Date: 2016-07-24T17:15:16+00:00

Actual source code: neldermead.c
petsc-3.7.3 2016-07-24
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      1: #include <../src/tao/unconstrained/impls/neldermead/neldermead.h>
      2: #include <petscvec.h>

      4: static PetscErrorCode NelderMeadSort(TAO_NelderMead *nm);
      5: static PetscErrorCode NelderMeadReplace(TAO_NelderMead *nm, PetscInt index, Vec Xmu, PetscReal f);
      6: /* ---------------------------------------------------------- */
      9: static PetscErrorCode TaoSetUp_NM(Tao tao)
     10: {
     12:   TAO_NelderMead *nm = (TAO_NelderMead *)tao->data;
     13:   PetscInt       n;

     16:   VecGetSize(tao->solution,&n);
     17:   nm->N = n;
     18:   nm->oneOverN = 1.0/n;
     19:   VecDuplicateVecs(tao->solution,nm->N+1,&nm->simplex);
     20:   PetscMalloc1(nm->N+1,&nm->f_values);
     21:   PetscMalloc1(nm->N+1,&nm->indices);
     22:   VecDuplicate(tao->solution,&nm->Xbar);
     23:   VecDuplicate(tao->solution,&nm->Xmur);
     24:   VecDuplicate(tao->solution,&nm->Xmue);
     25:   VecDuplicate(tao->solution,&nm->Xmuc);

     27:   tao->gradient=0;
     28:   tao->step=0;
     29:   return(0);
     30: }

     32: /* ---------------------------------------------------------- */
     35: PetscErrorCode TaoDestroy_NM(Tao tao)
     36: {
     37:   TAO_NelderMead *nm = (TAO_NelderMead*)tao->data;

     41:   if (tao->setupcalled) {
     42:     VecDestroyVecs(nm->N+1,&nm->simplex);
     43:     VecDestroy(&nm->Xmuc);
     44:     VecDestroy(&nm->Xmue);
     45:     VecDestroy(&nm->Xmur);
     46:     VecDestroy(&nm->Xbar);
     47:   }
     48:   PetscFree(nm->indices);
     49:   PetscFree(nm->f_values);
     50:   PetscFree(tao->data);
     51:   tao->data = 0;
     52:   return(0);
     53: }

     55: /*------------------------------------------------------------*/
     58: PetscErrorCode TaoSetFromOptions_NM(PetscOptionItems *PetscOptionsObject,Tao tao)
     59: {
     60:   TAO_NelderMead *nm = (TAO_NelderMead*)tao->data;

     64:   PetscOptionsHead(PetscOptionsObject,"Nelder-Mead options");
     65:   PetscOptionsReal("-tao_nm_lamda","initial step length","",nm->lamda,&nm->lamda,NULL);
     66:   PetscOptionsReal("-tao_nm_mu","mu","",nm->mu_oc,&nm->mu_oc,NULL);
     67:   nm->mu_ic = -nm->mu_oc;
     68:   nm->mu_r = nm->mu_oc*2.0;
     69:   nm->mu_e = nm->mu_oc*4.0;
     70:   PetscOptionsTail();
     71:   return(0);
     72: }

     74: /*------------------------------------------------------------*/
     77: PetscErrorCode TaoView_NM(Tao tao,PetscViewer viewer)
     78: {
     79:   TAO_NelderMead *nm = (TAO_NelderMead*)tao->data;
     80:   PetscBool      isascii;

     84:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii);
     85:   if (isascii) {
     86:     PetscViewerASCIIPushTab(viewer);
     87:     PetscViewerASCIIPrintf(viewer,"expansions: %D\n",nm->nexpand);
     88:     PetscViewerASCIIPrintf(viewer,"reflections: %D\n",nm->nreflect);
     89:     PetscViewerASCIIPrintf(viewer,"inside contractions: %D\n",nm->nincontract);
     90:     PetscViewerASCIIPrintf(viewer,"outside contractionss: %D\n",nm->noutcontract);
     91:     PetscViewerASCIIPrintf(viewer,"Shrink steps: %D\n",nm->nshrink);
     92:     PetscViewerASCIIPopTab(viewer);
     93:   }
     94:   return(0);
     95: }

     97: /*------------------------------------------------------------*/
    100: PetscErrorCode TaoSolve_NM(Tao tao)
    101: {
    102:   PetscErrorCode     ierr;
    103:   TAO_NelderMead     *nm = (TAO_NelderMead*)tao->data;
    104:   TaoConvergedReason reason;
    105:   PetscReal          *x;
    106:   PetscInt           i;
    107:   Vec                Xmur=nm->Xmur, Xmue=nm->Xmue, Xmuc=nm->Xmuc, Xbar=nm->Xbar;
    108:   PetscReal          fr,fe,fc;
    109:   PetscInt           shrink;
    110:   PetscInt           low,high;

    113:   nm->nshrink =      0;
    114:   nm->nreflect =     0;
    115:   nm->nincontract =  0;
    116:   nm->noutcontract = 0;
    117:   nm->nexpand =      0;

    119:   if (tao->XL || tao->XU || tao->ops->computebounds) {
    120:     PetscPrintf(((PetscObject)tao)->comm,"WARNING: Variable bounds have been set but will be ignored by NelderMead algorithm\n");
    121:   }

    123:   VecCopy(tao->solution,nm->simplex[0]);
    124:   TaoComputeObjective(tao,nm->simplex[0],&nm->f_values[0]);
    125:   nm->indices[0]=0;
    126:   for (i=1;i<nm->N+1;i++){
    127:     VecCopy(tao->solution,nm->simplex[i]);
    128:     VecGetOwnershipRange(nm->simplex[i],&low,&high);
    129:     if (i-1 >= low && i-1 < high) {
    130:       VecGetArray(nm->simplex[i],&x);
    131:       x[i-1-low] += nm->lamda;
    132:       VecRestoreArray(nm->simplex[i],&x);
    133:     }

    135:     TaoComputeObjective(tao,nm->simplex[i],&nm->f_values[i]);
    136:     nm->indices[i] = i;
    137:   }

    139:   /*  Xbar  = (Sum of all simplex vectors - worst vector)/N */
    140:   NelderMeadSort(nm);
    141:   VecSet(Xbar,0.0);
    142:   for (i=0;i<nm->N;i++) {
    143:     VecAXPY(Xbar,1.0,nm->simplex[nm->indices[i]]);
    144:   }
    145:   VecScale(Xbar,nm->oneOverN);
    146:   reason = TAO_CONTINUE_ITERATING;
    147:   while (1) {
    148:     shrink = 0;
    149:     VecCopy(nm->simplex[nm->indices[0]],tao->solution);
    150:     TaoMonitor(tao,tao->niter++,nm->f_values[nm->indices[0]],nm->f_values[nm->indices[nm->N]]-nm->f_values[nm->indices[0]],0.0,1.0,&reason);
    151:     if (reason != TAO_CONTINUE_ITERATING) break;

    153:     /* x(mu) = (1 + mu)Xbar - mu*X_N+1 */
    154:     VecAXPBYPCZ(Xmur,1+nm->mu_r,-nm->mu_r,0,Xbar,nm->simplex[nm->indices[nm->N]]);
    155:     TaoComputeObjective(tao,Xmur,&fr);

    157:     if (nm->f_values[nm->indices[0]] <= fr && fr < nm->f_values[nm->indices[nm->N-1]]) {
    158:       /*  reflect */
    159:       nm->nreflect++;
    160:       PetscInfo(0,"Reflect\n");
    161:       NelderMeadReplace(nm,nm->indices[nm->N],Xmur,fr);
    162:     } else if (fr < nm->f_values[nm->indices[0]]) {
    163:       /*  expand */
    164:       nm->nexpand++;
    165:       PetscInfo(0,"Expand\n");
    166:       VecAXPBYPCZ(Xmue,1+nm->mu_e,-nm->mu_e,0,Xbar,nm->simplex[nm->indices[nm->N]]);
    167:       TaoComputeObjective(tao,Xmue,&fe);
    168:       if (fe < fr) {
    169:         NelderMeadReplace(nm,nm->indices[nm->N],Xmue,fe);
    170:       } else {
    171:         NelderMeadReplace(nm,nm->indices[nm->N],Xmur,fr);
    172:       }
    173:     } else if (nm->f_values[nm->indices[nm->N-1]] <= fr && fr < nm->f_values[nm->indices[nm->N]]) {
    174:       /* outside contraction */
    175:       nm->noutcontract++;
    176:       PetscInfo(0,"Outside Contraction\n");
    177:       VecAXPBYPCZ(Xmuc,1+nm->mu_oc,-nm->mu_oc,0,Xbar,nm->simplex[nm->indices[nm->N]]);

    179:       TaoComputeObjective(tao,Xmuc,&fc);
    180:       if (fc <= fr) {
    181:         NelderMeadReplace(nm,nm->indices[nm->N],Xmuc,fc);
    182:       } else shrink=1;
    183:     } else {
    184:       /* inside contraction */
    185:       nm->nincontract++;
    186:       PetscInfo(0,"Inside Contraction\n");
    187:       VecAXPBYPCZ(Xmuc,1+nm->mu_ic,-nm->mu_ic,0,Xbar,nm->simplex[nm->indices[nm->N]]);
    188:       TaoComputeObjective(tao,Xmuc,&fc);
    189:       if (fc < nm->f_values[nm->indices[nm->N]]) {
    190:         NelderMeadReplace(nm,nm->indices[nm->N],Xmuc,fc);
    191:       } else shrink = 1;
    192:     }

    194:     if (shrink) {
    195:       nm->nshrink++;
    196:       PetscInfo(0,"Shrink\n");

    198:       for (i=1;i<nm->N+1;i++) {
    199:         VecAXPBY(nm->simplex[nm->indices[i]],1.5,-0.5,nm->simplex[nm->indices[0]]);
    200:         TaoComputeObjective(tao,nm->simplex[nm->indices[i]], &nm->f_values[nm->indices[i]]);
    201:       }
    202:       VecAXPBY(Xbar,1.5*nm->oneOverN,-0.5,nm->simplex[nm->indices[0]]);

    204:       /*  Add last vector's fraction of average */
    205:       VecAXPY(Xbar,nm->oneOverN,nm->simplex[nm->indices[nm->N]]);
    206:       NelderMeadSort(nm);
    207:       /*  Subtract new last vector from average */
    208:       VecAXPY(Xbar,-nm->oneOverN,nm->simplex[nm->indices[nm->N]]);
    209:     }
    210:   }
    211:   return(0);
    212: }

    214: /* ---------------------------------------------------------- */
    215: /*MC
    216:  TAONM - Nelder-Mead solver for derivative free, unconstrained minimization

    218:  Options Database Keys:
    219: + -tao_nm_lamda - initial step length
    220: . -tao_nm_mu - expansion/contraction factor

    222:  Level: beginner
    223: M*/

    227: PETSC_EXTERN PetscErrorCode TaoCreate_NM(Tao tao)
    228: {
    229:   TAO_NelderMead *nm;

    233:   PetscNewLog(tao,&nm);
    234:   tao->data = (void*)nm;

    236:   tao->ops->setup = TaoSetUp_NM;
    237:   tao->ops->solve = TaoSolve_NM;
    238:   tao->ops->view = TaoView_NM;
    239:   tao->ops->setfromoptions = TaoSetFromOptions_NM;
    240:   tao->ops->destroy = TaoDestroy_NM;

    242:   /* Override default settings (unless already changed) */
    243:   if (!tao->max_it_changed) tao->max_it = 2000;
    244:   if (!tao->max_funcs_changed) tao->max_funcs = 4000;

    246:   nm->simplex = 0;
    247:   nm->lamda = 1;

    249:   nm->mu_ic = -0.5;
    250:   nm->mu_oc = 0.5;
    251:   nm->mu_r = 1.0;
    252:   nm->mu_e = 2.0;

    254:   return(0);
    255: }

    258: /*------------------------------------------------------------*/
    261: PetscErrorCode NelderMeadSort(TAO_NelderMead *nm)
    262: {
    263:   PetscReal *values = nm->f_values;
    264:   PetscInt  *indices = nm->indices;
    265:   PetscInt  dim = nm->N+1;
    266:   PetscInt  i,j,index;
    267:   PetscReal val;

    270:   for (i=1;i<dim;i++) {
    271:     index = indices[i];
    272:     val = values[index];
    273:     for (j=i-1; j>=0 && values[indices[j]] > val; j--) {
    274:       indices[j+1] = indices[j];
    275:     }
    276:     indices[j+1] = index;
    277:   }
    278:   return(0);
    279: }

    282: /*------------------------------------------------------------*/
    285: PetscErrorCode NelderMeadReplace(TAO_NelderMead *nm, PetscInt index, Vec Xmu, PetscReal f)
    286: {

    290:   /*  Add new vector's fraction of average */
    291:   VecAXPY(nm->Xbar,nm->oneOverN,Xmu);
    292:   VecCopy(Xmu,nm->simplex[index]);
    293:   nm->f_values[index] = f;

    295:   NelderMeadSort(nm);

    297:   /*  Subtract last vector from average */
    298:   VecAXPY(nm->Xbar,-nm->oneOverN,nm->simplex[nm->indices[nm->N]]);
    299:   return(0);
    300: }