Loss_Fun how to programm it

Question

Farah Shahpoor 2019-5-21

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/463299-loss_fun-how-to-programm-it

关闭： MATLAB Answer Bot 2021-8-20

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Dear Community,

I have an optimazation problem.

I want to minimize the function:

L = Exp(0.5*pi)+ Exp(0.25*x)

I have the following code and need to understand it.

function [ LossVal, vol_pi, vol_x,vol_s ] = Loss_Fun( data, w_pi, w_x )
vol_pi = (mean(data.pi.^2));
vol_x = (mean(data.x.^2));
vol_s = (mean(data.st.^2));
LossVal =   w_pi * vol_pi ...
          + w_x  * vol_x  ...
          + w_s  * vol_s;
         w_pi = 0.5 ;   %1;
         w_x = 0.25;   %0.5;
       
end

As I understand w_pi and w_x are the weights of the paramater pi and x.

My problem is what is meant by data: Loss_Fun( data, w_pi, w_x )

vol_pi vol_x and vol_s should the mean, which I need for the function.

When Iam using this code for my model matlab gives me the errror:

Not enough input arguments.

Error in Loss_Fun (line 3)

vol_pi = (mean(data.pi.^2));

From where does matlab take this

vol_pi = (mean(data.pi.^2));
vol_x = (mean(data.x.^2));
vol_s = (mean(data.st.^2));

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Answer 1

Saumya Goel 2019-5-24

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链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/463299-loss_fun-how-to-programm-it#answer_376441

Whenever Loss_Fun is called, there are 3 input arguments that needs to be passed. So, data is one of them, which should contain -pi,x and st values on basis of which it will calculate the variables vol_pi,vol_x,vol_s.

Also, if you are looking for predefined functionalities on Optimization Problem, you may consider having a look at Optimization Toolbox: https://www.mathworks.com/help/optim/write-objective-function.html

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Farah Shahpoor 2019-5-24

在 MATLAB Online 中打开

Thanks for your reply.

This is my code now. When I run the code I am getting the error:

Not enough input arguments.

Error in lossc (line 3)

vol_pi = (mean(data.v_solution(2).^2));

and so on. What is the problem here?

function [ LossVal, vol_pi, vol_x ] = Loss_Fun( data, w_pi, w_x )
vol_pi = (mean(data.v_solution(2).^2));
vol_x = (mean(data.v_solution(1).^2));
LossVal =   w_pi * vol_pi ...
          + w_x  * vol_x;
       
         w_pi = 0.5 ;   %1;
         w_x = 0.25;   %0.5;
       
end