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)
{
;
}
}