pywrdrb.parameters.PredictionEnsemble

class pywrdrb.parameters.PredictionEnsemble(model, column, inflow_type, ensemble_indices, **kwargs)

Loads and stored ensemble of prediction timeseries used to inform NYC releases during simulation.

When calculating NYC release, we need use forecast/predicted downstream flows to calculate the releases neede to maintain the Montague and Trenton flow targets in 1-4 days ahead. These predictions are generated prior to the simulation (e.g., pywrdrb.pre.PredictedInflowPreprocessor) and stored in an HDF5 file, with unique predictions for each realization member.

setup()

Perform setup operations for the parameter. Automated pywr operation.

value(timestep, scenario_index)

Return the current flow for the specified timestep and scenario index.

load(model, data)

Load the parameter from the model dictionary.

ensemble_indices

The realization indices of the inflow ensemble to be used for this simulation.

Type:

list

pred_column_indices

The column indices of the inflow ensemble DataFrame corresponding to the realization indices.

Type:

list

pred_ensemble

The DataFrame containing the inflow ensemble data, indexed by datetime.

Type:

DataFrame

__init__(model, column, inflow_type, ensemble_indices, **kwargs)

Initialize the PredictionEnsemble parameter.

Parameters:

• model (Model) – The pywrdrb.Model object.

• column (str) – The name of the column in the HDF5 file to be used for the ensemble.

• inflow_type (str) – The dataset label. Expects to find an HDF5 file with inflow ensemble data in the pn.flows.input_dir directory.

• ensemble_indices (list) – The realization indices of the inflow ensemble to be used for this simulation.

• **kwargs (dict) – Additional keyword arguments to be passed to the pywr.Parameter class. None used.

Return type:

None

Methods

__init__(model, column, inflow_type, ...)	Initialize the PredictionEnsemble parameter.
after(self)
before(self)
finish(self)
get_all_values(self)
get_constant_value(self)	Return a constant value.
get_double_lower_bounds(self)
get_double_upper_bounds(self)
get_double_variables(self)
get_integer_lower_bounds(self)
get_integer_upper_bounds(self)
get_integer_variables(self)
get_value(self, ScenarioIndex scenario_index)
load(model, data)	Load the parameter using the pywrdrb.Model dictionary.
register(cls)
reset(self)
set_double_variables(self, double[)
set_integer_variables(self, int[)
setup()	Perform setup operations for the parameter.
unregister(cls)
value(timestep, scenario_index)	Return the current flow across scenarios for the specified timestep and scenario index.

Attributes

children
comment	str
double_size	'int'
integer_size	'int'
is_constant
is_variable	'bool'
model
name
parents
size
tags	dict