static double ComputeSmoothness(List <HistoryItem> history)
{
// for every point in [3, length-3], generate quadratic function for points [t - 3, t + 3].
// Then compute squared error for point.
double errSum = 0.0d;
for (int i = 3; i < history.Count - 3; i++)
{
var timeRange = new Range(i - 3, i + 4, 1);
var relevantPoints = history.GetRange(i - 3, 7);
var t = (from n in timeRange
select n).ToArray();
var fitFuncX = Fitters.GeneratePolynomialFitFunction(
timeRange,
(from point in relevantPoints
select point.Value.X).ToList(),
2);
var fitFuncY = Fitters.GeneratePolynomialFitFunction(
timeRange,
(from point in relevantPoints
select point.Value.Y).ToList(),
2);
var errX = fitFuncX(i);
var errY = fitFuncY(i);
errSum += errX + errY; // Return summed error.
}
return(errSum / history.Count);
}
public Vector2D ComputeCommand(WorldState worldState, Vector2D baseCommand)
{
// Create a range for t values.
var ts = new Range(0, Math.Min(HistoryLength, worldState.InputHistory.Count), 1);
// Fit a function on input for x-axis.
Func <double, double> funcX =
Fitters.GeneratePolynomialFitFunction(
ts,
(from l in worldState.InputHistory.TakeLast(HistoryLength)
select l.Value.X).ToList(),
FitFunctionDegree
);
// Fit a function on input fo y-axis.
Func <double, double> funcY =
Fitters.GeneratePolynomialFitFunction(
ts,
(from l in worldState.InputHistory.TakeLast(HistoryLength)
select l.Value.Y).ToList(),
FitFunctionDegree
);
// Predict next value and return.
double time = HistoryLength + 1;
var ret = new Vector2D(funcX(time), funcY(time));
if (double.IsNaN(ret.X))
{
ret.X = 0.0;
}
if (double.IsNaN(ret.Y))
{
ret.Y = 0.0;
}
return(ret.GetNormalized());
}