Using Parfor to create matrix from a vector

Question

I am new to Matlab and would appreciate any assistance possible!

I am running a simulation and so the results vary with each run of the simulation. I want to collect the results for analysis.

For example, during the first simulation run, the level of a plasma coagulation factor may vary over 5 hours as such: R(1) = [1.0 0.98 0.86 0.96 0.89]

In the second run, the levels at each time period may be slightly different, eg. R(2) = [1.0 0.95 0.96 0.89 0.86]

I would like to (perhaps by using the parfor function) to create a matrix eg. R = [1.0 0.98 0.86 0.96 0.89 1.0 0.95 0.96 0.89 0.86]

I have encountered problems ranging from "In an assignment A(I) = B, the number of elements in B and I must be the same" to getting a matrix of zeros or ones (depending on what I use for the preallocation).

I will need the simulation to run about 10000 times in order to collect a meaningful amount of results.

Can anyone suggest how this might be achieved? A detailed guidance or (semi)complete code would be much appreciated for someone new to Matlab like me.

Thanks in advance!

This is my actual code, and as you can see, there are 4 variables that vary over 744 hours (31 days) which I would like to individually collect:

Iterations = 10000;
PGINR = zeros(Iterations, 744);
PGAmount = zeros(Iterations, 744);
CAINR = zeros(Iterations, 744);
CAAmount = zeros(Iterations, 744);

for iii = 1:Iterations
    [{PGINR(iii)}, {PGAmount(iii)}, {CAINR(iii)}, {CAAmount(iii)}] = ChineseTTRSimulationB();
end

filename = 'ChineseTTRSimulationResults.xlsx';
xlswrite(filename, PGINR, 2)
xlswrite(filename, PGAmount, 3)
xlswrite(filename, CAINR, 5)
xlswrite(filename, CAAmount, 6)

Answer 1

Are you looking for something like this? I simplified a little bit your code for better understanding and added some dummy data, function.

main.m

Iterations  = 10;
PGINR       = zeros(Iterations, 2);
PGAmount    = zeros(Iterations, 2);

%fake data
x = rand(Iterations,1);
y = rand(Iterations,1);

parfor iii = 1:Iterations
    [PGINR(iii,:), PGAmount(iii,:)] = ChineseTTRSimulationB(x(iii), y(iii));
end

ChineseTTRSimulationB.m

function [PGINRi, PGAmounti] = ChineseTTRSimulationB(x,y)
    PGINRi       = [x + y, x];
    PGAmounti    = [x*y, y];
end

Answer 2

save each parfor-result in cells, and combine them later.

Iterations = 10000;
PGINR = cell(1, Iterations);
PGAmount = cell(1, Iterations);
CAINR = cell(1, Iterations);
CAAmount = cell(1, Iterations);

parfor i = 1:Iterations
    [PGINR{i}, PGAmount{i}, CAINR{i}, CAAmount{i}] = ChineseTTRSimulationB();
end

PGINR = cell2mat(PGINR); % 1x7440000 vector
%and so on...