Add Windows and CGAL_HEADER_ONLY cythonization support

Add OFF reader interfaces (required by Euclidean witness complex)
Add Euclidean_witness_complex



git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/ST_cythonize@2186 636b058d-ea47-450e-bf9e-a15bfbe3eedb

Former-commit-id: 4d780f05c3409bea47a81e4377dbaf509b9e718c

1 files changed, 39 insertions, 0 deletions

diff --git a/src/cython/test/test_euclidean_witness_complex.py b/src/cython/test/test_euclidean_witness_complex.py
new file mode 100755
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--- /dev/null
+++ b/src/cython/test/test_euclidean_witness_complex.py
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+import gudhi
+
+"""This file is part of the Gudhi Library. The Gudhi library
+   (Geometric Understanding in Higher Dimensions) is a generic C++
+   library for computational topology.
+
+   Author(s):       Vincent Rouvreau
+
+   Copyright (C) 2016 INRIA
+
+   This program is free software: you can redistribute it and/or modify
+   it under the terms of the GNU 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 General Public License for more details.
+
+   You should have received a copy of the GNU General Public License
+   along with this program.  If not, see <http://www.gnu.org/licenses/>.
+"""
+
+__author__ = "Vincent Rouvreau"
+__copyright__ = "Copyright (C) 2016 INRIA"
+__license__ = "GPL v3"
+
+
+def test_empty_euclidean_witness_complex():
+    euclidean_witness = gudhi.EuclideanWitnessComplex()
+    assert euclidean_witness.__is_defined() == False
+
+def test_witness_complex():
+    point_cloud = [[1.0, 1.0], [7.0, 0.0], [4.0, 6.0], [9.0, 6.0],
+        [0.0, 14.0], [2.0, 19.0], [9.0, 17.0]]
+    landmarks = gudhi.pick_n_random_points(points=point_cloud,nb_points=3)
+    euclidean_witness_complex = gudhi.EuclideanWitnessComplex(landmarks=landmarks, witnesses = point_cloud)
+    simplex_tree = euclidean_witness_complex.create_simplex_tree(max_alpha_square=4.1)