using findgroups and splitapply (or an alternative) to find the minimu value in a range of values
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Still Learning Matlab
on 29 Jun 2018
Commented: Still Learning Matlab
on 2 Jul 2018
I am using the below to find a Pareto Frontier of a large set of data (>1x10^8). The below basically pulls the minimum value of B from each distinct value of A. I am looking for help in expanding to the find the minimum value of B within a range of A values.
G = findgroups(A);
C = 1:numel(B);
OutC = splitapply(@(b,c) {c(b==min(b))}, B, C, G);
Out = cat(2, OutC{:}).';
The attached plot is the results, and is clearly NOT the actual pareto frontier. How can I implement this "binning" approach to find the minimum value of B in a range of A? Attached a subset of the data due to file size limitations
2 Comments
Image Analyst
on 29 Jun 2018
Wow - what an interesting concept - I had to look it up because I'd not heard of it before. More interesting than most questions we see here.
Anyway, have you considered the boundary() function if you just want to find some kind of outer boundary for the scattered points?
Accepted Answer
Jeff Miller
on 30 Jun 2018
Couldn't you just form a new variable Agrp which has the A values grouped into whatever bins you want? Then repeat what you are already doing, but use Agrp instead of A. As a crude example,
Agrp = round(A);
G = findgroups(Agrp);
...
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