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authorGravatar Chen-Pang He <jdh8@ms63.hinet.net>2012-10-15 00:21:12 +0800
committerGravatar Chen-Pang He <jdh8@ms63.hinet.net>2012-10-15 00:21:12 +0800
commitc4b83461d97a2520fecc00f647ca2ae9c4bf04d2 (patch)
treee146e77321041b851ae70acd53da527d710645f0 /unsupported
parentf34db6578a36438c6d229a9be25378cfe6fab38b (diff)
Make kroneckerProduct take two arguments and return an expression, which is more straight-forward.
Diffstat (limited to 'unsupported')
-rw-r--r--unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h258
-rw-r--r--unsupported/test/kronecker_product.cpp61
2 files changed, 201 insertions, 118 deletions
diff --git a/unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h b/unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h
index 14502f03f..a7cb5215b 100644
--- a/unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h
+++ b/unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h
@@ -3,138 +3,230 @@
//
// 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
+#define EIGEN_SIZE_PRODUCT(a,b) (!((int)a && (int)b) ? 0 \
+ : ((int)a == Dynamic || (int)b == Dynamic) ? Dynamic \
+ : (int)a * (int)b)
namespace Eigen {
namespace internal {
-/*!
- * Kronecker tensor product helper function for dense matrices
- *
- * \param A Dense matrix A
- * \param B Dense matrix B
- * \param AB_ Kronecker tensor product of A and B
- */
-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>
+struct traits<KroneckerProduct<_Lhs,_Rhs> >
{
- const unsigned int Ar = A.rows(),
- Ac = A.cols(),
- Br = B.rows(),
- Bc = B.cols();
- AB.resize(Ar*Br,Ac*Bc);
-
- 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;
-}
+ 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 Dense StorageKind;
+ typedef typename promote_index_type<typename Lhs::Index, typename Rhs::Index>::type Index;
+
+ enum {
+ RowsAtCompileTime = EIGEN_SIZE_PRODUCT(traits<Lhs>::RowsAtCompileTime, traits<Rhs>::RowsAtCompileTime),
+ ColsAtCompileTime = EIGEN_SIZE_PRODUCT(traits<Lhs>::ColsAtCompileTime, traits<Rhs>::ColsAtCompileTime),
+ MaxRowsAtCompileTime = EIGEN_SIZE_PRODUCT(traits<Lhs>::MaxRowsAtCompileTime, traits<Rhs>::MaxRowsAtCompileTime),
+ MaxColsAtCompileTime = EIGEN_SIZE_PRODUCT(traits<Lhs>::MaxColsAtCompileTime, traits<Rhs>::MaxColsAtCompileTime),
+ Flags = (MaxRowsAtCompileTime==1 ? RowMajorBit : 0)
+ | EvalBeforeNestingBit | EvalBeforeAssigningBit | NestByRefBit,
+ CoeffReadCost = Lhs::CoeffReadCost + Rhs::CoeffReadCost + NumTraits<Scalar>::MulCost
+ };
+};
+
+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 Sparse StorageKind;
+ typedef typename promote_index_type<typename Lhs::Index, typename Rhs::Index>::type Index;
+
+ enum {
+ LhsFlags = Lhs::Flags,
+ RhsFlags = Rhs::Flags,
+
+ RowsAtCompileTime = EIGEN_SIZE_PRODUCT(traits<Lhs>::RowsAtCompileTime, traits<Rhs>::RowsAtCompileTime),
+ ColsAtCompileTime = EIGEN_SIZE_PRODUCT(traits<Lhs>::ColsAtCompileTime, traits<Rhs>::ColsAtCompileTime),
+ MaxRowsAtCompileTime = EIGEN_SIZE_PRODUCT(traits<Lhs>::MaxRowsAtCompileTime, traits<Rhs>::MaxRowsAtCompileTime),
+ MaxColsAtCompileTime = EIGEN_SIZE_PRODUCT(traits<Lhs>::MaxColsAtCompileTime, traits<Rhs>::MaxColsAtCompileTime),
+
+ EvalToRowMajor = (LhsFlags & RhsFlags & RowMajorBit),
+ RemovedBits = ~(EvalToRowMajor ? 0 : RowMajorBit),
+
+ Flags = ((LhsFlags | RhsFlags) & HereditaryBits & RemovedBits)
+ | EvalBeforeNestingBit | EvalBeforeAssigningBit,
+ CoeffReadCost = Dynamic
+ };
+};
+} // end namespace internal
/*!
- * Kronecker tensor product helper function for matrices, where at least one is sparse
+ * \brief Kronecker tensor product helper class for dense matrices
*
- * \param A Matrix A
- * \param B 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_sparse(const Derived_A &A, const Derived_B &B, Derived_AB &AB)
+template<typename Lhs, typename Rhs>
+class KroneckerProduct : public MatrixBase<KroneckerProduct<Lhs,Rhs> >
+{
+ public:
+ typedef MatrixBase<KroneckerProduct> Base;
+ EIGEN_DENSE_PUBLIC_INTERFACE(KroneckerProduct)
+
+ /*! \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(); }
+
+ typename Base::CoeffReturnType coeff(Index row, Index col) const
+ {
+ return m_A.coeff(row / m_A.cols(), col / m_A.rows()) *
+ m_B.coeff(row % m_A.cols(), col % m_A.rows());
+ }
+
+ typename Base::CoeffReturnType 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());
+ }
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+ struct Unusable {};
+ Unusable& coeffRef(Index) { return *reinterpret_cast<Unusable*>(this); }
+ Unusable& coeffRef(Index,Index) { return *reinterpret_cast<Unusable*>(this); }
+#endif
+
+ private:
+ typename Lhs::Nested m_A;
+ typename Rhs::Nested m_B;
+};
+
+template<typename Lhs, typename Rhs>
+class KroneckerProductSparse : public SparseMatrixBase<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)
+ public:
+ typedef SparseMatrixBase<KroneckerProductSparse> Base;
+ EIGEN_DENSE_PUBLIC_INTERFACE(KroneckerProductSparse)
+
+ /*! \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(); }
+
+ 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
-
/*!
* 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));
- *
* \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, const MatrixBase<C>& c)
+template<typename A, typename B>
+KroneckerProduct<A,B> kroneckerProduct(const MatrixBase<A>& a, const MatrixBase<B>& b)
{
- internal::kroneckerProduct_full(a.derived(), b.derived(), c.const_cast_derived());
+ return KroneckerProduct<A, B>(a.derived(), b.derived());
}
/*!
- * Computes Kronecker tensor product of a dense and a sparse matrix
+ * Computes Kronecker tensor product of two matrices, at least one of
+ * which is sparse.
*
- * \param a Dense 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 MatrixBase<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());
}
-/*!
- * 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)
+template<typename Derived>
+template<typename Lhs, typename Rhs>
+Derived& MatrixBase<Derived>::lazyAssign(const KroneckerProduct<Lhs,Rhs>& other)
{
- internal::kroneckerProduct_sparse(a.derived(), b.derived(), c.derived());
+ other.evalTo(derived());
+ return derived();
}
-/*!
- * Computes Kronecker tensor product of two sparse matrices
- *
- * \param a Sparse 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 SparseMatrixBase<A>& a, const SparseMatrixBase<B>& b, SparseMatrixBase<C>& c)
+template<typename Derived>
+template<typename Lhs, typename Rhs>
+Derived& SparseMatrixBase<Derived>::operator=(const KroneckerProductSparse<Lhs,Rhs>& product)
{
- internal::kroneckerProduct_sparse(a.derived(), b.derived(), c.derived());
+ product.evalTo(derived());
+ return derived();
}
} // end namespace Eigen
diff --git a/unsupported/test/kronecker_product.cpp b/unsupported/test/kronecker_product.cpp
index a60bd3022..68fde8aa5 100644
--- a/unsupported/test/kronecker_product.cpp
+++ b/unsupported/test/kronecker_product.cpp
@@ -3,6 +3,7 @@
//
// 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
@@ -89,64 +90,55 @@ void test_kronecker_product()
MatrixXd DM_b(3,2);
SparseMatrix<double> SM_a(2,3);
SparseMatrix<double> SM_b(3,2);
- SM_a.insert(0,0) = DM_a(0,0) = -0.4461540300782201;
- SM_a.insert(0,1) = DM_a(0,1) = -0.8057364375283049;
- SM_a.insert(0,2) = DM_a(0,2) = 0.3896572459516341;
- SM_a.insert(1,0) = DM_a(1,0) = -0.9076572187376921;
- SM_a.insert(1,1) = DM_a(1,1) = 0.6469156566545853;
- SM_a.insert(1,2) = DM_a(1,2) = -0.3658010398782789;
- SM_b.insert(0,0) = DM_b(0,0) = 0.9004440976767099;
- SM_b.insert(0,1) = DM_b(0,1) = -0.2368830858139832;
- SM_b.insert(1,0) = DM_b(1,0) = -0.9311078389941825;
- SM_b.insert(1,1) = DM_b(1,1) = 0.5310335762980047;
- SM_b.insert(2,0) = DM_b(2,0) = -0.1225112806872035;
- SM_b.insert(2,1) = DM_b(2,1) = 0.5903998022741264;
+ SM_a.insert(0,0) = DM_a.coeffRef(0,0) = -0.4461540300782201;
+ SM_a.insert(0,1) = DM_a.coeffRef(0,1) = -0.8057364375283049;
+ SM_a.insert(0,2) = DM_a.coeffRef(0,2) = 0.3896572459516341;
+ SM_a.insert(1,0) = DM_a.coeffRef(1,0) = -0.9076572187376921;
+ SM_a.insert(1,1) = DM_a.coeffRef(1,1) = 0.6469156566545853;
+ SM_a.insert(1,2) = DM_a.coeffRef(1,2) = -0.3658010398782789;
+ SM_b.insert(0,0) = DM_b.coeffRef(0,0) = 0.9004440976767099;
+ SM_b.insert(0,1) = DM_b.coeffRef(0,1) = -0.2368830858139832;
+ SM_b.insert(1,0) = DM_b.coeffRef(1,0) = -0.9311078389941825;
+ SM_b.insert(1,1) = DM_b.coeffRef(1,1) = 0.5310335762980047;
+ SM_b.insert(2,0) = DM_b.coeffRef(2,0) = -0.1225112806872035;
+ SM_b.insert(2,1) = DM_b.coeffRef(2,1) = 0.5903998022741264;
SparseMatrix<double,RowMajor> SM_row_a(SM_a), SM_row_b(SM_b);
// test kroneckerProduct(DM_block,DM,DM_fixedSize)
- Matrix<double, 6, 6> DM_fix_ab;
- DM_fix_ab(0,0)=37.0;
- kroneckerProduct(DM_a.block(0,0,2,3),DM_b,DM_fix_ab);
+ Matrix<double, 6, 6> DM_fix_ab = kroneckerProduct(DM_a.topLeftCorner<2,3>(),DM_b);
CALL_SUBTEST(check_kronecker_product(DM_fix_ab));
// test kroneckerProduct(DM,DM,DM_block)
MatrixXd DM_block_ab(10,15);
- DM_block_ab(0,0)=37.0;
- kroneckerProduct(DM_a,DM_b,DM_block_ab.block(2,5,6,6));
- CALL_SUBTEST(check_kronecker_product(DM_block_ab.block(2,5,6,6)));
+ DM_block_ab.block<6,6>(2,5) = kroneckerProduct(DM_a,DM_b);
+ CALL_SUBTEST(check_kronecker_product(DM_block_ab.block<6,6>(2,5)));
// test kroneckerProduct(DM,DM,DM)
- MatrixXd DM_ab(1,5);
- DM_ab(0,0)=37.0;
- kroneckerProduct(DM_a,DM_b,DM_ab);
+ MatrixXd DM_ab = kroneckerProduct(DM_a,DM_b);
CALL_SUBTEST(check_kronecker_product(DM_ab));
// test kroneckerProduct(SM,DM,SM)
- SparseMatrix<double> SM_ab(1,20);
- SM_ab.insert(0,0)=37.0;
- kroneckerProduct(SM_a,DM_b,SM_ab);
+ SparseMatrix<double> SM_ab = kroneckerProduct(SM_a,DM_b);
CALL_SUBTEST(check_kronecker_product(SM_ab));
- SparseMatrix<double,RowMajor> SM_ab2(10,3);
- SM_ab2.insert(0,0)=37.0;
- kroneckerProduct(SM_a,DM_b,SM_ab2);
+ SparseMatrix<double,RowMajor> SM_ab2 = kroneckerProduct(SM_a,DM_b);
CALL_SUBTEST(check_kronecker_product(SM_ab2));
// test kroneckerProduct(DM,SM,SM)
SM_ab.insert(0,0)=37.0;
- kroneckerProduct(DM_a,SM_b,SM_ab);
+ SM_ab = kroneckerProduct(DM_a,SM_b);
CALL_SUBTEST(check_kronecker_product(SM_ab));
SM_ab2.insert(0,0)=37.0;
- kroneckerProduct(DM_a,SM_b,SM_ab2);
+ SM_ab2 = kroneckerProduct(DM_a,SM_b);
CALL_SUBTEST(check_kronecker_product(SM_ab2));
// test kroneckerProduct(SM,SM,SM)
SM_ab.resize(2,33);
SM_ab.insert(0,0)=37.0;
- kroneckerProduct(SM_a,SM_b,SM_ab);
+ SM_ab = kroneckerProduct(SM_a,SM_b);
CALL_SUBTEST(check_kronecker_product(SM_ab));
SM_ab2.resize(5,11);
SM_ab2.insert(0,0)=37.0;
- kroneckerProduct(SM_a,SM_b,SM_ab2);
+ SM_ab2 = kroneckerProduct(SM_a,SM_b);
CALL_SUBTEST(check_kronecker_product(SM_ab2));
// test kroneckerProduct(SM,SM,SM) with sparse pattern
@@ -163,17 +155,16 @@ void test_kronecker_product()
SM_b.finalize();
SM_ab.resize(1,1);
SM_ab.insert(0,0)=37.0;
- kroneckerProduct(SM_a,SM_b,SM_ab);
+ SM_ab = kroneckerProduct(SM_a,SM_b);
CALL_SUBTEST(check_sparse_kronecker_product(SM_ab));
// test dimension of result of kroneckerProduct(DM,DM,DM)
MatrixXd DM_a2(2,1);
MatrixXd DM_b2(5,4);
- MatrixXd DM_ab2;
- kroneckerProduct(DM_a2,DM_b2,DM_ab2);
+ MatrixXd DM_ab2 = kroneckerProduct(DM_a2,DM_b2);
CALL_SUBTEST(check_dimension(DM_ab2,2*5,1*4));
DM_a2.resize(10,9);
DM_b2.resize(4,8);
- kroneckerProduct(DM_a2,DM_b2,DM_ab2);
+ DM_ab2 = kroneckerProduct(DM_a2,DM_b2);
CALL_SUBTEST(check_dimension(DM_ab2,10*4,9*8));
}