diff --git a/examples/statistics.py b/examples/statistics.py
index 65cafa1..1168807 100644
--- a/examples/statistics.py
+++ b/examples/statistics.py
@@ -1,69 +1,86 @@
 #!/usr/bin/env python3
 # @file
 # @section LICENSE
 #
 # Copyright (©) 2016-19 EPFL (École Polytechnique Fédérale de Lausanne),
 # Laboratory (LSMS - Laboratoire de Simulation en Mécanique des Solides)
 #
 # This program is free software: you can redistribute it and/or modify
 # it under the terms of the GNU Affero General Public License as published
 # by the Free Software Foundation, either version 3 of the License, or
 # (at your option) any later version.
 #
 # This program is distributed in the hope that it will be useful,
 # but WITHOUT ANY WARRANTY; without even the implied warranty of
 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 # GNU Affero General Public License for more details.
 #
 # You should have received a copy of the GNU Affero General Public License
 # along with this program.  If not, see <https://www.gnu.org/licenses/>.
 
+import os
+
 import numpy as np
 import matplotlib.pyplot as plt
+import tamaas as tm
 
 from matplotlib.colors import LogNorm
 
-import tamaas as tm
-
 # Initialize threads and fftw
 tm.initialize()
 tm.set_log_level(tm.LogLevel.info)  # Show progression of solver
 
 # Surface size
 n = 512
 
 # Surface generator
 sg = tm.SurfaceGeneratorFilter2D()
 sg.setSizes([n, n])
 sg.random_seed = 0
 
 # Spectrum
 spectrum = tm.Isopowerlaw2D()
 sg.setFilter(spectrum)
 
 # Parameters
 spectrum.q0 = 16
 spectrum.q1 = 16
 spectrum.q2 = 64
 spectrum.hurst = 0.8
 
 # Generating surface
 surface = sg.buildSurface()
 
 # Computing PSD and shifting for plot
 psd = tm.Statistics2D.computePowerSpectrum(surface)
 psd = np.fft.fftshift(psd, axes=0)
 
 plt.imshow(psd.real, norm=LogNorm())
 plt.gca().set_title('Power Spectrum Density')
 plt.gcf().tight_layout()
 
 # Computing autocorrelation and shifting for plot
 acf = tm.Statistics2D.computeAutocorrelation(surface)
 acf = np.fft.fftshift(acf)
 
 plt.figure()
 plt.imshow(acf)
 plt.gca().set_title('Autocorrelation')
 plt.gcf().tight_layout()
 plt.show()
+
+# Write the rough surface in paraview's VTK format
+try:
+    import uvw
+    try:
+        os.mkdir('paraview')
+    except FileExistsError as e:
+        pass
+    x = np.linspace(0, 1, n, endpoint=True)
+    y = x.copy()
+
+    with uvw.RectilinearGrid(os.path.join('paraview', 'surface.vtr'), (x, y)) as grid:
+        grid.addPointData(uvw.DataArray(surface, range(2), 'surface'))
+except ImportError as e:
+    print("uvw not installed, will not write VTK file")
+    pass