Model

class rameau.core.Model(tree, inputs, init_states=None, simulation_settings=None, optimization_settings=None, forecast_settings=None, output_settings=None)[source]

Define a rameau model.

Parameters:

tree (dict or Tree) – Watershed connection tree.
inputs (dict or inputs.InputCollection) – Model input data.
init_states (dict or states.StatesCollection, optional) – Model initial states.
simulation_settings (dict or SimulationSettings, optional) – Settings related to a simulation run. See SimulationSettings for details.
optimization_settings (dict or OptimizationSettings, optional) – Settings related to an optimisation run. See OptimizationSettings for details.
forecast_settings (dict or ForecastSettings, optional) – Settings related to a forecast run. See ForecastSettings for details.
output_settings (dict or OutputSettings, optional) – Settings related to the simulation outputs See OutputSettings for details.

Returns:

Model

Examples

Constructing model from Tree and inputs.InputCollection.

>>> data = np.array([0.1, 0.2, 0.3])
>>> model = rm.Model(
...     tree=rm.Tree(watersheds=[{}]),
...     inputs=rm.inputs.InputCollection(rainfall=data, pet=data)
... )
>>> model.inputs.rainfall.data
array([[0.1],
       [0.2],
       [0.3]], dtype=float32)

Constructing model from dict.

>>> model = rm.Model(
...     tree=dict(watersheds=[{}]),
...     inputs=dict(rainfall=data, pet=data)
... )
>>> model.inputs.rainfall.data
array([[0.1],
       [0.2],
       [0.3]], dtype=float32)

Methods

`create_simulation`(**kwargs)	Create a simulation.
`from_toml`(path[, load_inputs])	Load a model from a TOML file.
`get_input`([variable])	Get model input data.
`run_forecast`([emission_date, scope, ...])	Start a forecast run.
`run_optimization`([maxit, starting_date, ...])	Start an optimisation run.
`run_simulation`([name, starting_date, ...])	Start a simulation run.
`to_toml`(path[, tree])	Dump the model to a TOML file.

Attributes

`forecast_settings`	Settings related to an forecast run.
`init_states`	Model initial states.
`inputs`	Model input data.
`optimization_settings`	Settings related to an optimization run.
`output_settings`	Settings related to simulation outputs.
`simulation_settings`	Settings related to a simulation run.
`tree`	Watershed connection tree of the model.