def test():
country = "france"
population_filename = os.path.join(SRC_PATH, 'countries', country,
'sources', 'data_fr', 'proj_pop_insee',
'proj_pop.h5')
profiles_filename = os.path.join(SRC_PATH, 'countries', country, 'sources',
'data_fr', 'NTA', 'nta.h5')
simulation = Simulation()
population_scenario = "projpop0760_FECbasESPbasMIGbas"
simulation.load_population(population_filename, population_scenario)
simulation.load_profiles(profiles_filename)
#Setting parameters
year_length = 200
r = 0.03
g = 0.01
n = 0.00
net_gov_wealth = -3217.7e+09
net_gov_spendings = 0
simulation.set_population_projection(year_length=year_length,
method="stable")
simulation.set_tax_projection(method="per_capita", rate=g)
simulation.set_growth_rate(g)
simulation.set_discount_rate(r)
simulation.set_population_growth_rate(n)
simulation.profiles = simulation.profiles.xs(1979, axis=0, level="year")
simulation.profiles.reset_index(inplace=True)
simulation.profiles['year'] = 1979
simulation.profiles.set_index(['age', 'sex', 'year'], inplace=True)
# simulation.profiles = simulation.profiles.ix[(0,0,1979):(100,1,1979)]
simulation.create_cohorts()
simulation.set_population_projection()
print simulation.cohorts
def test():
country = "france"
population_filename = os.path.join(SRC_PATH, 'countries', country, 'sources',
'data_fr', 'proj_pop_insee', 'proj_pop.h5')
profiles_filename = os.path.join(SRC_PATH, 'countries', country, 'sources',
'data_fr','NTA', 'nta.h5')
simulation = Simulation()
population_scenario = "projpop0760_FECbasESPbasMIGbas"
simulation.load_population(population_filename, population_scenario)
simulation.load_profiles(profiles_filename)
#Setting parameters
year_length = 200
r = 0.03
g = 0.01
n = 0.00
net_gov_wealth = -3217.7e+09
net_gov_spendings = 0
simulation.set_population_projection(year_length=year_length, method="stable")
simulation.set_tax_projection(method="per_capita", rate=g)
simulation.set_growth_rate(g)
simulation.set_discount_rate(r)
simulation.set_population_growth_rate(n)
simulation.profiles = simulation.profiles.xs(1979,axis=0,level="year")
simulation.profiles.reset_index(inplace=True)
simulation.profiles['year']=1979
simulation.profiles.set_index(['age', 'sex', 'year'], inplace=True)
# simulation.profiles = simulation.profiles.ix[(0,0,1979):(100,1,1979)]
simulation.create_cohorts()
simulation.set_population_projection()
print simulation.cohorts
def test_comparison():
population_dataframe = create_testing_population_dataframe(year_start=2001,
year_end=2261,
population=2)
profiles_dataframe = create_constant_profiles_dataframe(
population_dataframe, tax=1)
r = 0.00
g = 0.00
n = 0.00
simulation = Simulation()
simulation.population = population_dataframe
simulation.population_alt = population_dataframe
simulation.profiles = profiles_dataframe
net_gov_wealth = -10
net_gov_spending = 0
taxes_list = ['tax']
payments_list = ['sub']
simulation.set_population_projection(year_length=simulation.year_length,
method="exp_growth")
simulation.set_tax_projection(method="per_capita", rate=g)
simulation.set_growth_rate(g)
simulation.set_discount_rate(r)
simulation.set_population_growth_rate(n)
simulation.set_gov_wealth(net_gov_wealth)
simulation.set_gov_spendings(net_gov_spending, default=True)
simulation.create_cohorts()
simulation.create_present_values(typ='tax')
simulation.cohorts_alt = simulation.cohorts
simulation.cohorts_alt.loc[
[x == 2102 for x in simulation.cohorts_alt.index.get_level_values(2)],
'tax'] = (-100)
simulation.create_present_values(typ='tax', default=False)
ipl_base = simulation.compute_ipl(typ='tax')
ipl_alt = simulation.compute_ipl(typ='tax', default=False, precision=False)
#Saving the decomposed ipl:
to_save = simulation.break_down_ipl(typ='tax', default=False, threshold=60)
# to_save = age_class_pv
xls = "C:/Users/Utilisateur/Documents/GitHub/ga/src/countries/france/sources/Carole_Bonnet/choc_test_alt.xlsx"
to_save.to_excel(xls, 'ipl')
print ipl_base
print ipl_alt
assert ipl_base == -105232
def test_comparison():
population_dataframe = create_testing_population_dataframe(year_start=2001, year_end=2261, population=2)
profiles_dataframe = create_constant_profiles_dataframe(population_dataframe, tax=1)
r = 0.00
g = 0.00
n = 0.00
simulation = Simulation()
simulation.population = population_dataframe
simulation.population_alt = population_dataframe
simulation.profiles = profiles_dataframe
net_gov_wealth = -10
net_gov_spending = 0
taxes_list = ['tax']
payments_list = ['sub']
simulation.set_population_projection(year_length=simulation.year_length, method="exp_growth")
simulation.set_tax_projection(method="per_capita", rate=g)
simulation.set_growth_rate(g)
simulation.set_discount_rate(r)
simulation.set_population_growth_rate(n)
simulation.set_gov_wealth(net_gov_wealth)
simulation.set_gov_spendings(net_gov_spending, default=True)
simulation.create_cohorts()
simulation.create_present_values(typ='tax')
simulation.cohorts_alt = simulation.cohorts
simulation.cohorts_alt.loc[[x==2102 for x in simulation.cohorts_alt.index.get_level_values(2)], 'tax'] = (-100)
simulation.create_present_values(typ='tax', default=False)
ipl_base = simulation.compute_ipl(typ='tax')
ipl_alt = simulation.compute_ipl(typ='tax', default=False, precision=False)
#Saving the decomposed ipl:
to_save = simulation.break_down_ipl(typ='tax', default=False, threshold=60)
# to_save = age_class_pv
xls = os.path.join(SRC_PATH, 'test_comparison.xlsx')
to_save.to_excel(xls, 'ipl')
print ipl_base
print ipl_alt
assert ipl_base == -105232
