//---------------------------------------------------------------------
/// <summary>
/// Does cohort reproduction at certain specified sites.
/// </summary>
/// <param name="sites">
/// The sites where cohort reproduction should be done.
/// </param>
/// <remarks>
/// Because this is the last stage of succession during a timestep,
/// the NextTimeToRun is updated after all the sites are processed.
/// </remarks>
public void ReproduceCohorts(IEnumerable <MutableActiveSite> sites)
{
logger.Debug(string.Format("{0:G}", DateTime.Now));
int maxGeneration = GC.MaxGeneration;
for (int generation = 0; generation <= maxGeneration; generation++)
{
logger.Debug(string.Format(" gen {0}: {1}", generation,
GC.CollectionCount(generation)));
}
ProgressBar progressBar = null;
if (ShowProgress)
{
System.Console.WriteLine("Cohort reproduction ...");
progressBar = NewProgressBar();
}
foreach (ActiveSite site in sites)
{
Reproduction.Do(site);
#if WATCH_CHANGING_GC
bool collectionCountChanged = false;
for (int generation = 0; generation <= maxGeneration; generation++)
{
int currentCount = GC.CollectionCount(generation);
if (collectionCounts[generation] != currentCount)
{
collectionCountChanged = true;
collectionCounts[generation] = currentCount;
}
}
if (collectionCountChanged)
{
logger.Info(string.Format("Site {0}, index = {1}", site.Location, site.DataIndex));
for (int generation = 0; generation <= maxGeneration; generation++)
{
logger.Info(string.Format(" gen {0}: {1}", generation, collectionCounts[generation]));
}
}
#endif
if (ShowProgress)
{
Update(progressBar, site.DataIndex);
}
}
if (ShowProgress)
{
CleanUp(progressBar);
}
logger.Debug(string.Format("{0:G}", DateTime.Now));
for (int generation = 0; generation <= maxGeneration; generation++)
{
logger.Debug(string.Format(" gen {0}: {1}", generation,
GC.CollectionCount(generation)));
}
}
//---------------------------------------------------------------------
public bool Seeds(ISpecies species,
ActiveSite site)
{
if (!Reproduction.SufficientLight(species, site) ||
!Reproduction.Establish(species, site))
{
return(false);
}
double randomNum = Random.GenerateUniform();
foreach (RelativeLocation relLoc in neighborhoods[species.Index])
{
ActiveSite neighbor = site.GetNeighbor(relLoc) as ActiveSite;
if (neighbor != null)
{
float probability = seedDispersalMethod(species, neighbor, site);
if (randomNum < probability)
{
return(true);
}
}
}
return(false);
}
//---------------------------------------------------------------------
/// <summary>
/// Initializes the instance and its associated site variables.
/// </summary>
protected void Initialize(PlugIns.ICore modelCore,
double[,] establishProbabilities,
SeedingAlgorithms seedAlg,
Reproduction.Delegates.AddNewCohort addNewCohort)
{
Model.Core = modelCore;
SiteVars.Initialize();
Seeding.InitializeMaxSeedNeighborhood();
disturbedSites = new DisturbedSiteEnumerator(Model.Core.Landscape,
SiteVars.Disturbed);
SeedingAlgorithm algorithm;
switch (seedAlg)
{
case SeedingAlgorithms.NoDispersal:
algorithm = NoDispersal.Algorithm;
break;
case SeedingAlgorithms.UniversalDispersal:
algorithm = UniversalDispersal.Algorithm;
break;
case SeedingAlgorithms.WardSeedDispersal:
algorithm = WardSeedDispersal.Algorithm;
break;
default:
throw new ArgumentException(string.Format("Unknown seeding algorithm: {0}", seedAlg));
}
Reproduction.Initialize(establishProbabilities, algorithm,
addNewCohort == null ? null : new Reproduction.Delegates.AddNewCohort(addNewCohort));
}
//---------------------------------------------------------------------
/// <summary>
/// Initializes the instance and its associated site variables.
/// </summary>
protected void Initialize(int timestep,
double[,] establishProbabilities,
int startTime,
SeedingAlgorithms seedAlg,
Reproduction.AddNewCohortMethod addNewCohort)
{
this.timestep = timestep;
this.nextTimeToRun = startTime - 1 + timestep;
this.updateNextTimeToRun = false;
SiteVars.Initialize();
SeedingAlgorithm algorithm;
switch (seedAlg)
{
case SeedingAlgorithms.NoDispersal:
algorithm = NoDispersal.Algorithm;
break;
case SeedingAlgorithms.UniversalDispersal:
algorithm = UniversalDispersal.Algorithm;
break;
case SeedingAlgorithms.WardSeedDispersal:
algorithm = WardSeedDispersal.Algorithm;
break;
default:
throw new ArgumentException(string.Format("Unknown seeding algorithm: {0}", seedAlg));
}
Reproduction.Initialize(establishProbabilities, algorithm, addNewCohort);
}
public static bool Algorithm(ISpecies species,
ActiveSite site)
{
return(Reproduction.SufficientLight(species, site) &&
Reproduction.Establish(species, site) &&
Reproduction.MaturePresent(species, site));
}
//---------------------------------------------------------------------
/// <summary>
/// Initializes the instance and its associated site variables.
/// </summary>
protected void Initialize(int timestep,
double[,] establishProbabilities,
int startTime,
SeedingAlgorithms seedAlg,
Reproduction.AddNewCohortMethod addNewCohort)
{
this.timestep = timestep;
this.nextTimeToRun = startTime - 1 + timestep;
this.updateNextTimeToRun = false;
SiteVars.Initialize();
SeedingAlgorithm algorithm;
switch (seedAlg) {
case SeedingAlgorithms.NoDispersal:
algorithm = NoDispersal.Algorithm;
break;
case SeedingAlgorithms.UniversalDispersal:
algorithm = UniversalDispersal.Algorithm;
break;
case SeedingAlgorithms.WardSeedDispersal:
algorithm = WardSeedDispersal.Algorithm;
break;
default:
throw new ArgumentException(string.Format("Unknown seeding algorithm: {0}", seedAlg));
}
Reproduction.Initialize(establishProbabilities, algorithm, addNewCohort);
}
//---------------------------------------------------------------------
public void Do(ActiveSite site,
BitArray hasSeeded)
{
for (int i = 0; i < Model.Core.Species.Count; i++)
{
if (hasSeeded != null && hasSeeded[i])
{
continue;
}
ISpecies species = Model.Core.Species[i];
if (seedingAlgorithm(species, site))
{
Reproduction.AddNewCohort(species, site);
if (isDebugEnabled)
{
log.DebugFormat("site {0}: seeded {1}",
site.Location, species.Name);
}
if (hasSeeded != null)
{
hasSeeded[i] = true;
}
}
}
}
//---------------------------------------------------------------------
/// <summary>
/// Initializes the instance and its associated site variables.
/// </summary>
protected void Initialize(PlugIns.ICore modelCore,
double[,] establishProbabilities,
SeedingAlgorithms seedAlg,
Reproduction.Delegates.AddNewCohort addNewCohort)
{
Model.Core = modelCore;
SiteVars.Initialize();
Seeding.InitializeMaxSeedNeighborhood();
disturbedSites = new DisturbedSiteEnumerator(Model.Core.Landscape,
SiteVars.Disturbed);
SeedingAlgorithm algorithm;
switch (seedAlg) {
case SeedingAlgorithms.NoDispersal:
algorithm = NoDispersal.Algorithm;
break;
case SeedingAlgorithms.UniversalDispersal:
algorithm = UniversalDispersal.Algorithm;
break;
case SeedingAlgorithms.WardSeedDispersal:
algorithm = WardSeedDispersal.Algorithm;
break;
default:
throw new ArgumentException(string.Format("Unknown seeding algorithm: {0}", seedAlg));
}
Reproduction.Initialize(establishProbabilities, algorithm,
addNewCohort == null ? null : new Reproduction.Delegates.AddNewCohort(addNewCohort));
}
//---------------------------------------------------------------------
/// <summary>
/// Initializes the instance and its associated site variables.
/// </summary>
protected void Initialize(int timestep,
double[,] establishProbabilities)
{
this.timestep = timestep;
this.nextTimeToRun = timestep;
SiteVars.Initialize();
SiteVars.Reproduction.ActiveSiteValues = new ReproductionBySeeding(new UniversalSeeding());
Reproduction.SetEstablishProbabilities(establishProbabilities);
}
//---------------------------------------------------------------------
/// <summary>
/// Initializes the instance and its associated site variables.
/// </summary>
protected void Initialize(int timestep,
double[,] establishProbabilities)
{
this.timestep = timestep;
this.nextTimeToRun = timestep;
SiteVars.Initialize();
defaultReproduction = new Seeding(WardSeedDispersal.Algorithm);
SiteVars.Reproduction.ActiveSiteValues = defaultReproduction;
Reproduction.SetEstablishProbabilities(establishProbabilities);
}
//---------------------------------------------------------------------
public void Do(ActiveSite site)
{
for (int i = 0; i < Model.Species.Count; i++)
{
ISpecies species = Model.Species[i];
if (seedingAlgorithm(species, site))
{
Reproduction.AddNewCohort(species, site);
}
}
}
public static void Algorithm(//ISpecies species,
ActiveSite site)
{
foreach (ISpecies species in Model.Core.Species)
{
if (Reproduction.SufficientLight(species, site) && Reproduction.Establish(species, site))
{
Reproduction.AddNewCohort(species, site);
}
}
//return Reproduction.SufficientLight(species, site) &&
// Reproduction.Establish(species, site);
}
protected void Initialize(PlugIns.ICore modelCore,
double[,] establishProbabilities,
SeedingAlgorithms seedAlg,
Reproduction.AddNewCohortMethod addNewCohort)
{
Reproduction.Delegates.AddNewCohort wrappedMethod =
delegate(ISpecies species,
ActiveSite site)
{
addNewCohort(species, site);
};
Initialize(modelCore, establishProbabilities, seedAlg, wrappedMethod);
//new Reproduction.Delegates.AddNewCohort(addNewCohort));
// System.Delegate.CreateDelegate(typeof (Reproduction.Delegates.AddNewCohort),
// addNewCohort.Method));
}
//---------------------------------------------------------------------
public void Do(ActiveSite site)
{
for (int i = 0; i < Model.Core.Species.Count; i++)
{
ISpecies species = Model.Core.Species[i];
if (seedingAlgorithm(species, site))
{
Reproduction.AddNewCohort(species, site);
if (isDebugEnabled)
{
log.DebugFormat("site {0}: seeded {1}",
site.Location, species.Name);
}
}
}
}
//---------------------------------------------------------------------
bool IFormOfReproduction.TryAt(ActiveSite site)
{
bool success = false;
BitArray selectedSpeciesAtSite = selectedSpecies[site];
for (int index = 0; index < speciesDataset.Count; ++index)
{
if (selectedSpeciesAtSite.Get(index))
{
ISpecies species = speciesDataset[index];
if (PreconditionsSatisfied(species, site))
{
Reproduction.AddNewCohort(species, site);
success = true;
}
}
}
return(success);
}
//---------------------------------------------------------------------
public static bool Algorithm(ISpecies species,
ActiveSite site)
{
if (!Reproduction.SufficientLight(species, site) ||
!Reproduction.Establish(species, site))
{
return(false);
}
foreach (NeighborInfo neighborInfo in neighborhoods[species.Index])
{
ActiveSite neighbor = site.GetNeighbor(neighborInfo.RelativeLocation) as ActiveSite;
if (neighbor != null)
{
if (Util.Random.GenerateUniform() < neighborInfo.DistanceProbability)
{
return(true);
}
}
}
return(false);
}
//---------------------------------------------------------------------
public static void Algorithm(//ISpecies species,
ActiveSite site)
{
foreach (RelativeLocationWeighted reloc in Seeding.MaxSeedQuarterNeighborhood)
{
double distance = reloc.Weight;
foreach (ISpecies species in Model.Core.Species)
{
if (species.EffectiveSeedDist == EffectiveSeedDist.Universal)
{
if (Reproduction.SufficientLight(species, site) &&
Reproduction.Establish(species, site))
{
Reproduction.AddNewCohort(species, site);
break;
}
}
int EffD = species.EffectiveSeedDist;
int MaxD = species.MaxSeedDist;
if (distance > MaxD)
{
break; //Check no further
}
double dispersalProb = 0.0;
if (reloc.Location.Row == 0 && reloc.Location.Column == 0) //Check seeds on site
{
if (Reproduction.SufficientLight(species, site) &&
Reproduction.Establish(species, site) &&
Reproduction.MaturePresent(species, site))
{
Reproduction.AddNewCohort(species, site);
break;
}
}
else
{
dispersalProb = GetDispersalProbability(EffD, MaxD, distance);
//First check the Southeast quadrant:
Site neighbor = site.GetNeighbor(reloc.Location);
if (neighbor != null && neighbor.IsActive)
{
if (Reproduction.MaturePresent(species, neighbor))
{
if (dispersalProb > Landis.Util.Random.GenerateUniform())
{
Reproduction.AddNewCohort(species, site);
break;
}
}
}
//Next, check all other quadrants:
neighbor = site.GetNeighbor(new RelativeLocation(reloc.Location.Row * -1, reloc.Location.Column));
if (neighbor != null && neighbor.IsActive)
{
if (Reproduction.MaturePresent(species, neighbor))
{
if (dispersalProb > Landis.Util.Random.GenerateUniform())
{
Reproduction.AddNewCohort(species, site);
break;
}
}
}
neighbor = site.GetNeighbor(new RelativeLocation(reloc.Location.Row, reloc.Location.Column * -1));
if (neighbor != null && neighbor.IsActive)
{
if (Reproduction.MaturePresent(species, neighbor))
{
if (dispersalProb > Landis.Util.Random.GenerateUniform())
{
Reproduction.AddNewCohort(species, site);
break;
}
}
}
neighbor = site.GetNeighbor(new RelativeLocation(reloc.Location.Row * -1, reloc.Location.Column * -1));
if (neighbor != null && neighbor.IsActive)
{
if (Reproduction.MaturePresent(species, neighbor))
{
if (dispersalProb > Landis.Util.Random.GenerateUniform())
{
Reproduction.AddNewCohort(species, site);
break;
}
}
}
}
} //end species loop
} // end foreach relativelocation
return;
}
//---------------------------------------------------------------------
public static bool Algorithm(ISpecies species,
ActiveSite site)
{
if (!Reproduction.SufficientLight(species, site) ||
!Reproduction.Establish(species, site))
{
return(false);
}
if (Reproduction.MaturePresent(species, site))
{
return(true);
}
int row = (int)site.Location.Row;
int col = (int)site.Location.Column;
int cellDiam = (int)Model.CellLength;
int EffD = species.EffectiveSeedDist;
int MaxD = species.MaxSeedDist;
double ratio = 0.95; //the portion of the probability in the effective distance
//lambda1 parameterized for effective distance
double lambda1 = Math.Log(1 - ratio) / EffD;
//lambda2 parameterized for maximum distance
double lambda2 = Math.Log(0.01) / MaxD;
double lowBound = 0, upBound = 0;
//bool suitableDist=false;//flag to trigger if seed (plural) can get to a site based on distance probability
double distanceProb = 0.0;
int pixRange = Math.Max((int)((float)MaxD / (float)cellDiam), 1);
int maxrow = (int)Math.Min(row + pixRange, Model.Landscape.Rows);
int minrow = Math.Max(row - pixRange, 1);
for (int i = minrow; i <= maxrow; i++)
{
int x1, x2;
//float b = 5.0;
findX1X2(out x1, out x2, col, row, i, pixRange);
for (int j = x1; j <= x2; j++)
{
Location loc = new Location((uint)i, (uint)j);
if (Model.Landscape.GetSite(loc, ref neighbor) && neighbor.IsActive)
{
if (Reproduction.MaturePresent(species, neighbor))
{
float distance = (float)Math.Sqrt((float)((row - i) * (row - i) + (col - j) * (col - j))) * cellDiam; //Pythag
//set lower boundary to the theoretical (straight-line) edge of parent cell
lowBound = distance - cellDiam;
if (lowBound < 0)
{
lowBound = 0;
}
//set upper boundary to the outer theoretical boundary of the cell
upBound = distance;
if (cellDiam <= EffD)
{ //Draw probabilities from either EffD or MaxD curves
if (distance <= (float)EffD)
{ //BCW May 04
distanceProb = Math.Exp(lambda1 * lowBound) - Math.Exp(lambda1 * upBound);
}
else
{ //BCW May 04
distanceProb = (1 - ratio) * Math.Exp(lambda2 * (lowBound - EffD)) - (1 - ratio) * Math.Exp(lambda2 * (upBound - EffD));
}
}
else
{
if (distance <= cellDiam)
{ //Draw probabilities from both EffD and MaxD curves
distanceProb = Math.Exp(lambda1 * lowBound) - (1 - ratio) * Math.Exp(lambda2 * (upBound - EffD));
}
else
{
distanceProb = (1 - ratio) * Math.Exp(lambda2 * (lowBound - EffD)) - (1 - ratio) * Math.Exp(lambda2 * (upBound - EffD));
}
}
if (distanceProb > Landis.Util.Random.GenerateUniform()) // && frand() < l->probRepro(speciesNum)) Modified BCW May '04
{
// success = sites(row,col)->addNewCohort(s, sa, 10);
return(true);
}
}
} // if neighor is active
} // for each column, j, of current row in neighborhood
} // for each row, i, in the neighborhood
// Search failed.
return(false);
}
public bool Seeds(ISpecies species,
ActiveSite site)
{
return(Reproduction.SufficientLight(species, site) &&
Reproduction.Establish(species, site));
}
//---------------------------------------------------------------------
/// <summary>
/// Are the conditions necessary for planting a species at site
/// satified?
/// </summary>
protected override bool PreconditionsSatisfied(ISpecies species,
ActiveSite site)
{
return(Reproduction.GetEstablishProbability(species, site) > 0);
}
//---------------------------------------------------------------------
public static bool Algorithm(ISpecies species,
ActiveSite site)
{
if (species.EffectiveSeedDist == EffectiveSeedDist.Universal)
{
return(UniversalDispersal.Algorithm(species, site));
}
if (!Reproduction.SufficientLight(species, site))
{
if (isDebugEnabled)
{
log.DebugFormat("site {0}: {1} not seeded: insufficient light",
site.Location, species.Name);
}
return(false);
}
if (!Reproduction.Establish(species, site))
{
if (isDebugEnabled)
{
log.DebugFormat("site {0}: {1} not seeded: cannot establish",
site.Location, species.Name);
}
return(false);
}
if (Reproduction.MaturePresent(species, site))
{
if (isDebugEnabled)
{
log.DebugFormat("site {0}: {1} seeded on site",
site.Location, species.Name);
}
return(true);
}
if (isDebugEnabled)
{
log.DebugFormat("site {0}: search neighbors for {1}",
site.Location, species.Name);
}
//UI.WriteLine(" Ward seed disersal. Spp={0}, site={1},{2}.", species.Name, site.Location.Row, site.Location.Column);
foreach (RelativeLocationWeighted reloc in Seeding.MaxSeedQuarterNeighborhood)
{
double distance = reloc.Weight;
int rRow = (int)reloc.Location.Row;
int rCol = (int)reloc.Location.Column;
double EffD = (double)species.EffectiveSeedDist;
double MaxD = (double)species.MaxSeedDist;
if (distance > MaxD + ((double)Model.Core.CellLength / 2.0 * 1.414))
{
return(false); //Check no further
}
double dispersalProb = GetDispersalProbability(EffD, MaxD, distance);
//UI.WriteLine(" DispersalProb={0}, EffD={1}, MaxD={2}, distance={3}.", dispersalProb, EffD, MaxD, distance);
//First check the Southeast quadrant:
if (dispersalProb > Landis.Util.Random.GenerateUniform())
{
Site neighbor = site.GetNeighbor(reloc.Location);
if (neighbor != null && neighbor.IsActive)
{
if (Reproduction.MaturePresent(species, neighbor))
{
return(true);
}
}
}
//Next, check all other quadrants:
if (dispersalProb > Landis.Util.Random.GenerateUniform())
{
Site neighbor = site.GetNeighbor(new RelativeLocation(rRow * -1, rCol));
if (rCol == 0)
{
neighbor = site.GetNeighbor(new RelativeLocation(0, rRow));
}
if (neighbor != null && neighbor.IsActive)
{
if (Reproduction.MaturePresent(species, neighbor))
{
return(true);
}
}
}
if (dispersalProb > Landis.Util.Random.GenerateUniform())
{
Site neighbor = site.GetNeighbor(new RelativeLocation(rRow * -1, rCol * -1));
if (neighbor != null && neighbor.IsActive)
{
if (Reproduction.MaturePresent(species, neighbor))
{
return(true);
}
}
}
if (dispersalProb > Landis.Util.Random.GenerateUniform())
{
Site neighbor = site.GetNeighbor(new RelativeLocation(rRow, rCol * -1));
if (rCol == 0)
{
neighbor = site.GetNeighbor(new RelativeLocation(0, rRow * -1));
}
if (neighbor != null && neighbor.IsActive)
{
if (Reproduction.MaturePresent(species, neighbor))
{
return(true);
}
}
}
} // end foreach relativelocation
return(false);
}