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* bug fixes in: Dot, generalized eigen problem, singular matrix detetection in Cholesky

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* fix all numerical instabilies in the unit tests, now all tests can be run 2000 times
  with almost zero failures.
This commit is contained in:
Gael Guennebaud
2008-08-23 15:14:20 +00:00
parent 312013a089
commit 2120fed849
20 changed files with 632 additions and 103 deletions
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27
Eigen/src/QR/SelfAdjointEigenSolver.h
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@@ -225,22 +225,33 @@ void SelfAdjointEigenSolver<MatrixType>::
compute(const MatrixType& matA, const MatrixType& matB, bool computeEigenvectors)
{
ei_assert(matA.cols()==matA.rows() && matB.rows()==matA.rows() && matB.cols()==matB.rows());
// Compute the cholesky decomposition of matB = U'U
// Compute the cholesky decomposition of matB = L L'
Cholesky<MatrixType> cholB(matB);
// compute C = inv(U') A inv(U)
MatrixType matC = cholB.matrixL().solveTriangular(matA);
// FIXME since we currently do not support A * inv(U),
// let's do (inv(U') A')' :
matC = (cholB.matrixL().solveTriangular(matC.adjoint())).adjoint();
// compute C = inv(L) A inv(L')
MatrixType matC = matA;
cholB.matrixL().solveTriangularInPlace(matC);
// FIXME since we currently do not support A * inv(L'), let's do (inv(L) A')' :
matC = matC.adjoint().eval();
cholB.matrixL().template marked<Lower>().solveTriangularInPlace(matC);
matC = matC.adjoint().eval();
// this version works too:
// matC = matC.transpose();
// cholB.matrixL().conjugate().template marked<Lower>().solveTriangularInPlace(matC);
// matC = matC.transpose();
// FIXME: this should work: (currently it only does for small matrices)
// Transpose<MatrixType> trMatC(matC);
// cholB.matrixL().conjugate().eval().template marked<Lower>().solveTriangularInPlace(trMatC);
compute(matC, computeEigenvectors);
if (computeEigenvectors)
{
// transform back the eigen vectors: evecs = inv(U) * evecs
m_eivec = cholB.matrixL().adjoint().template marked<Upper>().solveTriangular(m_eivec);
cholB.matrixL().adjoint().template marked<Upper>().solveTriangularInPlace(m_eivec);
for (int i=0; i<m_eivec.cols(); ++i)
m_eivec.col(i) = m_eivec.col(i).normalized();
}
}