What is the fastest, circshift or indices ?

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Hi
I'm trying to improve the efficiency of my algorithm. I need to compute something like :
Y(2:end-1,:) = X(2:end-1,:) + X(1:end-2,:) - X(3:end,:)
For Y and X n by m matrices. I was wondering if it was faster to do it as it is above, or using circshift :
Y = X + circshift(X,[-1,0]) - circshift(X,[+1,0]).
I've done a few tests but I can't get a clear idea... The aim is to do this on pretty big matrices on a cluser with multiple cores...
Any idea ? Thanks.
Stéphane
  1 Comment
Adam
Adam on 5 Nov 2014
I regularly create small test scripts with as many alternative implementations as I can think of, each wrapped in a
timeit(f)
instruction for function handle, f. It is extremely useful for improving understanding as well as getting the (hopefully conclusive) final answer as to which method is fastest. Sounds like you did kind of do that though...

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Accepted Answer

Matt J
Matt J on 5 Nov 2014
Edited: Matt J on 5 Nov 2014
Just use conv2
Y=conv2(X,[-1;1;1],'valid');
As for circshift, it is not a builtin function and, if you look inside it
>>type circshift
you will see that it does pretty much the same indexing as you are doing. So, I wouldn't expect it to be a competitive approach.
  4 Comments
Stéphane
Stéphane on 5 Nov 2014
Second thought...
I've tried in 1D to understand what conv (conv2) does and it seems conv(X,[-1;1]) and the same with circshift doesn't produce the same result. Is it normal or am I doing something wrong ?
(What I want is X(2:end) - X(1:end-1) )
Matt J
Matt J on 5 Nov 2014
Edited: Matt J on 5 Nov 2014
(What I want is X(2:end) - X(1:end-1) )
That would correspond to
conv(X,[1;-1],'valid')
You could also do
diff(X)

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