def test_get_memory_usage():
simulation = SimulationBuilder().build_from_entities(
tax_benefit_system, single)
simulation.calculate('disposable_income', '2017-01')
memory_usage = simulation.get_memory_usage(variables=['salary'])
assert (memory_usage['total_nb_bytes'] > 0)
assert (len(memory_usage['by_variable']) == 1)
def test_get_memory_usage():
test_case = deepcopy(single)
test_case["persons"]["Alicia"]["salary"] = {"2017-01": 0}
simulation = SimulationBuilder().build_from_dict(tax_benefit_system, test_case)
simulation.calculate('disposable_income', '2017-01')
memory_usage = simulation.person.get_memory_usage(variables = ['salary'])
assert(memory_usage['total_nb_bytes'] > 0)
assert(len(memory_usage['by_variable']) == 1)
def test_get_memory_usage():
test_case = deepcopy(single)
test_case["persons"]["Alicia"]["salary"] = {"2017-01": 0}
simulation = SimulationBuilder().build_from_dict(tax_benefit_system,
test_case)
simulation.calculate('disposable_income', '2017-01')
memory_usage = simulation.person.get_memory_usage(variables=['salary'])
assert (memory_usage['total_nb_bytes'] > 0)
assert (len(memory_usage['by_variable']) == 1)
def test_dump():
directory = tempfile.mkdtemp(prefix = "openfisca_")
simulation = SimulationBuilder().build_from_entities(tax_benefit_system, couple)
calculated_value = simulation.calculate('disposable_income', '2018-01')
dump_simulation(simulation, directory)
simulation_2 = restore_simulation(directory, tax_benefit_system)
# Check entities structure have been restored
assert_array_equal(simulation.person.ids, simulation_2.person.ids)
assert_array_equal(simulation.person.count, simulation_2.person.count)
assert_array_equal(simulation.household.ids, simulation_2.household.ids)
assert_array_equal(simulation.household.count, simulation_2.household.count)
assert_array_equal(simulation.household.members_position, simulation_2.household.members_position)
assert_array_equal(simulation.household.members_entity_id, simulation_2.household.members_entity_id)
assert_array_equal(simulation.household.members_role, simulation_2.household.members_role)
# Check calculated values are in cache
disposable_income_holder = simulation_2.person.get_holder('disposable_income')
cached_value = disposable_income_holder.get_array('2018-01')
assert cached_value is not None
assert_array_equal(cached_value, calculated_value)
shutil.rmtree(directory)
def test_dump():
directory = tempfile.mkdtemp(prefix="openfisca_")
simulation = SimulationBuilder().build_from_entities(
tax_benefit_system, couple)
calculated_value = simulation.calculate('disposable_income', '2018-01')
dump_simulation(simulation, directory)
simulation_2 = restore_simulation(directory, tax_benefit_system)
# Check entities structure have been restored
assert_array_equal(simulation.person.ids, simulation_2.person.ids)
assert_array_equal(simulation.person.count, simulation_2.person.count)
assert_array_equal(simulation.household.ids, simulation_2.household.ids)
assert_array_equal(simulation.household.count,
simulation_2.household.count)
assert_array_equal(simulation.household.members_position,
simulation_2.household.members_position)
assert_array_equal(simulation.household.members_entity_id,
simulation_2.household.members_entity_id)
assert_array_equal(simulation.household.members_role,
simulation_2.household.members_role)
# Check calculated values are in cache
disposable_income_holder = simulation_2.person.get_holder(
'disposable_income')
cached_value = disposable_income_holder.get_array('2018-01')
assert cached_value is not None
assert_array_equal(cached_value, calculated_value)
shutil.rmtree(directory)
def calculate(tax_benefit_system, input_data):
simulation = SimulationBuilder().build_from_entities(
tax_benefit_system, input_data)
requested_computations = dpath.util.search(input_data,
'*/*/*/*',
afilter=lambda t: t is None,
yielded=True)
computation_results = {}
for computation in requested_computations:
path = computation[0]
entity_plural, entity_id, variable_name, period = path.split('/')
variable = tax_benefit_system.get_variable(variable_name)
result = simulation.calculate(variable_name, period)
population = simulation.get_population(entity_plural)
entity_index = population.get_index(entity_id)
if variable.value_type == Enum:
entity_result = result.decode()[entity_index].name
elif variable.value_type == float:
entity_result = float(
str(result[entity_index])
) # To turn the float32 into a regular float without adding confusing extra decimals. There must be a better way.
elif variable.value_type == str:
entity_result = str(result[entity_index])
else:
entity_result = result.tolist()[entity_index]
dpath.util.new(computation_results, path, entity_result)
dpath.merge(input_data, computation_results)
return input_data
def calculate(tax_benefit_system, input_data):
simulation = SimulationBuilder().build_from_entities(tax_benefit_system, input_data)
requested_computations = dpath.util.search(input_data, '*/*/*/*', afilter = lambda t: t is None, yielded = True)
computation_results = {}
for computation in requested_computations:
path = computation[0]
entity_plural, entity_id, variable_name, period = path.split('/')
variable = tax_benefit_system.get_variable(variable_name)
result = simulation.calculate(variable_name, period)
population = simulation.get_population(entity_plural)
entity_index = population.get_index(entity_id)
if variable.value_type == Enum:
entity_result = result.decode()[entity_index].name
elif variable.value_type == float:
entity_result = float(str(result[entity_index])) # To turn the float32 into a regular float without adding confusing extra decimals. There must be a better way.
elif variable.value_type == str:
entity_result = str(result[entity_index])
else:
entity_result = result.tolist()[entity_index]
dpath.util.new(computation_results, path, entity_result)
dpath.merge(input_data, computation_results)
return input_data
def test_calculate_with_trace():
simulation = SimulationBuilder().build_default_simulation(tax_benefit_system)
simulation.trace = True
simulation.calculate('income_tax', '2017-01')
salary_trace = simulation.tracer.trace['salary<2017-01>']
assert salary_trace['parameters'] == {}
income_tax_trace = simulation.tracer.trace['income_tax<2017-01>']
assert income_tax_trace['parameters']['taxes.income_tax_rate<2017-01-01>'] == 0.15
# Trace parameters called with indirect access
simulation.calculate('housing_tax', '2017')
housing_tax_trace = simulation.tracer.trace['housing_tax<2017>']
assert 'taxes.housing_tax<2017-01-01>' not in housing_tax_trace['parameters']
assert housing_tax_trace['parameters']['taxes.housing_tax.rate<2017-01-01>'] == 10
assert housing_tax_trace['parameters']['taxes.housing_tax.minimal_amount<2017-01-01>'] == 200
def trace(tax_benefit_system, input_data):
simulation = SimulationBuilder().build_from_entities(tax_benefit_system, input_data)
simulation.trace = True
requested_calculations = []
requested_computations = dpath.util.search(input_data, '*/*/*/*', afilter = lambda t: t is None, yielded = True)
for computation in requested_computations:
path = computation[0]
entity_plural, entity_id, variable_name, period = path.split('/')
requested_calculations.append(f"{variable_name}<{str(period)}>")
simulation.calculate(variable_name, period)
trace = simulation.tracer.get_serialized_flat_trace()
return {
"trace": trace,
"entitiesDescription": simulation.describe_entities(),
"requestedCalculations": requested_calculations
}
def test_calculate_full_tracer():
simulation = SimulationBuilder().build_default_simulation(
tax_benefit_system)
simulation.trace = True
simulation.calculate('income_tax', '2017-01')
income_tax_node = simulation.tracer.trees[0]
assert income_tax_node.name == 'income_tax'
assert str(income_tax_node.period) == '2017-01'
assert income_tax_node.value == 0
salary_node = income_tax_node.children[0]
assert salary_node.name == 'salary'
assert str(salary_node.period) == '2017-01'
assert salary_node.parameters == []
assert len(income_tax_node.parameters) == 1
assert income_tax_node.parameters[0].name == 'taxes.income_tax_rate'
assert income_tax_node.parameters[0].period == '2017-01-01'
assert income_tax_node.parameters[0].value == 0.15
def trace(tax_benefit_system, input_data):
simulation = SimulationBuilder().build_from_entities(tax_benefit_system, input_data, trace = True)
requested_computations = dpath.util.search(input_data, '*/*/*/*', afilter = lambda t: t is None, yielded = True)
for computation in requested_computations:
path = computation[0]
entity_plural, entity_id, variable_name, period = path.split('/')
simulation.calculate(variable_name, period)
trace = deepcopy(simulation.tracer.trace)
for vector_key, vector_trace in trace.items():
value = vector_trace['value'].tolist()
if isinstance(value[0], Enum):
value = [item.name for item in value]
if isinstance(value[0], bytes):
value = [to_unicode(item) for item in value]
vector_trace['value'] = value
return {
"trace": trace,
"entitiesDescription": {entity.plural: entity.ids for entity in simulation.entities.values()},
"requestedCalculations": list(simulation.tracer.requested_calculations)
}
def trace(tax_benefit_system, input_data):
simulation = SimulationBuilder().build_from_entities(tax_benefit_system, input_data)
simulation.trace = True
requested_computations = dpath.util.search(input_data, '*/*/*/*', afilter = lambda t: t is None, yielded = True)
for computation in requested_computations:
path = computation[0]
entity_plural, entity_id, variable_name, period = path.split('/')
simulation.calculate(variable_name, period)
trace = deepcopy(simulation.tracer.trace)
for _vector_key, vector_trace in trace.items():
value = vector_trace['value'].tolist()
if isinstance(vector_trace['value'], EnumArray):
value = [item.name for item in vector_trace['value'].decode()]
if isinstance(value[0], bytes):
value = [str(item) for item in value]
vector_trace['value'] = value
return {
"trace": trace,
"entitiesDescription": simulation.describe_entities(),
"requestedCalculations": list(simulation.tracer.requested_calculations)
}
def test_get_memory_usage():
simulation = SimulationBuilder().build_from_entities(tax_benefit_system, single)
simulation.calculate('disposable_income', '2017-01')
memory_usage = simulation.get_memory_usage(variables = ['salary'])
assert(memory_usage['total_nb_bytes'] > 0)
assert(len(memory_usage['by_variable']) == 1)