def test_no_asterisk(admits_floor_df, param):
param.n_days = 600
chart = build_admits_chart(alt=alt, admits_floor_df=admits_floor_df)
description = build_descriptions(chart=chart,
labels=param.labels,
prefix="admits_")
assert "*" not in description
def test_census(census_floor_df, param):
chart = build_census_chart(alt=alt, census_floor_df=census_floor_df)
description = build_descriptions(chart=chart,
labels=param.labels,
prefix="census_")
assert str(ceil(chart.data["census_ventilated"].max())) in description
assert str(chart.data["census_icu"].idxmax()) not in description
assert (datetime.strftime(
chart.data.iloc[chart.data["census_icu"].idxmax()].date, "%b %d")
in description)
def test_build_descriptions(admits_floor_df, param):
chart = build_admits_chart(alt=alt, admits_floor_df=admits_floor_df)
description = build_descriptions(chart=chart,
labels=param.labels,
prefix="admits_")
hosp, icu, vent = description.split(
"\n\n") # break out the description into lines
max_hosp = chart.data["admits_hospitalized"].max()
assert str(ceil(max_hosp)) in hosp
if st.checkbox("Show more info about this tool"):
notes = "The total size of the susceptible population will be the entire catchment area for Penn Medicine entities (HUP, PAH, PMC, CCH)"
display_more_info(st=st,
model=m,
parameters=p,
defaults=DEFAULTS,
notes=notes)
st.subheader("New Admissions")
st.markdown(
"Projected number of **daily** COVID-19 admissions at Penn hospitals")
admits_chart = build_admits_chart(alt=alt,
admits_df=m.admits_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))
display_download_link(
st,
filename=f"{p.current_date}_projected_admits.csv",
df=m.admits_df,
)
if st.checkbox("Show Projected Admissions in tabular form"):
admits_modulo = 1
if not st.checkbox("Show Daily Counts"):
admits_modulo = 7
table_df = build_table(df=m.admits_df,
labels=p.labels,
modulo=admits_modulo)
st.table(table_df)
p = display_sidebar(st, d)
m = SimSirModel(p)
display_header(st, m, p)
st.subheader("New Admissions")
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,
prefix="admits_",
suffix=" Admissions"))
display_download_link(
st,
filename=f"{p.current_date}_projected_admits.csv",
df=m.admits_df,
)
if st.checkbox("Show Projected Admissions in tabular form"):
admits_modulo = 1
if not st.checkbox("Show Daily Counts"):
admits_modulo = 7
table_df = build_table(df=m.admits_floor_df,
labels=p.labels,
modulo=admits_modulo)
st.table(table_df)
def display_body_charts(m, p: "Parameters", d: "Parameters",
actuals: "pd.DataFrame", mode: "Mode"):
st.subheader("New Hospital Admissions")
admits_chart = build_admits_chart(alt=alt,
admits_floor_df=m.admits_floor_df,
p=p,
actuals=actuals)
st.altair_chart(admits_chart, use_container_width=True)
zero_admits_warning(p)
st.markdown(
build_descriptions(
chart=admits_chart,
labels=p.admits_patient_chart_desc,
))
display_download_link(
filename=f"{p.current_date}_projected_admits.csv",
df=m.admits_df,
)
if st.checkbox("Show Projected Admissions in tabular form"):
admits_modulo = 1
if not st.checkbox("Show Daily Counts"):
admits_modulo = 7
table_df = build_table(df=m.admits_floor_df,
labels=p.labels,
modulo=admits_modulo)
st.table(table_df)
st.subheader("Hospital Census")
census_chart = build_census_chart(alt=alt,
census_floor_df=m.census_floor_df,
p=p,
actuals=actuals)
st.altair_chart(census_chart, use_container_width=True)
# Display census mismatch message if appropriate
census_mismatch_message(parameters=p, actuals=actuals, st=st)
st.markdown(
build_descriptions(
chart=census_chart,
labels=p.census_patient_chart_desc,
))
display_download_link(
filename=f"{p.current_date}_projected_census.csv",
df=m.census_df,
)
if st.checkbox("Show Projected Census in tabular form"):
census_modulo = 1
if not st.checkbox("Show Daily Census Counts"):
census_modulo = 7
table_df = build_table(df=m.census_floor_df,
labels=p.labels,
modulo=census_modulo)
st.table(table_df)
st.subheader("COVID-19 Capacity")
beds_chart = build_beds_chart(alt=alt,
beds_floor_df=m.beds_df,
parameters=p)
st.altair_chart(beds_chart, use_container_width=True)
st.markdown(
build_bed_descriptions(chart=beds_chart, labels=p.beds_chart_desc))
display_download_link(
filename=f"{p.current_date}_projected_capacity.csv",
df=m.beds_df,
)
if st.checkbox("Show Projected Capacity in tabular form"):
beds_modulo = 1
if not st.checkbox("Show Daily Capacity Counts"):
beds_modulo = 7
table_df = build_table(df=m.beds_floor_df,
labels=p.labels,
modulo=beds_modulo)
st.table(table_df)
st.subheader("Susceptible, Infected, and Recovered")
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,
actuals=actuals,
p=p)
st.altair_chart(sim_sir_w_date_chart, use_container_width=True)
display_download_link(
filename=f"{p.current_date}_sim_sir_w_date.csv",
df=m.sim_sir_w_date_df,
)
if st.checkbox("Show SIR Simulation in tabular form"):
table_df = build_table(df=m.sim_sir_w_date_floor_df, labels=p.labels)
st.table(table_df)
### PPE Section
st.subheader("Personal Protection Equipment")
show_ppe_section = st.checkbox("Show PPE Charts", value=p.show_ppe_section)
p.show_ppe_section = show_ppe_section
if show_ppe_section:
st.markdown("Quantity of PPE required per day")
for pc in list(p.ppe_labels.keys())[3:]:
ppe_chart = build_ppe_chart(alt=alt,
ppe_floor_df=m.ppe_floor_df,
p=p,
plot_columns=pc)
st.altair_chart(ppe_chart, use_container_width=True)
st.markdown(
build_ppe_descriptions(chart=ppe_chart,
label=p.ppe_labels[pc]["label"]))
st.markdown(" \n \n")
display_download_link(
filename=f"{p.current_date}_projected_ppe_required.csv",
df=m.ppe_df,
)
if st.checkbox("Show Projected PPE Required in tabular form"):
ppe_modulo = 1
if not st.checkbox("Show Daily PPE Required"):
ppe_modulo = 7
table_df = build_table(df=m.ppe_floor_df,
labels=p.labels,
modulo=ppe_modulo)
st.dataframe(table_df)
### Staffing Section
st.subheader("Staffing")
show_staffing_section = st.checkbox("Show Staffing Charts",
value=p.show_staffing_section)
p.show_staffing_section = show_staffing_section
if show_staffing_section:
st.markdown("Number of staff required per day")
for pc in list(p.staffing_labels.keys())[3:]:
staffing_chart = build_staffing_chart(
alt=alt,
staffing_floor_df=m.staffing_floor_df,
p=p,
plot_columns=pc)
st.altair_chart(staffing_chart, use_container_width=True)
st.markdown(
build_staffing_descriptions(
chart=staffing_chart,
label=p.staffing_labels[pc]["label"],
shift_duration=p.shift_duration))
st.markdown(" \n \n")
display_download_link(
filename=f"{p.current_date}_projected_staffing_required.csv",
df=m.staffing_df,
)
if st.checkbox("Show Projected Staffing Required in tabular form"):
staffing_modulo = 1
if not st.checkbox("Show Daily Staffing Required"):
staffing_modulo = 7
table_df = build_table(df=m.staffing_floor_df,
labels=p.labels,
modulo=staffing_modulo)
st.dataframe(table_df)
### Export Full Data and Parameters
st.header("Export Full Data and Parameters")
df = build_data_and_params(projection_admits=m.admits_df,
census_df=m.census_df,
beds_df=m.beds_df,
ppe_df=m.ppe_df,
staffing_df=m.staffing_df,
model=m,
parameters=p)
if st.checkbox("Show full data and parameters to be exported"):
st.dataframe(df)
filename = "Data" + "_" + p.author + "_" + p.scenario + "_" + (
datetime.datetime.utcnow() -
datetime.timedelta(hours=6)).isoformat() + ".csv"
csv = dataframe_to_base64(df)
st.markdown("""
<a download="{filename}" href="data:text/plain;base64,{csv}">Download full table as CSV</a>
""".format(csv=csv, filename=filename),
unsafe_allow_html=True)
if actuals is not None:
if st.checkbox("Display Uploaded Actuals"):
st.dataframe(actuals)