class MiscellaneousFeatureTests(CovaTest):
def setUp(self):
super().setUp()
self.sim = Sim(pop_size=500)
self.pars = parameters.make_pars()
self.is_debugging = False
def test_xslx_generation(self):
super().tearDown()
self.is_debugging = False
root_filename = "DEBUG_test_xlsx_generation"
excel_filename = f"{root_filename}.xlsx"
if os.path.isfile(excel_filename):
os.unlink(excel_filename)
test_infected_value = 31
params_dict = {'pop_size': 500, 'pop_infected': test_infected_value}
self.run_sim(params_dict)
self.sim.to_excel(filename=root_filename)
simulation_df = pd.ExcelFile(excel_filename)
expected_sheets = ['Results', 'Parameters']
for sheet in expected_sheets:
self.assertIn(sheet, simulation_df.sheet_names)
params_df = simulation_df.parse('Parameters')
observed_infected_param = params_df.loc[
params_df['Parameter'] == 'pop_infected', 'Value'].values[0]
self.assertEqual(
observed_infected_param,
test_infected_value,
msg=
"Should be able to parse the pop_infected parameter from the results sheet"
)
results_df = simulation_df.parse('Results')
observed_day_0_exposed = results_df.loc[results_df['t'] == 0,
'n_exposed'].values[0]
self.assertGreaterEqual(
observed_day_0_exposed,
test_infected_value,
msg=
"Should be able to parse the day 0 n_exposed value from the results sheet."
)
if not self.is_debugging:
os.unlink(excel_filename)
def test_set_pars_invalid_key(self):
with self.assertRaises(KeyError) as context:
self.sim['n_infectey'] = 10
error_message = str(context.exception)
self.assertIn('n_infectey', error_message)
self.assertIn('pop_infected', error_message)
def test_update_pars_invalid_key(self):
invalid_key = {'dooty_doo': 5}
with self.assertRaises(KeyError) as context:
self.sim.update_pars(invalid_key)
error_message = str(context.exception)
self.assertIn('dooty_doo', error_message)
class MiscellaneousFeatureTests(CovaSimTest):
def setUp(self):
super().setUp()
self.sim = Sim()
self.pars = parameters.make_pars()
self.is_debugging = False
def test_xslx_generation(self):
super().tearDown()
self.sim.run()
self.sim.to_xlsx()
pass
def test_set_pars_invalid_key(self):
with self.assertRaises(KeyError) as context:
self.sim['n_infectey'] = 10
pass
error_message = str(context.exception)
self.assertIn('n_infectey', error_message)
self.assertIn('n_infected', error_message)
print("OH YEAH")
pass
def test_update_pars_invalid_key(self):
invalid_key = {'dooty_doo': 5}
with self.assertRaises(KeyError) as context:
self.sim.update_pars(invalid_key)
pass
error_message = str(context.exception)
self.assertIn('dooty_doo', error_message)
pass
def test_update_pars_invalid_type(self):
invalid_key = ('dooty_doo', 5)
with self.assertRaises(TypeError) as context:
self.sim.update_pars(invalid_key)
pass
error_message = str(context.exception)
self.assertIn('dict', error_message)
pass
class CovaSimTest(unittest.TestCase):
def setUp(self):
self.is_debugging = False
self.simulation_parameters = None
self.simulation_prognoses = None
self.sim = None
self.simulation_result = None
self.interventions = None
self.expected_result_filename = f"DEBUG_{self.id()}.json"
if os.path.isfile(self.expected_result_filename):
os.unlink(self.expected_result_filename)
pass
def tearDown(self):
if not self.is_debugging:
if os.path.isfile(self.expected_result_filename):
os.unlink(self.expected_result_filename)
pass
# region configuration methods
def set_simulation_parameters(self, params_dict=None):
"""
Overrides all of the default sim parameters
with the ones in the dictionary
Args:
params_dict: keys are param names, values are expected values to use
Returns:
None, sets self.simulation_params
"""
if not self.simulation_parameters:
self.simulation_parameters = parameters.make_pars(
set_prognoses=True, prog_by_age=True)
if params_dict:
self.simulation_parameters.update(params_dict)
pass
def set_simulation_prognosis_probability(self, params_dict):
"""
Allows for testing prognoses probability as absolute rather than relative.
NOTE: You can only call this once per test or you will overwrite your stuff.
"""
ProbKeys = TestProperties.ParameterKeys.ProgressionKeys.ProbabilityKeys
RelativeProbabilityKeys = ProbKeys.RelativeProbKeys
supported_probabilities = [
RelativeProbabilityKeys.inf_to_symptomatic_probability,
RelativeProbabilityKeys.sym_to_severe_probability,
RelativeProbabilityKeys.sev_to_critical_probability,
RelativeProbabilityKeys.crt_to_death_probability
]
if not self.simulation_parameters:
self.set_simulation_parameters()
pass
if not self.simulation_prognoses:
self.simulation_prognoses = parameters.get_prognoses(
self.simulation_parameters[ProbKeys.progression_by_age])
PrognosisKeys = ProbKeys.PrognosesListKeys
for k in params_dict:
prognosis_in_question = None
expected_prob = params_dict[k]
if k == RelativeProbabilityKeys.inf_to_symptomatic_probability:
prognosis_in_question = PrognosisKeys.symptomatic_probabilities
elif k == RelativeProbabilityKeys.sym_to_severe_probability:
prognosis_in_question = PrognosisKeys.severe_probabilities
elif k == RelativeProbabilityKeys.sev_to_critical_probability:
prognosis_in_question = PrognosisKeys.critical_probabilities
elif k == RelativeProbabilityKeys.crt_to_death_probability:
prognosis_in_question = PrognosisKeys.death_probs
else:
raise KeyError(
f"Key {k} not found in {supported_probabilities}.")
old_probs = self.simulation_prognoses[prognosis_in_question]
self.simulation_prognoses[prognosis_in_question] = np.array(
[expected_prob] * len(old_probs))
pass
pass
def set_duration_distribution_parameters(self, duration_in_question, par1,
par2):
if not self.simulation_parameters:
self.set_simulation_parameters()
pass
duration_node = self.simulation_parameters["dur"]
duration_node[duration_in_question] = {
"dist": "normal",
"par1": par1,
"par2": par2
}
params_dict = {"dur": duration_node}
self.set_simulation_parameters(params_dict=params_dict)
def run_sim(self,
params_dict=None,
write_results_json=False,
population_type=None):
if not self.simulation_parameters or params_dict: # If we need one, or have one here
self.set_simulation_parameters(params_dict=params_dict)
pass
self.simulation_parameters['interventions'] = self.interventions
self.sim = Sim(pars=self.simulation_parameters, datafile=None)
if not self.simulation_prognoses:
self.simulation_prognoses = parameters.get_prognoses(
self.simulation_parameters[
TestProperties.ParameterKeys.ProgressionKeys.
ProbabilityKeys.progression_by_age])
pass
self.sim['prognoses'] = self.simulation_prognoses
if population_type:
self.sim.update_pars(pop_type=population_type)
self.sim.run(verbose=0)
self.simulation_result = self.sim.to_json(tostring=False)
if write_results_json or self.is_debugging:
with open(self.expected_result_filename, 'w') as outfile:
json.dump(self.simulation_result,
outfile,
indent=4,
sort_keys=True)
pass
# endregion
# region simulation results support
def get_full_result_channel(self, channel):
result_data = self.simulation_result["results"][channel]
return result_data
def get_day_zero_channel_value(
self,
channel=TestProperties.ResultsDataKeys.susceptible_at_timestep):
"""
Args:
channel: timeseries channel to report ('n_susceptible')
Returns: day zero value for channel
"""
result_data = self.get_full_result_channel(channel=channel)
return result_data[0]
def get_day_final_channel_value(self, channel):
channel = self.get_full_result_channel(channel=channel)
return channel[-1]
# endregion
# region interventions support
def intervention_set_changebeta(self,
days_array,
multiplier_array,
layers=None):
self.interventions = change_beta(days=days_array,
changes=multiplier_array,
layers=layers)
pass
def intervention_set_test_prob(self,
symptomatic_prob=0,
asymptomatic_prob=0,
asymptomatic_quarantine_prob=0,
symp_quar_prob=0,
test_sensitivity=1.0,
loss_prob=0.0,
test_delay=1,
start_day=0):
self.interventions = test_prob(
symp_prob=symptomatic_prob,
asymp_prob=asymptomatic_prob,
asymp_quar_prob=asymptomatic_quarantine_prob,
symp_quar_prob=symp_quar_prob,
test_sensitivity=test_sensitivity,
loss_prob=loss_prob,
test_delay=test_delay,
start_day=start_day)
pass
def intervention_set_contact_tracing(self,
start_day,
trace_probabilities=None,
trace_times=None):
# see ../tests/test_interventions_testing.test_tracedelay
# trace_probs = {'h': 1, 's': 1, 'w': 1, 'c': 1}
# trace_time = {'h': 0, 's': 1, 'w': 1, 'c': 2}
# pars.quar_period = 60 # 60 days
if not trace_probabilities:
trace_probabilities = {'h': 1, 's': 1, 'w': 1, 'c': 1}
pass
if not trace_times:
trace_times = {'h': 1, 's': 1, 'w': 1, 'c': 1}
self.interventions = contact_tracing(trace_probs=trace_probabilities,
trace_time=trace_times,
start_day=start_day)
pass
def intervention_build_sequence(self, day_list, intervention_list):
my_sequence = sequence(days=day_list, interventions=intervention_list)
self.interventions = my_sequence
# endregion
# region specialized simulation methods
def set_microsim(self):
Simkeys = TestProperties.ParameterKeys.SimulationKeys
Micro = TestProperties.SpecializedSimulations.Microsim
microsim_parameters = {
Simkeys.number_agents: Micro.n,
Simkeys.initial_infected_count: Micro.pop_infected,
Simkeys.number_simulated_days: Micro.n_days
}
self.set_simulation_parameters(microsim_parameters)
pass
def set_everyone_infected(self, agent_count=1000):
Simkeys = TestProperties.ParameterKeys.SimulationKeys
everyone_infected = {
Simkeys.number_agents: agent_count,
Simkeys.initial_infected_count: agent_count
}
self.set_simulation_parameters(params_dict=everyone_infected)
pass
DurationKeys = TestProperties.ParameterKeys.ProgressionKeys.DurationKeys
def set_everyone_infectious_same_day(self,
num_agents,
days_to_infectious=1,
num_days=60):
"""
Args:
num_agents: number of agents to create and infect
days_to_infectious: days until all agents are infectious (1)
num_days: days to simulate (60)
"""
self.set_everyone_infected(agent_count=num_agents)
prob_dict = {
TestProperties.ParameterKeys.ProgressionKeys.ProbabilityKeys.RelativeProbKeys.inf_to_symptomatic_probability:
0
}
self.set_simulation_prognosis_probability(prob_dict)
test_config = {
TestProperties.ParameterKeys.SimulationKeys.number_simulated_days:
num_days
}
self.set_duration_distribution_parameters(
duration_in_question=DurationKeys.exposed_to_infectious,
par1=days_to_infectious,
par2=0)
self.set_simulation_parameters(params_dict=test_config)
pass
def set_everyone_symptomatic(self, num_agents, constant_delay: int = None):
"""
Cause all agents in the simulation to begin infected
And proceed to symptomatic (but not severe or death)
Args:
num_agents: Number of agents to begin with
"""
self.set_everyone_infectious_same_day(num_agents=num_agents,
days_to_infectious=0)
prob_dict = {
TestProperties.ParameterKeys.ProgressionKeys.ProbabilityKeys.RelativeProbKeys.inf_to_symptomatic_probability:
1.0,
TestProperties.ParameterKeys.ProgressionKeys.ProbabilityKeys.RelativeProbKeys.sym_to_severe_probability:
0
}
self.set_simulation_prognosis_probability(prob_dict)
if constant_delay is not None:
self.set_duration_distribution_parameters(
duration_in_question=DurationKeys.infectious_to_symptomatic,
par1=constant_delay,
par2=0)
pass
def set_everyone_is_going_to_die(self, num_agents):
"""
Cause all agents in the simulation to begin infected and die.
Args:
num_agents: Number of agents to simulate
"""
ProbKeys = TestProperties.ParameterKeys.ProgressionKeys.ProbabilityKeys.RelativeProbKeys
self.set_everyone_infectious_same_day(num_agents=num_agents)
prob_dict = {
ProbKeys.inf_to_symptomatic_probability: 1,
ProbKeys.sym_to_severe_probability: 1,
ProbKeys.sev_to_critical_probability: 1,
ProbKeys.crt_to_death_probability: 1
}
self.set_simulation_prognosis_probability(prob_dict)
pass
def set_everyone_severe(self, num_agents, constant_delay: int = None):
self.set_everyone_symptomatic(num_agents=num_agents,
constant_delay=constant_delay)
prob_dict = {
TestProperties.ParameterKeys.ProgressionKeys.ProbabilityKeys.RelativeProbKeys.sym_to_severe_probability:
1.0,
TestProperties.ParameterKeys.ProgressionKeys.ProbabilityKeys.RelativeProbKeys.sev_to_critical_probability:
0.0
}
self.set_simulation_prognosis_probability(prob_dict)
if constant_delay is not None:
self.set_duration_distribution_parameters(
duration_in_question=DurationKeys.symptomatic_to_severe,
par1=constant_delay,
par2=0)
pass
def set_everyone_critical(self, num_agents, constant_delay: int = None):
"""
Causes all agents to become critically ill day 1
"""
self.set_everyone_severe(num_agents=num_agents,
constant_delay=constant_delay)
prob_dict = {
TestProperties.ParameterKeys.ProgressionKeys.ProbabilityKeys.RelativeProbKeys.sev_to_critical_probability:
1.0,
TestProperties.ParameterKeys.ProgressionKeys.ProbabilityKeys.RelativeProbKeys.crt_to_death_probability:
0.0
}
self.set_simulation_prognosis_probability(prob_dict)
if constant_delay is not None:
self.set_duration_distribution_parameters(
duration_in_question=DurationKeys.severe_to_critical,
par1=constant_delay,
par2=0)
pass
def set_smallpop_hightransmission(self):
"""
Creates a small population with lots of transmission
"""
Simkeys = TestProperties.ParameterKeys.SimulationKeys
Transkeys = TestProperties.ParameterKeys.TransmissionKeys
Hightrans = TestProperties.SpecializedSimulations.Hightransmission
hightrans_parameters = {
Simkeys.number_agents: Hightrans.n,
Simkeys.initial_infected_count: Hightrans.pop_infected,
Simkeys.number_simulated_days: Hightrans.n_days,
Transkeys.beta: Hightrans.beta
}
self.set_simulation_parameters(hightrans_parameters)
pass
# endregion
pass
