void ForSparseJacSet(
bool transpose ,
size_t q ,
const VectorSet& r ,
VectorSet& s ,
size_t total_num_var ,
CppAD::vector<size_t>& dep_taddr ,
CppAD::vector<size_t>& ind_taddr ,
CppAD::player<Base>& play ,
CPPAD_INTERNAL_SPARSE_SET& for_jac_sparsity )
{
// temporary indices
size_t i, j;
std::set<size_t>::const_iterator itr;
// range and domain dimensions for F
size_t m = dep_taddr.size();
size_t n = ind_taddr.size();
CPPAD_ASSERT_KNOWN(
q > 0,
"RevSparseJac: q is not greater than zero"
);
CPPAD_ASSERT_KNOWN(
size_t(r.size()) == n || transpose,
"RevSparseJac: size of r is not equal to n and transpose is false."
);
CPPAD_ASSERT_KNOWN(
size_t(r.size()) == q || ! transpose,
"RevSparseJac: size of r is not equal to q and transpose is true."
);
// allocate memory for the requested sparsity calculation
for_jac_sparsity.resize(total_num_var, q);
// set values corresponding to independent variables
if( transpose )
{ for(i = 0; i < q; i++)
{ // add the elements that are present
itr = r[i].begin();
while( itr != r[i].end() )
{ j = *itr++;
CPPAD_ASSERT_KNOWN(
j < n,
"ForSparseJac: transpose is true and element of the set\n"
"r[j] has value greater than or equal n."
);
CPPAD_ASSERT_UNKNOWN( ind_taddr[j] < total_num_var );
// operator for j-th independent variable
CPPAD_ASSERT_UNKNOWN( play.GetOp( ind_taddr[j] ) == InvOp );
for_jac_sparsity.add_element( ind_taddr[j], i);
}
}
}
else
{ for(i = 0; i < n; i++)
{ CPPAD_ASSERT_UNKNOWN( ind_taddr[i] < total_num_var );
// ind_taddr[i] is operator taddr for i-th independent variable
CPPAD_ASSERT_UNKNOWN( play.GetOp( ind_taddr[i] ) == InvOp );
// add the elements that are present
itr = r[i].begin();
while( itr != r[i].end() )
{ j = *itr++;
CPPAD_ASSERT_KNOWN(
j < q,
"ForSparseJac: an element of the set r[i] "
"has value greater than or equal q."
);
for_jac_sparsity.add_element( ind_taddr[i], j);
}
}
}
// evaluate the sparsity patterns
ForJacSweep(
n,
total_num_var,
&play,
for_jac_sparsity
);
// return values corresponding to dependent variables
CPPAD_ASSERT_UNKNOWN( size_t(s.size()) == m || transpose );
CPPAD_ASSERT_UNKNOWN( size_t(s.size()) == q || ! transpose );
for(i = 0; i < m; i++)
{ CPPAD_ASSERT_UNKNOWN( dep_taddr[i] < total_num_var );
// extract results from for_jac_sparsity
// and add corresponding elements to sets in s
CPPAD_ASSERT_UNKNOWN( for_jac_sparsity.end() == q );
for_jac_sparsity.begin( dep_taddr[i] );
j = for_jac_sparsity.next_element();
while( j < q )
{ if( transpose )
s[j].insert(i);
else s[i].insert(j);
j = for_jac_sparsity.next_element();
}
}
}
void ADFun<Base>::RevSparseJacCheckpoint(
size_t q ,
CPPAD_INTERNAL_SPARSE_SET& r ,
bool transpose ,
bool dependency ,
CPPAD_INTERNAL_SPARSE_SET& s )
{ size_t n = Domain();
size_t m = Range();
# ifndef NDEBUG
if( transpose )
{ CPPAD_ASSERT_UNKNOWN( r.n_set() == m );
CPPAD_ASSERT_UNKNOWN( r.end() == q );
}
else
{ CPPAD_ASSERT_UNKNOWN( r.n_set() == q );
CPPAD_ASSERT_UNKNOWN( r.end() == m );
}
for(size_t i = 0; i < m; i++)
CPPAD_ASSERT_UNKNOWN( dep_taddr_[i] < num_var_tape_ );
# endif
// holds reverse Jacobian sparsity pattern for all variables
CPPAD_INTERNAL_SPARSE_SET var_sparsity;
var_sparsity.resize(num_var_tape_, q);
// set sparsity pattern for dependent variables
if( transpose )
{ for(size_t i = 0; i < m; i++)
{ r.begin(i);
size_t j = r.next_element();
while( j < q )
{ var_sparsity.add_element( dep_taddr_[i], j );
j = r.next_element();
}
}
}
else
{ for(size_t j = 0; j < q; j++)
{ r.begin(j);
size_t i = r.next_element();
while( i < m )
{ var_sparsity.add_element( dep_taddr_[i], j );
i = r.next_element();
}
}
}
// evaluate the sparsity pattern for all variables
RevJacSweep(
dependency,
n,
num_var_tape_,
&play_,
var_sparsity
);
// dimension the return value
if( transpose )
s.resize(n, m);
else
s.resize(m, n);
// return values corresponding to independent variables
for(size_t j = 0; j < n; j++)
{ CPPAD_ASSERT_UNKNOWN( ind_taddr_[j] == (j+1) );
// ind_taddr_[j] is operator taddr for j-th independent variable
CPPAD_ASSERT_UNKNOWN( play_.GetOp( ind_taddr_[j] ) == InvOp );
// extract the result from var_sparsity
CPPAD_ASSERT_UNKNOWN( var_sparsity.end() == q );
var_sparsity.begin(j+1);
size_t i = var_sparsity.next_element();
while( i < q )
{ if( transpose )
s.add_element(j, i);
else
s.add_element(i, j);
i = var_sparsity.next_element();
}
}
}