A Monte Carlo optimizer. More...
#include <IMP/core/MonteCarlo.h>
Inheritance diagram for IMP::core::MonteCarlo:Public Member Functions | |
| MonteCarlo (Model *m=nullptr) | |
| double | get_best_accepted_energy () const |
| double | get_last_accepted_energy () const |
| double | get_maximum_difference () const |
| void | set_maximum_difference (double d) |
| void | set_return_best (bool tf) |
| Public Member Functions inherited from IMP::kernel::Optimizer | |
| Optimizer (Model *m, std::string name="Optimizer %1%") | |
| double | get_last_score () const |
| Return the score found in the last evaluate. | |
| Model * | get_model () const |
| Get the model being optimized. | |
| ScoringFunction * | get_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... | |
| void | set_model (Model *m) |
| Set the model being optimized. More... | |
| virtual void | set_scoring_function (ScoringFunctionAdaptor sf) |
| void | set_stop_on_good_score (bool tf) |
| virtual void | show (std::ostream &out=std::cout) const |
| Print info about the optimizer state. More... | |
| 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 () |
| OptimizerState * | get_optimizer_state (unsigned int i) const |
| OptimizerStates | get_optimizer_states () const |
| void | reserve_optimizer_states (unsigned int sz) |
| Public Member Functions inherited from IMP::base::Object | |
| virtual void | clear_caches () |
| virtual IMP::base::VersionInfo | get_version_info () const =0 |
| Get information about the module and version of the object. | |
| 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 | |
| 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 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 | |
| virtual void | do_step () |
| a class that inherits from this should override this method | |
| ParticleIndexes | get_movable_particles () const |
| Protected Member Functions inherited from IMP::kernel::Optimizer | |
| void | update_states () const |
| Update optimizer states, should be called at each successful step. More... | |
| double | width (FloatKey k) const |
| FloatIndexes | get_optimized_attributes () const |
| void | set_value (FloatIndex fi, double v) const |
| Float | get_value (FloatIndex fi) const |
| Float | get_derivative (FloatIndex fi) const |
| void | set_scaled_value (FloatIndex fi, Float v) const |
| double | get_scaled_value (FloatIndex fi) const |
| double | get_scaled_derivative (FloatIndex fi) const |
| void | clear_range_cache () |
| Clear the cache of range information. Do this at the start of optimization. | |
| Protected Member Functions inherited from IMP::base::Object | |
| Object (std::string name) | |
| Construct an object with the given name. More... | |
kT | |
The kT value has to be on the same scale as the differences in energy between good and bad states (and so the default is likely to not be a good choice). | |
| void | set_kt (Float t) |
| Float | get_kt () const |
Statistics | |
| unsigned int | get_number_of_forward_steps () const |
| Return how many times the optimizer has succeeded in taking a step. | |
| unsigned int | get_number_of_upward_steps () const |
| Return how many times the optimizer has stepped to higher energy. | |
Movers | |
The following methods are used to manipulate the list of Movers. Each mover is called at each optimization step, giving it a chance to change the current configuration. | |
| 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 () |
| MonteCarloMover * | get_mover (unsigned int i) const |
| MonteCarloMovers | get_movers () const |
| void | reserve_movers (unsigned int sz) |
Incremental | |
Efficient evaluation of non-bonded list based restraints is a bit tricky with incremental evaluation. | |
| void | set_incremental_scoring_function (IncrementalScoringFunction *isf) |
| bool | get_use_incremental_scoring_function () const |
| IncrementalScoringFunction * | get_incremental_scoring_function () const |
Additional Inherited Members | |
| Related Functions inherited from IMP::kernel::Optimizer | |
| typedef IMP::base::Vector < IMP::base::WeakPointer < Optimizer > > | OptimizersTemp |
Detailed Description
The optimizer uses a set of Mover objects to propose steps. Currently each Mover is called at each Monte Carlo iteration. If you only want to use one mover at a time, use a SerialMover. The movers propose some modification, which is then accepted or rejected based on the Metropolis criterion. Optionally, a number of local optimization steps are taken before the MonteCarlo step is accepted or rejected.
By default, the lowest score state encountered is returned.
- See Also
- Mover
Definition at line 42 of file MonteCarlo.h.
Member Function Documentation
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protected |
Note that if return best is true, this will save the current state of the model. Also, if the move is accepted, the optimizer states will be updated.
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protectedvirtual |
By default it just calls Optimizer::get_scoring_function()->evaluate(false). However, if an incremental scoring function is used, the list of moved particles will be used to evaluate the score more efficiently. Also, if there is a maximum allowed difference in scores Optimizer::get_scoring_function()->evaluate_if_below() will be called instead, allowing more efficient evaluation. Classes which override this method should be similarly aware for efficiency.
The list of moved particles is passed.
Reimplemented in IMP::isd::HybridMonteCarlo.
Definition at line 173 of file MonteCarlo.h.
Here is the call graph for this function:| double IMP::core::MonteCarlo::get_best_accepted_energy | ( | ) | const |
If return best is on, you can get the best energy found so far.
Definition at line 81 of file MonteCarlo.h.
| double IMP::core::MonteCarlo::get_last_accepted_energy | ( | ) | const |
Return the energy of last accepted state.
Definition at line 75 of file MonteCarlo.h.
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protected |
Get all movable particles (those that can be moved by the current movers.
| void IMP::core::MonteCarlo::set_incremental_scoring_function | ( | IncrementalScoringFunction * | isf | ) |
Set whether to use incremental evaluate or evaluate all restraints each time. This cannot be changed during optimization.
| void IMP::core::MonteCarlo::set_maximum_difference | ( | double | d | ) |
Computations can be acceletating by throwing out the tails of the distribution of accepted moves. To do this, specific a maximum acceptable difference between the before and after scores.
Definition at line 104 of file MonteCarlo.h.
| void IMP::core::MonteCarlo::set_return_best | ( | bool | tf | ) |
By default, the optimizer returns the lowest score state found so far. If, instead, you wish to return the last accepted state, set return best to false.
Definition at line 55 of file MonteCarlo.h.
The documentation for this class was generated from the following file: