diff options
author | RĂ©mi Flamary <remi.flamary@gmail.com> | 2020-04-21 17:48:37 +0200 |
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committer | GitHub <noreply@github.com> | 2020-04-21 17:48:37 +0200 |
commit | a303cc6b483d3cd958c399621e22e40574bcbbc8 (patch) | |
tree | dea049cb692020462da8f00d9e117f93b839bb55 /docs/source/auto_examples/plot_UOT_1D.ipynb | |
parent | 0b2d808aaebb1cab60a272ea7901d5f77df43a9f (diff) |
[MRG] Actually run sphinx-gallery (#146)
* generate gallery
* remove mock
* add sklearn to requirermnt?txt for example
* remove latex from fgw example
* add networks for graph example
* remove all
* add requirement.txt rtd
* rtd debug
* update readme
* eradthedoc with redirection
* add conf rtd
Diffstat (limited to 'docs/source/auto_examples/plot_UOT_1D.ipynb')
-rw-r--r-- | docs/source/auto_examples/plot_UOT_1D.ipynb | 108 |
1 files changed, 0 insertions, 108 deletions
diff --git a/docs/source/auto_examples/plot_UOT_1D.ipynb b/docs/source/auto_examples/plot_UOT_1D.ipynb deleted file mode 100644 index 640e398..0000000 --- a/docs/source/auto_examples/plot_UOT_1D.ipynb +++ /dev/null @@ -1,108 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "%matplotlib inline" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n# 1D Unbalanced optimal transport\n\n\nThis example illustrates the computation of Unbalanced Optimal transport\nusing a Kullback-Leibler relaxation.\n\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "# Author: Hicham Janati <hicham.janati@inria.fr>\n#\n# License: MIT License\n\nimport numpy as np\nimport matplotlib.pylab as pl\nimport ot\nimport ot.plot\nfrom ot.datasets import make_1D_gauss as gauss" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Generate data\n-------------\n\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "n = 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# make distributions unbalanced\nb *= 5.\n\n# loss matrix\nM = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)))\nM /= M.max()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Plot distributions and loss matrix\n----------------------------------\n\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "pl.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')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Solve Unbalanced Sinkhorn\n--------------\n\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "# Sinkhorn\n\nepsilon = 0.1 # entropy parameter\nalpha = 1. # Unbalanced KL relaxation parameter\nGs = ot.unbalanced.sinkhorn_unbalanced(a, b, M, epsilon, alpha, verbose=True)\n\npl.figure(4, figsize=(5, 5))\not.plot.plot1D_mat(a, b, Gs, 'UOT matrix Sinkhorn')\n\npl.show()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.9" - } - }, - "nbformat": 4, - "nbformat_minor": 0 -}
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