Changeset 31 for liacs/nc/low-correlation/mcs.m

Timestamp:

Dec 13, 2009, 4:55:02 PM (15 years ago)

Author:

Rick van der Zwet

Message:

Monto Carlo Search implementation completed

File:

• liacs/nc/low-correlation/mcs.m (modified) (1 diff)

liacs/nc/low-correlation/mcs.m

@@ -7 +7 @@
 % autocorrelation(best_20);
 
+function [fitness,value] = mcs(length, iterations)
+    best_fitness = 0;
+    for i = 1:iterations
+        % Generate a random column s={-1,1}^n
+        n = length;
+        s = rand(n,1);
+        s = round(s);
+        s = s - (s == 0);
+    
+        % Find whether we are better than everything else
+        fitness = autocorrelation(s);
+        if (fitness > best_fitness)
+            best_value = s;
+            best_fitness = fitness;
+        endif
+    endfor
+    fitness = best_fitness;
+    value = best_value;
+endfunction
 
-best_fitness = 0;
-while (1)
-    % Generate a random column s={-1,1}^n
-    n = 20;
-    s = rand(n,1);
-    s = round(s);
-    s = s - (s == 0);
+% Basic variables
+iterations = [1:10:200];
+repetitions = 20;
+length = 20;
 
-    % Find whether we are better than everything else
-    fitness = autocorrelation(s);
-    if (fitness > best_fitness)
-        best_result = s;
-        best_fitness = fitness
+
+% Plot the stuff
+fitnesses = [];
+for iteration = iterations
+    fitness = [];
+    for rep = 1:repetitions
+        printf('Iter:%i, Rep:%i\n',iteration,rep);
+        [new_fitness, value] =  mcs(length,iteration);
+        fitness = [fitness, new_fitness];
+
         % Little hack to display output nicely
-        disp(rot90(best_result,-1));
-    endif
-endwhile
+        % disp(rot90(value,-1));
+    endfor
+    
+    fitnesses = [fitnesses,mean(fitness)];
+endfor
 
+plot(iterations,fitnesses);
+title(sprintf('Monte-Carlo Search on Low-Corretation set - repetitions %i',repetitions));
+ylabel('fitness');
+xlabel('iterations');
+grid on;
+legend(sprintf('Length %i',length));
+print("mcs-fitness.eps","-depsc2");
+