model_WAVE2 = models.COVID19_SEIRD(
initial_states, params, time_dependent_parameters={'Nc': policies_WAVE2})
# -------------------
# Simulate the models
# -------------------
out_WAVE1 = model_WAVE1.sim('2020-07-07',
start_date=start_calibration_WAVE1,
warmup=warmup,
N=args.n_samples,
draw_fcn=draw_fcn_WAVE1,
samples=samples_dict_WAVE1)
simtime_WAVE1, df_2plot_WAVE1 = output_to_visuals(
out_WAVE1, ['H_in', 'H_tot', 'ICU', 'D', 'R'],
args.n_samples,
args.n_draws_per_sample,
LL=conf_int / 2,
UL=1 - conf_int / 2)
out_WAVE2 = model_WAVE2.sim('2021-02-01',
start_date=start_calibration_WAVE2,
warmup=0,
N=args.n_samples,
draw_fcn=draw_fcn_WAVE2,
samples=samples_dict_WAVE2)
simtime_WAVE2, df_2plot_WAVE2 = output_to_visuals(
out_WAVE2, ['H_in', 'H_tot', 'ICU', 'D', 'R'],
args.n_samples,
args.n_draws_per_sample,
LL=conf_int / 2,
UL=1 - conf_int / 2)
N=n_samples,
draw_fcn=draw_fcn,
samples=samples_dict)
# ------------------------------
# Function to add poisson draws
# ------------------------------
print('\n5) Adding a-posteriori uncertainty')
conf_int = 0.05
from covid19model.models.utils import output_to_visuals
simtime, df_2plot = output_to_visuals(out, ['H_in', 'H_tot', 'ICU', 'D', 'R'],
n_samples,
n_draws_per_sample,
LL=conf_int / 2,
UL=1 - conf_int / 2)
# -----------
# Visualizing
# -----------
print('\n6) Visualizing fit \n')
# Plot
fig, ax = plt.subplots(figsize=(10, 5))
# Incidence
ax.fill_between(pd.to_datetime(out['time'].values),
df_2plot['H_in', 'LL'],
df_2plot['H_in', 'UL'],
for ldx, order in enumerate(orders):
print('\t#### Vaccination order: ' + description_order[ldx])
model.parameters.update({'vacc_order': order})
# --------------
# Simulate model
# --------------
out_vacc = model.sim(end_sim,
start_date=start_sim,
warmup=warmup,
N=n_samples,
draw_fcn=draw_fcn,
samples=samples_dict)
simtime, df_2plot = output_to_visuals(out_vacc,
['H_in', 'H_tot'],
n_samples,
args.n_draws_per_sample,
LL=conf_int / 2,
UL=1 - conf_int / 2)
# Append to dataframe
columnnames = [
'incidences_mean', 'incidences_median', 'incidences_LL',
'incidences_UL', 'load_mean', 'load_median', 'load_LL',
'load_UL'
]
data = [
df_2plot['H_in', 'mean'], df_2plot['H_in', 'median'],
df_2plot['H_in', 'LL'], df_2plot['H_in', 'UL'],
df_2plot['H_tot', 'mean'], df_2plot['H_tot', 'median'],
df_2plot['H_tot', 'LL'], df_2plot['H_tot', 'UL']
]
for i in range(len(columnnames)):