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Fix compatibility with Eigen3 5.0.0 and bump version to 0.10.1 #105

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Merged
merged 3 commits into from
Oct 8, 2025
Merged

Fix compatibility with Eigen3 5.0.0 and bump version to 0.10.1 #105

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47ce8d2
Fix typo in if related to Eigen3::Eigen target and bump version to 0.…
traversaro Oct 7, 2025
bdeb794
Fix jacobiSvd invocation with Eigen3 5.0.0
traversaro Oct 7, 2025
4dc452e
Add Eigen3 to the public dependencies of the CMake config file
traversaro Oct 8, 2025
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4 changes: 2 additions & 2 deletions CMakeLists.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,7 @@ cmake_minimum_required(VERSION 3.5)

project(BayesFilters
LANGUAGES CXX
VERSION 0.10.0)
VERSION 0.10.1)

set(CMAKE_CXX_STANDARD 11)

Expand Down Expand Up @@ -77,7 +77,7 @@ install_basic_package_files(${PROJECT_NAME}
NO_SET_AND_CHECK_MACRO
VARS_PREFIX ${PROJECT_NAME}
NO_CHECK_REQUIRED_COMPONENTS_MACRO
DEPENDENCIES Threads)
DEPENDENCIES Eigen3 Threads)

# Add the uninstall target
include(AddUninstallTarget)
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2 changes: 1 addition & 1 deletion src/BayesFilters/CMakeLists.txt
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Expand Up @@ -155,7 +155,7 @@ set_target_properties(${LIBRARY_TARGET_NAME} PROPERTIES VERSION ${${PROJEC

target_include_directories(${LIBRARY_TARGET_NAME} PUBLIC "$<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}/include>"
"$<INSTALL_INTERFACE:$<INSTALL_PREFIX>/${CMAKE_INSTALL_INCLUDEDIR}>")
if(NOT TARGET Eigen3)
if(NOT TARGET Eigen3::Eigen)
target_include_directories(${LIBRARY_TARGET_NAME} PUBLIC ${EIGEN3_INCLUDE_DIR})

target_link_libraries(${LIBRARY_TARGET_NAME} PUBLIC Threads::Threads ${CMAKE_THREAD_LIBS_INIT})
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5 changes: 4 additions & 1 deletion src/BayesFilters/src/sigma_point.cpp
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Expand Up @@ -87,8 +87,11 @@ MatrixXd bfl::sigma_point::sigma_point(const GaussianMixture& state, const doubl

for (std::size_t i = 0; i < state.components; i++)
{
#if EIGEN_VERSION_AT_LEAST(5,0,0)
JacobiSVD<MatrixXd, Eigen::ComputeThinU> svd = state.covariance(i).jacobiSvd<Eigen::ComputeThinU>();
#else
JacobiSVD<MatrixXd> svd = state.covariance(i).jacobiSvd(ComputeThinU);

#endif
MatrixXd A = svd.matrixU() * svd.singularValues().cwiseSqrt().asDiagonal();

Ref<MatrixXd> sp = sigma_points.middleCols(((state.dim_covariance * 2) + 1) * i, ((state.dim_covariance * 2) + 1));
Expand Down