def setUp(self):
"""
This sets up the test case.
"""
def f(t,y):
eps = 1.e-6
my = 1./eps
yd_0 = y[1]
yd_1 = my*((1.-y[0]**2)*y[1]-y[0])
return N.array([yd_0,yd_1])
def jac(t,y):
eps = 1.e-6
my = 1./eps
J = N.zeros([2,2])
J[0,0]=0.
J[0,1]=1.
J[1,0]=my*(-2.*y[0]*y[1]-1.)
J[1,1]=my*(1.-y[0]**2)
return J
def jac_sparse(t,y):
eps = 1.e-6
my = 1./eps
J = N.zeros([2,2])
J[0,0]=0.
J[0,1]=1.
J[1,0]=my*(-2.*y[0]*y[1]-1.)
J[1,1]=my*(1.-y[0]**2)
return sp.csc_matrix(J)
#Define an Assimulo problem
y0 = [2.0,-0.6] #Initial conditions
exp_mod = Explicit_Problem(f,y0)
exp_mod_t0 = Explicit_Problem(f,y0,1.0)
exp_mod_sp = Explicit_Problem(f,y0)
exp_mod.jac = jac
exp_mod_sp.jac = jac_sparse
self.mod = exp_mod
#Define an explicit solver
self.sim = Radau5ODE(exp_mod) #Create a Radau5 solve
self.sim_t0 = Radau5ODE(exp_mod_t0)
self.sim_sp = Radau5ODE(exp_mod_sp)
#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
self.sim.usejac = False
def test_nbr_fcn_evals_due_to_jac(self):
sim = Radau5ODE(self.mod)
sim.usejac = False
sim.simulate(1)
assert sim.statistics["nfcnjacs"] > 0
sim = Radau5ODE(self.mod)
sim.simulate(1)
assert sim.statistics["nfcnjacs"] == 0
def test_time_event(self):
f = lambda t,y: [1.0]
global tnext
global nevent
tnext = 0.0
nevent = 0
def time_events(t,y,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 = Explicit_Problem(f,0.0)
exp_mod.time_events = time_events
exp_mod.handle_event = handle_event
#CVode
exp_sim = Radau5ODE(exp_mod)
exp_sim(5.,100)
assert nevent == 5
def setUp(self):
"""
This sets up the test case.
"""
f = lambda t,y:[1.0,2.0]
#Define an Assimulo problem
y0 = [2.0,-0.6] #Initial conditions
exp_mod = Explicit_Problem(f,y0)
self.sim = Radau5ODE(exp_mod)
def test_weighted_error(self):
def handle_result(solver, t, y):
err = solver.get_weighted_local_errors()
assert len(err) == len(y)
self.mod.handle_result = handle_result
#Define an explicit solver
sim = Radau5ODE(self.mod) #Create a Radau5 solve
sim.get_weighted_local_errors()
sim.simulate(1)
def test_event_localizer(self):
exp_mod = Extended_Problem() #Create the problem
exp_sim = Radau5ODE(exp_mod) #Create the solver
exp_sim.verbosity = 0
exp_sim.report_continuously = True
#Simulate
t, y = exp_sim.simulate(
10.0, 1000) #Simulate 10 seconds with 1000 communications points
#Basic test
nose.tools.assert_almost_equal(y[-1][0], 8.0)
nose.tools.assert_almost_equal(y[-1][1], 3.0)
nose.tools.assert_almost_equal(y[-1][2], 2.0)
def test_switches(self):
"""
This tests that the switches are actually turned when override.
"""
f = lambda t,x,sw: N.array([1.0])
state_events = lambda t,x,sw: N.array([x[0]-1.])
def handle_event(solver, event_info):
solver.sw = [False] #Override the switches to point to another instance
mod = Explicit_Problem(f,[0.0])
mod.sw0 = [True]
mod.state_events = state_events
mod.handle_event = handle_event
sim = Radau5ODE(mod)
assert sim.sw[0] == True
sim.simulate(3)
assert sim.sw[0] == False
def test_init(self):
#Test both y0 in problem and not.
sim = Radau5ODE(self.mod)
assert sim._leny == 2