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Many threads here show that accumarray is the answer in matlab for grouping (and calculating) values by index sets. As this works fast and fine, I need to have somethin similar for bigger (ND) data-fields.
Let's assume an example: We have a names-vector with (non unique) names inside and a data vector of earnings for different projects columnwise

names=str2mat('Tom','Sarah','Tom','Max','Max','Jon');
earnings=[100 200 20;20 100 500;1 5 900; 100 200 200;200 200 0; 300 100 -250];

and now we want to calculate the column-sums for each name.
Okay, we can find out the indices by

[namesuq,i1,i2]=unique(names,'rows')

but after that, the obvious call

accumarray(i2,earning)

is not working. One could of course use a for-loop over the unique names or the rows, but that might be a little bit inefficient. Are there better ideas?
Additionally I tried

accumarray(i2,@(i)earnings(i,:))

but this is not implemented and results in

Error using accumarray
Second input VAL must be a full numeric, logical, or char vector or scalar.

Thanks for ideas.

Additions: Thanks to eitan-t for his solution which is great for the example.
So sad, my minimum working example did not show all needs: The function which I want to aplly needs a whole row or later maybe a complete maxtrix, which I need to group over a 3rd or even higher dimension.

Maybe to make that clearer: Think of a matrix M in size a x b x c and each entry in a corresponds to a name or so. My need is best described for example summing up for all unique names.
Naive programming would be

nam=unique(names);
for ind=1:size(nam,2)
    N(ind,:,:)=sum(M(nam(ind)==names,:,:),1);
end

Is this clear? Are there solutions herefor?

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Bastian Ebeling
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  • possible duplicate of [MATLAB find and apply function to values of repeated indices](http://stackoverflow.com/questions/16086874/matlab-find-and-apply-function-to-values-of-repeated-indices) – Eitan T Aug 27 '13 at 11:24

1 Answers1

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Based on this answer, the solution you're looking for is:

[namesuq, i1, i2] = unique(names, 'rows');
[c, r] = meshgrid(1:size(earnings, 2), i2);
y = accumarray([r(:), c(:)], earnings(:));

where the rows match names(i1, :).

Example

%// Sample input
names = str2mat('Tom', 'Sarah', 'Tom', 'Max', 'Max', 'Jon');
earnings = [100 200 20; 20 100 500; 1 5 900; 100 200 200; 200 200 0; 300 100 -250]

%// Sum along columns by names 
[namesuq, i1, i2] = unique(names, 'rows');
[c, r] = meshgrid(1:size(earnings, 2), i2);
y = accumarray([r(:), c(:)], earnings(:))

The resulting sums are:

y =
   300   100  -250
   300   400   200
    20   100   500
   101   205   920

which correspond to names(i1, :):

ans =
    Jon  
    Max  
    Sarah
    Tom
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Eitan T
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  • Thanks for your fast answer and sorry for asking an already answered one. Further I was a bit too fast: Is there another chance to get that *without* scaler indexing? I have a function to apply, which would neet a whole column (what was not clear from the example). – Bastian Ebeling Aug 27 '13 at 11:47
  • Do you mean that you want to apply a function a group of values (for instance, apply it on `[100; 1]` in the first column for Tom, etc...)? Could you provide a clearer description of what you expect to obtain? – Eitan T Aug 27 '13 at 11:54
  • Hi Eitan, are you still reading? Have you got my update? Suggestions? Thanks in advance. – Bastian Ebeling Aug 29 '13 at 08:28
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    @BastianEbeling Of course, I just hadn't spare time to reread. I'll do my best to get to it today! :) – Eitan T Aug 29 '13 at 09:06