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// Copyright (c) 2007-09 INRIA (France).
// All rights reserved.
//
// This file is part of CGAL (www.cgal.org); you may redistribute it under
// the terms of the Q Public License version 1.0.
// See the file LICENSE.QPL distributed with CGAL.
//
// Licensees holding a valid commercial license may use this file in
// accordance with the commercial license agreement provided with the software.
//
// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
//
// $URL$
// $Id$
//
//
// Author(s) : Laurent Saboret, Pierre Alliez
#ifndef CGAL_POISSON_RECONSTRUCTION_FUNCTION_H
#define CGAL_POISSON_RECONSTRUCTION_FUNCTION_H
#include <queue>
#include <list>
#include <vector>
#include <deque>
#include <algorithm>
#include <cmath>
#include <fstream>
#include <CGAL/Reconstruction_triangulation_3.h>
#include <CGAL/spatial_sort.h>
#include <CGAL/taucs_solver.h>
#include <CGAL/k_nearest_neighbor.h>
#include <CGAL/centroid.h>
#include <CGAL/surface_reconstruction_points_assertions.h>
#include <CGAL/Memory_sizer.h>
#include <CGAL/Peak_memory_sizer.h>
#include <CGAL/poisson_refine_triangulation.h>
CGAL_BEGIN_NAMESPACE
// functor for priority queue
template<class Candidate>
struct less // read more priority
{
bool operator()(const Candidate& c1,
const Candidate& c2) const
{
return (c1.score() < c2.score());
}
};
// functor for priority queue
template<class Candidate>
struct more // read more priority
{
bool operator()(const Candidate& c1,
const Candidate& c2) const
{
return (c1.score() > c2.score());
}
};
template <class Handle, class Point>
class Candidate
{
private:
Handle m_v0;
Handle m_v1;
Handle m_v2;
Handle m_v3;
float m_score;
public:
Candidate(Handle v0,
Handle v1,
Handle v2,
Handle v3,
float score)
{
m_v0 = v0;
m_v1 = v1;
m_v2 = v2;
m_v3 = v3;
m_score = score;
}
~Candidate() {}
public:
float score() const { return m_score; }
float& score() { return m_score; }
Handle v0() { return m_v0; }
Handle v1() { return m_v1; }
Handle v2() { return m_v2; }
Handle v3() { return m_v3; }
};
/// Poisson_reconstruction_function computes an indicator function f() piecewise-linear
/// over the tetrahedra. We solve the Poisson equation
/// Laplacian(f) = divergent(normals field) at each vertex
/// of the triangulation via the TAUCS sparse linear solver.
/// One vertex outside of the surface will be constrained to a value of 0.0.
///
/// @heading Is Model for the Concepts:
/// Model of the 'ImplicitFunction' concept.
///
/// @heading Parameters:
/// @param Gt Geometric traits class
/// @param ReconstructionTriangulation_3 3D Delaunay triangulation,
/// model of ReconstructionTriangulation_3 concept.
template <class Gt, class ReconstructionTriangulation_3>
class Poisson_reconstruction_function
{
// Public types
public:
typedef ReconstructionTriangulation_3 Triangulation;
typedef Gt Geom_traits; ///< Kernel's geometric traits
typedef typename Geom_traits::FT FT;
typedef typename Geom_traits::Point_3 Point;
typedef typename Geom_traits::Vector_3 Vector;
typedef typename Geom_traits::Iso_cuboid_3 Iso_cuboid;
typedef typename Geom_traits::Sphere_3 Sphere;
typedef typename Triangulation::Point_with_normal Point_with_normal;
///< Model of PointWithNormal_3
typedef typename Point_with_normal::Normal Normal; ///< Model of Kernel::Vector_3 concept.
// Private types
private:
// Repeat ReconstructionTriangulation_3 types
typedef typename Triangulation::Triangulation_data_structure Triangulation_data_structure;
typedef typename Geom_traits::Ray_3 Ray;
typedef typename Geom_traits::Plane_3 Plane;
typedef typename Geom_traits::Segment_3 Segment;
typedef typename Geom_traits::Triangle_3 Triangle;
typedef typename Geom_traits::Tetrahedron_3 Tetrahedron;
typedef typename Triangulation::Cell_handle Cell_handle;
typedef typename Triangulation::Vertex_handle Vertex_handle;
typedef typename Triangulation::Cell Cell;
typedef typename Triangulation::Vertex Vertex;
typedef typename Triangulation::Facet Facet;
typedef typename Triangulation::Edge Edge;
typedef typename Triangulation::Cell_circulator Cell_circulator;
typedef typename Triangulation::Facet_circulator Facet_circulator;
typedef typename Triangulation::Cell_iterator Cell_iterator;
typedef typename Triangulation::Facet_iterator Facet_iterator;
typedef typename Triangulation::Edge_iterator Edge_iterator;
typedef typename Triangulation::Vertex_iterator Vertex_iterator;
typedef typename Triangulation::Point_iterator Point_iterator;
typedef typename Triangulation::Finite_vertices_iterator Finite_vertices_iterator;
typedef typename Triangulation::Finite_cells_iterator Finite_cells_iterator;
typedef typename Triangulation::Finite_facets_iterator Finite_facets_iterator;
typedef typename Triangulation::Finite_edges_iterator Finite_edges_iterator;
typedef typename Triangulation::All_cells_iterator All_cells_iterator;
typedef typename Triangulation::Locate_type Locate_type;
// neighbor search
typedef typename CGAL::K_nearest_neighbor<Geom_traits,Vertex_handle> K_nearest_neighbor;
typedef typename CGAL::Point_vertex_handle_3<Vertex_handle> Point_vertex_handle_3;
// TAUCS solver
typedef Taucs_solver<double> Solver;
typedef std::vector<double> Sparse_vector;
// Data members.
// Warning: the Surface Mesh Generation package makes copies of implicit functions,
// thus this class must be lightweight and stateless.
private:
Triangulation& m_tr; // f() is pre-computed on vertices of m_tr by solving
// the Poisson equation Laplacian(f) = divergent(normals field).
// contouring and meshing
Point m_sink; // Point with the minimum value of f()
mutable Cell_handle m_hint; // last cell found = hint for next search
// Public methods
public:
/// Creates a scalar function from a set of oriented points.
/// Inserts the iterator range [first, beyond) into the triangulation 'tr',
/// refines it and solves for a piecewise linear scalar function
/// which gradient best matches the input normals.
///
/// If 'tr' is empty, this method creates an empty implicit function.
///
/// @param tr ReconstructionTriangulation_3 base of the Poisson indicator function.
Poisson_reconstruction_function(ReconstructionTriangulation_3& tr)
: m_tr(tr)
{
}
/// Creates a scalar function from a set of oriented points.
/// Inserts the iterator range [first, beyond) into the triangulation 'tr',
/// refines it and solves for a piecewise linear scalar function
/// which gradient best matches the input normals.
///
/// @commentheading Precondition:
/// InputIterator value_type must be convertible to Point_with_normal.
///
/// @param tr ReconstructionTriangulation_3 base of the Poisson indicator function.
/// @param first Iterator over first point to add to 'tr'.
/// @param beyond Past-the-end iterator to add to 'tr'.
template < class InputIterator >
Poisson_reconstruction_function(ReconstructionTriangulation_3& tr,
InputIterator first, InputIterator beyond)
: m_tr(tr)
{
insert(first, beyond);
}
/// Insert points.
///
/// @commentheading Precondition:
/// InputIterator value_type must be convertible to Point_with_normal.
///
/// @param first Iterator over first point to add to 'tr'.
/// @param beyond Past-the-end iterator to add to 'tr'.
/// @return the number of inserted points.
template < class InputIterator >
int insert(InputIterator first, InputIterator beyond)
{
return m_tr.insert(first, beyond);
}
/// Remove all points.
void clear()
{
m_tr.clear();
}
/// Get embedded triangulation.
ReconstructionTriangulation_3& triangulation()
{
return m_tr;
}
const ReconstructionTriangulation_3& triangulation() const
{
return m_tr;
}
/// Returns a bounding box of the inferred surface.
Iso_cuboid bounding_box() const
{
return m_tr.input_points_bounding_box();
}
/// Returns a sphere bounding the inferred surface.
Sphere bounding_sphere() const
{
return m_tr.input_points_bounding_sphere();
}
/// Get the region of interest, ignoring the outliers.
/// This method is used to define the OpenGL arcball sphere.
Sphere region_of_interest() const
{
// A good candidate is a sphere containing the dense region of the point cloud:
// - center point is barycenter
// - Radius is 2 * standard deviation
Point barycenter = m_tr.barycenter();
FT radius = 2.f * (FT)m_tr.diameter_standard_deviation();
return Sphere(barycenter, radius*radius);
}
/// The function compute_implicit_function() must be called
/// after each insertion of oriented points.
/// It computes the piecewise linear scalar function 'f' by:
/// - applying Delaunay refinement.
/// - solving for 'f' at each vertex of the triangulation with a sparse linear solver.
/// - shifting and orienting 'f' such that 'f=0' at all input points and 'f<0' inside the inferred surface.
///
/// Returns false if the linear solver fails.
bool compute_implicit_function()
{
CGAL::Timer task_timer; task_timer.start();
CGAL_TRACE_STREAM << "Delaunay refinement...\n";
// Delaunay refinement
const FT radius_edge_ratio_bound = 2.5;
const unsigned int max_vertices = (unsigned int)1e7; // max 10M vertices
const FT enlarge_ratio = 1.5;
const FT size = sqrt(bounding_sphere().squared_radius()); // get triangulation's radius
const FT cell_radius_bound = size/5.; // large
unsigned int nb_vertices_added = delaunay_refinement(radius_edge_ratio_bound,cell_radius_bound,max_vertices,enlarge_ratio);
// Print status
CGAL_TRACE_STREAM << "Delaunay refinement: " << "added " << nb_vertices_added << " Steiner points, "
<< task_timer.time() << " seconds, "
<< (CGAL::Memory_sizer().virtual_size()>>20) << " Mb allocated"
<< std::endl;
task_timer.reset();
// Smooth normals field.
// Commented out as it shrinks the reconstructed model.
//extrapolate_normals();
CGAL_TRACE_STREAM << "Solve Poisson equation...\n";
// Compute the Poisson indicator function f()
// at each vertex of the triangulation.
double lambda = 0.1;
double duration_assembly, duration_factorization, duration_solve;
if (!solve_poisson(lambda, &duration_assembly, &duration_factorization, &duration_solve))
{
std::cerr << "Error: cannot solve Poisson equation" << std::endl;
return false;
}
// Shift and orient f() such that:
// - f() = 0 on the input points,
// - f() < 0 inside the surface.
set_contouring_value(median_value_at_input_vertices());
// Print status
CGAL_TRACE_STREAM << "Solve Poisson equation: " << task_timer.time() << " seconds, "
<< (CGAL::Memory_sizer().virtual_size()>>20) << " Mb allocated"
<< std::endl;
task_timer.reset();
return true;
}
//Calculate and store average spacing at each input point
void average_spacing_avg_knn_sq_distance_3()
{
Finite_vertices_iterator v;
for(v = m_tr.finite_vertices_begin(); v != m_tr.finite_vertices_end(); v++)
{
FT sq_distance = 0.0;
int counter = 0;
std::vector<Vertex_handle> v_neighbors;
m_tr.incident_vertices(v,std::back_inserter(v_neighbors));
typename std::vector<Vertex_handle>::iterator it;
for(it = v_neighbors.begin(); it != v_neighbors.end(); it++)
{
sq_distance = sq_distance + distance(*it,v)*distance(*it,v);
counter++;
}
v->average_spacing() = std::sqrt(sq_distance/counter);
}
}
/// Delaunay refinement (break bad tetrahedra, where
/// bad means badly shaped or too big). The normal of
/// Steiner points is set to zero.
/// Return the number of vertices inserted.
unsigned int delaunay_refinement(FT radius_edge_ratio_bound, ///< radius edge ratio bound (ignored if zero)
FT cell_radius_bound, ///< cell radius bound (ignored if zero)
unsigned int max_vertices, ///< number of vertices bound
FT enlarge_ratio) ///< bounding box enlarge ratio
{
CGAL_TRACE("Call delaunay_refinement(radius_edge_ratio_bound=%lf, cell_radius_bound=%lf, max_vertices=%u, enlarge_ratio=%lf)\n",
radius_edge_ratio_bound, cell_radius_bound, max_vertices, enlarge_ratio);
#define DELAUNAY_REFINEMENT_USE_BOUNDING_BOX
#ifdef DELAUNAY_REFINEMENT_USE_BOUNDING_BOX
Iso_cuboid enlarged_bbox = enlarged_bounding_box(enlarge_ratio);
unsigned int nb_vertices_added = poisson_refine_triangulation(m_tr,radius_edge_ratio_bound,cell_radius_bound,max_vertices,enlarged_bbox);
#else
Sphere enlarged_bbox = enlarged_bounding_sphere(enlarge_ratio);
unsigned int nb_vertices_added = poisson_refine_triangulation(m_tr,radius_edge_ratio_bound,cell_radius_bound,max_vertices,enlarged_bbox);
#endif
m_tr.invalidate_bounds();
CGAL_TRACE("End of delaunay_refinement()\n");
return nb_vertices_added;
}
unsigned int delaunay_refinement_shell(FT size_shell,
FT sizing,
unsigned int max_vertices)
{
// make parameters relative to size
Sphere bounding_sphere = m_tr.bounding_sphere();
FT size = sqrt(bounding_sphere.squared_radius());
size_shell *= size;
sizing *= size;
// neighbor search
K_nearest_neighbor nn_search;
init_nn_search_shell(nn_search);
typedef typename CGAL::Candidate<Vertex_handle,Point> Candidate;
typedef typename std::priority_queue<Candidate,
std::vector<Candidate>,
more<Candidate> > PQueue;
// push all cells to the queue
PQueue queue;
Finite_cells_iterator c;
for(c = m_tr.finite_cells_begin();
c != m_tr.finite_cells_end();
c++)
{
Point p;
FT size = 0.0;
if(is_refinable(c,nn_search,size_shell,sizing,size,p))
{
Vertex_handle v0 = c->vertex(0);
Vertex_handle v1 = c->vertex(1);
Vertex_handle v2 = c->vertex(2);
Vertex_handle v3 = c->vertex(3);
queue.push(Candidate(v0,v1,v2,v3,(float)size));
}
}
unsigned int nb = 0;
while(!queue.empty())
{
Candidate candidate = queue.top();
queue.pop();
Vertex_handle v0 = candidate.v0();
Vertex_handle v1 = candidate.v1();
Vertex_handle v2 = candidate.v2();
Vertex_handle v3 = candidate.v3();
Cell_handle cell = NULL;
if(m_tr.is_cell(v0,v1,v2,v3,cell))
{
Point circumcenter = m_tr.dual(cell);
Vertex_handle v = m_tr.insert(circumcenter, Triangulation::STEINER);
if(nb++ > max_vertices)
return nb; // premature ending
// iterate over incident cells and feed queue
std::vector<Cell_handle> cells;
m_tr.incident_cells(v,std::back_inserter(cells));
typename std::vector<Cell_handle>::iterator it;
for(it = cells.begin();
it != cells.end();
it++)
{
Cell_handle c = *it;
if(m_tr.is_infinite(c))
continue;
Point p;
FT size = 0.0;
if(is_refinable(c,nn_search,size_shell,sizing,size,p))
{
Vertex_handle v0 = c->vertex(0);
Vertex_handle v1 = c->vertex(1);
Vertex_handle v2 = c->vertex(2);
Vertex_handle v3 = c->vertex(3);
queue.push(Candidate(v0,v1,v2,v3,(float)size));
}
}
}
}
return nb;
}
/// Extrapolate the normals field:
/// compute null normals by averaging neighbor normals.
void extrapolate_normals()
{
// Compute extrapolated normals and store them in extrapolated_normals[]
std::map<Vertex_handle,Normal> extrapolated_normals; // vector + orientation
Finite_vertices_iterator v;
for(v = m_tr.finite_vertices_begin(); v != m_tr.finite_vertices_end(); v++)
{
if(v->normal() != CGAL::NULL_VECTOR)
continue;
Vector normal = CGAL::NULL_VECTOR; // normal vector to compute
std::vector<Vertex_handle> vertices;
m_tr.incident_vertices(v,std::back_inserter(vertices));
for(typename std::vector<Vertex_handle>::iterator it = vertices.begin();
it != vertices.end();
it++)
{
Vertex_handle nv = *it;
normal = normal + nv->normal();
}
FT sq_norm = normal * normal;
if(sq_norm > 0.0)
normal = normal / std::sqrt(sq_norm);
extrapolated_normals[v] = Normal(normal);
}
// set normals
for(v = m_tr.finite_vertices_begin(); v != m_tr.finite_vertices_end(); v++)
{
if(v->normal() != CGAL::NULL_VECTOR)
continue;
typename std::map<Vertex_handle,Normal>::iterator it = extrapolated_normals.find(v);
if(it != extrapolated_normals.end())
v->normal() = extrapolated_normals[v];
}
}
FT gaussian_function( FT sigma , FT distance)
{
FT answer = (1 / std::sqrt(2 * 3.14)) * std::exp(-1 * distance * distance /(2 * sigma * sigma));
return answer;
}
/// Extrapolate the normals field.
/// Return the number of normals computed.
int extrapolate_normals_using_gaussian_kernel()
{
int counter = 0;
Finite_vertices_iterator v;
for(v = m_tr.finite_vertices_begin(); v != m_tr.finite_vertices_end(); v++)
{
if(v->type() == Triangulation::INPUT)
{
FT limit_distance = v->average_spacing();
std::stack<Vertex_handle> vertices; // use to walk in 3D Delaunay
vertices.push(v);
while(!vertices.empty())
{
Vertex_handle v_cur = vertices.top();
vertices.pop();
FT distance_cur = distance(v,v_cur);
if (distance_cur > limit_distance)
continue;
if (v_cur->type() != Triangulation::INPUT)
{
FT gf = gaussian_function(limit_distance,distance_cur);
v_cur->normal() = v_cur->normal() + gf * v->normal();
}
// get incident_vertices
std::vector<Vertex_handle> v_neighbors;
m_tr.incident_vertices(v_cur,std::back_inserter(v_neighbors));
typename std::vector<Vertex_handle>::iterator it;
for(it = v_neighbors.begin(); it != v_neighbors.end(); it++)
{
Vertex_handle nv = *it;
int tag = nv->tag();
int index = v_cur->index();
if (tag != index)
{
vertices.push(nv);
nv->tag() = index;
}
}
}
}
}
for(v = m_tr.finite_vertices_begin(); v != m_tr.finite_vertices_end(); v++)
{
if(v->type() != Triangulation::INPUT )
{
FT sq_norm = std::sqrt(v->normal()*v->normal());
if(sq_norm > 0.0)
{
v->normal() = v->normal() / sq_norm;
counter++;
}
}
}
return counter;
}
/// Poisson reconstruction.
/// Return false on error.
bool solve_poisson(double lambda,
double* duration_assembly,
double* duration_factorization,
double* duration_solve,
bool is_normalized = false)
{
CGAL_TRACE("Call solve_poisson()\n");
double time_init = clock();
*duration_assembly = 0.0;
*duration_factorization = 0.0;
*duration_solve = 0.0;
long old_max_memory = CGAL::Peak_memory_sizer().peak_virtual_size();
CGAL_TRACE(" %ld Mb allocated, largest free memory block=%ld Mb, #blocks over 100 Mb=%ld\n",
long(CGAL::Memory_sizer().virtual_size())>>20,
long(CGAL::Peak_memory_sizer().largest_free_block()>>20),
long(CGAL::Peak_memory_sizer().count_free_memory_blocks(100*1048576)));
CGAL_TRACE(" Create matrix...\n");
// get #variables
unsigned int nb_variables = m_tr.index_unconstrained_vertices();
// at least one vertex must be constrained
if(nb_variables == m_tr.number_of_vertices())
{
constrain_one_vertex_on_convex_hull();
nb_variables = m_tr.index_unconstrained_vertices();
}
// Assemble linear system A*X=B
Solver solver(nb_variables, 9); // average non null elements per line = 8.3
Sparse_vector X(nb_variables);
Sparse_vector B(nb_variables);
Finite_vertices_iterator v;
for(v = m_tr.finite_vertices_begin();
v != m_tr.finite_vertices_end();
v++)
{
if(!v->constrained())
{
B[v->index()] = is_normalized ? div_normalized(v)
: div(v); // rhs -> divergent
assemble_poisson_row(solver,v,B,lambda);
}
}
*duration_assembly = (clock() - time_init)/CLOCKS_PER_SEC;
CGAL_TRACE(" Create matrix: done (%.2lf s)\n", *duration_assembly);
/*
time_init = clock();
if(!solver.solve_conjugate_gradient(B,X,10000,1e-15))
return false;
*duration_solve = (clock() - time_init)/CLOCKS_PER_SEC;
*/
CGAL_TRACE(" %ld Mb allocated, largest free memory block=%ld Mb, #blocks over 100 Mb=%ld\n",
long(CGAL::Memory_sizer().virtual_size())>>20,
long(CGAL::Peak_memory_sizer().largest_free_block()>>20),
long(CGAL::Peak_memory_sizer().count_free_memory_blocks(100*1048576)));
CGAL_TRACE(" Choleschy factorization...\n");
// Choleschy factorization M = L L^T
time_init = clock();
if(!solver.factorize_ooc())
return false;
*duration_factorization = (clock() - time_init)/CLOCKS_PER_SEC;
CGAL_TRACE(" Choleschy factorization: done (%.2lf s)\n", *duration_factorization);
// Print peak memory (Windows only)
long max_memory = CGAL::Peak_memory_sizer().peak_virtual_size();
if (max_memory > old_max_memory)
CGAL_TRACE(" Max allocation = %ld Mb\n", max_memory>>20);
CGAL_TRACE(" %ld Mb allocated, largest free memory block=%ld Mb, #blocks over 100 Mb=%ld\n",
long(CGAL::Memory_sizer().virtual_size())>>20,
long(CGAL::Peak_memory_sizer().largest_free_block()>>20),
long(CGAL::Peak_memory_sizer().count_free_memory_blocks(100*1048576)));
CGAL_TRACE(" Direct solve...\n");
// Direct solve by forward and backward substitution
time_init = clock();
if(!solver.solve_ooc(B,X))
return false;
*duration_solve = (clock() - time_init)/CLOCKS_PER_SEC;
CGAL_TRACE(" Direct solve: done (%.2lf s)\n", *duration_solve);
/*
// Choleschy factorization M = L L^T
time_init = clock();
if(!solver.factorize(true))
return false;
*duration_factorization = (clock() - time_init)/CLOCKS_PER_SEC;
// Direct solve by forward and backward substitution
time_init = clock();
if(!solver.solve(B,X,1))
return false;
*duration_solve = (clock() - time_init)/CLOCKS_PER_SEC;
*/
CGAL_TRACE(" Choleschy factorization + solve: done (%.2lf s)\n", *duration_factorization + *duration_solve);
// copy function's values to vertices
unsigned int index = 0;
for (v = m_tr.finite_vertices_begin(); v != m_tr.finite_vertices_end(); v++)
if(!v->constrained())
v->f() = X[index++];
CGAL_TRACE(" %ld Mb allocated, largest free memory block=%ld Mb, #blocks over 100 Mb=%ld\n",
long(CGAL::Memory_sizer().virtual_size())>>20,
long(CGAL::Peak_memory_sizer().largest_free_block()>>20),
long(CGAL::Peak_memory_sizer().count_free_memory_blocks(100*1048576)));
CGAL_TRACE("End of solve_poisson()\n");
return true;
}
void SaveAsMeshFile()
{
std::ofstream os("function.mesh");
Finite_vertices_iterator v;
int counter = 0;
for(v = m_tr.finite_vertices_begin();
v != m_tr.finite_vertices_end();
v++)
{
Point& p = v->point();
if (std::abs(f(p) - 0) < 0.001)
counter++;
}
os << "MeshVersionFormatted 1\n"
<< "Dimension\n"
<< "3 \n\n"
<< "Vertices\n"
<< counter << " \n";
for(v = m_tr.finite_vertices_begin();
v != m_tr.finite_vertices_end();
v++)
{
Point& p = v->point();
if (std::abs(f(p) - 0) < 0.01)
os << p.x() << " " << p.y() << " " << p.z() << " " << 0 << std::endl;
}
os << "\n" << "End\n";
os.close();
}
/// Shift and orient the implicit function such that:
/// - the implicit function = 0 for points / f() = contouring_value,
/// - the implicit function < 0 inside the surface.
///
/// Return the minimum value of the implicit function.
FT set_contouring_value(FT contouring_value)
{
// median value set to 0.0
shift_f(-contouring_value);
// check value on convex hull (should be positive)
Vertex_handle v = any_vertex_on_convex_hull();
if(v->f() < 0.0)
flip_f();
// Update m_sink
FT sink_value = find_sink();
return sink_value;
}
/// Evaluates the implicit function at a given 3D query point.
FT f(const Point& p) const
{
m_hint = m_tr.locate(p,m_hint);
if(m_hint == NULL)
return 1e38;
if(m_tr.is_infinite(m_hint))
return 1e38;
FT a,b,c,d;
barycentric_coordinates(p,m_hint,a,b,c,d);
return a * m_hint->vertex(0)->f() +
b * m_hint->vertex(1)->f() +
c * m_hint->vertex(2)->f() +
d * m_hint->vertex(3)->f();
}
/// Evaluates the implicit function at a given 3D query point.
/// ('ImplicitFunction' interface)
FT operator()(const Point& p) const
{
return f(p);
}
/// Returns a point located inside the inferred surface.
Point get_inner_point() const
{
// Get point / the implicit function is minimum
return m_sink;
}
/// Get average value of the implicit function over input vertices.
FT average_value_at_input_vertices() const
{
FT sum = 0.0;
unsigned int nb = 0;
Finite_vertices_iterator v;
for(v = m_tr.finite_vertices_begin();
v != m_tr.finite_vertices_end();
v++)
{
if(v->type() == Triangulation::INPUT)
{
sum += v->f();
nb++;
}
}
if(nb > 0)
return sum / (FT)nb;
else
{
std::cerr << "Contouring: no input points\n";
return (FT)0.0;
}
}
/// Get median value of the implicit function over input vertices.
FT median_value_at_input_vertices() const
{
std::deque<FT> values;
Finite_vertices_iterator v;
for(v = m_tr.finite_vertices_begin();
v != m_tr.finite_vertices_end();
v++)
if(v->type() == Triangulation::INPUT)
values.push_back(v->f());
int size = values.size();
if(size == 0)
{
std::cerr << "Contouring: no input points\n";
return 0.0;
}
std::sort(values.begin(),values.end());
int index = size/2;
// return values[size/2];
return 0.5 * (values[index] + values[index+1]); // avoids singular cases
}
/// Get min value of the implicit function over input vertices.
FT min_value_at_input_vertices() const
{
FT min_value = 1e38;
Finite_vertices_iterator v;
for(v = m_tr.finite_vertices_begin();
v != m_tr.finite_vertices_end();
v++)
{
if(v->type() == Triangulation::INPUT)
min_value = (std::min)(min_value, v->f());
}
if (m_tr.number_of_vertices() > 0)
{
return min_value;
}
else
{
std::cerr << "Contouring: no input points\n";
return (FT)0.0;
}
}
/// Get max value of the implicit function over input vertices.
FT max_value_at_input_vertices() const
{
FT max_value = -1e38;
Finite_vertices_iterator v;
for(v = m_tr.finite_vertices_begin();
v != m_tr.finite_vertices_end();
v++)
{
if(v->type() == Triangulation::INPUT)
max_value = (std::max)(max_value, v->f());
}
if (m_tr.number_of_vertices() > 0)
{
return max_value;
}
else
{
std::cerr << "Contouring: no input points\n";
return (FT)0.0;
}
}
/// Get median value of the implicit function over convex hull vertices.
FT median_value_at_convex_hull() const
{
// Get convex hull vertices
std::vector<Vertex_handle> convex_hull_vertices;
m_tr.incident_vertices(m_tr.infinite_vertex(),std::back_inserter(convex_hull_vertices));
// Get values of the implicit function over convex hull vertices
std::deque<FT> values;
typename std::vector<Vertex_handle>::iterator it;
for(it = convex_hull_vertices.begin();
it != convex_hull_vertices.end();
it++)
{
Vertex_handle v = *it;
values.push_back(v->f());
}
int size = values.size();
if(size == 0)
{
std::cerr << "Contouring: no input points\n";
return 0.0;
}
std::sort(values.begin(),values.end());
int index = size/2;
// return values[size/2];
return 0.5 * (values[index] + values[index+1]); // avoids singular cases
}
/// Get average value of the implicit function over convex hull vertices.
FT average_value_at_convex_hull() const
{
std::vector<Vertex_handle> convex_hull_vertices;
m_tr.incident_vertices(m_tr.infinite_vertex(),std::back_inserter(convex_hull_vertices));
FT sum = 0.0;
unsigned int nb = 0;
typename std::vector<Vertex_handle>::iterator it;
for(it = convex_hull_vertices.begin();
it != convex_hull_vertices.end();
it++,nb++)
{
Vertex_handle v = *it;
sum += v->f();
}
if(nb != 0)
return sum / (FT)nb;
else
return 0.0;
}
// Private methods:
private:
// PA: todo change type (FT)
// check if this is in CGAL already
void barycentric_coordinates(const Point& p,
Cell_handle cell,
double& a,
double& b,
double& c,
double& d) const
{
const Point& pa = cell->vertex(0)->point();
const Point& pb = cell->vertex(1)->point();
const Point& pc = cell->vertex(2)->point();
const Point& pd = cell->vertex(3)->point();
Tetrahedron ta(pb,pc,pd,p);
Tetrahedron tb(pa,pc,pd,p);
Tetrahedron tc(pb,pa,pd,p);
Tetrahedron td(pb,pc,pa,p);
Tetrahedron tet(pa,pb,pc,pd);
double v = tet.volume();
a = std::fabs(ta.volume() / v);
b = std::fabs(tb.volume() / v);
c = std::fabs(tc.volume() / v);
d = std::fabs(td.volume() / v);
}
FT distance(Vertex_handle v1, Vertex_handle v2) const
{
const Point& a = v1->point();
const Point& b = v2->point();
return std::sqrt(CGAL::squared_distance(a,b));
}
FT find_sink()
{
m_sink = CGAL::ORIGIN;
FT min_f = 1e38;
Finite_vertices_iterator v;
for(v = m_tr.finite_vertices_begin();
v != m_tr.finite_vertices_end();
v++)
{
if(v->f() < min_f)
{
m_sink = v->point();
min_f = v->f();
}
}
return min_f;
}
void shift_f(const FT shift)
{
Finite_vertices_iterator v;
for(v = m_tr.finite_vertices_begin();
v != m_tr.finite_vertices_end();
v++)
v->f() += shift;
}
void flip_f()
{
Finite_vertices_iterator v;
for(v = m_tr.finite_vertices_begin();
v != m_tr.finite_vertices_end();
v++)
v->f() = -v->f();
}
Vertex_handle any_vertex_on_convex_hull()
{
// TODO: return NULL if none and assert
std::vector<Vertex_handle> vertices;
m_tr.incident_vertices(m_tr.infinite_vertex(),std::back_inserter(vertices));
typename std::vector<Vertex_handle>::iterator it = vertices.begin();
return *it;
}
void constrain_one_vertex_on_convex_hull(const FT value = 0.0)
{
Vertex_handle v = any_vertex_on_convex_hull();
v->constrained() = true;
v->f() = value;
}
//void constrain_input_vertices_on_convex_hull(const FT value = 0.0)
//{
// for(Finite_vertices_iterator v = m_tr.finite_vertices_begin();
// v != m_tr.finite_vertices_end();
// v++)
// if (v->type() == Triangulation::INPUT)
// {
// v->constrained() = true;
// v->f() = value;
// }
//}
// divergent
FT div(Vertex_handle v)
{
std::vector<Cell_handle> cells;
m_tr.incident_cells(v,std::back_inserter(cells));
if(cells.size() == 0)
return 0.0;
FT div = 0.0;
typename std::vector<Cell_handle>::iterator it;
for(it = cells.begin(); it != cells.end(); it++)
{
Cell_handle cell = *it;
if(m_tr.is_infinite(cell))
continue;
// compute average normal per cell
Vector n = cell_normal(cell);
// zero normal - no need to compute anything else
if(n == CGAL::NULL_VECTOR)
continue;
// compute n'
int index = cell->index(v);
const Point& a = cell->vertex((index+1)%4)->point();
const Point& b = cell->vertex((index+2)%4)->point();
const Point& c = cell->vertex((index+3)%4)->point();
Vector nn = (index%2==0) ? CGAL::cross_product(b-a,c-a) : CGAL::cross_product(c-a,b-a);
nn = nn / std::sqrt(nn*nn); // normalize
Triangle face(a,b,c);
FT area = std::sqrt(face.squared_area());
div += n * nn * area;
}
return div;
}
FT div_normalized(Vertex_handle v)
{
std::vector<Cell_handle> cells;
m_tr.incident_cells(v,std::back_inserter(cells));
if(cells.size() == 0)
return 0.0;
FT length = 100000;
int counter = 0;
FT div = 0.0;
typename std::vector<Cell_handle>::iterator it;
for(it = cells.begin(); it != cells.end(); it++)
{
Cell_handle cell = *it;
if(m_tr.is_infinite(cell))
continue;
// compute average normal per cell
Vector n = cell_normal(cell);
// zero normal - no need to compute anything else
if(n == CGAL::NULL_VECTOR)
continue;
// compute n'
int index = cell->index(v);
const Point& x = cell->vertex(index)->point();
const Point& a = cell->vertex((index+1)%4)->point();
const Point& b = cell->vertex((index+2)%4)->point();
const Point& c = cell->vertex((index+3)%4)->point();
Vector nn = (index%2==0) ? CGAL::cross_product(b-a,c-a) : CGAL::cross_product(c-a,b-a);
nn = nn / std::sqrt(nn*nn); // normalize
Vector p = a - x;
Vector q = b - x;
Vector r = c - x;
FT p_n = std::sqrt(p*p);
FT q_n = std::sqrt(q*q);
FT r_n = std::sqrt(r*r);
FT solid_angle = p*(CGAL::cross_product(q,r));
solid_angle = std::abs(solid_angle * 1.0 / (p_n*q_n*r_n + (p*q)*r_n + (q*r)*p_n + (r*p)*q_n));
Triangle face(a,b,c);
FT area = std::sqrt(face.squared_area());
length = std::sqrt((x-a)*(x-a)) + std::sqrt((x-b)*(x-b)) + std::sqrt((x-c)*(x-c));
counter++;
div += n * nn * area * 3 / length ;
}
return div;
}
FT mesh_size(Vertex_handle v)
{
std::vector<Cell_handle> cells;
int counter = 0;
FT length_total = 100000.0;
m_tr.incident_cells(v,std::back_inserter(cells));
if(cells.size() == 0)
return 0.0;
typename std::vector<Cell_handle>::iterator it;
for(it = cells.begin(); it != cells.end(); it++)
{
Cell_handle cell = *it;
if(m_tr.is_infinite(cell))
continue;
int index = cell->index(v);
const Point& x = cell->vertex(index)->point();
const Point& a = cell->vertex((index+1)%4)->point();
const Point& b = cell->vertex((index+2)%4)->point();
const Point& c = cell->vertex((index+3)%4)->point();
if (length_total > std::sqrt((x-a)*(x-a)) + std::sqrt((x-b)*(x-b)) + std::sqrt((x-c)*(x-c)))
length_total = std::sqrt((x-a)*(x-a)) + std::sqrt((x-b)*(x-b)) + std::sqrt((x-c)*(x-c));
counter++;
}
return length_total / 3 ;
}
Vector cell_normal(Cell_handle cell)
{
const Vector& n0 = cell->vertex(0)->normal();
const Vector& n1 = cell->vertex(1)->normal();
const Vector& n2 = cell->vertex(2)->normal();
const Vector& n3 = cell->vertex(3)->normal();
Vector n = n0 + n1 + n2 + n3;
FT sq_norm = n*n;
if(sq_norm != 0.0)
return n / std::sqrt(sq_norm); // normalize
else
return CGAL::NULL_VECTOR;
}
// cotan formula as area(voronoi face) / len(primal edge)
FT cotan_geometric(Edge& edge)
{
Cell_handle cell = edge.first;
Vertex_handle vi = cell->vertex(edge.second);
Vertex_handle vj = cell->vertex(edge.third);
// primal edge
const Point& pi = vi->point();
const Point& pj = vj->point();
Vector primal = pj - pi;
FT len_primal = std::sqrt(primal * primal);
return area_voronoi_face(edge) / len_primal;
}
FT area_normal_ratio(Cell_handle cell, Edge& edge)
{
Vertex_handle vi = cell->vertex(edge.second);
Vertex_handle vj = cell->vertex(edge.third);
int index1 = cell->index(vi);
int index2 = cell->index(vj);
Point& p_vi = cell->vertex(index1)->point();
Point& p_vj = cell->vertex(index2)->point();
Point& a = cell->vertex(index1)->point();
Point& c = cell->vertex(index1)->point();
if ((index1+1)%4 == index2)
{
a = cell->vertex((index1+2)%4)->point();
c = cell->vertex((index1+3)%4)->point();
}
if ((index1+2)%4 == index2)
{
a = cell->vertex((index1+1)%4)->point();
c = cell->vertex((index1+3)%4)->point();
}
if ((index1+3)%4 == index2)
{
a = cell->vertex((index1+1)%4)->point();
c = cell->vertex((index1+2)%4)->point();
}
Triangle face(p_vi,a,c);
FT area = std::sqrt(face.squared_area());
Vector x = p_vj - a;
Vector n1 = CGAL::cross_product(a-c,p_vi-c);
FT sq_norm1 = std::sqrt(n1*n1);
FT normal = std::abs((x*n1)/sq_norm1);
Vector n2 = CGAL::cross_product(a-c,p_vj-c);
FT sq_norm2 = std::sqrt(n2*n2);
FT cos = std::abs(n1 * n2 / (sq_norm1 * sq_norm2));
return (area * cos / normal);
}
FT cotan_FEM(Edge& edge)
{
FT answer = 0.0;
Cell_circulator circ = m_tr.incident_cells(edge);
Cell_circulator done = circ;
do
{
Cell_handle cell = circ;
if(!m_tr.is_infinite(cell))
{
answer = answer + area_normal_ratio(cell,edge);
}
else return cotan_geometric(edge);
}
while ( circ != done);
return answer;
}
// spin around edge
// return area(voronoi face)
FT area_voronoi_face(Edge& edge)
{
// circulate around edge
Cell_circulator circ = m_tr.incident_cells(edge);
Cell_circulator done = circ;
std::vector<Point> voronoi_points;
do
{
Cell_handle cell = circ;
if(!m_tr.is_infinite(cell))
voronoi_points.push_back(m_tr.dual(cell));
else // one infinite tet, switch to another calculation
return area_voronoi_face_boundary(edge);
circ++;
}
while(circ != done);
if(voronoi_points.size() < 3)
{
CGAL_surface_reconstruction_points_assertion(false);
return 0.0;
}
// sum up areas
FT area = 0.0;
const Point& a = voronoi_points[0];
unsigned int nb_triangles = voronoi_points.size() - 2;
for(unsigned int i=1;i<nb_triangles;i++)
{
const Point& b = voronoi_points[i];
const Point& c = voronoi_points[i+1];
Triangle triangle(a,b,c);
area += std::sqrt(triangle.squared_area());
}
return area;
}
// approximate area when a cell is infinite
FT area_voronoi_face_boundary(Edge& edge)
{
FT area = 0.0;
Vertex_handle vi = edge.first->vertex(edge.second);
Vertex_handle vj = edge.first->vertex(edge.third);
const Point& pi = vi->point();
const Point& pj = vj->point();
Point m = CGAL::midpoint(pi,pj);
// circulate around each incident cell
Cell_circulator circ = m_tr.incident_cells(edge);
Cell_circulator done = circ;
do
{
Cell_handle cell = circ;
if(!m_tr.is_infinite(cell))
{
// circumcenter of cell
Point c = m_tr.dual(cell);
Tetrahedron tet = m_tr.tetrahedron(cell);
int i = cell->index(vi);
int j = cell->index(vj);
int k = -1, l = -1;
other_two_indices(i,j, &k,&l);
Vertex_handle vk = cell->vertex(k);
Vertex_handle vl = cell->vertex(l);
const Point& pk = vk->point();
const Point& pl = vl->point();
// if circumcenter is outside tet
// pick barycenter instead
if(tet.has_on_unbounded_side(c))
{
Point cell_points[4] = {pi,pj,pk,pl};
c = CGAL::centroid(cell_points, cell_points+4);
}
Point ck = CGAL::circumcenter(pi,pj,pk);
Point cl = CGAL::circumcenter(pi,pj,pl);
Triangle mcck(m,m,ck);
Triangle mccl(m,m,cl);
area += std::sqrt(mcck.squared_area());
area += std::sqrt(mccl.squared_area());
}
circ++;
}
while(circ != done);
return area;
}
// Get indices different from i and j
void other_two_indices(int i, int j, int* k, int* l)
{
CGAL_surface_reconstruction_points_assertion(i != j);
bool k_done = false;
bool l_done = false;
for(int index=0;index<4;index++)
{
if(index != i && index != j)
{
if(!k_done)
{
*k = index;
k_done = true;
}
else
{
*l = index;
l_done = true;
}
}
}
CGAL_surface_reconstruction_points_assertion(k_done);
CGAL_surface_reconstruction_points_assertion(l_done);
}
// Assemble vi's row of the linear system A*X=B
void assemble_poisson_row(Solver& solver,
Vertex_handle vi,
Sparse_vector& B,
double lambda)
{
// assemble new row
solver.begin_row();
// for each vertex vj neighbor of vi
std::vector<Vertex_handle> vertices;
m_tr.incident_vertices(vi,std::back_inserter(vertices));
double diagonal = 0.0;
for(typename std::vector<Vertex_handle>::iterator it = vertices.begin();
it != vertices.end();
it++)
{
Vertex_handle vj = *it;
if(m_tr.is_infinite(vj))
continue;
// get corresponding edge
Edge edge = sorted_edge(vi,vj);
// double cij = cotan_FEM(edge);
double cij = cotan_geometric(edge);
if(vj->constrained())
B[vi->index()] -= cij * vj->f(); // change rhs
else
solver.add_value(vj->index(),-cij); // off-diagonal coefficient
diagonal += cij;
}
// diagonal coefficient
if (vi->type() == Triangulation::INPUT)
solver.add_value(vi->index(),diagonal + lambda) ;
else
solver.add_value(vi->index(),diagonal);
// end matrix row
solver.end_row();
}
Edge sorted_edge(Vertex_handle vi,
Vertex_handle vj)
{
int i1 = 0;
int i2 = 0;
Cell_handle cell = NULL;
bool success;
if(vi->index() > vj->index())
success = m_tr.is_edge(vi,vj,cell,i1,i2);
else
success = m_tr.is_edge(vj,vi,cell,i1,i2);
CGAL_surface_reconstruction_points_assertion(success);
return Edge(cell,i1,i2);
}
/// Compute enlarged geometric bounding box of the embedded triangulation.
Iso_cuboid enlarged_bounding_box(FT ratio) const
{
// Get triangulation's bounding box
Iso_cuboid bbox = bounding_box();
// Its center point is:
FT mx = 0.5 * (bbox.xmax() + bbox.xmin());
FT my = 0.5 * (bbox.ymax() + bbox.ymin());
FT mz = 0.5 * (bbox.zmax() + bbox.zmin());
Point c(mx,my,mz);
// Compute enlarged bounding box
FT sx = 0.5 * ratio * (bbox.xmax() - bbox.xmin());
FT sy = 0.5 * ratio * (bbox.ymax() - bbox.ymin());
FT sz = 0.5 * ratio * (bbox.zmax() - bbox.zmin());
Point p(c.x() - sx, c.y() - sy, c.z() - sz);
Point q(c.x() + sx, c.y() + sy, c.z() + sz);
return Iso_cuboid(p,q);
}
/// Compute enlarged geometric bounding sphere of the embedded triangulation.
Sphere enlarged_bounding_sphere(FT ratio) const
{
Sphere bbox = bounding_sphere(); // triangulation's bounding sphere
return Sphere(bbox.center(), bbox.squared_radius() * ratio*ratio);
}
void init_nn_search_shell(K_nearest_neighbor& nn_search)
{
// Instanciate a KD-tree search.
// We have to wrap each input vertex by a Point_vertex_handle_3.
std::deque<Point_vertex_handle_3> kvertices;
for(Finite_vertices_iterator v = m_tr.finite_vertices_begin();
v != m_tr.finite_vertices_end();
v++)
{
if(v->type() != Triangulation::INPUT)
continue;
const Point& p = v->point();
Point_vertex_handle_3 kv(p.x(),p.y(),p.z(),v);
kvertices.push_back(kv);
}
nn_search = K_nearest_neighbor(kvertices.begin(), kvertices.end());
}
bool is_refinable(Cell_handle cell,
K_nearest_neighbor& nn_search,
const FT size_shell,
const FT sizing,
FT& size,
Point& p)
{
size = circumradius(cell);
if(size <= sizing)
return false;
// try circumcenter
p = m_tr.dual(cell);
if(distance_to_input_points(nn_search, p) < size_shell)
return true;
return false;
}
FT distance_to_input_points(K_nearest_neighbor& nn_search, const Point& p)
{
// Get nearest neighbor
std::list<Vertex_handle> nearest_vertices;
nn_search.get_k_nearest_neighbors(p,1,nearest_vertices);
Vertex_handle nv = *nearest_vertices.begin();
if(nv != NULL)
return distance(nv->point(),p);
else
return 0.0; // default
}
FT distance(const Point& a, const Point& b) const
{
return std::sqrt(CGAL::squared_distance(a,b));
}
FT circumradius(Cell_handle c) const
{
Point center = m_tr.dual(c);
const Point& p = c->vertex(0)->point();
return std::sqrt((p-center)*((p-center)));
}
}; // end of Poisson_reconstruction_function
CGAL_END_NAMESPACE
#endif // CGAL_POISSON_RECONSTRUCTION_FUNCTION_H
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