Скачать или смотреть How to Split a 2D Numpy Array into Smaller Arrays by Grid

Learn how to effectively split a large 2D numpy array into multiple smaller arrays using grid sizing. Our step-by-step guide makes it simple to break down your data!
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Splitting a 2D Numpy Array by Grid: A Comprehensive Guide

If you have ever found yourself needing to split a large 2D numpy array into smaller sections, you’re in luck! In this guide, we’ll walk you through how to divide an array into multiple smaller arrays using grid sizing. This can be particularly useful in applications such as image processing, data analysis, and more.

The Problem: Splitting a 2D Array

Let's say you have the following numpy 2D array:

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This prints out the array as follows:

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Your goal is to split this 6x6 array into smaller 2D arrays of size 3x3, like extracting pieces of a larger image. The expected output should look like this:

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The Solution: Using Numpy's Stride Tricks

To achieve this task, we can utilize a function from the numpy library called sliding_window_view. This function allows us to create a sliding window of the required shape, which in this case is (2, 2) for the smaller arrays.

Here’s how you can do it:

Import the necessary module:
Make sure you have numpy and sliding_window_view imported.

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Apply the sliding window:
Use the following code to split your original array into the smaller arrays:

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Check your output:
To see the result, convert the output to a list and print it:

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This will output:

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Conclusion

Splitting a large 2D numpy array into smaller arrays by grid sizes is a surprisingly easy task when you know the right tools in numpy. By leveraging the power of the sliding_window_view function, you can quickly and effectively divide your data into manageable sections. Now, whether you're handling images, data matrices, or other forms of structured data, this technique can save you time and effort.

Feel free to experiment with different grid sizes and explore the versatility of numpy in data manipulation. Happy coding!