public void Agent0x1Simulation_ZeroDimensional()
{
Console.WriteLine("Agent0x1Simulation_ZeroDimensional");
LoggerInitialization.SetThreshold(typeof(sim_tests), LogLevel.Debug);
LoggerInitialization.SetThreshold(typeof(AbstractAgent), LogLevel.Info);
LoggerInitialization.SetThreshold(typeof(AgentOrderbookLoader), LogLevel.Info);
LoggerInitialization.SetThreshold(typeof(Agent0x0), LogLevel.Info);
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 = 10;
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";
IAgentEvaluationBundle aeb = new AgentEvaluationBundle(PROPERTY);
// 1 hours
ISimulation sim = new Simulation(pop, ob, 0.0, 3600.0);
NamedMetricAgentEvaluationFactory metricEF = new NamedMetricAgentEvaluationFactory(PROPERTY);
sim.add(metricEF);
SingletonLogger.Instance().DebugLog(typeof(sim_tests), "Running Simulation");
ISimulationResults res = sim.run();
SingletonLogger.Instance().DebugLog(typeof(sim_tests), "Stopping Simulation");
IAgentEvaluation ae = metricEF.create();
aeb.addAgentEvaluation(ae);
SingletonLogger.Instance().DebugLog(typeof(sim_tests), "ob: " + ob.ToStringLong());
SingletonLogger.Instance().DebugLog(typeof(sim_tests), "aeb: " + aeb.ToStringLong());
SingletonLogger.Instance().DebugLog(typeof(sim_tests), "res: " + res.ToStringLong());
Assert.AreEqual(res.Valid, true);
}
public void DummySimulation1()
{
Console.WriteLine("DummySimulation1");
LoggerInitialization.SetThreshold(typeof(sim_tests), LogLevel.Debug);
LoggerInitialization.SetThreshold(typeof(AbstractAgent), LogLevel.Info);
LoggerInitialization.SetThreshold(typeof(AgentDummy), LogLevel.Info);
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);
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);
foreach (IAgent ag in pop)
{
SingletonLogger.Instance().DebugLog(typeof(metrics_tests), "agent: " + ag);
}
IOrderbook_Observable ob = new Orderbook();
string PROPERTY = "NetWorth";
IAgentEvaluationBundle aeb = new AgentEvaluationBundle(PROPERTY);
ISimulation sim = new Simulation(pop.clone(), ob.clone(), 0.0, 100.0);
NamedMetricAgentEvaluationFactory metricEF = new NamedMetricAgentEvaluationFactory(PROPERTY);
sim.add(metricEF);
SingletonLogger.Instance().DebugLog(typeof(sim_tests), "Running Simulation");
ISimulationResults res = sim.run();
SingletonLogger.Instance().DebugLog(typeof(sim_tests), "Stopping Simulation");
IAgentEvaluation ae = metricEF.create();
aeb.addAgentEvaluation(ae);
SingletonLogger.Instance().DebugLog(typeof(sim_tests), "aeb: " + aeb.ToStringLong());
SingletonLogger.Instance().DebugLog(typeof(sim_tests), "res: " + res.ToStringLong());
Assert.AreEqual(res.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());
}