Fix parameter when passing to optimizer

When working with optimizers in Julia, it is common to encounter situations where you need to fix certain parameters while optimizing others. In this article, we will explore three different ways to fix parameters when passing them to an optimizer in Julia.

Option 1: Using a closure

One way to fix parameters when passing them to an optimizer is by using a closure. A closure is a function that captures variables from its surrounding environment. By defining a closure, we can fix the desired parameters and pass the closure to the optimizer.

using Optim

function objective(x, fixed_param)
    # Define your objective function here
    # Use fixed_param in the objective function
end

fixed_param = 10.0
objective_closure = x -> objective(x, fixed_param)

result = optimize(objective_closure, initial_guess)

In this code snippet, we define the objective function `objective` that takes two arguments: `x` and `fixed_param`. We then create a closure `objective_closure` that fixes the `fixed_param` value and passes it to the optimizer using the `optimize` function.

Option 2: Using a function with default arguments

Another way to fix parameters when passing them to an optimizer is by using a function with default arguments. Default arguments allow us to specify a default value for a function parameter, which can be overridden when calling the function.

using Optim

function objective(x, fixed_param=10.0)
    # Define your objective function here
    # Use fixed_param in the objective function
end

result = optimize(x -> objective(x), initial_guess)

In this code snippet, we define the objective function `objective` with a default argument `fixed_param=10.0`. This allows us to fix the `fixed_param` value to 10.0 when calling the function. We then pass the objective function to the optimizer using the `optimize` function.

Option 3: Using a mutable struct

A third way to fix parameters when passing them to an optimizer is by using a mutable struct. A mutable struct is a user-defined type that can be modified after creation. By defining a mutable struct with the desired parameters, we can fix the values and pass the struct to the optimizer.

using Optim

mutable struct Objective
    fixed_param
end

function (obj::Objective)(x)
    # Define your objective function here
    # Use obj.fixed_param in the objective function
end

fixed_param = 10.0
objective = Objective(fixed_param)

result = optimize(objective, initial_guess)

In this code snippet, we define a mutable struct `Objective` with a single field `fixed_param`. We then define a function that takes an `Objective` object and an `x` argument. Inside the function, we can access the `fixed_param` field of the `Objective` object. We create an `Objective` object with the desired `fixed_param` value and pass it to the optimizer using the `optimize` function.

After exploring these three options, the best approach depends on the specific requirements of your problem. If you only need to fix a single parameter, using a closure or a function with default arguments can be more concise. However, if you have multiple parameters to fix, using a mutable struct provides a more structured and extensible solution.

Choose the option that best suits your needs and enjoy optimizing with Julia!