"""
Tax-Calculator Input-Output class.
"""
# CODING-STYLE CHECKS:
# pycodestyle taxcalcio.py
# pylint --disable=locally-disabled taxcalcio.py
# pylint: disable=too-many-lines
import os
import gc
import copy
import sqlite3
from pathlib import Path
import numpy as np
import pandas as pd
import paramtools
import behresp
from taxcalc.policy import Policy
from taxcalc.records import Records
from taxcalc.consumption import Consumption
from taxcalc.growdiff import GrowDiff
from taxcalc.growfactors import GrowFactors
from taxcalc.calculator import Calculator
from taxcalc.utils import (json_to_dict, delete_file, write_graph_file,
add_quantile_table_row_variable,
unweighted_sum, weighted_sum)
TMD_ASSUMES_FULL_CREDIT_CLAIMING = True
TMD_CREDIT_CLAIMING = {
# IMPORTANT NOTE: when changing either TMDCSV_YEAR or _claim_thd value(s),
# be sure to update changed info in the Tax-Calculator-LLM CLAUDE.md file.
'eitc_claim_thd': {f'{Records.TMDCSV_YEAR}': 1600},
'actc_claim_thd': {f'{Records.TMDCSV_YEAR}': 1500},
}
[docs]
class TaxCalcIO():
"""
Constructor for the Tax-Calculator Input-Output class.
TaxCalcIO class constructor call must be followed by init() call.
Parameters
----------
input_data: string or Pandas DataFrame
string is name of INPUT file that is CSV formatted containing
variable names in the Records USABLE_READ_VARS set, or
Pandas DataFrame is INPUT data containing variable names in
the Records USABLE_READ_VARS set. INPUT vsrisbles not in the
Records USABLE_READ_VARS set can be present but are ignored.
tax_year: integer
calendar year for which taxes will be computed for INPUT.
baseline: None or string
None implies baseline policy is current-law policy, or
string is name of optional BASELINE file that is a JSON
reform file.
reform: None or string
None implies no policy reform (current-law policy), or
string is name of optional REFORM file(s).
assump: None or string
None implies economic assumptions are standard assumptions,
or string is name of optional ASSUMP file.
behavior: None or string
None implies behavioral response elasticities are all zero,
or string is name of optional BEHAVIOR file.
runid: int
run id value to use for simpler output file names
silent: boolean
whether or not to suppress action messages.
Returns
-------
class instance: TaxCalcIO
"""
# pylint: disable=too-many-instance-attributes
def __init__(self, input_data, tax_year, baseline, reform,
assump, behavior, runid=0, silent=True):
# pylint: disable=too-many-arguments,too-many-positional-arguments
# pylint: disable=too-many-branches,too-many-statements,too-many-locals
self.silent = silent
self.gf_reform = None
self.errmsg = ''
# check name and existence of INPUT file
inp = 'x'
self.cps_input_data = False
self.puf_input_data = False
self.tmd_input_data = False
if isinstance(input_data, str):
# remove any leading directory path from INPUT filename
fname = os.path.basename(input_data)
# check if fname ends with ".csv"
if fname.endswith('.csv'):
inp = f'{fname[:-4]}-{str(tax_year)[2:]}'
else:
msg = 'INPUT file name does not end in .csv'
self.errmsg += f'ERROR: {msg}\n'
# check existence of INPUT file
self.cps_input_data = input_data.endswith('cps.csv')
self.puf_input_data = input_data.endswith('puf.csv')
self.tmd_input_data = input_data.endswith('tmd.csv')
if not self.cps_input_data and not os.path.isfile(input_data):
msg = 'INPUT file could not be found'
self.errmsg += f'ERROR: {msg}\n'
# if puf_input_data is True, construct weights and ratios paths
if self.puf_input_data: # pragma: no cover
puf_dir = os.path.dirname(input_data)
self.puf_weights = os.path.join(puf_dir, 'puf_weights.csv.gz')
self.puf_ratios = os.path.join(puf_dir, 'puf_ratios.csv')
if not os.path.isfile(self.puf_weights):
msg = f'weights file {self.puf_weights} could not be found'
self.errmsg += f'ERROR: {msg}\n'
if not os.path.isfile(self.puf_ratios):
msg = f'gfactor file {self.puf_ratios} could not be found'
self.errmsg += f'ERROR: {msg}\n'
# if tmd_input_data is True, construct weights and gfactor paths
if self.tmd_input_data: # pragma: no cover
tmd_dir = os.path.dirname(input_data)
if 'TMD_AREA' in os.environ:
area = os.environ['TMD_AREA']
wfile = f'{area}_tmd_weights.csv.gz'
inp = f'{fname[:-4]}_{area}-{str(tax_year)[2:]}'
else: # using national weights
wfile = 'tmd_weights.csv.gz'
self.tmd_weights = os.path.join(tmd_dir, wfile)
self.tmd_gfactor = os.path.join(tmd_dir, 'tmd_growfactors.csv')
if not os.path.isfile(self.tmd_weights):
msg = f'weights file {self.tmd_weights} could not be found'
self.errmsg += f'ERROR: {msg}\n'
if not os.path.isfile(self.tmd_gfactor):
msg = f'gfactor file {self.tmd_gfactor} could not be found'
self.errmsg += f'ERROR: {msg}\n'
elif isinstance(input_data, pd.DataFrame):
inp = f'df-{str(tax_year)[2:]}'
else:
msg = 'INPUT is neither string nor Pandas DataFrame'
self.errmsg += f'ERROR: {msg}\n'
# check name(s) and existence of BASELINE file(s)
if baseline is None:
self.specified_baseline = False
bas = '-#'
elif isinstance(baseline, str):
self.specified_baseline = True
bas = self._check_policy_files(baseline, 'BASELINE')
else:
bas = '-x'
msg = 'TaxCalcIO.ctor: baseline is neither None nor str'
self.errmsg += f'ERROR: {msg}\n'
# check name(s) and existence of REFORM file(s)
if reform is None:
self.specified_reform = False
ref = '-#'
elif isinstance(reform, str):
self.specified_reform = True
ref = self._check_policy_files(reform, 'REFORM')
else:
ref = '-x'
msg = 'TaxCalcIO.ctor: reform is neither None nor str'
self.errmsg += f'ERROR: {msg}\n'
# check name and existence of ASSUMP file
if assump is None:
asm = '-#'
elif isinstance(assump, str):
asm = self._check_single_json_file(assump, 'ASSUMP')
else:
asm = '-x'
msg = 'TaxCalcIO.ctor: assump is neither None nor str'
self.errmsg += f'ERROR: {msg}\n'
# check name and existence of BEHAVIOR file
self.behvdict = None
if behavior is None:
beh = '-#'
elif isinstance(behavior, str):
beh = self._check_single_json_file(behavior, 'BEHAVIOR')
else:
beh = '-x'
msg = 'TaxCalcIO.ctor: behavior is neither None nor str'
self.errmsg += f'ERROR: {msg}\n'
# create OUTPUT file name and delete any existing output files
self.output_filename = f'{inp}{bas}{ref}{asm}{beh}.xxx'
self.runid = runid
if runid > 0:
self.output_filename = f'run{runid}-{str(tax_year)[2:]}.xxx'
self.delete_output_files()
# initialize variables whose values are set in init method
self.pol_ref = None
self.pol_bas = None
self.recs_ref = None
self.recs_bas = None
self.con = None
self.aging_input_data = None
self.calc_ref = None
self.calc_bas = None
def delete_output_files(self):
"""
Delete all output files derived from self.output_filename.
"""
extensions = [
'-params.baseline',
'-params.reform',
'.tables',
'-atr.html',
'-mtr.html',
'-chg.html',
'.dumpdb',
]
for ext in extensions:
delete_file(self.output_filename.replace('.xxx', ext))
def init(self, input_data, tax_year, baseline, reform,
assump, behavior, exact_calculations):
"""
TaxCalcIO class post-constructor method that completes initialization.
Parameters
----------
First six are same as the first six of the TaxCalcIO constructor:
input_data, tax_year, baseline, reform, assump, behavior.
exact_calculations: boolean
specifies whether or not exact tax calculations are done without
any smoothing of "stair-step" provisions in the tax law.
"""
# pylint: disable=too-many-arguments,too-many-positional-arguments
# pylint: disable=too-many-statements,too-many-branches,too-many-locals
self.errmsg = ''
# instantiate base/reform GrowFactors objects used for param indexing
policy_gfactors_bas = GrowFactors()
policy_gfactors_ref = GrowFactors()
# instantiate base/reform GrowFactors objects used to extrapolate data
if self.tmd_input_data:
gfactors_bas = GrowFactors(self.tmd_gfactor) # pragma: no cover
gfactors_ref = GrowFactors(self.tmd_gfactor) # pragma: no cover
else:
gfactors_bas = GrowFactors()
gfactors_ref = GrowFactors()
# check tax_year validity
max_tax_year = gfactors_bas.last_year
if tax_year > max_tax_year:
msg = f'TAXYEAR={tax_year} is greater than {max_tax_year}'
self.errmsg += f'ERROR: {msg}\n'
if self.puf_input_data:
min_tax_year = max( # pragma: no cover
Policy.JSON_START_YEAR, Records.PUFCSV_YEAR)
elif self.cps_input_data:
min_tax_year = max(
Policy.JSON_START_YEAR, Records.CPSCSV_YEAR)
elif self.tmd_input_data:
min_tax_year = max( # pragma: no cover
Policy.JSON_START_YEAR, Records.TMDCSV_YEAR)
else:
min_tax_year = Policy.JSON_START_YEAR
if tax_year < min_tax_year:
msg = f'TAXYEAR={tax_year} is less than {min_tax_year}'
self.errmsg += f'ERROR: {msg}\n'
# tax_year out of valid range means cannot proceed with calculations
if self.errmsg:
return
# get assumption sub-dictionaries
assumpdict = Calculator.read_json_param_objects(None, assump)
# get behavior dictionary
if behavior:
with open(behavior, 'r', encoding='utf-8') as jfile:
json_text = jfile.read()
try:
self.behvdict = json_to_dict(json_text)
except ValueError as valerr: # pragma: no cover
msg = f'{behavior} contains invalid JSON'
self.errmsg = f'ERROR: BEHAVIOR file {msg}\n'
self.errmsg += f'{valerr}'
return
# check behavior response elasticity names and values
elasticity_set = set(self.behvdict.keys())
if elasticity_set != set(['sub', 'inc', 'cg']):
msg = f'{behavior} contains extra or missing elasticities'
self.errmsg = f'ERROR: BEHAVIOR file {msg}\n'
self.errmsg += 'Valid elasticities are "sub", "inc", "cg"'
return
if self.behvdict['sub'] < 0.0:
msg = f'{behavior} contains negative "sub" elasticity'
self.errmsg = f'ERROR: BEHAVIOR file {msg}\n'
if self.behvdict['inc'] > 0.0:
msg = f'{behavior} contains positive "inc" elasticity'
self.errmsg += f'ERROR: BEHAVIOR file {msg}\n'
if self.behvdict['cg'] > 0.0:
msg = f'{behavior} contains positive "cg" elasticity'
self.errmsg += f'ERROR: BEHAVIOR file {msg}\n'
if self.errmsg:
return
# get policy parameter dictionaries from --baseline file(s)
poldicts_bas = []
if self.specified_baseline:
for bas in baseline.split('+'):
pdict = Calculator.read_json_param_objects(bas, None)
poldicts_bas.append(pdict['policy'])
# get policy parameter dictionaries from --reform file(s)
poldicts_ref = []
if self.specified_reform:
for ref in reform.split('+'):
pdict = Calculator.read_json_param_objects(ref, None)
poldicts_ref.append(pdict['policy'])
# set last_b_year
last_b_year = max(tax_year, Policy.LAST_BUDGET_YEAR)
# create gdiff_baseline object
gdiff_baseline = GrowDiff(last_budget_year=last_b_year)
try:
gdiff_baseline.update_growdiff(assumpdict['growdiff_baseline'])
except paramtools.ValidationError as valerr_msg:
self.errmsg += str(valerr_msg)
# apply gdiff_baseline to gfactor_bas
gdiff_baseline.apply_to(gfactors_bas)
# specify gdiff_response object
gdiff_response = GrowDiff(last_budget_year=last_b_year)
try:
gdiff_response.update_growdiff(assumpdict['growdiff_response'])
except paramtools.ValidationError as valerr_msg:
self.errmsg += str(valerr_msg)
# apply gdiff_baseline and gdiff_response to gfactor_ref
gdiff_baseline.apply_to(gfactors_ref)
gdiff_response.apply_to(gfactors_ref)
self.gf_reform = copy.deepcopy(gfactors_ref)
# create Policy objects:
# ... apply gdiff_baseline to policy_gfactor_baseline
gdiff_baseline.apply_to(policy_gfactors_bas)
# ... apply gdiff_baseline and gdiff_response to policy_gfactor_ref
gdiff_baseline.apply_to(policy_gfactors_ref)
gdiff_response.apply_to(policy_gfactors_ref)
# ... the baseline Policy object
self.pol_bas = self._make_policy(policy_gfactors_bas, last_b_year)
if self.specified_baseline:
self._apply_poldicts(self.pol_bas, poldicts_bas)
# ... the reform Policy object (no reform implies reform == baseline)
if self.specified_reform:
self.pol_ref = self._make_policy(policy_gfactors_ref, last_b_year)
self._apply_poldicts(self.pol_ref, poldicts_ref)
else:
self.pol_ref = self._make_policy(policy_gfactors_bas, last_b_year)
# create Consumption object
self.con = Consumption(last_budget_year=last_b_year)
try:
self.con.update_consumption(assumpdict['consumption'])
except paramtools.ValidationError as valerr_msg:
self.errmsg += str(valerr_msg)
# any errors imply cannot proceed with calculations
if self.errmsg:
return
# set policy to tax_year
self.pol_ref.set_year(tax_year)
self.pol_bas.set_year(tax_year)
# read input file contents into Records objects
self.aging_input_data = (
self.cps_input_data or
self.puf_input_data or
self.tmd_input_data
)
if self.aging_input_data:
self.recs_ref = self._make_records(
gfactors_ref, input_data, tax_year, exact_calculations,
)
self.recs_bas = self._make_records(
gfactors_bas, input_data, tax_year, exact_calculations,
)
# extrapolate input data to tax_year
while self.recs_ref.current_year < tax_year:
self.recs_ref.increment_year()
self.recs_bas.increment_year()
else: # input_data are raw data that are not being aged
self.recs_ref = self._make_records(
None, input_data, tax_year, exact_calculations,
)
self.recs_bas = copy.deepcopy(self.recs_ref)
# create Calculator objects
self.calc_ref = self._make_calculator(
self.pol_ref, self.recs_ref, not self.silent,
)
self.calc_bas = self._make_calculator(
self.pol_bas, self.recs_bas, False,
)
[docs]
def tax_year(self):
"""
Return calendar year for which TaxCalcIO calculations are being done.
"""
return self.calc_ref.current_year
[docs]
def output_filepath(self):
"""
Return full path to output file named in TaxCalcIO constructor.
"""
dirpath = os.path.abspath(os.path.dirname(__file__))
return os.path.join(dirpath, self.output_filename)
def advance_to_year(self, year):
"""
Update self.output_filename and create Calculator objects for year.
"""
# update self.output_filename and delete output files
parts = self.output_filename.split('-')
if self.runid == 0: # if using legacy output file names
parts[1] = str(year)[2:]
else: # if using simpler output file names (runN-YY.xxx)
subparts = parts[1].split('.')
subparts[0] = str(year)[2:]
parts[1] = '.'.join(subparts)
self.output_filename = '-'.join(parts)
self.delete_output_files()
# create baseline and reform Calculator objects for specified year
# ... set policy for year
self.pol_ref.set_year(year)
self.pol_bas.set_year(year)
# ... set consumption for year
self.con.set_year(year)
# ... increment records to year
self.recs_ref.increment_year()
self.recs_bas.increment_year()
# ... delete old and create new Calculator objects
del self.calc_ref
self.calc_ref = self._make_calculator(
self.pol_ref, self.recs_ref, False,
)
del self.calc_bas
self.calc_bas = self._make_calculator(
self.pol_bas, self.recs_bas, False,
)
# report advance to new year
aging_data = (
self.cps_input_data or
self.puf_input_data or
self.tmd_input_data
)
idata = 'Advance input data and' if aging_data else 'Advance'
if not self.silent:
print(f'{idata} policy to {year}')
[docs]
def analyze(
self,
output_params=False,
output_tables=False,
output_graphs=False,
output_dump=False,
dump_varlist=None,
):
"""
Conduct tax analysis.
Parameters
----------
output_params: boolean
whether or not to write baseline and reform policy parameter
values to separate text files
output_tables: boolean
whether or not to generate and write distributional tables
to a text file
output_graphs: boolean
whether or not to generate and write HTML graphs of average
and marginal tax rates by income percentile
output_dump: boolean
whether or not to write SQLite3 database with baseline and
reform tables each containing the variables in dump_varlist.
dump_varlist: list
list of variables to include in dumpdb output;
list must include at least one variable.
Returns
-------
Nothing
"""
# pylint: disable=too-many-arguments,too-many-positional-arguments
# pylint: disable=too-many-branches,too-many-locals
doing_calcs = output_tables or output_graphs or output_dump
# optionally write --params output to text files
if output_params:
self.write_policy_params_files()
if not doing_calcs:
return
# do output calculations
if self.behvdict: # if assuming behavioral responses
br_dump_bas, br_dump_ref = behresp.response(
self.calc_bas, self.calc_ref,
self.behvdict, dump=True,
)
# copy returned dump dataframe values back into calc objects
self._copy_dump_into_calc(self.calc_bas, br_dump_bas)
del br_dump_bas
self._copy_dump_into_calc(self.calc_ref, br_dump_ref)
del br_dump_ref
else: # if assuming no behavioral responses
self.calc_bas.calc_all()
self.calc_ref.calc_all()
# handle MTR output variables
mtr_ptax_bas = None
mtr_itax_bas = None
mtr_ptax_ref = None
mtr_itax_ref = None
if output_dump:
assert isinstance(dump_varlist, list)
assert len(dump_varlist) > 0
mtr_output = (
'mtr_itax' in dump_varlist or
'mtr_ptax' in dump_varlist
)
if mtr_output:
(mtr_ptax_bas, mtr_itax_bas,
_) = self.calc_bas.mtr(
wrt_full_compensation=False,
calc_all_already_called=True)
(mtr_ptax_ref, mtr_itax_ref,
_) = self.calc_ref.mtr(
wrt_full_compensation=False,
calc_all_already_called=True)
# optionally write --tables output to text file
if output_tables:
self._write_tables_file()
# optionally write --graphs output to HTML files
if output_graphs:
self._write_graph_files()
# optionally write --dumpdb output to SQLite database file
if output_dump:
self._write_dumpdb_file(
dump_varlist,
mtr_ptax_ref, mtr_itax_ref,
mtr_ptax_bas, mtr_itax_bas,
)
def write_policy_params_files(self):
"""
Write baseline and reform policy parameter values to separate files.
"""
self._write_params(self.calc_bas, '-params.baseline', 'baseline')
self._write_params(self.calc_ref, '-params.reform', 'reform')
BASE_DUMPVARS = [
'RECID',
's006',
'data_source',
'XTOT',
'MARS',
'expanded_income',
]
MINIMAL_DUMPVARS = [
'RECID',
'iitax',
]
MTR_DUMPVARS = [
'mtr_itax',
'mtr_ptax',
]
def dump_variables(self, dumpvars_str):
"""
Return list of variable names extracted from dumpvars_str, plus
minimal baseline/reform variables even if not in dumpvars_str.
Also, builds self.errmsg if any specified variables are not valid.
"""
assert isinstance(dumpvars_str, str)
self.errmsg = ''
# get read and calc Records variables
recs_vinfo = Records(data=None) # contains records VARINFO only
valid_set = recs_vinfo.USABLE_READ_VARS | recs_vinfo.CALCULATED_VARS
# construct dumpvars list
if dumpvars_str == 'ALL':
dumpvars = list(valid_set) + TaxCalcIO.MTR_DUMPVARS
else:
# ... change some common non-space delimiter characters into spaces
dumpvars_str = dumpvars_str.replace(',', ' ')
dumpvars_str = dumpvars_str.replace(';', ' ')
dumpvars_str = dumpvars_str.replace('|', ' ')
# ... split dumpvars_str into dumpvars list
dumpvars = dumpvars_str.split()
# ... check that all dumpvars items are valid
for var in dumpvars:
if var not in valid_set and var not in TaxCalcIO.MTR_DUMPVARS:
msg = f'invalid variable name {var} in DUMPVARS file'
self.errmsg += f'ERROR: {msg}\n'
if self.errmsg:
return []
# construct variable list
dumpvars_list = list(TaxCalcIO.MINIMAL_DUMPVARS)
for var in dumpvars:
if var not in dumpvars_list and var not in TaxCalcIO.BASE_DUMPVARS:
dumpvars_list.append(var)
return dumpvars_list
# --- Begin private methods of the TaxCalcIO class --- #
def _check_policy_files(self, filespec, label):
"""
Check validity of the (possibly compound) BASELINE or REFORM filespec,
appending any errors to self.errmsg, and return the name fragment used
in constructing output file names.
"""
names = []
for path in filespec.split('+'):
# remove any leading directory path from filename
fname = os.path.basename(path)
# check if fname ends with ".json"
if not fname.endswith('.json'):
self.errmsg += (
f'ERROR: {label} file name {fname} does not end in .json\n'
)
# check existence of file
if os.path.isfile(path):
# check validity of JSON text
with open(path, 'r', encoding='utf-8') as jfile:
json_text = jfile.read()
try:
_ = json_to_dict(json_text)
except ValueError as valerr: # pragma: no cover
msg = f'{path} contains invalid JSON'
self.errmsg += f'ERROR: {label} file {msg}\n'
self.errmsg += f'{valerr}'
else:
msg = f'{path} could not be found'
self.errmsg += f'ERROR: {label} file {msg}\n'
# add fname to list of names used in output file names
names.append(fname)
# return (possibly compound) name fragment for output file names
return '-' + '+'.join(name[:-5] for name in names)
def _check_single_json_file(self, path, label):
"""
Check name and existence of the single ASSUMP or BEHAVIOR file,
appending any errors to self.errmsg, and return the name fragment
used in constructing output file names.
"""
# remove any leading directory path from filename
fname = os.path.basename(path)
# check if fname ends with ".json"
if fname.endswith('.json'):
fragment = f'-{fname[:-5]}'
else:
fragment = '-x'
self.errmsg += f'ERROR: {label} file name does not end in .json\n'
# check existence of file
if not os.path.isfile(path):
self.errmsg += f'ERROR: {label} file could not be found\n'
return fragment
def _make_policy(self, policy_gfactors, last_b_year):
"""
Return Policy object that uses the specified growfactors and that
optionally implements TMD credit-claiming thresholds.
"""
pol = Policy(
gfactors=policy_gfactors,
last_budget_year=last_b_year,
)
if self.tmd_input_data: # pragma: no cover
if not TMD_ASSUMES_FULL_CREDIT_CLAIMING:
pol.implement_reform(TMD_CREDIT_CLAIMING)
return pol
def _apply_poldicts(self, pol, poldicts):
"""
Implement each reform dict in poldicts on the pol Policy object,
appending any parameter errors to self.errmsg.
"""
for poldict in poldicts:
try:
pol.implement_reform(
poldict,
print_warnings=True,
raise_errors=False,
)
if self.errmsg:
self.errmsg += '\n'
for _, errors in pol.parameter_errors.items():
self.errmsg += '\n'.join(errors)
except paramtools.ValidationError as valerr_msg:
self.errmsg += str(valerr_msg)
def _make_records(self, gfactors, input_data,
tax_year, exact_calculations):
"""
Construct and return a Records object using the specified gfactors
and the input data type implied by the constructor arguments.
"""
# pylint: disable=too-many-arguments,too-many-positional-arguments
if self.cps_input_data:
return Records.cps_constructor(
gfactors=gfactors,
exact_calculations=exact_calculations,
)
if self.puf_input_data: # pragma: no cover
return Records.puf_constructor(
data=input_data,
gfactors=gfactors,
weights=self.puf_weights,
ratios=self.puf_ratios,
exact_calculations=exact_calculations,
)
if self.tmd_input_data: # pragma: no cover
return Records.tmd_constructor(
data_path=Path(input_data),
weights_path=Path(self.tmd_weights),
growfactors=gfactors,
exact_calculations=exact_calculations,
)
# input_data are raw data that are not being aged
return Records(
data=input_data,
start_year=tax_year,
gfactors=None,
weights=None,
adjust_ratios=None,
exact_calculations=exact_calculations,
)
def _make_calculator(self, policy, records, verbose):
"""
Construct and return a Calculator object from the specified policy
and records objects.
"""
return Calculator(
policy=policy,
records=records,
verbose=verbose,
consumption=self.con,
sync_years=self.aging_input_data,
)
def _copy_dump_into_calc(self, calc, br_dump):
"""
Copy behavioral-response dump DataFrame values back into the calc
object, skipping the marginal-tax-rate columns.
"""
int_variables = self.recs_bas.INTEGER_VARS
vnames = list(br_dump.columns)
for mtr_vname in ['mtr_ptax', 'mtr_itax', 'mtr_combined']:
if mtr_vname in vnames:
vnames.remove(mtr_vname)
for vname in vnames:
if vname in int_variables:
vdtype = np.int32
else:
vdtype = np.float64
calc.array(
vname,
br_dump[vname].to_numpy(dtype=vdtype, copy=True)
)
def _write_params(self, calc, ext, label):
"""
Write policy parameter values from calc to the ext output file.
"""
year = calc.current_year
fname = self.output_filename.replace('.xxx', ext)
with open(fname, 'w', encoding='utf-8') as pfile:
for pname in Policy.parameter_list():
pval = calc.policy_param(pname)
pfile.write(f'{year} {pname} {pval}\n')
if not self.silent:
print( # pragma: no cover
f'Write {label} policy parameter values to file {fname}'
)
def _write_tables_file(self):
"""
Write tables to text file.
"""
# pylint: disable=too-many-locals
tab_fname = self.output_filename.replace('.xxx', '.tables')
# skip tables if there are not some positive weights
if self.calc_bas.total_weight() <= 0.:
with open(tab_fname, 'w', encoding='utf-8') as tfile:
msg = 'No tables because sum of weights is not positive\n'
tfile.write(msg)
return
# create list of results for nontax variables
# - weights don't change with reform
# - expanded_income may change, so always use baseline expanded income
nontax_vars = ['s006', 'expanded_income']
nontax = [self.calc_bas.array(var) for var in nontax_vars]
# create list of results for tax variables from reform Calculator
tax_vars = ['iitax', 'payrolltax', 'lumpsum_tax', 'combined']
reform = [self.calc_ref.array(var) for var in tax_vars]
# create DataFrame with tax distribution under reform
dist = nontax + reform # using expanded_income under baseline policy
all_vars = nontax_vars + tax_vars
distdf = pd.DataFrame(data=np.column_stack(dist), columns=all_vars)
# create DataFrame with tax differences (reform - baseline)
base = [self.calc_bas.array(var) for var in tax_vars]
change = [(reform[idx] - base[idx]) for idx in range(0, len(tax_vars))]
diff = nontax + change # using expanded_income under baseline policy
diffdf = pd.DataFrame(data=np.column_stack(diff), columns=all_vars)
# write each kind of distributional table
year = self.calc_bas.current_year
with open(tab_fname, 'w', encoding='utf-8') as tfile:
TaxCalcIO._write_decile_table(
distdf,
tfile,
year,
tkind='Reform Totals',
)
tfile.write('\n')
TaxCalcIO._write_decile_table(
diffdf,
tfile,
year,
tkind='Differences',
)
# delete intermediate DataFrame objects
del distdf
del diffdf
gc.collect()
if not self.silent:
print( # pragma: no cover
f'Write tabular output to file {tab_fname}'
)
@staticmethod
def _write_decile_table(dfx, tfile, year, tkind='Totals'):
"""
Write to tfile the tkind decile table using dfx DataFrame.
"""
dfx = add_quantile_table_row_variable(dfx, 'expanded_income', 10,
decile_details=False,
pop_quantiles=False,
weight_by_income_measure=False)
# each table column: variable, aggregator, scale, header, units
wsum = weighted_sum
usum = unweighted_sum
columns = [
('s006', usum, 1e-6, ' Returns', ' (#m)'),
('expanded_income', wsum, 1e-9, ' ExpInc', ' ($b)'),
('iitax', wsum, 1e-9, ' IncTax', ' ($b)'),
('payrolltax', wsum, 1e-9, ' PayTax', ' ($b)'),
('lumpsum_tax', wsum, 1e-9, ' LSTax', ' ($b)'),
('combined', wsum, 1e-9, ' AllTax', ' ($b)'),
]
gdfx = dfx.groupby('table_row', as_index=False, observed=True)
series = [
gdfx.apply(agg, var, include_groups=False).values[:, 1]
for var, agg, _, _, _ in columns
]
scales = [scale for _, _, scale, _, _ in columns]
# write decile table to text file
row = (
f'Weighted Tax {tkind} by '
f'Baseline Expanded-Income Decile for {year}\n'
)
tfile.write(row)
# pylint: disable=consider-using-f-string
rowfmt = '{}{}{}{}{}{}\n'
tfile.write(rowfmt.format(*[header for _, _, _, header, _ in columns]))
tfile.write(rowfmt.format(*[units for _, _, _, _, units in columns]))
rowfmt = '{:9.2f}{:10.1f}{:10.1f}{:10.1f}{:10.1f}{:10.1f}\n'
for decile in range(0, 10):
row = f'{decile:2d}'
row += rowfmt.format(*[
ser[decile] * scl for ser, scl in zip(series, scales)
])
tfile.write(row)
row = ' A'
row += rowfmt.format(*[
ser.sum() * scl for ser, scl in zip(series, scales)
])
tfile.write(row)
# pylint: enable=consider-using-f-string
del gdfx
del series
gc.collect()
def _write_graph_files(self):
"""
Write graphs to HTML files.
All graphs contain same number of filing units in each quantile.
"""
pos_wght_sum = self.calc_ref.total_weight() > 0.0
# each graph is specified by output-file suffix, title, and builder
graph_specs = [
('-chg.html', 'CHG by Income Percentile',
lambda: self.calc_bas.pch_graph(
self.calc_ref, pop_quantiles=False)),
('-atr.html', 'ATR by Income Percentile',
lambda: self.calc_bas.atr_graph(
self.calc_ref, pop_quantiles=False)),
('-mtr.html', 'MTR by Income Percentile',
lambda: self.calc_bas.mtr_graph(
self.calc_ref,
alt_e00200p_text='Taxpayer Earnings',
pop_quantiles=False)),
]
fnames = []
for suffix, title, build_graph in graph_specs:
fname = self.output_filename.replace('.xxx', suffix)
fnames.append(fname)
if pos_wght_sum:
fig = build_graph()
write_graph_file(fig, fname, title)
del fig
gc.collect()
else:
reason = 'No graph because sum of weights is not positive'
TaxCalcIO._write_empty_graph_file(fname, title, reason)
if not self.silent:
print( # pragma: no cover
f'Write graphical output to file {fnames[0]}\n'
f'Write graphical output to file {fnames[1]}\n'
f'Write graphical output to file {fnames[2]}'
)
@staticmethod
def _write_empty_graph_file(fname, title, reason):
"""
Write HTML graph file with title but no graph for specified reason.
"""
txt = (
'<html>\n'
f'<head><title>{title}</title></head>\n'
f'<body><center<h1>{reason}</h1></center></body>\n'
'</html>\n'
)
with open(fname, 'w', encoding='utf-8') as gfile:
gfile.write(txt)
def _write_dumpdb_file(
self,
dump_varlist,
mtr_ptax_ref, mtr_itax_ref,
mtr_ptax_bas, mtr_itax_bas,
):
"""
Write dump output to SQLite database file.
"""
# pylint: disable=too-many-arguments,too-many-positional-arguments
def _dump_output(calcx, dumpvars, mtr_itax, mtr_ptax):
"""
Extract dump output from calcx and return it as Pandas DataFrame.
"""
odict = {}
for var in dumpvars:
if var == 'mtr_itax':
odict[var] = pd.Series(mtr_itax)
elif var == 'mtr_ptax':
odict[var] = pd.Series(mtr_ptax)
else:
odict[var] = pd.Series(calcx.array(var))
odf = pd.concat(odict, axis=1)
del odict
return odf
# begin main logic
assert isinstance(dump_varlist, list)
assert len(dump_varlist) > 0
db_fname = self.output_filename.replace('.xxx', '.dumpdb')
dbcon = sqlite3.connect(db_fname)
# write base table
outdf = pd.DataFrame()
for var in TaxCalcIO.BASE_DUMPVARS:
outdf[var] = self.calc_bas.array(var)
expanded_income_bin_edges = [ # default income_group definition
-1e300, # essentially -infinity
50e3,
100e3,
250e3,
500e3,
1e6,
1e300, # essentially +infinity
]
outdf['income_group'] = 1 + pd.cut( # default base.income_group values
outdf['expanded_income'],
expanded_income_bin_edges,
right=False, # bins are defined as [lo_edge, hi_edge)
labels=False, # pd.cut returns bins numbered 0,1,2,...
)
assert len(outdf.index) == self.calc_bas.array_len
outdf.to_sql('base', dbcon, index=False)
del outdf
# write income_group_definition table
num_groups = len(expanded_income_bin_edges) - 1
outdf = pd.DataFrame()
outdf['income_group'] = np.array([
1 + grp for grp in range(0, num_groups)
])
outdf['income_lower'] = np.array(expanded_income_bin_edges[:-1])
outdf['income_up_to'] = np.array(expanded_income_bin_edges[1:])
assert len(outdf.index) == num_groups
outdf.to_sql('income_group_definition', dbcon, index=False)
del outdf
# write baseline table
outdf = _dump_output(
self.calc_bas, dump_varlist,
mtr_itax_bas, mtr_ptax_bas,
)
assert len(outdf.index) == self.calc_bas.array_len
outdf.to_sql('baseline', dbcon, index=False)
del outdf
# write reform table
outdf = _dump_output(
self.calc_ref, dump_varlist,
mtr_itax_ref, mtr_ptax_ref,
)
assert len(outdf.index) == self.calc_ref.array_len
outdf.to_sql('reform', dbcon, index=False)
del outdf
dbcon.close()
del dbcon
gc.collect()
if not self.silent:
print( # pragma: no cover
f'Write dump output to sqlite3 database file {db_fname}'
)
