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authorGravatar Chen-Pang He <jdh8@ms63.hinet.net>2013-07-15 00:43:14 +0800
committerGravatar Chen-Pang He <jdh8@ms63.hinet.net>2013-07-15 00:43:14 +0800
commit9be658f7015161989b7ecccd70fd050ce563cad9 (patch)
tree070c28b551973bffe3452d40d8a6b727559dfc71 /unsupported/test/matrix_functions.h
parentb8f0364a1c56784fa666c783e21c4bd1b218b9b0 (diff)
generateTestMatrix can use processTriangularMatrix
Diffstat (limited to 'unsupported/test/matrix_functions.h')
-rw-r--r--unsupported/test/matrix_functions.h41
1 files changed, 31 insertions, 10 deletions
diff --git a/unsupported/test/matrix_functions.h b/unsupported/test/matrix_functions.h
index 5817caef6..295da16b6 100644
--- a/unsupported/test/matrix_functions.h
+++ b/unsupported/test/matrix_functions.h
@@ -10,27 +10,48 @@
#include "main.h"
#include <unsupported/Eigen/MatrixFunctions>
+// For complex matrices, any matrix is fine.
+template<typename MatrixType, int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex>
+struct processTriangularMatrix
+{
+ static void run(MatrixType&, MatrixType&, const MatrixType&)
+ { }
+};
+
+// For real matrices, make sure none of the eigenvalues are negative.
+template<typename MatrixType>
+struct processTriangularMatrix<MatrixType,0>
+{
+ static void run(MatrixType& m, MatrixType& T, const MatrixType& U)
+ {
+ typedef typename MatrixType::Index Index;
+ const Index size = m.cols();
+
+ for (Index i=0; i < size; ++i) {
+ if (i == size - 1 || T.coeff(i+1,i) == 0)
+ T.coeffRef(i,i) = std::abs(T.coeff(i,i));
+ else
+ ++i;
+ }
+ m = U * T * U.transpose();
+ }
+};
+
template <typename MatrixType, int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex>
struct generateTestMatrix;
-// for real matrices, make sure none of the eigenvalues are negative
template <typename MatrixType>
struct generateTestMatrix<MatrixType,0>
{
static void run(MatrixType& result, typename MatrixType::Index size)
{
- MatrixType mat = MatrixType::Random(size, size);
- EigenSolver<MatrixType> es(mat);
- typename EigenSolver<MatrixType>::EigenvalueType eivals = es.eigenvalues();
- for (typename MatrixType::Index i = 0; i < size; ++i) {
- if (eivals(i).imag() == 0 && eivals(i).real() < 0)
- eivals(i) = -eivals(i);
- }
- result = (es.eigenvectors() * eivals.asDiagonal() * es.eigenvectors().inverse()).real();
+ result = MatrixType::Random(size, size);
+ RealSchur<MatrixType> schur(result);
+ MatrixType T = schur.matrixT();
+ processTriangularMatrix<MatrixType>::run(result, T, schur.matrixU());
}
};
-// for complex matrices, any matrix is fine
template <typename MatrixType>
struct generateTestMatrix<MatrixType,1>
{