How do I speed up loops in the code?
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I have the following code which consists of three loops whicjh is taking a long time to run. Any ideas how to speed it up?
C=ones(NumSims, NumScen);
for i=1:NumScen
B=copularnd('Gaussian',PSDMatrix,NumSims);
C(:,i)=icdf('poisson',B(:,i),A(i,1));
M=cumsum(C);
Maxsim=M(end,:);
for i=1:NumScen
Col(1,i)=max(C(:,i));
Col2=max(Col);
LossFlag=zeros(NumSims,Col2);
end
for i=1:NumScen
for j=1:NumSims
for k=1:Col2
if k<=C(j,i)
LossFlag(j,k,i)=1;
else
0;
3 Comments
DGM
on 2 Feb 2023
Edited: DGM
on 2 Feb 2023
Since the pasted code is incomplete, I can only guess what's missing. I see a bunch of nested and/or improperly terminated loops. There appear to be two 1:NumScen loops that run inside of another for no apparent reason. I suspect that this can be simplified, but not without knowing what's missing.
C=ones(NumSims, NumScen);
for i=1:NumScen % everything is inside this loop
B=copularnd('Gaussian',PSDMatrix,NumSims);
C(:,i)=icdf('poisson',B(:,i),A(i,1));
% these get overwritten each time, but aren't apparently used
% if they aren't used, get rid of them
% if they can be calculated outside the loop, move them outside the loop
% if only Maxsim is needed, get rid of M
% Maxsim = sum(C,1);
M=cumsum(C);
Maxsim=M(end,:);
for i=1:NumScen % ... so this loop appears redundant or misplaced
% ... but idk if Col needs to be fully written
% if so, this could just be vectorized -- but idk what size Col is
% if Col is only used to calculate Col2, then this simplifies
Col(1,i)=max(C(:,i)); % i'm assuming Col is a vector?
Col2=max(Col); % ambiguous dimension; again, suggests Col is a vector
LossFlag=zeros(NumSims,Col2); % not preallocated to the size used later
end
for i=1:NumScen % ... and this loop appears redundant or misplaced
for j=1:NumSims
for k=1:Col2
% this should be able to be reduced to a single relational
% test for the entire array, without any loops needed
if k<=C(j,i)
LossFlag(j,k,i)=1;
else
0; % this does nothing
end % missing??
end % missing??
end % missing??
end % missing??
end % missing??
Perhaps something like this? (not tested)
% populate C
C=ones(NumSims, NumScen);
for i = 1:NumScen % everything is inside this loop
B = copularnd('Gaussian',PSDMatrix,NumSims);
C(:,i) = icdf('poisson',B(:,i),A(i,1));
end
% assuming this can be moved and that M is not needed itself
Maxsim = sum(C,1);
% assuming Col is only needed to calculate Col2
Col2 = max(C,[],'all');
k = 1:Col2; % a row vector
LossFlag = k <= permute(C,[1 3 2]); % compare to generate a 3D logical array
These are a lot of gross assumptions on my part, but that's all I can do.
Consider the example:
outvector = zeros(1,10); % a test vector
n = 0;
for k = 1:10
for k = 1:10 % trying to alter loop index within a loop is bad
% this runs 100 times, not 10
n = n+1;
outvector(k) = n;
end
end
% 90% of all the results are just discarded
outvector
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