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Merge pull request #257 from jdebacker/ind_calcs
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Updates to Calculator class
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@jdebacker
jdebacker committed May 10, 2019
2 parents df9bb27 + 4138bba commit 2e5289a
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Showing 3 changed files with 242 additions and 144 deletions.
175 changes: 31 additions & 144 deletions ccc/calculator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@
eq_metr, eq_mettr, eq_tax_wedge, eq_eatr)
from ccc.parameters import Specifications
from ccc.data import Assets
from ccc.utils import wavg, diff_two_tables
from ccc.utils import wavg, diff_two_tables, save_return_table
from ccc.constants import VAR_DICT, MAJOR_IND_ORDERED
# import pdb
# importing Bokeh libraries
Expand Down Expand Up @@ -168,7 +168,8 @@ def calc_all(self):
self.calc_base()
self.__assets.df = self.calc_other(self.__assets.df)

def calc_by_asset(self):
def calc_by_asset(self, include_inventories=True,
include_land=True):
'''
Calculates all variables by asset, including overall, and by
major asset categories.
Expand Down Expand Up @@ -401,33 +402,9 @@ def summary_table(self, calc, output_variable='mettr',
table_df[VAR_DICT[output_variable] +
' Under Reform Policy'] *= 100
table_df['Change from Baseline (pp)'] *= 100
if path is None:
if output_type == 'tex':
tab_str = table_df.to_latex(
buf=path, index=False, na_rep='',
float_format=lambda x: '%.0f' % x)
return tab_str
elif output_type == 'json':
tab_str = table_df.to_json(
path_or_buf=path, double_precision=0)
return tab_str
else:
return table_df
else:
if output_type == 'tex':
table_df.to_latex(buf=path, index=False, na_rep='',
float_format=lambda x: '%.0f' % x)
elif output_type == 'csv':
table_df.to_csv(path_or_buf=path, index=False, na_rep='',
float_format="%.0f")
elif output_type == 'json':
table_df.to_json(path_or_buf=path, double_precision=0)
elif output_type == 'excel':
table_df.to_excel(excel_writer=path, index=False, na_rep='',
float_format="%.0f")
else:
print('Please enter a valid output format')
assert(False)
table = save_return_table(table_df, output_type, path)

return table

def asset_share_table(self, include_land=True,
include_inventories=True, output_type='csv',
Expand Down Expand Up @@ -477,33 +454,10 @@ def asset_share_table(self, include_land=True,
table_dict['Pass-Through'].append(
df2[df2.Industry == item]['Pass-Through'].values[0])
table_df = pd.DataFrame.from_dict(table_dict, orient='columns')
if path is None:
if output_type == 'tex':
tab_str = table_df.to_latex(
buf=path, index=False, na_rep='',
float_format=lambda x: '%.2f' % x)
return tab_str
elif output_type == 'json':
tab_str = table_df.to_json(
path_or_buf=path, double_precision=2)
return tab_str
else:
return table_df
else:
if output_type == 'tex':
table_df.to_latex(buf=path, index=False, na_rep='',
float_format=lambda x: '%.2f' % x)
elif output_type == 'csv':
table_df.to_csv(path_or_buf=path, index=False, na_rep='',
float_format="%.2f")
elif output_type == 'json':
table_df.to_json(path_or_buf=path, double_precision=0)
elif output_type == 'excel':
table_df.to_excel(excel_writer=path, index=False, na_rep='',
float_format="%.2f")
else:
print('Please enter a valid output format')
assert(False)
table = save_return_table(table_df, output_type, path,
precision=2)

return table

def asset_summary_table(self, calc, output_variable='mettr',
include_land=True, include_inventories=True,
Expand Down Expand Up @@ -662,33 +616,9 @@ def asset_summary_table(self, calc, output_variable='mettr',
table_df[VAR_DICT[output_variable] +
' Under Reform Policy'] *= 100
table_df['Change from Baseline (pp)'] *= 100
if path is None:
if output_type == 'tex':
tab_str = table_df.to_latex(
buf=path, index=False, na_rep='',
float_format=lambda x: '%.0f' % x)
return tab_str
elif output_type == 'json':
tab_str = table_df.to_json(
path_or_buf=path, double_precision=0)
return tab_str
else:
return table_df
else:
if output_type == 'tex':
table_df.to_latex(buf=path, index=False, na_rep='',
float_format=lambda x: '%.0f' % x)
elif output_type == 'csv':
table_df.to_csv(path_or_buf=path, index=False, na_rep='',
float_format="%.0f")
elif output_type == 'json':
table_df.to_json(path_or_buf=path, double_precision=0)
elif output_type == 'excel':
table_df.to_excel(excel_writer=path, index=False, na_rep='',
float_format="%.0f")
else:
print('Please enter a valid output format')
assert(False)
table = save_return_table(table_df, output_type, path)

return table

def industry_summary_table(self, calc, output_variable='mettr',
include_land=True,
Expand Down Expand Up @@ -716,7 +646,7 @@ def industry_summary_table(self, calc, output_variable='mettr',
path: string, specifies path to save file with table to
Returns:
table_df: DataFrame, table
table: DataFrame or None, table
'''
self.calc_base()
calc.calc_base()
Expand Down Expand Up @@ -837,61 +767,28 @@ def industry_summary_table(self, calc, output_variable='mettr',
table_df[VAR_DICT[output_variable] +
' Under Reform Policy'] *= 100
table_df['Change from Baseline (pp)'] *= 100
if path is None:
if output_type == 'tex':
tab_str = table_df.to_latex(
buf=path, index=False, na_rep='',
float_format=lambda x: '%.0f' % x)
return tab_str
elif output_type == 'json':
tab_str = table_df.to_json(
path_or_buf=path, double_precision=0)
return tab_str
else:
return table_df
else:
if output_type == 'tex':
table_df.to_latex(buf=path, index=False, na_rep='',
float_format=lambda x: '%.0f' % x)
elif output_type == 'csv':
table_df.to_csv(path_or_buf=path, index=False, na_rep='',
float_format="%.0f")
elif output_type == 'json':
table_df.to_json(path_or_buf=path, double_precision=0)
elif output_type == 'excel':
table_df.to_excel(excel_writer=path, index=False, na_rep='',
float_format="%.0f")
else:
print('Please enter a valid output format')
assert(False)
table = save_return_table(table_df, output_type, path)

return table

def grouped_bar(self, calc, output_variable='mettr',
group_by_asset=True, corporate=True,
include_land=True, include_inventories=True):
if group_by_asset:
base_df = self.calc_by_asset()
reform_df = calc.calc_by_asset()
base_df = self.calc_by_asset(
include_land=include_land,
include_inventories=include_inventories)
reform_df = calc.calc_by_asset(
include_land=include_land,
include_inventories=include_inventories
)
base_df.drop(base_df[base_df.asset_name !=
base_df.major_asset_group].index,
inplace=True)
reform_df.drop(
reform_df[reform_df.asset_name !=
reform_df.major_asset_group].index,
inplace=True)
if not include_land:
base_df.drop(
base_df[base_df.asset_name == 'Land'].index,
inplace=True)
reform_df.drop(
reform_df[reform_df.asset_name == 'Land'].index,
inplace=True)
if not include_inventories:
base_df.drop(
base_df[base_df.asset_name == 'Inventories'].index,
inplace=True)
reform_df.drop(
reform_df[reform_df.asset_name == 'Inventories'].index,
inplace=True)
plot_label = 'major_asset_group'
plot_title = VAR_DICT[output_variable] + ' by Asset Category'
else:
Expand Down Expand Up @@ -971,8 +868,12 @@ def grouped_bar(self, calc, output_variable='mettr',
def range_plot(self, calc, output_variable='mettr',
corporate=True, include_land=True,
include_inventories=True):
base_df = self.calc_by_asset()
reform_df = calc.calc_by_asset()
base_df = self.calc_by_asset(
include_land=include_land,
include_inventories=include_inventories)
reform_df = calc.calc_by_asset(
include_land=include_land,
include_inventories=include_inventories)
base_df.drop(base_df[
(base_df.asset_name != base_df.major_asset_group) &
(base_df.asset_name != 'Overall') &
Expand All @@ -984,20 +885,6 @@ def range_plot(self, calc, output_variable='mettr',
(reform_df.asset_name != 'Land') &
(reform_df.asset_name != 'Inventories')].index,
inplace=True)
if not include_land:
base_df.drop(
base_df[base_df.asset_name == 'Land'].index,
inplace=True)
reform_df.drop(
reform_df[reform_df.asset_name == 'Land'].index,
inplace=True)
if not include_inventories:
base_df.drop(
base_df[base_df.asset_name == 'Inventories'].index,
inplace=True)
reform_df.drop(
reform_df[reform_df.asset_name == 'Inventories'].index,
inplace=True)
# Append dfs together so base policies in one
base_df['policy'] = 'Baseline'
reform_df['policy'] = 'Reform'
Expand Down Expand Up @@ -1783,7 +1670,7 @@ def current_year(self):
Returns:
None
"""
return self.__p.current_year
return self.__p.year

@property
def data_year(self):
Expand Down
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