def test_corrections(): years = [2006, 2007, 2008, 2009] df = get_denombrements_fiscaux_data_frame(years=years) index_by_variable_name = create_index_by_variable_name(formula_by_variable_name, level_2_formula_by_variable_name) test_by_variable = dict( # Correction of f5io in 2008 in Agrégats IPP benefices_agricoles_forfait_imposables=[ {"year": 2006, "target": 896512850}, {"year": 2008, "target": 883970587}, ], benefices_agricoles_reels_imposables=[ {"year": 2006, "target": 5150417953}, {"year": 2008, "target": 6515953706}, ], benefices_agricoles_reels_sans_cga_imposables=[{"year": 2006, "target": 165830038}], benefices_agricoles_reels_deficits=[{"year": 2006, "target": 519217942}], benefices_agricoles_reels_sans_cga_deficits=[{"year": 2006, "target": 208934263}], deficits_industriels_commerciaux_professionnels=[{"year": 2006, "target": 1427052021}], deficits_industriels_commerciaux_non_professionnels=[{"year": 2006, "target": 301194784}], plus_values_mobilieres_stock_options=[{"year": 2008, "target": 228873359}], ) def assert_value_construction(variable_name, test): year = test["year"] target = test["target"] value = get_or_construct_value(df, variable_name, index_by_variable_name, years=years)[0].loc[year] assert all(value == target), "{} for {}: got {} instead of {}".format(variable_name, year, value.values, target) for variable_name, tests in test_by_variable.iteritems(): for test in tests: yield assert_value_construction, variable_name, test
def test_run_through(): years = [2006, 2007, 2008, 2009] df = get_denombrements_fiscaux_data_frame(years=years) index_by_variable_name = create_index_by_variable_name( formula_by_variable_name, level_2_formula_by_variable_name) variable_name = 'interets_imposes_au_prelevement_liberatoire' get_or_construct_value(df, variable_name, index_by_variable_name, years=years) variable_name = 'dividendes_imposes_au_prelevement_liberatoire' get_or_construct_value(df, variable_name, index_by_variable_name, years=years) variable_name = 'revenus_imposes_au_prelevement_liberatoire' get_or_construct_value(df, variable_name, index_by_variable_name, years=years, fill_value=0) variable_name = 'assurances_vie_imposees_au_prelevement_liberatoire' get_or_construct_value(df, variable_name, index_by_variable_name, years=years) variable_name = 'f2da' get_or_construct_value(df, variable_name, index_by_variable_name, years=years)
def test_run_through(): years = [2006, 2007, 2008, 2009] df = get_denombrements_fiscaux_data_frame(years=years) index_by_variable_name = create_index_by_variable_name(formula_by_variable_name, level_2_formula_by_variable_name) variable_name = "interets_imposes_au_prelevement_liberatoire" get_or_construct_value(df, variable_name, index_by_variable_name, years=years) variable_name = "dividendes_imposes_au_prelevement_liberatoire" get_or_construct_value(df, variable_name, index_by_variable_name, years=years) variable_name = "revenus_imposes_au_prelevement_liberatoire" get_or_construct_value(df, variable_name, index_by_variable_name, years=years, fill_value=0) variable_name = "assurances_vie_imposees_au_prelevement_liberatoire" get_or_construct_value(df, variable_name, index_by_variable_name, years=years) variable_name = "f2da" get_or_construct_value(df, variable_name, index_by_variable_name, years=years)
def test_run_through(): years = [2006, 2007, 2008, 2009, 2010, 2011] df = get_denombrements_fiscaux_data_frame(years=years) index_by_variable_name = create_index_by_variable_name( formula_by_variable_name, level_2_formula_by_variable_name) variable_name = 'interets_imposes_au_prelevement_liberatoire' get_or_construct_value(df, variable_name, index_by_variable_name, years=years) variable_name = 'dividendes_imposes_au_prelevement_liberatoire' get_or_construct_value(df, variable_name, index_by_variable_name, years=years) variable_name = 'revenus_imposes_au_prelevement_liberatoire' get_or_construct_value(df, variable_name, index_by_variable_name, years=years, fill_value=0) variable_name = 'assurances_vie_imposees_au_prelevement_liberatoire' get_or_construct_value(df, variable_name, index_by_variable_name, years=years) variable_name = 'f2da' get_or_construct_value(df, variable_name, index_by_variable_name, years=years) variable_name = u'f5he' get_or_construct_value(df, variable_name, index_by_variable_name, years=range(2010, 2012)) variable_name = u'f5jr' get_or_construct_value(df, variable_name, index_by_variable_name, years=range(2007, 2012), fill_value=0) variable_name = 'plus_values_professionnelles_regime_normal' get_or_construct_value(df, variable_name, index_by_variable_name, years=range(2007, 2012), fill_value=0)
def test_run_through(): years = [2006, 2007, 2008, 2009, 2010, 2011] df = get_denombrements_fiscaux_data_frame(years = years) index_by_variable_name = create_index_by_variable_name(formula_by_variable_name, level_2_formula_by_variable_name) variable_name = 'interets_imposes_au_prelevement_liberatoire' get_or_construct_value(df, variable_name, index_by_variable_name, years = years) variable_name = 'dividendes_imposes_au_prelevement_liberatoire' get_or_construct_value(df, variable_name, index_by_variable_name, years = years) variable_name = 'revenus_imposes_au_prelevement_liberatoire' get_or_construct_value(df, variable_name, index_by_variable_name, years = years, fill_value = 0) variable_name = 'assurances_vie_imposees_au_prelevement_liberatoire' get_or_construct_value(df, variable_name, index_by_variable_name, years = years) variable_name = 'f2da' get_or_construct_value(df, variable_name, index_by_variable_name, years = years) variable_name = u'f5he' get_or_construct_value(df, variable_name, index_by_variable_name, years = range(2010, 2012)) variable_name = u'f5jr' get_or_construct_value(df, variable_name, index_by_variable_name, years = range(2007, 2012), fill_value = 0) variable_name = 'plus_values_professionnelles_regime_normal' get_or_construct_value(df, variable_name, index_by_variable_name, years = range(2007, 2012), fill_value = 0)
def test_corrections(): years = [2006, 2007, 2008, 2009] df = get_denombrements_fiscaux_data_frame(years=years) index_by_variable_name = create_index_by_variable_name( formula_by_variable_name, level_2_formula_by_variable_name) test_by_variable = dict( # Correction of f5io in 2008 in Agrégats IPP benefices_agricoles_forfait_imposables=[ { 'year': 2006, 'target': 896512850 }, { 'year': 2008, 'target': 883970587 }, ], benefices_agricoles_reels_imposables=[ { 'year': 2006, 'target': 5150417953 }, { 'year': 2008, 'target': 6515953706 }, ], benefices_agricoles_reels_sans_cga_imposables=[ { 'year': 2006, 'target': 165830038 }, ], benefices_agricoles_reels_deficits=[ { 'year': 2006, 'target': 519217942 }, ], benefices_agricoles_reels_sans_cga_deficits=[ { 'year': 2006, 'target': 208934263 }, ], deficits_industriels_commerciaux_professionnels=[ { 'year': 2006, 'target': 1427052021 }, ], deficits_industriels_commerciaux_non_professionnels=[ { 'year': 2006, 'target': 301194784 }, ], plus_values_mobilieres_stock_options=[{ 'year': 2008, 'target': 228873359 }], ) def assert_value_construction(variable_name, test): year = test['year'] target = test['target'] value = get_or_construct_value(df, variable_name, index_by_variable_name, years=years)[0].loc[year] assert all(value == target), "{} for {}: got {} instead of {}".format( variable_name, year, value.values, target) for variable_name, tests in test_by_variable.iteritems(): for test in tests: yield assert_value_construction, variable_name, test
def test_corrections(): years = range(2006, 2013) df = get_denombrements_fiscaux_data_frame(years=years) index_by_variable_name = create_index_by_variable_name( formula_by_variable_name, level_2_formula_by_variable_name) test_by_variable = dict( # Correction of f5io in 2008 in Agrégats IPP benefices_agricoles_forfait_imposables=[ { 'year': 2006, 'target': 896512850 }, { 'year': 2008, 'target': 883970587 }, ], benefices_agricoles_reels_imposables=[ { 'year': 2006, 'target': 5150417953 }, { 'year': 2008, 'target': 6515953706 }, ], benefices_agricoles_reels_imposables_sans_cga=[ { 'year': 2006, 'target': 165830038 }, ], benefices_agricoles_reels_deficits=[ { 'year': 2006, 'target': 519217942 }, ], benefices_agricoles_reels_sans_cga_deficits=[ { 'year': 2006, 'target': 208934263 }, ], deficits_industriels_commerciaux_professionnels=[ { 'year': 2006, 'target': 1427052021 }, ], deficits_industriels_commerciaux_non_professionnels=[ { 'year': 2006, 'target': 301194784 }, ], plus_values_mobilieres_stock_options=[ { 'year': 2008, 'target': 228873359 }, # {'year': 2010, 'target': 690459289}, TODO: check dénombremenst DGFIP vs IPP ], revenus_imposes_au_bareme=[ { 'year': 2010, 'target': 18907148239 }, ], plus_values_mobilieres_regime_normal=[ { 'year': 2010, 'target': 5393808406 }, ], plus_values_professionnelles_regime_normal=[ { 'year': 2011, 'target': 1101248065 }, { 'year': 2010, 'target': 1083102431 }, ], # Inversion 2ch et 2gr dans dénombrements fiscax (Agrégats IPP et en ligne) assurances_vie_imposees_au_bareme=[ { 'year': 2009, 'target': 1063726777 }, ], # Test revenus exonérés benefices_agricoles_forfait_exoneres=[ { 'year': 2011, 'target': (5826752 + 466632 + 467) }, ], benefices_agricoles_reels_exoneres=[ { 'year': 2011, 'target': (64880784 + 15074222 + 3733) }, ], benefices_agricoles_reels_exoneres_sans_cga=[ { 'year': 2011, 'target': (10214497 + 2275427 + 171787) }, ], ) def assert_value_construction(variable_name, test): year = test['year'] target = test['target'] value = get_or_construct_value(df, variable_name, index_by_variable_name, years=years, fill_value=0)[0].loc[year] if year >= 2009: assert all( value == target), "{} for {}: got {} instead of {}".format( variable_name, year, value.values, target) for variable_name, tests in test_by_variable.iteritems(): for test in tests: yield assert_value_construction, variable_name, test
def test_corrections(): years = range(2006, 2013) df = get_denombrements_fiscaux_data_frame(years = years) index_by_variable_name = create_index_by_variable_name(formula_by_variable_name, level_2_formula_by_variable_name) test_by_variable = dict( # Correction of f5io in 2008 in Agrégats IPP benefices_agricoles_forfait_imposables = [ {'year': 2006, 'target': 896512850}, {'year': 2008, 'target': 883970587}, ], benefices_agricoles_reels_imposables = [ {'year': 2006, 'target': 5150417953}, {'year': 2008, 'target': 6515953706}, ], benefices_agricoles_reels_imposables_sans_cga = [ {'year': 2006, 'target': 165830038}, ], benefices_agricoles_reels_deficits = [ {'year': 2006, 'target': 519217942}, ], benefices_agricoles_reels_sans_cga_deficits = [ {'year': 2006, 'target': 208934263}, ], deficits_industriels_commerciaux_professionnels = [ {'year': 2006, 'target': 1427052021}, ], deficits_industriels_commerciaux_non_professionnels = [ {'year': 2006, 'target': 301194784}, ], plus_values_mobilieres_stock_options = [ {'year': 2008, 'target': 228873359}, # {'year': 2010, 'target': 690459289}, TODO: check dénombremenst DGFIP vs IPP ], revenus_imposes_au_bareme = [ {'year': 2010, 'target': 18907148239}, ], plus_values_mobilieres_regime_normal = [ {'year': 2010, 'target': 5393808406}, ], plus_values_professionnelles_regime_normal = [ {'year': 2011, 'target': 1101248065}, {'year': 2010, 'target': 1083102431}, ], # Inversion 2ch et 2gr dans dénombrements fiscax (Agrégats IPP et en ligne) assurances_vie_imposees_au_bareme = [ {'year': 2009, 'target': 1063726777}, ], # Test revenus exonérés benefices_agricoles_forfait_exoneres = [ {'year': 2011, 'target': (5826752 + 466632 + 467)}, ], benefices_agricoles_reels_exoneres = [ {'year': 2011, 'target': (64880784 + 15074222 + 3733)}, ], benefices_agricoles_reels_exoneres_sans_cga = [ {'year': 2011, 'target': (10214497 + 2275427 + 171787)}, ], ) def assert_value_construction(variable_name, test): year = test['year'] target = test['target'] value = get_or_construct_value( df, variable_name, index_by_variable_name, years = years, fill_value = 0)[0].loc[year] if year >= 2009: assert all(value == target), "{} for {}: got {} instead of {}".format( variable_name, year, value.values, target) for variable_name, tests in test_by_variable.iteritems(): for test in tests: yield assert_value_construction, variable_name, test