def test_n_single_ages(n_people=1e4,
location='seattle_metro',
state_location='Washington',
country_location='usa'):
sc.heading('Running single ages')
sp.validate()
datadir = sp.datadir
age_bracket_distr = sp.read_age_bracket_distr(datadir, location,
state_location,
country_location)
gender_fraction_by_age = sp.read_gender_fraction_by_age_bracket(
datadir, location, state_location, country_location)
age_brackets_filepath = sp.get_census_age_brackets_path(
datadir, state_location, country_location)
age_brackets = sp.get_age_brackets_from_df(age_brackets_filepath)
# ## Test selecting an age and sex for an individual ###
a, s = sp.get_age_sex(gender_fraction_by_age, age_bracket_distr,
age_brackets)
print(a, s)
n_people = int(n_people)
ages, sexes = [], []
for p in range(n_people):
a, s = sp.get_age_sex(gender_fraction_by_age, age_bracket_distr,
age_brackets)
ages.append(a)
sexes.append(s)
return
def test_all(location='seattle_metro', state_location='Washington', country_location='usa', sheet_name='United States of America'):
''' Run all tests '''
sc.heading('Running all tests')
sp.validate() # Validate that data files can be found
# dropbox_path = sp.datadir
dropbox_path = sp.settings.datadir
age_bracket_distr = spdd.read_age_bracket_distr(dropbox_path, location, state_location, country_location)
gender_fraction_by_age = sp.read_gender_fraction_by_age_bracket(dropbox_path, location, state_location, country_location)
age_brackets_file, age_brackets_filepath = sp.get_census_age_brackets_path(dropbox_path, state_location, country_location)
print(age_brackets_filepath)
age_brackets = sp.get_age_brackets_from_df(age_brackets_filepath)
age_by_brackets_dic = sp.get_age_by_brackets_dic(age_brackets)
# ## Test selecting an age and sex for an individual ###
a, s = sp.get_age_sex(gender_fraction_by_age, age_bracket_distr, age_brackets)
print(a, s)
# ## Test age mixing matrix ###
# num_agebrackets = 18
# flu-like weights. calibrated to empirical diary survey data.
weights_dic = {'H': 4.11, 'S': 11.41, 'W': 8.07, 'C': 2.79}
age_mixing_matrix_dic = sp.get_contact_matrix_dic(dropbox_path, sheet_name)
# ## Test sampling contacts based on age ###
age, sex = sp.get_age_sex(gender_fraction_by_age, age_bracket_distr, age_brackets) # sample an age (and sex) from the seattle metro distribution
n_contacts = 30
contact_ages = sp.sample_n_contact_ages(n_contacts, age, age_brackets, age_by_brackets_dic, age_mixing_matrix_dic, weights_dic)
print(contact_ages)
# shut down schools
no_schools_weights = sc.dcp(weights_dic)
no_schools_weights['S'] = 0.1 # research shows that even with school closure, kids still have some contact with their friends from school.
f_reduced_contacts_students = 0.5
f_reduced_contacts_nonstudents = 0.2
if age < 20:
n_reduced_contacts = int(n_contacts * (1 - f_reduced_contacts_students))
else:
n_reduced_contacts = int(n_contacts * (1 - f_reduced_contacts_nonstudents))
contact_ages = sp.sample_n_contact_ages(n_reduced_contacts, age, age_brackets, age_by_brackets_dic, age_mixing_matrix_dic, no_schools_weights)
print(contact_ages)
return
import synthpops as sp
if __name__ == '__main__':
sp.validate()
datadir = sp.datadir
state_location = 'Washington'
location = 'seattle_metro'
country_location = 'usa'
sheet_name = 'United States of America'
n = 2000
verbose = True
verbose = False
plot = True
# plot = False
school_enrollment_counts_available = False
use_default = False
sp.generate_synthetic_population(
n,
datadir,
location=location,
state_location=state_location,
country_location=country_location,
sheet_name=sheet_name,
school_enrollment_counts_available=school_enrollment_counts_available,
verbose=verbose,
plot=plot,
use_default=use_default)
