mooflow.classes.Pywr_model¶

class mooflow.classes.Pywr_model(omo_setup, timeseries=False)¶

__init__(omo_setup, timeseries=False)¶

Class to manage the water allocation with the Pywr package

Parameters

omo_setupmooflow.classes.Omo_setup: the configured setup
timeseriesBool: if False, make a simple balance model (one timestep) if True, take the number of timesteps from the omo_setup

Methods

`__init__`(omo_setup[, timeseries])	Class to manage the water allocation with the Pywr package
`get_active_nodes`()	return the active nodes
`get_json`()	return the dict of the pywr model
`get_pywrfile`()	return the file name of the JSON model file
`nwt_well_shortages`(setup_mf, reg_well)	read the shortages for each well from the list file for the NWT model for each time step for pywr active nodes.
`prepare_pywr_model`(setup_mf, reg_wells, …)	Return a dictionary which summarizes for the active nodes.
`pywt_extr_nwt`(setup_mf, reg_well, reg_wellgroup)	For active nodes: this function first accumulates the total needed extractions and then accumulates the total shortages in extractions which is read from the list file from the NWT model.
`read_results`([func, return_dict])	Read the results from a pywr model run.
`run_pywr`([use_TablesRecorder])	Start the water allocation optimization pywr.
`set_pywrfile`(file_name[, datafile])	Set the JSON model file for Pywr
`update_nodes_in_model`([factor])	Configure the INFLOW nodes with the deliverable amount of water, e.g.
`write_nodefile`(setup_mf[, delimiter, …])	Write the CSV data file with all the well data for pywr.

Attributes