Introduction & Test Setup To perform memory tests to inquire about the points raised in the question, let’s define the inputs A and B: A = rand(M,N) B = rand(1,N) Here, M and N are the size parameters and are kept as really large numbers. I would be using repmat for comparisons as that seems … Read more
Here is vectorized implementation for computing the euclidean distance that is much faster than what you have (even significantly faster than PDIST2 on my machine): D = sqrt( bsxfun(@plus,sum(A.^2,2),sum(B.^2,2)’) – 2*(A*B’) ); It is based on the fact that: ||u-v||^2 = ||u||^2 + ||v||^2 – 2*u.v Consider below a crude comparison between the two methods: … Read more
Send x to the third dimension, so that singleton expansion would come into effect when bsxfun is used for multiplication with A, extending the product result to the third dimension. Then, perform the bsxfun multiplication – val = bsxfun(@times,A,permute(x,[3 1 2])) Now, val is a 3D matrix and the desired output is expected to be … Read more
A somewhat clearer way to do this is to use a loop A = rand(3,4); B = rand(3,4); [sortedA,ind] = sort(A,2); for r = 1:size(A,1) B(r,:) = B(r,ind(r,:)); end Interestingly, the loop version is faster for small (<12 rows) and large (>~700 rows) square arrays (r2010a, OS X). The more columns there are relative to … Read more
There are three reasons I use bsxfun (documentation, blog link) bsxfun is faster than repmat (see below) bsxfun requires less typing Using bsxfun, like using accumarray, makes me feel good about my understanding of MATLAB. bsxfun will replicate the input arrays along their “singleton dimensions”, i.e., the dimensions along which the size of the array … Read more
Introduction The debate on whether bsxfun is better than repmat or vice versa has been going on like forever. In this post, we would try to compare how the different built-ins that ship with MATLAB fight it out against repmat equivalents in terms of their runtime performances and hopefully draw some meaningful conclusions out of … Read more