how to efficiently vectorize nested for loops
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Hi everyone,
I am practicing vectorize programing and i faced a code that became a challenge for me,
this is the code in normal mode which runs correctly:
for t = 1:N
A(t,:) = a; B(t,:) = b; C(t,:) = c;
S = 0;
for i=1:2
for j=1:2
for k=1:2
M =((-1) ^ i).*((-1) ^ j).*((-1) ^ k);
R = sqrt((a(i))^2+(b(j))^2+(c(k))^2);
N = atan( (a(i) * b(j)) / (c(k) * R) );
S = S + R*sin(N/M);
end
end
end
end
here A,B and C are (N*2) data arrays.
first i dont know the general strategy when having more than 2 for loops.
and how can i rewrite the terms M and R and N for this example how can i write this code in effective way.
Thank you
采纳的回答
Walter Roberson
2019-9-2
编辑：Walter Roberson
2019-9-2
[aG, bG, cG] = ndgrid(a, b, c);
[iG, jG, kG] = ndgrid(1:size(a,2), 1:size(b,2), 1:size(c,2));
M = (-1).^(iG + jG + kG);
R = sqrt(aG.^2 + bG.^2 + cG.^2);
N = atan2(aG .* bG, cG .* R);
RS = R .* sin(N .* M); %with M being -1 or +1, multiplication is faster than division
S = sum(RS(:));
However, please check your equations to see whether atan2(y,x) makes sense instead of atan(y./x). The difference would be in the quadrant, which would affect the sign of the sin().
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