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Prediction Class Reference

sequence location. More...

#include <Prediction.h>

Inheritance diagram for Prediction:

Inheritance graph
Collaboration diagram for Prediction:

Collaboration graph
List of all members.

Public Types

typedef std::list< Prediction * > DataStorageType

Public Member Functions

 Prediction (const SeqLoc &sl, AnnotationScore d, int modelId, const string &str)
 Prediction (const Prediction &pred)
 copy constructor

virtual ~Prediction ()
 no dynamic memory management, does contain one 'stl string' object.

virtual void del ()=0
AnnotationScore getScore () const
 return score associated with this object

void setScore (const AnnotationScore &s)
 set score valuie

int getModelId () const
 get integer idx of this coding sequence prediction

const string & getDataSource () const
 get string identifier of the source of this prediction

virtual DataStorageType * makePlaceHolders () const=0
 all prediction type objects must be able convert themselfs into a list of pointers that contain each coding sequence seperately

virtual void print (std::ostream &os, const string &str) const
 print to ostream, information about this prediction

Detailed Description

sequence location.

GeneModels are a collection of GenePrediction objects.
Sequence Match models are a collection of MatchPrediction objects, both of which
are just DataSetAbstractProduct, whose behavior are outlined by this object.
In other words, one knowledge source might be made up of a collection of predictions about related sequence locations or it might be just one sequence location Presumeably, there will be many types of predictions: CDS, start or stop codons, 5' UTRs, 3' UTRS, introns, exons for starters.
SeqLoc, AnnotationScore

Constructor & Destructor Documentation

Prediction::Prediction const SeqLoc sl,
AnnotationScore  d,
int  modelId,
const string &  str

SeqLoc - sequence location this prediction refers to
AnnotationScore - the evaluation score of this prediction
int - a counter of ith element in the prediction model (only usefull for models made up of multiple components this should be phased out)
string - string identifier, defining the "source" of this prediction this value is gnerally computed automatically by the InputData class, so that the scoring functions can uniquely seperate different prediction sources...(e.g. nap versus gap)

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