Merge branch 'quinn_issue_255' of https://github.com/CodeForPhilly/chime into quinn_issue_255

Author: quinn-dougherty

src/penn_chime/presentation.py

@@ -116,7 +116,7 @@ def display_header(st, m, p):
     return None
 
 
-class InputWrapper:
+class Input:
     """Helper to separate Streamlit input definition from creation/rendering"""
     def __init__(self, st_obj, label, value, kwargs):
         self.st_obj = st_obj
@@ -128,17 +128,25 @@ def __call__(self):
         return self.st_obj(self.label, value=self.value, **self.kwargs)
 
 
-class NumberInputWrapper(InputWrapper):
+class NumberInput(Input):
     def __init__(self, st_obj, label, min_value=None, max_value=None, value=None, step=None, format=None, key=None):
         kwargs = dict(min_value=min_value, max_value=max_value, step=step, format=format, key=key)
         super().__init__(st_obj.number_input, label, value, kwargs)
 
-class DateInputWrapper(InputWrapper):
+class DateInput(Input):
     def __init__(self, st_obj, label, value=None, key=None):
         kwargs = dict(key=key)
         super().__init__(st_obj.date_input, label, value, kwargs)
 
-class CheckboxWrapper(InputWrapper):
+class PercentInput(NumberInput):
+    def __init__(self, st_obj, label, min_value=0.0, max_value=100.0, value=None, step=FLOAT_INPUT_STEP, format="%f", key=None):
+        super().__init__(st_obj, label, min_value, max_value, value * 100.0, step, format, key)
+
+    def __call__(self):
+        return super().__call__() / 100.0
+
+
+class CheckboxInput(Input):
     def __init__(self, st_obj, label, value=None, key=None):
         kwargs = dict(key=key)
         super().__init__(st_obj.checkbox, label, value, kwargs)
@@ -153,145 +161,127 @@ def display_sidebar(st, d: Constants) -> Parameters:
     if d.known_infected < 1:
         raise ValueError("Known cases must be larger than one to enable predictions.")
     st_obj = st.sidebar
-    current_hospitalized_input = NumberInputWrapper(
+    current_hospitalized_input = NumberInput(
         st_obj,
         "Currently Hospitalized COVID-19 Patients",
         min_value=0,
         value=d.current_hospitalized,
         step=1,
         format="%i",
     )
-    n_days_input = NumberInputWrapper(
+    n_days_input = NumberInput(
         st_obj,
         "Number of days to project",
         min_value=30,
         value=d.n_days,
         step=1,
         format="%i",
     )
-    doubling_time_input = NumberInputWrapper(
+    doubling_time_input = NumberInput(
         st_obj,
         "Doubling time before social distancing (days)",
         min_value=FLOAT_INPUT_MIN,
         value=d.doubling_time,
         step=FLOAT_INPUT_STEP,
         format="%f",
     )
-    date_first_hospitalized_input = DateInputWrapper(
+    date_first_hospitalized_input = DateInput(
         st_obj,
         "Date of first hospitalized case",
         value=d.date_first_hospitalized,
     )
-    relative_contact_rate_input = NumberInputWrapper(
+    relative_contact_pct_input = PercentInput(
         st_obj,
         "Social distancing (% reduction in social contact)",
-        min_value=0.0,
-        max_value=100.0,
-        value=d.relative_contact_rate * 100.0,
-        step=FLOAT_INPUT_STEP,
-        format="%f",
+        value=d.relative_contact_rate,
     )
-    hospitalized_rate_input = NumberInputWrapper(
+    hospitalized_pct_input = PercentInput(
         st_obj,
         "Hospitalization %(total infections)",
-        min_value=0.0,
-        max_value=100.0,
-        value=d.hospitalized.rate * 100,
-        step=FLOAT_INPUT_STEP,
-        format="%f",
+        value=d.hospitalized.rate,
     )
-    icu_rate_input = NumberInputWrapper(
+    icu_pct_input = PercentInput(
         st_obj,
         "ICU %(total infections)",
-        min_value=0.0,
-        max_value=100.0,
-        value=d.icu.rate * 100,
-        step=FLOAT_INPUT_STEP,
-        format="%f",
+        value=d.icu.rate,
     )
-    ventilated_rate_input = NumberInputWrapper(
+    ventilated_pct_input = PercentInput(
         st_obj,
         "Ventilated %(total infections)",
-        min_value=0.0,
-        max_value=100.0,
-        value=d.ventilated.rate * 100,
-        step=FLOAT_INPUT_STEP,
-        format="%f",
+        value=d.ventilated.rate,
     )
-    hospitalized_los_input = NumberInputWrapper(
+    hospitalized_los_input = NumberInput(
         st_obj,
         "Hospital Length of Stay",
         min_value=0,
         value=d.hospitalized.length_of_stay,
         step=1,
         format="%i",
     )
-    icu_los_input = NumberInputWrapper(
+    icu_los_input = NumberInput(
         st_obj,
         "ICU Length of Stay",
         min_value=0,
         value=d.icu.length_of_stay,
         step=1,
         format="%i",
     )
-    ventilated_los_input = NumberInputWrapper(
+    ventilated_los_input = NumberInput(
         st_obj,
         "Vent Length of Stay",
         min_value=0,
         value=d.ventilated.length_of_stay,
         step=1,
         format="%i",
     )
-    market_share_input = NumberInputWrapper(
+    market_share_pct_input = PercentInput(
         st_obj,
         "Hospital Market Share (%)",
         min_value=FLOAT_INPUT_MIN,
-        max_value=100.0,
-        value=d.market_share * 100,
-        step=FLOAT_INPUT_STEP,
-        format="%f",
+        value=d.market_share,
     )
-    population_input = NumberInputWrapper(
+    population_input = NumberInput(
         st_obj,
         "Regional Population",
         min_value=1,
         value=d.region.population,
         step=1,
         format="%i",
     )
-    known_infected_input = NumberInputWrapper(
+    known_infected_input = NumberInput(
         st_obj,
         "Currently Known Regional Infections (only used to compute detection rate - does not change projections)",
         min_value=0,
         value=d.known_infected,
         step=1,
         format="%i",
     )
-    as_date_input = CheckboxWrapper(st_obj, "Present result as dates instead of days", value=False)
-    max_y_axis_set_input = CheckboxWrapper(st_obj, "Set the Y-axis on graphs to a static value")
-    max_y_axis_input = NumberInputWrapper(st_obj, "Y-axis static value", value=500, format="%i", step=25)
+    as_date_input = CheckboxInput(st_obj, "Present result as dates instead of days", value=False)
+    max_y_axis_set_input = CheckboxInput(st_obj, "Set the Y-axis on graphs to a static value")
+    max_y_axis_input = NumberInput(st_obj, "Y-axis static value", value=500, format="%i", step=25)
 
     # Build in desired order
     st.sidebar.markdown("### Regional Parameters [ℹ]({docs_url}/what-is-chime/parameters)".format(docs_url=DOCS_URL))
     population = population_input()
-    market_share = market_share_input()
+    market_share = market_share_pct_input()
     known_infected = known_infected_input()
     current_hospitalized = current_hospitalized_input()
 
     st.sidebar.markdown("### Spread and Contact Parameters [ℹ]({docs_url}/what-is-chime/parameters)"
                         .format(docs_url=DOCS_URL))
+
     if st.sidebar.checkbox("I know the date of the first hospitalized case in the region."):
         date_first_hospitalized = date_first_hospitalized_input()
         doubling_time = None
     else:
         date_first_hospitalized = None
         doubling_time = doubling_time_input()
-    relative_contact_rate = relative_contact_rate_input()
+    relative_contact_rate = relative_contact_pct_input()
 
     st.sidebar.markdown("### Severity Parameters [ℹ]({docs_url}/what-is-chime/parameters)".format(docs_url=DOCS_URL))
-    hospitalized_rate = hospitalized_rate_input()
-    icu_rate = icu_rate_input()
-    ventilated_rate = ventilated_rate_input()
+    hospitalized_rate = hospitalized_pct_input()
+    icu_rate = icu_pct_input()
+    ventilated_rate = ventilated_pct_input()
     hospitalized_los = hospitalized_los_input()
     icu_los = icu_los_input()
     ventilated_los = ventilated_los_input()
@@ -308,19 +298,19 @@ def display_sidebar(st, d: Constants) -> Parameters:
     return Parameters(
         as_date=as_date,
         current_hospitalized=current_hospitalized,
-        market_share=market_share / 100.0,
+        market_share=market_share,
         known_infected=known_infected,
         doubling_time=doubling_time,
         date_first_hospitalized=date_first_hospitalized,
 
         max_y_axis=max_y_axis,
         n_days=n_days,
-        relative_contact_rate=relative_contact_rate / 100.0,
+        relative_contact_rate=relative_contact_rate,
         population=population,
 
-        hospitalized=RateLos(hospitalized_rate / 100.0, hospitalized_los),
-        icu=RateLos(icu_rate / 100.0, icu_los),
-        ventilated=RateLos(ventilated_rate / 100.0, ventilated_los),
+        hospitalized=RateLos(hospitalized_rate, hospitalized_los),
+        icu=RateLos(icu_rate, icu_los),
+        ventilated=RateLos(ventilated_rate, ventilated_los),
     )