How to compute the Euclidean Distance separately by using pdist function?

Hi everyone, I got a question when using pdist, it would be so many thanks if you could give me some advice. The pdist(D) usually gives the sum of the distance for the multiple dimension, however, I want to get the distance separately. For example I have a data set S which is a 10*2 matrix , I am using pdist(S(:,1)) and pdist(S(:,2)) to get the distance separately, but this seems very inefficient when the data has many dimensions. Is there any alternative way to achieve this more efficient? Thanks in advance!

Answer 1

[Image Analyst]

Use pdist2():

allDistances = pdist2(S, S);

[Zhida DENG]

Thank you! but this has same results with squareform(pdist(S)) which are not I wanted. I am seeking the results of S(1,1) - S(2,1) and S (2,1) -S(2,2) separately.