# load the forecast from TiDE and TimeGPT
tide_model_df = pd.read_csv('data/tide.csv', parse_dates=['delivery_week'])
timegpt_fcst_ex_vars_df = pd.read_csv('data/timegpt.csv', parse_dates=['delivery_week'])

# merge data frames with TiDE forecast and actuals
model_eval_df = pd.merge(holdout_df[['unique_id', 'delivery_week', 'target']], tide_model_df[['unique_id', 'delivery_week', 'forecast']], on=['unique_id', 'delivery_week'], how='inner')

# merge data frames with TimeGPT forecast and actuals
model_eval_df = pd.merge(model_eval_df, timegpt_fcst_ex_vars_df[['unique_id', 'delivery_week', 'TimeGPT']], on=['unique_id', 'delivery_week'], how='inner')

utils.plot_model_comparison(model_eval_df)