1 files changed, 0 insertions, 101 deletions
diff --git a/cython/example/alpha_rips_persistence_bottleneck_distance.py b/cython/example/alpha_rips_persistence_bottleneck_distance.py
deleted file mode 100755
index b51fa7a8..00000000
--- a/cython/example/alpha_rips_persistence_bottleneck_distance.py
+++ /dev/null
@@ -1,101 +0,0 @@
-#!/usr/bin/env python
-
-import gudhi
-import argparse
-import math
-
-"""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"
-
-parser = argparse.ArgumentParser(description='AlphaComplex and RipsComplex '
-                                 'persistence creation from points read in '
-                                 'a OFF file. Bottleneck distance computation'
-                                 ' on each dimension',
-                                 epilog='Example: '
-                                 'example/alpha_rips_persistence_bottleneck_distance.py '
-                                 '-f ../data/points/tore3D_1307.off -t 0.15 -d 3')
-parser.add_argument("-f", "--file", type=str, required=True)
-parser.add_argument("-t", "--threshold", type=float, default=0.5)
-parser.add_argument("-d", "--max_dimension", type=int, default=1)
-
-args = parser.parse_args()
-with open(args.file, 'r') as f:
-    first_line = f.readline()
-    if (first_line == 'OFF\n') or (first_line == 'nOFF\n'):
-        point_cloud = gudhi.read_off(off_file=args.file)
-        print("#####################################################################")
-        print("RipsComplex creation from points read in a OFF file")
-
-        message = "RipsComplex with max_edge_length=" + repr(args.threshold)
-        print(message)
-
-        rips_complex = gudhi.RipsComplex(points=point_cloud,
-                                         max_edge_length=args.threshold)
-
-        rips_stree = rips_complex.create_simplex_tree(max_dimension=args.max_dimension)
-
-        message = "Number of simplices=" + repr(rips_stree.num_simplices())
-        print(message)
-
-        rips_diag = rips_stree.persistence()
-
-        print("#####################################################################")
-        print("AlphaComplex creation from points read in a OFF file")
-
-        message = "AlphaComplex with max_edge_length=" + repr(args.threshold)
-        print(message)
-
-        alpha_complex = gudhi.AlphaComplex(points=point_cloud)
-        alpha_stree = alpha_complex.create_simplex_tree(max_alpha_square=(args.threshold * args.threshold))
-
-        message = "Number of simplices=" + repr(alpha_stree.num_simplices())
-        print(message)
-
-        alpha_diag = alpha_stree.persistence()
-
-        max_b_distance = 0.0
-        for dim in range(args.max_dimension):
-            # Alpha persistence values needs to be transform because filtration
-            # values are alpha square values
-            funcs = [math.sqrt, math.sqrt]
-            alpha_intervals = []
-            for interval in alpha_stree.persistence_intervals_in_dimension(dim):
-                alpha_intervals.append(map(lambda func,value: func(value), funcs, interval))
-
-            rips_intervals = rips_stree.persistence_intervals_in_dimension(dim)
-            bottleneck_distance = gudhi.bottleneck_distance(rips_intervals, alpha_intervals)
-            message = "In dimension " + repr(dim) + ", bottleneck distance = " + repr(bottleneck_distance)
-            print(message)
-            max_b_distance = max(bottleneck_distance, max_b_distance)
-
-        print("================================================================================")
-        message = "Bottleneck distance is " + repr(max_b_distance)
-        print(message)
-
-    else:
-        print(args.file, "is not a valid OFF file")
-
-    f.close()