/// <summary>
/// Constructs the behavior vector at the end of an individual evaluation.
/// </summary>
List<double> IBehaviorCharacterization.calculate(SimulatorExperiment exp, instance_pack ip)
{
// initialize the BC vector
BehaviorVector = new List<double>();
// If the robot never Stopped, set the max evaluation time as the end tick
if (endTick == 0)
endTick = exp.evaluationTime;
// Adjust end tick by the fraction we are sampling
endTick = (int)(endTick * 0.5);
// Calculate when to perform an update
int numBehaviorChunks = VectorLength / 2;
chunkSize = Convert.ToInt32(Math.Floor((double)endTick / (double)numBehaviorChunks)) * 2;
float x, y;
for (int chunkNum = 1; chunkNum < numBehaviorChunks + 1; chunkNum++)
{
// Take bc samples from the internal Trajectory store
x = Trajectory[chunkNum * chunkSize - 2];
x = (x - ip.env.AOIRectangle.Left) / ip.env.AOIRectangle.Width;
BehaviorVector.Add(x);
y = Trajectory[chunkNum * chunkSize - 1];
y = (y - ip.env.AOIRectangle.Top) / ip.env.AOIRectangle.Height;
BehaviorVector.Add(y);
}
return BehaviorVector;
}
/// <summary>
/// Constructs the behavior vector at the end of an individual evaluation.
/// </summary>
List <double> IBehaviorCharacterization.calculate(SimulatorExperiment exp, instance_pack ip)
{
// initialize the BC vector
BehaviorVector = new List <double>();
// If the robot never Stopped, set the max evaluation time as the end tick
if (endTick == 0)
{
endTick = exp.evaluationTime;
}
// Adjust end tick by the fraction we are sampling
endTick = (int)(endTick * 0.5);
// Calculate when to perform an update
int numBehaviorChunks = VectorLength / 2;
chunkSize = Convert.ToInt32(Math.Floor((double)endTick / (double)numBehaviorChunks)) * 2;
float x, y;
for (int chunkNum = 1; chunkNum < numBehaviorChunks + 1; chunkNum++)
{
// Take bc samples from the internal Trajectory store
x = Trajectory[chunkNum * chunkSize - 2];
x = (x - ip.env.AOIRectangle.Left) / ip.env.AOIRectangle.Width;
BehaviorVector.Add(x);
y = Trajectory[chunkNum * chunkSize - 1];
y = (y - ip.env.AOIRectangle.Top) / ip.env.AOIRectangle.Height;
BehaviorVector.Add(y);
}
return(BehaviorVector);
}
/// <summary>
/// Records the individual's location at each tick of the simulation.
/// </summary>
void IBehaviorCharacterization.update(SimulatorExperiment exp, instance_pack ip)
{
if (ip.robots[0].Stopped)
{
// If this is the first update after the robot has Stopped,
// send the endpoint to be the current simulation tick
if (endTick == 0)
{
endTick = Convert.ToInt32(ip.timeSteps * exp.timestep);
}
}
// initialize the Trajectory list
if (!Initialized)
{
// initialize the sensor value sampling/storage components
Trajectory = new List <int>(exp.evaluationTime * 2);
Initialized = true;
}
// update the Trajectory at every tick
Trajectory.Add(Convert.ToInt16(ip.robots[0].Location.X));
Trajectory.Add(Convert.ToInt16(ip.robots[0].Location.Y));
}
/// <summary>
/// Records the individual's location at each tick of the simulation.
/// </summary>
void IBehaviorCharacterization.update(SimulatorExperiment exp, instance_pack ip)
{
if (ip.robots[0].Stopped)
{
// If this is the first update after the robot has Stopped,
// send the endpoint to be the current simulation tick
if (endTick == 0)
endTick = Convert.ToInt32(ip.timeSteps * exp.timestep);
}
// initialize the Trajectory list
if (!Initialized)
{
// initialize the sensor value sampling/storage components
Trajectory = new List<int>(exp.evaluationTime * 2);
Initialized = true;
}
// update the Trajectory at every tick
Trajectory.Add(Convert.ToInt16(ip.robots[0].Location.X));
Trajectory.Add(Convert.ToInt16(ip.robots[0].Location.Y));
}
