Running calculations over columns
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    William Sheehan
 am 14 Aug. 2018
  
    
    
    
    
    Kommentiert: Stephen23
      
      
 am 17 Aug. 2018
            I currently have a running sample entropy code that works over a 300 sample point window. This works fine for matrices that contain only one column. I was wondering how I could amend the script in a way that it will calculate the running sample entropy for each column of a matrix with multiple columns. I'm guessing maybe a for loop may work in some way?
I have included the code with a sample example of data
X = randi(100,10000,1);
OutPut = SampEn(2,0.2,X,300);
function SampEnN = SampEn(dim,r,data,windowSize)
%%Set-up
correl = zeros(1,2);
[N,M] = size(data);
SampEnN = nan(N,M);
for t = windowSize+1:N
 tolerance = std(data(t-windowSize:t, :),'omitnan')*r;
 dataT = data(t-windowSize:t,:);
 dataMat = zeros(dim+1,windowSize-dim);
 for i = 1:dim+1
   dataMat(i,:) = dataT(i:windowSize-dim+i-1);
 end
 for m = dim:dim+1
   count = zeros(1,windowSize-dim);
   tempMat = dataMat(1:m,:);
   for i = 1:windowSize-m
     % calculate Chebyshev distance, excluding self-matching case
     dist = max(abs(tempMat(:,i+1:windowSize-dim) - repmat(tempMat(:,i),1,windowSize-dim-i)));
     % calculate Heaviside function of the distance
     % User can change it to any other function
     % for modified sample entropy (mSampEn) calculation
     D = (dist < tolerance);
     count(i) = sum(D)/(windowSize-dim);
   end
   correl(m-dim+1) = sum(count)/(windowSize-dim);
 end
 C = log(correl(1)/correl(2));
 SampEnN(t,:) = C;
end
end
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Akzeptierte Antwort
  Naman Chaturvedi
    
 am 17 Aug. 2018
        Hi,
If you don't want to change the function, you can use the following for loop code to compute the desired output.
output=[];
for i=1:size(X,2)
    output=[output SampEn(2,0.2,X(:,i),300)];
end
Hope this helps.
You can also modify(generalize) your function to calculate for any 2d array. MATLAB inbuilt functions work along columns and hence can generate column-wise results for a matrix.
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