Combining masks in 4D matrix

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Jlil 2023-3-7

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1924600-combining-masks-in-4d-matrix

评论： Jlil 2023-3-7

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!

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Jlil 2023-3-7

500 mm was a poor abbreviation - what i meant to write what that the matrix contains 500,000,000 values.

I wrote sparse meaning that the majority of the values are false.

I have updated the post for clarity on both these items - thanks

I am assuming that nested for loops will be a poor way of handling so many values across four dimensions but havent really tested. I was assuming that there were better ways maybe with vectorization of handling this.

Jan 2023-3-7

Don'toverestimate vectorization. If large temporary arrays are created, the code can be slower than with loops.

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Answer 1

Jan 2023-3-7

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1924600-combining-masks-in-4d-matrix#answer_1187550

编辑：Jan 2023-3-7

在 MATLAB Online 中打开

With FEX: RunLength :

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]