fuzzyARTMAP_examplesWrapper(varargin)

function [a, b, c] = fuzzyARTMAP_examplesWrapper(varargin)

if nargin==0
    init_vals.epochs=1;
    init_vals.rho=0;
    init_vals.alpha=10^(-8);
    init_vals.beta=.1;
    init_vals.epsilon=0;
    init_vals.gamma=10^-7;
    init_vals.plot_steps=0;
    init_vals.datasrc=6;

    disp('Running Fuzzy ARTMAP with following values on Circle-in-Square dataset');



    disp('1) Circle in Square benchmark (sparse)')
    disp('2) Circle in Square benchmark (dense)')
    disp('3) Stripes benchmark (sparse)')
    disp('4) Stripes benchmark (dense)')
    disp('5) Checkerboard benchmark (sparse)')
    disp('6) Checkerboard benchmark (dense)')
    disp('7) Boston Benchmark: test on stripe 1')
    disp('8) Boston Benchmark: test on stripe 2')
    disp('9) Boston Benchmark: test on stripe 3')
    disp('10) Boston Benchmark: test on stripe 4')
    disp('11) Movie Genre Benchmark')
    disp('Data Source No.')
    disp(init_vals.datasrc);
    disp('No. Epochs')
    disp(init_vals.epochs);
    disp('Baseline vigilance')
    disp(init_vals.rho);
    disp('alpha')
    disp(init_vals.alpha);
    disp('beta')
    disp(init_vals.beta);
    disp('gamma')
    disp(init_vals.gamma);
    disp('epsilon')
    disp(init_vals.epsilon);
    disp('Plot each training step 1|Yes 0|No')
    disp(init_vals.plot_steps);

    tmp_value=input('Train and test Fuzzy ARTMAP with current values? y | n ','s');
    
    if (strmatch(lower(tmp_value),'yn')==0)
        error('Input value must be "y" or "n"')
    end



    if (tmp_value=='n')
        if (strmatch(lower(tmp_value),'yn')==0)
            error('Input value must be "y" or "n"')
        end
        tmp_value_b=input('Only change dataset? y | n ','s');
        if (strmatch(lower(tmp_value_b),'yn')==0)
            error('Input value must be "y" or "n"')
        end
        if (tmp_value_b=='n')
            init_vals.epochs=input('Number of epochs? ');
            init_vals.rho=input('Baseline vigilance? ');
            init_vals.alpha=input('alpha value? (suggested value: 10^-8) ');
            init_vals.beta=input('beta value? (suggested value: 10^-1 fast learning) ');
            init_vals.gamma=input('gamma value? (suggested value: 10^-8) ');
            init_vals.epsilon=input('epsilon value? (suggested value: 0) ');
            init_vals.plot_steps=input('Plot each training step? 0 | No, 1 | Yes) ');
        end



        disp('1) Circle in Square benchmark (sparse)')
        disp('2) Circle in Square benchmark (dense)')
        disp('3) Stripes benchmark (sparse)')
        disp('4) Stripes benchmark (dense)')
        disp('5) Checkerboard benchmark (sparse)')
        disp('6) Checkerboard benchmark (dense)')
        disp('7) Boston Benchmark: test on stripe 1')
        disp('8) Boston Benchmark: test on stripe 2')
        disp('9) Boston Benchmark: test on stripe 3')
        disp('10) Boston Benchmark: test on stripe 4')
        disp('11) Movie Genre Benchmark')
        init_vals.datasrc=input('Dataset to train and test on? (1-12) ');


    end
    
    clear tmp_value tmp_value_b;

else
    init_vals=varargin{1};
    disp(init_vals)

end

gcf;
%imshow('figure_CIS.jpg')
%openfig('figure_cis.fig','reuse')
fuzzyARTMAP_examples;