pywfm.IWFMModel.get_stream_stages#

IWFMModel.get_stream_stages(stage_conversion_factor=1.0)#

Return stream stages at every stream node for the current timestep

Parameters:: stage_conversion_factor (float) – conversion factor for stream stages from the simulation units of length to a desired unit of length
Returns:: stages for all stream nodes for the current simulation timestep
Return type:: np.ndarray

Note

This method is designed for use when is_for_inquiry=0 to return stream stages at the current timestep during a simulation.

See also

IWFMModel.get_stream_inflows_at_some_locations: Return stream boundary inflows at a specified set of inflow locations listed by their indices for the current simulation timestep
IWFMModel.get_stream_flow_at_location: Return stream flow at a stream node for the current time step in a simulation
IWFMModel.get_stream_flows: Return stream flows at every stream node for the current timestep

Example

>>> from pywfm import IWFMModel
>>> pp_file = '../Preprocessor/PreProcessor_MAIN.IN'
>>> sim_file = 'Simulation_MAIN.IN'
>>> model = IWFMModel(pp_file, sim_file, is_for_inquiry=0)
>>> while not model.is_end_of_simulation():
...     # advance the simulation time one time step forward
...     model.advance_time()
...
...     # read all time series data from input files
...     model.read_timeseries_data()
...
...     # Simulate the hydrologic process for the timestep
...     model.simulate_for_one_timestep()
...
...     # get stream flows
...     stream_flows = model.get_stream_stages()
...     stream_node_ids = model.get_stream_node_ids()
...
...     # print the results to the user-specified output files
...     model.print_results()
...
...     # advance the state of the hydrologic system in time
...     model.advance_state()
>>> for i, flow in enumerate(stream_flows):
...     print(stream_node_ids[i], flow)
*   TIME STEP 3653 AT 09/30/2000_24:00
1 2.2952133835661925
2 2.265988534377925
3 2.23736219849917
4 2.209695515995236
5 2.183909078616921
6 2.1655452773528054
7 2.148149883990982
8 2.133630610251487
9 2.1115282647882054
10 2.1015104342912423
11 1.6783304406148432
12 1.4126136989034421e-06
13 0.0
14 0.0
15 0.0
16 0.0
17 0.0
18 0.08041698765009642
19 0.061386890202925315
20 0.046860127429624754
21 0.07388403067233185
22 0.050371296013054234
23 0.07860238766727434
>>> model.kill()
>>> model.close_log_file()