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

Update eigenvalues() and operatorNorm() methods in MatrixBase.

Browse Source 
* use SelfAdjointView instead of Eigen2's SelfAdjoint flag.
* add tests and documentation.
* allow eigenvalues() for non-selfadjoint matrices.
* they no longer depend only on SelfAdjointEigenSolver, so move them to
  a separate file
This commit is contained in:
Jitse Niesen
2010-05-24 17:43:50 +01:00
parent 8a3f552e39
commit e7d809d434
12 changed files with 222 additions and 56 deletions
Download Patch File Download Diff File Expand all files Collapse all files

23
test/eigensolver_complex.cpp
View File

@@ -26,6 +26,21 @@
#include <Eigen/Eigenvalues>
#include <Eigen/LU>
/* Check that two column vectors are approximately equal upto permutations,
by checking that the k-th power sums are equal for k = 1, ..., vec1.rows() */
template<typename VectorType>
void verify_is_approx_upto_permutation(const VectorType& vec1, const VectorType& vec2)
{
VERIFY(vec1.cols() == 1);
VERIFY(vec2.cols() == 1);
VERIFY(vec1.rows() == vec2.rows());
for (int k = 1; k <= vec1.rows(); ++k)
{
VERIFY_IS_APPROX(vec1.array().pow(k).sum(), vec2.array().pow(k).sum());
}
}
template<typename MatrixType> void eigensolver(const MatrixType& m)
{
/* this test covers the following files:
@@ -48,11 +63,17 @@ template<typename MatrixType> void eigensolver(const MatrixType& m)
ComplexEigenSolver<MatrixType> ei1(a);
VERIFY_IS_APPROX(a * ei1.eigenvectors(), ei1.eigenvectors() * ei1.eigenvalues().asDiagonal());
// Note: If MatrixType is real then a.eigenvalues() uses EigenSolver and thus
// another algorithm so results may differ slightly
verify_is_approx_upto_permutation(a.eigenvalues(), ei1.eigenvalues());
// Regression test for issue #66
MatrixType z = MatrixType::Zero(rows,cols);
ComplexEigenSolver<MatrixType> eiz(z);
VERIFY((eiz.eigenvalues().cwiseEqual(0)).all());
MatrixType id = MatrixType::Identity(rows, cols);
VERIFY_IS_APPROX(id.operatorNorm(), RealScalar(1));
}
void test_eigensolver_complex()

3
test/eigensolver_generic.cpp
View File

@@ -58,7 +58,10 @@ template<typename MatrixType> void eigensolver(const MatrixType& m)
VERIFY_IS_APPROX(a * ei1.pseudoEigenvectors(), ei1.pseudoEigenvectors() * ei1.pseudoEigenvalueMatrix());
VERIFY_IS_APPROX(a.template cast<Complex>() * ei1.eigenvectors(),
ei1.eigenvectors() * ei1.eigenvalues().asDiagonal());
VERIFY_IS_APPROX(a.eigenvalues(), ei1.eigenvalues());
MatrixType id = MatrixType::Identity(rows, cols);
VERIFY_IS_APPROX(id.operatorNorm(), RealScalar(1));
}
template<typename MatrixType> void eigensolver_verify_assert()

4
test/eigensolver_selfadjoint.cpp
View File

@@ -103,6 +103,7 @@ template<typename MatrixType> void selfadjointeigensolver(const MatrixType& m)
VERIFY((symmA * eiSymm.eigenvectors()).isApprox(
eiSymm.eigenvectors() * eiSymm.eigenvalues().asDiagonal(), largerEps));
VERIFY_IS_APPROX(symmA.template selfadjointView<Lower>().eigenvalues(), eiSymm.eigenvalues());
// generalized eigen problem Ax = lBx
VERIFY((symmA * eiSymmGen.eigenvectors()).isApprox(
@@ -111,6 +112,9 @@ template<typename MatrixType> void selfadjointeigensolver(const MatrixType& m)
MatrixType sqrtSymmA = eiSymm.operatorSqrt();
VERIFY_IS_APPROX(symmA, sqrtSymmA*sqrtSymmA);
VERIFY_IS_APPROX(sqrtSymmA, symmA*eiSymm.operatorInverseSqrt());
MatrixType id = MatrixType::Identity(rows, cols);
VERIFY_IS_APPROX(id.template selfadjointView<Lower>().operatorNorm(), RealScalar(1));
}
void test_eigensolver_selfadjoint()