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: + 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
162: Level: advanced
164: .seealso: `Tao`, `TAOBNCG`, `TaoBNCGSetType()`, `TaoBNCGGetType()`
165: E*/
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[];
184: /*J
185: TaoType - String with the name of a `Tao` method
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
200: Level: beginner
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"
240: PETSC_EXTERN PetscClassId TAO_CLASSID;
241: PETSC_EXTERN PetscFunctionList TaoList;
243: /*E
244: TaoConvergedReason - reason a `Tao` optimizer was said to have converged or diverged
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()`
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
272: Level: beginner
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).
278: Developer Note:
279: The names in `KSPConvergedReason`, `SNESConvergedReason`, and `TaoConvergedReason` should be uniformized
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;
301: PETSC_EXTERN const char **TaoConvergedReasons;
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);
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 *);
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 **);
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 TaoSetEqualityConstraintsRoutine(Tao, Vec, PetscErrorCode (*)(Tao, Vec, Vec, void *), void *);
354: PETSC_EXTERN PetscErrorCode TaoSetJacobianResidualRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
355: PETSC_EXTERN PetscErrorCode TaoSetJacobianRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
356: PETSC_EXTERN PetscErrorCode TaoSetJacobianStateRoutine(Tao, Mat, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, Mat, void *), void *);
357: PETSC_EXTERN PetscErrorCode TaoSetJacobianDesignRoutine(Tao, Mat, PetscErrorCode (*)(Tao, Vec, Mat, void *), void *);
358: PETSC_EXTERN PetscErrorCode TaoSetJacobianInequalityRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
359: PETSC_EXTERN PetscErrorCode TaoSetJacobianEqualityRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
361: PETSC_EXTERN PetscErrorCode TaoPythonSetType(Tao, const char[]);
362: PETSC_EXTERN PetscErrorCode TaoPythonGetType(Tao, const char *[]);
364: PETSC_EXTERN PetscErrorCode TaoShellSetSolve(Tao, PetscErrorCode (*)(Tao));
365: PETSC_EXTERN PetscErrorCode TaoShellSetContext(Tao, void *);
366: PETSC_EXTERN PetscErrorCode TaoShellGetContext(Tao, void *);
368: PETSC_EXTERN PetscErrorCode TaoSetStateDesignIS(Tao, IS, IS);
370: PETSC_EXTERN PetscErrorCode TaoComputeObjective(Tao, Vec, PetscReal *);
371: PETSC_EXTERN PetscErrorCode TaoComputeResidual(Tao, Vec, Vec);
372: PETSC_EXTERN PetscErrorCode TaoTestGradient(Tao, Vec, Vec);
373: PETSC_EXTERN PetscErrorCode TaoComputeGradient(Tao, Vec, Vec);
374: PETSC_EXTERN PetscErrorCode TaoComputeObjectiveAndGradient(Tao, Vec, PetscReal *, Vec);
375: PETSC_EXTERN PetscErrorCode TaoComputeConstraints(Tao, Vec, Vec);
376: PETSC_EXTERN PetscErrorCode TaoComputeInequalityConstraints(Tao, Vec, Vec);
377: PETSC_EXTERN PetscErrorCode TaoComputeEqualityConstraints(Tao, Vec, Vec);
378: PETSC_EXTERN PetscErrorCode TaoDefaultComputeGradient(Tao, Vec, Vec, void *);
379: PETSC_EXTERN PetscErrorCode TaoIsObjectiveDefined(Tao, PetscBool *);
380: PETSC_EXTERN PetscErrorCode TaoIsGradientDefined(Tao, PetscBool *);
381: PETSC_EXTERN PetscErrorCode TaoIsObjectiveAndGradientDefined(Tao, PetscBool *);
383: PETSC_EXTERN PetscErrorCode TaoTestHessian(Tao);
384: PETSC_EXTERN PetscErrorCode TaoComputeHessian(Tao, Vec, Mat, Mat);
385: PETSC_EXTERN PetscErrorCode TaoComputeResidualJacobian(Tao, Vec, Mat, Mat);
386: PETSC_EXTERN PetscErrorCode TaoComputeJacobian(Tao, Vec, Mat, Mat);
387: PETSC_EXTERN PetscErrorCode TaoComputeJacobianState(Tao, Vec, Mat, Mat, Mat);
388: PETSC_EXTERN PetscErrorCode TaoComputeJacobianEquality(Tao, Vec, Mat, Mat);
389: PETSC_EXTERN PetscErrorCode TaoComputeJacobianInequality(Tao, Vec, Mat, Mat);
390: PETSC_EXTERN PetscErrorCode TaoComputeJacobianDesign(Tao, Vec, Mat);
392: PETSC_EXTERN PetscErrorCode TaoDefaultComputeHessian(Tao, Vec, Mat, Mat, void *);
393: PETSC_EXTERN PetscErrorCode TaoDefaultComputeHessianColor(Tao, Vec, Mat, Mat, void *);
394: PETSC_EXTERN PetscErrorCode TaoDefaultComputeHessianMFFD(Tao, Vec, Mat, Mat, void *);
395: PETSC_EXTERN PetscErrorCode TaoComputeDualVariables(Tao, Vec, Vec);
396: PETSC_EXTERN PetscErrorCode TaoSetVariableBounds(Tao, Vec, Vec);
397: PETSC_EXTERN PetscErrorCode TaoGetVariableBounds(Tao, Vec *, Vec *);
398: PETSC_EXTERN PetscErrorCode TaoGetDualVariables(Tao, Vec *, Vec *);
399: PETSC_EXTERN PetscErrorCode TaoSetInequalityBounds(Tao, Vec, Vec);
400: PETSC_EXTERN PetscErrorCode TaoGetInequalityBounds(Tao, Vec *, Vec *);
401: PETSC_EXTERN PetscErrorCode TaoSetVariableBoundsRoutine(Tao, PetscErrorCode (*)(Tao, Vec, Vec, void *), void *);
402: PETSC_EXTERN PetscErrorCode TaoComputeVariableBounds(Tao);
404: PETSC_EXTERN PetscErrorCode TaoGetTolerances(Tao, PetscReal *, PetscReal *, PetscReal *);
405: PETSC_EXTERN PetscErrorCode TaoSetTolerances(Tao, PetscReal, PetscReal, PetscReal);
406: PETSC_EXTERN PetscErrorCode TaoGetConstraintTolerances(Tao, PetscReal *, PetscReal *);
407: PETSC_EXTERN PetscErrorCode TaoSetConstraintTolerances(Tao, PetscReal, PetscReal);
408: PETSC_EXTERN PetscErrorCode TaoSetFunctionLowerBound(Tao, PetscReal);
409: PETSC_EXTERN PetscErrorCode TaoSetInitialTrustRegionRadius(Tao, PetscReal);
410: PETSC_EXTERN PetscErrorCode TaoSetMaximumIterations(Tao, PetscInt);
411: PETSC_EXTERN PetscErrorCode TaoSetMaximumFunctionEvaluations(Tao, PetscInt);
412: PETSC_EXTERN PetscErrorCode TaoGetFunctionLowerBound(Tao, PetscReal *);
413: PETSC_EXTERN PetscErrorCode TaoGetInitialTrustRegionRadius(Tao, PetscReal *);
414: PETSC_EXTERN PetscErrorCode TaoGetCurrentTrustRegionRadius(Tao, PetscReal *);
415: PETSC_EXTERN PetscErrorCode TaoGetMaximumIterations(Tao, PetscInt *);
416: PETSC_EXTERN PetscErrorCode TaoGetCurrentFunctionEvaluations(Tao, PetscInt *);
417: PETSC_EXTERN PetscErrorCode TaoGetMaximumFunctionEvaluations(Tao, PetscInt *);
418: PETSC_EXTERN PetscErrorCode TaoGetIterationNumber(Tao, PetscInt *);
419: PETSC_EXTERN PetscErrorCode TaoSetIterationNumber(Tao, PetscInt);
420: PETSC_EXTERN PetscErrorCode TaoGetTotalIterationNumber(Tao, PetscInt *);
421: PETSC_EXTERN PetscErrorCode TaoSetTotalIterationNumber(Tao, PetscInt);
422: PETSC_EXTERN PetscErrorCode TaoGetResidualNorm(Tao, PetscReal *);
424: PETSC_EXTERN PetscErrorCode TaoAppendOptionsPrefix(Tao, const char[]);
425: PETSC_EXTERN PetscErrorCode TaoGetOptionsPrefix(Tao, const char *[]);
426: PETSC_EXTERN PetscErrorCode TaoResetStatistics(Tao);
427: PETSC_EXTERN PetscErrorCode TaoSetUpdate(Tao, PetscErrorCode (*)(Tao, PetscInt, void *), void *);
429: PETSC_EXTERN PetscErrorCode TaoGetKSP(Tao, KSP *);
430: PETSC_EXTERN PetscErrorCode TaoGetLinearSolveIterations(Tao, PetscInt *);
431: PETSC_EXTERN PetscErrorCode TaoKSPSetUseEW(Tao, PetscBool);
433: #include <petsctaolinesearch.h>
435: PETSC_EXTERN PetscErrorCode TaoGetLineSearch(Tao, TaoLineSearch *);
437: PETSC_EXTERN PetscErrorCode TaoSetConvergenceHistory(Tao, PetscReal *, PetscReal *, PetscReal *, PetscInt *, PetscInt, PetscBool);
438: PETSC_EXTERN PetscErrorCode TaoGetConvergenceHistory(Tao, PetscReal **, PetscReal **, PetscReal **, PetscInt **, PetscInt *);
439: PETSC_EXTERN PetscErrorCode TaoMonitorSet(Tao, PetscErrorCode (*)(Tao, void *), void *, PetscErrorCode (*)(void **));
440: PETSC_EXTERN PetscErrorCode TaoMonitorCancel(Tao);
441: PETSC_EXTERN PetscErrorCode TaoMonitorDefault(Tao, void *);
442: PETSC_EXTERN PetscErrorCode TaoMonitorGlobalization(Tao, void *);
443: PETSC_EXTERN PetscErrorCode TaoMonitorDefaultShort(Tao, void *);
444: PETSC_EXTERN PetscErrorCode TaoMonitorConstraintNorm(Tao, void *);
445: PETSC_EXTERN PetscErrorCode TaoMonitorSolution(Tao, void *);
446: PETSC_EXTERN PetscErrorCode TaoMonitorResidual(Tao, void *);
447: PETSC_EXTERN PetscErrorCode TaoMonitorGradient(Tao, void *);
448: PETSC_EXTERN PetscErrorCode TaoMonitorStep(Tao, void *);
449: PETSC_EXTERN PetscErrorCode TaoMonitorSolutionDraw(Tao, void *);
450: PETSC_EXTERN PetscErrorCode TaoMonitorStepDraw(Tao, void *);
451: PETSC_EXTERN PetscErrorCode TaoMonitorGradientDraw(Tao, void *);
452: PETSC_EXTERN PetscErrorCode TaoAddLineSearchCounts(Tao);
454: PETSC_EXTERN PetscErrorCode TaoDefaultConvergenceTest(Tao, void *);
455: PETSC_EXTERN PetscErrorCode TaoSetConvergenceTest(Tao, PetscErrorCode (*)(Tao, void *), void *);
457: PETSC_EXTERN PetscErrorCode TaoLCLSetStateDesignIS(Tao, IS, IS);
458: PETSC_EXTERN PetscErrorCode TaoMonitor(Tao, PetscInt, PetscReal, PetscReal, PetscReal, PetscReal);
459: typedef struct _n_TaoMonitorDrawCtx *TaoMonitorDrawCtx;
460: PETSC_EXTERN PetscErrorCode TaoMonitorDrawCtxCreate(MPI_Comm, const char[], const char[], int, int, int, int, PetscInt, TaoMonitorDrawCtx *);
461: PETSC_EXTERN PetscErrorCode TaoMonitorDrawCtxDestroy(TaoMonitorDrawCtx *);
463: PETSC_EXTERN PetscErrorCode TaoBRGNGetSubsolver(Tao, Tao *);
464: PETSC_EXTERN PetscErrorCode TaoBRGNSetRegularizerObjectiveAndGradientRoutine(Tao, PetscErrorCode (*)(Tao, Vec, PetscReal *, Vec, void *), void *);
465: PETSC_EXTERN PetscErrorCode TaoBRGNSetRegularizerHessianRoutine(Tao, Mat, PetscErrorCode (*)(Tao, Vec, Mat, void *), void *);
466: PETSC_EXTERN PetscErrorCode TaoBRGNSetRegularizerWeight(Tao, PetscReal);
467: PETSC_EXTERN PetscErrorCode TaoBRGNSetL1SmoothEpsilon(Tao, PetscReal);
468: PETSC_EXTERN PetscErrorCode TaoBRGNSetDictionaryMatrix(Tao, Mat);
469: PETSC_EXTERN PetscErrorCode TaoBRGNGetDampingVector(Tao, Vec *);
470: PETSC_EXTERN PetscErrorCode TaoBNCGSetType(Tao, TaoBNCGType);
471: PETSC_EXTERN PetscErrorCode TaoBNCGGetType(Tao, TaoBNCGType *);
473: PETSC_EXTERN PetscErrorCode TaoADMMGetMisfitSubsolver(Tao, Tao *);
474: PETSC_EXTERN PetscErrorCode TaoADMMGetRegularizationSubsolver(Tao, Tao *);
475: PETSC_EXTERN PetscErrorCode TaoADMMGetDualVector(Tao, Vec *);
476: PETSC_EXTERN PetscErrorCode TaoADMMGetSpectralPenalty(Tao, PetscReal *);
477: PETSC_EXTERN PetscErrorCode TaoADMMSetSpectralPenalty(Tao, PetscReal);
478: PETSC_EXTERN PetscErrorCode TaoGetADMMParentTao(Tao, Tao *);
479: PETSC_EXTERN PetscErrorCode TaoADMMSetConstraintVectorRHS(Tao, Vec);
480: PETSC_EXTERN PetscErrorCode TaoADMMSetRegularizerCoefficient(Tao, PetscReal);
481: PETSC_EXTERN PetscErrorCode TaoADMMGetRegularizerCoefficient(Tao, PetscReal *);
482: PETSC_EXTERN PetscErrorCode TaoADMMSetMisfitConstraintJacobian(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
483: PETSC_EXTERN PetscErrorCode TaoADMMSetRegularizerConstraintJacobian(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
484: PETSC_EXTERN PetscErrorCode TaoADMMSetRegularizerHessianRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
485: PETSC_EXTERN PetscErrorCode TaoADMMSetRegularizerObjectiveAndGradientRoutine(Tao, PetscErrorCode (*)(Tao, Vec, PetscReal *, Vec, void *), void *);
486: PETSC_EXTERN PetscErrorCode TaoADMMSetMisfitHessianRoutine(Tao, Mat, Mat, PetscErrorCode (*)(Tao, Vec, Mat, Mat, void *), void *);
487: PETSC_EXTERN PetscErrorCode TaoADMMSetMisfitObjectiveAndGradientRoutine(Tao, PetscErrorCode (*)(Tao, Vec, PetscReal *, Vec, void *), void *);
488: PETSC_EXTERN PetscErrorCode TaoADMMSetMisfitHessianChangeStatus(Tao, PetscBool);
489: PETSC_EXTERN PetscErrorCode TaoADMMSetRegHessianChangeStatus(Tao, PetscBool);
490: PETSC_EXTERN PetscErrorCode TaoADMMSetMinimumSpectralPenalty(Tao, PetscReal);
491: PETSC_EXTERN PetscErrorCode TaoADMMSetRegularizerType(Tao, TaoADMMRegularizerType);
492: PETSC_EXTERN PetscErrorCode TaoADMMGetRegularizerType(Tao, TaoADMMRegularizerType *);
493: PETSC_EXTERN PetscErrorCode TaoADMMSetUpdateType(Tao, TaoADMMUpdateType);
494: PETSC_EXTERN PetscErrorCode TaoADMMGetUpdateType(Tao, TaoADMMUpdateType *);
496: PETSC_EXTERN PetscErrorCode TaoALMMGetType(Tao, TaoALMMType *);
497: PETSC_EXTERN PetscErrorCode TaoALMMSetType(Tao, TaoALMMType);
498: PETSC_EXTERN PetscErrorCode TaoALMMGetSubsolver(Tao, Tao *);
499: PETSC_EXTERN PetscErrorCode TaoALMMSetSubsolver(Tao, Tao);
500: PETSC_EXTERN PetscErrorCode TaoALMMGetMultipliers(Tao, Vec *);
501: PETSC_EXTERN PetscErrorCode TaoALMMSetMultipliers(Tao, Vec);
502: PETSC_EXTERN PetscErrorCode TaoALMMGetPrimalIS(Tao, IS *, IS *);
503: PETSC_EXTERN PetscErrorCode TaoALMMGetDualIS(Tao, IS *, IS *);
505: PETSC_EXTERN PetscErrorCode TaoVecGetSubVec(Vec, IS, TaoSubsetType, PetscReal, Vec *);
506: PETSC_EXTERN PetscErrorCode TaoMatGetSubMat(Mat, IS, Vec, TaoSubsetType, Mat *);
507: PETSC_EXTERN PetscErrorCode TaoGradientNorm(Tao, Vec, NormType, PetscReal *);
508: PETSC_EXTERN PetscErrorCode TaoEstimateActiveBounds(Vec, Vec, Vec, Vec, Vec, Vec, PetscReal, PetscReal *, IS *, IS *, IS *, IS *, IS *);
509: PETSC_EXTERN PetscErrorCode TaoBoundStep(Vec, Vec, Vec, IS, IS, IS, PetscReal, Vec);
510: PETSC_EXTERN PetscErrorCode TaoBoundSolution(Vec, Vec, Vec, PetscReal, PetscInt *, Vec);
512: PETSC_EXTERN PetscErrorCode MatCreateSubMatrixFree(Mat, IS, IS, Mat *);
514: #include <petsctao_deprecations.h>