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-rw-r--r--Eigen/src/SparseLU/SparseLU.h49
1 files changed, 22 insertions, 27 deletions
diff --git a/Eigen/src/SparseLU/SparseLU.h b/Eigen/src/SparseLU/SparseLU.h
index 79b78da99..1e448f2ab 100644
--- a/Eigen/src/SparseLU/SparseLU.h
+++ b/Eigen/src/SparseLU/SparseLU.h
@@ -14,7 +14,7 @@
namespace Eigen {
-template <typename _MatrixType, typename _OrderingType = COLAMDOrdering<typename _MatrixType::Index> > class SparseLU;
+template <typename _MatrixType, typename _OrderingType = COLAMDOrdering<typename _MatrixType::StorageIndex> > class SparseLU;
template <typename MappedSparseMatrixType> struct SparseLUMatrixLReturnType;
template <typename MatrixLType, typename MatrixUType> struct SparseLUMatrixUReturnType;
@@ -70,7 +70,7 @@ template <typename MatrixLType, typename MatrixUType> struct SparseLUMatrixURetu
* \sa \ref OrderingMethods_Module
*/
template <typename _MatrixType, typename _OrderingType>
-class SparseLU : public SparseSolverBase<SparseLU<_MatrixType,_OrderingType> >, public internal::SparseLUImpl<typename _MatrixType::Scalar, typename _MatrixType::Index>
+class SparseLU : public SparseSolverBase<SparseLU<_MatrixType,_OrderingType> >, public internal::SparseLUImpl<typename _MatrixType::Scalar, typename _MatrixType::StorageIndex>
{
protected:
typedef SparseSolverBase<SparseLU<_MatrixType,_OrderingType> > APIBase;
@@ -82,13 +82,13 @@ class SparseLU : public SparseSolverBase<SparseLU<_MatrixType,_OrderingType> >,
typedef _OrderingType OrderingType;
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
- typedef typename MatrixType::Index Index;
- typedef SparseMatrix<Scalar,ColMajor,Index> NCMatrix;
- typedef internal::MappedSuperNodalMatrix<Scalar, Index> SCMatrix;
+ typedef typename MatrixType::StorageIndex StorageIndex;
+ typedef SparseMatrix<Scalar,ColMajor,StorageIndex> NCMatrix;
+ typedef internal::MappedSuperNodalMatrix<Scalar, StorageIndex> SCMatrix;
typedef Matrix<Scalar,Dynamic,1> ScalarVector;
- typedef Matrix<Index,Dynamic,1> IndexVector;
- typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
- typedef internal::SparseLUImpl<Scalar, Index> Base;
+ typedef Matrix<StorageIndex,Dynamic,1> IndexVector;
+ typedef PermutationMatrix<Dynamic, Dynamic, StorageIndex> PermutationType;
+ typedef internal::SparseLUImpl<Scalar, StorageIndex> Base;
public:
SparseLU():m_lastError(""),m_Ustore(0,0,0,0,0,0),m_symmetricmode(false),m_diagpivotthresh(1.0),m_detPermR(1)
@@ -146,9 +146,9 @@ class SparseLU : public SparseSolverBase<SparseLU<_MatrixType,_OrderingType> >,
* y = b; matrixU().solveInPlace(y);
* \endcode
*/
- SparseLUMatrixUReturnType<SCMatrix,MappedSparseMatrix<Scalar,ColMajor,Index> > matrixU() const
+ SparseLUMatrixUReturnType<SCMatrix,MappedSparseMatrix<Scalar,ColMajor,StorageIndex> > matrixU() const
{
- return SparseLUMatrixUReturnType<SCMatrix, MappedSparseMatrix<Scalar,ColMajor,Index> >(m_Lstore, m_Ustore);
+ return SparseLUMatrixUReturnType<SCMatrix, MappedSparseMatrix<Scalar,ColMajor,StorageIndex> >(m_Lstore, m_Ustore);
}
/**
@@ -324,7 +324,7 @@ class SparseLU : public SparseSolverBase<SparseLU<_MatrixType,_OrderingType> >,
std::string m_lastError;
NCMatrix m_mat; // The input (permuted ) matrix
SCMatrix m_Lstore; // The lower triangular matrix (supernodal)
- MappedSparseMatrix<Scalar,ColMajor,Index> m_Ustore; // The upper triangular matrix
+ MappedSparseMatrix<Scalar,ColMajor,StorageIndex> m_Ustore; // The upper triangular matrix
PermutationType m_perm_c; // Column permutation
PermutationType m_perm_r ; // Row permutation
IndexVector m_etree; // Column elimination tree
@@ -334,9 +334,9 @@ class SparseLU : public SparseSolverBase<SparseLU<_MatrixType,_OrderingType> >,
// SparseLU options
bool m_symmetricmode;
// values for performance
- internal::perfvalues<Index> m_perfv;
+ internal::perfvalues m_perfv;
RealScalar m_diagpivotthresh; // Specifies the threshold used for a diagonal entry to be an acceptable pivot
- Index m_nnzL, m_nnzU; // Nonzeros in L and U factors
+ Index m_nnzL, m_nnzU; // Nonzeros in L and U factors
Index m_detPermR; // Determinant of the coefficient matrix
private:
// Disable copy constructor
@@ -375,7 +375,7 @@ void SparseLU<MatrixType, OrderingType>::analyzePattern(const MatrixType& mat)
{
m_mat.uncompress(); //NOTE: The effect of this command is only to create the InnerNonzeros pointers. FIXME : This vector is filled but not subsequently used.
// Then, permute only the column pointers
- ei_declare_aligned_stack_constructed_variable(Index,outerIndexPtr,mat.cols()+1,mat.isCompressed()?const_cast<Index*>(mat.outerIndexPtr()):0);
+ ei_declare_aligned_stack_constructed_variable(StorageIndex,outerIndexPtr,mat.cols()+1,mat.isCompressed()?const_cast<StorageIndex*>(mat.outerIndexPtr()):0);
// If the input matrix 'mat' is uncompressed, then the outer-indices do not match the ones of m_mat, and a copy is thus needed.
if(!mat.isCompressed())
@@ -397,7 +397,7 @@ void SparseLU<MatrixType, OrderingType>::analyzePattern(const MatrixType& mat)
if (!m_symmetricmode) {
IndexVector post, iwork;
// Post order etree
- internal::treePostorder(m_mat.cols(), m_etree, post);
+ internal::treePostorder(StorageIndex(m_mat.cols()), m_etree, post);
// Renumber etree in postorder
@@ -449,7 +449,7 @@ void SparseLU<MatrixType, OrderingType>::factorize(const MatrixType& matrix)
eigen_assert(m_analysisIsOk && "analyzePattern() should be called first");
eigen_assert((matrix.rows() == matrix.cols()) && "Only for squared matrices");
- typedef typename IndexVector::Scalar Index;
+ typedef typename IndexVector::Scalar StorageIndex;
m_isInitialized = true;
@@ -461,11 +461,11 @@ void SparseLU<MatrixType, OrderingType>::factorize(const MatrixType& matrix)
{
m_mat.uncompress(); //NOTE: The effect of this command is only to create the InnerNonzeros pointers.
//Then, permute only the column pointers
- const Index * outerIndexPtr;
+ const StorageIndex * outerIndexPtr;
if (matrix.isCompressed()) outerIndexPtr = matrix.outerIndexPtr();
else
{
- Index* outerIndexPtr_t = new Index[matrix.cols()+1];
+ StorageIndex* outerIndexPtr_t = new StorageIndex[matrix.cols()+1];
for(Index i = 0; i <= matrix.cols(); i++) outerIndexPtr_t[i] = m_mat.outerIndexPtr()[i];
outerIndexPtr = outerIndexPtr_t;
}
@@ -479,7 +479,7 @@ void SparseLU<MatrixType, OrderingType>::factorize(const MatrixType& matrix)
else
{ //FIXME This should not be needed if the empty permutation is handled transparently
m_perm_c.resize(matrix.cols());
- for(Index i = 0; i < matrix.cols(); ++i) m_perm_c.indices()(i) = i;
+ for(StorageIndex i = 0; i < matrix.cols(); ++i) m_perm_c.indices()(i) = i;
}
Index m = m_mat.rows();
@@ -640,7 +640,7 @@ void SparseLU<MatrixType, OrderingType>::factorize(const MatrixType& matrix)
// Create supernode matrix L
m_Lstore.setInfos(m, n, m_glu.lusup, m_glu.xlusup, m_glu.lsub, m_glu.xlsub, m_glu.supno, m_glu.xsup);
// Create the column major upper sparse matrix U;
- new (&m_Ustore) MappedSparseMatrix<Scalar, ColMajor, Index> ( m, n, m_nnzU, m_glu.xusub.data(), m_glu.usub.data(), m_glu.ucol.data() );
+ new (&m_Ustore) MappedSparseMatrix<Scalar, ColMajor, StorageIndex> ( m, n, m_nnzU, m_glu.xusub.data(), m_glu.usub.data(), m_glu.ucol.data() );
m_info = Success;
m_factorizationIsOk = true;
@@ -649,7 +649,6 @@ void SparseLU<MatrixType, OrderingType>::factorize(const MatrixType& matrix)
template<typename MappedSupernodalType>
struct SparseLUMatrixLReturnType : internal::no_assignment_operator
{
- typedef typename MappedSupernodalType::Index Index;
typedef typename MappedSupernodalType::Scalar Scalar;
explicit SparseLUMatrixLReturnType(const MappedSupernodalType& mapL) : m_mapL(mapL)
{ }
@@ -666,7 +665,6 @@ struct SparseLUMatrixLReturnType : internal::no_assignment_operator
template<typename MatrixLType, typename MatrixUType>
struct SparseLUMatrixUReturnType : internal::no_assignment_operator
{
- typedef typename MatrixLType::Index Index;
typedef typename MatrixLType::Scalar Scalar;
explicit SparseLUMatrixUReturnType(const MatrixLType& mapL, const MatrixUType& mapU)
: m_mapL(mapL),m_mapU(mapU)
@@ -676,11 +674,8 @@ struct SparseLUMatrixUReturnType : internal::no_assignment_operator
template<typename Dest> void solveInPlace(MatrixBase<Dest> &X) const
{
- /* Explicit type conversion as the Index type of MatrixBase<Dest> may be wider than Index */
- eigen_assert(X.rows() <= NumTraits<Index>::highest());
- eigen_assert(X.cols() <= NumTraits<Index>::highest());
- Index nrhs = Index(X.cols());
- Index n = Index(X.rows());
+ Index nrhs = X.cols();
+ Index n = X.rows();
// Backward solve with U
for (Index k = m_mapL.nsuper(); k >= 0; k--)
{
generated by cgit v1.2.3 (git 2.39.1) at 2024-07-01 11:57:09 +0000