mirror of
https://gitlab.com/libeigen/eigen.git
synced 2024-12-15 07:10:37 +08:00
make Umeyama, and its unit-test, work for me on gcc 4.3
This commit is contained in:
parent
86be59124d
commit
ee92009fd8
@ -64,6 +64,7 @@
|
||||
YOU_CALLED_A_FIXED_SIZE_METHOD_ON_A_DYNAMIC_SIZE_MATRIX_OR_VECTOR,
|
||||
UNALIGNED_LOAD_AND_STORE_OPERATIONS_UNIMPLEMENTED_ON_ALTIVEC,
|
||||
NUMERIC_TYPE_MUST_BE_FLOATING_POINT,
|
||||
NUMERIC_TYPE_MUST_BE_REAL,
|
||||
COEFFICIENT_WRITE_ACCESS_TO_SELFADJOINT_NOT_SUPPORTED,
|
||||
WRITING_TO_TRIANGULAR_PART_WITH_UNIT_DIAGONAL_IS_NOT_SUPPORTED,
|
||||
THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE,
|
||||
|
@ -110,7 +110,7 @@ umeyama(const MatrixBase<Derived>& src, const MatrixBase<OtherDerived>& dst, boo
|
||||
typedef typename ei_traits<TransformationMatrixType>::Scalar Scalar;
|
||||
typedef typename NumTraits<Scalar>::Real RealScalar;
|
||||
|
||||
EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::IsComplex, NUMERIC_TYPE_MUST_BE_FLOATING_POINT)
|
||||
EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::IsComplex, NUMERIC_TYPE_MUST_BE_REAL)
|
||||
EIGEN_STATIC_ASSERT((ei_is_same_type<Scalar, typename ei_traits<OtherDerived>::Scalar>::ret),
|
||||
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
|
||||
|
||||
@ -141,7 +141,7 @@ umeyama(const MatrixBase<Derived>& src, const MatrixBase<OtherDerived>& dst, boo
|
||||
|
||||
// Eq. (36)-(37)
|
||||
const Scalar src_var = src_demean.rowwise().squaredNorm().sum() * one_over_n;
|
||||
const Scalar dst_var = dst_demean.rowwise().squaredNorm().sum() * one_over_n;
|
||||
// const Scalar dst_var = dst_demean.rowwise().squaredNorm().sum() * one_over_n;
|
||||
|
||||
// Eq. (38)
|
||||
const MatrixType sigma = (dst_demean*src_demean.transpose()).lazy() * one_over_n;
|
||||
@ -182,22 +182,4 @@ umeyama(const MatrixBase<Derived>& src, const MatrixBase<OtherDerived>& dst, boo
|
||||
return Rt;
|
||||
}
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
|
||||
/**
|
||||
* This is simply here to prevent the creation of dozens compile time errors for
|
||||
* std::complex types...
|
||||
*/
|
||||
template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols,
|
||||
typename _OtherScalar, int _OtherRows, int _OtherCols, int _OtherOptions, int _OtherMaxRows, int _OtherMaxCols>
|
||||
typename ei_umeyama_transform_matrix_type<Matrix<std::complex<_Scalar>,_Rows,_Cols,_Options,_MaxRows,_MaxCols>,
|
||||
Matrix<std::complex<_OtherScalar>,_OtherRows,_OtherCols,_OtherOptions,_OtherMaxRows,_OtherMaxCols> >::type
|
||||
umeyama(const MatrixBase<Matrix<std::complex<_Scalar>,_Rows,_Cols,_Options,_MaxRows,_MaxCols> >& src,
|
||||
const MatrixBase<Matrix<std::complex<_OtherScalar>,_OtherRows,_OtherCols,_OtherOptions,_OtherMaxRows,_OtherMaxCols> >& dst, bool with_scaling = true)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT(false, NUMERIC_TYPE_MUST_BE_FLOATING_POINT)
|
||||
}
|
||||
|
||||
#endif
|
||||
|
||||
#endif // EIGEN_UMEYAMA_H
|
||||
|
@ -33,17 +33,11 @@
|
||||
|
||||
using namespace Eigen;
|
||||
|
||||
#define VAR_CALL_SUBTEST(...) do { \
|
||||
g_test_stack.push_back(EI_PP_MAKE_STRING(__VA_ARGS__)); \
|
||||
__VA_ARGS__; \
|
||||
g_test_stack.pop_back(); \
|
||||
} while (0)
|
||||
|
||||
// Constructs a random matrix from the unitary group U(size).
|
||||
template <typename T>
|
||||
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> randMatrixUnitary(int size)
|
||||
{
|
||||
typedef typename T Scalar;
|
||||
typedef T Scalar;
|
||||
typedef typename NumTraits<Scalar>::Real RealScalar;
|
||||
|
||||
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> MatrixType;
|
||||
@ -55,58 +49,58 @@ Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> randMatrixUnitary(int size)
|
||||
|
||||
while (!is_unitary && max_tries > 0)
|
||||
{
|
||||
// initialize random matrix
|
||||
// initialize random matrix
|
||||
Q = MatrixType::Random(size, size);
|
||||
|
||||
// orthogonalize columns using the Gram-Schmidt algorithm
|
||||
for (int col = 0; col < size; ++col)
|
||||
{
|
||||
MatrixType::ColXpr colVec = Q.col(col);
|
||||
for (int prevCol = 0; prevCol < col; ++prevCol)
|
||||
{
|
||||
MatrixType::ColXpr prevColVec = Q.col(prevCol);
|
||||
// orthogonalize columns using the Gram-Schmidt algorithm
|
||||
for (int col = 0; col < size; ++col)
|
||||
{
|
||||
typename MatrixType::ColXpr colVec = Q.col(col);
|
||||
for (int prevCol = 0; prevCol < col; ++prevCol)
|
||||
{
|
||||
typename MatrixType::ColXpr prevColVec = Q.col(prevCol);
|
||||
colVec -= colVec.dot(prevColVec)*prevColVec;
|
||||
}
|
||||
Q.col(col) = colVec.normalized();
|
||||
}
|
||||
}
|
||||
Q.col(col) = colVec.normalized();
|
||||
}
|
||||
|
||||
// this additional orthogonalization is not necessary in theory but should enhance
|
||||
// this additional orthogonalization is not necessary in theory but should enhance
|
||||
// the numerical orthogonality of the matrix
|
||||
for (int row = 0; row < size; ++row)
|
||||
{
|
||||
MatrixType::RowXpr rowVec = Q.row(row);
|
||||
for (int prevRow = 0; prevRow < row; ++prevRow)
|
||||
{
|
||||
MatrixType::RowXpr prevRowVec = Q.row(prevRow);
|
||||
rowVec -= rowVec.dot(prevRowVec)*prevRowVec;
|
||||
}
|
||||
Q.row(row) = rowVec.normalized();
|
||||
}
|
||||
for (int row = 0; row < size; ++row)
|
||||
{
|
||||
typename MatrixType::RowXpr rowVec = Q.row(row);
|
||||
for (int prevRow = 0; prevRow < row; ++prevRow)
|
||||
{
|
||||
typename MatrixType::RowXpr prevRowVec = Q.row(prevRow);
|
||||
rowVec -= rowVec.dot(prevRowVec)*prevRowVec;
|
||||
}
|
||||
Q.row(row) = rowVec.normalized();
|
||||
}
|
||||
|
||||
// final check
|
||||
// final check
|
||||
is_unitary = Q.isUnitary();
|
||||
--max_tries;
|
||||
}
|
||||
|
||||
if (max_tries == 0)
|
||||
throw std::runtime_error("randMatrixUnitary: Could not construct unitary matrix!");
|
||||
ei_assert(false && "randMatrixUnitary: Could not construct unitary matrix!");
|
||||
|
||||
return Q;
|
||||
return Q;
|
||||
}
|
||||
|
||||
// Constructs a random matrix from the special unitary group SU(size).
|
||||
template <typename T>
|
||||
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> randMatrixSpecialUnitary(int size)
|
||||
{
|
||||
typedef typename T Scalar;
|
||||
typedef T Scalar;
|
||||
typedef typename NumTraits<Scalar>::Real RealScalar;
|
||||
|
||||
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> MatrixType;
|
||||
|
||||
// initialize unitary matrix
|
||||
MatrixType Q = randMatrixUnitary<Scalar>(size);
|
||||
// initialize unitary matrix
|
||||
MatrixType Q = randMatrixUnitary<Scalar>(size);
|
||||
|
||||
// tweak the first column to make the determinant be 1
|
||||
// tweak the first column to make the determinant be 1
|
||||
Q.col(0) *= ei_conj(Q.determinant());
|
||||
|
||||
return Q;
|
||||
@ -191,13 +185,13 @@ void test_umeyama()
|
||||
CALL_SUBTEST(run_test<MatrixXf>(dim, num_elements));
|
||||
}
|
||||
|
||||
VAR_CALL_SUBTEST(run_fixed_size_test<float, 2>(num_elements));
|
||||
VAR_CALL_SUBTEST(run_fixed_size_test<float, 3>(num_elements));
|
||||
VAR_CALL_SUBTEST(run_fixed_size_test<float, 4>(num_elements));
|
||||
CALL_SUBTEST((run_fixed_size_test<float, 2>(num_elements)));
|
||||
CALL_SUBTEST((run_fixed_size_test<float, 3>(num_elements)));
|
||||
CALL_SUBTEST((run_fixed_size_test<float, 4>(num_elements)));
|
||||
|
||||
VAR_CALL_SUBTEST(run_fixed_size_test<double, 2>(num_elements));
|
||||
VAR_CALL_SUBTEST(run_fixed_size_test<double, 3>(num_elements));
|
||||
VAR_CALL_SUBTEST(run_fixed_size_test<double, 4>(num_elements));
|
||||
CALL_SUBTEST((run_fixed_size_test<double, 2>(num_elements)));
|
||||
CALL_SUBTEST((run_fixed_size_test<double, 3>(num_elements)));
|
||||
CALL_SUBTEST((run_fixed_size_test<double, 4>(num_elements)));
|
||||
}
|
||||
|
||||
// Those two calls don't compile and result in meaningful error messages!
|
||||
|
Loading…
Reference in New Issue
Block a user