"""
Tax-Calculator GrowFactors class.
"""
# CODING-STYLE CHECKS:
# pycodestyle growfactors.py
# pylint --disable=locally-disabled growfactors.py
import os
import numpy as np
import pandas as pd
from taxcalc.utils import read_egg_csv
[docs]
class GrowFactors():
"""
Constructor for the GrowFactors class.
Parameters
----------
growfactors_filename: None or string
string is path to the CSV file in which grow factors reside;
default value of None uses file containing puf/cps grow factors.
Raises
------
ValueError:
if growfactors_filename is neither None or a string.
if growfactors_filename string points to a non-existent file.
Returns
-------
class instance: GrowFactors
Notes
-----
Typical usage is "gfactor = GrowFactors()", which produces an object
containing baseline growth factors in the GrowFactors.FILE_NAME file,
which is for use with puf and cps data from the taxdata repository.
"""
PACKAGE_FILE_NAMES = ['growfactors.csv']
FILE_PATH = os.path.abspath(os.path.dirname(__file__))
VALID_NAMES = set(['ABOOK', 'ACGNS', 'ACPIM', 'ACPIU',
'ADIVS', 'AINTS',
'AIPD', 'ASCHCI', 'ASCHCL',
'ASCHEI', 'ASCHEL', 'ASCHF',
'ASOCSEC', 'ATXPY', 'AUCOMP', 'AWAGE',
'ABENOTHER', 'ABENMCARE', 'ABENMCAID',
'ABENSSI', 'ABENSNAP', 'ABENWIC',
'ABENHOUSING', 'ABENTANF', 'ABENVET'])
def __init__(self, growfactors_filename=None):
# read grow factors from specified growfactors_filename
gfdf = pd.DataFrame()
if growfactors_filename is None:
# read puf/cps growfactors from package
gfdf = read_egg_csv(GrowFactors.PACKAGE_FILE_NAMES[0],
index_col='YEAR') # pragma: no cover
elif isinstance(growfactors_filename, str):
if growfactors_filename in GrowFactors.PACKAGE_FILE_NAMES:
# read growfactors from package
gfdf = read_egg_csv(growfactors_filename,
index_col='YEAR') # pragma: no cover
else:
if os.path.isfile(growfactors_filename):
gfdf = pd.read_csv(growfactors_filename, index_col='YEAR')
else: # file does not exist
msg = (
f'growfactors file {growfactors_filename} '
'does not exist'
)
raise ValueError(msg)
else:
raise ValueError('growfactors_filename is not a string')
assert isinstance(gfdf, pd.DataFrame)
# check validity of gfdf column names
gfdf_names = set(list(gfdf))
if gfdf_names != GrowFactors.VALID_NAMES:
msg = 'missing names are: {} and invalid names are: {}'
missing = GrowFactors.VALID_NAMES - gfdf_names
invalid = gfdf_names - GrowFactors.VALID_NAMES
raise ValueError(msg.format(missing, invalid))
# determine first_year and last_year from gfdf
self._first_year = min(gfdf.index)
self._last_year = max(gfdf.index)
# set gfdf as attribute of class
self.gfdf = pd.DataFrame()
setattr(self, 'gfdf', gfdf.astype(np.float64))
del gfdf
# specify factors as being unused (that is, not yet accessed)
self.used = False
@property
def first_year(self):
"""
GrowFactors class first_year property.
"""
return self._first_year
@property
def last_year(self):
"""
GrowFactors class last_year property.
"""
return self._last_year
[docs]
def price_inflation_rates(self, firstyear, lastyear):
"""
Return list of price inflation rates rounded to four decimal digits.
"""
self.used = True
if firstyear > lastyear:
msg = 'first_year={} > last_year={}'
raise ValueError(msg.format(firstyear, lastyear))
if firstyear < self.first_year:
msg = 'firstyear={} < GrowFactors.first_year={}'
raise ValueError(msg.format(firstyear, self.first_year))
if lastyear > self.last_year:
msg = 'last_year={} > GrowFactors.last_year={}'
raise ValueError(msg.format(lastyear, self.last_year))
rates = [round((self.gfdf['ACPIU'][cyr] - 1.0), 4)
for cyr in range(firstyear, lastyear + 1)]
return rates
[docs]
def wage_growth_rates(self, firstyear, lastyear):
"""
Return list of wage growth rates rounded to four decimal digits.
"""
self.used = True
if firstyear > lastyear:
msg = 'firstyear={} > lastyear={}'
raise ValueError(msg.format(firstyear, lastyear))
if firstyear < self.first_year:
msg = 'firstyear={} < GrowFactors.first_year={}'
raise ValueError(msg.format(firstyear, self.first_year))
if lastyear > self.last_year:
msg = 'lastyear={} > GrowFactors.last_year={}'
raise ValueError(msg.format(lastyear, self.last_year))
rates = [round((self.gfdf['AWAGE'][cyr] - 1.0), 4)
for cyr in range(firstyear, lastyear + 1)]
return rates
[docs]
def factor_value(self, name, year):
"""
Return value of factor with specified name for specified year.
"""
self.used = True
if name not in GrowFactors.VALID_NAMES:
msg = 'name={} not in GrowFactors.VALID_NAMES'
raise ValueError(msg.format(year, name))
if year < self.first_year:
msg = 'year={} < GrowFactors.first_year={}'
raise ValueError(msg.format(year, self.first_year))
if year > self.last_year:
msg = 'year={} > GrowFactors.last_year={}'
raise ValueError(msg.format(year, self.last_year))
return self.gfdf.loc[year, name]
[docs]
def update(self, name, year, diff):
"""
Add to self.gfdf (for name and year) the specified diff amount.
"""
if self.used:
msg = 'cannot update growfactors after they have been used'
raise ValueError(msg)
assert name in GrowFactors.VALID_NAMES
if year >= self.first_year and year <= self.last_year:
assert isinstance(diff, float)
self.gfdf.loc[year, name] += diff
