def test_offramp_network():
n = 5
t = 15
fw = CTMFreeway.standard(n)
ic = InitialConditions.blank(n)
bc = BoundaryConditions.blank(n, t)
ic.mainline[:] = 2.0
bc.demand[:, :4] = .3
bc.split_ratios[:, :] = .8
scen = Scenario(fw, ic, bc)
IpOptSolver(n_iters=100).solve(CTMAdjoint(scen), scen.no_control().flatten())
def test_offramp_network():
beta_op.beta = 200.0
beta_op.factor = 1.000
beta_op.beta_admm_factor = 1.000
beta_op.inner_iters = 15
beta = 10.0
n = 5
t = 15
fw = CTMFreeway.standard(n)
ic = InitialConditions.blank(n)
bc = BoundaryConditions.blank(n, t)
ic.mainline[:] = 2.0
bc.demand[:, :4] = 0.3
bc.split_ratios[:, :] = 0.8
scen = Scenario(fw, ic, bc)
print scen.ttt(scen.simulate())
sln = CtmAdjointAdmm.from_full_scenario(scen, 2, beta=beta, n_iters=400).solve().density_summary()
def test_congestion():
beta_op.beta = 50.0
beta_op.factor = 1.02
beta_op.factor = 1.000
beta_op.beta_admm_factor = 1.000
n, t = 4, 4
scen_full = Scenario.blank(n, t)
scen_full.ic.mainline[1] = 1.0
scen_full.ic.mainline[2] = 1.8
sln = CtmAdjointAdmm.from_full_scenario(scen_full, 2, beta=30.0, n_iters=400).solve()
sln.density_summary()
assert_less(sln.history.x[-1], 0.01)
assert_less(sln.history.y[-1], 0.01)
def test_pass_info():
beta_op.beta = 1.0
beta_op.factor = 1.02
beta_op.factor = 1.000
beta_op.beta_admm_factor = 1.000
n, t = 10, 10
scen_full = Scenario.blank(n, t)
scen_full.ic.mainline[0] = 0.5
admm = CtmAdjointAdmm.from_full_scenario(scen_full, 5, beta=30.0, n_iters=400)
d1 = admm.l_scen.simulate(admm.l_scen.no_control()).density
d2 = admm.r_scen.simulate(admm.r_scen.no_control()).density
sln = admm.solve()
d3 = sln.l.fs(sln.l.construct_control(sln.cl)).density
d4 = sln.r.fs(sln.r.construct_control(sln.cr)).density
subplot(2, 2, 1)
pcolor(d1, cmap="binary", vmin=0.0, vmax=1.0)
xlabel("Time")
ylabel("Space")
title("Initial Upstream Subnetwork")
colorbar()
subplot(2, 2, 2)
pcolor(d2, cmap="binary", vmin=0.0, vmax=1.0)
xlabel("Time")
ylabel("Space")
title("Initial Downstream Subnetwork")
colorbar()
subplot(2, 2, 3)
pcolor(d3, cmap="binary", vmin=0.0, vmax=1.0)
xlabel("Time")
ylabel("Space")
title("Final Upstream Subnetwork")
colorbar()
subplot(2, 2, 4)
pcolor(d4, cmap="binary", vmin=0.0, vmax=1.0)
xlabel("Time")
ylabel("Space")
title("Final Downstream Subnetwork")
colorbar()
savefig("init-final.pdf")
sln.density_summary()
cl = sln.l.construct_control(sln.cl)
cr = sln.r.construct_control(sln.cr)
assert_array_almost_equal(cl[0][-2:, :], cr[0][:2, :])
assert_array_almost_equal(cl[1], [0, 0, 0.5, 0], 2)
assert_array_almost_equal(cr[1], [0, 0.5, 0, 0], 2)
assert_almost_equals(sln.history.x[-1], 0.0, 2)
assert_almost_equals(sln.history.y[-1], 0.0, 2)
def test_two_length():
beta_op.beta = 50.0
# beta_op.beta = 0.8
beta_op.factor = 1.02
beta_op.beta = 100.0
beta_op.factor = 1.02
beta_op.factor = 1.000
beta = 100.0
beta_op.beta_admm_factor = 1.000
beta_op.inner_iters = 100
n, t = 2, 2
scen_full = Scenario.blank(n, t)
scen_full.ic.mainline[1] = 0.5
sln = CtmAdjointAdmm.from_full_scenario(scen_full, 1, beta=beta, n_iters=20).solve()
sln.density_summary()
cl = sln.l.construct_control(sln.cl)
cr = sln.r.construct_control(sln.cr)
assert_array_almost_equal(cl[0][-2:, :], cr[0][:2, :])
assert_array_almost_equal(cl[1], [0, 0, 0.5, 0], 2)
assert_array_almost_equal(cr[1], [0, 0.5, 0, 0], 2)
assert_almost_equals(sln.history.x[-1], 0.0, 2)
assert_almost_equals(sln.history.y[-1], 0.0, 2)
def test_smoother():
beta_op.beta = 20.0
beta_op.factor = 1.000
beta_op.beta_admm_factor = 1.000
beta_op.inner_iters = 30
beta = 1.0
n = 6
t = 10
fw = CTMFreeway.standard(n)
ic = InitialConditions.blank(n)
bc = BoundaryConditions.blank(n, t)
ic.mainline[:] = 1.0
ic.queue[0] = 0.5
ic.queue[[3]] = 0.5
bc.demand[0, :] = 0.5
bc.demand[[1, 4], :2] = 0.3
scen = Scenario(fw, ic, bc)
print scen.ttt(scen.simulate())
scen.simulate().plot()
# IpOptSolver(n_iters=100).solve(CTMAdjoint(scen), scen.no_control().flatten())
# u_star = AcceleratedGradient(n_iters=40, beta=50.0, lb=0.0, ub=1.0).solve(CTMAdjoint(scen),
# scen.no_control().transpose().flatten())
#
#
# print scen.ttt(scen.simulate(u_star))
# scen.simulate(u_star).plot()
sln = CtmAdjointAdmm.from_full_scenario(scen, 3, beta=beta, n_iters=100).solve()
u_star = sln.construct_control()
sln.density_summary()
print "###########"
print CTMAdjoint(scen).j(scen.simulate(u_star), u_star)
print scen.ttt(scen.simulate(u_star))
u_star = AcceleratedGradient(n_iters=20, beta=20.0, lb=0.0, ub=1.0).solve(
CTMAdjoint(scen), u_star.transpose().flatten()
)
print scen.ttt(scen.simulate(u_star))
