Forecast uncertainty

class rtctools.optimization.control_tree_mixin.ControlTreeMixin(*args, **kwargs)[source]

Bases: rtctools.optimization.optimization_problem.OptimizationProblem

Adds a stochastic control tree to your optimization problem.

control_tree_options() → Dict[str, Union[List[str], List[float], int]][source]

Returns a dictionary of options controlling the creation of a k-ary stochastic tree.

Option Type Default value
forecast_variables list of strings All constant inputs
branching_times list of floats self.times()
k int 2

A k-ary tree is generated, branching at every interior branching time. Ensemble members are clustered to paths through the tree based on average distance over all forecast variables.

Returns:A dictionary of control tree generation options.