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Updated fuzzy comparisons to use L2 norm as all my experiments
tends to show L2 norm works very well here. (the legacy implementation is still available via a preprocessor token to allow further experiments if needed...)
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@ -26,6 +26,78 @@
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#ifndef EIGEN_FUZZY_H
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#define EIGEN_FUZZY_H
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#ifndef EIGEN_LEGACY_COMPARES
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/** \returns \c true if \c *this is approximately equal to \a other, within the precision
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* determined by \a prec.
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*
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* \note The fuzzy compares are done multiplicatively. Two vectors \f$ v \f$ and \f$ w \f$
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* are considered to be approximately equal within precision \f$ p \f$ if
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* \f[ \Vert v - w \Vert \leqslant p\,\min(\Vert v\Vert, \Vert w\Vert). \f]
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* For matrices, the comparison is done using the Hilbert-Schmidt norm (aka Frobenius norm
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* L2 norm).
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*
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* \note Because of the multiplicativeness of this comparison, one can't use this function
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* to check whether \c *this is approximately equal to the zero matrix or vector.
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* Indeed, \c isApprox(zero) returns false unless \c *this itself is exactly the zero matrix
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* or vector. If you want to test whether \c *this is zero, use ei_isMuchSmallerThan(const
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* RealScalar&, RealScalar) instead.
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*
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* \sa ei_isMuchSmallerThan(const RealScalar&, RealScalar) const
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*/
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template<typename Derived>
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template<typename OtherDerived>
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bool MatrixBase<Derived>::isApprox(
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const MatrixBase<OtherDerived>& other,
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typename NumTraits<Scalar>::Real prec
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) const
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{
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const typename ei_nested<Derived,2>::type nested(derived());
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const typename ei_nested<OtherDerived,2>::type otherNested(other.derived());
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return (nested - otherNested).cwiseAbs2().sum() <= prec * prec * std::min(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum());
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}
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/** \returns \c true if the norm of \c *this is much smaller than \a other,
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* within the precision determined by \a prec.
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*
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* \note The fuzzy compares are done multiplicatively. A vector \f$ v \f$ is
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* considered to be much smaller than \f$ x \f$ within precision \f$ p \f$ if
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* \f[ \Vert v \Vert \leqslant p\,\vert x\vert. \f]
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* For matrices, the comparison is done using the Hilbert-Schmidt norm.
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*
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* \sa isApprox(), isMuchSmallerThan(const MatrixBase<OtherDerived>&, RealScalar) const
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*/
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template<typename Derived>
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bool MatrixBase<Derived>::isMuchSmallerThan(
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const typename NumTraits<Scalar>::Real& other,
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typename NumTraits<Scalar>::Real prec
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) const
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{
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return cwiseAbs2().sum() <= prec * prec * other * other * cols() * rows();
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}
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/** \returns \c true if the norm of \c *this is much smaller than the norm of \a other,
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* within the precision determined by \a prec.
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*
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* \note The fuzzy compares are done multiplicatively. A vector \f$ v \f$ is
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* considered to be much smaller than a vector \f$ w \f$ within precision \f$ p \f$ if
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* \f[ \Vert v \Vert \leqslant p\,\Vert w\Vert. \f]
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* For matrices, the comparison is done using the Hilbert-Schmidt norm.
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*
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* \sa isApprox(), isMuchSmallerThan(const RealScalar&, RealScalar) const
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*/
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template<typename Derived>
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template<typename OtherDerived>
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bool MatrixBase<Derived>::isMuchSmallerThan(
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const MatrixBase<OtherDerived>& other,
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typename NumTraits<Scalar>::Real prec
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) const
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{
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return this->cwiseAbs2().sum() <= prec * prec * other.cwiseAbs2().sum();
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}
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#else
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template<typename Derived, typename OtherDerived=Derived, bool IsVector=Derived::IsVectorAtCompileTime>
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struct ei_fuzzy_selector;
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@ -154,4 +226,6 @@ struct ei_fuzzy_selector<Derived,OtherDerived,false>
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}
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};
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#endif
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#endif // EIGEN_FUZZY_H
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