# split a matrix into two matrices according to some rule

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Alberto Acri am 12 Feb. 2024
Kommentiert: Cris LaPierre am 12 Feb. 2024
How can I generate two separate matrices, one containing the coordinates of line A and the other of line B?
figure
plot3(matrix(:,1),matrix(:,2),matrix(:,3),'k.','Markersize',5);
axis equal
grid off
I wanted to try this way but it does not seem the best way.
% range
xRange = [xmin xmax];
yRange = [ymin ymax];
zRange = [zmin zmax];
% indices of points in the range
idx = matrix(:,1) >= xRange(1) & matrix(:,1) <= xRange(2) & ...
matrix(:,2) >= yRange(1) & matrix(:,2) <= yRange(2) & ...
matrix(:,3) >= zRange(1) & matrix(:,3) <= zRange(2);
select_matrix = [matrix(idx,1), matrix(idx,2), matrix(idx,3)];
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Alberto Acri am 12 Feb. 2024
Hi Stephen! sorry, I realised I had not installed 'Image Processing Toolbox'!
Alberto Acri am 12 Feb. 2024
I wanted to know if there is a way to get the subdivision! I don't have any 'rules' at the moment!

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### Akzeptierte Antwort

Cris LaPierre am 12 Feb. 2024
Bearbeitet: Cris LaPierre am 12 Feb. 2024
I would look into clustering. Here is an attempt that uses dbscan, a spectral clustring algorithm included in the Statistics and Machine Learning Toolbox.
You can learn more about this and other clustering techniques in our Practical Data Science with MATLAB specialization on Coursera. It's free to enroll. Here is a link to the video Introdcution to Clustering Algorithms.
% view the raw data
plot3(matrix(:,1),matrix(:,2),matrix(:,3),'k.','Markersize',5);
% use dbscan to identify clusters
idx = dbscan(matrix,1.5,5);
gscatter(matrix(:,1),matrix(:,2),idx)
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Cris LaPierre am 12 Feb. 2024
If you know the number of clusters already, use spectralcluster.
idx = spectralcluster(matrix,2);
gscatter(matrix(:,1),matrix(:,2),idx)

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