mirror of
https://gitlab.com/libeigen/eigen.git
synced 2025-04-30 15:54:13 +08:00
UmfPack support: fix redundant evaluation/copies when calling compute() and support generic expressions as input
This commit is contained in:
parent
775f7e5fbb
commit
433bce5c3a
@ -107,6 +107,16 @@ inline int umfpack_get_determinant(std::complex<double> *Mx, double *Ex, void *N
|
||||
return umfpack_zi_get_determinant(&mx_real,0,Ex,NumericHandle,User_Info);
|
||||
}
|
||||
|
||||
namespace internal {
|
||||
template<typename T> struct umfpack_helper_is_sparse_plain : false_type {};
|
||||
template<typename Scalar, int Options, typename StorageIndex>
|
||||
struct umfpack_helper_is_sparse_plain<SparseMatrix<Scalar,Options,StorageIndex> >
|
||||
: true_type {};
|
||||
template<typename Scalar, int Options, typename StorageIndex>
|
||||
struct umfpack_helper_is_sparse_plain<MappedSparseMatrix<Scalar,Options,StorageIndex> >
|
||||
: true_type {};
|
||||
}
|
||||
|
||||
/** \ingroup UmfPackSupport_Module
|
||||
* \brief A sparse LU factorization and solver based on UmfPack
|
||||
*
|
||||
@ -199,8 +209,11 @@ class UmfPackLU : public SparseSolverBase<UmfPackLU<_MatrixType> >
|
||||
template<typename InputMatrixType>
|
||||
void compute(const InputMatrixType& matrix)
|
||||
{
|
||||
analyzePattern(matrix);
|
||||
factorize(matrix);
|
||||
if(m_symbolic) umfpack_free_symbolic(&m_symbolic,Scalar());
|
||||
if(m_numeric) umfpack_free_numeric(&m_numeric,Scalar());
|
||||
grapInput(matrix.derived());
|
||||
analyzePattern_impl();
|
||||
factorize_impl();
|
||||
}
|
||||
|
||||
/** Performs a symbolic decomposition on the sparcity of \a matrix.
|
||||
@ -212,22 +225,12 @@ class UmfPackLU : public SparseSolverBase<UmfPackLU<_MatrixType> >
|
||||
template<typename InputMatrixType>
|
||||
void analyzePattern(const InputMatrixType& matrix)
|
||||
{
|
||||
if(m_symbolic)
|
||||
umfpack_free_symbolic(&m_symbolic,Scalar());
|
||||
if(m_numeric)
|
||||
umfpack_free_numeric(&m_numeric,Scalar());
|
||||
if(m_symbolic) umfpack_free_symbolic(&m_symbolic,Scalar());
|
||||
if(m_numeric) umfpack_free_numeric(&m_numeric,Scalar());
|
||||
|
||||
grapInput(matrix);
|
||||
grapInput(matrix.derived());
|
||||
|
||||
int errorCode = 0;
|
||||
errorCode = umfpack_symbolic(matrix.rows(), matrix.cols(), m_outerIndexPtr, m_innerIndexPtr, m_valuePtr,
|
||||
&m_symbolic, 0, 0);
|
||||
|
||||
m_isInitialized = true;
|
||||
m_info = errorCode ? InvalidInput : Success;
|
||||
m_analysisIsOk = true;
|
||||
m_factorizationIsOk = false;
|
||||
m_extractedDataAreDirty = true;
|
||||
analyzePattern_impl();
|
||||
}
|
||||
|
||||
/** Performs a numeric decomposition of \a matrix
|
||||
@ -243,15 +246,9 @@ class UmfPackLU : public SparseSolverBase<UmfPackLU<_MatrixType> >
|
||||
if(m_numeric)
|
||||
umfpack_free_numeric(&m_numeric,Scalar());
|
||||
|
||||
grapInput(matrix);
|
||||
|
||||
int errorCode;
|
||||
errorCode = umfpack_numeric(m_outerIndexPtr, m_innerIndexPtr, m_valuePtr,
|
||||
m_symbolic, &m_numeric, 0, 0);
|
||||
|
||||
m_info = errorCode ? NumericalIssue : Success;
|
||||
m_factorizationIsOk = true;
|
||||
m_extractedDataAreDirty = true;
|
||||
grapInput(matrix.derived());
|
||||
|
||||
factorize_impl();
|
||||
}
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
@ -266,7 +263,6 @@ class UmfPackLU : public SparseSolverBase<UmfPackLU<_MatrixType> >
|
||||
|
||||
protected:
|
||||
|
||||
|
||||
void init()
|
||||
{
|
||||
m_info = InvalidInput;
|
||||
@ -280,7 +276,7 @@ class UmfPackLU : public SparseSolverBase<UmfPackLU<_MatrixType> >
|
||||
}
|
||||
|
||||
template<typename InputMatrixType>
|
||||
void grapInput(const InputMatrixType& mat)
|
||||
void grapInput_impl(const InputMatrixType& mat, internal::true_type)
|
||||
{
|
||||
m_copyMatrix.resize(mat.rows(), mat.cols());
|
||||
if( ((MatrixType::Flags&RowMajorBit)==RowMajorBit) || sizeof(typename MatrixType::Index)!=sizeof(int) || !mat.isCompressed() )
|
||||
@ -298,6 +294,45 @@ class UmfPackLU : public SparseSolverBase<UmfPackLU<_MatrixType> >
|
||||
m_valuePtr = mat.valuePtr();
|
||||
}
|
||||
}
|
||||
|
||||
template<typename InputMatrixType>
|
||||
void grapInput_impl(const InputMatrixType& mat, internal::false_type)
|
||||
{
|
||||
m_copyMatrix = mat;
|
||||
m_outerIndexPtr = m_copyMatrix.outerIndexPtr();
|
||||
m_innerIndexPtr = m_copyMatrix.innerIndexPtr();
|
||||
m_valuePtr = m_copyMatrix.valuePtr();
|
||||
}
|
||||
|
||||
template<typename InputMatrixType>
|
||||
void grapInput(const InputMatrixType& mat)
|
||||
{
|
||||
grapInput_impl(mat, internal::umfpack_helper_is_sparse_plain<InputMatrixType>());
|
||||
}
|
||||
|
||||
void analyzePattern_impl()
|
||||
{
|
||||
int errorCode = 0;
|
||||
errorCode = umfpack_symbolic(m_copyMatrix.rows(), m_copyMatrix.cols(), m_outerIndexPtr, m_innerIndexPtr, m_valuePtr,
|
||||
&m_symbolic, 0, 0);
|
||||
|
||||
m_isInitialized = true;
|
||||
m_info = errorCode ? InvalidInput : Success;
|
||||
m_analysisIsOk = true;
|
||||
m_factorizationIsOk = false;
|
||||
m_extractedDataAreDirty = true;
|
||||
}
|
||||
|
||||
void factorize_impl()
|
||||
{
|
||||
int errorCode;
|
||||
errorCode = umfpack_numeric(m_outerIndexPtr, m_innerIndexPtr, m_valuePtr,
|
||||
m_symbolic, &m_numeric, 0, 0);
|
||||
|
||||
m_info = errorCode ? NumericalIssue : Success;
|
||||
m_factorizationIsOk = true;
|
||||
m_extractedDataAreDirty = true;
|
||||
}
|
||||
|
||||
// cached data to reduce reallocation, etc.
|
||||
mutable LUMatrixType m_l;
|
||||
|
Loading…
x
Reference in New Issue
Block a user