Simple Question about Optimization of Nested IF-FOR loops

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)

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

'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?
Sorry! It should have been:
t = repmat(SliceMaskUr==1,[1,1,iNZ]);

1 Comment

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
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

No, I wouldn't expect it to give the same result if you still use
DoseCubeU(m+(l-1)*iNX+i*iNX*iNY)
As I already pointed out, that indexes DoseCubeU starting, not with 1 but with 1+iNX*iNY and ends not with iNX*iNY*iNZ but iNX*iNY*iNZ+iNX*iNY. In my modification I assumed you didn't want to do that. Note that this has nothing to do with reshaping SumDose. It should work in that code without being reshaped. Using t as a single logical index will cause it to be interpreted as a linear index. Similarly in DoseCubeU the use of the single logical vector t will be interpreted by DoseCubeU as a linear index. Note that I have assumed that both DoseCubeU and SumDose are of sizes iNX-by-iNY-by-iNZ.
Thank you for your reply. In my original code, I changed "m+(l-1)*iNX+i*iNX*iNY" to "m+(l-1)*iNX+(i-1)*iNX*iNY" so that the index of DoseCubeU is from 1 to iNX*iNY*iNZ.
Both DoseCubeU and SumDose are of sizes iNX-by-iNY-by-iNZ.
However, your code still gives me a different answer than my original code.
As a test, in order to use the subscription notation instead of indexing, I just modified my code to the following and surprisingly the results are again different from the two previous methods:
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
This is confusing!!
I think that the function poly2mask is in charge of these discrepancies. Any idea why? Here is the entire code:
iNNX=double(iNX);
iNNY=double(iNY);
for i=1:iNZ;
iPointsinSlice=1;
for j=1:iNCUr;
if UrContourZ(j)==ZSlice(i);
iPointsinSlice = iPointsinSlice+1;
UrPointX(iPointsinSlice-1)=1 + (UrContourX(j)-Offset(1,1));
UrPointY(iPointsinSlice-1)=1 + (UrContourY(j)-Offset(2,1));
end
end
if iPointsinSlice>0;
indx=round(iPointsinSlice);
indy=round(iPointsinSlice);
indx(1:iPointsinSlice-1)=UrPointX(1:iPointsinSlice-1)/DresX;
indy(1:iPointsinSlice-1)=UrPointY(1:iPointsinSlice-1)/DresY;
SliceMaskUr = poly2mask(indx,indy,iNNX,iNNY);
for m=1:iNX;
for l=1:iNY;
if SliceMaskUr(m,l)==1;
DoseCubeU(m+(l-1)*iNX+(i-1)*iNY*iNX)=100*SumDose(m,l,i)/RX_Dose;
end
end
end
end
end
Your help is much appreciated! :)
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
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

Thank you for your reply. In my original code, I changed "m+(l-1)*iNX+i*iNX*iNY" to "m+(l-1)*iNX+(i-1)*iNX*iNY" so that the index of DoseCubeU is from 1 to iNX*iNY*iNZ.
Both DoseCubeU and SumDose are of sizes iNX-by-iNY-by-iNZ.
However, your code still gives me a different answer than my original code.
As a test, in order to use the subscription notation instead of indexing, I just modified my code to the following and surprisingly the results are again different from the two previous methods:
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
This is confusing!!
I think that the function poly2mask is in charge of these discrepancies. Any idea why? Here is the entire code:
iNNX=double(iNX);
iNNY=double(iNY);
for i=1:iNZ;
iPointsinSlice=1;
for j=1:iNCUr;
if UrContourZ(j)==ZSlice(i);
iPointsinSlice = iPointsinSlice+1;
UrPointX(iPointsinSlice-1)=1 + (UrContourX(j)-Offset(1,1));
UrPointY(iPointsinSlice-1)=1 + (UrContourY(j)-Offset(2,1));
end
end
if iPointsinSlice>0;
indx=round(iPointsinSlice);
indy=round(iPointsinSlice);
indx(1:iPointsinSlice-1)=UrPointX(1:iPointsinSlice-1)/DresX;
indy(1:iPointsinSlice-1)=UrPointY(1:iPointsinSlice-1)/DresY;
SliceMaskUr = poly2mask(indx,indy,iNNX,iNNY);
for m=1:iNX;
for l=1:iNY;
if SliceMaskUr(m,l)==1;
DoseCubeU(m+(l-1)*iNX+(i-1)*iNY*iNX)=100*SumDose(m,l,i)/RX_Dose;
end
end
end
end
end
Your help is much appreciated! :)
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
Corrected. See ADD part in my answer.
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

This gives me a different answer than all the other four methods!
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

This question is closed.

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Asked:

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