900 lines
40 KiB
C++
900 lines
40 KiB
C++
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#include "FilamentGroup.hpp"
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#include "GCode/ToolOrderUtils.hpp"
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#include "FlushVolPredictor.hpp"
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#include <queue>
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#include <random>
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#include <cassert>
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#include <sstream>
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namespace Slic3r
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{
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using namespace FilamentGroupUtils;
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// clear the array and heap,save the groups in heap to the array
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static void change_memoryed_heaps_to_arrays(MemoryedGroupHeap& heap,const int total_filament_num,const std::vector<unsigned int>& used_filaments, std::vector<std::vector<int>>& arrs)
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{
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// switch the label idx
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arrs.clear();
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while (!heap.empty()) {
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auto top = heap.top();
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heap.pop();
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std::vector<int> labels_tmp(total_filament_num, 0);
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for (size_t idx = 0; idx < top.group.size(); ++idx)
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labels_tmp[used_filaments[idx]] = top.group[idx];
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arrs.emplace_back(std::move(labels_tmp));
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}
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}
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static std::unordered_map<int, int> get_merged_filament_map(const std::unordered_map<int, std::vector<int>>& merged_filaments)
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{
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std::unordered_map<int, int> filament_merge_map;
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for (auto elem : merged_filaments) {
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for (auto f : elem.second) {
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//traverse filaments in merged group
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filament_merge_map[f] = elem.first;
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}
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}
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return filament_merge_map;
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}
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std::vector<int> calc_filament_group_for_tpu(const std::set<int>& tpu_filaments, const int filament_nums, const int master_extruder_id)
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{
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std::vector<int> ret(filament_nums);
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for (size_t fidx = 0; fidx < filament_nums; ++fidx) {
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if (tpu_filaments.count(fidx))
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ret[fidx] = master_extruder_id;
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else
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ret[fidx] = 1 - master_extruder_id;
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}
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return ret;
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}
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bool can_swap_groups(const int extruder_id_0, const std::set<int>& group_0, const int extruder_id_1, const std::set<int>& group_1, const FilamentGroupContext& ctx)
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{
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std::vector<std::set<int>>extruder_unprintables(2);
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{
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std::vector<std::set<int>> unprintable_filaments = ctx.model_info.unprintable_filaments;
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if (unprintable_filaments.size() > 1)
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remove_intersection(unprintable_filaments[0], unprintable_filaments[1]);
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std::map<int, std::vector<int>>unplaceable_limts;
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for (auto& group_id : { extruder_id_0,extruder_id_1 })
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for (auto f : unprintable_filaments[group_id])
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unplaceable_limts[f].emplace_back(group_id);
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for (auto& elem : unplaceable_limts)
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sort_remove_duplicates(elem.second);
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for (auto& elem : unplaceable_limts) {
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for (auto& eid : elem.second) {
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if (eid == extruder_id_0) {
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extruder_unprintables[0].insert(elem.first);
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}
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if (eid == extruder_id_1) {
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extruder_unprintables[1].insert(elem.first);
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}
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}
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}
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}
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// check printable limits
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for (auto fid : group_0) {
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if (extruder_unprintables[1].count(fid) > 0)
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return false;
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}
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for (auto fid : group_1) {
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if (extruder_unprintables[0].count(fid) > 0)
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return false;
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}
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// check extruder capacity ,if result before exchange meets the constraints and the result after exchange does not meet the constraints, return false
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if (ctx.machine_info.max_group_size[extruder_id_0] >= group_0.size() && ctx.machine_info.max_group_size[extruder_id_1] >= group_1.size() && (ctx.machine_info.max_group_size[extruder_id_0] < group_1.size() || ctx.machine_info.max_group_size[extruder_id_1] < group_0.size()))
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return false;
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return true;
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}
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// only support extruder nums with 2, try to swap the master extruder id with the other extruder id
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std::vector<int> optimize_group_for_master_extruder(const std::vector<unsigned int>& used_filaments,const FilamentGroupContext& ctx, std::vector<int>& filament_map)
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{
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std::vector<int> ret = filament_map;
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std::unordered_map<int, std::set<int>> groups;
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for (size_t idx = 0; idx < used_filaments.size(); ++idx) {
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int filament_id = used_filaments[idx];
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int group_id = ret[filament_id];
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groups[group_id].insert(filament_id);
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}
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int none_master_extruder_id = 1 - ctx.machine_info.master_extruder_id;
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assert(0 <= none_master_extruder_id && none_master_extruder_id <= 1);
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if (can_swap_groups(none_master_extruder_id, groups[none_master_extruder_id], ctx.machine_info.master_extruder_id, groups[ctx.machine_info.master_extruder_id], ctx)
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&& groups[none_master_extruder_id].size()>groups[ctx.machine_info.master_extruder_id].size()) {
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for (auto fid : groups[none_master_extruder_id])
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ret[fid] = ctx.machine_info.master_extruder_id;
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for (auto fid : groups[ctx.machine_info.master_extruder_id])
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ret[fid] = none_master_extruder_id;
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}
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return ret;
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}
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/**
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* @brief Select the group that best fit the filaments in AMS
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*
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* Calculate the total color distance between the grouping results and the AMS filaments through
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* minimum cost maximum flow. Only those with a distance difference within the threshold are
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* considered valid.
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*
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* @param map_lists Group list with similar flush count
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* @param used_filaments Idx of used filaments
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* @param used_filament_info Information of filaments used
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* @param machine_filament_info Information of filaments loaded in printer
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* @param color_threshold Threshold for considering colors to be similar
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* @return The group that best fits the filament distribution in AMS
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*/
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std::vector<int> select_best_group_for_ams(const std::vector<std::vector<int>>& map_lists,
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const std::vector<unsigned int>& used_filaments,
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const std::vector<FilamentInfo>& used_filament_info,
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const std::vector<std::vector<MachineFilamentInfo>>& machine_filament_info_,
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const double color_threshold)
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{
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using namespace FlushPredict;
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const int fail_cost = 9999;
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// these code is to make we machine filament info size is 2
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std::vector<std::vector<MachineFilamentInfo>> machine_filament_info = machine_filament_info_;
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machine_filament_info.resize(2);
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int best_cost = std::numeric_limits<int>::max();
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std::vector<int>best_map;
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for (auto& map : map_lists) {
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std::vector<std::vector<int>> group_filaments(2);
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std::vector<std::vector<Color>>group_colors(2);
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for (size_t i = 0; i < used_filaments.size(); ++i) {
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int target_group = map[used_filaments[i]] == 0 ? 0 : 1;
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group_colors[target_group].emplace_back(used_filament_info[i].color);
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group_filaments[target_group].emplace_back(i);
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}
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int group_cost = 0;
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for (size_t i = 0; i < 2; ++i) {
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if (group_colors[i].empty())
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continue;
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if (machine_filament_info[i].empty()) {
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group_cost += group_colors.size() * fail_cost;
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continue;
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}
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std::vector<std::vector<float>>distance_matrix(group_colors[i].size(), std::vector<float>(machine_filament_info[i].size()));
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// calculate color distance matrix
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for (size_t src = 0; src < group_colors[i].size(); ++src) {
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for (size_t dst = 0; dst < machine_filament_info[i].size(); ++dst) {
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distance_matrix[src][dst] = calc_color_distance(
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RGBColor(group_colors[i][src].r, group_colors[i][src].g, group_colors[i][src].b),
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RGBColor(machine_filament_info[i][dst].color.r, machine_filament_info[i][dst].color.g, machine_filament_info[i][dst].color.b)
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);
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}
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}
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// get min cost by min cost max flow
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std::vector<int>l_nodes(group_colors[i].size()), r_nodes(machine_filament_info[i].size());
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std::iota(l_nodes.begin(), l_nodes.end(), 0);
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std::iota(r_nodes.begin(), r_nodes.end(), 0);
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std::unordered_map<int, std::vector<int>>unlink_limits;
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for (size_t from = 0; from < group_filaments[i].size(); ++from) {
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for (size_t to = 0; to < machine_filament_info[i].size(); ++to) {
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if (used_filament_info[group_filaments[i][from]].type != machine_filament_info[i][to].type ||
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used_filament_info[group_filaments[i][from]].is_support != machine_filament_info[i][to].is_support) {
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unlink_limits[from].emplace_back(to);
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}
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}
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}
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MatchModeGroupSolver mcmf(distance_matrix, l_nodes, r_nodes, std::vector<int>(r_nodes.size(), l_nodes.size()), unlink_limits);
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auto ams_map = mcmf.solve();
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for (size_t idx = 0; idx < ams_map.size(); ++idx) {
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if (ams_map[idx] == MaxFlowGraph::INVALID_ID || distance_matrix[idx][ams_map[idx]] > color_threshold) {
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group_cost += fail_cost;
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}
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else {
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group_cost += distance_matrix[idx][ams_map[idx]];
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}
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}
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}
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if (best_map.empty() || group_cost < best_cost) {
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best_cost = group_cost;
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best_map = map;
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}
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}
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return best_map;
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}
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void FilamentGroupUtils::update_memoryed_groups(const MemoryedGroup& item, const double gap_threshold, MemoryedGroupHeap& groups)
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{
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auto emplace_if_accepatle = [gap_threshold](MemoryedGroupHeap& heap, const MemoryedGroup& elem, const MemoryedGroup& best) {
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if (best.cost == 0) {
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if (std::abs(elem.cost - best.cost) <= ABSOLUTE_FLUSH_GAP_TOLERANCE)
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heap.push(elem);
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return;
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}
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double gap_rate = (double)std::abs(elem.cost - best.cost) / (double)best.cost;
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if (gap_rate < gap_threshold)
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heap.push(elem);
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};
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if (groups.empty()) {
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groups.push(item);
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}
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else {
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auto top = groups.top();
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// we only memory items with the highest prefer level
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if (top.prefer_level > item.prefer_level)
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return;
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else if (top.prefer_level == item.prefer_level) {
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if (top.cost <= item.cost) {
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emplace_if_accepatle(groups, item, top);
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}
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// find a group with lower cost, rebuild the heap
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else {
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MemoryedGroupHeap new_heap;
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new_heap.push(item);
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while (!groups.empty()) {
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auto top = groups.top();
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groups.pop();
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emplace_if_accepatle(new_heap, top, item);
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}
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groups = std::move(new_heap);
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}
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}
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// find a group with the higher prefer level, rebuild the heap
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else {
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groups = MemoryedGroupHeap();
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groups.push(item);
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}
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}
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}
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std::vector<unsigned int> collect_sorted_used_filaments(const std::vector<std::vector<unsigned int>>& layer_filaments)
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{
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std::set<unsigned int>used_filaments_set;
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for (const auto& lf : layer_filaments)
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for (const auto& f : lf)
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used_filaments_set.insert(f);
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std::vector<unsigned int>used_filaments(used_filaments_set.begin(), used_filaments_set.end());
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std::sort(used_filaments.begin(), used_filaments.end());
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return used_filaments;
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}
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FlushDistanceEvaluator::FlushDistanceEvaluator(const FlushMatrix& flush_matrix, const std::vector<unsigned int>& used_filaments, const std::vector<std::vector<unsigned int>>& layer_filaments, double p)
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{
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//calc pair counts
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std::vector<std::vector<int>>count_matrix(used_filaments.size(), std::vector<int>(used_filaments.size()));
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for (const auto& lf : layer_filaments) {
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for (auto iter = lf.begin(); iter != lf.end(); ++iter) {
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auto id_iter1 = std::find(used_filaments.begin(), used_filaments.end(), *iter);
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if (id_iter1 == used_filaments.end())
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continue;
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auto idx1 = id_iter1 - used_filaments.begin();
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for (auto niter = std::next(iter); niter != lf.end(); ++niter) {
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auto id_iter2 = std::find(used_filaments.begin(), used_filaments.end(), *niter);
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if (id_iter2 == used_filaments.end())
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continue;
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auto idx2 = id_iter2 - used_filaments.begin();
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count_matrix[idx1][idx2] += 1;
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count_matrix[idx2][idx1] += 1;
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}
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}
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}
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m_distance_matrix.resize(used_filaments.size(), std::vector<float>(used_filaments.size()));
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for (size_t i = 0; i < used_filaments.size(); ++i) {
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for (size_t j = 0; j < used_filaments.size(); ++j) {
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if (i == j)
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m_distance_matrix[i][j] = 0;
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else {
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//TODO: check m_flush_matrix
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float max_val = std::max(flush_matrix[used_filaments[i]][used_filaments[j]], flush_matrix[used_filaments[j]][used_filaments[i]]);
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float min_val = std::min(flush_matrix[used_filaments[i]][used_filaments[j]], flush_matrix[used_filaments[j]][used_filaments[i]]);
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m_distance_matrix[i][j] = (max_val * p + min_val * (1 - p)) * count_matrix[i][j];
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}
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}
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}
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}
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double FlushDistanceEvaluator::get_distance(int idx_a, int idx_b) const
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{
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assert(0 <= idx_a && idx_a < m_distance_matrix.size());
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assert(0 <= idx_b && idx_b < m_distance_matrix.size());
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return m_distance_matrix[idx_a][idx_b];
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}
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std::vector<int> KMediods2::cluster_small_data(const std::map<int, int>& unplaceable_limits, const std::vector<int>& group_size)
|
||
|
|
{
|
||
|
|
std::vector<int>labels(m_elem_count, -1);
|
||
|
|
std::vector<int>new_group_size = group_size;
|
||
|
|
|
||
|
|
for (auto& [elem, center] : unplaceable_limits) {
|
||
|
|
if (labels[elem] == -1) {
|
||
|
|
int gid = 1 - center;
|
||
|
|
labels[elem] = gid;
|
||
|
|
new_group_size[gid] -= 1;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
for (auto& label : labels) {
|
||
|
|
if (label == -1) {
|
||
|
|
int gid = -1;
|
||
|
|
for (size_t idx = 0; idx < new_group_size.size(); ++idx) {
|
||
|
|
if (new_group_size[idx] > 0) {
|
||
|
|
gid = idx;
|
||
|
|
break;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
if (gid != -1) {
|
||
|
|
label = gid;
|
||
|
|
new_group_size[gid] -= 1;
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
label = m_default_group_id;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
return labels;
|
||
|
|
}
|
||
|
|
|
||
|
|
std::vector<int> KMediods2::assign_cluster_label(const std::vector<int>& center, const std::map<int, int>& unplaceable_limtis, const std::vector<int>& group_size, const FGStrategy& strategy)
|
||
|
|
{
|
||
|
|
struct Comp {
|
||
|
|
bool operator()(const std::pair<int, int>& a, const std::pair<int, int>& b) {
|
||
|
|
return a.second > b.second;
|
||
|
|
}
|
||
|
|
};
|
||
|
|
|
||
|
|
std::vector<std::set<int>>groups(2);
|
||
|
|
std::vector<int>new_max_group_size = group_size;
|
||
|
|
// store filament idx and distance gap between center 0 and center 1
|
||
|
|
std::priority_queue<std::pair<int, int>, std::vector<std::pair<int, int>>, Comp>min_heap;
|
||
|
|
|
||
|
|
for (int i = 0; i < m_elem_count; ++i) {
|
||
|
|
if (auto it = unplaceable_limtis.find(i); it != unplaceable_limtis.end()) {
|
||
|
|
int gid = it->second;
|
||
|
|
assert(gid == 0 || gid == 1);
|
||
|
|
groups[1 - gid].insert(i); // insert to group
|
||
|
|
new_max_group_size[1 - gid] = std::max(new_max_group_size[1 - gid] - 1, 0); // decrease group_size
|
||
|
|
continue;
|
||
|
|
}
|
||
|
|
int distance_to_0 = m_evaluator->get_distance(i, center[0]);
|
||
|
|
int distance_to_1 = m_evaluator->get_distance(i, center[1]);
|
||
|
|
min_heap.push({ i,distance_to_0 - distance_to_1 });
|
||
|
|
}
|
||
|
|
|
||
|
|
bool have_enough_size = (min_heap.size() <= (new_max_group_size[0] + new_max_group_size[1]));
|
||
|
|
|
||
|
|
if (have_enough_size || strategy == FGStrategy::BestFit) {
|
||
|
|
while (!min_heap.empty()) {
|
||
|
|
auto top = min_heap.top();
|
||
|
|
min_heap.pop();
|
||
|
|
if (groups[0].size() < new_max_group_size[0] && (top.second <= 0 || groups[1].size() >= new_max_group_size[1]))
|
||
|
|
groups[0].insert(top.first);
|
||
|
|
else if (groups[1].size() < new_max_group_size[1] && (top.second > 0 || groups[0].size() >= new_max_group_size[0]))
|
||
|
|
groups[1].insert(top.first);
|
||
|
|
else {
|
||
|
|
if (top.second <= 0)
|
||
|
|
groups[0].insert(top.first);
|
||
|
|
else
|
||
|
|
groups[1].insert(top.first);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
while (!min_heap.empty()) {
|
||
|
|
auto top = min_heap.top();
|
||
|
|
min_heap.pop();
|
||
|
|
if (top.second <= 0)
|
||
|
|
groups[0].insert(top.first);
|
||
|
|
else
|
||
|
|
groups[1].insert(top.first);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
std::vector<int>labels(m_elem_count);
|
||
|
|
for (auto& f : groups[0])
|
||
|
|
labels[f] = 0;
|
||
|
|
for (auto& f : groups[1])
|
||
|
|
labels[f] = 1;
|
||
|
|
|
||
|
|
return labels;
|
||
|
|
}
|
||
|
|
|
||
|
|
int KMediods2::calc_cost(const std::vector<int>& labels, const std::vector<int>& medoids)
|
||
|
|
{
|
||
|
|
int total_cost = 0;
|
||
|
|
for (int i = 0; i < m_elem_count; ++i)
|
||
|
|
total_cost += m_evaluator->get_distance(i, medoids[labels[i]]);
|
||
|
|
return total_cost;
|
||
|
|
}
|
||
|
|
|
||
|
|
void KMediods2::do_clustering(const FGStrategy& g_strategy, int timeout_ms)
|
||
|
|
{
|
||
|
|
FlushTimeMachine T;
|
||
|
|
T.time_machine_start();
|
||
|
|
|
||
|
|
if (m_elem_count < m_k) {
|
||
|
|
m_cluster_labels = cluster_small_data(m_unplaceable_limits, m_max_cluster_size);
|
||
|
|
{
|
||
|
|
std::vector<int>cluster_center(m_k, -1);
|
||
|
|
for (size_t idx = 0; idx < m_cluster_labels.size(); ++idx) {
|
||
|
|
if (cluster_center[m_cluster_labels[idx]] == -1)
|
||
|
|
cluster_center[m_cluster_labels[idx]] = idx;
|
||
|
|
}
|
||
|
|
MemoryedGroup g(m_cluster_labels, calc_cost(m_cluster_labels, cluster_center), 1);
|
||
|
|
update_memoryed_groups(g, memory_threshold, memoryed_groups);
|
||
|
|
}
|
||
|
|
return;
|
||
|
|
}
|
||
|
|
|
||
|
|
std::vector<int>best_labels;
|
||
|
|
int best_cost = std::numeric_limits<int>::max();
|
||
|
|
|
||
|
|
for (int center_0 = 0; center_0 < m_elem_count; ++center_0) {
|
||
|
|
if (auto iter = m_unplaceable_limits.find(center_0); iter != m_unplaceable_limits.end() && iter->second == 0)
|
||
|
|
continue;
|
||
|
|
for (int center_1 = 0; center_1 < m_elem_count; ++center_1) {
|
||
|
|
if (center_0 == center_1)
|
||
|
|
continue;
|
||
|
|
if (auto iter = m_unplaceable_limits.find(center_1); iter != m_unplaceable_limits.end() && iter->second == 1)
|
||
|
|
continue;
|
||
|
|
|
||
|
|
std::vector<int>new_centers = { center_0,center_1 };
|
||
|
|
std::vector<int>new_labels = assign_cluster_label(new_centers, m_unplaceable_limits, m_max_cluster_size, g_strategy);
|
||
|
|
|
||
|
|
int new_cost = calc_cost(new_labels, new_centers);
|
||
|
|
if (new_cost < best_cost) {
|
||
|
|
best_cost = new_cost;
|
||
|
|
best_labels = new_labels;
|
||
|
|
}
|
||
|
|
|
||
|
|
{
|
||
|
|
MemoryedGroup g(new_labels,new_cost,1);
|
||
|
|
update_memoryed_groups(g, memory_threshold, memoryed_groups);
|
||
|
|
}
|
||
|
|
|
||
|
|
if (T.time_machine_end() > timeout_ms)
|
||
|
|
break;
|
||
|
|
}
|
||
|
|
if (T.time_machine_end() > timeout_ms)
|
||
|
|
break;
|
||
|
|
}
|
||
|
|
this->m_cluster_labels = best_labels;
|
||
|
|
}
|
||
|
|
|
||
|
|
std::vector<int> FilamentGroup::calc_min_flush_group(int* cost)
|
||
|
|
{
|
||
|
|
auto used_filaments = collect_sorted_used_filaments(ctx.model_info.layer_filaments);
|
||
|
|
int used_filament_num = used_filaments.size();
|
||
|
|
|
||
|
|
if (used_filament_num < 10)
|
||
|
|
return calc_min_flush_group_by_enum(used_filaments, cost);
|
||
|
|
else
|
||
|
|
return calc_min_flush_group_by_pam2(used_filaments, cost, 500);
|
||
|
|
}
|
||
|
|
|
||
|
|
std::unordered_map<int, std::vector<int>> FilamentGroup::try_merge_filaments()
|
||
|
|
{
|
||
|
|
std::unordered_map<int, std::vector<int>>merged_filaments;
|
||
|
|
|
||
|
|
std::unordered_map<std::string, std::vector<int>> merge_filament_map;
|
||
|
|
|
||
|
|
auto unprintable_stat_to_str = [unprintable_filaments = this->ctx.model_info.unprintable_filaments](int idx) {
|
||
|
|
std::string str;
|
||
|
|
for (size_t eid = 0; eid < unprintable_filaments.size(); ++eid) {
|
||
|
|
if (unprintable_filaments[eid].count(idx)) {
|
||
|
|
if (eid > 0)
|
||
|
|
str += ',';
|
||
|
|
str += std::to_string(idx);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
return str;
|
||
|
|
};
|
||
|
|
|
||
|
|
for (size_t idx = 0; idx < ctx.model_info.filament_ids.size(); ++idx) {
|
||
|
|
std::string id = ctx.model_info.filament_ids[idx];
|
||
|
|
Color color = ctx.model_info.filament_info[idx].color;
|
||
|
|
std::string unprintable_str = unprintable_stat_to_str(idx);
|
||
|
|
|
||
|
|
std::string key = id + "," + color.to_hex_str(true) + "," + unprintable_str;
|
||
|
|
merge_filament_map[key].push_back(idx);
|
||
|
|
}
|
||
|
|
|
||
|
|
for (auto& elem : merge_filament_map) {
|
||
|
|
if (elem.second.size() > 1) {
|
||
|
|
merged_filaments[elem.second.front()] = elem.second;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
return merged_filaments;
|
||
|
|
}
|
||
|
|
|
||
|
|
std::vector<int> FilamentGroup::seperate_merged_filaments(const std::vector<int>& filament_map, const std::unordered_map<int, std::vector<int>>& merged_filaments)
|
||
|
|
{
|
||
|
|
std::vector<int> ret_map = filament_map;
|
||
|
|
for (auto& elem : merged_filaments) {
|
||
|
|
int src = elem.first;
|
||
|
|
for (auto f : elem.second) {
|
||
|
|
ret_map[f] = ret_map[src];
|
||
|
|
}
|
||
|
|
}
|
||
|
|
return ret_map;
|
||
|
|
}
|
||
|
|
|
||
|
|
void FilamentGroup::rebuild_context(const std::unordered_map<int, std::vector<int>>& merged_filaments)
|
||
|
|
{
|
||
|
|
if (merged_filaments.empty())
|
||
|
|
return;
|
||
|
|
|
||
|
|
FilamentGroupContext new_ctx = ctx;
|
||
|
|
|
||
|
|
std::unordered_map<int, int> filament_merge_map = get_merged_filament_map(merged_filaments);
|
||
|
|
|
||
|
|
// modify layer filaments
|
||
|
|
for (auto& layer_filament : new_ctx.model_info.layer_filaments) {
|
||
|
|
for (auto& f : layer_filament) {
|
||
|
|
if (auto iter = filament_merge_map.find((int)(f)); iter != filament_merge_map.end()) {
|
||
|
|
f = iter->second;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
for (auto& unprintables : new_ctx.model_info.unprintable_filaments) {
|
||
|
|
std::set<int> new_unprintables;
|
||
|
|
for (auto f : unprintables) {
|
||
|
|
if (auto iter = filament_merge_map.find((int)(f)); iter != filament_merge_map.end()) {
|
||
|
|
new_unprintables.insert(iter->second);
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
new_unprintables.insert(f);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
ctx = new_ctx;
|
||
|
|
return;
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
std::vector<int> FilamentGroup::calc_filament_group(int* cost)
|
||
|
|
{
|
||
|
|
try {
|
||
|
|
if (FGMode::MatchMode == ctx.group_info.mode)
|
||
|
|
return calc_filament_group_for_match(cost);
|
||
|
|
}
|
||
|
|
catch (const FilamentGroupException& e) {
|
||
|
|
}
|
||
|
|
|
||
|
|
auto merged_map = try_merge_filaments();
|
||
|
|
rebuild_context(merged_map);
|
||
|
|
auto filamnet_map = calc_filament_group_for_flush(cost);
|
||
|
|
return seperate_merged_filaments(filamnet_map, merged_map);
|
||
|
|
}
|
||
|
|
|
||
|
|
std::vector<int> FilamentGroup::calc_filament_group_for_match(int* cost)
|
||
|
|
{
|
||
|
|
using namespace FlushPredict;
|
||
|
|
|
||
|
|
auto used_filaments = collect_sorted_used_filaments(ctx.model_info.layer_filaments);
|
||
|
|
std::vector<FilamentInfo> used_filament_list;
|
||
|
|
for (auto f : used_filaments)
|
||
|
|
used_filament_list.emplace_back(ctx.model_info.filament_info[f]);
|
||
|
|
|
||
|
|
std::vector<MachineFilamentInfo> machine_filament_list;
|
||
|
|
std::map<MachineFilamentInfo, std::set<int>> machine_filament_set;
|
||
|
|
for (size_t eid = 0; eid < ctx.machine_info.machine_filament_info.size();++eid) {
|
||
|
|
for (auto& filament : ctx.machine_info.machine_filament_info[eid]) {
|
||
|
|
machine_filament_set[filament].insert(machine_filament_list.size());
|
||
|
|
machine_filament_list.emplace_back(filament);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
if (machine_filament_list.empty())
|
||
|
|
throw FilamentGroupException(FilamentGroupException::EmptyAmsFilaments,"Empty ams filament in For-Match mode.");
|
||
|
|
|
||
|
|
std::map<int, int> unprintable_limit_indices; // key stores filament idx in used_filament, value stores unprintable extruder
|
||
|
|
extract_unprintable_limit_indices(ctx.model_info.unprintable_filaments, used_filaments, unprintable_limit_indices);
|
||
|
|
|
||
|
|
std::vector<std::vector<float>> color_dist_matrix(used_filament_list.size(), std::vector<float>(machine_filament_list.size()));
|
||
|
|
for (size_t i = 0; i < used_filament_list.size(); ++i) {
|
||
|
|
for (size_t j = 0; j < machine_filament_list.size(); ++j) {
|
||
|
|
color_dist_matrix[i][j] = calc_color_distance(
|
||
|
|
RGBColor(used_filament_list[i].color.r, used_filament_list[i].color.g, used_filament_list[i].color.b),
|
||
|
|
RGBColor(machine_filament_list[j].color.r, machine_filament_list[j].color.g, machine_filament_list[j].color.b)
|
||
|
|
);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
std::vector<int>l_nodes(used_filaments.size());
|
||
|
|
std::iota(l_nodes.begin(), l_nodes.end(), 0);
|
||
|
|
std::vector<int>r_nodes(machine_filament_list.size());
|
||
|
|
std::iota(r_nodes.begin(), r_nodes.end(), 0);
|
||
|
|
std::vector<int>machine_filament_capacity(machine_filament_list.size(),l_nodes.size());
|
||
|
|
std::vector<int>extruder_filament_count(2, 0);
|
||
|
|
|
||
|
|
auto is_extruder_filament_compatible = [&unprintable_limit_indices](int filament_idx, int extruder_id) {
|
||
|
|
auto iter = unprintable_limit_indices.find(filament_idx);
|
||
|
|
if (iter != unprintable_limit_indices.end() && iter->second == extruder_id)
|
||
|
|
return false;
|
||
|
|
return true;
|
||
|
|
};
|
||
|
|
|
||
|
|
auto build_unlink_limits = [](const std::vector<int>& l_nodes, const std::vector<int>& r_nodes, const std::function<bool(int, int)>& can_link) {
|
||
|
|
std::unordered_map<int, std::vector<int>> unlink_limits;
|
||
|
|
for (size_t i = 0; i < l_nodes.size(); ++i) {
|
||
|
|
std::vector<int> unlink_filaments;
|
||
|
|
for (size_t j = 0; j < r_nodes.size(); ++j) {
|
||
|
|
if (!can_link(l_nodes[i], r_nodes[j]))
|
||
|
|
unlink_filaments.emplace_back(j);
|
||
|
|
}
|
||
|
|
if (!unlink_filaments.empty())
|
||
|
|
unlink_limits.emplace(i, std::move(unlink_filaments));
|
||
|
|
}
|
||
|
|
return unlink_limits;
|
||
|
|
};
|
||
|
|
|
||
|
|
auto optimize_map_to_machine_filament = [&](const std::vector<int>& map_to_machine_filament, const std::vector<int>& l_nodes, const std::vector<int>& r_nodes, std::vector<int>& filament_map, bool consider_capacity) {
|
||
|
|
std::vector<int> ungrouped_filaments;
|
||
|
|
std::vector<int> filaments_to_optimize;
|
||
|
|
|
||
|
|
auto map_filament_to_machine_filament = [&](int filament_idx, int machine_filament_idx) {
|
||
|
|
auto& machine_filament = machine_filament_list[machine_filament_idx];
|
||
|
|
machine_filament_capacity[machine_filament_idx] = std::max(0, machine_filament_capacity[machine_filament_idx] - 1); // decrease machine filament capacity
|
||
|
|
filament_map[used_filaments[filament_idx]] = machine_filament.extruder_id; // set extruder id to filament map
|
||
|
|
extruder_filament_count[machine_filament.extruder_id] += 1; // increase filament count in extruder
|
||
|
|
};
|
||
|
|
auto unmap_filament_to_machine_filament = [&](int filament_idx, int machine_filament_idx) {
|
||
|
|
auto& machine_filament = machine_filament_list[machine_filament_idx];
|
||
|
|
machine_filament_capacity[machine_filament_idx] += 1; // increase machine filament capacity
|
||
|
|
extruder_filament_count[machine_filament.extruder_id] -= 1; // increase filament count in extruder
|
||
|
|
};
|
||
|
|
|
||
|
|
for (size_t idx = 0; idx < map_to_machine_filament.size(); ++idx) {
|
||
|
|
if (map_to_machine_filament[idx] == MaxFlowGraph::INVALID_ID) {
|
||
|
|
ungrouped_filaments.emplace_back(l_nodes[idx]);
|
||
|
|
continue;
|
||
|
|
}
|
||
|
|
int used_filament_idx = l_nodes[idx];
|
||
|
|
int machine_filament_idx = r_nodes[map_to_machine_filament[idx]];
|
||
|
|
auto& machine_filament = machine_filament_list[machine_filament_idx];
|
||
|
|
if (machine_filament_set[machine_filament].size() > 1 && unprintable_limit_indices.count(used_filament_idx) == 0)
|
||
|
|
filaments_to_optimize.emplace_back(idx);
|
||
|
|
|
||
|
|
map_filament_to_machine_filament(used_filament_idx, machine_filament_idx);
|
||
|
|
}
|
||
|
|
// try to optimize the result
|
||
|
|
for (auto idx : filaments_to_optimize) {
|
||
|
|
int filament_idx = l_nodes[idx];
|
||
|
|
int old_machine_filament_idx = r_nodes[map_to_machine_filament[idx]];
|
||
|
|
auto& old_machine_filament = machine_filament_list[old_machine_filament_idx];
|
||
|
|
|
||
|
|
int curr_gap = std::abs(extruder_filament_count[0] - extruder_filament_count[1]);
|
||
|
|
unmap_filament_to_machine_filament(filament_idx, old_machine_filament_idx);
|
||
|
|
|
||
|
|
auto optional_filaments = machine_filament_set[old_machine_filament];
|
||
|
|
auto iter = optional_filaments.begin();
|
||
|
|
for (; iter != optional_filaments.end(); ++iter) {
|
||
|
|
int new_extruder_id = machine_filament_list[*iter].extruder_id;
|
||
|
|
int new_gap = std::abs(extruder_filament_count[new_extruder_id] + 1 - extruder_filament_count[1 - new_extruder_id]);
|
||
|
|
if (new_gap < curr_gap && (!consider_capacity || machine_filament_capacity[*iter] > 0)) {
|
||
|
|
map_filament_to_machine_filament(filament_idx, *iter);
|
||
|
|
break;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
if (iter == optional_filaments.end())
|
||
|
|
map_filament_to_machine_filament(filament_idx, old_machine_filament_idx);
|
||
|
|
}
|
||
|
|
return ungrouped_filaments;
|
||
|
|
};
|
||
|
|
|
||
|
|
std::vector<int> group(ctx.group_info.total_filament_num, ctx.machine_info.master_extruder_id);
|
||
|
|
std::vector<int> ungrouped_filaments;
|
||
|
|
|
||
|
|
auto unlink_limits_full = build_unlink_limits(l_nodes, r_nodes, [&used_filament_list, &machine_filament_list, is_extruder_filament_compatible](int used_filament_idx, int machine_filament_idx) {
|
||
|
|
return used_filament_list[used_filament_idx].type == machine_filament_list[machine_filament_idx].type &&
|
||
|
|
used_filament_list[used_filament_idx].is_support == machine_filament_list[machine_filament_idx].is_support &&
|
||
|
|
is_extruder_filament_compatible(used_filament_idx, machine_filament_list[machine_filament_idx].extruder_id);
|
||
|
|
});
|
||
|
|
|
||
|
|
{
|
||
|
|
MatchModeGroupSolver s(color_dist_matrix, l_nodes, r_nodes, machine_filament_capacity, unlink_limits_full);
|
||
|
|
ungrouped_filaments = optimize_map_to_machine_filament(s.solve(), l_nodes, r_nodes,group,false);
|
||
|
|
if (ungrouped_filaments.empty())
|
||
|
|
return group;
|
||
|
|
}
|
||
|
|
|
||
|
|
// additionally remove type limits
|
||
|
|
{
|
||
|
|
l_nodes = ungrouped_filaments;
|
||
|
|
auto unlink_limits = build_unlink_limits(l_nodes, r_nodes, [&machine_filament_list, is_extruder_filament_compatible](int used_filament_idx, int machine_filament_idx) {
|
||
|
|
return is_extruder_filament_compatible(used_filament_idx, machine_filament_list[machine_filament_idx].extruder_id);
|
||
|
|
});
|
||
|
|
|
||
|
|
MatchModeGroupSolver s(color_dist_matrix, l_nodes, r_nodes, machine_filament_capacity, unlink_limits);
|
||
|
|
ungrouped_filaments = optimize_map_to_machine_filament(s.solve(), l_nodes, r_nodes, group,false);
|
||
|
|
if (ungrouped_filaments.empty())
|
||
|
|
return group;
|
||
|
|
}
|
||
|
|
|
||
|
|
// remove all limits
|
||
|
|
{
|
||
|
|
l_nodes = ungrouped_filaments;
|
||
|
|
MatchModeGroupSolver s(color_dist_matrix, l_nodes, r_nodes, machine_filament_capacity, {});
|
||
|
|
auto ret = optimize_map_to_machine_filament(s.solve(), l_nodes, r_nodes, group,false);
|
||
|
|
for (size_t idx = 0; idx < ret.size(); ++idx) {
|
||
|
|
if (ret[idx] == MaxFlowGraph::INVALID_ID)
|
||
|
|
assert(false);
|
||
|
|
else
|
||
|
|
group[used_filaments[l_nodes[idx]]] = machine_filament_list[r_nodes[ret[idx]]].extruder_id;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
return group;
|
||
|
|
}
|
||
|
|
|
||
|
|
std::vector<int> FilamentGroup::calc_filament_group_for_flush(int* cost)
|
||
|
|
{
|
||
|
|
auto used_filaments = collect_sorted_used_filaments(ctx.model_info.layer_filaments);
|
||
|
|
|
||
|
|
std::vector<int> ret = calc_min_flush_group(cost);
|
||
|
|
std::vector<std::vector<int>> memoryed_maps = this->m_memoryed_groups;
|
||
|
|
memoryed_maps.insert(memoryed_maps.begin(), ret);
|
||
|
|
|
||
|
|
std::vector<int> optimized_ret = optimize_group_for_master_extruder(used_filaments, ctx, ret);
|
||
|
|
if (optimized_ret != ret)
|
||
|
|
memoryed_maps.insert(memoryed_maps.begin(), optimized_ret);
|
||
|
|
|
||
|
|
std::vector<FilamentGroupUtils::FilamentInfo> used_filament_info;
|
||
|
|
for (auto f : used_filaments) {
|
||
|
|
used_filament_info.emplace_back(ctx.model_info.filament_info[f]);
|
||
|
|
}
|
||
|
|
|
||
|
|
ret = select_best_group_for_ams(memoryed_maps, used_filaments, used_filament_info, ctx.machine_info.machine_filament_info);
|
||
|
|
return ret;
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
// sorted used_filaments
|
||
|
|
std::vector<int> FilamentGroup::calc_min_flush_group_by_enum(const std::vector<unsigned int>& used_filaments, int* cost)
|
||
|
|
{
|
||
|
|
static constexpr int UNPLACEABLE_LIMIT_REWARD = 100; // reward value if the group result follows the unprintable limit
|
||
|
|
static constexpr int MAX_SIZE_LIMIT_REWARD = 10; // reward value if the group result follows the max size per extruder
|
||
|
|
static constexpr int BEST_FIT_LIMIT_REWARD = 1; // reward value if the group result try to fill the max size per extruder
|
||
|
|
|
||
|
|
MemoryedGroupHeap memoryed_groups;
|
||
|
|
|
||
|
|
auto bit_count_one = [](uint64_t n)
|
||
|
|
{
|
||
|
|
int count = 0;
|
||
|
|
while (n != 0)
|
||
|
|
{
|
||
|
|
n &= n - 1;
|
||
|
|
count++;
|
||
|
|
}
|
||
|
|
return count;
|
||
|
|
};
|
||
|
|
|
||
|
|
std::map<int, int>unplaceable_limit_indices;
|
||
|
|
extract_unprintable_limit_indices(ctx.model_info.unprintable_filaments, used_filaments, unplaceable_limit_indices);
|
||
|
|
|
||
|
|
int used_filament_num = used_filaments.size();
|
||
|
|
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;
|
||
|
|
int best_prefer_level = 0;
|
||
|
|
|
||
|
|
for (uint64_t i = 0; i < max_group_num; ++i) {
|
||
|
|
std::vector<std::set<int>>groups(2);
|
||
|
|
for (int j = 0; j < used_filament_num; ++j) {
|
||
|
|
if (i & (static_cast<uint64_t>(1) << j))
|
||
|
|
groups[1].insert(j);
|
||
|
|
else
|
||
|
|
groups[0].insert(j);
|
||
|
|
}
|
||
|
|
|
||
|
|
int prefer_level = 0;
|
||
|
|
|
||
|
|
if (check_printable(groups, unplaceable_limit_indices))
|
||
|
|
prefer_level += UNPLACEABLE_LIMIT_REWARD;
|
||
|
|
if (groups[0].size() <= ctx.machine_info.max_group_size[0] && groups[1].size() <= ctx.machine_info.max_group_size[1])
|
||
|
|
prefer_level += MAX_SIZE_LIMIT_REWARD;
|
||
|
|
if (FGStrategy::BestFit == ctx.group_info.strategy && groups[0].size() >= ctx.machine_info.max_group_size[0] && groups[1].size() >= ctx.machine_info.max_group_size[1])
|
||
|
|
prefer_level += BEST_FIT_LIMIT_REWARD;
|
||
|
|
|
||
|
|
std::vector<int>filament_maps(used_filament_num);
|
||
|
|
for (int i = 0; i < used_filament_num; ++i) {
|
||
|
|
if (groups[0].find(i) != groups[0].end())
|
||
|
|
filament_maps[i] = 0;
|
||
|
|
if (groups[1].find(i) != groups[1].end())
|
||
|
|
filament_maps[i] = 1;
|
||
|
|
}
|
||
|
|
|
||
|
|
int total_cost = reorder_filaments_for_minimum_flush_volume(
|
||
|
|
used_filaments,
|
||
|
|
filament_maps,
|
||
|
|
ctx.model_info.layer_filaments,
|
||
|
|
ctx.model_info.flush_matrix,
|
||
|
|
get_custom_seq,
|
||
|
|
nullptr
|
||
|
|
);
|
||
|
|
|
||
|
|
if (prefer_level > best_prefer_level || (prefer_level == best_prefer_level && total_cost < best_cost)) {
|
||
|
|
best_prefer_level = prefer_level;
|
||
|
|
best_cost = total_cost;
|
||
|
|
best_label = filament_maps;
|
||
|
|
}
|
||
|
|
|
||
|
|
{
|
||
|
|
MemoryedGroup mg(filament_maps, total_cost, prefer_level);
|
||
|
|
update_memoryed_groups(mg, ctx.group_info.max_gap_threshold, memoryed_groups);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
if (cost)
|
||
|
|
*cost = best_cost;
|
||
|
|
|
||
|
|
std::vector<int> filament_labels(ctx.group_info.total_filament_num, 0);
|
||
|
|
for (size_t i = 0; i < best_label.size(); ++i)
|
||
|
|
filament_labels[used_filaments[i]] = best_label[i];
|
||
|
|
|
||
|
|
|
||
|
|
change_memoryed_heaps_to_arrays(memoryed_groups, ctx.group_info.total_filament_num, used_filaments, m_memoryed_groups);
|
||
|
|
|
||
|
|
return filament_labels;
|
||
|
|
}
|
||
|
|
|
||
|
|
// sorted used_filaments
|
||
|
|
std::vector<int> FilamentGroup::calc_min_flush_group_by_pam2(const std::vector<unsigned int>& used_filaments, int* cost, int timeout_ms)
|
||
|
|
{
|
||
|
|
std::vector<int>filament_labels_ret(ctx.group_info.total_filament_num, ctx.machine_info.master_extruder_id);
|
||
|
|
|
||
|
|
std::map<int, int>unplaceable_limits;
|
||
|
|
extract_unprintable_limit_indices(ctx.model_info.unprintable_filaments, used_filaments, unplaceable_limits);
|
||
|
|
|
||
|
|
auto distance_evaluator = std::make_shared<FlushDistanceEvaluator>(ctx.model_info.flush_matrix[0], used_filaments, ctx.model_info.layer_filaments);
|
||
|
|
KMediods2 PAM((int)used_filaments.size(), distance_evaluator, ctx.machine_info.master_extruder_id);
|
||
|
|
PAM.set_max_cluster_size(ctx.machine_info.max_group_size);
|
||
|
|
PAM.set_unplaceable_limits(unplaceable_limits);
|
||
|
|
PAM.set_memory_threshold(ctx.group_info.max_gap_threshold);
|
||
|
|
PAM.do_clustering(ctx.group_info.strategy, timeout_ms);
|
||
|
|
|
||
|
|
std::vector<int>filament_labels = PAM.get_cluster_labels();
|
||
|
|
|
||
|
|
{
|
||
|
|
auto memoryed_groups = PAM.get_memoryed_groups();
|
||
|
|
change_memoryed_heaps_to_arrays(memoryed_groups, ctx.group_info.total_filament_num, used_filaments, m_memoryed_groups);
|
||
|
|
}
|
||
|
|
|
||
|
|
if (cost)
|
||
|
|
*cost = reorder_filaments_for_minimum_flush_volume(used_filaments, filament_labels, ctx.model_info.layer_filaments, ctx.model_info.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;
|
||
|
|
}
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|