CppAD: A C++ Algorithmic Differentiation Package
20130918
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struct_size_pair CppAD::optimize::record_vv | ( | 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 variable).
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: AddvvOp, DivvvOp, MulvvOp, PowvpOp, SubvvOp. |
arg | is the vector of arguments for this operator. |
Definition at line 978 of file optimize.hpp.
Referenced by optimize_run().