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Merge remote-tracking branch 'remotes/origin/feature_arrange_with_libnest2d'

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This commit is contained in:
bubnikv 2018-08-03 22:38:44 +02:00
commit 02d6d04185
14 changed files with 995 additions and 552 deletions
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2
xs/CMakeLists.txt
View File

@ -136,6 +136,7 @@ add_library(libslic3r STATIC
${LIBDIR}/libslic3r/Line.hpp
${LIBDIR}/libslic3r/Model.cpp
${LIBDIR}/libslic3r/Model.hpp
${LIBDIR}/libslic3r/ModelArrange.hpp
${LIBDIR}/libslic3r/MotionPlanner.cpp
${LIBDIR}/libslic3r/MotionPlanner.hpp
${LIBDIR}/libslic3r/MultiPoint.cpp
@ -729,6 +730,7 @@ set(LIBNEST2D_UNITTESTS ON CACHE BOOL "Force generating unittests for libnest2d"
add_subdirectory(${LIBDIR}/libnest2d)
target_include_directories(libslic3r PUBLIC BEFORE ${LIBNEST2D_INCLUDES})
target_include_directories(libslic3r_gui PUBLIC BEFORE ${LIBNEST2D_INCLUDES})
message(STATUS "Libnest2D Libraries: ${LIBNEST2D_LIBRARIES}")
target_link_libraries(libslic3r ${LIBNEST2D_LIBRARIES})

3
xs/src/libnest2d/cmake_modules/DownloadNLopt.cmake
View File

@ -27,5 +27,6 @@ set(NLOPT_LINK_PYTHON OFF CACHE BOOL "" FORCE)
add_subdirectory(${nlopt_SOURCE_DIR} ${nlopt_BINARY_DIR})
set(NLopt_LIBS nlopt)
set(NLopt_INCLUDE_DIR ${nlopt_BINARY_DIR})
set(NLopt_INCLUDE_DIR ${nlopt_BINARY_DIR}
${nlopt_BINARY_DIR}/src/api)
set(SHARED_LIBS_STATE ${SHARED_STATE})

137
xs/src/libnest2d/examples/main.cpp
View File

@ -545,59 +545,128 @@ void arrangeRectangles() {
// input.insert(input.end(), crasher.begin(), crasher.end());
Box bin(250*SCALE, 210*SCALE);
// PolygonImpl bin = {
// {
// {25*SCALE, 0},
// {0, 25*SCALE},
// {0, 225*SCALE},
// {25*SCALE, 250*SCALE},
// {225*SCALE, 250*SCALE},
// {250*SCALE, 225*SCALE},
// {250*SCALE, 25*SCALE},
// {225*SCALE, 0},
// {25*SCALE, 0}
// },
// {}
// };
auto min_obj_distance = static_cast<Coord>(0*SCALE);
using Placer = NfpPlacer;
using Placer = strategies::_NofitPolyPlacer<PolygonImpl, Box>;
using Packer = Arranger<Placer, FirstFitSelection>;
Packer arrange(bin, min_obj_distance);
Packer::PlacementConfig pconf;
pconf.alignment = Placer::Config::Alignment::CENTER;
pconf.starting_point = Placer::Config::Alignment::BOTTOM_LEFT;
pconf.starting_point = Placer::Config::Alignment::CENTER;
pconf.rotations = {0.0/*, Pi/2.0, Pi, 3*Pi/2*/};
pconf.accuracy = 0.5f;
double norm_2 = std::nan("");
pconf.object_function = [&bin, &norm_2](Placer::Pile pile, const Item& item,
double /*area*/, double norm, double penality) {
// auto bincenter = ShapeLike::boundingBox(bin).center();
// pconf.object_function = [&bin, bincenter](
// Placer::Pile pile, const Item& item,
// double /*area*/, double norm, double penality) {
using pl = PointLike;
// using pl = PointLike;
auto bb = ShapeLike::boundingBox(pile);
auto ibb = item.boundingBox();
auto minc = ibb.minCorner();
auto maxc = ibb.maxCorner();
// static const double BIG_ITEM_TRESHOLD = 0.2;
// static const double GRAVITY_RATIO = 0.5;
// static const double DENSITY_RATIO = 1.0 - GRAVITY_RATIO;
if(std::isnan(norm_2)) norm_2 = pow(norm, 2);
// // We will treat big items (compared to the print bed) differently
// NfpPlacer::Pile bigs;
// bigs.reserve(pile.size());
// for(auto& p : pile) {
// auto pbb = ShapeLike::boundingBox(p);
// auto na = std::sqrt(pbb.width()*pbb.height())/norm;
// if(na > BIG_ITEM_TRESHOLD) bigs.emplace_back(p);
// }
// We get the distance of the reference point from the center of the
// heat bed
auto cc = bb.center();
auto top_left = PointImpl{getX(minc), getY(maxc)};
auto bottom_right = PointImpl{getX(maxc), getY(minc)};
// // Candidate item bounding box
// auto ibb = item.boundingBox();
auto a = pl::distance(ibb.maxCorner(), cc);
auto b = pl::distance(ibb.minCorner(), cc);
auto c = pl::distance(ibb.center(), cc);
auto d = pl::distance(top_left, cc);
auto e = pl::distance(bottom_right, cc);
// // Calculate the full bounding box of the pile with the candidate item
// pile.emplace_back(item.transformedShape());
// auto fullbb = ShapeLike::boundingBox(pile);
// pile.pop_back();
auto area = bb.width() * bb.height() / norm_2;
// // The bounding box of the big items (they will accumulate in the center
// // of the pile
// auto bigbb = bigs.empty()? fullbb : ShapeLike::boundingBox(bigs);
auto min_dist = std::min({a, b, c, d, e}) / norm;
// // The size indicator of the candidate item. This is not the area,
// // but almost...
// auto itemnormarea = std::sqrt(ibb.width()*ibb.height())/norm;
// The score will be the normalized distance which will be minimized,
// effectively creating a circle shaped pile of items
double score = 0.8*min_dist + 0.2*area;
// // Will hold the resulting score
// double score = 0;
// If it does not fit into the print bed we will beat it
// with a large penality. If we would not do this, there would be only
// one big pile that doesn't care whether it fits onto the print bed.
if(!NfpPlacer::wouldFit(bb, bin)) score = 2*penality - score;
// if(itemnormarea > BIG_ITEM_TRESHOLD) {
// // This branch is for the bigger items..
// // Here we will use the closest point of the item bounding box to
// // the already arranged pile. So not the bb center nor the a choosen
// // corner but whichever is the closest to the center. This will
// // prevent unwanted strange arrangements.
return score;
};
// 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)};
// auto cc = fullbb.center(); // The gravity center
// // Now the distnce of the gravity center will be calculated to the
// // five anchor points and the smallest will be chosen.
// std::array<double, 5> dists;
// 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);
// auto dist = *(std::min_element(dists.begin(), dists.end())) / norm;
// // Density is the pack density: how big is the arranged pile
// auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm;
// // The score is a weighted sum of the distance from pile center
// // and the pile size
// score = GRAVITY_RATIO * dist + DENSITY_RATIO * density;
// } else if(itemnormarea < BIG_ITEM_TRESHOLD && bigs.empty()) {
// // If there are no big items, only small, we should consider the
// // density here as well to not get silly results
// auto bindist = pl::distance(ibb.center(), bincenter) / norm;
// auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm;
// score = GRAVITY_RATIO * bindist + DENSITY_RATIO * density;
// } 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;
// }
// // If it does not fit into the print bed we will beat it
// // with a large penality. If we would not do this, there would be only
// // one big pile that doesn't care whether it fits onto the print bed.
// if(!NfpPlacer::wouldFit(fullbb, bin)) score = 2*penality - score;
// return score;
// };
Packer::SelectionConfig sconf;
// sconf.allow_parallel = false;
@ -638,7 +707,7 @@ void arrangeRectangles() {
std::vector<double> eff;
eff.reserve(result.size());
auto bin_area = double(bin.height()*bin.width());
auto bin_area = ShapeLike::area<PolygonImpl>(bin);
for(auto& r : result) {
double a = 0;
std::for_each(r.begin(), r.end(), [&a] (Item& e ){ a += e.area(); });
@ -673,7 +742,7 @@ void arrangeRectangles() {
SVGWriter::Config conf;
conf.mm_in_coord_units = SCALE;
SVGWriter svgw(conf);
svgw.setSize(bin);
svgw.setSize(Box(250*SCALE, 210*SCALE));
svgw.writePackGroup(result);
// std::for_each(input.begin(), input.end(), [&svgw](Item& item){ svgw.writeItem(item);});
svgw.save("out");

2
xs/src/libnest2d/libnest2d.h
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@ -6,7 +6,7 @@
#include <libnest2d/clipper_backend/clipper_backend.hpp>
// We include the stock optimizers for local and global optimization
#include <libnest2d/optimizers/simplex.hpp> // Local simplex for NfpPlacer
#include <libnest2d/optimizers/subplex.hpp> // Local subplex for NfpPlacer
#include <libnest2d/optimizers/genetic.hpp> // Genetic for min. bounding box
#include <libnest2d/libnest2d.hpp>

2
xs/src/libnest2d/libnest2d/boost_alg.hpp
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@ -358,7 +358,7 @@ inline double ShapeLike::area(const PolygonImpl& shape)
#endif
template<>
inline bool ShapeLike::isInside(const PointImpl& point,
inline bool ShapeLike::isInside<PolygonImpl>(const PointImpl& point,
const PolygonImpl& shape)
{
return boost::geometry::within(point, shape);

104
xs/src/libnest2d/libnest2d/geometry_traits.hpp
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@ -3,6 +3,7 @@
#include <string>
#include <type_traits>
#include <algorithm>
#include <array>
#include <vector>
#include <numeric>
@ -85,6 +86,31 @@ public:
inline TCoord<RawPoint> height() const BP2D_NOEXCEPT;
inline RawPoint center() const BP2D_NOEXCEPT;
inline double area() const BP2D_NOEXCEPT {
return double(width()*height());
}
};
template<class RawPoint>
class _Circle {
RawPoint center_;
double radius_ = 0;
public:
_Circle() = default;
_Circle(const RawPoint& center, double r): center_(center), radius_(r) {}
inline const RawPoint& center() const BP2D_NOEXCEPT { return center_; }
inline const void center(const RawPoint& c) { center_ = c; }
inline double radius() const BP2D_NOEXCEPT { return radius_; }
inline void radius(double r) { radius_ = r; }
inline double area() const BP2D_NOEXCEPT {
return 2.0*Pi*radius_;
}
};
/**
@ -614,12 +640,34 @@ struct ShapeLike {
return box;
}
template<class RawShape>
static inline _Box<TPoint<RawShape>> boundingBox(
const _Circle<TPoint<RawShape>>& circ)
{
using Coord = TCoord<TPoint<RawShape>>;
TPoint<RawShape> pmin = {
static_cast<Coord>(getX(circ.center()) - circ.radius()),
static_cast<Coord>(getY(circ.center()) - circ.radius()) };
TPoint<RawShape> pmax = {
static_cast<Coord>(getX(circ.center()) + circ.radius()),
static_cast<Coord>(getY(circ.center()) + circ.radius()) };
return {pmin, pmax};
}
template<class RawShape>
static inline double area(const _Box<TPoint<RawShape>>& box)
{
return static_cast<double>(box.width() * box.height());
}
template<class RawShape>
static inline double area(const _Circle<TPoint<RawShape>>& circ)
{
return circ.area();
}
template<class RawShape>
static inline double area(const Shapes<RawShape>& shapes)
{
@ -629,6 +677,62 @@ struct ShapeLike {
});
}
template<class RawShape>
static bool isInside(const TPoint<RawShape>& point,
const _Circle<TPoint<RawShape>>& circ)
{
return PointLike::distance(point, circ.center()) < circ.radius();
}
template<class RawShape>
static bool isInside(const TPoint<RawShape>& point,
const _Box<TPoint<RawShape>>& box)
{
auto px = getX(point);
auto py = getY(point);
auto minx = getX(box.minCorner());
auto miny = getY(box.minCorner());
auto maxx = getX(box.maxCorner());
auto maxy = getY(box.maxCorner());
return px > minx && px < maxx && py > miny && py < maxy;
}
template<class RawShape>
static bool isInside(const RawShape& sh,
const _Circle<TPoint<RawShape>>& circ)
{
return std::all_of(cbegin(sh), cend(sh),
[&circ](const TPoint<RawShape>& p){
return isInside<RawShape>(p, circ);
});
}
template<class RawShape>
static bool isInside(const _Box<TPoint<RawShape>>& box,
const _Circle<TPoint<RawShape>>& circ)
{
return isInside<RawShape>(box.minCorner(), circ) &&
isInside<RawShape>(box.maxCorner(), circ);
}
template<class RawShape>
static bool isInside(const _Box<TPoint<RawShape>>& ibb,
const _Box<TPoint<RawShape>>& box)
{
auto iminX = getX(ibb.minCorner());
auto imaxX = getX(ibb.maxCorner());
auto iminY = getY(ibb.minCorner());
auto imaxY = getY(ibb.maxCorner());
auto minX = getX(box.minCorner());
auto maxX = getX(box.maxCorner());
auto minY = getY(box.minCorner());
auto maxY = getY(box.maxCorner());
return iminX > minX && imaxX < maxX && iminY > minY && imaxY < maxY;
}
template<class RawShape> // Potential O(1) implementation may exist
static inline TPoint<RawShape>& vertex(RawShape& sh, unsigned long idx)
{

24
xs/src/libnest2d/libnest2d/libnest2d.hpp
View File

@ -53,8 +53,8 @@ class _Item {
enum class Convexity: char {
UNCHECKED,
TRUE,
FALSE
C_TRUE,
C_FALSE
};
mutable Convexity convexity_ = Convexity::UNCHECKED;
@ -213,10 +213,10 @@ public:
switch(convexity_) {
case Convexity::UNCHECKED:
ret = sl::isConvex<RawShape>(sl::getContour(transformedShape()));
convexity_ = ret? Convexity::TRUE : Convexity::FALSE;
convexity_ = ret? Convexity::C_TRUE : Convexity::C_FALSE;
break;
case Convexity::TRUE: ret = true; break;
case Convexity::FALSE:;
case Convexity::C_TRUE: ret = true; break;
case Convexity::C_FALSE:;
}
return ret;
@ -254,7 +254,13 @@ public:
return sl::isInside(transformedShape(), sh.transformedShape());
}
inline bool isInside(const RawShape& sh) const
{
return sl::isInside(transformedShape(), sh);
}
inline bool isInside(const _Box<TPoint<RawShape>>& box) const;
inline bool isInside(const _Circle<TPoint<RawShape>>& box) const;
inline void translate(const Vertex& d) BP2D_NOEXCEPT
{
@ -467,8 +473,12 @@ public:
template<class RawShape>
inline bool _Item<RawShape>::isInside(const _Box<TPoint<RawShape>>& box) const {
_Rectangle<RawShape> rect(box.width(), box.height());
return _Item<RawShape>::isInside(rect);
return ShapeLike::isInside<RawShape>(boundingBox(), box);
}
template<class RawShape> inline bool
_Item<RawShape>::isInside(const _Circle<TPoint<RawShape>>& circ) const {
return ShapeLike::isInside<RawShape>(transformedShape(), circ);
}
/**

196
xs/src/libnest2d/libnest2d/placers/nfpplacer.hpp
View File

@ -46,14 +46,12 @@ struct NfpPConfig {
* function you can e.g. influence the shape of the arranged pile.
*
* \param shapes The first parameter is a container with all the placed
* polygons including the current candidate. You can calculate a bounding
* box or convex hull on this pile of polygons.
* polygons excluding the current candidate. You can calculate a bounding
* box or convex hull on this pile of polygons without the candidate item
* or push back the candidate item into the container and then calculate
* some features.
*
* \param item The second parameter is the candidate item. Note that
* calling transformedShape() on this second argument returns an identical
* shape as calling shapes.back(). These would not be the same objects only
* identical shapes! Using the second parameter is a lot faster due to
* caching some properties of the polygon (area, etc...)
* \param item The second parameter is the candidate item.
*
* \param occupied_area The third parameter is the sum of areas of the
* items in the first parameter so you don't have to iterate through them
@ -127,6 +125,8 @@ template<class RawShape> class EdgeCache {
std::vector<ContourCache> holes_;
double accuracy_ = 1.0;
void createCache(const RawShape& sh) {
{ // For the contour
auto first = ShapeLike::cbegin(sh);
@ -160,11 +160,26 @@ template<class RawShape> class EdgeCache {
}
}
size_t stride(const size_t N) const {
using std::ceil;
using std::round;
using std::pow;
return static_cast<Coord>(
std::round(N/std::pow(N, std::pow(accuracy_, 1.0/3.0)))
);
}
void fetchCorners() const {
if(!contour_.corners.empty()) return;
contour_.corners.reserve(contour_.distances.size() / 3 + 1);
for(size_t i = 0; i < contour_.distances.size() - 1; i += 3) {
const auto N = contour_.distances.size();
const auto S = stride(N);
contour_.corners.reserve(N / S + 1);
auto N_1 = N-1;
contour_.corners.emplace_back(0.0);
for(size_t i = 0; i < N_1; i += S) {
contour_.corners.emplace_back(
contour_.distances.at(i) / contour_.full_distance);
}
@ -174,8 +189,12 @@ template<class RawShape> class EdgeCache {
auto& hc = holes_[hidx];
if(!hc.corners.empty()) return;
hc.corners.reserve(hc.distances.size() / 3 + 1);
for(size_t i = 0; i < hc.distances.size() - 1; i += 3) {
const auto N = hc.distances.size();
const auto S = stride(N);
auto N_1 = N-1;
hc.corners.reserve(N / S + 1);
hc.corners.emplace_back(0.0);
for(size_t i = 0; i < N_1; i += S) {
hc.corners.emplace_back(
hc.distances.at(i) / hc.full_distance);
}
@ -224,6 +243,9 @@ public:
createCache(sh);
}
/// Resolution of returned corners. The stride is derived from this value.
void accuracy(double a /* within <0.0, 1.0>*/) { accuracy_ = a; }
/**
* @brief Get a point on the circumference of a polygon.
* @param distance A relative distance from the starting point to the end.
@ -419,12 +441,12 @@ Nfp::Shapes<RawShape> nfp( const Container& polygons,
// return nfps;
}
template<class RawShape>
class _NofitPolyPlacer: public PlacerBoilerplate<_NofitPolyPlacer<RawShape>,
RawShape, _Box<TPoint<RawShape>>, NfpPConfig<RawShape>> {
template<class RawShape, class TBin = _Box<TPoint<RawShape>>>
class _NofitPolyPlacer: public PlacerBoilerplate<_NofitPolyPlacer<RawShape, TBin>,
RawShape, TBin, NfpPConfig<RawShape>> {
using Base = PlacerBoilerplate<_NofitPolyPlacer<RawShape>,
RawShape, _Box<TPoint<RawShape>>, NfpPConfig<RawShape>>;
using Base = PlacerBoilerplate<_NofitPolyPlacer<RawShape, TBin>,
RawShape, TBin, NfpPConfig<RawShape>>;
DECLARE_PLACER(Base)
@ -434,6 +456,7 @@ class _NofitPolyPlacer: public PlacerBoilerplate<_NofitPolyPlacer<RawShape>,
const double penality_;
using MaxNfpLevel = Nfp::MaxNfpLevel<RawShape>;
using sl = ShapeLike;
public:
@ -441,7 +464,7 @@ public:
inline explicit _NofitPolyPlacer(const BinType& bin):
Base(bin),
norm_(std::sqrt(ShapeLike::area<RawShape>(bin))),
norm_(std::sqrt(sl::area<RawShape>(bin))),
penality_(1e6*norm_) {}
_NofitPolyPlacer(const _NofitPolyPlacer&) = default;
@ -452,18 +475,26 @@ public:
_NofitPolyPlacer& operator=(_NofitPolyPlacer&&) BP2D_NOEXCEPT = default;
#endif
bool static inline wouldFit(const Box& bb, const RawShape& bin) {
auto bbin = sl::boundingBox<RawShape>(bin);
auto d = bbin.center() - bb.center();
_Rectangle<RawShape> rect(bb.width(), bb.height());
rect.translate(bb.minCorner() + d);
return sl::isInside<RawShape>(rect.transformedShape(), bin);
}
bool static inline wouldFit(const RawShape& chull, const RawShape& bin) {
auto bbch = ShapeLike::boundingBox<RawShape>(chull);
auto bbin = ShapeLike::boundingBox<RawShape>(bin);
auto d = bbin.minCorner() - bbch.minCorner();
auto bbch = sl::boundingBox<RawShape>(chull);
auto bbin = sl::boundingBox<RawShape>(bin);
auto d = bbch.center() - bbin.center();
auto chullcpy = chull;
ShapeLike::translate(chullcpy, d);
return ShapeLike::isInside<RawShape>(chullcpy, bbin);
sl::translate(chullcpy, d);
return sl::isInside<RawShape>(chullcpy, bin);
}
bool static inline wouldFit(const RawShape& chull, const Box& bin)
{
auto bbch = ShapeLike::boundingBox<RawShape>(chull);
auto bbch = sl::boundingBox<RawShape>(chull);
return wouldFit(bbch, bin);
}
@ -472,6 +503,17 @@ public:
return bb.width() <= bin.width() && bb.height() <= bin.height();
}
bool static inline wouldFit(const Box& bb, const _Circle<Vertex>& bin)
{
return sl::isInside<RawShape>(bb, bin);
}
bool static inline wouldFit(const RawShape& chull,
const _Circle<Vertex>& bin)
{
return sl::isInside<RawShape>(chull, bin);
}
PackResult trypack(Item& item) {
PackResult ret;
@ -510,7 +552,10 @@ public:
std::vector<EdgeCache<RawShape>> ecache;
ecache.reserve(nfps.size());
for(auto& nfp : nfps ) ecache.emplace_back(nfp);
for(auto& nfp : nfps ) {
ecache.emplace_back(nfp);
ecache.back().accuracy(config_.accuracy);
}
struct Optimum {
double relpos;
@ -536,18 +581,25 @@ public:
pile_area += mitem.area();
}
auto merged_pile = Nfp::merge(pile);
// This is the kernel part of the object function that is
// customizable by the library client
auto _objfunc = config_.object_function?
config_.object_function :
[this](Nfp::Shapes<RawShape>& pile, Item,
double occupied_area, double /*norm*/,
double penality)
[this, &merged_pile](
Nfp::Shapes<RawShape>& /*pile*/,
const Item& item,
double occupied_area,
double norm,
double /*penality*/)
{
auto ch = ShapeLike::convexHull(pile);
merged_pile.emplace_back(item.transformedShape());
auto ch = sl::convexHull(merged_pile);
merged_pile.pop_back();
// The pack ratio -- how much is the convex hull occupied
double pack_rate = occupied_area/ShapeLike::area(ch);
double pack_rate = occupied_area/sl::area(ch);
// ratio of waste
double waste = 1.0 - pack_rate;
@ -557,7 +609,7 @@ public:
// (larger) values.
auto score = std::sqrt(waste);
if(!wouldFit(ch, bin_)) score = 2*penality - score;
if(!wouldFit(ch, bin_)) score += norm;
return score;
};
@ -569,23 +621,31 @@ public:
d += startpos;
item.translation(d);
// pile.emplace_back(item.transformedShape());
double occupied_area = pile_area + item.area();
double score = _objfunc(pile, item, occupied_area,
norm_, penality_);
// pile.pop_back();
return score;
};
auto boundaryCheck = [&](const Optimum& o) {
auto v = getNfpPoint(o);
auto d = v - iv;
d += startpos;
item.translation(d);
merged_pile.emplace_back(item.transformedShape());
auto chull = sl::convexHull(merged_pile);
merged_pile.pop_back();
return wouldFit(chull, bin_);
};
opt::StopCriteria stopcr;
stopcr.max_iterations = 1000;
stopcr.absolute_score_difference = 1e-20*norm_;
// stopcr.relative_score_difference = 1e-20;
opt::TOptimizer<opt::Method::L_SIMPLEX> solver(stopcr);
stopcr.max_iterations = 100;
stopcr.relative_score_difference = 1e-6;
opt::TOptimizer<opt::Method::L_SUBPLEX> solver(stopcr);
Optimum optimum(0, 0);
double best_score = penality_;
@ -604,7 +664,7 @@ public:
std::for_each(cache.corners().begin(),
cache.corners().end(),
[ch, &contour_ofn, &solver, &best_score,
&optimum] (double pos)
&optimum, &boundaryCheck] (double pos)
{
try {
auto result = solver.optimize_min(contour_ofn,
@ -613,22 +673,15 @@ public:
);
if(result.score < best_score) {
best_score = result.score;
optimum.relpos = std::get<0>(result.optimum);
optimum.nfpidx = ch;
optimum.hidx = -1;
Optimum o(std::get<0>(result.optimum), ch, -1);
if(boundaryCheck(o)) {
best_score = result.score;
optimum = o;
}
}
} catch(std::exception& e) {
derr() << "ERROR: " << e.what() << "\n";
}
// auto sc = contour_ofn(pos);
// if(sc < best_score) {
// best_score = sc;
// optimum.relpos = pos;
// optimum.nfpidx = ch;
// optimum.hidx = -1;
// }
});
for(unsigned hidx = 0; hidx < cache.holeCount(); ++hidx) {
@ -643,7 +696,7 @@ public:
std::for_each(cache.corners(hidx).begin(),
cache.corners(hidx).end(),
[&hole_ofn, &solver, &best_score,
&optimum, ch, hidx]
&optimum, ch, hidx, &boundaryCheck]
(double pos)
{
try {
@ -653,21 +706,16 @@ public:
);
if(result.score < best_score) {
best_score = result.score;
Optimum o(std::get<0>(result.optimum),
ch, hidx);
optimum = o;
if(boundaryCheck(o)) {
best_score = result.score;
optimum = o;
}
}
} catch(std::exception& e) {
derr() << "ERROR: " << e.what() << "\n";
}
// auto sc = hole_ofn(pos);
// if(sc < best_score) {
// best_score = sc;
// optimum.relpos = pos;
// optimum.nfpidx = ch;
// optimum.hidx = hidx;
// }
});
}
}
@ -702,34 +750,35 @@ public:
m.reserve(items_.size());
for(Item& item : items_) m.emplace_back(item.transformedShape());
auto&& bb = ShapeLike::boundingBox<RawShape>(m);
auto&& bb = sl::boundingBox<RawShape>(m);
Vertex ci, cb;
auto bbin = sl::boundingBox<RawShape>(bin_);
switch(config_.alignment) {
case Config::Alignment::CENTER: {
ci = bb.center();
cb = bin_.center();
cb = bbin.center();
break;
}
case Config::Alignment::BOTTOM_LEFT: {
ci = bb.minCorner();
cb = bin_.minCorner();
cb = bbin.minCorner();
break;
}
case Config::Alignment::BOTTOM_RIGHT: {
ci = {getX(bb.maxCorner()), getY(bb.minCorner())};
cb = {getX(bin_.maxCorner()), getY(bin_.minCorner())};
cb = {getX(bbin.maxCorner()), getY(bbin.minCorner())};
break;
}
case Config::Alignment::TOP_LEFT: {
ci = {getX(bb.minCorner()), getY(bb.maxCorner())};
cb = {getX(bin_.minCorner()), getY(bin_.maxCorner())};
cb = {getX(bbin.minCorner()), getY(bbin.maxCorner())};
break;
}
case Config::Alignment::TOP_RIGHT: {
ci = bb.maxCorner();
cb = bin_.maxCorner();
cb = bbin.maxCorner();
break;
}
}
@ -745,31 +794,32 @@ private:
void setInitialPosition(Item& item) {
Box&& bb = item.boundingBox();
Vertex ci, cb;
auto bbin = sl::boundingBox<RawShape>(bin_);
switch(config_.starting_point) {
case Config::Alignment::CENTER: {
ci = bb.center();
cb = bin_.center();
cb = bbin.center();
break;
}
case Config::Alignment::BOTTOM_LEFT: {
ci = bb.minCorner();
cb = bin_.minCorner();
cb = bbin.minCorner();
break;
}
case Config::Alignment::BOTTOM_RIGHT: {
ci = {getX(bb.maxCorner()), getY(bb.minCorner())};
cb = {getX(bin_.maxCorner()), getY(bin_.minCorner())};
cb = {getX(bbin.maxCorner()), getY(bbin.minCorner())};
break;
}
case Config::Alignment::TOP_LEFT: {
ci = {getX(bb.minCorner()), getY(bb.maxCorner())};
cb = {getX(bin_.minCorner()), getY(bin_.maxCorner())};
cb = {getX(bbin.minCorner()), getY(bbin.maxCorner())};
break;
}
case Config::Alignment::TOP_RIGHT: {
ci = bb.maxCorner();
cb = bin_.maxCorner();
cb = bbin.maxCorner();
break;
}
}
@ -780,7 +830,7 @@ private:
void placeOutsideOfBin(Item& item) {
auto&& bb = item.boundingBox();
Box binbb = ShapeLike::boundingBox<RawShape>(bin_);
Box binbb = sl::boundingBox<RawShape>(bin_);
Vertex v = { getX(bb.maxCorner()), getY(bb.minCorner()) };

2
xs/src/libnest2d/libnest2d/selections/djd_heuristic.hpp
View File

@ -535,7 +535,7 @@ public:
// then it should be removed from the not_packed list
{ auto it = store_.begin();
while (it != store_.end()) {
Placer p(bin);
Placer p(bin); p.configure(pconfig);
if(!p.pack(*it)) {
it = store_.erase(it);
} else it++;

2
xs/src/libnest2d/libnest2d/selections/firstfit.hpp
View File

@ -59,7 +59,7 @@ public:
// then it should be removed from the list
{ auto it = store_.begin();
while (it != store_.end()) {
Placer p(bin);
Placer p(bin); p.configure(pconfig);
if(!p.pack(*it)) {
it = store_.erase(it);
} else it++;

452
xs/src/libslic3r/Model.cpp
View File

@ -7,11 +7,6 @@
#include "Format/STL.hpp"
#include "Format/3mf.hpp"
#include <numeric>
#include <libnest2d.h>
#include <ClipperUtils.hpp>
#include "slic3r/GUI/GUI.hpp"
#include <float.h>
#include <boost/algorithm/string/predicate.hpp>
@ -304,435 +299,36 @@ static bool _arrange(const Pointfs &sizes, coordf_t dist, const BoundingBoxf* bb
return result;
}
namespace arr {
using namespace libnest2d;
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;
tmpmesh.scale(objinst->scaling_factor);
objinst->transform_mesh(&tmpmesh);
ExPolygons expolys = tmpmesh.horizontal_projection();
for(auto& expoly_complex : expolys) {
auto tmp = expoly_complex.simplify(1.0/SCALING_FACTOR);
if(tmp.empty()) continue;
auto 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.x << ", "
<< v.y << "},\n";
{
auto v = expoly.contour.points.front();
ss << "\t\t\t{" << v.x << ", " << v.y << "},\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.x << ", "
<< v.y << "},\n";
{
auto v = h.points.front();
ss << "\t\t\t\t{" << v.x << ", " << v.y << "},\n";
}
ss << "\t\t\t},\n";
}
ss << "\t\t},\n";
ss << "\t},\n";
}
}
}
ss << "}\n";
return ss.str();
}
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->scaling_factor);
objinst->transform_mesh(&tmpmesh);
ExPolygons expolys = tmpmesh.horizontal_projection();
svg.draw(expolys);
}
}
}
// A container which stores a pointer to the 3D object and its projected
// 2D shape from top view.
using ShapeData2D =
std::vector<std::pair<Slic3r::ModelInstance*, Item>>;
ShapeData2D projectModelFromTop(const Slic3r::Model &model) {
ShapeData2D ret;
auto s = std::accumulate(model.objects.begin(), model.objects.end(), 0,
[](size_t s, ModelObject* o){
return s + o->instances.size();
});
ret.reserve(s);
for(auto objptr : model.objects) {
if(objptr) {
auto rmesh = objptr->raw_mesh();
for(auto objinst : objptr->instances) {
if(objinst) {
Slic3r::TriangleMesh tmpmesh = rmesh;
ClipperLib::PolygonImpl pn;
tmpmesh.scale(objinst->scaling_factor);
// TODO export the exact 2D projection
auto p = tmpmesh.convex_hull();
p.make_clockwise();
p.append(p.first_point());
pn.Contour = Slic3rMultiPoint_to_ClipperPath( p );
// Efficient conversion to item.
Item item(std::move(pn));
// Invalid geometries would throw exceptions when arranging
if(item.vertexCount() > 3) {
item.rotation(objinst->rotation);
item.translation( {
ClipperLib::cInt(objinst->offset.x/SCALING_FACTOR),
ClipperLib::cInt(objinst->offset.y/SCALING_FACTOR)
});
ret.emplace_back(objinst, item);
}
}
}
}
}
return ret;
}
/**
* \brief Arranges the model objects on the screen.
*
* The arrangement considers multiple bins (aka. print beds) for placing all
* the items provided in the model argument. If the items don't fit on one
* print bed, the remaining will be placed onto newly created print beds.
* The first_bin_only parameter, if set to true, disables this behaviour and
* makes sure that only one print bed is filled and the remaining items will be
* untouched. When set to false, the items which could not fit onto the
* print bed will be placed next to the print bed so the user should see a
* pile of items on the print bed and some other piles outside the print
* area that can be dragged later onto the print bed as a group.
*
* \param model The model object with the 3D content.
* \param dist The minimum distance which is allowed for any pair of items
* on the print bed in any direction.
* \param bb The bounding box of the print bed. It corresponds to the 'bin'
* for bin packing.
* \param first_bin_only This parameter controls whether to place the
* remaining items which do not fit onto the print area next to the print
* bed or leave them untouched (let the user arrange them by hand or remove
* them).
*/
bool arrange(Model &model, coordf_t dist, const Slic3r::BoundingBoxf* bb,
bool first_bin_only,
std::function<void(unsigned)> progressind)
{
using ArrangeResult = _IndexedPackGroup<PolygonImpl>;
bool ret = true;
// Create the arranger config
auto min_obj_distance = static_cast<Coord>(dist/SCALING_FACTOR);
// Get the 2D projected shapes with their 3D model instance pointers
auto shapemap = arr::projectModelFromTop(model);
bool hasbin = bb != nullptr && bb->defined;
double area_max = 0;
// Copy the references for the shapes only as the arranger expects a
// sequence of objects convertible to Item or ClipperPolygon
std::vector<std::reference_wrapper<Item>> shapes;
shapes.reserve(shapemap.size());
std::for_each(shapemap.begin(), shapemap.end(),
[&shapes, min_obj_distance, &area_max, hasbin]
(ShapeData2D::value_type& it)
{
shapes.push_back(std::ref(it.second));
});
Box bin;
if(hasbin) {
// Scale up the bounding box to clipper scale.
BoundingBoxf bbb = *bb;
bbb.scale(1.0/SCALING_FACTOR);
bin = Box({
static_cast<libnest2d::Coord>(bbb.min.x),
static_cast<libnest2d::Coord>(bbb.min.y)
},
{
static_cast<libnest2d::Coord>(bbb.max.x),
static_cast<libnest2d::Coord>(bbb.max.y)
});
}
// Will use the DJD selection heuristic with the BottomLeft placement
// strategy
using Arranger = Arranger<NfpPlacer, FirstFitSelection>;
using PConf = Arranger::PlacementConfig;
using SConf = Arranger::SelectionConfig;
PConf pcfg; // Placement configuration
SConf scfg; // Selection configuration
// 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 };
// Magic: we will specify what is the goal of arrangement... In this case
// we override the default object function to make the larger items go into
// the center of the pile and smaller items orbit it so the resulting pile
// has a circle-like shape. This is good for the print bed's heat profile.
// We alse sacrafice a bit of pack efficiency for this to work. As a side
// effect, the arrange procedure is a lot faster (we do not need to
// calculate the convex hulls)
pcfg.object_function = [bin, hasbin](
NfpPlacer::Pile& pile, // The currently arranged pile
Item item,
double /*area*/, // Sum area of items (not needed)
double norm, // A norming factor for physical dimensions
double penality) // Min penality in case of bad arrangement
{
using pl = PointLike;
static const double BIG_ITEM_TRESHOLD = 0.2;
static const double GRAVITY_RATIO = 0.5;
static const double DENSITY_RATIO = 1.0 - GRAVITY_RATIO;
// We will treat big items (compared to the print bed) differently
NfpPlacer::Pile bigs;
bigs.reserve(pile.size());
for(auto& p : pile) {
auto pbb = ShapeLike::boundingBox(p);
auto na = std::sqrt(pbb.width()*pbb.height())/norm;
if(na > BIG_ITEM_TRESHOLD) bigs.emplace_back(p);
}
// Candidate item bounding box
auto ibb = item.boundingBox();
// Calculate the full bounding box of the pile with the candidate item
pile.emplace_back(item.transformedShape());
auto fullbb = ShapeLike::boundingBox(pile);
pile.pop_back();
// The bounding box of the big items (they will accumulate in the center
// of the pile
auto bigbb = bigs.empty()? fullbb : ShapeLike::boundingBox(bigs);
// The size indicator of the candidate item. This is not the area,
// but almost...
auto itemnormarea = std::sqrt(ibb.width()*ibb.height())/norm;
// Will hold the resulting score
double score = 0;
if(itemnormarea > BIG_ITEM_TRESHOLD) {
// This branch is for the bigger items..
// Here we will use the closest point of the item bounding box to
// the already arranged pile. So not the bb center nor the a choosen
// corner but whichever is the closest to the center. This will
// prevent unwanted strange arrangements.
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)};
auto cc = fullbb.center(); // The gravity center
// Now the distnce of the gravity center will be calculated to the
// five anchor points and the smallest will be chosen.
std::array<double, 5> dists;
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);
auto dist = *(std::min_element(dists.begin(), dists.end())) / norm;
// Density is the pack density: how big is the arranged pile
auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm;
// The score is a weighted sum of the distance from pile center
// and the pile size
score = GRAVITY_RATIO * dist + DENSITY_RATIO * density;
} else if(itemnormarea < BIG_ITEM_TRESHOLD && bigs.empty()) {
// If there are no big items, only small, we should consider the
// density here as well to not get silly results
auto bindist = pl::distance(ibb.center(), bin.center()) / norm;
auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm;
score = GRAVITY_RATIO * bindist + DENSITY_RATIO * density;
} 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;
}
// If it does not fit into the print bed we will beat it
// with a large penality. If we would not do this, there would be only
// one big pile that doesn't care whether it fits onto the print bed.
if(!NfpPlacer::wouldFit(fullbb, bin)) score = 2*penality - score;
return score;
};
// Create the arranger object
Arranger arranger(bin, min_obj_distance, pcfg, scfg);
// Set the progress indicator for the arranger.
arranger.progressIndicator(progressind);
// Arrange and return the items with their respective indices within the
// input sequence.
auto result = arranger.arrangeIndexed(shapes.begin(), shapes.end());
auto applyResult = [&shapemap](ArrangeResult::value_type& group,
Coord batch_offset)
{
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 tranformation data from the item object and scale it
// appropriately
auto off = item.translation();
Radians rot = item.rotation();
Pointf foff(off.X*SCALING_FACTOR + batch_offset,
off.Y*SCALING_FACTOR);
// write the tranformation data into the model instance
inst_ptr->rotation = rot;
inst_ptr->offset = foff;
}
};
if(first_bin_only) {
applyResult(result.front(), 0);
} else {
const auto STRIDE_PADDING = 1.2;
Coord stride = static_cast<Coord>(STRIDE_PADDING*
bin.width()*SCALING_FACTOR);
Coord batch_offset = 0;
for(auto& group : result) {
applyResult(group, batch_offset);
// 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;
}
}
/* arrange objects preserving their instance count
but altering their instance positions */
bool Model::arrange_objects(coordf_t dist, const BoundingBoxf* bb,
std::function<void(unsigned)> progressind)
bool Model::arrange_objects(coordf_t dist, const BoundingBoxf* bb)
{
bool ret = false;
if(bb != nullptr && bb->defined) {
// Despite the new arrange is able to run without a specified bin,
// the perl testsuit still fails for this case. For now the safest
// thing to do is to use the new arrange only when a proper bin is
// specified.
ret = arr::arrange(*this, dist, bb, false, progressind);
} else {
// get the (transformed) size of each instance so that we take
// into account their different transformations when packing
Pointfs instance_sizes;
Pointfs instance_centers;
for (const ModelObject *o : this->objects)
for (size_t i = 0; i < o->instances.size(); ++ i) {
// an accurate snug bounding box around the transformed mesh.
BoundingBoxf3 bbox(o->instance_bounding_box(i, true));
instance_sizes.push_back(bbox.size());
instance_centers.push_back(bbox.center());
}
Pointfs positions;
if (! _arrange(instance_sizes, dist, bb, positions))
return false;
size_t idx = 0;
for (ModelObject *o : this->objects) {
for (ModelInstance *i : o->instances) {
i->offset = positions[idx] - instance_centers[idx];
++ idx;
}
o->invalidate_bounding_box();
// get the (transformed) size of each instance so that we take
// into account their different transformations when packing
Pointfs instance_sizes;
Pointfs instance_centers;
for (const ModelObject *o : this->objects)
for (size_t i = 0; i < o->instances.size(); ++ i) {
// an accurate snug bounding box around the transformed mesh.
BoundingBoxf3 bbox(o->instance_bounding_box(i, true));
instance_sizes.push_back(bbox.size());
instance_centers.push_back(bbox.center());
}
Pointfs positions;
if (! _arrange(instance_sizes, dist, bb, positions))
return false;
size_t idx = 0;
for (ModelObject *o : this->objects) {
for (ModelInstance *i : o->instances) {
i->offset = positions[idx] - instance_centers[idx];
++ idx;
}
o->invalidate_bounding_box();
}
return ret;
return true;
}
// Duplicate the entire model preserving instance relative positions.

3
xs/src/libslic3r/Model.hpp
View File

@ -290,8 +290,7 @@ public:
void center_instances_around_point(const Pointf &point);
void translate(coordf_t x, coordf_t y, coordf_t z) { for (ModelObject *o : this->objects) o->translate(x, y, z); }
TriangleMesh mesh() const;
bool arrange_objects(coordf_t dist, const BoundingBoxf* bb = NULL,
std::function<void(unsigned)> progressind = [](unsigned){});
bool arrange_objects(coordf_t dist, const BoundingBoxf* bb = NULL);
// Croaks if the duplicated objects do not fit the print bed.
void duplicate(size_t copies_num, coordf_t dist, const BoundingBoxf* bb = NULL);
void duplicate_objects(size_t copies_num, coordf_t dist, const BoundingBoxf* bb = NULL);

597
xs/src/libslic3r/ModelArrange.hpp Normal file
View File

@ -0,0 +1,597 @@
#ifndef MODELARRANGE_HPP
#define MODELARRANGE_HPP
#include "Model.hpp"
#include "SVG.hpp"
#include <libnest2d.h>
#include <numeric>
#include <ClipperUtils.hpp>
#include <boost/geometry/index/rtree.hpp>
namespace Slic3r {
namespace arr {
using namespace libnest2d;
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;
tmpmesh.scale(objinst->scaling_factor);
objinst->transform_mesh(&tmpmesh);
ExPolygons expolys = tmpmesh.horizontal_projection();
for(auto& expoly_complex : expolys) {
auto tmp = expoly_complex.simplify(1.0/SCALING_FACTOR);
if(tmp.empty()) continue;
auto 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.x << ", "
<< v.y << "},\n";
{
auto v = expoly.contour.points.front();
ss << "\t\t\t{" << v.x << ", " << v.y << "},\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.x << ", "
<< v.y << "},\n";
{
auto v = h.points.front();
ss << "\t\t\t\t{" << v.x << ", " << v.y << "},\n";
}
ss << "\t\t\t},\n";
}
ss << "\t\t},\n";
ss << "\t},\n";
}
}
}
ss << "}\n";
return ss.str();
}
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->scaling_factor);
objinst->transform_mesh(&tmpmesh);
ExPolygons expolys = tmpmesh.horizontal_projection();
svg.draw(expolys);
}
}
}
namespace bgi = boost::geometry::index;
using SpatElement = std::pair<Box, unsigned>;
using SpatIndex = bgi::rtree< SpatElement, bgi::rstar<16, 4> >;
std::tuple<double /*score*/, Box /*farthest point from bin center*/>
objfunc(const PointImpl& bincenter,
double /*bin_area*/,
ShapeLike::Shapes<PolygonImpl>& pile, // The currently arranged pile
double /*pile_area*/,
const Item &item,
double norm, // A norming factor for physical dimensions
std::vector<double>& areacache, // pile item areas will be cached
// a spatial index to quickly get neighbors of the candidate item
SpatIndex& spatindex
)
{
using pl = PointLike;
using sl = ShapeLike;
static const double BIG_ITEM_TRESHOLD = 0.2;
static const double ROUNDNESS_RATIO = 0.5;
static const double DENSITY_RATIO = 1.0 - ROUNDNESS_RATIO;
// We will treat big items (compared to the print bed) differently
auto normarea = [norm](double area) { return std::sqrt(area)/norm; };
// If a new bin has been created:
if(pile.size() < areacache.size()) {
areacache.clear();
spatindex.clear();
}
// We must fill the caches:
int idx = 0;
for(auto& p : pile) {
if(idx == areacache.size()) {
areacache.emplace_back(sl::area(p));
if(normarea(areacache[idx]) > BIG_ITEM_TRESHOLD)
spatindex.insert({sl::boundingBox(p), idx});
}
idx++;
}
// Candidate item bounding box
auto ibb = item.boundingBox();
// Calculate the full bounding box of the pile with the candidate item
pile.emplace_back(item.transformedShape());
auto fullbb = ShapeLike::boundingBox(pile);
pile.pop_back();
// 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);
}
// The size indicator of the candidate item. This is not the area,
// but almost...
double item_normarea = normarea(item.area());
// Will hold the resulting score
double score = 0;
if(item_normarea > BIG_ITEM_TRESHOLD) {
// This branch is for the bigger items..
// Here we will use the closest point of the item bounding box to
// the already arranged pile. So not the bb center nor the a choosen
// corner but whichever is the closest to the center. This will
// prevent some unwanted strange arrangements.
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<double, 5> 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;
// Density is the pack density: how big is the arranged pile
auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm;
// Prepare a variable for the alignment score.
// This will indicate: how well is the candidate item aligned with
// its neighbors. We will check the aligment 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 = std::numeric_limits<double>::max();
auto& trsh = item.transformedShape();
auto querybb = item.boundingBox();
// Query the spatial index for the neigbours
std::vector<SpatElement> result;
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;
auto& p = pile[idx];
auto parea = areacache[idx];
auto bb = sl::boundingBox(sl::Shapes<PolygonImpl>{p, trsh});
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 neigbours
auto C = 0.33;
score = C * dist + C * density + C * alignment_score;
} else if( item_normarea < BIG_ITEM_TRESHOLD && spatindex.empty()) {
// If there are no big items, only small, we should consider the
// density here as well to not get silly results
auto bindist = pl::distance(ibb.center(), bincenter) / norm;
auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm;
score = ROUNDNESS_RATIO * bindist + DENSITY_RATIO * density;
} 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);
}
template<class PConf>
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 = 0.6f;
}
template<class TBin>
class AutoArranger {};
template<class TBin>
class _ArrBase {
protected:
using Placer = strategies::_NofitPolyPlacer<PolygonImpl, TBin>;
using Selector = FirstFitSelection;
using Packer = Arranger<Placer, Selector>;
using PConfig = typename Packer::PlacementConfig;
using Distance = TCoord<PointImpl>;
using Pile = ShapeLike::Shapes<PolygonImpl>;
Packer pck_;
PConfig pconf_; // Placement configuration
double bin_area_;
std::vector<double> areacache_;
SpatIndex rtree_;
public:
_ArrBase(const TBin& bin, Distance dist,
std::function<void(unsigned)> progressind):
pck_(bin, dist), bin_area_(ShapeLike::area<PolygonImpl>(bin))
{
fillConfig(pconf_);
pck_.progressIndicator(progressind);
}
template<class...Args> inline IndexedPackGroup operator()(Args&&...args) {
areacache_.clear();
return pck_.arrangeIndexed(std::forward<Args>(args)...);
}
};
template<>
class AutoArranger<Box>: public _ArrBase<Box> {
public:
AutoArranger(const Box& bin, Distance dist,
std::function<void(unsigned)> progressind):
_ArrBase<Box>(bin, dist, progressind)
{
pconf_.object_function = [this, bin] (
Pile& pile,
const Item &item,
double pile_area,
double norm,
double /*penality*/) {
auto result = objfunc(bin.center(), bin_area_, pile,
pile_area, item, norm, areacache_, rtree_);
double score = std::get<0>(result);
auto& fullbb = std::get<1>(result);
auto wdiff = fullbb.width() - bin.width();
auto hdiff = fullbb.height() - bin.height();
if(wdiff > 0) score += std::pow(wdiff, 2) / norm;
if(hdiff > 0) score += std::pow(hdiff, 2) / norm;
return score;
};
pck_.configure(pconf_);
}
};
template<>
class AutoArranger<PolygonImpl>: public _ArrBase<PolygonImpl> {
public:
AutoArranger(const PolygonImpl& bin, Distance dist,
std::function<void(unsigned)> progressind):
_ArrBase<PolygonImpl>(bin, dist, progressind)
{
pconf_.object_function = [this, &bin] (
Pile& pile,
const Item &item,
double pile_area,
double norm,
double /*penality*/) {
auto binbb = ShapeLike::boundingBox(bin);
auto result = objfunc(binbb.center(), bin_area_, pile,
pile_area, item, norm, areacache_, rtree_);
double score = std::get<0>(result);
pile.emplace_back(item.transformedShape());
auto chull = ShapeLike::convexHull(pile);
pile.pop_back();
// If it does not fit into the print bed we will beat it with a
// large penality. If we would not do this, there would be only one
// big pile that doesn't care whether it fits onto the print bed.
if(!Placer::wouldFit(chull, bin)) score += norm;
return score;
};
pck_.configure(pconf_);
}
};
template<> // Specialization with no bin
class AutoArranger<bool>: public _ArrBase<Box> {
public:
AutoArranger(Distance dist, std::function<void(unsigned)> progressind):
_ArrBase<Box>(Box(0, 0), dist, progressind)
{
this->pconf_.object_function = [this] (
Pile& pile,
const Item &item,
double pile_area,
double norm,
double /*penality*/) {
auto result = objfunc({0, 0}, 0, pile, pile_area,
item, norm, areacache_, rtree_);
return std::get<0>(result);
};
this->pck_.configure(pconf_);
}
};
// A container which stores a pointer to the 3D object and its projected
// 2D shape from top view.
using ShapeData2D =
std::vector<std::pair<Slic3r::ModelInstance*, Item>>;
ShapeData2D projectModelFromTop(const Slic3r::Model &model) {
ShapeData2D ret;
auto s = std::accumulate(model.objects.begin(), model.objects.end(), 0,
[](size_t s, ModelObject* o){
return s + o->instances.size();
});
ret.reserve(s);
for(auto objptr : model.objects) {
if(objptr) {
auto rmesh = objptr->raw_mesh();
for(auto objinst : objptr->instances) {
if(objinst) {
Slic3r::TriangleMesh tmpmesh = rmesh;
ClipperLib::PolygonImpl pn;
tmpmesh.scale(objinst->scaling_factor);
// TODO export the exact 2D projection
auto p = tmpmesh.convex_hull();
p.make_clockwise();
p.append(p.first_point());
pn.Contour = Slic3rMultiPoint_to_ClipperPath( p );
// Efficient conversion to item.
Item item(std::move(pn));
// Invalid geometries would throw exceptions when arranging
if(item.vertexCount() > 3) {
item.rotation(objinst->rotation);
item.translation( {
ClipperLib::cInt(objinst->offset.x/SCALING_FACTOR),
ClipperLib::cInt(objinst->offset.y/SCALING_FACTOR)
});
ret.emplace_back(objinst, item);
}
}
}
}
}
return ret;
}
enum BedShapeHint {
BOX,
CIRCLE,
IRREGULAR,
WHO_KNOWS
};
BedShapeHint bedShape(const Slic3r::Polyline& /*bed*/) {
// Determine the bed shape by hand
return BOX;
}
void applyResult(
IndexedPackGroup::value_type& group,
Coord batch_offset,
ShapeData2D& shapemap)
{
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 tranformation data from the item object and scale it
// appropriately
auto off = item.translation();
Radians rot = item.rotation();
Pointf foff(off.X*SCALING_FACTOR + batch_offset,
off.Y*SCALING_FACTOR);
// write the tranformation data into the model instance
inst_ptr->rotation = rot;
inst_ptr->offset = foff;
}
}
/**
* \brief Arranges the model objects on the screen.
*
* The arrangement considers multiple bins (aka. print beds) for placing all
* the items provided in the model argument. If the items don't fit on one
* print bed, the remaining will be placed onto newly created print beds.
* The first_bin_only parameter, if set to true, disables this behaviour and
* makes sure that only one print bed is filled and the remaining items will be
* untouched. When set to false, the items which could not fit onto the
* print bed will be placed next to the print bed so the user should see a
* pile of items on the print bed and some other piles outside the print
* area that can be dragged later onto the print bed as a group.
*
* \param model The model object with the 3D content.
* \param dist The minimum distance which is allowed for any pair of items
* on the print bed in any direction.
* \param bb The bounding box of the print bed. It corresponds to the 'bin'
* for bin packing.
* \param first_bin_only This parameter controls whether to place the
* remaining items which do not fit onto the print area next to the print
* bed or leave them untouched (let the user arrange them by hand or remove
* them).
*/
bool arrange(Model &model, coordf_t min_obj_distance,
const Slic3r::Polyline& bed,
BedShapeHint bedhint,
bool first_bin_only,
std::function<void(unsigned)> progressind)
{
using ArrangeResult = _IndexedPackGroup<PolygonImpl>;
bool ret = true;
// Get the 2D projected shapes with their 3D model instance pointers
auto shapemap = arr::projectModelFromTop(model);
// Copy the references for the shapes only as the arranger expects a
// sequence of objects convertible to Item or ClipperPolygon
std::vector<std::reference_wrapper<Item>> 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;
BoundingBox bbb(bed.points);
auto binbb = Box({
static_cast<libnest2d::Coord>(bbb.min.x),
static_cast<libnest2d::Coord>(bbb.min.y)
},
{
static_cast<libnest2d::Coord>(bbb.max.x),
static_cast<libnest2d::Coord>(bbb.max.y)
});
switch(bedhint) {
case BOX: {
// Create the arranger for the box shaped bed
AutoArranger<Box> arrange(binbb, min_obj_distance, progressind);
// Arrange and return the items with their respective indices within the
// input sequence.
result = arrange(shapes.begin(), shapes.end());
break;
}
case CIRCLE:
break;
case IRREGULAR:
case WHO_KNOWS: {
using P = libnest2d::PolygonImpl;
auto ctour = Slic3rMultiPoint_to_ClipperPath(bed);
P irrbed = ShapeLike::create<PolygonImpl>(std::move(ctour));
// std::cout << ShapeLike::toString(irrbed) << std::endl;
AutoArranger<P> arrange(irrbed, min_obj_distance, progressind);
// Arrange and return the items with their respective indices within the
// input sequence.
result = arrange(shapes.begin(), shapes.end());
break;
}
};
if(first_bin_only) {
applyResult(result.front(), 0, shapemap);
} else {
const auto STRIDE_PADDING = 1.2;
Coord stride = static_cast<Coord>(STRIDE_PADDING*
binbb.width()*SCALING_FACTOR);
Coord batch_offset = 0;
for(auto& group : result) {
applyResult(group, batch_offset, shapemap);
// 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;
}
}
}
#endif // MODELARRANGE_HPP

21
xs/src/slic3r/AppController.cpp
View File

@ -8,6 +8,7 @@
#include <unordered_map>
#include <slic3r/GUI/GUI.hpp>
#include <ModelArrange.hpp>
#include <slic3r/GUI/PresetBundle.hpp>
#include <Geometry.hpp>
@ -293,6 +294,8 @@ void AppController::arrange_model()
supports_asynch()? std::launch::async : std::launch::deferred,
[this]()
{
using Coord = libnest2d::TCoord<libnest2d::PointImpl>;
unsigned count = 0;
for(auto obj : model_->objects) count += obj->instances.size();
@ -310,13 +313,25 @@ void AppController::arrange_model()
auto dist = print_ctl()->config().min_object_distance();
BoundingBoxf bb(print_ctl()->config().bed_shape.values);
// Create the arranger config
auto min_obj_distance = static_cast<Coord>(dist/SCALING_FACTOR);
auto& bedpoints = print_ctl()->config().bed_shape.values;
Polyline bed; bed.points.reserve(bedpoints.size());
for(auto& v : bedpoints)
bed.append(Point::new_scale(v.x, v.y));
if(pind) pind->update(0, _(L("Arranging objects...")));
try {
model_->arrange_objects(dist, &bb, [pind, count](unsigned rem){
if(pind) pind->update(count - rem, _(L("Arranging objects...")));
arr::arrange(*model_,
min_obj_distance,
bed,
arr::BOX,
false, // create many piles not just one pile
[pind, count](unsigned rem) {
if(pind)
pind->update(count - rem, _(L("Arranging objects...")));
});
} catch(std::exception& e) {
std::cerr << e.what() << std::endl;