@@ -63,7 +63,6 @@ def make_forecast_horizon_metrics(results_df, normalize: bool = False) -> List[g
6363 forecast_horizon_metrics = {}
6464 # loop over the number of forecast horizons
6565 for i in range (n_forecast_hoirzons ):
66-
6766 forecast_horizon = (i + 1 ) * time_delta
6867 forecast_horizon_hours = forecast_horizon .seconds / 3600
6968
@@ -92,7 +91,6 @@ def make_forecast_horizon_metrics(results_df, normalize: bool = False) -> List[g
9291 trace_forecast_horizons = []
9392 # loop over the different columns / metrics and plot them
9493 for i in range (len (plotting_metrics )):
95-
9694 col = plotting_metrics [i ]
9795 colour = colours [i ]
9896
@@ -127,7 +125,6 @@ def make_gsp_id_metrics(
127125 n_gsp_ids = int (results_df ["gsp_id" ].max ())
128126 gsp_metrics = {}
129127 for i in range (n_gsp_ids ):
130-
131128 gsp_id = i + 1
132129
133130 results_df_one_forecast_hoirzon = results_df [results_df ["gsp_id" ] == gsp_id ]
@@ -146,7 +143,6 @@ def make_gsp_id_metrics(
146143 # plot metrics
147144 trace_gsp_id = []
148145 for i in range (len (plotting_metrics )):
149-
150146 col = plotting_metrics [i ]
151147 colour = colours [i ]
152148
@@ -202,7 +198,6 @@ def make_t0_datetime_utc_metrics(results_df, normalize: bool = False) -> (go.Sca
202198 )
203199
204200 for i in range (len (target_datetimes_utc )):
205-
206201 target_datetime_utc = target_datetimes_utc [i ]
207202
208203 results_df_one_datetime = results_df [
@@ -221,7 +216,6 @@ def make_t0_datetime_utc_metrics(results_df, normalize: bool = False) -> (go.Sca
221216 # plot metrics
222217 trace_gsp_id = []
223218 for i in range (len (plotting_metrics )):
224-
225219 col = plotting_metrics [i ]
226220 colour = colours [i ]
227221
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