Add interfaces with pandas, numpy and matplotlib

new examples : rips_persistence_diagram.py, random_cubical_complex_example & alpha_complex_from_file_example
new data files for alpha_complex_from_file_example



git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/ST_cythonize@1235 636b058d-ea47-450e-bf9e-a15bfbe3eedb

Former-commit-id: 901cc5eb791633f7bfcd86c0b7b8733cb6eb054c

1 files changed, 63 insertions, 0 deletions

diff --git a/src/cython/example/alpha_complex_from_file_example.py b/src/cython/example/alpha_complex_from_file_example.py
new file mode 100755
index 00000000..9ceb82b1
--- /dev/null
+++ b/src/cython/example/alpha_complex_from_file_example.py
@@ -0,0 +1,63 @@
+#!/usr/bin/env python
+
+import gudhi
+import pandas
+import argparse
+
+"""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 Saclay (France)
+
+   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 Saclay (France)"
+__license__ = "GPL v3"
+
+print("#####################################################################")
+print("AlphaComplex creation from points read in a file")
+
+parser = argparse.ArgumentParser(description='AlphaComplex creation from '
+                                 'points read in a file.',
+                                 epilog='Example: '
+                                 'example/alpha_complex_from_file_example.py '
+                                 'data/500_random_points_on_3D_Torus.csv '
+                                 '- Constructs a alpha complex with the '
+                                 'points from the given file. File format '
+                                 'is X1, X2, ..., Xn')
+parser.add_argument('file', type=argparse.FileType('r'))
+args = parser.parse_args()
+
+points = pandas.read_csv(args.file, header=None)
+
+alpha_complex = gudhi.AlphaComplex(points=points.values,
+                                   max_alpha_square=0.5)
+
+print("dimension=", alpha_complex.dimension())
+print("point[0]=", alpha_complex.get_point(0))
+print("point[5]=", alpha_complex.get_point(5))
+
+alpha_complex.initialize_filtration()
+diag = alpha_complex.persistence(homology_coeff_field=2, min_persistence=0.1)
+
+print("betti_numbers()=")
+print(alpha_complex.betti_numbers())
+
+print("star([0])=", alpha_complex.get_star_tree([0]))
+print("coface([0], 1)=", alpha_complex.get_coface_tree([0], 1))