PrusaSlicer-NonPlainar/src/libslic3r/Arrange.cpp
tamasmeszaros 2fd5a415c5 Fix arrange when some geometries are ill formed.
SPE-1216
The removed fix for issue 2209 is not needed anymore as the backend (arrange + libnest) takes care of such objects
- Offset is now done with libslic3r offset() wrapper (no expception thrown)
- Zero area objects are discarded in libnest
2022-04-19 11:45:17 +02:00

661 lines
22 KiB
C++

#include "Arrange.hpp"
#include "BoundingBox.hpp"
#include <libnest2d/backends/libslic3r/geometries.hpp>
#include <libnest2d/optimizers/nlopt/subplex.hpp>
#include <libnest2d/placers/nfpplacer.hpp>
#include <libnest2d/selections/firstfit.hpp>
#include <libnest2d/utils/rotcalipers.hpp>
#include <numeric>
#include <ClipperUtils.hpp>
#include <boost/geometry/index/rtree.hpp>
#if defined(_MSC_VER) && defined(__clang__)
#define BOOST_NO_CXX17_HDR_STRING_VIEW
#endif
#include <boost/multiprecision/integer.hpp>
#include <boost/rational.hpp>
namespace libnest2d {
#if !defined(_MSC_VER) && defined(__SIZEOF_INT128__) && !defined(__APPLE__)
using LargeInt = __int128;
#else
using LargeInt = boost::multiprecision::int128_t;
template<> struct _NumTag<LargeInt>
{
using Type = ScalarTag;
};
#endif
template<class T> struct _NumTag<boost::rational<T>>
{
using Type = RationalTag;
};
namespace nfp {
template<class S> struct NfpImpl<S, NfpLevel::CONVEX_ONLY>
{
NfpResult<S> operator()(const S &sh, const S &other)
{
return nfpConvexOnly<S, boost::rational<LargeInt>>(sh, other);
}
};
} // namespace nfp
} // namespace libnest2d
namespace Slic3r {
template<class Tout = double, class = FloatingOnly<Tout>, int...EigenArgs>
inline constexpr Eigen::Matrix<Tout, 2, EigenArgs...> unscaled(
const Slic3r::ClipperLib::IntPoint &v) noexcept
{
return Eigen::Matrix<Tout, 2, EigenArgs...>{unscaled<Tout>(v.x()),
unscaled<Tout>(v.y())};
}
namespace arrangement {
using namespace libnest2d;
// Get the libnest2d types for clipper backend
using Item = _Item<ExPolygon>;
using Box = _Box<Point>;
using Circle = _Circle<Point>;
using Segment = _Segment<Point>;
using MultiPolygon = ExPolygons;
// Summon the spatial indexing facilities from boost
namespace bgi = boost::geometry::index;
using SpatElement = std::pair<Box, unsigned>;
using SpatIndex = bgi::rtree< SpatElement, bgi::rstar<16, 4> >;
using ItemGroup = std::vector<std::reference_wrapper<Item>>;
// A coefficient used in separating bigger items and smaller items.
const double BIG_ITEM_TRESHOLD = 0.02;
// Fill in the placer algorithm configuration with values carefully chosen for
// Slic3r.
template<class PConf>
void fill_config(PConf& pcfg, const ArrangeParams &params) {
// 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.
if (params.allow_rotations)
pcfg.rotations = {0., PI / 2., PI, 3. * PI / 2. };
else
pcfg.rotations = {0.};
// The accuracy of optimization.
// Goes from 0.0 to 1.0 and scales performance as well
pcfg.accuracy = params.accuracy;
// Allow parallel execution.
pcfg.parallel = params.parallel;
}
// Apply penalty to object function result. This is used only when alignment
// after arrange is explicitly disabled (PConfig::Alignment::DONT_ALIGN)
// Also, this will only work well for Box shaped beds.
static double fixed_overfit(const std::tuple<double, Box>& result, const Box &binbb)
{
double score = std::get<0>(result);
Box pilebb = std::get<1>(result);
Box fullbb = sl::boundingBox(pilebb, binbb);
auto diff = double(fullbb.area()) - binbb.area();
if(diff > 0) score += diff;
return score;
}
// A class encapsulating the libnest2d Nester class and extending it with other
// management and spatial index structures for acceleration.
template<class TBin>
class AutoArranger {
public:
// Useful type shortcuts...
using Placer = typename placers::_NofitPolyPlacer<ExPolygon, TBin>;
using Selector = selections::_FirstFitSelection<ExPolygon>;
using Packer = _Nester<Placer, Selector>;
using PConfig = typename Packer::PlacementConfig;
using Distance = TCoord<PointImpl>;
protected:
Packer m_pck;
PConfig m_pconf; // Placement configuration
TBin m_bin;
double m_bin_area;
#ifdef _MSC_VER
#pragma warning(push)
#pragma warning(disable: 4244)
#pragma warning(disable: 4267)
#endif
SpatIndex m_rtree; // spatial index for the normal (bigger) objects
SpatIndex m_smallsrtree; // spatial index for only the smaller items
#ifdef _MSC_VER
#pragma warning(pop)
#endif
double m_norm; // A coefficient to scale distances
MultiPolygon m_merged_pile; // The already merged pile (vector of items)
Box m_pilebb; // The bounding box of the merged pile.
ItemGroup m_remaining; // Remaining items
ItemGroup m_items; // allready packed items
size_t m_item_count = 0; // Number of all items to be packed
template<class T> ArithmeticOnly<T, double> norm(T val)
{
return double(val) / m_norm;
}
// This is "the" object function which is evaluated many times for each
// vertex (decimated with the accuracy parameter) of each object.
// Therefore it is upmost crucial for this function to be as efficient
// as it possibly can be but at the same time, it has to provide
// reasonable results.
std::tuple<double /*score*/, Box /*farthest point from bin center*/>
objfunc(const Item &item, const Point &bincenter)
{
const double bin_area = m_bin_area;
const SpatIndex& spatindex = m_rtree;
const SpatIndex& smalls_spatindex = m_smallsrtree;
// We will treat big items (compared to the print bed) differently
auto isBig = [bin_area](double a) {
return a/bin_area > BIG_ITEM_TRESHOLD ;
};
// Candidate item bounding box
auto ibb = item.boundingBox();
// Calculate the full bounding box of the pile with the candidate item
auto fullbb = sl::boundingBox(m_pilebb, ibb);
// The bounding box of the big items (they will accumulate in the center
// of the pile
Box bigbb;
if(spatindex.empty()) bigbb = fullbb;
else {
auto boostbb = spatindex.bounds();
boost::geometry::convert(boostbb, bigbb);
}
// Will hold the resulting score
double score = 0;
// Density is the pack density: how big is the arranged pile
double density = 0;
// Distinction of cases for the arrangement scene
enum e_cases {
// This branch is for big items in a mixed (big and small) scene
// OR for all items in a small-only scene.
BIG_ITEM,
// This branch is for the last big item in a mixed scene
LAST_BIG_ITEM,
// For small items in a mixed scene.
SMALL_ITEM
} compute_case;
bool bigitems = isBig(item.area()) || spatindex.empty();
if(bigitems && !m_remaining.empty()) compute_case = BIG_ITEM;
else if (bigitems && m_remaining.empty()) compute_case = LAST_BIG_ITEM;
else compute_case = SMALL_ITEM;
switch (compute_case) {
case BIG_ITEM: {
const Point& minc = ibb.minCorner(); // bottom left corner
const Point& maxc = ibb.maxCorner(); // top right corner
// top left and bottom right corners
Point top_left{getX(minc), getY(maxc)};
Point bottom_right{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:
double dist = norm(*(std::min_element(dists.begin(), dists.end())));
double bindist = norm(pl::distance(ibb.center(), bincenter));
dist = 0.8 * dist + 0.2 * bindist;
// Prepare a variable for the alignment score.
// This will indicate: how well is the candidate item
// aligned with its neighbors. We will check the alignment
// with all neighbors and return the score for the best
// alignment. So it is enough for the candidate to be
// aligned with only one item.
auto alignment_score = 1.0;
auto query = bgi::intersects(ibb);
auto& index = isBig(item.area()) ? spatindex : smalls_spatindex;
// Query the spatial index for the neighbors
std::vector<SpatElement> result;
result.reserve(index.size());
index.query(query, std::back_inserter(result));
// now get the score for the best alignment
for(auto& e : result) {
auto idx = e.second;
Item& p = m_items[idx];
auto parea = p.area();
if(std::abs(1.0 - parea/item.area()) < 1e-6) {
auto bb = sl::boundingBox(p.boundingBox(), ibb);
auto bbarea = bb.area();
auto ascore = 1.0 - (item.area() + parea)/bbarea;
if(ascore < alignment_score) alignment_score = ascore;
}
}
density = std::sqrt(norm(fullbb.width()) * norm(fullbb.height()));
double R = double(m_remaining.size()) / m_item_count;
// The final mix of the score is the balance between the
// distance from the full pile center, the pack density and
// the alignment with the neighbors
if (result.empty())
score = 0.50 * dist + 0.50 * density;
else
// Let the density matter more when fewer objects remain
score = 0.50 * dist + (1.0 - R) * 0.20 * density +
0.30 * alignment_score;
break;
}
case LAST_BIG_ITEM: {
score = norm(pl::distance(ibb.center(), m_pilebb.center()));
break;
}
case SMALL_ITEM: {
// 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 = norm(pl::distance(ibb.center(), bigbb.center()));
break;
}
}
return std::make_tuple(score, fullbb);
}
std::function<double(const Item&)> get_objfn();
public:
AutoArranger(const TBin & bin,
const ArrangeParams &params,
std::function<void(unsigned)> progressind,
std::function<bool(void)> stopcond)
: m_pck(bin, params.min_obj_distance)
, m_bin(bin)
, m_bin_area(sl::area(bin))
, m_norm(std::sqrt(m_bin_area))
{
fill_config(m_pconf, params);
// Set up a callback that is called just before arranging starts
// This functionality is provided by the Nester class (m_pack).
m_pconf.before_packing =
[this](const MultiPolygon& merged_pile, // merged pile
const ItemGroup& items, // packed items
const ItemGroup& remaining) // future items to be packed
{
m_items = items;
m_merged_pile = merged_pile;
m_remaining = remaining;
m_pilebb = sl::boundingBox(merged_pile);
m_rtree.clear();
m_smallsrtree.clear();
// We will treat big items (compared to the print bed) differently
auto isBig = [this](double a) {
return a / m_bin_area > BIG_ITEM_TRESHOLD ;
};
for(unsigned idx = 0; idx < items.size(); ++idx) {
Item& itm = items[idx];
if(isBig(itm.area())) m_rtree.insert({itm.boundingBox(), idx});
m_smallsrtree.insert({itm.boundingBox(), idx});
}
};
m_pconf.object_function = get_objfn();
m_pconf.on_preload = [this](const ItemGroup &items, PConfig &cfg) {
if (items.empty()) return;
cfg.alignment = PConfig::Alignment::DONT_ALIGN;
auto bb = sl::boundingBox(m_bin);
auto bbcenter = bb.center();
cfg.object_function = [this, bb, bbcenter](const Item &item) {
return fixed_overfit(objfunc(item, bbcenter), bb);
};
};
auto on_packed = params.on_packed;
if (progressind || on_packed)
m_pck.progressIndicator([this, progressind, on_packed](unsigned rem) {
if (progressind)
progressind(rem);
if (on_packed) {
int last_bed = m_pck.lastPackedBinId();
if (last_bed >= 0) {
Item &last_packed = m_pck.lastResult()[last_bed].back();
ArrangePolygon ap;
ap.bed_idx = last_packed.binId();
ap.priority = last_packed.priority();
on_packed(ap);
}
}
});
if (stopcond) m_pck.stopCondition(stopcond);
m_pck.configure(m_pconf);
}
template<class It> inline void operator()(It from, It to) {
m_rtree.clear();
m_item_count += size_t(to - from);
m_pck.execute(from, to);
m_item_count = 0;
}
PConfig& config() { return m_pconf; }
const PConfig& config() const { return m_pconf; }
inline void preload(std::vector<Item>& fixeditems) {
for(unsigned idx = 0; idx < fixeditems.size(); ++idx) {
Item& itm = fixeditems[idx];
itm.markAsFixedInBin(itm.binId());
}
m_item_count += fixeditems.size();
}
};
template<> std::function<double(const Item&)> AutoArranger<Box>::get_objfn()
{
auto bincenter = m_bin.center();
return [this, bincenter](const Item &itm) {
auto result = objfunc(itm, bincenter);
double score = std::get<0>(result);
auto& fullbb = std::get<1>(result);
double miss = Placer::overfit(fullbb, m_bin);
miss = miss > 0? miss : 0;
score += miss * miss;
return score;
};
}
template<> std::function<double(const Item&)> AutoArranger<Circle>::get_objfn()
{
auto bincenter = m_bin.center();
return [this, bincenter](const Item &item) {
auto result = objfunc(item, bincenter);
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, m_bin);
if(miss < 0) miss = 0;
score += miss*miss;
}
return score;
};
}
// Specialization for a generalized polygon.
// Warning: this is unfinished business. It may or may not work.
template<>
std::function<double(const Item &)> AutoArranger<ExPolygon>::get_objfn()
{
auto bincenter = sl::boundingBox(m_bin).center();
return [this, bincenter](const Item &item) {
return std::get<0>(objfunc(item, bincenter));
};
}
template<class Bin> void remove_large_items(std::vector<Item> &items, Bin &&bin)
{
auto it = items.begin();
while (it != items.end())
sl::isInside(it->transformedShape(), bin) ?
++it : it = items.erase(it);
}
template<class S> Radians min_area_boundingbox_rotation(const S &sh)
{
return minAreaBoundingBox<S, TCompute<S>, boost::rational<LargeInt>>(sh)
.angleToX();
}
template<class S>
Radians fit_into_box_rotation(const S &sh, const _Box<TPoint<S>> &box)
{
return fitIntoBoxRotation<S, TCompute<S>, boost::rational<LargeInt>>(sh, box);
}
template<class BinT> // Arrange for arbitrary bin type
void _arrange(
std::vector<Item> & shapes,
std::vector<Item> & excludes,
const BinT & bin,
const ArrangeParams &params,
std::function<void(unsigned)> progressfn,
std::function<bool()> stopfn)
{
// Integer ceiling the min distance from the bed perimeters
coord_t md = params.min_obj_distance;
md = md / 2;
auto corrected_bin = bin;
sl::offset(corrected_bin, md);
ArrangeParams mod_params = params;
mod_params.min_obj_distance = 0;
AutoArranger<BinT> arranger{corrected_bin, mod_params, progressfn, stopfn};
auto infl = coord_t(std::ceil(params.min_obj_distance / 2.0));
for (Item& itm : shapes) itm.inflate(infl);
for (Item& itm : excludes) itm.inflate(infl);
remove_large_items(excludes, corrected_bin);
// If there is something on the plate
if (!excludes.empty()) arranger.preload(excludes);
std::vector<std::reference_wrapper<Item>> inp;
inp.reserve(shapes.size() + excludes.size());
for (auto &itm : shapes ) inp.emplace_back(itm);
for (auto &itm : excludes) inp.emplace_back(itm);
// Use the minimum bounding box rotation as a starting point.
// TODO: This only works for convex hull. If we ever switch to concave
// polygon nesting, a convex hull needs to be calculated.
if (params.allow_rotations) {
for (auto &itm : shapes) {
itm.rotation(min_area_boundingbox_rotation(itm.rawShape()));
// If the item is too big, try to find a rotation that makes it fit
if constexpr (std::is_same_v<BinT, Box>) {
auto bb = itm.boundingBox();
if (bb.width() >= bin.width() || bb.height() >= bin.height())
itm.rotate(fit_into_box_rotation(itm.transformedShape(), bin));
}
}
}
arranger(inp.begin(), inp.end());
for (Item &itm : inp) itm.inflate(-infl);
}
inline Box to_nestbin(const BoundingBox &bb) { return Box{{bb.min(X), bb.min(Y)}, {bb.max(X), bb.max(Y)}};}
inline Circle to_nestbin(const CircleBed &c) { return Circle({c.center()(0), c.center()(1)}, c.radius()); }
inline ExPolygon to_nestbin(const Polygon &p) { return ExPolygon{p}; }
inline Box to_nestbin(const InfiniteBed &bed) { return Box::infinite({bed.center.x(), bed.center.y()}); }
inline coord_t width(const BoundingBox& box) { return box.max.x() - box.min.x(); }
inline coord_t height(const BoundingBox& box) { return box.max.y() - box.min.y(); }
inline double area(const BoundingBox& box) { return double(width(box)) * height(box); }
inline double poly_area(const Points &pts) { return std::abs(Polygon::area(pts)); }
inline double distance_to(const Point& p1, const Point& p2)
{
double dx = p2.x() - p1.x();
double dy = p2.y() - p1.y();
return std::sqrt(dx*dx + dy*dy);
}
static CircleBed to_circle(const Point &center, const Points& points) {
std::vector<double> vertex_distances;
double avg_dist = 0;
for (const Point& pt : 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 = {};
break;
}
}
return ret;
}
// Create Item from Arrangeable
static void process_arrangeable(const ArrangePolygon &arrpoly,
std::vector<Item> & outp)
{
Polygon p = arrpoly.poly.contour;
const Vec2crd &offs = arrpoly.translation;
double rotation = arrpoly.rotation;
outp.emplace_back(std::move(p));
outp.back().rotation(rotation);
outp.back().translation({offs.x(), offs.y()});
outp.back().binId(arrpoly.bed_idx);
outp.back().priority(arrpoly.priority);
}
template<class Fn> auto call_with_bed(const Points &bed, Fn &&fn)
{
if (bed.empty())
return fn(InfiniteBed{});
else if (bed.size() == 1)
return fn(InfiniteBed{bed.front()});
else {
auto bb = BoundingBox(bed);
CircleBed circ = to_circle(bb.center(), bed);
auto parea = poly_area(bed);
if ((1.0 - parea / area(bb)) < 1e-3)
return fn(bb);
else if (!std::isnan(circ.radius()))
return fn(circ);
else
return fn(Polygon(bed));
}
}
template<>
void arrange(ArrangePolygons & items,
const ArrangePolygons &excludes,
const Points & bed,
const ArrangeParams & params)
{
call_with_bed(bed, [&](const auto &bin) {
arrange(items, excludes, bin, params);
});
}
template<class BedT>
void arrange(ArrangePolygons & arrangables,
const ArrangePolygons &excludes,
const BedT & bed,
const ArrangeParams & params)
{
namespace clppr = Slic3r::ClipperLib;
std::vector<Item> items, fixeditems;
items.reserve(arrangables.size());
for (ArrangePolygon &arrangeable : arrangables)
process_arrangeable(arrangeable, items);
for (const ArrangePolygon &fixed: excludes)
process_arrangeable(fixed, fixeditems);
for (Item &itm : fixeditems) itm.inflate(scaled(-2. * EPSILON));
auto &cfn = params.stopcondition;
auto &pri = params.progressind;
_arrange(items, fixeditems, to_nestbin(bed), params, pri, cfn);
for(size_t i = 0; i < items.size(); ++i) {
Point tr = items[i].translation();
arrangables[i].translation = {coord_t(tr.x()), coord_t(tr.y())};
arrangables[i].rotation = items[i].rotation();
arrangables[i].bed_idx = items[i].binId();
}
}
template void arrange(ArrangePolygons &items, const ArrangePolygons &excludes, const BoundingBox &bed, const ArrangeParams &params);
template void arrange(ArrangePolygons &items, const ArrangePolygons &excludes, const CircleBed &bed, const ArrangeParams &params);
template void arrange(ArrangePolygons &items, const ArrangePolygons &excludes, const Polygon &bed, const ArrangeParams &params);
template void arrange(ArrangePolygons &items, const ArrangePolygons &excludes, const InfiniteBed &bed, const ArrangeParams &params);
} // namespace arr
} // namespace Slic3r