computeCentroids.m

function centroids = computeCentroids(X, idx, K)
%COMPUTECENTROIDS returs the new centroids by computing the means of the 
%data points assigned to each centroid.
%   centroids = COMPUTECENTROIDS(X, idx, K) returns the new centroids by 
%   computing the means of the data points assigned to each centroid. It is
%   given a dataset X where each row is a single data point, a vector
%   idx of centroid assignments (i.e. each entry in range [1..K]) for each
%   example, and K, the number of centroids. You should return a matrix
%   centroids, where each row of centroids is the mean of the data points
%   assigned to it.
%

% Useful variables
[m n] = size(X);

% You need to return the following variables correctly.
centroids = zeros(K, n);


% ====================== YOUR CODE HERE ======================
% Instructions: Go over every centroid and compute mean of all points that
%               belong to it. Concretely, the row vector centroids(i, :)
%               should contain the mean of the data points assigned to
%               centroid i.
%
% Note: You can use a for-loop over the centroids to compute this.
%
	

	for i=1:K
		sel=find(idx==i);
		if sel>0
			centroids(i,:)=mean(X(sel,:));
		end
	end


	


%--------another working solution----------------
%num_in_centroid = zeros(K);

%for i = 1:m
%    k = idx(i);
    %size(centroids(k,:))
    %size(X(i,:))
%    centroids(k,:) = centroids(k,:) + X(i,:);

%   num_in_centroid(k) = num_in_centroid(k) + 1; 
%end

%for k = 1:K
%    if num_in_centroid(k) > 0
%        centroids(k,:) = centroids(k,:) / num_in_centroid(k); 
%    end
%end


% =============================================================


end