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Diffstat (limited to 'unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h')
| -rw-r--r-- | unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h | 281 |
1 files changed, 184 insertions, 97 deletions
diff --git a/unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h b/unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h index 84fd72fc6..532896c3b 100644 --- a/unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h +++ b/unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h @@ -3,153 +3,240 @@ // // Copyright (C) 2011 Kolja Brix <brix@igpm.rwth-aachen.de> // Copyright (C) 2011 Andreas Platen <andiplaten@gmx.de> +// Copyright (C) 2012 Chen-Pang He <jdh8@ms63.hinet.net> // // 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 KRONECKER_TENSOR_PRODUCT_H #define KRONECKER_TENSOR_PRODUCT_H - namespace Eigen { -namespace internal { +template<typename Scalar, int Options, typename Index> class SparseMatrix; /*! - * Kronecker tensor product helper function for dense matrices + * \brief Kronecker tensor product helper class for dense matrices * - * \param A Dense matrix A - * \param B Dense matrix B - * \param AB_ Kronecker tensor product of A and B + * This class is the return value of kroneckerProduct(MatrixBase, + * MatrixBase). Use the function rather than construct this class + * directly to avoid specifying template prarameters. + * + * \tparam Lhs Type of the left-hand side, a matrix expression. + * \tparam Rhs Type of the rignt-hand side, a matrix expression. */ -template<typename Derived_A, typename Derived_B, typename Derived_AB> -void kroneckerProduct_full(const Derived_A& A, const Derived_B& B, Derived_AB & AB) +template<typename Lhs, typename Rhs> +class KroneckerProduct : public ReturnByValue<KroneckerProduct<Lhs,Rhs> > { - const unsigned int Ar = A.rows(), - Ac = A.cols(), - Br = B.rows(), - Bc = B.cols(); - for (unsigned int i=0; i<Ar; ++i) - for (unsigned int j=0; j<Ac; ++j) - AB.block(i*Br,j*Bc,Br,Bc) = A(i,j)*B; -} + private: + typedef ReturnByValue<KroneckerProduct> Base; + typedef typename Base::Scalar Scalar; + typedef typename Base::Index Index; + + public: + /*! \brief Constructor. */ + KroneckerProduct(const Lhs& A, const Rhs& B) + : m_A(A), m_B(B) + {} + + /*! \brief Evaluate the Kronecker tensor product. */ + template<typename Dest> void evalTo(Dest& dst) const; + + inline Index rows() const { return m_A.rows() * m_B.rows(); } + inline Index cols() const { return m_A.cols() * m_B.cols(); } + + Scalar coeff(Index row, Index col) const + { + return m_A.coeff(row / m_B.rows(), col / m_B.cols()) * + m_B.coeff(row % m_B.rows(), col % m_B.cols()); + } + + Scalar coeff(Index i) const + { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(KroneckerProduct); + return m_A.coeff(i / m_A.size()) * m_B.coeff(i % m_A.size()); + } + private: + typename Lhs::Nested m_A; + typename Rhs::Nested m_B; +}; /*! - * Kronecker tensor product helper function for matrices, where at least one is sparse + * \brief Kronecker tensor product helper class for sparse matrices + * + * If at least one of the operands is a sparse matrix expression, + * then this class is returned and evaluates into a sparse matrix. + * + * This class is the return value of kroneckerProduct(EigenBase, + * EigenBase). Use the function rather than construct this class + * directly to avoid specifying template prarameters. * - * \param A Matrix A - * \param B Matrix B - * \param AB_ Kronecker tensor product of A and B + * \tparam Lhs Type of the left-hand side, a matrix expression. + * \tparam Rhs Type of the rignt-hand side, a matrix expression. */ -template<typename Derived_A, typename Derived_B, typename Derived_AB> -void kroneckerProduct_sparse(const Derived_A &A, const Derived_B &B, Derived_AB &AB) +template<typename Lhs, typename Rhs> +class KroneckerProductSparse : public EigenBase<KroneckerProductSparse<Lhs,Rhs> > { - const unsigned int Ar = A.rows(), - Ac = A.cols(), - Br = B.rows(), - Bc = B.cols(); - AB.resize(Ar*Br,Ac*Bc); - AB.resizeNonZeros(0); - AB.reserve(A.nonZeros()*B.nonZeros()); - - for (int kA=0; kA<A.outerSize(); ++kA) + private: + typedef typename internal::traits<KroneckerProductSparse>::Index Index; + + public: + /*! \brief Constructor. */ + KroneckerProductSparse(const Lhs& A, const Rhs& B) + : m_A(A), m_B(B) + {} + + /*! \brief Evaluate the Kronecker tensor product. */ + template<typename Dest> void evalTo(Dest& dst) const; + + inline Index rows() const { return m_A.rows() * m_B.rows(); } + inline Index cols() const { return m_A.cols() * m_B.cols(); } + + template<typename Scalar, int Options, typename Index> + operator SparseMatrix<Scalar, Options, Index>() + { + SparseMatrix<Scalar, Options, Index> result; + evalTo(result.derived()); + return result; + } + + private: + typename Lhs::Nested m_A; + typename Rhs::Nested m_B; +}; + +template<typename Lhs, typename Rhs> +template<typename Dest> +void KroneckerProduct<Lhs,Rhs>::evalTo(Dest& dst) const +{ + const int BlockRows = Rhs::RowsAtCompileTime, + BlockCols = Rhs::ColsAtCompileTime; + const Index Br = m_B.rows(), + Bc = m_B.cols(); + for (Index i=0; i < m_A.rows(); ++i) + for (Index j=0; j < m_A.cols(); ++j) + Block<Dest,BlockRows,BlockCols>(dst,i*Br,j*Bc,Br,Bc) = m_A.coeff(i,j) * m_B; +} + +template<typename Lhs, typename Rhs> +template<typename Dest> +void KroneckerProductSparse<Lhs,Rhs>::evalTo(Dest& dst) const +{ + const Index Br = m_B.rows(), + Bc = m_B.cols(); + dst.resize(rows(),cols()); + dst.resizeNonZeros(0); + dst.reserve(m_A.nonZeros() * m_B.nonZeros()); + + for (Index kA=0; kA < m_A.outerSize(); ++kA) { - for (int kB=0; kB<B.outerSize(); ++kB) + for (Index kB=0; kB < m_B.outerSize(); ++kB) { - for (typename Derived_A::InnerIterator itA(A,kA); itA; ++itA) + for (typename Lhs::InnerIterator itA(m_A,kA); itA; ++itA) { - for (typename Derived_B::InnerIterator itB(B,kB); itB; ++itB) + for (typename Rhs::InnerIterator itB(m_B,kB); itB; ++itB) { - const unsigned int iA = itA.row(), - jA = itA.col(), - iB = itB.row(), - jB = itB.col(), - i = iA*Br + iB, - j = jA*Bc + jB; - AB.insert(i,j) = itA.value() * itB.value(); + const Index i = itA.row() * Br + itB.row(), + j = itA.col() * Bc + itB.col(); + dst.insert(i,j) = itA.value() * itB.value(); } } } } } -} // end namespace internal +namespace internal { +template<typename _Lhs, typename _Rhs> +struct traits<KroneckerProduct<_Lhs,_Rhs> > +{ + typedef typename remove_all<_Lhs>::type Lhs; + typedef typename remove_all<_Rhs>::type Rhs; + typedef typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType Scalar; + + enum { + Rows = size_at_compile_time<traits<Lhs>::RowsAtCompileTime, traits<Rhs>::RowsAtCompileTime>::ret, + Cols = size_at_compile_time<traits<Lhs>::ColsAtCompileTime, traits<Rhs>::ColsAtCompileTime>::ret, + MaxRows = size_at_compile_time<traits<Lhs>::MaxRowsAtCompileTime, traits<Rhs>::MaxRowsAtCompileTime>::ret, + MaxCols = size_at_compile_time<traits<Lhs>::MaxColsAtCompileTime, traits<Rhs>::MaxColsAtCompileTime>::ret, + CoeffReadCost = Lhs::CoeffReadCost + Rhs::CoeffReadCost + NumTraits<Scalar>::MulCost + }; + + typedef Matrix<Scalar,Rows,Cols> ReturnType; +}; + +template<typename _Lhs, typename _Rhs> +struct traits<KroneckerProductSparse<_Lhs,_Rhs> > +{ + typedef MatrixXpr XprKind; + typedef typename remove_all<_Lhs>::type Lhs; + typedef typename remove_all<_Rhs>::type Rhs; + typedef typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType Scalar; + typedef typename promote_storage_type<typename traits<Lhs>::StorageKind, typename traits<Rhs>::StorageKind>::ret StorageKind; + typedef typename promote_index_type<typename Lhs::Index, typename Rhs::Index>::type Index; + + enum { + LhsFlags = Lhs::Flags, + RhsFlags = Rhs::Flags, + + RowsAtCompileTime = size_at_compile_time<traits<Lhs>::RowsAtCompileTime, traits<Rhs>::RowsAtCompileTime>::ret, + ColsAtCompileTime = size_at_compile_time<traits<Lhs>::ColsAtCompileTime, traits<Rhs>::ColsAtCompileTime>::ret, + MaxRowsAtCompileTime = size_at_compile_time<traits<Lhs>::MaxRowsAtCompileTime, traits<Rhs>::MaxRowsAtCompileTime>::ret, + MaxColsAtCompileTime = size_at_compile_time<traits<Lhs>::MaxColsAtCompileTime, traits<Rhs>::MaxColsAtCompileTime>::ret, + + EvalToRowMajor = (LhsFlags & RhsFlags & RowMajorBit), + RemovedBits = ~(EvalToRowMajor ? 0 : RowMajorBit), + + Flags = ((LhsFlags | RhsFlags) & HereditaryBits & RemovedBits) + | EvalBeforeNestingBit | EvalBeforeAssigningBit, + CoeffReadCost = Dynamic + }; +}; +} // end namespace internal /*! - * Computes Kronecker tensor product of two dense matrices + * \ingroup KroneckerProduct_Module * - * \param a Dense matrix a - * \param b Dense matrix b - * \param c Kronecker tensor product of a and b - */ -template<typename A,typename B,typename CScalar,int CRows,int CCols, int COptions, int CMaxRows, int CMaxCols> -void kroneckerProduct(const MatrixBase<A>& a, const MatrixBase<B>& b, Matrix<CScalar,CRows,CCols,COptions,CMaxRows,CMaxCols>& c) -{ - c.resize(a.rows()*b.rows(),a.cols()*b.cols()); - internal::kroneckerProduct_full(a.derived(), b.derived(), c); -} - -/*! * Computes Kronecker tensor product of two dense matrices * - * Remark: this function uses the const cast hack and has been - * implemented to make the function call possible, where the - * output matrix is a submatrix, e.g. - * kroneckerProduct(A,B,AB.block(2,5,6,6)); + * \warning If you want to replace a matrix by its Kronecker product + * with some matrix, do \b NOT do this: + * \code + * A = kroneckerProduct(A,B); // bug!!! caused by aliasing effect + * \endcode + * instead, use eval() to work around this: + * \code + * A = kroneckerProduct(A,B).eval(); + * \endcode * * \param a Dense matrix a * \param b Dense matrix b - * \param c Kronecker tensor product of a and b + * \return Kronecker tensor product of a and b */ -template<typename A,typename B,typename C> -void kroneckerProduct(const MatrixBase<A>& a, const MatrixBase<B>& b, MatrixBase<C> const & c_) +template<typename A, typename B> +KroneckerProduct<A,B> kroneckerProduct(const MatrixBase<A>& a, const MatrixBase<B>& b) { - MatrixBase<C>& c = const_cast<MatrixBase<C>& >(c_); - internal::kroneckerProduct_full(a.derived(), b.derived(), c.derived()); + return KroneckerProduct<A, B>(a.derived(), b.derived()); } /*! - * Computes Kronecker tensor product of a dense and a sparse matrix + * \ingroup KroneckerProduct_Module * - * \param a Dense matrix a - * \param b Sparse matrix b - * \param c Kronecker tensor product of a and b - */ -template<typename A,typename B,typename C> -void kroneckerProduct(const MatrixBase<A>& a, const SparseMatrixBase<B>& b, SparseMatrixBase<C>& c) -{ - internal::kroneckerProduct_sparse(a.derived(), b.derived(), c.derived()); -} - -/*! - * Computes Kronecker tensor product of a sparse and a dense matrix - * - * \param a Sparse matrix a - * \param b Dense matrix b - * \param c Kronecker tensor product of a and b - */ -template<typename A,typename B,typename C> -void kroneckerProduct(const SparseMatrixBase<A>& a, const MatrixBase<B>& b, SparseMatrixBase<C>& c) -{ - internal::kroneckerProduct_sparse(a.derived(), b.derived(), c.derived()); -} - -/*! - * Computes Kronecker tensor product of two sparse matrices + * Computes Kronecker tensor product of two matrices, at least one of + * which is sparse * - * \param a Sparse matrix a - * \param b Sparse matrix b - * \param c Kronecker tensor product of a and b + * \param a Dense/sparse matrix a + * \param b Dense/sparse matrix b + * \return Kronecker tensor product of a and b, stored in a sparse + * matrix */ -template<typename A,typename B,typename C> -void kroneckerProduct(const SparseMatrixBase<A>& a, const SparseMatrixBase<B>& b, SparseMatrixBase<C>& c) +template<typename A, typename B> +KroneckerProductSparse<A,B> kroneckerProduct(const EigenBase<A>& a, const EigenBase<B>& b) { - internal::kroneckerProduct_sparse(a.derived(), b.derived(), c.derived()); + return KroneckerProductSparse<A,B>(a.derived(), b.derived()); } } // end namespace Eigen |