template<class Base , class Vector_set >

void ForJacSweep	(	size_t	n,
		size_t	numvar,
		player< Base > *	play,
		Vector_set &	var_sparsity
	)

Given the sparsity pattern for the independent variables, ForJacSweep computes the sparsity pattern for all the other variables.

Template Parameters:

Base	base type for the operator; i.e., this operation sequence was recorded using AD< Base > and computations by this routine are done using type Base.
Vector_set	is the type used for vectors of sets. It can be either sparse_pack, sparse_set, or sparse_list.

Parameters:

n	is the number of independent variables on the tape.
numvar	is the total number of variables on the tape; i.e., play->num_rec_var().
play	The information stored in play is a recording of the operations corresponding to a function where is the number of independent variables and is the number of dependent variables. The object play is effectly constant. It is not declared const because while playing back the tape the object play holds information about the currentl location with in the tape and this changes during playback.
var_sparsity	Input: For j = 1 , ... , n, the sparsity pattern for the independent variable with index (j-1) corresponds to the set with index j in var_sparsity. Output: For i = n + 1 , ... , numvar - 1, the sparsity pattern for the variable with index i on the tape corresponds to the set with index i in var_sparsity.

Checked Assertions:

• numvar == var_sparsity.n_set()
• numvar == play->num_rec_var()

Definition at line 82 of file for_jac_sweep.hpp.

Referenced by ForSparseJacBool(), and ForSparseJacSet().