private void GetExpectedXY(out float expectedX, out float expectedY)
{
if (LightCurveReductionContext.Instance.IsDriftThrough)
{
int firstFrameId = m_PreviousPositionFrameIds[0];
expectedX = (float)m_LinearFitX.ComputeY(m_FrameNo - firstFrameId);
expectedY = (float)m_LinearFitY.ComputeY(m_FrameNo - firstFrameId);
}
else
{
expectedX = (float)OccultedStar.LastKnownGoodPosition.XDouble;
expectedY = (float)OccultedStar.LastKnownGoodPosition.YDouble;
}
}
public void Test4()
{
// Based on https://onlinecourses.science.psu.edu/stat501/node/397
double[] x_values = new double[] { 16, 14, 22, 10, 14, 17, 10, 13, 19, 12, 18, 11 };
double[] y_values = new double[] { 77, 70, 85, 50, 62, 70, 55, 63, 88, 57, 81, 51 };
var reg_ols = new LinearRegression();
for (int i = 0; i < x_values.Length; i++)
{
reg_ols.AddDataPoint(x_values[i], y_values[i]);
}
reg_ols.Solve();
Assert.AreEqual(3.269, reg_ols.A, 0.001);
Assert.AreEqual(19.47, reg_ols.B, 0.01);
Assert.AreEqual(4.5983, reg_ols.StdDev, 0.0001);
Assert.AreEqual(0.365, reg_ols.Uncertainty_A, 0.001);
Assert.AreEqual(5.52, reg_ols.Uncertainty_B, 0.01);
var residuals = reg_ols.Residuals.ToArray();
var reg2 = new LinearRegression();
for (int i = 0; i < x_values.Length; i++)
{
reg2.AddDataPoint(x_values[i], Math.Abs(residuals[i]));
}
reg2.Solve();
var predictedValues = new double[x_values.Length];
for (int i = 0; i < x_values.Length; i++)
{
predictedValues[i] = reg2.ComputeY(x_values[i]);
}
var reg_wls = new LinearRegression();
var factor = 1;
for (int i = 0; i < x_values.Length; i++)
{
double weight = factor / (predictedValues[i] * predictedValues[i]);
reg_wls.AddDataPoint(x_values[i], y_values[i], weight);
}
reg_wls.Solve();
Assert.AreEqual(3.421, reg_wls.A, 0.001);
Assert.AreEqual(17.30, reg_wls.B, 0.01);
Assert.AreEqual(1.15935, reg_wls.StdDevUnscaled, 0.00001);
}
internal double GetMidPointDEPosition()
{
double closestTimeOfDay = GetMidPointDelayCorrectedTimeOfDay();
if (m_RegressionDE != null)
{
var normalTime = double.Parse(closestTimeOfDay.ToString("0.000000"));
return(m_RegressionDE.ComputeY(normalTime));
}
return(0);
}
private DateTime ComputeCentralExposureTimeFromNtpTime(int frameNo, DateTime endFrameNtpTimestamp)
{
if (TangraConfig.Settings.AAV.NtpTimeUseDirectTimestamps)
{
if (endFrameNtpTimestamp.Ticks != 633979008000000000)
{
double frameDurationMilliseconds = 1000 / m_FrameRate;
long centralTicks = endFrameNtpTimestamp.AddMilliseconds(-0.5 * frameDurationMilliseconds).Ticks;
return(new DateTime(centralTicks));
}
return(DateTime.MinValue);
}
else
{
return(new DateTime(m_CalibratedNtpTimeZeroPoint).AddMilliseconds(m_CalibratedNtpTimeSource.ComputeY(frameNo)));
}
}
private ImagePixel GetExpectedPosition(int frameNo)
{
ImagePixel rv = null;
var intervalValues = new Dictionary <int, List <ImagePixel> >();
var intervalMedians = new Dictionary <int, ImagePixel>();
int earliestFrame = m_PastFrameNos[0];
for (int i = 0; i < m_PastFrameNos.Count; i++)
{
int integrationInterval = (m_PastFrameNos[i] - earliestFrame) / m_MeasurementContext.IntegratedFramesCount;
List <ImagePixel> intPoints;
if (!intervalValues.TryGetValue(integrationInterval, out intPoints))
{
intPoints = new List <ImagePixel>();
intervalValues.Add(integrationInterval, intPoints);
}
intPoints.Add(new ImagePixel(m_PastFramePosX[i], m_PastFramePosY[i]));
}
var calcBucketX = new List <double>();
var calcBucketY = new List <double>();
foreach (int key in intervalValues.Keys)
{
calcBucketX.Clear();
calcBucketY.Clear();
intervalValues[key].ForEach(v =>
{
calcBucketX.Add(v.XDouble);
calcBucketY.Add(v.YDouble);
});
double xMed = calcBucketX.Median();
double yMed = calcBucketY.Median();
intervalMedians.Add(key, new ImagePixel(xMed, yMed));
}
var xMotion = new LinearRegression();
var yMotion = new LinearRegression();
foreach (int intInt in intervalMedians.Keys)
{
long t = intInt;
double x = intervalMedians[intInt].XDouble;
double y = intervalMedians[intInt].YDouble;
if (x > 0 && y > 0)
{
xMotion.AddDataPoint(t, x);
yMotion.AddDataPoint(t, y);
}
}
try
{
xMotion.Solve();
yMotion.Solve();
int currIntInterval = (frameNo - earliestFrame) / m_MeasurementContext.IntegratedFramesCount;
rv = new ImagePixel(xMotion.ComputeY(currIntInterval), yMotion.ComputeY(currIntInterval));
}
catch (Exception ex)
{
Trace.WriteLine(ex.GetFullStackTrace());
}
return(rv);
}
public void Test1()
{
// Based on https://www.medcalc.org/manual/weighted-regression-worked-example.php
var reg = new LinearRegression();
double[] x_values = new double[]
{
27, 21, 22, 24, 25, 23, 20, 20, 29, 24, 25, 28, 26, 38, 32, 33, 31, 34, 37, 38, 33, 35, 30, 31, 37, 39, 46,
49, 40, 42, 43, 46, 43, 44, 46, 47, 45, 49, 48, 40, 42, 55, 54, 57, 52, 53, 56, 52, 50, 59, 50, 52, 58,
57
};
double[] y_values = new double[]
{
73, 66, 63, 75, 71, 70, 65, 70, 79, 72, 68, 67, 79, 91, 76, 69, 66, 73, 78, 87, 76, 79, 73, 80, 68, 75, 89,
101, 70, 72, 80, 83, 75, 71, 80, 96, 92, 80, 70, 90, 85, 76, 71, 99, 86, 79, 92, 85, 71, 90, 91, 100, 80,
109
};
for (int i = 0; i < x_values.Length; i++)
{
reg.AddDataPoint(x_values[i], y_values[i]);
}
reg.Solve();
Assert.AreEqual(0.5800, reg.A, 0.0001);
Assert.AreEqual(56.1569, reg.B, 0.0001);
Assert.AreEqual(8.1457, reg.StdDev, 0.0001);
Assert.AreEqual(0.09695, reg.Uncertainty_A, 0.0001);
Assert.AreEqual(3.9937, reg.Uncertainty_B, 0.0001);
var residuals = reg.Residuals.ToArray();
var reg2 = new LinearRegression();
for (int i = 0; i < x_values.Length; i++)
{
reg2.AddDataPoint(x_values[i], Math.Abs(residuals[i]));
}
reg2.Solve();
Assert.AreEqual(0.1982, reg2.A, 0.0001);
Assert.AreEqual(-1.5495, reg2.B, 0.0001);
Assert.AreEqual(4.4606, reg2.StdDev, 0.0001);
Assert.AreEqual(0.05309, reg2.Uncertainty_A, 0.0001);
Assert.AreEqual(2.1869, reg2.Uncertainty_B, 0.0001);
var predictedValues = new double[x_values.Length];
for (int i = 0; i < x_values.Length; i++)
{
predictedValues[i] = reg2.ComputeY(x_values[i]);
}
var reg3 = new LinearRegression();
var factor = 1;
for (int i = 0; i < x_values.Length; i++)
{
double weight = factor / (predictedValues[i] * predictedValues[i]);
reg3.AddDataPoint(x_values[i], y_values[i], weight);
}
reg3.Solve();
Assert.AreEqual(0.5963, reg3.A, 0.0001);
Assert.AreEqual(55.5658, reg3.B, 0.0001);
Assert.AreEqual(1.2130, reg3.StdDevUnscaled, 0.0001);
}
