Initial import of eigen 3.1.1
Added a README.android and a MODULE_LICENSE_MPL2 file.
Added empty Android.mk and CleanSpec.mk to optimize Android build.
Non MPL2 license code is disabled in ./Eigen/src/Core/util/NonMPL2.h.
Trying to include such files will lead to an error.
Change-Id: I0e148b7c3e83999bcc4dfaa5809d33bfac2aac32
diff --git a/Eigen/src/SparseCore/SparseSelfAdjointView.h b/Eigen/src/SparseCore/SparseSelfAdjointView.h
new file mode 100644
index 0000000..86ec0a6
--- /dev/null
+++ b/Eigen/src/SparseCore/SparseSelfAdjointView.h
@@ -0,0 +1,480 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// 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 EIGEN_SPARSE_SELFADJOINTVIEW_H
+#define EIGEN_SPARSE_SELFADJOINTVIEW_H
+
+namespace Eigen {
+
+/** \ingroup SparseCore_Module
+ * \class SparseSelfAdjointView
+ *
+ * \brief Pseudo expression to manipulate a triangular sparse matrix as a selfadjoint matrix.
+ *
+ * \param MatrixType the type of the dense matrix storing the coefficients
+ * \param UpLo can be either \c #Lower or \c #Upper
+ *
+ * This class is an expression of a sefladjoint matrix from a triangular part of a matrix
+ * with given dense storage of the coefficients. It is the return type of MatrixBase::selfadjointView()
+ * and most of the time this is the only way that it is used.
+ *
+ * \sa SparseMatrixBase::selfadjointView()
+ */
+template<typename Lhs, typename Rhs, int UpLo>
+class SparseSelfAdjointTimeDenseProduct;
+
+template<typename Lhs, typename Rhs, int UpLo>
+class DenseTimeSparseSelfAdjointProduct;
+
+namespace internal {
+
+template<typename MatrixType, unsigned int UpLo>
+struct traits<SparseSelfAdjointView<MatrixType,UpLo> > : traits<MatrixType> {
+};
+
+template<int SrcUpLo,int DstUpLo,typename MatrixType,int DestOrder>
+void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm = 0);
+
+template<int UpLo,typename MatrixType,int DestOrder>
+void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm = 0);
+
+}
+
+template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView
+ : public EigenBase<SparseSelfAdjointView<MatrixType,UpLo> >
+{
+ public:
+
+ typedef typename MatrixType::Scalar Scalar;
+ typedef typename MatrixType::Index Index;
+ typedef Matrix<Index,Dynamic,1> VectorI;
+ typedef typename MatrixType::Nested MatrixTypeNested;
+ typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested;
+
+ inline SparseSelfAdjointView(const MatrixType& matrix) : m_matrix(matrix)
+ {
+ eigen_assert(rows()==cols() && "SelfAdjointView is only for squared matrices");
+ }
+
+ inline Index rows() const { return m_matrix.rows(); }
+ inline Index cols() const { return m_matrix.cols(); }
+
+ /** \internal \returns a reference to the nested matrix */
+ const _MatrixTypeNested& matrix() const { return m_matrix; }
+ _MatrixTypeNested& matrix() { return m_matrix.const_cast_derived(); }
+
+ /** Efficient sparse self-adjoint matrix times dense vector/matrix product */
+ template<typename OtherDerived>
+ SparseSelfAdjointTimeDenseProduct<MatrixType,OtherDerived,UpLo>
+ operator*(const MatrixBase<OtherDerived>& rhs) const
+ {
+ return SparseSelfAdjointTimeDenseProduct<MatrixType,OtherDerived,UpLo>(m_matrix, rhs.derived());
+ }
+
+ /** Efficient dense vector/matrix times sparse self-adjoint matrix product */
+ template<typename OtherDerived> friend
+ DenseTimeSparseSelfAdjointProduct<OtherDerived,MatrixType,UpLo>
+ operator*(const MatrixBase<OtherDerived>& lhs, const SparseSelfAdjointView& rhs)
+ {
+ return DenseTimeSparseSelfAdjointProduct<OtherDerived,_MatrixTypeNested,UpLo>(lhs.derived(), rhs.m_matrix);
+ }
+
+ /** Perform a symmetric rank K update of the selfadjoint matrix \c *this:
+ * \f$ this = this + \alpha ( u u^* ) \f$ where \a u is a vector or matrix.
+ *
+ * \returns a reference to \c *this
+ *
+ * To perform \f$ this = this + \alpha ( u^* u ) \f$ you can simply
+ * call this function with u.adjoint().
+ */
+ template<typename DerivedU>
+ SparseSelfAdjointView& rankUpdate(const SparseMatrixBase<DerivedU>& u, Scalar alpha = Scalar(1));
+
+ /** \internal triggered by sparse_matrix = SparseSelfadjointView; */
+ template<typename DestScalar,int StorageOrder> void evalTo(SparseMatrix<DestScalar,StorageOrder,Index>& _dest) const
+ {
+ internal::permute_symm_to_fullsymm<UpLo>(m_matrix, _dest);
+ }
+
+ template<typename DestScalar> void evalTo(DynamicSparseMatrix<DestScalar,ColMajor,Index>& _dest) const
+ {
+ // TODO directly evaluate into _dest;
+ SparseMatrix<DestScalar,ColMajor,Index> tmp(_dest.rows(),_dest.cols());
+ internal::permute_symm_to_fullsymm<UpLo>(m_matrix, tmp);
+ _dest = tmp;
+ }
+
+ /** \returns an expression of P H P^-1 */
+ SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo> twistedBy(const PermutationMatrix<Dynamic,Dynamic,Index>& perm) const
+ {
+ return SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo>(m_matrix, perm);
+ }
+
+ template<typename SrcMatrixType,int SrcUpLo>
+ SparseSelfAdjointView& operator=(const SparseSymmetricPermutationProduct<SrcMatrixType,SrcUpLo>& permutedMatrix)
+ {
+ permutedMatrix.evalTo(*this);
+ return *this;
+ }
+
+
+ SparseSelfAdjointView& operator=(const SparseSelfAdjointView& src)
+ {
+ PermutationMatrix<Dynamic> pnull;
+ return *this = src.twistedBy(pnull);
+ }
+
+ template<typename SrcMatrixType,unsigned int SrcUpLo>
+ SparseSelfAdjointView& operator=(const SparseSelfAdjointView<SrcMatrixType,SrcUpLo>& src)
+ {
+ PermutationMatrix<Dynamic> pnull;
+ return *this = src.twistedBy(pnull);
+ }
+
+
+ // const SparseLLT<PlainObject, UpLo> llt() const;
+ // const SparseLDLT<PlainObject, UpLo> ldlt() const;
+
+ protected:
+
+ typename MatrixType::Nested m_matrix;
+ mutable VectorI m_countPerRow;
+ mutable VectorI m_countPerCol;
+};
+
+/***************************************************************************
+* Implementation of SparseMatrixBase methods
+***************************************************************************/
+
+template<typename Derived>
+template<unsigned int UpLo>
+const SparseSelfAdjointView<Derived, UpLo> SparseMatrixBase<Derived>::selfadjointView() const
+{
+ return derived();
+}
+
+template<typename Derived>
+template<unsigned int UpLo>
+SparseSelfAdjointView<Derived, UpLo> SparseMatrixBase<Derived>::selfadjointView()
+{
+ return derived();
+}
+
+/***************************************************************************
+* Implementation of SparseSelfAdjointView methods
+***************************************************************************/
+
+template<typename MatrixType, unsigned int UpLo>
+template<typename DerivedU>
+SparseSelfAdjointView<MatrixType,UpLo>&
+SparseSelfAdjointView<MatrixType,UpLo>::rankUpdate(const SparseMatrixBase<DerivedU>& u, Scalar alpha)
+{
+ SparseMatrix<Scalar,MatrixType::Flags&RowMajorBit?RowMajor:ColMajor> tmp = u * u.adjoint();
+ if(alpha==Scalar(0))
+ m_matrix.const_cast_derived() = tmp.template triangularView<UpLo>();
+ else
+ m_matrix.const_cast_derived() += alpha * tmp.template triangularView<UpLo>();
+
+ return *this;
+}
+
+/***************************************************************************
+* Implementation of sparse self-adjoint time dense matrix
+***************************************************************************/
+
+namespace internal {
+template<typename Lhs, typename Rhs, int UpLo>
+struct traits<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo> >
+ : traits<ProductBase<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> >
+{
+ typedef Dense StorageKind;
+};
+}
+
+template<typename Lhs, typename Rhs, int UpLo>
+class SparseSelfAdjointTimeDenseProduct
+ : public ProductBase<SparseSelfAdjointTimeDenseProduct<Lhs,Rhs,UpLo>, Lhs, Rhs>
+{
+ public:
+ EIGEN_PRODUCT_PUBLIC_INTERFACE(SparseSelfAdjointTimeDenseProduct)
+
+ SparseSelfAdjointTimeDenseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
+ {}
+
+ template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
+ {
+ // TODO use alpha
+ eigen_assert(alpha==Scalar(1) && "alpha != 1 is not implemented yet, sorry");
+ typedef typename internal::remove_all<Lhs>::type _Lhs;
+ typedef typename internal::remove_all<Rhs>::type _Rhs;
+ typedef typename _Lhs::InnerIterator LhsInnerIterator;
+ enum {
+ LhsIsRowMajor = (_Lhs::Flags&RowMajorBit)==RowMajorBit,
+ ProcessFirstHalf =
+ ((UpLo&(Upper|Lower))==(Upper|Lower))
+ || ( (UpLo&Upper) && !LhsIsRowMajor)
+ || ( (UpLo&Lower) && LhsIsRowMajor),
+ ProcessSecondHalf = !ProcessFirstHalf
+ };
+ for (Index j=0; j<m_lhs.outerSize(); ++j)
+ {
+ LhsInnerIterator i(m_lhs,j);
+ if (ProcessSecondHalf)
+ {
+ while (i && i.index()<j) ++i;
+ if(i && i.index()==j)
+ {
+ dest.row(j) += i.value() * m_rhs.row(j);
+ ++i;
+ }
+ }
+ for(; (ProcessFirstHalf ? i && i.index() < j : i) ; ++i)
+ {
+ Index a = LhsIsRowMajor ? j : i.index();
+ Index b = LhsIsRowMajor ? i.index() : j;
+ typename Lhs::Scalar v = i.value();
+ dest.row(a) += (v) * m_rhs.row(b);
+ dest.row(b) += internal::conj(v) * m_rhs.row(a);
+ }
+ if (ProcessFirstHalf && i && (i.index()==j))
+ dest.row(j) += i.value() * m_rhs.row(j);
+ }
+ }
+
+ private:
+ SparseSelfAdjointTimeDenseProduct& operator=(const SparseSelfAdjointTimeDenseProduct&);
+};
+
+namespace internal {
+template<typename Lhs, typename Rhs, int UpLo>
+struct traits<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo> >
+ : traits<ProductBase<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo>, Lhs, Rhs> >
+{};
+}
+
+template<typename Lhs, typename Rhs, int UpLo>
+class DenseTimeSparseSelfAdjointProduct
+ : public ProductBase<DenseTimeSparseSelfAdjointProduct<Lhs,Rhs,UpLo>, Lhs, Rhs>
+{
+ public:
+ EIGEN_PRODUCT_PUBLIC_INTERFACE(DenseTimeSparseSelfAdjointProduct)
+
+ DenseTimeSparseSelfAdjointProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
+ {}
+
+ template<typename Dest> void scaleAndAddTo(Dest& /*dest*/, Scalar /*alpha*/) const
+ {
+ // TODO
+ }
+
+ private:
+ DenseTimeSparseSelfAdjointProduct& operator=(const DenseTimeSparseSelfAdjointProduct&);
+};
+
+/***************************************************************************
+* Implementation of symmetric copies and permutations
+***************************************************************************/
+namespace internal {
+
+template<typename MatrixType, int UpLo>
+struct traits<SparseSymmetricPermutationProduct<MatrixType,UpLo> > : traits<MatrixType> {
+};
+
+template<int UpLo,typename MatrixType,int DestOrder>
+void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm)
+{
+ typedef typename MatrixType::Index Index;
+ typedef typename MatrixType::Scalar Scalar;
+ typedef SparseMatrix<Scalar,DestOrder,Index> Dest;
+ typedef Matrix<Index,Dynamic,1> VectorI;
+
+ Dest& dest(_dest.derived());
+ enum {
+ StorageOrderMatch = int(Dest::IsRowMajor) == int(MatrixType::IsRowMajor)
+ };
+
+ Index size = mat.rows();
+ VectorI count;
+ count.resize(size);
+ count.setZero();
+ dest.resize(size,size);
+ for(Index j = 0; j<size; ++j)
+ {
+ Index jp = perm ? perm[j] : j;
+ for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
+ {
+ Index i = it.index();
+ Index r = it.row();
+ Index c = it.col();
+ Index ip = perm ? perm[i] : i;
+ if(UpLo==(Upper|Lower))
+ count[StorageOrderMatch ? jp : ip]++;
+ else if(r==c)
+ count[ip]++;
+ else if(( UpLo==Lower && r>c) || ( UpLo==Upper && r<c))
+ {
+ count[ip]++;
+ count[jp]++;
+ }
+ }
+ }
+ Index nnz = count.sum();
+
+ // reserve space
+ dest.resizeNonZeros(nnz);
+ dest.outerIndexPtr()[0] = 0;
+ for(Index j=0; j<size; ++j)
+ dest.outerIndexPtr()[j+1] = dest.outerIndexPtr()[j] + count[j];
+ for(Index j=0; j<size; ++j)
+ count[j] = dest.outerIndexPtr()[j];
+
+ // copy data
+ for(Index j = 0; j<size; ++j)
+ {
+ for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
+ {
+ Index i = it.index();
+ Index r = it.row();
+ Index c = it.col();
+
+ Index jp = perm ? perm[j] : j;
+ Index ip = perm ? perm[i] : i;
+
+ if(UpLo==(Upper|Lower))
+ {
+ Index k = count[StorageOrderMatch ? jp : ip]++;
+ dest.innerIndexPtr()[k] = StorageOrderMatch ? ip : jp;
+ dest.valuePtr()[k] = it.value();
+ }
+ else if(r==c)
+ {
+ Index k = count[ip]++;
+ dest.innerIndexPtr()[k] = ip;
+ dest.valuePtr()[k] = it.value();
+ }
+ else if(( (UpLo&Lower)==Lower && r>c) || ( (UpLo&Upper)==Upper && r<c))
+ {
+ if(!StorageOrderMatch)
+ std::swap(ip,jp);
+ Index k = count[jp]++;
+ dest.innerIndexPtr()[k] = ip;
+ dest.valuePtr()[k] = it.value();
+ k = count[ip]++;
+ dest.innerIndexPtr()[k] = jp;
+ dest.valuePtr()[k] = internal::conj(it.value());
+ }
+ }
+ }
+}
+
+template<int _SrcUpLo,int _DstUpLo,typename MatrixType,int DstOrder>
+void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DstOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm)
+{
+ typedef typename MatrixType::Index Index;
+ typedef typename MatrixType::Scalar Scalar;
+ SparseMatrix<Scalar,DstOrder,Index>& dest(_dest.derived());
+ typedef Matrix<Index,Dynamic,1> VectorI;
+ enum {
+ SrcOrder = MatrixType::IsRowMajor ? RowMajor : ColMajor,
+ StorageOrderMatch = int(SrcOrder) == int(DstOrder),
+ DstUpLo = DstOrder==RowMajor ? (_DstUpLo==Upper ? Lower : Upper) : _DstUpLo,
+ SrcUpLo = SrcOrder==RowMajor ? (_SrcUpLo==Upper ? Lower : Upper) : _SrcUpLo
+ };
+
+ Index size = mat.rows();
+ VectorI count(size);
+ count.setZero();
+ dest.resize(size,size);
+ for(Index j = 0; j<size; ++j)
+ {
+ Index jp = perm ? perm[j] : j;
+ for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
+ {
+ Index i = it.index();
+ if((int(SrcUpLo)==int(Lower) && i<j) || (int(SrcUpLo)==int(Upper) && i>j))
+ continue;
+
+ Index ip = perm ? perm[i] : i;
+ count[int(DstUpLo)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++;
+ }
+ }
+ dest.outerIndexPtr()[0] = 0;
+ for(Index j=0; j<size; ++j)
+ dest.outerIndexPtr()[j+1] = dest.outerIndexPtr()[j] + count[j];
+ dest.resizeNonZeros(dest.outerIndexPtr()[size]);
+ for(Index j=0; j<size; ++j)
+ count[j] = dest.outerIndexPtr()[j];
+
+ for(Index j = 0; j<size; ++j)
+ {
+
+ for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
+ {
+ Index i = it.index();
+ if((int(SrcUpLo)==int(Lower) && i<j) || (int(SrcUpLo)==int(Upper) && i>j))
+ continue;
+
+ Index jp = perm ? perm[j] : j;
+ Index ip = perm? perm[i] : i;
+
+ Index k = count[int(DstUpLo)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++;
+ dest.innerIndexPtr()[k] = int(DstUpLo)==int(Lower) ? (std::max)(ip,jp) : (std::min)(ip,jp);
+
+ if(!StorageOrderMatch) std::swap(ip,jp);
+ if( ((int(DstUpLo)==int(Lower) && ip<jp) || (int(DstUpLo)==int(Upper) && ip>jp)))
+ dest.valuePtr()[k] = conj(it.value());
+ else
+ dest.valuePtr()[k] = it.value();
+ }
+ }
+}
+
+}
+
+template<typename MatrixType,int UpLo>
+class SparseSymmetricPermutationProduct
+ : public EigenBase<SparseSymmetricPermutationProduct<MatrixType,UpLo> >
+{
+ public:
+ typedef typename MatrixType::Scalar Scalar;
+ typedef typename MatrixType::Index Index;
+ protected:
+ typedef PermutationMatrix<Dynamic,Dynamic,Index> Perm;
+ public:
+ typedef Matrix<Index,Dynamic,1> VectorI;
+ typedef typename MatrixType::Nested MatrixTypeNested;
+ typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested;
+
+ SparseSymmetricPermutationProduct(const MatrixType& mat, const Perm& perm)
+ : m_matrix(mat), m_perm(perm)
+ {}
+
+ inline Index rows() const { return m_matrix.rows(); }
+ inline Index cols() const { return m_matrix.cols(); }
+
+ template<typename DestScalar, int Options, typename DstIndex>
+ void evalTo(SparseMatrix<DestScalar,Options,DstIndex>& _dest) const
+ {
+ internal::permute_symm_to_fullsymm<UpLo>(m_matrix,_dest,m_perm.indices().data());
+ }
+
+ template<typename DestType,unsigned int DestUpLo> void evalTo(SparseSelfAdjointView<DestType,DestUpLo>& dest) const
+ {
+ internal::permute_symm_to_symm<UpLo,DestUpLo>(m_matrix,dest.matrix(),m_perm.indices().data());
+ }
+
+ protected:
+ MatrixTypeNested m_matrix;
+ const Perm& m_perm;
+
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPARSE_SELFADJOINTVIEW_H