import numpy as np

def NewtonRaphson(F,J,x0,tol=0.001):
    x=x0
    error=10**5
    n=0
    while error > tol:
        dx= -np.linalg.solve(J(*x),F(*x)) #np.linalg.solve=Solve a linear matrix equation, or system of linear scalar equations.
        print(dx)
        error= np.linalg.norm(dx)/np.linalg.norm(x) #np.linalg.norm=Matrix or vector norm.
        x+=dx;
        n+=1
    print("Number of Iteration:",n)
    return x


F= lambda x, y: [x**2+y**2-3,x*y-1]

J= lambda x, y: [[2*x,2*y],[y,x]]

print("[x,y]=",NewtonRaphson(F,J,[0.5,1.5],0.0001))