Distance between all points in array and delete the second point if it is less that certian value (Victorized)

4 vues (au cours des 30 derniers jours)
I have this loop to calculate the distance between all of the points in R_all array and delete the second point if the distace less that 0.002, but if I have a huge number of points like 100000 it takes long time, I need to vectorize my code, if you can help me ,, thank you in advance,,
Rx=rand(n,1)*0.2;
Ry=rand(n,1)*0.2;
Rz=rand(n,1)*0.2;
R_all=[Rx Ry Rz];
n= 1000;
Df=0.002;
while j<n
i=j+1;
while i<=n
k = norm(R_all(j,:)-R_all(i,:)); %function of distance between points
if k < 1.5*Df % check the distance between all points; should not be < 1.5 Df
R_all(i,:)=[];
n=n-1;
end
i=i+1;
end
j=j+1;
end

Réponse acceptée

Rik
Rik le 13 Nov 2019
After a few runs I think this would be equivalent to your loop version. Note that it generates a matrix of size [n n 3] in one of the steps, so memory might become an issue. The pdist function would probably help, but I don't have the statistics and machine learning toolbox.
n= 1000;
Rx=rand(n,1)*0.2;
Ry=rand(n,1)*0.2;
Rz=rand(n,1)*0.2;
R_all=[Rx,Ry,Rz];
Df=0.002;
%calculate distance matrix for every point pair
A=permute(R_all,[1 3 2]);
B=permute(R_all,[3 1 2]);
dist=sqrt( sum( (A-B).^2 , 3) );
%mask the distance to the point itself and to all previous points
dist(1:(1+size(dist,1)):end)=inf;
dist(logical(triu(ones(size(dist)))))=inf;
L=dist<1.5*Df;
L=any(L,1);
R_all(L,:)=[];
  2 commentaires
Majeed
Majeed le 13 Nov 2019
Hello Rik;
I tried to run you code but it shows me error in dist=sqrt( sum( (A-B).^2 , 3) );
''Array dimensions must match for binary array op.''
this massage appears, thank you Mr. Rik
Rik
Rik le 13 Nov 2019
That means you're using a release prior to R2016b. If you're using an older version it is always a good idea to mention which release you are using.
In this case you can do the implicit expansion like this:
dist=sqrt( sum( bsxfun(@minus,A,B).^2 , 3) );

Connectez-vous pour commenter.

Plus de réponses (1)

Jeremy
Jeremy le 12 Nov 2019
Modifié(e) : Jeremy le 12 Nov 2019
Something like this?
n= 1000;
Rx=rand(n,1)*0.2;
Ry=rand(n,1)*0.2;
Rz=rand(n,1)*0.2;
R_all=[Rx Ry Rz];
Df=0.002;
Dr = diff(R_all,[],1); % compute differences between each row
% changing the third input from 1 to 2 makes diff compute column differences instead
[i,j,k] = find(Dr<1.5*Df); % get indices of out-of-tolerance lines
i = i + 1; % Delete the second of the lines that makes an OOT result
R_all(i,:) = []; % remove lines that are out-of-tolerance
  2 commentaires
Majeed
Majeed le 13 Nov 2019
Thank you Jeremy;
this code does not find a distance as a value (magnitude) to compare with 1.5 Df. also the loop that I showed in my question was calculating each point with all other points that mean calculate the distance between point 1 with all points from 2 to 1000 then point 2 with all points from 3 to 1000 and so on. many thanks for your help.

Connectez-vous pour commenter.

Catégories

En savoir plus sur Creating and Concatenating Matrices dans Help Center et File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by