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linest2d ready for arbitrary shaped beds.

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This commit is contained in:
tamasmeszaros 2018-07-30 15:16:44 +02:00
parent 4e901a9db7
commit d136d61edd
8 changed files with 275 additions and 77 deletions
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123
xs/src/libnest2d/examples/main.cpp
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@ -544,57 +544,126 @@ void arrangeRectangles() {
// input.insert(input.end(), proba.begin(), proba.end());
// input.insert(input.end(), crasher.begin(), crasher.end());
Box bin(250*SCALE, 210*SCALE);
// 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, PolygonImpl>;
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 = 1.0;
double norm_2 = std::nan("");
pconf.object_function = [&bin, &norm_2](Placer::Pile pile, const Item& item,
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;
auto bb = ShapeLike::boundingBox(pile);
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();
auto minc = ibb.minCorner();
auto maxc = ibb.maxCorner();
if(std::isnan(norm_2)) norm_2 = pow(norm, 2);
// 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();
// 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)};
// 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 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);
// The size indicator of the candidate item. This is not the area,
// but almost...
auto itemnormarea = std::sqrt(ibb.width()*ibb.height())/norm;
auto area = bb.width() * bb.height() / norm_2;
// Will hold the resulting score
double score = 0;
auto min_dist = std::min({a, b, c, d, e}) / norm;
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.
// 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;
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(bb, bin)) score = 2*penality - score;
if(!NfpPlacer::wouldFit(fullbb, bin)) score = 2*penality - score;
return score;
};
@ -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(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");