void ForSparseJacBool(
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 ,
sparse_pack& for_jac_sparsity )
{
// temporary indices
size_t i, j;
// range and domain dimensions for F
size_t m = dep_taddr.size();
size_t n = ind_taddr.size();
CPPAD_ASSERT_KNOWN(
q > 0,
"ForSparseJac: q is not greater than zero"
);
CPPAD_ASSERT_KNOWN(
size_t(r.size()) == n * q,
"ForSparseJac: size of r is not equal to\n"
"q times domain dimension for ADFun object."
);
// allocate memory for the requested sparsity calculation result
for_jac_sparsity.resize(total_num_var, q);
// set values corresponding to independent variables
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 );
// set bits that are true
if( transpose )
{ for(j = 0; j < q; j++) if( r[ j * n + i ] )
for_jac_sparsity.add_element( ind_taddr[i], j);
}
else
{ for(j = 0; j < q; j++) if( r[ i * q + j ] )
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 * q );
for(i = 0; i < m; i++)
{ CPPAD_ASSERT_UNKNOWN( dep_taddr[i] < total_num_var );
// extract the result from for_jac_sparsity
if( transpose )
{ for(j = 0; j < q; j++)
s[ j * m + i ] = false;
}
else
{ for(j = 0; j < q; j++)
s[ i * q + j ] = false;
}
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 * m + i] = true;
else s[i * q + j] = true;
j = for_jac_sparsity.next_element();
}
}
}
void sparsity_user2internal(
sparse_pack& internal ,
const VectorBool& user ,
size_t n_row ,
size_t n_col ,
bool transpose )
{ CPPAD_ASSERT_UNKNOWN( n_row * n_col == size_t(user.size()) );
size_t i, j;
CPPAD_ASSERT_KNOWN(
size_t( user.size() ) == n_row * n_col,
"Size of this vector of bools sparsity pattern is not equal product "
"of the domain and range dimensions for corresponding function."
);
// transposed pattern case
if( transpose )
{ internal.resize(n_col, n_row);
for(j = 0; j < n_col; j++)
{ for(i = 0; i < n_row; i++)
{ if( user[ i * n_col + j ] )
internal.add_element(j, i);
}
}
return;
}
// same pattern case
internal.resize(n_row, n_col);
for(i = 0; i < n_row; i++)
{ for(j = 0; j < n_col; j++)
{ if( user[ i * n_col + j ] )
internal.add_element(i, j);
}
}
return;
}