Through beds df and chart. no lines yet.

src/app.py

@@ -17,6 +17,7 @@
 from penn_chime.charts import (
     build_admits_chart,
     build_census_chart,
+    build_beds_chart,
     build_descriptions,
     build_sim_sir_w_date_chart,
     build_table,
@@ -43,7 +44,7 @@
 st.markdown("Projected number of **daily** COVID-19 admissions. \n\n _NOTE: Now including estimates of prior admissions for comparison._")
 admits_chart = build_admits_chart(alt=alt, admits_floor_df=m.admits_floor_df, max_y_axis=p.max_y_axis)
 st.altair_chart(admits_chart, use_container_width=True)
-st.markdown(build_descriptions(chart=admits_chart, labels=p.labels, suffix=" Admissions"))
+st.markdown(build_descriptions(chart=admits_chart, labels=p.patient_chart_desc))
 display_download_link(
     st,
     filename=f"{p.current_date}_projected_admits.csv",
@@ -66,7 +67,7 @@
 st.markdown("Projected **census** of COVID-19 patients, accounting for arrivals and discharges \n\n _NOTE: Now including estimates of prior census for comparison._")
 census_chart = build_census_chart(alt=alt, census_floor_df=m.census_floor_df, max_y_axis=p.max_y_axis)
 st.altair_chart(census_chart, use_container_width=True)
-st.markdown(build_descriptions(chart=census_chart, labels=p.labels, suffix=" Census"))
+st.markdown(build_descriptions(chart=census_chart, labels=p.patient_chart_desc))
 display_download_link(
     st,
     filename=f"{p.current_date}_projected_census.csv",
@@ -84,6 +85,27 @@
     st.table(table_df)
 
 
+st.subheader("COVID-19 Capacity")
+st.markdown(
+    "Projected **number** of available COVID-19 beds, accounting for admits and discharges"
+)  
+st.dataframe(m.beds_df)##########
+beds_chart = build_beds_chart(alt=alt, beds_floor_df=m.beds_df, max_y_axis=p.max_y_axis)
+st.altair_chart(beds_chart, use_container_width=True)
+# st.markdown(bed_chart_descriptions(beds_chart, p.bed_chart_desc))
+# if st.checkbox("Show Projected Available COVID-19 Beds in tabular form"):
+#     if st.checkbox("Show Daily Available Bed Counts"):
+#         draw_beds_table(st, p, m.beds_df, p.labels, as_date=p.as_date, daily_count=True)
+#     else:
+#         draw_beds_table(st, p, m.beds_df, p.labels, as_date=p.as_date, daily_count=False)
+#     build_download_link(st,
+#         filename="projected_beds.csv",
+#         df=m.beds_df,
+#         parameters=p
+#     )
+
+
+
 st.subheader("Susceptible, Infected, and Recovered")
 st.markdown("The number of susceptible, infected, and recovered individuals in the hospital catchment region at any given moment")
 sim_sir_w_date_chart = build_sim_sir_w_date_chart(alt=alt, sim_sir_w_date_floor_df=m.sim_sir_w_date_floor_df)

src/penn_chime/charts.py

@@ -24,13 +24,13 @@ def build_admits_chart(
 
     x = dict(shorthand="date:T", title="Date", axis=alt.Axis(format=(DATE_FORMAT)))
     y = dict(shorthand="value:Q", title="Daily admissions", scale=y_scale)
-    color = "key:N"
+    color = alt.Color("key:N", sort = ["total", "icu", "ventilators"])
     tooltip=["date:T", alt.Tooltip("value:Q", format=".0f", title="Admit"), "key:N"]
 
     # TODO fix the fold to allow any number of dispositions
     points = (
         alt.Chart()
-        .transform_fold(fold=["hospitalized", "icu", "ventilated"])
+        .transform_fold(fold=["total", "icu", "ventilators"])
         .encode(x=alt.X(**x), y=alt.Y(**y), color=color, tooltip=tooltip)
         .mark_line(point=True)
     )
@@ -57,13 +57,13 @@ def build_census_chart(
 
     x = dict(shorthand="date:T", title="Date", axis=alt.Axis(format=(DATE_FORMAT)))
     y = dict(shorthand="value:Q", title="Census", scale=y_scale)
-    color = "key:N"
+    color = alt.Color("key:N", sort = ["total", "icu", "ventilators"])
     tooltip = ["date:T", alt.Tooltip("value:Q", format=".0f", title="Census"), "key:N"]
 
     # TODO fix the fold to allow any number of dispositions
     points = (
         alt.Chart()
-        .transform_fold(fold=["hospitalized", "icu", "ventilated"])
+        .transform_fold(fold=["total", "icu", "ventilators"])
         .encode(x=alt.X(**x), y=alt.Y(**y), color=color, tooltip=tooltip)
         .mark_line(point=True)
     )
@@ -107,7 +107,58 @@ def build_sim_sir_w_date_chart(
     )
     return alt.layer(points, bar, data=sim_sir_w_date_floor_df)
 
+def build_beds_chart(
+    alt, 
+    beds_floor_df: pd.DataFrame, 
+    max_y_axis: Optional[int] = None,
+) -> Chart:
+    """docstring"""
+    y_scale = alt.Scale()
+    if max_y_axis is not None:
+        y_scale.domain = (0, max_y_axis)
 
+    x = dict(shorthand="date:T", title="Date", axis=alt.Axis(format=(DATE_FORMAT)))
+    y = dict(shorthand="value:Q", title="COVID-19 Capacity", scale=y_scale)
+    color = alt.Color("key:N", sort = ["total", "icu", "ventilators"])
+    tooltip = ["key:N", "value:Q"]
+
+    # census["line"] = 0
+    # TODO fix the fold to allow any number of dispositions
+    beds = (
+        alt.Chart()
+        .transform_fold(fold=["total", "icu", "ventilators"])
+        .mark_line(point=True)
+        .encode(x=alt.X(**x), y=alt.Y(**y), color=color, tooltip=tooltip)
+        .mark_line()
+    )
+    # Horizontal line at 0
+    # hline = alt.Chart(census.head(plot_projection_days)
+    # ).transform_fold(
+    #     fold=["line"]
+    # ).mark_line(
+    #     point=False,
+    #     color="black",
+    #     strokeDash=[5,3],
+    #     opacity=.5,
+    # ).encode(
+    #     x=alt.X(**x_kwargs),
+    #     y=alt.Y("value:Q"),
+    # )
+    # # Vertical line on today
+    # v_line_location = "0"
+    # if parameters.as_date:
+    #     today = datetime.date.today()
+    #     v_line_location = f"datetime({today.year}, {today.month - 1}, {today.day})" # Because Altair uses vega which has 0-based month indexes
+    # vline = alt.Chart(census.head(plot_projection_days)
+    # ).mark_rule(
+    #     strokeDash=[5,3],
+    #     opacity=.05, # This doesn't seem to do anything
+    # ).encode(
+    #     x="v_line_location:T" if parameters.as_date else "v_line_location:Q"
+    # ).transform_calculate(v_line_location=v_line_location)
+
+    # return beds + vline + hline, beds
+    return alt.layer(beds, data=beds_floor_df)
 def build_descriptions(
     *,
     chart: Chart,
@@ -124,7 +175,7 @@ def build_descriptions(
     """
     messages = []
 
-    cols = ["hospitalized", "icu", "ventilated"]
+    cols = ["total", "icu", "ventilators"]
     asterisk = False
     day = "date" if "date" in chart.data.columns else "day"
 
@@ -136,9 +187,8 @@ def build_descriptions(
         on = datetime.strftime(chart.data[day][chart.data[col].idxmax()], "%b %d")
 
         messages.append(
-            "{}{} peaks at {:,} on {}{}".format(
+            "{} {:,} on {}{}".format(
                 labels[col],
-                suffix,
                 ceil(chart.data[col].max()),
                 on,
                 "*" if asterisk else "",

src/penn_chime/models.py

@@ -160,6 +160,7 @@ def __init__(self, p: Parameters):
         self.sim_sir_w_date_floor_df = build_floor_df(self.sim_sir_w_date_df, self.keys)
         self.admits_floor_df = build_floor_df(self.admits_df, p.dispositions.keys())
         self.census_floor_df = build_floor_df(self.census_df, p.dispositions.keys())
+        self.beds_floor_df = build_floor_df(self.beds_df, p.dispositions.keys())
 
         self.daily_growth_rate = get_growth_rate(p.doubling_time)
         self.daily_growth_rate_t = get_growth_rate(self.doubling_time_t)
@@ -179,6 +180,7 @@ def run_projection(self, p):
         self.dispositions_df = build_dispositions_df(self.raw_df, self.rates, p.market_share, p.current_date)
         self.admits_df = build_admits_df(self.dispositions_df)
         self.census_df = build_census_df(self.admits_df, self.days)
+        self.beds_df = build_beds_df(self.census_df, p)
         self.current_infected = self.raw_df.infected.loc[self.i_day]
 
     def get_loss(self) -> float:
@@ -342,22 +344,19 @@ def build_census_df(
     })
 
 def build_beds_df(
-    census_df: pd.DataFrame, lengths_of_stay, p
+    census_df: pd.DataFrames,
+    p,
 ) -> pd.DataFrame:
     """ALOS for each category of COVID-19 case (total guesses)"""
-    # n_days = np.shape(census_df)[0]
-    census_dict = {}
-
-    beds_df = pd.DataFrame(census_dict)
-    beds_df["day"] = census_df.index
-
-    covid_non_icu_beds = p.total_covid_beds - p.covid_icu_beds
+    beds_df = pd.DataFrame()
+    beds_df["day"] = census_df["day"]
+    beds_df["date"] = census_df["date"]
 
     # If hospitalized < 0 and there's space in icu, start borrowing if possible
     # If ICU < 0, raise alarms. No changes.
-    beds_df["hospitalized"] = p.covid_non_icu_beds - census_df["hospitalized"]
-    beds_df["icu"] = p.covid_icu_beds - p.census_df["icu"]
-    beds_df["ventilators"] = p.covid_vents - p.census_df["ventilators"]
+    beds_df["hospitalized"] = p.total_covid_beds - p.icu_covid_beds - census_df["hospitalized"]
+    beds_df["icu"] = p.icu_covid_beds - census_df["icu"]
+    beds_df["ventilators"] = p.covid_ventilators - census_df["ventilators"]
     beds_df["total"] = p.total_covid_beds - census_df["hospitalized"] - census_df["icu"]
     # beds_df = beds_df.head(n_days)
 

src/penn_chime/parameters.py

@@ -123,7 +123,22 @@ def __init__(
         }
 
         self.dispositions = {
+            "total": hospitalized,
             "hospitalized": hospitalized,
             "icu": icu,
             "ventilators": ventilators,
         }
+
+        self.patient_chart_desc = {
+            "hospitalized": "Hospitalized COVID-19 Admissions peak at",
+            "icu": "ICU COVID-19 Admissions peak at",
+            "ventilators": "COVID-19 Ventilators peak at",
+            "total": "Total COVID-19 Admissions peaks at"
+        }
+
+        self.eqp_chart_desc = {
+            "hospitalized": "Hospitalized COVID-19 Beds",
+            "icu": "Total ICU COVID-19 Beds",
+            "ventilators": "COVID-19 Ventilators",
+            "total": "Total COVID-19 Beds"
+        }

src/penn_chime/presentation.py

@@ -80,7 +80,7 @@ def display_header(st, m, p):
 and daily growth rate of **{daily_growth_t:.2f}%**.
 """.format(
             total_infections=m.infected,
-            current_hosp=p.current_hospitalized,
+            current_hosp=p.covid_census_value,
             hosp_rate=p.hospitalized.rate,
             S=p.population,
             market_share=p.market_share,
@@ -330,7 +330,6 @@ def display_sidebar(st, d: Parameters) -> Parameters:
     )
     population = population_input()
     market_share = market_share_pct_input()
-    # known_infected = known_infected_input()
     covid_census_value = covid_census_value_input()
     covid_census_date = covid_census_date_input()