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49 lines
1.7 KiB
Matlab
49 lines
1.7 KiB
Matlab
clear
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RandStream.setDefaultStream(RandStream.create('mt19937ar','seed',0));
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figure(1), figure(2), figure(3), figure(4)
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trials=25;
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squares=1;
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if squares
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s=4;
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Xtest=pattern_squares_test(6,s);
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else
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gen='std';%'doubleoverlap';%'sixbars';%'unequal';%'fivebars';%'quadwidth';%'doublewidth';%
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Xtest=pattern_bars_test(5,gen);
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hierarchy=0;
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end
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for k=1:trials
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disp(['trial ',int2str(k)]); disp(' ');
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if squares
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[X,W,V,U]=learn_squares_feedback(s);
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set(0,'CurrentFigure',1); repW(k)=plot_squares(s,W);
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set(0,'CurrentFigure',2); repV(k)=plot_squares(s,V);
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set(0,'CurrentFigure',3); repU(k)=plot_squares(s,U);
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set(0,'CurrentFigure',4); respAcc(k)=test_response(Xtest,W,V);
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else
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if hierarchy
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[X,W,V,U,Wh,Vh,Uh]=learn_bars_hierarchy(gen);
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else
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[X,W,V,U]=learn_bars_feedback(gen);
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end
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set(0,'CurrentFigure',1); repW(k)=plot_bars(gen,W);
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set(0,'CurrentFigure',2); repV(k)=plot_bars(gen,V);
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set(0,'CurrentFigure',3); repU(k)=plot_bars(gen,U);
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if hierarchy
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set(0,'CurrentFigure',4); respAcc(k)=test_response(Xtest,Wh,Vh,Uh);
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else
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set(0,'CurrentFigure',4); respAcc(k)=test_response(Xtest,W,V);
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end
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end
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end
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sw=sum(W'), disp(num2str([max(sw),min(sw),max(max(W)),min(min(W))]))
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sv=sum(V'), disp(num2str([max(sv),min(sv),max(max(V)),min(min(V))]))
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su=sum(U'), disp(num2str([max(su),min(su),max(max(U)),min(min(U))]))
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disp(' ');
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disp([num2str(mean(repW)),' ',num2str(max(repW)),' ',num2str(min(repW))])
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disp([num2str(mean(repV)),' ',num2str(max(repV)),' ',num2str(min(repV))])
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disp([num2str(mean(repU)),' ',num2str(max(repU)),' ',num2str(min(repU))])
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disp([num2str(mean(respAcc)),' ',num2str(max(respAcc)),' ',num2str(min(respAcc))])
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reliability=length(find(respAcc==1))./trials |