#include "FilamentGroup.hpp" #include "GCode/ToolOrderUtils.hpp" #include namespace Slic3r { void KMediods::fit(const FGStrategy&g_strategy , int timeout_ms) { std::vectorbest_medoids; std::vectorbest_labels; int best_cost = std::numeric_limits::max(); FlushTimeMachine T; T.time_machine_start(); int count = 0; while (true) { std::vectormedoids; std::vectorlabels; if (count == 0) medoids = initialize(INIT_TYPE::Farthest); else medoids = initialize(INIT_TYPE::Random); labels = assign_label(medoids,g_strategy); int cost = calc_cost(labels, medoids); for (int i = 0; i < m_filament_num; ++i) { if (std::find(medoids.begin(), medoids.end(), i) != medoids.end()) continue; for (int j = 0; j < 2; ++j) { std::vector new_medoids = medoids; new_medoids[j] = i; std::vector new_labels = assign_label(new_medoids,g_strategy); int new_cost = calc_cost(new_labels, new_medoids); if (new_cost < cost) { labels = new_labels; cost = new_cost; medoids = new_medoids; } } } if (cost < best_cost) { best_cost = cost; best_labels = labels; best_medoids = medoids; } count += 1; if (T.time_machine_end() > timeout_ms || m_medoids_set.size() == (m_filament_num * (m_filament_num - 1) / 2)) break; } this->m_filament_labels = best_labels; } std::vector KMediods::assign_label(const std::vector& medoids,const FGStrategy&g_strategy) { std::vectorlabels(m_filament_num); struct Comp { bool operator()(const std::pair& a, const std::pair& b) { return a.second > b.second; } }; std::priority_queue, std::vector>,Comp>min_heap; for (int i = 0; i < m_filament_num; ++i) { int distancec_to_0 = m_distance_matrix[i][medoids[0]]; int distancec_to_1 = m_distance_matrix[i][medoids[1]]; min_heap.push({ i,distancec_to_0 - distancec_to_1 }); } std::set group_0, group_1; bool have_enough_size = (m_filament_num <= (m_max_group_size[0] + m_max_group_size[1])); if (have_enough_size || g_strategy == FGStrategy::BestFit) { while (!min_heap.empty()) { auto top = min_heap.top(); min_heap.pop(); if (group_0.size() < m_max_group_size[0] && (top.second <= 0 || group_1.size() >= m_max_group_size[1])) group_0.insert(top.first); else if (group_1.size() < m_max_group_size[1] && (top.second > 0 || group_0.size() >= m_max_group_size[0])) group_1.insert(top.first); else { if (top.second <= 0) group_0.insert(top.first); else group_1.insert(top.first); } } } else if (g_strategy == FGStrategy::BestCost) { while (!min_heap.empty()) { auto top = min_heap.top(); min_heap.pop(); if (top.second <= 0) group_0.insert(top.first); else group_1.insert(top.first); } } for (auto& item : group_0) labels[item] = 0; for (auto& item : group_1) labels[item] = 1; return labels; } int KMediods::calc_cost(const std::vector& labels, const std::vector& medoids) { int total_cost = 0; for (int i = 0; i < m_filament_num; ++i) total_cost += m_distance_matrix[i][medoids[labels[i]]]; return total_cost; } std::vector KMediods::initialize(INIT_TYPE type) { auto hash_func = [](int n1, int n2) { return n1 * 100 + n2; }; srand(time(nullptr)); std::vectorret; if (type == INIT_TYPE::Farthest) { //get the farthest items int target_i = 0, target_j = 0, target_val = std::numeric_limits::min(); for (int i = 0; i < m_distance_matrix.size(); ++i) { for (int j = 0; j < m_distance_matrix[0].size(); ++j) { if (i != j && m_distance_matrix[i][j] > target_val) { target_val = m_distance_matrix[i][j]; target_i = i; target_j = j; } } } ret.emplace_back(std::min(target_i, target_j)); ret.emplace_back(std::max(target_i, target_j)); } else if (type == INIT_TYPE::Random) { while (true) { std::vectormedoids; while (medoids.size() < k) { int candidate = rand() % m_filament_num; if (std::find(medoids.begin(), medoids.end(), candidate) == medoids.end()) medoids.push_back(candidate); } std::sort(medoids.begin(), medoids.end()); if (m_medoids_set.find(hash_func(medoids[0], medoids[1])) != m_medoids_set.end() && m_medoids_set.size() != (m_filament_num * (m_filament_num - 1) / 2)) continue; else { ret = medoids; break; } } } m_medoids_set.insert(hash_func(ret[0],ret[1])); return ret; } std::vector FilamentGroup::calc_filament_group(const std::vector>& layer_filaments, const FGStrategy& g_strategy,int* cost) { std::setused_filaments_set; for (const auto& lf : layer_filaments) for (const auto& extruder : lf) used_filaments_set.insert(extruder); std::vectorused_filaments = std::vector(used_filaments_set.begin(), used_filaments_set.end()); std::sort(used_filaments.begin(), used_filaments.end()); int used_filament_num = used_filaments.size(); std::vector filament_labels(m_total_filament_num, 0); if (used_filament_num <= 1) { if (cost) *cost = 0; return filament_labels; } if (used_filament_num < 10) return calc_filament_group_by_enum(layer_filaments, used_filaments, g_strategy, cost); else return calc_filament_group_by_pam(layer_filaments, used_filaments, g_strategy, cost, 100); } std::vector FilamentGroup::calc_filament_group_by_enum(const std::vector>& layer_filaments, const std::vector& used_filaments, const FGStrategy& g_strategy,int*cost) { auto bit_count_one = [](uint64_t n) { int count = 0; while (n != 0) { n &= n - 1; count++; } return count; }; int used_filament_num = used_filaments.size(); bool have_enough_size = (used_filament_num <= (m_max_group_size[0] + m_max_group_size[1])); uint64_t max_group_num = (static_cast(1) << used_filament_num); int best_cost = std::numeric_limits::max(); std::vectorbest_label; for (uint64_t i = 0; i < max_group_num; ++i) { int num_to_group_1 = bit_count_one(i); int num_to_group_0 = used_filament_num - num_to_group_1; bool should_accept = false; if (have_enough_size) should_accept = (num_to_group_0 <= m_max_group_size[0] && num_to_group_1 <= m_max_group_size[1]); else if (g_strategy == FGStrategy::BestCost) should_accept = true; else if (g_strategy == FGStrategy::BestFit) should_accept = (num_to_group_0 >= m_max_group_size[0] && num_to_group_1 >= m_max_group_size[1]); if (!should_accept) continue; std::setgroup_0, group_1; for (int j = 0; j < used_filament_num; ++j) { if (i & (static_cast(1) << j)) group_1.insert(used_filaments[j]); else group_0.insert(used_filaments[j]); } std::vectorfilament_maps(used_filament_num); for (int i = 0; i < used_filament_num; ++i) { if (group_0.find(used_filaments[i]) != group_0.end()) filament_maps[i] = 0; if (group_1.find(used_filaments[i]) != group_1.end()) filament_maps[i] = 1; } int total_cost = reorder_filaments_for_minimum_flush_volume( used_filaments, filament_maps, layer_filaments, m_flush_matrix, get_custom_seq, nullptr ); if (total_cost < best_cost) { best_cost = total_cost; best_label = filament_maps; } } if (cost) *cost = best_cost; std::vector filament_labels(m_total_filament_num, 0); for (int i = 0; i < best_label.size(); ++i) filament_labels[used_filaments[i]] = best_label[i]; return filament_labels; } std::vector FilamentGroup::calc_filament_group_by_pam(const std::vector>& layer_filaments, const std::vector& used_filaments, const FGStrategy& g_strategy, int*cost,int timeout_ms) { std::vectorfilament_labels_ret(m_total_filament_num, 0); int used_filament_num = used_filaments.size(); if (used_filaments.size() == 1) return filament_labels_ret; //calc pair counts std::vector>count_matrix(used_filament_num, std::vector(used_filament_num)); for (const auto& lf : layer_filaments) { for (auto iter = lf.begin(); iter != lf.end(); ++iter) { auto id_iter1 = std::find(used_filaments.begin(), used_filaments.end(), *iter); if (id_iter1 == used_filaments.end()) continue; auto idx1 = id_iter1 - used_filaments.begin(); for (auto niter = std::next(iter); niter != lf.end(); ++niter) { auto id_iter2 = std::find(used_filaments.begin(), used_filaments.end(), *niter); if (id_iter2 == used_filaments.end()) continue; auto idx2 = id_iter2 - used_filaments.begin(); count_matrix[idx1][idx2] += 1; count_matrix[idx2][idx1] += 1; } } } //calc distance matrix std::vector>distance_matrix(used_filament_num, std::vector(used_filament_num)); for (size_t i = 0; i < used_filaments.size(); ++i) { for (size_t j = 0; j < used_filaments.size(); ++j) { if (i == j) distance_matrix[i][j] = 0; else { //TODO: check m_flush_matrix float max_val = std::max(m_flush_matrix[0][used_filaments[i]][used_filaments[j]], m_flush_matrix[0][used_filaments[j]][used_filaments[i]]); float min_val = std::min(m_flush_matrix[0][used_filaments[i]][used_filaments[j]], m_flush_matrix[0][used_filaments[j]][used_filaments[i]]); double p = 0.65; distance_matrix[i][j] = (max_val * p + min_val * (1 - p)) * count_matrix[i][j]; } } } KMediods PAM(distance_matrix, used_filament_num, m_max_group_size); PAM.fit(g_strategy, timeout_ms); std::vectorfilament_labels = PAM.get_filament_labels(); if(cost) *cost=reorder_filaments_for_minimum_flush_volume(used_filaments,filament_labels,layer_filaments,m_flush_matrix,std::nullopt,nullptr); for (int i = 0; i < filament_labels.size(); ++i) filament_labels_ret[used_filaments[i]] = filament_labels[i]; return filament_labels_ret; } }