lines 7-242 of file: example/atomic_two/eigen_cholesky.cpp

{xrst_begin atomic_two_eigen_cholesky.cpp app}
{xrst_spell
   chol
}

Atomic Eigen Cholesky Factorization: Example and Test
#####################################################

Description
***********
The :ref:`ADFun-name` function object *f* for this example is

.. math::

   f(x)
   =
   \R{chol} \left( \begin{array}{cc}
      x_0   & x_1 \\
      x_1   & x_2
   \end{array} \right)
   =
   \frac{1}{ \sqrt{x_0} }
   \left( \begin{array}{cc}
      x_0 & 0 \\
      x_1 & \sqrt{ x_0 x_2 - x_1 x_1 }
   \end{array} \right)

where the matrix is positive definite; i.e.,
:math:`x_0 > 0`, :math:`x_2 > 0` and
:math:`x_0 x_2 - x_1 x_1 > 0`.

Contents
********
{xrst_toc_table
   xrst/theory/cholesky.xrst
   include/cppad/example/atomic_two/eigen_cholesky.hpp
}

Use Atomic Function
*******************
{xrst_spell_off}
{xrst_code cpp} */
# include <cppad/cppad.hpp>
# include <cppad/example/atomic_two/eigen_cholesky.hpp>

bool eigen_cholesky(void)
{
   typedef double scalar;
   typedef atomic_eigen_cholesky<scalar>::ad_scalar ad_scalar;
   typedef atomic_eigen_cholesky<scalar>::ad_matrix ad_matrix;
   //
   bool ok    = true;
   scalar eps = 10. * std::numeric_limits<scalar>::epsilon();
   using CppAD::NearEqual;
   //
/* {xrst_code}
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Constructor
===========
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{xrst_code cpp} */
   // -------------------------------------------------------------------
   // object that computes cholesky factor of a matrix
   atomic_eigen_cholesky<scalar> cholesky;
   // -------------------------------------------------------------------
   // declare independent variable vector x
   size_t n = 3;
   CPPAD_TESTVECTOR(ad_scalar) ad_x(n);
   ad_x[0] = 2.0;
   ad_x[1] = 0.5;
   ad_x[2] = 3.0;
   CppAD::Independent(ad_x);
   // -------------------------------------------------------------------
   // A = [ x[0]  x[1] ]
   //     [ x[1]  x[2] ]
   size_t nr  = 2;
   ad_matrix ad_A(nr, nr);
   ad_A(0, 0) = ad_x[0];
   ad_A(1, 0) = ad_x[1];
   ad_A(0, 1) = ad_x[1];
   ad_A(1, 1) = ad_x[2];
   // -------------------------------------------------------------------
   // use atomic operation to L such that A = L * L^T
   ad_matrix ad_L = cholesky.op(ad_A);
   // -------------------------------------------------------------------
   // declare the dependent variable vector y
   size_t m = 3;
   CPPAD_TESTVECTOR(ad_scalar) ad_y(m);
   ad_y[0] = ad_L(0, 0);
   ad_y[1] = ad_L(1, 0);
   ad_y[2] = ad_L(1, 1);
   CppAD::ADFun<scalar> f(ad_x, ad_y);
   // -------------------------------------------------------------------
   // check zero order forward mode
   CPPAD_TESTVECTOR(scalar) x(n), y(m);
   x[0] = 2.0;
   x[1] = 0.5;
   x[2] = 5.0;
   y   = f.Forward(0, x);
   scalar check;
   check = std::sqrt( x[0] );
   ok   &= NearEqual(y[0], check, eps, eps);
   check = x[1] / std::sqrt( x[0] );
   ok   &= NearEqual(y[1], check, eps, eps);
   check = std::sqrt( x[2] - x[1] * x[1] / x[0] );
   ok   &= NearEqual(y[2], check, eps, eps);
   // -------------------------------------------------------------------
   // check first order forward mode
   CPPAD_TESTVECTOR(scalar) x1(n), y1(m);
   //
   // partial w.r.t. x[0]
   x1[0] = 1.0;
   x1[1] = 0.0;
   x1[2] = 0.0;
   //
   y1    = f.Forward(1, x1);
   check = 1.0 / (2.0 * std::sqrt( x[0] ) );
   ok   &= NearEqual(y1[0], check, eps, eps);
   //
   check = - x[1] / (2.0 * x[0] * std::sqrt( x[0] ) );
   ok   &= NearEqual(y1[1], check, eps, eps);
   //
   check = std::sqrt( x[2] - x[1] * x[1] / x[0] );
   check = x[1] * x[1] / (x[0] * x[0] * 2.0 * check);
   ok   &= NearEqual(y1[2], check, eps, eps);
   //
   // partial w.r.t. x[1]
   x1[0] = 0.0;
   x1[1] = 1.0;
   x1[2] = 0.0;
   //
   y1    = f.Forward(1, x1);
   ok   &= NearEqual(y1[0], 0.0, eps, eps);
   //
   check = 1.0 / std::sqrt( x[0] );
   ok   &= NearEqual(y1[1], check, eps, eps);
   //
   check = std::sqrt( x[2] - x[1] * x[1] / x[0] );
   check = - 2.0 * x[1] / (2.0 * check * x[0] );
   ok   &= NearEqual(y1[2], check, eps, eps);
   //
   // partial w.r.t. x[2]
   x1[0] = 0.0;
   x1[1] = 0.0;
   x1[2] = 1.0;
   //
   y1    = f.Forward(1, x1);
   ok   &= NearEqual(y1[0], 0.0, eps, eps);
   ok   &= NearEqual(y1[1], 0.0, eps, eps);
   //
   check = std::sqrt( x[2] - x[1] * x[1] / x[0] );
   check = 1.0 / (2.0 * check);
   ok   &= NearEqual(y1[2], check, eps, eps);
   // -------------------------------------------------------------------
   // check second order forward mode
   CPPAD_TESTVECTOR(scalar) x2(n), y2(m);
   //
   // second partial w.r.t x[2]
   x2[0] = 0.0;
   x2[1] = 0.0;
   x2[2] = 0.0;
   y2    = f.Forward(2, x2);
   ok   &= NearEqual(y2[0], 0.0, eps, eps);
   ok   &= NearEqual(y2[1], 0.0, eps, eps);
   //
   check = std::sqrt( x[2] - x[1] * x[1] / x[0] );  // function value
   check = - 1.0 / ( 4.0 * check * check * check ); // second derivative
   check = 0.5 * check;                             // taylor coefficient
   ok   &= NearEqual(y2[2], check, eps, eps);
   // -------------------------------------------------------------------
   // check first order reverse mode
   CPPAD_TESTVECTOR(scalar) w(m), d1w(n);
   w[0] = 0.0;
   w[1] = 0.0;
   w[2] = 1.0;
   d1w  = f.Reverse(1, w);
   //
   // partial of f[2] w.r.t x[0]
   scalar f2    = std::sqrt( x[2] - x[1] * x[1] / x[0] );
   scalar f2_x0 = x[1] * x[1] / (2.0 * f2 * x[0] * x[0] );
   ok          &= NearEqual(d1w[0], f2_x0, eps, eps);
   //
   // partial of f[2] w.r.t x[1]
   scalar f2_x1 = - x[1] / (f2 * x[0] );
   ok          &= NearEqual(d1w[1], f2_x1, eps, eps);
   //
   // partial of f[2] w.r.t x[2]
   scalar f2_x2 = 1.0 / (2.0 * f2 );
   ok          &= NearEqual(d1w[2], f2_x2, eps, eps);
   // -------------------------------------------------------------------
   // check second order reverse mode
   CPPAD_TESTVECTOR(scalar) d2w(2 * n);
   d2w  = f.Reverse(2, w);
   //
   // check first order results
   ok &= NearEqual(d2w[0 * 2 + 0], f2_x0, eps, eps);
   ok &= NearEqual(d2w[1 * 2 + 0], f2_x1, eps, eps);
   ok &= NearEqual(d2w[2 * 2 + 0], f2_x2, eps, eps);
   //
   // check second order results
   scalar f2_x2_x0 = - 0.5 * f2_x0 / (f2 * f2 );
   ok             &= NearEqual(d2w[0 * 2 + 1], f2_x2_x0, eps, eps);
   scalar f2_x2_x1 = - 0.5 * f2_x1 / (f2 * f2 );
   ok             &= NearEqual(d2w[1 * 2 + 1], f2_x2_x1, eps, eps);
   scalar f2_x2_x2 = - 0.5 * f2_x2 / (f2 * f2 );
   ok             &= NearEqual(d2w[2 * 2 + 1], f2_x2_x2, eps, eps);
   // -------------------------------------------------------------------
   // check third order reverse mode
   CPPAD_TESTVECTOR(scalar) d3w(3 * n);
   d3w  = f.Reverse(3, w);
   //
   // check first order results
   ok &= NearEqual(d3w[0 * 3 + 0], f2_x0, eps, eps);
   ok &= NearEqual(d3w[1 * 3 + 0], f2_x1, eps, eps);
   ok &= NearEqual(d3w[2 * 3 + 0], f2_x2, eps, eps);
   //
   // check second order results
   ok             &= NearEqual(d3w[0 * 3 + 1], f2_x2_x0, eps, eps);
   ok             &= NearEqual(d3w[1 * 3 + 1], f2_x2_x1, eps, eps);
   ok             &= NearEqual(d3w[2 * 3 + 1], f2_x2_x2, eps, eps);
   // -------------------------------------------------------------------
   scalar f2_x2_x2_x0 = - 0.5 * f2_x2_x0 / (f2 * f2);
   f2_x2_x2_x0 += f2_x2 * f2_x0 / (f2 * f2 * f2);
   ok          &= NearEqual(d3w[0 * 3 + 2], 0.5 * f2_x2_x2_x0, eps, eps);
   scalar f2_x2_x2_x1 = - 0.5 * f2_x2_x1 / (f2 * f2);
   f2_x2_x2_x1 += f2_x2 * f2_x1 / (f2 * f2 * f2);
   ok          &= NearEqual(d3w[1 * 3 + 2], 0.5 * f2_x2_x2_x1, eps, eps);
   scalar f2_x2_x2_x2 = - 0.5 * f2_x2_x2 / (f2 * f2);
   f2_x2_x2_x2 += f2_x2 * f2_x2 / (f2 * f2 * f2);
   ok          &= NearEqual(d3w[2 * 3 + 2], 0.5 * f2_x2_x2_x2, eps, eps);
   return ok;
}
/* {xrst_code}
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{xrst_end atomic_two_eigen_cholesky.cpp}