def getTrap():
ds, run, chan = 1, 11085, 580 # C1P1D3
# trigger eff vals from old study: mu = 1.448, sig = 0.305
# 2016-9-15-P3LQG_Run60001538 C2P1D3 P42748B
# ds, run, chan = 4, 60001538, 1110
from ROOT import GATDataSet
gds = GATDataSet(run)
tt = gds.GetGatifiedChain()
bt = gds.GetBuiltChain()
tt.AddFriend(bt)
tCut = "channel==%d" % chan
n = tt.Draw("Entry$:Iteration$", tCut, "goff")
evt, itr = tt.GetV1(), tt.GetV2()
evtList = [[int(evt[i]), int(itr[i])] for i in range(n)]
trapOutput = []
pEvt = -1
for i, (iE, iH) in enumerate(evtList):
if iE != pEvt:
tt.GetEntry(iE)
pEvt = iE
hitE = tt.trapENFCal.at(iH)
wf = bt.event.GetWaveform(iH)
sig = wl.processWaveform(wf)
waveRaw = sig.GetWaveBLSub()
waveTS = sig.GetTS()
# mimic onboard energy trapezoid
eTrap = wl.trapFilter(waveRaw, 400, 180, 0)
nPad = len(waveRaw) - len(eTrap)
eTrap = np.pad(eTrap, (nPad, 0), 'constant')
eTrapTS = np.arange(0, len(eTrap) * 10., 10)
# trap timestamps shouldn't change, don't recalculate them
if i == 0:
pTS = eTrapTS
if not np.array_equal(eTrapTS, pTS):
print("Warning, the timestamps changed. Uggggg")
return
# print(i, iE, iH, hitE)
trapOutput.append(eTrap)
# np.savez("../data/trapOutput.npz",trapOutput,eTrapTS) # original ds4 run
np.savez("../data/trapOutput-2.npz", trapOutput, eTrapTS) # new ds1 run
def getOffset():
""" we're looking for the difference in the offsets between HG and LG waveforms. """
from ROOT import GATDataSet, TChain
ds, cIdx, run = 1, 41, 13387
det = dsi.DetInfo()
pMons = det.getPMon(ds)
# skim = TChain("skimTree")
# skim.Add("/global/homes/w/wisecg/project/cal/skim/skimDS1_run13387_low.root")
gds = GATDataSet(run)
gat = gds.GetGatifiedChain(False)
n = gat.Draw("Entry$:tOffset:channel", "trapENFCal < 250", "goff")
iEnt, tOff, chan = gat.GetV1(), gat.GetV2(), gat.GetV3()
iEnt = np.asarray([int(iEnt[i]) for i in range(n)])
tOff = np.asarray([tOff[i] for i in range(n)])
chan = np.asarray([chan[i] for i in range(n)])
chList = sorted(list(set(chan)))
chList = [ch for ch in chList if ch % 2 == 0]
chDiff = {ch: [] for ch in chList}
chNoPair = {ch: [] for ch in chList}
eList = sorted(list(
set(iEnt))) # we do this b/c the list isn't insanely huge
for iE in eList:
idx = np.where(iEnt == iE)
tOffTmp = tOff[idx]
chTmp = chan[idx]
for i, ch in enumerate(chTmp):
if ch % 2 == 1: continue
iM = np.where(chTmp == ch + 1)
if len(iM[0]) == 0:
chNoPair[ch].append(tOffTmp[i])
continue
diff = tOffTmp[i] - tOffTmp[iM] # HG - LG
chDiff[ch].append(tOffTmp[i] - tOffTmp[iM])
for ch in chList:
chDiff[ch] = np.asarray(chDiff[ch])
np.savez("../data/tOff-%d.npz" % run, chDiff, chNoPair)
def pulserBL():
""" For each bkgIdx, get the HG pulser events and all their baseline values.
Fill a dict of channels w/ the values, then make plots'n stuff.
"""
dsNum, modNum = 1, 1
goodList = ds.GetGoodChanList(dsNum)
# thing we want to make histos with
baseDict = {ch: [] for ch in goodList}
# for bkgIdx in range(ds.dsMap[dsNum]+1):
for bkgIdx in range(1):
print "DS-%d, bkgIdx %d" % (dsNum, bkgIdx)
runList = []
bkgList = ds.bkgRunsDS[dsNum][bkgIdx]
for idx in range(0, len(bkgList), 2):
[
runList.append(run)
for run in range(bkgList[idx], bkgList[idx + 1] + 1)
]
gds = GATDataSet()
[gds.AddRunNumber(run) for run in runList]
gatTree = gds.GetGatifiedChain()
bltTree = gds.GetBuiltChain()
gatTree.AddFriend(bltTree)
theCut = "EventDC1Bits && channel%2==0 && trapENFCal>50" # select pulser subset
gatTree.Draw(">>elist", theCut, "entrylist")
elist = gDirectory.Get("elist")
gatTree.SetEntryList(elist)
for iList in range(elist.GetN()):
entry = gatTree.GetEntryNumber(iList)
gatTree.LoadTree(entry)
gatTree.GetEntry(entry)
nChans = gatTree.channel.size()
numPass = gatTree.Draw("channel", theCut, "GOFF", 1, iList)
chans = gatTree.GetV1()
chanList = list(set(int(chans[n]) for n in xrange(numPass)))
hitList = (iH for iH in xrange(nChans)
if gatTree.channel.at(iH) in goodList)
for iH in hitList:
if dsNum == 2:
wf_downsampled = bltTree.event.GetWaveform(iH)
wf_regular = bltTree.event.GetAuxWaveform(iH)
wf = MJTMSWaveform(wf_downsampled, wf_regular)
else:
wf = bltTree.event.GetWaveform(iH)
chan = int(gatTree.channel.at(iH))
signal = wl.processWaveform(wf)
baseline, _ = signal.GetBaseNoise()
baseline = float("%.2f" %
baseline) # kill precision to save on memory
baseDict[chan].append(baseline)
# could pickle the baseDict here, but idk, let's move on
fig = plt.figure(figsize=(8, 7), facecolor='w')
p1 = plt.subplot(111)
# for ch in baseDict:
ch = 608
arr = np.asarray(baseDict[chan])
p1.hist(arr) #, bins='auto') # arguments are passed to np.histogram
p1.set_title("Channel 608")
plt.savefig("../plots/ch608-bl.pdf")
def main(argv):
"""
Matplotlib animation tutorial:
http://jakevdp.github.io/blog/2012/08/18/matplotlib-animation-tutorial/
Requires ffmpeg. (brew install ffmpeg)
"""
# Set input file and cuts
# gatFile = TFile("~/project/mjddatadir/gatified/mjd_run27012.root") # generate w/ process_mjd_data_p1
# bltFile = TFile("~/project/mjddatadir/built/OR_run27012.root")
# gatTree = gatFile.Get("mjdTree")
# bltTree = bltFile.Get("MGTree")
run = 23725
ds = GATDataSet(run)
gatTree = ds.GetGatifiedChain()
bltTree = ds.GetBuiltChain()
gatTree.AddFriend(bltTree)
print "Found",gatTree.GetEntries(),"input entries."
# Get first timestamp
gatTree.GetEntry(0)
# print type(gatTree.localTime.localTime)
theCut = "Entry$<50"
# theCut = "channel == 674" # C1P7D3
# theCut = "trapE < 6000 && channel==674 && timestamp/1e8 > 148359"
# theCut = "channel==632 && timestamp/1e8 > 148359"
outFile = "../plots/movie_run%d.mp4" % run
# Print cut and events passing cut
print "Using cut:\n",theCut,"\n"
gatTree.Draw(">>elist", theCut, "entrylist")
elist = gDirectory.Get("elist")
gatTree.SetEntryList(elist)
nList = elist.GetN()
print "Found",nList,"entries passing cuts."
# First set up the figure, the axis, and the plot element we want to animate
fig = plt.figure(figsize=(11,5), facecolor='w')
a1 = plt.subplot(111)
# a2 = plt.subplot(111)
# a1.set_xlim(0,50000)
# a1.set_ylim(0,1000)
a1.set_xlabel("time (ns)")
a1.set_ylabel("ADC")
p1, = a1.plot(np.ones(1), np.ones(1), color='blue')
p2, = a1.plot(np.ones(1), np.ones(1), color='red')
# initialization function: plot the background of each frame
def init():
p1.set_data([],[])
p2.set_data([],[])
return p1,p2,
# animation function. This is called sequentially (it's the loop over events.)
def animate(iList):
entry = gatTree.GetEntryNumber(iList);
gatTree.LoadTree(entry)
gatTree.GetEntry(entry)
nChans = gatTree.channel.size()
numPass = gatTree.Draw("channel",theCut,"GOFF",1,iList)
chans = gatTree.GetV1()
chanList = list(set(int(chans[n]) for n in xrange(numPass)))
event = bltTree.event
locTime = gatTree.localTime.localTime # wow, srsly?
# Loop over hits passing cuts
hitList = (iH for iH in xrange(nChans) if gatTree.channel.at(iH) in chanList) # a 'generator expression'
for iH in hitList:
# wf = MGTWaveform()
iEvent = 0
wf_downsampled = event.GetWaveform(iH)
wf_regular = event.GetAuxWaveform(iH)
wf = MJTMSWaveform(wf_downsampled,wf_regular)
iEvent = entry
run = gatTree.run
chan = gatTree.channel.at(iH)
energy = gatTree.trapE.at(iH)
# timestamp = gatTree.timestamp.at(iH) / 1e8
# locTime = timestamp - firstTime
signal = wl.processWaveform(wf)
waveRaw = signal.GetWaveRaw()
waveBLSub = signal.GetWaveBLSub()
waveTS = signal.GetTS()
baseline = np.sum(waveRaw[:50])/50
# B, A = butter(2,1e6/(1e8/2), btype='lowpass')
# data_lPass = lfilter(B, A, waveRaw)
# simple trap filter (broken)
trapTS = waveTS
ADCThresh = 1.
trap, trigger, triggerTS = trapFilt(waveBLSub,trapThresh=ADCThresh)
trap = trap + baseline
# fill the figure
p1.set_ydata(waveRaw)
p1.set_xdata(waveTS)
p2.set_ydata(trap)
p2.set_xdata(trapTS)
plt.title("Run %d Channel %d Entry %d trapE %.1f locTime %.1f s" % (run,chan,iList,energy,locTime))
# dynamically scale the axes
xmin, xmax = np.amin(waveTS), np.amax(waveTS)
a1.set_xlim([xmin,xmax])
if energy < 1000:
a1.set_ylim(0,1000)
else:
ymin, ymax = np.amin(waveRaw), np.amax(waveRaw)
a1.set_ylim([ymin-abs(0.1*ymin),ymax+abs(0.1*ymax)])
# print progress
# print "%d / %d Run %d nCh %d chan %d trapE %.1f samp %d" % (iList,nList,run,nChans,chan,energy,wf.GetLength())
if iList%500 == 0 and iList!=0:
print "%d / %d entries saved (%.2f %% done)." % (iList,nList,100*(float(iList)/nList))
return p1,p2,
# call the animator. blit=True means only re-draw the parts that have changed.
anim = animation.FuncAnimation(fig, animate, init_func=init, frames=elist.GetN(), interval=0, blit=True)
# save the animation as an mp4. This requires ffmpeg or mencoder to be
# installed. The extra_args ensure that the x264 codec is used, so that
# the video can be embedded in html5. You may need to adjust this for
# your system: for more information, see
# http://matplotlib.sourceforge.net/api/animation_api.html
anim.save(outFile, fps=20)#, extra_args=['-vcodec', 'libx264'])
def printOffsets():
from ROOT import GATDataSet, TChain
ds, cIdx, run = 1, 41, 13387
det = dsi.DetInfo()
# pMons = det.getPMon(ds) # this cal run isn't getting these
# print(pMons)
# return
cpdList = det.dets["M1"]
cpdPairs = {cpd: 0 for cpd in cpdList}
cpdOrphanHG = {cpd: 0 for cpd in cpdList}
cpdOrphanLG = {cpd: 0 for cpd in cpdList}
skim = TChain("skimTree")
skim.Add(
"/global/homes/w/wisecg/project/cal/skim/skimDS1_run13387_low.root")
# n = skim.Draw("iEvent:tOffset:channel","mH==1 && tOffset > 100","goff")
n = skim.Draw("iEvent:tOffset:channel", "mH==1", "goff")
iEnt, tOff, chan = skim.GetV1(), skim.GetV2(), skim.GetV3()
iEnt = [int(iEnt[i]) for i in range(n)]
tOff = [tOff[i] for i in range(n)]
chan = [chan[i] for i in range(n)]
gds = GATDataSet(run)
gat = gds.GetGatifiedChain(False)
iNWF, hitChans, tOffs, hitEs = [], [], [], []
for iE in iEnt:
gat.GetEntry(iE)
iN = gat.channel.size()
iNWF.append(iN)
hChs = [int(gat.channel.at(j)) for j in range(iN)]
hitChans.append(hChs)
tOffs.append([int(gat.tOffset.at(j)) for j in range(iN)])
hits = [gat.trapENFCal.at(j) for j in range(iN)]
hitEs.append(wl.niceList(hits))
pairs = []
for ch in hChs:
if ch + 1 in hChs: pairs.extend([ch, ch + 1])
hgOrphans = [
ch for ch in hChs
if ch + 1 not in hChs and ch not in pairs and ch % 2 == 0
]
lgOrphans = [
ch for ch in hChs
if ch - 1 not in hChs and ch not in pairs and ch % 2 == 1
]
# print(hChs, "pairs:", pairs, "hg orph", hgOrphans, "lg orph", lgOrphans)
for ch in pairs:
if ch % 2 == 1: continue
cpd = det.getChanCPD(ds, ch)
cpdPairs[cpd] += 1
for ch in hgOrphans:
cpd = det.getChanCPD(ds, ch)
cpdOrphanHG[cpd] += 1
for ch in lgOrphans:
cpd = det.getChanCPD(ds, ch - 1)
cpdOrphanLG[cpd] += 1
# nLim = 200 if n > 200 else n
# for i in range(nLim):
# print("%d %-5d %-4d gNWF %d" % (chan[i], iEnt[i], tOff[i], iNWF[i]), hitChans[i], tOffs[i], hitEs[i])
np.savez("../data/toffset-orphans.npz", cpdPairs, cpdOrphanHG, cpdOrphanLG)
