void Toolbox::calculateGlobalMeanAndStd(DataSet &X,dVector& mean,dVector& stdDev)
{
calculateGlobalMean(X,mean);
int nbElements = 0;
//Calculate standard deviation
stdDev.set(0);
for(int i = 0;i < (int)X.size() ;i++)
{
double* pData = X.at(i)->getPrecomputedFeatures()->get();
int Width = X.at(i)->getPrecomputedFeatures()->getWidth();
int Height = X.at(i)->getPrecomputedFeatures()->getHeight();
for(int col=0; col < Width; col++)
{
double* pStdDev = stdDev.get();
double* pMean = mean.get();
for(int row = 0; row < Height;row++)
{
*pStdDev += (*pData-*pMean) * (*pData-*pMean);
pStdDev++;
pData++;
pMean++;
}
}
nbElements+=Width;
}
stdDev.multiply(1.0/(double)nbElements);
stdDev.eltSqrt();
}
double GradientDD::computeGradient(dVector& vecGradrient, Model* m,DataSequence*)
{
dVector tmpVec;
vecGradrient = *(m->getWeights());
vecGradrient.add(mu);
tmpVec = vecGradrient;
tmpVec.transpose();
tmpVec.multiply(vecGradrient);
double f = exp(-0.5*tmpVec[0]);
vecGradrient.multiply(f);
return f;
}
void Toolbox::calculateGlobalMean(DataSet &X,dVector& mean)
{
dVector seqSum;
int nbElements = 0;
//Calculate mean
for(int i = 0;i < (int)X.size() ;i++)
{
X.at(i)->getPrecomputedFeatures()->rowSum(seqSum);
mean.add(seqSum);
nbElements+=X.at(i)->getPrecomputedFeatures()->getWidth();
}
mean.multiply(1.0/(double)nbElements);
}
