a question on for loop statement
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Dear all,
I have this for loop
T=1000;
k=0.1;
u=rand(T,1);
a = zeros(T,1);
a(1) =u(1)+ k*0.01;
for t=2:T
a(t) = u(t,1) + k*a(t-1);
end
Is there a faster way of obtaining a? Maybe if I avoid loop?
4 Comments
Luna
on 16 May 2019
Is T variable very large?
madhan ravi
on 16 May 2019
Luna T is 1000
This is the tricky part: *a(t-1)
Short answer to "is there a faster way": Probably not.
There's probably a way to avoid the loop by replacing it with a convoluted, unreadable, jumble of functions but I doubt it will be as fast and it will not be as intuitive. If your loop works for you, keep it. It's simple, clean, and fast.
Luna
on 16 May 2019
I agree with Adam I have tried with both T = 1000 and T = 1000000.
The time perfomances are below:
T = 1000 -> Elapsed time is 0.051244 seconds.
T = 1000000 -> Elapsed time is 0.073614 seconds.
The for loop is already as fast as it could be and the simplest solution.
Answers (1)
Jos (10584)
on 16 May 2019
This is filtering.
T=10; % smaller example
k=0.1;
u=rand(T,1);
% your loop -> a
a = zeros(T,1);
a(1) =u(1)+ k*0.01; % i do not get this addition ...
for t=2:T
a(t) = u(t,1) + k*a(t-1);
end
% filtering -> aa
uu = u ;
uu(1) = uu(1) + k*0.01 ; % implement offset?
aa = filter(1, [1 -k], uu) ;
% do they produce the same result?
isequal(a, aa) % YES
9 Comments
madhan ravi
on 16 May 2019
Answer using filter() was posted earlier but the OP claimed that it wasn't fast enough as the for loop.
Adam Danz
on 16 May 2019
I ran both versions through a speed tests where each version was executed 100,000 times and then the median speeds were compared. The loop method is 1.6 times faster (p<0.001, Wilcox signed rank) on my machine with a difference of 0.004 milliseconds.
Jos (10584)
on 16 May 2019
Thanks Adam :-) Did you exclude the copying of u and the add the initial (weird?) offset to u(1) directly? That would speed things up a little, I presume.
@madhan, sorry, I missed that post, apparently ....
Jos (10584)
on 16 May 2019
Internally filter uses a loop, for sure. I also expect error checks etc, that are omitted in the matlab for-loop. But still, it is pretty fast, and nice of course :-)
ektor
on 16 May 2019
No, the loop is still faster. As Jos mentioned, there's overhead computations in filter() that aren't needed in your loop.
It's a MYTH that loops are always slower than alternatives.
If you want something neat and tidy, use Jos' solution. If you want something that will save you fractions of microseconds and something you already understand, use your loop.
Jos (10584)
on 17 May 2019
btw, regarding execution time, you should also include the pre-allocation of the array :-D
Luna
on 17 May 2019
+1 Jos :)
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