Run optimize through a UI

[MosaSalim99]

Hi! First of all great Plugin! I am creating a tool that calculates utilization, carbon emission and cost of roof trusses and then outputs the best solution based on some inputs. I created a UI through human UI to get the inputs from the user but i want to include a few inputs to go to the tunny component UI. I used MetaHopper to refrence the tunny component and then in to python, but i cant figureout how to input the values i want, which are:
(Optimize tab)
Number of trials
Study Name
RunOptimize
(Visualize tab)
Open Optuna-Dashboard
(Output tab)
Target Study
All trials

[hrntsm]

Thanks @MosaSalim99 for your interest.
Sorry, I don't know much about Metahopper so I don't yet understand what kind of question you are asking.
Can you give me more details?

[MosaSalim99]

Shure!
The MetaHopper isnt that important i just use it so i can connect my Tunny component with Python.
I want to access the Tunny UI (when i doubbleclick Tunny) and input the values listed earlier, however i want to do it without opening the Tunny UI.

[hrntsm]

Tunny is optimizing by creating an Optuna class and executing the RunSolver method, but Tunny's optimization may not work well because it is based on the TunnyUI assumption.

Tunny/Tunny/Solver/Optuna.cs

Lines 22 to 62 in d101e78

	public class Optuna : PythonInit
	{
	public double[] XOpt { get; private set; }
	private readonly string _componentFolder;
	private readonly bool _hasConstraint;
	private readonly TunnySettings _settings;
	public Optuna(string componentFolder, TunnySettings settings, bool hasConstraint)
	{
	_componentFolder = componentFolder;
	_settings = settings;
	_hasConstraint = hasConstraint;
	}
	public bool RunSolver(
	List<Variable> variables,
	IEnumerable<IGH_Param> objectives,
	Dictionary<string, FishEgg> fishEggs,
	Func<ProgressState, int, EvaluatedGHResult> evaluate)
	{
	string[] objNickName = GetObjectiveNickName(objectives);
	EvaluatedGHResult Eval(ProgressState pState, int progress)
	{
	return evaluate(pState, progress);
	}
	try
	{
	var optimize = new Algorithm(variables, _hasConstraint, objNickName, fishEggs, _settings, Eval);
	optimize.Solve();
	XOpt = optimize.XOpt;
	ShowEndMessages(optimize.EndState);
	return true;
	}
	catch (Exception e)
	{
	ShowErrorMessages(e);
	return false;
	}
	}