Map a 2D matrix into 3D using loop for allotment along the 3rd dimension
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I am not able to map a 2D matrix into a 3D, in which I want the particular columns of original 2D matrix to be selected and separated by using 3rd dimension (or in other words breaking a continous data into trials based on columns' selection). I used to get it before, but somehow, I am facing trouble while doing this- it throws an error of "Subscripted dimension error mismatch". But, if I do allotment along the 3rd dimension, size mismatch in other 2 dimensions should not create a problem, this is what I think.
I am now doubtful after getting the dimension mismatch error for it in matlab.
My code is somewhat like this:
% data is 2D matrix of size 7*1298779
for i=1:20
data_trialwise(:,:,i)=data(:,begin(i):end(i)); % begin and end both have 20 elements with values less than the number of columns in data
end
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Turlough Hughes
2019-12-6
I would wager that the way you have generated begin and end do not provide an equal number of indices between them on each iteration. Try subtract the two to see if this is the case. Otherwise can you attach the variables?
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Turlough Hughes
2019-12-7
The best way to deal with that is to use a cell array. I've also just renamed 'end' to 'idxend' and 'i' to 'c' as these are predefined in matlab.
clear data_trialwise
for c=1:20
data_trialwise{c,1}=data(:,begin(c):idxend(c));
end
Alternatively, you could preallocate space in data_trialwise so the max(idxend-begin)+1 is assigned to the second dimension, but you would have extra columns of zeros where a given trial had less than 2572 samples.
clear data_trialwise
data_trialwise=zeros(7,max(idxend-begin)+1,20)
for c=1:20
data_trialwise(:,1:(idxend(c)-begin(c)+1),c)=data(:,begin(c):idxend(c));
end
You could also replace the above zeros function with
data_trialwise=NaN(7,max(idxend-begin)+1,20);
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