def TH1_to_TH2_Convert(filename, outputpath=''):
FILELIST = read_file_name(filename)
fn = FILELIST[0]; print(fn)
histo_name_list = GetHistoNameList(filename); print(histo_name_list)
# print(BranchName(histo_name_list[0]))
# print Exclued_BranchName(histo_name_list[0])
indicator = 0
histList = []
f = TFile(filename,"READ")
dirlist = f.GetListOfKeys()
ITER = dirlist.MakeIterator()
key = ITER.Next(); #print(key.GetName())
while key:
dirlistb = f.GetListOfKeys()
ITERb = dirlistb.MakeIterator()
keyb = ITERb.Next()
ijk = 0
while keyb:
if(Exclued_BranchName(key.GetName()) == Exclued_BranchName(keyb.GetName())):
if(key.GetName() != keyb.GetName()):
Name2DHist = Exclued_BranchName(key.GetName()) + "Y_" + BranchName(key.GetName()) + "_X_" + BranchName(keyb.GetName())
# hist = TH2D
print(Name2DHist)
indicator = indicator + 1
keyb = ITERb.Next()
key = ITER.Next()
print(indicator)
def Open(path):
from ROOT import TFile
f = TFile(path, 'read')
if len(f.GetListOfKeys()) > 0:
run_numbers = [key.GetName() for key in f.GetListOfKeys()]
return f, run_numbers
else:
return f, None
def add_signal(fname, process, signal_file, signal, scale):
print 'adding signal', signal, ' with cross section', scale, 'to', process
print 'working file', fname, 'signal file', signal_file
signal_file = TFile(signal_file, 'READ')
work_file = TFile(fname, 'UPDATE')
keys = work_file.GetListOfKeys()
signal_keys = signal_file.GetListOfKeys()
original = []
for key in keys:
key = str(key.GetName())
if len(key.split('__')) > 3: continue
category = key.split("__")[0]
#print key, category
if '*' in process:
process_split = process.split('*')
if not all(part in key for part in process_split): continue
#print 'matched',process,'with',key
elif process not in key:
continue
for signal_key in signal_keys:
signal_key = str(signal_key.GetName())
#print 'comparing',key, signal_key
sig_cat = signal_key.split("__")[0]
#print signal, signal_key.split('__')[1]
if signal.replace('-',
'_') not in signal_key.split("__")[1].replace(
'-', '_'):
continue
#print category, sig_cat
if category == sig_cat:
print 'adding', signal_key, 'to', key
sig_hist = signal_file.Get(signal_key).Clone()
#original.append(work_file.Get(key).Clone(key))
#binning = get_binning(original[-1])
hist = work_file.Get(key).Clone(key)
work_file.Delete(key + ';*')
binning = get_binning(hist)
#print binning
if binning:
sig_hist = sig_hist.Rebin(
len(binning) - 1, key, array.array('d', binning))
sig_hist.Scale(scale)
#print 'adding',sig_hist.GetIntegral(), 'to', original[-1].GetIntegral()
#original[-1].Add(sig_hist)
hist.Add(sig_hist)
original.append(hist) #.Write('',TObject.kOverwrite)
break
signal_file.Close()
work_file.cd()
for item in original:
item.Write('') #,TObject.kOverwrite);
work_file.Close()
def Fill_histograms(FILENAME, BRANCHLISTALL, DICHISTLIST, BranchListEachTree):
gBenchmark.Start("Filling & Writing Histograms")
# print("!@#!@#!#",DICHISTLIST.keys())
# print("!@#!@#!",BRANCHLISTALL)
DicNumpyArray_branch = {}
for numpyarray in BRANCHLISTALL:
a = numpy.array([0], 'd')
DicNumpyArray_branch[numpyarray] = a
DicNumpyArray_branch = collections.OrderedDict(
sorted(DicNumpyArray_branch.items())
) # !!!the input times are ordered!!!
# print("!@#!@#!#",DicNumpyArray_branch)
f = TFile(FILENAME, "READ")
dirlist = f.GetListOfKeys()
ITER = dirlist.MakeIterator()
key = ITER.Next()
while key:
it = 0
tree = key.ReadObj()
# print("!@#!@#!#",DICHISTLIST[tree.GetName()])
for i in range(len(DicNumpyArray_branch)):
if (list(DicNumpyArray_branch.keys())[i]
in BranchListEachTree[tree.GetName()]):
it = it + 1
pass
else:
continue
tree.SetBranchAddress(
list(DicNumpyArray_branch.keys())[i],
list(DicNumpyArray_branch.values())[i])
if (it == 0):
continue
ENTRY = tree.GetEntries()
print("for tree", tree.GetName())
for i in range(ENTRY):
tree.GetEntry(i)
if (i % 1000 == 0):
print("now looping", i, "th Events, total of ", ENTRY,
"events")
# for j in range(len(DICHISTLIST[tree.GetName()])):
for j in range(len(DicNumpyArray_branch)):
for k in range(len(DICHISTLIST[tree.GetName()])):
if (list(DicNumpyArray_branch.keys())[j]
in DICHISTLIST[tree.GetName()][k].GetName()):
DICHISTLIST[tree.GetName()][k].Fill(
list(DicNumpyArray_branch.values())[j][0])
else:
continue
#DICHISTLIST[tree.GetName()][k].Scale(DicNumpyArray_branch["JWeight"][j][0])
key = ITER.Next()
# print(DICHISTLIST)
# gBenchmark.Show("filling")
f.Close()
return DICHISTLIST
def signal_rebin(rebin_file, signal="Bprime", process='DATA'):
#print 'starting the rebinning of',rebin_file
work_file = TFile(rebin_file, "UPDATE")
keys = work_file.GetListOfKeys()
hist_list = []
for key in keys:
key = str(key.GetName())
if process in key:
hist = work_file.Get(key)
binning = get_binning(hist)
for other in keys:
other = str(other.GetName())
if not key.split('__')[0] in other: continue
if not signal in other: continue
#if len(other.split('__'))>2:continue
if not process in other:
#print other
work_hist = work_file.Get(other)
hist_list.append(
work_hist.Rebin(
len(binning) - 1, other, array.array('d',
binning)))
#work_hist.Write('',TObject.kOverwrite)
for item in hist_list:
item.Write('', TObject.kOverwrite)
work_file.Close()
del hist_list
def sys_reweight(filename, weight=''):
work_file = TFile(filename, "UPDATE")
keys = work_file.GetListOfKeys()
nominal_hists = []
uncer_list = []
for key in keys:
key = str(key.GetName())
if 'DATA' in key or 'Data' in key or 'Background' in key or 'Signal' in key:
continue
if 'minus' in key or 'plus' in key:
uncer = key.split('__')[2]
if uncer not in uncer_list: uncer_list.append(uncer)
continue
if key not in nominal_hists:
nominal_hists.append(key)
for hist in nominal_hists:
#print hist
nominal_number = (work_file.Get(hist)).Integral()
for uncer in uncer_list:
if weight not in uncer: continue
up = work_file.Get(hist + '__' + uncer + '__plus')
down = work_file.Get(hist + '__' + uncer + '__minus')
#print 'scale plus:',nominal_number/up.Integral(),'minus',nominal_number/down.Integral()
up.Scale(nominal_number / up.Integral())
down.Scale(nominal_number / down.Integral())
up.Write('', TObject.kOverwrite)
down.Write('', TObject.kOverwrite)
work_file.Close()
del nominal_hists
def add_substraction_unc(filename, signal_file, signal, values):
work_file = TFile(filename, 'UPDATE')
signal_file = TFile(signal_file, 'READ')
signal_cross = values[0]
uncer = values[1]
hist_list = []
keys = work_file.GetListOfKeys()
for key in keys:
key = str(key.GetName())
if len(key.split('__')) > 2: continue
if not 'Background' in key: continue
category = key.split('__')[0]
hist_up = work_file.Get(key).Clone(key + '__signalSub__plus')
hist_down = work_file.Get(key).Clone(key + '__signalSub__minus')
signal_hist = signal_file.Get(category + '__' + signal).Clone()
binning = get_binning(hist_up)
if binning:
signal_hist = signal_hist.Rebin(
len(binning) - 1, key, array.array('d', binning))
signal_hist.Scale(uncer)
hist_up.Add(signal_hist)
hist_down.Add(signal_hist, -1)
hist_list.append(hist_up)
hist_list.append(hist_down)
work_file.cd()
for item in hist_list:
item.Write('', TObject.kOverwrite)
work_file.Close()
signal_file.Close()
print 'added signal substraction uncertainty to', filename
def invert_bin_content(in_file, process="", out_file="", factor=-1.):
if not out_file:
out_file = in_file.replace(".root", "_inverted.root")
work_file = TFile(in_file, 'READ')
keys = work_file.GetListOfKeys()
hist_list = []
for key in keys:
key = str(key.GetName())
if len(key.split('__')) == 2:
hist = work_file.Get(key).Clone(
key.split('__')[0] + '__' + process)
else:
sign = ''
if 'minus' in key.split('__')[3]: sign = 'plus'
else: sign = 'minus'
hist = work_file.Get(key).Clone(
key.split('__')[0] + '__' + process + '__' +
key.split('__')[2] + '__' + sign)
#hist = work_file.Get(key).Clone(key.split('__')[0]+'__'+process+'__'+key.split('__')[2]+'__'+key.split('__')[3])
for i in xrange(hist.GetNcells()):
hist.SetBinContent(i, factor * hist.GetBinContent(i))
hist_list.append(hist)
print out_file
output = TFile(out_file, 'RECREATE')
for item in hist_list:
item.Write('', TObject.kOverwrite)
output.Close()
work_file.Close()
return out_file
def GetNumberOfEvents(FilesSet):
NumberOfEvents = {'SkimNumber' : {}, 'TotalNumber' : 0}
for histFile in FilesSet:
ScoutFile = TFile(histFile)
if ScoutFile.IsZombie():
print histFile + " is a bad root file."
FilesSet.remove(histFile)
continue
randomChannelDirectory = ""
TotalNumberTmp = 0
for key in ScoutFile.GetListOfKeys():
if key.GetClassName() != "TDirectoryFile" or "CutFlow" not in key.GetName():
continue
randomChannelDirectory = key.GetName()
channelName = randomChannelDirectory[0:len(randomChannelDirectory)-14]
if not NumberOfEvents['SkimNumber'].has_key(channelName):
NumberOfEvents['SkimNumber'][channelName] = 0
OriginalCounterObj = ScoutFile.Get(randomChannelDirectory + "/eventCounter")
SkimCounterObj = ScoutFile.Get(randomChannelDirectory + "/cutFlow")
TotalNumberTmp = 0
if not OriginalCounterObj:
print "Could not find eventCounter histogram in " + str(histFile) + " !"
continue
elif not SkimCounterObj:
print "Could not find cutFlow histogram in " + str(histFile) + " !"
else:
OriginalCounter = OriginalCounterObj.Clone()
OriginalCounter.SetDirectory(0)
TotalNumberTmp = TotalNumberTmp + OriginalCounter.GetBinContent(1)
SkimCounter = SkimCounterObj.Clone()
SkimCounter.SetDirectory(0)
NumberOfEvents['SkimNumber'][channelName] = NumberOfEvents['SkimNumber'][channelName] + SkimCounter.GetBinContent(SkimCounter.GetXaxis().GetNbins())
NumberOfEvents['TotalNumber'] = NumberOfEvents['TotalNumber'] + TotalNumberTmp
return NumberOfEvents
def sculp_categories(filename, category=[]):
print 'working on', filename
work_file = TFile(filename, 'READ')
keys = work_file.GetListOfKeys()
out = []
if not category:
for key in keys:
key = str(key.GetName())
cat = key.split('__')[0]
cat = cat.replace('Ele', '')
cat = cat.replace('Mu', '')
if cat not in category:
category.append(cat)
print category
for cat in category:
hists = []
for key in keys:
key = str(key.GetName())
if cat not in key: continue
hists.append(work_file.Get(key).Clone())
out_name = filename.replace('.root', '_' + cat + '.root')
out.append(out_name)
output = TFile(out_name, 'RECREATE')
output.cd()
for i in hists:
i.Write()
output.Close()
work_file.Close()
return out
def create_significance_files(filename, signal):
print 'starting to create significance file from', filename
work_file = TFile(filename, 'READ')
keys = work_file.GetListOfKeys()
categories_done = []
hist_sig = []
hist_other = []
masses = []
for key in keys:
key = str(key.GetName())
if signal in key: hist_sig.append(work_file.Get(key).Clone())
else: hist_other.append(work_file.Get(key).Clone())
for h in hist_sig:
name = h.GetName()
name = name.replace('10p', '')
name = name.replace('20p', '')
name = name.replace('30p', '')
name = ''.join(x for x in name if x.isdigit())
masses.append(name)
output = TFile(
filename.replace('.root', name + '_' + signal + '.root'),
'RECREATE')
output.Cd()
h.Write()
for o in hist_other:
o.Write()
output.Close()
work_file.Close()
return masses
def load_trees_from_file(file_name):
"""
Load all TTree from a ROOT file
@param file_name Name of ROOT file
@return dict with name of tree as key and the tree as value, ROOT file
"""
if not os.path.isfile(file_name):
raise IOError("File %s does not exist." % file_name)
root_file = TFile(file_name)
if root_file.IsZombie():
raise IOError("Can't open root file %s." % file_name)
keys = root_file.GetListOfKeys()
trees = {}
for key in keys:
tree = root_file.Get(key.GetName())
if isinstance(tree, TTree):
trees[key.GetName()] = tree
return trees, root_file
def Fill_histograms(FILENAME, BRANCHLISTALL, DICHISTLIST):
DicNumpyArray_branch = {}
for numpyarray in BRANCHLISTALL:
a = numpy.array([0], 'd')
DicNumpyArray_branch[numpyarray] = a
f = TFile(FILENAME, "READ")
dirlist = f.GetListOfKeys()
ITER = dirlist.MakeIterator()
key = ITER.Next()
while key:
tree = key.ReadObj()
for i in range(len(DicNumpyArray_branch)):
tree.SetBranchAddress(DicNumpyArray_branch.keys()[i],
DicNumpyArray_branch.values()[i])
ENTRY = tree.GetEntries()
for i in range(ENTRY):
tree.GetEntry(i)
for j in range(len(DICHISTLIST[tree.GetName()])):
for k in range(len(DICHISTLIST[tree.GetName()])):
if (DicNumpyArray_branch.keys()[j]
in DICHISTLIST[tree.GetName()][k].GetName()):
DICHISTLIST[tree.GetName()][k].Fill(
DicNumpyArray_branch.values()[j][0])
else:
continue
key = ITER.Next()
# print(DICHISTLIST)
return DICHISTLIST
def _guessTreeName(self, pattern):
"""
Find the set of keys of all TTrees in all files matching pattern.
If the set contains only one key
Returns: the TTree key
else raises ValueError.
"""
names = []
for fnam in self.files:
rfile = TFile(fnam)
for key in rfile.GetListOfKeys():
obj = rfile.Get(key.GetName())
if type(obj) is TTree:
names.append( key.GetName() )
thename = set(names)
if len(thename)==1:
return list(thename)[0]
else:
err = [
'several TTree keys in {pattern}:'.format(
pattern=pattern
),
','.join(thename)
]
raise ValueError('\n'.join(err))
def get_branch_list_each_tree(self):
PATH_included_root = read_file_name_root(self._infile)[2]
DicTreeBranchNameList = {}
f = TFile(PATH_included_root, "READ")
dirlist = f.GetListOfKeys()
ITER = dirlist.MakeIterator()
key = ITER.Next()
while key:
BranchNameList = []
tree = key.ReadObj()
branchlist = tree.GetListOfBranches()
if (branchlist.IsEmpty()):
continue
ITER_b = branchlist.MakeIterator()
key_b = ITER_b.Next()
while key_b:
BranchNameList.append(key_b.GetName())
key_b = ITER_b.Next()
DicTreeBranchNameList[tree.GetName()] = BranchNameList
key = ITER.Next()
f.Close()
return DicTreeBranchNameList
def merge_channel(in_file, channel=[], out_file=None):
if not out_file:
out_file = in_file.replace('.root', '_mergedChannel.root')
work_file = TFile(in_file, "READ")
keys = work_file.GetListOfKeys()
hist_list = []
categories = []
for key in keys:
key = str(key.GetName())
splitname = key.split('__')
category = splitname[0]
for item in channel:
category = category.replace(item, '')
process = splitname[1]
new_name = category + '__' + process
if new_name not in categories:
categories.append(new_name)
hist_list.append(work_file.Get(key).Clone(new_name))
else:
for i, cat in enumerate(categories):
if new_name in cat:
hist_list[i].Add(work_file.Get(key))
work_file.Close()
output_file = TFile(out_file, 'RECREATE')
for hist in hist_list:
hist.Write('', TObject.kOverwrite)
output_file.Close()
return out_file
def compute(filename):
warnings.simplefilter("ignore")
file = TFile(filename)
keys = file.GetListOfKeys()
print 'input file:', filename
tuple_store = []
for key in keys:
key = key.GetName()
if 'Background' in key or 'plus' in key or 'minus' in key or 'DATA' in key:
continue
signalname = key.split('__')[1]
histogram = file.Get(key)
#entries = float(histogram.GetSumOfWeights())
entries = float(histogram.GetEntries())
found_sig = False
if tuple_store:
for item in tuple_store:
if item.name == signalname:
#print 'add',key,entries, 'to', item.name, 'sum',item.entries+entries
item.Add(entries, histogram)
found_sig = True
break
if not found_sig:
#print 'creating',signalname,entries,'with', key
tuple_store.append(signal_store(entries, signalname, histogram))
#print tuple_store
tuple_store.sort(key=lambda x: x.mass)
return tuple_store
def get_branch_list_each_tree(PATH_included_root):
from ROOT import TTree, TFile
DicTreeBranchNameList = {}
f = TFile(PATH_included_root, "READ")
dirlist = f.GetListOfKeys()
ITER = dirlist.MakeIterator()
key = ITER.Next()
while key:
BranchNameList = []
tree = key.ReadObj()
branchlist = tree.GetListOfBranches()
if (branchlist.IsEmpty()):
continue
ITER_b = branchlist.MakeIterator()
key_b = ITER_b.Next()
while key_b:
BranchNameList.append(key_b.GetName())
key_b = ITER_b.Next()
DicTreeBranchNameList[tree.GetName()] = BranchNameList
key = ITER.Next()
return DicTreeBranchNameList
def randomize_hists(filename, contains, seed=0):
print 'randomize hists in', filename,
work_file = TFile(filename, "UPDATE")
keys = work_file.GetListOfKeys()
hist_list = []
random.seed(seed)
for key in keys:
key = str(key.GetName())
#print key
if not contains in key: continue
hist = work_file.Get(key).Clone()
work_file.Delete(key + ';*')
for i in xrange(hist.GetNcells()):
error = hist.GetBinError(i)
#if error ==0 and hist.GetBinContent(i)==0: error =1
new = (random.random() * 2 - 1) * error + hist.GetBinContent(i)
m = 0
while (new < 0 and m < 1000):
m += 1
new = (random.random() * 2 - 1) * error + hist.GetBinContent(i)
if (new < 0): new = 0
print key, 'new content', new, 'old', hist.GetBinContent(
i), 'error', error
hist.SetBinContent(i, new)
hist_list.append(hist)
for item in hist_list:
item.Write()
def getCutflow( ecm="161" ):
sampleCounters= dict()
filename= "sjm"+ecm+".root"
if ecm == "91":
filename= "sjm"+ecm+"_all.root"
f= TFile( filename )
eventCountsHisto= f.Get( "Eventcounts" )
eventCounts= unpackAlphanumericHisto( eventCountsHisto )
keyList= f.GetListOfKeys()
MCsamples= [ "Signal", "AltSignal", "BkgWWqqqq", "BkgWWllqq", "BkgWWeeqq" ]
samples= [ "Data" ] + MCsamples
countersKeys= [ key.GetTitle() for key in keyList if key.GetTitle() in samples ]
for counterskey in countersKeys:
hist= f.Get( counterskey )
if hist:
counters= unpackAlphanumericHisto( hist )
counters["events"]= eventCounts[counterskey]
sampleCounters[counterskey]= counters
import SjmConfigParser
cfgFilename= "sjmconfig_"+ecm+".cfg"
config= SjmConfigParser.readConfig( [ cfgFilename ] )
lumi= getFromConfig( config, "Data", "lumi" )
sampleCounters["Data"]["lumi"]= lumi
for section in MCsamples:
xsec= getFromConfig( config, section, "xsec" )
if xsec:
sampleCounters[section]["xsec"]= xsec
return sampleCounters
def readHists(h, fname, wanted=[], withProjections=True):
if fname[0:4] == "/eos":
eospath = gSystem.Getenv("EOSSHIP") + fname
f = TFile.Open(eospath)
else:
f = TFile(fname)
for akey in f.GetListOfKeys():
name = akey.GetName()
try:
hname = int(name)
except:
hname = name
if len(wanted) > 0:
if not hname in wanted: continue
obj = akey.ReadObj()
cln = obj.Class().GetName()
if not cln.find('TCanv') < 0:
h[hname] = obj.Clone()
if cln.find('TH') < 0: continue
if h.has_key(hname):
rc = h[hname].Add(obj)
if not rc: print "Error when adding histogram ", hname
else:
h[hname] = obj.Clone()
if h[hname].GetSumw2N() == 0: h[hname].Sumw2()
h[hname].SetDirectory(gROOT)
if (cln == 'TH2D' or cln == 'TH2F') and withProjections:
for p in ['_projx', '_projy']:
if type(hname) == type('s'): projname = hname + p
else: projname = str(hname) + p
if p.find('x') > -1: h[projname] = h[hname].ProjectionX()
else: h[projname] = h[hname].ProjectionY()
h[projname].SetName(name + p)
h[projname].SetDirectory(gROOT)
return
def showcase_set_branch_address(BRANCHLISTALL, PATH_FILE_NAME):
from ROOT import TTree, TFile
import numpy
DicNumpyArray_branch = {}
for numpyarray in BRANCHLISTALL:
a = numpy.array([0], 'd')
DicNumpyArray_branch[numpyarray] = a
f = TFile(PATH_FILE_NAME, "READ")
dirlist = f.GetListOfKeys()
ITER = dirlist.MakeIterator()
key = ITER.Next()
while key:
tree = key.ReadObj()
for i in range(len(DicNumpyArray_branch)):
tree.SetBranchAddress(DicNumpyArray_branch.keys()[i],
DicNumpyArray_branch.values()[i])
#print(DicNumpyArray_branch.keys()[i])
key = ITER.Next()
print(
"!!! This is just a showcase of SetBranchAddress, not really set !!!")
return DicNumpyArray_branch
def fillLists():
# List files and fill categories
for c in os.listdir('rootfiles_' + options.name + '/'):
if c.endswith('root'):
categories.append(c.replace('.root', ''))
# Read file and histograms
inFile = TFile("rootfiles_" + options.name + "/" + categories[0] + ".root",
"READ")
inFile.cd()
for key in inFile.GetListOfKeys():
obj = key.ReadObj()
if obj.IsA().InheritsFrom("TH1"):
name = obj.GetName()
if 'DM' in name:
sign.append(name)
elif not "data_obs" in name and not "BkgSum" in name:
back.append(name)
# Categories (directories)
if obj.IsFolder():
subdir = obj.GetName()
subdir = subdir.replace('Up', '').replace('Down', '')
print subdir
if not subdir in greenShape: continue
if not subdir in shape: shape.append(subdir)
inFile.Close()
def set_histograms(FILENAME, S_FILENAME, HISTO_XRANGE, NBins=100):
f = TFile(FILENAME, "READ")
dirlist = f.GetListOfKeys()
ITER = dirlist.MakeIterator()
key = ITER.Next()
DichistList = {}
# DichistList = dict()
while key:
histList = []
NamehistList = []
tree = key.ReadObj()
branchlist = tree.GetListOfBranches()
if (branchlist.IsEmpty()):
continue
ITER_b = branchlist.MakeIterator()
key_b = ITER_b.Next()
while key_b:
Namehist = S_FILENAME + "_" + tree.GetName() + "_" + key_b.GetName(
) + "_hist"
# print(Namehist)
for j in range(len(HISTO_XRANGE[tree.GetName()])):
if key_b.GetName() in HISTO_XRANGE[tree.GetName()].keys()[j]:
hist = TH1D(Namehist, Namehist, NBins,
HISTO_XRANGE[tree.GetName()].values()[j][0],
HISTO_XRANGE[tree.GetName()].values()[j][1])
histList.append(hist)
else:
continue
key_b = ITER_b.Next()
DichistList[tree.GetName()] = histList
key = ITER.Next()
f.Close()
print(DichistList)
return DichistList
def download_objects(input_file="t.root",
out_path="/tmp/ccdbtest2/",
host="http://ccdb-test.cern.ch:8080",
overwrite=False):
msg("Downloading CCDB objects from input file", input_file)
out_path = os.path.normpath(out_path)
f = TFile(input_file, "READ")
lk = f.GetListOfKeys()
obj_done = []
for i in lk:
name = i.GetName()
cycle = i.GetCycle()
if name in obj_done:
continue
obj_done.append(name)
obj = f.Get(f"{name};{cycle}")
name = name.replace("--", "/")
limits = [int(obj.GetPointY(j)) for j in range(obj.GetN())]
verbose_msg(name, len(limits), "First", limits[0],
convert_timestamp(limits[0]), "Last", limits[-1],
convert_timestamp(limits[-1]))
for j in limits:
get_ccdb_obj(name,
j,
out_path=out_path,
host=host,
show=False,
verbose=True,
tag=True,
overwrite_preexisting=overwrite)
f.Close()
for i in obj_downloaded:
msg("Downloaded", obj_downloaded[i], i)
def pyMakeClass(options, arguments):
from ROOT import TFile, TTree
inFile = TFile(options.inputSample)
fileKeyNames = []
for key in inFile.GetListOfKeys():
fileKeyNames.append(key.GetName())
if options.debug:
pprint(fileKeyNames)
if "/" in options.treeName:
if options.debug:
print "looks like the tree name specified is within some TDirectory structure"
treePath = options.treeName.split("/")
treeName = treePath.pop()
for tdirectory in treePath:
for dirKeys in inFile.Get(tdirectory).GetListOfKeys():
fileKeyNames.append(dirKeys.GetName())
inFile.cd(tdirectory)
if options.debug:
print "found these keys in the TDirectory structure:"
pprint(fileKeyNames)
else:
treeName = options.treeName
if not treeName in fileKeyNames:
print "Error: could not find a tree named %s in %s" % (
options.treeName, options.inputSample)
inFile.ls()
exit(1)
else:
inTree = inFile.Get(options.treeName)
inTree.MakeClass(options.className)
def getRegionsVars():
""" Get processed regions from hists produced """
f = TFile("hists/%s.root" % inputsamples[0])
keys = [name.GetName() for name in f.GetListOfKeys()]
#first get all the region and var names of hists
dupregions = []
dupvars = []
for key in keys:
pos = key.find('_')
dupregions.append(key[0:pos])
dupvars.append(key[pos + 1:len(key)])
#strip out the repeated region names
regions = []
for x in dupregions:
if x not in regions:
regions.append(x)
#strip out the repeated var names
varnames = []
for x in dupvars:
if x not in varnames:
varnames.append(x)
print 'Regions are processed: '
for region in regions:
print region
print 'variables are filled: '
for varname in varnames:
print varname
return regions, varnames
def readHists(h, fname):
if fname[0:4] == "/eos":
eospath = "root://eoslhcb.cern.ch/" + fname
f = ROOT.TFile.Open(eospath)
else:
f = TFile(fname)
for akey in f.GetListOfKeys():
name = akey.GetName()
try:
hname = int(name)
except:
hname = name
obj = akey.ReadObj()
cln = obj.Class().GetName()
if not cln.find('TCanv') < 0:
h[hname] = obj.Clone()
if cln.find('TH') < 0: continue
if h.has_key(hname):
rc = h[hname].Add(obj)
if not rc: print "Error when adding histogram ", hname
else:
h[hname] = obj.Clone()
if h[hname].GetSumw2N() == 0: h[hname].Sumw2()
h[hname].SetDirectory(gROOT)
if cln == 'TH2D' or cln == 'TH2F':
for p in ['_projx', '_projy']:
if type(hname) == type('s'): projname = hname + p
else: projname = str(hname) + p
if p.find('x') > -1: h[projname] = h[hname].ProjectionX()
else: h[projname] = h[hname].ProjectionY()
h[projname].SetName(name + p)
h[projname].SetDirectory(gROOT)
return
class Raw:
def __init__(self, c: Converter, load_file=False):
self.Parent = c
self.RunNumber = c.RunNumber
self.SoftDir = c.SoftDir.joinpath(c.Config.get('SOFTWARE', 'eudaq2'))
self.DataDir = c.DataDir
self.SaveDir = c.SaveDir
self.FilePath = self.load_file_path()
self.OutFilePath = c.SaveDir.joinpath(f'run{self.RunNumber:06d}.root')
if load_file:
self.F = TFile(str(self.OutFilePath)) if load_file else None
self.P = [
self.F.Get(key.GetName()).Get('Hits')
for key in self.F.GetListOfKeys()
if key.GetName().startswith('Plane')
]
self.Draw = Draw(c.Config.FilePath)
def __repr__(self):
return f'Raw file analysis run {self.RunNumber} ({self.FilePath.name})'
def load_file_path(self):
n = list(
self.DataDir.joinpath('raw').glob(f'run{self.RunNumber:06d}*.raw'))
return n[0] if len(n) else None
def generate_fit_files(self):
c = None
for dut in range(self.Parent.NDUTPlanes):
c = self.Parent.get_calibration(dut)
if not c.FitFileName.exists():
c.save_fit_pars()
return c.CalPath
def convert(self):
""" convert binary raw file to root file with eudaq"""
cal_path = self.generate_fit_files()
if self.FilePath is None:
critical('raw file does not exist for run: {}'.format(
self.RunNumber))
self.OutFilePath.parent.mkdir(exist_ok=True)
cmd = f'{self.SoftDir.joinpath("bin", "euCliConverter")} -i {self.FilePath} -o {self.OutFilePath} -c {cal_path}'
info(
f'Convert {self.FilePath.name} to {self.OutFilePath.name} using EUDAQ-2\n'
)
info(f'{cmd}\n')
check_call(cmd, shell=True)
for f in Path().glob('AutoDict_vector*'):
remove_file(f)
def make_cuts(self):
[t.SetEstimate(t.GetEntries() * 10) for t in self.P]
n = [get_tree_vec(t, 'NHits', dtype='i2') for t in self.P[:6]]
c = all([i == 1 for i in n], axis=0)
return [c.repeat(i) for i in n]
def getTasksFromRootfile(filePath):
file = TFile(filePath, 'READ')
keys = file.GetListOfKeys()
keyNames = [key.GetName() for key in keys]
#log.logDebug("%s" % keyNames)
file.Close()
return keyNames
