- move CompressedStorage and AmbiVector into internal namespace

- remove innerVectorNonZeros(j) => use innerVector(j).nonZeros()

2 files changed, 5 insertions, 5 deletions

diff --git a/unsupported/Eigen/src/SparseExtra/DynamicSparseMatrix.h b/unsupported/Eigen/src/SparseExtra/DynamicSparseMatrix.h
index 9a61ddb09..ce39a17f7 100644
--- a/unsupported/Eigen/src/SparseExtra/DynamicSparseMatrix.h
+++ b/unsupported/Eigen/src/SparseExtra/DynamicSparseMatrix.h
@@ -86,7 +86,7 @@ template<typename _Scalar, int _Options, typename _Index>
     typedef DynamicSparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> TransposedSparseMatrix;
 
     Index m_innerSize;
-    std::vector<CompressedStorage<Scalar,Index> > m_data;
+    std::vector<internal::CompressedStorage<Scalar,Index> > m_data;
 
   public:
 
@@ -96,8 +96,8 @@ template<typename _Scalar, int _Options, typename _Index>
     inline Index outerSize() const { return static_cast<Index>(m_data.size()); }
     inline Index innerNonZeros(Index j) const { return m_data[j].size(); }
 
-    std::vector<CompressedStorage<Scalar,Index> >& _data() { return m_data; }
-    const std::vector<CompressedStorage<Scalar,Index> >& _data() const { return m_data; }
+    std::vector<internal::CompressedStorage<Scalar,Index> >& _data() { return m_data; }
+    const std::vector<internal::CompressedStorage<Scalar,Index> >& _data() const { return m_data; }
 
     /** \returns the coefficient value at given position \a row, \a col
       * This operation involes a log(rho*outer_size) binary search.
diff --git a/unsupported/Eigen/src/SparseExtra/SparseLLT.h b/unsupported/Eigen/src/SparseExtra/SparseLLT.h
index 8ae116e82..fbfeecc35 100644
--- a/unsupported/Eigen/src/SparseExtra/SparseLLT.h
+++ b/unsupported/Eigen/src/SparseExtra/SparseLLT.h
@@ -177,7 +177,7 @@ void SparseLLT<_MatrixType,Backend>::compute(const _MatrixType& a)
   m_matrix.resize(size, size);
 
   // allocate a temporary vector for accumulations
-  AmbiVector<Scalar,Index> tempVector(size);
+  internal::AmbiVector<Scalar,Index> tempVector(size);
   RealScalar density = a.nonZeros()/RealScalar(size*size);
 
   // TODO estimate the number of non zeros
@@ -222,7 +222,7 @@ void SparseLLT<_MatrixType,Backend>::compute(const _MatrixType& a)
     RealScalar rx = internal::sqrt(internal::real(x));
     m_matrix.insert(j,j) = rx; // FIXME use insertBack
     Scalar y = Scalar(1)/rx;
-    for (typename AmbiVector<Scalar,Index>::Iterator it(tempVector, m_precision*rx); it; ++it)
+    for (typename internal::AmbiVector<Scalar,Index>::Iterator it(tempVector, m_precision*rx); it; ++it)
     {
       // FIXME use insertBack
       m_matrix.insertBack(it.index(), j) = it.value() * y;