public long realignAll()
{
int i;
long start = CSettings.currentTimeMillis();
CXYVector.realign(_trainingData[0], _mean, _weight);
_newMean = new CXYVector(_trainingData[0]);
for (i = 1; i < _numSamples; i++)
{
CXYVector.realign(_trainingData[i], _mean, _weight);
_newMean.add(_trainingData[i]);
}
_newMean.divide(_numSamples);
return(CSettings.currentTimeMillis() - start);
}
public CPointDistributionModel principalComponentAnalysis(Size clippingSize, out long time)
{
long start = CSettings.currentTimeMillis();
// Get Covarian Matrix
CMatrix s = new CMatrix(_numPoints * 2, false);
for (int i = 0; i < _numSamples; i++)
{
CVector dx = new CVector(_trainingData[i].substractCopy(_mean));
CMatrix dxdxT = dx.multiplyMatrix(dx);
s.add(dxdxT);
}
s.divide(_numSamples);
// Calculate Eigen
CPointDistributionModel ret = new CPointDistributionModel(clippingSize, _mean, CEigen.calculate(s), 7, _connectivity);
long end = CSettings.currentTimeMillis();
time = end - start;
return(ret);
}
