Extracting some points and finding some nearest elements.
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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)
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Answers (1)
Image Analyst
on 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);
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