#include "ModelArrange.hpp" #include "Model.hpp" #include "Geometry.hpp" #include "SVG.hpp" #include "MTUtils.hpp" #include #include #include #include #include #include namespace libnest2d { #if !defined(_MSC_VER) && defined(__SIZEOF_INT128__) && !defined(__APPLE__) using LargeInt = __int128; #else using LargeInt = boost::multiprecision::int128_t; template<> struct _NumTag { using Type = ScalarTag; }; #endif template struct _NumTag> { using Type = RationalTag; }; namespace nfp { template struct NfpImpl { NfpResult operator()(const S &sh, const S &other) { return nfpConvexOnly>(sh, other); } }; } } namespace Slic3r { namespace arr { using namespace libnest2d; // Only for debugging. Prints the model object vertices on stdout. std::string toString(const Model& model, bool holes = true) { std::stringstream ss; ss << "{\n"; for(auto objptr : model.objects) { if(!objptr) continue; auto rmesh = objptr->raw_mesh(); for(auto objinst : objptr->instances) { if(!objinst) continue; Slic3r::TriangleMesh tmpmesh = rmesh; // CHECK_ME -> Is the following correct ? tmpmesh.scale(objinst->get_scaling_factor()); objinst->transform_mesh(&tmpmesh); ExPolygons expolys = tmpmesh.horizontal_projection(); for(auto& expoly_complex : expolys) { ExPolygons tmp = expoly_complex.simplify(scaled(1.)); if(tmp.empty()) continue; ExPolygon expoly = tmp.front(); expoly.contour.make_clockwise(); for(auto& h : expoly.holes) h.make_counter_clockwise(); ss << "\t{\n"; ss << "\t\t{\n"; for(auto v : expoly.contour.points) ss << "\t\t\t{" << v(0) << ", " << v(1) << "},\n"; { auto v = expoly.contour.points.front(); ss << "\t\t\t{" << v(0) << ", " << v(1) << "},\n"; } ss << "\t\t},\n"; // Holes: ss << "\t\t{\n"; if(holes) for(auto h : expoly.holes) { ss << "\t\t\t{\n"; for(auto v : h.points) ss << "\t\t\t\t{" << v(0) << ", " << v(1) << "},\n"; { auto v = h.points.front(); ss << "\t\t\t\t{" << v(0) << ", " << v(1) << "},\n"; } ss << "\t\t\t},\n"; } ss << "\t\t},\n"; ss << "\t},\n"; } } } ss << "}\n"; return ss.str(); } // Debugging: Save model to svg file. void toSVG(SVG& svg, const Model& model) { for(auto objptr : model.objects) { if(!objptr) continue; auto rmesh = objptr->raw_mesh(); for(auto objinst : objptr->instances) { if(!objinst) continue; Slic3r::TriangleMesh tmpmesh = rmesh; tmpmesh.scale(objinst->get_scaling_factor()); objinst->transform_mesh(&tmpmesh); ExPolygons expolys = tmpmesh.horizontal_projection(); svg.draw(expolys); } } } namespace bgi = boost::geometry::index; using SpatElement = std::pair; using SpatIndex = bgi::rtree< SpatElement, bgi::rstar<16, 4> >; using ItemGroup = std::vector>; template using TPacker = typename placers::_NofitPolyPlacer; const double BIG_ITEM_TRESHOLD = 0.02; Box boundingBox(const Box& pilebb, const Box& ibb ) { auto& pminc = pilebb.minCorner(); auto& pmaxc = pilebb.maxCorner(); auto& iminc = ibb.minCorner(); auto& imaxc = ibb.maxCorner(); PointImpl minc, maxc; setX(minc, std::min(getX(pminc), getX(iminc))); setY(minc, std::min(getY(pminc), getY(iminc))); setX(maxc, std::max(getX(pmaxc), getX(imaxc))); setY(maxc, std::max(getY(pmaxc), getY(imaxc))); return Box(minc, maxc); } // This is "the" object function which is evaluated many times for each vertex // (decimated with the accuracy parameter) of each object. Therefore it is // upmost crucial for this function to be as efficient as it possibly can be but // at the same time, it has to provide reasonable results. std::tuple objfunc(const PointImpl& bincenter, const TMultiShape& merged_pile, const Box& pilebb, const ItemGroup& items, const Item &item, double bin_area, double norm, // A norming factor for physical dimensions // a spatial index to quickly get neighbors of the candidate item const SpatIndex& spatindex, const SpatIndex& smalls_spatindex, const ItemGroup& remaining ) { // We will treat big items (compared to the print bed) differently auto isBig = [bin_area](double a) { return a/bin_area > BIG_ITEM_TRESHOLD ; }; // Candidate item bounding box auto ibb = sl::boundingBox(item.transformedShape()); // Calculate the full bounding box of the pile with the candidate item auto fullbb = boundingBox(pilebb, ibb); // The bounding box of the big items (they will accumulate in the center // of the pile Box bigbb; if(spatindex.empty()) bigbb = fullbb; else { auto boostbb = spatindex.bounds(); boost::geometry::convert(boostbb, bigbb); } // Will hold the resulting score double score = 0; if(isBig(item.area()) || spatindex.empty()) { // This branch is for the bigger items.. auto minc = ibb.minCorner(); // bottom left corner auto maxc = ibb.maxCorner(); // top right corner // top left and bottom right corners auto top_left = PointImpl{getX(minc), getY(maxc)}; auto bottom_right = PointImpl{getX(maxc), getY(minc)}; // Now the distance of the gravity center will be calculated to the // five anchor points and the smallest will be chosen. std::array dists; auto cc = fullbb.center(); // The gravity center dists[0] = pl::distance(minc, cc); dists[1] = pl::distance(maxc, cc); dists[2] = pl::distance(ibb.center(), cc); dists[3] = pl::distance(top_left, cc); dists[4] = pl::distance(bottom_right, cc); // The smalles distance from the arranged pile center: auto dist = *(std::min_element(dists.begin(), dists.end())) / norm; auto bindist = pl::distance(ibb.center(), bincenter) / norm; dist = 0.8*dist + 0.2*bindist; // Density is the pack density: how big is the arranged pile double density = 0; if(remaining.empty()) { auto mp = merged_pile; mp.emplace_back(item.transformedShape()); auto chull = sl::convexHull(mp); placers::EdgeCache ec(chull); double circ = ec.circumference() / norm; double bcirc = 2.0*(fullbb.width() + fullbb.height()) / norm; score = 0.5*circ + 0.5*bcirc; } else { // Prepare a variable for the alignment score. // This will indicate: how well is the candidate item aligned with // its neighbors. We will check the alignment with all neighbors and // return the score for the best alignment. So it is enough for the // candidate to be aligned with only one item. auto alignment_score = 1.0; density = std::sqrt((fullbb.width() / norm )* (fullbb.height() / norm)); auto querybb = item.boundingBox(); // Query the spatial index for the neighbors std::vector result; result.reserve(spatindex.size()); if(isBig(item.area())) { spatindex.query(bgi::intersects(querybb), std::back_inserter(result)); } else { smalls_spatindex.query(bgi::intersects(querybb), std::back_inserter(result)); } for(auto& e : result) { // now get the score for the best alignment auto idx = e.second; Item& p = items[idx]; auto parea = p.area(); if(std::abs(1.0 - parea/item.area()) < 1e-6) { auto bb = boundingBox(p.boundingBox(), ibb); auto bbarea = bb.area(); auto ascore = 1.0 - (item.area() + parea)/bbarea; if(ascore < alignment_score) alignment_score = ascore; } } // The final mix of the score is the balance between the distance // from the full pile center, the pack density and the // alignment with the neighbors if(result.empty()) score = 0.5 * dist + 0.5 * density; else score = 0.40 * dist + 0.40 * density + 0.2 * alignment_score; } } else { // Here there are the small items that should be placed around the // already processed bigger items. // No need to play around with the anchor points, the center will be // just fine for small items score = pl::distance(ibb.center(), bigbb.center()) / norm; } return std::make_tuple(score, fullbb); } // Fill in the placer algorithm configuration with values carefully chosen for // Slic3r. template void fillConfig(PConf& pcfg) { // Align the arranged pile into the center of the bin pcfg.alignment = PConf::Alignment::CENTER; // Start placing the items from the center of the print bed pcfg.starting_point = PConf::Alignment::CENTER; // TODO cannot use rotations until multiple objects of same geometry can // handle different rotations // arranger.useMinimumBoundigBoxRotation(); pcfg.rotations = { 0.0 }; // The accuracy of optimization. // Goes from 0.0 to 1.0 and scales performance as well pcfg.accuracy = 0.65f; pcfg.parallel = true; } // Type trait for an arranger class for different bin types (box, circle, // polygon, etc...) template class AutoArranger {}; // A class encapsulating the libnest2d Nester class and extending it with other // management and spatial index structures for acceleration. template class _ArrBase { public: // Useful type shortcuts... using Placer = TPacker; using Selector = FirstFitSelection; using Packer = Nester; using PConfig = typename Packer::PlacementConfig; using Distance = TCoord; using Pile = TMultiShape; protected: Packer m_pck; PConfig m_pconf; // Placement configuration double m_bin_area; SpatIndex m_rtree; // spatial index for the normal (bigger) objects SpatIndex m_smallsrtree; // spatial index for only the smaller items double m_norm; // A coefficient to scale distances Pile m_merged_pile; // The already merged pile (vector of items) Box m_pilebb; // The bounding box of the merged pile. ItemGroup m_remaining; // Remaining items (m_items at the beginning) ItemGroup m_items; // The items to be packed public: _ArrBase(const TBin& bin, Distance dist, std::function progressind, std::function stopcond): m_pck(bin, dist), m_bin_area(sl::area(bin)), m_norm(std::sqrt(sl::area(bin))) { fillConfig(m_pconf); // Set up a callback that is called just before arranging starts // This functionality is provided by the Nester class (m_pack). m_pconf.before_packing = [this](const Pile& merged_pile, // merged pile const ItemGroup& items, // packed items const ItemGroup& remaining) // future items to be packed { m_items = items; m_merged_pile = merged_pile; m_remaining = remaining; m_pilebb = sl::boundingBox(merged_pile); m_rtree.clear(); m_smallsrtree.clear(); // We will treat big items (compared to the print bed) differently auto isBig = [this](double a) { return a/m_bin_area > BIG_ITEM_TRESHOLD ; }; for(unsigned idx = 0; idx < items.size(); ++idx) { Item& itm = items[idx]; if(isBig(itm.area())) m_rtree.insert({itm.boundingBox(), idx}); m_smallsrtree.insert({itm.boundingBox(), idx}); } }; m_pck.progressIndicator(progressind); m_pck.stopCondition(stopcond); } template inline IndexedPackGroup operator()(Args&&...args) { m_rtree.clear(); return m_pck.executeIndexed(std::forward(args)...); } inline void preload(const PackGroup& pg) { m_pconf.alignment = PConfig::Alignment::DONT_ALIGN; m_pconf.object_function = nullptr; // drop the special objectfunction m_pck.preload(pg); // Build the rtree for queries to work for(const ItemGroup& grp : pg) for(unsigned idx = 0; idx < grp.size(); ++idx) { Item& itm = grp[idx]; m_rtree.insert({itm.boundingBox(), idx}); } m_pck.configure(m_pconf); } bool is_colliding(const Item& item) { if(m_rtree.empty()) return false; std::vector result; m_rtree.query(bgi::intersects(item.boundingBox()), std::back_inserter(result)); return !result.empty(); } }; // Arranger specialization for a Box shaped bin. template<> class AutoArranger: public _ArrBase { public: AutoArranger(const Box& bin, Distance dist, std::function progressind = [](unsigned){}, std::function stopcond = [](){return false;}): _ArrBase(bin, dist, progressind, stopcond) { // Here we set up the actual object function that calls the common // object function for all bin shapes than does an additional inside // check for the arranged pile. m_pconf.object_function = [this, bin] (const Item &item) { auto result = objfunc(bin.center(), m_merged_pile, m_pilebb, m_items, item, m_bin_area, m_norm, m_rtree, m_smallsrtree, m_remaining); double score = std::get<0>(result); auto& fullbb = std::get<1>(result); double miss = Placer::overfit(fullbb, bin); miss = miss > 0? miss : 0; score += miss*miss; return score; }; m_pck.configure(m_pconf); } }; using lnCircle = libnest2d::_Circle; inline lnCircle to_lnCircle(const Circle& circ) { return lnCircle({circ.center()(0), circ.center()(1)}, circ.radius()); } // Arranger specialization for circle shaped bin. template<> class AutoArranger: public _ArrBase { public: AutoArranger(const lnCircle& bin, Distance dist, std::function progressind = [](unsigned){}, std::function stopcond = [](){return false;}): _ArrBase(bin, dist, progressind, stopcond) { // As with the box, only the inside check is different. m_pconf.object_function = [this, &bin] (const Item &item) { auto result = objfunc(bin.center(), m_merged_pile, m_pilebb, m_items, item, m_bin_area, m_norm, m_rtree, m_smallsrtree, m_remaining); double score = std::get<0>(result); auto isBig = [this](const Item& itm) { return itm.area()/m_bin_area > BIG_ITEM_TRESHOLD ; }; if(isBig(item)) { auto mp = m_merged_pile; mp.push_back(item.transformedShape()); auto chull = sl::convexHull(mp); double miss = Placer::overfit(chull, bin); if(miss < 0) miss = 0; score += miss*miss; } return score; }; m_pck.configure(m_pconf); } }; // Arranger specialization for a generalized polygon. // Warning: this is unfinished business. It may or may not work. template<> class AutoArranger: public _ArrBase { public: AutoArranger(const PolygonImpl& bin, Distance dist, std::function progressind = [](unsigned){}, std::function stopcond = [](){return false;}): _ArrBase(bin, dist, progressind, stopcond) { m_pconf.object_function = [this, &bin] (const Item &item) { auto binbb = sl::boundingBox(bin); auto result = objfunc(binbb.center(), m_merged_pile, m_pilebb, m_items, item, m_bin_area, m_norm, m_rtree, m_smallsrtree, m_remaining); double score = std::get<0>(result); return score; }; m_pck.configure(m_pconf); } }; // Specialization with no bin. In this case the arranger should just arrange // all objects into a minimum sized pile but it is not limited by a bin. A // consequence is that only one pile should be created. template<> class AutoArranger: public _ArrBase { public: AutoArranger(Distance dist, std::function progressind, std::function stopcond): _ArrBase(Box(0, 0), dist, progressind, stopcond) { this->m_pconf.object_function = [this] (const Item &item) { auto result = objfunc({0, 0}, m_merged_pile, m_pilebb, m_items, item, 0, m_norm, m_rtree, m_smallsrtree, m_remaining); return std::get<0>(result); }; this->m_pck.configure(m_pconf); } }; // A container which stores a pointer to the 3D object and its projected // 2D shape from top view. using ShapeData2D = std::vector>; ShapeData2D projectModelFromTop(const Slic3r::Model &model, const WipeTowerInfo &wti, double tolerance) { ShapeData2D ret; // Count all the items on the bin (all the object's instances) auto s = std::accumulate(model.objects.begin(), model.objects.end(), size_t(0), [](size_t s, ModelObject* o) { return s + o->instances.size(); }); ret.reserve(s); for(ModelObject* objptr : model.objects) { if (! objptr->instances.empty()) { // TODO export the exact 2D projection. Cannot do it as libnest2d // does not support concave shapes (yet). ClipperLib::Path clpath; // Object instances should carry the same scaling and // x, y rotation that is why we use the first instance. { ModelInstance *finst = objptr->instances.front(); Vec3d rotation = finst->get_rotation(); rotation.z() = 0.; Transform3d trafo_instance = Geometry::assemble_transform( Vec3d::Zero(), rotation, finst->get_scaling_factor(), finst->get_mirror()); Polygon p = objptr->convex_hull_2d(trafo_instance); assert(!p.points.empty()); // this may happen for malformed models, see: // https://github.com/prusa3d/PrusaSlicer/issues/2209 if (p.points.empty()) continue; if(tolerance > EPSILON) { Polygons pp { p }; pp = p.simplify(scaled(tolerance)); if (!pp.empty()) p = pp.front(); } p.reverse(); assert(!p.is_counter_clockwise()); clpath = Slic3rMultiPoint_to_ClipperPath(p); auto firstp = clpath.front(); clpath.emplace_back(firstp); } Vec3d rotation0 = objptr->instances.front()->get_rotation(); rotation0(2) = 0.; for(ModelInstance* objinst : objptr->instances) { ClipperLib::Polygon pn; pn.Contour = clpath; // Efficient conversion to item. Item item(std::move(pn)); // Invalid geometries would throw exceptions when arranging if(item.vertexCount() > 3) { item.rotation(Geometry::rotation_diff_z(rotation0, objinst->get_rotation())); item.translation({ scaled(objinst->get_offset(X)), scaled(objinst->get_offset(Y)) }); ret.emplace_back(objinst, item); } } } } // The wipe tower is a separate case (in case there is one), let's duplicate the code if (wti.is_wipe_tower) { Points pts; pts.emplace_back(coord_t(scale_(0.)), coord_t(scale_(0.))); pts.emplace_back(coord_t(scale_(wti.bb_size(0))), coord_t(scale_(0.))); pts.emplace_back(coord_t(scale_(wti.bb_size(0))), coord_t(scale_(wti.bb_size(1)))); pts.emplace_back(coord_t(scale_(-0.)), coord_t(scale_(wti.bb_size(1)))); pts.emplace_back(coord_t(scale_(-0.)), coord_t(scale_(0.))); Polygon p(std::move(pts)); ClipperLib::Path clpath = Slic3rMultiPoint_to_ClipperPath(p); ClipperLib::Polygon pn; pn.Contour = clpath; // Efficient conversion to item. Item item(std::move(pn)); item.rotation(wti.rotation), item.translation({ scaled(wti.pos(0)), scaled(wti.pos(1)) }); ret.emplace_back(nullptr, item); } return ret; } // Apply the calculated translations and rotations (currently disabled) to the // Model object instances. void applyResult( IndexedPackGroup::value_type& group, Coord batch_offset, ShapeData2D& shapemap, WipeTowerInfo& wti) { for(auto& r : group) { auto idx = r.first; // get the original item index Item& item = r.second; // get the item itself // Get the model instance from the shapemap using the index ModelInstance *inst_ptr = shapemap[idx].first; // Get the transformation data from the item object and scale it // appropriately auto off = item.translation(); Radians rot = item.rotation(); Vec3d foff(off.X*SCALING_FACTOR + batch_offset, off.Y*SCALING_FACTOR, inst_ptr ? inst_ptr->get_offset()(Z) : 0.); if (inst_ptr) { // write the transformation data into the model instance inst_ptr->set_rotation(Z, rot); inst_ptr->set_offset(foff); } else { // this is the wipe tower - we will modify the struct with the info // and leave it up to the called to actually move the wipe tower wti.pos = Vec2d(foff(0), foff(1)); wti.rotation = rot; } } } // Get the type of bed geometry from a simple vector of points. BedShapeHint bedShape(const Polyline &bed) { BedShapeHint ret; auto x = [](const Point& p) { return p(0); }; auto y = [](const Point& p) { return p(1); }; auto width = [x](const BoundingBox& box) { return x(box.max) - x(box.min); }; auto height = [y](const BoundingBox& box) { return y(box.max) - y(box.min); }; auto area = [&width, &height](const BoundingBox& box) { double w = width(box); double h = height(box); return w*h; }; auto poly_area = [](Polyline p) { Polygon pp; pp.points.reserve(p.points.size() + 1); pp.points = std::move(p.points); pp.points.emplace_back(pp.points.front()); return std::abs(pp.area()); }; auto distance_to = [x, y](const Point& p1, const Point& p2) { double dx = x(p2) - x(p1); double dy = y(p2) - y(p1); return std::sqrt(dx*dx + dy*dy); }; auto bb = bed.bounding_box(); auto isCircle = [bb, distance_to](const Polyline& polygon) { auto center = bb.center(); std::vector vertex_distances; double avg_dist = 0; for (auto pt: polygon.points) { double distance = distance_to(center, pt); vertex_distances.push_back(distance); avg_dist += distance; } avg_dist /= vertex_distances.size(); Circle ret(center, avg_dist); for(auto el : vertex_distances) { if (std::abs(el - avg_dist) > 10 * SCALED_EPSILON) { ret = Circle(); break; } } return ret; }; auto parea = poly_area(bed); if( (1.0 - parea/area(bb)) < 1e-3 ) { ret.type = BedShapeType::BOX; ret.shape.box = bb; } else if(auto c = isCircle(bed)) { ret.type = BedShapeType::CIRCLE; ret.shape.circ = c; } else { ret.type = BedShapeType::IRREGULAR; ret.shape.polygon = bed; } // Determine the bed shape by hand return ret; } static const SLIC3R_CONSTEXPR double SIMPLIFY_TOLERANCE_MM = 0.1; // The final client function to arrange the Model. A progress indicator and // a stop predicate can be also be passed to control the process. bool arrange(Model &model, // The model with the geometries WipeTowerInfo& wti, // Wipe tower info coord_t min_obj_distance, // Has to be in scaled (clipper) measure const Polyline &bed, // The bed geometry. BedShapeHint bedhint, // Hint about the bed geometry type. bool first_bin_only, // What to do is not all items fit. // Controlling callbacks. std::function progressind, std::function stopcondition) { bool ret = true; // Get the 2D projected shapes with their 3D model instance pointers auto shapemap = arr::projectModelFromTop(model, wti, SIMPLIFY_TOLERANCE_MM); // Copy the references for the shapes only as the arranger expects a // sequence of objects convertible to Item or ClipperPolygon std::vector> shapes; shapes.reserve(shapemap.size()); std::for_each(shapemap.begin(), shapemap.end(), [&shapes] (ShapeData2D::value_type& it) { shapes.push_back(std::ref(it.second)); }); IndexedPackGroup result; // If there is no hint about the shape, we will try to guess if(bedhint.type == BedShapeType::WHO_KNOWS) bedhint = bedShape(bed); BoundingBox bbb(bed); auto& cfn = stopcondition; // Integer ceiling the min distance from the bed perimeters coord_t md = min_obj_distance - SCALED_EPSILON; md = (md % 2) ? md / 2 + 1 : md / 2; auto binbb = Box({libnest2d::Coord{bbb.min(0)} - md, libnest2d::Coord{bbb.min(1)} - md}, {libnest2d::Coord{bbb.max(0)} + md, libnest2d::Coord{bbb.max(1)} + md}); switch(bedhint.type) { case BedShapeType::BOX: { // Create the arranger for the box shaped bed AutoArranger arrange(binbb, min_obj_distance, progressind, cfn); // Arrange and return the items with their respective indices within the // input sequence. result = arrange(shapes.begin(), shapes.end()); break; } case BedShapeType::CIRCLE: { auto c = bedhint.shape.circ; auto cc = to_lnCircle(c); AutoArranger arrange(cc, min_obj_distance, progressind, cfn); result = arrange(shapes.begin(), shapes.end()); break; } case BedShapeType::IRREGULAR: case BedShapeType::WHO_KNOWS: { using P = libnest2d::PolygonImpl; auto ctour = Slic3rMultiPoint_to_ClipperPath(bed); P irrbed = sl::create(std::move(ctour)); AutoArranger

arrange(irrbed, min_obj_distance, progressind, cfn); // Arrange and return the items with their respective indices within the // input sequence. result = arrange(shapes.begin(), shapes.end()); break; } }; if(result.empty() || stopcondition()) return false; if(first_bin_only) { applyResult(result.front(), 0, shapemap, wti); } else { const auto STRIDE_PADDING = 1.2; Coord stride = static_cast(STRIDE_PADDING* binbb.width()*SCALING_FACTOR); Coord batch_offset = 0; for(auto& group : result) { applyResult(group, batch_offset, shapemap, wti); // Only the first pack group can be placed onto the print bed. The // other objects which could not fit will be placed next to the // print bed batch_offset += stride; } } for(auto objptr : model.objects) objptr->invalidate_bounding_box(); return ret && result.size() == 1; } void find_new_position(const Model &model, ModelInstancePtrs toadd, coord_t min_obj_distance, const Polyline &bed, WipeTowerInfo& wti) { // Get the 2D projected shapes with their 3D model instance pointers auto shapemap = arr::projectModelFromTop(model, wti, SIMPLIFY_TOLERANCE_MM); // Copy the references for the shapes only as the arranger expects a // sequence of objects convertible to Item or ClipperPolygon PackGroup preshapes; preshapes.emplace_back(); ItemGroup shapes; preshapes.front().reserve(shapemap.size()); std::vector shapes_ptr; shapes_ptr.reserve(toadd.size()); IndexedPackGroup result; // If there is no hint about the shape, we will try to guess BedShapeHint bedhint = bedShape(bed); BoundingBox bbb(bed); // Integer ceiling the min distance from the bed perimeters coord_t md = min_obj_distance - SCALED_EPSILON; md = (md % 2) ? md / 2 + 1 : md / 2; auto binbb = Box({libnest2d::Coord{bbb.min(0)} - md, libnest2d::Coord{bbb.min(1)} - md}, {libnest2d::Coord{bbb.max(0)} + md, libnest2d::Coord{bbb.max(1)} + md}); for(auto it = shapemap.begin(); it != shapemap.end(); ++it) { if(std::find(toadd.begin(), toadd.end(), it->first) == toadd.end()) { if(it->second.isInside(binbb)) // just ignore items which are outside preshapes.front().emplace_back(std::ref(it->second)); } else { shapes_ptr.emplace_back(it->first); shapes.emplace_back(std::ref(it->second)); } } auto try_first_to_center = [&shapes, &shapes_ptr, &binbb] (std::function is_colliding, std::function preload) { // Try to put the first item to the center, as the arranger will not // do this for us. auto shptrit = shapes_ptr.begin(); for(auto shit = shapes.begin(); shit != shapes.end(); ++shit, ++shptrit) { // Try to place items to the center Item& itm = *shit; auto ibb = itm.boundingBox(); auto d = binbb.center() - ibb.center(); itm.translate(d); if(!is_colliding(itm)) { preload(itm); auto offset = itm.translation(); Radians rot = itm.rotation(); ModelInstance *minst = *shptrit; Vec3d foffset(offset.X*SCALING_FACTOR, offset.Y*SCALING_FACTOR, minst->get_offset()(Z)); // write the transformation data into the model instance minst->set_rotation(Z, rot); minst->set_offset(foffset); shit = shapes.erase(shit); shptrit = shapes_ptr.erase(shptrit); break; } } }; switch(bedhint.type) { case BedShapeType::BOX: { // Create the arranger for the box shaped bed AutoArranger arrange(binbb, min_obj_distance); if(!preshapes.front().empty()) { // If there is something on the plate arrange.preload(preshapes); try_first_to_center( [&arrange](const Item& itm) {return arrange.is_colliding(itm);}, [&arrange](Item& itm) { arrange.preload({{itm}}); } ); } // Arrange and return the items with their respective indices within the // input sequence. result = arrange(shapes.begin(), shapes.end()); break; } case BedShapeType::CIRCLE: { auto c = bedhint.shape.circ; auto cc = to_lnCircle(c); // Create the arranger for the box shaped bed AutoArranger arrange(cc, min_obj_distance); if(!preshapes.front().empty()) { // If there is something on the plate arrange.preload(preshapes); try_first_to_center( [&arrange](const Item& itm) {return arrange.is_colliding(itm);}, [&arrange](Item& itm) { arrange.preload({{itm}}); } ); } // Arrange and return the items with their respective indices within the // input sequence. result = arrange(shapes.begin(), shapes.end()); break; } case BedShapeType::IRREGULAR: case BedShapeType::WHO_KNOWS: { using P = libnest2d::PolygonImpl; auto ctour = Slic3rMultiPoint_to_ClipperPath(bed); P irrbed = sl::create(std::move(ctour)); AutoArranger

arrange(irrbed, min_obj_distance); if(!preshapes.front().empty()) { // If there is something on the plate arrange.preload(preshapes); try_first_to_center( [&arrange](const Item& itm) {return arrange.is_colliding(itm);}, [&arrange](Item& itm) { arrange.preload({{itm}}); } ); } // Arrange and return the items with their respective indices within the // input sequence. result = arrange(shapes.begin(), shapes.end()); break; } }; // Now we go through the result which will contain the fixed and the moving // polygons as well. We will have to search for our item. const auto STRIDE_PADDING = 1.2; Coord stride = Coord(STRIDE_PADDING*binbb.width()*SCALING_FACTOR); Coord batch_offset = 0; for(auto& group : result) { for(auto& r : group) if(r.first < shapes.size()) { Item& resultitem = r.second; unsigned idx = r.first; auto offset = resultitem.translation(); Radians rot = resultitem.rotation(); ModelInstance *minst = shapes_ptr[idx]; Vec3d foffset(offset.X*SCALING_FACTOR + batch_offset, offset.Y*SCALING_FACTOR, minst->get_offset()(Z)); // write the transformation data into the model instance minst->set_rotation(Z, rot); minst->set_offset(foffset); } batch_offset += stride; } } } }