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iCAPs/packages/gspbox/graphs/gsp_david_sensor_network.m
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gsp_david_sensor_network.m
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function [G]=gsp_david_sensor_network(N)
%GSP_DAVID_SENSOR_NETWORK Initialize a sensor network
% Usage: G=gsp_david_sensor_network(N);
%
% Input parameters:
% N : Number of vertices (default 64)
% Output parameters:
% G : Graph structure.
%
% 'gsp_david_sensor_network(N)' initializes a graph structure containing
% the weighted adjacency matrix (G.W), the number of vertices (G.N), the
% plotting coordinates (G.coords), and the plotting coordinate limits
% (G.limits) of a random sensor network with N vertices. The
% sensors are placed randomly in the unit square, and edges are placed
% between any sensors within a fixed radius of each other. The edge
% weights are assigned via a thresholded Gaussian kernel. The sensor
% network will be connected for N=500 or N=64.
%
% Warning: this graph is not necessarly connected...
%
% Example:
%
% G = gsp_david_sensor_network(64);
% paramplot.show_edges = 1;
% gsp_plot_graph(G,paramplot);
%
%
% Url: http://lts2research.epfl.ch/gsp/doc/graphs/gsp_david_sensor_network.php
% Copyright (C) 2013-2016 Nathanael Perraudin, Johan Paratte, David I Shuman.
% This file is part of GSPbox version 0.7.0
%
% 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/>.
% If you use this toolbox please kindly cite
% N. Perraudin, J. Paratte, D. Shuman, V. Kalofolias, P. Vandergheynst,
% and D. K. Hammond. GSPBOX: A toolbox for signal processing on graphs.
% ArXiv e-prints, Aug. 2014.
% http://arxiv.org/abs/1408.5781
% Author : David I Shuman, Nathanael Perraudin
% Test: test_graphs
if nargin<1
N = 64;
end
% TODO: To be changed
randn('seed', 18);
rand('seed', 18);
G.N=N;
if N==64
load('david64.mat');
G.W = W;
G.N = N;
G.coords = coords;
elseif N==500
load('david500.mat');
G.W = W;
G.N = N;
G.coords = coords;
else
error('Use 64 / 500 nodes or use the function gsp_sensor')
% % Generate sensor locations
% Xcoords = rand(N,1);
% Ycoords = rand(N,1);
% G.coords = [Xcoords,Ycoords];
%
% % Create weighted adjancency matrix
% target_dist_cutoff = -.125*N/436.075+.2183;
% T = .6;
% s = sqrt(-target_dist_cutoff^2/(2*log(T)));
% d = gsp_distanz(G.coords');
% G.W = exp(-d.^2/(2*s^2));
% G.W(G.W<T) = 0; % Thresholding to have sparse matrix
% G.W=G.W-diag(diag(G.W));
% G.W=sparse(G.W);
end
G.plotting.limits = [0,1,0,1];
G = gsp_graph_default_parameters(G);
end
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