Integrate(Func <double, double, Vector, Func <double, Vector, Vector>, IEnumerable <SolPoint> > Solver,
State initialState, double initialTime, double finalTime, Func <double, Vector, Vector> Flux,
SampleValue sample, List <ReportEntry> reports, Noise noise, bool nonTrivialSolution, Style style)
{
double redrawTick = initialTime; double redrawStep = (finalTime - initialTime) / 50;
double densityTick = initialTime; double densityStep = (finalTime - initialTime) / 1000;
int pointsCounter = 0;
int renderedCounter = 0;
double lastTime = finalTime;
State lastState = null;
if (initialState.NaN())
{
Gui.Log("Initial state contains NaN.");
return(lastTime, lastState);
}
KChartHandler.ChartClearData(style);
(string[] series, string[] seriesLNA) = GenerateSeries(reports, noise, style);
KChartHandler.LegendUpdate(style);
KScoreHandler.ScoreUpdate();
IEnumerable <SolPoint> solution = SolutionGererator(Solver, initialState, initialTime, finalTime, Flux, nonTrivialSolution, style);
List <TriggerEntry> triggers = sample.Triggers(style);
bool[] triggered = new bool[triggers.Count]; for (int i = 0; i < triggers.Count; i++)
{
triggered[i] = false;
}
// BEGIN foreach (SolPoint solPoint in solution) -- done by hand to catch exceptions in MoveNext()
SolPoint solPoint = new SolPoint(initialTime, initialState.Clone().ToArray());
bool hasSolPoint = false;
var enumerator = solution.GetEnumerator();
do
{
// Handle triggers first, they can apply to the initial state
if (triggers.Count > 0)
{
State state = null; // allocated on need from solPoint
State modifiedState = null; // allocated on need from state
for (int i = 0; i < triggers.Count; i++)
{
if (triggered[i] == false)
{
TriggerEntry trigger = triggers[i];
if (state == null)
{
state = new State(sample.Count(), lna: noise != Noise.None).InitAll(solPoint.X);
}
if (trigger.condition.ObserveBool(sample, solPoint.T, state, Flux, style))
{
if (modifiedState == null)
{
modifiedState = state.Clone();
}
double rawValue = trigger.assignment.ObserveMean(sample, solPoint.T, state, Flux, style);
double assignment = trigger.sample.stateMap.NormalizeDimension(trigger.target, rawValue, trigger.dimension, trigger.sample.Volume(), style);
int index = sample.stateMap.IndexOf(trigger.target.symbol);
modifiedState.SetMean(index, assignment);
if (noise != Noise.None && trigger.assignmentVariance != null)
{
double rawValueVariance = trigger.assignmentVariance.ObserveMean(sample, solPoint.T, state, Flux, style);
double assignmentVariance = trigger.sample.stateMap.NormalizeDimension(trigger.target, rawValueVariance, trigger.dimension, trigger.sample.Volume(), style);
modifiedState.SetCovar(index, index, assignmentVariance);
}
triggered[i] = true;
}
}
}
if (modifiedState != null) //restart the solver
{
State newState = modifiedState; // new State(sample.Count(), lna: noise != Noise.None).InitAll(modifiedState.ToArray());
solution = SolutionGererator(Solver, newState, solPoint.T, finalTime, Flux, nonTrivialSolution, style);
enumerator = solution.GetEnumerator();
}
}
try {
if (!enumerator.MoveNext())
{
break;
}
solPoint = enumerator.Current; // get next step of integration from solver
hasSolPoint = true;
}
catch (ConstantEvaluation e) { // stop simulation but allow execution to proceed
Gui.Log("Simulation stopped and ignored: cannot evaluate constant '" + e.Message + "'");
return(lastTime, lastState);
}
catch (Error e) { throw new Error(e.Message); }
catch (Exception e) { KChartHandler.ChartUpdate(style, false); throw new Error("ODE Solver FAILED: " + e.Message); }
pointsCounter++;
// LOOP BODY of foreach (SolPoint solPoint in solution):
if (!Exec.IsExecuting())
{
KChartHandler.ChartUpdate(style); throw new ExecutionEnded("");
} // break;
if (style.chartOutput) // Plot the new solution point
{
if (solPoint.T >= densityTick) // avoid drawing too many points
{
State state = new State(sample.Count(), lna: noise != Noise.None).InitAll(solPoint.X);
for (int i = 0; i < reports.Count; i++)
{
if (series[i] != null) // if a series was actually generated from this report
// generate deterministic series
{
if ((noise == Noise.None && reports[i].flow.HasDeterministicValue()) ||
(noise != Noise.None && reports[i].flow.HasStochasticMean()))
{
double mean = reports[i].flow.ObserveMean(sample, solPoint.T, state, Flux, style);
KChartHandler.ChartAddPoint(series[i], solPoint.T, mean, 0.0, Noise.None);
}
// generate LNA-dependent series
if (noise != Noise.None && reports[i].flow.HasStochasticVariance() && !reports[i].flow.HasNullVariance())
{
double mean = reports[i].flow.ObserveMean(sample, solPoint.T, state, Flux, style);
double variance = reports[i].flow.ObserveVariance(sample, solPoint.T, state, style);
KChartHandler.ChartAddPoint(seriesLNA[i], solPoint.T, mean, variance, noise);
}
}
}
renderedCounter++;
densityTick += densityStep;
}
if (solPoint.T >= redrawTick) // avoid redrawing the plot too often
{
KChartHandler.ChartUpdate(style, incremental: true);
redrawTick += redrawStep;
}
}
lastTime = solPoint.T;
// END foreach (SolPoint solPoint in solution)
} while (true);
if (hasSolPoint)
{
lastState = new State(sample.Count(), lna: noise != Noise.None).InitAll(solPoint.X);
}
KChartHandler.ChartUpdate(style, incremental: false);
return(lastTime, lastState);
}
public static void Trigger(SampleValue sample, TriggerEntry triggerEntry, Style style)
{
sample.AddTrigger(triggerEntry);
}