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Diffstat (limited to 'eigen/unsupported/Eigen/src/MatrixFunctions/MatrixPower.h')
| -rw-r--r-- | eigen/unsupported/Eigen/src/MatrixFunctions/MatrixPower.h | 508 |
1 files changed, 508 insertions, 0 deletions
diff --git a/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixPower.h b/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixPower.h new file mode 100644 index 0000000..78a307e --- /dev/null +++ b/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixPower.h @@ -0,0 +1,508 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2012, 2013 Chen-Pang He <jdh8@ms63.hinet.net> +// +// 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_MATRIX_POWER +#define EIGEN_MATRIX_POWER + +namespace Eigen { + +template<typename MatrixType> class MatrixPower; + +template<typename MatrixType> +class MatrixPowerRetval : public ReturnByValue< MatrixPowerRetval<MatrixType> > +{ + public: + typedef typename MatrixType::RealScalar RealScalar; + typedef typename MatrixType::Index Index; + + MatrixPowerRetval(MatrixPower<MatrixType>& pow, RealScalar p) : m_pow(pow), m_p(p) + { } + + template<typename ResultType> + inline void evalTo(ResultType& res) const + { m_pow.compute(res, m_p); } + + Index rows() const { return m_pow.rows(); } + Index cols() const { return m_pow.cols(); } + + private: + MatrixPower<MatrixType>& m_pow; + const RealScalar m_p; + MatrixPowerRetval& operator=(const MatrixPowerRetval&); +}; + +template<typename MatrixType> +class MatrixPowerAtomic +{ + private: + enum { + RowsAtCompileTime = MatrixType::RowsAtCompileTime, + MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime + }; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef std::complex<RealScalar> ComplexScalar; + typedef typename MatrixType::Index Index; + typedef Array<Scalar, RowsAtCompileTime, 1, ColMajor, MaxRowsAtCompileTime> ArrayType; + + const MatrixType& m_A; + RealScalar m_p; + + void computePade(int degree, const MatrixType& IminusT, MatrixType& res) const; + void compute2x2(MatrixType& res, RealScalar p) const; + void computeBig(MatrixType& res) const; + static int getPadeDegree(float normIminusT); + static int getPadeDegree(double normIminusT); + static int getPadeDegree(long double normIminusT); + static ComplexScalar computeSuperDiag(const ComplexScalar&, const ComplexScalar&, RealScalar p); + static RealScalar computeSuperDiag(RealScalar, RealScalar, RealScalar p); + + public: + MatrixPowerAtomic(const MatrixType& T, RealScalar p); + void compute(MatrixType& res) const; +}; + +template<typename MatrixType> +MatrixPowerAtomic<MatrixType>::MatrixPowerAtomic(const MatrixType& T, RealScalar p) : + m_A(T), m_p(p) +{ eigen_assert(T.rows() == T.cols()); } + +template<typename MatrixType> +void MatrixPowerAtomic<MatrixType>::compute(MatrixType& res) const +{ + res.resizeLike(m_A); + switch (m_A.rows()) { + case 0: + break; + case 1: + res(0,0) = std::pow(m_A(0,0), m_p); + break; + case 2: + compute2x2(res, m_p); + break; + default: + computeBig(res); + } +} + +template<typename MatrixType> +void MatrixPowerAtomic<MatrixType>::computePade(int degree, const MatrixType& IminusT, MatrixType& res) const +{ + int i = degree<<1; + res = (m_p-degree) / ((i-1)<<1) * IminusT; + for (--i; i; --i) { + res = (MatrixType::Identity(IminusT.rows(), IminusT.cols()) + res).template triangularView<Upper>() + .solve((i==1 ? -m_p : i&1 ? (-m_p-(i>>1))/(i<<1) : (m_p-(i>>1))/((i-1)<<1)) * IminusT).eval(); + } + res += MatrixType::Identity(IminusT.rows(), IminusT.cols()); +} + +// This function assumes that res has the correct size (see bug 614) +template<typename MatrixType> +void MatrixPowerAtomic<MatrixType>::compute2x2(MatrixType& res, RealScalar p) const +{ + using std::abs; + using std::pow; + + res.coeffRef(0,0) = pow(m_A.coeff(0,0), p); + + for (Index i=1; i < m_A.cols(); ++i) { + res.coeffRef(i,i) = pow(m_A.coeff(i,i), p); + if (m_A.coeff(i-1,i-1) == m_A.coeff(i,i)) + res.coeffRef(i-1,i) = p * pow(m_A.coeff(i,i), p-1); + else if (2*abs(m_A.coeff(i-1,i-1)) < abs(m_A.coeff(i,i)) || 2*abs(m_A.coeff(i,i)) < abs(m_A.coeff(i-1,i-1))) + res.coeffRef(i-1,i) = (res.coeff(i,i)-res.coeff(i-1,i-1)) / (m_A.coeff(i,i)-m_A.coeff(i-1,i-1)); + else + res.coeffRef(i-1,i) = computeSuperDiag(m_A.coeff(i,i), m_A.coeff(i-1,i-1), p); + res.coeffRef(i-1,i) *= m_A.coeff(i-1,i); + } +} + +template<typename MatrixType> +void MatrixPowerAtomic<MatrixType>::computeBig(MatrixType& res) const +{ + const int digits = std::numeric_limits<RealScalar>::digits; + const RealScalar maxNormForPade = digits <= 24? 4.3386528e-1f: // sigle precision + digits <= 53? 2.789358995219730e-1: // double precision + digits <= 64? 2.4471944416607995472e-1L: // extended precision + digits <= 106? 1.1016843812851143391275867258512e-1L: // double-double + 9.134603732914548552537150753385375e-2L; // quadruple precision + MatrixType IminusT, sqrtT, T = m_A.template triangularView<Upper>(); + RealScalar normIminusT; + int degree, degree2, numberOfSquareRoots = 0; + bool hasExtraSquareRoot = false; + + /* FIXME + * For singular T, norm(I - T) >= 1 but maxNormForPade < 1, leads to infinite + * loop. We should move 0 eigenvalues to bottom right corner. We need not + * worry about tiny values (e.g. 1e-300) because they will reach 1 if + * repetitively sqrt'ed. + * + * If the 0 eigenvalues are semisimple, they can form a 0 matrix at the + * bottom right corner. + * + * [ T A ]^p [ T^p (T^-1 T^p A) ] + * [ ] = [ ] + * [ 0 0 ] [ 0 0 ] + */ + for (Index i=0; i < m_A.cols(); ++i) + eigen_assert(m_A(i,i) != RealScalar(0)); + + while (true) { + IminusT = MatrixType::Identity(m_A.rows(), m_A.cols()) - T; + normIminusT = IminusT.cwiseAbs().colwise().sum().maxCoeff(); + if (normIminusT < maxNormForPade) { + degree = getPadeDegree(normIminusT); + degree2 = getPadeDegree(normIminusT/2); + if (degree - degree2 <= 1 || hasExtraSquareRoot) + break; + hasExtraSquareRoot = true; + } + MatrixSquareRootTriangular<MatrixType>(T).compute(sqrtT); + T = sqrtT.template triangularView<Upper>(); + ++numberOfSquareRoots; + } + computePade(degree, IminusT, res); + + for (; numberOfSquareRoots; --numberOfSquareRoots) { + compute2x2(res, std::ldexp(m_p, -numberOfSquareRoots)); + res = res.template triangularView<Upper>() * res; + } + compute2x2(res, m_p); +} + +template<typename MatrixType> +inline int MatrixPowerAtomic<MatrixType>::getPadeDegree(float normIminusT) +{ + const float maxNormForPade[] = { 2.8064004e-1f /* degree = 3 */ , 4.3386528e-1f }; + int degree = 3; + for (; degree <= 4; ++degree) + if (normIminusT <= maxNormForPade[degree - 3]) + break; + return degree; +} + +template<typename MatrixType> +inline int MatrixPowerAtomic<MatrixType>::getPadeDegree(double normIminusT) +{ + const double maxNormForPade[] = { 1.884160592658218e-2 /* degree = 3 */ , 6.038881904059573e-2, 1.239917516308172e-1, + 1.999045567181744e-1, 2.789358995219730e-1 }; + int degree = 3; + for (; degree <= 7; ++degree) + if (normIminusT <= maxNormForPade[degree - 3]) + break; + return degree; +} + +template<typename MatrixType> +inline int MatrixPowerAtomic<MatrixType>::getPadeDegree(long double normIminusT) +{ +#if LDBL_MANT_DIG == 53 + const int maxPadeDegree = 7; + const double maxNormForPade[] = { 1.884160592658218e-2L /* degree = 3 */ , 6.038881904059573e-2L, 1.239917516308172e-1L, + 1.999045567181744e-1L, 2.789358995219730e-1L }; +#elif LDBL_MANT_DIG <= 64 + const int maxPadeDegree = 8; + const double maxNormForPade[] = { 6.3854693117491799460e-3L /* degree = 3 */ , 2.6394893435456973676e-2L, + 6.4216043030404063729e-2L, 1.1701165502926694307e-1L, 1.7904284231268670284e-1L, 2.4471944416607995472e-1L }; +#elif LDBL_MANT_DIG <= 106 + const int maxPadeDegree = 10; + const double maxNormForPade[] = { 1.0007161601787493236741409687186e-4L /* degree = 3 */ , + 1.0007161601787493236741409687186e-3L, 4.7069769360887572939882574746264e-3L, 1.3220386624169159689406653101695e-2L, + 2.8063482381631737920612944054906e-2L, 4.9625993951953473052385361085058e-2L, 7.7367040706027886224557538328171e-2L, + 1.1016843812851143391275867258512e-1L }; +#else + const int maxPadeDegree = 10; + const double maxNormForPade[] = { 5.524506147036624377378713555116378e-5L /* degree = 3 */ , + 6.640600568157479679823602193345995e-4L, 3.227716520106894279249709728084626e-3L, + 9.619593944683432960546978734646284e-3L, 2.134595382433742403911124458161147e-2L, + 3.908166513900489428442993794761185e-2L, 6.266780814639442865832535460550138e-2L, + 9.134603732914548552537150753385375e-2L }; +#endif + int degree = 3; + for (; degree <= maxPadeDegree; ++degree) + if (normIminusT <= maxNormForPade[degree - 3]) + break; + return degree; +} + +template<typename MatrixType> +inline typename MatrixPowerAtomic<MatrixType>::ComplexScalar +MatrixPowerAtomic<MatrixType>::computeSuperDiag(const ComplexScalar& curr, const ComplexScalar& prev, RealScalar p) +{ + ComplexScalar logCurr = std::log(curr); + ComplexScalar logPrev = std::log(prev); + int unwindingNumber = std::ceil((numext::imag(logCurr - logPrev) - M_PI) / (2*M_PI)); + ComplexScalar w = numext::atanh2(curr - prev, curr + prev) + ComplexScalar(0, M_PI*unwindingNumber); + return RealScalar(2) * std::exp(RealScalar(0.5) * p * (logCurr + logPrev)) * std::sinh(p * w) / (curr - prev); +} + +template<typename MatrixType> +inline typename MatrixPowerAtomic<MatrixType>::RealScalar +MatrixPowerAtomic<MatrixType>::computeSuperDiag(RealScalar curr, RealScalar prev, RealScalar p) +{ + RealScalar w = numext::atanh2(curr - prev, curr + prev); + return 2 * std::exp(p * (std::log(curr) + std::log(prev)) / 2) * std::sinh(p * w) / (curr - prev); +} + +/** + * \ingroup MatrixFunctions_Module + * + * \brief Class for computing matrix powers. + * + * \tparam MatrixType type of the base, expected to be an instantiation + * of the Matrix class template. + * + * This class is capable of computing real/complex matrices raised to + * an arbitrary real power. Meanwhile, it saves the result of Schur + * decomposition if an non-integral power has even been calculated. + * Therefore, if you want to compute multiple (>= 2) matrix powers + * for the same matrix, using the class directly is more efficient than + * calling MatrixBase::pow(). + * + * Example: + * \include MatrixPower_optimal.cpp + * Output: \verbinclude MatrixPower_optimal.out + */ +template<typename MatrixType> +class MatrixPower +{ + private: + enum { + RowsAtCompileTime = MatrixType::RowsAtCompileTime, + ColsAtCompileTime = MatrixType::ColsAtCompileTime, + MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, + MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime + }; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef typename MatrixType::Index Index; + + public: + /** + * \brief Constructor. + * + * \param[in] A the base of the matrix power. + * + * The class stores a reference to A, so it should not be changed + * (or destroyed) before evaluation. + */ + explicit MatrixPower(const MatrixType& A) : m_A(A), m_conditionNumber(0) + { eigen_assert(A.rows() == A.cols()); } + + /** + * \brief Returns the matrix power. + * + * \param[in] p exponent, a real scalar. + * \return The expression \f$ A^p \f$, where A is specified in the + * constructor. + */ + const MatrixPowerRetval<MatrixType> operator()(RealScalar p) + { return MatrixPowerRetval<MatrixType>(*this, p); } + + /** + * \brief Compute the matrix power. + * + * \param[in] p exponent, a real scalar. + * \param[out] res \f$ A^p \f$ where A is specified in the + * constructor. + */ + template<typename ResultType> + void compute(ResultType& res, RealScalar p); + + Index rows() const { return m_A.rows(); } + Index cols() const { return m_A.cols(); } + + private: + typedef std::complex<RealScalar> ComplexScalar; + typedef Matrix<ComplexScalar, RowsAtCompileTime, ColsAtCompileTime, MatrixType::Options, + MaxRowsAtCompileTime, MaxColsAtCompileTime> ComplexMatrix; + + typename MatrixType::Nested m_A; + MatrixType m_tmp; + ComplexMatrix m_T, m_U, m_fT; + RealScalar m_conditionNumber; + + RealScalar modfAndInit(RealScalar, RealScalar*); + + template<typename ResultType> + void computeIntPower(ResultType&, RealScalar); + + template<typename ResultType> + void computeFracPower(ResultType&, RealScalar); + + template<int Rows, int Cols, int Options, int MaxRows, int MaxCols> + static void revertSchur( + Matrix<ComplexScalar, Rows, Cols, Options, MaxRows, MaxCols>& res, + const ComplexMatrix& T, + const ComplexMatrix& U); + + template<int Rows, int Cols, int Options, int MaxRows, int MaxCols> + static void revertSchur( + Matrix<RealScalar, Rows, Cols, Options, MaxRows, MaxCols>& res, + const ComplexMatrix& T, + const ComplexMatrix& U); +}; + +template<typename MatrixType> +template<typename ResultType> +void MatrixPower<MatrixType>::compute(ResultType& res, RealScalar p) +{ + switch (cols()) { + case 0: + break; + case 1: + res(0,0) = std::pow(m_A.coeff(0,0), p); + break; + default: + RealScalar intpart, x = modfAndInit(p, &intpart); + computeIntPower(res, intpart); + computeFracPower(res, x); + } +} + +template<typename MatrixType> +typename MatrixPower<MatrixType>::RealScalar +MatrixPower<MatrixType>::modfAndInit(RealScalar x, RealScalar* intpart) +{ + typedef Array<RealScalar, RowsAtCompileTime, 1, ColMajor, MaxRowsAtCompileTime> RealArray; + + *intpart = std::floor(x); + RealScalar res = x - *intpart; + + if (!m_conditionNumber && res) { + const ComplexSchur<MatrixType> schurOfA(m_A); + m_T = schurOfA.matrixT(); + m_U = schurOfA.matrixU(); + + const RealArray absTdiag = m_T.diagonal().array().abs(); + m_conditionNumber = absTdiag.maxCoeff() / absTdiag.minCoeff(); + } + + if (res>RealScalar(0.5) && res>(1-res)*std::pow(m_conditionNumber, res)) { + --res; + ++*intpart; + } + return res; +} + +template<typename MatrixType> +template<typename ResultType> +void MatrixPower<MatrixType>::computeIntPower(ResultType& res, RealScalar p) +{ + RealScalar pp = std::abs(p); + + if (p<0) m_tmp = m_A.inverse(); + else m_tmp = m_A; + + res = MatrixType::Identity(rows(), cols()); + while (pp >= 1) { + if (std::fmod(pp, 2) >= 1) + res = m_tmp * res; + m_tmp *= m_tmp; + pp /= 2; + } +} + +template<typename MatrixType> +template<typename ResultType> +void MatrixPower<MatrixType>::computeFracPower(ResultType& res, RealScalar p) +{ + if (p) { + eigen_assert(m_conditionNumber); + MatrixPowerAtomic<ComplexMatrix>(m_T, p).compute(m_fT); + revertSchur(m_tmp, m_fT, m_U); + res = m_tmp * res; + } +} + +template<typename MatrixType> +template<int Rows, int Cols, int Options, int MaxRows, int MaxCols> +inline void MatrixPower<MatrixType>::revertSchur( + Matrix<ComplexScalar, Rows, Cols, Options, MaxRows, MaxCols>& res, + const ComplexMatrix& T, + const ComplexMatrix& U) +{ res.noalias() = U * (T.template triangularView<Upper>() * U.adjoint()); } + +template<typename MatrixType> +template<int Rows, int Cols, int Options, int MaxRows, int MaxCols> +inline void MatrixPower<MatrixType>::revertSchur( + Matrix<RealScalar, Rows, Cols, Options, MaxRows, MaxCols>& res, + const ComplexMatrix& T, + const ComplexMatrix& U) +{ res.noalias() = (U * (T.template triangularView<Upper>() * U.adjoint())).real(); } + +/** + * \ingroup MatrixFunctions_Module + * + * \brief Proxy for the matrix power of some matrix (expression). + * + * \tparam Derived type of the base, a matrix (expression). + * + * This class holds the arguments to the matrix power until it is + * assigned or evaluated for some other reason (so the argument + * should not be changed in the meantime). It is the return type of + * MatrixBase::pow() and related functions and most of the + * time this is the only way it is used. + */ +template<typename Derived> +class MatrixPowerReturnValue : public ReturnByValue< MatrixPowerReturnValue<Derived> > +{ + public: + typedef typename Derived::PlainObject PlainObject; + typedef typename Derived::RealScalar RealScalar; + typedef typename Derived::Index Index; + + /** + * \brief Constructor. + * + * \param[in] A %Matrix (expression), the base of the matrix power. + * \param[in] p scalar, the exponent of the matrix power. + */ + MatrixPowerReturnValue(const Derived& A, RealScalar p) : m_A(A), m_p(p) + { } + + /** + * \brief Compute the matrix power. + * + * \param[out] result \f$ A^p \f$ where \p A and \p p are as in the + * constructor. + */ + template<typename ResultType> + inline void evalTo(ResultType& res) const + { MatrixPower<PlainObject>(m_A.eval()).compute(res, m_p); } + + Index rows() const { return m_A.rows(); } + Index cols() const { return m_A.cols(); } + + private: + const Derived& m_A; + const RealScalar m_p; + MatrixPowerReturnValue& operator=(const MatrixPowerReturnValue&); +}; + +namespace internal { + +template<typename MatrixPowerType> +struct traits< MatrixPowerRetval<MatrixPowerType> > +{ typedef typename MatrixPowerType::PlainObject ReturnType; }; + +template<typename Derived> +struct traits< MatrixPowerReturnValue<Derived> > +{ typedef typename Derived::PlainObject ReturnType; }; + +} + +template<typename Derived> +const MatrixPowerReturnValue<Derived> MatrixBase<Derived>::pow(const RealScalar& p) const +{ return MatrixPowerReturnValue<Derived>(derived(), p); } + +} // namespace Eigen + +#endif // EIGEN_MATRIX_POWER |