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

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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
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98
bench/BenchSparseUtil.h
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@@ -20,63 +20,51 @@ using namespace Eigen;
#endif
typedef SCALAR Scalar;
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
typedef Matrix<Scalar,Dynamic,1> DenseVector;
typedef Matrix<Scalar, Dynamic, Dynamic> DenseMatrix;
typedef Matrix<Scalar, Dynamic, 1> DenseVector;
typedef SparseMatrix<Scalar> EigenSparseMatrix;
void fillMatrix(float density, int rows, int cols, EigenSparseMatrix& dst)
{
dst.reserve(double(rows)*cols*density);
for(int j = 0; j < cols; j++)
{
for(int i = 0; i < rows; i++)
{
Scalar v = (internal::random<float>(0,1) < density) ? internal::random<Scalar>() : 0;
if (v!=0)
dst.insert(i,j) = v;
void fillMatrix(float density, int rows, int cols, EigenSparseMatrix& dst) {
dst.reserve(double(rows) * cols * density);
for (int j = 0; j < cols; j++) {
for (int i = 0; i < rows; i++) {
Scalar v = (internal::random<float>(0, 1) < density) ? internal::random<Scalar>() : 0;
if (v != 0) dst.insert(i, j) = v;
}
}
dst.finalize();
}
void fillMatrix2(int nnzPerCol, int rows, int cols, EigenSparseMatrix& dst)
{
// std::cout << "alloc " << nnzPerCol*cols << "\n";
dst.reserve(nnzPerCol*cols);
for(int j = 0; j < cols; j++)
{
void fillMatrix2(int nnzPerCol, int rows, int cols, EigenSparseMatrix& dst) {
// std::cout << "alloc " << nnzPerCol*cols << "\n";
dst.reserve(nnzPerCol * cols);
for (int j = 0; j < cols; j++) {
std::set<int> aux;
for(int i = 0; i < nnzPerCol; i++)
{
int k = internal::random<int>(0,rows-1);
while (aux.find(k)!=aux.end())
k = internal::random<int>(0,rows-1);
for (int i = 0; i < nnzPerCol; i++) {
int k = internal::random<int>(0, rows - 1);
while (aux.find(k) != aux.end()) k = internal::random<int>(0, rows - 1);
aux.insert(k);
dst.insert(k,j) = internal::random<Scalar>();
dst.insert(k, j) = internal::random<Scalar>();
}
}
dst.finalize();
}
void eiToDense(const EigenSparseMatrix& src, DenseMatrix& dst)
{
void eiToDense(const EigenSparseMatrix& src, DenseMatrix& dst) {
dst.setZero();
for (int j=0; j<src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it)
dst(it.index(),j) = it.value();
for (int j = 0; j < src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it) dst(it.index(), j) = it.value();
}
#ifndef NOGMM
#include "gmm/gmm.h"
typedef gmm::csc_matrix<Scalar> GmmSparse;
typedef gmm::col_matrix< gmm::wsvector<Scalar> > GmmDynSparse;
void eiToGmm(const EigenSparseMatrix& src, GmmSparse& dst)
{
typedef gmm::col_matrix<gmm::wsvector<Scalar> > GmmDynSparse;
void eiToGmm(const EigenSparseMatrix& src, GmmSparse& dst) {
GmmDynSparse tmp(src.rows(), src.cols());
for (int j=0; j<src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it)
tmp(it.index(),j) = it.value();
for (int j = 0; j < src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it) tmp(it.index(), j) = it.value();
gmm::copy(tmp, dst);
}
#endif
@@ -85,12 +73,10 @@ void eiToGmm(const EigenSparseMatrix& src, GmmSparse& dst)
#include <boost/numeric/mtl/mtl.hpp>
typedef mtl::compressed2D<Scalar, mtl::matrix::parameters<mtl::tag::col_major> > MtlSparse;
typedef mtl::compressed2D<Scalar, mtl::matrix::parameters<mtl::tag::row_major> > MtlSparseRowMajor;
void eiToMtl(const EigenSparseMatrix& src, MtlSparse& dst)
{
void eiToMtl(const EigenSparseMatrix& src, MtlSparse& dst) {
mtl::matrix::inserter<MtlSparse> ins(dst);
for (int j=0; j<src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it)
ins[it.index()][j] = it.value();
for (int j = 0; j < src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it) ins[it.index()][j] = it.value();
}
#endif
@@ -98,20 +84,18 @@ void eiToMtl(const EigenSparseMatrix& src, MtlSparse& dst)
extern "C" {
#include "cs.h"
}
void eiToCSparse(const EigenSparseMatrix& src, cs* &dst)
{
cs* aux = cs_spalloc (0, 0, 1, 1, 1);
for (int j=0; j<src.cols(); ++j)
void eiToCSparse(const EigenSparseMatrix& src, cs*& dst) {
cs* aux = cs_spalloc(0, 0, 1, 1, 1);
for (int j = 0; j < src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it)
if (!cs_entry(aux, it.index(), j, it.value()))
{
if (!cs_entry(aux, it.index(), j, it.value())) {
std::cout << "cs_entry error\n";
exit(2);
}
dst = cs_compress(aux);
// cs_spfree(aux);
dst = cs_compress(aux);
// cs_spfree(aux);
}
#endif // CSPARSE
#endif // CSPARSE
#ifndef NOUBLAS
#include <boost/numeric/ublas/vector.hpp>
@@ -123,22 +107,18 @@ void eiToCSparse(const EigenSparseMatrix& src, cs* &dst)
#include <boost/numeric/ublas/vector_of_vector.hpp>
#include <boost/numeric/ublas/operation.hpp>
typedef boost::numeric::ublas::compressed_matrix<Scalar,boost::numeric::ublas::column_major> UBlasSparse;
typedef boost::numeric::ublas::compressed_matrix<Scalar, boost::numeric::ublas::column_major> UBlasSparse;
void eiToUblas(const EigenSparseMatrix& src, UBlasSparse& dst)
{
void eiToUblas(const EigenSparseMatrix& src, UBlasSparse& dst) {
dst.resize(src.rows(), src.cols(), false);
for (int j=0; j<src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it)
dst(it.index(),j) = it.value();
for (int j = 0; j < src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it) dst(it.index(), j) = it.value();
}
template <typename EigenType, typename UblasType>
void eiToUblasVec(const EigenType& src, UblasType& dst)
{
void eiToUblasVec(const EigenType& src, UblasType& dst) {
dst.resize(src.size());
for (int j=0; j<src.size(); ++j)
dst[j] = src.coeff(j);
for (int j = 0; j < src.size(); ++j) dst[j] = src.coeff(j);
}
#endif