Vectorization of this loop
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The following loop calculates the distance and angle values of every location from a point and stores in arrays named Radius and theta. This loop is called nearly 3600 times in the code. This loop is effecting the performance of the code. Please suggest some ways to vectorise this loop.
xwidth and ywidth varies from 500 to 750. So, memory needed is also very high. Please suggest ways to decrease the memory needed.
x1=0;
y1=1;
inj_x=round(xwidth/2.0);
inj_y=round(ywidth/2.0);
Radius=zeros(ywidth,xwidth);
theta=zeros(ywidth,xwidth);
for r=1:ywidth
for c=1:xwidth
x2=r-inj_y;
y2=c-inj_x;
Radius(r,c)=(x2^2+y2^2)^.5;
theta(r,c)=mod(atan2(x1*y2-x2*y1,x1*x2+y1*y2),2*pi);
end
end
Thanks in advance
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採用された回答
Andrei Bobrov
2012 年 4 月 18 日
in your case
r = (1:ywidth).' - round(ywidth/2);
c = (1:xwidth) - round(xwidth/2);
Radius = bsxfun(@hypot,r,c);
theta = mod(bsxfun(@atan2,-r,c),2*pi);
その他の回答 (2 件)
Honglei Chen
2012 年 4 月 18 日
x1=0;
y1=1;
inj_x=round(xwidth/2.0);
inj_y=round(ywidth/2.0);
[x2,y2] = ndgrid((1:ywidth)'-inj_y,(1:xwidth)'-inj_x);
Radius=(x2.^2+y2.^2).^.5;
theta=mod(atan2(x1.*y2-x2.*y1,x1.*x2+y1.*y2),2*pi);
Jan
2012 年 4 月 18 日
For a fair speed comparison cleanup the loops:
- move all repeated calculation outside
- SSQRT() is faster than ^0.5
twoPi = 2 * pi;
for r = 1:ywidth
x2 = r - inj_y;
x2_2 = x2 * x2;
x1x2 = x1 * x2;
y1x2 = y1 * x2;
for c = 1:xwidth
y2 = c-inj_x;
Radius(r,c) = sqrt(x2_2 + y2^2);
theta(r,c) = mod(atan2(x1*y2 - y1x2, x1x2 + y1*y2), twoPi);
end
end
Perhaps a partial vectorization is fastest:
twoPi = 2*pi;
for c = 1:xwidth
y2 = c-inj_x;
x2 = transpose(1-inj_y:ywidth - inj_y);
Radius(:,c) = sqrt(x2.^2 + y2^2);
theta(:,c) = mod(atan2(x1*y2-x2*y1, x1*x2+y1*y2), twoPi);
end
And fully vectorized:
x2 = transpose(1 - inj_y:ywidth - inj_y);
y2 = 1 - inj_x:xwidth - inj_x;
Radius = sqrt(bsxfun(@plus, x2 .^ 2 + y2 .^ 2);
k1 = bsxfun(@minus, x1 * y2, y1 * x2);
k2 = bsxfun(@plus, x1 * x2, y1 * y2);
theta = mod(bsxfun(@atan, k1, k2), 2*pi);
And if x1 and y1 are really fixed to 0 and 1 this can be simplified.
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