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')