private void updateAlphaVec()
{
// Function calculates the alpha vector with given
// fixed pillars+values
// Write Matrix M
double tmp = 0.0;
for (int rowIt = 0; rowIt < xSize_; ++rowIt)
{
yVec_[rowIt] = this.yBegin_[rowIt];
tmp = 1.0 / gammaFunc(this.xBegin_[rowIt]);
for (int colIt = 0; colIt < xSize_; ++colIt)
{
M_[rowIt, colIt] = kernelAbs(this.xBegin_[rowIt],
this.xBegin_[colIt]) * tmp;
}
}
// Solve y=M*\alpha for \alpha
alphaVec_ = MatrixUtilities.qrSolve(M_, yVec_);
// check if inversion worked up to a reasonable precision.
// I've chosen not to check determinant(M_)!=0 before solving
Vector test = M_ * alphaVec_;
Vector diffVec = Vector.Abs((M_ * alphaVec_) - yVec_);
for (int i = 0; i < diffVec.size(); ++i)
{
Utils.QL_REQUIRE(diffVec[i] < invPrec_, () =>
"Inversion failed in 1d kernel interpolation");
}
}
private void updateAlphaVec()
{
// Function calculates the alpha vector with given
// fixed pillars+values
Vector Xk = new Vector(2), Xn = new Vector(2);
int rowCnt = 0, colCnt = 0;
double tmpVar = 0.0;
// write y-vector and M-Matrix
for (int j = 0; j < ySize_; ++j)
{
for (int i = 0; i < xSize_; ++i)
{
yVec_[rowCnt] = this.zData_[i, j];
// calculate X_k
Xk[0] = this.xBegin_[i];
Xk[1] = this.yBegin_[j];
tmpVar = 1 / gammaFunc(Xk);
colCnt = 0;
for (int jM = 0; jM < ySize_; ++jM)
{
for (int iM = 0; iM < xSize_; ++iM)
{
Xn[0] = this.xBegin_[iM];
Xn[1] = this.yBegin_[jM];
M_[rowCnt, colCnt] = kernelAbs(Xk, Xn) * tmpVar;
colCnt++; // increase column counter
}// end iM
}// end jM
rowCnt++; // increase row counter
} // end i
}// end j
alphaVec_ = MatrixUtilities.qrSolve(M_, yVec_);
// check if inversion worked up to a reasonable precision.
// I've chosen not to check determinant(M_)!=0 before solving
Vector diffVec = Vector.Abs(M_ * alphaVec_ - yVec_);
for (int i = 0; i < diffVec.size(); ++i)
{
Utils.QL_REQUIRE(diffVec[i] < invPrec_, () =>
"inversion failed in 2d kernel interpolation");
}
}
