move PartialLU to the new API

This commit is contained in:
Benoit Jacob
2009-10-21 17:06:42 -04:00
parent 13f31b8daf
commit 68d48511b2
3 changed files with 84 additions and 69 deletions

View File

@@ -209,7 +209,7 @@ template<typename MatrixType> class LU
*
* \returns a solution.
*
* \note_about_inexistant_solutions
* \note_about_checking_solutions
*
* \note_about_arbitrary_choice_of_solution
* \note_about_using_kernel_to_study_multiple_solutions
@@ -374,15 +374,12 @@ template<typename MatrixType> class LU
}
protected:
bool m_isInitialized;
MatrixType m_lu;
IntColVectorType m_p;
IntRowVectorType m_q;
int m_det_pq;
int m_nonzero_pivots;
RealScalar m_maxpivot;
bool m_usePrescribedThreshold;
RealScalar m_prescribedThreshold;
int m_det_pq, m_nonzero_pivots;
RealScalar m_maxpivot, m_prescribedThreshold;
bool m_isInitialized, m_usePrescribedThreshold;
};
template<typename MatrixType>

View File

@@ -26,6 +26,8 @@
#ifndef EIGEN_PARTIALLU_H
#define EIGEN_PARTIALLU_H
template<typename MatrixType, typename Rhs> struct ei_partiallu_solve_impl;
/** \ingroup LU_Module
*
* \class PartialLU
@@ -112,26 +114,46 @@ template<typename MatrixType> class PartialLU
return m_p;
}
/** This method finds the solution x to the equation Ax=b, where A is the matrix of which
* *this is the LU decomposition. Since if this partial pivoting decomposition the matrix is assumed
* to have full rank, such a solution is assumed to exist and to be unique.
*
* \warning Again, if your matrix may not have full rank, use class LU instead. See LU::solve().
/** This method returns a solution x to the equation Ax=b, where A is the matrix of which
* *this is the LU decomposition.
*
* \param b the right-hand-side of the equation to solve. Can be a vector or a matrix,
* the only requirement in order for the equation to make sense is that
* b.rows()==A.rows(), where A is the matrix of which *this is the LU decomposition.
* \param result a pointer to the vector or matrix in which to store the solution, if any exists.
* Resized if necessary, so that result->rows()==A.cols() and result->cols()==b.cols().
* If no solution exists, *result is left with undefined coefficients.
*
* \returns the solution.
*
* Example: \include PartialLU_solve.cpp
* Output: \verbinclude PartialLU_solve.out
*
* Since this PartialLU class assumes anyway that the matrix A is invertible, the solution
* theoretically exists and is unique regardless of b.
*
* \note_about_checking_solutions
*
* \sa TriangularView::solve(), inverse(), computeInverse()
*/
template<typename OtherDerived, typename ResultType>
void solve(const MatrixBase<OtherDerived>& b, ResultType *result) const;
template<typename Rhs>
inline const ei_partiallu_solve_impl<MatrixType, Rhs>
solve(const MatrixBase<Rhs>& b) const
{
ei_assert(m_isInitialized && "LU is not initialized.");
return ei_partiallu_solve_impl<MatrixType, Rhs>(*this, b.derived());
}
/** \returns the inverse of the matrix of which *this is the LU decomposition.
*
* \warning The matrix being decomposed here is assumed to be invertible. If you need to check for
* invertibility, use class LU instead.
*
* \sa MatrixBase::inverse(), LU::inverse()
*/
inline const ei_partiallu_solve_impl<MatrixType,NestByValue<typename MatrixType::IdentityReturnType> > inverse() const
{
ei_assert(m_isInitialized && "LU is not initialized.");
return ei_partiallu_solve_impl<MatrixType,NestByValue<typename MatrixType::IdentityReturnType> >
(*this, MatrixType::Identity(m_lu.rows(), m_lu.cols()).nestByValue());
}
/** \returns the determinant of the matrix of which
* *this is the LU decomposition. It has only linear complexity
@@ -148,34 +170,6 @@ template<typename MatrixType> class PartialLU
*/
typename ei_traits<MatrixType>::Scalar determinant() const;
/** Computes the inverse of the matrix of which *this is the LU decomposition.
*
* \param result a pointer to the matrix into which to store the inverse. Resized if needed.
*
* \warning The matrix being decomposed here is assumed to be invertible. If you need to check for
* invertibility, use class LU instead.
*
* \sa MatrixBase::computeInverse(), inverse()
*/
inline void computeInverse(MatrixType *result) const
{
solve(MatrixType::Identity(m_lu.rows(), m_lu.cols()), result);
}
/** \returns the inverse of the matrix of which *this is the LU decomposition.
*
* \warning The matrix being decomposed here is assumed to be invertible. If you need to check for
* invertibility, use class LU instead.
*
* \sa computeInverse(), MatrixBase::inverse()
*/
inline MatrixType inverse() const
{
MatrixType result;
computeInverse(&result);
return result;
}
protected:
MatrixType m_lu;
IntColVectorType m_p;
@@ -411,36 +405,60 @@ typename ei_traits<MatrixType>::Scalar PartialLU<MatrixType>::determinant() cons
return Scalar(m_det_p) * m_lu.diagonal().prod();
}
template<typename MatrixType>
template<typename OtherDerived, typename ResultType>
void PartialLU<MatrixType>::solve(
const MatrixBase<OtherDerived>& b,
ResultType *result
) const
/***** Implementation of solve() *****************************************************/
template<typename MatrixType,typename Rhs>
struct ei_traits<ei_partiallu_solve_impl<MatrixType,Rhs> >
{
ei_assert(m_isInitialized && "PartialLU is not initialized.");
typedef Matrix<typename Rhs::Scalar,
MatrixType::ColsAtCompileTime,
Rhs::ColsAtCompileTime,
Rhs::PlainMatrixType::Options,
MatrixType::MaxColsAtCompileTime,
Rhs::MaxColsAtCompileTime> ReturnMatrixType;
};
/* The decomposition PA = LU can be rewritten as A = P^{-1} L U.
* So we proceed as follows:
* Step 1: compute c = Pb.
* Step 2: replace c by the solution x to Lx = c.
* Step 3: replace c by the solution x to Ux = c.
*/
template<typename MatrixType, typename Rhs>
struct ei_partiallu_solve_impl : public ReturnByValue<ei_partiallu_solve_impl<MatrixType, Rhs> >
{
typedef typename ei_cleantype<typename Rhs::Nested>::type RhsNested;
typedef PartialLU<MatrixType> LUType;
const LUType& m_lu;
const typename Rhs::Nested m_rhs;
const int size = m_lu.rows();
ei_assert(b.rows() == size);
ei_partiallu_solve_impl(const LUType& lu, const Rhs& rhs)
: m_lu(lu), m_rhs(rhs)
{}
result->resize(size, b.cols());
inline int rows() const { return m_lu.matrixLU().cols(); }
inline int cols() const { return m_rhs.cols(); }
// Step 1
for(int i = 0; i < size; ++i) result->row(m_p.coeff(i)) = b.row(i);
template<typename Dest> void evalTo(Dest& dst) const
{
/* The decomposition PA = LU can be rewritten as A = P^{-1} L U.
* So we proceed as follows:
* Step 1: compute c = Pb.
* Step 2: replace c by the solution x to Lx = c.
* Step 3: replace c by the solution x to Ux = c.
*/
// Step 2
m_lu.template triangularView<UnitLowerTriangular>().solveInPlace(*result);
const int size = m_lu.matrixLU().rows();
ei_assert(m_rhs.rows() == size);
// Step 3
m_lu.template triangularView<UpperTriangular>().solveInPlace(*result);
}
dst.resize(size, m_rhs.cols());
// Step 1
for(int i = 0; i < size; ++i) dst.row(m_lu.permutationP().coeff(i)) = m_rhs.row(i);
// Step 2
m_lu.matrixLU().template triangularView<UnitLowerTriangular>().solveInPlace(dst);
// Step 3
m_lu.matrixLU().template triangularView<UpperTriangular>().solveInPlace(dst);
}
};
/******** MatrixBase methods *******/
/** \lu_module
*