//---------------------------------------------------------
bool CTable_PCA::Get_Matrix(CSG_Matrix &Matrix)
{
int i, j1, j2;
Matrix.Create(m_nFeatures, m_nFeatures);
Matrix.Set_Zero();
switch( m_Method )
{
//-----------------------------------------------------
default:
case 0: // Correlation matrix: Center and reduce the column vectors.
for(j1=0; j1<m_nFeatures; j1++)
{
Matrix[j1][j1] = 1.0;
}
for(i=0; i<m_pTable->Get_Count() && Set_Progress(i, m_pTable->Get_Count()); i++)
{
if( !is_NoData(i) )
{
for(j1=0; j1<m_nFeatures-1; j1++)
{
for(j2=j1+1; j2<m_nFeatures; j2++)
{
Matrix[j1][j2] += Get_Value(j1, i) * Get_Value(j2, i);
}
}
}
}
break;
//-----------------------------------------------------
case 1: // Variance-covariance matrix: Center the column vectors.
case 2: // Sums-of-squares-and-cross-products matrix
for(i=0; i<m_pTable->Get_Count() && Set_Progress(i, m_pTable->Get_Count()); i++)
{
if( !is_NoData(i) )
{
for(j1=0; j1<m_nFeatures; j1++)
{
for(j2=j1; j2<m_nFeatures; j2++)
{
Matrix[j1][j2] += Get_Value(j1, i) * Get_Value(j2, i);
}
}
}
}
break;
}
//-----------------------------------------------------
for(j1=0; j1<m_nFeatures; j1++)
{
for(j2=j1; j2<m_nFeatures; j2++)
{
Matrix[j2][j1] = Matrix[j1][j2];
}
}
return( true );
}
