def test_reform_choice():
c = cr.Cruncher(inputs="tests/test_adjustment_noreform.json",
custom_reform="tests/test_reform.json")
assert isinstance(c, cr.Cruncher)
with pytest.raises(AttributeError):
cr.Cruncher(inputs="tests/test_adjustment.json",
custom_reform="tests/test_reform.json")
def read_input(self):
"""
Reads csv input file
Returns
self.invar: Tax-Calculator style dataframe of inputs
self.rows: number of rows of input file
"""
ivar = pd.read_csv(self.path, delim_whitespace=True, header=None)
# translate INPUT variables into OUTPUT variables
c = cr.Cruncher()
self.invar = c.translate(ivar)
self.rows = len(self.invar.index)
return self.invar, self.rows
def read_input(self):
"""
Reads csv input file
Returns
self.invar: Tax-Calculator style dataframe of inputs
self.rows: number of rows of input file
"""
if isinstance(self.path, pd.DataFrame):
ivar = self.path
else:
ivar = pd.read_csv(self.path,
sep=",",
engine="python",
header=None)
# check that input CSV has 28 columns
assert len(ivar.columns) == 28
# check that year is the same across all rows
assert ivar[1].max() == ivar[1].min()
rows = len(ivar)
params = BatchParams()
# validate input
params.adjust(ivar)
array = np.empty((0, rows))
for label in params._data:
array = np.append(array,
[params._data[label]["value"][0]["value"]],
axis=0)
params_df = pd.DataFrame(array).transpose()
params_marg = params_df.copy()
params_marg.loc[:, 9] = params_marg.loc[:, 9] + FINITE_DIFF
# translate INPUT variables into OUTPUT variables
c = cr.Cruncher()
self.invar = c.translate(params_df)
self.invar_marg = c.translate(params_marg)
self.rows = len(self.invar.index)
return self.invar, self.invar_marg, self.rows
def read_input(self):
"""
Reads csv input file
Returns
self.invar: Tax-Calculator style dataframe of inputs
self.rows: number of rows of input file
"""
CURRENT_PATH = os.path.abspath(os.path.dirname(__file__))
if isinstance(self.path, pd.DataFrame):
ivar = self.path
else:
input_file = os.path.join(CURRENT_PATH, self.path)
ivar = pd.read_csv(input_file,
sep=',',
engine="python",
header=None)
# check that input CSV has 24 columns
assert len(ivar.columns) == 24
# check that year is the same across all rows
assert ivar[1].max() == ivar[1].min()
rows = len(ivar)
params = BatchParams()
# validate input
params.adjust(ivar)
array = np.empty((0, rows))
for label in params._data:
array = np.append(array,
[params._data[label]['value'][0]['value']],
axis=0)
params_df = pd.DataFrame(array).transpose()
# translate INPUT variables into OUTPUT variables
c = cr.Cruncher()
self.invar = c.translate(params_df)
self.rows = len(self.invar.index)
return self.invar, self.rows
def read_input(self):
"""
Reads csv input file
Returns
self.invar: Tax-Calculator style dataframe of inputs
self.rows: number of rows of input file
"""
CURRENT_PATH = os.path.abspath(os.path.dirname(__file__))
if isinstance(self.path, pd.DataFrame):
ivar = self.path
else:
input_file = os.path.join(CURRENT_PATH, self.path)
ivar = pd.read_csv(input_file,
sep=',',
engine="python",
header=None)
# translate INPUT variables into OUTPUT variables
c = cr.Cruncher()
self.invar = c.translate(ivar)
self.rows = len(self.invar.index)
return self.invar, self.rows
def test_reform_choice():
c = cr.Cruncher(inputs=no_reform_path, custom_reform=reform_path)
assert isinstance(c, cr.Cruncher)
with pytest.raises(AttributeError):
cr.Cruncher(inputs=input_path, custom_reform=reform_path)
def test_baseline_choice():
c = cr.Cruncher(baseline=reform_path)
assert isinstance(c, cr.Cruncher)
def test_baseline_choice():
c = cr.Cruncher(baseline="tests/test_reform.json")
assert isinstance(c, cr.Cruncher)
def create_data():
c = cr.Cruncher(inputs="tests/test_adjustment.json")
return c
def cr_data():
return cr.Cruncher(inputs=input_path)
def test_baseline_choice():
c = cr.Cruncher(baseline="tests/test_reform.json")
assert isinstance(c, cr.Cruncher)
with pytest.raises(AttributeError):
cr.Cruncher(baseline="tests/fake_file.json")
