Help needed to decrease computational time by removing for loops
1 view (last 30 days)
Show older comments
Hello Everyone, I have written following 40 lines of matlab code. It is working fine. Only problem is computational costs is very high for nx=1024 and ny=1024 number of points. I believe it is because of the multiple for loops that I have used. Can anybody please suggest me better coding practice to minimize computational time for this code when nx=1024?
tic
nx=512+1;
ny=nx;
dx=(2-(-2))/(nx-1);
dy=dx;
x=-2:dx:2;
y=-2:dy:2;
[Y,X]=meshgrid(x,y);
A=ones(nx,ny);
P=sqrt(A-X.^2-Y.^2);
P=real(P);
Hact=zeros(nx,ny);
error=0;
for i=1:1:(length(X)+1)/2
for j=1:1:(length(Y)+1)/2
Xp=X+(-X(i,j)+dx/2)*A;
Yp=Y+(-Y(i,j)+dy/2)*A;
Xm=X+(-X(i,j)-dx/2)*A;
Ym=Y+(-Y(i,j)-dy/2)*A;
E1=(Xp).*log((Yp+sqrt(Yp.^2+Xp.^2))./(Ym+sqrt(Ym.^2+Xp.^2)));
E2=(Xm).*log((Ym+sqrt(Ym.^2+Xm.^2))./(Yp+sqrt(Yp.^2+Xm.^2)));
E3=(Yp).*log((Xp+sqrt(Xp.^2+Yp.^2))./(Xm+sqrt(Xm.^2+Yp.^2)));
E4=(Ym).*log((Xm+sqrt(Ym.^2+Xm.^2))./(Xp+sqrt(Xp.^2+Ym.^2)));
K=(2/pi^2)*(E1+E2+E3+E4);
G(i,j)=sum(sum(K.*P));
end
end
et=toc;
I1=G(:,1:end-1);
I1=fliplr(I1);
I2=G(1:end-1,:);
I2=flipud(I2);
I3=G(1:end-1,1:end-1);
I3=rot90(I3,2);
D=[G I1;I2 I3];
Ho=(-1)*A;
H=Ho+0.5*X.^2+0.5*Y.^2+D;
for i=1:1:nx
for j=1:1:ny
if (X(i,j)^2+Y(i,j)^2 <= 1)
error=error+dx*dy*abs(H(i,j)-0);
end
end
end
0 Comments
Answers (2)
Seyedali Mirjalili
on 2 Mar 2018
You can use the concept of vectorization. Here is an example:
With for loop:
for k = 1 : 10
a(k) = k ^ 2;
end
Vectorized version:
k = 1 : 10;
a = k .^ 2
Good luck
0 Comments
Seyedali Mirjalili
on 2 Mar 2018
By the way, if you want to check the speed, just write:
tic
// code fragment for either for loop of vectoriaed version.
toc
0 Comments
See Also
Categories
Find more on Loops and Conditional Statements in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!