def do_parallel_run(env_dic, params, run_id, specific_seed, pba: ActorHandle):
run_stats = get_zero_run_stats(params)
random.seed(specific_seed)
np.random.seed(specific_seed)
params[store_preference_key] = 0.95
params[remote_work_key] = 0.98
params[innoculation_number_key] = 5
available_beds = params[icu_bed_per_thousand_individual_key] * params[
nindividual_key] / 1000
virus_dic = get_virus_simulation_t0(params)
for day in range(params[nday_key]):
pba.update.remote(1)
propagate_to_houses(env_dic, virus_dic, params[house_infect_key])
if not is_weekend(day):
propagate_to_transportation(env_dic, virus_dic,
params[transport_infection_key],
params[remote_work_key],
params[transport_contact_cap_key])
propagate_to_workplaces(env_dic, virus_dic,
params[work_infection_key],
params[remote_work_key])
if is_weekend(day):
propagate_to_stores(env_dic, virus_dic,
params[store_infection_key],
params[store_preference_key])
increment_pandemic_1_day(env_dic, virus_dic, available_beds)
update_run_stat(virus_dic, run_stats, day)
run_stats["loc"][day] = measure_lockdown_strength(params)
return run_id, run_stats
def do_parallel_run(env_dic, params, run_id, specific_seed, pba: ActorHandle):
run_stats = get_zero_run_stats(params)
random.seed(specific_seed)
np.random.seed(specific_seed)
if len(params[additional_scenario_params_key]) < 1:
raise AssertionError("Need more additional_scenario parameter")
nb_to_infect = int(params[additional_scenario_params_key][0])
params[store_preference_key] = 0.95
params[remote_work_key] = 0.98
params[house_infect_key] = 0.5
params[work_infection_key] = 0.01
params[transport_infection_key] = 0.01
params[innoculation_number_key] = 50
available_beds = params[icu_bed_per_thousand_individual_key] * params[
nindividual_key] / 1000
virus_dic = get_virus_simulation_t0(params)
for day in range(params[nday_key]):
pba.update.remote(1)
propagate_to_houses(env_dic, virus_dic, params[house_infect_key])
if not is_weekend(day):
propagate_to_transportation(env_dic, virus_dic,
params[transport_infection_key],
params[remote_work_key],
params[transport_contact_cap_key])
propagate_to_workplaces(env_dic, virus_dic,
params[work_infection_key],
params[remote_work_key])
if is_weekend(day):
propagate_to_stores(env_dic, virus_dic,
params[store_infection_key],
params[store_preference_key])
increment_pandemic_1_day(env_dic, virus_dic, available_beds)
update_infection_period(
get_random_sample(get_healthy_people(virus_dic), nb_to_infect),
virus_dic)
update_run_stat(virus_dic, run_stats, day)
run_stats["loc"][day] = measure_lockdown_strength(params)
return run_id, run_stats
def do_parallel_run(env_dic, params, run_id, specific_seed, pba: ActorHandle):
run_stats = get_zero_run_stats(params)
random.seed(specific_seed)
np.random.seed(specific_seed)
params[store_preference_key] = 0.95
params[remote_work_key] = 0.98
params[house_infect_key] = 0.5
params[work_infection_key] = 0.01
params[store_infection_key] = 0.001
params[transport_infection_key] = 0.01
params[innoculation_number_key] = 50
available_beds = params[icu_bed_per_thousand_individual_key] * params[
nindividual_key] / 1000
if len(params[additional_scenario_params_key]) < 3:
raise AssertionError("Need more additional_scenario parameter")
days_to_lockdown_loosening = float(
params[additional_scenario_params_key][0])
factor_bed = float(params[additional_scenario_params_key][1])
max_lockdown = float(params[additional_scenario_params_key][2])
days_with_no_cases = 0
days_to_lockdown_change = 0
first_day_lockdown_loosening = -1
virus_dic = get_virus_simulation_t0(params)
for day in range(params[nday_key]):
pba.update.remote(1)
propagate_to_houses(env_dic, virus_dic, params[house_infect_key])
if not is_weekend(day):
propagate_to_transportation(env_dic, virus_dic,
params[transport_infection_key],
params[remote_work_key],
params[transport_contact_cap_key])
propagate_to_workplaces(env_dic, virus_dic,
params[work_infection_key],
params[remote_work_key])
if is_weekend(day):
propagate_to_stores(env_dic, virus_dic,
params[store_infection_key],
params[store_preference_key])
increment_pandemic_1_day(env_dic, virus_dic, available_beds)
days_to_lockdown_change += 1
if virus_dic[NC_K] == 0:
days_with_no_cases += 1
else:
days_with_no_cases = 0
if days_with_no_cases > days_to_lockdown_loosening and days_to_lockdown_change >= 7:
if first_day_lockdown_loosening == -1:
first_day_lockdown_loosening = day
days_with_no_cases = 0
days_to_lockdown_change = 0
soften_full_lockdown(params)
if virus_dic[NC_K] >= available_beds * factor_bed and days_to_lockdown_change >= 7 \
and measure_lockdown_strength(params) < max_lockdown:
days_to_lockdown_change = 0
tighten_full_lockdown(params)
update_run_stat(virus_dic, run_stats, day)
run_stats["loc"][day] = measure_lockdown_strength(params)
return run_id, run_stats
def do_parallel_run(env_dic, params, run_id, specific_seed, pba: ActorHandle):
random.seed(specific_seed)
np.random.seed(specific_seed)
if len(params[additional_scenario_params_key]) < 1:
raise AssertionError("Need more additional_scenario parameter")
else:
rate_daily_vaccinated = int(params[additional_scenario_params_key][0])
if rate_daily_vaccinated < 0:
# Morrocan daily rate of vaccination
rate_daily_vaccinated = 0.00428
params[store_preference_key] = 0.5
params[remote_work_key] = 0.5
params[innoculation_number_key] = 5
available_beds = params[icu_bed_per_thousand_individual_key] * params[
nindividual_key] / 1000
run_stats = get_zero_run_stats(params)
params[house_infect_key] = 0.5
params[work_infection_key] = 0.05
params[store_infection_key] = 0.02
params[transport_infection_key] = 0.01
params[immunity_bounds_key] = (
270, 450) # assuming about a year of immunity (~flu)
virus_dic = get_virus_simulation_t0(params)
for day in range(params[nday_key]):
pba.update.remote(1)
old_healthy = [(k, env_dic[IAG_K][k])
for k, v in virus_dic[STA_K].items() if v == HEALTHY_V]
nb_indiv_vaccinated = max(
0,
int(params[nindividual_key] * rate_daily_vaccinated *
(1 - day / 100)))
if len(old_healthy) > nb_indiv_vaccinated and day <= 100:
old_sorted = sorted(old_healthy, key=lambda kv: -kv[1])
old_lucky = [o[0] for o in old_sorted[:nb_indiv_vaccinated]]
virus_dic[STA_K].update((o, IMMUNE_V) for o in old_lucky)
propagate_to_houses(env_dic, virus_dic, params[house_infect_key])
if not is_weekend(day):
propagate_to_transportation(env_dic, virus_dic,
params[transport_infection_key],
params[remote_work_key],
params[transport_contact_cap_key])
propagate_to_workplaces(env_dic, virus_dic,
params[work_infection_key],
params[remote_work_key])
if is_weekend(day):
propagate_to_stores(env_dic, virus_dic,
params[store_infection_key],
params[store_preference_key])
increment_pandemic_1_day(env_dic, virus_dic, available_beds)
update_run_stat(virus_dic, run_stats, day)
return run_id, run_stats
def do_parallel_run(env_dic, params, run_id, specific_seed, pba: ActorHandle):
run_stats = get_zero_run_stats(params)
random.seed(specific_seed)
np.random.seed(specific_seed)
if len(params[additional_scenario_params_key]) < 1:
raise AssertionError("Need more additional_scenario parameter")
relock_activated = bool(params[additional_scenario_params_key][0])
params[innoculation_number_key] = 5
days_to_lockdown_change = 0
days_to_lockdown_loosening = 14
unlock_progress = 0
pcn = (0.98, 0.5, 0.01, 0.01, 0.02, 0.95)
#pcn = (0.78, 0.5, 0.05, 0.05, 0.1, 0.55)
pvn = (0.58, 0.5, 0.05, 0.05, 0.1, 0.30)
params[remote_work_key] = pcn[0] * unlock_progress + (
pvn[0] - pcn[0]) * unlock_progress
params[house_infect_key] = pcn[1] * unlock_progress + (
pvn[1] - pcn[1]) * unlock_progress
params[transport_infection_key] = pcn[2] * unlock_progress + (
pvn[2] - pcn[2]) * unlock_progress
params[work_infection_key] = pcn[3] * unlock_progress + (
pvn[3] - pcn[3]) * unlock_progress
params[store_infection_key] = pcn[4] * unlock_progress + (
pvn[4] - pcn[4]) * unlock_progress
params[store_preference_key] = pcn[5] * unlock_progress + (
pvn[5] - pcn[5]) * unlock_progress
params[innoculation_number_key] = 5
available_beds = params[icu_bed_per_thousand_individual_key] * params[
nindividual_key] / 1000
virus_dic = get_virus_simulation_t0(params)
for day in range(params[nday_key]):
pba.update.remote(1)
params[remote_work_key] = pcn[0] * unlock_progress + (
pvn[0] - pcn[0]) * unlock_progress
params[house_infect_key] = pcn[1] * unlock_progress + (
pvn[1] - pcn[1]) * unlock_progress
params[transport_infection_key] = pcn[2] * unlock_progress + (
pvn[2] - pcn[2]) * unlock_progress
params[work_infection_key] = pcn[3] * unlock_progress + (
pvn[3] - pcn[3]) * unlock_progress
params[store_infection_key] = pcn[4] * unlock_progress + (
pvn[4] - pcn[4]) * unlock_progress
params[store_preference_key] = pcn[5] * unlock_progress + (
pvn[5] - pcn[5]) * unlock_progress
propagate_to_houses(env_dic, virus_dic, params[house_infect_key])
if not is_weekend(day):
propagate_to_transportation(env_dic, virus_dic,
params[transport_infection_key],
params[remote_work_key],
params[transport_contact_cap_key])
propagate_to_workplaces(env_dic, virus_dic,
params[work_infection_key],
params[remote_work_key])
if is_weekend(day):
propagate_to_stores(env_dic, virus_dic,
params[store_infection_key],
params[store_preference_key])
increment_pandemic_1_day(env_dic, virus_dic, available_beds)
days_to_lockdown_change += 1
if len(get_hospitalized_people(
virus_dic)) == 0 and days_to_lockdown_change >= 14:
days_to_lockdown_change = 0
unlock_progress = min(1, unlock_progress + 0.2)
if relock_activated:
if len(get_hospitalized_people(virus_dic)
) >= available_beds and days_to_lockdown_change >= 14:
days_to_lockdown_change = 0
unlock_progress = max(0, unlock_progress - 0.2)
update_run_stat(virus_dic, run_stats, day)
run_stats["loc"][day] = (1 - unlock_progress
) # measure_lockdown_strength(params)
return run_id, run_stats
def do_parallel_run(env_dic, params, run_id, specific_seed, pba: ActorHandle):
run_stats = get_zero_run_stats(params)
random.seed(specific_seed)
np.random.seed(specific_seed)
if len(params[additional_scenario_params_key]) < 1:
raise AssertionError("Need more additional_scenario parameter")
age_cutoff = int(params[additional_scenario_params_key][0])
params[innoculation_number_key] = 5
days_to_lockdown_change = 0
unlock_progress = 0
pcn = (0.98, 0.5, 0.01, 0.01, 0.02, 0.95)
pvn = (0.58, 0.5, 0.05, 0.05, 0.1, 0.30)
params[remote_work_key] = pcn[0] * unlock_progress + (pvn[0] - pcn[0]) * unlock_progress
params[house_infect_key] = pcn[1] * unlock_progress + (pvn[1] - pcn[1]) * unlock_progress
params[transport_infection_key] = pcn[2] * unlock_progress + (pvn[2] - pcn[2]) * unlock_progress
params[work_infection_key] = pcn[3] * unlock_progress + (pvn[3] - pcn[3]) * unlock_progress
params[store_infection_key] = pcn[4] * unlock_progress + (pvn[4] - pcn[4]) * unlock_progress
params[store_preference_key] = pcn[5] * unlock_progress + (pvn[5] - pcn[5]) * unlock_progress
params[innoculation_number_key] = 5
available_beds = params[icu_bed_per_thousand_individual_key] * params[nindividual_key] / 1000
virus_dic = get_virus_simulation_t0(params)
for day in range(params[nday_key]):
pba.update.remote(1)
params[remote_work_key] = pcn[0] * unlock_progress + (pvn[0] - pcn[0]) * unlock_progress
params[house_infect_key] = pcn[1] * unlock_progress + (pvn[1] - pcn[1]) * unlock_progress
params[transport_infection_key] = pcn[2] * unlock_progress + (pvn[2] - pcn[2]) * unlock_progress
params[work_infection_key] = pcn[3] * unlock_progress + (pvn[3] - pcn[3]) * unlock_progress
params[store_infection_key] = pcn[4] * unlock_progress + (pvn[4] - pcn[4]) * unlock_progress
params[store_preference_key] = pcn[5] * unlock_progress + (pvn[5] - pcn[5]) * unlock_progress
propagate_to_houses(env_dic, virus_dic, params[house_infect_key])
if not is_weekend(day):
propagate_to_transportation(env_dic, virus_dic, params[transport_infection_key],
params[remote_work_key], params[transport_contact_cap_key])
propagate_to_workplaces(env_dic, virus_dic, params[work_infection_key], params[remote_work_key])
if is_weekend(day):
propagate_to_stores(env_dic, virus_dic, params[store_infection_key], params[store_preference_key])
increment_pandemic_1_day(env_dic, virus_dic, available_beds)
days_to_lockdown_change += 1
young_healthy = [k for k, v in virus_dic[STA_K].items() if v == HEALTHY_V
and env_dic[IAD_K][k] == 1 and env_dic[IAG_K][k] <= age_cutoff]
young_unlucky = np.random.choice(young_healthy,
size=int(min(len(young_healthy), params[nindividual_key]/1000)),
replace=False)
virus_dic[STA_K].update((y, ISOLATED_V) for y in young_unlucky)
if len(get_hospitalized_people(virus_dic)) == 0 and days_to_lockdown_change >= 14:
days_to_lockdown_change = 0
unlock_progress = min(1, unlock_progress + 0.2)
if len(get_hospitalized_people(virus_dic)) >= available_beds and days_to_lockdown_change >= 14:
days_to_lockdown_change = 0
unlock_progress = max(0, unlock_progress - 0.2)
update_run_stat(virus_dic, run_stats, day)
# Override isolation to calculate
run_stats["iso"][day] = len(young_unlucky)
run_stats["loc"][day] = (1-unlock_progress)
return run_id, run_stats