/*
TAOCreate_BCG - Creates the data structure for the nonlinear BCG method
and sets the function pointers for all the routines it needs to call
(TAOSolve_BCG() etc.)
It must be wrapped in EXTERN_C_BEGIN to be dynamically linkable in C++
*/
EXTERN_C_BEGIN
#undef __FUNC__
#define __FUNC__ "TaoCreate_BCG"
int TaoCreate_BCG(TAO_SOLVER tao)
{
TAO_BCG *cg;
int info;
TaoFunctionBegin;
cg = TaoNew(TAO_BCG);CHKPTRQ(cg);
PLogObjectMemory(tao,sizeof(TAO_BCG));
info = TaoSetSolver(tao,TaoSetUp_BCG,TaoSetOptions_BCG,TaoSolve_BCG,
TaoView_BCG,TaoDestroy_BCG,(void*)cg); CHKERRQ(info);
info = TaoSetMaximumIterates(tao,2000); CHKERRQ(info);
info = TaoSetTolerances(tao,1e-4,0,0,0); CHKERRQ(info);
info = TaoSetMaximumFunctionEvaluations(tao,4000); CHKERRQ(info);
info = TaoCreateProjectedLineSearch(tao); CHKERRQ(info);
cg->eta = 100.0;
cg->type = TAO_CG_PRplus;
info = PetscObjectComposeFunctionDynamic((PetscObject)tao,"TaoBCGSetRestartTol_C",
"TaoBCGSetRestartTol_TaoBCG",
(void*)TaoBCGSetRestartTol_TaoBCG);CHKERRQ(info);
TaoFunctionReturn(0);
}
/* ---------------------------------------------------------- */
EXTERN_C_BEGIN
#undef __FUNCT__
#define __FUNCT__ "TaoCreate_SSFLS"
int TaoCreate_SSFLS(TAO_SOLVER tao)
{
TAO_SSLS *ssls;
int info;
TaoFunctionBegin;
info = TaoNew(TAO_SSLS,&ssls); CHKERRQ(info);
info = PetscLogObjectMemory(tao, sizeof(TAO_SSLS)); CHKERRQ(info);
ssls->delta = 1e-10;
ssls->rho = 2.1;
info=TaoSetTaoSolveRoutine(tao,TaoSolve_SSFLS,(void*)ssls); CHKERRQ(info);
info=TaoSetTaoSetUpDownRoutines(tao,TaoSetUp_SSLS,TaoSetDown_SSLS); CHKERRQ(info);
info=TaoSetTaoOptionsRoutine(tao,TaoSetOptions_SSLS); CHKERRQ(info);
info=TaoSetTaoViewRoutine(tao,TaoView_SSLS); CHKERRQ(info);
info = TaoCreateProjectedArmijoLineSearch(tao); CHKERRQ(info);
info = TaoSetMaximumIterates(tao,2000); CHKERRQ(info);
info = TaoSetMaximumFunctionEvaluations(tao,4000); CHKERRQ(info);
info = TaoSetTolerances(tao,0,0,0,0); CHKERRQ(info);
info = TaoSetGradientTolerances(tao,1.0e-16,0.0,0.0); CHKERRQ(info);
info = TaoSetFunctionLowerBound(tao,1.0e-8); CHKERRQ(info);
TaoFunctionReturn(0);
}
/*------------------------------------------------------------*/
EXTERN_C_BEGIN
#undef __FUNCT__
#define __FUNCT__ "TaoCreate_GPCG"
int TaoCreate_GPCG(TAO_SOLVER tao)
{
TAO_GPCG *gpcg;
int info;
TaoFunctionBegin;
info = TaoNew(TAO_GPCG,&gpcg); CHKERRQ(info);
info = PetscLogObjectMemory(tao,sizeof(TAO_GPCG)); CHKERRQ(info);
info=TaoSetTaoSolveRoutine(tao,TaoSolve_GPCG,(void*)gpcg); CHKERRQ(info);
info=TaoSetTaoSetUpDownRoutines(tao,TaoSetUp_GPCG,TaoSetDown_GPCG); CHKERRQ(info);
info=TaoSetTaoOptionsRoutine(tao,TaoSetFromOptions_GPCG); CHKERRQ(info);
info=TaoSetTaoViewRoutine(tao,TaoView_GPCG); CHKERRQ(info);
info=TaoSetTaoDualVariablesRoutine(tao,TaoGetDualVariables_GPCG); CHKERRQ(info);
info = TaoSetMaximumIterates(tao,500); CHKERRQ(info);
info = TaoSetMaximumFunctionEvaluations(tao,100000); CHKERRQ(info);
info = TaoSetTolerances(tao,1e-12,1e-12,0,0); CHKERRQ(info);
/* Initialize pointers and variables */
gpcg->n=0;
gpcg->maxgpits = 8;
gpcg->pg_ftol = 0.1;
gpcg->gp_iterates=0; /* Cumulative number */
gpcg->total_gp_its = 0;
/* Initialize pointers and variables */
gpcg->n_bind=0;
gpcg->n_free = 0;
gpcg->n_upper=0;
gpcg->n_lower=0;
// info = TaoCreateProjectedLineSearch(tao); CHKERRQ(info);
info = TaoGPCGCreateLineSearch(tao); CHKERRQ(info);
TaoFunctionReturn(0);
}
/*------------------------------------------------------------*/
EXTERN_C_BEGIN
#undef __FUNCT__
#define __FUNCT__ "TaoCreate_BNLS"
int TaoCreate_BNLS(TAO_SOLVER tao)
{
TAO_BNLS *bnls;
int info;
TaoFunctionBegin;
info = TaoNew(TAO_BNLS,&bnls); CHKERRQ(info);
info = PetscLogObjectMemory(tao,sizeof(TAO_BNLS)); CHKERRQ(info);
info=TaoSetTaoSolveRoutine(tao,TaoSolve_BNLS,(void*)bnls); CHKERRQ(info);
info=TaoSetTaoSetUpDownRoutines(tao,TaoSetUp_BNLS,TaoSetDown_BNLS); CHKERRQ(info);
info=TaoSetTaoOptionsRoutine(tao,TaoSetOptions_BNLS); CHKERRQ(info);
info=TaoSetTaoViewRoutine(tao,TaoView_BNLS); CHKERRQ(info);
info=TaoSetTaoDualVariablesRoutine(tao,TaoGetDualVariables_BNLS); CHKERRQ(info);
info = TaoSetMaximumIterates(tao,500); CHKERRQ(info);
info = TaoSetTolerances(tao,1e-12,1e-12,0,0); CHKERRQ(info);
/* Initialize pointers and variables */
bnls->gamma = 0.0;
bnls->gamma_factor = 0.01;
bnls->DX=0;
bnls->DXFree=0;
bnls->R=0;
bnls->Work=0;
bnls->FreeVariables=0;
bnls->Hsub=0;
bnls->M=0;
info = TaoCreateMoreThuenteBoundLineSearch(tao,0,0.9); CHKERRQ(info);
TaoFunctionReturn(0);
}
int main(int argc,char **argv)
{
PetscErrorCode ierr; /* used to check for functions returning nonzeros */
PetscReal zero=0.0;
Vec x; /* solution vector */
Mat H;
Tao tao; /* Tao solver context */
PetscBool flg, test_lmvm = PETSC_FALSE;
PetscMPIInt size,rank; /* number of processes running */
AppCtx user; /* user-defined application context */
TaoConvergedReason reason;
PetscInt its, recycled_its=0, oneshot_its=0;
/* Initialize TAO and PETSc */
ierr = PetscInitialize(&argc,&argv,(char*)0,help);if (ierr) return ierr;
ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr);
ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr);
if (size >1) SETERRQ(PETSC_COMM_SELF,1,"Incorrect number of processors");
/* Initialize problem parameters */
user.n = 2; user.alpha = 99.0; user.chained = PETSC_FALSE;
/* Check for command line arguments to override defaults */
ierr = PetscOptionsGetInt(NULL,NULL,"-n",&user.n,&flg);CHKERRQ(ierr);
ierr = PetscOptionsGetReal(NULL,NULL,"-alpha",&user.alpha,&flg);CHKERRQ(ierr);
ierr = PetscOptionsGetBool(NULL,NULL,"-chained",&user.chained,&flg);CHKERRQ(ierr);
ierr = PetscOptionsGetBool(NULL,NULL,"-test_lmvm",&test_lmvm,&flg);CHKERRQ(ierr);
/* Allocate vectors for the solution and gradient */
ierr = VecCreateSeq(PETSC_COMM_SELF,user.n,&x);CHKERRQ(ierr);
ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,2,user.n,user.n,1,NULL,&H);CHKERRQ(ierr);
/* The TAO code begins here */
/* Create TAO solver with desired solution method */
ierr = TaoCreate(PETSC_COMM_SELF,&tao);CHKERRQ(ierr);
ierr = TaoSetType(tao,TAOLMVM);CHKERRQ(ierr);
/* Set solution vec and an initial guess */
ierr = VecSet(x, zero);CHKERRQ(ierr);
ierr = TaoSetInitialVector(tao,x);CHKERRQ(ierr);
/* Set routines for function, gradient, hessian evaluation */
ierr = TaoSetObjectiveAndGradientRoutine(tao,FormFunctionGradient,&user);CHKERRQ(ierr);
ierr = TaoSetHessianRoutine(tao,H,H,FormHessian,&user);CHKERRQ(ierr);
/* Check for TAO command line options */
ierr = TaoSetFromOptions(tao);CHKERRQ(ierr);
/* Solve the problem */
ierr = TaoSetTolerances(tao, 1.e-5, 0.0, 0.0);CHKERRQ(ierr);
ierr = TaoSetMaximumIterations(tao, 5);CHKERRQ(ierr);
ierr = TaoLMVMRecycle(tao, PETSC_TRUE);CHKERRQ(ierr);
reason = TAO_CONTINUE_ITERATING;
while (reason != TAO_CONVERGED_GATOL) {
ierr = TaoSolve(tao);CHKERRQ(ierr);
ierr = TaoGetConvergedReason(tao, &reason);CHKERRQ(ierr);
ierr = TaoGetIterationNumber(tao, &its);CHKERRQ(ierr);
recycled_its += its;
ierr = PetscPrintf(PETSC_COMM_SELF, "-----------------------\n");CHKERRQ(ierr);
}
/* Disable recycling and solve again! */
ierr = TaoSetMaximumIterations(tao, 100);CHKERRQ(ierr);
ierr = TaoLMVMRecycle(tao, PETSC_FALSE);CHKERRQ(ierr);
ierr = VecSet(x, zero);CHKERRQ(ierr);
ierr = TaoSolve(tao);CHKERRQ(ierr);
ierr = TaoGetConvergedReason(tao, &reason);CHKERRQ(ierr);
if (reason != TAO_CONVERGED_GATOL) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_NOT_CONVERGED, "Solution failed to converge!");
ierr = TaoGetIterationNumber(tao, &oneshot_its);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_SELF, "-----------------------\n");CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_SELF, "recycled its: %D | oneshot its: %D\n", recycled_its, oneshot_its);CHKERRQ(ierr);
if (recycled_its != oneshot_its) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_NOT_CONVERGED, "LMVM recycling does not work!");
ierr = TaoDestroy(&tao);CHKERRQ(ierr);
ierr = VecDestroy(&x);CHKERRQ(ierr);
ierr = MatDestroy(&H);CHKERRQ(ierr);
ierr = PetscFinalize();
return ierr;
}
PetscErrorCode TaoPounders_solvequadratic(Tao tao,PetscReal *gnorm, PetscReal *qmin)
{
PetscErrorCode ierr;
#if defined(PETSC_USE_REAL_SINGLE)
PetscReal atol=1.0e-5;
#else
PetscReal atol=1.0e-10;
#endif
PetscInt info,its;
TAO_POUNDERS *mfqP = (TAO_POUNDERS*)tao->data;
PetscReal maxval;
PetscInt i,j;
PetscFunctionBegin;
ierr = VecCopy(mfqP->Gres, mfqP->subb);CHKERRQ(ierr);
ierr = VecSet(mfqP->subx,0.0);CHKERRQ(ierr);
ierr = VecSet(mfqP->subndel,-mfqP->delta);CHKERRQ(ierr);
ierr = VecSet(mfqP->subpdel,mfqP->delta);CHKERRQ(ierr);
ierr = MatCopy(mfqP->Hres,mfqP->subH,SAME_NONZERO_PATTERN);CHKERRQ(ierr);
ierr = TaoResetStatistics(mfqP->subtao);CHKERRQ(ierr);
ierr = TaoSetTolerances(mfqP->subtao,NULL,NULL,*gnorm,*gnorm,NULL);CHKERRQ(ierr);
/* enforce bound constraints -- experimental */
if (tao->XU && tao->XL) {
ierr = VecCopy(tao->XU,mfqP->subxu);CHKERRQ(ierr);
ierr = VecAXPY(mfqP->subxu,-1.0,tao->solution);CHKERRQ(ierr);
ierr = VecScale(mfqP->subxu,1.0/mfqP->delta);CHKERRQ(ierr);
ierr = VecCopy(tao->XL,mfqP->subxl);CHKERRQ(ierr);
ierr = VecAXPY(mfqP->subxl,-1.0,tao->solution);CHKERRQ(ierr);
ierr = VecScale(mfqP->subxl,1.0/mfqP->delta);CHKERRQ(ierr);
ierr = VecPointwiseMin(mfqP->subxu,mfqP->subxu,mfqP->subpdel);CHKERRQ(ierr);
ierr = VecPointwiseMax(mfqP->subxl,mfqP->subxl,mfqP->subndel);CHKERRQ(ierr);
} else {
ierr = VecCopy(mfqP->subpdel,mfqP->subxu);CHKERRQ(ierr);
ierr = VecCopy(mfqP->subndel,mfqP->subxl);CHKERRQ(ierr);
}
/* Make sure xu > xl */
ierr = VecCopy(mfqP->subxl,mfqP->subpdel);CHKERRQ(ierr);
ierr = VecAXPY(mfqP->subpdel,-1.0,mfqP->subxu); CHKERRQ(ierr);
ierr = VecMax(mfqP->subpdel,NULL,&maxval);CHKERRQ(ierr);
if (maxval > 1e-10) {
SETERRQ(PETSC_COMM_WORLD,1,"upper bound < lower bound in subproblem");
}
/* Make sure xu > tao->solution > xl */
ierr = VecCopy(mfqP->subxl,mfqP->subpdel);CHKERRQ(ierr);
ierr = VecAXPY(mfqP->subpdel,-1.0,mfqP->subx); CHKERRQ(ierr);
ierr = VecMax(mfqP->subpdel,NULL,&maxval);CHKERRQ(ierr);
if (maxval > 1e-10) {
SETERRQ(PETSC_COMM_WORLD,1,"initial guess < lower bound in subproblem");
}
ierr = VecCopy(mfqP->subx,mfqP->subpdel);CHKERRQ(ierr);
ierr = VecAXPY(mfqP->subpdel,-1.0,mfqP->subxu); CHKERRQ(ierr);
ierr = VecMax(mfqP->subpdel,NULL,&maxval);CHKERRQ(ierr);
if (maxval > 1e-10) {
SETERRQ(PETSC_COMM_WORLD,1,"initial guess > upper bound in subproblem");
}
ierr = TaoSolve(mfqP->subtao);CHKERRQ(ierr);
ierr = TaoGetSolutionStatus(mfqP->subtao,NULL,qmin,NULL,NULL,NULL,NULL);CHKERRQ(ierr);
/* test bounds post-solution*/
ierr = VecCopy(mfqP->subxl,mfqP->subpdel);CHKERRQ(ierr);
ierr = VecAXPY(mfqP->subpdel,-1.0,mfqP->subx); CHKERRQ(ierr);
ierr = VecMax(mfqP->subpdel,NULL,&maxval);CHKERRQ(ierr);
if (maxval > 1e-5) {
ierr = PetscInfo(tao,"subproblem solution < lower bound");CHKERRQ(ierr);
tao->reason = TAO_DIVERGED_TR_REDUCTION;
}
ierr = VecCopy(mfqP->subx,mfqP->subpdel);CHKERRQ(ierr);
ierr = VecAXPY(mfqP->subpdel,-1.0,mfqP->subxu); CHKERRQ(ierr);
ierr = VecMax(mfqP->subpdel,NULL,&maxval);CHKERRQ(ierr);
if (maxval > 1e-5) {
ierr = PetscInfo(tao,"subproblem solution > upper bound");
tao->reason = TAO_DIVERGED_TR_REDUCTION;
}
*qmin *= -1;
PetscFunctionReturn(0);
}
PetscErrorCode main(int argc,char **argv)
{
PetscErrorCode ierr; /* used to check for functions returning nonzeros */
PetscMPIInt size;
Vec x; /* solution */
KSP ksp;
PC pc;
Vec ceq,cin;
PetscBool flg; /* A return value when checking for use options */
Tao tao; /* Tao solver context */
TaoConvergedReason reason;
AppCtx user; /* application context */
/* Initialize TAO,PETSc */
ierr = PetscInitialize(&argc,&argv,(char *)0,help);CHKERRQ(ierr);
ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr);
/* Specify default parameters for the problem, check for command-line overrides */
ierr = PetscStrncpy(user.name,"HS21",8);CHKERRQ(ierr);
ierr = PetscOptionsGetString(NULL,NULL,"-cutername",user.name,24,&flg);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD,"\n---- MAROS Problem %s -----\n",user.name);CHKERRQ(ierr);
ierr = InitializeProblem(&user);CHKERRQ(ierr);
ierr = VecDuplicate(user.d,&x);CHKERRQ(ierr);
ierr = VecDuplicate(user.beq,&ceq);CHKERRQ(ierr);
ierr = VecDuplicate(user.bin,&cin);CHKERRQ(ierr);
ierr = VecSet(x,1.0);CHKERRQ(ierr);
ierr = TaoCreate(PETSC_COMM_WORLD,&tao);CHKERRQ(ierr);
ierr = TaoSetType(tao,TAOIPM);CHKERRQ(ierr);
ierr = TaoSetInitialVector(tao,x);CHKERRQ(ierr);
ierr = TaoSetObjectiveAndGradientRoutine(tao,FormFunctionGradient,(void*)&user);CHKERRQ(ierr);
ierr = TaoSetEqualityConstraintsRoutine(tao,ceq,FormEqualityConstraints,(void*)&user);CHKERRQ(ierr);
ierr = TaoSetInequalityConstraintsRoutine(tao,cin,FormInequalityConstraints,(void*)&user);CHKERRQ(ierr);
ierr = TaoSetInequalityBounds(tao,user.bin,NULL);CHKERRQ(ierr);
ierr = TaoSetJacobianEqualityRoutine(tao,user.Aeq,user.Aeq,FormEqualityJacobian,(void*)&user);CHKERRQ(ierr);
ierr = TaoSetJacobianInequalityRoutine(tao,user.Ain,user.Ain,FormInequalityJacobian,(void*)&user);CHKERRQ(ierr);
ierr = TaoSetHessianRoutine(tao,user.H,user.H,FormHessian,(void*)&user);CHKERRQ(ierr);
ierr = TaoGetKSP(tao,&ksp);CHKERRQ(ierr);
ierr = KSPGetPC(ksp,&pc);CHKERRQ(ierr);
ierr = PCSetType(pc,PCLU);CHKERRQ(ierr);
/*
This algorithm produces matrices with zeros along the diagonal therefore we need to use
SuperLU which does partial pivoting
*/
ierr = PCFactorSetMatSolverPackage(pc,MATSOLVERSUPERLU);CHKERRQ(ierr);
ierr = KSPSetType(ksp,KSPPREONLY);CHKERRQ(ierr);
ierr = TaoSetTolerances(tao,0,0,0);CHKERRQ(ierr);
ierr = TaoSetFromOptions(tao);CHKERRQ(ierr);
ierr = TaoSolve(tao);CHKERRQ(ierr);
ierr = TaoGetConvergedReason(tao,&reason);CHKERRQ(ierr);
if (reason < 0) {
ierr = PetscPrintf(MPI_COMM_WORLD, "TAO failed to converge due to %s.\n",TaoConvergedReasons[reason]);CHKERRQ(ierr);
} else {
ierr = PetscPrintf(MPI_COMM_WORLD, "Optimization completed with status %s.\n",TaoConvergedReasons[reason]);CHKERRQ(ierr);
}
ierr = DestroyProblem(&user);CHKERRQ(ierr);
ierr = VecDestroy(&x);CHKERRQ(ierr);
ierr = VecDestroy(&ceq);CHKERRQ(ierr);
ierr = VecDestroy(&cin);CHKERRQ(ierr);
ierr = TaoDestroy(&tao);CHKERRQ(ierr);
ierr = PetscFinalize();
return ierr;
}
int main(int argc,char **argv)
{
Vec p;
PetscScalar *x_ptr;
PetscErrorCode ierr;
PetscMPIInt size;
AppCtx ctx;
Vec lowerb,upperb;
Tao tao;
TaoConvergedReason reason;
KSP ksp;
PC pc;
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Initialize program
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
PetscInitialize(&argc,&argv,NULL,help);
PetscFunctionBeginUser;
ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr);
if (size != 1) SETERRQ(PETSC_COMM_SELF,1,"This is a uniprocessor example only!");
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Set runtime options
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = PetscOptionsBegin(PETSC_COMM_WORLD,NULL,"Swing equation options","");CHKERRQ(ierr);
{
ctx.beta = 2;
ctx.c = 10000.0;
ctx.u_s = 1.0;
ctx.omega_s = 1.0;
ctx.omega_b = 120.0*PETSC_PI;
ctx.H = 5.0;
ierr = PetscOptionsScalar("-Inertia","","",ctx.H,&ctx.H,NULL);CHKERRQ(ierr);
ctx.D = 5.0;
ierr = PetscOptionsScalar("-D","","",ctx.D,&ctx.D,NULL);CHKERRQ(ierr);
ctx.E = 1.1378;
ctx.V = 1.0;
ctx.X = 0.545;
ctx.Pmax = ctx.E*ctx.V/ctx.X;;
ierr = PetscOptionsScalar("-Pmax","","",ctx.Pmax,&ctx.Pmax,NULL);CHKERRQ(ierr);
ctx.Pm = 0.4;
ierr = PetscOptionsScalar("-Pm","","",ctx.Pm,&ctx.Pm,NULL);CHKERRQ(ierr);
ctx.tf = 0.1;
ctx.tcl = 0.2;
ierr = PetscOptionsReal("-tf","Time to start fault","",ctx.tf,&ctx.tf,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tcl","Time to end fault","",ctx.tcl,&ctx.tcl,NULL);CHKERRQ(ierr);
}
ierr = PetscOptionsEnd();CHKERRQ(ierr);
/* Create TAO solver and set desired solution method */
ierr = TaoCreate(PETSC_COMM_WORLD,&tao);CHKERRQ(ierr);
ierr = TaoSetType(tao,TAOBLMVM);CHKERRQ(ierr);
/*
Optimization starts
*/
/* Set initial solution guess */
ierr = VecCreateSeq(PETSC_COMM_WORLD,1,&p);CHKERRQ(ierr);
ierr = VecGetArray(p,&x_ptr);CHKERRQ(ierr);
x_ptr[0] = ctx.Pm;
ierr = VecRestoreArray(p,&x_ptr);CHKERRQ(ierr);
ierr = TaoSetInitialVector(tao,p);CHKERRQ(ierr);
/* Set routine for function and gradient evaluation */
ierr = TaoSetObjectiveRoutine(tao,FormFunction,(void *)&ctx);CHKERRQ(ierr);
ierr = TaoSetGradientRoutine(tao,TaoDefaultComputeGradient,(void *)&ctx);CHKERRQ(ierr);
/* Set bounds for the optimization */
ierr = VecDuplicate(p,&lowerb);CHKERRQ(ierr);
ierr = VecDuplicate(p,&upperb);CHKERRQ(ierr);
ierr = VecGetArray(lowerb,&x_ptr);CHKERRQ(ierr);
x_ptr[0] = 0.;
ierr = VecRestoreArray(lowerb,&x_ptr);CHKERRQ(ierr);
ierr = VecGetArray(upperb,&x_ptr);CHKERRQ(ierr);
x_ptr[0] = 1.1;;
ierr = VecRestoreArray(upperb,&x_ptr);CHKERRQ(ierr);
ierr = TaoSetVariableBounds(tao,lowerb,upperb);
/* Check for any TAO command line options */
ierr = TaoSetFromOptions(tao);CHKERRQ(ierr);
ierr = TaoGetKSP(tao,&ksp);CHKERRQ(ierr);
if (ksp) {
ierr = KSPGetPC(ksp,&pc);CHKERRQ(ierr);
ierr = PCSetType(pc,PCNONE);CHKERRQ(ierr);
}
ierr = TaoSetTolerances(tao,1e-15,1e-15,1e-15,1e-15,1e-15);
/* SOLVE THE APPLICATION */
ierr = TaoSolve(tao); CHKERRQ(ierr);
/* Get information on termination */
ierr = TaoGetConvergedReason(tao,&reason);CHKERRQ(ierr);
if (reason <= 0){
ierr=PetscPrintf(MPI_COMM_WORLD, "Try another method! \n");CHKERRQ(ierr);
}
ierr = VecView(p,PETSC_VIEWER_STDOUT_WORLD);CHKERRQ(ierr);
/* Free TAO data structures */
ierr = TaoDestroy(&tao);CHKERRQ(ierr);
ierr = VecDestroy(&p);CHKERRQ(ierr);
ierr = VecDestroy(&lowerb);CHKERRQ(ierr);
ierr = VecDestroy(&upperb);CHKERRQ(ierr);
ierr = PetscFinalize();
return 0;
}
int main(int argc,char **argv)
{
TS ts; /* nonlinear solver */
Vec ic;
PetscBool monitor = PETSC_FALSE;
PetscScalar *x_ptr;
PetscMPIInt size;
struct _n_User user;
PetscErrorCode ierr;
Tao tao;
TaoConvergedReason reason;
KSP ksp;
PC pc;
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Initialize program
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
PetscInitialize(&argc,&argv,NULL,help);
ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr);
if (size != 1) SETERRQ(PETSC_COMM_SELF,1,"This is a uniprocessor example only!");
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Set runtime options
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
user.mu = 1.0;
user.next_output = 0.0;
user.steps = 0;
user.ftime = 0.5;
ierr = PetscOptionsGetReal(NULL,"-mu",&user.mu,NULL);CHKERRQ(ierr);
ierr = PetscOptionsGetBool(NULL,"-monitor",&monitor,NULL);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Create necessary matrix and vectors, solve same ODE on every process
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = MatCreate(PETSC_COMM_WORLD,&user.A);CHKERRQ(ierr);
ierr = MatSetSizes(user.A,PETSC_DECIDE,PETSC_DECIDE,2,2);CHKERRQ(ierr);
ierr = MatSetFromOptions(user.A);CHKERRQ(ierr);
ierr = MatSetUp(user.A);CHKERRQ(ierr);
ierr = MatCreateVecs(user.A,&user.x,NULL);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Create timestepping solver context
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = TSCreate(PETSC_COMM_WORLD,&ts);CHKERRQ(ierr);
ierr = TSSetType(ts,TSRK);CHKERRQ(ierr);
ierr = TSSetRHSFunction(ts,NULL,RHSFunction,&user);CHKERRQ(ierr);
ierr = TSSetDuration(ts,PETSC_DEFAULT,user.ftime);CHKERRQ(ierr);
ierr = TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP);CHKERRQ(ierr);
if (monitor) {
ierr = TSMonitorSet(ts,Monitor,&user,NULL);CHKERRQ(ierr);
}
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Set initial conditions
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = VecGetArray(user.x,&x_ptr);CHKERRQ(ierr);
x_ptr[0] = 2.0; x_ptr[1] = 0.66666654321;
ierr = VecRestoreArray(user.x,&x_ptr);CHKERRQ(ierr);
ierr = TSSetTime(ts,0.0);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD,"mu %g, steps %D, ftime %g\n",(double)user.mu,user.steps,(double)(user.ftime));CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Save trajectory of solution so that TSAdjointSolve() may be used
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = TSSetSaveTrajectory(ts);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Set runtime options
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = TSSetFromOptions(ts);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Solve nonlinear system
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = TSSolve(ts,user.x);CHKERRQ(ierr);
ierr = TSGetSolveTime(ts,&(user.ftime));CHKERRQ(ierr);
ierr = TSGetTimeStepNumber(ts,&user.steps);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD,"mu %g, steps %D, ftime %g\n",(double)user.mu,user.steps,(double)user.ftime);CHKERRQ(ierr);
ierr = VecGetArray(user.x,&x_ptr);CHKERRQ(ierr);
user.x_ob[0] = x_ptr[0];
user.x_ob[1] = x_ptr[1];
ierr = MatCreateVecs(user.A,&user.lambda[0],NULL);CHKERRQ(ierr);
/* Create TAO solver and set desired solution method */
ierr = TaoCreate(PETSC_COMM_WORLD,&tao);CHKERRQ(ierr);
ierr = TaoSetType(tao,TAOCG);CHKERRQ(ierr);
/* Set initial solution guess */
ierr = MatCreateVecs(user.A,&ic,NULL);CHKERRQ(ierr);
ierr = VecGetArray(ic,&x_ptr);CHKERRQ(ierr);
x_ptr[0] = 2.1;
x_ptr[1] = 0.7;
ierr = VecRestoreArray(ic,&x_ptr);CHKERRQ(ierr);
ierr = TaoSetInitialVector(tao,ic);CHKERRQ(ierr);
/* Set routine for function and gradient evaluation */
ierr = TaoSetObjectiveAndGradientRoutine(tao,FormFunctionGradient,(void *)&user);CHKERRQ(ierr);
/* Check for any TAO command line options */
ierr = TaoSetFromOptions(tao);CHKERRQ(ierr);
ierr = TaoGetKSP(tao,&ksp);CHKERRQ(ierr);
if (ksp) {
ierr = KSPGetPC(ksp,&pc);CHKERRQ(ierr);
ierr = PCSetType(pc,PCNONE);CHKERRQ(ierr);
}
ierr = TaoSetTolerances(tao,1e-10,1e-10,1e-10,PETSC_DEFAULT,PETSC_DEFAULT);
/* SOLVE THE APPLICATION */
ierr = TaoSolve(tao); CHKERRQ(ierr);
/* Get information on termination */
ierr = TaoGetConvergedReason(tao,&reason);CHKERRQ(ierr);
if (reason <= 0){
ierr=PetscPrintf(MPI_COMM_WORLD, "Try another method! \n");CHKERRQ(ierr);
}
/* Free TAO data structures */
ierr = TaoDestroy(&tao);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Free work space. All PETSc objects should be destroyed when they
are no longer needed.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = MatDestroy(&user.A);CHKERRQ(ierr);
ierr = VecDestroy(&user.x);CHKERRQ(ierr);
ierr = VecDestroy(&user.lambda[0]);CHKERRQ(ierr);
ierr = TSDestroy(&ts);CHKERRQ(ierr);
ierr = VecDestroy(&ic);CHKERRQ(ierr);
ierr = PetscFinalize();
PetscFunctionReturn(0);
}
void TaoOptimizationSolver<T>::solve ()
{
LOG_SCOPE("solve()", "TaoOptimizationSolver");
this->init ();
this->system().solution->zero();
PetscMatrix<T> * hessian = cast_ptr<PetscMatrix<T> *>(this->system().matrix);
// PetscVector<T> * gradient = cast_ptr<PetscVector<T> *>(this->system().rhs);
PetscVector<T> * x = cast_ptr<PetscVector<T> *>(this->system().solution.get());
PetscVector<T> * ceq = cast_ptr<PetscVector<T> *>(this->system().C_eq.get());
PetscMatrix<T> * ceq_jac = cast_ptr<PetscMatrix<T> *>(this->system().C_eq_jac.get());
PetscVector<T> * cineq = cast_ptr<PetscVector<T> *>(this->system().C_ineq.get());
PetscMatrix<T> * cineq_jac = cast_ptr<PetscMatrix<T> *>(this->system().C_ineq_jac.get());
PetscVector<T> * lb = cast_ptr<PetscVector<T> *>(&this->system().get_vector("lower_bounds"));
PetscVector<T> * ub = cast_ptr<PetscVector<T> *>(&this->system().get_vector("upper_bounds"));
// Set the starting guess to zero.
x->zero();
PetscErrorCode ierr = 0;
// Workaround for bug where TaoSetFromOptions *reset*
// programmatically set tolerance and max. function evaluation
// values when "-tao_type ipm" was specified on the command line: we
// call TaoSetFromOptions twice (both before and after setting
// custom options programatically)
ierr = TaoSetFromOptions(_tao);
LIBMESH_CHKERR(ierr);
// Set convergence tolerances
// f(X) - f(X*) (estimated) <= fatol
// |f(X) - f(X*)| (estimated) / |f(X)| <= frtol
// ||g(X)|| <= gatol
// ||g(X)|| / |f(X)| <= grtol
// ||g(X)|| / ||g(X0)|| <= gttol
// Command line equivalents: -tao_fatol, -tao_frtol, -tao_gatol, -tao_grtol, -tao_gttol
ierr = TaoSetTolerances(_tao,
#if PETSC_RELEASE_LESS_THAN(3,7,0)
// Releases up to 3.X.Y had fatol and frtol, after that they were removed.
// Hopefully we'll be able to know X and Y soon. Guessing at 3.7.0.
/*fatol=*/PETSC_DEFAULT,
/*frtol=*/PETSC_DEFAULT,
#endif
/*gatol=*/PETSC_DEFAULT,
/*grtol=*/this->objective_function_relative_tolerance,
/*gttol=*/PETSC_DEFAULT);
LIBMESH_CHKERR(ierr);
// Set the max-allowed number of objective function evaluations
// Command line equivalent: -tao_max_funcs
ierr = TaoSetMaximumFunctionEvaluations(_tao, this->max_objective_function_evaluations);
LIBMESH_CHKERR(ierr);
// Set the max-allowed number of optimization iterations.
// Command line equivalent: -tao_max_it
// Not implemented for now as it seems fairly similar to
// ierr = TaoSetMaximumIterations(_tao, 4);
// LIBMESH_CHKERR(ierr);
// Set solution vec and an initial guess
ierr = TaoSetInitialVector(_tao, x->vec());
LIBMESH_CHKERR(ierr);
// We have to have an objective function
libmesh_assert( this->objective_object );
// Set routines for objective, gradient, hessian evaluation
ierr = TaoSetObjectiveRoutine(_tao, __libmesh_tao_objective, this);
LIBMESH_CHKERR(ierr);
if ( this->gradient_object )
{
ierr = TaoSetGradientRoutine(_tao, __libmesh_tao_gradient, this);
LIBMESH_CHKERR(ierr);
}
if ( this->hessian_object )
{
ierr = TaoSetHessianRoutine(_tao, hessian->mat(), hessian->mat(), __libmesh_tao_hessian, this);
LIBMESH_CHKERR(ierr);
}
if ( this->lower_and_upper_bounds_object )
{
// Need to actually compute the bounds vectors first
this->lower_and_upper_bounds_object->lower_and_upper_bounds(this->system());
ierr = TaoSetVariableBounds(_tao,
lb->vec(),
ub->vec());
LIBMESH_CHKERR(ierr);
}
if ( this->equality_constraints_object )
{
ierr = TaoSetEqualityConstraintsRoutine(_tao, ceq->vec(), __libmesh_tao_equality_constraints, this);
LIBMESH_CHKERR(ierr);
}
if ( this->equality_constraints_jacobian_object )
{
ierr = TaoSetJacobianEqualityRoutine(_tao,
ceq_jac->mat(),
ceq_jac->mat(),
__libmesh_tao_equality_constraints_jacobian,
this);
LIBMESH_CHKERR(ierr);
}
// Optionally set inequality constraints
if ( this->inequality_constraints_object )
{
ierr = TaoSetInequalityConstraintsRoutine(_tao, cineq->vec(), __libmesh_tao_inequality_constraints, this);
LIBMESH_CHKERR(ierr);
}
// Optionally set inequality constraints Jacobian
if ( this->inequality_constraints_jacobian_object )
{
ierr = TaoSetJacobianInequalityRoutine(_tao,
cineq_jac->mat(),
cineq_jac->mat(),
__libmesh_tao_inequality_constraints_jacobian,
this);
LIBMESH_CHKERR(ierr);
}
// Check for Tao command line options
ierr = TaoSetFromOptions(_tao);
LIBMESH_CHKERR(ierr);
// Perform the optimization
ierr = TaoSolve(_tao);
LIBMESH_CHKERR(ierr);
// Store the convergence/divergence reason
ierr = TaoGetConvergedReason(_tao, &_reason);
LIBMESH_CHKERR(ierr);
}
int main(int argc,char **argv)
{
Userctx user;
Vec p;
PetscScalar *x_ptr;
PetscErrorCode ierr;
PetscMPIInt size;
PetscInt i,numDataBuses;
KSP ksp;
PC pc;
Tao tao;
TaoConvergedReason reason;
Vec lowerb,upperb;
PetscViewer viewer;
PetscScalar *proj_vec;
//PetscLogDouble t0,t1;
/* time the inversion process */
//ierr = PetscGetTime(&t0);CHKERRQ(ierr);
ierr = PetscInitialize(&argc,&argv,"petscoptions",help);CHKERRQ(ierr);
PetscFunctionBeginUser;
ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr);
if (size > 1) SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_SUP,"Only for sequential runs");
ierr = ModelSetup(&user);CHKERRQ(ierr);
/* hard code the data projection here - for now assume data at all buses */
ierr = VecCreateSeq(PETSC_COMM_WORLD,nbus,&user.proj);CHKERRQ(ierr);
/*ierr = VecCreateSeq(PETSC_COMM_WORLD,4,&user.proj);CHKERRQ(ierr);*/
ierr = VecGetArray(user.proj,&proj_vec);CHKERRQ(ierr);
for(i=0; i<nbus; i++) {
proj_vec[i]=i;
}
srand( time(NULL) + rand () );
//VecView(user.proj, PETSC_VIEWER_STDOUT_WORLD);
/* -- 2 5 6 8 */
/* -- proj_vec[0]=1; proj_vec[1]=4; proj_vec[2]=5; proj_vec[3]=7; */
ierr = VecRestoreArray(user.proj,&proj_vec);CHKERRQ(ierr);
/* allocate/set the prior mean and its standard deviation */
ierr = PetscMalloc(3*sizeof(PetscScalar), &user.prior_mean);
ierr = PetscMalloc(3*sizeof(PetscScalar), &user.prior_stddev);
/*{23.64,6.4,3.01};*/
user.prior_mean[0] = 24.0;
user.prior_mean[1] = 6.0;
user.prior_mean[2] = 3.1;
for(i=0; i<3; i++) user.prior_stddev[i] = user.prior_mean[i]*user.prior_noise;
/* Create matrix to store solution */
if(user.saveSol) {
ierr = MatCreateSeqDense(PETSC_COMM_SELF,
user.neqs_pgrid+1,
(PetscInt) round((user.tfinal-user.t0)/user.dt+1),
NULL,
&user.Sol);
CHKERRQ(ierr);
}
printf("Num cols=%d\n", (PetscInt) round((user.tfinal-user.t0)/user.dt+1));
/* *********************************
* Generate/load observations
**********************************/
ierr = VecGetSize(user.proj, &numDataBuses);CHKERRQ(ierr);
/* Create matrix to save solutions at each time step */
ierr = MatCreateSeqDense(PETSC_COMM_SELF,
2*numDataBuses,
//(PetscInt) round((user.tfinal-user.tdisturb)/user.data_dt)+1,
(PetscInt) round((user.tfinal-user.trestore)/user.data_dt)+1,
NULL,
&user.obs);
CHKERRQ(ierr);
ierr = InitializeData(H0, &user, user.data_noise, user.data_dt);CHKERRQ(ierr);
if(0==strlen(user.loadObsFile)) {
/* save observations */
ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,"obs-perturbed.bin",FILE_MODE_WRITE,&viewer);CHKERRQ(ierr);
ierr = MatView(user.obs,viewer);CHKERRQ(ierr);
ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr);
printf("Observations generated.\n");
}
if(user.saveSol) {
ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,"out_pert.bin",FILE_MODE_WRITE,&viewer);CHKERRQ(ierr);
ierr = MatView(user.Sol,viewer);CHKERRQ(ierr);
ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr);
ierr = MatDestroy(&user.Sol);CHKERRQ(ierr);
CHKERRQ(ierr);
}
if(user.outputCov) {
printf("The diagonal of the data noise covariance matrix (%g absolute noise) is:\n", user.data_noise);
for(i=0; i<2*numDataBuses; i++) printf("%18.12f ", user.data_stddev[i]*user.data_stddev[i]); printf("\n");
printf("The prior mean is: ");
for(i=0; i<3; i++) printf("%18.12f ", user.prior_mean[i]); printf("\n");
printf("The diagonal of the prior covariance matrix (%g relative noise) is:\n", user.prior_noise);
for(i=0; i<3; i++) printf("%18.12f ", user.prior_stddev[i]*user.prior_stddev[i]); printf("\n");
goto finalize;
}
/* ***************************************
* Optimization phase
* ***************************************/
/* Create TAO solver and set desired solution method */
ierr = TaoCreate(PETSC_COMM_WORLD,&tao);CHKERRQ(ierr);
ierr = TaoSetType(tao,TAOBLMVM);CHKERRQ(ierr);
/*
Optimization starts
*/
printf("Starting optimization...\n");
/* PetscScalar H_disturb[3]= {25.,6.4,3.01}; New inertia (after tdisturb) to be estimated */
/* Set initial solution guess */
ierr = VecCreateSeq(PETSC_COMM_WORLD,3,&p);CHKERRQ(ierr);
ierr = VecGetArray(p,&x_ptr);CHKERRQ(ierr);
//x_ptr[0] = H0[0]; x_ptr[1] = H0[1]; x_ptr[2] = H0[2];
x_ptr[0] = H0[0]*1.1; x_ptr[1] = H0[1]*1.1; x_ptr[2] = H0[2]*1.1;
ierr = VecRestoreArray(p,&x_ptr);CHKERRQ(ierr);
ierr = TaoSetInitialVector(tao,p);CHKERRQ(ierr);
/* Set routine for function and gradient evaluation */
//ierr = TaoSetObjectiveRoutine(tao,FormFunction,(void *)&user);CHKERRQ(ierr);
//ierr = TaoSetGradientRoutine(tao,TaoDefaultComputeGradient,(void *)&user);CHKERRQ(ierr);
/* Sets the cost and gradient evaluation routine for minimization */
ierr = TaoSetObjectiveAndGradientRoutine(tao,FormFunctionGradient,&user);CHKERRQ(ierr);
/* Set bounds for the optimization */
ierr = VecDuplicate(p,&lowerb);CHKERRQ(ierr);
ierr = VecDuplicate(p,&upperb);CHKERRQ(ierr);
ierr = VecGetArray(lowerb,&x_ptr);CHKERRQ(ierr);
x_ptr[0] = 20.64; x_ptr[1] = 5.4; x_ptr[2] = 2.01;
ierr = VecRestoreArray(lowerb,&x_ptr);CHKERRQ(ierr);
ierr = VecGetArray(upperb,&x_ptr);CHKERRQ(ierr);
x_ptr[0] = 25.64; x_ptr[1] = 7.4; x_ptr[2] = 4.01;
ierr = VecRestoreArray(upperb,&x_ptr);CHKERRQ(ierr);
ierr = TaoSetVariableBounds(tao,lowerb,upperb);
/* Check for any TAO command line options */
ierr = TaoSetFromOptions(tao);CHKERRQ(ierr);
ierr = TaoGetKSP(tao,&ksp);CHKERRQ(ierr);
if (ksp) {
ierr = KSPGetPC(ksp,&pc);CHKERRQ(ierr);
ierr = PCSetType(pc,PCNONE);CHKERRQ(ierr);
}
//ierr = TaoSetTolerances(tao,1e-8,1e-6,1e-8,1e-6,1e-4);
ierr = TaoSetTolerances(tao,1e-8,1e-8,1e-8,1e-8,1e-6);
//ierr = TaoSetGradientTolerances(tao,1e-8, 1e-6, 1e-6);
/* SOLVE the estimation problem */
ierr = TaoSolve(tao); CHKERRQ(ierr);
/* Get information on termination */
printf("--- optimization done\n");
/* time the inversion process */
//ierr = PetscGetTime(&t1);CHKERRQ(ierr);
//printf("elapsed_time %f seconds\n", t1 - t0);
ierr = TaoGetConvergedReason(tao,&reason);CHKERRQ(ierr);
if (reason <= 0){
ierr=PetscPrintf(MPI_COMM_WORLD, "Try another method! \n");CHKERRQ(ierr);
}
/*ierr = VecView(p,PETSC_VIEWER_STDOUT_WORLD);CHKERRQ(ierr);*/
ierr = VecGetArray(p,&x_ptr);CHKERRQ(ierr);
printf("inertia-out: %.12f %.12f %.12f\n", x_ptr[0], x_ptr[1], x_ptr[2]);
ierr = VecRestoreArray(p,&x_ptr);CHKERRQ(ierr);
//ierr = EvaluateHessianFD(tao, p, &user);CHKERRQ(ierr);
/* Free TAO data structures */
ierr = TaoDestroy(&tao);CHKERRQ(ierr);
ierr = VecDestroy(&lowerb);CHKERRQ(ierr);
ierr = VecDestroy(&upperb);CHKERRQ(ierr);
finalize:
ierr = MatDestroy(&user.obs);CHKERRQ(ierr);
ierr = VecDestroy(&user.X0_disturb);CHKERRQ(ierr);
ierr = PetscFree(user.data_stddev);CHKERRQ(ierr);
PetscFree(user.prior_mean);
PetscFree(user.prior_stddev);
ierr = DMDestroy(&user.dmgen);CHKERRQ(ierr);
ierr = DMDestroy(&user.dmnet);CHKERRQ(ierr);
ierr = DMDestroy(&user.dmpgrid);CHKERRQ(ierr);
ierr = ISDestroy(&user.is_diff);CHKERRQ(ierr);
ierr = ISDestroy(&user.is_alg);CHKERRQ(ierr);
ierr = MatDestroy(&user.J);CHKERRQ(ierr);
ierr = MatDestroy(&user.Jacp);CHKERRQ(ierr);
ierr = MatDestroy(&user.Ybus);CHKERRQ(ierr);
ierr = VecDestroy(&user.V0);CHKERRQ(ierr);
ierr = VecDestroy(&p);CHKERRQ(ierr);
ierr = PetscFinalize();
return(0);
}
PetscErrorCode main(int argc,char **argv)
{
PetscErrorCode ierr; /* used to check for functions returning nonzeros */
Tao tao;
KSP ksp;
PC pc;
AppCtx user; /* application context */
ierr = PetscInitialize(&argc,&argv,(char *)0,help);
CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD,"\n---- TOY Problem -----\n");
CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD,"Solution should be f(1,1)=-2\n");
CHKERRQ(ierr);
ierr = InitializeProblem(&user);
CHKERRQ(ierr);
ierr = TaoCreate(PETSC_COMM_WORLD,&tao);
CHKERRQ(ierr);
ierr = TaoSetType(tao,TAOIPM);
CHKERRQ(ierr);
ierr = TaoSetInitialVector(tao,user.x);
CHKERRQ(ierr);
ierr = TaoSetVariableBounds(tao,user.xl,user.xu);
CHKERRQ(ierr);
ierr = TaoSetObjectiveAndGradientRoutine(tao,FormFunctionGradient,(void*)&user);
CHKERRQ(ierr);
ierr = TaoSetEqualityConstraintsRoutine(tao,user.ce,FormEqualityConstraints,(void*)&user);
CHKERRQ(ierr);
ierr = TaoSetInequalityConstraintsRoutine(tao,user.ci,FormInequalityConstraints,(void*)&user);
CHKERRQ(ierr);
ierr = TaoSetJacobianEqualityRoutine(tao,user.Ae,user.Ae,FormEqualityJacobian,(void*)&user);
CHKERRQ(ierr);
ierr = TaoSetJacobianInequalityRoutine(tao,user.Ai,user.Ai,FormInequalityJacobian,(void*)&user);
CHKERRQ(ierr);
ierr = TaoSetHessianRoutine(tao,user.H,user.H,FormHessian,(void*)&user);
CHKERRQ(ierr);
ierr = TaoSetTolerances(tao,0,0,0);
CHKERRQ(ierr);
ierr = TaoSetFromOptions(tao);
CHKERRQ(ierr);
ierr = TaoGetKSP(tao,&ksp);
CHKERRQ(ierr);
ierr = KSPGetPC(ksp,&pc);
CHKERRQ(ierr);
ierr = PCSetType(pc,PCLU);
CHKERRQ(ierr);
/*
This algorithm produces matrices with zeros along the diagonal therefore we need to use
SuperLU which does partial pivoting
*/
ierr = PCFactorSetMatSolverPackage(pc,MATSOLVERSUPERLU);
CHKERRQ(ierr);
ierr = KSPSetType(ksp,KSPPREONLY);
CHKERRQ(ierr);
ierr = KSPSetFromOptions(ksp);
CHKERRQ(ierr);
ierr = TaoSetTolerances(tao,0,0,0);
CHKERRQ(ierr);
ierr = TaoSolve(tao);
CHKERRQ(ierr);
ierr = DestroyProblem(&user);
CHKERRQ(ierr);
ierr = TaoDestroy(&tao);
CHKERRQ(ierr);
ierr = PetscFinalize();
return ierr;
}