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  2. Find an issue within this page? Please report it in the GitHub issues.

  3. A good understanding of SUEWS is a prerequisite to the proper use of SuPy.


supy.save_supy(df_output: pandas.core.frame.DataFrame, df_state_final: pandas.core.frame.DataFrame, freq_s: int = 3600, site: str = '', path_dir_save: str = PosixPath('.'), path_runcontrol: Optional[str] = None, save_tstep=False, logging_level=50, output_level=1, debug=False) list[source]ΒΆ

Save SuPy run results to files

  • df_output (pandas.DataFrame) – DataFrame of output

  • df_state_final (pandas.DataFrame) – DataFrame of final model states

  • freq_s (int, optional) – Output frequency in seconds (the default is 3600, which indicates hourly output)

  • site (str, optional) – Site identifier (the default is β€˜β€™, which indicates site identifier will be left empty)

  • path_dir_save (str, optional) – Path to directory to saving the files (the default is Path(β€˜.’), which indicates the current working directory)

  • path_runcontrol (str, optional) – Path to SUEWS RunControl.nml, which, if set, will be preferably used to derive freq_s, site and path_dir_save. (the default is None, which is unset)

  • save_tstep (bool, optional) – whether to save results in temporal resolution as in simulation (which may result very large files and slow progress), by default False.

  • logging_level (logging level) – one of these values [50 (CRITICAL), 40 (ERROR), 30 (WARNING), 20 (INFO), 10 (DEBUG)]. A lower value informs SuPy for more verbose logging info.

  • output_level (integer, optional) – option to determine selection of output variables, by default 1. Notes: 0 for all but snow-related; 1 for all; 2 for a minimal set without land cover specific information.

  • debug (bool, optional) – whether to enable debug mode (e.g., writing out in serial mode, and other debug uses), by default False.


a list of paths of saved files

Return type



  1. save results of a supy run to the current working directory with default settings

>>> list_path_save = supy.save_supy(df_output, df_state_final)
  1. save results according to settings in RunControl.nml

>>> list_path_save = supy.save_supy(df_output, df_state_final, path_runcontrol='path/to/RunControl.nml')
  1. save results of a supy run at resampling frequency of 1800 s (i.e., half-hourly results) under the site code Test to a customised location β€˜path/to/some/dir’

>>> list_path_save = supy.save_supy(df_output, df_state_final, freq_s=1800, site='Test', path_dir_save='path/to/some/dir')