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hc.cpp
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hc.cpp
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#include<iostream>
#include<hc.hpp>
#include<eap_resources.hpp>
#include<lua_cmds.hpp>
#include<boost/format.hpp>
#include<boost/filesystem.hpp>
namespace
{
const std::string c_iterations = "iterations";
const std::string c_convergence_factor = "convergence_factor";
}
hc::hc(std::string lua_file) : algorithm(lua_file)
{
m_convergence_factor = 0.0f;
m_converged_iterations = 0.0f;
}
/**
* @desc Loads parameters for the hill climber algorithm
*/
void hc::setup_algo_params()
{
try
{
algorithm::setup_algo_params();
m_iterations = eap::get_fvalue(c_iterations);
m_convergence_factor = eap::get_fvalue(c_convergence_factor);
m_converged_iterations = m_iterations * m_convergence_factor;
std::cout<<"***completed HC parameter setup"<<std::endl;
}
catch (const eap::InvalidStateException &e)
{
std::cerr<<e.what()<<"\n";
}
}
/**
* @desc Implements logic for HC runs
*/
void hc::run(unsigned int run_id)
{
std::ofstream outfile;
try
{
std::vector<position_ptr> placements;
outfile.open(eap::results_directory + boost::filesystem::basename(m_lua_file) + "_r" + std::to_string(run_id) + "iters.csv");
boost::format nec_input(eap::run_directory + "iter%09d");
int q = 0; // successive state with best solution
for (ant_config_ptr i_ant : m_ant_configs)
{
int pos;
do
{
pos = eap::rand(0, i_ant->m_positions.size() - 1);
} while(overlap(placements, i_ant->m_positions[pos]));
placements.push_back(i_ant->m_positions[pos]);
}
m_p_parent = create_individual(str(nec_input % 0) + "a%02d.nec", placements);
evaluate(0, m_p_parent);
outfile << 0 << "," << m_p_parent->m_fitness << "," << m_p_parent->m_gain_fitness << "," << m_p_parent->m_coupling_fitness << ",";
for (position_ptr p_pos : m_p_parent->m_positions)
outfile << p_pos->m_x << "," << p_pos->m_y << "," << p_pos->m_z <<",";
outfile << "\n";
for (unsigned int i=1; i<m_iterations; ++i)
{
std::vector<position_ptr> placements = mutate_pos_once(m_p_parent->m_positions);
individual_ptr p_child = create_individual(str(nec_input % i) + "a%02d.nec", placements);
evaluate(i, p_child);
if (p_child->m_fitness < m_p_parent->m_fitness)
{
swap(m_p_parent, p_child);
outfile << i << "," << m_p_parent->m_fitness << "," << m_p_parent->m_gain_fitness << "," << m_p_parent->m_coupling_fitness << ",";
for (position_ptr p_pos : m_p_parent->m_positions)
outfile << p_pos->m_x << "," << p_pos->m_y << "," << p_pos->m_z <<",";
outfile << "\n";
std::cout<<"***iter="<<i<<", best ind "<<m_p_parent->m_fitness<<"\n";
q = 0;
}
else
q++;
if (q > m_converged_iterations)
break;
// remove all after an iteration
boost::filesystem::path path_to_remove(eap::run_directory);
for (boost::filesystem::directory_iterator end_dir_it, it(path_to_remove); it!=end_dir_it; ++it)
remove_all(it->path());
}
outfile.close();
}
catch (...)
{
outfile.close();
throw;
}
}
void hc::evaluate(unsigned int id, individual_ptr &p_ind)
{
try
{
run_simulation(id);
boost::format nec_output(eap::run_directory + "iter%09da%02d.out");
for (unsigned int i_ant=0; i_ant<m_ant_configs.size(); ++i_ant)
{
evaluation_ptr p_eval(new evaluation);
p_ind->m_evals.push_back(p_eval);
unsigned int read = read_radiation(str(nec_output % id % i_ant), p_eval);
if (read != (num_polar() * m_step_freq))
throw eap::InvalidStateException("HC:Problem with output in " + str(nec_output % id % i_ant));
p_ind->m_one_ant_on_fitness.push_back(compare(m_free_inds[i_ant]->m_evals[0], p_ind->m_evals[i_ant]));
p_ind->m_gain_fitness += p_ind->m_one_ant_on_fitness[i_ant];
}
p_ind->m_gain_fitness /= m_max_gain;
p_ind->m_coupling_fitness = read_coupling(str(nec_output % id % m_ant_configs.size()), m_ant_configs.size());
//normalizing fitness
p_ind->m_coupling_fitness += std::abs(m_min_coup);
p_ind->m_coupling_fitness /= m_max_coup;
p_ind->m_fitness = cal_fitness(p_ind);
}
catch (...)
{
throw;
}
}
void hc::run_simulation(unsigned int id)
{
try
{
boost::format formatter("ls " + eap::run_directory + "iter%09da*.nec | parallel -j+0 nec2++ -i {}");
system(str(formatter % id).c_str());
std::cout<<"***completed simulation for iteration "<<id<<"\n";
}
catch (...)
{
throw;
}
}
hc::~hc(void)
{
}