CompleteOrthogonalDecomposition.h

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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2016 Rasmus Munk Larsen <rmlarsen@google.com>
//
// 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_COMPLETEORTHOGONALDECOMPOSITION_H
#define EIGEN_COMPLETEORTHOGONALDECOMPOSITION_H
 
#include "./InternalHeaderCheck.h"
 
namespace Eigen {
 
namespace internal {
template <typename MatrixType_, typename PermutationIndex_>
struct traits<CompleteOrthogonalDecomposition<MatrixType_, PermutationIndex_> >
    : traits<MatrixType_> {
  typedef MatrixXpr XprKind;
  typedef SolverStorage StorageKind;
  typedef PermutationIndex_ PermutationIndex;
  enum { Flags = 0 };
};
 
}  // end namespace internal
 
template <typename MatrixType_, typename PermutationIndex_> class CompleteOrthogonalDecomposition
          : public SolverBase<CompleteOrthogonalDecomposition<MatrixType_, PermutationIndex_> >
{
 public:
  typedef MatrixType_ MatrixType;
  typedef SolverBase<CompleteOrthogonalDecomposition> Base;
 
  template<typename Derived>
  friend struct internal::solve_assertion;
  typedef PermutationIndex_ PermutationIndex;
  EIGEN_GENERIC_PUBLIC_INTERFACE(CompleteOrthogonalDecomposition)
  enum {
    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
  };
  typedef typename internal::plain_diag_type<MatrixType>::type HCoeffsType;
  typedef PermutationMatrix<ColsAtCompileTime, MaxColsAtCompileTime, PermutationIndex>
      PermutationType;
  typedef typename internal::plain_row_type<MatrixType, Index>::type
      IntRowVectorType;
  typedef typename internal::plain_row_type<MatrixType>::type RowVectorType;
  typedef typename internal::plain_row_type<MatrixType, RealScalar>::type
      RealRowVectorType;
  typedef HouseholderSequence<
      MatrixType, internal::remove_all_t<
                      typename HCoeffsType::ConjugateReturnType>>
      HouseholderSequenceType;
  typedef typename MatrixType::PlainObject PlainObject;
 
 public:
  CompleteOrthogonalDecomposition() : m_cpqr(), m_zCoeffs(), m_temp() {}
 
  CompleteOrthogonalDecomposition(Index rows, Index cols)
      : m_cpqr(rows, cols), m_zCoeffs((std::min)(rows, cols)), m_temp(cols) {}
 
  template <typename InputType>
  explicit CompleteOrthogonalDecomposition(const EigenBase<InputType>& matrix)
      : m_cpqr(matrix.rows(), matrix.cols()),
        m_zCoeffs((std::min)(matrix.rows(), matrix.cols())),
        m_temp(matrix.cols())
  {
    compute(matrix.derived());
  }
 
  template<typename InputType>
  explicit CompleteOrthogonalDecomposition(EigenBase<InputType>& matrix)
    : m_cpqr(matrix.derived()),
      m_zCoeffs((std::min)(matrix.rows(), matrix.cols())),
      m_temp(matrix.cols())
  {
    computeInPlace();
  } 
 
  #ifdef EIGEN_PARSED_BY_DOXYGEN
  template <typename Rhs>
  inline const Solve<CompleteOrthogonalDecomposition, Rhs> solve(
      const MatrixBase<Rhs>& b) const;
  #endif
 
  HouseholderSequenceType householderQ(void) const;
  HouseholderSequenceType matrixQ(void) const { return m_cpqr.householderQ(); }
 
  MatrixType matrixZ() const {
    MatrixType Z = MatrixType::Identity(m_cpqr.cols(), m_cpqr.cols());
    applyZOnTheLeftInPlace<false>(Z);
    return Z;
  }
 
  const MatrixType& matrixQTZ() const { return m_cpqr.matrixQR(); }
 
  const MatrixType& matrixT() const { return m_cpqr.matrixQR(); }
 
  template <typename InputType>
  CompleteOrthogonalDecomposition& compute(const EigenBase<InputType>& matrix) {
    // Compute the column pivoted QR factorization A P = Q R.
    m_cpqr.compute(matrix);
    computeInPlace();
    return *this;
  }
 
  const PermutationType& colsPermutation() const {
    return m_cpqr.colsPermutation();
  }
 
  typename MatrixType::Scalar determinant() const;
 
  typename MatrixType::RealScalar absDeterminant() const;
 
  typename MatrixType::RealScalar logAbsDeterminant() const;
 
  inline Index rank() const { return m_cpqr.rank(); }
 
  inline Index dimensionOfKernel() const { return m_cpqr.dimensionOfKernel(); }
 
  inline bool isInjective() const { return m_cpqr.isInjective(); }
 
  inline bool isSurjective() const { return m_cpqr.isSurjective(); }
 
  inline bool isInvertible() const { return m_cpqr.isInvertible(); }
 
  inline const Inverse<CompleteOrthogonalDecomposition> pseudoInverse() const
  {
    eigen_assert(m_cpqr.m_isInitialized && "CompleteOrthogonalDecomposition is not initialized.");
    return Inverse<CompleteOrthogonalDecomposition>(*this);
  }
 
  inline Index rows() const { return m_cpqr.rows(); }
  inline Index cols() const { return m_cpqr.cols(); }
 
  inline const HCoeffsType& hCoeffs() const { return m_cpqr.hCoeffs(); }
 
  const HCoeffsType& zCoeffs() const { return m_zCoeffs; }
 
  CompleteOrthogonalDecomposition& setThreshold(const RealScalar& threshold) {
    m_cpqr.setThreshold(threshold);
    return *this;
  }
 
  CompleteOrthogonalDecomposition& setThreshold(Default_t) {
    m_cpqr.setThreshold(Default);
    return *this;
  }
 
  RealScalar threshold() const { return m_cpqr.threshold(); }
 
  inline Index nonzeroPivots() const { return m_cpqr.nonzeroPivots(); }
 
  inline RealScalar maxPivot() const { return m_cpqr.maxPivot(); }
 
  ComputationInfo info() const {
    eigen_assert(m_cpqr.m_isInitialized && "Decomposition is not initialized.");
    return Success;
  }
 
#ifndef EIGEN_PARSED_BY_DOXYGEN
  template <typename RhsType, typename DstType>
  void _solve_impl(const RhsType& rhs, DstType& dst) const;
 
  template<bool Conjugate, typename RhsType, typename DstType>
  void _solve_impl_transposed(const RhsType &rhs, DstType &dst) const;
#endif
 
 protected:
  EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
 
  template<bool Transpose_, typename Rhs>
  void _check_solve_assertion(const Rhs& b) const {
      EIGEN_ONLY_USED_FOR_DEBUG(b);
      eigen_assert(m_cpqr.m_isInitialized && "CompleteOrthogonalDecomposition is not initialized.");
      eigen_assert((Transpose_?derived().cols():derived().rows())==b.rows() && "CompleteOrthogonalDecomposition::solve(): invalid number of rows of the right hand side matrix b");
  }
 
  void computeInPlace();
 
  template <bool Conjugate, typename Rhs>
  void applyZOnTheLeftInPlace(Rhs& rhs) const;
 
  template <typename Rhs>
  void applyZAdjointOnTheLeftInPlace(Rhs& rhs) const;
 
  ColPivHouseholderQR<MatrixType, PermutationIndex> m_cpqr;
  HCoeffsType m_zCoeffs;
  RowVectorType m_temp;
};
 
template <typename MatrixType, typename PermutationIndex>
typename MatrixType::Scalar
CompleteOrthogonalDecomposition<MatrixType, PermutationIndex>::determinant() const {
  return m_cpqr.determinant();
}
 
template <typename MatrixType, typename PermutationIndex>
typename MatrixType::RealScalar
CompleteOrthogonalDecomposition<MatrixType, PermutationIndex>::absDeterminant() const {
  return m_cpqr.absDeterminant();
}
 
template <typename MatrixType, typename PermutationIndex>
typename MatrixType::RealScalar
CompleteOrthogonalDecomposition<MatrixType, PermutationIndex>::logAbsDeterminant() const {
  return m_cpqr.logAbsDeterminant();
}
 
template <typename MatrixType, typename PermutationIndex>
void CompleteOrthogonalDecomposition<MatrixType, PermutationIndex>::computeInPlace()
{
  eigen_assert(m_cpqr.cols() <= NumTraits<PermutationIndex>::highest());
 
  const Index rank = m_cpqr.rank();
  const Index cols = m_cpqr.cols();
  const Index rows = m_cpqr.rows();
  m_zCoeffs.resize((std::min)(rows, cols));
  m_temp.resize(cols);
 
  if (rank < cols) {
    // We have reduced the (permuted) matrix to the form
    //   [R11 R12]
    //   [ 0  R22]
    // where R11 is r-by-r (r = rank) upper triangular, R12 is
    // r-by-(n-r), and R22 is empty or the norm of R22 is negligible.
    // We now compute the complete orthogonal decomposition by applying
    // Householder transformations from the right to the upper trapezoidal
    // matrix X = [R11 R12] to zero out R12 and obtain the factorization
    // [R11 R12] = [T11 0] * Z, where T11 is r-by-r upper triangular and
    // Z = Z(0) * Z(1) ... Z(r-1) is an n-by-n orthogonal matrix.
    // We store the data representing Z in R12 and m_zCoeffs.
    for (Index k = rank - 1; k >= 0; --k) {
      if (k != rank - 1) {
        // Given the API for Householder reflectors, it is more convenient if
        // we swap the leading parts of columns k and r-1 (zero-based) to form
        // the matrix X_k = [X(0:k, k), X(0:k, r:n)]
        m_cpqr.m_qr.col(k).head(k + 1).swap(
            m_cpqr.m_qr.col(rank - 1).head(k + 1));
      }
      // Construct Householder reflector Z(k) to zero out the last row of X_k,
      // i.e. choose Z(k) such that
      // [X(k, k), X(k, r:n)] * Z(k) = [beta, 0, .., 0].
      RealScalar beta;
      m_cpqr.m_qr.row(k)
          .tail(cols - rank + 1)
          .makeHouseholderInPlace(m_zCoeffs(k), beta);
      m_cpqr.m_qr(k, rank - 1) = beta;
      if (k > 0) {
        // Apply Z(k) to the first k rows of X_k
        m_cpqr.m_qr.topRightCorner(k, cols - rank + 1)
            .applyHouseholderOnTheRight(
                m_cpqr.m_qr.row(k).tail(cols - rank).adjoint(), m_zCoeffs(k),
                &m_temp(0));
      }
      if (k != rank - 1) {
        // Swap X(0:k,k) back to its proper location.
        m_cpqr.m_qr.col(k).head(k + 1).swap(
            m_cpqr.m_qr.col(rank - 1).head(k + 1));
      }
    }
  }
}
 
template <typename MatrixType, typename PermutationIndex>
template <bool Conjugate, typename Rhs>
void CompleteOrthogonalDecomposition<MatrixType, PermutationIndex>::applyZOnTheLeftInPlace(
    Rhs& rhs) const {
  const Index cols = this->cols();
  const Index nrhs = rhs.cols();
  const Index rank = this->rank();
  Matrix<typename Rhs::Scalar, Dynamic, 1> temp((std::max)(cols, nrhs));
  for (Index k = rank-1; k >= 0; --k) {
    if (k != rank - 1) {
      rhs.row(k).swap(rhs.row(rank - 1));
    }
    rhs.middleRows(rank - 1, cols - rank + 1)
        .applyHouseholderOnTheLeft(
            matrixQTZ().row(k).tail(cols - rank).transpose().template conjugateIf<!Conjugate>(), zCoeffs().template conjugateIf<Conjugate>()(k),
            &temp(0));
    if (k != rank - 1) {
      rhs.row(k).swap(rhs.row(rank - 1));
    }
  }
}
 
template <typename MatrixType, typename PermutationIndex>
template <typename Rhs>
void CompleteOrthogonalDecomposition<MatrixType, PermutationIndex>::applyZAdjointOnTheLeftInPlace(
    Rhs& rhs) const {
  const Index cols = this->cols();
  const Index nrhs = rhs.cols();
  const Index rank = this->rank();
  Matrix<typename Rhs::Scalar, Dynamic, 1> temp((std::max)(cols, nrhs));
  for (Index k = 0; k < rank; ++k) {
    if (k != rank - 1) {
      rhs.row(k).swap(rhs.row(rank - 1));
    }
    rhs.middleRows(rank - 1, cols - rank + 1)
        .applyHouseholderOnTheLeft(
            matrixQTZ().row(k).tail(cols - rank).adjoint(), zCoeffs()(k),
            &temp(0));
    if (k != rank - 1) {
      rhs.row(k).swap(rhs.row(rank - 1));
    }
  }
}
 
#ifndef EIGEN_PARSED_BY_DOXYGEN
template <typename MatrixType_, typename PermutationIndex_>
template <typename RhsType, typename DstType>
void CompleteOrthogonalDecomposition<MatrixType_, PermutationIndex_>::_solve_impl(
    const RhsType& rhs, DstType& dst) const {
  const Index rank = this->rank();
  if (rank == 0) {
    dst.setZero();
    return;
  }
 
  // Compute c = Q^* * rhs
  typename RhsType::PlainObject c(rhs);
  c.applyOnTheLeft(matrixQ().setLength(rank).adjoint());
 
  // Solve T z = c(1:rank, :)
  dst.topRows(rank) = matrixT()
                          .topLeftCorner(rank, rank)
                          .template triangularView<Upper>()
                          .solve(c.topRows(rank));
 
  const Index cols = this->cols();
  if (rank < cols) {
    // Compute y = Z^* * [ z ]
    //                   [ 0 ]
    dst.bottomRows(cols - rank).setZero();
    applyZAdjointOnTheLeftInPlace(dst);
  }
 
  // Undo permutation to get x = P^{-1} * y.
  dst = colsPermutation() * dst;
}
 
template<typename MatrixType_, typename PermutationIndex_>
template<bool Conjugate, typename RhsType, typename DstType>
void CompleteOrthogonalDecomposition<MatrixType_, PermutationIndex_>::_solve_impl_transposed(const RhsType &rhs, DstType &dst) const
{
  const Index rank = this->rank();
 
  if (rank == 0) {
    dst.setZero();
    return;
  }
 
  typename RhsType::PlainObject c(colsPermutation().transpose()*rhs);
 
  if (rank < cols()) {
    applyZOnTheLeftInPlace<!Conjugate>(c);
  }
 
  matrixT().topLeftCorner(rank, rank)
           .template triangularView<Upper>()
           .transpose().template conjugateIf<Conjugate>()
           .solveInPlace(c.topRows(rank));
 
  dst.topRows(rank) = c.topRows(rank);
  dst.bottomRows(rows()-rank).setZero();
 
  dst.applyOnTheLeft(householderQ().setLength(rank).template conjugateIf<!Conjugate>() );
}
#endif
 
namespace internal {
 
template<typename MatrixType, typename PermutationIndex>
struct traits<Inverse<CompleteOrthogonalDecomposition<MatrixType, PermutationIndex> > >
  : traits<typename Transpose<typename MatrixType::PlainObject>::PlainObject>
{
  enum { Flags = 0 };
};
 
template<typename DstXprType, typename MatrixType, typename PermutationIndex>
struct Assignment<DstXprType, Inverse<CompleteOrthogonalDecomposition<MatrixType, PermutationIndex> >, internal::assign_op<typename DstXprType::Scalar,typename CompleteOrthogonalDecomposition<MatrixType, PermutationIndex>::Scalar>, Dense2Dense>
{
  typedef CompleteOrthogonalDecomposition<MatrixType, PermutationIndex> CodType;
  typedef Inverse<CodType> SrcXprType;
  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename CodType::Scalar> &)
  {
    typedef Matrix<typename CodType::Scalar, CodType::RowsAtCompileTime, CodType::RowsAtCompileTime, 0, CodType::MaxRowsAtCompileTime, CodType::MaxRowsAtCompileTime> IdentityMatrixType;
    dst = src.nestedExpression().solve(IdentityMatrixType::Identity(src.cols(), src.cols()));
  }
};
 
} // end namespace internal
 
template <typename MatrixType, typename PermutationIndex>
typename CompleteOrthogonalDecomposition<MatrixType, PermutationIndex>::HouseholderSequenceType
CompleteOrthogonalDecomposition<MatrixType, PermutationIndex>::householderQ() const {
  return m_cpqr.householderQ();
}
 
template <typename Derived>
template <typename PermutationIndex>
const CompleteOrthogonalDecomposition<typename MatrixBase<Derived>::PlainObject, PermutationIndex>
MatrixBase<Derived>::completeOrthogonalDecomposition() const {
  return CompleteOrthogonalDecomposition<PlainObject>(eval());
}
 
}  // end namespace Eigen
 
#endif  // EIGEN_COMPLETEORTHOGONALDECOMPOSITION_H