1 2 #include <../src/snes/impls/vi/ss/vissimpl.h> /*I "petscsnes.h" I*/ 3 #include <../include/petsc-private/kspimpl.h> 4 #include <../include/petsc-private/matimpl.h> 5 #include <../include/petsc-private/dmimpl.h> 6 7 8 /* 9 SNESVIComputeMeritFunction - Evaluates the merit function for the mixed complementarity problem. 10 11 Input Parameter: 12 . phi - the semismooth function 13 14 Output Parameter: 15 . merit - the merit function 16 . phinorm - ||phi|| 17 18 Notes: 19 The merit function for the mixed complementarity problem is defined as 20 merit = 0.5*phi^T*phi 21 */ 22 #undef __FUNCT__ 23 #define __FUNCT__ "SNESVIComputeMeritFunction" 24 static PetscErrorCode SNESVIComputeMeritFunction(Vec phi, PetscReal* merit,PetscReal* phinorm) 25 { 26 PetscErrorCode ierr; 27 28 PetscFunctionBegin; 29 ierr = VecNormBegin(phi,NORM_2,phinorm);CHKERRQ(ierr); 30 ierr = VecNormEnd(phi,NORM_2,phinorm);CHKERRQ(ierr); 31 32 *merit = 0.5*(*phinorm)*(*phinorm); 33 PetscFunctionReturn(0); 34 } 35 36 PETSC_STATIC_INLINE PetscScalar Phi(PetscScalar a,PetscScalar b) 37 { 38 return a + b - PetscSqrtScalar(a*a + b*b); 39 } 40 41 PETSC_STATIC_INLINE PetscScalar DPhi(PetscScalar a,PetscScalar b) 42 { 43 if ((PetscAbsScalar(a) >= 1.e-6) || (PetscAbsScalar(b) >= 1.e-6)) return 1.0 - a/ PetscSqrtScalar(a*a + b*b); 44 else return .5; 45 } 46 47 /* 48 SNESVIComputeFunction - Reformulates a system of nonlinear equations in mixed complementarity form to a system of nonlinear equations in semismooth form. 49 50 Input Parameters: 51 . snes - the SNES context 52 . x - current iterate 53 . functx - user defined function context 54 55 Output Parameters: 56 . phi - Semismooth function 57 58 */ 59 #undef __FUNCT__ 60 #define __FUNCT__ "SNESVIComputeFunction" 61 static PetscErrorCode SNESVIComputeFunction(SNES snes,Vec X,Vec phi,void* functx) 62 { 63 PetscErrorCode ierr; 64 SNES_VISS *vi = (SNES_VISS*)snes->data; 65 Vec Xl = snes->xl,Xu = snes->xu,F = snes->vec_func; 66 PetscScalar *phi_arr,*x_arr,*f_arr,*l,*u; 67 PetscInt i,nlocal; 68 69 PetscFunctionBegin; 70 ierr = (*vi->computeuserfunction)(snes,X,F,functx);CHKERRQ(ierr); 71 ierr = VecGetLocalSize(X,&nlocal);CHKERRQ(ierr); 72 ierr = VecGetArray(X,&x_arr);CHKERRQ(ierr); 73 ierr = VecGetArray(F,&f_arr);CHKERRQ(ierr); 74 ierr = VecGetArray(Xl,&l);CHKERRQ(ierr); 75 ierr = VecGetArray(Xu,&u);CHKERRQ(ierr); 76 ierr = VecGetArray(phi,&phi_arr);CHKERRQ(ierr); 77 78 for (i=0;i < nlocal;i++) { 79 if ((PetscRealPart(l[i]) <= SNES_VI_NINF) && (PetscRealPart(u[i]) >= SNES_VI_INF)) { /* no constraints on variable */ 80 phi_arr[i] = f_arr[i]; 81 } else if (PetscRealPart(l[i]) <= SNES_VI_NINF) { /* upper bound on variable only */ 82 phi_arr[i] = -Phi(u[i] - x_arr[i],-f_arr[i]); 83 } else if (PetscRealPart(u[i]) >= SNES_VI_INF) { /* lower bound on variable only */ 84 phi_arr[i] = Phi(x_arr[i] - l[i],f_arr[i]); 85 } else if (l[i] == u[i]) { 86 phi_arr[i] = l[i] - x_arr[i]; 87 } else { /* both bounds on variable */ 88 phi_arr[i] = Phi(x_arr[i] - l[i],-Phi(u[i] - x_arr[i],-f_arr[i])); 89 } 90 } 91 92 ierr = VecRestoreArray(X,&x_arr);CHKERRQ(ierr); 93 ierr = VecRestoreArray(F,&f_arr);CHKERRQ(ierr); 94 ierr = VecRestoreArray(Xl,&l);CHKERRQ(ierr); 95 ierr = VecRestoreArray(Xu,&u);CHKERRQ(ierr); 96 ierr = VecRestoreArray(phi,&phi_arr);CHKERRQ(ierr); 97 PetscFunctionReturn(0); 98 } 99 100 /* 101 SNESVIComputeBsubdifferentialVectors - Computes the diagonal shift (Da) and row scaling (Db) vectors needed for the 102 the semismooth jacobian. 103 */ 104 #undef __FUNCT__ 105 #define __FUNCT__ "SNESVIComputeBsubdifferentialVectors" 106 PetscErrorCode SNESVIComputeBsubdifferentialVectors(SNES snes,Vec X,Vec F,Mat jac,Vec Da,Vec Db) 107 { 108 PetscErrorCode ierr; 109 PetscScalar *l,*u,*x,*f,*da,*db,da1,da2,db1,db2; 110 PetscInt i,nlocal; 111 112 PetscFunctionBegin; 113 114 ierr = VecGetArray(X,&x);CHKERRQ(ierr); 115 ierr = VecGetArray(F,&f);CHKERRQ(ierr); 116 ierr = VecGetArray(snes->xl,&l);CHKERRQ(ierr); 117 ierr = VecGetArray(snes->xu,&u);CHKERRQ(ierr); 118 ierr = VecGetArray(Da,&da);CHKERRQ(ierr); 119 ierr = VecGetArray(Db,&db);CHKERRQ(ierr); 120 ierr = VecGetLocalSize(X,&nlocal);CHKERRQ(ierr); 121 122 for (i=0;i< nlocal;i++) { 123 if ((PetscRealPart(l[i]) <= SNES_VI_NINF) && (PetscRealPart(u[i]) >= SNES_VI_INF)) {/* no constraints on variable */ 124 da[i] = 0; 125 db[i] = 1; 126 } else if (PetscRealPart(l[i]) <= SNES_VI_NINF) { /* upper bound on variable only */ 127 da[i] = DPhi(u[i] - x[i], -f[i]); 128 db[i] = DPhi(-f[i],u[i] - x[i]); 129 } else if (PetscRealPart(u[i]) >= SNES_VI_INF) { /* lower bound on variable only */ 130 da[i] = DPhi(x[i] - l[i], f[i]); 131 db[i] = DPhi(f[i],x[i] - l[i]); 132 } else if (l[i] == u[i]) { /* fixed variable */ 133 da[i] = 1; 134 db[i] = 0; 135 } else { /* upper and lower bounds on variable */ 136 da1 = DPhi(x[i] - l[i], -Phi(u[i] - x[i], -f[i])); 137 db1 = DPhi(-Phi(u[i] - x[i], -f[i]),x[i] - l[i]); 138 da2 = DPhi(u[i] - x[i], -f[i]); 139 db2 = DPhi(-f[i],u[i] - x[i]); 140 da[i] = da1 + db1*da2; 141 db[i] = db1*db2; 142 } 143 } 144 145 ierr = VecRestoreArray(X,&x);CHKERRQ(ierr); 146 ierr = VecRestoreArray(F,&f);CHKERRQ(ierr); 147 ierr = VecRestoreArray(snes->xl,&l);CHKERRQ(ierr); 148 ierr = VecRestoreArray(snes->xu,&u);CHKERRQ(ierr); 149 ierr = VecRestoreArray(Da,&da);CHKERRQ(ierr); 150 ierr = VecRestoreArray(Db,&db);CHKERRQ(ierr); 151 PetscFunctionReturn(0); 152 } 153 154 /* 155 SNESVIComputeJacobian - Computes the jacobian of the semismooth function.The Jacobian for the semismooth function is an element of the B-subdifferential of the Fischer-Burmeister function for complementarity problems. 156 157 Input Parameters: 158 . Da - Diagonal shift vector for the semismooth jacobian. 159 . Db - Row scaling vector for the semismooth jacobian. 160 161 Output Parameters: 162 . jac - semismooth jacobian 163 . jac_pre - optional preconditioning matrix 164 165 Notes: 166 The semismooth jacobian matrix is given by 167 jac = Da + Db*jacfun 168 where Db is the row scaling matrix stored as a vector, 169 Da is the diagonal perturbation matrix stored as a vector 170 and jacfun is the jacobian of the original nonlinear function. 171 */ 172 #undef __FUNCT__ 173 #define __FUNCT__ "SNESVIComputeJacobian" 174 PetscErrorCode SNESVIComputeJacobian(Mat jac, Mat jac_pre,Vec Da, Vec Db) 175 { 176 PetscErrorCode ierr; 177 178 /* Do row scaling and add diagonal perturbation */ 179 ierr = MatDiagonalScale(jac,Db,PETSC_NULL);CHKERRQ(ierr); 180 ierr = MatDiagonalSet(jac,Da,ADD_VALUES);CHKERRQ(ierr); 181 if (jac != jac_pre) { /* If jac and jac_pre are different */ 182 ierr = MatDiagonalScale(jac_pre,Db,PETSC_NULL); 183 ierr = MatDiagonalSet(jac_pre,Da,ADD_VALUES);CHKERRQ(ierr); 184 } 185 PetscFunctionReturn(0); 186 } 187 188 /* 189 SNESVIComputeMeritFunctionGradient - Computes the gradient of the merit function psi. 190 191 Input Parameters: 192 phi - semismooth function. 193 H - semismooth jacobian 194 195 Output Parameters: 196 dpsi - merit function gradient 197 198 Notes: 199 The merit function gradient is computed as follows 200 dpsi = H^T*phi 201 */ 202 #undef __FUNCT__ 203 #define __FUNCT__ "SNESVIComputeMeritFunctionGradient" 204 PetscErrorCode SNESVIComputeMeritFunctionGradient(Mat H, Vec phi, Vec dpsi) 205 { 206 PetscErrorCode ierr; 207 208 PetscFunctionBegin; 209 ierr = MatMultTranspose(H,phi,dpsi);CHKERRQ(ierr); 210 PetscFunctionReturn(0); 211 } 212 213 214 215 /* 216 SNESSolve_VISS - Solves the complementarity problem with a semismooth Newton 217 method using a line search. 218 219 Input Parameters: 220 . snes - the SNES context 221 222 Output Parameter: 223 . outits - number of iterations until termination 224 225 Application Interface Routine: SNESSolve() 226 227 Notes: 228 This implements essentially a semismooth Newton method with a 229 line search. The default line search does not do any line seach 230 but rather takes a full newton step. 231 */ 232 #undef __FUNCT__ 233 #define __FUNCT__ "SNESSolve_VISS" 234 PetscErrorCode SNESSolve_VISS(SNES snes) 235 { 236 SNES_VISS *vi = (SNES_VISS*)snes->data; 237 PetscErrorCode ierr; 238 PetscInt maxits,i,lits; 239 PetscBool lssucceed; 240 MatStructure flg = DIFFERENT_NONZERO_PATTERN; 241 PetscReal gnorm,xnorm=0,ynorm; 242 Vec Y,X,F; 243 KSPConvergedReason kspreason; 244 DM dm; 245 SNESDM sdm; 246 247 PetscFunctionBegin; 248 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 249 ierr = DMSNESGetContext(dm,&sdm);CHKERRQ(ierr); 250 vi->computeuserfunction = sdm->computefunction; 251 sdm->computefunction = SNESVIComputeFunction; 252 253 snes->numFailures = 0; 254 snes->numLinearSolveFailures = 0; 255 snes->reason = SNES_CONVERGED_ITERATING; 256 257 maxits = snes->max_its; /* maximum number of iterations */ 258 X = snes->vec_sol; /* solution vector */ 259 F = snes->vec_func; /* residual vector */ 260 Y = snes->work[0]; /* work vectors */ 261 262 ierr = PetscObjectTakeAccess(snes);CHKERRQ(ierr); 263 snes->iter = 0; 264 snes->norm = 0.0; 265 ierr = PetscObjectGrantAccess(snes);CHKERRQ(ierr); 266 267 ierr = SNESVIProjectOntoBounds(snes,X);CHKERRQ(ierr); 268 ierr = SNESComputeFunction(snes,X,vi->phi);CHKERRQ(ierr); 269 if (snes->domainerror) { 270 snes->reason = SNES_DIVERGED_FUNCTION_DOMAIN; 271 sdm->computefunction = vi->computeuserfunction; 272 PetscFunctionReturn(0); 273 } 274 /* Compute Merit function */ 275 ierr = SNESVIComputeMeritFunction(vi->phi,&vi->merit,&vi->phinorm);CHKERRQ(ierr); 276 277 ierr = VecNormBegin(X,NORM_2,&xnorm);CHKERRQ(ierr); /* xnorm <- ||x|| */ 278 ierr = VecNormEnd(X,NORM_2,&xnorm);CHKERRQ(ierr); 279 if (PetscIsInfOrNanReal(vi->merit)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FP,"User provided compute function generated a Not-a-Number"); 280 281 ierr = PetscObjectTakeAccess(snes);CHKERRQ(ierr); 282 snes->norm = vi->phinorm; 283 ierr = PetscObjectGrantAccess(snes);CHKERRQ(ierr); 284 SNESLogConvHistory(snes,vi->phinorm,0); 285 ierr = SNESMonitor(snes,0,vi->phinorm);CHKERRQ(ierr); 286 287 /* set parameter for default relative tolerance convergence test */ 288 snes->ttol = vi->phinorm*snes->rtol; 289 /* test convergence */ 290 ierr = (*snes->ops->converged)(snes,0,0.0,0.0,vi->phinorm,&snes->reason,snes->cnvP);CHKERRQ(ierr); 291 if (snes->reason) { 292 sdm->computefunction = vi->computeuserfunction; 293 PetscFunctionReturn(0); 294 } 295 296 for (i=0; i<maxits; i++) { 297 298 /* Call general purpose update function */ 299 if (snes->ops->update) { 300 ierr = (*snes->ops->update)(snes, snes->iter);CHKERRQ(ierr); 301 } 302 303 /* Solve J Y = Phi, where J is the semismooth jacobian */ 304 /* Get the nonlinear function jacobian */ 305 ierr = SNESComputeJacobian(snes,X,&snes->jacobian,&snes->jacobian_pre,&flg);CHKERRQ(ierr); 306 /* Get the diagonal shift and row scaling vectors */ 307 ierr = SNESVIComputeBsubdifferentialVectors(snes,X,F,snes->jacobian,vi->Da,vi->Db);CHKERRQ(ierr); 308 /* Compute the semismooth jacobian */ 309 ierr = SNESVIComputeJacobian(snes->jacobian,snes->jacobian_pre,vi->Da,vi->Db);CHKERRQ(ierr); 310 /* Compute the merit function gradient */ 311 ierr = SNESVIComputeMeritFunctionGradient(snes->jacobian,vi->phi,vi->dpsi);CHKERRQ(ierr); 312 ierr = KSPSetOperators(snes->ksp,snes->jacobian,snes->jacobian_pre,flg);CHKERRQ(ierr); 313 ierr = SNES_KSPSolve(snes,snes->ksp,vi->phi,Y);CHKERRQ(ierr); 314 ierr = KSPGetConvergedReason(snes->ksp,&kspreason);CHKERRQ(ierr); 315 316 if (kspreason < 0) { 317 if (++snes->numLinearSolveFailures >= snes->maxLinearSolveFailures) { 318 ierr = PetscInfo2(snes,"iter=%D, number linear solve failures %D greater than current SNES allowed, stopping solve\n",snes->iter,snes->numLinearSolveFailures);CHKERRQ(ierr); 319 snes->reason = SNES_DIVERGED_LINEAR_SOLVE; 320 break; 321 } 322 } 323 ierr = KSPGetIterationNumber(snes->ksp,&lits);CHKERRQ(ierr); 324 snes->linear_its += lits; 325 ierr = PetscInfo2(snes,"iter=%D, linear solve iterations=%D\n",snes->iter,lits);CHKERRQ(ierr); 326 /* 327 if (snes->ops->precheckstep) { 328 PetscBool changed_y = PETSC_FALSE; 329 ierr = (*snes->ops->precheckstep)(snes,X,Y,snes->precheck,&changed_y);CHKERRQ(ierr); 330 } 331 332 if (PetscLogPrintInfo){ 333 ierr = SNESVICheckResidual_Private(snes,snes->jacobian,F,Y,G,W);CHKERRQ(ierr); 334 } 335 */ 336 /* Compute a (scaled) negative update in the line search routine: 337 Y <- X - lambda*Y 338 and evaluate G = function(Y) (depends on the line search). 339 */ 340 ierr = VecCopy(Y,snes->vec_sol_update);CHKERRQ(ierr); 341 ynorm = 1; gnorm = vi->phinorm; 342 /* ierr = (*snes->ops->linesearch)(snes,snes->lsP,X,vi->phi,Y,vi->phinorm,xnorm,G,W,&ynorm,&gnorm,&lssucceed);CHKERRQ(ierr); */ 343 ierr = SNESLineSearchApply(snes->linesearch, X, vi->phi, &gnorm, Y);CHKERRQ(ierr); 344 ierr = SNESLineSearchGetNorms(snes->linesearch, &xnorm, &gnorm, &ynorm);CHKERRQ(ierr); 345 ierr = PetscInfo4(snes,"fnorm=%18.16e, gnorm=%18.16e, ynorm=%18.16e, lssucceed=%d\n",(double)vi->phinorm,(double)gnorm,(double)ynorm,(int)lssucceed);CHKERRQ(ierr); 346 if (snes->reason == SNES_DIVERGED_FUNCTION_COUNT) break; 347 if (snes->domainerror) { 348 snes->reason = SNES_DIVERGED_FUNCTION_DOMAIN; 349 sdm->computefunction = vi->computeuserfunction; 350 PetscFunctionReturn(0); 351 } 352 ierr = SNESLineSearchGetSuccess(snes->linesearch, &lssucceed);CHKERRQ(ierr); 353 if (!lssucceed) { 354 if (++snes->numFailures >= snes->maxFailures) { 355 PetscBool ismin; 356 snes->reason = SNES_DIVERGED_LINE_SEARCH; 357 ierr = SNESVICheckLocalMin_Private(snes,snes->jacobian,vi->phi,X,gnorm,&ismin);CHKERRQ(ierr); 358 if (ismin) snes->reason = SNES_DIVERGED_LOCAL_MIN; 359 break; 360 } 361 } 362 /* Update function and solution vectors */ 363 vi->phinorm = gnorm; 364 vi->merit = 0.5*vi->phinorm*vi->phinorm; 365 /* Monitor convergence */ 366 ierr = PetscObjectTakeAccess(snes);CHKERRQ(ierr); 367 snes->iter = i+1; 368 snes->norm = vi->phinorm; 369 ierr = PetscObjectGrantAccess(snes);CHKERRQ(ierr); 370 SNESLogConvHistory(snes,snes->norm,lits); 371 ierr = SNESMonitor(snes,snes->iter,snes->norm);CHKERRQ(ierr); 372 /* Test for convergence, xnorm = || X || */ 373 if (snes->ops->converged != SNESSkipConverged) { ierr = VecNorm(X,NORM_2,&xnorm);CHKERRQ(ierr); } 374 ierr = (*snes->ops->converged)(snes,snes->iter,xnorm,ynorm,vi->phinorm,&snes->reason,snes->cnvP);CHKERRQ(ierr); 375 if (snes->reason) break; 376 } 377 if (i == maxits) { 378 ierr = PetscInfo1(snes,"Maximum number of iterations has been reached: %D\n",maxits);CHKERRQ(ierr); 379 if(!snes->reason) snes->reason = SNES_DIVERGED_MAX_IT; 380 } 381 sdm->computefunction = vi->computeuserfunction; 382 PetscFunctionReturn(0); 383 } 384 385 /* -------------------------------------------------------------------------- */ 386 /* 387 SNESSetUp_VISS - Sets up the internal data structures for the later use 388 of the SNES nonlinear solver. 389 390 Input Parameter: 391 . snes - the SNES context 392 . x - the solution vector 393 394 Application Interface Routine: SNESSetUp() 395 396 Notes: 397 For basic use of the SNES solvers, the user need not explicitly call 398 SNESSetUp(), since these actions will automatically occur during 399 the call to SNESSolve(). 400 */ 401 #undef __FUNCT__ 402 #define __FUNCT__ "SNESSetUp_VISS" 403 PetscErrorCode SNESSetUp_VISS(SNES snes) 404 { 405 PetscErrorCode ierr; 406 SNES_VISS *vi = (SNES_VISS*) snes->data; 407 408 PetscFunctionBegin; 409 ierr = SNESSetUp_VI(snes);CHKERRQ(ierr); 410 ierr = VecDuplicate(snes->vec_sol, &vi->dpsi);CHKERRQ(ierr); 411 ierr = VecDuplicate(snes->vec_sol, &vi->phi);CHKERRQ(ierr); 412 ierr = VecDuplicate(snes->vec_sol, &vi->Da);CHKERRQ(ierr); 413 ierr = VecDuplicate(snes->vec_sol, &vi->Db);CHKERRQ(ierr); 414 ierr = VecDuplicate(snes->vec_sol, &vi->z);CHKERRQ(ierr); 415 ierr = VecDuplicate(snes->vec_sol, &vi->t);CHKERRQ(ierr); 416 PetscFunctionReturn(0); 417 } 418 /* -------------------------------------------------------------------------- */ 419 #undef __FUNCT__ 420 #define __FUNCT__ "SNESReset_VISS" 421 PetscErrorCode SNESReset_VISS(SNES snes) 422 { 423 SNES_VISS *vi = (SNES_VISS*) snes->data; 424 PetscErrorCode ierr; 425 426 PetscFunctionBegin; 427 ierr = SNESReset_VI(snes);CHKERRQ(ierr); 428 ierr = VecDestroy(&vi->dpsi);CHKERRQ(ierr); 429 ierr = VecDestroy(&vi->phi);CHKERRQ(ierr); 430 ierr = VecDestroy(&vi->Da);CHKERRQ(ierr); 431 ierr = VecDestroy(&vi->Db);CHKERRQ(ierr); 432 ierr = VecDestroy(&vi->z);CHKERRQ(ierr); 433 ierr = VecDestroy(&vi->t);CHKERRQ(ierr); 434 PetscFunctionReturn(0); 435 } 436 437 /* -------------------------------------------------------------------------- */ 438 /* 439 SNESSetFromOptions_VISS - Sets various parameters for the SNESVI method. 440 441 Input Parameter: 442 . snes - the SNES context 443 444 Application Interface Routine: SNESSetFromOptions() 445 */ 446 #undef __FUNCT__ 447 #define __FUNCT__ "SNESSetFromOptions_VISS" 448 static PetscErrorCode SNESSetFromOptions_VISS(SNES snes) 449 { 450 PetscErrorCode ierr; 451 SNESLineSearch linesearch; 452 453 PetscFunctionBegin; 454 ierr = SNESSetFromOptions_VI(snes);CHKERRQ(ierr); 455 ierr = PetscOptionsHead("SNES semismooth method options");CHKERRQ(ierr); 456 ierr = PetscOptionsTail();CHKERRQ(ierr); 457 /* set up the default line search */ 458 if (!snes->linesearch) { 459 ierr = SNESGetSNESLineSearch(snes, &linesearch);CHKERRQ(ierr); 460 ierr = SNESLineSearchSetType(linesearch, SNESLINESEARCHBT);CHKERRQ(ierr); 461 } 462 463 PetscFunctionReturn(0); 464 } 465 466 467 /* -------------------------------------------------------------------------- */ 468 /*MC 469 SNESVISS - Semi-smooth solver for variational inequalities based on Newton's method 470 471 Options Database: 472 + -snes_vi_type <ss,rs,rsaug> a semi-smooth solver, a reduced space active set method, and a reduced space active set method that does not eliminate the active constraints from the Jacobian instead augments the Jacobian with additional variables that enforce the constraints 473 - -snes_vi_monitor - prints the number of active constraints at each iteration. 474 475 Level: beginner 476 477 References: 478 - T. S. Munson, F. Facchinei, M. C. Ferris, A. Fischer, and C. Kanzow. The semismooth 479 algorithm for large scale complementarity problems. INFORMS Journal on Computing, 13 (2001). 480 481 .seealso: SNESVISetVariableBounds(), SNESVISetComputeVariableBounds(), SNESCreate(), SNES, SNESSetType(), SNESVIRS, SNESVISS, SNESTR, SNESLineSearchSet(), 482 SNESLineSearchSetPostCheck(), SNESLineSearchNo(), SNESLineSearchCubic(), SNESLineSearchQuadratic(), 483 SNESLineSearchSet(), SNESLineSearchNoNorms(), SNESLineSearchSetPreCheck(), SNESLineSearchSetParams(), SNESLineSearchGetParams() 484 485 M*/ 486 EXTERN_C_BEGIN 487 #undef __FUNCT__ 488 #define __FUNCT__ "SNESCreate_VISS" 489 PetscErrorCode SNESCreate_VISS(SNES snes) 490 { 491 PetscErrorCode ierr; 492 SNES_VISS *vi; 493 494 PetscFunctionBegin; 495 snes->ops->reset = SNESReset_VISS; 496 snes->ops->setup = SNESSetUp_VISS; 497 snes->ops->solve = SNESSolve_VISS; 498 snes->ops->destroy = SNESDestroy_VI; 499 snes->ops->setfromoptions = SNESSetFromOptions_VISS; 500 snes->ops->view = PETSC_NULL; 501 502 snes->usesksp = PETSC_TRUE; 503 snes->usespc = PETSC_FALSE; 504 505 ierr = PetscNewLog(snes,SNES_VISS,&vi);CHKERRQ(ierr); 506 snes->data = (void*)vi; 507 508 ierr = PetscObjectComposeFunctionDynamic((PetscObject)snes,"SNESVISetVariableBounds_C","SNESVISetVariableBounds_VI",SNESVISetVariableBounds_VI);CHKERRQ(ierr); 509 ierr = PetscObjectComposeFunctionDynamic((PetscObject)snes,"SNESVISetComputeVariableBounds_C","SNESVISetComputeVariableBounds_VI",SNESVISetComputeVariableBounds_VI);CHKERRQ(ierr); 510 PetscFunctionReturn(0); 511 } 512 EXTERN_C_END 513 514