ItsMyCode: nxnxn matrix python

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In this tutorial, we will take a look at how to create the nxnxn matrix in Python.

What is NxNxN?

The term NxNxN (pronounced as N by N by N) is also called as NxNxN cube or NxNxN puzzle. It represents the cube with the same dimensions that means the cube will have the same height, width, and length.

The NxNxN puzzles that fit under this category include the 2x2x2 cube, the Rubik’s cube, the 4x4x4 cube, the 5x5x5 cube, etc. The 1x1x1 cube also belongs in this category, even if it is not a twisty puzzle because it does complete the NxNxN set.

How to Create NxNxN Matrix in Python?

Now that we know what is nxnxn, lets us learn how to create the nxnxn matrix in Python using different ways with examples.

Create NxN Matrix in Python with Non Duplicating numbers

The below code is to create an nxn matrix in Python, and it does not repeat the numbers row-wise and column-wise. These are mainly used in Puzzles like Sudoko.

# Python Program to create nxn Matrix
import numpy as np

# Provide the value of N 
N = 5

# returns evenly spaced values 
row = np.arange(N)

# create an new array filled with zeros of given shape and type
result = np.zeros((N, N))

# Logic to roll array elements of given axis
for i in row:
    result[i] = np.roll(row, i)

print(result)

Output

[[0. 1. 2. 3. 4.]
 [4. 0. 1. 2. 3.]
 [3. 4. 0. 1. 2.]
 [2. 3. 4. 0. 1.]
 [1. 2. 3. 4. 0.]]

Create NxNxN matrix in Python using numpy

The below code is to create an nxnxn matrix in Python. Just change the value of N based on the requirement and the shape that you need to generate. For a standard Rubik’s cube, it would be 3x3x3, so the value of n would be 3.

Example: 

# Python program to create nxnxn matrix
import numpy as np

# Provide the value of nxnxn
n = 3
a = np.arange(n)
b = np.array([a]*n)
matrix = np.array([b]*n)

#creating an array containg n-dimensional points
flat_mat = matrix.reshape((int(matrix.size/n),n))

#just a random matrix we will use as a rotation
rotate = np.eye(n) + 2

#apply the rotation on each n-dimensional point
result = np.array([rotate.dot(x) for x in flat_mat])
#return to original shape
result=result.reshape((n,n,n))
print(result)

Output

[[[6. 7. 8.]
  [6. 7. 8.]
  [6. 7. 8.]]

 [[6. 7. 8.]
  [6. 7. 8.]
  [6. 7. 8.]]

 [[6. 7. 8.]
  [6. 7. 8.]
  [6. 7. 8.]]]

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Python Bytes: #256 And the best open source project prize goes to ...

<p><strong>Watch the live stream:</strong></p> <a href='https://www.youtube.com/watch?v=ZrcwAIix9UA' style='font-weight: bold;'>Watch on YouTube</a><br> <br> <p><strong>About the show</strong></p> <p>Sponsored by <strong>Shortcut - Get started at</strong> <a href="http://shortcut.com/pythonbytes"><strong>shortcut.com/pythonbytes</strong></a></p> <p>Special guest: <strong>The Anthony Shaw</strong></p> <p><strong>Michael #0: It’s episode 2^8 (nearly 5 years of podcasting)</strong></p> <p><strong>Brian #1:</strong> <a href="https://lukasz.langa.pl/f15a8851-af26-4e94-a4b1-c146c57c9d20/"><strong>Where does all the effort go?</strong></a><a href="https://lukasz.langa.pl/f15a8851-af26-4e94-a4b1-c146c57c9d20/"><strong>:</strong></a> <a href="https://lukasz.langa.pl/f15a8851-af26-4e94-a4b1-c146c57c9d20/"><strong>Looking at Python core developer activity</strong></a></p> <ul> <li>Łukasz Langa</li> <li>A look into CPython repository history and PR data</li> <li>Also, nice example of datasette in action and lots of SQL queries. </li> <li>The data, as well as the process, is open for anyone to look at.</li> <li>Cool that the process was listed in the article, including helper scripts used.</li> <li>Timeframe for data is since Feb 10, 2017, when source moved to GitHub, through Oct 9, 2021. <ul> <li>However, some queries in the article are tighter than that.</li> </ul></li> <li>Queries <ul> <li>Files involved in PRs since 1/1/20 <ul> <li>top is ceval.c with 259 merged PRs</li> </ul></li> <li>Contributors by number of merged PRs <ul> <li>lots of familiar names in the top 50, along with some bots</li> <li>it’d be fun to talk with someone about the bots used to help the Python project</li> <li>nice note: “Clearly, it pays to be a bot … or a release manager since this naturally causes you to make a lot of commits. But Victor Stinner and Serhiy Storchaka are neither of these things and still generate amazing amounts of activity. Kudos! In any case, this is no competition but it was still interesting to see who makes all these recent changes.”</li> </ul></li> <li>Who contributed where? <ul> <li>Neat. There’s a self reported <a href="https://devguide.python.org/experts/">Experts Index</a> in the very nice <a href="https://devguide.python.org/">Python Developer’s Guide</a>. But some libraries don’t have anyone listed. The data does though. </li> <li>Łukasz generated a <a href="https://lukasz.langa.pl/f15a8851-af26-4e94-a4b1-c146c57c9d20/assets/all_experts.txt">top-5 list</a> for each file. Contributing to some file and have a question. 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