mscore_tandem.cpp

/*
 Copyright (C) 2003-2004 Ronald C Beavis, all rights reserved
 X! tandem 
 This software is a component of the X! proteomics software
 development project

Use of this software governed by the Artistic license, as reproduced here:

The Artistic License for all X! software, binaries and documentation

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*/

// File version: 2005-01-23

#include "stdafx.h"
#include "msequence.h"
#include "mspectrum.h"
#include "msequtilities.h"
#include "mscore_tandem.h"

// Factory instance, registers itself with the mscoremanager.
static mscorefactory_tandem factory;
	
mscorefactory_tandem::mscorefactory_tandem()
{
	mscoremanager::register_factory("tandem", this);
}

mplugin* mscorefactory_tandem::create_plugin()
{
	return new mscore_tandem();
}

mscore_tandem::mscore_tandem(void)
{
	m_dScale = 4.0;
	m_pFactorial = new double[64];
	double dFac = 1.0;
	m_pFactorial[0] = 1.0;
	long a = 1;
	while(a < 64)	{
		dFac *= (double)a;
		m_pFactorial[a] = dFac;
		a++;
	}
}

mscore_tandem::~mscore_tandem(void)
{
	if(m_pFactorial != NULL)
		delete m_pFactorial;
}

/*
 * add_mi does the work necessary to set up an mspectrum object for modeling. 
 *   - an entry in the m_State object is made for the parent ion M+H
 * once an mspectrum has been added, the original mspectrum is no longer
 * needed for modeling, as all of the work associated with a spectrum
 * is only done once, prior to modeling sequences.
 */
bool mscore_tandem::add_mi(mspectrum &_s)
{
	if (!mscore::add_mi(_s))
		return false;

	if (m_vmiType.size() == 0)
		m_vmiType.reserve((long)m_vSpec.size());
/*
 * use blur to improve accuracy at the edges of the fragment ion m/z error range
 */
	blur(_s.m_vMI);

	return true;
}

/*
 * blur takes an SMap object and adds values to it adjacent to the 
 * values in the existing map. this process makes the conversion from
 * floating point m/z values to integer SMap index values more accurate.
 * the half-width of the distribution around each initial value is set
 * by the m_fWidth value. For example, 
 *
 * if there is an intensity value I at index value N, 
 * then with a width of 2, the following new values are created,
 * I(N-2),I(N-1),I(N+1),I(N+2)
 *
 * the value for the width has an impact on the performance of the
 * protein modeling session: the wider the width, the more memory that is required to hold
 * the SMaps for the spectra. as that memory expands, the ability of
 * the various processor caches to hold the SMaps will change. keeping
 * the SMaps in the fastest cache speeds up the calculation considerably.
 */
inline bool mscore_tandem::blur(vector<mi> &_s)
{
	vmiType vType;
	MIType uType;
	uType.m_fI = 0.0;
	uType.m_lM = 0;
	long lValue = 0;
	long a = 0;
	long w = (long)(0.1+m_fWidth);
/*
 * fConvert and fFactor are only used if the m_lErrorType uses ppm for fragment ion mass errors
 * if ppm is used, the width at m/z = 200.0 is taken as the base width for blurring & the
 * width is scaled by the measured m/z. 
 * NOTE: the m_fErr value used in the ppm case is: (the error in ppm) x 200
 */
	float fConvert = m_fErr/m_fWidth;
	const float fFactor = (float)200.0/fConvert;
	const size_t tSize = _s.size();
	size_t tCount = 0;
	vType.reserve(tSize*3);
/*
 * add additional values based on the m_fWidth setting
 */
	while(tCount < tSize)	{
		if(_s[tCount].m_fI > 0.5)	{
			lValue = (long)(_s[tCount].m_fM/fConvert);
			a = -1*w;
			if(m_lErrorType & T_FRAGMENT_PPM)	{
				a = (long)((float)a * (float)lValue/fFactor - 0.5);
				if(a > -1*w)
					a = -1*w;
			}
			while(a <= w)	{
				if(uType.m_lM == lValue + a)	{
					if(uType.m_fI < _s[tCount].m_fI)	{
						vType.back().m_fI = _s[tCount].m_fI;
					}
				}
				else	{
						uType.m_lM = lValue + a;
						uType.m_fI = _s[tCount].m_fI;
						vType.push_back(uType);
				}
				a++;
			}
		}
		tCount++;
	}
	m_vmiType.push_back(vType);
	return true;
}

/*
 * hfactor returns a factor applied to the score to produce the
 * hyper score, given a number of ions matched.
 */
double mscore_tandem::hfactor(long _l) {
	return m_pFactorial[_l];
}
/*
 * hconvert is use to convert a hyper score to the value used in a score
 * histogram, since the actual scoring distribution may not lend itself
 * to statistical analysis through use of a histogram.
 */
float mscore_tandem::hconvert(float _f) {
	if(_f <= 0.0)
		return 0.0;
	return (float)(m_dScale*log10(_f));
}

bool mscore_tandem::clear()
{
	m_vmiType.clear();
	return true;
}

/*
 * dot is the fundamental logic for scoring a peptide with a mass spectrum.
 * the mass spectrum is determined by the value of m_lId, which is its index
 * number in the m_vsmapMI vector. the sequence is represented by the values
 * that are currently held in m_plSeq (integer masses) and m_pfSeq (scoring
 * weight factors). 
 * convolution scores are the sum of the products of the spectrum intensities
 * and the scoring weight factors for a spectrum.
 * hyper scores are the product of the products of the spectrum intensities
 * and the scoring weight factors for a spectrum.
 * the number of predicted ions that correspond to non-zero intensities in
 * the spectrum are tallied and returned.
 */

double mscore_tandem::dot(unsigned long *_v)
{
	float fScore = 0.0;
	float fValue0 = 0.0;
	unsigned long a = 0;
	unsigned long lCount = 0;
	long lType = 0;
	size_t b = 0;
	vector<MIType>::iterator itType = m_vmiType[m_lId].begin();
	vector<MIType>::const_iterator itEnd = m_vmiType[m_lId].end();
	// tType and tTypeSize were added in 2006.09.01 to correct a problem
	// created by VC++ 2005. This new version uses a strict bounds checking
	// style for STL iterators, that cause a run time error if an iterator
	// longer than .end() is produced by incrementing the iterator.
	size_t tType = 0;
	size_t tTypeSize = m_vmiType[m_lId].size();
	const size_t tStep = 5;
	while(m_plSeq[a] != 0 && itType != itEnd)	{
		lType = 0;
		if(itType->m_lM < m_plSeq[a])	{
			lType = 1;
			// Generally lots more spectrum peaks than sequence peaks.  Trying
			// large steps first helps reduce performance hit for this operation.
			// This is were the iterator bounds checking failed in VC++ 2005.
			// By checking the size first, the iterator is not evaluated and
			// does not produce the failure.
			while (tType+tStep < tTypeSize && (itType+tStep)->m_lM < m_plSeq[a]) {
				itType += tStep;
				tType += tStep;
			}
			do {
				itType++;
				tType++;
			} while(itType != itEnd && itType->m_lM < m_plSeq[a]);
		}
		else if(itType->m_lM > m_plSeq[a])	{
			do {
				a++;
			} while(itType->m_lM > m_plSeq[a] && m_plSeq[a] != 0);
		}
		if(m_plSeq[a] == 0 || itType == itEnd)	{
			break;
		}
		if(itType->m_lM == m_plSeq[a])	{
			fValue0 = itType->m_fI * m_pfSeq[a];
			if(fValue0 > 0.0)	{
				lCount++;
				fScore += fValue0;
			}
		}
		if(lType)	{
			a++;
		}
		else	{
			itType++;
			tType++;
		}
	}
	*_v = lCount;	
	return (fScore);
}