# Complicated for loops structuring

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Jonathan Cheong on 22 Mar 2021
Answered: Jonathan Cheong on 23 Mar 2021
Hello, this is a question for the pros, and feel free to only answer if it interest you.
I have this code which helps me model data for each independent event.
% Event 1
sm1 = smcellere{1,:}; t1 = 1:length(sm1);SMF_1 = (1:0.3:SMO(1));good1 = sm1(~isnan(sm1)).';
figure(1)
plot(t1,sm1,'--ob');
hold on
for i = 1:length(SMF_1)
for ii = 1:length(tau)
% This is the model
SM1 = (SMO(1)-SMF_1(i))*exp(-t1./tau(ii))+SMF_1(i);
rmse1(i,ii) = sqrt(sum((SM1-good1).^2)/length(good1));
end
end
[iii,jjj] = find(rmse1 == min(rmse1(:)));
smf1=SMF_1(iii);tau1 = tau(jjj);
sm1calc = (SMO(1)-smf1)*exp(-t1./tau1)+smf1;
plot(t1,sm1calc,'-or');
hold off
% Event 2
sm2 = smcellere{2,:}; t2 = 1:length(sm2);SMF_2 = (1:0.3:SMO(2));good2 = sm2(~isnan(sm2)).';
figure(2)
plot(t2,sm2,'--ob');
hold on
for ai = 1:length(SMF_2)
for aii = 1:length(tau)
SM1 = (SMO(2)-SMF_2(ai))*exp(-t2./tau(aii))+SMF_2(ai);
rmse2(ai,aii) = sqrt(sum((SM1-good2).^2)/length(good2));
end
end
[aai,aaj] = find(rmse2 == min(rmse2(:)));
smf2=SMF_2(aai);tau2 = tau(aaj);
sm2calc = (SMO(2)-smf2)*exp(-t2./tau2)+smf2;
plot(t2,sm2calc,'-or');
hold off
Now, the code is long, and this is only for 2 events. I have 34 events to go through, which I would be doing manually nonetheless if I can't figure out an algorithm to plot every event automatically. Furthermore, a working algorithm can help me cross check my answers.
This is what I'm trying to achieve by meshing everything into a single algorithm:
% Each event is represented as data in each row of cell
% Iterate through each event
for i = 1:length(smcellere)
sm = smcellere{i,:};
% The duration of event is denoted as t
t = 1:length(sm);
% SMO is the 1st data point for each row/event, and SMF is the interval
SMF = (1:0.3:SMO(i));
% Iterate through each data of SMF
for ai = 1:length(SMF)
% Iterate through each day in a year (tau)
for aii = 1:length(tau)
% Plot the initial graph of observed data for each event
figure, plot(t,sm,'--ob');
hold on
% This is the exponential model. Run this model for each
% day in tau and each point in SMF
SM = (SMO(i)-SMF(ai))*exp(-t./tau(aii))+SMF(ai);
for gi = 1:length(SM)
for ki = t
% Calculate Root Mean Square Error to plot as line of
% best fit
rmse(ai,aii) = sqrt(sum((SM(gi)-sm(ki)).^2)/length(sm(ki)));
% THis is the best RMSE
[aai,aaj] = find(rmse == min(rmse(:)));
smf=SMF(aai);tau2 = tau(aaj);
% Calculate the model results
smcalc = (SMO(i)-smf)*exp(-t./tau2)+smf;
end
end
end
end
% Plot line of best fit
plot(t,smcalc,'-or');
hold off
end
The problem is, I can't do trial and error with this because my computer will just freeze due to bad coding.
Thanks in advance for any who'd like a challenge.
##### 2 CommentsShowHide 1 older comment
darova on 22 Mar 2021
I don't see rmse preallocation. Did you define size of the variable?

Jonathan Cheong on 23 Mar 2021
Thanks this works perfectly.
smtmp = smcellere(:);
for i = 1:length(smtmp)
sm = smtmp{i,:}.';
t = 1:length(sm);
SMF = (1:0.1:SMO(i));
figure, plot(t,sm,'--ob');
hold on
rmse = zeros(size(SMF,1),length(tau));
for ai = 1:length(SMF)
for aii = 1:length(tau)
SM = (SMO(i)-SMF(ai))*exp(-t./tau(aii))+SMF(ai);
rmse(ai,aii) = sqrt(sum((SM-sm).^2)/length(sm));
end
end
[aai,aaj] = find(rmse == min(rmse(:)));
smf=SMF(aai);tau2 = tau(aaj);
smcalc = (SMO(i)-smf)*exp(-t./tau2)+smf;
plot(t,smcalc,'-or');
hold off
end