def run_model(param_updates, n_steps=200, lockdown_at=None):
params = setup_params(param_updates)
# Create an instance of the Model
model = Model(params)
m_out = []
for step in trange(n_steps):
# Evaluate each step and save the results
model.one_time_step()
# LOGGER.info(
# model.one_time_step_results()
# ) # If we want to see the results as we go uncomment this block
m_out.append(model.one_time_step_results())
if lockdown_at:
if step == lockdown_at:
model.update_running_params("lockdown_on", 1)
LOGGER.info(f"turning on lock down at step {step}")
LOGGER.info(
f'lockdown_house_interaction_multiplier = {params.get_param("lockdown_house_interaction_multiplier")}'
)
LOGGER.info(
f'lockdown_random_network_multiplier = {params.get_param("lockdown_random_network_multiplier")}'
)
for oc_net in OccupationNetworkEnum:
LOGGER.info(
f'lockdown_occupation_multiplier{oc_net.name} = {params.get_param(f"lockdown_occupation_multiplier{oc_net.name}")}'
)
df = pd.DataFrame(m_out)
model.write_output_files()
return df
def test_set_params_occupation_network_by_age_check_used(self):
p = Parameters(
read_param_file=True,
input_households="tests/data/baseline_household_demographics.csv",
input_param_file="tests/data/baseline_parameters.csv",
param_line_number=1,
)
model = Model(p)
non_scaled = [
model.get_param(f"daily_fraction_work_used{age.name}")
for age in OccupationNetworkEnum
]
model.update_running_params("lockdown_on", 1)
scaled = [
model.get_param(f"daily_fraction_work_used{age.name}")
for age in OccupationNetworkEnum
]
for non_scaled_i, scaled_i in zip(non_scaled, scaled):
assert non_scaled_i * 0.2 == scaled_i
model.update_running_params(
"lockdown_occupation_multiplier_primary_network", 10.0)
scaled = [
model.get_param(f"daily_fraction_work_used{age.name}")
for age in OccupationNetworkEnum
]
for non_scaled_i, scaled_i, factor in zip(non_scaled, scaled, [
10.0,
0.2,
0.2,
0.2,
0.2,
]):
assert non_scaled_i * factor == scaled_i
def test_set_params_manual_traceable_fraction(self):
p = Parameters(
read_param_file=True,
input_households="tests/data/baseline_household_demographics.csv",
input_param_file="tests/data/baseline_parameters.csv",
param_line_number=1,
)
p.set_param("manual_traceable_fraction_occupation", 0.8)
assert p.get_param("manual_traceable_fraction_occupation") == 0.8
p.set_param("manual_traceable_fraction_household", 0.6)
assert p.get_param("manual_traceable_fraction_household") == 0.6
assert p.get_param("manual_traceable_fraction_occupation") == 0.8
model = Model(p)
model.update_running_params("manual_traceable_fraction_household", 0.4)
assert model.get_param("manual_traceable_fraction_household") == 0.4