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.run_supy#

supy.run_supy(df_forcing: pandas.core.frame.DataFrame, df_state_init: pandas.core.frame.DataFrame, save_state=False, chunk_day=3660, logging_level=20, check_input=False, serial_mode=False) Tuple[pandas.core.frame.DataFrame, pandas.core.frame.DataFrame][source]#

Perform supy simulation.


forcing data for all grids in df_state_init.


initial model states; or a collection of model states with multiple timestamps, whose last temporal record will be used as the initial model states.

save_statebool, optional

flag for saving model states at each time step, which can be useful in diagnosing model runtime performance or performing a restart run. (the default is False, which instructs supy not to save runtime model states).

chunk_dayint, optional

chunk size (chunk_day days) to split simulation periods so memory usage can be reduced. (the default is 3660, which implies ~10-year forcing chunks used in simulations).

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.

check_inputbool, optional

flag for checking validity of input: df_forcing and df_state_init. If set to True, any detected invalid input will stop SuPy simulation; a False flag will bypass such validation and may incur kernel error if any invalid input. Note: such checking procedure may take some time if the input is large. (the default is False, which bypasses the validation).

serial_modebool, optional

If set to True, SuPy simulation will be conducted in serial mode; a False flag will try parallel simulation if possible (Windows not supported, i.e., always serial). (the default is False).

df_output, df_state_finalTuple[pandas.DataFrame, pandas.DataFrame]
>>> df_output, df_state_final = supy.run_supy(df_forcing, df_state_init)