|
Prev | Next | a_fun_jacobian_xam.py | Headings |
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 )
#