本文整理汇总了C++中eigen::PlainObjectBase::colwise方法的典型用法代码示例。如果您正苦于以下问题：C++ PlainObjectBase::colwise方法的具体用法？C++ PlainObjectBase::colwise怎么用？C++ PlainObjectBase::colwise使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类eigen::PlainObjectBase的用法示例。
在下文中一共展示了PlainObjectBase::colwise方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: assembleP
inline void igl::PlanarizerShapeUp<DerivedV, DerivedF>::planarize(Eigen::PlainObjectBase<DerivedV> &Vout)
{
Eigen::Matrix<typename DerivedV::Scalar, Eigen::Dynamic, 1> planarity;
Vout = Vin;
for (int iter =0; iter<maxIter; ++iter)
{
igl::quad_planarity(Vout, Fin, planarity);
typename DerivedV::Scalar nonPlanarity = planarity.cwiseAbs().maxCoeff();
//std::cerr<<"iter #"<<iter<<": max non-planarity: "<<nonPlanarity<<std::endl;
if (nonPlanarity<threshold)
break;
assembleP();
Vv = solver.solve(Q.transpose()*P);
if(solver.info()!=Eigen::Success)
{
std::cerr << "Linear solve failed - PlanarizerShapeUp.cpp" << std::endl;
assert(0);
}
for (int i =0;i<numV;++i)
Vout.row(i) << Vv.segment(3*i,3).transpose();
}
// set the mean of Vout to the mean of Vin
Eigen::Matrix<typename DerivedV::Scalar, 1, 3> oldMean, newMean;
oldMean = Vin.colwise().mean();
newMean = Vout.colwise().mean();
Vout.rowwise() += (oldMean - newMean);
};示例2: bounding_box
IGL_INLINE void igl::bounding_box(
const Eigen::PlainObjectBase<DerivedV>& V,
Eigen::PlainObjectBase<DerivedBV>& BV,
Eigen::PlainObjectBase<DerivedBF>& BF)
{
using namespace std;
const int dim = V.cols();
const auto & minV = V.colwise().minCoeff();
const auto & maxV = V.colwise().maxCoeff();
// 2^n vertices
BV.resize((1<<dim),dim);
// Recursive lambda to generate all 2^n combinations
const std::function<void(const int,const int,int*,int)> combos =
[&BV,&minV,&maxV,&combos](
const int dim,
const int i,
int * X,
const int pre_index)
{
for(X[i] = 0;X[i]<2;X[i]++)
{
int index = pre_index*2+X[i];
if((i+1)<dim)
{
combos(dim,i+1,X,index);
}else
{
for(int d = 0;d<dim;d++)
{
BV(index,d) = (X[d]?minV[d]:maxV[d]);
}
}
}
};
Eigen::VectorXi X(dim);
combos(dim,0,X.data(),0);
switch(dim)
{
case 2:
BF.resize(4,2);
BF<<
3,1,
1,0,
0,2,
2,3;
break;
case 3:
BF.resize(12,3);
BF<<
2,0,6,
0,4,6,
5,4,0,
5,0,1,
6,4,5,
5,7,6,
3,0,2,
1,0,3,
3,2,6,
6,7,3,
5,1,3,
3,7,5;
break;
default:
assert(false && "Unsupported dimension.");
break;
}
}