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https://github.com/OrcaSlicer/OrcaSlicer.git
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* Update eigen from v3.3.7 to v5.0.1. This updates eigen from v3.3.7 released on December 11, 2018-12-11 to v5.0.1 released on 2025-11-11. There have be a large number of bug-fixes, optimizations, and improvements between these releases. See the details at; https://gitlab.com/libeigen/eigen/-/releases It retains the previous custom minimal `CMakeLists.txt`, and adds a README-OrcaSlicer.md that explains what version and parts of the upstream eigen release have been included, and where the full release can be found. * Update libigl from v2.0.0 (or older) to v2.6.0. This updates libigl from what was probably v2.0.0 released on 2018-10-16 to v2.6.0 released on 2025-05-15. It's possible the old version was even older than that but there is no version indicators in the code and I ran out of patience identifying missing changes and only went back as far as v2.0.0. There have been a large number of bug-fixes, optimizations, and improvements between these versions. See the following for details; https://github.com/libigl/libigl/releases I retained the minimal custom `CMakeLists.txt`, added `README.md` from the libigl distribution which identifies the version, and added a README-OrcaSlicer.md that details the version and parts that have been included. * Update libslic3r for libigl v2.6.0 changes. This updates libslic3r for all changes moving to eigen v5.0.1 and libigl v2.6.0. Despite the large number of updates to both dependencies, no changes were required for the eigen update, and only one change was required for the libigl update. For libigl, `igl::Hit` was changed to a template taking the Scalar type to use. Previously it was hard-coded to `float`, so to minimize possible impact I've updated all places it is used from `igl::Hit` to `igl::Hit<float>`. * Add compiler option `-DNOMINMAX` for libigl with MSVC. MSVC by default defines `min(()` and `max()` macros that break `std::numeric_limits<>::max()`. The upstream cmake that we don't include adds `-DNOMINMAX` for the libigl module when compiling with MSVC, so we need to add the same thing here. * Fix src/libslic3r/TriangleMeshDeal.cpp for the unmodified upstream libigl. This fixes `TriangleMeshDeal.cpp` to work with the unmodified upstream libigl v2.6.0. loop.{h,cpp} implementation. This file and feature was added in PR "BBS Port: Mesh Subdivision" (#12150) which included changes to `loop.{h,cpp}` in the old version of libigl. This PR avoids modifying the included dependencies, and uses the updated upstream versions of those files without any modifications, which requires fixing TriangleMeshDeal.cpp to work with them. In particular, the modifications made to `loop.{h,cpp}` included changing the return type from void to bool, adding additional validation checking of the input meshes, and returning false if they failed validation. These added checks looked unnecessary and would only have caught problems if the input mesh was very corrupt. To make `TriangleMeshDeal.cpp` work without this built-in checking functionality, I removed checking/handling of any `false` return value. There was also a hell of a lot of redundant copying and casting back and forth between float and double, so I cleaned that up. The input and output meshs use floats for the vertexes, and there would be no accuracy benefits from casting to and from doubles for the simple weighted average operations done by igl::loop(). So this just uses `Eigen:Map` to use the original input mesh vertex data directly without requiring any copy or casting. * Move eigen from included `deps_src` to externaly fetched `deps`. This copys what PrusaSlicer did and moved it from an included dependency under `deps_src` to an externaly fetched dependency under `deps`. This requires updating some `CMakeList.txt` configs and removing the old and obsolete `cmake/modules/FindEigen3.cmake`. The details of when this was done in PrusaSlicer and the followup fixes are at; *21116995d7* https://github.com/prusa3d/PrusaSlicer/issues/13608 * https://github.com/prusa3d/PrusaSlicer/pull/13609 *e3c277b9eeFor some reason I don't fully understand this also required fixing `src/slic3r/GUI/GUI_App.cpp` by adding `#include <boost/nowide/cstdio.hpp>` to fix an `error: ‘remove’ is not a member of ‘boost::nowide'`. The main thing I don't understand is how it worked before. Note that this include is in the PrusaSlicer version of this file, but it also significantly deviates from what is currently in OrcaSlicer in many other ways. * Whups... I missed adding the deps/Eigen/Eigen.cmake file... * Tidy some whitespace indenting in CMakeLists.txt. * Ugh... tabs indenting needing fixes. * Change the include order of deps/Eigen. It turns out that although Boost includes some references to Eigen, Eigen also includes some references to Boost for supporting some of it's additional numeric types. I don't think it matters much since we are not using these features, but I think technically its more correct to say Eigen depends on Boost than the other way around, so I've re-ordered them. * Add source for Eigen 5.0.1 download to flatpak yml config. * Add explicit `DEPENDS dep_Boost to deps/Eigen. I missed this before. This ensures we don't rely on include orders to make sure Boost is installed before we configure Eigen. * Add `DEPENDS dep_Boost dep_GMP dep_MPFR` to deps/Eigen. It turns out Eigen can also use GMP and MPFR for multi-precision and multi-precision-rounded numeric types if they are available. Again, I don't think we are using these so it doesn't really matter, but it is technically correct and ensures they are there if we ever do need them. * Fix deps DEPENDENCY ordering for GMP, MPFR, Eigen, and CGAL. I think this is finally correct. Apparently CGAL also optionally depends on Eigen, so the correct dependency order from lowest to highest is GMP, MPFR, Eigen, and CGAL. --------- Co-authored-by: Donovan Baarda <dbaarda@google.com> Co-authored-by: Noisyfox <timemanager.rick@gmail.com>
936 lines
25 KiB
C++
936 lines
25 KiB
C++
// This file is part of libigl, a simple c++ geometry processing library.
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//
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// Copyright (C) 2013 Daniele Panozzo <daniele.panozzo@gmail.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla Public License
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// v. 2.0. If a copy of the MPL was not distributed with this file, You can
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// obtain one at http://mozilla.org/MPL/2.0/.
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#include "principal_curvature.h"
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#include <iostream>
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#include <fstream>
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#include <iomanip>
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#include <iostream>
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#include <queue>
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#include <list>
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#include <cmath>
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#include <limits>
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#include <Eigen/SparseCholesky>
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// Lib IGL includes
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#include "adjacency_list.h"
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#include "per_face_normals.h"
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#include "per_vertex_normals.h"
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#include "avg_edge_length.h"
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#include "vertex_triangle_adjacency.h"
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typedef enum
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{
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SPHERE_SEARCH,
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K_RING_SEARCH
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} searchType;
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typedef enum
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{
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AVERAGE,
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PROJ_PLANE
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} normalType;
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class CurvatureCalculator
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{
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public:
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/* Row number i represents the i-th vertex, whose columns are:
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curv[i][0] : K1
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curv[i][1] : K2
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curvDir[i][0] : PD1
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curvDir[i][1] : PD2
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*/
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std::vector< std::vector<double> > curv;
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std::vector< std::vector<Eigen::Vector3d> > curvDir;
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bool curvatureComputed;
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class Quadric
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{
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public:
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IGL_INLINE Quadric ()
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{
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a() = b() = c() = d() = e() = 1.0;
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}
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IGL_INLINE Quadric(double av, double bv, double cv, double dv, double ev)
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{
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a() = av;
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b() = bv;
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c() = cv;
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d() = dv;
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e() = ev;
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}
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IGL_INLINE double& a() { return data[0];}
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IGL_INLINE double& b() { return data[1];}
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IGL_INLINE double& c() { return data[2];}
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IGL_INLINE double& d() { return data[3];}
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IGL_INLINE double& e() { return data[4];}
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double data[5];
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IGL_INLINE double evaluate(double u, double v)
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{
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return a()*u*u + b()*u*v + c()*v*v + d()*u + e()*v;
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}
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IGL_INLINE double du(double u, double v)
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{
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return 2.0*a()*u + b()*v + d();
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}
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IGL_INLINE double dv(double u, double v)
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{
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return 2.0*c()*v + b()*u + e();
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}
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// Why do these take u,v arguments if they're not used?
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IGL_INLINE double duv(double , double )
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{
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return b();
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}
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IGL_INLINE double duu(double , double )
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{
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return 2.0*a();
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}
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IGL_INLINE double dvv(double , double )
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{
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return 2.0*c();
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}
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IGL_INLINE static Quadric fit(const std::vector<Eigen::Vector3d> &VV)
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{
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assert(VV.size() >= 5);
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Eigen::MatrixXd A(VV.size(),5);
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Eigen::MatrixXd b(VV.size(),1);
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Eigen::MatrixXd sol(5,1);
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for(unsigned int c=0; c < VV.size(); ++c)
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{
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double u = VV[c][0];
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double v = VV[c][1];
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double n = VV[c][2];
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A(c,0) = u*u;
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A(c,1) = u*v;
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A(c,2) = v*v;
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A(c,3) = u;
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A(c,4) = v;
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b(c) = n;
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}
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sol=A.jacobiSvd(Eigen::ComputeThinU | Eigen::ComputeThinV).solve(b);
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return Quadric(sol(0),sol(1),sol(2),sol(3),sol(4));
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}
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};
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public:
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Eigen::MatrixXd vertices;
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// Face list of current mesh (#F x 3) or (#F x 4)
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// The i-th row contains the indices of the vertices that forms the i-th face in ccw order
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Eigen::MatrixXi faces;
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std::vector<std::vector<int> > vertex_to_vertices;
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std::vector<std::vector<int> > vertex_to_faces;
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std::vector<std::vector<int> > vertex_to_faces_index;
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Eigen::MatrixXd face_normals;
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Eigen::MatrixXd vertex_normals;
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/* Size of the neighborhood */
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double sphereRadius;
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int kRing;
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bool localMode; /* Use local mode */
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bool projectionPlaneCheck; /* Check collected vertices on tangent plane */
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bool montecarlo;
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unsigned int montecarloN;
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searchType st; /* Use either a sphere search or a k-ring search */
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normalType nt;
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double lastRadius;
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double scaledRadius;
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std::string lastMeshName;
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/* Benchmark related variables */
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bool expStep; /* True if we want the radius to increase exponentially */
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int step; /* If expStep==false, by how much rhe radius increases on every step */
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int maxSize; /* The maximum limit of the radius in the benchmark */
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IGL_INLINE CurvatureCalculator();
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IGL_INLINE void init(const Eigen::MatrixXd& V, const Eigen::MatrixXi& F);
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IGL_INLINE void finalEigenStuff(int, const std::vector<Eigen::Vector3d>&, Quadric&);
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IGL_INLINE void fitQuadric(const Eigen::Vector3d&, const std::vector<Eigen::Vector3d>& ref, const std::vector<int>& , Quadric *);
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IGL_INLINE void applyProjOnPlane(const Eigen::Vector3d&, const std::vector<int>&, std::vector<int>&);
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IGL_INLINE void getSphere(const int, const double, std::vector<int>&, int min);
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IGL_INLINE void getKRing(const int, const double,std::vector<int>&);
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IGL_INLINE Eigen::Vector3d project(const Eigen::Vector3d&, const Eigen::Vector3d&, const Eigen::Vector3d&);
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IGL_INLINE void computeReferenceFrame(int, const Eigen::Vector3d&, std::vector<Eigen::Vector3d>&);
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IGL_INLINE void getAverageNormal(int, const std::vector<int>&, Eigen::Vector3d&);
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IGL_INLINE void getProjPlane(int, const std::vector<int>&, Eigen::Vector3d&);
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IGL_INLINE void applyMontecarlo(const std::vector<int>&,std::vector<int>*);
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IGL_INLINE void computeCurvature();
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IGL_INLINE void printCurvature(const std::string& outpath);
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IGL_INLINE double getAverageEdge();
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IGL_INLINE static int rotateForward (double *v0, double *v1, double *v2)
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{
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double t;
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if (std::abs(*v2) >= std::abs(*v1) && std::abs(*v2) >= std::abs(*v0))
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return 0;
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t = *v0;
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*v0 = *v2;
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*v2 = *v1;
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*v1 = t;
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return 1 + rotateForward (v0, v1, v2);
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}
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IGL_INLINE static void rotateBackward (int nr, double *v0, double *v1, double *v2)
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{
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double t;
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if (nr == 0)
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return;
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t = *v2;
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*v2 = *v0;
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*v0 = *v1;
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*v1 = t;
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rotateBackward (nr - 1, v0, v1, v2);
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}
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IGL_INLINE static Eigen::Vector3d chooseMax (Eigen::Vector3d n, Eigen::Vector3d abc, double ab)
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{
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int max_i;
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double max_sp;
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Eigen::Vector3d nt[8];
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n.normalize ();
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abc.normalize ();
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max_sp = - std::numeric_limits<double>::max();
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for (int i = 0; i < 4; ++i)
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{
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nt[i] = n;
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if (ab > 0)
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{
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switch (i)
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{
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case 0:
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break;
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case 1:
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nt[i][2] = -n[2];
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break;
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case 2:
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nt[i][0] = -n[0];
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nt[i][1] = -n[1];
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break;
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case 3:
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nt[i][0] = -n[0];
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nt[i][1] = -n[1];
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nt[i][2] = -n[2];
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break;
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}
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}
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else
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{
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switch (i)
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{
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case 0:
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nt[i][0] = -n[0];
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break;
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case 1:
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nt[i][1] = -n[1];
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break;
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case 2:
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nt[i][0] = -n[0];
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nt[i][2] = -n[2];
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break;
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case 3:
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nt[i][1] = -n[1];
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nt[i][2] = -n[2];
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break;
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}
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}
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if (nt[i].dot(abc) > max_sp)
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{
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max_sp = nt[i].dot(abc);
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max_i = i;
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}
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}
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return nt[max_i];
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}
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};
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class comparer
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{
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public:
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IGL_INLINE bool operator() (const std::pair<int, double>& lhs, const std::pair<int, double>&rhs) const
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{
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return lhs.second>rhs.second;
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}
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};
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IGL_INLINE CurvatureCalculator::CurvatureCalculator()
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{
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this->localMode=true;
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this->projectionPlaneCheck=true;
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this->sphereRadius=5;
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this->st=SPHERE_SEARCH;
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this->nt=AVERAGE;
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this->montecarlo=false;
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this->montecarloN=0;
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this->kRing=3;
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this->curvatureComputed=false;
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this->expStep=true;
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}
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IGL_INLINE void CurvatureCalculator::init(const Eigen::MatrixXd& V, const Eigen::MatrixXi& F)
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{
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// Normalize vertices
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vertices = V;
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// vertices = vertices.array() - vertices.minCoeff();
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// vertices = vertices.array() / vertices.maxCoeff();
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// vertices = vertices.array() * (1.0/igl::avg_edge_length(V,F));
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faces = F;
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igl::adjacency_list(F, vertex_to_vertices);
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igl::vertex_triangle_adjacency(V, F, vertex_to_faces, vertex_to_faces_index);
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igl::per_face_normals(V, F, face_normals);
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igl::per_vertex_normals(V, F, face_normals, vertex_normals);
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}
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IGL_INLINE void CurvatureCalculator::fitQuadric(const Eigen::Vector3d& v, const std::vector<Eigen::Vector3d>& ref, const std::vector<int>& vv, Quadric *q)
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{
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std::vector<Eigen::Vector3d> points;
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points.reserve (vv.size());
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for (unsigned int i = 0; i < vv.size(); ++i) {
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Eigen::Vector3d cp = vertices.row(vv[i]);
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// vtang non e` il v tangente!!!
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Eigen::Vector3d vTang = cp - v;
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double x = vTang.dot(ref[0]);
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double y = vTang.dot(ref[1]);
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double z = vTang.dot(ref[2]);
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points.push_back(Eigen::Vector3d (x,y,z));
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}
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if (points.size() < 5)
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{
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assert(false && "fit function requires at least 5 points");
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*q = Quadric(0,0,0,0,0);
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}
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else
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{
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*q = Quadric::fit (points);
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}
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}
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IGL_INLINE void CurvatureCalculator::finalEigenStuff(int i, const std::vector<Eigen::Vector3d>& ref, Quadric& q)
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{
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const double a = q.a();
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const double b = q.b();
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const double c = q.c();
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const double d = q.d();
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const double e = q.e();
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// if (fabs(a) < 10e-8 || fabs(b) < 10e-8)
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// {
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// std::cout << "Degenerate quadric: " << i << std::endl;
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// }
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double E = 1.0 + d*d;
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double F = d*e;
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double G = 1.0 + e*e;
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Eigen::Vector3d n = Eigen::Vector3d(-d,-e,1.0).normalized();
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double L = 2.0 * a * n[2];
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double M = b * n[2];
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double N = 2 * c * n[2];
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// ----------------- Eigen stuff
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Eigen::Matrix2d m;
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m << L*G - M*F, M*E-L*F, M*E-L*F, N*E-M*F;
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m = m / (E*G-F*F);
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Eigen::SelfAdjointEigenSolver<Eigen::Matrix2d> eig(m);
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Eigen::Vector2d c_val = eig.eigenvalues();
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Eigen::Matrix2d c_vec = eig.eigenvectors();
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// std::cerr << "c_val:" << c_val << std::endl;
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// std::cerr << "c_vec:" << c_vec << std::endl;
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// std::cerr << "c_vec:" << c_vec(0) << " " << c_vec(1) << std::endl;
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c_val = -c_val;
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Eigen::Vector3d v1, v2;
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v1[0] = c_vec(0);
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v1[1] = c_vec(1);
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v1[2] = 0; //d * v1[0] + e * v1[1];
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v2[0] = c_vec(2);
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v2[1] = c_vec(3);
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v2[2] = 0; //d * v2[0] + e * v2[1];
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// v1 = v1.normalized();
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// v2 = v2.normalized();
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Eigen::Vector3d v1global = ref[0] * v1[0] + ref[1] * v1[1] + ref[2] * v1[2];
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Eigen::Vector3d v2global = ref[0] * v2[0] + ref[1] * v2[1] + ref[2] * v2[2];
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v1global.normalize();
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v2global.normalize();
|
|
|
|
v1global *= c_val(0);
|
|
v2global *= c_val(1);
|
|
|
|
if (c_val[0] > c_val[1])
|
|
{
|
|
curv[i]=std::vector<double>(2);
|
|
curv[i][0]=c_val(0);
|
|
curv[i][1]=c_val(1);
|
|
curvDir[i]=std::vector<Eigen::Vector3d>(2);
|
|
curvDir[i][0]=v1global;
|
|
curvDir[i][1]=v2global;
|
|
}
|
|
else
|
|
{
|
|
curv[i]=std::vector<double>(2);
|
|
curv[i][0]=c_val(1);
|
|
curv[i][1]=c_val(0);
|
|
curvDir[i]=std::vector<Eigen::Vector3d>(2);
|
|
curvDir[i][0]=v2global;
|
|
curvDir[i][1]=v1global;
|
|
}
|
|
// ---- end Eigen stuff
|
|
}
|
|
|
|
IGL_INLINE void CurvatureCalculator::getKRing(const int start, const double r, std::vector<int>&vv)
|
|
{
|
|
int bufsize=vertices.rows();
|
|
vv.reserve(bufsize);
|
|
std::list<std::pair<int,int> > queue;
|
|
std::vector<bool> visited(bufsize, false);
|
|
queue.push_back(std::pair<int,int>(start,0));
|
|
visited[start]=true;
|
|
while (!queue.empty())
|
|
{
|
|
int toVisit=queue.front().first;
|
|
int distance=queue.front().second;
|
|
queue.pop_front();
|
|
vv.push_back(toVisit);
|
|
if(toVisit<vertex_to_vertices.size())
|
|
{
|
|
if (distance<(int)r)
|
|
{
|
|
for (unsigned int i=0; i<vertex_to_vertices[toVisit].size(); ++i)
|
|
{
|
|
int neighbor=vertex_to_vertices[toVisit][i];
|
|
if (!visited[neighbor])
|
|
{
|
|
queue.push_back(std::pair<int,int> (neighbor,distance+1));
|
|
visited[neighbor]=true;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
IGL_INLINE void CurvatureCalculator::getSphere(const int start, const double r, std::vector<int> &vv, int min)
|
|
{
|
|
int bufsize=vertices.rows();
|
|
vv.reserve(bufsize);
|
|
std::list<int> queue;
|
|
std::vector<bool> visited(bufsize, false);
|
|
queue.push_back(start);
|
|
visited[start]=true;
|
|
Eigen::Vector3d me=vertices.row(start);
|
|
std::priority_queue<std::pair<int, double>, std::vector<std::pair<int, double> >, comparer > extra_candidates;
|
|
while (!queue.empty())
|
|
{
|
|
int toVisit=queue.front();
|
|
queue.pop_front();
|
|
vv.push_back(toVisit);
|
|
for (unsigned int i=0; i<vertex_to_vertices[toVisit].size(); ++i)
|
|
{
|
|
int neighbor=vertex_to_vertices[toVisit][i];
|
|
if (!visited[neighbor])
|
|
{
|
|
Eigen::Vector3d neigh=vertices.row(neighbor);
|
|
double distance=(me-neigh).norm();
|
|
if (distance<r)
|
|
queue.push_back(neighbor);
|
|
else if ((int)vv.size()<min)
|
|
extra_candidates.push(std::pair<int,double>(neighbor,distance));
|
|
visited[neighbor]=true;
|
|
}
|
|
}
|
|
}
|
|
while (!extra_candidates.empty() && (int)vv.size()<min)
|
|
{
|
|
std::pair<int, double> cand=extra_candidates.top();
|
|
extra_candidates.pop();
|
|
vv.push_back(cand.first);
|
|
for (unsigned int i=0; i<vertex_to_vertices[cand.first].size(); ++i)
|
|
{
|
|
int neighbor=vertex_to_vertices[cand.first][i];
|
|
if (!visited[neighbor])
|
|
{
|
|
Eigen::Vector3d neigh=vertices.row(neighbor);
|
|
double distance=(me-neigh).norm();
|
|
extra_candidates.push(std::pair<int,double>(neighbor,distance));
|
|
visited[neighbor]=true;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
IGL_INLINE Eigen::Vector3d CurvatureCalculator::project(const Eigen::Vector3d& v, const Eigen::Vector3d& vp, const Eigen::Vector3d& ppn)
|
|
{
|
|
return (vp - (ppn * ((vp - v).dot(ppn))));
|
|
}
|
|
|
|
IGL_INLINE void CurvatureCalculator::computeReferenceFrame(int i, const Eigen::Vector3d& normal, std::vector<Eigen::Vector3d>& ref )
|
|
{
|
|
|
|
Eigen::Vector3d longest_v=Eigen::Vector3d(vertices.row(vertex_to_vertices[i][0]));
|
|
|
|
longest_v=(project(vertices.row(i),longest_v,normal)-Eigen::Vector3d(vertices.row(i))).normalized();
|
|
|
|
/* L'ultimo asse si ottiene come prodotto vettoriale tra i due
|
|
* calcolati */
|
|
Eigen::Vector3d y_axis=(normal.cross(longest_v)).normalized();
|
|
ref[0]=longest_v;
|
|
ref[1]=y_axis;
|
|
ref[2]=normal;
|
|
}
|
|
|
|
IGL_INLINE void CurvatureCalculator::getAverageNormal(int j, const std::vector<int>& vv, Eigen::Vector3d& normal)
|
|
{
|
|
normal=(vertex_normals.row(j)).normalized();
|
|
if (localMode)
|
|
return;
|
|
|
|
for (unsigned int i=0; i<vv.size(); ++i)
|
|
{
|
|
normal+=vertex_normals.row(vv[i]).normalized();
|
|
}
|
|
normal.normalize();
|
|
}
|
|
|
|
IGL_INLINE void CurvatureCalculator::getProjPlane(int j, const std::vector<int>& vv, Eigen::Vector3d& ppn)
|
|
{
|
|
int nr;
|
|
double a, b, c;
|
|
double nx, ny, nz;
|
|
double abcq;
|
|
|
|
a = b = c = 0;
|
|
|
|
if (localMode)
|
|
{
|
|
for (unsigned int i=0; i<vertex_to_faces.at(j).size(); ++i)
|
|
{
|
|
Eigen::Vector3d faceNormal=face_normals.row(vertex_to_faces.at(j).at(i));
|
|
a += faceNormal[0];
|
|
b += faceNormal[1];
|
|
c += faceNormal[2];
|
|
}
|
|
}
|
|
else
|
|
{
|
|
for (unsigned int i=0; i<vv.size(); ++i)
|
|
{
|
|
a+= vertex_normals.row(vv[i])[0];
|
|
b+= vertex_normals.row(vv[i])[1];
|
|
c+= vertex_normals.row(vv[i])[2];
|
|
}
|
|
}
|
|
nr = rotateForward (&a, &b, &c);
|
|
abcq = a*a + b*b + c*c;
|
|
nx = sqrt (a*a / abcq);
|
|
ny = sqrt (b*b / abcq);
|
|
nz = sqrt (1 - nx*nx - ny*ny);
|
|
rotateBackward (nr, &a, &b, &c);
|
|
rotateBackward (nr, &nx, &ny, &nz);
|
|
|
|
ppn = chooseMax (Eigen::Vector3d(nx, ny, nz), Eigen::Vector3d (a, b, c), a * b);
|
|
ppn.normalize();
|
|
}
|
|
|
|
|
|
IGL_INLINE double CurvatureCalculator::getAverageEdge()
|
|
{
|
|
double sum = 0;
|
|
int count = 0;
|
|
|
|
for (int i = 0; i<faces.rows(); ++i)
|
|
{
|
|
for (short unsigned j=0; j<3; ++j)
|
|
{
|
|
Eigen::Vector3d p1=vertices.row(faces.row(i)[j]);
|
|
Eigen::Vector3d p2=vertices.row(faces.row(i)[(j+1)%3]);
|
|
|
|
double l = (p1-p2).norm();
|
|
|
|
sum+=l;
|
|
++count;
|
|
}
|
|
}
|
|
|
|
return (sum/(double)count);
|
|
}
|
|
|
|
|
|
IGL_INLINE void CurvatureCalculator::applyProjOnPlane(const Eigen::Vector3d& ppn, const std::vector<int>& vin, std::vector<int> &vout)
|
|
{
|
|
for (std::vector<int>::const_iterator vpi = vin.begin(); vpi != vin.end(); ++vpi)
|
|
if (vertex_normals.row(*vpi) * ppn > 0.0)
|
|
vout.push_back(*vpi);
|
|
}
|
|
|
|
IGL_INLINE void CurvatureCalculator::applyMontecarlo(const std::vector<int>& vin, std::vector<int> *vout)
|
|
{
|
|
if (montecarloN >= vin.size ())
|
|
{
|
|
*vout = vin;
|
|
return;
|
|
}
|
|
|
|
float p = ((float) montecarloN) / (float) vin.size();
|
|
for (std::vector<int>::const_iterator vpi = vin.begin(); vpi != vin.end(); ++vpi)
|
|
{
|
|
float r;
|
|
if ((r = ((float)rand () / RAND_MAX)) < p)
|
|
{
|
|
vout->push_back(*vpi);
|
|
}
|
|
}
|
|
}
|
|
|
|
IGL_INLINE void CurvatureCalculator::computeCurvature()
|
|
{
|
|
//CHECK che esista la mesh
|
|
const size_t vertices_count=vertices.rows();
|
|
|
|
if (vertices_count ==0)
|
|
return;
|
|
|
|
curvDir=std::vector< std::vector<Eigen::Vector3d> >(vertices_count);
|
|
curv=std::vector<std::vector<double> >(vertices_count);
|
|
|
|
|
|
|
|
scaledRadius=getAverageEdge()*sphereRadius;
|
|
|
|
std::vector<int> vv;
|
|
std::vector<int> vvtmp;
|
|
Eigen::Vector3d normal;
|
|
|
|
//double time_spent;
|
|
//double searchtime=0, ref_time=0, fit_time=0, final_time=0;
|
|
|
|
for (size_t i=0; i<vertices_count; ++i)
|
|
{
|
|
vv.clear();
|
|
vvtmp.clear();
|
|
Eigen::Vector3d me=vertices.row(i);
|
|
switch (st)
|
|
{
|
|
case SPHERE_SEARCH:
|
|
getSphere(i,scaledRadius,vv,6);
|
|
break;
|
|
case K_RING_SEARCH:
|
|
getKRing(i,kRing,vv);
|
|
break;
|
|
default:
|
|
fprintf(stderr,"Error: search type not recognized");
|
|
return;
|
|
}
|
|
|
|
if (vv.size()<6)
|
|
{
|
|
//std::cerr << "Could not compute curvature of radius " << scaledRadius << std::endl;
|
|
continue;
|
|
}
|
|
|
|
|
|
if (projectionPlaneCheck)
|
|
{
|
|
vvtmp.reserve (vv.size ());
|
|
applyProjOnPlane (vertex_normals.row(i), vv, vvtmp);
|
|
if (vvtmp.size() >= 6 && vvtmp.size()<vv.size())
|
|
vv = vvtmp;
|
|
}
|
|
|
|
|
|
switch (nt)
|
|
{
|
|
case AVERAGE:
|
|
getAverageNormal(i,vv,normal);
|
|
break;
|
|
case PROJ_PLANE:
|
|
getProjPlane(i,vv,normal);
|
|
break;
|
|
default:
|
|
fprintf(stderr,"Error: normal type not recognized");
|
|
return;
|
|
}
|
|
if (vv.size()<6)
|
|
{
|
|
//std::cerr << "Could not compute curvature of radius " << scaledRadius << std::endl;
|
|
continue;
|
|
}
|
|
if (montecarlo)
|
|
{
|
|
if(montecarloN<6)
|
|
break;
|
|
vvtmp.reserve(vv.size());
|
|
applyMontecarlo(vv,&vvtmp);
|
|
vv=vvtmp;
|
|
}
|
|
|
|
if (vv.size()<6)
|
|
return;
|
|
std::vector<Eigen::Vector3d> ref(3);
|
|
computeReferenceFrame(i,normal,ref);
|
|
|
|
Quadric q;
|
|
fitQuadric (me, ref, vv, &q);
|
|
finalEigenStuff(i,ref,q);
|
|
}
|
|
|
|
lastRadius=sphereRadius;
|
|
curvatureComputed=true;
|
|
}
|
|
|
|
IGL_INLINE void CurvatureCalculator::printCurvature(const std::string& outpath)
|
|
{
|
|
using namespace std;
|
|
if (!curvatureComputed)
|
|
return;
|
|
|
|
std::ofstream of;
|
|
of.open(outpath.c_str());
|
|
|
|
if (!of)
|
|
{
|
|
fprintf(stderr, "Error: could not open output file %s\n", outpath.c_str());
|
|
return;
|
|
}
|
|
|
|
int vertices_count=vertices.rows();
|
|
of << vertices_count << endl;
|
|
for (int i=0; i<vertices_count; ++i)
|
|
{
|
|
of << curv[i][0] << " " << curv[i][1] << " " << curvDir[i][0][0] << " " << curvDir[i][0][1] << " " << curvDir[i][0][2] << " " <<
|
|
curvDir[i][1][0] << " " << curvDir[i][1][1] << " " << curvDir[i][1][2] << endl;
|
|
}
|
|
|
|
of.close();
|
|
|
|
}
|
|
|
|
template <
|
|
typename DerivedV,
|
|
typename DerivedF,
|
|
typename DerivedPD1,
|
|
typename DerivedPD2,
|
|
typename DerivedPV1,
|
|
typename DerivedPV2,
|
|
typename Index>
|
|
IGL_INLINE void igl::principal_curvature(
|
|
const Eigen::MatrixBase<DerivedV>& V,
|
|
const Eigen::MatrixBase<DerivedF>& F,
|
|
Eigen::PlainObjectBase<DerivedPD1>& PD1,
|
|
Eigen::PlainObjectBase<DerivedPD2>& PD2,
|
|
Eigen::PlainObjectBase<DerivedPV1>& PV1,
|
|
Eigen::PlainObjectBase<DerivedPV2>& PV2,
|
|
std::vector<Index>& bad_vertices,
|
|
unsigned radius,
|
|
bool useKring)
|
|
{
|
|
|
|
if (radius < 2)
|
|
{
|
|
radius = 2;
|
|
std::cout << "WARNING: igl::principal_curvature needs a radius >= 2, fixing it to 2." << std::endl;
|
|
}
|
|
|
|
// Preallocate memory
|
|
PD1.resize(V.rows(),3);
|
|
PD2.resize(V.rows(),3);
|
|
|
|
// Preallocate memory
|
|
PV1.resize(V.rows(),1);
|
|
PV2.resize(V.rows(),1);
|
|
|
|
// Precomputation
|
|
CurvatureCalculator cc;
|
|
cc.init(V.template cast<double>(),F.template cast<int>());
|
|
cc.sphereRadius = radius;
|
|
|
|
if (useKring)
|
|
{
|
|
cc.kRing = radius;
|
|
cc.st = K_RING_SEARCH;
|
|
}
|
|
|
|
// Compute
|
|
cc.computeCurvature();
|
|
|
|
// Copy it back
|
|
for (unsigned i=0; i<V.rows(); ++i)
|
|
{
|
|
if (!cc.curv[i].empty())
|
|
{
|
|
PD1.row(i) << cc.curvDir[i][0][0], cc.curvDir[i][0][1], cc.curvDir[i][0][2];
|
|
PD2.row(i) << cc.curvDir[i][1][0], cc.curvDir[i][1][1], cc.curvDir[i][1][2];
|
|
PD1.row(i).normalize();
|
|
PD2.row(i).normalize();
|
|
|
|
if (std::isnan(PD1(i,0)) || std::isnan(PD1(i,1)) || std::isnan(PD1(i,2)) || std::isnan(PD2(i,0)) || std::isnan(PD2(i,1)) || std::isnan(PD2(i,2)))
|
|
{
|
|
PD1.row(i) << 0,0,0;
|
|
PD2.row(i) << 0,0,0;
|
|
}
|
|
|
|
PV1(i) = cc.curv[i][0];
|
|
PV2(i) = cc.curv[i][1];
|
|
|
|
if (PD1.row(i) * PD2.row(i).transpose() > 10e-6)
|
|
{
|
|
bad_vertices.push_back((Index)i);
|
|
|
|
PD1.row(i) *= 0;
|
|
PD2.row(i) *= 0;
|
|
}
|
|
} else {
|
|
bad_vertices.push_back((Index)i);
|
|
|
|
PV1(i) = 0;
|
|
PV2(i) = 0;
|
|
PD1.row(i) << 0,0,0;
|
|
PD2.row(i) << 0,0,0;
|
|
}
|
|
}
|
|
|
|
}
|
|
|
|
template <
|
|
typename DerivedV,
|
|
typename DerivedF,
|
|
typename DerivedPD1,
|
|
typename DerivedPD2,
|
|
typename DerivedPV1,
|
|
typename DerivedPV2>
|
|
IGL_INLINE void igl::principal_curvature(
|
|
const Eigen::MatrixBase<DerivedV>& V,
|
|
const Eigen::MatrixBase<DerivedF>& F,
|
|
Eigen::PlainObjectBase<DerivedPD1>& PD1,
|
|
Eigen::PlainObjectBase<DerivedPD2>& PD2,
|
|
Eigen::PlainObjectBase<DerivedPV1>& PV1,
|
|
Eigen::PlainObjectBase<DerivedPV2>& PV2,
|
|
unsigned radius,
|
|
bool useKring)
|
|
{
|
|
if (radius < 2)
|
|
{
|
|
radius = 2;
|
|
std::cout << "WARNING: igl::principal_curvature needs a radius >= 2, fixing it to 2." << std::endl;
|
|
}
|
|
|
|
// Preallocate memory
|
|
PD1.resize(V.rows(),3);
|
|
PD2.resize(V.rows(),3);
|
|
|
|
// Preallocate memory
|
|
PV1.resize(V.rows(),1);
|
|
PV2.resize(V.rows(),1);
|
|
|
|
// Precomputation
|
|
CurvatureCalculator cc;
|
|
cc.init(V.template cast<double>(),F.template cast<int>());
|
|
cc.sphereRadius = radius;
|
|
|
|
if (useKring)
|
|
{
|
|
cc.kRing = radius;
|
|
cc.st = K_RING_SEARCH;
|
|
}
|
|
|
|
// Compute
|
|
cc.computeCurvature();
|
|
|
|
// Copy it back
|
|
for (unsigned i=0; i<V.rows(); ++i)
|
|
{
|
|
PD1.row(i) << cc.curvDir[i][0][0], cc.curvDir[i][0][1], cc.curvDir[i][0][2];
|
|
PD2.row(i) << cc.curvDir[i][1][0], cc.curvDir[i][1][1], cc.curvDir[i][1][2];
|
|
PD1.row(i).normalize();
|
|
PD2.row(i).normalize();
|
|
|
|
if (std::isnan(PD1(i,0)) || std::isnan(PD1(i,1)) || std::isnan(PD1(i,2)) || std::isnan(PD2(i,0)) || std::isnan(PD2(i,1)) || std::isnan(PD2(i,2)))
|
|
{
|
|
PD1.row(i) << 0,0,0;
|
|
PD2.row(i) << 0,0,0;
|
|
}
|
|
|
|
PV1(i) = cc.curv[i][0];
|
|
PV2(i) = cc.curv[i][1];
|
|
|
|
if (PD1.row(i) * PD2.row(i).transpose() > 10e-6)
|
|
{
|
|
assert(false && "PRINCIPAL_CURVATURE: Something is wrong with vertex");
|
|
PD1.row(i) *= 0;
|
|
PD2.row(i) *= 0;
|
|
}
|
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}
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}
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#ifdef IGL_STATIC_LIBRARY
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// Explicit template instantiation
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// generated by autoexplicit.sh
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template void igl::principal_curvature<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<int, -1, -1, 0, -1, -1>, Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<double, -1, 1, 0, -1, 1>, Eigen::Matrix<double, -1, 1, 0, -1, 1> >(Eigen::MatrixBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&, Eigen::MatrixBase<Eigen::Matrix<int, -1, -1, 0, -1, -1> > const&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, 1, 0, -1, 1> >&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, 1, 0, -1, 1> >&, unsigned int, bool);
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template void igl::principal_curvature<Eigen::Matrix<double, -1, 3, 0, -1, 3>, Eigen::Matrix<int, -1, 3, 0, -1, 3>, Eigen::Matrix<double, -1, 3, 0, -1, 3>, Eigen::Matrix<double, -1, 3, 0, -1, 3>, Eigen::Matrix<double, -1, 1, 0, -1, 1>, Eigen::Matrix<double, -1, 1, 0, -1, 1> >(Eigen::MatrixBase<Eigen::Matrix<double, -1, 3, 0, -1, 3> > const&, Eigen::MatrixBase<Eigen::Matrix<int, -1, 3, 0, -1, 3> > const&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, 3, 0, -1, 3> >&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, 3, 0, -1, 3> >&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, 1, 0, -1, 1> >&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, 1, 0, -1, 1> >&, unsigned int, bool);
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template void igl::principal_curvature<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<int, -1, -1, 0, -1, -1>, Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<double, -1, -1, 0, -1, -1> >(Eigen::MatrixBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&, Eigen::MatrixBase<Eigen::Matrix<int, -1, -1, 0, -1, -1> > const&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >&, unsigned int, bool);
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template void igl::principal_curvature<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<int, -1, -1, 0, -1, -1>, Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<double, -1, 1, 0, -1, 1>, Eigen::Matrix<double, -1, 1, 0, -1, 1>, int>(Eigen::MatrixBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&, Eigen::MatrixBase<Eigen::Matrix<int, -1, -1, 0, -1, -1> > const&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, 1, 0, -1, 1> >&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, 1, 0, -1, 1> >&, std::vector<int, std::allocator<int> >&, unsigned int, bool);
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#endif
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