def test_assign_teachers_to_work(location='seattle_metro',
state_location='Washington',
country_location='usa',
folder_name='contact_networks',
n=10000):
# Assign students to school
gen_schools, gen_school_uids = test_send_students_to_school()
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, n)
uids_in_school = sp.get_uids_in_school(datadir,
n,
location,
state_location,
country_location,
folder_name=folder_name,
use_default=True)
potential_worker_uids, potential_worker_uids_by_age, \
potential_worker_ages_left_count = sp.get_uids_potential_workers(uids_in_school, 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)
# Assign teachers and update school lists
syn_schools, syn_school_uids, potential_worker_uids, potential_worker_uids_by_age, \
workers_by_age_to_assign_count = sp.assign_teachers_to_work(gen_schools, gen_school_uids, employment_rates,
workers_by_age_to_assign_count,
potential_worker_uids, potential_worker_uids_by_age,
potential_worker_ages_left_count,
student_teacher_ratio=30, teacher_age_min=25,
teacher_age_max=75, verbose=False)
for n in range(len(syn_schools)):
print(syn_schools[n])
assert syn_schools[n] is not None
assert syn_school_uids[n] is not None
assert syn_schools == gen_schools
assert syn_school_uids == gen_school_uids
assert potential_worker_uids == potential_worker_uids
assert potential_worker_uids_by_age == potential_worker_uids_by_age
assert workers_by_age_to_assign_count == workers_by_age_to_assign_count
def test_get_uids_potential_workers(location='seattle_metro', state_location='Washington',
country_location='usa', folder_name='contact_networks'):
Nhomes = 10000
uids_in_school = sp.get_uids_in_school(datadir, Nhomes, location,
state_location,
country_location,
folder_name=folder_name,
use_default=True)
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, Nhomes)
potential_worker_uids, potential_worker_uids_by_age, potential_worker_ages_left_count = sp.get_uids_potential_workers(
uids_in_school, employment_rates, age_by_uid_dic)
assert potential_worker_ages_left_count is not None
return potential_worker_uids, potential_worker_uids_by_age, employment_rates, age_by_uid_dic
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_generate_workplace_sizes(location='seattle_metro',
state_location='Washington',
country_location='usa'):
Npeople = 10000
uids_in_school, uids_in_school_by_age, uids_in_school_count = sp.get_uids_in_school(
datadir,
Npeople,
location,
state_location,
country_location,
use_default=True)
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, Npeople)
potential_worker_uids, potential_worker_uids_by_age, potential_worker_ages_left_count = sp.get_uids_potential_workers(
uids_in_school, 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)
print(workplace_sizes)
y_sim[a] = new_ages_count[a]
ax.plot(x, y_exp, color=cmap(0.2), label='Expected')
ax.plot(x, y_sim, color=cmap3(0.6), label='Simulated')
leg = ax.legend(fontsize=18)
leg.draw_frame(False)
ax.set_xlim(left=0, right=100)
# fig.savefig('synthetic_age_comparison.pdf',format = 'pdf')
# plt.show()
sp.write_homes_by_age_and_uid(datadir, location, state_location,
country_location, homes_by_uids,
age_by_uid_dic)
age_by_uid_dic = sp.read_in_age_by_uid(datadir, location, state_location,
country_location, Nhomes)
level = 'county'
sc_df = sp.get_school_enrollment_rates_df(datadir, location, state_location,
level)
rates_by_age = sp.get_school_enrollment_rates(datadir, location,
state_location, level)
school_sizes_count = sp.get_school_sizes_by_bracket(datadir, location,
state_location)
# print(school_sizes_count)
uids_by_age_dic = sp.get_ids_by_age_dic(age_by_uid_dic)
# for a in sorted(uids_by_age_dic):
# print(a, len(uids_by_age_dic[a]))