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_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_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_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_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
]))
