import numpy as np
from qpsolvers import solve_ls

R = np.array([[1., 2., 0.], [-8., 3., 2.], [0., 1., 1.]])
s = np.array([3., 2., 3.])
G = np.array([[1., 2., 1.], [2., 0., 1.], [-1., 2., -1.]])
h = np.array([3., 2., -2.]).reshape((3,))

results = {
    "qpalm": solve_ls(R, s, G, h, solver="qpalm"),
    "proxqp_defaults": solve_ls(R, s, G, h, solver="proxqp"),
    "proxqp_check_duality_gap": solve_ls(
        R, s, G, h, solver="proxqp", check_duality_gap=True
    ),
}

for k, x in results.items():
    print(
        f"{k:25}: "
        f"objective={np.linalg.norm(R.dot(x) - s)**2:.1f}, "
        f"constraints_ok={np.all(G.dot(x) <= h)}"
    )