Hi Rafegh,
I understand that you want to fit a specific level (0.5) of a contour plot to your data (shown in yellow and blue dots) and find the optimal set of input variables for a function with 6 input variables. Here's a way to do it in MATLAB:
- Define your function.
- Create a function to calculate the difference between your data and the 0.5 contour level.
- Use fmincon to minimize this difference and find the optimal input variables.
Here's an example code:
% Example function with 6 input variables
myFunction = @(x1, x2, x3, x4, x5, x6, X, Y) ... % define your function
% Objective function to minimize the difference to the 0.5 contour
objective = @(vars) sum((myFunction(vars(1), vars(2), vars(3), vars(4), vars(5), vars(6), X, Y) - 0.5).^2);
% Initial guess for the variables
initialGuess = [1, 1, 1, 1, 1, 1];
% Optimization options
options = optimoptions('fmincon', 'Display', 'iter', 'Algorithm', 'interior-point');
% Run the optimization
optimalVars = fmincon(objective, initialGuess, [], [], [], [], [], [], [], options);
% Display the optimal variables
disp('Optimal variables:');
disp(optimalVars);
You can refer to the MathWorks documentation for more details on fmincon: https://www.mathworks.com/help/optim/ug/fmincon.html
Hope this helps.
Regards,
Nipun
