Effacer les filtres
Effacer les filtres

Running calculations over columns

5 vues (au cours des 30 derniers jours)
William Sheehan
William Sheehan le 14 Août 2018
Commenté : Stephen23 le 17 Août 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

Réponse acceptée

Naman Chaturvedi
Naman Chaturvedi le 17 Août 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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