def test_records(self, jhu_data, population_data):
scenario = Scenario(jhu_data, population_data, country="Italy")
record_df = scenario.records(show_figure=False)
warnings.filterwarnings("ignore", category=UserWarning)
record_df = scenario.records(show_figure=True)
assert isinstance(record_df, pd.DataFrame)
assert set(record_df.columns) == set(Term.NLOC_COLUMNS)
def test_interactive(self, jhu_data, population_data, country):
with pytest.raises(ValueError):
Scenario()
# Setting
scenario = Scenario(country=country)
scenario.register(jhu_data, population_data)
# Force interactive
scenario._interactive = True
warnings.filterwarnings("ignore", category=UserWarning)
scenario.records(show_figure=True)
def test_records(self, jhu_data, population_data, country):
warnings.simplefilter("ignore", category=UserWarning)
# Setting
snl = Scenario(jhu_data, population_data, country)
snl.first_date = "01Apr2020"
snl.last_date = "01Aug2020"
# Test
df = snl.records(show_figure=False)
assert isinstance(df, pd.DataFrame)
assert set(df.columns) == set(Term.NLOC_COLUMNS)
dates = df[Term.DATE]
assert dates.min() == Term.date_obj(snl.first_date)
assert dates.max() == Term.date_obj(snl.last_date)
df2 = snl.records(show_figure=True)
assert isinstance(df2, pd.DataFrame)
assert set(df2.columns) == set(Term.NLOC_COLUMNS)
def test_complement(self, jhu_data, population_data, country):
max_ignored = 100
# Auto complement
snl = Scenario(jhu_data,
population_data,
country,
auto_complement=True)
recovered = snl.records(show_figure=False)[Term.R]
assert recovered[recovered > max_ignored].value_counts().max() == 1
# Restore the raw data
snl.complement_reverse()
recovered = snl.records(show_figure=False)[Term.R]
assert recovered[recovered > max_ignored].value_counts().max() != 1
# Complement
snl.complement()
recovered = snl.records(show_figure=False)[Term.R]
assert recovered[recovered > max_ignored].value_counts().max() == 1
def test_scenario(self):
area = {"country": "Theoretical"}
# Set-up example dataset (from 01Jan2020 to 31Jan2020)
example_data = ExampleData(tau=1440, start_date="01Jan2020")
example_data.add(SIRF, step_n=30, **area)
# Population value
population_data = PopulationData(filename=None)
population_data.update(SIRF.EXAMPLE["population"], **area)
# Set-up Scenario instance
snl = Scenario(tau=1440, **area)
snl.register(example_data, population_data)
# Check records
record_df = snl.records(variables="CFR")
assert set(record_df.columns) == set(
[Term.DATE, Term.C, Term.F, Term.R])
# Add a past phase to 31Jan2020 with parameter values
snl.add(model=SIRF, **SIRF.EXAMPLE["param_dict"])
# Check summary
df = snl.summary()
assert not df.empty
assert len(df) == 1
assert Term.RT in df
# Main scenario
snl.add(end_date="31Dec2020", name="Main")
assert snl.get(Term.RT, phase="last", name="Main") == 2.50
# Lockdown scenario
snl.clear(name="Lockdown")
rho_lock = snl.get("rho", phase="0th") * 0.5
snl.add(end_date="31Dec2020", name="Lockdown", rho=rho_lock)
assert snl.get(Term.RT, phase="last", name="Lockdown") == 1.25
# Medicine scenario
snl.clear(name="Medicine")
kappa_med = snl.get("kappa", phase="0th") * 0.5
sigma_med = snl.get("sigma", phase="0th") * 2
snl.add(end_date="31Dec2020",
name="Medicine",
kappa=kappa_med,
sigma=sigma_med)
assert snl.get(Term.RT, phase="last", name="Medicine") == 1.31
# Add vaccine scenario
snl.clear(name="Vaccine")
rho_vac = snl.get("rho", phase="0th") * 0.8
kappa_vac = snl.get("kappa", phase="0th") * 0.6
sigma_vac = snl.get("sigma", phase="0th") * 1.2
snl.add(end_date="31Dec2020",
name="Vaccine",
rho=rho_vac,
kappa=kappa_vac,
sigma=sigma_vac)
assert snl.get(Term.RT, phase="last", name="Vaccine") == 1.72
# Description
snl.describe()
# History
snl.history("Rt")
snl.history("rho")
snl.history("Infected")
snl.history_rate(name="Medicine")
snl.simulate(name="Vaccine")
def test_records(self, jhu_data, population_data):
scenario = Scenario(jhu_data, population_data, country="Italy")
record_df = scenario.records(show_figure=False)
assert isinstance(record_df, pd.DataFrame)
assert set(record_df.columns) == set(Term.NLOC_COLUMNS)