def _run_SEIR_BAYES_model(N,
E0,
I0,
R0,
R0__params: 'repr. rate mean and std',
gamma_inv_params: 'removal rate mean and std',
alpha_inv_params: 'incubation rate mean and std',
t_max,
runs,
interactive=True,
scale='log',
show_uncertainty=True):
S, E, I, R, t_space = run_SEIR_BAYES_model(N, E0, I0, R0, R0__params,
gamma_inv_params,
alpha_inv_params, t_max, runs)
if interactive:
return seir_bayes_interactive_plot(N,
E0,
I0,
R0,
t_max,
runs,
S,
E,
I,
R,
t_space,
scale=scale,
show_uncertainty=show_uncertainty)
return seir_bayes_plot(N, E0, I0, R0, R0__params, gamma_inv_params,
alpha_inv_params, t_max, runs, S, E, I, R, t_space)
def _run_SEIR_BAYES_model(N, E0, I0, R0, R0__loc, R0__scale, gamma_loc,
gamma_scale, alpha_loc, alpha_scale, t_max, runs):
S, E, I, R, t_space = st.cache(run_SEIR_BAYES_model)(
N, E0, I0, R0, R0__loc, R0__scale, gamma_loc, gamma_scale, alpha_loc,
alpha_scale, t_max, runs)
fig = seir_bayes_plot(N, E0, I0, R0, R0__loc, R0__scale, gamma_loc,
gamma_scale, alpha_loc, alpha_scale, t_max, runs, S,
E, I, R, t_space)
return fig
