Plot inside a function

When working with Julia, it is common to encounter situations where you need to create a plot inside a function. This can be a bit tricky, as the plotting library in Julia, Plots.jl, requires some special handling when used inside a function.

Option 1: Using the global scope

One way to solve this issue is by using the global scope. By declaring the plot object as a global variable, it can be accessed and modified inside the function. Here’s an example:

using Plots

function plot_inside_function()
    global plot_object = plot()
    # Modify the plot object as needed
    plot_object = plot_object |> plot!(1:10, rand(10))
    # Show the plot
    display(plot_object)
end

plot_inside_function()

This approach works, but it is not recommended as it relies on global variables, which can lead to potential issues with variable scoping and code maintainability.

Option 2: Passing the plot object as an argument

A better approach is to pass the plot object as an argument to the function. This way, the function can modify the plot object directly without relying on global variables. Here’s an example:

using Plots

function plot_inside_function(plot_object)
    # Modify the plot object as needed
    plot_object = plot_object |> plot!(1:10, rand(10))
    # Show the plot
    display(plot_object)
end

# Create the plot object outside the function
plot_object = plot()
plot_inside_function(plot_object)

This approach is cleaner and more modular, as it avoids the use of global variables. It also allows for better code organization and reusability.

Option 3: Returning the modified plot object

Another option is to have the function return the modified plot object, instead of displaying it directly. This allows for more flexibility, as the caller can decide how to handle the plot object. Here’s an example:

using Plots

function plot_inside_function()
    plot_object = plot()
    # Modify the plot object as needed
    plot_object = plot_object |> plot!(1:10, rand(10))
    # Return the modified plot object
    return plot_object
end

# Call the function and handle the plot object as desired
plot_object = plot_inside_function()
display(plot_object)

This approach provides the most flexibility, as it allows the caller to decide how to handle the plot object. It can be useful when you need to further modify or combine multiple plots.

Overall, option 2, which involves passing the plot object as an argument, is the recommended approach. It provides a good balance between code organization, modularity, and flexibility. However, the best option may vary depending on the specific requirements of your project.