Скачать или смотреть Fixing 2D Matrix Initialization in Python: Ensure Correct Row Major Order Filling

Discover how to correctly initialize a 2D matrix in Python using list comprehension, ensuring the desired row major order filling.
---
This video is based on the question https://stackoverflow.com/q/63758415/ asked by the user 'Diya' ( https://stackoverflow.com/u/14131780/ ) and on the answer https://stackoverflow.com/a/63758453/ provided by the user 'Gil Pinsky' ( https://stackoverflow.com/u/4757715/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: filling 2D Matrix in row major order

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Fixing 2D Matrix Initialization in Python: Ensure Correct Row Major Order Filling

Creating a 2D matrix in Python can sometimes lead to unexpected outcomes, especially for newish programmers who might not be fully versed in the intricacies of list initialization. One common mistake occurs when trying to fill a matrix in row major order. In this guide, we will explore how to fix this issue so your 2D array behaves just as you expect.

Understanding the Problem

Let's take a look at the code that caused the confusion:

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

When this code is run, the output is as follows:

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

As you can see, this is not the desired output; instead of creating a filled 2D array from 1 to 9, we end up with multiple identical rows. The intended outcome was:

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

What Went Wrong?

The issue lies in how the 2D list A is initialized. The code A = [[0]*N]*N creates a matrix with rows that reference the same inner list in memory. This means when you modify one of the inner lists, it affects all of them, which is why every row ends up identical after the loop completes.

The Solution

To fix this problem, we need to ensure that each row in the 2D matrix points to different lists in memory. We can achieve this using list comprehension. Here’s the corrected code:

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

Explanation of the Fix

List Comprehension: The line A = [[0 for k in range(N)] for m in range(N)] creates a new list for each row of the matrix, effectively preventing the issue of reference copying. Each row is now its own distinct list.

Filling the Matrix: The nested for loops remain unchanged, allowing us to fill each element of the matrix correctly in row major order.

Output: When you run the corrected code, you should see the desired output:

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

Conclusion

By understanding how Python handles list initialization and making the simple adjustment of using list comprehension, you can easily create a 2D matrix that meets your expectations. This not only prevents unexpected behavior but also enhances your coding skills by building a solid foundation for working with data structures in Python.

If you run into problems while coding, remember that taking a step back to understand how elements are stored and referenced can often point you in the direction of the solution. Happy coding!