split the Sparse module into multiple ones, and move non stable parts to unsupported/
(see the ML for details)
diff --git a/test/sparse_basic.cpp b/test/sparse_basic.cpp
index 43d9c62..3d22109 100644
--- a/test/sparse_basic.cpp
+++ b/test/sparse_basic.cpp
@@ -24,40 +24,6 @@
#include "sparse.h"
-template<typename SetterType,typename DenseType, typename Scalar, int Options>
-bool test_random_setter(SparseMatrix<Scalar,Options>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords)
-{
- typedef SparseMatrix<Scalar,Options> SparseType;
- {
- sm.setZero();
- SetterType w(sm);
- std::vector<Vector2i> remaining = nonzeroCoords;
- while(!remaining.empty())
- {
- int i = ei_random<int>(0,static_cast<int>(remaining.size())-1);
- w(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y());
- remaining[i] = remaining.back();
- remaining.pop_back();
- }
- }
- return sm.isApprox(ref);
-}
-
-template<typename SetterType,typename DenseType, typename T>
-bool test_random_setter(DynamicSparseMatrix<T>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords)
-{
- sm.setZero();
- std::vector<Vector2i> remaining = nonzeroCoords;
- while(!remaining.empty())
- {
- int i = ei_random<int>(0,static_cast<int>(remaining.size())-1);
- sm.coeffRef(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y());
- remaining[i] = remaining.back();
- remaining.pop_back();
- }
- return sm.isApprox(ref);
-}
-
template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& ref)
{
const int rows = ref.rows();
@@ -136,47 +102,6 @@
}
*/
- // test SparseSetters
- // coherent setter
- // TODO extend the MatrixSetter
-// {
-// m.setZero();
-// VERIFY_IS_NOT_APPROX(m, refMat);
-// SparseSetter<SparseMatrixType, FullyCoherentAccessPattern> w(m);
-// for (int i=0; i<nonzeroCoords.size(); ++i)
-// {
-// w->coeffRef(nonzeroCoords[i].x(),nonzeroCoords[i].y()) = refMat.coeff(nonzeroCoords[i].x(),nonzeroCoords[i].y());
-// }
-// }
-// VERIFY_IS_APPROX(m, refMat);
-
- // random setter
-// {
-// m.setZero();
-// VERIFY_IS_NOT_APPROX(m, refMat);
-// SparseSetter<SparseMatrixType, RandomAccessPattern> w(m);
-// std::vector<Vector2i> remaining = nonzeroCoords;
-// while(!remaining.empty())
-// {
-// int i = ei_random<int>(0,remaining.size()-1);
-// w->coeffRef(remaining[i].x(),remaining[i].y()) = refMat.coeff(remaining[i].x(),remaining[i].y());
-// remaining[i] = remaining.back();
-// remaining.pop_back();
-// }
-// }
-// VERIFY_IS_APPROX(m, refMat);
-
- VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdMapTraits> >(m,refMat,nonzeroCoords) ));
- #ifdef EIGEN_UNORDERED_MAP_SUPPORT
- VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdUnorderedMapTraits> >(m,refMat,nonzeroCoords) ));
- #endif
- #ifdef _DENSE_HASH_MAP_H_
- VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleDenseHashMapTraits> >(m,refMat,nonzeroCoords) ));
- #endif
- #ifdef _SPARSE_HASH_MAP_H_
- VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleSparseHashMapTraits> >(m,refMat,nonzeroCoords) ));
- #endif
-
// test insert (inner random)
{
DenseMatrix m1(rows,cols);
@@ -213,22 +138,6 @@
VERIFY_IS_APPROX(m2,m1);
}
- // test RandomSetter
- /*{
- SparseMatrixType m1(rows,cols), m2(rows,cols);
- DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
- initSparse<Scalar>(density, refM1, m1);
- {
- Eigen::RandomSetter<SparseMatrixType > setter(m2);
- for (int j=0; j<m1.outerSize(); ++j)
- for (typename SparseMatrixType::InnerIterator i(m1,j); i; ++i)
- setter(i.index(), j) = i.value();
- }
- VERIFY_IS_APPROX(m1, m2);
- }*/
-// std::cerr << m.transpose() << "\n\n" << refMat.transpose() << "\n\n";
-// VERIFY_IS_APPROX(m, refMat);
-
// test basic computations
{
DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
@@ -263,6 +172,17 @@
// VERIFY_IS_APPROX(m3.cwise()/refM4, refM3.cwise()/refM4);
}
+ // test transpose
+ {
+ DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
+ SparseMatrixType m2(rows, rows);
+ initSparse<Scalar>(density, refMat2, m2);
+ VERIFY_IS_APPROX(m2.transpose().eval(), refMat2.transpose().eval());
+ VERIFY_IS_APPROX(m2.transpose(), refMat2.transpose());
+
+ VERIFY_IS_APPROX(SparseMatrixType(m2.adjoint()), refMat2.adjoint());
+ }
+
// test innerVector()
{
DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
@@ -292,17 +212,6 @@
//refMat2.block(0,j0,rows,n0) = refMat2.block(0,j0,rows,n0) + refMat2.block(0,j1,rows,n0);
}
- // test transpose
- {
- DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
- SparseMatrixType m2(rows, rows);
- initSparse<Scalar>(density, refMat2, m2);
- VERIFY_IS_APPROX(m2.transpose().eval(), refMat2.transpose().eval());
- VERIFY_IS_APPROX(m2.transpose(), refMat2.transpose());
-
- VERIFY_IS_APPROX(SparseMatrixType(m2.adjoint()), refMat2.adjoint());
- }
-
// test prune
{
SparseMatrixType m2(rows, rows);