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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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46
unsupported/test/autodiff_scalar.cpp
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@@ -15,36 +15,36 @@
* TODO add more tests!
*/
template<typename Scalar> void check_atan2()
{
template <typename Scalar>
void check_atan2() {
typedef Matrix<Scalar, 1, 1> Deriv1;
typedef AutoDiffScalar<Deriv1> AD;
AD x(internal::random<Scalar>(-3.0, 3.0), Deriv1::UnitX());
using std::exp;
Scalar r = exp(internal::random<Scalar>(-10, 10));
AD s = sin(x), c = cos(x);
AD res = atan2(r*s, r*c);
AD res = atan2(r * s, r * c);
VERIFY_IS_APPROX(res.value(), x.value());
VERIFY_IS_APPROX(res.derivatives(), x.derivatives());
res = atan2(r*s+0, r*c+0);
res = atan2(r * s + 0, r * c + 0);
VERIFY_IS_APPROX(res.value(), x.value());
VERIFY_IS_APPROX(res.derivatives(), x.derivatives());
}
template<typename Scalar> void check_hyperbolic_functions()
{
using std::sinh;
template <typename Scalar>
void check_hyperbolic_functions() {
using std::cosh;
using std::sinh;
using std::tanh;
typedef Matrix<Scalar, 1, 1> Deriv1;
typedef AutoDiffScalar<Deriv1> AD;
Deriv1 p = Deriv1::Random();
AD val(p.x(),Deriv1::UnitX());
AD val(p.x(), Deriv1::UnitX());
Scalar cosh_px = std::cosh(p.x());
AD res1 = tanh(val);
@@ -60,8 +60,8 @@ template<typename Scalar> void check_hyperbolic_functions()
VERIFY_IS_APPROX(res3.derivatives().x(), std::sinh(p.x()));
// Check constant values.
const Scalar sample_point = Scalar(1) / Scalar(3);
val = AD(sample_point,Deriv1::UnitX());
const Scalar sample_point = Scalar(1) / Scalar(3);
val = AD(sample_point, Deriv1::UnitX());
res1 = tanh(val);
VERIFY_IS_APPROX(res1.derivatives().x(), Scalar(0.896629559604914));
@@ -73,8 +73,7 @@ template<typename Scalar> void check_hyperbolic_functions()
}
template <typename Scalar>
void check_limits_specialization()
{
void check_limits_specialization() {
typedef Eigen::Matrix<Scalar, 1, 1> Deriv;
typedef Eigen::AutoDiffScalar<Deriv> AD;
@@ -87,13 +86,12 @@ void check_limits_specialization()
VERIFY(bool(std::is_base_of<B, A>::value));
}
EIGEN_DECLARE_TEST(autodiff_scalar)
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( check_atan2<float>() );
CALL_SUBTEST_2( check_atan2<double>() );
CALL_SUBTEST_3( check_hyperbolic_functions<float>() );
CALL_SUBTEST_4( check_hyperbolic_functions<double>() );
CALL_SUBTEST_5( check_limits_specialization<double>());
EIGEN_DECLARE_TEST(autodiff_scalar) {
for (int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1(check_atan2<float>());
CALL_SUBTEST_2(check_atan2<double>());
CALL_SUBTEST_3(check_hyperbolic_functions<float>());
CALL_SUBTEST_4(check_hyperbolic_functions<double>());
CALL_SUBTEST_5(check_limits_specialization<double>());
}
}