def getSamePeptideClusters(precMassClusters, scanFDict, svmModel, svmRange, ppmSTD=5, cutOff=0):
trueClusters = []
for cluster in precMassClusters:
if len(cluster) == 1:
trueClusters += [cluster]
else:
# print 'testing cluster', cluster
pairIndex = []
xVals = []
specs = []
for i in range(len(cluster)):
specs += [DataFile.getMassIntPairs(scanFDict[cluster[i]]['dta'])]
dMatrix = np.ones((len(cluster), len(cluster))) * -2
for i in range(len(cluster)):
for j in range(i+1, len(cluster)):
epSTD = ppmSTD * 10 ** -6 * scanFDict[cluster[i]]['precMass']
SVMClassificationInfo = SA.getSpectraPairInfoForSVMClassification(specs[i], specs[j], scanFDict[cluster[i]]['precMass'], NMod=0, CMod=0, epsilon=2*epSTD)
xVals += [SVMClassificationInfo]
pairIndex += [(i, j)]
xValsNorm = svmutil.normalize_instances(xVals, svmRange)
pLabs = svmutil.svm_predict([0]*len(xValsNorm), xValsNorm, svmModel)[0]
# print pLabs
for i, pLab in enumerate(pLabs):
# Scale distances by 4: totalTICRatio, 1: TotalSharedPeaksRatio
dMatrix[pairIndex[i][0]][pairIndex[i][1]] = dMatrix[pairIndex[i][1]][pairIndex[i][0]] = xVals[i][1] if pLab==1 else -1
trueClusters += heirarchicalClusteringAverageLinkage([[scanF] for scanF in cluster], dMatrix, cutOff=cutOff)
return trueClusters
def getPairs(pairs, xVals):
for pair in pairs:
lightSpecs = [DataFile.getMassIntPairs(scanFDict[lightScanF]['dta']) for lightScanF in samePeptideClusters[pair[0]]]
heavySpecs = [DataFile.getMassIntPairs(scanFDict[heavyScanF]['dta']) for heavyScanF in samePeptideClusters[pair[1]]]
lightPrecMass = np.average(np.array([scanFDict[lightScanF]['precMass'] for lightScanF in samePeptideClusters[pair[0]]]))
epSTD = (float(paramsDict['ppmstd']['value'])) * 10 ** -6 * lightPrecMass
lightMergedSpec = SA.mergeSpectra(lightSpecs, epsilon=2*epSTD)
heavyMergedSpec = SA.mergeSpectra(heavySpecs, epsilon=2*epSTD)
svmClassificationData = SA.getSpectraPairInfoForSVMClassification(lightMergedSpec, heavyMergedSpec, lightPrecMass, NMod=pairConfig['NMod'], CMod=pairConfig['CMod'], epsilon=2*epSTD)
xVals.put([svmClassificationData])
return xVals
svmRange = svmutil.load_ranges(parent + os.path.splitext(pairConfig['Model'])[0] + '.range')
xVals = []
# xVals = getPairsThread(pairs)
for pair in pairs:
lightSpecs = [DataFile.getMassIntPairs(scanFDict[lightScanF]['dta']) for lightScanF in samePeptideClusters[pair[0]]]
heavySpecs = [DataFile.getMassIntPairs(scanFDict[heavyScanF]['dta']) for heavyScanF in samePeptideClusters[pair[1]]]
lightPrecMass = np.average(np.array([scanFDict[lightScanF]['precMass'] for lightScanF in samePeptideClusters[pair[0]]]))
epSTD = options.ppmstd * 10 ** -6 * lightPrecMass
lightMergedSpec = SA.mergeSpectra(lightSpecs, epsilon=2*epSTD)
heavyMergedSpec = SA.mergeSpectra(heavySpecs, epsilon=2*epSTD)
svmClassificationData = SA.getSpectraPairInfoForSVMClassification(lightMergedSpec, heavyMergedSpec, lightPrecMass, NMod=pairConfig['NMod'], CMod=pairConfig['CMod'], epsilon=2*epSTD)
xVals += [svmClassificationData]
xValsNorm = svmutil.normalize_instances(xVals, svmRange)
pLab = svmutil.svm_predict([0]*len(xValsNorm), xValsNorm, svmModel)[0]
print 'Pairs found. Time taken:', time.time() - t1, '\n'
heavySeqMap = copy.deepcopy(seqMap['LADS Unit Test'])
heavySeqMap['Mods']['N-Term'] = paramsDict['Pair Configurations'][pairConfigName]['NModSymbol']
heavySeqMap['Mods']['C-Term'] = paramsDict['Pair Configurations'][pairConfigName]['CModSymbol']
# hyperParameters = PNet.getHyperParameters(pairConfigName)
# ambigPenaltyFun = DNS.getAmbigEdgePenaltyFunction(hyperParameters['minedge'], hyperParameters['ambigopen'], hyperParameters['ambigextend'])
# ppmPenaltyFun = DNS.getPPMPenaltyFun(hyperParameters['ppmstd'], hashedAAs, hyperParameters['minedge'], hyperParameters['ppmpen'], 0, epStep)
for cluster in precMassClusters:
if len(cluster) == 1:
continue
specs = []
for scanF in cluster:
specs += [DataFile.getMassIntPairs(scanFDict[scanF]['dta'])]
for i in range(len(cluster)):
for j in range(i+1, len(cluster)):
if cluster[i] in processedInfo[progName] and cluster[j] in processedInfo[progName]:
epSTD = options.ppmstd * 10 ** -6 * scanFDict[cluster[i]]['precMass']
SVMClassificationInfo = SA.getSpectraPairInfoForSVMClassification(specs[i], specs[j], scanFDict[cluster[i]]['precMass'], NMod=0, CMod=0, epsilon=2*epSTD)
seq1 = processedInfo[progName][cluster[i]][infoMap[progDict[progName]]['Peptide']]
seq2 = processedInfo[progName][cluster[j]][infoMap[progDict[progName]]['Peptide']]
xVal = 1 if seq1 == seq2 else -1
clusterOut.write(' '.join([str(xVal)] + ['%i:%f' % (key, SVMClassificationInfo[key]) for key in sorted(SVMClassificationInfo)]) + ' # Scans %s, %i - %s, %i\n' % (processedInfo[progName][cluster[i]][infoMap[progDict[progName]]['Peptide']], cluster[i], processedInfo[progName][cluster[j]][infoMap[progDict[progName]]['Peptide']], cluster[j]))
clusterOut.close()
for pairConfigName in paramsDict['Pair Configurations']:
pairConfig = paramsDict['Pair Configurations'][pairConfigName]
delta = pairConfig['NMod'] + pairConfig['CMod']
deltaPairs = An.findDeltaPairsClusters(precMassClusters, scanFDict, delta, ppm=options.ppmstd)
symLightInds.add(ion[0])
for ion in heavyIons:
totalHeavyInds.add(ion[0])
for ion in allPairedIonsDict[heavyIons]:
totalLightInds.add(ion[0])
totalNumPeaks = float(lightMergedSpec.shape[0] + heavyMergedSpec.shape[0])
totalSharedPeaksRatio = (len(totalLightInds) + len(totalHeavyInds))/totalNumPeaks
singleSymSharedPeaksRatio = (len(symLightInds) + len(symHeavyInds))/totalNumPeaks
doubleSymSharedPeaksRatio = (len(doubleSymLightInds) + len(doubleSymHeavyInds))/totalNumPeaks
"""
SVMClassificationInfo = SA.getSpectraPairInfoForSVMClassification(
lightMergedSpec,
heavyMergedSpec,
lightPrecMass,
pairConfig["NMod"],
pairConfig["CMod"],
epsilon=2 * epSTD,
)
possPairs = [
(lightScanF, heavyScanF)
for lightScanF in samePeptideClusters[pair[0]]
for heavyScanF in samePeptideClusters[pair[1]]
]
# possPairsList += [set(possPairs)]
y += [1 if any([pair in progPairs[pairConfigName] for pair in possPairs]) else -1]
# x += [{1: totalSharedPeaksRatio, 2: singleSymSharedPeaksRatio, 3: scanFDict[pair[0]]['precMass']}]
x += [SVMClassificationInfo]
# pairs[pairConfigName][pair] = getSharedPeaksRatio(lightSpec, heavySpec, pairConfig, epsilon)
