def makeXsecData(options, data):
    dummy,description = treedescription()
    allpar = description.split(':')

    xsecdata = {}

    if data == {}:
        print "Your data array is empty! Exiting"
        sys.exit()

    for key in data:
        
        CLsexp = float(data[key][allpar.index("CLsexp")])
        upperLimit = float(data[key][allpar.index("upperLimit")])
        expectedUpperLimit = float(data[key][allpar.index("expectedUpperLimit")])
        
        expectedUpperLimitMinus1Sig = float(data[key][allpar.index("expectedUpperLimitMinus1Sig")])
        expectedUpperLimitPlus1Sig = float(data[key][allpar.index("expectedUpperLimitPlus1Sig")])
        
        expectedUpperLimitMinus2Sig = float(data[key][allpar.index("expectedUpperLimitMinus2Sig")])
        expectedUpperLimitPlus2Sig = float(data[key][allpar.index("expectedUpperLimitPlus2Sig")])
        
        fID = int(float(data[key][allpar.index("fID")]))

        #print "-1: %.3f, -2: %.3f" % (expectedUpperLimitMinus1Sig, expectedUpperLimitMinus2Sig)

        # TODO need to extract this plus uncertainty from SignalDB
        # NOTE: hardcoded for 1 proc, hence the extra [0]
        xsec = xsecs[key][0] * 1000
        xsecUp = (1+xsecs[key][1]) * xsec
        xsecDown = (1-xsecs[key][1]) * xsec

        print "%s: xsec=%f relunc=%f up=%f down=%f" % (key, xsec, xsecs[key][1], xsecUp, xsecDown)

        xsec2 = xsec/2
        xsec4 = xsec/4
        xsec8 = xsec/8

        xsec2Up = xsecUp/2
        xsec4Up = xsecUp/4
        xsec8Up = xsecUp/8
        
        xsec2Down = xsecDown/2
        xsec4Down = xsecDown/4
        xsec8Down = xsecDown/8

        xsecdata[key] = {"upperLimit": upperLimit, "expectedUpperLimit" : expectedUpperLimit, "expectedUpperLimitMinus1Sig" : expectedUpperLimitMinus1Sig,
                         "expectedUpperLimitPlus1Sig" : expectedUpperLimitPlus1Sig, "expectedUpperLimitMinus2Sig" : expectedUpperLimitMinus2Sig,
                         "expectedUpperLimitPlus2Sig" : expectedUpperLimitPlus2Sig, "xsec" : xsec, "xsecUp" : xsecUp, "xsecDown" : xsecDown, "xsec2": xsec2, 
                         "xsec2Up" : xsec2Up, "xsec2Down" : xsec2Down,
                         "xsec4Up" : xsec4Up, "xsec4Down" : xsec4Down,
                         "xsec8Up" : xsec8Up, "xsec8Down" : xsec8Down,
                         "xsec4": xsec4, "xsec8": xsec8, "fID" : fID, "CLsexp": CLsexp}

    return xsecdata
Пример #2
0
def harvestToDict(harvestInputFileName=""):
    print ">>> entering harvestToDict()"

    massPlaneDict = {}

    harvestInput = open(harvestInputFileName, "r")

    print harvestInputFileName
    descriptionFileName = harvestInputFileName.rsplit(
        '/', 1)[0] + "/summary_harvest_tree_description.*"
    os.system("cp %s ." % descriptionFileName)
    descriptionFileName = harvestInputFileName + "_infoFile"
    os.system("cp %s output_infoFile" % descriptionFileName)
    os.system("cp %s output" % harvestInputFileName)

    from summary_harvest_tree_description import treedescription
    dummy, fieldNames = treedescription()
    fieldNames = fieldNames.split(':')

    if ".json" in harvestInputFileName and 0:
        print ">>> Interpreting json file"

        with open(harvestInput) as inputJSONFile:
            inputJSONFile = json.load(inputJSONFile)

    else:
        print ">>> Interpreting text file"

        for massLine in harvestInput.readlines():
            values = massLine.split()
            values = dict(zip(fieldNames, values))

            massPoint = (float(values["m0/F"]), float(values["m12/F"]))

            massPlaneDict[massPoint] = {
                "CLs":
                ROOT.RooStats.PValueToSignificance(float(values["CLs/F"])),
                "CLsexp":
                ROOT.RooStats.PValueToSignificance(float(values["CLsexp/F"])),
                "clsu1s":
                ROOT.RooStats.PValueToSignificance(float(values["clsu1s/F"])),
                # "clsu2s":     ROOT.RooStats.PValueToSignificance( float(values["clsu2s/F"])  ) ,
                "clsd1s":
                ROOT.RooStats.PValueToSignificance(float(values["clsd1s/F"])),
                # "clsd2s":     ROOT.RooStats.PValueToSignificance( float(values["clsd2s/F"])  ) ,
            }

    print massPlaneDict
    return massPlaneDict
Пример #3
0
def main():
    options = parseCmdLine(sys.argv)

    dummy, description = treedescription()
    allpar = description.split(':')

    xsecIdx = allpar.index('xsec')
    ULIdx = allpar.index('upperLimit')
    if options.expected:
        ULIdx = allpar.index('expectedUpperLimit')
    m0Idx = allpar.index('m0')
    m12Idx = allpar.index('m12')
    fIdIdx = allpar.index('fID')

    p0Idx = allpar.index('p0')
    p1Idx = allpar.index('p1')
    CLsIdx = allpar.index('CLs')
    CLsexpIdx = allpar.index('CLsexp')

    covqualIdx = allpar.index('covqual')
    dodgycovIdx = allpar.index('dodgycov')
    failedcovIdx = allpar.index('failedcov')
    failedfitIdx = allpar.index('failedfit')
    failedp0Idx = allpar.index('failedp0')
    failedstatusIdx = allpar.index('failedstatus')
    fitstatusIdx = allpar.index('fitstatus')

    #f = open(options.filename, "r")

    # get files to read
    f = open(
        "Outputs/%s_combined_fixSigXSecNominal__1_harvest_list_infoFile" %
        options.grid, "r")
    filenames = {}
    for l in f.readlines():
        (N, fname) = l.strip().split(":")
        filenames[int(
            N.strip())] = "Outputs/%s_%s_fixSigXSecNominal__1_harvest_list" % (
                options.grid, fname.strip())
    f.close()

    data = {}
    CLsdata = {}
    for N in filenames:
        f = open(filenames[N])
        for l in f.readlines():
            vals = l.strip().split(' ')
            key = "%d_%d" % (int(float(vals[m0Idx])), int(float(vals[m12Idx])))
            if key != options.point:
                continue

            data[N] = [float(vals[ULIdx]), float(vals[xsecIdx]), N]
            CLsdata[N] = [
                float(vals[p0Idx]),
                float(vals[p1Idx]),
                float(vals[CLsIdx]),
                float(vals[CLsexpIdx])
            ]

        f.close()

    if options.seperate:
        print "# x\ty\tUL\txsec\tSR\tCLs"
    else:
        print "# x\ty\tUL*xsec\tSR"

    for N in sorted(data):
        (x, y) = options.point.split("_")
        x = int(x)
        y = int(y)

        if options.seperate:
            print "%d\t%d\t%f\t%f\t%d\t%.2f\t%.2f (exp)" % (
                x, y, data[N][0], data[N][1], data[N][2], CLsdata[N][2],
                CLsdata[N][3])
        else:
            print "%d\t%d\t%f\t%d" % (x, y, data[N][0] * data[N][1],
                                      data[N][2])

        covqual = int(float(vals[covqualIdx]))
        dodgycov = int(float(vals[dodgycovIdx]))
        failedcov = int(float(vals[failedcovIdx]))
        failedfit = int(float(vals[failedfitIdx]))
        failedp0 = int(float(vals[failedp0Idx]))
        failedstatus = int(float(vals[failedstatusIdx]))
        fitstatus = int(float(vals[fitstatusIdx]))

        # verbose print line to see what's going on with a point
        print "\t ==> covqual = %d, dodgycov = %d, failedcov = %d, failedfit = %d, failedp0 = %d, failedstatus = %d, fitstatus = %d" % (
            covqual, dodgycov, failedcov, failedfit, failedp0, failedstatus,
            fitstatus)

    return
            #g.SetPoint(counter,i[0],StatTools.GetSigma(i[1]))
            
            counter+=1
        g.SetName(self.name)
        g.SetLineColor(color)
        g.SetMarkerColor(color) 
        g.SetLineWidth(2)        
        self.tgraph=g
        return g

#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%#
# Some global variables
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%#

from summary_harvest_tree_description import treedescription
dummy,description = treedescription()
allpar = description.split(':')
print dummy,description

# INPUTDIR has the workspaces from HistFitter
INPUTDIR="../../results/"
INPUTDIR_SIGNALDB="/afs/cern.ch/atlas/groups/susy/0lepton/ZeroLeptonFitter/ZeroLepton-00-00-36_Light/"

# OUTPUTDIR is where the combination of these using hadd will go, as well as 
#           all the list files for the contours, the histograms and the plots
OUTPUTDIR="Outputs/"
PLOTSDIR="plots/"

try:
    os.mkdir(OUTPUTDIR)
except:
Пример #5
0
def main():
    options = parseCmdLine(sys.argv)

    dummy, description = treedescription()
    allpar = description.split(':')

    if options.filename.find("Moriond13") != -1:
        # from HistFitter v24 source code
        description = "p0:p1:CLs:"
        description += "mode:nexp:"
        description += "seed:"
        description += "CLsexp:"
        description += "fID:sigma0:sigma1:"
        description += "clsu1s:clsd1s:clsu2s:clsd2s:"
        description += "upperLimit:upperLimitEstimatedError:expectedUpperLimit:expectedUpperLimitPlus1Sig:expectedUpperLimitPlus2Sig:expectedUpperLimitMinus1Sig:expectedUpperLimitMinus2Sig:xsec:excludedXsec:"
        description += "m0:m12"

        allpar = description.split(':')

    xsecIdx = allpar.index('xsec')
    ULIdx = allpar.index('upperLimit')
    if options.expected:
        ULIdx = allpar.index('expectedUpperLimit')

    if not "pMSSM" in options.filename:
        m0Idx = allpar.index('m0')
        m12Idx = allpar.index('m12')
    else:
        m0Idx = allpar.index('M1')
        m12Idx = allpar.index('M2')

    fIdIdx = allpar.index('fID')

    p0Idx = allpar.index('p0')
    p1Idx = allpar.index('p1')
    CLsIdx = allpar.index('CLs')
    CLsexpIdx = allpar.index('CLsexp')

    covqualIdx = allpar.index('covqual')
    dodgycovIdx = allpar.index('dodgycov')
    failedcovIdx = allpar.index('failedcov')
    failedfitIdx = allpar.index('failedfit')
    failedp0Idx = allpar.index('failedp0')
    failedstatusIdx = allpar.index('failedstatus')
    fitstatusIdx = allpar.index('fitstatus')

    f = open(options.filename, "r")

    data = {}
    CLsdata = {}
    for l in f.readlines():
        vals = l.strip().split(' ')
        key = "%d_%d" % (int(float(vals[m0Idx])), int(float(vals[m12Idx])))
        data[key] = [
            float(vals[ULIdx]),
            float(vals[xsecIdx]),
            int(vals[fIdIdx])
        ]
        CLsdata[key] = [
            float(vals[p0Idx]),
            float(vals[p1Idx]),
            float(vals[CLsIdx]),
            float(vals[CLsexpIdx])
        ]

    if options.seperate:
        print "# x\ty\tUL\txsec\tSR\tCLs"
    elif options.hepdata:
        print makeHepDataHeader(options.filename)
    else:
        print "# x\ty\tUL*xsec\tSR"

    for key in sorted(data.iterkeys(), key=lambda a: map(int, a.split('_'))):
        (x, y) = key.split("_")
        x = int(x)
        y = int(y)

        ## HACK to filter e.g. rectangle (easier to isolate crashed points)
        #if not (x > 200 and x < 300): continue
        #if not (y > 100 and y < 200): continue

        #if not y == 0: continue

        if options.seperate:
            print "%d\t%d\t%f\t%f\t%d\t%e\t%e (exp)" % (
                x, y, data[key][0], data[key][1], data[key][2],
                CLsdata[key][2], CLsdata[key][3])
        elif options.hepdata:
            UL = data[key][0] * data[key][1]
            SR = GetSRName(data[key][2])
            print "%d; %d; %e; %s" % (x, y, UL, SR)
        else:
            print "%d\t%d\t%f\t%d" % (x, y, data[key][0] * data[key][1],
                                      data[key][2])

        covqual = int(float(vals[covqualIdx]))
        dodgycov = int(float(vals[dodgycovIdx]))
        failedcov = int(float(vals[failedcovIdx]))
        failedfit = int(float(vals[failedfitIdx]))
        failedp0 = int(float(vals[failedp0Idx]))
        failedstatus = int(float(vals[failedstatusIdx]))
        fitstatus = int(float(vals[fitstatusIdx]))

        # verbose print line to see what's going on with a point
        #print "\t ==> covqual = %d, dodgycov = %d, failedcov = %d, failedfit = %d, failedp0 = %d, failedstatus = %d, fitstatus = %d" % (covqual, dodgycov, failedcov, failedfit, failedp0, failedstatus, fitstatus)

    return
def readData(options, filename):
    try:
        f = open(filename)
    except: 
        print "Cannot open file %s" % filename
        return

    print "Reading data from %s" % filename

    dummy,description = treedescription()
    allpar = description.split(':')
    
    #extend this to more pars on gridname if wanted
    par1_s = "mwino"

    data = {}
    for l in f.readlines():
        d = l.strip().split()
       
        selectpar = "expectedUpperLimit" # makes NO sense to use something different here
        pval = float( d[allpar.index(selectpar)]) 
        par1 = int(float( d[allpar.index(par1_s)]))
        key = "%d" % (par1)
      
        # float strings -> so make them float, then an int to throw away .0000 and then to bool
        failedcov =  bool(int(float(d[allpar.index("failedcov")])))  # Mediocre cov matrix quality
        covqual = int(float(d[allpar.index("covqual")]))             # covqual
        failedfit = bool(int(float(d[allpar.index("failedfit")])))   # Fit failure
        failedp0 = bool(int(float(d[allpar.index("failedp0")])))     # Base p0 ~ 0.5 (this can reject good fits)!
        fitstatus = bool(int(float(d[allpar.index("fitstatus")])))   # Fit status from Minuit
        nofit = bool(int(float(d[allpar.index("nofit")])))           # Whether there's a fit present
 
        if failedfit or failedcov:
            print "WARNING: fit failed for %s" % key
            continue

        if covqual < 3 and covqual != -1:
            print "WARNING: covqual=%d for %s" % (covqual, key)
            continue


        # this whole block is stolen from makeContoursNew.py. Do we need a module for this? Yes, we do.... --GJ, 4 feb 15

        if selectpar == "expectedUpperLimit" and pval < 0.00001:
            print "INFO: %s removing %s < 0.00001 for %s" % (filename, selectpar, key)
            continue
       
        # 110 is 20 times our default step -> this is almost certainly a bug
        if selectpar == "expectedUpperLimit" and pval == 110.0:
            print "INFO: %s removing expUL==110.0 for %s" % (filename, key)
            continue

        # if -1sig, -2sig == 0 and +1sig, 2sig == 100 -> almost certainly a bug too
        if selectpar == "expectedUpperLimit" and float(d[allpar.index("expectedUpperLimitMinus1Sig")]) == 0.0 and float(d[allpar.index("expectedUpperLimitMinus2Sig")]) == 0.0 and float(d[allpar.index("expectedUpperLimitPlus1Sig")]) == 100.0 and float(d[allpar.index("expectedUpperLimitPlus2Sig")]) == 100.0:
            print "INFO: %s removing point %s with expULMinus1Sig == expULMinus2Sig == 0 and expULPlus1Sig == expULPlus2Sig == 100" % (filename, key)
            continue

        if selectpar == "expectedUpperLimit" and float(d[allpar.index("upperLimit")]) == 0.0:
            print "INFO: %s removing obsUL=0.0 for %s" % (filename, key)
            continue

        # throw away points with CLsexp > 0.99 and UL < 1.0 and CLs=-1 and UL<1 when merging on UL                      
        CLsExp = float( d[allpar.index("CLsexp")])
        if selectpar == "expectedUpperLimit" and pval < 1.0 and (CLsExp>0.99 or CLsExp<0) and float( d[allpar.index("upperLimit")])<1:                   
            if CLsExp>0.99: print "INFO: %s replacing CLsexp with 0.01 since UL < 1.0  and CLsexp=1 for %s" % (filename, key)
            elif CLsExp<0: print "INFO: %s replacing CLsexp with 0.01 since UL < 1.0  and CLsexp=-1 for %s" % (filename, key)
            d[allpar.index("CLsexp")] = str(0.01)
            d[allpar.index("CLs")] = str(0.01)
            d[allpar.index("clsu1s")] = str(0.01)
            d[allpar.index("clsd1s")] = str(0.01)
            d[allpar.index("p1")] = str(0.01)

        data[key] = d
def makeXsecData(options, data):
    dummy,description = treedescription()
    allpar = description.split(':')

    xsecdata = {}
    xsecs = readCrossSections(options)

    if data == {}:
        print "Your data array is empty! Exiting"
        sys.exit()

    for key in data:
        # extend here to par3 if needed
        (par1, par2) = (int(x) for x in key.split("_"))
        if not useThisPoint(options, par1, par2):
            print "Skipping %s" % key
            continue
        
        CLsexp = float(data[key][allpar.index("CLsexp")])
        upperLimit = float(data[key][allpar.index("upperLimit")])
        expectedUpperLimit = float(data[key][allpar.index("expectedUpperLimit")])
        
        expectedUpperLimitMinus1Sig = float(data[key][allpar.index("expectedUpperLimitMinus1Sig")])
        expectedUpperLimitPlus1Sig = float(data[key][allpar.index("expectedUpperLimitPlus1Sig")])
        
        expectedUpperLimitMinus2Sig = float(data[key][allpar.index("expectedUpperLimitMinus2Sig")])
        expectedUpperLimitPlus2Sig = float(data[key][allpar.index("expectedUpperLimitPlus2Sig")])
        
        fID = int(float(data[key][allpar.index("fID")]))

        #print "-1: %.3f, -2: %.3f" % (expectedUpperLimitMinus1Sig, expectedUpperLimitMinus2Sig)

        # TODO need to extract this plus uncertainty from SignalDB
        # NOTE: hardcoded for 1 proc, hence the extra [0]
        xsec = xsecs[key][0][0]*1000
        xsecUp = (1+xsecs[key][0][1]) * xsec
        xsecDown = (1-xsecs[key][0][1]) * xsec

        print "%s: xsec=%.2e relunc=%.2e up=%.2e down=%.2e" % (key, xsec, xsecs[key][0][1], xsecUp, xsecDown)

        xsec2 = xsec/2
        xsec4 = xsec/4
        xsec8 = xsec/8

        xsec2Up = xsecUp/2
        xsec4Up = xsecUp/4
        xsec8Up = xsecUp/8
        
        xsec2Down = xsecDown/2
        xsec4Down = xsecDown/4
        xsec8Down = xsecDown/8

        xsecdata[key] = {"upperLimit": upperLimit, "expectedUpperLimit" : expectedUpperLimit, "expectedUpperLimitMinus1Sig" : expectedUpperLimitMinus1Sig,
                         "expectedUpperLimitPlus1Sig" : expectedUpperLimitPlus1Sig, "expectedUpperLimitMinus2Sig" : expectedUpperLimitMinus2Sig,
                         "expectedUpperLimitPlus2Sig" : expectedUpperLimitPlus2Sig, "xsec" : xsec, "xsecUp" : xsecUp, "xsecDown" : xsecDown, "xsec2": xsec2, 
                         "xsec2Up" : xsec2Up, "xsec2Down" : xsec2Down,
                         "xsec4Up" : xsec4Up, "xsec4Down" : xsec4Down,
                         "xsec8Up" : xsec8Up, "xsec8Down" : xsec8Down,
                         "xsec4": xsec4, "xsec8": xsec8, "fID" : fID, "CLsexp": CLsexp}

    return xsecdata
def readData(options, filename):
    try:
        f = open(filename)
    except: 
        print "Cannot open file %s" % filename
        return

    print "Reading data from %s" % filename

    dummy,description = treedescription()
    allpar = description.split(':')
    
    #extend this to more pars on gridname if wanted
    par1_s = "m0"
    par2_s = "m12"
    par3_s = ""

    data = {}
    for l in f.readlines():
        d = l.strip().split()
       
        selectpar = "expectedUpperLimit" # makes NO sense to use something different here
        pval = float( d[allpar.index(selectpar)]) 
        par1 = int(float( d[allpar.index(par1_s)]))
        par2 = int(float( d[allpar.index(par2_s)]))
        key = "%d_%d" % (par1, par2)
      
        # float strings -> so make them float, then an int to throw away .0000 and then to bool
        failedcov =  bool(int(float(d[allpar.index("failedcov")])))  # Mediocre cov matrix quality
        covqual = int(float(d[allpar.index("covqual")]))             # covqual
        failedfit = bool(int(float(d[allpar.index("failedfit")])))   # Fit failure
        failedp0 = bool(int(float(d[allpar.index("failedp0")])))     # Base p0 ~ 0.5 (this can reject good fits)!
        fitstatus = bool(int(float(d[allpar.index("fitstatus")])))   # Fit status from Minuit
        nofit = bool(int(float(d[allpar.index("nofit")])))           # Whether there's a fit present
 
        if failedfit or failedcov:
            print "WARNING: fit failed for %s" % key
            continue

        if covqual < 3 and covqual != -1:
            print "WARNING: covqual=%d for %s" % (covqual, key)
            continue

        if par3_s != "":
            par3 = int(float( d[allpar.index(par3_s)]))
            key = "%d_%d_%d" % (par1, par2, par3)

        # this whole block is stolen from makeContoursNew.py. Do we need a module for this? Yes, we do.... --GJ, 4 feb 15

        if selectpar == "expectedUpperLimit" and pval < 0.00001:
            print "INFO: %s removing %s < 0.00001 for %s" % (filename, selectpar, key)
            continue
       
        # 110 is 20 times our default step -> this is almost certainly a bug
        if selectpar == "expectedUpperLimit" and pval == 110.0:
            print "INFO: %s removing expUL==110.0 for %s" % (filename, key)
            continue

        # if -1sig, -2sig == 0 and +1sig, 2sig == 100 -> almost certainly a bug too
        if selectpar == "expectedUpperLimit" and float(d[allpar.index("expectedUpperLimitMinus1Sig")]) == 0.0 and float(d[allpar.index("expectedUpperLimitMinus2Sig")]) == 0.0 and float(d[allpar.index("expectedUpperLimitPlus1Sig")]) == 100.0 and float(d[allpar.index("expectedUpperLimitPlus2Sig")]) == 100.0:
            print "INFO: %s removing point %s with expULMinus1Sig == expULMinus2Sig == 0 and expULPlus1Sig == expULPlus2Sig == 100" % (filename, key)
            continue

        if selectpar == "expectedUpperLimit" and float(d[allpar.index("upperLimit")]) == 0.0:
            print "INFO: %s removing obsUL=0.0 for %s" % (filename, key)
            continue

        # throw away points with CLsexp > 0.99 and UL < 1.0 and CLs=-1 and UL<1 when merging on UL                      
        CLsExp = float( d[allpar.index("CLsexp")])
        if selectpar == "expectedUpperLimit" and pval < 1.0 and (CLsExp>0.99 or CLsExp<0) and float( d[allpar.index("upperLimit")])<1:                   
            if CLsExp>0.99: print "INFO: %s replacing CLsexp with 0.01 since UL < 1.0  and CLsexp=1 for %s" % (filename, key)
            elif CLsExp<0: print "INFO: %s replacing CLsexp with 0.01 since UL < 1.0  and CLsexp=-1 for %s" % (filename, key)
            d[allpar.index("CLsexp")] = str(0.01)
            d[allpar.index("CLs")] = str(0.01)
            d[allpar.index("clsu1s")] = str(0.01)
            d[allpar.index("clsd1s")] = str(0.01)
            d[allpar.index("p1")] = str(0.01)

        data[key] = d
def main():
    options = parseCmdLine(sys.argv)
    
    dummy,description = treedescription()
    allpar = description.split(':')

    xsecIdx = allpar.index('xsec')
    ULIdx   = allpar.index('upperLimit')
    if options.expected:
        ULIdx   = allpar.index('expectedUpperLimit')
    m0Idx   = allpar.index('m0')
    m12Idx  = allpar.index('m12')
    fIdIdx  = allpar.index('fID')
   
    p0Idx = allpar.index('p0')
    p1Idx = allpar.index('p1')
    CLsIdx = allpar.index('CLs')
    CLsexpIdx = allpar.index('CLsexp')

    covqualIdx = allpar.index('covqual')
    dodgycovIdx = allpar.index('dodgycov')
    failedcovIdx = allpar.index('failedcov')
    failedfitIdx = allpar.index('failedfit')
    failedp0Idx = allpar.index('failedp0')
    failedstatusIdx = allpar.index('failedstatus')
    fitstatusIdx = allpar.index('fitstatus')    

    #f = open(options.filename, "r")
    
    # get files to read 
    f = open("Outputs/%s_combined_fixSigXSecNominal__1_harvest_list_infoFile" % options.grid, "r")
    filenames = {}
    for l in f.readlines():
        (N, fname) = l.strip().split(":")
        filenames[int(N.strip())] = "Outputs/%s_%s_fixSigXSecNominal__1_harvest_list" % (options.grid, fname.strip())
    f.close()

    data = {}
    CLsdata = {}
    for N in filenames:
        f = open(filenames[N])
        for l in f.readlines():
            vals = l.strip().split(' ')
            key = "%d_%d" % (int(float(vals[m0Idx])), int(float(vals[m12Idx])))
            if key != options.point:
                continue
            
            data[N] = [float(vals[ULIdx]), float(vals[xsecIdx]), N]
            CLsdata[N] = [float(vals[p0Idx]), float(vals[p1Idx]), float(vals[CLsIdx]), float(vals[CLsexpIdx])]

        f.close()

    if options.seperate:
        print "# x\ty\tUL\txsec\tSR\tCLs"
    else:
        print "# x\ty\tUL*xsec\tSR"
    
    for N in sorted(data):
        (x, y) = options.point.split("_")
        x = int(x)
        y = int(y)

        if options.seperate:
            print "%d\t%d\t%f\t%f\t%d\t%.2f\t%.2f (exp)" % (x, y, data[N][0], data[N][1], data[N][2], CLsdata[N][2], CLsdata[N][3])
        else:
            print "%d\t%d\t%f\t%d" % (x, y, data[N][0] * data[N][1], data[N][2])

        covqual = int(float(vals[covqualIdx]))
        dodgycov = int(float(vals[dodgycovIdx]))
        failedcov = int(float(vals[failedcovIdx]))
        failedfit = int(float(vals[failedfitIdx]))
        failedp0 = int(float(vals[failedp0Idx]))
        failedstatus = int(float(vals[failedstatusIdx]))
        fitstatus = int(float(vals[fitstatusIdx]))

        # verbose print line to see what's going on with a point
        print "\t ==> covqual = %d, dodgycov = %d, failedcov = %d, failedfit = %d, failedp0 = %d, failedstatus = %d, fitstatus = %d" % (covqual, dodgycov, failedcov, failedfit, failedp0, failedstatus, fitstatus)

    return
Пример #10
0
def makeXsecData(options, data):
    dummy, description = treedescription()
    allpar = description.split(':')

    xsecdata = {}
    xsecs = readCrossSections(options)

    if data == {}:
        print "Your data array is empty! Exiting"
        sys.exit()

    for key in data:
        # extend here to par3 if needed
        (par1, par2) = (int(x) for x in key.split("_"))
        if not useThisPoint(options, par1, par2):
            print "Skipping %s" % key
            continue

        CLsexp = float(data[key][allpar.index("CLsexp")])
        upperLimit = float(data[key][allpar.index("upperLimit")])
        expectedUpperLimit = float(
            data[key][allpar.index("expectedUpperLimit")])

        expectedUpperLimitMinus1Sig = float(
            data[key][allpar.index("expectedUpperLimitMinus1Sig")])
        expectedUpperLimitPlus1Sig = float(
            data[key][allpar.index("expectedUpperLimitPlus1Sig")])

        expectedUpperLimitMinus2Sig = float(
            data[key][allpar.index("expectedUpperLimitMinus2Sig")])
        expectedUpperLimitPlus2Sig = float(
            data[key][allpar.index("expectedUpperLimitPlus2Sig")])

        fID = int(float(data[key][allpar.index("fID")]))

        #print "-1: %.3f, -2: %.3f" % (expectedUpperLimitMinus1Sig, expectedUpperLimitMinus2Sig)

        # TODO need to extract this plus uncertainty from SignalDB
        # NOTE: hardcoded for 1 proc, hence the extra [0]
        xsec = xsecs[key][0][0] * 1000
        xsecUp = (1 + xsecs[key][0][1]) * xsec
        xsecDown = (1 - xsecs[key][0][1]) * xsec

        print "%s: xsec=%.2e relunc=%.2e up=%.2e down=%.2e" % (
            key, xsec, xsecs[key][0][1], xsecUp, xsecDown)

        xsec2 = xsec / 2
        xsec4 = xsec / 4
        xsec8 = xsec / 8

        xsec2Up = xsecUp / 2
        xsec4Up = xsecUp / 4
        xsec8Up = xsecUp / 8

        xsec2Down = xsecDown / 2
        xsec4Down = xsecDown / 4
        xsec8Down = xsecDown / 8

        xsecdata[key] = {
            "upperLimit": upperLimit,
            "expectedUpperLimit": expectedUpperLimit,
            "expectedUpperLimitMinus1Sig": expectedUpperLimitMinus1Sig,
            "expectedUpperLimitPlus1Sig": expectedUpperLimitPlus1Sig,
            "expectedUpperLimitMinus2Sig": expectedUpperLimitMinus2Sig,
            "expectedUpperLimitPlus2Sig": expectedUpperLimitPlus2Sig,
            "xsec": xsec,
            "xsecUp": xsecUp,
            "xsecDown": xsecDown,
            "xsec2": xsec2,
            "xsec2Up": xsec2Up,
            "xsec2Down": xsec2Down,
            "xsec4Up": xsec4Up,
            "xsec4Down": xsec4Down,
            "xsec8Up": xsec8Up,
            "xsec8Down": xsec8Down,
            "xsec4": xsec4,
            "xsec8": xsec8,
            "fID": fID,
            "CLsexp": CLsexp
        }

    return xsecdata
def main():
    options = parseCmdLine(sys.argv)
    
    dummy,description = treedescription()
    allpar = description.split(':')

    if options.filename.find("Moriond13") != -1:
        # from HistFitter v24 source code
        description = "p0:p1:CLs:"
        description += "mode:nexp:"
        description += "seed:"
        description += "CLsexp:"
        description += "fID:sigma0:sigma1:"
        description += "clsu1s:clsd1s:clsu2s:clsd2s:"
        description += "upperLimit:upperLimitEstimatedError:expectedUpperLimit:expectedUpperLimitPlus1Sig:expectedUpperLimitPlus2Sig:expectedUpperLimitMinus1Sig:expectedUpperLimitMinus2Sig:xsec:excludedXsec:"
        description += "m0:m12"

        allpar = description.split(':')

    xsecIdx = allpar.index('xsec')
    ULIdx   = allpar.index('upperLimit')
    if options.expected:
        ULIdx   = allpar.index('expectedUpperLimit')
    
    if not "pMSSM" in options.filename: 
        m0Idx   = allpar.index('m0')
        m12Idx  = allpar.index('m12')
    else:
        m0Idx   = allpar.index('M1')
        m12Idx  = allpar.index('M2')
    
    fIdIdx  = allpar.index('fID')
   
    p0Idx = allpar.index('p0')
    p1Idx = allpar.index('p1')
    CLsIdx = allpar.index('CLs')
    CLsexpIdx = allpar.index('CLsexp')

    covqualIdx = allpar.index('covqual')
    dodgycovIdx = allpar.index('dodgycov')
    failedcovIdx = allpar.index('failedcov')
    failedfitIdx = allpar.index('failedfit')
    failedp0Idx = allpar.index('failedp0')
    failedstatusIdx = allpar.index('failedstatus')
    fitstatusIdx = allpar.index('fitstatus')    

    f = open(options.filename, "r")

    data = {}
    CLsdata = {}
    for l in f.readlines():
        vals = l.strip().split(' ')
        key = "%d_%d" % (int(float(vals[m0Idx])), int(float(vals[m12Idx])))
        data[key] = [float(vals[ULIdx]), float(vals[xsecIdx]), int(vals[fIdIdx])]
        CLsdata[key] = [float(vals[p0Idx]), float(vals[p1Idx]), float(vals[CLsIdx]), float(vals[CLsexpIdx])]

    if options.seperate:
        print "# x\ty\tUL\txsec\tSR\tCLs"
    elif options.hepdata:
        print makeHepDataHeader(options.filename)
    else:
        print "# x\ty\tUL*xsec\tSR"
    
    for key in sorted(data.iterkeys(), key=lambda a:map(int,a.split('_'))):
        (x, y) = key.split("_")
        x = int(x)
        y = int(y)

        ## HACK to filter e.g. rectangle (easier to isolate crashed points)
        #if not (x > 200 and x < 300): continue
        #if not (y > 100 and y < 200): continue

        #if not y == 0: continue

        if options.seperate:
            print "%d\t%d\t%f\t%f\t%d\t%e\t%e (exp)" % (x, y, data[key][0], data[key][1], data[key][2], CLsdata[key][2], CLsdata[key][3])
        elif options.hepdata:
            UL = data[key][0] * data[key][1]
            SR = GetSRName(data[key][2])
            print "%d; %d; %e; %s" % (x, y, UL, SR)
        else:
            print "%d\t%d\t%f\t%d" % (x, y, data[key][0] * data[key][1], data[key][2])

        covqual = int(float(vals[covqualIdx]))
        dodgycov = int(float(vals[dodgycovIdx]))
        failedcov = int(float(vals[failedcovIdx]))
        failedfit = int(float(vals[failedfitIdx]))
        failedp0 = int(float(vals[failedp0Idx]))
        failedstatus = int(float(vals[failedstatusIdx]))
        fitstatus = int(float(vals[fitstatusIdx]))

        # verbose print line to see what's going on with a point
        #print "\t ==> covqual = %d, dodgycov = %d, failedcov = %d, failedfit = %d, failedp0 = %d, failedstatus = %d, fitstatus = %d" % (covqual, dodgycov, failedcov, failedfit, failedp0, failedstatus, fitstatus)

    return
Пример #12
0
#!/usr/bin/env python
# usage :

#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%#
# Import Modules                                                             #
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%#
import sys, os, string, shutil, pickle, subprocess

import ROOT
ROOT.gROOT.Reset()
ROOT.gROOT.SetBatch(True)

#=========================================================================

from summary_harvest_tree_description import treedescription
dummy, description = treedescription()
allpar = description.split(':')
print dummy, description

myMap = {}
selectpar = "CLsexp"
par1 = "m0"
par2 = "m12"
xsecs = ["Nominal", "Up", "Down"]
regions = [
    "SRAmedium", "SRBmedium", "SRCloose", "SRCmedium", "SREloose", "SREmedium"
]
#regions = ["SRCmedium"]

for xsec in xsecs:
    myMap = {}
def Oring(config):
    # print which SRs you have to put in GetSRName.C
    for indx,ana in enumerate(config.anaList):
        print indx, ana
        pass;

    import sys, os, string, shutil, pickle, subprocess    
    import ROOT

    from summary_harvest_tree_description import treedescription
    dummy,description = treedescription()
    allpar = description.split(':')
    print allpar;

    ROOT.gROOT.Reset()
    ROOT.gROOT.SetBatch(True)

    # For all xsecs, merge on best selectpar (normally expected CLs)
    for xsecStr in allXS:
        myMap = {}
        myNomMap = {}
        myChosenAna = {}
        # skip when xsec != Nominal in discovery mode
        if config.discovery and xsecStr != "Nominal":
            continue;

        # if no UL's available, merge on CLsexp. Otherwise, use expectedUpperLimit
        # you should use CLsexp even if it's for observed limit because it can be bias?
        selectpar = "CLsexp"
        #selectpar = "CLs" 

        if config.makeUL and xsecStr == "Nominal": # ULs only available for Nominal
            selectpar = "expectedUpperLimit"
            pass;

        # select best SR based on p0exp    
        if config.discovery:
            selectpar = "p0exp"
            pass;

        print "Using selectpar = %s" % selectpar

        # default
        par1_s = "m0"
        par2_s = "m12"
        par3_s = ""
        listSuffix = "__1_harvest_list"

        # modifification depending on signal grid
        if config.grid.find("GG_onestepCC")!=-1:
            print "Ordering GG_onestepCC"
            par1_s = "mgluino"
            par2_s = "mchargino"
            par3_s = "mlsp"
            listSuffix = "__mlspNE60_harvest_list"
            pass;
        if config.grid.find("SS_onestepCC")!=-1:
            print "Ordering SS_onestepCC"
            par1_s = "msquark"
            par2_s = "mchargino"
            par3_s = "mlsp"
            listSuffix = "__mlspNE60_harvest_list"
            pass;
        if config.grid.find("SM_GG_N2")!=-1 :
            print "Ordering SM_GG_N2"
            par1_s = "mgluino"
            par2_s = "mlsp2"
            par3_s = "mlsp"
            pass;
        if config.grid.find("GG_onestep_mlsp60")!=-1:
            print "Ordering GG_onestep_mlsp60"
            par1_s = "mgluino"
            par2_s = "mchargino"
            par3_s = "mlsp"
            listSuffix = "__mlspEE60_harvest_list"
            pass;


        if config.discovery:
            listSuffix = "_discovery_1_harvest_list"
            pass;
            
        infoFilename = config.outputDir+config.outputName+"_combined_fixSigXSec"+xsecStr+listSuffix+"_infoFile"
        file_info = open(infoFilename,"w")
     
        # loop over ana (SRs)
        print " Oring :",config.anaList;
        for indx,ana in enumerate(config.anaList):

            filename = config.outputDir+config.outputName+"_"+ana+"_fixSigXSec"+xsecStr+listSuffix
            print filename
            nomfilename = config.outputDir+config.outputName+"_"+ana+"_fixSigXSecNominal"+listSuffix
            print nomfilename
            infoline="%i : %s\n"%(indx+1,ana)
            file_info.write(infoline)
            if not os.path.exists(filename):
                print "file does not exist -> skip"
                continue;
            
            infile = open(filename,'r')
            infilelines = infile.readlines()
            nomfile = open(nomfilename,'r')
            nomfilelines = nomfile.readlines()

            for i, line in enumerate(nomfilelines):
                vals = line.strip().split(' ')
                if len(allpar) != len(vals): 
                    print 'PRB!!!!!!!!!!!!!!!!!!!!'
                    print "summary file says %d components; file has %d per line" % (len(allpar),len(vals))
                    continue;
                
                vals[allpar.index("fID/C")]=(indx+1)
 
                pval = float( vals[allpar.index(selectpar+"/F")])
                par1 = float( vals[allpar.index(par1_s+"/F")])
                par2 = float( vals[allpar.index(par2_s+"/F")])
                key = "%d_%d" % (par1, par2)

                if config.grid.find("GG_onestepCC")!=-1: 
                    par3 = float( vals[allpar.index(par3_s+"/F")])
                    key += "_%d" % par3
                    pass;
                if config.grid.find("SS_onestepCC")!=-1: 
                    par3 = float( vals[allpar.index(par3_s+"/F")])
                    key += "_%d" % par3
                    pass;
                if config.grid.find("SM_GG_N2")!=-1: 
                    par3 = float( vals[allpar.index(par3_s+"/F")])
                    key += "_%d" % par3
                    pass;
                if config.grid.find("GG_onestep_mlsp60")!=-1: 
                    par3 = float( vals[allpar.index(par3_s+"/F")])
                    key += "_%d" % par3
                    pass;
           
                #print "DEBUG: %s selectpar=%.2e for %s" % (ana, pval, key)
                # ignore negative pvalue
                if pval < 0:
                    print "INFO: %s removing negative selectpar (%s = %.2e) for %s" % (ana, selectpar, pval, key)
                    continue;
                # ignore expectedUpperLimit < 0.00001 
                if selectpar == "expectedUpperLimit" and pval < 0.00001:
                    print "INFO: %s removing %s < 0.00001 for %s" % (ana, selectpar, key)
                    continue;
                # 110 is 20 times our default step -> this is almost certainly a bug
                if selectpar == "expectedUpperLimit" and pval == 110.0:
                    print "INFO: %s removing expUL==110.0 for %s" % (ana, key)
                    continue;
                # if -1sig, -2sig == 0 and +1sig, 2sig == 100 -> almost certainly a bug too
                if selectpar == "expectedUpperLimit" and float(vals[allpar.index("expectedUpperLimitMinus1Sig")]) == 0.0 and float(vals[allpar.index("expectedUpperLimitMinus2Sig")]) == 0.0 and float(vals[allpar.index("expectedUpperLimitPlus1Sig")]) == 100.0 and float(vals[allpar.index("expectedUpperLimitPlus2Sig")]) == 100.0:
                    print "INFO: %s removing point %s with expULMinus1Sig == expULMinus2Sig == 0 and expULPlus1Sig == expULPlus2Sig == 100" % (ana, key)
                    continue;
                # ignore observed upperLimit=0 when merging on UL
                if selectpar == "expectedUpperLimit" and float(vals[allpar.index("upperLimit")]) == 0.0:
                    print "INFO: %s removing obsUL=0.0 for %s" % (ana, key)
                    continue;

                # throw away points with CLsexp > 0.99 and UL < 1.0 and CLs=-1 and UL<1 when merging on UL                  
                CLsExp = float( vals[allpar.index("CLsexp/F")])
                if selectpar == "expectedUpperLimit" and pval < 1.0 and (CLsExp>0.99 or CLsExp<0) and float( vals[allpar.index("upperLimit")])<1:                   
                    if CLsExp>0.99: print "INFO: %s replacing CLsexp with 0.01 since UL < 1.0  and CLsexp=1 for %s" % (ana, key)
                    elif CLsExp<0: print "INFO: %s replacing CLsexp with 0.01 since UL < 1.0  and CLsexp=-1 for %s" % (ana, key)
                    vals[allpar.index("CLsexp/F")] = str(0.01)
                    vals[allpar.index("CLs/F")] = str(0.01)
                    vals[allpar.index("clsu1s/F")] = str(0.01)
                    vals[allpar.index("clsd1s/F")] = str(0.01)
                    vals[allpar.index("p1/F")] = str(0.01)

                    pass;
                 
                newline=""
                #print vals;
                for val in vals:
                    newline += (str)(val)+" "
                    pass;
                newline = newline.rstrip(" ")
                newline += "\n"

                # float strings -> so make them float, then an int to throw away .0000 and then to bool
                failedcov =  bool(int(float(vals[allpar.index("failedcov/F")])))  # Mediocre cov matrix quality
                covqual = int(float(vals[allpar.index("covqual/F")]))             # covqual
                failedfit = bool(int(float(vals[allpar.index("failedfit/F")])))   # Fit failure
                failedp0 = bool(int(float(vals[allpar.index("failedp0/F")])))     # Base p0 ~ 0.5 (this can reject good fits)!
                fitstatus = bool(int(float(vals[allpar.index("fitstatus/F")])))   # Fit status from Minuit
                nofit = bool(int(float(vals[allpar.index("nofit/F")])))           # Whether there's a fit present
                # ignore some checker
                """
                # ignore failed fit
                if failedfit:
                    print "INFO: %s removing failedfit=true for %s" % (ana, key)
                    continue
                # ignore bad mediocre cov matrix quality
                if failedcov:
                    print "INFO: %s removing failedcov=true for %s" % (ana, key)
                # ignore if covqual<3 & covqual!=-1
                if covqual < 3 and covqual != -1:
                    print "INFO: %s removing check if (covqual<3 and covqual!=-1) for %s (found covqual=%d)" % (ana, key, covqual)
                    continue
                """
    
                key = (par1,par2)
                if config.grid.find("GG_onestepCC")!=-1: 
                    key = (par1,par2,par3)
                    pass;
                if config.grid.find("SS_onestepCC")!=-1: 
                    key = (par1,par2,par3)
                    pass;
                if config.grid.find("SM_GG_N2")!=-1: 
                    key = (par1,par2,par3)
                    pass;
                if config.grid.find("GG_onestep_mlsp60")!=-1: 
                    key = (par1,par2,par3)
                    pass;
                
                if key not in myNomMap.keys():
                    myNomMap[key] = [pval,newline]
                    myChosenAna[key] = ana
                else:
                    if pval < myNomMap[key][0] and pval>=0 and (key != (1000.0, 500.0) or ana != "SRJigsawSRS2a"):
                        print "DEBUG: %s found new best value - selectpar=%.2e < previous=%e for %s" % (ana, pval, myNomMap[key][0], key)
                        myNomMap[key][0] = pval
                        myNomMap[key][1] = newline
                        myChosenAna[key] = ana
                        pass;
                    pass;
                pass;
            nomfile.close()

            for i, line in enumerate(infilelines):
                vals = line.strip().split(' ')
                if len(allpar) != len(vals): 
                    print 'PRB!!!!!!!!!!!!!!!!!!!!'
                    print "summary file says %d components; file has %d per line" % (len(allpar),len(vals))
                    continue;
                
                vals[allpar.index("fID/C")]=(indx+1)
 
                pval = float( vals[allpar.index(selectpar+"/F")])
                par1 = float( vals[allpar.index(par1_s+"/F")])
                par2 = float( vals[allpar.index(par2_s+"/F")])
                key = "%d_%d" % (par1, par2)

                if config.grid.find("GG_onestepCC")!=-1: 
                    par3 = float( vals[allpar.index(par3_s+"/F")])
                    key += "_%d" % par3
                    pass;
                if config.grid.find("SS_onestepCC")!=-1: 
                    par3 = float( vals[allpar.index(par3_s+"/F")])
                    key += "_%d" % par3
                    pass;
                if config.grid.find("SM_GG_N2")!=-1: 
                    par3 = float( vals[allpar.index(par3_s+"/F")])
                    key += "_%d" % par3
                    pass;
                if config.grid.find("GG_onestep_mlsp60")!=-1: 
                    par3 = float( vals[allpar.index(par3_s+"/F")])
                    key += "_%d" % par3
                    pass;
           
                #print "DEBUG: %s selectpar=%.2e for %s" % (ana, pval, key)
                # ignore negative pvalue
                if pval < 0:
                    print "INFO: %s removing negative selectpar (%s = %.2e) for %s" % (ana, selectpar, pval, key)
                    continue;
                # ignore expectedUpperLimit < 0.00001 
                if selectpar == "expectedUpperLimit" and pval < 0.00001:
                    print "INFO: %s removing %s < 0.00001 for %s" % (ana, selectpar, key)
                    continue;
                # 110 is 20 times our default step -> this is almost certainly a bug
                if selectpar == "expectedUpperLimit" and pval == 110.0:
                    print "INFO: %s removing expUL==110.0 for %s" % (ana, key)
                    continue;
                # if -1sig, -2sig == 0 and +1sig, 2sig == 100 -> almost certainly a bug too
                if selectpar == "expectedUpperLimit" and float(vals[allpar.index("expectedUpperLimitMinus1Sig")]) == 0.0 and float(vals[allpar.index("expectedUpperLimitMinus2Sig")]) == 0.0 and float(vals[allpar.index("expectedUpperLimitPlus1Sig")]) == 100.0 and float(vals[allpar.index("expectedUpperLimitPlus2Sig")]) == 100.0:
                    print "INFO: %s removing point %s with expULMinus1Sig == expULMinus2Sig == 0 and expULPlus1Sig == expULPlus2Sig == 100" % (ana, key)
                    continue;
                # ignore observed upperLimit=0 when merging on UL
                if selectpar == "expectedUpperLimit" and float(vals[allpar.index("upperLimit")]) == 0.0:
                    print "INFO: %s removing obsUL=0.0 for %s" % (ana, key)
                    continue;

                # throw away points with CLsexp > 0.99 and UL < 1.0 and CLs=-1 and UL<1 when merging on UL                  
                CLsExp = float( vals[allpar.index("CLsexp/F")])
                if selectpar == "expectedUpperLimit" and pval < 1.0 and (CLsExp>0.99 or CLsExp<0) and float( vals[allpar.index("upperLimit")])<1:                   
                    if CLsExp>0.99: print "INFO: %s replacing CLsexp with 0.01 since UL < 1.0  and CLsexp=1 for %s" % (ana, key)
                    elif CLsExp<0: print "INFO: %s replacing CLsexp with 0.01 since UL < 1.0  and CLsexp=-1 for %s" % (ana, key)
                    vals[allpar.index("CLsexp/F")] = str(0.01)
                    vals[allpar.index("CLs/F")] = str(0.01)
                    vals[allpar.index("clsu1s/F")] = str(0.01)
                    vals[allpar.index("clsd1s/F")] = str(0.01)
                    vals[allpar.index("p1/F")] = str(0.01)

                    pass;
                 
                newline=""
                #print vals;
                for val in vals:
                    newline += (str)(val)+" "
                    pass;
                newline = newline.rstrip(" ")
                newline += "\n"

                # float strings -> so make them float, then an int to throw away .0000 and then to bool
                failedcov =  bool(int(float(vals[allpar.index("failedcov/F")])))  # Mediocre cov matrix quality
                covqual = int(float(vals[allpar.index("covqual/F")]))             # covqual
                failedfit = bool(int(float(vals[allpar.index("failedfit/F")])))   # Fit failure
                failedp0 = bool(int(float(vals[allpar.index("failedp0/F")])))     # Base p0 ~ 0.5 (this can reject good fits)!
                fitstatus = bool(int(float(vals[allpar.index("fitstatus/F")])))   # Fit status from Minuit
                nofit = bool(int(float(vals[allpar.index("nofit/F")])))           # Whether there's a fit present
                # ignore some checker
                """
                # ignore failed fit
                if failedfit:
                    print "INFO: %s removing failedfit=true for %s" % (ana, key)
                    continue
                # ignore bad mediocre cov matrix quality
                if failedcov:
                    print "INFO: %s removing failedcov=true for %s" % (ana, key)
                # ignore if covqual<3 & covqual!=-1
                if covqual < 3 and covqual != -1:
                    print "INFO: %s removing check if (covqual<3 and covqual!=-1) for %s (found covqual=%d)" % (ana, key, covqual)
                    continue
                """
    
                key = (par1,par2)
                if config.grid.find("GG_onestepCC")!=-1: 
                    key = (par1,par2,par3)
                    pass;
                if config.grid.find("SS_onestepCC")!=-1: 
                    key = (par1,par2,par3)
                    pass;
                if config.grid.find("SM_GG_N2")!=-1: 
                    key = (par1,par2,par3)
                    pass;
                if config.grid.find("GG_onestep_mlsp60")!=-1: 
                    key = (par1,par2,par3)
                    pass;
                if key in myChosenAna.keys():
                    if ana == myChosenAna[key]:
#                    print "DEBUG: %s found new best value - selectpar=%.2e < previous=%e for %s" % (ana, pval, myMap[key][0], key)
                        myMap[key]= [pval,newline]
                        pass;
                    pass;
                pass;
                # if key not in myMap.keys():
                #     myMap[key] = [pval,newline]
                # else:
                #     if pval < myMap[key][0] and pval>=0 and (key != (1000.0, 500.0) or ana != "SRJigsawSRS2a"):
                #         print "DEBUG: %s found new best value - selectpar=%.2e < previous=%e for %s" % (ana, pval, myMap[key][0], key)
                #         myMap[key][0] = pval
                #         myMap[key][1] = newline
                #         pass;
                #     pass;
                # pass;
            infile.close()