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Simple Question about Optimization of Nested IF-FOR loops

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Does any one know how to optimize this code so that it runs faster:
for i=1:iNZ;
if iPointsinSlice>0;
for m=1:iNX;
for l=1:iNY;
if SliceMaskUr(m,l)==1;
DoseCubeU(m+(l-1)*iNX+i*iNX*iNY)=100*SumDose(m,l,i)/RX_Dose;
end
end
end
end
end
Your help is much appreciated! Thanks a lot!

Answers (5)

Roger Stafford
Roger Stafford on 17 Jun 2013
Is 'iPointsinSlice' a scalar? If so and if it is not positive, nothing will happen here.
Next, don't you mean "m+(l-1)*iNX+(i-1)*iNX*iNY" as the index to 'DoseCubeU'? As it stands it will vary from 1+iNX*iNY to iNX*iNY*iNZ+iNX*iNY. Assuming my guess is correct, do this:
if iPointsinSlice > 0
t = repmat(SliceMaskUr==1,1,1,iNZ);
DoseCubeU(t) = (100/RX_Dose)*SumDose(t);
end
In case 'iPointsinSlice' is not a scalar you will have to correct your code before we can see how to handle it.
  1 Comment
Mohsen
Mohsen on 17 Jun 2013
'iPointsinSlice' is a scalar. "m+(l-1)*iNX+(i-1)*iNX*iNY" is used as the index to 'DoseCubeU. But your code gives the error that REPMAT has too many arguments. How should I fix it?

Roger Stafford
Roger Stafford on 17 Jun 2013
Sorry! It should have been:
t = repmat(SliceMaskUr==1,[1,1,iNZ]);
  1 Comment
Mohsen
Mohsen on 18 Jun 2013
I changed
DoseCubeU(m+(l-1)*iNX+i*iNY*iNX)=100*SumDose(m,l,i)/RX_Dose;
to
DoseCubeU(double(m)+double((l-1))*double(iNX)+double((i-1))*double(iNY)*double(iNX))=100*SumDose(m,l,i)/RX_Dose;
Otherwise the indexing will not be correct. For example, iNX*iNY*iNZ (which is 120*120*11) becomes equal to 65535 (which is wrong). We should write it as double(iNX)*double(iNY)*double(iNZ) in order to get the correct results (ie. 158400).
By making this change, both the indexing (the initial) method and the subscription method (below) give the same results. But these results are different than any of the other proposed methods.
So, how can I optimize:
for i=1:iNZ;
if iPointsinSlice>0;
for m=1:iNX;
for l=1:iNY;
if SliceMaskUr(m,l)==1;
DoseCubeU(m,l,i)=100*SumDose(m,l,i)/RX_Dose;
end
end
end
end
end

Mohsen
Mohsen on 17 Jun 2013
This code doesn't give me the same result as my initial code. Please note that the purpose of "m+(l-1)*iNX+i*iNX*iNY" is to reshape the SumDose array which is (iNX by iNY by iNZ) to a one dimensional array (1 by iNX*iNY*iNZ).
I tried also
if SliceMaskUr==1;
DoseCubeU= reshape(SumDose,1,[iNX iNY iNZ])*(100/RX_Dose);
end
but it didn't work neither...
Any insight?
  4 Comments
Mohsen
Mohsen on 18 Jun 2013
I changed
DoseCubeU(m+(l-1)*iNX+i*iNY*iNX)=100*SumDose(m,l,i)/RX_Dose;
to
DoseCubeU(double(m)+double((l-1))*double(iNX)+double((i-1))*double(iNY)*double(iNX))=100*SumDose(m,l,i)/RX_Dose;
Otherwise the indexing will not be correct. For example, iNX*iNY*iNZ (which is 120*120*11) becomes equal to 65535 (which is wrong). We should write it as double(iNX)*double(iNY)*double(iNZ) in order to get the correct results (ie. 158400).
By making this change, both the indexing (the initial) method and the subscription method (below) give the same results. But these results are different than any of the other proposed methods.
So, how can I optimize:
for i=1:iNZ;
if iPointsinSlice>0;
for m=1:iNX;
for l=1:iNY;
if SliceMaskUr(m,l)==1;
DoseCubeU(m,l,i)=100*SumDose(m,l,i)/RX_Dose;
end
end
end
end
end

Andrei Bobrov
Andrei Bobrov on 18 Jun 2013
Edited: Andrei Bobrov on 19 Jun 2013
DoseCubeU = bsxfun(@times,100*SumDose/RX,SliceMaskUr==1);
ADD
s = SliceMaskUr(end:-1:1,end:-1:1);
tt = cumsum(cumsum(s),2);
t1 = flipud(any(tt,2));
t2 = fliplr(any(tt));
DoseCubeU = bsxfun(@times,100*SumDose(t1,t2,:)/RX_Dose,SliceMaskUr(t1,t2));
  4 Comments

Iain
Iain on 18 Jun 2013
Try:
DoseCubeU(NY,NX,NZ) = 0; % or any suitable initialisation
if iPointsinSlice>0;
DoseCubeU(SliceMaskUr(m,l)==1,:) = 100*SumDose(SliceMaskUr(m,l)==1,:);
end
  2 Comments
Mohsen
Mohsen on 18 Jun 2013
I changed
DoseCubeU(m+(l-1)*iNX+i*iNY*iNX)=100*SumDose(m,l,i)/RX_Dose;
to
DoseCubeU(double(m)+double((l-1))*double(iNX)+double((i-1))*double(iNY)*double(iNX))=100*SumDose(m,l,i)/RX_Dose;
Otherwise the indexing will not be correct. For example, iNX*iNY*iNZ (which is 120*120*11) becomes equal to 65535 (which is wrong). We should write it as double(iNX)*double(iNY)*double(iNZ) in order to get the correct results (ie. 158400).
By making this change, both the indexing (the initial) method and the subscription method (below) give the same results. But these results are different than any of the other proposed methods.
So, how can I optimize:
for i=1:iNZ;
if iPointsinSlice>0;
for m=1:iNX;
for l=1:iNY;
if SliceMaskUr(m,l)==1;
DoseCubeU(m,l,i)=100*SumDose(m,l,i)/RX_Dose;
end
end
end
end
end

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