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CppAD: A C++ Algorithmic Differentiation Package
20130918
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| struct_size_pair CppAD::optimize::record_vp | ( | const CppAD::vector< struct struct_old_variable > & | tape, |
| size_t | current, | ||
| size_t | npar, | ||
| const Base * | par, | ||
| recorder< Base > * | rec, | ||
| OpCode | op, | ||
| const addr_t * | arg | ||
| ) |
Record an operation of the form (variable op parameter).
| tape | is a vector that maps a variable index, in the old operation sequence, to an struct_old_variable information record. Note that the index for this vector must be greater than or equal zero and less than tape.size(). |
tape[i].op is the operator in the old operation sequence corresponding to the old variable index i. Assertion: NumRes(tape[i].op) > 0.tape[i].arg for j < NumArg( tape[i].op ), tape[i].arg[j] is the j-th the argument, in the old operation sequence, corresponding to the old variable index i. Assertion: tape[i].arg[j] < i.tape[i].new_var Suppose i <= current, j < NumArg( tape[i].op ), and k = tape[i].arg[j], and j corresponds to a variable for operator tape[i].op. It follows that tape[k].new_var has alread been set to the variable in the new operation sequence corresponding to the old variable index k. This means that the new_var value has been set for all the possible arguments that come before current.| current | is the index in the old operation sequence for the variable corresponding to the result for the current operator. Assertions: current < tape.size(), NumRes( tape[current].op ) > 0. |
| npar | is the number of parameters corresponding to this operation sequence. |
| par | is a vector of length npar containing the parameters for this operation sequence; i.e., given a parameter index i, the corresponding parameter value is par[i]. |
| rec | is the object that will record the operations. |
| op | is the operator that we are recording which must be one of the following: DivvpOp, PowvpOp, SubvpOp. |
| arg | is the vector of arguments for this operator. |
Definition at line 879 of file optimize.hpp.
Referenced by optimize_run().