def test_estimate(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"
with pytest.raises(ValueError):
snl.estimate(SIR)
snl.trend(include_init_phase=True, show_figure=False)
snl.disable(phases=["0th"])
with pytest.raises(AttributeError):
snl.estimate_history(phase="1th")
# Parameter estimation
with pytest.raises(KeyError):
snl.estimate(SIR, phases=["30th"])
with pytest.raises(ValueError):
snl.estimate(model=SIR, tau=1440)
snl.enable(phases=["0th"])
with pytest.raises(TypeError):
snl.estimate(model=SIR, phases="1st")
with pytest.raises(ValueError):
snl.estimate(model=SIR, phases=["0th"])
snl.clear(include_past=True)
snl.trend(show_figure=False)
snl.estimate(SIR)
# Estimation history
snl.estimate_history(phase="1st")
# Estimation accuracy
snl.estimate_accuracy(phase="1st")
# Get a value
snl.get(Term.RT)
with pytest.raises(KeyError):
snl.get("feeling")
def test_trend(self, jhu_data, population_data, country):
# Setting
snl = Scenario(jhu_data, population_data, country)
snl.first_date = "01Apr2020"
snl.last_date = "01Aug2020"
# Deprecated
warnings.simplefilter("error")
with pytest.raises(DeprecationWarning):
snl.trend(include_init_phase=False, show_figure=False)
warnings.simplefilter("ignore")
snl.trend(include_init_phase=False, show_figure=False)
# S-R trend analysis
snl.trend(show_figure=False)
assert snl["Main"]
with pytest.raises(ValueError):
snl.trend(show_figure=False, n_points=3)
# Disable/enable
length = len(snl["Main"])
snl.disable(phases=["0th"], name="Main")
assert len(snl["Main"]) == length - 1
snl.enable(phases=["0th"], name="Main")
assert len(snl["Main"]) == length
with pytest.raises(TypeError):
snl.enable(phases="0th", name="Main")
with pytest.raises(TypeError):
snl.disable(phases="1st", name="Main")
def test_simulate(self, jhu_data, population_data, country):
warnings.simplefilter("ignore", category=UserWarning)
warnings.simplefilter("ignore", category=DeprecationWarning)
# Setting
snl = Scenario(jhu_data, population_data, country)
snl.first_date = "01Apr2020"
snl.last_date = "01May2020"
with pytest.raises(ValueError):
snl.simulate()
with pytest.raises(ValueError):
snl.track()
snl.trend(show_figure=False)
# Parameter estimation
with pytest.raises(ValueError):
# Deprecated
snl.param_history(["rho"])
all_phases = snl.summary().index.tolist()
snl.disable(all_phases[:-2])
with pytest.raises(NameError):
snl.simulate()
snl.estimate(SIRF, timeout=5, timeout_iteration=5)
# Simulation
snl.simulate(variables=[Term.C, Term.CI, Term.F, Term.R])
snl.simulate(phases=all_phases[-2:])
# Parameter history (Deprecated)
snl.param_history([Term.RT], divide_by_first=False)
snl.param_history(["rho"])
snl.param_history(["rho"], show_figure=False)
snl.param_history(["rho"], show_box_plot=False)
with pytest.raises(KeyError):
snl.param_history(["feeling"])
# Comparison of scenarios
snl.describe()
snl.track()
snl.history(target="Rt")
snl.history(target="sigma")
snl.history(target="rho", show_figure=False)
snl.history(target="Infected", phases=all_phases[-2:])
with pytest.raises(KeyError):
snl.history(target="temperature")
# Change rate of parameters
snl.history_rate(name="Main")
snl.history_rate(
name="Main", params=["theta", "kappa"], show_figure=False)
with pytest.raises(TypeError):
snl.history_rate(params="", name="Main")
# Add new scenario
snl.add(end_date="01Sep2020", name="New")
snl.describe()
def test_trend(self, jhu_data, population_data, country):
# Setting
snl = Scenario(jhu_data, population_data, country)
snl.first_date = "01Apr2020"
snl.last_date = "01Aug2020"
snl.trend(show_figure=False)
assert snl["Main"]
with pytest.raises(ValueError):
snl.trend(show_figure=False, n_points=3)
# Disable/enable
length = len(snl["Main"])
snl.disable(phases=["0th"], name="Main")
assert len(snl["Main"]) == length - 1
snl.enable(phases=["0th"], name="Main")
assert len(snl["Main"]) == length
with pytest.raises(TypeError):
snl.enable(phases="0th", name="Main")
with pytest.raises(TypeError):
snl.disable(phases="1st", name="Main")
def test_score_error(self, jhu_data, population_data, country):
snl = Scenario(jhu_data, population_data, country)
with pytest.raises(ValueError):
snl.score()
snl.trend(show_figure=False)
with pytest.raises(NameError):
snl.score()
all_phases = snl.summary().index.tolist()
snl.disable(phases=all_phases[:-2])
snl.estimate(SIRF, timeout=10)
with pytest.raises(TypeError):
snl.score(phases="0th")
with pytest.raises(KeyError):
snl.score(phases=["100th"])
with pytest.raises(TypeError):
snl.score(variables="Infected")
with pytest.raises(KeyError):
snl.score(variables=["Susceptible"])
with pytest.raises(ValueError):
snl.score(metrics="Subjective evaluation")
with pytest.raises(ValueError):
snl.score(phases=["0th"], past_days=100)