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This commit is contained in:
Gael Guennebaud
2014-08-29 15:20:31 +02:00
parent f29dbec321 aec3d90ca6
commit 124d12a915
41 changed files with 630 additions and 296 deletions
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18
Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
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@@ -605,7 +605,6 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3
if(computeEigenvectors)
{
Scalar safeNorm2 = Eigen::NumTraits<Scalar>::epsilon();
safeNorm2 *= safeNorm2;
if((eivals(2)-eivals(0))<=Eigen::NumTraits<Scalar>::epsilon())
{
eivecs.setIdentity();
@@ -619,7 +618,7 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3
Scalar d0 = eivals(2) - eivals(1);
Scalar d1 = eivals(1) - eivals(0);
int k = d0 > d1 ? 2 : 0;
d0 = d0 > d1 ? d1 : d0;
d0 = d0 > d1 ? d0 : d1;
tmp.diagonal().array () -= eivals(k);
VectorType cross;
@@ -627,19 +626,25 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3
n = (cross = tmp.row(0).cross(tmp.row(1))).squaredNorm();
if(n>safeNorm2)
{
eivecs.col(k) = cross / sqrt(n);
}
else
{
n = (cross = tmp.row(0).cross(tmp.row(2))).squaredNorm();
if(n>safeNorm2)
{
eivecs.col(k) = cross / sqrt(n);
}
else
{
n = (cross = tmp.row(1).cross(tmp.row(2))).squaredNorm();
if(n>safeNorm2)
{
eivecs.col(k) = cross / sqrt(n);
}
else
{
// the input matrix and/or the eigenvaues probably contains some inf/NaN,
@@ -659,12 +664,16 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3
tmp.diagonal().array() -= eivals(1);
if(d0<=Eigen::NumTraits<Scalar>::epsilon())
{
eivecs.col(1) = eivecs.col(k).unitOrthogonal();
}
else
{
n = (cross = eivecs.col(k).cross(tmp.row(0).normalized())).squaredNorm();
n = (cross = eivecs.col(k).cross(tmp.row(0))).squaredNorm();
if(n>safeNorm2)
{
eivecs.col(1) = cross / sqrt(n);
}
else
{
n = (cross = eivecs.col(k).cross(tmp.row(1))).squaredNorm();
@@ -678,13 +687,14 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3
else
{
// we should never reach this point,
// if so the last two eigenvalues are likely to ve very closed to each other
// if so the last two eigenvalues are likely to be very close to each other
eivecs.col(1) = eivecs.col(k).unitOrthogonal();
}
}
}
// make sure that eivecs[1] is orthogonal to eivecs[2]
// FIXME: this step should not be needed
Scalar d = eivecs.col(1).dot(eivecs.col(k));
eivecs.col(1) = (eivecs.col(1) - d * eivecs.col(k)).normalized();
}