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https://gitlab.com/libeigen/eigen.git
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add a generic mechanism to copy a special matrix to a dense matrix so that
we don't need to add other specialization of MatrixBase::operator=, Matrix::=, and Matrix::Matrix(...)
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@ -225,47 +225,6 @@ template<typename MatrixType> struct LLT_Traits<MatrixType,UpperTriangular>
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template<typename MatrixType, int _UpLo>
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void LLT<MatrixType,_UpLo>::compute(const MatrixType& a)
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{
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// assert(a.rows()==a.cols());
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// const int size = a.rows();
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// m_matrix.resize(size, size);
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// // The biggest overall is the point of reference to which further diagonals
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// // are compared; if any diagonal is negligible compared
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// // to the largest overall, the algorithm bails. This cutoff is suggested
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// // in "Analysis of the Cholesky Decomposition of a Semi-definite Matrix" by
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// // Nicholas J. Higham. Also see "Accuracy and Stability of Numerical
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// // Algorithms" page 217, also by Higham.
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// const RealScalar cutoff = machine_epsilon<Scalar>() * size * a.diagonal().cwise().abs().maxCoeff();
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// RealScalar x;
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// x = ei_real(a.coeff(0,0));
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// m_matrix.coeffRef(0,0) = ei_sqrt(x);
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// if(size==1)
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// {
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// m_isInitialized = true;
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// return;
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// }
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// m_matrix.col(0).end(size-1) = a.row(0).end(size-1).adjoint() / ei_real(m_matrix.coeff(0,0));
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// for (int j = 1; j < size; ++j)
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// {
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// x = ei_real(a.coeff(j,j)) - m_matrix.row(j).start(j).squaredNorm();
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// if (ei_abs(x) < cutoff) continue;
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//
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// m_matrix.coeffRef(j,j) = x = ei_sqrt(x);
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//
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// int endSize = size-j-1;
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// if (endSize>0) {
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// // Note that when all matrix columns have good alignment, then the following
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// // product is guaranteed to be optimal with respect to alignment.
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// m_matrix.col(j).end(endSize) =
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// (m_matrix.block(j+1, 0, endSize, j) * m_matrix.row(j).start(j).adjoint()).lazy();
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//
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// // FIXME could use a.col instead of a.row
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// m_matrix.col(j).end(endSize) = (a.row(j).end(endSize).adjoint()
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// - m_matrix.col(j).end(endSize) ) / x;
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// }
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// }
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//
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// m_isInitialized = true;
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assert(a.rows()==a.cols());
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const int size = a.rows();
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m_matrix.resize(size, size);
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@ -50,6 +50,8 @@ class DiagonalBase : public MultiplierBase<Derived>
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#endif // not EIGEN_PARSED_BY_DOXYGEN
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DenseMatrixType toDenseMatrix() const { return derived(); }
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template<typename DenseDerived>
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void evalToDense(MatrixBase<DenseDerived> &other) const;
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inline const DiagonalVectorType& diagonal() const { return derived().diagonal(); }
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inline DiagonalVectorType& diagonal() { return derived().diagonal(); }
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@ -63,12 +65,11 @@ class DiagonalBase : public MultiplierBase<Derived>
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};
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template<typename Derived>
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template<typename DiagonalDerived>
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Derived& MatrixBase<Derived>::operator=(const DiagonalBase<DiagonalDerived> &other)
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template<typename DenseDerived>
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void DiagonalBase<Derived>::evalToDense(MatrixBase<DenseDerived> &other) const
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{
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setZero();
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diagonal() = other.diagonal();
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return derived();
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other.setZero();
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other.diagonal() = diagonal();
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}
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/** \class DiagonalMatrix
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@ -439,34 +439,20 @@ class Matrix
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{ other.evalTo(*this); }
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/** Destructor */
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inline ~Matrix() {}
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template<typename DiagonalDerived>
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EIGEN_STRONG_INLINE Matrix& operator=(const DiagonalBase<DiagonalDerived> &other)
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/** \sa MatrixBase::operator=(const AnyMatrixBase<OtherDerived>&) */
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE Matrix& operator=(const AnyMatrixBase<OtherDerived> &other)
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{
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resize(other.diagonal().size(), other.diagonal().size());
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Base::operator=(other);
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return *this;
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}
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template<typename DiagonalDerived>
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EIGEN_STRONG_INLINE Matrix(const DiagonalBase<DiagonalDerived> &other)
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: m_storage(other.diagonal().size() * other.diagonal().size(), other.diagonal().size(), other.diagonal().size())
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{
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*this = other;
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}
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template<typename TriangularDerived>
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EIGEN_STRONG_INLINE Matrix& operator=(const TriangularBase<TriangularDerived> &other)
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{
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resize(other.rows(), other.cols());
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resize(other.derived().rows(), other.derived().cols());
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Base::operator=(other.derived());
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return *this;
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}
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template<typename TriangularDerived>
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EIGEN_STRONG_INLINE Matrix(const TriangularBase<TriangularDerived> &other)
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: m_storage(other.rows() * other.cols(), other.rows(), other.cols())
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/** \sa MatrixBase::operator=(const AnyMatrixBase<OtherDerived>&) */
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE Matrix(const AnyMatrixBase<OtherDerived> &other)
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: m_storage(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
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{
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*this = other;
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}
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@ -284,6 +284,17 @@ template<typename Derived> class MatrixBase
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*/
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Derived& operator=(const MatrixBase& other);
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/** Copies the generic expression \a other into *this. \returns a reference to *this.
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* The expression must provide a (templated) evalToDense(Derived& dst) const function
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* which does the actual job. In practice, this allows any user to write its own
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* special matrix without having to modify MatrixBase */
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template<typename OtherDerived>
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Derived& operator=(const AnyMatrixBase<OtherDerived> &other)
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{ other.derived().evalToDense(derived()); return derived(); }
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template<typename OtherDerived,typename OtherEvalType>
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Derived& operator=(const ReturnByValue<OtherDerived,OtherEvalType>& func);
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#ifndef EIGEN_PARSED_BY_DOXYGEN
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/** Copies \a other into *this without evaluating other. \returns a reference to *this. */
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template<typename OtherDerived>
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@ -297,10 +308,6 @@ template<typename Derived> class MatrixBase
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template<typename OtherDerived>
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Derived& lazyAssign(const Flagged<OtherDerived, 0, EvalBeforeNestingBit | EvalBeforeAssigningBit>& other)
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{ return lazyAssign(other._expression()); }
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/** Overloaded for fast triangular part to dense matrix evaluation */
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template<typename TriangularDerived>
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Derived& lazyAssign(const TriangularBase<TriangularDerived> &other);
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#endif // not EIGEN_PARSED_BY_DOXYGEN
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CommaInitializer<Derived> operator<< (const Scalar& s);
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@ -403,12 +410,6 @@ template<typename Derived> class MatrixBase
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const DiagonalProduct<Derived, DiagonalDerived, DiagonalOnTheRight>
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operator*(const DiagonalBase<DiagonalDerived> &diagonal) const;
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template<typename DiagonalDerived>
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Derived& operator=(const DiagonalBase<DiagonalDerived> &other);
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template<typename TriangularDerived>
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Derived& operator=(const TriangularBase<TriangularDerived> &other);
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template<typename OtherDerived>
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typename ei_plain_matrix_type_column_major<OtherDerived>::type
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solveTriangular(const MatrixBase<OtherDerived>& other) const;
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@ -738,9 +739,6 @@ template<typename Derived> class MatrixBase
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// dense = dense * sparse
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template<typename Derived1, typename Derived2>
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Derived& lazyAssign(const SparseProduct<Derived1,Derived2,DenseTimeSparseProduct>& product);
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template<typename OtherDerived,typename OtherEvalType>
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Derived& operator=(const ReturnByValue<OtherDerived,OtherEvalType>& func);
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#ifdef EIGEN_MATRIXBASE_PLUGIN
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#include EIGEN_MATRIXBASE_PLUGIN
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@ -90,6 +90,11 @@ template<typename Derived> class TriangularBase : public MultiplierBase<Derived>
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inline Derived& derived() { return *static_cast<Derived*>(this); }
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#endif // not EIGEN_PARSED_BY_DOXYGEN
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template<typename DenseDerived>
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void evalToDense(MatrixBase<DenseDerived> &other) const;
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template<typename DenseDerived>
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void evalToDenseLazy(MatrixBase<DenseDerived> &other) const;
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protected:
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void check_coordinates(int row, int col)
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@ -516,36 +521,34 @@ void TriangularView<MatrixType, Mode>::lazyAssign(const TriangularBase<OtherDeri
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/** Assigns a triangular or selfadjoint matrix to a dense matrix.
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* If the matrix is triangular, the opposite part is set to zero. */
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template<typename Derived>
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template<typename TriangularDerived>
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Derived& MatrixBase<Derived>::operator=(const TriangularBase<TriangularDerived> &other)
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template<typename DenseDerived>
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void TriangularBase<Derived>::evalToDense(MatrixBase<DenseDerived> &other) const
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{
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if(ei_traits<TriangularDerived>::Flags & EvalBeforeAssigningBit)
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if(ei_traits<Derived>::Flags & EvalBeforeAssigningBit)
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{
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typename TriangularDerived::PlainMatrixType other_evaluated(other.rows(), other.cols());
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other_evaluated.lazyAssign(other);
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this->swap(other_evaluated);
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typename Derived::PlainMatrixType other_evaluated(rows(), cols());
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evalToDenseLazy(other_evaluated);
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other.derived().swap(other_evaluated);
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}
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else
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lazyAssign(other.derived());
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return derived();
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evalToDenseLazy(other.derived());
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}
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/** Assigns a triangular or selfadjoint matrix to a dense matrix.
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* If the matrix is triangular, the opposite part is set to zero. */
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template<typename Derived>
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template<typename TriangularDerived>
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Derived& MatrixBase<Derived>::lazyAssign(const TriangularBase<TriangularDerived> &other)
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template<typename DenseDerived>
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void TriangularBase<Derived>::evalToDenseLazy(MatrixBase<DenseDerived> &other) const
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{
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const bool unroll = Derived::SizeAtCompileTime * TriangularDerived::CoeffReadCost / 2
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const bool unroll = DenseDerived::SizeAtCompileTime * Derived::CoeffReadCost / 2
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<= EIGEN_UNROLLING_LIMIT;
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ei_assert(this->rows() == other.rows() && this->cols() == other.cols());
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ei_part_assignment_impl
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<Derived, typename ei_traits<TriangularDerived>::ExpressionType, TriangularDerived::Mode,
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unroll ? int(Derived::SizeAtCompileTime) : Dynamic,
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<DenseDerived, typename ei_traits<Derived>::ExpressionType, Derived::Mode,
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unroll ? int(DenseDerived::SizeAtCompileTime) : Dynamic,
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true // clear the opposite triangular part
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>::run(this->const_cast_derived(), other.derived()._expression());
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return derived();
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>::run(other.derived(), derived()._expression());
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}
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/** \deprecated use MatrixBase::triangularView() */
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@ -451,25 +451,19 @@ template<typename Derived> class SparseMatrixBase
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// Derived& setRandom();
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// Derived& setIdentity();
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template<typename DenseDerived>
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void evalToDense(MatrixBase<DenseDerived>& dst)
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{
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dst.resize(rows(),cols());
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dst.setZero();
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for (int j=0; j<outerSize(); ++j)
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for (typename Derived::InnerIterator i(derived(),j); i; ++i)
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res.coeffRef(i.row(),i.col()) = i.value();
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}
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Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> toDense() const
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{
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Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> res(rows(),cols());
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res.setZero();
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for (int j=0; j<outerSize(); ++j)
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{
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for (typename Derived::InnerIterator i(derived(),j); i; ++i)
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{
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if(IsRowMajor)
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std::cerr << i.row() << "," << i.col() << " == " << j << "," << i.index() << "\n";
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else
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std::cerr << i.row() << "," << i.col() << " == " << i.index() << "," << j << "\n";
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// if(IsRowMajor)
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res.coeffRef(i.row(),i.col()) = i.value();
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// else
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// res.coeffRef(i.index(),j) = i.value();
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}
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}
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return res;
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return derived();
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}
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template<typename OtherDerived>
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