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// SPDX-License-Identifier: EPL-2.0 OR GPL-2.0-or-later
// SPDX-FileCopyrightText: Bradley M. Bell <bradbell@seanet.com>
// SPDX-FileContributor: 2003-22 Bradley M. Bell
// ----------------------------------------------------------------------------
/*
{xrst_begin eigen_array.cpp}
Using Eigen Arrays: Example and Test
####################################
{xrst_literal
// BEGIN C++
// END C++
}
{xrst_end eigen_array.cpp}
*/
// BEGIN C++
# include <cppad/cppad.hpp>
# include <cppad/example/cppad_eigen.hpp>
bool eigen_array(void)
{ bool ok = true;
using CppAD::AD;
using CppAD::NearEqual;
//
typedef CppAD::eigen_vector< AD<double> > a_vector;
//
// domain and range space vectors
size_t n = 10, m = n;
a_vector a_x(n), a_y(m);
// set and declare independent variables and start tape recording
for(size_t j = 0; j < n; j++)
a_x[j] = double(1 + j);
CppAD::Independent(a_x);
// evaluate a component wise function
for(size_t j = 0; j < n; j++)
a_y[j] = a_x[j] + sin( a_x[j] );
// create f: x -> y and stop tape recording
CppAD::ADFun<double> f(a_x, a_y);
// compute the derivative of y w.r.t x using CppAD
CPPAD_TESTVECTOR(double) x(n);
for(size_t j = 0; j < n; j++)
x[j] = double(j) + 1.0 / double(j+1);
CPPAD_TESTVECTOR(double) jac = f.Jacobian(x);
// check Jacobian
double eps = 100. * CppAD::numeric_limits<double>::epsilon();
for(size_t i = 0; i < m; i++)
{ for(size_t j = 0; j < n; j++)
{ double check = 1.0 + cos(x[i]);
if( i != j )
check = 0.0;
ok &= NearEqual(jac[i * n + j], check, eps, eps);
}
}
return ok;
}
// END C++
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