process_data.m

implement basic routines in Matlab and Octave (currently using Matlab R13) for simulating adaptive b

load datafile-20040918T114013.mat

maxindex = max(datamatrix(:,1));
datamatrix_sorted = sortrows(datamatrix, [2 1]);
datamatrix_sorted(find(datamatrix_sorted(:,1) <= 0),:) = [];
    % datamatrix_sorted is now sorted by Nsamples values

NsamplesArray = unique(datamatrix_sorted(:,2)).'; Nsamples(find(Nsamples <= 0)) = [];

for Nsamples = NsamplesArray
    disp(['Now processing data with Nsamples = ', num2str(Nsamples)])
    datamatrix_conditioned = datamatrix_sorted(find(datamatrix_sorted(:,2)==Nsamples), :);

%    bad_indicies = find((datamatrix(:, 2) > (maxnumTestRuns-3)) + (datamatrix(:, 2) < 0));
%    datamatrix_conditioned(bad_indicies, :) = []; % Get rid of "outliers"

    ideal_minus_cvmov = datamatrix_conditioned(:, 3) - datamatrix_conditioned(:, 4);
    ideal_minus_cvmov_p = datamatrix_conditioned(:, 3) - datamatrix_conditioned(:, 5);
    ideal_minus_jdiv = datamatrix_conditioned(:, 3) - datamatrix_conditioned(:, 6);

    figure
    hist(ideal_minus_cvmov, 100)
    xlabel('Difference in number of iterations');
    ylabel('Count');
    title(['Histogram of ideal-estimated number of iterations for CVMOV algorithm, using Nsamples = ', num2str(Nsamples)])
   
    figure
    hist(ideal_minus_cvmov_p, 100)
    xlabel('Difference in number of iterations');
    ylabel('Count');
    title(['Histogram of ideal-estimated (corrvect) number of iterations for CVMOV algorithm, using Nsamples = ', num2str(Nsamples)])
    
    figure
    hist(datamatrix_conditioned(:, 3), 100)
    xlabel('Ideal number of iterations');
    ylabel('Count');
    title(['Histogram of ideal number of iterations, using Nsamples = ', num2str(Nsamples)])

    figure
    hist(datamatrix_conditioned(:, 4), 100)
    xlabel('Number of iterations using CVMOV algorithm');
    ylabel('Count');
    title(['Histogram of number of iterations using CVMOV algorithm, using Nsamples = ', num2str(Nsamples)])

    figure
    hist(datamatrix_conditioned(:, 6), 100)
    xlabel('Number of iterations using J-DIV algorithm');
    ylabel('Count');
    title(['Histogram of number of iterations using J-DIV algorithm, using Nsamples = ', num2str(Nsamples)])
    
end