Aurora/thirdparty/include/Spectra/MatOp/SparseGenMatProd.h

// 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_GEN_MAT_PROD_H
#define SPECTRA_SPARSE_GEN_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 matrix \f$A\f$, i.e., calculating \f$y=Ax\f$ for any vector
/// \f$x\f$. It is mainly used in the GenEigsSolver and SymEigsSolver
/// eigen solvers.
///
/// \tparam Scalar_      The element type of the matrix, for example,
///                      `float`, `double`, and `long double`.
/// \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 Flags = Eigen::ColMajor, typename StorageIndex = int>
class SparseGenMatProd
{
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>;

    const Eigen::Ref<const Eigen::SparseMatrix<double, Eigen::ColMajor, int>> 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>
    SparseGenMatProd(const Eigen::SparseMatrixBase<Derived>& mat) :
        m_mat(mat)
    {
        static_assert(
            static_cast<int>(Derived::PlainObject::IsRowMajor) == static_cast<int>(SparseMatrix::IsRowMajor),
            "SparseGenMatProd: 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());
        Eigen::VectorXd t = m_mat * x;
        Eigen::VectorXd t2 = t.transpose()*m_mat;
        y.noalias() = t2;
    }

    ///
    /// Perform the matrix-matrix multiplication operation \f$y=Ax\f$.
    ///
    Matrix operator*(const Eigen::Ref<const Matrix>& mat_in) const
    {
        return m_mat * 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_GEN_MAT_PROD_H