def execute(self, ws, debug = 0):
print self.legend, 'Profile Likelihood calculation started...'
# time the action
t = TStopwatch()
t.Start()
# model config is guaranteed to be here
# the action won't configure without it
# and this code will never run unless valid model config is found
mconf = ws.obj(self._model_config_name)
_poi = mconf.GetParametersOfInterest()
plcInt = self._plc.GetInterval()
# stop watch and print how long it took to get the interval
t.Print()
# iterate over all parameters of interest and print out the intervals
# (could there be more than one?)
_iter = _poi.createIterator()
while True:
_poi_name = _iter().GetTitle()
lower_limit = plcInt.LowerLimit( _poi[_poi_name] )
upper_limit = plcInt.UpperLimit( _poi[_poi_name] )
print self.legend, 'Profile Likelihood interval for', _poi_name, 'is ['+ \
str(lower_limit) + ', ' + \
str(upper_limit) + ']'
if _iter.Next() == None:
break
if self._scan_plot:
# draw scan plot
print self.legend, 'making the likelihood scan plot'
_plot_name = _poi_name+'_plc_scan_exost.'+self._plot_format
c1 = TCanvas("c1", "c1", 600, 600)
plcPlot = RooStats.LikelihoodIntervalPlot(plcInt)
gROOT.SetStyle("Plain")
plcPlot.Draw()
c1.SaveAs(_plot_name)
return (lower_limit, upper_limit)
def execute(self, ws, debug=0):
print self.legend, 'Feldman-Cousins calculation started...'
# time the action
t = TStopwatch()
t.Start()
# model config is guaranteed to be here
# the action won't configure without it
# and this code will never run unless valid model config is found
mconf = ws.obj(self._model_config_name)
_poi = mconf.GetParametersOfInterest()
fcInt = self._fc.GetInterval()
# stop watch and print how long it took to get the interval
t.Print()
# iterate over all parameters of interest and print out the intervals
# (could there be more than one?)
_iter = _poi.createIterator()
while True:
_poi_name = _iter().GetTitle()
lower_limit = fcInt.LowerLimit(_poi[_poi_name])
upper_limit = fcInt.UpperLimit(_poi[_poi_name])
print self.legend, 'Feldman-Cousins interval for', _poi_name, 'is ['+ \
str(lower_limit) + ', ' + \
str(upper_limit) + ']'
if _iter.Next() == None:
break
return (lower_limit, upper_limit)
help='turn on extra debugging information')
(opts, args) = parser.parse_args()
import pyroot_logon
#import HWW2DConfig
config = __import__(opts.modeConfig)
import RooWjj2DFitter
from ROOT import TCanvas, RooFit, RooLinkedListIter, TMath, RooRandom, TFile, \
RooDataHist, RooMsgService, TStopwatch
import pulls
timer = TStopwatch()
timer.Start()
if not opts.debug:
RooMsgService.instance().setGlobalKillBelow(RooFit.WARNING)
if hasattr(opts, "seed") and (opts.seed >= 0):
print "random seed:", opts.seed
RooRandom.randomGenerator().SetSeed(opts.seed)
pars = config.theConfig(Nj=opts.Nj,
mH=opts.mH,
isElectron=opts.isElectron,
initFile=args,
includeSignal=opts.includeSignal)
fitter = RooWjj2DFitter.Wjj2DFitter(pars)
def main():
try:
# Retrive command line options
shortopts = "m:i:t:o:vh?"
longopts = [
"methods=", "inputfile=", "inputtrees=", "outputfile=", "verbose",
"help", "usage"
]
opts, args = getopt.getopt(sys.argv[1:], shortopts, longopts)
except getopt.GetoptError:
# Print help information and exit:
print "ERROR: unknown options in argument %s" % sys.argv[1:]
usage()
sys.exit(1)
infname = DEFAULT_INFNAME
treeNameSig = DEFAULT_TREESIG
treeNameBkg = DEFAULT_TREEBKG
outfname = DEFAULT_OUTFNAME
methods = DEFAULT_METHODS
verbose = False
for o, a in opts:
if o in ("-?", "-h", "--help", "--usage"):
usage()
sys.exit(0)
elif o in ("-m", "--methods"):
methods = a
elif o in ("-i", "--inputfile"):
infname = a
elif o in ("-o", "--outputfile"):
outfname = a
elif o in ("-t", "--inputtrees"):
a.strip()
trees = a.rsplit(' ')
trees.sort()
trees.reverse()
if len(trees) - trees.count('') != 2:
print "ERROR: need to give two trees (each one for signal and background)"
print trees
sys.exit(1)
treeNameSig = trees[0]
treeNameBkg = trees[1]
elif o in ("-v", "--verbose"):
verbose = True
# Print methods
mlist = methods.replace(' ', ',').split(',')
print "=== TMVApplication: use method(s)..."
for m in mlist:
if m.strip() != '':
print "=== - <%s>" % m.strip()
# Import ROOT classes
from ROOT import gSystem, gROOT, gApplication, TFile, TTree, TCut, TH1F, TStopwatch
# check ROOT version, give alarm if 5.18
if gROOT.GetVersionCode() >= 332288 and gROOT.GetVersionCode() < 332544:
print "*** You are running ROOT version 5.18, which has problems in PyROOT such that TMVA"
print "*** does not run properly (function calls with enums in the argument are ignored)."
print "*** Solution: either use CINT or a C++ compiled version (see TMVA/macros or TMVA/examples),"
print "*** or use another ROOT version (e.g., ROOT 5.19)."
sys.exit(1)
# Logon not automatically loaded through PyROOT (logon loads TMVA library) load also GUI
gROOT.SetMacroPath("../macros/")
gROOT.Macro("../macros/TMVAlogon.C")
# Import TMVA classes from ROOT
from ROOT import TMVA
# Create the Reader object
reader = TMVA.Reader("!Color")
# Create a set of variables and declare them to the reader
# - the variable names must corresponds in name and type to
# those given in the weight file(s) that you use
# what to do ???
var1 = array('f', [0])
var2 = array('f', [0])
var3 = array('f', [0])
var4 = array('f', [0])
reader.AddVariable("var1+var2", var1)
reader.AddVariable("var1-var2", var2)
reader.AddVariable("var3", var3)
reader.AddVariable("var4", var4)
# book the MVA methods
dir = "weights/"
prefix = "TMVAnalysis_"
for m in mlist:
reader.BookMVA(m + " method", dir + prefix + m + ".weights.txt")
#######################################################################
# For an example how to apply your own plugin method, please see
# TMVA/macros/TMVApplication.C
#######################################################################
# Book output histograms
nbin = 80
histList = []
for m in mlist:
histList.append(TH1F(m, m, nbin, -3, 3))
# Book example histogram for probability (the other methods would be done similarly)
if "Fisher" in mlist:
probHistFi = TH1F("PROBA_MVA_Fisher", "PROBA_MVA_Fisher", nbin, 0, 1)
rarityHistFi = TH1F("RARITY_MVA_Fisher", "RARITY_MVA_Fisher", nbin, 0,
1)
# Prepare input tree (this must be replaced by your data source)
# in this example, there is a toy tree with signal and one with background events
# we'll later on use only the "signal" events for the test in this example.
#
fname = "./tmva_example.root"
print "--- Accessing data file: %s" % fname
input = TFile.Open(fname)
if not input:
print "ERROR: could not open data file: %s" % fname
sys.exit(1)
#
# Prepare the analysis tree
# - here the variable names have to corresponds to your tree
# - you can use the same variables as above which is slightly faster,
# but of course you can use different ones and copy the values inside the event loop
#
print "--- Select signal sample"
theTree = input.Get("TreeS")
userVar1 = array('f', [0])
userVar2 = array('f', [0])
theTree.SetBranchAddress("var1", userVar1)
theTree.SetBranchAddress("var2", userVar2)
theTree.SetBranchAddress("var3", var3)
theTree.SetBranchAddress("var4", var4)
# Efficiency calculator for cut method
nSelCuts = 0
effS = 0.7
# Process the events
print "--- Processing: %i events" % theTree.GetEntries()
sw = TStopwatch()
sw.Start()
for ievt in range(theTree.GetEntries()):
if ievt % 1000 == 0:
print "--- ... Processing event: %i" % ievt
# Fill event in memory
theTree.GetEntry(ievt)
# Compute MVA input variables
var1[0] = userVar1[0] + userVar2[0]
var2[0] = userVar1[0] - userVar2[0]
# Return the MVAs and fill to histograms
if "CutsGA" in mlist:
passed = reader.EvaluateMVA("CutsGA method", effS)
if passed:
nSelCuts = nSelCuts + 1
# Fill histograms with MVA outputs
for h in histList:
h.Fill(reader.EvaluateMVA(h.GetName() + " method"))
# Retrieve probability instead of MVA output
if "Fisher" in mlist:
probHistFi.Fill(reader.GetProba("Fisher method"))
rarityHistFi.Fill(reader.GetRarity("Fisher method"))
# Get elapsed time
sw.Stop()
print "--- End of event loop: %s" % sw.Print()
# Return computed efficeincies
if "CutsGA" in mlist:
eff = float(nSelCuts) / theTree.GetEntries()
deff = math.sqrt(eff * (1.0 - eff) / theTree.GetEntries())
print "--- Signal efficiency for Cuts method : %.5g +- %.5g (required was: %.5g)" % (
eff, deff, effS)
# Test: retrieve cuts for particular signal efficiency
mcuts = reader.FindMVA("CutsGA method")
cutsMin = array('d', [0, 0, 0, 0])
cutsMax = array('d', [0, 0, 0, 0])
mcuts.GetCuts(0.7, cutsMin, cutsMax)
print "--- -------------------------------------------------------------"
print "--- Retrieve cut values for signal efficiency of 0.7 from Reader"
for ivar in range(4):
print "... Cut: %.5g < %s <= %.5g" % (
cutsMin[ivar], reader.GetVarName(ivar), cutsMax[ivar])
print "--- -------------------------------------------------------------"
#
# write histograms
#
target = TFile("TMVApp.root", "RECREATE")
for h in histList:
h.Write()
# Write also probability hists
if "Fisher" in mlist:
probHistFi.Write()
rarityHistFi.Write()
target.Close()
print "--- Created root file: \"TMVApp.root\" containing the MVA output histograms"
print "==> TMVApplication is done!"
def inv1(x, b1): return tan(3*x*b1 + atan(a))
def inv2(x, b2): return rt*(-a*exp(x*b2/d) - a - rt*exp(x*b2/d) + rt)/(-a*exp(x*b2/d) + a - rt*exp(x*b2/d) -rt)
print('Inv1: ', inv1(0, b1))
print('Inv2: ', inv2(0, b2))
def fncomposition(a, b, a1, a2, b1, b2):
while (True):
nr = gRandom.Uniform(0,1)
nk = gRandom.Uniform(0,1)
if nk < a1:
return inv1(nr, b1)
else:
return inv2(nr, b2)
c2 = ROOT.TCanvas("myCanvasName2","The Canvas Title", 1200, 500)
h2 = TH1F("h2", "composition method", 50, -1, 1)
sw = TStopwatch()
sw.Start()
for i in range(0, 10000):
r = fncomposition(a, b, a1, a2, b1, b2)
h2.Fill(r)
sw.Stop()
sw.Print()
h2.Draw()
h2.Fit(ff)
c2.Draw()
print('First moment: ', h2.GetMean())
print('Mean square: ', h2.GetStdDev())
minnumberofsteps, maxnumberofsteps)
Integ_Midpoint.SetLineColor(kBlue)
Integ_Midpoint.SetLineWidth(6)
Integ_Err_Midpoint = TH1F("Integ_Err_Midpoint", "Integ_Err_Midpoint",
maxnumberofsteps, minnumberofsteps, maxnumberofsteps)
Integ_Err_Midpoint.SetLineColor(kBlue)
Integ_Err_Midpoint.SetLineWidth(3)
timer_1 = TStopwatch()
timer_Cpu_Midpoint = 0.0
Midpoint_stops_at_n = 0.0
old_integration_value = 0.0
first_time_flag = 0
for x in range(minnumberofsteps, maxnumberofsteps + 1):
timer_1.Start()
Integ_Midpoint.SetBinContent(x, MidPointIntegral(
a, b, x,
func)) # Set the value of the integral as a function of the steps x
y = old_integration_value - 1.0 * MidPointIntegral(
a, b, x, func) # Calculate Delta I
y = 1.0 * abs(y) / MidPointIntegral(a, b, x, func) # Calculate Delta I/I
Integ_Err_Midpoint.SetBinContent(
x, y) # Set the Error histogram equal to Delta I / I
old_integration_value = MidPointIntegral(
a, b, x, func) # Store the "old" integration value
timer_1.Stop()
timer_Cpu_Midpoint = timer_Cpu_Midpoint + timer_1.CpuTime()
#timer_Real_Midpoint = timer_Real_Midpoint + timer_1.RealTime()
timer_Midpoint.SetBinContent(x, timer_Cpu_Midpoint)
chainName = "OSUAnalysis/" + BNTreeChannel + "/BNTree_" + BNTreeChannel
command = "root -l -b -q '" + BNTreeScript + "+(\"" + condor_dir + "\",\"" + dataset + "\",\"" + chainName + "\"," + str(
arguments.condorProcessNum) + ")'"
print "About to execute command: " + command
os.system(command)
else:
for hist in input_histograms:
#chain trees together
ch = TChain("OSUAnalysis/" + hist['channel'] + "/BNTree_" +
hist['channel'])
ch.Add(condor_dir + "/" + dataset + "/hist_*.root")
print("Looping over chain with # entries = %f; split time = " %
ch.GetEntries()),
watch1.Stop()
watch1.Print()
watch1.Start()
outputFile = TFile(condor_dir + "/" + dataset + ".root",
"UPDATE")
if not outputFile or outputFile.IsZombie():
print "Could not open file: %s/%s.root" % (condor_dir,
dataset)
outputFile.cd("OSUAnalysis/" + hist['channel'])
deleteString = hist[
'histName'] + ";*" # delete all existing instances of the object
currentDir = outputFile.GetDirectory("OSUAnalysis/" +
hist['channel'])
if not currentDir:
print "Could not find directory OSUAnalysis/%s in file %s" % (
hist['channel'], outputFile.GetName())
def submitArrayToBatch(self, scripts, arrayscriptpath, jobid=None):
'''
submits given scripts as array to batch system
scripts: scripts to be submitted as array
arrayscriptpath: path to generated array file
jobid: newly created array job waits for the jobs given in jobid (as a list of ids) before executing
returns jobid of array as list
'''
submitclock = TStopwatch()
submitclock.Start()
arrayscriptpath = os.path.abspath(arrayscriptpath)
logdir = os.path.dirname(arrayscriptpath) + "/logs"
print "will save logs in", logdir
# if os.path.exists(logdir):
# print "emptying directory", logdir
# shutil.rmtree(logdir)
# os.makedirs(logdir)
if not os.path.exists(logdir):
os.makedirs(logdir)
# write array script
nscripts = len(scripts)
tasknumberstring = '1-' + str(nscripts)
arrayscriptpath = self.writeArrayCode(scripts=scripts,
arrayPath=arrayscriptpath,
logdir=logdir)
# prepate submit
if self.jobmode == "HTC":
print 'writing code for condor_submit-script'
hold = True if jobid else False
submitPath = self.writeSubmitCode(arrayscriptpath,
logdir,
hold=hold,
isArray=True,
nscripts=nscripts)
print 'submitting', submitPath
command = self.subname + " -terse " + submitPath
command = command.split()
else:
print 'submitting', arrayscriptpath
command = self.construct_array_submit()
if not command:
print "could not generate array submit command"
return
command.append('-t')
command.append(tasknumberstring)
if jobid:
command.append("-hold_jid")
command.append(str(jobid))
command.append(arrayscriptpath)
# submitting
print "command:", command
a = subprocess.Popen(command,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
stdin=subprocess.PIPE)
output = a.communicate()[0]
jobidstring = output
if len(jobidstring) < 2:
sys.exit("something did not work with submitting the array job")
# extracting jobid
try:
jobidint = int(output.split(".")[0])
except:
sys.exit(
"something went wrong with calling condor_submit command, submission of jobs was not succesfull"
)
submittime = submitclock.RealTime()
print "submitted job", jobidint, " in ", submittime
if hold:
self.setupRelease(jobid, jobidint)
return [jobidint]