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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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54
test/num_dimensions.cpp
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@@ -10,14 +10,13 @@
#include "main.h"
#include <Eigen/SparseCore>
template<int ExpectedDim,typename Xpr>
void check_dim(const Xpr& ) {
STATIC_CHECK( Xpr::NumDimensions == ExpectedDim );
template <int ExpectedDim, typename Xpr>
void check_dim(const Xpr&) {
STATIC_CHECK(Xpr::NumDimensions == ExpectedDim);
}
template<template <typename,int,int> class Object>
void map_num_dimensions()
{
template <template <typename, int, int> class Object>
void map_num_dimensions() {
typedef Object<double, 1, 1> ArrayScalarType;
typedef Object<double, 2, 1> ArrayVectorType;
typedef Object<double, 1, 2> TransposeArrayVectorType;
@@ -51,34 +50,33 @@ void map_num_dimensions()
STATIC_CHECK(DynamicArrayMap::NumDimensions == 2);
}
template<typename Scalar, int Rows, int Cols>
using TArray = Array<Scalar,Rows,Cols>;
template <typename Scalar, int Rows, int Cols>
using TArray = Array<Scalar, Rows, Cols>;
template<typename Scalar, int Rows, int Cols>
using TMatrix = Matrix<Scalar,Rows,Cols>;
template <typename Scalar, int Rows, int Cols>
using TMatrix = Matrix<Scalar, Rows, Cols>;
EIGEN_DECLARE_TEST(num_dimensions)
{
EIGEN_DECLARE_TEST(num_dimensions) {
int n = 10;
ArrayXXd A(n,n);
CALL_SUBTEST( check_dim<2>(A) );
CALL_SUBTEST( check_dim<2>(A.block(1,1,2,2)) );
CALL_SUBTEST( check_dim<1>(A.col(1)) );
CALL_SUBTEST( check_dim<1>(A.row(1)) );
ArrayXXd A(n, n);
CALL_SUBTEST(check_dim<2>(A));
CALL_SUBTEST(check_dim<2>(A.block(1, 1, 2, 2)));
CALL_SUBTEST(check_dim<1>(A.col(1)));
CALL_SUBTEST(check_dim<1>(A.row(1)));
MatrixXd M(n,n);
CALL_SUBTEST( check_dim<0>(M.row(1)*M.col(1)) );
MatrixXd M(n, n);
CALL_SUBTEST(check_dim<0>(M.row(1) * M.col(1)));
SparseMatrix<double> S(n,n);
CALL_SUBTEST( check_dim<2>(S) );
CALL_SUBTEST( check_dim<2>(S.block(1,1,2,2)) );
CALL_SUBTEST( check_dim<1>(S.col(1)) );
CALL_SUBTEST( check_dim<1>(S.row(1)) );
SparseMatrix<double> S(n, n);
CALL_SUBTEST(check_dim<2>(S));
CALL_SUBTEST(check_dim<2>(S.block(1, 1, 2, 2)));
CALL_SUBTEST(check_dim<1>(S.col(1)));
CALL_SUBTEST(check_dim<1>(S.row(1)));
SparseVector<double> s(n);
CALL_SUBTEST( check_dim<1>(s) );
CALL_SUBTEST( check_dim<1>(s.head(2)) );
CALL_SUBTEST(check_dim<1>(s));
CALL_SUBTEST(check_dim<1>(s.head(2)));
CALL_SUBTEST( map_num_dimensions<TArray>() );
CALL_SUBTEST( map_num_dimensions<TMatrix>() );
CALL_SUBTEST(map_num_dimensions<TArray>());
CALL_SUBTEST(map_num_dimensions<TMatrix>());
}