From 6ac8d405f16832e671c432d7b03ce3da38f8fedc Mon Sep 17 00:00:00 2001
From: Rémi Flamary <remi.flamary@gmail.com>
Date: Mon, 20 Apr 2020 16:01:15 +0200
Subject: add all pages in documentation

---
 docs/source/auto_examples/plot_screenkhorn_1D.py | 68 ++++++++++++++++++++++++
 1 file changed, 68 insertions(+)
 create mode 100644 docs/source/auto_examples/plot_screenkhorn_1D.py

(limited to 'docs/source/auto_examples/plot_screenkhorn_1D.py')

diff --git a/docs/source/auto_examples/plot_screenkhorn_1D.py b/docs/source/auto_examples/plot_screenkhorn_1D.py
new file mode 100644
index 0000000..840ead8
--- /dev/null
+++ b/docs/source/auto_examples/plot_screenkhorn_1D.py
@@ -0,0 +1,68 @@
+# -*- coding: utf-8 -*-
+"""
+===============================
+1D Screened optimal transport
+===============================
+
+This example illustrates the computation of Screenkhorn:
+Screening Sinkhorn Algorithm for Optimal transport.
+"""
+
+# Author: Mokhtar Z. Alaya <mokhtarzahdi.alaya@gmail.com>
+#
+# License: MIT License
+
+import numpy as np
+import matplotlib.pylab as pl
+import ot.plot
+from ot.datasets import make_1D_gauss as gauss
+from ot.bregman import screenkhorn
+
+##############################################################################
+# 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)
+
+# 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 Screenkhorn
+# -----------------------
+
+# Screenkhorn
+lambd = 2e-03  # entropy parameter
+ns_budget = 30  # budget number of points to be keeped in the source distribution
+nt_budget = 30  # budget number of points to be keeped in the target distribution
+
+G_screen = screenkhorn(a, b, M, lambd, ns_budget, nt_budget, uniform=False, restricted=True, verbose=True)
+pl.figure(4, figsize=(5, 5))
+ot.plot.plot1D_mat(a, b, G_screen, 'OT matrix Screenkhorn')
+pl.show()
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