From 5e7c6ab04be3dc2035ca2a7f9deab3bb3bfb8faa Mon Sep 17 00:00:00 2001
From: Rémi Flamary <remi.flamary@gmail.com>
Date: Tue, 25 Jun 2019 14:43:39 +0200
Subject: doc add examples unbalanced

---
 docs/source/auto_examples/plot_UOT_1D.py | 76 ++++++++++++++++++++++++++++++++
 1 file changed, 76 insertions(+)
 create mode 100644 docs/source/auto_examples/plot_UOT_1D.py

(limited to 'docs/source/auto_examples/plot_UOT_1D.py')

diff --git a/docs/source/auto_examples/plot_UOT_1D.py b/docs/source/auto_examples/plot_UOT_1D.py
new file mode 100644
index 0000000..2ea8b05
--- /dev/null
+++ b/docs/source/auto_examples/plot_UOT_1D.py
@@ -0,0 +1,76 @@
+# -*- coding: utf-8 -*-
+"""
+===============================
+1D Unbalanced optimal transport
+===============================
+
+This example illustrates the computation of Unbalanced Optimal transport
+using a Kullback-Leibler relaxation.
+"""
+
+# Author: Hicham Janati <hicham.janati@inria.fr>
+#
+# License: MIT License
+
+import numpy as np
+import matplotlib.pylab as pl
+import ot
+import ot.plot
+from ot.datasets import make_1D_gauss as gauss
+
+##############################################################################
+# Generate data
+# -------------
+
+
+#%% 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)
+
+# make distributions unbalanced
+b *= 5.
+
+# loss matrix
+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))
+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')
+
+
+##############################################################################
+# Solve Unbalanced Sinkhorn
+# --------------
+
+
+# Sinkhorn
+
+epsilon = 0.1  # entropy parameter
+alpha = 1.  # Unbalanced KL relaxation parameter
+Gs = ot.unbalanced.sinkhorn_unbalanced(a, b, M, epsilon, alpha, verbose=True)
+
+pl.figure(4, figsize=(5, 5))
+ot.plot.plot1D_mat(a, b, Gs, 'UOT matrix Sinkhorn')
+
+pl.show()
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