How to vectorize the MATLAB code?

6 vues (au cours des 30 derniers jours)
Sam Yeoh
Sam Yeoh le 14 Fév 2022
Commenté : Jan le 14 Fév 2022
This is the code that I have written and I saw articles about vectorization.
N = length(a);
b = zeros(1,N - 1);
for i = 1:N-1
b(i) = a(i) + a (i + 1);
end
How should I vectorize my code in this circumstance? Any suggestions? Thank you.

Réponse acceptée

Jan
Jan le 14 Fév 2022
Modifié(e) : Jan le 14 Fév 2022
a = rand(1, 11);
N = length(a);
b = zeros(1,N - 1);
for i = 1:N-1
b(i) = a(i) + a (i + 1);
end
% Vectorized 1:
b2 = a(1:end-1) + a(2:end);
% Vectorized 2:
b3 = conv(a, [1,1], 'valid')
% [EDITED] % Vectorized 3: Working only for even length of a!
% [EDITED] b4 = sum(reshape(a, 2, [])); % Not the same result!
% Thanks John D'Errico.
isequal(b, b2, b3)
ans = logical
1
For a = rand(1,1e6) and 100 repetitions, Matlab 2018b needs:
% Elapsed time is 0.683647 seconds. loop
% Elapsed time is 0.874940 seconds. 1:end-1 + 2:end
% Elapsed time is 0.477227 seconds. conv
You see, that vectorization is not a standard trick for accelerating code. The memory access can take more time than the loop.
  3 commentaires
John D'Errico
John D'Errico le 14 Fév 2022
While I gave a +1 to @Jan for the answer, b4 is incorrect.
a = rand(1, 10);
b3 = conv(a, [1,1], 'valid')
b3 = 1×9
1.0363 1.0664 0.8794 0.4572 0.8286 1.0839 0.8633 0.9137 0.8310
% Vectorized 3: Working only for even length of a!
b4 = sum(reshape(a, 2, []));
b3
b3 = 1×9
1.0363 1.0664 0.8794 0.4572 0.8286 1.0839 0.8633 0.9137 0.8310
b4
b4 = 1×5
1.0363 0.8794 0.8286 0.8633 0.8310
b4 sums the 1st and second, but NOT the 2nd and 3rd elements.
Jan
Jan le 14 Fév 2022
Thanks, John.

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