Extracting some points and finding some nearest elements.
1 vue (au cours des 30 derniers jours)
Afficher commentaires plus anciens
I have data I used dbscan clustering method. Now I need to find 5 different elements from each cluster. And calculate the 5 nearest elements of each point and group it.
In the below figure there are some points marked(pencil marked)and grouped the 5 elements(black round).
[I marked only 3 clusters just for example, I need it in the full clusters.]
After that how can I remove those clusters that do not have 5 nearest elements? Anybody, please help me.
clc;
clear;
data=xlsread('glass.xlsx');
minpts=6;
epsilon=4;
[idx, corepts] = dbscan(data,epsilon,minpts);
gscatter(data(:,1),data(:,2),idx);
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/275879/image.jpeg)
0 commentaires
Réponses (1)
Image Analyst
le 8 Mar 2020
I don't even think you need dbscan for this. You just need to define a length that separates "near enough" and "too far away". Then you just check every point in the array to see if it has 5 that are near enough, and keep those.
nearEnough = 0.02; % Whatever you want.
x = data(:,1);
y = data(:,2);
indexesToKeep = false(1, length(x)); % Initialize to not keeping any of them.
for k = 1 : length(x)
distances = sqrt((x(k) - x).^2 + (y(k) - y).^2);
if sum(distances > nearEnough) >= 5
% At least 5 are close enough to this k'th point, so keep this point.
indexesToKeep(k) = true;
end
end
x = x(indexesToKeep);
y = y(indexesToKeep);
12 commentaires
Voir également
Catégories
En savoir plus sur Statistics and Machine Learning Toolbox 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!