[SciPy-user] Jacobian matrix

[Nils Wagner]

Hi all,

Is there a simpler way (built-in function) to compute the Jacobian of a 
vector function ?
How about higher order derivatives of vector-valued functions ?


from scipy import *

def f(x):
#
   tmp = zeros(5,Float)
   tmp[0] = x[0] + x[1] + x[2]**2 + x[3]**2 + x[4]**2 - 2
   tmp[1] = x[0] - x[1] + x[2]**2 + x[3]**2 + x[4]**2
   tmp[2] = -x[2]**2 + x[3]**2 + x[4]**2
   tmp[3] =  x[2]**2 - x[3]**2 + x[4]**2
   tmp[4] =  x[2]**2 + x[3]**2 - x[4]**2
   return tmp

x0 = array(([1.02,1.02,0.02,0.02,0.02]))
eps = 1.e-5
J = zeros((5,5),Float)
for i in arange(0,5):

  ei = zeros(5,Float)
  ei[i] = 1.0
  J[:,i] = (f(x0+eps*ei)-f(x0))/eps


Any pointer would be appreciated.

Thanks in advance

                                          Nils