1 files changed, 0 insertions, 432 deletions
diff --git a/third_party/eigen3/Eigen/src/UmfPackSupport/UmfPackSupport.h b/third_party/eigen3/Eigen/src/UmfPackSupport/UmfPackSupport.h
deleted file mode 100644
index 3a48cecf76..0000000000
--- a/third_party/eigen3/Eigen/src/UmfPackSupport/UmfPackSupport.h
+++ /dev/null
@@ -1,432 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_UMFPACKSUPPORT_H
-#define EIGEN_UMFPACKSUPPORT_H
-
-namespace Eigen { 
-
-/* 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); *Numeric = 0; }
-
-inline void umfpack_free_numeric(void **Numeric, std::complex<double>)
-{ umfpack_zi_free_numeric(Numeric); *Numeric = 0; }
-
-inline void umfpack_free_symbolic(void **Symbolic, double)
-{ umfpack_di_free_symbolic(Symbolic); *Symbolic = 0; }
-
-inline void umfpack_free_symbolic(void **Symbolic, std::complex<double>)
-{ umfpack_zi_free_symbolic(Symbolic); *Symbolic = 0; }
-
-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,&numext::real_ref(Ax[0]),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,&numext::real_ref(Ax[0]),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,&numext::real_ref(Ax[0]),0,&numext::real_ref(X[0]),0,&numext::real_ref(B[0]),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)
-{
-  double& lx0_real = numext::real_ref(Lx[0]);
-  double& ux0_real = numext::real_ref(Ux[0]);
-  double& dx0_real = numext::real_ref(Dx[0]);
-  return umfpack_zi_get_numeric(Lp,Lj,Lx?&lx0_real:0,0,Up,Ui,Ux?&ux0_real:0,0,P,Q,
-                                Dx?&dx0_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])
-{
-  double& mx_real = numext::real_ref(*Mx);
-  return umfpack_zi_get_determinant(&mx_real,0,Ex,NumericHandle,User_Info);
-}
-
-/** \ingroup UmfPackSupport_Module
-  * \brief A sparse LU factorization and solver based on UmfPack
-  *
-  * This class allows to solve for A.X = B sparse linear problems via a LU factorization
-  * using the UmfPack library. The sparse matrix A must be squared and full rank.
-  * The vectors or matrices X and B can be either dense or sparse.
-  *
-  * \warning The input matrix A should be in a \b compressed and \b column-major form.
-  * Otherwise an expensive copy will be made. You can call the inexpensive makeCompressed() to get a compressed matrix.
-  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
-  *
-  * \sa \ref TutorialSparseDirectSolvers
-  */
-template<typename _MatrixType>
-class UmfPackLU : internal::noncopyable
-{
-  public:
-    typedef _MatrixType MatrixType;
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
-    typedef Matrix<Scalar,Dynamic,1> Vector;
-    typedef Matrix<int, 1, MatrixType::ColsAtCompileTime> IntRowVectorType;
-    typedef Matrix<int, MatrixType::RowsAtCompileTime, 1> IntColVectorType;
-    typedef SparseMatrix<Scalar> LUMatrixType;
-    typedef SparseMatrix<Scalar,ColMajor,int> UmfpackMatrixType;
-
-  public:
-
-    UmfPackLU() { init(); }
-
-    UmfPackLU(const MatrixType& matrix)
-    {
-      init();
-      compute(matrix);
-    }
-
-    ~UmfPackLU()
-    {
-      if(m_symbolic) umfpack_free_symbolic(&m_symbolic,Scalar());
-      if(m_numeric)  umfpack_free_numeric(&m_numeric,Scalar());
-    }
-
-    inline Index rows() const { return m_copyMatrix.rows(); }
-    inline Index cols() const { return m_copyMatrix.cols(); }
-
-    /** \brief Reports whether previous computation was successful.
-      *
-      * \returns \c Success if computation was succesful,
-      *          \c NumericalIssue if the matrix.appears to be negative.
-      */
-    ComputationInfo info() const
-    {
-      eigen_assert(m_isInitialized && "Decomposition is not initialized.");
-      return m_info;
-    }
-
-    inline const LUMatrixType& matrixL() const
-    {
-      if (m_extractedDataAreDirty) extractData();
-      return m_l;
-    }
-
-    inline const LUMatrixType& 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;
-    }
-
-    /** Computes the sparse Cholesky decomposition of \a matrix 
-     *  Note that the matrix should be column-major, and in compressed format for best performance.
-     *  \sa SparseMatrix::makeCompressed().
-     */
-    void compute(const MatrixType& matrix)
-    {
-      analyzePattern(matrix);
-      factorize(matrix);
-    }
-
-    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * \sa compute()
-      */
-    template<typename Rhs>
-    inline const internal::solve_retval<UmfPackLU, Rhs> solve(const MatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "UmfPackLU is not initialized.");
-      eigen_assert(rows()==b.rows()
-                && "UmfPackLU::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::solve_retval<UmfPackLU, Rhs>(*this, b.derived());
-    }
-
-    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * \sa compute()
-      */
-    template<typename Rhs>
-    inline const internal::sparse_solve_retval<UmfPackLU, Rhs> solve(const SparseMatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "UmfPackLU is not initialized.");
-      eigen_assert(rows()==b.rows()
-                && "UmfPackLU::solve(): invalid number of rows of the right hand side matrix b");
-      return internal::sparse_solve_retval<UmfPackLU, Rhs>(*this, b.derived());
-    }
-
-    /** Performs a symbolic decomposition on the sparcity of \a matrix.
-      *
-      * This function is particularly useful when solving for several problems having the same structure.
-      *
-      * \sa factorize(), compute()
-      */
-    void analyzePattern(const MatrixType& matrix)
-    {
-      if(m_symbolic)
-        umfpack_free_symbolic(&m_symbolic,Scalar());
-      if(m_numeric)
-        umfpack_free_numeric(&m_numeric,Scalar());
-      
-      grapInput(matrix);
-
-      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;
-    }
-
-    /** Performs a numeric decomposition of \a matrix
-      *
-      * The given matrix must has the same sparcity than the matrix on which the pattern anylysis has been performed.
-      *
-      * \sa analyzePattern(), compute()
-      */
-    void factorize(const MatrixType& matrix)
-    {
-      eigen_assert(m_analysisIsOk && "UmfPackLU: you must first call analyzePattern()");
-      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;
-    }
-
-    #ifndef EIGEN_PARSED_BY_DOXYGEN
-    /** \internal */
-    template<typename BDerived,typename XDerived>
-    bool _solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived> &x) const;
-    #endif
-
-    Scalar determinant() const;
-
-    void extractData() const;
-
-  protected:
-
-
-    void init()
-    {
-      m_info = InvalidInput;
-      m_isInitialized = false;
-      m_numeric = 0;
-      m_symbolic = 0;
-      m_outerIndexPtr = 0;
-      m_innerIndexPtr = 0;
-      m_valuePtr      = 0;
-    }
-    
-    void grapInput(const MatrixType& mat)
-    {
-      m_copyMatrix.resize(mat.rows(), mat.cols());
-      if( ((MatrixType::Flags&RowMajorBit)==RowMajorBit) || sizeof(typename MatrixType::Index)!=sizeof(int) || !mat.isCompressed() )
-      {
-        // non supported input -> copy
-        m_copyMatrix = mat;
-        m_outerIndexPtr = m_copyMatrix.outerIndexPtr();
-        m_innerIndexPtr = m_copyMatrix.innerIndexPtr();
-        m_valuePtr      = m_copyMatrix.valuePtr();
-      }
-      else
-      {
-        m_outerIndexPtr = mat.outerIndexPtr();
-        m_innerIndexPtr = mat.innerIndexPtr();
-        m_valuePtr      = mat.valuePtr();
-      }
-    }
-
-    // cached data to reduce reallocation, etc.
-    mutable LUMatrixType m_l;
-    mutable LUMatrixType m_u;
-    mutable IntColVectorType m_p;
-    mutable IntRowVectorType m_q;
-
-    UmfpackMatrixType m_copyMatrix;
-    const Scalar* m_valuePtr;
-    const int* m_outerIndexPtr;
-    const int* m_innerIndexPtr;
-    void* m_numeric;
-    void* m_symbolic;
-
-    mutable ComputationInfo m_info;
-    bool m_isInitialized;
-    int m_factorizationIsOk;
-    int m_analysisIsOk;
-    mutable bool m_extractedDataAreDirty;
-    
-  private:
-    UmfPackLU(UmfPackLU& ) { }
-};
-
-
-template<typename MatrixType>
-void UmfPackLU<MatrixType>::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 UmfPackLU<MatrixType>::Scalar UmfPackLU<MatrixType>::determinant() const
-{
-  Scalar det;
-  umfpack_get_determinant(&det, 0, m_numeric, 0);
-  return det;
-}
-
-template<typename MatrixType>
-template<typename BDerived,typename XDerived>
-bool UmfPackLU<MatrixType>::_solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived> &x) const
-{
-  const int rhsCols = b.cols();
-  eigen_assert((BDerived::Flags&RowMajorBit)==0 && "UmfPackLU backend does not support non col-major rhs yet");
-  eigen_assert((XDerived::Flags&RowMajorBit)==0 && "UmfPackLU backend does not support non col-major result yet");
-  eigen_assert(b.derived().data() != x.derived().data() && " Umfpack does not support inplace solve");
-  
-  int errorCode;
-  for (int j=0; j<rhsCols; ++j)
-  {
-    errorCode = umfpack_solve(UMFPACK_A,
-        m_outerIndexPtr, m_innerIndexPtr, m_valuePtr,
-        &x.col(j).coeffRef(0), &b.const_cast_derived().col(j).coeffRef(0), m_numeric, 0, 0);
-    if (errorCode!=0)
-      return false;
-  }
-
-  return true;
-}
-
-
-namespace internal {
-
-template<typename _MatrixType, typename Rhs>
-struct solve_retval<UmfPackLU<_MatrixType>, Rhs>
-  : solve_retval_base<UmfPackLU<_MatrixType>, Rhs>
-{
-  typedef UmfPackLU<_MatrixType> Dec;
-  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    dec()._solve(rhs(),dst);
-  }
-};
-
-template<typename _MatrixType, typename Rhs>
-struct sparse_solve_retval<UmfPackLU<_MatrixType>, Rhs>
-  : sparse_solve_retval_base<UmfPackLU<_MatrixType>, Rhs>
-{
-  typedef UmfPackLU<_MatrixType> Dec;
-  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
-
-  template<typename Dest> void evalTo(Dest& dst) const
-  {
-    this->defaultEvalTo(dst);
-  }
-};
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_UMFPACKSUPPORT_H