Clang-format tests, examples, libraries, benchmarks, etc.

This commit is contained in:
Antonio Sánchez
2023-12-05 21:22:55 +00:00
committed by Rasmus Munk Larsen
parent 3252ecc7a4
commit 46e9cdb7fe
876 changed files with 33453 additions and 37795 deletions

View File

@@ -29,12 +29,7 @@
#include <Eigen/LU>
#include <Eigen/Sparse>
enum {
ForceNonZeroDiag = 1,
MakeLowerTriangular = 2,
MakeUpperTriangular = 4,
ForceRealDiag = 8
};
enum { ForceNonZeroDiag = 1, MakeLowerTriangular = 2, MakeUpperTriangular = 4, ForceRealDiag = 8 };
/* Initializes both a sparse and dense matrix with same random values,
* and a ratio of \a density non zero entries.
@@ -43,113 +38,87 @@ enum {
* \param zeroCoords and nonzeroCoords allows to get the coordinate lists of the non zero,
* and zero coefficients respectively.
*/
template<typename Scalar,int Opt1,int Opt2,typename StorageIndex> void
initSparse(double density,
Matrix<Scalar,Dynamic,Dynamic,Opt1>& refMat,
SparseMatrix<Scalar,Opt2,StorageIndex>& sparseMat,
int flags = 0,
std::vector<Matrix<StorageIndex,2,1> >* zeroCoords = 0,
std::vector<Matrix<StorageIndex,2,1> >* nonzeroCoords = 0)
{
enum { IsRowMajor = SparseMatrix<Scalar,Opt2,StorageIndex>::IsRowMajor };
template <typename Scalar, int Opt1, int Opt2, typename StorageIndex>
void initSparse(double density, Matrix<Scalar, Dynamic, Dynamic, Opt1>& refMat,
SparseMatrix<Scalar, Opt2, StorageIndex>& sparseMat, int flags = 0,
std::vector<Matrix<StorageIndex, 2, 1> >* zeroCoords = 0,
std::vector<Matrix<StorageIndex, 2, 1> >* nonzeroCoords = 0) {
enum { IsRowMajor = SparseMatrix<Scalar, Opt2, StorageIndex>::IsRowMajor };
sparseMat.setZero();
//sparseMat.reserve(int(refMat.rows()*refMat.cols()*density));
// sparseMat.reserve(int(refMat.rows()*refMat.cols()*density));
int nnz = static_cast<int>((1.5 * density) * static_cast<double>(IsRowMajor ? refMat.cols() : refMat.rows()));
sparseMat.reserve(VectorXi::Constant(IsRowMajor ? refMat.rows() : refMat.cols(), nnz));
Index insert_count = 0;
for(Index j=0; j<sparseMat.outerSize(); j++)
{
//sparseMat.startVec(j);
for(Index i=0; i<sparseMat.innerSize(); i++)
{
for (Index j = 0; j < sparseMat.outerSize(); j++) {
// sparseMat.startVec(j);
for (Index i = 0; i < sparseMat.innerSize(); i++) {
Index ai(i), aj(j);
if(IsRowMajor)
std::swap(ai,aj);
Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
if ((flags&ForceNonZeroDiag) && (i==j))
{
if (IsRowMajor) std::swap(ai, aj);
Scalar v = (internal::random<double>(0, 1) < density) ? internal::random<Scalar>() : Scalar(0);
if ((flags & ForceNonZeroDiag) && (i == j)) {
// FIXME: the following is too conservative
v = internal::random<Scalar>()*Scalar(3.);
v = v*v;
if(numext::real(v)>0) v += Scalar(5);
else v -= Scalar(5);
v = internal::random<Scalar>() * Scalar(3.);
v = v * v;
if (numext::real(v) > 0)
v += Scalar(5);
else
v -= Scalar(5);
}
if ((flags & MakeLowerTriangular) && aj>ai)
if ((flags & MakeLowerTriangular) && aj > ai)
v = Scalar(0);
else if ((flags & MakeUpperTriangular) && aj<ai)
else if ((flags & MakeUpperTriangular) && aj < ai)
v = Scalar(0);
if ((flags&ForceRealDiag) && (i==j))
v = numext::real(v);
if ((flags & ForceRealDiag) && (i == j)) v = numext::real(v);
if (!numext::is_exactly_zero(v))
{
//sparseMat.insertBackByOuterInner(j,i) = v;
sparseMat.insertByOuterInner(j,i) = v;
if (!numext::is_exactly_zero(v)) {
// sparseMat.insertBackByOuterInner(j,i) = v;
sparseMat.insertByOuterInner(j, i) = v;
++insert_count;
if (nonzeroCoords)
nonzeroCoords->push_back(Matrix<StorageIndex,2,1> (ai,aj));
if (nonzeroCoords) nonzeroCoords->push_back(Matrix<StorageIndex, 2, 1>(ai, aj));
} else if (zeroCoords) {
zeroCoords->push_back(Matrix<StorageIndex, 2, 1>(ai, aj));
}
else if (zeroCoords)
{
zeroCoords->push_back(Matrix<StorageIndex,2,1> (ai,aj));
}
refMat(ai,aj) = v;
refMat(ai, aj) = v;
// make sure we only insert as many as the sparse matrix supports
if(insert_count == NumTraits<StorageIndex>::highest()) return;
if (insert_count == NumTraits<StorageIndex>::highest()) return;
}
}
//sparseMat.finalize();
// sparseMat.finalize();
}
template<typename Scalar,int Options,typename Index> void
initSparse(double density,
Matrix<Scalar,Dynamic,1>& refVec,
SparseVector<Scalar,Options,Index>& sparseVec,
std::vector<int>* zeroCoords = 0,
std::vector<int>* nonzeroCoords = 0)
{
sparseVec.reserve(int(refVec.size()*density));
template <typename Scalar, int Options, typename Index>
void initSparse(double density, Matrix<Scalar, Dynamic, 1>& refVec, SparseVector<Scalar, Options, Index>& sparseVec,
std::vector<int>* zeroCoords = 0, std::vector<int>* nonzeroCoords = 0) {
sparseVec.reserve(int(refVec.size() * density));
sparseVec.setZero();
for(int i=0; i<refVec.size(); i++)
{
Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
if (!numext::is_exactly_zero(v))
{
for (int i = 0; i < refVec.size(); i++) {
Scalar v = (internal::random<double>(0, 1) < density) ? internal::random<Scalar>() : Scalar(0);
if (!numext::is_exactly_zero(v)) {
sparseVec.insertBack(i) = v;
if (nonzeroCoords)
nonzeroCoords->push_back(i);
}
else if (zeroCoords)
zeroCoords->push_back(i);
if (nonzeroCoords) nonzeroCoords->push_back(i);
} else if (zeroCoords)
zeroCoords->push_back(i);
refVec[i] = v;
}
}
template<typename Scalar,int Options,typename Index> void
initSparse(double density,
Matrix<Scalar,1,Dynamic>& refVec,
SparseVector<Scalar,Options,Index>& sparseVec,
std::vector<int>* zeroCoords = 0,
std::vector<int>* nonzeroCoords = 0)
{
sparseVec.reserve(int(refVec.size()*density));
template <typename Scalar, int Options, typename Index>
void initSparse(double density, Matrix<Scalar, 1, Dynamic>& refVec, SparseVector<Scalar, Options, Index>& sparseVec,
std::vector<int>* zeroCoords = 0, std::vector<int>* nonzeroCoords = 0) {
sparseVec.reserve(int(refVec.size() * density));
sparseVec.setZero();
for(int i=0; i<refVec.size(); i++)
{
Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
if (v!=Scalar(0))
{
for (int i = 0; i < refVec.size(); i++) {
Scalar v = (internal::random<double>(0, 1) < density) ? internal::random<Scalar>() : Scalar(0);
if (v != Scalar(0)) {
sparseVec.insertBack(i) = v;
if (nonzeroCoords)
nonzeroCoords->push_back(i);
}
else if (zeroCoords)
zeroCoords->push_back(i);
if (nonzeroCoords) nonzeroCoords->push_back(i);
} else if (zeroCoords)
zeroCoords->push_back(i);
refVec[i] = v;
}
}
#endif // EIGEN_TESTSPARSE_H
#endif // EIGEN_TESTSPARSE_H