unsupported/Eigen/src/SparseExtra/UmfPackSupport.h - mirror - Git at Google

 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2008-2009 Gael Guennebaud <g.gael@free.fr>
 //
 // Eigen is free software; you can redistribute it and/or
 // modify it under the terms of the GNU Lesser General Public
 // License as published by the Free Software Foundation; either
 // version 3 of the License, or (at your option) any later version.
 //
 // Alternatively, you can redistribute it and/or
 // modify it under the terms of the GNU General Public License as
 // published by the Free Software Foundation; either version 2 of
 // the License, or (at your option) any later version.
 //
 // Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
 // WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
 // FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
 // GNU General Public License for more details.
 //
 // You should have received a copy of the GNU Lesser General Public
 // License and a copy of the GNU General Public License along with
 // Eigen. If not, see <http://www.gnu.org/licenses/>.

 #ifndef EIGEN_UMFPACKSUPPORT_H
 #define EIGEN_UMFPACKSUPPORT_H

 /* TODO extract L, extract U, compute det, etc... */

 // generic double/complex<double> wrapper functions:

 inline void umfpack_free_numeric(void **Numeric, double)
 { umfpack_di_free_numeric(Numeric); }

 inline void umfpack_free_numeric(void **Numeric, std::complex<double>)
 { umfpack_zi_free_numeric(Numeric); }

 inline void umfpack_free_symbolic(void **Symbolic, double)
 { umfpack_di_free_symbolic(Symbolic); }

 inline void umfpack_free_symbolic(void **Symbolic, std::complex<double>)
 { umfpack_zi_free_symbolic(Symbolic); }

 inline int umfpack_symbolic(int n_row,int n_col,
                             const int Ap[], const int Ai[], const double Ax[], void **Symbolic,
                             const double Control [UMFPACK_CONTROL], double Info [UMFPACK_INFO])
 {
   return umfpack_di_symbolic(n_row,n_col,Ap,Ai,Ax,Symbolic,Control,Info);
 }

 inline int umfpack_symbolic(int n_row,int n_col,
                             const int Ap[], const int Ai[], const std::complex<double> Ax[], void **Symbolic,
                             const double Control [UMFPACK_CONTROL], double Info [UMFPACK_INFO])
 {
   return umfpack_zi_symbolic(n_row,n_col,Ap,Ai,&Ax[0].real(),0,Symbolic,Control,Info);
 }

 inline int umfpack_numeric( const int Ap[], const int Ai[], const double Ax[],
                             void *Symbolic, void **Numeric,
                             const double Control[UMFPACK_CONTROL],double Info [UMFPACK_INFO])
 {
   return umfpack_di_numeric(Ap,Ai,Ax,Symbolic,Numeric,Control,Info);
 }

 inline int umfpack_numeric( const int Ap[], const int Ai[], const std::complex<double> Ax[],
                             void *Symbolic, void **Numeric,
                             const double Control[UMFPACK_CONTROL],double Info [UMFPACK_INFO])
 {
   return umfpack_zi_numeric(Ap,Ai,&Ax[0].real(),0,Symbolic,Numeric,Control,Info);
 }

 inline int umfpack_solve( int sys, const int Ap[], const int Ai[], const double Ax[],
                           double X[], const double B[], void *Numeric,
                           const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
 {
   return umfpack_di_solve(sys,Ap,Ai,Ax,X,B,Numeric,Control,Info);
 }

 inline int umfpack_solve( int sys, const int Ap[], const int Ai[], const std::complex<double> Ax[],
                           std::complex<double> X[], const std::complex<double> B[], void *Numeric,
                           const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
 {
   return umfpack_zi_solve(sys,Ap,Ai,&Ax[0].real(),0,&X[0].real(),0,&B[0].real(),0,Numeric,Control,Info);
 }

 inline int umfpack_get_lunz(int *lnz, int *unz, int *n_row, int *n_col, int *nz_udiag, void *Numeric, double)
 {
   return umfpack_di_get_lunz(lnz,unz,n_row,n_col,nz_udiag,Numeric);
 }

 inline int umfpack_get_lunz(int *lnz, int *unz, int *n_row, int *n_col, int *nz_udiag, void *Numeric, std::complex<double>)
 {
   return umfpack_zi_get_lunz(lnz,unz,n_row,n_col,nz_udiag,Numeric);
 }

 inline int umfpack_get_numeric(int Lp[], int Lj[], double Lx[], int Up[], int Ui[], double Ux[],
                                int P[], int Q[], double Dx[], int *do_recip, double Rs[], void *Numeric)
 {
   return umfpack_di_get_numeric(Lp,Lj,Lx,Up,Ui,Ux,P,Q,Dx,do_recip,Rs,Numeric);
 }

 inline int umfpack_get_numeric(int Lp[], int Lj[], std::complex<double> Lx[], int Up[], int Ui[], std::complex<double> Ux[],
                                int P[], int Q[], std::complex<double> Dx[], int *do_recip, double Rs[], void *Numeric)
 {
   return umfpack_zi_get_numeric(Lp,Lj,Lx?&Lx[0].real():0,0,Up,Ui,Ux?&Ux[0].real():0,0,P,Q,
                                Dx?&Dx[0].real():0,0,do_recip,Rs,Numeric);
 }

 inline int umfpack_get_determinant(double *Mx, double *Ex, void *NumericHandle, double User_Info [UMFPACK_INFO])
 {
   return umfpack_di_get_determinant(Mx,Ex,NumericHandle,User_Info);
 }

 inline int umfpack_get_determinant(std::complex<double> *Mx, double *Ex, void *NumericHandle, double User_Info [UMFPACK_INFO])
 {
   return umfpack_zi_get_determinant(&Mx->real(),0,Ex,NumericHandle,User_Info);
 }


 template<typename MatrixType>
 class SparseLU<MatrixType,UmfPack> : public SparseLU<MatrixType>
 {
   protected:
     typedef SparseLU<MatrixType> Base;
     typedef typename Base::Scalar Scalar;
     typedef typename Base::RealScalar RealScalar;
     typedef Matrix<Scalar,Dynamic,1> Vector;
     typedef Matrix<int, 1, MatrixType::ColsAtCompileTime> IntRowVectorType;
     typedef Matrix<int, MatrixType::RowsAtCompileTime, 1> IntColVectorType;
     typedef SparseMatrix<Scalar,Lower|UnitDiag> LMatrixType;
     typedef SparseMatrix<Scalar,Upper> UMatrixType;
     using Base::m_flags;
     using Base::m_status;

   public:

     SparseLU(int flags = NaturalOrdering)
       : Base(flags), m_numeric(0)
     {
     }

     SparseLU(const MatrixType& matrix, int flags = NaturalOrdering)
       : Base(flags), m_numeric(0)
     {
       compute(matrix);
     }

     ~SparseLU()
     {
       if (m_numeric)
         umfpack_free_numeric(&m_numeric,Scalar());
     }

     inline const LMatrixType& matrixL() const
     {
       if (m_extractedDataAreDirty) extractData();
       return m_l;
     }

     inline const UMatrixType& matrixU() const
     {
       if (m_extractedDataAreDirty) extractData();
       return m_u;
     }

     inline const IntColVectorType& permutationP() const
     {
       if (m_extractedDataAreDirty) extractData();
       return m_p;
     }

     inline const IntRowVectorType& permutationQ() const
     {
       if (m_extractedDataAreDirty) extractData();
       return m_q;
     }

     Scalar determinant() const;

     template<typename BDerived, typename XDerived>
     bool solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived>* x) const;

     void compute(const MatrixType& matrix);

   protected:

     void extractData() const;

   protected:
     // cached data:
     void* m_numeric;
     const MatrixType* m_matrixRef;
     mutable LMatrixType m_l;
     mutable UMatrixType m_u;
     mutable IntColVectorType m_p;
     mutable IntRowVectorType m_q;
     mutable bool m_extractedDataAreDirty;
 };

 template<typename MatrixType>
 void SparseLU<MatrixType,UmfPack>::compute(const MatrixType& a)
 {
   typedef typename MatrixType::Index Index;
   const Index rows = a.rows();
   const Index cols = a.cols();
   ei_assert((MatrixType::Flags&RowMajorBit)==0 && "Row major matrices are not supported yet");

   m_matrixRef = &a;

   if (m_numeric)
     umfpack_free_numeric(&m_numeric,Scalar());

   void* symbolic;
   int errorCode = 0;
   errorCode = umfpack_symbolic(rows, cols, a._outerIndexPtr(), a._innerIndexPtr(), a._valuePtr(),
                                   &symbolic, 0, 0);
   if (errorCode==0)
     errorCode = umfpack_numeric(a._outerIndexPtr(), a._innerIndexPtr(), a._valuePtr(),
                                    symbolic, &m_numeric, 0, 0);

   umfpack_free_symbolic(&symbolic,Scalar());

   m_extractedDataAreDirty = true;

   Base::m_succeeded = (errorCode==0);
 }

 template<typename MatrixType>
 void SparseLU<MatrixType,UmfPack>::extractData() const
 {
   if (m_extractedDataAreDirty)
   {
     // get size of the data
     int lnz, unz, rows, cols, nz_udiag;
     umfpack_get_lunz(&lnz, &unz, &rows, &cols, &nz_udiag, m_numeric, Scalar());

     // allocate data
     m_l.resize(rows,std::min(rows,cols));
     m_l.resizeNonZeros(lnz);

     m_u.resize(std::min(rows,cols),cols);
     m_u.resizeNonZeros(unz);

     m_p.resize(rows);
     m_q.resize(cols);

     // extract
     umfpack_get_numeric(m_l._outerIndexPtr(), m_l._innerIndexPtr(), m_l._valuePtr(),
                         m_u._outerIndexPtr(), m_u._innerIndexPtr(), m_u._valuePtr(),
                         m_p.data(), m_q.data(), 0, 0, 0, m_numeric);

     m_extractedDataAreDirty = false;
   }
 }

 template<typename MatrixType>
 typename SparseLU<MatrixType,UmfPack>::Scalar SparseLU<MatrixType,UmfPack>::determinant() const
 {
   Scalar det;
   umfpack_get_determinant(&det, 0, m_numeric, 0);
   return det;
 }

 template<typename MatrixType>
 template<typename BDerived,typename XDerived>
 bool SparseLU<MatrixType,UmfPack>::solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived> *x) const
 {
   //const int size = m_matrix.rows();
   const int rhsCols = b.cols();
 //   ei_assert(size==b.rows());
   ei_assert((BDerived::Flags&RowMajorBit)==0 && "UmfPack backend does not support non col-major rhs yet");
   ei_assert((XDerived::Flags&RowMajorBit)==0 && "UmfPack backend does not support non col-major result yet");

   int errorCode;
   for (int j=0; j<rhsCols; ++j)
   {
     errorCode = umfpack_solve(UMFPACK_A,
         m_matrixRef->_outerIndexPtr(), m_matrixRef->_innerIndexPtr(), m_matrixRef->_valuePtr(),
         &x->col(j).coeffRef(0), &b.const_cast_derived().col(j).coeffRef(0), m_numeric, 0, 0);
     if (errorCode!=0)
       return false;
   }
 //   errorCode = umfpack_di_solve(UMFPACK_A,
 //       m_matrixRef._outerIndexPtr(), m_matrixRef._innerIndexPtr(), m_matrixRef._valuePtr(),
 //       x->derived().data(), b.derived().data(), m_numeric, 0, 0);

   return true;
 }

 #endif // EIGEN_UMFPACKSUPPORT_H
	// This file is part of Eigen, a lightweight C++ template library
	// for linear algebra.
	//
	// Copyright (C) 2008-2009 Gael Guennebaud <g.gael@free.fr>
	//
	// Eigen is free software; you can redistribute it and/or
	// modify it under the terms of the GNU Lesser General Public
	// License as published by the Free Software Foundation; either
	// version 3 of the License, or (at your option) any later version.
	//
	// Alternatively, you can redistribute it and/or
	// modify it under the terms of the GNU General Public License as
	// published by the Free Software Foundation; either version 2 of
	// the License, or (at your option) any later version.
	//
	// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
	// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
	// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
	// GNU General Public License for more details.
	//
	// You should have received a copy of the GNU Lesser General Public
	// License and a copy of the GNU General Public License along with
	// Eigen. If not, see <http://www.gnu.org/licenses/>.

	#ifndef EIGEN_UMFPACKSUPPORT_H
	#define EIGEN_UMFPACKSUPPORT_H

	/* TODO extract L, extract U, compute det, etc... */

	// generic double/complex<double> wrapper functions:

	inline void umfpack_free_numeric(void **Numeric, double)
	{ umfpack_di_free_numeric(Numeric); }

	inline void umfpack_free_numeric(void **Numeric, std::complex<double>)
	{ umfpack_zi_free_numeric(Numeric); }

	inline void umfpack_free_symbolic(void **Symbolic, double)
	{ umfpack_di_free_symbolic(Symbolic); }

	inline void umfpack_free_symbolic(void **Symbolic, std::complex<double>)
	{ umfpack_zi_free_symbolic(Symbolic); }

	inline int umfpack_symbolic(int n_row,int n_col,
	const int Ap[], const int Ai[], const double Ax[], void **Symbolic,
	const double Control [UMFPACK_CONTROL], double Info [UMFPACK_INFO])
	{
	return umfpack_di_symbolic(n_row,n_col,Ap,Ai,Ax,Symbolic,Control,Info);
	}

	inline int umfpack_symbolic(int n_row,int n_col,
	const int Ap[], const int Ai[], const std::complex<double> Ax[], void **Symbolic,
	const double Control [UMFPACK_CONTROL], double Info [UMFPACK_INFO])
	{
	return umfpack_zi_symbolic(n_row,n_col,Ap,Ai,&Ax[0].real(),0,Symbolic,Control,Info);
	}

	inline int umfpack_numeric( const int Ap[], const int Ai[], const double Ax[],
	void Symbolic, void *Numeric,
	const double Control[UMFPACK_CONTROL],double Info [UMFPACK_INFO])
	{
	return umfpack_di_numeric(Ap,Ai,Ax,Symbolic,Numeric,Control,Info);
	}

	inline int umfpack_numeric( const int Ap[], const int Ai[], const std::complex<double> Ax[],
	void Symbolic, void *Numeric,
	const double Control[UMFPACK_CONTROL],double Info [UMFPACK_INFO])
	{
	return umfpack_zi_numeric(Ap,Ai,&Ax[0].real(),0,Symbolic,Numeric,Control,Info);
	}

	inline int umfpack_solve( int sys, const int Ap[], const int Ai[], const double Ax[],
	double X[], const double B[], void *Numeric,
	const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
	{
	return umfpack_di_solve(sys,Ap,Ai,Ax,X,B,Numeric,Control,Info);
	}

	inline int umfpack_solve( int sys, const int Ap[], const int Ai[], const std::complex<double> Ax[],
	std::complex<double> X[], const std::complex<double> B[], void *Numeric,
	const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
	{
	return umfpack_zi_solve(sys,Ap,Ai,&Ax[0].real(),0,&X[0].real(),0,&B[0].real(),0,Numeric,Control,Info);
	}

	inline int umfpack_get_lunz(int lnz, int unz, int n_row, int n_col, int nz_udiag, void Numeric, double)
	{
	return umfpack_di_get_lunz(lnz,unz,n_row,n_col,nz_udiag,Numeric);
	}

	inline int umfpack_get_lunz(int lnz, int unz, int n_row, int n_col, int nz_udiag, void Numeric, std::complex<double>)
	{
	return umfpack_zi_get_lunz(lnz,unz,n_row,n_col,nz_udiag,Numeric);
	}

	inline int umfpack_get_numeric(int Lp[], int Lj[], double Lx[], int Up[], int Ui[], double Ux[],
	int P[], int Q[], double Dx[], int do_recip, double Rs[], void Numeric)
	{
	return umfpack_di_get_numeric(Lp,Lj,Lx,Up,Ui,Ux,P,Q,Dx,do_recip,Rs,Numeric);
	}

	inline int umfpack_get_numeric(int Lp[], int Lj[], std::complex<double> Lx[], int Up[], int Ui[], std::complex<double> Ux[],
	int P[], int Q[], std::complex<double> Dx[], int do_recip, double Rs[], void Numeric)
	{
	return umfpack_zi_get_numeric(Lp,Lj,Lx?&Lx[0].real():0,0,Up,Ui,Ux?&Ux[0].real():0,0,P,Q,
	Dx?&Dx[0].real():0,0,do_recip,Rs,Numeric);
	}

	inline int umfpack_get_determinant(double Mx, double Ex, void *NumericHandle, double User_Info [UMFPACK_INFO])
	{
	return umfpack_di_get_determinant(Mx,Ex,NumericHandle,User_Info);
	}

	inline int umfpack_get_determinant(std::complex<double> Mx, double Ex, void *NumericHandle, double User_Info [UMFPACK_INFO])
	{
	return umfpack_zi_get_determinant(&Mx->real(),0,Ex,NumericHandle,User_Info);
	}


	template<typename MatrixType>
	class SparseLU<MatrixType,UmfPack> : public SparseLU<MatrixType>
	{
	protected:
	typedef SparseLU<MatrixType> Base;
	typedef typename Base::Scalar Scalar;
	typedef typename Base::RealScalar RealScalar;
	typedef Matrix<Scalar,Dynamic,1> Vector;
	typedef Matrix<int, 1, MatrixType::ColsAtCompileTime> IntRowVectorType;
	typedef Matrix<int, MatrixType::RowsAtCompileTime, 1> IntColVectorType;
	typedef SparseMatrix<Scalar,Lower\|UnitDiag> LMatrixType;
	typedef SparseMatrix<Scalar,Upper> UMatrixType;
	using Base::m_flags;
	using Base::m_status;

	public:

	SparseLU(int flags = NaturalOrdering)
	: Base(flags), m_numeric(0)
	{
	}

	SparseLU(const MatrixType& matrix, int flags = NaturalOrdering)
	: Base(flags), m_numeric(0)
	{
	compute(matrix);
	}

	~SparseLU()
	{
	if (m_numeric)
	umfpack_free_numeric(&m_numeric,Scalar());
	}

	inline const LMatrixType& matrixL() const
	{
	if (m_extractedDataAreDirty) extractData();
	return m_l;
	}

	inline const UMatrixType& matrixU() const
	{
	if (m_extractedDataAreDirty) extractData();
	return m_u;
	}

	inline const IntColVectorType& permutationP() const
	{
	if (m_extractedDataAreDirty) extractData();
	return m_p;
	}

	inline const IntRowVectorType& permutationQ() const
	{
	if (m_extractedDataAreDirty) extractData();
	return m_q;
	}

	Scalar determinant() const;

	template<typename BDerived, typename XDerived>
	bool solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived>* x) const;

	void compute(const MatrixType& matrix);

	protected:

	void extractData() const;

	protected:
	// cached data:
	void* m_numeric;
	const MatrixType* m_matrixRef;
	mutable LMatrixType m_l;
	mutable UMatrixType m_u;
	mutable IntColVectorType m_p;
	mutable IntRowVectorType m_q;
	mutable bool m_extractedDataAreDirty;
	};

	template<typename MatrixType>
	void SparseLU<MatrixType,UmfPack>::compute(const MatrixType& a)
	{
	typedef typename MatrixType::Index Index;
	const Index rows = a.rows();
	const Index cols = a.cols();
	ei_assert((MatrixType::Flags&RowMajorBit)==0 && "Row major matrices are not supported yet");

	m_matrixRef = &a;

	if (m_numeric)
	umfpack_free_numeric(&m_numeric,Scalar());

	void* symbolic;
	int errorCode = 0;
	errorCode = umfpack_symbolic(rows, cols, a._outerIndexPtr(), a._innerIndexPtr(), a._valuePtr(),
	&symbolic, 0, 0);
	if (errorCode==0)
	errorCode = umfpack_numeric(a._outerIndexPtr(), a._innerIndexPtr(), a._valuePtr(),
	symbolic, &m_numeric, 0, 0);

	umfpack_free_symbolic(&symbolic,Scalar());

	m_extractedDataAreDirty = true;

	Base::m_succeeded = (errorCode==0);
	}

	template<typename MatrixType>
	void SparseLU<MatrixType,UmfPack>::extractData() const
	{
	if (m_extractedDataAreDirty)
	{
	// get size of the data
	int lnz, unz, rows, cols, nz_udiag;
	umfpack_get_lunz(&lnz, &unz, &rows, &cols, &nz_udiag, m_numeric, Scalar());

	// allocate data
	m_l.resize(rows,std::min(rows,cols));
	m_l.resizeNonZeros(lnz);

	m_u.resize(std::min(rows,cols),cols);
	m_u.resizeNonZeros(unz);

	m_p.resize(rows);
	m_q.resize(cols);

	// extract
	umfpack_get_numeric(m_l._outerIndexPtr(), m_l._innerIndexPtr(), m_l._valuePtr(),
	m_u._outerIndexPtr(), m_u._innerIndexPtr(), m_u._valuePtr(),
	m_p.data(), m_q.data(), 0, 0, 0, m_numeric);

	m_extractedDataAreDirty = false;
	}
	}

	template<typename MatrixType>
	typename SparseLU<MatrixType,UmfPack>::Scalar SparseLU<MatrixType,UmfPack>::determinant() const
	{
	Scalar det;
	umfpack_get_determinant(&det, 0, m_numeric, 0);
	return det;
	}

	template<typename MatrixType>
	template<typename BDerived,typename XDerived>
	bool SparseLU<MatrixType,UmfPack>::solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived> *x) const
	{
	//const int size = m_matrix.rows();
	const int rhsCols = b.cols();
	// ei_assert(size==b.rows());
	ei_assert((BDerived::Flags&RowMajorBit)==0 && "UmfPack backend does not support non col-major rhs yet");
	ei_assert((XDerived::Flags&RowMajorBit)==0 && "UmfPack backend does not support non col-major result yet");

	int errorCode;
	for (int j=0; j<rhsCols; ++j)
	{
	errorCode = umfpack_solve(UMFPACK_A,
	m_matrixRef->_outerIndexPtr(), m_matrixRef->_innerIndexPtr(), m_matrixRef->_valuePtr(),
	&x->col(j).coeffRef(0), &b.const_cast_derived().col(j).coeffRef(0), m_numeric, 0, 0);
	if (errorCode!=0)
	return false;
	}
	// errorCode = umfpack_di_solve(UMFPACK_A,
	// m_matrixRef._outerIndexPtr(), m_matrixRef._innerIndexPtr(), m_matrixRef._valuePtr(),
	// x->derived().data(), b.derived().data(), m_numeric, 0, 0);

	return true;
	}

	#endif // EIGEN_UMFPACKSUPPORT_H