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<center><b><big><big>Creating Your Own Interface to an ADFun Object</big></big></b></center>
<code><font color="blue"><pre style='display:inline'> 

# include &lt;cppad/cppad.hpp&gt;

namespace {

	// This class is an example of a different interface to an AD function object
	template &lt;class Base&gt;
	class my_ad_fun {
	
	private:
		CppAD::<a href="funconstruct.xml" target="_top">ADFun</a>&lt;Base&gt; f;
	
	public:
		// default constructor
		my_ad_fun(void)
		{ }
	
		// destructor
		~ my_ad_fun(void)
		{ }
	
		// Construct an my_ad_fun object with an operation sequence.
		// This is the same as for <a href="funconstruct.xml" target="_top">ADFun</a>&lt;Base&gt; except that no zero 
		// order forward sweep is done. Note Hessian and Jacobian do 
		// their own zero order forward mode sweep. 
		template &lt;class ADvector&gt;
		my_ad_fun(const ADvector&amp; x, const ADvector&amp; y)
		{	f.Dependent(x, y); }
	
		// same as <a href="funconstruct.xml" target="_top">ADFun</a>&lt;Base&gt;::Jacobian
		template &lt;class VectorBase&gt;
		VectorBase jacobian(const VectorBase&amp; x) 
		{	return f.<a href="jacobian.xml" target="_top">Jacobian</a>(x); }

		// same as <a href="funconstruct.xml" target="_top">ADFun</a>&lt;Base&gt;::Hessian
	        template &lt;typename VectorBase&gt;
		VectorBase hessian(const VectorBase &amp;x, const VectorBase &amp;w)
		{	return f.Hessian(x, w); }
	}; 

} // End empty namespace

bool ad_fun(void)
{	// This example is similar to example/jacobian.cpp, except that it
	// uses my_ad_fun instead of ADFun.

	bool ok = true;
	using CppAD::AD;
	using CppAD::NearEqual;
	using CppAD::exp;
	using CppAD::sin;
	using CppAD::cos;

	// domain space vector
	size_t n = 2;
	<a href="test_vector.xml" target="_top">CPPAD_TEST_VECTOR</a>&lt; <a href="ad.xml" target="_top">AD</a>&lt;double&gt; &gt;  X(n);
	X[0] = 1.;
	X[1] = 2.;

	// declare independent variables and starting recording
	CppAD::<a href="independent.xml" target="_top">Independent</a>(X);

	// a calculation between the domain and range values
	<a href="ad.xml" target="_top">AD</a>&lt;double&gt; Square = X[0] * X[0];

	// range space vector
	size_t m = 3;
	<a href="test_vector.xml" target="_top">CPPAD_TEST_VECTOR</a>&lt; <a href="ad.xml" target="_top">AD</a>&lt;double&gt; &gt;  Y(m);
	Y[0] = Square * exp( X[1] );
	Y[1] = Square * sin( X[1] );
	Y[2] = Square * cos( X[1] );

	// create f: X -&gt; Y and stop tape recording
	my_ad_fun&lt;double&gt; f(X, Y);

	// new value for the independent variable vector
	<a href="test_vector.xml" target="_top">CPPAD_TEST_VECTOR</a>&lt;double&gt; x(n);
	x[0] = 2.;
	x[1] = 1.;

	// compute the derivative at this x
	<a href="test_vector.xml" target="_top">CPPAD_TEST_VECTOR</a>&lt;double&gt; jac( m * n );
	jac = f.jacobian(x);

	/*
	F'(x) = [ 2 * x[0] * exp(x[1]) ,  x[0] * x[0] * exp(x[1]) ]
	        [ 2 * x[0] * sin(x[1]) ,  x[0] * x[0] * cos(x[1]) ]
	        [ 2 * x[0] * cos(x[1]) , -x[0] * x[0] * sin(x[i]) ]
	*/
	ok &amp;=  <a href="nearequal.xml" target="_top">NearEqual</a>( 2.*x[0]*exp(x[1]), jac[0*n+0], 1e-10, 1e-10 );
	ok &amp;=  <a href="nearequal.xml" target="_top">NearEqual</a>( 2.*x[0]*sin(x[1]), jac[1*n+0], 1e-10, 1e-10 );
	ok &amp;=  <a href="nearequal.xml" target="_top">NearEqual</a>( 2.*x[0]*cos(x[1]), jac[2*n+0], 1e-10, 1e-10 );

	ok &amp;=  <a href="nearequal.xml" target="_top">NearEqual</a>( x[0] * x[0] *exp(x[1]), jac[0*n+1], 1e-10, 1e-10 );
	ok &amp;=  <a href="nearequal.xml" target="_top">NearEqual</a>( x[0] * x[0] *cos(x[1]), jac[1*n+1], 1e-10, 1e-10 );
	ok &amp;=  <a href="nearequal.xml" target="_top">NearEqual</a>(-x[0] * x[0] *sin(x[1]), jac[2*n+1], 1e-10, 1e-10 );

	return ok;
}


</pre>

</font></code>


<hr/>Input File: example/ad_fun.cpp

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