A class for goal-oriented adaptive solution of nonlinear variational problems. For a nonlinear variational problem of the form: find u in V satisfying
F(u; v) = 0 for all v in :math:`\hat V`
and a corresponding conforming discrete problem: find u_h in V_h satisfying (at least approximately)
F(u_h; v) = 0 for all v in :math:`\hat V_h`
and a given goal functional M and tolerance tol, the aim is to find a V_H and a u_H in V_H satisfying the discrete problem such that
\|M(u) - M(u_H)\| < tol
This strategy is based on dual-weighted residual error estimators designed and automatically generated for the primal problem and subsequent h-adaptivity.
Solve such that the estimated error in the functional ‘goal’ is less than the given tolerance ‘tol’.
tol (float)The error tolerance