1 files changed, 0 insertions, 72 deletions
diff --git a/src/Nerve_GIC/example/KeplerMapperVisuFromTxtFile.py b/src/Nerve_GIC/example/KeplerMapperVisuFromTxtFile.py
deleted file mode 100755
index d2897774..00000000
--- a/src/Nerve_GIC/example/KeplerMapperVisuFromTxtFile.py
+++ /dev/null
@@ -1,72 +0,0 @@
-#!/usr/bin/env python
-
-import km
-import numpy as np
-from collections import defaultdict
-
-"""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):       Mathieu Carriere
-
-   Copyright (C) 2017 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__ = "Mathieu Carriere"
-__copyright__ = "Copyright (C) 2017 INRIA"
-__license__ = "GPL v3"
-
-network = {}
-mapper = km.KeplerMapper(verbose=0)
-data = np.zeros((3,3))
-projected_data = mapper.fit_transform( data, projection="sum", scaler=None )
-
-f = open('SC.txt','r')
-nodes = defaultdict(list)
-links = defaultdict(list)
-custom = defaultdict(list)
-
-dat = f.readline()
-lens = f.readline()
-color = f.readline();
-param = [float(i) for i in f.readline().split(" ")]
-
-nums = [int(i) for i in f.readline().split(" ")]
-num_nodes = nums[0]
-num_edges = nums[1]
-
-for i in range(0,num_nodes):
-	point = [float(j) for j in f.readline().split(" ")]
-	nodes[  str(int(point[0]))  ] = [  int(point[0]), point[1], int(point[2])  ]
-	links[  str(int(point[0]))  ] = []
-	custom[  int(point[0])  ] = point[1]
-
-m = min([custom[i] for i in range(0,num_nodes)])
-M = max([custom[i] for i in range(0,num_nodes)])
-
-for i in range(0,num_edges):
-	edge = [int(j) for j in f.readline().split(" ")]	
-	links[  str(edge[0])  ].append(  str(edge[1])  )	
-	links[  str(edge[1])  ].append(  str(edge[0])  )
-
-network["nodes"] = nodes
-network["links"] = links
-network["meta"] = lens
-
-mapper.visualize(network, color_function = color, path_html="SC.html", title=dat,
-graph_link_distance=30, graph_gravity=0.1, graph_charge=-120, custom_tooltips=custom, width_html=0, 
-height_html=0, show_tooltips=True, show_title=True, show_meta=True, res=param[0],gain=param[1], minimum=m,maximum=M)