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new feature: copy from a sparse selfadjoint view to a full sparse matrix
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@ -108,7 +108,7 @@ class DynamicSparseMatrix
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/** \returns a reference to the coefficient value at given position \a row, \a col
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* This operation involes a log(rho*outer_size) binary search. If the coefficient does not
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* exist yet, then a sorted insertion Indexo a sequential buffer is performed.
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* exist yet, then a sorted insertion into a sequential buffer is performed.
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*/
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inline Scalar& coeffRef(Index row, Index col)
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{
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@ -69,6 +69,7 @@ class SparseMatrix
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{
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public:
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EIGEN_SPARSE_PUBLIC_INTERFACE(SparseMatrix)
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using Base::operator=;
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EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, +=)
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EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, -=)
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// FIXME: why are these operator already alvailable ???
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@ -46,6 +46,16 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
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typedef typename internal::traits<Derived>::Index Index;
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typedef SparseMatrixBase StorageBaseType;
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typedef EigenBase<Derived> Base;
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template<typename OtherDerived>
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Derived& operator=(const EigenBase<OtherDerived> &other)
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{
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other.derived().evalTo(derived());
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return derived();
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}
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// using Base::operator=;
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enum {
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@ -173,7 +183,7 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
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Derived& markAsRValue() { m_isRValue = true; return derived(); }
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SparseMatrixBase() : m_isRValue(false) { /* TODO check flags */ }
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inline Derived& operator=(const Derived& other)
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{
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// std::cout << "Derived& operator=(const Derived& other)\n";
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@ -45,12 +45,24 @@ class SparseSelfAdjointTimeDenseProduct;
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template<typename Lhs, typename Rhs, int UpLo>
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class DenseTimeSparseSelfAdjointProduct;
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namespace internal {
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template<typename MatrixType, unsigned int UpLo>
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struct traits<SparseSelfAdjointView<MatrixType,UpLo> > : traits<MatrixType> {
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};
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}
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template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView
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: public EigenBase<SparseSelfAdjointView<MatrixType,UpLo> >
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{
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public:
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typedef typename MatrixType::Scalar Scalar;
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typedef typename MatrixType::Index Index;
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typedef Matrix<Index,Dynamic,1> VectorI;
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typedef typename MatrixType::Nested MatrixTypeNested;
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typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested;
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inline SparseSelfAdjointView(const MatrixType& matrix) : m_matrix(matrix)
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{
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@ -77,7 +89,7 @@ template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView
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DenseTimeSparseSelfAdjointProduct<OtherDerived,MatrixType,UpLo>
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operator*(const MatrixBase<OtherDerived>& lhs, const SparseSelfAdjointView& rhs)
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{
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return DenseTimeSparseSelfAdjointProduct<OtherDerived,MatrixType,UpLo>(lhs.derived(), rhs.m_matrix);
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return DenseTimeSparseSelfAdjointProduct<OtherDerived,_MatrixTypeNested,UpLo>(lhs.derived(), rhs.m_matrix);
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}
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/** Perform a symmetric rank K update of the selfadjoint matrix \c *this:
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@ -93,6 +105,70 @@ template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView
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*/
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template<typename DerivedU>
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SparseSelfAdjointView& rankUpdate(const SparseMatrixBase<DerivedU>& u, Scalar alpha = Scalar(1));
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/** \internal triggered by sparse_matrix = SparseSelfadjointView; */
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template<typename DestScalar> void evalTo(SparseMatrix<DestScalar>& _dest) const
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{
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typedef SparseMatrix<DestScalar> Dest;
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Dest& dest(_dest.derived());
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enum {
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StorageOrderMatch = Dest::IsRowMajor == _MatrixTypeNested::IsRowMajor
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};
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VectorI count = Dest::IsRowMajor ? m_countPerRow : m_countPerCol;
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Index size = m_matrix.rows();
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count.resize(size);
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count.setZero();
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dest.resize(size,size);
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for(Index j = 0; j<size; ++j)
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{
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for(typename _MatrixTypeNested::InnerIterator it(m_matrix,j); it; ++it)
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{
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Index i = it.index();
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if(i==j)
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count[i]++;
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else if((UpLo==Lower && i>j) || (UpLo==Upper && i<j))
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{
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count[i]++;
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count[j]++;
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}
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}
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}
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Index nnz = count.sum();
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// reserve space
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dest.reserve(nnz);
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dest._outerIndexPtr()[0] = 0;
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for(Index j=0; j<size; ++j)
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dest._outerIndexPtr()[j+1] = dest._outerIndexPtr()[j] + count[j];
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for(Index j=0; j<size; ++j)
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count[j] = dest._outerIndexPtr()[j];
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// copy data
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for(Index j = 0; j<size; ++j)
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{
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for(typename _MatrixTypeNested::InnerIterator it(m_matrix,j); it; ++it)
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{
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Index i = it.index();
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if(i==j)
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{
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int k = count[i]++;
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dest._innerIndexPtr()[k] = i;
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dest._valuePtr()[k] = it.value();
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}
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else if((UpLo==Lower && i>j) || (UpLo==Upper && i<j))
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{
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int k = count[j]++;
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dest._innerIndexPtr()[k] = i;
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dest._valuePtr()[k] = it.value();
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k = count[i]++;
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dest._innerIndexPtr()[k] = j;
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dest._valuePtr()[k] = internal::conj(it.value());
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}
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}
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}
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}
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// const SparseLLT<PlainObject, UpLo> llt() const;
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// const SparseLDLT<PlainObject, UpLo> ldlt() const;
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@ -100,6 +176,8 @@ template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView
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protected:
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const typename MatrixType::Nested m_matrix;
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VectorI m_countPerRow;
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VectorI m_countPerCol;
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};
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/***************************************************************************
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@ -133,7 +211,7 @@ SparseSelfAdjointView<MatrixType,UpLo>::rankUpdate(const SparseMatrixBase<Derive
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if(alpha==Scalar(0))
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m_matrix.const_cast_derived() = tmp.template triangularView<UpLo>();
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else
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m_matrix.const_cast_derived() /*+*/= alpha * tmp.template triangularView<UpLo>();
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m_matrix.const_cast_derived() += alpha * tmp.template triangularView<UpLo>();
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return *this;
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}
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@ -251,10 +251,21 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
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VERIFY_IS_APPROX(m2, refM2);
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}
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// test selfadjointView
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{
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DenseMatrix refMat2(rows, rows), refMat3(rows, rows);
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SparseMatrixType m2(rows, rows), m3(rows, rows);
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initSparse<Scalar>(density, refMat2, m2);
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refMat3 = refMat2.template selfadjointView<Lower>();
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m3 = m2.template selfadjointView<Lower>();
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VERIFY_IS_APPROX(m3, refMat3);
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}
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// test sparseView
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{
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DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
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SparseMatrixType m2(rows, rows);
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initSparse<Scalar>(density, refMat2, m2);
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VERIFY_IS_APPROX(m2.eval(), refMat2.sparseView().eval());
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}
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}
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