sustaining_gazes/matlab_version/face_validation/DeepLearnToolbox/NN/nnupdatefigures.m

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2016-04-28 21:40:36 +02:00
function nnupdatefigures(nn,fhandle,L,opts,i)
%NNUPDATEFIGURES updates figures during training
if i > 1 %dont plot first point, its only a point
x_ax = 1:i;
% create legend
if opts.validation == 1
M = {'Training','Validation'};
else
M = {'Training'};
end
%create data for plots
if strcmp(nn.output,'softmax')
plot_x = x_ax';
plot_ye = L.train.e';
plot_yfrac = L.train.e_frac';
else
plot_x = x_ax';
plot_ye = L.train.e';
end
%add error on validation data if present
if opts.validation == 1
plot_x = [plot_x, x_ax'];
plot_ye = [plot_ye,L.val.e'];
end
%add classification error on validation data if present
if opts.validation == 1 && strcmp(nn.output,'softmax')
plot_yfrac = [plot_yfrac, L.val.e_frac'];
end
% plotting
figure(fhandle);
if strcmp(nn.output,'softmax') %also plot classification error
p1 = subplot(1,2,1);
plot(plot_x,plot_ye);
xlabel('Number of epochs'); ylabel('Error');title('Error');
title('Error')
legend(p1, M,'Location','NorthEast');
set(p1, 'Xlim',[0,opts.numepochs + 1])
p2 = subplot(1,2,2);
plot(plot_x,plot_yfrac);
xlabel('Number of epochs'); ylabel('Misclassification rate');
title('Misclassification rate')
legend(p2, M,'Location','NorthEast');
set(p2, 'Xlim',[0,opts.numepochs + 1])
else
p = plot(plot_x,plot_ye);
xlabel('Number of epochs'); ylabel('Error');title('Error');
legend(p, M,'Location','NorthEast');
set(gca, 'Xlim',[0,opts.numepochs + 1])
end
drawnow;
end
end