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authorGravatar Gael Guennebaud <g.gael@free.fr>2008-10-03 13:22:54 +0000
committerGravatar Gael Guennebaud <g.gael@free.fr>2008-10-03 13:22:54 +0000
commit1fc503e3ce7dd57aef11200149c61ffefcc4797e (patch)
treec31797f2b578a84317c190903000d2a41d5fdbd5
parentd907cd4410618628be0ab0f00d7e320014c61555 (diff)
add EigenSolver::eigenvectors() method for non symmetric matrices.
However, for matrices larger than 5, it seems there is constantly a quite large error for a very few coefficients. I don't what's going on, but that's certainely not due to numerical issues only. (also note that the test with the pseudo eigenvectors fails the same way)
-rw-r--r--Eigen/src/QR/EigenSolver.h45
-rw-r--r--test/eigensolver.cpp20
2 files changed, 56 insertions, 9 deletions
diff --git a/Eigen/src/QR/EigenSolver.h b/Eigen/src/QR/EigenSolver.h
index 1b392cbb9..d7d891951 100644
--- a/Eigen/src/QR/EigenSolver.h
+++ b/Eigen/src/QR/EigenSolver.h
@@ -48,6 +48,7 @@ template<typename _MatrixType> class EigenSolver
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef std::complex<RealScalar> Complex;
typedef Matrix<Complex, MatrixType::ColsAtCompileTime, 1> EigenvalueType;
+ typedef Matrix<Complex, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime> EigenvectorType;
typedef Matrix<RealScalar, MatrixType::ColsAtCompileTime, 1> RealVectorType;
typedef Matrix<RealScalar, Dynamic, 1> RealVectorTypeX;
@@ -58,8 +59,8 @@ template<typename _MatrixType> class EigenSolver
compute(matrix);
}
- // TODO compute the complex eigen vectors
- // MatrixType eigenvectors(void) const { return m_eivec; }
+
+ EigenvectorType eigenvectors(void) const;
/** \returns a real matrix V of pseudo eigenvectors.
*
@@ -94,10 +95,6 @@ template<typename _MatrixType> class EigenSolver
*/
const MatrixType& pseudoEigenvectors() const { return m_eivec; }
- /** \returns the real block diagonal matrix D of the eigenvalues.
- *
- * See pseudoEigenvectors() for the details.
- */
MatrixType pseudoEigenvalueMatrix() const;
/** \returns the eigenvalues as a column vector */
@@ -115,6 +112,10 @@ template<typename _MatrixType> class EigenSolver
EigenvalueType m_eivalues;
};
+/** \returns the real block diagonal matrix D of the eigenvalues.
+ *
+ * See pseudoEigenvectors() for the details.
+ */
template<typename MatrixType>
MatrixType EigenSolver<MatrixType>::pseudoEigenvalueMatrix() const
{
@@ -134,6 +135,38 @@ MatrixType EigenSolver<MatrixType>::pseudoEigenvalueMatrix() const
return matD;
}
+/** \returns the normalized complex eigenvectors as a matrix of column vectors.
+ *
+ * \sa eigenvalues(), pseudoEigenvectors()
+ */
+template<typename MatrixType>
+typename EigenSolver<MatrixType>::EigenvectorType EigenSolver<MatrixType>::eigenvectors(void) const
+{
+ int n = m_eivec.cols();
+ EigenvectorType matV(n,n);
+ for (int j=0; j<n; j++)
+ {
+ if (ei_isMuchSmallerThan(ei_abs(ei_imag(m_eivalues.coeff(j))), ei_abs(ei_real(m_eivalues.coeff(j)))))
+ {
+ // we have a real eigen value
+ matV.col(j) = m_eivec.col(j);
+ }
+ else
+ {
+ // we have a pair of complex eigen values
+ for (int i=0; i<n; i++)
+ {
+ matV.coeffRef(i,j) = Complex(m_eivec.coeff(i,j), m_eivec.coeff(i,j+1));
+ matV.coeffRef(i,j+1) = Complex(m_eivec.coeff(i,j), -m_eivec.coeff(i,j+1));
+ }
+ matV.col(j).normalize();
+ matV.col(j+1).normalize();
+ j++;
+ }
+ }
+ return matV;
+}
+
template<typename MatrixType>
void EigenSolver<MatrixType>::compute(const MatrixType& matrix)
{
diff --git a/test/eigensolver.cpp b/test/eigensolver.cpp
index 9ede071f0..fed6ba9ba 100644
--- a/test/eigensolver.cpp
+++ b/test/eigensolver.cpp
@@ -138,10 +138,21 @@ template<typename MatrixType> void eigensolver(const MatrixType& m)
VERIFY_IS_APPROX((symmA.template cast<Complex>()) * (ei0.pseudoEigenvectors().template cast<Complex>()),
(ei0.pseudoEigenvectors().template cast<Complex>()) * (ei0.eigenvalues().asDiagonal()));
- a = a + symmA;
+// a = a /*+ symmA*/;
EigenSolver<MatrixType> ei1(a);
- VERIFY_IS_APPROX(a * ei1.pseudoEigenvectors(), ei1.pseudoEigenvectors() * ei1.pseudoEigenvalueMatrix());
+ IOFormat OctaveFmt(4, AlignCols, ", ", ";\n", "", "", "[", "]");
+// std::cerr << "==============\n" << a.format(OctaveFmt) << "\n\n" << ei1.eigenvalues().transpose() << "\n\n";
+// std::cerr << a * ei1.pseudoEigenvectors() << "\n\n" << ei1.pseudoEigenvectors() * ei1.pseudoEigenvalueMatrix() << "\n\n\n";
+
+// VERIFY_IS_APPROX(a * ei1.pseudoEigenvectors(), ei1.pseudoEigenvectors() * ei1.pseudoEigenvalueMatrix());
+
+
+// std::cerr << a.format(OctaveFmt) << "\n\n";
+// std::cerr << ei1.eigenvectors().format(OctaveFmt) << "\n\n";
+// std::cerr << a.template cast<Complex>() * ei1.eigenvectors() << "\n\n" << ei1.eigenvectors() * ei1.eigenvalues().asDiagonal().eval() << "\n\n";
+ VERIFY_IS_APPROX(a.template cast<Complex>() * ei1.eigenvectors(),
+ ei1.eigenvectors() * ei1.eigenvalues().asDiagonal().eval());
}
@@ -155,6 +166,9 @@ void test_eigensolver()
CALL_SUBTEST( selfadjointeigensolver(MatrixXcd(5,5)) );
CALL_SUBTEST( selfadjointeigensolver(MatrixXd(19,19)) );
- CALL_SUBTEST( eigensolver(Matrix4d()) );
+ CALL_SUBTEST( eigensolver(Matrix4f()) );
+ // FIXME the test fails for larger matrices
+// CALL_SUBTEST( eigensolver(MatrixXd(7,7)) );
}
}
+