Random matrix - Code efficiency
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Hi, I've got a code to fill a matrix with random numbers. However, I haven't found a way to use efficient code and I must use for loop. Here is the code I would like to optimize :
PoissonZ=poissrnd(Lambda,NbTraj,NbDay);
for i=1:NbDay
for j=1:NbTraj
PoissonSauts(j,i)=sum(randn(PoissonZ(j,i),1));
end
end
As NbTraj and/or NbDay can achieve quickly high value, the code become very slow... I did not found a way to vectorize it. Thanks for suggestions !
G.
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the cyclist
2011-3-29
Looks to me that each element of PoissonSauts is the sum of K normally distributed variables, where K is itself drawn from a Poisson. I believe you can take advantage of the fact that the sum of K i.i.d. variables that are N(0,1) distributions is equal to sqrt(K) times an N(0,1):
PoissonZ=poissrnd(Lambda,NbTraj,NbDay);
PoissonSauts = randn(NbTraj,NbDay).*sqrt(PoissonZ);
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Matt Fig
2011-3-29
I would bet that your code is slow primarily because you did not pre-allocate the PoissonSauts array before the loops. Thus every time through the loop you are causing MATLAB to re-allocate memory for the array, which, as you discovered, is slow.
PoissonZ=poissrnd(Lambda,NbTraj,NbDay);
PoisonSauts = zeros(NBTraj,NbDay); % Pre-allocate the array!
for i=1:NbDay
for j=1:NbTraj
PoissonSauts(j,i)=sum(randn(PoissonZ(j,i),1));
end
end
Try that and see if your code speeds up dramatically.
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2011-3-29
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