def BranchObj(self, bname, typestr = None):
obj = None
if None == typestr:
# ok, branch for reading
b = self.tree.FindBranch(bname)
if None == b:
raise Exception('Unknown branch name \'%s\' in ' \
'TTree \'%a\' requested.' % (bname, self.tree.GetName()))
l = b.GetLeaf(bname)
if None == l:
raise Exception('Unknown leaf in branch in \'%s\' in ' \
'TTree \'%a\' requested.' % (bname, self.tree.GetName()))
typestr = l.GetTypeName()
obj = getTypeFactory(typestr)()
self.tree.SetBranchAddress(bname, obj)
else:
# new branch for writing
b = self.tree.FindBranch(bname)
if None != b:
raise Exception('Branch \'%s\' already exists in ' \
'TTree \'%s\'.' % (bname, self.tree.GetName()))
obj = getTypeFactory(typestr)()
bcallargs = (bname, obj)
if isinstance(obj, ctypes._SimpleCData):
# ok a POD type most likely, so ROOT needs telling what kind of
# branch it's supposed to create
if type(obj) not in self.__typedictPOD__:
raise Exception('Unknown data type for branch \'%s\' in '\
'tree \'%s\'' % (bname, self.tree.GetName()))
bcallargs += ('%s/%s' % (bname, self.__typedictPOD__[type(obj)]),)
self.tree.Branch(*bcallargs)
self.branches[bname] = obj
return obj
def createTree(filename, treename):
from ROOT import TFile, TRandom3
from ROOT import DotLock, TimeStamp, VersionedObject
from TypeHelper import getTypeFactory
from GUITree import Tree
# acquire write lock
dl = DotLock(filename)
# open file for writing (overwriting destination if it exists)
f = TFile(filename, 'RECREATE')
# be a bit more aggressive when compressing data: we're not CPU-limited
# when writing tuple files, but we're happy to get by using up less disk
# bandwidth
f.SetCompressionSettings(ROOT.ROOT.CompressionSettings(ROOT.ROOT.kLZMA, 6))
# create tree with given structure
t = Tree(treename, 'Velo DQ Tree prototype', {
# define branch names and types
'runnr': 'UInt_t', # this never gets updated, so no VersionedObject here
'checked': 'VersionedObject<UShort_t, TimeStamp, std::greater<TimeStamp> >',
'comment': 'VersionedObject<std::string, TimeStamp, std::greater<TimeStamp> >',
'meanpedestal': 'VersionedObject<Float_t, TimeStamp, std::greater<TimeStamp> >',
'occupancy': 'VersionedObject<std::map<int,std::vector<Float_t> >, TimeStamp, std::greater<TimeStamp> >'
})
# construct list of valid Velo sensor numbers
sensors = tuple(xrange(0, 42))
sensors += tuple(xrange(64, 64 + 42))
sensors += tuple(xrange(128, 132))
# get RNG to generate some data to put into the tuple
rnd = TRandom3()
# fill tree, 64 entries
for i in xrange(0, 64):
# clear out data from last run
t.comment.clear()
t.occupancy.clear()
t.meanpedestal.clear()
# fill new run
# step 1: generate time stamp (now)
now = TimeStamp()
# step 2: fill branches
t.runnr = 100000 + i
print 'Generating dummy DQ data for run %u' % t.runnr
t.checked[now] = 0
t.comment[now] = 'initial DQ for run %u: UNCHECKED' % t.runnr
t.meanpedestal[now] = rnd.Uniform(-5., 5.)
# simulate about 3 permille dead, 5 permille noisy channels, and have
# that fluctuate a bit
fdead = rnd.Uniform(0.003, 0.002)
if fdead < 0.: fdead = 0.
fnoisy = rnd.Uniform(0.005,0.003)
if fnoisy < 0.: fnoisy = 0.
# ok, put the per-strip occupancies in
for sensor in sensors:
# vector of per-strip occupancies
ov = getTypeFactory('std::vector<Float_t>')(2048, 0.)
for strip in xrange(0, 2048):
# simulate dead, noisy and normal strips
tmp = rnd.Uniform(0., 1.)
if tmp > (fdead + fnoisy): ov[strip] = rnd.Gaus(0.01, 0.0025)
elif tmp > fnoisy: ov[strip] = rnd.Uniform(0., 1.)
else: pass # zero anyway
# put that strip vector for the current sensor into the current
# version
t.occupancy[now][sensor] = ov
# step 3: fill tree
t.Fill()
# make sure tree is written to file
t.Write()
# close file
del t
f.Close()
del f
