test_self_adjoint_eigen_solver.py

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import numpy as np
 
import eigenpy
 
dim = 100
rng = np.random.default_rng()
 
A = rng.random((dim, dim))
A = (A + A.T) * 0.5
 
es = eigenpy.SelfAdjointEigenSolver(A)
 
V = es.eigenvectors()
D = es.eigenvalues()
 
assert eigenpy.is_approx(A.dot(V), V.dot(np.diag(D)), 1e-6)