From bb26d94821e2b57b0f3ef5df71d229fff066154b Mon Sep 17 00:00:00 2001 From: Anirban Chaudhuri <75496534+anirban-chaudhuri@users.noreply.github.com> Date: Thu, 21 Mar 2024 13:55:59 -0400 Subject: [PATCH] Revert "update optimize documentation for definition of static_parameter_intervention" This reverts commit 11cdaa9e5bb9f019eb07e57acb5d5c46e467b10b. --- pyciemss/interfaces.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/pyciemss/interfaces.py b/pyciemss/interfaces.py index 197754825..9adf72bfc 100644 --- a/pyciemss/interfaces.py +++ b/pyciemss/interfaces.py @@ -791,11 +791,11 @@ def optimize( - A callable function defining the quantity of interest to optimize over. risk_bounds: float - The threshold on the risk constraint. - static_parameter_interventions: Callable[[torch.Tensor], Dict[float, Dict[str, Intervention]]] - - A callable function of static parameter interventions to optimize over. - - The callable functions are created using the provided templates: - - param_value_objective(): creates a static parameter intervention when optimizing over (multiple) parameter values - - start_time_objective(): creates a static parameter intervention when optimizing over (multiple) start times for different parameter + static_parameter_interventions: Dict[torch.Tensor, str] + - A dictionary of the form {intervention_time: parameter_name} + of static parameter interventions to optimize over. + - Each key is the time at which the intervention is applied. + - Each value is a string with the intervention parameter name. objfun: Callable - The objective function defined as a callable function definition. - E.g., to minimize the absolute value of intervention parameters use lambda x: np.sum(np.abs(x))