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@@ -20,7 +20,7 @@ import pandas as pd
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from tqdm import tqdm
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SEASONS = {
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- 'name': ['RHO2013', 'BRK2013/16', 'HIGH2017', 'RHO2018', 'HIGH2019', 'LOW2020', 'HIGH2020', 'HIGH2021', 'NNBAR2021', 'HIGH2023'],
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+ 'name': ['RHO2013', 'BRK2013/16', 'HIGH2017', 'RHO2018', 'HIGH2019', 'LOW2020', 'HIGH2020', 'HIGH2021', 'NNBAR2022', 'HIGH2023'],
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'start_run': [18809, 32076, 36872, 48938, 70014, 85224, 89973, 98116, 107342, 131913, None],
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}
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@@ -46,7 +46,7 @@ class RunsDBHandler():
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----------
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range : Union[Tuple[int, Optional[int]], Tuple[datetime, datetime]]
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selection range
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- int range defines an interval in runs
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+ int range defines an interval in runs (first included, last excluded)
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datetime range defines a time interval (NSK: +7:00 time)
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energy_point : Optional[float]
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energy point name, MeV (default is None)
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@@ -58,7 +58,7 @@ class RunsDBHandler():
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if isinstance(range[0], int):
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cond = f" AND run >= {range[0]} "
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if range[1] is not None:
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- cond += f" AND run <= {range[1]} "
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+ cond += f" AND run < {range[1]} "
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elif isinstance(range[0], datetime):
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cond = f" AND starttime >= %s "
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if range[1] is not None:
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@@ -466,7 +466,7 @@ def process_combined(combined_df: pd.DataFrame, runs_df: pd.DataFrame, compton_d
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spread_mean=('spread_mean', 'min'), spread_mean_test=('spread_mean', 'max'),
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spread_std=('spread_std', 'min'), spread_std_test=('spread_std', 'max'),
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).reset_index().set_index('point_idx')
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- #return combined_df
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+ # return combined_df
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result_df = pd.DataFrame(columns=['energy_point', 'first_run', 'last_run', 'mean_energy', 'mean_energy_stat_err', 'mean_energy_sys_err', 'mean_spread', 'mean_spread_stat_err', 'used_lum', 'comment'])
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