function r = stats1(r)

	max_conv_length = 100;



	interval = 1500:2000;
	

for i=1:r.n

	part = r.x(i,interval);
	part = part - mean(part) * ones(size(part));
	
	res = xcorr( part, max_conv_length, 'coef');
	r.signal_xcorr(i,:) = res(max_conv_length+1+1:numel(res));
	

	seq = r.signal_xcorr(i,:); seq(1)=-1;
	[y, ind] = max(seq);
	step = ind(1);
	fprintf('For node %d, max corr is for step size = %d\n', i, step);
	
	r.conv_length(i) = step;
end



for i=1:r.n
	conv_length = r.conv_length(i);
	mask = ones(1,conv_length)/conv_length;
	
	degree = sum(r.A(i,:));
	res = conv( r.x(i,:) - r.epsilon  * r.compensate(i,:) , mask);
	r.convolved(i,1:numel(res)) = res;
end



T = size(r.x,2);
for k = 1:T
	x = r.convolved(:,k);
	r.convolved_disagreement(k) = x' * r.L * x;
	r.convolved_bias(k) = mean(x) - r.goal;
	r.convolved_mse(k) = 0;
	for i=1:r.n
		r.convolved_mse(k)=r.convolved_mse(k)+ (1/r.n) * ( x(i) - r.goal)^2;
	end
	
end

%return

figure; num_fig = 6; fig = 1;
colors = {'g','b','k','m'};


subplot(num_fig,1,fig); fig=fig+1; hold on;

	title('correlation / convolution step')

	plot(r.signal_xcorr', 'b.');	

	axis([1 size(r.signal_xcorr,2) 0 1.2]);


subplot(num_fig,1,fig); fig=fig+1; hold on;


	plot(r.x','b-');
	plot([0 T],[r.goal r.goal],'r-');

	title('Unsmoothed');

	a=axis; axis([1 T r.goal-3*r.epsilon r.goal+3*r.epsilon])


subplot(num_fig,1,fig); fig=fig+1; hold on;


	plot(r.convolved(:,1:T)','b-')
	plot([0 T],[r.goal r.goal],'r-');

	title('Smoothed');


	a=axis; axis([1 T r.goal-3*r.epsilon r.goal+3*r.epsilon])



	subplot(num_fig,1,fig); fig=fig+1; hold on;

			plot( log_or_small(r.mse(1:T)), 'r')
			plot( log_or_small(r.convolved_mse(1:T)),'b')

			legend('normal','convolved');

			title('MSE');
			ylabel('log')

		%	a=axis; axis([1500 2000 a(3) a(4)])



subplot(num_fig,1,fig); fig=fig+1; hold on;
	
		
		plot( log_or_small(r.disagreement(1:T)), 'r')
		plot( log_or_small(r.convolved_disagreement(1:T)),'b')
	
		legend('normal','convolved');
	
		title('Disagreement');
		ylabel('log')

	%	a=axis; axis([1500 2000 a(3) a(4)])



subplot(num_fig,1,fig); fig=fig+1; hold on;
	
		plot( r.bias(1:T), 'r')
		plot( r.convolved_bias(1:T),'b')
	
		legend('normal','convolved');
	
		title('Bias');
	
	%	a=axis; axis([1500 2000 a(3) a(4)])


		a=axis; axis([1 T -3*r.epsilon 3*r.epsilon])






function r = log_or_small(k)
	for i=1:numel(k)
		r(i) = log(max(k(i),0.00000001));
	end