GraphEvaluation.m

%*************************************************************************%
%@BeginVerbatim 
% Function: GraphEvaluation
% Description: Create an overview of the performance of the genetic algorithm for the traveling salesman
% Parameter(s): evaluation_history, matrix;
% Filename: GraphEvaluation.m
% Version: v00.02
% Author: Group 1
% Yr&Sec: 3-4
% Subject: Computational Intelligence
%@EndVebartim 
%*************************************************************************%

% Last Reviewed by: Periabras, 17 February 2017

%@Code Body***************************************************************%

function [ ] = GraphEvaluation( evaluation_history )
    %@Intialization*******************************************************%
        x = []; %all x coordinates
        y = []; %best and worst scores
        z = []; %average scores
    %*********************************************************************%
     
    %Loop throught the whole evaluation for every 6% of the total length of
    %   evaluation
    for cnt = 1:ceil(length(evaluation_history)*0.06):length(evaluation_history)
        x = cat(1,x,cnt);
        y = vertcat(y,evaluation_history(cnt,1:2));
        z = cat(1,z,evaluation_history(cnt,3));
    end
    
    %Create Graph
    hold on;
    axis([-10 length(evaluation_history)+10 0 70]); 
    bar(x,y); 
    title('Overview of Performance');
    xlabel(strcat('Generations: ',num2str(length(evaluation_history))));
    ylabel('Fitness');
    plot(x,z);
    plot(x,z,'or');
    legend('Best', 'Worst', 'Average');
    hold off;

end

%*************************************************************************%