def region(name):
return covid.region(name)
template.format(href="http://fce.unb.br/", name="UnB/FCE"),
template.format(href="http://www.butantan.gov.br/", name="Butantã"),
template.format(href="http://www.matogrossodosul.fiocruz.br/", name="Fiocruz"),
template.format(href="https://famed.ufms.br/", name="FAMED"),
]
links = _("Support: {institutions}").format(institutions=", ".join(institutions))
styles = "text-align: center; margin: 5rem 0 -5rem 0;"
html(f'<div style="{styles}">{links}</div>')
def fatality_rate(fs, dt=1):
fs = fs.copy()
fs.iloc[:-1] -= fs.values[1:]
fs /= -dt
fs.iloc[-1] = fs.iloc[-2]
return fs.apply(lambda x: round(x, 1))
def write_css():
html(asset("custom.html"))
if __name__ == "__main__":
region = covid.region("Brazil")
model = SEICHAR(region=region, prob_symptomatic=0.5, seed=1000)
model.run(180)
write_css()
app = Output(model)
app.run()
def test_city(self):
sp = region("Brazil/São Paulo")
assert sp.population_size == 11_253_503
def test_country(self):
br = region("Brazil")
assert br.population_size == 212_559_000
def test_metro_area(self):
sp = region("Brazil/Metropolitana de São Paulo")
assert sp.population_size == 21_154_988
def get_region(ref):
region = covid.region(ref)
if ref.lower().startswith("brazil/"):
region.demography = DEMOGRAPHY_CORRECTION
return region