CppAD: A C++ Algorithmic Differentiation Package  20171217
template<class Vector_set >
 void CppAD::local::reverse_sparse_jacobian_store_op ( bool dependency, OpCode op, const addr_t * arg, size_t num_combined, const size_t * combined, Vector_set & var_sparsity, Vector_set & vecad_sparsity )
inline

Reverse mode sparsity operations for StpvOp, StvpOp, and StvvOp.

The C++ source code corresponding to this operation is

```     v[x] = y
```

where v is a VecAD<Base> vector, x is an AD<Base> object, and y is AD<Base> or Base objects. We define the index corresponding to v[x] by

```     i_v_x = index_by_ind[ arg[0] + i_vec ]
```

where i_vec is defined under the heading arg[1] below:

This routine is given the sparsity patterns for G(v[x], y , w , u ... ) and it uses them to compute the sparsity patterns for

```     H(y , w , u , ... ) = G[ v[x], y , w , u , ... ]
```
Parameters
 dependency is this a dependency (or sparsity) calculation.
Template Parameters
 Vector_set is the type used for vectors of sets. It can be either sparse_pack or sparse_list.
Parameters
 op is the code corresponding to this operator; i.e., StpvOp, StvpOp, or StvvOp. arg arg[0] is the offset corresponding to this VecAD vector in the combined array. arg[2] The set with index arg[2] in var_sparsity is the sparsity pattern corresponding to y. (Note that arg[2] > 0 because y is a variable.) num_combined is the total number of elements in the VecAD address array. combined combined [ arg[0] - 1 ] is the index of the set in vecad_sparsity corresponding to the sparsity pattern for the vector v. We use the notation i_v below which is defined by ``` i_v = combined[ \a arg[0] - 1 ] ``` var_sparsity The set with index arg[2] in var_sparsity is the sparsity pattern for y. This is an input for forward mode operations. For reverse mode operations: The sparsity pattern for v is added to the spartisy pattern for y. vecad_sparsity The set with index i_v in vecad_sparsity is the sparsity pattern for v. This is an input for reverse mode operations. For forward mode operations, the sparsity pattern for y is added to the sparsity pattern for the vector v.
Checked Assertions
• NumArg(op) == 3
• NumRes(op) == 0
• 0 < arg[0]
• arg[0] < num_combined
• arg[2] < var_sparsity.n_set()