Prev Next a_fun_jacobian_xam.py Headings

@(@\newcommand{\B}[1]{ {\bf #1} } \newcommand{\R}[1]{ {\rm #1} }@)@
Python: Dense Jacobian Using AD: Example and Test
def a_fun_jacobian_xam() :
     #
     # load the Cppad Swig library
     import py_cppad
     #
     # initialize return variable
     ok = True
     # ---------------------------------------------------------------------
     # number of dependent and independent variables
     n_dep = 1
     n_ind = 3
     #
     # create the independent variables ax
     x = py_cppad.vec_double(n_ind)
     for i in range( n_ind  ) :
          x[i] = i + 2.0
     #
     ax = py_cppad.independent(x)
     #
     # create dependent variables ay with ay0 = ax_0 * ax_1 * ax_2
     ax_0 = ax[0]
     ax_1 = ax[1]
     ax_2 = ax[2]
     ay = py_cppad.vec_a_double(n_dep)
     ay[0] = ax_0 * ax_1 * ax_2
     #
     # define af corresponding to f(x) = x_0 * x_1 * x_2
     af = py_cppad.a_fun(ax, ay)
     #
     # compute the Jacobian f'(x) = ( x_1*x_2, x_0*x_2, x_0*x_1 )
     fp = af.jacobian(x)
     #
     # check Jacobian
     x_0 = x[0]
     x_1 = x[1]
     x_2 = x[2]
     ok = ok and fp[0 * n_ind + 0] == x_1 * x_2 
     ok = ok and fp[0 * n_ind + 1] == x_0 * x_2 
     ok = ok and fp[0 * n_ind + 2] == x_0 * x_1 
     #
     return( ok )
#

Input File: build/lib/example/python/a_fun_jacobian_xam.py