Merge pull request #170 from CodeForPhilly/add_cli

Add cli

Author: quinn-dougherty

cli.py

@@ -0,0 +1,105 @@
+"""CLI for CHIME."""
+
+from argparse import (
+    Action,
+    ArgumentParser,
+)
+from datetime import datetime
+
+from pandas import DataFrame
+
+from penn_chime.defaults import RateLos
+from penn_chime.models import Parameters
+from penn_chime.utils import build_admissions_df, build_census_df
+
+
+class FromFile(Action):
+    """From File."""
+
+    def __call__(self, parser, namespace, values, option_string=None):
+        with values as f:
+            parser.parse_args(f.read().split(), namespace)
+
+
+def validator(cast, min_value, max_value):
+    """Validator."""
+
+    def validate(string):
+        """Validate."""
+        value = cast(string)
+        if min_value is not None:
+            assert value >= min_value
+        if max_value is not None:
+            assert value <= max_value
+        return value
+
+    return validate
+
+
+def parse_args():
+    """Parse args."""
+    parser = ArgumentParser(description='CHIME')
+
+    parser.add_argument('--file', type=open, action=FromFile)
+    parser.add_argument(
+        '--prefix',
+        type=str,
+        default=datetime.now().strftime("%Y.%m.%d.%H.%M."),
+    )
+
+    for arg, cast, min_value, max_value, help in (
+        ('--current-hospitalized', int, 0, None, "Currently Hospitalized COVID-19 Patients (>= 0)"),
+        ('--doubling-time', float, 0.0, None, "Doubling time before social distancing (days)"),
+        ('--hospitalized-los', int, 0, None, "Hospitalized Length of Stay (days)"),
+        ('--hospitalized-rate', float, 0.00001, 1.0, "Hospitalized Rate: 0.00001 - 1.0"),
+        ('--icu-los', int, 0, None, "ICU Length of Stay (days)"),
+        ('--icu-rate', float, 0.0, 1.0, "ICU Rate: 0.0 - 1.0"),
+        ('--known-infected', int, 0, None,
+            "Currently Known Regional Infections (>=0) (only used to compute detection rate - does not change projections)"),
+        ('--market_share', float, 0.00001, 1.0, "Hospital Market Share (0.00001 - 1.0)"),
+        ('--n-days', int, 0, None, "Nuber of days to project >= 0"),
+        ('--relative-contact-rate', float, 0.0, 1.0, "Social Distancing Reduction Rate: 0.0 - 1.0"),
+        ('--susceptible', int, 1, None, "Regional Population >= 1"),
+        ('--ventilated-los', int, 0, None, "Hospitalized Length of Stay (days)"),
+        ('--ventilated-rate', float, 0.0, 1.0, "Ventilated Rate: 0.0 - 1.0"),
+    ):
+        parser.add_argument(arg, type=validator(cast, min_value, max_value))
+    return parser.parse_args()
+
+
+def main():
+    """Main."""
+    a = parse_args()
+
+    p = Parameters(
+        current_hospitalized=a.current_hospitalized,
+        doubling_time=a.doubling_time,
+        known_infected=a.known_infected,
+        market_share=a.market_share,
+        relative_contact_rate=a.relative_contact_rate,
+        susceptible=a.susceptible,
+        n_days=a.n_days,
+        hospitalized=RateLos(a.hospitalized_rate, a.hospitalized_los),
+        icu=RateLos(a.icu_rate, a.icu_los),
+        ventilated=RateLos(a.ventilated_rate, a.ventilated_los),
+    )
+
+    raw_df = DataFrame({
+        "Susceptible": p.susceptible_v,
+        "Infected": p.infected_v,
+        "Recovered": p.recovered_v,
+    })
+    admits_df = build_admissions_df(p.n_days, *p.dispositions)
+    census_df = build_census_df(admits_df, *p.lengths_of_stay)
+
+    prefix = a.prefix
+    for df, name in (
+        (raw_df, 'raw'),
+        (admits_df, 'admits'),
+        (census_df, 'census'),
+    ):
+        df.to_csv(prefix + name + '.csv')
+
+
+if __name__ == '__main__':
+    main()

penn_chime/models.py

@@ -22,7 +22,8 @@ def __init__(
         icu: RateLos,
         ventilated: RateLos,
 
-        max_y_axis: int
+        max_y_axis: int = None,
+        n_days: int = None
     ):
         self.current_hospitalized = current_hospitalized
         self.doubling_time = doubling_time
@@ -84,6 +85,13 @@ def __init__(
         # TODO constrain values np.log2(...) > 0.0
         self.doubling_time_t = 1.0 / np.log2(beta * susceptible - gamma + 1)
 
+        self.dispositions = None
+        self.susceptible_v = self.infected_v = self.recovered_v = None
+        self.hospitalized_v = self.icu_v = self.ventilated_v = None
+
+        if n_days is not None:
+            self.n_days = n_days
+
     @property
     def n_days(self):
         return self._n_days
@@ -92,10 +100,6 @@ def n_days(self):
     def n_days(self, n_days: int):
         self._n_days = n_days
 
-        # s := Susceptible, able to be infected
-        # i := Infected, currently infected with the virus
-        # r := Recovered, no longer infected with the virus
-
         s_v, i_v, r_v = sim_sir(
             self.susceptible,
             self.infected,

settings.cfg

@@ -0,0 +1,13 @@
+--current-hospitalized 6
+--doubling-time 6.0
+--known-infected 157
+--relative-contact-rate 0.0
+--hospitalized-los 7
+--hospitalized-rate 0.05
+--icu-los 9
+--icu-rate 0.02
+--market_share 0.15
+--n-days 60
+--susceptible 4119405
+--ventilated-los 10
+--ventilated-rate 0.01