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authorGravatar Desire NUENTSA <desire.nuentsa_wakam@inria.fr>2013-04-08 08:51:58 +0200
committerGravatar Desire NUENTSA <desire.nuentsa_wakam@inria.fr>2013-04-08 08:51:58 +0200
commitd97cd746ae1f6619b344267212a6f73ce31a2730 (patch)
tree9ceb2e8992ea0e454266f8c69b42ff04282d65a8 /Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
parent9b33ab62da11627143770acc64f71668a43fd562 (diff)
Replace int by Index
Diffstat (limited to 'Eigen/src/IterativeLinearSolvers/IncompleteLUT.h')
-rw-r--r--Eigen/src/IterativeLinearSolvers/IncompleteLUT.h54
1 files changed, 27 insertions, 27 deletions
diff --git a/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h b/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
index 8e3f95b44..17d18ef58 100644
--- a/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
+++ b/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
@@ -24,15 +24,15 @@ namespace internal {
* \param ind The array of index for the elements in @p row
* \param ncut The number of largest elements to keep
**/
-template <typename VectorV, typename VectorI>
-int QuickSplit(VectorV &row, VectorI &ind, int ncut)
+template <typename VectorV, typename VectorI, typename Index>
+Index QuickSplit(VectorV &row, VectorI &ind, Index ncut)
{
typedef typename VectorV::RealScalar RealScalar;
using std::swap;
using std::abs;
- int mid;
- int n = row.size(); /* length of the vector */
- int first, last ;
+ Index mid;
+ Index n = row.size(); /* length of the vector */
+ Index first, last ;
ncut--; /* to fit the zero-based indices */
first = 0;
@@ -42,7 +42,7 @@ int QuickSplit(VectorV &row, VectorI &ind, int ncut)
do {
mid = first;
RealScalar abskey = abs(row(mid));
- for (int j = first + 1; j <= last; j++) {
+ for (Index j = first + 1; j <= last; j++) {
if ( abs(row(j)) > abskey) {
++mid;
swap(row(mid), row(j));
@@ -247,7 +247,7 @@ void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
using std::abs;
eigen_assert((amat.rows() == amat.cols()) && "The factorization should be done on a square matrix");
- int n = amat.cols(); // Size of the matrix
+ Index n = amat.cols(); // Size of the matrix
m_lu.resize(n,n);
// Declare Working vectors and variables
Vector u(n) ; // real values of the row -- maximum size is n --
@@ -265,21 +265,21 @@ void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
u.fill(0);
// number of largest elements to keep in each row:
- int fill_in = static_cast<int> (amat.nonZeros()*m_fillfactor)/n+1;
+ Index fill_in = static_cast<Index> (amat.nonZeros()*m_fillfactor)/n+1;
if (fill_in > n) fill_in = n;
// number of largest nonzero elements to keep in the L and the U part of the current row:
- int nnzL = fill_in/2;
- int nnzU = nnzL;
+ Index nnzL = fill_in/2;
+ Index nnzU = nnzL;
m_lu.reserve(n * (nnzL + nnzU + 1));
// global loop over the rows of the sparse matrix
- for (int ii = 0; ii < n; ii++)
+ for (Index ii = 0; ii < n; ii++)
{
// 1 - copy the lower and the upper part of the row i of mat in the working vector u
- int sizeu = 1; // number of nonzero elements in the upper part of the current row
- int sizel = 0; // number of nonzero elements in the lower part of the current row
+ Index sizeu = 1; // number of nonzero elements in the upper part of the current row
+ Index sizel = 0; // number of nonzero elements in the lower part of the current row
ju(ii) = ii;
u(ii) = 0;
jr(ii) = ii;
@@ -288,7 +288,7 @@ void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
typename FactorType::InnerIterator j_it(mat, ii); // Iterate through the current row ii
for (; j_it; ++j_it)
{
- int k = j_it.index();
+ Index k = j_it.index();
if (k < ii)
{
// copy the lower part
@@ -304,7 +304,7 @@ void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
else
{
// copy the upper part
- int jpos = ii + sizeu;
+ Index jpos = ii + sizeu;
ju(jpos) = k;
u(jpos) = j_it.value();
jr(k) = jpos;
@@ -323,19 +323,19 @@ void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
rownorm = sqrt(rownorm);
// 3 - eliminate the previous nonzero rows
- int jj = 0;
- int len = 0;
+ Index jj = 0;
+ Index len = 0;
while (jj < sizel)
{
// In order to eliminate in the correct order,
// we must select first the smallest column index among ju(jj:sizel)
- int k;
- int minrow = ju.segment(jj,sizel-jj).minCoeff(&k); // k is relative to the segment
+ Index k;
+ Index minrow = ju.segment(jj,sizel-jj).minCoeff(&k); // k is relative to the segment
k += jj;
if (minrow != ju(jj))
{
// swap the two locations
- int j = ju(jj);
+ Index j = ju(jj);
swap(ju(jj), ju(k));
jr(minrow) = jj; jr(j) = k;
swap(u(jj), u(k));
@@ -361,11 +361,11 @@ void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
for (; ki_it; ++ki_it)
{
Scalar prod = fact * ki_it.value();
- int j = ki_it.index();
- int jpos = jr(j);
+ Index j = ki_it.index();
+ Index jpos = jr(j);
if (jpos == -1) // fill-in element
{
- int newpos;
+ Index newpos;
if (j >= ii) // dealing with the upper part
{
newpos = ii + sizeu;
@@ -394,7 +394,7 @@ void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
} // end of the elimination on the row ii
// reset the upper part of the pointer jr to zero
- for(int k = 0; k <sizeu; k++) jr(ju(ii+k)) = -1;
+ for(Index k = 0; k <sizeu; k++) jr(ju(ii+k)) = -1;
// 4 - partially sort and insert the elements in the m_lu matrix
@@ -407,7 +407,7 @@ void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
// store the largest m_fill elements of the L part
m_lu.startVec(ii);
- for(int k = 0; k < len; k++)
+ for(Index k = 0; k < len; k++)
m_lu.insertBackByOuterInnerUnordered(ii,ju(k)) = u(k);
// store the diagonal element
@@ -419,7 +419,7 @@ void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
// sort the U-part of the row
// apply the dropping rule first
len = 0;
- for(int k = 1; k < sizeu; k++)
+ for(Index k = 1; k < sizeu; k++)
{
if(abs(u(ii+k)) > m_droptol * rownorm )
{
@@ -435,7 +435,7 @@ void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
internal::QuickSplit(uu, juu, len);
// store the largest elements of the U part
- for(int k = ii + 1; k < ii + len; k++)
+ for(Index k = ii + 1; k < ii + len; k++)
m_lu.insertBackByOuterInnerUnordered(ii,ju(k)) = u(k);
}