1. Need help? Please let us know in the UMEP Community.

  2. Please report issues with the manual on the GitHub Issues.

  3. Please cite SUEWS with proper information from our Zenodo page. supy.save_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: str = None, save_tstep=False, logging_level=50, output_level=1, debug=False) list[source]#

Save SuPy run results to files


DataFrame of output


DataFrame of final model states

freq_sint, optional

Output frequency in seconds (the default is 3600, which indicates hourly output)

sitestr, optional

Site identifier (the default is ‘’, which indicates site identifier will be left empty)

path_dir_savestr, optional

Path to directory to saving the files (the default is Path(‘.’), which indicates the current working directory)

path_runcontrolstr, 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_tstepbool, 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_levelinteger, 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.

debugbool, 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

  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 ‘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')