function [ index ] = gsp_good_graph_index( G, X, param )
%GSP_GOOD_GRAPH_INDEX Index testing how well a given graph G, matches some data X
% Usage: gsp_good_graph(G, X);
%
% Input parameters:
% G : the graph
% X : a data matrix
% param : structure of optional parameters
% Output parameters:
% index : the computed index
%
% A wrapper function with which one may test how well a given graph G,
% matches some data X.
%
% Example:
% G = gsp_2dgrid(16);
% X = pinv(full(G.L)) randn(G.N, G.N);
% param.verbose = 1;
% param.index = 'tcer';
% index = gsp_good_graph_index(G, X, param)
% param.index = 'stationarity';
% index = gsp_good_graph_index(G, X, param)
%
% Optional paramaters
% -------------------
%
% param.index*: 'tcer' or 'stationarity' (default 'tcer').
%
% See also: gsp_learn_tcer, gsp_stationarity_ratio
%
% Url: https://epfl-lts2.github.io/gspbox-html/doc/utils/gsp_good_graph_index.html
% Copyright (C) 2013-2016 Nathanael Perraudin, Johan Paratte, David I Shuman.
% This file is part of GSPbox version 0.7.5
%
% 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 : Andreas Loukas
% Date : 15 Nov 2016
% Handle input
if nargin < 3, param = struct(); end
if not(isfield(param, 'index')); param.index = 'tcer'; end;
switch param.index,
case 'tcer',
index = gsp_learn_tcer(G, X, param);
case 'stationarity'
index = gsp_stationarity_ratio(G, X*X', param);
otherwise,
error('uknown index.');
end
end