void pcnn::simulate(const unsigned int steps, const pcnn_stimulus & stimulus, pcnn_dynamic & output_dynamic) {
output_dynamic.resize(steps, size());
for (unsigned int i = 0; i < steps; i++) {
calculate_states(stimulus);
store_dynamic(i, output_dynamic);
}
}
arma::Mat<double> RobotChasing::calculate_probabilities()
{
calculate_states();
arma::Mat<double> all_probabilities(state_to_ind.size() * m_possible_actions.size(),state_to_ind.size(), arma::fill::zeros);
int it = 0;
for(unsigned int i = 0; i <= m_max_x; i++)
{
for(unsigned int j = 0; j <= m_max_y; j++)
{
for(unsigned int k = 0; k <= m_max_x; k++)
{
for(unsigned int l = 0; l <= m_max_y; l++)
{
for(unsigned int a = 0; a < m_possible_actions.size(); a++)
{
vector<double> s;
s.push_back(i);
s.push_back(j);
s.push_back(k);
s.push_back(l);
if(i == k && j == l)
{
int ind = state_to_ind[s];
all_probabilities(it, ind) += 1.0;
}
else
{
vector<vector<double> > neighbors = get_neighbors(s,a);
for(unsigned int n = 0; n < neighbors.size(); n++)
{
vector<double> neighbor = neighbors[n];
// for(unsigned int z = 0; z < neighbor.size(); z++)
// {
// cout << neighbor[z] << ",";
// }
// cout << endl;
int ind = state_to_ind[neighbor];
all_probabilities(it, ind) += 1.0/neighbors.size();
}
}
it++;
}
}
}
}
}
//all_probabilities.print();
//exit(1);
return all_probabilities;
}
void legion_network::simulate(const unsigned int steps,
const double time,
const solve_type solver,
const bool collect_dynamic,
const legion_stimulus & stimulus,
legion_dynamic & output_dynamic) {
output_dynamic.clear();
m_stimulus = (legion_stimulus *) &stimulus;
create_dynamic_connections(stimulus);
const double step = time / (double) steps;
const double int_step = step / 10.0;
store_dynamic(0.0, collect_dynamic, output_dynamic); /* store initial state */
for (double cur_time = step; cur_time < time; cur_time += step) {
calculate_states(stimulus, solver, cur_time, step, int_step);
store_dynamic(cur_time, collect_dynamic, output_dynamic); /* store initial state */
}
}
