1a7e14dcfSSatish Balay #include "tao-private/taosolver_impl.h" /*I "taosolver.h" I*/ 2a7e14dcfSSatish Balay 3a7e14dcfSSatish Balay #undef __FUNCT__ 4a7e14dcfSSatish Balay #define __FUNCT__ "TaoSetInitialVector" 5a7e14dcfSSatish Balay /*@ 6a7e14dcfSSatish Balay TaoSetInitialVector - Sets the initial guess for the solve 7a7e14dcfSSatish Balay 8a7e14dcfSSatish Balay Logically collective on TaoSolver 9a7e14dcfSSatish Balay 10a7e14dcfSSatish Balay Input Parameters: 11a7e14dcfSSatish Balay + tao - the TaoSolver context 12a7e14dcfSSatish Balay - x0 - the initial guess 13a7e14dcfSSatish Balay 14a7e14dcfSSatish Balay Level: beginner 15a7e14dcfSSatish Balay .seealso: TaoCreate(), TaoSolve() 16a7e14dcfSSatish Balay @*/ 17a7e14dcfSSatish Balay 18a7e14dcfSSatish Balay PetscErrorCode TaoSetInitialVector(TaoSolver tao, Vec x0) { 19a7e14dcfSSatish Balay PetscErrorCode ierr; 20a7e14dcfSSatish Balay 21a7e14dcfSSatish Balay PetscFunctionBegin; 22a7e14dcfSSatish Balay PetscValidHeaderSpecific(tao,TAOSOLVER_CLASSID,1); 23a7e14dcfSSatish Balay if (x0) { 24a7e14dcfSSatish Balay PetscValidHeaderSpecific(x0,VEC_CLASSID,2); 25a7e14dcfSSatish Balay PetscObjectReference((PetscObject)x0); 26a7e14dcfSSatish Balay } 27a7e14dcfSSatish Balay if (tao->solution) { 28a7e14dcfSSatish Balay ierr = VecDestroy(&tao->solution); CHKERRQ(ierr); 29a7e14dcfSSatish Balay } 30a7e14dcfSSatish Balay tao->solution = x0; 31a7e14dcfSSatish Balay PetscFunctionReturn(0); 32a7e14dcfSSatish Balay } 33a7e14dcfSSatish Balay 34a7e14dcfSSatish Balay #undef __FUNCT__ 35a7e14dcfSSatish Balay #define __FUNCT__ "TaoComputeGradient" 36a7e14dcfSSatish Balay /*@ 37a7e14dcfSSatish Balay TaoComputeGradient - Computes the gradient of the objective function 38a7e14dcfSSatish Balay 39a7e14dcfSSatish Balay Collective on TaoSolver 40a7e14dcfSSatish Balay 41a7e14dcfSSatish Balay Input Parameters: 42a7e14dcfSSatish Balay + tao - the TaoSolver context 43a7e14dcfSSatish Balay - X - input vector 44a7e14dcfSSatish Balay 45a7e14dcfSSatish Balay Output Parameter: 46a7e14dcfSSatish Balay . G - gradient vector 47a7e14dcfSSatish Balay 48a7e14dcfSSatish Balay Notes: TaoComputeGradient() is typically used within minimization implementations, 49a7e14dcfSSatish Balay so most users would not generally call this routine themselves. 50a7e14dcfSSatish Balay 51a7e14dcfSSatish Balay Level: advanced 52a7e14dcfSSatish Balay 53a7e14dcfSSatish Balay .seealso: TaoComputeObjective(), TaoComputeObjectiveAndGradient(), TaoSetGradientRoutine() 54a7e14dcfSSatish Balay @*/ 55a7e14dcfSSatish Balay PetscErrorCode TaoComputeGradient(TaoSolver tao, Vec X, Vec G) 56a7e14dcfSSatish Balay { 57a7e14dcfSSatish Balay PetscErrorCode ierr; 58a7e14dcfSSatish Balay PetscReal dummy; 59*87f595a5SBarry Smith 60a7e14dcfSSatish Balay PetscFunctionBegin; 61a7e14dcfSSatish Balay PetscValidHeaderSpecific(tao,TAOSOLVER_CLASSID,1); 62a7e14dcfSSatish Balay PetscValidHeaderSpecific(X,VEC_CLASSID,2); 63a7e14dcfSSatish Balay PetscValidHeaderSpecific(G,VEC_CLASSID,2); 64a7e14dcfSSatish Balay PetscCheckSameComm(tao,1,X,2); 65a7e14dcfSSatish Balay PetscCheckSameComm(tao,1,G,3); 66a7e14dcfSSatish Balay if (tao->ops->computegradient) { 676c23d075SBarry Smith ierr = PetscLogEventBegin(TaoSolver_GradientEval,tao,X,G,NULL); CHKERRQ(ierr); 68a7e14dcfSSatish Balay PetscStackPush("TaoSolver user gradient evaluation routine"); 69a7e14dcfSSatish Balay CHKMEMQ; 70a7e14dcfSSatish Balay ierr = (*tao->ops->computegradient)(tao,X,G,tao->user_gradP); CHKERRQ(ierr); 71a7e14dcfSSatish Balay CHKMEMQ; 72a7e14dcfSSatish Balay PetscStackPop; 736c23d075SBarry Smith ierr = PetscLogEventEnd(TaoSolver_GradientEval,tao,X,G,NULL); CHKERRQ(ierr); 74a7e14dcfSSatish Balay tao->ngrads++; 75a7e14dcfSSatish Balay } else if (tao->ops->computeobjectiveandgradient) { 766c23d075SBarry Smith ierr = PetscLogEventBegin(TaoSolver_ObjGradientEval,tao,X,G,NULL); CHKERRQ(ierr); 77a7e14dcfSSatish Balay PetscStackPush("Tao user objective/gradient evaluation routine"); 78a7e14dcfSSatish Balay CHKMEMQ; 79a7e14dcfSSatish Balay ierr = (*tao->ops->computeobjectiveandgradient)(tao,X,&dummy,G,tao->user_objgradP); CHKERRQ(ierr); 80a7e14dcfSSatish Balay CHKMEMQ; 81a7e14dcfSSatish Balay PetscStackPop; 826c23d075SBarry Smith ierr = PetscLogEventEnd(TaoSolver_ObjGradientEval,tao,X,G,NULL); CHKERRQ(ierr); 83a7e14dcfSSatish Balay tao->nfuncgrads++; 84*87f595a5SBarry Smith } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"TaoSetGradientRoutine() has not been called"); 85a7e14dcfSSatish Balay PetscFunctionReturn(0); 86a7e14dcfSSatish Balay } 87a7e14dcfSSatish Balay 88a7e14dcfSSatish Balay 89a7e14dcfSSatish Balay #undef __FUNCT__ 90a7e14dcfSSatish Balay #define __FUNCT__ "TaoComputeObjective" 91a7e14dcfSSatish Balay /*@ 92a7e14dcfSSatish Balay TaoComputeObjective - Computes the objective function value at a given point 93a7e14dcfSSatish Balay 94a7e14dcfSSatish Balay Collective on TaoSolver 95a7e14dcfSSatish Balay 96a7e14dcfSSatish Balay Input Parameters: 97a7e14dcfSSatish Balay + tao - the TaoSolver context 98a7e14dcfSSatish Balay - X - input vector 99a7e14dcfSSatish Balay 100a7e14dcfSSatish Balay Output Parameter: 101a7e14dcfSSatish Balay . f - Objective value at X 102a7e14dcfSSatish Balay 103a7e14dcfSSatish Balay Notes: TaoComputeObjective() is typically used within minimization implementations, 104a7e14dcfSSatish Balay so most users would not generally call this routine themselves. 105a7e14dcfSSatish Balay 106a7e14dcfSSatish Balay Level: advanced 107a7e14dcfSSatish Balay 108a7e14dcfSSatish Balay .seealso: TaoComputeGradient(), TaoComputeObjectiveAndGradient(), TaoSetObjectiveRoutine() 109a7e14dcfSSatish Balay @*/ 110a7e14dcfSSatish Balay PetscErrorCode TaoComputeObjective(TaoSolver tao, Vec X, PetscReal *f) 111a7e14dcfSSatish Balay { 112a7e14dcfSSatish Balay PetscErrorCode ierr; 113a7e14dcfSSatish Balay Vec temp; 114*87f595a5SBarry Smith 115a7e14dcfSSatish Balay PetscFunctionBegin; 116a7e14dcfSSatish Balay PetscValidHeaderSpecific(tao,TAOSOLVER_CLASSID,1); 117a7e14dcfSSatish Balay PetscValidHeaderSpecific(X,VEC_CLASSID,2); 118a7e14dcfSSatish Balay PetscCheckSameComm(tao,1,X,2); 119a7e14dcfSSatish Balay if (tao->ops->computeobjective) { 1206c23d075SBarry Smith ierr = PetscLogEventBegin(TaoSolver_ObjectiveEval,tao,X,NULL,NULL); CHKERRQ(ierr); 121a7e14dcfSSatish Balay PetscStackPush("TaoSolver user objective evaluation routine"); 122a7e14dcfSSatish Balay CHKMEMQ; 123a7e14dcfSSatish Balay ierr = (*tao->ops->computeobjective)(tao,X,f,tao->user_objP); CHKERRQ(ierr); 124a7e14dcfSSatish Balay CHKMEMQ; 125a7e14dcfSSatish Balay PetscStackPop; 1266c23d075SBarry Smith ierr = PetscLogEventEnd(TaoSolver_ObjectiveEval,tao,X,NULL,NULL); CHKERRQ(ierr); 127a7e14dcfSSatish Balay tao->nfuncs++; 128a7e14dcfSSatish Balay } else if (tao->ops->computeobjectiveandgradient) { 129a7e14dcfSSatish Balay ierr = PetscInfo(tao,"Duplicating variable vector in order to call func/grad routine"); CHKERRQ(ierr); 130a7e14dcfSSatish Balay ierr = VecDuplicate(X,&temp); CHKERRQ(ierr); 1316c23d075SBarry Smith ierr = PetscLogEventBegin(TaoSolver_ObjGradientEval,tao,X,NULL,NULL); CHKERRQ(ierr); 132a7e14dcfSSatish Balay PetscStackPush("TaoSolver user objective/gradient evaluation routine"); 133a7e14dcfSSatish Balay CHKMEMQ; 134a7e14dcfSSatish Balay ierr = (*tao->ops->computeobjectiveandgradient)(tao,X,f,temp,tao->user_objgradP); CHKERRQ(ierr); 135a7e14dcfSSatish Balay CHKMEMQ; 136a7e14dcfSSatish Balay PetscStackPop; 1376c23d075SBarry Smith ierr = PetscLogEventEnd(TaoSolver_ObjGradientEval,tao,X,NULL,NULL); CHKERRQ(ierr); 138a7e14dcfSSatish Balay ierr = VecDestroy(&temp); CHKERRQ(ierr); 139a7e14dcfSSatish Balay tao->nfuncgrads++; 140*87f595a5SBarry Smith } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"TaoSetObjectiveRoutine() has not been called"); 141a7e14dcfSSatish Balay ierr = PetscInfo1(tao,"TAO Function evaluation: %14.12e\n",*f);CHKERRQ(ierr); 142a7e14dcfSSatish Balay PetscFunctionReturn(0); 143a7e14dcfSSatish Balay } 144a7e14dcfSSatish Balay 145a7e14dcfSSatish Balay #undef __FUNCT__ 146a7e14dcfSSatish Balay #define __FUNCT__ "TaoComputeObjectiveAndGradient" 147a7e14dcfSSatish Balay /*@ 148a7e14dcfSSatish Balay TaoComputeObjectiveAndGradient - Computes the objective function value at a given point 149a7e14dcfSSatish Balay 150a7e14dcfSSatish Balay Collective on TaoSolver 151a7e14dcfSSatish Balay 152a7e14dcfSSatish Balay Input Parameters: 153a7e14dcfSSatish Balay + tao - the TaoSolver context 154a7e14dcfSSatish Balay - X - input vector 155a7e14dcfSSatish Balay 156a7e14dcfSSatish Balay Output Parameter: 157a7e14dcfSSatish Balay + f - Objective value at X 158a7e14dcfSSatish Balay - g - Gradient vector at X 159a7e14dcfSSatish Balay 160a7e14dcfSSatish Balay Notes: TaoComputeObjectiveAndGradient() is typically used within minimization implementations, 161a7e14dcfSSatish Balay so most users would not generally call this routine themselves. 162a7e14dcfSSatish Balay 163a7e14dcfSSatish Balay Level: advanced 164a7e14dcfSSatish Balay 165a7e14dcfSSatish Balay .seealso: TaoComputeGradient(), TaoComputeObjectiveAndGradient(), TaoSetObjectiveRoutine() 166a7e14dcfSSatish Balay @*/ 167a7e14dcfSSatish Balay PetscErrorCode TaoComputeObjectiveAndGradient(TaoSolver tao, Vec X, PetscReal *f, Vec G) 168a7e14dcfSSatish Balay { 169a7e14dcfSSatish Balay PetscErrorCode ierr; 170*87f595a5SBarry Smith 171a7e14dcfSSatish Balay PetscFunctionBegin; 172a7e14dcfSSatish Balay PetscValidHeaderSpecific(tao,TAOSOLVER_CLASSID,1); 173a7e14dcfSSatish Balay PetscValidHeaderSpecific(X,VEC_CLASSID,2); 174a7e14dcfSSatish Balay PetscValidHeaderSpecific(G,VEC_CLASSID,4); 175a7e14dcfSSatish Balay PetscCheckSameComm(tao,1,X,2); 176a7e14dcfSSatish Balay PetscCheckSameComm(tao,1,G,4); 177a7e14dcfSSatish Balay if (tao->ops->computeobjectiveandgradient) { 1786c23d075SBarry Smith ierr = PetscLogEventBegin(TaoSolver_ObjGradientEval,tao,X,G,NULL); CHKERRQ(ierr); 179a7e14dcfSSatish Balay PetscStackPush("TaoSolver user objective/gradient evaluation routine"); 180a7e14dcfSSatish Balay CHKMEMQ; 181a7e14dcfSSatish Balay ierr = (*tao->ops->computeobjectiveandgradient)(tao,X,f,G,tao->user_objgradP); CHKERRQ(ierr); 182a7e14dcfSSatish Balay if (tao->ops->computegradient == TaoDefaultComputeGradient) { 183a7e14dcfSSatish Balay /* Overwrite gradient with finite difference gradient */ 184a7e14dcfSSatish Balay ierr = TaoDefaultComputeGradient(tao,X,G,tao->user_objgradP); CHKERRQ(ierr); 185a7e14dcfSSatish Balay } 186a7e14dcfSSatish Balay CHKMEMQ; 187a7e14dcfSSatish Balay PetscStackPop; 1886c23d075SBarry Smith ierr = PetscLogEventEnd(TaoSolver_ObjGradientEval,tao,X,G,NULL); CHKERRQ(ierr); 189a7e14dcfSSatish Balay tao->nfuncgrads++; 190a7e14dcfSSatish Balay } else if (tao->ops->computeobjective && tao->ops->computegradient) { 1916c23d075SBarry Smith ierr = PetscLogEventBegin(TaoSolver_ObjectiveEval,tao,X,NULL,NULL); CHKERRQ(ierr); 192a7e14dcfSSatish Balay PetscStackPush("TaoSolver user objective evaluation routine"); 193a7e14dcfSSatish Balay CHKMEMQ; 194a7e14dcfSSatish Balay ierr = (*tao->ops->computeobjective)(tao,X,f,tao->user_objP); CHKERRQ(ierr); 195a7e14dcfSSatish Balay CHKMEMQ; 196a7e14dcfSSatish Balay PetscStackPop; 1976c23d075SBarry Smith ierr = PetscLogEventEnd(TaoSolver_ObjectiveEval,tao,X,NULL,NULL); CHKERRQ(ierr); 198a7e14dcfSSatish Balay tao->nfuncs++; 1996c23d075SBarry Smith ierr = PetscLogEventBegin(TaoSolver_GradientEval,tao,X,G,NULL); CHKERRQ(ierr); 200a7e14dcfSSatish Balay PetscStackPush("TaoSolver user gradient evaluation routine"); 201a7e14dcfSSatish Balay CHKMEMQ; 202a7e14dcfSSatish Balay ierr = (*tao->ops->computegradient)(tao,X,G,tao->user_gradP); CHKERRQ(ierr); 203a7e14dcfSSatish Balay CHKMEMQ; 204a7e14dcfSSatish Balay PetscStackPop; 2056c23d075SBarry Smith ierr = PetscLogEventEnd(TaoSolver_GradientEval,tao,X,G,NULL); CHKERRQ(ierr); 206a7e14dcfSSatish Balay tao->ngrads++; 207*87f595a5SBarry Smith } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"TaoSetObjectiveRoutine() or TaoSetGradientRoutine() not set"); 208a7e14dcfSSatish Balay ierr = PetscInfo1(tao,"TAO Function evaluation: %14.12e\n",*f);CHKERRQ(ierr); 209a7e14dcfSSatish Balay PetscFunctionReturn(0); 210a7e14dcfSSatish Balay } 211a7e14dcfSSatish Balay 212a7e14dcfSSatish Balay #undef __FUNCT__ 213a7e14dcfSSatish Balay #define __FUNCT__ "TaoSetObjectiveRoutine" 214a7e14dcfSSatish Balay /*@C 215a7e14dcfSSatish Balay TaoSetObjectiveRoutine - Sets the function evaluation routine for minimization 216a7e14dcfSSatish Balay 217a7e14dcfSSatish Balay Logically collective on TaoSolver 218a7e14dcfSSatish Balay 219a7e14dcfSSatish Balay Input Parameter: 220a7e14dcfSSatish Balay + tao - the TaoSolver context 221a7e14dcfSSatish Balay . func - the objective function 222a7e14dcfSSatish Balay - ctx - [optional] user-defined context for private data for the function evaluation 2236c23d075SBarry Smith routine (may be NULL) 224a7e14dcfSSatish Balay 225a7e14dcfSSatish Balay Calling sequence of func: 226a7e14dcfSSatish Balay $ func (TaoSolver tao, Vec x, PetscReal *f, void *ctx); 227a7e14dcfSSatish Balay 228a7e14dcfSSatish Balay + x - input vector 229a7e14dcfSSatish Balay . f - function value 230a7e14dcfSSatish Balay - ctx - [optional] user-defined function context 231a7e14dcfSSatish Balay 232a7e14dcfSSatish Balay Level: beginner 233a7e14dcfSSatish Balay 234a7e14dcfSSatish Balay .seealso: TaoSetGradientRoutine(), TaoSetHessianRoutine() TaoSetObjectiveAndGradientRoutine() 235a7e14dcfSSatish Balay @*/ 236a7e14dcfSSatish Balay PetscErrorCode TaoSetObjectiveRoutine(TaoSolver tao, PetscErrorCode (*func)(TaoSolver, Vec, PetscReal*,void*),void *ctx) 237a7e14dcfSSatish Balay { 238a7e14dcfSSatish Balay PetscFunctionBegin; 239a7e14dcfSSatish Balay PetscValidHeaderSpecific(tao,TAOSOLVER_CLASSID,1); 240a7e14dcfSSatish Balay tao->user_objP = ctx; 241a7e14dcfSSatish Balay tao->ops->computeobjective = func; 242a7e14dcfSSatish Balay PetscFunctionReturn(0); 243a7e14dcfSSatish Balay } 244a7e14dcfSSatish Balay 245a7e14dcfSSatish Balay #undef __FUNCT__ 246a7e14dcfSSatish Balay #define __FUNCT__ "TaoSetSeparableObjectiveRoutine" 247a7e14dcfSSatish Balay /*@C 248a7e14dcfSSatish Balay TaoSetSeparableObjectiveRoutine - Sets the function evaluation routine for least-square applications 249a7e14dcfSSatish Balay 250a7e14dcfSSatish Balay Logically collective on TaoSolver 251a7e14dcfSSatish Balay 252a7e14dcfSSatish Balay Input Parameter: 253a7e14dcfSSatish Balay + tao - the TaoSolver context 254a7e14dcfSSatish Balay . func - the objective function evaluation routine 255a7e14dcfSSatish Balay - ctx - [optional] user-defined context for private data for the function evaluation 2566c23d075SBarry Smith routine (may be NULL) 257a7e14dcfSSatish Balay 258a7e14dcfSSatish Balay Calling sequence of func: 259a7e14dcfSSatish Balay $ func (TaoSolver tao, Vec x, Vec f, void *ctx); 260a7e14dcfSSatish Balay 261a7e14dcfSSatish Balay + x - input vector 262a7e14dcfSSatish Balay . f - function value vector 263a7e14dcfSSatish Balay - ctx - [optional] user-defined function context 264a7e14dcfSSatish Balay 265a7e14dcfSSatish Balay Level: beginner 266a7e14dcfSSatish Balay 267a7e14dcfSSatish Balay .seealso: TaoSetObjectiveRoutine(), TaoSetJacobianRoutine() 268a7e14dcfSSatish Balay @*/ 269a7e14dcfSSatish Balay PetscErrorCode TaoSetSeparableObjectiveRoutine(TaoSolver tao, Vec sepobj, PetscErrorCode (*func)(TaoSolver, Vec, Vec, void*),void *ctx) 270a7e14dcfSSatish Balay { 271a7e14dcfSSatish Balay PetscFunctionBegin; 272a7e14dcfSSatish Balay PetscValidHeaderSpecific(tao,TAOSOLVER_CLASSID,1); 273a7e14dcfSSatish Balay PetscValidHeaderSpecific(sepobj, VEC_CLASSID,2); 274a7e14dcfSSatish Balay tao->user_sepobjP = ctx; 275a7e14dcfSSatish Balay tao->sep_objective = sepobj; 276a7e14dcfSSatish Balay tao->ops->computeseparableobjective = func; 277a7e14dcfSSatish Balay PetscFunctionReturn(0); 278a7e14dcfSSatish Balay } 279a7e14dcfSSatish Balay 280a7e14dcfSSatish Balay #undef __FUNCT__ 281a7e14dcfSSatish Balay #define __FUNCT__ "TaoComputeSeparableObjective" 282a7e14dcfSSatish Balay /*@ 283a7e14dcfSSatish Balay TaoComputeSeparableObjective - Computes a separable objective function vector at a given point (for least-square applications) 284a7e14dcfSSatish Balay 285a7e14dcfSSatish Balay Collective on TaoSolver 286a7e14dcfSSatish Balay 287a7e14dcfSSatish Balay Input Parameters: 288a7e14dcfSSatish Balay + tao - the TaoSolver context 289a7e14dcfSSatish Balay - X - input vector 290a7e14dcfSSatish Balay 291a7e14dcfSSatish Balay Output Parameter: 292a7e14dcfSSatish Balay . f - Objective vector at X 293a7e14dcfSSatish Balay 294a7e14dcfSSatish Balay Notes: TaoComputeSeparableObjective() is typically used within minimization implementations, 295a7e14dcfSSatish Balay so most users would not generally call this routine themselves. 296a7e14dcfSSatish Balay 297a7e14dcfSSatish Balay Level: advanced 298a7e14dcfSSatish Balay 299a7e14dcfSSatish Balay .seealso: TaoSetSeparableObjectiveRoutine() 300a7e14dcfSSatish Balay @*/ 301a7e14dcfSSatish Balay PetscErrorCode TaoComputeSeparableObjective(TaoSolver tao, Vec X, Vec F) 302a7e14dcfSSatish Balay { 303a7e14dcfSSatish Balay PetscErrorCode ierr; 304*87f595a5SBarry Smith 305a7e14dcfSSatish Balay PetscFunctionBegin; 306a7e14dcfSSatish Balay PetscValidHeaderSpecific(tao,TAOSOLVER_CLASSID,1); 307a7e14dcfSSatish Balay PetscValidHeaderSpecific(X,VEC_CLASSID,2); 308a7e14dcfSSatish Balay PetscValidHeaderSpecific(F,VEC_CLASSID,3); 309a7e14dcfSSatish Balay PetscCheckSameComm(tao,1,X,2); 310a7e14dcfSSatish Balay PetscCheckSameComm(tao,1,F,3); 311a7e14dcfSSatish Balay if (tao->ops->computeseparableobjective) { 3126c23d075SBarry Smith ierr = PetscLogEventBegin(TaoSolver_ObjectiveEval,tao,X,NULL,NULL); CHKERRQ(ierr); 313a7e14dcfSSatish Balay PetscStackPush("TaoSolver user separable objective evaluation routine"); 314a7e14dcfSSatish Balay CHKMEMQ; 315a7e14dcfSSatish Balay ierr = (*tao->ops->computeseparableobjective)(tao,X,F,tao->user_sepobjP); CHKERRQ(ierr); 316a7e14dcfSSatish Balay CHKMEMQ; 317a7e14dcfSSatish Balay PetscStackPop; 3186c23d075SBarry Smith ierr = PetscLogEventEnd(TaoSolver_ObjectiveEval,tao,X,NULL,NULL); CHKERRQ(ierr); 319a7e14dcfSSatish Balay tao->nfuncs++; 320*87f595a5SBarry Smith } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"TaoSetSeparableObjectiveRoutine() has not been called"); 321a7e14dcfSSatish Balay ierr = PetscInfo(tao,"TAO separable function evaluation.\n"); CHKERRQ(ierr); 322a7e14dcfSSatish Balay PetscFunctionReturn(0); 323a7e14dcfSSatish Balay } 324a7e14dcfSSatish Balay 325a7e14dcfSSatish Balay #undef __FUNCT__ 326a7e14dcfSSatish Balay #define __FUNCT__ "TaoSetGradientRoutine" 327a7e14dcfSSatish Balay /*@C 328a7e14dcfSSatish Balay TaoSetGradientRoutine - Sets the gradient evaluation routine for minimization 329a7e14dcfSSatish Balay 330a7e14dcfSSatish Balay Logically collective on TaoSolver 331a7e14dcfSSatish Balay 332a7e14dcfSSatish Balay Input Parameter: 333a7e14dcfSSatish Balay + tao - the TaoSolver context 334a7e14dcfSSatish Balay . func - the gradient function 335a7e14dcfSSatish Balay - ctx - [optional] user-defined context for private data for the gradient evaluation 3366c23d075SBarry Smith routine (may be NULL) 337a7e14dcfSSatish Balay 338a7e14dcfSSatish Balay Calling sequence of func: 339a7e14dcfSSatish Balay $ func (TaoSolver tao, Vec x, Vec g, void *ctx); 340a7e14dcfSSatish Balay 341a7e14dcfSSatish Balay + x - input vector 342a7e14dcfSSatish Balay . g - gradient value (output) 343a7e14dcfSSatish Balay - ctx - [optional] user-defined function context 344a7e14dcfSSatish Balay 345a7e14dcfSSatish Balay Level: beginner 346a7e14dcfSSatish Balay 347a7e14dcfSSatish Balay .seealso: TaoSetObjectiveRoutine(), TaoSetHessianRoutine() TaoSetObjectiveAndGradientRoutine() 348a7e14dcfSSatish Balay @*/ 349a7e14dcfSSatish Balay PetscErrorCode TaoSetGradientRoutine(TaoSolver tao, PetscErrorCode (*func)(TaoSolver, Vec, Vec, void*),void *ctx) 350a7e14dcfSSatish Balay { 351a7e14dcfSSatish Balay PetscFunctionBegin; 352a7e14dcfSSatish Balay PetscValidHeaderSpecific(tao,TAOSOLVER_CLASSID,1); 353a7e14dcfSSatish Balay tao->user_gradP = ctx; 354a7e14dcfSSatish Balay tao->ops->computegradient = func; 355a7e14dcfSSatish Balay PetscFunctionReturn(0); 356a7e14dcfSSatish Balay } 357a7e14dcfSSatish Balay 358a7e14dcfSSatish Balay 359a7e14dcfSSatish Balay #undef __FUNCT__ 360a7e14dcfSSatish Balay #define __FUNCT__ "TaoSetObjectiveAndGradientRoutine" 361a7e14dcfSSatish Balay /*@C 362a7e14dcfSSatish Balay TaoSetObjectiveAndGradientRoutine - Sets a combined objective function and gradient evaluation routine for minimization 363a7e14dcfSSatish Balay 364a7e14dcfSSatish Balay Logically collective on TaoSolver 365a7e14dcfSSatish Balay 366a7e14dcfSSatish Balay Input Parameter: 367a7e14dcfSSatish Balay + tao - the TaoSolver context 368a7e14dcfSSatish Balay . func - the gradient function 369a7e14dcfSSatish Balay - ctx - [optional] user-defined context for private data for the gradient evaluation 3706c23d075SBarry Smith routine (may be NULL) 371a7e14dcfSSatish Balay 372a7e14dcfSSatish Balay Calling sequence of func: 373a7e14dcfSSatish Balay $ func (TaoSolver tao, Vec x, Vec g, void *ctx); 374a7e14dcfSSatish Balay 375a7e14dcfSSatish Balay + x - input vector 376a7e14dcfSSatish Balay . g - gradient value (output) 377a7e14dcfSSatish Balay - ctx - [optional] user-defined function context 378a7e14dcfSSatish Balay 379a7e14dcfSSatish Balay Level: beginner 380a7e14dcfSSatish Balay 381a7e14dcfSSatish Balay .seealso: TaoSetObjectiveRoutine(), TaoSetHessianRoutine() TaoSetObjectiveAndGradientRoutine() 382a7e14dcfSSatish Balay @*/ 383a7e14dcfSSatish Balay PetscErrorCode TaoSetObjectiveAndGradientRoutine(TaoSolver tao, PetscErrorCode (*func)(TaoSolver, Vec, PetscReal *, Vec, void*), void *ctx) 384a7e14dcfSSatish Balay { 385a7e14dcfSSatish Balay PetscFunctionBegin; 386a7e14dcfSSatish Balay PetscValidHeaderSpecific(tao,TAOSOLVER_CLASSID,1); 387a7e14dcfSSatish Balay tao->user_objgradP = ctx; 388a7e14dcfSSatish Balay tao->ops->computeobjectiveandgradient = func; 389a7e14dcfSSatish Balay PetscFunctionReturn(0); 390a7e14dcfSSatish Balay } 391a7e14dcfSSatish Balay 392a7e14dcfSSatish Balay #undef __FUNCT__ 393a7e14dcfSSatish Balay #define __FUNCT__ "TaoIsObjectiveDefined" 394a7e14dcfSSatish Balay /*@ 395a7e14dcfSSatish Balay TaoIsObjectiveDefined -- Checks to see if the user has 396a7e14dcfSSatish Balay declared an objective-only routine. Useful for determining when 397a7e14dcfSSatish Balay it is appropriate to call TaoComputeObjective() or 398a7e14dcfSSatish Balay TaoComputeObjectiveAndGradient() 399a7e14dcfSSatish Balay 400a7e14dcfSSatish Balay Collective on TaoSolver 401a7e14dcfSSatish Balay 402a7e14dcfSSatish Balay Input Parameter: 403a7e14dcfSSatish Balay + tao - the TaoSolver context 404a7e14dcfSSatish Balay - ctx - PETSC_TRUE if objective function routine is set by user, 405a7e14dcfSSatish Balay PETSC_FALSE otherwise 406a7e14dcfSSatish Balay Level: developer 407a7e14dcfSSatish Balay 408a7e14dcfSSatish Balay .seealso: TaoSetObjectiveRoutine(), TaoIsGradientDefined(), TaoIsObjectiveAndGradientDefined() 409a7e14dcfSSatish Balay @*/ 410a7e14dcfSSatish Balay PetscErrorCode TaoIsObjectiveDefined(TaoSolver tao, PetscBool *flg) 411a7e14dcfSSatish Balay { 412a7e14dcfSSatish Balay PetscFunctionBegin; 413a7e14dcfSSatish Balay PetscValidHeaderSpecific(tao,TAOSOLVER_CLASSID,1); 414a7e14dcfSSatish Balay if (tao->ops->computeobjective == 0) 415a7e14dcfSSatish Balay *flg = PETSC_FALSE; 416a7e14dcfSSatish Balay else 417a7e14dcfSSatish Balay *flg = PETSC_TRUE; 418a7e14dcfSSatish Balay PetscFunctionReturn(0); 419a7e14dcfSSatish Balay } 420a7e14dcfSSatish Balay 421a7e14dcfSSatish Balay #undef __FUNCT__ 422a7e14dcfSSatish Balay #define __FUNCT__ "TaoIsGradientDefined" 423a7e14dcfSSatish Balay /*@ 424a7e14dcfSSatish Balay TaoIsGradientDefined -- Checks to see if the user has 425a7e14dcfSSatish Balay declared an objective-only routine. Useful for determining when 426a7e14dcfSSatish Balay it is appropriate to call TaoComputeGradient() or 427a7e14dcfSSatish Balay TaoComputeGradientAndGradient() 428a7e14dcfSSatish Balay 429a7e14dcfSSatish Balay Not Collective 430a7e14dcfSSatish Balay 431a7e14dcfSSatish Balay Input Parameter: 432a7e14dcfSSatish Balay + tao - the TaoSolver context 433a7e14dcfSSatish Balay - ctx - PETSC_TRUE if gradient routine is set by user, PETSC_FALSE otherwise 434a7e14dcfSSatish Balay Level: developer 435a7e14dcfSSatish Balay 436a7e14dcfSSatish Balay .seealso: TaoSetGradientRoutine(), TaoIsObjectiveDefined(), TaoIsObjectiveAndGradientDefined() 437a7e14dcfSSatish Balay @*/ 438a7e14dcfSSatish Balay PetscErrorCode TaoIsGradientDefined(TaoSolver tao, PetscBool *flg) 439a7e14dcfSSatish Balay { 440a7e14dcfSSatish Balay PetscFunctionBegin; 441a7e14dcfSSatish Balay PetscValidHeaderSpecific(tao,TAOSOLVER_CLASSID,1); 442a7e14dcfSSatish Balay if (tao->ops->computegradient == 0) 443a7e14dcfSSatish Balay *flg = PETSC_FALSE; 444a7e14dcfSSatish Balay else 445a7e14dcfSSatish Balay *flg = PETSC_TRUE; 446a7e14dcfSSatish Balay PetscFunctionReturn(0); 447a7e14dcfSSatish Balay } 448a7e14dcfSSatish Balay 449a7e14dcfSSatish Balay 450a7e14dcfSSatish Balay #undef __FUNCT__ 451a7e14dcfSSatish Balay #define __FUNCT__ "TaoIsObjectiveAndGradientDefined" 452a7e14dcfSSatish Balay /*@ 453a7e14dcfSSatish Balay TaoIsObjectiveAndGradientDefined -- Checks to see if the user has 454a7e14dcfSSatish Balay declared a joint objective/gradient routine. Useful for determining when 455a7e14dcfSSatish Balay it is appropriate to call TaoComputeObjective() or 456a7e14dcfSSatish Balay TaoComputeObjectiveAndGradient() 457a7e14dcfSSatish Balay 458a7e14dcfSSatish Balay Not Collective 459a7e14dcfSSatish Balay 460a7e14dcfSSatish Balay Input Parameter: 461a7e14dcfSSatish Balay + tao - the TaoSolver context 462a7e14dcfSSatish Balay - ctx - PETSC_TRUE if objective/gradient routine is set by user, PETSC_FALSE otherwise 463a7e14dcfSSatish Balay Level: developer 464a7e14dcfSSatish Balay 465a7e14dcfSSatish Balay .seealso: TaoSetObjectiveAndGradientRoutine(), TaoIsObjectiveDefined(), TaoIsGradientDefined() 466a7e14dcfSSatish Balay @*/ 467a7e14dcfSSatish Balay PetscErrorCode TaoIsObjectiveAndGradientDefined(TaoSolver tao, PetscBool *flg) 468a7e14dcfSSatish Balay { 469a7e14dcfSSatish Balay PetscFunctionBegin; 470a7e14dcfSSatish Balay PetscValidHeaderSpecific(tao,TAOSOLVER_CLASSID,1); 471a7e14dcfSSatish Balay if (tao->ops->computeobjectiveandgradient == 0) 472a7e14dcfSSatish Balay *flg = PETSC_FALSE; 473a7e14dcfSSatish Balay else 474a7e14dcfSSatish Balay *flg = PETSC_TRUE; 475a7e14dcfSSatish Balay PetscFunctionReturn(0); 476a7e14dcfSSatish Balay } 477a7e14dcfSSatish Balay 478a7e14dcfSSatish Balay 479a7e14dcfSSatish Balay 480