def run_infectious_model(Debug):
epidemiology = extract_keys(PARAMS, params)
clinical = extract_keys(CLINICAL, params)
model = clinical_model = results = None
try:
model = ConstructModel(disease=disease, **epidemiology).new_model()
clinical_model = model.clinical.overflow_model(
icu_occupancy=0, hospital_occupancy=0, **clinical)
clinical_model.extra_info = params
self.show(clinical_model)
finally:
if Debug:
Debug.information_message(results, params, epidemiology,
clinical, model, clinical_model)
def from_children(
cls,
region: Union[Region, str],
model_cls: Type[Model],
options=MappingProxyType({}),
**kwargs,
) -> "ModelGroup":
"""
Create a group from children of the given Region.
"""
region: Region = mundi.region(region)
children = region.children(
**extract_keys(("deep", "type", "subtype", "which"), kwargs))
name = kwargs.pop("name", "{region.name}")
group = []
if options:
options = {mundi.region(k): v for k, v in options.items()}
for child in children:
opts = options.get(child, {})
if isinstance(name, str):
opts["name"] = name.format(region=child, **kwargs, **opts)
group.append(model_cls(region=child, **kwargs, **opts))
return ModelGroup(group)
def main(embed=False, disease=None):
"""
Run application.
"""
if not embed:
st.css(keep_menu=True)
st.sidebar.logo()
title = st.empty().title
title(_("Covid risk factors"))
else:
title = lambda *args: None
opts = sidebar(title,
where=st if embed else st.sidebar,
embed=embed,
disease=disease)
show_opts = extract_keys(SHOW_OPTS, opts)
clinical_opts = extract_keys(CLINICAL_OPTS, opts)
run_opts = extract_keys(RUN_OPTS, opts)
# Start model with known R0
region = opts["region"]
plot_opts = show_opts["plot_opts"]
st.header(_("Cases and deaths"))
region.ui.epidemic_summary()
region.ui.cases_and_deaths(title=None,
download=f"cases-{region.id}.csv",
**plot_opts)
model = start_model(**opts)
group = start_group(model, **run_opts)
show_outputs(model,
group,
clinical_opts=clinical_opts,
**opts,
**show_opts)
def process_data(self):
show_opts = extract_keys(SHOW_OPTS, self.user_inputs)
clinical_opts = extract_keys(CLINICAL_OPTS, self.user_inputs)
run_opts = extract_keys(RUN_OPTS, self.user_inputs)
# Start model with known R0
region = self.user_inputs["region"]
plot_opts = show_opts["plot_opts"]
self.where = st
self.where.header(_("Cases and deaths"))
region.ui.epidemic_summary()
region.ui.cases_and_deaths(title=None,
download=f"cases-{region.id}.csv",
**plot_opts)
model = self.start_model(region=self.user_inputs['region'])
group = self.start_group(model, **run_opts)
self.cmodels = group.clinical.overflow_model(**clinical_opts)
self.show_outputs(model,
group,
clinical_opts=clinical_opts,
**self.user_inputs,
**show_opts)
def main(embed=False, where=st, **kwargs):
"""
Main application function.
"""
st = where
if not embed:
st.css(keep_menu=True)
st.sidebar.logo()
st.title(_("Epidemic situation dashboard (Brazil)"))
options = sidebar(where=st.sidebar)
kwargs = extract_keys(("cmap", "static_table"), options)
kwargs["where"] = where
data = get_data()
data = data.loc[options.pop("regions")]
section_opt = options["section"]
if section_opt == "download":
download_data(data, **kwargs)
else:
section = SECTIONS[section_opt]
section.show(data, **kwargs)
def main(region="BR", disease=covid19):
st.css()
params = sidebar(
region=region,
disease=disease,
secret_date=datetime.date(1904, 11, 10),
secret_function=lambda: easter_egg(disease),
)
if params is None: # Secret function was activated
return
debug = False
if DEBUG and st.checkbox(_("Enable debug")):
st.info(_("Running in debug mode!"))
st.html(
"""
<ul>
<li><a href="#debug">{}</a></li>
</ul>""".format(
_("Debug section!")
)
)
debug = True
epidemiology = extract_keys(PARAMS, params)
clinical = extract_keys(CLINICAL, params)
# Run infections model
m = cm = results = None
try:
m = model(disease=disease, **epidemiology)
cm = m.clinical.overflow_model(icu_occupancy=0, hospital_occupancy=0, **clinical)
cm.extra_info = params
output(cm)
finally:
if debug:
if results:
st.html('<div style="height: 15rem"></div>')
st.html('<h2 id="debug">{}</h2>'.format(_("Debug information")))
st.subheader(_("Generic parameters"))
st.write(params)
st.subheader(_("Epidemiological parameters"))
st.write(epidemiology)
st.subheader(_("Clinical parameters"))
st.write(clinical)
st.subheader(_("Output"))
st.write(results)
if m:
st.line_chart(m.data)
if cm:
st.line_chart(cm[["infectious", "severe", "critical"]])
st.subheader(_("Distribution of deaths"))
df = cm[DEATH_DISTRIBUTION_COLUMNS]
df.columns = [DEATH_DISTRIBUTION_COL_NAMES[k] for k in df.columns]
st.area_chart(df)
