vectorizing or speeding looped code
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i am trying to speed up some code with multiple functions and have found the one that takes the most time (it is all a converted fortran code). it runs a nested for loop 4 times (each with modified input). i've had some success elsewhere in the code eliminating slow points but this one just cant get right. any ideas? (in 2016b for compatability reasons)
for II= 1:N
XP(1)= 1.0D0;
for JJ=2:IORD1
XP(JJ)=XP(JJ-1)*double(A1(II));
end
for JJ= 1:IORD1
for KK= 1:IORD1
B(JJ,KK)=B(JJ,KK)+XP(JJ)*XP(KK);
end
C(JJ)=C(JJ)+XP(JJ)*A2(II);
end
end
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Antworten (1)
Turlough Hughes
am 22 Sep. 2020
This should help, though I've already made assumptions about the sizes of arrays. How many rows/columns are in each variable?
XP(1) = 1;
for II= 1:N
XP(2:end) = XP(1:end-1)*double(A1(II));
B = B + XP(:).*XP(:).';
C = C + XP*A2(II);
end
10 Kommentare
Turlough Hughes
am 23 Sep. 2020
Verschoben: Rik
am 4 Feb. 2026 um 13:58
eqor=1 ? I assume that's MAXOR?
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