def getGTfromDQMFile(DQMfile, Run_number, globalTagVar):
if not os.path.isfile(DQMfile):
print("Error: file" + str(DQMfile) + "not found, exit")
sys.exit(0)
thefile = TFile(DQMfile)
globalTagDir = 'DQMData/Run ' + Run_number + '/Info/Run summary/CMSSWInfo'
if not gDirectory.GetDirectory(globalTagDir):
print("Warning: globalTag not found in DQM file")
sys.exit(0)
keys = gDirectory.GetDirectory(globalTagDir).GetListOfKeys()
key = keys[0]
globalTag = ''
while key:
obj = key.ReadObj()
if globalTagVar in obj.GetName():
globalTag = obj.GetName()[len("<" + globalTagVar +
">s="):-len("</" + globalTagVar +
">")]
break
key = keys.After(key)
if len(globalTag) > 1:
if globalTag.find('::') >= 0:
print(globalTag[0:globalTag.find('::')])
else:
print(globalTag)
return globalTag
def putHistogram(self, dataset, systematicVariation, var, cut, histogram):
## update or put a new histogram into store based on how it was created
# @param dataset Dataset object
# @param systematicVariation SystematicVariation object
# @param var Variable object
# @param cut Cut object
# @param histogram ROOT::TH1 object
#if not self._open( dataset, systematicVariation, var, cut ):
# return None
if not self._open(dataset, systematicVariation, var, cut, 'update'):
self.logger.warning(
'putHistogram(): unable to store histogram, file not open')
return None
path, histogramName = self._buildPath(dataset, systematicVariation,
var, cut)
self.logger.debug('putHistogram(): storing histogram "%s/%s"' %
(path, histogramName))
self._file.cd()
from ROOT import TObject, gDirectory
for directory in path.split('/'):
if not gDirectory.GetDirectory(directory):
gDirectory.mkdir(directory)
gDirectory.cd(directory)
histogram = histogram.Clone(histogramName)
histogram.Write(histogramName, TObject.kOverwrite)
def putHistogram(self, channelName, datasetName, systematicName, var, cut,
histogram):
## update or put a new histogram into store based on how it was created
# @param datasetName the name of the dataset
# @param systematicName the name of the systematic variation
# @param var the variable
# @param cut the cut
# @param histogram the histogram object
if not self._open():
return None
path, histogramName = self._buildPath(channelName, datasetName,
systematicName)
self.logger.debug('putHistogram(): storing histogram "%s/%s"' %
(path, histogramName))
self.file.cd()
from ROOT import TObject, gDirectory
for directory in path.split('/'):
if not gDirectory.GetDirectory(directory):
gDirectory.mkdir(directory)
gDirectory.cd(directory)
if 'resopara' in histogramName or 'resoperp' in histogramName:
if '_low' in histogramName:
histogramName.replace('_low', '')
elif '_high' in histogramName:
return
histogram.SetTitle(histogramName)
histogram.Write(histogramName, TObject.kOverwrite)
def postcmd(self, stop, line):
self.oldpwd = self.pwd.GetDirectory('')
self.pwd = gDirectory.GetDirectory('')
dirn = self.pwd.GetName()
if len(dirn) > 20:
dirn = '{}..{}'.format(dirn[0:9], dirn[-9:])
self.prompt = '{}> '.format(dirn)
return cmd.Cmd.postcmd(self, stop, line)
def get_dir(self, path=None):
"""Return directory from path.
Doesn't check for non-directory. It's the caller's
responsibility.
"""
if not path:
return gDirectory.GetDirectory('')
else:
path = pathspec(path)
with savepwd():
if path.rfile: # need to change to correct file first
if path.rfile not in [f.GetName() for f in self.files]:
# opening a file changes dir to the new file
self.files += [ROOT.TFile.Open(path.rfile, 'read')]
else:
gROOT.cd('{}:'.format(path.rfile))
return gDirectory.GetDirectory(path.rpath)
def applyInAllDirectories(functor, directory, depth=1):
oldDirectory = gDirectory.GetDirectory("")
directory.cd()
prefix = "-"
prefix *= depth * 2
print prefix, "Examining directory: %s" % directory.GetName()
# call our funciton
print "calling"
functor(directory)
# find sub directories
depth += 1
# recurse into subdirectories
for dir in objectsInheritingFrom("TDirectory", directory):
applyInAllDirectories(functor, dir, depth)
oldDirectory.cd()
from ROOT import gDirectory
import sys
import os
DQMfile = sys.argv[1]
RunNumber = sys.argv[2]
globalTagVar = sys.argv[3]
if not os.path.isfile(DQMfile):
# print "Error: file", DQMfile, "not found, exit"
sys.exit(0)
thefile = TFile(DQMfile)
globalTagDir = 'DQMData/Run ' + RunNumber + '/Info/Run summary/CMSSWInfo'
if not gDirectory.GetDirectory(globalTagDir):
# print "Warning: globalTag not found in DQM file"
sys.exit(0)
keys = gDirectory.GetDirectory(globalTagDir).GetListOfKeys()
key = keys[0]
globalTag = ''
while key:
obj = key.ReadObj()
if globalTagVar in obj.GetName():
globalTag = obj.GetName()[len("<" + globalTagVar +
">s="):-len("</" + globalTagVar + ">")]
break
key = keys.After(key)
if len(globalTag) > 1:
sys.path.append('python')
ifile = sys.argv[1]
cfgfile = sys.argv[2]
ofile = sys.argv[3]
iFILE = rt.TFile(ifile)
oFILE = rt.TFile(ofile, "RECREATE")
cfg = imp.load_source('final', cfgfile)
for _cfg in cfg.cfg:
hist = _cfg.getHist(iFILE)
if not gDirectory.GetDirectory(_cfg.collection):
gDirectory.mkdir(_cfg.collection + "/" + _cfg.ID)
gDirectory.cd(_cfg.collection + "/" + _cfg.ID)
else:
gDirectory.cd(_cfg.collection)
if not gDirectory.GetDirectory(_cfg.ID):
gDirectory.mkdir(_cfg.ID)
gDirectory.cd(_cfg.ID)
for h in hist:
h.Write()
#CANVAS.Print(_cfg.collection + "_" + _cfg.ID + "_" + h.GetName() + ".pdf")
gDirectory.cd("/")
oFILE.Close()
def __init__(self):
self.pwd = gDirectory.GetDirectory('')
def fhadd(self, prefix="", force=False, verbose=False, slow=True):
""" taken from https://root.cern.ch/phpBB3/viewtopic.php?t=14881
This function will merge objects from a list of root files and write them
to a target root file. The target file is newly created and must not
exist, or if -f ("force") is given, must not be one of the source files.
IMPORTANT: It is required that all files have the same content!
Fast but memory hungry alternative to ROOT's hadd.
Arguments:
target -- name of the target root file
sources -- list of source root files
classname -- restrict merging to objects inheriting from classname
force -- overwrite target file if exists
"""
target = prefix + self.Name + ".root"
sources = [j.Output for j in self.Jobs]
TH1.AddDirectory(False)
# check if target file exists and exit if it does and not in force mode
if not force and os.path.exists(target):
raise RuntimeError("target file %s exists" % target)
# open the target file
print "fhadd Target file:", target
outfile = TFile(target, "RECREATE")
# open the seed file - contents is looked up from here
seedfilename = sources[0]
print "fhadd Source file 1", seedfilename
seedfile = TFile(seedfilename)
# get contents of seed file
print "looping over seed file"
contents = self.loop(seedfile)
print "done %d objects are ready to be merged" % len(contents)
if (verbose):
for c in contents:
print c
# open remaining files
otherfiles = []
for n, f in enumerate(sources[1:]):
print "fhadd Source file %d: %s" % (n + 2, f)
otherfiles.append(TFile(f))
# loop over contents and merge objects from other files to seed file objects
for n, (path, hname) in enumerate(contents):
print "fhadd Target object: %s" % os.path.join(path, hname)
obj_path = os.path.join(path, hname)
obj_ = seedfile.Get(obj_path[1:])
outfile.cd('/')
# create target directory structure
for d in path.split('/')[1:]:
directory = gDirectory.GetDirectory(d)
if not directory:
gDirectory.mkdir(d).cd()
else:
gDirectory.cd(d)
obj = None
if obj_.InheritsFrom("TTree"):
obj = obj_.CloneTree()
else:
obj = obj_.Clone()
# merge objects
l = TList()
for o in [of.Get(obj_path[1:]) for of in otherfiles]:
l.Add(o)
obj.Merge(l)
# delete objects if in slow mode
if slow:
print "Deleting %d object(s)", l.GetEntries()
l.Delete()
# write object to target
obj.Write(obj.GetName(), TObject.kOverwrite)
print "Writing and closing file"
# let ROOT forget about open files - prevents deletion of TKeys
for f in [outfile, seedfile] + otherfiles:
gROOT.GetListOfFiles().Remove(f)
outfile.Write()
outfile.Close()
for f in [seedfile] + otherfiles:
f.Close()
def main():
args = parser()
filename = args.filename
os.system('mkdir -p rootfiles')
os.system('mkdir -p plots')
f = tables.open_file(filename)
print(f"Successfully opened file: {filename}.")
data = f.get_node('/data')
print("Read /data")
event_ids = getDataCol('event_id', data)
waveforms = getDataCol('waveform', data)
times = getDataCol('time', data)
timestamps = getDataCol('timestamp', data)
thresFlags = getDataCol('thresholdFlags', data)
i_1V1 = getDataCol('i_1V1', data)
i_1V35 = getDataCol('i_1V35', data)
i_1V8 = getDataCol('i_1V8', data)
i_2V5 = getDataCol('i_2V5', data)
i_3V3 = getDataCol('i_3V3', data)
v_1V1 = getDataCol('v_1V1', data)
v_1V35 = getDataCol('v_1V35', data)
v_1V8 = getDataCol('v_1V8', data)
v_2V5 = getDataCol('v_2V5', data)
v_3V3 = getDataCol('v_3V3', data)
nsamples = len(waveforms[0])
fq = np.linspace(0, 240, nsamples)
gmean = np.mean(waveforms[0])
globalmean = np.mean(waveforms)
print(np.mean(waveforms[0]))
c = TCanvas("c", "c", 800, 600)
c.Draw()
c.SetGrid()
of = TFile('rootfiles/{0}.root'.format(filename.split('.h', 1)[0]),
"RECREATE")
h = TH1D('qdist', 'qdist;ADC count;Entry', 500, -100, 900)
hpk = TH1D('peak', 'peak;ADC count;Entry', 500, -100, 900)
havg = TH1D('avgwf', 'Averaged Waveform;Sampling Bin;ADC count', nsamples,
0, nsamples)
havgfft = TH1D('avgfft',
'FFT Averaged Waveform;Frequency [MHz];Amplitude [LSB]',
int(len(fq) / 2) + 1, 0, 120 + 240 / (nsamples - 1))
hifft = TH1D('Subtwf', 'Averaged Waveform;Sampling Bin;ADC count',
nsamples, 0, nsamples)
hsfft = TH1D('Subtfft',
'FFT Averaged Waveform;Frequency [MHz];Amplitude [LSB]',
int(len(fq) / 2) + 1, 0, 120 + 240 / (nsamples - 1))
hsspe = TH1D('qdist_subt', 'qdist_subt;ADC count;Entry', 500, -100, 900)
hmax = TH1D('hmax', 'hmax;ADC count;Entry', 500, -100, 900)
bsfluc = TH1D('bsfluc', 'bsfluc;ADC count;Entry', 100,
int(globalmean) - 50,
int(globalmean) + 50)
bsshift = TGraphErrors()
bsshift.SetName('bsshift')
bsshift.SetTitle('bsshift;Event Number;Baseline [LSB]')
nrshift = TGraphErrors()
nrshift.SetName('nrshift')
nrshift.SetTitle('NoiseRateShift;Event Number;Noise Rate [Hz]')
rmsshift = TGraphErrors()
rmsshift.SetName('rmsshift')
rmsshift.SetTitle('RMSNoiseShift;Event Number;RMS Noise [LSB]')
rmstime = TGraphErrors()
rmstime.SetName('rmstime')
rmstime.SetTitle('rmstime;Unix time [s];RMS Noise [LSB]')
powerc = TGraphErrors()
powerc.SetName('powerc')
powerc.SetTitle('powerc;Event Number;Power Consumption [W]')
h_powerc = TH1D('h_powerc', 'h_powerc;Power Consumption [W];Entry', 100, 0,
5)
winmin = args.minimum
winmax = args.minimum + args.window
bsstart = args.baselineEst
print(f'Total #Events: {len(waveforms)}')
print(
f'Setting... Window [{winmin}:{winmax}] and Pedestal start from {bsstart}.\n'
)
topdir = gDirectory.GetDirectory(gDirectory.GetPath())
subdir = topdir.mkdir("Waveforms")
subdir2 = topdir.mkdir("FFT")
subdir3 = topdir.mkdir("proj")
thrdir = topdir.mkdir("thresFlags")
fltwfs = []
starttimestamp = timestamps[0]
procN = len(waveforms)
if args.nevents > 0:
procN = args.nevents
for i in tqdm(range(procN)):
if i < args.nskip:
continue
waveform = waveforms[i]
timestamp = timestamps[i]
bsfluc.Fill(np.mean(waveform))
n = bsshift.GetN()
bsshift.Set(n + 1)
bsshift.SetPoint(n, i, np.mean(waveform))
bsshift.SetPointError(n, 0, np.std(waveform))
n = rmsshift.GetN()
rmsshift.Set(n + 1)
rmsshift.SetPoint(n, i, np.std(waveform))
rmsshift.SetPointError(n, 0, 0)
hmax.Fill(np.max(waveform) - np.mean(waveform))
timeinterval = ((timestamp - starttimestamp - i * nsamples) / 240.e6 -
i * 0.501)
nr = 0
nrerr = 0
if timeinterval > 0:
nr = (i + 1) / timeinterval
nrerr = np.sqrt(i + 1) / timeinterval
n = nrshift.GetN()
nrshift.Set(n + 1)
nrshift.SetPoint(n, i, nr)
nrshift.SetPointError(n, 0, nrerr)
# FFT & IFFT ###
F_abs_amp = doFFT(waveform)
F = np.fft.fft(waveform)
F2 = np.copy(F)
fc = 60
df = 2
F2[(fq > fc - df) & (fq < fc + df)] = 0
F2[(fq > 2 * fc - df) & (fq < 2 * fc + df)] = 0
F2[(fq > 240 - fc - df) & (fq < 240 - fc + df)] = 0
F2_abs = np.abs(F2)
F2_abs_amp = F2_abs / len(waveform) * 2
F2_abs_amp[0] = F_abs_amp[0] / 2
F2_ifft = np.fft.ifft(F2)
F2_ifft_real = F2_ifft.real
######
baseline_mean = np.mean(waveform[bsstart:nsamples])
if args.fixbs:
baseline_mean = globalmean
center = int(baseline_mean)
proj = TH1D(f'proj{i}', f'Projection waveform{i};ADC count;Entry', 300,
center - 150, center + 150)
selected = waveform[waveform < np.mean(waveform) + 10]
for j in range(len(selected)):
proj.Fill(selected[j])
#proj.Fit("gaus")
#if len(selected) > 0:
# f = proj.GetFunction('gaus')
# norm = f.GetParameter(0)
# mean = f.GetParameter(1)
# sigma = f.GetParameter(2)
reduced_waveform = waveform - baseline_mean
scale = (nsamples - bsstart) / (winmax - winmin)
#h.Fill(sum(waveform[winmin:winmax])-sum(waveform[bsstart:nsamples])/scale)
h.Fill(sum(reduced_waveform[winmin:winmax]))
hsspe.Fill(
np.sum(F2_ifft_real[winmin:winmax]) - baseline_mean *
(winmax - winmin))
hpk.Fill(
max(waveform[winmin:winmax]) - np.mean(waveform[bsstart:nsamples]))
hfft = TH1D(f'FFT{i}', 'FFT{i};Frequency [MHz];Amplitude [LSB]',
int(len(fq) / 2) + 1, 0, 120 + 240 / (nsamples - 1))
hfft2 = TH1D(f'FFT2{i}', 'FFT2{i};Frequency [MHz];Amplitude [LSB]',
int(len(fq) / 2) + 1, 0, 120 + 240 / (nsamples - 1))
for j in range(int(len(F_abs_amp) / 2. + 1)):
hfft.Fill(fq[j], F_abs_amp[j])
hfft2.Fill(fq[j], F2_abs_amp[j])
h2 = TH1D(f'w{i}', 'Waveform{i};Sampling Bin;ADC count', nsamples, 0,
nsamples)
for j in range(len(waveform)):
h2.Fill(j, waveform[j])
#h2.Draw("hist")
#if np.max(F2_abs_amp[1:int(len(F2_abs_amp)/2.+1)]) > 0.5:
# c.SetLogy(0)
# h2.SetLineColor(4)
# h2.Draw("hist")
# c.Print(f"plots/w{i}.pdf(")
# c.SetLogy(1)
# hfft.SetLineColor(4)
# hfft.Draw("hist")
# c.Print(f"plots/w{i}.pdf)")
htot = TH1D(f'thresflags{i}',
'ThresholdFlags{i};Sampling Bin;Threshold Flag', nsamples,
0, nsamples)
for j in range(len(thresFlags[i])):
htot.Fill(j, thresFlags[i][j])
if max(waveform) - baseline_mean < args.threshold:
continue
fltwfs.append(waveform)
if args.silent:
del hfft
del hfft2
del h2
del htot
del proj
del waveform
del timestamp
del F
del F2
gc.collect()
continue
subdir2.cd()
hfft.Write()
subdir.cd()
h2.Write()
subdir3.cd()
proj.Write()
thrdir.cd()
htot.Write()
print('')
for i in range(len(i_1V1)):
internal_power = v_1V1[i] * i_1V1[i] + v_1V35[i] * i_1V35[i] + v_1V8[
i] * i_1V8[i] + v_2V5[i] * i_2V5[i] + v_3V3[i] * i_3V3[i]
n = powerc.GetN()
powerc.Set(n + 1)
powerc.SetPoint(n, i, internal_power * 1e-3)
powerc.SetPointError(n, 0, 0)
h_powerc.Fill(internal_power * 1e-3)
avgfltwfs = np.mean(fltwfs, axis=0)
for i in range(len(avgfltwfs)):
havg.Fill(i, avgfltwfs[i])
Favg_abs_amp = doFFT(avgfltwfs)
Favg = np.fft.fft(avgfltwfs)
Favg2 = np.copy(Favg)
Favg2[(fq > 59) & (fq < 61)] = 0
Favg2[(fq > 119) & (fq < 121)] = 0
Favg2[(fq > 179) & (fq < 181)] = 0
Favg2_abs = np.abs(Favg2)
Favg2_abs_amp = Favg2_abs / len(avgfltwfs) * 2
Favg2_abs_amp[0] = Favg_abs_amp[0] / 2
Favg2_ifft = np.fft.ifft(Favg2)
Favg2_ifft_real = Favg2_ifft.real
for i in range(int(len(Favg_abs_amp) / 2. + 1)):
havgfft.Fill(fq[i], Favg_abs_amp[i])
for i in range(int(len(Favg2_abs_amp) / 2. + 1)):
hsfft.Fill(fq[i], Favg2_abs_amp[i])
for i in range(len(Favg2_ifft_real)):
hifft.Fill(i, Favg2_ifft_real[i])
topdir.cd()
h.Write()
hpk.Write()
havg.Write()
havgfft.Write()
hsfft.Write()
hifft.Write()
hsspe.Write()
hmax.Write()
bsfluc.Write()
bsshift.Write()
nrshift.Write()
rmsshift.Write()
powerc.Write()
h_powerc.Write()
of.Close()
f.close()
