def test_snapshot():
sc.heading('Testing snapshot analyzer')
sim = cv.Sim(pars, analyzers=cv.snapshot('2020-04-04', '2020-04-14'))
sim.run()
snapshot = sim.get_analyzer()
people1 = snapshot.snapshots[0] # Option 1
people2 = snapshot.snapshots['2020-04-04'] # Option 2
people3 = snapshot.get('2020-04-14') # Option 3
people4 = snapshot.get(34) # Option 4
people5 = snapshot.get() # Option 5
assert people1 == people2, 'Snapshot options should match but do not'
assert people3 != people4, 'Snapshot options should not match but do'
return people5
def test_import1variant(do_plot=False, do_show=True, do_save=False):
sc.heading('Test introducing a new variant partway through a sim')
variant_pars = {
'rel_beta': 1.5,
}
pars = {'beta': 0.01}
variant = cv.variant(variant_pars,
days=1,
n_imports=20,
label='Variant 2: 1.5x more transmissible')
sim = cv.Sim(use_waning=True,
pars=pars,
variants=variant,
analyzers=cv.snapshot(30, 60),
**pars,
**base_pars)
sim.run()
return sim
def test_import1strain(do_plot=False, do_show=True, do_save=False):
sc.heading('Test introducing a new strain partway through a sim')
strain_pars = {
'rel_beta': 1.5,
}
pars = {'beta': 0.01}
strain = cv.strain(strain_pars,
days=1,
n_imports=20,
label='Strain 2: 1.5x more transmissible')
sim = cv.Sim(use_waning=True,
pars=pars,
strains=strain,
analyzers=cv.snapshot(30, 60),
**pars,
**base_pars)
sim.run()
return sim
'''
Test the people snapshot analyzer.
'''
import covasim as cv
sim = cv.Sim(analyzers=cv.snapshot('2020-04-04', '2020-04-14'))
sim.run()
snapshot = sim['analyzers'][0]
people = snapshot.snapshots[0] # Option 1
people = snapshot.snapshots['2020-04-04'] # Option 2
people = snapshot.get('2020-04-14') # Option 3
people = snapshot.get(34) # Option 4
return sim
def test_efficacy(do_plot=False, do_show=True, do_save=False):
sc.heading('Test the efficacy of infection against reinfection')
pars = sc.mergedicts(base_pars, {
'beta': 0.015,
'pop_infected': 100,
'pop_size': 50_000,
'n_days': 180,
})
interventions = [cv.change_beta([30, 90], [0.3, 1])]
sim = cv.Sim(
use_waning=True,
analyzers=cv.snapshot(90),
pars=pars,
interventions=interventions,
)
sim.run()
# Number of people exposed during the first wave:
snap = sim.get_analyzer()
d1 = 90
people0 = snap.get(d1)
people1 = sim.people
trial_arm_size = len(cvu.true(people0.n_infections > 0))
control_arm_size = len(cvu.true(people0.n_infections == 0))
trial_not_infected = len(
'''
Confirm that with default settings, all analyzers can be exported as JSONs.
'''
import sciris as sc
import covasim as cv
datafile = sc.thisdir(__file__, aspath=True).parent / 'example_data.csv'
# Create and runt he sim
sim = cv.Sim(analyzers=[
cv.snapshot(days='2020-04-04'),
cv.age_histogram(),
cv.daily_age_stats(),
cv.daily_stats()
],
datafile=datafile)
sim.run()
# Compute extra analyzers
tt = sim.make_transtree()
fit = sim.compute_fit()
# Construct list of all analyzers
analyzers = sim['analyzers'] + [tt, fit]
# Make jsons
jsons = {}
for an in analyzers:
print(f'Working on analyzer {an.label}...')
jsons[an.label] = an.to_json()
