Combining masks in 4D matrix

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Jlil
Jlil on 7 Mar 2023
Commented: Jlil on 7 Mar 2023
I have a 4D matrix of logical values with dimensions [trials, channels, frequencies, time] which contains about 500,000,000 elements which are mainly false. I would like to identify when there are a number of consecutive true cells in the time dimension. The number of consecutive elements are the same for each trial and channel, but will vary depending on frequency and are held in the variable nr_of_cycles.
Here is my pseudo code:
for i_freqs = foi_idx % foi_idx are indices of the frequencies (3rd dim) where the operation is to be done
conseq_n = nr_of_cycles(i_freqs); % nr_of_cycles is a simple 1d array
% Below is the function i need help with. It needs to go through in the
% 4th dimension (time) and only keep true values when they are part of
% a group of conseq_n consecutive trues
mask(:,:,i_freqs,:) = help_me_with_this_function(mask,conseq_n);
end
So for example if mask(1,1,1,:) is [0 1 0 1 1 0 1 0 1 1 1 1 1 1 1 0 1]
then help_me_with_this_function(mask,5) should return mask so that mask(1,1,1,:) is [0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0]
thanks!
  3 Comments
Jan
Jan on 7 Mar 2023
Don'toverestimate vectorization. If large temporary arrays are created, the code can be slower than with loops.

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Accepted Answer

Jan
Jan on 7 Mar 2023
Edited: Jan on 7 Mar 2023
s = size(mask);
mask = reshape(mask, [], s(4));
for k = 1:size(mask, 1) % [EDITED 2] Typo, data->mask
[b, n] = RunLength(mask(k, :)); % [EDITED] (:,k) -> (k,:)
b(n < conseq_n) = 0;
mask(:, k) = RunLength(b, n);
end
mask = reshape(mask, s); % [EDITED 2]
Please try this. You need a C-compiler or download pre-compiled mex functions from the page mentioned in the documentation.
  3 Comments
Jlil
Jlil on 7 Mar 2023
It is, takes 5-10 seconds to run which is just fine - FEX and reshape are new to me so io learned a bit as well
Many thanks for your help!

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