How to Use scipy.optimize.root_scalar() with Multiple Arguments in Python

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Introduction to the Problem

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And call it with arguments like:

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You may encounter a TypeError indicating that root_scalar() received multiple values for the argument args. This clearly suggests a misunderstanding in how to pass the function arguments correctly.

Understanding the Error

The key to resolving this issue lies in how the function and its arguments are structured. In the code:

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The issue arises because f is expecting its first argument as y, but m_l and m_B appear first in the args. The root_scalar function interprets it incorrectly, causing the error.

The Necessary Adjustments

Reordering Arguments

To avoid this confusion, you need to adjust the function definitions to ensure that the first argument corresponds to what root_scalar() expects. Here’s how you can redefine your function:

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Notice how y is now defined as the first parameter of the functions f and df.

Calling root_scalar Correctly

Now you can correctly call root_scalar like this:

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Key Code Steps

Here are the complete steps you would follow:

Import Numpy and SciPy: Ensure you have the necessary libraries imported.

Define Your Functions: Make sure to place the variable that will be iterated upon (y) as the first argument in your function definitions.

Setup Your Variables: Prepare the arrays and initial guess.

Call root_scalar(): With the correct ordering and passing of args, find the root.

Final Thoughts

Example Code

Here’s the full example code that incorporates all the outlined solutions:

[[See Video to Reveal this Text or Code Snippet]]