#include <../src/snes/impls/richardson/snesrichardsonimpl.h> #undef __FUNCT__ #define __FUNCT__ "SNESReset_NRichardson" PetscErrorCode SNESReset_NRichardson(SNES snes) { PetscErrorCode ierr; PetscFunctionBegin; if (snes->work) {ierr = VecDestroyVecs(snes->nwork,&snes->work);CHKERRQ(ierr);} PetscFunctionReturn(0); } /* SNESDestroy_NRichardson - Destroys the private SNES_NRichardson context that was created with SNESCreate_NRichardson(). Input Parameter: . snes - the SNES context Application Interface Routine: SNESDestroy() */ #undef __FUNCT__ #define __FUNCT__ "SNESDestroy_NRichardson" PetscErrorCode SNESDestroy_NRichardson(SNES snes) { PetscErrorCode ierr; PetscFunctionBegin; ierr = SNESReset_NRichardson(snes);CHKERRQ(ierr); ierr = PetscFree(snes->data);CHKERRQ(ierr); PetscFunctionReturn(0); } /* SNESSetUp_NRichardson - Sets up the internal data structures for the later use of the SNESNRICHARDSON nonlinear solver. Input Parameters: + snes - the SNES context - x - the solution vector Application Interface Routine: SNESSetUp() */ #undef __FUNCT__ #define __FUNCT__ "SNESSetUp_NRichardson" PetscErrorCode SNESSetUp_NRichardson(SNES snes) { PetscErrorCode ierr; PetscFunctionBegin; ierr = SNESDefaultGetWork(snes,1);CHKERRQ(ierr); PetscFunctionReturn(0); } /* SNESSetFromOptions_NRichardson - Sets various parameters for the SNESLS method. Input Parameter: . snes - the SNES context Application Interface Routine: SNESSetFromOptions() */ #undef __FUNCT__ #define __FUNCT__ "SNESSetFromOptions_NRichardson" static PetscErrorCode SNESSetFromOptions_NRichardson(SNES snes) { PetscErrorCode ierr; PetscFunctionBegin; ierr = PetscOptionsHead("SNES Richardson options");CHKERRQ(ierr); ierr = PetscOptionsTail();CHKERRQ(ierr); PetscFunctionReturn(0); } /* SNESView_NRichardson - Prints info from the SNESRichardson data structure. Input Parameters: + SNES - the SNES context - viewer - visualization context Application Interface Routine: SNESView() */ #undef __FUNCT__ #define __FUNCT__ "SNESView_NRichardson" static PetscErrorCode SNESView_NRichardson(SNES snes, PetscViewer viewer) { PetscBool iascii; PetscErrorCode ierr; PetscFunctionBegin; ierr = PetscTypeCompare((PetscObject) viewer, PETSCVIEWERASCII, &iascii);CHKERRQ(ierr); if (iascii) { ierr = PetscViewerASCIIPrintf(viewer," richardson variant: %s\n", SNESLineSearchTypeName(snes->ls_type));CHKERRQ(ierr); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "SNESLineSearchNo_NRichardson" PetscErrorCode SNESLineSearchNo_NRichardson(SNES snes,void *lsctx,Vec X,Vec F,Vec Y,PetscReal fnorm,PetscReal dummyXnorm,Vec dummyG,Vec W,PetscReal *dummyYnorm,PetscReal *gnorm,PetscBool *flag) { PetscErrorCode ierr; PetscFunctionBegin; ierr = VecAXPY(X, snes->damping, Y);CHKERRQ(ierr); ierr = SNESComputeFunction(snes, X, F);CHKERRQ(ierr); ierr = VecNorm(F, NORM_2, gnorm);CHKERRQ(ierr); if (PetscIsInfOrNanReal(*gnorm)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FP,"Infinite or not-a-number generated norm"); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "SNESLineSearchNoNorms_NRichardson" PetscErrorCode SNESLineSearchNoNorms_NRichardson(SNES snes,void *lsctx,Vec X,Vec F,Vec Y,PetscReal fnorm,PetscReal dummyXnorm,Vec dummyG,Vec W,PetscReal *dummyYnorm,PetscReal *gnorm,PetscBool *flag) { PetscErrorCode ierr; PetscFunctionBegin; ierr = VecAXPY(X, snes->damping, Y);CHKERRQ(ierr); ierr = SNESComputeFunction(snes, X, F);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "SNESLineSearchQuadratic_NRichardson" PetscErrorCode SNESLineSearchQuadratic_NRichardson(SNES snes,void *lsctx,Vec X,Vec F,Vec Y,PetscReal fnorm,PetscReal dummyXnorm,Vec G,Vec W,PetscReal *dummyYnorm,PetscReal *gnorm,PetscBool *flag) { PetscInt i; PetscReal alphas[3] = {0.0, 0.5, 1.0}; PetscReal norms[3]; PetscReal alpha,a,b; PetscErrorCode ierr; PetscFunctionBegin; norms[0] = fnorm; for(i=1; i < 3; ++i) { ierr = VecWAXPY(W, alphas[i], Y, X);CHKERRQ(ierr); /* W = X^n - \alpha Y */ ierr = SNESComputeFunction(snes, W, F);CHKERRQ(ierr); ierr = VecNorm(F, NORM_2, &norms[i]);CHKERRQ(ierr); } for(i = 0; i < 3; ++i) { norms[i] = PetscSqr(norms[i]); } /* Fit a quadratic: If we have x_{0,1,2} = 0, x_1, x_2 which generate norms y_{0,1,2} a = (x_1 y_2 - x_2 y_1 + (x_2 - x_1) y_0)/(x^2_2 x_1 - x_2 x^2_1) b = (x^2_1 y_2 - x^2_2 y_1 + (x^2_2 - x^2_1) y_0)/(x_2 x^2_1 - x^2_2 x_1) c = y_0 x_min = -b/2a If we let x_{0,1,2} = 0, 0.5, 1.0 a = 2 y_2 - 4 y_1 + 2 y_0 b = -y_2 + 4 y_1 - 3 y_0 c = y_0 */ a = (alphas[1]*norms[2] - alphas[2]*norms[1] + (alphas[2] - alphas[1])*norms[0])/(PetscSqr(alphas[2])*alphas[1] - alphas[2]*PetscSqr(alphas[1])); b = (PetscSqr(alphas[1])*norms[2] - PetscSqr(alphas[2])*norms[1] + (PetscSqr(alphas[2]) - PetscSqr(alphas[1]))*norms[0])/(alphas[2]*PetscSqr(alphas[1]) - PetscSqr(alphas[2])*alphas[1]); /* Check for positive a (concave up) */ if (a >= 0.0) { alpha = -b/(2.0*a); alpha = PetscMin(alpha, alphas[2]); alpha = PetscMax(alpha, alphas[0]); } else { alpha = 1.0; } if (snes->ls_monitor) { ierr = PetscViewerASCIIAddTab(snes->ls_monitor,((PetscObject)snes)->tablevel);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(snes->ls_monitor," Line search: norms[0] = %g, norms[1] = %g, norms[2] = %g alpha %g\n", sqrt(norms[0]),sqrt(norms[1]),sqrt(norms[2]),alpha);CHKERRQ(ierr); ierr = PetscViewerASCIISubtractTab(snes->ls_monitor,((PetscObject)snes)->tablevel);CHKERRQ(ierr); } ierr = VecAXPY(X, alpha, Y);CHKERRQ(ierr); if (alpha != 1.0) { ierr = SNESComputeFunction(snes, X, F);CHKERRQ(ierr); ierr = VecNorm(F, NORM_2, gnorm);CHKERRQ(ierr); } else { *gnorm = PetscSqrtReal(norms[2]); } if (alpha == 0.0) *flag = PETSC_FALSE; else *flag = PETSC_TRUE; PetscFunctionReturn(0); } /* SNESSolve_NRichardson - Solves a nonlinear system with the Richardson method. Input Parameters: . snes - the SNES context Output Parameter: . outits - number of iterations until termination Application Interface Routine: SNESSolve() */ #undef __FUNCT__ #define __FUNCT__ "SNESSolve_NRichardson" PetscErrorCode SNESSolve_NRichardson(SNES snes) { Vec X, Y, F, W; PetscReal fnorm; PetscInt maxits, i; PetscErrorCode ierr; SNESConvergedReason reason; PetscFunctionBegin; snes->reason = SNES_CONVERGED_ITERATING; maxits = snes->max_its; /* maximum number of iterations */ X = snes->vec_sol; /* X^n */ Y = snes->vec_sol_update; /* \tilde X */ F = snes->vec_func; /* residual vector */ W = snes->work[0]; /* work vector */ ierr = PetscObjectTakeAccess(snes);CHKERRQ(ierr); snes->iter = 0; snes->norm = 0.; ierr = PetscObjectGrantAccess(snes);CHKERRQ(ierr); ierr = SNESComputeFunction(snes,X,F);CHKERRQ(ierr); if (snes->domainerror) { snes->reason = SNES_DIVERGED_FUNCTION_DOMAIN; PetscFunctionReturn(0); } ierr = VecNorm(F, NORM_2, &fnorm);CHKERRQ(ierr); /* fnorm <- ||F|| */ if (PetscIsInfOrNanReal(fnorm)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); ierr = PetscObjectTakeAccess(snes);CHKERRQ(ierr); snes->norm = fnorm; ierr = PetscObjectGrantAccess(snes);CHKERRQ(ierr); SNESLogConvHistory(snes,fnorm,0); ierr = SNESMonitor(snes,0,fnorm);CHKERRQ(ierr); /* set parameter for default relative tolerance convergence test */ snes->ttol = fnorm*snes->rtol; /* test convergence */ ierr = (*snes->ops->converged)(snes,0,0.0,0.0,fnorm,&snes->reason,snes->cnvP);CHKERRQ(ierr); if (snes->reason) PetscFunctionReturn(0); for(i = 0; i < maxits; i++) { PetscBool lsSuccess = PETSC_TRUE; PetscReal dummyNorm; /* Call general purpose update function */ if (snes->ops->update) { ierr = (*snes->ops->update)(snes, snes->iter);CHKERRQ(ierr); } if (!snes->pc) { ierr = VecCopy(F,Y);CHKERRQ(ierr); ierr = VecScale(Y,-1.0);CHKERRQ(ierr); } else { ierr = VecCopy(X,Y);CHKERRQ(ierr); ierr = SNESSolve(snes->pc, snes->vec_rhs, Y);CHKERRQ(ierr); ierr = SNESGetConvergedReason(snes->pc,&reason);CHKERRQ(ierr); if (reason < 0 && reason != SNES_DIVERGED_MAX_IT) { snes->reason = SNES_DIVERGED_INNER; PetscFunctionReturn(0); } ierr = VecAXPY(Y,-1.0,X);CHKERRQ(ierr); } ierr = (*snes->ops->linesearch)(snes, snes->lsP, X, F, Y, fnorm, 0.0, 0, W, &dummyNorm, &fnorm, &lsSuccess);CHKERRQ(ierr); if (!lsSuccess) { if (++snes->numFailures >= snes->maxFailures) { snes->reason = SNES_DIVERGED_LINE_SEARCH; break; } } if (snes->nfuncs >= snes->max_funcs) { snes->reason = SNES_DIVERGED_FUNCTION_COUNT; break; } if (snes->domainerror) { snes->reason = SNES_DIVERGED_FUNCTION_DOMAIN; PetscFunctionReturn(0); } /* Monitor convergence */ ierr = PetscObjectTakeAccess(snes);CHKERRQ(ierr); snes->iter = i+1; snes->norm = fnorm; ierr = PetscObjectGrantAccess(snes);CHKERRQ(ierr); SNESLogConvHistory(snes,snes->norm,0); ierr = SNESMonitor(snes,snes->iter,snes->norm);CHKERRQ(ierr); /* Test for convergence */ ierr = (*snes->ops->converged)(snes,snes->iter,0.0,0.0,fnorm,&snes->reason,snes->cnvP);CHKERRQ(ierr); if (snes->reason) break; } if (i == maxits) { ierr = PetscInfo1(snes, "Maximum number of iterations has been reached: %D\n", maxits);CHKERRQ(ierr); if (!snes->reason) snes->reason = SNES_DIVERGED_MAX_IT; } PetscFunctionReturn(0); } EXTERN_C_BEGIN #undef __FUNCT__ #define __FUNCT__ "SNESLineSearchSetType_NRichardson" PetscErrorCode SNESLineSearchSetType_NRichardson(SNES snes, SNESLineSearchType type) { PetscErrorCode ierr; PetscFunctionBegin; switch (type) { case SNES_LS_BASIC: ierr = SNESLineSearchSet(snes,SNESLineSearchNo_NRichardson,PETSC_NULL);CHKERRQ(ierr); break; case SNES_LS_BASIC_NONORMS: ierr = SNESLineSearchSet(snes,SNESLineSearchNoNorms_NRichardson,PETSC_NULL);CHKERRQ(ierr); break; case SNES_LS_QUADRATIC: ierr = SNESLineSearchSet(snes,SNESLineSearchQuadratic_NRichardson,PETSC_NULL);CHKERRQ(ierr); break; default: SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP,"Unknown line search type"); break; } snes->ls_type = type; PetscFunctionReturn(0); } EXTERN_C_END /*MC SNESNRICHARDSON - Richardson nonlinear solver that uses successive substitutions, also sometimes known as Picard iteration. Level: beginner Options Database: + -snes_ls_damping - damping factor to apply to F(x) (used only if -snes_ls is basic or basicnonorms) - -snes_ls Notes: If no inner nonlinear preconditioner is provided then solves F(x) - b = 0 using x^{n+1} = x^{n} - lambda (F(x^n) - b) where lambda is obtained either SNESLineSearchSetDamping(), -snes_damping or a line search. If an inner nonlinear preconditioner is provided (either with -npc_snes_type or SNESSetPC()) then the inner solver is called an initial solution x^n and the nonlinear Richardson uses x^{n+1} = x^{n} + lambda d^{n} where d^{n} = \hat{x}^{n} - x^{n} where \hat{x}^{n} is the solution returned from the inner solver. This uses no derivative information thus will be much slower then Newton's method obtained with -snes_type ls .seealso: SNESCreate(), SNES, SNESSetType(), SNESLS, SNESTR, SNESNGMRES, SNESNQN M*/ EXTERN_C_BEGIN #undef __FUNCT__ #define __FUNCT__ "SNESCreate_NRichardson" PetscErrorCode SNESCreate_NRichardson(SNES snes) { PetscErrorCode ierr; PetscFunctionBegin; snes->ops->destroy = SNESDestroy_NRichardson; snes->ops->setup = SNESSetUp_NRichardson; snes->ops->setfromoptions = SNESSetFromOptions_NRichardson; snes->ops->view = SNESView_NRichardson; snes->ops->solve = SNESSolve_NRichardson; snes->ops->reset = SNESReset_NRichardson; snes->usesksp = PETSC_FALSE; snes->usespc = PETSC_TRUE; ierr = PetscObjectComposeFunctionDynamic((PetscObject)snes,"SNESLineSearchSetType_C","SNESLineSearchSetType_NRichardson",SNESLineSearchSetType_NRichardson);CHKERRQ(ierr); ierr = SNESLineSearchSetType(snes, SNES_LS_QUADRATIC);CHKERRQ(ierr); PetscFunctionReturn(0); } EXTERN_C_END