void frictionContact2D_enum(FrictionContactProblem* problem, double *reaction, double *velocity, int *info, SolverOptions* options, NumericsOptions* global_options)
{
int i;
// conversion into LCP
LinearComplementarityProblem* lcp_problem = (LinearComplementarityProblem*)malloc(sizeof(LinearComplementarityProblem));
FrictionContact2D_tolcp(problem, lcp_problem);
/* frictionContact_display(problem); */
/* linearComplementarity_display(lcp_problem); */
double *zlcp = (double*)malloc(lcp_problem->size * sizeof(double));
double *wlcp = (double*)malloc(lcp_problem->size * sizeof(double));
for (i = 0; i < lcp_problem->size; i++)
{
zlcp[i] = 0.0;
wlcp[i] = 0.0;
}
/* FILE * fcheck = fopen("lcp_relay.dat","w"); */
/* info = linearComplementarity_printInFile(lcp_problem,fcheck); */
// Call the lcp_solver
SolverOptions * lcp_options = options->internalSolvers;
lcp_enum_init(lcp_problem, lcp_options, 1);
//}
* info = linearComplementarity_driver(lcp_problem, zlcp , wlcp, lcp_options, global_options);
if (options->filterOn > 0)
lcp_compute_error(lcp_problem, zlcp, wlcp, lcp_options->dparam[0], &(lcp_options->dparam[1]));
lcp_enum_reset(lcp_problem, lcp_options, 1);
/* printf("\n"); */
int nc = problem->numberOfContacts;
// Conversion of result
for (i = 0; i < nc; i++)
{
/* printf("Contact number = %i\n",i); */
reaction[2 * i] = zlcp[3 * i];
reaction[2 * i + 1] = 1.0 / 2.0 * (zlcp[3 * i + 1] - wlcp[3 * i + 2]);
/* printf("reaction[ %i]=%12.10e\n", 2*i, reaction[2*i]); */
/* printf("reaction[ %i]=%12.10e\n", 2*i+1, reaction[2*i+1]); */
velocity[2 * i] = wlcp[3 * i];
velocity[2 * i + 1] = wlcp[3 * i + 1] - zlcp[3 * i + 2];
/* printf("velocity[ %i]=%12.10e\n", 2*i, velocity[2*i]); */
/* printf("velocity[ %i]=%12.10e\n", 2*i+1, velocity[2*i+1]); */
}
/* for (i=0; i< lcp_problem->size; i++){ */
/* printf("zlcp[ %i]=%12.10e,\t wlcp[ %i]=%12.10e \n", i, zlcp[i],i, wlcp[i]); */
/* } */
/* printf("\n"); */
/* for (i=0; i< problem->size; i++){ */
/* printf("z[ %i]=%12.10e,\t w[ %i]=%12.10e\n", i, z[i],i, w[i]); */
/* } */
/* printf("\n"); */
double error;
*info = FrictionContact2D_compute_error(problem, reaction , velocity, options->dparam[0], &error);
free(zlcp);
free(wlcp);
freeLinearComplementarityProblem(lcp_problem);
}
void lcp_path(LinearComplementarityProblem* problem, double *z, double *w, int *info , SolverOptions* options)
{
*info = 1;
#ifdef HAVE_PATHFERRIS
/* matrix M/vector q of the lcp */
double * M = problem->M->matrix0;
double * q = problem->q;
int nnz, i, j, dim;
/* size of the LCP */
int n = problem->size;
double tol = options->dparam[0];
MCP_Termination termination;
nnz = nbNonNulElems(n, M, 1.0e-18);
int * m_i = (int *)calloc(nnz + 1, sizeof(int));
int * m_j = (int *)calloc(nnz + 1, sizeof(int));
double * m_ij = (double *)calloc(nnz + 1, sizeof(double));
double * lb = (double *)calloc(n + 1, sizeof(double));
double * ub = (double *)calloc(n + 1, sizeof(double));
double err, val;
FortranToPathSparse(n, M, 1.0e-18, m_i, m_j, m_ij);
for (i = 0; i < n; i++)
{
lb[i] = 0.;
ub[i] = 1.e20;
}
SimpleLCP(n, nnz, m_i, m_j, m_ij, q, lb, ub,
&termination, z);
if (termination == MCP_Error)
{
*info = 1;
if (verbose > 0)
printf("PATH : Error in the solution.\n");
}
else if (termination == MCP_Solved)
{
for (i = 0; i < n; i++)
{
val = q[i];
for (j = 0; j < n; j++)
{
val += M[i + j * n] * z[j];
}
w[i] = val;
}
*info = 0;
/* **** Criterium convergence **** */
lcp_compute_error(problem, z, w, tol, &err);
if (verbose > 0)
printf("PATH : LCP Solved, error %10.7f.\n", err);
}
else
{
if (verbose > 0)
printf("PATH : Other error: %d\n", termination);
}
free(m_i);
free(m_j);
free(m_ij);
free(lb);
free(ub);
#endif /*HAVE_PATHFERRIS*/
return;
}
void lcp_nsgs_SBM(LinearComplementarityProblem* problem, double *z, double *w, int *info, SolverOptions* options)
{
/* Notes:
- we suppose that the trivial solution case has been checked
before, and that all inputs differs from NULL since this function
is supposed to be called from lcp_driver_global().
- Input matrix M of the problem is supposed to be sparse-block
with no null row (ie no rows with all blocks equal to null)
*/
if (problem->M->matrix1 == NULL)
{
fprintf(stderr, "lcp_NSGS_SBM error: wrong storage type for input matrix M of the LCP.\n");
exit(EXIT_FAILURE);
}
/*
The options for the global "block" solver are defined in options[0].\n
options[i], for 0<i<numberOfSolvers-1 correspond to local solvers.
*/
/* Global Solver parameters*/
int itermax = options[0].iparam[0];
double tolerance = options[0].dparam[0];
/* Matrix M/vector q of the LCP */
SparseBlockStructuredMatrix* blmat = problem->M->matrix1;
double * q = problem->q;
/* Number of non-null blocks in blmat */
int nbOfNonNullBlocks = blmat->nbblocks;
if (nbOfNonNullBlocks < 1)
{
fprintf(stderr, "Numerics::lcp_NSGS_SBM error: empty M matrix (all blocks = NULL).\n");
exit(EXIT_FAILURE);
}
/* Local problem initialization */
LinearComplementarityProblem * local_problem = (LinearComplementarityProblem *)malloc(sizeof(*local_problem));
local_problem->M = (NumericsMatrix *)malloc(sizeof(*local_problem->M));
local_problem->M->storageType = 0; // dense storage
local_problem->M->matrix0 = NULL;
local_problem->M->matrix1 = NULL;
local_problem->M->matrix2 = NULL;
local_problem->M->internalData = NULL;
/* Memory allocation for q. Size of q = blsizemax, size of the largest square-block in blmat */
int blsizemax = blmat->blocksize0[0];
int k;
for (unsigned int i = 1 ; i < blmat->blocknumber0 ; i++)
{
k = blmat->blocksize0[i] - blmat->blocksize0[i - 1];
if (k > blsizemax) blsizemax = k;
}
local_problem->q = (double*)malloc(blsizemax * sizeof(double));
/* Current row (of blocks) number */
unsigned int rowNumber;
/***** Gauss-Seidel iterations *****/
int iter = 0; /* Current iteration number */
double error = 1.; /* Current error */
int hasNotConverged = 1;
/* Output from local solver */
options[0].iparam[2] = 0;
options[0].dparam[2] = 0.0;
if (options->numberOfInternalSolvers < 1)
{
numericsError("lcp_nsgs_SBM", "The NSGS_SBM method needs options for the internal solvers, options[0].numberOfInternalSolvers should be >1");
}
/*Number of the local solver */
int localSolverNum = options->numberOfInternalSolvers ;
SolverOptions * internalSolvers = options->internalSolvers ;
int pos = 0;
/* Output from local solver */
int infoLocal = -1;
while ((iter < itermax) && (hasNotConverged > 0))
{
++iter;
/* Loop over the rows of blocks in blmat */
localSolverNum = 0;
pos = 0;
/* cblas_dcopy(problem->size,w,1,wBackup,1); */
for (rowNumber = 0; rowNumber < blmat->blocknumber0; ++rowNumber)
{
/* Local problem formalization */
lcp_nsgs_SBM_buildLocalProblem(rowNumber, blmat, local_problem, q, z);
/* Solve local problem */
infoLocal = lcp_driver_DenseMatrix(local_problem, &z[pos], &w[pos], &internalSolvers[localSolverNum]);
pos += local_problem->size;
/* sum of local number of iterations (output from local_driver)*/
if (options[localSolverNum].iparam != NULL)
options[0].iparam[2] += internalSolvers[localSolverNum].iparam[1];
/* sum of local errors (output from local_driver)*/
options[0].dparam[2] += internalSolvers[localSolverNum].dparam[1];
if (infoLocal > 0)
{
//free(local_problem->q);
//free(local_problem->M);
//free(local_problem);
/* Number of GS iterations */
options[0].iparam[1] = iter;
fprintf(stderr, "lcp_NSGS_SBM error: Warning local LCP solver at global iteration %d.\n for block-row number %d. Output info equal to %d.\n", iter, rowNumber, infoLocal);
//exit(EXIT_FAILURE);
break;
}
while (localSolverNum < options->numberOfInternalSolvers - 1)
localSolverNum++;
}
/* cblas_dcopy(problem->size , problem->q , 1 , w , 1); */
/* prod(problem->size,problem->size, 1.0, problem->M,z,1.0,w); */
/* cblas_daxpy(problem->size, -1.0, w,1,wBackup, 1); */
/* num = cblas_dnrm2(problem->size,wBackup,1); */
/* error = num*den; */
/* Criterium convergence */
hasNotConverged = lcp_compute_error(problem, z, w, tolerance, &error);
/* if(error<tolerance) hasNotConverged = 0; */
}
*info = hasNotConverged;
/* Number of GS iterations */
options[0].iparam[1] = iter;
/* Resulting error */
options[0].dparam[1] = error;
free(local_problem->q);
free(local_problem->M);
free(local_problem);
/* free(wBackup); */
}
void ncp_pathsearch(NonlinearComplementarityProblem* problem, double* z, double* F, int *info , SolverOptions* options)
{
/* Main step of the algorithm:
* - compute jacobians
* - call modified lemke
*/
unsigned int n = problem->n;
unsigned int preAlloc = options->iparam[SICONOS_IPARAM_PREALLOC];
int itermax = options->iparam[SICONOS_IPARAM_MAX_ITER];
double merit_norm = 1.0;
double nn_tol = options->dparam[SICONOS_DPARAM_TOL];
int nbiter = 0;
/* declare a LinearComplementarityProblem on the stack*/
LinearComplementarityProblem lcp_subproblem;
lcp_subproblem.size = n;
/* do some allocation if required
* - nabla_F (used also as M for the LCP subproblem)
* - q for the LCP subproblem
*
* Then fill the LCP subproblem
*/
if (!preAlloc || (preAlloc && !options->internalSolvers))
{
options->internalSolvers = (SolverOptions *) malloc(sizeof(SolverOptions));
solver_options_set(options->internalSolvers, SICONOS_LCP_PIVOT);
options->numberOfInternalSolvers = 1;
SolverOptions * lcp_options = options->internalSolvers;
/* We always allocation once and for all since we are supposed to solve
* many LCPs */
lcp_options->iparam[SICONOS_IPARAM_PREALLOC] = 1;
/* set the right pivot rule */
lcp_options->iparam[SICONOS_IPARAM_PIVOT_RULE] = SICONOS_LCP_PIVOT_PATHSEARCH;
/* set the right stacksize */
lcp_options->iparam[SICONOS_IPARAM_PATHSEARCH_STACKSIZE] = options->iparam[SICONOS_IPARAM_PATHSEARCH_STACKSIZE];
}
assert(problem->nabla_F);
lcp_subproblem.M = problem->nabla_F;
if (!preAlloc || (preAlloc && !options->dWork))
{
options->dWork = (double *) malloc(4*n*sizeof(double));
}
lcp_subproblem.q = options->dWork;
double* x = &options->dWork[n];
double* x_plus = &options->dWork[2*n];
double* r = &options->dWork[3*n];
NMS_data* data_NMS;
functions_LSA* functions;
if (!preAlloc || (preAlloc && !options->solverData))
{
options->solverData = malloc(sizeof(pathsearch_data));
pathsearch_data* solverData = (pathsearch_data*) options->solverData;
/* do all the allocation */
solverData->data_NMS = create_NMS_data(n, NM_DENSE, options->iparam, options->dparam);
solverData->lsa_functions = (functions_LSA*) malloc(sizeof(functions_LSA));
solverData->data_NMS->set = malloc(sizeof(positive_orthant));
data_NMS = solverData->data_NMS;
functions = solverData->lsa_functions;
/* for use in NMS; only those 3 functions are called */
init_lsa_functions(functions, &FB_compute_F_ncp, &ncp_FB);
functions->compute_H = &FB_compute_H_ncp;
set_set_id(data_NMS->set, SICONOS_SET_POSITIVE_ORTHANT);
/* fill ls_data */
data_NMS->ls_data->compute_F = functions->compute_F;
data_NMS->ls_data->compute_F_merit = functions->compute_F_merit;
data_NMS->ls_data->z = NULL; /* XXX to check -- xhub */
data_NMS->ls_data->zc = NMS_get_generic_workV(data_NMS->workspace, n);
data_NMS->ls_data->F = NMS_get_F(data_NMS->workspace, n);
data_NMS->ls_data->F_merit = NMS_get_F_merit(data_NMS->workspace, n);
data_NMS->ls_data->desc_dir = NMS_get_dir(data_NMS->workspace, n);
/** \todo this value should be settable by the user with a default value*/
data_NMS->ls_data->alpha_min = fmin(data_NMS->alpha_min_watchdog, data_NMS->alpha_min_pgrad);
data_NMS->ls_data->data = (void*)problem;
data_NMS->ls_data->set = data_NMS->set;
data_NMS->ls_data->sigma = options->dparam[SICONOS_DPARAM_NMS_SIGMA];
/* data_NMS->ls_data->searchtype is set in the NMS code */
}
else
{
pathsearch_data* solverData = (pathsearch_data*) options->solverData;
data_NMS = solverData->data_NMS;
functions = solverData->lsa_functions;
}
/* initial value for ref_merit */
problem->compute_F(problem->env, n, z, F);
functions->compute_F_merit(problem, z, F, data_NMS->ls_data->F_merit);
data_NMS->ref_merit = .5 * cblas_ddot(n, data_NMS->ls_data->F_merit, 1, data_NMS->ls_data->F_merit, 1);
data_NMS->merit_bestpoint = data_NMS->ref_merit;
cblas_dcopy(n, z, 1, NMS_checkpoint_0(data_NMS, n), 1);
cblas_dcopy(n, z, 1, NMS_checkpoint_T(data_NMS, n), 1);
cblas_dcopy(n, z, 1, NMS_bestpoint(data_NMS, n), 1);
/* -------------------- end init ---------------------------*/
int nms_failed = 0;
double err = 10*nn_tol;
/* to check the solution */
LinearComplementarityProblem lcp_subproblem_check;
int check_lcp_solution = 1; /* XXX add config for that */
double normal_norm2_newton_point;
/* F is already computed here at z */
while ((err > nn_tol) && (nbiter < itermax) && !nms_failed)
{
int force_watchdog_step = 0;
int force_d_step_merit_check = 0;
double check_ratio = 0.0;
nbiter++;
/* update M, q and r */
/* First find x */
ncp_pathsearch_compute_x_from_z(n, z, F, x);
pos_part(n, x, x_plus); /* update x_plus */
ncp_pathsearch_update_lcp_data(problem, &lcp_subproblem, n, x_plus, x, r);
if (check_lcp_solution)
{
lcp_subproblem_check.size = n;
lcp_subproblem_check.M = problem->nabla_F;
lcp_subproblem_check.q = lcp_subproblem.q;
//cblas_dcopy(n, x, 1, lcp_subproblem_check.q , 1);
//prodNumericsMatrix(n, n, -1.0, problem->nabla_F, x_plus, 0.0, lcp_subproblem.q);
}
double norm_r2 = cblas_ddot(n, r, 1, r, 1);
if (norm_r2 < DBL_EPSILON*DBL_EPSILON) /* ||r|| < 1e-15 */
{
DEBUG_PRINTF("ncp_pathsearch :: ||r|| = %e < %e; path search procedure was successful!\n", norm_r2, DBL_EPSILON*DBL_EPSILON);
(*info) = 0;
ncp_compute_error(n, z, F, nn_tol, &err); /* XXX F should be up-to-date, we should check only CC*/
break;
}
/* end update M, q and r */
lcp_pivot_covering_vector(&lcp_subproblem, x_plus, x, info, options->internalSolvers, r);
switch (*info)
{
case LCP_PIVOT_SUCCESS:
DEBUG_PRINT("ncp_pathsearch :: path search procedure was successful!\n");
if (check_lcp_solution)
{
double err_lcp = 0.0;
cblas_daxpy(n, 1.0, r, 1, lcp_subproblem_check.q, 1);
lcp_compute_error(&lcp_subproblem_check, x_plus, x, 1e-14, &err_lcp);
double local_tol = fmax(1e-14, DBL_EPSILON*sqrt(norm_r2));
printf("ncp_pathsearch :: lcp solved with error = %e; local_tol = %e\n", err_lcp, local_tol);
//assert(err_lcp < local_tol && "ncp_pathsearch :: lcp solved with very bad precision");
if (err_lcp > local_tol)
{
printf("ncp_pathsearch :: lcp solved with very bad precision\n");
NM_display(lcp_subproblem.M);
printf("z r q x_plus\n");
for (unsigned i = 0; i < n; ++i) printf("%e %e %e %e\n", z[i], r[i], lcp_subproblem.q[i], x_plus[i]);
options->internalSolvers->iparam[SICONOS_IPARAM_PIVOT_RULE] = 0;
lcp_pivot(&lcp_subproblem, x_plus, x, info, options->internalSolvers);
options->internalSolvers->iparam[SICONOS_IPARAM_PIVOT_RULE] = SICONOS_LCP_PIVOT_PATHSEARCH;
lcp_compute_error(&lcp_subproblem_check, x_plus, x, 1e-14, &err_lcp);
printf("ncp_pathsearch :: lcp resolved with error = %e; local_tol = %e\n", err_lcp, local_tol);
}
/* XXX missing recompute x ?*/
/* recompute the normal norm */
problem->compute_F(problem->env, n, x_plus, r);
cblas_daxpy(n, -1.0, x, 1, r, 1);
normal_norm2_newton_point = cblas_ddot(n, r, 1, r, 1);
if (normal_norm2_newton_point > norm_r2)
{
printf("ncp_pathsearch :: lcp successfully solved, but the norm of the normal map increased! %e > %e\n", normal_norm2_newton_point, norm_r2);
//assert(normal_norm2_newton_point <= norm_r2);
}
else
{
printf("ncp_pathsearch :: lcp successfully solved, norm of the normal map decreased! %e < %e\n", normal_norm2_newton_point, norm_r2);
//check_ratio = norm_r2/normal_norm2_newton_point;
}
if (50*normal_norm2_newton_point < norm_r2)
{
force_d_step_merit_check = 1;
}
else if (10*normal_norm2_newton_point < norm_r2)
{
// check_ratio = sqrt(norm_r2/normal_norm2_newton_point);
}
}
break;
case LCP_PIVOT_RAY_TERMINATION:
DEBUG_PRINT("ncp_pathsearch :: ray termination, let's fastened your seat belt!\n");
break;
case LCP_PATHSEARCH_LEAVING_T:
DEBUG_PRINT("ncp_pathsearch :: leaving t, fastened your seat belt!\n");
DEBUG_PRINTF("ncp_pathsearch :: max t value = %e\n", options->internalSolvers->dparam[2]); /* XXX fix 2 */
/* try to retry solving the problem */
/* XXX keep or not ? */
/* recompute the normal norm */
problem->compute_F(problem->env, n, x_plus, r);
cblas_daxpy(n, -1.0, x, 1, r, 1);
normal_norm2_newton_point = cblas_ddot(n, r, 1, r, 1);
if (normal_norm2_newton_point > norm_r2)
{
printf("ncp_pathsearch :: lcp successfully solved, but the norm of the normal map increased! %e > %e\n", normal_norm2_newton_point, norm_r2);
//assert(normal_norm2_newton_point <= norm_r2);
}
else
{
printf("ncp_pathsearch :: lcp successfully solved, norm of the normal map decreased! %e < %e\n", normal_norm2_newton_point, norm_r2);
check_ratio = 5.0*norm_r2/normal_norm2_newton_point;
}
if (options->internalSolvers->dparam[2] > 1e-5) break;
memset(x_plus, 0, sizeof(double) * n);
problem->compute_F(problem->env, n, x_plus, r);
ncp_pathsearch_compute_x_from_z(n, x_plus, r, x);
ncp_pathsearch_update_lcp_data(problem, &lcp_subproblem, n, x_plus, x, r);
lcp_pivot_covering_vector(&lcp_subproblem, x_plus, x, info, options->internalSolvers, r);
if (*info == LCP_PIVOT_SUCCESS)
{
DEBUG_PRINT("ncp_pathsearch :: Lemke start worked !\n");
double err_lcp = 0.0;
cblas_daxpy(n, 1.0, r, 1, lcp_subproblem_check.q, 1);
lcp_compute_error(&lcp_subproblem_check, x_plus, x, 1e-14, &err_lcp);
double local_tol = fmax(1e-14, DBL_EPSILON*sqrt(norm_r2));
printf("ncp_pathsearch :: lcp solved with error = %e; local_tol = %e\n", err_lcp, local_tol);
assert(err_lcp < local_tol);
}
else
{
NM_display(lcp_subproblem.M);
printf("z r q x_plus\n");
for (unsigned i = 0; i < n; ++i) printf("%e %e %e %e\n", z[i], r[i], lcp_subproblem.q[i], x_plus[i]);
DEBUG_PRINT("ncp_pathsearch :: Lemke start did not succeeded !\n");
lcp_pivot_diagnose_info(*info);
if (*info == LCP_PATHSEARCH_LEAVING_T)
{
DEBUG_PRINTF("ncp_pathsearch :: max t value after Lemke start = %e\n", options->internalSolvers->dparam[2]);
}
options->internalSolvers->iparam[SICONOS_IPARAM_PIVOT_RULE] = 0;
lcp_pivot(&lcp_subproblem, x_plus, x, info, options->internalSolvers);
options->internalSolvers->iparam[SICONOS_IPARAM_PIVOT_RULE] = SICONOS_LCP_PIVOT_PATHSEARCH;
double err_lcp = 0.0;
lcp_compute_error(&lcp_subproblem, x_plus, x, 1e-14, &err_lcp);
printf("ncp_pathsearch :: lemke start resolved with info = %d; error = %e\n", *info, err_lcp);
printf("x_plus x_minus\n");
for (unsigned i = 0; i < n; ++i) printf("%e %e\n", x_plus[i], x[i]);
/* recompute the normal norm */
problem->compute_F(problem->env, n, x_plus, r);
cblas_daxpy(n, -1.0, x, 1, r, 1);
double normal_norm2_newton_point = cblas_ddot(n, r, 1, r, 1);
if (normal_norm2_newton_point > norm_r2)
{
printf("ncp_pathsearch :: lcp successfully solved, but the norm of the normal map increased! %e > %e\n", normal_norm2_newton_point, norm_r2);
//assert(normal_norm2_newton_point <= norm_r2);
}
else
{
printf("ncp_pathsearch :: lcp successfully solved, norm of the normal map decreased! %.*e < %.*e\n", DECIMAL_DIG, normal_norm2_newton_point, DECIMAL_DIG, norm_r2);
}
if (100*normal_norm2_newton_point < norm_r2)
{
force_d_step_merit_check = 1;
}
}
break;
case LCP_PIVOT_NUL:
printf("ncp_pathsearch :: kaboom, kaboom still more work needs to be done\n");
lcp_pivot_diagnose_info(*info);
// exit(EXIT_FAILURE);
force_watchdog_step = 1;
break;
case LCP_PATHSEARCH_NON_ENTERING_T:
DEBUG_PRINT("ncp_pathsearch :: non entering t, something is wrong here. Fix the f****** code!\n");
assert(0 && "ncp_pathsearch :: non entering t, something is wrong here\n");
force_watchdog_step = 1;
break;
default:
printf("ncp_pathsearch :: unknown code returned by the path search\n");
exit(EXIT_FAILURE);
}
nms_failed = NMS(data_NMS, problem, functions, z, x_plus, force_watchdog_step, force_d_step_merit_check, check_ratio);
/* at this point z has been updated */
/* recompute the normal norm */
problem->compute_F(problem->env, n, z, F);
functions->compute_F_merit(problem, z, F, data_NMS->ls_data->F_merit);
/* XXX is this correct ? */
merit_norm = .5 * cblas_ddot(n, data_NMS->ls_data->F_merit, 1, data_NMS->ls_data->F_merit, 1);
ncp_compute_error(n, z, F, nn_tol, &err); /* XXX F should be up-to-date, we should check only CC*/
DEBUG_PRINTF("ncp_pathsearch :: iter = %d, ncp_error = %e; merit_norm^2 = %e\n", nbiter, err, merit_norm);
}
options->iparam[1] = nbiter;
options->dparam[1] = err;
if (nbiter == itermax)
{
*info = 1;
}
else if (nms_failed)
{
*info = 2;
}
else
{
*info = 0;
}
DEBUG_PRINTF("ncp_pathsearch procedure finished :: info = %d; iter = %d; ncp_error = %e; merit_norm^2 = %e\n", *info, nbiter, err, merit_norm);
if (!preAlloc)
{
freeNumericsMatrix(problem->nabla_F);
free(problem->nabla_F);
problem->nabla_F = NULL;
free(options->dWork);
options->dWork = NULL;
solver_options_delete(options->internalSolvers);
free(options->internalSolvers);
options->internalSolvers = NULL;
free_NMS_data(data_NMS);
free(functions);
free(options->solverData);
options->solverData = NULL;
}
}
