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library-> py_lib cpp_lib

py_lib-> py_fun py_sparse py_utility more_py

py_fun-> py_independent py_abort_recording py_fun_ctor py_fun_property py_fun_new_dynamic py_fun_jacobian py_fun_hessian py_fun_forward py_fun_reverse py_fun_optimize

py_fun_forward-> fun_forward_xam.py

fun_forward_xam.py

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def fun_forward_xam() :
     #
     import numpy
     import cppad_py
     #
     # initialize return variable
     ok = True
     # ---------------------------------------------------------------------
     # number of dependent and independent variables
     n_dep = 1
     n_ind = 2
     #
     # create the independent variables ax
     xp = numpy.empty(n_ind, dtype=float)
     for i in range( n_ind  ) :
          xp[i] = i + 1.0
     #
     ax = cppad_py.independent(xp)
     #
     # create dependent varialbes ay with ay0 = ax0 * ax1
     ax0    = ax[0]
     ax1    = ax[1]
     ay    = numpy.empty(n_dep, dtype=cppad_py.a_double)
     ay[0] = ax0 * ax1
     #
     # define af corresponding to f(x) = x0 * x1
     f  = cppad_py.d_fun(ax, ay)
     #
     # define X(t) = (3 + t, 2 + t)
     # it follows that Y(t) = f(X(t)) = (3 + t) * (2 + t)
     #
     # Y(0) = 6 and p ! = 1
     p     = 0
     xp[0] = 3.0
     xp[1] = 2.0
     yp = f.forward(p, xp)
     ok = ok and yp[0] == 6.0
     #
     # first order Taylor coefficients for X(t)
     p     = 1
     xp[0] = 1.0
     xp[1] = 1.0
     #
     # first order Taylor coefficient for Y(t)
     # Y'(0) = 3 + 2 = 5 and p ! = 1
     yp = f.forward(p, xp)
     ok = ok and yp[0] == 5.0
     #
     # second order Taylor coefficients for X(t)
     p     = 2
     xp[0] = 0.0
     xp[1] = 0.0
     #
     # second order Taylor coefficient for Y(t)
     # Y''(0) = 2.0 and p ! = 2
     yp = f.forward(p, xp)
     ok = ok and yp[0] == 1.0
     # ---------------------------------------------------------------------
     af = cppad_py.a_fun(f)
     ok = ok and af.size_order() == 0
     #
     # zero order forward
     p   = 0
     axp = numpy.empty(n_ind, dtype=cppad_py.a_double)
     axp[0] = 3.0
     axp[1] = 2.0
     ayp    = af.forward(p, axp)
     ok     = ok and ayp[0] == cppad_py.a_double(6.0)
     ok     = ok and af.size_order() == 1
     #
     return( ok )
#