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def fun_property_xam() :
#
import numpy
import cppad_py
#
# initialize return variable
ok = True
# ---------------------------------------------------------------------
n_ind = 1 # number of independent variables
n_dep = 2 # number of dependent variables
n_var = 1 # phantom variable at address 0
n_op = 1 # special operator at beginning
#
# dimension some vectors
# x = numpy.empty(n_ind, dtype=float)
x = numpy.empty(n_ind, dtype=float)
ay = numpy.empty(n_dep, dtype=cppad_py.a_double)
#
# independent variables
x[0] = 1.0
ax = cppad_py.independent(x)
n_var = n_var + n_ind # one for each indpendent
n_op = n_op + n_ind
#
# first dependent variable
ay[0] = ax[0] + ax[0]
n_var = n_var + 1 # one variable and operator
n_op = n_op + 1
#
# second dependent variable
ax0 = ax[0]
ay[1] = ax0.sin()
n_var = n_var + 2 # two varialbes, one operator
n_op = n_op + 1
#
# define f(x) = y
f = cppad_py.d_fun(ax, ay)
n_op = n_op + 1 # speical operator at end
#
# check af properties
ok = ok and f.size_domain() == n_ind
ok = ok and f.size_range() == n_dep
ok = ok and f.size_var() == n_var
ok = ok and f.size_op() == n_op
ok = ok and f.size_order() == 0
#
# compute zero order Taylor coefficients
y = f.forward(0, x)
ok = ok and f.size_order() == 1
# ---------------------------------------------------------------------
af = cppad_py.a_fun(f)
#
# check af properties
ok = ok and af.size_domain() == n_ind
ok = ok and af.size_range() == n_dep
ok = ok and af.size_var() == n_var
ok = ok and af.size_op() == n_op
ok = ok and af.size_order() == 0
#
return( ok )
#