how to Vectorize iterative '' coordinates transformation ''loop operation for speed

I want to transform local coordinates(tip positions) of a rotating blade into corresponding global coords. Tip coordinates and angular distance changes in time. which means there is a unique transformation matrix for every time step. hence i used loop to multiply transformation matrix (3*3) with local coords to get me global coords each time step. for accuracy reasons i need more than million transformations,which take more than 5 hours with my core i5 computer.its a 2D transformation. i need to vectorize only following part of the code.Please check attachment for complete code.
for i = 1: vec_size
M=[cos(theta_inst(i)) -sin(theta_inst(i)) dx(i);...
sin(theta_inst(i)) cos(theta_inst(i)) dy(i); ...
0 0 1]; %transformation matrix
glbl(1:3,i)= M*local(:,i); % dx,dy ~=0;
end

 Accepted Answer

In non-homogeneous coordinates,
c=cos(theta_inst(:)).'; s=sin(theta_inst(:)).';
dx=dx(:).'; dy=dy(:).';
L=local(1:2,:);
glbl = [ sum([c;-s].*L) ; sum([+s;c].*L) ]+[dx;dy] ;

4 Comments

Perfect...Thank you @Matt J. I compared results of both loop and vectorized operations. there is a difference of order 2^-16 to 2^-18 in both results. Is it because of using SUM ftn??? may be sum ftn will round off digits and hence creating a difference?
yes. difference of outputs (global coords) as calculated by iterative process (for loop) and by vectorized operation using sum function.
If it's relative error, it is likely due simply to floating point errors.

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R2018a

Asked:

on 7 Sep 2018

Commented:

on 10 Sep 2018

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