MATLAB: Using randsample on a matrix of weights

matrixrandsamplevectorize

Hi,
I have some code like this:
for k = 1:p
    new_index = randsample([1:n,nan],1,true,tot_weights(k,:));
    curr_indexes(k) = new_index;
    if ~isnan(new_index)
        currx(k) = x(i,new_index);
        curry(k) = y(i,new_index);
    else 
        currx(k) = nan;
        curry(k) = nan;  
    end
end
where tot_weights is a p x n matrix that has the weights for the sampling. I am trying to get rid of the for loop and vectorize the function. Basically I just want to get a total of p values that are between 1 to n or nan. The probability for the kth value to be a certain value is given by the weights in the kth row of tot_weights.
Any suggestions would be greatly appreciated! Right now, this for loop takes an annoying amount of time to run.
Cheers,
Sam

Best Answer

it doesn't seem like the assignment statement has any reason to be in the loop. Pulling it out may save a decent amount of time (especially if nan is common):
% sample each row of tot_weights
% there may be a direct way to sample a weight matrix like this loop-free, but I don't know it
for k = 1:p
    curr_indexes(k) = randsample([1:n,nan],1,true,tot_weights(k,:));
end
% set currx and curry to all-nans of the correct size
currx = nan(1,p);
curry = nan(1,p);
% update currx where curr_indexes is not nan
% fill these with curr_indexes of x (excluding places where curr_indexes is nan)
currx(~isnan(curr_indexes)) = x(i,curr_indexes(~isnan(curr_indexes)))
% same for curry
curry(~isnan(curr_indexes)) = y(i,curr_indexes(~isnan(curr_indexes)));
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