Sorting set of points

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Mahdi Skayni
Mahdi Skayni el 29 de Mzo. de 2021
Respondida: Abhinaya Kennedy el 19 de Ag. de 2024
Hello,
I have these set of red points that are saved in one variable. I want to separate them, close one in one variable and so on.
Any idea Please

Respuestas (1)

Abhinaya Kennedy
Abhinaya Kennedy el 19 de Ag. de 2024
To separate the clusters of red points into individual variables in MATLAB, you can use logical indexing or clustering techniques.
  1. Identify the clusters: You can manually identify the clusters based on their coordinates or use a clustering algorithm like "k-means" (https://www.mathworks.com/help/stats/kmeans.html).
  2. Separate the clusters: Use logical indexing to separate the points into different variables. For example:
% Assuming your points are stored in a variable called 'points'
% points is an Nx2 matrix where each row is a point (x, y)
% Example points (replace this with your actual data)
points = [1, 2; 2, 3; 3, 4; 10, 10; 11, 11; 12, 12; 20, 20; 21, 21; 22, 22];
% Number of clusters (adjust based on your data)
numClusters = 3;
% Perform k-means clustering
[idx, C] = kmeans(points, numClusters);
% Separate points into different variables based on cluster index
cluster1 = points(idx == 1, :);
cluster2 = points(idx == 2, :);
cluster3 = points(idx == 3, :);
% Display the clusters
figure;
hold on;
scatter(cluster1(:,1), cluster1(:,2), 'r');
scatter(cluster2(:,1), cluster2(:,2), 'g');
scatter(cluster3(:,1), cluster3(:,2), 'b');
legend('Cluster 1', 'Cluster 2', 'Cluster 3');
hold off;
This code uses "k-means" clustering to separate the points into three clusters. You can adjust the number of clusters ("numClusters") based on your data. Each cluster is then stored in a separate variable ("cluster1", "cluster2", "cluster3").
Adjust the code to fit your specific dataset and requirements.

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