void AddEstimates() { foreach (var o in _model.LeafObstacles()) { var satRates = _model.satisfactionRateRepository.GetObstacleSatisfactionRates(o.Identifier); if (satRates == null) { Console.WriteLine($"Obstacle '{o.Identifier}' not estimated."); } else { var estimates = satRates.Where(x => x.ExpertIdentifier != null); foreach (var estimate in estimates) { if (estimate is QuantileList qd) { try { ef.AddEstimate(estimate.ExpertIdentifier, o.Identifier, qd.Quantiles.ToArray()); } catch (Exception e) { Console.WriteLine("---"); Console.WriteLine($"An error occured while adding estimate for '{o.Identifier}' by expert '{estimate.ExpertIdentifier}'"); Console.WriteLine(e.Message); Console.WriteLine(e.StackTrace); Console.WriteLine("---"); } } else { throw new NotImplementedException("Distribution not supported"); } } } } }
void Initialize() { RootSatisfactionRates = new Dictionary <string, DoubleSatisfactionRate>(); TimeSpan monitoringDelay = TimeSpan.FromMinutes(1); // Create the new obstacle monitors foreach (var obstacle in _model_running.LeafObstacles() .Where(x => x.CustomData.ContainsKey("monitored") && x.CustomData["monitored"].Equals("true"))) { IStateInformationStorage storage = new FiniteStateInformationStorage(100); var monitor = new ObstacleMonitor(obstacle, _model_running, storage, monitoringDelay); obstacleMonitors.Add(obstacle.Identifier, monitor); } // Initialize the propagator _propagator = new BDDBasedPropagator(_model_running); foreach (var root in _roots) { _propagator.PreBuildObstructionSet(root); RootSatisfactionRates.Add(root.Identifier, null); } }
public static void Main(string[] args) { //DeployAmbulanceAtStationAllocator(); //Thread.Sleep(TimeSpan.FromSeconds(10)); Console.WriteLine("Hello World!"); var monitoringDelay = TimeSpan.FromSeconds(1); logger.Info("Connecting to database"); var provider = new PostgreSQLDatabaseProvider(); var connectionString = ConfigurationManager.ConnectionStrings["postgres"].ConnectionString; var config = DatabaseConfiguration.Build() .UsingConnectionString(connectionString) .UsingProvider(provider) .UsingDefaultMapper <ConventionMapper>(); db = new Database(config); incidentRepository = new IncidentRepository(db); ambulanceRepository = new AmbulanceRepository(db); allocationRepository = new AllocationRepository(db); hospitalRepository = new HospitalRepository(db); configurationRepository = new ConfigurationRepository(db); logger.Info("Connected to database"); logger.Info("Building KAOS model."); var filename = "./Models/simple.kaos"; var parser = new KAOSTools.Parsing.ModelBuilder(); model = parser.Parse(File.ReadAllText(filename), filename); var model2 = parser.Parse(File.ReadAllText(filename), filename); ActiveResolutions = Enumerable.Empty <Resolution>(); var declarations = parser.Declarations; logger.Info("(done)"); logger.Info("Configuring monitors."); // Configure all the monitors (for all obstacles and domain properties). KAOSMetaModelElement[] goals = model.Goals().ToArray(); KAOSMetaModelElement[] obstacles = model.LeafObstacles().ToArray(); var projection = new HashSet <string>(GetAllPredicates(goals)); monitor = new GoalMonitor(model, goals.Union(obstacles), projection, HandleFunc, // new TimedStateInformationStorage(TimeSpan.FromMinutes(60), TimeSpan.FromMinutes(120)), monitoringDelay); logger.Info("(done)"); foreach (var p in model.Predicates()) { Console.WriteLine(p.FriendlyName); } // What goals and obstacles should appear in LOG cpsGoals = model.Goals(x => x.CustomData.ContainsKey("log_cps")); cpsObstacles = model.Obstacles(x => x.CustomData.ContainsKey("log_cps")); // Initialize obstruction sets obstructionLock = new object(); ComputeObstructionSets(); Console.WriteLine("Waiting ..."); Console.ReadKey(); logger.Info("Launching monitors"); monitor.Run(false); var goalMonitorProcessor = new GoalMonitorProcessor(monitor); csvExport = new CSVGoalExportProcessor("experiment-goal.csv", "experiment-obstacle.csv"); // goalMonitorProcessor.AddProcessor(csvExport, monitoringDelay); new Timer((state) => UpdateCPS(), null, monitoringDelay, monitoringDelay); new Timer((state) => MonitorStep(), null, monitoringDelay, monitoringDelay); Thread.Sleep(TimeSpan.FromSeconds(5)); logger.Info("Launching processors"); //new Timer((state) => LogStatistic(), null, monitoringDelay, monitoringDelay); new Timer((state) => LogCSV(), null, monitoringDelay, monitoringDelay); // Configure optimization process. optimizer = new Optimizer(monitor, model2); new Timer((state) => Optimize(), null, TimeSpan.FromSeconds(30), TimeSpan.FromSeconds(60)); while (true) { ; } }