def test_generate_all_households(location='seattle_metro',
state_location='Washington',
country_location='usa'):
N = 1000
household_size_distr = sp.get_household_size_distr(datadir, location,
state_location,
country_location)
hh_sizes = sp.generate_household_sizes_from_fixed_pop_size(
N, household_size_distr)
hha_brackets = sp.get_head_age_brackets(datadir,
country_location=country_location)
hha_by_size_counts = sp.get_head_age_by_size_distr(
datadir, country_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)
age_by_brackets_dic = sp.get_age_by_brackets_dic(age_brackets)
contact_matrix_dic = sp.get_contact_matrix_dic(
datadir, sheet_name='United States of America')
single_year_age_distr = {}
for n in range(101):
single_year_age_distr[n] = float(1.0 / 101.0)
homes_dic, homes = sp.generate_all_households(
N, hh_sizes, hha_by_size_counts, hha_brackets, age_brackets,
age_by_brackets_dic, contact_matrix_dic, single_year_age_distr)
assert homes_dic, homes is not None
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_generate_larger_households(location='seattle_metro',
state_location='Washington',
country_location='usa'):
Nhomes_to_sample_smooth = 1000
household_size_distr = sp.get_household_size_distr(datadir, location,
state_location,
country_location)
hh_sizes = sp.generate_household_sizes(Nhomes_to_sample_smooth,
household_size_distr)
hha_brackets = sp.get_head_age_brackets(datadir,
country_location=country_location)
hha_by_size_counts = sp.get_head_age_by_size_distr(
datadir, country_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)
age_by_brackets_dic = sp.get_age_by_brackets_dic(age_brackets)
contact_matrix_dic = sp.get_contact_matrix_dic(
datadir, sheet_name='United States of America')
single_year_age_distr = {}
for n in range(101):
single_year_age_distr[n] = float(1.0 / 101.0)
# generate households of size 3
size = 3
# first variable is the household size to be created, so here this means we want to create all households of size 3 and the hh_sizes variable tells us how many of size 3 will be created at index 3-1 (since hh_sizes is an array rather than a dictionary)
larger_households = sp.generate_larger_households(
size, hh_sizes, hha_by_size_counts, hha_brackets, age_brackets,
age_by_brackets_dic, contact_matrix_dic, single_year_age_distr)
assert larger_households is not None
print(larger_households)
def test_send_students_to_school(n=10000,
location='seattle_metro',
state_location='Washington',
country_location='usa',
folder_name='contact_networks'):
homes = sprw.read_setting_groups(datadir,
location,
state_location,
country_location,
folder_name,
'households',
n,
with_ages=True)
homes_by_uids, age_by_uid_dic = sp.assign_uids_by_homes(homes)
uids_in_school, uids_in_school_by_age, ages_in_school_count = sp.get_uids_in_school(
datadir,
n,
location,
state_location,
country_location,
age_by_uid_dic,
homes_by_uids,
use_default=False)
school_size_distr_by_bracket = sp.get_school_size_distr_by_brackets(
datadir, location, state_location, country_location)
school_size_brackets = sp.get_school_size_brackets(datadir, location,
state_location,
country_location)
school_sizes = sp.generate_school_sizes(school_size_distr_by_bracket,
school_size_brackets,
uids_in_school)
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)
age_by_brackets_dic = sp.get_age_by_brackets_dic(age_brackets)
contact_matrix_dic = sp.get_contact_matrix_dic(
datadir, sheet_name='United States of America')
syn_schools, syn_school_uids, syn_school_types = sp.send_students_to_school(
school_sizes,
uids_in_school,
uids_in_school_by_age,
ages_in_school_count,
age_brackets,
age_by_brackets_dic,
contact_matrix_dic,
verbose=False)
assert syn_schools, syn_school_uids is not None
return syn_schools, syn_school_uids
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
def test_multiple_ages(n_people=1e4, location='seattle_metro', state_location='Washington', country_location='usa'):
sc.heading('Running multiple ages')
datadir = sp.settings.datadir
age_bracket_distr = spdd.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_file, 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)
ages, sexes = sp.get_age_sex_n(gender_fraction_by_age, age_bracket_distr, age_brackets, n_people)
print(len(ages), len(sexes))
return
def test_generate_workplace_sizes(location='seattle_metro', state_location='Washington',
country_location='usa', folder_name='contact_networks'):
Npeople = 10000
uids_in_school, uids_in_school_by_age, ages_in_school_count = sp.get_uids_in_school(datadir, Npeople, location,
state_location,
country_location,
folder_name=folder_name,
use_default=True)
school_size_distr_by_bracket = sp.get_school_size_distr_by_brackets(datadir, location, state_location,
country_location)
school_size_brackets = sp.get_school_size_brackets(datadir, location, state_location, country_location)
school_sizes = sp.generate_school_sizes(school_size_distr_by_bracket, school_size_brackets, uids_in_school)
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)
age_by_brackets_dic = sp.get_age_by_brackets_dic(age_brackets)
contact_matrix_dic = sp.get_contact_matrix_dic(datadir, sheet_name='United States of America')
# Need to instead get syn_schools now
syn_schools, syn_school_uids = sp.send_students_to_school(school_sizes, uids_in_school, uids_in_school_by_age,
ages_in_school_count, age_brackets, age_by_brackets_dic,
contact_matrix_dic)
employment_rates = sp.get_employment_rates(datadir, location=location, state_location=state_location,
country_location=country_location, use_default=True)
age_by_uid_dic = sp.read_in_age_by_uid(datadir, location, state_location, country_location, folder_name, Npeople)
potential_worker_uids, potential_worker_uids_by_age, potential_worker_ages_left_count = sp.get_uids_potential_workers(
syn_school_uids, employment_rates, age_by_uid_dic)
workers_by_age_to_assign_count = sp.get_workers_by_age_to_assign(employment_rates, potential_worker_ages_left_count,
age_by_uid_dic)
workplace_size_brackets = sp.get_workplace_size_brackets(datadir, location, state_location, country_location,
use_default=True)
workplace_size_distr_by_brackets = sp.get_workplace_size_distr_by_brackets(datadir,
state_location=state_location,
country_location=country_location,
use_default=True)
workplace_sizes = sp.generate_workplace_sizes(workplace_size_distr_by_brackets, workplace_size_brackets,
workers_by_age_to_assign_count)
return workers_by_age_to_assign_count, workplace_size_brackets, workplace_size_distr_by_brackets, workplace_sizes
def test_send_students_to_school(n=10000, location='seattle_metro', state_location='Washington',
country_location='usa', folder_name='contact_networks'):
homes = sp.read_setting_groups(datadir, location, state_location, country_location, 'households', folder_name, n, with_ages=True)
homes_by_uids, age_by_uid_dic = sp.assign_uids_by_homes(homes)
uids_in_school, uids_in_school_by_age, ages_in_school_count = sp.get_uids_in_school(datadir, n, location,
state_location,
country_location,
age_by_uid_dic,
homes_by_uids,
use_default=False)
# assert uids_in_school is not None
# def test_send_students_to_school(n=1000, location='seattle_metro', state_location='Washington',
# country_location='usa'):
# homes = sp.get_head_age_by_size_distr(datadir, state_location, country_location, file_path=None,
# household_size_1_included=False, use_default=True)
# homes_by_uids, age_by_uid_dic = sp.assign_uids_by_homes(homes, id_len=16)
# uids_in_school, uids_in_school_by_age, ages_in_school_count = sp.get_uids_in_school(datadir, n, location,
# state_location,
# country_location,
# age_by_uid_dic,
# homes_by_uids,
# use_default=False)
# >>>>>>> origin/mf/update-saved-pop-fixes
school_size_distr_by_bracket = sp.get_school_size_distr_by_brackets(datadir, location, state_location,
country_location)
school_size_brackets = sp.get_school_size_brackets(datadir, location, state_location, country_location)
school_sizes = sp.generate_school_sizes(school_size_distr_by_bracket, school_size_brackets, uids_in_school)
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)
age_by_brackets_dic = sp.get_age_by_brackets_dic(age_brackets)
contact_matrix_dic = sp.get_contact_matrix_dic(datadir, sheet_name='United States of America')
syn_schools, syn_school_uids = sp.send_students_to_school(school_sizes, uids_in_school, uids_in_school_by_age,
ages_in_school_count, age_brackets, age_by_brackets_dic,
contact_matrix_dic, verbose=False)
assert syn_schools, syn_school_uids is not None
return syn_schools, syn_school_uids
def test_send_students_to_school(location='seattle_metro',
state_location='Washington',
country_location='usa'):
NPeople = 10000
uids_in_school, uids_in_school_by_age, ages_in_school_count = sp.get_uids_in_school(
datadir,
NPeople,
location,
state_location,
country_location,
use_default=True)
school_size_distr_by_bracket = sp.get_school_size_distr_by_brackets(
datadir, location, state_location, country_location)
school_size_brackets = sp.get_school_size_brackets(datadir, location,
state_location,
country_location)
school_sizes = sp.generate_school_sizes(school_size_distr_by_bracket,
school_size_brackets,
uids_in_school)
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)
age_by_brackets_dic = sp.get_age_by_brackets_dic(age_brackets)
contact_matrix_dic = sp.get_contact_matrix_dic(
datadir, sheet_name='United States of America')
syn_schools, syn_school_uids = sp.send_students_to_school(
school_sizes,
uids_in_school,
uids_in_school_by_age,
ages_in_school_count,
age_brackets,
age_by_brackets_dic,
contact_matrix_dic,
verbose=False)
assert syn_schools, syn_school_uids is not None
