import numpy as np
from scipy.linalg import eig


A = np.array(
    [
        [4.0, 1.0, -2.0],
        [0.0, 3.0, 1.0],
        [0.0, 0.0, 2.0],
    ]
)

w, vr = eig(A)
residuals = np.linalg.norm(A @ vr - vr * w, axis=0)

np.set_printoptions(precision=6, suppress=True)
print("matrix rows:")
for row in A:
    print(row)
print("eigenvalues:", w)
print("right eigenvectors by row:")
for row in vr:
    print(row)
print("residuals:", residuals)
print("max_residual:", residuals.max())
print("verified:", bool(np.all(residuals < 1e-10)))