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authorRémi Flamary <remi.flamary@gmail.com>2017-09-15 13:57:01 +0200
committerRémi Flamary <remi.flamary@gmail.com>2017-09-15 13:57:01 +0200
commitdd3546baf9c59733b2109a971293eba48d2eaed3 (patch)
treedbc9c5dd126eecf537acbe7d205b91250f2bdc9b /notebooks
parentbad3d95523d005a4fbf64dd009c716b9dd560fe3 (diff)
add all files for doc
Diffstat (limited to 'notebooks')
-rw-r--r--notebooks/plot_gromov.ipynb231
-rw-r--r--notebooks/plot_gromov_barycenter.ipynb368
-rw-r--r--notebooks/plot_otda_semi_supervised.ipynb294
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+{
+ "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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Sya6vrwdTOkexmzR0U5DL5WJycpLGxkZSUlJwOp2kpaVta51wHPH5fFE/GB0OB0VFRXR1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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_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\nFRT/SuX6uDdLzd8vFrqxuDHD88RjWRBX6gsLic903VEyLb17Wz9HoVphqHnxT74oXS/7+S9FxNMo\n8s++1DGYvXTx/IUeg+8FV1TNAjsW7Rk5ufTOLUwMKDaQnGPRc/FEiwKt5ObiBWQXKxQbfnelKO62\n8nJOJo5SjpC5TK9fkxAhQrzZERDkECFChAgRIkSIECFMvJoivShW1JMFIXRYa5piBRROOMQTv9Qd\nmkDReINaEFkg0pEApWBxDsXdbYFIVWYtArKbAammoL1DWUWkuKtIVPErlRYiupDvKfKQ3NA+Zjt7\n7pxkE4YTdKECGkLZOsoqWYF+jqNYKPLkCl5YIMLxGZOMmEgJEe+KsUoGdMaGl41TFCbGnPLYyd99\nR8c58ii6k1JbB7IPua0a0LMZCuVafb9kKNvV/1zbGdzWue8C6Z0u67Gznu9z8xTFX3OicSgYvECh\nEM5tHHkUZtHVPg2vaXstuLC19vSY6QqQalNUlcLNjY58KQrUpusovoEL3/ltY4ZA00UUBtUHukaO\nP9BzU4DnnZYfD+XvGqd67PBGiveXSmPvP3SnSL6h92V4vYHraF/aKOK82NQ26ideUi/9ld67a/9a\nUbHxLV0r7ce4/0DT++94ZG14Xeep8eef6fiA0l/7f3APv3osIiLL2VvunBhId39X1+2NRCXc2n/x\nlf7d1EzMYcubE6WHagSy+ZeQWRtg7E+0jw2YcmzveeTtf9z6j0RE5P4nmq1pbetz03tCF0FtK368\n686Jejpv1zuKomdfPBARkc6x9oWGEXcnd9059T1I3AExdiYzkCfbfK77UbbqZd6SXe1v6yWk+TBv\nNC1xboyRl+7Lv9a9Y3uRyaPzK6qHv6OIkljiXtfvEyggS41xCPekZHNdRIyR0A/f11NocmOMQri+\n8kNdf8kGTF9Y4HdFZi7u6ZzGMOWgoUv+EBJt+L7g5yIio996T0REmv8WSPL3VZIyegSU+IcfaVtY\nuyJeCo6FpNy3KVtX9JH5e7nv5wDH5Mi8MXvovjeYcRz4jFl68wbmgk59lYzp3oFUg0V5Mdojsp/t\n7V86NkSIEG9WBAQ5RIgQIUKECBEiRAgTr4aDnOfevKP8gfun++UMTi35ylbwvRrk7/LXfTYsG204\nrlxsTDLYjxGuDdSU6DM5ZqW2Pvsa1wP693Kv1P8F+GhWZq6KADjR/aoAvZGGS4DoSlzmY5Or59AX\ny48G19lJtRElhUmK40XH5rcOzUuILmMcnAMixxZxJRLa3ANXDpbFlEVLgPjWBr5vlPHKYF1LgwQi\nyzSkqA8Nwg/whVJZRJKJHDtzhq6f6+my9iWd6rFEmzOgxAk4zvOen+vaAPa2lLIDAsY+FUB2Wsd+\nPAOgv63jvHSd2iApjTfyp0gN66x2ARnDBRFQ2BPXLo+nBsvi5okeSxm0HMfkZTVDDSC3T/9AEeLR\nfV0z3V+tlfo0+MjLR21dA9r8XJHBxrFe9/nvKrJ3bVnfP/i+z6YsPdZxTFZ0zIM/AE91oVmHiy19\nf/U/ee7OuThQlPnoIyD972sfPnhLOZvHQ83ADG77Nfo//LP/WURE/tuv/gvt46Z+dgFzk95jGNPc\nMRxQ3LujP9Dn5u2v3xURkZMPltBHPffF7/l1vfyZztcCzTSAynef6zjP7+IepIaHva/Pyenb4IZj\nSmsDZD1wv7Lf9dmhlc+0Ly///rLM/zfjL/8dR5Flms2qZJossst9aPFSkX/ua8VPle+7uELGjvs3\ns1J5ZZ9jxiw2km3ORIQZMxh1sB4kRw1Gduj57I3/GzUXbAdZPd7R4pMvcT2/ZjOYirjxLes9JjfZ\n9dEYksSrsBHHvpmTg4w9mfbvpb2YWUhKhxI9x1/Hi7Zzz++bXZ99FDGZwRAhQryxERDkECFChAgR\nIkSIECFMvBoOci2VdGNDpFkxtTDW0+QHpltl7q7jh1GFwSAQRP+ip8pDTMlVA/rMNh0nTERScuNo\nOLAFBYId2KtSCL7nFSkWm8pDTJ7sl/rgOM5Let1oYFBng2CIiLOujnH9gqYMF55PTJSXVc5xv1Kh\nD1TY8rBZMc2xOqUQzHWB9gujGBKB552w3zwGc0xeZjzyqP/aOarUgaw2joHwDhU+y/p6veTCI5S1\nM/DrHiqauJQpUpiCw9iGYsB8xQvs104wHzSvgMpExL5wvOd+PI0ninjOr+m9pCJEvK9oU4FxNud+\nHTjkB2Pm/PU+pYqGIr/Tu+vulI19tAvecjTWc7pApuvnem7tyNuWUzkjGei5y0CZa0c6x/UOkLen\nBkHC2qtTveIE7e0rkrYuyoFPn3tkjRX0d/4PIOFrOifp/iH6AUvlP/Pw82xJ56v1s8d6zqEee+fw\nrh77TNu88YXnOpNz2cUz0N5TZLT9V0qiJlP3ePiOO2f5//q5iIjc/oU+24tryice3NBxrP7J5yIi\nsra24s755/F/KSIid/+l8qNpwpBvgsO/g7FPzR6Ce9p7rn2SrzX7tPyobDJUP73nzml+ouiiM/ah\nYgx4uJ3rin5TUUbE82mXr6kqQTSGsgFrA3Cd6ee3/DmffSIiItdn9+TJuVmH33FEjYbE997yii6s\nBxkY5ZWpPsPxvZv6Btb7HFbetN/O2qbeAGYwnU91zcRQ7aD5jKDNyDyD0R2t7aBSzcU92odDAQP3\nPFvzHOQhMgb9T/X+F02oZAx07hfXsQcc+b046lb24nPYYd9VznCOTFN8ZvZiouTYG2Pwsd37GIfl\nYUesscFYqeiRd8BbhqV7YRWOkPnJt3RNpscwMZkEo5AQId70CAhyiBAhQoQIESJEiBAmXgmCLEUh\nxXx+SQe5MAiys+PEr2+nd0uElcoU5vxIyrbUBc912rmVvyIeMWTl+aRsKep40QbpSIAs8BypcJ2r\nfRQRhxi7qChrROzHwnB2G6x+R1+AGDs0nWiZ5QBSp5MoOf5GFZ6gtd119sNEQVy7QHyBhNv7ExMJ\nYjvUD8Y4yO6NhwZpwzlsh8huQR4f+piavkY8n9qnSVxqg+e4ey0iUQN9AHfX9x/XISfQ6DqT1+14\ngmwf6DzvtUO0zdijKeYY5zSOFelKRkDeBv4cdywQcNp3U+s45v236wX3J6HVLtZXDoSSqL1FNdk3\nIsfTNWRCFvqaHOdFx/OwZ139d2tJj4nOlZOeL0Pd5AgWvEbhoKBNL/jq4w29xx1mbzBvo23/23oF\nz32O6yx62pfxmh7To3busleKGN/AvEHpQGCzPl/TvjROhqX3ddA6L5M1fa8HBJKWwlyzVGQREWnB\nZthZFNP6lzx9qFckZu0QKZxjrpMLoJi0Xsbnk1W/39XBwZ2vdaR48hpxh7yQaDz1zwSilMlyey/W\nJMZD/XIqv5SiwFg5f1jvRFipICFG0ziazEvnpEMq8UTltqZe9aN5WD4nPi7vs7Xjsga6iNcgd9bY\nfI4xvmSMZ9JoxRfIuFQRY7ePX+A5SHx2RSr7KfeSuLoXW11n/DvGXDAbUaoZCREixBsZ4SkNESJE\niBAhQoQIEcLEq0GQ40SiXlfyHrim+AEdG25wsQK+Lfl8bfK2oEsKhIeopIhItgSXqxxcwHMghy3w\nb5tUT/BoAnFU/lKn29u8rxyz9BRosUU1T1Ftva78x+KxcmojcBCLU0Xeiute+zU+gkIEUKtsFbzf\nYxzr+MseNZtv6DF0k6PmLJFKOcPErXp9VTnR9qin6SqkMfYcqFxy7Hl4OTiuBQEvhz4CBfzsgVQj\nwXywmpucUMeHPlFecXbudUEjpyKCC+0px9W5+hHJPvKcvNzcKz24KL/kfTEIC9Hz6IXyeLORIkZE\nyfKx8hWttjV1t5nVoHpJRB4psw4PnrpzYmhYU9OaDoT1RbnPueFHE1Fl+zGQ6wxtWOUTdwq4wDF4\n40WtPI8x1qNVWmGF/LO/SwRZ+9/a1TU1A703q/v5zGv8q7rBK21dMy9/W89ZB6/cqn90sc4GH+nz\ncvgPgSpmytVNJ9r+tX/i5y36I9Wb3f872ok5XOuGv6Fzvf5zPXfvRx6N+5/+0f8iIiL/3R//52hE\n/xz8QO/XddFnb7ri0eDGia6rnd+GOsrpXR37ErWn9f393zc8+bFee7JcxgJ6T3UODr+vc7D6uefJ\nU1GF+tf1M0Wh2wdLpb7u/pbfQ7rPVEv6xe+0ZPb1a3TSS2PJ1vsyW8WzgHVu+fmz63C0Q0ZmvqzH\nNnb12Z6vQpGnYVwmN4CWZnqvawe6NrM+3BM70HTPys+ziEh6huv0dD4n2Gfbe9yn/Dw2dnTtT+/o\nem/8tXLIs/vKJ2Z9w+i9TXdO6xn23Lq2P76h7baew3kVSPJiy6+/AbjO6UTfaxzpmkmRvYmxT82v\ne958bRfPNLNrVMDo6RxMtnQNtXp+LY039DpO3x1b/Oi2r4EJESLEmxkBQQ4RIkSIECFChAgRwkT4\nD3KIECFChAgRIkSIECZejVHIbKaGH3G5MCQ3RiGyA8vYSkEDZdfylyhiMMUlCdK92eQKExLblk3T\nV9uHDJZLfZP2YQ08IIuWQTjfmZpAgD5GEVD+qRfHL6rGHU+VlsFEJkXpC2MoEj9OS+dkeYVuwL4j\nPX/VeFwcll8urpgDzuWCY36KPv/mx9qfmb/++U3YK0OiagZLaRb8MQ3a2veFfYuWttd8qrJNww9V\n0qi5p8fMlmFAkPgxOEONvJyKjWGzzOuwIE9EZAr5KVIBGodIh0JajZJWWep/76VW0klEUhR9ze4q\nTYZFReyjiDckaR4jjXyu1zl6T+cmmWmf23um2AfXrKOY6Oyu9rXzQl/PuzqPzV1Pl4iRhp5hXJSV\nq+1oqvjkh9rHpV96+SvZ0XW0/FDn6Xye4DXmE/f/5G1PSRhv6XurP1UKCqlE/WeaVm5+o9a42Ydb\nfjyQrGriPje+1D6ufKJrf46U8cOfeYmzd2pKoensad9OQHmI9vBsI6/ce+nT/P/NF/9URETW9/U+\nTTf0ut1nNJvR8XUfeiv1vIG5PAAl4BePRUSkdkdpFEzvjzc8RanGlDkMaeqwgeZcbxR6bF4zdug7\neq+WGqAv0aAGBjs0Cqmf+rWTPFBTiq3le/Li4jLN4DuL0USKn3wm9aoNsjUKUddwKUDXckfCBCT5\nCgWnhu7WRHsZaEGVnevqLxK0z9noPdL5JP3M0Z7Mnh9t61pMv1DzpqILitqPP9XXkMas/ytvApJX\nChKbn4H2hD2GRlPy8LE7pv9z3Dvub3NdJ/zGKjDeyBh8LPidwe810t3gddXE3mVpZHwanRkLvofa\nn5b7HCJEiDcvAoIcIkSIECFChAgRIoSJV1OkJ6KFepVf8oWVC6qgmi4odVUrLn3uZOOMWYB+UP1/\nvZEWqiC7LCRzVqv55etItQCu0mcWY5TOifgeXhcVpJeFJxZV51iBvxTVc6rXtX2qoBZRXD63MAWR\n7pi0jFjzHMovRVOPdBAdI5KbjnAsUDkipZQrEhEhMEzh/BS2ywkMNmowF8gMOpeMF+V2OU2QSysq\nYvwiIskISCTsgBNI90XjGfoRlfpox+hkm4DcsG+C6yct/wjURmyfc6HXYWGas7oem6LQNC8fOyrL\nOqXoM/tq+5RMUKg6h9wVCktpX23ngIWPyRQ22GPaIEMGEPOYjj16mV7gTRQZ0iwlmZSlDnnvbT9j\n3NyECoE4NsbcJGY4LDJNMC/pha7zhPM54nU94jqawEBlWu5DOoGtODMNM7+uWWyaUv0u4zzROh1z\nP/dzQNMLbnUR5suNB69js1fFE9533lusa7wfz+NyP0S8/OIiL2tVftcR6XN/qTh0doUxRXUvprlR\nhoI72wYLcqsSmEkZVS1MZigiAs39B1J4lEGLOGf2OjQOMrbQIuL3Ufd94Z/bS987lI/j2zzniu+W\noppRrIyjKl2qn1X24Oo8mr2Y57sx8nuoek6IECHeuAgIcogQIUKECBEiRIgQJl6N1XQcS9xqejtX\nRGHNEYgg18qXpMi/k/KyNsswCSB/2CG5/PVP3q3hfDnpMSIAK8oxjBNIatEwwmI+xjQAACAASURB\nVEiCReTe0dwD7ca8Ho4toQlED6oILxEUItkWTSCajes4ebq8bAYSNcw8EgElKsJ5pNU0jUSMqUQM\n4wdKtcWUPCNqAWF9K9DfqAFlAZqZjMuviwZkns49t5dIWwEJuPoRZOwggVebgbvb9giRO5/GDFXE\nmGiwQapS3o85OLs0BgCnNp57owsXWHtufsBjT44G5esb1DkZAZW9wBoZ6d8mjEKIaqYn1ixF54nm\nIY2jeqmPnD/K9Yl4maikVS9dpzjTY5p7kJYykno57m8NHNrWMVDMgb7OmzAFOTbZlAxziznIYaFc\nP5uX5qR+YFBBSPIlc+U/N077GAfGDqvc2sDIVPH+w4Ckuwv5PchuxYf4vOmfn8mpPlPxmXI860Bw\nyT2u7UNu0JjZkLfePDIyiGLMa2hMY5BdGksQvaZxEO2kiWCXrJhhglE7x/pF1iHmMcg4tfb9HlJg\nfpJ57vjgryOiJJF4ealk/iIiUpi15I5tlO2oC5iqxDTEaPl9iM9/wj2d+x/3Ku5ldr8jYoxnLbuu\nNQrJIfbBIZDqrl9LlKKMeR2a6hCJ7YMXbg1kqmhsVUqS3xfmHNc3ri/2m8ZC+M4pzSM/w/xwP+Ux\nNIXKT7ysZbwMabllPEeQDA0IcogQb34EBDlEiBAhQoQIESJECBOvkIMce4MIhEVCc1Q/u2peVjAD\n4RWYLxTG8pV8t5z8SyANRcXWWYoruM5EqvFrPwc657nD/hd8voR2dxTNSq5pJXW+q8oBEWx2s5e7\n7pwE/SZCSXOJGAiHQyhOTv110AeHBoNnx77GUNOwaDDRCaf6UOEe50CGLCfZoeREvIHS0nhi9Hsf\niIjny4qIXGyjDwu9zqIBNA7823kHKhZHHlFZNPW9FaCoR9/X/ndf6jHTJX1/1vd9a55QuUHbJa84\nvSCirH8aRx45nEDh4GKbKhMwAtijSQaQIQPcObWMOTi7ULwY3uqVrn9+2z8CRcJzoegx1HOP3ycv\nVq/T2fPIIeepeartDm5oe90dPWbW1QEt9fw5GdDe4fV66Tqdx3rdwx/oGlq1/GhW5GMcCdQ3ErxO\nj/QZmfXX3Dk5C/UPVMWCqFU8IoJM0x6D8G+pQQgNfZqnQOCBEsu2ft7eNZMNYxtaFHPMMVQ/8jWg\nZ4bz3nhZ5phmPd0rUnDUF6t6j9MHRtFlWec4IY0cz1OKTAn3n+5Lw93G2iTnPIblMrM16YG2sYCJ\nj4hICpvwBAoYkcs2JKU2IzMF3M9qL0591uA1httDuN+1vXlFfqSKJA75HOoekt/Qe5vsYc+yds5Y\nDxmQ3WQNpkrM0GBvsZb3MVFffA8w45RxX3V8Yr8WplBJaX6J9t69q+c+fKbnbigiG33xyJ0TXdf9\nOiKCu6Pjizd0PLRAj3Z89ivbVwUXosFUunB9xbnM6oiIRCtLpes4MyOMOT+EypH5buG8UBmJyiG8\nByFChHhzIyDIIUKECBEiRIgQIUKYeDUIchQpWukQSyCGBlF2aDJRBRxTgM/nqnwttwxoMDm0rhq5\ngqKWOMiGWywiztI6JvpMy1V7HK/DPvIYIhvkwFpuMJFqoErO5phzcAXnmv92yDeRBiIR8yuqui+N\nEeeAz8zrFkbpg/xkhxqRb4n32y/xeuSRtnhWtj4tqBgBFYB5T69XP/Pn5HWMfU/RkN5zRX8aLxWR\nqp3r9WZLfjz1U+rSUlMWfNwLyiXgXpx6zmR7oshhtOiU2iD6l0z0fYvcOfUDzikQsDYVQoB2FonR\nGiZ9HOoFKZDWWQfXBdLbPPBznZMzC83kKNM5b0LftwEL3tpLz0tMYKtOE3Kem+zrMf2nOo/U6hUx\nGYpVRbFqQ4yL3G2sw/qZ54C2a1yj0LAFGpaA85wDRU0O/XWKAazfgXRRA5hBu/coW/dvHmq/I2gK\nt3dhU76JNYpxFT2/xqJsqXS9lFmOVVqnox9zo75ArvO5ouRuDxmVNa+tOEx8jMwUOLTck1gfwewQ\n15KIR1/jHrIlXEMT3GPsWc0TbyNfWHWCb9Mu/y4iinWvbVRVLMxejOwW95AIWsNUgSm6+nnetDxf\nPJfHQJer6G9RVqYQMfxdzMd8RdutM/uGY+264L0jL9nVSXDv5V7cM3NPZJ/1DMjEybfUu4iIJOi3\nWzs8FmoW5CCXvifySs0LuduYJ2YPc8P3joBeF32MZ8C1ZfadECFCvJEREOQQIUKECBEiRIgQIUy8\nGie9PJN8MLiEfOa2At2pOihSQzUGh+iQl1s33MSKViU5vI4/TCTZurKRCwduXEw3J3LliKQMzK98\nnE9nJyogEBXJ98tqE/bYqIIWOWQqKV9XRC6rfKANpx1KFMZogBbDrPSZ4xRSs5Qohq3cBvqRk9c9\nHqNdPSeBy5xVsUjAkU0u4DjYKTtN0YGspOAAVI7V2+mQ+spAiWd6PSK+Ip4z6zRrK+vAoelm3jjv\nrg+nZRUOp4yRGp3TId4jX/0CyCcQHfIrLdd5QbQXLn5ULWieYG4mHKfhuE7At4VqRQ1tuDnmOCyf\nE+obdSB2TinEaR3jWRgZZQWsp9F95X4Or+vc9uurOkVAi4fX/CM9XdX3+r8EtxTvj+5pGx2oP8yv\nr7hzai/wLCzrPB2/r+11vtnEHOm6OPnQnSLrf6rHTu5oXwa39ZjBHXDU/1oRvfEtz/NNfqBocHFN\n250vg2d+U//2vkEGo3k5m3IKt8BrP0W/N1dLn5+865+z9ELR5qyNtY+MSA3Pz/Sufk59ZxGRFOoN\nF/cU6aTudTrQ+06k9eQdP9c3l/XY8Vsrkr98jQoFi4XkR8ceJUbkRhXGZbL2lIfL/TR5OHNtiFSU\nIrB35dxb4FDqMmR8js0+VGSnpffqbq/CXjyqPCMi0iGPmMguMxpoI/4G3wVW9/3CClL7ZyXHudz3\ncqMFHVUQXGYNXN8W2FtsHQ0/43cVdeUx124vXhinTX4fHJ6iT6jFqXwXhAgR4s2LgCCHCBEiRIgQ\nIUKECGEi/Ac5RIgQIUKECBEiRAgTr8YopFaX5OYNVxDnGh+OLh1bVMXpW0zlg87Q8PQCmgbUH7HA\nDzQNFpcwbW3S1+wDU/jz6yhq2oWpBNL/edfIlS3pOelet9wu0/MoqnLFeyISkQpAmseibORBM4HY\n0BgK0iIM9UQ7U5ati0zfHK2DFATSTjhOmo4YOTlK51G+LjkflcYjSN0XJoVf41gxtykKuVjcxsId\nFiqJiJfQO4fc1iFS6CjkSXBuvOQLaljk5YT5OR7QQEghYSpSr6n9TDfXSn1yhWu5pkttoSJJN8W0\nbLEbHaBYLkfKtu1TnY2T8jyRKtI4QREdKBfxmU9XFyyIxH2g6QbpETHX9bExD0CBESkiESgXGeax\n/gL0g6ExCsEctJ6CnnGGNQvjjsWKrpnVU7/eKCfH62SY0/ZjvT+uQO4rcw5MDuKhPjfLD1AgiWc5\n2deCzP43b7tzFs9eiohIE89E/UjXXeMM9+Wbp9r3+XV3zuxLSHO9+FJERGp7oIxM9P34gcp6iUlx\nUzJr7Zd+PYmIyB7S/Ti2u+ONRNIH2rcan2HuO1ijtT5kFF/s+/bwPLZprz7E8zIo2yxvtG77vmE9\n10+nzkb9dUTRakjx0dsyWyqn8OtHppAR63vRKx8zX+K+is87niriJB3/Gns8TGCyFgoxaZc+8Xvk\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
+}