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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
// ----------------------------------------------------------------------------
# include <cppad/cppad.hpp>
namespace {
using CppAD::AD;
typedef CPPAD_TESTVECTOR(AD<double>) ADVector;
// ------------------------------------------------------------------------
bool f_algo(const ADVector& x, ADVector& y)
{ size_t m = y.size();
assert( size_t(x.size()) == m + 1);
for(size_t i = 0; i < m; i++)
y[i] = x[i] * x[i+1];
return true;
}
bool g_algo(const ADVector& y, ADVector& z)
{ size_t m = z.size();
assert( size_t(y.size()) + 1 == m );
z[0] = 0.0;
for(size_t i = 1; i < m; i++)
{ z[0] += y[i-1];
z[i] = y[i-1];
}
return true;
}
bool test_one(void)
{ bool ok = true;
using CppAD::checkpoint;
using CppAD::ADFun;
using CppAD::NearEqual;
size_t i, j, k, n = 4, ell = n-1 , m = ell + 1;
double eps = 10. * std::numeric_limits<double>::epsilon();
// checkpoint version of the function F(x)
ADVector ax(n), ay(ell), az(m);
for(j = 0; j < n; j++)
ax[j] = double(j);
checkpoint<double> f_check("f_check", f_algo, ax, ay);
checkpoint<double> g_check("g_check", g_algo, ay, az);
// Record a version of z = g[f(x)] without checkpointing
Independent(ax);
f_algo(ax, ay);
g_algo(ay, az);
ADFun<double> check_not(ax, az);
// Record a version of z = g[f(x)] with checkpointing
Independent(ax);
f_check(ax, ay);
g_check(ay, az);
ADFun<double> check_yes(ax, az);
// compare forward mode results for orders 0, 1, 2
size_t p = 2;
CPPAD_TESTVECTOR(double) x_p(n*(p+1)), z_not(m*(p+1)), z_yes(m*(p+1));
for(j = 0; j < n; j++)
{ for(k = 0; k <= p; k++)
x_p[ j * (p+1) + k ] = 1.0 / double(p + 1 - k);
}
z_not = check_not.Forward(p, x_p);
z_yes = check_yes.Forward(p, x_p);
for(i = 0; i < m; i++)
{ for(k = 0; k <= p; k++)
{ double zik_not = z_not[ i * (p+1) + k];
double zik_yes = z_yes[ i * (p+1) + k];
ok &= NearEqual(zik_not, zik_yes, eps, eps);
}
}
// compare reverse mode results
CPPAD_TESTVECTOR(double) w(m*(p+1)), dw_not(n*(p+1)), dw_yes(n*(p+1));
for(i = 0; i < m; i++)
{ for(k = 0; k <= p; k++)
w[ i * (p+1) + k ] = 2.0 / double(p + 1 - k );
}
dw_not = check_not.Reverse(p+1, w);
dw_yes = check_yes.Reverse(p+1, w);
for(j = 0; j < n; j++)
{ for(k = 0; k <= p; k++)
{ double dwjk_not = dw_not[ j * (p+1) + k];
double dwjk_yes = dw_yes[ j * (p+1) + k];
ok &= NearEqual(dwjk_not, dwjk_yes, eps, eps);
}
}
// mix sparsity so test both cases
f_check.option( CppAD::atomic_base<double>::bool_sparsity_enum );
g_check.option( CppAD::atomic_base<double>::set_sparsity_enum );
// compare forward mode Jacobian sparsity patterns
size_t q = n - 1;
CppAD::vector< std::set<size_t> > r(n), s_not(m), s_yes(m);
for(j = 0; j < n; j++)
{ if( j < q )
r[j].insert(j);
else
{ r[j].insert(0);
r[j].insert(1);
}
}
s_not = check_not.ForSparseJac(q, r);
s_yes = check_yes.ForSparseJac(q, r);
for(i = 0; i < m; i++)
ok &= s_not[i] == s_yes[i];
// compare reverse mode Jacobian sparsity patterns
CppAD::vector< std::set<size_t> > s(m), r_not(m), r_yes(m);
for(i = 0; i < m; i++)
s[i].insert(i);
r_not = check_not.RevSparseJac(m, s);
r_yes = check_yes.RevSparseJac(m, s);
for(i = 0; i < m; i++)
ok &= s_not[i] == s_yes[i];
// compare reverse mode Hessian sparsity patterns
CppAD::vector< std::set<size_t> > s_one(1), h_not(q), h_yes(q);
for(i = 0; i < m; i++)
s_one[0].insert(i);
h_not = check_not.RevSparseHes(q, s_one);
h_yes = check_yes.RevSparseHes(q, s_one);
for(i = 0; i < q; i++)
ok &= h_not[i] == h_yes[i];
checkpoint<double>::clear();
return ok;
}
// ------------------------------------------------------------------------
bool h_algo(const ADVector& ax, ADVector& ay)
{ ay[0] = ax[0];
ay[1] = ax[1] + ax[2];
return true;
}
bool test_two(void)
{ bool ok = true;
using CppAD::checkpoint;
using CppAD::ADFun;
using CppAD::NearEqual;
// checkpoint version of H(x)
size_t m = 2;
size_t n = 3;
ADVector ax(n), ay(m);
for(size_t j = 0; j < n; j++)
ax[j] = double(j);
checkpoint<double> h_check("h_check", h_algo, ax, ay);
// record function using h_check
Independent(ax);
h_check(ax, ay);
ADFun<double> h(ax, ay);
//
// --------------------------------------------------------------------
// sparsity pattern
// --------------------------------------------------------------------
for(size_t k = 0; k < 3; k++)
{ if( k == 0 )
h_check.option(CppAD::atomic_base<double>::pack_sparsity_enum);
if( k == 1 )
h_check.option(CppAD::atomic_base<double>::bool_sparsity_enum);
if( k == 2 )
h_check.option(CppAD::atomic_base<double>::set_sparsity_enum);
// compute sparsity pattern h_1(x) = x[1] + x[2]
CppAD::vector< std::set<size_t> > r(1), s(1);
r[0].insert(1);
s = h.RevSparseJac(1, r);
// check result
std::set<size_t> check;
check.insert(1);
check.insert(2);
ok &= s[0] == check;
}
// --------------------------------------------------------------------
// base2ad
// --------------------------------------------------------------------
ADFun< AD<double> , double > ah;
ah = h.base2ad();
//
// forward mode
ADVector au(n), av(m);
for(size_t j = 0; j < n; j++)
ax[j] = au[j] = double(j + 1);
av = ah.Forward(0, au);
h_algo(ax, ay);
for(size_t i = 0; i < m; ++i)
ok &= av[i] == ay[i];
//
// reverse mode
ADVector adw(n), aw(m);
for(size_t i = 0; i < m; ++i)
aw[i] = 1.0;
adw = ah.Reverse(1, aw);
ok &= Value( adw[0] ) == 1.0;
ok &= Value( adw[1] ) == 1.0;
ok &= Value( adw[2] ) == 1.0;
//
return ok;
}
}
bool chkpoint_one(void)
{ bool ok = true;
ok &= test_one();
ok &= test_two();
return ok;
}
// END C++
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