# 10.3: Basic Gauss Jordan

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#  Load Useful Python Libraries
import numpy as np
import sympy as sym
sym.init_printing(use_unicode=True)

The following is implementation of the Basic Gauss-Jordan Elimination Algorithm for Matrix $$A^{m \times n}$$ (Pseudocode):

for i from 1 to m:
for j from 1 to m
if i ≠ j:
Ratio = A[j,i]/A[i,i]
#Elementary Row Operation 3
for k from 1 to n:
A[j,k] = A[j,k] - Ratio * A[i,k]
next k
endif
next j

#Elementary Row Operation 2
Const = A[i,i]
for k from 1 to n:
A[i,k] = A[i,k]/Const
next i

##### Do This

using the Pseudocode provided above, write a basic_gauss_jordan function which takes a list of lists $$A$$ as input and returns the modified list of lists:

# Put your answer here.

Lets check your function by applying the basic_gauss_jordan function and check to see if it matches the answer from matrix $$A$$ in the pre-class video:

A = [[1, 1, 1, 2], [2, 3, 1, 3], [0, -2, -3, -8]]
sym.Matrix(answer)
answer_from_video = [[1, 0, 0, -1], [0, 1, 0, 1], [0, 0, 1, 2]]
np.allclose(answer, answer_from_video)

The above psuedocode does not quite work properly for all matrices. For example, consider the following augmented matrix:

$\begin{split} B = \left[ \begin{matrix} 0 & 1 & 33\\ 5 & 3 & 7 \\ 6 & 69 & 4 \end{matrix} \, \middle\vert \, \begin{matrix} 30 \\ 90 \\ 420 \end{matrix} \right] \end{split} \nonumber$

##### Question

Explain why doesn’t the provided basic_gauss_jordan function work on the matrix $$B$$?

##### Question

Describe how you could modify matrix $$B$$ so that it would work with basic_gauss_jordan AND still give the correct solution?

This page titled 10.3: Basic Gauss Jordan is shared under a CC BY-NC 4.0 license and was authored, remixed, and/or curated by Dirk Colbry via source content that was edited to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.