private void PresentResults(int targetId, KweeVanWoerdenResult result, PolynomialFitResult polyResult = null)
{
var frmResults = new frmResults();
frmResults.Results = result;
frmResults.PolyResults = polyResult;
frmResults.TangraHost = m_TangraHost;
frmResults.TargetId = targetId;
frmResults.StartPosition = FormStartPosition.CenterParent;
frmResults.ShowDialog(m_TangraHost.ParentWindow);
}
private void ExecuteWithSimulatedData()
{
double[] times;
double[] varStar;
double[] varSky;
double[] compStar;
double[] compSky;
int dataPoints = 0;
byte[] bytes = LoadBytesFromEmbeddedResource("Input_Observations.bin");
double jdAtUtcMidnight = 2456967.1234567;
using (var memStr = new MemoryStream(bytes))
using (var rdr = new BinaryReader(memStr))
{
dataPoints = rdr.ReadInt32();
times = new double[dataPoints];
varStar = new double[dataPoints];
varSky = new double[dataPoints];
compStar = new double[dataPoints];
compSky = new double[dataPoints];
for (int i = 0; i < dataPoints; i++)
{
times[i] = rdr.ReadDouble() * 86400.0; // Convert from days to seconds
varStar[i] = rdr.ReadDouble();
varSky[i] = rdr.ReadDouble();
compStar[i] = rdr.ReadDouble();
compSky[i] = rdr.ReadDouble();
}
}
KweeVanWoerdenResult result = Kwee_van_Woerden(dataPoints, jdAtUtcMidnight, times, varStar, varSky, compStar, compSky, false);
PolynomialFitResult polyResult = PolynomialFit(dataPoints, jdAtUtcMidnight, times, varStar, varSky, compStar, compSky, (int)result.Start_Light_Curve_Obs_Index, (int)result.Stop_Light_Curve_Obs_Index, result.Time_Of_Minimum);
PresentResults(0, result, polyResult);
}
private void PresentResults(int targetId, KweeVanWoerdenResult result, PolynomialFitResult polyResult = null)
{
var frmResults = new frmResults();
frmResults.Results = result;
frmResults.PolyResults = polyResult;
frmResults.TangraHost = m_TangraHost;
frmResults.TargetId = targetId;
frmResults.StartPosition = FormStartPosition.CenterParent;
frmResults.ShowDialog(m_TangraHost.ParentWindow);
}
private KweeVanWoerdenResult Kwee_van_Woerden(
long Number_Obs, double Time_First_JD,
double[] SecondsFromTimeFirstJD, double[] Variable_Star_DN, double[] Variable_Sky_DN, double[] Comparison_Star_DN, double[] Comparison_Sky_DN,
bool fineGranedBins)
{
long BASE_NUMBER = fineGranedBins ? 1000 : 100;
/* Constant parameter */
long Normal_Points = BASE_NUMBER + 1; /* Number of evenly spaced data pairs used in the analysis */
long Normal_Point_Middle; /* Index of the middle element of the normal point array */
/* Luminosity values */
double[] Luminosity_Ratio; /* Variable luminosity divided by comparison luminosity */
double Luminosity_Normal_Sum; /* Summation of luminosities for normal point computation */
long Luminosity_Normal_Count; /* Counter for data points in one normal point */
double[] Luminosity_Normal = new double[BASE_NUMBER + 2]; /* Normalized luminosities */
/* Time values */
double Time_Interval; /* Time interval between observations */
double Time_Start, Time_Stop; /* Limits for normal points */
double[] Time_Normal = new double[BASE_NUMBER + 2]; /* Times corresponding to normal points */
/* Symmetry analysis */
double Luminosity_Faintest; /* Faintest normalized luminosity */
long Luminosity_Faintest_Index; /* Index of the faintest normalized luminosity */
long Start_Light_Curve; /* Start element of normalized light curve to analyze */
//long Middle_Light_Curve; /* Middle element of normalized light curve to analyze */
long Stop_Light_Curve; /* Stop element of normalized light curve to analyze */
long Start_Sum_Squares; /* Start element of the sum-of-squares array */
long Stop_Sum_Squares; /* Stop element of the sum-of-squares array */
double Sum_Of_Squares; /* Sum of squares across a time of symmetry */
long[] Sum_Of_Squares_Count = new long[BASE_NUMBER + 2]; /* Number of squares accumulated */
double[] Sum_Of_Squares_Mean = new double[BASE_NUMBER + 2]; /* Sum of squares divided by count */
long Sum_Of_Squares_Smallest_Index; /* Index of the smallest sum of squares */
double Sum_Of_Squares_Smallest; /* Smallest sum of squares */
/* Time of minimum and uncertainty */
double[] Quad = new double[4]; /* Inputs to the quadratic equation taken from the sums of squares */
double A, B, C; /* Intermediate values for quadratic equation */
double T0; /* Time of symmetry */
double T0_Uncertainty; /* Time of symmetry uncertainty */
//double Time_Of_Minimum; /* Time of minimum light */
//double Time_Of_Minimum_Uncertainty; /* Time of minimum light uncertainty */
/* Loop indices */
long i, j; /* Loop indices */
var rv = new KweeVanWoerdenResult()
{
NumberObservations = Number_Obs
};
rv.Observations_File.Add(" Time Luminosity_Ratio Variable_Star_DN Variable_Sky_DN Comparison_Star_DN Comparison_Sky_DN");
rv.Normals_File.Add(" Time Luminosity_Ratio");
double[] Time = new double[Number_Obs];
for (int k = 0; k < Number_Obs; k++)
Time[k] = SecondsFromTimeFirstJD[k] / 86400.0;
Luminosity_Ratio = new double[Number_Obs];
/* Determine luminosity ratios */
for (i = 0; i < Number_Obs; i++)
{
Luminosity_Ratio[i] = ( Variable_Star_DN[i] - Variable_Sky_DN[i] ) / ( Comparison_Star_DN[i] - Comparison_Sky_DN[i] );
rv.Observations_File.Add(
Time[i].ToString("#########0.000000").PadLeft(20) + " " +
Luminosity_Ratio[i].ToString("#########0.000000").PadLeft(20) + " " +
Variable_Star_DN[i].ToString("#########0.000000").PadLeft(20) + " " +
Variable_Sky_DN[i].ToString("#########0.000000").PadLeft(20) + " " +
Comparison_Star_DN[i].ToString("#########0.000000").PadLeft(20) + " " +
Comparison_Sky_DN[i].ToString("#########0.000000").PadLeft(20));
}
bool hasEmptyBins = false;
/* Compute normal point times and luminosities */
Time_Interval = ( Time[Number_Obs - 1] - Time[0] ) / (float)Normal_Points;
for (i = 0; i < Normal_Points; i++)
{
Time_Start = Time[0] + i * Time_Interval;
Time_Normal[i] = Time_Start + Time_Interval / 2.0;
Time_Stop = Time_Start + Time_Interval;
Luminosity_Normal_Sum = 0.0;
Luminosity_Normal_Count = 0;
for (j = 0; j < Number_Obs; j++ )
{
if ( ( Time[j] >= Time_Start ) && ( Time[j] < Time_Stop) )
{
Luminosity_Normal_Sum = Luminosity_Normal_Sum + Luminosity_Ratio[j];
Luminosity_Normal_Count = Luminosity_Normal_Count + 1;
}
}
if ( Luminosity_Normal_Count > 0 )
{
Luminosity_Normal[i] = Luminosity_Normal_Sum / (float)Luminosity_Normal_Count;
rv.Normals_File.Add(Time_Normal[i].ToString("#########0.000000").PadLeft(20) + " " + Luminosity_Normal[i].ToString("#########0.000000").PadLeft(20));
}
else
{
hasEmptyBins = true;
Luminosity_Normal[i] = double.NaN;
}
}
if (hasEmptyBins)
{
for (i = 0; i < Normal_Points; i++)
{
bool isEmptyBin = double.IsNaN(Luminosity_Normal[i]);
if (isEmptyBin)
{
double? prevBin2 = i <= 1 ? (double?)null : Luminosity_Normal[i - 2];
double? prevBin = i == 0 ? (double?) null : Luminosity_Normal[i - 1];
var emptyBins = new List<double>();
long k = i;
while (k < Normal_Points && double.IsNaN(Luminosity_Normal[k]))
{
k++;
emptyBins.Add(double.NaN);
}
double? nextBin = k == Normal_Points ? (double?)null : Luminosity_Normal[k];
double? nextBin2 = k + 1 < Normal_Points || k + 1 >= Luminosity_Normal.Length ? (double?)null : Luminosity_Normal[k + 1];
if ((prevBin == null && nextBin2 == null) || (prevBin2 == null && nextBin == null))
{
rv.ErrorMessage = "Too many empty bins!";
return rv;
}
double step = 0;
if (prevBin == null)
step = nextBin2.Value - nextBin.Value;
else if (nextBin == null)
step = prevBin.Value - prevBin2.Value;
else
step = (nextBin.Value - prevBin.Value) / (1 + emptyBins.Count);
for (int l = 0; l < emptyBins.Count; l++)
{
Luminosity_Normal[i + l] = prevBin.Value + l * step;
}
}
}
}
rv.Buckets.Clear();
rv.Buckets.AddRange(Luminosity_Normal);
/* Locate the faintest luminosity */
Luminosity_Faintest = 1000000000.0;
Luminosity_Faintest_Index = 0;
for (i = 0; i < Normal_Points; i++)
{
if ( Luminosity_Normal[i] < Luminosity_Faintest )
{
Luminosity_Faintest_Index = i;
Luminosity_Faintest = Luminosity_Normal[i];
}
}
/* Set the limits of the light curve to be symmetrical around the faintest luminosity */
Start_Light_Curve = 0;
Stop_Light_Curve = Normal_Points - 1;
Normal_Point_Middle = Normal_Points / 2;
if ( Luminosity_Faintest_Index < Normal_Point_Middle ) { Stop_Light_Curve = 2 * Luminosity_Faintest_Index; }
if ( Luminosity_Faintest_Index > Normal_Point_Middle ) { Start_Light_Curve = 2 * Luminosity_Faintest_Index - Normal_Points + 1; }
rv.IncludedObservations = 100 * (Stop_Light_Curve - Start_Light_Curve - 2) / BASE_NUMBER;
rv.Start_Light_Curve = Start_Light_Curve;
rv.Stop_Light_Curve = Stop_Light_Curve;
double startTime = Time[0] + Start_Light_Curve * Time_Interval;
double stopTime = Time[0] + (Stop_Light_Curve + 1) * Time_Interval;
long startIndex = 0;
long stopIndex = Number_Obs - 1;
for (int k = 0; k < Number_Obs; k++)
{
if (Start_Light_Curve > 0 && Time[k] <= startTime) startIndex = k + 1;
if (Stop_Light_Curve < Number_Obs - 1 && k > 1 && Time[k] > stopTime && Time[k - 1] < stopTime) stopIndex = k - 1;
}
rv.Start_Light_Curve_Obs_Index = startIndex;
rv.Stop_Light_Curve_Obs_Index = stopIndex;
/* Compute the normalized sums of squares of luminosity differences across an array of times */
Start_Sum_Squares = Start_Light_Curve + 1;
Stop_Sum_Squares = Stop_Light_Curve - 1;
for (i = Start_Sum_Squares; i <= Stop_Sum_Squares; i++)
{
Sum_Of_Squares = 0.0;
Sum_Of_Squares_Count[i] = 0;
for (j = 0; j < Normal_Points; j++)
{
if ( i - j >= 0 && i + j < Normal_Points )
{
Sum_Of_Squares = Sum_Of_Squares + Math.Pow(Luminosity_Normal[i-j] - Luminosity_Normal[i+j], 2);
Sum_Of_Squares_Count[i] = Sum_Of_Squares_Count[i] + 1;
}
}
Sum_Of_Squares_Mean[i] = Sum_Of_Squares / (float) Sum_Of_Squares_Count[i];
}
rv.Sum_Of_Squares_Count.Clear();
rv.Sum_Of_Squares_Count.AddRange(Sum_Of_Squares_Count);
rv.Sum_Of_Squares_Mean.Clear();
rv.Sum_Of_Squares_Mean.AddRange(Sum_Of_Squares_Mean);
/* Find the smallest normalized sum of squares */
Sum_Of_Squares_Smallest = 1000000000;
Sum_Of_Squares_Smallest_Index = 0;
for (i = Start_Sum_Squares; i <= Stop_Sum_Squares; i++)
{
if ( Sum_Of_Squares_Mean[i] < Sum_Of_Squares_Smallest )
{
/* Must also have a reasonable sample of points */
if ( Sum_Of_Squares_Count[i] > Normal_Points / 10 )
{
Sum_Of_Squares_Smallest_Index = i;
Sum_Of_Squares_Smallest = Sum_Of_Squares_Mean[i];
}
}
}
rv.Sum_Of_Squares_Smallest_Index = Sum_Of_Squares_Smallest_Index;
if (Sum_Of_Squares_Smallest_Index - 2 < 0 ||
Sum_Of_Squares_Smallest_Index + 2 > Sum_Of_Squares_Mean.Length - 1)
{
rv.ErrorMessage = string.Format("Cannot locate the smallest normalized sum of squares (Index = {0})", Sum_Of_Squares_Smallest_Index);
return rv;
}
/* Solve the quadratic equation */
for (i = 0; i <= 3; i++) {
Quad[i] = Sum_Of_Squares_Mean[Sum_Of_Squares_Smallest_Index+i-2];
}
A = -Quad[2] + ( Quad[3] + Quad[1] ) / 2.0;
B = -3.0 * A + Quad[2] - Quad[1];
C = Quad[1] - A - B;
/* Calculate the time of minimum and uncertainty */
T0 = -B / ( 2.0 * A );
T0_Uncertainty = Math.Sqrt((4.0 * A * C - B * B) / (4.0 * A * A) / ((float)Normal_Points / 4.0 - 1.0));
rv.T0 = T0;
rv.T0_Uncertainty = T0_Uncertainty;
rv.Time_Of_Minimum = Time_Normal[1] + ((Sum_Of_Squares_Smallest_Index - 1) + (T0 - 2.0)) * Time_Interval;
rv.Time_Of_Minimum_JD = Time_First_JD + rv.Time_Of_Minimum;
rv.Time_Of_Minimum_Uncertainty = T0_Uncertainty * Time_Interval;
rv.Success = true;
rv.Summary_File.Add(string.Format(" Time_First Number_Obs"));
rv.Summary_File.Add(Time_First_JD.ToString("#########0.000000").PadLeft(20) + " " + Number_Obs.ToString("#########0").PadLeft(20));
rv.Summary_File.Add(string.Format("\n Time of minimum: \n"));
rv.Summary_File.Add(string.Format(" Bins-Quadratic Uncertainty"));
rv.Summary_File.Add(T0.ToString("#########0.000000").PadLeft(20) + " " + T0_Uncertainty.ToString("#########0.000000").PadLeft(20));
rv.Summary_File.Add(string.Format(" From Time_First Uncertainty"));
rv.Summary_File.Add(rv.Time_Of_Minimum.ToString("#########0.000000").PadLeft(20) + " " + rv.Time_Of_Minimum_Uncertainty.ToString("#########0.000000").PadLeft(20));
rv.Summary_File.Add(string.Format(" Absolute Uncertainty"));
rv.Summary_File.Add(rv.Time_Of_Minimum_JD.ToString("#########0.000000").PadLeft(20) + " " + rv.Time_Of_Minimum_Uncertainty.ToString("#########0.000000").PadLeft(20));
/* Finish */
return rv;
}
private KweeVanWoerdenResult Kwee_van_Woerden(
long Number_Obs, double Time_First_JD,
double[] SecondsFromTimeFirstJD, double[] Variable_Star_DN, double[] Variable_Sky_DN, double[] Comparison_Star_DN, double[] Comparison_Sky_DN,
bool fineGranedBins)
{
long BASE_NUMBER = fineGranedBins ? 1000 : 100;
/* Constant parameter */
long Normal_Points = BASE_NUMBER + 1; /* Number of evenly spaced data pairs used in the analysis */
long Normal_Point_Middle; /* Index of the middle element of the normal point array */
/* Luminosity values */
double[] Luminosity_Ratio; /* Variable luminosity divided by comparison luminosity */
double Luminosity_Normal_Sum; /* Summation of luminosities for normal point computation */
long Luminosity_Normal_Count; /* Counter for data points in one normal point */
double[] Luminosity_Normal = new double[BASE_NUMBER + 2]; /* Normalized luminosities */
/* Time values */
double Time_Interval; /* Time interval between observations */
double Time_Start, Time_Stop; /* Limits for normal points */
double[] Time_Normal = new double[BASE_NUMBER + 2]; /* Times corresponding to normal points */
/* Symmetry analysis */
double Luminosity_Faintest; /* Faintest normalized luminosity */
long Luminosity_Faintest_Index; /* Index of the faintest normalized luminosity */
long Start_Light_Curve; /* Start element of normalized light curve to analyze */
//long Middle_Light_Curve; /* Middle element of normalized light curve to analyze */
long Stop_Light_Curve; /* Stop element of normalized light curve to analyze */
long Start_Sum_Squares; /* Start element of the sum-of-squares array */
long Stop_Sum_Squares; /* Stop element of the sum-of-squares array */
double Sum_Of_Squares; /* Sum of squares across a time of symmetry */
long[] Sum_Of_Squares_Count = new long[BASE_NUMBER + 2]; /* Number of squares accumulated */
double[] Sum_Of_Squares_Mean = new double[BASE_NUMBER + 2]; /* Sum of squares divided by count */
long Sum_Of_Squares_Smallest_Index; /* Index of the smallest sum of squares */
double Sum_Of_Squares_Smallest; /* Smallest sum of squares */
/* Time of minimum and uncertainty */
double[] Quad = new double[4]; /* Inputs to the quadratic equation taken from the sums of squares */
double A, B, C; /* Intermediate values for quadratic equation */
double T0; /* Time of symmetry */
double T0_Uncertainty; /* Time of symmetry uncertainty */
//double Time_Of_Minimum; /* Time of minimum light */
//double Time_Of_Minimum_Uncertainty; /* Time of minimum light uncertainty */
/* Loop indices */
long i, j; /* Loop indices */
var rv = new KweeVanWoerdenResult()
{
NumberObservations = Number_Obs
};
rv.Observations_File.Add(" Time Luminosity_Ratio Variable_Star_DN Variable_Sky_DN Comparison_Star_DN Comparison_Sky_DN");
rv.Normals_File.Add(" Time Luminosity_Ratio");
double[] Time = new double[Number_Obs];
for (int k = 0; k < Number_Obs; k++)
{
Time[k] = SecondsFromTimeFirstJD[k] / 86400.0;
}
Luminosity_Ratio = new double[Number_Obs];
/* Determine luminosity ratios */
for (i = 0; i < Number_Obs; i++)
{
Luminosity_Ratio[i] = (Variable_Star_DN[i] - Variable_Sky_DN[i]) / (Comparison_Star_DN[i] - Comparison_Sky_DN[i]);
rv.Observations_File.Add(
Time[i].ToString("#########0.000000").PadLeft(20) + " " +
Luminosity_Ratio[i].ToString("#########0.000000").PadLeft(20) + " " +
Variable_Star_DN[i].ToString("#########0.000000").PadLeft(20) + " " +
Variable_Sky_DN[i].ToString("#########0.000000").PadLeft(20) + " " +
Comparison_Star_DN[i].ToString("#########0.000000").PadLeft(20) + " " +
Comparison_Sky_DN[i].ToString("#########0.000000").PadLeft(20));
}
bool hasEmptyBins = false;
/* Compute normal point times and luminosities */
Time_Interval = (Time[Number_Obs - 1] - Time[0]) / (float)Normal_Points;
for (i = 0; i < Normal_Points; i++)
{
Time_Start = Time[0] + i * Time_Interval;
Time_Normal[i] = Time_Start + Time_Interval / 2.0;
Time_Stop = Time_Start + Time_Interval;
Luminosity_Normal_Sum = 0.0;
Luminosity_Normal_Count = 0;
for (j = 0; j < Number_Obs; j++)
{
if ((Time[j] >= Time_Start) && (Time[j] < Time_Stop))
{
Luminosity_Normal_Sum = Luminosity_Normal_Sum + Luminosity_Ratio[j];
Luminosity_Normal_Count = Luminosity_Normal_Count + 1;
}
}
if (Luminosity_Normal_Count > 0)
{
Luminosity_Normal[i] = Luminosity_Normal_Sum / (float)Luminosity_Normal_Count;
rv.Normals_File.Add(Time_Normal[i].ToString("#########0.000000").PadLeft(20) + " " + Luminosity_Normal[i].ToString("#########0.000000").PadLeft(20));
}
else
{
hasEmptyBins = true;
Luminosity_Normal[i] = double.NaN;
}
}
if (hasEmptyBins)
{
for (i = 0; i < Normal_Points; i++)
{
bool isEmptyBin = double.IsNaN(Luminosity_Normal[i]);
if (isEmptyBin)
{
double?prevBin2 = i <= 1 ? (double?)null : Luminosity_Normal[i - 2];
double?prevBin = i == 0 ? (double?)null : Luminosity_Normal[i - 1];
var emptyBins = new List <double>();
long k = i;
while (k < Normal_Points && double.IsNaN(Luminosity_Normal[k]))
{
k++;
emptyBins.Add(double.NaN);
}
double?nextBin = k == Normal_Points ? (double?)null : Luminosity_Normal[k];
double?nextBin2 = k + 1 < Normal_Points || k + 1 >= Luminosity_Normal.Length ? (double?)null : Luminosity_Normal[k + 1];
if ((prevBin == null && nextBin2 == null) || (prevBin2 == null && nextBin == null))
{
rv.ErrorMessage = "Too many empty bins!";
return(rv);
}
double step = 0;
if (prevBin == null)
{
step = nextBin2.Value - nextBin.Value;
}
else if (nextBin == null)
{
step = prevBin.Value - prevBin2.Value;
}
else
{
step = (nextBin.Value - prevBin.Value) / (1 + emptyBins.Count);
}
for (int l = 0; l < emptyBins.Count; l++)
{
Luminosity_Normal[i + l] = prevBin.Value + l * step;
}
}
}
}
rv.Buckets.Clear();
rv.Buckets.AddRange(Luminosity_Normal);
/* Locate the faintest luminosity */
Luminosity_Faintest = 1000000000.0;
Luminosity_Faintest_Index = 0;
for (i = 0; i < Normal_Points; i++)
{
if (Luminosity_Normal[i] < Luminosity_Faintest)
{
Luminosity_Faintest_Index = i;
Luminosity_Faintest = Luminosity_Normal[i];
}
}
/* Set the limits of the light curve to be symmetrical around the faintest luminosity */
Start_Light_Curve = 0;
Stop_Light_Curve = Normal_Points - 1;
Normal_Point_Middle = Normal_Points / 2;
if (Luminosity_Faintest_Index < Normal_Point_Middle)
{
Stop_Light_Curve = 2 * Luminosity_Faintest_Index;
}
if (Luminosity_Faintest_Index > Normal_Point_Middle)
{
Start_Light_Curve = 2 * Luminosity_Faintest_Index - Normal_Points + 1;
}
rv.IncludedObservations = 100 * (Stop_Light_Curve - Start_Light_Curve - 2) / BASE_NUMBER;
rv.Start_Light_Curve = Start_Light_Curve;
rv.Stop_Light_Curve = Stop_Light_Curve;
double startTime = Time[0] + Start_Light_Curve * Time_Interval;
double stopTime = Time[0] + (Stop_Light_Curve + 1) * Time_Interval;
long startIndex = 0;
long stopIndex = Number_Obs - 1;
for (int k = 0; k < Number_Obs; k++)
{
if (Start_Light_Curve > 0 && Time[k] <= startTime)
{
startIndex = k + 1;
}
if (Stop_Light_Curve < Number_Obs - 1 && k > 1 && Time[k] > stopTime && Time[k - 1] < stopTime)
{
stopIndex = k - 1;
}
}
rv.Start_Light_Curve_Obs_Index = startIndex;
rv.Stop_Light_Curve_Obs_Index = stopIndex;
/* Compute the normalized sums of squares of luminosity differences across an array of times */
Start_Sum_Squares = Start_Light_Curve + 1;
Stop_Sum_Squares = Stop_Light_Curve - 1;
for (i = Start_Sum_Squares; i <= Stop_Sum_Squares; i++)
{
Sum_Of_Squares = 0.0;
Sum_Of_Squares_Count[i] = 0;
for (j = 0; j < Normal_Points; j++)
{
if (i - j >= 0 && i + j < Normal_Points)
{
Sum_Of_Squares = Sum_Of_Squares + Math.Pow(Luminosity_Normal[i - j] - Luminosity_Normal[i + j], 2);
Sum_Of_Squares_Count[i] = Sum_Of_Squares_Count[i] + 1;
}
}
Sum_Of_Squares_Mean[i] = Sum_Of_Squares / (float)Sum_Of_Squares_Count[i];
}
rv.Sum_Of_Squares_Count.Clear();
rv.Sum_Of_Squares_Count.AddRange(Sum_Of_Squares_Count);
rv.Sum_Of_Squares_Mean.Clear();
rv.Sum_Of_Squares_Mean.AddRange(Sum_Of_Squares_Mean);
/* Find the smallest normalized sum of squares */
Sum_Of_Squares_Smallest = 1000000000;
Sum_Of_Squares_Smallest_Index = 0;
for (i = Start_Sum_Squares; i <= Stop_Sum_Squares; i++)
{
if (Sum_Of_Squares_Mean[i] < Sum_Of_Squares_Smallest)
{
/* Must also have a reasonable sample of points */
if (Sum_Of_Squares_Count[i] > Normal_Points / 10)
{
Sum_Of_Squares_Smallest_Index = i;
Sum_Of_Squares_Smallest = Sum_Of_Squares_Mean[i];
}
}
}
rv.Sum_Of_Squares_Smallest_Index = Sum_Of_Squares_Smallest_Index;
if (Sum_Of_Squares_Smallest_Index - 2 < 0 ||
Sum_Of_Squares_Smallest_Index + 2 > Sum_Of_Squares_Mean.Length - 1)
{
rv.ErrorMessage = string.Format("Cannot locate the smallest normalized sum of squares (Index = {0})", Sum_Of_Squares_Smallest_Index);
return(rv);
}
/* Solve the quadratic equation */
for (i = 0; i <= 3; i++)
{
Quad[i] = Sum_Of_Squares_Mean[Sum_Of_Squares_Smallest_Index + i - 2];
}
A = -Quad[2] + (Quad[3] + Quad[1]) / 2.0;
B = -3.0 * A + Quad[2] - Quad[1];
C = Quad[1] - A - B;
/* Calculate the time of minimum and uncertainty */
T0 = -B / (2.0 * A);
T0_Uncertainty = Math.Sqrt((4.0 * A * C - B * B) / (4.0 * A * A) / ((float)Normal_Points / 4.0 - 1.0));
rv.T0 = T0;
rv.T0_Uncertainty = T0_Uncertainty;
rv.Time_Of_Minimum = Time_Normal[1] + ((Sum_Of_Squares_Smallest_Index - 1) + (T0 - 2.0)) * Time_Interval;
rv.Time_Of_Minimum_JD = Time_First_JD + rv.Time_Of_Minimum;
rv.Time_Of_Minimum_Uncertainty = T0_Uncertainty * Time_Interval;
rv.Success = true;
rv.Summary_File.Add(string.Format(" Time_First Number_Obs"));
rv.Summary_File.Add(Time_First_JD.ToString("#########0.000000").PadLeft(20) + " " + Number_Obs.ToString("#########0").PadLeft(20));
rv.Summary_File.Add(string.Format("\n Time of minimum: \n"));
rv.Summary_File.Add(string.Format(" Bins-Quadratic Uncertainty"));
rv.Summary_File.Add(T0.ToString("#########0.000000").PadLeft(20) + " " + T0_Uncertainty.ToString("#########0.000000").PadLeft(20));
rv.Summary_File.Add(string.Format(" From Time_First Uncertainty"));
rv.Summary_File.Add(rv.Time_Of_Minimum.ToString("#########0.000000").PadLeft(20) + " " + rv.Time_Of_Minimum_Uncertainty.ToString("#########0.000000").PadLeft(20));
rv.Summary_File.Add(string.Format(" Absolute Uncertainty"));
rv.Summary_File.Add(rv.Time_Of_Minimum_JD.ToString("#########0.000000").PadLeft(20) + " " + rv.Time_Of_Minimum_Uncertainty.ToString("#########0.000000").PadLeft(20));
/* Finish */
return(rv);
}
