[Tutor] newton's method for system of nonlinear equations

[kgotlelelok at galmail.co.za]

Hi can someone help me with my program demostrating Newton's method for
system of nonlinear equations below. Line 45 gives an error saying return
is outside the function and I don't know how to rectify that. I neewd this
program to print differnt values of x until the differnce between previous
x and present x is less than tol.
Please help

Thank you

from scipy import*
tol=0.01
def swapRows(v,i,j):
    if len(v.getshape()) == 1: v[i],v[j] = v[j],v[i]
    else:
        temp = v[i].copy()
        v[i] = v[j]
        v[j] = temp

def swapCols(v,i,j):
    temp = v[:,j].copy()
    v[:,j] = v[:,i]
    v[:,i] = temp

def gaussPivot(a,b,tol=1.0e-12):
    n = len(b)

  # Set up scale factors
    s = zeros((n),float)
    for i in range(n):
        s[i] = max(abs(a[i,:]))

    for k in range(0,n-1):

      # Row interchange, if needed
        p = int(argmax(abs(a[k:n,k])/s[k:n])) + k
        if abs(a[p,k]) < tol: error.err('Matrix is singular')
        if p != k:
            swap.swapRows(b,k,p)
            swap.swapRows(s,k,p)
            swap.swapRows(a,k,p)

      # Elimination
        for i in range(k+1,n):
            if a[i,k] != 0.0:
                lam = a[i,k]/a[k,k]
                a[i,k+1:n] = a [i,k+1:n] - lam*a[k,k+1:n]
                b[i] = b[i] - lam*b[k]
    if abs(a[n-1,n-1]) < tol: error.err('Matrix is singular')


for k in range(n-1,-1,-1):
    b[k] = (b[k] - dot(a[k,k+1:n],b[k+1:n]))/a[k,k]
    return b

def newtonRaphson2(f,x,tol=1.0e-9):

    def jacobian(f,x):
        h = 1.0e-4
        n = len(x)
        jac = zeros((n,n),float)
        f0 = f(x)
        for i in range(n):
            temp = x[i]
            x[i] = temp + h
            f1 = f(x)
            x[i] = temp
            jac[:,i] = (f1 - f0)/h
        return jac,f0

    for i in range(30):
        jac,f0 = jacobian(f,x)
        if sqrt(dot(f0,f0)/len(x)) < tol: return x
        dx = gaussPivot(jac,-f0)
        x = x + dx
        if sqrt(dot(dx,dx)) < tol*max(max(abs(x)),1.0): return x
    print 'Too many iterations'

def f(x):
    f = zeros((len(x)),float)
    f[0] = sin(x[0]) + x[1]**2 + log(x[2]) - 7.0
    f[1] = 3.0*x[0] + 2.0**x[1] - x[2]**3 + 1.0
    f[2] = x[0] + x[1] + x[2] - 5.0
    return f

x = array([1.0, 1.0, 1.0])
print newtonRaphson2(f,x)
raw_input ("\nPress return to exit")



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