def test_linear_rates(self):
epi = EpiModel(list("SEIR"))
epi.add_transition_processes([
("E", 1.0, "I"),
("I", 1.0, "R"),
])
linear_rates = [ConstantLinearRate(1.0, 1), ConstantLinearRate(1.0, 2)]
linear_events = [np.array([0, -1, +1, 0]), np.array([0, 0, -1, +1.])]
for r0, r1 in zip(linear_rates, epi.linear_rate_functions):
assert (r0(0, [0.1, 0.2, 0.3, 0.4, 0.5]) == r1(
0, [0.1, 0.2, 0.3, 0.4, 0.5]))
for e0, e1 in zip(linear_events, epi.linear_event_updates):
assert (all([_e0 == _e1 for _e0, _e1 in zip(e0, e1)]))
epi = EpiModel(list("SEIR"))
_r0 = lambda t, y: 2 + np.cos(t)
_r1 = lambda t, y: 2 + np.sin(t)
epi.add_transition_processes([
("E", _r0, "I"),
("I", _r1, "R"),
])
linear_rates = [DynamicLinearRate(_r0, 1), DynamicLinearRate(_r1, 2)]
linear_events = [np.array([0, -1, +1, 0]), np.array([0, 0, -1, +1.])]
for r0, r1 in zip(linear_rates, epi.linear_rate_functions):
assert (r0(0, [0.1, 0.2, 0.3, 0.4, 0.5]) == r1(
0, [0.1, 0.2, 0.3, 0.4, 0.5]))
for e0, e1 in zip(linear_events, epi.linear_event_updates):
assert (all([_e0 == _e1 for _e0, _e1 in zip(e0, e1)]))
def test_correcting_for_declining_pop_size(self):
A, B = list("AB")
epi = EpiModel([A, B], 10, correct_for_dynamical_population_size=True)
epi.add_transition_processes([
#(None, 0.1, A),
])
epi.add_fusion_processes([
(A, B, 1, B),
])
epi.set_initial_conditions({B: 4, A: 6})
tt = np.linspace(0, 30)
result = epi.integrate(tt)
#from matplotlib import pyplot as pl
#pl.plot(tt, result[A], label=A)
#pl.plot(tt, result[B], label=B)
epi.correct_for_dynamical_population_size = False
result = epi.integrate(tt)