def test_coarse_contact_matrix(self):
m1 = contact_matrix('italy')
m2 = contact_matrix('italy', coarse=True)
assert abs(m1.values[:-1, :-1].sum() - m2.values[:-2, :-2].sum()) < 1e-3
assert list(m1.index) != list(m2.index)
assert (m2.index == age_distribution('Italy', 2020, coarse=True).index).all()
def test_load_covid_mortality_syncs_with_age_distribution(self):
dm = covid_mortality()
df = age_distribution("Brazil", 2020, coarse=True)
assert (dm.index == df.index).all()
def test_load_bad_age_distribution(self):
with pytest.raises(ValueError):
age_distribution("Brazil", 2050)
with pytest.raises(ValueError):
age_distribution("Bad spelling", 2050)
def test_load_age_distribution(self):
df = age_distribution("Brazil", 2020)
assert 209_000 <= df.sum() <= 220_000
import streamlit as st
import covid
from covid import gettext as _
from covid.data import countries
from covid.models import SEICHAR
from covid.utils import fmt, pc
from covid.data import age_distribution
TODAY = datetime.datetime.now()
TODAY = datetime.date(TODAY.year, TODAY.month, TODAY.day)
# Adjust demography to 2020. We only have citywise and statewise datasets
# from the Brazilian Census of 2010.
DEMOGRAPHY_CORRECTION = age_distribution("Brazil", 2020, coarse=True) / age_distribution(
"Brazil", 2010, coarse=True
)
class Input:
def __init__(self, country, display_country=None, target=None):
self.country = country
self.display_country = display_country or country.title()
self.target = target or st.sidebar
def run(self):
"""
Return a dictionary of keyword arguments from user input.
This dictionary can be passed to the model constructor with minimal