I’m working on a MATLAB project and I’m stuck. I’ve got two arrays, let’s call them start_points and end_points. They’re the same length, and I need to create sequences between each corresponding pair from these arrays.
For instance, if I have:
start_points = [3, 8];
end_points = [6, 10];
I aim to get something like:
result = [3 4 5 6 8 9 10];
I understand I could loop through the pairs, but I’m looking for a more efficient method, perhaps using a built-in function or vectorization. I’ve already tried using the colon operator directly with the arrays, but that approach didn’t work. Any suggestions on how to achieve this, especially with larger arrays? Thanks for the help!
hey charlottew, have u tried using arrayfun? it’s pretty neat for this kinda stuff. something like:
result = unique(cell2mat(arrayfun(@(x,y) x:y, start_points, end_points, ‘UniformOutput’, false)));
this should do the trick without loops. lmk if it helps!
I’ve faced a similar challenge in my MATLAB work before. While arrayfun is a good suggestion, I found that using bsxfun with the colon operator can be even more efficient, especially for larger arrays. Here’s what worked for me:
result = unique(reshape(bsxfun(@colon, start_points(:), end_points(:))', , 1));
This approach leverages MATLAB’s vectorization capabilities, making it quite fast. It creates a matrix where each row is a sequence, then reshapes and flattens it into a single column. The unique function at the end ensures no duplicates if your sequences overlap.
I’ve used this method in projects dealing with time series data where I needed to generate multiple sequences quickly. It scales well with larger inputs and doesn’t compromise on readability. Give it a try and see if it suits your needs!
I’ve encountered this issue before in signal processing tasks. A straightforward and efficient solution is to use cumsum and diff functions combined with logical indexing. Here’s how you can do it:
result = cumsum(accumarray(cumsum([1; diff(start_points(:)) ~= 0]), [start_points(:); end_points(:)] - [start_points(:); start_points(:)] + 1));
This approach is particularly effective for large arrays as it avoids explicit loops and utilizes MATLAB’s optimized built-in functions. It works by creating a cumulative sum of the differences between start and end points, then using logical indexing to extract the desired sequences.
I’ve found this method to be significantly faster than alternatives when dealing with extensive datasets, especially in scenarios involving multiple sequence generations. It might look complex at first, but it’s quite efficient in execution.