def get_brut_from_net(net,
type_sal=0,
hsup=0,
csg_rempl=0,
rev='sal',
year=2011):
from openfisca_core.simulations import ScenarioSimulation
import openfisca_france
openfisca_france.init_country()
simulation = ScenarioSimulation()
simulation.set_config(year=2011, nmen=2, x_axis="sali", maxrev=100)
simulation.set_param()
simulation.compute()
net = [net]
_defaultP = simulation.P
if rev == 'sal':
output = _salbrut_from_salnet(net, hsup, type_sal, _defaultP)
elif rev == 'cho':
output = _chobrut_from_chonet(net, csg_rempl, _defaultP)
elif rev == 'rst':
output = _rstbrut_from_rstnet(net, csg_rempl, _defaultP)
return output
def run_OF(ipp2of_input_variables, path_dta_input, param_scenario = None, dic = None, datesim = None, option = 'test_dta'):
'''
Lance le calculs sur OF à partir des cas-types issues de TaxIPP
input : base .dta issue de l'étape précédente
'''
def _test_of_dta(dta_input, dic):
''' Cette fonction teste que la table .dta trouvée
correspond au bon scénario '''
data = read_stata(dta_input)
dic_dta = data.loc[0, 'dic_scenar']
if str(dic) != str(dic_dta) :
print "La base .dta permettant de lancer la simulation OF est absente "
print "La base s'en rapprochant le plus a été construite avec les paramètres : ", dic_dta
pdb.set_trace()
else :
data = data.drop('dic_scenar', 1).sort(['id_foyf', 'id_indiv'], ascending = [True, False])
return data
def _scenar_dta(dta_input) :
''' cette fonction identifie le scenario enregistré dans la table d'input '''
data = read_stata(dta_input)
dic_dta = data.loc[0, 'dic_scenar']
data = data.drop('dic_scenar', 1).sort(['id_foyf', 'id_indiv'], ascending = [True, False])
return dic_dta, data
if option == 'test_dta':
data_IPP = _test_of_dta(path_dta_input, dic)
if option == 'list_dta':
dic_scenar, data_IPP = _scenar_dta(path_dta_input)
dict_scenar = dict()
expression = "dict_scenar.update(" + dic_scenar + ")"
eval(expression)
datesim = dict_scenar['datesim']
param_scenario = dict_scenar
if 'option' in param_scenario.keys() and param_scenario['option'] == 'brut':
TaxBenefitSystem = openfisca_france.init_country(start_from = "brut")
tax_benefit_system = TaxBenefitSystem()
del ipp2of_input_variables['sal_irpp_old']
ipp2of_input_variables['sal_brut'] = 'salbrut'
ipp2of_input_variables['chom_brut'] = 'chobrut'
ipp2of_input_variables['pension_brut'] = 'rstbrut'
else :
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
openfisca_survey = build_input_OF(data_IPP, ipp2of_input_variables, tax_benefit_system)
openfisca_survey = openfisca_survey.fillna(0) # .sort(['idfoy','noi'])
# print datesim
simulation = surveys.new_simulation_from_survey_data_frame(
# debug = True,
survey = openfisca_survey,
tax_benefit_system = tax_benefit_system,
year = datesim,
)
if option == 'list_dta':
return simulation, param_scenario
else:
return simulation
def simulation_from_test(test, verbose = False, monthly_amount = False, default_error_margin = 1, forced_error_margin = None):
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
year = test["year"]
parent1 = dict(birth = datetime.date(year - 40, 1, 1))
menage = dict()
foyer_fiscal = dict()
for variable, value in test['input_vars'].iteritems():
if variable == "age":
parent1['birth'] = datetime.date(year - value, 1, 1)
elif tax_benefit_system.column_by_name[variable].entity == 'men':
menage[variable] = value
elif tax_benefit_system.column_by_name[variable].entity == 'ind':
parent1[variable] = value
#TODO: if the person is a child
elif tax_benefit_system.column_by_name[variable].entity == 'foy':
foyer_fiscal[variable] = value
simulation = tax_benefit_system.new_scenario().init_single_entity(
parent1 = parent1,
menage = menage,
foyer_fiscal = foyer_fiscal,
year = year,
).new_simulation(debug = True)
return simulation
def test_survey_simulation():
year = 2006
input_data_frame = get_input_data_frame(year)
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system_class = TaxBenefitSystem
survey_scenario = SurveyScenario().init_from_data_frame(
input_data_frame = input_data_frame,
tax_benefit_system_class = tax_benefit_system_class,
year = year,
)
simulation = survey_scenario.new_simulation()
try:
from pandas import DataFrame
revdisp = DataFrame({"revdisp": simulation.calculate('revdisp')})
except NaNCreationError as error:
index = error.index
entity = error.entity
column_name = error.column_name
input_data_frame_debug = filter_input_data_frame(
simulation.input_data_frame,
entity,
index[:10],
)
survey_scenario_debug = SurveyScenario()
simulation_debug = survey_scenario_debug.new_simulation(
debug = True,
input_data_frame = input_data_frame_debug,
tax_benefit_system_class = tax_benefit_system_class,
year = year,
)
simulation_debug.calculate(column_name)
print revdisp.info()
print 'finished'
def test_check_rsa():
'''test rsa pour un célibataire avec différent sali'''
tests_list = [
{"year": 2014, "amount": 0, "rsa": 439},
{"year": 2014, "amount": 5000, "rsa": 281},
{"year": 2014, "amount": 10000, "rsa": 123},
{"year": 2014, "amount": 12000, "rsa": 59},
{"year": 2014, "amount": 13000, "rsa": 28},
{"year": 2014, "amount": 14000, "rsa": 0},
{"year": 2014, "amount": 15000, "rsa": 0},
{"year": 2014, "amount": 20000, "rsa": 0},
]
error_margin = 1
year = 2014
age = 29
revenu = "sali"
for test in tests_list:
print test
amount = test["amount"]
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
simulation = tax_benefit_system.new_scenario().init_single_entity(
period = periods.period('year', year),
parent1 = {
'birth': datetime.date(year - age + 1, 1, 1),
revenu: amount,
},
).new_simulation(debug = True)
calculated_rsa = simulation.calculate('rsa') / 12
assert abs(calculated_rsa - test['rsa']) < error_margin, \
'calculated_rsa {} is not equal to expected value {}'.format(test['rsa'], calculated_rsa)
def test_survey_simulation():
year = 2011
input_data_frame = get_input_data_frame(year)
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system_class = TaxBenefitSystem
survey_scenario = SurveyScenario().init_from_data_frame(
input_data_frame = input_data_frame,
tax_benefit_system_class = tax_benefit_system_class,
year = year,
)
simulation = survey_scenario.new_simulation()
try:
from pandas import DataFrame
revdisp = DataFrame({"revdisp": simulation.calculate('revdisp')})
except NaNCreationError as error:
index = error.index
entity = error.entity
column_name = error.column_name
input_data_frame_debug = filter_input_data_frame(
simulation.input_data_frame,
entity,
index[:10],
)
survey_scenario_debug = SurveyScenario()
simulation_debug = survey_scenario_debug.new_simulation(
debug = True,
input_data_frame = input_data_frame_debug,
tax_benefit_system_class = tax_benefit_system_class,
year = year,
)
simulation_debug.calculate(column_name)
print revdisp.info()
print 'finished'
def set_variables_default_value(dataframe, year):
import openfisca_france
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
for column_name, column in tax_benefit_system.column_by_name.iteritems():
if column_name in dataframe.columns:
dataframe[column_name].fillna(column.default, inplace = True)
dataframe[column_name] = dataframe[column_name].astype(column.dtype)
def set_variables_default_value(dataframe, year):
import openfisca_france
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
for column_name, column in tax_benefit_system.column_by_name.iteritems():
if column_name in dataframe.columns:
dataframe[column_name].fillna(column.default, inplace = True)
dataframe[column_name] = dataframe[column_name].astype(column.dtype)
def test_weights_building():
year = 2006
input_data_frame = get_input_data_frame(year)
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system_class = TaxBenefitSystem
survey_scenario = SurveyScenario().init_from_data_frame(
input_data_frame = input_data_frame,
tax_benefit_system_class = tax_benefit_system_class,
year = year,
)
simulation = survey_scenario.new_simulation()
def test_weights_building():
year = 2011
input_data_frame = get_input_data_frame(year)
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system_class = TaxBenefitSystem
survey_scenario = SurveyScenario().init_from_data_frame(
input_data_frame = input_data_frame,
tax_benefit_system_class = tax_benefit_system_class,
year = year,
)
simulation = survey_scenario.new_simulation()
def get_brut_from_net(net, type_sal = 0, hsup = 0, csg_rempl = 0, rev = 'sal', year = 2011):
from openfisca_core.simulations import ScenarioSimulation
import openfisca_france
openfisca_france.init_country()
simulation = ScenarioSimulation()
simulation.set_config(year = 2011, nmen = 2, x_axis = "sali", maxrev = 100)
simulation.set_param()
simulation.compute()
net = [net]
_defaultP = simulation.P
if rev == 'sal':
output = _salbrut_from_salnet(net, hsup, type_sal, _defaultP)
elif rev == 'cho':
output = _chobrut_from_chonet(net, csg_rempl, _defaultP)
elif rev == 'rst':
output = _rstbrut_from_rstnet(net, csg_rempl, _defaultP)
return output
def build_cerfa_fields_by_column_name(year, sections_cerfa):
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
cerfa_fields_by_column_name = dict()
for name, column in tax_benefit_system.column_by_name.iteritems():
for section_cerfa in sections_cerfa:
if name.startswith('f{}'.format(section_cerfa)):
start = column.start or None
end = column.end or None
if (start is None or start.year <= year) and (end is None or end.year >= year):
if column.entity == 'ind':
cerfa_field = ['f' + x.lower().encode('ascii', 'ignore') for x in column.cerfa_field.values()]
elif column.entity == 'foy':
cerfa_field = ['f' + column.cerfa_field.lower().encode('ascii', 'ignore')]
cerfa_fields_by_column_name[name.encode('ascii', 'ignore')] = cerfa_field
return cerfa_fields_by_column_name
def process_tests_list(tests_list, verbose = False, monthly_amount = False, default_error_margin = 1, forced_error_margin = None):
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
for test in tests_list:
if forced_error_margin:
error_margin = forced_error_margin
else:
error_margin = test.pop("error_margin", default_error_margin)
simulation = simulation_from_test(test)
for variable, expected_value in test['output_vars'].iteritems():
calculated_value = (simulation.calculate(variable)).sum() / (1 * (not monthly_amount) + 12 * monthly_amount)
assert abs(calculated_value - expected_value) < error_margin, u'Variable "{} = {}. Expected: {}'.format(
variable, calculated_value, expected_value)
def find_ultimate_dependancies(variable_name, date, tax_benefit_system=None, input_variables=None):
if input_variables is None:
input_variables = set()
elif isinstance(input_variables, list):
input_variables = set(input_variables)
if tax_benefit_system is None:
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
if variable_name not in TaxBenefitSystem.prestation_by_name:
input_variables.add(variable_name)
pass
else:
column = TaxBenefitSystem.prestation_by_name[variable_name]
column_formula_type = column.formula_constructor.__bases__
if AlternativeFormula in column_formula_type:
formula = column.formula_constructor.alternative_formulas_constructor[0]
formula.extract_parameters()
elif DatedFormula in column_formula_type:
dated_formula_classes = column.formula_constructor.dated_formulas_class
formula = [
dated_formula_class["formula_class"]
for dated_formula_class in dated_formula_classes
if dated_formula_class["start"] <= date <= dated_formula_class["end"]
][0]
elif SelectFormula in column_formula_type:
formula = column.formula_constructor.formula_constructor_by_main_variable.items()[0][1]
elif SimpleFormula in column_formula_type:
formula = column.formula_constructor
formula.extract_parameters()
formula.set_dependencies(column, tax_benefit_system)
for variable_name in formula.parameters:
find_ultimate_dependancies(variable_name, date, input_variables=input_variables)
return list(input_variables)
def adaptation_eipp_to_OF(years = None, filename = "test", check = False):
"""
Adapation des bases ERFS FPR de l'IPP pour OF
"""
if years is None:
log.error("A list of years to process is needed")
for year in years:
# load data
eipp_survey_collection = SurveyCollection.load(collection = 'eipp')
survey = eipp_survey_collection.surveys['eipp_{}'.format(year)]
base = survey.get_values(table = "base")
ipp2of_input_variables, ipp2of_output_variables = build_ipp2of_variables()
# print 'avant',list(base.columns.values)
# base.rename(columns = ipp2of_input_variables, inplace = True)
# print 'après',list(base.columns.values)
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
data_frame = build_input_OF(base, ipp2of_input_variables, tax_benefit_system)
return data_frame
def main():
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
scenario = tax_benefit_system.new_scenario()
scenario.period = periods.period('2014')
individu = read_data(data_dir)
year_birth = (2014 - individu['age']).astype(int).astype(str)
individu['birth'] = year_birth + '-10-02'
individu['birth'] = pd.to_datetime(individu['birth'])
del individu['age']
scenario.input_variables = {
variable_name: {periods.period('2014'): serie.values}
for variable_name, serie in individu.iterkv()
}
simulation = scenario.new_simulation()
ars = simulation.calculate('ars')
print ars
print len(ars)
#
# OpenFisca is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import datetime
import json
import xml.etree.ElementTree
import openfisca_france
openfisca_france.init_country()
from openfisca_core import conv, legislations, legislationsxml, model
def test_legislation_xml_file():
legislation_tree = xml.etree.ElementTree.parse(model.PARAM_FILE)
legislation_xml_json = conv.check(legislationsxml.xml_legislation_to_json)(legislation_tree.getroot(),
state = conv.default_state)
legislation_xml_json, errors = legislationsxml.validate_node_xml_json(legislation_xml_json,
state = conv.default_state)
if errors is not None:
errors = conv.embed_error(legislation_xml_json, 'errors', errors)
if errors is None:
raise ValueError(unicode(json.dumps(legislation_xml_json, ensure_ascii = False,
def compute(self):
"""
Computing the test case
"""
self.starting_long_process(_("Computing test case ..."))
# TODO
# Consistency check on scenario
# msg = self.scenario.check_consistency()
# if msg:
# QMessageBox.critical(self, u"Ménage non valide",
# msg,
# QMessageBox.Ok, QMessageBox.NoButton)
# return False
# If it is consistent starts the computation
self.action_compute.setEnabled(False)
# P, P_default = self.main.parameters.getParam(), self.main.parameters.getParam(defaut = True)
# self.simulation.set_param(P, P_default)
import openfisca_france
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
axes = [
dict(
count = self.nmen,
name = 'salaire_imposable',
max = self.maxrev,
min = 0,
),
]
test_case = {
"familles": {
"fam0": {
"parents": ['ind0'],
"enfants": [],
},
},
"foyers_fiscaux": {
"foy0": {
"declarants": ['ind0'],
"personnes_a_charge": [],
}
},
"individus": {
"ind0": {
"activite": 0,
"birth": '1970-01-01',
"statmarit": 2,
},
},
"menages": {
"men0": {
"personne_de_reference": 'ind0',
"conjoint": None,
"enfants": [],
"autres": [],
},
}
}
self.scenario = tax_benefit_system.new_scenario().init_from_attributes(
axes = axes,
test_case = test_case,
year = 2013,
)
print self.scenario.test_case
self.scenario.simulation = self.scenario.new_simulation(debug = True)
self.scenario.simulation.compute('revdisp')
self.main.scenario = self.scenario
self.main.refresh_test_case_plugins()
self.ending_long_process(_("Test case results are updated"))
# -*- coding: utf-8 -*-
import datetime
import numpy as np
import openfisca_france
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
def check_1_parent(year = 2013):
simulation = tax_benefit_system.new_scenario().init_single_entity(
axes = [
dict(
count = 3,
name = 'salaire_imposable',
max = 100000,
min = 0,
),
],
period = year,
parent1 = dict(date_naissance = datetime.date(year - 40, 1, 1)),
).new_simulation(debug = True)
simulation.calculate('revdisp')
salaire_imposable = simulation.get_holder('salaire_imposable').new_test_case_array(simulation.period)
assert (salaire_imposable - np.linspace(0, 100000, 3) == 0).all(), 'salaire_imposable: {}'.format(salaire_imposable)
def test_1_parent():
def test_rsa_couple():
'''test pour un célibataire avec son age variant entre 18 et 25 ans'''
tests_list = [
{
"year": 2014,
"parent1": {
"sali": 0,
"age": 29,
},
"parent2": {
"sali": 0,
"age": 29,
},
"rsa": 629,
},
{
"year": 2014,
"parent1": {
"sali": 5000,
"age": 29,
},
"parent2": {
"sali": 0,
"age": 29,
},
"rsa": 471,
},
{
"year": 2014,
"parent1": {
"sali": 10000,
"age": 29,
},
"parent2": {
"sali": 0,
"age": 29,
},
"rsa": 312,
},
{
"year": 2014,
"parent1": {
"sali": 12000,
"age": 29,
},
"parent2": {
"sali": 0,
"age": 29,
},
"rsa": 249,
},
{
"year": 2014,
"parent1": {
"sali": 13000,
"age": 29,
},
"parent2": {
"sali": 0,
"age": 29,
},
"rsa": 217,
},
{
"year": 2014,
"parent1": {
"sali": 14000,
"age": 29,
},
"parent2": {
"sali": 0,
"age": 29,
},
"rsa": 186,
},
{
"year": 2014,
"parent1": {
"sali": 15000,
"age": 29,
},
"parent2": {
"sali": 0,
"age": 29,
},
"rsa": 154,
},
{
"year": 2014,
"parent1": {
"sali": 16000,
"age": 29,
},
"parent2": {
"sali": 0,
"age": 29,
},
"rsa": 122,
},
{
"year": 2014,
"parent1": {
"sali": 17000,
"age": 29,
},
"parent2": {
"sali": 0,
"age": 29,
},
"rsa": 91,
},
{
"year": 2014,
"parent1": {
"sali": 18000,
"age": 29,
},
"parent2": {
"sali": 0,
"age": 29,
},
"rsa": 59,
},
{
"year": 2014,
"parent1": {
"sali": 19000,
"age": 29,
},
"parent2": {
"sali": 0,
"age": 29,
},
"rsa": 27,
},
{
"year": 2014,
"parent1": {
"sali": 9000,
"age": 29,
},
"parent2": {
"sali": 11000,
"age": 29,
},
"rsa": 0,
},
# test si le déclarant a moins 25 ans et le conjoint plus de 25
{
"year": 2014,
"parent1": {
"sali": 400,
"age": 21,
},
"parent2": {
"sali": 3000,
"age": 21,
},
"rsa": 0,
},
# test pour moins de 25 ans pour les deux
{
"year": 2014,
"parent1": {
"sali": 400,
"age": 21,
},
"parent2": {
"sali": 3000,
"age": 21,
},
"rsa": 0,
},
# test pour un parent isolé avec 1 enfant de 2 ans
# {
# "year": 2014,
# "parent1": {
# "sali": 5000,
# "age": 29,
# },
# "enfants": [
# dict(age = 2),
# ],
# "rsa": 550,
# },
# test pour un couple avec un enfant de moins de 3 ans
# Problème avec site de la cnaf pour changer les revenus
{
"year": 2014,
"parent1": {
"sali": 0,
"age": 29,
},
"parent2": {
"sali": 0,
"age": 29,
},
"enfants": [
dict(age = 2),
],
"rsa": 565,
# "paje": 184.62,
},
# TODO: Do not pass
# {
# "year": 2014,
# "parent1": {
# "sali": 5000,
# "age": 29,
# },
# "parent2": {
# "sali": 0,
# "age": 29,
# },
# "enfants": [
# dict(age = 2),
# ],
# "rsa": 444, # Unsure about the value
# },
# TODO: do not pass
# {
# "year": 2014,
# "parent1": {
# "sali": 10000,
# "age": 29,
# },
# "parent2": {
# "sali": 0,
# "age": 29,
# },
# "enfants": [
# dict(age = 2),
# ],
# "rsa": 565, # TODO: check that value
# },
# "revenu": [
# {"year": 2014, "amountdéclarant": 0, "amountconjoint":0, "rsa": 750 },
# {"year": 2014, "amountdéclarant": 5000, "amountconjoint":0, "rsa": 592 },
# {"year": 2014, "amountdéclarant": 10000, "amountconjoint":0, "rsa": 434 },
# {"year": 2014, "amountdéclarant": 12000, "amountconjoint":0, "rsa": 370 },
# {"year": 2014, "amountdéclarant": 13000, "amountconjoint":0, "rsa": 339 },
# {"year": 2014, "amountdéclarant": 14000, "amountconjoint":0, "rsa": 307 },
# {"year": 2014, "amountdéclarant": 15000, "amountconjoint":0, "rsa": 275 },
# {"year": 2014, "amountdéclarant": 16000, "amountconjoint":0, "rsa": 244 },
# {"year": 2014, "amountdéclarant": 17000, "amountconjoint":0, "rsa": 212 },
# {"year": 2014, "amountdéclarant": 18000, "amountconjoint":0, "rsa": 180 },
# {"year": 2014, "amountdéclarant": 19000, "amountconjoint":0, "rsa": 149 },
# {"year": 2014, "amountdéclarant": 20000, "amountconjoint":0, "rsa": 117 },
# {"year": 2014, "amountdéclarant": 21000, "amountconjoint":0, "rsa": 85 },
# {"year": 2014, "amountdéclarant": 22000, "amountconjoint":0, "rsa": 54 },
# {"year": 2014, "amountdéclarant": 23000, "amountconjoint":0, "rsa": 22 },
# {"year": 2014, "amountdéclarant": 24000, "amountconjoint":0, "rsa": 0 },
# ],
# test pour enfants ayant entre 3 et 13 ans
{
"year": 2014,
"parent1": {
"sali": 0,
"age": 29,
},
"parent2": {
"sali": 0,
"age": 29,
},
"enfants": [
dict(age = 10),
],
"rsa": 750,
},
]
error_margin = 1
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
for test in tests_list:
print test
test = test.copy()
test['period'] = periods.period('year', test.pop('year'))
target_rsa = test.pop("rsa") # enlève rsa du dictionnaire et l'assigne a calculated_rsa
scenario = tax_benefit_system.new_scenario().init_single_entity(**test)
scenario.suggest()
simulation = scenario.new_simulation(debug = True)
calculated_rsa = simulation.calculate('rsa') / 12
# if test['rsa'] != calculated_rsa :
assert abs(calculated_rsa - target_rsa) < error_margin, \
'calculated_rsa {} is not equal to expected value {}'.format(target_rsa, calculated_rsa)
# u'Variable "{} = {}. Expected: {}'.format(
# variable, calculated_value, expected_value)
print calculated_rsa
from datetime import date # module nécessaire pour la définition des dates, dont notamment les dates de naissances
from openfisca_core import periods
import openfisca_france # module décrivant le système socio-fiscal français
from openfisca_france.tests import base
#from modulation_allocations_familiales.reforms import af_modulation
from openfisca_core import rates
TaxBenefitSystem = openfisca_france.init_country() # Initialisation de la classe décrivant le système socio-fiscal français
print TaxBenefitSystem
tax_benefit_system = TaxBenefitSystem() # Création d'une instance du système socio-fiscal français
import cPickle
from openfisca_utils.make_ready_to_use_scenario import make_couple_with_child_scenario
salaire_de_base_min = 0
salaire_de_base_maximal = 2*10**5
count = 10000
year_range = range(2012,2016)
child_range = range (0, 5)
axes_variable = 'salaire_de_base'
simulation_var = ['rsa','af','salaire_net','rni','br_pf','aide_logement','decote_gain_fiscal', 'salaire_imposable']+\
['revdisp', 'irpp','avantage_qf','impo', 'decote', 'salaire_de_base', 'ir_plaf_qf','salaire_de_base','salcho_imp']
def make_result_dict_single(tax_benefit_system = tax_benefit_system, pickle = False, year_range = range(2012,2016),
simulation_var = simulation_var, child_range = range (0, 5) ):
legislation_var_year = dict()
for year in year_range:
simulation = dict()
for nb_enf in child_range:
simulation[nb_enf] = make_couple_with_child_scenario(nombre_enfants = nb_enf,
year = year,
def main(liam, annee_leg=None,annee_base=None, mode_output='array'):
''' Send data from the simulation to openfisca
- annee_base: si rempli alors on tourne sur cette année-là, sinon sur toute la base
mais à voir
- annee_leg pour donner les paramètres
'''
print "annee base", annee_base
## on recupere la liste des annees en entree
if annee_base is not None:
if isinstance(annee_base,int):
annee_base = [annee_base]
else:
#TODO: ? peut-être updater pour qaund
get_years = HDFStore(path_til + "/output/to_run_leg.h5")
years = [x[-4:] for x in dir(get_years.root) if x[0]!='_' ]
get_years.close()
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
column_by_name = tax_benefit_system.column_by_name
simulation = simulations.Simulation(
compact_legislation = None,
date = dt.date(2009, 5, 1),
debug = None,
debug_all = None,
tax_benefit_system = tax_benefit_system,
trace = None,
)
entities = liam.entities
entities_name = map( lambda e: e.name, liam.entities)
def _get_entity(name):
position = entities_name.index(name)
return liam.entities[position]
input = dict()
required = dict() # pour conserver les valeurs que l'on va vouloir sortir de of.
#pour chaque entité d'open fisca
## load data :
selected_rows = {}
for of_ent_name, of_entity in tax_benefit_system.entity_class_by_key_plural.iteritems():
input[of_ent_name] = []
required[of_ent_name] = []
# on cherche l'entité corrspondante dans liam
til_ent_name = traduc_entities[of_ent_name]
til_entity = _get_entity(til_ent_name)
til_entity = til_entity.array.columns
selected = np.ones(len(til_entity['id']), dtype=bool)
if of_entity.is_persons_entity:
selected = (til_entity['men'] > -1) & (til_entity['foy'] > -1)
til_entity['quimen'][selected] = deal_with_qui(til_entity['quimen'][selected],
til_entity['men'][selected])
til_entity['quifoy'][selected] = deal_with_qui(til_entity['quifoy'][selected],
til_entity['foy'][selected])
selected_rows[of_ent_name] = selected
of_entity.count = of_entity.step_size = sum(selected)
of_entity.roles_count = 10 #TODO: faire une fonction
# pour toutes les variables de l'entité of
for column in of_entity.column_by_name:
# on regarde si on les a dans til sous un nom ou un autre
if column in rename_variables.keys() + til_entity.keys() + new_ident.keys():
holder = simulation.get_or_new_holder(column)
#on selectionne les valeurs d'entrée
if holder.formula is None or column in input_even_if_formula:
input[of_ent_name].append(column)
if column in til_entity:
holder.array = til_entity[column][selected]
elif column in new_ident:
ident = til_entity[new_ident[column]][selected]
holder.array = rankdata(ident, 'dense').astype(int) - 2
else:
holder.array = til_entity[rename_variables[column]][selected]
# sinon, on conserve la liste des variable pour tout à l'heure
else:
required[of_ent_name].append(column)
# print(of_ent_name)
# print(required[of_ent_name])
# print(input[of_ent_name])
### load of outputs
for entity, entity_vars in required.iteritems():
til_ent_name = traduc_entities[entity]
til_entity = _get_entity(til_ent_name)
til_column = til_entity.array.columns
selected = selected_rows[entity]
for var in entity_vars:
til_column[var][selected] = simulation.calculate(var)
#TODO: check incidence of following line
til_column[var][~selected] = 0
def compute(self):
"""
Computing the test case
"""
self.starting_long_process(_("Computing test case ..."))
# TODO
# Consistency check on scenario
# msg = self.scenario.check_consistency()
# if msg:
# QMessageBox.critical(self, u"Ménage non valide",
# msg,
# QMessageBox.Ok, QMessageBox.NoButton)
# return False
# If it is consistent starts the computation
self.action_compute.setEnabled(False)
# P, P_default = self.main.parameters.getParam(), self.main.parameters.getParam(defaut = True)
# self.simulation.set_param(P, P_default)
import openfisca_france
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
axes = [
dict(
count=self.nmen,
name='sali',
max=self.maxrev,
min=0,
),
]
test_case = {
"familles": {
"fam0": {
"parents": ['ind0'],
"enfants": [],
},
},
"foyers_fiscaux": {
"foy0": {
"declarants": ['ind0'],
"personnes_a_charge": [],
}
},
"individus": {
"ind0": {
"activite": 0,
"birth": '1970-01-01',
"statmarit": 2,
},
},
"menages": {
"men0": {
"personne_de_reference": 'ind0',
"conjoint": None,
"enfants": [],
"autres": [],
},
}
}
self.scenario = tax_benefit_system.new_scenario().init_from_attributes(
axes=axes,
test_case=test_case,
year=2013,
)
print self.scenario.test_case
self.scenario.simulation = self.scenario.new_simulation(debug=True)
self.scenario.simulation.compute('revdisp')
self.main.scenario = self.scenario
self.main.refresh_test_case_plugins()
self.ending_long_process(_("Test case results are updated"))
# -*- coding: utf-8 -*-
'''
Created on 13 févr. 2014
@author: p702207
'''
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.pyplot as plt
from datetime import datetime
from openfisca_core import model
import openfisca_france
openfisca_france.init_country()
from openfisca_core.simulations import ScenarioSimulation
def case_study(year=2013):
simulation = ScenarioSimulation(
) #on instancie on prends une instance de ScenarioSimulation, on prends un exemple de cette classe là
simulation.set_config(
year=year,
nmen=500, #nombre de ménages
maxrev=100000,
x_axis='sali') #salaire imposable (une seule personne dans le ménage)
simulation.set_param() #prends les paramètres par défaut de la législation
df = simulation.get_results_dataframe(
) #renvoie la dataframe avec tout calculé
#print df.to_string()
return df
def run_OF(dic_input, path_dta_input, param_scenario = None, dic = None, datesim = None, option = 'test_dta'):
'''
Lance le calculs sur OF à partir des cas-types issues de TaxIPP
input : base .dta issue de l'étape précédente
'''
def _test_of_dta(dta_input, dic):
''' Cette fonction teste que la table .dta trouvée
correspond au bon scénario '''
data = read_stata(dta_input)
dic_dta = data.loc[0, 'dic_scenar']
if str(dic) != str(dic_dta) :
print "La base .dta permettant de lancer la simulation OF est absente "
print "La base s'en rapprochant le plus a été construite avec les paramètres : ", dic_dta
pdb.set_trace()
else :
data = data.drop('dic_scenar', 1).sort(['id_foyf', 'id_indiv'], ascending = [True, False])
return data
def _scenar_dta(dta_input) :
''' cette fonction identifie le scenario enregistré dans la table d'input '''
data = read_stata(dta_input)
dic_dta = data.loc[0, 'dic_scenar']
data = data.drop('dic_scenar', 1).sort(['id_foyf', 'id_indiv'], ascending = [True, False])
return dic_dta, data
if option == 'test_dta':
data_IPP = _test_of_dta(path_dta_input, dic)
if option == 'list_dta':
dic_scenar, data_IPP = _scenar_dta(path_dta_input)
dict_scenar = dict()
expression = "dict_scenar.update(" + dic_scenar + ")"
eval(expression)
datesim = dict_scenar['datesim']
param_scenario = dict_scenar
if 'salbrut' in param_scenario.items() :
if param_scenario['option'] == 'salbrut':
TaxBenefitSystem = openfisca_france.init_country(start_from = "brut")
tax_benefit_system = TaxBenefitSystem()
del dic_input['sal_irpp_old']
dic_input['sal_brut'] = 'salbrut'
else :
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
else :
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
openfisca_survey = build_input_OF(data_IPP, dic_input)
openfisca_survey = openfisca_survey.fillna(0) # .sort(['idfoy','noi'])
simulation = SurveySimulation()
simulation.set_config(year = datesim,
survey_filename = openfisca_survey,
param_file = os.path.join(os.path.dirname(model.PARAM_FILE), 'param.xml'))
simulation.set_param()
simulation.compute()
if option == 'list_dta':
return simulation, simulation.output_table.table, param_scenario
else:
return simulation, simulation.output_table.table
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
from __future__ import division
import datetime
import openfisca_france
from openfisca_france.model.cotisations_sociales.travail import CAT, TAUX_DE_PRIME
from pandas import DataFrame
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
def test_sal(year = 2013, verbose = False):
'''
Tests that _salbrut which computes "salaire brut" from "imposable" yields an amount compatbe
with the one obtained from running openfisca satrting with a "salaire brut"
'''
maxrev = 50000
for type_sal_category in ['prive_non_cadre', 'prive_cadre']: # , 'public_titulaire_etat']:
simulation = tax_benefit_system.new_scenario().init_single_entity(
axes = [ dict(name = 'salbrut', max = maxrev, min = 0, count = 11) ],
parent1 = dict(
def main():
parser = argparse.ArgumentParser()
parser.add_argument(
'-s',
'--source-dir',
default='yaml-clean',
help='path of source directory containing clean IPP YAML files')
parser.add_argument(
'-t',
'--target',
default='ipp-tax-and-benefit-tables-to-openfisca-parameters.yaml',
help=
'path of generated YAML file containing the association between IPP fields to OpenFisca parameters'
)
parser.add_argument('-v',
'--verbose',
action='store_true',
default=False,
help="increase output verbosity")
args = parser.parse_args()
logging.basicConfig(
level=logging.DEBUG if args.verbose else logging.WARNING,
stream=sys.stdout)
file_system_encoding = sys.getfilesystemencoding()
ipp_infos_by_value = {}
for source_dir_encoded, directories_name_encoded, filenames_encoded in os.walk(
args.source_dir):
directories_name_encoded.sort()
for filename_encoded in sorted(filenames_encoded):
if not filename_encoded.endswith('.yaml'):
continue
filename = filename_encoded.decode(file_system_encoding)
sheet_name = os.path.splitext(filename)[0]
source_file_path_encoded = os.path.join(source_dir_encoded,
filename_encoded)
relative_file_path_encoded = source_file_path_encoded[
len(args.source_dir):].lstrip(os.sep)
relative_file_path = relative_file_path_encoded.decode(
file_system_encoding)
if sheet_name.isupper():
continue
assert sheet_name.islower(), sheet_name
log.info(u'Loading file {}'.format(relative_file_path))
with open(source_file_path_encoded) as source_file:
data = yaml.load(source_file)
rows = data.get(u"Valeurs")
if rows is None:
log.info(u' Skipping file {} without "Valeurs"'.format(
relative_file_path))
continue
for row in rows:
start = row.get(u"Date d'effet")
if start is None:
for date_name in date_names:
start = row.get(date_name)
if start is not None:
break
else:
# No date found. Skip row.
continue
elif not isinstance(start, datetime.date):
start = start[u"Année Revenus"]
for name, child in row.iteritems():
if name in date_names:
continue
for path, value in iter_ipp_values(child):
if isinstance(value, basestring):
split_value = value.split()
if len(split_value) == 2 and split_value[1] in (
u'%',
u'AF', # anciens francs
u'CFA', # francs CFA
u'COTISATIONS',
u'EUR',
u'FRF',
):
value = float(split_value[0])
if isinstance(value, float) and value == int(value):
value = int(value)
full_path = tuple(
relative_file_path.split(os.sep)[:-1]) + (
sheet_name, name) + tuple(path)
ipp_infos_by_value.setdefault(value, []).append(
dict(
path=full_path,
start=start,
))
# print yaml.dump(ipp_infos_by_value, allow_unicode = True, default_flow_style = False, indent = 2, width = 120)
TaxBenefitSystem = init_country()
tax_benefit_system = TaxBenefitSystem()
# print yaml.dump(tax_benefit_system.legislation_json, allow_unicode = True, default_flow_style = False, indent = 2,
# width = 120)
# openfisca_infos_by_value = {}
# for path, start, value in iter_openfisca_values(tax_benefit_system.legislation_json):
# openfisca_infos_by_value.setdefault(value, []).append(dict(
# path = tuple(path),
# start = start,
# ))
# print yaml.dump(openfisca_infos_by_value, allow_unicode = True, default_flow_style = False, indent = 2, width = 120)
# ipp_count = {}
# for path, start, value in iter_openfisca_values(tax_benefit_system.legislation_json):
# ipp_infos = ipp_infos_by_value.get(value)
# if ipp_infos is None:
# # OpenFisca parameter doesn't exit in IPP.
# continue
# for ipp_info in ipp_infos:
# if ipp_info['start'] == start:
# ipp_child = ipp_count
# ipp_path = ipp_info['path']
# for name in path:
# ipp_child = ipp_child.setdefault(name, {})
# ipp_child_count = ipp_child.setdefault('count_by_path', {})
# for ipp_index in range(len(ipp_path)):
# ipp_sub_path = ipp_path[:ipp_index + 1]
# ipp_child_count[ipp_sub_path] = ipp_child_count.get(ipp_sub_path, 0) + 1
# print yaml.dump(ipp_count, allow_unicode = True, default_flow_style = False, indent = 2, width = 120)
starts_by_ipp_path_by_openfisca_path = {}
starts_by_openfisca_path_by_ipp_path = {}
for path, start, value in iter_openfisca_values(
tax_benefit_system.legislation_json):
ipp_infos = ipp_infos_by_value.get(value)
if ipp_infos is None:
# OpenFisca parameter doesn't exit in IPP.
continue
same_start_ipp_paths = [
ipp_info['path'] for ipp_info in ipp_infos
if ipp_info['start'] == start
]
if len(same_start_ipp_paths) == 1:
ipp_path = same_start_ipp_paths[0]
starts_by_ipp_path_by_openfisca_path.setdefault(
tuple(path), {}).setdefault(ipp_path, set()).add(start)
starts_by_openfisca_path_by_ipp_path.setdefault(
ipp_path, {}).setdefault(tuple(path), set()).add(start)
# for openfisca_path, starts_by_ipp_path in sorted(starts_by_ipp_path_by_openfisca_path.iteritems()):
## if len(starts_by_ipp_path) == 1:
## print u'.'.join(openfisca_path), '->', u' / '.join(starts_by_ipp_path.keys()[0])
# if len(starts_by_ipp_path) > 1:
# print u'.'.join(openfisca_path), '->', starts_by_ipp_path
# for ipp_path, starts_by_openfisca_path in sorted(starts_by_openfisca_path_by_ipp_path.iteritems()):
# if len(starts_by_openfisca_path) == 1:
# print u' / '.join(ipp_path), '->', u'.'.join(
# unicode(fragment)
# for fragment in starts_by_openfisca_path.keys()[0]
# )
## if len(starts_by_openfisca_path) > 1:
## print u' / '.join(ipp_path), '->', u'.'.join(
## unicode(fragment)
## for fragment in starts_by_openfisca_path.keys()[0]
## )
openfisca_path_by_ipp_tree = collections.OrderedDict()
for ipp_path, starts_by_openfisca_path in sorted(
starts_by_openfisca_path_by_ipp_path.iteritems()):
openfisca_path_by_ipp_sub_tree = openfisca_path_by_ipp_tree
for ipp_name in ipp_path[:-1]:
openfisca_path_by_ipp_sub_tree = openfisca_path_by_ipp_sub_tree.setdefault(
ipp_name, collections.OrderedDict())
ipp_name = ipp_path[-1]
openfisca_path_by_ipp_sub_tree[ipp_name] = [
u'.'.join(unicode(fragment) for fragment in openfisca_name)
for openfisca_name in sorted(starts_by_openfisca_path)
]
with open(args.target, 'w') as target_file:
yaml.dump(openfisca_path_by_ipp_tree,
target_file,
allow_unicode=True,
default_flow_style=False,
indent=2,
width=120)
return 0
def test_irpp():
"""
test pour un célibataire pour un revenu de 20 000, 50 000 € et 150 000 €
et des revenus de différentes origines
"""
dico = {
# test pour un célibataire ayant un revenu salarial (1AJ)
"sali": [
{"year": 2010, "amount": 20000, "irpp": -1181},
{"year": 2010, "amount": 50000, "irpp": -7934},
{"year": 2010, "amount": 150000, "irpp": -42338},
{"year": 2011, "amount": 20000, "irpp": -1181},
{"year": 2011, "amount": 50000, "irpp": -7934},
{"year": 2011, "amount": 150000, "irpp": -42338},
{"year": 2012, "amount": 20000, "irpp": -1181},
{"year": 2012, "amount": 50000, "irpp": -7934},
{"year": 2012, "amount": 150000, "irpp": -43222},
{"year": 2013, "amount": 20000, "irpp": -1170},
{"year": 2013, "amount": 50000, "irpp": -7889},
{"year": 2013, "amount": 150000, "irpp": -43076},
],
# test pour un retraité célibataire ayant une pension (1AS)
# TODO: test mal spécifié passe toujours au dessus du seuil
# qui est d'environ 3500 euros (e.g.faire test pour amount de 500
# 2000 5000, ou faire un seul test au dessus du seuil par année.)
"rsti": [
{"year": 2010, "amount": 20000, "irpp": -1181},
{"year": 2010, "amount": 50000, "irpp": -8336},
{"year": 2010, "amount": 150000, "irpp": -46642},
{"year": 2011, "amount": 20000, "irpp": -1181},
{"year": 2011, "amount": 50000, "irpp": -8336},
{"year": 2011, "amount": 150000, "irpp": -46642},
{"year": 2012, "amount": 20000, "irpp": -1181},
{"year": 2012, "amount": 50000, "irpp": -8336},
{"year": 2012, "amount": 150000, "irpp": -46642},
{"year": 2013, "amount": 20000, "irpp": -1170},
{"year": 2013, "amount": 50000, "irpp": -8283},
{"year": 2013, "amount": 150000, "irpp": -46523},
],
# test sur un revenu des actions soumises à un prélèvement libératoire de 21 % (2DA)
"f2da": [
{"year": 2010, "amount": 20000, "irpp": 0},
{"year": 2010, "amount": 50000, "irpp": 0},
{"year": 2010, "amount": 150000, "irpp": 0},
{"year": 2011, "amount": 20000, "irpp": 0},
{"year": 2011, "amount": 50000, "irpp": 0},
{"year": 2011, "amount": 150000, "irpp": 0},
{"year": 2012, "amount": 20000, "irpp": 0},
{"year": 2012, "amount": 50000, "irpp": 0},
{"year": 2012, "amount": 150000, "irpp": 0},
# {"year": 2013, "amount": 20000, "irpp": 0},
# {"year": 2013, "amount": 50000, "irpp": 0},
# {"year": 2013, "amount": 150000, "irpp": 0},TODO: check mahdi if 2DA exist in 2013
],
# test sur un revenu (2DH) issu des produits d'assurance vie et de capitalisation soumis au prélèvement
# libératoire de 7.5 %
"f2dh": [
{"year": 2010, "amount": 20000, "irpp": 345},
{"year": 2010, "amount": 50000, "irpp": 345},
{"year": 2010, "amount": 150000, "irpp": 345},
{"year": 2011, "amount": 20000, "irpp": 345},
{"year": 2011, "amount": 50000, "irpp": 345},
{"year": 2011, "amount": 150000, "irpp": 345},
{"year": 2012, "amount": 20000, "irpp": 345},
{"year": 2012, "amount": 50000, "irpp": 345},
{"year": 2012, "amount": 150000, "irpp": 345},
{"year": 2013, "amount": 20000, "irpp": 345},
{"year": 2013, "amount": 50000, "irpp": 345},
{"year": 2013, "amount": 150000, "irpp": 345}
],
# test sur un revenu des actions et parts (2DC)
"f2dc": [
{"year": 2010, "amount": 20000, "irpp": 0},
{"year": 2010, "amount": 50000, "irpp": -2976},
{"year": 2010, "amount": 150000, "irpp": -22917},
{"year": 2011, "amount": 20000, "irpp": 0},
{"year": 2011, "amount": 50000, "irpp": -2976},
{"year": 2011, "amount": 150000, "irpp": -22917},
{"year": 2012, "amount": 20000, "irpp": 0},
{"year": 2012, "amount": 50000, "irpp": -3434},
{"year": 2012, "amount": 150000, "irpp": -23542},
# {"year": 2013, "amount": 20000, "irpp": -},
# {"year": 2013, "amount": 50000, "irpp": -},
# {"year": 2013, "amount": 150000, "irpp": -}, TODO: check with mahdi
],
# test sur le revenu de valeurs mobilières (2TS)
"f2ts": [
{"year": 2010, "amount": 20000, "irpp": -1461},
{"year": 2010, "amount": 50000, "irpp": -9434},
{"year": 2010, "amount": 150000, "irpp": -48142},
{"year": 2011, "amount": 20000, "irpp": -1461},
{"year": 2011, "amount": 50000, "irpp": -9434},
{"year": 2011, "amount": 150000, "irpp": -48142},
{"year": 2012, "amount": 20000, "irpp": -1461},
{"year": 2012, "amount": 50000, "irpp": -9434},
{"year": 2012, "amount": 150000, "irpp": -48142},
{"year": 2013, "amount": 20000, "irpp": -1450},
{"year": 2013, "amount": 50000, "irpp": -9389},
{"year": 2013, "amount": 150000, "irpp": -48036},
],
# test sur les intérêts (2TR)
"f2tr": [
{"year": 2010, "amount": 20000, "irpp": -1461},
{"year": 2010, "amount": 50000, "irpp": -9434},
{"year": 2010, "amount": 150000, "irpp": -48142},
{"year": 2011, "amount": 20000, "irpp": -1461},
{"year": 2011, "amount": 50000, "irpp": -9434},
{"year": 2011, "amount": 150000, "irpp": -48142},
{"year": 2012, "amount": 20000, "irpp": -1461},
{"year": 2012, "amount": 50000, "irpp": -9434},
{"year": 2012, "amount": 150000, "irpp": -48142},
{"year": 2013, "amount": 20000, "irpp": -1450},
{"year": 2013, "amount": 50000, "irpp": -9389},
{"year": 2013, "amount": 150000, "irpp": -48036},
],
# test sur les revenus fonciers (4BA)
"f4ba": [
{"year": 2010, "amount": 20000, "irpp": -1461},
{"year": 2010, "amount": 50000, "irpp": -9434},
{"year": 2010, "amount": 150000, "irpp": -48142},
{"year": 2011, "amount": 20000, "irpp": -1461},
{"year": 2011, "amount": 50000, "irpp": -9434},
{"year": 2011, "amount": 150000, "irpp": -48142},
{"year": 2012, "amount": 20000, "irpp": -1461},
{"year": 2012, "amount": 50000, "irpp": -9434},
{"year": 2012, "amount": 150000, "irpp": -48142},
{"year": 2013, "amount": 20000, "irpp": -1450},
{"year": 2013, "amount": 50000, "irpp": -9389},
{"year": 2013, "amount": 150000, "irpp": -48036},
],
# test sur les plus-values mobilières (3VG)
"f3vg": [
{"year": 2010, "amount": 20000, "irpp": -3600},
{"year": 2010, "amount": 50000, "irpp": -9000},
{"year": 2010, "amount": 150000, "irpp": -27000},
{"year": 2011, "amount": 20000, "irpp": -3800},
{"year": 2011, "amount": 50000, "irpp": -9500},
{"year": 2011, "amount": 150000, "irpp": -28500},
{"year": 2012, "amount": 20000, "irpp": -4800},
{"year": 2012, "amount": 50000, "irpp": -12000},
{"year": 2012, "amount": 150000, "irpp": -36000},
{"year": 2013, "amount": 20000, "irpp": -1450},
{"year": 2013, "amount": 50000, "irpp": -9389},
{"year": 2013, "amount": 150000, "irpp": -48036},
],
# test sur les plus-values immobilières (3VZ)
"f3vz": [
# TODO: voir pour tests 2010
{"year": 2011, "amount": 20000, "irpp": 0},
{"year": 2011, "amount": 50000, "irpp": 0},
{"year": 2011, "amount": 150000, "irpp": 0},
{"year": 2012, "amount": 20000, "irpp": 0},
{"year": 2012, "amount": 50000, "irpp": 0},
{"year": 2012, "amount": 150000, "irpp": 0},
{"year": 2013, "amount": 20000, "irpp": 0},
{"year": 2013, "amount": 50000, "irpp": 0},
{"year": 2013, "amount": 150000, "irpp": 0},
],
}
for revenu, test_list in dico.iteritems():
for item in test_list:
year = item["year"]
amount = item["amount"]
irpp = item["irpp"]
fiscal_values = ["f2da", "f2dh", "f2dc", "f2ts", "f2tr", "f4ba", "f3vg", "f3vz"]
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
# if revenu != "f2dc":
# continue
if revenu in ["rsti", "sali"]:
simulation = tax_benefit_system.new_scenario().init_single_entity(
period = periods.period('year', year),
parent1 = {
'birth': datetime.date(year - 40, 1, 1),
revenu: amount,
},
).new_simulation(debug = True)
elif revenu in fiscal_values:
simulation = tax_benefit_system.new_scenario().init_single_entity(
period = periods.period('year', year),
parent1 = {
'birth': datetime.date(year - 40, 1, 1),
},
foyer_fiscal = {revenu: amount},
).new_simulation(debug = True)
yield check_irpp, amount, irpp, revenu, simulation, year
def test_couple(verbose = False):
"""Couple de retraités"""
tests_list = [
{
"year": 2013,
"input_vars": {
"age": 73,
"activite": 3,
"rsti": 12500,
},
"output_vars": {
"rst": 2 * 12500,
}
},
]
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
passed = True
for test in tests_list:
year = test["year"]
parent1 = dict(birth = datetime.date(year - 40, 1, 1))
parent2 = dict(birth = datetime.date(year - 40, 1, 1))
menage = dict()
foyer_fiscal = dict()
for variable, value in test['input_vars'].iteritems():
if variable == "age":
parent1['birth'] = datetime.date(year - value, 1, 1)
parent2['birth'] = datetime.date(year - value, 1, 1)
elif tax_benefit_system.column_by_name[variable].entity == 'men':
menage[variable] = value
elif tax_benefit_system.column_by_name[variable].entity == 'ind':
parent1[variable] = value
parent2[variable] = value
elif tax_benefit_system.column_by_name[variable].entity == 'foy':
foyer_fiscal[variable] = value
simulation = tax_benefit_system.new_scenario().init_single_entity(
period = periods.period('year', year),
parent1 = parent1,
parent2 = parent2,
menage = menage,
foyer_fiscal = foyer_fiscal,
).new_simulation(debug = True)
for variable, value in test['output_vars'].iteritems():
computed_value = (simulation.calculate(variable)).sum()
test_assertion = abs(abs(computed_value) - value) < 1
expression = "Test failed for variable %s on year %i and case %s:\n" \
"OpenFisca value: %s\n" \
" Real value: %s \n" % (variable, year, test['input_vars'], abs(computed_value), value)
if not test_assertion:
print expression
passed = False
else:
if verbose:
expression = "Test passed for variable %s on year %i and case %s:\n" \
"OpenFisca value: %s\n" \
" Real value: %s \n" % (variable, year, test['input_vars'], abs(computed_value), value)
print expression
assert passed, "Test failed for some variables"
# -*- coding: utf-8 -*-
import datetime
import json
from openfisca_core import conv, legislations, legislationsxml
from openfisca_france import init_country
# Exceptionally for this test do not import TaxBenefitSystem from tests.base.
TaxBenefitSystem = init_country()
def check_legislation_xml_file(year):
legislation_tree = conv.check(
legislationsxml.make_xml_legislation_info_list_to_xml_element(False))(
TaxBenefitSystem.legislation_xml_info_list,
state=conv.default_state)
legislation_xml_json = conv.check(legislationsxml.xml_legislation_to_json)(
legislation_tree,
state=conv.default_state,
)
legislation_xml_json, errors = legislationsxml.validate_legislation_xml_json(
legislation_xml_json, state=conv.default_state)
if errors is not None:
errors = conv.embed_error(legislation_xml_json, 'errors', errors)
if errors is None:
raise ValueError(
unicode(
json.dumps(legislation_xml_json,
def test_cotsoc():
"""
Cotisations sur les revenus du capital
"""
cotsoc_cap = {
# test sur un revenu des actions soumises à un prélèvement libératoire de 21 % (2DA)
"f2da" : [
{"year" : 2012, "amount": 20000,
"vars" :
{"prelsoc_cap_lib":-(4.5 + 2 + 0.3) * 0.01 * 20000,
"csg_cap_lib":-.082 * 20000,
"crds_cap_lib":-.005 * 20000 } },
{"year" : 2011, "amount": 20000,
"vars" :
{"prelsoc_cap_lib":-(3.4 + 1.1 + 0.3) * 0.01 * 20000,
"csg_cap_lib":-.082 * 20000,
"crds_cap_lib":-.005 * 20000 } },
{"year" : 2010, "amount": 20000,
"vars" : {"prelsoc_cap_lib":-(2.2 + 1.1 + 0.3) * 0.01 * 20000,
"csg_cap_lib":-.082 * 20000,
"crds_cap_lib":-.005 * 20000 } }
],
# Célibataire sans enfant
# test sur un revenu des actions et parts (2DC)
"f2dc" :[
{"year" : 2013, "amount": 20000,
"vars" :
{"prelsoc_cap_bar":-1360,
"csg_cap_bar":-1640,
"crds_cap_bar":-100,
"ir_plaf_qf": 330,
"irpp":-0} },
{"year" : 2012, "amount": 20000,
"vars" :
{"prelsoc_cap_bar":-(4.5 + 2 + 0.3) * 0.01 * 20000,
"csg_cap_bar":-.082 * 20000,
"crds_cap_bar":-.005 * 20000 } },
{"year" : 2011, "amount": 20000,
"vars" :
{"prelsoc_cap_bar":-(3.4 + 1.1 + 0.3) * 0.01 * 20000,
"csg_cap_bar":-.082 * 20000,
"crds_cap_bar":-.005 * 20000 } },
{"year" : 2010, "amount": 20000,
"vars" :
{"prelsoc_cap_bar":-(2.2 + 1.1 + 0.3) * 0.01 * 20000,
"csg_cap_bar":-.082 * 20000,
"crds_cap_bar":-.005 * 20000 } },
],
# # test sur le Revenus imposables des titres non côtés détenus dans le PEA et distributions perçues via votre entreprise
# ## donnant droit à abattement (2fu)
"f2fu" :[
{"year" : 2013, "amount": 20000,
"vars" :
{"prelsoc_cap_bar":-1360,
"csg_cap_bar":-1640,
"crds_cap_bar":-100,
"ir_plaf_qf": 330,
"irpp":0} },
],
# Autres revenus distribués et revenus des structures soumises hors de France à un régime fiscal privilégié (2Go)
"f2go" :[
{"year" : 2013, "amount": 20000,
"vars" :
{"rev_cat_rvcm" : 25000,
"prelsoc_cap_bar":-1700,
"csg_cap_bar":-2050,
"crds_cap_bar":-125,
"ir_plaf_qf": 2150,
"irpp":-2150 } },
],
"f2ts" :[
{"year" : 2013, "amount": 20000,
"vars" :
{"rev_cat_rvcm" : 20000,
"prelsoc_cap_bar":-1360,
"csg_cap_bar":-1640,
"crds_cap_bar":-100,
"ir_plaf_qf": 1450,
"irpp":-1450 } },
{"year" : 2012, "amount": 20000,
"vars" :
{"prelsoc_cap_bar":-(4.5 + 2 + 0.3) * 0.01 * 20000,
"csg_cap_bar":-.082 * 20000,
"crds_cap_bar":-.005 * 20000 } },
{"year" : 2011, "amount": 20000,
"vars" :
{"prelsoc_cap_bar":-(3.4 + 1.1 + 0.3) * 0.01 * 20000,
"csg_cap_bar":-.082 * 20000,
"crds_cap_bar":-.005 * 20000 } },
{"year" : 2010, "amount": 20000,
"vars" :
{"prelsoc_cap_bar":-(2.2 + 1.1 + 0.3) * 0.01 * 20000,
"csg_cap_bar":-.082 * 20000,
"crds_cap_bar":-.005 * 20000 } },
],
# # test sur les intérêts (2TR)
"f2tr" :[
{"year" : 2013, "amount": 20000,
"vars" :
{"prelsoc_cap_bar":-1360,
"csg_cap_bar":-1640,
"crds_cap_bar":-100,
"ir_plaf_qf": 1450,
"irpp":-1450 } },
{"year" : 2012, "amount": 20000,
"vars" :
{"prelsoc_cap_bar":-(4.5 + 2 + 0.3) * 0.01 * 20000,
"csg_cap_bar":-.082 * 20000,
"crds_cap_bar":-.005 * 20000, } },
{"year" : 2011, "amount": 20000,
"vars" :
{"prelsoc_cap_bar":-(3.4 + 1.1 + 0.3) * 0.01 * 20000,
"csg_cap_bar":-.082 * 20000,
"crds_cap_bar":-.005 * 20000 } },
{"year" : 2010, "amount": 20000,
"vars" :
{"prelsoc_cap_bar":-(2.2 + 1.1 + 0.3) * 0.01 * 20000,
"csg_cap_bar":-.082 * 20000,
"crds_cap_bar":-.005 * 20000 } },
],
# # test sur les revenus fonciers (4BA)
"f4ba":[
{"year" : 2013, "amount": 20000,
"vars" :
{"prelsoc_fon":-1360,
"csg_fon":-1640,
"crds_fon":-100,
"ir_plaf_qf": 1450,
"irpp":-1450} },
{"year" : 2012, "amount": 20000,
"vars" :
{"prelsoc_fon":-(4.5 + 2 + 0.3) * 0.01 * 20000,
"csg_fon":-.082 * 20000,
"crds_fon":-.005 * 20000,
"irpp" :-1461 } },
{"year" : 2011, "amount": 20000,
"vars" :
{"prelsoc_fon":-(3.4 + 1.1 + 0.3) * 0.01 * 20000,
"csg_fon":-.082 * 20000,
"crds_fon":-.005 * 20000 } },
{"year" : 2010, "amount": 20000,
"vars" :
{"prelsoc_fon":-(2.2 + 1.1 + 0.3) * 0.01 * 20000,
"csg_fon":-.082 * 20000,
"crds_fon":-.005 * 20000 } },
],
# # test (3VG) Plus-values de cession de valeurs mobilières, droits sociaux et gains assimilés
"f3vg" :[
{"year" : 2013, "amount": 20000,
"vars" :
{"prelsoc_pv_mo":-1360,
"csg_pv_mo":-1640,
"crds_pv_mo":-100,
"ir_plaf_qf": 1450,
"irpp":-1450} },
{"year" : 2012, "amount": 20000,
"vars" :
{"prelsoc_pv_mo":-(4.5 + 2 + 0.3) * 0.01 * 20000,
"csg_pv_mo":-.082 * 20000,
"crds_pv_mo":-.005 * 20000 } },
{"year" : 2011, "amount": 20000,
"vars" :
{"prelsoc_pv_mo":-(3.4 + 1.1 + 0.3) * 0.01 * 20000,
"csg_pv_mo":-.082 * 20000,
"crds_pv_mo":-.005 * 20000 } },
{"year" : 2010, "amount": 20000,
"vars" :
{"prelsoc_pv_mo":-(2.2 + 1.1 + 0.3) * 0.01 * 20000,
"csg_pv_mo":-.082 * 20000,
"crds_pv_mo":-.005 * 20000 } },
{"year" : 2006, "amount": 20000,
"vars" :
{"prelsoc_pv_mo":-460 ,
"csg_pv_mo":-1640,
"crds_pv_mo":-100} },
],
# # test sur les plus-values immobilières (3VZ)
"f3vz" :[
{"year" : 2012, "amount": 20000,
"vars" :
{"prelsoc_pv_immo":-(4.5 + 2 + 0.3) * 0.01 * 20000,
"csg_pv_immo":-.082 * 20000,
"crds_pv_immo":-.005 * 20000 } },
{"year" : 2011, "amount": 20000,
"vars" :
{"prelsoc_pv_immo":-(3.4 + 1.1 + 0.3) * 0.01 * 20000,
"csg_pv_immo":-.082 * 20000,
"crds_pv_immo":-.005 * 20000 } },
{"year" : 2010, "amount": 20000,
"vars" :
{"prelsoc_pv_immo":-(2.2 + 1.1 + 0.3) * 0.01 * 20000,
"csg_pv_immo":-.082 * 20000,
"crds_pv_immo":-.005 * 20000 } },
],
}
for revenu, test_list in cotsoc_cap.iteritems():
for item in test_list:
year = item["year"]
amount = item["amount"]
for var, value in item["vars"].iteritems():
parent1 = dict(birth = datetime.date(year - 40, 1, 1))
foyer_fiscal = dict()
if revenu in ["rsti", "sali"]:
parent1[revenu] = value
elif revenu in ["f2da", "f2dh", "f2dc", "f2ts", "f2tr", "f4ba", "f3vg", "f3vz", "f2fu", "f4ba", "f2go"]:
foyer_fiscal[revenu] = amount
else:
print revenu
assert False
TaxBenefitSystem = openfisca_france.init_country()
tax_benefit_system = TaxBenefitSystem()
simulation = tax_benefit_system.new_scenario().init_single_entity(
period = periods.period('year', year),
parent1 = parent1,
foyer_fiscal = foyer_fiscal,
).new_simulation(debug = True)
val = simulation.calculate(var)
difference = abs(val - value)
passed = (difference < 1)
if not passed:
expression = "Test failed for variable %s on year %i : \n OpenFisca value : %s \n Real value : %s \n" % (var, year, abs(val), value)
assert passed, expression
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import datetime
import json
import xml.etree.ElementTree
from openfisca_core import conv, legislations, legislationsxml
from openfisca_france import init_country
TaxBenefitSystem = init_country()
def check_legislation_xml_file(year):
legislation_tree = xml.etree.ElementTree.parse(TaxBenefitSystem.legislation_xml_file_path)
legislation_xml_json = conv.check(legislationsxml.xml_legislation_to_json)(legislation_tree.getroot(),
state = conv.default_state)
legislation_xml_json, errors = legislationsxml.validate_legislation_xml_json(legislation_xml_json,
state = conv.default_state)
if errors is not None:
errors = conv.embed_error(legislation_xml_json, 'errors', errors)
if errors is None:
raise ValueError(unicode(json.dumps(legislation_xml_json, ensure_ascii = False,
indent = 2)).encode('utf-8'))
raise ValueError(u'{0} for: {1}'.format(
def main():
parser = argparse.ArgumentParser()
parser.add_argument('-s', '--source-dir', default = 'yaml-clean',
help = 'path of source directory containing clean IPP YAML files')
parser.add_argument('-t', '--target', default = 'ipp-tax-and-benefit-tables-to-openfisca-parameters.yaml',
help = 'path of generated YAML file containing the association between IPP fields to OpenFisca parameters')
parser.add_argument('-v', '--verbose', action = 'store_true', default = False, help = "increase output verbosity")
args = parser.parse_args()
logging.basicConfig(level = logging.DEBUG if args.verbose else logging.WARNING, stream = sys.stdout)
file_system_encoding = sys.getfilesystemencoding()
ipp_infos_by_value = {}
for source_dir_encoded, directories_name_encoded, filenames_encoded in os.walk(args.source_dir):
directories_name_encoded.sort()
for filename_encoded in sorted(filenames_encoded):
if not filename_encoded.endswith('.yaml'):
continue
filename = filename_encoded.decode(file_system_encoding)
sheet_name = os.path.splitext(filename)[0]
source_file_path_encoded = os.path.join(source_dir_encoded, filename_encoded)
relative_file_path_encoded = source_file_path_encoded[len(args.source_dir):].lstrip(os.sep)
relative_file_path = relative_file_path_encoded.decode(file_system_encoding)
if sheet_name.isupper():
continue
assert sheet_name.islower(), sheet_name
log.info(u'Loading file {}'.format(relative_file_path))
with open(source_file_path_encoded) as source_file:
data = yaml.load(source_file)
rows = data.get(u"Valeurs")
if rows is None:
log.info(u' Skipping file {} without "Valeurs"'.format(relative_file_path))
continue
for row in rows:
start = row.get(u"Date d'effet")
if start is None:
for date_name in date_names:
start = row.get(date_name)
if start is not None:
break
else:
# No date found. Skip row.
continue
elif not isinstance(start, datetime.date):
start = start[u"Année Revenus"]
for name, child in row.iteritems():
if name in date_names:
continue
for path, value in iter_ipp_values(child):
if isinstance(value, basestring):
split_value = value.split()
if len(split_value) == 2 and split_value[1] in (
u'%',
u'AF', # anciens francs
u'CFA', # francs CFA
u'COTISATIONS',
u'EUR',
u'FRF',
):
value = float(split_value[0])
if isinstance(value, float) and value == int(value):
value = int(value)
full_path = tuple(relative_file_path.split(os.sep)[:-1]) + (sheet_name, name) + tuple(path)
ipp_infos_by_value.setdefault(value, []).append(dict(
path = full_path,
start = start,
))
# print yaml.dump(ipp_infos_by_value, allow_unicode = True, default_flow_style = False, indent = 2, width = 120)
TaxBenefitSystem = init_country()
tax_benefit_system = TaxBenefitSystem()
# print yaml.dump(tax_benefit_system.legislation_json, allow_unicode = True, default_flow_style = False, indent = 2,
# width = 120)
# openfisca_infos_by_value = {}
# for path, start, value in iter_openfisca_values(tax_benefit_system.legislation_json):
# openfisca_infos_by_value.setdefault(value, []).append(dict(
# path = tuple(path),
# start = start,
# ))
# print yaml.dump(openfisca_infos_by_value, allow_unicode = True, default_flow_style = False, indent = 2, width = 120)
# ipp_count = {}
# for path, start, value in iter_openfisca_values(tax_benefit_system.legislation_json):
# ipp_infos = ipp_infos_by_value.get(value)
# if ipp_infos is None:
# # OpenFisca parameter doesn't exit in IPP.
# continue
# for ipp_info in ipp_infos:
# if ipp_info['start'] == start:
# ipp_child = ipp_count
# ipp_path = ipp_info['path']
# for name in path:
# ipp_child = ipp_child.setdefault(name, {})
# ipp_child_count = ipp_child.setdefault('count_by_path', {})
# for ipp_index in range(len(ipp_path)):
# ipp_sub_path = ipp_path[:ipp_index + 1]
# ipp_child_count[ipp_sub_path] = ipp_child_count.get(ipp_sub_path, 0) + 1
# print yaml.dump(ipp_count, allow_unicode = True, default_flow_style = False, indent = 2, width = 120)
starts_by_ipp_path_by_openfisca_path = {}
starts_by_openfisca_path_by_ipp_path = {}
for path, start, value in iter_openfisca_values(tax_benefit_system.legislation_json):
ipp_infos = ipp_infos_by_value.get(value)
if ipp_infos is None:
# OpenFisca parameter doesn't exit in IPP.
continue
same_start_ipp_paths = [
ipp_info['path']
for ipp_info in ipp_infos
if ipp_info['start'] == start
]
if len(same_start_ipp_paths) == 1:
ipp_path = same_start_ipp_paths[0]
starts_by_ipp_path_by_openfisca_path.setdefault(tuple(path), {}).setdefault(ipp_path, set()).add(start)
starts_by_openfisca_path_by_ipp_path.setdefault(ipp_path, {}).setdefault(tuple(path), set()).add(start)
# for openfisca_path, starts_by_ipp_path in sorted(starts_by_ipp_path_by_openfisca_path.iteritems()):
## if len(starts_by_ipp_path) == 1:
## print u'.'.join(openfisca_path), '->', u' / '.join(starts_by_ipp_path.keys()[0])
# if len(starts_by_ipp_path) > 1:
# print u'.'.join(openfisca_path), '->', starts_by_ipp_path
# for ipp_path, starts_by_openfisca_path in sorted(starts_by_openfisca_path_by_ipp_path.iteritems()):
# if len(starts_by_openfisca_path) == 1:
# print u' / '.join(ipp_path), '->', u'.'.join(
# unicode(fragment)
# for fragment in starts_by_openfisca_path.keys()[0]
# )
## if len(starts_by_openfisca_path) > 1:
## print u' / '.join(ipp_path), '->', u'.'.join(
## unicode(fragment)
## for fragment in starts_by_openfisca_path.keys()[0]
## )
openfisca_path_by_ipp_tree = collections.OrderedDict()
for ipp_path, starts_by_openfisca_path in sorted(starts_by_openfisca_path_by_ipp_path.iteritems()):
openfisca_path_by_ipp_sub_tree = openfisca_path_by_ipp_tree
for ipp_name in ipp_path[:-1]:
openfisca_path_by_ipp_sub_tree = openfisca_path_by_ipp_sub_tree.setdefault(ipp_name,
collections.OrderedDict())
ipp_name = ipp_path[-1]
openfisca_path_by_ipp_sub_tree[ipp_name] = [
u'.'.join(
unicode(fragment)
for fragment in openfisca_name
)
for openfisca_name in sorted(starts_by_openfisca_path)
]
with open(args.target, 'w') as target_file:
yaml.dump(openfisca_path_by_ipp_tree, target_file, allow_unicode = True, default_flow_style = False, indent = 2,
width = 120)
return 0
#
# OpenFisca is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
from __future__ import division
import sys
import logging
import openfisca_france
openfisca_france.init_country(start_from = "brut")
from openfisca_core.simulations import ScenarioSimulation
from openfisca_france.model.cotisations_sociales.travail import CAT
def test_case_study(year = 2013, verbose = False):
for type_sal_category in ['prive_non_cadre', 'prive_cadre', 'public_titulaire_etat']:
simulation = ScenarioSimulation()
maxrev = 24000
simulation.set_config(year = year, reforme = False, nmen = 1, x_axis = 'salbrut')
# Add husband/wife on the same tax sheet (foyer).
# simulation.scenario.addIndiv(1, datetime.date(1975, 1, 1), 'conj', 'part')
simulation.scenario.indiv[0]['salbrut'] = maxrev
simulation.scenario.indiv[0]['type_sal'] = CAT[type_sal_category]
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
from __future__ import division
import sys
import datetime
import logging
import nose
import pdb
import openfisca_france
openfisca_france.init_country(start_from = "brut")
from openfisca_core.simulations import ScenarioSimulation
from openfisca_france.model.cotisations_sociales.travail import CAT
def test_cotsoc_celib():
"""
test pour un célibataire
"""
# Comparaison avec la fiche de paie IPP calculé avec une cotisation transport correspondant à Paris ((.026)
# alors qu'Openfisca la cacule pour Lyon (.0175)
tests_list = [
# Célibataires (pas de supplément familial de traitement
{"year" : 2012,
"input_vars":
