1 files changed, 72 insertions, 0 deletions
diff --git a/src/Nerve_GIC/example/KeplerMapperVisuFromTxtFile.py b/src/Nerve_GIC/example/KeplerMapperVisuFromTxtFile.py
new file mode 100755
index 00000000..d2897774
--- /dev/null
+++ b/src/Nerve_GIC/example/KeplerMapperVisuFromTxtFile.py
@@ -0,0 +1,72 @@
+#!/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)