void ForSparseJacSet(
	bool                        transpose        , 
	size_t                      q                , 
	const VectorSet&            r                ,
	VectorSet&                  s                ,
	size_t                      total_num_var    ,
	CppAD::vector<size_t>&      dep_taddr        ,
	CppAD::vector<size_t>&      ind_taddr        ,
	CppAD::player<Base>&        play             ,
	CPPAD_INTERNAL_SPARSE_SET&  for_jac_sparsity )
{
	// temporary indices
	size_t i, j;
	std::set<size_t>::const_iterator itr;

	// range and domain dimensions for F
	size_t m = dep_taddr.size();
	size_t n = ind_taddr.size();

	CPPAD_ASSERT_KNOWN(
		q > 0,
		"RevSparseJac: q is not greater than zero"
	);
	CPPAD_ASSERT_KNOWN(
		size_t(r.size()) == n || transpose,
		"RevSparseJac: size of r is not equal to n and transpose is false."
	);
	CPPAD_ASSERT_KNOWN(
		size_t(r.size()) == q || ! transpose,
		"RevSparseJac: size of r is not equal to q and transpose is true."
	);

	// allocate memory for the requested sparsity calculation
	for_jac_sparsity.resize(total_num_var, q);

	// set values corresponding to independent variables
	if( transpose )
	{	for(i = 0; i < q; i++)
		{	// add the elements that are present
			itr = r[i].begin();
			while( itr != r[i].end() )
			{	j = *itr++;
				CPPAD_ASSERT_KNOWN(
				j < n,
				"ForSparseJac: transpose is true and element of the set\n"
				"r[j] has value greater than or equal n."
				);
				CPPAD_ASSERT_UNKNOWN( ind_taddr[j] < total_num_var );
				// operator for j-th independent variable
				CPPAD_ASSERT_UNKNOWN( play.GetOp( ind_taddr[j] ) == InvOp );
				for_jac_sparsity.add_element( ind_taddr[j], i);
			}
		}
	}
	else
	{	for(i = 0; i < n; i++)
		{	CPPAD_ASSERT_UNKNOWN( ind_taddr[i] < total_num_var );
			// ind_taddr[i] is operator taddr for i-th independent variable
			CPPAD_ASSERT_UNKNOWN( play.GetOp( ind_taddr[i] ) == InvOp );

			// add the elements that are present
			itr = r[i].begin();
			while( itr != r[i].end() )
			{	j = *itr++;
				CPPAD_ASSERT_KNOWN(
					j < q,
					"ForSparseJac: an element of the set r[i] "
					"has value greater than or equal q."
				);
				for_jac_sparsity.add_element( ind_taddr[i], j);
			}
		}
	}
	// evaluate the sparsity patterns
	ForJacSweep(
		n,
		total_num_var,
		&play,
		for_jac_sparsity
	);

	// return values corresponding to dependent variables
	CPPAD_ASSERT_UNKNOWN( size_t(s.size()) == m || transpose );
	CPPAD_ASSERT_UNKNOWN( size_t(s.size()) == q || ! transpose );
	for(i = 0; i < m; i++)
	{	CPPAD_ASSERT_UNKNOWN( dep_taddr[i] < total_num_var );

		// extract results from for_jac_sparsity
		// and add corresponding elements to sets in s
		CPPAD_ASSERT_UNKNOWN( for_jac_sparsity.end() == q );
		for_jac_sparsity.begin( dep_taddr[i] );
		j = for_jac_sparsity.next_element();
		while( j < q )
		{	if( transpose )
				s[j].insert(i);
			else	s[i].insert(j);
			j = for_jac_sparsity.next_element();
		}
	}
}
Beispiel #2
0
void RevSparseHesSet(
	bool                       transpose         ,
	size_t                     q                 ,
	const  VectorSet&          s                 ,
	VectorSet&                 h                 ,
	size_t                     num_var           ,
	CppAD::vector<size_t>&     dep_taddr         ,
	CppAD::vector<size_t>&     ind_taddr         ,
	CppAD::player<Base>&       play              ,
	CPPAD_INTERNAL_SPARSE_SET& for_jac_sparsity  )
{
	// temporary indices
	size_t i, j;
	std::set<size_t>::const_iterator itr;

	// check VectorSet is Simple Vector class with sets for elements
	CheckSimpleVector<std::set<size_t>, VectorSet>(
		one_element_std_set<size_t>(), two_element_std_set<size_t>()
	);

	// range and domain dimensions for F
# ifndef NDEBUG
	size_t m = dep_taddr.size();
# endif
	size_t n = ind_taddr.size();

	CPPAD_ASSERT_KNOWN(
		q == for_jac_sparsity.end(),
		"RevSparseHes: q is not equal to its value\n"
		"in the previous call to ForSparseJac with this ADFun object."
	);
	CPPAD_ASSERT_KNOWN(
		s.size() == 1,
		"RevSparseHes: size of s is not equal to one."
	);

	// Array that will hold reverse Jacobian dependency flag.
	// Initialize as true for the dependent variables.
	pod_vector<bool> RevJac;
	RevJac.extend(num_var);	
	for(i = 0; i < num_var; i++)
		RevJac[i] = false;
	itr = s[0].begin();
	while( itr != s[0].end() )
	{	i = *itr++;
		CPPAD_ASSERT_KNOWN(
			i < m,
			"RevSparseHes: an element of the set s[0] has value "
			"greater than or equal m"
		);
		CPPAD_ASSERT_UNKNOWN( dep_taddr[i] < num_var );
		RevJac[ dep_taddr[i] ] = true;
	}


	// vector of sets that will hold reverse Hessain values
	CPPAD_INTERNAL_SPARSE_SET rev_hes_sparsity;
	rev_hes_sparsity.resize(num_var, q);

	// compute the Hessian sparsity patterns
	RevHesSweep(
		n,
		num_var,
		&play,
		for_jac_sparsity, 
		RevJac.data(),
		rev_hes_sparsity
	);

	// return values corresponding to independent variables
	// j is index corresponding to reverse mode partial
	CPPAD_ASSERT_UNKNOWN( size_t(h.size()) == q || transpose );
	CPPAD_ASSERT_UNKNOWN( size_t(h.size()) == n || ! transpose );
	for(j = 0; j < n; j++)
	{	CPPAD_ASSERT_UNKNOWN( ind_taddr[j] < num_var );
		CPPAD_ASSERT_UNKNOWN( ind_taddr[j] == j + 1 );
		CPPAD_ASSERT_UNKNOWN( play.GetOp( ind_taddr[j] ) == InvOp );

		// extract the result from rev_hes_sparsity
		// and add corresponding elements to result sets in h
		CPPAD_ASSERT_UNKNOWN( rev_hes_sparsity.end() == q );
		rev_hes_sparsity.begin(j+1);
		i = rev_hes_sparsity.next_element();
		while( i < q )
		{	if( transpose )
				h[j].insert(i);
			else	h[i].insert(j);
			i = rev_hes_sparsity.next_element();
		}
	}

	return;
}
Beispiel #3
0
void ADFun<Base>::RevSparseJacCheckpoint(
	size_t                        q          ,
	CPPAD_INTERNAL_SPARSE_SET&    r          ,
	bool                          transpose  ,
	bool                          dependency ,
	CPPAD_INTERNAL_SPARSE_SET&    s          )
{	size_t n = Domain();
	size_t m = Range();

# ifndef NDEBUG
	if( transpose )
	{	CPPAD_ASSERT_UNKNOWN( r.n_set() == m );
		CPPAD_ASSERT_UNKNOWN( r.end()   == q );
	}
	else
	{	CPPAD_ASSERT_UNKNOWN( r.n_set() == q );
		CPPAD_ASSERT_UNKNOWN( r.end()   == m );
	}
	for(size_t i = 0; i < m; i++)
		CPPAD_ASSERT_UNKNOWN( dep_taddr_[i] < num_var_tape_ );
# endif

	// holds reverse Jacobian sparsity pattern for all variables
	CPPAD_INTERNAL_SPARSE_SET var_sparsity;
	var_sparsity.resize(num_var_tape_, q);

	// set sparsity pattern for dependent variables
	if( transpose )
	{	for(size_t i = 0; i < m; i++)
		{	r.begin(i);
			size_t j = r.next_element();
			while( j < q )
			{	var_sparsity.add_element( dep_taddr_[i], j );
				j = r.next_element();
			}
		}
	}
	else
	{	for(size_t j = 0; j < q; j++)
		{	r.begin(j);
			size_t i = r.next_element();
			while( i < m )
			{	var_sparsity.add_element( dep_taddr_[i], j );
				i = r.next_element();
			}
		}
	}

	// evaluate the sparsity pattern for all variables
	RevJacSweep(
		dependency,
		n,
		num_var_tape_,
		&play_,
		var_sparsity
	);

	// dimension the return value
	if( transpose )
		s.resize(n, m);
	else
		s.resize(m, n);

	// return values corresponding to independent variables
	for(size_t j = 0; j < n; j++)
	{	CPPAD_ASSERT_UNKNOWN( ind_taddr_[j] == (j+1) );

		// ind_taddr_[j] is operator taddr for j-th independent variable
		CPPAD_ASSERT_UNKNOWN( play_.GetOp( ind_taddr_[j] ) == InvOp );

		// extract the result from var_sparsity
		CPPAD_ASSERT_UNKNOWN( var_sparsity.end() == q );
		var_sparsity.begin(j+1);
		size_t i = var_sparsity.next_element();
		while( i < q )
		{	if( transpose )
				s.add_element(j, i);
			else
				s.add_element(i, j);
			i  = var_sparsity.next_element();
		}
	}

}