// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2006-2008 Benoit Jacob // Copyright (C) 2008 Gael Guennebaud // // 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 . #ifndef EIGEN_FUZZY_H #define EIGEN_FUZZY_H namespace Eigen { namespace internal { template::IsInteger> struct isApprox_selector { static bool run(const Derived& x, const OtherDerived& y, typename Derived::RealScalar prec) { using std::min; typename internal::nested::type nested(x); typename internal::nested::type otherNested(y); return (nested - otherNested).cwiseAbs2().sum() <= prec * prec * (min)(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum()); } }; template struct isApprox_selector { static bool run(const Derived& x, const OtherDerived& y, typename Derived::RealScalar) { return x.matrix() == y.matrix(); } }; template::IsInteger> struct isMuchSmallerThan_object_selector { static bool run(const Derived& x, const OtherDerived& y, typename Derived::RealScalar prec) { return x.cwiseAbs2().sum() <= abs2(prec) * y.cwiseAbs2().sum(); } }; template struct isMuchSmallerThan_object_selector { static bool run(const Derived& x, const OtherDerived&, typename Derived::RealScalar) { return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix(); } }; template::IsInteger> struct isMuchSmallerThan_scalar_selector { static bool run(const Derived& x, const typename Derived::RealScalar& y, typename Derived::RealScalar prec) { return x.cwiseAbs2().sum() <= abs2(prec * y); } }; template struct isMuchSmallerThan_scalar_selector { static bool run(const Derived& x, const typename Derived::RealScalar&, typename Derived::RealScalar) { return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix(); } }; } // end namespace internal /** \returns \c true if \c *this is approximately equal to \a other, within the precision * determined by \a prec. * * \note The fuzzy compares are done multiplicatively. Two vectors \f$ v \f$ and \f$ w \f$ * are considered to be approximately equal within precision \f$ p \f$ if * \f[ \Vert v - w \Vert \leqslant p\,\min(\Vert v\Vert, \Vert w\Vert). \f] * For matrices, the comparison is done using the Hilbert-Schmidt norm (aka Frobenius norm * L2 norm). * * \note Because of the multiplicativeness of this comparison, one can't use this function * to check whether \c *this is approximately equal to the zero matrix or vector. * Indeed, \c isApprox(zero) returns false unless \c *this itself is exactly the zero matrix * or vector. If you want to test whether \c *this is zero, use internal::isMuchSmallerThan(const * RealScalar&, RealScalar) instead. * * \sa internal::isMuchSmallerThan(const RealScalar&, RealScalar) const */ template template bool DenseBase::isApprox( const DenseBase& other, RealScalar prec ) const { return internal::isApprox_selector::run(derived(), other.derived(), prec); } /** \returns \c true if the norm of \c *this is much smaller than \a other, * within the precision determined by \a prec. * * \note The fuzzy compares are done multiplicatively. A vector \f$ v \f$ is * considered to be much smaller than \f$ x \f$ within precision \f$ p \f$ if * \f[ \Vert v \Vert \leqslant p\,\vert x\vert. \f] * * For matrices, the comparison is done using the Hilbert-Schmidt norm. For this reason, * the value of the reference scalar \a other should come from the Hilbert-Schmidt norm * of a reference matrix of same dimensions. * * \sa isApprox(), isMuchSmallerThan(const DenseBase&, RealScalar) const */ template bool DenseBase::isMuchSmallerThan( const typename NumTraits::Real& other, RealScalar prec ) const { return internal::isMuchSmallerThan_scalar_selector::run(derived(), other, prec); } /** \returns \c true if the norm of \c *this is much smaller than the norm of \a other, * within the precision determined by \a prec. * * \note The fuzzy compares are done multiplicatively. A vector \f$ v \f$ is * considered to be much smaller than a vector \f$ w \f$ within precision \f$ p \f$ if * \f[ \Vert v \Vert \leqslant p\,\Vert w\Vert. \f] * For matrices, the comparison is done using the Hilbert-Schmidt norm. * * \sa isApprox(), isMuchSmallerThan(const RealScalar&, RealScalar) const */ template template bool DenseBase::isMuchSmallerThan( const DenseBase& other, RealScalar prec ) const { return internal::isMuchSmallerThan_object_selector::run(derived(), other.derived(), prec); } } // end namespace Eigen #endif // EIGEN_FUZZY_H