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172 lines
5.7 KiB
C++
172 lines
5.7 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 modify it under the
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// terms of the GNU General Public License as published by the Free Software
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// Foundation; either version 2 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 General Public License for more
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// details.
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//
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// You should have received a copy of the GNU General Public License along
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// with Eigen; if not, write to the Free Software Foundation, Inc., 51
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// Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
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//
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// As a special exception, if other files instantiate templates or use macros
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// or functions from this file, or you compile this file and link it
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// with other works to produce a work based on this file, this file does not
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// by itself cause the resulting work to be covered by the GNU General Public
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// License. This exception does not invalidate any other reasons why a work
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// based on this file might be covered by the GNU General Public License.
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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 DotUnroller
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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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DotUnroller<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 DotUnroller<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 DotUnroller<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 DotUnroller<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 Scalar, typename Derived>
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template<typename OtherDerived>
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Scalar MatrixBase<Scalar, Derived>::dot(const OtherDerived& other) const
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{
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assert(Traits::IsVectorAtCompileTime
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&& OtherDerived::Traits::IsVectorAtCompileTime
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&& size() == other.size());
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Scalar res;
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if(EIGEN_UNROLLED_LOOPS
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&& Traits::SizeAtCompileTime != Dynamic
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&& Traits::SizeAtCompileTime <= 16)
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DotUnroller<Traits::SizeAtCompileTime-1, Traits::SizeAtCompileTime,
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Derived, OtherDerived>
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::run(*static_cast<const Derived*>(this), other, res);
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else
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{
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res = (*this).coeff(0) * ei_conj(other.coeff(0));
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for(int i = 1; i < size(); i++)
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res += (*this).coeff(i)* ei_conj(other.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 Scalar, typename Derived>
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typename NumTraits<Scalar>::Real MatrixBase<Scalar, 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 Scalar, typename Derived>
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typename NumTraits<Scalar>::Real MatrixBase<Scalar, 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 Scalar, typename Derived>
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const ScalarMultiple<typename NumTraits<Scalar>::Real, Derived>
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MatrixBase<Scalar, 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 Scalar, typename Derived>
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template<typename OtherDerived>
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bool MatrixBase<Scalar, Derived>::isOrtho
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(const OtherDerived& other,
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typename NumTraits<Scalar>::Real prec) const
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{
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return ei_abs2(dot(other)) <= prec * prec * norm2() * other.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 Scalar, typename Derived>
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bool MatrixBase<Scalar, Derived>::isOrtho
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(typename NumTraits<Scalar>::Real prec) const
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{
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for(int i = 0; i < cols(); i++)
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{
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if(!ei_isApprox(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(col(i).dot(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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