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The K-D tree is a good data structure for solving this. However you can't blindly apply the search procedure only to the center point, you must be a bit smarter. While searching the K-D tree for your points, every time you must choose the left or right child to search in, check whether the splitting plane is to the left of your circle, intersects it, or is ...


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Use changepoint detection. This will identify the boundaries between the clusters.


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Set threshold to, say 30 (arbitrary value greater than noise in the plot) and start from left to right, if value is greater than threshold, keep it as run - collect data to temporary array, if values drop below threshold then discard data and create new array for another run. This will cut 5 bars and discard data between, if you want to keep data, you have ...


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