Replacing
MinDist=[MinDist sqrt(min(sum(DIFF.^2,2)))];
by
MinDist=[MinDist sqrt(min(sum(DIFF.*DIFF,2)))];
will be at least twice faster. Crunching elapsed time could be done by
using parallel_run (with 5.5.2 version) if you have a multi-core processor.
S.
Le 31/01/2018 à 09:36, Dang Ngoc Chan, Christophe a écrit :
Hello,
The following suggestions will probably not have a drastic influence
(I don't see how it could be more vectorised)
but his a little thing I see:
De : users [mailto:[email protected]] De la part de Heinz Nabielek
Envoyé : mercredi 31 janvier 2018 00:13
MinDist=[MinDist sqrt(min(sum(DIFF.^2,2)))];
Maybe you could concatenate the squares of the distance
and then compute the square root of the whole vector in the end:
sqMinDist=[sqMinDist min(sum(DIFF.^2,2))];
…
end
…
MinDist = sqrt(sqMinDist)
Hope this helps,
Regards
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Mechanical calculation engineer
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Stéphane Mottelet
Ingénieur de recherche
EA 4297 Transformations Intégrées de la Matière Renouvelable
Département Génie des Procédés Industriels
Sorbonne Universités - Université de Technologie de Compiègne
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