bug #877, bug #572: Introduce a global Index typedef. Rename Sparse*::Index to StorageIndex, make Dense*::StorageIndex an alias to DenseIndex. Overall this commit gets rid of all Index conversion warnings.
diff --git a/test/sparse_basic.cpp b/test/sparse_basic.cpp
index 097959c..a26fd5d 100644
--- a/test/sparse_basic.cpp
+++ b/test/sparse_basic.cpp
@@ -13,11 +13,11 @@
template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& ref)
{
- typedef typename SparseMatrixType::Index Index;
- typedef Matrix<Index,2,1> Vector2;
+ typedef typename SparseMatrixType::StorageIndex StorageIndex;
+ typedef Matrix<StorageIndex,2,1> Vector2;
- const Index rows = ref.rows();
- const Index cols = ref.cols();
+ const StorageIndex rows = ref.rows();
+ const StorageIndex cols = ref.cols();
const Index inner = ref.innerSize();
const Index outer = ref.outerSize();
@@ -56,27 +56,27 @@
VERIFY_IS_APPROX(m, refMat);
// test InnerIterators and Block expressions
- for (int t=0; t<10; ++t)
+ for (Index t=0; t<10; ++t)
{
- int j = internal::random<int>(0,cols-1);
- int i = internal::random<int>(0,rows-1);
- int w = internal::random<int>(1,cols-j-1);
- int h = internal::random<int>(1,rows-i-1);
+ Index j = internal::random<Index>(0,cols-1);
+ Index i = internal::random<Index>(0,rows-1);
+ Index w = internal::random<Index>(1,cols-j-1);
+ Index h = internal::random<Index>(1,rows-i-1);
VERIFY_IS_APPROX(m.block(i,j,h,w), refMat.block(i,j,h,w));
- for(int c=0; c<w; c++)
+ for(Index c=0; c<w; c++)
{
VERIFY_IS_APPROX(m.block(i,j,h,w).col(c), refMat.block(i,j,h,w).col(c));
- for(int r=0; r<h; r++)
+ for(Index r=0; r<h; r++)
{
// FIXME col().coeff() not implemented yet
// VERIFY_IS_APPROX(m.block(i,j,h,w).col(c).coeff(r), refMat.block(i,j,h,w).col(c).coeff(r));
}
}
- for(int r=0; r<h; r++)
+ for(Index r=0; r<h; r++)
{
VERIFY_IS_APPROX(m.block(i,j,h,w).row(r), refMat.block(i,j,h,w).row(r));
- for(int c=0; c<w; c++)
+ for(Index c=0; c<w; c++)
{
// FIXME row().coeff() not implemented yet
// VERIFY_IS_APPROX(m.block(i,j,h,w).row(r).coeff(c), refMat.block(i,j,h,w).row(r).coeff(c));
@@ -84,13 +84,13 @@
}
}
- for(int c=0; c<cols; c++)
+ for(Index c=0; c<cols; c++)
{
VERIFY_IS_APPROX(m.col(c) + m.col(c), (m + m).col(c));
VERIFY_IS_APPROX(m.col(c) + m.col(c), refMat.col(c) + refMat.col(c));
}
- for(int r=0; r<rows; r++)
+ for(Index r=0; r<rows; r++)
{
VERIFY_IS_APPROX(m.row(r) + m.row(r), (m + m).row(r));
VERIFY_IS_APPROX(m.row(r) + m.row(r), refMat.row(r) + refMat.row(r));
@@ -153,7 +153,7 @@
SparseMatrixType m2(rows,cols);
VectorXi r(VectorXi::Constant(m2.outerSize(), ((mode%2)==0) ? int(m2.innerSize()) : std::max<int>(1,int(m2.innerSize())/8)));
m2.reserve(r);
- for (int k=0; k<rows*cols; ++k)
+ for (Index k=0; k<rows*cols; ++k)
{
Index i = internal::random<Index>(0,rows-1);
Index j = internal::random<Index>(0,cols-1);
@@ -390,7 +390,7 @@
// test setFromTriplets
{
- typedef Triplet<Scalar,Index> TripletType;
+ typedef Triplet<Scalar,StorageIndex> TripletType;
std::vector<TripletType> triplets;
Index ntriplets = rows*cols;
triplets.reserve(ntriplets);
@@ -398,8 +398,8 @@
refMat.setZero();
for(Index i=0;i<ntriplets;++i)
{
- Index r = internal::random<Index>(0,rows-1);
- Index c = internal::random<Index>(0,cols-1);
+ StorageIndex r = internal::random<StorageIndex>(0,rows-1);
+ StorageIndex c = internal::random<StorageIndex>(0,cols-1);
Scalar v = internal::random<Scalar>();
triplets.push_back(TripletType(r,c,v));
refMat(r,c) += v;
@@ -482,17 +482,17 @@
// test conservative resize
{
- std::vector< std::pair<Index,Index> > inc;
+ std::vector< std::pair<StorageIndex,StorageIndex> > inc;
if(rows > 3 && cols > 2)
- inc.push_back(std::pair<Index,Index>(-3,-2));
- inc.push_back(std::pair<Index,Index>(0,0));
- inc.push_back(std::pair<Index,Index>(3,2));
- inc.push_back(std::pair<Index,Index>(3,0));
- inc.push_back(std::pair<Index,Index>(0,3));
+ inc.push_back(std::pair<StorageIndex,StorageIndex>(-3,-2));
+ inc.push_back(std::pair<StorageIndex,StorageIndex>(0,0));
+ inc.push_back(std::pair<StorageIndex,StorageIndex>(3,2));
+ inc.push_back(std::pair<StorageIndex,StorageIndex>(3,0));
+ inc.push_back(std::pair<StorageIndex,StorageIndex>(0,3));
for(size_t i = 0; i< inc.size(); i++) {
- Index incRows = inc[i].first;
- Index incCols = inc[i].second;
+ StorageIndex incRows = inc[i].first;
+ StorageIndex incCols = inc[i].second;
SparseMatrixType m1(rows, cols);
DenseMatrix refMat1 = DenseMatrix::Zero(rows, cols);
initSparse<Scalar>(density, refMat1, m1);
@@ -527,28 +527,28 @@
template<typename SparseMatrixType>
-void big_sparse_triplet(typename SparseMatrixType::Index rows, typename SparseMatrixType::Index cols, double density) {
-typedef typename SparseMatrixType::Index Index;
-typedef typename SparseMatrixType::Scalar Scalar;
-typedef Triplet<Scalar,Index> TripletType;
-std::vector<TripletType> triplets;
-double nelements = density * rows*cols;
-VERIFY(nelements>=0 && nelements < NumTraits<Index>::highest());
-Index ntriplets = Index(nelements);
-triplets.reserve(ntriplets);
-Scalar sum = Scalar(0);
-for(Index i=0;i<ntriplets;++i)
-{
- Index r = internal::random<Index>(0,rows-1);
- Index c = internal::random<Index>(0,cols-1);
- Scalar v = internal::random<Scalar>();
- triplets.push_back(TripletType(r,c,v));
- sum += v;
-}
-SparseMatrixType m(rows,cols);
-m.setFromTriplets(triplets.begin(), triplets.end());
-VERIFY(m.nonZeros() <= ntriplets);
-VERIFY_IS_APPROX(sum, m.sum());
+void big_sparse_triplet(Index rows, Index cols, double density) {
+ typedef typename SparseMatrixType::StorageIndex StorageIndex;
+ typedef typename SparseMatrixType::Scalar Scalar;
+ typedef Triplet<Scalar,Index> TripletType;
+ std::vector<TripletType> triplets;
+ double nelements = density * rows*cols;
+ VERIFY(nelements>=0 && nelements < NumTraits<StorageIndex>::highest());
+ Index ntriplets = Index(nelements);
+ triplets.reserve(ntriplets);
+ Scalar sum = Scalar(0);
+ for(Index i=0;i<ntriplets;++i)
+ {
+ Index r = internal::random<Index>(0,rows-1);
+ Index c = internal::random<Index>(0,cols-1);
+ Scalar v = internal::random<Scalar>();
+ triplets.push_back(TripletType(r,c,v));
+ sum += v;
+ }
+ SparseMatrixType m(rows,cols);
+ m.setFromTriplets(triplets.begin(), triplets.end());
+ VERIFY(m.nonZeros() <= ntriplets);
+ VERIFY_IS_APPROX(sum, m.sum());
}