public override void Calculate()
{
Times = Generate.LinearSpaced(base.Samples, base.Start, base.Start + base.Duration);
PolyFit.FitAndGetPoints(UserTimes, UserValues, Order, Samples, Times, out double[] caculatedVariables);
values = caculatedVariables;
}
public DosingInterval(List <float> time, List <float> conc, PKCalculationOptions options)
{
_options = options;
_time = time;
_concentration = conc;
_timeSteps = ArrayHelper.TimeStepsFrom(time);
_polyFit = new PolyFit();
}
public PKInterval(List <float> time, List <float> concentration, PKCalculationOptions options, double?drugMassPerBodyWeight = null, double?concentrationThreshold = null)
{
_options = options;
DrugMassPerBodyWeight = drugMassPerBodyWeight;
_time = time;
_concentration = concentration;
_concentrationThreshold = concentrationThreshold;
_timeSteps = ArrayHelper.TimeStepsFrom(time);
_polyFit = new PolyFit();
}
/// <summary> Use LU Decomposition to approximate arc length and inverse arc length functions for faster computation. They will be used in the XML navigation file. </summary>
/// <returns>double[nbLanes,nbAnchors-1,2,3] with 2 being (arcLength,invArcLength) and 3 being(x^3,x^2,x)</returns>
public static double[,,,] ArcLengthApproximations(QuadraticPolynomial[,] lanePolynoms)
{
var arcLengthApproximations = new double[lanePolynoms.GetLength(0), lanePolynoms.GetLength(1), 2, 3];
var steps = new double[11];
var values = new double[11];
for (int j = 0; j < lanePolynoms.GetLength(0); j++)
{
for (int k = 0; k < lanePolynoms.GetLength(1); k++)
{
for (var i = 0; i < 11; i++)
{
steps[i] = i / 10d;
values[i] = lanePolynoms[j, k].ArcLength(0.0, steps[i]);
}
if (lanePolynoms[j, k]._coeffs[0, 0] < 0.0001 && lanePolynoms[j, k]._coeffs[0, 1] < 0.0001 && lanePolynoms[j, k]._coeffs[0, 2] < 0.0001)
{
arcLengthApproximations[j, k, 0, 0] = 0;
arcLengthApproximations[j, k, 1, 0] = 0;
arcLengthApproximations[j, k, 2, 0] = lanePolynoms[j, k].ArcLength(0.0, 1.0);
arcLengthApproximations[j, k, 0, 1] = 0;
arcLengthApproximations[j, k, 1, 1] = 0;
arcLengthApproximations[j, k, 2, 1] = 1 / arcLengthApproximations[j, k, 0, 2];
}
else
{
var aLen = new PolyFit(steps, values, 3);
arcLengthApproximations[j, k, 0, 0] = aLen.Coeff[3];
arcLengthApproximations[j, k, 1, 0] = aLen.Coeff[2];
arcLengthApproximations[j, k, 2, 0] = aLen.Coeff[1];
var invaLen = new PolyFit(values, steps, 3);
arcLengthApproximations[j, k, 0, 1] = invaLen.Coeff[3];
arcLengthApproximations[j, k, 1, 1] = invaLen.Coeff[2];
arcLengthApproximations[j, k, 2, 1] = invaLen.Coeff[1];
}
}
}
return(arcLengthApproximations);
}
public void BodePlot(ref List <List <float> > FrqDataList)
{
List <float> FrqList = new List <float>();
List <float> Ftest = new List <float>();
List <List <float> > BodeDataList = new List <List <float> >();
BodeDataList.Add(new List <float>());
BodeDataList.Add(new List <float>());
BodeDataList.Add(new List <float>());
// int Index = 0;
while (true)
{
if (FrqDataList[1][0] == 0)
{
Ftest.Add(FrqDataList[0][0]);
for (int i = 0; i < 3; i++)
{
FrqDataList[i].RemoveAt(0);
}
}
else
{
break;
}
}
while (true)
{
int last = FrqDataList[1].Count - 1;
if (FrqDataList[1][last] == 0)
{
Ftest.Add(FrqDataList[0][last]);
for (int i = 0; i < 3; i++)
{
FrqDataList[i].RemoveAt(last);
}
}
else
{
break;
}
}
//float b = FrqDataList[2].Average();
float b = -0.175022362F;
float DisAvg = Ftest.Average();
//float K = -0.142118886F;
int DataLength = FrqDataList[0].Count;
float DisturbanceMax = FrqDataList[1].Max(), DisturbanceMin = FrqDataList[1].Min();
for (int i = 0; i < DataLength - 1; i++)
{
FrqList.Add(FrqDataList[0][i]);
if (FrqDataList[2][i + 1] != FrqDataList[2][i] || i == DataLength - 1)
{
double[] xx = new double[FrqList.Count];
double[] yy = new double[FrqList.Count];
for (int j = 0; j < FrqList.Count; j++)
{
xx[j] = j;
yy[j] = FrqList[j];
}
//FrqDataList[2].GetRange(PhaseStart, (int)PeriodTimes).CopyTo(yy);
var polyfit = new PolyFit(xx, yy, 5);
var fitted = polyfit.Fit(xx);
BodeDataList[0].Add(FrqDataList[2][i]);
BodeDataList[1].Add((float)(20 * Math.Log10((fitted.Max() - fitted.Min()) / (DisturbanceMax - DisturbanceMin))));
FrqList.Clear();
}
}
double PeriodTimes = 0, PhaseDelay = 0;
int TCMDMaxIndex = 0, TCMDMinIndex = 0, FRTCMMaxIndex = 0, FRTCMMinIndex, PhaseStart = 0, PhaseEnd = 0, cctest = 0;
//Index = 0;
List <float> TCMDList = new List <float>();
List <float> FRTCMList = new List <float>();
for (int i = 0; i < DataLength - 1; i++)
{
if (FrqDataList[2][i + 1] != FrqDataList[2][i] || i == DataLength - 1)
{
PeriodTimes = (1 / FrqDataList[2][i]) * 1000 * 4;
PhaseStart = (i - (int)PeriodTimes + 1);
float Amp = (FrqDataList[0].GetRange(PhaseStart, (int)PeriodTimes).Max() - FrqDataList[0].GetRange(PhaseStart, (int)PeriodTimes).Min()) / 2;
double[] xx = new double[(int)PeriodTimes];
double[] yy = new double[(int)PeriodTimes];
for (int j = 0; j < (int)PeriodTimes; j++)
{
xx[j] = j;
yy[j] = FrqDataList[0][j + PhaseStart];
}
//FrqDataList[2].GetRange(PhaseStart, (int)PeriodTimes).CopyTo(yy);
var polyfit = new PolyFit(xx, yy, 4);
var fitted = polyfit.Fit(xx);
if ((FrqDataList[1][PhaseStart] >= 0 && fitted[0] >= 0) || (FrqDataList[1][PhaseStart] <= 0 && fitted[0] <= 0))
{
if (FrqDataList[1][PhaseStart] >= 0)
{
for (int j = PhaseStart; j < i + 1; j++)
{
if (FrqDataList[1][j] < 0)
{
FRTCMMaxIndex = j;
break;
}
}
for (int j = 0; j < (int)PeriodTimes; j++)
{
if (fitted[j] < DisAvg)
{
TCMDMaxIndex = j + PhaseStart;
break;
}
}
}
else if (FrqDataList[1][PhaseStart] <= 0)
{
for (int j = PhaseStart; j < i + 1; j++)
{
if (FrqDataList[1][j] > 0)
{
FRTCMMaxIndex = j;
break;
}
}
for (int j = 0; j < (int)PeriodTimes; j++)
{
if (fitted[j] > DisAvg)
{
TCMDMaxIndex = j + PhaseStart;
break;
}
}
}
PhaseDelay = (double)(FRTCMMaxIndex - TCMDMaxIndex) / PeriodTimes * 360;
}
else
{
if (FrqDataList[1][PhaseStart] >= 0)
{
for (int j = PhaseStart; j < i + 1; j++)
{
if (FrqDataList[1][j] < 0)
{
FRTCMMaxIndex = j;
break;
}
}
for (int j = 0; j < (int)PeriodTimes; j++)
{
if (fitted[j] > DisAvg)
{
TCMDMaxIndex = j + PhaseStart;
break;
}
}
}
else if (FrqDataList[1][PhaseStart] <= 0)
{
for (int j = PhaseStart; j < i + 1; j++)
{
if (FrqDataList[1][j] > 0)
{
FRTCMMaxIndex = j;
break;
}
}
for (int j = 0; j < (int)PeriodTimes; j++)
{
if (fitted[j] < DisAvg)
{
TCMDMaxIndex = j + PhaseStart;
break;
}
}
}
PhaseDelay = (double)(FRTCMMaxIndex - TCMDMaxIndex) / PeriodTimes * 360 - 180;
}
while (PhaseDelay < -330)
{
PhaseDelay += 360;
}
while (PhaseDelay > 30)
{
PhaseDelay += -360;
}
BodeDataList[2].Add((float)PhaseDelay);
}
}
//for (int i = 0; i < DataLength - 1; i++)
//{
// if (FrqDataList[2][i + 1] != FrqDataList[2][i] || i == DataLength - 1)
// {
// PeriodTimes = (1 / FrqDataList[2][i]) * 1000 * 4;
// double[] xx = new double[(int)PeriodTimes];
// double[] yy = new double[(int)PeriodTimes];
// for (int j = 0; j < (int)PeriodTimes; j++)
// {
// xx[j] = j;
// yy[j] = FrqDataList[0][j + PhaseStart];
// }
// var polyfit = new PolyFit(xx, yy, 10);
// var fitted = polyfit.Fit(xx);
// FRTCMMaxIndex = FrqDataList[1].GetRange(i, (int)PeriodTimes).IndexOf(FrqDataList[1].GetRange(i, (int)PeriodTimes).Max());
// FRTCMMinIndex = FrqDataList[1].GetRange(i, (int)PeriodTimes).IndexOf(FrqDataList[1].GetRange(i, (int)PeriodTimes).Min());
// TCMDMaxIndex = FrqDataList[2].GetRange(i, (int)PeriodTimes).IndexOf(FrqDataList[2].GetRange(i, (int)PeriodTimes).Max());
// TCMDMinIndex = FrqDataList[2].GetRange(i, (int)PeriodTimes).IndexOf(FrqDataList[2].GetRange(i, (int)PeriodTimes).Min());
// PhaseDelay = -(TCMDMaxIndex - FRTCMMaxIndex) / PeriodTimes * 360;
// if (PhaseDelay < -350)
// PhaseDelay += 360;
// else if (PhaseDelay > 10)
// PhaseDelay += -360;
// BodeDataList[2].Add((float)PhaseDelay);
// }
//}
FrqDataList.Clear();
FrqDataList = BodeDataList;
}
