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Fix many long to int conversion warnings:

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- fix usage of Index (API) versus StorageIndex (when multiple indexes are stored)
 - use StorageIndex(val) when the input has already been check
 - use internal::convert_index<StorageIndex>(val) when val is potentially unsafe (directly comes from user input)
This commit is contained in:
Gael Guennebaud
2015-02-16 13:19:05 +01:00
parent fc202bab39
commit aa6c516ec1
37 changed files with 397 additions and 398 deletions
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24
Eigen/src/OrderingMethods/Ordering.h
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@@ -111,12 +111,12 @@ class NaturalOrdering
* Functor computing the \em column \em approximate \em minimum \em degree ordering
* The matrix should be in column-major and \b compressed format (see SparseMatrix::makeCompressed()).
*/
template<typename Index>
template<typename StorageIndex>
class COLAMDOrdering
{
public:
typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
typedef Matrix<Index, Dynamic, 1> IndexVector;
typedef PermutationMatrix<Dynamic, Dynamic, StorageIndex> PermutationType;
typedef Matrix<StorageIndex, Dynamic, 1> IndexVector;
/** Compute the permutation vector \a perm form the sparse matrix \a mat
* \warning The input sparse matrix \a mat must be in compressed mode (see SparseMatrix::makeCompressed()).
@@ -126,26 +126,26 @@ class COLAMDOrdering
{
eigen_assert(mat.isCompressed() && "COLAMDOrdering requires a sparse matrix in compressed mode. Call .makeCompressed() before passing it to COLAMDOrdering");
Index m = mat.rows();
Index n = mat.cols();
Index nnz = mat.nonZeros();
StorageIndex m = StorageIndex(mat.rows());
StorageIndex n = StorageIndex(mat.cols());
StorageIndex nnz = StorageIndex(mat.nonZeros());
// Get the recommended value of Alen to be used by colamd
Index Alen = internal::colamd_recommended(nnz, m, n);
StorageIndex Alen = internal::colamd_recommended(nnz, m, n);
// Set the default parameters
double knobs [COLAMD_KNOBS];
Index stats [COLAMD_STATS];
StorageIndex stats [COLAMD_STATS];
internal::colamd_set_defaults(knobs);
IndexVector p(n+1), A(Alen);
for(Index i=0; i <= n; i++) p(i) = mat.outerIndexPtr()[i];
for(Index i=0; i < nnz; i++) A(i) = mat.innerIndexPtr()[i];
for(StorageIndex i=0; i <= n; i++) p(i) = mat.outerIndexPtr()[i];
for(StorageIndex i=0; i < nnz; i++) A(i) = mat.innerIndexPtr()[i];
// Call Colamd routine to compute the ordering
Index info = internal::colamd(m, n, Alen, A.data(), p.data(), knobs, stats);
StorageIndex info = internal::colamd(m, n, Alen, A.data(), p.data(), knobs, stats);
EIGEN_UNUSED_VARIABLE(info);
eigen_assert( info && "COLAMD failed " );
perm.resize(n);
for (Index i = 0; i < n; i++) perm.indices()(p(i)) = i;
for (StorageIndex i = 0; i < n; i++) perm.indices()(p(i)) = i;
}
};