ciemss / pyciemss

Causal and probabilistic reasoning with continuous time dynamical systems
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Add parameter value and start time as combined intervention for optimize #584

Closed anirban-chaudhuri closed 3 months ago

liunelson commented 3 months ago

For clarity, this refers to a new type of intervention templates, right?


static_parameter_interventions = param_value_objective(...)
# static_parameter_interventions = start_time_objective(...)
# static_parameter_interventions = param_value_start_time_objective(...) <--- ?

result = pyciemss.optimize(
    model,
    end_time,
    logging_step_size,
    qoi,
    risk_bound,
    static_parameter_interventions,
    objfun,
    initial_guess_interventions = initial_guess_interventions,
    bounds_interventions = bounds_interventions,
    start_time = start_time,
    n_samples_ouu = num_samples_ouu,
    maxiter = maxiter,
    maxfeval = maxfeval,
    solver_method = "rk4",
    solver_options = {"step_size": 1.},
)