839 lines
28 KiB
C++
839 lines
28 KiB
C++
#include "Arrange.hpp"
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#include "Geometry.hpp"
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#include "SVG.hpp"
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#include "MTUtils.hpp"
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#include <libnest2d/backends/clipper/geometries.hpp>
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#include <libnest2d/optimizers/nlopt/subplex.hpp>
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#include <libnest2d/placers/nfpplacer.hpp>
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#include <libnest2d/selections/firstfit.hpp>
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#include <numeric>
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#include <ClipperUtils.hpp>
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#include <boost/geometry/index/rtree.hpp>
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#include <boost/multiprecision/integer.hpp>
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#include <boost/rational.hpp>
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namespace libnest2d {
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#if !defined(_MSC_VER) && defined(__SIZEOF_INT128__) && !defined(__APPLE__)
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using LargeInt = __int128;
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#else
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using LargeInt = boost::multiprecision::int128_t;
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template<> struct _NumTag<LargeInt>
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{
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using Type = ScalarTag;
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};
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#endif
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template<class T> struct _NumTag<boost::rational<T>>
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{
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using Type = RationalTag;
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};
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namespace nfp {
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template<class S> struct NfpImpl<S, NfpLevel::CONVEX_ONLY>
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{
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NfpResult<S> operator()(const S &sh, const S &other)
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{
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return nfpConvexOnly<S, boost::rational<LargeInt>>(sh, other);
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}
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};
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} // namespace nfp
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} // namespace libnest2d
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namespace Slic3r {
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template<class Tout = double, class = FloatingOnly<Tout>>
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inline SLIC3R_CONSTEXPR EigenVec<Tout, 2> unscaled(
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const ClipperLib::IntPoint &v) SLIC3R_NOEXCEPT
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{
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return EigenVec<Tout, 2>{unscaled<Tout>(v.X), unscaled<Tout>(v.Y)};
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}
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namespace arrangement {
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using namespace libnest2d;
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namespace clppr = ClipperLib;
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using Item = _Item<clppr::Polygon>;
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using Box = _Box<clppr::IntPoint>;
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using Circle = _Circle<clppr::IntPoint>;
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using Segment = _Segment<clppr::IntPoint>;
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using MultiPolygon = TMultiShape<clppr::Polygon>;
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using PackGroup = _PackGroup<clppr::Polygon>;
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// Only for debugging. Prints the model object vertices on stdout.
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//std::string toString(const Model& model, bool holes = true) {
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// std::stringstream ss;
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// ss << "{\n";
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// for(auto objptr : model.objects) {
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// if(!objptr) continue;
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// auto rmesh = objptr->raw_mesh();
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// for(auto objinst : objptr->instances) {
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// if(!objinst) continue;
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// Slic3r::TriangleMesh tmpmesh = rmesh;
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// // CHECK_ME -> Is the following correct ?
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// tmpmesh.scale(objinst->get_scaling_factor());
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// objinst->transform_mesh(&tmpmesh);
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// ExPolygons expolys = tmpmesh.horizontal_projection();
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// for(auto& expoly_complex : expolys) {
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// ExPolygons tmp = expoly_complex.simplify(scaled<double>(1.));
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// if(tmp.empty()) continue;
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// ExPolygon expoly = tmp.front();
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// expoly.contour.make_clockwise();
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// for(auto& h : expoly.holes) h.make_counter_clockwise();
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// ss << "\t{\n";
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// ss << "\t\t{\n";
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// for(auto v : expoly.contour.points) ss << "\t\t\t{"
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// << v(0) << ", "
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// << v(1) << "},\n";
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// {
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// auto v = expoly.contour.points.front();
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// ss << "\t\t\t{" << v(0) << ", " << v(1) << "},\n";
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// }
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// ss << "\t\t},\n";
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// // Holes:
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// ss << "\t\t{\n";
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// if(holes) for(auto h : expoly.holes) {
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// ss << "\t\t\t{\n";
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// for(auto v : h.points) ss << "\t\t\t\t{"
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// << v(0) << ", "
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// << v(1) << "},\n";
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// {
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// auto v = h.points.front();
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// ss << "\t\t\t\t{" << v(0) << ", " << v(1) << "},\n";
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// }
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// ss << "\t\t\t},\n";
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// }
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// ss << "\t\t},\n";
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// ss << "\t},\n";
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// }
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// }
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// }
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// ss << "}\n";
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// return ss.str();
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//}
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// Debugging: Save model to svg file.
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//void toSVG(SVG& svg, const Model& model) {
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// for(auto objptr : model.objects) {
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// if(!objptr) continue;
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// auto rmesh = objptr->raw_mesh();
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// for(auto objinst : objptr->instances) {
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// if(!objinst) continue;
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// Slic3r::TriangleMesh tmpmesh = rmesh;
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// tmpmesh.scale(objinst->get_scaling_factor());
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// objinst->transform_mesh(&tmpmesh);
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// ExPolygons expolys = tmpmesh.horizontal_projection();
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// svg.draw(expolys);
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// }
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// }
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//}
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namespace bgi = boost::geometry::index;
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using SpatElement = std::pair<Box, unsigned>;
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using SpatIndex = bgi::rtree< SpatElement, bgi::rstar<16, 4> >;
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using ItemGroup = std::vector<std::reference_wrapper<Item>>;
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const double BIG_ITEM_TRESHOLD = 0.02;
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Box boundingBox(const Box& pilebb, const Box& ibb ) {
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auto& pminc = pilebb.minCorner();
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auto& pmaxc = pilebb.maxCorner();
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auto& iminc = ibb.minCorner();
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auto& imaxc = ibb.maxCorner();
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PointImpl minc, maxc;
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setX(minc, std::min(getX(pminc), getX(iminc)));
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setY(minc, std::min(getY(pminc), getY(iminc)));
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setX(maxc, std::max(getX(pmaxc), getX(imaxc)));
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setY(maxc, std::max(getY(pmaxc), getY(imaxc)));
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return Box(minc, maxc);
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}
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// Fill in the placer algorithm configuration with values carefully chosen for
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// Slic3r.
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template<class PConf>
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void fillConfig(PConf& pcfg) {
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// Align the arranged pile into the center of the bin
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pcfg.alignment = PConf::Alignment::CENTER;
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// Start placing the items from the center of the print bed
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pcfg.starting_point = PConf::Alignment::CENTER;
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// TODO cannot use rotations until multiple objects of same geometry can
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// handle different rotations
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// arranger.useMinimumBoundigBoxRotation();
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pcfg.rotations = { 0.0 };
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// The accuracy of optimization.
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// Goes from 0.0 to 1.0 and scales performance as well
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pcfg.accuracy = 0.65f;
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pcfg.parallel = true;
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}
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// Type trait for an arranger class for different bin types (box, circle,
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// polygon, etc...)
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//template<class TBin>
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//class AutoArranger {};
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template<class Bin> clppr::IntPoint center(const Bin& bin) { return bin.center(); }
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template<> clppr::IntPoint center(const clppr::Polygon &bin) { return sl::boundingBox(bin).center(); }
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// A class encapsulating the libnest2d Nester class and extending it with other
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// management and spatial index structures for acceleration.
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template<class TBin>
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class AutoArranger {
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public:
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// Useful type shortcuts...
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using Placer = typename placers::_NofitPolyPlacer<clppr::Polygon, TBin>;
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using Selector = selections::_FirstFitSelection<clppr::Polygon>;
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using Packer = Nester<Placer, Selector>;
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using PConfig = typename Packer::PlacementConfig;
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using Distance = TCoord<PointImpl>;
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protected:
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Packer m_pck;
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PConfig m_pconf; // Placement configuration
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TBin m_bin;
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double m_bin_area; // caching
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PointImpl m_bincenter; // caching
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SpatIndex m_rtree; // spatial index for the normal (bigger) objects
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SpatIndex m_smallsrtree; // spatial index for only the smaller items
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double m_norm; // A coefficient to scale distances
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MultiPolygon m_merged_pile; // The already merged pile (vector of items)
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Box m_pilebb; // The bounding box of the merged pile.
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ItemGroup m_remaining; // Remaining items (m_items at the beginning)
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ItemGroup m_items; // The items to be packed
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// This is "the" object function which is evaluated many times for each
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// vertex (decimated with the accuracy parameter) of each object.
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// Therefore it is upmost crucial for this function to be as efficient
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// as it possibly can be but at the same time, it has to provide
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// reasonable results.
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std::tuple<double /*score*/, Box /*farthest point from bin center*/>
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objfunc(const Item &item )
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{
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const double bin_area = m_bin_area;
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const SpatIndex& spatindex = m_rtree;
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const SpatIndex& smalls_spatindex = m_smallsrtree;
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const ItemGroup& remaining = m_remaining;
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// We will treat big items (compared to the print bed) differently
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auto isBig = [bin_area](double a) {
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return a/bin_area > BIG_ITEM_TRESHOLD ;
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};
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// Candidate item bounding box
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auto ibb = sl::boundingBox(item.transformedShape());
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// Calculate the full bounding box of the pile with the candidate item
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auto fullbb = boundingBox(m_pilebb, ibb);
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// The bounding box of the big items (they will accumulate in the center
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// of the pile
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Box bigbb;
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if(spatindex.empty()) bigbb = fullbb;
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else {
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auto boostbb = spatindex.bounds();
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boost::geometry::convert(boostbb, bigbb);
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}
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// Will hold the resulting score
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double score = 0;
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if(isBig(item.area()) || spatindex.empty()) {
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// This branch is for the bigger items..
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auto minc = ibb.minCorner(); // bottom left corner
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auto maxc = ibb.maxCorner(); // top right corner
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// top left and bottom right corners
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auto top_left = PointImpl{getX(minc), getY(maxc)};
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auto bottom_right = PointImpl{getX(maxc), getY(minc)};
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// Now the distance of the gravity center will be calculated to the
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// five anchor points and the smallest will be chosen.
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std::array<double, 5> dists;
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auto cc = fullbb.center(); // The gravity center
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dists[0] = pl::distance(minc, cc);
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dists[1] = pl::distance(maxc, cc);
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dists[2] = pl::distance(ibb.center(), cc);
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dists[3] = pl::distance(top_left, cc);
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dists[4] = pl::distance(bottom_right, cc);
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// The smalles distance from the arranged pile center:
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double dist = *(std::min_element(dists.begin(), dists.end())) / m_norm;
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double bindist = pl::distance(ibb.center(), m_bincenter) / m_norm;
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dist = 0.8*dist + 0.2*bindist;
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// Density is the pack density: how big is the arranged pile
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double density = 0;
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if(remaining.empty()) {
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auto mp = m_merged_pile;
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mp.emplace_back(item.transformedShape());
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auto chull = sl::convexHull(mp);
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placers::EdgeCache<clppr::Polygon> ec(chull);
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double circ = ec.circumference() / m_norm;
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double bcirc = 2.0*(fullbb.width() + fullbb.height()) / m_norm;
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score = 0.5*circ + 0.5*bcirc;
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} else {
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// Prepare a variable for the alignment score.
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// This will indicate: how well is the candidate item
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// aligned with its neighbors. We will check the alignment
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// with all neighbors and return the score for the best
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// alignment. So it is enough for the candidate to be
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// aligned with only one item.
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auto alignment_score = 1.0;
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auto querybb = item.boundingBox();
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density = std::sqrt((fullbb.width() / m_norm )*
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(fullbb.height() / m_norm));
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// Query the spatial index for the neighbors
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std::vector<SpatElement> result;
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result.reserve(spatindex.size());
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if(isBig(item.area())) {
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spatindex.query(bgi::intersects(querybb),
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std::back_inserter(result));
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} else {
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smalls_spatindex.query(bgi::intersects(querybb),
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std::back_inserter(result));
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}
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// now get the score for the best alignment
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for(auto& e : result) {
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auto idx = e.second;
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Item& p = m_items[idx];
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auto parea = p.area();
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if(std::abs(1.0 - parea/item.area()) < 1e-6) {
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auto bb = boundingBox(p.boundingBox(), ibb);
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auto bbarea = bb.area();
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auto ascore = 1.0 - (item.area() + parea)/bbarea;
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if(ascore < alignment_score) alignment_score = ascore;
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}
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}
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// The final mix of the score is the balance between the
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// distance from the full pile center, the pack density and
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// the alignment with the neighbors
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if (result.empty())
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score = 0.5 * dist + 0.5 * density;
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else
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score = 0.40 * dist + 0.40 * density + 0.2 * alignment_score;
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}
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} else {
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// Here there are the small items that should be placed around the
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// already processed bigger items.
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// No need to play around with the anchor points, the center will be
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// just fine for small items
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score = pl::distance(ibb.center(), bigbb.center()) / m_norm;
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}
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return std::make_tuple(score, fullbb);
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}
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std::function<double(const Item&)> get_objfn();
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public:
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AutoArranger(const TBin & bin,
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Distance dist,
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std::function<void(unsigned)> progressind,
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std::function<bool(void)> stopcond)
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: m_pck(bin, dist)
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, m_bin(bin)
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, m_bin_area(sl::area(bin))
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, m_bincenter(center(bin))
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, m_norm(std::sqrt(m_bin_area))
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{
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fillConfig(m_pconf);
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// Set up a callback that is called just before arranging starts
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// This functionality is provided by the Nester class (m_pack).
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m_pconf.before_packing =
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[this](const MultiPolygon& merged_pile, // merged pile
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const ItemGroup& items, // packed items
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const ItemGroup& remaining) // future items to be packed
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{
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m_items = items;
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m_merged_pile = merged_pile;
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m_remaining = remaining;
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m_pilebb = sl::boundingBox(merged_pile);
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m_rtree.clear();
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m_smallsrtree.clear();
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// We will treat big items (compared to the print bed) differently
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auto isBig = [this](double a) {
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return a/m_bin_area > BIG_ITEM_TRESHOLD ;
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};
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for(unsigned idx = 0; idx < items.size(); ++idx) {
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Item& itm = items[idx];
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if(isBig(itm.area())) m_rtree.insert({itm.boundingBox(), idx});
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m_smallsrtree.insert({itm.boundingBox(), idx});
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}
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};
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m_pconf.object_function = get_objfn();
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if (progressind) m_pck.progressIndicator(progressind);
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if (stopcond) m_pck.stopCondition(stopcond);
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m_pck.configure(m_pconf);
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}
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template<class...Args> inline PackGroup operator()(Args&&...args) {
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m_rtree.clear();
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return m_pck.execute(std::forward<Args>(args)...);
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}
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inline void preload(std::vector<Item>& fixeditems) {
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m_pconf.alignment = PConfig::Alignment::DONT_ALIGN;
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// m_pconf.object_function = nullptr; // drop the special objectfunction
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// m_pck.preload(pg);
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// Build the rtree for queries to work
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for(unsigned idx = 0; idx < fixeditems.size(); ++idx) {
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Item& itm = fixeditems[idx];
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itm.markAsFixed();
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m_rtree.insert({itm.boundingBox(), idx});
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}
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m_pck.configure(m_pconf);
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}
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bool is_colliding(const Item& item) {
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if(m_rtree.empty()) return false;
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std::vector<SpatElement> result;
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m_rtree.query(bgi::intersects(item.boundingBox()),
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std::back_inserter(result));
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return !result.empty();
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}
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};
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template<> std::function<double(const Item&)> AutoArranger<Box>::get_objfn()
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{
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return [this](const Item &itm) {
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auto result = objfunc(itm);
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double score = std::get<0>(result);
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auto& fullbb = std::get<1>(result);
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double miss = Placer::overfit(fullbb, m_bin);
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miss = miss > 0? miss : 0;
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score += miss*miss;
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return score;
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};
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}
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template<> std::function<double(const Item&)> AutoArranger<Circle>::get_objfn()
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{
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return [this](const Item &item) {
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auto result = objfunc(item);
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double score = std::get<0>(result);
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auto isBig = [this](const Item& itm) {
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return itm.area()/m_bin_area > BIG_ITEM_TRESHOLD ;
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};
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if(isBig(item)) {
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auto mp = m_merged_pile;
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mp.push_back(item.transformedShape());
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auto chull = sl::convexHull(mp);
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double miss = Placer::overfit(chull, m_bin);
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if(miss < 0) miss = 0;
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score += miss*miss;
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}
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return score;
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};
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}
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template<> std::function<double(const Item&)> AutoArranger<clppr::Polygon>::get_objfn()
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{
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return [this] (const Item &item) { return std::get<0>(objfunc(item)); };
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}
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// Arranger specialization for a Box shaped bin.
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//template<> class AutoArranger<Box>: public _ArrBase<Box> {
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//public:
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// AutoArranger(const Box& bin, Distance dist,
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// std::function<void(unsigned)> progressind = [](unsigned){},
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// std::function<bool(void)> stopcond = [](){return false;}):
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// _ArrBase<Box>(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(), item);
|
|
|
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// double score = std::get<0>(result);
|
|
// auto& fullbb = std::get<1>(result);
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|
|
|
// double miss = Placer::overfit(fullbb, bin);
|
|
// miss = miss > 0? miss : 0;
|
|
// score += miss*miss;
|
|
|
|
// return score;
|
|
// };
|
|
|
|
// m_pck.configure(m_pconf);
|
|
// }
|
|
//};
|
|
|
|
inline Circle to_lnCircle(const CircleBed& circ) {
|
|
return Circle({circ.center()(0), circ.center()(1)}, circ.radius());
|
|
}
|
|
|
|
//// Arranger specialization for circle shaped bin.
|
|
//template<> class AutoArranger<Circle>: public _ArrBase<Circle> {
|
|
//public:
|
|
|
|
// AutoArranger(const Circle& bin, Distance dist,
|
|
// std::function<void(unsigned)> progressind = [](unsigned){},
|
|
// std::function<bool(void)> stopcond = [](){return false;}):
|
|
// _ArrBase<Circle>(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(), item);
|
|
|
|
// 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<PolygonImpl>: public _ArrBase<PolygonImpl> {
|
|
//public:
|
|
// AutoArranger(const PolygonImpl& bin, Distance dist,
|
|
// std::function<void(unsigned)> progressind = [](unsigned){},
|
|
// std::function<bool(void)> stopcond = [](){return false;}):
|
|
// _ArrBase<PolygonImpl>(bin, dist, progressind, stopcond)
|
|
// {
|
|
// m_pconf.object_function = [this, &bin] (const Item &item) {
|
|
|
|
// auto binbb = sl::boundingBox(bin);
|
|
// auto result = objfunc(binbb.center(), item);
|
|
// double score = std::get<0>(result);
|
|
|
|
// return score;
|
|
// };
|
|
|
|
// m_pck.configure(m_pconf);
|
|
// }
|
|
//};
|
|
|
|
// 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(X); };
|
|
auto y = [](const Point& p) { return p(Y); };
|
|
|
|
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<double> 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();
|
|
|
|
CircleBed ret(center, avg_dist);
|
|
for(auto el : vertex_distances)
|
|
{
|
|
if (std::abs(el - avg_dist) > 10 * SCALED_EPSILON) {
|
|
ret = CircleBed();
|
|
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;
|
|
}
|
|
|
|
template<class BinT> // Arrange for arbitrary bin type
|
|
PackGroup _arrange(std::vector<Item> & shapes,
|
|
std::vector<Item> & excludes,
|
|
const BinT & bin,
|
|
coord_t minobjd,
|
|
std::function<void(unsigned)> prind,
|
|
std::function<bool()> stopfn)
|
|
{
|
|
AutoArranger<BinT> arranger{bin, minobjd, prind, stopfn};
|
|
|
|
for(auto it = excludes.begin(); it != excludes.end(); ++it)
|
|
if (!sl::isInside(it->transformedShape(), bin))
|
|
it = excludes.erase(it);
|
|
|
|
// If there is something on the plate
|
|
if(!excludes.empty()) {
|
|
// arranger.preload(preshapes);
|
|
auto binbb = sl::boundingBox(bin);
|
|
|
|
// Try to put the first item to the center, as the arranger will not
|
|
// do this for us.
|
|
for (auto it = shapes.begin(); it != shapes.end(); ++it) {
|
|
Item &itm = *it;
|
|
auto ibb = itm.boundingBox();
|
|
auto d = binbb.center() - ibb.center();
|
|
itm.translate(d);
|
|
|
|
if (!arranger.is_colliding(itm)) {
|
|
itm.markAsFixed();
|
|
// arranger.preload({{itm}});
|
|
|
|
// Write the transformation data into the item. The callback
|
|
// was set on the instantiation of Item and calls the
|
|
// Arrangeable interface.
|
|
it->callApplyFunction(0);
|
|
|
|
// Remove this item, as it is arranged now
|
|
it = shapes.erase(it);
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
|
|
return arranger(shapes.begin(), shapes.end());
|
|
}
|
|
|
|
inline SLIC3R_CONSTEXPR coord_t stride_padding(coord_t w)
|
|
{
|
|
return w + w / 5;
|
|
}
|
|
|
|
// The final client function for arrangement. A progress indicator and
|
|
// a stop predicate can be also be passed to control the process.
|
|
bool arrange(ArrangeablePtrs & arrangables,
|
|
const ArrangeablePtrs & excludes,
|
|
coord_t min_obj_distance,
|
|
const BedShapeHint & bedhint,
|
|
std::function<void(unsigned)> progressind,
|
|
std::function<bool()> stopcondition)
|
|
{
|
|
bool ret = true;
|
|
namespace clppr = ClipperLib;
|
|
|
|
std::vector<Item> items, fixeditems;
|
|
items.reserve(arrangables.size());
|
|
coord_t binwidth = 0;
|
|
|
|
auto process_arrangeable =
|
|
[](const Arrangeable * arrangeable,
|
|
std::vector<Item> & outp,
|
|
std::function<void(const Item &, unsigned)> applyfn)
|
|
{
|
|
assert(arrangeable);
|
|
|
|
auto arrangeitem = arrangeable->get_arrange_polygon();
|
|
|
|
Polygon & p = std::get<0>(arrangeitem);
|
|
const Vec2crd &offs = std::get<1>(arrangeitem);
|
|
double rotation = std::get<2>(arrangeitem);
|
|
|
|
if (p.is_counter_clockwise()) p.reverse();
|
|
|
|
clppr::Polygon clpath(Slic3rMultiPoint_to_ClipperPath(p));
|
|
|
|
auto firstp = clpath.Contour.front();
|
|
clpath.Contour.emplace_back(firstp);
|
|
|
|
outp.emplace_back(applyfn, std::move(clpath));
|
|
outp.back().rotation(rotation);
|
|
outp.back().translation({offs.x(), offs.y()});
|
|
};
|
|
|
|
for (Arrangeable *arrangeable : arrangables) {
|
|
process_arrangeable(
|
|
arrangeable,
|
|
items,
|
|
// callback called by arrange to apply the result on the arrangeable
|
|
[arrangeable, &binwidth](const Item &itm, unsigned binidx) {
|
|
clppr::cInt stride = binidx * stride_padding(binwidth);
|
|
|
|
clppr::IntPoint offs = itm.translation();
|
|
arrangeable->apply_arrange_result({unscaled(offs.X + stride),
|
|
unscaled(offs.Y)},
|
|
itm.rotation());
|
|
});
|
|
}
|
|
|
|
for (const Arrangeable * fixed: excludes)
|
|
process_arrangeable(fixed, fixeditems, nullptr);
|
|
|
|
// 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& cfn = stopcondition;
|
|
|
|
switch (bedhint.type) {
|
|
case BedShapeType::BOX: {
|
|
// Create the arranger for the box shaped bed
|
|
BoundingBox bbb = bedhint.shape.box;
|
|
bbb.min -= Point{md, md}, bbb.max += Point{md, md};
|
|
Box binbb{{bbb.min(X), bbb.min(Y)}, {bbb.max(X), bbb.max(Y)}};
|
|
binwidth = coord_t(binbb.width());
|
|
|
|
_arrange(items, fixeditems, binbb, min_obj_distance, progressind, cfn);
|
|
break;
|
|
}
|
|
case BedShapeType::CIRCLE: {
|
|
auto c = bedhint.shape.circ;
|
|
auto cc = to_lnCircle(c);
|
|
binwidth = scaled(c.radius());
|
|
|
|
_arrange(items, fixeditems, cc, min_obj_distance, progressind, cfn);
|
|
break;
|
|
}
|
|
case BedShapeType::IRREGULAR: {
|
|
auto ctour = Slic3rMultiPoint_to_ClipperPath(bedhint.shape.polygon);
|
|
auto irrbed = sl::create<clppr::Polygon>(std::move(ctour));
|
|
BoundingBox polybb(bedhint.shape.polygon);
|
|
binwidth = (polybb.max(X) - polybb.min(X));
|
|
|
|
_arrange(items, fixeditems, irrbed, min_obj_distance, progressind, cfn);
|
|
break;
|
|
}
|
|
case BedShapeType::INFINITE: {
|
|
// const InfiniteBed& nobin = bedhint.shape.infinite;
|
|
//Box infbb{{nobin.center.x(), nobin.center.y()}};
|
|
Box infbb;
|
|
|
|
_arrange(items, fixeditems, infbb, min_obj_distance, progressind, cfn);
|
|
break;
|
|
}
|
|
case BedShapeType::UNKNOWN: {
|
|
// We know nothing about the bed, let it be infinite and zero centered
|
|
_arrange(items, fixeditems, Box{}, min_obj_distance, progressind, cfn);
|
|
break;
|
|
}
|
|
};
|
|
|
|
if(stopcondition()) return false;
|
|
|
|
return ret;
|
|
}
|
|
|
|
// Arrange, without the fixed items (excludes)
|
|
bool arrange(ArrangeablePtrs & inp,
|
|
coord_t min_d,
|
|
const BedShapeHint & bedhint,
|
|
std::function<void(unsigned)> prfn,
|
|
std::function<bool()> stopfn)
|
|
{
|
|
return arrange(inp, {}, min_d, bedhint, prfn, stopfn);
|
|
}
|
|
|
|
} // namespace arr
|
|
} // namespace Slic3r
|