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matlabmaxminsummary

Index from accumarray with max/min


I have a vector and a cell array (with repeating strings) with the same size. The cell array defines the groups. I want to find min/max values in the vector for each group.

For example:

value = randperm(5) %# just an example, non-unique in general
value =
     4     1     2     3     5
group = {'a','b','a','c','b'};
[grnum, grname] = grp2idx(group);

I use ACCUMARRAY function for this:

grvalue = accumarray(grnum,value,[],@max);

So I have new cell array with unique group name (grname) and new vector (grvalue).

grname = 
    'a'
    'b'
    'c'
grvalue =
     4
     5
     3

But I also need to find location index of values from old vector that has been included into the new vector.

gridx = 1 5 4

Any ideas? It's not necessary to use accumarray but I'm looking for fast vectorized solution.


Solution

  • The best vectorized answer I can see is:

    gridx = arrayfun(@(grix)find((grnum(:)==grix) & (value(:)==grvalue(grix)),1),unique(grnum));
    

    but I cannot call this a "fast" vectorized solution. arrayfun is really useful, but generally no faster than a loop.


    However, the fastest answer is not always vectorized. If I re-implement the code as you wrote it, but with a larger data set:

    nValues = 1000000;
    value = floor(rand(nValues,1)*100000);
    group = num2cell(char(floor(rand(nValues,1)*4)+'a'));
    tic;
    [grnum, grname] = grp2idx(group);
    grvalue = accumarray(grnum,value,[],@max);
    toc;
    

    My computer gives me a tic/toc time of 0.886 seconds. (Note, all tic/tock times are from the second run of a function defined in a file, to avoid one-time pcode generation.)

    Adding the "vectorized" (really arrayfun) one line gridx computation leads to a tic/tock time of 0.975 seconds. Not bad, additional investigation shows that most of the time is being consumed in the grp2idx call.

    If we reimplement this as a non-vectorized, simple loop, including the gridx computation, like this:

    tic
    [grnum, grname] = grp2idx(group);
    grvalue = -inf*ones(size(grname));
    gridx = zeros(size(grname));
    for ixValue = 1:length(value)
        tmpGrIdx = grnum(ixValue);
        if value(ixValue) > grvalue(tmpGrIdx)
            grvalue(tmpGrIdx) = value(ixValue);
            gridx(tmpGrIdx) = ixValue;
        end
    end
    toc
    

    the tic/toc time is about 0.847 seconds, slightly faster than the original code.


    Taking this a bit further, most of the time appears to be lost in the cell-array memory access. For example:

    tic; groupValues = double(cell2mat(group')); toc  %Requires 0.754 seconds
    tic; dummy       =       (cell2mat(group')); toc  %Requires 0.718 seconds
    

    If you initially define your group names as a numeric array (for example, I'll use groupValues as I defined them above), the the times decrease quite a bit, even using the same code:

    groupValues = double(cell2mat(group'));  %I'm assuming this is precomputed
    tic
    [grnum, grname] = grp2idx(groupValues);
    grname = num2cell(char(str2double(grname))); %Recapturing your original names
    grvalue = -inf*ones(size(grname));
    gridx = zeros(size(grname));
    for ixValue = 1:length(value)
        tmpGrIdx = grnum(ixValue);
        if value(ixValue) > grvalue(tmpGrIdx)
            grvalue(tmpGrIdx) = value(ixValue);
            gridx(tmpGrIdx) = ixValue;
        end
    end
    toc
    

    This produces a tic/tock time of 0.16 seconds.