Alternate to the circshift function in a 3d matix for an agent based model
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Hey there,
I have a 3 dimensional matrix randworld and need to perform certain calculations on each the row and column cell around a randomly selected cell holding the third dimension constant. I used the circshift function for this. However as I need to do 121000000 iterations, this method is very slow. I noticed the circshift function consumes most of the time (from profile viewer). Could you please suggest an alternative to the circshift function.
I have copied the code below so that you have an idea of what I'm looking to do.
Thank you.
nside=11; %rows and coloumns
u=120; %neighbours
randworld=randi(10,nside,nside,5); %create a random 3-d world
%select a random agent and feature
randomagentr=randi(10,1);
randomagentc=randi(10,1);
randomfeat=randi(5,1);
nsize=0;
%neighbourhood
for q=-5:5
for w=-5:5
if abs(q)+abs(w)~=0
nsize=nsize+1;
neigh(nsize,:)=[q,w];
end
end
end
for k=1:u
vm=circshift(randworld,[neigh(k,1),neigh(k,2)]);
v=vm(randomagentr,randomagentc,randomfeat);
%perform certain computations on this new variable v
end
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Roger Stafford
il 29 Ago 2013
If a circular shift by +1 done with indexing is significantly faster than your 'circshift' operations, then you can do the equivalent of your circular shifts in the last nested for-loops as a succession of such "index" shifts by +1 and it would then presumably be faster. Don't create the array 'neigh'. Just do this:
vm = circshift(squeeze(randworld(:,:,randomfeat)),[-5,-5]);
p = [11,1:10]; % <-- Another way to do circular shift by +1
for ir = 1:11
for ic = 1:11
v=vm(randomagentr,randomagentc);
%perform certain computations on this new variable v
vm = vm(:,p); % Circular column shift by +1
end
vm = vm(p,:); % Circular row shift by +1
end
You will have to test for the case ir == 6 and ic == 6 to avoid the case when there is to be no overall shift in order to get just 120 instead of 121 steps.
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