/**
* Used internally to find the solution to a single column vector.
*/
private void solveInternalL()
{
// This takes advantage of the diagonal elements always being real numbers
// solve L*y=b storing y in x
TriangularSolver_CDRM.solveL_diagReal(t, vv, n);
// solve L^T*x=y
TriangularSolver_CDRM.solveConjTranL_diagReal(t, vv, n);
}
/**
* Sets the matrix to the inverse using a lower triangular matrix.
*/
public void setToInverseL(float[] a)
{
// the more direct method which takes full advantage of the sparsity of the data structures proved to
// be difficult to get right due to the conjugates and reordering.
// See comparable real number code for an example.
for (int col = 0; col < n; col++)
{
//Arrays.fill(vv, 0);
Array.Clear(vv, 0, vv.Length);
vv[col * 2] = 1;
TriangularSolver_CDRM.solveL_diagReal(t, vv, n);
TriangularSolver_CDRM.solveConjTranL_diagReal(t, vv, n);
for (int i = 0; i < n; i++)
{
a[(i * numCols + col) * 2] = vv[i * 2];
a[(i * numCols + col) * 2 + 1] = vv[i * 2 + 1];
}
}
// NOTE: If you want to make inverse faster take advantage of the sparsity
}