def test_correct_caching2(self):
# setup equation
eqn = Seir(population=1)
# setup ode solver
ti = 0.
tf = 2.
n_steps = 3
rk = RKSolver(ti, tf, n_steps)
rk.output_frequency = 1
rk.set_output_storing_flag(True)
rk.equation = eqn
u0 = np.array([100., 0., 10., 0.])
du0_dp = np.zeros((eqn.n_components(), eqn.n_parameters()))
rk.set_initial_condition(u0, du0_dp)
rk.set_output_gradient_flag(True)
# setup cached simulation object
cached_sim = CachedSEIRSimulation(rk)
params = np.array([2.3, 0.2, 1. / 3., 1. / 4.])
(f, df) = cached_sim(params)
f1 = np.copy(f)
df1 = np.copy(df)
f *= 0.
df += 0.
(f2, df2) = cached_sim(params)
assert np.allclose(f1, f2)
assert np.allclose(df1, df2)
def test_correct_caching3(self):
# setup equation
eqn = Seir(population=1)
# setup ode solver
ti = 0.
tf = 2.
n_steps = 3
rk = RKSolver(ti, tf, n_steps)
rk.output_frequency = 1
rk.set_output_storing_flag(True)
rk.equation = eqn
u0 = np.array([100., 0., 10., 0.])
rk.set_initial_condition(u0)
# setup cached simulation object
cached_sim = CachedSEIRSimulation(rk)
cached_sim.set_gradient_flag(False)
params = np.array([2.3, 0.2, 1. / 3., 1. / 4.])
f = cached_sim(params)[0]
f1 = np.copy(f)
params2 = np.array([2.32, 0.2, 1. / 3., 1. / 4.])
f2 = cached_sim(params2)[0]
assert not np.allclose(f1, f2)
def test_interface(self):
rk = RKSolver(0, 1)
rk.initial_time = 0.5
rk.final_time = 5
rk.n_steps = 10
self.assertEqual(rk.initial_time,0.5)
self.assertEqual(rk.final_time,5)
self.assertEqual(rk.n_steps,10)
eqn = Seir()
rk.equation = eqn
self.assertEqual(rk.equation, eqn)
rk.output_frequency = 20
self.assertEqual(rk.output_frequency, 20)