devtools/eigen
1
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2026-04-10 11:34:33 +08:00
Code Issues Packages Projects Releases Wiki Activity

merge with default branch

Browse Source
This commit is contained in:
Gael Guennebaud
2014-04-22 17:00:38 +02:00
parent 5c5231ab71 e5d0cb54a5
commit 934ce93886
19 changed files with 108 additions and 24 deletions
Download Patch File Download Diff File Expand all files Collapse all files

3
test/CMakeLists.txt
View File

@@ -315,6 +315,9 @@ find_package(CUDA)
if(CUDA_FOUND)
set(CUDA_PROPAGATE_HOST_FLAGS OFF)
if("${CMAKE_CXX_COMPILER_ID}" STREQUAL "Clang")
set(CUDA_NVCC_FLAGS "-ccbin /usr/bin/clang" CACHE STRING "nvcc flags" FORCE)
endif()
cuda_include_directories(${CMAKE_CURRENT_BINARY_DIR})
set(EIGEN_ADD_TEST_FILENAME_EXTENSION "cu")

4
test/cholesky.cpp
View File

@@ -82,10 +82,6 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
symm += a1 * a1.adjoint();
}
// to test if really Cholesky only uses the upper triangular part, uncomment the following
// FIXME: currently that fails !!
//symm.template part<StrictlyLower>().setZero();
{
SquareMatrixType symmUp = symm.template triangularView<Upper>();
SquareMatrixType symmLo = symm.template triangularView<Lower>();

2
test/cuda_basic.cu
View File

@@ -129,7 +129,7 @@ void test_cuda_basic()
CALL_SUBTEST( run_and_compare_to_cuda(prod<Matrix4f,Vector4f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(diagonal<Matrix3f,Vector3f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_c<uda(diagonal<Matrix4f,Vector4f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(diagonal<Matrix4f,Vector4f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(eigenvalues<Matrix3f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(eigenvalues<Matrix2f>(), nthreads, in, out) );

13
test/eigensolver_generic.cpp
View File

@@ -121,5 +121,18 @@ void test_eigensolver_generic()
}
);
// regression test for bug 793
#ifdef EIGEN_TEST_PART_2
{
MatrixXd a(3,3);
a << 0, 0, 1,
1, 1, 1,
1, 1e+200, 1;
Eigen::EigenSolver<MatrixXd> eig(a);
VERIFY_IS_APPROX(a * eig.pseudoEigenvectors(), eig.pseudoEigenvectors() * eig.pseudoEigenvalueMatrix());
VERIFY_IS_APPROX(a * eig.eigenvectors(), eig.eigenvectors() * eig.eigenvalues().asDiagonal());
}
#endif
TEST_SET_BUT_UNUSED_VARIABLE(s)
}