diff options
Diffstat (limited to 'src/Nerve_GIC/example/KeplerMapperVisuFromTxtFile.py')
-rwxr-xr-x | src/Nerve_GIC/example/KeplerMapperVisuFromTxtFile.py | 70 |
1 files changed, 70 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..406264ba --- /dev/null +++ b/src/Nerve_GIC/example/KeplerMapperVisuFromTxtFile.py @@ -0,0 +1,70 @@ +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) |