Can this silly accumarray for-loop be removed by a vectorization?
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I have a matrix A where some of the values in column 1 are duplicates. Where a duplicate exists in column 1 (representing a timestamp) I want to replace the corresponding values in the other columns by a mean value of the duplicates.
Right now Im doing it by identifying the unique values and then loop through the columns one by one via a temporary variable since accumarray only accepts one column at a time:
[UA,~,idx] = unique(A(:,1)); % Finds duplicates in the first column of matrix A
for i = 28:-1:2
Temp = [UA,accumarray(idx,A(:,i),[],@mean)]; % Replaces duplicates with the mean of the duplicate values in column i
B(:,i) = Temp(:,2); % Transfers the results and builds the final matrix B containing the same as A but with no duplicates
end
It is doing what I want but it is really slow, is there any simple way of rewriting it so I don’t have to deal with the for-loop?
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Accepted Answer
Sean de Wolski
on 18 Aug 2015
Edited: Sean de Wolski
on 18 Aug 2015
A = randi(32280,28);
[UA,~,idx] = unique(A(:,1));
[X,Y] = ndgrid(idx, 2:size(A,2));
newcolumns = accumarray([X(:), Y(:)], reshape(A(:,2:end),[],1), [], @mean);
The ndgrid needs to start in the second column and only extract the 2nd through end columns of A for vals.
More Answers (2)
Kelly Kearney
on 18 Aug 2015
I'm not sure if it will be faster, but you may try my aggregate function. It only calls accumarray once under the hood, though, using indices to make the application to multiple columns a little more efficient.
[~, B] = aggregate(A(:,1), A, @(x) mean(x,1));
B = cat(1, B{:});
Walter Roberson
on 17 Aug 2015
colidx = repmat(1:size(A,2), size(A,1), 1);
newcolumns = accumarray([idx, colidx(:)], reshape(A(2:end,:),[],1), [], @mean);
output = [UA, newcolumns];
3 Comments
Walter Roberson
on 17 Aug 2015
Hmmm... Try
[X,Y] = ndgrid(idx, 1:size(A,2));
newcolumns = accumarray([X(:), Y(:)], reshape(A(2:end,:),[],1), [], @mean);
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