I've encountered this several times, and it always bothers me. Say for example I want to sum each row of matrix A, for values less than 0.5:
But it feels like I should be able to simplify this, with something like:
row_sum = sum( A(A<0.5), 2 );
but this obviously fails because while A<0.5 preserves shape, A(A<0.5) returns a vector where the A<0.5 matrix is implicitly linearized.
I get why this happens (A>0.5 elements would be undefined in a matrix), but it seems incongruous with how logical indices are presented to the user as shape-preserving operations. After all, A<0.5 returns a logical matrix and you would need to call find(A<0.5) to acess the linear indices used to generate A(A<0.5).
In my humble opinion, it seems like this is exactly what NaN should exist for. If the default behavior of A(A<0.5) was to return NaN for A(A>0.5), then having functions like sum with 'omitnan' enabled by default would produce more intuitive results. Am I missing something?
Getting back to earth, are there any practical ways to simplify the above process?