void ADFun<Base,RecBase>::ForSparseHesCase(
const std::set<size_t>& set_type ,
const SetVector& r ,
const SetVector& s ,
SetVector& h )
{
// used to identify the RecBase type in calls to sweeps
RecBase not_used_rec_base;
//
size_t n = Domain();
# ifndef NDEBUG
size_t m = Range();
# endif
std::set<size_t>::const_iterator itr_1;
//
// check SetVector is Simple Vector class with sets for elements
CheckSimpleVector<std::set<size_t>, SetVector>(
local::one_element_std_set<size_t>(), local::two_element_std_set<size_t>()
);
CPPAD_ASSERT_KNOWN(
r.size() == 1,
"ForSparseHes: size of s is not equal to one."
);
CPPAD_ASSERT_KNOWN(
s.size() == 1,
"ForSparseHes: size of s is not equal to one."
);
//
// sparsity pattern corresponding to r
local::sparse_list for_jac_pattern;
for_jac_pattern.resize(num_var_tape_, n + 1);
itr_1 = r[0].begin();
while( itr_1 != r[0].end() )
{ size_t i = *itr_1++;
CPPAD_ASSERT_UNKNOWN( ind_taddr_[i] < n + 1 );
// ind_taddr_[i] is operator taddr for i-th independent variable
CPPAD_ASSERT_UNKNOWN( play_.GetOp( ind_taddr_[i] ) == local::InvOp );
//
// Use add_element when only adding one element per set is added.
for_jac_pattern.add_element( ind_taddr_[i], ind_taddr_[i] );
}
// compute forward Jacobiain sparsity pattern
bool dependency = false;
local::sweep::for_jac<addr_t>(
&play_,
dependency,
n,
num_var_tape_,
for_jac_pattern,
not_used_rec_base
);
// sparsity pattern correspnding to s
local::sparse_list rev_jac_pattern;
rev_jac_pattern.resize(num_var_tape_, 1);
itr_1 = s[0].begin();
while( itr_1 != s[0].end() )
{ size_t i = *itr_1++;
CPPAD_ASSERT_KNOWN(
i < m,
"ForSparseHes: an element of the set s[0] has value "
"greater than or equal m"
);
CPPAD_ASSERT_UNKNOWN( dep_taddr_[i] < num_var_tape_ );
//
// Use add_element when only adding one element per set is added.
rev_jac_pattern.add_element( dep_taddr_[i], 0);
}
//
// compute reverse sparsity pattern for dependency analysis
// (note that we are only want non-zero derivatives not true dependency)
local::sweep::rev_jac<addr_t>(
&play_,
dependency,
n,
num_var_tape_,
rev_jac_pattern,
not_used_rec_base
);
//
// vector of sets that will hold reverse Hessain values
local::sparse_list for_hes_pattern;
for_hes_pattern.resize(n+1, n+1);
//
// compute the Hessian sparsity patterns
local::sweep::for_hes<addr_t>(
&play_,
n,
num_var_tape_,
for_jac_pattern,
rev_jac_pattern,
for_hes_pattern,
not_used_rec_base
);
// return values corresponding to independent variables
// j is index corresponding to reverse mode partial
h.resize(n);
CPPAD_ASSERT_UNKNOWN( for_hes_pattern.end() == n+1 );
for(size_t i = 0; i < n; i++)
{ CPPAD_ASSERT_UNKNOWN( ind_taddr_[i] == i + 1 );
CPPAD_ASSERT_UNKNOWN( play_.GetOp( ind_taddr_[i] ) == local::InvOp );
// extract the result from for_hes_pattern
local::sparse_list::const_iterator itr_2(for_hes_pattern, ind_taddr_[i] );
size_t j = *itr_2;
while( j < for_hes_pattern.end() )
{ CPPAD_ASSERT_UNKNOWN( 0 < j )
h[i].insert(j-1);
j = *(++itr_2);
}
}
}
void ADFun<Base,RecBase>::ForSparseHesCase(
bool set_type ,
const SetVector& r ,
const SetVector& s ,
SetVector& h )
{
// used to identify the RecBase type in calls to sweeps
RecBase not_used_rec_base;
//
size_t n = Domain();
size_t m = Range();
//
// check Vector is Simple SetVector class with bool elements
CheckSimpleVector<bool, SetVector>();
//
CPPAD_ASSERT_KNOWN(
size_t(r.size()) == n,
"ForSparseHes: size of r is not equal to\n"
"domain dimension for ADFun object."
);
CPPAD_ASSERT_KNOWN(
size_t(s.size()) == m,
"ForSparseHes: size of s is not equal to\n"
"range dimension for ADFun object."
);
//
// sparsity pattern corresponding to r
local::sparse_pack for_jac_pattern;
for_jac_pattern.resize(num_var_tape_, n + 1);
for(size_t i = 0; i < n; i++)
{ CPPAD_ASSERT_UNKNOWN( ind_taddr_[i] < n + 1 );
// ind_taddr_[i] is operator taddr for i-th independent variable
CPPAD_ASSERT_UNKNOWN( play_.GetOp( ind_taddr_[i] ) == local::InvOp );
//
// Use add_element when only adding one element per set is added.
if( r[i] )
for_jac_pattern.add_element( ind_taddr_[i], ind_taddr_[i] );
}
// compute forward Jacobiain sparsity pattern
bool dependency = false;
local::sweep::for_jac<addr_t>(
&play_,
dependency,
n,
num_var_tape_,
for_jac_pattern,
not_used_rec_base
);
// sparsity pattern correspnding to s
local::sparse_pack rev_jac_pattern;
rev_jac_pattern.resize(num_var_tape_, 1);
for(size_t i = 0; i < m; i++)
{ CPPAD_ASSERT_UNKNOWN( dep_taddr_[i] < num_var_tape_ );
//
// Use add_element when only adding one element per set is added.
if( s[i] )
rev_jac_pattern.add_element( dep_taddr_[i], 0);
}
// compute reverse sparsity pattern for dependency analysis
// (note that we are only want non-zero derivatives not true dependency)
local::sweep::rev_jac<addr_t>(
&play_,
dependency,
n,
num_var_tape_,
rev_jac_pattern,
not_used_rec_base
);
// vector of sets that will hold the forward Hessain values
local::sparse_pack for_hes_pattern;
for_hes_pattern.resize(n+1, n+1);
//
// compute the Hessian sparsity patterns
local::sweep::for_hes<addr_t>(
&play_,
n,
num_var_tape_,
for_jac_pattern,
rev_jac_pattern,
for_hes_pattern,
not_used_rec_base
);
// initialize return values corresponding to independent variables
h.resize(n * n);
for(size_t i = 0; i < n; i++)
{ for(size_t j = 0; j < n; j++)
h[ i * n + j ] = false;
}
// copy to result pattern
CPPAD_ASSERT_UNKNOWN( for_hes_pattern.end() == n+1 );
for(size_t i = 0; i < n; i++)
{ // ind_taddr_[i] is operator taddr for i-th independent variable
CPPAD_ASSERT_UNKNOWN( ind_taddr_[i] == i + 1 );
CPPAD_ASSERT_UNKNOWN( play_.GetOp( ind_taddr_[i] ) == local::InvOp );
// extract the result from for_hes_pattern
local::sparse_pack::const_iterator itr(for_hes_pattern, ind_taddr_[i] );
size_t j = *itr;
while( j < for_hes_pattern.end() )
{ CPPAD_ASSERT_UNKNOWN( 0 < j )
h[ i * n + (j-1) ] = true;
j = *(++itr);
}
}
}
