# start Steepest descent

IterMax = 30
tolerance = 1.0e-14
# start simple gradient descent with random guess again
x = np.random.randn(2,1)

# The residual
r = A @ x-b.T 
i = 0
# a more intelligent iterative process
while (i <= IterMax):
    z = A @ r
    c = r.T @ r
    deno = r.T @ z
    alpha = c/deno
    x -= alpha*r
    r =  (A @ x)-b.T;
    if(np.sqrt(r.T @ r) < tolerance):
        break
    i += 1

print("Absolute error for Steepest descent solution",np.abs(x-exact))