1 MatrixXd
X = MatrixXd::Random(5,5);
2 MatrixXd
A =
X +
X.transpose();
3 cout <<
"Here is a random symmetric matrix, A:" << endl <<
A << endl;
4 X = MatrixXd::Random(5,5);
5 MatrixXd
B =
X *
X.transpose();
6 cout <<
"and a random postive-definite matrix, B:" << endl << B << endl << endl;
8 GeneralizedSelfAdjointEigenSolver<MatrixXd>
es(
A,B);
9 cout <<
"The eigenvalues of the pencil (A,B) are:" << endl <<
es.eigenvalues() << endl;
10 cout <<
"The matrix of eigenvectors, V, is:" << endl <<
es.eigenvectors() << endl << endl;
13 cout <<
"Consider the first eigenvalue, lambda = " << lambda << endl;
14 VectorXd
v =
es.eigenvectors().col(0);
15 cout <<
"If v is the corresponding eigenvector, then A * v = " << endl <<
A * v << endl;
16 cout <<
"... and lambda * B * v = " << endl << lambda * B * v << endl << endl;
cout<< "Here is a random symmetric matrix, A:"<< endl<< A<< endl;X=MatrixXd::Random(5, 5);MatrixXd B=X *X.transpose();cout<< "and a random postive-definite matrix, B:"<< endl<< B<< endl<< endl;GeneralizedSelfAdjointEigenSolver< MatrixXd > es(A, B)
cout<< "The eigenvalues of A are:"<< endl<< ces.eigenvalues()<< endl;cout<< "The matrix of eigenvectors, V, is:"<< endl<< ces.eigenvectors()<< endl<< endl;complex< float > lambda