def clone(self, debug = False, trace = False):
"""
Copy the simulation just enough to be able to run the copy without modifying the original simulation
"""
new = empty_clone(self)
new_dict = new.__dict__
for key, value in self.__dict__.items():
if key not in ('debug', 'trace', 'tracer'):
new_dict[key] = value
new.persons = self.persons.clone(new)
setattr(new, new.persons.key, new.persons)
new.entities = {new.persons.key: new.persons}
for entity_class in self.tax_benefit_system.group_entities:
entity = self.entities[entity_class.key].clone(new)
new.entities[entity.key] = entity
setattr(new, entity_class.key, entity) # create shortcut simulation.household (for instance)
if debug:
new_dict['debug'] = True
if trace:
new_dict['trace'] = True
if debug or trace:
if self.debug or self.trace:
new_dict['tracer'] = self.tracer.clone()
else:
new_dict['tracer'] = Tracer()
return new
def check_tracing_params(accessor, param_key):
tracer = Tracer()
tracer.record_calculation_start('A', '2015-01')
tracingParams = TracingParameterNodeAtInstant(parameters('2015-01-01'),
tracer)
param = accessor(tracingParams)
assert_near(tracer.trace['A<2015-01>']['parameters'][param_key], param)
def test_variable_stats():
tracer = Tracer()
tracer.record_calculation_start("A", 2017)
tracer.record_calculation_start("B", 2017)
tracer.record_calculation_start("B", 2017)
tracer.record_calculation_start("B", 2016)
assert_equals(tracer.usage_stats['B']['nb_requests'], 3)
assert_equals(tracer.usage_stats['A']['nb_requests'], 1)
assert_equals(tracer.usage_stats['C']['nb_requests'], 0)
def test_log_format():
tracer = Tracer()
tracer.record_calculation_start("A", 2017)
tracer.record_calculation_start("B", 2017)
tracer.record_calculation_end("B", 2017, 1)
tracer.record_calculation_end("A", 2017, 2)
lines = tracer.computation_log()
assert_equals(lines[0], ' A<2017> >> 2')
assert_equals(lines[1], ' B<2017> >> 1')
def __init__(
self,
tax_benefit_system,
simulation_json=None,
debug=False,
period=None,
trace=False,
opt_out_cache=False,
memory_config=None,
):
"""
Create an empty simulation
To fill the simulation with input data, you can use the :any:`SimulationBuilder` or proceed manually.
"""
self.tax_benefit_system = tax_benefit_system
assert tax_benefit_system is not None
if period:
assert isinstance(period, periods.Period)
self.period = period
# To keep track of the values (formulas and periods) being calculated to detect circular definitions.
# See use in formulas.py.
# The data structure of requested_periods_by_variable_name is: {variable_name: [period1, period2]}
self.requested_periods_by_variable_name = {}
self.max_nb_cycles = None
self.debug = debug
self.trace = trace or self.debug
if self.trace:
self.tracer = Tracer()
else:
self.tracer = None
self.opt_out_cache = opt_out_cache
self.memory_config = memory_config
self._data_storage_dir = None
self.instantiate_entities()
if simulation_json is not None:
warnings.warn(
' '.join([
"The 'simulation_json' argument of the Simulation is deprecated since version 25.0, and will be removed in the future.",
"The proper way to init a simulation from a JSON-like dict is to use SimulationBuilder.build_from_entities. See <https://openfisca.org/doc/openfisca-python-api/simulation_builder.html#openfisca_core.simulation_builder.SimulationBuilder.build_from_dict>"
]), Warning)
from openfisca_core.simulation_builder import SimulationBuilder
SimulationBuilder().build_from_entities(tax_benefit_system,
simulation_json,
simulation=self)
def __init__(
self,
tax_benefit_system,
simulation_json = None,
debug = False,
period = None,
trace = False,
opt_out_cache = False,
memory_config = None,
):
"""
If a ``simulation_json`` is given, initialises a simulation from a JSON dictionary.
Note: This way of initialising a simulation, still under experimentation, aims at replacing the initialisation from `scenario.make_json_or_python_to_attributes`.
If no ``simulation_json`` is given, initialises an empty simulation.
"""
self.tax_benefit_system = tax_benefit_system
assert tax_benefit_system is not None
if period:
assert isinstance(period, periods.Period)
self.period = period
# To keep track of the values (formulas and periods) being calculated to detect circular definitions.
# See use in formulas.py.
# The data structure of requested_periods_by_variable_name is: {variable_name: [period1, period2]}
self.requested_periods_by_variable_name = {}
self.max_nb_cycles = None
self.debug = debug
self.trace = trace or self.debug
if self.trace:
self.tracer = Tracer()
else:
self.tracer = None
self.opt_out_cache = opt_out_cache
self.memory_config = memory_config
self._data_storage_dir = None
self.instantiate_entities(simulation_json)
def test_consistency():
tracer = Tracer()
tracer.record_calculation_start("rsa", 2017)
tracer.record_calculation_end("unkwonn", 2017, 100)
# -*- coding: utf-8 -*-
from nose.tools import raises
from openfisca_core.tracers import Tracer
tracer = Tracer()
@raises(ValueError)
def test_consistency():
tracer.record_calculation_start("rsa", "2016-01")
tracer.record_calculation_end("unkwonn", "2016-01", 100)