62 for( run1 = 0; run1 <
dim; run1++ ){
70 for( run1 = 0; run1 <
dim; run1++ ){
72 for( run2 = 0; run2 < nIndex[run1]; run2++ )
80 for( run1 = 0; run1 <
dim; run1++ ){
97 for( run1 = 0; run1 <
dim; run1++ )
152 for( run1 = 0; run1 <
dim; run1++ ){
155 bound = dim*(run1+1);
156 bound2 = run1*(dim+1);
160 while( counter <
nDense ){
162 if( diagFound ==
BT_FALSE && indices[counter] >= bound2 ){
167 if( indices[counter] >= bound )
break;
171 nIndex[run1] = counter - counter0;
175 for( run1 = 0; run1 <
dim; run1++ )
176 delete[]
index[run1];
183 for( run1 = 0; run1 <
dim; run1++ ){
185 for( run2 = 0; run2 < nIndex[run1]; run2++ ){
214 for( i = 0; i <
dim; i++ ){
217 for( j = 0; j <
nIndex[i]; j++ ){
231 for( i = 0; i <
dim; i++ ){
237 for( i = 0; i <
dim; i++ ){
239 for( j = 0; j <
nIndex[i]; j++ ){
254 for( run1 = 0; run1 <
dim; run1++ )
267 for( run1 = 0; run1 <
dim; run1++ )
SymmetricConjugateGradientMethod()
IntermediateState sqrt(const Expression &arg)
virtual returnValue applyInversePreconditioner(double *x_)
virtual returnValue computePreconditioner(double *A_)
Allows to pass back messages to the calling function.
virtual returnValue setIndices(const int *rowIdx_, const int *colIdx_)
#define CLOSE_NAMESPACE_ACADO
virtual SparseSolver * clone() const
Implements a conjugate gradient method as sparse linear algebra solver for symmetric linear systems...
virtual void multiply(double *xx, double *result)
Implements a conjugate gradient method as sparse linear algebra solver.
virtual ~SymmetricConjugateGradientMethod()
Generic interface for sparse solvers to be coupled with ACADO Toolkit.
#define BEGIN_NAMESPACE_ACADO
virtual returnValue applyPreconditioner(double *b)
#define ACADOERROR(retval)