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- 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
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
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)
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')
save results of a supy run at resampling frequency of 1800 s (i.e., half-hourly results) under the site code
Testto 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')