1: /*$Id: lsparams.c,v 1.12 2001/08/06 21:17:15 bsmith Exp $*/

 3:  #include src/snes/impls/ls/ls.h

  5: #undef __FUNCT__  
  7: /*@C
  8:    SNESSetLineSearchParams - Sets the parameters associated with the line search
  9:    routine in the Newton-based method SNESLS.

 11:    Collective on SNES

 13:    Input Parameters:
 14: +  snes    - The nonlinear context obtained from SNESCreate()
 15: .  alpha   - The scalar such that .5*f_{n+1} . f_{n+1} <= .5*f_n . f_n - alpha |f_n . J . f_n|
 16: .  maxstep - The maximum norm of the update vector
 17: -  steptol - The minimum norm fraction of the original step after scaling

 19:    Level: intermediate

 21:    Note:
 22:    Pass in PETSC_DEFAULT for any parameter you do not wish to change.

 24:    We are finding the zero of f() so the one dimensional minimization problem we are
 25:    solving in the line search is minimize .5*f(x_n + lambda*step_direction) . f(x_n + lambda*step_direction)

 27:    Contributed by: Mathew Knepley

 29: .keywords: SNES, nonlinear, set, line search params

 31: .seealso: SNESGetLineSearchParams(), SNESSetLineSearch()
 32: @*/
 33: int SNESSetLineSearchParams(SNES snes,PetscReal alpha,PetscReal maxstep,PetscReal steptol)
 34: {
 35:   SNES_LS *ls;


 40:   ls = (SNES_LS*)snes->data;
 41:   if (alpha   >= 0.0) ls->alpha   = alpha;
 42:   if (maxstep >= 0.0) ls->maxstep = maxstep;
 43:   if (steptol >= 0.0) ls->steptol = steptol;
 44:   return(0);
 45: }

 47: #undef __FUNCT__  
 49: /*@C
 50:    SNESGetLineSearchParams - Gets the parameters associated with the line search
 51:      routine in the Newton-based method SNESLS.

 53:    Not collective, but any processor will return the same values

 55:    Input Parameters:
 56: +  snes    - The nonlinear context obtained from SNESCreate()
 57: .  alpha   - The scalar such that .5*f_{n+1} . f_{n+1} <= .5*f_n . f_n - alpha |f_n . J . f_n|
 58: .  maxstep - The maximum norm of the update vector
 59: -  steptol - The minimum norm fraction of the original step after scaling

 61:    Level: intermediate

 63:    Note:
 64:     To not get a certain parameter, pass in PETSC_NULL

 66:    We are finding the zero of f() so the one dimensional minimization problem we are
 67:    solving in the line search is minimize .5*f(x_n + lambda*step_direction) . f(x_n + lambda*step_direction)

 69:    Contributed by: Mathew Knepley

 71: .keywords: SNES, nonlinear, set, line search parameters

 73: .seealso: SNESSetLineSearchParams(), SNESSetLineSearch()
 74: @*/
 75: int SNESGetLineSearchParams(SNES snes,PetscReal *alpha,PetscReal *maxstep,PetscReal *steptol)
 76: {
 77:   SNES_LS *ls;


 82:   ls = (SNES_LS*)snes->data;
 83:   if (alpha) {
 85:     *alpha   = ls->alpha;
 86:   }
 87:   if (maxstep) {
 89:     *maxstep = ls->maxstep;
 90:   }
 91:   if (steptol) {
 93:     *steptol = ls->steptol;
 94:   }
 95:   return(0);
 96: }