Files
Aurora/thirdparty/include/Spectra/MatOp/SparseSymMatProd.h
2023-06-02 10:49:02 +08:00

109 lines
3.6 KiB
C++

// Copyright (C) 2016-2022 Yixuan Qiu <yixuan.qiu@cos.name>
//
// 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 https://mozilla.org/MPL/2.0/.
#ifndef SPECTRA_SPARSE_SYM_MAT_PROD_H
#define SPECTRA_SPARSE_SYM_MAT_PROD_H
#include <Eigen/Core>
#include <Eigen/SparseCore>
namespace Spectra {
///
/// \ingroup MatOp
///
/// This class defines the matrix-vector multiplication operation on a
/// sparse real symmetric matrix \f$A\f$, i.e., calculating \f$y=Ax\f$ for any vector
/// \f$x\f$. It is mainly used in the SymEigsSolver eigen solver.
///
/// \tparam Scalar_ The element type of the matrix, for example,
/// `float`, `double`, and `long double`.
/// \tparam Uplo Either `Eigen::Lower` or `Eigen::Upper`, indicating which
/// triangular part of the matrix is used.
/// \tparam Flags Either `Eigen::ColMajor` or `Eigen::RowMajor`, indicating
/// the storage format of the input matrix.
/// \tparam StorageIndex The type of the indices for the sparse matrix.
///
template <typename Scalar_, int Uplo = Eigen::Lower, int Flags = Eigen::ColMajor, typename StorageIndex = int>
class SparseSymMatProd
{
public:
///
/// Element type of the matrix.
///
using Scalar = Scalar_;
private:
using Index = Eigen::Index;
using Vector = Eigen::Matrix<Scalar, Eigen::Dynamic, 1>;
using MapConstVec = Eigen::Map<const Vector>;
using MapVec = Eigen::Map<Vector>;
using Matrix = Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>;
using SparseMatrix = Eigen::SparseMatrix<Scalar, Flags, StorageIndex>;
using ConstGenericSparseMatrix = const Eigen::Ref<const SparseMatrix>;
ConstGenericSparseMatrix m_mat;
public:
///
/// Constructor to create the matrix operation object.
///
/// \param mat An **Eigen** sparse matrix object, whose type can be
/// `Eigen::SparseMatrix<Scalar, ...>` or its mapped version
/// `Eigen::Map<Eigen::SparseMatrix<Scalar, ...> >`.
///
template <typename Derived>
SparseSymMatProd(const Eigen::SparseMatrixBase<Derived>& mat) :
m_mat(mat)
{
static_assert(
static_cast<int>(Derived::PlainObject::IsRowMajor) == static_cast<int>(SparseMatrix::IsRowMajor),
"SparseSymMatProd: the \"Flags\" template parameter does not match the input matrix (Eigen::ColMajor/Eigen::RowMajor)");
}
///
/// Return the number of rows of the underlying matrix.
///
Index rows() const { return m_mat.rows(); }
///
/// Return the number of columns of the underlying matrix.
///
Index cols() const { return m_mat.cols(); }
///
/// Perform the matrix-vector multiplication operation \f$y=Ax\f$.
///
/// \param x_in Pointer to the \f$x\f$ vector.
/// \param y_out Pointer to the \f$y\f$ vector.
///
// y_out = A * x_in
void perform_op(const Scalar* x_in, Scalar* y_out) const
{
MapConstVec x(x_in, m_mat.cols());
MapVec y(y_out, m_mat.rows());
y.noalias() = m_mat.template selfadjointView<Uplo>() * x;
}
///
/// Perform the matrix-matrix multiplication operation \f$y=Ax\f$.
///
Matrix operator*(const Eigen::Ref<const Matrix>& mat_in) const
{
return m_mat.template selfadjointView<Uplo>() * mat_in;
}
///
/// Extract (i,j) element of the underlying matrix.
///
Scalar operator()(Index i, Index j) const
{
return m_mat.coeff(i, j);
}
};
} // namespace Spectra
#endif // SPECTRA_SPARSE_SYM_MAT_PROD_H