//step 2
/// <summary>
/// Computes the destinations in a parallel thread
/// </summary>
/// <param name="externalDepth">The external depth of view.</param>
/// <param name="desiredNumber">The desired number of destinations to keep after simplification.</param>
/// <param name="cellularFloor">The cellular floor.</param>
/// <param name="staticCost">The static cost.</param>
/// <param name="Tolerance">The tolerance.</param>
public void ComputeDestinations(double externalDepth, int desiredNumber,
CellularFloor cellularFloor, Dictionary <Cell, double> staticCost, double Tolerance = OSMDocument.AbsoluteTolerance)
{
AgentEscapeRoutes agentScapeRoutes = null;
try
{
agentScapeRoutes = CellularIsovistCalculator.GetAgentEscapeRoutes(this.VantageCell,
externalDepth, desiredNumber, cellularFloor, staticCost, Tolerance);
}
catch (Exception er)
{
this.Error = er.Report();
}
if (agentScapeRoutes == null)
{
this._destinations = null;
}
else
{
this._destinations = agentScapeRoutes.Destinations;
}
}
private void updateDestination()
{
try
{
//update the destination
AgentEscapeRoutes escapeRoute = null;
var vantageCell = this._cellularFloor.FindCell(this.CurrentState.Location);
if (!this._escapeRouts.ContainsKey(vantageCell))
{
try
{
escapeRoute = CellularIsovistCalculator.GetAgentEscapeRoutes(
vantageCell,
this._isovistExternalRadius,
this._destinationCount,
this._cellularFloor,
this._staticCost,
0.0000001d);
}
catch (Exception)
{
//throw new ArgumentException("Escape Routes cannot be calculated for the agent training!");
//MessageBox.Show(e.Report());
//try
//{
// escapeRoute = CellularIsovistCalculator.GetAgentEscapeRoutes(
// vantageCell,
// this._isovistRadius,
// this._destinationCount,
// this._cellularFloor,
// this._staticCost,
// 0.0000001d);
//}
//catch (Exception) { }
}
if (escapeRoute == null)
{
return;
}
this._escapeRouts.Add(vantageCell, escapeRoute);
}
else
{
escapeRoute = this._escapeRouts[vantageCell];
}
this.DecisionMakingPeriod = this.DecisionMakingPeriodDistribution.Sample();
this.WalkTime = 0.0d;
//updating desired state
//filtering the destinations to those in the cone of vision
var visibleDestinationList = new List <AgentCellDestination>();
foreach (var item in escapeRoute.Destinations)
{
UV direction = item.Destination - this.CurrentState.Location;
direction.Unitize();
if (direction.DotProduct(this.CurrentState.Direction) >= this.VisibilityCosineFactor)
{
visibleDestinationList.Add(item);
}
}
AgentCellDestination[] destinations;
if (visibleDestinationList.Count > 0)
{
destinations = visibleDestinationList.ToArray();
visibleDestinationList.Clear();
visibleDestinationList = null;
}
else
{
destinations = escapeRoute.Destinations;
}
double[] normalizedAngleCost = new double[destinations.Length]; //between zero and 1
for (int i = 0; i < destinations.Length; i++)
{
UV direction = destinations[i].Destination - this.CurrentState.Location;
direction.Unitize();
normalizedAngleCost[i] = (direction.DotProduct(this.CurrentState.Direction) + 1) / 2;
}
double[] weighted = new double[destinations.Length];
double sum = 0;
for (int i = 0; i < destinations.Length; i++)
{
weighted[i] = this.AngleDistributionLambdaFactor * Math.Exp(-this.AngleDistributionLambdaFactor * normalizedAngleCost[i]) +
this.DesirabilityDistributionLambdaFactor * Math.Exp(-this.DesirabilityDistributionLambdaFactor * destinations[i].DesirabilityCost);
sum += weighted[i];
}
double selected = this._random.NextDouble() * sum;
sum = 0;
int selectedIndex = 0;
for (int i = 0; i < destinations.Length; i++)
{
sum += weighted[i];
if (sum > selected)
{
selectedIndex = i;
break;
}
}
this.Destination = destinations[selectedIndex].Destination;
}
catch (Exception)
{
//MessageBox.Show(e.Report());
}
}
