public bool TryNewClustering(double dt)
{
bool reclustered = false;
if (ABevolver[0].HistoryChangeRate.Count >= order - 1)
{
if (adaptive)
{
if (TimeInfo.TimeStepNumber % reclusteringInterval == 0)
{
// Fix for update problem of artificial viscosity
RaiseOnBeforeComputechangeRate(Time, dt);
//#if DEBUG
Console.WriteLine("\n-------------------------------------------------------------------------------------------");
Console.WriteLine("### BUILD NEW CLUSTERING FOR TESTING ###");
//#endif
// Necessary in order to use the number of sub-grids specified by the user for the reclustering in each time step
// Otherwise the value could be changed by the constructor of the parent class (AdamsBashforthLTS.cs) --> CreateSubGrids()
Clusterer.Clustering newClustering = clusterer.CreateClustering(numberOfClustersInitial, this.TimeStepConstraints, this.SubGrid);
newClustering = clusterer.TuneClustering(newClustering, Time, this.TimeStepConstraints); // Might remove sub-grids when their time step sizes are too similar
reclustered = clusterer.CheckForNewClustering(CurrentClustering, newClustering);
//#if DEBUG
//Console.WriteLine("########################################");
Console.WriteLine("-------------------------------------------------------------------------------------------");
//#endif
// After the intitial phase, activate adaptive mode for all ABevolve objects
foreach (ABevolve abE in ABevolver)
{
abE.adaptive = true;
}
if (reclustered)
{
Console.WriteLine("### RECLUSTERING ###");
CurrentClustering = newClustering;
ShortenHistories(ABevolver);
ABevolve[] oldABevolver = ABevolver;
CreateNewABevolver();
CopyHistoriesOfABevolver(oldABevolver);
}
GetBoundaryTopology();
}
}
}
return(reclustered);
}
public IBMAdamsBashforthLTS(SpatialOperator standardOperator, SpatialOperator boundaryOperator, CoordinateMapping fieldsMap, CoordinateMapping boundaryParameterMap, ISpeciesMap ibmSpeciesMap, IBMControl control, IList <TimeStepConstraint> timeStepConstraints, int reclusteringInterval, bool fluxCorrection)
: base(standardOperator, fieldsMap, boundaryParameterMap, control.ExplicitOrder, control.NumberOfSubGrids, true, timeStepConstraints, reclusteringInterval: reclusteringInterval, fluxCorrection: fluxCorrection, subGrid: ibmSpeciesMap.SubGrid)
{
this.speciesMap = ibmSpeciesMap as ImmersedSpeciesMap;
if (this.speciesMap == null)
{
throw new ArgumentException(
"Only supported for species maps of type 'ImmersedSpeciesMap'",
"speciesMap");
}
this.standardOperator = standardOperator;
this.boundaryOperator = boundaryOperator;
this.boundaryParameterMap = boundaryParameterMap;
this.fieldsMap = fieldsMap;
this.control = control;
agglomerationPatternHasChanged = true;
cutCells = speciesMap.Tracker.Regions.GetCutCellMask();
cutAndTargetCells = cutCells.Union(speciesMap.Agglomerator.AggInfo.TargetCells);
// Normal LTS constructor
NumberOfLocalTimeSteps = new List <int>(control.NumberOfSubGrids);
clusterer = new Clusterer(this.gridData, this.TimeStepConstraints);
CurrentClustering = clusterer.CreateClustering(control.NumberOfSubGrids, speciesMap.SubGrid);
CurrentClustering = CalculateNumberOfLocalTS(CurrentClustering); // Might remove sub-grids when time step sizes are too similar
ABevolver = new IBMABevolve[CurrentClustering.NumberOfClusters];
for (int i = 0; i < ABevolver.Length; i++)
{
ABevolver[i] = new IBMABevolve(standardOperator, boundaryOperator, fieldsMap, boundaryParameterMap, speciesMap, control.ExplicitOrder, control.LevelSetQuadratureOrder, control.CutCellQuadratureType, sgrd: CurrentClustering.Clusters[i], adaptive: this.adaptive);
ABevolver[i].OnBeforeComputeChangeRate += (t1, t2) => this.RaiseOnBeforeComputechangeRate(t1, t2);
}
GetBoundaryTopology();
#if DEBUG
for (int i = 0; i < CurrentClustering.NumberOfClusters; i++)
{
Console.WriteLine("IBM AB LTS ctor: id=" + i + " -> sub-steps=" + NumberOfLocalTimeSteps[i] + " and elements=" + CurrentClustering.Clusters[i].GlobalNoOfCells);
}
#endif
// Start-up phase needs an IBM Runge-Kutta time stepper
RungeKuttaScheme = new IBMSplitRungeKutta(standardOperator, boundaryOperator, fieldsMap, boundaryParameterMap, speciesMap, timeStepConstraints);
}
//################# Hack for saving to database in every (A)LTS sub-step
/// <summary>
/// Standard constructor for the (adaptive) local time stepping algorithm
/// </summary>
/// <param name="spatialOp">Spatial operator</param>
/// <param name="Fieldsmap">Coordinate mapping for the variable fields</param>
/// <param name="Parameters">optional parameter fields, can be null if <paramref name="spatialOp"/> contains no parameters; must match the parameter field list of <paramref name="spatialOp"/>, see <see cref="BoSSS.Foundation.SpatialOperator.ParameterVar"/></param>
/// <param name="order">LTS/AB order</param>
/// <param name="numOfClusters">Amount of sub-grids/clusters to be used for LTS</param>
/// <param name="timeStepConstraints">Time step constraints for later usage as metric</param>
/// <param name="subGrid">Sub-grids, e.g., from previous time steps</param>
/// <param name="fluxCorrection">Bool for triggering the fluss correction</param>
/// <param name="reclusteringInterval">Interval for potential reclustering</param>
/// <param name="saveToDBCallback">Hack for plotting all sub-steps</param>
/// <remarks>Uses the k-Mean clustering, see <see cref="BoSSS.Solution.Utils.Kmeans"/>, to generate the element groups</remarks>
public AdamsBashforthLTS(SpatialOperator spatialOp, CoordinateMapping Fieldsmap, CoordinateMapping Parameters, int order, int numOfClusters, IList <TimeStepConstraint> timeStepConstraints = null, SubGrid subGrid = null, bool fluxCorrection = true, int reclusteringInterval = 0, Action <TimestepNumber, double> saveToDBCallback = null, int initialTimestepNumber = 1)
: base(spatialOp, Fieldsmap, Parameters, order, timeStepConstraints, subGrid)
{
if (reclusteringInterval != 0)
{
numberOfClustersInitial = numOfClusters;
this.timestepNumber = initialTimestepNumber;
this.adaptive = true;
}
// Add OnBeforeComputeChangeRate (AV) to start-up phase time stepper
RungeKuttaScheme.OnBeforeComputeChangeRate += (t1, t2) => this.RaiseOnBeforeComputechangeRate(t1, t2);
this.reclusteringInterval = reclusteringInterval;
this.gridData = Fieldsmap.Fields.First().GridDat;
this.fluxCorrection = fluxCorrection;
NumberOfLocalTimeSteps = new List <int>(numOfClusters);
clusterer = new Clusterer(this.gridData, this.TimeStepConstraints);
CurrentClustering = clusterer.CreateClustering(numOfClusters, this.SubGrid); // Might remove clusters when their centres are too close
CurrentClustering = CalculateNumberOfLocalTS(CurrentClustering); // Might remove clusters when time step sizes are too similar
ABevolver = new ABevolve[CurrentClustering.NumberOfClusters];
for (int i = 0; i < ABevolver.Length; i++)
{
ABevolver[i] = new ABevolve(spatialOp, Fieldsmap, Parameters, order, adaptive: this.adaptive, sgrd: CurrentClustering.Clusters[i]);
ABevolver[i].OnBeforeComputeChangeRate += (t1, t2) => this.RaiseOnBeforeComputechangeRate(t1, t2);
}
GetBoundaryTopology();
#if DEBUG
for (int i = 0; i < CurrentClustering.NumberOfClusters; i++)
{
Console.WriteLine("AB LTS Ctor: id=" + i + " -> sub-steps=" + NumberOfLocalTimeSteps[i] + " and elements=" + CurrentClustering.Clusters[i].GlobalNoOfCells);
}
#endif
// Saving time steps in subgrids
//this.saveToDBCallback = saveToDBCallback;
}
////################# Hack for saving to database in every (A)LTS sub-step
//private Action<TimestepNumber, double> saveToDBCallback;
////################# Hack for saving to database in every (A)LTS sub-step
/// <summary>
/// Standard constructor for the (adaptive) local time stepping algorithm
/// </summary>
/// <param name="spatialOp">Spatial operator</param>
/// <param name="Fieldsmap">Coordinate mapping for the variable fields</param>
/// <param name="Parameters">optional parameter fields, can be null if <paramref name="spatialOp"/> contains no parameters; must match the parameter field list of <paramref name="spatialOp"/>, see <see cref="BoSSS.Foundation.SpatialOperator.ParameterVar"/></param>
/// <param name="order">LTS/AB order</param>
/// <param name="numOfClusters">Amount of sub-grids/clusters to be used for LTS</param>
/// <param name="timeStepConstraints">Time step constraints for later usage as metric</param>
/// <param name="subGrid">Sub-grids, e.g., from previous time steps</param>
/// <param name="fluxCorrection">Bool for triggering the fluss correction</param>
/// <param name="reclusteringInterval">Interval for potential reclustering</param>
/// <param name="saveToDBCallback">Hack for plotting all sub-steps</param>
/// <remarks>Uses the k-Mean clustering, see <see cref="BoSSS.Solution.Utils.Kmeans"/>, to generate the element groups</remarks>
public AdamsBashforthLTS(SpatialOperator spatialOp, CoordinateMapping Fieldsmap, CoordinateMapping Parameters, int order, int numOfClusters, IList <TimeStepConstraint> timeStepConstraints = null, SubGrid subGrid = null, bool fluxCorrection = true, int reclusteringInterval = 0, Action <TimestepNumber, double> saveToDBCallback = null, int maxNumOfSubSteps = 0, bool forceReclustering = false, bool logging = false, bool consoleOutput = false)
: base(spatialOp, Fieldsmap, Parameters, order, timeStepConstraints, subGrid)
{
this.forceReclustering = forceReclustering;
this.Logging = logging;
this.ConsoleOutput = consoleOutput;
if (reclusteringInterval != 0)
{
NumberOfClustersInitial = numOfClusters;
this.adaptive = true;
}
// Add OnBeforeComputeChangeRate (AV) to start-up phase time stepper
RungeKuttaScheme.OnBeforeComputeChangeRate += (t1, t2) => this.RaiseOnBeforeComputechangeRate(t1, t2);
this.reclusteringInterval = reclusteringInterval;
this.gridData = Fieldsmap.Fields.First().GridDat;
this.fluxCorrection = fluxCorrection;
if (ConsoleOutput)
{
Console.WriteLine("### This is ABLTS ctor ###");
}
clusterer = new Clusterer(this.gridData, maxNumOfSubSteps);
CurrentClustering = clusterer.CreateClustering(numOfClusters, this.TimeStepConstraints, this.SubGrid); // Might remove clusters when their centres are too close
CurrentClustering = clusterer.TuneClustering(CurrentClustering, Time, this.TimeStepConstraints); // Might remove clusters when their time step sizes are too similar
ABevolver = new ABevolve[CurrentClustering.NumberOfClusters];
for (int i = 0; i < ABevolver.Length; i++)
{
ABevolver[i] = new ABevolve(spatialOp, Fieldsmap, Parameters, order, adaptive: this.adaptive, sgrd: CurrentClustering.Clusters[i]);
ABevolver[i].OnBeforeComputeChangeRate += (t1, t2) => this.RaiseOnBeforeComputechangeRate(t1, t2);
}
GetBoundaryTopology();
// Saving time steps in subgrids
//this.saveToDBCallback = saveToDBCallback;
}
/// <summary>
/// Performs a time step
/// </summary>
/// <param name="dt">Time step size that equals -1, if no fixed time step is prescribed</param>
public override double Perform(double dt)
{
using (new ilPSP.Tracing.FuncTrace()) {
if (ABevolver[0].HistoryChangeRate.Count >= order - 1)
{
bool reclustered = false;
if (adaptive)
{
if (timestepNumber % reclusteringInterval == 0)
{
// Fix for update problem of artificial viscosity
RaiseOnBeforeComputechangeRate(Time, dt);
Clusterer.Clustering oldClustering = CurrentClustering;
// Necessary in order to use the number of sub-grids specified by the user for the reclustering in each time step
// Otherwise the value could be changed by the constructor of the parent class (AdamsBashforthLTS.cs) --> CreateSubGrids()
CurrentClustering = clusterer.CreateClustering(numberOfClustersInitial, this.SubGrid);
CurrentClustering = CalculateNumberOfLocalTS(CurrentClustering); // Might remove sub-grids when time step sizes are too similar
reclustered = clusterer.CheckForNewClustering(oldClustering, CurrentClustering);
// After the intitial phase, activate adaptive mode for all ABevolve objects
foreach (ABevolve abE in ABevolver)
{
abE.adaptive = true;
}
if (reclustered)
{
ShortenHistories(ABevolver);
ABevolve[] oldABevolver = ABevolver;
CreateNewABevolver();
CopyHistoriesOfABevolver(oldABevolver);
}
GetBoundaryTopology();
#if DEBUG
if (reclustered)
{
Console.WriteLine("RECLUSTERING");
}
#endif
}
}
// Number of substeps could have changed
if (TimeStepConstraints != null)
{
dt = CalculateTimeStep();
}
double[,] CorrectionMatrix = new double[CurrentClustering.NumberOfClusters, CurrentClustering.NumberOfClusters];
// Saves the results at t_n
double[] y0 = new double[Mapping.LocalLength];
DGCoordinates.CopyTo(y0, 0);
double time0 = m_Time;
double time1 = m_Time + dt;
TimestepNumber subTimestep = new TimestepNumber(timestepNumber - 1);
// Evolves each sub-grid with its own time step (only one step)
// (The result is not written to m_DGCoordinates!)
for (int i = 0; i < ABevolver.Length; i++)
{
//localABevolve[i].completeBndFluxes.Clear();
//if (localABevolve[i].completeBndFluxes.Any(x => x != 0.0)) Console.WriteLine("Not all Bnd fluxes were used in correction step!!!");
ABevolver[i].Perform(dt / (double)NumberOfLocalTimeSteps[i]);
}
// After evolving each cell update the time with dt_min
m_Time = m_Time + dt / (double)NumberOfLocalTimeSteps[CurrentClustering.NumberOfClusters - 1];
if (saveToDBCallback != null)
{
subTimestep = subTimestep.NextIteration();
saveToDBCallback(subTimestep, m_Time);
}
// Saves the history of DG_Coordinates for each cluster
Queue <double[]>[] historyDGC_Q = new Queue <double[]> [CurrentClustering.NumberOfClusters];
for (int i = 0; i < historyDGC_Q.Length; i++)
{
historyDGC_Q[i] = ABevolver[i].HistoryDGCoordinate;
}
if (!adaptive)
{
// Saves DtHistory for each cluster
historyTime_Q = new Queue <double> [CurrentClustering.NumberOfClusters];
for (int i = 0; i < historyTime_Q.Length; i++)
{
historyTime_Q[i] = ABevolver[i].HistoryTime;
}
}
// Perform the local time steps
for (int localTS = 1; localTS < NumberOfLocalTimeSteps.Last(); localTS++)
{
for (int id = 1; id < CurrentClustering.NumberOfClusters; id++)
{
//Evolve Condition: Is "ABevolve.Time" at "AB_LTS.Time"?
if ((ABevolver[id].Time - m_Time) < 1e-10)
{
double localDt = dt / NumberOfLocalTimeSteps[id];
foreach (Chunk chunk in CurrentClustering.Clusters[id].VolumeMask)
{
foreach (int cell in chunk.Elements)
{
// f == each field
// n == basis polynomial
foreach (DGField f in Mapping.Fields)
{
for (int n = 0; n < f.Basis.GetLength(cell); n++)
{
int coordinateIndex = Mapping.LocalUniqueCoordinateIndex(f, cell, n);
DGCoordinates[coordinateIndex] = historyDGC_Q[id].Last()[coordinateIndex];
}
}
}
}
Dictionary <int, double> myDic = InterpolateBoundaryValues(historyDGC_Q, id, ABevolver[id].Time);
foreach (KeyValuePair <int, double> kvp in myDic)
{
DGCoordinates[kvp.Key] = kvp.Value;
}
ABevolver[id].Perform(localDt);
m_Time = ABevolver.Min(s => s.Time);
if (saveToDBCallback != null)
{
subTimestep = subTimestep.NextIteration();
saveToDBCallback(subTimestep, m_Time);
}
}
// Are we at an (intermediate-) syncronization levels?
// For conservatvity, we have to correct the values of the larger cell cluster
if (fluxCorrection)
{
for (int idCoarse = 0; idCoarse < id; idCoarse++)
{
if (Math.Abs(ABevolver[id].Time - ABevolver[idCoarse].Time) < 1e-10 &&
!(Math.Abs(ABevolver[idCoarse].Time - CorrectionMatrix[idCoarse, id]) < 1e-10))
{
if (fluxCorrection)
{
CorrectFluxes(idCoarse, id, historyDGC_Q);
}
CorrectionMatrix[idCoarse, id] = ABevolver[idCoarse].Time;
}
}
}
}
}
// Finalize step
// Use unmodified values in history of DGCoordinates (DGCoordinates could have been modified by
// InterpolateBoundaryValues, should be resetted afterwards)
DGCoordinates.Clear();
for (int id = 0; id < historyDGC_Q.Length; id++)
{
DGCoordinates.axpy <double[]>(historyDGC_Q[id].Last(), 1);
}
// Update time
m_Time = time0 + dt;
}
else
{
double[] currentChangeRate = new double[Mapping.LocalLength];
double[] upDGC = new double[Mapping.LocalLength];
// Save time history
if (adaptive)
{
for (int i = 0; i < ABevolver.Length; i++)
{
double[] currentTime = new double[ABevolver[i].ABSubGrid.LocalNoOfCells];
for (int j = 0; j < currentTime.Length; j++)
{
currentTime[j] = m_Time;
}
ABevolver[i].historyTimePerCell.Enqueue(currentTime);
}
}
else
{
if (ABevolver[0].HistoryTime.Count == 0)
{
for (int i = 0; i < ABevolver.Length; i++)
{
ABevolver[i].HistoryTime.Enqueue(m_Time);
}
}
}
// Needed for the history
for (int i = 0; i < CurrentClustering.NumberOfClusters; i++)
{
double[] localCurrentChangeRate = new double[currentChangeRate.Length];
double[] edgeFlux = new double[gridData.iGeomEdges.Count * Mapping.Fields.Count];
ABevolver[i].ComputeChangeRate(localCurrentChangeRate, m_Time, 0, edgeFlux);
ABevolver[i].HistoryChangeRate.Enqueue(localCurrentChangeRate);
ABevolver[i].HistoryBoundaryFluxes.Enqueue(edgeFlux);
}
dt = RungeKuttaScheme.Perform(dt);
DGCoordinates.CopyTo(upDGC, 0);
// Saves ChangeRateHistory for AB LTS
// Only entries for the specific cluster
for (int i = 0; i < CurrentClustering.NumberOfClusters; i++)
{
ABevolver[i].HistoryDGCoordinate.Enqueue(OrderValuesByCluster(CurrentClustering.Clusters[i], upDGC));
if (!adaptive)
{
ABevolver[i].HistoryTime.Enqueue(RungeKuttaScheme.Time);
}
}
// RK is a global timeStep
// -> time update for all other timeStepper with rk.Time
m_Time = RungeKuttaScheme.Time;
foreach (ABevolve ab in ABevolver)
{
ab.ResetTime(m_Time, timestepNumber);
}
}
}
if (adaptive)
{
timestepNumber++;
}
return(dt);
}
