#include "petsctaolinesearch.h" PetscErrorCode TaoLineSearchApply(TaoLineSearch ls, Vec x, PetscReal *f, Vec g, Vec s, PetscReal *steplength, TaoLineSearchConvergedReason *reason)Collective on TaoLineSearch
| ls | - the Tao context | |
| s | - search direction |
| x | - The current solution (on output x contains the new solution determined by the line search) | |
| f | - objective function value at current solution (on output contains the objective function value at new solution) | |
| g | - gradient evaluated at x (on output contains the gradient at new solution) |
| steplength | - scalar multiplier of s used ( x = x0 + steplength * x) | |
| reason | - reason why the line-search stopped |
| TAOLINESEARCH_FAILED_ASCENT | - initial line search step * g is not descent direction | |
| TAOLINESEARCH_FAILED_INFORNAN | - function evaluation gives Inf or Nan value | |
| TAOLINESEARCH_FAILED_BADPARAMETER | - negative value set as parameter | |
| TAOLINESEARCH_HALTED_MAXFCN | - maximum number of function evaluation reached | |
| TAOLINESEARCH_HALTED_UPPERBOUND | - step is at upper bound | |
| TAOLINESEARCH_HALTED_LOWERBOUND | - step is at lower bound | |
| TAOLINESEARCH_HALTED_RTOL | - range of uncertainty is smaller than given tolerance | |
| TAOLINESEARCH_HALTED_USER | - user can set this reason to stop line search | |
| TAOLINESEARCH_HALTED_OTHER | - any other reason | |
| TAOLINESEARCH_SUCCESS | - successful line search |
The algorithm developer must set up the TaoLineSearch with calls to TaoLineSearchSetObjectiveRoutine() and TaoLineSearchSetGradientRoutine(), TaoLineSearchSetObjectiveAndGradientRoutine(), or TaoLineSearchUseTaoRoutines()
You may or may not need to follow this with a call to TaoAddLineSearchCounts(), depending on whether you want these evaluations to count toward the total function/gradient evaluations.
.seealso: TaoLineSearchCreate(), TaoLineSearchSetType(), TaoLineSearchSetInitialStepLength(), TaoAddLineSearchCounts()