Eigne Matrix Class Library
Dependents: Eigen_test Odometry_test AttitudeEstimation_usingTicker MPU9250_Quaternion_Binary_Serial ... more
Eigen Matrix Class Library for mbed.
Finally, you can use Eigen on your mbed!!!
Diff: src/Core/Fuzzy.h
- Revision:
- 0:13a5d365ba16
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/src/Core/Fuzzy.h Thu Oct 13 04:07:23 2016 +0000 @@ -0,0 +1,150 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> +// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> +// +// 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_FUZZY_H +#define EIGEN_FUZZY_H + +namespace Eigen { + +namespace internal +{ + +template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger> +struct isApprox_selector +{ + static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec) + { + using std::min; + typename internal::nested<Derived,2>::type nested(x); + typename internal::nested<OtherDerived,2>::type otherNested(y); + return (nested - otherNested).cwiseAbs2().sum() <= prec * prec * (min)(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum()); + } +}; + +template<typename Derived, typename OtherDerived> +struct isApprox_selector<Derived, OtherDerived, true> +{ + static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar&) + { + return x.matrix() == y.matrix(); + } +}; + +template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger> +struct isMuchSmallerThan_object_selector +{ + static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec) + { + return x.cwiseAbs2().sum() <= numext::abs2(prec) * y.cwiseAbs2().sum(); + } +}; + +template<typename Derived, typename OtherDerived> +struct isMuchSmallerThan_object_selector<Derived, OtherDerived, true> +{ + static bool run(const Derived& x, const OtherDerived&, const typename Derived::RealScalar&) + { + return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix(); + } +}; + +template<typename Derived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger> +struct isMuchSmallerThan_scalar_selector +{ + static bool run(const Derived& x, const typename Derived::RealScalar& y, const typename Derived::RealScalar& prec) + { + return x.cwiseAbs2().sum() <= numext::abs2(prec * y); + } +}; + +template<typename Derived> +struct isMuchSmallerThan_scalar_selector<Derived, true> +{ + static bool run(const Derived& x, const typename Derived::RealScalar&, const 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<typename Derived> +template<typename OtherDerived> +bool DenseBase<Derived>::isApprox( + const DenseBase<OtherDerived>& other, + const RealScalar& prec +) const +{ + return internal::isApprox_selector<Derived, OtherDerived>::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<OtherDerived>&, RealScalar) const + */ +template<typename Derived> +bool DenseBase<Derived>::isMuchSmallerThan( + const typename NumTraits<Scalar>::Real& other, + const RealScalar& prec +) const +{ + return internal::isMuchSmallerThan_scalar_selector<Derived>::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<typename Derived> +template<typename OtherDerived> +bool DenseBase<Derived>::isMuchSmallerThan( + const DenseBase<OtherDerived>& other, + const RealScalar& prec +) const +{ + return internal::isMuchSmallerThan_object_selector<Derived, OtherDerived>::run(derived(), other.derived(), prec); +} + +} // end namespace Eigen + +#endif // EIGEN_FUZZY_H \ No newline at end of file