Add flag to ignore look-ahead period counts when parsing RTS-GMLC.

RTS-GMLC metadata has "Look_Ahead_Periods_per_Step" fields that indicate
how much data to include in each simulation step. Consumers of RTS-GMLC
data (such as Prescient) may have their own mechanisms for determining
the simulation horizon, and it may not match the values stored in the
metadata.

This commit adds a new argument to rts_gmlc.parser.parse_to_cache(), called
"honor_lookahead". If this is True (the default), it uses the lookahead
period count found in the data's metadata. If it is False, it does not
include any extra data beyond the specified end_time. When calling this
function, consumers of the parsed data are expected to adjust the end_time
to include any look-ahead periods it may need.

egret/parsers/rts_gmlc/parser.py

@@ -102,7 +102,8 @@ def create_model_data_dict(rts_gmlc_dir:str,
 def parse_to_cache(rts_gmlc_dir:str, 
                    begin_time:Union[datetime,str],
                    end_time:Union[datetime,str],
-                   t0_state:Optional[dict]=None) -> ParsedCache:
+                   t0_state:Optional[dict]=None,
+                   honor_lookahead=True) -> ParsedCache:
     ''' Parse data in RTS-GMLC format, keeping the portions between a start and end time
 
     rts_gmlc_dir : str
@@ -127,7 +128,7 @@ def parse_to_cache(rts_gmlc_dir:str,
     model_data = _create_rtsgmlc_skeleton(rts_gmlc_dir)
 
     # Save the data frequencies
-    metadata_df = _read_metadata(rts_gmlc_dir)
+    metadata_df = _read_metadata(rts_gmlc_dir, honor_lookahead)
     minutes_per_period = {'DAY_AHEAD':int(metadata_df.loc['Period_Resolution', 'DAY_AHEAD'])//60,
                           'REAL_TIME':int(metadata_df.loc['Period_Resolution', 'REAL_TIME'])//60}
 
@@ -151,14 +152,18 @@ def parse_to_cache(rts_gmlc_dir:str,
                        timeseries_df, load_participation_factors, constant_reserve_data)
 
 
-def _read_metadata(base_dir:str) -> pd.DataFrame:
+def _read_metadata(base_dir:str, honor_lookahead:bool) -> pd.DataFrame:
     metadata_path = os.path.join(base_dir, "simulation_objects.csv")
     if not os.path.exists(metadata_path):
         raise ValueError(f'RTS-GMLC directory "{rts_gmlc_dir}" does not contain expected CSV files.')
 
     # Read metadata about the data
     metadata_df = pd.read_csv(metadata_path, index_col=0)
 
+    if not honor_lookahead:
+        metadata_df.loc['Look_Ahead_Periods_per_Step']['DAY_AHEAD'] = 0
+        metadata_df.loc['Look_Ahead_Periods_per_Step']['REAL_TIME'] = 0
+
     return metadata_df
 
 def _get_data_date_range(metadata_df) -> Tuple[datetime, datetime]: