def run_projection(self, p: Parameters, policy: Sequence[Tuple[float, int]]):
raw = sim_sir(
self.susceptible,
self.infected,
p.recovered,
self.gamma,
-self.i_day,
policy
)
calculate_dispositions(raw, self.rates, p.market_share)
calculate_admits(raw, self.rates)
calculate_census(raw, self.days)
return raw
def test_sim_sir():
"""
Rounding to move fast past decimal place issues
"""
raw = sim_sir(
5,
6,
7,
0.1,
0,
[(0.1, 40)], # s # i # r # gamma # i_day # beta1 # n_days1
)
assert round(raw["susceptible"][0], 0) == 5
assert round(raw["infected"][0], 2) == 6
assert round(raw["recovered"][0], 0) == 7
assert round(raw["susceptible"][-1], 2) == 0
assert round(raw["infected"][-1], 2) == 0.18
assert round(raw["recovered"][-1], 2) == 17.82
def fixture_penn_chime_raw_df_no_policy(penn_chime_setup) -> DataFrame:
"""Runs penn_chime SIR model for no social policies
"""
p, simsir = penn_chime_setup
n_days = simsir.raw_df.day.max() - simsir.raw_df.day.min()
policies = [(simsir.beta, n_days)]
raw = sim_sir(
simsir.susceptible,
simsir.infected,
p.recovered,
simsir.gamma,
-simsir.i_day,
policies,
)
calculate_dispositions(raw, simsir.rates, market_share=p.market_share)
calculate_admits(raw, simsir.rates)
calculate_census(raw, simsir.days)
raw_df = DataFrame(raw)
raw_df.index = simsir.raw_df.date
return raw_df.fillna(0)