Extracting some points and finding some nearest elements.

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sreelekshmi ms 2020-3-8

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评论： sreelekshmi ms 2020-3-11

glass.xlsx

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);

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回答（1 个）

Image Analyst 2020-3-8

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https://ww2.mathworks.cn/matlabcentral/answers/509695-extracting-some-points-and-finding-some-nearest-elements#answer_419096

在 MATLAB Online 中打开

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);