How to change and plot a variogram cloud in a empirical variogram

For the ones that likes images, here is my problem on picture.

http://www.seas.upenn.edu/~ese502/lab-content/extra_materials/EMPIRICAL%20VARIOGRAMS.pdf

I would like to put the values from Matrix C into 30 bins and have a point which represent the mean of each bin in order to get an empirical variogram. I think I got the code of how to create bins but I have no ideas how to plot the whole.

Can somebody give me a hand? Cheers

% Creation of a new matrix with all points against each other. % Calculation of the distance between two points (diagonal of the matrix=0

dist = zeros( length(x), length(x) ); angle = zeros( length(x), length(x) );

for i=1: length(x) for j=1: length(x) deltaX = x(i)-x(j); deltaY = y(i)-y(j);

        dist (i,j) = sqrt( deltaX^2 + deltaY^2 );
        % Calculation of the angle in degrees
        angle (i,j) = atan(deltaY / deltaX) * 180 / pi; 
    end
end

A = dist;

% Take half of the symetric matrix B = sparse(triu(A)); C = full(B);

% Save matrices save('A.mat', 'A'); save('B.mat', 'B'); save('C.mat', 'C');

% Replace all zero numbers by nan C(C == 0) = nan;

% Same code as above to create a matrix of same dimensions but with the % square difference of snow depth (sdepth)

sdepth = zeros( length(x), length(x) );

for i=1: length(x) for j=1: length(x)

        deltaZ = z(i)-z(j);

        sdepth (i,j) = deltaZ^2;

    end
end

D = sdepth;

% Take half of the symetric matrix E = sparse(triu(D)); F = full(E);

% Save matrices save('D.mat', 'D'); save('E.mat', 'E'); save('F.mat', 'F');

% Replace all zero numbers by nan F(F == 0) = nan;

% Calculation of the number of pair distance in the C matrix by calculating % the number of arrays in C minus the number of nan Nk = numel(C) - sum(sum(isnan(C)));

MaxValue = max(C(:));

% Dividing the distance numbers from matrix C in Bins

a = C(:); %split into a and b b = F(:);

topEdge = 100; % define limits botEdge = 0; % define limits numBins = 30; % define number of bins

binEdges = linspace(botEdge, topEdge, numBins+1);

[h,whichBin] = histc(a, binEdges);

for i = a:numBins flagBinMembers = (whichBin == i); binMembers = b(flagBinMembers);

    if any(isnan (a))
    continue

    binMean(i)  = mean(binMembers);
    end

end

% The variogram cloud is given by scatter(C(:),F(:));