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);
}
//################# 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;
}
/// <summary>
/// Calculates the number of sub-steps for each sub-grid
/// </summary>
protected Clusterer.Clustering CalculateNumberOfLocalTS(Clusterer.Clustering clustering)
{
NumberOfLocalTimeSteps.Clear();
double[] sendHmin = new double[clustering.NumberOfClusters];
double[] rcvHmin = new double[clustering.NumberOfClusters];
MultidimensionalArray cellMetric = clusterer.GetStableTimestepSize(clustering.SubGrid);
for (int i = 0; i < clustering.NumberOfClusters; i++)
{
double h_min = double.MaxValue;
CellMask volumeMask = clustering.Clusters[i].VolumeMask;
foreach (Chunk c in volumeMask)
{
int JE = c.JE;
for (int j = c.i0; j < JE; j++)
{
h_min = Math.Min(cellMetric[clustering.SubGrid.LocalCellIndex2SubgridIndex[j]], h_min);
}
}
sendHmin[i] = h_min;
}
// MPI to ensure that each processor has the local time step sizes
unsafe
{
fixed(double *pSend = sendHmin, pRcv = rcvHmin)
{
csMPI.Raw.Allreduce((IntPtr)(pSend), (IntPtr)(pRcv), clustering.NumberOfClusters, csMPI.Raw._DATATYPE.DOUBLE, csMPI.Raw._OP.MIN, csMPI.Raw._COMM.WORLD);
}
}
int[] numOfSubSteps = new int[clustering.NumberOfClusters];
for (int i = 0; i < numOfSubSteps.Length; i++)
{
double fraction = rcvHmin[0] / rcvHmin[i];
// Accounting for roundoff errors
double eps = 1.0e-2;
int subSteps;
if (fraction > Math.Floor(fraction) + eps)
{
subSteps = (int)Math.Ceiling(fraction);
}
else
{
subSteps = (int)Math.Floor(fraction);
}
numOfSubSteps[i] = subSteps;
}
List <SubGrid> newClusters = new List <SubGrid>();
for (int i = 0; i < clustering.NumberOfClusters; i++)
{
if (i < clustering.NumberOfClusters - 1 && numOfSubSteps[i] == numOfSubSteps[i + 1])
{
// Combine both sub-grids and remove the previous one
SubGrid combinedSubGrid = new SubGrid(clustering.Clusters[i].VolumeMask.Union(clustering.Clusters[i + 1].VolumeMask));
newClusters.Add(combinedSubGrid);
Debug.WriteLine("CalculateNumberOfLocalTS: Clustering leads to sub-grids which are too similar, i.e. they have the same number of local time steps. They are combined.");
NumberOfLocalTimeSteps.Add(numOfSubSteps[i]);
i++;
}
else
{
newClusters.Add(clustering.Clusters[i]);
NumberOfLocalTimeSteps.Add(numOfSubSteps[i]);
}
}
#if DEBUG
Console.WriteLine("COMBINING CLUSTERS");
for (int i = 0; i < newClusters.Count; i++)
{
Console.WriteLine("id=" + i + " -> sub-steps=" + NumberOfLocalTimeSteps[i] + " and elements=" + newClusters[i].GlobalNoOfCells);
}
#endif
return(new Clusterer.Clustering(newClusters, clustering.SubGrid));
}
/// <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);
}
