xref: /petsc/include/petsctao.h (revision 1b4e8d383929f90da10c6216833dd32b321a83f9)
1 #pragma once
2 
3 #include <petscsnes.h>
4 
5 /* SUBMANSEC = Tao */
6 
7 PETSC_EXTERN PetscErrorCode MatDSFischer(Mat, Vec, Vec, Vec, Vec, PetscReal, Vec, Vec, Vec, Vec, Vec);
8 PETSC_EXTERN PetscErrorCode TaoSoftThreshold(Vec, PetscReal, PetscReal, Vec);
9 
10 /*E
11   TaoSubsetType - Type representing the way the `Tao` solvers handle active sets
12 
13   Values:
14 + `TAO_SUBSET_SUBVEC`     - Tao uses `MatCreateSubMatrix()` and `VecGetSubVector()`
15 . `TAO_SUBSET_MASK`       - Matrices are zeroed out corresponding to active set entries
16 - `TAO_SUBSET_MATRIXFREE` - Same as `TAO_SUBSET_MASK` but it can be applied to matrix-free operators
17 
18   Options database Key:
19 . -different_hessian - `Tao` will use a copy of the Hessian operator for masking.  By default `Tao` will directly alter the Hessian operator.
20 
21   Level: intermediate
22 
23 .seealso: [](ch_tao), `TaoVecGetSubVec()`, `TaoMatGetSubMat()`, `Tao`, `TaoCreate()`, `TaoDestroy()`, `TaoSetType()`, `TaoType`
24 E*/
25 typedef enum {
26   TAO_SUBSET_SUBVEC,
27   TAO_SUBSET_MASK,
28   TAO_SUBSET_MATRIXFREE
29 } TaoSubsetType;
30 PETSC_EXTERN const char *const TaoSubsetTypes[];
31 
32 /*S
33    Tao - Abstract PETSc object that manages optimization solvers.
34 
35    Level: advanced
36 
37    Note:
38    `Tao` is the object, while TAO, which stands for Toolkit for Advanced Optimization, is the software package.
39 
40 .seealso: [](doc_taosolve), [](ch_tao), `TaoCreate()`, `TaoDestroy()`, `TaoSetType()`, `TaoType`
41 S*/
42 typedef struct _p_Tao *Tao;
43 
44 /*E
45   TaoADMMUpdateType - Determine the spectral penalty update routine for the Lagrange augmented term for `TAOADMM`.
46 
47   Level: advanced
48 
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[];
57 
58 /*MC
59   TAO_ADMM_UPDATE_BASIC - Use same spectral penalty set at the beginning. This never performs an update to the penalty
60 
61   Level: advanced
62 
63   Note:
64   Most basic implementation of `TAOADMM`. Generally slower than adaptive or adaptive relaxed version.
65 
66 .seealso: [](ch_tao), `Tao`, `TAOADMM`, `TaoADMMSetUpdateType()`, `TAO_ADMM_UPDATE_ADAPTIVE`, `TAO_ADMM_UPDATE_ADAPTIVE_RELAXED`
67 M*/
68 
69 /*MC
70   TAO_ADMM_UPDATE_ADAPTIVE - Adaptively update the spectral penalty
71 
72   Level: advanced
73 
74   Note:
75   Adaptively updates spectral penalty of `TAOADMM` by using both steepest descent and minimum gradient.
76 
77 .seealso: [](ch_tao), `Tao`, `TAOADMM`, `TaoADMMSetUpdateType()`, `TAO_ADMM_UPDATE_BASIC`, `TAO_ADMM_UPDATE_ADAPTIVE_RELAXED`
78 M*/
79 
80 /*MC
81   ADMM_UPDATE_ADAPTIVE_RELAXED - Adaptively update spectral penalty, and relaxes parameter update
82 
83   Level: advanced
84 
85   Note:
86   With adaptive spectral penalty update, it also relaxes the `x` vector update by a factor.
87 
88 .seealso: [](ch_tao), `Tao`, `TaoADMMSetUpdateType()`, `TAO_ADMM_UPDATE_BASIC`, `TAO_ADMM_UPDATE_ADAPTIVE`
89 M*/
90 
91 /*E
92   TaoADMMRegularizerType - Determine regularizer routine - either user provided or soft threshold for `TAOADMM`
93 
94   Level: advanced
95 
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[];
103 
104 /*MC
105   TAO_ADMM_REGULARIZER_USER - User provided routines for regularizer part of `TAOADMM`
106 
107   Level: advanced
108 
109   Note:
110   User needs to provided appropriate routines and type for regularizer solver
111 
112 .seealso: [](ch_tao), `Tao`, `TAOADMM`, `TaoADMMSetRegularizerType()`, `TAO_ADMM_REGULARIZER_SOFT_THRESH`
113 M*/
114 
115 /*MC
116   TAO_ADMM_REGULARIZER_SOFT_THRESH - Soft threshold to solve regularizer part of `TAOADMM`
117 
118   Level: advanced
119 
120   Note:
121   Utilizes built-in SoftThreshold routines
122 
123 .seealso: [](ch_tao), `Tao`, `TAOADMM`, `TaoSoftThreshold()`, `TaoADMMSetRegularizerObjectiveAndGradientRoutine()`,
124           `TaoADMMSetRegularizerHessianRoutine()`, `TaoADMMSetRegularizerType()`, `TAO_ADMM_REGULARIZER_USER`
125 M*/
126 
127 /*E
128    TaoALMMType - Determine the augmented Lagrangian formulation used in the `TAOALMM` subproblem.
129 
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
133 
134   Level: advanced
135 
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[];
143 
144 /*E
145   TaoBNCGType - Determine the conjugate gradient update formula used in the `TAOBNCG` algorithm.
146 
147   Values:
148 +  `TAO_BNCG_GD`         - basic gradient descent, no CG update
149 .  `TAO_BNCG_PCGD`       - preconditioned/scaled gradient descent
150 .  `TAO_BNCG_HS`         - Hestenes-Stiefel
151 .  `TAO_BNCG_FR`         - Fletcher-Reeves
152 .  `TAO_BNCG_PRP`        - Polak-Ribiere-Polyak (PRP)
153 .  `TAO_BNCG_PRP_PLUS`   - Polak-Ribiere-Polyak "plus" (PRP+)
154 .  `TAO_BNCG_DY`         - Dai-Yuan
155 .  `TAO_BNCG_HZ`         - Hager-Zhang (CG_DESCENT 5.3)
156 .  `TAO_BNCG_DK`         - Dai-Kou (2013)
157 .  `TAO_BNCG_KD`         - Kou-Dai (2015)
158 .  `TAO_BNCG_SSML_BFGS`  - Self-Scaling Memoryless BFGS (Perry-Shanno)
159 .  `TAO_BNCG_SSML_DFP`   - Self-Scaling Memoryless DFP
160 -  `TAO_BNCG_SSML_BRDN`  - Self-Scaling Memoryless (Symmetric) Broyden
161 
162   Level: advanced
163 
164 .seealso: `Tao`, `TAOBNCG`, `TaoBNCGSetType()`, `TaoBNCGGetType()`
165 E*/
166 
167 typedef enum {
168   TAO_BNCG_GD,
169   TAO_BNCG_PCGD,
170   TAO_BNCG_HS,
171   TAO_BNCG_FR,
172   TAO_BNCG_PRP,
173   TAO_BNCG_PRP_PLUS,
174   TAO_BNCG_DY,
175   TAO_BNCG_HZ,
176   TAO_BNCG_DK,
177   TAO_BNCG_KD,
178   TAO_BNCG_SSML_BFGS,
179   TAO_BNCG_SSML_DFP,
180   TAO_BNCG_SSML_BRDN
181 } TaoBNCGType;
182 PETSC_EXTERN const char *const TaoBNCGTypes[];
183 
184 /*J
185   TaoType - String with the name of a `Tao` method
186 
187   Values:
188 + `TAONLS`      - nls Newton's method with line search for unconstrained minimization
189 . `TAONTR`      - ntr Newton's method with trust region for unconstrained minimization
190 . `TAONTL`      - ntl Newton's method with trust region, line search for unconstrained minimization
191 . `TAOLMVM`     - lmvm Limited memory variable metric method for unconstrained minimization
192 . `TAOCG`       - cg Nonlinear conjugate gradient method for unconstrained minimization
193 . `TAONM`       - nm Nelder-Mead algorithm for derivate-free unconstrained minimization
194 . `TAOTRON`     - tron Newton Trust Region method for bound constrained minimization
195 . `TAOGPCG`     - gpcg Newton Trust Region method for quadratic bound constrained minimization
196 . `TAOBLMVM`    - blmvm Limited memory variable metric method for bound constrained minimization
197 . `TAOLCL`      - lcl Linearly constrained Lagrangian method for pde-constrained minimization
198 - `TAOPOUNDERS` - Pounders Model-based algorithm for nonlinear least squares
199 
200   Level: beginner
201 
202 .seealso: [](doc_taosolve), [](ch_tao), `Tao`, `TaoCreate()`, `TaoSetType()`
203 J*/
204 typedef const char *TaoType;
205 #define TAOLMVM     "lmvm"
206 #define TAONLS      "nls"
207 #define TAONTR      "ntr"
208 #define TAONTL      "ntl"
209 #define TAOCG       "cg"
210 #define TAOTRON     "tron"
211 #define TAOOWLQN    "owlqn"
212 #define TAOBMRM     "bmrm"
213 #define TAOBLMVM    "blmvm"
214 #define TAOBQNLS    "bqnls"
215 #define TAOBNCG     "bncg"
216 #define TAOBNLS     "bnls"
217 #define TAOBNTR     "bntr"
218 #define TAOBNTL     "bntl"
219 #define TAOBQNKLS   "bqnkls"
220 #define TAOBQNKTR   "bqnktr"
221 #define TAOBQNKTL   "bqnktl"
222 #define TAOBQPIP    "bqpip"
223 #define TAOGPCG     "gpcg"
224 #define TAONM       "nm"
225 #define TAOPOUNDERS "pounders"
226 #define TAOBRGN     "brgn"
227 #define TAOLCL      "lcl"
228 #define TAOSSILS    "ssils"
229 #define TAOSSFLS    "ssfls"
230 #define TAOASILS    "asils"
231 #define TAOASFLS    "asfls"
232 #define TAOIPM      "ipm"
233 #define TAOPDIPM    "pdipm"
234 #define TAOSHELL    "shell"
235 #define TAOADMM     "admm"
236 #define TAOALMM     "almm"
237 #define TAOPYTHON   "python"
238 #define TAOSNES     "snes"
239 
240 PETSC_EXTERN PetscClassId      TAO_CLASSID;
241 PETSC_EXTERN PetscFunctionList TaoList;
242 
243 /*E
244     TaoConvergedReason - reason a `Tao` optimizer was said to have converged or diverged
245 
246    Values:
247 +  `TAO_CONVERGED_GATOL`       - $||g(X)|| < gatol$
248 .  `TAO_CONVERGED_GRTOL`       - $||g(X)|| / f(X)  < grtol$
249 .  `TAO_CONVERGED_GTTOL`       - $||g(X)|| / ||g(X0)|| < gttol$
250 .  `TAO_CONVERGED_STEPTOL`     - step size smaller than tolerance
251 .  `TAO_CONVERGED_MINF`        - $F < F_min$
252 .  `TAO_CONVERGED_USER`        - the user indicates the optimization has succeeded
253 .  `TAO_DIVERGED_MAXITS`       - the maximum number of iterations allowed has been achieved
254 .  `TAO_DIVERGED_NAN`          - not a number appeared in the computations
255 .  `TAO_DIVERGED_MAXFCN`       - the maximum number of function evaluations has been computed
256 .  `TAO_DIVERGED_LS_FAILURE`   - a linesearch failed
257 .  `TAO_DIVERGED_TR_REDUCTION` - trust region failure
258 .  `TAO_DIVERGED_USER`         - the user has indicated the optimization has failed
259 -  `TAO_CONTINUE_ITERATING`    - the optimization is still running, `TaoSolve()`
260 
261    where
262 +  X            - current solution
263 .  X0           - initial guess
264 .  f(X)         - current function value
265 .  f(X*)        - true solution (estimated)
266 .  g(X)         - current gradient
267 .  its          - current iterate number
268 .  maxits       - maximum number of iterates
269 .  fevals       - number of function evaluations
270 -  max_funcsals - maximum number of function evaluations
271 
272    Level: beginner
273 
274    Note:
275    The two most common reasons for divergence are  an incorrectly coded or computed gradient or Hessian failure or lack of convergence
276    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).
277 
278    Developer Note:
279    The names in `KSPConvergedReason`, `SNESConvergedReason`, and `TaoConvergedReason` should be uniformized
280 
281 .seealso: [](ch_tao), `Tao`, `TaoSolve()`, `TaoGetConvergedReason()`, `KSPConvergedReason`, `SNESConvergedReason`
282 E*/
283 typedef enum {               /* converged */
284   TAO_CONVERGED_GATOL   = 3, /* ||g(X)|| < gatol */
285   TAO_CONVERGED_GRTOL   = 4, /* ||g(X)|| / f(X)  < grtol */
286   TAO_CONVERGED_GTTOL   = 5, /* ||g(X)|| / ||g(X0)|| < gttol */
287   TAO_CONVERGED_STEPTOL = 6, /* step size small */
288   TAO_CONVERGED_MINF    = 7, /* F < F_min */
289   TAO_CONVERGED_USER    = 8, /* User defined */
290   /* diverged */
291   TAO_DIVERGED_MAXITS       = -2,
292   TAO_DIVERGED_NAN          = -4,
293   TAO_DIVERGED_MAXFCN       = -5,
294   TAO_DIVERGED_LS_FAILURE   = -6,
295   TAO_DIVERGED_TR_REDUCTION = -7,
296   TAO_DIVERGED_USER         = -8, /* User defined */
297   /* keep going */
298   TAO_CONTINUE_ITERATING = 0
299 } TaoConvergedReason;
300 
301 PETSC_EXTERN const char **TaoConvergedReasons;
302 
303 PETSC_EXTERN PetscErrorCode TaoInitializePackage(void);
304 PETSC_EXTERN PetscErrorCode TaoFinalizePackage(void);
305 PETSC_EXTERN PetscErrorCode TaoCreate(MPI_Comm, Tao *);
306 PETSC_EXTERN PetscErrorCode TaoSetFromOptions(Tao);
307 PETSC_EXTERN PetscErrorCode TaoSetUp(Tao);
308 PETSC_EXTERN PetscErrorCode TaoSetType(Tao, TaoType);
309 PETSC_EXTERN PetscErrorCode TaoGetType(Tao, TaoType *);
310 PETSC_EXTERN PetscErrorCode TaoSetApplicationContext(Tao, void *);
311 PETSC_EXTERN PetscErrorCode TaoGetApplicationContext(Tao, void *);
312 PETSC_EXTERN PetscErrorCode TaoDestroy(Tao *);
313 PETSC_EXTERN PetscErrorCode TaoParametersInitialize(Tao);
314 
315 PETSC_EXTERN PetscErrorCode TaoSetOptionsPrefix(Tao, const char[]);
316 PETSC_EXTERN PetscErrorCode TaoView(Tao, PetscViewer);
317 PETSC_EXTERN PetscErrorCode TaoViewFromOptions(Tao, PetscObject, const char[]);
318 
319 PETSC_EXTERN PetscErrorCode TaoSolve(Tao);
320 
321 PETSC_EXTERN PetscErrorCode TaoRegister(const char[], PetscErrorCode (*)(Tao));
322 PETSC_EXTERN PetscErrorCode TaoRegisterDestroy(void);
323 
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 
330 PETSC_EXTERN PetscErrorCode TaoSetObjective(Tao, PetscErrorCode (*)(Tao, Vec, PetscReal *, void *), void *);
331 PETSC_EXTERN PetscErrorCode TaoGetObjective(Tao, PetscErrorCode (**)(Tao, Vec, PetscReal *, void *), void **);
332 PETSC_EXTERN PetscErrorCode TaoSetGradient(Tao, Vec, PetscErrorCode (*)(Tao, Vec, Vec, void *), void *);
333 PETSC_EXTERN PetscErrorCode TaoGetGradient(Tao, Vec *, PetscErrorCode (**)(Tao, Vec, Vec, void *), void **);
334 PETSC_EXTERN PetscErrorCode TaoSetObjectiveAndGradient(Tao, Vec, PetscErrorCode (*)(Tao, Vec, PetscReal *, Vec, void *), void *);
335 PETSC_EXTERN PetscErrorCode TaoGetObjectiveAndGradient(Tao, Vec *, PetscErrorCode (**)(Tao, Vec, PetscReal *, Vec, void *), void **);
336 PETSC_EXTERN PetscErrorCode TaoSetHessian(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
337 PETSC_EXTERN PetscErrorCode TaoGetHessian(Tao, Mat *, Mat *, PetscErrorCode (**)(Tao, Vec, Mat, Mat, void *), void **);
338 
339 PETSC_EXTERN PetscErrorCode TaoSetGradientNorm(Tao, Mat);
340 PETSC_EXTERN PetscErrorCode TaoGetGradientNorm(Tao, Mat *);
341 PETSC_EXTERN PetscErrorCode TaoSetLMVMMatrix(Tao, Mat);
342 PETSC_EXTERN PetscErrorCode TaoGetLMVMMatrix(Tao, Mat *);
343 PETSC_EXTERN PetscErrorCode TaoSetRecycleHistory(Tao, PetscBool);
344 PETSC_EXTERN PetscErrorCode TaoGetRecycleHistory(Tao, PetscBool *);
345 PETSC_EXTERN PetscErrorCode TaoLMVMSetH0(Tao, Mat);
346 PETSC_EXTERN PetscErrorCode TaoLMVMGetH0(Tao, Mat *);
347 PETSC_EXTERN PetscErrorCode TaoLMVMGetH0KSP(Tao, KSP *);
348 PETSC_EXTERN PetscErrorCode TaoLMVMRecycle(Tao, PetscBool);
349 PETSC_EXTERN PetscErrorCode TaoSetResidualRoutine(Tao, Vec, PetscErrorCode (*)(Tao, Vec, Vec, void *), void *);
350 PETSC_EXTERN PetscErrorCode TaoSetResidualWeights(Tao, Vec, PetscInt, PetscInt *, PetscInt *, PetscReal *);
351 PETSC_EXTERN PetscErrorCode TaoSetConstraintsRoutine(Tao, Vec, PetscErrorCode (*)(Tao, Vec, Vec, void *), void *);
352 PETSC_EXTERN PetscErrorCode TaoSetInequalityConstraintsRoutine(Tao, Vec, PetscErrorCode (*)(Tao, Vec, Vec, void *), void *);
353 PETSC_EXTERN PetscErrorCode TaoGetInequalityConstraintsRoutine(Tao, Vec *, PetscErrorCode (**)(Tao, Vec, Vec, void *), void **);
354 PETSC_EXTERN PetscErrorCode TaoSetEqualityConstraintsRoutine(Tao, Vec, PetscErrorCode (*)(Tao, Vec, Vec, void *), void *);
355 PETSC_EXTERN PetscErrorCode TaoGetEqualityConstraintsRoutine(Tao, Vec *, PetscErrorCode (**)(Tao, Vec, Vec, void *), void **);
356 PETSC_EXTERN PetscErrorCode TaoSetJacobianResidualRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
357 PETSC_EXTERN PetscErrorCode TaoSetJacobianRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
358 PETSC_EXTERN PetscErrorCode TaoSetJacobianStateRoutine(Tao, Mat, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, Mat, void *), void *);
359 PETSC_EXTERN PetscErrorCode TaoSetJacobianDesignRoutine(Tao, Mat, PetscErrorCode (*)(Tao, Vec, Mat, void *), void *);
360 PETSC_EXTERN PetscErrorCode TaoSetJacobianInequalityRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
361 PETSC_EXTERN PetscErrorCode TaoSetJacobianEqualityRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
362 
363 PETSC_EXTERN PetscErrorCode TaoPythonSetType(Tao, const char[]);
364 PETSC_EXTERN PetscErrorCode TaoPythonGetType(Tao, const char *[]);
365 
366 PETSC_EXTERN PetscErrorCode TaoShellSetSolve(Tao, PetscErrorCode (*)(Tao));
367 PETSC_EXTERN PetscErrorCode TaoShellSetContext(Tao, void *);
368 PETSC_EXTERN PetscErrorCode TaoShellGetContext(Tao, void *);
369 
370 PETSC_EXTERN PetscErrorCode TaoSetStateDesignIS(Tao, IS, IS);
371 
372 PETSC_EXTERN PetscErrorCode TaoComputeObjective(Tao, Vec, PetscReal *);
373 PETSC_EXTERN PetscErrorCode TaoComputeResidual(Tao, Vec, Vec);
374 PETSC_EXTERN PetscErrorCode TaoTestGradient(Tao, Vec, Vec);
375 PETSC_EXTERN PetscErrorCode TaoComputeGradient(Tao, Vec, Vec);
376 PETSC_EXTERN PetscErrorCode TaoComputeObjectiveAndGradient(Tao, Vec, PetscReal *, Vec);
377 PETSC_EXTERN PetscErrorCode TaoComputeConstraints(Tao, Vec, Vec);
378 PETSC_EXTERN PetscErrorCode TaoComputeInequalityConstraints(Tao, Vec, Vec);
379 PETSC_EXTERN PetscErrorCode TaoComputeEqualityConstraints(Tao, Vec, Vec);
380 PETSC_EXTERN PetscErrorCode TaoDefaultComputeGradient(Tao, Vec, Vec, void *);
381 PETSC_EXTERN PetscErrorCode TaoIsObjectiveDefined(Tao, PetscBool *);
382 PETSC_EXTERN PetscErrorCode TaoIsGradientDefined(Tao, PetscBool *);
383 PETSC_EXTERN PetscErrorCode TaoIsObjectiveAndGradientDefined(Tao, PetscBool *);
384 
385 PETSC_EXTERN PetscErrorCode TaoTestHessian(Tao);
386 PETSC_EXTERN PetscErrorCode TaoComputeHessian(Tao, Vec, Mat, Mat);
387 PETSC_EXTERN PetscErrorCode TaoComputeResidualJacobian(Tao, Vec, Mat, Mat);
388 PETSC_EXTERN PetscErrorCode TaoComputeJacobian(Tao, Vec, Mat, Mat);
389 PETSC_EXTERN PetscErrorCode TaoComputeJacobianState(Tao, Vec, Mat, Mat, Mat);
390 PETSC_EXTERN PetscErrorCode TaoComputeJacobianEquality(Tao, Vec, Mat, Mat);
391 PETSC_EXTERN PetscErrorCode TaoComputeJacobianInequality(Tao, Vec, Mat, Mat);
392 PETSC_EXTERN PetscErrorCode TaoComputeJacobianDesign(Tao, Vec, Mat);
393 
394 PETSC_EXTERN PetscErrorCode TaoDefaultComputeHessian(Tao, Vec, Mat, Mat, void *);
395 PETSC_EXTERN PetscErrorCode TaoDefaultComputeHessianColor(Tao, Vec, Mat, Mat, void *);
396 PETSC_EXTERN PetscErrorCode TaoDefaultComputeHessianMFFD(Tao, Vec, Mat, Mat, void *);
397 PETSC_EXTERN PetscErrorCode TaoComputeDualVariables(Tao, Vec, Vec);
398 PETSC_EXTERN PetscErrorCode TaoSetVariableBounds(Tao, Vec, Vec);
399 PETSC_EXTERN PetscErrorCode TaoGetVariableBounds(Tao, Vec *, Vec *);
400 PETSC_EXTERN PetscErrorCode TaoGetDualVariables(Tao, Vec *, Vec *);
401 PETSC_EXTERN PetscErrorCode TaoSetInequalityBounds(Tao, Vec, Vec);
402 PETSC_EXTERN PetscErrorCode TaoGetInequalityBounds(Tao, Vec *, Vec *);
403 PETSC_EXTERN PetscErrorCode TaoSetVariableBoundsRoutine(Tao, PetscErrorCode (*)(Tao, Vec, Vec, void *), void *);
404 PETSC_EXTERN PetscErrorCode TaoComputeVariableBounds(Tao);
405 
406 PETSC_EXTERN PetscErrorCode TaoGetTolerances(Tao, PetscReal *, PetscReal *, PetscReal *);
407 PETSC_EXTERN PetscErrorCode TaoSetTolerances(Tao, PetscReal, PetscReal, PetscReal);
408 PETSC_EXTERN PetscErrorCode TaoGetConstraintTolerances(Tao, PetscReal *, PetscReal *);
409 PETSC_EXTERN PetscErrorCode TaoSetConstraintTolerances(Tao, PetscReal, PetscReal);
410 PETSC_EXTERN PetscErrorCode TaoSetFunctionLowerBound(Tao, PetscReal);
411 PETSC_EXTERN PetscErrorCode TaoSetInitialTrustRegionRadius(Tao, PetscReal);
412 PETSC_EXTERN PetscErrorCode TaoSetMaximumIterations(Tao, PetscInt);
413 PETSC_EXTERN PetscErrorCode TaoSetMaximumFunctionEvaluations(Tao, PetscInt);
414 PETSC_EXTERN PetscErrorCode TaoGetFunctionLowerBound(Tao, PetscReal *);
415 PETSC_EXTERN PetscErrorCode TaoGetInitialTrustRegionRadius(Tao, PetscReal *);
416 PETSC_EXTERN PetscErrorCode TaoGetCurrentTrustRegionRadius(Tao, PetscReal *);
417 PETSC_EXTERN PetscErrorCode TaoGetMaximumIterations(Tao, PetscInt *);
418 PETSC_EXTERN PetscErrorCode TaoGetCurrentFunctionEvaluations(Tao, PetscInt *);
419 PETSC_EXTERN PetscErrorCode TaoGetMaximumFunctionEvaluations(Tao, PetscInt *);
420 PETSC_EXTERN PetscErrorCode TaoGetIterationNumber(Tao, PetscInt *);
421 PETSC_EXTERN PetscErrorCode TaoSetIterationNumber(Tao, PetscInt);
422 PETSC_EXTERN PetscErrorCode TaoGetTotalIterationNumber(Tao, PetscInt *);
423 PETSC_EXTERN PetscErrorCode TaoSetTotalIterationNumber(Tao, PetscInt);
424 PETSC_EXTERN PetscErrorCode TaoGetResidualNorm(Tao, PetscReal *);
425 
426 PETSC_EXTERN PetscErrorCode TaoAppendOptionsPrefix(Tao, const char[]);
427 PETSC_EXTERN PetscErrorCode TaoGetOptionsPrefix(Tao, const char *[]);
428 PETSC_EXTERN PetscErrorCode TaoResetStatistics(Tao);
429 PETSC_EXTERN PetscErrorCode TaoSetUpdate(Tao, PetscErrorCode (*)(Tao, PetscInt, void *), void *);
430 
431 PETSC_EXTERN PetscErrorCode TaoGetKSP(Tao, KSP *);
432 PETSC_EXTERN PetscErrorCode TaoGetLinearSolveIterations(Tao, PetscInt *);
433 PETSC_EXTERN PetscErrorCode TaoKSPSetUseEW(Tao, PetscBool);
434 
435 #include <petsctaolinesearch.h>
436 
437 PETSC_EXTERN PetscErrorCode TaoGetLineSearch(Tao, TaoLineSearch *);
438 
439 PETSC_EXTERN PetscErrorCode TaoSetConvergenceHistory(Tao, PetscReal *, PetscReal *, PetscReal *, PetscInt *, PetscInt, PetscBool);
440 PETSC_EXTERN PetscErrorCode TaoGetConvergenceHistory(Tao, PetscReal **, PetscReal **, PetscReal **, PetscInt **, PetscInt *);
441 PETSC_EXTERN PetscErrorCode TaoMonitorSet(Tao, PetscErrorCode (*)(Tao, void *), void *, PetscCtxDestroyFn *);
442 PETSC_EXTERN PetscErrorCode TaoMonitorCancel(Tao);
443 PETSC_EXTERN PetscErrorCode TaoMonitorDefault(Tao, void *);
444 PETSC_EXTERN PetscErrorCode TaoMonitorGlobalization(Tao, void *);
445 PETSC_EXTERN PetscErrorCode TaoMonitorDefaultShort(Tao, void *);
446 PETSC_EXTERN PetscErrorCode TaoMonitorConstraintNorm(Tao, void *);
447 PETSC_EXTERN PetscErrorCode TaoMonitorSolution(Tao, void *);
448 PETSC_EXTERN PetscErrorCode TaoMonitorResidual(Tao, void *);
449 PETSC_EXTERN PetscErrorCode TaoMonitorGradient(Tao, void *);
450 PETSC_EXTERN PetscErrorCode TaoMonitorStep(Tao, void *);
451 PETSC_EXTERN PetscErrorCode TaoMonitorSolutionDraw(Tao, void *);
452 PETSC_EXTERN PetscErrorCode TaoMonitorStepDraw(Tao, void *);
453 PETSC_EXTERN PetscErrorCode TaoMonitorGradientDraw(Tao, void *);
454 PETSC_EXTERN PetscErrorCode TaoAddLineSearchCounts(Tao);
455 
456 PETSC_EXTERN PetscErrorCode TaoDefaultConvergenceTest(Tao, void *);
457 PETSC_EXTERN PetscErrorCode TaoSetConvergenceTest(Tao, PetscErrorCode (*)(Tao, void *), void *);
458 
459 PETSC_EXTERN PetscErrorCode          TaoLCLSetStateDesignIS(Tao, IS, IS);
460 PETSC_EXTERN PetscErrorCode          TaoMonitor(Tao, PetscInt, PetscReal, PetscReal, PetscReal, PetscReal);
461 typedef struct _n_TaoMonitorDrawCtx *TaoMonitorDrawCtx;
462 PETSC_EXTERN PetscErrorCode          TaoMonitorDrawCtxCreate(MPI_Comm, const char[], const char[], int, int, int, int, PetscInt, TaoMonitorDrawCtx *);
463 PETSC_EXTERN PetscErrorCode          TaoMonitorDrawCtxDestroy(TaoMonitorDrawCtx *);
464 
465 /*E
466   TaoBRGNRegularizationType - The regularization added in the `TAOBRGN` solver.
467 
468   Values:
469 + TAOBRGN_REGULARIZATION_USER   - A user-defined regularizer
470 . TAOBRGN_REGULARIZATION_L2PROX - $\tfrac{1}{2}\|x - x_k\|_2^$, where $x_k$ is the latest solution
471 . TAOBRGN_REGULARIZATION_L2PURE - $\tfrac{1}{2}\|x\|_2^2$
472 . TAOBRGN_REGULARIZATION_L1DICT - $\|D x\|_1$, where $D$ is a dictionary matrix
473 - TAOBRGN_REGULARIZATION_LM     - Levenberg-Marquardt, $\tfrac{1}{2} x^T \mathrm{diag}(J^T J) x$, where $J$ is the Jacobian of the least-squares residual
474 
475   Options database Key:
476 . -tao_brgn_regularization_type <user,l2prox,l2pure,l1dict,lm> - one of the above regularization types
477 
478   Level: advanced
479 
480   Notes:
481   If `TAOBRGN_REGULARIZATION_USER`, the regularizer is set either by calling
482   `TaoBRGNSetRegularizerObjectiveAndGradientRoutine()` and
483   `TaoBRGNSetRegulazerHessianRoutine()` or by calling `TaoBRGNSetRegularizerTerm()`.
484 
485   If `TAOBRGN_REGULARIZATION_L1DICT`, the dictionary matrix is set with `TaoBRGNSetDictionaryMatrix()` and the smoothing parameter of the
486   approximate $\ell_1$ norm is set with `TaoBRGNSetL1SmoothEpsilon()`.
487 
488   If `TAOBRGN_REGULARIZATION_LM`, the diagonal damping vector $\mathrm{diag}(J^T J)$ can be obtained with `TaoBRGNGetDampingVector()`.
489 
490 .seealso: [](ch_tao), `Tao`, `TaoBRGNGetSubsolver()`, `TaoBRGNSetRegularizerWeight()`, `TaoBRGNSetL1SmoothEpsilon()`, `TaoBRGNSetDictionaryMatrix()`,
491           `TaoBRGNSetRegularizerObjectiveAndGradientRoutine()`, `TaoBRGNSetRegularizerHessianRoutine()`,
492           `TaoBRGNGetRegularizationType()`, `TaoBRGNSetRegularizationType()`
493 E*/
494 typedef enum {
495   TAOBRGN_REGULARIZATION_USER,
496   TAOBRGN_REGULARIZATION_L2PROX,
497   TAOBRGN_REGULARIZATION_L2PURE,
498   TAOBRGN_REGULARIZATION_L1DICT,
499   TAOBRGN_REGULARIZATION_LM,
500 } TaoBRGNRegularizationType;
501 
502 PETSC_EXTERN const char *const TaoBRGNRegularizationTypes[];
503 
504 PETSC_EXTERN PetscErrorCode TaoBRGNGetSubsolver(Tao, Tao *);
505 PETSC_EXTERN PetscErrorCode TaoBRGNGetRegularizationType(Tao, TaoBRGNRegularizationType *);
506 PETSC_EXTERN PetscErrorCode TaoBRGNSetRegularizationType(Tao, TaoBRGNRegularizationType);
507 PETSC_EXTERN PetscErrorCode TaoBRGNSetRegularizerObjectiveAndGradientRoutine(Tao, PetscErrorCode (*)(Tao, Vec, PetscReal *, Vec, void *), void *);
508 PETSC_EXTERN PetscErrorCode TaoBRGNSetRegularizerHessianRoutine(Tao, Mat, PetscErrorCode (*)(Tao, Vec, Mat, void *), void *);
509 PETSC_EXTERN PetscErrorCode TaoBRGNSetRegularizerWeight(Tao, PetscReal);
510 PETSC_EXTERN PetscErrorCode TaoBRGNSetL1SmoothEpsilon(Tao, PetscReal);
511 PETSC_EXTERN PetscErrorCode TaoBRGNSetDictionaryMatrix(Tao, Mat);
512 PETSC_EXTERN PetscErrorCode TaoBRGNGetDampingVector(Tao, Vec *);
513 PETSC_EXTERN PetscErrorCode TaoBNCGSetType(Tao, TaoBNCGType);
514 PETSC_EXTERN PetscErrorCode TaoBNCGGetType(Tao, TaoBNCGType *);
515 
516 PETSC_EXTERN PetscErrorCode TaoADMMGetMisfitSubsolver(Tao, Tao *);
517 PETSC_EXTERN PetscErrorCode TaoADMMGetRegularizationSubsolver(Tao, Tao *);
518 PETSC_EXTERN PetscErrorCode TaoADMMGetDualVector(Tao, Vec *);
519 PETSC_EXTERN PetscErrorCode TaoADMMGetSpectralPenalty(Tao, PetscReal *);
520 PETSC_EXTERN PetscErrorCode TaoADMMSetSpectralPenalty(Tao, PetscReal);
521 PETSC_EXTERN PetscErrorCode TaoGetADMMParentTao(Tao, Tao *);
522 PETSC_EXTERN PetscErrorCode TaoADMMSetConstraintVectorRHS(Tao, Vec);
523 PETSC_EXTERN PetscErrorCode TaoADMMSetRegularizerCoefficient(Tao, PetscReal);
524 PETSC_EXTERN PetscErrorCode TaoADMMGetRegularizerCoefficient(Tao, PetscReal *);
525 PETSC_EXTERN PetscErrorCode TaoADMMSetMisfitConstraintJacobian(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
526 PETSC_EXTERN PetscErrorCode TaoADMMSetRegularizerConstraintJacobian(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
527 PETSC_EXTERN PetscErrorCode TaoADMMSetRegularizerHessianRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
528 PETSC_EXTERN PetscErrorCode TaoADMMSetRegularizerObjectiveAndGradientRoutine(Tao, PetscErrorCode (*)(Tao, Vec, PetscReal *, Vec, void *), void *);
529 PETSC_EXTERN PetscErrorCode TaoADMMSetMisfitHessianRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
530 PETSC_EXTERN PetscErrorCode TaoADMMSetMisfitObjectiveAndGradientRoutine(Tao, PetscErrorCode (*)(Tao, Vec, PetscReal *, Vec, void *), void *);
531 PETSC_EXTERN PetscErrorCode TaoADMMSetMisfitHessianChangeStatus(Tao, PetscBool);
532 PETSC_EXTERN PetscErrorCode TaoADMMSetRegHessianChangeStatus(Tao, PetscBool);
533 PETSC_EXTERN PetscErrorCode TaoADMMSetMinimumSpectralPenalty(Tao, PetscReal);
534 PETSC_EXTERN PetscErrorCode TaoADMMSetRegularizerType(Tao, TaoADMMRegularizerType);
535 PETSC_EXTERN PetscErrorCode TaoADMMGetRegularizerType(Tao, TaoADMMRegularizerType *);
536 PETSC_EXTERN PetscErrorCode TaoADMMSetUpdateType(Tao, TaoADMMUpdateType);
537 PETSC_EXTERN PetscErrorCode TaoADMMGetUpdateType(Tao, TaoADMMUpdateType *);
538 
539 PETSC_EXTERN PetscErrorCode TaoALMMGetType(Tao, TaoALMMType *);
540 PETSC_EXTERN PetscErrorCode TaoALMMSetType(Tao, TaoALMMType);
541 PETSC_EXTERN PetscErrorCode TaoALMMGetSubsolver(Tao, Tao *);
542 PETSC_EXTERN PetscErrorCode TaoALMMSetSubsolver(Tao, Tao);
543 PETSC_EXTERN PetscErrorCode TaoALMMGetMultipliers(Tao, Vec *);
544 PETSC_EXTERN PetscErrorCode TaoALMMSetMultipliers(Tao, Vec);
545 PETSC_EXTERN PetscErrorCode TaoALMMGetPrimalIS(Tao, IS *, IS *);
546 PETSC_EXTERN PetscErrorCode TaoALMMGetDualIS(Tao, IS *, IS *);
547 
548 PETSC_EXTERN PetscErrorCode TaoVecGetSubVec(Vec, IS, TaoSubsetType, PetscReal, Vec *);
549 PETSC_EXTERN PetscErrorCode TaoMatGetSubMat(Mat, IS, Vec, TaoSubsetType, Mat *);
550 PETSC_EXTERN PetscErrorCode TaoGradientNorm(Tao, Vec, NormType, PetscReal *);
551 PETSC_EXTERN PetscErrorCode TaoEstimateActiveBounds(Vec, Vec, Vec, Vec, Vec, Vec, PetscReal, PetscReal *, IS *, IS *, IS *, IS *, IS *);
552 PETSC_EXTERN PetscErrorCode TaoBoundStep(Vec, Vec, Vec, IS, IS, IS, PetscReal, Vec);
553 PETSC_EXTERN PetscErrorCode TaoBoundSolution(Vec, Vec, Vec, PetscReal, PetscInt *, Vec);
554 
555 PETSC_EXTERN PetscErrorCode MatCreateSubMatrixFree(Mat, IS, IS, Mat *);
556 
557 #include <petsctao_deprecations.h>
558