/**
* <p>
* A = (I + W Y<sup>T</sup>)<sup>T</sup>A<BR>
* A = A + Y (W<sup>T</sup>A)<BR>
* <br>
* where A is a submatrix of the input matrix.
* </p>
*/
protected void updateA(FSubmatrixD1 A)
{
setW();
A.row0 = Y.row0;
A.row1 = Y.row1;
A.col0 = Y.col1;
A.col1 = Y.original.numCols;
WTA.row0 = 0;
WTA.col0 = 0;
WTA.row1 = W.col1 - W.col0;
WTA.col1 = A.col1 - A.col0;
WTA.original.reshape(WTA.row1, WTA.col1, false);
if (A.col1 > A.col0)
{
BlockHouseHolder_FDRB.computeW_Column(blockLength, Y, W, temp, gammas, Y.col0);
MatrixMult_FDRB.multTransA(blockLength, W, A, WTA);
BlockHouseHolder_FDRB.multAdd_zeros(blockLength, Y, WTA, A);
}
else if (saveW)
{
BlockHouseHolder_FDRB.computeW_Column(blockLength, Y, W, temp, gammas, Y.col0);
}
}
/**
* <p>
* Multiplies the provided matrix by Q<sup>T</sup> using householder reflectors. This is more
* efficient that computing Q then applying it to the matrix.
* </p>
*
* <p>
* Q = Q*(I - γ W*Y^T)<br>
* QR = A ≥ R = Q^T*A = (Q3^T * (Q2^T * (Q1^t * A)))
* </p>
*
* @param B Matrix which Q is applied to. Modified.
*/
public void applyQTran(FMatrixRBlock B)
{
int minDimen = Math.Min(dataA.numCols, dataA.numRows);
FSubmatrixD1 subB = new FSubmatrixD1(B);
W.col0 = W.row0 = 0;
Y.row1 = W.row1 = dataA.numRows;
WTA.row0 = WTA.col0 = 0;
// (Q3^T * (Q2^T * (Q1^t * A)))
for (int i = 0; i < minDimen; i += blockLength)
{
Y.col0 = i;
Y.col1 = Math.Min(Y.col0 + blockLength, dataA.numCols);
Y.row0 = i;
subB.row0 = i;
// subB.row1 = B.numRows;
// subB.col0 = 0;
// subB.col1 = B.numCols;
setW();
// W.original.reshape(W.row1,W.col1,false);
WTA.row0 = 0;
WTA.col0 = 0;
WTA.row1 = W.col1 - W.col0;
WTA.col1 = subB.col1 - subB.col0;
WTA.original.reshape(WTA.row1, WTA.col1, false);
// Compute W matrix from reflectors stored in Y
if (!saveW)
{
BlockHouseHolder_FDRB.computeW_Column(blockLength, Y, W, temp, gammas, Y.col0);
}
// Apply the Qi to Q
MatrixMult_FDRB.multTransA(blockLength, W, subB, WTA);
BlockHouseHolder_FDRB.multAdd_zeros(blockLength, Y, WTA, subB);
}
}