1: /*
2: Context for conjugate gradient method (unconstrained minimization)
3: */
6: #ifndef __TAO_CG_H
9: #include <petsc/private/taoimpl.h> 11: typedef struct {
12: Vec G_old;
13: Vec X_old;
14: Vec W; /* work vector */
16: PetscReal eta; /* Restart tolerance */
17: PetscReal delta_max; /* Minimum value for scaling */
18: PetscReal delta_min; /* Maximum value for scaling */
21: /* The algorithm restarts when the gradient at the current point g_k,
22: and the gradient of the previous point, g_{k-1}, satisfy the
23: following inequality:
25: abs(inner(g_k, g_{k-1})) > eta * norm(g_k, 2)^2. */
27: PetscInt ngradsteps; /* Number of gradient steps */
28: PetscInt nresetsteps; /* Number of reset steps */
30: PetscInt cg_type; /* Formula to use */
31: } TAO_CG;
33: #endif /* ifndef __TAO_CG_H */