IGL_INLINE void igl::sparse(
const IndexVector & I,
const IndexVector & J,
const ValueVector & V,
const size_t m,
const size_t n,
Eigen::SparseMatrix<T>& X)
{
using namespace std;
using namespace Eigen;
assert((int)I.maxCoeff() < (int)m);
assert((int)I.minCoeff() >= 0);
assert((int)J.maxCoeff() < (int)n);
assert((int)J.minCoeff() >= 0);
assert(I.size() == J.size());
assert(J.size() == V.size());
// Really we just need .size() to be the same, but this is safer
assert(I.rows() == J.rows());
assert(J.rows() == V.rows());
assert(I.cols() == J.cols());
assert(J.cols() == V.cols());
vector<Triplet<T> > IJV;
IJV.reserve(I.size());
for(int x = 0;x<I.size();x++)
{
IJV.push_back(Triplet<T >(I(x),J(x),V(x)));
}
X.resize(m,n);
X.setFromTriplets(IJV.begin(),IJV.end());
}
IGL_INLINE void igl::sparse(
const IndexVector & I,
const IndexVector & J,
const ValueVector & V,
const size_t m,
const size_t n,
Eigen::SparseMatrix<T>& X)
{
using namespace std;
using namespace Eigen;
assert((int)I.maxCoeff() < (int)m);
assert((int)I.minCoeff() >= 0);
assert((int)J.maxCoeff() < (int)n);
assert((int)J.minCoeff() >= 0);
assert(I.size() == J.size());
assert(J.size() == V.size());
// Really we just need .size() to be the same, but this is safer
assert(I.rows() == J.rows());
assert(J.rows() == V.rows());
assert(I.cols() == J.cols());
assert(J.cols() == V.cols());
//// number of values
//int nv = V.size();
//Eigen::DynamicSparseMatrix<T, Eigen::RowMajor> dyn_X(m,n);
//// over estimate the number of entries
//dyn_X.reserve(I.size());
//for(int i = 0;i < nv;i++)
//{
// dyn_X.coeffRef((int)I(i),(int)J(i)) += (T)V(i);
//}
//X = Eigen::SparseMatrix<T>(dyn_X);
vector<Triplet<T> > IJV;
IJV.reserve(I.size());
for(int x = 0;x<I.size();x++)
{
IJV.push_back(Triplet<T >(I(x),J(x),V(x)));
}
X.resize(m,n);
X.setFromTriplets(IJV.begin(),IJV.end());
}
