CODEWITHSUNDEEP
pythonnumpy
dinusha
dinusha

Reputation: 43

Two different numpy arrays are being assigned the same values when only one array is being referenced

I'm trying to write some code to carry out the Jacobi method for solving linear equations (I realise my method is not the most efficient way to do this but I am trying to figure out why it's not working).

I have tried to debug the problem and noticed the following issue. The code finishes after 2 iterations because on the second iteration on line 32 when xnew[i] is assigned a new value, the same value is also assigned to x[i], even though x[i] is not referenced. Why is this happening on the second iteration and not the first time the for loop is run and is there a way to fix this?

Thanks in advance

import numpy as np

A = np.array(
    [[0.93, 0.24, 0],
     [0.04, 0.54, 0.26],
     [1, 1, 1]])

b = np.array([[6.0], [2.0], [10.0]])

n , m  = np.shape(A) 

x = np.zeros(shape=(n,1))

xnew = np.zeros(shape=(n,1))

iterlimit = 100 
tol = 0.0000001 


for  iteration in range(iterlimit):

    convergence = True
    for i in range(n):
        sum=0
        for j in range(n):
            if j != i:
                sum = sum + (A[i,j] * x[j])
        
        #on second iteration (iteration =1) below line begins to
        #assign x[i] the same values as it assigns xnew[i] causing the 
        #convergence check below to not run and results in a premature break
        xnew[i] = 1/A[i,i] * (b[i] - sum) 
                     
        if abs(xnew[i]-x[i]) > tol:
            convergence = False
            
    if convergence:
        break
    
    x = xnew

print("Iteration:", iteration+1)
print("Solution:")
print(np.matrix(xnew))

Upvotes: 1

Views: 511

Answers (2)

kaouther
kaouther

Reputation: 359

The problem is here : x = xnew

In fact, this way you are referencing to the same object now. So obviously when you will change xnew , you are changing the object represented by xnew which is now also referenced by x.

So to just make a copy you can write :

x = xnew[:]
OR
x = xnew.copy()

Upvotes: 1

Michael
Michael

Reputation: 2414

x = xnew

This line assigns xnew to x. Not the contents of xnew, but the array itself. So after your first iteration, x and xnew reference the same array in memory.

Try instead x[:] = xnew[:]

Upvotes: 2

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