def get(self):
query = Parameters.query()
parameters = query.fetch(limit=None)
if parameters is None or len(parameters) == 0:
p = Parameters(name="ADE Project", value="TELECOM Nancy")
p.put()
query = Parameters.query()
parameters = query.fetch(limit=None)
time.sleep(1)
self.render("administration_parameters.html", parameters=parameters)
def test_update_fatality_fraction(self):
params = Parameters(
constant.TEST_DATA_TEMPLATE,
constant.PARAM_LINE_NUMBER,
constant.DATA_DIR_TEST,
constant.TEST_HOUSEHOLD_FILE,
constant.TEST_HOSPITAL_FILE,
)
params.set_param( "n_total", 50000 )
model = Model(params)
assert model.get_param("fatality_fraction_80") == 1.0
model.update_running_params("fatality_fraction_80", 0.6)
assert model.get_param("fatality_fraction_80") == 0.6
def test_model_total_infected_by_age(self):
params = Parameters(
constant.TEST_DATA_TEMPLATE,
constant.PARAM_LINE_NUMBER,
constant.DATA_DIR_TEST,
constant.TEST_HOUSEHOLD_FILE,
)
params.set_param( "app_users_fraction", 0.25)
model = Model(params)
for _ in range(30):
model.one_time_step()
res = model.one_time_step_results()
for age in AgeGroupEnum:
assert res.get(f"total_infected{age.name}", None) is not None, f"Could not get total_infected{age.name}"
assert res.get("total_infected") == sum([res.get(f"total_infected{age.name}") for age in AgeGroupEnum]), "Total infected does not equal sum of age groups"
def test_set_lockdown_multiplier_params(self):
params = Parameters(
constant.TEST_DATA_TEMPLATE,
constant.PARAM_LINE_NUMBER,
constant.DATA_DIR_TEST,
constant.TEST_HOUSEHOLD_FILE,
)
model = Model(params)
assert covid19.get_param_lockdown_on(model.c_params) == 0
model.update_running_params("lockdown_work_network_multiplier", 0.4)
assert model.get_param("lockdown_work_network_multiplier") == 0.4
model.update_running_params("lockdown_random_network_multiplier", 0.8)
assert model.get_param("lockdown_random_network_multiplier") == 0.8
model.update_running_params("lockdown_house_interaction_multiplier",
1.2)
assert model.get_param("lockdown_house_interaction_multiplier") == 1.2
model.update_running_params("lockdown_on", 1)
assert covid19.get_param_lockdown_on(model.c_params) == 1
model.update_running_params("lockdown_work_network_multiplier", 0.5)
assert model.get_param("lockdown_work_network_multiplier") == 0.5
model.update_running_params("lockdown_random_network_multiplier", 0.9)
assert model.get_param("lockdown_random_network_multiplier") == 0.9
model.update_running_params("lockdown_house_interaction_multiplier",
1.3)
assert model.get_param("lockdown_house_interaction_multiplier") == 1.3
assert covid19.get_param_lockdown_on(model.c_params) == 1
def test_hostpital_admissions(self):
params = Parameters(
constant.TEST_DATA_TEMPLATE,
constant.PARAM_LINE_NUMBER,
constant.DATA_DIR_TEST,
constant.TEST_HOUSEHOLD_FILE,
constant.TEST_HOSPITAL_FILE,
)
params.set_param( "n_total", 50000 )
model = Model(params)
daily_hospitalisations = []
for step in range(50):
model.one_time_step()
daily_h = model.one_time_step_results()["hospital_admissions"]
daily_hospitalisations.append(daily_h)
assert sum(daily_hospitalisations) == model.one_time_step_results()["hospital_admissions_total"]
assert sum(daily_hospitalisations) > 0
def test_icu_entry(self):
params = Parameters(
constant.TEST_DATA_TEMPLATE,
constant.PARAM_LINE_NUMBER,
constant.DATA_DIR_TEST,
constant.TEST_HOUSEHOLD_FILE,
constant.TEST_HOSPITAL_FILE,
)
params.set_param( "n_total", 50000 )
model = Model(params)
daily_critical = []
for step in range(50):
model.one_time_step()
daily_c = model.one_time_step_results()["hospital_to_critical_daily"]
daily_critical.append(daily_c)
assert sum(daily_critical) == model.one_time_step_results()["hospital_to_critical_total"]
assert sum(daily_critical) > 0
def test_deaths(self):
params = Parameters(
constant.TEST_DATA_TEMPLATE,
constant.PARAM_LINE_NUMBER,
constant.DATA_DIR_TEST,
constant.TEST_HOUSEHOLD_FILE,
constant.TEST_HOSPITAL_FILE,
)
params.set_param( "n_total", 50000);
model = Model(params)
daily_deaths = []
for step in range(50):
model.one_time_step()
daily_death = model.one_time_step_results()["daily_death"]
daily_deaths.append(daily_death)
assert sum(daily_deaths) == model.one_time_step_results()["total_death"]
assert sum(daily_deaths) > 0
def basic_example_lockdown_agent():
params = Parameters("../tests/data/baseline_parameters.csv", 1, ".",
"../tests/data/baseline_household_demographics.csv")
T = 35
params.set_param("end_time", T)
model = simulation.COVID19IBM(model=Model(params))
agent = LockdownAt20()
sim = simulation.Simulation(env=model,
agent=agent,
end_time=T,
verbose=True)
# Run the model for 25 time steps, print output
sim.steps(25)
print(sim.results)
model.model.write_output_files()
def get_sim_parameters():
sim_params = Parameters()
sim_params.t0 = 0
sim_params.tf = 10
sim_params.dt = 0.04
sim_params.x0 = [0, 0, 0]
sim_params.xf = [5, 5, 0]
return sim_params
def test_daily_deaths_by_age(self):
params = Parameters(
constant.TEST_DATA_TEMPLATE,
constant.PARAM_LINE_NUMBER,
constant.DATA_DIR_TEST,
constant.TEST_HOUSEHOLD_FILE,
constant.TEST_HOSPITAL_FILE,
)
params.set_param( "n_total", 50000 )
model = Model(params)
for step in range(50):
model.one_time_step()
daily_death = model.one_time_step_results()["daily_death"]
sum_daily_deaths_by_age = 0
for age in AgeGroupEnum:
sum_daily_deaths_by_age += model.one_time_step_results()[f"daily_death{age.name}"]
assert daily_death == sum_daily_deaths_by_age
assert model.one_time_step_results()[f"daily_death{age.name}"] > 0
def basic_example_dummy_agent():
params = Parameters("../tests/data/baseline_parameters.csv", 1, ".",
"../tests/data/baseline_household_demographics.csv")
T = 15
params.set_param("end_time", T)
model = simulation.COVID19IBM(model=Model(params))
agent = simulation.Agent() # Dummy agent
sim = simulation.Simulation(env=model,
agent=agent,
end_time=T,
verbose=True)
# Run the model for 3 time steps, print output
sim.steps(3)
print(sim.results)
# RUn for another 5 time steps, print output
sim.steps(5)
print(sim.results)
def test_set_parameters_arrays_set_single_value(self):
p = Parameters(input_households="notset.csv", read_param_file=False, read_hospital_param_file=False)
assert (
p.get_param("population_40_49") == 0
), "Array memebers not intilialised to zero"
p.set_param("population_40_49", 400)
assert (
p.get_param("population_40_49") == 400
), "Did not set pop group to 400"
assert p.get_param("population_50_59") == 0
def test_set_lockdown_multiplier_params(self):
params = Parameters(
constant.TEST_DATA_TEMPLATE,
constant.PARAM_LINE_NUMBER,
constant.DATA_DIR_TEST,
constant.TEST_HOUSEHOLD_FILE,
constant.TEST_HOSPITAL_FILE,
constant.PARAM_LINE_NUMBER
)
params.set_param( "n_total", 50000 )
model = Model(params)
assert covid19.get_param_lockdown_on(model.c_params) == 0
for oc_net in OccupationNetworkEnum:
model.update_running_params(f"lockdown_occupation_multiplier{oc_net.name}", 0.4)
assert model.get_param(f"lockdown_occupation_multiplier{oc_net.name}") == 0.4
for oc_net in OccupationNetworkEnum:
model.update_running_params(f"lockdown_occupation_multiplier{oc_net.name}", 0.8)
assert model.get_param(f"lockdown_occupation_multiplier{oc_net.name}") == 0.8
model.update_running_params("lockdown_house_interaction_multiplier", 1.2)
assert model.get_param("lockdown_house_interaction_multiplier") == 1.2
model.update_running_params("lockdown_on", 1)
assert covid19.get_param_lockdown_on(model.c_params) == 1
for oc_net in OccupationNetworkEnum:
model.update_running_params(f"lockdown_occupation_multiplier{oc_net.name}", 0.5)
assert model.get_param(f"lockdown_occupation_multiplier{oc_net.name}") == 0.5
model.update_running_params("lockdown_random_network_multiplier", 0.9)
assert model.get_param("lockdown_random_network_multiplier") == 0.9
model.update_running_params("lockdown_house_interaction_multiplier", 1.3)
assert model.get_param("lockdown_house_interaction_multiplier") == 1.3
assert covid19.get_param_lockdown_on(model.c_params) == 1
def get_traj_parameters():
sim_params = get_sim_parameters()
traj_params = Parameters()
traj_params.t0 = sim_params.t0 + 1
traj_params.tf = sim_params.tf - 1
# boundary conditions for y1
traj_params.Y1A = np.array([sim_params.x0[0], 0])
traj_params.Y1B = np.array([sim_params.xf[0], 0])
# boundary conditions for y2
traj_params.Y2A = np.array([sim_params.x0[1], tan(sim_params.x0[2]), 0])
traj_params.Y2B = np.array([sim_params.xf[1], tan(sim_params.xf[2]), 0])
return traj_params
def test_hostpital_admissions(self):
params = Parameters(
constant.TEST_DATA_TEMPLATE,
constant.PARAM_LINE_NUMBER,
constant.DATA_DIR_TEST,
constant.TEST_HOUSEHOLD_FILE,
)
model = Model(params)
daily_hospitalisations = []
daily_critical = []
for step in range(10):
model.one_time_step()
daily_h = model.one_time_step_results()["hospital_admissions"]
daily_c = model.one_time_step_results()["hospital_to_critical_daily"]
daily_hospitalisations.append(daily_h)
daily_critical.append(daily_c)
assert sum(daily_hospitalisations) == model.one_time_step_results()["hospital_admissions_total"]
assert sum(daily_critical) == model.one_time_step_results()["hospital_to_critical_total"]
def basic_example_lockdown_infected_agent():
params = Parameters("../tests/data/baseline_parameters.csv", 1, ".",
"../tests/data/baseline_household_demographics.csv")
T = 50
params.set_param("end_time", T)
params.set_param("n_total", 10000)
model = simulation.COVID19IBM(model=Model(params))
agent = LockdownInfectedOnePercent()
sim = simulation.Simulation(env=model,
agent=agent,
end_time=T,
verbose=True)
# Run the model for 25 time steps, print output
sim.steps(25)
print(sim.results)
def test_set_parameters_arrays_init_to_zero(self):
p = Parameters(input_households="notset.csv", read_param_file=False, read_hospital_param_file=False)
assert p.get_param("population_40_49") == 0
def test_set_age_out_of_range(self):
p = Parameters(input_households="notset.csv", read_param_file=False, read_hospital_param_file=False)
with pytest.raises(ParameterException):
p.set_param("population_80_89", 5000)
hyperparams_dict["dataset"] = 'metr-la'
hyperparams_dict["horizon"] = 12
hyperparams_dict["history_length"] = 12
print("*********************************")
print("LOADING DATA")
print("*********************************")
dataset = Dataset(name=hyperparams_dict["dataset"],
horizon=hyperparams_dict["horizon"],
history_length=hyperparams_dict["history_length"],
path=DATADIR)
hyperparams_dict["num_nodes"] = dataset.num_nodes
hyperparams = Parameters(**hyperparams_dict)
print("*********************************")
print("TRAINING MODELS")
print("*********************************")
trainer = Trainer(hyperparams=hyperparams, logdir=LOGDIR)
trainer.fit(dataset=dataset)
print("*********************************")
print("COMPUTING METRICS")
print("*********************************")
early_stop_mae_h_repeats = dict()
early_stop_mape_h_repeats = dict()
early_stop_rmse_h_repeats = dict()
def test_set_get_model_parameters(self):
"""
Test the a parameter can be changed in between step runs
"""
# Cr.eate model object
params = Parameters(
constant.TEST_DATA_TEMPLATE,
constant.PARAM_LINE_NUMBER,
constant.DATA_DIR_TEST,
constant.TEST_HOUSEHOLD_FILE,
constant.TEST_HOSPITAL_FILE,
constant.HOSPITAL_PARAM_LINE_NUMBER
)
params.set_param( "n_total", 50000 )
model = Model(params)
# Run steps
for step in range(0, STEPS):
model.one_time_step()
# Try to set valid model parameters
model.update_running_params("test_on_symptoms", 1)
np.testing.assert_equal(model.get_param("test_on_symptoms"), 1)
model.update_running_params("test_on_traced", 1)
np.testing.assert_equal(model.get_param("test_on_traced"), 1)
model.update_running_params("quarantine_on_traced", 1)
np.testing.assert_equal(model.get_param("quarantine_on_traced"), 1)
model.update_running_params("traceable_interaction_fraction", 0.30)
np.testing.assert_equal(
model.get_param("traceable_interaction_fraction"), 0.30
)
model.update_running_params("tracing_network_depth", 1)
np.testing.assert_equal(model.get_param("tracing_network_depth"), 1)
model.update_running_params("allow_clinical_diagnosis", 1)
np.testing.assert_equal(model.get_param("allow_clinical_diagnosis"), 1)
model.update_running_params("quarantine_household_on_positive", 1)
np.testing.assert_equal(
model.get_param("quarantine_household_on_positive"), 1
)
model.update_running_params("quarantine_household_on_symptoms", 1)
np.testing.assert_equal(
model.get_param("quarantine_household_on_symptoms"), 1
)
model.update_running_params("quarantine_household_on_traced_positive", 1)
np.testing.assert_equal(
model.get_param("quarantine_household_on_traced_positive"), 1
)
model.update_running_params("quarantine_household_contacts_on_positive", 1)
np.testing.assert_equal(
model.get_param("quarantine_household_contacts_on_positive"), 1,
)
model.update_running_params("quarantine_days", 1)
np.testing.assert_equal(model.get_param("quarantine_days"), 1)
model.update_running_params("test_order_wait", 1)
np.testing.assert_equal(model.get_param("test_order_wait"), 1)
model.update_running_params("test_result_wait", 1)
np.testing.assert_equal(model.get_param("test_result_wait"), 1)
model.update_running_params("self_quarantine_fraction", 1)
np.testing.assert_equal(model.get_param("self_quarantine_fraction"), 1)
# Try to set/get array model parameters
for age in AgeGroupEnum:
contacts = randrange(1, 10)
model.update_running_params(f"priority_test_contacts{age.name}", contacts)
assert model.get_param(f"priority_test_contacts{age.name}") == contacts
# Try to set/get invalid parameters
with pytest.raises(ModelParameterException):
model.update_running_params("wrong_parameter", 1)
with pytest.raises(ModelParameterException):
model.get_param("wrong_parameter")
from typing import Union
from constants import Constants
app = Flask(__name__)
database = Database(
os.environ[Constants.DATABASE_URL],
os.environ[Constants.DATABASE_REPLICA_SET],
int(os.environ[Constants.DATABASE_PORT]),
os.environ[Constants.DATABASE_NAME],
)
request_validator = UserRequest(database)
storage = ObjectStorage(database)
data = Data(database, storage)
parameters_handler = Parameters(database, data)
@app.route("/defaultModel", methods=["POST"])
def create_default_model() -> jsonify:
service_type = request.args.get(Constants.TYPE_PARAM_NAME)
model_name = request.json[Constants.MODEL_FIELD_NAME]
description = request.json[Constants.DESCRIPTION_FIELD_NAME]
module_path = request.json[Constants.MODULE_PATH_FIELD_NAME]
class_name = request.json[Constants.CLASS_FIELD_NAME]
class_parameters = request.json[Constants.FUNCTION_PARAMETERS_NAME]
request_errors = analyse_post_request_errors(
request_validator,
model_name,
def test_set_get_parameters(self):
"""
Test the a parameter can be changed in between step runs
"""
# Create model object
params = Parameters(
constant.TEST_DATA_TEMPLATE,
constant.PARAM_LINE_NUMBER,
constant.DATA_DIR_TEST,
constant.TEST_HOUSEHOLD_FILE,
)
params.set_param("app_users_fraction", 0.25)
model = Model(params)
STEPS = 2
# Run steps
for step in range(0, STEPS):
model.one_time_step()
res = model.one_time_step_results()
# Try to set valid parameters
model.update_running_params("test_on_symptoms", 1)
np.testing.assert_equal(model.get_param("test_on_symptoms"), 1)
model.update_running_params("test_on_traced", 1)
np.testing.assert_equal(model.get_param("test_on_traced"), 1)
model.update_running_params("quarantine_on_traced", 1)
np.testing.assert_equal(model.get_param("quarantine_on_traced"), 1)
model.update_running_params("traceable_interaction_fraction", 0.30)
np.testing.assert_equal(
model.get_param("traceable_interaction_fraction"), 0.30)
model.update_running_params("tracing_network_depth", 1)
np.testing.assert_equal(model.get_param("tracing_network_depth"),
1)
model.update_running_params("allow_clinical_diagnosis", 1)
np.testing.assert_equal(
model.get_param("allow_clinical_diagnosis"), 1)
model.update_running_params("quarantine_household_on_positive", 1)
np.testing.assert_equal(
model.get_param("quarantine_household_on_positive"), 1)
model.update_running_params("quarantine_household_on_symptoms", 1)
np.testing.assert_equal(
model.get_param("quarantine_household_on_symptoms"), 1)
model.update_running_params(
"quarantine_household_on_traced_positive", 1)
np.testing.assert_equal(
model.get_param("quarantine_household_on_traced_positive"), 1)
model.update_running_params(
"quarantine_household_contacts_on_positive", 1)
np.testing.assert_equal(
model.get_param("quarantine_household_contacts_on_positive"),
1,
)
model.update_running_params("quarantine_days", 1)
np.testing.assert_equal(model.get_param("quarantine_days"), 1)
model.update_running_params("test_order_wait", 1)
np.testing.assert_equal(model.get_param("test_order_wait"), 1)
model.update_running_params("test_result_wait", 1)
np.testing.assert_equal(model.get_param("test_result_wait"), 1)
model.update_running_params("self_quarantine_fraction", 1)
np.testing.assert_equal(
model.get_param("self_quarantine_fraction"), 1)
# Try to set/get invalid parameters
with pytest.raises(ModelParameterException):
model.update_running_params("wrong_parameter", 1)
with pytest.raises(ModelParameterException):
model.get_param("wrong_parameter")
def get_controller_params():
k = Parameters()
k.k01 = 1
k.k02 = 1
k.k12 = 5
return k