183 lines
6.3 KiB
C++
183 lines
6.3 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2006-2008 Benoit Jacob <jacob@math.jussieu.fr>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#ifndef EIGEN_DOT_H
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#define EIGEN_DOT_H
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template<int Index, int Size, typename Derived1, typename Derived2>
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struct ei_dot_unroller
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{
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static void run(const Derived1 &v1, const Derived2& v2, typename Derived1::Scalar &dot)
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{
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ei_dot_unroller<Index-1, Size, Derived1, Derived2>::run(v1, v2, dot);
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dot += v1.coeff(Index) * ei_conj(v2.coeff(Index));
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}
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};
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template<int Size, typename Derived1, typename Derived2>
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struct ei_dot_unroller<0, Size, Derived1, Derived2>
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{
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static void run(const Derived1 &v1, const Derived2& v2, typename Derived1::Scalar &dot)
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{
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dot = v1.coeff(0) * ei_conj(v2.coeff(0));
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}
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};
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template<int Index, typename Derived1, typename Derived2>
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struct ei_dot_unroller<Index, Dynamic, Derived1, Derived2>
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{
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static void run(const Derived1&, const Derived2&, typename Derived1::Scalar&) {}
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};
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// prevent buggy user code from causing an infinite recursion
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template<int Index, typename Derived1, typename Derived2>
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struct ei_dot_unroller<Index, 0, Derived1, Derived2>
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{
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static void run(const Derived1&, const Derived2&, typename Derived1::Scalar&) {}
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};
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/** \returns the dot product of *this with other.
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*
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* \only_for_vectors
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*
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* \note If the scalar type is complex numbers, then this function returns the hermitian
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* (sesquilinear) dot product, linear in the first variable and anti-linear in the
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* second variable.
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*
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* \sa norm2(), norm()
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*/
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template<typename Derived>
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template<typename OtherDerived>
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typename ei_traits<Derived>::Scalar
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MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
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{
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typedef typename Derived::XprCopy XprCopy;
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typedef typename OtherDerived::XprCopy OtherXprCopy;
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typedef typename ei_unref<XprCopy>::type _XprCopy;
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typedef typename ei_unref<OtherXprCopy>::type _OtherXprCopy;
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XprCopy xprCopy(derived());
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OtherXprCopy otherXprCopy(other.derived());
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ei_assert(_XprCopy::IsVectorAtCompileTime
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&& _OtherXprCopy::IsVectorAtCompileTime
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&& xprCopy.size() == otherXprCopy.size());
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Scalar res;
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const bool unroll = SizeAtCompileTime
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* (_XprCopy::CoeffReadCost + _OtherXprCopy::CoeffReadCost + NumTraits<Scalar>::MulCost)
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+ (SizeAtCompileTime - 1) * NumTraits<Scalar>::AddCost
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<= EIGEN_UNROLLING_LIMIT;
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if(unroll)
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ei_dot_unroller<SizeAtCompileTime-1,
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unroll ? SizeAtCompileTime : Dynamic,
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_XprCopy, _OtherXprCopy>
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::run(xprCopy, otherXprCopy, res);
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else
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{
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res = xprCopy.coeff(0) * ei_conj(otherXprCopy.coeff(0));
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for(int i = 1; i < size(); i++)
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res += xprCopy.coeff(i)* ei_conj(otherXprCopy.coeff(i));
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}
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return res;
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}
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/** \returns the squared norm of *this, i.e. the dot product of *this with itself.
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*
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* \only_for_vectors
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*
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* \sa dot(), norm()
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*/
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template<typename Derived>
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typename NumTraits<typename ei_traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm2() const
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{
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return ei_real(dot(*this));
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}
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/** \returns the norm of *this, i.e. the square root of the dot product of *this with itself.
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*
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* \only_for_vectors
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*
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* \sa dot(), norm2()
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*/
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template<typename Derived>
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typename NumTraits<typename ei_traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm() const
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{
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return ei_sqrt(norm2());
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}
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/** \returns an expression of the quotient of *this by its own norm.
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*
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* \only_for_vectors
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*
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* \sa norm()
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*/
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template<typename Derived>
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const CwiseUnaryOp<ei_scalar_multiple_op<typename ei_traits<Derived>::Scalar>, Derived>
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MatrixBase<Derived>::normalized() const
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{
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return (*this) / norm();
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}
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/** \returns true if *this is approximately orthogonal to \a other,
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* within the precision given by \a prec.
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*
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* Example: \include MatrixBase_isOrtho_vector.cpp
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* Output: \verbinclude MatrixBase_isOrtho_vector.out
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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>::isOrtho
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(const MatrixBase<OtherDerived>& other, RealScalar prec) const
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{
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typename ei_xpr_copy<Derived,2>::type xprCopy(derived());
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typename ei_xpr_copy<OtherDerived,2>::type otherXprCopy(other.derived());
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return ei_abs2(xprCopy.dot(otherXprCopy)) <= prec * prec * xprCopy.norm2() * otherXprCopy.norm2();
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}
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/** \returns true if *this is approximately an unitary matrix,
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* within the precision given by \a prec. In the case where the \a Scalar
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* type is real numbers, a unitary matrix is an orthogonal matrix, whence the name.
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*
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* \note This can be used to check whether a family of vectors forms an orthonormal basis.
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* Indeed, \c m.isOrtho() returns true if and only if the columns of m form an
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* orthonormal basis.
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*
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* Example: \include MatrixBase_isOrtho_matrix.cpp
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* Output: \verbinclude MatrixBase_isOrtho_matrix.out
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*/
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template<typename Derived>
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bool MatrixBase<Derived>::isOrtho(RealScalar prec) const
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{
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typename Derived::XprCopy xprCopy(derived());
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for(int i = 0; i < cols(); i++)
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{
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if(!ei_isApprox(xprCopy.col(i).norm2(), static_cast<Scalar>(1), prec))
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return false;
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for(int j = 0; j < i; j++)
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if(!ei_isMuchSmallerThan(xprCopy.col(i).dot(xprCopy.col(j)), static_cast<Scalar>(1), prec))
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return false;
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}
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return true;
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}
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#endif // EIGEN_DOT_H
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