Question: Debug this code and ensure that the error indicated below is obtained / solved . import numpy as np def construct _ A ( n

Debug this code and ensure that the error indicated below is obtained/solved.
import numpy as np
def construct_A(n):
A = np.zeros((n, n))
for i in range(n):
for j in range(n):
if i < j:
A[i, j]= max(0, n/10+2*(i - j))
else:
A[i, j]= max(0, n/10-2*(i - j))
return A
def construct_B(n):
return np.array([(-1)**i for i in range(n)])
def forward_substitution(L, b):
n = L.shape[0]
y = np.zeros_like(b)
for i in range(n):
y[i]=(b[i]- np.dot(L[i, :i], y[:i]))/ L[i, i]
return y
def DOS(A, B, x0, w1, w2, tol=1e-6):
# Handle scalar x0 input
if np.isscalar(x0):
x0= np.full(B.shape, x0)
D = np.diag(np.diag(A))
L = np.tril(A,-1)
U = np.triu(A,1)
x = x0
iteration_count =0
error = np.inf
while error > tol:
# Step 1: Solve D*x(k+1/2)= w1*D +(w1-1)*(L+U)* x(k)+(1-w1)*B
x_half =(np.linalg.solve(D, w1* B +(1- w1)*(np.dot(L + U, x))))
# Step 2: Solve (D+w2*L)* x(k+1)=[(1-w2)*D - w2*U]*x(k+1/2)+ w2*B
x_new = forward_substitution(D + w2* L,(1- w2)* np.dot(D, x_half)- w2* np.dot(U, x_half)+ w2* B)
error = np.linalg.norm(x_new - x)
x = x_new
iteration_count +=1
return x, error, iteration_count
# Parameters for the DOS function
n =200
w1=0.3
w2=0.6
tol =0.02
x0=0 # Initial guess for the solution
A = construct_A(n)
B = construct_B(n)
# Execute the DOS function
solution, err, iterations = DOS(A, B, x0, w1, w2, tol)
print("Solution:", solution)
print("Error:", err)
print("Iterations:", iterations)
##This is the encountered error RuntimeWarning: invalid value encountered in scalar subtract y[i]=(b[i]- np.dot(L[i, :i], y[:i]))/ L[i, i]

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