/// <summary>
/// Reset the internal state of the evaluation scheme if any exists.
/// Note. The XOR problem domain has no internal state. This method does nothing.
/// </summary>
public void Reset()
{
IDMotorUtils.SetCSVData(false);
_Data = IDMotorUtils.GetData;
_rows = new int[_Data.GetLength(0)];
for (int i = 0; i < _Data.GetLength(0); i++)
{
_rows[i] = _Data[i].GetLength(0);
}
_MaxFitness = 2 * IDMotorUtils.GetMaxFitness;
StopFitness = _MaxFitness * (1 - tol);
}
/// <summary>
/// Evaluate the provided IBlackBox against the IDMotor problem domain and return its fitness score.
/// </summary>
public FitnessInfo Evaluate(IBlackBox box)
{
if (_evalCount == 0)
{
Reset();
}
double ePAgg = 0, eVAgg = 0;
double fitness = 0;
double afitness = 0;
double[] error;
double output;
double[] pos;
double[] posD;
double[] h;
ISignalArray inputArr = box.InputSignalArray;
ISignalArray outputArr = box.OutputSignalArray;
//
_evalCount++;
/*
#region Null test
* box.ResetState();
* rt = new Random();
* output = 0;
* for (int i =0; i <100;i++)
* {
* inputArr[0] = rt.NextDouble();
* inputArr[1] = 0;
* if (i==0)
* inputArr[2] = 0;
* else
* inputArr[2] = output;
* box.Activate();
* output = outputArr[0];
* ePAgg += Math.Abs(output);
* }
*
#endregion
*/
for (int k = 0; k < _Data.GetLength(0); k++)
{
error = new double[_rows[k]];
pos = new double[_rows[k]];
posD = new double[_rows[k]];
h = new double[_rows[k]];
initialCondition = _Data[k][0, 2];
//----- First Test
box.ResetState();
// Set the input values
inputArr[0] = _Data[k][0, 0];
h[0] = inputArr[0];
inputArr[1] = _Data[k][0, 1];
inputArr[2] = initialCondition;
posD[0] = _Data[k][0, 2];
//box.OutputSignalArray[0] = initialCondition;
// Activate the black box.
box.Activate();
if (!box.IsStateValid)
{ // Any black box that gets itself into an invalid state is unlikely to be
// any good, so lets just bail out here.
return(FitnessInfo.Zero);
}
// Read output signal.
output = outputArr[0];
pos[0] = output;
// Calculate this test case's contribution to the overall fitness score.
error[0] = _Data[k][0, 2] - output;
if (System.Math.Abs(error[0]) > tol)
{
ePAgg += System.Math.Abs(error[0]);
}
//----- Rest of the Tests
// Set the input values
for (int i = 1; i < _rows[k]; i++)
{
inputArr[0] = _Data[k][i, 0] - _Data[k][i - 1, 0];
h[i] = inputArr[0];
inputArr[1] = _Data[k][i, 1];
inputArr[2] = output;
posD[i] = _Data[k][i, 2];
// Activate the black box.
box.Activate();
if (!box.IsStateValid)
{ // Any black box that gets itself into an invalid state is unlikely to be
// any good, so lets just bail out here.
return(FitnessInfo.Zero);
}
// Read output signal.
output = outputArr[0];
pos[i] = output;
// Calculate this test case's contribution to the overall fitness score.
error[i] = _Data[k][i, 2] - output;
if (System.Math.Abs(error[i]) > tol)
{
ePAgg += System.Math.Abs(error[i]);
}
/*
* if (error[i] * error[i] > tol)
* ePAgg += error[i] * error[i];*/
}
double[] vel = IDMotorUtils.Derivate(pos, h);
double[] velD = IDMotorUtils.Derivate(posD, h);
for (int i = 0; i < _rows[k]; i++)
{
eVAgg += System.Math.Abs(velD[i] - vel[i]);
}
}
afitness = _MaxFitness - eVAgg;
fitness = _MaxFitness - kp * ePAgg - kv * eVAgg;
/*if (fitness >= StopFitness) {
* _stopConditionSatisfied = true;
* }
*/
_stopConditionSatisfied = fitness >= StopFitness;
if (fitness >= 0 && afitness >= 0)
{
return(new FitnessInfo(fitness, afitness));
}
return(FitnessInfo.Zero);
}
