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Regression test for (invalid) bug #900. We should make it possible somehow to increase the problem size depending on the available RAM.

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This commit is contained in:
Christoph Hertzberg 2014-10-31 17:19:05 +01:00
parent 0833b82efd
commit c5a3777666
1 changed files with 30 additions and 0 deletions
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30
test/sparse_basic.cpp
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@ -520,6 +520,32 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
} }
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 test_sparse_basic() void test_sparse_basic()
{ {
for(int i = 0; i < g_repeat; i++) { for(int i = 0; i < g_repeat; i++) {
@ -539,4 +565,8 @@ void test_sparse_basic()
CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,ColMajor,short int>(short(r), short(c))) )); CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,ColMajor,short int>(short(r), short(c))) ));
CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,RowMajor,short int>(short(r), short(c))) )); CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,RowMajor,short int>(short(r), short(c))) ));
} }
// Regression test for bug 900: (manually insert higher values here, if you have enough RAM):
CALL_SUBTEST_3((big_sparse_triplet<SparseMatrix<float, RowMajor, int> >(10000, 10000, 0.125)));
CALL_SUBTEST_4((big_sparse_triplet<SparseMatrix<double, ColMajor, long int> >(10000, 10000, 0.125)));
} }