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9 import string
10 import sys
11 sys.path=[sys.path,"/usr/people/robert/development/xpktools/"]
12 import xpktools
13
14 -def predictNOE(peaklist,originNuc,detectedNuc,originResNum,toResNum):
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28 returnLine=""
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30 datamap=_data_map(peaklist.datalabels)
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33 originAssCol = datamap[originNuc+".L"]+1
34 originPPMCol = datamap[originNuc+".P"]+1
35 detectedPPMCol = datamap[detectedNuc+".P"]+1
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37
38 if (peaklist.residue_dict(detectedNuc).has_key(str(toResNum)) and
39 peaklist.residue_dict(detectedNuc).has_key(str(originResNum))):
40 detectedList=peaklist.residue_dict(detectedNuc)[str(toResNum)]
41 originList=peaklist.residue_dict(detectedNuc)[str(originResNum)]
42 returnLine=detectedList[0]
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44 for line in detectedList:
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46 aveDetectedPPM =_col_ave(detectedList,detectedPPMCol)
47 aveOriginPPM =_col_ave(originList,originPPMCol)
48 originAss =string.splitfields(originList[0])[originAssCol]
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50 returnLine=xpktools.replace_entry(returnLine,originAssCol+1,originAss)
51 returnLine=xpktools.replace_entry(returnLine,originPPMCol+1,aveOriginPPM)
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53 return returnLine
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59 i=0
60 datamap={}
61 labelList=string.splitfields(labelline)
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64 for i in range(len(labelList)):
65 datamap[labelList[i]]=i
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67 return datamap
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