本文整理汇总了C++中eigen::VectorXi::coeffRef方法的典型用法代码示例。如果您正苦于以下问题：C++ VectorXi::coeffRef方法的具体用法？C++ VectorXi::coeffRef怎么用？C++ VectorXi::coeffRef使用的例子？那么, 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::VectorXi的用法示例。
在下文中一共展示了VectorXi::coeffRef方法的1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: slice
IGL_INLINE void igl::slice(
const Eigen::SparseMatrix<TX>& X,
const Eigen::Matrix<int,Eigen::Dynamic,1> & R,
const Eigen::Matrix<int,Eigen::Dynamic,1> & C,
Eigen::SparseMatrix<TY>& Y)
{
#if 1
int xm = X.rows();
int xn = X.cols();
int ym = R.size();
int yn = C.size();
// special case when R or C is empty
if(ym == 0 || yn == 0)
{
Y.resize(ym,yn);
return;
}
assert(R.minCoeff() >= 0);
assert(R.maxCoeff() < xm);
assert(C.minCoeff() >= 0);
assert(C.maxCoeff() < xn);
// Build reindexing maps for columns and rows, -1 means not in map
std::vector<std::vector<int> > RI;
RI.resize(xm);
for(int i = 0;i<ym;i++)
{
RI[R(i)].push_back(i);
}
std::vector<std::vector<int> > CI;
CI.resize(xn);
// initialize to -1
for(int i = 0;i<yn;i++)
{
CI[C(i)].push_back(i);
}
// Resize output
Eigen::DynamicSparseMatrix<TY, Eigen::RowMajor> dyn_Y(ym,yn);
// Take a guess at the number of nonzeros (this assumes uniform distribution
// not banded or heavily diagonal)
dyn_Y.reserve((X.nonZeros()/(X.rows()*X.cols())) * (ym*yn));
// Iterate over outside
for(int k=0; k<X.outerSize(); ++k)
{
// Iterate over inside
for(typename Eigen::SparseMatrix<TX>::InnerIterator it (X,k); it; ++it)
{
std::vector<int>::iterator rit, cit;
for(rit = RI[it.row()].begin();rit != RI[it.row()].end(); rit++)
{
for(cit = CI[it.col()].begin();cit != CI[it.col()].end(); cit++)
{
dyn_Y.coeffRef(*rit,*cit) = it.value();
}
}
}
}
Y = Eigen::SparseMatrix<TY>(dyn_Y);
#else
// Alec: This is _not_ valid for arbitrary R,C since they don't necessary
// representation a strict permutation of the rows and columns: rows or
// columns could be removed or replicated. The removal of rows seems to be
// handled here (although it's not clear if there is a performance gain when
// the #removals >> #remains). If this is sufficiently faster than the
// correct code above, one could test whether all entries in R and C are
// unique and apply the permutation version if appropriate.
//
int xm = X.rows();
int xn = X.cols();
int ym = R.size();
int yn = C.size();
// special case when R or C is empty
if(ym == 0 || yn == 0)
{
Y.resize(ym,yn);
return;
}
assert(R.minCoeff() >= 0);
assert(R.maxCoeff() < xm);
assert(C.minCoeff() >= 0);
assert(C.maxCoeff() < xn);
// initialize row and col permutation vectors
Eigen::VectorXi rowIndexVec = Eigen::VectorXi::LinSpaced(xm,0,xm-1);
Eigen::VectorXi rowPermVec = Eigen::VectorXi::LinSpaced(xm,0,xm-1);
for(int i=0;i<ym;i++)
{
int pos = rowIndexVec.coeffRef(R(i));
if(pos != i)
{
int& val = rowPermVec.coeffRef(i);
std::swap(rowIndexVec.coeffRef(val),rowIndexVec.coeffRef(R(i)));
std::swap(rowPermVec.coeffRef(i),rowPermVec.coeffRef(pos));
}
//.........这里部分代码省略.........