static void
nma_sparse_hessian(gmx_sparsematrix_t * sparse_hessian,
gmx_bool bM,
t_topology * top,
int neig,
real * eigenvalues,
real * eigenvectors)
{
int i, j, k;
int row, col;
real mass_fac;
int iatom, katom;
int natoms;
int ndim;
natoms = top->atoms.nr;
ndim = DIM*natoms;
/* Cannot check symmetry since we only store half matrix */
/* divide elements hess[i][j] by sqrt(mas[i])*sqrt(mas[j]) when required */
if (bM)
{
for (iatom = 0; (iatom < natoms); iatom++)
{
for (j = 0; (j < DIM); j++)
{
row = DIM*iatom+j;
for (k = 0; k < sparse_hessian->ndata[row]; k++)
{
col = sparse_hessian->data[row][k].col;
katom = col/3;
mass_fac = gmx_invsqrt(top->atoms.atom[iatom].m*top->atoms.atom[katom].m);
sparse_hessian->data[row][k].value *= mass_fac;
}
}
}
}
fprintf(stderr, "\nDiagonalizing to find eigenvectors 1 through %d...\n", neig);
fflush(stderr);
sparse_eigensolver(sparse_hessian, neig, eigenvalues, eigenvectors, 10000000);
/* Scale output eigenvectors */
if (bM && eigenvectors != NULL)
{
for (i = 0; i < neig; i++)
{
for (j = 0; j < natoms; j++)
{
mass_fac = gmx_invsqrt(top->atoms.atom[j].m);
for (k = 0; (k < DIM); k++)
{
eigenvectors[i*ndim+j*DIM+k] *= mass_fac;
}
}
}
}
}
static void
nma_sparse_hessian(gmx_sparsematrix_t *sparse_hessian,
gmx_bool bM,
const t_topology *top,
const std::vector<size_t> &atom_index,
int neig,
real *eigenvalues,
real *eigenvectors)
{
int i, k;
int row, col;
real mass_fac;
int katom;
size_t ndim;
ndim = DIM*atom_index.size();
/* Cannot check symmetry since we only store half matrix */
/* divide elements hess[i][j] by sqrt(mas[i])*sqrt(mas[j]) when required */
GMX_RELEASE_ASSERT(sparse_hessian != NULL, "NULL matrix pointer provided to nma_sparse_hessian");
if (bM)
{
for (size_t iatom = 0; (iatom < atom_index.size()); iatom++)
{
size_t ai = atom_index[iatom];
for (size_t j = 0; (j < DIM); j++)
{
row = DIM*iatom+j;
for (k = 0; k < sparse_hessian->ndata[row]; k++)
{
col = sparse_hessian->data[row][k].col;
katom = col/3;
size_t ak = atom_index[katom];
mass_fac = gmx::invsqrt(top->atoms.atom[ai].m*top->atoms.atom[ak].m);
sparse_hessian->data[row][k].value *= mass_fac;
}
}
}
}
fprintf(stderr, "\nDiagonalizing to find eigenvectors 1 through %d...\n", neig);
fflush(stderr);
sparse_eigensolver(sparse_hessian, neig, eigenvalues, eigenvectors, 10000000);
/* Scale output eigenvectors */
if (bM && eigenvectors != NULL)
{
for (i = 0; i < neig; i++)
{
for (size_t j = 0; j < atom_index.size(); j++)
{
size_t aj = atom_index[j];
mass_fac = gmx::invsqrt(top->atoms.atom[aj].m);
for (k = 0; (k < DIM); k++)
{
eigenvectors[i*ndim+j*DIM+k] *= mass_fac;
}
}
}
}
}