string SpikingGroup::get_output_line(NeuronID i)
{
stringstream oss;
for ( map<string,gsl_vector_float *>::const_iterator iter = state_vector.begin() ;
iter != state_vector.end() ;
++iter ) {
oss << scientific << gsl_vector_float_get( iter->second, i ) << " ";
}
for ( NeuronID k = 0 ; k < pretraces.size() ; k++ ) {
// TODO this is actually a bug and only a part of the pretrace gets saved this way
for ( NeuronID l = 0 ; l < get_locked_range() ; ++l ) {
NeuronID t = get_locked_range()*(i)+l;
if ( t < get_size() )
oss << pretraces[k]->get(t) << " ";
else
oss << 0.0 << " ";
}
}
for ( NeuronID k = 0 ; k < posttraces.size() ; k++ ) {
oss << posttraces[k]->get(i) << " ";
}
oss << "\n";
return oss.str();
}
int
gsl_linalg_bidiag_unpack2_float (gsl_matrix_float * A,
gsl_vector_float * tau_U,
gsl_vector_float * tau_V,
gsl_matrix_float * V)
{
const size_t M = A->size1;
const size_t N = A->size2;
const size_t K = GSL_MIN(M, N);
if (M < N)
{
GSL_ERROR ("matrix A must have M >= N", GSL_EBADLEN);
}
else if (tau_U->size != K)
{
GSL_ERROR ("size of tau must be MIN(M,N)", GSL_EBADLEN);
}
else if (tau_V->size + 1 != K)
{
GSL_ERROR ("size of tau must be MIN(M,N) - 1", GSL_EBADLEN);
}
else if (V->size1 != N || V->size2 != N)
{
GSL_ERROR ("size of V must be N x N", GSL_EBADLEN);
}
else
{
size_t i, j;
/* Initialize V to the identity */
gsl_matrix_float_set_identity (V);
for (i = N - 1; i > 0 && i--;)
{
/* Householder row transformation to accumulate V */
gsl_vector_float_const_view r = gsl_matrix_float_const_row (A, i);
gsl_vector_float_const_view h =
gsl_vector_float_const_subvector (&r.vector, i + 1, N - (i+1));
float ti = gsl_vector_float_get (tau_V, i);
gsl_matrix_float_view m =
gsl_matrix_float_submatrix (V, i + 1, i + 1, N-(i+1), N-(i+1));
gsl_linalg_householder_hm_float (ti, &h.vector, &m.matrix);
}
/* Copy superdiagonal into tau_v */
for (i = 0; i < N - 1; i++)
{
float Aij = gsl_matrix_float_get (A, i, i+1);
gsl_vector_float_set (tau_V, i, Aij);
}
/* Allow U to be unpacked into the same memory as A, copy
diagonal into tau_U */
for (j = N; j > 0 && j--;)
{
/* Householder column transformation to accumulate U */
float tj = gsl_vector_float_get (tau_U, j);
float Ajj = gsl_matrix_float_get (A, j, j);
gsl_matrix_float_view m = gsl_matrix_float_submatrix (A, j, j, M-j, N-j);
gsl_vector_float_set (tau_U, j, Ajj);
gsl_linalg_householder_hm1_float (tj, &m.matrix);
}
return GSL_SUCCESS;
}
}
AurynFloat TIFGroup::get_bg_current(NeuronID i) {
if ( localrank(i) )
return gsl_vector_float_get ( bg_current , global2rank(i) ) ;
else
return 0;
}
