Functions
	getTileModuleHistogram (inputs, name, title)
	setTileModuleHistogramStyle (histogram, markerStyle=None, markerSize=None, markerColor=None, labelSize=None, ymin=None, ymax=None, delta=0.1)
	getProfile2D_RMS (inputs, title, name)
	getTilePartitionRawChannelNoise (inputs)
	getTileModulePedestalsAndLFN (inputs)
	getTileModuleHFN (inputs)
	getTileModuleCRC (inputs)
	getTileModuleBCID (inputs)
	getTileStuckBitsNumber2 (inputHistogram)
	getTileStuckBitsNumber (inputHistogram)
	getTileModuleStuckBits (inputs)
	getTileModuleCovariance (inputs)
	getTileModuleChi2VsAmplitude (inputs)
	getTileModuleAmplitudeAndSigmaWithRMS (inputs)
	fillTileModuleMeanAndRMS (histogram, inputs)
	getTileModuleSumHistogram (inputs, name, title)
	getTileModuleTime (inputs)
	getTileModuleTimeCorrected (inputs)
	getTileModuleAmplitudeDiffBetweenOfflineAndDSP (inputs)
	getTileModuleAmplitudeDSP (inputs)
	getTileModuleTimeDiffBetweenOfflineAndDSP (inputs)
	channelToPMT (module, channel)
	getTileModuleAmplitudeVarianceOverMean (inputs)
	getTileModuleAmplitudeOverChargeRatio (inputs)
	getTileModuleTimeSlopeAndOffset (inputs)
	sigtermHandler (signal, frame)

Variables
	parser = argparse.ArgumentParser()
	action
	help
	dest
	type
	int
	default
	args = parser.parse_args()
str	server = 'Histogramming'
	partition = os.getenv("TDAQ_PARTITION", "ATLAS")
	dataPath = find_datafile('TileMonitoring')
str	inputPath = f'{partition};{server};TileMIG:TileGatherer'
str	outputPath = f'{partition};{server};TilePT-stateless-PP'
list	physConfigurations = []
tuple	physPostProcess
list	noiseConfigurations = []
tuple	noisePostProcess

Detailed Description

@file TilePostProcessing.py
@brief Functions for post-processing of histograms from TileMonitoring for the Run III

Function Documentation

◆ channelToPMT()

TilePostProcessing.channelToPMT	(		module,
			channel )

This function converts Tile channel number to PMT number (hole/position in drawer)

   Negative number means that PMT is not connected!

Definition at line 691 of file TilePostProcessing.py.

def channelToPMT(module, channel):
    """
    This function converts Tile channel number to PMT number (hole/position in drawer)
 
       Negative number means that PMT is not connected!
    """
 
    position = [ 1,   2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,
                 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24,
                 27, 26, 25, 30, 29, 28,-33,-32, 31, 36, 35, 34,
                 39, 38, 37, 42, 41, 40, 45,-44, 43, 48, 47, 46,
 
                 1,   2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,
                 13, 14, 15, 16, 17, 18,-19,-20, 21, 22, 23, 24,
                 -27,-26,-25,-31,-32,-28, 33, 29, 30,-36,-35, 34,
                 44, 38, 37, 43, 42, 41,-45,-39,-40,-48,-47,-46 ]
 
    if module.startswith('EB'):
        channel += 48 # Extended barrel
    pmt = position[channel]
    # One need to do something for special modules EBA15 and EBC18 where
    # the first 4 channels are not connected, but E3 and E4 gap scintilators
    # are connected to channels 18 and 19 correspondingly
    if module in ['EBA15', 'EBC18'] and (channel < 4 or channel in [18, 19]):
        pmt = -pmt
 
    return pmt
 
 

◆ fillTileModuleMeanAndRMS()

TilePostProcessing.fillTileModuleMeanAndRMS	(		histogram,
			inputs )

This function fills 1D summary histogram per Tile module with mean value and RMS of all channels in the module

Definition at line 596 of file TilePostProcessing.py.

def fillTileModuleMeanAndRMS(histogram, inputs):
    """ This function fills 1D summary histogram per Tile module with mean value and RMS of all channels in the module """
 
    for input in inputs:
 
        inputHistogram = input[1][0]
        nEntries = inputHistogram.GetEntries()
        if nEntries > 0:
            channel = int(input[0]['channel'])
            bin = int(channel) + 1
 
            rms = inputHistogram.GetRMS()
            mean = inputHistogram.GetMean()
            histogram.SetBinContent(bin, mean)
            histogram.SetBinError(bin, rms)
 
 

◆ getProfile2D_RMS()

TilePostProcessing.getProfile2D_RMS	(	inputs,
		title,
		name )

This function produces 2D histogram with RMS from Profile2D per Tile partition

Definition at line 55 of file TilePostProcessing.py.

def getProfile2D_RMS(inputs, title, name):
    """ This function produces 2D histogram with RMS from Profile2D per Tile partition """
 
    assert len(inputs) == 1
 
    inputProfile = inputs[0][1][0]
    assert "TProfile2D" in str(inputProfile.ClassName())
    inputProfile.SetErrorOption("s")
 
    fullName = '{}_{}'.format(name, inputs[0][0]['partition'])
    if 'gain' in inputs[0][0]:
        fullName += '_' + inputs[0][0]['gain']
 
    fullTitle = str(inputProfile.GetTitle()).split(':')[0] + ': ' + title
 
    nBinsX = inputProfile.GetNbinsX()
    nBinsY = inputProfile.GetNbinsY()
 
    outputHistogram = inputProfile.Clone()
    outputHistogram.Reset()
    outputHistogram.SetTitle(fullTitle)
    outputHistogram.SetName(fullName)
    for binX in range(0, nBinsX + 1):
         for binY in range(0, nBinsY + 1):
             rms = inputProfile.GetBinError(binX, binY)
             if rms != 0:
                 outputHistogram.SetBinContent(binX, binY, rms)
                 outputHistogram.SetBinEntries(inputProfile.GetBin(binX, binY), 1)
 
    return [outputHistogram]
 
 

◆ getTileModuleAmplitudeAndSigmaWithRMS()

TilePostProcessing.getTileModuleAmplitudeAndSigmaWithRMS ( inputs )

This function produces 1D summary histogram per Tile module with amplitude, sigma, and RMS of all channels in the module

Definition at line 540 of file TilePostProcessing.py.

def getTileModuleAmplitudeAndSigmaWithRMS(inputs):
    """ This function produces 1D summary histogram per Tile module with amplitude, sigma, and RMS of all channels in the module """
 
    import math
    import ROOT
    # Force batch mode
    ROOT.gROOT.SetBatch(True)
 
    gain = inputs[0][0]['gain']
 
    amplitudeHistogram = getTileModuleHistogram(inputs, 'amp', 'Average Amplitude and RMS')
    rmsHistogram = getTileModuleHistogram(inputs, 'rms', 'RMS of Amplitude')
    sigmaHistogram = getTileModuleHistogram(inputs, 'sigma', 'Sigma of Amplitude from Gaussian fit')
 
    fitFunction = ROOT.TF1("g", 'gaus')
    inputHistogram = inputs[0][1][0]
    overlapHistogram = inputHistogram.GetBinWidth(1) == inputHistogram.GetBinWidth(100)
 
    for input in inputs:
 
        inputHistogram = input[1][0]
        nEntries = inputHistogram.GetEntries()
        if nEntries > 0:
            channel = int(input[0]['channel'])
            bin = int(channel) + 1
 
            rms = inputHistogram.GetRMS()
            amplitude = inputHistogram.GetMean()
            amplitudeHistogram.SetBinContent(bin, amplitude)
            amplitudeHistogram.SetBinError(bin, rms / math.sqrt(nEntries))
 
            rmsHistogram.SetBinContent(bin, rms)
            rmsHistogram.SetBinError(bin, rms / math.sqrt(2.0 * nEntries))
 
            if nEntries > 90:
                if overlapHistogram:
                    inputHistogram.Scale(1, 'width')
                inputHistogram.Fit(fitFunction, 'Q')
                sigma = fitFunction.GetParameter(2)
                sigmaError = fitFunction.GetParError(2)
                sigmaHistogram.SetBinContent(bin, sigma)
                sigmaHistogram.SetBinError(bin, sigmaError)
 
    setTileModuleHistogramStyle(amplitudeHistogram, markerStyle=21, markerSize=0.75, labelSize=0.08,
                                ymin={'hi' : -0.05, 'lo' : -1.0}.get(gain),
                                ymax={'hi' : 0.05, 'lo' : 1.0}.get(gain))
 
    yMin = min(0.0, rmsHistogram.GetMinimum(), sigmaHistogram.GetMinimum())
    yMax = max({'hi' : 0.05, 'lo' : 1.0}.get(gain), rmsHistogram.GetMaximum(), sigmaHistogram.GetMaximum())
 
    setTileModuleHistogramStyle(rmsHistogram, markerStyle=21, markerSize=0.75, labelSize=0.08, ymin=yMin, ymax=yMax)
    setTileModuleHistogramStyle(sigmaHistogram, markerStyle=25, markerSize=0.75, labelSize=0.08,ymin=yMin, ymax=yMax)
 
    return [amplitudeHistogram, sigmaHistogram, rmsHistogram]
 
 

◆ getTileModuleAmplitudeDiffBetweenOfflineAndDSP()

TilePostProcessing.getTileModuleAmplitudeDiffBetweenOfflineAndDSP ( inputs )

This function produces 1D summary histogram per Tile module with amplitude difference between offline and DSP of all channels in the module

Definition at line 658 of file TilePostProcessing.py.

def getTileModuleAmplitudeDiffBetweenOfflineAndDSP(inputs):
    """ This function produces 1D summary histogram per Tile module with amplitude difference between offline and DSP of all channels in the module """
 
    ampDiffHistogram = getTileModuleHistogram(inputs, 'dspfit_ampdiff', '(DSP-OFFLINE)/OFFLINE Amplitude and RMS')
    fillTileModuleMeanAndRMS(ampDiffHistogram, inputs)
    setTileModuleHistogramStyle(ampDiffHistogram, markerStyle=21, markerSize=0.75, labelSize=0.08, ymin=-0.05, ymax=0.05)
 
    sumAmpDiffHistogram = getTileModuleSumHistogram(inputs, 'dspfit_amphbar', '(DSP-OFFLINE)/OFFLINE Amplitude for all channels')
 
    return [ampDiffHistogram, sumAmpDiffHistogram]

◆ getTileModuleAmplitudeDSP()

TilePostProcessing.getTileModuleAmplitudeDSP ( inputs )

This function produces 1D summary histogram per Tile module with DSP amplitudes of all channels in the module

Definition at line 670 of file TilePostProcessing.py.

def getTileModuleAmplitudeDSP(inputs):
    """ This function produces 1D summary histogram per Tile module with DSP amplitudes of all channels in the module """
 
    amplitudeHistogram = getTileModuleHistogram(inputs, 'dspamp', 'Average DSP Amplitude and RMS')
    fillTileModuleMeanAndRMS(amplitudeHistogram, inputs)
 
    return [amplitudeHistogram]

◆ getTileModuleAmplitudeOverChargeRatio()

TilePostProcessing.getTileModuleAmplitudeOverChargeRatio ( inputs )

This function produces 1D summary histogram graph per Tile module with amplitude over charge ratio of all channels in the module

Definition at line 780 of file TilePostProcessing.py.

def getTileModuleAmplitudeOverChargeRatio(inputs):
    """ This function produces 1D summary histogram graph per Tile module with amplitude over charge ratio of all channels in the module """
 
    import ROOT
    # Force batch mode
    ROOT.gROOT.SetBatch(True)
 
    from TileCalibBlobObjs.Classes import TileCalibUtils as Tile
 
    capactior = str(inputs[0][1][0].GetName()).split('_').pop()
    amplitudeOverQHistogram = getTileModuleHistogram(inputs, f'qratio_{capactior}', f'Amplitude/Q Ratio for {capactior} pF')
 
    gain = inputs[0][0]['gain']
    gainName = {'hi' : 'high', 'lo' : 'low'}.get(gain)
    module = inputs[0][0]['module']
    run = str(inputs[0][1][0].GetTitle()).split(' ')[1]
 
    amplitudeOverQGraphName = f'{module}_{gain}_tails_{capactior}'
    amplitudeOverQGraphTitle = f'Run {run} {module} {gainName} gain: Mean Amplitude/Q and up/down tails for {capactior} pF'
    amplitudeOverQGraph = ROOT.TGraphAsymmErrors(Tile.MAX_CHAN)
    amplitudeOverQGraph.SetName(amplitudeOverQGraphName)
    amplitudeOverQGraph.SetTitle(amplitudeOverQGraphTitle)
 
    downLimit = 0.7
    upLimit = 1.3
 
    lowIntegralLimit = 0.005
    mediumIntegralLimit = 0.010
    highIntegralLimit = 0.015
 
    for input in inputs:
 
        inputHistogram = input[1][0]
        channel = int(input[0]['channel'])
        nEntries = inputHistogram.GetEntries()
        if nEntries > 0:
            bin = int(channel) + 1
 
            mean = inputHistogram.GetMean()
            amplitudeOverQHistogram.SetBinContent(bin, mean)
 
            # The following code calculates the error bars of amplitude over Q summary plots.
            # The error bar depends on the percentage of events outside a certain limit.
            # If the  percentage of events outside a certain limit is below the threshold,
            # then the error bar length is set to 0.
            # There are 3 different thresholds and a lower and an upper limit.
            minBin = inputHistogram.FindFirstBinAbove(0)
            maxBin = inputHistogram.FindLastBinAbove(0)
            xMin = inputHistogram.GetBinCenter(minBin)
            xMax = inputHistogram.GetBinCenter(maxBin)
            if downLimit < mean < upLimit:
                if xMin > downLimit:
                    xMin = mean
                else:
                    downLimitBin = inputHistogram.FindBin(downLimit)
                    # We also want underflow, in case... Integral() is calculated including the contents of both limiting bins.
                    # As 0.7 falls in the middle of a bin, we are calculating the integral by excess
                    integral = inputHistogram.Integral(0, downLimitBin)
                    ratio = integral / nEntries
                    if ratio > highIntegralLimit:
                        # Larger error bar
                        xMin = mean - 1.05
                    elif ratio > mediumIntegralLimit:
                        # Intermediate error bar
                        xMin = mean - 0.7
                    elif ratio > lowIntegralLimit:
                        # Small error bar
                        xMin = mean - 0.35
                    else:
                        xMin = mean
 
                if xMax < upLimit:
                    xMax = mean
                else:
                    upLimitBin = inputHistogram.FindBin(upLimit)
                    # We also want overflow, in case...  Integral() is calculated including the contents of both limiting bins.
                    # As 1.3 falls in the middle of a bin, we are calculating the integral by excess.
                    integral = inputHistogram.Integral(upLimitBin, (inputHistogram.GetNbinsX() + 1))
                    ratio = integral / nEntries
                    if ratio > highIntegralLimit:
                        # Larger error bar
                        xMax = mean + 1.05
                    elif ratio > mediumIntegralLimit:
                        # Intermediate error bar
                        xMax = mean + 0.7
                    elif ratio > lowIntegralLimit:
                        # Small error bar
                        xMax = mean + 0.35
                    else:
                        xMax = mean
 
            amplitudeOverQGraph.SetPoint(channel, channel + 0.5, mean)
            amplitudeOverQGraph.SetPointError(channel, 0.0, 0.0, max(0.0, mean - xMin), max(0.0, xMax - mean))
        else:
            amplitudeOverQGraph.SetPoint(channel, channel + 0.5, 0.0)
 
    amplitudeOverQHistogram.SetStats(ROOT.kFALSE)
    setTileModuleHistogramStyle(amplitudeOverQHistogram, markerStyle=21, markerSize=0.75, ymin=-0.2, ymax=2.2, labelSize=0.06)
 
    amplitudeOverQGraph.GetXaxis().SetRangeUser(0, 48)
    setTileModuleHistogramStyle(amplitudeOverQGraph, markerStyle=21, markerSize=0.75, ymin=-0.2, ymax=2.2)
 
 
    return [amplitudeOverQHistogram, amplitudeOverQGraph]
 
 

◆ getTileModuleAmplitudeVarianceOverMean()

TilePostProcessing.getTileModuleAmplitudeVarianceOverMean ( inputs )

This function produces 1D summary histogram per Tile module with amplitude variance over mean of all channels in the module

Definition at line 720 of file TilePostProcessing.py.

def getTileModuleAmplitudeVarianceOverMean(inputs):
    """ This function produces 1D summary histogram per Tile module with amplitude variance over mean of all channels in the module """
 
    import math
    module = inputs[0][0]['module']
 
    emptyPMTHistogram = getTileModuleHistogram(inputs, 'pmtGain_empty', 'Variance/Mean')
    setTileModuleHistogramStyle(emptyPMTHistogram, markerStyle=21, markerSize=0.75, labelSize=0.08, ymin=-0.2, ymax=2.2)
 
    evenPMTHistogram = getTileModuleHistogram(inputs, 'pmtGain_even', 'Variance/Mean')
    setTileModuleHistogramStyle(evenPMTHistogram, markerStyle=22, markerSize=0.75, labelSize=0.08, markerColor=2, ymin=-0.2, ymax=2.2)
 
    oddPMTHistogram = getTileModuleHistogram(inputs, 'pmtGain_odd', 'Variance/Mean')
    setTileModuleHistogramStyle(oddPMTHistogram, markerStyle=23, markerSize=0.75, markerColor=4, labelSize=0.08, ymin=-0.2, ymax=2.2)
 
    kapa = 1.30e-3
 
    for input in inputs:
 
        inputHistogram = input[1][0]
        nEntries = inputHistogram.GetEntries()
        if nEntries > 0:
            channel = int(input[0]['channel'])
            bin = int(channel) + 1
            pmt = channelToPMT(module, channel)
            if pmt < 0: # PMT is not connected
                emptyPMTHistogram.SetBinContent(bin, 0.01)
                emptyPMTHistogram.SetBinError(bin, 0.01)
            else:
                mean = inputHistogram.GetMean()
                rms = inputHistogram.GetRMS()
 
                meanError = rms / math.sqrt(nEntries)
                rmsError = rms / math.sqrt(2 * nEntries)
 
                if mean > 10e-3 and rms > 0.:
                    varianceOverMean = rms * rms / mean - kapa * mean
                    varianceOverMeanError = (rms * rms / mean) * math.sqrt(4 * (rmsError / rms) * (rmsError / rms) +
                                                                           (meanError / mean) * (meanError / mean))
                else:
                    varianceOverMean = -0.5
                    varianceOverMeanError = 0.001
 
                if pmt % 2 == 0:
                    evenPMTHistogram.SetBinContent(bin, varianceOverMean)
                    evenPMTHistogram.SetBinError(bin, varianceOverMeanError)
                else:
                    oddPMTHistogram.SetBinContent(bin, varianceOverMean)
                    oddPMTHistogram.SetBinError(bin, varianceOverMeanError)
 
 
    maxY = max(1.05 * oddPMTHistogram.GetMaximum(), 1.05 * evenPMTHistogram.GetMaximum(), 0.20)
    minY = min(oddPMTHistogram.GetMinimum() - 0.05 * abs(oddPMTHistogram.GetMinimum()),
               evenPMTHistogram.GetMinimum() - 0.05 * abs(evenPMTHistogram.GetMinimum()), -0.10)
 
    emptyPMTHistogram.GetYaxis().SetRangeUser(minY, maxY)
 
    return [evenPMTHistogram, oddPMTHistogram, emptyPMTHistogram]
 
 

◆ getTileModuleBCID()

TilePostProcessing.getTileModuleBCID ( inputs )

This function produces 1D summary histogram per Tile module with BCID errors of all DMU in the module

Definition at line 253 of file TilePostProcessing.py.

def getTileModuleBCID(inputs):
    """ This function produces 1D summary histogram per Tile module with BCID errors of all DMU in the module """
 
    import ROOT
    # Force batch mode
    ROOT.gROOT.SetBatch(True)
 
    gain = inputs[0][0]['gain']
    gainName = {'hi' : 'high', 'lo' : 'low'}.get(gain)
    module = inputs[0][0]['module']
    run = str(inputs[0][1][0].GetTitle()).split(' ')[1]
 
    bcidName = f'{module}_{gain}_bcid'
    bcidTitle = f'Run {run} {module} {gainName} gain: BCID errors'
    bcidHistogram = ROOT.TH1F(bcidName, bcidTitle, 16, 0.0, 16.0)
 
    for input in inputs:
 
        inputHistogram = input[1][0]
        dmu = int(input[0]['dmu'])
        bin = int(dmu) + 1
 
        underflow = inputHistogram.GetBinContent(0)
        bcidZero = inputHistogram.GetBinContent(1)
        bcidOk = inputHistogram.GetBinContent(2)
        bcidOther = inputHistogram.GetBinContent(3)
 
        weight = -1
        if (underflow + bcidOther) > 0:
            weight = 2 # all other errors in BCID
        else:
            if bcidOk == 0:
                weight = 0 # all zeros
            elif bcidZero == 0:
                weight = 1 # all OK
            else:
                # FIXME: weight = 1.0 - bcidZero / nEvents # percentage of good events
                weight = 1
                if weight > 0.8:
                     weight = 0.8 # to see clearly even one event with zeros
 
        bcidHistogram.SetBinContent(bin, weight)
 
    return [bcidHistogram]
 
 
 

◆ getTileModuleChi2VsAmplitude()

TilePostProcessing.getTileModuleChi2VsAmplitude ( inputs )

This function produces 2D summary histogram per Tile module with Chi2 vs amplitude of all channels in the module

Definition at line 515 of file TilePostProcessing.py.

def getTileModuleChi2VsAmplitude(inputs):
    """ This function produces 2D summary histogram per Tile module with Chi2 vs amplitude of all channels in the module """
 
    gain = inputs[0][0]['gain']
    gainName = {'hi' : 'high', 'lo' : 'low'}.get(gain)
    module = inputs[0][0]['module']
    run = str(inputs[0][1][0].GetTitle()).split(' ')[1]
 
    chi2AmpName = f'{module}_{gain}_summary_chi2_amp'
    chi2AmpTitle = f'Run {run} {module} {gainName} gain: Summary DSP #chi^{2} vs Amplitude'
    inputHistogram = inputs[0][1][0]
    chi2AmpHistogram = inputHistogram.Clone()
    chi2AmpHistogram.Reset()
    chi2AmpHistogram.SetTitle(chi2AmpTitle)
    chi2AmpHistogram.SetName(chi2AmpName)
 
    for input in inputs:
        inputHistogram = input[1][0]
        if inputHistogram.GetEntries() > 0:
            chi2AmpHistogram.Add(inputHistogram)
 
    setTileModuleHistogramStyle(chi2AmpHistogram, markerStyle=21, markerSize=0.75, labelSize=0.08, ymin=-0.05, ymax=10.0)
 
    return [chi2AmpHistogram]
 

◆ getTileModuleCovariance()

TilePostProcessing.getTileModuleCovariance ( inputs )

Produce Tile 2D histograms per module with covariance and correlation of channels in the module.

Definition at line 456 of file TilePostProcessing.py.

def getTileModuleCovariance(inputs):
    """ Produce Tile 2D histograms per module with covariance and correlation of channels in the module. """
 
    import ROOT
    # Force batch mode
    ROOT.gROOT.SetBatch(True)
 
    import math
 
    from TileCalibBlobObjs.Classes import TileCalibUtils as Tile
 
    gain = inputs[0][0]['gain']
    gainName = {'hi' : 'high', 'lo' : 'low'}.get(gain)
    module = inputs[0][0]['module']
    run = str(inputs[0][1][0].GetTitle()).split(' ')[1]
 
    covarianceName = f'{module}_{gain}_covar'
    covarianceTitle = f'Run {run} {module} {gainName} gain: Covariance'
    covarianceHistogram = ROOT.TH2F(covarianceName, covarianceTitle,
                                    Tile.MAX_CHAN, 0.0, Tile.MAX_CHAN,
                                    Tile.MAX_CHAN, 0.0, Tile.MAX_CHAN)
 
    correlationName = f'{module}_{gain}_corr'
    correlationTitle = f'Run {run} {module} {gainName} gain: Correlation'
    correlationHistogram = ROOT.TH2F(correlationName, correlationTitle,
                                     Tile.MAX_CHAN, 0.0, Tile.MAX_CHAN,
                                     Tile.MAX_CHAN, 0.0, Tile.MAX_CHAN)
 
    meanSampleHistogram = inputs[0][1][0]
    meanSample12Histogram = inputs[0][1][1]
 
    meanRMS = [0 for i in range(0,48)]
    covariance = [[0 for i in range(0,48)] for j in range(0,48)]
 
    for channel1 in range(0, Tile.MAX_CHAN):
        meanSample1 = meanSampleHistogram.GetBinContent(channel1 + 1)
        for channel2 in range(0, Tile.MAX_CHAN):
            meanSample2 = meanSampleHistogram.GetBinContent(channel2 + 1)
            meanSample12 = meanSample12Histogram.GetBinContent(channel1 + 1, channel2 + 1)
            covariance12 = meanSample12 - meanSample1*meanSample2
            covariance[channel1][channel2] = covariance12
 
        covariance11 = covariance[channel1][channel1]
        meanRMS[channel1] = 0 if covariance11 == 0 else covariance11 / math.sqrt(abs(covariance11))
 
    for channel1 in range(0, Tile.MAX_CHAN):
        for channel2 in range(0, Tile.MAX_CHAN):
            meanRMS1 = meanRMS[channel1]
            meanRMS2 = meanRMS[channel2]
            if (meanRMS1 == 0) or (meanRMS2 == 0):
                correlation = 0
            else:
                correlation = covariance[channel1][channel2] / (meanRMS1 * meanRMS2)
            correlationHistogram.SetBinContent(channel1 + 1, channel2 + 1, correlation)
            covarianceHistogram.SetBinContent(channel1 + 1, channel2 + 1, covariance[channel1][channel2])
 
    return [covarianceHistogram, correlationHistogram]
 
 

◆ getTileModuleCRC()

TilePostProcessing.getTileModuleCRC ( inputs )

This function produces 1D summary histogram per Tile module with CRC errors of all DMU in the module

Definition at line 200 of file TilePostProcessing.py.

def getTileModuleCRC(inputs):
    """ This function produces 1D summary histogram per Tile module with CRC errors of all DMU in the module """
 
    import ROOT
    # Force batch mode
    ROOT.gROOT.SetBatch(True)
 
    module = inputs[0][0]['module']
    run = str(inputs[0][1][0].GetTitle()).split(' ')[1]
 
    crcName = f'{module}_crc'
    crcTitle = f'Run {run} {module}: CRC errors'
    crcHistogram = ROOT.TH1F(crcName, crcTitle, 16, 0.0, 16.0)
 
    for input in inputs:
 
        inputHistogram = input[1][0]
        dmu = int(input[0]['dmu'])
        bin = int(dmu) + 1
 
        underflow = inputHistogram.GetBinContent(0)
        crcGlobal = inputHistogram.GetBinContent(1)
        crcOk = inputHistogram.GetBinContent(2)
        crcFE = inputHistogram.GetBinContent(3)
        crcROD = inputHistogram.GetBinContent(4)
        crcFE_ROD = inputHistogram.GetBinContent(5)
 
        weight = -1
        if (underflow + crcFE + crcROD + crcFE_ROD) > 0:
            if (crcROD == 0) and (crcFE_ROD == 0):
                weight = 2 # FE CRC only errors
            elif (crcFE == 0) and (crcFE_ROD == 0):
                weight = 3 # ROD CRC only errors
            else:
                # If there are ROD and FE errors (not necessary at the same time), weight is 2.5
                weight = 2.5 #ROD and FE CRC errors
        else:
            if crcOk == 0:
                weight = 0 # all zeros
            elif crcGlobal == 0:
                weight = 1 # all OK
            else:
                # FIXME: weight = 1.0 - crcGlobal / nEvents # percentage of good events
                weight = 1
                if weight > 0.8:
                     weight = 0.8 # to see clearly even one event with zeros
 
        crcHistogram.SetBinContent(bin, weight)
 
    return [crcHistogram]
 
 
 

◆ getTileModuleHFN()

TilePostProcessing.getTileModuleHFN ( inputs )

This function produces 1D summary histogram per Tile module with HFN of all channels in the module

Definition at line 183 of file TilePostProcessing.py.

def getTileModuleHFN(inputs):
    """ This function produces 1D summary histogram per Tile module with HFN of all channels in the module """
 
    hfnHistogram = getTileModuleHistogram(inputs, 'rms_hfr', 'RMS noise high frequency')
 
    for input in inputs:
 
        inputHistogram = input[1][0]
        channel = int(input[0]['channel'])
        bin = int(channel) + 1
 
        hfn = inputHistogram.GetMean()
        hfnHistogram.SetBinContent(bin, hfn)
 
    return [hfnHistogram]

◆ getTileModuleHistogram()

TilePostProcessing.getTileModuleHistogram	(	inputs,
		name,
		title )

This function returns 1D histogram for Tile module

Definition at line 15 of file TilePostProcessing.py.

def getTileModuleHistogram(inputs, name, title):
    """ This function returns 1D histogram for Tile module """
 
    import ROOT
    # Force batch mode
    ROOT.gROOT.SetBatch(True)
 
    from TileCalibBlobObjs.Classes import TileCalibUtils as Tile
 
    gain = inputs[0][0]['gain']
    gainName = {'hi' : 'high', 'lo' : 'low'}.get(gain)
    module = inputs[0][0]['module']
    run = str(inputs[0][1][0].GetTitle()).split(' ')[1]
 
    fullName = f'{module}_{gain}_{name}'
    fullTitle = f'Run {run} {module} {gainName} gain: {title}'
    histogram = ROOT.TH1F(fullName, fullTitle, Tile.MAX_CHAN, 0.0, Tile.MAX_CHAN)
 
    return histogram
 
 

◆ getTileModulePedestalsAndLFN()

TilePostProcessing.getTileModulePedestalsAndLFN ( inputs )

This function produces 1D summary histogram per Tile module with pedestals and LFN of all channels in the module

Definition at line 161 of file TilePostProcessing.py.

def getTileModulePedestalsAndLFN(inputs):
    """ This function produces 1D summary histogram per Tile module with pedestals and LFN of all channels in the module """
 
    pedestalHistogram = getTileModuleHistogram(inputs, 'ped', 'Pedestal[0]')
    lfnHistogram = getTileModuleHistogram(inputs, 'rms_lfr', 'RMS noise low frequency')
 
    for input in inputs:
 
        inputHistogram = input[1][0]
        channel = int(input[0]['channel'])
        bin = int(channel) + 1
 
        rms = inputHistogram.GetRMS()
        pedestal = inputHistogram.GetMean()
        pedestalHistogram.SetBinContent(bin, pedestal)
        pedestalHistogram.SetBinError(bin, rms)
 
        lfnHistogram.SetBinContent(bin, rms)
 
    return [pedestalHistogram, lfnHistogram]
 
 

◆ getTileModuleStuckBits()

TilePostProcessing.getTileModuleStuckBits ( inputs )

Produce Tile 1D summary histograms per module with stuck bits and zeros for all channels in the module

Definition at line 426 of file TilePostProcessing.py.

def getTileModuleStuckBits(inputs):
    """ Produce Tile 1D summary histograms per module with stuck bits and zeros for all channels in the module """
 
    bitsHistogram = getTileModuleHistogram(inputs, 'bits', 'Stuck bits and zero amplitudes')
 
    for input in inputs:
 
        inputHistogram = input[1][0]
        channel = int(input[0]['channel'])
        bin = int(channel) + 1
 
        nZeros = inputHistogram.GetBinContent(1)
        integral = inputHistogram.Integral(2, inputHistogram.GetNbinsX()) # first bin is excluded
 
        weight = 0
        if integral > 0: # if we have weight=0, then there is no non-zero amplitudes
            if nZeros > 0:
                weight = 0.5 # sometimes zeros
            else:
                weight = 1.0 # assume that all OK
 
        nStuckBits = getTileStuckBitsNumber(inputHistogram)
        if nStuckBits > 0:
            weight += 1.0 # some stuck bits
 
        bitsHistogram.SetBinContent(bin, weight)
 
    return [bitsHistogram]
 
 

◆ getTileModuleSumHistogram()

TilePostProcessing.getTileModuleSumHistogram	(	inputs,
		name,
		title )

This function produces 1D summary histogram per Tile module adding all histograms per channel in the module

Definition at line 613 of file TilePostProcessing.py.

def getTileModuleSumHistogram(inputs, name, title):
    """ This function produces 1D summary histogram per Tile module adding all histograms per channel in the module """
 
    gain = inputs[0][0]['gain']
    gainName = {'hi' : 'high', 'lo' : 'low'}.get(gain)
    module = inputs[0][0]['module']
    run = str(inputs[0][1][0].GetTitle()).split(' ')[1]
 
    fullName = f'{module}_{gain}_{name}'
    fullTitle = f'Run {run} {module} {gainName} gain: {title}'
    inputHistogram = inputs[0][1][0]
    sumHistogram = inputHistogram.Clone()
    sumHistogram.Reset()
    sumHistogram.SetTitle(fullTitle)
    sumHistogram.SetName(fullName)
 
    for input in inputs:
        inputHistogram = input[1][0]
        nEntries = inputHistogram.GetEntries()
        if nEntries > 0:
            sumHistogram.Add(inputHistogram)
 
    return sumHistogram
 
 

◆ getTileModuleTime()

TilePostProcessing.getTileModuleTime ( inputs )

This function produces 1D summary histogram per Tile module with time of all channels in the module

Definition at line 638 of file TilePostProcessing.py.

def getTileModuleTime(inputs):
    """ This function produces 1D summary histogram per Tile module with time of all channels in the module """
 
    timeHistogram = getTileModuleHistogram(inputs, 'time', 'Average Time and RMS')
    fillTileModuleMeanAndRMS(timeHistogram, inputs)
    setTileModuleHistogramStyle(timeHistogram, markerStyle=21, markerSize=0.75, ymin=-25.0, ymax=25.0, labelSize=0.08)
 
    return [timeHistogram]
 
 

◆ getTileModuleTimeCorrected()

TilePostProcessing.getTileModuleTimeCorrected ( inputs )

This function produces 1D summary histogram per Tile module with time corrected of all channels in the module

Definition at line 648 of file TilePostProcessing.py.

def getTileModuleTimeCorrected(inputs):
    """ This function produces 1D summary histogram per Tile module with time corrected of all channels in the module """
 
    timeHistogram = getTileModuleHistogram(inputs, 'time_corr', 'Average Time corrected and RMS')
    fillTileModuleMeanAndRMS(timeHistogram, inputs)
    setTileModuleHistogramStyle(timeHistogram, markerStyle=21, markerSize=0.75, ymin=-25.0, ymax=25.0, labelSize=0.08)
 
    return [timeHistogram]
 
 

◆ getTileModuleTimeDiffBetweenOfflineAndDSP()

TilePostProcessing.getTileModuleTimeDiffBetweenOfflineAndDSP ( inputs )

This function produces 1D summary histogram per Tile module with time difference between offline and DSP of all channels in the module

Definition at line 679 of file TilePostProcessing.py.

def getTileModuleTimeDiffBetweenOfflineAndDSP(inputs):
    """ This function produces 1D summary histogram per Tile module with time difference between offline and DSP of all channels in the module """
 
    timeDiffHistogram = getTileModuleHistogram(inputs, 'dspfit_timediff', 'DSP-OFFLINE Time and RMS')
    fillTileModuleMeanAndRMS(timeDiffHistogram, inputs)
    setTileModuleHistogramStyle(timeDiffHistogram, markerStyle=21, markerSize=0.75, labelSize=0.08, ymin=-0.5, ymax=0.5)
 
    sumTimeDiffHistogram = getTileModuleSumHistogram(inputs, 'dspfit_amphbar', 'DSP-OFFLINE Time for all channels')
 
    return [timeDiffHistogram, sumTimeDiffHistogram]

◆ getTileModuleTimeSlopeAndOffset()

TilePostProcessing.getTileModuleTimeSlopeAndOffset ( inputs )

This function produces 1D summary histogram per Tile module with amplitude over charge ratio of all channels in the module

Definition at line 886 of file TilePostProcessing.py.

def getTileModuleTimeSlopeAndOffset(inputs):
    """ This function produces 1D summary histogram per Tile module with amplitude over charge ratio of all channels in the module """
 
    import ROOT
    # Force batch mode
    ROOT.gROOT.SetBatch(True)
 
    capactior = str(inputs[0][1][0].GetName()).split('_').pop()
    timeSlopeHistogram = getTileModuleHistogram(inputs, f'tslope_{capactior}', f'Time slope for {capactior} pF')
    timeOffsetHistogram = getTileModuleHistogram(inputs, f'toffset_{capactior}', f'Time offset for {capactior} pF')
 
    fitFunction = ROOT.TF1("polfun", "pol1", 0., 25.)
 
    for input in inputs:
 
        inputHistogram = input[1][0]
 
        nEntries = inputHistogram.GetEntries()
        if nEntries > 0:
            profile = inputHistogram.ProfileX()
            nBins = profile.GetNbinsX()
            histogram = ROOT.TH1S("histogram", "TMP Histogram", nBins, profile.GetBinLowEdge(1), profile.GetBinLowEdge(nBins + 1))
 
            timeShift = 0
            lastBin = 0
            lastBinContent = -99.0
            for xBin in range(1, nBins + 1):
                if profile.GetBinError(xBin) > 1e-7:
                    binContent = profile.GetBinContent(xBin)
                    # Allow only 1 shift and only of negative sign
                    if (timeShift < 1) and (binContent - (lastBinContent + (xBin - lastBin))) < -10.0:
                        timeShift = 25.
                    lastBin = xBin
                    lastBinContent = binContent
                    histogram.SetBinContent(xBin, binContent + timeShift)
                    histogram.SetBinError(xBin, profile.GetBinError(xBin))
 
            if histogram.GetEntries() > 1:
                histogram.Fit(fitFunction, "NQ")
 
                channel = int(input[0]['channel'])
                bin = int(channel) + 1
 
                # Shift by -25 ns to be consistent with previous definition
                timeOffset = fitFunction.GetParameter(0) - 25.0
                timeOffsetError = min(5.0, fitFunction.GetParError(0))
                timeOffsetHistogram.SetBinContent(bin, timeOffset)
                timeOffsetHistogram.SetBinError(bin, timeOffsetError)
 
                timeSlope = fitFunction.GetParameter(1)
                timeSlopeError = min(5.0, fitFunction.GetParError(1))
                timeSlopeHistogram.SetBinContent(bin, timeSlope)
                timeSlopeHistogram.SetBinError(bin, timeSlopeError)
 
    setTileModuleHistogramStyle(timeSlopeHistogram, markerStyle=21, markerSize=0.75, ymin=-0.1, ymax=1.4, labelSize=0.1)
    setTileModuleHistogramStyle(timeOffsetHistogram, markerStyle=21, markerSize=0.75, ymin=-15, ymax=15, labelSize=0.1)
 
    return [timeSlopeHistogram, timeOffsetHistogram]
 
 

◆ getTilePartitionRawChannelNoise()

TilePostProcessing.getTilePartitionRawChannelNoise ( inputs )

This function produces 2D histograms with Tile raw channel noise per partition

Definition at line 87 of file TilePostProcessing.py.

def getTilePartitionRawChannelNoise(inputs):
    """ This function produces 2D histograms with Tile raw channel noise per partition """
 
    import ROOT
    # Force batch mode
    ROOT.gROOT.SetBatch(True)
 
    from TileMonitoring.TileMonitoringCfgHelper import getLabels
    from TileCalibBlobObjs.Classes import TileCalibUtils as Tile
 
    def _getTilePartitionHistogram2D(name, title, partition, run):
        fullName = 'TileRawChannelNoise_{}_{}'.format(name, partition)
        fullTitle = 'Run {} Partition {}: {}'.format(run, partition, title)
        histogram = ROOT.TH2F(fullName, fullTitle,
                              Tile.MAX_DRAWER, 0.5, Tile.MAX_DRAWER + 0.5,
                              Tile.MAX_CHAN, -0.5, Tile.MAX_CHAN - 0.5)
        moduleLables = getLabels(('modules'), partition)
        channelLables = getLabels(('channels'), partition)
        for axis,labels in ((histogram.GetXaxis(), moduleLables), (histogram.GetYaxis(), channelLables)):
            for bin in range(0, len(labels)):
                axis.SetBinLabel(bin + 1, labels[bin])
        return histogram
 
 
    partition = inputs[0][0]['module'][:3]
    run = str(inputs[0][1][0].GetTitle()).split(' ')[1]
 
    rmsHistogram = _getTilePartitionHistogram2D('RMS', 'RMS of gaussians', partition, run)
    sigmaHistogram = _getTilePartitionHistogram2D('Sigma', 'Sigma of gaussians', partition, run)
    chi2Histogram = _getTilePartitionHistogram2D('Chi2', 'Chi2 of gaussians', partition, run)
    probabilityHistogram = _getTilePartitionHistogram2D('Prob', 'Probability of gaussians', partition, run)
    rmsOverSigmaHistogram = _getTilePartitionHistogram2D('RmsOverSigma', 'RMS/Sigma of gaussians', partition, run)
 
    fitfunction = ROOT.TF1("total", "gaus(0)")
    fitfunction.SetLineColor(2)
 
    for input in inputs:
 
        module = int(input[0]['module'][3:])
        channel = int(input[0]['channel'])
 
        plot = input[1][0]
 
        nEntries = plot.GetEntries()
 
        if nEntries > 100:
 
            rms = plot.GetRMS()
            rmsHistogram.Fill(module, channel, rms)
 
            fitfunction.SetParameters(0.1 * nEntries, 0., 0.7 * rms)
 
            binWidth = plot.GetBinWidth(0)
            lowLimit = binWidth * 0.5
            highLimit = max(rms * 1.05, binWidth * 2.0)
 
            fitfunction.SetParLimits(0, 0., nEntries)
            fitfunction.FixParameter(1, 0.)
            fitfunction.SetParLimits(2, lowLimit, highLimit)
 
            plot.Fit(fitfunction, "BQ")
 
            sigma = fitfunction.GetParameter(2)
            chi2 = fitfunction.GetChisquare()
            prob = fitfunction.GetProb()
 
            sigmaHistogram.Fill(module, channel, sigma)
            chi2Histogram.Fill(module, channel, chi2)
            probabilityHistogram.Fill(module, channel, prob)
            rmsOverSigmaHistogram.Fill(module, channel, rms/sigma)
 
    return [rmsHistogram, sigmaHistogram, chi2Histogram, probabilityHistogram, rmsOverSigmaHistogram]
 
 

◆ getTileStuckBitsNumber()

TilePostProcessing.getTileStuckBitsNumber ( inputHistogram )

This function analyzes a histogram with samples from Tile channel and returns number of stuck bits

Definition at line 365 of file TilePostProcessing.py.

def getTileStuckBitsNumber(inputHistogram):
    """ This function analyzes a histogram with samples from Tile channel and returns number of stuck bits """
 
    import math
    nStuckBits = 0
 
    # If all bins at given hypothetical stuck value (0,1) and stuck bit (0,...,9,...)
    # are empty then this bin is stuck in this value. Do this procedure only for
    # bins between the first and the last non-zeroth one.
 
    # Find first/last non-zero bin in the histogram
    firstBin = inputHistogram.FindFirstBinAbove(0)
    if firstBin < 0:  # empty histogram, nothing to do
        return 0
 
    lastBin = inputHistogram.FindLastBinAbove(0)
 
    # bins in histogram are counted from 1 to max(ADC) + 1, but actual X value for those bins are 0 ... max(ADC)
 
    # if there is nothing in first half of histogram
    # or there is nothing in second half and there is a sharp edge at mid
    # it can be that upper most bit is stuck in 0 or 1
 
    nBins = inputHistogram.GetNbinsX() # max(ADC) + 1
 
    if (firstBin == nBins / 2 + 1) or (lastBin == nBins / 2 and inputHistogram.GetBinContent(lastBin) > 3):
        nStuckBits += 1 # "The last Bit is stuck"
 
    firstBin -= 1 # shift to zero bin
    lastBin += 1 # shift to zero bin
 
    nBits = round(math.log2(nBins))
    for stuckValue in (0, 1): # bit stuck at value 0 or 1
        for stuckBit in range(0, nBits): # which bit is stuck
            sumInBinsChecked = 0
            nBinsChecked = 0
 
            windowLength = (1 << stuckBit) # length of one interval with all zeros if bit is stuck
            beginBin = (1 - stuckValue) * windowLength # beginning of first interval to check
 
            while beginBin + 1 < lastBin:
                endBin = beginBin + windowLength # end of interval to check
 
                if endBin > firstBin:
                    for bin in range(beginBin, endBin):
                        # bin is from 0 to max(ADC) here - must be changed in GetBinConent to (bin+1)
                        if (firstBin < bin + 1) and (bin + 1 < lastBin):
                            sumInBinsChecked += inputHistogram.GetBinContent(bin + 1)
                            nBinsChecked += 1
 
                beginBin = endBin + windowLength # beginning of next interval
 
    if sumInBinsChecked == 0 and nBinsChecked > 0:
        nStuckBits += 1
 
    if (nStuckBits == 0):
        nStuckBits = getTileStuckBitsNumber2(inputHistogram)
 
    return nStuckBits
 
 

◆ getTileStuckBitsNumber2()

TilePostProcessing.getTileStuckBitsNumber2 ( inputHistogram )

This function analyzes a histogram with samples from Tile channel and returns number of stuck bits

New function implemented by Tibor Zenis, which checks how many bit flips happen compared to the expected ones
It works for CIS and Laser because the adc range is not sufficiently excersized in the other run types.

Definition at line 300 of file TilePostProcessing.py.

def getTileStuckBitsNumber2(inputHistogram):
    """
    This function analyzes a histogram with samples from Tile channel and returns number of stuck bits
 
    New function implemented by Tibor Zenis, which checks how many bit flips happen compared to the expected ones
    It works for CIS and Laser because the adc range is not sufficiently excersized in the other run types.
    """
 
    import math
    nBins = inputHistogram.GetNbinsX()
    nBits = round(math.log2(nBins))
 
    bitValue = [1 << bit for bit in range(0, nBits)]
    nBitFlipsAtSignalRegion = [0 for bit in range(0, nBits)]
    nBitFlipsAtSignalEdges = [0 for bit in range(0, nBits)]
 
    nextBinContent = inputHistogram.GetBinContent(1)
    previousBinIsNotEmpty = nextBinContent > 0 # flip-flop of non-zero contents of previous bin
 
    currentBinContent = 2
    for currentBin in range(1, nBins):
 
        previousBinContent = currentBinContent
        currentBinContent = nextBinContent
        binIsNotEmpty = currentBinContent > 0
        nextBinContent = inputHistogram.GetBinContent(currentBin + 2) if currentBin < nBins - 1 else  0
 
        probability = 1.
        expectedContent = 0.125 * (nextBinContent + previousBinContent - math.sqrt(nextBinContent) - math.sqrt(previousBinContent))
        if binIsNotEmpty and currentBinContent < expectedContent:
            probability = 1. - currentBinContent / expectedContent
            binIsNotEmpty = False
 
        if binIsNotEmpty or previousBinIsNotEmpty: # count bit flips in bins with non-zero contents and adjacent bins
            for bit in range(0, nBits):
                if ((currentBin & bitValue[bit]) != ((currentBin - 1) & bitValue[bit])):
                    nBitFlipsAtSignalRegion[bit] += 1
                else:
                    break # higher bit can flip only if the previous one does
 
        if (binIsNotEmpty and previousBinIsNotEmpty) or not (binIsNotEmpty or previousBinIsNotEmpty):
            continue
 
        # bin content flips (zero - non-zero)
        for bit in range(0, nBits): # count bits flipped at this position
            if ((currentBin & bitValue[bit]) != ((currentBin - 1) & bitValue[bit])):
                if (currentBin & bitValue[bit]):
                    nBitFlipsAtSignalEdges[bit] += probability if binIsNotEmpty else -probability
                else:
                    nBitFlipsAtSignalEdges[bit] += -probability if binIsNotEmpty else probability
            else:
                break
 
        previousBinIsNotEmpty = not previousBinIsNotEmpty
 
    nStuckBits = 0
    for bit in range(0, nBits):
        if (((nBitFlipsAtSignalRegion[bit] > 2) and abs(nBitFlipsAtSignalEdges[bit]) == nBitFlipsAtSignalRegion[bit])
            or (abs(nBitFlipsAtSignalEdges[bit]) > 7 and abs(nBitFlipsAtSignalEdges[bit]) * 3 > nBitFlipsAtSignalRegion[bit])):
            nStuckBits += 1
 
    return nStuckBits
 
 
 

◆ setTileModuleHistogramStyle()

TilePostProcessing.setTileModuleHistogramStyle	(	histogram,
		markerStyle = None,
		markerSize = None,
		markerColor = None,
		labelSize = None,
		ymin = None,
		ymax = None,
		delta = 0.1 )

This function set up stype of Tile module monitoring histogram

Definition at line 36 of file TilePostProcessing.py.

                                labelSize=None, ymin=None, ymax=None, delta=0.1):
    """ This function set up stype of Tile module monitoring histogram """
 
    if ymin and (histogram.GetMinimum() > ymin + delta * abs(ymin)):
        histogram.SetMinimum(ymin)
    if ymax and (histogram.GetMaximum() < (1.0 - delta) * ymax):
        histogram.SetMaximum(ymax)
    if markerStyle:
        histogram.SetMarkerStyle(markerStyle)
    if markerColor:
        histogram.SetMarkerColor(markerColor)
    if markerSize:
        histogram.SetMarkerSize(markerSize)
    if labelSize:
        histogram.SetLabelSize(labelSize, "X")
        histogram.SetLabelSize(labelSize, "Y")
 
 

◆ sigtermHandler()

TilePostProcessing.sigtermHandler	(		signal,
			frame )

Definition at line 968 of file TilePostProcessing.py.

        def sigtermHandler(signal, frame):
            print('Terminating postporcessing ...')
            sys.exit(0)
 

Variable Documentation

◆ action

TilePostProcessing.action

Definition at line 951 of file TilePostProcessing.py.

◆ args

TilePostProcessing.args = parser.parse_args()

Definition at line 959 of file TilePostProcessing.py.

◆ dataPath

TilePostProcessing.dataPath = find_datafile('TileMonitoring')

Definition at line 966 of file TilePostProcessing.py.

◆ default

TilePostProcessing.default

Definition at line 955 of file TilePostProcessing.py.

◆ dest

TilePostProcessing.dest

Definition at line 953 of file TilePostProcessing.py.

◆ help

TilePostProcessing.help

Definition at line 951 of file TilePostProcessing.py.

◆ inputPath

str TilePostProcessing.inputPath = f'{partition};{server};TileMIG:TileGatherer'

Definition at line 976 of file TilePostProcessing.py.

◆ int

TilePostProcessing.int

Definition at line 955 of file TilePostProcessing.py.

◆ noiseConfigurations

list TilePostProcessing.noiseConfigurations = []

Definition at line 995 of file TilePostProcessing.py.

◆ noisePostProcess

tuple TilePostProcessing.noisePostProcess

Initial value:

=  (['histgrinder', inputPath, outputPath,
                                 '--inmodule', 'DQOnlinePostprocessing.atlas_oh.OHInputModule',
                                 '--outmodule', 'DQOnlinePostprocessing.atlas_oh.OHOutputModule',
                                 '--prefix', '/', '-c'] + noiseConfigurations)

Definition at line 1001 of file TilePostProcessing.py.

◆ outputPath

str TilePostProcessing.outputPath = f'{partition};{server};TilePT-stateless-PP'

Definition at line 977 of file TilePostProcessing.py.

◆ parser

TilePostProcessing.parser = argparse.ArgumentParser()

Definition at line 949 of file TilePostProcessing.py.

◆ partition

TilePostProcessing.partition = os.getenv("TDAQ_PARTITION", "ATLAS")

Definition at line 964 of file TilePostProcessing.py.

◆ physConfigurations

list TilePostProcessing.physConfigurations = []

Definition at line 979 of file TilePostProcessing.py.

◆ physPostProcess

tuple TilePostProcessing.physPostProcess

Initial value:

=  (['histgrinder', inputPath, outputPath,
                                 '--inmodule', 'DQOnlinePostprocessing.atlas_oh.OHInputModule',
                                 '--outmodule', 'DQOnlinePostprocessing.atlas_oh.OHOutputModule',
                                 '--prefix', '/', '-c'] + physConfigurations)

Definition at line 983 of file TilePostProcessing.py.

◆ server

str TilePostProcessing.server = 'Histogramming'

Definition at line 963 of file TilePostProcessing.py.

◆ type

TilePostProcessing.type

Definition at line 955 of file TilePostProcessing.py.

Functions

Variables

Detailed Description

Function Documentation

◆ channelToPMT()

◆ fillTileModuleMeanAndRMS()

◆ getProfile2D_RMS()

◆ getTileModuleAmplitudeAndSigmaWithRMS()

◆ getTileModuleAmplitudeDiffBetweenOfflineAndDSP()

◆ getTileModuleAmplitudeDSP()

◆ getTileModuleAmplitudeOverChargeRatio()

◆ getTileModuleAmplitudeVarianceOverMean()

◆ getTileModuleBCID()

◆ getTileModuleChi2VsAmplitude()

◆ getTileModuleCovariance()

◆ getTileModuleCRC()

◆ getTileModuleHFN()

◆ getTileModuleHistogram()

◆ getTileModulePedestalsAndLFN()

◆ getTileModuleStuckBits()

◆ getTileModuleSumHistogram()

◆ getTileModuleTime()

◆ getTileModuleTimeCorrected()

◆ getTileModuleTimeDiffBetweenOfflineAndDSP()

◆ getTileModuleTimeSlopeAndOffset()

◆ getTilePartitionRawChannelNoise()

◆ getTileStuckBitsNumber()

◆ getTileStuckBitsNumber2()

◆ setTileModuleHistogramStyle()

◆ sigtermHandler()

Variable Documentation

◆ action

◆ args

◆ dataPath

◆ default

◆ dest

◆ help

◆ inputPath

◆ int

◆ noiseConfigurations

◆ noisePostProcess

◆ outputPath

◆ parser

◆ partition

◆ physConfigurations

◆ physPostProcess

◆ server

◆ type