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00010 #ifndef EIGEN_UMFPACKSUPPORT_H
00011 #define EIGEN_UMFPACKSUPPORT_H
00012
00013 namespace Eigen {
00014
00015
00016
00017
00018
00019 inline void umfpack_free_numeric(void **Numeric, double)
00020 { umfpack_di_free_numeric(Numeric); *Numeric = 0; }
00021
00022 inline void umfpack_free_numeric(void **Numeric, std::complex<double>)
00023 { umfpack_zi_free_numeric(Numeric); *Numeric = 0; }
00024
00025 inline void umfpack_free_symbolic(void **Symbolic, double)
00026 { umfpack_di_free_symbolic(Symbolic); *Symbolic = 0; }
00027
00028 inline void umfpack_free_symbolic(void **Symbolic, std::complex<double>)
00029 { umfpack_zi_free_symbolic(Symbolic); *Symbolic = 0; }
00030
00031 inline int umfpack_symbolic(int n_row,int n_col,
00032 const int Ap[], const int Ai[], const double Ax[], void **Symbolic,
00033 const double Control [UMFPACK_CONTROL], double Info [UMFPACK_INFO])
00034 {
00035 return umfpack_di_symbolic(n_row,n_col,Ap,Ai,Ax,Symbolic,Control,Info);
00036 }
00037
00038 inline int umfpack_symbolic(int n_row,int n_col,
00039 const int Ap[], const int Ai[], const std::complex<double> Ax[], void **Symbolic,
00040 const double Control [UMFPACK_CONTROL], double Info [UMFPACK_INFO])
00041 {
00042 return umfpack_zi_symbolic(n_row,n_col,Ap,Ai,&numext::real_ref(Ax[0]),0,Symbolic,Control,Info);
00043 }
00044
00045 inline int umfpack_numeric( const int Ap[], const int Ai[], const double Ax[],
00046 void *Symbolic, void **Numeric,
00047 const double Control[UMFPACK_CONTROL],double Info [UMFPACK_INFO])
00048 {
00049 return umfpack_di_numeric(Ap,Ai,Ax,Symbolic,Numeric,Control,Info);
00050 }
00051
00052 inline int umfpack_numeric( const int Ap[], const int Ai[], const std::complex<double> Ax[],
00053 void *Symbolic, void **Numeric,
00054 const double Control[UMFPACK_CONTROL],double Info [UMFPACK_INFO])
00055 {
00056 return umfpack_zi_numeric(Ap,Ai,&numext::real_ref(Ax[0]),0,Symbolic,Numeric,Control,Info);
00057 }
00058
00059 inline int umfpack_solve( int sys, const int Ap[], const int Ai[], const double Ax[],
00060 double X[], const double B[], void *Numeric,
00061 const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
00062 {
00063 return umfpack_di_solve(sys,Ap,Ai,Ax,X,B,Numeric,Control,Info);
00064 }
00065
00066 inline int umfpack_solve( int sys, const int Ap[], const int Ai[], const std::complex<double> Ax[],
00067 std::complex<double> X[], const std::complex<double> B[], void *Numeric,
00068 const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
00069 {
00070 return umfpack_zi_solve(sys,Ap,Ai,&numext::real_ref(Ax[0]),0,&numext::real_ref(X[0]),0,&numext::real_ref(B[0]),0,Numeric,Control,Info);
00071 }
00072
00073 inline int umfpack_get_lunz(int *lnz, int *unz, int *n_row, int *n_col, int *nz_udiag, void *Numeric, double)
00074 {
00075 return umfpack_di_get_lunz(lnz,unz,n_row,n_col,nz_udiag,Numeric);
00076 }
00077
00078 inline int umfpack_get_lunz(int *lnz, int *unz, int *n_row, int *n_col, int *nz_udiag, void *Numeric, std::complex<double>)
00079 {
00080 return umfpack_zi_get_lunz(lnz,unz,n_row,n_col,nz_udiag,Numeric);
00081 }
00082
00083 inline int umfpack_get_numeric(int Lp[], int Lj[], double Lx[], int Up[], int Ui[], double Ux[],
00084 int P[], int Q[], double Dx[], int *do_recip, double Rs[], void *Numeric)
00085 {
00086 return umfpack_di_get_numeric(Lp,Lj,Lx,Up,Ui,Ux,P,Q,Dx,do_recip,Rs,Numeric);
00087 }
00088
00089 inline int umfpack_get_numeric(int Lp[], int Lj[], std::complex<double> Lx[], int Up[], int Ui[], std::complex<double> Ux[],
00090 int P[], int Q[], std::complex<double> Dx[], int *do_recip, double Rs[], void *Numeric)
00091 {
00092 double& lx0_real = numext::real_ref(Lx[0]);
00093 double& ux0_real = numext::real_ref(Ux[0]);
00094 double& dx0_real = numext::real_ref(Dx[0]);
00095 return umfpack_zi_get_numeric(Lp,Lj,Lx?&lx0_real:0,0,Up,Ui,Ux?&ux0_real:0,0,P,Q,
00096 Dx?&dx0_real:0,0,do_recip,Rs,Numeric);
00097 }
00098
00099 inline int umfpack_get_determinant(double *Mx, double *Ex, void *NumericHandle, double User_Info [UMFPACK_INFO])
00100 {
00101 return umfpack_di_get_determinant(Mx,Ex,NumericHandle,User_Info);
00102 }
00103
00104 inline int umfpack_get_determinant(std::complex<double> *Mx, double *Ex, void *NumericHandle, double User_Info [UMFPACK_INFO])
00105 {
00106 double& mx_real = numext::real_ref(*Mx);
00107 return umfpack_zi_get_determinant(&mx_real,0,Ex,NumericHandle,User_Info);
00108 }
00109
00123 template<typename _MatrixType>
00124 class UmfPackLU : internal::noncopyable
00125 {
00126 public:
00127 typedef _MatrixType MatrixType;
00128 typedef typename MatrixType::Scalar Scalar;
00129 typedef typename MatrixType::RealScalar RealScalar;
00130 typedef typename MatrixType::Index Index;
00131 typedef Matrix<Scalar,Dynamic,1> Vector;
00132 typedef Matrix<int, 1, MatrixType::ColsAtCompileTime> IntRowVectorType;
00133 typedef Matrix<int, MatrixType::RowsAtCompileTime, 1> IntColVectorType;
00134 typedef SparseMatrix<Scalar> LUMatrixType;
00135 typedef SparseMatrix<Scalar,ColMajor,int> UmfpackMatrixType;
00136
00137 public:
00138
00139 UmfPackLU() { init(); }
00140
00141 UmfPackLU(const MatrixType& matrix)
00142 {
00143 init();
00144 compute(matrix);
00145 }
00146
00147 ~UmfPackLU()
00148 {
00149 if(m_symbolic) umfpack_free_symbolic(&m_symbolic,Scalar());
00150 if(m_numeric) umfpack_free_numeric(&m_numeric,Scalar());
00151 }
00152
00153 inline Index rows() const { return m_copyMatrix.rows(); }
00154 inline Index cols() const { return m_copyMatrix.cols(); }
00155
00161 ComputationInfo info() const
00162 {
00163 eigen_assert(m_isInitialized && "Decomposition is not initialized.");
00164 return m_info;
00165 }
00166
00167 inline const LUMatrixType& matrixL() const
00168 {
00169 if (m_extractedDataAreDirty) extractData();
00170 return m_l;
00171 }
00172
00173 inline const LUMatrixType& matrixU() const
00174 {
00175 if (m_extractedDataAreDirty) extractData();
00176 return m_u;
00177 }
00178
00179 inline const IntColVectorType& permutationP() const
00180 {
00181 if (m_extractedDataAreDirty) extractData();
00182 return m_p;
00183 }
00184
00185 inline const IntRowVectorType& permutationQ() const
00186 {
00187 if (m_extractedDataAreDirty) extractData();
00188 return m_q;
00189 }
00190
00195 void compute(const MatrixType& matrix)
00196 {
00197 analyzePattern(matrix);
00198 factorize(matrix);
00199 }
00200
00205 template<typename Rhs>
00206 inline const internal::solve_retval<UmfPackLU, Rhs> solve(const MatrixBase<Rhs>& b) const
00207 {
00208 eigen_assert(m_isInitialized && "UmfPackLU is not initialized.");
00209 eigen_assert(rows()==b.rows()
00210 && "UmfPackLU::solve(): invalid number of rows of the right hand side matrix b");
00211 return internal::solve_retval<UmfPackLU, Rhs>(*this, b.derived());
00212 }
00213
00218 template<typename Rhs>
00219 inline const internal::sparse_solve_retval<UmfPackLU, Rhs> solve(const SparseMatrixBase<Rhs>& b) const
00220 {
00221 eigen_assert(m_isInitialized && "UmfPackLU is not initialized.");
00222 eigen_assert(rows()==b.rows()
00223 && "UmfPackLU::solve(): invalid number of rows of the right hand side matrix b");
00224 return internal::sparse_solve_retval<UmfPackLU, Rhs>(*this, b.derived());
00225 }
00226
00233 void analyzePattern(const MatrixType& matrix)
00234 {
00235 if(m_symbolic)
00236 umfpack_free_symbolic(&m_symbolic,Scalar());
00237 if(m_numeric)
00238 umfpack_free_numeric(&m_numeric,Scalar());
00239
00240 grapInput(matrix);
00241
00242 int errorCode = 0;
00243 errorCode = umfpack_symbolic(matrix.rows(), matrix.cols(), m_outerIndexPtr, m_innerIndexPtr, m_valuePtr,
00244 &m_symbolic, 0, 0);
00245
00246 m_isInitialized = true;
00247 m_info = errorCode ? InvalidInput : Success;
00248 m_analysisIsOk = true;
00249 m_factorizationIsOk = false;
00250 }
00251
00258 void factorize(const MatrixType& matrix)
00259 {
00260 eigen_assert(m_analysisIsOk && "UmfPackLU: you must first call analyzePattern()");
00261 if(m_numeric)
00262 umfpack_free_numeric(&m_numeric,Scalar());
00263
00264 grapInput(matrix);
00265
00266 int errorCode;
00267 errorCode = umfpack_numeric(m_outerIndexPtr, m_innerIndexPtr, m_valuePtr,
00268 m_symbolic, &m_numeric, 0, 0);
00269
00270 m_info = errorCode ? NumericalIssue : Success;
00271 m_factorizationIsOk = true;
00272 }
00273
00274 #ifndef EIGEN_PARSED_BY_DOXYGEN
00275
00276 template<typename BDerived,typename XDerived>
00277 bool _solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived> &x) const;
00278 #endif
00279
00280 Scalar determinant() const;
00281
00282 void extractData() const;
00283
00284 protected:
00285
00286
00287 void init()
00288 {
00289 m_info = InvalidInput;
00290 m_isInitialized = false;
00291 m_numeric = 0;
00292 m_symbolic = 0;
00293 m_outerIndexPtr = 0;
00294 m_innerIndexPtr = 0;
00295 m_valuePtr = 0;
00296 }
00297
00298 void grapInput(const MatrixType& mat)
00299 {
00300 m_copyMatrix.resize(mat.rows(), mat.cols());
00301 if( ((MatrixType::Flags&RowMajorBit)==RowMajorBit) || sizeof(typename MatrixType::Index)!=sizeof(int) || !mat.isCompressed() )
00302 {
00303
00304 m_copyMatrix = mat;
00305 m_outerIndexPtr = m_copyMatrix.outerIndexPtr();
00306 m_innerIndexPtr = m_copyMatrix.innerIndexPtr();
00307 m_valuePtr = m_copyMatrix.valuePtr();
00308 }
00309 else
00310 {
00311 m_outerIndexPtr = mat.outerIndexPtr();
00312 m_innerIndexPtr = mat.innerIndexPtr();
00313 m_valuePtr = mat.valuePtr();
00314 }
00315 }
00316
00317
00318 mutable LUMatrixType m_l;
00319 mutable LUMatrixType m_u;
00320 mutable IntColVectorType m_p;
00321 mutable IntRowVectorType m_q;
00322
00323 UmfpackMatrixType m_copyMatrix;
00324 const Scalar* m_valuePtr;
00325 const int* m_outerIndexPtr;
00326 const int* m_innerIndexPtr;
00327 void* m_numeric;
00328 void* m_symbolic;
00329
00330 mutable ComputationInfo m_info;
00331 bool m_isInitialized;
00332 int m_factorizationIsOk;
00333 int m_analysisIsOk;
00334 mutable bool m_extractedDataAreDirty;
00335
00336 private:
00337 UmfPackLU(UmfPackLU& ) { }
00338 };
00339
00340
00341 template<typename MatrixType>
00342 void UmfPackLU<MatrixType>::extractData() const
00343 {
00344 if (m_extractedDataAreDirty)
00345 {
00346
00347 int lnz, unz, rows, cols, nz_udiag;
00348 umfpack_get_lunz(&lnz, &unz, &rows, &cols, &nz_udiag, m_numeric, Scalar());
00349
00350
00351 m_l.resize(rows,(std::min)(rows,cols));
00352 m_l.resizeNonZeros(lnz);
00353
00354 m_u.resize((std::min)(rows,cols),cols);
00355 m_u.resizeNonZeros(unz);
00356
00357 m_p.resize(rows);
00358 m_q.resize(cols);
00359
00360
00361 umfpack_get_numeric(m_l.outerIndexPtr(), m_l.innerIndexPtr(), m_l.valuePtr(),
00362 m_u.outerIndexPtr(), m_u.innerIndexPtr(), m_u.valuePtr(),
00363 m_p.data(), m_q.data(), 0, 0, 0, m_numeric);
00364
00365 m_extractedDataAreDirty = false;
00366 }
00367 }
00368
00369 template<typename MatrixType>
00370 typename UmfPackLU<MatrixType>::Scalar UmfPackLU<MatrixType>::determinant() const
00371 {
00372 Scalar det;
00373 umfpack_get_determinant(&det, 0, m_numeric, 0);
00374 return det;
00375 }
00376
00377 template<typename MatrixType>
00378 template<typename BDerived,typename XDerived>
00379 bool UmfPackLU<MatrixType>::_solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived> &x) const
00380 {
00381 const int rhsCols = b.cols();
00382 eigen_assert((BDerived::Flags&RowMajorBit)==0 && "UmfPackLU backend does not support non col-major rhs yet");
00383 eigen_assert((XDerived::Flags&RowMajorBit)==0 && "UmfPackLU backend does not support non col-major result yet");
00384 eigen_assert(b.derived().data() != x.derived().data() && " Umfpack does not support inplace solve");
00385
00386 int errorCode;
00387 for (int j=0; j<rhsCols; ++j)
00388 {
00389 errorCode = umfpack_solve(UMFPACK_A,
00390 m_outerIndexPtr, m_innerIndexPtr, m_valuePtr,
00391 &x.col(j).coeffRef(0), &b.const_cast_derived().col(j).coeffRef(0), m_numeric, 0, 0);
00392 if (errorCode!=0)
00393 return false;
00394 }
00395
00396 return true;
00397 }
00398
00399
00400 namespace internal {
00401
00402 template<typename _MatrixType, typename Rhs>
00403 struct solve_retval<UmfPackLU<_MatrixType>, Rhs>
00404 : solve_retval_base<UmfPackLU<_MatrixType>, Rhs>
00405 {
00406 typedef UmfPackLU<_MatrixType> Dec;
00407 EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
00408
00409 template<typename Dest> void evalTo(Dest& dst) const
00410 {
00411 dec()._solve(rhs(),dst);
00412 }
00413 };
00414
00415 template<typename _MatrixType, typename Rhs>
00416 struct sparse_solve_retval<UmfPackLU<_MatrixType>, Rhs>
00417 : sparse_solve_retval_base<UmfPackLU<_MatrixType>, Rhs>
00418 {
00419 typedef UmfPackLU<_MatrixType> Dec;
00420 EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
00421
00422 template<typename Dest> void evalTo(Dest& dst) const
00423 {
00424 this->defaultEvalTo(dst);
00425 }
00426 };
00427
00428 }
00429
00430 }
00431
00432 #endif // EIGEN_UMFPACKSUPPORT_H