Re: [eigen] Re: Eigen solver usage: simple questions

[Benoit Jacob <jacob.benoit.1@xxxxxxxxx>]

Indeed, that is the explanation. If your matrix is not selfadjoint,
just use class EigenSolver.

EigenSolver solver(matrix);
result = solver.eigenvalues();

Benoit

2010/7/20 William Oquendo <woquendo@xxxxxxxxx>:
> Dear all,
> It seems that .eigenvalues() assumes the matrix is selfadjoint since it is
> calling the self adjoint mehotd (as shown by the compiler in the assertion
> and after looking the source code), and of course produces bad results when
> compiling -DNDEBUG and disabling the assertion
> Is there a way to explicitly indicates that a given matrix is not
> selfadjoint, and in that case to use the more general procedure ?
> Best regards / Cordialmente,
>
> --
> William Oquendo
> Phd Candidate
> Simulation Of Physical Systems Group
> National University of Colombia
> Linux User # 321481
> *********************
> Este correo puede carecer de tildes o eñes ya que el teclado no contiene
> estos caracteres. Presento excusas por eso.
>
> *********************
>
>
>
> On Tue, Jul 20, 2010 at 4:06 PM, William Oquendo <woquendo@xxxxxxxxx> wrote:
>>
>> Dear all,
>> First of all I apologize in advance if my questions are too simple, I read
>> the docs but the info about eigen solvers is small. Second, I would like to
>> thank you for the great work in Eigen!
>> I have been using eigen  (currently 2.0.15, compiler g++ 4.4.4,
>> Slackware64 13.1) to solve eigenvalue problems. But now I am concerned with
>> the way I am using the library. I have a 3x3 array (simulating the matrix)
>> and I need to compute, by now, only the eigenvalues. When I execute the code
>> (please see a reduced example copied at the end and also attached), the
>> program dies with the following error assertion (in general my matrix is not
>> self adjoint):
>> a.out:
>> /usr/local/include/eigen2/Eigen/src/QR/SelfAdjointEigenSolver.h:296:
>> Eigen::Matrix<typename Eigen::NumTraits<typename
>> Eigen::ei_traits<T>::Scalar>::Real, Eigen::ei_traits::ColsAtCompileTime, 1,
>> 2, Eigen::ei_traits::ColsAtCompileTime, 1>
>> Eigen::MatrixBase<Derived>::eigenvalues() const [with Derived =
>> Eigen::Map<Eigen::Matrix<double, 3, 3, 2, 3, 3>, 1>]: Assertion
>> `Flags&SelfAdjointBit' failed.
>> But, if I compile with the flag -DNDEBUG, the programs ends successfully
>> with the correct data (even with null matrices), as far as I have checked.
>> How can I specify to Eigen that my matrix is not selfAdjoint? (if that is
>> the problem ...
>> Let's assume now that I need both the eigen values and eigen vectors, and
>> I am using the full eigen solver:
>> EigenSolver<Matrix3d> solver(Meigen);
>> Is it possible to sort the eigen values by norm and, of course, their
>> corresponding eigen vectors by means of some internal eigen function? I can
>> write a function to do that, but I would like to know if Eigen can do it
>> already.
>> Thanks in advance for your kind help and reply.
>> Best regards / Cordialmente,
>>
>> --
>> William Oquendo
>> Phd Candidate
>> Simulation Of Physical Systems Group
>> National University of Colombia
>> Linux User # 321481
>> *********************
>> Este correo puede carecer de tildes o eñes ya que el teclado no contiene
>> estos caracteres. Presento excusas por eso.
>>
>> *********************
>>
>>
>> CODE
>> #include <iostream>
>> #include <eigen2/Eigen/Core>
>> #include <eigen2/Eigen/Array>
>> #include <eigen2/Eigen/QR>
>> using namespace Eigen;
>> using namespace std;
>> void ComputeEigenValues(double Matrix[][3], double & l0, double & l1,
>> double & l2);
>> int main()
>> {
>>   double M[3][3] = { 1, 0, 0,
>>     0, 1, 0,
>>     0, 0, 1 };
>>   double e0, e1, e2;
>>
>>   ComputeEigenValues(M, e0, e1, e2);
>>
>>   clog << "The eigen values are " << endl
>>        << e0 << endl
>>        << e1 << endl
>>        << e2 << endl
>>        << endl;
>>
>>   return 0;
>> }
>> void ComputeEigenValues(double Matrix[][3], double & l0, double & l1,
>> double & l2)
>> {
>>   l0 = l1 = l2 = 0;
>>   Map<Matrix3d> Meigen(&Matrix[0][0]);
>>   Vector3d veval =  Meigen.eigenvalues();
>>   l0 = veval.real()[0];
>>   l1 = veval.real()[1];
>>   l2 = veval.real()[2];
>> }
>>
>
>