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#ifndef INCLUDED_NJN_LOCALMAXSTATMATRIX
#define INCLUDED_NJN_LOCALMAXSTATMATRIX
/* $Id: $
* ===========================================================================
*
* PUBLIC DOMAIN NOTICE
* National Center for Biotechnology Information
*
* This software/database is a "United States Government Work" under the
* terms of the United States Copyright Act. It was written as part of
* the author's offical duties as a United States Government employee and
* thus cannot be copyrighted. This software/database is freely available
* to the public for use. The National Library of Medicine and the U.S.
* Government have not placed any restriction on its use or reproduction.
*
* Although all reasonable efforts have been taken to ensure the accuracy
* and reliability of the software and data, the NLM and the U.S.
* Government do not and cannot warrant the performance or results that
* may be obtained by using this software or data. The NLM and the U.S.
* Government disclaim all warranties, express or implied, including
* warranties of performance, merchantability or fitness for any particular
* purpose.
*
* Please cite the author in any work or product based on this material.
*
* ===========================================================================*/
/*****************************************************************************
File name: njn_localmaxstatmatrix.hpp
Author: John Spouge
Contents: Random walk parameters
******************************************************************************/
#include "njn_localmaxstat.hpp"
namespace Njn {
class LocalMaxStatMatrix : public LocalMaxStat {
// calculates the statistical parameters for the local maximum in a random walk
//
// The scores are uniqued and
// with the correspondence to probabilities maintained, placed in ascending order.
//
// The default p2_ = 0 is equivalent to the symmetric probabilities p2_ = p_ (on the same alphabet).
//
// The default dimMatrix2_ = 0 is equivalent to the same alphabet dimMatrix2_ = dimMatrix_.
public:
inline LocalMaxStatMatrix (
size_t dimMatrix_ = 0, // #(distinct values)
const long int *const *scoreMatrix_ = 0, // score matrix [0...dimMatrix_)[0...dimMatrix2_)
const double *p_ = 0, // probability of "letters" p_ [0...dimMatrix_)
const double *p2_ = 0, // probability of "letters" p2_ [0...dimMatrix2_), the second (j) set of letter-probabilities
size_t dimMatrix2_ = 0, // #(distinct values) in the second alphabet
double time_=0)
: LocalMaxStat (), d_dimMatrix (0), d_scoreMatrix_p (0), d_p_p (0), d_p2_p (0), d_dimMatrix2 (0)
{
setTime(time_);
copy (dimMatrix_, scoreMatrix_, p_, p2_, dimMatrix2_);
}
inline ~LocalMaxStatMatrix () {free2 ();}
inline LocalMaxStatMatrix &operator= (const LocalMaxStatMatrix &localMaxStat_) // random walk parameters
{
if (this != &localMaxStat_) copy (localMaxStat_);
return *this;
}
void copy (
size_t dimMatrix_, // #(distinct values) of scores & probabilities (which are paired)
const long int *const *scoreMatrix_, // score matrix [0...dimMatrix_)[0...dimMatrix_)
const double *p_, // probability of "letters" p_ [0...dimMatrix_)
const double *p2_ = 0, // probability of "letters" p2_ [0...dimMatrix2_), the second (j) set of letter-probabilities
size_t dimMatrix2_ = 0); // #(distinct letters) in the second alphabet
void copy (
LocalMaxStat localMaxStat_, // base object
size_t dimMatrix_, // #(distinct values) of scores & probabilities (which are paired)
const long int *const *scoreMatrix_, // score matrix [0...dimMatrix_)[0...dimMatrix_)
const double *p_, // probability of "letters" p_ [0...dimMatrix_)
const double *p2_ = 0, // probability of "letters" p2_ [0...dimMatrix2_), the second (j) set of letter-probabilities
size_t dimMatrix2_ = 0); // #(distinct letters) in the second alphabet
inline void copy (const LocalMaxStatMatrix &localMaxStatMatrix_)
{
copy (localMaxStatMatrix_, localMaxStatMatrix_.getDimMatrix (), localMaxStatMatrix_.getScoreMatrix (), localMaxStatMatrix_.getP (), localMaxStatMatrix_.getP2 (), localMaxStatMatrix_.getDimMatrix2 ());
}
using LocalMaxStat::operator bool; // ? is the object ready for computation ?
using LocalMaxStat::out; // output
using LocalMaxStat::getR; // r (theta_) : dominant eigenvalue for theta_
using LocalMaxStat::getA; // lim expected [length] / y for achieving y
using LocalMaxStat::getAlpha; // lim var [length] / y for achieving y
using LocalMaxStat::getDimension; // #(distinct values) of scores & probabilities (which are paired)
using LocalMaxStat::getScore; // scores in increasing order
using LocalMaxStat::getProb; // probabilities
using LocalMaxStat::getLambda; // lambda for associated random walk
using LocalMaxStat::getK; // k for random walk : exponential prefactor
using LocalMaxStat::getC; // c for random walk : exponential prefactor (global alignment)
using LocalMaxStat::getThetaMin; // theta for minimum expectation (exp (theta * score))
using LocalMaxStat::getRMin; // minimum expectation (exp (theta * score))
using LocalMaxStat::getDelta; // span
using LocalMaxStat::getThetaMinusDelta; // renewal span parameter
using LocalMaxStat::getMu; // step mean for random walk
using LocalMaxStat::getSigma; // step standard deviation for random walk
using LocalMaxStat::getMuAssoc; // step mean for associated random walk (relative entropy)
using LocalMaxStat::getSigmaAssoc; // step standard deviation for associated random walk
using LocalMaxStat::getMeanWDLE; // expected renewal length for weak ladder epochs
inline size_t getDimMatrix () const {return d_dimMatrix;} // #(distinct values) of scores & probabilities (which are paired)
inline const long int *const *getScoreMatrix () const {return d_scoreMatrix_p;} // score matrix [0...dimMatrix_)[0...dimMatrix_)
inline const double *getP () const {return d_p_p;} // probability of "letters" d_p_p [0...dimMatrix_)
inline const double *getP2 () const {return d_p2_p;} // probability of "letters" p2_ [0...dimMatrix_), the second (j) set of letter-probabilities
inline size_t getDimMatrix2 () const {return d_dimMatrix2;} // #(distinct letters) in the second alphabet
private:
size_t d_dimMatrix; // #(distinct values) of scores & probabilities (which are paired)
long int **d_scoreMatrix_p; // score matrix [0...dimMatrix_)[0...dimMatrix_)
double *d_p_p; // probability of "letters" d_p_p [0...dimMatrix_)
double *d_p2_p; // probability of "letters" p2_ [0...dimMatrix_), the second (j) set of letter-probabilities
size_t d_dimMatrix2; // #(distinct letters) in the second alphabet
void init (size_t dimMatrix_, size_t dimMatrix2_ = 0);
void free2 ();
};
}
#endif //!INCLUDED_NJS_LOCALMAXSTAT
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