// $Id$
/* --------------------------------------------------------------------------
CppAD: C++ Algorithmic Differentiation: Copyright (C) 2003-15 Bradley M. Bell

CppAD is distributed under multiple licenses. This distribution is under
the terms of the
                    GNU General Public License Version 3.

A copy of this license is included in the COPYING file of this distribution.
Please visit http://www.coin-or.org/CppAD/ for information on other licenses.
-------------------------------------------------------------------------- */
# include <iostream>
# include <cppad/cppad.hpp>

// Test multiple level conditional skip where value of comparision is
// uncertain during forward mode base Base value can be a variable.
bool mul_cskip(void)
{	bool ok = true;
	using namespace CppAD;
	using CppAD::vector;

	typedef AD<double>  a1type;
	typedef AD<a1type>  a2type;

	size_t n = 2;
	size_t m = 1;
	vector<double> x(n), y(m);
	x[0] = 0.0;
	x[1] = 1.0;

	// start recording a2type operations
	vector<a2type> a2x(n), a2y(m);
	for (size_t j = 0; j < n; j++)
		a2x[j] = a2type( a1type(x[j]) );
	Independent(a2x);

	// a1f(x) = x_0 * x_1 if x[0] == 1
	//         0.0       otherwise
	a2type a2zero = a2type(0.0);
	a2type a2one  = a2type(1.0);
	a2type a2p    = a2x[0] * a2x[1];
	a2y[0]        = CondExpEq(a2x[0], a2one, a2p, a2zero);
	ADFun<a1type> a1f(a2x, a2y);

	// Optimization will check to see if we can skip part of conditional
	// expression that is not used.
	a1f.optimize();

	// f(x) = x_0 * x_1 if x[0] == 1
	//        0.0       otherwise
	vector<a1type> a1x(n), a1y(m);
	for (size_t j = 0; j < n; j++)
		a1x[j] = a1type(x[j]);
	Independent(a1x);
	a1y = a1f.Forward(0, a1x);
	CppAD::ADFun<double> f(a1x, a1y);

	// check case where x[0] == 1
	x[0] = 1.0;
	x[1] = 2.0;
	y = f.Forward(0, x);
	ok &= y[0] == x[1];

	// check case where x[0] != 1
	x[0] = 3.0;
	x[1] = 2.0;
	y = f.Forward(0, x);
	ok &= y[0] == 0.0;

	return ok;
}
