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//
// Copyright (C) : Please refer to the COPYRIGHT file distributed
// with this source distribution.
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
///////////////////////////////////////////////////////////////////////////////
#include "normal_cycle.h"
#include "matrix_util.h"
namespace OGF {
//_________________________________________________________
NormalCycle::NormalCycle() {
}
void NormalCycle::begin() {
M_[0] = M_[1] = M_[2] = M_[3] = M_[4] = M_[5] = 0 ;
}
void NormalCycle::end() {
double eigen_vectors[9] ;
MatrixUtil::semi_definite_symmetric_eigen(M_, 3, eigen_vectors, eigen_value_) ;
axis_[0] = Vec3r(
eigen_vectors[0], eigen_vectors[1], eigen_vectors[2]
) ;
axis_[1] = Vec3r(
eigen_vectors[3], eigen_vectors[4], eigen_vectors[5]
) ;
axis_[2] = Vec3r(
eigen_vectors[6], eigen_vectors[7], eigen_vectors[8]
) ;
// Normalize the eigen vectors
for(int i=0; i<3; i++) {
axis_[i].normalize() ;
}
// Sort the eigen vectors
i_[0] = 0 ;
i_[1] = 1 ;
i_[2] = 2 ;
double l0 = ::fabs(eigen_value_[0]) ;
double l1 = ::fabs(eigen_value_[1]) ;
double l2 = ::fabs(eigen_value_[2]) ;
if(l1 > l0) {
ogf_swap(l0 , l1 ) ;
ogf_swap(i_[0], i_[1]) ;
}
if(l2 > l1) {
ogf_swap(l1 , l2 ) ;
ogf_swap(i_[1], i_[2]) ;
}
if(l1 > l0) {
ogf_swap(l0 , l1 ) ;
ogf_swap(i_[0],i_[1]) ;
}
}
void NormalCycle::accumulate_dihedral_angle(
const Vec3r& edge, double beta, double neigh_area
) {
Vec3r e = edge ;
e.normalize() ;
double s = edge.norm() * beta * neigh_area ;
M_[0] += s * e.x() * e.x() ;
M_[1] += s * e.x() * e.y() ;
M_[2] += s * e.y() * e.y() ;
M_[3] += s * e.x() * e.z() ;
M_[4] += s * e.y() * e.z() ;
M_[5] += s * e.z() * e.z() ;
}
//_________________________________________________________
}
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