def test_binomial_vs_poisson(R0, I):
R0 = torch.tensor(R0)
I = torch.tensor(I)
d1 = infection_dist(individual_rate=R0, num_infectious=I)
d2 = infection_dist(individual_rate=R0, num_infectious=I,
num_susceptible=1000., population=1000.)
assert isinstance(d1, dist.Poisson)
assert isinstance(d2, dist.Binomial)
assert_dist_close(d1, d2)
def test_beta_binomial_vs_negative_binomial(R0, I, k):
R0 = torch.tensor(R0)
I = torch.tensor(I)
d1 = infection_dist(individual_rate=R0, num_infectious=I, concentration=k)
d2 = infection_dist(individual_rate=R0, num_infectious=I, concentration=k,
num_susceptible=1000., population=1000.)
assert isinstance(d1, dist.NegativeBinomial)
assert isinstance(d2, dist.BetaBinomial)
assert_dist_close(d1, d2)
def test_negative_binomial_vs_poisson(R0, I):
R0 = torch.tensor(R0)
I = torch.tensor(I)
d1 = infection_dist(individual_rate=R0, num_infectious=I)
d2 = infection_dist(individual_rate=R0, num_infectious=I,
concentration=200.)
assert isinstance(d1, dist.Poisson)
assert isinstance(d2, dist.NegativeBinomial)
assert_dist_close(d1, d2)
def test_beta_binomial_vs_binomial(R0, I):
R0 = torch.tensor(R0)
I = torch.tensor(I)
d1 = infection_dist(individual_rate=R0, num_infectious=I,
num_susceptible=20., population=30.)
d2 = infection_dist(individual_rate=R0, num_infectious=I,
num_susceptible=20., population=30.,
concentration=200.)
assert isinstance(d1, dist.Binomial)
assert isinstance(d2, dist.BetaBinomial)
assert_dist_close(d1, d2)