def test_case_study(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"
'''
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 = 11, maxrev = maxrev, x_axis = 'salbrut')
simulation.scenario.indiv[0]['salbrut'] = maxrev
simulation.scenario.indiv[0]['type_sal'] = CAT[type_sal_category]
if type_sal_category == 'public_titulaire_etat':
from openfisca_france.model.cotisations_sociales.travail import TAUX_DE_PRIME
simulation.scenario.indiv[0]['primes'] = TAUX_DE_PRIME * maxrev
simulation.set_param()
# The aefa prestation can be disabled by uncommenting the following line:
# simulation.disable_prestations( ['aefa'])
df = simulation.get_results_dataframe(index_by_code = True)
from openfisca_france.model.inversion_revenus import _salbrut
df_b2i = df.transpose()
if verbose:
print df_b2i.to_string()
sali = df_b2i['sal'].get_values()
hsup = simulation.input_table.table['hsup'].get_values()
type_sal = simulation.input_table.table['type_sal'].get_values()
primes = simulation.input_table.table['hsup'].get_values()
defaultP = simulation.P_default
from pandas import DataFrame
df_i2b = DataFrame({'sal': sali, 'salbrut' : _salbrut(sali, hsup, type_sal, defaultP) })
if verbose:
print df_i2b.to_string()
for var in ['sal', 'salbrut']:
passed = ((df_b2i[var] - df_i2b[var]).abs() < .01).all()
if (not passed) or type_sal_category in ['public_titulaire_etat']:
print (df_b2i / 12).to_string()
print (df_i2b / 12).to_string()
assert passed, "difference in %s for %s" % (var, type_sal_category)
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"
'''
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 = 11, maxrev = maxrev, x_axis = 'salbrut')
simulation.scenario.indiv[0]['salbrut'] = maxrev
simulation.scenario.indiv[0]['type_sal'] = CAT[type_sal_category]
if type_sal_category == 'public_titulaire_etat':
from openfisca_france.model.cotisations_sociales.travail import TAUX_DE_PRIME
simulation.scenario.indiv[0]['primes'] = TAUX_DE_PRIME * maxrev
simulation.set_param()
df = simulation.get_results_dataframe(index_by_code = True)
from openfisca_france.model.inversion_revenus import _salbrut
df_b2i = df.transpose()
if verbose:
print df_b2i.to_string()
sali = df_b2i['sal'].get_values()
hsup = simulation.input_table.table['hsup'].get_values()
type_sal = simulation.input_table.table['type_sal'].get_values()
primes = simulation.input_table.table['hsup'].get_values()
defaultP = simulation.P_default
from pandas import DataFrame
df_i2b = DataFrame({'sal': sali, 'salbrut' : _salbrut(sali, hsup, type_sal, defaultP) })
if verbose:
print df_i2b.to_string()
for var in ['sal', 'salbrut']:
passed = ((df_b2i[var] - df_i2b[var]).abs() < .01).all()
if (not passed) or type_sal_category in ['public_titulaire_etat']:
print (df_b2i / 12).to_string()
print (df_i2b / 12).to_string()
assert passed, "difference in %s for %s" % (var, type_sal_category)
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(
birth = datetime.date(year - 40, 1, 1),
primes = TAUX_DE_PRIME * maxrev if type_sal_category == 'public_titulaire_etat' else None,
type_sal = CAT[type_sal_category],
),
year = year,
).new_simulation(debug = True)
df_b2i = DataFrame(dict(sal = simulation.calculate('sal'),
salbrut = simulation.calculate('salbrut'),
))
from openfisca_france.model.inversion_revenus import _salbrut
sali = df_b2i['sal'].get_values()
hsup = simulation.calculate('hsup')
type_sal = simulation.calculate('type_sal')
# primes = simulation.calculate('primes')
defaultP = simulation.default_compact_legislation
df_i2b = DataFrame({'sal': sali, 'salbrut' : _salbrut(sali, hsup, type_sal, defaultP) })
for var in ['sal', 'salbrut']:
passed = ((df_b2i[var] - df_i2b[var]).abs() < .01).all()
if (not passed) or type_sal_category in ['public_titulaire_etat'] or verbose:
print "Brut to imposable"
print (df_b2i[['salbrut', 'sal' ]] / 12).to_string()
print "Imposable to brut"
print (df_i2b / 12).to_string()
assert passed, "difference in %s for %s" % (var, type_sal_category)
