def test_primal_poa(self):
c, G, h, A, b = CongestionPoA.primal_poa(*self.args1)
sol = lp('cvxopt', c, G, h, A, b)
self.assertEqual(round(-1. / sol['min'], 4), .5)
c, G, h, A, b = CongestionPoA.primal_poa(*self.args2)
sol2 = lp('cvxopt', c, G, h, A, b)
self.assertEqual(round(-1. / sol2['min'], 4), .6329)
def test_worst_case(self):
n = self.args3[0]
c, G, h, A, b = CongestionPoA.primal_poa(*self.args3)
theta = lp('cvxopt', c, G, h, A, b)['argmin']
CongestionPoA.TOL = 4
actions, values = CongestionPoA.worst_case(theta, n)
self.assertEqual(actions, [[(0, ), (1, 2)], [(1, ), (0, 3)]])
self.assertEqual(values, [0.5, 0.5, 0.5, 0.5])
def test_poa(self):
w = [0., 1, 1, 1]
f = [0., 1, 0, 0]
optf = [0., 1., .43, .29]
c, G, h = ResourcePoA.function_poa(w)
rpoaf = [0.] + lp('cvxopt', c, G, h)['argmin'][1:]
rpoaf = [round(e, 2) for e in rpoaf]
self.assertEqual(rpoaf, optf)
c, G, h = ResourcePoA.dual_poa(f, w)
d_poa = 1. / lp('cvxopt', c, G, h)['min']
self.assertEqual(round(d_poa, 3), .5)
c, G, h, A, b = ResourcePoA.primal_poa(f, w)
p_poa = -1. / lp('cvxopt', c, G, h, A, b)['min']
self.assertEqual(round(p_poa, 3), .5)
def test_worst_case(self):
w = [0., 1, 1]
f = [0., 1, 0]
c, G, h, A, b = ResourcePoA.primal_poa(f, w)
theta = lp('cvxopt', c, G, h, A, b)['argmin']
ResourcePoA.TOL = 5
actions, values = ResourcePoA.worst_case(theta, 2)
self.assertEqual(actions, [[(2, ), (1, 3)], [(3, ), (0, 2)]])
self.assertEqual(values, [0.5, 0.5, 0.5, 0.5])
def cong_worst_game(n, w, flist, solver): theta = lp(solver, CongestionPoA.primal_poa(n, w, flist))['argmin'] actions, values = CongestionPoA.worst_case(theta, n) #### TODO ###
def cong_poa(n, w, flist, solver): return -1./lp(solver, CongestionPoA.primal_poa(n, w, flist))['min']
def worst_game(f, w, solver): theta = lp(solver, ResourcePoA.primal_poa(f, w))['argmin'] N = len(f) actions, values = ResourcePoA.worst_case(theta, N) return welfare_resource_game(actions, values, w, f)
def res_opt_f(w, solver): sol = lp(solver, ResourcePoA.function_poa(w)) f = [0.] + sol['argmin'][1:] poa = 1./sol['min'] return poa, f
def res_poa(f, w, solver): return 1./lp(solver, ResourcePoA.dual_poa(f, w))['min']