eigs_sp_t.cc

// -*- mode: c++; fill-column: 80; c-basic-offset: 2; indent-tabs-mode: nil -*-
/*
    Copyright (c) 2010 Juan Jose Garcia Ripoll

    Tensor is free software; you can redistribute it and/or modify it
    under the terms of the GNU Library General Public License as published
    by the Free Software Foundation; either version 2 of the License, or
    (at your option) any later version.

    This program is distributed in the hope that it will be useful,
    but WITHOUT ANY WARRANTY; without even the implied warranty of
    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
    GNU Library General Public License for more details.

    You should have received a copy of the GNU General Public License along
    with this program; if not, write to the Free Software Foundation, Inc.,
    51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
*/

//----------------------------------------------------------------------
// ARPACK DRIVER FOR NONSYMMETRIC SPARSE EIGENVALUE PROBLEMS
//

#include "linalg.h"
#include "arpack.h"

Tensor<ELT_T>
eigs(const Sparse<ELT_T> &A, int eig_type, size_t neig,
     Tensor<ELT_T> *eigenvectors,
     const Tensor::elt_t *initial_guess)
{
    Arpack::EigType t = (Arpack::EigType)eig_type;
    size_t n = A.columns();

    if (n <= 10) {
        return eigs(full(A), t, neig, eigenvectors, initial_guess);
    }

    if (A.rows() != n) {
        std::cerr << "In eigs(): Can only compute eigenvalues of square matrices.";
        myabort();
    }

    Arpack data(A.columns(), t, neig);

    if (initial_guess)
        data.set_start_vector(initial_guess);

    while (data.update() < Arpack::Finished) {
        data.set_y(mmult(A, data.get_x()));
    }
    if (data.get_status() == Arpack::Finished) {
        return data.get_data(eigenvectors);
    } else {
        std::cerr << data.error_message() << '\n';
        myabort();
    }
    return Tensor<ELT_T>();
}