Actual source code: petsctao.h
1: #pragma once
3: #include <petscsnes.h>
5: /* SUBMANSEC = Tao */
7: PETSC_EXTERN PetscErrorCode VecFischer(Vec, Vec, Vec, Vec, Vec);
8: PETSC_EXTERN PetscErrorCode VecSFischer(Vec, Vec, Vec, Vec, PetscReal, Vec);
9: PETSC_EXTERN PetscErrorCode MatDFischer(Mat, Vec, Vec, Vec, Vec, Vec, Vec, Vec, Vec);
10: PETSC_EXTERN PetscErrorCode MatDSFischer(Mat, Vec, Vec, Vec, Vec, PetscReal, Vec, Vec, Vec, Vec, Vec);
11: PETSC_EXTERN PetscErrorCode TaoSoftThreshold(Vec, PetscReal, PetscReal, Vec);
13: /*E
14: TaoSubsetType - Type representing the way TAO handles active sets
16: Values:
17: + `TAO_SUBSET_SUBVEC` - Tao uses `MatCreateSubMatrix()` and `VecGetSubVector()`
18: . `TAO_SUBSET_MASK` - Matrices are zeroed out corresponding to active set entries
19: - `TAO_SUBSET_MATRIXFREE` - Same as `TAO_SUBSET_MASK` but it can be applied to matrix-free operators
21: Options database Key:
22: . -different_hessian - Tao will use a copy of the Hessian operator for masking. By default TAO will directly alter the Hessian operator.
24: Level: intermediate
26: .seealso: [](ch_tao), `TaoVecGetSubVec()`, `TaoMatGetSubMat()`, `Tao`, `TaoCreate()`, `TaoDestroy()`, `TaoSetType()`, `TaoType`
27: E*/
28: typedef enum {
29: TAO_SUBSET_SUBVEC,
30: TAO_SUBSET_MASK,
31: TAO_SUBSET_MATRIXFREE
32: } TaoSubsetType;
33: PETSC_EXTERN const char *const TaoSubsetTypes[];
35: /*S
36: Tao - Abstract PETSc object that manages nonlinear optimization solves
38: Level: advanced
40: .seealso: [](doc_taosolve), [](ch_tao), `TaoCreate()`, `TaoDestroy()`, `TaoSetType()`, `TaoType`
41: S*/
42: typedef struct _p_Tao *Tao;
44: /*E
45: TaoADMMUpdateType - Determine spectral penalty update routine for Lagrange augmented term for `TAOADMM`.
47: Level: advanced
49: .seealso: [](ch_tao), `Tao`, `TAOADMM`, `TaoADMMSetUpdateType()`
50: E*/
51: typedef enum {
52: TAO_ADMM_UPDATE_BASIC,
53: TAO_ADMM_UPDATE_ADAPTIVE,
54: TAO_ADMM_UPDATE_ADAPTIVE_RELAXED
55: } TaoADMMUpdateType;
56: PETSC_EXTERN const char *const TaoADMMUpdateTypes[];
58: /*MC
59: TAO_ADMM_UPDATE_BASIC - Use same spectral penalty set at the beginning. No update
61: Level: advanced
63: Note:
64: Most basic implementation of `TAOADMM`. Generally slower than adaptive or adaptive relaxed version.
66: .seealso: [](ch_tao), `Tao`, `TAOADMM`, `TaoADMMSetUpdateType()`, `TAO_ADMM_UPDATE_ADAPTIVE`, `TAO_ADMM_UPDATE_ADAPTIVE_RELAXED`
67: M*/
69: /*MC
70: TAO_ADMM_UPDATE_ADAPTIVE - Adaptively update spectral penalty
72: Level: advanced
74: Note:
75: Adaptively updates spectral penalty of `TAOADMM` by using both steepest descent and minimum gradient.
77: .seealso: [](ch_tao), `Tao`, `TAOADMM`, `TaoADMMSetUpdateType()`, `TAO_ADMM_UPDATE_BASIC`, `TAO_ADMM_UPDATE_ADAPTIVE_RELAXED`
78: M*/
80: /*MC
81: ADMM_UPDATE_ADAPTIVE_RELAXED - Adaptively update spectral penalty, and relaxes parameter update
83: Level: advanced
85: Note:
86: With adaptive spectral penalty update, it also relaxes x vector update by a factor.
88: .seealso: [](ch_tao), `Tao`, `TaoADMMSetUpdateType()`, `TAO_ADMM_UPDATE_BASIC`, `TAO_ADMM_UPDATE_ADAPTIVE`
89: M*/
91: /*E
92: TaoADMMRegularizerType - Determine regularizer routine - either user provided or soft threshold for `TAOADMM`
94: Level: advanced
96: .seealso: [](ch_tao), `Tao`, `TAOADMM`, `TaoADMMSetRegularizerType()`
97: E*/
98: typedef enum {
99: TAO_ADMM_REGULARIZER_USER,
100: TAO_ADMM_REGULARIZER_SOFT_THRESH
101: } TaoADMMRegularizerType;
102: PETSC_EXTERN const char *const TaoADMMRegularizerTypes[];
104: /*MC
105: TAO_ADMM_REGULARIZER_USER - User provided routines for regularizer part of `TAOADMM`
107: Level: advanced
109: Note:
110: User needs to provided appropriate routines and type for regularizer solver
112: .seealso: [](ch_tao), `Tao`, `TAOADMM`, `TaoADMMSetRegularizerType()`, `TAO_ADMM_REGULARIZER_SOFT_THRESH`
113: M*/
115: /*MC
116: TAO_ADMM_REGULARIZER_SOFT_THRESH - Soft threshold to solve regularizer part of `TAOADMM`
118: Level: advanced
120: Note:
121: Utilizes built-in SoftThreshold routines
123: .seealso: [](ch_tao), `Tao`, `TAOADMM`, `TaoSoftThreshold()`, `TaoADMMSetRegularizerObjectiveAndGradientRoutine()`,
124: `TaoADMMSetRegularizerHessianRoutine()`, `TaoADMMSetRegularizerType()`, `TAO_ADMM_REGULARIZER_USER`
125: M*/
127: /*E
128: TaoALMMType - Determine the augmented Lagrangian formulation used in the `TAOALMM` subproblem.
130: Values:
131: + `TAO_ALMM_CLASSIC` - classic augmented Lagrangian definition including slack variables for inequality constraints
132: - `TAO_ALMM_PHR` - Powell-Hestenes-Rockafellar formulation without slack variables, uses pointwise min() for inequalities
134: Level: advanced
136: .seealso: [](ch_tao), `Tao`, `TAOALMM`, `TaoALMMSetType()`, `TaoALMMGetType()`
137: E*/
138: typedef enum {
139: TAO_ALMM_CLASSIC,
140: TAO_ALMM_PHR
141: } TaoALMMType;
142: PETSC_EXTERN const char *const TaoALMMTypes[];
144: /*E
145: TaoBNCGType - Determine the conjugate gradient update formula used in the TAOBNCG algorithm.
147: Values:
148: .vb
149: TAO_BNCG_GD - basic gradient descent, no CG update
150: TAO_BNCG_PCGD - preconditioned/scaled gradient descent
151: TAO_BNCG_HS - Hestenes-Stiefel
152: TAO_BNCG_FR - Fletcher-Reeves
153: TAO_BNCG_PRP - Polak-Ribiere-Polyak (PRP)
154: TAO_BNCG_PRP_PLUS - Polak-Ribiere-Polyak "plus" (PRP+)
155: TAO_BNCG_DY - Dai-Yuan
156: TAO_BNCG_HZ - Hager-Zhang (CG_DESCENT 5.3)
157: TAO_BNCG_DK - Dai-Kou (2013)
158: TAO_BNCG_KD - Kou-Dai (2015)
159: TAO_BNCG_SSML_BFGS - Self-Scaling Memoryless BFGS (Perry-Shanno)
160: TAO_BNCG_SSML_DFP - Self-Scaling Memoryless DFP
161: TAO_BNCG_SSML_BRDN - Self-Scaling Memoryless (Symmetric) Broyden
162: .ve
163: Level: advanced
165: .seealso: `Tao`, `TAOBNCG`, `TaoBNCGSetType()`, `TaoBNCGGetType()`
166: E*/
168: typedef enum {
169: TAO_BNCG_GD,
170: TAO_BNCG_PCGD,
171: TAO_BNCG_HS,
172: TAO_BNCG_FR,
173: TAO_BNCG_PRP,
174: TAO_BNCG_PRP_PLUS,
175: TAO_BNCG_DY,
176: TAO_BNCG_HZ,
177: TAO_BNCG_DK,
178: TAO_BNCG_KD,
179: TAO_BNCG_SSML_BFGS,
180: TAO_BNCG_SSML_DFP,
181: TAO_BNCG_SSML_BRDN
182: } TaoBNCGType;
183: PETSC_EXTERN const char *const TaoBNCGTypes[];
185: /*J
186: TaoType - String with the name of a `Tao` method
188: Values:
189: + `TAONLS` - nls Newton's method with line search for unconstrained minimization
190: . `TAONTR` - ntr Newton's method with trust region for unconstrained minimization
191: . `TAONTL` - ntl Newton's method with trust region, line search for unconstrained minimization
192: . `TAOLMVM` - lmvm Limited memory variable metric method for unconstrained minimization
193: . `TAOCG` - cg Nonlinear conjugate gradient method for unconstrained minimization
194: . `TAONM` - nm Nelder-Mead algorithm for derivate-free unconstrained minimization
195: . `TAOTRON` - tron Newton Trust Region method for bound constrained minimization
196: . `TAOGPCG` - gpcg Newton Trust Region method for quadratic bound constrained minimization
197: . `TAOBLMVM` - blmvm Limited memory variable metric method for bound constrained minimization
198: . `TAOLCL` - lcl Linearly constrained Lagrangian method for pde-constrained minimization
199: - `TAOPOUNDERS` - Pounders Model-based algorithm for nonlinear least squares
201: Level: beginner
203: .seealso: [](doc_taosolve), [](ch_tao), `Tao`, `TaoCreate()`, `TaoSetType()`
204: J*/
205: typedef const char *TaoType;
206: #define TAOLMVM "lmvm"
207: #define TAONLS "nls"
208: #define TAONTR "ntr"
209: #define TAONTL "ntl"
210: #define TAOCG "cg"
211: #define TAOTRON "tron"
212: #define TAOOWLQN "owlqn"
213: #define TAOBMRM "bmrm"
214: #define TAOBLMVM "blmvm"
215: #define TAOBQNLS "bqnls"
216: #define TAOBNCG "bncg"
217: #define TAOBNLS "bnls"
218: #define TAOBNTR "bntr"
219: #define TAOBNTL "bntl"
220: #define TAOBQNKLS "bqnkls"
221: #define TAOBQNKTR "bqnktr"
222: #define TAOBQNKTL "bqnktl"
223: #define TAOBQPIP "bqpip"
224: #define TAOGPCG "gpcg"
225: #define TAONM "nm"
226: #define TAOPOUNDERS "pounders"
227: #define TAOBRGN "brgn"
228: #define TAOLCL "lcl"
229: #define TAOSSILS "ssils"
230: #define TAOSSFLS "ssfls"
231: #define TAOASILS "asils"
232: #define TAOASFLS "asfls"
233: #define TAOIPM "ipm"
234: #define TAOPDIPM "pdipm"
235: #define TAOSHELL "shell"
236: #define TAOADMM "admm"
237: #define TAOALMM "almm"
238: #define TAOPYTHON "python"
239: #define TAOSNES "snes"
241: PETSC_EXTERN PetscClassId TAO_CLASSID;
242: PETSC_EXTERN PetscFunctionList TaoList;
244: /*E
245: TaoConvergedReason - reason a `Tao` optimizer was said to have converged or diverged
247: Values:
248: + `TAO_CONVERGED_GATOL` - ||g(X)|| < gatol
249: . `TAO_CONVERGED_GRTOL` - ||g(X)|| / f(X) < grtol
250: . `TAO_CONVERGED_GTTOL` - ||g(X)|| / ||g(X0)|| < gttol
251: . `TAO_CONVERGED_STEPTOL` - step size smaller than tolerance
252: . `TAO_CONVERGED_MINF` - F < F_min
253: . `TAO_CONVERGED_USER` - the user indicates the optimization has succeeded
254: . `TAO_DIVERGED_MAXITS` - the maximum number of iterations allowed has been achieved
255: . `TAO_DIVERGED_NAN` - not a number appeared in the computations
256: . `TAO_DIVERGED_MAXFCN` - the maximum number of function evaluations has been computed
257: . `TAO_DIVERGED_LS_FAILURE` - a linesearch failed
258: . `TAO_DIVERGED_TR_REDUCTION` - trust region failure
259: . `TAO_DIVERGED_USER` - the user has indicated the optimization has failed
260: - `TAO_CONTINUE_ITERATING` - the optimization is still running, `TaoSolve()`
262: where
263: + X - current solution
264: . X0 - initial guess
265: . f(X) - current function value
266: . f(X*) - true solution (estimated)
267: . g(X) - current gradient
268: . its - current iterate number
269: . maxits - maximum number of iterates
270: . fevals - number of function evaluations
271: - max_funcsals - maximum number of function evaluations
273: Level: beginner
275: Note:
276: The two most common reasons for divergence are an incorrectly coded or computed gradient or Hessian failure or lack of convergence
277: in the linear system solve (in this case we recommend testing with `-pc_type lu` to eliminate the linear solver as the cause of the problem).
279: Developer Note:
280: The names in `KSPConvergedReason`, `SNESConvergedReason`, and `TaoConvergedReason` should be uniformized
282: .seealso: [](ch_tao), `Tao`, `TaoSolve()`, `TaoGetConvergedReason()`, `KSPConvergedReason`, `SNESConvergedReason`
283: E*/
284: typedef enum { /* converged */
285: TAO_CONVERGED_GATOL = 3, /* ||g(X)|| < gatol */
286: TAO_CONVERGED_GRTOL = 4, /* ||g(X)|| / f(X) < grtol */
287: TAO_CONVERGED_GTTOL = 5, /* ||g(X)|| / ||g(X0)|| < gttol */
288: TAO_CONVERGED_STEPTOL = 6, /* step size small */
289: TAO_CONVERGED_MINF = 7, /* F < F_min */
290: TAO_CONVERGED_USER = 8, /* User defined */
291: /* diverged */
292: TAO_DIVERGED_MAXITS = -2,
293: TAO_DIVERGED_NAN = -4,
294: TAO_DIVERGED_MAXFCN = -5,
295: TAO_DIVERGED_LS_FAILURE = -6,
296: TAO_DIVERGED_TR_REDUCTION = -7,
297: TAO_DIVERGED_USER = -8, /* User defined */
298: /* keep going */
299: TAO_CONTINUE_ITERATING = 0
300: } TaoConvergedReason;
302: PETSC_EXTERN const char **TaoConvergedReasons;
304: PETSC_EXTERN PetscErrorCode TaoInitializePackage(void);
305: PETSC_EXTERN PetscErrorCode TaoFinalizePackage(void);
306: PETSC_EXTERN PetscErrorCode TaoCreate(MPI_Comm, Tao *);
307: PETSC_EXTERN PetscErrorCode TaoSetFromOptions(Tao);
308: PETSC_EXTERN PetscErrorCode TaoSetUp(Tao);
309: PETSC_EXTERN PetscErrorCode TaoSetType(Tao, TaoType);
310: PETSC_EXTERN PetscErrorCode TaoGetType(Tao, TaoType *);
311: PETSC_EXTERN PetscErrorCode TaoSetApplicationContext(Tao, void *);
312: PETSC_EXTERN PetscErrorCode TaoGetApplicationContext(Tao, void *);
313: PETSC_EXTERN PetscErrorCode TaoDestroy(Tao *);
315: PETSC_EXTERN PetscErrorCode TaoSetOptionsPrefix(Tao, const char[]);
316: PETSC_EXTERN PetscErrorCode TaoView(Tao, PetscViewer);
317: PETSC_EXTERN PetscErrorCode TaoViewFromOptions(Tao, PetscObject, const char[]);
319: PETSC_EXTERN PetscErrorCode TaoSolve(Tao);
321: PETSC_EXTERN PetscErrorCode TaoRegister(const char[], PetscErrorCode (*)(Tao));
322: PETSC_EXTERN PetscErrorCode TaoRegisterDestroy(void);
324: PETSC_EXTERN PetscErrorCode TaoGetConvergedReason(Tao, TaoConvergedReason *);
325: PETSC_EXTERN PetscErrorCode TaoGetSolutionStatus(Tao, PetscInt *, PetscReal *, PetscReal *, PetscReal *, PetscReal *, TaoConvergedReason *);
326: PETSC_EXTERN PetscErrorCode TaoSetConvergedReason(Tao, TaoConvergedReason);
327: PETSC_EXTERN PetscErrorCode TaoSetSolution(Tao, Vec);
328: PETSC_EXTERN PetscErrorCode TaoGetSolution(Tao, Vec *);
329: PETSC_DEPRECATED_FUNCTION(3, 17, 0, "TaoSetSolution()", ) static inline PetscErrorCode TaoSetInitialVector(Tao t, Vec v)
330: {
331: return TaoSetSolution(t, v);
332: }
333: PETSC_DEPRECATED_FUNCTION(3, 17, 0, "TaoGetSolution()", ) static inline PetscErrorCode TaoGetInitialVector(Tao t, Vec *v)
334: {
335: return TaoGetSolution(t, v);
336: }
338: PETSC_EXTERN PetscErrorCode TaoSetObjective(Tao, PetscErrorCode (*)(Tao, Vec, PetscReal *, void *), void *);
339: PETSC_EXTERN PetscErrorCode TaoGetObjective(Tao, PetscErrorCode (**)(Tao, Vec, PetscReal *, void *), void **);
340: PETSC_EXTERN PetscErrorCode TaoSetGradient(Tao, Vec, PetscErrorCode (*)(Tao, Vec, Vec, void *), void *);
341: PETSC_EXTERN PetscErrorCode TaoGetGradient(Tao, Vec *, PetscErrorCode (**)(Tao, Vec, Vec, void *), void **);
342: PETSC_EXTERN PetscErrorCode TaoSetObjectiveAndGradient(Tao, Vec, PetscErrorCode (*)(Tao, Vec, PetscReal *, Vec, void *), void *);
343: PETSC_EXTERN PetscErrorCode TaoGetObjectiveAndGradient(Tao, Vec *, PetscErrorCode (**)(Tao, Vec, PetscReal *, Vec, void *), void **);
344: PETSC_EXTERN PetscErrorCode TaoSetHessian(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
345: PETSC_EXTERN PetscErrorCode TaoGetHessian(Tao, Mat *, Mat *, PetscErrorCode (**)(Tao, Vec, Mat, Mat, void *), void **);
346: PETSC_DEPRECATED_FUNCTION(3, 17, 0, "TaoSetObjective()", ) static inline PetscErrorCode TaoSetObjectiveRoutine(Tao t, PetscErrorCode (*f)(Tao, Vec, PetscReal *, void *), void *c)
347: {
348: return TaoSetObjective(t, f, c);
349: }
350: PETSC_DEPRECATED_FUNCTION(3, 17, 0, "TaoGetGradient()", ) static inline PetscErrorCode TaoGetGradientVector(Tao t, Vec *v)
351: {
352: return TaoGetGradient(t, v, PETSC_NULLPTR, PETSC_NULLPTR);
353: }
354: PETSC_DEPRECATED_FUNCTION(3, 17, 0, "TaoSetGradient()", ) static inline PetscErrorCode TaoSetGradientRoutine(Tao t, PetscErrorCode (*f)(Tao, Vec, Vec, void *), void *c)
355: {
356: return TaoSetGradient(t, PETSC_NULLPTR, f, c);
357: }
358: PETSC_DEPRECATED_FUNCTION(3, 17, 0, "TaoSetObjectiveAndGradient()", ) static inline PetscErrorCode TaoSetObjectiveAndGradientRoutine(Tao t, PetscErrorCode (*f)(Tao, Vec, PetscReal *, Vec, void *), void *c)
359: {
360: return TaoSetObjectiveAndGradient(t, PETSC_NULLPTR, f, c);
361: }
362: PETSC_DEPRECATED_FUNCTION(3, 17, 0, "TaoSetHessian()", ) static inline PetscErrorCode TaoSetHessianRoutine(Tao t, Mat H, Mat P, PetscErrorCode (*f)(Tao, Vec, Mat, Mat, void *), void *c)
363: {
364: return TaoSetHessian(t, H, P, f, c);
365: }
367: PETSC_EXTERN PetscErrorCode TaoSetGradientNorm(Tao, Mat);
368: PETSC_EXTERN PetscErrorCode TaoGetGradientNorm(Tao, Mat *);
369: PETSC_EXTERN PetscErrorCode TaoSetLMVMMatrix(Tao, Mat);
370: PETSC_EXTERN PetscErrorCode TaoGetLMVMMatrix(Tao, Mat *);
371: PETSC_EXTERN PetscErrorCode TaoSetRecycleHistory(Tao, PetscBool);
372: PETSC_EXTERN PetscErrorCode TaoGetRecycleHistory(Tao, PetscBool *);
373: PETSC_EXTERN PetscErrorCode TaoLMVMSetH0(Tao, Mat);
374: PETSC_EXTERN PetscErrorCode TaoLMVMGetH0(Tao, Mat *);
375: PETSC_EXTERN PetscErrorCode TaoLMVMGetH0KSP(Tao, KSP *);
376: PETSC_EXTERN PetscErrorCode TaoLMVMRecycle(Tao, PetscBool);
377: PETSC_EXTERN PetscErrorCode TaoSetResidualRoutine(Tao, Vec, PetscErrorCode (*)(Tao, Vec, Vec, void *), void *);
378: PETSC_EXTERN PetscErrorCode TaoSetResidualWeights(Tao, Vec, PetscInt, PetscInt *, PetscInt *, PetscReal *);
379: PETSC_EXTERN PetscErrorCode TaoSetConstraintsRoutine(Tao, Vec, PetscErrorCode (*)(Tao, Vec, Vec, void *), void *);
380: PETSC_EXTERN PetscErrorCode TaoSetInequalityConstraintsRoutine(Tao, Vec, PetscErrorCode (*)(Tao, Vec, Vec, void *), void *);
381: PETSC_EXTERN PetscErrorCode TaoSetEqualityConstraintsRoutine(Tao, Vec, PetscErrorCode (*)(Tao, Vec, Vec, void *), void *);
382: PETSC_EXTERN PetscErrorCode TaoSetJacobianResidualRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
383: PETSC_EXTERN PetscErrorCode TaoSetJacobianRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
384: PETSC_EXTERN PetscErrorCode TaoSetJacobianStateRoutine(Tao, Mat, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, Mat, void *), void *);
385: PETSC_EXTERN PetscErrorCode TaoSetJacobianDesignRoutine(Tao, Mat, PetscErrorCode (*)(Tao, Vec, Mat, void *), void *);
386: PETSC_EXTERN PetscErrorCode TaoSetJacobianInequalityRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
387: PETSC_EXTERN PetscErrorCode TaoSetJacobianEqualityRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
389: PETSC_EXTERN PetscErrorCode TaoPythonSetType(Tao, const char[]);
390: PETSC_EXTERN PetscErrorCode TaoPythonGetType(Tao, const char *[]);
392: PETSC_EXTERN PetscErrorCode TaoShellSetSolve(Tao, PetscErrorCode (*)(Tao));
393: PETSC_EXTERN PetscErrorCode TaoShellSetContext(Tao, void *);
394: PETSC_EXTERN PetscErrorCode TaoShellGetContext(Tao, void *);
396: PETSC_DEPRECATED_FUNCTION(3, 11, 0, "TaoSetResidualRoutine()", ) static inline PetscErrorCode TaoSetSeparableObjectiveRoutine(Tao tao, Vec res, PetscErrorCode (*func)(Tao, Vec, Vec, void *), void *ctx)
397: {
398: return TaoSetResidualRoutine(tao, res, func, ctx);
399: }
400: PETSC_DEPRECATED_FUNCTION(3, 11, 0, "TaoSetResidualWeights()", ) static inline PetscErrorCode TaoSetSeparableObjectiveWeights(Tao tao, Vec sigma_v, PetscInt n, PetscInt *rows, PetscInt *cols, PetscReal *vals)
401: {
402: return TaoSetResidualWeights(tao, sigma_v, n, rows, cols, vals);
403: }
405: PETSC_EXTERN PetscErrorCode TaoSetStateDesignIS(Tao, IS, IS);
407: PETSC_EXTERN PetscErrorCode TaoComputeObjective(Tao, Vec, PetscReal *);
408: PETSC_EXTERN PetscErrorCode TaoComputeResidual(Tao, Vec, Vec);
409: PETSC_EXTERN PetscErrorCode TaoTestGradient(Tao, Vec, Vec);
410: PETSC_EXTERN PetscErrorCode TaoComputeGradient(Tao, Vec, Vec);
411: PETSC_EXTERN PetscErrorCode TaoComputeObjectiveAndGradient(Tao, Vec, PetscReal *, Vec);
412: PETSC_EXTERN PetscErrorCode TaoComputeConstraints(Tao, Vec, Vec);
413: PETSC_EXTERN PetscErrorCode TaoComputeInequalityConstraints(Tao, Vec, Vec);
414: PETSC_EXTERN PetscErrorCode TaoComputeEqualityConstraints(Tao, Vec, Vec);
415: PETSC_EXTERN PetscErrorCode TaoDefaultComputeGradient(Tao, Vec, Vec, void *);
416: PETSC_EXTERN PetscErrorCode TaoIsObjectiveDefined(Tao, PetscBool *);
417: PETSC_EXTERN PetscErrorCode TaoIsGradientDefined(Tao, PetscBool *);
418: PETSC_EXTERN PetscErrorCode TaoIsObjectiveAndGradientDefined(Tao, PetscBool *);
420: PETSC_DEPRECATED_FUNCTION(3, 11, 0, "TaoComputeResidual()", ) static inline PetscErrorCode TaoComputeSeparableObjective(Tao tao, Vec X, Vec F)
421: {
422: return TaoComputeResidual(tao, X, F);
423: }
425: PETSC_EXTERN PetscErrorCode TaoTestHessian(Tao);
426: PETSC_EXTERN PetscErrorCode TaoComputeHessian(Tao, Vec, Mat, Mat);
427: PETSC_EXTERN PetscErrorCode TaoComputeResidualJacobian(Tao, Vec, Mat, Mat);
428: PETSC_EXTERN PetscErrorCode TaoComputeJacobian(Tao, Vec, Mat, Mat);
429: PETSC_EXTERN PetscErrorCode TaoComputeJacobianState(Tao, Vec, Mat, Mat, Mat);
430: PETSC_EXTERN PetscErrorCode TaoComputeJacobianEquality(Tao, Vec, Mat, Mat);
431: PETSC_EXTERN PetscErrorCode TaoComputeJacobianInequality(Tao, Vec, Mat, Mat);
432: PETSC_EXTERN PetscErrorCode TaoComputeJacobianDesign(Tao, Vec, Mat);
434: PETSC_EXTERN PetscErrorCode TaoDefaultComputeHessian(Tao, Vec, Mat, Mat, void *);
435: PETSC_EXTERN PetscErrorCode TaoDefaultComputeHessianColor(Tao, Vec, Mat, Mat, void *);
436: PETSC_EXTERN PetscErrorCode TaoDefaultComputeHessianMFFD(Tao, Vec, Mat, Mat, void *);
437: PETSC_EXTERN PetscErrorCode TaoComputeDualVariables(Tao, Vec, Vec);
438: PETSC_EXTERN PetscErrorCode TaoSetVariableBounds(Tao, Vec, Vec);
439: PETSC_EXTERN PetscErrorCode TaoGetVariableBounds(Tao, Vec *, Vec *);
440: PETSC_EXTERN PetscErrorCode TaoGetDualVariables(Tao, Vec *, Vec *);
441: PETSC_EXTERN PetscErrorCode TaoSetInequalityBounds(Tao, Vec, Vec);
442: PETSC_EXTERN PetscErrorCode TaoGetInequalityBounds(Tao, Vec *, Vec *);
443: PETSC_EXTERN PetscErrorCode TaoSetVariableBoundsRoutine(Tao, PetscErrorCode (*)(Tao, Vec, Vec, void *), void *);
444: PETSC_EXTERN PetscErrorCode TaoComputeVariableBounds(Tao);
446: PETSC_EXTERN PetscErrorCode TaoGetTolerances(Tao, PetscReal *, PetscReal *, PetscReal *);
447: PETSC_EXTERN PetscErrorCode TaoSetTolerances(Tao, PetscReal, PetscReal, PetscReal);
448: PETSC_EXTERN PetscErrorCode TaoGetConstraintTolerances(Tao, PetscReal *, PetscReal *);
449: PETSC_EXTERN PetscErrorCode TaoSetConstraintTolerances(Tao, PetscReal, PetscReal);
450: PETSC_EXTERN PetscErrorCode TaoSetFunctionLowerBound(Tao, PetscReal);
451: PETSC_EXTERN PetscErrorCode TaoSetInitialTrustRegionRadius(Tao, PetscReal);
452: PETSC_EXTERN PetscErrorCode TaoSetMaximumIterations(Tao, PetscInt);
453: PETSC_EXTERN PetscErrorCode TaoSetMaximumFunctionEvaluations(Tao, PetscInt);
454: PETSC_EXTERN PetscErrorCode TaoGetFunctionLowerBound(Tao, PetscReal *);
455: PETSC_EXTERN PetscErrorCode TaoGetInitialTrustRegionRadius(Tao, PetscReal *);
456: PETSC_EXTERN PetscErrorCode TaoGetCurrentTrustRegionRadius(Tao, PetscReal *);
457: PETSC_EXTERN PetscErrorCode TaoGetMaximumIterations(Tao, PetscInt *);
458: PETSC_EXTERN PetscErrorCode TaoGetCurrentFunctionEvaluations(Tao, PetscInt *);
459: PETSC_EXTERN PetscErrorCode TaoGetMaximumFunctionEvaluations(Tao, PetscInt *);
460: PETSC_EXTERN PetscErrorCode TaoGetIterationNumber(Tao, PetscInt *);
461: PETSC_EXTERN PetscErrorCode TaoSetIterationNumber(Tao, PetscInt);
462: PETSC_EXTERN PetscErrorCode TaoGetTotalIterationNumber(Tao, PetscInt *);
463: PETSC_EXTERN PetscErrorCode TaoSetTotalIterationNumber(Tao, PetscInt);
464: PETSC_EXTERN PetscErrorCode TaoGetResidualNorm(Tao, PetscReal *);
466: PETSC_EXTERN PetscErrorCode TaoAppendOptionsPrefix(Tao, const char[]);
467: PETSC_EXTERN PetscErrorCode TaoGetOptionsPrefix(Tao, const char *[]);
468: PETSC_EXTERN PetscErrorCode TaoResetStatistics(Tao);
469: PETSC_EXTERN PetscErrorCode TaoSetUpdate(Tao, PetscErrorCode (*)(Tao, PetscInt, void *), void *);
471: PETSC_EXTERN PetscErrorCode TaoGetKSP(Tao, KSP *);
472: PETSC_EXTERN PetscErrorCode TaoGetLinearSolveIterations(Tao, PetscInt *);
473: PETSC_EXTERN PetscErrorCode TaoKSPSetUseEW(Tao, PetscBool);
475: #include <petsctaolinesearch.h>
477: PETSC_EXTERN PetscErrorCode TaoGetLineSearch(Tao, TaoLineSearch *);
479: PETSC_EXTERN PetscErrorCode TaoSetConvergenceHistory(Tao, PetscReal *, PetscReal *, PetscReal *, PetscInt *, PetscInt, PetscBool);
480: PETSC_EXTERN PetscErrorCode TaoGetConvergenceHistory(Tao, PetscReal **, PetscReal **, PetscReal **, PetscInt **, PetscInt *);
481: PETSC_EXTERN PetscErrorCode TaoSetMonitor(Tao, PetscErrorCode (*)(Tao, void *), void *, PetscErrorCode (*)(void **));
482: PETSC_EXTERN PetscErrorCode TaoCancelMonitors(Tao);
483: PETSC_EXTERN PetscErrorCode TaoMonitorDefault(Tao, void *);
484: PETSC_DEPRECATED_FUNCTION(3, 9, 0, "TaoMonitorDefault()", ) static inline PetscErrorCode TaoDefaultMonitor(Tao tao, void *ctx)
485: {
486: return TaoMonitorDefault(tao, ctx);
487: }
488: PETSC_EXTERN PetscErrorCode TaoDefaultGMonitor(Tao, void *);
489: PETSC_EXTERN PetscErrorCode TaoDefaultSMonitor(Tao, void *);
490: PETSC_EXTERN PetscErrorCode TaoDefaultCMonitor(Tao, void *);
491: PETSC_EXTERN PetscErrorCode TaoSolutionMonitor(Tao, void *);
492: PETSC_EXTERN PetscErrorCode TaoResidualMonitor(Tao, void *);
493: PETSC_EXTERN PetscErrorCode TaoGradientMonitor(Tao, void *);
494: PETSC_EXTERN PetscErrorCode TaoStepDirectionMonitor(Tao, void *);
495: PETSC_EXTERN PetscErrorCode TaoDrawSolutionMonitor(Tao, void *);
496: PETSC_EXTERN PetscErrorCode TaoDrawStepMonitor(Tao, void *);
497: PETSC_EXTERN PetscErrorCode TaoDrawGradientMonitor(Tao, void *);
498: PETSC_EXTERN PetscErrorCode TaoAddLineSearchCounts(Tao);
500: PETSC_EXTERN PetscErrorCode TaoDefaultConvergenceTest(Tao, void *);
501: PETSC_EXTERN PetscErrorCode TaoSetConvergenceTest(Tao, PetscErrorCode (*)(Tao, void *), void *);
503: PETSC_EXTERN PetscErrorCode TaoLCLSetStateDesignIS(Tao, IS, IS);
504: PETSC_EXTERN PetscErrorCode TaoMonitor(Tao, PetscInt, PetscReal, PetscReal, PetscReal, PetscReal);
505: typedef struct _n_TaoMonitorDrawCtx *TaoMonitorDrawCtx;
506: PETSC_EXTERN PetscErrorCode TaoMonitorDrawCtxCreate(MPI_Comm, const char[], const char[], int, int, int, int, PetscInt, TaoMonitorDrawCtx *);
507: PETSC_EXTERN PetscErrorCode TaoMonitorDrawCtxDestroy(TaoMonitorDrawCtx *);
509: PETSC_EXTERN PetscErrorCode TaoBRGNGetSubsolver(Tao, Tao *);
510: PETSC_EXTERN PetscErrorCode TaoBRGNSetRegularizerObjectiveAndGradientRoutine(Tao, PetscErrorCode (*)(Tao, Vec, PetscReal *, Vec, void *), void *);
511: PETSC_EXTERN PetscErrorCode TaoBRGNSetRegularizerHessianRoutine(Tao, Mat, PetscErrorCode (*)(Tao, Vec, Mat, void *), void *);
512: PETSC_EXTERN PetscErrorCode TaoBRGNSetRegularizerWeight(Tao, PetscReal);
513: PETSC_EXTERN PetscErrorCode TaoBRGNSetL1SmoothEpsilon(Tao, PetscReal);
514: PETSC_EXTERN PetscErrorCode TaoBRGNSetDictionaryMatrix(Tao, Mat);
515: PETSC_EXTERN PetscErrorCode TaoBRGNGetDampingVector(Tao, Vec *);
516: PETSC_EXTERN PetscErrorCode TaoBNCGSetType(Tao, TaoBNCGType);
517: PETSC_EXTERN PetscErrorCode TaoBNCGGetType(Tao, TaoBNCGType *);
519: PETSC_EXTERN PetscErrorCode TaoADMMGetMisfitSubsolver(Tao, Tao *);
520: PETSC_EXTERN PetscErrorCode TaoADMMGetRegularizationSubsolver(Tao, Tao *);
521: PETSC_EXTERN PetscErrorCode TaoADMMGetDualVector(Tao, Vec *);
522: PETSC_EXTERN PetscErrorCode TaoADMMGetSpectralPenalty(Tao, PetscReal *);
523: PETSC_EXTERN PetscErrorCode TaoADMMSetSpectralPenalty(Tao, PetscReal);
524: PETSC_EXTERN PetscErrorCode TaoGetADMMParentTao(Tao, Tao *);
525: PETSC_EXTERN PetscErrorCode TaoADMMSetConstraintVectorRHS(Tao, Vec);
526: PETSC_EXTERN PetscErrorCode TaoADMMSetRegularizerCoefficient(Tao, PetscReal);
527: PETSC_EXTERN PetscErrorCode TaoADMMGetRegularizerCoefficient(Tao, PetscReal *);
528: PETSC_EXTERN PetscErrorCode TaoADMMSetMisfitConstraintJacobian(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
529: PETSC_EXTERN PetscErrorCode TaoADMMSetRegularizerConstraintJacobian(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
530: PETSC_EXTERN PetscErrorCode TaoADMMSetRegularizerHessianRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
531: PETSC_EXTERN PetscErrorCode TaoADMMSetRegularizerObjectiveAndGradientRoutine(Tao, PetscErrorCode (*)(Tao, Vec, PetscReal *, Vec, void *), void *);
532: PETSC_EXTERN PetscErrorCode TaoADMMSetMisfitHessianRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
533: PETSC_EXTERN PetscErrorCode TaoADMMSetMisfitObjectiveAndGradientRoutine(Tao, PetscErrorCode (*)(Tao, Vec, PetscReal *, Vec, void *), void *);
534: PETSC_EXTERN PetscErrorCode TaoADMMSetMisfitHessianChangeStatus(Tao, PetscBool);
535: PETSC_EXTERN PetscErrorCode TaoADMMSetRegHessianChangeStatus(Tao, PetscBool);
536: PETSC_EXTERN PetscErrorCode TaoADMMSetMinimumSpectralPenalty(Tao, PetscReal);
537: PETSC_EXTERN PetscErrorCode TaoADMMSetRegularizerType(Tao, TaoADMMRegularizerType);
538: PETSC_EXTERN PetscErrorCode TaoADMMGetRegularizerType(Tao, TaoADMMRegularizerType *);
539: PETSC_EXTERN PetscErrorCode TaoADMMSetUpdateType(Tao, TaoADMMUpdateType);
540: PETSC_EXTERN PetscErrorCode TaoADMMGetUpdateType(Tao, TaoADMMUpdateType *);
542: PETSC_EXTERN PetscErrorCode TaoALMMGetType(Tao, TaoALMMType *);
543: PETSC_EXTERN PetscErrorCode TaoALMMSetType(Tao, TaoALMMType);
544: PETSC_EXTERN PetscErrorCode TaoALMMGetSubsolver(Tao, Tao *);
545: PETSC_EXTERN PetscErrorCode TaoALMMSetSubsolver(Tao, Tao);
546: PETSC_EXTERN PetscErrorCode TaoALMMGetMultipliers(Tao, Vec *);
547: PETSC_EXTERN PetscErrorCode TaoALMMSetMultipliers(Tao, Vec);
548: PETSC_EXTERN PetscErrorCode TaoALMMGetPrimalIS(Tao, IS *, IS *);
549: PETSC_EXTERN PetscErrorCode TaoALMMGetDualIS(Tao, IS *, IS *);
551: PETSC_EXTERN PetscErrorCode TaoVecGetSubVec(Vec, IS, TaoSubsetType, PetscReal, Vec *);
552: PETSC_EXTERN PetscErrorCode TaoMatGetSubMat(Mat, IS, Vec, TaoSubsetType, Mat *);
553: PETSC_EXTERN PetscErrorCode TaoGradientNorm(Tao, Vec, NormType, PetscReal *);
554: PETSC_EXTERN PetscErrorCode TaoEstimateActiveBounds(Vec, Vec, Vec, Vec, Vec, Vec, PetscReal, PetscReal *, IS *, IS *, IS *, IS *, IS *);
555: PETSC_EXTERN PetscErrorCode TaoBoundStep(Vec, Vec, Vec, IS, IS, IS, PetscReal, Vec);
556: PETSC_EXTERN PetscErrorCode TaoBoundSolution(Vec, Vec, Vec, PetscReal, PetscInt *, Vec);