public static Scene testScene_featuressimulation(double distmean, double diststd, int features)
{
var r = new Scene();
var c = new PinholeCamera(CameraIntrinsics.GOPROHERO3_BROWNR3_AFGEROND_EXTRADIST);
r.Add(c);
Random rand = new WH2006();
for (int i = 0; i < features; i++)
{
var sensorx = rand.NextDouble() * c.Intrinsics.PictureSize.Width;
var sensory = rand.NextDouble() * c.Intrinsics.PictureSize.Height;
var dist = Util.NextGaussian(distmean, diststd);
r.Add(CreateFeatureFromCamera(c, sensorx, sensory, dist, i));
}
return(r);
}
public static WH2006 wH2006 = new WH2006(); // random number generator
public static Func <int, int, float> ReturnFunction(float yMin, float yMax, bool rand, params int[] sizes) // returns a function
{
if (rand)
{
return((int rows, int columns) => (float)wH2006.NextDouble() * (yMax - yMin) + yMin); // random
}
else
{
return((int rows, int columns) => (yMax - yMin) / sizes[0] / sizes[1] * rows + columns * (yMax - yMin) / sizes[1] + yMin); // definiteve
}
}
public virtual IAction SelectAction(uint stateID)
{
//get current policy and normalize
var policy = this.GetPolicy(stateID);
//choose an action randomly based on policy/distribution for state
var prob = Rand.NextDouble();
var sum = 0d;
for (var i = 0; i < this.Actions.Count; i++)
{
sum += policy[(uint)i];
if (sum >= prob)
{
return(this.ActionList[i]);
}
}
//should never get here if policy is non-zero
return(this.SelectGreedyAction(stateID));
}