def test_check():
for employee_type, test_parameters in test_case_by_employee_type.iteritems():
period = test_parameters.get("period", default_period)
parent1 = dict(
birth = datetime.date(periods.period(period).start.year - 40, 1, 1),
)
parent1.update(test_parameters['input_variables'])
simulation = tax_benefit_system.new_scenario().init_single_entity(
period = period,
parent1 = parent1,
).new_simulation(debug = True)
for variable, amounts in test_parameters['output_variables'].iteritems():
if isinstance(amounts, dict):
for period_str, amount in amounts.iteritems():
output = simulation.calculate(variable, period = periods.period(period_str))
variable_message = "{} at {}".format(variable, period_str)
yield assert_variable, variable_message, employee_type, amount, output
else:
output = simulation.calculate(variable)
variable_message = variable
amount = amounts
yield assert_variable, variable_message, employee_type, amount, output
def test_decomposition(print_decomposition=False):
simulation = tax_benefit_system.new_scenario().init_single_entity(
period="2013-01",
parent1=dict(
effectif_entreprise=3000,
exposition_accident=3,
code_postal_entreprise="75001",
ratio_alternants=.025,
salaire_de_base={"2013": 12 * 3000},
taille_entreprise=3,
categorie_salarie=0,
),
menage=dict(zone_apl=1, ),
).new_simulation()
xml_file_path = os.path.join(tax_benefit_system.DECOMP_DIR,
"fiche_de_paie_decomposition.xml")
decomposition_json = decompositions.get_decomposition_json(
tax_benefit_system, xml_file_path=xml_file_path)
simulations = [simulation]
response = decompositions.calculate(simulations, decomposition_json)
if print_decomposition:
print unicode(
json.dumps(response,
encoding='utf-8',
ensure_ascii=False,
indent=2))
def check_sal(type_sal, year = 2014):
period = periods.period("{}-01".format(year))
single_entity_kwargs = dict(
axes = [dict(count = 101, max = 2000, min = 40, name = 'salaire_de_base')], # TODO: min = 0
period = period,
parent1 = dict(
birth = datetime.date(year - 40, 1, 1),
type_sal = type_sal,
),
)
simulation = tax_benefit_system.new_scenario().init_single_entity(
**single_entity_kwargs
).new_simulation(debug = False)
brut = simulation.get_holder('salaire_de_base').array
smic_horaire = simulation.legislation_at(period.start).cotsoc.gen.smic_h_b
smic_mensuel = smic_horaire * 35 * 52 / 12
brut = simulation.get_holder('salaire_de_base').array
simulation.get_or_new_holder('contrat_de_travail').array = brut < smic_mensuel # temps plein ou temps partiel
simulation.get_or_new_holder('heures_remunerees_volume').array = brut // smic_horaire # temps plein ou partiel
imposable = simulation.calculate('salaire_imposable')
inversion_reform = inversion_revenus.build_reform(tax_benefit_system)
inverse_simulation = inversion_reform.new_scenario().init_single_entity(
**single_entity_kwargs).new_simulation(debug = True)
inverse_simulation.get_holder('salaire_de_base').delete_arrays()
inverse_simulation.get_or_new_holder('salaire_imposable_pour_inversion').array = imposable.copy()
inverse_simulation.get_or_new_holder('contrat_de_travail').array = brut < smic_mensuel # temps plein ou partiel
inverse_simulation.get_or_new_holder('heures_remunerees_volume').array = (
(brut // smic_horaire) * (brut < smic_mensuel)
)
new_brut = inverse_simulation.calculate('salaire_de_base')
assert_near(new_brut, brut, absolute_error_margin = 1)
def test_decomposition(print_decomposition=False):
from openfisca_core.decompositions import calculate, get_decomposition_json
import json
import os
simulation = tax_benefit_system.new_scenario().init_single_entity(
period="2013-01",
parent1=dict(
effectif_entreprise=3000,
exposition_accident=3,
localisation_entreprise="75001",
ratio_alternants=.025,
salaire_de_base={"2013": 12 * 3000},
taille_entreprise=3,
type_sal=0,
),
menage=dict(zone_apl=1, ),
).new_simulation(debug=True)
xml_file_path = os.path.join(tax_benefit_system.DECOMP_DIR,
"fiche_de_paie_decomposition.xml")
decomposition_json = get_decomposition_json(xml_file_path,
tax_benefit_system)
response = calculate(simulation, decomposition_json)
if print_decomposition:
print unicode(
json.dumps(response,
encoding='utf-8',
ensure_ascii=False,
indent=2))
def test_check():
for employee_type, test_parameters in test_case_by_employee_type.iteritems(
):
period = test_parameters.get("period", default_period)
parent1 = dict(birth=datetime.date(
periods.period(period).start.year - 40, 1, 1), )
parent1.update(test_parameters['input_variables'])
simulation = tax_benefit_system.new_scenario().init_single_entity(
period=period,
parent1=parent1,
).new_simulation(debug=True)
for variable, amounts in test_parameters['output_variables'].iteritems(
):
if isinstance(amounts, dict):
for period_str, amount in amounts.iteritems():
output = simulation.calculate(
variable, period=periods.period(period_str))
variable_message = "{} at {}".format(variable, period_str)
yield assert_variable, variable_message, employee_type, amount, output
else:
output = simulation.calculate(variable)
variable_message = variable
amount = amounts
yield assert_variable, variable_message, employee_type, amount, output
def net_plot(revenu, count = 11, max_revenu = 5000, min_revenu = 0):
year = 2014
period = periods.period("{}-01".format(year))
if revenu == 'chomage':
brut_name = 'chobrut'
net_name = 'chonet'
elif revenu == 'retraite':
brut_name = 'rstbrut'
net_name = 'rstnet'
elif revenu == 'salaire':
brut_name = 'salaire_de_base'
net_name = 'salaire_net'
else:
return
single_entity_kwargs = dict(
axes = [[
dict(count = count, max = max_revenu, min = min_revenu, name = brut_name)
]],
period = period,
parent1 = dict(
birth = datetime.date(year - 40, 1, 1),
),
)
simulation = tax_benefit_system.new_scenario().init_single_entity(
**single_entity_kwargs).new_simulation(debug = True)
smic_horaire = simulation.legislation_at(period.start).cotsoc.gen.smic_h_b
smic_mensuel = smic_horaire * 35 * 52 / 12
brut = simulation.get_holder(brut_name).array
simulation.get_or_new_holder('contrat_de_travail').array = brut < smic_mensuel # temps plein ou temps partiel
simulation.get_or_new_holder('heures_remunerees_volume').array = brut // smic_horaire # temps plein ou temps partiel
net = simulation.calculate(net_name)
inversion_reform = inversion_revenus.build_reform(tax_benefit_system)
inverse_simulation = inversion_reform.new_scenario().init_single_entity(
**single_entity_kwargs).new_simulation(debug = True)
inverse_simulation.get_holder(brut_name).delete_arrays()
inverse_simulation.get_or_new_holder(net_name).array = net.copy()
inverse_simulation.get_or_new_holder('contrat_de_travail').array = brut < smic_mensuel # temps plein ou temps partiel
inverse_simulation.get_or_new_holder('heures_remunerees_volume').array = (
(brut // smic_horaire) * (brut < smic_mensuel)
)
print inverse_simulation.get_or_new_holder('contrat_de_travail').array
print inverse_simulation.get_or_new_holder('heures_remunerees_volume').array
new_brut = inverse_simulation.calculate(brut_name)
pyplot.subplot(2, 1, 1)
pyplot.plot(brut, net, 'ro', label = "direct")
pyplot.plot(new_brut, net, 'db', label = "inversed")
pyplot.legend()
pyplot.subplot(2, 1, 2)
pyplot.plot(brut, new_brut - brut, 'r-')
pyplot.show()
assert_near(new_brut, brut, absolute_error_margin = 1)
def test_cho(year = 2014):
simulation = tax_benefit_system.new_scenario().init_single_entity(
axes = [dict(count = 11, max = 24000, min = 0, name = 'chobrut')],
period = year,
parent1 = dict(
birth = datetime.date(year - 40, 1, 1),
),
).new_simulation(debug = True)
brut = simulation.get_holder('chobrut').array
imposable = simulation.calculate('cho')
inversion_reform = inversion_revenus.build_reform(tax_benefit_system)
inverse_simulation = inversion_reform.new_scenario().init_single_entity(
axes = [dict(count = 11, max = 24000, min = 0, name = 'chobrut')],
period = year,
parent1 = dict(
birth = datetime.date(year - 40, 1, 1),
),
).new_simulation(debug = True)
inverse_simulation.get_holder('chobrut').delete_arrays()
inverse_simulation.get_or_new_holder('choi').array = imposable.copy()
new_brut = inverse_simulation.calculate('chobrut')
assert_near(new_brut, brut, error_margin = 1)
def test_decomposition(print_decomposition = False):
simulation = tax_benefit_system.new_scenario().init_single_entity(
period = "2013-01",
parent1 = dict(
effectif_entreprise = 3000,
exposition_accident = 3,
code_postal_entreprise = "75001",
ratio_alternants = .025,
salaire_de_base = {"2013": 12 * 3000},
taille_entreprise = 3,
type_sal = 0,
),
menage = dict(
zone_apl = 1,
),
).new_simulation(debug = True)
xml_file_path = os.path.join(
tax_benefit_system.DECOMP_DIR,
"fiche_de_paie_decomposition.xml"
)
decomposition_json = decompositions.get_decomposition_json(tax_benefit_system, xml_file_path = xml_file_path)
simulations = [simulation]
response = decompositions.calculate(simulations, decomposition_json)
if print_decomposition:
print unicode(
json.dumps(response, encoding = 'utf-8', ensure_ascii = False, indent = 2)
)
def make_couple_with_child_scenario(nombre_enfants=0,
year=None,
tax_benefit_system=tax_benefit_system,
axes_variable='salaire_de_base',
ax_variable_max=300000,
count=5000):
enfant = [dict(birth=date(2005, 1, 1), )]
enfants = enfant * nombre_enfants
scenario = tax_benefit_system.new_scenario().init_single_entity(
axes=[[
dict(
count=count,
min=0,
max=ax_variable_max,
name=axes_variable,
period=year - 2,
),
dict(
count=count,
min=0,
max=ax_variable_max,
name=axes_variable,
period=year - 1,
),
dict(
count=count,
min=0,
max=ax_variable_max,
name=axes_variable,
period=year,
),
]],
period=year,
parent1=dict(
birth=date(1980, 1, 1),
statmarit=5, #pacsés
ppe_du_sa=1610,
),
parent2=dict(
birth=date(1980, 1, 1),
statmarit=5,
),
enfants=enfants,
menage=dict(
loyer=1000,
statut_occupation=4,
),
)
return scenario
def test_check():
for test_parameters in iter_scenarios():
test_name = test_parameters["name"]
period = test_parameters["period"]
parent1 = dict(
birth = datetime.date(periods.period(period).start.year - 40, 1, 1),
)
parent1.update(test_parameters['input_variables'])
simulation = tax_benefit_system.new_scenario().init_single_entity(
period = period,
parent1 = parent1,
).new_simulation(debug = True)
for variable_name, expected_value in test_parameters['output_variables'].iteritems():
yield check_variable, simulation, variable_name, test_name, expected_value
def simple_check(tests):
for test_parameters in tests:
name = test_parameters["name"]
period = test_parameters["period"]
parent1 = dict(
birth = datetime.date(periods.period(period).start.year - 40, 1, 1),
)
parent1.update(test_parameters['input_variables'])
simulation = tax_benefit_system.new_scenario().init_single_entity(
period = period,
parent1 = parent1,
).new_simulation(debug = True)
for variable, monthly_amount in test_parameters['output_variables'].iteritems():
check_variable(simulation, variable, name, monthly_amount)
def test_rst(year=2014):
simulation = tax_benefit_system.new_scenario().init_single_entity(
axes=[dict(count=11, max=24000, min=0, name='rstbrut')],
period=year,
parent1=dict(birth=datetime.date(year - 40, 1, 1), ),
).new_simulation(debug=True)
brut = simulation.get_holder('rstbrut').array
imposable = simulation.calculate('rst')
inverse_simulation = simulation.clone(debug=True)
inverse_simulation.get_holder('rstbrut').delete_arrays()
inverse_simulation.get_or_new_holder('rsti').array = imposable.copy()
new_brut = inverse_simulation.calculate('rstbrut')
assert_near(new_brut, brut, error_margin=1)
def test_check():
for test_parameters in iter_scenarios():
test_name = test_parameters["name"]
period = test_parameters["period"]
parent1 = dict(birth=datetime.date(
periods.period(period).start.year - 40, 1, 1), )
parent1.update(test_parameters['input_variables'])
simulation = tax_benefit_system.new_scenario().init_single_entity(
period=period,
parent1=parent1,
).new_simulation(debug=True)
for variable_name, expected_value in test_parameters[
'output_variables'].iteritems():
yield check_variable, simulation, variable_name, test_name, expected_value
def simple_check(tests):
for test_parameters in tests:
name = test_parameters["name"]
period = test_parameters["period"]
parent1 = dict(birth=datetime.date(
periods.period(period).start.year - 40, 1, 1), )
parent1.update(test_parameters['input_variables'])
simulation = tax_benefit_system.new_scenario().init_single_entity(
period=period,
parent1=parent1,
).new_simulation(debug=True)
for variable, monthly_amount in test_parameters[
'output_variables'].iteritems():
check_variable(simulation, variable, name, monthly_amount)
def test_1():
simulation = tax_benefit_system.new_scenario().init_single_entity(
period="2013",
parent1=dict(
effectif_entreprise=3000,
exposition_accident=3,
localisation_entreprise="75001",
ratio_alternants=.025,
salaire_de_base={"2011:3": 12 * 3000},
taille_entreprise=3,
type_sal=0,
),
menage=dict(zone_apl=1, ),
).new_simulation(debug=True)
simulation.calculate("revdisp")
def brut_plot(revenu, count = 11, max_revenu = 5000, min_revenu = 0):
year = 2014
period = periods.period("{}-01".format(year))
if revenu == 'chomage':
brut_name = 'chobrut'
imposable_name = 'cho'
inversible_name = 'choi'
elif revenu == 'retraite':
brut_name = 'rstbrut'
imposable_name = 'rst'
inversible_name = 'rsti'
elif revenu == 'salaire':
brut_name = 'salaire_de_base'
imposable_name = 'sal'
inversible_name = 'sali'
else:
return
single_entity_kwargs = dict(
axes = [dict(count = count, max = max_revenu, min = min_revenu, name = brut_name)],
period = period,
parent1 = dict(
birth = datetime.date(year - 40, 1, 1),
),
)
simulation = tax_benefit_system.new_scenario().init_single_entity(
**single_entity_kwargs).new_simulation(debug = True)
brut = simulation.get_holder(brut_name).array
imposable = simulation.calculate(imposable_name)
inversion_reform = inversion_revenus.build_reform(tax_benefit_system)
inverse_simulation = inversion_reform.new_scenario().init_single_entity(
**single_entity_kwargs).new_simulation(debug = True)
inverse_simulation.get_holder(brut_name).delete_arrays()
inverse_simulation.get_or_new_holder(inversible_name).array = imposable.copy()
new_brut = inverse_simulation.calculate(brut_name)
pyplot.subplot(2, 1, 1)
pyplot.plot(brut, imposable, 'ro', label = "direct")
pyplot.plot(new_brut, imposable, 'db', label = "inversed")
pyplot.legend()
pyplot.subplot(2, 1, 2)
pyplot.plot(brut, new_brut - brut, 'r-')
pyplot.show()
assert_near(new_brut, brut, absolute_error_margin = 1)
def make_couple_with_child_scenario(nombre_enfants = 0, year = None, tax_benefit_system = tax_benefit_system,
axes_variable = 'salaire_de_base', ax_variable_max = 300000, count = 5000):
enfant = [dict(
birth = date(2005, 1, 1),
)]
enfants = enfant * nombre_enfants
scenario = tax_benefit_system.new_scenario().init_single_entity(
axes = [[
dict(
count = count,
min = 0,
max = ax_variable_max,
name = axes_variable,
period = year-2,
),
dict(
count = count,
min = 0,
max = ax_variable_max,
name = axes_variable,
period = year-1,
),
dict(
count = count,
min = 0,
max = ax_variable_max,
name = axes_variable,
period = year,
),
]],
period = year,
parent1 = dict(
birth = date(1980, 1, 1),
statmarit = 5, #pacsés
ppe_du_sa = 1610,
),
parent2 = dict(
birth = date(1980, 1, 1),
statmarit = 5,
),
enfants = enfants,
menage = dict(
loyer = 1000,
statut_occupation = 4,
),
)
return scenario
def test_1():
simulation = tax_benefit_system.new_scenario().init_single_entity(
period = "2013-12",
parent1 = dict(
effectif_entreprise = 3000,
exposition_accident = 3,
localisation_entreprise = "75001",
ratio_alternants = .025,
salaire_de_base = {"2013-01:12": 12 * 3000},
taille_entreprise = 3,
type_sal = 1,
),
menage = dict(
zone_apl = 1,
),
).new_simulation(debug = True)
simulation.calculate("agff_tranche_a_employe", period = "2013-12")
def test_check():
for test_parameters in tests:
name = test_parameters["name"]
period = test_parameters["period"]
parent1 = dict(birth=datetime.date(
periods.period(period).start.year - 40, 1, 1), )
foyer_fiscal = dict()
foyer_fiscal.update(test_parameters['input_variables'])
simulation = tax_benefit_system.new_scenario().init_single_entity(
period=period,
parent1=parent1,
foyer_fiscal=foyer_fiscal,
).new_simulation(debug=True)
for variable, monthly_amount in test_parameters[
'output_variables'].iteritems():
output = simulation.calculate(variable)
yield assert_variable, variable, name, monthly_amount, output
def check_sal(type_sal, year = 2014):
simulation = tax_benefit_system.new_scenario().init_single_entity(
axes = [dict(count = 11, max = 24000, min = 0, name = 'salbrut')],
period = year,
parent1 = dict(
birth = datetime.date(year - 40, 1, 1),
type_sal = type_sal,
),
).new_simulation(debug = False)
brut = simulation.get_holder('salbrut').array
imposable = simulation.calculate('sal')
inverse_simulation = simulation.clone(debug = True)
inverse_simulation.get_holder('salbrut').delete_arrays()
inverse_simulation.get_or_new_holder('sali').array = imposable.copy()
new_brut = inverse_simulation.calculate('salbrut')
assert_near(new_brut, brut, error_margin = 1)
def test_check():
for test_parameters in tests:
name = test_parameters["name"]
period = test_parameters["period"]
parent1 = dict(
birth = datetime.date(periods.period(period).start.year - 40, 1, 1),
)
foyer_fiscal = dict()
foyer_fiscal.update(test_parameters['input_variables'])
simulation = tax_benefit_system.new_scenario().init_single_entity(
period = period,
parent1 = parent1,
foyer_fiscal = foyer_fiscal,
).new_simulation(debug = True)
for variable, monthly_amount in test_parameters['output_variables'].iteritems():
output = simulation.calculate_add(variable)
yield assert_variable, variable, name, monthly_amount, output
def simple_check(tests):
for test_parameters in tests:
name = test_parameters["name"]
period = test_parameters["period"]
parent1 = dict(
birth = datetime.date(periods.period(period).start.year - 40, 1, 1),
)
parent1.update(test_parameters['input_variables'])
simulation = tax_benefit_system.new_scenario().init_single_entity(
period = period,
parent1 = parent1,
).new_simulation(debug = True)
for variable_name, expected_value in test_parameters['output_variables'].iteritems():
if isinstance(expected_value, dict):
for item_period, item_value in expected_value.iteritems():
check_variable(simulation, variable_name, test_name, item_period, item_value)
else:
check_variable(simulation, variable_name, test_name, period, expected_value)
def test_rst(year = 2014):
period = periods.period("{}-01".format(year))
single_entity_kwargs = dict(
axes = [dict(count = 101, max = 2000, min = 0, name = 'rstbrut')],
period = period,
parent1 = dict(
birth = datetime.date(year - 40, 1, 1),
),
)
simulation = tax_benefit_system.new_scenario().init_single_entity(
**single_entity_kwargs
).new_simulation(debug = True)
brut = simulation.get_holder('rstbrut').array
imposable = simulation.calculate('rst')
inversion_reform = inversion_revenus.build_reform(tax_benefit_system)
inverse_simulation = inversion_reform.new_scenario().init_single_entity(
**single_entity_kwargs).new_simulation(debug = True)
inverse_simulation.get_holder('rstbrut').delete_arrays()
inverse_simulation.get_or_new_holder('rsti').array = imposable.copy()
new_brut = inverse_simulation.calculate('rstbrut')
assert_near(new_brut, brut, absolute_error_margin = 1)
if json_dumped_file:
with io.open(json_dumped_file, 'w', encoding='utf-8') as f:
f.write(
unicode(
json.dumps(scenario_json,
ensure_ascii=False,
encoding='utf-8',
indent=2)))
if __name__ == '__main__':
from openfisca_france.tests.base import tax_benefit_system
period = "2014-12"
parent1 = dict(
date_naissance=datetime.date(
periods.period(period).start.year - 40, 1, 1),
salbrut={"2014-12": 1445.38},
)
scenario = tax_benefit_system.new_scenario().init_single_entity(
period=period,
parent1=parent1,
)
variables = ["salaire_super_brut"]
trace(
scenario,
variables,
api_url=u"http://127.0.0.1:2000",
json_dumped_file="test_smicard.json",
)
url = trace_base_url + "?" + urllib.urlencode({
"simulation": json.dumps(simulation_json),
"api_url": api_url,
})
browser = webbrowser.get(browser_name)
browser.open_new_tab(url)
if json_dumped_file:
with io.open(json_dumped_file, 'w', encoding='utf-8') as f:
f.write(unicode(json.dumps(scenario_json, ensure_ascii=False, encoding='utf-8', indent = 2)))
if __name__ == '__main__':
from openfisca_france.tests.base import tax_benefit_system
period = "2014-12"
parent1 = dict(
birth = datetime.date(periods.period(period).start.year - 40, 1, 1),
salbrut = {"2014-12": 1445.38},
)
scenario = tax_benefit_system.new_scenario().init_single_entity(
period = period,
parent1 = parent1,
)
variables = ["salaire_super_brut"]
trace(
scenario,
variables,
api_url = u"http://127.0.0.1:2000",
json_dumped_file = "test_smicard.json",
)
