// This file is part of Eigen, a lightweight C++ template library // for linear algebra. Eigen itself is part of the KDE project. // // Copyright (C) 2006-2008 Benoit Jacob // // 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 /** \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 on all columns. * * \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 ei_isMuchSmallerThan(const * RealScalar&, RealScalar) instead. * * \sa ei_isMuchSmallerThan(const RealScalar&, RealScalar) const */ template template bool MatrixBase::isApprox( const MatrixBase& other, typename NumTraits::Real prec ) const { ei_assert(rows() == other.rows() && cols() == other.cols()); if(IsVectorAtCompileTime) { return((*this - other).norm2() <= std::min(norm2(), other.norm2()) * prec * prec); } else { typename Derived::XprCopy xprCopy(derived()); typename OtherDerived::XprCopy otherXprCopy(other.derived()); for(int i = 0; i < cols(); i++) if((xprCopy.col(i) - otherXprCopy.col(i)).norm2() > std::min(xprCopy.col(i).norm2(), otherXprCopy.col(i).norm2()) * prec * prec) return false; return true; } } /** \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 on all columns. * * \sa isApprox(), isMuchSmallerThan(const MatrixBase&, RealScalar) const */ template bool MatrixBase::isMuchSmallerThan( const typename NumTraits::Real& other, typename NumTraits::Real prec ) const { if(IsVectorAtCompileTime) { return(norm2() <= ei_abs2(other * prec)); } else { typename Derived::XprCopy xprCopy(*this); for(int i = 0; i < cols(); i++) if(xprCopy.col(i).norm2() > ei_abs2(other * prec)) return false; return true; } } /** \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 on all columns. * * \sa isApprox(), isMuchSmallerThan(const RealScalar&, RealScalar) const */ template template bool MatrixBase::isMuchSmallerThan( const MatrixBase& other, typename NumTraits::Real prec ) const { ei_assert(rows() == other.rows() && cols() == other.cols()); if(IsVectorAtCompileTime) { return(norm2() <= other.norm2() * prec * prec); } else { typename Derived::XprCopy xprCopy(*this); typename OtherDerived::XprCopy otherXprCopy(other); for(int i = 0; i < cols(); i++) if(xprCopy.col(i).norm2() > otherXprCopy.col(i).norm2() * prec * prec) return false; return true; } } #endif // EIGEN_FUZZY_H