Trying to solve use Gauss elimination to solve

I’ve tried solving the matrix using gauss elimination, and as far as I know, the first portion of the code is correct, but I’m not sure I’m calling the matrix correctly

Hi Dave, and welcome!

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Continuing the discussion from Trying to solve use Gauss elimination to solve:

Thanks for the notice Steven, here’s the code.

import numpy as np
import copy
from numpy import c_

def GaussNaive(A,b):
    'solve Ax=b using Naive Gauss elimination'
    A=A.astype(np.float64) ; b=b.astype(np.float64)
    m,n = A.shape
    if m != n:
        print('Matrix A must be square')
    m1,n1 = b.shape
    if m1 != m:
        print('b and A must have the same number of rows')
    Aug = c_[A,b]
    nm1 = n-1; np1 = n+1
    for i in range(nm1):
        for j in range(i+1,n):
            fac = Aug[j,i]/Aug[i,i]
            for k in range(i,np1):
                Aug[j,k] += -Aug[i,k]*fac
    for i in range(nm1-1,-1,-1):
        for k in range (i+1,n):
            s += x[k]*Aug[i,k]
    print('\n {x} ='); print(x)
    return x

if __name__ == '__problem_4__':
    A=[[1, 1, -1],
      [6, 2, 2],
      [-3, 4, 1]]
    b=[-3, 2, 1]

The values of A and b that are being passed into GaussNaive are lists of lists, so A.astype(np.float64) and b.astype(np.float64) aren’t going to work because lists don’t have a .astype method.

They need to be converted to numpy arrays first:

A = np.array(A).astype(np.float64)
b = np.array(b).astype(np.float64)