Vectorizing evaluation of cell array of functions
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I have an S-by-1 cell array of function handles, each taking one argument---call it 'funcell'. I also have an S-by-1 vector of numeric values---call it 'inputs'. My goal is to obtain a numeric vector of size S-by-1---call it 'output', such that each element j of 'output' contains the corresponding function evaluated at the corresponding numeric value.
In a for loop, this would just be:
for j=1:S
output(j)=funcell{j}(inputs(j))
end
The problem is that S is very large, so this is slow. Is there a way to vectorize this process for speed?
1 Comment
Bruno Luong
on 19 Sep 2019
Edited: Bruno Luong
on 19 Sep 2019
"The problem is that S is very large, so this is slow. Is there a way to vectorize this process for speed?"
This is again a wrong preconceived slowness of FOR-LOOP. It is slow because you evaluate many function handles not because it is embeded in a FOR-LOOP.
Answers (1)
James Tursa
on 18 Sep 2019
Edited: James Tursa
on 18 Sep 2019
Not sure this will be any faster since the loop is just hidden, but you can try this:
output = arrayfun(@(x,y)x{1}(y),funcell,inputs);
Did you pre-allocate output before your loop? I'm assuming your example was a typo and was supposed to read:
output(j)=funcell{j}(inputs(j))
2 Comments
Bruno Luong
on 19 Sep 2019
It yields a modest speed-up
Expected, because the slowness is NOT due to the for-loop.
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