def write_graph_files(self):
"""
Write graphs to HTML files.
"""
pos_wght_sum = self.calc.records.s006.sum() > 0.
atr_fname = self._output_filename.replace('.csv', '-atr.html')
atr_title = 'ATR by Income Percentile'
if pos_wght_sum:
atr_data = atr_graph_data(self.calc_clp, self.calc)
atr_plot = xtr_graph_plot(atr_data)
write_graph_file(atr_plot, atr_fname, atr_title)
else:
reason = 'No graph because sum of weights is not positive'
TaxCalcIO.write_empty_graph_file(atr_fname, atr_title, reason)
mtr_fname = self._output_filename.replace('.csv', '-mtr.html')
mtr_title = 'MTR by Income Percentile'
if pos_wght_sum:
mtr_data = mtr_graph_data(self.calc_clp,
self.calc,
alt_e00200p_text='Taxpayer Earnings')
mtr_plot = xtr_graph_plot(mtr_data)
write_graph_file(mtr_plot, mtr_fname, mtr_title)
else:
reason = 'No graph because sum of weights is not positive'
TaxCalcIO.write_empty_graph_file(mtr_fname, mtr_title, reason)
def test_atr_graph_data(records_2009):
calc = Calculator(policy=Policy(), records=records_2009)
with pytest.raises(ValueError):
gdata = atr_graph_data(calc, calc, mars='bad')
with pytest.raises(ValueError):
gdata = atr_graph_data(calc, calc, mars=0)
with pytest.raises(ValueError):
gdata = atr_graph_data(calc, calc, mars=list())
with pytest.raises(ValueError):
gdata = atr_graph_data(calc, calc, atr_measure='badtax')
with pytest.raises(ValueError):
calcx = Calculator(policy=Policy(), records=records_2009)
calcx.advance_to_year(2020)
gdata = atr_graph_data(calcx, calc)
gdata = atr_graph_data(calc, calc, mars=1, atr_measure='combined')
gdata = atr_graph_data(calc, calc, atr_measure='itax')
gdata = atr_graph_data(calc, calc, atr_measure='ptax')
assert isinstance(gdata, dict)
def test_atr_graph_data(cps_subsample):
pol = Policy()
rec = Records.cps_constructor(data=cps_subsample)
calc = Calculator(policy=pol, records=rec)
with pytest.raises(ValueError):
atr_graph_data(calc, calc, mars='bad')
with pytest.raises(ValueError):
atr_graph_data(calc, calc, mars=0)
with pytest.raises(ValueError):
atr_graph_data(calc, calc, mars=list())
with pytest.raises(ValueError):
atr_graph_data(calc, calc, atr_measure='badtax')
gdata = atr_graph_data(calc, calc, mars=1, atr_measure='combined')
gdata = atr_graph_data(calc, calc, atr_measure='itax')
gdata = atr_graph_data(calc, calc, atr_measure='ptax')
assert isinstance(gdata, dict)
with pytest.raises(ValueError):
calcx = Calculator(policy=pol, records=rec)
calcx.advance_to_year(2020)
atr_graph_data(calcx, calc)
def test_atr_graph_data(cps_subsample):
pol = Policy()
rec = Records.cps_constructor(data=cps_subsample, no_benefits=True)
calc = Calculator(policy=pol, records=rec)
year = calc.current_year
with pytest.raises(ValueError):
atr_graph_data(None, year, mars='bad')
with pytest.raises(ValueError):
atr_graph_data(None, year, mars=0)
with pytest.raises(ValueError):
atr_graph_data(None, year, mars=list())
with pytest.raises(ValueError):
atr_graph_data(None, year, atr_measure='badtax')
calc.calc_all()
vdf = calc.dataframe(['s006', 'MARS', 'expanded_income'])
tax = 0.20 * np.ones_like(vdf['expanded_income'])
vdf['tax1'] = tax
vdf['tax2'] = tax
gdata = atr_graph_data(vdf, year, mars=1, atr_measure='combined')
gdata = atr_graph_data(vdf, year, atr_measure='itax')
gdata = atr_graph_data(vdf, year, atr_measure='ptax')
assert isinstance(gdata, dict)
def test_atr_graph_data(cps_subsample):
pol = Policy()
rec = Records.cps_constructor(data=cps_subsample)
calc = Calculator(policy=pol, records=rec)
year = calc.current_year
with pytest.raises(ValueError):
atr_graph_data(None, year, mars='bad')
with pytest.raises(ValueError):
atr_graph_data(None, year, mars=0)
with pytest.raises(ValueError):
atr_graph_data(None, year, mars=list())
with pytest.raises(ValueError):
atr_graph_data(None, year, atr_measure='badtax')
calc.calc_all()
vdf = calc.dataframe(['s006', 'MARS', 'expanded_income'])
tax = 0.20 * np.ones_like(vdf['expanded_income'])
vdf['tax1'] = tax
vdf['tax2'] = tax
gdata = atr_graph_data(vdf, year, mars=1, atr_measure='combined')
gdata = atr_graph_data(vdf, year, atr_measure='itax')
gdata = atr_graph_data(vdf, year, atr_measure='ptax')
assert isinstance(gdata, dict)
def static_analysis(self,
writing_output_file=False,
output_graph=False,
output_ceeu=False,
output_dump=False):
"""
Conduct STATIC tax analysis for INPUT and write or return OUTPUT.
Parameters
----------
writing_output_file: boolean
output_graph: boolean
whether or not to generate and show HTML graphs of average
and marginal tax rates by income percentile
output_ceeu: boolean
whether or not to calculate and write to stdout standard
certainty-equivalent expected-utility statistics
output_dump: boolean
whether or not to replace standard output with all input and
calculated variables using their Tax-Calculator names
Returns
-------
Nothing
"""
# pylint: disable=too-many-arguments,too-many-locals,too-many-branches
# conduct STATIC tax analysis
if output_dump:
(mtr_paytax, mtr_inctax,
_) = self._calc.mtr(wrt_full_compensation=False)
else: # do not need marginal tax rates
self._calc.calc_all()
# optionally conduct normative welfare analysis
if output_ceeu:
self._calc_clp.calc_all()
cedict = ce_aftertax_income(self._calc_clp,
self._calc,
require_no_agg_tax_change=False)
ceeu_results = TaxCalcIO.ceeu_output(cedict)
else:
ceeu_results = None
# extract output if writing_output_file
if writing_output_file:
if output_dump:
outdf = self.dump_output(mtr_inctax, mtr_paytax)
else:
outdf = self.standard_output()
assert len(outdf.index) == self._calc.records.dim
outdf.to_csv(self._output_filename,
index=False,
float_format='%.2f')
# optionally write --graph output to HTML files
if output_graph:
atr_data = atr_graph_data(self._calc_clp, self._calc)
atr_plot = xtr_graph_plot(atr_data)
atr_fname = self._output_filename.replace('.csv', '-atr.html')
atr_title = 'ATR by Income Percentile'
write_graph_file(atr_plot, atr_fname, atr_title)
mtr_data = mtr_graph_data(self._calc_clp,
self._calc,
alt_e00200p_text='Taxpayer Earnings')
mtr_plot = xtr_graph_plot(mtr_data)
mtr_fname = self._output_filename.replace('.csv', '-mtr.html')
mtr_title = 'MTR by Income Percentile'
write_graph_file(mtr_plot, mtr_fname, mtr_title)
# optionally write --ceeu output to stdout
if ceeu_results:
print(ceeu_results) # pylint: disable=superfluous-parens