def setUp(self):
self.test_outflow_data = pd.DataFrame({
'compartment_duration': [1, 1, 2, 2.5, 10],
'total_population': [4, 2, 2, 4, 3],
'outflow_to': ['jail', 'prison', 'jail', 'prison', 'prison'],
'compartment': ['test'] * 5
})
self.historical_data = pd.DataFrame({
2015: {
'jail': 2,
'prison': 2
},
2016: {
'jail': 1,
'prison': 0
},
2017: {
'jail': 1,
'prison': 1
}
})
self.compartment_policies = []
self.test_transition_table = IncarceratedTransitions(
self.test_outflow_data)
self.test_transition_table.initialize_transition_table()
self.test_transition_table.initialize(self.compartment_policies)
def initialize(self):
"""Initialize the transition tables, and then the compartments, for the SubSimulation"""
# TODO(#4512): allow sparse data
if not self.microsim and not self.total_population_data.empty:
if self.user_inputs['start_time_step'] not in self.total_population_data.time_step.values:
raise ValueError(f"Start time must be included in population data input\n"
f"Expected: {self.user_inputs['start_time_step']}, "
f"Actual: {self.total_population_data.time_step.values}")
# Initialize a default transition class for each compartment to represent the no-policy scenario
transitions_per_compartment = {}
for compartment in self.simulation_architecture:
transition_type = self.simulation_architecture[compartment]
compartment_duration_data = self.transitions_data[self.transitions_data['compartment'] == compartment]
if compartment_duration_data.empty:
if transition_type is not None:
raise ValueError(f"Transition data missing for compartment {compartment}. Data is required for all "
"disaggregtion axes. Even the 'release' compartment needs transition data even if "
"it's just outflow to 'release'")
else:
if transition_type == 'incarcerated':
transition_class = IncarceratedTransitions(compartment_duration_data)
elif transition_type == 'released':
transition_class = ReleasedTransitions(compartment_duration_data)
else:
raise ValueError(f'unrecognized transition table type {transition_type}')
transition_class.initialize_transition_table()
transitions_per_compartment[compartment] = transition_class
# Create a transition object for each compartment and year with policies applied and store shell policies
shell_policies = dict()
for compartment in self.simulation_architecture:
# Select any policies that are applicable for this compartment
compartment_policies = SparkPolicy.get_compartment_policies(self.policy_list, compartment)
# add to the dict compartment -> transition class with policies applied
if compartment in transitions_per_compartment:
transitions_per_compartment[compartment].initialize(compartment_policies)
# add shell policies to dict that gets passed to initialization
else:
shell_policies[compartment] = compartment_policies
# Preprocess the historical data into separate pieces per compartment
historical_outflows = self._load_data()
# Initialize the compartment classes
self._initialize_compartments(historical_outflows, transitions_per_compartment, shell_policies)
class TestShellCompartment(unittest.TestCase):
"""Test the ShellCompartment class runs correctly"""
def setUp(self):
self.test_outflow_data = pd.DataFrame({
'compartment_duration': [1, 1, 2, 2.5, 10],
'total_population': [4, 2, 2, 4, 3],
'outflow_to': ['jail', 'prison', 'jail', 'prison', 'prison'],
'compartment': ['test'] * 5
})
self.historical_data = pd.DataFrame({
2015: {
'jail': 2,
'prison': 2
},
2016: {
'jail': 1,
'prison': 0
},
2017: {
'jail': 1,
'prison': 1
}
})
self.compartment_policies = []
self.test_transition_table = IncarceratedTransitions(
self.test_outflow_data)
self.test_transition_table.initialize_transition_table()
self.test_transition_table.initialize(self.compartment_policies)
def test_all_edges_fed_to(self):
"""ShellCompartments require edges to the compartments defined in the outflows_data"""
starting_ts = 2015
policy_ts = 2018
test_shell_compartment = ShellCompartment(self.test_outflow_data,
starting_ts=starting_ts,
policy_ts=policy_ts,
tag='test_shell',
constant_admissions=True,
policy_list=[])
test_full_compartment = FullCompartment(self.historical_data,
self.test_transition_table,
starting_ts=starting_ts,
policy_ts=policy_ts,
tag='test_compartment')
with self.assertRaises(ValueError):
test_shell_compartment.initialize_edges(
[test_shell_compartment, test_full_compartment])
class TestFullCompartment(unittest.TestCase):
"""Test the FullCompartment runs correctly"""
def setUp(self):
self.test_supervision_data = pd.DataFrame({
'compartment_duration': [1, 1, 2, 2.5, 10],
'total_population': [4, 2, 2, 4, 3],
'outflow_to': ['jail', 'prison', 'jail', 'prison', 'prison'],
'compartment': ['test'] * 5
})
self.test_incarceration_data = pd.DataFrame({
'compartment_duration': [1, 1, 2, 2.5, 10],
'total_population': [4, 2, 2, 4, 3],
'outflow_to': ['supervision', 'release', 'supervision', 'release', 'release'],
'compartment': ['test'] * 5
})
self.compartment_policies = []
self.incarceration_transition_table = IncarceratedTransitions(self.test_incarceration_data)
self.incarceration_transition_table.initialize_transition_table()
self.incarceration_transition_table.initialize(self.compartment_policies)
self.release_transition_table = ReleasedTransitions(self.test_supervision_data)
self.release_transition_table.initialize_transition_table()
self.release_transition_table.initialize(self.compartment_policies)
self.historical_data = pd.DataFrame({
2015: {'jail': 2, 'prison': 2},
2016: {'jail': 1, 'prison': 0},
2017: {'jail': 1, 'prison': 1}
})
def test_step_forward_fails_without_initialized_edges(self):
"""Tests that step_forward() needs the initialize_edges() to have been run"""
rel_compartment = FullCompartment(self.historical_data, self.release_transition_table, 2015, 2018, 'release')
with self.assertRaises(ValueError):
rel_compartment.step_forward()
def test_all_edges_fed_to(self):
"""Tests that all edges in self.edges are included in self.transition_tables"""
rel_compartment = FullCompartment(self.historical_data, self.release_transition_table, 2015, 2018, 'release')
test_compartment = FullCompartment(self.historical_data, self.incarceration_transition_table, 2015, 2018,
'test_compartment')
compartment_list = [rel_compartment, test_compartment]
for compartment in compartment_list:
compartment.initialize_edges(compartment_list)
for compartment in compartment_list:
compartment.step_forward()
def setUp(self):
self.test_incarceration_data = pd.DataFrame({
'compartment_duration': [1, 1, 2, 2.5, 10],
'total_population': [4, 2, 2, 4, 3],
'inflow_to': ['supervision', 'release', 'supervision', 'release', 'release']
})
self.compartment_policies = pd.DataFrame(columns=[
'compartment', 'sub_population', 'retroactive_policies', 'non_retroactive_policies'])
self.incarceration_transition_table = IncarceratedTransitions(['release'])
self.incarceration_transition_table.initialize_transition_table(self.test_incarceration_data)
self.incarceration_transition_table.initialize(self.compartment_policies)
self.historical_data = pd.DataFrame({
2015: {'jail': 2, 'prison': 2},
2016: {'jail': 1, 'prison': 0},
2017: {'jail': 1, 'prison': 1}
})
def test_transition_table_rejects_impossible_large_probabilities(self):
compartment_transitions = IncarceratedTransitions(self.test_data)
compartment_transitions.initialize_transition_table()
compartment_transitions.initialize(self.compartment_policies)