Пример #1
0
            bad = len(badids[TT])
            n_all = len(badids[TT])+len(goodids[TT])
            if n_all != 0:
                fRej = float(bad)/float(n_all)
            else:
                fRej = float('nan')

            print >> FracRejFile, AP+' | '+TT+' | '+str(fRej)
            #print ObservedData.keys(), NewNuisanceData.keys(), goodids.keys()
            outdata = dfp.applyGoodIDs(ObservedData[TT],NewNuisanceData[TT],goodids[TT])
            if dfp.ToBeBinned(Object.name,TT):
                outdata = dfp.BinnedData(outdata,45e0)
            NuisFile = DataPrepPath+Object.name+'.AP'+AP+'.'+TT+'.nus'
            LCFile = DataPrepPath+Object.name+'.AP'+AP+'.'+TT+'.lc'
            NuisFileObject = open(NuisFile,'w')
            LCFileObject = open(LCFile,'w')
        
            dtheader = dfp.detrendHeader
            LCheader = dfp.LCHeader
            print >> NuisFileObject, dtheader
            print >> LCFileObject, LCheader
            for i in range(len(outdata['time'])):
                lcline = dfp.LClineFromIndex(outdata,i)
                dtline = dfp.dtlineFromIndex(outdata,i)
                print >> NuisFileObject, dtline 
                print >> LCFileObject, lcline

            print 'outlier/binning writing: %s' % (NuisFile)
            print '%s' % (LCFile)

FracRejFile.close()
Пример #2
0
for fileName in os.listdir(DataPrepPath):
    if fileName.startswith(Object.name) and fileName.endswith('.data'):
        AP = dfp.getAP(fileName)
        outdict = dfp.readDataFile(DataPrepPath+fileName)
        TT = dfp.getTT(fileName,Object.name)
        T0 = Object.ParDict['T0.'+TT]['value']
        tT = Object.ParDict['tT']['value']
        tG = Object.ParDict['tG']['value']
        outdict, normalizing_factor = dfp.normalizeFluxRatio(outdict,T0,tT,tG)
        FluxNorm[AP][TT] = normalizing_factor
        NuisFile = DataPrepPath+Object.name+'.AP'+AP+'.'+TT+'.nus0'
        LCFile = DataPrepPath+Object.name+'.AP'+AP+'.'+TT+'.lc0'
        NuisFileObject = open(NuisFile,'w')
        LCFileObject = open(LCFile,'w')
        dtheader = dfp.detrendHeader
        LCheader = dfp.LCHeader
        print >> NuisFileObject, dtheader
        print >> LCFileObject, LCheader
        for i in range(len(outdict['time'])):
            lcline = dfp.LClineFromIndex(outdict,i)
            dtline = dfp.dtlineFromIndex(outdict,i)
            print >> NuisFileObject, dtline 
            print >> LCFileObject, lcline

        print 'writing: %s' % (NuisFile)
        print '%s' % (LCFile)
 
fileOut = open(cfp.PicklePath+Object.name+'.FluxNorm.pickle','wb')
pickle.dump(FluxNorm,fileOut,-1)
fileOut.close()