Скачать или смотреть How to Append 2D and 3D Arrays in Python for New 3D Structures

Learn how to successfully combine `2D` and `3D` arrays in Python using NumPy, creating a new 3D array while avoiding common errors.
---
This video is based on the question https://stackoverflow.com/q/71742300/ asked by the user 'squip_works' ( https://stackoverflow.com/u/18705487/ ) and on the answer https://stackoverflow.com/a/71742722/ provided by the user 'hpaulj' ( https://stackoverflow.com/u/901925/ ) 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: python: Appending 2D and 3D array to make new 3D (bigger 3rd dimension)

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.
---
How to Append 2D and 3D Arrays in Python for New 3D Structures

Appending data from multiple arrays in Python, especially when dealing with multidimensional arrays, can seem daunting. A common issue arises when trying to merge a 2D array with a 3D array seamlessly. If you’re facing a situation where you need to augment your data with new parameters while avoiding errors, this guide will walk you through the process step-by-step.

The Problem Statement

Imagine you have two arrays:

Array A: [3124, 5]

This represents 3124 different models, each with 5 reference parameters.

Array B: [3124, 19, 12288]

This array consists of 3124 models as well, but each of these models has 19 time steps and 12288 data points representing temperature fields.

Your goal is to create a new array (AB) that combines these two arrays, such that AB has the shape [3124, 19, 12293], incorporating the 5 values from A into the beginning of the temperature field data in B for each time step.

If you attempt to use a function like np.dstack() to combine the arrays, you may run into the following error message:

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

This is a common issue when trying to combine arrays of different shapes or dimensions. Let’s delve into the solution.

Solution Overview

To achieve the desired result, you need to make sure that the dimensions of both arrays match appropriately along the axes you want to concatenate. Here’s how to accomplish this using NumPy, a powerful library for numerical computations in Python.

Step-by-Step Guide

Expand Array A:
We need to reshape A so it can be compatible with B. Specifically, we want to add dimensions to A and repeat its parameters across the time steps. Use the following code:

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

This code expands A to have the shape (3124, 19, 5), which creates a new dimension for time steps and duplicates A across those steps.

Check Shapes:
After expansion, you can confirm the shape of A to ensure it matches what we expect:

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

Concatenate the Arrays:
Now that both A and B are compatible, you can concatenate them along the last axis (axis 2):

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

This will yield a new array AB with the shape (3124, 19, 12293) as desired.

Final Shape Check:
Verify the final array's shape to confirm everything looks good:

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

Conclusion

By following the outlined steps, you can successfully combine a 2D and a 3D array in Python while mitigating common errors encountered during the process. Using NumPy’s powerful functionality allows for efficient reshaping and concatenating of arrays, enabling seamless data manipulation for a variety of applications.

If you encounter any challenges or have questions on this topic, feel free to reach out or leave a comment below! Happy coding!