dust3d/third_party/libigl/include/igl/biharmonic_coordinates.cpp

204 lines
5.9 KiB
C++

// This file is part of libigl, a simple c++ geometry processing library.
//
// Copyright (C) 2015 Alec Jacobson <alecjacobson@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla Public License
// v. 2.0. If a copy of the MPL was not distributed with this file, You can
// obtain one at http://mozilla.org/MPL/2.0/.
#include "biharmonic_coordinates.h"
#include "cotmatrix.h"
#include "sum.h"
#include "massmatrix.h"
#include "min_quad_with_fixed.h"
#include "crouzeix_raviart_massmatrix.h"
#include "crouzeix_raviart_cotmatrix.h"
#include "normal_derivative.h"
#include "on_boundary.h"
#include <Eigen/Sparse>
template <
typename DerivedV,
typename DerivedT,
typename SType,
typename DerivedW>
IGL_INLINE bool igl::biharmonic_coordinates(
const Eigen::PlainObjectBase<DerivedV> & V,
const Eigen::PlainObjectBase<DerivedT> & T,
const std::vector<std::vector<SType> > & S,
Eigen::PlainObjectBase<DerivedW> & W)
{
return biharmonic_coordinates(V,T,S,2,W);
}
template <
typename DerivedV,
typename DerivedT,
typename SType,
typename DerivedW>
IGL_INLINE bool igl::biharmonic_coordinates(
const Eigen::PlainObjectBase<DerivedV> & V,
const Eigen::PlainObjectBase<DerivedT> & T,
const std::vector<std::vector<SType> > & S,
const int k,
Eigen::PlainObjectBase<DerivedW> & W)
{
using namespace Eigen;
using namespace std;
// This is not the most efficient way to build A, but follows "Linear
// Subspace Design for Real-Time Shape Deformation" [Wang et al. 2015].
SparseMatrix<double> A;
{
DiagonalMatrix<double,Dynamic> Minv;
SparseMatrix<double> L,K;
Array<bool,Dynamic,Dynamic> C;
{
Array<bool,Dynamic,1> I;
on_boundary(T,I,C);
}
#ifdef false
// Version described in paper is "wrong"
// http://www.cs.toronto.edu/~jacobson/images/error-in-linear-subspace-design-for-real-time-shape-deformation-2017-wang-et-al.pdf
SparseMatrix<double> N,Z,M;
normal_derivative(V,T,N);
{
std::vector<Triplet<double> >ZIJV;
for(int t =0;t<T.rows();t++)
{
for(int f =0;f<T.cols();f++)
{
if(C(t,f))
{
const int i = t+f*T.rows();
for(int c = 1;c<T.cols();c++)
{
ZIJV.emplace_back(T(t,(f+c)%T.cols()),i,1);
}
}
}
}
Z.resize(V.rows(),N.rows());
Z.setFromTriplets(ZIJV.begin(),ZIJV.end());
N = (Z*N).eval();
}
cotmatrix(V,T,L);
K = N+L;
massmatrix(V,T,MASSMATRIX_TYPE_DEFAULT,M);
// normalize
M /= ((VectorXd)M.diagonal()).array().abs().maxCoeff();
Minv =
((VectorXd)M.diagonal().array().inverse()).asDiagonal();
#else
Eigen::SparseMatrix<double> M;
Eigen::MatrixXi E;
Eigen::VectorXi EMAP;
crouzeix_raviart_massmatrix(V,T,M,E,EMAP);
crouzeix_raviart_cotmatrix(V,T,E,EMAP,L);
// Ad #E by #V facet-vertex incidence matrix
Eigen::SparseMatrix<double> Ad(E.rows(),V.rows());
{
std::vector<Eigen::Triplet<double> > AIJV(E.size());
for(int e = 0;e<E.rows();e++)
{
for(int c = 0;c<E.cols();c++)
{
AIJV[e+c*E.rows()] = Eigen::Triplet<double>(e,E(e,c),1);
}
}
Ad.setFromTriplets(AIJV.begin(),AIJV.end());
}
// Degrees
Eigen::VectorXd De;
sum(Ad,2,De);
Eigen::DiagonalMatrix<double,Eigen::Dynamic> De_diag =
De.array().inverse().matrix().asDiagonal();
K = L*(De_diag*Ad);
// normalize
M /= ((VectorXd)M.diagonal()).array().abs().maxCoeff();
Minv = ((VectorXd)M.diagonal().array().inverse()).asDiagonal();
// kill boundary edges
for(int f = 0;f<T.rows();f++)
{
for(int c = 0;c<T.cols();c++)
{
if(C(f,c))
{
const int e = EMAP(f+T.rows()*c);
Minv.diagonal()(e) = 0;
}
}
}
#endif
switch(k)
{
default:
assert(false && "unsupported");
case 2:
// For C1 smoothness in 2D, one should use bi-harmonic
A = K.transpose() * (Minv * K);
break;
case 3:
// For C1 smoothness in 3D, one should use tri-harmonic
A = K.transpose() * (Minv * (-L * (Minv * K)));
break;
}
}
// Vertices in point handles
const size_t mp =
count_if(S.begin(),S.end(),[](const vector<int> & h){return h.size()==1;});
// number of region handles
const size_t r = S.size()-mp;
// Vertices in region handles
size_t mr = 0;
for(const auto & h : S)
{
if(h.size() > 1)
{
mr += h.size();
}
}
const size_t dim = T.cols()-1;
// Might as well be dense... I think...
MatrixXd J = MatrixXd::Zero(mp+mr,mp+r*(dim+1));
VectorXi b(mp+mr);
MatrixXd H(mp+r*(dim+1),dim);
{
int v = 0;
int c = 0;
for(int h = 0;h<S.size();h++)
{
if(S[h].size()==1)
{
H.row(c) = V.block(S[h][0],0,1,dim);
J(v,c++) = 1;
b(v) = S[h][0];
v++;
}else
{
assert(S[h].size() >= dim+1);
for(int p = 0;p<S[h].size();p++)
{
for(int d = 0;d<dim;d++)
{
J(v,c+d) = V(S[h][p],d);
}
J(v,c+dim) = 1;
b(v) = S[h][p];
v++;
}
H.block(c,0,dim+1,dim).setIdentity();
c+=dim+1;
}
}
}
// minimize ½ W' A W'
// subject to W(b,:) = J
return min_quad_with_fixed(
A,VectorXd::Zero(A.rows()).eval(),b,J,SparseMatrix<double>(),VectorXd(),true,W);
}
#ifdef IGL_STATIC_LIBRARY
// Explicit template instantiation
template bool igl::biharmonic_coordinates<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<int, -1, -1, 0, -1, -1>, int, Eigen::Matrix<double, -1, -1, 0, -1, -1> >(Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&, Eigen::PlainObjectBase<Eigen::Matrix<int, -1, -1, 0, -1, -1> > const&, std::vector<std::vector<int, std::allocator<int> >, std::allocator<std::vector<int, std::allocator<int> > > > const&, int, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >&);
#endif