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visualising_results.m
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visualising_results.m
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%for cocaine group all data
alpha= [0.32 0.34 0.02 0.98 0.14 0.04 0.12 0.24 0.12 0.72 0.96 0.10 0.02 0.00 0.58 0.98 0.98 0.06 0.24 0.28 0.22 0.02 0.10]
beta= [1.49 1.61 1.77 1.01 2.93 2.59 2.75 0.79 2.07 2.07 1.07 1.23 1.23 0.01 0.63 0.49 0.53 2.99 1.91 2.31 2.11 2.99 2.99]
%comparing LLR in 2 model vs 3 model test
LLR_alpha3_vs_2param = [-2.807725106 -2.027355893 -11.10817085 -0.229646631 -2.431169312 -0.816438187 -3.030595225 -0.081672866 -0.200288742 -0.064859502 -0.104232721 -3.712785886 -0.961820336 -0.017677968 -0.009502609 0 -0.208851708 -1.693699473 -0.529394717 -5.282797327 -1.733321667 0 -0.125820873; -3.671186704 -1.454692314 -6.065353489 0 -1.24200215 -0.814267031 -2.41470551 -6.117065475 -2.846076847 -7.86493008 -2.118698166 -0.208122148 -2.202022969 -4.415946039 -0.729054664 -1.33604125 -3.629086225 -0.303896097 -14.89682851 -4.074246211 -0.474378908 -4.577671564 -4.891538088];
LLR_alpha3_vs_2param=LLR_alpha3_vs_2param*-1
LLR_kappa3_vs_2param = [2.807725106 1.653144663 11.44400618 2.447620402 3.80118525 9.513419837 0.095915178 13.87910841 0.265407657 0.256097095 -0.009999572 5.862039259 2.661895447 1.359658811 8.2963725 4.798952918 0.940428676 4.43839817 2.186295493 0.489360847 0.833828759 -0.037016785 0.208176681; 0.403091526 -0.007232571 4.072828152 -0.039418158 0.930493141 0.074453289 11.49821973 0.294232866 1.658423727 1.043141639 4.39789125 3.688971851 -0.012346088 10.56234852 3.646511728 0.465048283 0.206465427 0.574976618 5.189980624 -0.025702747 1.649514493 3.80562516 0.505492977];
x=[1,2];
barh(LLR_alpha3_vs_2param, 'r');
title('Model 2 vs Model 3')
xlabel('Likelihood Ratio Test (d)');
yticklabels({'Cocaine', 'Controls'});
hold on;
x1=3.84;
y1=get(gca,'ylim');
plot([x1 x1],y1);
set(findall(gca, 'Type', 'Line'),'LineWidth',2);
barh(LLR_kappa3_vs_2param, 'b');
title('Model 2 vs Model 4')
xlabel('Likelihood Ratio Test (d)');
yticklabels({'Cocaine', 'Controls'});
hold on;
x1=3.84;
y1=get(gca,'ylim');
plot([x1 x1],y1);
set(findall(gca, 'Type', 'Line'),'LineWidth',2);
pvalues_d=1-chi2cdf(LLR_alpha3_vs_2param,1)
Evidence_based_vs_free=[-0.253882558 -0.303467378 -0.178916623 -0.189569496 -0.130353313 -0.236465403 -0.137299083 -0.416382301 0.015050341 0.061520375 -0.078979584 -0.105868326 -0.091922698 -0.190875788 -0.357166417 -0.10309863 -0.017432435 -0.096454741 -0.198443784 -0.024287324 -0.186233863 -0.141177907 -0.083149586; -0.076930409 -0.040497343 -0.053028535 -0.007146895 0.023068676 -0.037781375 -0.063210626 -0.036012795 0.008835382 -0.14698527 -0.113177689 -0.139998829 -0.112381386 -0.223346844 -0.318882916 -0.015968514 0.058573633 -0.096220397 -0.370319818 -0.175128981 -0.011122101 0.023011296 0.009611614]
barh(Evidence_based_vs_free);
title('Q-Learning (left) vs Policy Learning (right)')
xlabel('log Model Evidence Ratio');
yticklabels({'Cocaine', 'Controls'});
%https://uk.mathworks.com/help/matlab/ref/errorbar.html
ma=mean(alpha)
mb=mean(beta)
sa=std(alpha)/sqrt(23)
sb=std(beta)/sqrt(23)
errorbar(ma, mb,yneg,ypos,xneg,xpos,'o')
yneg=sb
ypos=sb
xneg=sa
xpos=sa
xlim manual
ylim([0 3]);
xlim([0 1]);
PDF_mat_HE=zeros(length(PDF),0);
subject_list_HE=[5 22 1 16 23 18 3 6 4 8 13 15];
for subject=subject_list_HE;
subject_mat=(PDF_all{subject})';
PDF_mat_HE=horzcat(PDF_mat_HE, subject_mat);
end;
subject_list_LE=[2 9 7 11 19 10 24 12 21 17 20];
PDF_mat_LE=zeros(length(PDF),0);
for subject=subject_list_LE;
subject_mat=(PDF_all{subject})';
PDF_mat_LE=horzcat(PDF_mat_LE, subject_mat);
end;
for i=1:length(PDF);
mean_PDF_HE(i)=mean(PDF_mat_HE(i, :));
end
mean_PDF_HE=mean_PDF_HE';
for i=1:length(PDF);
mean_PDF_LE(i)=mean(PDF_mat_LE(i, :));
end
mean_PDF_LE=mean_PDF_LE';
mean_PDF_HE=mean_PDF_HE+2;
cline(index(:,2), index(:,3), mean_PDF_LE, mean_PDF_HE);
upperl=max(mean_PDF_LE)+3;
lowerl=max(mean_PDF_LE)-5;
zlim([lowerl upperl]);
xlabel('beta');
ylabel('kappa');
zlabel('log(P(D|M,theta)');
hold on
cline(index(:,2), index(:,3), mean_PDF_HE, 'b');
plot3(index(:,2), index(:,3), mean_PDF_LE);
upperl=max(mean_PDF_LE)+3;
lowerl=max(mean_PDF_LE)-5;
zlim([lowerl upperl]);
xlabel('beta');
ylabel('kappa');
zlabel('log(P(D|M,theta)');
hold on
plot3(index(:,2), index(:,3), mean_PDF_HE);
mean_HE_Reshaped=reshape(mean_PDF_HE,[50, 63, 26]);
surf(k, j, mean_HE_Reshaped(:,:,1))