why do I get a negative numbers???
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im in the process of programming for a project and i keep getting funtionally impossible answers for the variables everytime i run the code it says it stops prematurely so is that the main problem? it is currently only going through "2.300000e+03" itterations is there a way to increase that?
4 Comments
Jacob Mathew
on 29 Nov 2024
Hi Jonah,
Could you share related code to help debug ?
Walter Roberson
on 29 Nov 2024
Are you using:
- fminunc
- fmincon
- fsolve
- fzero
- ga
- vpasolve
- something else?
If you are using fmincon() are you using any constraints?
If you are using fzero() are you using a single scalar as the starting point, or are you using a vector of two values?
Jonah
on 29 Nov 2024
Jonah
on 29 Nov 2024
Answers (1)
Walter Roberson
on 29 Nov 2024
opts = optimoptions('fsolve', 'MaxFunctionEvaluations', 1e6, 'MaxIterations', 1e6);
Guess = linspace(0,.001, 23);
Answers = fsolve(function_name, Guess, opts)
Notice that the guess is set to something non-zero: it is often a bad choice to start the function off at the all-zero vector.
4 Comments
Jonah
on 29 Nov 2024
Jonah
on 29 Nov 2024
Walter Roberson
on 29 Nov 2024
There is no way to force fsolve to give only positive answers.
Generally speaking, the way around that is to instead use fmincon:
fun2 = @(X) function_name(X).^2;
A = []; b = [];
Aeq = []; beq = [];
lb = zeros(1,length(Guess));
ub = inf(1,length(Guess));
nonlcon = [];
opts = optimoptions('fmincon', 'MaxFunctionEvaluations', 1e6, 'MaxIterations', 1e6);
Answers = fmincon(fun2, Guess, A, b, Aeq, beq, nonlcon, opts);
The trick here is that solving for zero is closely approximated by minimizing the square of the function.
Torsten
on 29 Nov 2024
There is no way to force fsolve to give only positive answers.
Generally speaking, the way around that is to instead use fmincon
... or to use the variables squared instead of the variables themselves in the equations you are trying to solve.
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