BambuStudio/src/libslic3r/FilamentGroup.cpp

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#include "FilamentGroup.hpp"
#include "GCode/ToolOrderUtils.hpp"
#include <queue>
namespace Slic3r
{
void KMediods::fit(const FGStrategy&g_strategy , int timeout_ms)
{
std::vector<int>best_medoids;
std::vector<int>best_labels;
int best_cost = std::numeric_limits<int>::max();
FlushTimeMachine T;
T.time_machine_start();
int count = 0;
while (true)
{
std::vector<int>medoids;
std::vector<int>labels;
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<int> new_medoids = medoids;
new_medoids[j] = i;
std::vector<int> 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<int> KMediods::assign_label(const std::vector<int>& medoids,const FGStrategy&g_strategy)
{
std::vector<int>labels(m_filament_num);
struct Comp {
bool operator()(const std::pair<int, int>& a, const std::pair<int, int>& b) {
return a.second > b.second;
}
};
std::priority_queue<std::pair<int, int>, std::vector<std::pair<int, int>>,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<int> 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<int>& labels, const std::vector<int>& 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<int> KMediods::initialize(INIT_TYPE type)
{
auto hash_func = [](int n1, int n2) {
return n1 * 100 + n2;
};
srand(time(nullptr));
std::vector<int>ret;
if (type == INIT_TYPE::Farthest) {
//get the farthest items
int target_i = 0, target_j = 0, target_val = std::numeric_limits<int>::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::vector<int>medoids;
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<int> FilamentGroup::calc_filament_group(const std::vector<std::vector<unsigned int>>& layer_filaments, const FGStrategy& g_strategy,int* cost)
{
std::set<unsigned int>used_filaments_set;
for (const auto& lf : layer_filaments)
for (const auto& extruder : lf)
used_filaments_set.insert(extruder);
std::vector<unsigned int>used_filaments = std::vector<unsigned int>(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<int> 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<int> FilamentGroup::calc_filament_group_by_enum(const std::vector<std::vector<unsigned int>>& layer_filaments, const std::vector<unsigned int>& 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<uint64_t>(1) << used_filament_num);
int best_cost = std::numeric_limits<int>::max();
std::vector<int>best_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::set<int>group_0, group_1;
for (int j = 0; j < used_filament_num; ++j) {
if (i & (static_cast<uint64_t>(1) << j))
group_1.insert(used_filaments[j]);
else
group_0.insert(used_filaments[j]);
}
std::vector<int>filament_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<int> 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<int> FilamentGroup::calc_filament_group_by_pam(const std::vector<std::vector<unsigned int>>& layer_filaments, const std::vector<unsigned int>& used_filaments, const FGStrategy& g_strategy, int*cost,int timeout_ms)
{
std::vector<int>filament_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<std::vector<int>>count_matrix(used_filament_num, std::vector<int>(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<std::vector<float>>distance_matrix(used_filament_num, std::vector<float>(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::vector<int>filament_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;
}
}