|
| | solver = pa.PANOCSolver(pa.PANOCParams(), pa.LBFGSDirection(pa.LBFGSParams())) |
| |
| | l = pa.LBFGSParams(cbfgs=pa.LBFGSParamsCBFGS(α=5)) |
| |
| | α |
| |
| | hess_prod = lambda L, x, v: cs.gradient(cs.jtimes(L, x, v, False), x) |
| |
| int | n = 2 |
| |
| int | m = 2 |
| |
| | x = cs.SX.sym("x", n) |
| |
| | λ = cs.SX.sym("λ", m) |
| |
| | v = cs.SX.sym("v", n) |
| |
| | Q = np.array([[1.5, 0.5], [0.5, 1.5]]) |
| |
| | f_ = x.T @ Q @ x |
| |
| | g_ = x |
| |
| int | L = f_ + cs.dot(λ, g_) if m > 0 else f_ |
| |
| | f = cs.Function("f", [x], [f_]) |
| |
| | grad_f = cs.Function("grad_f", [x], [cs.gradient(f_, x)]) |
| |
| | g = cs.Function("g", [x], [g_]) |
| |
| | grad_g_prod = cs.Function("grad_g_prod", [x, λ], [cs.jtimes(g_, x, λ, True)]) |
| |
| | grad_gi = lambda x, i: grad_g_prod(x, np.eye(1, m, i)) |
| |
| | Hess_L = cs.Function("Hess_L", [x, λ], [cs.hessian(L, x)[0]]) |
| |
| | Hess_L_prod = cs.Function("Hess_L_prod", [x, λ, v], [hess_prod(L, x, v)]) |
| |
| | p = pa.Problem(n, m) |
| |
| | hess_L |
| |
| | hess_L_prod |
| |
| | lowerbound |
| |
| | upperbound |
| |
| | x0 = np.array([3, 3]) |
| |
| | y0 = np.zeros((m,)) |
| |
| int | Σ = 1e3 * np.ones((m,)) |
| |
| int | ε = 1e-8 |
| |
| | y |
| |
| | err_z |
| |
| | stats |
| |
| | almparams = pa.ALMParams(max_iter=20, print_interval=1, preconditioning=False) |
| |
| | almsolver = pa.ALMSolver(almparams, solver) |
| |
| | old_x0 = x0 |
| |
| | sol = almsolver(p, x=x0, y=y0) |
| |
| string | name = "testproblem" |
| |
| | cgen |
| |
| | num_p |
| |
| | prefix |
| |
| | cfile = cgen.generate(join(tmpdir, "")) |
| |
| | sofile = join(tmpdir, f"{name}.so") |
| |
| | C = pa.Box([10], [-2.5]) |
| |
| | params |
| |
