IMP  2.2.1
The Integrative Modeling Platform
IMP::core::MonteCarloWithBasinHopping Class Reference

This variant of Monte Carlo uses basis hopping. More...

#include <IMP/core/MonteCarlo.h>

+ Inheritance diagram for IMP::core::MonteCarloWithBasinHopping:

Public Member Functions

 MonteCarloWithBasinHopping (Optimizer *opt, unsigned int ns)
 
virtual std::string get_type_name () const
 
virtual ::IMP::base::VersionInfo get_version_info () const
 Get information about the module and version of the object.
 
- Public Member Functions inherited from IMP::core::MonteCarloWithLocalOptimization
 MonteCarloWithLocalOptimization (Optimizer *opt, unsigned int steps)
 
Optimizerget_local_optimizer () const
 
unsigned int get_number_of_steps () const
 
- Public Member Functions inherited from IMP::core::MonteCarlo
 MonteCarlo (kernel::Model *m)
 
double get_best_accepted_energy () const
 
double get_last_accepted_energy () const
 
double get_maximum_difference () const
 
double get_score_threshold () const
 Get the score threshold.
 
void set_maximum_difference (double d)
 
void set_return_best (bool tf)
 
void set_score_threshold (double s)
 Set the score threshold.
 
void set_kt (Float t)
 
Float get_kt () const
 
unsigned int get_number_of_forward_steps () const
 Return how many times the optimizer has succeeded in taking a step. More...
 
unsigned int get_number_of_downward_steps () const
 Return how many times the optimizer has stepped to lower score.
 
unsigned int get_number_of_upward_steps () const
 Return how many times the optimizer has stepped to higher score.
 
unsigned int get_number_of_proposed_steps () const
 Get number of proposed moves.
 
unsigned int get_number_of_accepted_steps () const
 Get number of accepted moves.
 
void reset_statistics ()
 
void remove_mover (MonteCarloMover *d)
 
void remove_movers (const MonteCarloMovers &d)
 
void set_movers (const MonteCarloMovers &ps)
 
void set_movers_order (const MonteCarloMovers &objs)
 
unsigned int add_mover (MonteCarloMover *obj)
 
void add_movers (const MonteCarloMovers &objs)
 
void clear_movers ()
 
unsigned int get_number_of_movers () const
 
bool get_has_movers ()
 
MonteCarloMoverget_mover (unsigned int i) const
 
MonteCarloMovers get_movers () const
 
void reserve_movers (unsigned int sz)
 
void set_incremental_scoring_function (IncrementalScoringFunction *isf)
 
bool get_use_incremental_scoring_function () const
 
IncrementalScoringFunctionget_incremental_scoring_function () const
 
- Public Member Functions inherited from IMP::kernel::Optimizer
 Optimizer (kernel::Model *m, std::string name="Optimizer %1%")
 
double get_last_score () const
 Return the score found in the last evaluate.
 
ScoringFunctionget_scoring_function () const
 Return the scoring function that is being used.
 
bool get_stop_on_good_score () const
 
double optimize (unsigned int max_steps)
 Optimize the model for up to max_steps iterations. More...
 
virtual void set_scoring_function (ScoringFunctionAdaptor sf)
 
void set_stop_on_good_score (bool tf)
 
void remove_optimizer_state (OptimizerState *d)
 
void remove_optimizer_states (const OptimizerStates &d)
 
void set_optimizer_states (const OptimizerStates &ps)
 
void set_optimizer_states_order (const OptimizerStates &objs)
 
unsigned int add_optimizer_state (OptimizerState *obj)
 
void add_optimizer_states (const OptimizerStates &objs)
 
void clear_optimizer_states ()
 
unsigned int get_number_of_optimizer_states () const
 
bool get_has_optimizer_states ()
 
OptimizerStateget_optimizer_state (unsigned int i) const
 
OptimizerStates get_optimizer_states () const
 
void reserve_optimizer_states (unsigned int sz)
 
- Public Member Functions inherited from IMP::kernel::ModelObject
 ModelObject (kernel::Model *m, std::string name)
 
bool get_has_dependencies () const
 Return whether this object has dependencies computed.
 
bool get_has_required_score_states () const
 
ModelObjectsTemp get_inputs () const
 
ModelObjectsTemps get_interactions () const
 
Modelget_model () const
 
ModelObjectsTemp get_outputs () const
 
const ScoreStatesTempget_required_score_states () const
 
void set_has_dependencies (bool tf)
 
void set_has_required_score_states (bool tf)
 
- Public Member Functions inherited from IMP::base::Object
virtual void clear_caches ()
 
virtual void do_destroy ()
 
CheckLevel get_check_level () const
 
LogLevel get_log_level () const
 
void set_check_level (CheckLevel l)
 
void set_log_level (LogLevel l)
 Set the logging level used in this object. More...
 
void set_was_used (bool tf) const
 
void show (std::ostream &out=std::cout) const
 
const std::string & get_name () const
 
void set_name (std::string name)
 

Protected Member Functions

virtual void do_step ()
 a class that inherits from this should override this method
 
- Protected Member Functions inherited from IMP::core::MonteCarlo
bool do_accept_or_reject_move (double score, double last, double proposal_ratio)
 
bool do_accept_or_reject_move (double score, double proposal_ratio)
 
virtual double do_evaluate (const kernel::ParticleIndexes &moved) const
 Get the current energy. More...
 
MonteCarloMoverResult do_move ()
 
virtual Float do_optimize (unsigned int max_steps)
 override this function to do actual optimization
 
kernel::ParticleIndexes get_movable_particles () const
 
- Protected Member Functions inherited from IMP::kernel::Optimizer
virtual ModelObjectsTemp do_get_inputs () const
 
virtual ModelObjectsTemp do_get_outputs () const
 don't return anything here to avoid pointless dependencies
 
ModelObjectsTemp get_optimizer_state_inputs () const
 
void update_states () const
 Update optimizer states, should be called at each successful step. More...
 
- Protected Member Functions inherited from IMP::kernel::ModelObject
virtual ModelObjectsTemps do_get_interactions () const
 
virtual void handle_set_has_required_score_states (bool)
 
- Protected Member Functions inherited from IMP::base::Object
 Object (std::string name)
 Construct an object with the given name. More...
 

Detailed Description

Basin hopping is where, after a move, a local optimizer is used to relax the model before the energy computation. However, the pre-relaxation state of the model is used as the starting point for the next step. The idea is that models are accepted or rejected based on the score of the nearest local minima, but they can still climb the barriers in between as the model is not reset to the minima after each step.

Definition at line 245 of file MonteCarlo.h.


The documentation for this class was generated from the following file: