ObjCryst::MonteCarloObj Class Reference

Base object for Monte-Carlo Global Optimization methods. More...

Inheritance diagram for ObjCryst::MonteCarloObj:

Collaboration diagram for ObjCryst::MonteCarloObj:

List of all members.

Public Member Functions

MonteCarloObj (const string name="")

Constructor.

MonteCarloObj (const bool internalUseOnly)

Constructor.

virtual ~MonteCarloObj ()

Destructor.

void SetAlgorithmSimulAnnealing (const AnnealingSchedule scheduleTemp, const REAL tMax, const REAL tMin, const AnnealingSchedule scheduleMutation=ANNEALING_CONSTANT, const REAL mutMax=16., const REAL mutMin=.125, const long nbTrialRetry=0, const REAL minCostRetry=0.)

Set the refinement method to simulated Annealing.

void SetAlgorithmParallTempering (const AnnealingSchedule scheduleTemp, const REAL tMax, const REAL tMin, const AnnealingSchedule scheduleMutation=ANNEALING_CONSTANT, const REAL mutMax=16., const REAL mutMin=.125)

Set the refinement method to Parallel Tempering.

virtual void Optimize (long &nbSteps, const bool silent=false, const REAL finalcost=0, const REAL maxTime=-1)

Launch optimization (a single run) for N steps.

virtual void MultiRunOptimize (long &nbCycle, long &nbSteps, const bool silent=false, const REAL finalcost=0, const REAL maxTime=-1)

Launch optimization for multiple runs of N steps.

void RunSimulatedAnnealing (long &nbSteps, const bool silent=false, const REAL finalcost=0, const REAL maxTime=-1)

void RunParallelTempering (long &nbSteps, const bool silent=false, const REAL finalcost=0, const REAL maxTime=-1)

virtual void XMLOutput (ostream &os, int indent=0) const

Output a description of the object in XML format to a stream.

virtual void XMLInput (istream &is, const XMLCrystTag &tag)

Input in XML format from a stream, restoring the set of refined objects and the associated cost functions.

virtual const string GetClassName () const

Get the name for this class type.

Protected Member Functions

virtual void NewConfiguration (const RefParType *type=gpRefParTypeObjCryst)

Make a random change in the configuration.

virtual void InitOptions ()

Initialization of options.

Protected Attributes

RefObjOpt mGlobalOptimType

Method used for the global optimization.

REAL mCurrentCost

Current value of the cost function.

RefObjOpt mSaveTrackedData

Option to save the evolution of tracked data (cost functions, likelihhod, individual parameters,.

REAL mTemperature

Current temperature for annealing.

REAL mTemperatureMax

Beginning temperature for annealing.

REAL mTemperatureMin

Lower temperature.

RefObjOpt mAnnealingScheduleTemp

Schedule for the annealing.

REAL mTemperatureGamma

Gamma for the 'gamma' temperature schedule.

REAL mMutationAmplitude

Mutation amplitude.

REAL mMutationAmplitudeMax

Mutation amplitude at the beginning of the optimization.

REAL mMutationAmplitudeMin

Mutation amplitude at the end of the optimization.

RefObjOpt mAnnealingScheduleMutation

Schedule for the annealing.

REAL mMutationAmplitudeGamma

Gamma for the 'gamma' Mutation amplitude schedule.

long mNbTrialRetry

Number of trials before testing if we are below the given minimum cost.

REAL mMinCostRetry

Cost to reach unless an automatic randomization and retry is done.

Detailed Description

Base object for Monte-Carlo Global Optimization methods.

The algorithm is quite simple, whith two type of optimizations, either simulated Annealing or Parallel Tempering, the latter being recommanded for most real-world optimizations.

Definition at line 322 of file GlobalOptimObj.h.

Constructor & Destructor Documentation

ObjCryst::MonteCarloObj::MonteCarloObj ( const bool internalUseOnly )

Constructor.

Using internalUseOnly=true will avoid registering the the object to any registry, and thus (for example) no display will be created, nor will this object be automatically be saved.

Definition at line 404 of file GlobalOptimObj.cpp.

Member Function Documentation

void ObjCryst::MonteCarloObj::SetAlgorithmSimulAnnealing	(	const AnnealingSchedule	scheduleTemp,
		const REAL	tMax,
		const REAL	tMin,
		const AnnealingSchedule	scheduleMutation = `ANNEALING_CONSTANT`,
		const REAL	mutMax = `16.`,
		const REAL	mutMin = `.125`,
		const long	nbTrialRetry = `0`,
		const REAL	minCostRetry = `0.`
	)

Set the refinement method to simulated Annealing.

Note that Parellel Tempering is more efficient to get out of local minima, so you sould rather use that method.

The refinement begins at max and finishes at min temperature.

Parameters:

	scheduleTemp,:	temperature schedule. See AnnealingSchedule.
	tMax,tMin,:	Max and Min temperatures.
	scheduleMutation,:	the mutation schedule. For each new configuration, the variation of each refinable parameter is less than its RefinablePar::GlobalOptimStep(), multiplied by the current mutation amplitude. By default this mutation is equal to 1., but making bigger steps is a good idea at the beginning of the refinement (for higher temperatures). See AnnealingSchedule. See AnnealingSchedule.
	mutMax,mutMin,:	Max and Min mutation amplitudes.
	minCostRetry,nbTrialRetry,:	if after nbTrialRetry, the cost function is still above minCostRetry, then start again from a random configuration. No randomization is made if nbTrialRetry <= 0.
	maxNbTrialSinceBest,:	if more than maxNbTrialSinceBest trials have been made since the best configuration was recorded, then revert to that configuration. This should be large enough to have an ergodic search (the default is never to revert..)

Warning:: do not use the 'smart' option for the temperature schedule, it is not yet implemented. Later it will be used to set the temperatures as a function of the amplitude schedule, so that we accept between 30% and 70% moves.

Note:: this will be removed when we separate the different algorithms in different classes.

Definition at line 430 of file GlobalOptimObj.cpp.

void ObjCryst::MonteCarloObj::SetAlgorithmParallTempering	(	const AnnealingSchedule	scheduleTemp,
		const REAL	tMax,
		const REAL	tMin,
		const AnnealingSchedule	scheduleMutation = `ANNEALING_CONSTANT`,
		const REAL	mutMax = `16.`,
		const REAL	mutMin = `.125`
	)

Set the refinement method to Parallel Tempering.

The refinement begins at max and finishes at min temperature.

Parameters:

	scheduleTemp,:	temperature schedule
	tMax,tMin,:	Max and Min temperatures. See AnnealingSchedule.
	scheduleMutation,:	the mutation schedule. For each new configuration, the variation of each refinable parameter is less than its RefinablePar::GlobalOptimStep(), multiplied by the current mutation amplitude. By default this mutation is equal to 1., but making bigger steps can be a good idea at the beginning of the refinement. Thus you can choose a schedule for the amplitude, exactly like for the temperature.
	mutMax,mutMin,:	Max and Min mutation amplitudes.

Warning:: do not use the 'smart' option for the temperature schedule, it is not yet implemented. Later it will be used to set the temperatures as a function of the amplitude schedule, so that we keep accepted move between 30% and 70%.

Note:: this will be removed when we separate the different algorithms in different classes.

Definition at line 451 of file GlobalOptimObj.cpp.

void ObjCryst::MonteCarloObj::Optimize	(	long &	nbSteps,
		const bool	silent = `false`,
		const REAL	finalcost = `0`,
		const REAL	maxTime = `-1`
	)			`[virtual]`

Launch optimization (a single run) for N steps.

Parameters:

	nbSteps,:	the number of steps to go. This number is modified (decreases!) as the refinement goes on.
	silent	: if true, absolutely no message should be printed (except debugging)
	finalcost,:	the optimization will stop if overall cost fallse below this value
	maxTime,:	the optimization will stop after the given number of seconds has been spent optimizing (ignored if <0).

Implements ObjCryst::OptimizationObj.

Definition at line 469 of file GlobalOptimObj.cpp.

void ObjCryst::MonteCarloObj::MultiRunOptimize	(	long &	nbCycle,
		long &	nbSteps,
		const bool	silent = `false`,
		const REAL	finalcost = `0`,
		const REAL	maxTime = `-1`
	)			`[virtual]`

Launch optimization for multiple runs of N steps.

Parameters:

	nbCycle,:	the number of runs (cycles) to perform. The structure is randomized at the beginning of each cycle. If nbCycle==-1, this will run indefinitely. The nbCycle parameter is decreased after each run.
	nbSteps,:	the number of steps to go. This number is modified (decreases!) as the refinement goes on.
	silent	: if true, absolutely no message should be printed (except debugging)
	finalcost,:	the optimization will stop if overall cost fallse below this value
	maxTime,:	the optimization will stop after the given number of seconds has been spent optimizing (ignored if <0).

Implements ObjCryst::OptimizationObj.

Definition at line 534 of file GlobalOptimObj.cpp.

void ObjCryst::MonteCarloObj::RunSimulatedAnnealing	(	long &	nbSteps,
		const bool	silent = `false`,
		const REAL	finalcost = `0`,
		const REAL	maxTime = `-1`
	)

For internal use only.

Do a single simulated annealing run. This is called by Optimize(...) and MultiRunOptimize(), which must also prepare the optimization (PrepareRefParList(), etc..).

Definition at line 643 of file GlobalOptimObj.cpp.

void ObjCryst::MonteCarloObj::RunParallelTempering	(	long &	nbSteps,
		const bool	silent = `false`,
		const REAL	finalcost = `0`,
		const REAL	maxTime = `-1`
	)

For internal use only.

Do a single Parallel Tempering run. This is called by Optimize(...) and MultiRunOptimize(), which must also prepare the optimization (PrepareRefParList(), etc..).

Definition at line 841 of file GlobalOptimObj.cpp.

void ObjCryst::MonteCarloObj::XMLOutput	(	ostream &	os,
		int	indent = `0`
	)			const `[virtual]`

Output a description of the object in XML format to a stream.

This saves the list of refined object and the cost functions, as well as options for the refinement. The refined objects are not saved, so this must be done somewhere else (they must be reloaded before this object).

Implements ObjCryst::OptimizationObj.

Definition at line 1395 of file GlobalOptimObj.cpp.

void ObjCryst::MonteCarloObj::XMLInput	(	istream &	is,
		const XMLCrystTag &	tag
	)			`[virtual]`

Input in XML format from a stream, restoring the set of refined objects and the associated cost functions.

Note that the corresponding objects must have been loaded in memory before, else shit happens.

Implements ObjCryst::OptimizationObj.

Definition at line 1452 of file GlobalOptimObj.cpp.

void ObjCryst::MonteCarloObj::NewConfiguration ( const RefParType * type = gpRefParTypeObjCryst ) [protected, virtual]

Make a random change in the configuration.

For internal use only.

This just generates a new configuration with random changes (according to current parameters). The new configuration is not tested in this function vs temperature: this should be done in the OptimizationObj::Optimize() function, which also chooses whether to revert to the previous configuration.

Random moves are made by the objects and not by this function, because the new configuration can be specific (like, for example, permutations between some of the parameters (atoms)).

Parameters:

type,:

can be used to restrict the move to a given category of parameters.

Definition at line 1530 of file GlobalOptimObj.cpp.

Member Data Documentation

RefObjOpt ObjCryst::MonteCarloObj::mGlobalOptimType [protected]

Method used for the global optimization.

Should be removed when we switch to using several classes for different algorithms.

Definition at line 437 of file GlobalOptimObj.h.

RefObjOpt ObjCryst::MonteCarloObj::mSaveTrackedData [protected]

Option to save the evolution of tracked data (cost functions, likelihhod, individual parameters,.

..)

Definition at line 446 of file GlobalOptimObj.h.

REAL ObjCryst::MonteCarloObj::mMutationAmplitude [protected]

Mutation amplitude.

From .25 to 64. Random moves will have a maximum amplitude equal to this amplitude multiplied by the Global optimization step defined for each RefinablePar. Large amplitude should be used at the beginning of the refinement (high temeratures).

Definition at line 464 of file GlobalOptimObj.h.

long ObjCryst::MonteCarloObj::mNbTrialRetry [protected]

Number of trials before testing if we are below the given minimum cost.

If <=0, this will be ignored.

Definition at line 476 of file GlobalOptimObj.h.

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


Public Member Functions
	MonteCarloObj (const string name="")
	Constructor.
	MonteCarloObj (const bool internalUseOnly)
	Constructor.
virtual	~MonteCarloObj ()
	Destructor.
void	SetAlgorithmSimulAnnealing (const AnnealingSchedule scheduleTemp, const REAL tMax, const REAL tMin, const AnnealingSchedule scheduleMutation=ANNEALING_CONSTANT, const REAL mutMax=16., const REAL mutMin=.125, const long nbTrialRetry=0, const REAL minCostRetry=0.)
	Set the refinement method to simulated Annealing.
void	SetAlgorithmParallTempering (const AnnealingSchedule scheduleTemp, const REAL tMax, const REAL tMin, const AnnealingSchedule scheduleMutation=ANNEALING_CONSTANT, const REAL mutMax=16., const REAL mutMin=.125)
	Set the refinement method to Parallel Tempering.
virtual void	Optimize (long &nbSteps, const bool silent=false, const REAL finalcost=0, const REAL maxTime=-1)
	Launch optimization (a single run) for N steps.
virtual void	MultiRunOptimize (long &nbCycle, long &nbSteps, const bool silent=false, const REAL finalcost=0, const REAL maxTime=-1)
	Launch optimization for multiple runs of N steps.
void	RunSimulatedAnnealing (long &nbSteps, const bool silent=false, const REAL finalcost=0, const REAL maxTime=-1)
void	RunParallelTempering (long &nbSteps, const bool silent=false, const REAL finalcost=0, const REAL maxTime=-1)
virtual void	XMLOutput (ostream &os, int indent=0) const
	Output a description of the object in XML format to a stream.
virtual void	XMLInput (istream &is, const XMLCrystTag &tag)
	Input in XML format from a stream, restoring the set of refined objects and the associated cost functions.
virtual const string	GetClassName () const
	Get the name for this class type.
Protected Member Functions
virtual void	NewConfiguration (const RefParType *type=gpRefParTypeObjCryst)
	Make a random change in the configuration.
virtual void	InitOptions ()
	Initialization of options.
Protected Attributes
RefObjOpt	mGlobalOptimType
	Method used for the global optimization.
REAL	mCurrentCost
	Current value of the cost function.
RefObjOpt	mSaveTrackedData
	Option to save the evolution of tracked data (cost functions, likelihhod, individual parameters,.
REAL	mTemperature
	Current temperature for annealing.
REAL	mTemperatureMax
	Beginning temperature for annealing.
REAL	mTemperatureMin
	Lower temperature.
RefObjOpt	mAnnealingScheduleTemp
	Schedule for the annealing.
REAL	mTemperatureGamma
	Gamma for the 'gamma' temperature schedule.
REAL	mMutationAmplitude
	Mutation amplitude.
REAL	mMutationAmplitudeMax
	Mutation amplitude at the beginning of the optimization.
REAL	mMutationAmplitudeMin
	Mutation amplitude at the end of the optimization.
RefObjOpt	mAnnealingScheduleMutation
	Schedule for the annealing.
REAL	mMutationAmplitudeGamma
	Gamma for the 'gamma' Mutation amplitude schedule.
long	mNbTrialRetry
	Number of trials before testing if we are below the given minimum cost.
REAL	mMinCostRetry
	Cost to reach unless an automatic randomization and retry is done.