From 28b549ef3ef93c01462cd811d6e55c36ae5a76a2 Mon Sep 17 00:00:00 2001
From: Hicham Janati <hicham.janati@inria.fr>
Date: Wed, 12 Jun 2019 15:50:25 +0200
Subject: add test and example of UOT

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

(limited to 'examples')

diff --git a/examples/plot_UOT_1D.py b/examples/plot_UOT_1D.py
new file mode 100644
index 0000000..1b1dd9c
--- /dev/null
+++ b/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
+
+lambd = 0.1
+alpha = 1.
+Gs = ot.unbalanced.sinkhorn_unbalanced(a, b, M, lambd, 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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