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final paper examples #158

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20 changes: 20 additions & 0 deletions examples/paper/seeds_final_examples.txt
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@@ -0,0 +1,20 @@
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47 changes: 7 additions & 40 deletions examples/paper/simulate_idealized_NYC_epidemic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -67,7 +67,7 @@
set_num_threads(1)

# Set random seeds for reproducibility
seed = 942395
seed = 1231414#1285854#1237102#123746
seed_three_random_states(seed)

# contact network ##############################################################
Expand Down Expand Up @@ -119,7 +119,7 @@
statuses = random_epidemic(
network.get_node_count(),
network.get_nodes(),
fraction_infected=0.0025)
fraction_infected=0.0015)

epidemic_simulator.set_statuses(statuses)

Expand All @@ -129,7 +129,7 @@
# set the new contact rates on the network
# run the kinetic model [kinetic produces the current statuses used as data]
network = epidemic_simulator.run(
stop_time = epidemic_simulator.time + 18,
stop_time = epidemic_simulator.time + 19,
current_network = network)

kinetic_model = epidemic_simulator.kinetic_model
Expand All @@ -141,40 +141,7 @@
λ_min = 2 # minimum contact rate
λ_max = 8 # maximum contact rate

health_service = epidemic_simulator.health_service

statuses = epidemic_simulator.kinetic_model.current_statuses

epidemic_simulator = EpidemicSimulator(
network,
community_transmission_rate = community_transmission_rate['mean'],
hospital_transmission_reduction = hospital_transmission_reduction,
static_contact_interval = static_contact_interval,
mean_contact_lifetime = mean_contact_lifetime,
day_inception_rate = λ_max,
night_inception_rate = λ_min,
health_service = health_service,
start_time = epidemic_simulator.time)

epidemic_simulator.set_statuses(statuses)

# run the kinetic model
network = epidemic_simulator.run(
stop_time = epidemic_simulator.time + 83,
current_network = network)

for key in kinetic_model.statuses.keys():
kinetic_model.statuses[key].extend(epidemic_simulator.kinetic_model.statuses[key])


kinetic_model.times.extend(kinetic_model.times[-1]+epidemic_simulator.kinetic_model.times)

################################################################################
# loosening SD intervention ####################################################
################################################################################

λ_min = 2 # minimum contact rate
λ_max = 22 # maximum contact rate
network.set_lambdas(λ_min, λ_max)

health_service = epidemic_simulator.health_service

Expand All @@ -195,20 +162,20 @@

# run the kinetic model
network = epidemic_simulator.run(
stop_time = epidemic_simulator.time + 90,
stop_time = epidemic_simulator.time + 112,
current_network = network)

for key in kinetic_model.statuses.keys():
kinetic_model.statuses[key].extend(epidemic_simulator.kinetic_model.statuses[key])

kinetic_model.times.extend(kinetic_model.times[-1]+epidemic_simulator.kinetic_model.times)
kinetic_model.times.extend(epidemic_simulator.kinetic_model.times)

################################################################################
# save #########################################################################
################################################################################
if SAVE_FLAG:
np.savetxt(
os.path.join(SIMULATION_PATH, 'NYC_interventions_1e5.txt'),
os.path.join(SIMULATION_PATH, 'NYC_interventions_1e5_13.txt'),
np.c_[
kinetic_model.times,
kinetic_model.statuses['S'],
Expand Down
8 changes: 4 additions & 4 deletions examples/paper/simulate_idealized_NYC_epidemic_nointervention.py
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Original file line number Diff line number Diff line change
Expand Up @@ -67,7 +67,7 @@
set_num_threads(1)

# Set random seeds for reproducibility
seed = 942395
seed = 914235813
seed_three_random_states(seed)

# contact network ##############################################################
Expand Down Expand Up @@ -119,7 +119,7 @@
statuses = random_epidemic(
network.get_node_count(),
network.get_nodes(),
fraction_infected=0.0025)
fraction_infected=0.0015)

epidemic_simulator.set_statuses(statuses)

Expand All @@ -129,7 +129,7 @@
# set the new contact rates on the network
# run the kinetic model [kinetic produces the current statuses used as data]
network = epidemic_simulator.run(
stop_time = epidemic_simulator.time + 185,
stop_time = epidemic_simulator.time + 132,
current_network = network)

kinetic_model = epidemic_simulator.kinetic_model
Expand All @@ -139,7 +139,7 @@
################################################################################
if SAVE_FLAG:
np.savetxt(
os.path.join(SIMULATION_PATH, 'NYC_nointerventions_1e5.txt'),
os.path.join(SIMULATION_PATH, 'NYC_nointerventions_1e5_19.txt'),
np.c_[
kinetic_model.times,
kinetic_model.statuses['S'],
Expand Down
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