for cluster in samePeptideClusters:
if scanFDict[cluster[0]]['sequenced'] or True:
continue
scanData = {}
specsInfo = [DataFile.getMassIntPairs(scanFDict[scanF]['dta']) for scanF in cluster]
precMass = np.average(np.array([scanFDict[scanF]['precMass'] for scanF in cluster]))
scanData['light scan'] = None
scanData['heavy scan'] = 'N/A'
scanData['shared peaks ratio'] = 'N/A'
print 'Now sequencing unpaired scan(s) %s \n' % (str(cluster),)
s1 = time.time()
sharedInfo, starts, ends, deltas, G = DNS.prepSingleSpectrumGraph(specsInfo, precMass, addEnds, options.ppmstd, 0, 0, verbose=options.verbose)
scanData['M+H'] = precMass
epMean = options.ppmsyserror * precMass * 10**-6
epSTD = options.ppmstd * precMass * 10**-6
specs = [PN.Spectrum(PNet, precMass, Nmod=0, Cmod=0, epsilon=2*epSTD, spectrum=massIntPairs) for massIntPairs in specsInfo]
for spec in specs:
spec.initializeNoiseModel()
scanData.update(DNS.getSpectrumGraphData(G, deltas, specs, starts, ends, precMass - Constants.mods['H+'] - Constants.mods['H2O'], ambigPenaltyFun, ppmPenaltyFun, hashedAAs, termModHash=termModHash, maxEdge=options.maxedge, minEdge=options.minedge, subGraphCut=options.subgraphcut, subAlpha=0.3, alpha=options.alpha, epMean=epMean, epSTD=epSTD, epStep=epStep, verbose=options.verbose))
scanData['sequencing time'] = time.time() - s1
scanData['pair configuration'] = 'N/A'
if options.output:
for scanF in cluster:
scanData['light scan'] = int(scanF)
outFile.write('\t'.join([str(scanData[col]) for col in cols]) + '\n')
