public static double ComputeWeight(WeightingMode mode, double solutionUncertaintyArcSec, double fwhmArcSec, double snr, double detection, double minUncertainty)
{
if (mode == WeightingMode.SNR)
{
// Positional uncertainty estimation by Neuschaefer and Windhorst 1994
var sigmaPosition = fwhmArcSec / (2.355 * snr);
if (sigmaPosition < minUncertainty)
{
sigmaPosition = minUncertainty;
}
var combinedUncertainty = Math.Sqrt(sigmaPosition * sigmaPosition + solutionUncertaintyArcSec * solutionUncertaintyArcSec);
return(1 / (combinedUncertainty * combinedUncertainty));
}
else if (mode == WeightingMode.SolutionUncertainty)
{
if (solutionUncertaintyArcSec < minUncertainty)
{
return(1 / (minUncertainty * minUncertainty));
}
else
{
return(1 / (solutionUncertaintyArcSec * solutionUncertaintyArcSec));
}
}
else if (mode == WeightingMode.Detection)
{
return(detection / (solutionUncertaintyArcSec * solutionUncertaintyArcSec));
}
return(1);
}
private void Recalculate()
{
if (m_DataProvider != null && !m_LoadingData)
{
WeightingMode mode = WeightingMode.None;
if (rbWeightingPosAstr.Checked)
{
mode = WeightingMode.SNR;
}
else if (rbWeightingAstr.Checked)
{
mode = WeightingMode.SolutionUncertainty;
}
var settings = new ReductionSettings()
{
InstrumentalDelaySec = nudInstDelaySec.Value,
Weighting = mode,
NumberOfChunks = (int)nudMeaIntervals.Value,
RemoveOutliers = cbxOutlierRemoval.Checked,
ConstraintPattern = cbxContraintPattern.SelectedIndex,
BestPositionUncertaintyArcSec = TangraConfig.Settings.Astrometry.AssumedPositionUncertaintyPixels * (double)nudPixelsPerArcSec.Value,
SmallestReportedUncertaintyArcSec = TangraConfig.Settings.Astrometry.SmallestReportedUncertaintyArcSec,
FactorInPositionalUncertainty = cbxFactorInPositionalUncertainty.Checked,
ErrorMethod = (ErrorMethod)cbxErrorMethod.SelectedIndex,
OutliersSigmaThreashold = (double)nudSigmaExclusion.Value
};
m_PositionExtractor.Calculate(
m_DataProvider,
settings);
Replot();
var lines = m_PositionExtractor.ExtractPositions(tbxObsCode.Text, tbxObjectDesign.Text, dtpDate.Value.Date, m_RovingObservatoryProvider);
tbxMeasurements.Text = string.Join("\r\n", lines);
}
}
private double ComputePositionWeight(double solutionUncertaintyArcSec, SingleMultiFrameMeasurement measurement, double minUncertainty, WeightingMode mode)
{
if (mode == WeightingMode.SNR)
{
// Positional uncertainty estimation by Neuschaefer and Windhorst 1994
var sigmaPosition = measurement.FWHMArcSec / (2.355 * measurement.SNR);
var combinedUncertainty = Math.Sqrt(sigmaPosition * sigmaPosition + solutionUncertaintyArcSec * solutionUncertaintyArcSec);
if (combinedUncertainty < minUncertainty) combinedUncertainty = minUncertainty;
return 1 / (combinedUncertainty * combinedUncertainty);
}
else if (mode == WeightingMode.Detection)
{
return measurement.Detection / (solutionUncertaintyArcSec * solutionUncertaintyArcSec);
}
return 1;
}
private double ComputePositionWeight(double solutionUncertaintyArcSec, SingleMultiFrameMeasurement measurement, double minUncertainty, WeightingMode mode)
{
return(FlyByMotionFitter.ComputeWeight(mode, solutionUncertaintyArcSec, measurement.FWHMArcSec, measurement.SNR, measurement.Detection, minUncertainty));
}
public void Calculate(
MeasurementPositionEntry[] entries, WeightingMode weighting, bool removeOutliers, double outlierSigmaCoeff,
double instDelayTimeOfDay, double minUncertainty,
bool includePositionalUncertainties, ErrorMethod errorMethod, double smallestReportedUncertaintyArcSec)
{
m_InstDelayTimeOfDay = instDelayTimeOfDay;
m_Weighting = weighting;
m_ErrorMethod = errorMethod;
m_SmallestReportedUncertaintyArcSec = smallestReportedUncertaintyArcSec;
m_MinSinglePositionUncertainty = minUncertainty;
var regRA = new LinearRegression();
var regDE = new LinearRegression();
foreach (var entry in entries)
{
var midFrameTime = entry.TimeOfDayUTC - instDelayTimeOfDay;
if (weighting == WeightingMode.None)
{
regRA.AddDataPoint(midFrameTime, entry.RADeg);
regDE.AddDataPoint(midFrameTime, entry.DEDeg);
}
else
{
var weightRA = CalulateWeight(entry, entry.SolutionUncertaintyRACosDEArcSec);
var weightDE = CalulateWeight(entry, entry.SolutionUncertaintyDEArcSec);
regRA.AddDataPoint(midFrameTime, entry.RADeg, weightRA);
regDE.AddDataPoint(midFrameTime, entry.DEDeg, weightDE);
}
}
m_Entries = new List <MeasurementPositionEntry>();
regRA.Solve();
regDE.Solve();
RemovedOutliers = 0;
if (removeOutliers)
{
var outlierLimitRA = regRA.StdDev * outlierSigmaCoeff;
var residualsRA = regRA.Residuals.ToArray();
var outlierLimitDE = regDE.StdDev * outlierSigmaCoeff;
var residualsDE = regDE.Residuals.ToArray();
for (int i = 0; i < entries.Length; i++)
{
if (Math.Abs(residualsRA[i]) <= outlierLimitRA && Math.Abs(residualsDE[i]) <= outlierLimitDE)
{
m_Entries.Add(entries[i]);
}
else
{
RemovedOutliers++;
}
}
m_RegressionRA = new LinearRegression();
m_RegressionDE = new LinearRegression();
foreach (var entry in m_Entries)
{
var midFrameTime = entry.TimeOfDayUTC - instDelayTimeOfDay;
if (weighting == WeightingMode.None)
{
m_RegressionRA.AddDataPoint(midFrameTime, entry.RADeg);
m_RegressionDE.AddDataPoint(midFrameTime, entry.DEDeg);
}
else
{
var weightRA = CalulateWeight(entry, entry.SolutionUncertaintyRACosDEArcSec);
m_RegressionRA.AddDataPoint(midFrameTime, entry.RADeg, weightRA);
var weightDE = CalulateWeight(entry, entry.SolutionUncertaintyDEArcSec);
m_RegressionDE.AddDataPoint(midFrameTime, entry.DEDeg, weightDE);
}
}
m_RegressionRA.Solve();
m_RegressionDE.Solve();
}
else
{
m_RegressionRA = regRA;
m_RegressionDE = regDE;
m_Entries = entries.ToList();
}
if (includePositionalUncertainties)
{
var posUncertaintyAveLst = new List <double>();
foreach (var entry in m_Entries)
{
var posUncertainty = entry.FWHMArcSec / (2.355 * entry.SNR);
if (posUncertainty < m_MinSinglePositionUncertainty)
{
posUncertainty = m_MinSinglePositionUncertainty;
}
posUncertaintyAveLst.Add(posUncertainty);
}
var posUncertaintyMedian = posUncertaintyAveLst.Median();
m_PosUncertaintyMedArcSec = posUncertaintyMedian / Math.Sqrt(posUncertaintyAveLst.Count);
}
else
{
m_PosUncertaintyMedArcSec = null;
}
}
