% Compute KL distace D(p||q) = sum_x(p(x)*log2(p(x)/q(x))
% Input:
%	 data - m x n numeric data matrix 
%	        each element has to be positive 
% Output:
%	  kl - Kullback-Leibler divergence
%		m x 1 log base 2 used
%
% Date: 3/1/2006

function kl = my_mediankl(data)

	[m n] = size(data);
	kl = zeros(m, 1);

	% check each element 
	for i=1:m
		for j=1:n
			if data(i,j) <= 0
				disp('data has to be positive');
				return;
			end
		end
	end

	% take the median of each column
	medians = median(data);
	
	% normalize each row by the sum
	for i=1:m
		total = sum(data(i,:));
		for j=1:n
			data(i,j) = data(i,j) / total;
		end
	end
	
	% also normalize medians
	medians = medians / sum(medians);
	
	% calculate Kullback-Leibler divergence for each row
	for i=1:m
		for j=1:n
			kl(i) = kl(i) + data(i, j) * log2(data(i, j) / medians(j));
		end
	end