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Split the computation of the ILUT into two steps

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Desire NUENTSA
2012-02-10 18:57:01 +01:00
parent a815d962da
commit edbebb14de
2 changed files with 222 additions and 200 deletions
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15
Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
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@@ -35,9 +35,10 @@ namespace internal {
* approximation of Ax=b (regardless of b)
* \param iters On input the max number of iteration, on output the number of performed iterations.
* \param tol_error On input the tolerance error, on output an estimation of the relative error.
* \return false in the case of numerical issue, for example a break down of BiCGSTAB.
*/
template<typename MatrixType, typename Rhs, typename Dest, typename Preconditioner>
void bicgstab(const MatrixType& mat, const Rhs& rhs, Dest& x,
bool bicgstab(const MatrixType& mat, const Rhs& rhs, Dest& x,
const Preconditioner& precond, int& iters,
typename Dest::RealScalar& tol_error)
{
@@ -46,7 +47,6 @@ void bicgstab(const MatrixType& mat, const Rhs& rhs, Dest& x,
typedef typename Dest::RealScalar RealScalar;
typedef typename Dest::Scalar Scalar;
typedef Matrix<Scalar,Dynamic,1> VectorType;
RealScalar tol = tol_error;
int maxIters = iters;
@@ -70,10 +70,11 @@ void bicgstab(const MatrixType& mat, const Rhs& rhs, Dest& x,
while ( r.squaredNorm()/r0_sqnorm > tol2 && i<maxIters )
{
// std::cout<<i<<" : Relative residual norm " << sqrt(r.squaredNorm()/r0_sqnorm)<<"\n";
Scalar rho_old = rho;
rho = r0.dot(r);
eigen_assert((rho != Scalar(0)) && "BiCGSTAB BROKE DOWN !!!");
if (rho == Scalar(0)) return false; /* New search directions cannot be found */
Scalar beta = (rho/rho_old) * (alpha / w);
p = r + beta * (p - w * v);
@@ -94,6 +95,7 @@ void bicgstab(const MatrixType& mat, const Rhs& rhs, Dest& x,
}
tol_error = sqrt(r.squaredNorm()/r0_sqnorm);
iters = i;
return true;
}
}
@@ -214,17 +216,18 @@ public:
template<typename Rhs,typename Dest>
void _solveWithGuess(const Rhs& b, Dest& x) const
{
bool ok;
for(int j=0; j<b.cols(); ++j)
{
m_iterations = Base::maxIterations();
m_error = Base::m_tolerance;
typename Dest::ColXpr xj(x,j);
internal::bicgstab(*mp_matrix, b.col(j), xj, Base::m_preconditioner, m_iterations, m_error);
ok = internal::bicgstab(*mp_matrix, b.col(j), xj, Base::m_preconditioner, m_iterations, m_error);
}
if (ok == false) m_info = NumericalIssue;
else m_info = m_error <= Base::m_tolerance ? Success : NoConvergence;
m_isInitialized = true;
m_info = m_error <= Base::m_tolerance ? Success : NoConvergence;
}
/** \internal */