CppAD: A C++ Algorithmic Differentiation Package
20130918
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void CppAD::reverse_sparse_jacobian_cond_op | ( | bool | nz_compare, |
size_t | i_z, | ||
const addr_t * | arg, | ||
size_t | num_par, | ||
Vector_set & | sparsity | ||
) | [inline] |
Compute reverse Jacobian sparsity patterns for op = CExpOp.
This routine is given the sparsity patterns for a function G(z, y, x, ... ) and it uses them to compute the sparsity patterns for
H( y, x, w , u , ... ) = G[ z(x,y) , y , x , w , u , ... ]
where y represents the combination of y_0, y_1, y_2, and y_3.
The C++ source code coresponding to this operation is
z = CondExpRel(y_0, y_1, y_2, y_3)
where Rel is one of the following: Lt, Le, Eq, Ge, Gt.
Vector_set | is the type used for vectors of sets. It can be either sparse_pack , sparse_set , or sparse_list . |
i_z | is the AD variable index corresponding to the variable z. |
arg | arg[0] is static cast to size_t from the enum type enum CompareOp { CompareLt, CompareLe, CompareEq, CompareGe, CompareGt, CompareNe } arg[1] & 1 If this is zero, y_0 is a parameter. Otherwise it is a variable. arg[1] & 2 If this is zero, y_1 is a parameter. Otherwise it is a variable. arg[1] & 4 If this is zero, y_2 is a parameter. Otherwise it is a variable. arg[1] & 8 If this is zero, y_3 is a parameter. Otherwise it is a variable. arg[2 + j ] for j = 0, 1, 2, 3 is the index corresponding to y_j. |
num_par | is the total number of values in the vector parameter. |
nz_compare | Are the derivatives with respect to left and right of the expression below considered to be non-zero: CondExpRel(left, right, if_true, if_false) |
sparsity | if y_2 is a variable, the set with index t is the sparsity pattern corresponding to y_2. This identifies which of the dependent variables depend on the variable y_2. On input, this pattern corresponds to the function G. On ouput, it corresponds to the function H. if y_3 is a variable, the set with index t is the sparsity pattern corresponding to y_3. This identifies which of the dependent variables depeond on the variable y_3. On input, this pattern corresponds to the function G. On ouput, it corresponds to the function H. Output: The set with index T is the sparsity pattern corresponding to z. This identifies which of the dependent variables depend on the variable z. On input and output, this pattern corresponds to the function G. |
Definition at line 968 of file cond_op.hpp.
Referenced by RevJacSweep().