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diff --git a/examples/domain-adaptation/plot_otda_linear_mapping.py b/examples/domain-adaptation/plot_otda_linear_mapping.py
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+++ b/examples/domain-adaptation/plot_otda_linear_mapping.py
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+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+============================
+Linear OT mapping estimation
+============================
+
+
+"""
+
+# Author: Remi Flamary <remi.flamary@unice.fr>
+#
+# License: MIT License
+
+# sphinx_gallery_thumbnail_number = 2
+
+import numpy as np
+import pylab as pl
+import ot
+
+##############################################################################
+# Generate data
+# -------------
+
+n = 1000
+d = 2
+sigma = .1
+
+# source samples
+angles = np.random.rand(n, 1) * 2 * np.pi
+xs = np.concatenate((np.sin(angles), np.cos(angles)),
+                    axis=1) + sigma * np.random.randn(n, 2)
+xs[:n // 2, 1] += 2
+
+
+# target samples
+anglet = np.random.rand(n, 1) * 2 * np.pi
+xt = np.concatenate((np.sin(anglet), np.cos(anglet)),
+                    axis=1) + sigma * np.random.randn(n, 2)
+xt[:n // 2, 1] += 2
+
+
+A = np.array([[1.5, .7], [.7, 1.5]])
+b = np.array([[4, 2]])
+xt = xt.dot(A) + b
+
+##############################################################################
+# Plot data
+# ---------
+
+pl.figure(1, (5, 5))
+pl.plot(xs[:, 0], xs[:, 1], '+')
+pl.plot(xt[:, 0], xt[:, 1], 'o')
+
+
+##############################################################################
+# Estimate linear mapping and transport
+# -------------------------------------
+
+Ae, be = ot.da.OT_mapping_linear(xs, xt)
+
+xst = xs.dot(Ae) + be
+
+
+##############################################################################
+# Plot transported samples
+# ------------------------
+
+pl.figure(1, (5, 5))
+pl.clf()
+pl.plot(xs[:, 0], xs[:, 1], '+')
+pl.plot(xt[:, 0], xt[:, 1], 'o')
+pl.plot(xst[:, 0], xst[:, 1], '+')
+
+pl.show()
+
+##############################################################################
+# Load image data
+# ---------------
+
+
+def im2mat(I):
+    """Converts and image to matrix (one pixel per line)"""
+    return I.reshape((I.shape[0] * I.shape[1], I.shape[2]))
+
+
+def mat2im(X, shape):
+    """Converts back a matrix to an image"""
+    return X.reshape(shape)
+
+
+def minmax(I):
+    return np.clip(I, 0, 1)
+
+
+# Loading images
+I1 = pl.imread('../../data/ocean_day.jpg').astype(np.float64) / 256
+I2 = pl.imread('../../data/ocean_sunset.jpg').astype(np.float64) / 256
+
+
+X1 = im2mat(I1)
+X2 = im2mat(I2)
+
+##############################################################################
+# Estimate mapping and adapt
+# ----------------------------
+
+mapping = ot.da.LinearTransport()
+
+mapping.fit(Xs=X1, Xt=X2)
+
+
+xst = mapping.transform(Xs=X1)
+xts = mapping.inverse_transform(Xt=X2)
+
+I1t = minmax(mat2im(xst, I1.shape))
+I2t = minmax(mat2im(xts, I2.shape))
+
+# %%
+
+
+##############################################################################
+# Plot transformed images
+# -----------------------
+
+pl.figure(2, figsize=(10, 7))
+
+pl.subplot(2, 2, 1)
+pl.imshow(I1)
+pl.axis('off')
+pl.title('Im. 1')
+
+pl.subplot(2, 2, 2)
+pl.imshow(I2)
+pl.axis('off')
+pl.title('Im. 2')
+
+pl.subplot(2, 2, 3)
+pl.imshow(I1t)
+pl.axis('off')
+pl.title('Mapping Im. 1')
+
+pl.subplot(2, 2, 4)
+pl.imshow(I2t)
+pl.axis('off')
+pl.title('Inverse mapping Im. 2')