void QrRegSuf::refresh_qr(const std::vector<Ptr<RegressionData> > &raw_data) const {
if(current) return;
int n = raw_data.size(); // number of observations
if(n==0){
current=false;
return;}
Ptr<RegressionData> rdp = DAT(raw_data[0]);
uint dim_beta = rdp->xdim();
Matrix X(n, dim_beta);
Vector y(n);
sumsqy=0.0;
for(int i = 0; i<n; ++i){
rdp = DAT(raw_data[i]);
y[i] = rdp->y();
const Vector & x(rdp->x());
X.set_row(i,x);
// X(i,0)=1.0; // this stuff is no longer needed b/c the intercept is explicit
// int k=0;
// for(int j=x.lo(); j<=x.hi(); ++j) X(i,++k) = x[j];
sumsqy += y[i]*y[i];
}
qr.decompose(X);
X = qr.getQ();
Qty = y*X;
current=true;
x_column_sums_ = ColSums(X);
}
//======================================================================
QrRegSuf::QrRegSuf(const Mat&X, const Vector &y):
qr(X),
Qty(),
sumsqy(0.0),
current(true)
{
Matrix Q(qr.getQ());
Qty = y*Q;
sumsqy = y.dot(y);
x_column_sums_ = ColSums(X);
}
NeRegSuf::NeRegSuf(const Matrix &X, const Vector &y)
: needs_to_reflect_(false),
xtx_is_fixed_(false),
sumsqy(y.normsq()),
n_(nrow(X)),
sumy_(y.sum()),
x_column_sums_(ColSums(X))
{
xty_ =y*X;
xtx_ = X.inner();
sumsqy = y.dot(y);
}
bool VerifyRotationMatrix(const vnl_double_3x3 &M)
{
//check row sums
std::vector<double> RowSums(3);
for(unsigned int i = 0; i < 3; i++)
{
vnl_double_3 r = M.get_row(i);
double sum = 0;
for(unsigned int j = 0; j < 3; j++)
sum += pow(r[j], 2);
RowSums[i] = sum;
//cout << "Sum of row " << i << " = " << sum << endl;
}
//check col sums
std::vector<double> ColSums(3);
for(unsigned int i = 0; i < 3; i++)
{
vnl_double_3 c = M.get_column(i);
double sum = 0;
for(unsigned int j = 0; j < 3; j++)
sum += pow(c[j], 2);
ColSums[i] = sum;
//cout << "Sum of col " << i << " = " << sum << endl;
}
double eps = 1e-4;
for(unsigned int i = 0; i < 3; i++)
{
if( fabs(RowSums[i] - 1.0) > eps )
return false;
if( fabs(ColSums[i] - 1.0) > eps )
return false;
}
return true;
}
