using .name.lower to match fixed sc point attributes

reV/econ/economies_of_scale.py

@@ -3,16 +3,20 @@
 reV module for calculating economies of scale where larger power plants will
 have reduced capital cost.
 """
+
 import copy
 import logging
 import re
 
 # pylint: disable=unused-import
-import numpy as np
 import pandas as pd
 from rex.utilities.utilities import check_eval_str
 
 from reV.econ.utilities import lcoe_fcr
+from reV.utilities import (
+    OldSupplyCurveField,
+    SupplyCurveField,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -59,23 +63,32 @@ def _preflight(self):
             check_eval_str(str(self._eqn))
 
         if isinstance(self._data, pd.DataFrame):
-            self._data = {k: self._data[k].values.flatten()
-                          for k in self._data.columns}
+            self._data = {
+                k: self._data[k].values.flatten() for k in self._data.columns
+            }
 
         if not isinstance(self._data, dict):
-            e = ('Cannot evaluate EconomiesOfScale with data input of type: {}'
-                 .format(type(self._data)))
+            e = (
+                "Cannot evaluate EconomiesOfScale with data input of type: "
+                "{}".format(type(self._data))
+            )
+
             logger.error(e)
             raise TypeError(e)
 
         missing = [name for name in self.vars if name not in self._data]
 
         if any(missing):
-            e = ('Cannot evaluate EconomiesOfScale, missing data for variables'
-                 ': {} for equation: {}'.format(missing, self._eqn))
+            e = (
+                "Cannot evaluate EconomiesOfScale, missing data for variables"
+                ": {} for equation: {}".format(missing, self._eqn)
+            )
             logger.error(e)
             raise KeyError(e)
 
+        rename_map = SupplyCurveField.map_from(OldSupplyCurveField)
+        self._data = {rename_map.get(k, k): v for k, v in self._data.items()}
+
     @staticmethod
     def is_num(s):
         """Check if a string is a number"""
@@ -89,7 +102,7 @@ def is_num(s):
     @staticmethod
     def is_method(s):
         """Check if a string is a numpy/pandas or python builtin method"""
-        return bool(s.startswith(('np.', 'pd.')) or s in dir(__builtins__))
+        return bool(s.startswith(("np.", "pd.")) or s in dir(__builtins__))
 
     @property
     def vars(self):
@@ -105,8 +118,8 @@ def vars(self):
         """
         var_names = []
         if self._eqn is not None:
-            delimiters = ('*', '/', '+', '-', ' ', '(', ')', '[', ']', ',')
-            regex_pattern = '|'.join(map(re.escape, delimiters))
+            delimiters = ("*", "/", "+", "-", " ", "(", ")", "[", "]", ",")
+            regex_pattern = "|".join(map(re.escape, delimiters))
             var_names = []
             for sub in re.split(regex_pattern, str(self._eqn)):
                 if sub and not self.is_num(sub) and not self.is_method(sub):
@@ -160,9 +173,10 @@ def _get_prioritized_keys(input_dict, key_list):
                 break
 
         if out is None:
-            e = ('Could not find requested key list ({}) in the input '
-                 'dictionary keys: {}'
-                 .format(key_list, list(input_dict.keys())))
+            e = (
+                "Could not find requested key list ({}) in the input "
+                "dictionary keys: {}".format(key_list, list(input_dict.keys()))
+            )
             logger.error(e)
             raise KeyError(e)
 
@@ -190,7 +204,10 @@ def raw_capital_cost(self):
         out : float | np.ndarray
             Unscaled (raw) capital_cost found in the data input arg.
         """
-        key_list = ['capital_cost', 'mean_capital_cost']
+        key_list = [
+            SupplyCurveField.CAPITAL_COST,
+            "mean_capital_cost",
+        ]
         return self._get_prioritized_keys(self._data, key_list)
 
     @property
@@ -217,7 +234,7 @@ def system_capacity(self):
         -------
         out : float | np.ndarray
         """
-        key_list = ['system_capacity', 'mean_system_capacity']
+        key_list = ["system_capacity", "mean_system_capacity"]
         return self._get_prioritized_keys(self._data, key_list)
 
     @property
@@ -229,9 +246,12 @@ def fcr(self):
         out : float | np.ndarray
             Fixed charge rate from input data arg
         """
-        key_list = ['fixed_charge_rate',
-                    'mean_fixed_charge_rate',
-                    'fcr', 'mean_fcr']
+        key_list = [
+            SupplyCurveField.FIXED_CHARGE_RATE,
+            "mean_fixed_charge_rate",
+            "fcr",
+            "mean_fcr",
+        ]
         return self._get_prioritized_keys(self._data, key_list)
 
     @property
@@ -243,9 +263,12 @@ def foc(self):
         out : float | np.ndarray
             Fixed operating cost from input data arg
         """
-        key_list = ['fixed_operating_cost',
-                    'mean_fixed_operating_cost',
-                    'foc', 'mean_foc']
+        key_list = [
+            SupplyCurveField.FIXED_OPERATING_COST,
+            "mean_fixed_operating_cost",
+            "foc",
+            "mean_foc",
+        ]
         return self._get_prioritized_keys(self._data, key_list)
 
     @property
@@ -257,9 +280,12 @@ def voc(self):
         out : float | np.ndarray
             Variable operating cost from input data arg
         """
-        key_list = ['variable_operating_cost',
-                    'mean_variable_operating_cost',
-                    'voc', 'mean_voc']
+        key_list = [
+            SupplyCurveField.VARIABLE_OPERATING_COST,
+            "mean_variable_operating_cost",
+            "voc",
+            "mean_voc",
+        ]
         return self._get_prioritized_keys(self._data, key_list)
 
     @property
@@ -285,7 +311,7 @@ def raw_lcoe(self):
         -------
         lcoe : float | np.ndarray
         """
-        key_list = ["raw_lcoe", "mean_lcoe"]
+        key_list = [SupplyCurveField.RAW_LCOE, SupplyCurveField.MEAN_LCOE]
         return copy.deepcopy(self._get_prioritized_keys(self._data, key_list))
 
     @property
@@ -301,5 +327,6 @@ def scaled_lcoe(self):
             LCOE calculated with the scaled capital cost based on the
             EconomiesOfScale input equation.
         """
-        return lcoe_fcr(self.fcr, self.scaled_capital_cost, self.foc,
-                        self.aep, self.voc)
+        return lcoe_fcr(
+            self.fcr, self.scaled_capital_cost, self.foc, self.aep, self.voc
+        )

reV/supply_curve/aggregation.py

@@ -18,7 +18,7 @@
 from reV.supply_curve.extent import SupplyCurveExtent
 from reV.supply_curve.points import AggregationSupplyCurvePoint
 from reV.supply_curve.tech_mapping import TechMapping
-from reV.utilities import SupplyCurveField, log_versions
+from reV.utilities import ResourceMetaField, SupplyCurveField, log_versions
 from reV.utilities.exceptions import (
     EmptySupplyCurvePointError,
     FileInputError,
@@ -472,12 +472,17 @@ def _parse_gen_index(gen_fpath):
             logger.error(msg)
             raise FileInputError(msg)
 
+        gen_index = gen_index.rename(
+            ResourceMetaField.map_to(SupplyCurveField), axis=1
+        )
         if SupplyCurveField.GID in gen_index:
             gen_index = gen_index.rename(
                 columns={SupplyCurveField.GID: SupplyCurveField.RES_GIDS}
             )
             gen_index[SupplyCurveField.GEN_GIDS] = gen_index.index
-            gen_index = gen_index[[SupplyCurveField.RES_GIDS, SupplyCurveField.GEN_GIDS]]
+            gen_index = gen_index[
+                [SupplyCurveField.RES_GIDS, SupplyCurveField.GEN_GIDS]
+            ]
             gen_index = gen_index.set_index(keys=SupplyCurveField.RES_GIDS)
             gen_index = gen_index.reindex(
                 range(int(gen_index.index.max() + 1))
@@ -696,7 +701,10 @@ def run_serial(
             "area_filter_kernel": area_filter_kernel,
             "min_area": min_area,
         }
-        dsets = (*agg_dset, "meta",)
+        dsets = (
+            *agg_dset,
+            "meta",
+        )
         agg_out = {ds: [] for ds in dsets}
         with AggFileHandler(excl_fpath, h5_fpath, **file_kwargs) as fh:
             n_finished = 0

reV/supply_curve/points.py

@@ -2219,7 +2219,7 @@ def point_summary(self, args=None):
             SupplyCurveField.SC_POINT_ANNUAL_ENERGY_AC,
         ]
         for attr in extra_atts:
-            value = getattr(self, attr)
+            value = getattr(self, attr.name.lower())
             if value is not None:
                 ARGS[attr] = value
 

reV/utilities/__init__.py

@@ -86,6 +86,7 @@ class ResourceMetaField(FieldEnum):
     "sc_row_ind": "SC_ROW_IND",
     "sc_col_ind": "SC_COL_IND",
     "mean_cf": "MEAN_CF",
+    "capital_cost": "CAPITAL_COST",
 }