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Improved libnest2d caching

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tamasmeszaros 2018-07-27 12:28:14 +02:00
parent c430f57187
commit 84f97e1f64
22 changed files with 1178 additions and 768 deletions
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34
xs/src/libslic3r/Model.cpp
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@ -529,6 +529,7 @@ bool arrange(Model &model, coordf_t dist, const Slic3r::BoundingBoxf* bb,
// handle different rotations
// arranger.useMinimumBoundigBoxRotation();
pcfg.rotations = { 0.0 };
double norm_2 = std::nan("");
// 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
@ -537,33 +538,46 @@ bool arrange(Model &model, coordf_t dist, const Slic3r::BoundingBoxf* bb,
// 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](
pcfg.object_function = [bin, hasbin, &norm_2](
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;
auto bb = ShapeLike::boundingBox(pile);
auto ibb = item.boundingBox();
auto minc = ibb.minCorner();
auto maxc = ibb.maxCorner();
// We get the current item that's being evaluated.
auto& sh = pile.back();
// We retrieve the reference point of this item
auto rv = ShapeLike::boundingBox(sh).center();
if(std::isnan(norm_2)) norm_2 = pow(norm, 2);
// We get the distance of the reference point from the center of the
// heat bed
auto c = bin.center();
auto d = PointLike::distance(rv, c);
auto cc = bb.center();
auto top_left = PointImpl{getX(minc), getY(maxc)};
auto bottom_right = PointImpl{getX(maxc), getY(minc)};
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);
auto area = bb.width() * bb.height() / norm_2;
auto min_dist = std::min({a, b, c, d, e}) / norm;
// The score will be the normalized distance which will be minimized,
// effectively creating a circle shaped pile of items
double score = d/norm;
double score = 0.8*min_dist + 0.2*area;
// 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(hasbin && !NfpPlacer::wouldFit(bb, bin)) score = 2*penality - score;
if(!NfpPlacer::wouldFit(bb, bin)) score = 2*penality - score;
return score;
};