def test_fusion_and_adding_rates(self):
A, B, C = list("ABC")
epi = EpiModel(list("ABC"))
# this should not raise a warning that rates do not sum to zero
# as it will be actively suppressed
epi.add_fusion_processes([
(A, B, 1, C),
])
with self.assertWarns(UserWarning):
# this should raise a warning that rates do not sum to zero
epi.add_quadratic_events([
((A, B), 1, [(C, -1), (A, +1)]),
])
# now rates should sum to zero
epi.add_quadratic_events([
((A, B), 1, [(B, +1)]),
])
with self.assertWarns(UserWarning):
# this should raise a warning that rates do not sum to zero
epi.add_linear_events([((A, ), 1, [(B, -1)])])
def test_stochastic_fission(self):
A, B, C = list("ABC")
N = 10
epi = EpiModel([A, B, C],
N,
correct_for_dynamical_population_size=True)
epi.add_fusion_processes([
(A, B, 1.0, C),
])
epi.set_initial_conditions({A: 5, B: 5})
t, res = epi.simulate(1e9)
assert (res[C][-1] == 5)
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)