gauss jordan method python
# Importing NumPy Library
import numpy as np
import sys
# Reading number of unknowns
n = int(input('Enter number of unknowns: '))
# Making numpy array of n x n+1 size and initializing
# to zero for storing augmented matrix
a = np.zeros((n,n+1))
# Making numpy array of n size and initializing
# to zero for storing solution vector
x = np.zeros(n)
# Reading augmented matrix coefficients
print('Enter Augmented Matrix Coefficients:')
for i in range(n):
for j in range(n+1):
a[i][j] = float(input( 'a['+str(i)+']['+ str(j)+']='))
# Applying Gauss Jordan Elimination
for i in range(n):
if a[i][i] == 0.0:
sys.exit('Divide by zero detected!')
for j in range(n):
if i != j:
ratio = a[j][i]/a[i][i]
for k in range(n+1):
a[j][k] = a[j][k] - ratio * a[i][k]
# Obtaining Solution
for i in range(n):
x[i] = a[i][n]/a[i][i]
# Displaying solution
print('\nRequired solution is: ')
for i in range(n):
print('X%d = %0.2f' %(i,x[i]), end = '\t')
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