diff options
Diffstat (limited to 'extern/Eigen3/Eigen/src/Core/StableNorm.h')
-rw-r--r-- | extern/Eigen3/Eigen/src/Core/StableNorm.h | 190 |
1 files changed, 190 insertions, 0 deletions
diff --git a/extern/Eigen3/Eigen/src/Core/StableNorm.h b/extern/Eigen3/Eigen/src/Core/StableNorm.h new file mode 100644 index 00000000000..f667272e4a4 --- /dev/null +++ b/extern/Eigen3/Eigen/src/Core/StableNorm.h @@ -0,0 +1,190 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.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_STABLENORM_H +#define EIGEN_STABLENORM_H + +namespace internal { +template<typename ExpressionType, typename Scalar> +inline void stable_norm_kernel(const ExpressionType& bl, Scalar& ssq, Scalar& scale, Scalar& invScale) +{ + Scalar max = bl.cwiseAbs().maxCoeff(); + if (max>scale) + { + ssq = ssq * abs2(scale/max); + scale = max; + invScale = Scalar(1)/scale; + } + // TODO if the max is much much smaller than the current scale, + // then we can neglect this sub vector + ssq += (bl*invScale).squaredNorm(); +} +} + +/** \returns the \em l2 norm of \c *this avoiding underflow and overflow. + * This version use a blockwise two passes algorithm: + * 1 - find the absolute largest coefficient \c s + * 2 - compute \f$ s \Vert \frac{*this}{s} \Vert \f$ in a standard way + * + * For architecture/scalar types supporting vectorization, this version + * is faster than blueNorm(). Otherwise the blueNorm() is much faster. + * + * \sa norm(), blueNorm(), hypotNorm() + */ +template<typename Derived> +inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real +MatrixBase<Derived>::stableNorm() const +{ + using std::min; + const Index blockSize = 4096; + RealScalar scale = 0; + RealScalar invScale = 1; + RealScalar ssq = 0; // sum of square + enum { + Alignment = (int(Flags)&DirectAccessBit) || (int(Flags)&AlignedBit) ? 1 : 0 + }; + Index n = size(); + Index bi = internal::first_aligned(derived()); + if (bi>0) + internal::stable_norm_kernel(this->head(bi), ssq, scale, invScale); + for (; bi<n; bi+=blockSize) + internal::stable_norm_kernel(this->segment(bi,(min)(blockSize, n - bi)).template forceAlignedAccessIf<Alignment>(), ssq, scale, invScale); + return scale * internal::sqrt(ssq); +} + +/** \returns the \em l2 norm of \c *this using the Blue's algorithm. + * A Portable Fortran Program to Find the Euclidean Norm of a Vector, + * ACM TOMS, Vol 4, Issue 1, 1978. + * + * For architecture/scalar types without vectorization, this version + * is much faster than stableNorm(). Otherwise the stableNorm() is faster. + * + * \sa norm(), stableNorm(), hypotNorm() + */ +template<typename Derived> +inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real +MatrixBase<Derived>::blueNorm() const +{ + using std::pow; + using std::min; + using std::max; + static Index nmax = -1; + static RealScalar b1, b2, s1m, s2m, overfl, rbig, relerr; + if(nmax <= 0) + { + int nbig, ibeta, it, iemin, iemax, iexp; + RealScalar abig, eps; + // This program calculates the machine-dependent constants + // bl, b2, slm, s2m, relerr overfl, nmax + // from the "basic" machine-dependent numbers + // nbig, ibeta, it, iemin, iemax, rbig. + // The following define the basic machine-dependent constants. + // For portability, the PORT subprograms "ilmaeh" and "rlmach" + // are used. For any specific computer, each of the assignment + // statements can be replaced + nbig = (std::numeric_limits<Index>::max)(); // largest integer + ibeta = std::numeric_limits<RealScalar>::radix; // base for floating-point numbers + it = std::numeric_limits<RealScalar>::digits; // number of base-beta digits in mantissa + iemin = std::numeric_limits<RealScalar>::min_exponent; // minimum exponent + iemax = std::numeric_limits<RealScalar>::max_exponent; // maximum exponent + rbig = (std::numeric_limits<RealScalar>::max)(); // largest floating-point number + + iexp = -((1-iemin)/2); + b1 = RealScalar(pow(RealScalar(ibeta),RealScalar(iexp))); // lower boundary of midrange + iexp = (iemax + 1 - it)/2; + b2 = RealScalar(pow(RealScalar(ibeta),RealScalar(iexp))); // upper boundary of midrange + + iexp = (2-iemin)/2; + s1m = RealScalar(pow(RealScalar(ibeta),RealScalar(iexp))); // scaling factor for lower range + iexp = - ((iemax+it)/2); + s2m = RealScalar(pow(RealScalar(ibeta),RealScalar(iexp))); // scaling factor for upper range + + overfl = rbig*s2m; // overflow boundary for abig + eps = RealScalar(pow(double(ibeta), 1-it)); + relerr = internal::sqrt(eps); // tolerance for neglecting asml + abig = RealScalar(1.0/eps - 1.0); + if (RealScalar(nbig)>abig) nmax = int(abig); // largest safe n + else nmax = nbig; + } + Index n = size(); + RealScalar ab2 = b2 / RealScalar(n); + RealScalar asml = RealScalar(0); + RealScalar amed = RealScalar(0); + RealScalar abig = RealScalar(0); + for(Index j=0; j<n; ++j) + { + RealScalar ax = internal::abs(coeff(j)); + if(ax > ab2) abig += internal::abs2(ax*s2m); + else if(ax < b1) asml += internal::abs2(ax*s1m); + else amed += internal::abs2(ax); + } + if(abig > RealScalar(0)) + { + abig = internal::sqrt(abig); + if(abig > overfl) + { + eigen_assert(false && "overflow"); + return rbig; + } + if(amed > RealScalar(0)) + { + abig = abig/s2m; + amed = internal::sqrt(amed); + } + else + return abig/s2m; + } + else if(asml > RealScalar(0)) + { + if (amed > RealScalar(0)) + { + abig = internal::sqrt(amed); + amed = internal::sqrt(asml) / s1m; + } + else + return internal::sqrt(asml)/s1m; + } + else + return internal::sqrt(amed); + asml = (min)(abig, amed); + abig = (max)(abig, amed); + if(asml <= abig*relerr) + return abig; + else + return abig * internal::sqrt(RealScalar(1) + internal::abs2(asml/abig)); +} + +/** \returns the \em l2 norm of \c *this avoiding undeflow and overflow. + * This version use a concatenation of hypot() calls, and it is very slow. + * + * \sa norm(), stableNorm() + */ +template<typename Derived> +inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real +MatrixBase<Derived>::hypotNorm() const +{ + return this->cwiseAbs().redux(internal::scalar_hypot_op<RealScalar>()); +} + +#endif // EIGEN_STABLENORM_H |