@@ -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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