from pycppad import *
def pycppad_test_get_started() :
  def F(x) :                                   # function to be differentiated
    return exp(-(x[0]**2. + x[1]**2.) / 2.)    # is Gaussian density
  x     = numpy.array( [ 1.,  2.] )
  a_x   = independent(x)
  a_y   = numpy.array( [ F(a_x) ] ) 
  f     = adfun(a_x, a_y)
  J     = f.jacobian(x)                        # J = F'(x)
  assert abs( J[0, 0] + F(x) * x[0] ) < 1e-10  # J[0,0] ~= - F(x) * x[0]
  assert abs( J[0, 1] + F(x) * x[1] ) < 1e-10  # J[0,1] ~= - F(x) * x[1]