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/*
* contentmodel.hh
*
* License: Artistic License, see file LICENSE.TXT or
* https://opensource.org/licenses/artistic-license-1.0
*/
#ifndef __CONTENTMODEL_HH
#define __CONTENTMODEL_HH
// project includes
#include "types.hh"
#include "motif.hh"
// standard C/C++ includes
#include <string>
#include <iostream>
#include <iomanip>
using namespace std;
/**
* @brief Model typical sequences by pattern frequencies
*
* @author Mario Stanke
* @version 0.2
*/
class ContentModel {
public:
/*
* default contructor
*/
ContentModel(){}
/*
* contructor
*/
ContentModel(int k, int f = 1){
init(k,f);
};
void init(int k, int f){
this->k = k;
patprob.assign(f, POWER4TOTHE(k+1));
}
void setRandomPatProbs();
string generateRandSeq(int n, int startFrame = 0) const;
static int randomIndex(const Double* p, int count);
Double seqProbUnderModel(const char *seq, int len, int frame) const;
BaseCount getMeanContent();
Double getPatProb(int f, int pn) const{ return patprob[f][pn]; }
// const Double* getPatProb(int f) const {return (*patprob)[f];}
vector<Double> copyPatProb(int f) const {return patprob.getRow(f);}
void setPatProb(const Matrix<Double>& newpatprob);
void setPatProb(int frame, const vector<Double>& newRow);
// void setPatProbClone(const Matrix<Double>& newpatprob);
int getNumFrames() const { return patprob.getColSize(); }
int getNumPatterns() const { return patprob.getRowSize(); }
void print();
static double DiscrimDifference(const ContentModel *a, const ContentModel *b,
int n, int fa=0, int fb=0);
private:
int k;
Matrix<Double> patprob;
};
#endif //__CONTENTMODEL_HH
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