function res = cons_experiments1_analyze(res, file)
	fid = fopen(file, 'w');

	% consider statistics in the last delta steps
	delta = 100;
	
	for s=1:numel(res.scenarios)
		fprintf('\nScenario: %s\n\tAlgo\t\tDrift\t\tDisag\n', res.scenarios{s}{1});
	
		for a=1:numel(res.algos)
			r = res.results{s,a};
			
			algo_name = res.algos{a}{1};
			scenario_name =  res.scenarios{s}{1};

			max_disag = max(r.disagreement(r.T-delta:r.T));
			max_avg_disag = max_disag / (r.n * r.Delta);

			max_drift = max(abs(r.drift(r.T-delta:r.T)));
	

			fprintf('\t%s\t\t%.8f\t\t%.8f\n', algo_name, max_drift, max_avg_disag);
			
			i1 = 1; %last_index_above(abs(r.drift), max_drift);
			i2 = last_index_above(r.disagreement, 	1.001*max_disag);
			
			fprintf('\t%s\t\t(%d)\t\t(%d)\n', res.algos{a}{1}, i1, i2);

		fprintf(fid,'\\newcommand{\\%sO%sO%s}{%.8f}\n', scenario_name, algo_name, 'drift', max_drift );
		fprintf(fid,'\\newcommand{\\%sO%sO%s}{%.8f}\n', scenario_name, algo_name, 'disag', max_avg_disag);
		fprintf(fid,'\\newcommand{\\%sO%sO%s}{%d}\n', scenario_name, algo_name, 'drifti', i1 );
		fprintf(fid,'\\newcommand{\\%sO%sO%s}{%d}\n', scenario_name, algo_name, 'disagi', i2);
			

		end

		
			drift_bound = 0.5 * r.eta;
			fprintf('\t d(k) <= %8.8f \n', drift_bound);
			
			e = eig(r.L); l_n = e(r.n); l_2 = e(2);
			
			avg_disag_bound = r.eta * sqrt(3/2) * (l_n / l_2);
			fprintf('\t dis(k) <= %8.8f \n', avg_disag_bound);

			fprintf(fid,'\\newcommand{\\%sO%sO%s}{%.8f}\n', scenario_name, algo_name, 'disagbound', avg_disag_bound);
			fprintf(fid,'\\newcommand{\\%sO%sO%s}{%.8f}\n', scenario_name, algo_name, 'driftbound', drift_bound);
			
	end
	
	
function r = last_index_above(series, threshold)
	r = max(find(series>threshold));
	if size(r) == 0
		r = 1
	end