PrusaSlicer-NonPlainar/src/libslic3r/SLA/SLASupportTreeIGL.cpp

#include <cmath>
#include "SLA/SLASupportTree.hpp"
#include "SLA/SLABoilerPlate.hpp"
#include "SLA/SLASpatIndex.hpp"

// Workaround: IGL signed_distance.h will define PI in the igl namespace.
#undef PI

// HEAVY headers... takes eternity to compile

// for concave hull merging decisions
#include "SLABoostAdapter.hpp"
#include "boost/geometry/index/rtree.hpp"

#ifdef _MSC_VER
#pragma warning(push)
#pragma warning(disable: 4244)
#pragma warning(disable: 4267)
#endif
#include <igl/ray_mesh_intersect.h>
#include <igl/point_mesh_squared_distance.h>
#include <igl/remove_duplicate_vertices.h>
#include <igl/signed_distance.h>
#ifdef _MSC_VER
#pragma warning(pop)
#endif

#include <tbb/parallel_for.h>

#include "SLASpatIndex.hpp"
#include "ClipperUtils.hpp"

namespace Slic3r {
namespace sla {

// Bring back PI from the igl namespace
using igl::PI;

/* **************************************************************************
 * PointIndex implementation
 * ************************************************************************** */

class PointIndex::Impl {
public:
    using BoostIndex = boost::geometry::index::rtree< PointIndexEl,
                       boost::geometry::index::rstar<16, 4> /* ? */ >;

    BoostIndex m_store;
};

PointIndex::PointIndex(): m_impl(new Impl()) {}
PointIndex::~PointIndex() {}

PointIndex::PointIndex(const PointIndex &cpy): m_impl(new Impl(*cpy.m_impl)) {}
PointIndex::PointIndex(PointIndex&& cpy): m_impl(std::move(cpy.m_impl)) {}

PointIndex& PointIndex::operator=(const PointIndex &cpy)
{
    m_impl.reset(new Impl(*cpy.m_impl));
    return *this;
}

PointIndex& PointIndex::operator=(PointIndex &&cpy)
{
    m_impl.swap(cpy.m_impl);
    return *this;
}

void PointIndex::insert(const PointIndexEl &el)
{
    m_impl->m_store.insert(el);
}

bool PointIndex::remove(const PointIndexEl& el)
{
    return m_impl->m_store.remove(el) == 1;
}

std::vector<PointIndexEl>
PointIndex::query(std::function<bool(const PointIndexEl &)> fn)
{
    namespace bgi = boost::geometry::index;

    std::vector<PointIndexEl> ret;
    m_impl->m_store.query(bgi::satisfies(fn), std::back_inserter(ret));
    return ret;
}

std::vector<PointIndexEl> PointIndex::nearest(const Vec3d &el, unsigned k = 1)
{
    namespace bgi = boost::geometry::index;
    std::vector<PointIndexEl> ret; ret.reserve(k);
    m_impl->m_store.query(bgi::nearest(el, k), std::back_inserter(ret));
    return ret;
}

size_t PointIndex::size() const
{
    return m_impl->m_store.size();
}

void PointIndex::foreach(std::function<void (const PointIndexEl &)> fn)
{
    for(auto& el : m_impl->m_store) fn(el);
}

/* **************************************************************************
 * BoxIndex implementation
 * ************************************************************************** */

class BoxIndex::Impl {
public:
    using BoostIndex = boost::geometry::index::
        rtree<BoxIndexEl, boost::geometry::index::rstar<16, 4> /* ? */>;

    BoostIndex m_store;
};

BoxIndex::BoxIndex(): m_impl(new Impl()) {}
BoxIndex::~BoxIndex() {}

BoxIndex::BoxIndex(const BoxIndex &cpy): m_impl(new Impl(*cpy.m_impl)) {}
BoxIndex::BoxIndex(BoxIndex&& cpy): m_impl(std::move(cpy.m_impl)) {}

BoxIndex& BoxIndex::operator=(const BoxIndex &cpy)
{
    m_impl.reset(new Impl(*cpy.m_impl));
    return *this;
}

BoxIndex& BoxIndex::operator=(BoxIndex &&cpy)
{
    m_impl.swap(cpy.m_impl);
    return *this;
}

void BoxIndex::insert(const BoxIndexEl &el)
{
    m_impl->m_store.insert(el);
}

bool BoxIndex::remove(const BoxIndexEl& el)
{
    return m_impl->m_store.remove(el) == 1;
}

std::vector<BoxIndexEl> BoxIndex::query(const BoundingBox &qrbb,
                                        BoxIndex::QueryType qt)
{
    namespace bgi = boost::geometry::index;
    
    std::vector<BoxIndexEl> ret; ret.reserve(m_impl->m_store.size());
    
    switch (qt) {
    case qtIntersects:
        m_impl->m_store.query(bgi::intersects(qrbb), std::back_inserter(ret));
        break;
    case qtWithin:
        m_impl->m_store.query(bgi::within(qrbb), std::back_inserter(ret));
    }
    
    return ret;
}

size_t BoxIndex::size() const
{
    return m_impl->m_store.size();
}

void BoxIndex::foreach(std::function<void (const BoxIndexEl &)> fn)
{
    for(auto& el : m_impl->m_store) fn(el);
}

/* ****************************************************************************
 * EigenMesh3D implementation
 * ****************************************************************************/

class EigenMesh3D::AABBImpl: public igl::AABB<Eigen::MatrixXd, 3> {
public:
#ifdef SLIC3R_SLA_NEEDS_WINDTREE
    igl::WindingNumberAABB<Vec3d, Eigen::MatrixXd, Eigen::MatrixXi> windtree;
#endif /* SLIC3R_SLA_NEEDS_WINDTREE */
};

EigenMesh3D::EigenMesh3D(const TriangleMesh& tmesh): m_aabb(new AABBImpl()) {
    static const double dEPS = 1e-6;

    const stl_file& stl = tmesh.stl;

    auto&& bb = tmesh.bounding_box();
    m_ground_level += bb.min(Z);

    Eigen::MatrixXd V;
    Eigen::MatrixXi F;

    V.resize(3*stl.stats.number_of_facets, 3);
    F.resize(stl.stats.number_of_facets, 3);
    for (unsigned int i = 0; i < stl.stats.number_of_facets; ++i) {
        const stl_facet &facet = stl.facet_start[i];
		V.block<1, 3>(3 * i + 0, 0) = facet.vertex[0].cast<double>();
		V.block<1, 3>(3 * i + 1, 0) = facet.vertex[1].cast<double>();
		V.block<1, 3>(3 * i + 2, 0) = facet.vertex[2].cast<double>();
        F(i, 0) = int(3*i+0);
        F(i, 1) = int(3*i+1);
        F(i, 2) = int(3*i+2);
    }

    // We will convert this to a proper 3d mesh with no duplicate points.
    Eigen::VectorXi SVI, SVJ;
    igl::remove_duplicate_vertices(V, F, dEPS, m_V, SVI, SVJ, m_F);

    // Build the AABB accelaration tree
    m_aabb->init(m_V, m_F);
#ifdef SLIC3R_SLA_NEEDS_WINDTREE
    m_aabb->windtree.set_mesh(m_V, m_F);
#endif /* SLIC3R_SLA_NEEDS_WINDTREE */
}

EigenMesh3D::~EigenMesh3D() {}

EigenMesh3D::EigenMesh3D(const EigenMesh3D &other):
    m_V(other.m_V), m_F(other.m_F), m_ground_level(other.m_ground_level),
    m_aabb( new AABBImpl(*other.m_aabb) ) {}

EigenMesh3D &EigenMesh3D::operator=(const EigenMesh3D &other)
{
    m_V = other.m_V;
    m_F = other.m_F;
    m_ground_level = other.m_ground_level;
    m_aabb.reset(new AABBImpl(*other.m_aabb)); return *this;
}

EigenMesh3D::hit_result
EigenMesh3D::query_ray_hit(const Vec3d &s, const Vec3d &dir) const
{
    igl::Hit hit;
    hit.t = std::numeric_limits<float>::infinity();
    m_aabb->intersect_ray(m_V, m_F, s, dir, hit);

    hit_result ret(*this);
    ret.m_t = double(hit.t);
    ret.m_dir = dir;
    ret.m_source = s;
    if(!std::isinf(hit.t) && !std::isnan(hit.t)) ret.m_face_id = hit.id;

    return ret;
}

#ifdef SLIC3R_SLA_NEEDS_WINDTREE
EigenMesh3D::si_result EigenMesh3D::signed_distance(const Vec3d &p) const {
    double sign = 0; double sqdst = 0; int i = 0;  Vec3d c;
    igl::signed_distance_winding_number(*m_aabb, m_V, m_F, m_aabb->windtree,
                                        p, sign, sqdst, i, c);

    return si_result(sign * std::sqrt(sqdst), i, c);
}

bool EigenMesh3D::inside(const Vec3d &p) const {
    return m_aabb->windtree.inside(p);
}
#endif /* SLIC3R_SLA_NEEDS_WINDTREE */

double EigenMesh3D::squared_distance(const Vec3d &p, int& i, Vec3d& c) const {
    double sqdst = 0;
    Eigen::Matrix<double, 1, 3> pp = p;
    Eigen::Matrix<double, 1, 3> cc;
    sqdst = m_aabb->squared_distance(m_V, m_F, pp, i, cc);
    c = cc;
    return sqdst;
}

/* ****************************************************************************
 * Misc functions
 * ****************************************************************************/

bool point_on_edge(const Vec3d& p, const Vec3d& e1, const Vec3d& e2,
                   double eps = 0.05)
{
    using Line3D = Eigen::ParametrizedLine<double, 3>;

    auto line = Line3D::Through(e1, e2);
    double d = line.distance(p);
    return std::abs(d) < eps;
}

template<class Vec> double distance(const Vec& pp1, const Vec& pp2) {
    auto p = pp2 - pp1;
    return std::sqrt(p.transpose() * p);
}

PointSet normals(const PointSet& points,
                 const EigenMesh3D& mesh,
                 double eps,
                 std::function<void()> thr, // throw on cancel
                 const std::vector<unsigned>& pt_indices = {})
{
    if(points.rows() == 0 || mesh.V().rows() == 0 || mesh.F().rows() == 0)
        return {};

    std::vector<unsigned> range = pt_indices;
    if(range.empty()) {
        range.resize(size_t(points.rows()), 0);
        std::iota(range.begin(), range.end(), 0);
    }

    PointSet            ret(range.size(), 3);

    tbb::parallel_for(size_t(0), range.size(),
                      [&ret, &range, &mesh, &points, thr, eps](size_t ridx)
    {
        thr();
        auto eidx = Eigen::Index(range[ridx]);
        int faceid = 0;
        Vec3d p;

        mesh.squared_distance(points.row(eidx), faceid, p);

        auto trindex = mesh.F().row(faceid);

        const Vec3d& p1 = mesh.V().row(trindex(0));
        const Vec3d& p2 = mesh.V().row(trindex(1));
        const Vec3d& p3 = mesh.V().row(trindex(2));

        // We should check if the point lies on an edge of the hosting triangle.
        // If it does then all the other triangles using the same two points
        // have to be searched and the final normal should be some kind of
        // aggregation of the participating triangle normals. We should also
        // consider the cases where the support point lies right on a vertex
        // of its triangle. The procedure is the same, get the neighbor
        // triangles and calculate an average normal.

        // mark the vertex indices of the edge. ia and ib marks and edge ic
        // will mark a single vertex.
        int ia = -1, ib = -1, ic = -1;

        if(std::abs(distance(p, p1)) < eps) {
            ic = trindex(0);
        }
        else if(std::abs(distance(p, p2)) < eps) {
            ic = trindex(1);
        }
        else if(std::abs(distance(p, p3)) < eps) {
            ic = trindex(2);
        }
        else if(point_on_edge(p, p1, p2, eps)) {
            ia = trindex(0); ib = trindex(1);
        }
        else if(point_on_edge(p, p2, p3, eps)) {
            ia = trindex(1); ib = trindex(2);
        }
        else if(point_on_edge(p, p1, p3, eps)) {
            ia = trindex(0); ib = trindex(2);
        }

        // vector for the neigboring triangles including the detected one.
        std::vector<Vec3i> neigh;
        if(ic >= 0) { // The point is right on a vertex of the triangle
            for(int n = 0; n < mesh.F().rows(); ++n) {
                thr();
                Vec3i ni = mesh.F().row(n);
                if((ni(X) == ic || ni(Y) == ic || ni(Z) == ic))
                    neigh.emplace_back(ni);
            }
        }
        else if(ia >= 0 && ib >= 0) { // the point is on and edge
            // now get all the neigboring triangles
            for(int n = 0; n < mesh.F().rows(); ++n) {
                thr();
                Vec3i ni = mesh.F().row(n);
                if((ni(X) == ia || ni(Y) == ia || ni(Z) == ia) &&
                   (ni(X) == ib || ni(Y) == ib || ni(Z) == ib))
                    neigh.emplace_back(ni);
            }
        }

        // Calculate the normals for the neighboring triangles
        std::vector<Vec3d> neighnorms; neighnorms.reserve(neigh.size());
        for(const Vec3i& tri : neigh) {
            const Vec3d& pt1 = mesh.V().row(tri(0));
            const Vec3d& pt2 = mesh.V().row(tri(1));
            const Vec3d& pt3 = mesh.V().row(tri(2));
            Eigen::Vector3d U = pt2 - pt1;
            Eigen::Vector3d V = pt3 - pt1;
            neighnorms.emplace_back(U.cross(V).normalized());
        }

        // Throw out duplicates. They would cause trouble with summing. We will
        // use std::unique which works on sorted ranges. We will sort by the
        // coefficient-wise sum of the normals. It should force the same
        // elements to be consecutive.
        std::sort(neighnorms.begin(), neighnorms.end(),
                  [](const Vec3d& v1, const Vec3d& v2){
            return v1.sum() < v2.sum();
        });

        auto lend = std::unique(neighnorms.begin(), neighnorms.end(),
                                [](const Vec3d& n1, const Vec3d& n2) {
            // Compare normals for equivalence. This is controvers stuff.
            auto deq = [](double a, double b) { return std::abs(a-b) < 1e-3; };
            return deq(n1(X), n2(X)) && deq(n1(Y), n2(Y)) && deq(n1(Z), n2(Z));
        });

        if(!neighnorms.empty()) { // there were neighbors to count with
            // sum up the normals and then normalize the result again.
            // This unification seems to be enough.
            Vec3d sumnorm(0, 0, 0);
            sumnorm = std::accumulate(neighnorms.begin(), lend, sumnorm);
            sumnorm.normalize();
            ret.row(long(ridx)) = sumnorm;
        }
        else { // point lies safely within its triangle
            Eigen::Vector3d U = p2 - p1;
            Eigen::Vector3d V = p3 - p1;
            ret.row(long(ridx)) = U.cross(V).normalized();
        }
    });

    return ret;
}
namespace bgi = boost::geometry::index;
using Index3D = bgi::rtree< PointIndexEl, bgi::rstar<16, 4> /* ? */ >;

ClusteredPoints cluster(Index3D &sindex,
                        unsigned max_points,
                        std::function<std::vector<PointIndexEl>(
                            const Index3D &, const PointIndexEl &)> qfn)
{
    using Elems = std::vector<PointIndexEl>;

    // Recursive function for visiting all the points in a given distance to
    // each other
    std::function<void(Elems&, Elems&)> group =
    [&sindex, &group, max_points, qfn](Elems& pts, Elems& cluster)
    {
        for(auto& p : pts) {
            std::vector<PointIndexEl> tmp = qfn(sindex, p);
            auto cmp = [](const PointIndexEl& e1, const PointIndexEl& e2){
                return e1.second < e2.second;
            };

            std::sort(tmp.begin(), tmp.end(), cmp);

            Elems newpts;
            std::set_difference(tmp.begin(), tmp.end(),
                                cluster.begin(), cluster.end(),
                                std::back_inserter(newpts), cmp);

            int c = max_points && newpts.size() + cluster.size() > max_points?
                        int(max_points - cluster.size()) : int(newpts.size());

            cluster.insert(cluster.end(), newpts.begin(), newpts.begin() + c);
            std::sort(cluster.begin(), cluster.end(), cmp);

            if(!newpts.empty() && (!max_points || cluster.size() < max_points))
                group(newpts, cluster);
        }
    };

    std::vector<Elems> clusters;
    for(auto it = sindex.begin(); it != sindex.end();) {
        Elems cluster = {};
        Elems pts = {*it};
        group(pts, cluster);

        for(auto& c : cluster) sindex.remove(c);
        it = sindex.begin();

        clusters.emplace_back(cluster);
    }

    ClusteredPoints result;
    for(auto& cluster : clusters) {
        result.emplace_back();
        for(auto c : cluster) result.back().emplace_back(c.second);
    }

    return result;
}

namespace {
std::vector<PointIndexEl> distance_queryfn(const Index3D& sindex,
                                          const PointIndexEl& p,
                                          double dist,
                                          unsigned max_points)
{
    std::vector<PointIndexEl> tmp; tmp.reserve(max_points);
    sindex.query(
        bgi::nearest(p.first, max_points),
        std::back_inserter(tmp)
    );

    for(auto it = tmp.begin(); it < tmp.end(); ++it)
        if(distance(p.first, it->first) > dist) it = tmp.erase(it);

    return tmp;
}
}

// Clustering a set of points by the given criteria
ClusteredPoints cluster(
        const std::vector<unsigned>& indices,
        std::function<Vec3d(unsigned)> pointfn,
        double dist,
        unsigned max_points)
{
    // A spatial index for querying the nearest points
    Index3D sindex;

    // Build the index
    for(auto idx : indices) sindex.insert( std::make_pair(pointfn(idx), idx));

    return cluster(sindex, max_points,
                   [dist, max_points](const Index3D& sidx, const PointIndexEl& p)
    {
        return distance_queryfn(sidx, p, dist, max_points);
    });
}

// Clustering a set of points by the given criteria
ClusteredPoints cluster(
        const std::vector<unsigned>& indices,
        std::function<Vec3d(unsigned)> pointfn,
        std::function<bool(const PointIndexEl&, const PointIndexEl&)> predicate,
        unsigned max_points)
{
    // A spatial index for querying the nearest points
    Index3D sindex;

    // Build the index
    for(auto idx : indices) sindex.insert( std::make_pair(pointfn(idx), idx));

    return cluster(sindex, max_points,
        [max_points, predicate](const Index3D& sidx, const PointIndexEl& p)
    {
        std::vector<PointIndexEl> tmp; tmp.reserve(max_points);
        sidx.query(bgi::satisfies([p, predicate](const PointIndexEl& e){
            return predicate(p, e);
        }), std::back_inserter(tmp));
        return tmp;
    });
}

ClusteredPoints cluster(const PointSet& pts, double dist, unsigned max_points)
{
    // A spatial index for querying the nearest points
    Index3D sindex;

    // Build the index
    for(Eigen::Index i = 0; i < pts.rows(); i++)
        sindex.insert(std::make_pair(Vec3d(pts.row(i)), unsigned(i)));

    return cluster(sindex, max_points,
                   [dist, max_points](const Index3D& sidx, const PointIndexEl& p)
    {
        return distance_queryfn(sidx, p, dist, max_points);
    });
}

}
}