<jupyter_start><jupyter_text>Jul<jupyter_code>run_name = "1594480618.481472"
output_folder = '../../misc/reports/{}'.format(run_name)
filename = f'{output_folder}/output-{run_name}.csv'
fig, df_true, df_prediction = plot_backtest_seir(gt_dataloader='AthenaLoader', preds_source='filename', fname_format='old_output', 
                                                 filename=filename, which_forecast=50, truncate_plotting_range=True,
                                                 separate_compartments=False)

fig, df_true, df_prediction = plot_backtest_seir(gt_dataloader='AthenaLoader', preds_source='filename', fname_format='old_output', 
                                                 filename=filename, which_forecast=50, truncate_plotting_range=True,
                                                 separate_compartments=True)

lc.backtesting_loss_week_by_week(df_prediction, df_true)<jupyter_output><empty_output><jupyter_text>Aug<jupyter_code>filename = '../../misc/oncall/08_2020_aug/nayana/seihrd.csv'
fig, df_true, df_prediction = plot_backtest_seir(gt_dataloader='AthenaLoader', preds_source='filename', fname_format='new_deciles', 
                                                 filename=filename, which_forecast=80, truncate_plotting_range=True,
                                                 separate_compartments=False)

fig, df_true, df_prediction = plot_backtest_seir(gt_dataloader='AthenaLoader', preds_source='filename', fname_format='new_deciles', 
                                                 filename=filename, which_forecast=80, truncate_plotting_range=True,
                                                 separate_compartments=True)

lc.backtesting_loss_week_by_week(df_prediction, df_true)<jupyter_output><empty_output><jupyter_text>Sept<jupyter_code>output_folder = '../../misc/reports/{}'.format("2020_0908_090609")
with open(join(output_folder, 'predictions_dict.pkl'), 'rb') as f:
    predictions_dict = pkl.load(f)
fig, df_true, df_prediction = plot_backtest_seir(gt_dataloader='AthenaLoader', preds_source='pickle', predictions_dict=predictions_dict, 
                                                 which_forecast=80, truncate_plotting_range=True,
                                                 separate_compartments=False)

fig, df_true, df_prediction = plot_backtest_seir(gt_dataloader='AthenaLoader', preds_source='pickle', predictions_dict=predictions_dict, 
                                                 which_forecast=80, truncate_plotting_range=True,
                                                 separate_compartments=True)

lc.backtesting_loss_week_by_week(df_prediction, df_true)<jupyter_output><empty_output>
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{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '251543', 'license': 'MIT', 'n_tokens_mistral': 814, 'n_tokens_neox': 771, 'n_words': 80, 'path': 'notebooks/seir/[STABLE] backtesting.ipynb', 'repo_name': 'WadhwaniAI/covid-modelling', 'size': '2678'}