static void parse_tetri(char *tetri_raw, t_tetrimino *t)
{
char **t_tab;
char *t_raw;
int i;
if (!(t_tab = ft_strsplit(tetri_raw, '\n')))
return (fillit_error_msg_exit("some split failed somewhere"));
if (!(t_raw = ft_strnew(16)))
return (fillit_error_msg_exit("some malloc failed somewhere"));
i = 0;
while (t_tab[i])
{
ft_strcpy(t_raw + (i * 4), t_tab[i]);
i++;
}
free_tab(&t_tab);
t->value = raw_to_binary_represention(t_raw);
t->pattern_index = get_matched_pattern_index(t->value);
if (t->pattern_index == -1)
return (fillit_error_msg_exit("invalid pattern"));
t->offset.x = 0;
t->offset.y = 0;
ft_strdel(&t_raw);
set_v(t);
}
void Hamiltonian::set_v(boost::python::list v_) {
/**
Update Hamiltonian velocities (all are real-valued scalars -the components of Python list) - Python-friendly
\param[in] v The vector of real-valued velocities to be used for Hamiltonian calculations.
The velocities are only needed for vibronic Hamiltonian (adiabatic representation) calculations.
Otherwise, they are not used.
Only status_adi is set to 0, so only adiabatic Hamiltonian is recomputed.
For future: in fact, we only need to update the vibronic Hamiltonian, so we still may save a lot, when adiabatic
calculations imply electronic structure calculations
*/
int sz = boost::python::len(v_);
vector<double> tmp_v(sz,0.0);
for(int i=0; i<sz; i++) {
tmp_v[i] = boost::python::extract<double>(v_[i]);
}
set_v(tmp_v);
}
Edge3D::Edge3D(Node3D* u, Node3D* v): m_u(0), m_v(0)
{
set_u(u);
set_v(v);
}
bool atomic_base<Base>::rev_sparse_hes(
const vector<Base>& x ,
const local::pod_vector<size_t>& x_index ,
const local::pod_vector<size_t>& y_index ,
const InternalSparsity& for_jac_sparsity ,
bool* rev_jac_flag ,
InternalSparsity& rev_hes_sparsity )
{ CPPAD_ASSERT_UNKNOWN( for_jac_sparsity.end() == rev_hes_sparsity.end() );
size_t q = rev_hes_sparsity.end();
size_t n = x_index.size();
size_t m = y_index.size();
bool ok = false;
size_t thread = thread_alloc::thread_num();
allocate_work(thread);
bool zero_empty = true;
bool input_empty = false;
bool transpose = false;
//
// vx
vector<bool> vx(n);
for(size_t j = 0; j < n; j++)
vx[j] = x_index[j] != 0;
//
// note that s and t are vectors so transpose does not matter for bool case
vector<bool> bool_s( work_[thread]->bool_s );
vector<bool> bool_t( work_[thread]->bool_t );
//
bool_s.resize(m);
bool_t.resize(n);
//
for(size_t i = 0; i < m; i++)
{ if( y_index[i] > 0 )
bool_s[i] = rev_jac_flag[ y_index[i] ];
}
//
std::string msg = ": atomic_base.rev_sparse_hes: returned false";
if( sparsity_ == pack_sparsity_enum )
{ vectorBool& pack_r( work_[thread]->pack_r );
vectorBool& pack_u( work_[thread]->pack_u );
vectorBool& pack_v( work_[thread]->pack_h );
//
pack_v.resize(n * q);
//
local::get_internal_sparsity(
transpose, x_index, for_jac_sparsity, pack_r
);
local::get_internal_sparsity(
transpose, y_index, rev_hes_sparsity, pack_u
);
//
ok = rev_sparse_hes(vx, bool_s, bool_t, q, pack_r, pack_u, pack_v, x);
if( ! ok )
ok = rev_sparse_hes(vx, bool_s, bool_t, q, pack_r, pack_u, pack_v);
if( ! ok )
{ msg = afun_name() + msg + " sparsity = pack_sparsity_enum";
CPPAD_ASSERT_KNOWN(false, msg.c_str());
}
local::set_internal_sparsity(zero_empty, input_empty,
transpose, x_index, rev_hes_sparsity, pack_v
);
}
else if( sparsity_ == bool_sparsity_enum )
{ vector<bool>& bool_r( work_[thread]->bool_r );
vector<bool>& bool_u( work_[thread]->bool_u );
vector<bool>& bool_v( work_[thread]->bool_h );
//
bool_v.resize(n * q);
//
local::get_internal_sparsity(
transpose, x_index, for_jac_sparsity, bool_r
);
local::get_internal_sparsity(
transpose, y_index, rev_hes_sparsity, bool_u
);
//
ok = rev_sparse_hes(vx, bool_s, bool_t, q, bool_r, bool_u, bool_v, x);
if( ! ok )
ok = rev_sparse_hes(vx, bool_s, bool_t, q, bool_r, bool_u, bool_v);
if( ! ok )
{ msg = afun_name() + msg + " sparsity = bool_sparsity_enum";
CPPAD_ASSERT_KNOWN(false, msg.c_str());
}
local::set_internal_sparsity(zero_empty, input_empty,
transpose, x_index, rev_hes_sparsity, bool_v
);
}
else
{ CPPAD_ASSERT_UNKNOWN( sparsity_ == set_sparsity_enum );
vector< std::set<size_t> >& set_r( work_[thread]->set_r );
vector< std::set<size_t> >& set_u( work_[thread]->set_u );
vector< std::set<size_t> >& set_v( work_[thread]->set_h );
//
set_v.resize(n);
//
local::get_internal_sparsity(
transpose, x_index, for_jac_sparsity, set_r
);
local::get_internal_sparsity(
transpose, y_index, rev_hes_sparsity, set_u
);
//
ok = rev_sparse_hes(vx, bool_s, bool_t, q, set_r, set_u, set_v, x);
if( ! ok )
ok = rev_sparse_hes(vx, bool_s, bool_t, q, set_r, set_u, set_v);
if( ! ok )
{ msg = afun_name() + msg + " sparsity = set_sparsity_enum";
CPPAD_ASSERT_KNOWN(false, msg.c_str());
}
local::set_internal_sparsity(zero_empty, input_empty,
transpose, x_index, rev_hes_sparsity, set_v
);
}
for(size_t j = 0; j < n; j++)
{ if( x_index[j] > 0 )
rev_jac_flag[ x_index[j] ] |= bool_t[j];
}
return ok;
}
