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CNoiseReduction.cpp
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CNoiseReduction.cpp
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/*
Copyright 2007-2016, Michael R. Hoopmann, Institute for Systems Biology
Michael J. MacCoss, University of Washington
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
#include "CNoiseReduction.h"
using namespace std;
using namespace MSToolkit;
CNoiseReduction::CNoiseReduction(){
pos=0;
posA=0;
lastFile="";
}
CNoiseReduction::CNoiseReduction(MSReader* msr, CHardklorSetting& hs){
r=msr;
cs=hs;
pos=0;
posA=0;
lastFile="";
}
CNoiseReduction::~CNoiseReduction(){
r=NULL;
}
//Calculates the resolution (FWHM) of a peak
double CNoiseReduction::calcFWHM(double mz){
double deltaM;
switch(cs.msType){
case OrbiTrap:
deltaM = mz * sqrt(mz) / (20*cs.res400); //(20*userParams.res400); //sqare root of 400
break;
case TOF:
deltaM = mz / cs.res400;
break;
case QIT:
deltaM = cs.res400 / 5000.0;
break;
case FTICR:
default:
deltaM = mz * mz / (400*cs.res400);
break;
}
return deltaM;
}
bool CNoiseReduction::DeNoise(Spectrum& sp){
double ppm;
int i,j,k;
int index;
int matchCount;
char cFilter1[256];
char cFilter2[256];
Spectrum tmpSpec;
vector<int> v;
sp.clear();
if(pos==0){
if((cs.scan.iLower>0)) {
k=cs.scan.iLower;
r->readFile(&cs.inFile[0],tmpSpec,cs.scan.iLower);
} else {
r->readFile(&cs.inFile[0],tmpSpec);
k=tmpSpec.getScanNumber();
}
if(tmpSpec.getScanNumber()==0) return false;
tmpSpec.getRawFilter(cFilter1,256);
//Gather left side of scan
i=1;
j=0;
while( k-i > 0){
r->readFile(&cs.inFile[0],tmpSpec,cs.scan.iLower-i);
if(tmpSpec.getScanNumber()==0) {
i++;
continue;
}
tmpSpec.getRawFilter(cFilter2,256);
//Assume High resolution data at all times
if(!cs.centroid) {
FirstDerivativePeaks(tmpSpec,1);
tmpSpec.setRawFilter(cFilter2);
}
s.push_front(tmpSpec);
if(strcmp(cFilter1,cFilter2)==0){
j++;
if(j==(int)(cs.boxcar/2)) break;
}
i++;
}
//cout << "Done left " << s.size() << " " << cs.rawAvgWidth << endl;
//Get our position again
r->readFile(&cs.inFile[0],tmpSpec,k);
//Assume High resolution data at all times
if(!cs.centroid) {
FirstDerivativePeaks(tmpSpec,1);
tmpSpec.setRawFilter(cFilter1);
}
//Add first target scan
s.push_back(tmpSpec);
pos=(int)s.size()-1;
//Add right side of scan
i=1;
j=0;
while(true){
r->readFile(NULL,tmpSpec);
if(tmpSpec.getScanNumber()==0) break;
tmpSpec.getRawFilter(cFilter2,256);
//Assume High resolution data at all times
if(!cs.centroid) {
FirstDerivativePeaks(tmpSpec,1);
tmpSpec.setRawFilter(cFilter2);
}
s.push_back(tmpSpec);
//cout << tmpSpec.getScanNumber() << " " << cFilter1 << " xx " << cFilter2 << endl;
if(strcmp(cFilter1,cFilter2)==0){
j++;
if(j==(int)(cs.boxcar/2)) break;
}
i++;
}
}
//return false if we reached the end
if(pos>=(int)s.size()) return false;
//Because Deque may have mixed spectra, create list of Deque indexes to compare
//Shrink Deque on the left if some spectra are not needed
//Expand Deque to the right if needed and possible
//cout << "Checking scan " << s[pos].getScanNumber() << endl;
v.clear();
s[pos].getRawFilter(cFilter1,256);
//look left
for(i=pos-1;i>=0;i--){
s[i].getRawFilter(cFilter2,256);
if(strcmp(cFilter1,cFilter2)==0) {
v.push_back(i);
if(v.size()==(int)(cs.boxcar/2)) break;
}
}
//erase unneeded left items
while(i>0){
s.pop_front();
i--;
for(j=0;j<(int)v.size();j++) v[j]--;
pos--;
}
//look right
j=0;
for(i=pos+1;i<(int)s.size();i++){
s[i].getRawFilter(cFilter2,256);
if(strcmp(cFilter1,cFilter2)==0) {
v.push_back(i);
j++;
if(j==(int)(cs.boxcar/2)) break;
}
}
//extend right side if needed
while(j<(int)(cs.boxcar/2)){
r->readFile(NULL,tmpSpec);
if(tmpSpec.getScanNumber()==0) break;
tmpSpec.getRawFilter(cFilter2,256);
//Assume High resolution data at all times
if(!cs.centroid) {
FirstDerivativePeaks(tmpSpec,1);
tmpSpec.setRawFilter(cFilter2);
}
s.push_back(tmpSpec);
if(strcmp(cFilter1,cFilter2)==0) {
v.push_back((int)s.size()-1);
j++;
}
}
//if there is nothing to compare to, exit now
if(v.size()==0) return false;
//compare peaks
//cout << "Checking " << s[pos].size() << " peaks." << endl;
for(i=0;i<s[pos].size();i++){
matchCount=1;
for(j=0;j<(int)v.size();j++){
if(s[v[j]].size()<1) continue;
index = NearestPeak(s[v[j]],s[pos].at(i).mz);
ppm=fabs( (s[v[j]].at(index).mz-s[pos].at(i).mz)/s[pos].at(i).mz * 1000000);
if(ppm<cs.ppm) matchCount++;
}
if(matchCount>=cs.boxcarFilter || matchCount==v.size()) sp.add(s[pos].at(i));
}
sp.setScanNumber(s[pos].getScanNumber());
sp.setScanNumber(s[pos].getScanNumber(true),true);
sp.setRTime(s[pos].getRTime());
pos++;
//cout << sp.getScanNumber() << endl;
//cout << "Done! " << sp.size() << " " << pos << endl;
return true;
}
//Overloaded function allows user to just pass an array of spectra to be compared.
//No file reading/parsing is performed.
/*
bool CNoiseReduction::DeNoise(Spectrum& sp, vector<Spectrum>& vs, int pivot, bool findPeaks){
double ppm;
int i,j;
int index;
int matchCount;
Spectrum tmpSpec;
vector<int> v;
sp.clear();
//Find peaks (centroid) for all scans (assume high res data)
if(findPeaks) {
for(i=0;i<vs.size();i++) FirstDerivativePeaks(vs[i],1);
}
//compare peaks
for(i=0;i<vs[pivot].size();i++){
matchCount=1;
for(j=0;j<vs.size();j++){
if(j==pivot) continue;
if(vs[j].size()<1) continue;
index = NearestPeak(vs[j],vs[pivot].at(i).mz);
ppm=fabs( (vs[j].at(index).mz-vs[pivot].at(i).mz)/vs[pivot].at(i).mz * 1000000);
if(ppm<cs.ppm) matchCount++;
}
if(matchCount>=cs.ppMatch || matchCount==v.size()) sp.add(vs[pivot].at(i));
}
sp.setScanNumber(vs[pivot].getScanNumber());
sp.setScanNumber(vs[pivot].getScanNumber(true),true);
sp.setRTime(vs[pivot].getRTime());
//cout << "Done! " << sp.size() << " " << pivot << endl;
return true;
}
//Overloaded function allows user to just pass an array of spectra to be compared.
//No file reading/parsing is performed.
bool CNoiseReduction::DeNoise(Spectrum& sp, deque<Spectrum>& vs, int pivot, bool findPeaks){
double ppm;
int i,j;
int index;
int matchCount;
Spectrum tmpSpec;
vector<int> v;
sp.clear();
//Find peaks (centroid) for all scans (assume high res data)
if(findPeaks) {
for(i=0;i<vs.size();i++) FirstDerivativePeaks(vs[i],1);
}
//compare peaks
for(i=0;i<vs[pivot].size();i++){
matchCount=1;
for(j=0;j<vs.size();j++){
if(j==pivot) continue;
if(vs[j].size()<1) continue;
index = NearestPeak(vs[j],vs[pivot].at(i).mz);
ppm=fabs( (vs[j].at(index).mz-vs[pivot].at(i).mz)/vs[pivot].at(i).mz * 1000000);
if(ppm<cs.ppm) matchCount++;
}
if(matchCount>=cs.ppMatch || matchCount==v.size()) sp.add(vs[pivot].at(i));
}
sp.setScanNumber(vs[pivot].getScanNumber());
sp.setScanNumber(vs[pivot].getScanNumber(true),true);
sp.setRTime(vs[pivot].getRTime());
//cout << "Done! " << sp.size() << " " << pos << endl;
return true;
}
*/
//First derivative method taken from CSpecAnalyze, returns base peak intensity of the set
void CNoiseReduction::FirstDerivativePeaks(Spectrum& sp, int winSize){
int i,j;
float maxIntensity;
int bestPeak;
bool bLastPos;
Spectrum gp;
int nextBest;
double FWHM;
Peak_T centroid;
bLastPos=false;
for(i=0;i<sp.size()-winSize;i++){
if(sp.at(i).intensity<sp.at(i+winSize).intensity) {
bLastPos=true;
continue;
} else {
if(bLastPos){
bLastPos=false;
//find max and add peak
maxIntensity=0;
for(j=i;j<i+winSize;j++){
if (sp.at(j).intensity>maxIntensity){
maxIntensity=sp.at(j).intensity;
bestPeak = j;
}
}
//Best estimate of Gaussian centroid
//Get 2nd highest point of peak
if(bestPeak==sp.size()-1){
nextBest=bestPeak-1;
} else if(sp.at(bestPeak-1).intensity > sp.at(bestPeak+1).intensity){
nextBest=bestPeak-1;
} else {
nextBest=bestPeak+1;
}
//Get FWHM
FWHM = calcFWHM(sp.at(bestPeak).mz);
//Calc centroid MZ (in three lines for easy reading)
centroid.mz = pow(FWHM,2)*log(sp.at(bestPeak).intensity/sp.at(nextBest).intensity);
centroid.mz /= GC*(sp.at(bestPeak).mz-sp.at(nextBest).mz);
centroid.mz += (sp.at(bestPeak).mz+sp.at(nextBest).mz)/2;
//Calc centroid intensity
centroid.intensity=(float)(sp.at(bestPeak).intensity/exp(-pow((sp.at(bestPeak).mz-centroid.mz)/FWHM,2)*GC));
//some peaks are funny shaped and have bad gaussian fit.
//if error is more than 10%, keep existing intensity
if( fabs((sp.at(bestPeak).intensity - centroid.intensity) / centroid.intensity * 100) > 10 ||
//not a good check for infinity
centroid.intensity>999999999999.9 ||
centroid.intensity < 0 ) {
centroid.intensity=sp.at(bestPeak).intensity;
}
//Hack until I put in mass ranges
if(centroid.mz<0 || centroid.mz>2000) {
//do nothing if invalid mz
} else {
gp.add(centroid);
}
i+=winSize-1;
}
}
}
int scanNumber=sp.getScanNumber();
int scanNumber2=sp.getScanNumber(false);
float rTime=sp.getRTime();
sp = gp;
sp.setRTime(rTime);
sp.setScanNumber(scanNumber);
sp.setScanNumber(scanNumber2,true);
}
//Binary search to quickly find the nearest peak
int CNoiseReduction::NearestPeak(Spectrum& sp, double mz){
int pivot=0;
int width=0;
int lastWidth=0;
int best=0;
double dif=9999999.9;
double d;
pivot=sp.size()/2;
width=(int)(pivot/2.0+0.5);
while(width!=lastWidth && pivot<sp.size() && pivot>-1){
d=fabs(sp.at(pivot).mz-mz);
if(d<dif){
dif=d;
best=pivot;
}
if(sp.at(pivot).mz==mz){
return pivot;
} else if(sp.at(pivot).mz > mz){
pivot-=width;
lastWidth=width;
width=(int)(width/2.0+0.5);
} else {
pivot+=width;
lastWidth=width;
width=(int)(width/2.0+0.5);
}
}
if(pivot<sp.size() && pivot>-1){
d=fabs(sp.at(pivot).mz-mz);
if(d<dif) best=pivot;
}
return best;
}
bool CNoiseReduction::ScanAverage(Spectrum& sp, std::string file, int width, float cutoff){
Spectrum ts;
Spectrum ps=sp;
MSReader r;
int i;
int j;
int k;
int widthCount=0;
int numScans=1;
double dif;
double prec;
double dt;
double c=CParam(ps,3);
bool bLeft=true;
int posLeft=ps.getScanNumber()-1;
int posRight=ps.getScanNumber()+1;
char cFilter1[256];
char cFilter2[256];
ps.getRawFilter(cFilter1,256);
while(widthCount<(width*2)){
//Alternate looking left and right
if(bLeft){
bLeft=false;
widthCount++;
while(posLeft>0){
r.readFile(file.c_str(),ts,posLeft);
if(ts.getScanNumber()==0) break;
ts.getRawFilter(cFilter2,256);
if(strcmp(cFilter1,cFilter2)==0) break;
posLeft--;
}
} else {
bLeft=true;
widthCount++;
while(true){
r.readFile(file.c_str(),ts,posRight);
if(ts.getScanNumber()==0) break;
ts.getRawFilter(cFilter2,256);
if(strcmp(cFilter1,cFilter2)==0) break;
posRight++;
}
}
if(ts.getScanNumber()==0) continue;
numScans++;
//Match peaks between pivot scan and temp scan
k=0;
for(i=0;i<ps.size();i++){
dif=100000.0;
prec = c * ps.at(i).mz * ps.at(i).mz / 2;
for(j=k;j<ts.size();j++){
dt=fabs(ps.at(i).mz-ts.at(j).mz);
if(dt<=dif) {
if(dt<prec) {
ps.at(i).intensity+=ts.at(j).intensity;
ts.at(j).mz=-1.0;
k=j+1;
break;
}
dif=dt;
} else {
k=j-1;
break;
}
}
}
//Add unmatched peaks from temp scan
for(i=0;i<ts.size();i++){
if(ts.at(i).mz>-1.0) ps.add(ts.at(i));
}
//Sort pivot scan peaks for fast traversal against next temp scan
ps.sortMZ();
}
//Average points and apply cutoff
sp.clear();
for(i=0;i<ps.size();i++) {
ps.at(i).intensity/=numScans;
if(ps.at(i).intensity>=cutoff) sp.add(ps.at(i));
}
sp.setScanNumber(ps.getScanNumber());
sp.setScanNumber(ps.getScanNumber(true),true);
sp.setRTime(ps.getRTime());
return true;
}
bool CNoiseReduction::NewScanAverage(Spectrum& sp, std::string file, int width, float cutoff, int scanNum){
Spectrum ts;
vector<int> vPos;
int i;
int j;
int k;
int m;
int widthCount=0;
int numScans=1;
double dif;
double prec=0;
double dt;
double c=0;
double ppm;
bool bLeft=true;
int posLeft;
int posRight;
int index;
char cFilter1[256];
//char cFilter2[256];
//double slope;
//double intercept;
sp.clear();
Spectrum* specs;
specs = new Spectrum[width*2+1];
//if file is not null, create new buffer
if(file.length()){
lastFile = file;
bs.clear();
if (scanNum > 0) {
int scn = scanNum;
r->readFile(file.c_str(), ts, scn);
while (ts.getScanNumber() == 0) {
scn++;
if (cs.scan.iUpper > 0) {
if (scn > cs.scan.iUpper) break;
} else {
if (scn > r->getLastScan()) break;
}
r->readFile(NULL, ts, scn);
}
} else r->readFile(file.c_str(), ts);
if(ts.getScanNumber()==0) {
delete [] specs;
return false;
}
bs.push_back(ts);
specs[0]=bs[0];
if (!cs.centroid) c = CParam(specs[0], 3);
posA=0;
} else {
posA++;
if(posA>=(int)bs.size()) { //end of buffer, no more data
delete [] specs;
return false;
}
specs[0]=bs[posA];
if (!cs.centroid) c = CParam(specs[0], 3);
}
specs[0].getRawFilter(cFilter1,256);
posLeft=posA;
posRight=posA;
while(widthCount<(width*2)){
index=-1;
//Alternate looking left and right
if(bLeft){
bLeft=false;
widthCount++;
while(true){
posLeft--;
if(posLeft<0) { //buffer is too short on left, add spectra
i=bs[0].getScanNumber();
while(true){
i--;
if(i==0) break;
r->readFile(NULL,ts,i);
if(ts.getScanNumber()==0) continue;
else break;
}
if(i==0) break;
bs.push_front(ts);
posA++;
posRight++;
posLeft=0;
//ts.getRawFilter(cFilter2,256);
if(ts.getMsLevel()==cs.msLevel) {
index=posLeft;
break;
}
} else {
//bs[posLeft].getRawFilter(cFilter2,256);
if(bs[posLeft].getMsLevel()==cs.msLevel) {
index=posLeft;
break;
}
}
}
} else {
bLeft=true;
widthCount++;
while(true){
posRight++;
if(posRight>=(int)bs.size()) { //buffer is too short on right, add spectra
r->readFile(lastFile.c_str(),ts,bs[bs.size()-1].getScanNumber());
r->readFile(NULL,ts);
if(ts.getScanNumber()==0) {
posRight--;
break;
}
bs.push_back(ts);
//ts.getRawFilter(cFilter2,256);
if(ts.getMsLevel()==cs.msLevel) {
index=posRight;
break;
}
} else {
//bs[posRight].getRawFilter(cFilter2,256);
if(bs[posRight].getMsLevel()==cs.msLevel) {
index=posRight;
break;
}
}
}
}
if(index==-1) continue;
specs[numScans++]=bs[index];
}
double tmz;
int mzcount=0;
/* Ledford equation correction
double freq;
double conA=0.0;
double conB=0.0;
for(m=0;m<numScans;m++){
conA+=specs[m].getConversionA();
conB+=specs[m].getConversionB();
}
conA/=numScans;
conB/=numScans;
printf("%.10lf, %.10lf\n",conA,conB);
for(k=0;k<numScans;k++){
for(j=0;j<specs[k].size();j++){
freq = sqrt(specs[k].getConversionA()*specs[k].getConversionA() - (4*specs[k].at(j).mz*(-specs[k].getConversionB())));
freq += specs[k].getConversionA();
freq /= (2*specs[k].at(j).mz);
specs[k].at(j).mz = conA/freq + conB/(freq*freq);
}
}
*/
//Match peaks between pivot scan (0) and neighbors (the rest)
for(m=0;m<numScans;m++){
vPos.clear();
for(i=0;i<numScans;i++) vPos.push_back(0);
for(i=0;i<specs[m].size();i++){ //iterate all points
if(specs[m].at(i).intensity<0.1) continue;
tmz=specs[m].at(i).mz;
mzcount=1;
if (!cs.centroid) prec = c * tmz * tmz / 2;
for(k=m+1;k<numScans;k++){ //iterate all neighbors
dif=100000.0;
for(j=vPos[k];j<specs[k].size();j++){ //check if point is a match
if(specs[k].at(j).intensity<0.1) continue; //skip meaningless datapoints to speed along
dt=fabs(tmz-specs[k].at(j).mz);
if(dt<=dif) {
if (cs.centroid){
ppm = dt / specs[k].at(j).mz*1e6;
if (ppm<cs.ppm){
specs[m].at(i).intensity += specs[k].at(j).intensity;
specs[m].at(i).mz += specs[k].at(j).mz;
vPos[k] = j + 1;
specs[k].at(j).intensity = -1.0;
mzcount++;
break;
}
} else if(dt<prec) {
//linear interpolate
//if(specs[k].at(j).mz<tmz && j<specs[k].size()-1){
// slope=(specs[k].at(j+1).intensity-specs[k].at(j).intensity)/(specs[k].at(j+1).mz-specs[k].at(j).mz);
// intercept=specs[k].at(j).intensity-specs[k].at(j).mz*slope;
// specs[m].at(i).intensity+=(tmz*slope+intercept);
//} else if(specs[k].at(j).mz>tmz && j>0) {
// slope=(specs[k].at(j).intensity-specs[k].at(j-1).intensity)/(specs[k].at(j).mz-specs[k].at(j-1).mz);
// intercept=specs[k].at(j).intensity-specs[k].at(j).mz*slope;
// specs[m].at(i).intensity+=(tmz*slope+intercept);
//} else {
specs[m].at(i).intensity += specs[k].at(j).intensity;
//}
//Averaging the mz values appears equivalent to realigning all spectra against
//an average Ledford correction.
specs[m].at(i).mz += specs[k].at(j).mz;
vPos[k]=j+1;
specs[k].at(j).intensity=-1.0;
mzcount++;
break;
}
dif=dt;
} else {
vPos[k]=j-1;
break;
}
}
}//for k
sp.add(specs[m].at(i).mz/mzcount,specs[m].at(i).intensity/numScans);
} //next i
} //next m
if(sp.size()>0) sp.sortMZ();
sp.setScanNumber(specs[0].getScanNumber());
sp.setScanNumber(specs[0].getScanNumber(true),true);
sp.setRTime(specs[0].getRTime());
sp.setRawFilter(cFilter1);
if(posLeft>0){
while(posLeft>0){
bs.pop_front();
posLeft--;
posA--;
}
}
delete [] specs;
return true;
}
/*
bool CNoiseReduction::ScanAverage(Spectrum& sp, vector<Spectrum>& vs, int pivot, float cutoff, double cp){
int i;
int j;
int k;
int ts;
int widthCount=0;
int numScans=1;
double dif;
double prec;
double dt;
double c;
if(cp==0.0) c=CParam(vs[pivot],1);
else c=cp;
bool bLeft=true;
int posLeft=pivot-1;
int posRight=pivot+1;
cout << "PIVOT: " << vs[pivot].getScanNumber() << endl;
cout << c << endl;
while(numScans<vs.size()){
//Alternate looking left and right
if(bLeft){
bLeft=false;
if(posLeft<0) continue;
ts=posLeft;
posLeft--;
} else {
bLeft=true;
if(posRight>=vs.size()) continue;
ts=posRight;
posRight++;
}
numScans++;
cout << "TS: " << ts << " " << vs[ts].getScanNumber() << endl;
for(i=0;i<vs[ts].size();i++) cout << vs[ts].at(i).mz << " " << vs[ts].at(i).intensity << endl;
//Match peaks between pivot scan and temp scan
k=0;
for(i=0;i<vs[pivot].size();i++){
dif=100000.0;
prec = c * vs[pivot].at(i).mz * vs[pivot].at(i).mz / 2;
for(j=k;j<vs[ts].size();j++){
dt=fabs(vs[pivot].at(i).mz-vs[ts].at(j).mz);
if(dt<=dif) {
if(dt<prec) {
cout << "MATCH: " << vs[pivot].at(i).mz << " to " << vs[ts].at(j).mz << " was " << vs[pivot].at(i).intensity;
vs[pivot].at(i).intensity+=vs[ts].at(j).intensity;
cout << " is now " << vs[pivot].at(i).intensity << endl;
vs[ts].at(j).mz=-1.0;
k=j+1;
break;
}
dif=dt;
} else {
k=j-1;
break;
}
}
}
//Add unmatched peaks from temp scan
for(i=0;i<vs[ts].size();i++){
if(vs[ts].at(i).mz>-1.0) {
vs[pivot].add(vs[ts].at(i));
cout << "Adding " << vs[ts].at(i).mz << endl;
}
}
//Sort pivot scan peaks for fast traversal against next temp scan
vs[pivot].sortMZ();
}
cout << "NUMSCANS: " << numScans << endl;
//Average points and apply cutoff
sp.clear();
for(i=0;i<vs[pivot].size();i++) {
vs[pivot].at(i).intensity/=numScans;
if(vs[pivot].at(i).intensity>=cutoff) sp.add(vs[pivot].at(i));
}
sp.setScanNumber(vs[pivot].getScanNumber());
sp.setScanNumber(vs[pivot].getScanNumber(true),true);
sp.setRTime(vs[pivot].getRTime());
return true;
}
bool CNoiseReduction::ScanAverage(Spectrum& sp, deque<Spectrum>& vs, int pivot, float cutoff){
int i;
int j;
int k;
int ts;
int widthCount=0;
int numScans=1;
double dif;
double prec;
double dt;
double c=CParam(vs[pivot],1);
bool bLeft=true;
int posLeft=pivot-1;
int posRight=pivot+1;
while(numScans<vs.size()){
//Alternate looking left and right
if(bLeft){
bLeft=false;
if(posLeft<0) continue;
ts=posLeft;
posLeft--;
} else {
bLeft=true;
if(posRight>=vs.size()) continue;
ts=posRight;
posRight++;
}
numScans++;
//Match peaks between pivot scan and temp scan
k=0;
for(i=0;i<vs[pivot].size();i++){
dif=100000.0;
prec = c * vs[pivot].at(i).mz * vs[pivot].at(i).mz / 2;
for(j=k;j<vs[ts].size();j++){
dt=fabs(vs[pivot].at(i).mz-vs[ts].at(j).mz);
if(dt<=dif) {
if(dt<prec) {
vs[pivot].at(i).intensity+=vs[ts].at(j).intensity;
vs[ts].at(j).mz=-1.0;
k=j+1;
break;
}
dif=dt;
} else {
k=j-1;
break;
}
}
}
//Add unmatched peaks from temp scan
for(i=0;i<vs[ts].size();i++){
if(vs[ts].at(i).mz>-1.0) vs[pivot].add(vs[ts].at(i));
}
//Sort pivot scan peaks for fast traversal against next temp scan
vs[pivot].sortMZ();
}
//Average points and apply cutoff
sp.clear();
for(i=0;i<vs[pivot].size();i++) {
vs[pivot].at(i).intensity/=numScans;
if(vs[pivot].at(i).intensity>=cutoff) sp.add(vs[pivot].at(i));
}
sp.setScanNumber(vs[pivot].getScanNumber());
sp.setScanNumber(vs[pivot].getScanNumber(true),true);
sp.setRTime(vs[pivot].getRTime());
return true;
}
*/
/*
bool CNoiseReduction::ScanAverageBuffered(Spectrum& sp, char* file, int width, float cutoff, int scanNum){
Spectrum ts;
Spectrum ps;
//MSReader r;
int i;
int j;
int k;
int widthCount=0;
int numScans=1;
double dif;
double prec;
double dt;
double c;
bool bLeft=true;
int posLeft=ps.getScanNumber()-1;
int posRight=ps.getScanNumber()+1;
int index;
char cFilter1[256];
char cFilter2[256];
sp.clear();
//if file is not null, create new buffer
if(file!=NULL){
strcpy(lastFile,file);
bs.clear();