template<class Base >

template<class SizeVector >

void CppAD::ADFun< Base >::for_jac_sparsity	(	const sparse_rc< SizeVector > &	pattern_in,
		bool	transpose,
		bool	dependency,
		bool	internal_bool,
		sparse_rc< SizeVector > &	pattern_out
	)

Forward Jacobian sparsity patterns.

Template Parameters

Base	is the base type for this recording.
SizeVector	is the simple vector with elements of type size_t that is used for row, column index sparsity patterns.

Parameters

pattern_in	is the sparsity pattern for for R or R^T depending on transpose.
transpose	Is the input and returned sparsity pattern transposed.
dependency	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) This is used by the optimizer to obtain the correct dependency relations.
internal_bool	If this is true, calculations are done with sets represented by a vector of boolean values. Othewise, a vector of standard sets is used.
pattern_out	The value of transpose is false (true), the return value is a sparsity pattern for J(x) ( J(x)^T ) where Here F is the function corresponding to the operation sequence and x is any argument value.

Definition at line 208 of file for_jac_sparsity.hpp.