public void Creation()
{
var covariance = new RunningCovariance();
Assert.That(covariance.MeanX, Is.EqualTo(0.0));
Assert.That(covariance.MeanY, Is.EqualTo(0.0));
Assert.That(covariance.Covariance, Is.EqualTo(0.0));
}
public CovarianceBuilder(PhotographData data)
{
int size = data.NPsf;
iMatrix = new RunningCovariance[size, size];
for (int i = 0; i < size; i++)
{
for (int j = i; j < size; j++) {
iMatrix[i, j] = new RunningCovariance();
}
}
Data = data;
}
private void Init(int size)
{
Size = size;
covarianceMatrix = new RunningCovariance[Size, Size];
for (int i = 0; i < Size; i++)
{
for (int j = i; j < Size; j++)
{
covarianceMatrix[i, j] = new RunningCovariance();
}
}
meanVector = new double[Size];
SampleSize = 0;
}
public CovarianceBuilder(PhotographData data)
{
int size = data.NPsf;
iMatrix = new RunningCovariance[size, size];
for (int i = 0; i < size; i++)
{
for (int j = i; j < size; j++)
{
iMatrix[i, j] = new RunningCovariance();
}
}
Data = data;
}
public void InitialCovariance()
{
var covariance = new RunningCovariance();
int nPoints = 250;
double[] dataX = new double[nPoints];
double[] dataY = new double[nPoints];
for (int i = 0; i < nPoints; i++)
{
dataX[i] = i + 1;
dataY[nPoints - 1 - i] = i + 1;
}
for (int i = 0; i < dataX.Length; i++)
{
covariance.Add(dataX[i], dataY[i]);
double meanX = 0;
double meanY = 0;
double covar = 0;
for (int j = 0; j <= i; j++)
{
meanX += dataX[j];
meanY += dataY[j];
}
meanX /= (i + 1);
meanY /= (i + 1);
Assert.That(covariance.MeanX, Is.EqualTo(meanX).Within(0.00001), "Initial meanX i = " + i);
Assert.That(covariance.MeanY, Is.EqualTo(meanY).Within(0.00001), "Initial meanY i = " + i);
if (i > 1)
{
for (int j = 0; j <= i; j++)
{
double termX = dataX[j] - meanX;
double termY = dataY[j] - meanY;
covar += (termX * termY);
}
covar /= i;
Assert.That(covariance.Covariance, Is.EqualTo(covar).Within(0.0000000001), "Initial variance i = " + i);
}
}
}
private void Init(int size)
{
Size = size;
covarianceMatrix = new RunningCovariance[Size, Size];
for (int i = 0; i < Size; i++)
{
for (int j = i; j < Size; j++)
{
covarianceMatrix[i, j] = new RunningCovariance();
}
}
meanVector = new double[Size];
SampleSize = 0;
}
public void InitialCovariance()
{
var covariance = new RunningCovariance();
int nPoints = 250;
double[] dataX = new double[nPoints];
double[] dataY = new double[nPoints];
for (int i = 0; i < nPoints; i++)
{
dataX[i] = i + 1;
dataY[nPoints - 1 - i] = i + 1;
}
for (int i = 0; i < dataX.Length; i++)
{
covariance.Add(dataX[i], dataY[i]);
double meanX = 0;
double meanY = 0;
double covar = 0;
for (int j = 0; j <= i; j++)
{
meanX += dataX[j];
meanY += dataY[j];
}
meanX /= (i + 1);
meanY /= (i + 1);
Assert.That(covariance.MeanX, Is.EqualTo(meanX).Within(0.00001), "Initial meanX i = " + i);
Assert.That(covariance.MeanY, Is.EqualTo(meanY).Within(0.00001), "Initial meanY i = " + i);
if (i > 1)
{
for (int j = 0; j <= i; j++)
{
double termX = dataX[j] - meanX;
double termY = dataY[j] - meanY;
covar += (termX * termY);
}
covar /= i;
Assert.That(covariance.Covariance, Is.EqualTo(covar).Within(0.0000000001), "Initial variance i = " + i);
}
}
}
public void Creation()
{
var covariance = new RunningCovariance();
Assert.That(covariance.MeanX, Is.EqualTo(0.0));
Assert.That(covariance.MeanY, Is.EqualTo(0.0));
Assert.That(covariance.Covariance, Is.EqualTo(0.0));
}
