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authorRémi Flamary <remi.flamary@gmail.com>2018-05-30 09:58:51 +0200
committerRémi Flamary <remi.flamary@gmail.com>2018-05-30 09:58:51 +0200
commitb5e45bbc83fd8cd8c1634a78f2f983d1cf28af73 (patch)
tree965b01f0313ff5ac2c2013239adda48f767ba992 /docs/source/auto_examples/plot_OT_1D.ipynb
parent90e42f32bdf0dd06667edaf172c51f4d4fce2c8b (diff)
update examples and notebooks
Diffstat (limited to 'docs/source/auto_examples/plot_OT_1D.ipynb')
-rw-r--r--docs/source/auto_examples/plot_OT_1D.ipynb68
1 files changed, 34 insertions, 34 deletions
diff --git a/docs/source/auto_examples/plot_OT_1D.ipynb b/docs/source/auto_examples/plot_OT_1D.ipynb
index 649efa6..bd0439e 100644
--- a/docs/source/auto_examples/plot_OT_1D.ipynb
+++ b/docs/source/auto_examples/plot_OT_1D.ipynb
@@ -1,6 +1,7 @@
{
"cells": [
{
+ "cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
@@ -8,35 +9,35 @@
"outputs": [],
"source": [
"%matplotlib inline"
- ],
- "cell_type": "code"
+ ]
},
{
+ "cell_type": "markdown",
"metadata": {},
"source": [
"\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"
+ ]
},
{
+ "cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
- "# Author: Remi Flamary <remi.flamary@unice.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 get_1D_gauss as gauss"
- ],
- "cell_type": "code"
+ "# Author: Remi Flamary <remi.flamary@unice.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": "markdown"
+ ]
},
{
+ "cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
@@ -44,17 +45,17 @@
"outputs": [],
"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()"
- ],
- "cell_type": "code"
+ ]
},
{
+ "cell_type": "markdown",
"metadata": {},
"source": [
"Plot distributions and loss matrix\n----------------------------------\n\n"
- ],
- "cell_type": "markdown"
+ ]
},
{
+ "cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
@@ -62,17 +63,17 @@
"outputs": [],
"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')"
- ],
- "cell_type": "code"
+ ]
},
{
+ "cell_type": "markdown",
"metadata": {},
"source": [
"Solve EMD\n---------\n\n"
- ],
- "cell_type": "markdown"
+ ]
},
{
+ "cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
@@ -80,17 +81,17 @@
"outputs": [],
"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')"
- ],
- "cell_type": "code"
+ ]
},
{
+ "cell_type": "markdown",
"metadata": {},
"source": [
"Solve Sinkhorn\n--------------\n\n"
- ],
- "cell_type": "markdown"
+ ]
},
{
+ "cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
@@ -98,29 +99,28 @@
"outputs": [],
"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()"
- ],
- "cell_type": "code"
+ ]
}
],
"metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
"language_info": {
- "name": "python",
"codemirror_mode": {
"name": "ipython",
"version": 3
},
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
"nbconvert_exporter": "python",
- "version": "3.5.2",
"pygments_lexer": "ipython3",
- "file_extension": ".py",
- "mimetype": "text/x-python"
- },
- "kernelspec": {
- "display_name": "Python 3",
- "name": "python3",
- "language": "python"
+ "version": "3.6.5"
}
},
- "nbformat_minor": 0,
- "nbformat": 4
+ "nbformat": 4,
+ "nbformat_minor": 0
} \ No newline at end of file