1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathMatrixXcf A = MatrixXcf::Random(4,4);
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathcout << "Here is a random 4x4 matrix, A:" << endl << A << endl << endl;
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathComplexEigenSolver<MatrixXcf> ces;
5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathces.compute(A);
6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathcout << "The eigenvalues of A are:" << endl << ces.eigenvalues() << endl;
7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathcout << "The matrix of eigenvectors, V, is:" << endl << ces.eigenvectors() << endl << endl;
8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathcomplex<float> lambda = ces.eigenvalues()[0];
10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathcout << "Consider the first eigenvalue, lambda = " << lambda << endl;
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathVectorXcf v = ces.eigenvectors().col(0);
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathcout << "If v is the corresponding eigenvector, then lambda * v = " << endl << lambda * v << endl;
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathcout << "... and A * v = " << endl << A * v << endl << endl;
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathcout << "Finally, V * D * V^(-1) = " << endl
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath     << ces.eigenvectors() * ces.eigenvalues().asDiagonal() * ces.eigenvectors().inverse() << endl;
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