close all
clear all 
clc

load('convolution_in_matlab_insuline_data.mat') % defines T, x, tx
tg = 0:T:420; % we use the same range of x
g1 = .76*exp(-.14*tg)+.24*exp(-0.2*tg);
y1 = T*conv(x,g1);
ty = tx(1)+tg(1):T:tx(end)+tg(end);
g2 = .76*exp(-.14*tg)+.24*exp(-0.02*tg);
y2 = T*conv(x,g2);
g3 = .76*exp(-.14*tg)+.24*exp(-0.002*tg);
y3 = T*conv(x,g3);

figure
subplot(2,2,1)
plot(tx,x)
grid
axis([0 420 ylim])
xlabel('t [min]')
ylabel('x(t) [pmol/L/min]')
title('pancreatic secretion')
subplot(2,2,2)
plot(tg,g1,tg,g2,tg,g3)
grid
axis([0 420 ylim])
xlabel('t')
ylabel('g(t)')
legend('b=0.2','b=0.02','b=0.002')
title('filter response')
subplot(2,1,2)
plot(ty,y1,ty,y2,ty,y3)
grid
axis([0 420 ylim])
xlabel('t')
ylabel('y(t) [pmol/L]')
title('plasma concentration')
sgtitle('hormone C-peptide kinetics')

% printing figure in png format
set(gcf,'PaperUnits','inches','PaperPosition',[0 0 6 4.5])
print -dpng homework2.png -r100