cols = ['light scan', 'heavy scan', 'pair configuration', 'M+H', 'score', 'seq', 'epsilon', 'ambiguous edges', 'num ambig edges']
if options.output:
outFile = open(options.output, 'w')
outFile.write('\t'.join([col.upper() for col in cols]) + '\n')
PNet = PN.ProbNetwork(options.config, options.model)
dtaList = glob.glob(options.dtadir + '/*.dta')
scanFDict = getScanFDict(dtaList)
aas = Constants.addPepsToAADict(300)
hashedAAs = Constants.hashAAsEpsilonRange(aas, epStep, maxEp)
ambigOpenPenalty = 0
ambigPenaltyFun = DNS.getAmbigEdgePenaltyFunction(options.minedge, ambigOpenPenalty, options.ambigpenalty)
ppmPenaltyFun = DNS.getPPMPenaltyFun(options.ppmstd, hashedAAs, options.minedge, options.ppmpenalty, options.ppmsyserror, epStep)
print 'Getting Clusters'
parent = os.path.abspath(os.pardir)
clusterSVMModel = svmutil.svm_load_model(parent + paramsDict['Cluster Configuration']['model'])
clusterSVMRanges = svmutil.load_ranges(parent + os.path.splitext((paramsDict['Cluster Configuration']['model']))[0] + '.range')
precMassClusters = Analytics.findSamePrecMassClusters(dtaList, ppm=options.ppmstd)
# print 'precMassClusters', precMassClusters
samePeptideClusters = Analytics.getSamePeptideClusters(precMassClusters, scanFDict, clusterSVMModel, clusterSVMRanges, ppmSTD=options.ppmstd, cutOff=float(paramsDict['Cluster Configuration']['cutoff']))
# samePeptideClusters = Analytics.getSamePeptideClusters(precMassClusters, scanFDict, clusterSVMModel, clusterSVMRanges, ppmSTD=options.ppmstd, cutOff=4)
# samePeptideClusters = An.getSamePeptideClusters(precMassClusters, scanFDict, clusterSVMModel, clusterSVMRanges, ppmSTD=options.ppmstd, cutOff=4)
# To test without any clustering
#samePeptideClusters = [[scanF] for scanF in scanFDict]
