def solve(self, problem:Problem):
problem.reassign_dofs()
M = problem.M(True)
K = problem.K(True)
ndofs = 3 * len(problem.nodes)
free_dofs = problem.free_dofs()
full_eigenvectors = np.zeros((len(free_dofs), ndofs))
# Unsymmetric reduction
A = np.linalg.solve(M, K)
# Symmetry preserving reduction
#L = np.linalg.cholesky(M)
#A = np.linalg.inv(L) @ K @ np.linalg.inv(L.T)
eigenvalues, eigenvectors = np.linalg.eig(A)
eigenvectors = eigenvectors.T # Row-major
eigenvectors = eigenvectors[eigenvalues.argsort()]
eigenvalues.sort()
full_eigenvectors[:,free_dofs] = eigenvectors
return results.ResultsModal(problem, eigenvalues, full_eigenvectors)
