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GlareAlgorithmGoodHit Class Reference

#include <GlareAlgorithmGoodHit.h>

Inheritance diagram for GlareAlgorithmGoodHit:

GlareAlgorithm List of all members.

Public Methods

 GlareAlgorithmGoodHit (float p_first_fraction_to_keep=0.75)
virtual bool isOptimized (void)
virtual void evaluateGoodness (void)
virtual void pruneDimensions (void)
virtual void resetIterationCounter (void)
virtual std::ostream & getTrace (std::ostream &p_ostream)
float getFractionGoodHit (void)
void setFractionGoodHitThreshold (float p_fraction)
float getFractionGoodHitThreshold (void) const
void setMaximumIterationThreshold (int p_limit)
int getMaximumIterationThreshold (void) const
unsigned long int getNumberInitialGoodHit (void) const
unsigned long int getNumberEvaluated (void) const
unsigned long int getNumberInitialEvaluated (void) const
unsigned long int getNumberGoodHit (void) const
void setDoScaleWithSize (bool p_do_scale)
void setScaleWithSizeParam (float p_scale_param)
void setPruneZeroOccurence (bool p_prune_zero_occurence)
void setGoodnessRule (GoodnessRule p_goodness_rule)

Detailed Description

Major class for combinatorial optimization.

Constructor & Destructor Documentation

GlareAlgorithmGoodHit::GlareAlgorithmGoodHit float    p_first_fraction_to_keep = 0.75


p_first_fraction_to_keep  Is the fraction of Fragment to keep after the first iteration. The rest is rejected.

Member Function Documentation

virtual void GlareAlgorithmGoodHit::evaluateGoodness void    [virtual]

Score every Fragment of the LibrarySets given to this class. By product properties such as the goodness are calculated. Each time this method is called, it is considered as an additional iteration.

Implements GlareAlgorithm.

float GlareAlgorithmGoodHit::getFractionGoodHit void   

Returns the goodness of the LibrarySets used in the optimization.

float GlareAlgorithmGoodHit::getFractionGoodHitThreshold void    const

Return the goodnes targeted during the optimization.

int GlareAlgorithmGoodHit::getMaximumIterationThreshold void    const

Return the maximum number of iterations to perform. This is a stop criteria.

unsigned long int GlareAlgorithmGoodHit::getNumberEvaluated void    const

Return the number of products evaluated in method evaluateGoodness().

unsigned long int GlareAlgorithmGoodHit::getNumberGoodHit void    const

Return the number of 'good' products found in the last call to evaluateGoodness() method.

unsigned long int GlareAlgorithmGoodHit::getNumberInitialEvaluated void    const

Return the number of products evaluated at the first iteration (before any pruning occured).

unsigned long int GlareAlgorithmGoodHit::getNumberInitialGoodHit void    const

Return the number of 'good' products found in the first evaluation.

virtual std::ostream& GlareAlgorithmGoodHit::getTrace std::ostream &    p_ostream [virtual]

Prints to the passed stream the trace that defined the current status of the optimization.

Implements GlareAlgorithm.

virtual bool GlareAlgorithmGoodHit::isOptimized void    [virtual]

Return 'true' when one of the stop criteria is met.

Implements GlareAlgorithm.

virtual void GlareAlgorithmGoodHit::pruneDimensions void    [virtual]

Reject Fragments that are identified as non-viable. The normal sequence is to call: evaluateGoodness(), pruneDimensions(), isOptimized() and looping until isOptimized() returns 'true'.

Implements GlareAlgorithm.

virtual void GlareAlgorithmGoodHit::resetIterationCounter void    [virtual]

Set to zero the internal iteration counter.

void GlareAlgorithmGoodHit::setDoScaleWithSize bool    p_do_scale

Tell the algorithm if the scaled pruning needs to be used.

void GlareAlgorithmGoodHit::setFractionGoodHitThreshold float    p_fraction

Sets the goodness targeted during the optimization. This constitutes a stop criteria.

void GlareAlgorithmGoodHit::setGoodnessRule GoodnessRule    p_goodness_rule

Associate a GoodnessRule object that will be used to assess the goodness of each product.

void GlareAlgorithmGoodHit::setMaximumIterationThreshold int    p_limit

Set the maximum number of iterations to perform. Any additional step is not performs as this constitutes a stop criteria.

void GlareAlgorithmGoodHit::setPruneZeroOccurence bool    p_prune_zero_occurence

Tell the algorithm if only the Fragment with a zero occurence counter are rejected at first iteration.

void GlareAlgorithmGoodHit::setScaleWithSizeParam float    p_scale_param

Set the exponential pre-factor for the scaled pruning. However the method setDoScaleWithSize() must be called if the scale pruning is to be used.

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