def test_update_consumption():
consump = Consumption()
consump.update_consumption({})
revision = {
'MPC_e20400': {2014: 0.05,
2015: 0.06},
'BEN_mcare_value': {2014: 0.75,
2015: 0.80}
}
consump.update_consumption(revision)
expected_mpc_e20400 = np.full((Consumption.DEFAULT_NUM_YEARS,), 0.06)
expected_mpc_e20400[0] = 0.0
expected_mpc_e20400[1] = 0.05
assert np.allclose(consump._MPC_e20400,
expected_mpc_e20400,
rtol=0.0)
assert np.allclose(consump._MPC_e17500,
np.zeros((Consumption.DEFAULT_NUM_YEARS,)),
rtol=0.0)
expected_ben_mcare_value = np.full((Consumption.DEFAULT_NUM_YEARS,), 0.80)
expected_ben_mcare_value[0] = 1.0
expected_ben_mcare_value[1] = 0.75
assert np.allclose(consump._BEN_mcare_value,
expected_ben_mcare_value,
rtol=0.0)
assert np.allclose(consump._BEN_snap_value,
np.ones((Consumption.DEFAULT_NUM_YEARS,)),
rtol=0.0)
consump.set_year(2015)
assert consump.current_year == 2015
assert consump.MPC_e20400 == 0.06
assert consump.MPC_e17500 == 0.0
assert consump.BEN_mcare_value == 0.80
assert consump.BEN_snap_value == 1.0
def test_update_consumption():
consump = Consumption(start_year=2013)
consump.update_consumption({
2014: {
'_MPC_e20400': [0.05],
'_BEN_mcare_value': [0.75]
},
2015: {
'_MPC_e20400': [0.06],
'_BEN_mcare_value': [0.80]
}
})
expected_mpc_e20400 = np.full((Consumption.DEFAULT_NUM_YEARS, ), 0.06)
expected_mpc_e20400[0] = 0.0
expected_mpc_e20400[1] = 0.05
assert np.allclose(consump._MPC_e20400, expected_mpc_e20400, rtol=0.0)
assert np.allclose(consump._MPC_e17500,
np.zeros((Consumption.DEFAULT_NUM_YEARS, )),
rtol=0.0)
expected_ben_mcare_value = np.full((Consumption.DEFAULT_NUM_YEARS, ), 0.80)
expected_ben_mcare_value[0] = 1.0
expected_ben_mcare_value[1] = 0.75
assert np.allclose(consump._BEN_mcare_value,
expected_ben_mcare_value,
rtol=0.0)
assert np.allclose(consump._BEN_snap_value,
np.ones((Consumption.DEFAULT_NUM_YEARS, )),
rtol=0.0)
consump.set_year(2015)
assert consump.current_year == 2015
assert consump.MPC_e20400 == 0.06
assert consump.MPC_e17500 == 0.0
assert consump.BEN_mcare_value == 0.80
assert consump.BEN_snap_value == 1.0
def test_future_update_consumption():
consump = Consumption()
assert consump.current_year == consump.start_year
assert consump.has_response() is False
cyr = 2020
consump.set_year(cyr)
consump.update_consumption({cyr: {'_MPC_e20400': [0.01]}})
assert consump.current_year == cyr
assert consump.has_response() is True
consump.set_year(cyr - 1)
assert consump.has_response() is False
def test_future_update_consumption():
consump = Consumption()
assert consump.current_year == consump.start_year
assert consump.has_response() is False
cyr = 2020
consump.set_year(cyr)
consump.update_consumption({cyr: {"_MPC_e20400": [0.01]}})
assert consump.current_year == cyr
assert consump.has_response() is True
consump.set_year(cyr - 1)
assert consump.has_response() is False
def test_update_consumption():
consump = Consumption(start_year=2013)
consump.update_consumption({2014: {"_MPC_e20400": [0.05]}, 2015: {"_MPC_e20400": [0.06]}})
expected_mpc_e20400 = np.full((Consumption.DEFAULT_NUM_YEARS,), 0.06)
expected_mpc_e20400[0] = 0.0
expected_mpc_e20400[1] = 0.05
assert np.allclose(consump._MPC_e20400, expected_mpc_e20400, rtol=0.0)
assert np.allclose(consump._MPC_e17500, np.zeros((Consumption.DEFAULT_NUM_YEARS,)), rtol=0.0)
consump.set_year(2015)
assert consump.current_year == 2015
assert consump.MPC_e20400 == 0.06
assert consump.MPC_e17500 == 0.0
def test_update_consumption():
consump = Consumption(start_year=2013)
consump.update_consumption({2014: {'_MPC_e20400': [0.05]},
2015: {'_MPC_e20400': [0.06]}})
expected_mpc_e20400 = np.full((Consumption.DEFAULT_NUM_YEARS,), 0.06)
expected_mpc_e20400[0] = 0.0
expected_mpc_e20400[1] = 0.05
assert np.allclose(consump._MPC_e20400,
expected_mpc_e20400,
rtol=0.0)
assert np.allclose(consump._MPC_e17500,
np.zeros((Consumption.DEFAULT_NUM_YEARS,)),
rtol=0.0)
consump.set_year(2015)
assert consump.current_year == 2015
assert consump.MPC_e20400 == 0.06
assert consump.MPC_e17500 == 0.0
def test_update_consumption():
consump = Consumption()
consump.update_consumption({})
revision = {
'MPC_e20400': {
2014: 0.05,
2015: 0.06
},
'BEN_mcare_value': {
2014: 0.75,
2015: 0.80
}
}
consump.update_consumption(revision)
expected_mpc_e20400 = np.full((Consumption.DEFAULT_NUM_YEARS, ), 0.06)
expected_mpc_e20400[0] = 0.0
expected_mpc_e20400[1] = 0.05
assert np.allclose(consump._MPC_e20400, expected_mpc_e20400, rtol=0.0)
assert np.allclose(consump._MPC_e17500,
np.zeros((Consumption.DEFAULT_NUM_YEARS, )),
rtol=0.0)
expected_ben_mcare_value = np.full((Consumption.DEFAULT_NUM_YEARS, ), 0.80)
expected_ben_mcare_value[0] = 1.0
expected_ben_mcare_value[1] = 0.75
assert np.allclose(consump._BEN_mcare_value,
expected_ben_mcare_value,
rtol=0.0)
assert np.allclose(consump._BEN_snap_value,
np.ones((Consumption.DEFAULT_NUM_YEARS, )),
rtol=0.0)
consump.set_year(2015)
assert consump.current_year == 2015
assert consump.MPC_e20400 == 0.06
assert consump.MPC_e17500 == 0.0
assert consump.BEN_mcare_value == 0.80
assert consump.BEN_snap_value == 1.0
def test_future_update_consumption():
consump = Consumption()
assert consump.current_year == consump.start_year
assert consump.has_response() is False
cyr = 2020
consump.set_year(cyr)
consump.update_consumption({cyr: {'_MPC_e20400': [0.01]}})
assert consump.current_year == cyr
assert consump.has_response() is True
consump.set_year(cyr - 1)
assert consump.has_response() is False
# test future updates for benefits
consump_ben = Consumption()
assert consump_ben.current_year == consump_ben.start_year
assert consump_ben.has_response() is False
consump_ben.set_year(cyr)
consump_ben.update_consumption({cyr: {'_BEN_vet_value': [0.95]}})
assert consump_ben.current_year == cyr
assert consump_ben.has_response() is True
consump_ben.set_year(cyr - 1)
assert consump_ben.has_response() is False
def test_future_update_consumption():
consump = Consumption()
assert consump.current_year == consump.start_year
assert consump.has_response() is False
cyr = 2020
consump.set_year(cyr)
consump.update_consumption({'MPC_e20400': {cyr: 0.01}})
assert consump.current_year == cyr
assert consump.has_response() is True
consump.set_year(cyr - 1)
assert consump.has_response() is False
# test future updates for benefits
consump_ben = Consumption()
assert consump_ben.current_year == consump_ben.start_year
assert consump_ben.has_response() is False
consump_ben.set_year(cyr)
consump_ben.update_consumption({'BEN_vet_value': {cyr: 0.95}})
assert consump_ben.current_year == cyr
assert consump_ben.has_response() is True
consump_ben.set_year(cyr - 1)
assert consump_ben.has_response() is False
def test_json_file_contents(tests_path, fname):
"""
Check contents of JSON parameter files in Tax-Calculator/taxcalc directory.
"""
first_year = Policy.JSON_START_YEAR
last_known_year = Policy.LAST_KNOWN_YEAR # for indexed parameter values
known_years = set(range(first_year, last_known_year + 1))
long_params = [
'II_brk1', 'II_brk2', 'II_brk3', 'II_brk4', 'II_brk5', 'II_brk6',
'II_brk7', 'PT_brk1', 'PT_brk2', 'PT_brk3', 'PT_brk4', 'PT_brk5',
'PT_brk6', 'PT_brk7', 'PT_qbid_taxinc_thd', 'ALD_BusinessLosses_c',
'STD', 'II_em', 'II_em_ps', 'AMT_em', 'AMT_em_ps', 'AMT_em_pe',
'ID_ps', 'ID_AllTaxes_c'
]
# for TCJA-reverting long_params
long_known_years = set(range(first_year, last_known_year + 1))
long_known_years.add(2026)
# check elements in each parameter sub-dictionary
failures = ''
with open(os.path.join(tests_path, "..", fname)) as f:
allparams = json.loads(f.read())
for pname in allparams:
if pname == "schema":
continue
# check that param contains required keys
param = allparams[pname]
# check that indexable and indexed are False in many files
if fname != 'policy_current_law.json':
assert param.get('indexable', False) is False
assert param.get('indexed', False) is False
# check that indexable is True when indexed is True
if param.get('indexed', False) and not param.get('indexable', False):
msg = 'param:<{}>; indexed={}; indexable={}'
fail = msg.format(pname, param.get('indexed', False),
param.get('indexable', False))
failures += fail + '\n'
# check that indexable param has value_type float
if param.get('indexable', False) and param['type'] != 'float':
msg = 'param:<{}>; type={}; indexable={}'
fail = msg.format(pname, param['type'],
param.get('indexable', False))
failures += fail + '\n'
# ensure that indexable is False when value_type is not real
if param.get('indexable', False) and param['type'] != 'float':
msg = 'param:<{}>; indexable={}; type={}'
fail = msg.format(pname, param.get('indexable', False),
param['value_type'])
failures += fail + '\n'
if fname == "consumption.json":
o = Consumption()
elif fname == "policy_current_law.json":
o = Policy()
elif fname == "growdiff.json":
o = GrowDiff()
param_list = []
for k in o:
if k[0].isupper(): # find parameters by case of first letter
param_list.append(k)
for param in param_list:
for y in known_years:
o.set_year(y)
if np.isnan(getattr(o, param)).any():
msg = 'param:<{}>; not found in year={}'
fail = msg.format(param, y)
failures += fail + '\n'
if failures:
raise ValueError(failures)
