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bug #1076: fix scaling in IncompleteCholesky, improve doc, add read-only access to the different factors, remove debugging code.

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Gael Guennebaud 2015-10-06 13:25:45 +02:00
parent f25bdc707f
commit 752a0e5339
1 changed files with 25 additions and 5 deletions
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30
unsupported/Eigen/src/IterativeSolvers/IncompleteCholesky.h
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@ -24,6 +24,11 @@ namespace Eigen {
* matrix. It is advised to give a row-oriented sparse matrix
* \tparam _UpLo The triangular part of the matrix to reference.
* \tparam _OrderingType
*
* It performs the following incomplete factorization: \f$ S P A P' S \approx L L' \f$
* where L is a lower triangular factor, S if a diagonal scaling matrix, and P is a
* fill-in reducing permutation as computed of the ordering method.
*
*/
template <typename Scalar, int _UpLo = Lower, typename _OrderingType = AMDOrdering<int> >
@ -86,6 +91,7 @@ class IncompleteCholesky : public SparseSolverBase<IncompleteCholesky<Scalar,_Up
if(pinv.size()>0) m_perm = pinv.inverse();
else m_perm.resize(0);
m_analysisIsOk = true;
m_isInitialized = true;
}
template<typename MatrixType>
@ -110,9 +116,17 @@ class IncompleteCholesky : public SparseSolverBase<IncompleteCholesky<Scalar,_Up
x = m_scale.asDiagonal() * x;
if (m_perm.rows() == b.rows())
x = m_perm.inverse() * x;
}
/** \returns the sparse lower triangular factor L */
const FactorType& matrixL() const { return m_L; }
/** \returns a vector representing the scaling factor S */
const VectorRx& scalingS() const { return m_scale; }
/** \returns the fill-in reducing permutation P (can be empty for a natural ordering) */
const PermutationType permutationP() const { return m_perm; }
protected:
FactorType m_L; // The lower part stored in CSC
VectorRx m_scale; // The vector for scaling the matrix
@ -121,7 +135,7 @@ class IncompleteCholesky : public SparseSolverBase<IncompleteCholesky<Scalar,_Up
bool m_factorizationIsOk;
ComputationInfo m_info;
PermutationType m_perm;
private:
inline void updateList(Ref<const VectorIx> colPtr, Ref<VectorIx> rowIdx, Ref<VectorSx> vals, const Index& col, const Index& jk, VectorIx& firstElt, VectorList& listCol);
};
@ -176,13 +190,21 @@ void IncompleteCholesky<Scalar,_UpLo, OrderingType>::factorize(const _MatrixType
}
m_scale = m_scale.cwiseSqrt().cwiseSqrt();
for (Index j = 0; j < n; ++j)
if(m_scale(j)>(std::numeric_limits<RealScalar>::min)())
m_scale(j) = RealScalar(1)/m_scale(j);
else
m_scale(j) = 1;
// FIXME disable scaling if not needed, i.e., if it is roughtly uniform? (this will make solve() faster)
// Scale and compute the shift for the matrix
RealScalar mindiag = NumTraits<RealScalar>::highest();
for (Index j = 0; j < n; j++)
{
for (Index k = colPtr[j]; k < colPtr[j+1]; k++)
vals[k] /= (m_scale(j)*m_scale(rowIdx[k]));
vals[k] *= (m_scale(j)*m_scale(rowIdx[k]));
eigen_internal_assert(rowIdx[colPtr[j]]==j && "IncompleteCholesky: only the lower triangular part must be stored");
mindiag = numext::mini(numext::real(vals[colPtr[j]]), mindiag);
}
@ -240,7 +262,6 @@ void IncompleteCholesky<Scalar,_UpLo, OrderingType>::factorize(const _MatrixType
// Scale the current column
if(numext::real(diag) <= 0)
{
std::cerr << "\nNegative diagonal during Incomplete factorization at position " << j << " (value = " << diag << ")\n";
m_info = NumericalIssue;
return;
}
@ -276,7 +297,6 @@ void IncompleteCholesky<Scalar,_UpLo, OrderingType>::factorize(const _MatrixType
updateList(colPtr,rowIdx,vals,j,jk,firstElt,listCol);
}
m_factorizationIsOk = true;
m_isInitialized = true;
m_info = Success;
}