Пример #1
0
void ncp_newton_FBLSA(NonlinearComplementarityProblem* problem, double *z, double* F, int *info, SolverOptions* options)
{
    functions_LSA functions_FBLSA_ncp;
    init_lsa_functions(&functions_FBLSA_ncp, &FB_compute_F_ncp, &ncp_FB);
    functions_FBLSA_ncp.compute_H = &FB_compute_H_ncp;
    functions_FBLSA_ncp.compute_error = &FB_compute_error_ncp;

    set_lsa_params_data(options, problem->nabla_F);
    newton_LSA(problem->n, z, F, info, (void *)problem, options, &functions_FBLSA_ncp);
}
Пример #2
0
void mcp_newton_FBLSA(MixedComplementarityProblem2* problem, double *z, double* Fmcp, int *info , SolverOptions* options)
{
  functions_LSA functions_FBLSA_mcp;
  init_lsa_functions(&functions_FBLSA_mcp, &FB_compute_F_mcp, &mcp_FB);
  functions_FBLSA_mcp.compute_H = &FB_compute_H_mcp;
  functions_FBLSA_mcp.compute_error = &FB_compute_error_mcp;

  set_lsa_params_data(options, problem->nabla_Fmcp);
  newton_LSA(problem->n1 + problem->n2, z, Fmcp, info, (void *)problem, options, &functions_FBLSA_mcp);
}
Пример #3
0
void mlcp_newton_FB(MixedLinearComplementarityProblem* problem, double *z, double *w, int *info , SolverOptions* options)
{
  functions_LSA functions_FBLSA_mlcp;
  init_lsa_functions(&functions_FBLSA_mlcp, &FB_compute_F_mlcp, (compute_F_merit_ptr)&mlcp_FB);
  functions_FBLSA_mlcp.compute_H = &FB_compute_H_mlcp;
  functions_FBLSA_mlcp.compute_error = &FB_compute_error_mlcp;

  set_lsa_params_data(options, problem->M);
  newton_LSA(problem->n + problem->m, z, w, info, (void *)problem, options, &functions_FBLSA_mlcp);
}
Пример #4
0
void lcp_newton_minFB(LinearComplementarityProblem* problem, double *z, double *w, int *info , SolverOptions* options)
{
  functions_LSA functions_minFBLSA_lcp;
  init_lsa_functions(&functions_minFBLSA_lcp, &FB_compute_F_lcp, &lcp_FB);
  functions_minFBLSA_lcp.compute_H = &FB_compute_H_lcp;
  functions_minFBLSA_lcp.compute_error = &FB_compute_error_lcp;
  functions_minFBLSA_lcp.compute_RHS_desc = &lcp_min;
  functions_minFBLSA_lcp.compute_H_desc = &min_compute_H_lcp;

  set_lsa_params_data(options, problem->M);
  newton_LSA(problem->size, z, w, info, (void *)problem, options, &functions_minFBLSA_lcp);
}
Пример #5
0
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;
  }
}
void fc3d_nonsmooth_Newton_AlartCurnier2(
  FrictionContactProblem* problem,
  double *reaction,
  double *velocity,
  int *info,
  SolverOptions *options)
{
  assert(problem);
  assert(reaction);
  assert(velocity);
  assert(info);
  assert(options);

  assert(problem->dimension == 3);

  assert(options->iparam);
  assert(options->dparam);

  assert(problem->q);
  assert(problem->mu);
  assert(problem->M);

  assert(!options->iparam[4]); // only host

  AlartCurnierParams acparams;

  switch (options->iparam[10])
  {
  case 0:
  {
    acparams.computeACFun3x3 = &computeAlartCurnierSTD;
    break;
  }
  case 1:
  {
    acparams.computeACFun3x3 = &computeAlartCurnierJeanMoreau;
    break;
  };
  case 2:
  {
    acparams.computeACFun3x3 = &fc3d_AlartCurnierFunctionGenerated;
    break;
  }
  case 3:
  {
    acparams.computeACFun3x3 = &fc3d_AlartCurnierJeanMoreauFunctionGenerated;
    break;
  }
  }

  fc3d_nonsmooth_Newton_solvers equation;

  equation.problem = problem;
  equation.data = (void *) &acparams;
  equation.function = &nonsmoothEqnAlartCurnierFun;

  /*************************************************************************
   * START NEW STUFF
   */
  size_t problemSize = problem->M->size0;
  size_t _3problemSize = problemSize + problemSize + problemSize;
  FC3D_Newton_data opaque_data;
  opaque_data.problem = problem;
  opaque_data.equation = &equation;
  opaque_data.rho = (double*)calloc(problemSize, sizeof(double));
  for (size_t i = 0; i < problemSize; ++i) opaque_data.rho[i] = 1.;
  opaque_data.Ax = (double*)calloc(_3problemSize, sizeof(double));
  opaque_data.Bx = (double*)calloc(_3problemSize, sizeof(double));
  opaque_data.normq = cblas_dnrm2(problemSize, problem->q, 1);
  opaque_data.AwpB_data_computed = false;

  functions_LSA functions_AC;
  init_lsa_functions(&functions_AC, &FC3D_compute_F, &FC3D_compute_F_merit);
  functions_AC.compute_H = &FC3D_compute_AWpB;
  functions_AC.compute_error = &FC3D_compute_error;
  functions_AC.get_set_from_problem_data = NULL;

  set_lsa_params_data(options, problem->M);
  newton_LSA_param* params = (newton_LSA_param*) options->solverParameters;
  params->check_dir_quality = false;

  options->iparam[SICONOS_IPARAM_LSA_SEARCH_CRITERION] = SICONOS_LSA_GOLDSTEIN;
//  options->iparam[SICONOS_IPARAM_LSA_SEARCH_CRITERION] = SICONOS_LSA_ARMIJO;
  /*************************************************************************
   * END NEW STUFF
   */

  if(options->iparam[SICONOS_FRICTION_3D_NSN_HYBRID_STRATEGY] ==  SICONOS_FRICTION_3D_NSN_HYBRID_STRATEGY_VI_EG_NSN)
  {
    SolverOptions * options_vi_eg =(SolverOptions *)malloc(sizeof(SolverOptions));
    fc3d_VI_ExtraGradient_setDefaultSolverOptions(options_vi_eg);
    options_vi_eg->iparam[0] = 50;
    options_vi_eg->dparam[0] = sqrt(options->dparam[0]);
    options_vi_eg->iparam[SICONOS_VI_IPARAM_ERROR_EVALUATION] = SICONOS_VI_ERROR_EVALUATION_LIGHT;
    fc3d_VI_ExtraGradient(problem, reaction , velocity , info , options_vi_eg);
    solver_options_delete(options_vi_eg);
    free(options_vi_eg);

    newton_LSA(problemSize, reaction, velocity, info, (void *)&opaque_data, options, &functions_AC);
  }
  else if (options->iparam[SICONOS_FRICTION_3D_NSN_HYBRID_STRATEGY] ==  SICONOS_FRICTION_3D_NSN_HYBRID_STRATEGY_NO)
  {
    newton_LSA(problemSize, reaction, velocity, info, (void *)&opaque_data, options, &functions_AC);
  }
  else
  {
    numerics_error("fc3d_nonsmooth_Newton_AlartCurnier","Unknown nsn hybrid solver");
  }

  free(opaque_data.rho);
  free(opaque_data.Ax);
  free(opaque_data.Bx);
}