Corrcoef in Matlab is very slow

Question

I have the following code:

for k = 1:256
            for t = 1:10000
                % R matrix
                buffer = corrcoef(matrixA(:,k),matrixB(:,t));
                correlation_matrix(k,t)  = buffer (2,1);
            end
        end

I calculate the pearson correlation of the columns of two matrices. This works fine for me and the results are correct. However the process seems to be very very slow. Does anyone have an idea how to accelerate the calculations here?

score 3 · Accepted Answer · answered Jun 10 '15 at 13:05

3

You can remove the loop entirely by using corr from the stats toolbox

>> matrixA = randn(100, 256);
>> matrixB = randn(100, 10000);
>> size(corr(matrixA, matrixB))
ans =

   256   10000

answered Jun 10 '15 at 13:05

Chris Taylor

46,912
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score 1 · Answer 2 · answered Jun 10 '15 at 12:33

1

Just concatenate the matrices, calculate all the correlations in one operation, and then extract the relevant ones.

>> matrixA = rand(100,256);
>> matrixB = rand(100,10000);
>> matrixC = [matrixA,matrixB];
>> c = corrcoef(matrixC);
>> correlation_matrix = c(1:256, 257:10256)

Should be quite a lot faster.

answered Jun 10 '15 at 12:33

Sam Roberts

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Thank you very much. It works but one gets a "out of memory exception" for large matrices. Using just corr is much more efficient. – JoeLiBuDa Jun 10 '15 at 16:15

Corrcoef in Matlab is very slow

2 Answers2