			% lstm on data
			%% Pyhton script
			fileNameInput = 'pendulum.csv';
			parameters = ' 0.9 50 30 100 64';
			command = ['python lstm.py input/', fileNameInput, parameters];
			system(command);
			%% load generated data
			load('output/dataset.mat')
			load('output/trainPredict.mat')
			load('output/testPredict.mat')
			load('output/score.mat')
			%% Define useful variables
			steps = (1:length(dataset))';
			m = length(trainPredict);
			m_test = length(testPredict);
			N = length(steps);

			%% plot
			display(score);
			figure(1)
			set(gca,'FontSize',14)
			set(gcf,'units','normalized','outerposition',[0 0 1 1])
			hold on
			plot(steps,dataset,'.');
			plot(steps(2:m+1),trainPredict,'.')
			plot(steps((N - m_test - 1):N-2),testPredict,'.')
			xlabel('steps')
			ylabel('nb passengers [10^3]')
			grid on
			% % figg = gcf;
			% % figg.PaperUnits = 'centimeters';
			% % figg.PaperPosition = [0 0 26 13];
			% % print('Heisenberg1','-depsc');
			hold off

R2096/lstm/lstm1.m
c755270c71b7master

lstm1.m
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