def test_target():
# Calculator
records_x = Records(data=TAXDATA, weights=WEIGHTS, start_year=2009)
policy_x = Policy()
growth_x = Growth()
calc_x = Calculator(policy=policy_x, records=records_x,
growth=growth_x)
# set target
factor_x = {2015: {'_factor_target': [0.04]}}
growth_x.update_economic_growth(factor_x)
AGDPN_pre = calc_x.records.BF.AGDPN[2015]
ATXPY_pre = calc_x.records.BF.ATXPY[2015]
target(calc_x, growth_x._factor_target, 2015)
distance = ((growth_x._factor_target[2015 - 2013] -
Growth.default_real_GDP_growth_rate(2015 - 2013)) /
calc_x.records.BF.APOPN[2015])
AGDPN_post = AGDPN_pre + distance
ATXPY_post = ATXPY_pre + distance
assert calc_x.records.BF.AGDPN[2015] == AGDPN_post
assert calc_x.records.BF.ATXPY[2015] == ATXPY_post
def test_make_calculator_with_growth(records_2009):
grow = Growth()
calc = Calculator(policy=Policy(), records=records_2009, growth=grow)
assert calc.current_year == 2013
assert isinstance(calc, Calculator)
# test correct Growth instantiation with dictionary
grow = Growth(growth_dict=dict())
assert isinstance(grow, Growth)
# test incorrect Growth instantiation
with pytest.raises(ValueError):
grow = Growth(growth_dict=list())
with pytest.raises(ValueError):
grow = Growth(num_years=0)
def main():
parser = argparse.ArgumentParser(
prog="python stats_summary.py",
description=('Generates a files for either statistics summary'
'on a 10-year span or correlation matrix of current'
'tax year. Adding either sum-stats or correlation'
'as an argument after python Stats_Summary.py --output'))
parser.add_argument('--output', default='sum-stats')
args = parser.parse_args()
# create a calculator
tax_dta1 = pd.read_csv(PUF_PATH)
records1 = Records(tax_dta1)
policy1 = Policy(start_year=2013)
growth1 = Growth()
calc1 = Calculator(records=records1, policy=policy1)
table = creat_table_base(records=records1)
if args.output == 'sum-stats':
gen_sum_stats(table, calc=calc1)
elif args.output == 'correlation':
gen_correlation(table, calc=calc1)
else:
print("no such output available")
return 0
def test_make_calculator_with_growth():
# create a Records and Params object
records_x = Records(data=TAXDATA, weights=WEIGHTS, start_year=2009)
records_y = Records(data=TAXDATA, weights=WEIGHTS, start_year=2009)
policy_x = Policy()
policy_y = Policy()
# create two Calculators
growth_x = Growth()
growth_y = Growth()
calc_x = Calculator(policy=policy_x, records=records_x, growth=growth_x)
calc_y = Calculator(policy=policy_y, records=records_y, growth=growth_y)
assert calc_x.current_year == 2013
assert isinstance(calc_x, Calculator)
assert isinstance(calc_y, Calculator)
def test_factor_target(records_2009):
calc = Calculator(policy=Policy(), records=records_2009, growth=Growth())
AGDPN_pre = calc.records.BF.AGDPN[2015]
ATXPY_pre = calc.records.BF.ATXPY[2015]
# specify _factor_target
ft2015 = 0.04
factor_target = {2015: {'_factor_target': [ft2015]}}
calc.growth.update_economic_growth(factor_target)
assert calc.current_year == 2013
calc.increment_year()
calc.increment_year()
assert calc.current_year == 2015
distance = ((ft2015 - Growth.default_real_gdp_growth_rate(2015 - 2013)) /
calc.records.BF.APOPN[2015])
AGDPN_post = AGDPN_pre + distance
ATXPY_post = ATXPY_pre + distance
assert calc.records.BF.AGDPN[2015] == AGDPN_post
assert calc.records.BF.ATXPY[2015] == ATXPY_post
def test_update_growth():
records_x = Records(data=TAXDATA, weights=WEIGHTS, start_year=2009)
records_y = Records(data=TAXDATA, weights=WEIGHTS, start_year=2009)
policy_x = Policy()
policy_y = Policy()
# change growth adjustment/target
growth_x = Growth()
factor_x = {2015: {'_factor_target': [0.04]}}
growth_x.update_economic_growth(factor_x)
growth_y = Growth()
factor_y = {2015: {'_factor_adjustment': [0.01]}}
growth_y.update_economic_growth(factor_y)
# create two Calculators
calc_x = Calculator(policy=policy_x, records=records_x,
growth=growth_x)
calc_y = Calculator(policy=policy_y, records=records_y,
growth=growth_y)
assert_array_equal(calc_x.growth.factor_target,
growth_x.factor_target)
assert_array_equal(calc_x.growth._factor_target,
np.array([0.0226, 0.0241, 0.04, 0.04, 0.04,
0.04, 0.04, 0.04, 0.04, 0.04, 0.04,
0.04, 0.04, 0.04]))
assert_array_equal(calc_y.growth.factor_adjustment,
growth_y.factor_adjustment)
assert_array_equal(calc_y.growth._factor_adjustment,
np.array([0.0, 0.0, 0.01, 0.01, 0.01, 0.01,
0.01, 0.01, 0.01, 0.01, 0.01, 0.01,
0.01, 0.01]))
def test_factor_adjustment(records_2009):
calc = Calculator(policy=Policy(), records=records_2009, growth=Growth())
ATXPY_pre = calc.records.BF.ATXPY[2015]
AGDPN_pre = calc.records.BF.AGDPN[2015]
# specify _factor_adjustment
fa2015 = 0.01
factor_adj = {2015: {'_factor_adjustment': [fa2015]}}
calc.growth.update_economic_growth(factor_adj)
assert calc.current_year == 2013
calc.increment_year()
calc.increment_year()
assert calc.current_year == 2015
assert calc.records.BF.AGDPN[2015] == AGDPN_pre + fa2015
assert calc.records.BF.ATXPY[2015] == ATXPY_pre + fa2015
def test_target():
# Calculator
records_x = Records(data=TAXDATA, weights=WEIGHTS, start_year=2009)
policy_x = Policy()
growth_x = Growth()
calc_x = Calculator(policy=policy_x, records=records_x, growth=growth_x)
# set target
factor_x = {2015: {'_factor_target': [0.04]}}
growth_x.update_economic_growth(factor_x)
AGDPN_pre = calc_x.records.BF.AGDPN[2015]
ATXPY_pre = calc_x.records.BF.ATXPY[2015]
target(calc_x, growth_x._factor_target, 2015)
distance = ((growth_x._factor_target[2015 - 2013] -
Growth.default_real_GDP_growth_rate(2015 - 2013)) /
calc_x.records.BF.APOPN[2015])
AGDPN_post = AGDPN_pre + distance
ATXPY_post = ATXPY_pre + distance
assert calc_x.records.BF.AGDPN[2015] == AGDPN_post
assert calc_x.records.BF.ATXPY[2015] == ATXPY_post
def test_factor_target(records_2009):
calc = Calculator(policy=Policy(), records=records_2009, growth=Growth())
AGDPN_pre = calc.records.BF.AGDPN[2015]
ATXPY_pre = calc.records.BF.ATXPY[2015]
# specify _factor_target
ft2015 = 0.04
factor_target = {2015: {'_factor_target': [ft2015]}}
calc.growth.update_economic_growth(factor_target)
assert calc.current_year == 2013
calc.increment_year()
calc.increment_year()
assert calc.current_year == 2015
distance = ((ft2015 - Growth.default_real_gdp_growth_rate(2015 - 2013)) /
calc.records.BF.APOPN[2015])
AGDPN_post = AGDPN_pre + distance
ATXPY_post = ATXPY_pre + distance
assert calc.records.BF.AGDPN[2015] == AGDPN_post
assert calc.records.BF.ATXPY[2015] == ATXPY_post
def test_update_growth():
records_x = Records(data=TAXDATA, weights=WEIGHTS, start_year=2009)
records_y = Records(data=TAXDATA, weights=WEIGHTS, start_year=2009)
policy_x = Policy()
policy_y = Policy()
# change growth adjustment/target
growth_x = Growth()
factor_x = {2015: {'_factor_target': [0.04]}}
growth_x.update_economic_growth(factor_x)
growth_y = Growth()
factor_y = {2015: {'_factor_adjustment': [0.01]}}
growth_y.update_economic_growth(factor_y)
# create two Calculators
calc_x = Calculator(policy=policy_x, records=records_x, growth=growth_x)
calc_y = Calculator(policy=policy_y, records=records_y, growth=growth_y)
assert_array_equal(calc_x.growth.factor_target, growth_x.factor_target)
assert_array_equal(
calc_x.growth._factor_target,
np.array([
0.0226, 0.0241, 0.04, 0.04, 0.04, 0.04, 0.04, 0.04, 0.04, 0.04,
0.04, 0.04, 0.04, 0.04
]))
assert_array_equal(calc_y.growth.factor_adjustment,
growth_y.factor_adjustment)
assert_array_equal(
calc_y.growth._factor_adjustment,
np.array([
0.0, 0.0, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01,
0.01, 0.01, 0.01
]))
def test_update_growth():
# try incorrect updates
grow = Growth()
with pytest.raises(ValueError):
grow.update_economic_growth({2013: list()})
with pytest.raises(ValueError):
grow.update_economic_growth({2013: {'bad_name': [0.02]}})
with pytest.raises(ValueError):
grow.update_economic_growth({2013: {'bad_name_cpi': True}})
bad_params = {2015: {'_factor_adjustment': [0.01],
'_factor_target': [0.08]}}
with pytest.raises(ValueError):
grow.update_economic_growth(bad_params)
# try correct updates
grow_x = Growth()
factor_x = {2015: {'_factor_target': [0.04]}}
grow_x.update_economic_growth(factor_x)
grow_y = Growth()
factor_y = {2015: {'_factor_adjustment': [0.01]}}
grow_y.update_economic_growth(factor_y)
# create two Calculators
recs_x = Records(data=TAXDATA, weights=WEIGHTS, start_year=2009)
recs_y = Records(data=TAXDATA, weights=WEIGHTS, start_year=2009)
calc_x = Calculator(policy=Policy(), records=recs_x, growth=grow_x)
calc_y = Calculator(policy=Policy(), records=recs_y, growth=grow_y)
assert_array_equal(calc_x.growth.factor_target,
grow_x.factor_target)
assert_array_equal(calc_x.growth._factor_target,
np.array([0.0226, 0.0241, 0.04, 0.04, 0.04,
0.04, 0.04, 0.04, 0.04, 0.04, 0.04,
0.04, 0.04, 0.04]))
assert_array_equal(calc_y.growth.factor_adjustment,
grow_y.factor_adjustment)
assert_array_equal(calc_y.growth._factor_adjustment,
np.array([0.0, 0.0, 0.01, 0.01, 0.01, 0.01,
0.01, 0.01, 0.01, 0.01, 0.01, 0.01,
0.01, 0.01]))
def test_growth_default_data():
paramdata = Growth.default_data()
assert paramdata['_factor_adjustment'] == [0.0]
def test_hard_coded_gdp_growth():
growth = Growth()
assert_array_equal(growth._factor_target,
np.array(Growth.REAL_GDP_GROWTH_RATES))
def test_growth_default_data():
paramdata = Growth.default_data()
assert paramdata['_factor_adjustment'] == [0.0]
def test_update_growth(puf_1991, weights_1991):
# try incorrect updates
grow = Growth()
with pytest.raises(ValueError):
grow.update_economic_growth({2013: list()})
with pytest.raises(ValueError):
grow.update_economic_growth({2013: {'bad_name': [0.02]}})
with pytest.raises(ValueError):
grow.update_economic_growth({2013: {'bad_name_cpi': True}})
bad_params = {
2015: {
'_factor_adjustment': [0.01],
'_factor_target': [0.08]
}
}
with pytest.raises(ValueError):
grow.update_economic_growth(bad_params)
# try correct updates
grow_x = Growth()
factor_x = {2015: {'_factor_target': [0.04]}}
grow_x.update_economic_growth(factor_x)
grow_y = Growth()
factor_y = {2015: {'_factor_adjustment': [0.01]}}
grow_y.update_economic_growth(factor_y)
# create two Calculators
recs_x = Records(data=puf_1991, weights=weights_1991, start_year=2009)
recs_y = Records(data=puf_1991, weights=weights_1991, start_year=2009)
calc_x = Calculator(policy=Policy(), records=recs_x, growth=grow_x)
calc_y = Calculator(policy=Policy(), records=recs_y, growth=grow_y)
assert_array_equal(calc_x.growth.factor_target, grow_x.factor_target)
assert_array_equal(
calc_x.growth._factor_target,
np.array([
0.0226, 0.0241, 0.04, 0.04, 0.04, 0.04, 0.04, 0.04, 0.04, 0.04,
0.04, 0.04, 0.04, 0.04
]))
assert_array_equal(calc_y.growth.factor_adjustment,
grow_y.factor_adjustment)
assert_array_equal(
calc_y.growth._factor_adjustment,
np.array([
0.0, 0.0, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01,
0.01, 0.01, 0.01
]))
