/**
* <p>
* Computes the householder vector "u" for the first column of submatrix j. Note this is
* a specialized householder for this problem. There is some protection against
* overfloaw and underflow.
* </p>
* <p>
* Q = I - γuu<sup>T</sup>
* </p>
* <p>
* This function finds the values of 'u' and 'γ'.
* </p>
*
* @param j Which submatrix to work off of.
*/
protected void householder(int j)
{
double[] u = dataQR[j];
// find the largest value in this column
// this is used to normalize the column and mitigate overflow/underflow
double max = QrHelperFunctions_ZDRM.findMax(u, j, numRows - j);
if (max == 0.0)
{
gamma = 0;
error = true;
}
else
{
// computes tau and gamma, and normalizes u by max
gamma = QrHelperFunctions_ZDRM.computeTauGammaAndDivide(j, numRows, u, max, tau);
// divide u by u_0
// double u_0 = u[j] + tau;
double real_u_0 = u[j * 2] + tau.real;
double imag_u_0 = u[j * 2 + 1] + tau.imaginary;
QrHelperFunctions_ZDRM.divideElements(j + 1, numRows, u, 0, real_u_0, imag_u_0);
tau.real *= max;
tau.imaginary *= max;
u[j * 2] = -tau.real;
u[j * 2 + 1] = -tau.imaginary;
}
gammas[j] = gamma;
}
public ZMatrixRMaj getQ(ZMatrixRMaj Q, bool compact)
{
if (compact)
{
Q = UtilDecompositons_ZDRM.checkIdentity(Q, numRows, minLength);
}
else
{
Q = UtilDecompositons_ZDRM.checkIdentity(Q, numRows, numRows);
}
for (int j = minLength - 1; j >= 0; j--)
{
double[] u = dataQR[j];
double vvReal = u[j * 2];
double vvImag = u[j * 2 + 1];
u[j * 2] = 1;
u[j * 2 + 1] = 0;
double gammaReal = gammas[j];
QrHelperFunctions_ZDRM.rank1UpdateMultR(Q, u, 0, gammaReal, j, j, numRows, v);
u[j * 2] = vvReal;
u[j * 2 + 1] = vvImag;
}
return(Q);
}
override public /**/ double quality()
{
return(SpecializedOps_ZDRM.qualityTriangular(R));
}
/**
* Solves for X using the QR decomposition.
*
* @param B A matrix that is n by m. Not modified.
* @param X An n by m matrix where the solution is written to. Modified.
*/
override public void solve(ZMatrixRMaj B, ZMatrixRMaj X)
{
UtilEjml.checkReshapeSolve(numRows, numCols, B, X);
int BnumCols = B.numCols;
// solve each column one by one
for (int colB = 0; colB < BnumCols; colB++)
{
// make a copy of this column in the vector
for (int i = 0; i < numRows; i++)
{
int indexB = (i * BnumCols + colB) * 2;
a.data[i * 2] = B.data[indexB];
a.data[i * 2 + 1] = B.data[indexB + 1];
}
// Solve Qa=b
// a = Q'b
// a = Q_{n-1}...Q_2*Q_1*b
//
// Q_n*b = (I-gamma*u*u^T)*b = b - u*(gamma*U^T*b)
for (int n = 0; n < numCols; n++)
{
double[] u = QR[n];
double realVV = u[n * 2];
double imagVV = u[n * 2 + 1];
u[n * 2] = 1;
u[n * 2 + 1] = 0;
QrHelperFunctions_ZDRM.rank1UpdateMultR(a, u, 0, gammas[n], 0, n, numRows, temp.data);
u[n * 2] = realVV;
u[n * 2 + 1] = imagVV;
}
// solve for Rx = b using the standard upper triangular solver
TriangularSolver_ZDRM.solveU(R.data, a.data, numCols);
// save the results
for (int i = 0; i < numCols; i++)
{
int indexB = (i * BnumCols + colB) * 2;
X.data[indexB] = a.data[i * 2];
X.data[indexB + 1] = a.data[i * 2 + 1];
}
}
}
