npos[0][:, 1], color='r')\r\n",
+ "\r\n",
+ "ax2 = pl.subplot2grid((4, 4), (0, 1))\r\n",
+ "pl.xlim((-1, 1))\r\n",
+ "pl.ylim((-1, 1))\r\n",
+ "ax2.scatter(npost01[1][:, 0], npost01[1][:, 1], color='b')\r\n",
+ "\r\n",
+ "ax3 = pl.subplot2grid((4, 4), (0, 2))\r\n",
+ "pl.xlim((-1, 1))\r\n",
+ "pl.ylim((-1, 1))\r\n",
+ "ax3.scatter(npost01[0][:, 0], npost01[0][:, 1], color='b')\r\n",
+ "\r\n",
+ "ax4 = pl.subplot2grid((4, 4), (0, 3))\r\n",
+ "pl.xlim((-1, 1))\r\n",
+ "pl.ylim((-1, 1))\r\n",
+ "ax4.scatter(npos[1][:, 0], npos[1][:, 1], color='r')\r\n",
+ "\r\n",
+ "ax5 = pl.subplot2grid((4, 4), (1, 0))\r\n",
+ "pl.xlim((-1, 1))\r\n",
+ "pl.ylim((-1, 1))\r\n",
+ "ax5.scatter(npost02[1][:, 0], npost02[1][:, 1], color='b')\r\n",
+ "\r\n",
+ "ax6 = pl.subplot2grid((4, 4), (1, 3))\r\n",
+ "pl.xlim((-1, 1))\r\n",
+ "pl.ylim((-1, 1))\r\n",
+ "ax6.scatter(npost13[1][:, 0], npost13[1][:, 1], color='b')\r\n",
+ "\r\n",
+ "ax7 = pl.subplot2grid((4, 4), (2, 0))\r\n",
+ "pl.xlim((-1, 1))\r\n",
+ "pl.ylim((-1, 1))\r\n",
+ "ax7.scatter(npost02[0][:, 0], npost02[0][:, 1], color='b')\r\n",
+ "\r\n",
+ "ax8 = pl.subplot2grid((4, 4), (2, 3))\r\n",
+ "pl.xlim((-1, 1))\r\n",
+ "pl.ylim((-1, 1))\r\n",
+ "ax8.scatter(npost13[0][:, 0], npost13[0][:, 1], color='b')\r\n",
+ "\r\n",
+ "ax9 = pl.subplot2grid((4, 4), (3, 0))\r\n",
+ "pl.xlim((-1, 1))\r\n",
+ "pl.ylim((-1, 1))\r\n",
+ "ax9.scatter(npos[2][:, 0], npos[2][:, 1], color='r')\r\n",
+ "\r\n",
+ "ax10 = pl.subplot2grid((4, 4), (3, 1))\r\n",
+ "pl.xlim((-1, 1))\r\n",
+ "pl.ylim((-1, 1))\r\n",
+ "ax10.scatter(npost23[1][:, 0], npost23[1][:, 1], color='b')\r\n",
+ "\r\n",
+ "ax11 = pl.subplot2grid((4, 4), (3, 2))\r\n",
+ "pl.xlim((-1, 1))\r\n",
+ "pl.ylim((-1, 1))\r\n",
+ "ax11.scatter(npost23[0][:, 0], npost23[0][:, 1], color='b')\r\n",
+ "\r\n",
+ "ax12 = pl.subplot2grid((4, 4), (3, 3))\r\n",
+ "pl.xlim((-1, 1))\r\n",
+ "pl.ylim((-1, 1))\r\n",
+ "ax12.scatter(npos[3][:, 0], npos[3][:, 1], color='r')"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/notebooks/plot_optim_OTreg.ipynb b/notebooks/plot_optim_OTreg.ipynb
new file mode 100644
index 0000000..d36b0ee
--- /dev/null
+++ b/notebooks/plot_optim_OTreg.ipynb
@@ -0,0 +1,762 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# Regularized OT with generic solver\n",
+ "\n",
+ "\n",
+ "Illustrates the use of the generic solver for regularized OT with\n",
+ "user-designed regularization term. It uses Conditional gradient as in [6] and\n",
+ "generalized Conditional Gradient as proposed in [5][7].\n",
+ "\n",
+ "\n",
+ "[5] N. Courty; R. Flamary; D. Tuia; A. Rakotomamonjy, Optimal Transport for\n",
+ "Domain Adaptation, in IEEE Transactions on Pattern Analysis and Machine\n",
+ "Intelligence , vol.PP, no.99, pp.1-1.\n",
+ "\n",
+ "[6] Ferradans, S., Papadakis, N., Peyré, G., & Aujol, J. F. (2014).\n",
+ "Regularized discrete optimal transport. SIAM Journal on Imaging Sciences,\n",
+ "7(3), 1853-1882.\n",
+ "\n",
+ "[7] Rakotomamonjy, A., Flamary, R., & Courty, N. (2015). Generalized\n",
+ "conditional gradient: analysis of convergence and applications.\n",
+ "arXiv preprint arXiv:1510.06567.\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "import matplotlib.pylab as pl\n",
+ "import ot"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Generate data\n",
+ "-------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "#%% parameters\n",
+ "\n",
+ "n = 100 # nb bins\n",
+ "\n",
+ "# bin positions\n",
+ "x = np.arange(n, dtype=np.float64)\n",
+ "\n",
+ "# Gaussian distributions\n",
+ "a = ot.datasets.get_1D_gauss(n, m=20, s=5) # m= mean, s= std\n",
+ "b = ot.datasets.get_1D_gauss(n, m=60, s=10)\n",
+ "\n",
+ "# loss matrix\n",
+ "M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)))\n",
+ "M /= M.max()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Solve EMD\n",
+ "---------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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yfTl0MwB7P90UqJg4PRvlTJdCbbVo4aMcjjyyYl8I8MknOy+389xzUFLixzRq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\ngSsiEhMFrohITP4PrQ161dhEqnEAAAAASUVORK5CYII=\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f6c14006e10>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% EMD\n",
+ "\n",
+ "G0 = ot.emd(a, b, M)\n",
+ "\n",
+ "pl.figure(3, figsize=(5, 5))\n",
+ "ot.plot.plot1D_mat(a, b, G0, 'OT matrix G0')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Solve EMD with Frobenius norm regularization\n",
+ "--------------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 0|1.760578e-01|0.000000e+00\n",
+ " 1|1.669467e-01|-5.457501e-02\n",
+ " 2|1.665639e-01|-2.298130e-03\n",
+ " 3|1.664378e-01|-7.572776e-04\n",
+ " 4|1.664077e-01|-1.811855e-04\n",
+ " 5|1.663912e-01|-9.936787e-05\n",
+ " 6|1.663852e-01|-3.555826e-05\n",
+ " 7|1.663814e-01|-2.305693e-05\n",
+ " 8|1.663785e-01|-1.760450e-05\n",
+ " 9|1.663767e-01|-1.078011e-05\n",
+ " 10|1.663751e-01|-9.525192e-06\n",
+ " 11|1.663737e-01|-8.396466e-06\n",
+ " 12|1.663727e-01|-6.086938e-06\n",
+ " 13|1.663720e-01|-4.042609e-06\n",
+ " 14|1.663713e-01|-4.160914e-06\n",
+ " 15|1.663707e-01|-3.823502e-06\n",
+ " 16|1.663702e-01|-3.022440e-06\n",
+ " 17|1.663697e-01|-3.181249e-06\n",
+ " 18|1.663692e-01|-2.698532e-06\n",
+ " 19|1.663687e-01|-3.258253e-06\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 20|1.663682e-01|-2.741118e-06\n",
+ " 21|1.663678e-01|-2.624135e-06\n",
+ " 22|1.663673e-01|-2.645179e-06\n",
+ " 23|1.663670e-01|-1.957237e-06\n",
+ " 24|1.663666e-01|-2.261541e-06\n",
+ " 25|1.663663e-01|-1.851305e-06\n",
+ " 26|1.663660e-01|-1.942296e-06\n",
+ " 27|1.663657e-01|-2.092896e-06\n",
+ " 28|1.663653e-01|-1.924361e-06\n",
+ " 29|1.663651e-01|-1.625455e-06\n",
+ " 30|1.663648e-01|-1.641123e-06\n",
+ " 31|1.663645e-01|-1.566666e-06\n",
+ " 32|1.663643e-01|-1.338514e-06\n",
+ " 33|1.663641e-01|-1.222711e-06\n",
+ " 34|1.663639e-01|-1.221805e-06\n",
+ " 35|1.663637e-01|-1.440781e-06\n",
+ " 36|1.663634e-01|-1.520091e-06\n",
+ " 37|1.663632e-01|-1.288193e-06\n",
+ " 38|1.663630e-01|-1.123055e-06\n",
+ " 39|1.663628e-01|-1.024487e-06\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 40|1.663627e-01|-1.079606e-06\n",
+ " 41|1.663625e-01|-1.172093e-06\n",
+ " 42|1.663623e-01|-1.047880e-06\n",
+ " 43|1.663621e-01|-1.010577e-06\n",
+ " 44|1.663619e-01|-1.064438e-06\n",
+ " 45|1.663618e-01|-9.882375e-07\n",
+ " 46|1.663616e-01|-8.532647e-07\n",
+ " 47|1.663615e-01|-9.930189e-07\n",
+ " 48|1.663613e-01|-8.728955e-07\n",
+ " 49|1.663612e-01|-9.524214e-07\n",
+ " 50|1.663610e-01|-9.088418e-07\n",
+ " 51|1.663609e-01|-7.639430e-07\n",
+ " 52|1.663608e-01|-6.662611e-07\n",
+ " 53|1.663607e-01|-7.133700e-07\n",
+ " 54|1.663605e-01|-7.648141e-07\n",
+ " 55|1.663604e-01|-6.557516e-07\n",
+ " 56|1.663603e-01|-7.304213e-07\n",
+ " 57|1.663602e-01|-6.353809e-07\n",
+ " 58|1.663601e-01|-7.968279e-07\n",
+ " 59|1.663600e-01|-6.367159e-07\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 60|1.663599e-01|-5.610790e-07\n",
+ " 61|1.663598e-01|-5.787466e-07\n",
+ " 62|1.663596e-01|-6.937777e-07\n",
+ " 63|1.663596e-01|-5.599432e-07\n",
+ " 64|1.663595e-01|-5.813048e-07\n",
+ " 65|1.663594e-01|-5.724600e-07\n",
+ " 66|1.663593e-01|-6.081892e-07\n",
+ " 67|1.663592e-01|-5.948732e-07\n",
+ " 68|1.663591e-01|-4.941833e-07\n",
+ " 69|1.663590e-01|-5.213739e-07\n",
+ " 70|1.663589e-01|-5.127355e-07\n",
+ " 71|1.663588e-01|-4.349251e-07\n",
+ " 72|1.663588e-01|-5.007084e-07\n",
+ " 73|1.663587e-01|-4.880265e-07\n",
+ " 74|1.663586e-01|-4.931950e-07\n",
+ " 75|1.663585e-01|-4.981309e-07\n",
+ " 76|1.663584e-01|-3.952959e-07\n",
+ " 77|1.663584e-01|-4.544857e-07\n",
+ " 78|1.663583e-01|-4.237579e-07\n",
+ " 79|1.663582e-01|-4.382386e-07\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 80|1.663582e-01|-3.646051e-07\n",
+ " 81|1.663581e-01|-4.197994e-07\n",
+ " 82|1.663580e-01|-4.072764e-07\n",
+ " 83|1.663580e-01|-3.994645e-07\n",
+ " 84|1.663579e-01|-4.842721e-07\n",
+ " 85|1.663578e-01|-3.276486e-07\n",
+ " 86|1.663578e-01|-3.737346e-07\n",
+ " 87|1.663577e-01|-4.282043e-07\n",
+ " 88|1.663576e-01|-4.020937e-07\n",
+ " 89|1.663576e-01|-3.431951e-07\n",
+ " 90|1.663575e-01|-3.052335e-07\n",
+ " 91|1.663575e-01|-3.500538e-07\n",
+ " 92|1.663574e-01|-3.063176e-07\n",
+ " 93|1.663573e-01|-3.576367e-07\n",
+ " 94|1.663573e-01|-3.224681e-07\n",
+ " 95|1.663572e-01|-3.673221e-07\n",
+ " 96|1.663572e-01|-3.635561e-07\n",
+ " 97|1.663571e-01|-3.527236e-07\n",
+ " 98|1.663571e-01|-2.788548e-07\n",
+ " 99|1.663570e-01|-2.727141e-07\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 100|1.663570e-01|-3.127278e-07\n",
+ " 101|1.663569e-01|-2.637504e-07\n",
+ " 102|1.663569e-01|-2.922750e-07\n",
+ " 103|1.663568e-01|-3.076454e-07\n",
+ " 104|1.663568e-01|-2.911509e-07\n",
+ " 105|1.663567e-01|-2.403398e-07\n",
+ " 106|1.663567e-01|-2.439790e-07\n",
+ " 107|1.663567e-01|-2.634542e-07\n",
+ " 108|1.663566e-01|-2.452203e-07\n",
+ " 109|1.663566e-01|-2.852991e-07\n",
+ " 110|1.663565e-01|-2.165490e-07\n",
+ " 111|1.663565e-01|-2.450250e-07\n",
+ " 112|1.663564e-01|-2.685294e-07\n",
+ " 113|1.663564e-01|-2.821800e-07\n",
+ " 114|1.663564e-01|-2.237390e-07\n",
+ " 115|1.663563e-01|-1.992842e-07\n",
+ " 116|1.663563e-01|-2.166739e-07\n",
+ " 117|1.663563e-01|-2.086064e-07\n",
+ " 118|1.663562e-01|-2.435945e-07\n",
+ " 119|1.663562e-01|-2.292497e-07\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 120|1.663561e-01|-2.366209e-07\n",
+ " 121|1.663561e-01|-2.138746e-07\n",
+ " 122|1.663561e-01|-2.009637e-07\n",
+ " 123|1.663560e-01|-2.386258e-07\n",
+ " 124|1.663560e-01|-1.927442e-07\n",
+ " 125|1.663560e-01|-2.081681e-07\n",
+ " 126|1.663559e-01|-1.759123e-07\n",
+ " 127|1.663559e-01|-1.890771e-07\n",
+ " 128|1.663559e-01|-1.971315e-07\n",
+ " 129|1.663558e-01|-2.101983e-07\n",
+ " 130|1.663558e-01|-2.035645e-07\n",
+ " 131|1.663558e-01|-1.984492e-07\n",
+ " 132|1.663557e-01|-1.849064e-07\n",
+ " 133|1.663557e-01|-1.795703e-07\n",
+ " 134|1.663557e-01|-1.624087e-07\n",
+ " 135|1.663557e-01|-1.689557e-07\n",
+ " 136|1.663556e-01|-1.644308e-07\n",
+ " 137|1.663556e-01|-1.618007e-07\n",
+ " 138|1.663556e-01|-1.483013e-07\n",
+ " 139|1.663555e-01|-1.708771e-07\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 140|1.663555e-01|-2.013847e-07\n",
+ " 141|1.663555e-01|-1.721217e-07\n",
+ " 142|1.663554e-01|-2.027911e-07\n",
+ " 143|1.663554e-01|-1.764565e-07\n",
+ " 144|1.663554e-01|-1.677151e-07\n",
+ " 145|1.663554e-01|-1.351982e-07\n",
+ " 146|1.663553e-01|-1.423360e-07\n",
+ " 147|1.663553e-01|-1.541112e-07\n",
+ " 148|1.663553e-01|-1.491601e-07\n",
+ " 149|1.663553e-01|-1.466407e-07\n",
+ " 150|1.663552e-01|-1.801524e-07\n",
+ " 151|1.663552e-01|-1.714107e-07\n",
+ " 152|1.663552e-01|-1.491257e-07\n",
+ " 153|1.663552e-01|-1.513799e-07\n",
+ " 154|1.663551e-01|-1.354539e-07\n",
+ " 155|1.663551e-01|-1.233818e-07\n",
+ " 156|1.663551e-01|-1.576219e-07\n",
+ " 157|1.663551e-01|-1.452791e-07\n",
+ " 158|1.663550e-01|-1.262867e-07\n",
+ " 159|1.663550e-01|-1.316379e-07\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 160|1.663550e-01|-1.295447e-07\n",
+ " 161|1.663550e-01|-1.283286e-07\n",
+ " 162|1.663550e-01|-1.569222e-07\n",
+ " 163|1.663549e-01|-1.172942e-07\n",
+ " 164|1.663549e-01|-1.399809e-07\n",
+ " 165|1.663549e-01|-1.229432e-07\n",
+ " 166|1.663549e-01|-1.326191e-07\n",
+ " 167|1.663548e-01|-1.209694e-07\n",
+ " 168|1.663548e-01|-1.372136e-07\n",
+ " 169|1.663548e-01|-1.338395e-07\n",
+ " 170|1.663548e-01|-1.416497e-07\n",
+ " 171|1.663548e-01|-1.298576e-07\n",
+ " 172|1.663547e-01|-1.190590e-07\n",
+ " 173|1.663547e-01|-1.167083e-07\n",
+ " 174|1.663547e-01|-1.069425e-07\n",
+ " 175|1.663547e-01|-1.217780e-07\n",
+ " 176|1.663547e-01|-1.140754e-07\n",
+ " 177|1.663546e-01|-1.160707e-07\n",
+ " 178|1.663546e-01|-1.101798e-07\n",
+ " 179|1.663546e-01|-1.114904e-07\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 180|1.663546e-01|-1.064022e-07\n",
+ " 181|1.663546e-01|-9.258231e-08\n",
+ " 182|1.663546e-01|-1.213120e-07\n",
+ " 183|1.663545e-01|-1.164296e-07\n",
+ " 184|1.663545e-01|-1.188762e-07\n",
+ " 185|1.663545e-01|-9.394153e-08\n",
+ " 186|1.663545e-01|-1.028656e-07\n",
+ " 187|1.663545e-01|-1.115348e-07\n",
+ " 188|1.663544e-01|-9.768310e-08\n",
+ " 189|1.663544e-01|-1.021806e-07\n",
+ " 190|1.663544e-01|-1.086303e-07\n",
+ " 191|1.663544e-01|-9.879008e-08\n",
+ " 192|1.663544e-01|-1.050210e-07\n",
+ " 193|1.663544e-01|-1.002463e-07\n",
+ " 194|1.663543e-01|-1.062747e-07\n",
+ " 195|1.663543e-01|-9.348538e-08\n",
+ " 196|1.663543e-01|-7.992512e-08\n",
+ " 197|1.663543e-01|-9.558020e-08\n",
+ " 198|1.663543e-01|-9.993772e-08\n",
+ " 199|1.663543e-01|-8.588499e-08\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 200|1.663543e-01|-8.737134e-08\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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oq6JWraoPK41RJ5I5qVlfB70KOd8K1xe9cNz+FO+xCYA+XdcyvNcyABYc2YnZ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\nTkSuQmCC\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f6c021c77b8>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% Example with Frobenius norm regularization\n",
+ "\n",
+ "\n",
+ "def f(G):\n",
+ " return 0.5 * np.sum(G**2)\n",
+ "\n",
+ "\n",
+ "def df(G):\n",
+ " return G\n",
+ "\n",
+ "\n",
+ "reg = 1e-1\n",
+ "\n",
+ "Gl2 = ot.optim.cg(a, b, M, reg, f, df, verbose=True)\n",
+ "\n",
+ "pl.figure(3)\n",
+ "ot.plot.plot1D_mat(a, b, Gl2, 'OT matrix Frob. reg')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Solve EMD with entropic regularization\n",
+ "--------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 0|1.692289e-01|0.000000e+00\n",
+ " 1|1.617643e-01|-4.614437e-02\n",
+ " 2|1.612546e-01|-3.161037e-03\n",
+ " 3|1.611040e-01|-9.349544e-04\n",
+ " 4|1.610346e-01|-4.310179e-04\n",
+ " 5|1.610072e-01|-1.701719e-04\n",
+ " 6|1.609947e-01|-7.759814e-05\n",
+ " 7|1.609934e-01|-7.941439e-06\n",
+ " 8|1.609841e-01|-5.797180e-05\n",
+ " 9|1.609838e-01|-1.559407e-06\n",
+ " 10|1.609685e-01|-9.530282e-05\n",
+ " 11|1.609666e-01|-1.142129e-05\n",
+ " 12|1.609541e-01|-7.799970e-05\n",
+ " 13|1.609496e-01|-2.780416e-05\n",
+ " 14|1.609385e-01|-6.887105e-05\n",
+ " 15|1.609334e-01|-3.174241e-05\n",
+ " 16|1.609231e-01|-6.420777e-05\n",
+ " 17|1.609115e-01|-7.189949e-05\n",
+ " 18|1.608815e-01|-1.865331e-04\n",
+ " 19|1.608799e-01|-1.013039e-05\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 20|1.608695e-01|-6.468606e-05\n",
+ " 21|1.608686e-01|-5.738419e-06\n",
+ " 22|1.608661e-01|-1.495923e-05\n",
+ " 23|1.608657e-01|-2.784611e-06\n",
+ " 24|1.608633e-01|-1.512408e-05\n",
+ " 25|1.608624e-01|-5.397916e-06\n",
+ " 26|1.608617e-01|-4.115218e-06\n",
+ " 27|1.608561e-01|-3.503396e-05\n",
+ " 28|1.608479e-01|-5.098773e-05\n",
+ " 29|1.608452e-01|-1.659203e-05\n",
+ " 30|1.608399e-01|-3.298319e-05\n",
+ " 31|1.608330e-01|-4.302183e-05\n",
+ " 32|1.608310e-01|-1.273465e-05\n",
+ " 33|1.608280e-01|-1.827713e-05\n",
+ " 34|1.608231e-01|-3.039842e-05\n",
+ " 35|1.608212e-01|-1.229256e-05\n",
+ " 36|1.608200e-01|-6.900556e-06\n",
+ " 37|1.608159e-01|-2.554039e-05\n",
+ " 38|1.608103e-01|-3.521137e-05\n",
+ " 39|1.608058e-01|-2.795180e-05\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 40|1.608040e-01|-1.119118e-05\n",
+ " 41|1.608027e-01|-8.193369e-06\n",
+ " 42|1.607994e-01|-2.026719e-05\n",
+ " 43|1.607985e-01|-5.819902e-06\n",
+ " 44|1.607978e-01|-4.048170e-06\n",
+ " 45|1.607978e-01|-3.007470e-07\n",
+ " 46|1.607950e-01|-1.705375e-05\n",
+ " 47|1.607927e-01|-1.430186e-05\n",
+ " 48|1.607925e-01|-1.166526e-06\n",
+ " 49|1.607911e-01|-9.069406e-06\n",
+ " 50|1.607910e-01|-3.804209e-07\n",
+ " 51|1.607910e-01|-5.942399e-08\n",
+ " 52|1.607910e-01|-2.321380e-07\n",
+ " 53|1.607907e-01|-1.877655e-06\n",
+ " 54|1.607906e-01|-2.940224e-07\n",
+ " 55|1.607877e-01|-1.814208e-05\n",
+ " 56|1.607841e-01|-2.236496e-05\n",
+ " 57|1.607810e-01|-1.951355e-05\n",
+ " 58|1.607804e-01|-3.578228e-06\n",
+ " 59|1.607789e-01|-9.442277e-06\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 60|1.607779e-01|-5.997371e-06\n",
+ " 61|1.607754e-01|-1.564408e-05\n",
+ " 62|1.607742e-01|-7.693285e-06\n",
+ " 63|1.607727e-01|-9.030547e-06\n",
+ " 64|1.607719e-01|-5.103894e-06\n",
+ " 65|1.607693e-01|-1.605420e-05\n",
+ " 66|1.607676e-01|-1.047837e-05\n",
+ " 67|1.607675e-01|-6.026848e-07\n",
+ " 68|1.607655e-01|-1.240216e-05\n",
+ " 69|1.607632e-01|-1.434674e-05\n",
+ " 70|1.607618e-01|-8.829808e-06\n",
+ " 71|1.607606e-01|-7.581824e-06\n",
+ " 72|1.607590e-01|-1.009457e-05\n",
+ " 73|1.607586e-01|-2.222963e-06\n",
+ " 74|1.607577e-01|-5.564775e-06\n",
+ " 75|1.607574e-01|-1.932763e-06\n",
+ " 76|1.607573e-01|-8.148685e-07\n",
+ " 77|1.607554e-01|-1.187660e-05\n",
+ " 78|1.607546e-01|-4.557651e-06\n",
+ " 79|1.607537e-01|-5.911902e-06\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 80|1.607529e-01|-4.710187e-06\n",
+ " 81|1.607528e-01|-8.866080e-07\n",
+ " 82|1.607522e-01|-3.620627e-06\n",
+ " 83|1.607514e-01|-5.091281e-06\n",
+ " 84|1.607498e-01|-9.932095e-06\n",
+ " 85|1.607487e-01|-6.852804e-06\n",
+ " 86|1.607478e-01|-5.373596e-06\n",
+ " 87|1.607473e-01|-3.287295e-06\n",
+ " 88|1.607470e-01|-1.666655e-06\n",
+ " 89|1.607469e-01|-5.293790e-07\n",
+ " 90|1.607466e-01|-2.051914e-06\n",
+ " 91|1.607456e-01|-6.422797e-06\n",
+ " 92|1.607456e-01|-1.110433e-07\n",
+ " 93|1.607451e-01|-2.803849e-06\n",
+ " 94|1.607451e-01|-2.608066e-07\n",
+ " 95|1.607441e-01|-6.290352e-06\n",
+ " 96|1.607429e-01|-7.298455e-06\n",
+ " 97|1.607429e-01|-8.969905e-09\n",
+ " 98|1.607427e-01|-7.923968e-07\n",
+ " 99|1.607427e-01|-3.519286e-07\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 100|1.607426e-01|-3.563804e-07\n",
+ " 101|1.607410e-01|-1.004042e-05\n",
+ " 102|1.607410e-01|-2.124801e-07\n",
+ " 103|1.607398e-01|-7.556935e-06\n",
+ " 104|1.607398e-01|-7.606853e-08\n",
+ " 105|1.607385e-01|-8.058684e-06\n",
+ " 106|1.607383e-01|-7.393061e-07\n",
+ " 107|1.607381e-01|-1.504958e-06\n",
+ " 108|1.607377e-01|-2.508807e-06\n",
+ " 109|1.607371e-01|-4.004631e-06\n",
+ " 110|1.607365e-01|-3.580156e-06\n",
+ " 111|1.607364e-01|-2.563573e-07\n",
+ " 112|1.607354e-01|-6.390137e-06\n",
+ " 113|1.607348e-01|-4.119553e-06\n",
+ " 114|1.607339e-01|-5.299475e-06\n",
+ " 115|1.607335e-01|-2.316767e-06\n",
+ " 116|1.607330e-01|-3.444737e-06\n",
+ " 117|1.607324e-01|-3.467980e-06\n",
+ " 118|1.607320e-01|-2.374632e-06\n",
+ " 119|1.607319e-01|-7.978255e-07\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 120|1.607312e-01|-4.221434e-06\n",
+ " 121|1.607310e-01|-1.324597e-06\n",
+ " 122|1.607304e-01|-3.650359e-06\n",
+ " 123|1.607298e-01|-3.732712e-06\n",
+ " 124|1.607295e-01|-1.994082e-06\n",
+ " 125|1.607289e-01|-3.954139e-06\n",
+ " 126|1.607286e-01|-1.532372e-06\n",
+ " 127|1.607286e-01|-1.167223e-07\n",
+ " 128|1.607283e-01|-2.157376e-06\n",
+ " 129|1.607279e-01|-2.253077e-06\n",
+ " 130|1.607274e-01|-3.301532e-06\n",
+ " 131|1.607269e-01|-2.650754e-06\n",
+ " 132|1.607264e-01|-3.595551e-06\n",
+ " 133|1.607262e-01|-1.159425e-06\n",
+ " 134|1.607258e-01|-2.512411e-06\n",
+ " 135|1.607255e-01|-1.998792e-06\n",
+ " 136|1.607251e-01|-2.486536e-06\n",
+ " 137|1.607246e-01|-2.782996e-06\n",
+ " 138|1.607246e-01|-2.922470e-07\n",
+ " 139|1.607242e-01|-2.071131e-06\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 140|1.607237e-01|-3.154193e-06\n",
+ " 141|1.607235e-01|-1.194962e-06\n",
+ " 142|1.607232e-01|-2.035251e-06\n",
+ " 143|1.607232e-01|-6.027855e-08\n",
+ " 144|1.607229e-01|-1.555696e-06\n",
+ " 145|1.607228e-01|-1.081740e-06\n",
+ " 146|1.607225e-01|-1.881070e-06\n",
+ " 147|1.607224e-01|-4.100096e-07\n",
+ " 148|1.607223e-01|-7.785200e-07\n",
+ " 149|1.607222e-01|-2.094072e-07\n",
+ " 150|1.607220e-01|-1.440814e-06\n",
+ " 151|1.607217e-01|-1.997794e-06\n",
+ " 152|1.607214e-01|-2.011022e-06\n",
+ " 153|1.607212e-01|-8.808854e-07\n",
+ " 154|1.607211e-01|-7.245877e-07\n",
+ " 155|1.607207e-01|-2.217159e-06\n",
+ " 156|1.607201e-01|-3.817891e-06\n",
+ " 157|1.607200e-01|-7.409600e-07\n",
+ " 158|1.607198e-01|-1.497698e-06\n",
+ " 159|1.607195e-01|-1.729666e-06\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 160|1.607195e-01|-2.115187e-07\n",
+ " 161|1.607192e-01|-1.643727e-06\n",
+ " 162|1.607192e-01|-1.712969e-07\n",
+ " 163|1.607189e-01|-1.805877e-06\n",
+ " 164|1.607189e-01|-1.209827e-07\n",
+ " 165|1.607185e-01|-2.060002e-06\n",
+ " 166|1.607182e-01|-1.961341e-06\n",
+ " 167|1.607181e-01|-1.020366e-06\n",
+ " 168|1.607179e-01|-9.760982e-07\n",
+ " 169|1.607178e-01|-7.219236e-07\n",
+ " 170|1.607175e-01|-1.837718e-06\n",
+ " 171|1.607174e-01|-3.337578e-07\n",
+ " 172|1.607173e-01|-5.298564e-07\n",
+ " 173|1.607173e-01|-6.864278e-08\n",
+ " 174|1.607173e-01|-2.008419e-07\n",
+ " 175|1.607171e-01|-1.375630e-06\n",
+ " 176|1.607168e-01|-1.911257e-06\n",
+ " 177|1.607167e-01|-2.709815e-07\n",
+ " 178|1.607167e-01|-1.390953e-07\n",
+ " 179|1.607165e-01|-1.199675e-06\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 180|1.607165e-01|-1.457259e-07\n",
+ " 181|1.607163e-01|-1.049154e-06\n",
+ " 182|1.607163e-01|-2.753577e-09\n",
+ " 183|1.607163e-01|-6.972814e-09\n",
+ " 184|1.607161e-01|-1.552100e-06\n",
+ " 185|1.607159e-01|-1.068596e-06\n",
+ " 186|1.607157e-01|-1.247724e-06\n",
+ " 187|1.607155e-01|-1.158164e-06\n",
+ " 188|1.607155e-01|-2.616199e-07\n",
+ " 189|1.607154e-01|-3.595874e-07\n",
+ " 190|1.607154e-01|-5.334527e-08\n",
+ " 191|1.607153e-01|-3.452744e-07\n",
+ " 192|1.607153e-01|-1.239593e-07\n",
+ " 193|1.607152e-01|-8.184984e-07\n",
+ " 194|1.607150e-01|-1.316308e-06\n",
+ " 195|1.607150e-01|-7.100882e-09\n",
+ " 196|1.607148e-01|-1.393958e-06\n",
+ " 197|1.607146e-01|-1.242735e-06\n",
+ " 198|1.607144e-01|-1.123993e-06\n",
+ " 199|1.607143e-01|-3.512071e-07\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 200|1.607143e-01|-2.151971e-10\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f6c307057f0>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% Example with entropic regularization\n",
+ "\n",
+ "\n",
+ "def f(G):\n",
+ " return np.sum(G * np.log(G))\n",
+ "\n",
+ "\n",
+ "def df(G):\n",
+ " return np.log(G) + 1.\n",
+ "\n",
+ "\n",
+ "reg = 1e-3\n",
+ "\n",
+ "Ge = ot.optim.cg(a, b, M, reg, f, df, verbose=True)\n",
+ "\n",
+ "pl.figure(4, figsize=(5, 5))\n",
+ "ot.plot.plot1D_mat(a, b, Ge, 'OT matrix Entrop. reg')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Solve EMD with Frobenius norm + entropic regularization\n",
+ "-------------------------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 0|1.693084e-01|0.000000e+00\n",
+ " 1|1.610121e-01|-5.152589e-02\n",
+ " 2|1.609378e-01|-4.622297e-04\n",
+ " 3|1.609284e-01|-5.830043e-05\n",
+ " 4|1.609284e-01|-1.111407e-12\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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39uUWxIqzJI6rLVzr/50LN8bhJ8Hfimv9hDU29o59sf28Ql1nvv3Va3x87/LP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\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f6c306f6048>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#%% Example with Frobenius norm + entropic regularization with gcg\n",
+ "\n",
+ "\n",
+ "def f(G):\n",
+ " return 0.5 * np.sum(G**2)\n",
+ "\n",
+ "\n",
+ "def df(G):\n",
+ " return G\n",
+ "\n",
+ "\n",
+ "reg1 = 1e-3\n",
+ "reg2 = 1e-1\n",
+ "\n",
+ "Gel2 = ot.optim.gcg(a, b, M, reg1, reg2, f, df, verbose=True)\n",
+ "\n",
+ "pl.figure(5, figsize=(5, 5))\n",
+ "ot.plot.plot1D_mat(a, b, Gel2, 'OT entropic + matrix Frob. reg')\n",
+ "pl.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/notebooks/plot_otda_classes.ipynb b/notebooks/plot_otda_classes.ipynb
new file mode 100644
index 0000000..1955676
--- /dev/null
+++ b/notebooks/plot_otda_classes.ipynb
@@ -0,0 +1,313 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# OT for domain adaptation\n",
+ "\n",
+ "\n",
+ "This example introduces a domain adaptation in a 2D setting and the 4 OTDA\n",
+ "approaches currently supported in POT.\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Authors: Remi Flamary <remi.flamary@unice.fr>\n",
+ "# Stanislas Chambon <stan.chambon@gmail.com>\n",
+ "#\n",
+ "# License: MIT License\n",
+ "\n",
+ "import matplotlib.pylab as pl\n",
+ "import ot"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Generate data\n",
+ "-------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "n_source_samples = 150\n",
+ "n_target_samples = 150\n",
+ "\n",
+ "Xs, ys = ot.datasets.get_data_classif('3gauss', n_source_samples)\n",
+ "Xt, yt = ot.datasets.get_data_classif('3gauss2', n_target_samples)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Instantiate the different transport algorithms and fit them\n",
+ "-----------------------------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 0|1.017912e+01|0.000000e+00\n",
+ " 1|2.096083e+00|-3.856258e+00\n",
+ " 2|1.842979e+00|-1.373343e-01\n",
+ " 3|1.781632e+00|-3.443301e-02\n",
+ " 4|1.760919e+00|-1.176281e-02\n",
+ " 5|1.750958e+00|-5.688541e-03\n",
+ " 6|1.746386e+00|-2.618021e-03\n",
+ " 7|1.741793e+00|-2.636854e-03\n",
+ " 8|1.739054e+00|-1.575065e-03\n",
+ " 9|1.736474e+00|-1.486027e-03\n",
+ " 10|1.734361e+00|-1.218441e-03\n",
+ " 11|1.734259e+00|-5.863179e-05\n",
+ " 12|1.733704e+00|-3.201643e-04\n",
+ " 13|1.733018e+00|-3.957711e-04\n",
+ " 14|1.731842e+00|-6.791025e-04\n",
+ " 15|1.730974e+00|-5.012271e-04\n",
+ " 16|1.730584e+00|-2.257722e-04\n",
+ " 17|1.730492e+00|-5.272976e-05\n",
+ " 18|1.730153e+00|-1.961758e-04\n",
+ " 19|1.729837e+00|-1.828284e-04\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 20|1.729361e+00|-2.749072e-04\n"
+ ]
+ }
+ ],
+ "source": [
+ "# EMD Transport\n",
+ "ot_emd = ot.da.EMDTransport()\n",
+ "ot_emd.fit(Xs=Xs, Xt=Xt)\n",
+ "\n",
+ "# Sinkhorn Transport\n",
+ "ot_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)\n",
+ "ot_sinkhorn.fit(Xs=Xs, Xt=Xt)\n",
+ "\n",
+ "# Sinkhorn Transport with Group lasso regularization\n",
+ "ot_lpl1 = ot.da.SinkhornLpl1Transport(reg_e=1e-1, reg_cl=1e0)\n",
+ "ot_lpl1.fit(Xs=Xs, ys=ys, Xt=Xt)\n",
+ "\n",
+ "# Sinkhorn Transport with Group lasso regularization l1l2\n",
+ "ot_l1l2 = ot.da.SinkhornL1l2Transport(reg_e=1e-1, reg_cl=2e0, max_iter=20,\n",
+ " verbose=True)\n",
+ "ot_l1l2.fit(Xs=Xs, ys=ys, Xt=Xt)\n",
+ "\n",
+ "# transport source samples onto target samples\n",
+ "transp_Xs_emd = ot_emd.transform(Xs=Xs)\n",
+ "transp_Xs_sinkhorn = ot_sinkhorn.transform(Xs=Xs)\n",
+ "transp_Xs_lpl1 = ot_lpl1.transform(Xs=Xs)\n",
+ "transp_Xs_l1l2 = ot_l1l2.transform(Xs=Xs)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Fig 1 : plots source and target samples\n",
+ "---------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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bhBX799X5fKcKC7l84TyyHYV4EHC7WXckFdbD+NN7Bipsvyb16s2H11zHm1s3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\n3c2/GSgWjfHgheNT5wfXh3nw309y3cSLG445HA7+cPCO/OHgxFbHV4+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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fdef9077e48>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "pl.figure(1, figsize=(10, 5))\n",
+ "pl.subplot(1, 2, 1)\n",
+ "pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.legend(loc=0)\n",
+ "pl.title('Source samples')\n",
+ "\n",
+ "pl.subplot(1, 2, 2)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.legend(loc=0)\n",
+ "pl.title('Target samples')\n",
+ "pl.tight_layout()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Fig 2 : plot optimal couplings and transported samples\n",
+ "------------------------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/home/rflamary/.local/lib/python3.5/site-packages/matplotlib/cbook.py:136: MatplotlibDeprecationWarning: The spectral and spectral_r colormap was deprecated in version 2.0. Use nipy_spectral and nipy_spectral_r instead.\n",
+ " warnings.warn(message, mplDeprecation, stacklevel=1)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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KLor601Yv0Hs6f+MpDonqAb+iHY0z7mW8r3MalwPp4414/ww1ty7nHQDa0z7S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GyVy+hCNrDFZsAmNrewcXrVnHsz1nKKXeym2ZLNdu2jzpsxd0r2FTSyvXb92GJ8KzZ07z/SNH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ozTisMVNlxeB017UwQbO1BtKgWl+Zl4YXdZmyKpuLVoyS/xM+/qORkxvr2baskv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\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fdef6f3c3c8>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "param_img = {'interpolation': 'nearest', 'cmap': 'spectral'}\n",
+ "\n",
+ "pl.figure(2, figsize=(15, 8))\n",
+ "pl.subplot(2, 4, 1)\n",
+ "pl.imshow(ot_emd.coupling_, **param_img)\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Optimal coupling\\nEMDTransport')\n",
+ "\n",
+ "pl.subplot(2, 4, 2)\n",
+ "pl.imshow(ot_sinkhorn.coupling_, **param_img)\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Optimal coupling\\nSinkhornTransport')\n",
+ "\n",
+ "pl.subplot(2, 4, 3)\n",
+ "pl.imshow(ot_lpl1.coupling_, **param_img)\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Optimal coupling\\nSinkhornLpl1Transport')\n",
+ "\n",
+ "pl.subplot(2, 4, 4)\n",
+ "pl.imshow(ot_l1l2.coupling_, **param_img)\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Optimal coupling\\nSinkhornL1l2Transport')\n",
+ "\n",
+ "pl.subplot(2, 4, 5)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n",
+ " label='Target samples', alpha=0.3)\n",
+ "pl.scatter(transp_Xs_emd[:, 0], transp_Xs_emd[:, 1], c=ys,\n",
+ " marker='+', label='Transp samples', s=30)\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Transported samples\\nEmdTransport')\n",
+ "pl.legend(loc=\"lower left\")\n",
+ "\n",
+ "pl.subplot(2, 4, 6)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n",
+ " label='Target samples', alpha=0.3)\n",
+ "pl.scatter(transp_Xs_sinkhorn[:, 0], transp_Xs_sinkhorn[:, 1], c=ys,\n",
+ " marker='+', label='Transp samples', s=30)\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Transported samples\\nSinkhornTransport')\n",
+ "\n",
+ "pl.subplot(2, 4, 7)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n",
+ " label='Target samples', alpha=0.3)\n",
+ "pl.scatter(transp_Xs_lpl1[:, 0], transp_Xs_lpl1[:, 1], c=ys,\n",
+ " marker='+', label='Transp samples', s=30)\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Transported samples\\nSinkhornLpl1Transport')\n",
+ "\n",
+ "pl.subplot(2, 4, 8)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n",
+ " label='Target samples', alpha=0.3)\n",
+ "pl.scatter(transp_Xs_l1l2[:, 0], transp_Xs_l1l2[:, 1], c=ys,\n",
+ " marker='+', label='Transp samples', s=30)\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Transported samples\\nSinkhornL1l2Transport')\n",
+ "pl.tight_layout()\n",
+ "\n",
+ "pl.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/notebooks/plot_otda_color_images.ipynb b/notebooks/plot_otda_color_images.ipynb
new file mode 100644
index 0000000..7c04d33
--- /dev/null
+++ b/notebooks/plot_otda_color_images.ipynb
@@ -0,0 +1,322 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# OT for image color adaptation\n",
+ "\n",
+ "\n",
+ "This example presents a way of transferring colors between two image\n",
+ "with Optimal Transport as introduced in [6]\n",
+ "\n",
+ "[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014).\n",
+ "Regularized discrete optimal transport.\n",
+ "SIAM Journal on Imaging Sciences, 7(3), 1853-1882.\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Authors: Remi Flamary <remi.flamary@unice.fr>\n",
+ "# Stanislas Chambon <stan.chambon@gmail.com>\n",
+ "#\n",
+ "# License: MIT License\n",
+ "\n",
+ "import numpy as np\n",
+ "from scipy import ndimage\n",
+ "import matplotlib.pylab as pl\n",
+ "import ot\n",
+ "\n",
+ "\n",
+ "r = np.random.RandomState(42)\n",
+ "\n",
+ "\n",
+ "def im2mat(I):\n",
+ " \"\"\"Converts and image to matrix (one pixel per line)\"\"\"\n",
+ " return I.reshape((I.shape[0] * I.shape[1], I.shape[2]))\n",
+ "\n",
+ "\n",
+ "def mat2im(X, shape):\n",
+ " \"\"\"Converts back a matrix to an image\"\"\"\n",
+ " return X.reshape(shape)\n",
+ "\n",
+ "\n",
+ "def minmax(I):\n",
+ " return np.clip(I, 0, 1)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Generate data\n",
+ "-------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Loading images\n",
+ "I1 = ndimage.imread('../data/ocean_day.jpg').astype(np.float64) / 256\n",
+ "I2 = ndimage.imread('../data/ocean_sunset.jpg').astype(np.float64) / 256\n",
+ "\n",
+ "X1 = im2mat(I1)\n",
+ "X2 = im2mat(I2)\n",
+ "\n",
+ "# training samples\n",
+ "nb = 1000\n",
+ "idx1 = r.randint(X1.shape[0], size=(nb,))\n",
+ "idx2 = r.randint(X2.shape[0], size=(nb,))\n",
+ "\n",
+ "Xs = X1[idx1, :]\n",
+ "Xt = X2[idx2, :]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plot original image\n",
+ "-------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.text.Text at 0x7effc9a46ef0>"
+ ]
+ },
+ "execution_count": 4,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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CEak80UoJuMvPYUazG3B4UEMNJxBbHX2zO/ZRkfDDzwKo2oWbuJRctlKPMJzS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\nU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SSUldaKMNk6ALXMMQ8Y0q9ARfNsXQ8FxmYcgpeCk2pSzTJyGBt+9LM9b3AwrBhkRJzH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\ng4/KMWgODg4ODj4q/xcSFp/MDyAjtgAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7effced885c0>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "pl.figure(1, figsize=(6.4, 3))\n",
+ "\n",
+ "pl.subplot(1, 2, 1)\n",
+ "pl.imshow(I1)\n",
+ "pl.axis('off')\n",
+ "pl.title('Image 1')\n",
+ "\n",
+ "pl.subplot(1, 2, 2)\n",
+ "pl.imshow(I2)\n",
+ "pl.axis('off')\n",
+ "pl.title('Image 2')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Scatter plot of colors\n",
+ "----------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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Lm3ZQU5XlknMWcObCWT6K1OPxeBiloviDB9bxxIu70ga/UFwMjMDEGYIgpLTG\npsYx5CK0KkBDiv6/Qf10CzVQ4xjnIB/HhNlMsUxcNjTccM2ZvPMVpx3RuM+aO4VbfvcsNq0249IA\nF0Oi3JLmTzZPOLqWSLl8RJwGyAwUu/pxNbzWL496PB5PRUadKCrw0W8tw1lHwOCIUxdFJU1vHS7n\nihVp4nxSvk1RnFBSoQUkjjFxSbpCCASOqePHcdWFc7ls8VQuOm1KWe7e4TJvagsXnTaTZau3kovi\n1FpMumkEqXFYlQl47aWLjuj4vX05bv3Zg6x8cQsALY11vPmay5g327db8ng8nkNh1InittZu2rv6\nkiLaBVETwZTU9lQbY4yBKE6swhKXXdzbhwlDJDBYIEAwcTw4ET/Vx92tnbznytOKy6T3/34jX//5\ncra3djJzYiMfeP35XHLGoXd1+PAbLuaRVZv51VPryEeWtrZu9nf0ElYFRNbyqgsXcNnZpxzRtfnP\nH97L1h2t2HSJdk/bfr75w1/yV3/2Bia0+MoyHo/HczCGVRRF5GrgSyRdmv5LVW+ssM+1wCdJjMCn\nVfVtBzrmnv29BLbExEuDU5xzmEyYRIZaBwMiLEs7F2kUoxFUhclWY4doBxVDUCM8tnIHr71kHr96\nYh3/9P3fkUvLsK3d3sbf3HQf//LeV3DpGbP45bIX+OnvVpKPLC8/fx5vevkSaqrKa8kZES5dPJtL\nF88ubtu0cx9tHb3Mnd5CY101zilbduzFGGH65OZD8vdt39XG9l1tRUEsnoK1PPj4St5w9cUHPYZn\n7DEcc9DjGcsMmyiKSAB8DbgS2AosF5E7VHVVyT7zgb8FLlHVfSIy6ZA/IK05WrYpiiETYkpEJGn9\nlIhe4GJMnATkaGBwJiA4yHJoPnI88MxGLj5jKl/+yeNFQSyQiyxf/sljPPTEen735Hr68omJuXV3\nB/evWM83/vYNZMIAVaU3F1GVCQkGRKrOntLM7DR9YvWGHXz55l/R25eUYmuoq+HD73oVp0yfcMBx\ntrUnHSkGhug4p+xq7Tjgez1jk2Gfgx7PGGQ4LcULgLWquh5ARG4FXgeUlnK5Dviaqu4DUNXdh3rw\ngiCWd31yxYKmSlI82wSCUQicxaSClZR9s0SxxVQowVaKdcqvV6zjgac34EqdkCVs3tlOx5795EsE\nMx9Ztu3p4HdPbqC5LstXb3mAPfs6CQLDVRcv4ro/uoRsprxzx/7uXv71prvI5ft9m3vaOvnnb9zB\nV//+HVRyi7cOAAAgAElEQVRXDVXBHKZNbqmcfxgGzJ3lfYonKcM6Bz2eschwiuJ0YEvJ863AhQP2\nWQAgIg+TLO98UlXvGXggEXkf8D4AaloIKghi8XlqLarGiLW4GMJsFpOPy/ZPS5gS52PCmgzEFQQv\ngNBE5GMlii3j6jNYN3i/QJMKOwPpzcX8dsWLrHxhS1HorLPc++jzdPXm+Jv3XFm2/yNPri3mMZbi\nrLJi5QYuPXcB+zt7+N97H+HpVRsIw4BLzjudV79sKS1N9Zx9+hyefn4DUSrOIkJVNsNLlh5ZtKxn\n1DMsc3DWrEP3oXs8o42RDrQJgfnAFcAM4AERWaKq7aU7qeo3gW8CSOOsyuZa/97g0hZOqVhFfTkC\nGdx9XkhaKn3v767m6Rf38MtHN7B5VyddfTkksASBK8tRzOdigszgvowOh3ODk/czoWHbrnbyUXkR\n7nxkefip9bS/qaespmj7/u6ioJUSWUtHZy+5fMRnvn4b+zt7khZPwK8eeor1W3bykfe+nre+7jKm\nTWnhwcdWkctHLJo/g1e/fCl1tUeX4uEZ0xz2HFy6dOlB5qDHM3oZTlHcBswseT4j3VbKVuAxVY2A\nDSLyAskEXX7AI8cxmnaoKA1C0YH9BFWTvoFGyivHlDB1Qh0XL57GxYun8WevPwvnlIuv/xbdfYOX\nIkUhG0C+zKp0IBCGBhdZSg29wBiMOioYf2TCgD37uspEcdG8adz78Er68uWewdAYTpszlcd+v4bu\n3r6iIAJEsWX95p1s2rab2dMn8bKLl/Cyi5cMceE8JxnDNwc9njHKwWuTHTnLgfkiMkdEssBbgDsG\n7PNTkl+oiMgEkqWc9Qc8qiq4GI37cHEfNurF2bi4fCmFThZpVCqkhcBVBy1xVmcD/uFPk6jMvlzM\nJ2/6NWe/46u0t3Vi+3K4Eh9dNjRcfcECaqoCwBYfglKVCfj4n76c2VOaqcqG1FSFNNfX8C/vfxVn\nzJ9aFvhTILaWaRMby7YtWTCTU2ZMKCu1VpUNWbJwBvNmTWL9ll3k8wNbPyVs2dF6wMvmOSkZnjno\n8Yxhhs1SVNVYRD4A/JLEV/FtVV0pIp8CVqjqHelrV4nIKhKV+StV3Xvwow+IOnUR4ixi0w71mQxY\nV/QhGmexGhEGVWUGo5iYXyxbxZnzJ3Djd+/n4ac3kU8T+J0DcpaahjrEGE6bPYGPv+NSNu5azA1f\nuQvrHArEseP6113AFefM5Ypz5rJ1dwf5yHLK1GaMEaaMr+PBJ9fRl4vScSvZTIbXXr6EcTXlRcyN\nEf72fa/h14+u4oEVawiM4eUXLeLy8xcCMHViM5kwIIrLl1hFhAm+w71nAMM7Bz2esYlUChA5kZGG\nmZq56CODX3BK6BKrMMxkkNQGNjgCtYSpBRkEBhMIYhwiSXf5mqoMxlpimwaolBy2paGWb33iTSya\nPbG4LYotK9ZsoycXcd6CaTTV1RxwzM+t3c4nv/G/9OT6EARjhFdeuJgPvuWqw6qQ09ndy999/mb6\ncvniNmOEiS2N/NOH3n5U1XY8xw4ReUJVl470OIaLpUuX6ooVK0Z6GB7PkBzNHBzO5dPjS0l2vrWF\n1ItUCEuaAwcZhwlscZnVOaUvF5GzlSNa93X2kjHllykTBly8eBavOHfeQQUR4Pb7lpGP8+noFOsc\n9z/xPHc/9PvDOsX6cTX89fveyKxpEzHGEBjD6afO4q+ue6MXRI/H4zkGHNLyqYjUAn8JzFLV69KE\n34Wqeuewju5w0JL/O0uh7XCmpCeiDPETwDrFAeHgAFUCIzy3fienzhx/RMPq7s3x5OpNg3IIc/mY\nH933OK956TmHdbwZUyfw9x94M719eYLA+FZPJwmjYg56PGOAQ7UUvwPkgEKtsG3APw/LiA6FgUu+\nqgSlmuMcLh8R2DyG/n11cEApkPgYG4ZI4s+EAdMHBMQcjG279/HEqg3sbe8cFElayp59nXzia7cO\n8hEeCjXVWS+IJxcn1hz0eMYoh3pXnaeqbxaRtwKoao+MVAO+kqjS5DmYNKE+6fxUqGoj2MgRmPJO\nGqKJH640Sb46G/LFG/6QD33hDqK4XzkDI0ydUM/SRdMPaWi9fXk+8fXbeeaFLWTCgHwUc+k5C7C2\nguipAo6Va7fws988zpuu8rVJPQfkxJmDHs8Y5lAtxbyI1JAuUorIPJJfrSOC5m0SbaoO0SSiE3WI\nxohaUIc6h3NKlLeoKoERqrMhb375El59yQKyYUBVJmByyzi++pHX8Irz5/GDT72FOdOayYYBmdBw\n4Rkz+d4/XnvIDXi/+IN7eOaFzeSjmO7eHFFseeCJ1cRxVJYSoqppGTpLPoq599Gnh+9iecYKJ9Qc\n9HjGKodqKf4jcA8wU0R+CFwCvHu4BnUouMgRSKHg9wDUglXEBKhVqiXgf//tzSyeN7HYtaKnL6Kz\nJ8ek5nFF0Ttr/lR+8aU/ZW9HD9kwoH5c1cAjD0k+ivnt8lWDlkKtc7i8ks26ZDyYdB23P2UkPoLl\nU89Jxwk3Bz2escghiaKq/kpEngQuItGgG1R1RLLFJzbWsA9NqrmpIxwYdelsYv6qQwi48sK5fO6G\nK5kzvblst9rqDLXVlQtsj2+srbj9QOSjeEDdUsWIK/o0XeyAuNjeqkAmDLjsvNPp7u1ly449NDfW\nM3l8+Vg9nhNpDno8Y5lDjT59afpnZ/r/00UEVX1geIY1NHW1WboyMTavyVKpFaRQ11T7ra8wMPz8\ni2/lsnNmD3msSvTlInpyeZrra+no7iUbhtRWJ0E4sbXs7+qloa6GMCgPVR1XU8XUCU1s3dUGJOkg\nBh1UWc5FiTAaEWqqs0xsaiCQiOs+8XkyYUBsLQtOmclH3/MWxtX4mqWehBNpDnpGjn27W3nmkWV0\n7N3HjFPnsviC86jy94ljyqEun/5Vyd/VJC1pngBefsxHdBC27umAGRESKIhDokzqV+xHUS49exZL\n5k/iO3c/xq59nVywaDZXnD0PYyq7Ubt6c/zDN37Grx5bhaIUNE8EXnLmqSw5ZSq3/GIZUWzJhAHv\nfcPlvOu1lxatPhHhL9/1h3zsi/9DFMeJv3MIV2RDbRWzp03gyovOpioj3HT7z4nimCitprN6w2a+\n8oMf87Hr3n5sLppnLHDCzEHPyLBpzYvc/f1bsdaizrFt/UaefuhR3nLD9dTUjRvyfc5atj2/mn07\ndlDX0sKsJWcQZg/cMu9k5ogq2ojITOCLqvpHx35IByZonK7Bef8HIREdiQ3GBkhqIxaKglc3xdRW\nGRChNxcxrjrLkrlTuf2f30NHVy+f+f4vuG/5asLA8IbLz2btxl08/cIW8rElCMtrhxtJCoqH2u+/\nrK7KcMPbruLNr7qobHybd7Ry2y8f4/7lT5MfIh0jzEZJFZ3AMK2lie27B6+ChWHANz/5UerHHf5S\nrmdkOR4VbUZyDvqKNscfdY5vf+bz9HR2lW03QcCSi8/npdf8YcX35Xt7ufc//pPe/fuJ83nCbJYg\nk+Gq6/8vdS0tx2PoI8LRzMEjTXTbCiw6wvceHQpg+7MPQ4cTRWyAqEDgMOMiYpT9+SS8NsDQ3Zfn\n6bXb+MZPH+aWXy1jT3tXMaH+e3cvQ9URQFq9ptzEc5r4MLXklb5cxLd+8sAgUZw5ZTw1VUoU5dK9\nB5qLiWjnoggi2LGncpnJwBh6evu8KHqGYuTmoOe4s39fO/m+wcHGzlrWr1w9pCg+fe+v6Nq3D03T\nwuJ8njiKeOB7NzOutpp8Tw9TFy1i/mWXUTVuaGvzZOJQfYpfob9mjAHOBp4crkEdcCxGcdLfKSIg\ngMCgQQwo2WpH6Qqpg8S3h9Cbj/nOXY/Sl+8rqzDjit00FBUdMgVjoE3d1tE1aJ+HnlzJ3Q8uJ7YR\nRpJAnuR4ybvDjC2zQp0qgcig5sLZTIYJLU0Hvhiek4YTaQ56jj+ZqizqKlcfqaquHCXvrGXzM88W\nBbGIKh179tCrSbWv7r172fL73/PKD32ITLX3Tx6qpVi6VhIDt6jqw8MwnoNinVIa4mKxJIunBd/e\n4Pc4KL5nd/t+MsHQolfIJ6wkjAO3zJo6uPTbz377WNoRA5xGCCZJw0DJZB1mwGerCNXVVeTzEbG1\niAiZMOS6N72GYAj/p+ek5ISZg57jT21dHVNmz2T7xs1l4hhmMpx5SflqlY0ilt/1c9Y9uQKJ+++N\nZahirSUwBmctue5u1j/2GAsvv3y4T+WE51BTMr433AM5KkxEEDoQxaoQECCFQqeqqDiUIPlqqOJU\n04LgyfJm6ZfGOiUMQNUhxiLGAopogNiQQr2DqmyGj7zjDwCI4pinVq8jl4/o6u4pG5riQB3ZTEg2\nDLFa/qutubGef/vQddz5u0d57sWNTBrfzDUvewnzZ88YlkvlGZ2c8HPQM+xc/fZr+elN32N/2z4Q\nwVnLaeedxennnwskP+jXPPIoK+65C2eTH+aGAIMpF8a0KpgAzjmMMbg4ZtcLL3hR5CCiKCLPMnjV\nEBI1UVU9c1hGdUDKLbkgsIRhaeqDYjUmIOwXRiwqNhE2E4GUnlRSNrxUGnNRTHWVS9pLpXsajXAm\nIhtUs3DmTD741qu4cMk8Vq7bxEe/cBNRHKMosY3ACOIMhrAQ/kMYCGcumMPzGzYTxTGZTEhgDB9/\n79tobmzgHde8ativnGf0cWLOQc9IUFtfx1s//H52b91OV8d+Js+YRl1Tf13mJ+68i1UPP4xKXLw/\nOmyZIBYaBgUudUGp4qzFhCE1jYdX43mscjBL8TXHZRSHgyrq8ihgAghDU3Gp06pNJSktAwdkgggx\nWr7GqooSExYFDIxJBVFAnCIlUaexy9GV6+DM+TPo7u3jAzd+jSi2iEmEOTm0osZi1ZKVZHvsYqK4\nl4+9981s3L6b5vo6Ljl7MdVVPjTac0BOvDnoOaZoKkxBePCFOxFh8szpTJ5ZXo8539vLqgcfwtoY\nky2/H1ripI8rhsA5JLUS0wMmVqNznHrJJcfojEY3B/xXUNVNA7eJyARgr454d2LFHbA6mibl3nDp\nKqnDBAwWUAFw1FVliWKLU0tg0lPTckFMNik7Wvdxx4MreGr1mrSsW6kglh+74M+01vLMmnU4p3zu\nI+8/ivP2nEyc2HPQczSoKst+fT8P3nMvvT29NDQ2cuUbr+GM88877GN17NmDCUNsHFfeQUDUYSp0\nGCrUjm6aOrXspa4d29n7whoyNbVMXHImmZqD944dCxxs+fQi4EagDfg0cDMwATAi8k5VvWf4hzjk\n6ADFOSWoFDiTVNxO9hQIyxIqygmM4RsfewenzZ7Kv37/5/zysaeJNV9xX0jSKR58aiUr176Iohyo\nv29pkE9sLavWbWTX3jYmjx+7OUKeY8eJPQdPXnJ9OdauXkeYyXDqaXMJ0mof61av5e7/uYud23Yw\naeok/uCPX82CMxZWPMYjv/oNv7vrHqJ8cq/Z397OHT+4hTCb5bSzlhzWeOqam3GpIKoFgvJgwSCT\nZeqU6bSuW9f/6z0VSEkbFOx89hnqp05j3MSJPPeD77Pz90+S3MFAbgs598/eT8up8w9rXKORg9nr\nXwU+DjQCvwH+QFWXichpwC0kBYpHFBsrxgyIFlUttv9ICoY7DA40QBkcWdpcX8tLlpwKwPtefwX3\nPf4USQep0s7FqdVJUlZuQlNDsfj30HKrg7aHQUBbR6cXRc+hcsLPwbFGHMXs2dNGY2M9teMGW0eP\nPbicm79xS7E6ViYT8sGPX0++r4+b/u0/idKiHRs6N3DT577BH73rTZxx3pnUNdUDkOvtY/++Dh68\n596iIBaIcnnu+/FPmTVvDrV1dYc85pr6emYuPp0tq1Zhozi5VaVFSMIwQ7Y9onX7i7iMQ6qDJO4B\nLS6lmnzME//5LXBK9fgGtK+z7MamLubJb3yVi//6b8mOqyMzrvLYbF8v+fZ2ECVT30RYO/ryrA9Y\n0UZEfq+qZ6d/P6+qi0pee0pVD69t/DFA6iepnHctBT0XLJlsSBCa9LmCRgSSOJgDMRhRQiOIGEwY\nFMZfDNj5/PXX8tpLzubOh5dz4/d+TE9vDhEhDKvSHMeIwhIpAAqvf9lLWLVuI1t3tQJSVhaulOyA\n+qdV2Qy3ff7T1AyRW+QZ/RzLijYn4hwcyxVt7rnzfv7nB3fgUj/fRZecy3V//nay2STneNf2XXzq\nozcWha9ATW0NUyY3s2vrjuI2cUoQuVSYQmbOP4VpMybz+wcfR4zAuHLfjMSWwDrEKsYJjS3jueo9\nb2H24oWse+pptjy/hvqWZhZfejF1zUkOc2nQYRxFPPaTn7Ju+QqIepA0yjTsBNyAxAyBoCGDqQoI\nevMEeVt8PVMjSepY6dhQQhwm9Xs2nbqARW9/D5naJOHfxRGbb7uFthWPJ/1sUSRraDrzbGb98TsI\nqo5v/uNwVrQpzRbtHfDaCPozLGARMYQZixIR5YSMAZOR/tUBHE6Trhku/f65SAiCKpAkd/Di0+fx\nsnNP4+obPsm+zu6k0gyAc0jUhxiQQMrFTuDnDy7js3/+Hj77nVvJ5yKs7RfG6myGMAgJcERRVGwy\nXJXN8s7XXu0F0XM4nKBzcGzx7DOr+fpXvkfb7vayaM3HHnkKYwzX3/BOAB7+zbLypuGaWFtxro+t\nG7Ym7ewCgyiJIAJoIlibV73AludfwEjS+Dys7e+YI84lgphXJJ8UEunY0crtN36N2oZaxMREuRxB\nGLL8zl9w+oXns2HFU+S6e2iZMY3L/uTNTF+0kEuu/WNmnjafh2/+HnE+n3x7XKX2euC6I4zGqSCW\nRKgOKOpVEEQRUJss0bavXcNz3/4PzvnARwHY8uPb2PfEclCLhOnX0lk6nnmSjTZm3ruuP/p/pOPE\nwUTxLBHZT3KJatK/SZ8fVPpF5GrgSyRutf9S1RuH2O+PgNuB81X1kH+CaprzJwIEinWUxJAmwwxk\n4PKqYm0fRrKExvDFG97G527+MXva92MLSbGqhE4RbPIFr1QRQBNf5Ff/+s/5zh33smnnLhbMmsFV\nF53LpJZmTp05jY7OLm65+z5WrFpNS0MDf/yql3HxWWcc6ul5PHCCz8GxwAsvrOfGz36duCcalOie\nz0c88uAK3n3dtdTUVtPV2Y1Lq2EVGp0D2IKlpSCRJSyWi9SkTnO6FKkKVhVjBNttCeoCRBUTxahV\nTJ6yMahTutu7yVQn0fY2jsEpq3/XX7ehbet2fnbjvzP79EVc+q63smP1aqK+vnSMlUpNFo7tMHmH\nqhT9i0n+o2BKAgcNgyvpqLV0bdtCz+5dVDc107b8MdTGSFi+MqZO6Vz1LFHnfjL1DYf6TzIkGuWx\n2zYgmSxm2imH3AD+cDhY9GlwoNcPhCT9nL4GXElSp3G5iNyhqqsG7FcP3AA8diSfo2mGhQhgSpYT\nVAnVEmRk8IXTpNrM1ImTmDq+iV+veLZfEIHAabFqqTrFiUOk/Dgi0FRfx+lzZ/NvH7qu4tjGNzXy\ngbcd93rNnjHEaJiDo53bbr2TfD6PGUI8jDF0dnZTU1vNmUvPYPlDK8j19SWdcAbsm5SVhNi55Ae6\nxqTxnUBy3zBicE7RXBL1GZoIDcBYAwysYqWIcahLgmEQwWiFUHdVNj23kp3/8Eky1Yqz/VGoxoQE\nbuDXSDHGgbWoLY+KiHMZsmG/uShUrhQmQUCuYx9htgpEks5FA/dJKgTQt2fnUYti/pll5O76AZik\nUbvUjKPmrX9BMGn6wd98GAxnHbELgLWqul5V88CtwOsq7Pdp4F+BvqP/SMU5h6aCKDLE6lL6nfrC\nX7w9Kas2oDdi8nVQEIvaCM3ncbkcNpej4INtrKvj7AVzj37IHs/wMQJzcPSxdet2AFSSZcuBhJmQ\n8RMSH96Z557B3AVzCA5moaiCJvWYoSAviiqJS8fGhPkI6c7hOh22U3F28GcHoSXMOIwppE5YYiyD\nYkFEEAMmzJcJIkBUHePKrL1EaEMTgThcqNjAFc/d5SPivBCmKRhO+w3JslOMY+qmzSDT0IDJZov3\n1UoYc6S9JxLs7m3k7vw+RDnI9UI+h3a00XvzF9AD5+YdNsMpitOBLSXPt6bbiojIucBMVb3rQAcS\nkfeJyAoRWUFUcKv0p1uUoi7Cxfnkl8QBPC6ilg9//j/54d3387rLLyCbKf1HUzBxsuxR/J2XlGtz\n+RzN9XV86xMfHrI3o8dzgjAsc3DPnj3HfqQjyMxZySVR098YoEC2KsOfvPuNxZQLRZk7ZwYaRRDH\naD6fPKIorUmaPEKJk+jOksVQoZAoD0F/eiDOgVrF9rkysRNRTDCwUbmUlCMBnGJ6I4KuHEFXRLzf\nom6gYEI8zlE/czJhTQYTWjKZfHLckocLtXjusy+/gqqaENE+1OUoVBIrYLJZpl58GVvuup0VH38/\nudw+nLqK4olIGnxz5ERPPAB2cA6mRnnshjVHdeyBjNhdXZIabF8A/vJg+6rqN1V1qaouJVNN4SsR\nZkpEUdO1++QJcfqPoE4H/6pSxdiYHa1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xowr1h3YoOukJXV8KM12+EIgiuXa31SUjWIsa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\nSCQi/x+ffxVo88QyfAAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f000447e908>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "pl.figure(2, figsize=(6.4, 3))\n",
+ "\n",
+ "pl.subplot(1, 2, 1)\n",
+ "pl.scatter(Xs[:, 0], Xs[:, 2], c=Xs)\n",
+ "pl.axis([0, 1, 0, 1])\n",
+ "pl.xlabel('Red')\n",
+ "pl.ylabel('Blue')\n",
+ "pl.title('Image 1')\n",
+ "\n",
+ "pl.subplot(1, 2, 2)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 2], c=Xt)\n",
+ "pl.axis([0, 1, 0, 1])\n",
+ "pl.xlabel('Red')\n",
+ "pl.ylabel('Blue')\n",
+ "pl.title('Image 2')\n",
+ "pl.tight_layout()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Instantiate the different transport algorithms and fit them\n",
+ "-----------------------------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# EMDTransport\n",
+ "ot_emd = ot.da.EMDTransport()\n",
+ "ot_emd.fit(Xs=Xs, Xt=Xt)\n",
+ "\n",
+ "# SinkhornTransport\n",
+ "ot_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)\n",
+ "ot_sinkhorn.fit(Xs=Xs, Xt=Xt)\n",
+ "\n",
+ "# prediction between images (using out of sample prediction as in [6])\n",
+ "transp_Xs_emd = ot_emd.transform(Xs=X1)\n",
+ "transp_Xt_emd = ot_emd.inverse_transform(Xt=X2)\n",
+ "\n",
+ "transp_Xs_sinkhorn = ot_emd.transform(Xs=X1)\n",
+ "transp_Xt_sinkhorn = ot_emd.inverse_transform(Xt=X2)\n",
+ "\n",
+ "I1t = minmax(mat2im(transp_Xs_emd, I1.shape))\n",
+ "I2t = minmax(mat2im(transp_Xt_emd, I2.shape))\n",
+ "\n",
+ "I1te = minmax(mat2im(transp_Xs_sinkhorn, I1.shape))\n",
+ "I2te = minmax(mat2im(transp_Xt_sinkhorn, I2.shape))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plot new images\n",
+ "---------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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qnzjnIq/1I2p6Hg8LrnQj2q5mhaeT3K6lOF7sx4gIJ7FhVe7rRJWbGvikHDO2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\nmAs7GYPLt0Xyl0n9QKsOOaMpcDshO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ABNEa2EBnch7ARCOm9CmCVYb1tCE06JwN2xDNGH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\nAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7effc8072a58>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "pl.figure(3, figsize=(8, 4))\n",
+ "\n",
+ "pl.subplot(2, 3, 1)\n",
+ "pl.imshow(I1)\n",
+ "pl.axis('off')\n",
+ "pl.title('Image 1')\n",
+ "\n",
+ "pl.subplot(2, 3, 2)\n",
+ "pl.imshow(I1t)\n",
+ "pl.axis('off')\n",
+ "pl.title('Image 1 Adapt')\n",
+ "\n",
+ "pl.subplot(2, 3, 3)\n",
+ "pl.imshow(I1te)\n",
+ "pl.axis('off')\n",
+ "pl.title('Image 1 Adapt (reg)')\n",
+ "\n",
+ "pl.subplot(2, 3, 4)\n",
+ "pl.imshow(I2)\n",
+ "pl.axis('off')\n",
+ "pl.title('Image 2')\n",
+ "\n",
+ "pl.subplot(2, 3, 5)\n",
+ "pl.imshow(I2t)\n",
+ "pl.axis('off')\n",
+ "pl.title('Image 2 Adapt')\n",
+ "\n",
+ "pl.subplot(2, 3, 6)\n",
+ "pl.imshow(I2te)\n",
+ "pl.axis('off')\n",
+ "pl.title('Image 2 Adapt (reg)')\n",
+ "pl.tight_layout()\n",
+ "\n",
+ "pl.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/notebooks/plot_otda_d2.ipynb b/notebooks/plot_otda_d2.ipynb
new file mode 100644
index 0000000..038434a
--- /dev/null
+++ b/notebooks/plot_otda_d2.ipynb
@@ -0,0 +1,320 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# OT for domain adaptation on empirical distributions\n",
+ "\n",
+ "\n",
+ "This example introduces a domain adaptation in a 2D setting. It explicits\n",
+ "the problem of domain adaptation and introduces some optimal transport\n",
+ "approaches to solve it.\n",
+ "\n",
+ "Quantities such as optimal couplings, greater coupling coefficients and\n",
+ "transported samples are represented in order to give a visual understanding\n",
+ "of what the transport methods are doing.\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Authors: Remi Flamary <remi.flamary@unice.fr>\n",
+ "# Stanislas Chambon <stan.chambon@gmail.com>\n",
+ "#\n",
+ "# License: MIT License\n",
+ "\n",
+ "import matplotlib.pylab as pl\n",
+ "import ot"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "generate data\n",
+ "-------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "n_samples_source = 150\n",
+ "n_samples_target = 150\n",
+ "\n",
+ "Xs, ys = ot.datasets.get_data_classif('3gauss', n_samples_source)\n",
+ "Xt, yt = ot.datasets.get_data_classif('3gauss2', n_samples_target)\n",
+ "\n",
+ "# Cost matrix\n",
+ "M = ot.dist(Xs, Xt, metric='sqeuclidean')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Instantiate the different transport algorithms and fit them\n",
+ "-----------------------------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# EMD Transport\n",
+ "ot_emd = ot.da.EMDTransport()\n",
+ "ot_emd.fit(Xs=Xs, Xt=Xt)\n",
+ "\n",
+ "# Sinkhorn Transport\n",
+ "ot_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)\n",
+ "ot_sinkhorn.fit(Xs=Xs, Xt=Xt)\n",
+ "\n",
+ "# Sinkhorn Transport with Group lasso regularization\n",
+ "ot_lpl1 = ot.da.SinkhornLpl1Transport(reg_e=1e-1, reg_cl=1e0)\n",
+ "ot_lpl1.fit(Xs=Xs, ys=ys, Xt=Xt)\n",
+ "\n",
+ "# transport source samples onto target samples\n",
+ "transp_Xs_emd = ot_emd.transform(Xs=Xs)\n",
+ "transp_Xs_sinkhorn = ot_sinkhorn.transform(Xs=Xs)\n",
+ "transp_Xs_lpl1 = ot_lpl1.transform(Xs=Xs)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Fig 1 : plots source and target samples + matrix of pairwise distance\n",
+ "---------------------------------------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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gT4qzXkLy10DcG42+S5ImyEqpMhVWjV3rir22xC8IVkiqCcl1u3j2u5W8s2sH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\nxjrvokYGGT+CfUtQXHT2c+2vD3ut7BT2dYilLge+SM/ZunF9YIwjQcEdC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Avs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\nB/u4Lir5zTcvAAAAAElFTkSuQmCC\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f98066d6470>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "pl.figure(1, figsize=(10, 10))\n",
+ "pl.subplot(2, 2, 1)\n",
+ "pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.legend(loc=0)\n",
+ "pl.title('Source samples')\n",
+ "\n",
+ "pl.subplot(2, 2, 2)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.legend(loc=0)\n",
+ "pl.title('Target samples')\n",
+ "\n",
+ "pl.subplot(2, 2, 3)\n",
+ "pl.imshow(M, interpolation='nearest')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Matrix of pairwise distances')\n",
+ "pl.tight_layout()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Fig 2 : plots optimal couplings for the different methods\n",
+ "---------------------------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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eNb6/H9bCZr+dtbVsiTSu1SQ979xK0o9RWQk4Niqflq1t1Wles64Ods+NSPUM\nz2sWlxTEMCVBZYVsNe3i6VXFGRjQZlTCxOrVnZ2p+vpuTa/miqXywXc8vVZUAI6N+X/nJsmF9OqH\nd3gdAI0gpIP1ykw1BWkgnzw0dR1xONSBYWaAoWGkL3X4i+kLl5C+IDOyjaoqadQubI4cpsY9iluD\nECMjsN94F8ToKIwl7bBPnIbZ2CjHVG6O6fNutreapOedW2l6IEZDzQUcO/AQCyeIf9x+p2x+oNxw\n45KCGKYkGBpGuqPTX9T06oZOhA3mMJ5e0w9tgRhLw1i6CPbJMzI/ALpeba+J0Hh6DTfvcewg5lg4\n0hBPpSDu2QjaeofmQWa9MlNNQRrIU0mSt/fZywfYeGaYKYIsM0iogSzP5JVocgYHpVEbSuwB9DrH\nzu1hWR7ue6/Jm+rpczBXLfez4Y2Na7VzAIDV1hpJplO9YcJWwj3U6wFg990M4h9fPSzru6o36Jj6\nxgxTCmTUqxs64RnMSXh6tV7YBzg27FNnYa5aLvMDkINelyzS4ozVa1Kvx+67CTEyAjEyAnrlIMTe\nI3p3Pa71zUwxJW8gMwzDMAzDMEwukBin000+qKF6cTc9nO/LYBifZy8fgLnw9D4hxNZ8X0shwppl\nEjFMwLHR/9M7MO/r+/1kTHP9athHT/j/+rtXVGjVTozq6sj0udnYqNXZ9abh1eNeqd2FWzcu8TRA\nDKzX2UucnpLo/J/3ovWTL0fWmyuXafklSZz/3/dgyf/KrunKbvE8+sWNgtIre5CZomUmQ2Q4MZOZ\nLRgb1iRuUzubZY2bjFn/8mVc+eqyYP2lKwAQaSoTLgUYdzMPtyh2hoejJQT7CjvZm2HyATU3Zr3v\ncELBBBpLx64P0/rS6Pg7FTBsIE8hHNc8s7DRWviomeVWWyto251yfaZSaoYJs3ZekO1OpGXce5gr\nl0XWxWE21Mc2KIFhwn7wLtgP3iW3GyasJYu0xiGzEefQ64nb/M5mEyB9/iKaf+x4MFZ//4THyoZC\nnB0tJqzWFtgP3jX+jkQwa2q06hRx5eHC8chJmHV1sU1LYJgYfXQrRh/dGuh1nERCJko2nl+P5T8d\nb89kqm6iUvbcvqzPVYiUrIGcD0P10ZZNbLQxsxIqs/QkGcP028N6N85052UItw10bAMCt06q2VAP\nYTug9SvljVAImXGvdOoyVyxN/qF3zw24N/meG7p30R2D7loLa+chWDtl3WUyCE5Pb5D4w0l6TImS\npFf/NYBq1PCOAAAgAElEQVT0lS6YL+1PHsN92DXnz4cQItArXAMqpFfn4PH4gZRzm00LYPf1acm7\nvl63rEPqhUNIvRDoVdzsj+zHMFNFyRrIbKgWJ+yBL07EWFqva+zY/rJIp92bZfBzYzbURwfxGoR0\nd8MZGIBz8Lg0bImkV9ftzAWM0+VOObfX9EDzWLtjiL1H/CoWzvCw/Fedzle7+M0SvJJ6uWC/MQsv\nYwK+11FtIgFg9LFtsftnCv9gsieTXr1/jTkViQ09APgPu2G9Ulm5DMWZgF7trmuAEFq7aV+vew77\nXTKdkREIR8Duu6ntZ65dme1HMGu59c67x99pHG6+Z0dW+6m18YuRkjOQOcyhuOEHm+InXMYJOzbI\nm5xyQ/a65AHA4E/cLTtvJXmAhNDLOcWd0zW4nfv0748X4qF6rGnLepi188Z9HwBiS9OVMuHY3mww\nv/fahM/nl9VzH448yr+zJ3b/TOEfzMQIhymIezYCSJjlAXDrXTtw6107EvUqxkbHDcUxa2rkOUJ6\n9dar7aaNTetg1tWFTqL/nnjYx09lPC8DzH1y96THmPelXVntp9bGL0a4isUM8OzlA2z4lQDPiae4\nikUCnmZH/tM2pP4t3rgpJpbvqcCZbcPj78gULIWYFV8o+Hp98zakvl38el25J4VT20byfRnMJChE\nvZacB7kQ8Yxj9mwzpU6ScSzesElL2POqIXitajVCnilzxdJIe9pcGe94o6LC914B8I3j6794z6TO\nOxvImHAZ2Tm+mUM4MTIuyQtI+L4wEyaTcZzt9HhYW6OPbo1PssuB8Y436+o0z7dnHF/6vXsndd7Z\nQE56TSBrHRZ585ZZaSDny1BlLzIz27BaWwAA9IMDoFQ5rKWL5Yb6WoDIr4mrIYT2w2qfPgd7xx2R\n3czVK7K6BiorBzbFx65aSxfDWroYzugY7IEBGBUV2s15/t9nV8NzNpM0FR+/c3RaHEAkhCYpSz72\n+8JMC2J0NKuYb5FOa3otf3Yvhh6K6tUL3RgPSqUwtj3+vOa6VTDXrYJ9sx/pix2R6jTtfxit2cvo\n5KTXBLLWYYLei4VZaSAzDMMwDMMwTBJFbyBPxBvMnlyGmRm8KhKArKGbPncB5z92j0zCicl/8Kdr\nQ54HY+cBrWwUANgnTsOsqUmsvND7XhkeIcZGIfYeia2bnD53AelzF+T5hJANJ4a4wQTD2F3X4Bx6\nHec/lhxmlKTXin99NaJXeuUgjOrq8fU6MgLzxdeiyb4A7GMnYR87qemVYaaLojeQp9PY5ZhhhskN\ns3ZetLlAKA5tye/rYQtjj2zF2CMy99GvahCHUjbKw+7vh93d7TcSufDRIAax7gn9PF7d5MnGMzNM\nqWDW1UVK7I2n15G3bMPIW2QZvlz16gwMwO7uhtm0AABw7hOB8R3Rq1sajvXK5IuiN5CnE/Y0lzb8\nADT12H03Yb4YKvvl2BmL+Jd9dy/Kvrt3UudNd3QCABZ/ePwYxIw39RCzrQ7yRIyR22/bnvW+ajc1\ns6bGT/bxmk74+8V1PgQw+I7J13BlAuze3kiJvfHiRlPP7EHqmQyVL7Jo2GF3XQMALP2d8WP8c9Er\n18ken2u/OvlExt6fyy55OVzGr9hgA3kaYMOrOOAHoBnCMEHl5TDuCG5eniGmGUJex6ytd8j2te5U\nrLl6xdRmQ7tjUVm5/+c8sBnO/Zsj55ltdZBzMUY85vy/V7PeV+2mZvf3+8k+XtMJf7+EqfOqpyZf\nw5UZh5AOs93P1+u6VVPr9fX0mkrJJNqKCthvvEs2qAnpletkj8+CT08+kbHun7JLXjZ2FrctxAZy\nApMxctnwYmY7ZFlafKIYGYFzJLh5eYaYZggpHe7IKvObVtgnTutere13xt64z/6x69VwYx99I1wt\nGbX9zqDDn9uVS4yNwnhpP4zv7weE4+9a7F2gGCZbNL0qOszUSS9Rr0dP6A9auepVLUOm6nVkROYI\nDA/D/N5rkQY1rFdmqmEDOYEkI5e9wwwzPl4L5/BUuVf/GEC0O5a6X1Nyy2OypRGr1lUGgFV/dtY9\nuYx99G7Saskoc1AvJ0aplFbT02yo90vROd3XE6+BYUoJT69hkupRhzFbxwlFIsOPO/ZY9edu++mQ\nXoceWu/vY4zo12RUVmoPvJbyO+Eo3TkZZiooCgO5kNpHs3eYYaJQmaU12jA2roWxcW1kqlxtQWv3\n9uqDGKbvRRL9A3LaVmkJbTU3wWpugnHhKqzWFjgDch+vyYTdI8czVy7TKlZYO90YSyJQT19wzakU\nxMiIVtPTuTkgq1oAEGuX5/w5MEwxQGWW9oBpbFgTG7+bVI9aHqTote9mol7Ns5dhtS6UcceKp9i+\nLg3asF7nfNv1DBPB6AqMXkql4AwNaVVm7BvBb4hYHa16wTCToSjSQydrlHKrZ4aZXkQ6Dbu/31+O\njQU0TJgN9f5UbBgyCCKdBlkW0uuXwjp7xU/mAYD01S45TEUFaM4ckGVJz5fbZML718t+9zCbFshy\nc0LA6bsZrG9dCDjSG213XJbv4e51QdzckVM5fgoMUxyIdFo+YLo4h09EdzJMWAubtFKNceOQZcFe\nsxjmmSuatj29UioFM5UClZXLkCbXU+zr1a0u46Hq1e4NHmjN5gUQKfkw7Jy9IPW6Yx2Ml/bLHeLe\nA8NMgqLwIE+WfBnHheL1ZphpJxyqGFPiyWpvgfA8ynHJPyR/jsy2FpSduwrRWC9XW5aWjOMMD8Pp\nuwnhJMRHhs5tXwtCJTSPtuNAWCaEZcJY0g6zoR5lXYGRH+7uxjAlQzZ6XdQKMXQ7cQgypIbN5iaY\n564C82vlejWeGW7scN9NCDu7rmrqLJPWsc0RQJkFlFkwF7XBrKtD2RVFrxNIMGWYTMwKAxnIj7HK\nXmtmtkCmqRu9SpMAf0q18wqcW7fk9rgmIevd1tG2A2dwCGJOme8ljjQOaahLLkelnNtsbIRIj0W3\nA7Ab58G50AnnQidwrQfOrUGguyeyH8OUGpn06j2M2h2XYff1xRztHrJOafV+exjO3IpgVidkrBqN\nDdnptaEeYnQ0uh2A3VwHceaC/Lt+Q4Za9PRG9mOYqWLWGMgMwzAMwzAMkw2zxkDOtzeXwy2YUkY4\nNqi83F82Vy2HuUomufkxh+k0IERiEwjnwDFQWTnSlzrg3LoVqY1rNi2Qf42NsDtkXCRZQbKRuHcj\nAMBqbZF/7W0yJtL1VlNZOazWlqA81Z7Dfpk3ryavrcQo09Y7Jv25MEwhIhwbZJX5y6pe/bJq4+n1\n0OtSrx2dsG8NJuu1aYGuV7eMW0Svba2wlUoUcXr1yrz5elX3Z70yU8ysMZBzYTqM2Xwb6AwzrYgg\nXvDKB++FfeK0rF8cgxoHrGa9A0rcr3dTVKZq7a5r8q+7WzO6nYEBnPy7baCXDwKQXfXSHZ1IX+qI\njJ3uvKyVdcv4lkI3fIYpGUSgtY7fDek1FKqQ1LQFUPSqGtUuvl67rul6HRzEyc9ujerV7Ybpa9/V\na5KBHrkW1iszxbCBHAPXQGaY3CArKPm08E/1Tk3GpnWJx6ke25G3bJP7u3VOzdp5etMAdczQTXPV\nB5TWt0pM4/Bbo22QzeYFsqKGapyrMZgMU+Koem37uK5Xc+3KrMbwWox7GjUb6nW9KprSmvUAWPW+\nvbH7Df9IVK9G7Ty/Ak6w0mS9MtMOG8g5MBEvMBvVzGxApO3YLHKzoR7OgWPassfYm7Zo+6aekUau\nMzQEs6YGdt9NOIODkTGt9jbZTSvUaMSvw6xk5Fd861XQlqDxgNm0AOkLlwDHht13M8i4d48xqqpk\nC1tgattbM0wBkaRXALCPnfRfm+tWJY7htRh3BgdhNTfB7rmh69XT1B1rpKZDY3mtqTW9/uuruPWu\nHcE+K5bKcnGODbvnBoyqKmmEOzYgRDAGMLXtrfMFG/0FBRvIEyRbw5dDK5hZQ8yPux3qbmX33ABt\nuxMAUPbcvsj+1kLZkUutqewPX1buxygDstGI88BmOA9s1o/xWte6DUTEvqMAgOu/eI9WVxmIdhBz\nBgeDFrZJWfcMUwpkYYzZx07Kds8JeHr1ah5rw7t69VrM28dO6nr1aiaH9Dr3a7sAuHoN1TR3Bgc1\nI1ytu1wSZd4ytfZmZhw2kCcIG77FA3vxZ4gMP+5GZWVgsO45rHl+VNJXrkbWkdpkIFSb2Hhpf9Ao\nQL0OIbR9jYoKzP/7V5KvnSjWY+wlEs0Wso3P1shgQI2L+5mbq1doq9MPb4nbO7IfMwnGMcb82Z5X\nk2N74/Rqzm+Q5domoVertSWjXqmsPPa7euuddycew0jSD8VrKxec+7Kzf8LtxYsNNpCnCDbCChd+\nmJl+yDSS66oSBe1hvRqrMd30vHazVlsrzPkNwPY7ZV3VkZHIjdZaujjDxSixj9XVgGHGJxrt2ACj\nshJGZSXMeTWyXbb6g07kJxLNFrTGDNmSwYAaF9dLH07otJ6Pzi7E7cdMjPH0CgBO/62MYUbWsiXy\n39YWX68wTNjXeyIzR1nrtaoKMMz47n07NsCsqYFZUwOjao4c1/Vge+PMfXJ38nkYAID1Qry2csHv\nNjoO4Rm7YoMN5CkiWyOMDWmmFBG2o3uk1M5cSlZ6prAFr+VsuqNTdtN69XDitGn63IUMFxOc2xkY\nSD7nrkNwhobgDA3B7rspy0apP+juGPN2NiSfa4owqqsjXtMJeXMZJgumQq/ps+flv52Xfb0m7Z+1\nXgcHM+rV7u+Xf65eNQ+2O0b19+cnn2uKMKqrIzkUrNfSgw3kGSYXb+azlw+wQc0weebmfT2x672k\nIDVDf+TN2zDy5m05n8MZGNC8ps59m3DpgxmmQmM8e2oCpFFd7V9fSSQvMUyWDNx/PXa9F+Kl6fUt\n2/zqObngDAxoORTOfZvQ8Zs56nV+8OBt1tQEei0rj+zL5Ac2kBmGYRiGYRhGgQ3kAubRlk0cP+vC\nnnSm0PDCP/z4agCpb+9B6tt7kg7JGmPngUh9Wo2YaWg17tMZGNA7GGY6V6hGLaB7oyfK1f96r1+x\nIKme9UTwxrKWLErcx7l/85SdjykNvDwGTa/P7PHLS04GY+cBtP5Rjnq9HsxM2f39gV5D+RbZcP0X\n78n5mDBDPx4kON78mR0Z9px6sq29PdOwgcwUBdP1oMCGNzPbUQ0Gj3CSVRzh0A1r6WItGavp1SFZ\nscAwY+tZT5S+t7lVMzKUKbu5PLvuawxTCmSs0JMl/YuCMJB5X9w16fFy4fz/Lsz4bTaQ8wDHFhcO\n7KFnskGt35otSbGEZFlakxO/wYlr8GmGZ1zpuXs2wly70u8mqDVgMEzAMGX1Dnc8v2OgYcJa2Jx1\n697xCHum0+cuaMlY9AP3N26K60nXfHmXf74k6p6YvMHAFC/O/ZtznkVI1GtZuTajkqtesf1OmKtX\n+El85vrV+v6eXr2Sh6pe21qnTK/j0fwXGTzg00z7O47k7dyZYAM5D5RC6AQb+MxswviPAzD+4wDM\npgWw2lqzO2ZedcL6GlBtjV/eyvfgCgGzrg7GssALS2XKzde7Ib9yEPbxU37pOnH2YhDC4NiAY8vq\nHW5Wv9fO21y5FDAMGE1BDWqrtSWr98IwxYSx8wCMnQdgzm/I+jtu1MyNXz+vGjQvg15XLvX3JVMx\nkL0ZjlcPwz5x2i+hKM5ciNerV/LQ0+tqWfbSaA5KT2pl7Zhphw3kAqNYDM9iN/AZJifcUlR21zWk\nOzoBIt+zM/pYkAU/9shWjD2yFUAQYxgORbB7bkjvp9cgQfHE2r29sE+ewdXfvBdmXZ1elzihsYMz\nPCzb/ba36RtC3iz7xGmkOy/LVtsusfVmGabY8fR6vUd+xw3Tj7VXq8yMvWmLX67NCysKe5Lt6z2y\npF2SXo+fQtev3wuzdp4ePzyeXhe36xvCej1+CumOTqTPX/TXxTVmYaYPEgXY2rCG6sXd9HC+L6Oo\nefbyATZip5jnxFP7hBBb830dhUipa9a7manG5VQy9shW9Kwrz2qak7beAePSNeD2MOz+ftlMxb1p\ne0aAc/t2cIMmin9d4uwWz6Nf3Bi/n/IspOT16sbCZ6y/PAnSD21Bz/oUmv4qi7CE7XfCungNYuh2\nVK/uQ7YzOhaEIrFeCwb2IJco02kcF4uXmylsjOr4EIS8E5P8lb5wadqMYwAo++7erGMAxd4jsLuu\nwe7vl8uKR8trfOLdVI2qKkAIfOjsa+7Bs+Nmy0w9MxULmzNxeg3Fw2tVVDIkd8qdk7sHelgv7MvO\nOAaAVw8jfbUrXq/DwzJUSo3TFwIfP/eq/5rJH2wgMzmjGt9sLDMTxRkYyPclxBNzUzIqKoK/LEuW\nmauWhwYx/bG0bcoNmSwLVnOTv2w1N+ltgN191BAPNSGPLEsL6fCqR/zBsrtkS+D1q7WkPrVZAcNk\nIrZdeyGQhV61KioJRqe5wo0lVj257liRRFgXsiwtxtlsbEzUq5ekp+rVS9IL87tLt8sEvTvWaEl9\nU1F+kckeNpBnEdNhzHIYBzMb8D09pql5gDJ5wUWlXrrIXLEEZFlwhochLnYqgwfeI5FOw+7p9ZdH\nV7bArK+DWV/nx0aKdBoQAuSeW03IM6qrE6/J6bkBcb4D1B8YC1QVrYHMMMWOqlfY2VVRcer0JD1z\n+RJ/LHEhg16Vesaj69th1tbCrK2N6NVwq1+oejVr5sJMSA50bvQCFzpBg7f9dVRToLNuJQobyAzD\nMAzDMAyjwAZyiaN6jdnbyzATxJsKtW0YqZQfypAUJkKWBXHkpHztepLsk2cg0mkYG9bAqKv1p2LV\n0k3W0sUw2xYGp/3+ftg9N2D33Agy5N3j7O5uAHLa1ZvatXt7Yff2yqx9NwTDn9qd3wAqL4dzs98f\n3756bYo+IIYpIFy9inQaVF4eCT0KQ5YF7D8uX3t6PX1ODrVxLYzaefF6XbIIZmugV/PF13wNahUt\nwnqd3yDX9d2UZd0M09epr9eGevkbo8wo2Ze5isVMwgZyiTMVRjHHGTOzHbOhHmZDPZxhWTlC2DYM\nt9mHeuP1QhxEOp3Y4tk5cgrpq11+2SiVcHJR7LXU1+kxzJYFu7sbVlNQLxXb1wf1U9etkGN3dMLu\n69OMeq2MHMOUCJ5exchIoFc3flfTa1UVjKqqzHo9fBLpy1cCvRqB2ZQ+f1GWgBvvWlYuC1ZYFuzr\nPRG9mgvd3ANPr5c6WK95hg3kWUouRi97npnZjt3dDbu7G+b61dKDJIS/LNJpmKvlTc0ZGPBvaJ4n\nSPUkmU0LghhG18ul1TYlSuzMZT94F4zKSulRPnFabq6uht11DSCSRrfHrkN+/VSx/2hwPUJodV69\n62aYUsLTq/PAZvkdd2uYA6EqEoODfgKfl3yreX4BqVcyQGXloLJyvXa4kiwL6MZ3z/vukdfScwP2\nyTPBtXVdk7ofR69eLoFXuhEAxBv4XjyTJM85MCWJZxiz0cswuWMfPaEvH5eGqmewqlB5uebxGXzH\n3aj6ulK+ScQkD4UaEZgrl+L2kloAQPmze+Eouxob18I5eDwYDwBtWS8X9x2NDj0y4tZVdXzj3T51\nLsO7ZZjixnhpP7JtdK51rQQw+BN3o+rru+WCY0PEtUwXQqvuYaxejuFWadg2fFZvd25sWgfnwDF/\nPCCzXp2BAYAIYnTU1yteOZzlu2GmAjaQZxlhw5gbijDM+JhrVwKQ3a004m6a3qZQfHLVU7uDhVAD\nANp2J4YXVCD1b3u0Y+yTZ1B+Sp/oc+7bhPLTV4Cbg3Agy1B5N2njovSS2QnNBsirwpEwncwwpYBX\nGi38QJsJr8Wzh28cA1G9bl6PkaZKlH8npNdjJ1F2PKTXBzaj/OQVoHcgqtcLcvbINszYRiFklUmP\nNus1L3CIRYGQrzhfNo4ZZnycU+fgKN5Wo6oKxsa1AACzdp6/3qydpy0D0OoaA+40rHKztZqbIPYc\njhjHAOR+jq0Z4sbLh+EM3Apa0Loxkeb61UEoyPIlvnfKr+8KJMZZMkwp4Zw4A+dEENZg1tQEenXL\nrXmv1WUAWl1jIEavC5sh9h+NGMcA4vX6/UNwbvYHjYY8va5bBft6j4xHXtIe6NUtLwfEhHswMwob\nyAVCoRmqnJjHMAHhJB6jei5oVC7ffGRtsOPCBfJPPXauXms4bKRqsYguppsAGItja40PnKEhAMBY\n3Rx/nX32IozzV0CW5WfjM8xsIaxXqq8FjUmjtf+HFb02N8o/9dgavRFQRK9XopUkwg/FGo7taxQI\n9JquC34X0ucvBd7kM+eTx2JmFDaQmVim0mBnY5spNdJXu2S4BRHmfm0XzLo6mTB3/FQkDEMzUMdr\nc+sd09sbWUdl5ZFSVWpXP2OnojPHlqXh3CYFmYjrDHjxI/dmdZ2ZoLJy//32PX7PpMeLjJ9KZdiY\n3efMlDju9yB9/iLsY7Lsohc6YTY2wj55RkugA2LCqLIgHJ4B6Ml1sZf2g5BevYYjE2gvfeEPplZf\nUz1escIGMjNhsjV8C807zjC5Yq5cJks1EemtYd2bmd3bG4k5jrSFdWMLjYoKWMuW+Ks1A5VI64Tn\nt6UlghgbhUinYbW1wqyd57fQVUMovEx71ZBWW9waG9ZodVzJsvQ2vC6LPvLy+B/KOIixUf/zqf38\nK+PsPYHxM5W8moCRwZQO5oqlgS4SHpa8usT+MQltnI3KSq1MW1ivaoiGus3zFFsLm6VeXYNZHcur\nz5yo141rI3qNY/GHplZfUz1escIGcgFSLB5XNnyZ2YJ96izsU2dB5eXaetOtZZp+eEvEE2v33NAH\nEQLm/AY4w8Oydqpr+GoGqhCaoe23pRUC5tqVMFevcOsZ35Qlqh7YrHmoxdiob0j761xD0hkYgHPo\ndW2KWDjxhqS1ZNH4H0oOqDd5hplu7NPnYJ8+J1u0hzTroT5YAjF6dXGGhqT2veZAIb3a/UHjHXXb\ntV+VszDpK1elXl2D2T51NjjcDQVJ1OvB45pek96L88Dm2PUTZfTRrbkf5P6elRJsIDMMwzAMwzCM\nAhvIBUg+PLPF4rVmmLygtJomI/CS2NfkNK31/L5IqIKxYY22bC1s9uMMzbq62E56QCi2dscGvyuY\nffyUrLfsemnM1StgvLRfC/mw2ttgtbfFv4XKSljNTZp32KyZG7uvXyFjiohLbGKYacPVq3OzH7Dj\nSzGGk1eNTeu0ZbMxSN4z5zckdttTG4Vg+50w6+pg1tVhwafdMCVPr15oharXhc2JsytGVRWs1hY9\nhKq8LH7fl/bHrp8o5c/uzf2ghN+zYqaoDGQ24qYPDpdgpoOBd+8IFohgzm+QL1MpYMeGrMeJq+pg\n3LEmZs8YDDNSas3fVFGh3+CIQJvXR3d0SzdFbpIZbgjOodf9rnVUVq4ZiXFJeP6QamztrkOyE5c6\n/evFPXvNSZSSUulLHUhf6oi/nqEhpK92acZvXHIRM3vJNLVuP3jXDF5J9tDWO6Irk/SqHqfG/ZaV\nwzlwDJd/O0hOVWOU7es9iSEEaqMQvHoYdm+vrm9Pr15oharXK1cTHx6dwUGkOy9rhjzrdWYpKgO5\n1Iw4NviZUqf6n3cFC0L4HlQxMgLsOpT1OHEGpXPk9ewOduzYUmqAvLlpNzgh/FavcRgb10aSbABZ\ng9hqaw32cxPtvDqmfj1T5SZL2+4EbbtTH7+qKrE6g3re4ADpjfIePDLhPwgoN/lsjmNmD5k8h+aL\nr83glWSP2HskcRttvQPmulWx24ylwUyKMacCIELLH8ckp3q5Am/YCOcNG/Uxqqv1B2x124bkB/ik\nB3bteC+nQdVr04KEvZnpoKgM5FKjmAx+NuaZ2YyfoHPwOOxTZ2E2LYC5diVEOg0qK4d99ATSHZ3B\n1K6SaKdWrIAQMBvqQZYFsecwxJ7DMFevCDaPjECMxXu8fA8Uke+ZhmPDrKuD3XNDu+ma8xv8xghe\nyIUzMiKvT/F6+6WlGKaE8PQq9h6BfeykrPzidsP0tGOfOuvr1e7v93URfhA1G+pBpglj5wEYOw/o\ner19G87oWOw1OIfcB3hVr5CzYemua5qxazbUB3p1H7Sd28NRvXZdm9DnwUwMNpBLjOkyZIvJmGeY\nacMwQakUxK1BiA45Nap1u/K6aBmm7/kR1/XseNG6AMa8msCb7Dj+NrO5CWbj+F5docZVlpfBrK3V\njF3n5gCoQ3rNHXda1qyvg1FVqXuo1ZJ1DFNqeHrtH8har+jWHxqd9mYYtfMCvSraM5sWwFowf9zL\n0PRqWTDn1cBRwqac/luBXm/Kqhhm3TzWa55hA7nESDJk2QPMMBNj8B13QzhClkRzbIiREVliLVT3\nGECQzOfYQeyhUgYKgPRC99zwk1rsU2dlneN7N8oSbl3XACJc+Gh8sw4jlYJRFTQhsLuuwe7tDcVG\nO37csnPrltyv5wacgQE9xtmJT2BimGJl6O1Rvdr9/dnrNRTnK/YflQ+fnl5Pnwv02nlZhm8RJTbX\nMObMgTk3KAFpd3fD7rsZiY1mvRYebCDPEmbCA8xGOFOKVD212/c0We1tsFpb/G2+d8fzPnkeKSAS\n++h3ljPMaOyvEKCXD8ptjY2AEFj84ZfldKvrufJiHZ3hYXmz97xJavMSr6lITCKh1doiK2KsWu5v\nCmfuM0yxU/m0ote2Vk2vEVS9rl+tbfKT+AwzGvur6NVqbpJ6/dAr8lyeXt3GIM7QkHxIzqRX1avt\n6bW9DWZjox8aArBeZxoSBViWo4bqxd30cL4vgykhPON9Mg8Kz4mn9gkhJlBBvfRhzZYWVmsL0p2X\np2w82rIeYl9y8mMcp57YAgBY+d598WNaFux77oTx/fgSV7vF8+gXN0qrc8EUwXotMdwunVM2XCqV\nuVNlDF/rkN333tU2sTbVhahX9iAzEUrRE/xoyyaOo2YmjVk7L77yg2FqLWfTD0njzqulqm7zEnZG\nH9uG0ce2acNYi9sTq1hkij/0EnwyETduUuvaqTSOAeRsHAPSME4yjgHZhSzJOGYYQNFrTHk2s3ae\n/2cSiuAAACAASURBVHrsEen3iKsSQakUQISRN2/DyJtDel2yKLGKRUa9ZuEJzkWvU11/OFfjGJCG\n8USN40KFDWSGYRiGYRiGUWADmYl4jNnTyjA61uJ2WIvbYffd9KtF+HVK3SQfu7/f76JlvSA9n3Z3\nN0CkJep58Ybl39mD8u/s0T3PFy5J702Mx8uLlbSWLYFz/2Z/tVlXB+fgca2Ziv3gXTAb6uXlufVY\n47xCSU0UGKaY8TpK+noVQtcrZDKep9ey78r6z16CrIoYGQGEQOrbe5D69h7N85w+f1HWUc+k16WL\n4dwX3FPNhno4B45penUe2Byv1/C1sF5nFDaQS5hsQyXYIGaYzKQvXEL6wiWZOOMmufmtpR3bv5F5\nXbTMxsZgijU0/Wk2Nsq2z26bWftW0KLauGONrFscN2Xqjpc+e14LLbD7+mBsXKs1UzFffC3Iinfr\nsVptrbI+rDJ1G9ehkGGKHa+jpNXWKusaE+l6dclKr00LZNvn5iZYzU2w+2/524wNa2Atbo9vGe+G\nQ6TPXYCxM7gX2zd6YWxYo+nVeGl/VK+L20FWmRbCwXqdWdhALhImEhfMhi/DTA2USoFSKTjd1yE6\nrkR3CN0g7e5uGOtWauu82GOntxdGU2PQZlYEdZCdoycgbt/2l61lS/ymB/6N3a3Z6nmejVQKzsHj\n8nW4dbZ6iSOjMJYvgbFiSbDS5FsAU3pQWbls4NN9HaLz6rgxunZ3N8y1K7R1vl57boBammSb9qtd\nul4Pn4AYCjpxWksW+aXjfG+vq1evu6aRSvlGsPe7EsvIKIyVSwDWa95IiPhmCo1CNnanokIEwxQy\nXnhC+DZrNtT7np8w4VbY5oL5EFVzYJ88g/S5C8rgQnutNvxIn7sAw72BinQaRlWV7wmz+/ulZ0xp\nle1kSK6xu7uB7m4AwOB3ZLewqsfOJu7PMMWKWjYt2/Q1++gJbdlsb0H67HmIdDroYglE9epqCgDS\nFztl22og4rH26jCrehWjSnm3EOmrXcBV2Tzk7cfkOZ7mKm8zCj+OMJOm0CpElGIVjpIjLmZvOpmm\nDlRJxnEc6c7LsE+eye0EQsi6x+5N1b/pKtsjy1lktFc9djYwjpXP5sZ/zj0LXdy7MXFbonfMxYsL\nHXlLqDrAwubY/dWasMzUc+2X45vTAJh5zWaJF7s71aTPns/9IMeWTYTCOk0iS70+va4RT69rzP16\nciDj//00M/zW7Xk7dybYQC5y2BiMUkjGOpPATNdfn2wHKq/NrGHCqKiA1dykJeuE8ZoEAJCNBNRt\nG9dKw9CdirXa2/xt5oql8WXkMmBUV8Na2KyXgPKakSgNRszaeXJKN7Sf+tnU/+MrOZ0bgGyYkMB4\n5aI8QyL1zB5tffrK1dj97eOncrw6JhcW/N+XkzcWYM8EIOEhVdErpVIyd0BJhg2j6TXUWMTYtE6G\nR0ylXpubonr1kvQy6XUaH1Iy/t9PMxXfejVv584EG8hFBlecYJg84thwRkZgt84HGuWNMa42qTMc\nGIZ2u15b1bh+E87tYa2Ll4foug7nZkxL3DDqjXJsTCb+KO1sqcwC6mtBVhmoXMZS2v23IEZH9Ux4\nbl3LlCKeZ9ZtNT26eD6wIDu9ji3SPbXG9ZtwBoemVq+9fZpR7ukVAFBWBiBBrwX6kFKqsIFcZOTb\nIGaPNTMb8cq8AQCEkI0vuq7LRTu4aXrJQeqNVOw7po1lX7sOMuI9Qc7AgN52Nu5aWlu0NtZG8wKI\nkREIO0georXLQf23IMZGIZa2uoPbIHN6Qk0YppDQ9ArA+MFB4JqM7df0Gk6ABWDs0Zva2F3dul6V\n187AAER6LPO1LGzW20UvbJJ6VYxdWrMMdGtILixzPdSODbLKxnmnzHTCraaLlGcvH8i7sTzb4FbT\nycxWzWZqyWrW1WmlnAZ+cgdqvr43p1qmxoY1SNfNka9f0rvGmWtXRkIOPMPZPnYy4YIpctMdzyAv\nVgqxdW2hMGv0mkMLZnN+g5Yge+tdOzD3a7tyGoe2rIc9V87YGP9xQDvGXLcqoktz/WoA0QRB9fqp\nvBxwgnFYrzMHe5CLlJkwjp+9fIA9xgyTgUwxtqpxDAC1h3oSjeOk+qbi+FkMtKcw0B5NdkvXVkbW\nDayuw8DqDLVShYAYG4XZ3gKzvaVkb7YMAyCnkATVOAaAeQevJ46TWI/40CkMtKUw0JaKHJOunRPZ\nfWB1LQZW1yZflBAQIyMwW5thtjazXmcYNpAZhmEYhmEYRoFDLEoErkU8/XCIRTKzRbNGRQVgmnCG\nhnQPERHM2lrfazzylm1IPbMH5uoVsE+chrW4HekLl+SulgWRTiP98BYAgPX8Pn8Yq7kJ9vUET3OG\naV7vPJmO8c6b7ZjFTiFO2RYKs0avlZVSr7duxXa09GoY3/6x7ZjzjVdhbFjjN/Hw8HQz+pgsRVj+\nnaDiitXaArvrWu56jQm3iBzOes077EHOM1MVwlBotYgZpiRZtQRYuTi4SbnZ6WSVaSEVc146BrIs\n32j1jGNAxi0bFRWoONaJimOd+vipcphNetULDzXrPYKdUI1CjYF0S8FpJa3aWpPHZJgih5a2A8vj\nW0GrDT6qnj8OsqyIcQy4eq2sROXBS6g8eEnfWGbBTKjZnVGvo5kT+wDAbGuJ6jVUgo6ZXoraQC6F\n+Fg2aplSxtiwJlggAnZs8Bcz1REO1yyN1O5F5gYVKtayJUGZpVAdUWvpYlhLFwfnbWzUrzmEc+h1\nOAeUqhTujTccG+gMDibGGzuDg3CGh4NW0wrpC5eQ7ryceFwS9ulzidv8sS91QKTT0vutrGMYj0zN\nIpz7CvNede4Tyc1t7KMndL0mIKtRZNDr0FC8Xs9fTNTQpPV6/mJUrx2dGY5gppqiNpDZuJx6SuGh\ngykcNI+MEMCuQ/6i3Xcz8Ti7v19bjqvdm6lBhUr67PnAgxROnDl3QWv7bHd3x3qRzBVLYa5Yqq3z\nusBpRrfbTEDfUV+mVEqWgnOxlizS9x+nGYDV3uZnvwOAuVK2jVY9Tea6VTAbZT1X4441/riUShVs\nRzQm/2RqFmHsLMx7w9LfiTa3sZYtkQ/GClOmV+WBOjJeDFZbq1aW0Vy1XJ4mQa++tr0mP6zXvFHU\nBrIKG3ZTAz90MFNJpItcdbX/+soHk71V6g0pjHejC2eSxzUAAKB1vvK6VAUr9BsklZVH2h4D0uMT\n9vr4HiLV6I5pJhBpLjAyonmc0+cv6vuPE2OYvtShlYWyT8mW0aqnyT520p9Cdo68Lt+3mxFfqjGM\nzORJCu8BgFNPbJnBK8mevsejHuT02fORVtFTplflgToyXgzpjk4t3thrN5+kV/voCWksu23mWa/5\no2QM5GI27Ni4Z0qV9NUubdkZCLpOLfzTZG9VpnJG3o0uXEYtaYpUnQJ1hodDg+k3SDE2Gml7HHt9\nb9gUeHqUsBGjqirwVHmneGBz5sHiPEQT8BqpXioQwWxslDHGRFoTEYZJwu66lrht5Xv3JW7LJ7Wf\nH789+vBbtwehU9vv9NfH6dVLxktkuvTqPZwQafHRTP4oGQO5mBnPuGcDmmEKBMMEWRbKzl8LvEJK\n2IgzOCj/7pdGsbWwGdZrp3Uj2vWim00LIh47q71NesJz9BqZK5bqWfFCwL5+HbBMv/ZxZCqZYUod\nwwSVlaPq7E04R9ymOq8e9jd7eh1+63YAMjRjzp4z2hBmXR1ABKut1X3gDMwmc9VyOduVo16NO9ZE\n9drd478GkmfEmJmDDeQCRTWKi9k7zjAlhWPLEm2dlyM3xbOfDKZ6y46cBwAM3L0IzsAArEtB0wHf\ni+4I+aeM4yXS5Yp95nx0pRB6+EZ4KtklHAbDMCWDY0OMjcqQpND3/9Tn7/JfV70ijeIbdzfD7rmh\n7Wf39roPmWMQY2PaOPbJMxNq3uEcOxWzMhTaMYHfAWZqYQO5QJmMUcweZ4aZeZb9z2Cq1wv/mPON\nVwEA6c7LMkFOwe7u9qdST/7t9sRpWnPdKn061lu/dmWw4BrZzn2bsqs2oMReh8NgGGY2sPLx1/zX\nXhe9mq/s8tdF9Np1zQ9ByajXtSt1bXrrVQ27xvBE9MrMHGwgMwzDMAzDMIwCG8glSNj7zB5lhpli\nvBJMgB9vDMgOepEqGF7d5pGRxOFW/dKrWqjF1d+41w99sI+djO26ZR/Xp2mt9jYYOw8E5bgyeZzi\nsvcZplQh8suqqUmzcXr1Yn9z0WvXr9/r5xPYx09FtAkgomFrcTvrtcBhA3kWMJMxzGyMM7MCrwQT\nAOP7+/3VqWf2RKtgTODG1vypl3MOfYg0LMjyvCc/F5Tvuv1j23M6JxBTOk9hvM5fnjESLtmXNH2d\nqfwfwyQihF9WzXgps14nEvvb9JcvZ6wAEofaXRNA1nqlrXf4r698Y21O5xyPcO3oMEllADM1fSpm\n2EBmppRiTShkw56Zraz6+aB8lxcznU0Gve+R80rnheIkrcXtflfAJCPaM0bCJfsiVQGIYFRVQYyN\n+sb0jX+NxmX75+YW2kyJIvYe8V8v/LHj2R1EhPTDeh3ruGYq4drRYZIeAsJNn4yqKt9T3/N+mbyc\nqUNpocIGMpNXCsUwLVbDnmGmg0xeNE+zaqMDuUKfBlY9ZJH60zlfkIjUv67/kWjYiX9ubsnLMABc\nvQoB63m9jnVcM5Wpwhkc9D31DZ+RyctxHUoLHTaQmbySq2FaKAY1w8xWHm3ZBKO6WvMym00LQJvX\ngzavj+xvP3hXZF0m1DbaACKxmWZdXSTUwqypgVlTAwAYePcObs/LMC6PtmySzVDU2Z3mJpirlvtt\nrzWUmu1xhGeXzNUrtGW1WyogZ4/CoRlqg5Yb/znaCbFQKAkDmY2m2QN7eosUJakNQKwhlYhhytar\nkyBidIUhijWqSjW2LolILHACzsCA72W2Wltgd12D2H8UYv/R6JgvvhZZ5+N+5motZvvoCfS8T7lp\nKl5ps6YGdm9vpPas3d8Pu78fAFD9z7u4Pe8kCYfEWEsW5elKmEx4YU7j4QwO6rM7V7tgnzzjt73W\nUBofRSCKzC7ZJ07jJ44HoRdqt1RAzh6FQzO8Bi0AUP+P43dCzBclYSCz0cRMJc9ePsAPXVONktQG\nINaQSsSxJ9161T56IvMOQsQaVeHYulInEgucBV6ccRKeh8lqbtIeQmjLepBVBrOxUUtIHH1sGxo+\nG9w0VWPNM4LNhnr9Gh7e4sdYevVryeK6sRMlHBKjNZxhCoZImNMUYM5vAADYb9RnfswVSwFEY4nN\nVcvx9bWBhzjOqRCOdbYWt8Na3A5A8UhXJif75ouSMJCZwqRYjcxHWzbxQxcza1CnTG+98+6cj8/k\ndb71zrthnzgNwG1IojyEiH1H4WxfB7u7W2usUP4dvaqAaqx5yXfhbmfW9w7A+p78vfHKc4k0l8Vi\nSpvrH5ja8ARx70ZfW+b39Jkf+/Q5XPq9eyKxxPbp8/pyjFMhHOssbvZD3JQPu75HemiSeQrTABvI\nzLSRrZFZrIY0w5QC6pTp3Cd3Z3UMbVnvh63Yvb0wNqzB2CNbMfbIVm2/uU/u9j1FseP8QGpfrRvr\nxRJHMEykOzrHrVBhrluVVRUOhil25v9dduEJ4p6NsNrbtGX7wbsi+QH08kFYi9rCh/u0f+zlyDqz\nZm78zu5skdlQHwlfs/tvwe6/JUM27tmY1XvIB2wgMwzDMAzDMIwCG8hM3slHOAN7rRkmM5m8sOK1\nYxhpCjxHzqHXUfbdvSj77t7IvpGGCOPgxRmrmGtX4tyXZWKnX1tZzZZXSszZx05C2BxewcwuMjXs\nod1HMLAlaNpDrxyE+dJ+mErTFI+c9RoTUmGuX41Tn5PeaftGbzS/w9OrEKBXDuZ0vpmEDWSmpMjW\n8OUYY4YJiAuDUEMvIsayELBe2Ies8KZaw1243LJTY2/aEru/h/3Gu2AfP4Wl7z7kn9t5YLOfLR9O\nCqKycnnjnVN4ST8MMxXE6VWN1Y90nHRsvwmQT0Jisn+O9vhQi4heQ4h7NsI+egIr37svOM/2O/3t\nXhJgcLGu3ufOyThuPmADuYhhL2gUNnyZaSVUk9ernBCuqpDE0I/nngTnYbW1YuQt2/TL2bRuwuMB\ngeE7ntdoIu13g4PlTTjShcv1+JY9ty92f49wshCgtwsOe7C8EnDiduEl/TB5xq3xm61eJ1ujd+An\nd2jLXne5yTKuXkNlECd0jnDrepeIXkPEeoRfPey/tK/36Ns8vd+6ndP1zQRsIBcxbAxOPfzQwWTE\n0afuve5U4aoKSVT+S3ZJcHGkOzqReiZU4eHAsQmPBwSG77VfvjdYaUTLoxl3uKWdwrWiY/ZNDM1I\naN6hTg1HvMyIT9rzSrkBQN/PJhgx3CyECePW+M1Wr5Ot0Vv91V3ashET0jARet8bfOfj9EZb73Bf\nhDQQp4kknWShV6u1JbrdbQCiDaV4tHt+oXj0ygYywyioDx1sLDOzhQX/V8lOdx8CVCPUOeKWdnK9\nPV78L5mmtuwRrmahHtvz/nvQ8/7gJqlODUe8zIiPSfZKuQFA7RcCI0a7+XKzEKZEqXsi+M57D7mq\noSz2HnFfuHp1G4pQuTRUVSOWrDIMvT1mZss9tu/xe9D3eLxe42qgew1AtKEUj3bDPyh6fV9h65UN\n5CKCDbaZhT30TC4MviO4yXgxgl2/7npmY9q3/n/23jtOruo8+P+eadv7rlar3juoS4hmEB1jA8aY\nZmMTVxLHSey88S/JG4ckTnD8Jk5CbGMbbGzTMSB6MwgQQn1R772spO3aOvXO+f1x7uzemZ1dzTZt\n0fP9fOajnVvOPXd0n3ue85yneMaM7piyrIdWlO5abVPBqYQmEvP/jQ18zupZOhJJGqwXo+iRtRQ9\n0j/Vs5yDr9B3JE6AhjpqYTcqeQ4ycj4qTrq9KzeoWEGRmEw7lVgdDpG5ovOVrfzfryX/913L1dlS\nL3aGsyDQYEQU5CGEKGypI5MJ4VyT9Xz7IBPzESx9yLbMJinfGjlRQeRERfzGHlpROh0ce2OVSVCu\n+yq3sCsrK+ky7CPHVvdJ+0Lfk1g+eKijy7tRyXOQ0XRZTfIdKbg/9YTO5PXXDnnt8B4bJoiCPIgQ\npa7vkMmE0B8ojyduIIol2veMLE3p/MQgu+7gmTCO0PXx56vFF3RydGp0qfQmKNe9CtRzEG1pSboM\n+/Vxl/ZJ+4LQGTF5SVVeG+++6OwHdUFikF5S16O+IlkqtT6gM3n96nkgr6IgDyJEqet7ZNIh9CU6\nEokbiNwfmAwLkdOVKZ2fGGTXHSJHjnUow6w3bu/k6NToK6UXjFtJXPopeyLReFfnSkYyBd3pqtLZ\ndRKxrlyAdaWZrCivb9i5BAh9Q0xeUpXX3KfWnf2gLkgM0uvK9ehc4xk7JmkqN6e/cRxKJbVK13+5\n60wf7uKijqkbHVX8Yv7RgxFRkIVhQWeKsEw6BKEb9MBnORahHjl6PD79lD2RyHtxc9txzsHwzL3L\naPmsSZPn3J770eFOr+UZOyZpiitX0MIVNBYzHQ4NO5cAQehrIsdPJE3lVvCsmfS7p0yM237khxeh\n5s7o8I4oeadzeQU7rVuCddsprzH/aMliIQiCIAiCIAiDHKUHYWqNXFWol6qrBrobQi94++SWYWe9\nfVc/X6617kcnsqGLyOzQ55WKjXx2dBc+0koNylRMnbFev0ejrht8ZqlBgMjr0Oes8upy95kf8rlg\nMMqrWJCFfuFcKcdvn9wifsaC0AckDrYdinY4leMlF8RFtrunT4k7NFnUe4zK71zcnv6uO6QQlR++\ndtGgXKoVhL6mg7wmVgd0KMeuuTPjinW4p06KPzehXLuTU9+9mFPf7YG8poD/5iWDWl5FQRaGJDGl\n+LpR84adpVoQBhL3rGlAQtEOexBrG4Q3bI+LbLf2HohrI1nUe/X9y3DNmUHpQ2sofWhNW+5UZ2Wu\nLnFawzoZVL3vbGpT5HXe4A3+EYS+IhbsFlcd0JaPWKW76NbdccU6rP2H4ttIKNcOUPH/GaW47Cdr\nKPvJmrbCQc4CQr0l4+UNbfIaLeh8Uj1QiIIsDEnOpYVaEM4nrF37Om60B7HYIGxdsQBP2ci23a23\nLsUzelTS0rPuggIASh5eayryKQVKteVOdVbmgiQKc8xybA/6yusDlTB02W0qr4+W20wWDNXQmsLd\nCsLQJpZJJw5bXmOV7vQl8+Iyu7R8finu4iKTYSKxPbu0++gf2TncbdmKFRnRoVDc8YkKczL57bCi\nFJPXtLS2VHqu+o6T6oFmSCrIorQI5wqxTvcNTXde1PbihfbKXMkqMCWm/lKLL+j9MtxZzndlZSXN\njRq8oed5i4cz7g8+IXLqdNv3zBXriVScTFp61qqvj9+gdZe+zNFAID71U8xyHLMMh0MdfSvtNnU4\nRNYLnVcFE1Kj4sX4SnMxmaz/StcpvYTBifp4S1xml6zn12PV1JoMEwl0KO2eKK+J+dGDwbh3e+KE\nl6jVcUUpJq/BYK9T6fUnQ1JBFqVF6A0ywTr35DyzLu7FG3tZJ6vAlJibV2/c3vvgsLOcH21pSZob\nNe3NnuctHmp0mJgkLqWeQ1/BttRPNrftrurg5yz0H6M/F19pLiaTBb8d3KWBzycSLbUdcn/3USW9\nVEhUqm/YeQbPpAnn7Pr9xZBUkAWhpwzH7BqC0Fs8Y8d0nJjYS6pA7zJYxPyXbVeLxO2RqxbGb08Y\n2IM3LOaFmSPi/JxD17Unk3FlZbUt2UJ7TuW+9JUUhMGEZ/zYDpbauNzffZDBorNqg07ZS0bkqoW8\nOTufyKEjbdtiRXyAOGsz0C7vmSnGIpxDREEWBjV9be0V5VgQOpLMkh9HJ8pxzTc6LrlX/enFNNzj\nqJ4X819O5moBeN4rj9+eMLAns+L73m6vSBZtaWlbslVeX5v1OU7BF4RhhFVxqusDOlGOq7/VUV4r\n//zipNUrO6s26JS9ZHSQZ8D9fruftNParDye9r62BhJPG3BEQRYGNb1RaMWVQhBSw5OY0s3GNXcm\nrrkzO1TVilH86IYO20b8Yj15T/bMr3Dfr7ufZtyZssoZqS8IwxVXXm7S7Wr+bNT82binTU66v+QX\nHV1kSv93DVnP98xvf//vFpz9oASc75K+LHXfH4iCLAiCIAiCIAgOREEWBh19ZfkVdwpBSI2ky6lK\nEd26m+jW3VgHDsftcl04A+Xx4M426Zuc2T5cGeldBtR5xo7BM3ZM0n3Tvppk+TZZsJEjYNCZ07Xl\ntqUdC5wIwjDDqu+YtxhAb96J3rwTa9/BuO2eSRNAqba0btFPzW/b587PwzV3ZqfX8owZnTTbEMDU\nL3dMMReXgcbGWaTE+S5p+fxS3CUlnV57oBEFWRh09FSxFZcKQeglTmW0q1Rs2/agIxGsxkZc6elx\nfsLRlpb2gDo7N7Hz78jxE0SOnyB0/WLq/sT4RDoreXVVEaxN8U7s25ILYMkFZL2wPr7AiSAMR7oZ\ngBc5dAS0bkvr5vpwc9s+60wD0a27277HgltjimvkRAWRExWc+NuLCV3fMe1lYu7zxAw00NH1ybpi\nAdYVC0y6uerqbt3LuWTIKsiiDAmJiMV48OFMHaYWzm5TfvTFczs/yeU2H0dhCGcUdIwO0dBdtOea\nMyPpLs+EcXgmjDNWlPT01Ku6DVd6EPneIe+pEzs3cYe/Ad9bGyn8jfGJdFbyiqsIlkBixb42Nmw3\nH6FP8EwcH/f9Owf2DFBPhHNNLLg1UXEd8+AafG91DJiNVJyMsxCngvuDT5IXOBlkDFkFWZShoYtM\nbs4fnEEYunxnm/Kj1mzt/KSoZT6OwhDOKOgYHRLad9FedEfyAT5y5BiRI8eMFSUQ6FrZG8Y4c6iq\nRXPa//Z4UB4PVd82ZWc7m2j0Fc6Au1RJNnkSekfk8NG47w9N6d//d6F7OCfy0cva3SVi8hrLVqEW\nX9Cv/YjlOu5OcGyXxpFBxpBVkIWhi7hQCMLgoemOi+JyqOpNO9p8hHUkgo5EGPFTU3a2s4lGMiJX\nLaT5dpM+yulC0RVOf+JOsd1AYkp9sslTspLXgjAccM2b1T6Rd7lxfdTuLhGT11i2Cr2xi1UVR+7w\nGKE/ju/kYPuUBEuxM9dxZ8QyasRWE9WarUmvPRgRBVkY9MQUY1k1EIS+J+fZdR0CayLHT3R5Tsy9\nJRbsE5cG7qIL0cvm4nmvnOw/mPRRThcKlZbWrSIerqys+A1Ry+Q7dhZGiLW9+ALcpSOSlrwWhOFA\ndMsuPGUj7S+puUTF5C2y3BTl8YwsbS/3fPHcNkuz75qjHc/1+toUYx0OnVWxbeubjbXvIK6cnPiU\nbva13bOmpTx5HghEQRYGPf2tGItlWjjv6aY1J+beEgv2ictysW4bam27C01b0I+tVOtg0Pg52pbg\n2KAdI1Eh9l8+q8P1W25qX1bG5W5bWtYbt6PafNe93bonQRgq6JaOgXBdHm/7FXtWmiIezqw1as3W\neEtzrPKlHaSnw6E4xTh4Y0Ku8oQsMy3zx3a4fvPV7TLsjEuxdu1DB0zfVPrgq3wpCrIw5JDqeoLQ\nt0RbWuK+dyj/3At0MEj1/cs6+ozb1q/YoJ3Yl7r7llF337KklfQyV6zHnZuLZ/xYiFptS8vQPvjr\ncLjP7kEQBhMpx184SZwEd+bmEKt8mZhdwt6e9nqCPCZWvnxjY3ugNUbRzlyxnm/sO4QrK6tDcZCY\nu0hMUR5MiIIsDAq6o/SKQisI/YvnvfIu8wmHr17I8X+4uO27u6CgzYqbjJKH2yt4pepiUfjYWgof\naz+vzdJsD+pWYyORo8fP2o4gnA94xne03MZouOciqr/VXv7dM2Y0yu1GuZPkGE/AnZubesagGFEL\n90yTkjGmaP9q2qQOE/HB7ocsCrIgCIIgCIIgOBAFWRgQEi3GYhUWhMFF3TXxKdf2/3Rp29/ed8sZ\n+y9r2r5b9fVxbg5d4ZoyAdeUCR22dygQkkCbK0YXBUwE4Xyl/qL4anf7/6fdYpz35Lq4VZzIHTBK\nEAAAIABJREFUiYqU5TU6dSzRqR2t02erWGnt3HvWtge7LIuCLPQrnblOiEIsCIMHZ2BcLE9p3hPr\n2nwJq/70YqZ+ez1q4exeX8vauTfp4GnV1uGZMK7b7TnzwArC+YDTRSl8rQmay3m2XV5rv76MqX+x\nDn1J78dZXb4TXb6zw3arsqpLt47O6O/czH2JKMjDgMGchUEUYWE4EPOvdefntUV3n43O0hd5ykaa\ntGh2kIwzxZq7qLAtb2jsuh07Ex9c487N7ZgKLfF4TBEOz9gxeMa0W5piVlunb2BcERe7aMuInxtr\ncbKBsi+JHDnW7XOceWAFoSsO/Jexqp763sVnOdIQK4TRZ/SRz20sKwWA951N7TtseS16xFiL1cf9\nqxv0JAagy9zMgwxRkIcBUnhDEPqX2HJktLkFq6ambbt71jQgeYU5Z+7fGK45M4icOm3Sotm5QKOt\n7SmbrNo6rH0H467bdq2pk0x2Cfs8gND1i7EaGzsGv8R13o5K33+IyPETRE5UtF+vvmMfgW7lKU6F\nvm5PEHrC9J+ZDCej361P6fhwWX6vrhcrlBOj7isXdXKkMBhRehD6gOSqQr1UXTXQ3RD6mKFe8ONd\n/Xy51nrR2Y88/xCZHZ58dlctAK/MKjo3F1xyAWzoGwvTev0ejbpucIfJDxAir8OTW3eZjBErZqW2\nytVb1KI56E07+qStwSivYkEWzhnXjZo3JJVjsbQL5yuvzCpKWTl2pafjSk9v++6eMhGWXNBl2Wen\nOwkAG7aftUx0h3MA9+zpuGdPb/tuXbEgpT4LwnBixaySlJVjd0EB7oKC+G1Fhehlczs9x3Vh/EqZ\n3rSD6KVdj+lq0ZwO21o/t5TWzy1NcvTgYlgpyKLICP3BUFTqB5SEykq43ISuXxxfztg+pu5PlnU8\nPaHscVcv7BixUqipkGy5352fl9TfsLO8vkJHooFAW9J/sKvrbdjeZdlnpztJjLOViU52TmLgn/uD\nT1LpstAJTXcmdwVI+3Bk0u3C0MOqr8eqj3c1sWrr4qpgJhLdtqfDNtfqrvWuZBbmzBfXk/ni+hR7\nOnAMKwVZFJneIRMMoU9IqKxE1ML31sY4X9vYMYW/WUsiccdBly/sGDocSrl7zgCXGNaZBiKHjnQ8\nNiENkiszM24CELNmRpYv7DgxSEKcEt5ZJatOUIvmoObHZ5FILNPcXTqdWPR1Av9BXhBAiCfnmXVJ\ntwc/dfoc96RvcU+ZCEDgpiUpHe+a17HMeXcIXx0vn/Vf6WgQEAYvw0pBFnpHX00wRNEWhivR1ta4\nCUDMmulZWd5xYpCEOCXcEWyXCnrTDvTm+CwSiWWau0tsYuG/OUFhSOhXolW/fUeSSUGybVrHuV/E\nHe5ctk1ybrI0bq65M9v+dk+fkvT6yutNej3h/MU6cBiA9Nc2pHR8dMuuXl3P+268fBb8tqNBoCd0\nkNcEOq18l2yi2snktTOZd8pr0hW2JR3TuLlnTm0/v5NJh/Klvgp4rhAFWehzUlW0RZEWhMFBxsvt\nCsPJv+mYAitm1T/0VIJsJ5sUdDJRcLpfxG13LtsmOTdZGrfo1t1tf1t7DyS9vg6Hk15PEIY6Tnmt\n+H5HebUaGwE4+OT8+Elnsgl5J5P0xJW8tu0OeU1aaCRJkK21e3/7+Z1MOnQo9VXAc4UoyIIgCIIg\nCILgQBRkYcBItDSLRVkQBganL/KoH6/p9LhJd8fLaLKCCyf/5uIBq24nQZXC+YDThWL0v3cur5Pv\n2Ry3KnPqu8nlNZlbxDkhhbiNgUQUZGHQMNBBlqKgC+cLetncuOwg3QlydFL2nx0H51E/XtMn1e3c\nUyfhnjqpy2OyVsWntEq65CsIPWWQBpfGXCi6S9lPkstrX+UePxuvVSTETKQQtzGQiIIsDErePrnl\nnCusA62gC8K5Qq3dmlJ2kM5wZWXhLh3R3l5aGrVfW0bt19qj9GPW3FjmgFSJlei29h/C2n/I0Wmj\nrLTc1p4/teVyUxhBeX1tVnBXejqesWO6dU1BSMogLKTWE9z5ebiL2/OZu7KyOPW9i5OuACXmOj5r\n2473QDLC17bX1rpptMnqodLS2tJtxuR9MCIKsnBO6K6yO1SLigjCcOHAf8fnwj3yL+3Kb7SlBauy\nqu27DgYpenQtRY+2R+nHrLmxzAGpkrREd2YmKDNcZb3QMX+qDofarODRQIDI8RPduqYgDHUS5fXw\nj9rl1TrTgFVT2/Y92tJC2X+uSboClCzXcVc43wMxnK5O3nc2ddivg8G2dJvJ5H2wMChLTSulqoGj\nA90PQUhgvNb63NTwHGKIzAqDEJHXThB5FQYhg05eB6WCLAiCIAiCIAgDhbhYCIIgCIIgCIIDUZAF\nQRAEQRAEwYEoyIIgCIIgCILgQBRkQRAEQRAEQXAgCrIgCIIgCIIgOBAFWRAEQRAEQRAciIIsCIIg\nCIIgCA5EQRYEQRAEQRAEB6IgC4IgCIIgCIIDUZAFQRAEQRAEwYEoyIIgCIIgCILgQBRkQRAEQRAE\nQXAgCrIgCIIgCIIgODjvFGSl1DilVLNSyj3QfUkFpdQVSqkTju87lVJXDGCXuoVS6n6lVKX9mxcp\npS5RSu23v9+ilHpTKfXlFNoZUvct9A0ir+cWkVeht4jMnltEZvsPpbUe6D6kjFLqCDAKGKW1rnFs\n3wzMAyZqrY8MTO/6B/uBfUJrPWag+9JdlFJeoBG4SGu91d72HvCK1vp/BqhPDwBTtNZfHIjrn0+I\nvA4tRF4Fkdmhhchs/zIULciHgbtiX5RSFwCZA9cdoQtKgXRgp2Pb+ITvwvBG5HXoIPIqgMjsUEJk\ntj/RWg+ZD3AE+L/ARse2/wD+HtDABHvbp4HNmJnVceABx/ET7GM99vcPgH8BPgaagHeA4i76cDOw\nxW77IHC9vX0U8ApQBxwAvu4457fADx3frwBOJNzX3wK7gHrgMSC9i2Ovtv9+AHgO+L3d953AIsex\nC+zfoQn4A/Cssx9J7u3rwG77+F3AAnv7TPt3OmNf47OOc9Ls/4NjQCXwCyADmAa02L91M7DS/r2i\ngN/elma3+7UU+uC8bxfw/9nt1dq/QWHC/++X7T7VAH9v77seCAFh+/pb7e1fAQ7Z1zwM3DPQz/pw\n+CDymvjcPoDIq8jrIP4gMpv47D6AyOx5K7MD3oEeCO/VwF77gXIDJzAzJqfwXgFcYP8nX2g/VLd0\nIbwH7Yctw/7+o06uvwRoAK6x2x4NzLD3rQJ+jpnNzQOqgeXdEN4dwFigEPMi+WGKwhsAbrR/iweB\ndfY+H3AU+AvAC3zOfnCTCi9wO1ABLAYUMMX+Xb2Yl9Hf2W0utx/y6fZ5/4V5aRUCOcCrwIPJfuvE\n/jt+/6911Yck9/0XwDpgDOYF8Evg6YRrPmL/f84FgsBMx2/2hOP6WZgXcex+yoDZA/2sD4cPIq+J\nz+0DiLyKvA7iDyKzic/uA4jMnrcyOxRdLAAeB+7FCNFuzH94G1rrD7TW27XWUa31NuBp4FNdtPeY\n1nqf1tqPmSnN6+S4rwK/0Vr/0W67Qmu9Ryk1FrgE+L7WOqC13gI8avcxVX6qtT6uta4D/hXHEtdZ\nWK21fkNrbWF+l7n29osAD/CQ1jqstX4R2NBFO18Dfqy13qgNB7TWR+12sjEvtJDWeiXwGnCXUkoB\n3wD+Smtdp7VuAv4NuLMb951KHxL5FmbGekJrHcQI5OeVUh7HMf+ktfZr45e1lfbfJRlRYI5SKkNr\nfUprLctTfYvIazsiryKvQwGR2XZEZs9TmfWc/ZBByeOY2eREzNJHHEqppcCPgDmYGVkaZvmjM047\n/m7FPKzJGAu8kWT7KCD28MY4Cizq4pqJHE84d1SK5yX2Pd1+iEcBFVqbKVuSayQyFjPLT2QUcFxr\nHU3o32igBOObVm7kGDCz0p5GL3fWh0TGAyuUUs4+WRh/rBgp/Z9qrVuUUncAfw38Win1MfA9rfWe\nbvVc6AqR13ZEXg0ir4Mbkdl2RGYN553MDkkLsj3jOYxZ9ngxySFPYZYkxmqt8zA+OyrJcd3lODA5\nyfaTQKFSKsexbRzts+4W4oMcRiZpY2zCuSd70U+AU8Bo5ZCqhGsk0tW9jVVKOZ+V2L3VYHydZmut\n8+1Pnta6s5ff2eisD8mOu8FxzXytdbrWuuKsZ5qlofgNWr+ttb4Gs/SzB7N0JPQRIq8pIfKaHJHX\nAUBkNiVEZpMzbGR2SCrINl/F+B+1JNmXg5ltBpRSS4C7++iavwbuU0pdpZRyKaVGK6VmaK2PA2uA\nB5VS6UqpC+3+PWGftwW4USlVqJQaCfxlkrb/TCk1RilViAmIeLaXfV2LmfF9WynlUUrdjPHv6oxH\ngb9WSi1UhilKqfHAeszs8G+UUl47Jc5ngGfsGe8jwH8ppUYA2L/JdT3sc2d9SOQXwL/G9imlSuz7\nS4VKYELsZaSUKlVK3ayUysL4UTVjloOEvkXktWtEXpMj8jpwiMx2jchscoaNzA5ZBVlrfVBrvamT\n3X8K/LNSqgn4AcbnqS+uuQG4D+M03wB8iFmKAOPPNAEzG1wB/KPW+l173+MYH50jmAjeZIL5lL3v\nEGYJ5Ie97GsIEzTwVUxk7Bcxfk3BTo7/A8Yv6ylMgMBLmKjVEEZYb8DMZn8O3OtYHvk+JsBgnVKq\nEXgXmN7DPiftQ5JD/wdjvXjH/j9eByxN8TKxZcBapdQnGBn4Lub/rQ7jR3d/T/ovdI7I61n7KvKa\nHJHXAUJk9qx9FZlNzrCR2SFVKGS4okxy9q85hL2/rrMe+IXW+rH+vI4gDGdEXgVhaCEyK/SEIWtB\nFs6OUupTSqmR9vLPlzHpeN4a6H4JgtARkVdBGFqIzA5vhmoWCyE1pmOWvrIwy0qf11qfGtguCYLQ\nCSKvgjC0EJkdxoiLhSAIgiAIgiA4EBcLQRAEQRAEQXAgCrIgCMMGpdQ9Sql3Ujz2K0qp1d3dJwhC\ncs43+VNK/VYp1atsGMLgRRTkHqKUOqKU8iulmh2fn9qCrZVS/5Vw/M329t/a3yfY32PnViqlXlNK\nXeM4x9l2NOF695zjW+4z7NyL4tsj9Bil1KVKqTVKqQalVJ1S6mOl1GKt9ZNa62sHun/dQeRcGGoM\nJ/mDtvH86l624VNKPW+3pe18xrF9bzpkOqyUCjm+/6LXNzCAKKVOOO91OCEKcu/4jNY62/H5tr39\nIPAFFV+3/MvAviRt5NtVceYCf8SUd/wKgLNt4FjC9Z5MbCjheoOSodBHYXCjlMrF5Bv9X0wOz9HA\nP9FJ/tGB5mzPvMi5MJQYbvLXx6zG5EN2lmFGa32DQ8afBH7skPFvJTYyFORnKPSxt4iC3D+cBrYD\n1wEoU7nnYkzi7aRorU9rrf8HeAD4dxVfdjIpSqkfKqWeVUo9bSfz/qJSaplSap1S6oxS6pRS6iGl\nlNc+3mPPbL+plDqglKpXSj3kaG+aUmqVbRWoUUo9lXDenyulDtv7fqTaK+W4lFI/UEodVUpV2ctO\nufa+Kfa59ymljmESta+y98Vm0Iu7/xML5zHTALTWT2utLa21X2v9jtZ6m0pYmrWfvW8ppfbbMvEz\npVTSkrhKqf+nlFqtlMpzbPsPW04OK6VucGwfpZR6xbaeHVBKfd2x7wHbkvSEMon9v2Jve04p9Xul\nVJNSaqdSalEqNytyLgwyzhv5U0pdoYyF9O9seTiiOlnV0VqHtNb/rbVejamwlzJKqavttv9OKXUa\neEQpVaSUekMpVW3/Bq8qpUY7zlmtlPonZSz5TUqpt5TRNVBKZSqlnlJK1dq/+walVLHjvH9VSm2y\n3wErlFIFjnZvtX+fM0qplUqp6Y59J5RS/0cptR1oUUo9DYwCYhby73bnvgc7oiD3H78H7rX/vhN4\nmdRm2C8CI0i9Us6tmKo4eZjqQRHgL4Bi4BLgeuCbCefcCCwE5mMG29jS0r8CrwMFwBjgZwnn3Qws\nsM/9PO339zXMrPkKTJ33AkwlHieXAzOAT9t/Oy1nG1O8V0EAsxJjKaV+p5S6wfly74SbgMWYHKVf\nwJ64xrAVv0fs/ddqrRvsXUuBvRhZ+jHwa8fg/gxwAjM4fB74N6XUckezNwPPA/kYixHAZ+3z8jGT\n5Z92455FzoXBwvkmfyPtPozGrAT/yqk09iFjgGxgHKZSoQtTZnocpppgmI7ydrfdp1JMqrmYgnof\nkGm3WWS3F3Ccd6/9GQUoTOVClFIzMVUJ/xwowVTte0XZk2+bOzFV//K11ndhKuTFLOQ/6dUvMMgQ\nBbl3vGTPsmKfrzv2rQCusGfD92IU5lQ4af+brPxjMlZrrV/VWkftmfxGrfV6rXVEa30I+BWmtKOT\nB7XWDVrrI8AHwDx7exhTyrNMax3QWn+ccN6PtNb1WuujwEOY0p8A9wD/obU+rLVuAv4OuFvFW8H/\nUWvdqrX2p3hfgpAUrXUjcCmgMQNItW1NKu3klB9prc9orY8B79P+vAN4gacx8vYZrXWrY99RrfUj\nWmsL+B1QBpQqpcZilNLv23KyBXiUdkUSYK3W+qWYXNrbVmut37DbexzjVpUqIufCoOA8lb9/0FoH\ntdYfYiaXX+jGuakSAR6wLdF+rXW11nqF/Xcj8G90lPFfa63327/bH4iX8WJgim3l36S1bnac9zut\n9S6tdQumVPid9uTjTuAVrfVKrXUY+BFmUu4sM/0/WusT54OMi4LcO27RWuc7Po/EdtgPz+vA/wWK\nkgxCnRFbQqlL8fjjzi9KqRlKqdeVUqft5aV/xgiKE6d/VCtm1grwPcwLa5NSarsylYE6u9ZRzOwT\n+9+jCft8mBlo0n4KQm/QWu/WWn9Faz0GmIN5Bv+7k8M7e94BpmCsTf+ktQ51dp5j4M62r1VnK4kx\njtIuu5D8eU/sR7pK3Y9P5FwYNJxn8ldvK5LOa43q7OBeUOn8DZRS2UqpR5VSx2wZX0nqMv5bjPX3\nOaVUhTKuUs57TZTxNMwkJU7GtdZRjKX+bL/tsEQU5P7l95jB6IlunHMrUIVZWkqFxCjxXwI7MDPH\nXMzsMKnPV4eGtD6ltf6a1roM+DPMUtJExyFjHX+Po93afRKzBOTcFwKqHW07+ymR7UKfobXegxkQ\n5vTg9N2Y5cg3u7FsehIoVErlOLaNAyqc3epBX7pC5FwYlJwH8leglMpKuNbJzg7uBYl9/j/ARGCJ\nLePLO57SSUPGCv2A1nomxtp/K2YFKEaijAcxRrk4GbdXh8bQ9W87bOVcFOT+5UPgGky0b5copUqV\nUt8G/hH4W3vm1hNygAaMA/1MOvoldtWHLziCAM5gHnxnsMHfKKXylVLjgO9gfCHBLJF9V5nUdTkY\nH8enu7iHKkArpSalfFeCYGNbT7+nlBpjfx+LcQNY15P2tNZPY9wF3lVKTU7h+OPAGuBBpVS6UupC\n4Kt0byLcW0TOhQFhGMuf124v9nFaXP9JmTRul2F8qv+QrAGlVJpSKt3+6rPbSWnimoQcjFW4XilV\nhJkEp4RSarlSao6t4DZiXC6ccnqv/f+YhclA8pw9uX0O+KwywYlejJLeBKzv4nKVwLCUcVGQe8er\nKj6H6QrnTm14T2vdlbvEGaVUCybrxY3A7Vrr3/SiT9/DOO03YaxMz3Z9eBxLgY12f14E/sz2G4vx\nKrAF2Izxsf6tvf0R+zofYerRN2ECiJJiL409CKy3fbdTiuYXBJsmzLO63n5W12Gsqd/raYNa699h\n3BRWKqUmpHDKXRg/3pMYWfhHrfW7Pb1+DxA5FwaK4Sp/bwB+x+cBe/tpoN6+1pPAt2yreTL22ueO\nBt62/x7fybFn4ycY/99azITgzW6cOwoj243AToy7xVOO/Y9jJhSnADfwlwBa652Y98rDmJWh64HP\n2v7InfFvmAnEGaXUX3ajj4MeFb8iJggdsWfSYWCiHfAjCMIwQ+RcEOJRpgDGE7av9bBAmTR8j2qt\nfzvQfRnsiAVZEARBEARBEByIgiwIgiAIgiAIDsTFQhAEQRAEQRAciAVZEARBEARBEBykmqQegOLi\nYj1hwoR+6oogCADl5eU1WuuSsx/ZNSKvgnBu6AuZFXkVhHNDqvLaLQV5woQJbNq0qee9EgThrCil\njp79qLMj8ioI54a+kFmRV0E4N6Qqr+JiIQiCIAiCIAgOREEWBEEQBEEQBAeiIAuCIAiCIAiCA1GQ\nBUEQBEEQBMGBKMiCIAiCIAiC4KBbWSyGAturKvn5xnUcqq9nbulI7l+8lIn5BQPdLUEQktAYDPLY\nlnLePrCf7LQ0vjJ3PjdMmYZSaqC7JghCEt47fJBfby6nzu/nqomT+Nr8RRRkZAx0twShzxlWCvKq\no0e4//WXCUQiaOBgfR1vHNjH87ffxYziXqeVpba1lfUVx8nwerlk7Hh8bnfvOy0I5ymt4TC3PPME\np5qbCFoWADurqthaeZq/vfRTvW7fikZZV3GcOr+fhWWjGJWT2+s2BeF85uGN6/npxnX4IxEAjpyp\nZ8WeXbxx973kp/deST565gzbqk5TmpXN4lGjZaIsDCjDRkHWWvOD9981gqshU2fT6mqmNRzmwdWr\n+N0tt/Wq/d9sLuf/rfkIj8uNAtwuxWM338a8kWV9cwOCcJ7xwq4dVLY0E7Qs0iLphFQQP2F+t3Uz\nX52/kBFZ2T1u+/CZeu558TmagiFAE4lGueeCufz9ZVfIoCsIPaAxGOShDWsJWhauqAuP5SVEkHq/\nnye2beHbS5b1uO2o1vzNH9/i9f178biM52dJVhZPfe4LjMzO6atbEIRuMWx8kFvCYSqamgAYG57M\n5xq+ysLWy/FG0/jkVEWv2t5aeZr/WLuaoGXREg7RHA7REAxy38svELItX4IgdI8Pjh7GH4ngstws\n8S9ngf9ysqwcfC43m0+f6nG7Wmu+9soKKpubaQmHaAmHCVoWT+/YztsHD/ThHQjC+cOu6qq2VdOp\ngQtZFriWsuA4QpEo7x853Ku2n96xjTcP7LPH2DAt4TDHGhr48zdf64uuC0KP6FcFOao1jcEgUa37\n8zIApHs8bTPPGs9pDvn2MDu4iM81/glzwguIRnve9nM7t7cpwotaP8X40DQALK1Zc/xYr/suCIOF\n1nCYoL182t+UZefgUoqoy+KU+xjZOpcLAksY459Gnqvn1uP9dbWcbm5CA4WBUuY2X4Q3moY/Eubx\nbZv77gYEYYAJWxZNwSD6HIyxxZmZROyB9JT7GCECTAnPMTLrGkVvuvD4ts34IxFUVLGkaTmFoRKi\nWrO9qpLqlpY+ugNB6B794mKhtebRTzbxs03raQ2Hyfb5+KulF/OlufP743IAeFwubp81m+d378Qf\naWFN1tvsSdvM0sAVzKi/lIcfhmuvhSlToLsrrE22ku/WHkojo5kdXMSh0G62531EazjUPzckCOeQ\n3dVVfP/dt9ldU41SiuUTJvHgVdf2a/DNl+bO58U9uwjoCId9uwmGgxTqIsooo3H/SPaFYdIk8HTz\nLeUPh3ErM1nOjxYxMjKOgqYS9mZuI+CPEo2Ca9isnQnnI8FIhB+u+oDnd+/A0pqy7Bx+eOXVXDZ+\nQr9dc0phEVMKi9hdXUWTt569aislkTLyVC4L1Tw2bIAZMyAvr/ttt4bDAGRGcyi0Sris5dPstbZy\nNHsn/ki4j+9EEFKjX4aJ323dzH+vX0NjMEgkGuVMIMCPPl7F87t29Mfl2vj7y67g2klT8Lnd5Ph8\ntKTVMvrSQ9xxhyYahaeegiefhKqq7rV7w9RpZHq9WCrCGzlPszn9YyaEp3FN3d2MCk/ol3sRhHNF\ndUsLdzz/LDuqq7C08dd9/8gh7lnxh361TE0vKuYn19xAbloaGWlemtNryC4I883rJlFaqjh8GD76\nCI4fp1srQDNLRrRNgg9l7mJj+iosLC5oXcwl7oupqoKGBgiF6JXVSxAGir/+41s8v3snQcsiEo1y\nvLGBb77+MjuqKvv1uo9+9lYuLB1JmtdNJL2JUFoL1y4o5dL52TQ3w9q1sG0b+P3da/e6yVPxuty0\neBp5L2sFJz1HmRGYx6eaP01WpAcatyD0Aao7A+CiRYv0pk2bzn7cIz+nzu9HacXk0GwO+nailWZU\nTg6r7/tGb/obR0VTI//4/nusOnYEj8vFTVOn838vv4KQFeVUcxPj8/LJTUsDwLJg40b48EMIBmHB\nArjySsjKOvt1rGiUP3nlRcpPnqQ1EsalFKXRMm6M3EKkOYNFi+Caa8Dn67NbE85jlFLlWutFvW0n\nVXn96Ya1/GzjeoKWRVl4HA2uOlrdzWR6vfzulttYWDa6t10BjMvVLzdt4NHN5TQEA8woKuYHn1rO\n/JFl7K6qIdOTRnown8ZGmDDBKLB79hhlNjsbpk2DkhST0bx1YB/ffedNwpaFpTWFuoC5ah6XF8yj\nIM/FnDmmTZcL0tMhIwMkKY3QU/pCZlOV1+rWFi577BFCloXPyqDEGkmF7zAKuH7KVH5242d70404\ntpw+xQMfrGRHdSU5Ph9fnruAby+5iNPNTdQ0BRidUURNpYf8fCguhoMH4dgxs0o7YQJMnJjaCtCZ\ngJ+bn3mSmtYW/JEIvqiH8eFpXJO+nCxPGsuWwdy53V/9FYRkpCqvfe5iEdWaOnv6OC48lUtar2Nq\ncA6rs96iqqWxz67THApxyzNPcibgb7N6vbx3D7uqq3j1ri9RnJkZd7zbDRddBBdeaJTkTZtg+3a4\n7DKzvSshdrtc/Oazn+OdQwd468B+sn0+7ph9ATMLM1i5Etatg0OH4JZbYOzYPrtFQTgn7K+ra4tM\nn+NfihsXu9I3UeM5xvGGhj5TkH+0+kOe3L61LUXUrppq7nv5BZ75/J3MHlGKZZkBsKUFTp407hVL\nl8Lp07BvH3zyCRQVmWXc7LO4KF8/ZRpTC4t4asc2KpubuXzcRK4cNYOaShd79hj5nz4dxo0z1q7W\nVvB6jbKcni4DsTB4OdnYiM/tJmRZTAvNYVxoGqWRsWxLX8vB+vo+u87+2lruefG5Nnl7+c2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/fuNRPaq682k3jh3KN1CAKvoQPvgKsAlXEnyjd3oLs1NBXkGAcPGr/d5mYTbHDZZakpoOWnKvhV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K+OhleNxpZk1dQ75Yx9CgTMYUv6vHI4Bxc7MI4k7xn6K4Qb0cyXc5ti0WsU89JebpqVNFutyR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yFJExbR4iqIfK5yL4GzcOUYbvorYPdSLIV5Yfu7kWWLJXN/NX7M/RB875s5JP8n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\ny7K455cPk0lmkBSV2tO/ROHMxXS++hitrU+jXvGr0fcuOmUeT9/yI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+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f9804347080>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "pl.figure(2, figsize=(10, 6))\n",
+ "\n",
+ "pl.subplot(2, 3, 1)\n",
+ "pl.imshow(ot_emd.coupling_, interpolation='nearest')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Optimal coupling\\nEMDTransport')\n",
+ "\n",
+ "pl.subplot(2, 3, 2)\n",
+ "pl.imshow(ot_sinkhorn.coupling_, interpolation='nearest')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Optimal coupling\\nSinkhornTransport')\n",
+ "\n",
+ "pl.subplot(2, 3, 3)\n",
+ "pl.imshow(ot_lpl1.coupling_, interpolation='nearest')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Optimal coupling\\nSinkhornLpl1Transport')\n",
+ "\n",
+ "pl.subplot(2, 3, 4)\n",
+ "ot.plot.plot2D_samples_mat(Xs, Xt, ot_emd.coupling_, c=[.5, .5, 1])\n",
+ "pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Main coupling coefficients\\nEMDTransport')\n",
+ "\n",
+ "pl.subplot(2, 3, 5)\n",
+ "ot.plot.plot2D_samples_mat(Xs, Xt, ot_sinkhorn.coupling_, c=[.5, .5, 1])\n",
+ "pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Main coupling coefficients\\nSinkhornTransport')\n",
+ "\n",
+ "pl.subplot(2, 3, 6)\n",
+ "ot.plot.plot2D_samples_mat(Xs, Xt, ot_lpl1.coupling_, c=[.5, .5, 1])\n",
+ "pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Main coupling coefficients\\nSinkhornLpl1Transport')\n",
+ "pl.tight_layout()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Fig 3 : plot transported samples\n",
+ "--------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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iTrVtt1q5cMRILhwxspMSazS9hx3l5QQiYdLc8YAxIJTuTqDYW8+RulpGDkoB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ADODCR5e5fG1V3pu4iIgUBnf781qEGr/82UQVkjwBoblkZkwCo0pzjWSJACJHVvm4oUIjEo+Bpa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\niwtj0zdo2QAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f9804344d68>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# display transported samples\n",
+ "pl.figure(4, figsize=(10, 4))\n",
+ "pl.subplot(1, 3, 1)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n",
+ " label='Target samples', alpha=0.5)\n",
+ "pl.scatter(transp_Xs_emd[:, 0], transp_Xs_emd[:, 1], c=ys,\n",
+ " marker='+', label='Transp samples', s=30)\n",
+ "pl.title('Transported samples\\nEmdTransport')\n",
+ "pl.legend(loc=0)\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "\n",
+ "pl.subplot(1, 3, 2)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n",
+ " label='Target samples', alpha=0.5)\n",
+ "pl.scatter(transp_Xs_sinkhorn[:, 0], transp_Xs_sinkhorn[:, 1], c=ys,\n",
+ " marker='+', label='Transp samples', s=30)\n",
+ "pl.title('Transported samples\\nSinkhornTransport')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "\n",
+ "pl.subplot(1, 3, 3)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n",
+ " label='Target samples', alpha=0.5)\n",
+ "pl.scatter(transp_Xs_lpl1[:, 0], transp_Xs_lpl1[:, 1], c=ys,\n",
+ " marker='+', label='Transp samples', s=30)\n",
+ "pl.title('Transported samples\\nSinkhornLpl1Transport')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "\n",
+ "pl.tight_layout()\n",
+ "pl.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/notebooks/plot_otda_mapping.ipynb b/notebooks/plot_otda_mapping.ipynb
new file mode 100644
index 0000000..f25eb11
--- /dev/null
+++ b/notebooks/plot_otda_mapping.ipynb
@@ -0,0 +1,288 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# OT mapping estimation for domain adaptation\n",
+ "\n",
+ "\n",
+ "This example presents how to use MappingTransport to estimate at the same\n",
+ "time both the coupling transport and approximate the transport map with either\n",
+ "a linear or a kernelized mapping as introduced in [8].\n",
+ "\n",
+ "[8] M. Perrot, N. Courty, R. Flamary, A. Habrard,\n",
+ " \"Mapping estimation for discrete optimal transport\",\n",
+ " Neural Information Processing Systems (NIPS), 2016.\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Authors: Remi Flamary <remi.flamary@unice.fr>\n",
+ "# Stanislas Chambon <stan.chambon@gmail.com>\n",
+ "#\n",
+ "# License: MIT License\n",
+ "\n",
+ "import numpy as np\n",
+ "import matplotlib.pylab as pl\n",
+ "import ot"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Generate data\n",
+ "-------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "n_source_samples = 100\n",
+ "n_target_samples = 100\n",
+ "theta = 2 * np.pi / 20\n",
+ "noise_level = 0.1\n",
+ "\n",
+ "Xs, ys = ot.datasets.get_data_classif(\n",
+ " 'gaussrot', n_source_samples, nz=noise_level)\n",
+ "Xs_new, _ = ot.datasets.get_data_classif(\n",
+ " 'gaussrot', n_source_samples, nz=noise_level)\n",
+ "Xt, yt = ot.datasets.get_data_classif(\n",
+ " 'gaussrot', n_target_samples, theta=theta, nz=noise_level)\n",
+ "\n",
+ "# one of the target mode changes its variance (no linear mapping)\n",
+ "Xt[yt == 2] *= 3\n",
+ "Xt = Xt + 4"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plot data\n",
+ "---------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.text.Text at 0x7fb0178b1208>"
+ ]
+ },
+ "execution_count": 4,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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39DRG1p4fRyNHjmThwoUsX76c8ePHF87YqyuuuOKKGm+laoiSPG4kRteXuIQk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\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fb019d04d68>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "pl.figure(1, (10, 5))\n",
+ "pl.clf()\n",
+ "pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')\n",
+ "pl.legend(loc=0)\n",
+ "pl.title('Source and target distributions')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Instantiate the different transport algorithms and fit them\n",
+ "-----------------------------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 0|4.210546e+03|0.000000e+00\n",
+ " 1|4.194392e+03|-3.836611e-03\n",
+ " 2|4.194053e+03|-8.094371e-05\n",
+ " 3|4.193924e+03|-3.056965e-05\n",
+ " 4|4.193849e+03|-1.797118e-05\n",
+ " 5|4.193801e+03|-1.140070e-05\n",
+ " 6|4.193776e+03|-5.930168e-06\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 0|4.245881e+02|0.000000e+00\n",
+ " 1|4.181680e+02|-1.512078e-02\n",
+ " 2|4.178974e+02|-6.472597e-04\n",
+ " 3|4.177550e+02|-3.406786e-04\n",
+ " 4|4.176586e+02|-2.307406e-04\n",
+ " 5|4.175879e+02|-1.692203e-04\n",
+ " 6|4.175338e+02|-1.295518e-04\n",
+ " 7|4.174909e+02|-1.028089e-04\n",
+ " 8|4.174570e+02|-8.123852e-05\n",
+ " 9|4.174309e+02|-6.257777e-05\n",
+ " 10|4.174083e+02|-5.401101e-05\n"
+ ]
+ }
+ ],
+ "source": [
+ "# MappingTransport with linear kernel\n",
+ "ot_mapping_linear = ot.da.MappingTransport(\n",
+ " kernel=\"linear\", mu=1e0, eta=1e-8, bias=True,\n",
+ " max_iter=20, verbose=True)\n",
+ "\n",
+ "ot_mapping_linear.fit(Xs=Xs, Xt=Xt)\n",
+ "\n",
+ "# for original source samples, transform applies barycentric mapping\n",
+ "transp_Xs_linear = ot_mapping_linear.transform(Xs=Xs)\n",
+ "\n",
+ "# for out of source samples, transform applies the linear mapping\n",
+ "transp_Xs_linear_new = ot_mapping_linear.transform(Xs=Xs_new)\n",
+ "\n",
+ "\n",
+ "# MappingTransport with gaussian kernel\n",
+ "ot_mapping_gaussian = ot.da.MappingTransport(\n",
+ " kernel=\"gaussian\", eta=1e-5, mu=1e-1, bias=True, sigma=1,\n",
+ " max_iter=10, verbose=True)\n",
+ "ot_mapping_gaussian.fit(Xs=Xs, Xt=Xt)\n",
+ "\n",
+ "# for original source samples, transform applies barycentric mapping\n",
+ "transp_Xs_gaussian = ot_mapping_gaussian.transform(Xs=Xs)\n",
+ "\n",
+ "# for out of source samples, transform applies the gaussian mapping\n",
+ "transp_Xs_gaussian_new = ot_mapping_gaussian.transform(Xs=Xs_new)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plot transported samples\n",
+ "------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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7eZHN9B+Lx6idWsXerQ1oGGadLSrrKvDTATMWTGX1P9cRK4pRXlWKBiF+KqS8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\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7fb0177ef7f0>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "pl.figure(2)\n",
+ "pl.clf()\n",
+ "pl.subplot(2, 2, 1)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n",
+ " label='Target samples', alpha=.2)\n",
+ "pl.scatter(transp_Xs_linear[:, 0], transp_Xs_linear[:, 1], c=ys, marker='+',\n",
+ " label='Mapped source samples')\n",
+ "pl.title(\"Bary. mapping (linear)\")\n",
+ "pl.legend(loc=0)\n",
+ "\n",
+ "pl.subplot(2, 2, 2)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n",
+ " label='Target samples', alpha=.2)\n",
+ "pl.scatter(transp_Xs_linear_new[:, 0], transp_Xs_linear_new[:, 1],\n",
+ " c=ys, marker='+', label='Learned mapping')\n",
+ "pl.title(\"Estim. mapping (linear)\")\n",
+ "\n",
+ "pl.subplot(2, 2, 3)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n",
+ " label='Target samples', alpha=.2)\n",
+ "pl.scatter(transp_Xs_gaussian[:, 0], transp_Xs_gaussian[:, 1], c=ys,\n",
+ " marker='+', label='barycentric mapping')\n",
+ "pl.title(\"Bary. mapping (kernel)\")\n",
+ "\n",
+ "pl.subplot(2, 2, 4)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n",
+ " label='Target samples', alpha=.2)\n",
+ "pl.scatter(transp_Xs_gaussian_new[:, 0], transp_Xs_gaussian_new[:, 1], c=ys,\n",
+ " marker='+', label='Learned mapping')\n",
+ "pl.title(\"Estim. mapping (kernel)\")\n",
+ "pl.tight_layout()\n",
+ "\n",
+ "pl.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/notebooks/plot_otda_mapping_colors_images.ipynb b/notebooks/plot_otda_mapping_colors_images.ipynb
new file mode 100644
index 0000000..288f4f1
--- /dev/null
+++ b/notebooks/plot_otda_mapping_colors_images.ipynb
@@ -0,0 +1,363 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# OT for image color adaptation with mapping estimation\n",
+ "\n",
+ "\n",
+ "OT for domain adaptation with image color adaptation [6] with mapping\n",
+ "estimation [8].\n",
+ "\n",
+ "[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014). Regularized\n",
+ " discrete optimal transport. SIAM Journal on Imaging Sciences, 7(3),\n",
+ " 1853-1882.\n",
+ "[8] M. Perrot, N. Courty, R. Flamary, A. Habrard, \"Mapping estimation for\n",
+ " discrete optimal transport\", Neural Information Processing Systems (NIPS),\n",
+ " 2016.\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Authors: Remi Flamary <remi.flamary@unice.fr>\n",
+ "# Stanislas Chambon <stan.chambon@gmail.com>\n",
+ "#\n",
+ "# License: MIT License\n",
+ "\n",
+ "import numpy as np\n",
+ "from scipy import ndimage\n",
+ "import matplotlib.pylab as pl\n",
+ "import ot\n",
+ "\n",
+ "r = np.random.RandomState(42)\n",
+ "\n",
+ "\n",
+ "def im2mat(I):\n",
+ " \"\"\"Converts and image to matrix (one pixel per line)\"\"\"\n",
+ " return I.reshape((I.shape[0] * I.shape[1], I.shape[2]))\n",
+ "\n",
+ "\n",
+ "def mat2im(X, shape):\n",
+ " \"\"\"Converts back a matrix to an image\"\"\"\n",
+ " return X.reshape(shape)\n",
+ "\n",
+ "\n",
+ "def minmax(I):\n",
+ " return np.clip(I, 0, 1)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Generate data\n",
+ "-------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Loading images\n",
+ "I1 = ndimage.imread('../data/ocean_day.jpg').astype(np.float64) / 256\n",
+ "I2 = ndimage.imread('../data/ocean_sunset.jpg').astype(np.float64) / 256\n",
+ "\n",
+ "\n",
+ "X1 = im2mat(I1)\n",
+ "X2 = im2mat(I2)\n",
+ "\n",
+ "# training samples\n",
+ "nb = 1000\n",
+ "idx1 = r.randint(X1.shape[0], size=(nb,))\n",
+ "idx2 = r.randint(X2.shape[0], size=(nb,))\n",
+ "\n",
+ "Xs = X1[idx1, :]\n",
+ "Xt = X2[idx2, :]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Domain adaptation for pixel distribution transfer\n",
+ "-------------------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 0|3.680514e+02|0.000000e+00\n",
+ " 1|3.592355e+02|-2.395298e-02\n",
+ " 2|3.590579e+02|-4.943115e-04\n",
+ " 3|3.589661e+02|-2.556530e-04\n",
+ " 4|3.589094e+02|-1.577896e-04\n",
+ " 5|3.588705e+02|-1.084239e-04\n",
+ " 6|3.588421e+02|-7.914757e-05\n",
+ " 7|3.588206e+02|-6.013011e-05\n",
+ " 8|3.588034e+02|-4.783086e-05\n",
+ " 9|3.587895e+02|-3.866500e-05\n",
+ " 10|3.587781e+02|-3.194454e-05\n",
+ " 11|3.587684e+02|-2.697250e-05\n",
+ " 12|3.587601e+02|-2.296505e-05\n",
+ " 13|3.587530e+02|-1.975975e-05\n",
+ " 14|3.587468e+02|-1.733678e-05\n",
+ " 15|3.587413e+02|-1.535580e-05\n",
+ " 16|3.587365e+02|-1.350581e-05\n",
+ " 17|3.587321e+02|-1.209997e-05\n",
+ " 18|3.587282e+02|-1.086348e-05\n",
+ " 19|3.587268e+02|-4.096770e-06\n",
+ "It. |Loss |Delta loss\n",
+ "--------------------------------\n",
+ " 0|3.784725e+02|0.000000e+00\n",
+ " 1|3.646380e+02|-3.655332e-02\n",
+ " 2|3.642858e+02|-9.660434e-04\n",
+ " 3|3.641516e+02|-3.683776e-04\n",
+ " 4|3.640785e+02|-2.008220e-04\n",
+ " 5|3.640320e+02|-1.276966e-04\n",
+ " 6|3.639999e+02|-8.796173e-05\n",
+ " 7|3.639764e+02|-6.455658e-05\n",
+ " 8|3.639583e+02|-4.976436e-05\n",
+ " 9|3.639440e+02|-3.946556e-05\n",
+ " 10|3.639322e+02|-3.222132e-05\n"
+ ]
+ }
+ ],
+ "source": [
+ "# EMDTransport\n",
+ "ot_emd = ot.da.EMDTransport()\n",
+ "ot_emd.fit(Xs=Xs, Xt=Xt)\n",
+ "transp_Xs_emd = ot_emd.transform(Xs=X1)\n",
+ "Image_emd = minmax(mat2im(transp_Xs_emd, I1.shape))\n",
+ "\n",
+ "# SinkhornTransport\n",
+ "ot_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1)\n",
+ "ot_sinkhorn.fit(Xs=Xs, Xt=Xt)\n",
+ "transp_Xs_sinkhorn = ot_emd.transform(Xs=X1)\n",
+ "Image_sinkhorn = minmax(mat2im(transp_Xs_sinkhorn, I1.shape))\n",
+ "\n",
+ "ot_mapping_linear = ot.da.MappingTransport(\n",
+ " mu=1e0, eta=1e-8, bias=True, max_iter=20, verbose=True)\n",
+ "ot_mapping_linear.fit(Xs=Xs, Xt=Xt)\n",
+ "\n",
+ "X1tl = ot_mapping_linear.transform(Xs=X1)\n",
+ "Image_mapping_linear = minmax(mat2im(X1tl, I1.shape))\n",
+ "\n",
+ "ot_mapping_gaussian = ot.da.MappingTransport(\n",
+ " mu=1e0, eta=1e-2, sigma=1, bias=False, max_iter=10, verbose=True)\n",
+ "ot_mapping_gaussian.fit(Xs=Xs, Xt=Xt)\n",
+ "\n",
+ "X1tn = ot_mapping_gaussian.transform(Xs=X1) # use the estimated mapping\n",
+ "Image_mapping_gaussian = minmax(mat2im(X1tn, I1.shape))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plot original images\n",
+ "--------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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JTgVSA3I4do8zhuEidFGaFmaCU5wpbnj5AuYU59/z72bRawh8214lb8rgJBnJY6ARKALr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\nMhjpyin4AAAAAElFTkSuQmCC\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f281a75f748>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "pl.figure(1, figsize=(6.4, 3))\n",
+ "pl.subplot(1, 2, 1)\n",
+ "pl.imshow(I1)\n",
+ "pl.axis('off')\n",
+ "pl.title('Image 1')\n",
+ "\n",
+ "pl.subplot(1, 2, 2)\n",
+ "pl.imshow(I2)\n",
+ "pl.axis('off')\n",
+ "pl.title('Image 2')\n",
+ "pl.tight_layout()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plot pixel values distribution\n",
+ "------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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TTVQ29qQaXoEDbYeq1kB1OByOU80ZJYrfe3oH2SrtlmqRVG0biOK0Azs8Bl7G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\nzMyyvwEnvbs5vBaWXAAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f281541a780>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "pl.figure(2, figsize=(6.4, 5))\n",
+ "\n",
+ "pl.subplot(1, 2, 1)\n",
+ "pl.scatter(Xs[:, 0], Xs[:, 2], c=Xs)\n",
+ "pl.axis([0, 1, 0, 1])\n",
+ "pl.xlabel('Red')\n",
+ "pl.ylabel('Blue')\n",
+ "pl.title('Image 1')\n",
+ "\n",
+ "pl.subplot(1, 2, 2)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 2], c=Xt)\n",
+ "pl.axis([0, 1, 0, 1])\n",
+ "pl.xlabel('Red')\n",
+ "pl.ylabel('Blue')\n",
+ "pl.title('Image 2')\n",
+ "pl.tight_layout()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plot transformed images\n",
+ "-----------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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OeUI9r3V7/FncBOA1bpv3hE16F2hS4BvdnLfEVW73RXf8EKZZjhIINNyhcz4g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LuEu7pTrRvyeREASY46RahzJiu2qf4tq6QOhwFih7LmyIr6+zP3jLa+6Te/aCEsh3hIR6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hJkHqkrgez5i7PI+65ZmgTjyZbZveotRU5qwfQFb3TfQjdMWFNhaiGse+ZdxcXDjtnLicqC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\ne7Rknttkrk08fSqIwNWJxwLbULhFZ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u4ryu0M03nDE6vC/fuFA205ksDv3R653EEsHmMM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\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rmSn0ZKuV2P1+aihAtz+wuO9j5KSAVyvM6DUe6Q3PMo9YTuCNBJKpOB+/+9afRAH8jbff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\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f28105bc2e8>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "pl.figure(2, figsize=(10, 5))\n",
+ "\n",
+ "pl.subplot(2, 3, 1)\n",
+ "pl.imshow(I1)\n",
+ "pl.axis('off')\n",
+ "pl.title('Im. 1')\n",
+ "\n",
+ "pl.subplot(2, 3, 4)\n",
+ "pl.imshow(I2)\n",
+ "pl.axis('off')\n",
+ "pl.title('Im. 2')\n",
+ "\n",
+ "pl.subplot(2, 3, 2)\n",
+ "pl.imshow(Image_emd)\n",
+ "pl.axis('off')\n",
+ "pl.title('EmdTransport')\n",
+ "\n",
+ "pl.subplot(2, 3, 5)\n",
+ "pl.imshow(Image_sinkhorn)\n",
+ "pl.axis('off')\n",
+ "pl.title('SinkhornTransport')\n",
+ "\n",
+ "pl.subplot(2, 3, 3)\n",
+ "pl.imshow(Image_mapping_linear)\n",
+ "pl.axis('off')\n",
+ "pl.title('MappingTransport (linear)')\n",
+ "\n",
+ "pl.subplot(2, 3, 6)\n",
+ "pl.imshow(Image_mapping_gaussian)\n",
+ "pl.axis('off')\n",
+ "pl.title('MappingTransport (gaussian)')\n",
+ "pl.tight_layout()\n",
+ "\n",
+ "pl.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/notebooks/plot_otda_semi_supervised.ipynb b/notebooks/plot_otda_semi_supervised.ipynb
new file mode 100644
index 0000000..6c538e9
--- /dev/null
+++ b/notebooks/plot_otda_semi_supervised.ipynb
@@ -0,0 +1,294 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# OTDA unsupervised vs semi-supervised setting\n",
+ "\n",
+ "\n",
+ "This example introduces a semi supervised domain adaptation in a 2D setting.\n",
+ "It explicits the problem of semi supervised domain adaptation and introduces\n",
+ "some optimal transport approaches to solve it.\n",
+ "\n",
+ "Quantities such as optimal couplings, greater coupling coefficients and\n",
+ "transported samples are represented in order to give a visual understanding\n",
+ "of what the transport methods are doing.\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Authors: Remi Flamary <remi.flamary@unice.fr>\n",
+ "# Stanislas Chambon <stan.chambon@gmail.com>\n",
+ "#\n",
+ "# License: MIT License\n",
+ "\n",
+ "import matplotlib.pylab as pl\n",
+ "import ot"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Generate data\n",
+ "-------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "n_samples_source = 150\n",
+ "n_samples_target = 150\n",
+ "\n",
+ "Xs, ys = ot.datasets.get_data_classif('3gauss', n_samples_source)\n",
+ "Xt, yt = ot.datasets.get_data_classif('3gauss2', n_samples_target)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Transport source samples onto target samples\n",
+ "--------------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# unsupervised domain adaptation\n",
+ "ot_sinkhorn_un = ot.da.SinkhornTransport(reg_e=1e-1)\n",
+ "ot_sinkhorn_un.fit(Xs=Xs, Xt=Xt)\n",
+ "transp_Xs_sinkhorn_un = ot_sinkhorn_un.transform(Xs=Xs)\n",
+ "\n",
+ "# semi-supervised domain adaptation\n",
+ "ot_sinkhorn_semi = ot.da.SinkhornTransport(reg_e=1e-1)\n",
+ "ot_sinkhorn_semi.fit(Xs=Xs, Xt=Xt, ys=ys, yt=yt)\n",
+ "transp_Xs_sinkhorn_semi = ot_sinkhorn_semi.transform(Xs=Xs)\n",
+ "\n",
+ "# semi supervised DA uses available labaled target samples to modify the cost\n",
+ "# matrix involved in the OT problem. The cost of transporting a source sample\n",
+ "# of class A onto a target sample of class B != A is set to infinite, or a\n",
+ "# very large value\n",
+ "\n",
+ "# note that in the present case we consider that all the target samples are\n",
+ "# labeled. For daily applications, some target sample might not have labels,\n",
+ "# in this case the element of yt corresponding to these samples should be\n",
+ "# filled with -1.\n",
+ "\n",
+ "# Warning: we recall that -1 cannot be used as a class label"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Fig 1 : plots source and target samples + matrix of pairwise distance\n",
+ "---------------------------------------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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bt3+TXe/ezz4tM6WbVwSvx8MfPl/OG5df2WRxKKUiiz6kp5RSqkUSEdZVMn/y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7Rv6dgU9m22Sv3lZ40z6AVjm5vcMByvDV37B7/elcU3rw93KIpCitmslOYXEcn2/VpKlvW+szDa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\nAkV5lP87fkfnuv8EU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RTpJbEk3b4vHEMUAyO+z8/4Kx4oxiUDDGtXTVmyE0j/4Nc3ZYm8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t9BRd6j7SLEEX/S86ei6eD33B3St/rsWZlJYqYTyQbeu+Ua7I1+CvdvwcQJawCfOVxomelwwm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\nI5zfFdvfv6ztnPtRXDpuQH48DAkCx26bqIEsqsRccfteeRtKZi1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RkRyScyEk2bhPcgJO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jSLWO55pcOMgb4OJslR18/3Xrf7VHeIGOr/ESjNnRf0Gsbb2r/anh0DjhetugczRWmbETwz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\nQmCC\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f69e2066910>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "pl.figure(1, figsize=(10, 10))\n",
+ "pl.subplot(2, 2, 1)\n",
+ "pl.scatter(Xs[:, 0], Xs[:, 1], c=ys, marker='+', label='Source samples')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.legend(loc=0)\n",
+ "pl.title('Source samples')\n",
+ "\n",
+ "pl.subplot(2, 2, 2)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o', label='Target samples')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.legend(loc=0)\n",
+ "pl.title('Target samples')\n",
+ "\n",
+ "pl.subplot(2, 2, 3)\n",
+ "pl.imshow(ot_sinkhorn_un.cost_, interpolation='nearest')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Cost matrix - unsupervised DA')\n",
+ "\n",
+ "pl.subplot(2, 2, 4)\n",
+ "pl.imshow(ot_sinkhorn_semi.cost_, interpolation='nearest')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Cost matrix - semisupervised DA')\n",
+ "\n",
+ "pl.tight_layout()\n",
+ "\n",
+ "# the optimal coupling in the semi-supervised DA case will exhibit \" shape\n",
+ "# similar\" to the cost matrix, (block diagonal matrix)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Fig 2 : plots optimal couplings for the different methods\n",
+ "---------------------------------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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CBAd7AUQhEaepCTRb9XOxlOwCsgwWQKwU1vTGJPSMCrAzNm8OrVku53nxinze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\nrkJggg==\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f69dfe5ce90>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "pl.figure(2, figsize=(8, 4))\n",
+ "\n",
+ "pl.subplot(1, 2, 1)\n",
+ "pl.imshow(ot_sinkhorn_un.coupling_, interpolation='nearest')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Optimal coupling\\nUnsupervised DA')\n",
+ "\n",
+ "pl.subplot(1, 2, 2)\n",
+ "pl.imshow(ot_sinkhorn_semi.coupling_, interpolation='nearest')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "pl.title('Optimal coupling\\nSemi-supervised DA')\n",
+ "\n",
+ "pl.tight_layout()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Fig 3 : plot transported samples\n",
+ "--------------------------------\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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Xe2X87W/fg0LxvTnzuHzSZF7btZN3S/eSm+Imw+mkrsPLI+vWcPu8M3WCPI3m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\nHRXgKIqiKIrS7/x/4rlZk3fEE94AAAAASUVORK5CYII=\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x7f69dfc71890>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# display transported samples\n",
+ "pl.figure(4, figsize=(8, 4))\n",
+ "pl.subplot(1, 2, 1)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n",
+ " label='Target samples', alpha=0.5)\n",
+ "pl.scatter(transp_Xs_sinkhorn_un[:, 0], transp_Xs_sinkhorn_un[:, 1], c=ys,\n",
+ " marker='+', label='Transp samples', s=30)\n",
+ "pl.title('Transported samples\\nEmdTransport')\n",
+ "pl.legend(loc=0)\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "\n",
+ "pl.subplot(1, 2, 2)\n",
+ "pl.scatter(Xt[:, 0], Xt[:, 1], c=yt, marker='o',\n",
+ " label='Target samples', alpha=0.5)\n",
+ "pl.scatter(transp_Xs_sinkhorn_semi[:, 0], transp_Xs_sinkhorn_semi[:, 1], c=ys,\n",
+ " marker='+', label='Transp samples', s=30)\n",
+ "pl.title('Transported samples\\nSinkhornTransport')\n",
+ "pl.xticks([])\n",
+ "pl.yticks([])\n",
+ "\n",
+ "pl.tight_layout()\n",
+ "pl.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/ot/__init__.py b/ot/__init__.py
index a295e1b..a5df43d 100644
--- a/ot/__init__.py
+++ b/ot/__init__.py
@@ -29,7 +29,7 @@ from .gromov import gromov_wasserstein, gromov_wasserstein2
# utils functions
from .utils import dist, unif, tic, toc, toq
-__version__ = "0.3.1"
+__version__ = "0.4.0"
__all__ = ["emd", "emd2", "sinkhorn", "sinkhorn2", "utils", 'datasets',
'bregman', 'lp', 'plot', 'tic', 'toc', 'toq',