public IBlauSpaceEvaluation MeanEvaluation(IBlauSpaceLattice lattice) { IAgentEvaluationBundleCollapser meanCalculator = AgentEvaluationBundleCollapser_Mean.Instance(); IBlauSpaceEvaluation mean = meanCalculator.eval(this, lattice); return(mean); }
public IBlauSpaceEvaluation eval(IAgentEvaluationBundle aeb, IBlauSpaceLattice lattice) { IBlauSpaceEvaluation meanEval = aeb.MeanEvaluation(lattice); IBlauSpaceMultiEvaluation bsme = new BlauSpaceMultiEvaluation(aeb.Name, lattice); IBlauSpaceEvaluation bse = new BlauSpaceEvaluation(aeb.Name + "-Std", lattice); foreach (IAgentEvaluation ae in aeb.Evaluations) { ae.AddToBlauSpaceMultiEvaluation(bsme); } foreach (IBlauPoint p in bsme.AssignedLatticePoints) { LinkedList <IScore> scores = bsme.eval(p); double meanValue = meanEval.eval(p); double total = 0.0; int count = 0; foreach (IScore s in scores) { double delta = (s.Value - meanValue); total += (delta * delta); count++; } double mean = Math.Sqrt(total) / (double)count; bse.set(p, mean); } return(bse); }
public IBlauSpaceEvaluation StdEvaluation(IBlauSpaceLattice lattice) { IAgentEvaluationBundleCollapser stdCalculator = AgentEvaluationBundleCollapser_Std.Instance(); IBlauSpaceEvaluation std = stdCalculator.eval(this, lattice); return(std); }
public IBlauSpaceEvaluation AssignmentCounts(IBlauSpaceLattice lattice) { IAgentEvaluationBundleCollapser countsCalculator = AgentEvaluationBundleCollapser_Counts.Instance(); IBlauSpaceEvaluation counts = countsCalculator.eval(this, lattice); return(counts); }
private void CreateGnuplotScript(IBlauSpaceEvaluation bse, IBlauSpaceEvaluation std, int c) { this.AppendToPresentation("set terminal postscript eps enhanced"); this.AppendToPresentation("set output \"" + bse.Name + "" + c + ".eps\""); string axisName = _exp.theBlauSpace.getAxis(c).Name; Latex.AddImage("" + bse.Name + "" + c + ".eps", "Influence of " + axisName + " (BlauSpace coord " + c + ") on " + bse.Name + ""); this.AppendToPresentation("set title \"" + _experimentName + " " + bse.Name + " Agent Evaluation\""); this.AppendToPresentation("set ylabel \"" + bse.Name + "\""); this.AppendToPresentation("set xlabel \"" + axisName + " (BlauSpace coord " + c + ")\""); this.AppendToPresentation("set autoscale y"); string s = "plot \"../" + _exp.BSE_DIR_STRING + "/" + bse.Name + "" + c + ".bse\" using 1:2:3 with yerrorbars t \"" + bse.Name + "\" lc 1"; this.AppendToPresentation(s); }
private void Present(IBlauSpaceEvaluation bse, IBlauSpaceEvaluation std, int c) { this.BeginPresentation(_datadir, bse.Name + "" + c + ".bse"); string header = "# BlauSpaceEvaluation " + bse.Name + ""; this.AppendToPresentation(header); header = "# " + bse.Lattice.BlauSpace + " mean std"; this.AppendToPresentation(header); foreach (IBlauPoint p in bse.AssignedLatticePoints) { string val = "" + bse.eval(p); string bar = "" + std.eval(p); string str = "" + p.getCoordinate(c) + "\t" + val + "\t" + bar; this.AppendToPresentation(str); } this.EndPresentation(); this.BeginPresentation(_gpdir, bse.Name + "" + c + ".bse.gp"); CreateGnuplotScript(bse, std, c); this.EndPresentation(); }
public void Agent0x1Simulation_TrajectoryBundles() { Console.WriteLine("Agent0x1Simulation_TrajectoryBundles"); LoggerInitialization.SetThreshold(typeof(sim_tests), LogLevel.Debug); //LoggerInitialization.SetThreshold(typeof(Agent0x1), LogLevel.Info); //LoggerInitialization.SetThreshold(typeof(AbstractAgent), LogLevel.Info); //LoggerInitialization.SetThreshold(typeof(SimulationBundle), LogLevel.Debug); //LoggerInitialization.SetThreshold(typeof(Scheduler), LogLevel.Debug); //LoggerInitialization.SetThreshold(typeof(Trajectory), LogLevel.Debug); int dim = 0; string [] names = new string [0]; double [] mins = new double [0]; double [] maxs = new double [0]; IBlauSpace s = BlauSpace.create(dim, names, mins, maxs); IBlauPoint mean = new BlauPoint(s); IBlauPoint std = new BlauPoint(s); IDistribution d = new Distribution_Gaussian(s, mean, std); IAgentFactory afact = new Agent0x0_Factory(d); int NUMAGENTS = 25; IPopulation pop = PopulationFactory.Instance().create(afact, NUMAGENTS); foreach (IAgent ag in pop) { SingletonLogger.Instance().DebugLog(typeof(metrics_tests), "agent: " + ag); } string PATH = "" + ApplicationConfig.EXECDIR + "orderbooks/orderbook.csv"; AgentOrderbookLoader loader = MakeAgentOrderbookLoader(PATH); pop.addAgent(loader); IOrderbook_Observable ob = new Orderbook(); string PROPERTY = "NetWorth"; // 1 hours ISimulationBundle simb = new SimulationBundle(pop, ob, 0.0, 3600.0); IAgentEvaluationFactory metricEF = new NamedMetricAgentEvaluationFactory(PROPERTY); simb.add(metricEF); ITrajectoryFactory priceTF = new TrajectoryFactory_Price(10.0, 0.8); simb.add(priceTF); ITrajectoryFactory spreadTF = new TrajectoryFactory_Spread(10.0, 0.0); simb.add(spreadTF); int NUMTRIALS = 25; SingletonLogger.Instance().DebugLog(typeof(sim_tests), "Running Simulation"); ISimulationResultsBundle resb = simb.run(NUMTRIALS); SingletonLogger.Instance().DebugLog(typeof(sim_tests), "Stopping Simulation"); SingletonLogger.Instance().DebugLog(typeof(sim_tests), "resb: " + resb.ToString()); int STEPS = 1; int [] STEPSarray = new int[s.Dimension]; for (int j = 0; j < s.Dimension; j++) { STEPSarray[j] = STEPS; } IBlauSpaceLattice bsl = BlauSpaceLattice.create(s, STEPSarray); foreach (IAgentEvaluationBundle aeb in resb.getAgentEvaluationBundles()) { IBlauSpaceEvaluation meanEval = aeb.MeanEvaluation(bsl); IBlauSpaceEvaluation stdEval = aeb.StdEvaluation(bsl); SingletonLogger.Instance().DebugLog(typeof(sim_tests), "meanEval: " + meanEval.ToStringLong()); SingletonLogger.Instance().DebugLog(typeof(sim_tests), "stdEval: " + stdEval.ToStringLong()); } foreach (ITrajectoryBundle tb in resb.getTrajectoryBundles()) { SingletonLogger.Instance().DebugLog(typeof(sim_tests), "Computing meanTraj"); ITrajectory meanTraj = tb.MeanTrajectory; SingletonLogger.Instance().DebugLog(typeof(sim_tests), "Computing stdTraj"); ITrajectory stdTraj = tb.StdTrajectory; SingletonLogger.Instance().DebugLog(typeof(sim_tests), "meanTraj: " + meanTraj.ToStringLong()); SingletonLogger.Instance().DebugLog(typeof(sim_tests), "stdTraj: " + stdTraj.ToStringLong()); } Assert.AreEqual(resb.Valid, true); }
public void NamedMetricAgentEvaluationFactoryTest() { Console.WriteLine("NamedMetricAgentEvaluationFactoryTest"); int dim = 3; string [] names = new string [3] { "x", "y", "z" }; double [] mins = new double [3] { 0.0, 0.0, 0.0 }; double [] maxs = new double [3] { 100.0, 100.0, 100.0 }; IBlauSpace s = BlauSpace.create(dim, names, mins, maxs); int STEPS = 10; int [] STEPSarray = new int[s.Dimension]; for (int j = 0; j < s.Dimension; j++) { STEPSarray[j] = STEPS; } IBlauSpaceLattice bsl = BlauSpaceLattice.create(s, STEPSarray); IBlauPoint mean = new BlauPoint(s); mean.setCoordinate(0, 10.0); mean.setCoordinate(1, 20.0); mean.setCoordinate(2, 30.0); IBlauPoint std = new BlauPoint(s); std.setCoordinate(0, 2.0); std.setCoordinate(1, 4.0); std.setCoordinate(2, 6.0); IDistribution d = new Distribution_Gaussian(s, mean, std); IAgentFactory afact = new AgentDummy_Factory(d); int NUMAGENTS = 100; IPopulation pop = PopulationFactory.Instance().create(afact, NUMAGENTS); IOrderbook_Observable ob = new Orderbook(); foreach (IAgent ag in pop) { SingletonLogger.Instance().DebugLog(typeof(metrics_tests), "agent: " + ag); } string PROPERTY = "NetWorth"; IAgentEvaluationBundle aeb = new AgentEvaluationBundle(PROPERTY); int NUMTRIALS = 100; for (int trial = 0; trial < NUMTRIALS; trial++) { SingletonLogger.Instance().DebugLog(typeof(metrics_tests), "*** Trial " + trial); ISimulation sim = new Simulation(pop.clone(), ob.clone(), 0.0, 100.0); NamedMetricAgentEvaluationFactory metricEF = new NamedMetricAgentEvaluationFactory(PROPERTY); sim.add(metricEF); sim.broadcast(new SimulationStart()); sim.broadcast(new SimulationEnd()); IAgentEvaluation ae = metricEF.create(); aeb.addAgentEvaluation(ae); } IBlauSpaceEvaluation meanEval = aeb.MeanEvaluation(bsl); IBlauSpaceEvaluation stdEval = aeb.StdEvaluation(bsl); foreach (IBlauPoint p in meanEval.AssignedLatticePoints) { double meanval = meanEval.eval(p); double stdval = stdEval.eval(p); SingletonLogger.Instance().DebugLog(typeof(metrics_tests), "Scores binned to Blaupoint: " + p + " ===> mean:" + meanval + ", std:" + stdval); Assert.Less(Math.Abs(meanval - AgentDummy.MEANWORTH), 0.1); Assert.Less(stdval, 0.1); } SingletonLogger.Instance().DebugLog(typeof(metrics_tests), "aeb: " + aeb.ToString()); SingletonLogger.Instance().DebugLog(typeof(metrics_tests), "meanEval: " + meanEval.ToStringLong()); SingletonLogger.Instance().DebugLog(typeof(metrics_tests), "stdEval: " + stdEval.ToStringLong()); }
public void AgentEvaluationBundleCollapsingTest() { Console.WriteLine("AgentEvaluationBundleCollapsingTest"); int dim = 3; string [] names = new string [3] { "x", "y", "z" }; double [] mins = new double [3] { 0.0, 0.0, 0.0 }; double [] maxs = new double [3] { 100.0, 100.0, 100.0 }; IBlauSpace s = BlauSpace.create(dim, names, mins, maxs); int STEPS = 10; int [] STEPSarray = new int[s.Dimension]; for (int j = 0; j < s.Dimension; j++) { STEPSarray[j] = STEPS; } IBlauSpaceLattice bsl = BlauSpaceLattice.create(s, STEPSarray); IBlauPoint mean = new BlauPoint(s); mean.setCoordinate(0, 10.0); mean.setCoordinate(1, 20.0); mean.setCoordinate(2, 30.0); IBlauPoint std = new BlauPoint(s); std.setCoordinate(0, 2.0); std.setCoordinate(1, 4.0); std.setCoordinate(2, 6.0); IDistribution d = new Distribution_Gaussian(s, mean, std); IAgentFactory afact = new AgentDummy_Factory(d); int NUMAGENTS = 100; IAgent[] agents = new IAgent[NUMAGENTS]; for (int i = 0; i < NUMAGENTS; i++) { agents[i] = afact.create(); } string PROPERTY = "NetWorth"; IAgentEvaluationBundle aeb = new AgentEvaluationBundle(PROPERTY); int NUMTRIALS = 1000; double MEANVAL = 1.0; for (int trial = 0; trial < NUMTRIALS; trial++) { SingletonLogger.Instance().DebugLog(typeof(metrics_tests), "*** Trial " + trial); IAgentEvaluation ae = new AgentEvaluation(PROPERTY, null); for (int i = 0; i < NUMAGENTS; i++) { ae.set(agents[i], SingletonRandomGenerator.Instance.NextGaussian(MEANVAL, 0.2)); } aeb.addAgentEvaluation(ae); } IBlauSpaceEvaluation meanEval = aeb.MeanEvaluation(bsl); IBlauSpaceEvaluation stdEval = aeb.StdEvaluation(bsl); foreach (IBlauPoint p in meanEval.AssignedLatticePoints) { double meanval = meanEval.eval(p); double stdval = stdEval.eval(p); SingletonLogger.Instance().DebugLog(typeof(metrics_tests), "Scores binned to Blaupoint: " + p + " ===> mean:" + meanval + ", std:" + stdval); Assert.Less(Math.Abs(meanval - MEANVAL), 0.1); Assert.Less(stdval, 0.1); } SingletonLogger.Instance().DebugLog(typeof(metrics_tests), "aeb: " + aeb.ToString()); SingletonLogger.Instance().DebugLog(typeof(metrics_tests), "meanEval: " + meanEval.ToStringLong()); SingletonLogger.Instance().DebugLog(typeof(metrics_tests), "stdEval: " + stdEval.ToStringLong()); }
public override void run() { LoggerInitialization.SetThreshold(typeof(SingleDistributionExperiment), LogLevel.Debug); SingletonLogger.Instance().DebugLog(typeof(SingleDistributionExperiment), "run()"); SingletonLogger.Instance().InfoLog(typeof(SingleDistributionExperiment), "distribution => " + theActualDistribution); IAgentFactory af = CreateAgentFactory(theActualDistribution, theTableConfig.AgentFactoryClassName); SingletonLogger.Instance().InfoLog(typeof(SingleDistributionExperiment), "agent factory => " + theTableConfig.AgentFactoryClassName); af.Initialize(theTableConfig); SingletonLogger.Instance().InfoLog(typeof(SingleDistributionExperiment), "creating initial orderbook"); IOrderbook_Observable ob = new Orderbook(); /* No Burnin at this point * * SingletonLogger.Instance().InfoLog(typeof(SingleDistributionExperiment), "Executing burnin..."); * IPopulation popburn = CreatePopulation(af, theTableConfig.NumAgents, Path.Combine(ApplicationConfig.ROOTDIR, theTableConfig.InitialOrderbook)); * ISimulation simburn = new Simulation(popburn, ob, 0.0, COMMON_BURNIN_TIME_SECONDS, false, "burnin") ; * ISimulationResults resultsburn = simburn.run(); * ob = (IOrderbook_Observable)simburn.Orderbook; * SingletonLogger.Instance().InfoLog(typeof(SingleDistributionExperiment), "Done with burnin."); */ ISimulationBundle accumulated_simb = null; ISimulationResultsBundle accumulated_resb = null; for (int popi = 0; popi < theTableConfig.Populations; popi++) { SingletonLogger.Instance().InfoLog(typeof(SingleDistributionExperiment), "creating population... " + theTableConfig.NumAgents); // Populations all contain an OrderBookLoader agent IPopulation pop = CreatePopulation(af, theTableConfig.NumAgents, Path.Combine(ApplicationConfig.ROOTDIR, theTableConfig.InitialOrderbook)); // SingletonLogger.Instance().InfoLog(typeof(SingleDistributionExperiment), "done."); string popname = POP_FILE_PREFIX + "." + popi + ".Validation"; string poppath = Path.Combine(_popdir, popname); SingletonLogger.Instance().InfoLog(typeof(SingleDistributionExperiment), "population " + popi + " => " + poppath); savePopulation(poppath, pop); _simb = new SimulationBundle(pop, ob, 0.0, theTableConfig.DurationHours * 3600.0, LOG_FRAMES, "pop-" + popi); if (accumulated_simb == null) { accumulated_simb = _simb; } foreach (TrajectoryFactoryConfig tfc in theTrajConfig.getTrajectories()) { IPassiveTrajectoryFactory tf = CreatePassiveTrajectoryFactory(tfc); tf.Initialize(theTableConfig); _simb.add(tf); } /* * foreach (IAgent ag in pop) { * if (ag is IAgent_NonParticipant) continue; * * _simb.add (new TrajectoryFactory_AgentNamedMetric(ag, Agent1x0.NetWorth_METRICNAME, 1.0, 0.0)); * } */ double MAX_ALPHA = 0.10; double TEMPORAL_GRANULARITY_FOR_ALPHA_SLICES = 1.0; for (double alpha = 0.0; alpha <= MAX_ALPHA; alpha += MAX_ALPHA / (double)theTableConfig.NumCombs) { TrajectoryFactory_AlphaSlice tf = new TrajectoryFactory_AlphaSlice(TEMPORAL_GRANULARITY_FOR_ALPHA_SLICES, 0.0, alpha, true); tf.Initialize(theTableConfig); _simb.add(tf); TrajectoryFactory_AlphaSlice tf2 = new TrajectoryFactory_AlphaSlice(TEMPORAL_GRANULARITY_FOR_ALPHA_SLICES, 0.0, alpha, false); tf2.Initialize(theTableConfig); _simb.add(tf2); } foreach (AgentEvaluationConfig aefc in theAgentEvaluationFactorySetConfig.getAgentEvaluations()) { IAgentEvaluationFactory aef = CreateAgentEvaluationFactory(aefc); _simb.add(aef, aefc); } _resb = _simb.run(theTableConfig.Trials); //popname = POP_FILE_PREFIX+"."+popi+".Validation-Post"; //poppath = Path.Combine(_popdir, popname); //SingletonLogger.Instance().InfoLog(typeof(SingleDistributionExperiment), "population post "+popi+" => "+poppath); //savePopulation(poppath, pop); if (accumulated_resb == null) { accumulated_resb = _resb; } else { accumulated_resb.add(_resb); } //WriteTrajectories(popi, _simb, _resb); } //WriteTrajectories(-1, accumulated_simb, accumulated_resb); PresentationConfig.Directory = Path.Combine(OutputDirectory, "results"); if (!Directory.Exists(PresentationConfig.Directory)) { Directory.CreateDirectory(PresentationConfig.Directory); } Latex.ClearImages(); SingletonLogger.Instance().InfoLog(typeof(SingleDistributionExperiment), "Writing BlauSpaceEvaluations."); foreach (IAgentEvaluationBundle aeb in accumulated_resb.getAgentEvaluationBundles()) { IBlauSpaceLattice bsl = accumulated_simb.getLattice(theActualDistribution, aeb); IBlauSpaceEvaluation meanEval = aeb.MeanEvaluation(bsl); IBlauSpaceEvaluation stdEval = aeb.StdEvaluation(bsl); BlauSpaceEvaluationGnuplotPresenter pres = new BlauSpaceEvaluationGnuplotPresenter(_bsedir, PresentationConfig.Directory); pres.Present(this, meanEval, stdEval); } SingletonLogger.Instance().InfoLog(typeof(SingleDistributionExperiment), "Writing TrajectoryBundles."); foreach (ITrajectoryBundle tb in accumulated_resb.getTrajectoryBundles()) { TrajectoryBundleGnuplotPresenter pres = new TrajectoryBundleGnuplotPresenter(_trajdir, PresentationConfig.Directory); pres.Present(this, tb); } SingletonLogger.Instance().InfoLog(typeof(SingleDistributionExperiment), "Writing Latex."); Latex.Instance().Present(this); CreateReport(this); SingletonLogger.Instance().InfoLog(typeof(SingleDistributionExperiment), "Done."); }
private void WriteTrajectories(int popi, ISimulationBundle simb, ISimulationResultsBundle resb) { string trajname = TRAJ_FILE_PREFIX + "." + popi + ".Validation"; string trajpath = Path.Combine(_trajdir, trajname); TextWriter trajWriter = File.CreateText(trajpath); foreach (IAgentEvaluationBundle aeb in resb.getAgentEvaluationBundles()) { trajWriter.WriteLine("# AgentEvaluation: " + aeb.Name); trajWriter.Write("# BlauPoint-Coordinates \t "); trajWriter.Write("mean \t std \t count"); trajWriter.WriteLine(""); IBlauSpaceLattice bsl = simb.getLattice(theActualDistribution, aeb); IBlauSpaceEvaluation meanEval = aeb.MeanEvaluation(bsl); IBlauSpaceEvaluation stdEval = aeb.StdEvaluation(bsl); IBlauSpaceEvaluation ctEval = aeb.AssignmentCounts(bsl); foreach (IBlauPoint bp in meanEval.AssignedLatticePoints) { for (int c = 0; c < bp.Space.Dimension; c++) { trajWriter.Write("" + bp.Space.getAxis(c).Name + "=" + bp.getCoordinate(c).ToString("#0.000") + "\t"); } trajWriter.Write("" + meanEval.eval(bp).ToString("#0.000") + "\t"); trajWriter.Write("" + stdEval.eval(bp).ToString("#0.000") + "\t"); trajWriter.Write("" + ctEval.eval(bp).ToString("#0.000") + "\t"); trajWriter.WriteLine(""); } } double NUMTICKS = 100.0; foreach (ITrajectoryBundle tb in resb.getTrajectoryBundles()) { trajWriter.WriteLine("# TrajectoryBundle: " + tb.Name); trajWriter.WriteLine("# time \t mean \t std \t center \t dev"); ITrajectory meanTraj = tb.MeanTrajectory; ITrajectory stdTraj = tb.StdTrajectory; ITrajectory centerTraj = tb.CentralTrajectory; ITrajectory devTraj = tb.CentralDevTrajectory; double mint = tb.MinimumTime; double maxt = tb.MaximumTime; double stept = (maxt - mint) / NUMTICKS; for (double t = mint; t < maxt; t += stept) { trajWriter.Write("" + t.ToString("#0.000") + "\t"); trajWriter.Write("" + meanTraj.eval(t).ToString("#0.000") + "\t"); trajWriter.Write("" + stdTraj.eval(t).ToString("#0.000") + "\t"); trajWriter.Write("" + centerTraj.eval(t).ToString("#0.000") + "\t"); trajWriter.Write("" + devTraj.eval(t).ToString("#0.000") + "\t"); trajWriter.WriteLine(""); } } trajWriter.Flush(); trajWriter.Close(); }