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Update utility for experimenting with 3x3 eigenvalues

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This commit is contained in:
Gael Guennebaud 2015-06-08 15:54:53 +02:00
parent 8f031a3cee
commit 913a61870d
1 changed files with 28 additions and 29 deletions
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57
bench/eig33.cpp
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@ -50,7 +50,7 @@ inline void computeRoots(const Matrix& m, Roots& roots)
{
typedef typename Matrix::Scalar Scalar;
const Scalar s_inv3 = 1.0/3.0;
const Scalar s_sqrt3 = internal::sqrt(Scalar(3.0));
const Scalar s_sqrt3 = std::sqrt(Scalar(3.0));
// The characteristic equation is x^3 - c2*x^2 + c1*x - c0 = 0. The
// eigenvalues are the roots to this equation, all guaranteed to be
@ -73,23 +73,13 @@ inline void computeRoots(const Matrix& m, Roots& roots)
q = Scalar(0);
// Compute the eigenvalues by solving for the roots of the polynomial.
Scalar rho = internal::sqrt(-a_over_3);
Scalar theta = std::atan2(internal::sqrt(-q),half_b)*s_inv3;
Scalar cos_theta = internal::cos(theta);
Scalar sin_theta = internal::sin(theta);
roots(0) = c2_over_3 + Scalar(2)*rho*cos_theta;
roots(1) = c2_over_3 - rho*(cos_theta + s_sqrt3*sin_theta);
roots(2) = c2_over_3 - rho*(cos_theta - s_sqrt3*sin_theta);
// Sort in increasing order.
if (roots(0) >= roots(1))
std::swap(roots(0),roots(1));
if (roots(1) >= roots(2))
{
std::swap(roots(1),roots(2));
if (roots(0) >= roots(1))
std::swap(roots(0),roots(1));
}
Scalar rho = std::sqrt(-a_over_3);
Scalar theta = std::atan2(std::sqrt(-q),half_b)*s_inv3;
Scalar cos_theta = std::cos(theta);
Scalar sin_theta = std::sin(theta);
roots(2) = c2_over_3 + Scalar(2)*rho*cos_theta;
roots(0) = c2_over_3 - rho*(cos_theta + s_sqrt3*sin_theta);
roots(1) = c2_over_3 - rho*(cos_theta - s_sqrt3*sin_theta);
}
template<typename Matrix, typename Vector>
@ -99,9 +89,12 @@ void eigen33(const Matrix& mat, Matrix& evecs, Vector& evals)
// Scale the matrix so its entries are in [-1,1]. The scaling is applied
// only when at least one matrix entry has magnitude larger than 1.
Scalar scale = mat.cwiseAbs()/*.template triangularView<Lower>()*/.maxCoeff();
Scalar shift = mat.trace()/3;
Matrix scaledMat = mat;
scaledMat.diagonal().array() -= shift;
Scalar scale = scaledMat.cwiseAbs()/*.template triangularView<Lower>()*/.maxCoeff();
scale = std::max(scale,Scalar(1));
Matrix scaledMat = mat / scale;
scaledMat/=scale;
// Compute the eigenvalues
// scaledMat.setZero();
@ -166,6 +159,7 @@ void eigen33(const Matrix& mat, Matrix& evecs, Vector& evals)
// Rescale back to the original size.
evals *= scale;
evals.array()+=shift;
}
int main()
@ -173,24 +167,29 @@ int main()
BenchTimer t;
int tries = 10;
int rep = 400000;
typedef Matrix3f Mat;
typedef Vector3f Vec;
typedef Matrix3d Mat;
typedef Vector3d Vec;
Mat A = Mat::Random(3,3);
A = A.adjoint() * A;
// Mat Q = A.householderQr().householderQ();
// A = Q * Vec(2.2424567,2.2424566,7.454353).asDiagonal() * Q.transpose();
SelfAdjointEigenSolver<Mat> eig(A);
BENCH(t, tries, rep, eig.compute(A));
std::cout << "Eigen: " << t.best() << "s\n";
std::cout << "Eigen iterative: " << t.best() << "s\n";
BENCH(t, tries, rep, eig.computeDirect(A));
std::cout << "Eigen direct : " << t.best() << "s\n";
Mat evecs;
Vec evals;
BENCH(t, tries, rep, eigen33(A,evecs,evals));
std::cout << "Direct: " << t.best() << "s\n\n";
std::cerr << "Eigenvalue/eigenvector diffs:\n";
std::cerr << (evals - eig.eigenvalues()).transpose() << "\n";
for(int k=0;k<3;++k)
if(evecs.col(k).dot(eig.eigenvectors().col(k))<0)
evecs.col(k) = -evecs.col(k);
std::cerr << evecs - eig.eigenvectors() << "\n\n";
// std::cerr << "Eigenvalue/eigenvector diffs:\n";
// std::cerr << (evals - eig.eigenvalues()).transpose() << "\n";
// for(int k=0;k<3;++k)
// if(evecs.col(k).dot(eig.eigenvectors().col(k))<0)
// evecs.col(k) = -evecs.col(k);
// std::cerr << evecs - eig.eigenvectors() << "\n\n";
}