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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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106
test/nesting_ops.cpp
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@@ -13,95 +13,89 @@
#include "main.h"
template <int N, typename XprType>
void use_n_times(const XprType &xpr)
{
typename internal::nested_eval<XprType,N>::type mat(xpr);
void use_n_times(const XprType& xpr) {
typename internal::nested_eval<XprType, N>::type mat(xpr);
typename XprType::PlainObject res(mat.rows(), mat.cols());
nb_temporaries--; // remove res
nb_temporaries--; // remove res
res.setZero();
for(int i=0; i<N; ++i)
res += mat;
for (int i = 0; i < N; ++i) res += mat;
}
template <int N, typename ReferenceType, typename XprType>
bool verify_eval_type(const XprType &, const ReferenceType&)
{
typedef typename internal::nested_eval<XprType,N>::type EvalType;
bool verify_eval_type(const XprType&, const ReferenceType&) {
typedef typename internal::nested_eval<XprType, N>::type EvalType;
return internal::is_same<internal::remove_all_t<EvalType>, internal::remove_all_t<ReferenceType>>::value;
}
template <typename MatrixType> void run_nesting_ops_1(const MatrixType& _m)
{
typename internal::nested_eval<MatrixType,2>::type m(_m);
template <typename MatrixType>
void run_nesting_ops_1(const MatrixType& _m) {
typename internal::nested_eval<MatrixType, 2>::type m(_m);
// Make really sure that we are in debug mode!
VERIFY_RAISES_ASSERT(eigen_assert(false));
// The only intention of these tests is to ensure that this code does
// not trigger any asserts or segmentation faults... more to come.
VERIFY_IS_APPROX( (m.transpose() * m).diagonal().sum(), (m.transpose() * m).diagonal().sum() );
VERIFY_IS_APPROX( (m.transpose() * m).diagonal().array().abs().sum(), (m.transpose() * m).diagonal().array().abs().sum() );
VERIFY_IS_APPROX((m.transpose() * m).diagonal().sum(), (m.transpose() * m).diagonal().sum());
VERIFY_IS_APPROX((m.transpose() * m).diagonal().array().abs().sum(),
(m.transpose() * m).diagonal().array().abs().sum());
VERIFY_IS_APPROX( (m.transpose() * m).array().abs().sum(), (m.transpose() * m).array().abs().sum() );
VERIFY_IS_APPROX((m.transpose() * m).array().abs().sum(), (m.transpose() * m).array().abs().sum());
}
template <typename MatrixType> void run_nesting_ops_2(const MatrixType& _m)
{
template <typename MatrixType>
void run_nesting_ops_2(const MatrixType& _m) {
typedef typename MatrixType::Scalar Scalar;
Index rows = _m.rows();
Index cols = _m.cols();
MatrixType m1 = MatrixType::Random(rows,cols);
Matrix<Scalar,MatrixType::RowsAtCompileTime,MatrixType::ColsAtCompileTime,ColMajor> m2;
MatrixType m1 = MatrixType::Random(rows, cols);
Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime, ColMajor> m2;
if((MatrixType::SizeAtCompileTime==Dynamic))
{
VERIFY_EVALUATION_COUNT( use_n_times<1>(m1 + m1*m1), 1 );
VERIFY_EVALUATION_COUNT( use_n_times<10>(m1 + m1*m1), 1 );
if ((MatrixType::SizeAtCompileTime == Dynamic)) {
VERIFY_EVALUATION_COUNT(use_n_times<1>(m1 + m1 * m1), 1);
VERIFY_EVALUATION_COUNT(use_n_times<10>(m1 + m1 * m1), 1);
VERIFY_EVALUATION_COUNT( use_n_times<1>(m1.template triangularView<Lower>().solve(m1.col(0))), 1 );
VERIFY_EVALUATION_COUNT( use_n_times<10>(m1.template triangularView<Lower>().solve(m1.col(0))), 1 );
VERIFY_EVALUATION_COUNT(use_n_times<1>(m1.template triangularView<Lower>().solve(m1.col(0))), 1);
VERIFY_EVALUATION_COUNT(use_n_times<10>(m1.template triangularView<Lower>().solve(m1.col(0))), 1);
VERIFY_EVALUATION_COUNT( use_n_times<1>(Scalar(2)*m1.template triangularView<Lower>().solve(m1.col(0))), 2 ); // FIXME could be one by applying the scaling in-place on the solve result
VERIFY_EVALUATION_COUNT( use_n_times<1>(m1.col(0)+m1.template triangularView<Lower>().solve(m1.col(0))), 2 ); // FIXME could be one by adding m1.col() inplace
VERIFY_EVALUATION_COUNT( use_n_times<10>(m1.col(0)+m1.template triangularView<Lower>().solve(m1.col(0))), 2 );
VERIFY_EVALUATION_COUNT(use_n_times<1>(Scalar(2) * m1.template triangularView<Lower>().solve(m1.col(0))),
2); // FIXME could be one by applying the scaling in-place on the solve result
VERIFY_EVALUATION_COUNT(use_n_times<1>(m1.col(0) + m1.template triangularView<Lower>().solve(m1.col(0))),
2); // FIXME could be one by adding m1.col() inplace
VERIFY_EVALUATION_COUNT(use_n_times<10>(m1.col(0) + m1.template triangularView<Lower>().solve(m1.col(0))), 2);
}
{
VERIFY( verify_eval_type<10>(m1, m1) );
if(!NumTraits<Scalar>::IsComplex)
{
VERIFY( verify_eval_type<3>(2*m1, 2*m1) );
VERIFY( verify_eval_type<4>(2*m1, m1) );
VERIFY(verify_eval_type<10>(m1, m1));
if (!NumTraits<Scalar>::IsComplex) {
VERIFY(verify_eval_type<3>(2 * m1, 2 * m1));
VERIFY(verify_eval_type<4>(2 * m1, m1));
} else {
VERIFY(verify_eval_type<2>(2 * m1, 2 * m1));
VERIFY(verify_eval_type<3>(2 * m1, m1));
}
else
{
VERIFY( verify_eval_type<2>(2*m1, 2*m1) );
VERIFY( verify_eval_type<3>(2*m1, m1) );
}
VERIFY( verify_eval_type<2>(m1+m1, m1+m1) );
VERIFY( verify_eval_type<3>(m1+m1, m1) );
VERIFY( verify_eval_type<1>(m1*m1.transpose(), m2) );
VERIFY( verify_eval_type<1>(m1*(m1+m1).transpose(), m2) );
VERIFY( verify_eval_type<2>(m1*m1.transpose(), m2) );
VERIFY( verify_eval_type<1>(m1+m1*m1, m1) );
VERIFY(verify_eval_type<2>(m1 + m1, m1 + m1));
VERIFY(verify_eval_type<3>(m1 + m1, m1));
VERIFY(verify_eval_type<1>(m1 * m1.transpose(), m2));
VERIFY(verify_eval_type<1>(m1 * (m1 + m1).transpose(), m2));
VERIFY(verify_eval_type<2>(m1 * m1.transpose(), m2));
VERIFY(verify_eval_type<1>(m1 + m1 * m1, m1));
VERIFY( verify_eval_type<1>(m1.template triangularView<Lower>().solve(m1), m1) );
VERIFY( verify_eval_type<1>(m1+m1.template triangularView<Lower>().solve(m1), m1) );
VERIFY(verify_eval_type<1>(m1.template triangularView<Lower>().solve(m1), m1));
VERIFY(verify_eval_type<1>(m1 + m1.template triangularView<Lower>().solve(m1), m1));
}
}
EIGEN_DECLARE_TEST(nesting_ops)
{
CALL_SUBTEST_1(run_nesting_ops_1(MatrixXf::Random(25,25)));
CALL_SUBTEST_2(run_nesting_ops_1(MatrixXcd::Random(25,25)));
EIGEN_DECLARE_TEST(nesting_ops) {
CALL_SUBTEST_1(run_nesting_ops_1(MatrixXf::Random(25, 25)));
CALL_SUBTEST_2(run_nesting_ops_1(MatrixXcd::Random(25, 25)));
CALL_SUBTEST_3(run_nesting_ops_1(Matrix4f::Random()));
CALL_SUBTEST_4(run_nesting_ops_1(Matrix2d::Random()));
Index s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
CALL_SUBTEST_1( run_nesting_ops_2(MatrixXf(s,s)) );
CALL_SUBTEST_2( run_nesting_ops_2(MatrixXcd(s,s)) );
CALL_SUBTEST_3( run_nesting_ops_2(Matrix4f()) );
CALL_SUBTEST_4( run_nesting_ops_2(Matrix2d()) );
Index s = internal::random<int>(1, EIGEN_TEST_MAX_SIZE);
CALL_SUBTEST_1(run_nesting_ops_2(MatrixXf(s, s)));
CALL_SUBTEST_2(run_nesting_ops_2(MatrixXcd(s, s)));
CALL_SUBTEST_3(run_nesting_ops_2(Matrix4f()));
CALL_SUBTEST_4(run_nesting_ops_2(Matrix2d()));
TEST_SET_BUT_UNUSED_VARIABLE(s)
}