GSLSimAnFunc class description. Interface class for the objetive function to be used in simulated annealing If user wants to re-implement some of the methods (like the one defining the metric) which are used by the the simulated annealing algorithm must build a user derived class. NOTE: Derived classes must re-implement the assignment and copy constructor to call them of the parent class @ingroup MultiMin
virtual | ~GSLSimAnFunc() |
virtual ROOT::Math::GSLSimAnFunc* | Clone() const |
virtual double | Distance(const ROOT::Math::GSLSimAnFunc& func) const |
virtual double | Energy() const |
virtual ROOT::Math::GSLSimAnFunc& | FastCopy(const ROOT::Math::GSLSimAnFunc& f) |
ROOT::Math::GSLSimAnFunc | GSLSimAnFunc(const ROOT::Math::GSLSimAnFunc&) |
ROOT::Math::GSLSimAnFunc | GSLSimAnFunc(const ROOT::Math::IMultiGenFunction& func, const double* x) |
ROOT::Math::GSLSimAnFunc | GSLSimAnFunc(const ROOT::Math::IMultiGenFunction& func, const double* x, const double* scale) |
unsigned int | NDim() const |
virtual void | Print() |
double | Scale(unsigned int i) const |
void | SetX(const double* x) |
void | SetX(unsigned int i, double x) |
virtual void | Step(const ROOT::Math::GSLRandomEngine& r, double maxstep) |
const vector<double>& | X() const |
double | X(unsigned int i) const |
ROOT::Math::GSLSimAnFunc | GSLSimAnFunc() |
const ROOT::Math::IMultiGenFunction* | fFunc | |
vector<double> | fScale | |
vector<double> | fX |
construct from an interface of a multi-dimensional function
construct from an interface of a multi-dimensional function Use optionally a scale factor (for each coordinate) which can be used to scale the step sizes (this is used for example by the minimization algorithm)
fast copy method called by GSL simuated annealing internally copy only the things which have been changed must be re-implemented by derived classes if needed
clone method. Needs to be re-implemented by the derived classes for deep copying
evaluate the energy ( objective function value) re-implement by derived classes if needed to be modified
change the x[i] value using a random value urndm generated between [0,1] up to a maximum value maxstep re-implement by derived classes if needed to be modified
calculate the distance (metric) between this one and another configuration Presently a cartesian metric is used. re-implement by derived classes if needed to be modified
print the position in the standard output ostream GSL prints in addition n iteration, n function calls, temperature and energy re-implement by derived classes if necessary