def setUp(self):
"""
This sets up the test case.
"""
#Define the residual
def f(t,y,yd):
eps = 1.e-6
my = 1./eps
yd_0 = y[1]
yd_1 = my*((1.-y[0]**2)*y[1]-y[0])
res_0 = yd[0]-yd_0
res_1 = yd[1]-yd_1
return N.array([res_0,res_1])
y0 = [2.0,-0.6] #Initial conditions
yd0 = [-.6,-200000.]
#Define an Assimulo problem
self.mod = Implicit_Problem(f,y0,yd0)
self.mod_t0 = Implicit_Problem(f,y0,yd0,1.0)
#Define an explicit solver
self.sim = Radau5DAE(self.mod) #Create a Radau5 solve
self.sim_t0 = Radau5DAE(self.mod_t0)
#Sets the parameters
self.sim.atol = 1e-4 #Default 1e-6
self.sim.rtol = 1e-4 #Default 1e-6
self.sim.inith = 1.e-4 #Initial step-size
def test_time_event(self):
f = lambda t,y,yd: y-yd
global tnext
global nevent
tnext = 0.0
nevent = 0
def time_events(t,y,yd,sw):
global tnext,nevent
events = [1.0, 2.0, 2.5, 3.0]
for ev in events:
if t < ev:
tnext = ev
break
else:
tnext = None
nevent += 1
return tnext
def handle_event(solver, event_info):
#solver.y+= 1.0
global tnext
nose.tools.assert_almost_equal(solver.t, tnext)
assert event_info[0] == []
assert event_info[1] == True
exp_mod = Implicit_Problem(f,0.0,0.0)
exp_mod.time_events = time_events
exp_mod.handle_event = handle_event
#CVode
exp_sim = Radau5DAE(exp_mod)
exp_sim.verbosity = 0
exp_sim(5.,100)
assert nevent == 5
def test_nbr_fcn_evals_due_to_jac(self):
sim = Radau5DAE(self.mod)
sim.usejac = False
sim.simulate(1)
assert sim.statistics["nfcnjacs"] > 0
def test_init(self):
"""
This tests the functionality of Radau5 Implicit Init.
"""
#Test both y0 in problem and not.
sim = Radau5DAE(self.mod)
assert sim._leny == 2
def test_simulate_explicit(self):
"""
Test a simulation of an explicit problem using Radau5DAE.
"""
f = lambda t,y:N.array(-y)
y0 = [1.0]
problem = Explicit_Problem(f,y0)
simulator = Radau5DAE(problem)
assert simulator.yd0[0] == -simulator.y0[0]
t,y = simulator.simulate(1.0)
nose.tools.assert_almost_equal(float(y[-1]), float(N.exp(-1.0)),4)
def test_switches(self):
"""
This tests that the switches are actually turned when override.
"""
res = lambda t,x,xd,sw: N.array([1.0 - xd])
state_events = lambda t,x,xd,sw: N.array([x[0]-1.])
def handle_event(solver, event_info):
solver.sw = [False] #Override the switches to point to another instance
mod = Implicit_Problem(res,[0.0], [1.0])
mod.sw0 = [True]
mod.state_events = state_events
mod.handle_event = handle_event
sim = Radau5DAE(mod)
assert sim.sw[0] == True
sim.simulate(3)
assert sim.sw[0] == False
