def test_parameters_get_default_start_year():
paramdata = Policy.default_data(metadata=True, start_year=2015)
# 1D data, has 2015 values
meta_II_em = paramdata['_II_em']
assert meta_II_em['start_year'] == 2015
assert meta_II_em['row_label'] == ['2015', '2016']
assert meta_II_em['value'] == [4000, 4050]
# 2D data, has 2015 values
meta_std_aged = paramdata['_STD_Aged']
assert meta_std_aged['start_year'] == 2015
assert meta_std_aged['row_label'] == ['2015', '2016']
assert meta_std_aged['value'] == [[1550, 1250, 1250, 1550, 1550, 1250],
[1550, 1250, 1250, 1550, 1550, 1250]]
# 1D data, doesn't have 2015 values, is CPI inflated
meta_amt_thd_marrieds = paramdata['_AMT_thd_MarriedS']
assert meta_amt_thd_marrieds['start_year'] == 2015
assert meta_amt_thd_marrieds['row_label'] == ['2015']
# Take the 2014 parameter value and multiply by inflation for that year
should_be = 41050 * (1.0 + Policy.default_inflation_rates()[2014])
meta_amt_thd_marrieds['value'] == should_be
# 1D data, doesn't have 2015 values, is not CPI inflated
meta_kt_c_age = paramdata['_KT_c_Age']
assert meta_kt_c_age['start_year'] == 2015
assert meta_kt_c_age['row_label'] == ['2015']
assert meta_kt_c_age['value'] == [24]
def test_parameters_get_default_start_year():
paramdata = Policy.default_data(metadata=True, start_year=2015)
# 1D data, has 2015 values
meta_II_em = paramdata['_II_em']
assert meta_II_em['start_year'] == 2015
assert meta_II_em['row_label'] == ['2015', '2016']
assert meta_II_em['value'] == [4000, 4050]
# 2D data, has 2015 values
meta_std_aged = paramdata['_STD_Aged']
assert meta_std_aged['start_year'] == 2015
assert meta_std_aged['row_label'] == ['2015', '2016']
assert meta_std_aged['value'] == [[1550, 1250, 1250, 1550, 1550, 1250],
[1550, 1250, 1250, 1550, 1550, 1250]]
# 1D data, doesn't have 2015 values, is CPI inflated
meta_amt_thd_marrieds = paramdata['_AMT_thd_MarriedS']
assert meta_amt_thd_marrieds['start_year'] == 2015
assert meta_amt_thd_marrieds['row_label'] == ['2015']
# Take the 2014 parameter value and multiply by inflation for that year
should_be = 41050 * (1.0 + Policy.default_inflation_rates()[2014])
meta_amt_thd_marrieds['value'] == should_be
# 1D data, doesn't have 2015 values, is not CPI inflated
meta_kt_c_age = paramdata['_KT_c_Age']
assert meta_kt_c_age['start_year'] == 2015
assert meta_kt_c_age['row_label'] == ['2015']
assert meta_kt_c_age['value'] == [24]
def test_create_parameters_from_file(policyfile):
with open(policyfile.name) as pfile:
policy = json.load(pfile)
ppo = Policy(parameter_dict=policy)
irates = Policy.default_inflation_rates()
inf_rates = [irates[ppo.start_year + i] for i in range(0, ppo.num_years)]
assert_allclose(ppo._almdep,
Policy.expand_array(np.array([7150, 7250, 7400]),
inflate=True,
inflation_rates=inf_rates,
num_years=ppo.num_years),
atol=0.01,
rtol=0.0)
assert_allclose(ppo._almsep,
Policy.expand_array(np.array([40400, 41050]),
inflate=True,
inflation_rates=inf_rates,
num_years=ppo.num_years),
atol=0.01,
rtol=0.0)
assert_allclose(ppo._rt5,
Policy.expand_array(np.array([0.33]),
inflate=False,
inflation_rates=inf_rates,
num_years=ppo.num_years),
atol=0.01,
rtol=0.0)
assert_allclose(ppo._rt7,
Policy.expand_array(np.array([0.396]),
inflate=False,
inflation_rates=inf_rates,
num_years=ppo.num_years),
atol=0.01,
rtol=0.0)
def test_create_parameters_from_file(policyfile):
with open(policyfile.name) as pfile:
policy = json.load(pfile)
ppo = Policy(parameter_dict=policy)
irates = Policy.default_inflation_rates()
inf_rates = [irates[ppo.start_year + i] for i in range(0, ppo.num_years)]
assert_allclose(ppo._almdep,
Policy.expand_array(np.array([7150, 7250, 7400]),
inflate=True,
inflation_rates=inf_rates,
num_years=ppo.num_years),
atol=0.01, rtol=0.0)
assert_allclose(ppo._almsep,
Policy.expand_array(np.array([40400, 41050]),
inflate=True,
inflation_rates=inf_rates,
num_years=ppo.num_years),
atol=0.01, rtol=0.0)
assert_allclose(ppo._rt5,
Policy.expand_array(np.array([0.33]),
inflate=False,
inflation_rates=inf_rates,
num_years=ppo.num_years),
atol=0.01, rtol=0.0)
assert_allclose(ppo._rt7,
Policy.expand_array(np.array([0.396]),
inflate=False,
inflation_rates=inf_rates,
num_years=ppo.num_years),
atol=0.01, rtol=0.0)
def test_expand_2D_accept_None():
_II_brk2 = [[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, None, None, None, None, None]]
exp1 = 74900 * 1.02
exp2 = 37450 * 1.02
exp3 = 50200 * 1.02
exp4 = 74900 * 1.02
exp5 = 37450 * 1.02
exp = [[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, exp1, exp2, exp3, exp4, exp5]]
exp = np.array(exp).astype('i4', casting='unsafe')
res = Policy.expand_array(_II_brk2, inflate=True,
inflation_rates=[0.02] * 5,
num_years=4)
npt.assert_array_equal(res, exp)
user_mods = {2016: {u'_II_brk2': _II_brk2}}
pol = Policy(start_year=2013)
pol.implement_reform(user_mods)
pol.set_year(2019)
irates = Policy.default_inflation_rates()
# The 2019 policy should be the combination of the user-defined
# value and CPI-inflated values from 2018
exp_2019 = [41000.] + [(1 + irates[2018]) * i for i in _II_brk2[2][1:]]
exp_2019 = np.array(exp_2019)
npt.assert_array_equal(pol.II_brk2, exp_2019)
def test_expand_2D_accept_None():
_II_brk2 = [[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, None, None, None, None, None]]
exp1 = 74900 * 1.02
exp2 = 37450 * 1.02
exp3 = 50200 * 1.02
exp4 = 74900 * 1.02
exp5 = 37450 * 1.02
exp = [[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, exp1, exp2, exp3, exp4, exp5]]
exp = np.array(exp).astype('i4', casting='unsafe')
res = Policy.expand_array(_II_brk2,
inflate=True,
inflation_rates=[0.02] * 5,
num_years=4)
npt.assert_array_equal(res, exp)
user_mods = {2016: {u'_II_brk2': _II_brk2}}
pol = Policy(start_year=2013)
pol.implement_reform(user_mods)
pol.set_year(2019)
irates = Policy.default_inflation_rates()
# The 2019 policy should be the combination of the user-defined
# value and CPI-inflated values from 2018
exp_2019 = [41000.] + [(1 + irates[2018]) * i for i in _II_brk2[2][1:]]
exp_2019 = np.array(exp_2019)
npt.assert_array_equal(pol.II_brk2, exp_2019)
def test_expand_2D_accept_None_additional_row():
_II_brk2 = [[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, None, None, None, None, None],
[43000, None, None, None, None, None]]
exp1 = 74900 * 1.02
exp2 = 37450 * 1.02
exp3 = 50200 * 1.02
exp4 = 74900 * 1.02
exp5 = 37450 * 1.02
exp6 = exp1 * 1.03
exp7 = exp2 * 1.03
exp8 = exp3 * 1.03
exp9 = exp4 * 1.03
exp10 = exp5 * 1.03
exp = [[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, exp1, exp2, exp3, exp4, exp5],
[43000, exp6, exp7, exp8, exp9, exp10]]
inflation_rates = [0.015, 0.02, 0.02, 0.03]
res = Policy.expand_array(_II_brk2,
inflate=True,
inflation_rates=inflation_rates,
num_years=5)
npt.assert_array_equal(res, exp)
user_mods = {2016: {u'_II_brk2': _II_brk2}}
pol = Policy(start_year=2013)
pol.implement_reform(user_mods)
pol.set_year(2020)
irates = Policy.default_inflation_rates()
# The 2020 policy should be the combination of the user-defined
# value and CPI-inflated values from 2018
exp_2020 = [43000.] + [(1 + irates[2019]) * (1 + irates[2018]) * i
for i in _II_brk2[2][1:]]
exp_2020 = np.array(exp_2020)
npt.assert_allclose(pol.II_brk2, exp_2020)
def test_expand_2D_accept_None_additional_row():
_II_brk2 = [
[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, None, None, None, None, None],
[43000, None, None, None, None, None],
]
exp1 = 74900 * 1.02
exp2 = 37450 * 1.02
exp3 = 50200 * 1.02
exp4 = 74900 * 1.02
exp5 = 37450 * 1.02
exp6 = exp1 * 1.03
exp7 = exp2 * 1.03
exp8 = exp3 * 1.03
exp9 = exp4 * 1.03
exp10 = exp5 * 1.03
exp = [
[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, exp1, exp2, exp3, exp4, exp5],
[43000, exp6, exp7, exp8, exp9, exp10],
]
inflation_rates = [0.015, 0.02, 0.02, 0.03]
res = Policy.expand_array(_II_brk2, inflate=True, inflation_rates=inflation_rates, num_years=5)
npt.assert_array_equal(res, exp)
user_mods = {2016: {u"_II_brk2": _II_brk2}}
pol = Policy(start_year=2013)
pol.implement_reform(user_mods)
pol.set_year(2020)
irates = Policy.default_inflation_rates()
# The 2020 policy should be the combination of the user-defined
# value and CPI-inflated values from 2018
exp_2020 = [43000.0] + [(1 + irates[2019]) * (1 + irates[2018]) * i for i in _II_brk2[2][1:]]
exp_2020 = np.array(exp_2020)
npt.assert_allclose(pol.II_brk2, exp_2020)
