Find the maximum value in each group of a big matrix
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I have a big matrix and I'm looking for an easy way to group them by a certain way then find the maximum in each group. I have created this code but I got stuck. Anyway to help please. I need to know the indexes of all the maximum points to extract more information from the big matrix.
data = randn(10,1)*10;
edges = 0:5:35';
Y = discretize(data,edges);
[B,I] = sort(Y);
SortedMatrix = [B data(I)];
5 件のコメント
Jan
2019 年 4 月 26 日
編集済み: Jan
2019 年 4 月 26 日
So is sortedMatrix your actual input data? Or do you want to process data, which is set to a random array for a demonstration?
It would be easier, if you avoid to create the NaNs, e.g. by adding a final edge Inf. Then splitapply(@max, data(I), B) would solve the problem.
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Jan
2019 年 4 月 26 日
編集済み: Jan
2019 年 4 月 26 日
data = randn(10,1)*10;
edges = [-Inf, 0:5:35, Inf];
Y = discretize(data, edges);
Result = accumarray(Y, data, [], @max)
I'm confused that this does not work reliably with splitapply:
Result = splitapply(@max, data, Y)
It fails with an error message, if an interval is empty:
For N groups, every integer between 1 and N must occur at least
once in the vector of group numbers.
2 件のコメント
Rik
2019 年 4 月 26 日
I was thinking way too complicated here. This was the start of my idea:
nanflag=false;
if any(isnan(B))
replaceNaN=max(B)+1;
B(isnan(B))=replaceNaN;
nanflag=true;
end
b=accumarray(B,Y,[],@max,NaN);
After which removal of empty lines (and putting back the NaN) to get to the desired output should be easy.
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