make the accessors to internal sparse storage part of the public API and remove their "_" prefix.

This commit is contained in:
Gael Guennebaud
2011-12-04 12:19:26 +01:00
parent 1cdbae62db
commit 32917515df
13 changed files with 153 additions and 130 deletions

View File

@@ -156,8 +156,8 @@ class SparseInnerVectorSet<SparseMatrix<_Scalar, _Options, _Index>, Size>
Index nnz = tmp.nonZeros();
Index nnz_previous = nonZeros();
Index free_size = matrix.data().allocatedSize() + nnz_previous;
std::size_t nnz_head = m_outerStart==0 ? 0 : matrix._outerIndexPtr()[m_outerStart];
std::size_t tail = m_matrix._outerIndexPtr()[m_outerStart+m_outerSize.value()];
std::size_t nnz_head = m_outerStart==0 ? 0 : matrix.outerIndexPtr()[m_outerStart];
std::size_t tail = m_matrix.outerIndexPtr()[m_outerStart+m_outerSize.value()];
std::size_t nnz_tail = matrix.nonZeros() - tail;
if(nnz>free_size)
@@ -203,13 +203,13 @@ class SparseInnerVectorSet<SparseMatrix<_Scalar, _Options, _Index>, Size>
Index p = nnz_head;
for(Index k=0; k<m_outerSize.value(); ++k)
{
matrix._outerIndexPtr()[m_outerStart+k] = p;
matrix.outerIndexPtr()[m_outerStart+k] = p;
p += tmp.innerVector(k).nonZeros();
}
std::ptrdiff_t offset = nnz - nnz_previous;
for(Index k = m_outerStart + m_outerSize.value(); k<=matrix.outerSize(); ++k)
{
matrix._outerIndexPtr()[k] += offset;
matrix.outerIndexPtr()[k] += offset;
}
return *this;
@@ -220,30 +220,30 @@ class SparseInnerVectorSet<SparseMatrix<_Scalar, _Options, _Index>, Size>
return operator=<SparseInnerVectorSet>(other);
}
inline const Scalar* _valuePtr() const
{ return m_matrix._valuePtr() + m_matrix._outerIndexPtr()[m_outerStart]; }
inline Scalar* _valuePtr()
{ return m_matrix.const_cast_derived()._valuePtr() + m_matrix._outerIndexPtr()[m_outerStart]; }
inline const Scalar* valuePtr() const
{ return m_matrix.valuePtr() + m_matrix.outerIndexPtr()[m_outerStart]; }
inline Scalar* valuePtr()
{ return m_matrix.const_cast_derived().valuePtr() + m_matrix.outerIndexPtr()[m_outerStart]; }
inline const Index* _innerIndexPtr() const
{ return m_matrix._innerIndexPtr() + m_matrix._outerIndexPtr()[m_outerStart]; }
inline Index* _innerIndexPtr()
{ return m_matrix.const_cast_derived()._innerIndexPtr() + m_matrix._outerIndexPtr()[m_outerStart]; }
inline const Index* innerIndexPtr() const
{ return m_matrix.innerIndexPtr() + m_matrix.outerIndexPtr()[m_outerStart]; }
inline Index* innerIndexPtr()
{ return m_matrix.const_cast_derived().innerIndexPtr() + m_matrix.outerIndexPtr()[m_outerStart]; }
inline const Index* _outerIndexPtr() const
{ return m_matrix._outerIndexPtr() + m_outerStart; }
inline Index* _outerIndexPtr()
{ return m_matrix.const_cast_derived()._outerIndexPtr() + m_outerStart; }
inline const Index* outerIndexPtr() const
{ return m_matrix.outerIndexPtr() + m_outerStart; }
inline Index* outerIndexPtr()
{ return m_matrix.const_cast_derived().outerIndexPtr() + m_outerStart; }
Index nonZeros() const
{
if(m_matrix.compressed())
return std::size_t(m_matrix._outerIndexPtr()[m_outerStart+m_outerSize.value()])
- std::size_t(m_matrix._outerIndexPtr()[m_outerStart]);
return std::size_t(m_matrix.outerIndexPtr()[m_outerStart+m_outerSize.value()])
- std::size_t(m_matrix.outerIndexPtr()[m_outerStart]);
else if(m_outerSize.value()==0)
return 0;
else
return Map<const Matrix<Index,Size,1> >(m_matrix._innerNonZeroPtr(), m_outerSize.value()).sum();
return Map<const Matrix<Index,Size,1> >(m_matrix.innerNonZeroPtr(), m_outerSize.value()).sum();
}
const Scalar& lastCoeff() const
@@ -251,9 +251,9 @@ class SparseInnerVectorSet<SparseMatrix<_Scalar, _Options, _Index>, Size>
EIGEN_STATIC_ASSERT_VECTOR_ONLY(SparseInnerVectorSet);
eigen_assert(nonZeros()>0);
if(m_matrix.compressed())
return m_matrix._valuePtr()[m_matrix._outerIndexPtr()[m_outerStart+1]-1];
return m_matrix.valuePtr()[m_matrix.outerIndexPtr()[m_outerStart+1]-1];
else
return m_matrix._valuePtr()[m_matrix._outerIndexPtr()[m_outerStart]+m_matrix._innerNonZeroPtr()[m_outerStart]-1];
return m_matrix.valuePtr()[m_matrix.outerIndexPtr()[m_outerStart]+m_matrix.innerNonZeroPtr()[m_outerStart]-1];
}
// template<typename Sparse>